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. Author manuscript; available in PMC: 2014 Jul 1.
Published in final edited form as: Appl Geogr. 2013 Jul;41:1–14. doi: 10.1016/j.apgeog.2013.03.006

Table 6. Multilevel logistic models for risks of physical inactivity (PI) and obesity (OB) using urban ratio as urbanicity measure.

Model PI4 Model PI5 Model OB4 Model OB5
Intercept 0.45580*** 0.45920*** 0.07106*** 0.07172***
Individual-level variables
Female 0.01511*** 0.01510*** −0.00565** −0.00566**
Age (18+) 0.00608*** 0.00609*** 0.01915*** 0.01914***
Age squared −0.00004*** −0.00004*** −0.00019*** −0.00019***
Hispanic 0.03089*** 0.03065*** −0.00163 −0.00151
Married 0.00112 0.00092 −0.00267 −0.00274
Education (1-6) −0.05867*** −0.05866*** −0.02605*** −0.02604***
Employed −0.00661** −0.00664** −0.01197*** −0.01196***
Income (1-8) −0.03126*** −0.03124*** −0.01716*** −0.01716***
Smoker 0.01590*** 0.01585*** −0.03772*** −0.03773***
County-level variables
Racial-ethnic heterogeneity 0.02169* 0.02352* −0.00450 −0.00647
Poverty 0.00118*** 0.00124*** 0.00219*** 0.00229***
Street connectivity 0.00033*** −0.00005
Population-adjusted street connectivity −0.00008 −0.00016**
Urban ratio 0.02880 0.01341 0.04220* 0.05215**
Urban ratio squared −0.03212 0.00756 −0.04544* −0.03987*
No. observations 251,247 251,247 251,247 251,247
AIC 263,127.8 263,140.2 288,846.1 288,839.3

Note: Models PI4 and PI5 for physical inactivity, and models OB4 and OB5 for obesity;

***

statistically significant at 0.001,

**

statistically significant at 0.01,

*

statistically significant at 0.05