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Bao C, Han L. Gender difference in anxiety and related factors among adolescents. Front Public Health 2025; 12:1410086. [PMID: 39830180 PMCID: PMC11738925 DOI: 10.3389/fpubh.2024.1410086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Accepted: 12/12/2024] [Indexed: 01/22/2025] Open
Abstract
Background Anxiety is widespread among adolescents, and research has shown that this condition can profoundly affect their mental, emotional, and physical well-being. The purpose of this study was to analyze gender differences in anxiety levels among adolescents and to explore the influencing factors and pathways. Methods A total of 3601 adolescents were included in this study (age: 15.14±1.97 years; male: 48.76%). Gender, age, school category, grade, duration of sleep, duration on Internet, anxiety and several social factors were investigated by online questionnaire. Teachers were responsible for organizing students to fill out the questionnaire. The Generalized Anxiety Disorder (GAD-7) was applied to measure participants' anxiety levels over the past 2 weeks. An Ordinal Logistic Regression measured risk factors of anxiety, while a path analysis was used to estimate the structural relationship between risk factors and anxiety. Results The severity of anxiety in female was higher. Approaching graduation, lack of sleep, poor peer relationships, poor ability to complete tasks, and unwillingness to seek help when in a bad mood were risk factors for anxiety in both male and female adolescents. Among female, prolonged Internet access is a risk factor for anxiety. The fit indices for the modified models were appropriate (male: GFI=0.999, IFI=0.996, TLI=0.976, CFI=0.995, AGFI=0.990, RMSEA=0.021, SRMR=0.016; female: GFI=0.997, IFI=0.990, TLI=0.971, CFI=0.990, AGFI=0.990, RMSEA=0.020, SRMR=0.018). Conclusion The female adolescents might have higher levels of anxiety, that academic stress, sleep, peer relationships, competence, and level of social support might be influence factors on anxiety in adolescents, and that "daily duration on Internet" might not be the risk factor in male adolescent.
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Affiliation(s)
| | - Lili Han
- Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing, China
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Miller CN, Li Y, Beier KT, Aoto J. Acute stress causes sex-dependent changes to ventral subiculum synapses, circuitry, and anxiety-like behavior. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.02.606264. [PMID: 39131353 PMCID: PMC11312572 DOI: 10.1101/2024.08.02.606264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Experiencing a single severe stressor is sufficient to drive sexually dimorphic psychiatric disease development. The ventral subiculum (vSUB) emerges as a site where stress may induce sexually dimorphic adaptations due to its sex-specific organization and pivotal role in stress integration. Using a 1-hr acute restraint stress model, we uncover that stress causes a net decrease in vSUB activity in females that is potent, long-lasting, and driven by adrenergic receptor signaling. By contrast, males exhibit a net increase in vSUB activity that is transient and driven by corticosterone signaling. We further identified sex-dependent changes in vSUB output to the bed nucleus of the stria terminalis and in anxiety-like behavior in response to stress. These findings reveal striking changes in psychiatric disease-relevant brain regions and behavior following stress with sex-, cell-type, and synapse-specificity that contribute to our understanding of sex-dependent adaptations that may shape stress-related psychiatric disease risk.
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Affiliation(s)
- Carley N Miller
- Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Yuan Li
- Department of Physiology and Biophysics, University of California, Irvine, CA, USA 92697
| | - Kevin T Beier
- Department of Physiology and Biophysics, University of California, Irvine, CA, USA 92697
- Department of Neurobiology and Behavior, University of California, Irvine, CA, USA 92697
- Department of Biomedical Engineering, University of California, Irvine, CA, USA 92697
- Department of Pharmaceutical Sciences, University of California, Irvine, CA, USA 92697
| | - Jason Aoto
- Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
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Han X, Zeng Y, Shang Y, Hu Y, Hou C, Yang H, Chen W, Ying Z, Sun Y, Qu Y, Wang J, Zhang W, Fang F, Valdimarsdóttir U, Song H. Risk of Cardiovascular Disease Hospitalization After Common Psychiatric Disorders: Analyses of Disease Susceptibility and Progression Trajectory in the UK Biobank. PHENOMICS (CHAM, SWITZERLAND) 2024; 4:327-338. [PMID: 39583312 PMCID: PMC11584824 DOI: 10.1007/s43657-023-00134-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 10/01/2023] [Accepted: 10/11/2023] [Indexed: 11/26/2024]
Abstract
Whether associations between psychiatric disorders and hospitalization for cardiovascular diseases (CVDs) can be modified by disease susceptibility and the temporal pattern of these associated CVDs remain unknown. In our study, we conducted a matched cohort study of the UK Biobank including 44,430 patients with common psychiatric disorders (anxiety, depression, and stress-related disorders) between 1997 and 2019, together with 222,150 sex-, Townsend deprivation index-, and birth year- individually matched unexposed individuals. The hazard ratios (HRs) for CVD hospitalization associated with a prior psychiatric disorder were derived from Cox models, adjusted for multiple confounders. We then stratified the analyses by self-reported family history of CVD and CVD polygenic risk score (PRS) calculated based on summary statistics of independent genome-wide association studies. We further conducted disease trajectory analysis and visualized the temporal pattern of CVDs after common psychiatric disorders. During a mean follow-up of 12.28 years, we observed an elevated risk of CVD hospitalization among patients with psychiatric disorders, compared with matched unexposed individuals (hazard ratios [HRs] = 1.20, 95% confidence interval [CI]: 1.18-1.23), especially during the first six months of follow-up (1.72 [1.55-1.91]). The stratification analyses by family history of CVD and by CVD PRS obtained similar estimates between subgroups with different susceptibilities to CVD. We conducted trajectory analysis to visualize the temporal pattern of CVDs after common psychiatric disorders, identifying primary hypertension, acute myocardial infarction, and stroke as three main intermediate steps leading to further increased risk of other CVDs. In conclusion, the association between common psychiatric disorders and subsequent CVD hospitalization is not modified by predisposition to CVD. Hypertension, acute myocardial infarction, and stroke are three initial CVDs linking psychiatric disorders to other CVD sequelae, highlighting a need of timely intervention on these targets to prevent further CVD sequelae among all individuals with common psychiatric disorders. Supplementary Information The online version contains supplementary material available at 10.1007/s43657-023-00134-w.
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Affiliation(s)
- Xin Han
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Guo Xue Lane 37, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
| | - Yu Zeng
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Guo Xue Lane 37, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
| | - Yanan Shang
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Guo Xue Lane 37, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
| | - Yao Hu
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Guo Xue Lane 37, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
| | - Can Hou
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Guo Xue Lane 37, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
| | - Huazhen Yang
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Guo Xue Lane 37, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
| | - Wenwen Chen
- Division of Nephrology, Kidney Research Institute, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, 610000 China
| | - Zhiye Ying
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Guo Xue Lane 37, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
| | - Yajing Sun
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Guo Xue Lane 37, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
| | - Yuanyuan Qu
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Guo Xue Lane 37, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
| | - Junren Wang
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Guo Xue Lane 37, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
| | - Wei Zhang
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Guo Xue Lane 37, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, 610000 China
| | - Fang Fang
- Institute of Environmental Medicine, Karolinska Institutet, 17177 Stockholm, Sweden
| | - Unnur Valdimarsdóttir
- Center of Public Health Sciences, Faculty of Medicine, University of Iceland, 102 Reykjavík, Iceland
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 17177 Stockholm, Sweden
- Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA 02115 USA
| | - Huan Song
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Guo Xue Lane 37, Chengdu, 610000 China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610000 China
- Center of Public Health Sciences, Faculty of Medicine, University of Iceland, 102 Reykjavík, Iceland
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Stevens SK, Williams DP, Thayer JF, Zalta AK. Differential Associations of Childhood Abuse and Neglect With Adult Autonomic Regulation and Mood-Related Pathology. Psychosom Med 2023; 85:682-690. [PMID: 37506294 DOI: 10.1097/psy.0000000000001239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/30/2023]
Abstract
OBJECTIVE This study assessed whether different types of childhood maltreatment (i.e., abuse versus neglect) had differential relationships with heart rate variability (HRV) and baroreflex sensitivity. In addition, this study tested the indirect effect of maltreatment subtypes on adult mood-related psychopathology via HRV, and whether these relationships differed in those with HRV above and below established clinical cutoffs. METHODS Secondary analysis was performed using the Midlife Development in the United States data set ( N = 967; Mage = 55; 58.4% female; 75.9% White). In a single study visit, autonomic measurements were captured at rest, during two cognitive stressors (Stroop and MATH tasks), and during recovery after the tasks. Structural equation modeling was used to assess the relationships between key variables during all three measurement periods. RESULTS Resting pathways from abuse and neglect to baroreflex sensitivity were nonsignificant, as was the pathway from HRV to mood-related pathology. Notably, greater abuse was significantly predictive of lower HRV (standardized β = -0.42, p = .009), whereas greater neglect was significantly predictive of higher HRV (standardized β = 0.32, p = .034). In addition, higher abuse was significantly predictive of greater adult symptoms (standardized β = 0.39, p < .001), but neglect was not found to be related to adult mood-related pathology. Significant relationships between variables were only found in those with low HRV. CONCLUSIONS Although cross-sectional, our findings provide further evidence that low HRV may be a transdiagnostic endophenotype for mood-related pathology and suggest that greater differentiation between abuse and neglect is appropriate when investigating the impact of childhood maltreatment on adult health outcomes.
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Affiliation(s)
- Sarah K Stevens
- From the Department of Psychological Science, University of California-Irvine, Irvine, California
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