Objectives: To analyze the relationship between residential physical activity environment and food environment respectively and adolescent BMI level, the correlation between adolescent physical activity level and food intake behavior respectively and adolescent BMI level, as well as compare the difference of correlation between residential single physical activity environment or combined physical activity environment and adolescent BMI level, and the difference of correlation between food environment and adolescent BMI level. Methods: Based on the cross-sectional study design, a total of 1035 adolescents aged 11 to 17 years were surveyed in the urban area of Jinhua City. The final valid sample was 884 (including 411 males and 473 females) after screening, due to the methodological difficulties of the food intake frequency survey. The height and weight of the sample were measured, and the subjective perception evaluation of physical activity level, frequency of food intake, residential physical activity environment, and food environment were investigated. Results: (1) No significant difference exists in BMI between physical activity levels in the sample overall and among men, but a significant difference exists between physical activity levels among women (p<0.05). A significant difference exists in BMI between the frequencies of non-healthy food intake in the overall sample (p<0.05 or p<0.01). After differentiating by gender, there were significant differences in BMI among different frequencies of fried food, puffed food, and carbonated beverage intake among men (p<0.05 or p<0.01), and among women for different frequencies of puffed food, sugary drinks, and carbonated beverages (p<0.05 or p<0.01). (2) All indicators of physical activity environment in the residence were correlated with the physical activity level of adolescents and were significant (p<0.05 or p<0.01). The physical activity level of females compared to males was correlated with the safety of physical activity facilities and other environmental indicators in and around the residence and was significant after differentiating by gender. (3) Binary Logistic Regression results showed that when the independent variable was the combination of "physical activity and frequency of food intake", fried food (OR=1.771, p<0.05), puffed food (OR=1.762, p<0.05), and carbonated beverage intake frequency (OR=2.082, p<0.05) were risk factors for adolescent obesity. When the independent variable was a combination of "physical activity environment and food environment", fewer stray dogs roaming in and around the residence (OR=0.766, p<0.05), better physical activity venues/facilities (OR=0.661, p<0.05), and more free physical exercise areas (OR= 0.686, p < 0.01) were protective factors for adolescent obesity. Conclusion: The overall physical activity level of adolescents in Jinhua urban area was low and the frequency of unhealthy food intake was high. The differences between groups with different unhealthy food intake frequencies were significant. There were significant correlations between physical activity environment and physical activity level of adolescents, and food environment and frequency of unhealthy food intake of adolescents. A better physical activity environment and food environment in and around the residence contributed to adolescents showing relatively lower BMI levels. Female adolescents need to pay more attention to the combined effect of "physical activity environment and food environment" in obesity prevention and control, compared with male adolescents.