Sex-Specific Effects of Resistance Training Intensity on High-Density Lipoprotein Cholesterol in Aging Adults - Intan Suraya Ellyas; Abdelhalim Yousef; Carla Mariela Salazar-Ayala (Multidisciplinary Journal of Tourism, Hospitality, Sport and Physical Education, 2026)
Purpose of the study: This study aims to examine the effects of light and moderate resistance training intensities on high-density lipoprotein (HDL) cholesterol levels in aging adults, compare sex differences in HDL cholesterol responses, and analyze whether sex modifies the relationship between training intensity and lipid adaptation. Methodology: This study employed a quasi-experimental 2×2 factorial design involving adults aged 45–75 years from the Senam Sehat Indonesia (SSI) PWRI group in Karangpandan, Indonesia. Participants underwent eight weeks of light- or moderate-intensity resistance training. HDL cholesterol was assessed through blood analysis, and changes were evaluated using two-way ANOVA following normality and homogeneity assumption testing. Main Findings: Both light and moderate resistance training were associated with increased HDL cholesterol levels, with no significant difference between training intensities (p = 0.769). Female participants showed a higher average HDL improvement than male participants at the descriptive level; however, this sex difference did not reach statistical significance (p = 0.187), despite a medium effect size (η² = 0.06), indicating that the study was likely underpowered to detect it. No significant interaction was found between training intensity and sex (p = 0.482). Novelty/Originality of this study: Rather than assuming a uniform physiological response, this study explored whether biological sex influences lipid adaptation following resistance training. Although the sex-related effect was not statistically significant, the observed medium effect size highlights potential biological differences in HDL responses. These findings emphasize the importance of adequately powered sex-stratified trials and provide effect-size estimates to support future research design