Mapping of variations in child stunting, wasting and underweight within the states of India: the Global Burden of Disease Study 2000–2017

Hemalatha Rajkumar(Indian Council of Medical Research), Anamika Pandey(Public Health Foundation of India), Damaris K. Kinyoki(Seattle University), Siddarth Ramji(Maulana Azad Medical College), Rakesh Lodha(All India Institute of Medical Sciences), G Anil Kumar(Public Health Foundation of India), Nicholas J Kassebaum(Institute for Health Metrics and Evaluation), Elaine Borghi(World Health Organization), Deepti Agrawal(World Health Organization - India), Subodh S. Gupta(Mahatma Gandhi Institute of Medical Sciences), Avula Laxmaiah(National Institute of Nutrition), Anita Kar(Savitribai Phule Pune University), Matthews Mathai(Liverpool School of Tropical Medicine), Chris M Varghese(Public Health Foundation of India), Shally Awasthi(King George's Medical University), Priyanka Bansal(Indian Council of Medical Research), Joy Kumar Chakma(Indian Council of Medical Research), Michael L. Collison(Institute for Health Metrics and Evaluation), Supriya Dwivedi(Indian Council of Medical Research), Mahaveer Golechha(Indian Institute of Public Health Gandhinagar), Zaozianlungliu Gonmei(Indian Council of Medical Research), Suparna Ghosh‐Jerath(Public Health Foundation of India), Rajni Kant(Indian Council of Medical Research), Ajay Khera(Government of India), Rinu P Krishnankutty(Public Health Foundation of India), Anura V. Kurpad(St.John's Medical College Hospital), Laishram Ladusingh(Bodoland University), Ridhima Malhotra(Public Health Foundation of India), Raja Sriswan Mamidi(Indian Council of Medical Research), Helena Manguerra(Institute for Health Metrics and Evaluation), Joseph L. Mathew(Post Graduate Institute of Medical Education and Research), Parul Mutreja(Public Health Foundation of India), Nimmathota Arlappa(Indian Council of Medical Research), Ashalata Pati(Ministry of Health and Family Welfare), Manorama Purwar, Kankipati V. Radhakrishna(Indian Council of Medical Research), Neena Raina(World Health Organization Regional Office for South-East Asia), Mari Jeeva Sankar(All India Institute of Medical Sciences), Deepika Saraf(Indian Council of Medical Research), Megan F. Schipp(Institute for Health Metrics and Evaluation), Rajesh Sharma(Indian Council of Medical Research), Chander Shekhar(Indian Council of Medical Research), Anju Sinha(Indian Council of Medical Research), V. Sreenivas(All India Institute of Medical Sciences), K. Srinath Reddy(Public Health Foundation of India), Hendrik J Bekedam(World Health Organization - India), Soumya Swaminathan(World Health Organization), Stephen S Lim(University of Washington), Rakhi Dandona(University of Washington), Christopher J L Murray(Institute for Health Metrics and Evaluation), Simon I Hay(Seattle University), Gurudayal Singh Toteja(Indian Council of Medical Research), Lalit Dandona(Seattle University)
EClinicalMedicine
May 1, 2020
Cited by 55Open Access
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Abstract

BACKGROUND: 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. METHODS: 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. FINDINGS: 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. INTERPRETATION: 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.


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