Psychosocial factors represent modifiable targets relevant to alleviate depression risk. While individual psychosocial risks are well-documented, their combined status across multiple life domains is underexplored. We aimed to construct a novel multidimensional composite score of psychosocial status and explore its association with incidence of depression.

A total of 336,922 individuals (mean age 56.21 years) without depression at baseline from the UK Biobank were included. Psychosocial status was assessed across four dimensions (recent stressful events, current psychiatric symptoms, social contact and socio-economic status) using 18 factors. A composite psychosocial score was constructed by weight effect of each factor, with higher values indicating lower level of psychosocial status. Using Cox proportional hazards models to evaluate the associations between individual psychosocial factor, psychosocial score and the risk of depression.

During a median follow-up of 13.60 years, 14,806 depression cases were identified. Low household income, recent depressive symptoms, loneliness and financial difficulties emerged as the most significant predictors of depression across four domains, with hazard ratios (HRs) of 3.82 (95% confidence intervals [CIs]: 3.43–4.26), 3.09 (2.99–3.19), 2.46 (2.37–2.54) and 1.96 (1.88–2.04), respectively. Each one-point increase in the psychosocial score was associated with a 42% higher depression risk. Compared to individuals with high psychosocial status, those in the medium- and low-level groups had an adjusted HR of 1.71 (95% CI: 1.62–1.81) and 4.36 (95% CI: 4.15–4.58), respectively.

These findings highlight that psychosocial factors collectively represent modifiable targets for preventing depression, with interventions addressing the combined status of these domains likely offering greater impact than focusing on isolated factors.

Disclosure of a mental health problem carries both risks and benefits. It can be seen as a measure of perceptions of the social environment in which people with mental health problems live, work and study. A nationally representative Australian survey conducted in 2014 showed that, in many settings, non-disclosure was more common than disclosure. This study aimed to investigate whether disclosure in a broad range of settings has changed since the 2014 national survey.

Large nationally representative surveys of Australian adults were conducted in 2014 and 2024. For each, those who reported a mental health problem or were experiencing high psychological distress (n = 1381 in 2014, n = 2613 in 2024) were asked about disclosure in multiple settings. Regression analyses were used to explore whether changes between survey years were significant at p < 0.01, adjusting for sociodemographic variables of age, gender, education level, language spoken at home, country of birth and type of mental health problem. Secondary analyses assessed the sociodemographic and mental health problem characteristics associated with changes.

In 2024, participants were less likely than in 2014 to have disclosed to friends, partners, family members and some people in the neighbourhood, with relative risk ratios (RRRs) ranging from 0.33 (99% confidence interval [CI]: 0.23, 0.48; p < 0.001) for all family members to 0.64 (99% CI: 0.46, 0.88; p < 0.001) for some people in the neighbourhood. Workplace disclosure did not change significantly. For health professionals not involved in mental health treatment, the RRRs of disclosure were higher in 2024 than in 2014 (RRR = 1.56 [99% CI: 1.16, 2.10; p < 0.001] for disclosure to some and RRR = 2.31 [99% CI: 1.61, 3.32; p < 0.001] for disclosure to all).

Except for disclosure to health professionals not involved in mental health treatment, there have been decreases or no changes in disclosure of a mental health problem in most settings over the last 10 years. This likely reflects both perceptions of, and actual, reductions in supportive social environments. Urgent action is needed to ensure that, for people who do disclose a mental health problem, the benefits strongly outweigh the risks.

This study aims to examine the longitudinal associations between work–family conflict (WFC) and mental health among working parents. Specifically, we investigated whether within-person changes in WFC and family-to-work conflict (FWC) are associated with changes in mental health.

Data from the Household, Income and Labour Dynamics in Australia survey were used to employ within-person fixed effects regression analysis to examine associations between WFC and mental health in working-age adults (18–64 years) with parental responsibilities for children ≤14 years. The outcome, general mental health and overall psychological well-being, was assessed using the Mental Health Inventory-5 scale as a continuous variable with scores ranging from 0 to 100. Both dimensions of WFC, measured as continuous variables ranging from 1 to 7 with higher scores indicative of greater conflict (work-to-family and family-to-work), were interrogated, as were gender differences. Exposures, outcome and covariates were assessed repeatedly across the 21-year follow-up period.

A total of 7,265 participants (46,564 observations) across waves 2001–2021 who were working-age parents engaged in paid employment with children ≤14 years, with at least two waves of data and non-missing data were included in the analyses. Mean (SD) duration of follow-up was 6.1 (3.7) years and 6.7 (4.2) years for mothers and fathers, respectively. A total of 49.6% of participants were female, and the mean baseline age was 35 years for both mothers and fathers. Increasing WFC was negatively associated with mental health in women (β coefficient = −1.25 [95% CI: −1.45, −1.05]) and men (β coefficient = −1.21 [95% CI: −1.40, −1.02]). Increasing FWC was associated with worse mental health in women (β coefficient = −1.09 [95% CI: −1.33, −0.85]) and men (β coefficient = −1.51 [95% CI: −1.75, −1.28]).

Changes in both WFC and FWC over time are associated with changes in mental health for women and men. More attention needs to be devoted to identifying and implementing strategies to enable working parents to cope with or reduce WFC.

The risk of cognitive decline after losing a spouse remained mixed. This study aims to investigate the association between spousal loss and risk of cognitive decline, assess whether this association varies by sex and age, and identify modifiable factors.

We conducted a prospective cohort study using harmonized data from six population-based ageing surveys: the US Health and Retirement Study and its sister surveys in England, Mexico, China, India and South Africa, incorporating their respective Harmonized Cognitive Assessment Protocol (HCAP) sub-studies. Spousal loss (yes vs no) was the exposure. Cognitive outcomes (i.e., orientation, memory, executive function and language) were assessed using HCAP neuropsychological batteries. We conducted parallel analyses in six cohorts. Associations between spousal loss and cognitive outcomes were estimated using generalized linear models, and summarised estimates were derived via random-effects meta-analyses. Sex stratification and restricted cubic splines were used to examine how these associations vary by sex and age, respectively.

The analytical cohort consisted of 18,551 individuals aged 61.39 (6.40) to 71.06 (7.22) years. Widowhood prevalence ranged from 14.1% in the China Health and Retirement Longitudinal Study to 53.9% in Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa (HAALSI). Spousal loss was associated with poorer memory (multivariable-adjusted β = −0.07, 95% confidence interval [CI]: −0.12 to −0.01) and executive function (multivariable-adjusted β = −0.08, 95% CI: −0.13 to −0.03) in the meta-analysis, with no significant associations for orientation or language. While results were generally consistent in five cohorts, the English Longitudinal Study of Ageing (ELSA) showed divergent patterns (orientation: β = 0.10, 95% CI: 0.06–0.13; memory: β = 0.05, 95% CI: 0.02–0.08; language: β = 0.16, 95% CI: 0.12–0.19). Sex-stratified analyses indicated poorer executive function among men (multivariable-adjusted β = −0.14, 95% CI: −0.19 to −0.08) and poorer memory among women (multivariable-adjusted β = −0.07, 95% CI: −0.14 to −0.01) following widowhood. Nonlinear age-related effects on cognition were observed in ELSA, Longitudinal Ageing Study in India, and HAALSI. Higher education, internet use and body mass index were negatively associated with the risk of cognitive decline among widowed participants.

Spousal loss is associated with domain- and sex-specific differences in cognitive performance, with substantial heterogeneity across study populations. Future research should integrate biopsychosocial markers to develop context-sensitive interventions for widowed older adults.

To systematically identify and prioritize age- and sex-specific modifiable risk factors for incident depression, and to characterize integrated risk patterns to pinpoint high-risk populations across different life stages.

Using data from 428,078 participants in a cohort, incident depression was identified using hospital records. Cox proportional hazards models were applied to assess age- (the middle-aged, quinquagenarian and the elderly) and sex-specific (females and males) associations between modifiable risk factors and depression incidence. Population-attributable fractions (PAFs) prioritized predominant factors, and self-organizing maps (SOMs) visualized integrated risk patterns. Mendelian randomization (MR) analyses examined potential causal associations between top-ranked factors and depression risk.

During a mean follow-up of 13.11 years, 15,106 (3.53%) participants developed depression. Hazard ratios for modifiable factors were similar between sexes but varied by age. Generally, the overall PAFs decreased with age (PAF of 83.47% in the middle-aged, 82.96% in the quinquagenarian and 76.77% in the elderly). Health-related factors consistently showed the highest PAFs (33.46–38.12%) across all age subgroups and females, driven by weak grip strength (12.60–18.09%) and unhealthy body mass index (6.94–7.80%). Socioeconomic factors ranked first in males (24.55%), with unemployment contributing the most (9.27%). Lifestyle factors ranked second in younger groups and females, led by poor sleep quality and smoking. Environmental exposure and social support were the last two risk profiles across all subgroups, jointly contributing to about 12% of PAF. SOM integrated patterns predominated by less social support and low socioeconomic status increased depression risk up to 4.37-fold. Potential causal associations between the top five risk factors and depression were observed by MR analyses.

Health condition, socioeconomic status and lifestyle factors demonstrated stronger associations and greater PAFs for depression among relatively younger adults, pinpointing the importance of targeting these impactful factors from an earlier age.

Sexual minority adolescents consistently exhibit a higher prevalence of suicidality compared with their heterosexual peers. This study aims to decompose the disparity in suicidal ideation by quantifying the extent to which it is attributable to differences in exposure to risk and protective factors between heterosexual and sexual minority adolescents, as opposed to differences in their responses to these factors. In addition, this study addresses the limited evidence from Chinese contexts by examining these mechanisms among adolescents in Hong Kong.

Data were extracted from a population-based survey conducted among local secondary school students in Hong Kong in 2021, encompassing 6883 adolescents. Logistic regression examined the factors associated with suicidal ideation. Decomposition analysis assessed the contribution of these factors to disparities in suicidal ideation between heterosexual and sexual minority adolescents, as well as disparities between sexual minority boys and girls.

Body dissatisfaction, cyberbullying, sexual harassment, perceptions of family life and academic performance were associated with suicidal ideation among adolescents, irrespective of their sex or sexual orientation. Approximately 31%–45% of the disparities in suicidal ideation were driven by differences in their exposure to risk and protective factors, and 55%–69% were driven by differences in how these factors relate to suicidal ideation and potentially unobserved characteristics. Among these factors, perceptions of family life played the most substantial role. Sex-specific patterns were also observed.

The higher prevalence of suicidal ideation among Chinese sexual minority adolescents appears to reflect both their greater exposure to stress and lower levels of support, as well as their distinct responses to these factors. Family-related factors are crucial for understanding this disparity. The observed sex differences emphasize the necessity for more nuanced approaches to addressing the varied experiences of sexual minority adolescents in Chinese societies.

This analysis aimed to examine past 20-year prevalence trends of multiple mental health outcomes by age and sex, using repeated cross-sectional survey data from the Canadian household population.

Age- and sex-stratified bootstrap-weighted prevalence estimates were calculated from available Canadian Community Health Survey datasets between 2002 and 2024. Categorizations for age included adolescents and young adults (12–29 years), middle-aged adults (30–64 years) and older adults (65+ years). Mental health outcomes included self-reported professionally diagnosed mood and anxiety disorder, depression survey scales (Composite International Diagnostic Interview Short Form for Major Depression /9-item brief Patient Health Questionnaire) and fair/poor self-perceived mental health. Stratified prevalence estimates from each year were combined and assessed for heterogeneity using random-effects meta-analysis. In the instance of heterogeneity, meta-regression models were applied to generate predicted prevalence trends over time for each mental health outcome, by age and sex categories.

The prevalence of all mental health outcomes increased from 2002/2003 to 2024, in all age groups of both sexes. For example, in adolescent and young adult males, the weighted prevalence of diagnosed mood disorder increased from 2.37% (95% confidence interval [CI]: 2.03, 2.78) in 2003 to 12.58% (95% CI: 10.37, 15.19) in 2024, while prevalence in females of this age group increased from 5.23% (95% CI: 4.76, 5.74) in 2003 to 21.49% (95% CI: 18.97, 24.24) in 2024. Generally, young males saw the greatest relative increases in prevalence, while young females had the greatest absolute increases. Middle-aged and older adults also saw notable increases in their prevalence of poor mental health. Quadratic survey year terms were statistically significant in meta-regression analysis for all outcomes, age and sex groups (excluding mood disorder trends in65+-year-old adults), suggesting curvilinear trends. Male age categories showed more similar trends over time when compared to age-specific estimates of females.

The broad identification of increasing prevalence across various outcomes, age and sex groups has not been highlighted by prior research. Though prevalence increases in young females remain distinct, this finding aligns with previous literature. Consistency of trend patterns between diverse mental health outcomes indicates that multiple dimensions of mental health may be changing similarly over time. Future analyses are critical in understanding the potential factors contributing to these trends and should look to include broad population samples, rather than limiting analyses to specific age/sex groups.

Mental and physical disorders are leading contributors to global disability. However, estimates of their health-related burden often overlook the pervasive comorbidity among conditions. This study aimed to quantify the independent and combined effects of these disorders on self-rated health in nationally representative Chinese adults, explicitly accounting for comorbidity.

Data were drawn from the China Mental Health Survey (CMHS), a cross-sectional nationally representative survey. Mental disorders were assessed using the Composite International Diagnostic Interview 3.0, and physical disorders were measured through structured self-report. Health-related burden was assessed using a 0–100 visual analogue scale (VAS) of self-rated health over the past 30 days. Nested regression models examined disorder-specific and multimorbidity effects, followed by interaction-based counterfactual simulations to estimate disorder-specific burden net of comorbidity at individual and population levels.

Among 27,505 respondents included in multivariate analyses, comorbidity was highly prevalent. In crude models, all 20 disorders were associated with lower VAS scores, with the largest decrements observed for mental disorders such as generalized anxiety disorder (GAD), bipolar disorder and major depressive disorder (MDD). After accounting for disorder type and comorbidity structure, many associations were attenuated and the independent effect of disorder count became non-significant. Counterfactual simulations showed the largest individual-level burdens for GAD (–14.71), cancer (–9.02), bipolar disorder (–8.59) and MDD (–8.53). At the population level, insomnia symptoms (–1.56), arthritis (–0.81) and cardiovascular disorders (–0.64) contributed the greatest burden.

Accounting for comorbidity substantially alters estimates of disorder-specific health burden. Mental disorders impose the greatest impairment at the individual level, whereas prevalent physical conditions dominate population burden.

Sleep disturbances are linked to psychiatric disorders, and obesity is associated with a higher risk of several psychiatric disorders. However, evidence is lacking on how a composite sleep score relates to psychiatric disorder risk in preclinical obesity and on the proteomic pathways that mediate this relationship. Our study aimed to investigate the association of composite sleep score and the risk of multiple specific psychiatric disorders in participants with preclinical obesity.

The prospective cohort study from the UK Biobank included 91,380 participants with preclinical obesity. Six groups were categorized according to sleep scores. Hazard ratios (HRs) for the incidence risk of psychiatric disorders were estimated using multiple Cox proportional hazards regression analysis. Mediation analysis of plasma proteomics in this association was conducted in a subset of participants (n = 9,486).

After a mean follow-up period of 12.9 years, a total of 8,992 incident cases of psychiatric disorders were observed. Using Group 1 as the reference, the risk of psychiatric disorders decreased significantly across Groups 2–6 with increasing sleep score, reaching the lowest in Group 6 (fully adjusted HR = 0.47, 95% CI: 0.33–0.67). Analyses of specific psychiatric disorders revealed that the inverse associations remained significant after full adjustment, with the most notable effect observed for attention deficit hyperactivity disorder (HR = 0.24, 95% CI: 0.08–0.72). Mediation analysis further identified 16 plasma proteins that exerted significant partial mediating effects in this association.

Our findings underscore that better sleep quality is associated with a lower risk of psychiatric disorders among individuals with preclinical obesity. The identification of proteomic mediators may provide further insight into the underlying biological mechanisms, highlighting the clinical significance of integrating sleep-related assessment and intervention.

Post-traumatic stress symptoms (PTSS) are a substantial yet underrecognised mental health concern in oncology. Large-scale epidemiological data across diverse cancer types are scarce. This study aimed to estimate the prevalence of post-traumatic stress disorder (PTSD) and to identify socio-demographic and psychosocial correlates in a large, unselected outpatient cohort.

In this cross-sectional study, 4,103 adult outpatients with solid tumours or haematologic malignancies were screened during routine care using the PTSS-8-Cancer scale. Socio-demographic, clinical and psychosocial variables were collected concurrently. Associations between screening results and patient characteristics were examined using correlational and chi-square analyses.

Overall, 32.5% screened positive for probable PTSD. Prevalence was highest in breast cancer (39.7%), female genital cancers (37.2%) and head and neck cancers (36.1%). A positive screening for PTSD was more common among women, younger patients, those with lower income, without a partner and with a history of psychiatric illness. While these associations were statistically significant, effect sizes were generally small.

One in three cancer outpatients experience substantial PTSS, with elevated prevalence in certain diagnostic groups. Small effect sizes for socio-demographic predictors underscore that psychological distress is broadly distributed. Findings support universal psychosocial screening and integration of trauma-informed care into oncology services to address a significant, population-level mental health burden.

Workforce counts and early-readmission indicators often appear side by side in health-system dashboards, encouraging the assumption that more staff should accompany fewer returns to hospital. We examined whether annual variation in previous-year medical-nursing headcount density was associated with Italy’s official provider-side indicators of unplanned readmission within 30 days after eligible ordinary psychiatric discharges from public psychiatric wards and, secondarily, within 7 days.

Using national mental-health, hospital-discharge and population data, we assembled a retrospective 2015–2024 panel of 21 Italian territorial units (210 unit-years). Exposure was medical and nursing headcount at the end of the preceding year per 100,000 adults. We modelled 30-day readmission counts using Poisson pseudo-maximum likelihood (PPML) with an eligible-discharge offset and territorial-unit and year fixed effects. Primary inference used a restricted wild cluster score bootstrap with 9,999 Rademacher draws and 21 clusters. Secondary and sensitivity analyses were prespecified, source blanks were not imputed, and analytical materials and scripts are openly archived.

Outcome counts and eligible-discharge denominators were complete for all 210 observations; exposure was available for 205. The incidence rate ratio (IRR) per 10 additional medical-nursing staff per 100,000 adults was 1.006 (95% CI 0.934–1.034; p = 0.8095), compatible with relative changes from a 6.6% reduction to a 3.4% increase. Across linear PPML sensitivity analyses, IRRs ranged from 0.995 to 1.042, with all confidence intervals including 1. Across 31 leave-one-unit or leave-one-year-out re-estimates, IRRs ranged from 0.974 to 1.044, and every confidence interval included 1. The nonlinearity test gave p = 0.8572. The 7-day IRR was 1.032 (95% CI 0.929–1.075; p = 0.6743), while the weighted linear model estimated +0.215 percentage points (95% CI −1.159 to +0.704; p = 0.7203).

The data did not provide evidence of a detectable longitudinal ecological association between year-to-year variation in medical-nursing headcount density and the official 30-day readmission indicator. This does not imply that workforce is unimportant: headcount does not capture full-time-equivalent availability, deployment or transition processes, and the provider-side design cannot support patient-level or causal inference. Territorial policy should combine adequate resources with a whole-system view of their deployment, post-discharge organisation, and the social, economic and health context in which care is delivered.

Although asthma is strongly associated with elevated psychiatric morbidity, the extent to which neighbourhood deprivation is associated with psychiatric disorder risk in this population remains insufficiently understood. This study aims to examine whether neighbourhood deprivation is associated with the incidence of psychiatric disorders among adults with asthma, and whether these associations vary by sex and psychiatric disorder subtype.

Using nationwide Swedish registers (1997–2018), we identified 393,061 adults aged 25–64 years with asthma and followed them for incident psychiatric disorders. Neighbourhood deprivation was assessed at baseline and categorized into low, moderate and high levels. Cox proportional hazards models estimated hazard ratios (HRs) with 95% confidence intervals (CIs) and were stratified by sex and psychiatric disorder subtype.

During the follow-up period, 207,900 individuals (68,327 men and 139,573 women) developed psychiatric disorders. The incidence of psychiatric disorders increased progressively with higher levels of neighbourhood deprivation. In the fully adjusted models, compared with those living in low-deprivation areas, men in moderate and high deprivation areas had 11% (HR, 1.11; 95% CI, 1.08–1.13) and 31% (HR, 1.31; 95% CI, 1.27–1.35) higher hazards, respectively, while women had 10% (HR, 1.10; 95% CI, 1.08–1.11) and 22% (HR, 1.22; 95% CI, 1.19–1.25) higher hazards. Disorder-specific analyses revealed particularly strong associations for developmental delay (HR = 2.82), pervasive developmental disorder (HR = 1.96), schizophrenia (HR = 1.79) and substance use disorder (HR = 1.71). Women consistently showed higher cumulative incidence than men across all deprivation levels.

Neighbourhood deprivation was associated with higher psychiatric morbidity among individuals with asthma. These findings suggest the importance of integrating respiratory and mental healthcare with structural interventions targeting socio-economic disadvantage to help reduce inequalities in psychiatric outcomes.

Depression and post-traumatic stress disorder (PTSD) are highly prevalent and frequently co-occur in conflict-affected populations, yet the complex relationships among their symptoms remain poorly understood. This study applied psychological network analysis and Bayesian network modelling to examine symptom associations and exploratory directional dependencies among participants living in Cox’s Bazar and neighbouring Bandarban, Bangladesh.

Baseline data were obtained from 9,397 participants, including forcibly displaced Rohingya refugees and host-community members. Depression symptoms (Patient Health Questionnaire-9) and PTSD symptoms (Harvard Trauma Questionnaire-16) were analysed using regularized partial correlation networks and directed acyclic graphs. Symptom centrality, bridge centrality, predictability and network stability were assessed, alongside sensitivity analyses by settlement status and sex.

Distinct yet interconnected clusters of depression and PTSD symptoms emerged. Guilt, anhedonia, recurrent traumatic thoughts, emotional detachment, hopelessness about the future and rumination emerged as the most central symptoms. Bridge-strength analyses identified guilt and physical health problems as the most prominent bridge symptoms linking depression and PTSD symptom communities. Bayesian network analysis identified several highly stable exploratory directional dependencies involving anhedonia, guilt, rumination, recurrent traumatic thoughts and emotional detachment. The network demonstrated excellent stability (correlation stability = 0.75), while symptom-level classification accuracy ranged from 0.542 to 0.791. Sensitivity analyses indicated that network structure differed across settlement settings, whereas no significant difference in overall network structure was detected between sexes.

These findings provide a nuanced understanding of symptom interrelationships between depression and PTSD in a major humanitarian setting. Symptoms such as guilt, rumination, recurrent traumatic thoughts and physical health problems warrant further interventions as potential intervention targets, potentially informing more focused and culturally sensitive mental health strategies for conflict-affected populations.