ArticleEClinicalMedicine2020
Mapping of variations in child stunting, wasting and underweight within the states of India: the Global Burden of Disease Study 2000-2017.
Article in EClinicalMedicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Geospatial estimation of reproductive, maternal, newborn and child health indicators: a systematic review of methodological aspects of studies based on household surveys.International journal of health geographics · 2020Pooled it
- Geospatial variation and risk factors for malnutrition among postpartum women in rural Bangladesh.PLOS global public health · 2026Article
- Prevalence of severe and moderate anthropometric failure among children in India, 1993-2021.Maternal & child nutrition · 2025Article
- Prevalence and factors contributing to stunted growth in young children of Khordha district, Odisha: A cross-sectional study.Journal of family medicine and primary care · 2024Article
- Spatial variation and risk factors of the dual burden of childhood stunting and underweight in India: a copula geoadditive modelling approach.Journal of nutritional science · 2024Article
- Decomposition analysis of the decline in binary and triad undernutrition among preschool children in India.PloS one · 2023Article
- Quality of anthropometric data in India's National Family Health Survey: Disentangling interviewer and area effect using a cross-classified multilevel model.SSM - population health · 2022Article
- Childhood deprivations predict late-life cognitive impairment among older adults in India.Scientific reports · 2022Article
- Secular Growth Trends in Early Childhood-Evidence from Two Low-Income Birth Cohorts Recruited over a Decade in Vellore, India.The American journal of tropical medicine and hygiene · 2022Article
- Modeling the potential impacts of improved monthly income on child stunting in India: a subnational geospatial perspective.BMJ open · 2022Article
- Determinants of severe acute malnutrition among children aged 6-36 months in Kalafo district (riverine context) of Ethiopia.Scientific reports · 2022Article
- Can fruit and vegetable aggregation systems better balance improved producer livelihoods with more equitable distribution?World development · 2021Article
- Determinants of minimum acceptable diet feeding among children aged 6-23 months in Odisha, India.Public health nutrition · 2021Article
- Multilevel analysis of geographic variation among correlates of child undernutrition in India.Maternal & child nutrition · 2021Article
- Mapping Geographical Differences and Examining the Determinants of Childhood Stunting in Ethiopia: A Bayesian Geostatistical Analysis.Nutrients · 2021Article
- Mapping changes in district level prevalence of childhood stunting in India 1998-2016: An application of small area estimation techniques.SSM - population health · 2021Article
- Changes in socio-economic inequality in nutritional status among children in EAG states, India.Public health nutrition · 2021Article
- Frequency of anemia and micronutrient deficiency among children with cleft lip and palate: a single-center cross-sectional study from Uttarakhand, India.Archives of craniofacial surgery · 2021Article
- Subnational mapping of under-5 and neonatal mortality trends in India: the Global Burden of Disease Study 2000-17.Lancet (London, England) · 2020Article
- Eco-geographic patterns of child malnutrition in India and its association with cereal cultivation: An analysis using demographic health survey and agriculture datasets.Wellcome open research · 2020Article
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Abstract
backgroundTo 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.
methodsWe 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.
findingsThe 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.
interpretationCGF 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.
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