Juvenile obesity and its association with utilisation and costs of pharmaceuticals - results from the KiGGS study

Table 2 Number of pharmaceuticals - results of regression analysis

	Number of drugs (after exclusion)		Number of drugs (before exclusion)
Parameter	Exp(Est)	Pr > \|t\|^e	Exp(Est)	Pr > \|t\|^e
Intercept	1.472	< 0.0001	1.608	< 0.0001
Sex: female	1.225	< 0.0001	1.145	< 0.0001
Age	0.796	< 0.0001	0.820	< 0.0001
Age squared	1.011	< 0.0001	1.009	< 0.0001
BMI^a: very underweight	1.080	0.0332	1.160	0.0891
underweight	1.070		1.091
overweight	1.077		1.035
obese	1.140**		1.060
Socioeconomic status^b: high	1.099**	0.0154	1.234***	< 0.0001
medium	1.075*		1.121***
Season^c: spring	0.944	0.1102	0.935	0.0178
summer	0.270*		0.848**
autumn	0.951		0.955
Migrant^d	0.773***	< 0.0001	0.739***	< 0.0001

N = 14, 531.
Negative binomial model, random effect: sample point, dependent variable: number of pharmaceuticals.
Reference: ^anormal weight; ^blow socioeconomic status; ^cwinter; ^dnon-migrant.
^ep-value of total effect.
Significance levels for individual effect levels: *** < 0.001, ** < 0.01, * < 0.05.
BMI, body mass index.

ISSN: 1472-6963