Interventions for the management of obesity in people with bipolar disorder

Neighbourhood deprivation and type 2 diabetes in patients with bipolar disorder: A nationwide follow-up study

Patients with bipolar disorder have higher rates of type 2 diabetes (T2D) compared to the general population. Neighbourhood deprivation is associated with T2D and bipolar disorder. The aim of this study was to explore the potential effect of neighbourhood deprivation on incident T2D in patients with bipolar disorder. This nationwide open cohort study (1997-2018) included adults in Sweden ≥20 years with bipolar disorder (90,780 patients) to examine the subsequent risk of T2D. The association between neighbourhood deprivation and T2D was explored using Cox regression analysis, with hazard ratios (HRs) and 95% confidence intervals (95% CIs). All models were conducted in both men and women and adjusted for individual-level sociodemographic factors and comorbidities. Neighbourhood deprivation was significantly associated with T2D in patients with bipolar disorder. The HRs were 1.61 (95% CI 1.40-1.86) for men and 1.83 (1.60-2.10) for women living in high deprivation neighbourhoods compared to those from low deprivation neighbourhoods. After adjustment, these results remained significant: 1.35 (1.17-1.56) in men and 1.39 (1.20-1.60) in women living in high deprivation neighbourhoods. The suggested graded association of higher incident T2D among patients with bipolar disorder, observed when levels of neighbourhood deprivation increased, raises important clinical and public health concerns. The results may help develop a contextual approach to prevention of T2D in patients with bipolar disorder that includes the neighbourhood environment.

Significant Weight Gain With the Administration of Lurasidone and Valproic Acid in Schizophrenia and Bipolar Disorder Patients

Antipsychotics are frequently used to treat psychiatric disorders and have been associated with weight gain. Mental disorders are likely to reduce patients' quality of life. Unhealthy lifestyles such as reduced physical activity, sleep disturbances, and irregular diets can lead to weight gain. Herein, we report two cases of schizophrenia and bipolar disorder who had a 10-kg gain in weight in six months with the administration of lurasidone and valproic acid. Lurasidone has fewer side effects, such as weight gain and somnolence. However, concomitant use of sedating antipsychotics or mood stabilizers in the acute phase and multiple doses increase the risk of weight gain. Additionally, various factors, including psychiatric symptoms and lifestyle changes, are believed to contribute to weight gain, and a comprehensive approach should be followed.

Pharmacological treatment of bipolar disorder and risk of diabetes mellitus: A nationwide study of 30,451 patients

OBJECTIVE

While treatment with antipsychotics and antiepileptics have been associated with an increased risk of diabetes mellitus (DM), lithium may have the opposite effect via inhibition of glycogen synthase kinase-3. The aim of this study was to investigate whether treatment of bipolar disorder with lithium, antipsychotics, or antiepileptics is associated with the risk of DM in a real-world clinical setting.

METHODS

Using nationwide registers, we identified all patients diagnosed with bipolar disorder in Danish Psychiatric Services from January 1, 1996, to January 1, 2019 (N = 30,451). The risk of developing DM was operationalized via hospital diagnoses and redeemed prescriptions for glucose-lowering drugs. For lithium, antipsychotics, valproate, and lamotrigine, we calculated hazard rate ratios (HRR) for developing DM via adjusted Cox proportional hazards models. Potential cumulative dose-response-like associations were examined using the log-rank test.

RESULTS

During follow-up (245,181 person-years), 2107 (6.9%) patients developed DM. Compared with non-users of the respective drugs, we found no clinically or statistically significant difference in the risk of developing DM among patients receiving lithium (n = 11,690; incidence rate of DM/1000 person-years (IR) = 8.87, 95% CI: 8.02-9.90; HRR = 0.94, 95% CI: 0.84-1.06) or lamotrigine (n = 11,785; IR = 7.58, 95% CI: 6.69-8.59; HRR = 0.89, 95% CI: 0.77-1.02), respectively. Conversely, for patients receiving valproate (n = 5171; IR = 12.68, 95% CI: 10.87-14.80; HRR = 1.34, 95% CI: 1.14-1.58) and antipsychotics (n = 22,719; IR = 12.00, 95% CI: 11.14-12.94; HRR = 1.65, 95% CI: 1.45-1.88), respectively, there was increased risk of developing DM. For antipsychotics, we observed a clear cumulative dose-response-like association with the risk of DM.

CONCLUSIONS

Treatment with valproate and antipsychotics-but not with lithium and lamotrigine-was associated with increased risk of DM in a real-world cohort of patients with bipolar disorder.

Self-management interventions for adults living with obesity to improve patient-relevant outcomes: An evidence map

OBJECTIVES

To conduct an evidence map on self-management interventions and patient-relevant outcomes for adults living with overweight/obesity.

METHODS

Following Arksey and O'Malley methodology, we searched in five electronical databases including randomized controlled trials (RCTs) on SMIs for overweight/obesity. We used the terms "self-management", "adult" and "obesity" for content. Two independent reviewers assessed eligible references; one reviewer extracted data, a second checked accuracy.

RESULTS

We identified 497 RCTs (58% US, 20% Europe) including 99,741 (median 112, range 11-5145) adults living with overweight/obesity. Most research evaluated clinical outcomes (617, 55%) and behaviors adherence (255, 23%). Empowerment skills, quality of life and satisfaction were less targeted (8%, 7%, 0.2%, respectively). The most frequent techniques included sharing information (858, 99%), goal setting (619, 72%) and self-monitoring training (614, 71%), provided face-to-face (386, 45%) or in combination with remote techniques (256, 30%). Emotional management, social support and shared-decision were less frequent (18%, 26%, 4%). Socio-economic status, minorities or health literacy were seldom reported.

CONCLUSION

There is a need of widening the scope of research by focusing on outcomes important to patients, assessing emotional/social/share-decision support, exploring remote techniques and including vulnerable populations.

Exploring Lead loci shared between schizophrenia and Cardiometabolic traits

Individuals with schizophrenia (SCZ) have, on average, a 10- to 20-year shorter expected life span than the rest of the population, primarily due to cardiovascular disease comorbidity. Genome-wide association studies (GWAS) have previously been used to separately identify common variants in SCZ and cardiometabolic traits. However, genetic variants jointly influencing both traits remain to be fully characterised. To assess overlaps (if any) between the genetic architecture of SCZ and cardiometabolic traits, we used conditional false discovery rate (FDR) and local genetic correlation statistical framework analyses. A conjunctional FDR was used to identify shared genetic traits between SCZ and cardiometabolic risk factors. We identified 144 genetic variants which were shared between SCZ and body mass index (BMI), and 15 variants shared between SCZ and triglycerides (TG). Furthermore, we discovered four novel single nucleotide polymorphisms (SNPs) (rs3865350, rs9860913, rs13307 and rs9614186) and four proximate genes (DERL2, SNX4, LY75 and EFCAB6) which were shared by SCZ and BMI. We observed that the novel genetic variant rs13307 and the most proximate gene LY75 exerted potential effects on SCZ and BMI comorbidity. Also, we observed a mixture of concordant and opposite direction associations with shared genetic variants. We demonstrated a moderate to high genetic overlap between SCZ and cardiometabolic traits associated with a pattern of bidirectional associations. Our data suggested a complex interplay between metabolism-related gene pathways in SCZ pathophysiology.

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

OBJECT

Despite 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.

METHODS

In 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.

RESULTS

The 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).

CONCLUSIONS

Obesity 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.

Obesity and metabolic comorbidity in bipolar disorder: do patients on lithium comprise a subgroup? A naturalistic study

BACKGROUND

Bipolar disorders (BD) are associated with increased prevalence of obesity and metabolic syndrome (MetS). Nevertheless, there is a wide range in prevalence estimates, with little known about the contributions of pharmacotherapy. It has been suggested that lithium might have a more favorable metabolic profile. We hypothesized that lithium use is associated with less increased body mass index (BMI), MetS, and type II diabetes, when compared with non-lithium users (those on anticonvulsants, second-generation antipsychotics).

METHODS

Cross-sectional study of 129 patients aged 18-85 with bipolar disorder, followed at tertiary care clinics in Montreal. Patients using lithium were compared with those not on lithium, for body mass index and metabolic syndrome.

RESULTS

The prevalence of obesity and metabolic syndrome in the sample of lithium-using patients with BD was 42.4 and 35.7% respectively, with an average BMI of 29.10 (+/- 6.70). Lithium and non-lithium groups did not differ in BMI or prevalence of MetS. However, compared to the non-lithium group, lithium users had lower hemoglobin A1C (5.24 +/- 0.53 versus 6.01 +/- 1.83, U = 753.5, p = 0.006) and lower triglycerides (1.46 +/- 0.88 versus 2.01 +/- 1.25, U = 947, p = 0.020).

CONCLUSIONS

There is a high prevalence of obesity and metabolic syndrome among patients with bipolar disorder. However, this did not appear to be associated with lithium use, when compared to those not on lithium. The lithium subgroup was also associated with lower prevalence of type II diabetes. Future prospective and intervention studies with larger sample sizes are necessary to further explore the association between lithium and insulin resistance, as well as its underlying mechanisms.

Update on the Relationship Between Depression and Neuroendocrine Metabolism

Through the past decade of research, the correlation between depression and metabolic diseases has been noticed. More and more studies have confirmed that depression is comorbid with a variety of metabolic diseases, such as obesity, diabetes, metabolic syndrome and so on. Studies showed that the underlying mechanisms of both depression and metabolic diseases include chronic inflammatory state, which is significantly related to the severity. In addition, they also involve endocrine, immune systems. At present, the effects of clinical treatments of depression is limited. Therefore, exploring the co-disease mechanism of depression and metabolic diseases is helpful to find a new clinical therapeutic intervention strategy. Herein, focusing on the relationship between depression and metabolic diseases, this manuscript aims to provide an overview of the comorbidity of depression and metabolic.

Metabolic Syndrome Impairs Executive Function in Bipolar Disorder

Background: Metabolic syndrome (MetS) is more prevalent in individuals with bipolar disorder and has a negative impact on cognition, in particular on executive function, which is already impaired in individuals with bipolar disorder compared to healthy controls.

Methods: In a cross-sectional study, we compared 148 euthymic patients with bipolar disorder and 117 healthy controls in cognitive function depending on the diagnosis of MetS. A neuropsychological test battery was used including the Trail Making Test A/B, Stroop Color and Word Interference Test, the d2 Test of Attention Revised, and the California Verbal Learning Test. In addition, MetS variables as well as the defining variables waist circumference, serum triglyceride levels, high-density lipoprotein cholesterol levels, blood pressure, fasting glucose levels, and body mass index were compared between patients and controls. In addition, illness-related variables were associated with MetS in individuals with bipolar disorder.

Results: The prevalence of MetS in patients with bipolar disorder was higher than in controls (30.4 vs. 15.4%). Patients with bipolar disorder with MetS had impaired executive function compared to patients without MetS or healthy controls with and without MetS (p = 0.020). No MetS effects or interaction MetS × Group was found in attention/processing speed (p = 0.883) and verbal learning/memory (p = 0.373). Clinical variables (illness duration, suicidality, number of affective episodes, medication, age of onset, and history of psychosis) did not relate to MetS in bipolar disorder (p > 0.05).

Conclusion: Bipolar disorder comorbid with MetS bears additional risk for impaired executive function. Executive function includes action planning, inhibition, and impulse control and could play a critical role in keeping long-term goals in mind associated with gaining and maintaining a healthy weight.