AUTHOR=Said Mohamed Ahmed , Alibrahim Mohammed Shaab 

TITLE=From activity to obesity: understanding gender and type of school divide among Saudi adolescents

JOURNAL=Frontiers in Public Health

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2025.1552243

DOI=10.3389/fpubh.2025.1552243

ISSN=2296-2565

ABSTRACT=BackgroundObesity has emerged as a significant predictor of the nationwide burden of non-communicable diseases in Saudi Arabia.ObjectivesThis study explores patterns in body mass index (BMI), physical activity (PA), and sedentary behavior (SB) among Saudi adolescents, focusing on variations by gender and school type (public vs. private). It identifies key factors affecting BMI.MethodsA total of 2,815 students (53.64% male, aged 15.21 ± 1.55 years) participated. Body weight and composition were determined by bioelectrical impedance, while PA levels and SB scores were assessed through validated questionnaires. Two models were created, one with overall SB and the other with specific SBs.ResultsAmong participants, 28.4% were overweight/obese, with 17.2% classified as obese. Obesity prevalence was higher in boys (26.9%) compared to girls (6.0%). Overweight prevalence was slightly lower in private schools (9.9%) than in public schools (11.8%), while obesity rates were similar (17.3% vs. 17.2%). A significant association between BMI and school type was identified solely in girls (Model 1: p = 0.004, ES = 0.109; Model 2: p = 0.012, ES = 0.096). Age was positively associated with BMI (Model 1: p < 0.004, ES = 0.025; Model 2: p < 0.001, ES = 0.019), as were SB scores (p < 0.001, ES = 0.17). Conversely, PA levels exhibited a negative correlation with BMI (Model 1: p < 0.001, effect size = −0.104; Model 2: p < 0.001, effect size = −0.106). Polynomial analysis revealed a cubic relationship between BMI and PA across all groups, though with low effect sizes.ConclusionGender, age, PA, and SB explained a small portion of BMI variance. Future research should investigate mechanisms underlying these non-linear trends and explore additional confounding variables.