Table 2.

Multivariate linear regression models by race/ethnicity (percent overweight as outcome).

	Overall		African-American		Latino		White
	Model 1a Beta (95% CIc)	Model 2b Beta (95% CI)	Model 1a Beta (95% CI)	Model 2b Beta (95% CI)	Model 1a Beta (95% CI)	Model 2b Beta (95% CI)	Model 1a Beta (95% CI)	Model 2b Beta (95% CI)
Percent below poverty	0.58 (0.49–0.67)	0.58 (0.48–0.67)	0.19 (0.10–0.27)	0.22 (0.13–0.31)	0.21 (0.15–0.27)	0.22 (0.16–0.29)	0.34 (0.22–0.46)	0.34 (0.21–0.47)
Intercept	19.4 (17.9–20.8)	19.4 (17.7–21.0)	25.4 (24–26.8)	25.0 (23.3–26.8)	31.6 (30.6–32.6)	31.5 (30.3–32.7)	17.1 (15.1–19.0)	17.1 (14.8–19.5)
Overall Model	p<0.001	p<0.001	p<0.001	p<0.001	p<0.001	p<0.001	p<0.001	p<0.001
r2	0.67	0.69	0.18	0.34	0.38	0.47	0.29	0.36
AICd	397.4	394.4	393.1	380.8	336.5	326.8	443.8	437.8
Moran’s I (p value)e	0.13 (0.03)		0.28 (<0.001)		0.25 (<0.001)		0.17 (<0.01)

^aOrdinary least squares regression.

^bSpatially adjusted model–using spatial error model.

^cConfidence interval.

^dAkaike’s Information Criteria, lower values indicating improved model fit.

^eMoran’s I statistic based on the residuals from the model, not calculated for models including spatial error term.