European Journal of Cardiovascular Medicine

Non-communicable diseases (NCDs) are a major global health challenge, causing more deaths than all other causes combined, with deaths projected to rise from 38 million in 2012 to 52 million by 2030.⁽¹⁾ In 2021, non-communicable diseases (NCDs) caused 43 million deaths, 75% of non-pandemic-related deaths globally, with 73% of NCD deaths occurring in low- and middle-income countries.⁽²⁾ Among the NCDs Diabetes is a major health issue that has reached alarming levels.⁽³⁾ Among adults aged 20-79 years, 537 million people (10.5% of the world's population) have diabetes. By 2045, this figure is predicted to increase to 783 million (12.2%) and 643 million (11.3%).⁽⁴⁾ Of the 240 million people with undiagnosed diabetes, almost half are not aware that they have the disease.⁽³⁾ In nations with low and moderate incomes, about 90% of people with undiagnosed diabetes reside. In the Western Pacific, Africa, and South-East Asia, almost half of diabetics go misdiagnosed. India accounts for 1 in 7 of all adults living with diabetes worldwide.⁽⁴⁾ As per National Family Health Survey in India about 13.5% women and 15.6% men are having diabetes.⁽⁵⁾

Diabetes mellitus increases the risk of vascular diseases, blindness, and renal failure while significantly impacting quality of life. Managing diabetes is stressful due to dietary restrictions, medications, and the fear of complications. Type II diabetes inflicts a significant burden in terms of disability and impaired QOL.⁽⁶⁾ Health-Related Quality of Life (HRQOL) is crucial for assessing the disease’s impact on well-being and healthcare costs.⁽⁷⁾ People with DM require not only drug intervention and blood glucose control, but also a healthy lifestyle and positive changes in lifestyle.⁽⁸⁾ This situation may have a deep psychological impact on affected individuals and increase their perception of a poor Quality of Life (QOL).⁽⁹⁾QOL and glycaemic control are not only treated as independent outcomes but also they are considered to be achievable as well in diabetes management.⁽¹⁰⁾

Studies show that diabetes patients have poorer HRQOL than the general population, impacting health and increasing mortality.^(11–13) In developing countries, diabetes-related morbidity is higher, further worsening HRQOL.⁽¹⁴⁾ However, research on HRQOL in diabetic patients, especially in these regions, remains limited. Few studies exist on HRQOL in type II diabetes patients in rural India, with none in Ranga Reddy, Telangana. Hence this study was carried out with the main objective of assessing Health Related Quality of Life among type 2 diabetes mellitus patients at rural Medchal Mandal, Ranga Reddy district.a

for a period of two years from October 2015 to October 2017 in 40 villages in rural area of Medchal Mandal. Rural Medchal Mandal consists of 40 villages. Among the 40 enlisted villages of Medchal Mandal 13 villages were selected by random sampling (lottery method) for data collection. A preliminary house to house survey was carried out to identify and make a list of the known type II diabetic individuals in each village. Total population of villages was 49,300 based on the census 2011. The total sample (1033) was divided by probability proportional to size (PPS) in which the village with more population required more sample and the village with less population required fewer samples.Sample Size was calculated assuming the prevalence of Diabetes as 8.5%,⁽¹⁵⁾ relative precision of 20% of P, the sample size was calculated as follows:

Inclusion criteria: Individuals diagnosed with Type 2 Diabetes Mellitus for more than one year, aged 30 years or older (both male and female), and willing to participate in the study.

Exclusion criteria: Individuals with chronic illnesses, pregnant women, those with gestational diabetes mellitus (GDM), individuals unable to communicate due to physical or mental disabilities, and those who do not consent to participate.

Methods: Before the initiation of the study, 50 known type II diabetes mellitus patients were selected out of the entire sampled villages and questionnaire was administered. After pre- testing, the required corrections were made in the questionnaire wherever applicable and the study was commenced.

After explaining nature and scope of the study, informed consent was taken from the participants. Data was collected by interviewing the participants by house to house visit. If the individuals were not available at the time of study or the house was locked then a second visit was made to the house after one week. If the person was still unavailable then he was excluded from the study. People who did not give consent or those who met the exclusion criteria were excluded and the next numbers on the list were included.

Participants were asked to rate their QOL using the WHOQOL-BREF questionnaire translated into Telugu and to provide ratings of their opinion. The WHOQOL-BREF is an abbreviated version of the WHOQOL-100 QOL assessment. It produces scores for four domains (physical health, psychological, social relationships and environment) related to QOL. The four domain scores denote an individual's perception of QOL in each particular domain. Domain scores are scaled in a positive direction (i.e. higher scores denote higher QOL). The mean score of items within each domain is used to calculate the domain score. Mean scores are then multiplied by 4 in order to make domain scores comparable with the scores used in the WHOQOL-100.⁽¹⁶⁾BMI was categorized on the WHO Expert consultation classification of Body Mass Index for Asians (Underweight < 18.5, Normal ≥18.5 & < 23, Overweight ≥ 23 & < 27.5 and Obese ≥ 27.5).⁽¹⁷⁾ Hypertensive status was classified based on JNC 8 classification of hypertension.⁽¹⁸⁾

STATISTICAL ANALYSIS PLAN: The data was statistically analysed using Statistical Package for Social Sciences (SPSS version17.0). For descriptive analysis numbers and percentages were used for. Mean values and standard deviations were calculated for continuous parametric data collected. Chi-Square test and unpaired T test were used for analytical data. A p value less than 0.05 were taken as significant.

The study calculated a sample size of 1033, used Probability Proportion to Size (PPS) for village-wise distribution, excluded 8 unavailable participants, and collected data from 1025 known type II diabetes patients. The male to female ratio was 1.25: 1 (569: 456) and the mean age of male and female respondents was 53.09 ± 11.2 and 53.60 ± 10.8 years, respectively. Table 1 presents the basic demographic characteristics of the participants. Males had significantly higher mean height, weight, waist, and hip circumference than females (p < 0.05), while BMI was similar (~25 kg/m²) with gender wise statistically significant difference. Among respondents, 46.5% had normal BMI, 22.1% were overweight, 17.8% were obese, and 13.6% were underweight. Most belonged to the lower middle (59.7%) or middle (27.9%) socio-economic class. Pre-hypertension was observed in 53.9%, and stage 1 hypertension in 35.3%. Smoking was more prevalent among men (60.6%) than women (4.8%), and alcohol consumption was higher in men (54.0%) than women (6.8%), with statistically significant gender differences in alcohol consumption, smoking, hypertension, and BMI categories. (Table 1)

Table 2 shows that the mean overall score on the QOL scale was 49.95. All four domains received low scores, with psychological and environmental health receiving comparatively worse values. 29% of all respondents reported their quality of life was good, whereas 28.7% reported it was low (Fig. 1).

Table 3 suggests that, although not statistically significant (p > 0.05), physical health scores were somewhat higher among individuals under 50. Those over 50 had poorer psychological health, which declined significantly with age (p < 0.05). Age-group variations in social and environmental health scores were not statistically significant (p > 0.05). Figure 2 illustrates that there was no difference in the social and environmental domain scores between the sexes. Although the difference was not statistically significant, women had a higher mean score for physical health and a lower mean score for psychological health.

Table 1: Baseline characteristics of the Study Participants (N = 1025)

*Unpaired T test, ^# Chi-Square test

Table 2: Domain wise assessment of Health-Related Quality of Life among Study Participants (N = 1025)

Fig 1: Pie diagram showing the overall perception of QOL among Study Participants (N = 1025)

Table 3: Age Group Distribution of HRQOL Scores across Domains among Study Participants (N = 1025)

*Unpaired T test

Fig: 2 Gender wise distribution of HRQOL score across domains among study participants (N = 1025)

The purpose of this study was to assess the Health-Related Quality of Life (HRQoL) in individuals with type II diabetes mellitus. In this study, the majority of diabetic patients were male (55.5%), consistent with findings from V. B. Prajapati et al⁽¹⁹⁾, Vishakha Jain et al⁽²⁰⁾, and Tewodros Eshete Wonde et al.⁽²¹⁾ However, the percentage of male participants in these studies was slightly higher, typically reaching 60% or more. In contrast, studies by Habtamu Esubalew et al⁽²²⁾ and Tadesse Gebremedhin et al⁽²³⁾ reported a higher prevalence of diabetes among females (58.9% and 55.1%, respectively). The mean age of participants in this study was 53.34 ± 12.23 years, which is similar to some studies but slightly higher than the mean age reported by Tadesse Gebremedhin et al⁽²³⁾ (45 ± 9.84 years) and lower than that of V. B. Prajapati et al⁽¹⁹⁾ (60.34 ± 12.04 years). Majority of participants were in the age group of 41-65 years (72.8%) as in study by V. B. Prajapati et al⁽¹⁹⁾ (56.8%). These differences in demographic characteristics may be attributed to variations in the study settings.

The overall HRQoL score in this study was 49.95 ± 16.23, which is comparable to findings from a community-based study in rural Kerala.⁽²⁴⁾ However, a study conducted in Ethopia⁽²⁵⁾ reported that more than half of participants had good HRQoL, a higher proportion than in this study. This difference may be attributed to the hospital-based nature of the Ethopia study⁽²⁵⁾, which limits its generalizability, necessitating caution when comparing results.

In this study, the most affected domain was the psychological domain, contrasting with findings from studies conducted in other regions.^(23,26) This can be explained by the chronic stress of disease management, fear of complications, and lifestyle restrictions. Additionally, factors such as blood sugar fluctuations, financial burden, and a higher prevalence of depression and anxiety contribute to emotional distress. The significance of taking local circumstances into account when evaluating the effect of type 2 diabetes on quality of life is highlighted by these geographical variations. Socioeconomic, cultural, and medical factors can change which aspects of everyday life are most strongly affected by the illness. To enhance patients' general well-being, healthcare professionals should customize interventions to meet the unique requirements and worries of patients in various geographic areas.

HRQoL was lower in individuals above 51 years of age, consistent with previous studies.^(24,27–29) This decline can be attributed to worsening diabetes-related complications, reduced physical activity, and increased psychological stress. Overall, age showed an inverse relationship with all aspects of HRQoL in this study, aligning with findings from earlier research.

In our study, males had a higher psychological domain score than females. This may be due to stronger coping mechanisms, greater social support, and lower emotional distress among males, whereas females often experience higher stress levels and caregiving burdens. Similar findings have been observed in previous studies.^(30,31) In contrast, females may have better HRQoL in the physical domain in line with a Siddiqui et al⁽³²⁾ study by  possibly due to greater health awareness and a more proactive approach to seeking healthcare.

MERITS & DEMERITS: The strengths of this study include being the first of its kind in our field and its community-based design. However, a limitation is the lack of consideration for the independent associations between the factors and quality of life, as well as the inability to account for numerous potential confounding variables

Type 2 Diabetes Mellitus is a major public health concern, leading to high mortality, disability, and healthcare costs. Improving quality of life requires strategies like regular meditation, self-help groups, physical activity, glycaemic control, social support, and counselling. Future studies should explore additional factors and develop a culturally sensitive Telugu version of the WHOQOL tool for rural Indian diabetic patients.

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