Data analysis
METABOLIC SYNDROME
We used the Statistical Package for Social Sciences (SPSS) software version 27.0 (International Business Machines Corporation, Armonk, NY, USA). All statistical tests were two-sided with 0.05 levels of statistical significance (α). Descriptive analysis included means, standard deviations, and frequency distribution (percentages) for the demographic, lifestyle behaviors, and biomarkers of metabolic syndrome. A number of the baseline intervention and control arm continuous variables failed the Shapiro–Wilk test of normality. The Chi-square test for dichotomous variables and the Mann–Whitney U test for continuous and ordinal variables examined baseline differences between the intervention and control arms. Generalized estimating equations (GEE) compared rates of change between the intervention and control arms from baseline to the six- and 18-month assessments.The effect size was obtained by pooling estimates across both pretest and posttest standard deviations for weighting the differences of the pre-post-means to account for intervention’s influence on the standard deviation. Additionally, a bias correction was appliedEffect size for frequency data was computed based on Binomial Effect Size Display