Population-based cohort analyses of the bidirectional relationship between type 2 diabetes and depression

  • Chen P
  • Chan Y
  • Chen H
 et al. 
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Abstract

OBJECTIVE: This study addresses the strength of association for the bidirectional relationship between type 2 diabetes and depression.

RESEARCH DESIGN AND METHODS: We used two cohort studies with the same source of database to determine the link between depression and type 2 diabetes. The data analyzed included a random sample of 1 million beneficiaries selected from the National Health Insurance claims in 2000. The analysis of diabetes predicting the depression onset consisted of 16,957 diabetic patients and the same number of sex- and age-matched nondiabetic control subjects. The analysis of depression predicting diabetes onset included 5,847 depressive patients and 5,847 sex- and age-matched nondepressive control subjects. The follow-up period was between 2000 and 2006, and onset of end points was identified from ambulatory care claims. The Cox proportional hazards regression model adjusted for potential confounders was used to estimate relative hazards.

RESULTS: The first cohort analysis noted an incidence density (ID) of 7.03 per 1,000 person-years (PY) and 5.04 per 1,000 PY for depression in diabetic and nondiabetic subjects, respectively, representing a covariate-adjusted hazard ratio (HR) of 1.43 (95% CI 1.16-1.77). The second cohort analysis noted an ID of 27.59 per 1,000 PY and 9.22 per 1,000 PY for diabetes in depressive and nondepressive subjects, respectively. The covariate-adjusted HR was stronger at 2.02 (1.80-2.27) for incident diabetes associated with baseline depression.

CONCLUSIONS: The two cohort studies provided evidence for the bidirectional relationship between diabetes and depression, with a stronger association noted for the depression predicting onset of diabetes.

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