SourcePsychological Medicine, 47, 6, (2017), pp. 1041-1052
Article / Letter to editor
Display more detailsDisplay less details
SubjectRadboudumc 0: Other Research RIHS: Radboud Institute for Health Sciences
BACKGROUND: Depression is associated with the metabolic syndrome (MS). We examined whether metabolic dysregulation predicted the 2-year course of clinical depression. METHOD: A total of 285 older persons (60 years) suffering from depressive disorder according to DSM-IV-TR criteria was followed up for 2 years. Severity of depression was assessed with the Inventory of Depressive Symptomatology (IDS) at 6-month intervals. Metabolic syndrome was defined according the National Cholesterol Education Programme (NCEP-ATP III). We applied logistic regression and linear mixed models adjusted for age, sex, years of education, smoking, alcohol use, physical activity, somatic co-morbidity, cognitive functioning and drug use (antidepressants, anti-inflammatory drugs) and severity of depression at baseline. RESULTS: MS predicted non-remission at 2 years (odds ratioper component = 1.26, 95% confidence interval 1.00-1.58), p = 0.047), which was driven by the waist circumference and HDL cholesterol. MS was not associated with IDS sum score. Subsequent analyses on its subscales, however, identified an association with the somatic symptom subscale score over time (interaction time x somatic subscale, p = 0.005), driven by higher waist circumference and elevated fasting glucose level. CONCLUSIONS: Metabolic dysregulation predicts a poor course of late-life depression. This finding supports the concept of 'metabolic depression', recently proposed on population-based findings of a protracted course of depressive symptoms in the presence of metabolic dysregulation. Our findings seem to be driven by abdominal obesity (as indicated by the waist circumference) and HDL cholesterol dysregulation.
This item appears in the following Collection(s)
- Academic publications 
- Faculty of Medical Sciences 
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.