The investigators identified confounding factors a priori using a directed acyclic graph, which is a causal diagram used to characterize the relationship among variables that influence the primary independent and the dependent variables based on both theorized and documented relationships. In all models, confounders included maternal education (< primary school complete, [Symbol] primary school complete), maternal age (years), marital status (married or living together versus single, widowed, divorced), parity, morbidity (presence of diarrhea or fever in the last two weeks), child age (months), and urban/rural status. The investigators aimed to specify covariates in a way that allowed for the same specification in each country and for each outcome. For variables that were in their continuous form in the DHS (maternal age, child age, parity), the investigators assessed their linearity with the outcomes by specifying disjoint indicator variables. Because variables were approximately linearly associated with the outcomes in most countries, they were retained in their continuous form to minimize the number of observations dropped from the model due to small cell sizes. Marital status and maternal education were dichotomized because there were very few people in some categories (e.g. divorced).