A systematic understanding of population-level trends in deaths due to road injuries at the subnational level over time for India's 1·4 billion people, by age, sex, and type of road user is not ...readily available; we aimed to fill this knowledge gap.
As part of the Global Burden of Diseases, Injuries, and Risk Factors Study, we estimated the rate of deaths due to road injuries in each state of India from 1990 to 2017 based on several verbal autopsy data sources. We calculated the number of deaths and death rate for road injuries by type of road user, and assessed the age and sex distribution of these deaths over time. Based on the trends of the age-standardised death rate from 1990 to 2017, we projected the age-standardised death rate to 2030 to assess if the states of India would meet the Sustainable Development Goal (SDG) target to halve the death rate for road injuries from 2015 by 2020 or 2030. We calculated 95% uncertainty intervals (UIs) for the point estimates.
In 2017, 218 876 deaths (95% UI 201 734 to 231 141) due to road injuries occurred in India, with an age-standardised death rate for road injuries of 17·2 deaths (15·7 to 18·1) per 100 000 population, which was much higher in males (25·7 deaths 23·5 to 27·4 per 100 000) than in females (8·5 deaths 7·2 to 9·1 per 100 000). The number of deaths due to road injuries in India increased by 58·7% (43·6 to 74·7) from 1990 to 2017, but the age-standardised death rate decreased slightly, by 9·2% (0·6 to 18·3). In 2017, pedestrians accounted for 76 729 (35·1%) of all deaths due to road injuries, motorcyclists accounted for 67 524 (30·9%), motor vehicle occupants accounted for 57 802 (26·4%), and cyclists accounted for 15 324 (7·0%). India had a higher age-standardised death rate for road injury among motorcyclists (4·9 deaths 3·9–5·4 per 100 000 population) and cyclists (1·2 deaths 0·9–1·4 per 100 000 population) than the global average. Road injury was the leading cause of death in males aged 15 to 39 years in India in 2017, and the second leading cause in this age group for both sexes combined. The overall age-standardised death rate for road injuries varied by up to 2·6 times between states in 2017. Wide variations were seen between the states in the percentage change in age-standardised death rate for road injuries from 1990 to 2017, ranging from a reduction of 38·2% (22·3 to 51·7) in Delhi to an increase of 17·0% (0·6 to 34·7) in Odisha. If the trends estimated up to 2017 were to continue, no state in India or India overall would achieve the SDG 2020 target in 2020 or even in 2030.
India's contribution to the global number of deaths due to road injuries is increasing, and the country is unlikely to meet the SDG targets if the trends up to 2017 continue. India needs to implement evidence-based road safety interventions, promote strong policies and traffic law enforcement, have better road and vehicle design, and improve care for road injuries at the state level to meet the SDG goal.
Bill & Melinda Gates Foundation and Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.
To inform actions at the district level under the National Nutrition Mission (NNM), we assessed the prevalence trends of child growth failure (CGF) indicators for all districts in India and ...inequality between districts within the states.
We assessed the trends of CGF indicators (stunting, wasting and underweight) from 2000 to 2017 across the districts of India, aggregated from 5 × 5 km grid estimates, using all accessible data from various surveys with subnational geographical information. The states were categorised into three groups using their Socio-demographic Index (SDI) levels calculated as part of the Global Burden of Disease Study based on per capita income, mean education and fertility rate in women younger than 25 years. Inequality between districts within the states was assessed using coefficient of variation (CV). We projected the prevalence of CGF indicators for the districts up to 2030 based on the trends from 2000 to 2017 to compare with the NNM 2022 targets for stunting and underweight, and the WHO/UNICEF 2030 targets for stunting and wasting. We assessed Pearson correlation coefficient between two major national surveys for district-level estimates of CGF indicators in the states.
The prevalence of stunting ranged 3.8-fold from 16.4% (95% UI 15.2–17.8) to 62.8% (95% UI 61.5–64.0) among the 723 districts of India in 2017, wasting ranged 5.4-fold from 5.5% (95% UI 5.1–6.1) to 30.0% (95% UI 28.2–31.8), and underweight ranged 4.6-fold from 11.0% (95% UI 10.5–11.9) to 51.0% (95% UI 49.9–52.1). 36.1% of the districts in India had stunting prevalence 40% or more, with 67.0% districts in the low SDI states group and only 1.1% districts in the high SDI states with this level of stunting. The prevalence of stunting declined significantly from 2010 to 2017 in 98.5% of the districts with a maximum decline of 41.2% (95% UI 40.3–42.5), wasting in 61.3% with a maximum decline of 44.0% (95% UI 42.3–46.7), and underweight in 95.0% with a maximum decline of 53.9% (95% UI 52.8–55.4). The CV varied 7.4-fold for stunting, 12.2-fold for wasting, and 8.6-fold for underweight between the states in 2017; the CV increased for stunting in 28 out of 31 states, for wasting in 16 states, and for underweight in 20 states from 2000 to 2017. In order to reach the NNM 2022 targets for stunting and underweight individually, 82.6% and 98.5% of the districts in India would need a rate of improvement higher than they had up to 2017, respectively. To achieve the WHO/UNICEF 2030 target for wasting, all districts in India would need a rate of improvement higher than they had up to 2017. The correlation between the two national surveys for district-level estimates was poor, with Pearson correlation coefficient of 0.7 only in Odisha and four small north-eastern states out of the 27 states covered by these surveys.
CGF indicators have improved in India, but there are substantial variations between the districts in their magnitude and rate of decline, and the inequality between districts has increased in a large proportion of the states. The poor correlation between the national surveys for CGF estimates highlights the need to standardise collection of anthropometric data in India. The district-level trends in this report provide a useful reference for targeting the efforts under NNM to reduce CGF across India and meet the Indian and global targets.
18% 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.
Using 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.
DALYs 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 leading causes of disease burden in India in 2016, five causes had at least a five-times difference between the highest and lowest state-specific DALY rates for individual causes.
Per capita disease burden measured as DALY rate has dropped by about a third in India over the past 26 years. However, the magnitude and causes of disease burden and the risk factors vary greatly between the states. The change to dominance of NCDs and injuries over CMNNDs occurred about a quarter century apart in the four ETL state groups. Nevertheless, the burden of some of the leading CMNNDs continues to be very high, especially in the lowest ETL states. This comprehensive mapping of inequalities in disease burden and its causes across the states of India can be a crucial input for more specific health planning for each state as is envisioned by the Government of India's premier think tank, the National Institution for Transforming India, and the National Health Policy 2017.
Bill & Melinda Gates Foundation; Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India; and World Bank
Mental disorders are among the leading causes of non-fatal disease burden in India, but a systematic understanding of their prevalence, disease burden, and risk factors is not readily available for ...each state of India. In this report, we describe the prevalence and disease burden of each mental disorder for the states of India, from 1990 to 2017.
We used all accessible data from multiple sources to estimate the prevalence of mental disorders, years lived with disability (YLDs), and disability-adjusted life-years (DALYs) caused by these disorders for all the states of India from 1990 to 2017, as part of the Global Burden of Diseases, Injuries, and Risk Factors Study. We assessed the heterogeneity and time trends of mental disorders across the states of India. We grouped states on the basis of their Socio-demographic Index (SDI), which is a composite measure of per-capita income, mean education, and fertility rate in women younger than 25 years. We also assessed the association of major mental disorders with suicide deaths. We calculated 95% uncertainty intervals (UIs) for the point estimates.
In 2017, 197·3 million (95% UI 178·4–216·4) people had mental disorders in India, including 45·7 million (42·4–49·8) with depressive disorders and 44·9 million (41·2–48·9) with anxiety disorders. We found a significant, but modest, correlation between the prevalence of depressive disorders and suicide death rate at the state level for females (r2=0·33, p=0·0009) and males (r2=0·19, p=0·015). The contribution of mental disorders to the total DALYs in India increased from 2·5% (2·0–3·1) in 1990 to 4·7% (3·7–5·6) in 2017. In 2017, depressive disorders contributed the most to the total mental disorders DALYs (33·8%, 29·5–38·5), followed by anxiety disorders (19·0%, 15·9–22·4), idiopathic developmental intellectual disability (IDID; 10·8%, 6·3–15·9), schizophrenia (9·8%, 7·7–12·4), bipolar disorder (6·9%, 4·9–9·6), conduct disorder (5·9%, 4·0–8·1), autism spectrum disorders (3·2%, 2·7–3·8), eating disorders (2·2%, 1·7–2·8), and attention-deficit hyperactivity disorder (ADHD; 0·3%, 0·2–0·5); other mental disorders comprised 8·0% (6·1–10·1) of DALYs. Almost all (>99·9%) of these DALYs were made up of YLDs. The DALY rate point estimates of mental disorders with onset predominantly in childhood and adolescence (IDID, conduct disorder, autism spectrum disorders, and ADHD) were higher in low SDI states than in middle SDI and high SDI states in 2017, whereas the trend was reversed for mental disorders that manifest predominantly during adulthood. Although the prevalence of mental disorders with onset in childhood and adolescence decreased in India from 1990 to 2017, with a stronger decrease in high SDI and middle SDI states than in low SDI states, the prevalence of mental disorders that manifest predominantly during adulthood increased during this period.
One in seven Indians were affected by mental disorders of varying severity in 2017. The proportional contribution of mental disorders to the total disease burden in India has almost doubled since 1990. Substantial variations exist between states in the burden from different mental disorders and in their trends over time. These state-specific trends of each mental disorder reported here could guide appropriate policies and health system response to more effectively address the burden of mental disorders in India.
Bill & Melinda Gates Foundation; and Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.
The association of air pollution with multiple adverse health outcomes is becoming well established, but its negative economic impact is less well appreciated. It is important to elucidate this ...impact for the states of India.
We estimated exposure to ambient particulate matter pollution, household air pollution, and ambient ozone pollution, and their attributable deaths and disability-adjusted life-years in every state of India as part of the Global Burden of Disease Study (GBD) 2019. We estimated the economic impact of air pollution as the cost of lost output due to premature deaths and morbidity attributable to air pollution for every state of India, using the cost-of-illness method.
1·67 million (95% uncertainty interval 1·42–1·92) deaths were attributable to air pollution in India in 2019, accounting for 17·8% (15·8–19·5) of the total deaths in the country. The majority of these deaths were from ambient particulate matter pollution (0·98 million 0·77–1·19) and household air pollution (0·61 million 0·39–0·86). The death rate due to household air pollution decreased by 64·2% (52·2–74·2) from 1990 to 2019, while that due to ambient particulate matter pollution increased by 115·3% (28·3–344·4) and that due to ambient ozone pollution increased by 139·2% (96·5–195·8). Lost output from premature deaths and morbidity attributable to air pollution accounted for economic losses of US$28·8 billion (21·4–37·4) and $8·0 billion (5·9–10·3), respectively, in India in 2019. This total loss of $36·8 billion (27·4–47·7) was 1·36% of India's gross domestic product (GDP). The economic loss as a proportion of the state GDP varied 3·2 times between the states, ranging from 0·67% (0·47–0·91) to 2·15% (1·60–2·77), and was highest in the low per-capita GDP states of Uttar Pradesh, Bihar, Rajasthan, Madhya Pradesh, and Chhattisgarh. Delhi had the highest per-capita economic loss due to air pollution, followed by Haryana in 2019, with 5·4 times variation across all states.
The high burden of death and disease due to air pollution and its associated substantial adverse economic impact from loss of output could impede India's aspiration to be a $5 trillion economy by 2024. Successful reduction of air pollution in India through state-specific strategies would lead to substantial benefits for both the health of the population and the economy.
UN Environment Programme; Bill & Melinda Gates Foundation; and Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.
Air pollution is a major planetary health risk, with India estimated to have some of the worst levels globally. To inform action at subnational levels in India, we estimated the exposure to air ...pollution and its impact on deaths, disease burden, and life expectancy in every state of India in 2017.
We estimated exposure to air pollution, including ambient particulate matter pollution, defined as the annual average gridded concentration of PM2.5, and household air pollution, defined as percentage of households using solid cooking fuels and the corresponding exposure to PM2.5, across the states of India using accessible data from multiple sources as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017. The states were categorised into three Socio-demographic Index (SDI) levels as calculated by GBD 2017 on the basis of lag-distributed per-capita income, mean education in people aged 15 years or older, and total fertility rate in people younger than 25 years. We estimated deaths and disability-adjusted life-years (DALYs) attributable to air pollution exposure, on the basis of exposure–response relationships from the published literature, as assessed in GBD 2017; the proportion of total global air pollution DALYs in India; and what the life expectancy would have been in each state of India if air pollution levels had been less than the minimum level causing health loss.
The annual population-weighted mean exposure to ambient particulate matter PM2·5 in India was 89·9 μg/m3 (95% uncertainty interval UI 67·0–112·0) in 2017. Most states, and 76·8% of the population of India, were exposed to annual population-weighted mean PM2·5 greater than 40 μg/m3, which is the limit recommended by the National Ambient Air Quality Standards in India. Delhi had the highest annual population-weighted mean PM2·5 in 2017, followed by Uttar Pradesh, Bihar, and Haryana in north India, all with mean values greater than 125 μg/m3. The proportion of population using solid fuels in India was 55·5% (54·8–56·2) in 2017, which exceeded 75% in the low SDI states of Bihar, Jharkhand, and Odisha. 1·24 million (1·09–1·39) deaths in India in 2017, which were 12·5% of the total deaths, were attributable to air pollution, including 0·67 million (0·55–0·79) from ambient particulate matter pollution and 0·48 million (0·39–0·58) from household air pollution. Of these deaths attributable to air pollution, 51·4% were in people younger than 70 years. India contributed 18·1% of the global population but had 26·2% of the global air pollution DALYs in 2017. The ambient particulate matter pollution DALY rate was highest in the north Indian states of Uttar Pradesh, Haryana, Delhi, Punjab, and Rajasthan, spread across the three SDI state groups, and the household air pollution DALY rate was highest in the low SDI states of Chhattisgarh, Rajasthan, Madhya Pradesh, and Assam in north and northeast India. We estimated that if the air pollution level in India were less than the minimum causing health loss, the average life expectancy in 2017 would have been higher by 1·7 years (1·6–1·9), with this increase exceeding 2 years in the north Indian states of Rajasthan, Uttar Pradesh, and Haryana.
India has disproportionately high mortality and disease burden due to air pollution. This burden is generally highest in the low SDI states of north India. Reducing the substantial avoidable deaths and disease burden from this major environmental risk is dependent on rapid deployment of effective multisectoral policies throughout India that are commensurate with the magnitude of air pollution in each state.
Bill & Melinda Gates Foundation; and Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.
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.
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.
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.
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 effort needed in each state, which will be useful in tracking and motivating further progress. Similar subnational analyses might be useful for other low-income and middle-income countries.
Bill & Melinda Gates Foundation; Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.
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