Antidepressant use has been linked to new-onset diabetes. However, the existing literature on this relationship has yielded inconsistent findings. The primary objective of this study was to systematically synthesize the literature on the relationship between antidepressant use and new-onset diabetes using meta-analysis.
A systematic literature search was conducted to identify relevant studies in seven electronic databases. Two independent reviewers identified the final list of studies to be included in the meta-analysis using a priori selection criteria. Results for the primary outcome of interest, that is, odds and hazards of developing new-onset diabetes, were pooled using a random-effects model. Egger's regression test and the Trim and Fill method were utilized to detect the presence of any potential publication bias. Sensitivity analysis was conducted using the leave-one-out method as well as individual categories of antidepressant drugs.
Eight studies met the inclusion criteria. Random effects models revealed that adults with any use of antidepressants were more likely to develop new-onset diabetes compared with those without any use of antidepressants [odd ratios = 1.50, 95% confidence interval (CI), 1.08–2.10; hazards ratio = 1.19, 95% CI, 1.08–1.32]. Sensitivity analyses revealed fair robustness; selective serotonin reuptake inhibitors and tricyclic antidepressants were more likely to be associated with the development of new-onset diabetes. Results from the Egger's regression test and Trim and Fill method revealed no evidence of publication bias.
Among adults, antidepressant use was associated with higher chances of new-onset diabetes. However, because a cause-and-effect relationship cannot be established by observational studies, future randomized controlled studies are needed to confirm this association. Copyright © 2013 John Wiley & Sons, Ltd.