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Background The purpose of this study is to assess the status of physical body indices such as body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) among the older adults aged 45 and above in India. Further, to explore the association of anthropometric indices with various non-communicable morbidities. Methods The study uses secondary data of the Longitudinal Ageing Survey’s first wave in India (2017–18). The national representative sample for older adults 45 and above (65,662) considered for the analysis. The prevalence of the non-communicable diseases (NCDs) included in the study is based on the self-reporting of the participants. Diseases included are among the top ten causes of death, such as cancer, hypertension, stroke, chronic heart diseases, diabetes, chronic respiratory diseases, and multi-morbidity. Multi-morbidity is a case of having more than one of the morbidities mentioned above. BMI-obese indicates an individual having a BMI ≥30, and the critical threshold value for high-risk WC for men is ≥102 cm while for women is ≥88 cm. The critical limit for the high-risk WHR for men and women is ≥0.90 and ≥ 0.85, respectively. Descriptive statistics and multiple logistic regressions are used to assess the association BMI, WC, and WHR with non-communicable morbidities. Results Based on the multivariate-adjusted model, odds shows that an Indian older adult aged 45 and above is 2.3 times more likely (AOR: 2.33; 95% CI (2.2, 2.5)) by obesity, 61% more likely (AOR: 1.61; 95% CI (1.629, 1.631)) by high-risk WHR and 98% more likely (AOR: 1.98; 95% CI (1.9, 2.1)) by high-risk WC to develop CVDs than their normal counterparts. Similarly, significant positive associations of obesity, high-risk WC, and high-risk WHR were observed with other NCDs and multi-morbidity. Conclusion Our study shows that obesity, high-risk WC, and high-risk WHR are significant risks for developing NCDs and multi-morbidity among the older adults in India. There is a need for a multi-sectoral approach to reduce the share of the elderly population in high-risk groups of BMIs, WHR, and WC.

Background: COVID-19 is an emerging infectious disease which has been declared a Pandemic by the World Health Organization (WHO) on 11th March 2020. The Indian public health care system is already overstretched, and this pandemic is making things even worse. That is why forecasting cases for India is necessary to meet the future demands of the health infrastructure caused due to COVID-19. Objective: Our study forecasts the confirmed and active cases for COVID-19 until July mid, using time series Autoregressive Integrated Moving Average (ARIMA) model. Additionally, we estimated the number of isolation beds, Intensive Care Unit (ICU) beds and ventilators required for the growing number of COVID-19 patients. Methods: We used ARIMA model for forecasting confirmed and active cases till the 15th July. We used time-series data of COVID-19 cases in India from 14th March to 22nd May. We estimated the requirements for ICU beds as 10%, ventilators as 5% and isolation beds as 85% of the active cases forecasted using the ARIMA model. Results: Our forecasts indicate that India will have an estimated 7,47,772 confirmed cases (95% CI: 493943, 1001601) and 296,472 active cases (95% CI:196820, 396125) by 15th July. While Maharashtra will be the most affected state, having the highest number of active and confirmed cases, Punjab is expected to have an estimated 115 active cases by 15th July. India needs to prepare 2,52,001 isolation beds (95% CI: 167297, 336706), 29,647 ICU beds (95% CI: 19682, 39612), and 14,824 ventilator beds (95% CI: 9841, 19806). Conclusion: Our forecasts show an alarming situation for India, and Maharashtra in particular. The actual numbers can go higher than our estimated numbers as India has a limited testing facility and coverage.

Background Globally, one in three women experienced domestic violence. Alike the scenario observed in India, and a very few studies talk about violence and its consequences on women's health. Hence, the purpose of this study is to access the level of various types of spousal violence in India and to understand the association between physical, sexual and emotional violence against ever-married women by their husbands. The study further examines the consequences of spousal violence on women's health in terms of adverse pregnancy outcomes and reproductive health in India. Methods The study uses secondary data from National Family Health Survey-4 (NFHS-4, 2015–16). The analysis was based on a sample of ever-married women aged 15–49 years. Bivariate descriptive analysis and multiple regression analyses have been carried out to understand the association between spousal violence and its consequences on women's health. Results The study finds that the physical, sexual and emotional violence experienced by ever-married women in India are 29.8%, 13.8% and 7.0%, respectively. Further, the physical and sexual violence experienced by women have a significant association with an unwanted pregnancy, abortion, miscarriages and ever had termination of pregnancies. The regression analysis shows that violence by sexual partners among battered women increased the likelihood of unwanted pregnancy. Similarly, abortion and ever had a termination of pregnancies are also adversely affected by partner violence. Further, the risk of sexually transmitted infection increases 77% by sexual violence and 44% by emotional violence among battered women. Also, Sexual violence substantially increases the risk of prolonged labour during pregnancy. Conclusion This study revealed that one in three women experiencing violence by their husband and also it is evident that various forms of spousal violence adversely affect pregnancies outcomes and reproductive health among battered women compared to not battered.

Self-rated health (SRH) is a well-established measure in public health to administer the general health of an individual. It can also be used to assess overall health status’ relationship with the social, physical, and mental health of a person. In this study, we examine the association of SRH and various socio-economic & health-related factors such as multi-morbidity status, mental health, functional health, and social participation. Data used in this paper is collated from the first wave of Longitudinal Ageing Study in India (LASI) 2017-18. A total of 65,562 older adults aged 45 or above are considered in our study. Various indices (multimorbidity, social participation, functional and mental health) have been created to measure factors influencing the SRH of an individual. Overall, in the study population, around 18.4% of people reported poor SRH. Dominance Analysis results show that the contribution of multimorbidity in predicting poor SRH is highest, followed by functional health, mental health, and social participation. In a developing country like India, there is a dire need for policies having a holistic approach regarding the health and well-being of the older population.