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Abstract
Objectives
Approximately one-third of the world’s stunted (low height-for-age) preschool-aged
children live in India. The success of interventions designed to tackle stunting appears
to vary by location and depth of poverty. We developed small-area estimation models
to assess the potential impact of increments in household income on stunting across
the country.
Design
Two nationally representative cross-sectional datasets were used: India’s National
Family Health Survey 4 (2015–2016) and the 68th round of the National Sample Survey
on consumer expenditure. The two datasets were combined with statistical matching.
Gaussian process regressions were used to perform geospatial modelling of ‘stunting’
controlling for household wealth and other covariates.
Setting and participants
The number of children in this sample totalled 259 627. Children with implausible
height-for-age z-scores (HAZs) >5 or <−5, or missing data on drinking water, sanitation
facility, mother’s education, or geolocation and children not residing in mainland
India were excluded, resulting in 207 695 observations for analysis.
Results
A monthly transfer of ~$7 (500 Indian rupees) per capita to every household (not targeted
or conditional) was estimated to reduce stunting nationally by 3.8 percentage points
on average (95% credible interval: 0.14%–10%), but with substantial variation by state.
Estimated reduction in stunting varied by wealth of households, with the poorest quintile
being likely to benefit the most.
Conclusion
Improving household income, which can be supported through cash transfers, has the
potential to significantly reduce stunting in parts of India where the burdens of
both stunting and poverty are high. Modelling shows that for other regions, income
transfers may raise incomes and contribute to improved nutrition, but there would
be a need for complementary activities for alleviating stunting. While having value
for the country as a whole, impact of income gained could be variable, and underlying
drivers of stunting need to be tackled through supplementary interventions.
Summary Background 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. Methods 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. Findings 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. Interpretation 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. Funding 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
Summary 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 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. Funding 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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History
Date
received
: 08
July
2021
Date
accepted
: 14
March
2022
Funding
Funded by:
the United States Agency for International Development (USAID);
Award ID: AID-OAA-L-10-00006
Funded by:
FundRef http://dx.doi.org/10.13039/501100009053, The Wellcome Trust DBT India Alliance;