There is a strong and robust association between depression and incidence of type 2 diabetes, but only a weak relation between diabetes and risk of depression. Early retrospective studies had suggested that the relationship between depression and diabetes was bi-directional, but prospective analyses were necessary to understand its natural history. In contrast to the reports of depression predicting diabetes, there was no evidence of heterogeneity or moderation of effect among the studies of diabetes predicting depression. Diabetes is a serious metabolic disorder that has life-changing consequences for individuals affected by it. Depression is a complex condition characterized by disruptions in all facets of life—social, psychological, behavioral, and biological. The finding that depression is associated with a 60% increase in risk of developing type 2 diabetes rivals other known risk factors for this disease, such as smoking (31
). Our findings suggest that there is only a modest association between diabetes and incidence of depression, but it is an understudied phenomenon, and it may be that competing risks for late-life depression (i.e., macrovascular disease, functional/cognitive decline) mask this relationship. Depression is also difficult to detect in older adults (32
), and thus measurement error may partially explain why this association is so modest. The subgroup analyses suggest this relationship may vary by age and sex, and studies should focus on identifying groups in which this association is particularly robust to target prevention efforts.
Risk factor epidemiology can inform prioritization of prevention efforts through the notion of population-attributable risk (33
). The population-attributable risk describes the magnitude of reduction in a given outcome expected if the effect of the risk factor were eliminated, assuming the risk factor is a necessary cause of the outcome. It is a function of the strength of the association and the prevalence of the risk factor. For example, atypical antipsychotic medications are associated with ~30% increased risk of type 2 diabetes (15
), but use of these agents is rare in the general population (prevalence <1%), and thus the associated population-attributable risk is on the order of 0.5%. In contrast, the risk for diabetes associated with depression reported above coupled with a prevalence of 16% (2
) is associated with a population-attributable risk of 9% because depression is much more common.
This analysis has strengths and limitations. The primary strengths are the expansive literature search and the explicit assessment of the bi-directionality of the depression-diabetes relationship, which previous reviews have not systematically evaluated. We also conducted sensitivity analyses to assess the robustness of our findings. The primary limitation stems from the quality of the included studies. There was evidence of heterogeneity and potential publication bias among the studies of depression predicting diabetes, and while we conducted a relatively broad search, by limiting it to only one database, we may have missed some reports. However, inclusion of the hypothetical missing negative studies still resulted in a statistically significant, albeit attenuated, pooled estimate of elevated risk of diabetes. Importantly, even this attenuated risk estimate was of greater magnitude than the pooled risk estimate of diabetes predicting depression. While we attempted to generate the total effect of the depression-diabetes relationship by selecting estimates adjusted primarily for demographic characteristics, adjustment for confounders varied, and thus our pooled analyses only approximate the total effect. We did not examine the role of diabetes complications in this analysis, although there is compelling evidence that depression is associated with poorer glycemic control (34
) and increased risk of complications (35
Research should move from epidemiologic investigations that have established this association and begin the process of empirically testing causal hypotheses. Many aspects of this relationship—most notably, whether treating depression lowers the increased risk of diabetes—have yet to be examined in a controlled manner, although there is suggestive evidence that antidepressant use is associated with elevated, not lowered, risk of diabetes, possibly an example of confounding by indication (36
). The studies reviewed here demonstrate the importance of early detection of depression and the important role of primary care physicians in careful monitoring of the physiological consequences and correlates of psychiatric disorders.