Background: Physical aging increases the sensitivity to the effects of substance use, elevating the risk for cognitive impairment among older adults. Since studies on the association of substance use with cognitive ability in later years are scant in India, we aimed to explore the factors associated with cognitive impairment especially, alcohol consumption, smoking, and chewing tobacco later in life. Methods: The present research used nationally representative data from Building a Knowledge Base on Population Aging in India (BKPAI) that was conducted in 2011, across seven states of India (N=9,453). Sample distribution along with percentage distribution was calculated for cognitive impairment over explanatory variables. For finding the association between cognitive impairment over explanatory variables, binary logistic regression models were estimated. Results: About 16.5 percent of older adults in rural areas consumed smoked tobacco compared to 11.7 percent in urban areas. Nearly, 23.7 percent of rural older adults consumed smokeless tobacco in comparison to 16 percent in urban areas. Alcohol consumption was high among rural residents (7.9%) than urban counterparts (6.7%). The prevalence of cognitive impairment was 62.8% and 58% among older adults from rural and urban areas respectively. Older adults who smoked tobacco had a 24 percent significantly higher likelihood to have cognitive impairment with reference to older adults who did not smoke [OR: 1.24, CI: 1.02-1.49]. Moreover, older adults who consumed alcohol had a 30 percent significantly higher likelihood to have cognitive impairment [OR: 1.02, 1.65]. It was also found that older adults who had smoked along with consuming alcohol were at risk of worse cognitive outcomes than those who neither smoke nor drink alcohol [OR: 1.56, CI: 1.21-2.00] or consumed either of them unlike consuming smokeless tobacco only. Conclusion: The encouragement of older people to stop smoking and smokeless tobacco use could be considered as part of a strategy to reduce the incidence of cognitive impairment. Further, appropriate measures should be taken for the detection of early stages of cognitive decline in older individuals and efforts should be made to improve the availability and quality of care for dementing older adults.

In a culturally different and low-resource setting, where lifestyle habits, including dietary pattern and physical activities differ from those in high-income countries, the association between physical activity and cognition is expected to differ. We aimed to investigate the association between physical activity and cognitive functioning after controlling for potential confounders among older adults in India. Furthermore, gender differences in this relationship were analyzed. Using a national-level data from the Longitudinal Ageing Study in India (2017–2018), this paper employed propensity score matching (PSM) approach to examine the association between physical activities and cognitive functioning among Indian older adults. Cognitive impairment was measured through five broad domains (memory, orientation, arithmetic function, executive function, and object naming). We limit our sample to older adults aged 60 + years, and our final dataset contains 31,464 participants (men = 16,366, and women = 15,098). The results indicated that older adults who engaged in frequent physical activity have greater cognitive functioning than older adults without physical activity after adjusting for various individual, health, lifestyle, and household factors. This association holds true for both older men and older women. The results from the PSM revealed that the cognitive function score was increased by 0.98 and 1.32 points for the frequently physically active older men and women population, respectively. The results demonstrate the possible beneficial effects of frequent physical activity on cognitive functioning among older adults. Thus, regular physical activity can be considered as an effective lifestyle factor to promote healthy cognitive aging.

Background: India suffers from a high burden of diarrhoea and other water-borne diseases due to unsafe water, inadequate sanitation and poor hygiene practices among human population. With age the immune system becomes complex and antibody alone does not determine susceptibility to diseases which increases the chances of waterborne disease among elderly population. Therefore the study examines the prevalence and predictors of water-borne diseases among elderly in India. Method: Data for this study was collected from the Longitudinal Ageing Study in India (LASI), 2017–18. Descriptive statistics along with bivariate analysis was used in the present study to reveal the initial results. Proportion test was applied to check the significance level of prevalence of water borne diseases between urban and rural place of residence. Additionally, binary logistic regression analysis was used to estimate the association between the outcome variable (water borne diseases) and the explanatory variables. Results: The study finds the prevalence of water borne disease among the elderly is more in the rural (22.5%) areas compared to the urban counterparts (12.2%) due to the use of unimproved water sources. The percentage of population aged 60 years and above with waterborne disease is more in the central Indian states like Chhattisgarh and Madhya Pradesh followed by the North Indian states. Sex of the participate, educational status, work status, BMI, place of residence, type of toilet facility and water source are important determinants of water borne disease among elderly in India. Conclusion: Elderly people living in the rural areas are more prone to waterborne diseases. The study also finds state wise variation in prevalence of waterborne diseases. The elderly people might not be aware of the hygiene practices which further adhere to the disease risk. Therefore, there is a need to create awareness on basic hygiene among this population for preventing such bacterial diseases.

Background: With increasing urbanization in India, child growth among urban poor has emerged as a paramount public health concern amidst the continuously growing slum population and deteriorating quality of life. This study analyses child undernutrition among urban poor and non-poor and decomposes the contribution of various factors influencing socio-economic inequality. This paper uses data from two recent rounds of National Family Health Survey (NFHS-3&4) conducted during 2005–06 and 2015–16. Methods: The concentration index (CI) and the concentration curve (CC) measure socio-economic inequality in child growth in terms of stunting, wasting, and underweight. Wagstaff decomposition further analyses key contributors in CI by segregating significant covariates into five groups-mother’s factor, health-seeking factors, environmental factors, child factors, and socio-economic factors. Results: The prevalence of child undernutrition was more pronounced among children from poor socio-economic strata. The concentration index decreased for stunting (− 0.186 to − 0.156), underweight (− 0.213 to − 0.162) and wasting (− 0.116 to − 0.045) from 2005 to 06 to 2015–16 respectively. The steepness in growth was more among urban poor than among urban non-poor in every age interval. Maternal education contributed about 19%, 29%, and 33% to the inequality in stunting, underweight and wasting, respectively during 2005–06. During 2005–06 as well as 2015–16, maternal factors (specifically mother’s education) were the highest contributory factors in explaining rich-poor inequality in stunting as well as underweight. More than 85% of the economic inequality in stunting, underweight, and wasting among urban children were explained by maternal factors, environmental factors, and health-seeking factors. Conclusion: All the nutrition-specific and nutrition-sensitive interventions in urban areas should be prioritized, focusing on urban poor, who are often clustered in low-income slums. Rich-poor inequality in child growth calls out for integration and convergence of nutrition interventions with policy interventions aimed at poverty reduction. There is also a need to expand the scope of the Integrated Child Development Services (ICDS) program to provide mass education regarding nutrition and health by making provisions of home visits of workers primarily focusing on pregnant and lactating mothers.

Objective To explore the associations between obesity-related measures and multimorbidity among older Indian adults and the interactive effects of physical activity in those associations. Design A cross-sectional study was conducted using large representative survey data. Setting and participants The present study used data from the Longitudinal Aging Study in India (LASI) conducted during 2017–2018. Participants included 15 098 male and 16 366 female older adults aged 60 years and above in India. Primary and secondary outcome measures The outcome variable was multimorbidity among older adults coded as no and yes. Descriptive statistics along with bivariate analysis are presented in the paper. Additionally, binary logistic regression analysis was used to fulfil the study objectives. Results About 24% of older adults in the LASI cohort suffered from multimorbidity. Older adults who were overweight/obese (adjusted OR (AOR): 1.61, CI 1.48 to 1.74), had high-risk waist circumference (AOR: 1.66, CI 1.52 to 1.80) and had high-risk waist to hip ratio (AOR: 1.45, CI 1.33 to 1.59) were significantly more likely to suffer from multimorbidity compared with their counterparts. Older adults who were obese and physically inactive had significantly increased odds of suffering from multimorbidity compared with older adults who were obese and physically active. Similarly, older adults with high-risk waist circumference (AOR: 1.30, CI 1.11 to 1.53) and high-risk waist to hip ratio (AOR: 1.32, CI 1.20 to 1.46) along with being physically inactive had significantly higher odds of suffering from multimorbidity in comparison with older adults with high-risk waist circumference and waist to hip ratio along with being physically active. Conclusion While developing health strategies for older adults, physical activity needs to be recognised as a way of minimising comorbidities. Further, the study highlights the importance of using multiple obesity-related measures to predict chronic conditions in the older population.

Background: Older people coming from a lower wealth gradient are more vulnerable to have stressful life events further adding more risk for common mental health disorders and psychological distress situations. The present study explores the associations between socioeconomic and health-related variables and psychological distress among older adults in India and the contribution of such factors to the inequalities in psychological distress.Methods: A cross-sectional survey of 9181 older adults conducted as ‘Building a Knowledge Base on Population Ageing in India’ was assessed. Logistic regression and decomposition models were used to analyze the data. Psychological distress was measured from General Health Questionnaire (GHQ-12). The value of Cronbach's alpha was 0.90. It was having a scale of 0 to 12 on the basis of experiencing stressful symptoms and was re-coded as 0 (representing 6+ stressful symptoms) and 1 (representing 5 and fewer symptoms).Results: Older adults from the poorest wealth quintile, having no source of income, not working for the last one year period, suffering from multi-morbidity, disabled, with low activities of daily living and low instrumental activities of daily living and poor cognitive ability were suffering from high psychological distress in India. Further, factors such as religion, caste, education, living arrangements, and self-worth in the family were major contributors to the concentration of psychological distress in older adults from poor households (concentration index: − 0.23).Conclusion: The study suggests that among older people, there is a wide disparity of experiencing psychological distress across different socio-economic groups with significant factors being responsible for inequality in psychological distress. There is a need to build a “win-win” circumstance across sectors, including a broad spectrum of health, social and economic benefits to the vulnerable older population.