Epidemiology and Psychiatric Sciences最新文献

Aims: While depressive symptoms are common during menopausal transition, the relationship between the two remains unclear. Therefore, this study aimed to examine the longitudinal changes in depressive symptoms among middle-aged Korean women and identify those with elevated and worsening symptoms during this period.

Methods: A total of 1,178 participants who underwent comprehensive health examinations at Kangbuk Samsung Hospital in Korea were followed for a median of 10.8 years (IQR, 9.2-11.6; maximum, 12.7), including all women who reached natural menopause during follow-up, with only data prior to HRT initiation included. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (CES-D), and menopausal stages were classified according to the STRAW + 10 criteria and final menstrual period (FMP). Linear mixed-effects models and group-based trajectory modelling (GBTM) were applied to evaluate longitudinal changes in depressive symptoms and to identify distinct trajectories in the severity and stability of depressive symptoms.

Results: The age-adjusted prevalence of CES-D ≥ 16 was 11.0%, 11.5%, 11.2% and 12.4%, with corresponding mean scores of 6.7, 6.6, 6.9 and 7.1 across stages. After adjusting for time-varying age and covariates, menopausal stage transitions were not significantly associated with higher levels of depressive symptoms, whether analysed as continuous or binary variables. For binary CES-D (≥16), the estimated coefficients (95% CI) were 0.10 (-0.20 to 0.41) for early transition, 0.09 (-0.21 to 0.39) for late transition and 0.26 (-0.09 to 0.61) for post-menopause. Similarly, time relative to the FMP (-11 to +9 years) showed no significant association with depressive symptoms. GBTM identified three distinct trajectories: most participants (75.5%) maintained consistently low depressive symptoms throughout the transition, whereas 5.8% showed worsening symptoms. Poor sleep quality (OR 5.83, 95% CI 3.25 to 10.45) and moderate-to-severe vasomotor symptoms (OR 2.95, 95% CI 1.30 to 6.70) were significantly associated with the worsening trajectory. Suicidal ideation was higher in this group (45.4% at baseline, increasing to 70.5% at follow-up).

Conclusions: Most women maintained low depressive symptoms during the menopausal transition; however, a subset experienced worsening symptoms linked to menopause-related physical symptoms. Medical visits for menopause-related symptoms may provide opportunities for screening depressive symptoms in higher-risk women, though the screening effectiveness requires further evaluation.

Aims: To investigate the association of midlife and late-life undiagnosed mood symptoms, especially their comorbidity, with long-term dementia risk among multi-regional and ethnic adults.

Methods: The prospective study used data from the UK Biobank (N = 142,670; mean follow-up 11.0 years) and three Asian studies (N = 1,610; mean follow-up 4.4 years). Undiagnosed mood symptoms (manic symptoms, depressive symptoms and comorbidity of depressive and manic symptoms) and diagnosed mood disorders (depression, mania and bipolar disorders) were classified. Plasma levels of 168 metabolites were measured. The association between undiagnosed mood symptoms and 12-year dementia (including subtypes) risk and domain-specific cognitive function was examined. The contribution of metabolites in explaining the association between symptom comorbidity and dementia risk was estimated.

Results: Undiagnosed mood symptoms were prevalent (11.4% in the UK cohort and 31.2% in Asian cohorts) among 1,462 (1.0%) and 74 (19.4%) participants who developed dementia. Comorbidity of undiagnosed mood symptoms was associated with higher dementia risk (sub-distribution hazard ratios = 9.46; 95% confidence interval = 4.07-21.97), especially Alzheimer's disease, and with worse reasoning ability, poorer numeric memory and metabolic dysfunction. Glucose and total Esterified Cholesterol explained 9.1% of the association between symptom comorbidity and dementia, with most of the contribution being from glucose (6.8%).

Conclusions: Comorbidity of undiagnosed mood symptoms was associated with a higher cumulative risk of dementia in the long term. Glucose metabolism could be implicated in the development of mood disorders and dementia. The distinctive pathophysiological mechanism between psychiatric and neurodegenerative disorders warrants further exploration.

Aims: Depression among middle-aged and older adults is a critical public health priority. Clarifying the dynamic evolution of depression is essential for establishing prevention and intervention strategies; however, relevant research is limited. The aim of this study was to elucidate the transition patterns underlying different depressive symptoms (DS) states.

Methods: Data from the China Health and Retirement Longitudinal Study were utilised in this study, which included participants aged ≥45 years with multiple DS assessments via the Center for Epidemiological Studies Depression Scale. Multi-state Markov models were employed to estimate transition probabilities and intensities between DS states, the total length of stay and mean sojourn time in each state and the hazard ratios (HRs) of factors.

Results: Among 19,991 participants (average follow-up: 7.3 years), the 10-year cumulative probabilities of transition from non-DS to depressive states increased by 19.4% in males and 31.8% in females. Mild DS was the most unstable state, with the highest transition intensities (males: 1.029; females: 0.970) and shortest sojourn time (males: 0.959 years; females: 1.022 years). Sex and age strongly influenced depressive state transitions. Compared to participants without chronic disease, those with ≥3 chronic diseases had a higher risk of developing mild DS (HR = 1.685, 95% Confidence Interval [CI]: 1.530-1.856) and transitioning to death from both the non-DS (HR = 2.905, 95% CI: 2.293-3.681) and severe-DS (HR = 3.429, 95% CI: 1.290-9.112) states, but a lower likelihood of recovery from mild DS (HR = 0.821, 95% CI: 0.749-0.900) and severe DS (HR = 0.730, 95% CI: 0.630-0.847). Compared to no participation in social activities, frequent participation was associated with a lower risk of progression to the mild-DS state (HR = 0.851, 95% CI: 0.785-0.920) and a greater likelihood of recovery from severe DS (HR = 1.169, 95% CI: 1.034-1.322). Being underweight was associated with an increased risk of mild-DS onset (HR = 1.338, 95% CI: 1.129-1.587) and transitioning to death from both the non-DS and mild-DS states, compared with individuals of normal weight.

Conclusions: Our study revealed a continuous population shift towards depressive states and identified the mild-DS state as a critical intervention state owing to its instability. In addition to sex and age, modifiable factors, including chronic disease conditions, social activity participation and weight status, significantly influenced DS-state transitions, offering actionable insights for precision prevention strategies.

Aims: Fine particulate matter (PM_2.5) exposure and unfavourable lifestyle are both significant risk factors for mental health disorders, yet their combined effects on adolescent depression and anxiety remain poorly understood. This study aims to determine whether PM_2.5 exposure and lifestyle are independently associated with adolescent depression and anxiety, and whether there are joint effects between these factors on mental health outcomes.

Methods: In this cross-sectional study, 19852 participants were analysed. PM_2.5 concentrations were obtained from the ChinaHighAirPollutants (CHAP) dataset. Lifestyle factors were assessed through self-reported questionnaires, and a healthy lifestyle score was developed based on eight lifestyle risk factors. Depression and anxiety were assessed using the PHQ-9 and GAD-7 scales. Restricted cubic spline analysed dose-response relationships between PM_2.5 exposure and mental health outcomes. The independent and joint effects were assessed using logistic regression models. Both multiplicative and additive interactions (relative excess risk due to interaction, RERI) were examined. Multiple classification approaches were incorporated to ensure robust results.

Results: The study included 19852 participants with a mean age of 15.16 years (SD 1.60), comprising 9886 (49.8%) males and 9966 (50.2%) females. Depression and anxiety were identified in 3845 (19.37%) and 3230 (16.27%) participants, respectively. PM_2.5 exposure showed a linear dose-response relationship with depression and anxiety. Joint effects analysis at the 75th percentile of PM_2.5 with a lifestyle risk score of 4 revealed the strongest associations, with adjusted odds ratios of 4.49 (95% CI: 3.79-5.33) for depression, 4.01 (95% CI: 3.36-4.78) for anxiety and 4.24 (95% CI: 3.52-5.10) for their comorbidity. Simultaneously, significant additive interactions (RERI > 0) between high levels of PM_2.5 exposure and unfavourable lifestyle factors were detected, suggesting synergistic effects on mental health outcomes. Subgroup and sensitivity analyses confirmed the robustness of these findings.

Conclusions: High PM_2.5 exposure and unfavourable lifestyle factors demonstrated significant independent and joint effects on depression and anxiety among adolescents. These findings highlight that implementing stringent air pollution control measures, combined with promoting healthy lifestyle practices, may be crucial for protecting adolescent mental health.

Background: Promoting mental health, preventing mental disorders and providing effective treatments are public health priorities. Randomized controlled trials (RCTs) frequently evaluate mental health and psychosocial support interventions to achieve one or more of these objectives. Distinguishing between RCTs focused on mental health promotion, prevention or treatment remains conceptually and methodologically challenging. No standardized tool exists to position RCTs along a promotion-to-treatment continuum in mental health. We aimed to develop and validate the VErona-LUgano Tool (VELUT) for distinguishing RCTs along the promotion-to-treatment continuum.

Methods: An interdisciplinary tool development group (TDG) was established. The Population, Intervention, Comparison and Outcome framework was used to define key constructs. Items in the tool were devised, categorized and reduced through qualitative and quantitative methods. Finally, we performed a preliminary validation of the VELUT applying item response theory (IRT) using data from 180 RCTs.

Results: The TDG generated 33 items for the initial version of the VELUT, reduced to 16 through review, cognitive interviews and psychometric analysis. Analyses of 180 RCTs using the 16-item tool showed high internal consistency (α = 0.94) and unidimensionality. Following item reduction and IRT, a final 8-item version was retained, and IRT models confirmed strong item discrimination for the 8 items and high scale reliability (marginal reliability >0.90 across most of the range of the scale), good response distribution, item performance and alignment with the Institute of Medicine (IOM) promotion-to-treatment continuum.

Conclusions: The VELUT addresses methodological gaps in global mental health research by helping to position RCTs of MHPSS interventions along the IOM promotion-to-treatment continuum.

Aims: This study employs a longitudinal network approach to investigate the dynamic relationships between COVID-19-related stressors and depressive symptoms among Canadian adults and to explore any sex and age differences in these associations.

Methods: The study utilised data from the Canadian Longitudinal Study on Ageing (CLSA), a large, national, long-term study of Canadian adults aged 45 years and older. Depressive symptoms were measured using the Centre for Epidemiologic Studies Depression Scale (CES-D), and COVID-19-related stressors were evaluated using a standardised stress inventory adapted for the pandemic context. The cross-lagged panel network analysis (CLPN) was employed to examine the temporal relationships and dynamic interactions between depressive symptoms and COVID-19-related stressors.

Results: Significant variations in network structures and strengths were identified across demographic groups. Individuals aged between 45 and 65 years and females exhibited stronger connections between COVID-19-related stressors and depressive symptoms. Central symptoms such as "feeling unhappy" were consistent across groups, while "feeling depressed" was more central among males and "increased verbal or physical conflict" among females. Additionally, health-related stressors and family separation emerged as critical bridge symptoms for males and individuals under 65 years, respectively.

Conclusions: Both cross-sectional and longitudinal relationships, and directionality between COVID-19-related stressors and depressive symptoms across sex and age groups were identified. The findings of the study highlight that dedicated mental health intervention and prevention efforts are warranted to ameliorate the negative impact of stressors on depressive symptoms.

Aims: The epidemiology and age-specific patterns of lifetime suicide attempts (LSA) in China remain unclear. We aimed to examine age-specific prevalence and predictors of LSA among Chinese adults using machine learning (ML).

Methods: We analyzed 25,047 adults in the 2024 Psychology and Behavior Investigation of Chinese Residents (PBICR-2024), stratified into three age groups (18-24, 25-44, ≥ 45 years). Thirty-seven candidate predictors across six domains-sociodemographic, physical health, mental health, lifestyle, social environment, and self-injury/suicide history-were assessed. Five ML models-random forest, logistic regression, support vector machine (SVM), Extreme Gradient Boosting (XGBoost), and Naive Bayes-were compared. SHapley Additive exPlanations (SHAP) were used to quantify feature importance.

Results: The overall prevalence of LSA was 4.57% (1,145/25,047), with significant age differences: 8.10% in young adults (18-24), 4.67% in adults aged 25-44, and 2.67% in older adults (≥45). SVM achieved the best test-set performance across all ages [area under the curve (AUC) 0.88-0.94, sensitivity 0.79-0.87, specificity 0.81-0.88], showing superior calibration and net clinical benefit. SHAP analysis identified both shared and age-specific predictors. Suicidal ideation, adverse childhood experiences, and suicide disclosure were consistent top predictors across all ages. Sleep disturbances and anxiety symptoms stood out in young adults; marital status, living alone, and perceived stress in mid-life; and functional limitations, poor sleep, and depressive symptoms in older adults.

Conclusions: LSA prevalence in Chinese adults is relatively high, with a clear age gradient peaking in young adulthood. Risk profiles revealed both shared and age-specific predictors, reflecting distinct life-stage vulnerabilities. These findings support age-tailored suicide prevention strategies in China.

Aims: The COVID-19 pandemic exacerbated psychological distress, but limited information is available on the shifts in mental health symptoms and their associated factors across different stages. This study was conducted to more reliably estimate shifts in mental health impacts and to identify factors associated with symptoms at different pandemic stages.

Methods: We performed a national repeated cross-sectional study at stable (2021), recurrence (2022), and end-of-emergency (2023) stages based on representative general national population with extensive geographic coverage. Anxiety, depression, post-traumatic stress disorder (PTSD) and insomnia symptoms were evaluated by GAD-7, PHQ-9, IES-R and ISI scales, respectively, and their associated factors were identified via multivariable linear regression.

Results: Generally, 42,000 individuals were recruited, and 36,218, 36,097 and 36,306 eligible participants were included at each stage. The prevalence of anxiety, depression and insomnia symptoms increased from 13.7-16.4% at stable to 17.3-22.2% at recurrence and decreased to 14.5-18.6% at end of emergency, while PTSD symptom continuously increased from 5.1% to 7.6% and 9.2%, respectively (all significant, P < 0.001). Common factors associated with mental health symptoms across all stages included centralized quarantine, frontline work and residence in initially widely infected areas. Centralized quarantine was linked to anxiety, depression, PTSD and insomnia during the stable, recurrence and end-of-emergency stages. Frontline workers exhibited higher risks of anxiety, depression and insomnia throughout these stages. Individuals in initially widely infected areas were more likely to experience depression and PTSD, particularly during the stable and recurrence stages. Stage-specific risk factors were also identified. Lack of outdoor activity was associated with anxiety, depression and insomnia during the stable and recurrence stages. Residents in high-risk areas during the recurrence stage correlated with increased anxiety and insomnia. Suspected infection was tied to anxiety and insomnia in the recurrence and end-of-emergency stages, while the death of family or friends was linked to PTSD during recurrence and to depression, PTSD and insomnia at the end-of-emergency stage.

Conclusions: Mental health symptoms increased when pandemic recurred, and could remain after end-of-emergency, requiring prolonged interventions. Several key factors associated with mental symptoms and their variations were identified at different pandemic stages, suggesting different at-risk populations.

Aims: Although the United States incarcerates nearly two million people, the epidemiology of psychiatric disorders in correctional populations is not well understood, and no study has examined temporal trends in psychiatric disorder prevalences within a single correctional system. This study assessed how psychiatric disorder prevalences have changed in the Texas Department of Criminal Justice (TDCJ), the largest American state prison system housing post-conviction, sentenced individuals.

Methods: This retrospective cohort study of TDCJ electronic medical record data from 1 January 2016 through 31 December 2023 included all persons incarcerated for any duration during that period. Diagnoses were based on International Classification of Disease (ICD-10) diagnostic codes. Outcomes were annual prevalences of depressive, bipolar and schizophrenia spectrum disorders stratified by age, race and sex. Cochran-Armitage Tests were used to assess temporal trends within each stratum. Two-way interactions were assessed by fitting Generalized Estimating Equations models using autoregressive correlation with repeated subjects.

Results: The overall population ranged from 170,269 to 222,798 individuals. Approximately, one-third were White (34.5-35.4%), one-third Black (31.0-32.3%), and one-third Hispanic (32.7-33.5%). Most were aged 30-49 (52.8-57.3%), and men (88.9-90.7%) outnumbered women (9.3-11.1%). The prevalences (per 100 [95% CI]) of psychiatric disorders generally increased when comparing 2016 to 2023. Depressive disorders increased the most among those aged 30-49 (5.23 [5.10-5.35] to 6.71 [6.56-6.86]), Hispanic individuals (3.86 [3.72-4.00] to 5.72 [5.53-5.90]), and men (4.72 [4.63-4.82] to 6.53 [6.42-6.65]). Bipolar disorders increased the most among those aged ≥50 (2.57 [2.42-2.72] to 3.46 [3.29-3.63]), Hispanic individuals (1.31 [1.23-1.40] to 2.23 [2.11-2.35]), and men (2.26 [2.20-2.33] to 3.12 [3.04-3.20]). Schizophrenia spectrum disorders increased the most among those aged ≤29 (1.33 [1.24-1.42] to 2.52 [2.35-2.68]), Hispanic individuals (1.53 [1.44-1.62] to 3.21 [3.35-4.40]), and women (1.27 [1.56-1.89] to 4.24 [3.95-4.53]). When stratified by demographic variables, trend tests were significant for nearly all comparisons (P < 0.0001), and all two-way interactions were significant (P < 0.0001).

Conclusions: The prevalences of major psychiatric disorders in the Texas prison system increased when comparing 2016 to 2023, with certain disorders rising more rapidly than others within specific subgroups. These findings emphasize the need for expanded mental health treatment options and resources within correctional settings.

Aims: Evidence on the effects of parental Adverse Childhood Experiences (ACEs) on adolescent mental health remains limited. This study investigates the associations between parental ACEs, children's exposure to threat- and deprivation-related ACEs, and adolescent depression and anxiety using data from the Longitudinal Study of Australian Children.

Methods: We conducted a secondary analysis of the Longitudinal Study of Australian Children (LSAC), a population-based longitudinal cohort study. Parental ACEs were retrospectively reported by caregivers. Children's exposure to ACEs was assessed from ages 4-17 years and categorised as threat-related ACEs (e.g., bullying, hostile parenting, unsafe neighbourhoods, family violence) or deprivation-related ACEs (e.g., financial hardship, parental substance abuse, parental psychological distress, death of a family member, parental separation, parental legal problems). Depressive and anxiety symptoms were self-reported by adolescents at ages between 12 and 17 years. Modified Poisson regression models were used to examine the independent and combined associations of parental ACEs and children's threat- and deprivation-related ACEs (assessed before ages 12, 14, and 16 years) with depression and anxiety outcomes, including tests for interaction effects.

Results: The analysis included 3,956 children aged 12-13 years, 3,357 children aged 14-15 years, and 3,089 children aged 16-17 years. Males comprised 50.8-59.8% and females 40.2-49.2% across all ages. By the age of 17, 30.4% and 9.4% of the adolescents had depression and anxiety, respectively. Parental ACEs (≥2) were associated with increased depression risk at ages 12 to 13 years (RR = 1.42; 95% CI: 1.10-1.84) and at 16-17 years (RR = 1.19; 95% CI: 1.02-1.39). Exposure to ≥ 2 deprivation-related ACEs significantly increased the risk of depression across all ages, with relative risks ranging from 1.31 to 2.18. High threat-related ACEs (≥2) were associated with increased depression risk only at 12 to 13 years (RR = 2.01; 95% CI: 1.28-3.17). No significant interactions were observed.

Conclusions: The findings reinforce the ACEs model by showing that, at the population level, early identification of children exposed to early life deprivations rooted in financial crisis or familial adversities, combined with targeted interventions for both children and parents and supportive social policies, can reduce long-term mental health risks.