Published October 12, 2021 | Version v1
Journal article Open

ENSO impacts child undernutrition in the global tropics

  • 1. University of San Francisco
  • 2. University of Chicago
  • 3. University of California, San Diego

Description

The El Niño Southern Oscillation (ENSO) is a principal component of global climate variability known to influence a host of social and economic outcomes, but its systematic effects on human health remain poorly understood. We estimate ENSO's association with child nutrition at global scale by combining variation in ENSO intensity from 1986-2018 with children's height and weight from 186 surveys conducted in 51 teleconnected countries, containing 48% of the world's under-5 population. Warmer El Niño conditions predict worse child undernutrition in most of the developing world, but better outcomes in the small number of areas where precipitation is positively affected by warmer ENSO. ENSO's contemporaneous effects on child weight loss are detectable years later as decreases in height. This relationship looks similar at both global and regional scale, and has not appreciably weakened over the last four decades. Results imply that almost 6 million additional children were underweight during the 2015 El Niño compared to a counterfactual of neutral ENSO conditions in 2015. This demonstrates a pathway through which human well-being remains subject to predictable climatic processes.

Data availability

The raw survey data are subject to a user agreement and are available at available from the Demographics and Health Surveys Program at https://dhsprogram.com. The raw ENSO data are available via NOAA at https://www.cpc.ncep.noaa.gov/data/indices/. The processed ENSO data are available on Zenodo at https://doi.org/10.5281/zenodo.5208080. The University of Delaware gridded weather data are available at http://climate.geog.udel.edu/climate/html_pages/archive.html. All other datasets produced or used in this analysis can be found at https://doi.org/10.5281/zenodo.5208080.

Data were analyzed using Stata 16, QGIS 2.18, and Matlab 2018b. Code45 to replicate all results is available on Zenodo at https://doi.org/10.5281/zenodo.5208080.

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Additional details

Identifiers

DOI
10.1038/s41467-021-26048-7
Other
oai:uchicago.tind.io:14569

UChicago Information

Division(s)
Harris School of Public Policy Studies
Department(s)
Harris School of Public Policy Studies Research Publications