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.

Wenig et al. BMC Health Services Research 2011 11:340   doi:10.1186/1472-6963-11-340