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Do We Have The Wrong End Of The Stick On Reducing Undernutrition? Insights On Determinants Of Subnational Trends In India
Author(s) -
Me Purnima,
Cyriac Shruthi,
Kadiyala Suneetha
Publication year - 2015
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.29.1_supplement.31.7
Subject(s) - underweight , food security , poverty , malnutrition , environmental health , sanitation , medicine , geography , breastfeeding , socioeconomics , overweight , demography , agriculture , obesity , economics , economic growth , pediatrics , archaeology , pathology , sociology
Background Studies of national trends in undernutrition have identified underlying determinants (education, sanitation, poverty, food security) as key drivers of change. We aimed to understand the role of immediate & underlying determinants of subnational trends in underweight between 2002 & 2011 in India. Data We constructed a district‐level dataset from 2 surveys, 9y apart, of children <5y in 100 poor districts in India, using variables common across surveys & including additional variables from other district data sources. Outcome variable: percent change in district‐level prevalence of underweight (weight‐for‐age <‐2 z‐scores) between 2002 & 2011 (stunting trend data not available). Regressions included variables capturing immediate and underlying factors & initial underweight levels. Results Mean underweight decline was 15.10±12.10 pp. Improvements in maternal education (p<0.1), household assets (p<0.05), access to toilets (p<0.05), household diet quality (% of food expenditures spent on cereals) (p<0.001), poverty (share of food expenditures out of total) (p<0.001) & rural roads (p<0.1) were associated with underweight declines (R 2 =0.83). Change in immediate determinants (breastfeeding, immunization & diarrhea) was not associated with declines, possibly due to poor measurement or an incomplete set of available determinants. Conclusions Our results point to improvements in social equity‐related factors as primary drivers of nutrition change in poor areas. They also highlight a need to invest in better integrated datasets for robust analysis of the balance of immediate and underlying determinants. Funding: UKAID, through Transform Nutrition, led by IFPRI.