Statistical analysis
REGRESSION, SECONDARY
All analyses were conducted using SAS 9.4 (SAS Institute). A We assessed normality of all variables in this analysis using histograms and kernel density plots in order to determine their distribution. Outliers were flagged and examined to determine their biological plausibility, using box plots. Data for this secondary analysis were restricted to those participants with any one of the 
Sample size chart for maternal and cord Se biomarkers included in the analysis of associations with growth outcomes. LAZ, length-for-age z-score; WAZ, weight-for-age z-score; WFL, weight-for-length; HCAZ, head circumference for age z-score; LBW, low birth weight; SGA, small for gestational age.We used linear regression and generated bivariate and multivariable models adjusting for covariates after generating directed acyclic graphs to account for hypothesised confounding and biological plausibility of associations. Biomarkers were scaled by a unit of 10 for whole blood and serum We also examined associations between selenoproteins glutathione peroxidase and thioredoxin reductase measured in maternal plasma at mid-gestation (17–24 weeks) and delivery and growth outcomes using linear regression, associations with birth weight, specifically (presented in online Supplementary Tables 