PUB - Publikationen an der Universität Bielefeld

Background Patients with depression and comorbid obesity may be more prone to weight modulating and cardiovascular side effects of selected antidepressants (AD). It is important to ascertain whether these AD prescriptions differ by patient weight status. Methods Canadian Primary Care Sentinel Surveillance Network (CPCSSN) electronic medical records were used. Participants were adults with depression prescribed an AD in 2000–2016, with weight categories established before the first prescription. Logistic regression and mixed effects models were applied to examine associations between obesity and AD prescribing, adjusted for sex, age, and comorbidities. Machine learning algorithm random forest (RF) was used to evaluate the importance of weight in predicting prescribing patterns. Results Of 26,571 participants, 72.4% were women, mean age was 38.9 years (standard deviation (SD)=14.2) and mean BMI 27.0 kg/m2 (SD = 6.5); 9.5% had ≥ 1 comorbidity. Patients with obesity, compared to normal weight patients, were more likely to receive bupropion (adjusted odds ratio (aOR) 1.24, 95%CI: 1.09,1.42), fluoxetine (aOR 1.14, 95%CI: 0.97,1.34), and amitriptyline (aOR 1.13, 95%CI: 0.93,1.36), and less likely to receive mirtazapine (aOR 0.55, 95%CI: 0.44,0.68) and escitalopram (aOR 0.88, 95%CI: 0.80, 0.97). RF analysis showed that weight was among the most important predictors of prescribing patterns, equivalent to age and more important than sex. Conclusions AD prescribing patterns for patients with obesity appear to be different for selected AD types, including AD known for their weight-modulating and cardiovascular side effects. Longitudinal studies are needed to examine whether these prescribing patterns are associated with significant health outcomes.