Major Depressive Disorder, Antidepressant Use, and Subsequent 2-Year Weight Change Patterns in the Netherlands Study of Depression and Anxiety

2015 ◽  
Vol 77 (02) ◽  
pp. e144-e151 ◽  
Author(s):  
Deborah Gibson-Smith ◽  
Mariska Bot ◽  
Yuri Milaneschi ◽  
Jos W. Twisk ◽  
Marjolein Visser ◽  
...  
2014 ◽  
Vol 156 ◽  
pp. 156-163 ◽  
Author(s):  
Jérôme J.J. Schuch ◽  
Annelieke M. Roest ◽  
Willem A. Nolen ◽  
Brenda W.J.H. Penninx ◽  
Peter de Jonge

PLoS ONE ◽  
2016 ◽  
Vol 11 (5) ◽  
pp. e0156624 ◽  
Author(s):  
Jordan M. Ramsey ◽  
Jason D. Cooper ◽  
Mariska Bot ◽  
Paul C. Guest ◽  
Femke Lamers ◽  
...  

2008 ◽  
Vol 65 (12) ◽  
pp. 1358 ◽  
Author(s):  
Carmilla M. M. Licht ◽  
Eco J. C. de Geus ◽  
Frans G. Zitman ◽  
Witte J. G. Hoogendijk ◽  
Richard van Dyck ◽  
...  

2013 ◽  
Vol 44 (10) ◽  
pp. 2017-2028 ◽  
Author(s):  
D. Vancampfort ◽  
C. U. Correll ◽  
M. Wampers ◽  
P. Sienaert ◽  
A. J. Mitchell ◽  
...  

BackgroundIndividuals with depression have an elevated risk of cardiovascular disease (CVD) and metabolic syndrome (MetS) is an important risk factor for CVD. We aimed to clarify the prevalence and correlates of MetS in persons with robustly defined major depressive disorder (MDD).MethodWe searched Medline, PsycINFO, EMBASE and CINAHL up until June 2013 for studies reporting MetS prevalences in individuals with MDD. Medical subject headings ‘metabolic’ OR ‘diabetes’ or ‘cardiovascular’ or ‘blood pressure’ or ‘glucose’ or ‘lipid’ AND ‘depression’ OR ‘depressive’ were used in the title, abstract or index term fields. Manual searches were conducted using reference lists from identified articles.ResultsThe initial electronic database search resulted in 91 valid hits. From candidate publications following exclusions, our search generated 18 studies with interview-defined depression (n = 5531, 38.9% male, mean age = 45.5 years). The overall proportion with MetS was 30.5% [95% confidence interval (CI) 26.3–35.1] using any standardized MetS criteria. Compared with age- and gender-matched control groups, individuals with MDD had a higher MetS prevalence [odds ratio (OR) 1.54, 95% CI 1.21–1.97, p = 0.001]. They also had a higher risk for hyperglycemia (OR 1.33, 95% CI 1.03–1.73, p = 0.03) and hypertriglyceridemia (OR 1.17, 95% CI 1.04–1.30, p = 0.008). Antipsychotic use (p < 0.05) significantly explained higher MetS prevalence estimates in MDD. Differences in MetS prevalences were not moderated by age, gender, geographical area, smoking, antidepressant use, presence of psychiatric co-morbidity, and median year of data collection.ConclusionsThe present findings strongly indicate that persons with MDD are a high-risk group for MetS and related cardiovascular morbidity and mortality. MetS risk may be highest in those prescribed antipsychotics.


1989 ◽  
Vol 25 (7) ◽  
pp. A150-A151
Author(s):  
Timothy Hsu ◽  
James E. Shipley ◽  
John F. Greden ◽  
Alan S. Eiser ◽  
Alan B. Douglass ◽  
...  

Author(s):  
Damien Etchecopar-Etchart ◽  
Theo Korchia ◽  
Anderson Loundou ◽  
Pierre-Michel Llorca ◽  
Pascal Auquier ◽  
...  

Abstract Comorbid major depressive disorder (MDD) in schizophrenia (SZ; SZ-MDD) has been identified as a major prognostic factor. However, the prevalence and associated factors of SZ-MDD have never been explored in a meta-analysis. All studies assessing the prevalence of SZ-MDD in stabilized outpatients with a standardized scale or with structured interviews were included. The Medline, Web of Science, PsycINFO, and Google Scholar databases were searched. Using random effects models, we calculated the pooled estimate of the prevalence of SZ-MDD. We used meta-regression and subgroup analyses to evaluate the potential moderators of the prevalence estimates, and we used the leave-one-out method for sensitivity analyses. Of the 5633 potentially eligible studies identified, 18 studies (n = 6140 SZ stabilized outpatients) were retrieved in the systematic review and included in the meta-analysis. The pooled estimate of the prevalence of SZ-MDD was 32.6% (95% CI: 27.9–37.6); there was high heterogeneity (I2 = 92.6%), and Egger’s test did not reveal publication bias (P = .122). The following factors were found to be sources of heterogeneity: publication in or after 2015, the inclusion of patients from larger studies, the assessment tools, the inclusion of patients with substance use disorder or somatic chronic diseases, age, education level, the lifetime number of hospitalizations, and antidepressant use. Two-thirds of the extracted variables could not be explored due to an insufficient amount of published data. The prevalence of MDD is high among SZ individuals. Healthcare providers and public health officials should have an increased awareness of the burden of SZ-MDD.


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