Key predictors of postpartum depression and anxiety symptoms among mothers in Kilifi, Kenya: a machine learning approach

Abstract

Postpartum mental health disorders remain a substantial burden in SSA. This study demonstrates the feasibility of using ML to predict depressive and anxiety symptoms in postpartum mothers. The findings identify key predictors, notably increased household food insecurity, alongside socioeconomic status and maternal health characteristics, that could inform the design and testing of targeted interventions. Future studies should include external validation and examine causal links between these predictors and postpartum mental health outcomes.