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Table 3 Multivariate analysis: variables independently associated with the dichotomized AD prescription ratio (<0.42 for lower prescribers and ≥0.42 for higher prescribers)

From: How do GP practices and patient characteristics influence the prescription of antidepressants? A cross-sectional study

Variable Mean difference in AD prescription ratio [95% CI] b OR [95% CI] c
GP’s age   
60 0 1
 50–59 0.026 [−0.023; 0.074] 1.87 [1.29; 2.71]
 40–49 0.038 [−0.049; 0.080] 1.74 [1.14; 2.64]
 <40 −0.068 [−0.14; 0.00] 0.65 [0.35; 1.2]
Practice location:   
 Rural 0 1
 Urban 0.056 [0.016; 0.096] 1.954 [1.3; −2.80]
Number of consultations/year/GP*   0.93a [0.90–0.97]
Number of patients with low income   
 ≥80   1
 40–79   1.69 [1.06; 2.67]
 <39   2.23 [1.45; 3.40]
Class of prescription   
 <70% new ADs 0 1
 >70% new ADs 0.12 [0.058; 0.18] 3.45 [1.94; 6.15]
Cumulative number of sick leave days prescribed per year   
6,000   1
 4,000–5,999   0.91 [0.55; 1.47]
 2,000–3,999   1.12 [0.68; 1.84]
 Fewer than 1,999   0.43 [0.24; 0.78]
Total volume of drugs reimbursed −0.0053* [−0.0084; −0.00233]  
Total volume of prescription orders 0.0462** [0.0184; 0.0740]  
Number of consultations and home visits −0.0128*** [−0.0179; −0.0077]  
  1. *Mean difference per 1,000 additional drugs reimbursed (quantitative variable).
  2. **Mean difference per 1,000 additional prescription orders (quantitative variable).
  3. ***Mean difference per 100 additional consultations or home visits.
  4. aOdds ratio per 100 additional consultations (quantitative variable).
  5. bFrom multiple linear regression applied to the AD prescription ratio as a continuous variable.
  6. cFrom multiple logistic regression applied to the dichotomized AD prescription ratio using the lower prescription level as the reference level.