Statistical analyses
inflammation, MP, stunting
INFLAMMATION, SECONDARY
To detect a 0.35 SD or greater difference between any 2 groups at 5% significance level and 80% power while allowing for 10% attrition, we recruited 150 children per group (600 in total based on the 4 combinations of MP and WP). If there were no interactions between the 2 experimental arms, then 2 groups of 300 children could be compared enabling differences of 0.24 SD to be detected. In the Participant data were collected using paper case report forms, double-entered in EpiData (Epidata Association, Odense, Denmark) with inbuilt range checks, and submitted weekly using REDCap (Open Source Vanderbilt University) onto a secure server at UCPH. Statistical analyses were carried out using Stata 14. Descriptive statistics were presented as mean (SD) for normally distributed variables, median (interquartile range) for non-normally distributed continuous variables and frequency % (n) for categorical variables. Distribution was assessed visually using normal probability plots. Mean changes in anthropometry and body composition among unsupplemented children were given with 95% confidence intervals (CIs) and The statistical analyses were based on the intention-to-treat (ITT) principle using available case data. The 2 × 2 factorial design was analyzed using a linear mixed model, where we first tested for any interactions between the 2 interventions in the matrix (MP versus WP). In case of no interaction, we then tested for main effects on linear growth and body composition (i.e., +MP versus -MP and +WP versus -WP). In our secondary analysis, we also compared the intervention, i.e., LNS irrespective of ingredient (600 participants) against the unsupplemented reference group (150 participants). We carried out prespecified subgroup analyses for breastfeeding status, sex, stunting severity, and inflammation (defined as serum AGP, a slow reacting acute phase reactant, >1.2 g/l) to test for any further interactions [All our models included the baseline value of the outcome as fixed effect and participant as random effect. Adjusted analyses further included age, sex, and season as fixed effects and site as random effect to obtain the adjusted measures at 95% CI and Difference in compliance between LNS formulations, sex, age category, and breastfeeding status were assessed by chi-square tests.