A Causal Mediation Analysis for Investigating the Effect of a Randomized Cash-Transfer Program in Nicaragua

Abstract

Abstract Mediation analysis can be applied to data from randomized trials of health and social interventions to draw causal inference concerning their mechanisms. We used data from a cluster-randomized trial in Nicaragua, fielded between 2000 and 2002, to investigate whether the impact of providing access to a conditional cash-transfer program on child nutritional outcomes was mediated by child health check-ups and household dietary diversity. In a sample of 443 children 6–35 months old, we estimated the controlled direct (CDE) effect of random assignment on measured height-for-age z scores had we intervened so that all children received a health check-up and had the same level of household dietary diversity, using inverse-probability weighted marginal structural models to account for mediator-outcome confounding. Sensitivity analyses corrected the CDE for potential nondifferential error in the measurement of dietary diversity. Treatment assignment increased height-for-age z score by 0.37 (95% CI: 0.05, 0.69) standard deviations. The CDE was 0.20 (95% CI: −0.17, 0.57) standard deviations, suggesting nearly one-half of the program’s impact on child nutrition would be eliminated had we intervened on these factors, although estimates were relatively imprecise. This study provides an illustration of how causal mediation analysis can be applied to examine the mechanisms of multifaceted interventions.