A geospatial analysis of noncommunicable disease (NCD) burden in Indian agro-climatic and political regions

Informal sector employment and the health outcomes of older workers in India

A large proportion of the older population in India constitutes an undeniable share of workforce after the retirement age. This stresses the need to understand the implications of working at older ages on health outcomes. The main objective of this study is to examine the variations in health outcomes by formal/informal sector of employment of older workers using the first wave of the Longitudinal Ageing Study in India. Using binary logistic regression models, the results of this study affirm that type of work does play a significant role in determining health outcomes even after controlling socio-economic, demographic, life-style behaviour, childhood health and work characteristics. The risk of Poor Cognitive Functioning (PCF) is high among informal workers, while formal workers suffer greatly from Chronic Health Conditions (CHC) and Functional Limitations (FL). Moreover, the risk of PCF and/or FL among formal workers increases with the increase in risk of CHC. Therefore, the present research study underscores the relevance of policies focusing on providing health and healthcare benefits by respective economic activity and socio-economic position of older workers.

Spatial association of socio-demographic, environmental factors and prevalence of diabetes mellitus in middle-aged and elderly people in Thailand

The burden of diabetes mellitus (DM), one of the major noncommunicable diseases (NCDs), has been significantly rising globally. In the Asia-Pacific region, Thailand ranks within the top ten of diabetic patient populations and the disease has increased from 2.3% in 1991 to 8.0% in 2015. This study applied local indicators of spatial association (LISA) and spatial regression to examine the local associations in Thailand with night-time light, spatial density of alcohol/convenience stores, concentration of elderly population and prevalence of DM among middle-aged and elderly people. Univariate LISA identified the statistically significant cluster of DM prevalence in the upper north-eastern region. For multivariate spatial analysis, the obtained R2 values of the spatial lag model (SLM) and spatial error model (SEM) were 0.310 and 0.316, respectively. These two models indicated a statistical significant association of several sociodemographic and environmental characteristics with the DM prevalence: food shops (SLM coefficient = 9.625, p<0.001; SEM coefficient = 9.695, p<0.001), alcohol stores (SLM coefficient = 1.936, p<0.05; SEM coefficient = 1.894, p<0.05), population density of elderly people (SLM coefficient = 0.156, p<0.05; SEM coefficient = 0.188, p<0.05) and night-time light density (SLM coefficient = -0.437, p<0.001; SEM coefficient = -0.437, p<0.001). These findings are useful for policymakers and public health professionals in formulating measures aimed at reducing DM burden in the country.

Exploring the Linkages Between Non-Communicable Disease Multimorbidity, Health Care Utilization and Expenditure Among Aboriginal Older Adult Population in India

Objective: The study investigates the magnitude and correlates of non-communicable disease multimorbidity and explores its linkages with health care utilization and out-of-pocket expenditure among aboriginal or tribal older adults.

Methods: The study employed data on 11,365 older adults from Scheduled Tribes from the Longitudinal Ageing Study in India, 2017-18. A disease score was computed integrating sixteen non-communicable diseases. Descriptive, bivariate, and multivariable analyses were performed to identify the magnitude and correlates of multimorbidity. The study further explored the linkages between selected diseases and multimorbidity with health care utilization and expenditure.

Results: The findings suggest that 27.1 and 14.5% of the aboriginal population lived with single or multiple disease, respectively. Hypertension and gastrointestinal disorders were frequent diseases. Higher age, Muslim religion, higher education, unemployment, and affluent background were the major correlates of multimorbidity. Health care utilization, mean expenditure on hospitalization, and outpatient visits increased significantly with multimorbidity.

Conclusion: Multimorbidity is emerging as a health care challenge among the aboriginal population. Measures need to be taken to assess the multimorbidity burden and reduce health care expenditure, ensuring health equity among country’s vulnerable population.

Identifying spatial variation in the burden of diabetes among women across 640 districts in India: a cross-sectional study

Purpose

Diabetes is one of the leading causes of mortality and morbidity among women in India. The burden of diabetes among women was found to increase with age and exposure to the post-partum period. The present study examines the spatial variation in the prevalence of diabetes among women in the late reproductive age-group of 35-49 years across 640 districts in India.

Methods

The study utilized data from the recent round of the National Family Health Survey, 2015-16. Age-standardized prevalence rates were calculated, followed by an examination of economic inequality using the poor-rich-ratio (PRR) and Wagstaff's concentration index. Spatial variation in the prevalence of diabetes was explored with a series of quantile maps, univariate, and bivariate LISA cluster maps. Further, to explore the district-level diabetes prevalence among women in the country, Ordinary Least Square and Spatial Autoregressive (SAR) models were used.

Results

The study findings affirm the presence of spatial clustering in the burden of diabetes among women. The burden is relatively higher among women from the Southern and Eastern parts of the country. Findings establish obesity, hypertension, and living in urban areas as major correlates of diabetes.

Conclusion

Program with an aim to lower the intensity of community-based prevalence of diabetes, especially among women in their late reproductive ages, should adopt differential approaches across different states/districts in the context of their lifestyle, dietary pattern, working pattern, and other socio-cultural practices.