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Using the 2010 pilot study of the Longitudinal Aging Study in India (LASI), we examine the socioeconomic and behavioral risk factors for poor cardiovascular health among middle-aged and older Indians, focusing on self-reported and directly measured hypertension. The LASI pilot survey (N=1,683) was fielded in four states: Karnataka, Kerala, Punjab, and Rajasthan. These four states were chosen to capture regional variations and socioeconomic and cultural differences. We find significant interstate differences across multiple measures of cardiac health and risk factors for hypertension, including body mass index, waist-to-hip ratio, and health behaviors. In contrast to the findings from developed countries, we find education and other markers of higher socioeconomic status (SES) to be positively associated with hypertension. Among the hypertensive, however, we find that those at higher SES are less likely to be undiagnosed and more likely to be in better control of their blood pressure than respondents with low SES. We also find significant interstate variations in hypertension prevalence, diagnosis, and management that remain even after accounting for socio economic differences, obesity, and health behaviors. We conclude by discussing these findings and their implications for public health and economic development in India and the developing country context more generally.

Background The rise in life expectancy and the share of older population represents the most significant demographic transformation in the twenty-first century. Increasing longevity with the coexistence of chronic multimorbidity makes the elderly population vulnerable to functional limitation, disability and more frequent hospitalization, resulting deterioration in QoL. The present study aims to investigate the association between non-communicable disease (NCD) multimorbidity and QoL among the older population in Varanasi, India. Methods A cross-sectional data of 500 individuals in the Varanasi district aged 50 + years were collected, using a multistage simple random sampling procedure from November 2017 to May 2018. WHOQOL-BREF was utilised to assess the quality of life of the study participants, and the important covariates used in the analysis are; age, sex, marital status, place of residence, health factors, socioeconomic status, and behavioral risk factors. Descriptive analysis was performed to assess the mean QoL score pattern, whereas multivariate linear regression analysis examines the association between multimorbidity and QoL. Results The QoL scores decreased with age and was higher among females. Regression results show that demographic and lifestyle risk factors are closely associated with QoL. multimorbidity was significantly associated with reduced quality of life. Older adults with multimorbidity had 5 points lower quality of life than those with no chronic diseases. Conclusions Multimorbidity along with demographic and lifestyle factors are significantly associated with QoL. Healthcare programmes need to factor in multimorbidity while promoting a healthy and risk-free lifestyle to control modifiable risk factors. Government assistance is necessary for the most economically dependent older population for their day-to-day needs.

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