Differential risk factor profile of diabetes and atherosclerosis in rural, sub-urban and urban regions of South India: The KMCH-Non-communicable disease studies

Urban-Rural Differences in the Prevalence of Diabetes Among Adults in Haryana, India: The ICMR-INDIAB Study (ICMR-INDIAB-18)

INTRODUCTION

Diabetes is a multifactorial disease with far-reaching consequences. Environmental factors, such as urban or rural residence, influence its prevalence and associated comorbidities. Haryana-a north Indian state-has undergone rapid urbanisation, and part of it is included in the National Capital Region (NCR). The primary aim of the study is to estimate the prevalence of diabetes in Haryana with urban-rural, NCR and non-NCR regional stratification and assess the factors affecting the likelihood of having diabetes among adults.

METHODS

This sub-group analysis of the Indian Council of Medical Research-India Diabetes (ICMR-INDIAB) study (a nationally representative cross-sectional population-based survey) was done for Haryana using data from 3722 participants. The dependent variable was diabetes, while residence in NCR/non-NCR and urban-rural areas were prime independent variables. Weighted prevalence was estimated using state-specific sampling weights and standardized using National Family Health Survey-5 (NFHS-5) study weights. Associations were depicted using bivariate analysis, and factors describing the likelihood of living with diabetes were explored using a multivariable binary logistic regression analysis approach.

RESULTS

Overall, the weighted prevalence of diabetes in Haryana was higher than the national average (12.4% vs. 11.4%). The prevalence was higher in urban (17.9%) than in rural areas (9.5%). The prevalence of diabetes in rural areas was higher in the NCR region, while that of prediabetes was higher in rural non-NCR region. Urban-rural participants' anthropometric measurements and biochemical profiles depicted non-significant differences. Urban-rural status, age and physical activity levels were the most significant factors that affected the likelihood of living with diabetes.

CONCLUSIONS

The current analysis provides robust prevalence estimates highlighting the urban-rural disparities. Urban areas continue to have a high prevalence of diabetes and prediabetes; rural areas depict a much higher prevalence of prediabetes than diabetes. With the economic transition rapidly bridging the gap between urban and rural populations, health policymakers should plan efficient strategies to tackle the diabetes epidemic.

Decomposing rural-urban differences in successful aging among older Indian adults

The modernization and shift towards urbanized lifestyles have triggered several diseases, and the context of aging varies in urban and rural settings in India. The study aimed to investigate the urban-rural differences in successful ageing among older adults in India and the contributing factors in those differences. The study utilizes data from nationally representative Longitudinal Ageing Study in India (LASI, 2017-18). The analytical sample size for the study was 31,464 older adults aged 60 years and above. Descriptive statistics and bivariate analysis were carried out to present the initial results. Multivariable logistic regression and decomposition analysis was used to find the associations between explanatory variables and successful aging and to identify the contributions of covariates that explain the rural-urban differences in successful ageing. A proportion of 32% and 24% of older adults from rural and urban areas were successful agers with an urban disadvantage. Urban-dwelling older adults had 0.67 times [95% confidence interval (CI): (0.64, 0.71)] lower unadjusted odds of successful ageing than rural older adults. Again, after adjusting for the effect of other explanatory variables, urban older adults had 0.92 times [CI: (0.87, 0.98)] lower odds of being successful agers than their rural counterparts. The major contributors to the rural-urban inequality in successful aging were differences in regional distribution (17% contribution), waist circumference (16%), working status (16%), body mass index (13%) and physical activity (8%) among rural and urban older adults. The urban disadvantage in aging successfully may reflect the higher prevalence of adverse lifestyle behaviours in urban dwellers and under-diagnosis and under-reporting of many diseases in rural areas, particularly non-communicable diseases, suggesting the need for further investigation.