Litcius/Paper detail

Poverty and Childhood Obesity: Current Evidence and Methodologies for Future Research

Richard Liang, Ryunosuke Goto, Yusuke Okubo, David H. Rehkopf, Kosuke Inoue

2025Current Obesity Reports8 citationsDOIOpen Access PDF

Abstract

PURPOSE OF REVIEW: This narrative review summarizes current knowledge on the link between poverty and childhood obesity, and then describes conventional and modern epidemiologic methods for causal inference that may help provide more robust evidence on how poverty reduction can prevent childhood obesity. RECENT FINDINGS: Household poverty has been consistently associated with increased risk of childhood obesity across observational studies in industrialized countries. Due to ethical and feasibility limitations, few randomized controlled trials directly test the effect of poverty reduction. A growing number of studies use quasi-experimental methods to study the effects of poverty reduction policies on childhood obesity. These methods include instrumental variables, difference-in-differences, interrupted time series analysis, and regression discontinuity. Other complementary methods such as causal mediation analysis allow us to elucidate the mechanisms of how poverty reduction affects childhood obesity outcomes, while examining heterogeneous treatment effects using cutting-edge machine learning algorithms may further identify subpopulations that benefit the most from poverty interventions. Despite the strong associations between poverty and childhood obesity observed in industrialized countries, current evidence about the causal effect of poverty reduction on childhood obesity is mixed. This is likely due to the complex etiology of childhood obesity and potentially unintended effects of policies. Future studies that leverage advances in causal inference with quasi-experimental approaches will help provide more robust evidence to help guide practitioners and policymakers in ongoing childhood obesity prevention efforts.

Topics & Concepts

PovertyChildhood obesityCausal inferencePsychological interventionObservational studyMediationMedicineObesityLeverage (statistics)PsychologyEnvironmental healthOverweightEconomicsEconomic growthPsychiatrySociologySocial scienceComputer sciencePathologyInternal medicineMachine learningObesity, Physical Activity, DietHealth disparities and outcomesIncome, Poverty, and Inequality