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

India State-Level Disease Burden Initiative CGF Collaborators. EClinicalMedicine. .

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.

Keywords: Child growth failure; District-level; Geospatial mapping; Inequality; National Nutrition Mission; Prevalence; Stunting; Time trends; Under-five; Undernutrition; Underweight; WHO/UNICEF targets; Wasting.

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Conflict of interest statement

RH, AL, PGB, JKC, SD, ZG, RK, AN, KVR, DSS, RSS, CS, AS, RSM, GST and LD work with the Indian Council of Medical Research, which partially funded this research. All other authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Stunting, wasting, and underweight mapping in India. (A) 2000, (B) 2010, and (C) 2017. (D) Tertile groupings of district-level prevalence in 2017 against the annual rate of reduction from 2010 to 2017.
Fig. 1c
Fig. 1
Fig. 1c
Fig. 1
Fig. 2
Fig. 2
Coefficient of variation for stunting, wasting and underweight between the districts within the states of India, 2000 and 2017. Data shown for states with more than 10 districts.
Fig. 3
Fig. 3
Identification of priority districts of Odisha, Uttar Pradesh and Bihar based on tertile groupings of district-level prevalence of child growth failure indicators in 2017 against the annual rate of their reduction from 2010 to 2017.
Fig. 3
Fig. 3
Identification of priority districts of Odisha, Uttar Pradesh and Bihar based on tertile groupings of district-level prevalence of child growth failure indicators in 2017 against the annual rate of their reduction from 2010 to 2017.
Fig. 3
Fig. 3
Fig. 4
Fig. 4
Gap between the projected prevalence of child growth failure indicators in the districts of India in 2022 and 2030 based on the trends from 2000 to 2017 versus the NNM 2022 and the WHO/UNICEF 2030 targets.
Fig. 5
Fig. 5
Correlation between the national surveys for district-level prevalence of stunting, wasting and underweight in Bihar, Uttar Pradesh and Maharashtra. NFHS = National Family Health Survey; DLHS = District-level household survey; AHS = Annual Health Survey; r = Pearson correlation coefficient.

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