Quality of Life of Type II Diabetic Patients

Sulochana Ghimire; Gita Neupane; Chanda Sah; Mahesh Raj Ghimire; Binita Soti

doi:10.12688/f1000research.176141.1

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Research Article

Quality of Life of Type II Diabetic Patients

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

Sulochana Ghimire ¹, Gita Neupane¹, Chanda Sah¹, Mahesh Raj Ghimire², Binita Soti³

Sulochana Ghimire ¹, Gita Neupane¹, [...] Chanda Sah¹, Mahesh Raj Ghimire², Binita Soti³

PUBLISHED 11 Mar 2026

Author details Author details

¹ Nursing, Universal College of Medical Sciences, Siddharthanagar, Lumbini Province, 32900, Nepal
² Medicine, Crimson Hospital, Tilottama, Lumbini, 32900, Nepal
³ Nursing, Lumbini Provincial Hospital, Butwol, Lumbini, 32900, Nepal

Sulochana Ghimire
Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

Gita Neupane
Roles: Conceptualization, Data Curation, Methodology, Supervision, Writing – Review & Editing

Chanda Sah
Roles: Data Curation, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

Mahesh Raj Ghimire
Roles: Conceptualization, Investigation, Methodology, Project Administration, Supervision, Validation, Writing – Review & Editing

Binita Soti
Roles: Data Curation, Investigation, Methodology, Project Administration, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

Abstract

Introduction

Diabetes Mellitus poses significant challenges to an individual’s well-being, affecting various aspects of their lives beyond the physical symptoms of the disease. Understanding the multidimensional aspects of QoL among patients with diabetes is crucial for providing holistic healthcare interventions and improving overall health outcomes. This study aimed to evaluate the quality of life of patients with type 2 Diabetes Mellitus.

Material and Methods

Descriptive cross-sectional study was conducted among 334 diagnosed cases of Type 2 Diabetes Mellitus for more than or equal to 6 months attending the outpatient department of UCMS-TH. Non-probability purposive sampling technique was used to select samples for the study. The WHOQOL-BREF questionnaire was used to measure QoL. Data were analyzed with descriptive statistics (frequency, percentage, mean, standard deviation) and inferential statistics (t-test, one way ANOVA and correlation test) to explore associations between QoL domains and sociodemographic characteristics.

Results

More than half (56.6%) of the respondents were between the age group of 41-60 years with a mean age of 58.42. The highest mean score ± SD was found in the social domain (60.77 ± 13.83), followed by the environmental (56.05 ± 10.38) and psychological domains (55.67 ±8.44), with the lowest mean domain score in the physical domain (49.99 ± 14.53). The results showed that diabetic patients, particularly women and those with comorbid conditions, reported a lower quality of life in all domains. Additionally, no significant association was found between a family history of diabetes and quality of life. There was a strong positive correlation between the physical and environmental domains of quality of life (r = 0.70, p< 0.001).

Conclusion

Comprehensive management strategies focusing on all dimensions of health are necessary to improve the quality of life of patients with Diabetes Mellitus.

Keywords

Diabetes Mellitus, Quality of Life, WHO QoL BREF

Corresponding author: Sulochana Ghimire

Competing interests: No competing interests were disclosed.

Grant information: The author(s) declared that no grants were involved in supporting this work.

Copyright: © 2026 Ghimire 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: Ghimire S, Neupane G, Sah C et al. Quality of Life of Type II Diabetic Patients [version 1; peer review: 1 approved with reservations]. F1000Research 2026, 15:392 (https://doi.org/10.12688/f1000research.176141.1) First published: 11 Mar 2026, 15:392 (https://doi.org/10.12688/f1000research.176141.1) Latest published: 11 Mar 2026, 15:392 (https://doi.org/10.12688/f1000research.176141.1)

Introduction

Background of the study

Diabetes Mellitus is a chronic disease that represents a significant global health challenge and is classified among the top four priority noncommunicable disease.¹ An estimated three in four people have Diabetes Mellitus in low- and middle-income countries.² The prevalence of prediabetes and diabetes has gradually increased with advancing age. The prevalence of diabetes Mellitus varied significantly across Nepal’s provinces, ranging from as low as 2% in province 6 to as high as 10% in provinces 3 and 4.³ Diabetes Mellitus complications include macrovascular (coronary artery disease, peripheral arterial disease, and stroke) and microvascular (nephropathy, neuropathy, and retinopathy).⁴ Diabetes Mellitus not only affects physical health but also social and mental health, including the psychological well-being of people living with it. Psychosocial issues frequently experienced by individuals with diabetes often have substantial adverse effects on their well-being.⁵ Individuals diagnosed with type 2 diabetes mellitus (T2DM) encounter notable obstacles during their treatment, potentially hindering effective disease control. Effective management of this condition can alleviate symptoms, enhance glycemic control, prevent complications, and minimize hospital readmissions and mortality.⁶ A qualitative study showed that certain adults, such as those aged >45 years with type 2 diabetes mellitus, encountered both physical and psychological ailments. Managing life with type 2 Diabetes Mellitus is impacted by factors including family support, inadequate adherence to treatment protocols, and availability of information, education, and communication resources.⁷ Increasing prevalence of Diabetes Mellitus will lead to a higher incidence of chronic and acute illnesses within the general population, resulting in significant implications for quality of life, healthcare service demand, and economic expenditures.⁸ Diabetes therapy, such as insulin use, impacts quality of life both positively by lowering high blood sugar levels and negatively by raising low blood sugar levels. Psychosocial burden also affects self-care and increases the risk of long-term complications that reduce QoL.⁹ The WHO defines Quality of Life as an individual’s view of their position in life, shaped by cultural value systems, goals, expectations, standards, and concerns.¹⁰ All members of the interprofessional healthcare team should acknowledge the importance of quality of life.¹¹ Diabetes Mellitus significantly affects QoL, physical health, emotional well-being, social interactions, and finances. Effective management strategies, including education, support, and access to healthcare resources, are essential to improve the QoL of individuals with Diabetes Mellitus. Understanding the quality of life of patients with type 2 diabetes mellitus is essential for formulating strategies to support patient-centered care, optimize treatment modalities, and promote overall well-being. This study aimed to assess the quality of life of people diagnosed with type 2 Diabetes Mellitus at a tertiary care center in Nepal. A preprint of this article has been deposited on medRxiv and is available at: https://doi.org/10.1101/2024.11.07.24316896.¹²

Materials and methods

Study setting

This cross-sectional descriptive study was conducted to determine the quality of life of patients with diabetes. The study was conducted at the Universal College of Medical Sciences, Teaching Hospital (UCMS-TH) Rupandehi, Nepal which is 750 bedded well equipped multi-specialty hospital. Participants were patients diagnosed with Type II Diabetes Mellitus for at least 6 months, attending the outpatient department of UCMS-TH, who consented to the study and were available to provide information during data collection.

Sampling

Sample size was determined using Cochran’s formula by taking a 95% confidence level and the prevalence of good quality of life of diabetic patients (P = 68%) from a study conducted in rural south India.¹³ Based on the calculation, 334 diabetic patients were involved in this study by using a non-probability purposive sampling technique, and respondents who visited the OPD were interviewed on a first-come first basis.

Research instrument

For data collection, a structured interview questionnaire was developed that consisted of the following two parts: the first part socio-demographic questions contains age, sex, marital status, education, occupation, family history of diabetes, years of diagnosis of diabetes, modalities of treatment, and comorbidities related questions.

The second part of the WHOQOL-BREF is a 26-item questionnaire measuring an individual’s quality of life. The WHOQOL-BREF assesses quality of life across four domains: physical health, psychological well-being, social relationships, and environment. It also includes two separate questions about overall quality of life and health perception. Each individual item of the WHOQOL-BREF was scored from 1 to 5 on a response scale.¹⁴ Domain scores are scaled in a positive direction (i.e., higher scores denote a higher quality of life). Three items (i.e., items 3, 4, and 26) are phrased negatively, so before calculating the raw score, three items were reversed scored. The mean score in each domain was multiplied by 4 to align with the WHOQOL-100 scores, then converted to a 0-100 scale, where 100 indicates the highest and 0 the lowest quality of life, as per the WHO scoring manual. The WHOQOL-BREF has a reliability of 0.896, as measured by Cronbach’s alpha coefficient and test–retest analysis.¹⁵ Permission to reproduce, reprint, and translate the WHO QoL Questionnaire was obtained from WHO. The English version of the questionnaire was translated into Nepali and back-translated before data collection. The pretesting of the instrument was performed on 33 respondents who were not included in the main study.

Ethical approval and consent

Ethical approval was obtained from the Institutional Review Committee of the Universal College of Medical Science (UCMS/IRC/030/23). Administrative approval for data collection was provided by the Medical Superintendent of UCMS-TH. Written informed consent was obtained from each respondent after explaining the objectives of the study. Respondents were assured of the confidentiality of their information. The collected data were checked immediately for completion and coded, edited, classified, entered, and cleaned. The researcher collected the data within six months (01^st October 2023 to 29^th March 2024).

Statistical analysis

The reliability of the pre-test, measured by Cronbach’s alpha, was 0.880. The Kolmogorov-Smirnov normality test scores showed a normal distribution, with a p-value of 0.068. Data analysis was performed using SPSS version 20. Associations between QoL domains and sociodemographic characteristics were tested using t – test or one-way ANOVA.

Results

A total of 334 respondents participated in the study. The sociodemographic information of the respondents is shown in Table 1. More than half (56.6%) of the respondents were between the age group of 41-60 years with a mean age of 58.42 ± 10.34 SD. Twenty-nine percent of the respondents perceived their overall good quality of life as and 21.9% of the respondents were satisfied with their health assessed by 1^st and 2^nd general question of the WHO QoL BREF Questionnaire, respectively.

Table 1. Socio-demographic characteristics of respondents.

		N = 334
Variables	Frequency	Percentage
Age (in completed years)
21-40	13	3.9
41-60	189	56.6
>60	132	39.5
*Mean ± SD (58.42 ± 10.34)*
Gender
Male	182	54.5
Female	152	45.5
Marital Status
Married	287	85.9
Unmarried	11	3.3
Divorced	36	10.8
Education
Illiterate	125	37.5
Literate	209	62.5
Occupation
Business	76	22.8
Service	86	25.7
Agriculture	55	16.5
Retired	15	4.5
Homemaker	102	30.5
Family History of Diabetes Mellitus
Yes	197	59.0
No	137	41.0
Duration of Diagnosis of Diabetes Mellitus
≤5 years	169	50.6
6-10 years	124	37.1
>10 years	41	12.3
Treatment used
Diet + Oral Agents	278	83.2
Diet + Insulin	45	13.5
Diet + Oral agents + Insulin	11	3.3
Comorbidities
Yes	179	53.6
No	155	46.4

The four domains of physical, psychological, social, and environmental scores denote an individual’s perception of quality of life in each domain and were analyzed according to the WHO QoL BREF questionnaire. Transformed scores were calculated from raw scores for comparison with WHOQOL the 100 score as shown in Table 2. The highest mean score ± SD was found in the social domain (60.77 ± 13.83), followed by the environmental (56.05 ± 10.38) and psychological domains (55.67 ±8.44), with the lowest mean domain score in the physical domain (49.99 ± 14.53).

Table 2. WHO-BREF QOL domain score of respondents.

			N = 334
WHO-BREF QOL Domain	Raw Score		Transformed score (0-100)
WHO-BREF QOL Domain	Mean score ± SD	Range	Mean score ± SD	Range
Physical Domain	20.29 ± 4.07	12 – 28	49.99 ± 14.53	19 – 75
Psychological Domain	19.37 ± 2.00	14 – 24	55.67 ± 8.44	31 – 75
Social Domain	10.30 ± 1.62	6 – 15	60.77 ± 13.83	25 – 100
Environmental Domain	25.45 ± 3.27	16 – 34	56.05 ± 10.38	25 – 81

In the age groups, statistically significant differences were found in the four QoL domains. For the physical and psychological domains, the mean score for those aged >60 years was lower than that for those aged 21–40 years or 41–60 years. For the social and environmental domains, the mean score of the >60 years age group was lower than the mean score of the 41–60 years age group.

There was a statistically significant difference between sexes in the four domains of QoL. In all domains, the mean score for male was higher than female. In terms of marital status, there were statistically significant differences between physical and environmental domains. For the physical and environmental domains, the mean score of divorced individuals was significantly lower than that of unmarried individuals. Likewise, there was a statistically significant difference in educational status in all four domains of Quality of Life. In all domains, the mean score for the literate group was higher than that for the illiterate group.

There were statistically significant differences in the four domains of QoL in terms of the duration of Diabetes Mellitus diagnosis. For the physical and environmental domains, the mean score of respondents whose Diabetes Mellitus was diagnosed within ≤ five years was higher than the mean score of respondents whose duration of Diabetes Mellitus was 6 -10 or >10 years. For psychological domain, the mean score of respondents whose Diabetes Mellitus was diagnosed in ≤5 years was higher as compared to mean score of respondents whose duration of Diabetes Mellitus was 6-10 years. For the social domain, the mean score of respondents whose Diabetes Mellitus was diagnosed within ≤5 years was higher than that of those with >10 years of illness duration.

Similarly, in the treatment group, there were statistically significant differences in psychological and environmental domains. For psychological domain, the mean score of respondents using diet and oral hypoglycemic agents for managing Diabetes Mellitus have higher mean score as compared to the mean score of groups of respondents using diet and insulin or diet, oral hypoglycemic agents and insulin for managing Diabetes Mellitus.

Statistically significant differences were observed between the presence of comorbidities in all four QoL domains of quality of life. In all domains, the mean score of the respondents without any comorbidities was higher as compared to the mean score of the respondents with comorbidities, as shown in Table 3.

Table 3. Association between WHO QoL BREF domains and Sociodemographic Characteristics.

				N = 334
Variables	Physical domain	Psychological domain	Social domain	Environmental domain
Age Group (in completed Years)
21-40	59.15 ± 11.29^b	59.38 ± 10.73^b	61.07 ± 13.02	56.46 ± 12.93
41-60	55.30 ± 12.57^a	57.81 ± 8.02^a	63.93 ± 14.05^a	59.31 ± 9.51^a
>60	41.46 ± 13.27^a,b	52.23 ± 7.62^a,b	56.21 ± 12.32^a	51.34 ± 9.54^a
	(p = <0.001)	(p = <0.001)	(p = <0.001)	(p = <0.001)
Gender
Male	53.86 ± 13.29	57.95 ± 8.11	62.91 ± 14.04	57.70 ± 9.74
Female	45.34 ± 14.63	52.94 ± 8.01	58.20 ± 13.16	54.07 ± 10.80
	(p = <0.001)	(p = <0.001)	(p = 0.002)	(p = 0.001)
Marital Status
Married	50.34 ± 14.49	55.96 ± 8.06	61.40 ± 13.66	56.64 ± 10.06
Unmarried	56.18 ± 8.42^a	57.27 ± 6.26	61.90 ± 9.57	61.00 ± 7.56^a
Divorced	45.25 ± 15.37^a	52.86 ± 11.20	55.41 ± 15.34	49.86 ± 11.48^a
	(p = 0.049)	(p = 0.094)	(p = 0.048)	(p = <0.001)
Educational Status
Illiterate	42.27 ± 13.39	52.27 ± 7.37	57.07 ± 12.33	52.89 ± 10.18
Literate	54.60 ± 13.19	57.70 ± 8.39	62.98 ± 14.22	57.94 ± 10.05
	(p = <0.001)	(p = <0.001)	(p = <0.001)	(p = <0.001)
Occupation
Business	49.30 ± 16.41	53.25 ± 9.05	58.19 ± 14.54	54.77 ± 10.16
Service	51.00 ± 14.43	56.72 ± 8.27	61.12 ± 13.83	56.27 ± 10.44
Agriculture	50.78 ± 12.86	57.07 ± 8.05	63.40 ± 10.50	56.76 ± 10.38
Retired	45.60 ± 12.70	57.13 ± 8.21	63.33 ± 10.85	55.13 ± 12.40
Homemaker	49.86 ± 14.33	55.61 ± 8.08	60.59 ± 15.07	56.56 ± 10.29
	(p = 0.715)	(p = 0.047)	(p = 0.247)	(p = 0.772)
Family History of Diabetes Mellitus
Yes	49.37 ± 14.63	55.50 ± 8.80	59.65 ± 13.58	55.43 ± 10.77
No	50.86 ± 14.39	55.91 ± 7.90	62.37 ± 14.08	56.94 ± 9.76
	(p = 0.357)	(p = 0.663)	(p = 0.078)	(p = 0.193)
Duration of Diagnosis of Diabetes Mellitus
≤5 years	54.26 ± 12.98^a,b	57.34 ± 8.21^a	63.60 ± 13.71^a	59.23 ± 10.33^a,b
6-10 years	45.08 ± 15.01^a	53.77 ± 8.45^a	58.91 ± 12.78	52.98 ± 9.69^a
>10 years	47.19 ± 14.03^b	54.48 ± 8.06	54.73 ± 14.76^a	54.73 ± 14.76^b
	(p = <0.001)	(p = 0.001)	(p = <0.001)	(p = <0.001)
Treatment Used
Diet + Oral Agents	51.93 ± 13.58^a,b,c	56.88 ± 7.88^a,b	61.93 ± 13.63	57.14 ± 10.23^a
Diet + Insulin	42.48 ± 14.38	49.95 ± 9.00^a	55.24 ± 13.41	50.86 ± 9.88
Diet + Oral agents + Insulin	31.36 ± 16.41	48.36 ± 14.53^b	53. 90 ± 14.17	49.63 ± 7.67^a
	(p = <0.001)	(p = <0.001)	(p = 0.002)	(p = <0.001)
Comorbidities
Yes	45.87 ± 14.74	53.25 ± 8.29	58.11 ± 13.80	53.97 ± 10.05
No	54.74 ± 12.76	58.46 ± 7.73	63.83 ± 13.26	58.45 ± 10.27
	(p = <0.001)	(p = <0.001)	(p = <0.001)	(p = <0.001)

a,b,c Pair wise difference.

Cronbach’s alpha coefficient was used to assess the internal consistency of the WHO QoL BREF scale and its four domains. Table 4 shows the significant correlations between all the domains (p < 0.05). A moderate positive correlation was found between the physical and psychological domains (r = 0.63, p < 0.001), whereas a strong positive correlation was observed between the physical and environmental domains (r = 0.70, p < 0.001).

Table 4. Correlation coefficient in four domains of WHO QoL BREF.

					N = 334
		Physical	Psychological	Social	Environmental
Physical	Correlation Coefficient	1	0.639	0.437	0.707
	Sig (2-tailed)		<0.001	<0.001	<0.001
Psychological	Correlation Coefficient		1	0.459	0.596
	Sig (2-tailed)			<0.001	<0.001
Social	Correlation Coefficient			1	0.575
	Sig (2-tailed)				<0.001
Environmental	Correlation Coefficient				1
	Sig (2-tailed)

Discussion

The prevalence of diabetes has significantly increased in both developed and developing countries over the past four decades, and is largely attributed to an abundance of food, shifts in dietary habits, and a decrease in physical activity.¹⁶ Diabetes Mellitus significantly affects an individual’s quality of life, making it essential to address the quality of life aspects in diabetes management to improve overall outcomes.

In the present study, the majority (56.6%) of the respondents were between the age group of 41-60 years. This finding is consistent with a study conducted in India¹⁷ in which the majority (62.13%) of the respondents were age group–41-60 years. The distribution of gender (male: 54.5% and female: 45.5%) in the present study is consistent with the study of India¹⁸ and Bangladesh,¹⁹ where respondents were equally distributed between males and females. The reason for these similar findings might be that the demographic profiles of Nepal, India, and Bangladesh share significant similarities due to their geographical proximity, cultural connections, and comparable socioeconomic conditions. These factors often lead to parallel patterns in population characteristics, including sex distribution.

The mean QoL scores were the highest in the social domain, followed by the environmental, psychological, and physical domains. This finding was similar to that of a study conducted in Nepal.²⁰ While discussing the reasons for low quality of life scores in the physical domain among patients with diabetes, it is important to explore the various factors that contribute to the physical challenges and limitations experienced by these individuals. Mental health issues can manifest physically by decreasing energy levels, increasing fatigue, and reducing the overall willingness to participate in physical activities, which are crucial for maintaining physical health and wellbeing. Strict dietary restrictions necessary for diabetes management can lead to nutritional deficiencies, affecting physical energy levels and overall physical health. The fear of experiencing hypoglycemia during exercise may discourage patients with diabetes from participating in physical activities, leading to a sedentary lifestyle and lower quality of life in the physical domain.

In the present study, there was a statistically significant difference between sexes in all four domains of Quality of Life. This finding is consistent with those of a study conducted in India.^13,17,19 The observed lower quality of life scores among females might be related to various challenges faced by females like economic disparities between male and females which might lead to delays in health-seeking behavior. Furthermore, cultural and gender roles might place additional pressure on females, which could adversely affect their quality of life.

There was no statistically significant difference between the family history of Diabetes Mellitus and all four domains of Quality of Life. This finding was supported by a study conducted in eastern India.¹⁷ The absence of a significant difference suggests that having a family history of diabetes does not directly influence how patients perceive their quality of life in four domains (physical, psychological, social relationships, and environment). This implies that various factors, such as access to healthcare, individual health behaviors, socioeconomic status, education, and support systems, might have a more pronounced effect on quality of life than family history. These factors could overshadow the potential influence of family history on QoL.

In the present study, there were statistically significant differences in the presence of comorbidities in all four domains of quality of life. Comorbid conditions can impose greater restrictions on daily activities, which may explain the lower quality of life scores among those with comorbidities, compared to those without such conditions who face fewer limitations. Furthermore, the reduced complexity of disease management among patients without comorbid conditions may lead to a lower healthcare burden and improved quality of life, as managing diabetes alone is less demanding than simultaneously managing multiple chronic conditions.

Conclusion

Based on the findings of this study, it was concluded that Diabetes Mellitus has a huge impact on QoL. The findings demonstrate that patients with diabetes, especially females and those with comorbidities, experience lower QoL across all domains. Furthermore, no significant difference was observed between family history of diabetes and QoL, suggesting that factors beyond genetic predisposition, such as disease management and psychosocial support, may have a more influential role in determining overall quality of life. The results underscore the need for a more holistic approach to diabetes care, focusing not only on glycemic control but also on addressing psychological support, lifestyle modifications, and the management of comorbid conditions to improve patients’ quality of life.

Data availability

The datasets generated and analysed during this study are openly available in the Zenodo repository under a Creative Commons Attribution 4.0 International at: Ghimire, S. (2026). Data set for Quality of Life of Patients with Type II Diabetes Mellitus (version 1.0) [Data set]. Zenodo; 2026 https://doi.org/10.5281/zenodo.18365391²¹

In addition, all extended data, including the quality-of-life (WHO_BREF_questionnaire) in english language, Informed consent form template are available in Zenodo Ghimire, S. “Additional documents for: Quality of Life of Patients with Type II Diabetes Mellitus” (Version 1.1). Zenodo; 2026 https://doi.org/10.5281/zenodo.18396828.²² These materials are provided under a Creative Commons Attribution 4.0 International and are fully accessible to enable verification, reuse, and replication of the study findings.

Acknowledgements

The authors would like to extend their sincere thanks to the WHO for granting permission to use the WHOQOL-BREF scale for this study. The WHOQOL-BREF provides a comprehensive tool for assessing QoL among diabetic patients, which is essential for the success of this research. We also thank Mr. Pradeep Chhetri and Mr. Shakti Shrestha, whose statistical guidance and expertise were invaluable throughout the study. Finally, the authors express their deepest gratitude to all the respondents who participated in the study. Respondents’ willingness to share their experiences and insights was invaluable to our understanding of the quality of life of diabetic patients.

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Author details Author details

¹ Nursing, Universal College of Medical Sciences, Siddharthanagar, Lumbini Province, 32900, Nepal
² Medicine, Crimson Hospital, Tilottama, Lumbini, 32900, Nepal
³ Nursing, Lumbini Provincial Hospital, Butwol, Lumbini, 32900, Nepal

Sulochana Ghimire
Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

Gita Neupane
Roles: Conceptualization, Data Curation, Methodology, Supervision, Writing – Review & Editing

Chanda Sah
Roles: Data Curation, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

Mahesh Raj Ghimire
Roles: Conceptualization, Investigation, Methodology, Project Administration, Supervision, Validation, Writing – Review & Editing

Binita Soti
Roles: Data Curation, Investigation, Methodology, Project Administration, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

The author(s) declared that no grants were involved in supporting this work.

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Published: 11 Mar 2026, 15:392

https://doi.org/10.12688/f1000research.176141.1

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© 2026 Ghimire 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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Ghimire S, Neupane G, Sah C et al. Quality of Life of Type II Diabetic Patients [version 1; peer review: 1 approved with reservations]. F1000Research 2026, 15:392 (https://doi.org/10.12688/f1000research.176141.1)

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Open Peer Review

Version 1

VERSION 1

PUBLISHED 11 Mar 2026

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Reviewer Report 31 Mar 2026

Yohanes Andy Rias, Institut Ilmu Kesehatan Bhakti Wiyata, Kediri, Indonesia

Approved with Reservations

https://doi.org/10.5256/f1000research.194175.r467392

- In general, this title is relevant to the content of the abstract, because the research focuses on the quality of life of type 2 DM patients. However, if viewed more critically, this title is still too general and does ... Continue reading

- In general, this title is relevant to the content of the abstract, because the research focuses on the quality of life of type 2 DM patients. However, if viewed more critically, this title is still too general and does not fully reflect the details of the study in the abstract.
- abstract. Is this study solely descriptive, or does it also aim to identify factors that influence quality of life (QoL)?
-Mention the brief research gap. Moreover, what is not known from previous research
- Introduction. There is no synthesis of previous studies. The authors cite some facts and one qualitative study, but have not yet addressed the following: What were the outcomes of previous studies related to QoL in T2DM? Were the results consistent or varied? Please specify: What are the main findings of prior studies concerning QoL in T2DM patients? Were there any inconsistencies in the results between the studies forming the basis of this research?
- Currently, the last paragraph jumps to the point without bridging the gap. Please mention what gaps in previous research this study aims to address? Why is it necessary to conduct this study in a Nepalese setting?
-The background section discusses how common diabetes is in Nepal, but it doesn't give enough information about the local context of this study. It is uncertain whether the current evidence concerning the QoL of patients with T2DM in Nepal is insufficient or absent. The authors ought to clarify whether there exists inadequate data concerning QoL in this population, as this would enhance the justification for the study.
-The manuscript also does not talk about possible sociocultural differences that could affect QoL outcomes when compared to other countries. It is important to explain how cultural values, social support systems, health beliefs, and access to healthcare can be very different in different places and how these factors in Nepal may affect the quality of life of individuals with T2DM in a unique way. This will help show why this study is needed.
-Methods: statistical analysis section. Cronbach's alpha is stated as 0.880, but it is not explained whether this applies to the entire instrument or to each WHOQOL-BREF domain.
-If the ANOVA shows a significant difference, please include a post hoc test (e.g., Tukey's) to determine the difference between groups. The analysis should be bivariate (t-test/ANOVA), even though QoL is influenced by many factors. Consider multivariate analysis (e.g., linear regression) to control for confounding variables.
-Discussion. Are there significant differences in QoL domains between the Nepalese population and populations from other studies? If so, what might explain these differences?
-I suggest that authors need to discuss the correlations between domains found (e.g., r = 0.70 between physical and environmental) to provide deeper insight.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

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

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Biobehavioral, Non-communicable diseases (NCDs), particularly diabetes mellitus and chronic kidney disease, epidemiology, risk prediction modelling, and community-based nursing interventions

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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Yohanes Andy Rias, Institut Ilmu Kesehatan Bhakti Wiyata, Kediri, Indonesia

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Reviewer Report

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31 Mar 2026 | for Version 1

Yohanes Andy Rias, Institut Ilmu Kesehatan Bhakti Wiyata, Kediri, Indonesia

1 Views Cite this report Responses(0)

Approved With Reservations

- In general, this title is relevant to the content of the abstract, because the research focuses on the quality of life of type 2 DM patients. However, if viewed more critically, this title is still too general and does not fully reflect the details of the study in the abstract.
- abstract. Is this study solely descriptive, or does it also aim to identify factors that influence quality of life (QoL)?
-Mention the brief research gap. Moreover, what is not known from previous research
- Introduction. There is no synthesis of previous studies. The authors cite some facts and one qualitative study, but have not yet addressed the following: What were the outcomes of previous studies related to QoL in T2DM? Were the results consistent or varied? Please specify: What are the main findings of prior studies concerning QoL in T2DM patients? Were there any inconsistencies in the results between the studies forming the basis of this research?
- Currently, the last paragraph jumps to the point without bridging the gap. Please mention what gaps in previous research this study aims to address? Why is it necessary to conduct this study in a Nepalese setting?
-The background section discusses how common diabetes is in Nepal, but it doesn't give enough information about the local context of this study. It is uncertain whether the current evidence concerning the QoL of patients with T2DM in Nepal is insufficient or absent. The authors ought to clarify whether there exists inadequate data concerning QoL in this population, as this would enhance the justification for the study.
-The manuscript also does not talk about possible sociocultural differences that could affect QoL outcomes when compared to other countries. It is important to explain how cultural values, social support systems, health beliefs, and access to healthcare can be very different in different places and how these factors in Nepal may affect the quality of life of individuals with T2DM in a unique way. This will help show why this study is needed.
-Methods: statistical analysis section. Cronbach's alpha is stated as 0.880, but it is not explained whether this applies to the entire instrument or to each WHOQOL-BREF domain.
-If the ANOVA shows a significant difference, please include a post hoc test (e.g., Tukey's) to determine the difference between groups. The analysis should be bivariate (t-test/ANOVA), even though QoL is influenced by many factors. Consider multivariate analysis (e.g., linear regression) to control for confounding variables.
-Discussion. Are there significant differences in QoL domains between the Nepalese population and populations from other studies? If so, what might explain these differences?
-I suggest that authors need to discuss the correlations between domains found (e.g., r = 0.70 between physical and environmental) to provide deeper insight.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

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

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Biobehavioral, Non-communicable diseases (NCDs), particularly diabetes mellitus and chronic kidney disease, epidemiology, risk prediction modelling, and community-based nursing interventions

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.

Respond to this report

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[2] 2. Chen L, Magliano DJ, Zimmet PZ: The worldwide epidemiology of type 2 diabetes mellitus—present and future perspectives. Nat. Rev. Endocrinol. 2012 Apr; 8(4): 228–236. Publisher Full Text

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[8] 8. Harding JL, Pavkov ME, Magliano DJ, et al.: Global trends in diabetes complications: a review of current evidence. Diabetologia. 2019 Jan; 62: 3–16. PubMed Abstract | Publisher Full Text

[9] 9. Rubin RR, Peyrot M: Quality of life and diabetes. Diabetes/metabolism research and reviews. 1999 May;15(3):205-18. Deshpande AD, Harris-Hayes M, Schootman M. Epidemiology of diabetes and diabetes-related complications. Phys. Ther. 2008 Nov 1; 88(11): 1254–1264.

[10] 10. Harper A, Orley J: WHOQOL-BREF: Introduction, administration, scoring and generic version of the assessment. Programme on Mental Health. Geneva: World Health Organization; 1996.

[11] 11. Teoli D, Ghassemzadeh S: Patient self-determination act. StatPearls. StatPearls Publishing; 2023 Aug 28.

[12] 12. Ghimire S, Neupane G, Sah C, et al.: Quality of life of Type II Diabetic patients. medRxiv. 2024 Nov 8; 2011–2024.

[13] 13. Manjunath K, Christopher P, Gopichandran V, et al.: Quality of life of a patient with type 2 diabetes: A cross-sectional study in Rural South India. J. Family Med. Prim. Care. 2014 Oct; 3(4): 396–399. PubMed Abstract | Publisher Full Text

[14] 14. Ilić I, Šipetić-Grujičić S, Grujičić J, et al.: Psychometric properties of the world health organization’s quality of life (WHOQOL-BREF) questionnaire in medical students. Medicina. 2019 Dec 4; 55(12): 772. Publisher Full Text

[15] 15. World Health Organisation: Programme on mental health: WHOQOL user manual. World Health Organization; 1998.

[16] 16. Trikkalinou A, Papazafiropoulou AK, Melidonis A: Type 2 diabetes and quality of life. World J. Diabetes. 2017 Apr 4; 8(4): 120–129. PubMed Abstract | Publisher Full Text

[17] 17. Sahoo SS, Sahoo JR, Taywade M, et al.: Quality of life and its determinants among ambulatory diabetic patients attending NCD prevention clinic: A cross sectional study from Eastern India. Clinical Epidemiology and Global Health. 2023 May 1; 21: 101275. Publisher Full Text

[18] 18. Patil S, Patil Y, Patil SK: Assessment of quality of life in type 2 diabetes mellitus patients using World Health Organization quality of life-BREF questionnaire and appraisal of diabetes scale-a cross-sectional study. Italian Journal of Medicine. 2021 Oct 5; 15(3). Publisher Full Text

[19] 19. Amin MF, Bhowmik B, Rouf R, et al.: Assessment of quality of life and its determinants in type-2 diabetes patients using the WHOQOL-BREF instrument in Bangladesh. BMC Endocr. Disord. 2022 Jun 18; 22(1): 162. PubMed Abstract | Publisher Full Text

[20] 20. Mishra SR, Sharma A, Bhandari PM, et al.: Depression and health-related quality of life among patients with type 2 diabetes mellitus: a cross-sectional study in Nepal. PloS one. 2015 Nov 23; 10(11): e0141385. PubMed Abstract | Publisher Full Text

[21] 21. Ghimire S: Data set for Quality of Life of Patients with Type II Diabetes Mellitus. Zenodo. 2026.

[22] 22. Ghimire S: Additional documents for: Quality of Life of Patients with Type II Diabetes Mellitus. Zenodo. 2026.

Quality of Life of Type II Diabetic Patients

Abstract

Introduction

Material and Methods

Results

Conclusion

Keywords

Introduction

Background of the study

Materials and methods

Study setting

Sampling

Research instrument

Ethical approval and consent

Statistical analysis

Results

Table 1. Socio-demographic characteristics of respondents.

Table 2. WHO-BREF QOL domain score of respondents.

Table 3. Association between WHO QoL BREF domains and Sociodemographic Characteristics.

Table 4. Correlation coefficient in four domains of WHO QoL BREF.

Discussion

Conclusion

Data availability

Acknowledgements

References

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