Journal of affective disorders最新文献

{"title":"Genetic and environmental predictors of seasonality and seasonal affective disorder in individuals with depression.","authors":"Floris Huider, Jacob J Crouse, Sarah E Medland, Ian B Hickie, Nicholas G Martin, Jodi T Thomas, Brittany L Mitchell","doi":"10.1016/j.jad.2026.122672","DOIUrl":"https://doi.org/10.1016/j.jad.2026.122672","url":null,"abstract":"<p><strong>Background: </strong>The etiology and nosological status of seasonal affective disorder (SAD) as a specifier of depressive episodes versus a transdiagnostic disorder are the subject of debate. In this study, we investigated the underlying etiology of SAD and dimensional seasonality by examining their association with latitude and genetic risk for a range of traits, and investigated gene-environment interactions.</p><p><strong>Methods: </strong>This study included 12,460 adults (76% female, aged 18-90) with a history of depression from the Australian Genetics of Depression Study. Regression models included predictors for latitude (distance from equator) and polygenic scores for eight traits; major depressive disorder, bipolar disorder, anxiety disorders, chronotype, sleep duration, body mass index, vitamin D levels, and educational attainment. Outcomes were SAD status and general seasonality score.</p><p><strong>Results: </strong>SAD was positively associated with latitude (OR[95%CI] = 1.05[1.03-1.06], p_adjusted < 0.001), and there was nominal evidence of additive and multiplicative interactions between chronotype genetic risk and latitude (OR = 0.99[0.99-0.99], p_adjusted = 0.381; OR = 0.98[0.97-0.99], p_adjusted = 0.489). General seasonality score was associated with latitude (IRR = 1.01[1.01-1.01], p_adjusted 0.001) and genetic risk for major depressive disorder (IRR =1.02[1.01-1.03], p_adjusted < 0.001), bipolar disorder (IRR = 1.02[1.01-1.03], p_adjusted = 0.001), anxiety disorders (IRR = 1.03[1.01-1.04], p_adjusted < 0.001), vitamin D levels (OR = 0.89[0.80-0.95], p_adjusted = 0.048), and educational attainment (IRR = 0.97[0.96-0.99], p_adjusted < 0.001).</p><p><strong>Conclusions: </strong>These findings enhance understanding of SAD etiology, highlighting contributions of psychiatric genetic risk and geographic measures on seasonal behavior, and support examining seasonality as a continuous dimension.</p>","PeriodicalId":14963,"journal":{"name":"Journal of affective disorders","volume":" ","pages":"122672"},"PeriodicalIF":5.7,"publicationDate":"2026-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149267718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An explainable machine learning framework integrating heart rate variability and insomnia for severe BDI-II-defined depressive symptom burden in Psychiatric outpatients.","authors":"Sanghoon Choi, Hyo-Chang Seo, Hong Jin Jeon","doi":"10.1016/j.jad.2026.122674","DOIUrl":"https://doi.org/10.1016/j.jad.2026.122674","url":null,"abstract":"<p><strong>Background: </strong>Depression is a common mental health condition requiring repeated symptom severity assessment. While short-term electrocardiography (ECG)-derived heart rate variability (HRV) provides objective autonomic markers, it may not fully capture the clinical burden of depressive symptoms. We developed an interpretable machine learning framework combining short-term ECG-derived HRV and evaluated the incremental value of insomnia symptoms for classifying severe depressive symptom burden (Beck Depression Inventory-II ≥ 29).</p><p><strong>Methods: </strong>We analyzed 2663 psychiatric outpatients. Seven classifiers, a penalized logistic regression baseline, and three voting ensembles were evaluated using stratified 5-fold cross-validation with validation-selected decision thresholds. Feature ablation, decision curve analysis, and explainable artificial intelligence (SHAP and LIME) examined the contributions of HRV and Hamilton Depression Rating Scale (HAMD)-derived insomnia score.</p><p><strong>Results: </strong>The weighted soft-voting ensemble achieved the highest performance, with an area under the receiver operating characteristic curve (AUROC) of 0.837 (95%CI, 0.821-0.852), accuracy 0.756, sensitivity 0.721, specificity 0.776, and F1 score 0.686. Adding the insomnia score improved ensemble AUROC from 0.701 to 0.837 (Δ = 0.136, P < 0.001), while adding HRV features to age, gender, and insomnia score increased AUROC from 0.737 to 0.837 (Δ = 0.100, P < 0.001). Excluding nine duration-sensitive HRV indices yielded an AUROC of 0.787. SHAP and LIME identified age, insomnia score, and mean heart rate as primary contributors, confirming patient-level interpretability.</p><p><strong>Conclusions: </strong>Adding insomnia score to ECG-derived HRV appears to improve the classification of severe depressive symptom burden over HRV alone. This interpretable, low-burden framework shows potential clinical utility, suggesting that it may serve as an adjunctive screening tool for depression care.</p>","PeriodicalId":14963,"journal":{"name":"Journal of affective disorders","volume":" ","pages":"122674"},"PeriodicalIF":5.7,"publicationDate":"2026-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149267780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Low-dose ketamine modulates brain entropy in treatment-resistant depression: Results from two neuroimaging clinical trials.","authors":"Ying-Jay Liou, Li-Kai Cheng, Wei-Chen Lin, Tung-Ping Su, Li-Fen Chen, Pei-Chi Tu, Cheng-Ta Li, Ya-Mei Bai, Shih-Jen Tsai, Mu-Hong Chen","doi":"10.1016/j.jad.2026.122673","DOIUrl":"https://doi.org/10.1016/j.jad.2026.122673","url":null,"abstract":"<p><strong>Background: </strong>Several studies have reported entropy reductions in regions of the brain associated with affective-regulatory and reward- and motivation-related processes in patients with major depressive disorder. However, whether low-dose ketamine modulates this reduction remains unclear.</p><p><strong>Methods: </strong>We analyzed resting-state functional magnetic resonance imaging data from two single-infusion low-dose ketamine trials. Data at baseline and 3 days after infusion were analyzed. In Trial 1, patients with treatment-resistant depression were randomized to receive 0.2 or 0.5 mg/kg ketamine or normal saline. In Trial 2, patients with treatment-resistant depression and suicidal ideation were randomized to receive either 0.5 mg/kg ketamine or 0.045 mg/kg midazolam. Sample entropy was calculated from the spontaneous blood oxygenation level-dependent time series of 166 regions of interest defined by the automated anatomical labeling atlas 3.</p><p><strong>Results: </strong>In Trial 1, increased brain entropy was observed in the gyrus rectus, cerebellar vermis I/II, substantia nigra, red nucleus, and bilateral locus coeruleus after low-dose ketamine infusion. In Trial 2, the ketamine group exhibited higher brain entropy in the left amygdala compared with the midazolam group.</p><p><strong>Discussion: </strong>Low-dose ketamine rapidly increases brain entropy (from baseline to day 3) in frontolimbic, cerebellar, and ascending neuromodulatory regions, including the gyrus rectus, cerebellar vermis I/II, substantia nigra, red nucleus, bilateral locus coeruleus, and left amygdala. Changes in brain entropy after low-dose ketamine infusion may be associated with its rapid antidepressant and antianhedonic effects, although this relationship requires further investigation.</p>","PeriodicalId":14963,"journal":{"name":"Journal of affective disorders","volume":" ","pages":"122673"},"PeriodicalIF":5.7,"publicationDate":"2026-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149267741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hippocampal subfield functional connectivity alterations in major depressive disorder: A systematic review and meta-analysis.","authors":"Yulong Liu, Yu Chen, Min Kong, Zhi Xu, Wenhao Jiang","doi":"10.1016/j.jad.2026.122669","DOIUrl":"https://doi.org/10.1016/j.jad.2026.122669","url":null,"abstract":"<p><strong>Background: </strong>Major depressive disorder (MDD) is increasingly conceptualized as a disorder of distributed neural network dysfunction. The hippocampus comprises functionally distinct subfields, yet evidence on subfield-level functional connectivity (FC) abnormalities in MDD remains heterogeneous, partly because studies use different segmentation approaches.</p><p><strong>Methods: </strong>Following PRISMA 2020, we systematically searched PubMed and Scopus for English-language studies published from January 2020 to August 2026 examining FC involving hippocampal subfields or subregions in depression. We summarized segmentation methods, compared atlas-level spatial overlap, performed random-effects meta-analyses where data were comparable, and narratively synthesized case-control and treatment-related findings.</p><p><strong>Results: </strong>Eighteen studies including 1366 patients with MDD and 935 healthy controls were included. Segmentation approaches differed substantially in hippocampal coverage and granularity. Five studies contributed to exploratory network-specific meta-analyses. FC was lower in MDD for hippocampal subregion-default mode network connections (g = -0.74, 95% CI -0.98 to -0.50) and visual network connections (g = -0.64, 95% CI -0.94 to -0.34). Estimates for salience, limbic, and sensorimotor networks were imprecise and heterogeneous. Narrative findings were bidirectional, while longitudinal studies suggested treatment-related connectivity changes.</p><p><strong>Conclusions: </strong>MDD is associated with heterogeneous, subregion-specific hippocampal dysconnectivity. Atlas non-equivalence may contribute to variability across studies, supporting more harmonized and method-aware segmentation approaches.</p>","PeriodicalId":14963,"journal":{"name":"Journal of affective disorders","volume":" ","pages":"122669"},"PeriodicalIF":5.7,"publicationDate":"2026-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149267749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global synchrony moderates sad mood and is associated with emotional Stroop interference and somatic symptoms.","authors":"Sammi T S T Mabel-Kenzie, Nichol M L Wong, Tatia M C Lee","doi":"10.1016/j.jad.2026.122665","DOIUrl":"https://doi.org/10.1016/j.jad.2026.122665","url":null,"abstract":"<p><p>Mood-congruent attention in depression has been studied via emotional interference tasks, including tasks comparing responses to sad and happy stimuli. Mood induction offers a way to experimentally induce sad mood in non-clinical samples and examine its association with subsequent emotional interference, including Sad-Happy interference. Previous studies have separately linked resting-state global neural dynamics (synchrony, metastability) to depressive symptoms and attentional processing. However, whether individual differences in baseline global synchrony and metastability relate to how individuals respond to sad mood remains largely unclear. This study therefore examined the relationship between neural dynamics, sadder mood after induction, and Sad-Happy interference. Depressive symptoms also encompass somatic domains alongside cognitive-affective domains, though these are rarely distinguished in neuroimaging studies. We further examined whether baseline neural dynamics and their association with sadder mood and Sad-Happy interference were related to depressive symptoms (total, cognitive-affective, and somatic). Forty-eight non-clinical individuals completed resting-state neuroimaging, mood induction (sad or non-sad), and an emotional Stroop task. We found in a cross-sectional moderated mediation model that sadder mood after induction was associated with greater interference from sad compared to happy stimuli at medium and high levels of global synchrony, particularly in exploratory path models that included somatic symptoms. Findings suggest that individual differences in resting-state global synchrony may be a neural correlate of sadder mood after induction and Sad-Happy interference in non-clinical individuals. This study offers preliminary associations linking neural dynamics, sad mood, emotional interference, and somatic symptoms, providing insights into the role of neural dynamics in emotional and attentional processing.</p>","PeriodicalId":14963,"journal":{"name":"Journal of affective disorders","volume":" ","pages":"122665"},"PeriodicalIF":5.7,"publicationDate":"2026-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149267800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Psychocognitive vulnerability and risk of incident ADL disability and mortality across six prospective cohort studies.","authors":"Ying Zeng, Xin Yang, Shuiying Hua, Li Zhang, Fuzhou Hua, Dehui Liu","doi":"10.1016/j.jad.2026.122666","DOIUrl":"https://doi.org/10.1016/j.jad.2026.122666","url":null,"abstract":"<p><strong>Introduction: </strong>Depressive symptoms and lower word-recall performance often co-occur with chronic disease in middle-aged and older adults. We examined their separate and joint associations with subsequent activities of daily living (ADL) disability and mortality across multimorbidity strata.</p><p><strong>Methods: </strong>We pooled harmonised data from CHARLS, ELSA, HRS, KLoSA, MHAS and SHARE. Adults ≥45 years contributed observed person-intervals. Study-wave standardised scores defined none, single-domain or dual-domain vulnerability. Outcomes were incident ADL disability (primary) and all-cause mortality. Modified Poisson models estimated risk ratios (RRs); cohort-stratified Cox models estimated hazard ratios (HRs).</p><p><strong>Results: </strong>Among 257,922 participants (mean age 62.4 years; 55.5% female), 181,551 contributed 512,522 eligible ADL intervals (45,430 events). Complete-case adjusted analyses included 179,248 participants (500,911 intervals; 44,178 ADL events) and 213,268 participants (605,704 mortality windows; 27,782 deaths). ADL RRs versus none were 1.68 (95% CI, 1.65-1.71) for single-domain and 2.19 (2.12-2.27) for dual-domain vulnerability, with 48.7 and 85.3 excess events per 1000 standardised interval observations, respectively. Corresponding summary mortality HRs were 1.56 (95% CI, 1.51-1.60) and 1.79 (1.71-1.86). Interaction-model absolute ADL risk was 27.2% with dual-domain vulnerability and ≥ 3 chronic conditions at the next observed assessment. Four categories distinguished endpoint-specific single-domain associations; joint ADL associations were below multiplicative and additive expectations (interaction ratio 0.756; relative excess risk due to interaction [RERI] -0.240). Mortality hazards were nonproportional.</p><p><strong>Discussion: </strong>A simple psychocognitive vulnerability classification was associated with graded risks of ADL disability and mortality across six cohorts. The largest absolute ADL risk increases accompanied multimorbidity.</p>","PeriodicalId":14963,"journal":{"name":"Journal of affective disorders","volume":" ","pages":"122666"},"PeriodicalIF":5.7,"publicationDate":"2026-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149267708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Circulating immune cells phenotypes discriminate bipolar disorder from major depressive disorder during a depressive episode: A machine learning elastic-net approach.","authors":"Sara Poletti, Beatrice Bravi, Federico Calesella, Veronica Aggio, Benedetta Vai, Annamaria Finardi, Alessandra Mandelli, Cristina Lorenzi, Cristina Colombo, Roberto Furlan, Francesco Benedetti","doi":"10.1016/j.jad.2026.122658","DOIUrl":"https://doi.org/10.1016/j.jad.2026.122658","url":null,"abstract":"<p><p>MDD and BD are characterized by differences in peripheral immune markers, in frequencies of T helper, T cytotoxic, Natural Killer (NK) and T regulatory cells that may contribute to the development of mood disorders. However, few studies have used immune cells populations to discriminate MDD from BD with inconsistent findings. We applied an elastic-net machine learning pipeline predictive model using 5-fold nested cross-validation based on a wide panel of immune cell populations to discriminate between MDD and BD. The sample included 124 MDD and 89 BD hospitalised for depressive episode, and 40 healthy controls (HC). The predictive model achieved an accuracy of 78%, with 76% sensitivity, 80% specificity. The model performed significantly better than chance (p < 0.001). BD diagnosis was associated with higher frequencies of cells populations producing proinflammatory cytokines (i.e. CD4⁺IFN-γ, CD4⁺IL-17, CD4⁺TNF-α, CD8⁺TNF-α, NK cells/TNF-α), and regulatory cells (FOXP3), whereas MDD diagnosis was associated with elevated frequencies of early activating memory cells both T helper and cytotoxic (i.e. CD4⁺CM/CD69⁺, CD4⁺EM/CD69⁺, CD8⁺CM/CD69⁺), and cytotoxic effector cells producing apoptotic proteins (CD8⁺EM/Perf⁺GrzB⁺, NK cells/Perf⁺GrzB⁺). Excluding patients in lithium only early activated and cytotoxic cells differentiated the two diagnoses. Limitations include possible residual instrument-related effects and cryopreservation effects, lack of generalization to other phases of the illness, lack of external validation. Our data confirm that MDD and BD show different immune signatures and suggest a more pronounced alteration of immune cell populations in MDD especially in cytotoxic CD8+ cells. Future studies should address these differences to develop more effective therapies for mood disorders.</p>","PeriodicalId":14963,"journal":{"name":"Journal of affective disorders","volume":" ","pages":"122658"},"PeriodicalIF":5.7,"publicationDate":"2026-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149244675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning-based computerized adaptive testing of PHQ-8 and GAD-7 in psychiatric outpatients.","authors":"Edimansyah Abdin, Anitha Jeyagurunathan, Sing Chik Tan, Yee Ming Mok, Swapna Verma, Mengling Feng, Mythily Subramaniam","doi":"10.1016/j.jad.2026.122660","DOIUrl":"https://doi.org/10.1016/j.jad.2026.122660","url":null,"abstract":"<p><strong>Background: </strong>Scalable, accurate and efficient monitoring tools are urgently needed to support psychiatric assessment in routine care. This study aimed to evaluate a machine learning-based computerized adaptive testing (ML-CAT) model for the PHQ-8 and GAD-7 in psychiatric outpatient settings.</p><p><strong>Methods: </strong>Data were obtained from a longitudinal cohort study of patients with depression or anxiety diagnoses. ML-CAT models were developed using the M5P algorithm. Model performance was evaluated via 10-fold cross-validation. Concurrent validity was assessed with Pearson's r, R², and mean absolute error (MAE). Longitudinal change detection used paired t-tests and Cohen's d. Diagnostic classification agreement (based on ≥10 cutoff between assessments) was examined using percentage agreement and Cohen's κ.</p><p><strong>Results: </strong>The ML-CAT administered a median of 2 items per instrument (66-71% item reduction) while achieving near-perfect concurrent validity with full-scale scores (r = 0.996-0.997; R² = 0.986-0.991; MAE < 0.62). Both ML-CAT versions reliably detected symptom reductions at 6 months and 1 year. Classification agreement between ML-CAT and full-scale versions was high at 6 months and 1 year for PHQ-8 (κ = 0.85-0.93) and GAD-7 (κ = 0.91-0.96).</p><p><strong>Conclusions: </strong>The ML-CAT model reproduced PHQ-8 and GAD-7 scores with high accuracy and detected meaningful clinical change across two follow-up waves. The resulting adaptive questionnaire can be presented as a flowchart and administered both online and offline, providing real-world clinical evidence for scalable ML-CAT-based psychiatric assessment.</p>","PeriodicalId":14963,"journal":{"name":"Journal of affective disorders","volume":" ","pages":"122660"},"PeriodicalIF":5.7,"publicationDate":"2026-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149244704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Burden and trends of anxiety, depressive, and bipolar disorders in China from 1990 to 2023: Joinpoint, age-period-cohort effects, and forecasts.","authors":"Sha Wei, Jing Wu, Mingzhao Xiao","doi":"10.1016/j.jad.2026.122657","DOIUrl":"https://doi.org/10.1016/j.jad.2026.122657","url":null,"abstract":"<p><strong>Background: </strong>Anxiety disorders, depressive disorders, and bipolar disorder are major contributors to global disability and functional impairment. Updated evidence on temporal trends, demographic patterns, and projected burden is needed to characterise the population-level burden of these disorders in China.</p><p><strong>Methods: </strong>Using Global Burden of Disease Study 2023 estimates, we assessed disability-adjusted life-year (DALY) counts and age-standardised DALY rates (ASDRs) for anxiety disorders, depressive disorders, and bipolar disorder in China from 1990 to 2023. We described age- and sex-specific DALY patterns in 2023, evaluated ASDR trends using Joinpoint regression, examined age-, period-, and cohort-related patterns using an age-period-cohort estimable-function framework, and decomposed changes in DALY counts into contributions from population growth, population ageing, and epidemiological change. Bayesian age-period-cohort modelling was used to project ASDRs for 2024-2038. We characterised attributable DALY burden for violence- and trauma-related risk factors across applicable disorder-exposure pairs.</p><p><strong>Results: </strong>From 1990 to 2023, ASDRs increased overall for anxiety disorders and depressive disorders, whereas bipolar-disorder ASDRs remained comparatively stable. Anxiety-disorder burden showed a younger age distribution, whereas depressive-disorder burden was more concentrated in middle-to-older adulthood; bipolar-disorder burden was primarily concentrated in midlife. Females generally had higher age-standardised DALY rates than males across all three disorders, with sex disparities largest for anxiety and depressive disorders. Decomposition analyses indicated distinct contributions of population growth, population ageing, and epidemiological change across disorders. Projections suggested a continued increase in the anxiety-disorder ASDR, an initial increase followed by stabilisation or gradual decline in the depressive-disorder ASDR, and a relatively stable bipolar-disorder ASDR through 2038. GBD-derived attributable DALY burden related to bullying victimisation, sexual violence against children, and intimate partner violence varied across eligible risk-outcome pairs and age groups.</p><p><strong>Conclusions: </strong>Mental-disorder burden in China showed heterogeneous temporal and demographic patterns from 1990 to 2023. Anxiety and depressive disorders showed increasing age-standardised burden, whereas bipolar disorder remained comparatively stable in age-standardised terms despite sustained absolute health loss. These population-level descriptive findings and model-based projections provide updated evidence on burden magnitude and trajectories but do not establish individual-level causal mechanisms or intervention effects.</p>","PeriodicalId":14963,"journal":{"name":"Journal of affective disorders","volume":" ","pages":"122657"},"PeriodicalIF":5.7,"publicationDate":"2026-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149244612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"National trends in suicidal ideation, planning, and attempts among US adults aged 50 and older, 2021-2024.","authors":"Kevin H Yang, Tyler Simi, Krish Jagasia, Alison A Moore, Joseph J Palamar","doi":"10.1016/j.jad.2026.122650","DOIUrl":"https://doi.org/10.1016/j.jad.2026.122650","url":null,"abstract":"<p><strong>Background: </strong>Suicide rates among middle-aged and older adults in the US remain disproportionately high, yet recent national trends in suicidal ideation, suicide planning, and suicide attempts and their clinical correlates remain poorly characterized.</p><p><strong>Methods: </strong>This exploratory, serial cross-sectional study analyzed data from the 2021-2024 National Survey on Drug Use and Health, a nationally representative survey of 42,440 US adults aged ≥50 years. Logistic regression estimated temporal trends in suicidality; interaction terms tested differential trends by sociodemographic characteristics, past-year major depressive episode (MDE), serious psychological distress (SPD), substance use, prescription medication misuse, and chronic medical conditions for suicidal ideation and planning.</p><p><strong>Results: </strong>From 2021 through 2024, suicidal ideation increased from 2.0% to 2.9% (p = 0.049), suicide planning from 0.3% to 1.1% (p < 0.001), and suicide attempts from 0.2% to 0.6% (p = 0.02). Significant increases in ideation and planning were concentrated among those without MDE, while increases in ideation were also observed among those without SPD, alcohol use, and prescription medication misuse. Suicide planning increased more steeply among those with cannabis use than those without (449.9% vs. 188.3% increase; interaction p = 0.04).</p><p><strong>Conclusions: </strong>Suicidality increased significantly among US adults aged ≥50 years from 2021 through 2024. While individuals with MDE and other traditional risk factors had elevated absolute risk, increases in ideation were concentrated among those without these factors, and planning increased broadly across most subgroups. These findings highlight potential gaps in prevention frameworks that rely exclusively on traditional risk factor screening and underscore the need for broader risk assessment in this population.</p>","PeriodicalId":14963,"journal":{"name":"Journal of affective disorders","volume":" ","pages":"122650"},"PeriodicalIF":5.7,"publicationDate":"2026-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149238672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}