Background Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019.Methods 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10-14 and 50-54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed agespecific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. FindingsThe global TFR decreased from 2•72 (95% uncertainty interval [UI] 2•66-2•79) in 2000 to 2•31 (2•17-2•46) in 2019. Global annual livebirths increased from 134•5 million (131•5-137•8) in 2000 to a peak of 139•6 million (133•0-146•9) in 2016. Global livebirths then declined to 135•3 million (127•2-144•1) in 2019. Of the 204 countries and territories included in...

SummaryBackground18% of the world's population lives in India, and many states of India have populations similar to those of large countries. Action to effectively improve population health in India requires availability of reliable and comprehensive state-level estimates of disease burden and risk factors over time. Such comprehensive estimates have not been available so far for all major diseases and risk factors. Thus, we aimed to estimate the disease burden and risk factors in every state of India as part of the Global Burden of Disease (GBD) Study 2016.MethodsUsing all available data sources, the India State-level Disease Burden Initiative estimated burden (metrics were deaths, disability-adjusted life-years [DALYs], prevalence, incidence, and life expectancy) from 333 disease conditions and injuries and 84 risk factors for each state of India from 1990 to 2016 as part of GBD 2016. We divided the states of India into four epidemiological transition level (ETL) groups on the basis of the ratio of DALYs from communicable, maternal, neonatal, and nutritional diseases (CMNNDs) to those from non-communicable diseases (NCDs) and injuries combined in 2016. We assessed variations in the burden of diseases and risk factors between ETL state groups and between states to inform a more specific health-system response in the states and for India as a whole.FindingsDALYs due to NCDs and injuries exceeded those due to CMNNDs in 2003 for India, but this transition had a range of 24 years for the four ETL state groups. The age-standardised DALY rate dropped by 36·2% in India from 1990 to 2016. The numbers of DALYs and DALY rates dropped substantially for most CMNNDs between 1990 and 2016 across all ETL groups, but rates of reduction for CMNNDs were slowest in the low ETL state group. By contrast, numbers of DALYs increased substantially for NCDs in all ETL state groups, and increased significantly for injuries in all ETL state groups except the highest. The all-age prevalence of most leading NCDs increased substantially in India from 1990 to 2016, and a modest decrease was recorded in the age-standardised NCD DALY rates. The major risk factors for NCDs, including high systolic blood pressure, high fasting plasma glucose, high total cholesterol, and high body-mass index, increased from 1990 to 2016, with generally higher levels in higher ETL states; ambient air pollution also increased and was highest in the low ETL group. The incidence rate of the leading causes of injuries also increased from 1990 to 2016. The five leading individual causes of DALYs in India in 2016 were ischaemic heart disease, chronic obstructive pulmonary disease, diarrhoeal diseases, lower respiratory infections, and cerebrovascular disease; and the five leading risk factors for DALYs in 2016 were child and maternal malnutrition, air pollution, dietary risks, high systolic blood pressure, and high fasting plasma glucose. Behind these broad trends many variations existed between the ETL state groups and between states within the ETL groups. Of the ten le...

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a rules-based synthesis of the available evidence on levels and trends in health outcomes, a diverse set of risk factors, and health system responses. GBD 2019 covered 204 countries and territories, as well as first administrative level disaggregations for 22 countries, from 1990 to 2019. Because GBD is highly standardised and comprehensive, spanning both fatal and non-fatal outcomes, and uses a mutually exclusive and collectively exhaustive list of hierarchical disease and injury causes, the study provides a powerful basis for detailed and broad insights on global health trends and emerging challenges. GBD 2019 incorporates data from 281 586 sources and provides more than 3•5 billion estimates of health outcome and health system measures of interest for global, national, and subnational policy dialogue. All GBD estimates are publicly available and adhere to the Guidelines on Accurate and Transparent Health Estimate Reporting. From this vast amount of information, five key insights that are important for health, social, and economic development strategies have been distilled. These insights are subject to the many limitations outlined in each of the component GBD capstone papers.

Background Malnutrition is a major contributor to disease burden in India. To inform subnational action, we aimed to assess the disease burden due to malnutrition and the trends in its indicators in every state of India in relation to Indian and global nutrition targets. Methods We analysed the disease burden attributable to child and maternal malnutrition, and the trends in the malnutrition indicators from 1990 to 2017 in every state of India using all accessible data from multiple sources, as part of Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017. The states were categorised into three groups using their Socio-demographic Index (SDI) calculated by GBD on the basis of per capita income, mean education, and fertility rate in women younger than 25 years. We projected the prevalence of malnutrition indicators for the states of India up to 2030 on the basis of the 1990-2017 trends for comparison with India National Nutrition Mission (NNM) 2022 and WHO and UNICEF 2030 targets. Findings Malnutrition was the predominant risk factor for death in children younger than 5 years of age in every state of India in 2017, accounting for 68•2% (95% UI 65•8-70•7) of the total under-5 deaths, and the leading risk factor for health loss for all ages, responsible for 17•3% (16•3-18•2) of the total disability-adjusted life years (DALYs). The malnutrition DALY rate was much higher in the low SDI than in the middle SDI and high SDI state groups. This rate varied 6•8 times between the states in 2017, and was highest in the states of Uttar Pradesh, Bihar, Assam, and Rajasthan. The prevalence of low birthweight in India in 2017 was 21•4% (20•8-21•9), child stunting 39•3% (38•7-40•1), child wasting 15•7% (15•6-15•9), child underweight 32•7% (32•3-33•1), anaemia in children 59•7% (56•2-63•8), anaemia in women 15-49 years of age 54•4% (53•7-55•2), exclusive breastfeeding 53•3% (51•5-54•9), and child overweight 11•5% (8•5-14•9). If the trends estimated up to 2017 for the indicators in the NNM 2022 continue in India, there would be 8•9% excess prevalence for low birthweight, 9•6% for stunting, 4•8% for underweight, 11•7% for anaemia in children, and 13•8% for anaemia in women relative to the 2022 targets. For the additional indicators in the WHO and UNICEF 2030 targets, the trends up to 2017 would lead to 10•4% excess prevalence for wasting, 14•5% excess prevalence for overweight, and 10•7% less exclusive breastfeeding in 2030. The prevalence of malnutrition indicators, their rates of improvement, and the gaps between projected prevalence and targets vary substantially between the states. Interpretation Malnutrition continues to be the leading risk factor for disease burden in India. It is encouraging that India has set ambitious targets to reduce malnutrition through NNM. The trends up to 2017 indicate that substantially higher rates of improvement will be needed for all malnutrition indicators in most states to achieve the Indian 2022 and the global 2030 targets. The state-specific findings in this report indicate the...

Majority (53.8%) of the adolescents in this study area are thin and only 2.2% were overweight.

HighlightsPentavalent reassortant rotavirus vaccine was tested for efficacy in infants.The vaccine (BRV-PV) showed excellent tolerability and a good safety profile.Primary analysis efficacy was 36% against SRVGE and up to 60.5% against VSRVGE.The efficacy through 2 years of age was 39.5% (SRVGE) and 54.7% (VSRVGE).The intent to treat analyses confirmed all the per protocol analyses.

Background India has made substantial progress in improving child survival over the past few decades, but a comprehensive understanding of child mortality trends at disaggregated geographical levels is not available. We present a detailed analysis of subnational trends of child mortality to inform efforts aimed at meeting the India National Health Policy (NHP) and Sustainable Development Goal (SDG) targets for child mortality. MethodsWe assessed the under-5 mortality rate (U5MR) and neonatal mortality rate (NMR) from 2000 to 2017 in 5 × 5 km grids across India, and for the districts and states of India, using all accessible data from various sources including surveys with subnational geographical information. The 31 states and groups of union territories were categorised into three groups using their Socio-demographic Index (SDI) level, calculated as part of the Global Burden of Diseases, Injuries, and Risk Factors Study on the basis of per-capita income, mean education, and total fertility rate in women younger than 25 years. Inequality between districts within the states was assessed using the coefficient of variation. We projected U5MR and NMR for the states and districts up to 2025 and 2030 on the basis of the trends from 2000 to 2017 and compared these projections with the NHP 2025 and SDG 2030 targets for U5MR (23 deaths and 25 deaths per 1000 livebirths, respectively) and NMR (16 deaths and 12 deaths per 1000 livebirths, respectively). We assessed the causes of child death and the contribution of risk factors to child deaths at the state level. Findings U5MR in India decreased from 83•1 (95% uncertainty interval [UI] 76•7-90•1) in 2000 to 42•4 (36•5-50•0) per 1000 livebirths in 2017, and NMR from 38•0 (34•2-41•6) to 23•5 (20•1-27•8) per 1000 livebirths. U5MR varied 5•7 times between the states of India and 10•5 times between the 723 districts of India in 2017, whereas NMR varied 4•5 times and 8•0 times, respectively. In the low SDI states, 275 (88%) districts had a U5MR of 40 or more per 1000 livebirths and 291 (93%) districts had an NMR of 20 or more per 1000 livebirths in 2017. The annual rate of change from 2010 to 2017 varied among the districts from a 9•02% (95% UI 6•30-11•63) reduction to no significant change for U5MR and from an 8•05% (95% UI 5•34-10•74) reduction to no significant change for NMR. Inequality between districts within the states increased from 2000 to 2017 in 23 of the 31 states for U5MR and in 24 states for NMR, with the largest increases in Odisha and Assam among the low SDI states. If the trends observed up to 2017 were to continue, India would meet the SDG 2030 U5MR target but not the SDG 2030 NMR target or either of the NHP 2025 targets. To reach the SDG 2030 targets individually, 246 (34%) districts for U5MR and 430 (59%) districts for NMR would need a higher rate of improvement than they had up to 2017. For all major causes of under-5 death in India, the death rate decreased between 2000 and 2017, with the highest decline for infectious diseases, intermediate decline for neona...

BackgroundIn 2005, India established a conditional cash transfer program called Janani Suraksha Yojana (JSY), to increase institutional delivery and encourage the use of reproductive and child health-related services.ObjectiveTo assess the effect of maternal receipt of financial assistance from JSY on childhood immunizations, post-partum care, breastfeeding practices, and care-seeking behaviors.MethodsWe use data from the latest district-level household survey (2007–2008) to conduct a propensity score matching analysis with logistic regression. We conduct the analyses at the national level as well as separately across groups of states classified as high-focus and non-high-focus. We carry out several sensitivity analyses including a subgroup analysis stratified by possession of an immunization card.ResultsReceipt of financial assistance from JSY led to an increase in immunization rates ranging from 3.1 (95%CI 2.2–4.0) percentage points for one dose of polio vaccine to 9.1 (95%CI 7.5–10.7) percentage points in the proportion of fully vaccinated children. Our findings also indicate JSY led to increased post-partum check-up rates and healthy early breastfeeding practices around the time of childbirth. No effect of JSY was found on exclusive breastfeeding practices and care-seeking behaviors. Effect sizes were consistently larger in states identified as being a key focus for the program. In an analysis stratified by possession of an immunization card, there was little to no effect of JSY among those with vaccination cards, while the effect size was much larger than the base case results for those missing vaccination cards, across nearly all immunization outcomes.ConclusionsEarly results suggest the JSY program led to a significant increase in childhood immunization rates and some healthy reproductive health behaviors, but the structuring of financial incentives to pregnant women and health workers warrants further review. Causal interpretation of our results relies on the assumption that propensity scores balance unobservable characteristics.