In the three cohorts of more than 160,000 US men and women with 12–16 years of follow-up, ADM users were at a moderately increased risk of developing type 2 diabetes mellitus after adjusting for diabetes risk factors. The increased risk did not appear to differ by types of ADM (SSRIs or others). The association was in part but not completely explained by BMI
The relationship between depression and diabetes is of particular interest, since both conditions are major contributors to the global burden of chronic diseases. Several epidemiological studies have documented a bidirectional association between depression and diabetes: depression increases the risk of developing diabetes, and vice verse, diabetes is also associated with an increased risk of being depressed [23
]. However, whether antidepressant treatment could elevate diabetes risk remains controversial. Rubin et al.[8
] found in the Diabetes Prevention Program (DPP) study that ADM use (78% were SSRIs) was associated with a more than two-fold increased risk of type 2 diabetes among participants with impaired glucose tolerance who were assigned to lifestyle or placebo diabetes prevention interventions, even after controlling for depressive symptoms. However, the increased risk was not detected in participants in metformin intervention arm [8
]. Recently, two large nested case-control studies using medical record database in the UK [9
] and Finland [10
] both found an increased diabetes risk associated with long-term ADM use of moderate and/or high daily doses for depression treatment, and the association was independent of depression severity. The associations were found for both SSRIs and TCAs in these two studies [9
]. A cohort study among 1000 older Australians found that ADM use was associated with an 80% (95% CI −9%, 257%) non-significant increased risk [12
]. Campayo et al. [13
] found in a Spanish community sample of adults aged ≥55 years (n=3,521) that the HR for ADM use was 1.26 (95% CI 0.63, 2.50). Knol et al. [11
] used prescription data from the PHARMO database and did not find an increased risk in antidepressant users. However, this study lacked information on BMI and lifestyle factors, and included only patients with anti-diabetic treatment as diabetes cases. We also found that only baseline ADM use did not predict risk of type 2 diabetes, suggesting that recent ADM use might be more relevant to the elevated risk. The results concurred with Andersohn’s findings [9
] that recent ADM use was positively associated with the risk of type 2 diabetes, but not past use or former use of antidepressants.
To the best of our knowledge, the current analysis is the largest prospective cohort study investigating the association between ADM use and diabetes risk. Despite heterogeneity in study design, population characteristics and risk estimates, our findings are largely consistent with those from previous studies. The results from NHS I were somewhat weaker than those from NHS II and HPFS. Despite homogeneity in study design and target population (health professionals or nurses, mostly whites), the cohorts have considerable heterogeneity. First, the age ranges are different. The NHS I encompasses middle-aged and elderly women (50–79 years old at baseline), while NHS II consists of a group of younger women (29–46 years old at baseline). One potential reason for the null association in NHS I was that the early-onset diabetes had been excluded, and participants with severe depression were more likely to withdraw from the study during the early follow-up of the entire cohort before 1996 (1976–1996), and thus, the remaining participants in NHS I were relatively less depressed. Whether the increased risk found in NHS II but not in NHS I reflects an age-specific effects of ADM on diabetes risk remains unclear and deserves further investigation. Second, the prevalence of ADM use was substantially lower in men compared to women. This might reflect the gender difference of depression prevalence [25
], as well as the reluctance of men to seek [26
] or receive treatment [27
] compared to women. In the current study, the baseline ADM use prevalence in HPFS was 1.2% in 1990, which was consistent with the National Comorbidity Survey 1990–1992 where 1.4% of male participants reported ADM use [28
]. This prevalence climbed to 2.9% in 1996 and 7.1% in 2004 in HPFS. The prevalence of ADM use over time in our studies was consistent with several national data [1
]. Finally, the results of specific types of ADM use should be interpreted cautiously because the reasons for prescribing the specific types of ADM may be different. The prevalence of SSRIs use has increased in all three cohorts over time, which was coincident with the practice that SSRIs have became the first-line treatment for depression during the follow-up [29
]. Individuals using TCAs or multiple types were more likely to be non-responsive to the initial medication [29
Antidepressants might be associated with an increased diabetes risk through a variety of mechanisms. First, ADM use may primarily be a marker of depression severity and/or chronicity, and depression has been shown to increase risk of subsequent diabetes [23
]. ADM users might have been more severely depressed or have a history of chronic or recurrent depression. Second, ADM use was associated with poor health behaviors (i.e.
, smoking and physical inactivity) and high prevalence of major comorbidities in this study. Although we controlled for a large number of health behavior factors and other medical conditions, residual confounding is still possible. Furthermore, weight gain is a common side effect in short- and long-term treatment with TCAs [4
]. There is evidence of an initial stable weight or even weight loss with the use of SSRIs, followed by weight gain in the long-term phase [5
]. Kivimaki et al. [10
] found that ADM use (and different types) was associated with significantly more weight gain compared to non-users in a nested case-control study. The association between ADM use and diabetes was largely attenuated but remained significant even after controlling for updated BMI or weight gain in our study, which is consistent with the DPP results [8
], suggesting that other mechanisms beyond weight gain may have a role. Moreover, a mechanistic study found that some SSRIs could act as inhibitors of insulin signaling and as potential inducers of cellular insulin resistance [6
]. Different ADMs have varied binding affinities to various receptors, which may be involved in different effects on insulin secretion and action [30
]. The associations with different types of ADM, even within a certain type, have been suggested by a recent report [9
]. Therefore, future studies need to be more specific on types of ADM, beyond those of SSRIs and TCAs, and should examine more recent forms of ADM, such as serotonin-norepinephrine reuptake inhibitors.
Strengths, limitations and implications
Strengths of the current study include the large sample size, long-term follow-up, and biennially updated information on medication use, disease onset and lifestyle risk factors. Time-dependent Cox models were performed to incorporate these repeated measures, which minimized the possibility of residual and time-dependent confounding.
This study also has several limitations and the results should be interpreted with caution. First, our study populations primarily consisted of health professionals with European ancestry. Although their concern about health status and better understanding of health-related issues enhanced the reliability and validity of our questionnaire data, the generalizability to other populations may be limited. Nevertheless, it appears unlikely that the fundamental biology underlying a relation of ADM to diabetes would be different between our cohorts and the general population.
Second, the diabetes cases were self-reported, but we only included cases confirmed by the supplemental questionnaires. Moreover, information on ADM use was self-reported, and we could not assess the association between specific agents, doses and duration of drug use with diabetes risk. Furthermore, we lacked clinical data on participants’ depression history, severity and chronicity. Notably, ADM use may be a marker of depression severity and/or chronicity, and it is possible that the underlying more severe depressive disorder rather than ADM use increases risk of diabetes. We attempted to account for this by adjusting for a depressive score in women, but residual confounding may remain since this score could not capture the history and chronicity of depression, and we did not have depressive symptoms information in men. Aspecific depression symptoms measure (such as the Diagnostic Interview Schedule, Center for Epidemiologic Studies Depression Scale) may better capture the severity of depression.
Another limitation is that ADMs can be used for conditions other than depression, such as anxiety disorders, insomnia, neuropathic pain, and premenstrual syndrome and hot flushes in women. We could not distinguish different indications for ADMs in our cohorts. In a secondary analysis, we found that 79% of ADM users in HPFS reported a lifetime history of depression in 2002, and the proportion was 91% in NHS II in 2001, when questions about lifetime history of depression were asked. These data indicate that the majority of participants used ADM for treating depression or related symptoms.
In addition, surveillance bias due to the disease diagnosis is also possible in our analyses, although our participants had regular physical examinations and ready access to health care system. Finally, our results cannot prove causality, like any other observational data. Studies with post-intervention follow-up of existing randomized placebo-controlled antidepressant trials can be used to evaluate the effects on glucose homeostasis, insulin sensitivity and diabetes risk.
In conclusion, the results from the three large long-term cohort studies suggest that individuals with antidepressant treatment had a moderately increased risk of developing type 2 diabetes. This association appeared to be partly mediated through BMI, particularly in women. However, this study cannot determine whether ADM use is a causal risk factor for type 2 diabetes, or serves as a marker of depression severity/chronicity. Additional research is needed to confirm these results with more detailed information on dose and duration of treatment, and other clinical parameters. Mechanistic studies are also required to better understand the influence of antidepressants on glucose tolerance and carbohydrate metabolism. Before conclusive evidence on this relationship is obtained, patients with depression are recommended to adhere to their treatment strategies with careful attention of their body weights and blood glucose levels.