Body mass index (BMI) levels have been proven to have a significant relationship with depression. However, there is limited evidence regarding the impact of BMI trajectories and the average annual changes among adults aged 40-74 years on the risk of developing depression.

In this cross-sectional study, participants aged 40-74 were retrieved from the National Health and Nutrition Examination Survey (NHANES) 2005-2018. The latent class trajectory model (LCTM) was employed to identify BMI trajectories. Depression was evaluated using the validated Patient Health Questionnaire (PHQ-9). Multinomial logistic regression models were conducted to explore the associations between BMI trajectories, its average annual changes and depression.

A total of 17, 171 participants were included. Five BMI trajectories were identified and labeled as the slight increase trajectory (n = 7830, 45.60 %), stable trajectory (n = 5605, 32.64 %), moderate increase trajectory (n = 2562, 14.92 %), rapid increase trajectory (n = 685, 3.99 %) and increase-to-decrease trajectory (n = 489, 2.85 %), respectively. Compared to individuals with stable trajectory, those who experienced a rapid increase trajectory (OR = 2.39, 95%CI 1.72-3.34) and an increase-to-decrease trajectory (OR = 2.07, 95%CI 1.51-2.84) had a higher risk of developing depression. During early adulthood, absolute (OR = 1.46, 95%CI 1.23-1.73) and relative (OR = 1.47, 95%CI 1.25-1.71) average annual BMI growths were associated with depression. In recent adulthood, average annual BMI loss was shown to increase the risk of developing depression.

This study highlights an increased risk of depression among participants aged 40-74 years with non-stable BMI trajectories, particularly among females. These findings emphasize the importance of maintaining a stable weight to reduce the risk of depression, especially in middle-aged and older adults.

Depression is associated with alterations in immuno-metabolic biomarkers, but it remains unclear whether these alterations are limited to specific markers, and whether there are subtypes of depression and depressive symptoms which are associated with specific patterns of immuno-metabolic dysfunction.

To investigate whether immuno-metabolic biomarkers could be used to profile subtypes of depression, we applied regression, clustering, and machine learning to a dataset comprising depression diagnosis, depressive and anxiety symptoms, and blood-based immunological and metabolic biomarkers (n = 118). We measured inflammatory proteins, cell counts, lipids, hormones, and metabolites from up to n = 4161 participants (2363 female, 337 with depression) aged 24 years from the Avon Longitudinal Study of Parents and Children birth cohort.

Depression at age 24 was associated with both altered concentrations of immuno-metabolic markers, and increased extreme-valued inflammatory markers. Inflammatory and metabolic biomarkers show distinct, opposing associations with somatic and anxiety symptoms. We identified two latent components representing the relationship between blood biomarkers, symptoms, and covariates, one characterised by higher somatic symptoms and inflammatory markers (neutrophils, WBC, IL-6), and the other characterised by higher anxiety and worry and lower inflammatory markers (CRP, WBC, IL-6). Individuals with higher somatic-inflammatory component scores had greater depressive symptoms severity over the next five years. Immuno-metabolic biomarkers predicted depression diagnosis (Balanced Accuracy = 0.580) and depression with high somatic symptoms (Balanced Accuracy = 0.575) better than chance, but not depression with high anxiety symptoms (Balanced Accuracy = 0.479).

Alterations in immuno-metabolic homeostasis is present in young adults with depression well before the typical age of onset of cardiometabolic diseases. The relationships between affective symptoms and blood immuno-metabolic biomarkers indicate two biotypes of depressive symptoms (somatic-inflamed vs anxious-non-inflamed). These patterns are relevant for prognosis and prediction, highlighting the potential usefulness of immuno-metabolic biomarkers for depression subtyping.

Recent studies have suggested body mass index (BMI) change patterns in adulthood may be crucial for depression. This purpose of this study is to evaluate the impact of adult BMI change patterns on depression.

The National Health and Nutrition Examination Survey 2007 to 2018 generated the data. The relationships between adult BMI change patterns and depression / Patient Health Questionnaire 9 (PHQ-9) were investigated using logistic regression and generalized linear model with a Poisson distribution. The relationships between BMI change patterns, depressive symptoms, and all-cause mortality were examined by Cox proportional hazards models. Kaplan-Meier curves were employed to illustrate the cumulative incidence over time. To explore whether adult BMI change patterns mediate this link between depression and all-cause mortality, mediation analysis was conducted.

A total of 10,448 participants were included, with 7.8% reporting depression. Significant differences were observed in demographic, lifestyle, and health characteristics across BMI change patterns. The high-increase pattern was linked to a1.61 times greater odds of depression after adjustment (odds ratio = 1.61, 95% confidence interval (CI): [1.16, 2.24], P = 0.006) compared to the non-overweight pattern. Gender and age differences were also observed. The higher PHQ-9 was correlated with increased all-cause mortality risk, even after adjustment (hazard ratio: 1.03; 95%CI: 1.02-1.05). Mediation analysis revealed that adult BMI change patterns mediated 26.98% of the correlation between depressive symptoms and all-cause mortality.

Persistent obesity in adulthood rises the risk of depression, and BMI change patterns playing a modest role in mediating the link between depressive symptoms and all-cause mortality. Early intervention in individuals at-risk BMI change patterns might reduce depression risk. Future research should investigate whether modifying BMI change patterns can lower depression incidence.

Not applicable.

Adhering to the ketogenic diet can reduce or stop seizures, even when other treatments fail, via mechanism(s) distinct from other available therapies. These results have led to interest in the diet for treating conditions such as Alzheimer's disease, depression and schizophrenia. Evidence points to the neuromodulator adenosine as a key mechanism underlying therapeutic benefits of a ketogenic diet. Adenosine represents a unique and direct link among cell energy, neuronal activity, and gene expression, and adenosine receptors form functional heteromers with dopamine receptors. The importance of the dopaminergic system is established in addiction, as are the challenges of modulating the dopamine system directly. A mediator that could antagonize dopamine's effects would be useful, and adenosine is such a mediator due to its function and location. Studies report that the ketogenic diet improves cognition, sociability, and perseverative behaviors, and might improve depression. Many of the translational opportunities based on the ketogenic diet/adenosine link have come to the fore, including addiction, autism spectrum disorder, painful conditions, and a range of hyperdopaminergic disorders.

This is the first large-scale longitudinal study of children that describes the temporal trajectories of an extensive collection of metabolic measures that are relevant for lifelong cardiometabolic risk. We also provide a comprehensive picture on how metabolism develops into mature adult sex-specific phenotypes.

Children born in 1962-92 were recruited by three European studies (n = 20 377 eligible). Biochemical data for ages 0-26 years were available for n = 14 958 participants (n = 8385 with metabolomics). Age associations for 168 metabolic measures (6 physiological traits, 6 clinical biomarkers, and 156 serum metabolomics measures) were determined by using curvilinear regression. Puberty effects were calculated by using logistic regression of biological sex for pre- and post-pubertal age strata.

Age-specific concentrations were reported for all measures. Nonlinear age associations were typical, including insulin (R2 = 20.7% ±0.6% variance explained ±SE), glycerol (13.3% ±1.3%), glycoprotein acetyls (40.3% ±1.5%), and branched-chain amino acids (19.5% ±1.6%). Apolipoprotein B was not associated with age (0.7% ±0.4%). Multivariate modeling indicated that boys diverged from girls metabolically during ages 13-17 years. Puberty effects were observed for large high-density lipoprotein cholesterol (P = 8.5 × 10-288), leucine (P < 2.3 × 10-308), glutamine (P < 2.3 × 10-308), albumin (P = 1.7 × 10-161), docosahexaenoic acid (P = 5.2 × 10-50), and sphingomyelin (P = 4.4 × 10-90).

Novel associations between emerging cardiometabolic risk factors, such as amino acids and glycoprotein acetyls, and growth and puberty were observed. Conversely, apolipoprotein B was stable, which favors its utility for early assessments of lifetime cardiovascular risk.

Studies exploring early life-course BMI trajectories and subsequent mental health outcomes are limited but may provide important insights for early intervention. We investigated associations between BMI trajectories from 0 to 18 years and mental health outcomes in emerging adulthood.

Data were obtained from 434 participants in the Melbourne Atopy Cohort Study (MACS). Anthropometric data were collected across 26 timepoints from infancy to age 25 and group-based trajectory modelling was used to develop BMI trajectories from 0.1 to 18 years. Moderate-to-severe psychological distress (MSPD) and likely depression were assessed at age 18 and 25 years. Associations between BMI trajectories and mental health at 25 years and change in mental health between 18 and 25 years were estimated using logistic regression. History of asthma, hay fever or eczema were independently examined as potential effect modifiers.

Five BMI trajectories were identified from 1 month to 18 years. When compared to the stable average BMI trajectory, we found an increased risk of MSPD (OR = 2.97; 95%CI: 1.09,8.06) and likely depression (3.56; 1.39,9.12) at age 25 in the average increasing-to-high trajectory. This group also had a greater likelihood of new-onset depression (4.82; 1.54,15.0) from 18 to 25 years of age.

MACS participants are not representative of the general population and mental health data was not available before 18 years of age.

Excessive weight gain across the childhood transition was associated with poorer mental health in emerging adulthood, highlighting the importance of monitoring growth to allow for early identification and stratification of individuals at risk of poor mental health.

Memory impairment is a serious cognitive side effect of electroconvulsive therapy (ECT) in the treatment of major depressive episodes (MDEs) and has garnered widespread attention in clinical practice, but its underlying evolution pattern during the course of ECT remains rarely understood in detail. Associative memory (AM) is a core indicator that reflects memory impairment in ECT. This study aimed to identify the dynamic trajectory of AM impairment and explore associated predictive factors. 405 intensive longitudinal AM data from 81 patients with MDE were collected at the baseline, after the first, third, fifth, and eighth ECT using five sets of face-cued word memory paradigms. Changes in AM score over time were analyzed using a linear mixed effects model. Trajectory subgroups and predictive factors were investigated using growth mixture model and logistic regression. AM score during ECT were significantly lower than at baseline, with the lowest scores observed after the eighth ECT session. Two trajectories of rapid (N = 56, 69.14%) and slow (N = 25, 30.86%) AM impairment were differentiated. Older female with lower education level were significant predictors contributing to more rapid memory impairment for ECT. The evolving pattern of associative memory impairment during ECT appears to occur early and worsen with subsequent treatment. This study may provide the important evidence understanding of the number effect of ECT sessions on memory impairment and suggest individual factors for predicting ECT memory outcome.

The use of clinical prediction models to produce individualized risk estimates can facilitate the implementation of precision psychiatry. As a source of data from large, clinically representative patient samples, electronic health records (EHRs) provide a platform to develop and validate clinical prediction models, as well as potentially implement them in routine clinical care. The current review describes promising use cases for the application of precision psychiatry to EHR data and considers their performance in terms of discrimination (ability to separate individuals with and without the outcome) and calibration (extent to which predicted risk estimates correspond to observed outcomes), as well as their potential clinical utility (weighing benefits and costs associated with the model compared to different approaches across different assumptions of the number needed to test). We review 4 externally validated clinical prediction models designed to predict psychosis onset, psychotic relapse, cardiometabolic morbidity, and suicide risk. We then discuss the prospects for clinically implementing these models and the potential added value of integrating data from evidence syntheses, standardized psychometric assessments, and biological data into EHRs. Clinical prediction models can utilize routinely collected EHR data in an innovative way, representing a unique opportunity to inform real-world clinical decision making. Combining data from other sources (e.g., meta-analyses) or enhancing EHR data with information from research studies (clinical and biomarker data) may enhance our abilities to improve the performance of clinical prediction models.

Children with high body mass index (BMI) are at heightened risk of developing health issues in adulthood, yet the causality between childhood BMI and adult psychiatric disorders remains unclear. Using a life course Mendelian randomization (MR) framework, we investigated the causal effects of childhood and adulthood BMI on adult psychiatric disorders, including Alzheimer's disease, anxiety, major depressive disorder, obsessive-compulsive disorder (OCD), and schizophrenia, using data from the Psychiatric Genomics Consortium and FinnGen study. Childhood BMI was significantly associated with an increased risk of schizophrenia, while adulthood BMI was associated with a decreased risk of OCD and schizophrenia. Multivariable MR analyses indicated a direct causal effect of childhood BMI on schizophrenia, independent of adulthood BMI and lifestyle factors. No evidence of causal associations was found between childhood BMI and other psychiatric outcomes. The sensitivity analyses yielded broadly consistent findings. These findings highlight the critical importance of early-life interventions to mitigate the long-term consequences of childhood adiposity.

Short sleep duration over a prolonged period in childhood could have a detrimental impact on long-term mental health, including the development of psychosis. Further, potential underlying mechanisms of these associations remain unknown.

To examine the association between persistent shorter nighttime sleep duration throughout childhood with psychotic experiences (PEs) and/or psychotic disorder (PD) at age 24 years and whether inflammatory markers (C-reactive protein [CRP] and interleukin 6 [IL-6]) potentially mediate any association.

This cohort study used data from the Avon Longitudinal Study of Parents and Children. Data analysis was conducted from January 30 to August 1, 2023.

Nighttime sleep duration was collected at 6, 18, and 30 months and at 3.5, 4 to 5, 5 to 6, and 6 to 7 years.

PEs and PD were assessed at age 24 years from the Psychosislike Symptoms Interview. CRP level at ages 9 and 15 years and IL-6 level at 9 years were used as mediators. Latent class growth analyses (LCGAs) were applied to detect trajectories of nighttime sleep duration, and logistic regressions were applied for the longitudinal associations between trajectories of nighttime sleep duration and psychotic outcomes at 24 years. Path analyses were applied to test CRP and IL-6 as potential mediators.

Data were available on 12 394 children (6254 female [50.5%]) for the LCGA and on 3962 young adults (2429 female [61.3%]) for the logistic regression and path analyses. The LCGA identified a group of individuals with persistent shorter nighttime sleep duration across childhood. These individuals were more likely to develop PD (odds ratio [OR], 2.50; 95% CI, 1.51-4.15; P < .001) and PEs (OR, 3.64; 95% CI, 2.23-5.95; P < .001) at age 24 years. Increased levels of IL-6 at 9 years, but not CRP at 9 or 15 years, partially mediated the associations between persistent shorter sleep duration and PD (bias-corrected estimate = 0.003; 95% CI, 0.002-0.005; P = .007) and PEs (bias-corrected estimate = 0.002; 95% CI, 0-0.003; P = .03) in young adulthood.

Findings of this cohort study highlight the necessity of addressing short sleep duration in children, as persistence of this sleep problem was associated with subsequent psychosis. This study also provides preliminary evidence for future targeted interventions in children addressing both sleep and inflammatory responses.

In recent years, the risk of depression has increased among young people, and changes in body mass index (BMI) during childhood may be important factors in their development. However, the relationship between changes in BMI during childhood and the risk of depression needs further research and exploration.

The annual health examination data were collected from Physical Examination Center of Wuhan Mental Health Center Hospital, including 1226 students. The height and weight of students at the age of 11, 14, and 17 were recorded in sequence, and at 18 years old, these students were followed up according to the Hamilton Depression Scale (HAMD) to evaluate the depression. The relationship between BMI trends and depression was analyzed through Logistic regression analysis.

The growth trend of BMI was divided into normal growth, slow growth, and excessive growth. The odds ratio (OR) value for depression in the slow growth was 1.218 (95% CI, 0.995-1.493) compared to the normal growth, which was no significant difference (P = .056). The OR value for depression in the excessive growth was 1.982 (95% CI, 1.243-3.177) compared to the normal growth, which was significant difference (P = .003).

The rapid growth of BMI is correlated with the occurrence of depression in young individuals and may be a contributing factor to the development of depression in this demographic.

Childhood-onset type 1 diabetes (T1D) is associated with substantial psychiatric morbidity in later life, but it remains unknown whether these associations are due to common underlying biological mechanisms or the impacts of living with the condition and its treatment. Here, using Czech national register data, we identified children with T1D aged ≤14 years between 1994 and 2007 and estimated the risk of psychiatric disorders up to 24 years later. We found that children diagnosed with T1D had an elevated risk of developing substance use, mood, anxiety and personality disorders, and behavioral syndromes. Conversely, we found that children with T1D had a lower risk of developing psychotic disorders. In Mendelian randomization analysis, we found an association with schizophrenia, which, however, did not persist following multiple testing adjustment. The combined observational and Mendelian randomization evidence suggests that T1D diagnosis in childhood predisposes to far-reaching, extensive psychiatric morbidity, which is unlikely to be explicable by common underlying biological mechanisms. The findings of this study highlight that monitoring and addressing the mental health needs of children with T1D is imperative, whereas glucose dysregulation and/or inflammation implicated in schizophrenia pathogenesis warrants future research.

N-acetylasparate and lactate are two prominent brain metabolites closely related to mitochondrial functioning. Prior research revealing lower levels of NAA and higher levels of lactate in the cerebral cortex of patients with schizophrenia suggest possible abnormalities in the energy supply pathway necessary for brain function. Given that stress and adversity are a strong risk factor for a variety of mental health problems, including psychotic disorders, we investigated the hypothesis that stress contributes to abnormal neuroenergetics in patients with schizophrenia. To test this hypothesis, we used the Stress and Adversity Inventory (STRAIN) to comprehensively assess the lifetime stressor exposure profiles of 35 patients with schizophrenia spectrum disorders and 33 healthy controls who were also assessed with proton magnetic resonance spectroscopy at the anterior cingulate cortex using 3 Tesla scanner. Consistent with the hypothesis, greater lifetime stressor exposure was significantly associated with lower levels of N-acetylasparate (β = -0.36, p = .005) and higher levels of lactate (β = 0.43, p = .001). Moreover, these results were driven by patients, as these associations were significant for the patient but not control group. Though preliminary, these findings suggest a possible role for stress processes in the pathophysiology of abnormal neuroenergetics in schizophrenia.

Although significant advances have been made in understanding the patho-physiology of psychiatric disorders (PDs), therapeutic advances have not been very convincing. While psychotropic medications can reduce classical symptoms in patients with PDs, their long-term use has been reported to induce or exaggerate various pre-existing metabolic abnormalities including diabetes, obesity and non-alcoholic fatty liver disease (NAFLD). The mechanism(s) underlying these metabolic abnormalities is not clear; however, lipid/fatty acid accumulation due to enhanced de novo lipogenesis (DNL) has been shown to reduce membrane fluidity, increase oxidative stress and inflammation leading to the development of the aforementioned metabolic abnormalities. Intriguingly, emerging evidence suggest that DNL dysregulation and fatty acid accumulation could be the major mechanisms associated with the development of obesity, diabetes and NAFLD after long-term treatment with psychotropic medications in patients with PDs. In support of this, several adjunctive drugs comprising of anti-oxidants and anti-inflammatory agents, that are used in treating PDs in combination with psychotropic medications, have been shown to reduce insulin resistance and development of NAFLD. In conclusion, the above evidence suggests that DNL could be a potential pathological factor associated with various metabolic abnormalities, and a new avenue for translational research and therapeutic drug designing in PDs.

Given the physical health disparities associated with mental illness, targeted lifestyle interventions are required to reduce the risk of cardiometabolic disease. Integrating physical health early in mental health treatment among young people is essential for preventing physical comorbidities, reducing health disparities, managing medication side effects, and improving overall health outcomes. Digital technology is increasingly used to promote fitness, lifestyle, and physical health among the general population. However, using these interventions to promote physical health within mental health care requires a nuanced understanding of the factors that affect their adoption and implementation.

Using a qualitative design, we explored the attitudes of mental health care professionals (MHCPs) toward digital technologies for physical health with the goal of illuminating the opportunities, development, and implementation of the effective use of digital tools for promoting healthier lifestyles in mental health care.

Semistructured interviews were conducted with MHCPs (N=13) using reflexive thematic analysis to explore their experiences and perspectives on using digital health to promote physical health in youth mental health care settings.

Three overarching themes from the qualitative analysis are reported: (1) motivation will affect implementation, (2) patients' readiness and capability, and (3) reallocation of staff roles and responsibilities. The subthemes within, and supporting quotes, are described.

The use of digital means presents many opportunities for improving the provision of physical health interventions in mental health care settings. However, given the limited experience of many MHCPs with these technologies, formal training and additional support may improve the likelihood of implementation. Factors such as patient symptomatology, safety, and access to technology, as well as the readiness, acceptability, and capability of both MHCPs and patients to engage with digital tools, must also be considered. In addition, the potential benefits of data integration must be carefully weighed against the associated risks.

Pediatric obesity and comorbidities related to insulin resistance continue to be a growing public health crisis. If lifestyle measures are unsuccessful, pharmacological and surgical interventions are offered. In this paper, we describe the driving force of the obesity crisis: hyperinsulinemia and the development of insulin resistance. We give historical background of key policy issues which have contributed to this pandemic as well as the physiologic mechanisms of insulin resistance. The prevalence of obesity will continue to rise unless the root cause of hyperinsulinemia is addressed.

Current research on insulin resistance demonstrates that a decreased consumption of carbohydrates is an effective first-line dietary intervention for the treatment of obesity and related metabolic diseases. Evidence shows it is safe and beneficial. A low-carbohydrate eating pattern can be helpful to address pediatric obesity. However, there must be policy guardrails in place to ensure that this is a sustainable and viable option for children and their families. There must be a change in the nutritional environment to help individuals battle the chronic disease of obesity.

The association between birth weight and childhood body mass index (BMI) and frailty has been extensively studied, but it is currently unclear whether this relationship is causal.

We utilized a two-sample Mendelian randomization (MR) methodology to investigate the causal effects of birth weight and childhood BMI on the risk of frailty. Instrumental variables (p < 5E-08) strongly associated with own birth weight (N = 298,142 infants), offspring birth weight (N = 210,267 mothers), and childhood BMI (N = 39,620) were identified from large-scale genomic data from genome-wide association studies (GWAS). The frailty status was assessed using the frailty index, which was derived from comprehensive geriatric assessments of older adults within the UK Biobank and the TwinGene database (N = 175,226).

Genetically predicted one standard deviation (SD) increase in own birth weight, but not offspring birth weight (maternal-specific), was linked to a decreased frailty index (β per SD increase = -0.068, 95%CI = -0.106 to -0.030, p = 3.92E-04). Conversely, genetically predicted one SD increase in childhood BMI was associated with an elevated frailty index (β per SD increase = 0.080, 95%CI = 0.046 to 0.114, p = 3.43E-06) with good statistical power (99.8%). The findings remained consistent across sensitivity analyses and showed no horizontal pleiotropy (p > 0.05).

This MR study provides evidence supporting a causal relationship between lower birth weight, higher childhood BMI, and an increased risk of frailty.

The ketogenic diet (KD, also known as metabolic therapy) has been successful in the treatment of obesity, type 2 diabetes, and epilepsy. More recently, this treatment has shown promise in the treatment of psychiatric illness. We conducted a 4-month pilot study to investigate the effects of a KD on individuals with schizophrenia or bipolar disorder with existing metabolic abnormalities. Twenty-three participants were enrolled in a single-arm trial. Results showcased improvements in metabolic health, with no participants meeting metabolic syndrome criteria by study conclusion. Adherent individuals experienced significant reduction in weight (12 %), BMI (12 %), waist circumference (13 %), and visceral adipose tissue (36 %). Observed biomarker enhancements in this population include a 27 % decrease in HOMA-IR, and a 25 % drop in triglyceride levels. In psychiatric measurements, participants with schizophrenia showed a 32 % reduction in Brief Psychiatric Rating Scale scores. Overall Clinical Global Impression (CGI) severity improved by an average of 31 %, and the proportion of participants that started with elevated symptomatology improved at least 1-point on CGI (79 %). Psychiatric outcomes across the cohort encompassed increased life satisfaction (17 %) and enhanced sleep quality (19 %). This pilot trial underscores the potential advantages of adjunctive ketogenic dietary treatment in individuals grappling with serious mental illness.

Single measures of adiposity markers, such as body mass index (BMI) and waist circumference (WC), are associated with adverse mental health outcomes; however, long-term patterns of adiposity and their health effects remain unclear. The current study assessed adiposity trajectories during a 14-year span beyond middle age and their relevance to mental well-being in late life, and the contribution of genetic and lifestyle factors to the trajectories. Based on a nationally representative sample with longitudinal anthropometric measures, adiposity trajectories were identified by latent mixture modeling, and logistic regression model was used to estimate their associations with mental well-being, with adjustment for confounders. Of the 3491 eligible participants included (mean [SD] age, 69.5 [8.9] years), five discrete BMI and four WC trajectory patterns were identified over 14 years. Compared with the low-stable BMI group (range, 22.8 to 22.9 kg/m²; representing stable healthy body weight), the high-stable group (range, 34.3 to 35.4 kg/m²; stable obese) was associated with increased risk of depression (odds ratio [OR], 1.63; 95 % CI, 1.28-2.07) and low subjective well-being (OR, 1.35; 95 % CI, 1.02-1.79). Compared with the low-stable WC group (range, 75 to 79 cm healthy WC), the high-increasing group (range, 114 to 121 cm) was associated with increased risk of depression (odds ratio [OR], 1.64; 95 % CI, 1.19-2.25) and low well-being (OR, 1.48; 95 % CI, 1.01-2.16). The adiposity trajectories, especially the high-stable/increasing groups, were driven by genetic factors in a dose-response manner, whereas the high/moderate-increasing groups were also behaviorally related. This longitudinal cohort study reveals that stably high trajectory patterns of central and general adiposity during middle age were associated with higher risk of depression and low well-being in late life. The findings indicate the importance of weight management beyond middle age, such as adherence to a healthy lifestyle, in promoting mental health and well-being.

Depression is a global health priority. Maintaining and delaying depressive symptoms in older adults is a key to healthy aging. This study aimed to identify depressive symptom trajectories, predictors and mortality, while also exploring the relationship between air quality and depressive symptoms in older adults in the Hong Kong community over 14 years.

This study is a longitudinal study in Hong Kong. The target population was community-dwelling older adults over age 65. Depressive symptoms were measured by the Geriatric Depression Scale (GDS-15). Group-based trajectory model was used to identify heterogeneity in longitudinal changes over 14 years and examine the associations between baseline variables and trajectories for different cohort members using multinomial logistic regression. The Kaplan-Meier method was employed to conduct survival analysis and explore the variations in survival probabilities over time among different trajectory group. Linear mixed model was used to explore the relationship between air quality and depressive symptoms.

A total of 2828 older adults were included. Three different trajectories of depressive symptoms in older people were identified: relatively stable (15.4%), late increase (67.1%) and increase (17.5%). Female, more number of chronic diseases, poor cognitive function, and poor health-related quality of life (HRQOL) were significantly associated with other less favorable trajectories compared with participants with stable levels of depressive symptoms. The late increase group had a lower mortality rate than the relatively stable and increased groups. Lower baseline ambient air pollutant exposure to NO2 over 14 years was significantly associated with fewer depressive symptoms.

In this study, we found that a late increase in depressive symptoms was the predominant trend in older Chinese people in Hong Kong. Poorer HRQOL was predictive of less favorable trajectories of depressive symptoms. Ambient air pollution was associated with depressive symptoms. This novel observation strengthens the epidemiological evidence of longitudinal changes in depressive symptoms and associations with late-life exposure to air pollution.

To systematically review studies evaluating pharmacological treatment intervention of the atypical antipsychotic induced weight gain in the pediatric population and summarize the current evidence of the pharmacological treatment. According to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, we searched the various databases Medline, PubMed, PubMed central (PMC), CINAHL, and clinicaltrial.gov. until Jan 30th, 2022 for relevant clinical studies. Medical subject heading (MeSH) terms or keywords were used, "Body Weight," "Weight Gain," "Weight Loss," "Body Weight Maintenance," "Pediatric Obesity" in "Pediatrics," "Adolescent," "Child" in context of "Antipsychotic Agents" and "Drug Therapy," "Therapeutics," "Treatment Outcome," "Early Medical Intervention." We used the PICO algorithm for our search (Population, Intervention, Comparison, Outcomes, and Study Design) framework. The initial search included 746 articles, nine studies were ultimately selected in the final qualitative review. We included relevant clinical reviews, case series, and randomized clinical trials that evaluated pharmacological intervention for antipsychotic-induced weight gain in the pediatric population. Non-peer-reviewed, non-human, non-English languages article was excluded. Metformin is the most studied medication for antipsychotic-induced weight gain in children. Three studies have shown that adding Metformin to the antipsychotics can significantly reduce the body weight and body mass index with mild transient side effects. Other adjunct medications like topiramate, amantadine, betahistine, or melatonin vary greatly in mitigating weight with various side effects. Lifestyle modification is the first step in dealing with AIWG, but the result is inconsistent. Avoiding the use of antipsychotic in children is preferred. Adding an adjuvant medication to the antipsychotic could prevent or mitigate their negative metabolic effect on the body weight and body mass index. Metformin has the most evidence, topiramate, betahistine, amantadine, and melatonin is possible alternatives in the pediatric patient without changing their antipsychotic medication. Other viable options show some benefits but need further clinical studies to establish efficacy and safety.

The aim of this study was to examine BMI trajectories from birth throughout childhood, associations with health outcomes at age 13 years, and time frames during which early-life BMI influenced adolescent health.

Participants (1902, 44% male) reported perceived stress and psychosomatic symptoms and were examined for waist circumference (WC), systolic blood pressure (SBP), pulse wave velocity, and white blood cell counts (WBC). BMI trajectory was analyzed using group-based trajectory modeling of retrospective data of weight/height from birth throughout childhood. The authors performed linear regression to assess associations between BMI trajectories and health outcomes at age 13 years, presented as estimated mean differences with 95% CI among trajectories.

Three BMI trajectories were identified: normal; moderate; and excessive gain. Adjusting for covariates, adolescents with excessive gain had higher WC (19.2 [95% CI: 18.4-20.0] cm), SBP (3.6 [95% CI: 2.4-4.4] mm Hg), WBC (0.7 [95% CI: 0.4-0.9] × 109 /L), and stress (1.1 [95% CI: 0.2-1.9]) than adolescents with normal gain. Higher WC (6.4 [95% CI: 5.8-6.9] cm), SBP (1.8 [95% CI: 1.0-2.5] mm Hg), and stress (0.7 [95% CI: 0.1-1.2]) were found in adolescents with moderate versus normal gain. The association of early-life BMI with SBP started around age 6 years with the excessive gain group, which was earlier than in the normal and moderate gain groups, in which it started at age 12 years.

An excessive gain BMI trajectory from birth predicts cardiometabolic risk and stress in 13-year-old individuals.

Psychiatric patients are at high risk of readmission, and a high body mass index has previously been shown as a risk factor. We sought to replicate this finding and 1) to prospectively assess the association of metabolic syndrome and its five components with readmission in psychiatric hospitals and 2) to identify other clinical and sociodemographic predictors of readmission.

Between 2007 and 2019, data on 16727 admissions of 7786 adult and elderly patients admitted to the Department of Psychiatry of the Lausanne University Hospital, were collected. Metabolic syndrome was defined according to the International Diabetes Federation definition. Cox frailty models were used to investigate the associations between readmission and metabolic disturbances.

A total of 2697 (35%) patients were readmitted to our psychiatric hospital. Novel risk factors for readmission in non-smokers were identified, including being overweight (HR=1.26; 95%CI=[1.05; 1.51]) or obese (HR=1.33; 95%CI=[1.08; 1.62]), displaying hypertriglyceridemia (HR=1.21; 95%CI=[1.04; 1.40]) and metabolic syndrome (HR=1.26; 95%CI=[1.02; 1.55]). Central obesity and hyperglycemia increased the risk of readmission when considering the Health of the Nation Outcome Scales variable. In first-episode psychosis patients, obesity (HR=2.23; 95%CI=[1.14; 4.30]) and high-density lipoprotein hypocholesterolemia (HR=1.90; 95%CI=[1.14; 3.20]) doubled the risk of readmission.

The observed interaction between smoking and metabolic variables are compatible with a ceiling effect; metabolic variables increase the risk of readmission in non-smokers but not in smokers who are already at higher risk. Future studies should determine whether better metabolic monitoring and treatment can reduce readmission risk.

Exposure to heavy metals considered a major risk factor for mental health.

Examining how heavy metals in blood are associated with depression in individuals of various body mass indexes.

A total sample of 15,560 individuals was screened, with 4355 participants finally enrolled to study. The PHQ-9 was used to assess participants' depressive symptoms.

A logistic regression analysis was used to investigate the relationship between the levels of heavy metals in the blood and the depression. Serum cadmium levels were found to be associated with risk of depression, with an odds ratio of 2.247 (95 % CI: 1.584-3.244). However, no significant correlations were observed between depression and blood levels of lead, selenium, and manganese. Subgroup analysis was performed and found that higher Cd concentrations were associated with a greater risk of depression at the same BMI. With the same Cd concentration, the risk of depression was lowest when participants' BMI was ≥30 kg/m2 and increased with increasing BMI when participants' BMI was <30 kg/m2.

It is not possible to analyze the effect of external exposure to Cd.

Cd in blood may be positively correlated with depression in American adults, and the effect of this trend is different in people with different body mass indices. With the increase in BMI, the risk gradually rises. However, it is lowest among obese people.

The aim of this study was to explore prospective relationships between changing patterns of BMI/waist to height ratio (WHtR) during adolescence and subsequent neurobehavioral development.

In this prospective cohort study, randomized stratified sampling was used to recruit six middle schools and 609 students in Shanghai, China. In Grades 6, 7, and 9, the Youth Self Report scale was used to assess student neurobehavioral status and anthropometric measurements were conducted to calculate BMI z scores and WHtRs. Longitudinal data were analyzed using latent class mixture modeling to delineate trajectories of BMI z scores ("stable," "decreasing," "rapidly increasing") and WHtRs ("stable," "rapidly increasing"), and their associations with neurobehavioral status in Grade 9 were assessed.

In Grades 6 through 9 (ages 11-15 years), the prevalence of overall obesity and abdominal obesity ranged from 10.7% to 13.0% and 13.0% to 19.8%, respectively. Compared with the stable BMI z score trajectory, the rapidly increasing BMI z score trajectory was longitudinally associated with delinquent behavior, aggressive behavior, and externalizing problems (incidence rate ratio: 1.564-1.613, adjusted p < 0.05). Compared with the stable WHtR trajectory, the rapidly increasing WHtR trajectory significantly predicted increased risks of social problems and delinquent behavior (incidence rate ratios: 1.776-1.967, adjusted p < 0.05). Significant associations of the rapidly increasing BMI z score/WHtR trajectories with subsequent neurobehavioral deficits were observed among girls (adjusted p < 0.05) but not among boys (adjusted p > 0.05).

Rapid increases in BMI or WHtR during adolescence could predict subsequent neurobehavioral deficits, especially for externalizing behaviors. Timely intervention for weight control may be considered to promote adolescent mental health.

Accumulating evidence suggests individuals with psychotic disorder show abnormalities in metabolic and inflammatory processes. Recently, several studies have employed blood-based predictors in models predicting transition to psychotic disorder in risk-enriched populations. A systematic review of the performance and methodology of prognostic models using blood-based biomarkers in the prediction of psychotic disorder from risk-enriched populations is warranted. Databases (PubMed, EMBASE and PsycINFO) were searched for eligible texts from 1998 to 15/05/2023, which detailed model development or validation studies. The checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) was used to guide data extraction from eligible texts and the Prediction Model Risk of Bias Assessment Tool (PROBAST) was used to assess the risk of bias and applicability of the studies. A narrative synthesis of the included studies was performed. Seventeen eligible studies were identified: 16 eligible model development studies and one eligible model validation study. A wide range of biomarkers were assessed, including nucleic acids, proteins, metabolites, and lipids. The range of C-index (area under the curve) estimates reported for the models was 0.67-1.00. No studies assessed model calibration. According to PROBAST criteria, all studies were at high risk of bias in the analysis domain. While a wide range of potentially predictive biomarkers were identified in the included studies, most studies did not account for overfitting in model performance estimates, no studies assessed calibration, and all models were at high risk of bias according to PROBAST criteria. External validation of the models is needed to provide more accurate estimates of their performance. Future studies which follow the latest available methodological and reporting guidelines and adopt strategies to accommodate required sample sizes for model development or validation will clarify the value of including blood-based biomarkers in models predicting psychosis.

This retrospective cohort study aimed to identify the cardiometabolic characteristics, cross-sectionally and longitudinally, associated with clinical stage in youth accessing early intervention mental health services.

Cardiometabolic data we collected in 511 young people (aged 12-25 years at entry) receiving mental health care at the early intervention services in Sydney, Australia.

The majority of young people (N = 448, 87.67%) were classified in stage 1a or 1b at entry. At entry to care, there was no cross-sectional relationship between clinical stage and age, gender, fasting insulin, fasting glucose, updated homeostatic model assessment for insulin resistance (HOMA2-IR) score, BMI or waist circumference. Of the 111 (21.7%) young people initially classified at stage 1a ('non-specific symptoms') and the 337 (65.9%) classified in stage 1b ('attenuated syndromes'), 40 individuals transitioned to stage 2+ (7.8%) ("full-threshold disorders") longitudinally. No cardiometabolic factors predicted clinical stage transitions. However, those with an increase in BMI over the course of care (n = 54) were 1.46 (OR; 95% CI: 1.02-2.17) times more likely to progress to stage 2+ at follow up.

Whilst no relationships were found between demographic or cardiometabolic variables and clinical stage at entry to care, an increased BMI over time was associated with clinical stage transition longitudinally. Further longitudinal research is needed to understand the demographic, clinical, illness progression or treatment factors associated with changes in cardiometabolic status.

Nearly 40% of US youth aged 2 to 19 years do not have a body mass index (BMI) in the healthy weight category. However, there are no recent estimates for BMI-associated expenditures using clinical or claims data.

To estimate medical expenditures among US youth across all BMI categories along with sex and age groups.

This cross-sectional study used IQVIA's ambulatory electronic medical records (AEMR) data set linked with IQVIA's PharMetrics Plus Claims database from January 2018 through December 2018. Analysis was performed from March 25, 2022, through June 20, 2022. It included a convenience sample of a geographically diverse patient population from AEMR and PharMetrics Plus. The study sample included privately insured individuals with a BMI measurement in 2018 and excluded patients with pregnancy-related visits.

BMI categories.

Total medical expenditures were estimated using generalized linear model regression with γ distribution and log-link function. For out-of-pocket (OOP) expenditures, a 2-part model was used that included logistic regression to estimate the probability of positive expenditures followed by generalized linear model. Estimates were shown with and without accounting for sex, race and ethnicity, payer type, geographic region, age interacted with sex and BMI categories, and confounding conditions.

The sample included 205 876 individuals aged 2 to 19 years; 104 066 were male (50.5%) and the median age was 12 years. Compared with those with healthy weight, total and OOP expenditures were higher for all other BMI categories. Differences in total expenditures were highest for those with severe obesity ($909; 95% CI, $600-$1218) followed by underweight ($671; 95% CI, $286-$1055) compared with healthy weight. Differences in OOP expenditures were highest for those with severe obesity ($121; 95% CI, $86-$155) followed by underweight ($117; 95% CI, $78-$157) compared with healthy weight. Having underweight was associated with higher total expenditures at ages 2 to 5 years and 6 to 11 years by $679 (95% CI, $228-$1129) and $1166 (95% CI, $632-$1700), respectively; having severe obesity was associated with higher total expenditures at ages 2 to 5 years, 6 to 11 years, and 12 to 17 years by $1035 (95% CI, $208-$1863), $821 (95% CI, $414-$1227), and $1088 (95% CI, $594-$1582), respectively.

The study team found medical expenditures to be higher for all BMI categories when compared with those with healthy weight. These findings may indicate potential economic value of interventions or treatments aimed at reducing BMI-associated health risks.

Obesity is a risk factor for multimorbidity, including depression and possibly anxiety. However, it is currently unclear how patterns of change in BMI over the life course differentially influence the magnitude in risk of depression and anxiety in mid-adulthood. We aimed to examine associations between BMI trajectories from childhood to adulthood and the risk of depression and anxiety in middle age.

In the Tasmanian Longitudinal Health Study (n = 2416), five distinct BMI trajectories were previously defined from age 5 to 45 years using group-based modelling. At age 53, current depression and anxiety were assessed using the Patient Health Questionnaire and the Generalized Anxiety Disorder scale, respectively. Logistic regression models adjusted for potential confounders estimated associations between BMI trajectories and these outcomes.

Those belonging to the child average-increasing (OR = 2.24; 95%CI: 1.24, 4.06) and persistently high (OR = 2.64; 1.26, 5.52) trajectories were more likely to have depression in middle age, compared to the persistently average trajectory. However, the odds of experiencing greater severity of depressive symptoms was highest in the child average-increasing group (OR = 2.36; 1.59, 3.49). Despite finding no evidence of association between BMI trajectories and current anxiety, we observed less severe symptoms in the child high-decreasing trajectory (OR = 0.68; 0.51, 0.91).

We found an increased risk of depression in middle age among individuals with a persistently high BMI from childhood to mid-adulthood and individuals with an average BMI in childhood which then increased consistently throughout adulthood. Encouragingly, resolving childhood adiposity by adulthood was associated with lesser anxiety symptoms. Taken together, these findings highlight the need to target mental health screening and treatment towards high-risk BMI trajectory groups and the importance of early interventions to prevent and resolve excess weight.

This review aimed to evaluate the effects of weight change from childhood to adulthood on depression and/or anxiety risk in adulthood. We systematically searched MEDLINE, PsychINFO, Embase, Cumulative Index to Nursing and Allied Health Literature, and Scopus for longitudinal studies assessing changes in weight status between childhood (≤18 years) and adulthood (≥19 years) in association with outcomes of depression and/or anxiety in adulthood. Study quality was assessed using a modified version of the Newcastle-Ottawa Scale, and data were narratively synthesized. Seventeen articles met our inclusion criteria: 13 evaluated outcomes of depression, one evaluated outcomes of anxiety, and five evaluated composite measures of depression and anxiety. Evidence was most consistent regarding outcomes of depression, with most finding that persistent and/or increasing adiposity from childhood to adulthood is associated with an increased risk of depression, particularly in women. However, heterogeneity and limitations in the evidence preclude definitive conclusions and inconsistent findings were reported in the few studies that assessed anxiety and composite outcomes. Overall, it appears that early intervention to both prevent or resolve excess weight may aid in reducing the burden of depression, along with mental health support targeting adolescents with persistent and/or increasing adiposity. However, further high-quality research is needed to address the methodological limitations discussed.

Background: Individuals with a diagnosis of schizophrenia are known to be at high risk of premature mortality due to poor physical health, especially cardiovascular disease, diabetes, and obesity. The reasons for these physical health outcomes within this patient population are complex. Despite well-documented cardiometabolic adverse effects of certain antipsychotic drugs and lifestyle factors, schizophrenia may have an independent effect. Aims: To investigate if there is evidence that schizophrenia is causally related to cardiometabolic traits (blood lipids, anthropometric traits, glycaemic traits, blood pressure) and vice versa using bi-directional two-sample Mendelian randomization (MR) analysis. Methods: We used 185 genetic variants associated with schizophrenia from the latest Psychiatric Genomics Consortium GWAS (n = 130,644) in the forward analysis (schizophrenia to cardiometabolic traits) and genetic variants associated with the cardiometabolic traits from various consortia in the reverse analysis (cardiometabolic traits to schizophrenia), both at genome-wide significance (5 × 10-8). The primary method was inverse-variance weighted MR, supported by supplementary methods such as MR-Egger, as well as median and mode-based methods. Results: In the forward analysis, schizophrenia was associated with slightly higher low-density lipoprotein (LDL) cholesterol levels (0.013 SD change in LDL per log odds increase in schizophrenia risk, 95% CI, 0.001-0.024 SD; p = 0.027) and total cholesterol levels (0.013 SD change in total cholesterol per log odds increase in schizophrenia risk, 95% CI, 0.002-0.025 SD; p = 0.023). However, these associations did not survive multiple testing corrections. There was no evidence of a causal effect of cardiometabolic traits on schizophrenia in the reverse analysis. Discussion: Dyslipidemia and obesity in schizophrenia patients are unlikely to be driven primarily by schizophrenia itself. Therefore, lifestyle, diet, antipsychotic drugs side effects, as well as shared mechanisms for metabolic dysfunction and schizophrenia such as low-grade systemic inflammation could be possible reasons for the apparent increased risk of metabolic disease in people with schizophrenia. Further research is needed to examine the shared immune mechanism hypothesis.

To evaluate the changes in mental health, quality of life (QOL) and physical activity (PA) among adolescent athletes during the COVID-19 pandemic as organised sports resumed.

Adolescent athletes completed surveys including demographic and sport participation information, 7-item Generalized Anxiety Disorder, 9-item Patient Health Questionnaire, Pediatric Quality of Life Inventory and the Hospital for Special Surgery Pediatric Functional Activity Brief Scale in May 2020 following COVID-19-related sport cancellations (Spring20) and after returning to sports in May 2021 (Spring21). The groups were balanced by inverse propensity score weighting and compared using analysis of variance models and ordinal regression models.

17 421 participants were included (Spring20=13 002; Spring21=4419; 16.2±1.2 years; 53% female). Anxiety was significantly lower (better) in Spring21 (Spring20=7.0, 95% CI 6.9 to 7.1; Spring21=4.9, 95% CI 4.8 to 5.0, p<0.001), as was the prevalence of moderate to severe anxiety (Spring20=29.4%, Spring21=17.1%, p<0.001). Depression was significantly improved in Spring21 (Spring20=7.6, 95% CI 7.5 to 7.7; Spring21=4.6, 95% CI 4.5 to 4.8, p<0.001), as was the prevalence of moderate to severe depression (Spring20=32.2%, Spring21=15.4%, p<0.001). Athletes in Spring21 reported higher QOL (Spring20=79.6, 95% CI 79.3 to 79.9; Spring21=84.7, 95% CI 84.4 to 85.0, p<0.001) and increased levels of PA (Spring20=13.8, 95% CI 13.6 to 13.9; Spring21=22.7, 95% CI 22.6 to 22.9, p<0.001).

Early COVID-19 sports restrictions were associated with worsening mental health in adolescents. In 2021, after returning to sports, athletes reported significant improvements in mental health, QOL and PA, although mental health adversities remain an important priority.

This perspective article applies public health principles to improve the physical health of selected populations with mental disorders. Two preventable adverse outcomes, poorer physical health and premature mortality, are described across mental disorders. Evidence of the lifetime effects of adverse childhood experiences and inequalities is presented: these are the 'causes of the causes'. Seven drivers of physical disorders are illustrated that drive preventable deaths and as doctors, psychiatrists must lead from the front to reverse rising mortality. Evidence supports universal and selective interventions and even the most difficult challenges such as weight gain and opioid misuse are an opportunity for psychiatry to engage with individual patients and their organisations, public health colleagues, health systems and beyond. Interventions complement and do not replace existing clinical practices that reduce self-harm and prevent suicide. Mental health teams already do most of the work in this arena, and the case is made to refocus on physical health with task sharing. The top 10 recommendations within a personalised medicine framework are listed in this paper as a starting point.

Metformin is a medication likely to improve measures of cardiometabolic disturbance in young people with mental illness. Evidence also suggests metformin may improve depressive symptoms. This 52-week double-blind randomised control trial (RCT) aims to investigate the efficacy of metformin pharmacotherapy as an adjunct to a healthy lifestyle behavioural intervention in improving cardiometabolic outcomes, and depressive, anxiety and psychotic symptoms in youth with clinically diagnosed major mood syndromes.

At least 266 young people aged 16-25 presenting for mental healthcare for major mood syndromes who are also at risk for poor cardiometabolic outcomes will be invited to participate in this study. All participants will engage in a 12-week sleep-wake, activity and metabolically focused behavioural intervention programme. As an adjunctive intervention, participants will receive either metformin (500-1000 mg) or placebo pharmacotherapy for 52 weeks.Participants will undergo a series of assessments including: (1) self-report and clinician-administered assessments; (2) blood tests; (3) anthropometric assessments (height, weight, waist circumference and blood pressure); and (4) actigraphy. Univariate and multivariate tests (generalised mixed-effects models) will be used to examine changes in primary and secondary outcomes (and associations with predetermined predictor variables).

This study has been approved by the Sydney Local Health District Research Ethics and Governance Office (X22-0017). The results of this double-blind RCT will be disseminated into the scientific and broader community through peer-reviewed journals, conference presentations, social media and university websites.

Australian New Zealand Clinical Trials Registry (ANZCTR) Number: ACTRN12619001559101p, 12 November 2019.

Psychotic-like experiences (PLEs) constitute subthreshold symptoms of psychotic disorders, and belong to five distinct dimensions: Positive, Negative, Depressive, Mania and Disorganization. PLEs are associated with various psychiatric disorders. However, few studies examined their association with physical disorders.

Our aims were (1) to assess the associations between various physical disorders and PLEs in a U.S. representative sample, and (2) to examine these associations according to the five dimensions of PLEs.

We used data from the wave II (2004-2005) of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC-II), a large national sample representative of the US population (N = 34,653). Participants were assessed with the Alcohol Use Disorder and Associated Disabilities Interview Schedule 4. Twenty-two PLEs were examined. Lifetime prevalence and adjusted Odds-Ratio (aOR) reflecting the association of sixteen physical disorders (including notably metabolic conditions and heart diseases) with PLEs were calculated.

All studied physical disorders were associated with the presence of PLEs. Particularly the presence of any physical condition, any heart disease and diabetes were more frequent in participants with at least one PLE compared with the group without any PLE (aOR = 1.74, 95% CI = 1.62-1.87, aOR = 1.44, 95% CI = 1.33-1.55 and aOR = 1.38, 95% CI = 1.24-1.54, respectively). Almost all physical disorders were associated with the five dimensions of PLEs.

PLEs were associated with a large range of physical disorders, with a gradual dose effect. To assess PLEs in the general population could help with the screening of subjects with physical disorders.

This study aimed to identify body mass index (BMI) trajectories from childhood and their relationships with depression, anxiety, and stress symptoms in young adulthood. A total of 687 children aged 4-18 years were recruited from the Tehran Lipid and Glucose Study. Throughout 18 years of follow-up, BMI was measured every 3 years for a maximum of 6 data points. Participants completed the depression, anxiety, and stress scale in their young adulthood (aged 22-36). The group-based trajectory modelling was applied to identify BMI patterns. The logistic regression model was used to assess the association between BMI trajectories and depression, anxiety, and stress symptoms in adulthood. Two BMI trajectories were identified from childhood to young adulthood: healthy weight (HW = 69.6%) and persistent increasing overweight/obesity (PIO = 30.4%). After adjusting for potential confounders, compared with the HW group, men in the PIO group were more likely to experience higher stress levels (OR: 1.62, 95% CI: 0.99-2.63; p = 0.05). No significant association was observed between the PIO trajectory and depression and anxiety among both sexes and stress symptoms in females. Our results highlight that developing overweight and obesity from childhood may be related to increased stress in males.

Cardiometabolic dysfunction is common in young people with psychosis. Recently, the Psychosis Metabolic Risk Calculator (PsyMetRiC) was developed and externally validated in the UK, predicting up-to six-year risk of metabolic syndrome (MetS) from routinely collected data. The full-model includes age, sex, ethnicity, body-mass index, smoking status, prescription of metabolically-active antipsychotic medication, high-density lipoprotein, and triglyceride concentrations; the partial-model excludes biochemical predictors.

To move toward a future internationally-useful tool, we externally validated PsyMetRiC in two independent European samples. We used data from the PsyMetab (Lausanne, Switzerland) and PAFIP (Cantabria, Spain) cohorts, including participants aged 16-35y without MetS at baseline who had 1-6y follow-up. Predictive performance was assessed primarily via discrimination (C-statistic), calibration (calibration plots), and decision curve analysis. Site-specific recalibration was considered.

We included 1024 participants (PsyMetab n=558, male=62%, outcome prevalence=19%, mean follow-up=2.48y; PAFIP n=466, male=65%, outcome prevalence=14%, mean follow-up=2.59y). Discrimination was better in the full- compared with partial-model (PsyMetab=full-model C=0.73, 95% C.I., 0.68-0.79, partial-model C=0.68, 95% C.I., 0.62-0.74; PAFIP=full-model C=0.72, 95% C.I., 0.66-0.78; partial-model C=0.66, 95% C.I., 0.60-0.71). As expected, calibration plots revealed varying degrees of miscalibration, which recovered following site-specific recalibration. PsyMetRiC showed net benefit in both new cohorts, more so after recalibration.

The study provides evidence of PsyMetRiC's generalizability in Western Europe, although further local and international validation studies are required. In future, PsyMetRiC could help clinicians internationally to identify young people with psychosis who are at higher cardiometabolic risk, so interventions can be directed effectively to reduce long-term morbidity and mortality.

NIHR Cambridge Biomedical Research Centre (BRC-1215-20014); The Wellcome Trust (201486/Z/16/Z); Swiss National Research Foundation (320030-120686, 324730- 144064, and 320030-173211); The Carlos III Health Institute (CM20/00015, FIS00/3095, PI020499, PI050427, and PI060507); IDIVAL (INT/A21/10 and INT/A20/04); The Andalusian Regional Government (A1-0055-2020 and A1-0005-2021); SENY Fundacion Research (2005-0308007); Fundacion Marques de Valdecilla (A/02/07, API07/011); Ministry of Economy and Competitiveness and the European Fund for Regional Development (SAF2016-76046-R and SAF2013-46292-R).For the Spanish and French translation of the abstract see Supplementary Materials section.

Abnormal glucose and lipid metabolism is common in antipsychotic-naive first-episode patients with schizophrenia, but it is unclear whether these changes can already be seen in premorbid or prodromal period, before the first psychotic episode. We examined insulin, total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, and triglyceride trajectories in children and adolescents (9-18 years old), who were later diagnosed with schizophrenia, any non-affective psychosis (NAP) or affective disorder (AD). The study population consisted of a general population-based cohort "The Cardiovascular Risk in Young Finns Study", started in 1980 (n = 3596). Psychiatric diagnoses were derived from the Health Care Register up to the year 2018. Multivariate statistical analysis indicated no significant differences in insulin or lipid levels in children and adolescents who later developed schizophrenia (n = 41) compared to the cohort control group (n = 3202). In addition, no changes in these parameters were seen in the NAP (n = 74) or AD (n = 156) groups compared to the controls, but lower triglyceride levels in childhood/adolescence associated with earlier diagnosis of psychotic disorder in the NAP group. Taken together, our results do not support any gross-level insulin or lipid changes during childhood and adolescence in individuals with later diagnosis of schizophrenia-spectrum disorder. Since changes in glucose and lipid metabolism can be observed in neuroleptic-naive patients with schizophrenia, we hypothesize that the more marked metabolic changes develop during the prodrome closer to the onset of the first psychotic episode. The findings have relevance for studies on developmental hypotheses of schizophrenia.