Physical Activity Dose-Response and Long-Term Effects on Dyslipidemia in Chinese Adults: A CHARLS Study

Abstract Background: This longitudinal study aimed to investigate the dose-response relationship and long-term protective effects of physical activity (PA) on dyslipidemia among middle-aged and older Chinese adults, with a focus on identifying optimal PA thresholds for sustained improvements in lipid profiles. Methods: Utilizing data from the China Health and Retirement Longitudinal Study (CHARLS, 2011–2020), 3,719 participants aged ≥45 years were stratified into quartiles (Q1–Q4) based on weekly metabolic equivalent hours (MET-h/week). Restricted cubic spline (RCS) models and Cox proportional hazards regression adjusted for demographics, lifestyle factors, and physiological parameters were employed to assess nonlinear associations between PA dose and dyslipidemia incidence (defined by elevated TC, TG, LDL-C, or reduced HDL-C). Results: Higher PA levels demonstrated a graded reduction in dyslipidemia risk. Compared to Q1 (lowest activity), Q4 (highest activity) exhibited a 19% lower risk (fully adjusted HR=0.81, 95% CI:0.66–0.98). RCS analysis revealed a nonlinear dose-response curve, with maximal risk reduction at 63.88–163.66 MET-h/week. Subgroup analyses confirmed consistent protective effects across genders, age groups, and BMI categories. Notably, PA exerted heterogeneous effects on lipid subcomponents: HDL-C and TG showed the strongest improvements, while LDL-C reductions plateaued at higher PA doses. Conclusions:This longitudinal study advocates metabolically-tailored PA prescriptions for dyslipidemia, with a nonlinear dose-response curve refuting "more is better" assumptions. Lipid-specific mechanisms demand differentiated exercise regimens: dose-dependent HDL-C optimization versus moderate LDL-C control. Age- and region-specific PA responsiveness underscores demographically-informed guidelines. These findings provide evidence to inform precision exercise guidelines aimed at reducing cardiovascular risk in aging populations.