General Health and Quality of Life Among Ethnic Minority Elderly with Type 2 Diabetes: A Cross-Sectional Study

INTRODUCTION

Type 2 diabetes represents a growing public health issue in India, driven by an aging population, urbanization, and changing lifestyles. In older adults, diabetes often comes with chronic problems like neuropathy and heart disease, which contribute to disease burden (Hills et al., 2018; American Diabetes Association, 2021). People from ethnic minority communities may face extra challenges in managing diabetes due to cultural practices, language barriers, and social structures. These issues complicate diabetes management (Attridge et al., 2014). Even with the heavy impact of diabetes in South Asia, ongoing healthcare inequalities still affect access to care and its quality (Ong et al., 2023).

Aside from medical factors, psychological and behavioral aspects are important in managing diabetes. Emotional stress, fear of low blood sugar or disease progression, and low confidence can disrupt treatment compliance and hurt perceived health status, especially in older people (Perrin et al., 2017). Health-related quality of life tools like the SF-36 and EQ-5D-5L assess physical, emotional, and social health dimensions and are commonly used in diabetes research (Jing et al., 2018; Al-Ibrahimy and Rabea, 2023). The ability to maintain self-care despite chronic illness often reflects a person's coping skills, health knowledge shaped by sociocultural context (Zeng et al., 2023).

However, there is limited information on general health and quality of life among older ethnic minority individuals with type 2 diabetes in India. Their experiences and specific challenges are often overlooked in usual clinical assessments. This study aimed to evaluate general health status and health-related quality of life among older ethnic minority adults with type 2 diabetes in the Nilgiris district of Tamil Nadu. It also examined how clinical, psychological, and social factors influence these outcomes using validated assessment tools.

MATERIALS AND METHODS

Study design and participants

This cross-sectional study was conducted at a private multispecialty hospital in Ooty, The Nilgiris, Tamil Nadu, between August 2024 and January 2025. A total of 232 elderly individuals from ethnic minority communities were recruited using convenience sampling. Participants aged ≥65 years with a confirmed diagnosis of type 2 diabetes mellitus were included. Individuals diagnosed within the past one year and those unwilling to participate were excluded. Ethical approval was obtained from the Institutional Review Board of JSS College of Pharmacy, Ooty, with approval number JSSCP/IRB/10/2024-25.

Data collection and study instruments

Sociodemographic and clinical information, including age, gender, education, marital status, occupation, lifestyle factors, duration of diabetes, hospitalizations, comorbidities, complications, medications, and participation in health education programs, were collected. General health status and health-related quality of life were assessed using tools like SF-36 and EQ-5D-5L. The SF-36 evaluates eight health domains and includes a single item on perceived health change (Hays et al., 1993). The EQ-5D-5L assesses five health dimensions and includes the EQ visual analogue scale for self-rated health (Herdman et al., 2011).

Diabetes-related self-efficacy was measured using DSES, an eight-item instrument scored on a 10-point Likert scale, with higher scores indicating greater self-efficacy (Ritter et al., 2016). Fear of hypoglycemia was assessed using HFS-II, comprising behavior and worry components scored on a 5-point Likert scale (Gonder-Frederick et al., 2011). Fear of disease progression was evaluated using FOP-Q-SF, with higher scores indicating greater fear (Mehnert et al., 2009). Data were collected by trained interviewers using Google Forms.

Statistical analysis

Data were analysed using IBM SPSS v22.0. Continuous variables were summarized as mean±standard deviation, and categorical variables as frequencies and percentages. Pearson correlation analysis was performed to examine associations among general health, health-related quality of life, diabetes self-efficacy, fear of hypoglycemia, and fear of progression. Multivariable linear regression analyses were conducted to identify factors predicting general health and health-related quality of life. Statistical significance was set at p<0.05.

RESULTS

Sociodemographic and clinical characteristics

The sociodemographic and clinical characteristics of the participants are presented in Tables 1 and 2. Most participants were aged 65-70 years, with a higher proportion of females than males. Illiteracy was common, and the majority were married. Most participants reported no history of smoking or alcohol consumption, and over half reported no regular exercise. The duration of diabetes was most commonly 1-4 years, and more than half had experienced two or more hospitalizations. Hypertension was the most frequently reported comorbidity, while retinopathy was the most common diabetes-related complication. Oral hypoglycemic agents were the most commonly used treatment, and most participants had received health education programs.

General health status and health-related quality of life

Mean domain/dimension scores for SF-36 and EQ-5D-5L are shown in Figures 1 and 2, respectively. General health had the lowest mean score among SF-36 domains, while social functioning had the highest. In EQ-5D-5L, pain/discomfort showed the highest mean score, whereas self-care showed the lowest. Unlike SF-36, higher scores in EQ-5D-5L indicate greater impairment.

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Self-efficacy, fear of hypoglycemia, and fear of progression

The mean DSES score among participants was 44.19±16.67, with a mean item score of 5.52±2.08. The mean FOH behavior and worry scores were 20.84±13.59 and 21.34±17.63, corresponding to mean item scores of 1.38±0.90 and 1.18±0.97, respectively. The mean FOP-Q-SF score was 31.76±12.10, with a mean item score of 2.64±1.00.

Correlation among general health, health-related quality of life, self-efficacy, and fears

Pearson correlation analysis showed significant associations among general health, EQ-index, EQ-VAS, DSES, FOH, and FOP (p<0.01), as shown in Table 3. General health and DSES were positively correlated with EQ-index and EQ-VAS, whereas FOH and FOP showed negative correlations with general health and health-related quality of life measures. FOH and FOP were positively correlated with each other.

Factors associated with general health and health-related quality of life

Multivariable linear regression analyses were performed with general health, EQ-index, and EQ-VAS as dependent variables, as shown in Table 4. Education level and DSES were significantly positively associated with general health, EQ-index, and EQ-VAS, while FOP showed significant negative associations (p<0.05). Age was significantly negatively associated with general health and EQ-index. Former drinking status and diabetic foot ulcer were significantly negatively associated with EQ-VAS and EQ-index, respectively. Variance inflation factor values for all predictors were within acceptable ranges.

DISCUSSION

This study examined health-related quality of life in elderly individuals with type 2 diabetes from ethnic minority communities in India. Diabetes affected multiple health domains, including physical discomfort, emotional strain, and psychosocial well-being. General health and pain were the most affected SF-36 areas, reflecting common neuropathic and musculoskeletal problems in older adults (Marttinen et al., 2019), which are frequently reported among older individuals with diabetes (American Diabetes Association, 2021). Lower perceived health change scores indicate declining health, while better social functioning may reflect supportive family and community environments.

Findings from the EQ-5D-5L similarly showed a greater impact on pain and discomfort. However, self-care was less affected. This suggests that many participants maintained functional independence despite chronic illness (Abedini et al., 2020). These patterns may reflect coping strategies shaped by sociocultural context within these communities (Zulkifli et al., 2024). Concerns about hypoglycemia and disease progression were evident. This aligns with reports that older adults with type 2 diabetes worry about acute events and long-term complications (Polonsky et al., 2023; Pang et al., 2023).

Diabetes self-efficacy significantly affected health outcomes in this group. Higher self-efficacy related to better general health and quality of life. This is supported by evidence showing that self-efficacy contributes to improved self-management and perceived health outcomes among individuals with type 2 diabetes (Ataya et al., 2024). These results demonstrate how psychological resources impact quality of life for older adults with diabetes. On the other hand, lower self-efficacy along greater psychological burden was linked to worse self-reported health (Jankowska et al., 2021).

Sociodemographic and clinical factors influenced health perceptions. Older age was linked to lower health-related quality of life, likely due to comorbidities and functional decline. In contrast, higher education levels were tied to better outcomes, suggesting a connection to health literacy and involvement in care (Kim et al., 2024). Osteopathy and diabetic foot ulcers were connected to lower health scores, reflecting their effect on pain and mobility (Al-Rub et al., 2019). Behavioral and treatment-related factors were important. Past alcohol use was associated with poorer perceived health, while insulin-only therapy was linked to higher EQ-VAS scores (Engler et al., 2013; Negash et al., 2023). This reflects the potential role of past alcohol use on overall health status, and how differences in treatment maybe associated with variations in quality of life among these people.

Overall, the findings show that health-related quality of life for older ethnic minority individuals with type 2 diabetes is influenced by a combination of sociodemographic characteristics, clinical conditions, and psychological factors (Yildirim et al., 2023; Zan et al., 2024). The results highlight the need for culturally sensitive, patient-focused approaches addressing both physical and emotional health. Interventions that build self-confidence, lessen fear-related stress, and encourage self-care practices may improve the quality of life for this group (Rawal et al., 2021).

This study has limitations. The cross-sectional design restricts causal inference. Excluding individuals with type 1 diabetes limits broader comparisons, and convenience sampling may introduce selection bias. Interviewer-administered questionnaires may be affected by recall or social desirability bias. Future studies should adopt longitudinal designs, include objective measures such as HbA1c, and involve more diverse populations.

CONCLUSION

This study shows how type 2 diabetes affects health-related quality of life in elderly people from ethnic minority communities in India. Physical discomfort, especially pain, along with emotional factors like fear and self-belief, significantly influence perceived health. Sociodemographic factors such as age, education, and other health conditions also impact HRQoL results. These findings highlight the need for culturally aware, patient-focused programs that consider both the physical and emotional aspects of diabetes care for older adults. As a future implication, tailored digital health solutions that include teleconsultation services or mobile health applications may help improve diabetes management and quality of life in such populations.