Analyses of data drawn from a cohort of >150,000 adults revealed a series of important results. First, antidepressant medication use, as indicated by completed prescriptions exceeding 200 defined daily doses, was associated with a doubling of the risk of diagnosed type 2 diabetes, irrespective of a record of severe depression. The excess risk associated with antidepressants was observable for both SSRIs and tricyclic antidepressants. Second, in absolute terms, the 5-year risk of diagnosed diabetes increased in a dose-response fashion, depending on the level of exposure to antidepressant medication: 1.1% in nonusers, 1.7% among those treated with 200–399 daily defined doses 1 year, and 2.3% among those using ≥400 doses. Third, supporting biological plausibility of this association, weight gain was more rapid among long-term antidepressant users than in nonusers matched for depression-related characteristics.
Our findings add to the existing evidence from recent studies. In the randomized Diabetes Prevention Program of prediabetic individuals, use of antidepressants at baseline was associated with an increased risk of type 2 diabetes at follow-up, whereas self-reported depressive symptoms at baseline were not predictive of subsequent diabetes risk (9
). An analysis of medical records of depressive patients from the U.K. General Practice Research Database found that long-term use of antidepressants with high or moderate daily doses was associated with increased risk of diabetes, but treatment with lower daily doses was not (10
). In the present study, the number of antidepressant users was 6 times higher than that in these two studies together, and we targeted a nonclinical occupational cohort including groups that were not covered by those studies, also took into account dose and duration of antidepressant use as well as baseline status of severe depression, and demonstrated a plausible mediating mechanism.
Other studies in the field have reported inconsistent findings. A Norwegian cross-sectional health survey (11
), a study of spontaneous reports listed in the WHO Adverse Drug Reaction Database (12
), and an analysis of data from one province in Canada (13
) all found support for an association between antidepressant use and diabetes. In a community sample of adults aged ≤55 years, treatment with antidepressants was not associated with an increased risk of diabetes, but the study lacked adequate statistical power because the number of antidepressant users who developed diabetes was only four (17
). Analyses using prescription data from the PHARMO database from the Netherlands did not find an increased risk of diabetes among antidepressant users (18
). However, that study did not consider the duration or the dose of antidepressant treatment. Our findings and other studies (10
) suggest that inclusion of short-term/low-dose treatments in the definition of antidepressant use is likely to dilute the association. In the present study, exposure to <200 defined daily doses of antidepressants was not associated with diabetes risk.
Weight gain, both in relative and absolute terms, was greater among antidepressant users than among their control subjects matched for depression status using recorded and self-reported information on depression and related traits. A previous trajectory analysis of repeat BMI measurements found on average a 0.03 unit faster annual increase in BMI among individuals who later developed type 2 diabetes compared with those who remained disease-free (19
). This translates to ~0.1 kg excess weight gain per year for incident diabetes case subjects. With use of that metric, our findings suggest that antidepressant medication use is related to ~0.3 kg excess yearly weight gain, a change clearly large enough to contribute to diabetes risk. Our findings are in agreement with previous studies confirming that tricyclic antidepressants may induce weight gain and promote hyperglycemia (20
) and showing that SSRI use, despite being related to stable weight or even weight loss in the short term, is associated with an increased risk of weight gain in the longer term (22
In the weight gain study reported herein, we undertook a sensitivity analysis based on a subgroup of incident antidepressant medication users who started treatment between baseline and follow-up weight measurements, excluding all prevalent antidepressant users. This exclusion affected little estimated significant weight gain associated with SSRIs but showed even a greater weight gain in relation to tricyclic antidepressant treatment. Because weight gain is a recognized side effect of tricyclic antidepressants, the main analysis may include an underrepresentation of patients who did not tolerate antidepressant treatment well (the depletion of susceptibility bias), contributing to an underestimation of the weight gain associated with tricyclic antidepressant treatment.
Strengths and limitations
Information on the daily dose of antidepressant medication, based on WHO definitions of average maintenance dose, is an advantage because it enabled determination of the level of exposure to these drugs. Use of records of completed antidepressant prescriptions is also a specific strength, because previous studies have typically relied on information on prescriptions irrespective of whether the patient actually filled them. Our data on antidepressants, being based on physician-prescribed medication that was then purchased by the user from a pharmacy, are likely to be more accurate, although we cannot ascertain the extent to which the medication purchased was actually taken. In this study, comprehensive records on medications and diagnoses of depression and diabetes from national registers unusually covered the entire cohort during the entire follow-up period. Thus, biases related to sample attrition were avoided.
Several limitations to this study are noteworthy. First, the assessment of type 2 diabetes and depression with records from national health registers does not capture nondiagnosed or nontreated diabetes or depression, introducing a source of misclassification. However, an association of antidepressant use and incident diabetes, similar to that found in the present study, has previously been confirmed in a study with glucose-based assessment of incident type 2 diabetes (9
), which will capture case subjects with nondiagnosed and nontreated diabetes.
Second, we assessed weight change using self-reports. Although self-reported weights are correlated with objective weight measurements, there are errors in self-reports that are systematic instead of random, reflecting both roundings to the nearest point of heaping and a tendency to report weights closer to ideal weight. In the present study, the weight change calculated by deducting self-reported weight at follow-up from that at baseline may therefore have, if anything, underestimated large weight changes. The influence of antidepressant use on the accuracy of self-reporting is not known; such impacts could potentially introduce some bias to our results.
Third, other mechanisms beyond weight gain, such as the hyperglycemic effects of noradrenergic activity of antidepressants, may have a role in the increased diabetes risk associated with antidepressants. Further research is therefore needed to examine the entire pathway from antidepressant use to subsequent physical and biochemical changes, including weight gain and the onset of type 2 diabetes. Given that diabetogenic effects are likely to vary depending on a drug's chemical substance, antidepressant-specific analyses, beyond those of SSRIs and tricyclic medication, would be important and should cover, for example, the increasingly popular serotonin-norepinephrine reuptake inhibitors.
Fourth, the possibility of residual or unmeasured confounding cannot be excluded in epidemiological studies such as ours. The fact that the association between antidepressant use and diabetes was similar in severely depressive patients and the remaining study members suggests that the observed association was not driven by confounding factors strongly related to depression. Likewise, the association of antidepressant use and weight gain was robust to matching for 16 depression-related characteristics, such as GHQ-12 caseness, a correlate of clinical depression (23
Fifth, observational data cannot prove causality. We therefore recommend confirmatory studies, such as postintervention follow-ups for existing antidepressant trials for assessment of diabetes risk in randomized data.
Potential diabetes risk is currently not taken into consideration in clinical guidelines for treating depression (8
). We observed a substantially increased relative and modestly increased absolute risk of type 2 diabetes associated with continuing antidepressant medication use. If this risk reflects a causal effect, then it should be incorporated into clinical decision making in recurrent depression because diabetes is a serious disease with potentially fatal complications.