Statistical analyses
We conducted a descriptive analysis to obtain the frequency and percentage for categorical variables and mean and standard deviation (SD) for continuous variables. We used a one-way analysis of variance (ANOVA) for continuous variables and the chi-square test for categorical variables to determine differences between groups at baseline. Given the study's repeated measurement design, we utilized mixed-effect models with a random effect on individuals nested within the group to account for intrapersonal variation (R-packages: lme4). In this study, we employed a mixed-effect model that comprised the fixed effect of groups (control, MICT, and HIIT) and measurement time (pre and post-test), while controlling for gender, age, education level, residence, self-perceived income level, and body mass index (BMI) as covariates. The interaction effect of measurement time and groups indicated the changes in group differences from pre to post-test, which indicated the causal effect of the intervention. Pairwise comparisons of changing outcomes between groups during the intervention period were further performed (R-packages: emmeans). The generalized additive model with penalized spline was used to estimate the possible nonlinearity dose–response correlations between the performance of TMT response and CBF controlling the measurement time, education, birthplace, age, and BMI. Moreover, the independent sample t-test was used to compare PACES and RPE results among HIIT and MICT groups.We performed a series of sensitivity analyses to assess the robustness of our findings: (1) We reran the main analysis using repeated measures analysis of variance; (2) we also re-analyzed the association of CBF and executive function using a generalized linear model (Supplementary Table 