Sociodemographic risk factors of under-five stunting in Bangladesh: Assessing the role of interactions using a machine learning method.

ABSTRACT: This paper aims to demonstrate the importance of studying interactions among various sociodemographic risk factors of childhood stunting in Bangladesh with the help of an interpretable machine learning method. Data used for the analyses are extracted from the Bangladesh Demographic and Health Survey (BDHS) 2014 and pertain to a sample of 6,170 under-5 children. Social and economic determinants such as wealth, mother's decision making on healthcare, parental education are considered in addition to geographic divisions and common demographic characteristics of children including age, sex and birth order. A classification tree was first constructed to identify important interaction-based rules that characterize children with different profiles of risk for stunting. Then binary logistic regres

SUBMITTER: Mansur M 

PROVIDER: S-EPMC8407547 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature