{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T22:33:55Z","timestamp":1785537235765,"version":"3.56.0"},"reference-count":101,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2024,6,25]],"date-time":"2024-06-25T00:00:00Z","timestamp":1719273600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"UK Aid from the UK Department for International Development","award":["GB-CHC-1047501-MERIAM"],"award-info":[{"award-number":["GB-CHC-1047501-MERIAM"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Nutrients"],"abstract":"<jats:p>Despite a remarkable reduction in global poverty and famines, substantial childhood malnutrition continues to persist. In 2017, over 50 million and 150 million young children suffered from acute malnutrition (wasting) and chronic malnutrition (stunting), respectively. Yet, the measurable impact of determinants is obscure. We evaluate proposed socio-environmental related determinants of stunting and wasting across Kenya and Nigeria and quantify their effectiveness. We combine health and demographic data from Kenya and Nigeria Demographic Health Surveys (2003, 2008\u20132009, 2013, 2014) with spatially explicit precipitation, temperature, and vegetation data. Geospatial and disaggregated data help to understand better who is at risk and where to target mitigation efforts. We evaluate the responsiveness of malnutrition indicators using a four-level random intercept hierarchical generalized logit model. We find that spatial and hierarchical relationships explain 28% to 36% of malnutrition outcome variation. Temporal variation in precipitation, temperature, and vegetation corresponds with more than a 50% change in malnutrition rates. Wasting is most impacted by mother\u2019s education, family wealth, clinical delivery, and vaccinations. Stunting is most impacted by family wealth, mother\u2019s education, clinical delivery, vaccinations, and children asymptomatic of fever, cough, or diarrhea. Remotely monitored climatic variables are powerful determinants, however, their effects are inconsistent across different indicators and locations.<\/jats:p>","DOI":"10.3390\/nu16132014","type":"journal-article","created":{"date-parts":[[2024,6,25]],"date-time":"2024-06-25T12:46:56Z","timestamp":1719319616000},"page":"2014","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["The Socio-Environmental Determinants of Childhood Malnutrition: A Spatial and Hierarchical Analysis"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7830-8302","authenticated-orcid":false,"given":"Austin","family":"Sandler","sequence":"first","affiliation":[{"name":"Department of Agricultural and Resource Economics, University of Connecticut, 1376 Storrs Rd., Unit 4021W.B. Young 302, Storrs, CT 06269, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7784-7942","authenticated-orcid":false,"given":"Laixiang","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Geographical Sciences, University of Maryland, 2181 LeFrak Hall, 7251 Preinkert Dr., College Park, MD 20740, USA"},{"name":"School of Finance & Management, SOAS University of London, London WC1H 0XG, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,6,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1016\/S0140-6736(13)60937-X","article-title":"Maternal and child undernutrition and overweight in low-income and middle-income countries","volume":"382","author":"Black","year":"2013","journal-title":"Lancet"},{"key":"ref_2","unstructured":"Smith, L.C., and Haddad, L.J. (2000). 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