Construction and validation of a covariate-based model for district-level estimation of excess deaths due to COVID-19 in India.

Background: Different statistical approaches for estimating excess deaths due to coronavirus disease 2019 (COVID-19) pandemic have led to varying estimates. In this study, we developed and validated a covariate-based model (CBM) with imputation for prediction of district-level excess deaths in India. Methods: We used data extracted from deaths registered under the Civil Registration System for 2015-19 for 684 of 713 districts in India to estimate expected deaths for 2020 through a negative binomial regression model (NBRM) and to calculate excess observed deaths. Specifically, we used 15 covariates across four domains (state, health system, population, COVID-19) in a zero inflated NBRM to identify covariates significantly (P < 0.05) associated with excess deaths estimate in 460 districts. We then validated this CBM in 140 districts by comparing predicted and estimated excess. For 84 districts with missing covariates, we validated the imputation with CBM by comparing estimated with predicted excess deaths. We imputed covariate data to predict excess deaths for 29 districts which did not have data on deaths. Results: The share of elderly and urban population, the under-five mortality rate, prevalence of diabetes, and bed availability were significantly associated with estimated excess deaths and were used for CBM. The mean of the CBM-predicted excess deaths per district (x̄ = 989, standard deviation (SD) = 1588) was not significantly different from the estimated one (x̄ = 1448, SD = 3062) (P = 0.25). The estimated excess deaths (n = 67 540; 95% confidence interval (CI) = 35 431, 99 648) were similar to the predicted excess death (n = 64 570; 95% CI = 54 140, 75 000) by CBM with imputation. The total national estimate of excess deaths for all 713 districts was 794 989 (95% CI = 664 895, 925 082). Conclusions: A CBM with imputation can be used to predict excess deaths in an appropriate context.

WHO Non-Lab-Based CVD Risk Assessment: A Reliable Measure in a North Indian Population.

Introduction: Timely, affordable, and sustained interventions reduce the risk of heart attack or Stroke in people with a high total risk of cardiovascular diseases (CVD). Risk prediction tools are available to estimate the cardiovascular risk using information on multiple variables. CVD risk charts prepared by the World Health Organization (WHO) has laboratory-based and non-laboratory-based charts with the latter meant for use in resource limited settings. We conducted a study to determine concordance between the laboratory- and non-laboratory risk charts and to estimate the prevalence of selected CVD risk factors in a rural Indian population. Methods: A community-based cross-sectional study was conducted in rural area of Ballabgarh in district Faridabad, Haryana. Sample of 1,018 participants aged 30-69 years was selected randomly from study area. Information on CVDs risk factors was obtained using WHO STEPS questionnaire, anthropometry and laboratory investigation. Risk distribution among the study participants was observed. Concordance between laboratory- and non-laboratory-based WHO CVD risk charts was determined using agreement analysis. Results: The mean age of the study participants was 43.9 (8.9) years and 55.6% participants were women. Among various CVD risk factors, hypertension (39.4%) was the major factor followed by overweight (34.1%) was found to be major factor, followed by current smoking (23.6%) and hypercholesterolemia (18.7%). The concordance between the two charts was 83.3% with kappa value of 0.64. Considering laboratory-based charts as the gold standard, the sensitivity and specificity of non-laboratory-based risk charts at 5% risk as cut-off was 86.5% and 90.3% respectively. Conclusion: The study shows a good agreement between the laboratory-based and non-laboratory-based risk charts. Thus non-laboratory-based risk charts are suitable for risk estimation of CVDs for use in resource limited settings like India.

Sleep Quality Assessment of Adolescents Residing in an Urban Resettlement Colony, New Delhi, India.

BACKGROUND: Sleep is essential for physical and psychological development of children as well as adolescents. Poor sleep has been noted to lead to poor diet, obesity, stunted growth, mental health issues, and substance abuse. Despite the knowledge regarding the importance of sufficient sleep, the prevalence of insufficient sleep has been noted to increase among children and adolescents. OBJECTIVE AND AIM: The aim of the study was to determine the prevalence of poor sleep quality among adolescents of an urban resettlement colony and to evaluate the association of poor sleep quality with the correlates. MATERIALS AND METHODS: A community-based cross-sectional study was conducted including 620 adolescents aged 10-19 years, in an Urban Resettlement Colony, Dakshinpuri Extension, New Delhi. A self-reported interview was conducted with the pretested, semi-structured interview schedule. The interview focused on sociodemographic variable, sleep quality using Pittsburgh sleep quality index, Perceived stress scale, screen time, and anthropometric measurements. RESULTS: The mean of Pittsburgh sleep quality index total score was 2.3 (standard deviation = 1.9). Among the adolescents, 7.3% of them were found to be poor sleepers. Poor sleep quality was observed to be higher during school days as compared to vacation (9.3%, 6.5%, respectively). Adolescents of age group equal to and > 15 years have higher odds of having poor sleep quality than those younger than 15 years of age (odds ratio = 4.9; 95% confidence interval: 2.2, 10.8). CONCLUSION: Significant difference in sleep duration was noted among adolescents of age ≥15 years as compared to the younger group in the present study.

Screen-based media use and screen time assessment among adolescents residing in an Urban Resettlement Colony in New Delhi, India.

BACKGROUND: Media forms an important part of the lives of adolescents in as much as the shows they watch on television, playing video games, as well as visiting the various websites. There is a growing concern of the influence of media on every aspect of health of children and adolescents. About 95% of the population in India has availability of television. India has limited studies which have explored the use of screen-based media (SBM) and its effect on child health. This study was conducted to assess the pattern of SBM use. METHODS: A community-based cross-sectional study was conducted in an Urban Resettlement Colony, New Delhi. The study included 550 adolescents of age group from 10 to 19 years of age selected through simple random sampling from a list of adolescents residing in the area. A semi-structured interview schedule was used. RESULTS: About 98% of the adolescents used SBM. Television formed the maximum used media (96.5%). The mean (standard deviation) of the screen time was found to be 3.8 (2.77) h/day. Out of the total screen time, time contributed by television is 2.8 h/day followed by other SBM. About 68% of adolescents reported having screen time more than the recommended (>2 h). Significant association was observed between screen time and watching television while eating [odds ratio (95% confidence interval) = 0.35 (0.22, 0.55)]. CONCLUSION: High proportion of adolescents use SBM for more than the recommended screen time. We should have a recommendation for maximum screen time separately for developing countries.