The relationship between abdominal obesity and depression in the general population: A systematic review and meta-analysis

The cross-sectional association between dietary total, animal, and plant-based protein intake and the prevalence and severity of depressive symptoms in Dutch adults with type 2 diabetes: The Hoorn Diabetes Care System cohort

OBJECTIVE

This study aimed to investigate cross-sectional associations of total, animal, and plant-based protein intake and depressive symptoms in Dutch adults with type 2 diabetes (T2D).

METHODS

We included 1137 individuals with T2D (aged 68.6 ± 9.0) from the Hoorn Diabetes Care System cohort. Energy-adjusted protein intake was assessed using a validated Food Frequency Questionnaire. The nine-item Patient Health Questionnaire (PHQ-9) was used to assess the prevalence of depressive symptoms (PHQ-9 ≥ 10 and/or anti-depressant use) and the severity of depressive symptoms (continuous PHQ-9 score). Associations between total, animal, and plant-based protein (quartiles) with depressive symptoms were assessed using multiple logistic and linear regression.

RESULTS

Highest intake of total, animal, and plant-based protein was not associated with the prevalence of depressive symptoms, compared to lowest intake (e.g., total protein, ORQ4vsQ1:0.75, 95%CI 0.42;1.32). For the severity of depressive symptoms, highest total protein intake was significantly associated with lower PHQ-9 scores (ORQ4vsQ1:0.87, 95%CI 0.75;1.00), compared to lowest intake. Animal protein was not associated with the severity of depressive symptoms (β ∼ 1), while the association for plant-based protein was marginally non-significant (βQ4vsQ1:0.88, 95%CI 0.76;1.02).

CONCLUSION

In individuals with T2D, higher total protein intake was associated with reduced severity of depressive symptoms, but not with the prevalence of depressive symptoms. Further prospective research with a larger sample size is needed to confirm these associations.

Leptin's Inverse Association With Brain Morphology and Depressive Symptoms: A Discovery and Confirmatory Study Across 2 Independent Samples

BACKGROUND

Major depressive disorder has a complex, bidirectional relationship with metabolic dysfunction, but the neural correlates of this association are not well understood.

METHODS

In this cross-sectional investigation, we used a 2-step discovery and confirmatory strategy utilizing 2 independent samples (sample 1: 288 participants, sample 2: 196 participants) to examine the association between circulating indicators of metabolic health (leptin and adiponectin) and brain structures in individuals with major depressive disorder.

RESULTS

We found a replicable inverse correlation between leptin levels and cortical surface area within essential brain areas responsible for emotion regulation, such as the left posterior cingulate cortex, right pars orbitalis, right superior temporal gyrus, and right insula (standardized beta coefficient range: -0.27 to -0.49, puncorrected < .05). Notably, this relationship was independent of C-reactive protein levels. We also identified a significant interaction effect of leptin levels and diagnosis on the cortical surface area of the right superior temporal gyrus (standardized beta coefficient = 0.26 in sample 1, standardized beta coefficient = 0.30 in sample 2, puncorrected < .05). We also observed a positive correlation between leptin levels and atypical depressive symptoms in both major depressive disorder groups (r = 0.14 in sample 1, r = 0.29 in sample 2, puncorrected < .05).

CONCLUSIONS

The inverse association between leptin and cortical surface area in brain regions that are important for emotion processing and leptin's association with atypical depressive symptoms support the hypothesis that metabolic processes may be related to emotion regulation. However, the molecular mechanisms through which leptin may exert these effects should be explored further.

The impact of educational attainment on mental health: A Causal Assessment from the UKB and FinnGen Cohorts

Observational studies report inverse associations between educational attainment and depression/anxiety risks, but confounding hinders causal inference. This study aimed to assess potential causal relationships using Mendelian randomization (MR). Two-sample MR analysis was conducted using genetic instruments for education, smoking, body mass index, and physical activity from published genome-wide association studies. Depression and anxiety data came from the UK Biobank ([UKB] 117,782 individuals) and FinnGen (215,644 individuals) cohorts. Inverse variance weighted regression determined associations between exposures and mental health outcomes. Increased educational attainment was causally associated with reduced risks of depression (odds ratio [OR] = 0.99 per year, 95% confidence interval [CI]: 0.990-0.996, P < .001) and anxiety (OR = 0.99, CI: 0.98-0.991, P < .001) in both cohorts. Smoking initiation conferred higher risks of depression (UKB OR = 1.05, CI: 1.03-1.06, P < .001; FinnGen OR = 1.20, CI: 1.10-1.32, P < .001) and anxiety (FinnGen only, OR = 1.10, CI: 1.01-1.21, P < .05). Likewise, maternal smoking history associated with greater depression (UKB OR = 1.15, CI: 1.10-1.35, P = .027) and anxiety susceptibility (FinnGen OR = 3.02, CI: 1.67-5.46, P = .011). Higher body mass index elevated depression risk in both cohorts. Physical activity showed no clear associations. This MR study provides evidence that education may causally reduce mental health disorder risk. Smoking, obesity, and low activity appear detrimentally linked to depression and anxiety. Improving access to education could offer effective strategies for lowering population psychiatric burden.

Metabolomics in Depression: What We Learn from Preclinical and Clinical Evidences

Depression is one of the predominant common mental illnesses that affects millions of people of all ages worldwide. Random mood changes, loss of interest in routine activities, and prevalent unpleasant senses often characterize this common depreciated mental illness. Subjects with depressive disorders have a likelihood of developing cardiovascular complications, diabesity, and stroke. The exact genesis and pathogenesis of this disease are still questionable. A significant proportion of subjects with clinical depression display inadequate response to antidepressant therapies. Hence, clinicians often face challenges in predicting the treatment response. Emerging reports have indicated the association of depression with metabolic alterations. Metabolomics is one of the promising approaches that can offer fresh perspectives into the diagnosis, treatment, and prognosis of depression at the metabolic level. Despite numerous studies exploring metabolite profiles post-pharmacological interventions, a quantitative understanding of consistently altered metabolites is not yet established. The article gives a brief discussion on different biomarkers in depression and the degree to which biomarkers can improve treatment outcomes. In this review article, we have systemically reviewed the role of metabolomics in depression along with current challenges and future perspectives.

Mutational landscape of risk variants in comorbid depression and obesity: a next-generation sequencing approach

Major depression (MD) and obesity are complex genetic disorders that are frequently comorbid. However, the study of both diseases concurrently remains poorly addressed and therefore the underlying genetic mechanisms involved in this comorbidity remain largely unknown. Here we examine the contribution of common and rare variants to this comorbidity through a next-generation sequencing (NGS) approach. Specific genomic regions of interest in MD and obesity were sequenced in a group of 654 individuals from the PISMA-ep epidemiological study. We obtained variants across the entire frequency spectrum and assessed their association with comorbid MD and obesity, both at variant and gene levels. We identified 55 independent common variants and a burden of rare variants in 4 genes (PARK2, FGF21, HIST1H3D and RSRC1) associated with the comorbid phenotype. Follow-up analyses revealed significantly enriched gene-sets associated with biological processes and pathways involved in metabolic dysregulation, hormone signaling and cell cycle regulation. Our results suggest that, while risk variants specific to the comorbid phenotype have been identified, the genes functionally impacted by the risk variants share cell biological processes and signaling pathways with MD and obesity phenotypes separately. To the best of our knowledge, this is the first study involving a targeted sequencing approach toward the study of the comorbid MD and obesity. The framework presented here allowed a deep characterization of the genetics of the co-occurring MD and obesity, revealing insights into the mutational and functional profile that underlies this comorbidity and contributing to a better understanding of the relationship between these two disabling disorders.

Obesity and lipid indices as predictors of depressive symptoms in middle-aged and elderly Chinese: insights from a nationwide cohort study

BACKGROUND

Depressive symptoms are one of the most common psychiatric disorders, with a high lifetime prevalence rate among middle-aged and elderly Chinese. Obesity may be one of the risk factors for depressive symptoms, but there is currently no consensus on this view. Therefore, we investigate the relationship and predictive ability of 13 obesity- and lipid-related indices with depressive symptoms among middle-aged and elderly Chinese.

METHODS

The data were obtained from The China Health and Retirement Longitudinal Study (CHARLS). Our analysis includes individuals who did not have depressive symptoms at the baseline of the CHARLS Wave 2011 study and were successfully follow-up in 2013 and 2015. Finally, 3790 participants were included in the short-term (from 2011 to 2013), and 3660 participants were included in the long-term (from 2011 to 2015). The average age of participants in short-term and long-term was 58.47 years and 57.88 years. The anthropometric indicators used in this analysis included non-invasive [e.g. waist circumference (WC), body mass index (BMI), and a body mass index (ABSI)], and invasive anthropometric indicators [e.g. lipid accumulation product (LAP), triglyceride glucose index (TyG index), and its-related indices (e.g. TyG-BMI, and TyG-WC)]. Receiver operating characteristic (ROC) analysis was used to examine the predictive ability of various indicators for depressive symptoms. The association of depressive symptoms with various indicators was calculated using binary logistic regression.

RESULTS

The overall incidence of depressive symptoms was 20.79% in the short-term and 27.43% in the long-term. In males, WC [AUC = 0.452], LAP [AUC = 0.450], and TyG-WC [AUC = 0.451] were weak predictors of depressive symptoms during the short-term (P < 0.05). In females, BMI [AUC = 0.468], LAP [AUC = 0.468], and TyG index [AUC = 0.466] were weak predictors of depressive symptoms during the long-term (P < 0.05). However, ABSI cannot predict depressive symptoms in males and females during both periods (P > 0.05).

CONCLUSION

The research indicates that in the middle-aged and elderly Chinese, most obesity- and lipid-related indices have statistical significance in predicting depressive symptoms, but the accuracy of these indicators in prediction is relatively low and may not be practical predictors.

Metabolic Health, Overweight or Obesity, and Depressive Symptoms among Older Australian Adults

BACKGROUND

The relationship between overweight or obesity and depressive symptoms in individuals with or without cardio-metabolic abnormalities is unclear. In a cross-sectional study we examined the odds of experiencing depressive symptoms in overweight or obese older adults with or without metabolic abnormalities.

METHODS

The participants included 3318 older adults from the Hunter Community Study Cohort with a Body Mass Index (BMI) ≥ 18.5 kgm2, stratified by BMI and metabolic health risk. Obesity was defined as BMI ≥ 30 kgm2 and metabolically healthy as the absence of metabolic risk factors, according to International Diabetic Federation criteria for metabolic syndromes. Moderate to severe depressive symptoms were defined as a Centre for Epidemiological Studies Depression Scale (CES-D) score ≥ 16.

RESULTS

Compared to the metabolically healthy normal weight (MHNW) group, the odds of experiencing moderate/severe depressive symptoms were higher in those classified as a metabolically unhealthy normal weight (MUNW) (odds ratio (OR) = 1.25, 95% Confidence Interval (CI): 0.76-2.06) or metabolically unhealthy obesity (MUO) (OR = 1.48, 95% CI: 1.00-2.19), but not in those classified as metabolically unhealthy overweight (MUOW) (OR = 0.96, 95% CI: 0.63-1.45), metabolically healthy overweight (MHOW) (OR = 0.80, 95% CI: 0.51-1.26), and metabolically healthy obesity (MHO) (OR = 1.03, 95% CI: 0.65-1.64). Compared with MHNW males, the odds of moderate/severe depressive symptoms were increased in all other BMI category-metabolic health groups for males and females.

LIMITATIONS

Our relatively small sample size and cross-sectional design did not allow us to robustly establish causality.

CONCLUSION

The odds of experiencing moderate/severe depressive symptoms were increased in metabolically unhealthy older adults regardless of normal weight or obesity, with the odds of having moderate/severe depressive symptoms being higher in females than in males.

Precision Medicine in Depression: The Role of Proteomics and Metabolomics in Personalized Treatment Approaches

Depression, or major depressive disorder (MDD), is a widespread mental health condition marked by enduring feelings of sorrow and loss of interest. Treatment of depression frequently combines psychotherapy, medication, and lifestyle modifications. However, the occurrence of treatment resistance in certain individuals makes it difficult for physicians to effectively manage this disorder, calling for the implementation of alternative therapeutic strategies. Recently, precision medicine has gained increased attention in the field of mental health, paving the way for more personalized and effective therapeutic interventions in depression. Also known as personalized medicine, this approach relies on genetic composition, molecular profiles, and environmental variables to customize therapies to individual patients. In particular, precision medicine has offered novel viewpoints on depression through two specific domains: proteomics and metabolomics. On one hand, proteomics is the thorough study of proteins in a biological system, while metabolomics focuses on analyzing the complete set of metabolites in a living being. In the past few years, progress in research has led to the identification of numerous depression-related biomarkers using proteomics and metabolomics techniques, allowing for early identification, precise diagnosis, and improved clinical outcome. However, despite significant progress in these techniques, further efforts are required for advancing precision medicine in the diagnosis and treatment of depression. The overarching goal of this chapter is to provide the current state of knowledge regarding the use of proteomics and metabolomics in identifying biomarkers related to depression. It also highlights the potential of proteomics and metabolomics in elucidating the intricate processes underlying depression, opening the door for tailored therapies that could eventually enhance clinical outcome in depressed patients. This chapter finally discusses the main challenges in the use of proteomics and metabolomics and discusses potential future research directions.

Obesity and psychological distress

The relationship between high body weight and mental health has been studied for several decades. Improvements in the quality of epidemiological, mechanistic and psychological research have brought greater consistency to our understanding of the links. Large-scale population-based epidemiological research has established that high body weight is associated with poorer mental health, particularly depression and subclinical depressive symptoms. There is some evidence for bidirectional relationships, but the most convincing findings are that greater body weight leads to psychological distress rather than the reverse. Particular symptoms of depression and distress may be specifically related to greater body weight. The psychological stress induced by weight stigma and discrimination contributes to psychological distress, and may in turn handicap efforts at weight control. Heightened systemic inflammation and dysregulation of the hypothalamic-pituitary-adrenal axis are biological mechanisms that mediate in part the relationship of greater body weight with poorer mental health. Changing negative societal attitudes to high body weights would improve the wellbeing of people living with obesity, and promote more effective weight-inclusive attitudes and behaviours in society at large, particularly in healthcare settings. This article is part of a discussion meeting issue 'Causes of obesity: theories, conjectures and evidence (Part II)'.

Effectiveness of internet-based and mobile-based interventions for adults with overweight or obesity experiencing symptoms of depression: a systematic review protocol

INTRODUCTION

Internet-based and mobile-based interventions (IMIs) provide innovative low-threshold and cost-effective prevention and self-management options for mental health problems complementary to standard treatment. The objective of this systematic review is to summarise the effectiveness and to critically evaluate studies on IMIs addressing comorbid depressive symptoms in adults with overweight or obesity.

METHODS AND ANALYSIS

The study authors will systematically search the databases MEDLINE, Cochrane Library, PsycINFO, Web of Science, Embase and Google Scholar (for grey literature) for randomised controlled trials (RCTs) of IMIs for individuals with overweight or obesity and comorbid depressive symptoms without restrictions on publication date (planned inception 1 June 2023 to 1 December 2023). Two reviewers will independently extract and evaluate data from studies eligible for inclusion by assessing quality of evidence and qualitatively synthesising results. Preferred Reporting Items for Systematic reviews Meta-Analyses (PRISMA) standards and the revised Cochrane Risk of Bias tool in RCTs (RoB 2) will be applied.

ETHICS AND DISSEMINATION

Ethical approval is not required as no primary data will be collected. Study results will be disseminated through publication in a peer-reviewed journal and presentations on conferences.

PROSPERO REGISTRATION NUMBER

CRD42023361771.

Impact of insulin and insulin resistance on brain dopamine signalling and reward processing- an underexplored mechanism in the pathophysiology of depression?

Type 2 diabetes and major depressive disorder (MDD) are the leading causes of disability worldwide and have a high comorbidity rate with fatal outcomes. Despite the long-established association between these conditions, the underlying molecular mechanisms remain unknown. Since the discovery of insulin receptors in the brain and the brain's reward system, evidence has accumulated indicating that insulin modulates dopaminergic (DA) signalling and reward behaviour. Here, we review the evidence from rodent and human studies, that insulin resistance directly alters central DA pathways, which may result in motivational deficits and depressive symptoms. Specifically, we first elaborate on the differential effects of insulin on DA signalling in the ventral tegmental area (VTA) - the primary DA source region in the midbrain - and the striatum as well as its effects on behaviour. We then focus on the alterations induced by insulin deficiency and resistance. Finally, we review the impact of insulin resistance in DA pathways in promoting depressive symptoms and anhedonia on a molecular and epidemiological level and discuss its relevance for stratified treatment strategies.

Weight changes in adults with major depressive disorder: A systematic review and meta-analysis of prospective studies

BACKGROUND

Major Depressive Disorder (MDD) and obesity are bidirectionally related, but the amount of weight-gain secondary to MDD is unknown. We aimed to estimate the adjusted effect of MDD on weight-change in prospective studies compared to individuals without MDD.

METHODS

Scopus/MEDLINE, PsycInfo, Web of Science and Cochrane were systematically searched for prospective observational studies of participants with a diagnosis of MDD. We included studies that conducted regression analyses on weight-variables. We searched for weight-variables reported at baseline, follow-up, and regression analyses. A meta-analysis of the odds ratios reported in logistic regression models was performed using the generic inverse weight variance method.

RESULTS

Eight studies were included with a total of 60,443 subjects; 56.8 % with MDD. Weight-variables included weight, BMI, waist circumference, fat mass, and obesity incidence. In three follow-up reports, weight-variables increased more in participants with MDD and its subphenotypes than in control subjects, except for one MDD subphenotype. Meta-analysis of three eligible studies (n = 21,935) showed a significantly greater likelihood of incident obesity in participants with MDD (OR:1.48, 95%CI 1.03-2.13). MDD subphenotype reports might suggest a greater risk for atypical MDD.

LIMITATIONS

Heterogeneity in weight related variables, follow-ups, and regression models; scarcity of follow-up data; and limited studies eligible for meta-analysis.

CONCLUSIONS

Despite previous associations between MDD and obesity, current prospective evidence on MDD related weight-change is scarce and heterogeneous. Our findings suggest a need to standardize weight-change assessment in MDD trials. Moreover, careful weight tracking and management should be incorporated in clinical settings. PROSPERO registration CRD42020214427.

Importance of immunometabolic markers for the classification of patients with major depressive disorder using machine learning

BACKGROUND

Although there is scientific evidence of the presence of immunometabolic alterations in major depression, not all patients present them. Recent studies point to the association between an inflammatory phenotype and certain clinical symptoms in patients with depression. The objective of our study was to classify major depression disorder patients using supervised learning algorithms or machine learning, based on immunometabolic and oxidative stress biomarkers and lifestyle habits.

METHODS

Taking into account a series of inflammatory and oxidative stress biomarkers (C-reactive protein (CRP), tumor necrosis factor (TNF), 4-hydroxynonenal (HNE) and glutathione), metabolic risk markers (blood pressure, waist circumference and glucose, triglyceride and cholesterol levels) and lifestyle habits of the participants (physical activity, smoking and alcohol consumption), a study was carried out using machine learning in a sample of 171 participants, 91 patients with depression (71.42% women, mean age = 50.64) and 80 healthy subjects (67.50% women, mean age = 49.12). The algorithm used was the support vector machine, performing cross validation, by which the subdivision of the sample in training (70%) and test (30%) was carried out in order to estimate the precision of the model. The prediction of belonging to the patient group (MDD patients versus control subjects), melancholic type (melancholic versus non-melancholic patients) or resistant depression group (treatment-resistant versus non-treatment-resistant) was based on the importance of each of the immunometabolic and lifestyle variables.

RESULTS

With the application of the algorithm, controls versus patients, such as patients with melancholic symptoms versus non-melancholic symptoms, and resistant versus non-resistant symptoms in the test phase were optimally classified. The variables that showed greater importance, according to the results of the area under the ROC curve, for the discrimination between healthy subjects and patients with depression were current alcohol consumption (AUC = 0.62), TNF-α levels (AUC = 0.61), glutathione redox status (AUC = 0.60) and the performance of both moderate (AUC = 0.59) and vigorous physical exercise (AUC = 0.58). On the other hand, the most important variables for classifying melancholic patients in relation to lifestyle habits were past (AUC = 0.65) and current (AUC = 0.60) tobacco habit, as well as walking routinely (AUC = 0.59) and in relation to immunometabolic markers were the levels of CRP (AUC = 0.62) and glucose (AUC = 0.58). In the analysis of the importance of the variables for the classification of treatment-resistant patients versus non-resistant patients, the systolic blood pressure (SBP) variable was shown to be the most relevant (AUC = 0.67). Other immunometabolic variables were also among the most important such as TNF-α (AUC = 0.65) and waist circumference (AUC = 0.64). In this case, sex (AUC = 0.59) was also relevant along with alcohol (AUC = 0.58) and tobacco (AUC = 0.56) consumption.

CONCLUSIONS

The results obtained in our study show that it is possible to predict the diagnosis of depression and its clinical typology from immunometabolic markers and lifestyle habits, using machine learning techniques. The use of this type of methodology could facilitate the identification of patients at risk of presenting depression and could be very useful for managing clinical heterogeneity.

The Association Between Depression and Obesity Among Adults in Jeddah, Saudi Arabia, in 2022

Background Depression has emerged as a significant contributor to the worldwide loss of disability-adjusted life years. Simultaneously, obesity is regarded as a substantial global health issue. The co-existence of depression and obesity can further exacerbate negative health outcomes. Objective The objective of this study was to investigate the relationship between depression and obesity in adult populations in Jeddah, Saudi Arabia. Further, the study aimed to examine the impact of confounding variables and their association with depression and obesity. Methods This analytical cross-sectional study utilized an interviewer-assisted questionnaire to collect data from adult participants aged 18 y/o or older attending primary healthcare centers at the Ministry of Health in Jeddah. The study was conducted at primary healthcare centers in Jeddah city, Saudi Arabia. The questionnaire included information on demographic characteristics, comorbidities, weight and height, and the Patient Health Questionnaire-9 (PHQ-9) tool for assessing the incidence of depression. Results A total of 397 individuals were included in the study with more than 50% of the participants between 26 and 45 years. The majority of the participants were males in the study (56.9%). The self-reported chronic diseases by the participants included diabetes mellites (25.9%), hypertension (23.7%), and dyslipidemia (19.9%). The study found that 12.8% of respondents had depression, 11.1% had anxiety, and 2.5% had obsessive-compulsive disorder. A total of 29.7% of participants had a PHQ-9 score of 10 or more. A significant negative linear correlation was found between the PHQ-9 score of the participants and their body mass index (BMI) results. However, this association did not remain significant when the chi-square test was used. Moreover, diabetes mellites and hypertension among the study sample were significantly associated with moderate to severe depression (p-values = .006 and = .005, respectively). The PHQ-9 score was negatively correlated with the participants' BMI, with a coefficient of -.190 (p-value < .001). Conclusion In the current study, the majority of obese participants displayed symptoms of depression ranging from mild to moderate. However, no significant correlation was established between depression and BMI.

Association of metabolic syndrome and its components with the risk of depressive symptoms: A systematic review and meta-analysis of cohort studies

BACKGROUND

The purpose of this meta-analysis was to quantitatively analyze the association between metabolic syndrome (MetS) and the risk of depressive symptoms.

METHODS

Three electronic databases (PubMed, Embase, and PsycINFO) were searched for articles published through February 15, 2022. Cohort studies evaluating the association between MetS and depressive symptoms were selected for inclusion in this study. A random-effects model was used to evaluate the pooled estimates of MetS, including each of its components, associated with depressive symptoms.

RESULTS

A total of 11 cohort studies were selected including >2.65 million participants. There was a significant association between MetS and depressive symptoms risk, albeit with a high degree of heterogeneity (relative risk = 1.29, 95 % confidence interval: 1.12-1.48; I2 = 79.3 %). This association was consistently significant in Western countries, but it was not significant in Asian countries. When stratified by sex, age, and geographical region, MetS and its components exhibited varying degrees of association with depressive symptoms.

CONCLUSIONS

MetS is a risk factor for depressive symptoms. Further large-scale prospective cohort studies are required to confirm our findings.

Challenges in Cardiovascular Evaluation and Management of Obese Patients: JACC State-of-the-Art Review

Many unique clinical challenges accompany the diagnosis and treatment of cardiovascular disease (CVD) in people living with overweight/obesity. Similarly, physicians encounter numerous complicating factors when managing obesity among people with CVD. Diagnostic accuracy in CVD medicine can be hampered by the presence of obesity, and pharmacological treatments or cardiac procedures require careful adjustment to optimize efficacy. The obesity paradox concept remains a source of confusion within the clinical community that may cause important risk factors to go unaddressed, and body mass index is a misleading measure that cannot account for body composition (eg, lean mass). Lifestyle modifications that support weight loss require long-term commitment, but cardiac rehabilitation programs represent a potential opportunity for structured interventions, and bariatric surgery may reduce CVD risk factors in obesity and CVD. This review examines the key issues and considerations for physicians involved in the management of concurrent obesity and CVD.

The Impact of Various Methods of Obesity Treatment on the Quality of Life and Mental Health-A Narrative Review

Obesity, defined as body mass index (BMI) ≥ 30 kg/m², is one of the most important public health problems. Over one billion people are obese, including 650 million adults, which is 13% of the worldwide population, according to the World Health Organization (WHO). Similar to obesity, mental disorders such as depression and anxiety are huge social problems with serious health implications. There are numerous studies proving a strong link between the prevalence of obesity and depressive disorders, and being overweight is also associated with decreased health-related quality of life (HRQoL). Due to the broad negative impact of obesity on a patient's health, proper treatment is crucial. Currently, the literature describes many methods of treatment such as dietary treatment, pharmacotherapy using glucagon-like peptide-1 (GLP-1) analogs, orlistat, naltrexone/bupropion (NB), or finally bariatric surgery. The most commonly used methods of obesity treatment significantly improve the patient's quality of life and reduce the symptoms of depression and anxiety. The aim of our study was to summarize the knowledge about the impact of known and commonly used methods of obesity treatment (e.g., dietary treatment, bariatric surgery, and pharmacological treatment) on mental health and quality of life. For this purpose, we will try to review the current scientific data, originating from international reports.

Association of metabolic syndrome with depression in US adults: A nationwide cross-sectional study using propensity score-based analysis

Background

The association of metabolic syndrome (MetS) with depression has been previously reported; however, the results are ambiguous due to imbalanced confounding factors. Propensity score-based analysis is of great significance to minimize the impact of confounders in observational studies. Thus, the current study aimed to clarify the influence of MetS on depression incidence in the U.S. adult population by using propensity score (PS)-based analysis.

Methods

Data from 11,956 adults aged 20-85 years from the National Health and Nutrition Examination Survey (NHANES) database between 2005 and 2018 were utilized. Using 1:1 PS matching (PSM), the present cross-sectional study included 4,194 participants with and without MetS. A multivariate logistic regression model and three PS-based methods were applied to assess the actual association between MetS and depression incidence. Stratified analyses and interactions were performed based on age, sex, race, and components of MetS.

Results

After PSM, the risk of developing depression in patients with MetS increased by 40% in the PS-adjusted model (OR = 1.40, 95% confidence interval [CI]: 1.202-1.619, P < 0.001), and we could still observe a positive association in the fully adjusted model (OR = 1.37, 95% CI: 1.172-1.596, P < 0.001). Regarding the count of MetS components, having four and five conditions significantly elevated the risk of depression both in the PS-adjusted model (OR = 1.78, 95% CI: 1.341-2.016, P < 0.001 vs. OR = 2.11, 95% CI: 1.626-2.699, P < 0.001) and in the fully adjusted model (OR = 1.56, 95 CI%: 1.264-1.933, P < 0.001 vs. OR = 1.90, 95% CI: 1.458-2.486, P < 0.001). In addition, an elevation in MetS component count was associated with a significant linear elevation in the mean score of PHQ-9 (F =2.8356, P < 0.001). In the sensitivity analysis, similar conclusions were reached for both the original and weighted cohorts. Further interaction analysis revealed a clear gender-based difference in the association between MetS and depression incidence.

Conclusion

MetS exhibited the greatest influence on depression incidence in US adults, supporting the necessity of early detection and treatment of depressive symptoms in patients with MetS (or its components), particularly in female cases.

Machine learning-based prediction of clinical outcomes after first-ever ischemic stroke

Background

Accurate prediction of clinical outcomes in individual patients following acute stroke is vital for healthcare providers to optimize treatment strategies and plan further patient care. Here, we use advanced machine learning (ML) techniques to systematically compare the prediction of functional recovery, cognitive function, depression, and mortality of first-ever ischemic stroke patients and to identify the leading prognostic factors.

Methods

We predicted clinical outcomes for 307 patients (151 females, 156 males; 68 ± 14 years) from the PROSpective Cohort with Incident Stroke Berlin study using 43 baseline features. Outcomes included modified Rankin Scale (mRS), Barthel Index (BI), Mini-Mental State Examination (MMSE), Modified Telephone Interview for Cognitive Status (TICS-M), Center for Epidemiologic Studies Depression Scale (CES-D) and survival. The ML models included a Support Vector Machine with a linear kernel and a radial basis function kernel as well as a Gradient Boosting Classifier based on repeated 5-fold nested cross-validation. The leading prognostic features were identified using Shapley additive explanations.

Results

The ML models achieved significant prediction performance for mRS at patient discharge and after 1 year, BI and MMSE at patient discharge, TICS-M after 1 and 3 years and CES-D after 1 year. Additionally, we showed that National Institutes of Health Stroke Scale (NIHSS) was the top predictor for most functional recovery outcomes as well as education for cognitive function and depression.

Conclusion

Our machine learning analysis successfully demonstrated the ability to predict clinical outcomes after first-ever ischemic stroke and identified the leading prognostic factors that contribute to this prediction.

The Prevalence of Depression Symptoms and Their Socioeconomic and Health Predictors in a Local Community with a High Deprivation: A Cross-Sectional Studies

Depression is a heterogeneous and etiologically complex psychiatric syndrome thatshows a strong sexual dimorphism and often impacts people with a low socioeconomic status (SES). The aim of the study was to estimate the occurrence of depression symptoms in a local community with a high deprivation rate, the example being the inhabitants of the JanówLubelski County in eastern Poland. A cross-sectional study was carried out on 3752 people aged between 35 and 64. The prevalence of depression symptoms was assessed using the Patient Health Questionnaire-9 (PHQ-9) scale. In the screening for depression symptoms in the entire population we studied, the risk of depression symptoms was 16.1% (n = 605), with women having a significantly higher mean score than men (p < 0.001). Significant predictors associated with the achievement of 10 points and more in the PHQ-9 assessment in the case of women and men were: living alone, education and having comorbidities. Moreover, female participants living in rural areas were significantly more likely to exhibit depression symptoms, whereas smoking was a significant predictor of depressive symptoms in men. It was observed that in the case of obese women, the chance of being in the higher category of the PHQ-9 assessment was 1.41 times higher than in women with normal body weight. However, in the case of men, an increase in age by one year increased the chance of being in a higher category by 1.02 times. Moreover, the odds of falling into a higher category, as assessed by the PHQ-9 questionnaire, among men who drink alcohol more than once a week was 1.7 times higher than in men who do not drink or consume alcohol occasionally. Summarising the results of studies conducted in a local community characterised by a high deprivation rate, socioeconomic and health variables related to SES significantly impacted the incidence of depression, but they differ in terms of gender.

Risk factors for depression in the elderly: An umbrella review of published meta-analyses and systematic reviews

BACKGROUND

Depression has been identified as one of the leading causes of the disease burden worldwide. Identification of the potential factors that increased or decreased the risk of depression could be important to provide prevention strategies. We aimed to conduct an umbrella review of risk factors for depression in the elderly and assessed the credibility of evidence of the association between each factor and depression.

METHODS

We searched PubMed and Web of Science from 1990 to April 11, 2021 for articles investigating associations between potential factors and depression. For each association, we recalculated the summary effect size and 95% confidence intervals using random effects models. The 95% prediction interval and between-heterogeneity were also reported. For publication bias, small-study effect and excess of significance bias were assessed.

RESULTS

Twenty-five publications met the inclusion criteria, including twenty-two meta-analyses and three qualitative systematic reviews. Approximately 1,199,927 participants and 82 unique factors were reported. Two factors were rated as convincing evidence and four factors showed highly suggestive evidence. These risk factors were aspirin use, individuals aged 80 years and above, sleep disturbances and persistent sleep disturbances, hearing problem, poor vision, and cardiac disease.

LIMITATIONS

Most studies that we included were of low quality.

CONCLUSIONS

We found several risk factors for depression with different levels of evidence, in which aspirin use and individuals aged 80 years and above presented the strongest evidence. Further research is warranted to support other findings from this umbrella review using a large, well-designed cohort study.

Melanocortin Signaling Connecting Systemic Metabolism With Mood Disorders

Obesity and mood disorders are often overlapping pathologies that are prevalent public health concerns. Many studies have indicated a positive correlation between depression and obesity, although weight loss and decreased appetite are also recognized as features of depression. Accordingly, DSM-5 defines two subtypes of depression associated with changes in feeding: melancholic depression, characterized by anhedonia and associated with decreased feeding and appetite; and atypical depression, characterized by fatigue, sleepiness, hyperphagia, and weight gain. The central nervous system plays a key role in the regulation of feeding and mood, thus suggesting that overlapping neuronal circuits may be involved in their modulation. However, these circuits have yet to be completely characterized. The central melanocortin system, a circuitry characterized by the expression of specific peptides (pro-opiomelanocortins, agouti-related protein, and neuropeptide Y) and their melanocortin receptors, has been shown to be a key player in the regulation of feeding. In addition, the melanocortin system has also been shown to affect anxiety and depressive-like behavior, thus suggesting a possible role of the melanocortin system as a biological substrate linking feeding and depression. However, more studies are needed to fully understand this complex system and its role in regulating metabolic and mood disorders. In this review, we will discuss the current literature on the role of the melanocortin system in human and animal models in feeding and mood regulation, providing evidence of the biological interplay between anxiety, major depressive disorders, appetite, and body weight regulation.

New Insights Into the Pivotal Role of CREB-Regulated Transcription Coactivator 1 in Depression and Comorbid Obesity

Depression and obesity are major public health concerns, and there is mounting evidence that they share etiopathophysiological mechanisms. The neurobiological pathways involved in both mood and energy balance regulation are complex, multifactorial and still incompletely understood. As a coactivator of the pleiotropic transcription factor cAMP response element-binding protein (CREB), CREB-regulated transcription coactivator 1 (CRTC1) has recently emerged as a novel regulator of neuronal plasticity and brain functions, while CRTC1 dysfunction has been associated with neurodegenerative and psychiatric diseases. This review focuses on recent evidence emphasizing the critical role of CRTC1 in the neurobiology of depression and comorbid obesity. We discuss the role of CRTC1 downregulation in mediating chronic stress-induced depressive-like behaviors, and antidepressant response in the light of the previously characterized Crtc1 knockout mouse model of depression. The putative role of CRTC1 in the alteration of brain energy homeostasis observed in depression is also discussed. Finally, we highlight rodent and human studies supporting the critical involvement of CRTC1 in depression-associated obesity.

The menace of obesity to depression and anxiety prevalence

The incidence of depression and anxiety is amplified by obesity. Mounting evidence reveals that the psychiatric consequences of obesity stem from poor diet, inactivity, and visceral adipose accumulation. Resulting metabolic and vascular dysfunction, including inflammation, insulin and leptin resistance, and hypertension, have emerged as key risks to depression and anxiety development. Recent research advancements are exposing the important contribution of these different corollaries of obesity and their impact on neuroimmune status and the neural circuits controlling mood and emotional states. Along these lines, this review connects the clinical manifestations of depression and anxiety in obesity to our current understanding of the origins and biology of immunometabolic threats to central nervous system function and behavior.

The association between depression and metabolic syndrome and its components: a bidirectional two-sample Mendelian randomization study

Observational studies suggested a bidirectional correlation between depression and metabolic syndrome (MetS) and its components. However, the causal associations between them remained unclear. We aimed to investigate whether genetically predicted depression is related to the risk of MetS and its components, and vice versa. We performed a bidirectional two-sample Mendelian randomization (MR) study using summary-level data from the most comprehensive genome-wide association studies (GWAS) of depression (n = 2,113,907), MetS (n = 291,107), waist circumference (n = 462,166), hypertension (n = 463,010) fasting blood glucose (FBG, n = 281,416), triglycerides (n = 441,016), high-density lipoprotein cholesterol (HDL-C, n = 403,943). The random-effects inverse-variance weighted (IVW) method was applied as the primary method. The results identified that genetically predicted depression was significantly positive associated with risk of MetS (OR: 1.224, 95% CI: 1.091-1.374, p = 5.58 × 10^-4), waist circumference (OR: 1.083, 95% CI: 1.027-1.143, p = 0.003), hypertension (OR: 1.028, 95% CI: 1.016-1.039, p = 1.34 × 10^-6) and triglycerides (OR: 1.111, 95% CI: 1.060-1.163, p = 9.35 × 10^-6) while negative associated with HDL-C (OR: 0.932, 95% CI: 0.885-0.981, p = 0.007) but not FBG (OR: 1.010, 95% CI: 0.986-1.034, p = 1.34). No causal relationships were identified for MetS and its components on depression risk. The present MR analysis strength the evidence that depression is a risk factor for MetS and its components (waist circumference, hypertension, FBG, triglycerides, and HDL-C). Early diagnosis and prevention of depression are crucial in the management of MetS and its components.

Designing Lifestyle Interventions for Common Mental Disorders: What Can We Learn from Diabetes Prevention Programs?

Lifestyle factors including diet, sleep, physical activity, and substance use cessation, are recognised as treatment targets for common mental disorders (CMDs). As the field of lifestyle-based mental health care evolves towards effectiveness trials and real-world translation, it is timely to consider how such innovations can be integrated into clinical practice. This paper discusses the utility and scale-up of lifestyle interventions for CMDs and draws on diabetes prevention literature to identify enablers and barriers to translation efforts. We discuss the extent to which lifestyle interventions aimed at managing CMDs and preventing diabetes share commonalities (program content, theoretical underpinnings, program structures, interventionists, frameworks promoting fidelity, quality, sustainability). Specific considerations when utilising these programs for mental health include personalising content with respect to symptoms and trajectories of depression and anxiety, medication regimen and genetic risk profile. As this field moves from efficacy to effectiveness and implementation, it is important to ensure issues in implementation science, including "voltage drop", "program drift", logistics, funding, and resourcing, are in line with evidence-based models that are effective in research settings. Ongoing considerations includes who is best placed to deliver this care and the need for models to support implementation including long-term financing, workforce training, supervision, stakeholder and organisational support.

Major Depressive Disorder and Lifestyle: Correlated Genetic Effects in Extended Twin Pedigrees

In recent years, evidence has accumulated with regard to the ubiquity of pleiotropy across the genome, and shared genetic etiology is thought to play a large role in the widespread comorbidity among psychiatric disorders and risk factors. Recent methods investigate pleiotropy by estimating genetic correlation from genome-wide association summary statistics. More comprehensive estimates can be derived from the known relatedness between genetic relatives. Analysis of extended twin pedigree data allows for the estimation of genetic correlation for additive and non-additive genetic effects, as well as a shared household effect. Here we conduct a series of bivariate genetic analyses in extended twin pedigree data on lifetime major depressive disorder (MDD) and three indicators of lifestyle, namely smoking behavior, physical inactivity, and obesity, decomposing phenotypic variance and covariance into genetic and environmental components. We analyze lifetime MDD and lifestyle data in a large multigenerational dataset of 19,496 individuals by variance component analysis in the ‘Mendel’ software. We find genetic correlations for MDD and smoking behavior (r_G = 0.249), physical inactivity (r_G = 0.161), body-mass index (r_G = 0.081), and obesity (r_G = 0.155), which were primarily driven by additive genetic effects. These outcomes provide evidence in favor of a shared genetic etiology between MDD and the lifestyle factors.

Relationship between abdominal obesity (based on waist circumference) and serum vitamin D levels: a systematic review and meta-analysis of epidemiologic studies

CONTEXT

Although previous observational studies have investigated the association between waist circumference (WC) values and serum vitamin D levels, findings have been inconsistent.

OBJECTIVE

A systematic review and meta-analysis was performed to evaluate the effect of abdominal obesity (based on WC) on vitamin D deficiency or insufficiency in adults.

DATA SOURCES

A systematic search of the published literature up to September 2020 was conducted in electronic databases, including MEDLINE (PubMed), EMBASE, Institute for Scientific Information (ISI) (Web of Science), Scopus, and Google Scholar, for observational studies that investigated the association between abdominal obesity (based on WC) or different categories of WC as the exposure and serum 25-hydroxy vitamin D levels as the outcome.

DATA EXTRACTION

Eighteen cross-sectional studies were included in the review. The relationship between WC values and combined serum vitamin D deficiency and insufficiency (<30 ng/mL) or vitamin D deficiency (<20 ng/mL) was evaluated.

DATA ANALYSIS

Combining 8 effect sizes from 5 investigations, including 7997 individuals, illustrated that the highest category of WC, compared with the lowest category of WC, was related to 82% increased odds of combined serum vitamin D deficiency and insufficiency (<30 ng/mL) (OR: 1.82; 95% CI: 1.34, 2.49). Moreover, in studies that investigated both genders together, the highest category of WC, compared with the lowest category of WC, was associated with 61% increased odds of serum vitamin D deficiency (<20 ng/mL) (OR: 1.61; 95% CI: 1.12, 2.31). The same results were obtained for almost all subgroups for several covariates.

CONCLUSION

This meta-analysis of cross-sectional studies confirmed that increased WC was related to the elevated risk of combined vitamin D deficiency and insufficiency in adults. More prospective studies are needed to confirm causality.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration no. CRD42020190485.

Risk of comorbidities following physician-diagnosed knee or hip osteoarthritis: a register-based cohort study

OBJECTIVE

To estimate the risk of developing comorbidities in patients after physician-diagnosed knee or hip osteoarthritis (OA).

DESIGN

Cohort study using Swedish longitudinal healthcare register data; we studied residents in the Skåne region aged ≥35 years at January 1, 2010 free from diagnosed hip or knee OA (n= 548,681). We then identified subjects with at least one new diagnosis of knee or hip OA (incident OA) between 2010 and 2017 (n=50,942 considered exposed). Subjects without diagnosed OA were considered unexposed. From January 2010 both unexposed and exposed subjects were observed for the occurrence of 18 different pre-defined comorbidities until either relocation outside of the region, death, occurrence of the comorbidity, or December 2017, whichever came first. We calculated unadjusted and adjusted hazard ratios (HR, aHR) of comorbidities using Cox models with knee and hip OA as time-varying exposures.

RESULTS

Subjects with incident knee or hip OA had 7% to 60% higher adjusted hazards (aHR between 1.07 to 1.60), of depression, cardiovascular diseases, back pain, and osteoporosis than individuals without an OA diagnosis. An increased risk of diabetes was found only for knee OA (aHR 1.19, 95% CI 1.13-1.26). For the rest of the diagnoses, we found either no increased risk or estimates with wide confidence intervals, excluding clear interpretations of the direction or size of effects.

CONCLUSIONS

Incident physician-diagnosed knee and hip OA is associated with increased risk of depression, cardiovascular diseases, back pain, osteoporosis, and diabetes. However, the latter only for knee OA.

Linking atypical depression and insulin resistance-related disorders via low-grade chronic inflammation: Integrating the phenotypic, molecular and neuroanatomical dimensions

Insulin resistance (IR) and related disorders, such as T2DM, increase the risk of major depressive disorder (MDD) and vice versa. Current evidence indicates that psychological stress and overeating can induce chronic low-grade inflammation that can interfere with glutamate metabolism in MDD as well as insulin signaling, particularly in the atypical subtype. Here we first review the interactive role of inflammatory processes in the development of MDD, IR and related metabolic disorders. Next, we describe the role of the anterior cingulate cortex in the pathophysiology of MDD and IR-related disorders. Furthermore, we outline how specific clinical features of atypical depression, such as hyperphagia, are more associated with inflammation and IR-related disorders. Finally, we examine the regional specificity of the effects of inflammation on the brain that show an overlap with the functional and morphometric brain patterns activated in MDD and IR-related disorders.

Association of Lower Nutritional Status and Education Level with the Severity of Depression Symptoms in Older Adults-A Cross Sectional Survey

The study analyzes the relationship between nutritional status and depression symptoms severity in the older population. A total of 1975 older outpatients (1457 women and 518 men, median age 75) were included in the study. Depression symptoms severity was assessed using the Geriatric Depression Scale (GDS). Participants were divided into two subgroups according to GDS score. Group A: 0–5 points—without depression symptoms (1237, W:898, M:339), and group B: 6–15 points—with depression symptoms (738, W:559, M:179). The nutritional status of the patients was assessed with Mini Nutritional Assessment (MNA) and basic anthropometric variables (waist, hips, calf circumferences, body mass index (BMI), waist to hip ratio (WHR), and waist to height ratio (WHtR)). Education years and chronic diseases were also noted. Women with higher depression symptoms severity had significantly lower MNA scores [A: 26.5 (24–28) (median (25%−75% quartiles)) vs. B:23 (20.5–26)], shorter education time [A:12 (8–16) vs. B:7 (7–12)], smaller calf circumference [A:36 (33–38) vs. B: 34 (32–37)], and higher WHtR score [A:57.4 (52.3–62.9) vs. B:58.8 (52.1–65.6)]. Men with depression symptoms had lower MNA scores [A:26.5 (24.5–28) vs. B:24 (20.5–26.5)], shorter education [A:12 (9.5–16), B:10 (7–12)], and smaller calf circumference [A:37 (34–39), B:36 (33–38)]. In the model of stepwise multiple regression including age, years of education, anthropometric variables, MNA and concomitant diseases nutritional assessment, and education years were the only independent variables predicting severity of depression symptoms both in women and men. Additionally, in the female group, odds were higher with higher WHtR. Results obtained in the study indicate a strong relationship between proper nutritional status and education level with depression symptoms severity in older women and men.

The Role of Hypothalamic Inflammation in Diet-Induced Obesity and Its Association with Cognitive and Mood Disorders

Obesity is often associated with cognitive and mood disorders. Recent evidence suggests that obesity may cause hypothalamic inflammation. Our aim was to investigate the hypothesis that there is a causal link between obesity-induced hypothalamic inflammation and cognitive and mood disorders. Inflammation may influence hypothalamic inter-connections with regions important for cognition and mood, while it may cause dysregulation of the Hypothalamic-Pituitary-Adrenal (HPA) axis and influence monoaminergic systems. Exercise, healthy diet, and glucagon-like peptide receptor agonists, which can reduce hypothalamic inflammation in obese models, could improve the deleterious effects on cognition and mood.

Inconsistent social rhythms are associated with abdominal adiposity after involuntary job loss: An observational study

Objective

Unemployment is an established risk factor for obesity. However, few studies have examined obesity-related health behavior after involuntary job loss specifically. Job loss confers a disruption in daily time structure that could lead to negative metabolic and psychological outcomes through chronobiological mechanisms. This study examines whether individuals with unstable social rhythms after involuntary job loss present with higher abdominal adiposity than individuals with more consistent social rhythms and whether this relationship varies as a function of depressive symptoms.

Methods

Cross-sectional baseline data (n = 191) from the ongoing Assessing Daily Activity Patterns in occupational Transitions (ADAPT) study were analyzed using linear regression techniques. Participants completed the Social Rhythm Metric-17 (SRM) daily over 2 weeks. They also completed the Beck Depression Inventory II (BDI-II) and participated in standardized waist circumference measurements (cm).

Results

A significant interaction emerged between SRM and BDI-II demonstrating that less consistent social rhythms were associated with larger waist circumference at lower levels of depressive symptoms. Additional exploratory analyses demonstrated a positive association between the number of daily activities performed alone and waist circumference when controlling for symptoms of depression.

Conclusion

These findings are the first to demonstrate a relationship between social rhythm stability and abdominal adiposity in adults who have recently, involuntarily lost their jobs. Results highlight the moderating role of depressive symptoms on daily routine in studies of metabolic health. Future prospective analysis is necessary to examine causal pathways.

The psychology of obesity: An umbrella review and evidence-based map of the psychological correlates of heavier body weight

Psychological factors may explain why some people develop obesity and others remain a normal weight during their life course. We use an umbrella review approach to build an evidence-based map of the psychological correlates of heavier body weight. Synthesising findings from 42 meta-analyses that have examined associations between psychological factors and heavier body weight, we assessed level of evidence for a range of cognitive, psychosocial and mental health individual difference factors. There is convincing evidence that impaired mental health is associated with heavier body weight and highly suggestive evidence that numerous cognitive factors are associated with heavier body weight. However, the relatively low methodological quality of meta-analyses resulted in lower evidential certainty for most psychosocial factors. Psychological correlates of heavier body weight tended to be small in statistical size and on average, people with obesity were likely to be more psychologically similar than different to people with normal weight. We consider implications for understanding the development of heavier body weight and identifying effective public health interventions to reduce obesity.

Depression Heterogeneity and Its Biological Underpinnings: Toward Immunometabolic Depression

Epidemiological evidence indicates the presence of dysregulated homeostatic biological pathways in depressed patients, such as increased inflammation and disrupted energy-regulating neuroendocrine signaling (e.g., leptin, insulin). Alterations in these biological pathways may explain the considerable comorbidity between depression and cardiometabolic conditions (e.g., obesity, metabolic syndrome, diabetes) and represent a promising target for intervention. This review describes how immunometabolic dysregulations vary as a function of depression heterogeneity by illustrating that such biological dysregulations map more consistently to atypical behavioral symptoms reflecting altered energy intake/expenditure balance (hyperphagia, weight gain, hypersomnia, fatigue, and leaden paralysis) and may moderate the antidepressant effects of standard or novel (e.g., anti-inflammatory) therapeutic approaches. These lines of evidence are integrated in a conceptual model of immunometabolic depression emerging from the clustering of immunometabolic biological dysregulations and specific behavioral symptoms. The review finally elicits questions to be answered by future research and describes how the immunometabolic depression dimension could be used to dissect the heterogeneity of depression and potentially to match subgroups of patients to specific treatments with higher likelihood of clinical success.

Depression and Obesity: Analysis of Common Biomarkers

Depression and obesity are very common pathologies. Both cause significant problems of both morbidity and mortality and have decisive impacts not only on the health and well-being of patients, but also on socioeconomic and health expenditure aspects. Many epidemiological studies, clinical studies and meta-analyses support the association between mood disorders and obesity in relationships to different conditions such as the severity of depression, the severity of obesity, gender, socioeconomic status, genetic susceptibility, environmental influences and adverse experiences of childhood. Currently, both depression and obesity are considered pathologies with a high-inflammatory impact; it is believed that several overlapping factors, such as the activation of the cortico-adrenal axis, the exaggerated and prolonged response of the innate immune system and proinflammatory cytokines to stress factors and pathogens-as well as alterations of the intestinal microbiota which promote intestinal permeability-can favor the expression of an increasingly proinflammatory phenotype that can be considered a key and common phenomenon between these two widespread pathologies. The purpose of this literature review is to evaluate the common and interacting mechanisms between depression and obesity.

The association between physical fitness and mental health in Norwegian adolescents

BACKGROUND

Studies indicate that health-related components of physical fitness are associated with mental health outcomes. However, research is scarce concerning this relationship in young adolescents in general and non-existent in Norwegian populations specifically. The aim of the study was to examine whether body composition, muscular strength and cardiorespiratory fitness were associated with self-reported mental health in Norwegian adolescents.

METHODS

Adolescents from four regions of Norway (n = 1486; mean age = 13.9; girls = 50.6%) participated. Self-reported mental health (psychological difficulties) was measured by completing the Strengths and Difficulties Questionnaire. Cardiorespiratory fitness was assessed with an intermittent running test; muscular strength was assessed by measuring handgrip strength, standing broad jump and sit-ups; and body composition was assessed by calculating body mass index from weight and height. Linear mixed effects models were conducted to assess the associations between the health-related components of physical fitness and psychological difficulties. School clusters were included as random effects and all models were controlled for sex, socioeconomic status and birthplace (domestic or foreign).

RESULTS

Body composition was not associated with psychological difficulties. Muscular strength was independently associated with psychological difficulties, but when all independent variables were entered in the fully adjusted model, only cardiorespiratory fitness was associated with psychological difficulties.

CONCLUSIONS

There was a small but significant inverse association between cardiorespiratory fitness and levels of psychological difficulties in Norwegian adolescents. The results suggest that muscular strength is not associated with psychological difficulties in adolescents, when controlling for cardiorespiratory fitness. Future research should focus on the prospective association between physical fitness components and mental health outcomes in adolescents.

TRIAL REGISTRATION

The study is registered in ClinicalTrials.gov ID nr: NCT03817047. Retrospectively registered January 25, 2019.

The moderator effect of age in the association between mood and adiposity in the elderly is specific for the subcutaneous adipose compartment: An MRI study

The positive association between obesity and depressive mood in young- and middle-age individuals is a phenomenon with major clinical implications in public health. Interestingly, the trend of this association in older individuals is not clear, given the conflicting results of multiple studies. Since aging is accompanied by changes in body fat distribution, we questioned whether age is a modulator of such association. This study explores the role of age in the association between mood and general (body mass index [BMI]) and abdominal adiposity (waist circumference [WC]) in older adults characterizing the different abdominal adipose tissue compartments (subcutaneous adipose tissue [SAT] and visceral adipose tissue [VAT]) with magnetic resonance imaging (MRI) techniques.

METHODS

One hundred twenty aged community-dwelling individuals (≥50 y of age) were assessed regarding depressive mood (Geriatric Depression Scale) and adiposity (BMI and WC). From these, 96 were assessed for SAT and VAT using MRI.

RESULTS

Using multiple linear regression models, depressive mood was positively associated with BMI, WC, and VAT. Age was a significant moderator of the association between depressive mood and BMI, WC, and SAT: positive in younger participants and null or negative in older participants. On the other hand, higher VAT was significantly associated with a more depressive mood, independently of age.

CONCLUSIONS

This study identifies age as a relevant moderator in the association between depressive mood and adiposity in the elderlies. Furthermore, the body fat compartment analysis revealed that the effect of age is specific for the SAT, suggesting its protective role in depressive mood.

Adiposity, depression and anxiety: interrelationship and possible mediators

OBJECTIVES

To explore the association between adiposity, major depressive disorder and generalized anxiety disorder, and to assess the role of inflammation, diet quality and physical activity in this association.

METHODS

We used data from 2,977 individuals from the 1993 Pelotas Cohort (Brazil) who attended the 18- and 22-year follow-ups. We assessed general obesity using body mass index, fat mass index, and abdominal obesity using waist circumference. Major Depressive Disorder and generalized anxiety disorder were assessed using the mini-international neuropsychiatric interview. C-reactive protein and interleukin-6 (IL-6) levels were used as a measure of inflammation; diet quality was estimated using the revised diet quality index, and physical activity was assessed by the International physical activity questionnaire (IPAQ, min/day). The association between adiposity and major depressive disorder and generalized anxiety disorder was assessed using logistic regression, and the natural indirect effect via the mediators was estimated using G-computation.

RESULTS

General obesity assessed by body mass index (OR: 2.3; 95% CI:1.13; 4.85), fat mass index (OR: 2.6; 95%CI: 1.37; 4.83), and abdominal obesity (OR: 2.5; 95%CI: 1.18; 5.39) were associated with higher odds of major depressive disorder, whereas major depressive disorder was only associated with obesity assessed by body mass index (OR=1.9; 95% CI: 1.09; 3.46). Obesity and generalized anxiety disorder were not associated. C-reactive protein, diet quality and physical activity did not mediate the effect of obesity on major depressive disorder, and C-reactive protein mediated about 25% of the effect of major depressive disorder on adiposity.

CONCLUSIONS

Depression, but not generalized anxiety disorder, is associated with adiposity in both directions, with a stronger evidence for the direction obesity-depression. Inflammation explains part of the effect of major depressive disorder on obesity but not the other way around. Further research should explore other mechanisms that could be involved in the association between obesity and depression.

The brain-adipocyte-gut network: Linking obesity and depression subtypes

Major depressive disorder (MDD) and obesity are dominant and inter-related health burdens. Obesity is a risk factor for MDD, and there is evidence MDD increases risk of obesity. However, description of a bidirectional relationship between obesity and MDD is misleading, as closer examination reveals distinct unidirectional relationships in MDD subtypes. MDD is frequently associated with weight loss, although obesity promotes MDD. In contrast, MDD with atypical features (MDD-AF) is characterised by subsequent weight gain and obesity. The bases of these distinct associations remain to be detailed, with conflicting findings clouding interpretation. These associations can be viewed within a systems biology framework-the psycho-immune neuroendocrine (PINE) network shared between MDD and metabolic disorders. Shared PINE subsystem perturbations may underlie increased MDD in overweight and obese people (obesity-associated depression), while obesity in MDD-AF (depression-associated obesity) involves more complex interactions between behavioural and biomolecular changes. In the former, the chronic PINE dysfunction triggering MDD is augmented by obesity-dependent dysregulation in shared networks, including inflammatory, leptin-ghrelin, neuroendocrine, and gut microbiome systems, influenced by chronic image-associated psychological stress (particularly in younger or female patients). In MDD-AF, behavioural dysregulation, including hypersensitivity to interpersonal rejection, fundamentally underpins energy imbalance (involving hyperphagia, lethargy, hypersomnia), with evolving obesity exaggerating these drivers via positive feedback (and potentially augmenting PINE disruption). In both settings, sex and age are important determinants of outcome, associated with differences in emotional versus cognitive dysregulation. A systems biology approach is recommended for further research into the pathophysiological networks underlying MDD and linking depression and obesity.

Obesity Prevention Worksite Wellness Interventions for Health Care Workers: A Narrative Review

Background: Health care workers face elevated risk of obesity due to their unique work requirements. The purpose of this systematic review was to present a narrative summary of the characteristics and effectiveness of worksite wellness programs focusing on preventing obesity among health care workers. Method: The databases Medline, CINAHL, Embase, PsycINFO, and PubMed were searched. Experimental and quasi-experimental studies published in English (between 2000 and 2018) that (a) were worksite interventions, (b) had intervention directed toward health care employees, and (c) reported weight-related outcomes were included. We excluded commercial weight loss studies. Two coders extracted data on the following: purpose, key study characteristics, design, type and dosage of intervention, outcome measure(s), attrition rate, and risk of bias. Results: Of the 51 studies included in this review, the majority (75%, n = 38) targeted diet and physical activity behaviors. The majority reported improved weight outcomes in favor of the intervention. Overall, moderate- to high-intensity behavioral strategies, using any mode of intervention delivery (phone, face-to-face, or Internet), delivered by a trained professional were effective in improving weight-related outcomes. Environmental strategies were effective in improving healthier habits. Self-directed strategies worked better for motivated employees. Discussion: Multicomponent interventions offered in health care settings may be successful in improving employee weight. Across study designs, several gaps in the reporting of intervention design, dosage, fidelity, and system-level outcomes were found. Conclusion/Applying research to practice: Occupational health professionals should continue to be creative in developing multicomponent interventions (combining behavioral/educational, environmental, and organizational support) and use evidence guidance frameworks/tools to design an intervention and report dosage outcomes.

Depression and obesity: evidence of shared biological mechanisms

Depression and obesity are common conditions with major public health implications that tend to co-occur within individuals. The relationship between these conditions is bidirectional: the presence of one increases the risk for developing the other. It has thus become crucial to gain a better understanding of the mechanisms responsible for the intertwined downward physiological spirals associated with both conditions. The present review focuses specifically on shared biological pathways that may mechanistically explain the depression-obesity link, including genetics, alterations in systems involved in homeostatic adjustments (HPA axis, immuno-inflammatory activation, neuroendocrine regulators of energy metabolism including leptin and insulin, and microbiome) and brain circuitries integrating homeostatic and mood regulatory responses. Furthermore, the review addresses interventional opportunities and questions to be answered by future research that will enable a comprehensive characterization and targeting of the biological links between depression and obesity.

Anti-Obesity Effects of Medicinal and Edible Mushrooms

Obesity is a group of metabolic disorders caused by multiple factors, including heredity, diet, lifestyle, societal determinants, environment, and infectious agents, which can all lead to the enhancement of storage body fat. Excess visceral fat mass in adipose tissue generate several metabolic disorders, including cardiovascular diseases with chronic inflammation based pathophysiology. The objective of the current review is to summarize the cellular mechanisms of obesity that attenuate by antioxidant potentials of medicinal and edible mushrooms. Studies have showed that mushrooms potentially have antioxidant capacities, which increase the antioxidant defense systems in cells. They boost anti-inflammatory actions and thereby protect against obesity-related hypertension and dyslipidemia. The practice of regular consumption of mushrooms is effective in the treatment of metabolic syndrome, including obesity, and thus could be a good candidate for use in future pharmaceutical or nutraceutical applications.

Obesity and depressive symptoms in mid-life: a population-based cohort study

BACKGROUND

Obesity and depression are both highly prevalent public health disorders and evidence on their relationship is inconsistent. This study examined whether depressive symptoms are associated with current obesity, and further, whether obesity in turn is associated with an increased odds of depressive symptoms five years later after accounting for potential lifestyle confounders and depressive symptoms at baseline.

METHODS

Data were obtained from the 1958 British birth cohort (N = 9217 for cross-sectional and 7340 for prospective analysis). Clinical Interview Schedule-Revised and Mental Health Inventory-5 were used for screening depressive symptoms at ages 45 and 50 years, respectively. General and central obesity were defined using measurements of body mass index (BMI) and waist circumference (WC) at 45 years, respectively.

RESULTS

There was a cross-sectional association between depressive symptoms and obesity: participants with ≥2 depressive symptoms had 31% (95%CI 11% to 55%) higher odds of general and 26% higher odds of central obesity (95%CI 8% to 47%). In prospective analyses, both general and central obesity were associated with higher odds of depressive symptoms five years later among women but not in men (P_interaction < 0.01). After adjustment for depressive symptoms at baseline, sociodemographic and lifestyle factors, women with general obesity had 38% (95% CI 7% to 77%) and women with central obesity 34% (95%CI 9% to 65%) higher odds of depression compared to others.

CONCLUSIONS

Depressive symptoms are associated with concurrent obesity and related lifestyle factors among women and men in mid-life. Our study suggests that obesity in turn affects long-term risk of depressive symptoms in women but not in men, independently of concurrent associations, providing an important target group for the implementation of preventative strategies.

Polycystic Ovary Syndrome Is Associated With Adverse Mental Health and Neurodevelopmental Outcomes

CONTEXT

Polycystic ovary syndrome (PCOS) is characterized by hyperandrogenism and subfertility, but the effects on mental health and child neurodevelopment are unclear.

OBJECTIVES

To determine if (1) there is an association between PCOS and psychiatric outcomes and (2) whether rates of autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) are higher in children of mothers with PCOS.

DESIGN

Data were extracted from the Clinical Practice Research Datalink. Patients with PCOS were matched to two control sets (1:1) by age, body mass index, and primary care practice. Control set 2 was additionally matched on prior mental health status. Primary outcomes were the incidence of depression, anxiety, and bipolar disorder. Secondary outcomes were the prevalence of ADHD or ASD in the children.

RESULTS

Eligible patients (16,986) were identified; 16,938 and 16,355 were matched to control sets 1 and 2, respectively. Compared with control set 1, baseline prevalence was 23.1% vs 19.3% for depression, 11.5% vs 9.3% for anxiety, and 3.2% vs 1.5% for bipolar disorder (P < 0.001). The hazard ratio for time to each endpoint was 1.26 (95% confidence interval 1.19 to 1.32), 1.20 (1.11 to 1.29), and 1.21 (1.03 to 1.42) for set 1 and 1.38 (1.30 to 1.45), 1.39 (1.29 to 1.51), and 1.44 (1.21 to 1.71) for set 2. The odds ratios for ASD and ADHD in children were 1.54 (1.12 to 2.11) and 1.64 (1.16 to 2.33) for set 1 and 1.76 (1.27 to 2.46) and 1.34 (0.96 to 1.89) for set 2.

CONCLUSIONS

PCOS is associated with psychiatric morbidity and increased risk of ADHD and ASD in their children. Screening for mental health disorders should be considered during assessment.

A comparative study on cardiovascular disease risk factors in Korean adults according to clinical depression status

This study was conducted to compare the association between depression and cardiovascular disease risk factors among Korean adults. This study was based on the data from the Korea National Health and Nutrition Examination Survey conducted in 2012-2014. Using a multivariable logistic regression model, we calculated odds ratios (ORs) and 95% confidence intervals (CIs). A total of 10,359 subjects aged 19-64 years were selected, and 432 subjects (74 men, 358 women) were included in the physician-diagnosed depression group. Several cardiovascular risk factors were associated with higher odds of clinical depression. For men, high waist circumference (≥91.3 cm) and body mass index (≥25.0 kg/m²) were significantly associated with increased odds of depression, and high physical activity (≥50 MET h/week) was associated with decreased odds of depression. Men with dyslipidemia and metabolic syndrome had 2.43-fold and 2.0-fold higher odds of depression than those without the diseases. For women, current smokers had 2.25-fold higher odds of depression than nonsmokers, and frequent alcohol drinkers (≥4 times/week) also had 2.88-fold higher odds of depression than nondrinkers. Korean adults with clinical depression had a higher prevalence of some risk factors for cardiovascular diseases than those without depression.

Central or overall obesity: which one is a better predictor of depressive symptoms in children, adolescents, and youths?

BACKGROUND AND PURPOSE

Despite the strong effect of central obesity on individuals' physical health outcomes, there is little evidence underlying the relationship between central obesity and mental disorders such as depression, especially in children, adolescents, and youths of the developing countries. This study explores the relationship between depressive symptoms (DS) with central and overall obesity in a sample of Iranian children, adolescents, and youths.

METHODS

One thousand and fifty-two male participants ranging from 7 to 24 years old underwent standard anthropometry, and filled the DS questionnaire.

RESULTS

Having controlled the potential confounders (e.g., age, socioeconomic status, pubertal maturation status, and physical activity), we found waist circumference (WC) significantly related to DS in the children (standardized β = 0.14; P < 0.05) and adolescents (standardized β = 0.13; P < 0.05). No significant relationship was observed between WC and DS in the youths (standardized β = 0.09; P = 0.22). In addition, no significant relationship was observed between DS and the percentage of fat in the sampled children (standardized β = 0.085; P = 0.13), adolescents (standardized β = 0.10; P = 0.10), and youths (standardized β = -0.02; P = 0.75).

CONCLUSION

Central obesity (but not overall obesity) was a significant predictor of DS in the children and adolescents (7-18 years). However, DS in the youths (19-24 years) were not significantly associated with both the central and overall body obesity indices.