. Author manuscript; available in PMC: 2020 Oct 30.

Published in final edited form as: Int J Transgend. 2016 Nov 22;18(2):199–214. doi: 10.1080/15532739.2016.1252300

Table 4.

Logistic regression models predicting physical health variables.

	Arthritis, gout, lupus, fibromyalgia (N = 324)				Asthma (N = 338)
	Block 1		Block 2		Block 1		Block 2
Control Variables	B (SE)	Odds Ratio	B (SE)	Odds Ratio	B (SE)	Odds Ratio	B (SE)	Odds Ratio
Health insurance (y/n)	1.00^* (0.51)	2.72	1.17^* (0.52)	3.23	0.66 (0.41)	1.94	0.74^{^} (0.43)	2.1
Exercise in past mo. (y/n)	−0.28 (0.30)	0.76	−0.33 (0.31)	0.72	−0.21 (0.29)	0.81	−0.29 (0.29)	0.75
Age	0 39^*** (0.09)	1.48	0 44^*** (0.10)	1.55	−0.10 (0.09)	0.9	−0.13 (0.09)	0.88
Predictor Variables
Race (White/POC)			0.90^* (0.36)	2.46			0.81^* (0.32)	2.26
Annual household income			−0.11 (0.12)	0.89			0.07 (0.11)	1.08
No. adults in household			0.02 (0.14)	1.02			−0.18 (0.13)	0.84
No. children in household			−0.20 (0.22)	0.82			−0.22 (0.20)	0.8
Model Results
Omnibus Model Test (χ²)	26.54^*** (df = 3)		34 14^*** (df = 7)		4.45 (df = 3)		14.47^* (df = 7)
Nagelkerke R²	0.12		0.15		0.02		0.06

^{^}

p < .10.

p < .05.

^***

p < .001.