Integrating machine learning and statistical analysis to forecast insufficient physical activity trends using socio-demographic predictors.

The model intercept was negative and highly significant (β = −148.30, SE = 10.64, z = −13.94, p < 0.001), providing the baseline for interpreting the effects of sex, region, and time.

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