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Lu C, Zhang Z, Li D, Huang C, Liu C, Peng J, Xue Y, Zhang J, Xu J. The mediating effect of lifestyle behaviors on the relationship between self-perceived work stress and suboptimal health status: a cross-sectional study involving Chinese urban workers. Public Health 2024; 236:396-403. [PMID: 39303628 DOI: 10.1016/j.puhe.2024.07.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 07/17/2024] [Accepted: 07/23/2024] [Indexed: 09/22/2024]
Abstract
STUDY DESIGN Cross-sectional study. OBJECTIVES Suboptimal health status (SHS) is a third state between health and disease. Long-term being SHS will be detrimental to one's ability development. Previous studies have demonstrated the associations of lifestyle behaviors or work stress with SHS, but few studies have comprehensively analyzed the underlying factors and mechanisms between the three. This study aimed to investigate whether lifestyle behaviors mediated the relationship between self-perceived work stress and SHS. METHODS A total of 4238 urban workers, who participated in a cross-sectional survey conducted from December 2018 to October 2019, were included. A general linear model was used to explore the associations between lifestyle behaviors and self-perceived work stress with SHS after adjusting for demographic variables. Structural equation modeling was performed to examine the mediation by lifestyle behaviors. RESULTS The mean transformed scores of physical, mental, and social SHS were 70.98, 67.17, and 61.72, respectively. Unhealthy lifestyle behaviors and high self-perceived work stress positively affected SHS (P < 0.001). Self-perceived work stress imposed negative effects on physical SHS (β = -0.228, P < 0.001), mental SHS (β = -0.237, P < 0.001), and social SHS (β = -0.092, P < 0.001). The indirect effects of self-perceived work stress on physical SHS (β = -0.139, 95% CI: -0.178 to -0.106), mental SHS (β = -0.106, 95% CI: -0.134 to -0.082), and social SHS (β = -0.121, 95% CI: -0.154 to -0.092) were statistically significant. CONCLUSIONS Lifestyle behaviors and self-perceived work stress were significantly associated with SHS among Chinese urban workers. The mediating effects of unhealthy lifestyle behaviors were found in the relationship between high self-perceived work stress and SHS. Future longitudinal research may verify these associations and elucidate the underlying mechanisms.
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Affiliation(s)
- C Lu
- School of Health Management, Southern Medical University, Guangzhou, Guangdong Province, China; Department of Operation Management, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Z Zhang
- School of Health Management, Southern Medical University, Guangzhou, Guangdong Province, China; Department of Operation Management, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, China
| | - D Li
- School of Health Management, Southern Medical University, Guangzhou, Guangdong Province, China; Department of Operation Management, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, China
| | - C Huang
- School of Public Health, Southern Medical University, Guangzhou, Guangdong Province, China
| | - C Liu
- School of Health Management, Southern Medical University, Guangzhou, Guangdong Province, China; Department of Operation Management, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, China
| | - J Peng
- School of Health Management, Southern Medical University, Guangzhou, Guangdong Province, China; Department of Operation Management, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Y Xue
- Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Guangzhou, Guangdong Province, China
| | - J Zhang
- Institute of Scientific Research, Southern Medical University, Guangzhou, Guangdong Province, China
| | - J Xu
- Department of Operation Management, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, China.
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Wang X, Wu Y, Chen Y, Gao Q, Liu W, Xu J, Zang S. Network analysis for inter-relationships of the suboptimal health status with depression and anxiety during the COVID-19 pandemic: A perspective of predictive, preventive, and personalized health. J Affect Disord 2024; 356:155-161. [PMID: 38604454 DOI: 10.1016/j.jad.2024.04.032] [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: 11/28/2023] [Revised: 03/27/2024] [Accepted: 04/08/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND The Coronavirus Disease-2019 (COVID-19) pandemic has had a profound impact on suboptimal health status, depression, and anxiety, necessitating a comprehensive understanding of their inter-relationships at the national level. This study aims to investigate the inter-relationships among suboptimal health status, depression, and anxiety using a network analysis approach. METHODS We conducted a national survey between June 20 and August 31, 2022. Three network models were constructed and analyzed to independently examine the inter-relationships among suboptimal health status, depression, and anxiety. RESULTS A total of 26,152 participants were included in this study. The study network analysis indicated that item 9 (i.e., Slow response) exhibited the highest node strength within the suboptimal health status questionnaire-short form (SHSQ-SF) network, followed by item 5 (i.e., Breathlessness at rest). Additionally, positive correlations were observed between depression and anxiety severity and most of the SHSO-SF items. CONCLUSIONS This study provided valuable insights into inter-relationships between suboptimal health status, depression, and anxiety, informing the development of comprehensive intervention strategies for the general population. These findings have important implications for promoting the well-being and mental health of individuals during and beyond the COVID-19 pandemic.
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Affiliation(s)
- Xue Wang
- Department of Community Nursing, School of Nursing, China Medical University, Shenyang, China
| | - Yibo Wu
- School of Public Health, Peking University, Beijing, China
| | - Yu Chen
- School of Nursing, Southern Medical University, Guangzhou, China
| | - Qian Gao
- Department of Environmental Health, School of Public Health, China Medical University, Shenyang, China
| | - Wenting Liu
- School of Nursing, Southern Medical University, Guangzhou, China
| | - Jiayi Xu
- Department of Community Nursing, School of Nursing, China Medical University, Shenyang, China
| | - Shuang Zang
- Department of Community Nursing, School of Nursing, China Medical University, Shenyang, China.
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Liu Y, Ge P, Zhang X, Wu Y, Sun Z, Bai Q, Jing S, Zuo H, Wang P, Cong J, Li X, Liu K, Wu Y, Wei B. Intrarelationships between suboptimal health status and anxiety symptoms: A network analysis. J Affect Disord 2024; 354:679-687. [PMID: 38527530 DOI: 10.1016/j.jad.2024.03.104] [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: 01/02/2024] [Revised: 03/20/2024] [Accepted: 03/22/2024] [Indexed: 03/27/2024]
Abstract
BACKGROUND Suboptimal health status is a global public health concern of worldwide academic interest, which is an intermediate health status between health and illness. The purpose of the survey is to investigate the relationship between anxiety statuses and suboptimal health status and to identify the central symptoms and bridge symptoms. METHODS This study recruited 26,010 participants aged <60 from a cross-sectional study in China in 2022. General Anxiety Disorder-7 (GAD-7) and suboptimal health status short form (SHSQ-9) were used to quantify the levels of anxiety and suboptimal health symptoms, respectively. The network analysis method by the R program was used to judge the central and bridge symptoms. The Network Comparison Test (NCT) was used to investigate the network differences by gender, place of residence, and age in the population. RESULTS In this survey, the prevalence of anxiety symptoms, SHS, and comorbidities was 50.7 %, 54.8 %, and 38.5 %, respectively. "Decreased responsiveness", "Shortness of breath", "Uncontrollable worry" were the nodes with the highest expected influence. "Irritable", "Exhausted" were the two symptom nodes with the highest expected bridge influence in the network. There were significant differences in network structure among different subgroup networks. LIMITATIONS Unable to study the causal relationship and dynamic changes among variables. Anxiety and sub-health were self-rated and may be limited by memory bias. CONCLUSIONS Interventions targeting central symptoms and bridge nodes may be expected to improve suboptimal health status and anxiety in Chinese residents. Researchers can build symptom networks for different populations to capture symptom relationships.
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Affiliation(s)
- Yangyu Liu
- Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao 266112, China; Qingdao Academy of Chinese Medical Sciences, Shandong University of Traditional Chinese Medicine, Qingdao 266112, China; Qingdao Key Laboratory of Artificial Intelligence Technology in Traditional Chinese Medicine, Qingdao 266112, China
| | - Pu Ge
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100105, China
| | - Xiaoming Zhang
- Department of Cardiovascular Surgery, The Affiliated Hospital of Qingdao University, Qingdao 266000, China
| | - Yunchou Wu
- School of Psychology, Southwest University, Chongqing 400715, China
| | - Zhaocai Sun
- Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao 266112, China; Qingdao Academy of Chinese Medical Sciences, Shandong University of Traditional Chinese Medicine, Qingdao 266112, China; Qingdao Key Laboratory of Artificial Intelligence Technology in Traditional Chinese Medicine, Qingdao 266112, China
| | - Qian Bai
- School of Management, Beijing University of Chinese Medicine, Beijing 100105, China
| | - Shanshan Jing
- College of Health Sciences, Shandong University of Traditional Chinese Medicine, Jinan, Shandong 250355, China
| | - Huali Zuo
- Warshel Institute for Computational Biology, The Chinese University of Hong Kong, Shenzhen 518172, China
| | - Pingping Wang
- Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao 266112, China; Qingdao Academy of Chinese Medical Sciences, Shandong University of Traditional Chinese Medicine, Qingdao 266112, China; Qingdao Key Laboratory of Artificial Intelligence Technology in Traditional Chinese Medicine, Qingdao 266112, China
| | - Jinyu Cong
- Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao 266112, China; Qingdao Academy of Chinese Medical Sciences, Shandong University of Traditional Chinese Medicine, Qingdao 266112, China; Qingdao Key Laboratory of Artificial Intelligence Technology in Traditional Chinese Medicine, Qingdao 266112, China
| | - Xiang Li
- Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao 266112, China; Qingdao Academy of Chinese Medical Sciences, Shandong University of Traditional Chinese Medicine, Qingdao 266112, China; Qingdao Key Laboratory of Artificial Intelligence Technology in Traditional Chinese Medicine, Qingdao 266112, China
| | - Kunmeng Liu
- Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao 266112, China; Qingdao Academy of Chinese Medical Sciences, Shandong University of Traditional Chinese Medicine, Qingdao 266112, China; Qingdao Key Laboratory of Artificial Intelligence Technology in Traditional Chinese Medicine, Qingdao 266112, China.
| | - Yibo Wu
- School of Public Health, Peking University, Haidian District, Beijing 100191, China.
| | - Benzheng Wei
- Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao 266112, China; Qingdao Academy of Chinese Medical Sciences, Shandong University of Traditional Chinese Medicine, Qingdao 266112, China; Qingdao Key Laboratory of Artificial Intelligence Technology in Traditional Chinese Medicine, Qingdao 266112, China.
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Duan Y, Li S, Su Q, Xu S, Lu G. Influence of exercise prescription intervention based on WeChat on glycolipid metabolism and fitness of suboptimal-health teachers. Medicine (Baltimore) 2024; 103:e38167. [PMID: 38788028 PMCID: PMC11124765 DOI: 10.1097/md.0000000000038167] [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: 03/03/2024] [Accepted: 04/17/2024] [Indexed: 05/26/2024] Open
Abstract
Exercise is an effective means to promote health, but adherence is low. Due to the advantages of immediacy, economy and effectiveness, the use of WeChat social software has permeated into every aspect in daily life in China. To explore the influence of WeChat-based exercise prescription intervention mode on glycolipid metabolism and fitness of suboptimal-health teachers. 293 suboptimal-health teachers with senior professional titles were randomized to a control group (CG) or an experimental group (e.g.). The CG exercised on its own, while the e.g. adopted the exercise prescription intervention based on WeChat. The intervention period was 6 months. Finally, 264 cases were adhered to and completed, including 132 cases in the CG and 132 cases in the e.g.. The Suboptimal-Health Status Questionnaires-25 scores (SHSQ-25 scores), exercise adherence, subjective feelings, physical fitness, blood glucose and blood lipids were detected before and after intervention and compared between 2 groups. After the intervention, the SHSQ-25 scores in the e.g. was significantly decreased than those in the CG (P < .01). The complete exercise adherence in the e.g. was significantly higher than those in the CG (P < .01). After intervention, the subjective feelings of e.g. were significantly improved compared to CG (P < .05). The body shape, body function and physical quality in the e.g. was higher than those in the CG (P < .05). Total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C) decreased significantly in the e.g. but not in the CG (P < .05). Fasting blood glucose (FBG) decreased significantly in the e.g. but not in the CG, with a significant difference between groups (P < .05). The subjects in the e.g. were very satisfied with WeChat management. WeChat-based exercise prescription intervention could improve SHS, exercise adherence, subjective feelings, physical fitness and glycolipid metabolism.
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Affiliation(s)
- Yimei Duan
- Institute of Sports Medicine and Health, Chengdu Sports University, Chengdu, Sichuan, China
- College of Physical Education, Sichuan Normal University, Chengdu, Sichuan, China
| | - Shunchang Li
- Institute of Sports Medicine and Health, Chengdu Sports University, Chengdu, Sichuan, China
| | - Quansheng Su
- Institute of Sports Medicine and Health, Chengdu Sports University, Chengdu, Sichuan, China
| | - Simao Xu
- College of Physical Education, Guangxi Normal University, Guilin, Guangxi, China
| | - Guotian Lu
- College of Physical Education, Sichuan Normal University, Chengdu, Sichuan, China
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Yu L, Liu W, Wang J, Jin Z, Meng R, Wu Z, Zheng Y, Guo Z. Evaluating the association between effort-reward imbalance and suboptimal health status among hospital nurses: a cross-sectional study. Int J Occup Med Environ Health 2024; 37:165-175. [PMID: 38529760 PMCID: PMC11142399 DOI: 10.13075/ijomeh.1896.02223] [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: 05/07/2023] [Accepted: 01/30/2024] [Indexed: 03/27/2024] Open
Abstract
OBJECTIVES Occupational stress is a common complaint in nurses, who perceived more sense of effort-reward imbalance (ERI). Suboptimal health status (SHS) is a state between health and disease. However, the correlation between ERI and SHS is unclear. Therefore, the aim of this study was to examine the prevalence of SHS and ERI and evaluate the relationship between ERI and SHS in clinical nurses by a cross-sectional study. MATERIAL AND METHODS The current cross-sectional study was conducted through an online survey at Dongping People's Hospital in China. A total of 633 completed surveys were received. Effort-reward imbalance was measured by subscales of the ERI questionnaire. SHS was measured by the Suboptimal Health Status Questionnaire - 25 (SHSQ-25). The relationship between ERI and SHS in nurses was subsequently assessed by Spearman's correlation coefficient and logistic regression model. RESULTS The mean age of the optimal health status (OHS) group (M±SD 26.3±7.3 years) was younger than the SHS group (M±SD 30.3±6.9 years). The prevalence of SHS was 54.5% (345/633). Female nurses aged ≥30 years, a junior college or university graduate educational level, smokers, and nurses without regular exercise were at a higher risk of SHS. In Spearman's correlation analysis, ERI reflected by the effort-reward ratio was correlated with SHSQ-25 score (r = 0.662, p < 0.001). In logistic regression, ERI was strongly associated with SHS after potential confounding factors adjusting (OR 27.924, 95% CI 22.845-34.132). CONCLUSIONS The prevalence of SHS was significantly high in clinical nurses. Administrators should pay more attention to health status of female nurses aged ≥30 years, with a junior college or bachelor's degree, smoking, and without regular exercise to reduce the SHS and ERI. Int J Occup Med Environ Health. 2024;37(2):166-75.
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Affiliation(s)
- Leilei Yu
- The Affiliated Tai'an City Central Hospital of Qingdao University, Department of Endocrinology, Tai'an, China
| | - Weiting Liu
- Edith Cowan University, School of Nursing and Midwifery, Joondalup, Australia
| | - Jingzheng Wang
- Dongping People's Hospital, Department of Laboratory, Tai'an, China
| | - Ziyao Jin
- Zhejiang University School of Medicine, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Stomatology Hospital, School of Stomatology, Hangzhou, China
| | - Ruoyu Meng
- Shandong Provincial Hospital Affiliated to Shandong First Medical University, Department of Minimally Invasive Comprehensive Treatment of Cancer, Ji'nan, China
| | - Zhiyuan Wu
- Capital Medical University, Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Beijing, China
- Edith Cowan University, Centre for Precision Health, Joondalup, Australia
| | - Yuanyuan Zheng
- The Affiliated Tai'an City Central Hospital of Qingdao University, Department of Radiotherapy, Tai'an, China
| | - Zheng Guo
- Edith Cowan University, Centre for Precision Health, Joondalup, Australia
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Tong LK, Au ML, Zheng MR, Liu YB, Fu GL, Li YY. The effect of family health on suboptimal health status: The parallel mediation role of sleep quality and health behaviour. J Glob Health 2024; 14:04071. [PMID: 38574356 PMCID: PMC10994672 DOI: 10.7189/jogh.14.04071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/06/2024] Open
Abstract
Background The prevalence of suboptimal health status has been increasing worldwide, posing a significant challenge to public health. Meanwhile, family health has been recognised as an important factor influencing individual health outcomes. However, the mechanisms through which family health affects suboptimal health status remain unclear. We aimed to investigate the parallel mediation role of sleep quality and health behaviour in the relationship between family health and suboptimal health status. Methods We conducted a cross-sectional online survey with a sample of adults >18 years old from four provinces in China. The survey questionnaires queried their demographic characteristics, family health, suboptimal health status, sleep quality, and health behaviour. We assessed family health by the Family Health Scale-Short Form and suboptimal health status using the Suboptimal Health Status Questionnaire. We employed structural equation modelling to analyse the data and test the proposed mediation model. Results we collected 4918 valid questionnaires. The mean age of the participants was 30.1 years (standard deviation = 12.5). The correlation analysis demonstrated a significant negative association between family health and suboptimal health status (r = -0.44; P < 0.001). The results of the parallel mediation analysis showed that family health had a significant indirect effect on suboptimal health status through both sleep quality (β = -0.350; P < 0.001) and health behaviour (β = -0.137; P < 0.001). The total indirect effect of family health on suboptimal health status through both sleep quality and health behaviour was also significant (β = -0.569, P < 0.001). Conclusions This study highlights the significance of family health as a predictor of suboptimal health status and suggests that sleep quality and health behaviour are parallel mediators in this relationship. By understanding the role of family health, sleep quality, and health behaviour, interventions can be targeted to improve overall health outcomes.
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Affiliation(s)
- Lai Kun Tong
- Research Management and Development Department, Kiang Wu Nursing College of Macau, Macao, China
| | - Mio Leng Au
- Education Department, Kiang Wu Nursing College of Macau, Macao, China
| | - Mu Rui Zheng
- Faculty of Health Sciences, University of Macau, Macao, China
| | - Yong Bing Liu
- School of Nursing, Yangzhou University, Yangzhou, China
| | - Guang Lei Fu
- Infectious Disease Department, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Yue Yi Li
- Education Department, Kiang Wu Nursing College of Macau, Macao, China
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Guan Q, Dong H, Zhang Z, Guo Z, Lin Z, Niu H, Wu Y, Hou H. The mediating effect of perceived stress on the relationship between big five personality traits and suboptimal health status in Chinese population: a nationwide survey in the framework of predictive, preventive, and personalized medicine. EPMA J 2024; 15:25-38. [PMID: 38463623 PMCID: PMC10923761 DOI: 10.1007/s13167-023-00349-x] [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: 09/02/2023] [Accepted: 11/22/2023] [Indexed: 03/12/2024]
Abstract
Background The effects of psychological factors on suboptimal health status (SHS) have been widely described; however, mechanisms behind the complex relationships among the Big Five personality traits and SHS are unclear. Identifying people with specific traits who are susceptible to SHS will help improve life quality and reduce the chronic disease burden under the framework of predictive, preventive, and personalized medicine (PPPM / 3PM). This study investigated the relationships among personality traits and SHS. It also explored whether perceived stress plays a mediating role in SHS development. Method A nationwide cross-sectional survey based on multistage random sampling was conducted in 148 cities in China between June 20 and August 31, 2022. Personality traits, perceived stress, and SHS were evaluated using the Big Five Inventory-10 (BFI-10), the 4-item Perceived Stress Scale (PSS-4), and the Short-Form Suboptimal Health Status Questionnaire (SHSQ-SF), respectively. Pearson's correlation analysis was employed to examine the associations between personality traits, perceived stress, and SHS. Structural equation modeling (SEM) was used to discern the mediating role of perceived stress in the relationships among personality traits and SHS. Result A total of 22,897 participants were enrolled in this study, among whom the prevalence of SHS was 52.9%. SHS was negatively correlated with three trait dimensions (i.e., extraversion, agreeableness, and conscientiousness) but positively correlated with neuroticism. Meanwhile, stress was negatively correlated with extraversion, agreeableness, conscientiousness, and openness, whereas it was positively correlated with neuroticism. The SEM results showed that, when adjusting for covariates (i.e., gender, age, BMI, educational level, current residence, marital status, and occupational status), higher agreeableness (β = - 0.049, P < 0.001) and conscientiousness (β = - 0.103, P < 0.001) led to lower SHS prevalence, higher neuroticism (β = 0.130, P < 0.001), and openness (β = 0.026, P < 0.001) caused SHS to be more prevalent. Perceived stress played a partial mediating role in the relationships among personality traits and SHS, respectively, contributing 41.3%, 35.9%, and 32.5% to the total effects of agreeableness, conscientiousness, and neuroticism on SHS. Additionally, the mediating impact of stress was significant even though extraversion had no direct effect on SHS. Conclusion This study revealed a high prevalence of SHS in Chinese residents. Personality traits significantly influenced SHS rates, which perceived stress tended to mediate. From a PPPM perspective, early screening and targeted intervention for people with neuroticism (as well as stress alleviation) might contribute to health enhancement and chronic disease prevention. Supplementary Information The online version contains supplementary material available at 10.1007/s13167-023-00349-x.
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Affiliation(s)
- Qihua Guan
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Hualei Dong
- Department of Sanatorium, Shandong Provincial Taishan Hospital, Taian, China
| | - Zhihui Zhang
- Department of Thoracic Surgery, The Second Affiliated Hospital of Shandong First Medical University, Taian, China
| | - Zheng Guo
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN USA
- School of Public Health, Edith Cowan University, Perth, Australia
| | - Zi Lin
- Department of Pediatrics, Taian Maternity and Child Health Hospital, Taian, China
| | - Hui Niu
- Department of Pediatrics, Taian Maternity and Child Health Hospital, Taian, China
| | - Yibo Wu
- School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing, 100191 China
| | - Haifeng Hou
- School of Public Health and The Second Affiliated Hospital of Shandong First Medical University, 6699 Qingdao Road, Jinan, 250117 Taian China
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Guo Z, Meng R, Zheng Y, Li X, Zhou Z, Yu L, Tang Q, Zhao Y, Garcia M, Yan Y, Song M, Balmer L, Wen J, Hou H, Tan X, Wang W. Translation and cross-cultural validation of a precision health tool, the Suboptimal Health Status Questionnaire-25, in Korean. J Glob Health 2022; 12:04077. [PMID: 36181723 PMCID: PMC9526479 DOI: 10.7189/jogh.12.04077] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Suboptimal health status (SHS) is a reversible stage between health and illness that is characterized by health complaints, low energy, general weakness, and chronic fatigue. The Suboptimal Health Status Questionnaire-25 (SHSQ-25) has been validated in three major populations (African, Asian, and Caucasian) and is internationally recognized as a reliable and robust tool for health estimation in general populations. This study focused on the development of K-SHSQ-25, a Korean version of the SHSQ-25, from its English version. METHODS The SHSQ-25 was translated from English to Korean according to international guidelines set forth by the World Health Organization (WHO) for health instrument translation between different languages. A subsequent cross-sectional survey involved 460 healthy South Korean participants (aged 18-83 years; 65.4% females) to answer the 25 questions focusing on the health perspectives of 5 domains, 1) fatigue, 2) cardiovascular health, 3) digestive tract, 4) immune system and 5) mental health. The K-SHSQ-25 was further validated using tests for reliability, internal consistency, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA). RESULTS The version of K-SHSQ-25 achieved linguistic, cultural, and conceptual equivalence to the English version. The intraclass correlation coefficient (ICC) of test-retest reliability for individual items ranged from 0.88 to 0.99. Reliability estimates based on internal consistency reached a Cronbach's α of 0.953; the Cronbach's α for each domain ranged from 0.76 to 0.94. Regarding construct validity, the EFA of the K-SHSQ-25 generally replicated the multidimensional structure (fatigue, cardiovascular, digestive, immune system, and mental health) and 25 questions. The CFA revealed that the root mean square error of approximation (RMSEA), goodness-of-fit index (GFI) and adjusted goodness of fit index (AGFI) were excellent (RMSEA = 0.069<0.08, GFI = 0.929>0.90, AGFI = 0.907>0.90). The five domains of the K-SHSQ-25 showed significant correlations with each other (r = 0.59-0.81, P<0.001). The cut-off point of K-SHSQ-25 for SHS was determined as an SHS score of 25. The prevalence of SHS in this study was 60.0% (276/460), with 47.8% (76/159) for males and 58.5% for females (176/301). CONCLUSIONS Our results indicate that the Korean version of SHSQ-25, K-SHSQ-25, is a transcultural equivalent, robust, valid, and reliable assessment tool for evaluating SHS in the Korean-speaking population.
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Affiliation(s)
- Zheng Guo
- Centre for Precision Health, Edith Cowan University, Joondalup, Western Australia, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia
- The Nathan Centre, Joondalup, Western Australia, Australia
| | - Ruoyu Meng
- Department of Physiology, Institute of Medical Science, Jeonbuk National University Medical School, Jeonju, Korea
| | - Yulu Zheng
- Centre for Precision Health, Edith Cowan University, Joondalup, Western Australia, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia
- The Nathan Centre, Joondalup, Western Australia, Australia
| | - Xingang Li
- Centre for Precision Health, Edith Cowan University, Joondalup, Western Australia, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia
- The Nathan Centre, Joondalup, Western Australia, Australia
| | - Ziqi Zhou
- Department of Herbology, School of Korean Medicine, Wonkwang University, Jeonbuk, Korea
| | - Leilei Yu
- Department of Endocrinology, Taian City Central Hospital, Taian, China
| | - Qian Tang
- Department of Obstetrics, Tengzhou People's Central Hospital, Tengzhou, China
| | - Ying Zhao
- School of Foreign Languages, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong, China
| | - Monique Garcia
- Centre for Precision Health, Edith Cowan University, Joondalup, Western Australia, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia
- The Nathan Centre, Joondalup, Western Australia, Australia
| | - Yuxiang Yan
- School of Foreign Languages, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong, China
| | - Manshu Song
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia
| | - Lois Balmer
- Centre for Precision Health, Edith Cowan University, Joondalup, Western Australia, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia
- Department of Physiology, Institute of Medical Science, Jeonbuk National University Medical School, Jeonju, Korea
| | - Jun Wen
- School of Business and Law, Edith Cowan University, Joondalup, Western Australia, Australia
| | - Haifeng Hou
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia
- School of Public Health, Shandong First Medical University &
- Shandong Academy of Medical Sciences, Taian, Shandong, China
| | - Xuerui Tan
- The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Wei Wang
- Centre for Precision Health, Edith Cowan University, Joondalup, Western Australia, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia
- The Nathan Centre, Joondalup, Western Australia, Australia
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong, China
- The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
- Nutrition & Health Innovation Research Institute, Edith Cowan University, Joondalup, Western Australia, Australia
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Guo Z, Wen J, Zheng D, Yulu Z, Hou H, Wang W. Proposing an avenue for suboptimal health research through the lens of tourism. J Glob Health 2022; 12:03058. [PMID: 36065526 PMCID: PMC9445567 DOI: 10.7189/jogh.12.03058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Affiliation(s)
- Zheng Guo
- Centre for Precision Health, Edith Cowan University, Joondalup, Australia
| | - Jun Wen
- School of Business and Law, Edith Cowan University, Joondalup, Australia
| | - Danni Zheng
- Department of Tourism, Fudan University, Shanghai, China
| | - Zheng Yulu
- Centre for Precision Health, Edith Cowan University, Joondalup, Australia
| | - Haifeng Hou
- School of Public Health, Shandong First Medical University &
- Shandong Academy of Medical Sciences, Taian, China
| | - Wei Wang
- Centre for Precision Health, Edith Cowan University, Joondalup, Australia
- School of Public Health, Shandong First Medical University &
- Shandong Academy of Medical Sciences, Taian, China
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
- The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
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10
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Wang Y, Tian J, Qu H, Yu L, Zhang X, Huang L, Zhou J, Lian W, Wang R, Wang L, Li G, Tang L. Changes in blood pressure and related risk factors among nurses working in a negative pressure isolation ward. Front Public Health 2022; 10:942904. [PMID: 35937224 PMCID: PMC9353044 DOI: 10.3389/fpubh.2022.942904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 06/22/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectiveTo observe changes in blood pressure (ΔBP) and explore potential risk factors for high ΔBP among nurses working in a negative pressure isolation ward (NPIW).MethodsData from the single-center prospective observational study were used. Based on a routine practice plan, female nurses working in NPIW were scheduled to work for 4 days/week in different shifts, with each day working continuously for either 5 or 6 h. BP was measured when they entered and left NPIW. Multivariable logistic regression was used to assess potential risk factors in relation to ΔBP ≥ 5 mm Hg.ResultsA total of 84 nurses were included in the analysis. The ΔBP was found to fluctuate on different working days; no significant difference in ΔBP was observed between the schedules of 5 and 6 h/day. The standardized score from the self-rating anxiety scale (SAS) was significantly associated with an increased risk of ΔBP ≥ 5 mm Hg (odds ratio [OR] = 1.12, 95% CI: 1.00–1.24). Working 6 h/day (vs. 5 h/day) in NPIW was non-significantly related to decreased risk of ΔBP (OR = 0.70), while ≥ 2 consecutive working days (vs. 1 working day) was non-significantly associated with increased risk of ΔBP (OR = 1.50).ConclusionThis study revealed no significant trend for ΔBP by working days or working time. Anxiety was found to be significantly associated with increased ΔBP, while no <2 consecutive working days were non-significantly related to ΔBP. These findings may provide some preliminary evidence for BP control in nurses who are working in NPIW for Coronavirus Disease 2019 (COVID-19).
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Affiliation(s)
- Yaoyao Wang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Junzhang Tian
- Institute for Healthcare Artificial Intelligence Application, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Hongying Qu
- Center for Clinical Epidemiology and Methodology (CCEM), Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Lingna Yu
- Nursing Department, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Xiaoqin Zhang
- Nursing Department, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Lishan Huang
- Infectious Diseases Ward, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Jianqun Zhou
- Infectious Diseases Ward, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Wanmin Lian
- Center for Information, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Ruoting Wang
- Center for Clinical Epidemiology and Methodology (CCEM), Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Lijun Wang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Guowei Li
- Center for Clinical Epidemiology and Methodology (CCEM), Guangdong Second Provincial General Hospital, Guangzhou, China
- Department of Health Research Methods, Evidence, and Impact (HEI), McMaster University, Hamilton, ON, Canada
- Li Tang
| | - Li Tang
- Nursing Department, Guangdong Second Provincial General Hospital, Guangzhou, China
- *Correspondence: Guowei Li
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11
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Wang W, Yan Y, Guo Z, Hou H, Garcia M, Tan X, Anto EO, Mahara G, Zheng Y, Li B, Kang T, Zhong Z, Wang Y, Guo X, Golubnitschaja O. All around suboptimal health - a joint position paper of the Suboptimal Health Study Consortium and European Association for Predictive, Preventive and Personalised Medicine. EPMA J 2021; 12:403-433. [PMID: 34539937 PMCID: PMC8435766 DOI: 10.1007/s13167-021-00253-2] [Citation(s) in RCA: 58] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 08/25/2021] [Indexed: 02/07/2023]
Abstract
First two decades of the twenty-first century are characterised by epidemics of non-communicable diseases such as many hundreds of millions of patients diagnosed with cardiovascular diseases and the type 2 diabetes mellitus, breast, lung, liver and prostate malignancies, neurological, sleep, mood and eye disorders, amongst others. Consequent socio-economic burden is tremendous. Unprecedented decrease in age of maladaptive individuals has been reported. The absolute majority of expanding non-communicable disorders carry a chronic character, over a couple of years progressing from reversible suboptimal health conditions to irreversible severe pathologies and cascading collateral complications. The time-frame between onset of SHS and clinical manifestation of associated disorders is the operational area for an application of reliable risk assessment tools and predictive diagnostics followed by the cost-effective targeted prevention and treatments tailored to the person. This article demonstrates advanced strategies in bio/medical sciences and healthcare focused on suboptimal health conditions in the frame-work of Predictive, Preventive and Personalised Medicine (3PM/PPPM). Potential benefits in healthcare systems and for society at large include but are not restricted to an improved life-quality of major populations and socio-economical groups, advanced professionalism of healthcare-givers and sustainable healthcare economy. Amongst others, following medical areas are proposed to strongly benefit from PPPM strategies applied to the identification and treatment of suboptimal health conditions:Stress overload associated pathologiesMale and female healthPlanned pregnanciesPeriodontal healthEye disordersInflammatory disorders, wound healing and pain management with associated complicationsMetabolic disorders and suboptimal body weightCardiovascular pathologiesCancersStroke, particularly of unknown aetiology and in young individualsSleep medicineSports medicineImproved individual outcomes under pandemic conditions such as COVID-19.
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Affiliation(s)
- Wei Wang
- Centre for Precision Health, Edith Cowan University, Perth, Australia
- Beijing Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai’an, China
- First Affiliated Hospital, Shantou University Medical College, Shantou, China
- Suboptimal Health Study Consortium, Kumasi, Ghana
- Suboptimal Health Study Consortium, Perth, Australia
- Suboptimal Health Study Consortium, Beijing, China
- Suboptimal Health Study Consortium, Bonn, Germany
- European Association for Predictive, Preventive and Personalised, Medicine, Brussels, Belgium
| | - Yuxiang Yan
- Beijing Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
- Suboptimal Health Study Consortium, Kumasi, Ghana
- Suboptimal Health Study Consortium, Perth, Australia
- Suboptimal Health Study Consortium, Beijing, China
- Suboptimal Health Study Consortium, Bonn, Germany
- European Association for Predictive, Preventive and Personalised, Medicine, Brussels, Belgium
| | - Zheng Guo
- Centre for Precision Health, Edith Cowan University, Perth, Australia
- Suboptimal Health Study Consortium, Kumasi, Ghana
- Suboptimal Health Study Consortium, Perth, Australia
- Suboptimal Health Study Consortium, Beijing, China
- Suboptimal Health Study Consortium, Bonn, Germany
- European Association for Predictive, Preventive and Personalised, Medicine, Brussels, Belgium
| | - Haifeng Hou
- Centre for Precision Health, Edith Cowan University, Perth, Australia
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai’an, China
- Suboptimal Health Study Consortium, Kumasi, Ghana
- Suboptimal Health Study Consortium, Perth, Australia
- Suboptimal Health Study Consortium, Beijing, China
- Suboptimal Health Study Consortium, Bonn, Germany
- European Association for Predictive, Preventive and Personalised, Medicine, Brussels, Belgium
| | - Monique Garcia
- Centre for Precision Health, Edith Cowan University, Perth, Australia
- Suboptimal Health Study Consortium, Kumasi, Ghana
- Suboptimal Health Study Consortium, Perth, Australia
- Suboptimal Health Study Consortium, Beijing, China
- Suboptimal Health Study Consortium, Bonn, Germany
- European Association for Predictive, Preventive and Personalised, Medicine, Brussels, Belgium
| | - Xuerui Tan
- First Affiliated Hospital, Shantou University Medical College, Shantou, China
- Suboptimal Health Study Consortium, Kumasi, Ghana
- Suboptimal Health Study Consortium, Perth, Australia
- Suboptimal Health Study Consortium, Beijing, China
- Suboptimal Health Study Consortium, Bonn, Germany
- European Association for Predictive, Preventive and Personalised, Medicine, Brussels, Belgium
| | - Enoch Odame Anto
- Centre for Precision Health, Edith Cowan University, Perth, Australia
- Suboptimal Health Study Consortium, Kumasi, Ghana
- Suboptimal Health Study Consortium, Perth, Australia
- Suboptimal Health Study Consortium, Beijing, China
- Suboptimal Health Study Consortium, Bonn, Germany
- European Association for Predictive, Preventive and Personalised, Medicine, Brussels, Belgium
- Department of Medical Diagnostics, College of Health Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Gehendra Mahara
- First Affiliated Hospital, Shantou University Medical College, Shantou, China
- Suboptimal Health Study Consortium, Kumasi, Ghana
- Suboptimal Health Study Consortium, Perth, Australia
- Suboptimal Health Study Consortium, Beijing, China
- Suboptimal Health Study Consortium, Bonn, Germany
- European Association for Predictive, Preventive and Personalised, Medicine, Brussels, Belgium
| | - Yulu Zheng
- Centre for Precision Health, Edith Cowan University, Perth, Australia
- Suboptimal Health Study Consortium, Kumasi, Ghana
- Suboptimal Health Study Consortium, Perth, Australia
- Suboptimal Health Study Consortium, Beijing, China
- Suboptimal Health Study Consortium, Bonn, Germany
- European Association for Predictive, Preventive and Personalised, Medicine, Brussels, Belgium
| | - Bo Li
- Suboptimal Health Study Consortium, Kumasi, Ghana
- Suboptimal Health Study Consortium, Perth, Australia
- Suboptimal Health Study Consortium, Beijing, China
- Suboptimal Health Study Consortium, Bonn, Germany
- European Association for Predictive, Preventive and Personalised, Medicine, Brussels, Belgium
- School of Nursing and Health, Henan University, Kaifeng, China
| | - Timothy Kang
- Suboptimal Health Study Consortium, Kumasi, Ghana
- Suboptimal Health Study Consortium, Perth, Australia
- Suboptimal Health Study Consortium, Beijing, China
- Suboptimal Health Study Consortium, Bonn, Germany
- European Association for Predictive, Preventive and Personalised, Medicine, Brussels, Belgium
- Institute of Chinese Acuology, Perth, Australia
| | - Zhaohua Zhong
- Suboptimal Health Study Consortium, Kumasi, Ghana
- Suboptimal Health Study Consortium, Perth, Australia
- Suboptimal Health Study Consortium, Beijing, China
- Suboptimal Health Study Consortium, Bonn, Germany
- European Association for Predictive, Preventive and Personalised, Medicine, Brussels, Belgium
- School of Basic Medicine, Harbin Medical University, Harbin, China
| | - Youxin Wang
- Centre for Precision Health, Edith Cowan University, Perth, Australia
- Beijing Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
- Suboptimal Health Study Consortium, Kumasi, Ghana
- Suboptimal Health Study Consortium, Perth, Australia
- Suboptimal Health Study Consortium, Beijing, China
- Suboptimal Health Study Consortium, Bonn, Germany
- Department of Medical Diagnostics, College of Health Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Xiuhua Guo
- Beijing Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
- Suboptimal Health Study Consortium, Kumasi, Ghana
- Suboptimal Health Study Consortium, Perth, Australia
- Suboptimal Health Study Consortium, Beijing, China
- Suboptimal Health Study Consortium, Bonn, Germany
- European Association for Predictive, Preventive and Personalised, Medicine, Brussels, Belgium
| | - Olga Golubnitschaja
- Suboptimal Health Study Consortium, Kumasi, Ghana
- Suboptimal Health Study Consortium, Perth, Australia
- Suboptimal Health Study Consortium, Beijing, China
- Suboptimal Health Study Consortium, Bonn, Germany
- European Association for Predictive, Preventive and Personalised, Medicine, Brussels, Belgium
- Predictive, Preventive and Personalised (3P) Medicine, Department of Radiation Oncology, University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
| | - On Behalf of Suboptimal Health Study Consortium and European Association for Predictive, Preventive and Personalised Medicine
- Centre for Precision Health, Edith Cowan University, Perth, Australia
- Beijing Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai’an, China
- First Affiliated Hospital, Shantou University Medical College, Shantou, China
- Suboptimal Health Study Consortium, Kumasi, Ghana
- Suboptimal Health Study Consortium, Perth, Australia
- Suboptimal Health Study Consortium, Beijing, China
- Suboptimal Health Study Consortium, Bonn, Germany
- European Association for Predictive, Preventive and Personalised, Medicine, Brussels, Belgium
- Department of Medical Diagnostics, College of Health Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
- School of Nursing and Health, Henan University, Kaifeng, China
- Institute of Chinese Acuology, Perth, Australia
- School of Basic Medicine, Harbin Medical University, Harbin, China
- Predictive, Preventive and Personalised (3P) Medicine, Department of Radiation Oncology, University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
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Mahara G, Liang J, Zhang Z, Ge Q, Zhang J. Associated Factors of Suboptimal Health Status Among Adolescents in China: A Cross-Sectional Study. J Multidiscip Healthc 2021; 14:1063-1071. [PMID: 33994792 PMCID: PMC8114174 DOI: 10.2147/jmdh.s302826] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 04/01/2021] [Indexed: 12/27/2022] Open
Abstract
PURPOSE Suboptimal health status (SHS) is a state between health and disease, has several adverse effects, although, its main underlying mechanism is still unclear. This study aimed to investigate SHS and its associated factors of adolescents. METHODS A community-based cross-sectional study was conducted in the three different geographic locations of China (Shanxi, Guangzhou, and Tibet). A multidimensional sub-health questionnaire of adolescent (MSQA) is used to evaluate SHS. Independent two-sample K-S test was performed for the quantitative data as the non-parametric test, whereas Chi-square test method was applied to explore the difference of discrete variables data between groups. Then finally, multiple logistic regression analysis was applied to analyze the influential factors of SHS. RESULTS Among 1461 respondents (between 15 and 18 years old), females proportion (56.47%) was higher than males (43.53%) where SHS was higher in Shanxi followed by Tibet and then Guangdong. The rural area, grade, lack of sleep time, home visit in a week, lack of exercise, a heavy burden of study, smoking, drinking, and fewer friends were the risk factors of SHS, while families living status, seeking help and extroversion were the protective factors. CONCLUSION SHS is significantly associated with behavior and lifestyle-related factors. For comprehensively prevention and control of the SHS, it is urgently needed to reduce the risk factors and enhance the protective factors among adolescents.
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Affiliation(s)
- Gehendra Mahara
- Department of Medical Statistics, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, People’s Republic of China
| | - Jiazhi Liang
- Center for Disease Control and Prevention at Haizhu, Guangzhou, Guangdong, 510288, People’s Republic of China
| | - Zhirong Zhang
- Nanhai District People’s Hospital of Foshan City, Foshan, Guangdong, People’s Republic of China
| | - Qi Ge
- Department of Medical Statistics, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, People’s Republic of China
| | - Jinxin Zhang
- Department of Medical Statistics, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, People’s Republic of China
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13
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Liskova A, Samec M, Koklesova L, Kudela E, Kubatka P, Golubnitschaja O. Mitochondriopathies as a Clue to Systemic Disorders-Analytical Tools and Mitigating Measures in Context of Predictive, Preventive, and Personalized (3P) Medicine. Int J Mol Sci 2021; 22:ijms22042007. [PMID: 33670490 PMCID: PMC7922866 DOI: 10.3390/ijms22042007] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 02/11/2021] [Accepted: 02/14/2021] [Indexed: 02/06/2023] Open
Abstract
The mitochondrial respiratory chain is the main site of reactive oxygen species (ROS) production in the cell. Although mitochondria possess a powerful antioxidant system, an excess of ROS cannot be completely neutralized and cumulative oxidative damage may lead to decreasing mitochondrial efficiency in energy production, as well as an increasing ROS excess, which is known to cause a critical imbalance in antioxidant/oxidant mechanisms and a "vicious circle" in mitochondrial injury. Due to insufficient energy production, chronic exposure to ROS overproduction consequently leads to the oxidative damage of life-important biomolecules, including nucleic acids, proteins, lipids, and amino acids, among others. Different forms of mitochondrial dysfunction (mitochondriopathies) may affect the brain, heart, peripheral nervous and endocrine systems, eyes, ears, gut, and kidney, among other organs. Consequently, mitochondriopathies have been proposed as an attractive diagnostic target to be investigated in any patient with unexplained progressive multisystem disorder. This review article highlights the pathomechanisms of mitochondriopathies, details advanced analytical tools, and suggests predictive approaches, targeted prevention and personalization of medical services as instrumental for the overall management of mitochondriopathy-related cascading pathologies.
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Affiliation(s)
- Alena Liskova
- Clinic of Obstetrics and Gynecology, Jessenius Faculty of Medicine, Comenius University in Bratislava, 036 01 Martin, Slovakia; (A.L.); (M.S.); (L.K.); (E.K.)
| | - Marek Samec
- Clinic of Obstetrics and Gynecology, Jessenius Faculty of Medicine, Comenius University in Bratislava, 036 01 Martin, Slovakia; (A.L.); (M.S.); (L.K.); (E.K.)
| | - Lenka Koklesova
- Clinic of Obstetrics and Gynecology, Jessenius Faculty of Medicine, Comenius University in Bratislava, 036 01 Martin, Slovakia; (A.L.); (M.S.); (L.K.); (E.K.)
| | - Erik Kudela
- Clinic of Obstetrics and Gynecology, Jessenius Faculty of Medicine, Comenius University in Bratislava, 036 01 Martin, Slovakia; (A.L.); (M.S.); (L.K.); (E.K.)
| | - Peter Kubatka
- Department of Medical Biology, Jessenius Faculty of Medicine, Comenius University in Bratislava, 036 01 Martin, Slovakia
- European Association for Predictive, Preventive and Personalised Medicine, EPMA, 1160 Brussels, Belgium
- Correspondence: (P.K.); (O.G.)
| | - Olga Golubnitschaja
- European Association for Predictive, Preventive and Personalised Medicine, EPMA, 1160 Brussels, Belgium
- Predictive, Preventive and Personalised (3P) Medicine, Department of Radiation Oncology, University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, 53127 Bonn, Germany
- Correspondence: (P.K.); (O.G.)
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14
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Al Maqbali M, Al Sinani M, Al-Lenjawi B. Prevalence of stress, depression, anxiety and sleep disturbance among nurses during the COVID-19 pandemic: A systematic review and meta-analysis. J Psychosom Res 2021; 141:110343. [PMID: 33360329 PMCID: PMC7831768 DOI: 10.1016/j.jpsychores.2020.110343] [Citation(s) in RCA: 227] [Impact Index Per Article: 75.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 12/14/2020] [Accepted: 12/14/2020] [Indexed: 12/23/2022]
Abstract
BACKGROUND The new coronavirus disease's (COVID-19) high risk of infection can increase the workload of healthcare workers, especially nurses, as they are most of the healthcare workforce. These problems can lead to psychological problems. Therefore, the aim of this systematic review and meta-analysis to ascertain the present impact of the COVID-19 outbreak on the prevalence of stress, anxiety, depression and sleep disturbance among nurses. METHODS A systematic review and meta-analysis were conducted. The following databases were searched: PubMed, CHINAL, MEDLINE, EMBASE, PsycINFO, MedRxiv and Google Scholar, from January 2020 up to 26th October 2020. Prevalence rates were pooled with meta-analysis using a random-effects model. Heterogeneity was tested using I-squared (I2) statistics. RESULTS A total of 93 studies (n = 93,112), published between January 2020 and September 2020, met the inclusion criteria. The overall prevalence of stress was assessed in 40 studies which accounted for 43% (95% CI 37-49). The pooled prevalence of anxiety was 37% (95% CI 32-41) in 73 studies. Depression was assessed in 62 studies, with a pooled prevalence of 35% (95% CI 31-39). Finally, 18 studies assessed sleep disturbance and the pooled prevalence was 43% (95% CI 36-50). CONCLUSION This meta-analysis found that approximately one third of nurses working during the COVID-19 epidemic were suffering from psychological symptoms. This highlights the importance of providing comprehensive support strategies to reduce the psychological impact of the COVID-19 outbreak among nurses under pandemic conditions. Further longitudinal study is needed to distinguish of psychological symptoms during and after the infectious disease outbreaks.
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Affiliation(s)
| | - Mohammed Al Sinani
- Reproductive and Developmental Biology Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK
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