Statistical analysis
’s dietary behavior
REGRESSION, SECONDARY, LITTLE
All statistical analyses were carried out as per study protocol [Descriptive analysis was conducted to describe mothers’ demographic characteristics, child BMI and BMI z-score, and secondary outcomes (i.e., children’s dietary behavior and activity behavior). Pearson’s Chi-squared tests examined the differences in mothers’ demographic characteristics between intervention and control groups.Multiple linear regression models investigated effects of the intervention on child BMI and BMI z-score at 3 years of age. Multiple logistic regression models were fitted to investigate effects of the intervention on secondary outcomes. Adjusted odds ratios (AORs) were calculated. Since the randomization at age 2 years was stratified by group allocation in the previous trial [Missing data analyses were conducted for study outcomes to examine the patterns and mechanisms of missing data. Little’s test was conducted to test if missing was completely at random (MCAR). Models for missingness were also fitted to examine whether missing was at random. Since the missing was at random, MI by chained equations was used to address potential bias due to missing values. We imputed all missing values for the full intention to treat analysis of all 662 randomized participants. The imputation model predicting missing outcome values was based on all plausible observed values of outcomes, dietary and activity behaviors and family demographics at baseline (2 years of age) and at 3 years of age. We used 20 imputations each time which gave a relative efficiency of 99% [