Socio-demographic and behavioral correlates of excess weight and its health consequences among older adults in India: Evidence from a cross-sectional study, 2017-18

Background Rapid population aging is expected to become one of the major demographic transitions in the twenty-first century due to the continued decline in fertility and rise in life expectancy. Such a rise in the aged population is associated with increasing non-communicable diseases. India has suffered from obesity epidemic, with morbid obesity affecting 5% of the population and continuing an upward trend in other developing countries. This study estimates the prevalence of excess weight among older adults in India, and examines the socio-demographic and behavioral factors and its health consequences. Methods The study used data from the Longitudinal Ageing Study in India (LASI) wave 1 (2017-18). A total sample of 25,952 older adults (>= 60 years) was selected for the study. Descriptive statistics, bivariate Chi-Square test, and logistic regression models were applied to accomplish the study objectives. Body mass index (BMI) has been computed for the study according to the classification of the World Health Organization, and "excess weight" refers to a score of BMI >= 25.0 kg/m(2). Results Overall, 23% of older adults (>= 60 years) were estimated with excess weight in India, which was higher among women irrespective of socioeconomic and health conditions. The higher levels of excess weight (than the national average of >= 22.7%) were observed among older adults in states like Haryana, Tamil Nadu, Telangana, Maharashtra, Gujarat, Manipur, Goa, Kerala, Karnataka, Himachal Pradesh, Punjab, Sikkim and some other states. After adjusting for selected covariates, the odds of excess weight were higher among females than males [OR: 2.21, 95% CI: 1.89, 2.60]. Similarly, the likelihood of excess weight was 2.18 times higher among older adults who were living in urban areas compared to their rural counterparts [OR: 2.18; 95% CI: 1.90, 2.49]. Higher level of education is significantly positively correlated with excess weight. Similarly, higher household wealth index was significantly positively correlated with excess weight [OR: 1.98, CI: 1.62, 2.41]. Having hypertension, diabetes and heart diseases were associated with excess weight among older adults. Regional variations were also observed in the prevalence of excess weight among older adults. Conclusion The findings suggest that introducing measures that help to reduce the risk of non-communicable diseases, and campaigns to encourage physical activity, and community awareness may help reduce the high burden of excess weight and obesity among older Indians. The findings are important for identifying the at-risk sub-populations and for the better functioning of any public health programme and suitable intervention techniques to lower the prevalence and risk factors for excess weight in later life.