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Table 2 Number of pharmaceuticals - results of regression analysis

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

  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
BMIa: 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 statusb: high 1.099** 0.0154 1.234*** < 0.0001
   medium 1.075*   1.121***  
Seasonc: spring 0.944 0.1102 0.935 0.0178
   summer 0.270*   0.848**  
   autumn 0.951   0.955  
Migrantd 0.773*** < 0.0001 0.739*** < 0.0001
  1. N = 14, 531.
  2. Negative binomial model, random effect: sample point, dependent variable: number of pharmaceuticals.
  3. Reference: anormal weight; blow socioeconomic status; cwinter; dnon-migrant.
  4. ep-value of total effect.
  5. Significance levels for individual effect levels: *** < 0.001, ** < 0.01, * < 0.05.
  6. BMI, body mass index.