Analysis of primary and secondary outcomes
REGRESSION, SECONDARY
We conducted analyses in SAS software version 9.4 (Cary, NC) and defined statistical significance as estimates with a For the primary outcomes, we used linear mixed effects regression to estimate mean unadjusted and adjusted differences in BMIz and modified BMIz change per school year from baseline to follow up for the intervention relative to control. Random intercepts accounted for nesting of timepoints (For child-level secondary outcomes, we used logistic mixed effects regression to estimate (in odds ratios) the effect of intervention on health behavior recommendations at follow-up (controlling for baseline). Random intercepts accounted for nesting of children (