Statistical analysis
depression
REGRESSION
Descriptive analyses (means or percentages and standard deviations) were used to report characteristics of the study population. The wealth gaps in cognitive and social-emotional scores over time were visualized separately for boys and girls. Multivariable linear regression analyses were used to assess the association of wealth quintile with child development. To assess the roles of potential mitigating factors, we estimated the size of the wealth gaps for the lowest and highest quintiles in five sequential steps: In step 0, we included only wealth as predictor variable (unadjusted model). In step 1, we included the quality of home environment score in early childhood (for outcomes at 1y and 2y) and the home environment in both early and middle childhood (for outcomes at 6-7y). In step 2, we included additional maternal factors (education, IQ, and depression). In step 3, we added child HAZ at 1y as an indicator of early child nutrition. Finally, in step 4 we added school attendance that was measured in middle childhood. We adjusted for ethnicity, types of preconception supplementation, child age and child sex at all steps. Bootstrap methods [