| Resumo: |
*Objective:* To investigate the best statistical models that describe the effect of physical activity on BMI.
*Design:* Cross-sectional analyses of physical activity and BMI data.Subjects: 107 obese, overweight, and healthy college students (mean duration of physical activity for the normal, overweight, and obese students: 89, 59, and 24 months, respectively; mean BMI for the normal, overweight, and obese students: 21.61, 27.07, and 35.54 kg/m^2^, respectively).
*Measurements:* Inverse linear, inverse logarithmic, and inverse logistics models were used to analyze survey data for physical activity (measured by both frequency and duration of exercise) and BMI. Gender, age, and physical intensity variables were also statistically controlled. 
*Results:* Coefficients of determination, r-squared, showed the inverse logarithmic model is more accurate in describing the effect of physical activity on BMI than is the inverse linear model. The inverse logistic method also showed physical activity affects BMI. 
*Conclusions:* Although the inverse logarithmic method can be used in some cases, the inverse logistic model seems to be theoretically and empirically best suited in describing the relationship between physical activity and body weight.
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