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A diet high in sodium contributes to a significant proportion of Disability Adjusted Life Years (DALYs) due to cardiovascular diseases. This paper describes the awareness, behaviour and determinants related to dietary salt intake in an adult population of 18–69 years that were assessed as part of the National NCD Monitoring Survey (NNMS) in India. A sub-sample of 3000 adults selected through simple random sampling from 150 nationally representative Primary Sampling Units (PSUs) was included. Data regarding awareness and behaviour related to dietary salt intake were collected. Urinary sodium excretion in spot urine samples was estimated and used to calculate dietary salt intake. The dietary salt intake's sociodemographic, behavioural and metabolic determinants were also analysed. Less than one-third of the adults of both genders in all age groups in rural and urban areas were aware that daily high salt intake could affect health. The estimated mean daily salt intake was 8.0 g (8.9 g/day for men and 7.1 g/day for women). The salt intake was significantly higher in men [Adjusted OR = 17.66 (5.24–59.46)], rural areas [Adjusted OR = 6.14 (1.83–20.60)], overweight and obese respondents [Adjusted OR = 17.62 (3.17–98.07)]. The perception of the harmful effects of high salt intake and practices to limit salt intake was low in the study population. The mean daily salt intake was higher than the WHO recommendation of up to 5 g daily. The mean dietary salt intake is high in the Indian population, which calls for planning and implementing control of dietary salt consumption measures. [ABSTRACT FROM AUTHOR]

In low-and-middle-income countries, people develop chronic diseases at a younger age, leading to health-and-economic loss. Estimates of the age of onset of chronic disease provide evidence for policy intervention, but in the Indian context, evidence is limited. The present study aims to explore the onset of seven chronic diseases across adults and the elderly, along with the prognostic factors of chronic disease onset. Using Wave 1 data of the Longitudinal Ageing Study in India (LASI), we estimated the statistical distributions, the median age at onset, and Loglogistic and Weibull accelerated failure time model to understand the onset of seven medically diagnosed self-reported chronic diseases across age groups. We also obtained the sub-distribution hazard ratio (SHR) from the Fine-Gray model to determine the risk of contracting selected chronic diseases in a competing risk setup. The seven chronic diseases– hypertension, diabetes, lung disease, heart disease/stroke, arthritis, neurological disease, and cancer– were developing early, especially in individuals aged 45–54 and 55–64. Arthritis risk was higher in rural areas, and physically active adults and elderly were 1.32 times (95% CI 1.12–1.56) more likely to develop heart disease/stroke. The emerging evidence of the early onset of neurological diseases in middle-aged adults (i.e., among the 45–54 age group) reminds us of the need to reinforce a balance between the physical and mental life of individuals. The early onset of chronic diseases in the independent and working-age category (45–54 years) can have many social and economic implications. For instance, it can create a greater healthcare burden when these individuals grow older with these diseases. Further, disease-specific interventions would be helpful in reducing future chronic disease burden. [ABSTRACT FROM AUTHOR]

Assessing the impact of lockdowns on COVID-19 incidence may provide important lessons for management of pandemic in resource-limited settings. We examined growth of incident confirmed COVID-19 patients before, during and after lockdowns during the first wave in Pune city that reported the largest COVID-19 burden at the peak of the pandemic. Using anonymized individual-level data captured by Pune's public health surveillance program between February 1st and September 15th 2020, we assessed weekly incident COVID-19 patients, infection rates, and epidemic curves by lockdown status (overall and by sex, age, and population density) and modelled the natural epidemic using the compartmental model. Effect of lockdown on incident patients was assessed using multilevel Poisson regression. We used geospatial mapping to characterize regional spread. Of 241,629 persons tested for SARS-CoV-2, 64,526 (26%) were positive, contributing to an overall rate of COVID-19 disease of 267·0 (95% CI 265·3–268·8) per 1000 persons. The median age of COVID-19 patients was 36 (interquartile range [IQR] 25–50) years, 36,180 (56%) were male, and 9414 (15%) were children < 18 years. Epidemic curves and geospatial mapping showed delayed peak of the patients by approximately 8 weeks during the lockdowns as compared to modelled natural epidemic. Compared to a subsequent unlocking period, incident COVID-19 patients were 43% lower (IRR 0·57, 95% CI 0·53–0·62) during India's nationwide lockdown and were 22% lower (IRR 0·78, 95% CI 0.73–0.84) during Pune's regional lockdown and was uniform across age groups and population densities. Both national and regional lockdowns slowed the COVID-19 infection rates in population dense, urban region in India, underscoring its impact on COVID-19 control efforts. [ABSTRACT FROM AUTHOR]

COVID-19 has affected all countries. Its containment represents a unique challenge for India due to a large population (> 1.38 billion) across a wide range of population densities. Assessment of the COVID-19 disease burden is required to put the disease impact into context and support future pandemic policy development. Here, we present the national-level burden of COVID-19 in India in 2020 that accounts for differences across urban and rural regions and across age groups. Input data were collected from official records or published literature. The proportion of excess COVID-19 deaths was estimated using the Institute for Health Metrics and Evaluation, Washington data. Disability-adjusted life years (DALY) due to COVID-19 were estimated in the Indian population in 2020, comprised of years of life lost (YLL) and years lived with disability (YLD). YLL was estimated by multiplying the number of deaths due to COVID-19 by the residual standard life expectancy at the age of death due to the disease. YLD was calculated as a product of the number of incident cases of COVID-19, disease duration and disability weight. Scenario analyses were conducted to account for excess deaths not recorded in the official data and for reported COVID-19 deaths. The direct impact of COVID-19 in 2020 in India was responsible for 14,100,422 (95% uncertainty interval [UI] 14,030,129–14,213,231) DALYs, consisting of 99.2% (95% UI 98.47–99.64%) YLLs and 0.80% (95% UI 0.36–1.53) YLDs. DALYs were higher in urban (56%; 95% UI 56–57%) than rural areas (44%; 95% UI 43.4–43.6) and in men (64%) than women (36%). In absolute terms, the highest DALYs occurred in the 51–60-year-old age group (28%) but the highest DALYs per 100,000 persons were estimated for the 71–80 years old age group (5481; 95% UI 5464–5500 years). There were 4,815,908 (95% UI 4,760,908–4,924,307) DALYs after considering reported COVID-19 deaths only. The DALY estimations have direct and immediate implications not only for public policy in India, but also internationally given that India represents one sixth of the world's population. [ABSTRACT FROM AUTHOR]

Since untreated or undertreated late-life mental disorders is associated with grave consequences including poor quality of life and increased mortality rates, this study investigates the associated factors of psychiatric disorders and its treatment seeking among older adults in India. Data for this study were derived from the Longitudinal Ageing Study in India (LASI) conducted during 2017–2018. The effective sample size was 31,464 older adults aged 60 years and above. Descriptive statistics and bivariate analysis were used to present the preliminary results. Chi-square test was used to find the significance level for bivariate association. Additionally, the Heckprobit selection model was employed to fulfil the objectives. It was revealed that about 2.8% of older adults had psychiatric disorder and of those who were suffering from psychiatric disorder, 41.3% (out of 2.8%) sought medical treatment. It was found that older adults who ever worked but currently not working, who had low level of life satisfaction, had poor self-rated health, had difficulty in activities of daily living (ADL) and instrumental ADL and had symptoms of psychological distress had higher probability of suffering from psychiatric disorder in reference to their counterparts. Older adults from oldest-old age group, who were females, from poorest wealth quintile, from Scheduled Tribe and from eastern region had lower probability of seeking treatment for psychiatric disorder in reference to their counterparts. The findings of the present study urge that greater attention be devoted at detecting and preventing late-life psychiatric disorder particularly among those who are at greater risk vis., male gender, working status as "ever worked but currently not working", having low life satisfaction, poor SRH, ADL and IADL difficulties, higher psychological distress, belonging to higher wealth quintile and rural place of residence. [ABSTRACT FROM AUTHOR]