Faculty of Public Health - Andalas University - OCS, 13th IEA SEA Meeting and ICPH - SDev

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Anthropometric failure among children in India: A district level scenario and geospatial analysis of malnutrition
Manisha Dubey

Last modified: 2018-08-09

Abstract


Background: India is grappling with a multiple burdens of malnutrition. About 40 percent of Indian population is undernourished, every third child is undernourished and every second child is anaemic. Almost half of under-five mortality are attributable to malnutrition. Its well documented that 80% Indian children do not have access to dietary diversity. As every sixth human is from India, to achieve SDG goals, especially zero hunger by 2030, India has a vital role.

Material and Methods: National Family Health Survey-4 data of 0.22 million children of age 0-59 months born during 2010-16 in 640 districts (29 states and 7 union territories) of India is used in the study. We have used WHO child growth standard to check malnutrition in children aged 0-59 months. A composite index of anthropometric failure is computed to assess the extent of problem. We used multivariable multinomial logistic regression to analyse the predictors of various levels of complete anthropometric failure.

Results: In India, 54.90% (95% CI: 54.60%-55.21%) of children aged 0-59 months are suffering from any form of malnutrition (stunting, wasting, underweight). Out of 640 districts, prevalence of malnutrition is more than 50% in 390 districts; highest in Dang district (78.05%) followed by Gulbarga (77.98%) and Paschim Singhbhumi (77.49%). Malnourishment is high among poorest quintile 67.85% (95% CI, 67.34%-68.34%) and rural residents 57.45% (95% CI, 57.13%-57.55%).  Composite index of anthropometric failure  shows that 40.72% (95%CI: 40.32%-41.12%) of children have single malnutrition (presence of any one: stunting/wasting/underweight), 47.65% (95% CI: 47.25%-48.05%) children have dual burden of malnutrition (underweight along with stunting or wasting) and 11.62% (95% CI: 11.37%-11.88%) children have complete anthropometric failure (presence of stunting, wasting and underweight). In multivariable multinomial logistic regression, it is observed that wealth quintile, sex of child, mother’s body mass index, mother’s anaemia, antenatal care visits and place of residence is associated with single, double or complete anthropometric failure. Geospatial analysis (LISA) depicts the spatial correlation between single, double and complete anthropometric failure.

Conclusion: This study has identified substantial within and between state variations in malnutrition in India. Nutrition is central to the achievement of SDG goals and other national policies. Findings of the present study would guide to target the most vulnerable and needy population which can be translated into early and efficient improvement and achievement of  programs and policies.