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Xiao Y, Chen TT, Zhang Z, Liu L, Du N. Changes in the Disease Burden of Depressive Disorders Among Middle-Aged and Older Adults (Aged 45-89) in China Over 30 years: Insights From the Global Burden of Disease Study 2021. Int J Geriatr Psychiatry 2025; 40:e70069. [PMID: 40090859 DOI: 10.1002/gps.70069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2024] [Revised: 01/29/2025] [Accepted: 03/06/2025] [Indexed: 03/17/2025]
Abstract
OBJECTIVES In China, depressive disorder (DD) among middle-aged and older adults is a significant public health concern. This research utilized the latest Global Burden of Disease Study (GBD) database to evaluate the evolving disease burden of DD in this demographic over the past 3 decades. METHODS Data on the incidence and disability-adjusted life years (DALY) of DD among people aged 45-89 in China between 1992 and 2021 were collected from the GBD 2021. The age-period-cohort (APC) model was applied to determine the effects of age, period, and cohort on the incidence and DALY rates of DD. RESULTS (1) Over the last 30 years, there was a 6.49% increase in the overall age-standardized incidence rate (ASIR) and a 3.99% increase in age-standardized DALY rates (ASDR) for DD among middle-aged and older adults in China, with females consistently exhibiting higher ASIR and ASDR than males. In 2020, COVID-19 significantly increased the ASIR and ASDR of DD in the population, especially in females. (2) The APC analysis revealed an annual net drift of 0.38% in incidence and 0.17% in DALY rate. For both genders, local drifts of incidence were negative for the 45-54 age group and positive for the 55-89 age group; DALY rates showed negative local drifts for the 45-59 age group and positive for the 60-89 age group. (3) Incidence and DALY rates increased with age, displaying a trend of initial decline followed by an increase in period effects, but a trend of initial increase followed by a decrease in cohort effects. Moreover, the impacts of age, period, and cohort exhibited gender differences. CONCLUSIONS Our findings provide a comprehensive and in-depth perspective for studying the changing trends of DD's burden in China and for identifying targeted prevention and treatment policies for DD from different aspects.
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Affiliation(s)
- Yu Xiao
- Psychosomatic Medical Center, The Fourth People's Hospital of Chengdu, Chengdu, China
| | - Ting-Ting Chen
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Zhou Zhang
- Department of Gastroenterology, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang, China
| | - Liang Liu
- Department of Urology, Baoding No.1 Central Hospital, Baoding, China
| | - Na Du
- Psychosomatic Medical Center, The Fourth People's Hospital of Chengdu, Chengdu, China
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Ma S, Huang D, Ji S, Mi G, Zheng D. Network of depression and anxiety symptoms in Chinese middle-aged and older people and its relationship with family health. Rev Esc Enferm USP 2025; 58:e20240136. [PMID: 39918344 PMCID: PMC11804662 DOI: 10.1590/1980-220x-reeusp-2024-0136en] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2024] [Accepted: 11/23/2024] [Indexed: 02/09/2025] Open
Abstract
OBJECTIVE To examine the network structure of depression and anxiety symptoms and their association with Family Health among middle-aged and older people in China. METHOD This was a quantitative cross-sectional study, a total of 3,365 middle-aged and older people over 45 years were recruited, comprising 1,748 males and 1,617 females. Data were collected by using Patient Health Questionnaire-9, the Generalized Anxiety Disorder-7, and the Short Form of the Family Health Scale. RESULTS The network structure of anxiety and depression symptoms was stable, and "Fatigue" and "Restlessness" were central symptoms and bridge symptoms. "Family, social or emotional health process" and "Family Healthy Lifestyle" exhibited a significant positive correlation, whereas "Family health resources" and "Suicide" demonstrated a significant negative correlation. CONCLUSION "Fatigue" and "Restlessness" are the targeted symptoms for preventing comorbid depression and anxiety symptoms among middle-aged and older adults, and the enhancement of "Family health resources" could be crucial for averting the onset of depression and anxiety symptoms within this demographic group.
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Affiliation(s)
- Shilin Ma
- Ningxia Medical University, School of Nursing, Yinchuan, China
| | - Doudou Huang
- Ningxia Medical University, School of Nursing, Yinchuan, China
| | - Shuangdui Ji
- Ningxia Medical University, General Hospital, Yinchuan, China
| | - Guangli Mi
- Ningxia Medical University, General Hospital, Nursing Department, Yinchuan, China
| | - Donglian Zheng
- Ningxia Medical University, General Hospital, Yinchuan, China
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Zheng YB, Huang YT, Gong YM, Li MZ, Zeng N, Wu SL, Zhang ZB, Tian SS, Yuan K, Liu XX, Vitiello MV, Wang YM, Wang YX, Zhang XJ, Shi J, Shi L, Yan W, Lu L, Bao YP. Association of lifestyle with sleep health in general population in China: a cross-sectional study. Transl Psychiatry 2024; 14:320. [PMID: 39098892 PMCID: PMC11298538 DOI: 10.1038/s41398-024-03002-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 06/24/2024] [Accepted: 07/02/2024] [Indexed: 08/06/2024] Open
Abstract
The concept of a healthy lifestyle is receiving increasing attention. This study sought to identify an optimal healthy lifestyle profile associated with sleep health in general population of China. An online cross-sectional survey was conducted from June to July 2022. Six healthy lifestyle factors were assessed: healthy diet, regular physical exercise, never smoking, never drinking alcohol, low sedentary behavior, and normal weight. Participants were categorized into the healthy lifestyle (5-6 factors), average (3-4 factors), and unhealthy lifestyle groups (0-2 factors). The study's primary outcome was sleep health, which included sleep quality, duration, pattern, and the presence of any sleep disorder or disturbance, including insomnia, excessive daytime sleepiness, obstructive apnea syndrome, and narcolepsy. Multivariable logistic regression analysis was applied to explore lifestyles associated with the selected sleep health outcomes. 41,061 individuals were included, forming 18.8% healthy, 63.8% average, and 17.4% unhealthy lifestyle groups. After adjusting for covariates, participants with healthy lifestyle were associated with a higher likelihood of good sleep quality (OR = 1.56, 95% CI = 1.46-1.68), normal sleep duration (OR = 1.60, 95% CI = 1.49-1.72), healthy sleep pattern (OR = 2.15, 95% CI = 2.00-2.31), and lower risks of insomnia (OR = 0.66, 95% CI = 0.61-0.71), excessive daytime sleepiness (OR = 0.66, 95% CI = 0.60-0.73), and obstructive apnea syndrome (OR = 0.40, 95% CI = 0.37-0.43), but not narcolepsy (OR = 0.92, 95% CI = 0.83-1.03), compared to those with unhealthy lifestyle. This large cross-sectional study is the first to our knowledge to quantify the associations of a healthy lifestyle with specific aspects of sleep health. The findings offer support for efforts to improve sleep health by modulating lifestyle.
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Affiliation(s)
- Yong-Bo Zheng
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
- Peking-Tsinghua Centre for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Yue-Tong Huang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Yi-Miao Gong
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Ming-Zhe Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
- Peking-Tsinghua Centre for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Na Zeng
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China
- School of Public Health, Peking University, Beijing, China
| | - Shui-Lin Wu
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China
- School of Public Health, Peking University, Beijing, China
| | - Zhi-Bo Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Shan-Shan Tian
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Kai Yuan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Xiao-Xing Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Michael V Vitiello
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA
| | - Yu-Mei Wang
- Institute of Brain Science and Brain-inspired Research, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong Province, 250117, China
| | - Yong-Xiang Wang
- Institute of Brain Science and Brain-inspired Research, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong Province, 250117, China
| | - Xiu-Jun Zhang
- School of Psychology, College of Public Health, North China University of Science and Technology, Tangshan, 063210, Hebei Province, China
| | - Jie Shi
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China
| | - Le Shi
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China.
| | - Wei Yan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China.
| | - Lin Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China.
- Peking-Tsinghua Centre for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China.
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China.
- Chinese Academy of Medical Sciences Research Unit (No. 2018RU006), Peking University, Beijing, China.
- Shandong Institute of Brain Science and Brain-inspired Research; Medical Science and Technology Innovation Center, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong Province, 271016, China.
| | - Yan-Ping Bao
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China.
- School of Public Health, Peking University, Beijing, China.
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Liu X, Liu M, Ai G, Hu N, Liu W, Lai C, Xu F, Xie Z. Sleep and mental health during the COVID-19 pandemic: findings from an online questionnaire survey in China. Front Neurol 2024; 15:1396673. [PMID: 38952466 PMCID: PMC11215081 DOI: 10.3389/fneur.2024.1396673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Accepted: 05/27/2024] [Indexed: 07/03/2024] Open
Abstract
Introduction The online study investigated the sleep, psychological conditions, and risk factors during the wave of transmission of COVID-19 since December 7, 2022. Methods We distributed questionnaires through networking mediums to residents to gather information about COVID-19 infection, sleep, and mental status. Results During the extraordinary period in China, 91.9% of 1094 participants claimed to be infected with COVID-19, 36.8% reported poor sleep quality, 75.9% reported anxiety, and 65.5% reported depression. In retrospect, people have experienced lower sleep quality, longer sleep latency, enhanced rising time, and decreased sleep efficiency after the infection wave. After adjusting confounding factors, the elderly, women, urban residents, people with comorbidity, anxiety, depression, stress state, and COVID-19 infection have high risks for sleep disorders during the period. Discussion The survey indicates that sleep disturbance caused by COVID-19 involves multiple dimensions, such as physiology, psychology, and society. The COVID-19 infection-related sleep problem should be taken seriously. Apart from conventional treatment, psychological issues of insomnia can not be ignored.
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Affiliation(s)
- Xuqian Liu
- Department of Neurology, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Mingyue Liu
- Department of Neurology, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Guangyuan Ai
- Department of Neurology, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Naijun Hu
- Department of Neurology, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Wenhan Liu
- Department of Neurology, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Chao Lai
- Department of Neurology, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Feng Xu
- School of Management, Shandong University, Jinan, China
| | - Zhaohong Xie
- Department of Neurology, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
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Chan JK, Marzuki AA, Vafa S, Thanaraju A, Yap J, Chan XW, Harris HA, Todi K, Schaefer A. A systematic review on the relationship between socioeconomic conditions and emotional disorder symptoms during Covid-19: unearthing the potential role of economic concerns and financial strain. BMC Psychol 2024; 12:237. [PMID: 38671542 PMCID: PMC11046828 DOI: 10.1186/s40359-024-01715-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 04/07/2024] [Indexed: 04/28/2024] Open
Abstract
BACKGROUND Covid-19 has disrupted the lives of many and resulted in high prevalence rates of mental disorders. Despite a vast amount of research into the social determinants of mental health during Covid-19, little is known about whether the results are consistent with the social gradient in mental health. Here we report a systematic review of studies that investigated how socioeconomic condition (SEC)-a multifaceted construct that measures a person's socioeconomic standing in society, using indicators such as education and income, predicts emotional health (depression and anxiety) risk during the pandemic. Furthermore, we examined which classes of SEC indicators would best predict symptoms of emotional disorders. METHODS Following PRISMA guidelines, we conducted search over six databases, including Scopus, PubMed, etc., between November 4, 2021 and November 11, 2021 for studies that investigated how SEC indicators predict emotional health risks during Covid-19, after obtaining approval from PROSPERO (ID: CRD42021288508). Using Covidence as the platform, 362 articles (324 cross-sectional/repeated cross-sectional and 38 longitudinal) were included in this review according to the eligibility criteria. We categorized SEC indicators into 'actual versus perceived' and 'static versus fluid' classes to explore their differential effects on emotional health. RESULTS Out of the 1479 SEC indicators used in these 362 studies, our results showed that 43.68% of the SEC indicators showed 'expected' results (i.e., higher SEC predicting better emotional health outcomes); 51.86% reported non-significant results and 4.46% reported the reverse. Economic concerns (67.16% expected results) and financial strains (64.16%) emerged as the best predictors while education (26.85%) and living conditions (30.14%) were the worst. CONCLUSIONS This review summarizes how different SEC indicators influenced emotional health risks across 98 countries, with a total of 5,677,007 participants, ranging from high to low-income countries. Our findings showed that not all SEC indicators were strongly predictive of emotional health risks. In fact, over half of the SEC indicators studied showed a null effect. We found that perceived and fluid SEC indicators, particularly economic concerns and financial strain could best predict depressive and anxiety symptoms. These findings have implications for policymakers to further understand how different SEC classes affect mental health during a pandemic in order to tackle associated social issues effectively.
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Affiliation(s)
- Jee Kei Chan
- Department of Psychology, Monash University Malaysia, Jalan Lagoon Selatan, 47500, Bandar Sunway, Petaling Jaya, Selangor Darul Ehsan, Malaysia.
- Department of Psychology, Sunway University Malaysia, Jalan Universiti, No 5, 47500, Bandar Sunway, Petaling Jaya, Selangor Darul Ehsan, Malaysia.
- Sunway University Malaysia, Room: 4-4-11, Jalan Lagoon Selatan, Bandar Sunway, Petaling Jaya, 47500, Selangor, Malaysia.
| | - Aleya A Marzuki
- Department of Psychology, Sunway University Malaysia, Jalan Universiti, No 5, 47500, Bandar Sunway, Petaling Jaya, Selangor Darul Ehsan, Malaysia
| | - Samira Vafa
- Department of Psychology, Sunway University Malaysia, Jalan Universiti, No 5, 47500, Bandar Sunway, Petaling Jaya, Selangor Darul Ehsan, Malaysia
| | - Arjun Thanaraju
- Department of Psychology, Sunway University Malaysia, Jalan Universiti, No 5, 47500, Bandar Sunway, Petaling Jaya, Selangor Darul Ehsan, Malaysia
| | - Jie Yap
- Department of Psychology, Sunway University Malaysia, Jalan Universiti, No 5, 47500, Bandar Sunway, Petaling Jaya, Selangor Darul Ehsan, Malaysia
| | - Xiou Wen Chan
- Department of Psychology, Monash University Malaysia, Jalan Lagoon Selatan, 47500, Bandar Sunway, Petaling Jaya, Selangor Darul Ehsan, Malaysia
| | - Hanis Atasha Harris
- Department of Psychology, Monash University Malaysia, Jalan Lagoon Selatan, 47500, Bandar Sunway, Petaling Jaya, Selangor Darul Ehsan, Malaysia
| | - Khushi Todi
- Department of Psychology, Monash University Malaysia, Jalan Lagoon Selatan, 47500, Bandar Sunway, Petaling Jaya, Selangor Darul Ehsan, Malaysia
| | - Alexandre Schaefer
- Department of Psychology, Sunway University Malaysia, Jalan Universiti, No 5, 47500, Bandar Sunway, Petaling Jaya, Selangor Darul Ehsan, Malaysia
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Li C, Guo D, Liu S, Yu A, Sun C, Zhou L. COVID-19 pandemic impacts on the elderly: the relationship between PPPD and prefrontal alpha rhythm. Int J Neurosci 2024; 134:341-346. [PMID: 35848522 DOI: 10.1080/00207454.2022.2102978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 07/06/2022] [Accepted: 07/12/2022] [Indexed: 10/31/2022]
Abstract
BACKGROUND In the COVID-19 epidemic more patients presented with persistent postural-perceptual dizziness (PPPD), but it has received little attention by the doctors in China and many patients reject psychological measurements or scales. Therefore, there is an urgent need for an objective method to diagnose and evaluate PPPD. OBJECTIVE To investigate the effect of the COVID-19 epidemic on elderly PPPD patients and define the relationship between prefrontal alpha rhythm asymmetry (FAA) by Electroencephalography (EEG) and PPPD. METHODS This case-control study was conducted to discuss the differences of elderly outpatients (>60 years) with PPPD during the peak period of COVID-19 in 2020 and the corresponding period in 2019, and collect the prefrontal FAA value in PPPD during COVID-19 outbreak, which were compared to its FAA in healthy control. RESULTS Compared with the same period in 2019, the number of elderly PPPD patients during the epidemic period in 2020 increased significantly (16.4%, p = 0.000, x2 =31.802) . The left alpha wave signal power (F3) was significantly higher than the right alpha wave signal power (F4) (Z= -3.073, p = 0.002). In PPPD patients FAA were significantly lower in patients compared to control group (Z = -11.535, p = 0.000). There was a negative correlation between FAA and HAMA scores (R2 =0.906, p < 0.05) and a negative correlation between FAA and HAMD scores (R2 =0.859, p < 0.05), too. CONCLUSIONS The increase in cases of elderly PPPD patients is most likely attributed to the mental health in older adults during the COVID-19 pandemic. Less left frontal brain activity in EEG may be related to elderly PPPD.
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Affiliation(s)
- Changqing Li
- Department of Neurology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, PR China
| | - Dongsheng Guo
- Department of Emergency, Beijing Chaoyang Hospital, Capital Medical University, Beijing, PR China
| | - Siwei Liu
- Department of Neurology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, PR China
| | - Aihui Yu
- Department of Neurology, The Sixth Medical Center of PLA General Hospital, Beijing, PR China
| | - Chenjing Sun
- Department of Neurology, The Sixth Medical Center of PLA General Hospital, Beijing, PR China
| | - Lichun Zhou
- Department of Neurology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, PR China
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Liao DD, Hu JH, Ding KR, Hou CL, Tan WY, Ke YF, Jia FJ, Wang SB. Prevalence and Patterns of Insomnia Symptoms Among People Aged 65 and Above in Guangdong Province, China. ALPHA PSYCHIATRY 2024; 25:233-242. [PMID: 38798807 PMCID: PMC11117421 DOI: 10.5152/alphapsychiatry.2024.231458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Accepted: 02/28/2024] [Indexed: 05/29/2024]
Abstract
Objective This survey investigated the prevalence, distribution, and correlative factors of insomnia symptoms among people aged 65 and above in Guangdong Province, China. Methods The Guangdong Mental Health Survey was conducted on the elderly in all 21 cities of Guangdong Province from September to December 2021. Multistage stratified cluster sampling was adopted, and 16 377 adult residents were interviewed face-to-face, from which 4001 elderly participants aged 65 and above were included for this study. Complex weighted adjustment methods were applied to weight the data. Multinomial logistic regression was applied to test the independent associations of clinical insomnia symptoms (CIS) and subthreshold insomnia symptoms (SIS) with the factors. Results The pooled estimate of insomnia symptoms was 13.44% [95% confidence interval (CI): 12.2 %-14.7%]. The 1-month weighted prevalence of SIS and CIS were 11.15% (95% CI: 10.05%-12.37%) and 2.28% (95%CI: 1.77%-2.94%), respectively. Multinomial logistic regression analysis revealed that urban residence, irregular diet, low body mass index, chronic disease, napping 3-4/week, early changes in dementia, symptoms of subthreshold depression, subthreshold generalized anxiety, and generalized anxiety disorder were positively associated with SIS. Additionally, living in urban areas, having chronic diseases, symptoms of subthreshold depression, major depressive disorder, subthreshold generalized anxiety, generalized anxiety disorder were positively associated with CIS. Conclusion Insomnia symptoms, including CIS and SIS, were prevalent among the elderly in Guangdong Province. Given the high burden of CIS and SIS, policymakers and healthcare professionals must explore and treat the related factors accordingly.
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Affiliation(s)
- Dan-Dan Liao
- Guangdong Mental Health Center, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangdong, China
- Southern Medical University, Second School of Clinical Medicine, Guangdong, China
| | - Jia-Hui Hu
- Guangdong Mental Health Center, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangdong, China
- Department of Psychology, Southern Medical University, School of Public Health, Guangdong, China
| | - Kai-Rong Ding
- Guangdong Mental Health Center, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangdong, China
- Department of Psychology, Southern Medical University, School of Public Health, Guangdong, China
| | - Cai-Lan Hou
- Guangdong Mental Health Center, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangdong, China
- Southern Medical University, Second School of Clinical Medicine, Guangdong, China
- Department of Psychology, Southern Medical University, School of Public Health, Guangdong, China
| | - Wen-Yan Tan
- Guangdong Mental Health Center, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangdong, China
| | - Yun-Fei Ke
- Guangdong Mental Health Center, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangdong, China
| | - Fu-Jun Jia
- Guangdong Mental Health Center, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangdong, China
- Southern Medical University, Second School of Clinical Medicine, Guangdong, China
- Department of Psychology, Southern Medical University, School of Public Health, Guangdong, China
| | - Shi-Bin Wang
- Guangdong Mental Health Center, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangdong, China
- Zhuhai College of Science and Technology, School of Health, Guangdong, China
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8
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Gao N, Zheng Y, Yang Y, Huang Y, Wang S, Gong Y, Zeng N, Ni S, Wu S, Su S, Zhang Z, Yuan K, Shi L, Zhang Z, Yan W, Lu L, Bao Y. Association between Shift Work and Health Outcomes in the General Population in China: A Cross-Sectional Study. Brain Sci 2024; 14:145. [PMID: 38391721 PMCID: PMC10886504 DOI: 10.3390/brainsci14020145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Revised: 01/05/2024] [Accepted: 01/16/2024] [Indexed: 02/24/2024] Open
Abstract
Shift work may adversely affect individuals' health, thus, the current study aimed to investigate the association between shift work and health outcomes in the general population. A total of 41,061 participants were included in this online cross-sectional survey, among which 9612 (23.4%) individuals engaged in shift work and 31,449 (76.6%) individuals engaged in non-shift work. Multiple logistic regression analyses were conducted to explore the association between shift work and health outcomes (psychiatric disorders, mental health symptoms, and physical disorders). In addition, associations between the duration (≤1 year, 1-3 years, 3-5 years, 5-10 years, ≥10 years) and frequency of shift work (<1 or ≥1 night/week) and health outcomes were also explored. The results showed that compared to non-shift workers, shift workers had a higher likelihood of any psychiatric disorders (odds ratios [OR] = 1.80, 95% CI = 1.56-2.09, p < 0.001), mental health symptoms (OR = 1.76, 95% CI = 1.68-1.85, p < 0.001), and physical disorders (OR = 1.48, 95% CI = 1.39-1.57, p < 0.001). In addition, inverted U-shaped associations were observed between the duration of shift work and health outcomes. These results indicated that shift work was closely related to potential links with poor health outcomes. The findings highlighted the importance of paying attention to the health conditions of shift workers and the necessity of implementing comprehensive protective measures for shift workers to reduce the impact of shift work.
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Affiliation(s)
- Nan Gao
- The First Affiliated Hospital of Xinxiang Medical University, Xinxiang Medical University, Xinxiang 453199, China
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China
| | - Yongbo Zheng
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China
- Peking-Tsinghua Centre for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100191, China
| | - Yingbo Yang
- The First Affiliated Hospital of Xinxiang Medical University, Xinxiang Medical University, Xinxiang 453199, China
| | - Yuetong Huang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China
| | - Sanwang Wang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Yimiao Gong
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China
| | - Na Zeng
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China
- School of Public Health, Peking University, Beijing 100191, China
| | - Shuyu Ni
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China
- School of Public Health, Peking University, Beijing 100191, China
| | - Shuilin Wu
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China
- School of Public Health, Peking University, Beijing 100191, China
| | - Sizhen Su
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China
| | - Zhibo Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China
| | - Kai Yuan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China
| | - Le Shi
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China
| | - Zhaohui Zhang
- The First Affiliated Hospital of Xinxiang Medical University, Xinxiang Medical University, Xinxiang 453199, China
| | - Wei Yan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China
| | - Lin Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China
- Peking-Tsinghua Centre for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100191, China
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China
- Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder, Chinese Academy of Medical Sciences (No. 2018RU006), Beijing 100191, China
| | - Yanping Bao
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China
- School of Public Health, Peking University, Beijing 100191, China
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9
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Su S, Zhao Y, Zeng N, Liu X, Zheng Y, Sun J, Zhong Y, Wu S, Ni S, Gong Y, Zhang Z, Gao N, Yuan K, Yan W, Shi L, Ravindran AV, Kosten T, Shi J, Bao Y, Lu L. Epidemiology, clinical presentation, pathophysiology, and management of long COVID: an update. Mol Psychiatry 2023; 28:4056-4069. [PMID: 37491461 DOI: 10.1038/s41380-023-02171-3] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 06/20/2023] [Accepted: 06/27/2023] [Indexed: 07/27/2023]
Abstract
The increasing number of coronavirus disease 2019 (COVID-19) infections have highlighted the long-term consequences of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection called long COVID. Although the concept and definition of long COVID are described differently across countries and institutions, there is general agreement that it affects multiple systems, including the immune, respiratory, cardiovascular, gastrointestinal, neuropsychological, musculoskeletal, and other systems. This review aims to provide a synthesis of published epidemiology, symptoms, and risk factors of long COVID. We also summarize potential pathophysiological mechanisms and biomarkers for precise prevention, early diagnosis, and accurate treatment of long COVID. Furthermore, we suggest evidence-based guidelines for the comprehensive evaluation and management of long COVID, involving treatment, health systems, health finance, public attitudes, and international cooperation, which is proposed to improve the treatment strategies, preventive measures, and public health policy making of long COVID.
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Affiliation(s)
- Sizhen Su
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yimiao Zhao
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China
- Scholl of Public Health, Peking University, Beijing, China
| | - Na Zeng
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China
- Scholl of Public Health, Peking University, Beijing, China
| | - Xiaoxing Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yongbo Zheng
- Peking-Tsinghua Center for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Jie Sun
- Pain Medicine Center, Peking University Third Hospital, Beijing, China
| | - Yi Zhong
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Shuilin Wu
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China
- Scholl of Public Health, Peking University, Beijing, China
| | - Shuyu Ni
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China
- Scholl of Public Health, Peking University, Beijing, China
| | - Yimiao Gong
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
- Peking-Tsinghua Center for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Zhibo Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Nan Gao
- The First Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
| | - Kai Yuan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Wei Yan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Le Shi
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Arun V Ravindran
- Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Thomas Kosten
- Department of Psychiatry, Baylor College of Medicine, Houston, TX, USA
| | - Jie Shi
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China
| | - Yanping Bao
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China.
- Scholl of Public Health, Peking University, Beijing, China.
| | - Lin Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China.
- Peking-Tsinghua Center for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China.
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10
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Mi W, Di X, Wang Y, Li H, Xu X, Li L, Wang H, Wang G, Zhang K, Tian F, Luo J, Yang C, Zhou Y, Xie S, Zhong H, Wu B, Yang D, Chen Z, Li Y, Chen J, Lv S, Yi Q, Jiang Z, Tian J, Zhang H. A phase 3, multicenter, double-blind, randomized, placebo-controlled clinical trial to verify the efficacy and safety of ansofaxine (LY03005) for major depressive disorder. Transl Psychiatry 2023; 13:163. [PMID: 37164957 PMCID: PMC10171157 DOI: 10.1038/s41398-023-02435-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 03/31/2023] [Accepted: 04/18/2023] [Indexed: 05/12/2023] Open
Abstract
Major depressive disorder (MDD) is the most prevalent form of depression and is becoming a great challenge for public health and medical practice. Although first-line antidepressants offer therapeutic benefits, about 35% of depressed patients are not adequately treated, creating a substantial unmet medical need. A multicenter, double-blind, randomized, placebo-controlled phase 3 clinical trial was conducted in patients with MDD in China to assess the efficacy and safety of ansofaxine (LY03005), a potential triple reuptake inhibitor of serotonin, norepinephrine, and dopamine. Eligible 588 MDD patients were included and randomly assigned (1:1:1) to 8-week treatment with ansofaxine 80 mg/day(n = 187), ansofaxine 160 mg/day(n = 186), or placebo(n = 185). The primary efficacy endpoint was the Montgomery-Åsberg Depression Rating Scale (MADRS) total score change from baseline to the end of the study. Safety indexes included adverse events, vital signs, physical examination, laboratory tests, 12-lead electrocardiogram (ECG), and evaluation of suicide tendency and sexual function. Significant differences were found in mean changes in MADRS total score at week 8 in the two ansofaxine groups (80 mg, -20.0; 160 mg, -19.9) vs. placebo (-14.6; p < 0.0001). All doses of ansofaxine were generally well-tolerated. Treatment-emergent adverse events (TEAEs) were reported by 137 (74.46%) patients in ansofaxine 80 mg group, 144 (78.26%) patients in ansofaxine 160 mg and 125 (67.93%) patients in the placebo group. The incidence of treatment-related adverse events (TRAEs) was 59.2% (109 patients), 65.22% (120 patients) in the 80, 160 mg ansofaxine groups, and 45.11% (83 patients) in the placebo group. The initial results of this trial indicate that ansofaxine at both the 80 mg/day and 160 mg/day was effective and safe in adult patients with MDD. ClinicalTrials.gov Identifier: NCT04853407.
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Affiliation(s)
- Weifeng Mi
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Xiaolan Di
- Beijing Huilongguan Hospital, Beijing, China
| | - Yiming Wang
- The Affiliated Hospital of Guizhou Medical University, Guizhou, China
| | - Huafang Li
- Shanghai Mental Health Center, Shanghai, China
| | - Xiufeng Xu
- First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Lehua Li
- Second Xiangya Hospital of Central South University, Changsha, China
| | - Huaning Wang
- First Affiliated Hospital of the Fourth Military Medical University of Chinese People's Liberation Army, Xi'an, China
| | | | - Kerang Zhang
- First Hospital of Shanxi Medical University, Taiyuan, China
| | - Feng Tian
- Second Hospital of Shanxi Medical University, Taiyuan, China
| | - Jiong Luo
- Beijing Anding Hospital of Capital Medical University, Beijing, China
| | - Chanjuan Yang
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | | | | | - Hua Zhong
- Huzhou Third Municipal Hospital, Huzhou, China
| | - Bin Wu
- Xi 'an Mental Health Center, Xi'an, China
| | - Dong Yang
- Hunan Brain Hospital, Changsha, China
| | - Zhenhua Chen
- Renmin Hospital of Wuhan University, Wuhan, China
| | - Yi Li
- Wuhan Mental Health Center, Wuhan, China
| | | | - Shuyun Lv
- The Fourth People Hospital of Urumqi, Urumqi, China
| | - Qizhong Yi
- The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Zhiwei Jiang
- Beijing KeyTech Statistical Technology Co., Ltd, Beijing, China
| | | | - Hongyan Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
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11
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Zheng YB, Zeng N, Yuan K, Tian SS, Yang YB, Gao N, Chen X, Zhang AY, Kondratiuk AL, Shi PP, Zhang F, Sun J, Yue JL, Lin X, Shi L, Lalvani A, Shi J, Bao YP, Lu L. Prevalence and risk factor for long COVID in children and adolescents: A meta-analysis and systematic review. J Infect Public Health 2023; 16:660-672. [PMID: 36931142 PMCID: PMC9990879 DOI: 10.1016/j.jiph.2023.03.005] [Citation(s) in RCA: 80] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 01/09/2023] [Accepted: 03/05/2023] [Indexed: 03/09/2023] Open
Abstract
BACKGROUND Millions of COVID-19 pediatric survivors are facing the risk of long COVID after recovery from acute COVID-19. The primary objective of this study was to systematically review the available literature and determine the pooled prevalence of, and risk factors for long COVID among the pediatric survivors. METHODS Studies that assessed the prevalence of, or risk factors associated with long COVID among pediatric COVID-19 survivors were systematically searched in PubMed, Embase, and Cochrane Library up to December 11th, 2022. Random effects model was performed to estimate the pooled prevalence of long COVID among pediatric COVID-19 patients. Subgroup analyses and meta-regression on the estimated prevalence of long COVID were performed by stratification with follow-up duration, mean age, sex ratio, percentage of multisystem inflammatory syndrome, hospitalization rate at baseline, and percentage of severe illness. RESULTS Based on 40 studies with 12,424 individuals, the pooled prevalence of any long COVID was 23.36 % ([95 % CI 15.27-32.53]). The generalized symptom (19.57 %, [95 % CI 9.85-31.52]) was reported most commonly, followed by respiratory (14.76 %, [95 % CI 7.22-24.27]), neurologic (13.51 %, [95 % CI 6.52-22.40]), and psychiatric (12.30 %, [95% CI 5.38-21.37]). Dyspnea (22.75 %, [95% CI 9.38-39.54]), fatigue (20.22 %, [95% CI 9.19-34.09]), and headache (15.88 %, [95 % CI 6.85-27.57]) were most widely reported specific symptoms. The prevalence of any symptom during 3-6, 6-12, and> 12 months were 26.41 % ([95 % CI 14.33-40.59]), 20.64 % ([95 % CI 17.06-24.46]), and 14.89 % ([95 % CI 6.09-26.51]), respectively. Individuals with aged over ten years, multisystem inflammatory syndrome, or had severe clinical symptoms exhibited higher prevalence of long COVID in multi-systems. Factors such as older age, female, poor physical or mental health, or had severe infection or more symptoms were more likely to have long COVID in pediatric survivors. CONCLUSIONS Nearly one quarter of pediatric survivors suffered multisystem long COVID, even at 1 year after infection. Ongoing monitoring, comprehensive prevention and intervention is warranted for pediatric survivors, especially for individuals with high risk factors.
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Affiliation(s)
- Yong-Bo Zheng
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China; Peking-Tsinghua Centre for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Na Zeng
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China; School of Public Health, Peking University, Beijing, China; Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Kai Yuan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Shan-Shan Tian
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Ying-Bo Yang
- The First Affiliated Hospital of Xinxiang Medical University, Henan, China
| | - Nan Gao
- The First Affiliated Hospital of Xinxiang Medical University, Henan, China
| | - Xuan Chen
- The First Affiliated Hospital of Xinxiang Medical University, Henan, China
| | - An-Yi Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Alexandra L Kondratiuk
- NIHR Health Protection Research Unit in Respiratory Infections, National Heart and Lung Institute, Imperial College, London W2 1NY, UK
| | - Pei-Pei Shi
- Department of Neurology, Taiyuan Central Hospital of Shanxi Medical University, Taiyuan, China
| | - Fang Zhang
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Beijing, China
| | - Jie Sun
- Pain Medicine Center, Peking University Third Hospital, Beijing, China
| | - Jing-Li Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Xiao Lin
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Le Shi
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Ajit Lalvani
- NIHR Health Protection Research Unit in Respiratory Infections, National Heart and Lung Institute, Imperial College, London W2 1NY, UK
| | - Jie Shi
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China
| | - Yan-Ping Bao
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China; School of Public Health, Peking University, Beijing, China.
| | - Lin Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China; Peking-Tsinghua Centre for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China; National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China.
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12
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Yang K, Zhu J, Yang L, Lin Y, Huang X, Li Y. Analysis of network public opinion on COVID-19 epidemic based on the WSR theory. Front Public Health 2023; 10:1104031. [PMID: 36711404 PMCID: PMC9880161 DOI: 10.3389/fpubh.2022.1104031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 12/20/2022] [Indexed: 01/15/2023] Open
Abstract
Objective To obtain the influencing factors of public opinion reactions and to construct a basic framework of the factors causing the occurrence of online public opinion in the epidemic area. Methods The hot news comments on microblogs during the epidemic in Shanghai were collected and analyzed with qualitative analysis, grounded theory, and the "Wuli-Shili-Renli" (WSR) methodology as an auxiliary method. Results (1) Three core categories of the Wuli system, the Shili system, and the Renli system, 15 main categories, and 86 categories that influence the development of network public opinion are obtained. (2) WSR Elements Framework Of Network Public Opinion (WSR-EFONPO) is established. (3) The WSR-EFONPO is explained. Conclusion The framework of factors for the occurrence of network public opinion is proposed, and the development process of network public opinion under COVID-19 is sorted out, which is of great theoretical value in guiding the public in the epidemic area to form reasonable behavior.
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13
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Liu YY, Yeh YC. Complementary and Alternative Medicines Used by Middle-Aged to Older Taiwanese Adults to Cope with Stress during the COVID-19 Pandemic: A Cross-Sectional Survey. Healthcare (Basel) 2022; 10:2250. [PMID: 36360594 PMCID: PMC9690493 DOI: 10.3390/healthcare10112250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 11/07/2022] [Indexed: 11/12/2022] Open
Abstract
Background: This study aimed to investigate the factors influencing the use of complementary and alternative medicines (CAMs) to manage stress during the COVID-19 pandemic in Taiwan. Methods: A cross-sectional survey was administered to community-dwelling adults between the ages of 46 and 75 years, and a total of 351 participants completed the questionnaire. Log-binominal regression analyses were fitted to explore the factors associated with the use of CAMs. Results: The mean age of the participants was 57.0 years, and 67.0% reported that they had used CAMs within the past three months. Middle-aged adults were more likely to use CAMs than late middle-aged adults and older adults (p < 0.001). Overall, the major CAMs utilized to relieve psychological stress were music therapies (37.6%), massage (31.1%), spinal manipulation (25.1%), relaxing therapies (24.2%), and reading scriptures or The Bible (23.9%). Religion and vegetarian diets were the most important factors influencing participants to use CAMs, especially music therapies, massage, and reading scriptures/The Bible. Conclusions: CAM use was very prevalent among middle-aged adults in Taiwan; in particular, music therapies were the most favored activities for reducing stress. Population-specific mental health interventions using music can be developed to improve stress management outcomes during public health emergencies.
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Affiliation(s)
- Yo-Yu Liu
- Master’s Program in Natural Healing Sciences, Department of Natural Biotechnology, Nanhua University, Chiayi 622, Taiwan
- Doctoral Program in Management Science, Department of Business Administration, Nanhua University, Chiayi 622, Taiwan
| | - Yueh-Chiao Yeh
- Master’s Program in Natural Healing Sciences, Department of Natural Biotechnology, Nanhua University, Chiayi 622, Taiwan
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14
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Long-term psychological profile of general population following COVID-19 outbreak: symptom trajectories and evolution of psychopathological network. Epidemiol Psychiatr Sci 2022; 31:e69. [PMID: 36165185 PMCID: PMC9531590 DOI: 10.1017/s2045796022000518] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
AIMS COVID-19 has long-term impacts on public mental health, while few research studies incorporate multidimensional methods to thoroughly characterise the psychological profile of general population and little detailed guidance exists for mental health management during the pandemic. This research aims to capture long-term psychological profile of general population following COVID-19 by integrating trajectory modelling approaches, latent trajectory pattern identification and network analyses. METHODS Longitudinal data were collected from a nationwide sample of 18 804 adults in 12 months after COVID-19 outbreak in China. Patient Health Questionnaire-9, Generalised Anxiety Disorder-7 and Insomnia Severity Index were used to measure depression, anxiety and insomnia, respectively. The unconditional and conditional latent growth curve models were fitted to investigate trajectories and long-term predictors for psychological symptoms. We employed latent growth mixture model to identify the major psychological symptom trajectory patterns, and ran sparse Gaussian graphical models with graphical lasso to explore the evolution of psychopathological network. RESULTS At 12 months after COVID-19 outbreak, psychological symptoms generally alleviated, and five psychological symptom trajectories with different demographics were identified: normal stable (63.4%), mild stable (15.3%), mild-increase to decrease (11.7%), mild-decrease to increase (4.0%) and moderate/severe stable (5.5%). The finding indicated that there were still about 5% individuals showing consistently severe distress and approximately 16% following fluctuating psychological trajectories, who should be continuously monitored. For individuals with persistently severe trajectories and those with fluctuating trajectories, central or bridge symptoms in the network were mainly 'motor abnormality' and 'sad mood', respectively. Compared with initial peak and late COVID-19 phase, aftermath of initial peak might be a psychologically vulnerable period with highest network connectivity. The central and bridge symptoms for aftermath of initial peak ('appetite change' and 'trouble of relaxing') were totally different from those at other pandemic phases ('sad mood'). CONCLUSIONS This research identified the overall growing trend, long-term predictors, trajectory classes and evolutionary pattern of psychopathological network of psychological symptoms in 12 months after COVID-19 outbreak. It provides a multidimensional long-term psychological profile of the general population after COVID-19 outbreak, and accentuates the essentiality of continuous psychological monitoring, as well as population- and time-specific psychological management after COVID-19. We believe our findings can offer reference for long-term psychological management after pandemics.
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15
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Li XJ, Guo TZ, Xie Y, Bao YP, Si JY, Li Z, Xiong YT, Li H, Li SX, Lu L, Wang XQ. Cross-sectional survey following a longitudinal study on mental health and insomnia of people with sporadic COVID-19. World J Psychiatry 2022; 12:1076-1087. [PMID: 36158301 PMCID: PMC9476843 DOI: 10.5498/wjp.v12.i8.1076] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 04/20/2022] [Accepted: 07/06/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND In the post-pandemic era, the emergence of sporadic cases of coronavirus disease 2019 (COVID-19) and the scale of the pandemic are unpredictable. Therefore, the impact of sporadic cases of COVID-19 and isolation measures on mental health and sleep in different groups of people need to be analyzed. AIM To clarify the severity of psychological problems and insomnia of staff and community residents around a hospital with sporadic cases of COVID-19, and their relationship with quarantine location and long-term changes. METHODS A cross-sectional survey was conducted on community residents and medical staff. Many of these medical staff had been subjected to different places of quarantine. Community residents did not experience quarantine. Hospital anxiety and depression scale (HADS), acute stress disorder scale (ASDS) and insomnia severity index (ISI) were used to evaluate anxiety and depression, acute stress disorder symptoms, and the severity of insomnia. Additionally, we conducted a 1-year follow-up study on medical staff, with related scales measurement immediately after and one year after the 2-wk quarantine period. RESULTS We included 406 medical staff and 226 community residents. The total scores of ISI and subscale in HADS of community residents were significantly higher than that of medical staff. Further analysis of medical staff who experienced quarantine showed that 134 were quarantined in hotels, 70 in hospitals and 48 at home. Among all subjects, the proportions of HADS, ASDS and ISI scores above normal cutoff value were 51.94%, 19.17% and 31.11%, respectively. Multivariable logistic regression analysis found that subjects with higher total ASDS scores had a greater risk to develop anxiety and depression. The total ISI score for medical staff in hotel quarantine was significantly higher than those in home quarantine. Total 199 doctors and nurses who completed the 1-year follow-up study. Compared with baseline, HADS and ASDS scores decreased significantly one year after the end of quarantine, while ISI scores did not change significantly. CONCLUSION Sporadic COVID-19 cases had a greater psychological impact on residents in surrounding communities, mainly manifested as insomnia and depressive symptoms. Hotel quarantine aggravated the severity of insomnia in medical staff, whose symptoms lasted ≥ 1 year.
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Affiliation(s)
- Xiao-Jun Li
- Department of Psychiatry, Peking University International Hospital, Beijing 102206, China
| | - Tian-Ze Guo
- Department of Bioengineering, University of California San Diego, San Diego, CA 92093, United States
| | - Yan Xie
- Department of Psychology, Peking University International Hospital, Beijing 102206, China
| | - Yan-Ping Bao
- Department of Epidemiology, National Institute on Drug Dependence and Beijing Key laboratory of Drug Dependence, Peking University, Beijing 100191, China
| | - Jia-Yue Si
- University of California Davis, Davis, CA 95616, United States
| | - Zhe Li
- Department of History, University College London, London WC1E 6BT, United Kingdom
| | - Yi-Ting Xiong
- Department of Psychiatry, Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China
| | - Hui Li
- Department of Psychiatry, Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China
| | - Su-Xia Li
- Department of Clinical Pharmacology, National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China
| | - Lin Lu
- Department of Psychiatry, Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China
- Peking-Tsinghua Centre for Life Sciences and Peking University-International Development Group/McGovern Institute for Brain Research, Peking University, Beijing 100091, China
| | - Xue-Qin Wang
- Department of Psychiatry, Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China
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16
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Li L, Zhang SX, Graf-Vlachy L. Predicting Managers' Mental Health Across Countries: Using Country-Level COVID-19 Statistics. Front Public Health 2022; 10:791977. [PMID: 35664112 PMCID: PMC9160832 DOI: 10.3389/fpubh.2022.791977] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Accepted: 02/03/2022] [Indexed: 11/20/2022] Open
Abstract
Background There is limited research focusing on publicly available statistics on the Coronavirus disease 2019 (COVID-19) pandemic as predictors of mental health across countries. Managers are at risk of suffering from mental disorders during the pandemic because they face particular hardship. Objective We aim to predict mental disorder (anxiety and depression) symptoms of managers across countries using country-level COVID-19 statistics. Methods A two-wave online survey of 406 managers from 26 countries was performed in May and July 2020. We used logistic panel regression models for our main analyses and performed robustness checks using ordinary least squares regressions. In the sample, 26.5% of managers reached the cut-off levels for anxiety (General Anxiety Disorder-7; GAD-7) and 43.5% did so for depression (Patient Health Questionnaire-9; PHQ-9) symptoms. Findings We found that cumulative COVID-19 statistics (e.g., cumulative cases, cumulative cases per million, cumulative deaths, and cumulative deaths per million) predicted managers' anxiety and depression symptoms positively, whereas daily COVID-19 statistics (daily new cases, smoothed daily new cases, daily new deaths, smoothed daily new deaths, daily new cases per million, and smoothed daily new cases per million) predicted anxiety and depression symptoms negatively. In addition, the reproduction rate was a positive predictor, while stringency of governmental lockdown measures was a negative predictor. Individually, we found that the cumulative count of deaths is the most suitable single predictor of both anxiety and depression symptoms. Conclusions Cumulative COVID-19 statistics predicted managers' anxiety and depression symptoms positively, while non-cumulative daily COVID-19 statistics predicted anxiety and depression symptoms negatively. Cumulative count of deaths is the most suitable single predictor of both anxiety and depression symptoms. Reproduction rate was a positive predictor, while stringency of governmental lockdown measures was a negative predictor.
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Affiliation(s)
- Lun Li
- School of Economics and Management, Tsinghua University, Beijing, China
| | - Stephen X. Zhang
- Adelaide Business School, University of Adelaide, Adelaide, SA, Australia
| | - Lorenz Graf-Vlachy
- TU Dortmund University, Dortmund, Germany
- ESCP Business School, Paris, France
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17
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Zhu XM, Yan W, Sun J, Liu L, Zhao YM, Zheng YB, Que JY, Sun SW, Gong YM, Zeng N, Yuan K, Shi L, Sun YK, Guo SH, Lu Y, Ran MS, Wong SYS, Shi J, Jiang ZD, Bao YP, Lu L. Patterns and influencing factors of COVID-19 vaccination willingness among college students in China. Vaccine 2022; 40:3046-3054. [PMID: 35450782 PMCID: PMC8995203 DOI: 10.1016/j.vaccine.2022.04.013] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2021] [Revised: 03/09/2022] [Accepted: 04/04/2022] [Indexed: 12/28/2022]
Abstract
Background Vaccination is an important preventive measure against the coronavirus disease 19 (COVID-19) pandemic. We aimed to examine the willingness to vaccination and influencing factors among college students in China. Methods From March 18 to April 26, 2021, we conducted a cross-sectional online survey among college students from 30 universities in Wuhan, Hubei Province, China. The survey was composed of the sociodemographic information, psychological status, experience during pandemic, the willingness of vaccination and related information. Students’ attitudes towards vaccination were classified as ‘vaccine acceptance’, ‘vaccine hesitancy’, and ‘vaccine resistance’. Multinomial logistic regression analyses were performed to identify the influencing factors associated with vaccine hesitancy and resistance. Results Among 23,143 students who completed the survey, a total of 22,660 participants were included in the final analysis with an effective rate of 97.9% after excluding invalid questionnaires. A total of 60.6% of participants would be willing to receive COVID-19 vaccine, 33.4% were hesitant to vaccination, and 6.0% were resistant to vaccination. Social media platforms and government agencies were the main sources of information vaccination. Worry about the efficacy and adverse effects of vaccine were the top two common reason of vaccine hesitancy and resistance. Multiple multinomial logistic regression analysis identified that participants who worried about the adverse effects of vaccination were more likely to be vaccine hesitancy (aOR = 2.44, 95% CI = 2.30, 2.58) and resistance (aOR = 2.71, 95% CI = 2.40, 3.05). Conclusion More than half of college students are willing to receive the COVID-19 vaccine, whereas nearly one-third college students are still hesitant or resistant. It is crucial to provide sufficient and scientific information on the efficacy and safety of vaccine through social media and government agencies platforms to promote vaccine progress against COVID-19 and control the pandemic in China.
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Affiliation(s)
- Xi-Mei Zhu
- Institute of Mental Health, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health and Peking University Sixth Hospital, Peking University, Beijing 100191, China
| | - Wei Yan
- Institute of Mental Health, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health and Peking University Sixth Hospital, Peking University, Beijing 100191, China
| | - Jie Sun
- Center for Pain Medicine, Peking University Third Hospital, Beijing 100191, China
| | - Lin Liu
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China; School of Public Health, Peking University, Beijing 100191, China
| | - Yi-Miao Zhao
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China; School of Public Health, Peking University, Beijing 100191, China
| | - Yong-Bo Zheng
- Institute of Mental Health, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health and Peking University Sixth Hospital, Peking University, Beijing 100191, China; Peking-Tsinghua Center for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100191, China
| | - Jian-Yu Que
- Institute of Mental Health, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health and Peking University Sixth Hospital, Peking University, Beijing 100191, China
| | - Si-Wei Sun
- Institute of Mental Health, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health and Peking University Sixth Hospital, Peking University, Beijing 100191, China
| | - Yi-Miao Gong
- Institute of Mental Health, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health and Peking University Sixth Hospital, Peking University, Beijing 100191, China; Peking-Tsinghua Center for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100191, China
| | - Na Zeng
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China; School of Public Health, Peking University, Beijing 100191, China
| | - Kai Yuan
- Institute of Mental Health, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health and Peking University Sixth Hospital, Peking University, Beijing 100191, China
| | - Le Shi
- Institute of Mental Health, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health and Peking University Sixth Hospital, Peking University, Beijing 100191, China
| | - Yan-Kun Sun
- Institute of Mental Health, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health and Peking University Sixth Hospital, Peking University, Beijing 100191, China
| | - Sui-Huai Guo
- Wuhan Wuchang Hospital, Wuhan University of Science and Technology, Wuhan, China
| | - Yu Lu
- Wuhan Wuchang Hospital, Wuhan University of Science and Technology, Wuhan, China
| | - Mao-Sheng Ran
- Department of Social Work and Social Administration, University of Hong Kong, Hong Kong, China
| | - Samuel Yeung Shan Wong
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Jie Shi
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China
| | - Zheng-Dong Jiang
- Wuhan Wuchang Hospital, Wuhan University of Science and Technology, Wuhan, China
| | - Yan-Ping Bao
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China; School of Public Health, Peking University, Beijing 100191, China
| | - Lin Lu
- Institute of Mental Health, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health and Peking University Sixth Hospital, Peking University, Beijing 100191, China; National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China; Peking-Tsinghua Center for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100191, China.
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18
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Gong Y, Liu X, Zheng Y, Mei H, Que J, Yuan K, Yan W, Shi L, Meng S, Bao Y, Lu L. COVID-19 Induced Economic Slowdown and Mental Health Issues. Front Psychol 2022; 13:777350. [PMID: 35310204 PMCID: PMC8931846 DOI: 10.3389/fpsyg.2022.777350] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 02/09/2022] [Indexed: 11/21/2022] Open
Abstract
The COVID-19 pandemic has pressed a pause button on global economic development, and induced significant mental health problems. In order to demonstrate the progressed relationship between the pandemic, economic slowdown, and mental health burden, we overviewed the global-level gross domestic product changes and mental problems variation since the outbreak of COVID-19, and reviewed comprehensively the specific sectors influenced by the pandemic, including international trade, worldwide travel, education system, healthcare system, and individual employment. We hope to provide timely evidence to help with the promotion of policymakers’ effective strategies in mitigating economic losses induced by the pandemic; we suggest different governments or policy makers in different countries to share information and experience in dealing with COVID-19-induced economic slowdown and promote COVID-19 vaccine popularization plan to protect every individual worldwide against the coronavirus essentially; and we appeal international information share and collaboration to minimize stigmatization related to adverse mental consequences of COVID-19 and to increase mental health wellbeings of people all over the world.
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Affiliation(s)
- Yimiao Gong
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
- Peking-Tsinghua Centre for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Xiaoxing Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yongbo Zheng
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
- Peking-Tsinghua Centre for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Huan Mei
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China
- School of Public Health, Peking University, Beijing, China
| | - Jianyu Que
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Kai Yuan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Wei Yan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Le Shi
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Shiqiu Meng
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China
- *Correspondence: Shiqiu Meng,
| | - Yanping Bao
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China
- School of Public Health, Peking University, Beijing, China
- Yanping Bao,
| | - Lin Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
- Peking-Tsinghua Centre for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Lin Lu,
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19
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Sun J, Zheng YB, Liu L, Li SQ, Zhao YM, Zhu XM, Que JY, Li MZ, Liu WJ, Yuan K, Yan W, Liu XG, Chang SH, Chen X, Gao N, Shi J, Bao YP, Lu L. The Impact of Quarantine on Pain Sensation among the General Population in China during the COVID-19 Pandemic. Brain Sci 2022; 12:brainsci12010079. [PMID: 35053822 PMCID: PMC8773642 DOI: 10.3390/brainsci12010079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 12/29/2021] [Accepted: 12/31/2021] [Indexed: 02/04/2023] Open
Abstract
During the pandemic era, quarantines might potentially have negative effects and disproportionately exacerbate health condition problems. We conducted this cross-sectional, national study to ascertain the prevalence of constant pain symptoms and how quarantines impacted the pain symptoms and identify the factors associated with constant pain to further guide reducing the prevalence of chronic pain for vulnerable people under the pandemic. The sociodemographic data, quarantine conditions, mental health situations and pain symptoms of the general population were collected. After adjusting for potential confounders, long-term quarantine (≥15 days) exposures were associated with an increased risk of constant pain complaints compared to those not under a quarantine (Odds Ratio (OR): 1.26; 95% Confidence Interval (CI): 1.03, 1.54; p = 0.026). Risk factors including unemployment (OR: 1.55), chronic disease history (OR: 2.38) and infection with COVID-19 (OR: 2.15), and any of mental health symptoms including depression, anxiety, insomnia and PTSD (OR: 5.44) were identified by a multivariable logistic regression. Additionally, mediation analysis revealed that the effects of the quarantine duration on pain symptoms were mediated by mental health symptoms (indirect effects: 0.075, p < 0.001). These results advocated that long-term quarantine measures were associated with an increased risk of experiencing pain, especially for vulnerable groups with COVID-19 infection and with mental health symptoms. The findings also suggest that reducing mental distress during the pandemic might contribute to reducing the burden of pain symptoms and prioritizing interventions for those experiencing a long-term quarantine.
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Affiliation(s)
- Jie Sun
- Pain Medicine Center, Peking University Third Hospital, Beijing 100191, China; (J.S.); (S.-Q.L.); (X.-G.L.)
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit (No. 2018RU006), Peking University, Beijing 100191, China; (Y.-B.Z.); (L.L.); (X.-M.Z.); (J.-Y.Q.); (M.-Z.L.); (W.-J.L.); (K.Y.); (W.Y.); (S.-H.C.); (X.C.); (N.G.)
| | - Yong-Bo Zheng
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit (No. 2018RU006), Peking University, Beijing 100191, China; (Y.-B.Z.); (L.L.); (X.-M.Z.); (J.-Y.Q.); (M.-Z.L.); (W.-J.L.); (K.Y.); (W.Y.); (S.-H.C.); (X.C.); (N.G.)
- Peking-Tsinghua Center for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Beijing 100191, China
| | - Lin Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit (No. 2018RU006), Peking University, Beijing 100191, China; (Y.-B.Z.); (L.L.); (X.-M.Z.); (J.-Y.Q.); (M.-Z.L.); (W.-J.L.); (K.Y.); (W.Y.); (S.-H.C.); (X.C.); (N.G.)
| | - Shui-Qing Li
- Pain Medicine Center, Peking University Third Hospital, Beijing 100191, China; (J.S.); (S.-Q.L.); (X.-G.L.)
| | - Yi-Miao Zhao
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China; (Y.-M.Z.); (J.S.)
- School of Public Health, Peking University, Beijing 100191, China
| | - Xi-Mei Zhu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit (No. 2018RU006), Peking University, Beijing 100191, China; (Y.-B.Z.); (L.L.); (X.-M.Z.); (J.-Y.Q.); (M.-Z.L.); (W.-J.L.); (K.Y.); (W.Y.); (S.-H.C.); (X.C.); (N.G.)
| | - Jian-Yu Que
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit (No. 2018RU006), Peking University, Beijing 100191, China; (Y.-B.Z.); (L.L.); (X.-M.Z.); (J.-Y.Q.); (M.-Z.L.); (W.-J.L.); (K.Y.); (W.Y.); (S.-H.C.); (X.C.); (N.G.)
| | - Ming-Zhe Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit (No. 2018RU006), Peking University, Beijing 100191, China; (Y.-B.Z.); (L.L.); (X.-M.Z.); (J.-Y.Q.); (M.-Z.L.); (W.-J.L.); (K.Y.); (W.Y.); (S.-H.C.); (X.C.); (N.G.)
- Peking-Tsinghua Center for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Beijing 100191, China
| | - Wei-Jian Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit (No. 2018RU006), Peking University, Beijing 100191, China; (Y.-B.Z.); (L.L.); (X.-M.Z.); (J.-Y.Q.); (M.-Z.L.); (W.-J.L.); (K.Y.); (W.Y.); (S.-H.C.); (X.C.); (N.G.)
| | - Kai Yuan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit (No. 2018RU006), Peking University, Beijing 100191, China; (Y.-B.Z.); (L.L.); (X.-M.Z.); (J.-Y.Q.); (M.-Z.L.); (W.-J.L.); (K.Y.); (W.Y.); (S.-H.C.); (X.C.); (N.G.)
| | - Wei Yan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit (No. 2018RU006), Peking University, Beijing 100191, China; (Y.-B.Z.); (L.L.); (X.-M.Z.); (J.-Y.Q.); (M.-Z.L.); (W.-J.L.); (K.Y.); (W.Y.); (S.-H.C.); (X.C.); (N.G.)
| | - Xiao-Guang Liu
- Pain Medicine Center, Peking University Third Hospital, Beijing 100191, China; (J.S.); (S.-Q.L.); (X.-G.L.)
| | - Su-Hua Chang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit (No. 2018RU006), Peking University, Beijing 100191, China; (Y.-B.Z.); (L.L.); (X.-M.Z.); (J.-Y.Q.); (M.-Z.L.); (W.-J.L.); (K.Y.); (W.Y.); (S.-H.C.); (X.C.); (N.G.)
| | - Xuan Chen
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit (No. 2018RU006), Peking University, Beijing 100191, China; (Y.-B.Z.); (L.L.); (X.-M.Z.); (J.-Y.Q.); (M.-Z.L.); (W.-J.L.); (K.Y.); (W.Y.); (S.-H.C.); (X.C.); (N.G.)
| | - Nan Gao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit (No. 2018RU006), Peking University, Beijing 100191, China; (Y.-B.Z.); (L.L.); (X.-M.Z.); (J.-Y.Q.); (M.-Z.L.); (W.-J.L.); (K.Y.); (W.Y.); (S.-H.C.); (X.C.); (N.G.)
| | - Jie Shi
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China; (Y.-M.Z.); (J.S.)
| | - Yan-Ping Bao
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China; (Y.-M.Z.); (J.S.)
- School of Public Health, Peking University, Beijing 100191, China
- Correspondence: (Y.-P.B.); (L.L.)
| | - Lin Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit (No. 2018RU006), Peking University, Beijing 100191, China; (Y.-B.Z.); (L.L.); (X.-M.Z.); (J.-Y.Q.); (M.-Z.L.); (W.-J.L.); (K.Y.); (W.Y.); (S.-H.C.); (X.C.); (N.G.)
- Peking-Tsinghua Center for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Beijing 100191, China
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China; (Y.-M.Z.); (J.S.)
- Correspondence: (Y.-P.B.); (L.L.)
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20
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A systematic review and meta-analysis on prevalence of and risk factors associated with depression, anxiety and insomnia in infectious diseases, including COVID-19: a call to action. Mol Psychiatry 2022; 27:3214-3222. [PMID: 35668158 PMCID: PMC9168354 DOI: 10.1038/s41380-022-01638-z] [Citation(s) in RCA: 106] [Impact Index Per Article: 35.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 05/11/2022] [Accepted: 05/18/2022] [Indexed: 11/08/2022]
Abstract
Infectious disease epidemics have become more frequent and more complex during the 21st century, posing a health threat to the general public and leading to psychological symptoms. The current study was designed to investigate the prevalence of and risk factors associated with depression, anxiety and insomnia symptoms during epidemic outbreaks, including COVID-19. We systematically searched the PubMed, Embase, Web of Science, OVID, Medline, Cochrane databases, bioRxiv and medRxiv to identify studies that reported the prevalence of depression, anxiety or insomnia during infectious disease epidemics, up to August 14th, 2020. Prevalence of mental symptoms among different populations including the general public, health workers, university students, older adults, infected patients, survivors of infection, and pregnant women across all types of epidemics was pooled. In addition, prevalence of mental symptoms during COVID-19 was estimated by time using meta-regression analysis. A total of 17,506 papers were initially retrieved, and a final of 283 studies met the inclusion criteria, representing a total of 948,882 individuals. The pooled prevalence of depression ranged from 23.1%, 95% confidential intervals (95% CI: [13.9-32.2]) in survivors to 43.3% (95% CI: [27.1-59.6]) in university students, the pooled prevalence of anxiety ranged from 25.0% (95% CI: [12.0-38.0]) in older adults to 43.3% (95% CI: [23.3-63.3]) in pregnant women, and insomnia symptoms ranged from 29.7% (95% CI: [24.4-34.9]) in the general public to 58.4% (95% CI: [28.1-88.6]) in university students. Prevalence of moderate-to-severe mental symptoms was lower but had substantial variation across different populations. The prevalence of mental problems increased over time during the COVID-19 pandemic among the general public, health workers and university students, and decreased among infected patients. Factors associated with increased prevalence for all three mental health symptoms included female sex, and having physical disorders, psychiatric disorders, COVID infection, colleagues or family members infected, experience of frontline work, close contact with infected patients, high exposure risk, quarantine experience and high concern about epidemics. Frequent exercise and good social support were associated with lower risk for these three mental symptoms. In conclusion, mental symptoms are common during epidemics with substantial variation across populations. The population-specific psychological crisis management are needed to decrease the burden of psychological problem and improve the mental wellbeing during epidemic.
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21
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Chu M, Li H, Lin S, Cai X, Li X, Chen SH, Zhang X, Man Q, Lee CY, Chiang YC. Appropriate Strategies for Reducing the Negative Impact of Online Reports of Suicide and Public Opinion From Social Media in China. Front Public Health 2021; 9:756360. [PMID: 34926380 PMCID: PMC8678273 DOI: 10.3389/fpubh.2021.756360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 11/02/2021] [Indexed: 11/13/2022] Open
Abstract
Suicide events may have a negative impact on all of society. The media plays a significant role in suicide prevention. Therefore, the aims of this study are (a) to understand the association between characteristics of suicide events and characteristics of who committed suicide, and event impact indexes (EIIs) of suicide reported on the internet; (b) to analyze violation of recommendations for reporting suicide by Weibo, and (c) to investigate the effect of online reports of suicide on public opinion. We carried out a content analysis of online reports of suicide. This study analyzed 113 suicide events, 300 news reports of suicide, and 2,654 Weibo comments about suicide collected from the WeiboReach between 2015 and 2020. We used a t-test and analysis of variance (ANOVA) to explore the potential factors associated with the EIIs of suicide events. The results found that (a) The suicide events reported on the internet during COVID-19 and those related to celebrities and students tend to have higher EIIs; (b) suicide reports on Weibo frequently violated WHO recommendations for suicide reporting in the media; and (c) public opinion of suicide reporting in the online media was mostly emotional and irrational, which is not beneficial for public mental health and suicide prevention. In conclusion, first, the situation of many people working from home or studying from home and spreading more time online during COVID-19 may lead to suicide events obtain more public attention. Online media could further improve public responsible reporting and daily media-content surveillance, especially taking particular care in those suicide events during COVID-19, and related to celebrities and students, which may have a higher event impact on the internet. Second, health managers should regular assessment of observance of the WHO recommendations for suicide reporting by online social media to prevent suicide. Third, health communication managers should use big data to identify, assess, and manage harmful information about suicide; and track anyone affected by suicide-related reports on social media to reduce the negative impact of public opinion to intervene suicide in the early stage of suicide.
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Affiliation(s)
- Meijie Chu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Hongye Li
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Shengnan Lin
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Xinlan Cai
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Xian Li
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Shih-Han Chen
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Xiaoke Zhang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Qingli Man
- Department of Technical Cooperation, Zhiwei Research Institute, Beijing, China
| | - Chun-Yang Lee
- School of International Business, Xiamen University Tan Kah Kee College, Zhangzhou, China
| | - Yi-Chen Chiang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
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22
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Jia P, Zhuang J, Vaca Lucero AM, Osei CD, Li J. Does Participation in Local Non-agricultural Employment Improve the Mental Health of Elderly Adults in Rural Areas? Evidence From China. Front Public Health 2021; 9:746580. [PMID: 34778181 PMCID: PMC8578795 DOI: 10.3389/fpubh.2021.746580] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Accepted: 10/04/2021] [Indexed: 12/05/2022] Open
Abstract
A rising rate of suicide among the elderly in rural China has been recognized to be triggered by mental health-associated factors. This study uses 3,397 sampled rural elderly adults from China Labor-force Dynamic Survey in 2016 to explore the response mechanism through which non-agricultural employment participation by the elderly adults in rural China can influence their mental health. Utilizing the Multivariate Regression, Instrumental Variable and Propensity Score Matching methods, we find that, the rural elderly adults who participate in local non-agricultural employment significantly improve their mental health. Self-employment tends to have a greater positive contribution to the mental health of the elderly population than waged employment. Further, work income, need for belongingness and respect, and human capital development significantly mediates the influence of participation in local non-agricultural employment on the mental health of the elderly adults. Finally, we put forward relevant policy suggestions to improving the mental health of the elderly in the countryside.
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Affiliation(s)
- Peng Jia
- School of Management, Jiangsu University, Zhenjiang, China
| | - Jincai Zhuang
- School of Management, Jiangsu University, Zhenjiang, China
| | | | | | - Juan Li
- School of Business, Guilin University of Electronic Technology, Guilin, China
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23
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Zhang QQ, Li L, Zhong BL. Prevalence of Insomnia Symptoms in Older Chinese Adults During the COVID-19 Pandemic: A Meta-Analysis. Front Med (Lausanne) 2021; 8:779914. [PMID: 34869501 PMCID: PMC8634335 DOI: 10.3389/fmed.2021.779914] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 10/12/2021] [Indexed: 11/29/2022] Open
Abstract
Background: The ongoing COVID-19 pandemic has disproportionately affected the sleep health of older adults, but the limited number of studies on insomnia symptoms of older Chinese adults differed in terms of screener of insomnia, sample size, and prevalence, making mental health planning for this population difficult. This meta-analysis estimated the prevalence of insomnia symptoms in older Chinese adults during the COVID-19 pandemic. Methods: Both Chinese (CNKI, Wanfang, VIP) and English (PubMed, EmBase, PsycInfo) databases were systematically searched to identify cross-sectional studies containing data on the prevalence of insomnia symptoms in older Chinese adults during the pandemic. Risk of bias (RoB) of included studies was assessed with the Joanna Briggs Institute Critical Appraisal Checklist for Studies Reporting Prevalence Data. Results: Nine studies with a total of 27,207 older Chinese adults were included. RoB scores of these studies ranged between zero and six. The pooled prevalence rates of insomnia symptoms and moderate and severe insomnia symptoms were 24.6% [95% confidence interval (CI): 19.5-30.5%] and 11.1% (95% CI: 7.2-16.9%), respectively. In subgroup analysis, significantly higher prevalence rates were observed in studies defining insomnia symptoms as "Insomnia Severity Index (ISI) ≥ 8" than in those defining them as "ISI ≥ 15" (32.6 vs. 15.6%, P < 0.001) and in older adults living in the COVID-19 epicenter than in those living in other places (35.2 vs. 23.3%, P = 0.006). Conclusion: Nearly one out of every four older Chinese adults suffered from insomnia symptoms during the pandemic. Mental health services for this population during the pandemic should include supportive activities aimed at improving mental well-being, periodic assessment of insomnia symptoms, and psychiatric assessment and treatment when necessary.
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Affiliation(s)
| | | | - Bao-Liang Zhong
- Affiliated Wuhan Mental Health Center, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China
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24
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Chiang YC, Chu M, Lin S, Cai X, Chen Q, Wang H, Li A, Rui J, Zhang X, Xie F, Lee CY, Chen T. Capturing the Trajectory of Psychological Status and Analyzing Online Public Reactions During the Coronavirus Disease 2019 Pandemic Through Weibo Posts in China. Front Psychol 2021; 12:744691. [PMID: 34659064 PMCID: PMC8511417 DOI: 10.3389/fpsyg.2021.744691] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 08/25/2021] [Indexed: 12/23/2022] Open
Abstract
When a major, sudden infectious disease occurs, people tend to react emotionally and display reactions such as tension, anxiety, fear, depression, and somatization symptoms. Social media played a substantial awareness role in developing countries during the outbreak of coronavirus disease 2019 (COVID-19). This study aimed to analyze public opinion regarding COVID-19 and to explore the trajectory of psychological status and online public reactions to the COVID-19 pandemic by examining online content from Weibo in China. This study consisted of three steps: first, Weibo posts created during the pandemic were collected and preprocessed on a large scale; second, public sentiment orientation was classified as "optimistic/pessimistic/neutral" orientation via natural language processing and manual determination procedures; and third, qualitative and quantitative analyses were conducted to reveal the trajectory of public psychological status and online public reactions during the COVID-19 pandemic. Public psychological status differed in different periods of the pandemic (from December 2019 to May 2020). The newly confirmed cases had an almost 1-month lagged effect on public psychological status. Among the 15 events with high impact indexes or related to government decisions, there were 10 optimism orientation > pessimism orientation (OP) events (2/3) and 5 pessimism orientation > optimism orientation (PO) events (1/3). Among the top two OP events, the high-frequency words were "race against time" and "support," while in the top two PO events, the high-frequency words were "irrationally purchase" and "pass away." We proposed a hypothesis that people developed negative self-perception when they received PO events, but their cognition was developed by how these external stimuli were processed and evaluated. These results offer implications for public health policymakers on understanding public psychological status from social media. This study demonstrates the benefits of promoting psychological healthcare and hygiene activity in the early period and improving risk perception for the public based on public opinion and the coping abilities of people. Health managers should focus on disseminating socially oriented strategies to improve the policy literacy of Internet users, thereby facilitating the disease prevention work for the COVID-19 pandemic and other major public events.
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Affiliation(s)
- Yi-Chen Chiang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Meijie Chu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Shengnan Lin
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Xinlan Cai
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Qing Chen
- Nanjing Terlton Information Technology Co. Ltd., Nanjing, China
| | - Hongshuai Wang
- Beijing Hongbo Zhiwei Technology Co. Ltd., Beijing, China
| | - An Li
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Jia Rui
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Xiaoke Zhang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Fang Xie
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Chun-Yang Lee
- School of International Business, Xiamen University Tan Kah Kee College, Zhangzhou, China
| | - Tianmu Chen
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
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25
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Zheng YB, Sun J, Liu L, Zhao YM, Yan W, Yuan K, Su SZ, Lu ZA, Huang YT, Liu L, Zeng N, Zhu XM, Gong YM, Lin X, Meng SQ, Wong SYS, Ran MS, Shi J, Shi L, Kosten T, Bao YP, Lu L. COVID-19 Vaccine-Related Psychological Stress Among General Public in China. Front Psychiatry 2021; 12:774504. [PMID: 34950070 PMCID: PMC8689133 DOI: 10.3389/fpsyt.2021.774504] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Accepted: 11/12/2021] [Indexed: 11/13/2022] Open
Abstract
Background: The COVID-19 pandemic is our generation's greatest global challenge to our public health system. Vaccines are considered one of the most effective tools available for preventing COVID-19 infection and its complications and sequelae. Understanding and addressing the psychological stress related to COVID-19 vaccination may promote acceptance of these vaccines. Methods: We conducted an online survey from January 29 to April 26, 2021 to explore stress levels related to COVID-19 vaccination among the general public in China. Participants were asked to evaluate their psychological stress of considering whether or not to get vaccinated at the beginning period of the COVID-19 mass vaccination, after getting access to the information about the vaccine, as well as after getting vaccinated, using visual analog stress scale. Multiple linear regression analysis was performed to explore factors potentially associated with COVID-19-related psychological stress levels before and after getting vaccinated. Results: A total of 34,041 participants were included in the final analysis. The mean stress score concerning COVID-19 vaccination was 3.90 ± 2.60 among all participants, and significantly decreased over time. In addition, the vaccine-related stress level significantly decreased after accessing information about the COVID-19 vaccine (N = 29,396), as well as after getting vaccinated (N = 5,103). Multivariable regression analysis showed higher stress levels related to COVID-19 vaccination in participants who were younger, having lower education level, having history of chronic diseases, mistrusting vaccine's efficacy, experience of vaccine allergy events, being affected by the COVID-19 epidemic, and having mental illness symptoms. Moreover, mistrust in vaccine efficacy and experience of vaccine allergy events had a long-term impact on psychological stress levels about COVID-19 vaccination even after getting vaccinated. Conclusions: The current findings profiled the COVID-19 vaccine-related psychological stress among the general public in China. Population-specific management and interventions targeting the stress related to COVID-19 vaccination are needed to help governments and policy makers promote individual's willingness to get vaccinations for public well-being during the COVID-19 pandemic.
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Affiliation(s)
- Yong-Bo Zheng
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China.,Peking-Tsinghua Centre for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Jie Sun
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China.,Pain Medicine Center, Peking University Third Hospital, Beijing, China
| | - Lin Liu
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
| | - Yi-Miao Zhao
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China.,School of Public Health, Peking University, Beijing, China
| | - Wei Yan
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
| | - Kai Yuan
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
| | - Si-Zhen Su
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
| | - Zheng-An Lu
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
| | - Yue-Tong Huang
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
| | - Lin Liu
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China.,School of Public Health, Peking University, Beijing, China
| | - Na Zeng
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China.,School of Public Health, Peking University, Beijing, China.,Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Xi-Mei Zhu
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
| | - Yi-Miao Gong
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
| | - Xiao Lin
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
| | - Shi-Qiu Meng
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China
| | - Samuel Yeung Shan Wong
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Mao-Sheng Ran
- Department of Social Work and Social Administration, University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Jie Shi
- Pain Medicine Center, Peking University Third Hospital, Beijing, China
| | - Le Shi
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
| | - Thomas Kosten
- Department of Psychiatry, Baylor College of Medicine, Houston, TX, United States.,Department of Pharmacology, Baylor College of Medicine, Houston, TX, United States.,Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States.,Department of Immunology, Baylor College of Medicine, Houston, TX, United States
| | - Yan-Ping Bao
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China.,School of Public Health, Peking University, Beijing, China
| | - Lin Lu
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China.,Peking-Tsinghua Centre for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China.,National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China
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