Antidepressant use and glycemic control

Alcohol Consumption Is a Coping Mechanism for Male Patients with Severe Anxiety Disorders Treated with Antidepressants Monotherapy

Background: Anxiety disorders are prevalent mental health conditions often accompanied by various comorbidities. The association between anxiety and liver disease, as well as fluctuations in blood sugar levels, highlights the importance of carefully evaluating patients with anxiety undergoing antidepressant therapy. The aim of this study was to conduct a comparative assessment of liver function and blood glucose levels in patients diagnosed with anxiety disorders while considering potential gender-specific differences. Methods: An analysis was conducted over a 24-month period. This study included 88 patients diagnosed with anxiety disorders, with symptoms severe enough to require hospitalization, aged 18 or older, undergoing antidepressant monotherapy, without any additional pathologies. Liver enzymes (AST, ALT, GGT), AST/ALT ratio, and blood glucose levels were measured and compared. Results: While no significant differences were found between antidepressant classes, increased GGT levels were observed in men older than 40 years compared to women of the same age, suggesting that alcohol consumption may be a coping mechanism for anxiety. This gender difference was not observed among young patients. Conclusions: Early detection of alcohol consumption is essential in patients with anxiety disorders in order to prevent alcohol-related liver damage and to adjust the management of both conditions accordingly.

Increased Levels of HbA1c in Individuals with Type 2 Diabetes and Depression: A Meta-Analysis of 34 Studies with 68,398 Participants

Glycosylated hemoglobin is used to diagnose type 2 diabetes mellitus and assess metabolic control. Depression itself has been associated with high levels of HbA1c in individuals with T2DM. The association between diabetes and depression suggests the usefulness of determining HbA1c as a biological marker of depressive symptoms. The aim of this study was to determine HbA1c levels in individuals with T2DM with vs. without depression. Additionally, we analyzed the influence of pharmacological treatments, time of evolution, and complications of disease. We performed a literature search in different databases published up to January 2020. A total of 34 articles were included. Our results showed that individuals with T2DM with depression showed increased levels of HbA1c in comparison to individuals with T2DM without depression (d = 0.18, 95% CI: 0.12−0.29, p(Z) < 0.001; I2 = 85.00). We also found that HbA1c levels remained elevated in individuals with T2DM with depression who were taking hypoglycemic drugs (d = 0.20 95% CI: 0.11−0.30, p(Z) < 0.001; I2 = 86.80), in individuals with less than 10 years of evolution (d = 0.17 95% CI: 0.09−0.26, p(Z) = 0.001; I2 = 66.03) and in individuals with complications of the disease (d = 0.17, 95% CI: 0.07−0.26, p(Z) < 0.001; I2 = 58.41). Our results show that HbA1c levels in individuals with T2DM with depression are significantly increased compared to controls with T2DM without depression. Additionally, these levels remained elevated in individuals who were taking hypoglycemic drugs, those with less than 10 years of disease evolution, and those with complications related to diabetes. It is necessary to examine the existence of a diabetes−HbA1c−depression connection.

A Within-Subject Before-After Study of the Impact of Antidepressants on Hemoglobin A1c and Low-Density Lipoprotein Levels in Type 2 Diabetes

PURPOSE/BACKGROUND

Data on the effect of treatment with antidepressant drugs on metabolic control in diabetes are sparse. In this controlled within-subject before-after study, the impact of initiation and discontinuation of antidepressant treatment on hemoglobin A1c (HbA1c) and low-density lipoprotein (LDL) levels in type 2 diabetes was estimated.

METHODS/PROCEDURES

All individuals with newly developed type 2 diabetes (first HbA1c ≥ 6.5%) between 2000 and 2016 in Northern and Central Denmark were identified using register-based health care data. Among these, we identified individuals initiating and discontinuing antidepressant treatment. Using a within-subject before-after design, we examined HbA1c and LDL in the 16 months leading up to and the 16 months after antidepressant treatment initiation or discontinuation, respectively. For comparison, we ran similar time trend analyses in a reference population of age- and sex-matched type 2 diabetes individuals not receiving antidepressant treatment.

FINDINGS/RESULTS

Mean HbA1c decreased after initiation of antidepressant treatment (-0.16%; 95% confidence interval [CI], -0.18 to -0.13%). In the reference population, no material change in HbA1c over time (-0.03%; 95% CI, -0.04 to -0.01%) was seen. Mean LDL decreased not only in antidepressant initiators (-0.17 mmol/L; 95% CI, -0.19 to -0.15 mmol/L) but also in the reference population (-0.15 mmol/L; 95% CI, -0.16 to -0.13 mmol/L). Among antidepressant discontinuers, there was also a decrease in HbA1c (-0.32%; 95% CI, -0.37 to -0.28%), with no change in the reference population (-0.02%; 95% CI, -0.04 to 0.00%). Decreases in LDL were found both in antidepressant discontinuers (-0.09 mmol/L; 95% CI, -0.14 to -0.04 mmol/L) and in the reference population (-0.16 mmol/L0; 95% CI, -0.18 to -0.13 mmol/L).

IMPLICATIONS/CONCLUSIONS

Antidepressant treatment in type 2 diabetes may have a beneficial effect on glycemic control, as the decrease in HbA1c after discontinuation of antidepressants likely reflects remission of depression. Conversely, antidepressant treatment does not seem to affect LDL levels.

Genetic Overlap Between Type 2 Diabetes and Depression in a Sri Lankan Population Twin Sample

OBJECTIVE

Results from twin studies examining the genetic overlap between type 2 diabetes and depression are currently inconclusive. This question has not been addressed in non-Western populations. We aimed to examine whether there are common genetic factors between type 2 diabetes and depression in a Sri Lankan population using genetic model-fitting analysis.

METHOD

The Colombo Twin and Singleton Study-Phase 2 consists of 2019 singletons, and 842 monozygotic and 578 dizygotic twin pairs. The primary outcomes were self-reported type 2 diabetes diagnosis and Beck Depression Inventory scores. Standard bivariate twin models were fitted to estimate the genetic and environmental (co)variance of type 2 diabetes and depression.

RESULTS

In the best-fitting model, the phenotypic correlation between type 2 diabetes and depression was significant in female individuals only (r = 0.15 [0.08-0.21]). This association was primarily attributed to a significant genetic correlation between the traits (rA = 0.53 [0.19-0.98]).

CONCLUSIONS

In female individuals, but not male individuals, we found a significant genetic overlap between type 2 diabetes and depression in the context of a modest phenotypic correlation.

The association between antidepressant use and hemoglobin A1C in older adults

Depression is known to increase diabetes risk and worsen glycemic control in older adults, who already experience high rates of diabetes. The independent impact of antidepressants on glucose control is less clear. Data was drawn from the Health and Retirement Study, a large nationally-representative longitudinal study of retired individuals. Crude and adjusted linear models stratified by diabetes status were used to examine the cross-sectional associations between antidepressant use categorized by subclass and continuous hemoglobin A1C. The sample included 1,153 individuals, most over the age of 70. Antidepressant use was not associated with hemoglobin A1C in any model whether stratified or in the total combined sample. Antidepressants as a class were also not associated with hemoglobin A1C. These findings add to the literature suggesting that antidepressants are not associated with diabetes risk or glycemic control. Prospective studies with larger sample sizes are needed to confirm this finding.

Use of antidepressant medications not associated with A1C among individuals with diabetes in NHANES sample

INTRODUCTION

Studies on the relationships between antidepressant medications and A1C, a measure of glucose levels over the past three months, have resulted in mixed findings. Most available research examined subclass effects. The current study aims to measure the association between individual antidepressant medications and A1C in a large nationally-representative dataset.

METHODS

The sample of this study consists of 45,786 individuals who participated in the National Health and Nutrition Examination Survey between 1999 and 2012. We examined the relationships between 18 antidepressant medications and continuous A1C in crude and adjusted linear models stratified by diabetes status (ever or never diagnosed). Adjusted models included demographic covariates (age, gender, race/ethnicity, and education), smoking status, and physical activity.

RESULTS

No significant associations were found for most antidepressants. However, those who used selegiline (n=11), all of whom were in the no diabetes stratum, were found to have a higher A1C compared with individuals who do not use antidepressants.

DISCUSSION

The study agrees with a number of earlier findings. Most antidepressant medications do not appear to be associated with A1C levels among individuals with or without diabetes. Limitations include small numbers for some exposure categories and cross-sectional data. Strengths include use of a nationally-representative dataset and large total sample size.

Diabetes mellitus in people with schizophrenia, bipolar disorder and major depressive disorder: a systematic review and large scale meta-analysis

Type 2 diabetes mellitus (T2DM) is highly predictive of cardiovascular diseases and can have particularly deleterious health impacts in people with severe mental illness (SMI), i.e. schizophrenia, bipolar disorder or major depressive disorder. This meta-analysis aimed: a) to describe pooled frequencies of T2DM in people with SMI; b) to analyze the influence of demographic, illness and treatment variables as well as T2DM assessment methods; and c) to describe T2DM prevalence in studies directly comparing persons with each specific SMI diagnosis to general population samples. The trim and fill adjusted pooled T2DM prevalence among 438,245 people with SMI was 11.3% (95% CI: 10.0%-12.6%). In antipsychotic-naïve participants, the prevalence of T2DM was 2.9% (95% CI: 1.7%-4.8%). There were no significant diagnostic subgroup differences. A comparative meta-analysis established that multi-episode persons with SMI (N=133,470) were significantly more likely to have T2DM than matched controls (N=5,622,664): relative risk, RR=1.85, 95% CI: 1.45-2.37, p<0.001. The T2DM prevalence was consistently elevated in each of the three major diagnostic subgroups compared to matched controls. Higher T2DM prevalences were observed in women with SMI compared to men (RR=1.43, 95% CI: 1.20-1.69, p<0.001). Multi-episode (versus first-episode) status was the only significant predictor for T2DM in a multivariable meta-regression analysis (r(2) =0.52, p<0.001). The T2DM prevalence was higher in patients prescribed antipsychotics, except for aripriprazole and amisulpride. Routine screening and multidisciplinary management of T2DM is needed. T2DM risks of individual antipsychotic medications should be considered when making treatment choices.

Type 2 Diabetes Among People With Posttraumatic Stress Disorder: Systematic Review and Meta-Analysis

OBJECTIVE

To clarify the prevalence and predictors of Type 2 diabetes mellitus (T2DM) in people with posttraumatic stress disorder (PTSD) and where possible compare this to healthy controls.

METHODS

We searched major electronic databases until May 2015 for studies reporting T2DM prevalence in people with PTSD. Two independent authors extracted data and completed methodological quality appraisal. A random-effects meta-analysis was used.

RESULTS

From 1171 candidate publications after exclusions, nine publications were included (n = 23,396; 28.6% male; mean age = 35-60 years). The overall prevalence of T2DM was 10.0% (95% confidence interval [CI] = 8.1%-12.0%). Subgroup analysis demonstrated that war veterans experience higher prevalence of T2DM (16.3%; 95% CI = 5.2%-31.8%; n studies = 3, n = 473) compared with mixed samples (11.8%; 95% CI = 6.34-18.7, p < .001; n studies = 4, n = 2753). Increasing age (β = 0.0593, 95% CI = 0.010-0.109, z = 2.34, p = .019), median year of publication (β = -0.08, 95% CI = -0.14 to -0.03, z = -3.09, p = .002), and a lower percentage of white participants (β = -3.21, 95% CI = -5.12 to -1.29, z = -2.28, p = .001) predicted prevalence of T2DM. A relative risk meta-analysis comparing controls (n = 125,723) against those with PTSD (n = 23,203) demonstrated a significantly increased risk of T2DM (n studies = 5, relative risk = 1.49, 95% CI = 1.17-1.89, p = .001).

CONCLUSIONS

People with PTSD are at a high risk for developing T2DM. The current findings should, however, be interpreted with caution because most studies were based on self-report data.

The association between antidepressant use and glycemic control in the Southern Community Cohort Study (SCCS)

INTRODUCTION

Among people with diabetes, comorbid depression has been associated with suboptimal health outcomes. However, the independent impact of antidepressant use on glycemic control (A1C) has not been well understood.

RESEARCH DESIGN AND METHODS

The Southern Community Cohort Study collected self-reported antidepressant use and measured continuous A1C in a sample of racially diverse adults with and without diabetes who visited community health clinics serving low-income families in the southeastern United States (N=2445). Crude and adjusted linear regression models were used to examine the relationships between using specific antidepressant subclasses and continuous A1C.

RESULTS

Although use of any single antidepressant subclass was not a significant predictor of A1C level, there was a significant association between using multiple antidepressant subclasses and higher A1C, specifically among individuals with diabetes (standardized effect size=.12, p=.04).

CONCLUSION

Among adults with diabetes, the use of multiple antidepressant subclasses may be a risk factor for suboptimal glycemic control. Prospective studies are needed to confirm the direction of this observation, as the present study was limited by a cross-sectional design and small sample size.

The association of antidepressant medications and diabetic retinopathy among people with diabetes

OBJECTIVE

To determine if the use of antidepressants was associated with lower odds of diabetic retinopathy and if so, to determine if this association was mediated by decreased inflammation as measured by C-reactive protein (CRP).

DESIGN

This was a cross sectional study of 1,041 participants with type 2 diabetes 40-85years old from the 2005-2008 National Health and Nutrition Examination Survey (NHANES). Multiple logistic regression was used to examine the association between the outcome of diabetic retinopathy and the primary exposure of antidepressant medication usage. We also determined whether CRP meets standard criteria as a mediator between antidepressant use and diabetic retinopathy.

RESULTS

Participants using antidepressants were less likely to have diabetic retinopathy (OR 0.50, 95% CI: 0.31-0.82). CRP did not meet one of the criteria for mediation. However, CRP was an effect modifier such that the association of antidepressant use and diabetic retinopathy was only present among participants with CRP ≥0.3mg/dl. Among the antidepressant drug classes, selective serotonin reuptake inhibitor (SSRI) users had significantly lower odds of developing diabetic retinopathy compared to non-users of antidepressants.

CONCLUSIONS

Using representative survey data of US adults with type-2 diabetes, this study found that antidepressant use was associated with lower odds of diabetic retinopathy. Further longitudinal and experimental studies are necessary to confirm this finding and to determine if there is a role for antidepressants in preventing diabetic retinopathy in select patient populations.

TYPE 2 DIABETES IN PATIENTS WITH MAJOR DEPRESSIVE DISORDER: A META-ANALYSIS OF PREVALENCE ESTIMATES AND PREDICTORS

BACKGROUND

Patients with depression may be at increased risk of type 2 diabetes mellitus (T2DM), which is a risk factor for cardiovascular diseases and premature mortality. We aimed to clarify the prevalence and predictors of T2DM in patients with major depressive disorder (MDD) and where possible compare the prevalence of T2DM in those with MDD versus general population controls.

METHODS

We searched major electronic databases until December 2014 for studies reporting T2DM prevalence in patients with MDD. Two independent authors extracted data and completed methodological quality appraisal in accordance with the meta-analysis of observational studies in epidemiology (MOOSE) guidelines. A random effects meta-analysis was utilized.

RESULTS

The initial electronic database search resulted in 145 valid hits and 16 publications with clearly defined MDD (n = 15,8834; 31% male; mean age = 39-78 years) met the eligibility criteria. The overall prevalence of T2DM was 8.7% (95% confidence interval [CI] = 7.3-10.2%). Mean age of the MDD sample predicted a higher prevalence of T2DM (β = 0.0411; 95% CI = 0.0032-0.079, P = .03; R² = .22). A comparative meta-analysis revealed people with MDD (n = 154,366) had a higher risk of T2DM versus general controls (n = 2,098,063; relative risk [RR] = 1.49; 95% CI = 1.29-1.72; P < 0.001, N = 10). The RR (N = 3) focusing on age- and gender-matched general population controls (n = 103,555) was 1.36 (95% CI = 1.28-1.44; P < 0.001, n [MDD] = 10,895).

CONCLUSIONS

T2DM is significantly more common in people with MDD compared with the general population. The current meta-analysis indicates that action is needed in order to curb the diabetes epidemic in this high-risk population.

Risk of metabolic syndrome and its components in people with schizophrenia and related psychotic disorders, bipolar disorder and major depressive disorder: a systematic review and meta-analysis

Metabolic syndrome (MetS) and its components are highly predictive of cardiovascular diseases. The primary aim of this systematic review and meta-analysis was to assess the prevalence of MetS and its components in people with schizophrenia and related psychotic disorders, bipolar disorder and major depressive disorder, comparing subjects with different disorders and taking into account demographic variables and psychotropic medication use. The secondary aim was to compare the MetS prevalence in persons with any of the selected disorders versus matched general population controls. The pooled MetS prevalence in people with severe mental illness was 32.6% (95% CI: 30.8%-34.4%; N = 198; n = 52,678). Relative risk meta-analyses established that there was no significant difference in MetS prevalence in studies directly comparing schizophrenia versus bipolar disorder, and in those directly comparing bipolar disorder versus major depressive disorder. Only two studies directly compared people with schizophrenia and major depressive disorder, precluding meta-analytic calculations. Older age and a higher body mass index were significant moderators in the final demographic regression model (z = -3.6, p = 0.0003, r(2)  = 0.19). People treated with all individual antipsychotic medications had a significantly (p<0.001) higher MetS risk compared to antipsychotic-naïve participants. MetS risk was significantly higher with clozapine and olanzapine (except vs. clozapine) than other antipsychotics, and significantly lower with aripiprazole than other antipsychotics (except vs. amisulpride). Compared with matched general population controls, people with severe mental illness had a significantly increased risk for MetS (RR = 1.58; 95% CI: 1.35-1.86; p<0.001) and all its components, except for hypertension (p = 0.07). These data suggest that the risk for MetS is similarly elevated in the diagnostic subgroups of severe mental illness. Routine screening and multidisciplinary management of medical and behavioral conditions is needed in these patients. Risks of individual antipsychotics should be considered when making treatment choices.

Major Depressive Disorder and Bipolar Disorder Predispose Youth to Accelerated Atherosclerosis and Early Cardiovascular Disease: A Scientific Statement From the American Heart Association

In the 2011 "Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents," several medical conditions among youth were identified that predispose to accelerated atherosclerosis and early cardiovascular disease (CVD), and risk stratification and management strategies for youth with these conditions were elaborated. Major depressive disorder (MDD) and bipolar disorder (BD) among youth satisfy the criteria set for, and therefore merit inclusion among, Expert Panel tier II moderate-risk conditions. The combined prevalence of MDD and BD among adolescents in the United States is ≈10%, at least 10 times greater than the prevalence of the existing moderate-risk conditions combined. The high prevalence of MDD and BD underscores the importance of positioning these diseases alongside other pediatric diseases previously identified as moderate risk for CVD. The overall objective of this statement is to increase awareness and recognition of MDD and BD among youth as moderate-risk conditions for early CVD. To achieve this objective, the primary specific aims of this statement are to (1) summarize evidence that MDD and BD are tier II moderate-risk conditions associated with accelerated atherosclerosis and early CVD and (2) position MDD and BD as tier II moderate-risk conditions that require the application of risk stratification and management strategies in accordance with Expert Panel recommendations. In this scientific statement, there is an integration of the various factors that putatively underlie the association of MDD and BD with CVD, including pathophysiological mechanisms, traditional CVD risk factors, behavioral and environmental factors, and psychiatric medications.

Antidepressant medication use and trajectories of fasting plasma glucose, glycated haemoglobin, β-cell function and insulin sensitivity: a 9-year longitudinal study of the D.E.S.I.R. cohort

BACKGROUND

Use of antidepressants is seen to be a risk factor for type 2 diabetes, even though the underlying mechanisms remain unclear. We examined whether antidepressant use was associated with change in fasting plasma glucose, glycated haemoglobin (HbA1c), β-cell function (HOMA2-%B) and insulin sensitivity (HOMA2-%S) over time.

METHODS

Participants in the French D.E.S.I.R. cohort study included over 4700 men (48.1%) and women, free of diabetes, aged 30-65 years at baseline in 1994-96 (D.E.S.I.R. 0), who were followed for 9 years at 3-yearly intervals (D.E.S.I.R. 3, 1997-99; 6, 2000-02; 9, 2003-05). Antidepressant use, fasting plasma glucose, HbA1c, HOMA2-%B and HOMA2-%S were assessed concurrently at four medical examinations. Linear mixed models were used to examine the cross-sectional and longitudinal associations of time-dependent antidepressant use with changes in these four biological parameters.

RESULTS

Mean fasting plasma glucose and HbA1c increased whereas HOMA2-%B and HOMA2-%S decreased over the follow-up. In a fully adjusted model, there were no differences in: mean fasting plasma glucose (β = 0.01 mmol/l, P = 0.702); HbA1c (β = 0.01 %, P = 0.738); HOMA2-%B (β = 0.00, P = 0.812); or HOMA2-%S (β =-0.01, P = 0.791) at baseline (1994-96) between antidepressant users and non-users. The interaction term with time also suggested no differences in the annual change in: fasting plasma glucose (β = 0.00 mmol/l, P = 0.322); HbA1c (β = 0.00 %, P = 0.496); HOMA2-%B (β = 0.00, P = 0.609); or HOMA2-%S (β = 0.00, P = 0.332) between antidepressant users and non-users. Similar associations were observed in analyses of type and cumulative use of antidepressants over follow-up.

CONCLUSION

Our longitudinal data show that use of antidepressants is not associated with altered glucose metabolism, suggesting that the association between antidepressant use and diabetes reported by previous studies may not be causal. Detection bias or clinical ascertainment bias may account for much of this apparent association.

The prevalence and risk of metabolic syndrome and its components among people with posttraumatic stress disorder: a systematic review and meta-analysis

OBJECTIVE

People with posttraumatic stress disorder (PTSD) have a higher mortality than the general population, mainly due to cardiovascular diseases (CVD). Metabolic syndrome (MetS) and its components are highly predictive of CVD. The aim of this meta-analysis was to describe pooled frequencies of MetS and its components in people with PTSD and to compare MetS prevalence in PTSD versus the general population.

METHOD

Medline, PsycARTICLES, Embase and CINAHL were searched until 02/2015 for cross-sectional and baseline data of longitudinal studies in adults with PTSD. Two independent reviewers conducted the searches and extracted data. Random effects meta-analysis with a relative risk, subgroups and meta-regression analyses were employed.

RESULTS

Overall, 9 studies met the inclusion criteria including 9,673 individuals in midlife with PTSD and 6852 general population controls. The pooled MetS prevalence was 38.7% (95% CI = 32.1%-45.6%; Q = 52.1, p < 0.001; N = 9; n = 9,673; age range = 44-61 years). Abdominal obesity was observed in 49.3% (95% CI = 29.7%-69.0%), hyperglycemia in 36.1% (95% CI = 18.8%-55.6%), hypertriglyceridemia in 45.9% (95% CI = 12.2%-81.9%), low high density-lipoprotein-cholesterol in 46.4% (95% CI = 26.4%-67.0%) and hypertension in 76.9% (95% CI = 67.9%-84.8%). The MetS prevalence was consistently high across geographical regions, settings or populations (war veterans or not). Compared with matched general population controls, people with PTSD had an almost double increased risk for MetS (RR = 1.82; 95% CI = 1.72-1.92; p < 0.001). Most analyses were not statistically heterogeneous.

CONCLUSIONS

MetS is highly prevalent in people with PTSD. Routine screening and multidisciplinary management of medical and behavioral conditions is needed. Future research should focus on how cardio-metabolic outcomes are moderated by clinical and treatment characteristics and genetic factors.

Metabolic syndrome and metabolic abnormalities in patients with major depressive disorder: a meta-analysis of prevalences and moderating variables

BACKGROUND

Individuals 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).

METHOD

We 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.

RESULTS

The 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.

CONCLUSIONS

The 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.