Skip to main content
. 2019 Jul 10;14(7):e0219314. doi: 10.1371/journal.pone.0219314

Table 2. Associations of excess body weight with residential density (OR and 95%CI) among urban men and women in 2017 in Nanjing, China.

Residential density a Participants having excess body weight (% and n/N) b Mixed-effects logistic regression models
Model 1 c Model 2 d
OR (95% CI) P value OR (95% CI) P value
Overall
Upper 45.9 (274/597) 1.00 1.00
Middle 52.8 (281/532) 1.32 (1.04–1.67) 0.02 1.29 (1.01–1.64) 0.04
Lower 57.1 (241/422) 1.57 (1.22–2.02) <0.01 1.38 (1.06–181) 0.02
Men
Upper 49.0 (142/290) 1.00 1.00
Middle 57.4 (143/249) 1.41 (1.00–1.98) 0.05 1.38 (0.97–1.97) 0.08
Lower 58.9 (119/202) 1.49 (1.04–2.15) 0.03 1.48 (1.01–2.19) 0.04
Women
Upper 43.0 (132/307) 1.00 1.00
Middle 48.8 (138/283) 1.26 (0.91–1.75) 0.16 1.26 (0.89–1.78) 0.20
Lower 55.5 (122/220) 1.65 (1.16–2.34) 0.01 1.28 (0.88–1.88) 0.20

n: number of participants within higher physical activity category; N: total number of participants within sub-group of residential density.

a Residential density was analyzed as a trichotomous variable (Lower, Middle and Upper tertile, with cut-off values of 56,524 and 29,786 persons/km2).

b physical activity was analyzed as a dichotomous variable (≥150mins/week vs.<150mins/week).

c Model 1 was a univariate analysis with residential density as the single predictor.

d Model 2 was a multivariate mixed-effects logistic regression model with adjustment for age, sex (overall model only), marital status, educational attainment, occupation, smoking status, redmeat intake, physical activity, diabetic status and potential neighborhood-level clustering effects.