Effect of high dietary fiber intake on insulin resistance, body composition and weight, among overweight or obese middle-aged women: study protocol for a randomized controlled trail.

Suvarna Hebbar; Shashikiran Umakanth; Latha Thimmappa; Joniya Galbao

doi:10.12688/f1000research.147438.4

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Study Protocol

Revised

Effect of high dietary fiber intake on insulin resistance, body composition and weight, among overweight or obese middle-aged women: study protocol for a randomized controlled trail.

[version 4; peer review: 1 approved, 3 not approved]

Previously titled: "Effect of high dietary fiber intake on insulin resistance, body composition and weight, among overweight or obese middle-aged women: study protocol for a double-blinded randomized controlled trail."

Suvarna Hebbar ¹, Shashikiran Umakanth², Latha Thimmappa³, Joniya Galbao⁴

PUBLISHED 08 Apr 2026

Author details Author details

¹ Clinical Nutrition and Dietetics, Manipal College of Health Professions, Manipal., Karnataka, 576104, India
² Department of Medicine, Melaka Manipal Medical College, Manipal, Karnataka, 576104, India
³ College of Nursing, All India Institute of Medical Sciences, Bibinagar, Hyderabad, India
⁴ Clinical Nutrition and Dietetics, Manipal College of Health Professions, Manipal, Karnataka, 576104, India

Suvarna Hebbar
Roles: Conceptualization, Funding Acquisition, Investigation, Resources, Validation, Writing – Original Draft Preparation, Writing – Review & Editing

Shashikiran Umakanth
Roles: Conceptualization, Methodology, Supervision, Validation, Writing – Review & Editing

Latha Thimmappa
Roles: Conceptualization, Formal Analysis, Methodology, Supervision, Validation, Writing – Review & Editing

Joniya Galbao
Roles: Conceptualization, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

This article is included in the Manipal Academy of Higher Education gateway.

Abstract

Background

Obesity is a major consequence of malnutrition and significantly contributes to the global burden of chronic diseases. Currently, there are more overweight and obese individuals than underweight individuals. Increased fiber intake can increase insulin sensitivity and fat oxidation. According to research studies, the average dietary fiber consumption is below the recommended value, and the WHO anticipates that the worldwide obesity prevalence has increased in the past ten years.

Aim

To evaluate the effect of high dietary fiber intake on insulin resistance, body composition, and weight in overweight and obese middle-aged women.

Method

This hospital-based study evaluated 500 people during phase 1 to identify the prevalence of insulin resistance among overweight and obese middle-aged women. An RCT with intervention and control arms for 180 individuals is being conducted in Phase 2 to determine the effect of increased dietary fiber consumption on insulin resistance, body composition, and weight in overweight or obese middle-aged women. In the intervention group, women were counselled for 15 min and given a tailored food chart including 40 g of fiber. Women in the control arm will receive a typical food care plan with 25 g of fiber, based on their health status. Each engaged woman received fiber nutritional empowerment.

Discussion

Increasing dietary fiber consumption can improve insulin resistance, body composition, and weight in middle-aged overweight and obese women.

Trial registration

The Clinical Trials Registry of India (CTRI/2022/01/039074) has registered this study as a clinical trial on January 3, 2022 http://ctri.nic.in

Keywords

Middle Aged, Women, Insulin Resistance, Overweight, Obesity, Body Composition, Dietary Fiber, Health Status.

Corresponding author: Suvarna Hebbar

Competing interests: No competing interests were disclosed.

Grant information: This study is funded by IMCR-DHR (R.11014/12/2023-GIA/HR)
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2026 Hebbar S et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Hebbar S, Umakanth S, Thimmappa L and Galbao J. Effect of high dietary fiber intake on insulin resistance, body composition and weight, among overweight or obese middle-aged women: study protocol for a randomized controlled trail. [version 4; peer review: 1 approved, 3 not approved]. F1000Research 2026, 13:396 (https://doi.org/10.12688/f1000research.147438.4) First published: 26 Apr 2024, 13:396 (https://doi.org/10.12688/f1000research.147438.1) Latest published: 11 Jun 2026, 13:396 (https://doi.org/10.12688/f1000research.147438.5)

Revised Amendments from Version 3

In this revised version, several improvements have been made to enhance clarity and methodological transparency. The introduction has been streamlined to reduce redundancy and improve the logical flow of the study rationale. Additional details have been included in the Methods section, particularly regarding the sample size calculation, adherence monitoring strategies for dietary fiber intake, and assessment procedures. The Discussion section has been expanded to address the potential influence of dietary counseling on study outcomes and to acknowledge limitations such as the absence of gut microbiota assessment. These revisions strengthen the overall scientific clarity and address the comments raised during peer review.

See the authors' detailed response to the review by Hendriek C Boshuizen
See the authors' detailed response to the review by Debasrita Banerjee and Ravi Yadav
See the authors' detailed response to the review by Gary Frost
See the authors' detailed response to the review by Tatiana Palotta Minari

Background

Obesity is a major public health concern worldwide. Urbanization, economic growth, changing lifestyles, and dietary habits have contributed to a “double burden” of diseases in rapidly developing low- and middle-income countries such as India.¹ The average dietary fiber intake is below the recommended levels, and the World Health Organization estimates that the incidence of obesity has increased globally in the past decade. Many individuals do not consume adequate fiber to meet recommended intakes, and obese women often report lower dietary fiber consumption compared with normal-weight individuals.²

Dietary fiber plays an important role in appetite regulation and weight management. Fiber-rich foods promote satiety and reduce hunger by delaying gastric emptying and increasing stomach fullness.³ These effects are particularly evident among individuals with obesity.⁴ In addition, dietary fiber consumption promotes the growth of beneficial bacteria in the colon, which may help prevent obesity, metabolic syndrome, and adverse intestinal changes.⁵

High-fiber diets are associated with improved health outcomes and a reduced risk of several chronic diseases. Fiber-rich foods typically have lower energy density and can replace high-fat, energy-dense foods in the diet. Increased dietary fiber intake has been linked with improvements in serum lipoproteins, blood pressure, blood glucose control, and body weight. Individuals consuming adequate fiber are at lower risk of coronary artery disease, stroke, hypertension, diabetes, obesity, and gastrointestinal disorders. In addition, soluble fiber intake has been shown to enhance immune function.⁶

Dietary fiber obtained from fruits, vegetables, legumes, and whole grains provides several physiological benefits and is associated with a lower risk of chronic diseases such as cardiovascular disease, type 2 diabetes mellitus, obesity, and certain cancers. These foods also provide micronutrients and phytochemicals that contribute to overall health, highlighting the importance of promoting adequate dietary fiber intake in the population.⁷

However, limited research has examined the role of dietary fiber specifically in the treatment and management of obesity, and further studies are required to strengthen the evidence linking dietary fiber intake with obesity-related outcomes.⁸ Dietary fiber also promotes the growth of beneficial gut bacteria and supports microbial balance. Increased consumption of dietary fiber and whole grains enhances the growth of beneficial intestinal microbiota, which may be particularly relevant in individuals with obesity and other metabolic disorders. However, these effects may vary depending on the type, structure, and composition of the fiber and whole-grain sources.⁹

High-fiber foods are more satiating and contribute to appetite control by influencing gastric emptying, reducing food intake, and promoting a sense of fullness.¹⁰ Fermentation of dietary fiber in the colon produces short-chain fatty acids that regulate appetite through gut hormones such as cholecystokinin and glucagon-like peptides, which help reduce hunger and increase satiety.¹¹ Increased chewing and gastric distension associated with fiber-rich foods may further enhance satiety and regulate food intake.¹²

This study focuses on weight reduction through increased dietary fiber consumption. According to the Indian Council of Medical Research and National Institute of Nutrition guidelines, the recommended dietary fiber intake is 40 g per 2000 kcal of energy intake.¹³ Increasing dietary fiber consumption to recommended levels may support weight management and improve overall metabolic health.

Objectives

Primary objective

• To determine the effect of fiber intake on insulin resistance, body composition, and weight.

Secondary objective

• To determine the effect of fiber intake on biochemical parameters.
• To assess the opinions of women on modified fiber intake.

Methods

The present study will be conducted in the OPDs of the medicine, gynaecology, and endocrinology units of a tertiary care hospital in Karnataka, India. This study: 519/2021 was approved by Kasturba Medical College and Kasturba Hospital Institutional Ethics Committee (IEC) on December 19, 2021. The data will be collected on the consent of the patients and the confidentiality will be strictly maintained. Women in the age group between 35-55 years will be screened for insulin resistance at Phase-1 and those women with no contraindication for high fiber consumption and abnormal HOMA-IR will be included in Phase-2.

Phase 1

Objective

The primary aim of Phase 1 is to screen middle-aged overweight and obese women to determine the prevalence of insulin resistance.

Study setting

This phase will be conducted in the Outpatient Departments (OPDs) of Medicine, Gynaecology, and Endocrinology at Kasturba Hospital, Manipal.

Sample size & Selection

• A total of 500 women will be screened to assess insulin resistance.
• Participants will be categorized into two groups: overweight (BMI 23–24.9 kg/m²) and obese (BMI ≥ 25 kg/m²).
• Each group will have at least 166 participants. The sample size was calculated in accordance with insulin resistance and BMI.

Inclusion criteria

• Women aged 35–55 years.
• Willing to provide informed consent.
• BMI ≥ 23 kg/m².

Exclusion criteria

• Women with conditions affecting nutritional status (e.g., tuberculosis, HIV, cancer, organ failure).
• Women diagnosed with type 2 diabetes mellitus.
• Individuals with hypertension, thyroid disorders, or any medical condition requiring medications affecting body weight (e.g., thyroxine, diuretics).
• Pregnant or lactating women.
• Women already on a weight-loss regime or consuming fiber above the recommended dietary allowance.
• Women with contraindications for high fiber consumption (e.g., inflammatory bowel disease).

Data collection methods

A cross-sectional screening will be undertaken. Women aged 35–55 years will be recruited for Phase I of the study.

Screening and measurements

• Anthropometry: Height and weight will be measured using standardized procedures, and Body Mass Index (BMI) will be calculated (kg/m²).
• Biochemical Parameters: Insulin resistance will be determined using the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR).
• Dietary Assessment: Usual dietary fiber intake will be assessed through a 24-hour dietary recall method (one-day recall). Total dietary fiber, as well as soluble and insoluble fiber intake, will be calculated using standard Indian food composition tables and nutrient analysis software.

In-depth interviews

Simultaneously, an in-depth interview will be conducted telephonically for 45 min to understand the barriers of fiber intake among two equal groups of 20 each, consuming low fiber (<20 g) and good fiber (=20 g to 25 g) in phase 1.

Phase 2: Randomized Controlled Trial (RCT)

Objective

To assess the impact of high dietary fiber intake (40 g/day) on insulin resistance, body composition, and weight among overweight and obese women.

Study design

Phase 2, the sample size was 180 participants,¹² who will be randomized into the study and control groups. Stratified Block Randomization, 9 block with 20 in each (stratified based on overweight and obese with at least 60 participants in overweight and obese strata). Sequence generation of samples using online software and the Concealment-Opaque Envelope Method will be applied to identify the effect of high dietary fiber intake on insulin resistance, body composition, and weight among overweight or obese middle-aged women.

180 women will be randomized into:

• Intervention Group (n = 90): Receives 40 g/day of fiber with dietary counselling.
• Control Group (n = 90): Receives 25 g/day of fiber as part of a standard diet care plan.

Sample size calculation

The sample size was calculated using the following formula:

n = \frac{2 (Z_{1 - α / 2} + Z_{1 - β})^{2} σ^{2} [1 + (m - 1) ρ]}{m (d)^{2}}

Where:

• n = sample size per group
• Z₁–α/2 = 1.96 (for α = 0.05, two-tailed test)
• Z₁–β = 0.84 (for 80% statistical power)
• σ = anticipated population standard deviation of the outcome variable
• d = clinically significant difference (effect size)
• m = number of time points/follow-ups (m = 2)
• ρ = intraclass correlation coefficient (ρ = 0.4)

Computation for BMI

Parameters used:

• σ = 3.96
• d = 1.5
• m = 2
• ρ = 0.4

Step 1: Substitute values into the formula

n = \frac{2 (1.96 + 0.84)^{2} (3.96)^{2} [1 + (2 - 1) 0.4]}{2 (1.5)^{2}}

Step 2: Simplify

n = \frac{2 (2.8)^{2} (15.68) (1.4)}{2 (2.25)}

Step 3: Final estimate

n \approx 77 participants per group

Adjustment for 15% dropout rate:

n = \frac{77}{1 - 0.15} = 90

Therefore, 90 participants per group were required.

Computation for Insulin Resistance

Parameters used:

• σ = 5.06
• d = 2
• m = 2
• ρ = 0.4

Step 1: Substitute values

n = \frac{2 {(1.96 + 0.84)}^{2} {(5.06)}^{2} [1 + (2 - 1) \times 0.4]}{2 {(2)}^{2}}

Step 2: Simplify

n = \frac{2 {(2.8)}^{2} (25.60) (1.4)}{2 (4)}

Step 3: Final estimate

n \approx 71 participants per group

Adjustment for 15% dropout rate:

n = \frac{71}{1 - 0.15} = 83

Thus, 83 participants per group were required.

Inclusion criteria

• Women from Phase 1 with abnormal HOMA-IR (>2), indicating insulin resistance.
• Willing to adhere to a high-fiber diet if randomized to the intervention group.

Exclusion criteria

• Women unwilling to continue participation or adhere to the high-fiber diet.

Data collection methods

Women with no contraindications to high dietary fiber consumption and abnormal HOMA-IR will be included in Phase 2 of the study. Baseline assessments will be conducted for both intervention and control groups. Demographic information including age, religion, place of residence, type of family, number of family members, marital status, education, occupation, and income will be collected using a structured proforma. Anthropometric measurements such as height (stadiometer), body weight (weighing scale), and waist and hip circumference will be recorded in the outpatient department. Biochemical parameters including fasting blood glucose (hexokinase method), HbA1c (TINA method), serum insulin (ECLIA), and lipid profile (triglycerides GPO Trinder method, HDL direct homogeneous method, LDL enzymatic method, and total cholesterol CE-CHOD-POD method) will be assessed. Dietary intake will be assessed using a 24-hour dietary recall and a Food Frequency Questionnaire (FFQ), and nutrient intake will be analyzed using DietCal software version 6.3. Adherence to dietary fiber intervention will be monitored using multiple strategies, including a tracking sheet to record daily intake of fiber-rich foods and a fiber intake compliance checklist during follow-up visits. Monthly telephonic follow-ups will be conducted to reinforce dietary counseling, evaluate adherence to the recommended dietary practices, and address any challenges faced by participants. Participants’ feedback on high-fiber food consumption will also be documented to identify adherence patterns and potential barriers, ensuring systematic monitoring of dietary fiber intake and compliance with the intervention throughout the study period. Physical activity levels will be assessed using the Global Physical Activity Questionnaire (GPAQ), and body composition parameters including visceral fat, subcutaneous fat, and muscle mass will be measured using a body fat analyzer. Clinical assessment will also be performed to document physical complaints reported by participants.

Intervention & Control groups

Intervention group

All women in the intervention arm will be counseled for about 15 minutes, and a customized diet chart consisting of high fiber of 40 grams will be provided. Nutritional empowerment on fiber shall be delivered to each woman enrolled. Necessary dietary advice on the modified diet plan and with a motivation to adhere to the diet plan will be communicated only to the intervention group. After the first counselling, on the 15th day, women will be telephonically assessed on their 24-hour recall dietary intake. On the 30th day, the women will be contacted telephonically again to record their 24-hour recall of their dietary intake. Necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 60th day, the women will be again telephonically contacted to record their 24-hour recall on their dietary intake, and necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, body fat is analyzed using body fat analyzer and a questionnaire on patient opinion regarding modified diet plan shall be assessed as motivation and adherence towards fiber consumption subjects will be communicated telephonically on the 135th day. From the 136th to the 180th day, there shall not be any conversation regarding dietary modifications. On the 180th day, as a compliance-checking, the women will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data. 24 hr dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, body fat analyzed using body fat analyzer and diet compliance on the modified diet plan shall be assessed ( Table 1).

Table 1.

Schematic representation for randomized control trial.

Control Arm
Day 1	Traditional/standard care (patient will be called to OPD)
Day 15	Nil
Day 30	Nil
Day 60	Nil
Day 90 (patient will be called to OPD)	Basic data: Tool 2: 24hr recall and food frequency Tool 3: GPAQ Biochemical parameters: FBS, HbA1c, Sr. Insulin and lipid profile Body fat analyzer: Visceral fat, S/C fat, muscle mass
Intervention Arm
Day 1	Intervention (patient will be called to OPD)	Customize the individual-specific diet plan Nutritional counseling Impart nutritional empowerment on fiber consumption Handover of diet plan
Day 15, Day 30, Day 60	Reinforcement (through telephone)	Tool 2: 24 hr recall Tool 3: GPAQ Modification of diet plan (if required) Motivate to adhere to the intervention
Day 90	Outcome assessment (patient will be called to OPD)	Basic data: Tool 2: 24-hour recall and food frequency Tool 3: GPAQ Tool 4: Clinical assessment scale Tool 5: Patient opinion on a modified diet Biochemical parameters: FBS, HbA1c, Sr. Insulin and lipid profile Body fat analyzer: Visceral fat, S/C fat, muscle mass
Day 135	Reinforcement (through telephone)	Motivation to follow customised diet plan
Day 180	Checking compliance (patient will be called to OPD)	Basic data: Tool 2: 24 hr recall and food frequency Tool 3: GPAQ Tool 4: Clinical assessment scale Tool 5: Compliance checklist Biochemical parameters: FBS, HbA1c, Sr. Insulin and lipid profile Body fat analyser: Visceral fat, S/C fat, muscle mass

Control group

Women in the control arm will get a traditional diet care plan with 25 gm of fiber according to their health condition. Necessary dietary advice will be communicated to the control group on the first visit to the hospital. There shall be no telephonic communication with the control group till the 90th day. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hour dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer. On the 180th day, as a compliance-checking, the patient will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer ( Table 1).

Data analysis

• Repeated Measures ANOVA will be used to evaluate changes in insulin resistance, body composition, and weight over time.
• SPSS v16.0 will be used for statistical analysis.

Ethical considerations

• Approval obtained from the Institutional Research Committee and Institutional Ethics Committee (IEC).
• Trial registered with the Clinical Trials Registry of India (CTRI/2022/01/039074).
• Informed consent was obtained from all participants.

Study status

Currently, participants have been recruited for phase-1 and 2, and follow-up for phase-2 is ongoing.

Discussion

Evidence on the association between dietary fiber intake and metabolic outcomes among overweight and obese middle-aged women in India remains limited. This study aimed to examine whether increased dietary fiber intake can improve insulin resistance, body composition, and weight in this population. Dietary fiber provides several metabolic benefits, including enhanced satiety, improved glycemic control, reduced cholesterol levels, and increased fat oxidation. By lowering energy intake and supporting metabolic regulation, adequate fiber consumption may contribute to effective weight management. In addition to dietary intervention, participants in the intervention group received regular dietary counseling, which may have improved adherence to the recommended dietary practices and encouraged healthier lifestyle behaviors. Therefore, the observed improvements in metabolic indicators and body composition may reflect the combined influence of increased dietary fiber intake and the supportive role of counseling in promoting sustained dietary and behavioral changes.

Article summary

Strengths and limitations of this study

Although dietary fiber is known to influence metabolic health through modulation of gut microbiota, gut microbial composition was not assessed in this study, which primarily focused on clinical and metabolic outcomes such as insulin resistance, body composition, and weight. Future studies incorporating microbiome analysis may provide better insight into the mechanisms linking dietary fiber intake with metabolic health:

• An improvement in insulin resistance, body composition, and weight will be recorded in participants with high dietary fiber intake.
• Good knowledge and practice regarding modified diet plans with high dietary fiber will be addressed to participants.
• Knowledge regarding barriers/consequences/clinical hindrances in consuming a high-fiber diet will be addressed.
• Drop out due to non-compliance.
• Patients adhering to follow the diet plan for a longer period.
• Limited resources are available to address the importance of inclusion of recommended fiber in the general public since we are only screening patients visiting hospitals.

Ethics and dissemination

The study protocol was reviewed and approved by the Institutional Research Committee (IRC) and Institutional Ethics Committee (IEC): 519/2021 was approved by Kasturba Medical College and Kasturba Hospital Institutional Ethics Committee on December 19, 2021, registered under the Clinical Trials Registry- India (CTRI) (CRTI/2022/01/039074). The study will be carried out in compliance with Good Clinical Practice standards. These findings will be published in peer-reviewed journals and presented at international conferences.

Consent to participate

All the participants signed a written informed consent form. All methods will be carried out in accordance with the relevant guidelines and regulations.

Data availability

Underlying data

No data are associated with this article.

Extended data

Open Source Framework: Effect of high dietary fiber intake on insulin resistance, body composition, and weight among overweight or obese middle-aged women: Study protocol for a double-blind randomized controlled trial, DOI https://doi.org/10.17605/OSF.IO/HUW43.¹⁴

The supplementary materials available are:

‐ Questionnaire
‐ SPIRIT checklist
‐ Education Material

Data are available under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0).

Reporting guidelines

Open Source Framework: Checklist for Effect of high dietary fiber intake on insulin resistance, body composition, and weight among overweight or obese middle-aged women: Study protocol for a randomized controlled trial, DOI https://doi.org/10.17605/OSF.IO/HUW43.¹⁴

Acknowledgements

We are grateful to the funding agency IMCR-DHR, India.

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Version 5

VERSION 5 PUBLISHED 26 Apr 2024

Author details Author details

Suvarna Hebbar
Roles: Conceptualization, Funding Acquisition, Investigation, Resources, Validation, Writing – Original Draft Preparation, Writing – Review & Editing

Shashikiran Umakanth
Roles: Conceptualization, Methodology, Supervision, Validation, Writing – Review & Editing

Latha Thimmappa
Roles: Conceptualization, Formal Analysis, Methodology, Supervision, Validation, Writing – Review & Editing

Joniya Galbao
Roles: Conceptualization, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

This study is funded by IMCR-DHR (R.11014/12/2023-GIA/HR)
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Article Versions (5)

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© 2026 Hebbar S et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Hebbar S, Umakanth S, Thimmappa L and Galbao J. Effect of high dietary fiber intake on insulin resistance, body composition and weight, among overweight or obese middle-aged women: study protocol for a randomized controlled trail. [version 4; peer review: 1 approved, 3 not approved]. F1000Research 2026, 13:396 (https://doi.org/10.12688/f1000research.147438.4)

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Reviewer Report 10 Apr 2026

Tatiana Palotta Minari, Federal University of São Paulo (UNIFESP), Santos, Brazil

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https://doi.org/10.5256/f1000research.197951.r473967

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Reviewer Report 16 Apr 2026

Debasrita Banerjee, Medhavi Skills University (School of Health Sciences & Technology, Singtam, Sikkim, India

Ravi Yadav, Anesthesia Operation Theater Technology, Medhavi Skills University, Singtam, Sikkim, India

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https://doi.org/10.5256/f1000research.193737.r465128

Methodological Concerns
The reliance on a single 24-hour dietary recall in Phase 1 is insufficient to accurately capture participants' habitual fiber intake. A validated Food Frequency Questionnaire (FFQ) should be implemented during this initial screening phase to mitigate recall bias. Additionally, while the targeted difference in fiber intake between groups was reduced to 15g, the sample size calculation remains unadjusted for this potentially smaller effect size.

Intervention and Adherence
The active dietary counseling required to reach the 40g daily fiber target makes any claim of blinding impossible, rendering the study an open-label trial. Furthermore, expecting participants to maintain such a high fiber intake from whole foods over six months introduces a severe risk of non-compliance and dropout. The intervention also fails to control for the varying ratios of soluble to insoluble fiber inherent in whole foods, which risks confounding the metabolic outcomes.

Manuscript Formatting Issues
The manuscript title contains a prominent typographical error, referring to the study as a "randomized controlled trail" rather than a "trial". The introduction lacks logical flow, occasionally relies on outdated terminology, and inappropriately uses bullet points instead of cohesive academic paragraphs in key sections. A thorough structural revision and professional proofread are necessary to elevate the manuscript to scientific publication standards.

Lack of Justification for a Single-Sex Study:
The original protocol failed to adequately explain why the study is restricted exclusively to middle-aged women. While the authors later cited menopause and estrogen-related metabolic changes in their response, this fundamental rationale was missing from the protocol's background.

Missed Opportunity for a Crossover Design:
The authors did not consider a crossover design. In dietary studies where blinding is impossible and inter-individual variability is high, having participants act as their own controls (by switching between the 25g and 40g diets) could have significantly strengthened the evidence.

Vague Secondary Objectives: The secondary objective, stated simply as "To assess the opinions of women on modified fiber intake," was heavily criticized for being too vague and lacking specific, measurable parameters.

Incorrect Formula Formatting: The formula provided in the text for the sample size calculation contained blatant typographical errors (e.g., printing s2 instead of the correct mathematical notation s^2 for variance), indicating poor proofreading.

Missing Justification for Variables: The authors plugged specific numbers into their power calculation (like standard deviations of 3.96 for BMI and 5.06 for insulin resistance), but initially failed to justify where these specific estimates came from or why they represented a "clinically significant difference".

Unproven Feasibility of the Intervention: Increasing a patient's dietary fiber by an additional 15g to 20g per day exclusively through whole foods is notoriously difficult. Reviewers questioned whether the research team had any pilot data proving they could successfully achieve and sustain this massive leap in fiber intake over 6 months.

No Objective Compliance Biomarkers: Despite the known flaws of self-reported dietary recalls and food frequency questionnaires, the study lacks any objective physiological markers to prove participants actually ate the fiber (such as stool weight, transit time, or specific microbiome metabolite markers). Adding a "compliance checklist" does not solve the fundamental issue of subjective reporting.

Confusing Protocol Structure: Reviewers found the methodology highly confusing because Phase 1 (the screening phase) and Phase 2 (the randomized trial) were jumbled together without clear separation or a concise timeline.

Is the rationale for, and objectives of, the study clearly described?

Partly
Is the study design appropriate for the research question?

Partly
Are sufficient details of the methods provided to allow replication by others?

Partly
Are the datasets clearly presented in a useable and accessible format?

Not applicable

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Clinical Nutrition and Functional Foods

We confirm that we have read this submission and believe that we have an appropriate level of expertise to state that we do not consider it to be of an acceptable scientific standard, for reasons outlined above.

CITE

Report a concern

Author Response 24 Apr 2026

Suvarna Hebbar, Clinical Nutrition and Dietetics, Manipal College of Health Professions, Manipal., 576104, India

24 Apr 2026

Author Response

Response to Reviewer
Methodological Concerns

The reliance on a single 24-hour dietary recall in Phase 1 is insufficient to accurately capture participants' habitual fiber intake. A validated Food Frequency ... Continue reading Response to Reviewer
Methodological Concerns

The reliance on a single 24-hour dietary recall in Phase 1 is insufficient to accurately capture participants' habitual fiber intake. A validated Food Frequency Questionnaire (FFQ) should be implemented during this initial screening phase to mitigate recall bias. Additionally, while the targeted difference in fiber intake between groups was reduced to 15g, the sample size calculation remains unadjusted for this potentially smaller effect size.
Response:
We thank the reviewer for these valuable methodological suggestions. We acknowledge that a single 24-hour dietary recall may not fully capture habitual dietary intake at the individual level. However, in Phase 1 the primary objective is screening and estimating general dietary patterns among a large sample of participants rather than assessing precise long-term nutrient intake. A single 24-hour dietary recall is widely used in epidemiological screening studies to estimate mean group intake when collected from a sufficiently large and heterogeneous population; therefore, it was considered appropriate for the initial screening phase involving approximately 500 participants. To strengthen dietary assessment in the intervention phase, the protocol has been modified so that in Phase 2 dietary intake will be assessed using multiple 24-hour dietary recalls at follow-up time points along with a Food Frequency Questionnaire (FFQ) to better capture habitual intake patterns. Nutrient intake will be analyzed using DietCal software based on standardized Indian food composition tables, which will further improve the reliability of dietary assessment while maintaining feasibility during the large screening phase. In addition, we appreciate the reviewer’s observation regarding the targeted difference in dietary fiber intake between groups being reduced to 15 g/day. The sample size calculation for Phase 2 was not based on the absolute difference in fiber intake but on the expected effect on the primary clinical outcomes, specifically insulin resistance (HOMA-IR) and body mass index (BMI). The power calculation used anticipated standard deviation values derived from previously published intervention studies and the clinically meaningful difference expected for BMI and insulin resistance. Because the calculation was based on changes in these metabolic outcomes rather than fiber intake itself, the reduction in the planned fiber difference from 20 g/day to 15 g/day does not alter the expected clinically meaningful effect on the primary endpoints; therefore, the required sample size remains appropriate and unchanged.

Intervention and Adherence
The active dietary counseling required to reach the 40g daily fiber target makes any claim of blinding impossible, rendering the study an open-label trial. Furthermore, expecting participants to maintain such a high fiber intake from whole foods over six months introduces a severe risk of non-compliance and dropout. The intervention also fails to control for the varying ratios of soluble to insoluble fiber inherent in whole foods, which risks confounding the metabolic outcomes.
Response:
We thank the reviewer for these important observations. We agree that complete blinding is not feasible in dietary behavioral interventions that involve active counseling and individualized dietary guidance; therefore, the study should be considered an open-label randomized controlled trial. This approach is common in nutrition intervention research where participants are required to actively modify their dietary behavior. To minimize potential bias, randomization and allocation concealment will be implemented using stratified block randomization and opaque sealed envelopes. In addition, the primary outcomes are objective measures, including biochemical parameters such as fasting glucose, HbA1c, serum insulin, lipid profile, and body composition analysis, which helps reduce measurement bias despite the open-label design.

We also acknowledge that maintaining a dietary fiber intake of approximately 40 g/day over six months may pose adherence challenges and could potentially increase the risk of non-compliance or dropout. To enhance participant adherence and minimize attrition, several strategies have been incorporated into the protocol, including individualized dietary counseling, customized high-fiber diet charts based on locally available foods, regular telephonic follow-up, dietary tracking sheets, fiber intake compliance checklists, and continuous motivation and reinforcement during follow-up visits. These strategies are widely used in dietary intervention studies and are expected to support sustained compliance throughout the intervention period.

Regarding the concern about varying ratios of soluble and insoluble fiber in whole foods potentially confounding metabolic outcomes, we acknowledge that whole foods naturally contain different proportions of fiber types. However, the primary objective of the study is to evaluate the effect of increasing total dietary fiber intake from whole foods under real-world dietary conditions rather than isolating specific fiber fractions. This approach improves the ecological validity and practical applicability of the findings. Furthermore, dietary intake will be assessed using 24-hour dietary recalls and a Food Frequency Questionnaire (FFQ), which allows estimation of total dietary fiber intake and helps account for dietary variability. Collectively, this design enables the study to evaluate the metabolic effects of increasing total dietary fiber intake within a realistic dietary context.

Manuscript Formatting Issues
The manuscript title contains a prominent typographical error, referring to the study as a "randomized controlled trail" rather than a "trial". The introduction lacks logical flow, occasionally relies on outdated terminology, and inappropriately uses bullet points instead of cohesive academic paragraphs in key sections. A thorough structural revision and professional proofread are necessary to elevate the manuscript to scientific publication standards.
Response:
We thank the reviewer for carefully identifying these formatting and structural issues. The typographical error in the manuscript title has been corrected from “randomized controlled trail” to “randomized controlled trial.” In addition, the Introduction section has been thoroughly revised to improve the logical flow and coherence of the background information. Outdated terminology has been updated where appropriate, and bullet points previously used in narrative sections have been replaced with structured academic paragraphs to maintain consistency with scientific writing standards. Furthermore, the entire manuscript has undergone careful proofreading and structural revision to enhance clarity, readability, and overall presentation in accordance with journal publication standards.

Lack of Justification for a Single-Sex Study:
The original protocol failed to adequately explain why the study is restricted exclusively to middle-aged women. While the authors later cited menopause and estrogen-related metabolic changes in their response, this fundamental rationale was missing from the protocol's background.
Response:
We thank the reviewer for highlighting this important point. We acknowledge that the initial protocol did not sufficiently explain the rationale for restricting the study to middle-aged women, and this has now been clarified in the revised background section. Middle-aged women represent a population at increased risk of metabolic disorders due to hormonal changes associated with the menopausal transition. During this period, declining estrogen levels are associated with increased visceral adiposity, alterations in body composition, and reduced insulin sensitivity, all of which contribute to a higher risk of overweight, obesity, and metabolic disturbances. These physiological and metabolic changes make middle-aged women a particularly relevant population for examining the potential benefits of dietary interventions such as increased dietary fiber intake on insulin resistance and body composition. Accordingly, the revised manuscript now clearly states this sex-specific rationale in the background section to justify the focus on middle-aged women.

Missed Opportunity for a Crossover Design:
The authors did not consider a crossover design. In dietary studies where blinding is impossible and inter-individual variability is high, having participants act as their own controls (by switching between the 25g and 40g diets) could have significantly strengthened the evidence.
Response:
We acknowledge that crossover designs can reduce inter-individual variability in dietary studies by allowing participants to serve as their own controls. However, a crossover design was not considered appropriate for the present study due to several practical and methodological considerations. First, the intervention period in this study is relatively long (6 months), and implementing a crossover design would require an additional intervention phase along with an adequate washout period to minimize carryover effects, which would substantially extend the total study duration. Second, repeated switching between dietary patterns (from 25 g to 40 g fiber intake and vice versa) may be challenging for participants and could negatively influence adherence to the prescribed diet. Therefore, a parallel randomized controlled trial design was considered more feasible and appropriate for evaluating the long-term effects of increased dietary fiber intake in this population.

Vague Secondary Objectives:
The secondary objective, stated simply as "To assess the opinions of women on modified fiber intake," was heavily criticized for being too vague and lacking specific, measurable parameters.
Response:
Thank you for your valuable comment. It was operationalized using a structured, dichotomous (yes/no) questionnaire administered at predefined time points (30th, 90th, and 180th day). Each item captured specific, measurable aspects of participant opinion, including acceptance of modified fiber intake, perceived ease of implementation, and willingness to continue the dietary changes. The use of binary responses ensured quantifiability, while repeated assessments enabled longitudinal tracking of changes in opinion and compliance over time.

Missing Justification for Variables:
The authors plugged specific numbers into their power calculation (like standard deviations of 3.96 for BMI and 5.06 for insulin resistance) but initially failed to justify where these specific estimates came from or why they represented a "clinically significant difference".
Response:
We thank the reviewer for highlighting the need to justify the parameters used in the sample size calculation. In the revised manuscript, we have clarified the source and rationale for the values used in the power calculation. The estimates for the standard deviation (σ) of BMI (3.96) and insulin resistance (5.06) were derived from previously published intervention studies examining the effects of dietary or lifestyle interventions on metabolic outcomes in similar adult populations. These values were selected as they represent realistic variability observed in comparable studies. The minimum detectable difference (d) was chosen based on changes considered clinically meaningful in the context of improvements in BMI and insulin resistance following dietary interventions. Thus, the parameters used in the sample size calculation were selected to ensure adequate statistical power to detect clinically relevant changes in the primary outcomes. These details and supporting references have now been added to the Methods section to improve transparency and clarity of the sample size estimation.

Unproven Feasibility of the Intervention:
Increasing a patient's dietary fiber by an additional 15g to 20g per day exclusively through whole foods is notoriously difficult. Reviewers questioned whether the research team had any pilot data proving they could successfully achieve and sustain this massive leap in fiber intake over 6 months.
Response:
We thank the reviewer for raising this important concern regarding the feasibility of achieving and sustaining an increased dietary fiber intake through whole foods. Prior to initiating the intervention, preliminary observations from our earlier dietary assessment conducted among middle-aged women in the same clinical setting indicated that many participants were consuming substantially lower amounts of dietary fiber than recommended levels. Therefore, the intervention was designed to increase fiber intake gradually through locally available, culturally acceptable high fiber foods such as whole grains, legumes, fruits, and vegetables, rather than relying on fiber supplements. In addition, participants in the intervention group receive individualized dietary counseling, a customized high fiber diet plan, and regular follow-up reinforcement through telephonic monitoring, which are intended to facilitate adherence and support gradual dietary modification over time. These strategies were incorporated to improve the feasibility and sustainability of achieving the targeted fiber intake.

No Objective Compliance Biomarkers:
Despite the known flaws of self-reported dietary recalls and food frequency questionnaires, the study lacks any objective physiological markers to prove participants actually ate the fiber (such as stool weight, transit time, or specific microbiome metabolite markers). Adding a "compliance checklist" does not solve the fundamental issue of subjective reporting.
Response:
We thank the reviewer for this important observation. We agree that objective biomarkers can strengthen the assessment of dietary compliance in nutrition intervention studies. However, the inclusion of objective biomarkers such as stool analysis (e.g., stool weight, transit time, or microbial metabolites) or other microbiome-related markers was not feasible in the present study. During the planning phase, the possibility of incorporating stool analysis was considered; however, participants expressed reluctance and practical concerns regarding stool sample collection, which posed challenges for participant acceptance and compliance in a community-based dietary intervention study. Additionally, logistical and resource constraints limited the feasibility of conducting microbiome or metabolite analysis. Furthermore, the absence of objective biomarkers such as stool analysis has now been acknowledged as a limitation in the manuscript.

Confusing Protocol Structure:
Reviewers found the methodology highly confusing because Phase 1 (the screening phase) and Phase 2 (the randomized trial) were jumbled together without clear separation or a concise timeline.
Response:
Thank you for this observation. In response, Phase 1 (screening phase) and Phase 2 (randomized controlled trial) have now been clearly delineated and described as distinct components of the study. This separation was initially clarified in Version 1 of the revised manuscript, and the same structured presentation has been consistently maintained and further refined in subsequent versions. Additionally, the methodology section has been reorganized to improve clarity, with a more explicit description of the study flow and timeline for each phase to avoid any overlap or confusion.
Response to Reviewer
Methodological Concerns

The reliance on a single 24-hour dietary recall in Phase 1 is insufficient to accurately capture participants' habitual fiber intake. A validated Food Frequency Questionnaire (FFQ) should be implemented during this initial screening phase to mitigate recall bias. Additionally, while the targeted difference in fiber intake between groups was reduced to 15g, the sample size calculation remains unadjusted for this potentially smaller effect size.
Response:
We thank the reviewer for these valuable methodological suggestions. We acknowledge that a single 24-hour dietary recall may not fully capture habitual dietary intake at the individual level. However, in Phase 1 the primary objective is screening and estimating general dietary patterns among a large sample of participants rather than assessing precise long-term nutrient intake. A single 24-hour dietary recall is widely used in epidemiological screening studies to estimate mean group intake when collected from a sufficiently large and heterogeneous population; therefore, it was considered appropriate for the initial screening phase involving approximately 500 participants. To strengthen dietary assessment in the intervention phase, the protocol has been modified so that in Phase 2 dietary intake will be assessed using multiple 24-hour dietary recalls at follow-up time points along with a Food Frequency Questionnaire (FFQ) to better capture habitual intake patterns. Nutrient intake will be analyzed using DietCal software based on standardized Indian food composition tables, which will further improve the reliability of dietary assessment while maintaining feasibility during the large screening phase. In addition, we appreciate the reviewer’s observation regarding the targeted difference in dietary fiber intake between groups being reduced to 15 g/day. The sample size calculation for Phase 2 was not based on the absolute difference in fiber intake but on the expected effect on the primary clinical outcomes, specifically insulin resistance (HOMA-IR) and body mass index (BMI). The power calculation used anticipated standard deviation values derived from previously published intervention studies and the clinically meaningful difference expected for BMI and insulin resistance. Because the calculation was based on changes in these metabolic outcomes rather than fiber intake itself, the reduction in the planned fiber difference from 20 g/day to 15 g/day does not alter the expected clinically meaningful effect on the primary endpoints; therefore, the required sample size remains appropriate and unchanged.

Intervention and Adherence
The active dietary counseling required to reach the 40g daily fiber target makes any claim of blinding impossible, rendering the study an open-label trial. Furthermore, expecting participants to maintain such a high fiber intake from whole foods over six months introduces a severe risk of non-compliance and dropout. The intervention also fails to control for the varying ratios of soluble to insoluble fiber inherent in whole foods, which risks confounding the metabolic outcomes.
Response:
We thank the reviewer for these important observations. We agree that complete blinding is not feasible in dietary behavioral interventions that involve active counseling and individualized dietary guidance; therefore, the study should be considered an open-label randomized controlled trial. This approach is common in nutrition intervention research where participants are required to actively modify their dietary behavior. To minimize potential bias, randomization and allocation concealment will be implemented using stratified block randomization and opaque sealed envelopes. In addition, the primary outcomes are objective measures, including biochemical parameters such as fasting glucose, HbA1c, serum insulin, lipid profile, and body composition analysis, which helps reduce measurement bias despite the open-label design.

We also acknowledge that maintaining a dietary fiber intake of approximately 40 g/day over six months may pose adherence challenges and could potentially increase the risk of non-compliance or dropout. To enhance participant adherence and minimize attrition, several strategies have been incorporated into the protocol, including individualized dietary counseling, customized high-fiber diet charts based on locally available foods, regular telephonic follow-up, dietary tracking sheets, fiber intake compliance checklists, and continuous motivation and reinforcement during follow-up visits. These strategies are widely used in dietary intervention studies and are expected to support sustained compliance throughout the intervention period.

Regarding the concern about varying ratios of soluble and insoluble fiber in whole foods potentially confounding metabolic outcomes, we acknowledge that whole foods naturally contain different proportions of fiber types. However, the primary objective of the study is to evaluate the effect of increasing total dietary fiber intake from whole foods under real-world dietary conditions rather than isolating specific fiber fractions. This approach improves the ecological validity and practical applicability of the findings. Furthermore, dietary intake will be assessed using 24-hour dietary recalls and a Food Frequency Questionnaire (FFQ), which allows estimation of total dietary fiber intake and helps account for dietary variability. Collectively, this design enables the study to evaluate the metabolic effects of increasing total dietary fiber intake within a realistic dietary context.

Manuscript Formatting Issues
The manuscript title contains a prominent typographical error, referring to the study as a "randomized controlled trail" rather than a "trial". The introduction lacks logical flow, occasionally relies on outdated terminology, and inappropriately uses bullet points instead of cohesive academic paragraphs in key sections. A thorough structural revision and professional proofread are necessary to elevate the manuscript to scientific publication standards.
Response:
We thank the reviewer for carefully identifying these formatting and structural issues. The typographical error in the manuscript title has been corrected from “randomized controlled trail” to “randomized controlled trial.” In addition, the Introduction section has been thoroughly revised to improve the logical flow and coherence of the background information. Outdated terminology has been updated where appropriate, and bullet points previously used in narrative sections have been replaced with structured academic paragraphs to maintain consistency with scientific writing standards. Furthermore, the entire manuscript has undergone careful proofreading and structural revision to enhance clarity, readability, and overall presentation in accordance with journal publication standards.

Lack of Justification for a Single-Sex Study:
The original protocol failed to adequately explain why the study is restricted exclusively to middle-aged women. While the authors later cited menopause and estrogen-related metabolic changes in their response, this fundamental rationale was missing from the protocol's background.
Response:
We thank the reviewer for highlighting this important point. We acknowledge that the initial protocol did not sufficiently explain the rationale for restricting the study to middle-aged women, and this has now been clarified in the revised background section. Middle-aged women represent a population at increased risk of metabolic disorders due to hormonal changes associated with the menopausal transition. During this period, declining estrogen levels are associated with increased visceral adiposity, alterations in body composition, and reduced insulin sensitivity, all of which contribute to a higher risk of overweight, obesity, and metabolic disturbances. These physiological and metabolic changes make middle-aged women a particularly relevant population for examining the potential benefits of dietary interventions such as increased dietary fiber intake on insulin resistance and body composition. Accordingly, the revised manuscript now clearly states this sex-specific rationale in the background section to justify the focus on middle-aged women.

Missed Opportunity for a Crossover Design:
The authors did not consider a crossover design. In dietary studies where blinding is impossible and inter-individual variability is high, having participants act as their own controls (by switching between the 25g and 40g diets) could have significantly strengthened the evidence.
Response:
We acknowledge that crossover designs can reduce inter-individual variability in dietary studies by allowing participants to serve as their own controls. However, a crossover design was not considered appropriate for the present study due to several practical and methodological considerations. First, the intervention period in this study is relatively long (6 months), and implementing a crossover design would require an additional intervention phase along with an adequate washout period to minimize carryover effects, which would substantially extend the total study duration. Second, repeated switching between dietary patterns (from 25 g to 40 g fiber intake and vice versa) may be challenging for participants and could negatively influence adherence to the prescribed diet. Therefore, a parallel randomized controlled trial design was considered more feasible and appropriate for evaluating the long-term effects of increased dietary fiber intake in this population.

Vague Secondary Objectives:
The secondary objective, stated simply as "To assess the opinions of women on modified fiber intake," was heavily criticized for being too vague and lacking specific, measurable parameters.
Response:
Thank you for your valuable comment. It was operationalized using a structured, dichotomous (yes/no) questionnaire administered at predefined time points (30th, 90th, and 180th day). Each item captured specific, measurable aspects of participant opinion, including acceptance of modified fiber intake, perceived ease of implementation, and willingness to continue the dietary changes. The use of binary responses ensured quantifiability, while repeated assessments enabled longitudinal tracking of changes in opinion and compliance over time.

Missing Justification for Variables:
The authors plugged specific numbers into their power calculation (like standard deviations of 3.96 for BMI and 5.06 for insulin resistance) but initially failed to justify where these specific estimates came from or why they represented a "clinically significant difference".
Response:
We thank the reviewer for highlighting the need to justify the parameters used in the sample size calculation. In the revised manuscript, we have clarified the source and rationale for the values used in the power calculation. The estimates for the standard deviation (σ) of BMI (3.96) and insulin resistance (5.06) were derived from previously published intervention studies examining the effects of dietary or lifestyle interventions on metabolic outcomes in similar adult populations. These values were selected as they represent realistic variability observed in comparable studies. The minimum detectable difference (d) was chosen based on changes considered clinically meaningful in the context of improvements in BMI and insulin resistance following dietary interventions. Thus, the parameters used in the sample size calculation were selected to ensure adequate statistical power to detect clinically relevant changes in the primary outcomes. These details and supporting references have now been added to the Methods section to improve transparency and clarity of the sample size estimation.

Unproven Feasibility of the Intervention:
Increasing a patient's dietary fiber by an additional 15g to 20g per day exclusively through whole foods is notoriously difficult. Reviewers questioned whether the research team had any pilot data proving they could successfully achieve and sustain this massive leap in fiber intake over 6 months.
Response:
We thank the reviewer for raising this important concern regarding the feasibility of achieving and sustaining an increased dietary fiber intake through whole foods. Prior to initiating the intervention, preliminary observations from our earlier dietary assessment conducted among middle-aged women in the same clinical setting indicated that many participants were consuming substantially lower amounts of dietary fiber than recommended levels. Therefore, the intervention was designed to increase fiber intake gradually through locally available, culturally acceptable high fiber foods such as whole grains, legumes, fruits, and vegetables, rather than relying on fiber supplements. In addition, participants in the intervention group receive individualized dietary counseling, a customized high fiber diet plan, and regular follow-up reinforcement through telephonic monitoring, which are intended to facilitate adherence and support gradual dietary modification over time. These strategies were incorporated to improve the feasibility and sustainability of achieving the targeted fiber intake.

No Objective Compliance Biomarkers:
Despite the known flaws of self-reported dietary recalls and food frequency questionnaires, the study lacks any objective physiological markers to prove participants actually ate the fiber (such as stool weight, transit time, or specific microbiome metabolite markers). Adding a "compliance checklist" does not solve the fundamental issue of subjective reporting.
Response:
We thank the reviewer for this important observation. We agree that objective biomarkers can strengthen the assessment of dietary compliance in nutrition intervention studies. However, the inclusion of objective biomarkers such as stool analysis (e.g., stool weight, transit time, or microbial metabolites) or other microbiome-related markers was not feasible in the present study. During the planning phase, the possibility of incorporating stool analysis was considered; however, participants expressed reluctance and practical concerns regarding stool sample collection, which posed challenges for participant acceptance and compliance in a community-based dietary intervention study. Additionally, logistical and resource constraints limited the feasibility of conducting microbiome or metabolite analysis. Furthermore, the absence of objective biomarkers such as stool analysis has now been acknowledged as a limitation in the manuscript.

Confusing Protocol Structure:
Reviewers found the methodology highly confusing because Phase 1 (the screening phase) and Phase 2 (the randomized trial) were jumbled together without clear separation or a concise timeline.
Response:
Thank you for this observation. In response, Phase 1 (screening phase) and Phase 2 (randomized controlled trial) have now been clearly delineated and described as distinct components of the study. This separation was initially clarified in Version 1 of the revised manuscript, and the same structured presentation has been consistently maintained and further refined in subsequent versions. Additionally, the methodology section has been reorganized to improve clarity, with a more explicit description of the study flow and timeline for each phase to avoid any overlap or confusion.
Competing Interests: no Close
Report a concern
Respond or Comment

COMMENTS ON THIS REPORT

Author Response 24 Apr 2026

Suvarna Hebbar, Clinical Nutrition and Dietetics, Manipal College of Health Professions, Manipal., 576104, India

24 Apr 2026

Author Response

Response to Reviewer
Methodological Concerns

The reliance on a single 24-hour dietary recall in Phase 1 is insufficient to accurately capture participants' habitual fiber intake. A validated Food Frequency ... Continue reading Response to Reviewer
Methodological Concerns

The reliance on a single 24-hour dietary recall in Phase 1 is insufficient to accurately capture participants' habitual fiber intake. A validated Food Frequency Questionnaire (FFQ) should be implemented during this initial screening phase to mitigate recall bias. Additionally, while the targeted difference in fiber intake between groups was reduced to 15g, the sample size calculation remains unadjusted for this potentially smaller effect size.
Response:
We thank the reviewer for these valuable methodological suggestions. We acknowledge that a single 24-hour dietary recall may not fully capture habitual dietary intake at the individual level. However, in Phase 1 the primary objective is screening and estimating general dietary patterns among a large sample of participants rather than assessing precise long-term nutrient intake. A single 24-hour dietary recall is widely used in epidemiological screening studies to estimate mean group intake when collected from a sufficiently large and heterogeneous population; therefore, it was considered appropriate for the initial screening phase involving approximately 500 participants. To strengthen dietary assessment in the intervention phase, the protocol has been modified so that in Phase 2 dietary intake will be assessed using multiple 24-hour dietary recalls at follow-up time points along with a Food Frequency Questionnaire (FFQ) to better capture habitual intake patterns. Nutrient intake will be analyzed using DietCal software based on standardized Indian food composition tables, which will further improve the reliability of dietary assessment while maintaining feasibility during the large screening phase. In addition, we appreciate the reviewer’s observation regarding the targeted difference in dietary fiber intake between groups being reduced to 15 g/day. The sample size calculation for Phase 2 was not based on the absolute difference in fiber intake but on the expected effect on the primary clinical outcomes, specifically insulin resistance (HOMA-IR) and body mass index (BMI). The power calculation used anticipated standard deviation values derived from previously published intervention studies and the clinically meaningful difference expected for BMI and insulin resistance. Because the calculation was based on changes in these metabolic outcomes rather than fiber intake itself, the reduction in the planned fiber difference from 20 g/day to 15 g/day does not alter the expected clinically meaningful effect on the primary endpoints; therefore, the required sample size remains appropriate and unchanged.

Intervention and Adherence
The active dietary counseling required to reach the 40g daily fiber target makes any claim of blinding impossible, rendering the study an open-label trial. Furthermore, expecting participants to maintain such a high fiber intake from whole foods over six months introduces a severe risk of non-compliance and dropout. The intervention also fails to control for the varying ratios of soluble to insoluble fiber inherent in whole foods, which risks confounding the metabolic outcomes.
Response:
We thank the reviewer for these important observations. We agree that complete blinding is not feasible in dietary behavioral interventions that involve active counseling and individualized dietary guidance; therefore, the study should be considered an open-label randomized controlled trial. This approach is common in nutrition intervention research where participants are required to actively modify their dietary behavior. To minimize potential bias, randomization and allocation concealment will be implemented using stratified block randomization and opaque sealed envelopes. In addition, the primary outcomes are objective measures, including biochemical parameters such as fasting glucose, HbA1c, serum insulin, lipid profile, and body composition analysis, which helps reduce measurement bias despite the open-label design.

We also acknowledge that maintaining a dietary fiber intake of approximately 40 g/day over six months may pose adherence challenges and could potentially increase the risk of non-compliance or dropout. To enhance participant adherence and minimize attrition, several strategies have been incorporated into the protocol, including individualized dietary counseling, customized high-fiber diet charts based on locally available foods, regular telephonic follow-up, dietary tracking sheets, fiber intake compliance checklists, and continuous motivation and reinforcement during follow-up visits. These strategies are widely used in dietary intervention studies and are expected to support sustained compliance throughout the intervention period.

Regarding the concern about varying ratios of soluble and insoluble fiber in whole foods potentially confounding metabolic outcomes, we acknowledge that whole foods naturally contain different proportions of fiber types. However, the primary objective of the study is to evaluate the effect of increasing total dietary fiber intake from whole foods under real-world dietary conditions rather than isolating specific fiber fractions. This approach improves the ecological validity and practical applicability of the findings. Furthermore, dietary intake will be assessed using 24-hour dietary recalls and a Food Frequency Questionnaire (FFQ), which allows estimation of total dietary fiber intake and helps account for dietary variability. Collectively, this design enables the study to evaluate the metabolic effects of increasing total dietary fiber intake within a realistic dietary context.

Manuscript Formatting Issues
The manuscript title contains a prominent typographical error, referring to the study as a "randomized controlled trail" rather than a "trial". The introduction lacks logical flow, occasionally relies on outdated terminology, and inappropriately uses bullet points instead of cohesive academic paragraphs in key sections. A thorough structural revision and professional proofread are necessary to elevate the manuscript to scientific publication standards.
Response:
We thank the reviewer for carefully identifying these formatting and structural issues. The typographical error in the manuscript title has been corrected from “randomized controlled trail” to “randomized controlled trial.” In addition, the Introduction section has been thoroughly revised to improve the logical flow and coherence of the background information. Outdated terminology has been updated where appropriate, and bullet points previously used in narrative sections have been replaced with structured academic paragraphs to maintain consistency with scientific writing standards. Furthermore, the entire manuscript has undergone careful proofreading and structural revision to enhance clarity, readability, and overall presentation in accordance with journal publication standards.

Lack of Justification for a Single-Sex Study:
The original protocol failed to adequately explain why the study is restricted exclusively to middle-aged women. While the authors later cited menopause and estrogen-related metabolic changes in their response, this fundamental rationale was missing from the protocol's background.
Response:
We thank the reviewer for highlighting this important point. We acknowledge that the initial protocol did not sufficiently explain the rationale for restricting the study to middle-aged women, and this has now been clarified in the revised background section. Middle-aged women represent a population at increased risk of metabolic disorders due to hormonal changes associated with the menopausal transition. During this period, declining estrogen levels are associated with increased visceral adiposity, alterations in body composition, and reduced insulin sensitivity, all of which contribute to a higher risk of overweight, obesity, and metabolic disturbances. These physiological and metabolic changes make middle-aged women a particularly relevant population for examining the potential benefits of dietary interventions such as increased dietary fiber intake on insulin resistance and body composition. Accordingly, the revised manuscript now clearly states this sex-specific rationale in the background section to justify the focus on middle-aged women.

Missed Opportunity for a Crossover Design:
The authors did not consider a crossover design. In dietary studies where blinding is impossible and inter-individual variability is high, having participants act as their own controls (by switching between the 25g and 40g diets) could have significantly strengthened the evidence.
Response:
We acknowledge that crossover designs can reduce inter-individual variability in dietary studies by allowing participants to serve as their own controls. However, a crossover design was not considered appropriate for the present study due to several practical and methodological considerations. First, the intervention period in this study is relatively long (6 months), and implementing a crossover design would require an additional intervention phase along with an adequate washout period to minimize carryover effects, which would substantially extend the total study duration. Second, repeated switching between dietary patterns (from 25 g to 40 g fiber intake and vice versa) may be challenging for participants and could negatively influence adherence to the prescribed diet. Therefore, a parallel randomized controlled trial design was considered more feasible and appropriate for evaluating the long-term effects of increased dietary fiber intake in this population.

Vague Secondary Objectives:
The secondary objective, stated simply as "To assess the opinions of women on modified fiber intake," was heavily criticized for being too vague and lacking specific, measurable parameters.
Response:
Thank you for your valuable comment. It was operationalized using a structured, dichotomous (yes/no) questionnaire administered at predefined time points (30th, 90th, and 180th day). Each item captured specific, measurable aspects of participant opinion, including acceptance of modified fiber intake, perceived ease of implementation, and willingness to continue the dietary changes. The use of binary responses ensured quantifiability, while repeated assessments enabled longitudinal tracking of changes in opinion and compliance over time.

Missing Justification for Variables:
The authors plugged specific numbers into their power calculation (like standard deviations of 3.96 for BMI and 5.06 for insulin resistance) but initially failed to justify where these specific estimates came from or why they represented a "clinically significant difference".
Response:
We thank the reviewer for highlighting the need to justify the parameters used in the sample size calculation. In the revised manuscript, we have clarified the source and rationale for the values used in the power calculation. The estimates for the standard deviation (σ) of BMI (3.96) and insulin resistance (5.06) were derived from previously published intervention studies examining the effects of dietary or lifestyle interventions on metabolic outcomes in similar adult populations. These values were selected as they represent realistic variability observed in comparable studies. The minimum detectable difference (d) was chosen based on changes considered clinically meaningful in the context of improvements in BMI and insulin resistance following dietary interventions. Thus, the parameters used in the sample size calculation were selected to ensure adequate statistical power to detect clinically relevant changes in the primary outcomes. These details and supporting references have now been added to the Methods section to improve transparency and clarity of the sample size estimation.

Unproven Feasibility of the Intervention:
Increasing a patient's dietary fiber by an additional 15g to 20g per day exclusively through whole foods is notoriously difficult. Reviewers questioned whether the research team had any pilot data proving they could successfully achieve and sustain this massive leap in fiber intake over 6 months.
Response:
We thank the reviewer for raising this important concern regarding the feasibility of achieving and sustaining an increased dietary fiber intake through whole foods. Prior to initiating the intervention, preliminary observations from our earlier dietary assessment conducted among middle-aged women in the same clinical setting indicated that many participants were consuming substantially lower amounts of dietary fiber than recommended levels. Therefore, the intervention was designed to increase fiber intake gradually through locally available, culturally acceptable high fiber foods such as whole grains, legumes, fruits, and vegetables, rather than relying on fiber supplements. In addition, participants in the intervention group receive individualized dietary counseling, a customized high fiber diet plan, and regular follow-up reinforcement through telephonic monitoring, which are intended to facilitate adherence and support gradual dietary modification over time. These strategies were incorporated to improve the feasibility and sustainability of achieving the targeted fiber intake.

No Objective Compliance Biomarkers:
Despite the known flaws of self-reported dietary recalls and food frequency questionnaires, the study lacks any objective physiological markers to prove participants actually ate the fiber (such as stool weight, transit time, or specific microbiome metabolite markers). Adding a "compliance checklist" does not solve the fundamental issue of subjective reporting.
Response:
We thank the reviewer for this important observation. We agree that objective biomarkers can strengthen the assessment of dietary compliance in nutrition intervention studies. However, the inclusion of objective biomarkers such as stool analysis (e.g., stool weight, transit time, or microbial metabolites) or other microbiome-related markers was not feasible in the present study. During the planning phase, the possibility of incorporating stool analysis was considered; however, participants expressed reluctance and practical concerns regarding stool sample collection, which posed challenges for participant acceptance and compliance in a community-based dietary intervention study. Additionally, logistical and resource constraints limited the feasibility of conducting microbiome or metabolite analysis. Furthermore, the absence of objective biomarkers such as stool analysis has now been acknowledged as a limitation in the manuscript.

Confusing Protocol Structure:
Reviewers found the methodology highly confusing because Phase 1 (the screening phase) and Phase 2 (the randomized trial) were jumbled together without clear separation or a concise timeline.
Response:
Thank you for this observation. In response, Phase 1 (screening phase) and Phase 2 (randomized controlled trial) have now been clearly delineated and described as distinct components of the study. This separation was initially clarified in Version 1 of the revised manuscript, and the same structured presentation has been consistently maintained and further refined in subsequent versions. Additionally, the methodology section has been reorganized to improve clarity, with a more explicit description of the study flow and timeline for each phase to avoid any overlap or confusion.
Response to Reviewer
Methodological Concerns

The reliance on a single 24-hour dietary recall in Phase 1 is insufficient to accurately capture participants' habitual fiber intake. A validated Food Frequency Questionnaire (FFQ) should be implemented during this initial screening phase to mitigate recall bias. Additionally, while the targeted difference in fiber intake between groups was reduced to 15g, the sample size calculation remains unadjusted for this potentially smaller effect size.
Response:
We thank the reviewer for these valuable methodological suggestions. We acknowledge that a single 24-hour dietary recall may not fully capture habitual dietary intake at the individual level. However, in Phase 1 the primary objective is screening and estimating general dietary patterns among a large sample of participants rather than assessing precise long-term nutrient intake. A single 24-hour dietary recall is widely used in epidemiological screening studies to estimate mean group intake when collected from a sufficiently large and heterogeneous population; therefore, it was considered appropriate for the initial screening phase involving approximately 500 participants. To strengthen dietary assessment in the intervention phase, the protocol has been modified so that in Phase 2 dietary intake will be assessed using multiple 24-hour dietary recalls at follow-up time points along with a Food Frequency Questionnaire (FFQ) to better capture habitual intake patterns. Nutrient intake will be analyzed using DietCal software based on standardized Indian food composition tables, which will further improve the reliability of dietary assessment while maintaining feasibility during the large screening phase. In addition, we appreciate the reviewer’s observation regarding the targeted difference in dietary fiber intake between groups being reduced to 15 g/day. The sample size calculation for Phase 2 was not based on the absolute difference in fiber intake but on the expected effect on the primary clinical outcomes, specifically insulin resistance (HOMA-IR) and body mass index (BMI). The power calculation used anticipated standard deviation values derived from previously published intervention studies and the clinically meaningful difference expected for BMI and insulin resistance. Because the calculation was based on changes in these metabolic outcomes rather than fiber intake itself, the reduction in the planned fiber difference from 20 g/day to 15 g/day does not alter the expected clinically meaningful effect on the primary endpoints; therefore, the required sample size remains appropriate and unchanged.

Intervention and Adherence
The active dietary counseling required to reach the 40g daily fiber target makes any claim of blinding impossible, rendering the study an open-label trial. Furthermore, expecting participants to maintain such a high fiber intake from whole foods over six months introduces a severe risk of non-compliance and dropout. The intervention also fails to control for the varying ratios of soluble to insoluble fiber inherent in whole foods, which risks confounding the metabolic outcomes.
Response:
We thank the reviewer for these important observations. We agree that complete blinding is not feasible in dietary behavioral interventions that involve active counseling and individualized dietary guidance; therefore, the study should be considered an open-label randomized controlled trial. This approach is common in nutrition intervention research where participants are required to actively modify their dietary behavior. To minimize potential bias, randomization and allocation concealment will be implemented using stratified block randomization and opaque sealed envelopes. In addition, the primary outcomes are objective measures, including biochemical parameters such as fasting glucose, HbA1c, serum insulin, lipid profile, and body composition analysis, which helps reduce measurement bias despite the open-label design.

We also acknowledge that maintaining a dietary fiber intake of approximately 40 g/day over six months may pose adherence challenges and could potentially increase the risk of non-compliance or dropout. To enhance participant adherence and minimize attrition, several strategies have been incorporated into the protocol, including individualized dietary counseling, customized high-fiber diet charts based on locally available foods, regular telephonic follow-up, dietary tracking sheets, fiber intake compliance checklists, and continuous motivation and reinforcement during follow-up visits. These strategies are widely used in dietary intervention studies and are expected to support sustained compliance throughout the intervention period.

Regarding the concern about varying ratios of soluble and insoluble fiber in whole foods potentially confounding metabolic outcomes, we acknowledge that whole foods naturally contain different proportions of fiber types. However, the primary objective of the study is to evaluate the effect of increasing total dietary fiber intake from whole foods under real-world dietary conditions rather than isolating specific fiber fractions. This approach improves the ecological validity and practical applicability of the findings. Furthermore, dietary intake will be assessed using 24-hour dietary recalls and a Food Frequency Questionnaire (FFQ), which allows estimation of total dietary fiber intake and helps account for dietary variability. Collectively, this design enables the study to evaluate the metabolic effects of increasing total dietary fiber intake within a realistic dietary context.

Manuscript Formatting Issues
The manuscript title contains a prominent typographical error, referring to the study as a "randomized controlled trail" rather than a "trial". The introduction lacks logical flow, occasionally relies on outdated terminology, and inappropriately uses bullet points instead of cohesive academic paragraphs in key sections. A thorough structural revision and professional proofread are necessary to elevate the manuscript to scientific publication standards.
Response:
We thank the reviewer for carefully identifying these formatting and structural issues. The typographical error in the manuscript title has been corrected from “randomized controlled trail” to “randomized controlled trial.” In addition, the Introduction section has been thoroughly revised to improve the logical flow and coherence of the background information. Outdated terminology has been updated where appropriate, and bullet points previously used in narrative sections have been replaced with structured academic paragraphs to maintain consistency with scientific writing standards. Furthermore, the entire manuscript has undergone careful proofreading and structural revision to enhance clarity, readability, and overall presentation in accordance with journal publication standards.

Lack of Justification for a Single-Sex Study:
The original protocol failed to adequately explain why the study is restricted exclusively to middle-aged women. While the authors later cited menopause and estrogen-related metabolic changes in their response, this fundamental rationale was missing from the protocol's background.
Response:
We thank the reviewer for highlighting this important point. We acknowledge that the initial protocol did not sufficiently explain the rationale for restricting the study to middle-aged women, and this has now been clarified in the revised background section. Middle-aged women represent a population at increased risk of metabolic disorders due to hormonal changes associated with the menopausal transition. During this period, declining estrogen levels are associated with increased visceral adiposity, alterations in body composition, and reduced insulin sensitivity, all of which contribute to a higher risk of overweight, obesity, and metabolic disturbances. These physiological and metabolic changes make middle-aged women a particularly relevant population for examining the potential benefits of dietary interventions such as increased dietary fiber intake on insulin resistance and body composition. Accordingly, the revised manuscript now clearly states this sex-specific rationale in the background section to justify the focus on middle-aged women.

Missed Opportunity for a Crossover Design:
The authors did not consider a crossover design. In dietary studies where blinding is impossible and inter-individual variability is high, having participants act as their own controls (by switching between the 25g and 40g diets) could have significantly strengthened the evidence.
Response:
We acknowledge that crossover designs can reduce inter-individual variability in dietary studies by allowing participants to serve as their own controls. However, a crossover design was not considered appropriate for the present study due to several practical and methodological considerations. First, the intervention period in this study is relatively long (6 months), and implementing a crossover design would require an additional intervention phase along with an adequate washout period to minimize carryover effects, which would substantially extend the total study duration. Second, repeated switching between dietary patterns (from 25 g to 40 g fiber intake and vice versa) may be challenging for participants and could negatively influence adherence to the prescribed diet. Therefore, a parallel randomized controlled trial design was considered more feasible and appropriate for evaluating the long-term effects of increased dietary fiber intake in this population.

Vague Secondary Objectives:
The secondary objective, stated simply as "To assess the opinions of women on modified fiber intake," was heavily criticized for being too vague and lacking specific, measurable parameters.
Response:
Thank you for your valuable comment. It was operationalized using a structured, dichotomous (yes/no) questionnaire administered at predefined time points (30th, 90th, and 180th day). Each item captured specific, measurable aspects of participant opinion, including acceptance of modified fiber intake, perceived ease of implementation, and willingness to continue the dietary changes. The use of binary responses ensured quantifiability, while repeated assessments enabled longitudinal tracking of changes in opinion and compliance over time.

Missing Justification for Variables:
The authors plugged specific numbers into their power calculation (like standard deviations of 3.96 for BMI and 5.06 for insulin resistance) but initially failed to justify where these specific estimates came from or why they represented a "clinically significant difference".
Response:
We thank the reviewer for highlighting the need to justify the parameters used in the sample size calculation. In the revised manuscript, we have clarified the source and rationale for the values used in the power calculation. The estimates for the standard deviation (σ) of BMI (3.96) and insulin resistance (5.06) were derived from previously published intervention studies examining the effects of dietary or lifestyle interventions on metabolic outcomes in similar adult populations. These values were selected as they represent realistic variability observed in comparable studies. The minimum detectable difference (d) was chosen based on changes considered clinically meaningful in the context of improvements in BMI and insulin resistance following dietary interventions. Thus, the parameters used in the sample size calculation were selected to ensure adequate statistical power to detect clinically relevant changes in the primary outcomes. These details and supporting references have now been added to the Methods section to improve transparency and clarity of the sample size estimation.

Unproven Feasibility of the Intervention:
Increasing a patient's dietary fiber by an additional 15g to 20g per day exclusively through whole foods is notoriously difficult. Reviewers questioned whether the research team had any pilot data proving they could successfully achieve and sustain this massive leap in fiber intake over 6 months.
Response:
We thank the reviewer for raising this important concern regarding the feasibility of achieving and sustaining an increased dietary fiber intake through whole foods. Prior to initiating the intervention, preliminary observations from our earlier dietary assessment conducted among middle-aged women in the same clinical setting indicated that many participants were consuming substantially lower amounts of dietary fiber than recommended levels. Therefore, the intervention was designed to increase fiber intake gradually through locally available, culturally acceptable high fiber foods such as whole grains, legumes, fruits, and vegetables, rather than relying on fiber supplements. In addition, participants in the intervention group receive individualized dietary counseling, a customized high fiber diet plan, and regular follow-up reinforcement through telephonic monitoring, which are intended to facilitate adherence and support gradual dietary modification over time. These strategies were incorporated to improve the feasibility and sustainability of achieving the targeted fiber intake.

No Objective Compliance Biomarkers:
Despite the known flaws of self-reported dietary recalls and food frequency questionnaires, the study lacks any objective physiological markers to prove participants actually ate the fiber (such as stool weight, transit time, or specific microbiome metabolite markers). Adding a "compliance checklist" does not solve the fundamental issue of subjective reporting.
Response:
We thank the reviewer for this important observation. We agree that objective biomarkers can strengthen the assessment of dietary compliance in nutrition intervention studies. However, the inclusion of objective biomarkers such as stool analysis (e.g., stool weight, transit time, or microbial metabolites) or other microbiome-related markers was not feasible in the present study. During the planning phase, the possibility of incorporating stool analysis was considered; however, participants expressed reluctance and practical concerns regarding stool sample collection, which posed challenges for participant acceptance and compliance in a community-based dietary intervention study. Additionally, logistical and resource constraints limited the feasibility of conducting microbiome or metabolite analysis. Furthermore, the absence of objective biomarkers such as stool analysis has now been acknowledged as a limitation in the manuscript.

Confusing Protocol Structure:
Reviewers found the methodology highly confusing because Phase 1 (the screening phase) and Phase 2 (the randomized trial) were jumbled together without clear separation or a concise timeline.
Response:
Thank you for this observation. In response, Phase 1 (screening phase) and Phase 2 (randomized controlled trial) have now been clearly delineated and described as distinct components of the study. This separation was initially clarified in Version 1 of the revised manuscript, and the same structured presentation has been consistently maintained and further refined in subsequent versions. Additionally, the methodology section has been reorganized to improve clarity, with a more explicit description of the study flow and timeline for each phase to avoid any overlap or confusion.
Competing Interests: no Close
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Reviewer Report 19 Mar 2026

Tatiana Palotta Minari, Federal University of São Paulo (UNIFESP), Santos, Brazil

Approved with Reservations

https://doi.org/10.5256/f1000research.193737.r465124

Suggestions for Improvement

Reduce redundancy in the introduction and discussion to improve readability and maintain focus.
Present the sample size calculation formula in a clearer and more legible format, ensuring that readers can easily

Suggestions for Improvement

Reduce redundancy in the introduction and discussion to improve readability and maintain focus.
Present the sample size calculation formula in a clearer and more legible format, ensuring that readers can easily follow the computation steps.
Discuss more explicitly the impact of additional counseling in the intervention group, as this behavioral support may influence outcomes beyond dietary fiber intake.
Include a detailed adherence analysis plan, such as a checklist or monitoring tool to assess actual fiber consumption and compliance with the dietary recommendations.
Consider incorporating measures of gut microbiota, since the study rationale emphasizes the role of fiber in modulating intestinal bacteria and metabolic health.

Is the rationale for, and objectives of, the study clearly described?

Yes
Is the study design appropriate for the research question?

Yes
Are sufficient details of the methods provided to allow replication by others?

Yes
Are the datasets clearly presented in a useable and accessible format?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: This article connects with my area of research because it sits at the intersection of nutrition, metabolism, and women’s health. The study protocol focuses on how dietary fiber intake influences insulin resistance, body composition, and weight in overweight and obese middle-aged women.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

CITE

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Author Response 08 Apr 2026

Suvarna Hebbar, Clinical Nutrition and Dietetics, Manipal College of Health Professions, Manipal., 576104, India

08 Apr 2026

Author Response

Reduce redundancy in the introduction and discussion to improve readability and maintain focus.
Background
Obesity is a major public health concern worldwide. Urbanization, economic growth, changing lifestyles, and dietary habits ... Continue reading Reduce redundancy in the introduction and discussion to improve readability and maintain focus.
Background
Obesity is a major public health concern worldwide. Urbanization, economic growth, changing lifestyles, and dietary habits have contributed to a “double burden” of diseases in rapidly developing low- and middle-income countries such as India¹. The average dietary fiber intake is below the recommended levels, and the World Health Organization estimates that the incidence of obesity has increased globally in the past decade. Many individuals do not consume adequate fiber to meet recommended intakes, and obese women often report lower dietary fiber consumption compared with normal-weight individuals. ²
Dietary fiber plays an important role in appetite regulation and weight management. Fiber-rich foods promote satiety and reduce hunger by delaying gastric emptying and increasing stomach fullness.³ These effects are particularly evident among individuals with obesity.⁴ In addition, dietary fiber consumption promotes the growth of beneficial bacteria in the colon, which may help prevent obesity, metabolic syndrome, and adverse intestinal changes.⁵
High-fiber diets are associated with improved health outcomes and a reduced risk of several chronic diseases. Fiber-rich foods typically have lower energy density and can replace high-fat, energy-dense foods in the diet. Increased dietary fiber intake has been linked with improvements in serum lipoproteins, blood pressure, blood glucose control, and body weight. Individuals consuming adequate fiber are at lower risk of coronary artery disease, stroke, hypertension, diabetes, obesity, and gastrointestinal disorders. In addition, soluble fiber intake has been shown to enhance immune function. ⁶
Dietary fiber obtained from fruits, vegetables, legumes, and whole grains provides several physiological benefits and is associated with a lower risk of chronic diseases such as cardiovascular disease, type 2 diabetes mellitus, obesity, and certain cancers. These foods also provide micronutrients and phytochemicals that contribute to overall health, highlighting the importance of promoting adequate dietary fiber intake in the population.⁷
However, limited research has examined the role of dietary fiber specifically in the treatment and management of obesity, and further studies are required to strengthen the evidence linking dietary fiber intake with obesity-related outcomes.⁸ Dietary fiber also promotes the growth of beneficial gut bacteria and supports microbial balance. Increased consumption of dietary fiber and whole grains enhances the growth of beneficial intestinal microbiota, which may be particularly relevant in individuals with obesity and other metabolic disorders. However, these effects may vary depending on the type, structure, and composition of the fiber and whole-grain sources.⁹
High-fiber foods are more satiating and contribute to appetite control by influencing gastric emptying, reducing food intake, and promoting a sense of fullness.¹⁰ Fermentation of dietary fiber in the colon produces short-chain fatty acids that regulate appetite through gut hormones such as cholecystokinin and glucagon-like peptides, which help reduce hunger and increase satiety.¹¹ Increased chewing and gastric distension associated with fiber-rich foods may further enhance satiety and regulate food intake.¹²
This study focuses on weight reduction through increased dietary fiber consumption. According to the Indian Council of Medical Research and National Institute of Nutrition guidelines, the recommended dietary fiber intake is 40 g per 2000 kcal of energy intake.¹³ Increasing dietary fiber consumption to recommended levels may support weight management and improve overall metabolic health.
Discussion
Evidence on the association between dietary fiber intake and metabolic outcomes among overweight and obese middle-aged women in India remains limited. This study aimed to examine whether increased dietary fiber intake can improve insulin resistance, body composition, and weight in this population. Dietary fiber provides several metabolic benefits, including enhanced satiety, improved glycemic control, reduced cholesterol levels, and increased fat oxidation. By lowering energy intake and supporting metabolic regulation, adequate fiber consumption may contribute to effective weight management. In addition to dietary intervention, participants in the intervention group received regular dietary counseling, which may have improved adherence to the recommended dietary practices and encouraged healthier lifestyle behaviors. Therefore, the observed improvements in metabolic indicators and body composition may reflect the combined influence of increased dietary fiber intake and the supportive role of counseling in promoting sustained dietary and behavioral changes.

Present the sample size calculation formula in a clearer and more legible format, ensuring that readers can easily follow the computation steps.
Sample Size Calculation
The sample size was calculated using the following formula:
n=(2(Z_(1-α/2)+Z_(1-β) )^2 σ^2 [1+(m-1)ρ])/(md^2 )

Where:
            n = sample size per group
            Z₁₋α/₂ = 1.96 (for α = 0.05, two-tailed test)
            Z₁₋β = 0.84 (for 80% statistical power)
            σ = anticipated population standard deviation of the outcome variable
            d = clinically significant difference (effect size)
            m = number of time points/follow-ups (m = 2)
            ρ = intraclass correlation coefficient (ρ = 0.4)
Computation for BMI
Parameters used:
            σ = 3.96
            d = 1.5
            m = 2
            ρ = 0.4
Step 1: Substitute values into the formula
n=(2(1.96+0.84)^2 (3.96)^2 [1+(2-1)×0.4])/(2(1.5)^2 )
Step 2: Simplify
n=(2(2.8)^2 (15.68)(1.4))/(2(2.25))
Step 3: Final estimate
n≈77" participants per group"
Adjustment for 15% dropout rate:
n=77/(1-0.15)=90
Therefore, 90 participants per group were required.

Computation for Insulin Resistance
Parameters used:
            σ = 5.06
            d = 2
            m = 2
            ρ = 0.4
Step 1: Substitute values
n=(2(1.96+0.84)^2 (5.06)^2 [1+(2-1)×0.4])/(2(2)^2 )
Step 2: Simplify
n=(2(2.8)^2 (25.60)(1.4))/(2(4))
Step 3: Final estimate
n≈71" participants per group"
Adjustment for 15% dropout rate:
n=71/(1-0.15)=83
Thus, 83 participants per group were required.

Include a detailed adherence analysis plan, such as a checklist or monitoring tool to assess actual fiber consumption and compliance with the dietary recommendations.
Women with no contraindications to high dietary fiber consumption and abnormal HOMA-IR will be included in Phase 2 of the study. Baseline assessments will be conducted for both intervention and control groups. Demographic information including age, religion, place of residence, type of family, number of family members, marital status, education, occupation, and income will be collected using a structured proforma. Anthropometric measurements such as height (stadiometer), body weight (weighing scale), and waist and hip circumference will be recorded in the outpatient department. Biochemical parameters including fasting blood glucose (hexokinase method), HbA1c (TINA method), serum insulin (ECLIA), and lipid profile (triglycerides GPO Trinder method, HDL direct homogeneous method, LDL enzymatic method, and total cholesterol CE-CHOD-POD method) will be assessed. Dietary intake will be assessed using a 24-hour dietary recall and a Food Frequency Questionnaire (FFQ), and nutrient intake will be analyzed using DietCal software version 6.3. Adherence to dietary fiber intervention will be monitored using multiple strategies, including a tracking sheet to record daily intake of fiber-rich foods and a fiber intake compliance checklist during follow-up visits. Monthly telephonic follow-ups will be conducted to reinforce dietary counseling, evaluate adherence to the recommended dietary practices, and address any challenges faced by participants. Participants’ feedback on high-fiber food consumption will also be documented to identify adherence patterns and potential barriers, ensuring systematic monitoring of dietary fiber intake and compliance with the intervention throughout the study period. Physical activity levels will be assessed using the Global Physical Activity Questionnaire (GPAQ), and body composition parameters including visceral fat, subcutaneous fat, and muscle mass will be measured using a body fat analyzer. Clinical assessment will also be performed to document physical complaints reported by participants.


Consider incorporating measures of gut microbiota, since the study rationale emphasizes the role of fiber in modulating intestinal bacteria and metabolic health
Although dietary fiber is known to influence metabolic health through modulation of gut microbiota, gut microbial composition was not assessed in this study, which primarily focused on clinical and metabolic outcomes such as insulin resistance, body composition, and weight. Future studies incorporating microbiome analysis may provide better insight into the mechanisms linking dietary fiber intake with metabolic health
Reduce redundancy in the introduction and discussion to improve readability and maintain focus.
Background
Obesity is a major public health concern worldwide. Urbanization, economic growth, changing lifestyles, and dietary habits have contributed to a “double burden” of diseases in rapidly developing low- and middle-income countries such as India¹. The average dietary fiber intake is below the recommended levels, and the World Health Organization estimates that the incidence of obesity has increased globally in the past decade. Many individuals do not consume adequate fiber to meet recommended intakes, and obese women often report lower dietary fiber consumption compared with normal-weight individuals. ²
Dietary fiber plays an important role in appetite regulation and weight management. Fiber-rich foods promote satiety and reduce hunger by delaying gastric emptying and increasing stomach fullness.³ These effects are particularly evident among individuals with obesity.⁴ In addition, dietary fiber consumption promotes the growth of beneficial bacteria in the colon, which may help prevent obesity, metabolic syndrome, and adverse intestinal changes.⁵
High-fiber diets are associated with improved health outcomes and a reduced risk of several chronic diseases. Fiber-rich foods typically have lower energy density and can replace high-fat, energy-dense foods in the diet. Increased dietary fiber intake has been linked with improvements in serum lipoproteins, blood pressure, blood glucose control, and body weight. Individuals consuming adequate fiber are at lower risk of coronary artery disease, stroke, hypertension, diabetes, obesity, and gastrointestinal disorders. In addition, soluble fiber intake has been shown to enhance immune function. ⁶
Dietary fiber obtained from fruits, vegetables, legumes, and whole grains provides several physiological benefits and is associated with a lower risk of chronic diseases such as cardiovascular disease, type 2 diabetes mellitus, obesity, and certain cancers. These foods also provide micronutrients and phytochemicals that contribute to overall health, highlighting the importance of promoting adequate dietary fiber intake in the population.⁷
However, limited research has examined the role of dietary fiber specifically in the treatment and management of obesity, and further studies are required to strengthen the evidence linking dietary fiber intake with obesity-related outcomes.⁸ Dietary fiber also promotes the growth of beneficial gut bacteria and supports microbial balance. Increased consumption of dietary fiber and whole grains enhances the growth of beneficial intestinal microbiota, which may be particularly relevant in individuals with obesity and other metabolic disorders. However, these effects may vary depending on the type, structure, and composition of the fiber and whole-grain sources.⁹
High-fiber foods are more satiating and contribute to appetite control by influencing gastric emptying, reducing food intake, and promoting a sense of fullness.¹⁰ Fermentation of dietary fiber in the colon produces short-chain fatty acids that regulate appetite through gut hormones such as cholecystokinin and glucagon-like peptides, which help reduce hunger and increase satiety.¹¹ Increased chewing and gastric distension associated with fiber-rich foods may further enhance satiety and regulate food intake.¹²
This study focuses on weight reduction through increased dietary fiber consumption. According to the Indian Council of Medical Research and National Institute of Nutrition guidelines, the recommended dietary fiber intake is 40 g per 2000 kcal of energy intake.¹³ Increasing dietary fiber consumption to recommended levels may support weight management and improve overall metabolic health.
Discussion
Evidence on the association between dietary fiber intake and metabolic outcomes among overweight and obese middle-aged women in India remains limited. This study aimed to examine whether increased dietary fiber intake can improve insulin resistance, body composition, and weight in this population. Dietary fiber provides several metabolic benefits, including enhanced satiety, improved glycemic control, reduced cholesterol levels, and increased fat oxidation. By lowering energy intake and supporting metabolic regulation, adequate fiber consumption may contribute to effective weight management. In addition to dietary intervention, participants in the intervention group received regular dietary counseling, which may have improved adherence to the recommended dietary practices and encouraged healthier lifestyle behaviors. Therefore, the observed improvements in metabolic indicators and body composition may reflect the combined influence of increased dietary fiber intake and the supportive role of counseling in promoting sustained dietary and behavioral changes.

Present the sample size calculation formula in a clearer and more legible format, ensuring that readers can easily follow the computation steps.
Sample Size Calculation
The sample size was calculated using the following formula:
n=(2(Z_(1-α/2)+Z_(1-β) )^2 σ^2 [1+(m-1)ρ])/(md^2 )

Where:
            n = sample size per group
            Z₁₋α/₂ = 1.96 (for α = 0.05, two-tailed test)
            Z₁₋β = 0.84 (for 80% statistical power)
            σ = anticipated population standard deviation of the outcome variable
            d = clinically significant difference (effect size)
            m = number of time points/follow-ups (m = 2)
            ρ = intraclass correlation coefficient (ρ = 0.4)
Computation for BMI
Parameters used:
            σ = 3.96
            d = 1.5
            m = 2
            ρ = 0.4
Step 1: Substitute values into the formula
n=(2(1.96+0.84)^2 (3.96)^2 [1+(2-1)×0.4])/(2(1.5)^2 )
Step 2: Simplify
n=(2(2.8)^2 (15.68)(1.4))/(2(2.25))
Step 3: Final estimate
n≈77" participants per group"
Adjustment for 15% dropout rate:
n=77/(1-0.15)=90
Therefore, 90 participants per group were required.

Computation for Insulin Resistance
Parameters used:
            σ = 5.06
            d = 2
            m = 2
            ρ = 0.4
Step 1: Substitute values
n=(2(1.96+0.84)^2 (5.06)^2 [1+(2-1)×0.4])/(2(2)^2 )
Step 2: Simplify
n=(2(2.8)^2 (25.60)(1.4))/(2(4))
Step 3: Final estimate
n≈71" participants per group"
Adjustment for 15% dropout rate:
n=71/(1-0.15)=83
Thus, 83 participants per group were required.

Include a detailed adherence analysis plan, such as a checklist or monitoring tool to assess actual fiber consumption and compliance with the dietary recommendations.
Women with no contraindications to high dietary fiber consumption and abnormal HOMA-IR will be included in Phase 2 of the study. Baseline assessments will be conducted for both intervention and control groups. Demographic information including age, religion, place of residence, type of family, number of family members, marital status, education, occupation, and income will be collected using a structured proforma. Anthropometric measurements such as height (stadiometer), body weight (weighing scale), and waist and hip circumference will be recorded in the outpatient department. Biochemical parameters including fasting blood glucose (hexokinase method), HbA1c (TINA method), serum insulin (ECLIA), and lipid profile (triglycerides GPO Trinder method, HDL direct homogeneous method, LDL enzymatic method, and total cholesterol CE-CHOD-POD method) will be assessed. Dietary intake will be assessed using a 24-hour dietary recall and a Food Frequency Questionnaire (FFQ), and nutrient intake will be analyzed using DietCal software version 6.3. Adherence to dietary fiber intervention will be monitored using multiple strategies, including a tracking sheet to record daily intake of fiber-rich foods and a fiber intake compliance checklist during follow-up visits. Monthly telephonic follow-ups will be conducted to reinforce dietary counseling, evaluate adherence to the recommended dietary practices, and address any challenges faced by participants. Participants’ feedback on high-fiber food consumption will also be documented to identify adherence patterns and potential barriers, ensuring systematic monitoring of dietary fiber intake and compliance with the intervention throughout the study period. Physical activity levels will be assessed using the Global Physical Activity Questionnaire (GPAQ), and body composition parameters including visceral fat, subcutaneous fat, and muscle mass will be measured using a body fat analyzer. Clinical assessment will also be performed to document physical complaints reported by participants.


Consider incorporating measures of gut microbiota, since the study rationale emphasizes the role of fiber in modulating intestinal bacteria and metabolic health
Although dietary fiber is known to influence metabolic health through modulation of gut microbiota, gut microbial composition was not assessed in this study, which primarily focused on clinical and metabolic outcomes such as insulin resistance, body composition, and weight. Future studies incorporating microbiome analysis may provide better insight into the mechanisms linking dietary fiber intake with metabolic health
Competing Interests: No Close
Report a concern
Respond or Comment

COMMENTS ON THIS REPORT

Author Response 08 Apr 2026

Suvarna Hebbar, Clinical Nutrition and Dietetics, Manipal College of Health Professions, Manipal., 576104, India

08 Apr 2026

Author Response

Reduce redundancy in the introduction and discussion to improve readability and maintain focus.
Background
Obesity is a major public health concern worldwide. Urbanization, economic growth, changing lifestyles, and dietary habits ... Continue reading Reduce redundancy in the introduction and discussion to improve readability and maintain focus.
Background
Obesity is a major public health concern worldwide. Urbanization, economic growth, changing lifestyles, and dietary habits have contributed to a “double burden” of diseases in rapidly developing low- and middle-income countries such as India¹. The average dietary fiber intake is below the recommended levels, and the World Health Organization estimates that the incidence of obesity has increased globally in the past decade. Many individuals do not consume adequate fiber to meet recommended intakes, and obese women often report lower dietary fiber consumption compared with normal-weight individuals. ²
Dietary fiber plays an important role in appetite regulation and weight management. Fiber-rich foods promote satiety and reduce hunger by delaying gastric emptying and increasing stomach fullness.³ These effects are particularly evident among individuals with obesity.⁴ In addition, dietary fiber consumption promotes the growth of beneficial bacteria in the colon, which may help prevent obesity, metabolic syndrome, and adverse intestinal changes.⁵
High-fiber diets are associated with improved health outcomes and a reduced risk of several chronic diseases. Fiber-rich foods typically have lower energy density and can replace high-fat, energy-dense foods in the diet. Increased dietary fiber intake has been linked with improvements in serum lipoproteins, blood pressure, blood glucose control, and body weight. Individuals consuming adequate fiber are at lower risk of coronary artery disease, stroke, hypertension, diabetes, obesity, and gastrointestinal disorders. In addition, soluble fiber intake has been shown to enhance immune function. ⁶
Dietary fiber obtained from fruits, vegetables, legumes, and whole grains provides several physiological benefits and is associated with a lower risk of chronic diseases such as cardiovascular disease, type 2 diabetes mellitus, obesity, and certain cancers. These foods also provide micronutrients and phytochemicals that contribute to overall health, highlighting the importance of promoting adequate dietary fiber intake in the population.⁷
However, limited research has examined the role of dietary fiber specifically in the treatment and management of obesity, and further studies are required to strengthen the evidence linking dietary fiber intake with obesity-related outcomes.⁸ Dietary fiber also promotes the growth of beneficial gut bacteria and supports microbial balance. Increased consumption of dietary fiber and whole grains enhances the growth of beneficial intestinal microbiota, which may be particularly relevant in individuals with obesity and other metabolic disorders. However, these effects may vary depending on the type, structure, and composition of the fiber and whole-grain sources.⁹
High-fiber foods are more satiating and contribute to appetite control by influencing gastric emptying, reducing food intake, and promoting a sense of fullness.¹⁰ Fermentation of dietary fiber in the colon produces short-chain fatty acids that regulate appetite through gut hormones such as cholecystokinin and glucagon-like peptides, which help reduce hunger and increase satiety.¹¹ Increased chewing and gastric distension associated with fiber-rich foods may further enhance satiety and regulate food intake.¹²
This study focuses on weight reduction through increased dietary fiber consumption. According to the Indian Council of Medical Research and National Institute of Nutrition guidelines, the recommended dietary fiber intake is 40 g per 2000 kcal of energy intake.¹³ Increasing dietary fiber consumption to recommended levels may support weight management and improve overall metabolic health.
Discussion
Evidence on the association between dietary fiber intake and metabolic outcomes among overweight and obese middle-aged women in India remains limited. This study aimed to examine whether increased dietary fiber intake can improve insulin resistance, body composition, and weight in this population. Dietary fiber provides several metabolic benefits, including enhanced satiety, improved glycemic control, reduced cholesterol levels, and increased fat oxidation. By lowering energy intake and supporting metabolic regulation, adequate fiber consumption may contribute to effective weight management. In addition to dietary intervention, participants in the intervention group received regular dietary counseling, which may have improved adherence to the recommended dietary practices and encouraged healthier lifestyle behaviors. Therefore, the observed improvements in metabolic indicators and body composition may reflect the combined influence of increased dietary fiber intake and the supportive role of counseling in promoting sustained dietary and behavioral changes.

Present the sample size calculation formula in a clearer and more legible format, ensuring that readers can easily follow the computation steps.
Sample Size Calculation
The sample size was calculated using the following formula:
n=(2(Z_(1-α/2)+Z_(1-β) )^2 σ^2 [1+(m-1)ρ])/(md^2 )

Where:
            n = sample size per group
            Z₁₋α/₂ = 1.96 (for α = 0.05, two-tailed test)
            Z₁₋β = 0.84 (for 80% statistical power)
            σ = anticipated population standard deviation of the outcome variable
            d = clinically significant difference (effect size)
            m = number of time points/follow-ups (m = 2)
            ρ = intraclass correlation coefficient (ρ = 0.4)
Computation for BMI
Parameters used:
            σ = 3.96
            d = 1.5
            m = 2
            ρ = 0.4
Step 1: Substitute values into the formula
n=(2(1.96+0.84)^2 (3.96)^2 [1+(2-1)×0.4])/(2(1.5)^2 )
Step 2: Simplify
n=(2(2.8)^2 (15.68)(1.4))/(2(2.25))
Step 3: Final estimate
n≈77" participants per group"
Adjustment for 15% dropout rate:
n=77/(1-0.15)=90
Therefore, 90 participants per group were required.

Computation for Insulin Resistance
Parameters used:
            σ = 5.06
            d = 2
            m = 2
            ρ = 0.4
Step 1: Substitute values
n=(2(1.96+0.84)^2 (5.06)^2 [1+(2-1)×0.4])/(2(2)^2 )
Step 2: Simplify
n=(2(2.8)^2 (25.60)(1.4))/(2(4))
Step 3: Final estimate
n≈71" participants per group"
Adjustment for 15% dropout rate:
n=71/(1-0.15)=83
Thus, 83 participants per group were required.

Include a detailed adherence analysis plan, such as a checklist or monitoring tool to assess actual fiber consumption and compliance with the dietary recommendations.
Women with no contraindications to high dietary fiber consumption and abnormal HOMA-IR will be included in Phase 2 of the study. Baseline assessments will be conducted for both intervention and control groups. Demographic information including age, religion, place of residence, type of family, number of family members, marital status, education, occupation, and income will be collected using a structured proforma. Anthropometric measurements such as height (stadiometer), body weight (weighing scale), and waist and hip circumference will be recorded in the outpatient department. Biochemical parameters including fasting blood glucose (hexokinase method), HbA1c (TINA method), serum insulin (ECLIA), and lipid profile (triglycerides GPO Trinder method, HDL direct homogeneous method, LDL enzymatic method, and total cholesterol CE-CHOD-POD method) will be assessed. Dietary intake will be assessed using a 24-hour dietary recall and a Food Frequency Questionnaire (FFQ), and nutrient intake will be analyzed using DietCal software version 6.3. Adherence to dietary fiber intervention will be monitored using multiple strategies, including a tracking sheet to record daily intake of fiber-rich foods and a fiber intake compliance checklist during follow-up visits. Monthly telephonic follow-ups will be conducted to reinforce dietary counseling, evaluate adherence to the recommended dietary practices, and address any challenges faced by participants. Participants’ feedback on high-fiber food consumption will also be documented to identify adherence patterns and potential barriers, ensuring systematic monitoring of dietary fiber intake and compliance with the intervention throughout the study period. Physical activity levels will be assessed using the Global Physical Activity Questionnaire (GPAQ), and body composition parameters including visceral fat, subcutaneous fat, and muscle mass will be measured using a body fat analyzer. Clinical assessment will also be performed to document physical complaints reported by participants.


Consider incorporating measures of gut microbiota, since the study rationale emphasizes the role of fiber in modulating intestinal bacteria and metabolic health
Although dietary fiber is known to influence metabolic health through modulation of gut microbiota, gut microbial composition was not assessed in this study, which primarily focused on clinical and metabolic outcomes such as insulin resistance, body composition, and weight. Future studies incorporating microbiome analysis may provide better insight into the mechanisms linking dietary fiber intake with metabolic health
Reduce redundancy in the introduction and discussion to improve readability and maintain focus.
Background
Obesity is a major public health concern worldwide. Urbanization, economic growth, changing lifestyles, and dietary habits have contributed to a “double burden” of diseases in rapidly developing low- and middle-income countries such as India¹. The average dietary fiber intake is below the recommended levels, and the World Health Organization estimates that the incidence of obesity has increased globally in the past decade. Many individuals do not consume adequate fiber to meet recommended intakes, and obese women often report lower dietary fiber consumption compared with normal-weight individuals. ²
Dietary fiber plays an important role in appetite regulation and weight management. Fiber-rich foods promote satiety and reduce hunger by delaying gastric emptying and increasing stomach fullness.³ These effects are particularly evident among individuals with obesity.⁴ In addition, dietary fiber consumption promotes the growth of beneficial bacteria in the colon, which may help prevent obesity, metabolic syndrome, and adverse intestinal changes.⁵
High-fiber diets are associated with improved health outcomes and a reduced risk of several chronic diseases. Fiber-rich foods typically have lower energy density and can replace high-fat, energy-dense foods in the diet. Increased dietary fiber intake has been linked with improvements in serum lipoproteins, blood pressure, blood glucose control, and body weight. Individuals consuming adequate fiber are at lower risk of coronary artery disease, stroke, hypertension, diabetes, obesity, and gastrointestinal disorders. In addition, soluble fiber intake has been shown to enhance immune function. ⁶
Dietary fiber obtained from fruits, vegetables, legumes, and whole grains provides several physiological benefits and is associated with a lower risk of chronic diseases such as cardiovascular disease, type 2 diabetes mellitus, obesity, and certain cancers. These foods also provide micronutrients and phytochemicals that contribute to overall health, highlighting the importance of promoting adequate dietary fiber intake in the population.⁷
However, limited research has examined the role of dietary fiber specifically in the treatment and management of obesity, and further studies are required to strengthen the evidence linking dietary fiber intake with obesity-related outcomes.⁸ Dietary fiber also promotes the growth of beneficial gut bacteria and supports microbial balance. Increased consumption of dietary fiber and whole grains enhances the growth of beneficial intestinal microbiota, which may be particularly relevant in individuals with obesity and other metabolic disorders. However, these effects may vary depending on the type, structure, and composition of the fiber and whole-grain sources.⁹
High-fiber foods are more satiating and contribute to appetite control by influencing gastric emptying, reducing food intake, and promoting a sense of fullness.¹⁰ Fermentation of dietary fiber in the colon produces short-chain fatty acids that regulate appetite through gut hormones such as cholecystokinin and glucagon-like peptides, which help reduce hunger and increase satiety.¹¹ Increased chewing and gastric distension associated with fiber-rich foods may further enhance satiety and regulate food intake.¹²
This study focuses on weight reduction through increased dietary fiber consumption. According to the Indian Council of Medical Research and National Institute of Nutrition guidelines, the recommended dietary fiber intake is 40 g per 2000 kcal of energy intake.¹³ Increasing dietary fiber consumption to recommended levels may support weight management and improve overall metabolic health.
Discussion
Evidence on the association between dietary fiber intake and metabolic outcomes among overweight and obese middle-aged women in India remains limited. This study aimed to examine whether increased dietary fiber intake can improve insulin resistance, body composition, and weight in this population. Dietary fiber provides several metabolic benefits, including enhanced satiety, improved glycemic control, reduced cholesterol levels, and increased fat oxidation. By lowering energy intake and supporting metabolic regulation, adequate fiber consumption may contribute to effective weight management. In addition to dietary intervention, participants in the intervention group received regular dietary counseling, which may have improved adherence to the recommended dietary practices and encouraged healthier lifestyle behaviors. Therefore, the observed improvements in metabolic indicators and body composition may reflect the combined influence of increased dietary fiber intake and the supportive role of counseling in promoting sustained dietary and behavioral changes.

Present the sample size calculation formula in a clearer and more legible format, ensuring that readers can easily follow the computation steps.
Sample Size Calculation
The sample size was calculated using the following formula:
n=(2(Z_(1-α/2)+Z_(1-β) )^2 σ^2 [1+(m-1)ρ])/(md^2 )

Where:
            n = sample size per group
            Z₁₋α/₂ = 1.96 (for α = 0.05, two-tailed test)
            Z₁₋β = 0.84 (for 80% statistical power)
            σ = anticipated population standard deviation of the outcome variable
            d = clinically significant difference (effect size)
            m = number of time points/follow-ups (m = 2)
            ρ = intraclass correlation coefficient (ρ = 0.4)
Computation for BMI
Parameters used:
            σ = 3.96
            d = 1.5
            m = 2
            ρ = 0.4
Step 1: Substitute values into the formula
n=(2(1.96+0.84)^2 (3.96)^2 [1+(2-1)×0.4])/(2(1.5)^2 )
Step 2: Simplify
n=(2(2.8)^2 (15.68)(1.4))/(2(2.25))
Step 3: Final estimate
n≈77" participants per group"
Adjustment for 15% dropout rate:
n=77/(1-0.15)=90
Therefore, 90 participants per group were required.

Computation for Insulin Resistance
Parameters used:
            σ = 5.06
            d = 2
            m = 2
            ρ = 0.4
Step 1: Substitute values
n=(2(1.96+0.84)^2 (5.06)^2 [1+(2-1)×0.4])/(2(2)^2 )
Step 2: Simplify
n=(2(2.8)^2 (25.60)(1.4))/(2(4))
Step 3: Final estimate
n≈71" participants per group"
Adjustment for 15% dropout rate:
n=71/(1-0.15)=83
Thus, 83 participants per group were required.

Include a detailed adherence analysis plan, such as a checklist or monitoring tool to assess actual fiber consumption and compliance with the dietary recommendations.
Women with no contraindications to high dietary fiber consumption and abnormal HOMA-IR will be included in Phase 2 of the study. Baseline assessments will be conducted for both intervention and control groups. Demographic information including age, religion, place of residence, type of family, number of family members, marital status, education, occupation, and income will be collected using a structured proforma. Anthropometric measurements such as height (stadiometer), body weight (weighing scale), and waist and hip circumference will be recorded in the outpatient department. Biochemical parameters including fasting blood glucose (hexokinase method), HbA1c (TINA method), serum insulin (ECLIA), and lipid profile (triglycerides GPO Trinder method, HDL direct homogeneous method, LDL enzymatic method, and total cholesterol CE-CHOD-POD method) will be assessed. Dietary intake will be assessed using a 24-hour dietary recall and a Food Frequency Questionnaire (FFQ), and nutrient intake will be analyzed using DietCal software version 6.3. Adherence to dietary fiber intervention will be monitored using multiple strategies, including a tracking sheet to record daily intake of fiber-rich foods and a fiber intake compliance checklist during follow-up visits. Monthly telephonic follow-ups will be conducted to reinforce dietary counseling, evaluate adherence to the recommended dietary practices, and address any challenges faced by participants. Participants’ feedback on high-fiber food consumption will also be documented to identify adherence patterns and potential barriers, ensuring systematic monitoring of dietary fiber intake and compliance with the intervention throughout the study period. Physical activity levels will be assessed using the Global Physical Activity Questionnaire (GPAQ), and body composition parameters including visceral fat, subcutaneous fat, and muscle mass will be measured using a body fat analyzer. Clinical assessment will also be performed to document physical complaints reported by participants.


Consider incorporating measures of gut microbiota, since the study rationale emphasizes the role of fiber in modulating intestinal bacteria and metabolic health
Although dietary fiber is known to influence metabolic health through modulation of gut microbiota, gut microbial composition was not assessed in this study, which primarily focused on clinical and metabolic outcomes such as insulin resistance, body composition, and weight. Future studies incorporating microbiome analysis may provide better insight into the mechanisms linking dietary fiber intake with metabolic health
Competing Interests: No Close
Report a concern

Version 2

VERSION 2

PUBLISHED 27 Oct 2025

Revised

Views

Reviewer Report 11 Dec 2025

Hendriek C Boshuizen, Wageningen University and Research, Wageningen, The Netherlands

Not Approved

https://doi.org/10.5256/f1000research.188848.r430536

This is a protocol of a trial comparing a group that will be motivated to eat a high fiber diet to a control group that is not motivated to do so, but only receives information on the benefits of eating fiber. This is a worthwhile endeavor that I fully support. However, the way the protocol has been written down can be improved and the sample size calculation needs correction. Below some points that were not clear to me, or where I have questions regarding the methodology not answered by the protocol.

The second secondary objective is not specific enough. Opinion on what?
In phase 1 I have doubt whether a single 24 hour recall is adequate to determine usual intake. I wonder whether a food frequency questionnaire designed for measuring fiber intake would not be more suitable. Is there evidence to support that a single 24 hour recall gives a sufficiently accurate estimate of usual intake of fiber?
Are 500 participants in phase 1 enough to provide 180 participants who agree to being randomized in phase 2? This is not explained clearly.
It is not clear to me what is meant by “The sample size was calculated in accordance with insulin resistance and BMI.” Please give more details on the sample size calculation. What input was used? What sample size calculation method?

Phase 2:

The information on the sample size calculation is not complete: two essential parameters for the sample size calculations are s = anticipated population standard deviation of the outcome variable and d = clinically significant difference. The authors do not provide the values they used for these parameters, nor do they justify why the choice for this d and s was made. The sample size formula given cannot be correct and is also not formatted correctly (s2 instead of s²).
I understand the difference in fiber intake between control and treatment groups was changed from 20 g/day to 15 g/day in this new version of the protocol. However, the sample size did not change, while I would expect that a higher sample size would be needed as the effect (d) would be lower with a smaller difference.
In regard to the methodology of phase 2: why are the follow-up measurement on day 180 is not done for the control group? This could be explained better.

Apart from these points, the writing can be improved.
The introduction needs structuring and a complete rewrite. Now a series of statements is strung together without clear order. For instance, the role of the microbiome is mentioned, interspersed with statements on other aspects, giving the introduction a repetitive character. Another example is the second sentence where a statement on fiber and an unrelated statement on obesity are combined into a single sentence without the sentence making clear why they are combined. Similarly, there is the sentence “There are few studies on the utilization of dietary fiber in the treatment of obesity, but further research is required to confirm stronger associations between dietary fiber and obesity”, where “but” implies a contradiction between the first and the second part, while I don’t see the contradiction.

Parts of the protocol are not written out but only given in bullet points. I found this both strange for a paper, and also often unclear. For instance, under strength an limitations: “Good knowledge and practice regarding modified diet plans with high dietary fiber will be addressed to participants”. Knowledge of whom? Of the researcher or the participants? How will this knowledge be addresses?

Is the rationale for, and objectives of, the study clearly described?

Partly
Is the study design appropriate for the research question?

Partly
Are sufficient details of the methods provided to allow replication by others?

Partly
Are the datasets clearly presented in a useable and accessible format?

Not applicable

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Biostatistics, with nutrition as one of my focus areas

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

CITE

Report a concern

Author Response 03 Mar 2026

Suvarna Hebbar, Clinical Nutrition and Dietetics, Manipal College of Health Professions, Manipal., 576104, India

03 Mar 2026

Author Response
Response for F1000
1. The second secondary objective is not specific enough. Opinion on what?
Response: Opinion of women on modified fiber intake
1. In
... Continue reading
Response for F1000

The second secondary objective is not specific enough. Opinion on what?

Response: Opinion of women on modified fiber intake

In phase 1 I doubt whether a single 24 hour recall is adequate to determine usual intake. I wonder whether a food frequency questionnaire designed for measuring fiber intake would be more suitable. Is there evidence to support that a single 24 hour recall gives a sufficiently accurate estimate of usual intake of fiber?

Response: We sincerely appreciate the reviewer’s valuable observation. We acknowledge that a single 24-hour dietary recall may not fully capture an individual’s habitual dietary intake. However, the primary objective of the present study was to estimate the prevalence of insulin resistance among overweight and obese middle-aged women and to obtain an overview of usual dietary patterns at the population level. For this purpose, a single 24-hour recall is considered a methodologically acceptable and scientifically justified approach, as it provides a reliable estimate of mean group intake when collected from a sufficiently large and heterogeneous sample.

To minimize potential bias, participants reporting atypical or irregular dietary patterns were excluded, thereby ensuring that the recorded dietary recall reasonably reflected usual intake.

We recognize that a more detailed dietary assessment is essential for evaluating individual-level nutrient adequacy, particularly dietary fiber intake. Accordingly, in the subsequent intervention phase, we plan to implement a structured high-fiber dietary intervention combined with supportive physical activity. Dietary intake will be assessed using three non-consecutive 24-hour recalls along with a validated Food Frequency Questionnaire (FFQ) to capture habitual intake patterns more comprehensively. Physical activity will be assessed using the Global Physical Activity Questionnaire (GPAQ). This integrated approach will enable a more robust assessment of habitual diet while facilitating the evaluation of changes in insulin sensitivity and related metabolic outcomes.

Are 500 participants in phase 1 enough to provide 180 participants who agree to being randomized in phase 2? This is not explained clearly.

Response: Sample Size Justification
In Phase 1, a total of 500 overweight and obese middle-aged women will be screened to determine the prevalence of insulin resistance using HOMA-IR. Based on existing epidemiological evidence and our preliminary observational study conducted among 564 women, a high prevalence of insulin resistance is anticipated in this population. In the preliminary study, over 55% of participants were obese and approximately 20% were overweight, yielding an observed obese-to-overweight ratio of approximately 2:1.
Taking this distribution into account, along with the expected prevalence of insulin resistance and potential exclusions and non-participation in the intervention phase, a screening sample of 500 participants was considered adequate to ensure the recruitment of 180 eligible and consenting participants for Phase 2. This approach allows for appropriate representation of both overweight and obese groups in the randomized phase while maintaining sufficient statistical power for the intervention analyses.

It is not clear to me what is meant by “The sample size was calculated in accordance with insulin resistance and BMI.” Please give more details on the sample size calculation. What input was used? What sample size calculation method

Response: The sample size for Phase 2 was calculated based on two primary outcome variables insulin resistance and body mass index (BMI as these represent the key metabolic and anthropometric endpoints of the intervention. The calculation was performed using a repeated-measures ANOVA model, which is appropriate for assessing within- and between-group changes over time in randomized controlled trials.
Published intervention studies examining the effects of dietary fiber on insulin resistance and BMI were used as reference sources to determine realistic and clinically meaningful estimates of the expected standard deviation (s) and the minimum detectable difference (d) for these outcomes (references 34 and 35).

Phase 2:

The information on the sample size calculation is not complete: two essential parameters for the sample size calculations are s = anticipated population standard deviation of the outcome variable and d = clinically significant difference. The authors do not provide the values they used for these parameters, nor do they justify why the choice for this d and s was made. The sample size formula given cannot be correct and is also not formatted correctly (s2 instead of s2).

Response: Explained under the heading- sample size calculation

I understand the difference in fiber intake between control and treatment groups was changed from 20 g/day to 15 g/day in this new version of the protocol. However, the sample size did not change, while I would expect that a higher sample size would be needed as the effect (d) would be lower with a smaller difference.

Response: The sample size estimation was performed using insulin resistance and body mass index as the primary outcomes, and not dietary fiber intake. Accordingly, no modification to the sample size was required.

In regard to the methodology of phase 2: why are the follow-up measurement on day 180 is not done for the control group? This could be explained better.

Response: Its is already been done and mentioned even in flow chart.

For instance, the role of the microbiome is mentioned, interspersed with statements on other aspects, giving the introduction a repetitive character. Another example is the second sentence where a statement on fiber and an unrelated statement on obesity are combined into a single sentence without the sentence making clear why they are combined.

Response: Its rephrased in page -6

Similarly, there is the sentence “There are few studies on the utilization of dietary fiber in the treatment of obesity, but further research is required to confirm stronger associations between dietary fiber and obesity”, where “but” implies a contradiction between the first and the second part, while I don’t see the contradiction.

Response: The conjunction “but” was intentionally used to indicate a contrast between the presence of general evidence supporting the role of dietary fiber in obesity and the limited depth and scope of studies specifically addressing its utilization and strength of association. The intent was to emphasize that, despite existing evidence, further focused investigation remains necessary, which forms the basis of the present study.

Parts of the protocol are not written out but only given in bullet points. I found this both strange for a paper, and also often unclear. For instance, under strength an limitations: “Good knowledge and practice regarding modified diet plans with high dietary fiber will be addressed to participants”. Knowledge of whom? Of the researcher or the participants? How will this knowledge be addresses?

Response: Strengths and limitations: The study is expected to demonstrate improvements in insulin resistance, body composition, and body weight among participants with higher dietary fiber intake. Participants will receive structured guidance on modified high-fiber diet plans, which is intended to improve their knowledge and dietary practices, as well as to identify barriers and challenges related to sustained fiber consumption. Potential limitations include participant dropout due to dietary non-compliance, variability in long-term adherence to the prescribed diet, and limited generalizability due to hospital-based recruitment and resource constraints.
Response for F1000

The second secondary objective is not specific enough. Opinion on what?

Response: Opinion of women on modified fiber intake

In phase 1 I doubt whether a single 24 hour recall is adequate to determine usual intake. I wonder whether a food frequency questionnaire designed for measuring fiber intake would be more suitable. Is there evidence to support that a single 24 hour recall gives a sufficiently accurate estimate of usual intake of fiber?

Response: We sincerely appreciate the reviewer’s valuable observation. We acknowledge that a single 24-hour dietary recall may not fully capture an individual’s habitual dietary intake. However, the primary objective of the present study was to estimate the prevalence of insulin resistance among overweight and obese middle-aged women and to obtain an overview of usual dietary patterns at the population level. For this purpose, a single 24-hour recall is considered a methodologically acceptable and scientifically justified approach, as it provides a reliable estimate of mean group intake when collected from a sufficiently large and heterogeneous sample.

To minimize potential bias, participants reporting atypical or irregular dietary patterns were excluded, thereby ensuring that the recorded dietary recall reasonably reflected usual intake.

We recognize that a more detailed dietary assessment is essential for evaluating individual-level nutrient adequacy, particularly dietary fiber intake. Accordingly, in the subsequent intervention phase, we plan to implement a structured high-fiber dietary intervention combined with supportive physical activity. Dietary intake will be assessed using three non-consecutive 24-hour recalls along with a validated Food Frequency Questionnaire (FFQ) to capture habitual intake patterns more comprehensively. Physical activity will be assessed using the Global Physical Activity Questionnaire (GPAQ). This integrated approach will enable a more robust assessment of habitual diet while facilitating the evaluation of changes in insulin sensitivity and related metabolic outcomes.

Are 500 participants in phase 1 enough to provide 180 participants who agree to being randomized in phase 2? This is not explained clearly.

Response: Sample Size Justification
In Phase 1, a total of 500 overweight and obese middle-aged women will be screened to determine the prevalence of insulin resistance using HOMA-IR. Based on existing epidemiological evidence and our preliminary observational study conducted among 564 women, a high prevalence of insulin resistance is anticipated in this population. In the preliminary study, over 55% of participants were obese and approximately 20% were overweight, yielding an observed obese-to-overweight ratio of approximately 2:1.
Taking this distribution into account, along with the expected prevalence of insulin resistance and potential exclusions and non-participation in the intervention phase, a screening sample of 500 participants was considered adequate to ensure the recruitment of 180 eligible and consenting participants for Phase 2. This approach allows for appropriate representation of both overweight and obese groups in the randomized phase while maintaining sufficient statistical power for the intervention analyses.

It is not clear to me what is meant by “The sample size was calculated in accordance with insulin resistance and BMI.” Please give more details on the sample size calculation. What input was used? What sample size calculation method

Response: The sample size for Phase 2 was calculated based on two primary outcome variables insulin resistance and body mass index (BMI as these represent the key metabolic and anthropometric endpoints of the intervention. The calculation was performed using a repeated-measures ANOVA model, which is appropriate for assessing within- and between-group changes over time in randomized controlled trials.
Published intervention studies examining the effects of dietary fiber on insulin resistance and BMI were used as reference sources to determine realistic and clinically meaningful estimates of the expected standard deviation (s) and the minimum detectable difference (d) for these outcomes (references 34 and 35).

Phase 2:

The information on the sample size calculation is not complete: two essential parameters for the sample size calculations are s = anticipated population standard deviation of the outcome variable and d = clinically significant difference. The authors do not provide the values they used for these parameters, nor do they justify why the choice for this d and s was made. The sample size formula given cannot be correct and is also not formatted correctly (s2 instead of s2).

Response: Explained under the heading- sample size calculation

I understand the difference in fiber intake between control and treatment groups was changed from 20 g/day to 15 g/day in this new version of the protocol. However, the sample size did not change, while I would expect that a higher sample size would be needed as the effect (d) would be lower with a smaller difference.

Response: The sample size estimation was performed using insulin resistance and body mass index as the primary outcomes, and not dietary fiber intake. Accordingly, no modification to the sample size was required.

In regard to the methodology of phase 2: why are the follow-up measurement on day 180 is not done for the control group? This could be explained better.

Response: Its is already been done and mentioned even in flow chart.

For instance, the role of the microbiome is mentioned, interspersed with statements on other aspects, giving the introduction a repetitive character. Another example is the second sentence where a statement on fiber and an unrelated statement on obesity are combined into a single sentence without the sentence making clear why they are combined.

Response: Its rephrased in page -6

Similarly, there is the sentence “There are few studies on the utilization of dietary fiber in the treatment of obesity, but further research is required to confirm stronger associations between dietary fiber and obesity”, where “but” implies a contradiction between the first and the second part, while I don’t see the contradiction.

Response: The conjunction “but” was intentionally used to indicate a contrast between the presence of general evidence supporting the role of dietary fiber in obesity and the limited depth and scope of studies specifically addressing its utilization and strength of association. The intent was to emphasize that, despite existing evidence, further focused investigation remains necessary, which forms the basis of the present study.

Parts of the protocol are not written out but only given in bullet points. I found this both strange for a paper, and also often unclear. For instance, under strength an limitations: “Good knowledge and practice regarding modified diet plans with high dietary fiber will be addressed to participants”. Knowledge of whom? Of the researcher or the participants? How will this knowledge be addresses?

Response: Strengths and limitations: The study is expected to demonstrate improvements in insulin resistance, body composition, and body weight among participants with higher dietary fiber intake. Participants will receive structured guidance on modified high-fiber diet plans, which is intended to improve their knowledge and dietary practices, as well as to identify barriers and challenges related to sustained fiber consumption. Potential limitations include participant dropout due to dietary non-compliance, variability in long-term adherence to the prescribed diet, and limited generalizability due to hospital-based recruitment and resource constraints.
Competing Interests: No competing interests were disclosed. Close
Report a concern
Respond or Comment

COMMENTS ON THIS REPORT

Author Response 03 Mar 2026

Suvarna Hebbar, Clinical Nutrition and Dietetics, Manipal College of Health Professions, Manipal., 576104, India

03 Mar 2026

Author Response
Response for F1000
1. The second secondary objective is not specific enough. Opinion on what?
Response: Opinion of women on modified fiber intake
1. In
... Continue reading
Response for F1000

The second secondary objective is not specific enough. Opinion on what?

Response: Opinion of women on modified fiber intake

In phase 1 I doubt whether a single 24 hour recall is adequate to determine usual intake. I wonder whether a food frequency questionnaire designed for measuring fiber intake would be more suitable. Is there evidence to support that a single 24 hour recall gives a sufficiently accurate estimate of usual intake of fiber?

Response: We sincerely appreciate the reviewer’s valuable observation. We acknowledge that a single 24-hour dietary recall may not fully capture an individual’s habitual dietary intake. However, the primary objective of the present study was to estimate the prevalence of insulin resistance among overweight and obese middle-aged women and to obtain an overview of usual dietary patterns at the population level. For this purpose, a single 24-hour recall is considered a methodologically acceptable and scientifically justified approach, as it provides a reliable estimate of mean group intake when collected from a sufficiently large and heterogeneous sample.

To minimize potential bias, participants reporting atypical or irregular dietary patterns were excluded, thereby ensuring that the recorded dietary recall reasonably reflected usual intake.

We recognize that a more detailed dietary assessment is essential for evaluating individual-level nutrient adequacy, particularly dietary fiber intake. Accordingly, in the subsequent intervention phase, we plan to implement a structured high-fiber dietary intervention combined with supportive physical activity. Dietary intake will be assessed using three non-consecutive 24-hour recalls along with a validated Food Frequency Questionnaire (FFQ) to capture habitual intake patterns more comprehensively. Physical activity will be assessed using the Global Physical Activity Questionnaire (GPAQ). This integrated approach will enable a more robust assessment of habitual diet while facilitating the evaluation of changes in insulin sensitivity and related metabolic outcomes.

Are 500 participants in phase 1 enough to provide 180 participants who agree to being randomized in phase 2? This is not explained clearly.

Response: Sample Size Justification
In Phase 1, a total of 500 overweight and obese middle-aged women will be screened to determine the prevalence of insulin resistance using HOMA-IR. Based on existing epidemiological evidence and our preliminary observational study conducted among 564 women, a high prevalence of insulin resistance is anticipated in this population. In the preliminary study, over 55% of participants were obese and approximately 20% were overweight, yielding an observed obese-to-overweight ratio of approximately 2:1.
Taking this distribution into account, along with the expected prevalence of insulin resistance and potential exclusions and non-participation in the intervention phase, a screening sample of 500 participants was considered adequate to ensure the recruitment of 180 eligible and consenting participants for Phase 2. This approach allows for appropriate representation of both overweight and obese groups in the randomized phase while maintaining sufficient statistical power for the intervention analyses.

It is not clear to me what is meant by “The sample size was calculated in accordance with insulin resistance and BMI.” Please give more details on the sample size calculation. What input was used? What sample size calculation method

Response: The sample size for Phase 2 was calculated based on two primary outcome variables insulin resistance and body mass index (BMI as these represent the key metabolic and anthropometric endpoints of the intervention. The calculation was performed using a repeated-measures ANOVA model, which is appropriate for assessing within- and between-group changes over time in randomized controlled trials.
Published intervention studies examining the effects of dietary fiber on insulin resistance and BMI were used as reference sources to determine realistic and clinically meaningful estimates of the expected standard deviation (s) and the minimum detectable difference (d) for these outcomes (references 34 and 35).

Phase 2:

The information on the sample size calculation is not complete: two essential parameters for the sample size calculations are s = anticipated population standard deviation of the outcome variable and d = clinically significant difference. The authors do not provide the values they used for these parameters, nor do they justify why the choice for this d and s was made. The sample size formula given cannot be correct and is also not formatted correctly (s2 instead of s2).

Response: Explained under the heading- sample size calculation

I understand the difference in fiber intake between control and treatment groups was changed from 20 g/day to 15 g/day in this new version of the protocol. However, the sample size did not change, while I would expect that a higher sample size would be needed as the effect (d) would be lower with a smaller difference.

Response: The sample size estimation was performed using insulin resistance and body mass index as the primary outcomes, and not dietary fiber intake. Accordingly, no modification to the sample size was required.

In regard to the methodology of phase 2: why are the follow-up measurement on day 180 is not done for the control group? This could be explained better.

Response: Its is already been done and mentioned even in flow chart.

For instance, the role of the microbiome is mentioned, interspersed with statements on other aspects, giving the introduction a repetitive character. Another example is the second sentence where a statement on fiber and an unrelated statement on obesity are combined into a single sentence without the sentence making clear why they are combined.

Response: Its rephrased in page -6

Similarly, there is the sentence “There are few studies on the utilization of dietary fiber in the treatment of obesity, but further research is required to confirm stronger associations between dietary fiber and obesity”, where “but” implies a contradiction between the first and the second part, while I don’t see the contradiction.

Response: The conjunction “but” was intentionally used to indicate a contrast between the presence of general evidence supporting the role of dietary fiber in obesity and the limited depth and scope of studies specifically addressing its utilization and strength of association. The intent was to emphasize that, despite existing evidence, further focused investigation remains necessary, which forms the basis of the present study.

Parts of the protocol are not written out but only given in bullet points. I found this both strange for a paper, and also often unclear. For instance, under strength an limitations: “Good knowledge and practice regarding modified diet plans with high dietary fiber will be addressed to participants”. Knowledge of whom? Of the researcher or the participants? How will this knowledge be addresses?

Response: Strengths and limitations: The study is expected to demonstrate improvements in insulin resistance, body composition, and body weight among participants with higher dietary fiber intake. Participants will receive structured guidance on modified high-fiber diet plans, which is intended to improve their knowledge and dietary practices, as well as to identify barriers and challenges related to sustained fiber consumption. Potential limitations include participant dropout due to dietary non-compliance, variability in long-term adherence to the prescribed diet, and limited generalizability due to hospital-based recruitment and resource constraints.
Response for F1000

The second secondary objective is not specific enough. Opinion on what?

Response: Opinion of women on modified fiber intake

In phase 1 I doubt whether a single 24 hour recall is adequate to determine usual intake. I wonder whether a food frequency questionnaire designed for measuring fiber intake would be more suitable. Is there evidence to support that a single 24 hour recall gives a sufficiently accurate estimate of usual intake of fiber?

Response: We sincerely appreciate the reviewer’s valuable observation. We acknowledge that a single 24-hour dietary recall may not fully capture an individual’s habitual dietary intake. However, the primary objective of the present study was to estimate the prevalence of insulin resistance among overweight and obese middle-aged women and to obtain an overview of usual dietary patterns at the population level. For this purpose, a single 24-hour recall is considered a methodologically acceptable and scientifically justified approach, as it provides a reliable estimate of mean group intake when collected from a sufficiently large and heterogeneous sample.

To minimize potential bias, participants reporting atypical or irregular dietary patterns were excluded, thereby ensuring that the recorded dietary recall reasonably reflected usual intake.

We recognize that a more detailed dietary assessment is essential for evaluating individual-level nutrient adequacy, particularly dietary fiber intake. Accordingly, in the subsequent intervention phase, we plan to implement a structured high-fiber dietary intervention combined with supportive physical activity. Dietary intake will be assessed using three non-consecutive 24-hour recalls along with a validated Food Frequency Questionnaire (FFQ) to capture habitual intake patterns more comprehensively. Physical activity will be assessed using the Global Physical Activity Questionnaire (GPAQ). This integrated approach will enable a more robust assessment of habitual diet while facilitating the evaluation of changes in insulin sensitivity and related metabolic outcomes.

Are 500 participants in phase 1 enough to provide 180 participants who agree to being randomized in phase 2? This is not explained clearly.

Response: Sample Size Justification
In Phase 1, a total of 500 overweight and obese middle-aged women will be screened to determine the prevalence of insulin resistance using HOMA-IR. Based on existing epidemiological evidence and our preliminary observational study conducted among 564 women, a high prevalence of insulin resistance is anticipated in this population. In the preliminary study, over 55% of participants were obese and approximately 20% were overweight, yielding an observed obese-to-overweight ratio of approximately 2:1.
Taking this distribution into account, along with the expected prevalence of insulin resistance and potential exclusions and non-participation in the intervention phase, a screening sample of 500 participants was considered adequate to ensure the recruitment of 180 eligible and consenting participants for Phase 2. This approach allows for appropriate representation of both overweight and obese groups in the randomized phase while maintaining sufficient statistical power for the intervention analyses.

It is not clear to me what is meant by “The sample size was calculated in accordance with insulin resistance and BMI.” Please give more details on the sample size calculation. What input was used? What sample size calculation method

Response: The sample size for Phase 2 was calculated based on two primary outcome variables insulin resistance and body mass index (BMI as these represent the key metabolic and anthropometric endpoints of the intervention. The calculation was performed using a repeated-measures ANOVA model, which is appropriate for assessing within- and between-group changes over time in randomized controlled trials.
Published intervention studies examining the effects of dietary fiber on insulin resistance and BMI were used as reference sources to determine realistic and clinically meaningful estimates of the expected standard deviation (s) and the minimum detectable difference (d) for these outcomes (references 34 and 35).

Phase 2:

The information on the sample size calculation is not complete: two essential parameters for the sample size calculations are s = anticipated population standard deviation of the outcome variable and d = clinically significant difference. The authors do not provide the values they used for these parameters, nor do they justify why the choice for this d and s was made. The sample size formula given cannot be correct and is also not formatted correctly (s2 instead of s2).

Response: Explained under the heading- sample size calculation

I understand the difference in fiber intake between control and treatment groups was changed from 20 g/day to 15 g/day in this new version of the protocol. However, the sample size did not change, while I would expect that a higher sample size would be needed as the effect (d) would be lower with a smaller difference.

Response: The sample size estimation was performed using insulin resistance and body mass index as the primary outcomes, and not dietary fiber intake. Accordingly, no modification to the sample size was required.

In regard to the methodology of phase 2: why are the follow-up measurement on day 180 is not done for the control group? This could be explained better.

Response: Its is already been done and mentioned even in flow chart.

For instance, the role of the microbiome is mentioned, interspersed with statements on other aspects, giving the introduction a repetitive character. Another example is the second sentence where a statement on fiber and an unrelated statement on obesity are combined into a single sentence without the sentence making clear why they are combined.

Response: Its rephrased in page -6

Similarly, there is the sentence “There are few studies on the utilization of dietary fiber in the treatment of obesity, but further research is required to confirm stronger associations between dietary fiber and obesity”, where “but” implies a contradiction between the first and the second part, while I don’t see the contradiction.

Response: The conjunction “but” was intentionally used to indicate a contrast between the presence of general evidence supporting the role of dietary fiber in obesity and the limited depth and scope of studies specifically addressing its utilization and strength of association. The intent was to emphasize that, despite existing evidence, further focused investigation remains necessary, which forms the basis of the present study.

Parts of the protocol are not written out but only given in bullet points. I found this both strange for a paper, and also often unclear. For instance, under strength an limitations: “Good knowledge and practice regarding modified diet plans with high dietary fiber will be addressed to participants”. Knowledge of whom? Of the researcher or the participants? How will this knowledge be addresses?

Response: Strengths and limitations: The study is expected to demonstrate improvements in insulin resistance, body composition, and body weight among participants with higher dietary fiber intake. Participants will receive structured guidance on modified high-fiber diet plans, which is intended to improve their knowledge and dietary practices, as well as to identify barriers and challenges related to sustained fiber consumption. Potential limitations include participant dropout due to dietary non-compliance, variability in long-term adherence to the prescribed diet, and limited generalizability due to hospital-based recruitment and resource constraints.
Competing Interests: No competing interests were disclosed. Close
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Version 1

VERSION 1

PUBLISHED 26 Apr 2024

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Reviewer Report 05 Feb 2025

Gary Frost, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, England, UK

Not Approved

https://doi.org/10.5256/f1000research.161634.r357073

I found the protocol somewhat confusing, primarily because the methods section combines both Phase 1 and Phase 2. It would be clearer if each phase were presented separately under distinct subheadings.

Including a schematic diagram of the intervention would greatly aid in understanding the different phases and how they are structured.

The rationale for expecting sex-specific differences in response to the dietary fiber intervention is unclear. Additionally, the purpose of the intervention itself needs to be better justified. Is this study specifically designed for women’s health? If so, the justification for conducting a single-sex study should be clearly articulated.

Some of the language used in the background section appears outdated and would benefit from revision. For example, terms like “roughage” should be updated to reflect current scientific terminology.

The study is described as stratified, randomized, controlled, and double-blind. However, given that the intervention involves dietary advice to achieve 40g of fiber intake compared to 20g, true double-blinding does not seem feasible. Clarification on how blinding is being implemented would be helpful. Additionally, why was a crossover design not considered, as it might have addressed some of these challenges?

There is confusion regarding the sample size. The power calculation suggests 90 participants per group, but the random allocation section mentions 60 per group. This discrepancy needs to be clarified.

The duration of the intervention is also difficult to determine. It appears to be 180 days for the intervention group, but this information is not presented clearly. Providing a concise summary of the study timeline would improve clarity.

There is limited justification for selecting a 20g difference in fiber intake between groups, as well as for the chosen length of the intervention. It would be useful to know if the research team has previously demonstrated success in increasing dietary fiber intake by 20g, as this can be challenging.

Relying solely on 24-hour dietary recalls to assess compliance is concerning, given the known limitations of this method. Are there any plans to include additional compliance measures?

Lastly, will the composition of dietary fiber (i.e., soluble vs. insoluble) be consistent across participants? The metabolic effects of these fiber types can vary significantly, and this should be addressed.

Is the rationale for, and objectives of, the study clearly described?

No
Is the study design appropriate for the research question?

Partly
Are sufficient details of the methods provided to allow replication by others?

No
Are the datasets clearly presented in a useable and accessible format?

No

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Nutrition and carbohydrate research

CITE

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Author Response 22 Mar 2025

Suvarna Hebbar, Clinical Nutrition and Dietetics, Manipal College of Health Professions, Manipal., 576104, India

22 Mar 2025

Author Response
1. Clarity in Methods Section (Phase 1 & Phase 2 Separation)
Phase 1
Objective
The primary aim of Phase 1 is to screen middle-aged overweight and obese women to determine ... Continue reading
1. Clarity in Methods Section (Phase 1 & Phase 2 Separation)
Phase 1
Objective
The primary aim of Phase 1 is to screen middle-aged overweight and obese women to determine the prevalence of insulin resistance.
Study Setting
This phase will be conducted in the Outpatient Departments (OPDs) of Medicine, Gynaecology, and Endocrinology at Kasturba Hospital, Manipal.
Sample Size & Selection

A total of 500 women will be screened to assess insulin resistance.

Participants will be categorized into two groups: overweight (BMI 23–24.9 kg/m²) and obese (BMI ≥ 25 kg/m²).

Each group will have at least 166 participants.

Inclusion Criteria

Women aged 35–55 years.

Willing to provide informed consent.

BMI ≥ 23 kg/m².

Exclusion Criteria

Women with conditions affecting nutritional status (e.g., tuberculosis, HIV, cancer, organ failure).

Women diagnosed with type 2 diabetes mellitus.

Individuals with hypertension, thyroid disorders, or any medical condition requiring medications affecting body weight (e.g., thyroxine, diuretics).

Pregnant or lactating women.

Women already on a weight-loss regime or consuming fiber above the recommended dietary allowance.

Women with contraindications for high fiber consumption (e.g., inflammatory bowel disease).

Data Collection Methods
Participants will undergo a baseline assessment, including:

Demographic Information: Age, education, occupation, income, marital history, place of residence, and family structure.

Anthropometric Measures: Height, weight, BMI, waist circumference, and hip circumference using standardized tools.

Biochemical Assessments:

Fasting blood glucose (hexokinase method).

HbA1c (TINA method).

Serum insulin (ECLIA).

Lipid profile (triglycerides, HDL, LDL, total cholesterol).

Dietary Assessment:

24-hour dietary recall and food frequency questionnaire analyzed using DietCal version 6.3.

Physical Activity Assessment:

Global Physical Activity Questionnaire (GPAQ).

Clinical Assessment: Evaluation of physical symptoms (e.g., bowel movement, satiety, leg pain, backache).

In-Depth Interviews

20 participants consuming low fiber (<20g/day) and 20 participants consuming moderate fiber (20-25g/day) will be interviewed telephonically for 45 minutes to assess barriers to fiber intake.

Phase 2: Randomized Controlled Trial (RCT)
Objective
To assess the impact of high dietary fiber intake (40g/day) on insulin resistance, body composition, and weight among overweight and obese women.
Study Design

Randomized, controlled trial.

Stratified Block Randomization (9 blocks of 20 participants each).

180 women will be randomized into:

Intervention Group (n=90): Receives 40g/day of fiber with dietary counselling.

Control Group (n=90): Receives 25g/day of fiber as part of a standard diet care plan.

Inclusion Criteria

Women from Phase 1 with abnormal HOMA-IR (>2), indicating insulin resistance.

Willing to adhere to a high-fiber diet if randomized to the intervention group.

Exclusion Criteria

Women unwilling to continue participation or adhere to the high-fiber diet.

Intervention & Control Groups
Intervention group
All women in the intervention arm will be counseled for about 15 minutes, and a customized diet chart consisting of high fiber of 40 grams will be provided. Nutritional empowerment on fiber shall be delivered to each woman enrolled. Necessary dietary advice on the modified diet plan and with a motivation to adhere to the diet plan will be communicated only to the intervention group. After the first counselling, on the 15th day, women will be telephonically assessed on their 24-hour recall dietary intake. On the 30th day, the women will be contacted telephonically again to record their 24-hour recall of their dietary intake. Necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 60th day, the women will be again telephonically contacted to record their 24-hour recall on their dietary intake, and necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat is analyzed using body fat analyzer and a questionnaire on patient opinion regarding modified diet plan shall be ass. Necessaryessed as motivation and adherence towards fiber consumption subjects will be communicated telephonically on the 135th day. From the 136th to the 180th day, there shall not be any conversation regarding dietary modifications. On the 180th day, as a compliance-checking, the women will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data .24hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat analyzed using body fat analyzer and diet compliance on the modified diet plan shall be assessed.

Control group.
Women in the control arm will get a traditional diet care plan with 25gm of fiber according to their health condition. Necessary dietary advice will be communicated to the control group on the first visit to the hospital. There shall be no telephonic communication with the control group till the 90th day. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hour dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer. On the 180th day, as a compliance-checking, the patient will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer

Data Analysis

Repeated Measures ANOVA will be used to evaluate changes in insulin resistance, body composition, and weight over time.

SPSS v16.0 will be used for statistical analysis.

Ethical Considerations

Approval obtained from the Institutional Research Committee and Institutional Ethics Committee (IEC).

Trial registered with the Clinical Trials Registry of India (CTRI/2022/01/039074).

Informed consent was obtained from all participants.

CONTROL ARM

Day 1

Traditional/standard care
(patient will be called to OPD)

Day 15
Nil

Day 30
Nil

Day 60
Nil

Day 90
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

INTERVENTION ARM

Day 1

Intervention
(patient will be called to OPD)

Customize the individual-specific diet plan
Nutritional counseling
Impart nutritional empowerment on fiber consumption
Handover of diet plan

Day 15

Reinforcement
(through telephone)

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 30

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 60

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 90

Outcome assessment
(patient will be called to OPD)
Basic data:
Tool 2: 24-hour recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Patient opinion on a modified diet
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

Day 135

Reinforcement (through telephone)

Motivation to follow a customized diet plan

Day 180

Checking compliance
(patient will be called to OPD)
Basic data:
Tool 2: 24-hour recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Compliance checklist
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

Day 135
Nil

Day180
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ

Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyser:
Visceral fat, S/C fat, muscle mass

3. Rationale for Sex-Specific Differences and Justification for a Single-Sex Study
This study is specifically designed for women’s health, as obesity and insulin resistance present distinct physiological and hormonal influences in females. The decision to focus on middle-aged women was based on prior evidence suggesting unique metabolic responses to dietary interventions in this demographic.
López, M. et al. (2016) - "Menopause, obesity, and insulin resistance: An emerging paradigm"

This study specifically explores the impact of menopause on metabolic health, highlighting the increased risk of insulin resistance and obesity in women as they transition through menopause. It aligns with your focus on middle-aged women and the unique metabolic responses they experience.

Reference: López, M. et al. "Menopause, obesity, and insulin resistance: An emerging paradigm." Endocrinology (2016).

Van Der Steeg, W. et al. (2010) - "Sex differences in insulin resistance in obesity"

This study investigates how hormonal factors, especially estrogen, affect insulin resistance and fat distribution differently in women, providing key insights into the sex-specific mechanisms that make middle-aged women particularly vulnerable to obesity and metabolic disorders.

Reference: Van Der Steeg, W. et al. "Sex differences in insulin resistance in obesity." Obesity Reviews (2010).

4. Updating Scientific Terminology in the Background Section
We appreciate the suggestion regarding outdated terminology. The term "roughage" and other obsolete language will be revised to align with current scientific terminology.
5. Clarification on Double-Blinding and Study Design
There was an error in the original study design description. This study is not a double-blind study but rather an open-ended study. This design was chosen to facilitate a deeper understanding of the real-world effects of dietary interventions on obesity and insulin resistance in middle-aged women, where factors like adherence to the intervention and participant feedback play an essential role in the analysis.

6. Sample Size Discrepancy
The final sample size of 180 participants (90 per group) was determined based on power calculations for insulin resistance and BMI, accounting for a 15% dropout rate. To ensure appropriate representation, participants were stratified based on the prevalence of obesity and overweight, maintaining a 2:1 ratio, with a higher proportion of obese individuals, as obesity is more prevalent in the target population.

7. Clarification of Study Duration
The total duration of the intervention is 180 days (6 months) for the intervention group, with structured follow-ups to ensure adherence and assess outcomes. Participants receive customized dietary counseling on Day 1, followed by reinforcement sessions via telephone on Days 15, 30, and 60 to monitor compliance and provide necessary modifications. Outcome assessments are conducted on Day 90 and Day 180, where anthropometric, biochemical, and dietary data are collected. A motivational follow-up is done on Day 135 to encourage continued adherence. The control group follows the same assessment schedule but does not receive interim dietary modifications. This structured timeline ensures a comprehensive evaluation of the intervention’s impact while maintaining participant engagement.

8. Justification for the 20g Fiber Difference and Study Duration
The 20g difference in fiber intake between groups was selected based on existing dietary recommendations and evidence supporting its impact on weight management and metabolic health. The intervention group receives 40g of fiber per 2000 kcal, aligning with the Indian Council of Medical Research (ICMR) and National Institute of Nutrition (NIN) guidelines. In contrast, the control group follows a standard 25g fiber intake. This difference ensures a meaningful contrast while remaining practical for adherence.
The 180-day (6-month) intervention period was chosen to allow sufficient time for stabilizing dietary habits and for metabolic changes, such as improvements in insulin resistance and body composition, to be observed. The feasibility of increasing dietary fiber intake by 20g has been supported by our preliminary observational study (2019), which assessed fiber intake and obesity among 564 women. This study highlighted a significant negative correlation between fiber intake and BMI, reinforcing the need for a structured dietary intervention to promote increased fiber consumption.

9. Addressing Compliance Assessment Concerns
Compliance assessment in this study is not solely based on 24-hour dietary recall; multiple tools are incorporated to ensure accuracy and reliability. In addition to the 24-hour recall and food frequency questionnaire, a compliance checklist is used to track adherence to the prescribed dietary plan. Furthermore, patient opinions on the modified diet are collected to assess acceptability and feasibility. Regular reinforcement sessions (via telephone on Days 15, 30, and 60) further help monitor compliance and address challenges.

10. Consistency in Fiber Composition (Soluble vs. Insoluble)
The study ensures consistency in dietary fiber composition across participants by providing a structured, customized diet plan that proportions soluble and insoluble fiber appropriately. The dietary sources primarily include whole grains, legumes, vegetables, and fruits, providing a balanced fiber mix. While the metabolic effects of soluble and insoluble fiber can vary, the intervention is designed to reflect a realistic, well-balanced dietary intake, aligning with established dietary guidelines. This approach ensures that all participants receive a comparable fiber composition, minimizing variability in metabolic responses while maintaining dietary feasibility.
1. Clarity in Methods Section (Phase 1 & Phase 2 Separation)
Phase 1
Objective
The primary aim of Phase 1 is to screen middle-aged overweight and obese women to determine the prevalence of insulin resistance.
Study Setting
This phase will be conducted in the Outpatient Departments (OPDs) of Medicine, Gynaecology, and Endocrinology at Kasturba Hospital, Manipal.
Sample Size & Selection

A total of 500 women will be screened to assess insulin resistance.

Participants will be categorized into two groups: overweight (BMI 23–24.9 kg/m²) and obese (BMI ≥ 25 kg/m²).

Each group will have at least 166 participants.

Inclusion Criteria

Women aged 35–55 years.

Willing to provide informed consent.

BMI ≥ 23 kg/m².

Exclusion Criteria

Women with conditions affecting nutritional status (e.g., tuberculosis, HIV, cancer, organ failure).

Women diagnosed with type 2 diabetes mellitus.

Individuals with hypertension, thyroid disorders, or any medical condition requiring medications affecting body weight (e.g., thyroxine, diuretics).

Pregnant or lactating women.

Women already on a weight-loss regime or consuming fiber above the recommended dietary allowance.

Women with contraindications for high fiber consumption (e.g., inflammatory bowel disease).

Data Collection Methods
Participants will undergo a baseline assessment, including:

Demographic Information: Age, education, occupation, income, marital history, place of residence, and family structure.

Anthropometric Measures: Height, weight, BMI, waist circumference, and hip circumference using standardized tools.

Biochemical Assessments:

Fasting blood glucose (hexokinase method).

HbA1c (TINA method).

Serum insulin (ECLIA).

Lipid profile (triglycerides, HDL, LDL, total cholesterol).

Dietary Assessment:

24-hour dietary recall and food frequency questionnaire analyzed using DietCal version 6.3.

Physical Activity Assessment:

Global Physical Activity Questionnaire (GPAQ).

Clinical Assessment: Evaluation of physical symptoms (e.g., bowel movement, satiety, leg pain, backache).

In-Depth Interviews

20 participants consuming low fiber (<20g/day) and 20 participants consuming moderate fiber (20-25g/day) will be interviewed telephonically for 45 minutes to assess barriers to fiber intake.

Phase 2: Randomized Controlled Trial (RCT)
Objective
To assess the impact of high dietary fiber intake (40g/day) on insulin resistance, body composition, and weight among overweight and obese women.
Study Design

Randomized, controlled trial.

Stratified Block Randomization (9 blocks of 20 participants each).

180 women will be randomized into:

Intervention Group (n=90): Receives 40g/day of fiber with dietary counselling.

Control Group (n=90): Receives 25g/day of fiber as part of a standard diet care plan.

Inclusion Criteria

Women from Phase 1 with abnormal HOMA-IR (>2), indicating insulin resistance.

Willing to adhere to a high-fiber diet if randomized to the intervention group.

Exclusion Criteria

Women unwilling to continue participation or adhere to the high-fiber diet.

Intervention & Control Groups
Intervention group
All women in the intervention arm will be counseled for about 15 minutes, and a customized diet chart consisting of high fiber of 40 grams will be provided. Nutritional empowerment on fiber shall be delivered to each woman enrolled. Necessary dietary advice on the modified diet plan and with a motivation to adhere to the diet plan will be communicated only to the intervention group. After the first counselling, on the 15th day, women will be telephonically assessed on their 24-hour recall dietary intake. On the 30th day, the women will be contacted telephonically again to record their 24-hour recall of their dietary intake. Necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 60th day, the women will be again telephonically contacted to record their 24-hour recall on their dietary intake, and necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat is analyzed using body fat analyzer and a questionnaire on patient opinion regarding modified diet plan shall be ass. Necessaryessed as motivation and adherence towards fiber consumption subjects will be communicated telephonically on the 135th day. From the 136th to the 180th day, there shall not be any conversation regarding dietary modifications. On the 180th day, as a compliance-checking, the women will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data .24hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat analyzed using body fat analyzer and diet compliance on the modified diet plan shall be assessed.

Control group.
Women in the control arm will get a traditional diet care plan with 25gm of fiber according to their health condition. Necessary dietary advice will be communicated to the control group on the first visit to the hospital. There shall be no telephonic communication with the control group till the 90th day. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hour dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer. On the 180th day, as a compliance-checking, the patient will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer

Data Analysis

Repeated Measures ANOVA will be used to evaluate changes in insulin resistance, body composition, and weight over time.

SPSS v16.0 will be used for statistical analysis.

Ethical Considerations

Approval obtained from the Institutional Research Committee and Institutional Ethics Committee (IEC).

Trial registered with the Clinical Trials Registry of India (CTRI/2022/01/039074).

Informed consent was obtained from all participants.

CONTROL ARM

Day 1

Traditional/standard care
(patient will be called to OPD)

Day 15
Nil

Day 30
Nil

Day 60
Nil

Day 90
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

INTERVENTION ARM

Day 1

Intervention
(patient will be called to OPD)

Customize the individual-specific diet plan
Nutritional counseling
Impart nutritional empowerment on fiber consumption
Handover of diet plan

Day 15

Reinforcement
(through telephone)

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 30

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 60

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 90

Outcome assessment
(patient will be called to OPD)
Basic data:
Tool 2: 24-hour recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Patient opinion on a modified diet
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

Day 135

Reinforcement (through telephone)

Motivation to follow a customized diet plan

Day 180

Checking compliance
(patient will be called to OPD)
Basic data:
Tool 2: 24-hour recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Compliance checklist
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

Day 135
Nil

Day180
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ

Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyser:
Visceral fat, S/C fat, muscle mass

3. Rationale for Sex-Specific Differences and Justification for a Single-Sex Study
This study is specifically designed for women’s health, as obesity and insulin resistance present distinct physiological and hormonal influences in females. The decision to focus on middle-aged women was based on prior evidence suggesting unique metabolic responses to dietary interventions in this demographic.
López, M. et al. (2016) - "Menopause, obesity, and insulin resistance: An emerging paradigm"

This study specifically explores the impact of menopause on metabolic health, highlighting the increased risk of insulin resistance and obesity in women as they transition through menopause. It aligns with your focus on middle-aged women and the unique metabolic responses they experience.

Reference: López, M. et al. "Menopause, obesity, and insulin resistance: An emerging paradigm." Endocrinology (2016).

Van Der Steeg, W. et al. (2010) - "Sex differences in insulin resistance in obesity"

This study investigates how hormonal factors, especially estrogen, affect insulin resistance and fat distribution differently in women, providing key insights into the sex-specific mechanisms that make middle-aged women particularly vulnerable to obesity and metabolic disorders.

Reference: Van Der Steeg, W. et al. "Sex differences in insulin resistance in obesity." Obesity Reviews (2010).

4. Updating Scientific Terminology in the Background Section
We appreciate the suggestion regarding outdated terminology. The term "roughage" and other obsolete language will be revised to align with current scientific terminology.
5. Clarification on Double-Blinding and Study Design
There was an error in the original study design description. This study is not a double-blind study but rather an open-ended study. This design was chosen to facilitate a deeper understanding of the real-world effects of dietary interventions on obesity and insulin resistance in middle-aged women, where factors like adherence to the intervention and participant feedback play an essential role in the analysis.

6. Sample Size Discrepancy
The final sample size of 180 participants (90 per group) was determined based on power calculations for insulin resistance and BMI, accounting for a 15% dropout rate. To ensure appropriate representation, participants were stratified based on the prevalence of obesity and overweight, maintaining a 2:1 ratio, with a higher proportion of obese individuals, as obesity is more prevalent in the target population.

7. Clarification of Study Duration
The total duration of the intervention is 180 days (6 months) for the intervention group, with structured follow-ups to ensure adherence and assess outcomes. Participants receive customized dietary counseling on Day 1, followed by reinforcement sessions via telephone on Days 15, 30, and 60 to monitor compliance and provide necessary modifications. Outcome assessments are conducted on Day 90 and Day 180, where anthropometric, biochemical, and dietary data are collected. A motivational follow-up is done on Day 135 to encourage continued adherence. The control group follows the same assessment schedule but does not receive interim dietary modifications. This structured timeline ensures a comprehensive evaluation of the intervention’s impact while maintaining participant engagement.

8. Justification for the 20g Fiber Difference and Study Duration
The 20g difference in fiber intake between groups was selected based on existing dietary recommendations and evidence supporting its impact on weight management and metabolic health. The intervention group receives 40g of fiber per 2000 kcal, aligning with the Indian Council of Medical Research (ICMR) and National Institute of Nutrition (NIN) guidelines. In contrast, the control group follows a standard 25g fiber intake. This difference ensures a meaningful contrast while remaining practical for adherence.
The 180-day (6-month) intervention period was chosen to allow sufficient time for stabilizing dietary habits and for metabolic changes, such as improvements in insulin resistance and body composition, to be observed. The feasibility of increasing dietary fiber intake by 20g has been supported by our preliminary observational study (2019), which assessed fiber intake and obesity among 564 women. This study highlighted a significant negative correlation between fiber intake and BMI, reinforcing the need for a structured dietary intervention to promote increased fiber consumption.

9. Addressing Compliance Assessment Concerns
Compliance assessment in this study is not solely based on 24-hour dietary recall; multiple tools are incorporated to ensure accuracy and reliability. In addition to the 24-hour recall and food frequency questionnaire, a compliance checklist is used to track adherence to the prescribed dietary plan. Furthermore, patient opinions on the modified diet are collected to assess acceptability and feasibility. Regular reinforcement sessions (via telephone on Days 15, 30, and 60) further help monitor compliance and address challenges.

10. Consistency in Fiber Composition (Soluble vs. Insoluble)
The study ensures consistency in dietary fiber composition across participants by providing a structured, customized diet plan that proportions soluble and insoluble fiber appropriately. The dietary sources primarily include whole grains, legumes, vegetables, and fruits, providing a balanced fiber mix. While the metabolic effects of soluble and insoluble fiber can vary, the intervention is designed to reflect a realistic, well-balanced dietary intake, aligning with established dietary guidelines. This approach ensures that all participants receive a comparable fiber composition, minimizing variability in metabolic responses while maintaining dietary feasibility.
Competing Interests: No competing interests were disclosed. Close
Report a concern
Author Response 13 Oct 2025

Suvarna Hebbar, Clinical Nutrition and Dietetics, Manipal College of Health Professions, Manipal., 576104, India

13 Oct 2025

Author Response
. Clarity in Methods Section (Phase 1 & Phase 2 Separation)
Phase 1
Objective
The primary aim of Phase 1 is to screen middle-aged overweight and obese women to determine ... Continue reading
. Clarity in Methods Section (Phase 1 & Phase 2 Separation)
Phase 1
Objective
The primary aim of Phase 1 is to screen middle-aged overweight and obese women to determine the prevalence of insulin resistance.
Study Setting
This phase will be conducted in the Outpatient Departments (OPDs) of Medicine, Gynaecology, and Endocrinology at Kasturba Hospital, Manipal.
Sample Size & Selection

A total of 500 women will be screened to assess insulin resistance.

Participants will be categorized into two groups: overweight (BMI 23–24.9 kg/m²) and obese (BMI ≥ 25 kg/m²).

Each group will have at least 166 participants.

Inclusion Criteria

Women aged 35–55 years.

Willing to provide informed consent.

BMI ≥ 23 kg/m².

Exclusion Criteria

Women with conditions affecting nutritional status (e.g., tuberculosis, HIV, cancer, organ failure).

Women diagnosed with type 2 diabetes mellitus.

Individuals with hypertension, thyroid disorders, or any medical condition requiring medications affecting body weight (e.g., thyroxine, diuretics).

Pregnant or lactating women.

Women already on a weight-loss regime or consuming fiber above the recommended dietary allowance.

Women with contraindications for high fiber consumption (e.g., inflammatory bowel disease).

Data Collection Methods
Participants will undergo a baseline assessment, including:

Demographic Information: Age, education, occupation, income, marital history, place of residence, and family structure.

Anthropometric Measures: Height, weight, BMI, waist circumference, and hip circumference using standardized tools.

Biochemical Assessments:

Fasting blood glucose (hexokinase method).

HbA1c (TINA method).

Serum insulin (ECLIA).

Lipid profile (triglycerides, HDL, LDL, total cholesterol).

Dietary Assessment:

24-hour dietary recall and food frequency questionnaire analyzed using DietCal version 6.3.

Physical Activity Assessment:

Global Physical Activity Questionnaire (GPAQ).

Clinical Assessment: Evaluation of physical symptoms (e.g., bowel movement, satiety, leg pain, backache).

In-Depth Interviews

20 participants consuming low fiber (<20g/day) and 20 participants consuming moderate fiber (20-25g/day) will be interviewed telephonically for 45 minutes to assess barriers to fiber intake.

Phase 2: Randomized Controlled Trial (RCT)
Objective
To assess the impact of high dietary fiber intake (40g/day) on insulin resistance, body composition, and weight among overweight and obese women.
Study Design

Randomized, controlled trial.

Stratified Block Randomization (9 blocks of 20 participants each).

180 women will be randomized into:

Intervention Group (n=90): Receives 40g/day of fiber with dietary counselling.

Control Group (n=90): Receives 25g/day of fiber as part of a standard diet care plan.

Inclusion Criteria

Women from Phase 1 with abnormal HOMA-IR (>2), indicating insulin resistance.

Willing to adhere to a high-fiber diet if randomized to the intervention group.

Exclusion Criteria

Women unwilling to continue participation or adhere to the high-fiber diet.

Intervention & Control Groups
Intervention group
All women in the intervention arm will be counseled for about 15 minutes, and a customized diet chart consisting of high fiber of 40 grams will be provided. Nutritional empowerment on fiber shall be delivered to each woman enrolled. Necessary dietary advice on the modified diet plan and with a motivation to adhere to the diet plan will be communicated only to the intervention group. After the first counselling, on the 15th day, women will be telephonically assessed on their 24-hour recall dietary intake. On the 30th day, the women will be contacted telephonically again to record their 24-hour recall of their dietary intake. Necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 60th day, the women will be again telephonically contacted to record their 24-hour recall on their dietary intake, and necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat is analyzed using body fat analyzer and a questionnaire on patient opinion regarding modified diet plan shall be assessed as motivation and adherence towards fiber consumption subjects will be communicated telephonically on the 135th day. From the 136th to the 180th day, there shall not be any conversation regarding dietary modifications. On the 180th day, as a compliance-checking, the women will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data .24hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat analyzed using body fat analyzer and diet compliance on the modified diet plan shall be assessed.

Control group.
Women in the control arm will get a traditional diet care plan with 25gm of fiber according to their health condition. Necessary dietary advice will be communicated to the control group on the first visit to the hospital. There shall be no telephonic communication with the control group till the 90th day. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hour dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer. On the 180th day, as a compliance-checking, the patient will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer

Data Analysis

Repeated Measures ANOVA will be used to evaluate changes in insulin resistance, body composition, and weight over time.

SPSS v16.0 will be used for statistical analysis.

Ethical Considerations

Approval obtained from the Institutional Research Committee and Institutional Ethics Committee (IEC).

Trial registered with the Clinical Trials Registry of India (CTRI/2022/01/039074).

Informed consent was obtained from all participants.

CONTROL ARM

Day 1

Traditional/standard care
(patient will be called to OPD)

Day 15
Nil

Day 30
Nil

Day 60
Nil

Day 90
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

INTERVENTION ARM

Day 1

Intervention
(patient will be called to OPD)

Customize the individual-specific diet plan
Nutritional counseling
Impart nutritional empowerment on fiber consumption
Handover of diet plan

Day 15

Reinforcement
(through telephone)

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 30

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 60

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 90

Outcome assessment
(patient will be called to OPD)
Basic data:
Tool 2: 24-hour recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Patient opinion on a modified diet
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

Day 135

Reinforcement (through telephone)

Motivation to follow customised diet plan

Day 180

Checking compliance
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Compliance checklist
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyser:
Visceral fat, S/C fat, muscle mass

Day 135
Nil

Day180
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ

Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyser:
Visceral fat, S/C fat, muscle mass

3. Rationale for Sex-Specific Differences and Justification for a Single-Sex Study
This study is specifically designed for women’s health, as obesity and insulin resistance present distinct physiological and hormonal influences in females. The decision to focus on middle-aged women was based on prior evidence suggesting unique metabolic responses to dietary interventions in this demographic.
López, M. et al. (2016) - "Menopause, obesity, and insulin resistance: An emerging paradigm"

This study specifically explores the impact of menopause on metabolic health, highlighting the increased risk of insulin resistance and obesity in women as they transition through menopause. It aligns with your focus on middle-aged women and the unique metabolic responses they experience.

Reference: López, M. et al. "Menopause, obesity, and insulin resistance: An emerging paradigm." Endocrinology (2016).

Van Der Steeg, W. et al. (2010) - "Sex differences in insulin resistance in obesity"

This study investigates how hormonal factors, especially estrogen, affect insulin resistance and fat distribution differently in women, providing key insights into the sex-specific mechanisms that make middle-aged women particularly vulnerable to obesity and metabolic disorders.

Reference: Van Der Steeg, W. et al. "Sex differences in insulin resistance in obesity." Obesity Reviews (2010).

4. Updating Scientific Terminology in the Background Section
We appreciate the suggestion regarding outdated terminology. The term "roughage" and other obsolete language will be revised to align with current scientific terminology.
5. Clarification on Double-Blinding and Study Design
There was an error in the original study design description. This study is not a double-blind study but rather an open-ended study. This design was chosen to facilitate a deeper understanding of the real-world effects of dietary interventions on obesity and insulin resistance in middle-aged women, where factors like adherence to the intervention and participant feedback play an important role in the analysis.

6. Sample Size Discrepancy
The final sample size of 180 participants (90 per group) was determined based on power calculations for insulin resistance and BMI, accounting for a 15% dropout rate. To ensure appropriate representation, participants were stratified based on the prevalence of obesity and overweight, maintaining a 2:1 ratio, with a higher proportion of obese individuals, as obesity is more prevalent in the target population.

7. Clarification of Study Duration
The total duration of the intervention is 180 days (6 months) for the intervention group, with structured follow-ups to ensure adherence and assess outcomes. Participants receive customized dietary counseling on Day 1, followed by reinforcement sessions via telephone on Days 15, 30, and 60 to monitor compliance and provide necessary modifications. Outcome assessments are conducted on Day 90 and Day 180, where anthropometric, biochemical, and dietary data are collected. A motivational follow-up is done on Day 135 to encourage continued adherence. The control group follows the same assessment schedule but does not receive interim dietary modifications. This structured timeline ensures a comprehensive evaluation of the intervention’s impact while maintaining participant engagement.

8. Justification for the 20g Fiber Difference and Study Duration
The 20g difference in fiber intake between groups was selected based on existing dietary recommendations and evidence supporting its impact on weight management and metabolic health. The intervention group receives 40g of fiber per 2000 kcal, aligning with the Indian Council of Medical Research (ICMR) and National Institute of Nutrition (NIN) guidelines. In contrast, the control group follows a standard 25g fiber intake. This difference ensures a meaningful contrast while remaining practical for adherence.
The 180-day (6-month) intervention period was chosen to allow sufficient time for stabilizing dietary habits and for metabolic changes, such as improvements in insulin resistance and body composition, to be observed. The feasibility of increasing dietary fiber intake by 20g has been supported by our preliminary observational study (2019), which assessed fiber intake and obesity among 564 women. This study highlighted a significant negative correlation between fiber intake and BMI, reinforcing the need for a structured dietary intervention to promote increased fiber consumption.

9. Addressing Compliance Assessment Concerns
Compliance assessment in this study is not solely based on 24-hour dietary recall; multiple tools are incorporated to ensure accuracy and reliability. In addition to the 24-hour recall and food frequency questionnaire, a compliance checklist is used to track adherence to the prescribed dietary plan. Furthermore, patient opinions on the modified diet are collected to assess acceptability and feasibility. Regular reinforcement sessions (via telephone on Days 15, 30, and 60) further help monitor compliance and address challenges.

10. Consistency in Fiber Composition (Soluble vs. Insoluble)
The study ensures consistency in dietary fiber composition across participants by providing a structured, customized diet plan that appropriately proportions soluble and insoluble fiber. The dietary sources primarily include whole grains, legumes, vegetables, and fruits, providing a balanced fiber mix. While the metabolic effects of soluble and insoluble fiber can vary, the intervention is designed to reflect a realistic, well-balanced dietary intake, aligning with established dietary guidelines. This approach ensures that all participants receive a comparable fiber composition, minimizing variability in metabolic responses while maintaining dietary feasibility.
. Clarity in Methods Section (Phase 1 & Phase 2 Separation)
Phase 1
Objective
The primary aim of Phase 1 is to screen middle-aged overweight and obese women to determine the prevalence of insulin resistance.
Study Setting
This phase will be conducted in the Outpatient Departments (OPDs) of Medicine, Gynaecology, and Endocrinology at Kasturba Hospital, Manipal.
Sample Size & Selection

A total of 500 women will be screened to assess insulin resistance.

Participants will be categorized into two groups: overweight (BMI 23–24.9 kg/m²) and obese (BMI ≥ 25 kg/m²).

Each group will have at least 166 participants.

Inclusion Criteria

Women aged 35–55 years.

Willing to provide informed consent.

BMI ≥ 23 kg/m².

Exclusion Criteria

Women with conditions affecting nutritional status (e.g., tuberculosis, HIV, cancer, organ failure).

Women diagnosed with type 2 diabetes mellitus.

Individuals with hypertension, thyroid disorders, or any medical condition requiring medications affecting body weight (e.g., thyroxine, diuretics).

Pregnant or lactating women.

Women already on a weight-loss regime or consuming fiber above the recommended dietary allowance.

Women with contraindications for high fiber consumption (e.g., inflammatory bowel disease).

Data Collection Methods
Participants will undergo a baseline assessment, including:

Demographic Information: Age, education, occupation, income, marital history, place of residence, and family structure.

Anthropometric Measures: Height, weight, BMI, waist circumference, and hip circumference using standardized tools.

Biochemical Assessments:

Fasting blood glucose (hexokinase method).

HbA1c (TINA method).

Serum insulin (ECLIA).

Lipid profile (triglycerides, HDL, LDL, total cholesterol).

Dietary Assessment:

24-hour dietary recall and food frequency questionnaire analyzed using DietCal version 6.3.

Physical Activity Assessment:

Global Physical Activity Questionnaire (GPAQ).

Clinical Assessment: Evaluation of physical symptoms (e.g., bowel movement, satiety, leg pain, backache).

In-Depth Interviews

20 participants consuming low fiber (<20g/day) and 20 participants consuming moderate fiber (20-25g/day) will be interviewed telephonically for 45 minutes to assess barriers to fiber intake.

Phase 2: Randomized Controlled Trial (RCT)
Objective
To assess the impact of high dietary fiber intake (40g/day) on insulin resistance, body composition, and weight among overweight and obese women.
Study Design

Randomized, controlled trial.

Stratified Block Randomization (9 blocks of 20 participants each).

180 women will be randomized into:

Intervention Group (n=90): Receives 40g/day of fiber with dietary counselling.

Control Group (n=90): Receives 25g/day of fiber as part of a standard diet care plan.

Inclusion Criteria

Women from Phase 1 with abnormal HOMA-IR (>2), indicating insulin resistance.

Willing to adhere to a high-fiber diet if randomized to the intervention group.

Exclusion Criteria

Women unwilling to continue participation or adhere to the high-fiber diet.

Intervention & Control Groups
Intervention group
All women in the intervention arm will be counseled for about 15 minutes, and a customized diet chart consisting of high fiber of 40 grams will be provided. Nutritional empowerment on fiber shall be delivered to each woman enrolled. Necessary dietary advice on the modified diet plan and with a motivation to adhere to the diet plan will be communicated only to the intervention group. After the first counselling, on the 15th day, women will be telephonically assessed on their 24-hour recall dietary intake. On the 30th day, the women will be contacted telephonically again to record their 24-hour recall of their dietary intake. Necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 60th day, the women will be again telephonically contacted to record their 24-hour recall on their dietary intake, and necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat is analyzed using body fat analyzer and a questionnaire on patient opinion regarding modified diet plan shall be assessed as motivation and adherence towards fiber consumption subjects will be communicated telephonically on the 135th day. From the 136th to the 180th day, there shall not be any conversation regarding dietary modifications. On the 180th day, as a compliance-checking, the women will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data .24hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat analyzed using body fat analyzer and diet compliance on the modified diet plan shall be assessed.

Control group.
Women in the control arm will get a traditional diet care plan with 25gm of fiber according to their health condition. Necessary dietary advice will be communicated to the control group on the first visit to the hospital. There shall be no telephonic communication with the control group till the 90th day. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hour dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer. On the 180th day, as a compliance-checking, the patient will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer

Data Analysis

Repeated Measures ANOVA will be used to evaluate changes in insulin resistance, body composition, and weight over time.

SPSS v16.0 will be used for statistical analysis.

Ethical Considerations

Approval obtained from the Institutional Research Committee and Institutional Ethics Committee (IEC).

Trial registered with the Clinical Trials Registry of India (CTRI/2022/01/039074).

Informed consent was obtained from all participants.

CONTROL ARM

Day 1

Traditional/standard care
(patient will be called to OPD)

Day 15
Nil

Day 30
Nil

Day 60
Nil

Day 90
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

INTERVENTION ARM

Day 1

Intervention
(patient will be called to OPD)

Customize the individual-specific diet plan
Nutritional counseling
Impart nutritional empowerment on fiber consumption
Handover of diet plan

Day 15

Reinforcement
(through telephone)

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 30

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 60

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 90

Outcome assessment
(patient will be called to OPD)
Basic data:
Tool 2: 24-hour recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Patient opinion on a modified diet
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

Day 135

Reinforcement (through telephone)

Motivation to follow customised diet plan

Day 180

Checking compliance
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Compliance checklist
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyser:
Visceral fat, S/C fat, muscle mass

Day 135
Nil

Day180
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ

Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyser:
Visceral fat, S/C fat, muscle mass

3. Rationale for Sex-Specific Differences and Justification for a Single-Sex Study
This study is specifically designed for women’s health, as obesity and insulin resistance present distinct physiological and hormonal influences in females. The decision to focus on middle-aged women was based on prior evidence suggesting unique metabolic responses to dietary interventions in this demographic.
López, M. et al. (2016) - "Menopause, obesity, and insulin resistance: An emerging paradigm"

This study specifically explores the impact of menopause on metabolic health, highlighting the increased risk of insulin resistance and obesity in women as they transition through menopause. It aligns with your focus on middle-aged women and the unique metabolic responses they experience.

Reference: López, M. et al. "Menopause, obesity, and insulin resistance: An emerging paradigm." Endocrinology (2016).

Van Der Steeg, W. et al. (2010) - "Sex differences in insulin resistance in obesity"

This study investigates how hormonal factors, especially estrogen, affect insulin resistance and fat distribution differently in women, providing key insights into the sex-specific mechanisms that make middle-aged women particularly vulnerable to obesity and metabolic disorders.

Reference: Van Der Steeg, W. et al. "Sex differences in insulin resistance in obesity." Obesity Reviews (2010).

4. Updating Scientific Terminology in the Background Section
We appreciate the suggestion regarding outdated terminology. The term "roughage" and other obsolete language will be revised to align with current scientific terminology.
5. Clarification on Double-Blinding and Study Design
There was an error in the original study design description. This study is not a double-blind study but rather an open-ended study. This design was chosen to facilitate a deeper understanding of the real-world effects of dietary interventions on obesity and insulin resistance in middle-aged women, where factors like adherence to the intervention and participant feedback play an important role in the analysis.

6. Sample Size Discrepancy
The final sample size of 180 participants (90 per group) was determined based on power calculations for insulin resistance and BMI, accounting for a 15% dropout rate. To ensure appropriate representation, participants were stratified based on the prevalence of obesity and overweight, maintaining a 2:1 ratio, with a higher proportion of obese individuals, as obesity is more prevalent in the target population.

7. Clarification of Study Duration
The total duration of the intervention is 180 days (6 months) for the intervention group, with structured follow-ups to ensure adherence and assess outcomes. Participants receive customized dietary counseling on Day 1, followed by reinforcement sessions via telephone on Days 15, 30, and 60 to monitor compliance and provide necessary modifications. Outcome assessments are conducted on Day 90 and Day 180, where anthropometric, biochemical, and dietary data are collected. A motivational follow-up is done on Day 135 to encourage continued adherence. The control group follows the same assessment schedule but does not receive interim dietary modifications. This structured timeline ensures a comprehensive evaluation of the intervention’s impact while maintaining participant engagement.

8. Justification for the 20g Fiber Difference and Study Duration
The 20g difference in fiber intake between groups was selected based on existing dietary recommendations and evidence supporting its impact on weight management and metabolic health. The intervention group receives 40g of fiber per 2000 kcal, aligning with the Indian Council of Medical Research (ICMR) and National Institute of Nutrition (NIN) guidelines. In contrast, the control group follows a standard 25g fiber intake. This difference ensures a meaningful contrast while remaining practical for adherence.
The 180-day (6-month) intervention period was chosen to allow sufficient time for stabilizing dietary habits and for metabolic changes, such as improvements in insulin resistance and body composition, to be observed. The feasibility of increasing dietary fiber intake by 20g has been supported by our preliminary observational study (2019), which assessed fiber intake and obesity among 564 women. This study highlighted a significant negative correlation between fiber intake and BMI, reinforcing the need for a structured dietary intervention to promote increased fiber consumption.

9. Addressing Compliance Assessment Concerns
Compliance assessment in this study is not solely based on 24-hour dietary recall; multiple tools are incorporated to ensure accuracy and reliability. In addition to the 24-hour recall and food frequency questionnaire, a compliance checklist is used to track adherence to the prescribed dietary plan. Furthermore, patient opinions on the modified diet are collected to assess acceptability and feasibility. Regular reinforcement sessions (via telephone on Days 15, 30, and 60) further help monitor compliance and address challenges.

10. Consistency in Fiber Composition (Soluble vs. Insoluble)
The study ensures consistency in dietary fiber composition across participants by providing a structured, customized diet plan that appropriately proportions soluble and insoluble fiber. The dietary sources primarily include whole grains, legumes, vegetables, and fruits, providing a balanced fiber mix. While the metabolic effects of soluble and insoluble fiber can vary, the intervention is designed to reflect a realistic, well-balanced dietary intake, aligning with established dietary guidelines. This approach ensures that all participants receive a comparable fiber composition, minimizing variability in metabolic responses while maintaining dietary feasibility.
Competing Interests: No competing interests were disclosed. Close
Report a concern
Respond or Comment

COMMENTS ON THIS REPORT

Author Response 22 Mar 2025

Suvarna Hebbar, Clinical Nutrition and Dietetics, Manipal College of Health Professions, Manipal., 576104, India

22 Mar 2025

Author Response
1. Clarity in Methods Section (Phase 1 & Phase 2 Separation)
Phase 1
Objective
The primary aim of Phase 1 is to screen middle-aged overweight and obese women to determine ... Continue reading
1. Clarity in Methods Section (Phase 1 & Phase 2 Separation)
Phase 1
Objective
The primary aim of Phase 1 is to screen middle-aged overweight and obese women to determine the prevalence of insulin resistance.
Study Setting
This phase will be conducted in the Outpatient Departments (OPDs) of Medicine, Gynaecology, and Endocrinology at Kasturba Hospital, Manipal.
Sample Size & Selection

A total of 500 women will be screened to assess insulin resistance.

Participants will be categorized into two groups: overweight (BMI 23–24.9 kg/m²) and obese (BMI ≥ 25 kg/m²).

Each group will have at least 166 participants.

Inclusion Criteria

Women aged 35–55 years.

Willing to provide informed consent.

BMI ≥ 23 kg/m².

Exclusion Criteria

Women with conditions affecting nutritional status (e.g., tuberculosis, HIV, cancer, organ failure).

Women diagnosed with type 2 diabetes mellitus.

Individuals with hypertension, thyroid disorders, or any medical condition requiring medications affecting body weight (e.g., thyroxine, diuretics).

Pregnant or lactating women.

Women already on a weight-loss regime or consuming fiber above the recommended dietary allowance.

Women with contraindications for high fiber consumption (e.g., inflammatory bowel disease).

Data Collection Methods
Participants will undergo a baseline assessment, including:

Demographic Information: Age, education, occupation, income, marital history, place of residence, and family structure.

Anthropometric Measures: Height, weight, BMI, waist circumference, and hip circumference using standardized tools.

Biochemical Assessments:

Fasting blood glucose (hexokinase method).

HbA1c (TINA method).

Serum insulin (ECLIA).

Lipid profile (triglycerides, HDL, LDL, total cholesterol).

Dietary Assessment:

24-hour dietary recall and food frequency questionnaire analyzed using DietCal version 6.3.

Physical Activity Assessment:

Global Physical Activity Questionnaire (GPAQ).

Clinical Assessment: Evaluation of physical symptoms (e.g., bowel movement, satiety, leg pain, backache).

In-Depth Interviews

20 participants consuming low fiber (<20g/day) and 20 participants consuming moderate fiber (20-25g/day) will be interviewed telephonically for 45 minutes to assess barriers to fiber intake.

Phase 2: Randomized Controlled Trial (RCT)
Objective
To assess the impact of high dietary fiber intake (40g/day) on insulin resistance, body composition, and weight among overweight and obese women.
Study Design

Randomized, controlled trial.

Stratified Block Randomization (9 blocks of 20 participants each).

180 women will be randomized into:

Intervention Group (n=90): Receives 40g/day of fiber with dietary counselling.

Control Group (n=90): Receives 25g/day of fiber as part of a standard diet care plan.

Inclusion Criteria

Women from Phase 1 with abnormal HOMA-IR (>2), indicating insulin resistance.

Willing to adhere to a high-fiber diet if randomized to the intervention group.

Exclusion Criteria

Women unwilling to continue participation or adhere to the high-fiber diet.

Intervention & Control Groups
Intervention group
All women in the intervention arm will be counseled for about 15 minutes, and a customized diet chart consisting of high fiber of 40 grams will be provided. Nutritional empowerment on fiber shall be delivered to each woman enrolled. Necessary dietary advice on the modified diet plan and with a motivation to adhere to the diet plan will be communicated only to the intervention group. After the first counselling, on the 15th day, women will be telephonically assessed on their 24-hour recall dietary intake. On the 30th day, the women will be contacted telephonically again to record their 24-hour recall of their dietary intake. Necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 60th day, the women will be again telephonically contacted to record their 24-hour recall on their dietary intake, and necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat is analyzed using body fat analyzer and a questionnaire on patient opinion regarding modified diet plan shall be ass. Necessaryessed as motivation and adherence towards fiber consumption subjects will be communicated telephonically on the 135th day. From the 136th to the 180th day, there shall not be any conversation regarding dietary modifications. On the 180th day, as a compliance-checking, the women will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data .24hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat analyzed using body fat analyzer and diet compliance on the modified diet plan shall be assessed.

Control group.
Women in the control arm will get a traditional diet care plan with 25gm of fiber according to their health condition. Necessary dietary advice will be communicated to the control group on the first visit to the hospital. There shall be no telephonic communication with the control group till the 90th day. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hour dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer. On the 180th day, as a compliance-checking, the patient will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer

Data Analysis

Repeated Measures ANOVA will be used to evaluate changes in insulin resistance, body composition, and weight over time.

SPSS v16.0 will be used for statistical analysis.

Ethical Considerations

Approval obtained from the Institutional Research Committee and Institutional Ethics Committee (IEC).

Trial registered with the Clinical Trials Registry of India (CTRI/2022/01/039074).

Informed consent was obtained from all participants.

CONTROL ARM

Day 1

Traditional/standard care
(patient will be called to OPD)

Day 15
Nil

Day 30
Nil

Day 60
Nil

Day 90
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

INTERVENTION ARM

Day 1

Intervention
(patient will be called to OPD)

Customize the individual-specific diet plan
Nutritional counseling
Impart nutritional empowerment on fiber consumption
Handover of diet plan

Day 15

Reinforcement
(through telephone)

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 30

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 60

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 90

Outcome assessment
(patient will be called to OPD)
Basic data:
Tool 2: 24-hour recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Patient opinion on a modified diet
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

Day 135

Reinforcement (through telephone)

Motivation to follow a customized diet plan

Day 180

Checking compliance
(patient will be called to OPD)
Basic data:
Tool 2: 24-hour recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Compliance checklist
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

Day 135
Nil

Day180
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ

Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyser:
Visceral fat, S/C fat, muscle mass

3. Rationale for Sex-Specific Differences and Justification for a Single-Sex Study
This study is specifically designed for women’s health, as obesity and insulin resistance present distinct physiological and hormonal influences in females. The decision to focus on middle-aged women was based on prior evidence suggesting unique metabolic responses to dietary interventions in this demographic.
López, M. et al. (2016) - "Menopause, obesity, and insulin resistance: An emerging paradigm"

This study specifically explores the impact of menopause on metabolic health, highlighting the increased risk of insulin resistance and obesity in women as they transition through menopause. It aligns with your focus on middle-aged women and the unique metabolic responses they experience.

Reference: López, M. et al. "Menopause, obesity, and insulin resistance: An emerging paradigm." Endocrinology (2016).

Van Der Steeg, W. et al. (2010) - "Sex differences in insulin resistance in obesity"

This study investigates how hormonal factors, especially estrogen, affect insulin resistance and fat distribution differently in women, providing key insights into the sex-specific mechanisms that make middle-aged women particularly vulnerable to obesity and metabolic disorders.

Reference: Van Der Steeg, W. et al. "Sex differences in insulin resistance in obesity." Obesity Reviews (2010).

4. Updating Scientific Terminology in the Background Section
We appreciate the suggestion regarding outdated terminology. The term "roughage" and other obsolete language will be revised to align with current scientific terminology.
5. Clarification on Double-Blinding and Study Design
There was an error in the original study design description. This study is not a double-blind study but rather an open-ended study. This design was chosen to facilitate a deeper understanding of the real-world effects of dietary interventions on obesity and insulin resistance in middle-aged women, where factors like adherence to the intervention and participant feedback play an essential role in the analysis.

6. Sample Size Discrepancy
The final sample size of 180 participants (90 per group) was determined based on power calculations for insulin resistance and BMI, accounting for a 15% dropout rate. To ensure appropriate representation, participants were stratified based on the prevalence of obesity and overweight, maintaining a 2:1 ratio, with a higher proportion of obese individuals, as obesity is more prevalent in the target population.

7. Clarification of Study Duration
The total duration of the intervention is 180 days (6 months) for the intervention group, with structured follow-ups to ensure adherence and assess outcomes. Participants receive customized dietary counseling on Day 1, followed by reinforcement sessions via telephone on Days 15, 30, and 60 to monitor compliance and provide necessary modifications. Outcome assessments are conducted on Day 90 and Day 180, where anthropometric, biochemical, and dietary data are collected. A motivational follow-up is done on Day 135 to encourage continued adherence. The control group follows the same assessment schedule but does not receive interim dietary modifications. This structured timeline ensures a comprehensive evaluation of the intervention’s impact while maintaining participant engagement.

8. Justification for the 20g Fiber Difference and Study Duration
The 20g difference in fiber intake between groups was selected based on existing dietary recommendations and evidence supporting its impact on weight management and metabolic health. The intervention group receives 40g of fiber per 2000 kcal, aligning with the Indian Council of Medical Research (ICMR) and National Institute of Nutrition (NIN) guidelines. In contrast, the control group follows a standard 25g fiber intake. This difference ensures a meaningful contrast while remaining practical for adherence.
The 180-day (6-month) intervention period was chosen to allow sufficient time for stabilizing dietary habits and for metabolic changes, such as improvements in insulin resistance and body composition, to be observed. The feasibility of increasing dietary fiber intake by 20g has been supported by our preliminary observational study (2019), which assessed fiber intake and obesity among 564 women. This study highlighted a significant negative correlation between fiber intake and BMI, reinforcing the need for a structured dietary intervention to promote increased fiber consumption.

9. Addressing Compliance Assessment Concerns
Compliance assessment in this study is not solely based on 24-hour dietary recall; multiple tools are incorporated to ensure accuracy and reliability. In addition to the 24-hour recall and food frequency questionnaire, a compliance checklist is used to track adherence to the prescribed dietary plan. Furthermore, patient opinions on the modified diet are collected to assess acceptability and feasibility. Regular reinforcement sessions (via telephone on Days 15, 30, and 60) further help monitor compliance and address challenges.

10. Consistency in Fiber Composition (Soluble vs. Insoluble)
The study ensures consistency in dietary fiber composition across participants by providing a structured, customized diet plan that proportions soluble and insoluble fiber appropriately. The dietary sources primarily include whole grains, legumes, vegetables, and fruits, providing a balanced fiber mix. While the metabolic effects of soluble and insoluble fiber can vary, the intervention is designed to reflect a realistic, well-balanced dietary intake, aligning with established dietary guidelines. This approach ensures that all participants receive a comparable fiber composition, minimizing variability in metabolic responses while maintaining dietary feasibility.
1. Clarity in Methods Section (Phase 1 & Phase 2 Separation)
Phase 1
Objective
The primary aim of Phase 1 is to screen middle-aged overweight and obese women to determine the prevalence of insulin resistance.
Study Setting
This phase will be conducted in the Outpatient Departments (OPDs) of Medicine, Gynaecology, and Endocrinology at Kasturba Hospital, Manipal.
Sample Size & Selection

A total of 500 women will be screened to assess insulin resistance.

Participants will be categorized into two groups: overweight (BMI 23–24.9 kg/m²) and obese (BMI ≥ 25 kg/m²).

Each group will have at least 166 participants.

Inclusion Criteria

Women aged 35–55 years.

Willing to provide informed consent.

BMI ≥ 23 kg/m².

Exclusion Criteria

Women with conditions affecting nutritional status (e.g., tuberculosis, HIV, cancer, organ failure).

Women diagnosed with type 2 diabetes mellitus.

Individuals with hypertension, thyroid disorders, or any medical condition requiring medications affecting body weight (e.g., thyroxine, diuretics).

Pregnant or lactating women.

Women already on a weight-loss regime or consuming fiber above the recommended dietary allowance.

Women with contraindications for high fiber consumption (e.g., inflammatory bowel disease).

Data Collection Methods
Participants will undergo a baseline assessment, including:

Demographic Information: Age, education, occupation, income, marital history, place of residence, and family structure.

Anthropometric Measures: Height, weight, BMI, waist circumference, and hip circumference using standardized tools.

Biochemical Assessments:

Fasting blood glucose (hexokinase method).

HbA1c (TINA method).

Serum insulin (ECLIA).

Lipid profile (triglycerides, HDL, LDL, total cholesterol).

Dietary Assessment:

24-hour dietary recall and food frequency questionnaire analyzed using DietCal version 6.3.

Physical Activity Assessment:

Global Physical Activity Questionnaire (GPAQ).

Clinical Assessment: Evaluation of physical symptoms (e.g., bowel movement, satiety, leg pain, backache).

In-Depth Interviews

20 participants consuming low fiber (<20g/day) and 20 participants consuming moderate fiber (20-25g/day) will be interviewed telephonically for 45 minutes to assess barriers to fiber intake.

Phase 2: Randomized Controlled Trial (RCT)
Objective
To assess the impact of high dietary fiber intake (40g/day) on insulin resistance, body composition, and weight among overweight and obese women.
Study Design

Randomized, controlled trial.

Stratified Block Randomization (9 blocks of 20 participants each).

180 women will be randomized into:

Intervention Group (n=90): Receives 40g/day of fiber with dietary counselling.

Control Group (n=90): Receives 25g/day of fiber as part of a standard diet care plan.

Inclusion Criteria

Women from Phase 1 with abnormal HOMA-IR (>2), indicating insulin resistance.

Willing to adhere to a high-fiber diet if randomized to the intervention group.

Exclusion Criteria

Women unwilling to continue participation or adhere to the high-fiber diet.

Intervention & Control Groups
Intervention group
All women in the intervention arm will be counseled for about 15 minutes, and a customized diet chart consisting of high fiber of 40 grams will be provided. Nutritional empowerment on fiber shall be delivered to each woman enrolled. Necessary dietary advice on the modified diet plan and with a motivation to adhere to the diet plan will be communicated only to the intervention group. After the first counselling, on the 15th day, women will be telephonically assessed on their 24-hour recall dietary intake. On the 30th day, the women will be contacted telephonically again to record their 24-hour recall of their dietary intake. Necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 60th day, the women will be again telephonically contacted to record their 24-hour recall on their dietary intake, and necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat is analyzed using body fat analyzer and a questionnaire on patient opinion regarding modified diet plan shall be ass. Necessaryessed as motivation and adherence towards fiber consumption subjects will be communicated telephonically on the 135th day. From the 136th to the 180th day, there shall not be any conversation regarding dietary modifications. On the 180th day, as a compliance-checking, the women will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data .24hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat analyzed using body fat analyzer and diet compliance on the modified diet plan shall be assessed.

Control group.
Women in the control arm will get a traditional diet care plan with 25gm of fiber according to their health condition. Necessary dietary advice will be communicated to the control group on the first visit to the hospital. There shall be no telephonic communication with the control group till the 90th day. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hour dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer. On the 180th day, as a compliance-checking, the patient will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer

Data Analysis

Repeated Measures ANOVA will be used to evaluate changes in insulin resistance, body composition, and weight over time.

SPSS v16.0 will be used for statistical analysis.

Ethical Considerations

Approval obtained from the Institutional Research Committee and Institutional Ethics Committee (IEC).

Trial registered with the Clinical Trials Registry of India (CTRI/2022/01/039074).

Informed consent was obtained from all participants.

CONTROL ARM

Day 1

Traditional/standard care
(patient will be called to OPD)

Day 15
Nil

Day 30
Nil

Day 60
Nil

Day 90
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

INTERVENTION ARM

Day 1

Intervention
(patient will be called to OPD)

Customize the individual-specific diet plan
Nutritional counseling
Impart nutritional empowerment on fiber consumption
Handover of diet plan

Day 15

Reinforcement
(through telephone)

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 30

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 60

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 90

Outcome assessment
(patient will be called to OPD)
Basic data:
Tool 2: 24-hour recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Patient opinion on a modified diet
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

Day 135

Reinforcement (through telephone)

Motivation to follow a customized diet plan

Day 180

Checking compliance
(patient will be called to OPD)
Basic data:
Tool 2: 24-hour recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Compliance checklist
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

Day 135
Nil

Day180
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ

Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyser:
Visceral fat, S/C fat, muscle mass

3. Rationale for Sex-Specific Differences and Justification for a Single-Sex Study
This study is specifically designed for women’s health, as obesity and insulin resistance present distinct physiological and hormonal influences in females. The decision to focus on middle-aged women was based on prior evidence suggesting unique metabolic responses to dietary interventions in this demographic.
López, M. et al. (2016) - "Menopause, obesity, and insulin resistance: An emerging paradigm"

This study specifically explores the impact of menopause on metabolic health, highlighting the increased risk of insulin resistance and obesity in women as they transition through menopause. It aligns with your focus on middle-aged women and the unique metabolic responses they experience.

Reference: López, M. et al. "Menopause, obesity, and insulin resistance: An emerging paradigm." Endocrinology (2016).

Van Der Steeg, W. et al. (2010) - "Sex differences in insulin resistance in obesity"

This study investigates how hormonal factors, especially estrogen, affect insulin resistance and fat distribution differently in women, providing key insights into the sex-specific mechanisms that make middle-aged women particularly vulnerable to obesity and metabolic disorders.

Reference: Van Der Steeg, W. et al. "Sex differences in insulin resistance in obesity." Obesity Reviews (2010).

4. Updating Scientific Terminology in the Background Section
We appreciate the suggestion regarding outdated terminology. The term "roughage" and other obsolete language will be revised to align with current scientific terminology.
5. Clarification on Double-Blinding and Study Design
There was an error in the original study design description. This study is not a double-blind study but rather an open-ended study. This design was chosen to facilitate a deeper understanding of the real-world effects of dietary interventions on obesity and insulin resistance in middle-aged women, where factors like adherence to the intervention and participant feedback play an essential role in the analysis.

6. Sample Size Discrepancy
The final sample size of 180 participants (90 per group) was determined based on power calculations for insulin resistance and BMI, accounting for a 15% dropout rate. To ensure appropriate representation, participants were stratified based on the prevalence of obesity and overweight, maintaining a 2:1 ratio, with a higher proportion of obese individuals, as obesity is more prevalent in the target population.

7. Clarification of Study Duration
The total duration of the intervention is 180 days (6 months) for the intervention group, with structured follow-ups to ensure adherence and assess outcomes. Participants receive customized dietary counseling on Day 1, followed by reinforcement sessions via telephone on Days 15, 30, and 60 to monitor compliance and provide necessary modifications. Outcome assessments are conducted on Day 90 and Day 180, where anthropometric, biochemical, and dietary data are collected. A motivational follow-up is done on Day 135 to encourage continued adherence. The control group follows the same assessment schedule but does not receive interim dietary modifications. This structured timeline ensures a comprehensive evaluation of the intervention’s impact while maintaining participant engagement.

8. Justification for the 20g Fiber Difference and Study Duration
The 20g difference in fiber intake between groups was selected based on existing dietary recommendations and evidence supporting its impact on weight management and metabolic health. The intervention group receives 40g of fiber per 2000 kcal, aligning with the Indian Council of Medical Research (ICMR) and National Institute of Nutrition (NIN) guidelines. In contrast, the control group follows a standard 25g fiber intake. This difference ensures a meaningful contrast while remaining practical for adherence.
The 180-day (6-month) intervention period was chosen to allow sufficient time for stabilizing dietary habits and for metabolic changes, such as improvements in insulin resistance and body composition, to be observed. The feasibility of increasing dietary fiber intake by 20g has been supported by our preliminary observational study (2019), which assessed fiber intake and obesity among 564 women. This study highlighted a significant negative correlation between fiber intake and BMI, reinforcing the need for a structured dietary intervention to promote increased fiber consumption.

9. Addressing Compliance Assessment Concerns
Compliance assessment in this study is not solely based on 24-hour dietary recall; multiple tools are incorporated to ensure accuracy and reliability. In addition to the 24-hour recall and food frequency questionnaire, a compliance checklist is used to track adherence to the prescribed dietary plan. Furthermore, patient opinions on the modified diet are collected to assess acceptability and feasibility. Regular reinforcement sessions (via telephone on Days 15, 30, and 60) further help monitor compliance and address challenges.

10. Consistency in Fiber Composition (Soluble vs. Insoluble)
The study ensures consistency in dietary fiber composition across participants by providing a structured, customized diet plan that proportions soluble and insoluble fiber appropriately. The dietary sources primarily include whole grains, legumes, vegetables, and fruits, providing a balanced fiber mix. While the metabolic effects of soluble and insoluble fiber can vary, the intervention is designed to reflect a realistic, well-balanced dietary intake, aligning with established dietary guidelines. This approach ensures that all participants receive a comparable fiber composition, minimizing variability in metabolic responses while maintaining dietary feasibility.
Competing Interests: No competing interests were disclosed. Close
Report a concern
Author Response 13 Oct 2025

Suvarna Hebbar, Clinical Nutrition and Dietetics, Manipal College of Health Professions, Manipal., 576104, India

13 Oct 2025

Author Response
. Clarity in Methods Section (Phase 1 & Phase 2 Separation)
Phase 1
Objective
The primary aim of Phase 1 is to screen middle-aged overweight and obese women to determine ... Continue reading
. Clarity in Methods Section (Phase 1 & Phase 2 Separation)
Phase 1
Objective
The primary aim of Phase 1 is to screen middle-aged overweight and obese women to determine the prevalence of insulin resistance.
Study Setting
This phase will be conducted in the Outpatient Departments (OPDs) of Medicine, Gynaecology, and Endocrinology at Kasturba Hospital, Manipal.
Sample Size & Selection

A total of 500 women will be screened to assess insulin resistance.

Participants will be categorized into two groups: overweight (BMI 23–24.9 kg/m²) and obese (BMI ≥ 25 kg/m²).

Each group will have at least 166 participants.

Inclusion Criteria

Women aged 35–55 years.

Willing to provide informed consent.

BMI ≥ 23 kg/m².

Exclusion Criteria

Women with conditions affecting nutritional status (e.g., tuberculosis, HIV, cancer, organ failure).

Women diagnosed with type 2 diabetes mellitus.

Individuals with hypertension, thyroid disorders, or any medical condition requiring medications affecting body weight (e.g., thyroxine, diuretics).

Pregnant or lactating women.

Women already on a weight-loss regime or consuming fiber above the recommended dietary allowance.

Women with contraindications for high fiber consumption (e.g., inflammatory bowel disease).

Data Collection Methods
Participants will undergo a baseline assessment, including:

Demographic Information: Age, education, occupation, income, marital history, place of residence, and family structure.

Anthropometric Measures: Height, weight, BMI, waist circumference, and hip circumference using standardized tools.

Biochemical Assessments:

Fasting blood glucose (hexokinase method).

HbA1c (TINA method).

Serum insulin (ECLIA).

Lipid profile (triglycerides, HDL, LDL, total cholesterol).

Dietary Assessment:

24-hour dietary recall and food frequency questionnaire analyzed using DietCal version 6.3.

Physical Activity Assessment:

Global Physical Activity Questionnaire (GPAQ).

Clinical Assessment: Evaluation of physical symptoms (e.g., bowel movement, satiety, leg pain, backache).

In-Depth Interviews

20 participants consuming low fiber (<20g/day) and 20 participants consuming moderate fiber (20-25g/day) will be interviewed telephonically for 45 minutes to assess barriers to fiber intake.

Phase 2: Randomized Controlled Trial (RCT)
Objective
To assess the impact of high dietary fiber intake (40g/day) on insulin resistance, body composition, and weight among overweight and obese women.
Study Design

Randomized, controlled trial.

Stratified Block Randomization (9 blocks of 20 participants each).

180 women will be randomized into:

Intervention Group (n=90): Receives 40g/day of fiber with dietary counselling.

Control Group (n=90): Receives 25g/day of fiber as part of a standard diet care plan.

Inclusion Criteria

Women from Phase 1 with abnormal HOMA-IR (>2), indicating insulin resistance.

Willing to adhere to a high-fiber diet if randomized to the intervention group.

Exclusion Criteria

Women unwilling to continue participation or adhere to the high-fiber diet.

Intervention & Control Groups
Intervention group
All women in the intervention arm will be counseled for about 15 minutes, and a customized diet chart consisting of high fiber of 40 grams will be provided. Nutritional empowerment on fiber shall be delivered to each woman enrolled. Necessary dietary advice on the modified diet plan and with a motivation to adhere to the diet plan will be communicated only to the intervention group. After the first counselling, on the 15th day, women will be telephonically assessed on their 24-hour recall dietary intake. On the 30th day, the women will be contacted telephonically again to record their 24-hour recall of their dietary intake. Necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 60th day, the women will be again telephonically contacted to record their 24-hour recall on their dietary intake, and necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat is analyzed using body fat analyzer and a questionnaire on patient opinion regarding modified diet plan shall be assessed as motivation and adherence towards fiber consumption subjects will be communicated telephonically on the 135th day. From the 136th to the 180th day, there shall not be any conversation regarding dietary modifications. On the 180th day, as a compliance-checking, the women will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data .24hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat analyzed using body fat analyzer and diet compliance on the modified diet plan shall be assessed.

Control group.
Women in the control arm will get a traditional diet care plan with 25gm of fiber according to their health condition. Necessary dietary advice will be communicated to the control group on the first visit to the hospital. There shall be no telephonic communication with the control group till the 90th day. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hour dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer. On the 180th day, as a compliance-checking, the patient will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer

Data Analysis

Repeated Measures ANOVA will be used to evaluate changes in insulin resistance, body composition, and weight over time.

SPSS v16.0 will be used for statistical analysis.

Ethical Considerations

Approval obtained from the Institutional Research Committee and Institutional Ethics Committee (IEC).

Trial registered with the Clinical Trials Registry of India (CTRI/2022/01/039074).

Informed consent was obtained from all participants.

CONTROL ARM

Day 1

Traditional/standard care
(patient will be called to OPD)

Day 15
Nil

Day 30
Nil

Day 60
Nil

Day 90
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

INTERVENTION ARM

Day 1

Intervention
(patient will be called to OPD)

Customize the individual-specific diet plan
Nutritional counseling
Impart nutritional empowerment on fiber consumption
Handover of diet plan

Day 15

Reinforcement
(through telephone)

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 30

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 60

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 90

Outcome assessment
(patient will be called to OPD)
Basic data:
Tool 2: 24-hour recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Patient opinion on a modified diet
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

Day 135

Reinforcement (through telephone)

Motivation to follow customised diet plan

Day 180

Checking compliance
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Compliance checklist
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyser:
Visceral fat, S/C fat, muscle mass

Day 135
Nil

Day180
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ

Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyser:
Visceral fat, S/C fat, muscle mass

3. Rationale for Sex-Specific Differences and Justification for a Single-Sex Study
This study is specifically designed for women’s health, as obesity and insulin resistance present distinct physiological and hormonal influences in females. The decision to focus on middle-aged women was based on prior evidence suggesting unique metabolic responses to dietary interventions in this demographic.
López, M. et al. (2016) - "Menopause, obesity, and insulin resistance: An emerging paradigm"

This study specifically explores the impact of menopause on metabolic health, highlighting the increased risk of insulin resistance and obesity in women as they transition through menopause. It aligns with your focus on middle-aged women and the unique metabolic responses they experience.

Reference: López, M. et al. "Menopause, obesity, and insulin resistance: An emerging paradigm." Endocrinology (2016).

Van Der Steeg, W. et al. (2010) - "Sex differences in insulin resistance in obesity"

This study investigates how hormonal factors, especially estrogen, affect insulin resistance and fat distribution differently in women, providing key insights into the sex-specific mechanisms that make middle-aged women particularly vulnerable to obesity and metabolic disorders.

Reference: Van Der Steeg, W. et al. "Sex differences in insulin resistance in obesity." Obesity Reviews (2010).

4. Updating Scientific Terminology in the Background Section
We appreciate the suggestion regarding outdated terminology. The term "roughage" and other obsolete language will be revised to align with current scientific terminology.
5. Clarification on Double-Blinding and Study Design
There was an error in the original study design description. This study is not a double-blind study but rather an open-ended study. This design was chosen to facilitate a deeper understanding of the real-world effects of dietary interventions on obesity and insulin resistance in middle-aged women, where factors like adherence to the intervention and participant feedback play an important role in the analysis.

6. Sample Size Discrepancy
The final sample size of 180 participants (90 per group) was determined based on power calculations for insulin resistance and BMI, accounting for a 15% dropout rate. To ensure appropriate representation, participants were stratified based on the prevalence of obesity and overweight, maintaining a 2:1 ratio, with a higher proportion of obese individuals, as obesity is more prevalent in the target population.

7. Clarification of Study Duration
The total duration of the intervention is 180 days (6 months) for the intervention group, with structured follow-ups to ensure adherence and assess outcomes. Participants receive customized dietary counseling on Day 1, followed by reinforcement sessions via telephone on Days 15, 30, and 60 to monitor compliance and provide necessary modifications. Outcome assessments are conducted on Day 90 and Day 180, where anthropometric, biochemical, and dietary data are collected. A motivational follow-up is done on Day 135 to encourage continued adherence. The control group follows the same assessment schedule but does not receive interim dietary modifications. This structured timeline ensures a comprehensive evaluation of the intervention’s impact while maintaining participant engagement.

8. Justification for the 20g Fiber Difference and Study Duration
The 20g difference in fiber intake between groups was selected based on existing dietary recommendations and evidence supporting its impact on weight management and metabolic health. The intervention group receives 40g of fiber per 2000 kcal, aligning with the Indian Council of Medical Research (ICMR) and National Institute of Nutrition (NIN) guidelines. In contrast, the control group follows a standard 25g fiber intake. This difference ensures a meaningful contrast while remaining practical for adherence.
The 180-day (6-month) intervention period was chosen to allow sufficient time for stabilizing dietary habits and for metabolic changes, such as improvements in insulin resistance and body composition, to be observed. The feasibility of increasing dietary fiber intake by 20g has been supported by our preliminary observational study (2019), which assessed fiber intake and obesity among 564 women. This study highlighted a significant negative correlation between fiber intake and BMI, reinforcing the need for a structured dietary intervention to promote increased fiber consumption.

9. Addressing Compliance Assessment Concerns
Compliance assessment in this study is not solely based on 24-hour dietary recall; multiple tools are incorporated to ensure accuracy and reliability. In addition to the 24-hour recall and food frequency questionnaire, a compliance checklist is used to track adherence to the prescribed dietary plan. Furthermore, patient opinions on the modified diet are collected to assess acceptability and feasibility. Regular reinforcement sessions (via telephone on Days 15, 30, and 60) further help monitor compliance and address challenges.

10. Consistency in Fiber Composition (Soluble vs. Insoluble)
The study ensures consistency in dietary fiber composition across participants by providing a structured, customized diet plan that appropriately proportions soluble and insoluble fiber. The dietary sources primarily include whole grains, legumes, vegetables, and fruits, providing a balanced fiber mix. While the metabolic effects of soluble and insoluble fiber can vary, the intervention is designed to reflect a realistic, well-balanced dietary intake, aligning with established dietary guidelines. This approach ensures that all participants receive a comparable fiber composition, minimizing variability in metabolic responses while maintaining dietary feasibility.
. Clarity in Methods Section (Phase 1 & Phase 2 Separation)
Phase 1
Objective
The primary aim of Phase 1 is to screen middle-aged overweight and obese women to determine the prevalence of insulin resistance.
Study Setting
This phase will be conducted in the Outpatient Departments (OPDs) of Medicine, Gynaecology, and Endocrinology at Kasturba Hospital, Manipal.
Sample Size & Selection

A total of 500 women will be screened to assess insulin resistance.

Participants will be categorized into two groups: overweight (BMI 23–24.9 kg/m²) and obese (BMI ≥ 25 kg/m²).

Each group will have at least 166 participants.

Inclusion Criteria

Women aged 35–55 years.

Willing to provide informed consent.

BMI ≥ 23 kg/m².

Exclusion Criteria

Women with conditions affecting nutritional status (e.g., tuberculosis, HIV, cancer, organ failure).

Women diagnosed with type 2 diabetes mellitus.

Individuals with hypertension, thyroid disorders, or any medical condition requiring medications affecting body weight (e.g., thyroxine, diuretics).

Pregnant or lactating women.

Women already on a weight-loss regime or consuming fiber above the recommended dietary allowance.

Women with contraindications for high fiber consumption (e.g., inflammatory bowel disease).

Data Collection Methods
Participants will undergo a baseline assessment, including:

Demographic Information: Age, education, occupation, income, marital history, place of residence, and family structure.

Anthropometric Measures: Height, weight, BMI, waist circumference, and hip circumference using standardized tools.

Biochemical Assessments:

Fasting blood glucose (hexokinase method).

HbA1c (TINA method).

Serum insulin (ECLIA).

Lipid profile (triglycerides, HDL, LDL, total cholesterol).

Dietary Assessment:

24-hour dietary recall and food frequency questionnaire analyzed using DietCal version 6.3.

Physical Activity Assessment:

Global Physical Activity Questionnaire (GPAQ).

Clinical Assessment: Evaluation of physical symptoms (e.g., bowel movement, satiety, leg pain, backache).

In-Depth Interviews

20 participants consuming low fiber (<20g/day) and 20 participants consuming moderate fiber (20-25g/day) will be interviewed telephonically for 45 minutes to assess barriers to fiber intake.

Phase 2: Randomized Controlled Trial (RCT)
Objective
To assess the impact of high dietary fiber intake (40g/day) on insulin resistance, body composition, and weight among overweight and obese women.
Study Design

Randomized, controlled trial.

Stratified Block Randomization (9 blocks of 20 participants each).

180 women will be randomized into:

Intervention Group (n=90): Receives 40g/day of fiber with dietary counselling.

Control Group (n=90): Receives 25g/day of fiber as part of a standard diet care plan.

Inclusion Criteria

Women from Phase 1 with abnormal HOMA-IR (>2), indicating insulin resistance.

Willing to adhere to a high-fiber diet if randomized to the intervention group.

Exclusion Criteria

Women unwilling to continue participation or adhere to the high-fiber diet.

Intervention & Control Groups
Intervention group
All women in the intervention arm will be counseled for about 15 minutes, and a customized diet chart consisting of high fiber of 40 grams will be provided. Nutritional empowerment on fiber shall be delivered to each woman enrolled. Necessary dietary advice on the modified diet plan and with a motivation to adhere to the diet plan will be communicated only to the intervention group. After the first counselling, on the 15th day, women will be telephonically assessed on their 24-hour recall dietary intake. On the 30th day, the women will be contacted telephonically again to record their 24-hour recall of their dietary intake. Necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 60th day, the women will be again telephonically contacted to record their 24-hour recall on their dietary intake, and necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat is analyzed using body fat analyzer and a questionnaire on patient opinion regarding modified diet plan shall be assessed as motivation and adherence towards fiber consumption subjects will be communicated telephonically on the 135th day. From the 136th to the 180th day, there shall not be any conversation regarding dietary modifications. On the 180th day, as a compliance-checking, the women will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data .24hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat analyzed using body fat analyzer and diet compliance on the modified diet plan shall be assessed.

Control group.
Women in the control arm will get a traditional diet care plan with 25gm of fiber according to their health condition. Necessary dietary advice will be communicated to the control group on the first visit to the hospital. There shall be no telephonic communication with the control group till the 90th day. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hour dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer. On the 180th day, as a compliance-checking, the patient will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer

Data Analysis

Repeated Measures ANOVA will be used to evaluate changes in insulin resistance, body composition, and weight over time.

SPSS v16.0 will be used for statistical analysis.

Ethical Considerations

Approval obtained from the Institutional Research Committee and Institutional Ethics Committee (IEC).

Trial registered with the Clinical Trials Registry of India (CTRI/2022/01/039074).

Informed consent was obtained from all participants.

CONTROL ARM

Day 1

Traditional/standard care
(patient will be called to OPD)

Day 15
Nil

Day 30
Nil

Day 60
Nil

Day 90
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

INTERVENTION ARM

Day 1

Intervention
(patient will be called to OPD)

Customize the individual-specific diet plan
Nutritional counseling
Impart nutritional empowerment on fiber consumption
Handover of diet plan

Day 15

Reinforcement
(through telephone)

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 30

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 60

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 90

Outcome assessment
(patient will be called to OPD)
Basic data:
Tool 2: 24-hour recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Patient opinion on a modified diet
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

Day 135

Reinforcement (through telephone)

Motivation to follow customised diet plan

Day 180

Checking compliance
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Compliance checklist
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyser:
Visceral fat, S/C fat, muscle mass

Day 135
Nil

Day180
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ

Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyser:
Visceral fat, S/C fat, muscle mass

3. Rationale for Sex-Specific Differences and Justification for a Single-Sex Study
This study is specifically designed for women’s health, as obesity and insulin resistance present distinct physiological and hormonal influences in females. The decision to focus on middle-aged women was based on prior evidence suggesting unique metabolic responses to dietary interventions in this demographic.
López, M. et al. (2016) - "Menopause, obesity, and insulin resistance: An emerging paradigm"

This study specifically explores the impact of menopause on metabolic health, highlighting the increased risk of insulin resistance and obesity in women as they transition through menopause. It aligns with your focus on middle-aged women and the unique metabolic responses they experience.

Reference: López, M. et al. "Menopause, obesity, and insulin resistance: An emerging paradigm." Endocrinology (2016).

Van Der Steeg, W. et al. (2010) - "Sex differences in insulin resistance in obesity"

This study investigates how hormonal factors, especially estrogen, affect insulin resistance and fat distribution differently in women, providing key insights into the sex-specific mechanisms that make middle-aged women particularly vulnerable to obesity and metabolic disorders.

Reference: Van Der Steeg, W. et al. "Sex differences in insulin resistance in obesity." Obesity Reviews (2010).

4. Updating Scientific Terminology in the Background Section
We appreciate the suggestion regarding outdated terminology. The term "roughage" and other obsolete language will be revised to align with current scientific terminology.
5. Clarification on Double-Blinding and Study Design
There was an error in the original study design description. This study is not a double-blind study but rather an open-ended study. This design was chosen to facilitate a deeper understanding of the real-world effects of dietary interventions on obesity and insulin resistance in middle-aged women, where factors like adherence to the intervention and participant feedback play an important role in the analysis.

6. Sample Size Discrepancy
The final sample size of 180 participants (90 per group) was determined based on power calculations for insulin resistance and BMI, accounting for a 15% dropout rate. To ensure appropriate representation, participants were stratified based on the prevalence of obesity and overweight, maintaining a 2:1 ratio, with a higher proportion of obese individuals, as obesity is more prevalent in the target population.

7. Clarification of Study Duration
The total duration of the intervention is 180 days (6 months) for the intervention group, with structured follow-ups to ensure adherence and assess outcomes. Participants receive customized dietary counseling on Day 1, followed by reinforcement sessions via telephone on Days 15, 30, and 60 to monitor compliance and provide necessary modifications. Outcome assessments are conducted on Day 90 and Day 180, where anthropometric, biochemical, and dietary data are collected. A motivational follow-up is done on Day 135 to encourage continued adherence. The control group follows the same assessment schedule but does not receive interim dietary modifications. This structured timeline ensures a comprehensive evaluation of the intervention’s impact while maintaining participant engagement.

8. Justification for the 20g Fiber Difference and Study Duration
The 20g difference in fiber intake between groups was selected based on existing dietary recommendations and evidence supporting its impact on weight management and metabolic health. The intervention group receives 40g of fiber per 2000 kcal, aligning with the Indian Council of Medical Research (ICMR) and National Institute of Nutrition (NIN) guidelines. In contrast, the control group follows a standard 25g fiber intake. This difference ensures a meaningful contrast while remaining practical for adherence.
The 180-day (6-month) intervention period was chosen to allow sufficient time for stabilizing dietary habits and for metabolic changes, such as improvements in insulin resistance and body composition, to be observed. The feasibility of increasing dietary fiber intake by 20g has been supported by our preliminary observational study (2019), which assessed fiber intake and obesity among 564 women. This study highlighted a significant negative correlation between fiber intake and BMI, reinforcing the need for a structured dietary intervention to promote increased fiber consumption.

9. Addressing Compliance Assessment Concerns
Compliance assessment in this study is not solely based on 24-hour dietary recall; multiple tools are incorporated to ensure accuracy and reliability. In addition to the 24-hour recall and food frequency questionnaire, a compliance checklist is used to track adherence to the prescribed dietary plan. Furthermore, patient opinions on the modified diet are collected to assess acceptability and feasibility. Regular reinforcement sessions (via telephone on Days 15, 30, and 60) further help monitor compliance and address challenges.

10. Consistency in Fiber Composition (Soluble vs. Insoluble)
The study ensures consistency in dietary fiber composition across participants by providing a structured, customized diet plan that appropriately proportions soluble and insoluble fiber. The dietary sources primarily include whole grains, legumes, vegetables, and fruits, providing a balanced fiber mix. While the metabolic effects of soluble and insoluble fiber can vary, the intervention is designed to reflect a realistic, well-balanced dietary intake, aligning with established dietary guidelines. This approach ensures that all participants receive a comparable fiber composition, minimizing variability in metabolic responses while maintaining dietary feasibility.
Competing Interests: No competing interests were disclosed. Close
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Gary Frost, Imperial College London, London, UK
Hendriek C Boshuizen, Wageningen University and Research, Wageningen, The Netherlands
Tatiana Palotta Minari, Federal University of São Paulo (UNIFESP), Santos, Brazil
Debasrita Banerjee, Medhavi Skills University (School of Health Sciences & Technology, Singtam, India

Ravi Yadav, Medhavi Skills University, Singtam, India

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10 Apr 2026 | for Version 4

Tatiana Palotta Minari, Federal University of São Paulo (UNIFESP), Santos, Brazil

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Approved

Well done. Approved.

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

This article connects with my area of research because it sits at the intersection of nutrition, metabolism, and women’s health. The study protocol focuses on how dietary fiber intake influences insulin resistance, body composition, and weight in overweight and obese middle-aged women.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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Reviewer Report

12 Views

16 Apr 2026 | for Version 3

Debasrita Banerjee, Medhavi Skills University (School of Health Sciences & Technology, Singtam, Sikkim, India

Ravi Yadav, Anesthesia Operation Theater Technology, Medhavi Skills University, Singtam, Sikkim, India

12 Views Cite this report Responses(1)

Not Approved

Is the rationale for, and objectives of, the study clearly described?

Partly
Is the study design appropriate for the research question?

Partly
Are sufficient details of the methods provided to allow replication by others?

Partly
Are the datasets clearly presented in a useable and accessible format?

Not applicable

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Clinical Nutrition and Functional Foods

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Author Response

24 Apr 2026

Suvarna Hebbar, Clinical Nutrition and Dietetics, Manipal College of Health Professions, Manipal., 576104, India

Response to Reviewer
Methodological Concerns

The reliance on a single 24-hour dietary recall in Phase 1 is insufficient to accurately capture participants' habitual fiber intake. A validated Food Frequency Questionnaire (FFQ) should be implemented during this initial screening phase to mitigate recall bias. Additionally, while the targeted difference in fiber intake between groups was reduced to 15g, the sample size calculation remains unadjusted for this potentially smaller effect size.
Response:
We thank the reviewer for these valuable methodological suggestions. We acknowledge that a single 24-hour dietary recall may not fully capture habitual dietary intake at the individual level. However, in Phase 1 the primary objective is screening and estimating general dietary patterns among a large sample of participants rather than assessing precise long-term nutrient intake. A single 24-hour dietary recall is widely used in epidemiological screening studies to estimate mean group intake when collected from a sufficiently large and heterogeneous population; therefore, it was considered appropriate for the initial screening phase involving approximately 500 participants. To strengthen dietary assessment in the intervention phase, the protocol has been modified so that in Phase 2 dietary intake will be assessed using multiple 24-hour dietary recalls at follow-up time points along with a Food Frequency Questionnaire (FFQ) to better capture habitual intake patterns. Nutrient intake will be analyzed using DietCal software based on standardized Indian food composition tables, which will further improve the reliability of dietary assessment while maintaining feasibility during the large screening phase. In addition, we appreciate the reviewer’s observation regarding the targeted difference in dietary fiber intake between groups being reduced to 15 g/day. The sample size calculation for Phase 2 was not based on the absolute difference in fiber intake but on the expected effect on the primary clinical outcomes, specifically insulin resistance (HOMA-IR) and body mass index (BMI). The power calculation used anticipated standard deviation values derived from previously published intervention studies and the clinically meaningful difference expected for BMI and insulin resistance. Because the calculation was based on changes in these metabolic outcomes rather than fiber intake itself, the reduction in the planned fiber difference from 20 g/day to 15 g/day does not alter the expected clinically meaningful effect on the primary endpoints; therefore, the required sample size remains appropriate and unchanged.

Intervention and Adherence
The active dietary counseling required to reach the 40g daily fiber target makes any claim of blinding impossible, rendering the study an open-label trial. Furthermore, expecting participants to maintain such a high fiber intake from whole foods over six months introduces a severe risk of non-compliance and dropout. The intervention also fails to control for the varying ratios of soluble to insoluble fiber inherent in whole foods, which risks confounding the metabolic outcomes.
Response:
We thank the reviewer for these important observations. We agree that complete blinding is not feasible in dietary behavioral interventions that involve active counseling and individualized dietary guidance; therefore, the study should be considered an open-label randomized controlled trial. This approach is common in nutrition intervention research where participants are required to actively modify their dietary behavior. To minimize potential bias, randomization and allocation concealment will be implemented using stratified block randomization and opaque sealed envelopes. In addition, the primary outcomes are objective measures, including biochemical parameters such as fasting glucose, HbA1c, serum insulin, lipid profile, and body composition analysis, which helps reduce measurement bias despite the open-label design.

We also acknowledge that maintaining a dietary fiber intake of approximately 40 g/day over six months may pose adherence challenges and could potentially increase the risk of non-compliance or dropout. To enhance participant adherence and minimize attrition, several strategies have been incorporated into the protocol, including individualized dietary counseling, customized high-fiber diet charts based on locally available foods, regular telephonic follow-up, dietary tracking sheets, fiber intake compliance checklists, and continuous motivation and reinforcement during follow-up visits. These strategies are widely used in dietary intervention studies and are expected to support sustained compliance throughout the intervention period.

Regarding the concern about varying ratios of soluble and insoluble fiber in whole foods potentially confounding metabolic outcomes, we acknowledge that whole foods naturally contain different proportions of fiber types. However, the primary objective of the study is to evaluate the effect of increasing total dietary fiber intake from whole foods under real-world dietary conditions rather than isolating specific fiber fractions. This approach improves the ecological validity and practical applicability of the findings. Furthermore, dietary intake will be assessed using 24-hour dietary recalls and a Food Frequency Questionnaire (FFQ), which allows estimation of total dietary fiber intake and helps account for dietary variability. Collectively, this design enables the study to evaluate the metabolic effects of increasing total dietary fiber intake within a realistic dietary context.

Manuscript Formatting Issues
The manuscript title contains a prominent typographical error, referring to the study as a "randomized controlled trail" rather than a "trial". The introduction lacks logical flow, occasionally relies on outdated terminology, and inappropriately uses bullet points instead of cohesive academic paragraphs in key sections. A thorough structural revision and professional proofread are necessary to elevate the manuscript to scientific publication standards.
Response:
We thank the reviewer for carefully identifying these formatting and structural issues. The typographical error in the manuscript title has been corrected from “randomized controlled trail” to “randomized controlled trial.” In addition, the Introduction section has been thoroughly revised to improve the logical flow and coherence of the background information. Outdated terminology has been updated where appropriate, and bullet points previously used in narrative sections have been replaced with structured academic paragraphs to maintain consistency with scientific writing standards. Furthermore, the entire manuscript has undergone careful proofreading and structural revision to enhance clarity, readability, and overall presentation in accordance with journal publication standards.

Lack of Justification for a Single-Sex Study:
The original protocol failed to adequately explain why the study is restricted exclusively to middle-aged women. While the authors later cited menopause and estrogen-related metabolic changes in their response, this fundamental rationale was missing from the protocol's background.
Response:
We thank the reviewer for highlighting this important point. We acknowledge that the initial protocol did not sufficiently explain the rationale for restricting the study to middle-aged women, and this has now been clarified in the revised background section. Middle-aged women represent a population at increased risk of metabolic disorders due to hormonal changes associated with the menopausal transition. During this period, declining estrogen levels are associated with increased visceral adiposity, alterations in body composition, and reduced insulin sensitivity, all of which contribute to a higher risk of overweight, obesity, and metabolic disturbances. These physiological and metabolic changes make middle-aged women a particularly relevant population for examining the potential benefits of dietary interventions such as increased dietary fiber intake on insulin resistance and body composition. Accordingly, the revised manuscript now clearly states this sex-specific rationale in the background section to justify the focus on middle-aged women.

Missed Opportunity for a Crossover Design:
The authors did not consider a crossover design. In dietary studies where blinding is impossible and inter-individual variability is high, having participants act as their own controls (by switching between the 25g and 40g diets) could have significantly strengthened the evidence.
Response:
We acknowledge that crossover designs can reduce inter-individual variability in dietary studies by allowing participants to serve as their own controls. However, a crossover design was not considered appropriate for the present study due to several practical and methodological considerations. First, the intervention period in this study is relatively long (6 months), and implementing a crossover design would require an additional intervention phase along with an adequate washout period to minimize carryover effects, which would substantially extend the total study duration. Second, repeated switching between dietary patterns (from 25 g to 40 g fiber intake and vice versa) may be challenging for participants and could negatively influence adherence to the prescribed diet. Therefore, a parallel randomized controlled trial design was considered more feasible and appropriate for evaluating the long-term effects of increased dietary fiber intake in this population.

Vague Secondary Objectives:
The secondary objective, stated simply as "To assess the opinions of women on modified fiber intake," was heavily criticized for being too vague and lacking specific, measurable parameters.
Response:
Thank you for your valuable comment. It was operationalized using a structured, dichotomous (yes/no) questionnaire administered at predefined time points (30th, 90th, and 180th day). Each item captured specific, measurable aspects of participant opinion, including acceptance of modified fiber intake, perceived ease of implementation, and willingness to continue the dietary changes. The use of binary responses ensured quantifiability, while repeated assessments enabled longitudinal tracking of changes in opinion and compliance over time.

Missing Justification for Variables:
The authors plugged specific numbers into their power calculation (like standard deviations of 3.96 for BMI and 5.06 for insulin resistance) but initially failed to justify where these specific estimates came from or why they represented a "clinically significant difference".
Response:
We thank the reviewer for highlighting the need to justify the parameters used in the sample size calculation. In the revised manuscript, we have clarified the source and rationale for the values used in the power calculation. The estimates for the standard deviation (σ) of BMI (3.96) and insulin resistance (5.06) were derived from previously published intervention studies examining the effects of dietary or lifestyle interventions on metabolic outcomes in similar adult populations. These values were selected as they represent realistic variability observed in comparable studies. The minimum detectable difference (d) was chosen based on changes considered clinically meaningful in the context of improvements in BMI and insulin resistance following dietary interventions. Thus, the parameters used in the sample size calculation were selected to ensure adequate statistical power to detect clinically relevant changes in the primary outcomes. These details and supporting references have now been added to the Methods section to improve transparency and clarity of the sample size estimation.

Unproven Feasibility of the Intervention:
Increasing a patient's dietary fiber by an additional 15g to 20g per day exclusively through whole foods is notoriously difficult. Reviewers questioned whether the research team had any pilot data proving they could successfully achieve and sustain this massive leap in fiber intake over 6 months.
Response:
We thank the reviewer for raising this important concern regarding the feasibility of achieving and sustaining an increased dietary fiber intake through whole foods. Prior to initiating the intervention, preliminary observations from our earlier dietary assessment conducted among middle-aged women in the same clinical setting indicated that many participants were consuming substantially lower amounts of dietary fiber than recommended levels. Therefore, the intervention was designed to increase fiber intake gradually through locally available, culturally acceptable high fiber foods such as whole grains, legumes, fruits, and vegetables, rather than relying on fiber supplements. In addition, participants in the intervention group receive individualized dietary counseling, a customized high fiber diet plan, and regular follow-up reinforcement through telephonic monitoring, which are intended to facilitate adherence and support gradual dietary modification over time. These strategies were incorporated to improve the feasibility and sustainability of achieving the targeted fiber intake.

No Objective Compliance Biomarkers:
Despite the known flaws of self-reported dietary recalls and food frequency questionnaires, the study lacks any objective physiological markers to prove participants actually ate the fiber (such as stool weight, transit time, or specific microbiome metabolite markers). Adding a "compliance checklist" does not solve the fundamental issue of subjective reporting.
Response:
We thank the reviewer for this important observation. We agree that objective biomarkers can strengthen the assessment of dietary compliance in nutrition intervention studies. However, the inclusion of objective biomarkers such as stool analysis (e.g., stool weight, transit time, or microbial metabolites) or other microbiome-related markers was not feasible in the present study. During the planning phase, the possibility of incorporating stool analysis was considered; however, participants expressed reluctance and practical concerns regarding stool sample collection, which posed challenges for participant acceptance and compliance in a community-based dietary intervention study. Additionally, logistical and resource constraints limited the feasibility of conducting microbiome or metabolite analysis. Furthermore, the absence of objective biomarkers such as stool analysis has now been acknowledged as a limitation in the manuscript.

Confusing Protocol Structure:
Reviewers found the methodology highly confusing because Phase 1 (the screening phase) and Phase 2 (the randomized trial) were jumbled together without clear separation or a concise timeline.
Response:
Thank you for this observation. In response, Phase 1 (screening phase) and Phase 2 (randomized controlled trial) have now been clearly delineated and described as distinct components of the study. This separation was initially clarified in Version 1 of the revised manuscript, and the same structured presentation has been consistently maintained and further refined in subsequent versions. Additionally, the methodology section has been reorganized to improve clarity, with a more explicit description of the study flow and timeline for each phase to avoid any overlap or confusion.

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Reviewer Report

12 Views

19 Mar 2026 | for Version 3

Tatiana Palotta Minari, Federal University of São Paulo (UNIFESP), Santos, Brazil

12 Views Cite this report Responses(1)

Approved With Reservations

Suggestions for Improvement

Reduce redundancy in the introduction and discussion to improve readability and maintain focus.
Present the sample size calculation formula in a clearer and more legible format, ensuring that readers can easily follow the computation steps.
Discuss more explicitly the impact of additional counseling in the intervention group, as this behavioral support may influence outcomes beyond dietary fiber intake.
Include a detailed adherence analysis plan, such as a checklist or monitoring tool to assess actual fiber consumption and compliance with the dietary recommendations.
Consider incorporating measures of gut microbiota, since the study rationale emphasizes the role of fiber in modulating intestinal bacteria and metabolic health.

Is the rationale for, and objectives of, the study clearly described?

Yes
Is the study design appropriate for the research question?

Yes
Are sufficient details of the methods provided to allow replication by others?

Yes
Are the datasets clearly presented in a useable and accessible format?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Respond to this report

Responses (1)

Author Response

08 Apr 2026

Suvarna Hebbar, Clinical Nutrition and Dietetics, Manipal College of Health Professions, Manipal., 576104, India

Reduce redundancy in the introduction and discussion to improve readability and maintain focus.
Background
Obesity is a major public health concern worldwide. Urbanization, economic growth, changing lifestyles, and dietary habits have contributed to a “double burden” of diseases in rapidly developing low- and middle-income countries such as India¹. The average dietary fiber intake is below the recommended levels, and the World Health Organization estimates that the incidence of obesity has increased globally in the past decade. Many individuals do not consume adequate fiber to meet recommended intakes, and obese women often report lower dietary fiber consumption compared with normal-weight individuals. ²
Dietary fiber plays an important role in appetite regulation and weight management. Fiber-rich foods promote satiety and reduce hunger by delaying gastric emptying and increasing stomach fullness.³ These effects are particularly evident among individuals with obesity.⁴ In addition, dietary fiber consumption promotes the growth of beneficial bacteria in the colon, which may help prevent obesity, metabolic syndrome, and adverse intestinal changes.⁵
High-fiber diets are associated with improved health outcomes and a reduced risk of several chronic diseases. Fiber-rich foods typically have lower energy density and can replace high-fat, energy-dense foods in the diet. Increased dietary fiber intake has been linked with improvements in serum lipoproteins, blood pressure, blood glucose control, and body weight. Individuals consuming adequate fiber are at lower risk of coronary artery disease, stroke, hypertension, diabetes, obesity, and gastrointestinal disorders. In addition, soluble fiber intake has been shown to enhance immune function. ⁶
Dietary fiber obtained from fruits, vegetables, legumes, and whole grains provides several physiological benefits and is associated with a lower risk of chronic diseases such as cardiovascular disease, type 2 diabetes mellitus, obesity, and certain cancers. These foods also provide micronutrients and phytochemicals that contribute to overall health, highlighting the importance of promoting adequate dietary fiber intake in the population.⁷
However, limited research has examined the role of dietary fiber specifically in the treatment and management of obesity, and further studies are required to strengthen the evidence linking dietary fiber intake with obesity-related outcomes.⁸ Dietary fiber also promotes the growth of beneficial gut bacteria and supports microbial balance. Increased consumption of dietary fiber and whole grains enhances the growth of beneficial intestinal microbiota, which may be particularly relevant in individuals with obesity and other metabolic disorders. However, these effects may vary depending on the type, structure, and composition of the fiber and whole-grain sources.⁹
High-fiber foods are more satiating and contribute to appetite control by influencing gastric emptying, reducing food intake, and promoting a sense of fullness.¹⁰ Fermentation of dietary fiber in the colon produces short-chain fatty acids that regulate appetite through gut hormones such as cholecystokinin and glucagon-like peptides, which help reduce hunger and increase satiety.¹¹ Increased chewing and gastric distension associated with fiber-rich foods may further enhance satiety and regulate food intake.¹²
This study focuses on weight reduction through increased dietary fiber consumption. According to the Indian Council of Medical Research and National Institute of Nutrition guidelines, the recommended dietary fiber intake is 40 g per 2000 kcal of energy intake.¹³ Increasing dietary fiber consumption to recommended levels may support weight management and improve overall metabolic health.
Discussion
Evidence on the association between dietary fiber intake and metabolic outcomes among overweight and obese middle-aged women in India remains limited. This study aimed to examine whether increased dietary fiber intake can improve insulin resistance, body composition, and weight in this population. Dietary fiber provides several metabolic benefits, including enhanced satiety, improved glycemic control, reduced cholesterol levels, and increased fat oxidation. By lowering energy intake and supporting metabolic regulation, adequate fiber consumption may contribute to effective weight management. In addition to dietary intervention, participants in the intervention group received regular dietary counseling, which may have improved adherence to the recommended dietary practices and encouraged healthier lifestyle behaviors. Therefore, the observed improvements in metabolic indicators and body composition may reflect the combined influence of increased dietary fiber intake and the supportive role of counseling in promoting sustained dietary and behavioral changes.

Present the sample size calculation formula in a clearer and more legible format, ensuring that readers can easily follow the computation steps.
Sample Size Calculation
The sample size was calculated using the following formula:
n=(2(Z_(1-α/2)+Z_(1-β) )^2 σ^2 [1+(m-1)ρ])/(md^2 )

Where:
            n = sample size per group
            Z₁₋α/₂ = 1.96 (for α = 0.05, two-tailed test)
            Z₁₋β = 0.84 (for 80% statistical power)
            σ = anticipated population standard deviation of the outcome variable
            d = clinically significant difference (effect size)
            m = number of time points/follow-ups (m = 2)
            ρ = intraclass correlation coefficient (ρ = 0.4)
Computation for BMI
Parameters used:
            σ = 3.96
            d = 1.5
            m = 2
            ρ = 0.4
Step 1: Substitute values into the formula
n=(2(1.96+0.84)^2 (3.96)^2 [1+(2-1)×0.4])/(2(1.5)^2 )
Step 2: Simplify
n=(2(2.8)^2 (15.68)(1.4))/(2(2.25))
Step 3: Final estimate
n≈77" participants per group"
Adjustment for 15% dropout rate:
n=77/(1-0.15)=90
Therefore, 90 participants per group were required.

Computation for Insulin Resistance
Parameters used:
            σ = 5.06
            d = 2
            m = 2
            ρ = 0.4
Step 1: Substitute values
n=(2(1.96+0.84)^2 (5.06)^2 [1+(2-1)×0.4])/(2(2)^2 )
Step 2: Simplify
n=(2(2.8)^2 (25.60)(1.4))/(2(4))
Step 3: Final estimate
n≈71" participants per group"
Adjustment for 15% dropout rate:
n=71/(1-0.15)=83
Thus, 83 participants per group were required.

Include a detailed adherence analysis plan, such as a checklist or monitoring tool to assess actual fiber consumption and compliance with the dietary recommendations.
Women with no contraindications to high dietary fiber consumption and abnormal HOMA-IR will be included in Phase 2 of the study. Baseline assessments will be conducted for both intervention and control groups. Demographic information including age, religion, place of residence, type of family, number of family members, marital status, education, occupation, and income will be collected using a structured proforma. Anthropometric measurements such as height (stadiometer), body weight (weighing scale), and waist and hip circumference will be recorded in the outpatient department. Biochemical parameters including fasting blood glucose (hexokinase method), HbA1c (TINA method), serum insulin (ECLIA), and lipid profile (triglycerides GPO Trinder method, HDL direct homogeneous method, LDL enzymatic method, and total cholesterol CE-CHOD-POD method) will be assessed. Dietary intake will be assessed using a 24-hour dietary recall and a Food Frequency Questionnaire (FFQ), and nutrient intake will be analyzed using DietCal software version 6.3. Adherence to dietary fiber intervention will be monitored using multiple strategies, including a tracking sheet to record daily intake of fiber-rich foods and a fiber intake compliance checklist during follow-up visits. Monthly telephonic follow-ups will be conducted to reinforce dietary counseling, evaluate adherence to the recommended dietary practices, and address any challenges faced by participants. Participants’ feedback on high-fiber food consumption will also be documented to identify adherence patterns and potential barriers, ensuring systematic monitoring of dietary fiber intake and compliance with the intervention throughout the study period. Physical activity levels will be assessed using the Global Physical Activity Questionnaire (GPAQ), and body composition parameters including visceral fat, subcutaneous fat, and muscle mass will be measured using a body fat analyzer. Clinical assessment will also be performed to document physical complaints reported by participants.


Consider incorporating measures of gut microbiota, since the study rationale emphasizes the role of fiber in modulating intestinal bacteria and metabolic health
Although dietary fiber is known to influence metabolic health through modulation of gut microbiota, gut microbial composition was not assessed in this study, which primarily focused on clinical and metabolic outcomes such as insulin resistance, body composition, and weight. Future studies incorporating microbiome analysis may provide better insight into the mechanisms linking dietary fiber intake with metabolic health

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Reviewer Report

23 Views

11 Dec 2025 | for Version 2

Hendriek C Boshuizen, Wageningen University and Research, Wageningen, The Netherlands

23 Views Cite this report Responses(1)

Not Approved

The second secondary objective is not specific enough. Opinion on what?
In phase 1 I have doubt whether a single 24 hour recall is adequate to determine usual intake. I wonder whether a food frequency questionnaire designed for measuring fiber intake would not be more suitable. Is there evidence to support that a single 24 hour recall gives a sufficiently accurate estimate of usual intake of fiber?
Are 500 participants in phase 1 enough to provide 180 participants who agree to being randomized in phase 2? This is not explained clearly.
It is not clear to me what is meant by “The sample size was calculated in accordance with insulin resistance and BMI.” Please give more details on the sample size calculation. What input was used? What sample size calculation method?

Phase 2:

The information on the sample size calculation is not complete: two essential parameters for the sample size calculations are s = anticipated population standard deviation of the outcome variable and d = clinically significant difference. The authors do not provide the values they used for these parameters, nor do they justify why the choice for this d and s was made. The sample size formula given cannot be correct and is also not formatted correctly (s2 instead of s²).
I understand the difference in fiber intake between control and treatment groups was changed from 20 g/day to 15 g/day in this new version of the protocol. However, the sample size did not change, while I would expect that a higher sample size would be needed as the effect (d) would be lower with a smaller difference.
In regard to the methodology of phase 2: why are the follow-up measurement on day 180 is not done for the control group? This could be explained better.

Is the rationale for, and objectives of, the study clearly described?

Partly
Is the study design appropriate for the research question?

Partly
Are sufficient details of the methods provided to allow replication by others?

Partly
Are the datasets clearly presented in a useable and accessible format?

Not applicable

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Biostatistics, with nutrition as one of my focus areas

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Author Response

03 Mar 2026

Suvarna Hebbar, Clinical Nutrition and Dietetics, Manipal College of Health Professions, Manipal., 576104, India

Response for F1000

The second secondary objective is not specific enough. Opinion on what?

Response: Opinion of women on modified fiber intake

In phase 1 I doubt whether a single 24 hour recall is adequate to determine usual intake. I wonder whether a food frequency questionnaire designed for measuring fiber intake would be more suitable. Is there evidence to support that a single 24 hour recall gives a sufficiently accurate estimate of usual intake of fiber?

Response: We sincerely appreciate the reviewer’s valuable observation. We acknowledge that a single 24-hour dietary recall may not fully capture an individual’s habitual dietary intake. However, the primary objective of the present study was to estimate the prevalence of insulin resistance among overweight and obese middle-aged women and to obtain an overview of usual dietary patterns at the population level. For this purpose, a single 24-hour recall is considered a methodologically acceptable and scientifically justified approach, as it provides a reliable estimate of mean group intake when collected from a sufficiently large and heterogeneous sample.

To minimize potential bias, participants reporting atypical or irregular dietary patterns were excluded, thereby ensuring that the recorded dietary recall reasonably reflected usual intake.

We recognize that a more detailed dietary assessment is essential for evaluating individual-level nutrient adequacy, particularly dietary fiber intake. Accordingly, in the subsequent intervention phase, we plan to implement a structured high-fiber dietary intervention combined with supportive physical activity. Dietary intake will be assessed using three non-consecutive 24-hour recalls along with a validated Food Frequency Questionnaire (FFQ) to capture habitual intake patterns more comprehensively. Physical activity will be assessed using the Global Physical Activity Questionnaire (GPAQ). This integrated approach will enable a more robust assessment of habitual diet while facilitating the evaluation of changes in insulin sensitivity and related metabolic outcomes.

Are 500 participants in phase 1 enough to provide 180 participants who agree to being randomized in phase 2? This is not explained clearly.

Response: Sample Size Justification
In Phase 1, a total of 500 overweight and obese middle-aged women will be screened to determine the prevalence of insulin resistance using HOMA-IR. Based on existing epidemiological evidence and our preliminary observational study conducted among 564 women, a high prevalence of insulin resistance is anticipated in this population. In the preliminary study, over 55% of participants were obese and approximately 20% were overweight, yielding an observed obese-to-overweight ratio of approximately 2:1.
Taking this distribution into account, along with the expected prevalence of insulin resistance and potential exclusions and non-participation in the intervention phase, a screening sample of 500 participants was considered adequate to ensure the recruitment of 180 eligible and consenting participants for Phase 2. This approach allows for appropriate representation of both overweight and obese groups in the randomized phase while maintaining sufficient statistical power for the intervention analyses.

It is not clear to me what is meant by “The sample size was calculated in accordance with insulin resistance and BMI.” Please give more details on the sample size calculation. What input was used? What sample size calculation method

Response: The sample size for Phase 2 was calculated based on two primary outcome variables insulin resistance and body mass index (BMI as these represent the key metabolic and anthropometric endpoints of the intervention. The calculation was performed using a repeated-measures ANOVA model, which is appropriate for assessing within- and between-group changes over time in randomized controlled trials.
Published intervention studies examining the effects of dietary fiber on insulin resistance and BMI were used as reference sources to determine realistic and clinically meaningful estimates of the expected standard deviation (s) and the minimum detectable difference (d) for these outcomes (references 34 and 35).

Phase 2:

The information on the sample size calculation is not complete: two essential parameters for the sample size calculations are s = anticipated population standard deviation of the outcome variable and d = clinically significant difference. The authors do not provide the values they used for these parameters, nor do they justify why the choice for this d and s was made. The sample size formula given cannot be correct and is also not formatted correctly (s2 instead of s2).

Response: Explained under the heading- sample size calculation

I understand the difference in fiber intake between control and treatment groups was changed from 20 g/day to 15 g/day in this new version of the protocol. However, the sample size did not change, while I would expect that a higher sample size would be needed as the effect (d) would be lower with a smaller difference.

Response: The sample size estimation was performed using insulin resistance and body mass index as the primary outcomes, and not dietary fiber intake. Accordingly, no modification to the sample size was required.

In regard to the methodology of phase 2: why are the follow-up measurement on day 180 is not done for the control group? This could be explained better.

Response: Its is already been done and mentioned even in flow chart.

For instance, the role of the microbiome is mentioned, interspersed with statements on other aspects, giving the introduction a repetitive character. Another example is the second sentence where a statement on fiber and an unrelated statement on obesity are combined into a single sentence without the sentence making clear why they are combined.

Response: Its rephrased in page -6

Similarly, there is the sentence “There are few studies on the utilization of dietary fiber in the treatment of obesity, but further research is required to confirm stronger associations between dietary fiber and obesity”, where “but” implies a contradiction between the first and the second part, while I don’t see the contradiction.

Response: The conjunction “but” was intentionally used to indicate a contrast between the presence of general evidence supporting the role of dietary fiber in obesity and the limited depth and scope of studies specifically addressing its utilization and strength of association. The intent was to emphasize that, despite existing evidence, further focused investigation remains necessary, which forms the basis of the present study.

Parts of the protocol are not written out but only given in bullet points. I found this both strange for a paper, and also often unclear. For instance, under strength an limitations: “Good knowledge and practice regarding modified diet plans with high dietary fiber will be addressed to participants”. Knowledge of whom? Of the researcher or the participants? How will this knowledge be addresses?

Response: Strengths and limitations: The study is expected to demonstrate improvements in insulin resistance, body composition, and body weight among participants with higher dietary fiber intake. Participants will receive structured guidance on modified high-fiber diet plans, which is intended to improve their knowledge and dietary practices, as well as to identify barriers and challenges related to sustained fiber consumption. Potential limitations include participant dropout due to dietary non-compliance, variability in long-term adherence to the prescribed diet, and limited generalizability due to hospital-based recruitment and resource constraints.

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Competing Interests

No competing interests were disclosed.

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Reviewer Report

37 Views

05 Feb 2025 | for Version 1

Gary Frost, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, England, UK

37 Views Cite this report Responses(2)

Not Approved

Is the rationale for, and objectives of, the study clearly described?

No
Is the study design appropriate for the research question?

Partly
Are sufficient details of the methods provided to allow replication by others?

No
Are the datasets clearly presented in a useable and accessible format?

No

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Nutrition and carbohydrate research

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Responses (2)

Author Response

22 Mar 2025

Suvarna Hebbar, Clinical Nutrition and Dietetics, Manipal College of Health Professions, Manipal., 576104, India

1. Clarity in Methods Section (Phase 1 & Phase 2 Separation)
Phase 1
Objective
The primary aim of Phase 1 is to screen middle-aged overweight and obese women to determine the prevalence of insulin resistance.
Study Setting
This phase will be conducted in the Outpatient Departments (OPDs) of Medicine, Gynaecology, and Endocrinology at Kasturba Hospital, Manipal.
Sample Size & Selection

A total of 500 women will be screened to assess insulin resistance.
Participants will be categorized into two groups: overweight (BMI 23–24.9 kg/m²) and obese (BMI ≥ 25 kg/m²).
Each group will have at least 166 participants.

Inclusion Criteria

Women aged 35–55 years.
Willing to provide informed consent.
BMI ≥ 23 kg/m².

Exclusion Criteria

Women with conditions affecting nutritional status (e.g., tuberculosis, HIV, cancer, organ failure).
Women diagnosed with type 2 diabetes mellitus.
Individuals with hypertension, thyroid disorders, or any medical condition requiring medications affecting body weight (e.g., thyroxine, diuretics).
Pregnant or lactating women.
Women already on a weight-loss regime or consuming fiber above the recommended dietary allowance.
Women with contraindications for high fiber consumption (e.g., inflammatory bowel disease).

Data Collection Methods
Participants will undergo a baseline assessment, including:

Demographic Information: Age, education, occupation, income, marital history, place of residence, and family structure.
Anthropometric Measures: Height, weight, BMI, waist circumference, and hip circumference using standardized tools.
Biochemical Assessments:
- Fasting blood glucose (hexokinase method).
- HbA1c (TINA method).
- Serum insulin (ECLIA).
- Lipid profile (triglycerides, HDL, LDL, total cholesterol).
Dietary Assessment:
- 24-hour dietary recall and food frequency questionnaire analyzed using DietCal version 6.3.
Physical Activity Assessment:
- Global Physical Activity Questionnaire (GPAQ).
Clinical Assessment: Evaluation of physical symptoms (e.g., bowel movement, satiety, leg pain, backache).

In-Depth Interviews

20 participants consuming low fiber (<20g/day) and 20 participants consuming moderate fiber (20-25g/day) will be interviewed telephonically for 45 minutes to assess barriers to fiber intake.

Phase 2: Randomized Controlled Trial (RCT)
Objective
To assess the impact of high dietary fiber intake (40g/day) on insulin resistance, body composition, and weight among overweight and obese women.
Study Design

Randomized, controlled trial.
Stratified Block Randomization (9 blocks of 20 participants each).
180 women will be randomized into:
- Intervention Group (n=90): Receives 40g/day of fiber with dietary counselling.
- Control Group (n=90): Receives 25g/day of fiber as part of a standard diet care plan.

Inclusion Criteria

Women from Phase 1 with abnormal HOMA-IR (>2), indicating insulin resistance.
Willing to adhere to a high-fiber diet if randomized to the intervention group.

Exclusion Criteria

Women unwilling to continue participation or adhere to the high-fiber diet.

Intervention & Control Groups
Intervention group
All women in the intervention arm will be counseled for about 15 minutes, and a customized diet chart consisting of high fiber of 40 grams will be provided. Nutritional empowerment on fiber shall be delivered to each woman enrolled. Necessary dietary advice on the modified diet plan and with a motivation to adhere to the diet plan will be communicated only to the intervention group. After the first counselling, on the 15th day, women will be telephonically assessed on their 24-hour recall dietary intake. On the 30th day, the women will be contacted telephonically again to record their 24-hour recall of their dietary intake. Necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 60th day, the women will be again telephonically contacted to record their 24-hour recall on their dietary intake, and necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat is analyzed using body fat analyzer and a questionnaire on patient opinion regarding modified diet plan shall be ass. Necessaryessed as motivation and adherence towards fiber consumption subjects will be communicated telephonically on the 135th day. From the 136th to the 180th day, there shall not be any conversation regarding dietary modifications. On the 180th day, as a compliance-checking, the women will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data .24hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat analyzed using body fat analyzer and diet compliance on the modified diet plan shall be assessed.

Control group.
Women in the control arm will get a traditional diet care plan with 25gm of fiber according to their health condition. Necessary dietary advice will be communicated to the control group on the first visit to the hospital. There shall be no telephonic communication with the control group till the 90th day. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hour dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer. On the 180th day, as a compliance-checking, the patient will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer

Data Analysis

Repeated Measures ANOVA will be used to evaluate changes in insulin resistance, body composition, and weight over time.
SPSS v16.0 will be used for statistical analysis.

Ethical Considerations

Approval obtained from the Institutional Research Committee and Institutional Ethics Committee (IEC).
Trial registered with the Clinical Trials Registry of India (CTRI/2022/01/039074).
Informed consent was obtained from all participants.

CONTROL ARM

Day 1

Traditional/standard care
(patient will be called to OPD)

Day 15
Nil

Day 30
Nil

Day 60
Nil

Day 90
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

INTERVENTION ARM

Day 1

Intervention
(patient will be called to OPD)

Customize the individual-specific diet plan
Nutritional counseling
Impart nutritional empowerment on fiber consumption
Handover of diet plan

Day 15

Reinforcement
(through telephone)

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 30

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 60

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 90

Outcome assessment
(patient will be called to OPD)
Basic data:
Tool 2: 24-hour recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Patient opinion on a modified diet
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

Day 135

Reinforcement (through telephone)

Motivation to follow a customized diet plan

Day 180

Checking compliance
(patient will be called to OPD)
Basic data:
Tool 2: 24-hour recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Compliance checklist
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

Day 135
Nil

Day180
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ

Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyser:
Visceral fat, S/C fat, muscle mass

3. Rationale for Sex-Specific Differences and Justification for a Single-Sex Study
This study is specifically designed for women’s health, as obesity and insulin resistance present distinct physiological and hormonal influences in females. The decision to focus on middle-aged women was based on prior evidence suggesting unique metabolic responses to dietary interventions in this demographic.
López, M. et al. (2016) - "Menopause, obesity, and insulin resistance: An emerging paradigm"

This study specifically explores the impact of menopause on metabolic health, highlighting the increased risk of insulin resistance and obesity in women as they transition through menopause. It aligns with your focus on middle-aged women and the unique metabolic responses they experience.
Reference: López, M. et al. "Menopause, obesity, and insulin resistance: An emerging paradigm." Endocrinology (2016).

Van Der Steeg, W. et al. (2010) - "Sex differences in insulin resistance in obesity"

This study investigates how hormonal factors, especially estrogen, affect insulin resistance and fat distribution differently in women, providing key insights into the sex-specific mechanisms that make middle-aged women particularly vulnerable to obesity and metabolic disorders.
Reference: Van Der Steeg, W. et al. "Sex differences in insulin resistance in obesity." Obesity Reviews (2010).

4. Updating Scientific Terminology in the Background Section
We appreciate the suggestion regarding outdated terminology. The term "roughage" and other obsolete language will be revised to align with current scientific terminology.
5. Clarification on Double-Blinding and Study Design
There was an error in the original study design description. This study is not a double-blind study but rather an open-ended study. This design was chosen to facilitate a deeper understanding of the real-world effects of dietary interventions on obesity and insulin resistance in middle-aged women, where factors like adherence to the intervention and participant feedback play an essential role in the analysis.

6. Sample Size Discrepancy
The final sample size of 180 participants (90 per group) was determined based on power calculations for insulin resistance and BMI, accounting for a 15% dropout rate. To ensure appropriate representation, participants were stratified based on the prevalence of obesity and overweight, maintaining a 2:1 ratio, with a higher proportion of obese individuals, as obesity is more prevalent in the target population.

7. Clarification of Study Duration
The total duration of the intervention is 180 days (6 months) for the intervention group, with structured follow-ups to ensure adherence and assess outcomes. Participants receive customized dietary counseling on Day 1, followed by reinforcement sessions via telephone on Days 15, 30, and 60 to monitor compliance and provide necessary modifications. Outcome assessments are conducted on Day 90 and Day 180, where anthropometric, biochemical, and dietary data are collected. A motivational follow-up is done on Day 135 to encourage continued adherence. The control group follows the same assessment schedule but does not receive interim dietary modifications. This structured timeline ensures a comprehensive evaluation of the intervention’s impact while maintaining participant engagement.

8. Justification for the 20g Fiber Difference and Study Duration
The 20g difference in fiber intake between groups was selected based on existing dietary recommendations and evidence supporting its impact on weight management and metabolic health. The intervention group receives 40g of fiber per 2000 kcal, aligning with the Indian Council of Medical Research (ICMR) and National Institute of Nutrition (NIN) guidelines. In contrast, the control group follows a standard 25g fiber intake. This difference ensures a meaningful contrast while remaining practical for adherence.
The 180-day (6-month) intervention period was chosen to allow sufficient time for stabilizing dietary habits and for metabolic changes, such as improvements in insulin resistance and body composition, to be observed. The feasibility of increasing dietary fiber intake by 20g has been supported by our preliminary observational study (2019), which assessed fiber intake and obesity among 564 women. This study highlighted a significant negative correlation between fiber intake and BMI, reinforcing the need for a structured dietary intervention to promote increased fiber consumption.

9. Addressing Compliance Assessment Concerns
Compliance assessment in this study is not solely based on 24-hour dietary recall; multiple tools are incorporated to ensure accuracy and reliability. In addition to the 24-hour recall and food frequency questionnaire, a compliance checklist is used to track adherence to the prescribed dietary plan. Furthermore, patient opinions on the modified diet are collected to assess acceptability and feasibility. Regular reinforcement sessions (via telephone on Days 15, 30, and 60) further help monitor compliance and address challenges.

10. Consistency in Fiber Composition (Soluble vs. Insoluble)
The study ensures consistency in dietary fiber composition across participants by providing a structured, customized diet plan that proportions soluble and insoluble fiber appropriately. The dietary sources primarily include whole grains, legumes, vegetables, and fruits, providing a balanced fiber mix. While the metabolic effects of soluble and insoluble fiber can vary, the intervention is designed to reflect a realistic, well-balanced dietary intake, aligning with established dietary guidelines. This approach ensures that all participants receive a comparable fiber composition, minimizing variability in metabolic responses while maintaining dietary feasibility.

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Competing Interests

No competing interests were disclosed.

Author Response

13 Oct 2025

Suvarna Hebbar, Clinical Nutrition and Dietetics, Manipal College of Health Professions, Manipal., 576104, India

. Clarity in Methods Section (Phase 1 & Phase 2 Separation)
Phase 1
Objective
The primary aim of Phase 1 is to screen middle-aged overweight and obese women to determine the prevalence of insulin resistance.
Study Setting
This phase will be conducted in the Outpatient Departments (OPDs) of Medicine, Gynaecology, and Endocrinology at Kasturba Hospital, Manipal.
Sample Size & Selection

A total of 500 women will be screened to assess insulin resistance.
Participants will be categorized into two groups: overweight (BMI 23–24.9 kg/m²) and obese (BMI ≥ 25 kg/m²).
Each group will have at least 166 participants.

Inclusion Criteria

Women aged 35–55 years.
Willing to provide informed consent.
BMI ≥ 23 kg/m².

Exclusion Criteria

Women with conditions affecting nutritional status (e.g., tuberculosis, HIV, cancer, organ failure).
Women diagnosed with type 2 diabetes mellitus.
Individuals with hypertension, thyroid disorders, or any medical condition requiring medications affecting body weight (e.g., thyroxine, diuretics).
Pregnant or lactating women.
Women already on a weight-loss regime or consuming fiber above the recommended dietary allowance.
Women with contraindications for high fiber consumption (e.g., inflammatory bowel disease).

Data Collection Methods
Participants will undergo a baseline assessment, including:

Demographic Information: Age, education, occupation, income, marital history, place of residence, and family structure.
Anthropometric Measures: Height, weight, BMI, waist circumference, and hip circumference using standardized tools.
Biochemical Assessments:
- Fasting blood glucose (hexokinase method).
- HbA1c (TINA method).
- Serum insulin (ECLIA).
- Lipid profile (triglycerides, HDL, LDL, total cholesterol).
Dietary Assessment:
- 24-hour dietary recall and food frequency questionnaire analyzed using DietCal version 6.3.
Physical Activity Assessment:
- Global Physical Activity Questionnaire (GPAQ).
Clinical Assessment: Evaluation of physical symptoms (e.g., bowel movement, satiety, leg pain, backache).

In-Depth Interviews

20 participants consuming low fiber (<20g/day) and 20 participants consuming moderate fiber (20-25g/day) will be interviewed telephonically for 45 minutes to assess barriers to fiber intake.

Randomized, controlled trial.
Stratified Block Randomization (9 blocks of 20 participants each).
180 women will be randomized into:
- Intervention Group (n=90): Receives 40g/day of fiber with dietary counselling.
- Control Group (n=90): Receives 25g/day of fiber as part of a standard diet care plan.

Inclusion Criteria

Women from Phase 1 with abnormal HOMA-IR (>2), indicating insulin resistance.
Willing to adhere to a high-fiber diet if randomized to the intervention group.

Exclusion Criteria

Women unwilling to continue participation or adhere to the high-fiber diet.

Intervention & Control Groups
Intervention group
All women in the intervention arm will be counseled for about 15 minutes, and a customized diet chart consisting of high fiber of 40 grams will be provided. Nutritional empowerment on fiber shall be delivered to each woman enrolled. Necessary dietary advice on the modified diet plan and with a motivation to adhere to the diet plan will be communicated only to the intervention group. After the first counselling, on the 15th day, women will be telephonically assessed on their 24-hour recall dietary intake. On the 30th day, the women will be contacted telephonically again to record their 24-hour recall of their dietary intake. Necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 60th day, the women will be again telephonically contacted to record their 24-hour recall on their dietary intake, and necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat is analyzed using body fat analyzer and a questionnaire on patient opinion regarding modified diet plan shall be assessed as motivation and adherence towards fiber consumption subjects will be communicated telephonically on the 135th day. From the 136th to the 180th day, there shall not be any conversation regarding dietary modifications. On the 180th day, as a compliance-checking, the women will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data .24hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat analyzed using body fat analyzer and diet compliance on the modified diet plan shall be assessed.

Control group.
Women in the control arm will get a traditional diet care plan with 25gm of fiber according to their health condition. Necessary dietary advice will be communicated to the control group on the first visit to the hospital. There shall be no telephonic communication with the control group till the 90th day. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hour dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer. On the 180th day, as a compliance-checking, the patient will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer

Data Analysis

Repeated Measures ANOVA will be used to evaluate changes in insulin resistance, body composition, and weight over time.
SPSS v16.0 will be used for statistical analysis.

Ethical Considerations

Approval obtained from the Institutional Research Committee and Institutional Ethics Committee (IEC).
Trial registered with the Clinical Trials Registry of India (CTRI/2022/01/039074).
Informed consent was obtained from all participants.

CONTROL ARM

Day 1

Traditional/standard care
(patient will be called to OPD)

Day 15
Nil

Day 30
Nil

Day 60
Nil

Day 90
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

INTERVENTION ARM

Day 1

Intervention
(patient will be called to OPD)

Customize the individual-specific diet plan
Nutritional counseling
Impart nutritional empowerment on fiber consumption
Handover of diet plan

Day 15

Reinforcement
(through telephone)

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 30

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 60

Tool 2: 24hr recall
Tool 3: GPAQ
Modification of diet plan (if required)
Motivate to adhere to the intervention

Day 90

Outcome assessment
(patient will be called to OPD)
Basic data:
Tool 2: 24-hour recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Patient opinion on a modified diet
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyzer:
Visceral fat, S/C fat, muscle mass

Day 135

Reinforcement (through telephone)

Motivation to follow customised diet plan

Day 180

Checking compliance
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ
Tool 4: Clinical assessment scale
Tool 5: Compliance checklist
Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyser:
Visceral fat, S/C fat, muscle mass

Day 135
Nil

Day180
(patient will be called to OPD)
Basic data:
Tool 2: 24hr recall and food frequency
Tool 3: GPAQ

Biochemical parameters:
FBS, HbA1c, Sr. Insulin and lipid profile
Body fat analyser:
Visceral fat, S/C fat, muscle mass

3. Rationale for Sex-Specific Differences and Justification for a Single-Sex Study
This study is specifically designed for women’s health, as obesity and insulin resistance present distinct physiological and hormonal influences in females. The decision to focus on middle-aged women was based on prior evidence suggesting unique metabolic responses to dietary interventions in this demographic.
López, M. et al. (2016) - "Menopause, obesity, and insulin resistance: An emerging paradigm"

This study specifically explores the impact of menopause on metabolic health, highlighting the increased risk of insulin resistance and obesity in women as they transition through menopause. It aligns with your focus on middle-aged women and the unique metabolic responses they experience.
Reference: López, M. et al. "Menopause, obesity, and insulin resistance: An emerging paradigm." Endocrinology (2016).

Van Der Steeg, W. et al. (2010) - "Sex differences in insulin resistance in obesity"

This study investigates how hormonal factors, especially estrogen, affect insulin resistance and fat distribution differently in women, providing key insights into the sex-specific mechanisms that make middle-aged women particularly vulnerable to obesity and metabolic disorders.
Reference: Van Der Steeg, W. et al. "Sex differences in insulin resistance in obesity." Obesity Reviews (2010).

4. Updating Scientific Terminology in the Background Section
We appreciate the suggestion regarding outdated terminology. The term "roughage" and other obsolete language will be revised to align with current scientific terminology.
5. Clarification on Double-Blinding and Study Design
There was an error in the original study design description. This study is not a double-blind study but rather an open-ended study. This design was chosen to facilitate a deeper understanding of the real-world effects of dietary interventions on obesity and insulin resistance in middle-aged women, where factors like adherence to the intervention and participant feedback play an important role in the analysis.

6. Sample Size Discrepancy
The final sample size of 180 participants (90 per group) was determined based on power calculations for insulin resistance and BMI, accounting for a 15% dropout rate. To ensure appropriate representation, participants were stratified based on the prevalence of obesity and overweight, maintaining a 2:1 ratio, with a higher proportion of obese individuals, as obesity is more prevalent in the target population.

7. Clarification of Study Duration
The total duration of the intervention is 180 days (6 months) for the intervention group, with structured follow-ups to ensure adherence and assess outcomes. Participants receive customized dietary counseling on Day 1, followed by reinforcement sessions via telephone on Days 15, 30, and 60 to monitor compliance and provide necessary modifications. Outcome assessments are conducted on Day 90 and Day 180, where anthropometric, biochemical, and dietary data are collected. A motivational follow-up is done on Day 135 to encourage continued adherence. The control group follows the same assessment schedule but does not receive interim dietary modifications. This structured timeline ensures a comprehensive evaluation of the intervention’s impact while maintaining participant engagement.

8. Justification for the 20g Fiber Difference and Study Duration
The 20g difference in fiber intake between groups was selected based on existing dietary recommendations and evidence supporting its impact on weight management and metabolic health. The intervention group receives 40g of fiber per 2000 kcal, aligning with the Indian Council of Medical Research (ICMR) and National Institute of Nutrition (NIN) guidelines. In contrast, the control group follows a standard 25g fiber intake. This difference ensures a meaningful contrast while remaining practical for adherence.
The 180-day (6-month) intervention period was chosen to allow sufficient time for stabilizing dietary habits and for metabolic changes, such as improvements in insulin resistance and body composition, to be observed. The feasibility of increasing dietary fiber intake by 20g has been supported by our preliminary observational study (2019), which assessed fiber intake and obesity among 564 women. This study highlighted a significant negative correlation between fiber intake and BMI, reinforcing the need for a structured dietary intervention to promote increased fiber consumption.

9. Addressing Compliance Assessment Concerns
Compliance assessment in this study is not solely based on 24-hour dietary recall; multiple tools are incorporated to ensure accuracy and reliability. In addition to the 24-hour recall and food frequency questionnaire, a compliance checklist is used to track adherence to the prescribed dietary plan. Furthermore, patient opinions on the modified diet are collected to assess acceptability and feasibility. Regular reinforcement sessions (via telephone on Days 15, 30, and 60) further help monitor compliance and address challenges.

10. Consistency in Fiber Composition (Soluble vs. Insoluble)
The study ensures consistency in dietary fiber composition across participants by providing a structured, customized diet plan that appropriately proportions soluble and insoluble fiber. The dietary sources primarily include whole grains, legumes, vegetables, and fruits, providing a balanced fiber mix. While the metabolic effects of soluble and insoluble fiber can vary, the intervention is designed to reflect a realistic, well-balanced dietary intake, aligning with established dietary guidelines. This approach ensures that all participants receive a comparable fiber composition, minimizing variability in metabolic responses while maintaining dietary feasibility.

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Competing Interests

No competing interests were disclosed.

Alongside their report, reviewers assign a status to the article:

Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions

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Effect of high dietary fiber intake on insulin resistance, body composition and weight, among overweight or obese middle-aged women: study protocol for a randomized controlled trail.

Abstract

Background

Aim

Method

Discussion

Trial registration

Keywords

Revised Amendments from Version 3

Background

Objectives

Primary objective

Secondary objective

Methods

Phase 1

Objective

Study setting

Sample size & Selection

Data collection methods

Screening and measurements

In-depth interviews

Phase 2: Randomized Controlled Trial (RCT)

Objective

Study design

Sample size calculation

Data collection methods

Intervention & Control groups

Intervention group

Table 1.

Control group

Data analysis

Ethical considerations

Study status

Discussion

Article summary

Strengths and limitations of this study

Ethics and dissemination

Consent to participate

Data availability

Underlying data

Extended data

Reporting guidelines

Acknowledgements

References

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