Table 4.

Multinomial logistic regression analysis of GPs’ preferences for time spent on preventive health care services¹

	Risk conditions		Preventive health clinics		School health services
Independent variables	Less time	More time	Less time	More time	Less time	More time
	OR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)
Age 50+	1.0 (0.6 – 1.6)	1.1 (0.8 – 1.5)	1.3 (0.8 – 2.0)	1.5 (0.6 – 3.8)	1.4 (0.9 – 2.1)	1.8 (0.6 – 5.5)
Female	1.0 (0.6 – 1.5)	1.3 (1.0 – 1.7)	0.8 (0.6 – 1.3)	1.0 (0.5 – 2.2)	0.6 (0.4 – 0.9)	2.0 (0.8 – 4.7)
Municipality >20,000 inhabitants	1.1 (0.7 – 1.8)	0.9 (0.7 – 1.3)	1.4 (0.9 – 2.1)	0.6 (0.2 – 1.4)	1.0 (0.7 – 1.6)	0.4 (0.1 – 1.1)
Specialist in GP	1.6 (0.9 – 2.8)	0.8 (0.5 – 1.0)	1.0 (0.6 – 1.6)	0.5 (0.2 – 1.3)	1.0 (0.6 – 1.6)	0.2 (0.1 – 0.6)
List size < 1,200	1.8 (1.1 – 2.9)	0.7 (0.5 – 1.0)2	0.6 (0.4 – 0.9)	1.4 (0.6 – 3.4)	0.6 (0.4 – 0.9)	2.0 (0.7 – 5.7)
< 4 GPs in the practice	0.6 (0.3 – 0.9)	0.8 (0.6 – 1.1)	1.4 (1.0 – 2.1)	0.7 (0.3 – 1.6)	1.0 (0.7 – 1.5)	0.6 (0.2 – 1.4)
Salaried position	1.7 (0.8 – 3.5)	1.0 (0.6 – 1.8)	0.5 (0.1 – 1.6)	1.8 (0.6 – 5.2)	0.6 (0.2 – 1.7)	3.7 (1.5 – 9.4)
Pseudo R-Square (Nagelkerke)	0.03		0.05		0.10

¹ In the multinomial models the GPs’ preferences for using less time as well as more time were contrasted to no change in the time spent on different preventive health care services.

² p=0.026, CI includes 1.0 due to rounding.