Prevalence of type 2 diabetes mellitus, impaired fasting glucose, general obesity, and abdominal obesity in patients with bipolar disorder: A systematic review and meta-analysis

Liu, Yuhan Karida; Ling, Susan; Lui, Leanna M.W.; Ceban, Felicia; Vinberg, Maj; Kessing, Lars Vedel; Ho, Roger; Rhee, Taeho Greg; Gill, Hartej; Cao, Bing; Mansur, Rodrigo B.; Lee, Yena; Rosenblat, Joshua D.; Teopiz, Kayla M.; McIntyre, Roger S.

doi:10.1016/j.jad.2021.12.110

Cited by 46 publications

(39 citation statements)

References 109 publications

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“…According to the recommendations of international societies, the proposed diagnostic tools for carbohydrate metabolism disorders include determination of the FG concentration twice, OGTT, and determination of the percentage of HbA 1c [8]. Studies assessing the risk of developing prediabetes and DM in people using antipsychotics take into account many markers of carbohydrate metabolism disorders (including C peptide concentration, fasting insulin level) and that level and after 2 hours in OGTT, HOMA-IR, and other IR markers, showing large discrepancies between the evaluated diagnostic tests.…”

Section: Reviewmentioning

confidence: 99%

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Diagnosis and management of hyperglycaemia in patients treated with antipsychotic drugs

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This article is available in open access under Creative Common Attribution-Non-Commercial-No Derivatives 4.0 International (CC BY-NC-ND 4.0) license, allowing to download articles and share them with others as long as they credit the authors and the publisher, but without permission to change them in any way or use them commerciallyThe Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 reported that mental disorders accounted for 654.8 million estimated cases in 1990 and 970.1 million cases in 2019 (an increase of 48.1%) [5]. A review and meta-analysis perform by Jongsma et al. showed that the prevalence of all psychotic disorders was 26.6 per 100,000 person-years [6]. It is estimated that DM can affect 8.7% with major depressive disorders, 6.2% with bipolar disorders, and 12% of patients with severe mental illnesses (schizophrenia, depression, bipolar and psychotic disorders). A high (19%) incidence of "prediabetic conditions" in patients with various types of psychoses has also been observed [7]. A recent study by Liu et al. indicates that patients with bipolar disorders have nearly 1.6 times greater risk of developing DM [8]. These data may be underestimate to the real risk of antipsychotic drugs. This is because they often do not take into account the presence of undiagnosed type 2 diabetes before using antipsychotic drugs.

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Section: Reviewmentioning

confidence: 99%

“…A high (19%) incidence of "prediabetic conditions" in patients with various types of psychoses has also been observed [7]. A recent study by Liu et al indicates that patients with bipolar disorders have nearly 1.6 times greater risk of developing DM [8]. These data may be underestimate to the real risk of antipsychotic drugs.…”

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Diagnosis and management of hyperglycaemia in patients treated with antipsychotic drugs

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“…People with BD have a high prevalence of obesity. A meta-analysis of 49 studies found that the pooled prevalence of general obesity (BMI ≥ 30 kg/m 2 ) was 29.0% among 322,494 adults with BD, which was significantly higher than their healthy counterparts ( 15 ). This meta-analysis also suggested that the pooled prevalence of abdominal obesity in 2,378 BD patients was up to 51.1%, and female BD patients and duration of BD were significantly associated with abdominal obesity ( 15 ).…”

Section: Introductionmentioning

confidence: 99%

Prevalence and associated factors of obesity and overweight in Chinese patients with bipolar disorder

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Front. Psychiatry

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ObjectDespite abundant literature demonstrating a high prevalence of obesity and overweight in people with bipolar disorder (BD), little is known about this topic in China. Therefore, we assessed the prevalence and associated factors of obesity and overweight among inpatients with BD in our hospital, one of the largest public psychiatric hospitals in China.MethodsIn this retrospective, cross-sectional study, 1,169 inpatients ≥18 years with BD during 2019 were included. Obesity was defined as having a BMI ≥25 kg/m2, and overweight was defined as having a BMI from 23 kg/m2 to <25 kg/m2. Binary logistic regression analysis was performed to identify factors associated with obesity and overweight.ResultsThe prevalence of obesity and overweight was 21.0% and 32.2% in patients with BD, respectively. Compared to patients with overweight and normal weight, patients with obesity were older, had a longer duration of BD and a longer length of hospital stay, had a higher prevalence of diabetes and hypertension, and had a higher level of all metabolic indices, except for HDL cholesterol. Binary logistic regression analysis showed that duration of BD, uric acid, alanine aminotransferase (ALT), triglyceride, and LDL cholesterol were significantly associated with obesity, and male sex and uric acid level were significantly associated with overweight (p < 0.05).ConclusionsObesity and overweight were fairly prevalent in Chinese BD patients, and several factors were related to obesity and overweight. The results of the present study call for the need to implement early screening, prevention and interventions for obesity and overweight in patients with BD in China.

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“…Of the many contributors to this association, obesity is likely one of the most important [3,4]. This is because obesity is known to increase mortality [3][4][5] and there are many studies linking bipolar disorder to obesity [6]. However, it remains unknown whether this link is a direct causal effect of the genetic liability to bipolar disorder.…”

Section: Introductionmentioning

confidence: 99%

Genetic liability to bipolar disorder and body mass index: A bidirectional two-sample mendelian randomization study

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et al. 2022

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Objectives: Bipolar disorder is associated with increased body mass index (BMI), but it remains undetermined if this association is causal and, if so, in which direction it goes. Here, we sought to answer these questions using bidirectional two-sample Mendelian Randomization, a method from genetic epidemiology that uses data from genome-wide association studies (GWAS) to examine whether a risk factor is causal for an outcome. Methods: We used summary statistics from GWAS of bipolar disorder and BMI conducted using data collected by the Psychiatric Genomics Consortium and the UK Biobank, respectively. The genetic instrument for bipolar disorder contained 53 SNPs and explained 0.5% of phenotypic variance, while the genetic instrument for BMI contained 517 SNPs and explained 7.1% of phenotypic variance. Results: We found that a two-fold increase in the genetic liability to bipolar disorder causes a 0.6 (kg/m2) reduction in BMI, which is statistically significant (P=0.009), and predominantly driven by reduced fat mass. Conversely, we found no evidence that BMI causes changes in the risk of developing bipolar disorder (P=0.59). Conclusion: The findings of this study indicate that the increased BMI observed among individuals with bipolar disorder is not a direct consequence of genetic liability to bipolar disorder, but more likely represents the sum of downstream correlates of manifest bipolar disorder, such as side effects of pharmacological treatment, poor diet and sedentary lifestyle, that are all modifiable and could potentially be targeted as part of clinical management.

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Prevalence of type 2 diabetes mellitus, impaired fasting glucose, general obesity, and abdominal obesity in patients with bipolar disorder: A systematic review and meta-analysis

Cited by 46 publications

References 109 publications

Diagnosis and management of hyperglycaemia in patients treated with antipsychotic drugs

Diagnosis and management of hyperglycaemia in patients treated with antipsychotic drugs

Prevalence and associated factors of obesity and overweight in Chinese patients with bipolar disorder

Genetic liability to bipolar disorder and body mass index: A bidirectional two-sample mendelian randomization study

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