Table 3.

Logistic regression results predicting low birth weight from dichotomous altitude of residence adjusting for pregnancy weight gain and background factors

Independent variable	Unstandardized regression coefficient (b)	Wald	Adjusted odds ratio	95% CI
Maternal height	− .07	1234.48	.94	.93–.94
Pre-pregnancy BMI	− .04	1548.49	.96	.96–.97
Pregnancy induced hypertensiona	1.29	5027.67	3.64	3.52–3.78
Cigarette use during pregnancyb	.57	1156.23	1.77	1.71–1.83
Eclampsiac	1.99	2264.11	7.34	6.76–7.97
Marital statusd	.19	205.81	1.21	1.18–1.25
Ethnicitye	− .20	238.53	.82	.80–.84
Family income	− .05	201.35	.95	.94–.96
Maternal age	.02	369.11	1.02	1.02–1.02
Number of previous pregnancies	.02	20.37	1.02	1.01–1.02
WICf	.06	18.91	.94	.92–.97
Gestational diabetesg	.09	14.21	1.10	1.05–1.15
Pregnancy weight gain	− .02	3466.78	.98	.98–.98
Elevation of maternal residenceh	.24	39.86	1.27	1.18–1.37

All significant variables from Table 1 were included as potential covariates in the model. Covariates were entered stepwise in the first step, followed by entry of pregnancy weight gain in the second step, and altitude of residence in the final step. Individual variable values above are from the final step of the model with all variables entered

Overall model: R² = .059; χ² = 13,813.89, p < .001; 91.5% correctly classified

^aNo pregnancy hypertension is reference group

^bNon-smoker during pregnancy is reference group

^cNo eclampsia is reference group

^dMarried is reference group

^eNon-Hispanic is reference group

^fNot receiving WIC benefits is reference group

^gNo gestational diabetes is reference group

^hElevation < 2500 m is reference group