Diabetes increases the risk of depression: A systematic review, meta-analysis and estimates of population attributable fractions based on prospective studies

Abstract

We aim to examine the relationship between diabetes and depression risk in longitudinal cohort studies and by how much the incidence of depression in a population would be reduced if diabetes was reduced. Medline/PubMed, EMBASE, PsycINFO, and Cochrane Library databases were searched for English-language published literature from January 1990 to December 2017. Longitudinal studies with criteria for depression and self-report doctors' diagnoses or diagnostic blood test measurement of diabetes were assessed. Systematic review with meta-analysis synthesized the results. Study quality, heterogeneity, and publication bias were examined. Pooled odds ratios were calculated using random effects models. Population attributable fractions (PAFs) were used to estimate potential preventive impact. Twenty high-quality articles met inclusion criteria and were analyzed. The pooled odds ratio (OR) between diabetes and depression was 1.33 (95% CI, 1.18–1.51). For the various study types the ORs were as follows: prospective studies (OR 1.34, 95% CI 1.14–1.57); retrospective studies (OR 1.30, 95% CI 1.05–1.62); self-reported diagnosis of diabetes (OR 1.37, 95% CI 1.17–1.60); and diagnostic diabetes blood test (OR 1.25, 95% CI 1.04–1.52). PAFs suggest that over 9.5 million of global depression cases are potentially attributable to diabetes. A 10–25% reduction in diabetes could potentially prevent 930,000 to 2.34 million depression cases worldwide. Our systematic review provides fairly robust evidence to support the hypothesis that diabetes is an independent risk factor for depression while also acknowledging the impact of risk factor reduction, study design and diagnostic measurement of exposure which may inform preventive interventions. Keywords: Epidemiology, Diabetes, Depression, Systematic review, Meta-analysis, Population attributable fractions, Projected effects