Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol

Jiaying Zhou; Mayue Shi; Mingzhu Cai

doi:10.12688/f1000research.157875.2

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Study Protocol

Revised

Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol

[version 2; peer review: 1 approved with reservations]

Jiaying Zhou¹, Mayue Shi², Mingzhu Cai ¹

PUBLISHED 03 Apr 2025

Author details Author details

¹ 1. Department of Metabolism, Digestion and Reproduction, Imperial College London, London, England, UK
² Department of Electrical and Electronic Engineering, Imperial College London, London, England, UK

Jiaying Zhou
Roles: Methodology, Writing – Original Draft Preparation

Mayue Shi
Roles: Conceptualization, Supervision, Writing – Review & Editing

Mingzhu Cai
Roles: Conceptualization, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

Abstract

Background

Traditional dietary assessments are often inaccurate and prone to self-reporting biases. Tracking the physiological responses associated with eating and digestion events via wearable technologies may provide an effective approach for continuously monitoring food intake and estimating energy consumption. Eating and digestion are accompanied by a series of changes in the heart rate, skin temperature, blood oxygen saturation, and blood pressure. These changes can be tracked by wearable devices, such as smartwatches, which have been widely accepted in the market. This systematic review is the first to evaluate the effectiveness of tracking such physiological biomarkers in differentiating between high- and low-calorie meals, potentially paving the way for more accurate dietary monitoring.

Methods

Following the PRISMA-P guidelines, we will conduct a systematic literature search through MEDLINE, EMBASE, and PubMed for clinical trials that investigated physiological responses following meal intake in healthy subjects. Two independent reviewers will screen and select articles based on pre-defined eligibility criteria, with a third review to resolve any discrepancies. This will be followed by data extraction and quality assessment of the included studies. Statistical analyses, including meta-analyses, will be performed using R Studio software. Our primary outcome will be the comparison of physiological biomarkers before and after meal intake, while secondary outcomes will include comparisons of physiological biomarkers between high- and low-calorie meal consumption and the correlation between the caloric content of consumed meals and postprandial physiological changes.

Discussion

This systematic review and meta-analysis will identify physiological indicators for eating events and inform the design of wearable sensors that estimate food intake in healthy subjects.

Systematic Review Registration

PROSPERO Registration ID: CRD42024544353

Keywords

Dietary behaviour, food intake, physiological biomarkers, heart rate, blood pressure wearable sensor

Corresponding authors: Mayue Shi, Mingzhu Cai

Competing interests: No competing interests were disclosed.

Grant information: This work was supported by the Dame Julia Higgins Postdoc Collaborative Research Fund. The sponsor had no role in composing the study design, collection, management, analysis, and interpretation of data.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2025 Zhou J 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: Zhou J, Shi M and Cai M. Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol [version 2; peer review: 1 approved with reservations]. F1000Research 2025, 13:1358 (https://doi.org/10.12688/f1000research.157875.2) First published: 13 Nov 2024, 13:1358 (https://doi.org/10.12688/f1000research.157875.1) Latest published: 03 Apr 2025, 13:1358 (https://doi.org/10.12688/f1000research.157875.2)

Revised Amendments from Version 1

This revised version addresses all peer review comments. We clarified that the manuscript is a study protocol for a systematic review and meta-analysis, highlighting its role as secondary research. Redundancies in the “Study Design and Context” section were removed for clarity. The primary and secondary outcomes now more clearly define the physiological biomarkers of interest—heart rate, blood pressure, skin temperature, blood oxygen saturation, and blood glucose—which will be assessed before and after meals, and across high- and low-calorie conditions. An “Expected Results/Findings” section has been added, outlining anticipated postprandial physiological changes and potential dose-response relationships with caloric intake. We also expanded the data extraction section to include planned comparisons between wearable devices and traditional clinical methods, where data are available.

See the authors' detailed response to the review by Faiza Jan Iftikhar

Background

Diet is essential for human health, and understanding what people eat in their daily lives is a fundamental challenge. Traditional dietary assessments rely on self-reporting and present high levels of subjectivity and recall biases. These limitations have driven the development of objective and reliable tools for dietary monitoring.

Recent advances in metabolomic techniques, combined with bioinformatics analysis, have opened new avenues for developing dietary biomarkers. These approaches aim to identify blood or urine metabolites as biomarkers of food intake (BFIs) that reflect the consumption of specific foods or dietary patterns (Cuparencu et al., 2024; Maruvada et al., 2020). However, this approach is limited by laboratory analysis and does not enable continuous dietary monitoring.

Wearable sensor-based methods have also been proposed for continuous dietary monitoring. Various wearable sensors function by tracking the oral phase of digestion (capturing bites, chewing, and swallowing actions) and hand gestures to identify eating episodes (Burrows & Rollo, 2019). However, they often fall short of providing contextual meal information, such as energy intake estimates (Vu et al., 2017). Camera-based systems have also been proposed, with the ability to estimate meal energy by measuring food volume and categorizing food types. However, these systems have significant privacy concerns, particularly when personal images are involved (Doulah et al., 2022). To date, a widely accessible, user-friendly tool for real-time monitoring of food and energy intake is still lacking.

Tracking the physiological responses associated with eating and digestion events via wearable technologies may provide a solution for the continuous monitoring of food intake. Physiological changes after food consumption, such as increased heart rate, elevated skin temperature, and decreased blood oxygen saturation, have been well documented (De Aguiar Cassiani et al., 2011; Sit & Chou, 1984; Westerterp, 2004). Heart rate changes showed a strong correlation with meal size, suggesting that physiological responses could serve as valuable indicators of both food consumption and energy intake (Sidery & Macdonald, 1994). Despite this, there remains no consensus on whether monitoring physiological responses can serve as reliable indicators of energy intake.

This systematic review aims to identify and evaluate physiological biomarkers associated with food and energy intake. The specific objectives are: (1) to investigate physiological responses, such as heart rate, blood pressure, skin temperature, and blood oxygen saturation, following the consumption of high-caloric versus low-calorie meals through meta-analysis; and (2) to assess whether there is a dose-response relationship between these physiological changes and the caloric content of meals using meta-regression analysis. This can inform the design of new dietary monitoring tools and whether tracking such changes can effectively differentiate between high- and low-calorie intake.

Methods

This protocol will follow the PRISMA-P Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA-P) guidelines to ensure a systematic and transparent process (Moher et al., 2015; Shamseer et al., 2015). We will systematically identify, extract and synthesize data from eligible studies to determine the physiological biomarkers associated with food and energy intake.

Outcomes

Primary outcomes

Our primary outcomes will focus on key physiological biomarker fluctuations associated with dietary intake, specifically comparing pre- and post-meal periods to assess immediate physiological changes after food consumption and high- vs. low-calorie meals to evaluate how meal calorie content influences biomarker variations, with biomarkers of interest including heart rate, blood pressure, blood glucose levels, metabolic markers, and other relevant physiological parameters.

Secondary outcomes

Our secondary outcomes will focus on two key areas::

• Correlation and Dose-Response Relationships – We will investigate the relationship between meal energy content and physiological biomarker responses, specifically assessing whether higher-calorie meals elicit stronger or more prolonged physiological changes.
• Wearable Technology Capabilities for Dietary Monitoring – We will evaluate the accuracy and effectiveness of wearable sensing technologies (e.g., smartwatches, continuous glucose monitors, bioimpedance sensors) in detecting meal-induced physiological changes and compare wearable-derived data with traditional clinical measurements to assess their real-world applicability in dietary monitoring.

Eligibility criteria for including studies

The eligibility criteria for this review are structured according to the PICO framework to clearly define the target population, interventions, comparators, outcomes, and study context. This framework is essential for identifying physiological biomarkers that reflect dietary behaviors and evaluating their applications in wearable sensing technology for food intake monitoring.

Population

Inclusion criteria:

• Healthy participants included individuals who are underweight, overweight, or of normal weight, provided that they are otherwise in good health.

Exclusion criteria:

• Patients diagnosed with diabetes, cardiovascular disease, or any other type of chronic condition.
• Animal studies.

Intervention

Inclusion criteria:

• Meal intake with adequate nutrient and calorie information, regardless of meal form (liquid, solid, or mixed)
• Monitoring physiological biomarkers before and after dietary intake. Key physiological biomarkers included heart rate, body temperature, oxygen consumption, cardiac output, blood pressure, blood flow, and blood glucose through a continuous glucose monitor.

Exclusion criteria:

• Studies investigating the impacts of water consumption, drug effects, long-term dietary consequences, and specific types of food or exercise
• Studies lacking sufficient information to calculate the test meal’s caloric content

Comparator

Inclusion criteria:

• Comparing the pre- and postprandial changes in physiological biomarkers.
• Comparing the physiological biomarkers changes after consuming meals of different calories content.
• Comparing wearable sensors with traditional methods for monitoring physiological biomarkers related to food intake.

Outcomes

Inclusion criteria:

• Pre- and post-meal monitoring of heart rate, skin temperature, blood oxygen saturation, cardiac output, blood pressure, and intestinal blood flow measured using wearable or traditional devices.
• Pre- and post-meal blood glucose monitoring using wearable devices, such as continuous glucose monitors (CGMs).
• If measured using wearable devices, the performance metrics include accuracy, specificity, precision, recall, and F1-score.

Exclusion criteria:

• Articles without reported results from empirical research.

Study design and context

Inclusion criteria:

• Experiential studies involving human participants in either controlled or real-life environments.
• Randomised or non-randomised trial, including single-arm studies.
• English-language articles in peer-reviewed journals.

Exclusion criteria:

• Review articles, commentaries, and protocols.
• Studies without human involvement.
• A publication cutoff date of February 7, 2024, will be applied.

Information sources and search strategy

Literature searches will be conducted across the MEDLINE, EMBASE, and PubMed databases following pre-defined eligibility criteria. We will use search strategies that incorporate both Medical Subject Headings (MeSH) and a suite of keywords pertinent to wearable sensors and their applications in monitoring eating behaviors. The selection of keywords will include terms such as ‘eating,’ ‘energy intake,’ ‘caloric intake,’ ‘postprandial period,’ ‘postprandial state,’ ‘oxygen consumption,’ ‘heart rate,’ ‘blood pressure,’ ‘cardiac output,’ ‘body temperature,’ ‘regional blood flow,’ and ‘blood glucose’ to ensure broad yet relevant coverage. For detailed insights into the search strategy employed for each database, please refer to Supplementary Table 1 (Appendix).

Screen and selection process

The literature search results will be uploaded to Covidence, a web-based tool for systematic review and management. The duplicates will be automatically removed upon uploading. Our team will create and refine screening questions and forms, aligning them with predetermined inclusion and exclusion criteria.

The selection process will start with all three authors independently reviewing the titles and abstracts to check if they met the inclusion criteria. Titles that seem to fit these criteria or whose eligibility is not clear will be selected for a full-report review to confirm that they comply with the inclusion criteria. Conflicts on Covidence will be resolved through discussions in review team meetings, and the reasons for excluding texts will be recorded. The flow diagram of the article selection process for Covidence will be shown in the PRISMA flow diagram Supplementary Figure 1.

Supplementary Figure 1 (Refer extended data) PRISMA Flow Diagram of the Article Screening Process.

Data extraction

J.Z. will independently extract specified characteristics from selected studies into a designated Excel spreadsheet for data extraction. Subsequently, M.C. and M.S. will independently assessed the extracted data. Any discrepancies identified during the review will b resolved through team meetings. Given the diversity of the data items to be extracted and the varied focus across papers, it is expected that not all papers will contain every piece of desired information.

Data will be extracted from eligible studies, including quantitative measures of physiological biomarkers before and after meal consumption. These extracted findings will be synthesized through meta-analysis (if feasible) or narrative synthesis to determine trends in postprandial physiological changes.Pre-defined study characteristics and outcome measures will be recorded in a standardized data extraction Excel spreadsheet, which will include the following information:

Study design: randomised trials or non-randomised studies.

Population:

1. Participant characteristics including age, gender, BMI, ethnicity, and healthy status.
2. Sample size: number of participants enrolled and analysed in the study.

Intervention:

3. Meal content: Food items, nutritional, and calorie information. Calorie intake will be either extracted directly or calculated using reported nutritional information.
4. Timing and length of meal consumption
5. Fasting duration before interventions

Comparisons:

6. Definition of ‘control’ groups (e.g., pre-meal vs. post-meal; high-calorie vs. low-calorie meal)

Outcomes:

7. Quantitative data on physiological biomarkers: Time-series changes in heart rate, skin temperature, blood oxygen saturation, cardiac output, blood pressure, and intestinal blood flow before and after meals
8. Measurement instrument and intervals: Indicate whether outcomes are measured using traditional or wearable devices. If wearable devices are used, the performance metrics (e.g., accuracy, specificity, precision, recall, and F1-score) of the wearable sensors will be extracted, where applicable.
8. In addition to extracting predefined data fields, we anticipate comparing wearable sensor-derived measurements with traditional clinical methods where possible. As the data extraction and synthesis is still ongoing, we cannot definitively determine which traditional methods will be available for comparison, as this depends on the data available in the included studies. However, we expect to include comparisons with standard clinical assessments—such as pulse oximeters for heart rate and oxygen saturation, upper-arm blood pressure monitors for systolic and diastolic blood pressure, and lab-based tests for glucose and metabolic markers. Our systematic review will identify and compare the wearable sensor-based methods with these traditional approaches where data are available.

Risk of bias assessment

In this systematic review, a comprehensive assessment of the risk of bias in individual studies will b conducted to ensure the reliability and validity of our findings. We will follow the structured guidelines provided in Chapter 25 of the Cochrane Handbook for Systematic Reviews of Interventions, utilizing specific tools tailored to the type of study under review (Higgins et al., 2019).

• Risk of Bias In Non-randomized Studies-of Interventions (ROBINS-I) tool: for non-randomized studies, evaluating domains such as confounding, selection of participants, classification of interventions, deviations from intended interventions, missing data, measurement of outcomes, and selection of reported results (Sterne, Jonathan AC et al., 2016).
• Risk of Bias (RoB) 2 tool: for randomized studies, examining domains including the randomization process, deviations from intended interventions, missing outcome data, measurement of the outcome, and selection of the reported results (Sterne, Jonathan A. C. et al., 2019).

Risk of bias assessment will be carried out at both the study and outcome levels to identify biases that could impact the overall study or specific outcomes. The results of these assessments will b crucial to the data synthesis process.

• Categorization of Studies: Each study will be categorized based on its assessed risk of bias: low, moderate, high, or critical. This categorization directly influenced the weight of each study contributing to the synthesis.
• Interpretation of Findings: Categorization will also play a vital role in interpreting the review’s findings, especially when integrating results from studies with high or critical risk of bias.

Visualization of bias assessment

The results of the risk of bias assessments will be visualized using Robvis, a tool that generates high-quality publication-ready figures summarizing these assessments for systematic reviews (McGuinness & Higgins, 2021). This visualization tool allows for customization according to the specific assessment tools used, such as RoB 2 or ROBINS-I, ensuring that our review’s risk-of-bias visualization is both informative and tailored to our specific methodology. These visualizations will aid in transparent reporting and a detailed discussion of the biases inherent in the included studies.

Data synthesis

This systematic review will integrate quantitative data from studies that examine physiological changes in postprandial status. Given the anticipated variation in study designs, populations, and measurement methods, we will initially perform a narrative synthesis to summarize and interpret the findings across different studies.

A meta-analysis will be considered if the data extracted from the included studies demonstrate sufficient homogeneity in terms of the study design, intervention types, and reported outcomes. Our meta-analytic process willinclude the following steps.

1. Software for Data Synthesis: Statistical analyses, including meta-analysis, will be conducted using R Studio with the ‘metafor’ package, supporting fixed and random-effects models, heterogeneity assessment, subgroup, and sensitivity analyses.
2. Models for Meta-Analysis: We will select the meta-analytic model based on the data characteristics; a fixed-effects model will be used if the studies are sufficiently similar. Otherwise, a random-effects model will be employed to account for variability both within and across studies, if significant heterogeneity was detected.
3. Heterogeneity and Sensitivity Analysis: Heterogeneity will be assessed using the Q test and quantified using the I² statistic, which indicates the proportion of variance due to actual differences rather than chance, with values over 50% indicating substantial heterogeneity. Sensitivity analyses will be conducted by systematically excluding each study to check for significant changes in heterogeneity and overall results, ensuring that no single study disproportionately influences the effect sizes.
4. Subgroup Analyses and Meta-Regression: Subgroup analyses will be conducted to investigate whether moderators, such as high- and low-calorie meals, influence physiological biomarker changes differently. Meta-regression was performed to assess whether a dose-response relationship exists.
5. Assessment of Reporting Biases: To investigate potential publication biases, funnel plots will be used for visual examination and Egger’s test will be used to statistically determine the likelihood of bias influencing the reported results.

Handling missing and incomplete data

Where caloric information is missing, it will be calculated based on the macronutrient composition of the meal. Alternatively, the authors of the original study will be contacted.

Where necessary, we will calculate standard deviations from the provided sample size and standard error mean or consider estimation methods if original data cannot be retrieved, adhering to the Cochrane guidelines (Higgins et al., 2019).

Expected results/ findings

Based on previous literature and physiological mechanisms, we anticipate the following outcomes:

• Transient increases in heart rate and blood pressure post-meal, with potentially greater fluctuations following high-calorie meals. We also expect a correlation between meal calorie content and the magnitude of postprandial changes compared to baseline measurements.
• Variations in blood glucose and metabolic markers, influenced by meal composition and individual metabolic responses. For example, higher-calorie meals, particularly those rich in carbohydrates, are expected to lead to greater postprandial increases in blood glucose levels.
• A more pronounced cardiovascular and metabolic response to high-calorie meals compared to low-calorie meals, potentially reflecting differences in autonomic regulation, metabolic load, and the body’s adaptive mechanisms to energy intake.

Confidence in cumulative evidence

We used the GRADE framework to assess the quality of the evidence. Adjustments to the quality ratings will be made based on several factors: (i) Risk of Bias (RoB) across studies, (ii) indirect evidence, (iii) inconsistency of results, (iv) imprecision in data, and (v) Potential for Publication Bias. Evidence levels will be categorized as “high”, “moderate”, or “low”. Each reason for potential downgrade will be evaluated as “none,” “serious,” or “very serious.”

Discussion

Wearable devices have shown promise for monitoring eating episodes by capturing eating gestures or food images. Integrating physiological parameters, such as heart rate, blood pressure, and skin temperature, may enhance the estimation of food and energy intake. A systematic review is needed to consolidate the current evidence on the relationship between these physiological parameters and dietary intake and to assess the potential for tracking these changes in differentiating high- and low-calorie intake.

This protocol is designed in strict adherence to the PRISMA-P guidelines to ensure the execution of a high-quality systematic review and meta-analysis. To our knowledge, this review is the first to systematically investigate the changes in key physiological biomarkers from pre- to post-meal states and their relationships with energy intake. The planned systematic review will enhance our understanding of physiological responses following dietary intake and may inform new wearable technologies for more accurate and real-time monitoring of food consumption.

Declarations

Ethics and dissemination

This systematic review does not require ethical approval as it relies on previously published studies that contain non-identifiable data. The outcomes of the review will be shared through publication in a peer-reviewed journal, and presentations at conferences and seminars.

Patient consent for publication

Not required.

Author’s contributions

M.C. and M.S. designed and directed the project; M.C. and M.S. acquired funding as co-PIs; J.Z., M.C., and M.S. wrote this protocol.

Data availability

Underlying data

No data are associated with this article.

Extended data

Figshare: Extended data for ‘Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol’. DOI: https://doi.org/10.6084/m9.figshare.27303741.v1 (Zhou et al., 2024).

The project contains the following extended data:

• Data file 2: Search Strategy

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

Reporting guidelines

The project contains the following Reporting guidelines:

• Data file 1: PRISMA Flow Chart
• Data file 3: PRISMA-P Checklist

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

References

Burrows TL, Rollo ME: Advancement in Dietary Assessment and Self-Monitoring Using Technology. Nutrients. 2019; 11(7): 1648. PubMed Abstract | Publisher Full Text | Free Full Text
Cuparencu C, Bulmuş-Tüccar T, Stanstrup J, et al.: Towards nutrition with precision: unlocking biomarkers as dietary assessment tools. Nat. Metab. 2024; 6(8): 1438–1453. PubMed Abstract | Publisher Full Text
De Aguiar Cassiani R, Manfredi C, Santos JA, et al.: Arterial oxygen saturation and heart rate during a meal in chronic obstructive pulmonary disease.2011.
Doulah A, Ghosh T, Hossain D, et al.: Energy intake estimation using a novel wearable sensor and food images in a laboratory (pseudo-free-living) meal setting: quantification and contribution of sources of error. Springer Science and Business Media LLC; 2022.
Higgins JPT, Thomas J, Chandler J, et al.: Cochrane Handbook for Systematic Reviews of Interventions. Wiley Cochrane Series. 2nd ed.Newark: John Wiley & Sons, Ltd; 2019.
Maruvada P, Lampe JW, Wishart DS, et al.: Perspective: Dietary Biomarkers of Intake and Exposure—Exploration with Omics Approaches. Adv. Nutr. 2020; 11(2): 200–215. PubMed Abstract | Publisher Full Text | Free Full Text
McGuinness LA, Higgins JPT: Risk-of-bias VISualization (robvis): An R package and Shiny web app for visualizing risk-of-bias assessments. Res. Synth. Methods. 2021; 12(1): 55–61. PubMed Abstract | Publisher Full Text
Moher D, Shamseer L, Clarke M, et al.: Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst. Rev. 2015; 4(1). PubMed Abstract | Publisher Full Text | Free Full Text
Shamseer L, Moher D, Clarke M, et al.: Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ. 2015; 349(jan02 1): 7647. PubMed Abstract | Publisher Full Text
Sidery MB, Macdonald IA: The effect of meal size on the cardiovascular responses to food ingestion. Br. J. Nutr. 1994; 71(6): 835–848. PubMed Abstract | Publisher Full Text
Sit SP, Chou CC: Time course of jejunal blood flow, O2 uptake, and O2 extraction during nutrient absorption. Am. J. Physiol. Heart Circ. Physiol. 1984; 247(3): H395–H402. PubMed Abstract | Publisher Full Text
Sterne JAC, Savović J, Page MJ, et al.: RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ (Online). 2019; 366: l4898. Publisher Full Text
Sterne JA, Hernán MA, Reeves BC, et al.: ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ (Online). 2016; 355: i4919. PubMed Abstract | Publisher Full Text | Free Full Text
Vu T, Lin F, Alshurafa N, et al.: Wearable Food Intake Monitoring Technologies: A Comprehensive Review. Computers (Basel). 2017; 6(1): 4. Publisher Full Text
Westerterp KR: Diet induced thermogenesis. Nutr. Metab. 2004; 1(1): 5. PubMed Abstract | Publisher Full Text | Free Full Text
Zhou J, Shi M, Cai M: Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol. Dataset. figshare. 2024. Publisher Full Text

Comments on this article Comments (0)

Version 2

VERSION 2 PUBLISHED 13 Nov 2024

Author details Author details

Jiaying Zhou
Roles: Methodology, Writing – Original Draft Preparation

Mayue Shi
Roles: Conceptualization, Supervision, Writing – Review & Editing

Mingzhu Cai
Roles: Conceptualization, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

This work was supported by the Dame Julia Higgins Postdoc Collaborative Research Fund. The sponsor had no role in composing the study design, collection, management, analysis, and interpretation of data.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Article Versions (2)

version 2

Revised

Published: 03 Apr 2025, 13:1358

https://doi.org/10.12688/f1000research.157875.2

version 1

Published: 13 Nov 2024, 13:1358

https://doi.org/10.12688/f1000research.157875.1

© 2025 Zhou J 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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Zhou J, Shi M and Cai M. Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol [version 2; peer review: 1 approved with reservations]. F1000Research 2025, 13:1358 (https://doi.org/10.12688/f1000research.157875.2)

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Open Peer Review

Version 2

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PUBLISHED 03 Apr 2025

Revised

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Reviewer Report 05 May 2025

Faiza Jan Iftikhar, National University of Technology (NUTECH), Islamabad, Pakistan

Approved with Reservations

https://doi.org/10.5256/f1000research.179800.r375418

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Version 1

VERSION 1

PUBLISHED 13 Nov 2024

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Reviewer Report 27 Jan 2025

Faiza Jan Iftikhar, National University of Technology (NUTECH), Islamabad, Pakistan

Approved with Reservations

https://doi.org/10.5256/f1000research.173392.r343907

The work is innovative but does not touch the theme of oncology or related research as is the focus of the journal. It aims to assess the effectiveness of wearable technologies by tracking physiological biomarkers pre- and postprandial. It is contended that the wearable devices are able to monitor the changes in heart rate, oxygen level, skin temperature etc., in a more accurate and continuous manner. This study aims to study these biomarkers that results due to high and low calories meals.

It should be made clear that it is a secondary research. The PICO method is not explained and the different PICOs are given though with some repetition
Different frameworks are being referred to but not explained.
The expected results of the methods used is not given. Hence outcomes are not clear. They should include measurable results expected from the test
It looks more like writing a review but expected results and findings extracted from secondary research is not given
It says: Comparing wearable sensors with traditional methods for monitoring physiological biomarkers related to food intake. Mention what are the traditional methods that will be compared with.

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?

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

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Bio sensor /chemical sensors including wearable sensor.

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.

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Author Response 03 Apr 2025

Jiaying Zhou, 1. Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK

03 Apr 2025

Author Response
Dear Reviewer,
We sincerely appreciate your time and valuable feedback on our manuscript. Your comments have helped us refine our work, and we have made the necessary revisions accordingly. Below, ... Continue reading
Dear Reviewer,
We sincerely appreciate your time and valuable feedback on our manuscript. Your comments have helped us refine our work, and we have made the necessary revisions accordingly. Below, we address each of your concerns in detail.
Response to Specific Comments:
Journal Focus
Reviewer Comment: The work is innovative but does not touch the theme of oncology or related research as is the focus of the journal.

Response:

As stated in F1000Research’s scope, “F1000Research publishes articles and other research outputs reporting basic scientific, scholarly, translational and clinical research across the physical and life sciences, engineering, medicine, social sciences and humanities.” and it “ publishes different type of research, including clinical trials, systematic reviews, software tools, method articles, and many others”. https://f1000research.com/about#aims-and-scope

The present work describes a study protocol aiming to identify new tools for tracking food and energy intake, which may help combat the diet-related diseases such as obesity. This work aligns with the journal’s aims and scope.

Clarifying that this is a secondary research study and improving PICO explanation
Reviewer Comment: It should be made clear that it is a secondary research. The PICO method is not explained, and the different PICOs are given with some repetition.
Response: We confirm the following edits have been made to clarify the study design and improved PICO explanation:

We have stated in the title, Introduction and Methods sections that this is a study protocol for systematic review and meta-analysis, making it clear that it is a secondary research study.

The PICO framework was applied to structure both the eligibility criteria and data extraction items. A detailed explanation of this framework is provided in the Methods section, under “Eligibility criteria for including studies.” in line number 68-72.

Regarding the repetition in the ‘Study design and context’ section, please find below the revised version, which removes redundancy. We have revised the study design and context section, in the line 127-136 of the manuscript to remove redundancy. The revised version is below:

“Study Design and Context
Inclusion Criteria:

Experiential studies involving human participants in either controlled or real-life environments.

Randomized or non-randomized trials, including single-arm studies.

English-language articles published in peer-reviewed journals.

Exclusion Criteria:

Review articles, commentaries, and protocols.

Studies without human involvement.

A publication cutoff date of February 7, 2024, will be applied.”

Explanation of Different Frameworks
Reviewer Comment: Different frameworks are being referred to but not explained.
Response:

We have followed a standardized framework for conducting a systematic review in accordance with the Cochrane guidelines as described in the Methods section. The specific frameworks used are detailed as follows:

The PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) framework, which ensures transparency and completeness in systematic review protocols, is introduced in the opening statement of the Methods section in line number 39-43.

The PICO (Population, Intervention, Comparison, and Outcome) framework, which helps structure research questions in systematic reviews, is discussed in the Eligibility Criteria subsection, where we outline how it was used to define our inclusion and exclusion criteria in line number 68-72.

The ROBINS-I (Risk of Bias in Non-randomized Studies of Interventions) tool and RoB 2 (Revised Cochrane Risk of Bias Tool for Randomized Trials), which assess the risk of bias in non-randomized and randomized controlled trials, respectively, are described in the Risk of Bias Assessment subsection in line number 233-241.

The GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework, which provides a systematic approach for rating the certainty of evidence, is explained in the Quality of Evidence Assessment subsection, where we describe how it was applied to evaluate the overall strength of our findings in line number 314-319.

Expected Results and Measurable Outcomes
Reviewer Comment: The expected results of the methods used are not given. Hence, outcomes are not clear. They should include measurable results expected from the test.
Response:

We have added Expected results section in the manuscript in line 297-312. As this is a protocol, the exact study results are unknown. However, we anticipate obtaining measurable outcomes related to postprandial physiological changes. Specifically, we expect to extract quantitative data on heart rate, blood pressure, skin temperature, blood oxygen saturation, and blood glucose levels before and after meal consumption. These biomarkers will be compared pre- and post-meal, as well as between high- and low-calorie meal conditions. If applicable, we will also assess correlations between caloric intake and physiological responses through meta-regression analysis

We have expanded the primary and secondary outcomes and included measurable results to enhance clarity in line 45-66. Please find below the expanded ‘Primary Outcomes’ and ‘Secondary Outcomes’:

“Primary Outcomes
Our primary outcomes will focus on key physiological biomarker fluctuations associated with dietary intake, specifically comparing pre- and post-meal periods to assess immediate physiological changes after food consumption and high- vs. low-calorie meals to evaluate how meal calorie content influences biomarker variations, with biomarkers of interest including heart rate, blood pressure, blood glucose levels, metabolic markers, and other relevant physiological parameters.
Secondary Outcomes
Our secondary outcomes will focus on two key areas:

Correlation and Dose-Response Relationships – We will investigate the relationship between meal energy content and physiological biomarker responses, specifically assessing whether higher-calorie meals elicit stronger or more prolonged physiological changes.

Wearable Technology Capabilities for Dietary Monitoring – We will evaluate the accuracy and effectiveness of wearable sensing technologies (e.g., smartwatches, continuous glucose monitors, bioimpedance sensors) in detecting meal-induced physiological changes and compare wearable-derived data with traditional clinical measurements to assess their real-world applicability in dietary monitoring.”

Expected Findings from Secondary Research
Reviewer Comment: It looks more like writing a review, but expected results and findings extracted from secondary research are not given.
Response:

This protocol outlines the methodology for a systematic review and meta-analysis. We have made in cleared in the method section in line 39-43 that “we will systematically identify, extract and synthesize data from eligible studies to determine the physiological biomarkers associated with food and energy intake.”

For data extraction, as stated in the line 188-193 “Data will be extracted from eligible studies, including quantitative measures of physiological biomarkers before and after meal consumption. These extracted findings will be synthesized through meta-analysis (if feasible) or narrative synthesis to determine trends in postprandial physiological changes.”

We have added a section of Expected Results /Findings “ in the manuscript in line 297-312. Please find below the ‘Expected Results/Findings’ added:

“Expected Results/Findings
Based on previous literature and physiological mechanisms, we anticipate the following outcomes:

Transient increases in heart rate and blood pressure post-meal, with potentially greater fluctuations following high-calorie meals. We also expect a correlation between meal calorie content and the magnitude of postprandial changes compared to baseline measurements.

Variations in blood glucose and metabolic markers, influenced by meal composition and individual metabolic responses. For example, higher-calorie meals, particularly those rich in carbohydrates, are expected to lead to greater postprandial increases in blood glucose levels.

A more pronounced cardiovascular and metabolic response to high-calorie meals compared to low-calorie meals, potentially reflecting differences in autonomic regulation, metabolic load, and the body’s adaptive mechanisms to energy intake.”

Comparison with Traditional Methods for Monitoring Physiological Biomarkers
Reviewer Comment: The manuscript states that it will compare wearable sensors with traditional methods for monitoring physiological biomarkers related to food intake. However, it does not specify which traditional methods will be compared.
Response:

To clarify the traditional methods intended for comparison with wearable sensing technologies, the following paragraph has been added to the ‘Data Extraction’ section at line 218-226: “As the data extraction and synthesis is still ongoing, we cannot definitively determine which traditional methods will be available for comparison, as this depends on the data available in the included studies. However, we expect to include comparisons with standard clinical assessments—such as pulse oximeters for heart rate and oxygen saturation, upper-arm blood pressure monitors for systolic and diastolic blood pressure, and lab-based tests for glucose and metabolic markers. Our systematic review will identify and compare the wearable sensor-based methods with these traditional approaches where data are available.”

Sincerely,
Jiaying Zhou
Dear Reviewer,
We sincerely appreciate your time and valuable feedback on our manuscript. Your comments have helped us refine our work, and we have made the necessary revisions accordingly. Below, we address each of your concerns in detail.
Response to Specific Comments:
Journal Focus
Reviewer Comment: The work is innovative but does not touch the theme of oncology or related research as is the focus of the journal.

Response:

As stated in F1000Research’s scope, “F1000Research publishes articles and other research outputs reporting basic scientific, scholarly, translational and clinical research across the physical and life sciences, engineering, medicine, social sciences and humanities.” and it “ publishes different type of research, including clinical trials, systematic reviews, software tools, method articles, and many others”. https://f1000research.com/about#aims-and-scope

The present work describes a study protocol aiming to identify new tools for tracking food and energy intake, which may help combat the diet-related diseases such as obesity. This work aligns with the journal’s aims and scope.

Clarifying that this is a secondary research study and improving PICO explanation
Reviewer Comment: It should be made clear that it is a secondary research. The PICO method is not explained, and the different PICOs are given with some repetition.
Response: We confirm the following edits have been made to clarify the study design and improved PICO explanation:

We have stated in the title, Introduction and Methods sections that this is a study protocol for systematic review and meta-analysis, making it clear that it is a secondary research study.

The PICO framework was applied to structure both the eligibility criteria and data extraction items. A detailed explanation of this framework is provided in the Methods section, under “Eligibility criteria for including studies.” in line number 68-72.

Regarding the repetition in the ‘Study design and context’ section, please find below the revised version, which removes redundancy. We have revised the study design and context section, in the line 127-136 of the manuscript to remove redundancy. The revised version is below:

“Study Design and Context
Inclusion Criteria:

Experiential studies involving human participants in either controlled or real-life environments.

Randomized or non-randomized trials, including single-arm studies.

English-language articles published in peer-reviewed journals.

Exclusion Criteria:

Review articles, commentaries, and protocols.

Studies without human involvement.

A publication cutoff date of February 7, 2024, will be applied.”

Explanation of Different Frameworks
Reviewer Comment: Different frameworks are being referred to but not explained.
Response:

We have followed a standardized framework for conducting a systematic review in accordance with the Cochrane guidelines as described in the Methods section. The specific frameworks used are detailed as follows:

The PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) framework, which ensures transparency and completeness in systematic review protocols, is introduced in the opening statement of the Methods section in line number 39-43.

The PICO (Population, Intervention, Comparison, and Outcome) framework, which helps structure research questions in systematic reviews, is discussed in the Eligibility Criteria subsection, where we outline how it was used to define our inclusion and exclusion criteria in line number 68-72.

The ROBINS-I (Risk of Bias in Non-randomized Studies of Interventions) tool and RoB 2 (Revised Cochrane Risk of Bias Tool for Randomized Trials), which assess the risk of bias in non-randomized and randomized controlled trials, respectively, are described in the Risk of Bias Assessment subsection in line number 233-241.

The GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework, which provides a systematic approach for rating the certainty of evidence, is explained in the Quality of Evidence Assessment subsection, where we describe how it was applied to evaluate the overall strength of our findings in line number 314-319.

Expected Results and Measurable Outcomes
Reviewer Comment: The expected results of the methods used are not given. Hence, outcomes are not clear. They should include measurable results expected from the test.
Response:

We have added Expected results section in the manuscript in line 297-312. As this is a protocol, the exact study results are unknown. However, we anticipate obtaining measurable outcomes related to postprandial physiological changes. Specifically, we expect to extract quantitative data on heart rate, blood pressure, skin temperature, blood oxygen saturation, and blood glucose levels before and after meal consumption. These biomarkers will be compared pre- and post-meal, as well as between high- and low-calorie meal conditions. If applicable, we will also assess correlations between caloric intake and physiological responses through meta-regression analysis

We have expanded the primary and secondary outcomes and included measurable results to enhance clarity in line 45-66. Please find below the expanded ‘Primary Outcomes’ and ‘Secondary Outcomes’:

“Primary Outcomes
Our primary outcomes will focus on key physiological biomarker fluctuations associated with dietary intake, specifically comparing pre- and post-meal periods to assess immediate physiological changes after food consumption and high- vs. low-calorie meals to evaluate how meal calorie content influences biomarker variations, with biomarkers of interest including heart rate, blood pressure, blood glucose levels, metabolic markers, and other relevant physiological parameters.
Secondary Outcomes
Our secondary outcomes will focus on two key areas:

Correlation and Dose-Response Relationships – We will investigate the relationship between meal energy content and physiological biomarker responses, specifically assessing whether higher-calorie meals elicit stronger or more prolonged physiological changes.

Wearable Technology Capabilities for Dietary Monitoring – We will evaluate the accuracy and effectiveness of wearable sensing technologies (e.g., smartwatches, continuous glucose monitors, bioimpedance sensors) in detecting meal-induced physiological changes and compare wearable-derived data with traditional clinical measurements to assess their real-world applicability in dietary monitoring.”

Expected Findings from Secondary Research
Reviewer Comment: It looks more like writing a review, but expected results and findings extracted from secondary research are not given.
Response:

This protocol outlines the methodology for a systematic review and meta-analysis. We have made in cleared in the method section in line 39-43 that “we will systematically identify, extract and synthesize data from eligible studies to determine the physiological biomarkers associated with food and energy intake.”

For data extraction, as stated in the line 188-193 “Data will be extracted from eligible studies, including quantitative measures of physiological biomarkers before and after meal consumption. These extracted findings will be synthesized through meta-analysis (if feasible) or narrative synthesis to determine trends in postprandial physiological changes.”

We have added a section of Expected Results /Findings “ in the manuscript in line 297-312. Please find below the ‘Expected Results/Findings’ added:

“Expected Results/Findings
Based on previous literature and physiological mechanisms, we anticipate the following outcomes:

Transient increases in heart rate and blood pressure post-meal, with potentially greater fluctuations following high-calorie meals. We also expect a correlation between meal calorie content and the magnitude of postprandial changes compared to baseline measurements.

Variations in blood glucose and metabolic markers, influenced by meal composition and individual metabolic responses. For example, higher-calorie meals, particularly those rich in carbohydrates, are expected to lead to greater postprandial increases in blood glucose levels.

A more pronounced cardiovascular and metabolic response to high-calorie meals compared to low-calorie meals, potentially reflecting differences in autonomic regulation, metabolic load, and the body’s adaptive mechanisms to energy intake.”

Comparison with Traditional Methods for Monitoring Physiological Biomarkers
Reviewer Comment: The manuscript states that it will compare wearable sensors with traditional methods for monitoring physiological biomarkers related to food intake. However, it does not specify which traditional methods will be compared.
Response:

To clarify the traditional methods intended for comparison with wearable sensing technologies, the following paragraph has been added to the ‘Data Extraction’ section at line 218-226: “As the data extraction and synthesis is still ongoing, we cannot definitively determine which traditional methods will be available for comparison, as this depends on the data available in the included studies. However, we expect to include comparisons with standard clinical assessments—such as pulse oximeters for heart rate and oxygen saturation, upper-arm blood pressure monitors for systolic and diastolic blood pressure, and lab-based tests for glucose and metabolic markers. Our systematic review will identify and compare the wearable sensor-based methods with these traditional approaches where data are available.”

Sincerely,
Jiaying Zhou
Competing Interests: The authors declare no competing interests. Close
Report a concern
Respond or Comment

COMMENTS ON THIS REPORT

Author Response 03 Apr 2025

Jiaying Zhou, 1. Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK

03 Apr 2025

Author Response
Dear Reviewer,
We sincerely appreciate your time and valuable feedback on our manuscript. Your comments have helped us refine our work, and we have made the necessary revisions accordingly. Below, ... Continue reading
Dear Reviewer,
We sincerely appreciate your time and valuable feedback on our manuscript. Your comments have helped us refine our work, and we have made the necessary revisions accordingly. Below, we address each of your concerns in detail.
Response to Specific Comments:
Journal Focus
Reviewer Comment: The work is innovative but does not touch the theme of oncology or related research as is the focus of the journal.

Response:

As stated in F1000Research’s scope, “F1000Research publishes articles and other research outputs reporting basic scientific, scholarly, translational and clinical research across the physical and life sciences, engineering, medicine, social sciences and humanities.” and it “ publishes different type of research, including clinical trials, systematic reviews, software tools, method articles, and many others”. https://f1000research.com/about#aims-and-scope

The present work describes a study protocol aiming to identify new tools for tracking food and energy intake, which may help combat the diet-related diseases such as obesity. This work aligns with the journal’s aims and scope.

Clarifying that this is a secondary research study and improving PICO explanation
Reviewer Comment: It should be made clear that it is a secondary research. The PICO method is not explained, and the different PICOs are given with some repetition.
Response: We confirm the following edits have been made to clarify the study design and improved PICO explanation:

We have stated in the title, Introduction and Methods sections that this is a study protocol for systematic review and meta-analysis, making it clear that it is a secondary research study.

The PICO framework was applied to structure both the eligibility criteria and data extraction items. A detailed explanation of this framework is provided in the Methods section, under “Eligibility criteria for including studies.” in line number 68-72.

Regarding the repetition in the ‘Study design and context’ section, please find below the revised version, which removes redundancy. We have revised the study design and context section, in the line 127-136 of the manuscript to remove redundancy. The revised version is below:

“Study Design and Context
Inclusion Criteria:

Experiential studies involving human participants in either controlled or real-life environments.

Randomized or non-randomized trials, including single-arm studies.

English-language articles published in peer-reviewed journals.

Exclusion Criteria:

Review articles, commentaries, and protocols.

Studies without human involvement.

A publication cutoff date of February 7, 2024, will be applied.”

Explanation of Different Frameworks
Reviewer Comment: Different frameworks are being referred to but not explained.
Response:

We have followed a standardized framework for conducting a systematic review in accordance with the Cochrane guidelines as described in the Methods section. The specific frameworks used are detailed as follows:

The PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) framework, which ensures transparency and completeness in systematic review protocols, is introduced in the opening statement of the Methods section in line number 39-43.

The PICO (Population, Intervention, Comparison, and Outcome) framework, which helps structure research questions in systematic reviews, is discussed in the Eligibility Criteria subsection, where we outline how it was used to define our inclusion and exclusion criteria in line number 68-72.

The ROBINS-I (Risk of Bias in Non-randomized Studies of Interventions) tool and RoB 2 (Revised Cochrane Risk of Bias Tool for Randomized Trials), which assess the risk of bias in non-randomized and randomized controlled trials, respectively, are described in the Risk of Bias Assessment subsection in line number 233-241.

The GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework, which provides a systematic approach for rating the certainty of evidence, is explained in the Quality of Evidence Assessment subsection, where we describe how it was applied to evaluate the overall strength of our findings in line number 314-319.

Expected Results and Measurable Outcomes
Reviewer Comment: The expected results of the methods used are not given. Hence, outcomes are not clear. They should include measurable results expected from the test.
Response:

We have added Expected results section in the manuscript in line 297-312. As this is a protocol, the exact study results are unknown. However, we anticipate obtaining measurable outcomes related to postprandial physiological changes. Specifically, we expect to extract quantitative data on heart rate, blood pressure, skin temperature, blood oxygen saturation, and blood glucose levels before and after meal consumption. These biomarkers will be compared pre- and post-meal, as well as between high- and low-calorie meal conditions. If applicable, we will also assess correlations between caloric intake and physiological responses through meta-regression analysis

We have expanded the primary and secondary outcomes and included measurable results to enhance clarity in line 45-66. Please find below the expanded ‘Primary Outcomes’ and ‘Secondary Outcomes’:

“Primary Outcomes
Our primary outcomes will focus on key physiological biomarker fluctuations associated with dietary intake, specifically comparing pre- and post-meal periods to assess immediate physiological changes after food consumption and high- vs. low-calorie meals to evaluate how meal calorie content influences biomarker variations, with biomarkers of interest including heart rate, blood pressure, blood glucose levels, metabolic markers, and other relevant physiological parameters.
Secondary Outcomes
Our secondary outcomes will focus on two key areas:

Correlation and Dose-Response Relationships – We will investigate the relationship between meal energy content and physiological biomarker responses, specifically assessing whether higher-calorie meals elicit stronger or more prolonged physiological changes.

Wearable Technology Capabilities for Dietary Monitoring – We will evaluate the accuracy and effectiveness of wearable sensing technologies (e.g., smartwatches, continuous glucose monitors, bioimpedance sensors) in detecting meal-induced physiological changes and compare wearable-derived data with traditional clinical measurements to assess their real-world applicability in dietary monitoring.”

Expected Findings from Secondary Research
Reviewer Comment: It looks more like writing a review, but expected results and findings extracted from secondary research are not given.
Response:

This protocol outlines the methodology for a systematic review and meta-analysis. We have made in cleared in the method section in line 39-43 that “we will systematically identify, extract and synthesize data from eligible studies to determine the physiological biomarkers associated with food and energy intake.”

For data extraction, as stated in the line 188-193 “Data will be extracted from eligible studies, including quantitative measures of physiological biomarkers before and after meal consumption. These extracted findings will be synthesized through meta-analysis (if feasible) or narrative synthesis to determine trends in postprandial physiological changes.”

We have added a section of Expected Results /Findings “ in the manuscript in line 297-312. Please find below the ‘Expected Results/Findings’ added:

“Expected Results/Findings
Based on previous literature and physiological mechanisms, we anticipate the following outcomes:

Transient increases in heart rate and blood pressure post-meal, with potentially greater fluctuations following high-calorie meals. We also expect a correlation between meal calorie content and the magnitude of postprandial changes compared to baseline measurements.

Variations in blood glucose and metabolic markers, influenced by meal composition and individual metabolic responses. For example, higher-calorie meals, particularly those rich in carbohydrates, are expected to lead to greater postprandial increases in blood glucose levels.

A more pronounced cardiovascular and metabolic response to high-calorie meals compared to low-calorie meals, potentially reflecting differences in autonomic regulation, metabolic load, and the body’s adaptive mechanisms to energy intake.”

Comparison with Traditional Methods for Monitoring Physiological Biomarkers
Reviewer Comment: The manuscript states that it will compare wearable sensors with traditional methods for monitoring physiological biomarkers related to food intake. However, it does not specify which traditional methods will be compared.
Response:

To clarify the traditional methods intended for comparison with wearable sensing technologies, the following paragraph has been added to the ‘Data Extraction’ section at line 218-226: “As the data extraction and synthesis is still ongoing, we cannot definitively determine which traditional methods will be available for comparison, as this depends on the data available in the included studies. However, we expect to include comparisons with standard clinical assessments—such as pulse oximeters for heart rate and oxygen saturation, upper-arm blood pressure monitors for systolic and diastolic blood pressure, and lab-based tests for glucose and metabolic markers. Our systematic review will identify and compare the wearable sensor-based methods with these traditional approaches where data are available.”

Sincerely,
Jiaying Zhou
Dear Reviewer,
We sincerely appreciate your time and valuable feedback on our manuscript. Your comments have helped us refine our work, and we have made the necessary revisions accordingly. Below, we address each of your concerns in detail.
Response to Specific Comments:
Journal Focus
Reviewer Comment: The work is innovative but does not touch the theme of oncology or related research as is the focus of the journal.

Response:

As stated in F1000Research’s scope, “F1000Research publishes articles and other research outputs reporting basic scientific, scholarly, translational and clinical research across the physical and life sciences, engineering, medicine, social sciences and humanities.” and it “ publishes different type of research, including clinical trials, systematic reviews, software tools, method articles, and many others”. https://f1000research.com/about#aims-and-scope

The present work describes a study protocol aiming to identify new tools for tracking food and energy intake, which may help combat the diet-related diseases such as obesity. This work aligns with the journal’s aims and scope.

Clarifying that this is a secondary research study and improving PICO explanation
Reviewer Comment: It should be made clear that it is a secondary research. The PICO method is not explained, and the different PICOs are given with some repetition.
Response: We confirm the following edits have been made to clarify the study design and improved PICO explanation:

We have stated in the title, Introduction and Methods sections that this is a study protocol for systematic review and meta-analysis, making it clear that it is a secondary research study.

The PICO framework was applied to structure both the eligibility criteria and data extraction items. A detailed explanation of this framework is provided in the Methods section, under “Eligibility criteria for including studies.” in line number 68-72.

Regarding the repetition in the ‘Study design and context’ section, please find below the revised version, which removes redundancy. We have revised the study design and context section, in the line 127-136 of the manuscript to remove redundancy. The revised version is below:

“Study Design and Context
Inclusion Criteria:

Experiential studies involving human participants in either controlled or real-life environments.

Randomized or non-randomized trials, including single-arm studies.

English-language articles published in peer-reviewed journals.

Exclusion Criteria:

Review articles, commentaries, and protocols.

Studies without human involvement.

A publication cutoff date of February 7, 2024, will be applied.”

Explanation of Different Frameworks
Reviewer Comment: Different frameworks are being referred to but not explained.
Response:

We have followed a standardized framework for conducting a systematic review in accordance with the Cochrane guidelines as described in the Methods section. The specific frameworks used are detailed as follows:

The PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) framework, which ensures transparency and completeness in systematic review protocols, is introduced in the opening statement of the Methods section in line number 39-43.

The PICO (Population, Intervention, Comparison, and Outcome) framework, which helps structure research questions in systematic reviews, is discussed in the Eligibility Criteria subsection, where we outline how it was used to define our inclusion and exclusion criteria in line number 68-72.

The ROBINS-I (Risk of Bias in Non-randomized Studies of Interventions) tool and RoB 2 (Revised Cochrane Risk of Bias Tool for Randomized Trials), which assess the risk of bias in non-randomized and randomized controlled trials, respectively, are described in the Risk of Bias Assessment subsection in line number 233-241.

The GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework, which provides a systematic approach for rating the certainty of evidence, is explained in the Quality of Evidence Assessment subsection, where we describe how it was applied to evaluate the overall strength of our findings in line number 314-319.

Expected Results and Measurable Outcomes
Reviewer Comment: The expected results of the methods used are not given. Hence, outcomes are not clear. They should include measurable results expected from the test.
Response:

We have added Expected results section in the manuscript in line 297-312. As this is a protocol, the exact study results are unknown. However, we anticipate obtaining measurable outcomes related to postprandial physiological changes. Specifically, we expect to extract quantitative data on heart rate, blood pressure, skin temperature, blood oxygen saturation, and blood glucose levels before and after meal consumption. These biomarkers will be compared pre- and post-meal, as well as between high- and low-calorie meal conditions. If applicable, we will also assess correlations between caloric intake and physiological responses through meta-regression analysis

We have expanded the primary and secondary outcomes and included measurable results to enhance clarity in line 45-66. Please find below the expanded ‘Primary Outcomes’ and ‘Secondary Outcomes’:

“Primary Outcomes
Our primary outcomes will focus on key physiological biomarker fluctuations associated with dietary intake, specifically comparing pre- and post-meal periods to assess immediate physiological changes after food consumption and high- vs. low-calorie meals to evaluate how meal calorie content influences biomarker variations, with biomarkers of interest including heart rate, blood pressure, blood glucose levels, metabolic markers, and other relevant physiological parameters.
Secondary Outcomes
Our secondary outcomes will focus on two key areas:

Correlation and Dose-Response Relationships – We will investigate the relationship between meal energy content and physiological biomarker responses, specifically assessing whether higher-calorie meals elicit stronger or more prolonged physiological changes.

Wearable Technology Capabilities for Dietary Monitoring – We will evaluate the accuracy and effectiveness of wearable sensing technologies (e.g., smartwatches, continuous glucose monitors, bioimpedance sensors) in detecting meal-induced physiological changes and compare wearable-derived data with traditional clinical measurements to assess their real-world applicability in dietary monitoring.”

Expected Findings from Secondary Research
Reviewer Comment: It looks more like writing a review, but expected results and findings extracted from secondary research are not given.
Response:

This protocol outlines the methodology for a systematic review and meta-analysis. We have made in cleared in the method section in line 39-43 that “we will systematically identify, extract and synthesize data from eligible studies to determine the physiological biomarkers associated with food and energy intake.”

For data extraction, as stated in the line 188-193 “Data will be extracted from eligible studies, including quantitative measures of physiological biomarkers before and after meal consumption. These extracted findings will be synthesized through meta-analysis (if feasible) or narrative synthesis to determine trends in postprandial physiological changes.”

We have added a section of Expected Results /Findings “ in the manuscript in line 297-312. Please find below the ‘Expected Results/Findings’ added:

“Expected Results/Findings
Based on previous literature and physiological mechanisms, we anticipate the following outcomes:

Transient increases in heart rate and blood pressure post-meal, with potentially greater fluctuations following high-calorie meals. We also expect a correlation between meal calorie content and the magnitude of postprandial changes compared to baseline measurements.

Variations in blood glucose and metabolic markers, influenced by meal composition and individual metabolic responses. For example, higher-calorie meals, particularly those rich in carbohydrates, are expected to lead to greater postprandial increases in blood glucose levels.

A more pronounced cardiovascular and metabolic response to high-calorie meals compared to low-calorie meals, potentially reflecting differences in autonomic regulation, metabolic load, and the body’s adaptive mechanisms to energy intake.”

Comparison with Traditional Methods for Monitoring Physiological Biomarkers
Reviewer Comment: The manuscript states that it will compare wearable sensors with traditional methods for monitoring physiological biomarkers related to food intake. However, it does not specify which traditional methods will be compared.
Response:

To clarify the traditional methods intended for comparison with wearable sensing technologies, the following paragraph has been added to the ‘Data Extraction’ section at line 218-226: “As the data extraction and synthesis is still ongoing, we cannot definitively determine which traditional methods will be available for comparison, as this depends on the data available in the included studies. However, we expect to include comparisons with standard clinical assessments—such as pulse oximeters for heart rate and oxygen saturation, upper-arm blood pressure monitors for systolic and diastolic blood pressure, and lab-based tests for glucose and metabolic markers. Our systematic review will identify and compare the wearable sensor-based methods with these traditional approaches where data are available.”

Sincerely,
Jiaying Zhou
Competing Interests: The authors declare no competing interests. Close
Report a concern

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Version 2

VERSION 2 PUBLISHED 13 Nov 2024

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Version 2 (revision) 03 Apr 25	read
Version 1 13 Nov 24	read

Faiza Jan Iftikhar, National University of Technology (NUTECH), Islamabad, Pakistan

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Reviewer Report

2 Views

05 May 2025 | for Version 2

Faiza Jan Iftikhar, National University of Technology (NUTECH), Islamabad, Pakistan

2 Views Cite this report Responses(0)

Approved With Reservations

Avoid using first person (plural) pronouns
2.      Two independent reviewers will screen and select articles based on pre-defined eligibility criteria, with a third review to resolve any discrepancies. What is meant by reviewer here?
3.      Our primary outcome will be the comparison of physiological biomarkers: mention the physiological biomarkers here
4.      Intestinal blood flow measured using wearable or traditional devices: what wearables are used to detect intestinal blood flow. The intestinal flow is mentioned only twice and it seems it is added as an afterthought. Please check.
5.      The results section shows no graphs. Is that normal when publishing a study protocol?

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Bio sensor /chemical sensors including wearable sensor.

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Reviewer Report

15 Views

27 Jan 2025 | for Version 1

Faiza Jan Iftikhar, National University of Technology (NUTECH), Islamabad, Pakistan

15 Views Cite this report Responses(1)

Approved With Reservations

It should be made clear that it is a secondary research. The PICO method is not explained and the different PICOs are given though with some repetition
Different frameworks are being referred to but not explained.
The expected results of the methods used is not given. Hence outcomes are not clear. They should include measurable results expected from the test
It looks more like writing a review but expected results and findings extracted from secondary research is not given
It says: Comparing wearable sensors with traditional methods for monitoring physiological biomarkers related to food intake. Mention what are the traditional methods that will be compared with.

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?

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

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Bio sensor /chemical sensors including wearable sensor.

Respond to this report

Responses (1)

Author Response

03 Apr 2025

Jiaying Zhou, 1. Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK

Dear Reviewer,
We sincerely appreciate your time and valuable feedback on our manuscript. Your comments have helped us refine our work, and we have made the necessary revisions accordingly. Below, we address each of your concerns in detail.
Response to Specific Comments:
Journal Focus
Reviewer Comment: The work is innovative but does not touch the theme of oncology or related research as is the focus of the journal.

Response:

As stated in F1000Research’s scope, “F1000Research publishes articles and other research outputs reporting basic scientific, scholarly, translational and clinical research across the physical and life sciences, engineering, medicine, social sciences and humanities.” and it “ publishes different type of research, including clinical trials, systematic reviews, software tools, method articles, and many others”. https://f1000research.com/about#aims-and-scope

The present work describes a study protocol aiming to identify new tools for tracking food and energy intake, which may help combat the diet-related diseases such as obesity. This work aligns with the journal’s aims and scope.

Clarifying that this is a secondary research study and improving PICO explanation
Reviewer Comment: It should be made clear that it is a secondary research. The PICO method is not explained, and the different PICOs are given with some repetition.
Response: We confirm the following edits have been made to clarify the study design and improved PICO explanation:

We have stated in the title, Introduction and Methods sections that this is a study protocol for systematic review and meta-analysis, making it clear that it is a secondary research study.
The PICO framework was applied to structure both the eligibility criteria and data extraction items. A detailed explanation of this framework is provided in the Methods section, under “Eligibility criteria for including studies.” in line number 68-72.
Regarding the repetition in the ‘Study design and context’ section, please find below the revised version, which removes redundancy. We have revised the study design and context section, in the line 127-136 of the manuscript to remove redundancy. The revised version is below:

“Study Design and Context
Inclusion Criteria:

Experiential studies involving human participants in either controlled or real-life environments.
Randomized or non-randomized trials, including single-arm studies.
English-language articles published in peer-reviewed journals.

Exclusion Criteria:

Review articles, commentaries, and protocols.
Studies without human involvement.

A publication cutoff date of February 7, 2024, will be applied.”

Explanation of Different Frameworks
Reviewer Comment: Different frameworks are being referred to but not explained.
Response:

We have followed a standardized framework for conducting a systematic review in accordance with the Cochrane guidelines as described in the Methods section. The specific frameworks used are detailed as follows:

The PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) framework, which ensures transparency and completeness in systematic review protocols, is introduced in the opening statement of the Methods section in line number 39-43.
The PICO (Population, Intervention, Comparison, and Outcome) framework, which helps structure research questions in systematic reviews, is discussed in the Eligibility Criteria subsection, where we outline how it was used to define our inclusion and exclusion criteria in line number 68-72.
The ROBINS-I (Risk of Bias in Non-randomized Studies of Interventions) tool and RoB 2 (Revised Cochrane Risk of Bias Tool for Randomized Trials), which assess the risk of bias in non-randomized and randomized controlled trials, respectively, are described in the Risk of Bias Assessment subsection in line number 233-241.
The GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework, which provides a systematic approach for rating the certainty of evidence, is explained in the Quality of Evidence Assessment subsection, where we describe how it was applied to evaluate the overall strength of our findings in line number 314-319.

Expected Results and Measurable Outcomes
Reviewer Comment: The expected results of the methods used are not given. Hence, outcomes are not clear. They should include measurable results expected from the test.
Response:

We have added Expected results section in the manuscript in line 297-312. As this is a protocol, the exact study results are unknown. However, we anticipate obtaining measurable outcomes related to postprandial physiological changes. Specifically, we expect to extract quantitative data on heart rate, blood pressure, skin temperature, blood oxygen saturation, and blood glucose levels before and after meal consumption. These biomarkers will be compared pre- and post-meal, as well as between high- and low-calorie meal conditions. If applicable, we will also assess correlations between caloric intake and physiological responses through meta-regression analysis
We have expanded the primary and secondary outcomes and included measurable results to enhance clarity in line 45-66. Please find below the expanded ‘Primary Outcomes’ and ‘Secondary Outcomes’:

“Primary Outcomes
Our primary outcomes will focus on key physiological biomarker fluctuations associated with dietary intake, specifically comparing pre- and post-meal periods to assess immediate physiological changes after food consumption and high- vs. low-calorie meals to evaluate how meal calorie content influences biomarker variations, with biomarkers of interest including heart rate, blood pressure, blood glucose levels, metabolic markers, and other relevant physiological parameters.
Secondary Outcomes
Our secondary outcomes will focus on two key areas:

Correlation and Dose-Response Relationships – We will investigate the relationship between meal energy content and physiological biomarker responses, specifically assessing whether higher-calorie meals elicit stronger or more prolonged physiological changes.
Wearable Technology Capabilities for Dietary Monitoring – We will evaluate the accuracy and effectiveness of wearable sensing technologies (e.g., smartwatches, continuous glucose monitors, bioimpedance sensors) in detecting meal-induced physiological changes and compare wearable-derived data with traditional clinical measurements to assess their real-world applicability in dietary monitoring.”

Expected Findings from Secondary Research
Reviewer Comment: It looks more like writing a review, but expected results and findings extracted from secondary research are not given.
Response:

This protocol outlines the methodology for a systematic review and meta-analysis. We have made in cleared in the method section in line 39-43 that “we will systematically identify, extract and synthesize data from eligible studies to determine the physiological biomarkers associated with food and energy intake.”
For data extraction, as stated in the line 188-193 “Data will be extracted from eligible studies, including quantitative measures of physiological biomarkers before and after meal consumption. These extracted findings will be synthesized through meta-analysis (if feasible) or narrative synthesis to determine trends in postprandial physiological changes.”
We have added a section of Expected Results /Findings “ in the manuscript in line 297-312. Please find below the ‘Expected Results/Findings’ added:

“Expected Results/Findings
Based on previous literature and physiological mechanisms, we anticipate the following outcomes:

Transient increases in heart rate and blood pressure post-meal, with potentially greater fluctuations following high-calorie meals. We also expect a correlation between meal calorie content and the magnitude of postprandial changes compared to baseline measurements.
Variations in blood glucose and metabolic markers, influenced by meal composition and individual metabolic responses. For example, higher-calorie meals, particularly those rich in carbohydrates, are expected to lead to greater postprandial increases in blood glucose levels.
A more pronounced cardiovascular and metabolic response to high-calorie meals compared to low-calorie meals, potentially reflecting differences in autonomic regulation, metabolic load, and the body’s adaptive mechanisms to energy intake.”

Comparison with Traditional Methods for Monitoring Physiological Biomarkers
Reviewer Comment: The manuscript states that it will compare wearable sensors with traditional methods for monitoring physiological biomarkers related to food intake. However, it does not specify which traditional methods will be compared.
Response:

To clarify the traditional methods intended for comparison with wearable sensing technologies, the following paragraph has been added to the ‘Data Extraction’ section at line 218-226: “As the data extraction and synthesis is still ongoing, we cannot definitively determine which traditional methods will be available for comparison, as this depends on the data available in the included studies. However, we expect to include comparisons with standard clinical assessments—such as pulse oximeters for heart rate and oxygen saturation, upper-arm blood pressure monitors for systolic and diastolic blood pressure, and lab-based tests for glucose and metabolic markers. Our systematic review will identify and compare the wearable sensor-based methods with these traditional approaches where data are available.”

Sincerely,
Jiaying Zhou

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Competing Interests

The authors declare no competing interests.

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

[1] Burrows TL, Rollo ME: Advancement in Dietary Assessment and Self-Monitoring Using Technology. Nutrients. 2019; 11(7): 1648. PubMed Abstract | Publisher Full Text | Free Full Text

[2] Cuparencu C, Bulmuş-Tüccar T, Stanstrup J, et al.: Towards nutrition with precision: unlocking biomarkers as dietary assessment tools. Nat. Metab. 2024; 6(8): 1438–1453. PubMed Abstract | Publisher Full Text

[3] De Aguiar Cassiani R, Manfredi C, Santos JA, et al.: Arterial oxygen saturation and heart rate during a meal in chronic obstructive pulmonary disease.2011.

[4] Doulah A, Ghosh T, Hossain D, et al.: Energy intake estimation using a novel wearable sensor and food images in a laboratory (pseudo-free-living) meal setting: quantification and contribution of sources of error. Springer Science and Business Media LLC; 2022.

[5] Higgins JPT, Thomas J, Chandler J, et al.: Cochrane Handbook for Systematic Reviews of Interventions. Wiley Cochrane Series. 2nd ed.Newark: John Wiley & Sons, Ltd; 2019.

[6] Maruvada P, Lampe JW, Wishart DS, et al.: Perspective: Dietary Biomarkers of Intake and Exposure—Exploration with Omics Approaches. Adv. Nutr. 2020; 11(2): 200–215. PubMed Abstract | Publisher Full Text | Free Full Text

[7] McGuinness LA, Higgins JPT: Risk-of-bias VISualization (robvis): An R package and Shiny web app for visualizing risk-of-bias assessments. Res. Synth. Methods. 2021; 12(1): 55–61. PubMed Abstract | Publisher Full Text

[8] Moher D, Shamseer L, Clarke M, et al.: Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst. Rev. 2015; 4(1). PubMed Abstract | Publisher Full Text | Free Full Text

[9] Shamseer L, Moher D, Clarke M, et al.: Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ. 2015; 349(jan02 1): 7647. PubMed Abstract | Publisher Full Text

[10] Sidery MB, Macdonald IA: The effect of meal size on the cardiovascular responses to food ingestion. Br. J. Nutr. 1994; 71(6): 835–848. PubMed Abstract | Publisher Full Text

[11] Sit SP, Chou CC: Time course of jejunal blood flow, O2 uptake, and O2 extraction during nutrient absorption. Am. J. Physiol. Heart Circ. Physiol. 1984; 247(3): H395–H402. PubMed Abstract | Publisher Full Text

[12] Sterne JAC, Savović J, Page MJ, et al.: RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ (Online). 2019; 366: l4898. Publisher Full Text

[13] Sterne JA, Hernán MA, Reeves BC, et al.: ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ (Online). 2016; 355: i4919. PubMed Abstract | Publisher Full Text | Free Full Text

[14] Vu T, Lin F, Alshurafa N, et al.: Wearable Food Intake Monitoring Technologies: A Comprehensive Review. Computers (Basel). 2017; 6(1): 4. Publisher Full Text

[15] Westerterp KR: Diet induced thermogenesis. Nutr. Metab. 2004; 1(1): 5. PubMed Abstract | Publisher Full Text | Free Full Text

[16] Zhou J, Shi M, Cai M: Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol. Dataset. figshare. 2024. Publisher Full Text

Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol

Abstract

Background

Methods

Discussion

Systematic Review Registration

Keywords

Revised Amendments from Version 1

Background

Methods

Outcomes

Eligibility criteria for including studies

Population

Intervention

Comparator

Outcomes

Study design and context

Information sources and search strategy

Screen and selection process

Data extraction

Risk of bias assessment

Visualization of bias assessment

Data synthesis

Handling missing and incomplete data

Confidence in cumulative evidence

Discussion

Declarations

Ethics and dissemination

Patient consent for publication

Author’s contributions

Data availability

Underlying data

Extended data

Reporting guidelines

References

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