The effect of air pollution and household environmental indicators on anemia status among under-five children in low-middle income countries: exploring potential machine learning applications on demographic and health surveys.

ABSTRACT: Exposure to air pollution has been associated with anemia in children, but little effort has been made in low- and middle-income countries (LMICs) in which the prevalence of anemia is persistently high. This study aimed to assess the effects of air pollution and household environmental indicators on anemia among children aged 6-59 months using machine learning algorithms. The Demographic and Health Survey (DHS) datasets from 45 LMICs were linked with the satellite-derived estimates of annual average particulate matter (PM_2.5) and nitrogen dioxide (NO₂) based on children's area of residence. The modified Poisson regression model was used to assess the association between exposure to air pollutants, household environmental indicators, and anemia status of children. Mach

SUBMITTER: Fenta HM 

PROVIDER: S-EPMC12852912 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature