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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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Ayubi E, Khazaei S, Borzouei S, Soltanian AR, Ghelichkhani S, Karbin F, Yan Y, Song M, Tian C, Zhang W, Sun J, Wang W. Validity and reliability of the Persian version of the Suboptimal Health Status Questionnaire among university staff in Iran. J Glob Health 2023; 13:04162. [PMID: 38098436 PMCID: PMC10722246 DOI: 10.7189/jogh.13.04162] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2023] Open
Abstract
Background Suboptimal Health Status Questionnaire-25 (SHSQ-25) is an established tool for measuring a precision health state between health and illness. The present study aims to assess the validity and reliability of a Persian version of SHSQ-25 (P-SHSQ-25) in a university staff Iranian population. Methods A sample of 316 academic and supporting staff (163 males, age range from 23 to 64 years old) from Hamadan University of Medical Sciences, Hamadan, Iran was recruited in this population-based cross-sectional study with a questionnaire validation from Apri1 to October 2022. Forward-backward translation method was performed for the SHSQ-25 translation from English to Persian. Internal reliability, content, convergence, discriminative and construct validity of the P-SHSQ-25 were examined. The factorial structure of the P-SHSQ-25 across groups was examined using measurement invariant test. Results In the translation process, the conceptual equivalence of the P-SHSQ-25 with the English version was confirmed. The item-content validity index and content validity ratio of all P-SHSQ-25 items were higher than the cut-off values of 0.70 and 0.62, respectively. Cronbach's α was higher than 0.70 for all P-SHSQ-25 domains. The confirmatory factor analysis (CFA) showed the fitness of five factors on the data set (comparative fit index = 0.88, and root mean square error of approximation = 0.07). The CFA model fit did not change substantially across sex, age, occupation, economic status, and body mass index (Δ comparative fit index (CFI)<0.01). Conclusions The P-SHSQ-25 can be used as a reliable and valid tool to measure health status for screening pre-chronic disease conditions in a primary care setting among Iranian population.
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Affiliation(s)
- Erfan Ayubi
- Social Determinants of Health Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Salman Khazaei
- Research Center for Health Sciences, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Shiva Borzouei
- Department of Endocrinology, School of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Ali Reza Soltanian
- Modeling of Noncommunicable Diseases Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Samereh Ghelichkhani
- Mother and Child Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Fatemeh Karbin
- Student Research Committee, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Yuxiang Yan
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Manshu Song
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Cuihong Tian
- Clinical Research Center, First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
- Center for Precision Health, Edith Cowan University, Joondalup, WA, Australia
| | - Wei Zhang
- Centre for Cognitive Neurology, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jing Sun
- School of Medicine and Dentistry, and Institute for Integrated and Intelligent Systems, Griffith University, Gold Coast, Australia
| | - Wei Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Clinical Research Center, First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
- Center for Precision Health, Edith Cowan University, Joondalup, WA, Australia
| | - Global Health Epidemiology Research Group (GHERG)
- Social Determinants of Health Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
- Research Center for Health Sciences, Hamadan University of Medical Sciences, Hamadan, Iran
- Department of Endocrinology, School of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran
- Modeling of Noncommunicable Diseases Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
- Mother and Child Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
- Student Research Committee, Hamadan University of Medical Sciences, Hamadan, Iran
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Clinical Research Center, First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
- Centre for Cognitive Neurology, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- School of Medicine and Dentistry, and Institute for Integrated and Intelligent Systems, Griffith University, Gold Coast, Australia
- Center for Precision Health, Edith Cowan University, Joondalup, WA, Australia
| | - Global Suboptimal Health Consortium (GSHC)
- Social Determinants of Health Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
- Research Center for Health Sciences, Hamadan University of Medical Sciences, Hamadan, Iran
- Department of Endocrinology, School of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran
- Modeling of Noncommunicable Diseases Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
- Mother and Child Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
- Student Research Committee, Hamadan University of Medical Sciences, Hamadan, Iran
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Clinical Research Center, First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
- Centre for Cognitive Neurology, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- School of Medicine and Dentistry, and Institute for Integrated and Intelligent Systems, Griffith University, Gold Coast, Australia
- Center for Precision Health, Edith Cowan University, Joondalup, WA, Australia
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Wang J, Wang Y, Guo Z, Lin Z, Jin X, Niu H, Wu Y, Tang L, Hou H. Influence of lifestyle on suboptimal health: Insights from a national cross-sectional survey in China. J Glob Health 2023; 13:04151. [PMID: 37974435 PMCID: PMC10654550 DOI: 10.7189/jogh.13.04151] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2023] Open
Abstract
Background Suboptimal health status (SHS) is a non-clinical or pre-disease state between optimal/ideal health and disease. While its etiology remains unclear, lifestyle is considered one of the most important risk factors. We aimed to examine the effects of lifestyles on SHS through a nationwide survey in China. Methods We conducted a cross-sectional survey in 148 cities across China between 20 June and 31 August 2022, on 30 505 participants from rural and urban communities gathered through stratified quota sampling. We measured SHS with the Short-Form Suboptimal Health Status Questionnaire (SHSQ-SF). We gathered information on participants' lifestyles (ie, smoking, alcohol consumption, breakfast habits, weekly food delivery frequency, intermittent fasting, sleep duration and physical activities) through face-to-face interview. We determined the relationship between lifestyle and SHS logistic regression analysis by based on odds ratios (ORs) and 95% confidence intervals (CIs). Results We included 22 897 participants (female: 13 056, male: 9841), 12 108 (52.88%) of whom reported exposure to SHS. After adjusting for demographic characteristics, individuals who currently smoked (OR = 1.165; 95% CI = 1.058-1.283) and those who drank alcohol (OR = 1.483; 95% CI = 1.377.1.596) were at a higher risk of SHS than those who have never done either. In a dose-response way, takeaway food consumption was associated with a higher risk of SHS, while increased frequency of breakfast and mild-intensity exercise conversely reduced said risk. Individuals with shorter sleep duration had a higher risk of SHS when compared to those who slept for more than seven hours per day. Conclusions We observed a relatively high prevalence of SHS across China, highlighting the importance of lifestyle in health promotion. Specifically, adopting healthy dietary habits, engaging in regular physical activity, and ensuring high-quality sleep are key in preventing SHS. Registration Chinese Clinical Trial Registry (ChiCTR2200061046).
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Affiliation(s)
- Jie Wang
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Yinghao Wang
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Zheng Guo
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, Tennessee
- School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
| | - Zi Lin
- Taian Maternity and Child Health Hospital, Taian, China
| | - Xiangqian Jin
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Hui Niu
- Taian Maternity and Child Health Hospital, Taian, China
| | - Yibo Wu
- School of Public Health, Peking University, Beijing, China
| | - Lihua Tang
- Department of Blood Transfusion, The Affiliated Taian City Central Hospital of Qingdao University, Taian, China
| | - Haifeng Hou
- School of Public Health and The Second Affiliated Hospital of Shandong First Medical University, Taian, China
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Liu Y, Wan C, Xi X. Measurement properties of the EQ-5D-5L in sub-health: evidence based on primary health care workers in China. Health Qual Life Outcomes 2023; 21:22. [PMID: 36890491 PMCID: PMC9996950 DOI: 10.1186/s12955-023-02105-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2022] [Accepted: 02/21/2023] [Indexed: 03/10/2023] Open
Abstract
BACKGROUND Sub-health which is the state between health and disease is a major global public health challenge. As a reversible stage, sub-health can work as a effective tool for the early detection or prevention of chronic disease. The EQ-5D-5L (5L) is a widely used, generic preference-based instrument while its validity in measuring sub-health is not clear. The aim of the study was thus to assess its measurement properties in individuals with sub-health in China. METHODS The data used were from a nationwide cross-sectional survey conducted among primary health care workers who were selected on the basis of convenience and voluntariness. The questionnaire was composited of 5L, Sub-Health Measurement Scale V1.0 (SHMS V1.0), social-demographic characteristics and a question assessing the presence of disease. Missing values and ceiling effects of 5L were calculated. The convergent validity of 5L utility and VAS scores was tested by assessing their correlations with SHMS V1.0 using Spearman's correlation coefficient. The known-groups validity of 5L utility and VAS scores was assessed by comparing their values between subgroups defined by SHMS V1.0 scores using the Kruskal-Wallis test. We also did an analysis in subgroups according to different regions of China. RESULTS A total of 2063 respondents were included in the analysis. No missing data were observed for the 5L dimensions and only one missing value was for the VAS score. 5L showed strong overall ceiling effects (71.1%). The ceiling effects were slightly weaker on the "pain/discomfort" (82.3%) and "anxiety/depression" (79.5%) dimensions compared with the other three dimensions (nearly 100%). The 5L weakly correlated with SHMS V1.0: the correlation coefficients were mainly between 0.2 and 0.3 for the two scores. 5L was yet not sensitive in distinguishing subgroups of respondents with different levels of sub-health, especially the subgroups with adjacent health status (p > 0.05). The results of subgroup analysis were generally consistent with those of the full sample. CONCLUSIONS It appears that the measurement properties of EQ-5D-5L in individuals with sub-health are not satisfactory in China. We thus should be cautious to use it in the population.
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Affiliation(s)
- Yueyue Liu
- The Research Center of National Drug Policy & Ecosystem, China Pharmaceutical University, No.639 Longmian Avenue, Jiangning District, Nanjing, Jiangsu Province, China
| | - Chuchuan Wan
- The Research Center of National Drug Policy & Ecosystem, China Pharmaceutical University, No.639 Longmian Avenue, Jiangning District, Nanjing, Jiangsu Province, China
| | - Xiaoyu Xi
- The Research Center of National Drug Policy & Ecosystem, China Pharmaceutical University, No.639 Longmian Avenue, Jiangning District, Nanjing, Jiangsu Province, China.
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Meng X, Wang F, Gao X, Wang B, Xu X, Wang Y, Wang W, Zeng Q. Association of IgG N-glycomics with prevalent and incident type 2 diabetes mellitus from the paradigm of predictive, preventive, and personalized medicine standpoint. EPMA J 2023; 14:1-20. [PMID: 36866157 PMCID: PMC9971369 DOI: 10.1007/s13167-022-00311-3] [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: 10/31/2022] [Accepted: 12/12/2022] [Indexed: 12/25/2022]
Abstract
Objectives Type 2 diabetes mellitus (T2DM), a major metabolic disorder, is expanding at a rapidly rising worldwide prevalence and has emerged as one of the most common chronic diseases. Suboptimal health status (SHS) is considered a reversible intermediate state between health and diagnosable disease. We hypothesized that the time frame between the onset of SHS and the clinical manifestation of T2DM is the operational area for the application of reliable risk assessment tools, such as immunoglobulin G (IgG) N-glycans. From the viewpoint of predictive, preventive, and personalized medicine (PPPM/3PM), the early detection of SHS and dynamic monitoring by glycan biomarkers could provide a window of opportunity for targeted prevention and personalized treatment of T2DM. Methods Case-control and nested case-control studies were performed and consisted of 138 and 308 participants, respectively. The IgG N-glycan profiles of all plasma samples were detected by an ultra-performance liquid chromatography instrument. Results After adjustment for confounders, 22, five, and three IgG N-glycan traits were significantly associated with T2DM in the case-control setting, baseline SHS, and baseline optimal health participants from the nested case-control setting, respectively. Adding the IgG N-glycans to the clinical trait models, the average area under the receiver operating characteristic curves (AUCs) of the combined models based on repeated 400 times fivefold cross-validation differentiating T2DM from healthy individuals were 0.807 in the case-control setting and 0.563, 0.645, and 0.604 in the pooled samples, baseline SHS, and baseline optimal health samples of nested case-control setting, respectively, which presented moderate discriminative ability and were generally better than models with either glycans or clinical features alone. Conclusions This study comprehensively illustrated that the observed altered IgG N-glycosylation, i.e., decreased galactosylation and fucosylation/sialylation without bisecting GlcNAc, as well as increased galactosylation and fucosylation/sialylation with bisecting GlcNAc, reflects a pro-inflammatory state of T2DM. SHS is an important window period of early intervention for individuals at risk for T2DM; glycomic biosignatures as dynamic biomarkers have the ability to identify populations at risk for T2DM early, and the combination of evidence could provide suggestive ideas and valuable insight for the PPPM of T2DM. Supplementary information The online version contains supplementary material available at 10.1007/s13167-022-00311-3.
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Affiliation(s)
- Xiaoni Meng
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen, Fengtai District, Beijing, 100069 China
| | - Fei Wang
- Health Management Institute, Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese People’s Liberation Army General Hospital, 28 Fuxing Road, Haidian District, Beijing, 100853 China
| | - Xiangyang Gao
- Health Management Institute, Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese People’s Liberation Army General Hospital, 28 Fuxing Road, Haidian District, Beijing, 100853 China
| | - Biyan Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen, Fengtai District, Beijing, 100069 China
| | - Xizhu Xu
- School of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, 250117 China
| | - Youxin Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen, Fengtai District, Beijing, 100069 China
| | - Wei Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen, Fengtai District, Beijing, 100069 China
- School of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, 250117 China
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Perth, WA 6027 Australia
| | - Qiang Zeng
- Health Management Institute, Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese People’s Liberation Army General Hospital, 28 Fuxing Road, Haidian District, Beijing, 100853 China
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Trbojević-Akmačić I, Lageveen-Kammeijer GSM, Heijs B, Petrović T, Deriš H, Wuhrer M, Lauc G. High-Throughput Glycomic Methods. Chem Rev 2022; 122:15865-15913. [PMID: 35797639 PMCID: PMC9614987 DOI: 10.1021/acs.chemrev.1c01031] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Glycomics aims to identify the structure and function of the glycome, the complete set of oligosaccharides (glycans), produced in a given cell or organism, as well as to identify genes and other factors that govern glycosylation. This challenging endeavor requires highly robust, sensitive, and potentially automatable analytical technologies for the analysis of hundreds or thousands of glycomes in a timely manner (termed high-throughput glycomics). This review provides a historic overview as well as highlights recent developments and challenges of glycomic profiling by the most prominent high-throughput glycomic approaches, with N-glycosylation analysis as the focal point. It describes the current state-of-the-art regarding levels of characterization and most widely used technologies, selected applications of high-throughput glycomics in deciphering glycosylation process in healthy and disease states, as well as future perspectives.
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Affiliation(s)
| | | | - Bram Heijs
- Center
for Proteomics and Metabolomics, Leiden
University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands
| | - Tea Petrović
- Genos,
Glycoscience Research Laboratory, Borongajska cesta 83H, 10 000 Zagreb, Croatia
| | - Helena Deriš
- Genos,
Glycoscience Research Laboratory, Borongajska cesta 83H, 10 000 Zagreb, Croatia
| | - Manfred Wuhrer
- Center
for Proteomics and Metabolomics, Leiden
University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands
| | - Gordan Lauc
- Genos,
Glycoscience Research Laboratory, Borongajska cesta 83H, 10 000 Zagreb, Croatia
- Faculty
of Pharmacy and Biochemistry, University
of Zagreb, A. Kovačića 1, 10 000 Zagreb, Croatia
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Multi-block data integration analysis for identifying and validating targeted N-glycans as biomarkers for type II diabetes mellitus. Sci Rep 2022; 12:10974. [PMID: 35768493 PMCID: PMC9243128 DOI: 10.1038/s41598-022-15172-z] [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: 01/03/2022] [Accepted: 04/28/2022] [Indexed: 11/08/2022] Open
Abstract
Plasma N-glycan profiles have been shown to be defective in type II diabetes Mellitus (T2DM) and holds a promise to discovering biomarkers. The study comprised 232 T2DM patients and 219 healthy individuals. N-glycans were analysed by high-performance liquid chromatography. The multivariate integrative framework, DIABLO was employed for the statistical analysis. N-glycan groups (GPs 34, 32, 26, 31, 36 and 30) were significantly expressed in T2DM in component 1 and GPs 38 and 20 were related to T2DM in component 2. Four clusters were observed based on the correlation of the expressive signatures of the 39 N-glycans across T2DM and controls. Cluster A, B, C and D had 16, 16, 4 and 3 N-glycans respectively, of which 11, 8, 1 and 1 were found to express differently between controls and T2DM in a univariate analysis \documentclass[12pt]{minimal}
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\begin{document}$$(p < 0.05)$$\end{document}(p<0.05). Multi-block analysis revealed that trigalactosylated (G3), triantennary (TRIA), high branching (HB) and trisialylated (S3) expressed significantly highly in T2DM than healthy controls. A bipartite relevance network revealed that HB, monogalactosylated (G1) and G3 were central in the network and observed more connections, highlighting their importance in discriminating between T2DM and healthy controls. Investigation of these N-glycans can enhance the understanding of T2DM.
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Anto EO, Frimpong J, Boadu WIO, Tamakloe VCKT, Hughes C, Acquah B, Acheampong E, Asamoah EA, Opoku S, Appiah M, Tawiah A, Annani-Akollor ME, Wiafe YA, Addai-Mensah O, Obirikorang C. Prevalence of Cardiometabolic Syndrome and its Association With Body Shape Index and A Body Roundness Index Among Type 2 Diabetes Mellitus Patients: A Hospital-Based Cross-Sectional Study in a Ghanaian Population. FRONTIERS IN CLINICAL DIABETES AND HEALTHCARE 2022; 2:807201. [PMID: 36994331 PMCID: PMC10012128 DOI: 10.3389/fcdhc.2021.807201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 12/22/2021] [Indexed: 11/13/2022]
Abstract
Cardiometabolic syndrome (MetS) is closely linked to type 2 diabetes mellitus (T2DM) and is the leading cause of diabetes complications. Anthropometric indices could be used as a cheap approach to identify MetS among T2DM patients. We determined the prevalence of MetS and its association with sociodemographic and anthropometric indices among T2DM patients in a tertiary hospital in the Ashanti region of Ghana. A comparative cross-sectional study was conducted among 241 T2DM outpatients attending the Komfo Anokye Teaching Hospital (KATH) and the Kumasi South Hospital for routine check-up. Sociodemographic characteristics, clinicobiochemical markers, namely, systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting blood glucose (FBG), and glycated hemoglobin (HbA1C) were measured. Anthropometric indices, namely, body mass index (BMI), Conicity index (CI), body adiposity index (BAI), A body shape index (ABSI), body roundness index (BRI), Waist-to-hip ratio (WHR), and Waist-to-height ratio (WHtR) were computed based on either the Height, Weight, Waist circumference (WC) or Hip circumference (HC) of the patients. Metabolic syndrome (MetS) was classified using the National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III) criteria. Data entry and analysis were done using Excel 2016 and SPSS version 25.0 respectively. Of the 241 T2DM patients, 99 (41.1%) were males whereas 144 (58.9%) were females. The prevalence of cardiometabolic syndrome (MetS) was 42.7% with dyslipidemia and hypertension recording a prevalence of 6.6 and 36.1%, respectively. Being a female T2DM patient [aOR = 3.02, 95%CI (1.59-5.76), p = 0.001] and divorced [aOR = 4.05, 95%CI (1.22-13.43), p = 0.022] were the independent sociodemographic predictors of MetS among T2DM patients. The 4th quartile for ABSI and 2nd to 4th quartiles for BSI were associated with MetS on univariate logistic regression (p <0.05). Multivariate logistic regression identified the 3rd quartile (aOR = 25.15 (2.02-313.81), p = 0.012) and 4th quartile (aOR = 39.00, 95%CI (2.68-568.49), p = 0.007) for BRI as the independent predictors of MetS among T2DM. The prevalence of cardiometabolic syndrome is high among T2DM patients and this was influenced by female gender, being divorced, and increased BRI. Integration of BRI as part of routine assessment could be used as early indicator of cardiometabolic syndrome among T2DM patients.
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Affiliation(s)
- Enoch Odame Anto
- Department of Medical Diagnostics, Faculty of Allied Health Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia
| | - Joseph Frimpong
- Department of Medical Diagnostics, Faculty of Allied Health Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Wina Ivy Ofori Boadu
- Department of Medical Diagnostics, Faculty of Allied Health Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | | | - Charity Hughes
- Department of Medical Diagnostics, Faculty of Allied Health Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Benjamin Acquah
- Department of Medical Diagnostics, Faculty of Allied Health Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Emmanuel Acheampong
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia
- Department of Molecular Medicine, School of Medicine and Dentistry, College of Health Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Evans Adu Asamoah
- Department of Molecular Medicine, School of Medicine and Dentistry, College of Health Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Stephen Opoku
- Department of Medical Diagnostics, Faculty of Allied Health Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Michael Appiah
- Department of Medical Laboratory Technology, Accra Technical University, Accra, Ghana
| | - Augustine Tawiah
- Department of Obstetrics and Gynaecology, Komfo Anokye Teaching Hospital, Kumasi, Ghana
| | - Max Efui Annani-Akollor
- Department of Molecular Medicine, School of Medicine and Dentistry, College of Health Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Yaw Amo Wiafe
- Department of Medical Diagnostics, Faculty of Allied Health Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Otchere Addai-Mensah
- Department of Medical Diagnostics, Faculty of Allied Health Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Christian Obirikorang
- Department of Molecular Medicine, School of Medicine and Dentistry, College of Health Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
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9
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Wang J, Du J, Ge X, Peng W, Guo X, Li W, Huang S. Circulating Ism1 Reduces the Risk of Type 2 Diabetes but not Diabetes-Associated NAFLD. Front Endocrinol (Lausanne) 2022; 13:890332. [PMID: 35712241 PMCID: PMC9195582 DOI: 10.3389/fendo.2022.890332] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Accepted: 04/27/2022] [Indexed: 11/13/2022] Open
Abstract
PURPOSE To examine the association of serum Ism1, a new adipokine that can regulate glucose uptake, with type 2 diabetes (T2D) in a Chinese population. Considering high prevalence of Nonalcoholic Fatty Liver Disease in patients with type 2 diabetes and the regulating role of Ism1 on glucose uptake of peripheral tissues, we further explored the association between Ism1 and diabetes-associated nonalcoholic fatty liver disease. METHODS A total of 120 newly diagnosed T2D patients and 60 control subjects with normal glucose were recruited in the case-control study. Serum Ism1 concentrations were determined by ELISA. Multivariate logistic regression analysis was used to evaluate the independent association of serum Ism1 concentration with the risk of T2D. The 120 newly diagnosed T2D patients were divided into uncomplicated T2D group and diabetes-associated NAFLD group according to the FLI score. RESULTS The Ism1 level of normoglycemic controls was higher than that of T2D patients (3.91 ± 0.24 ng/ml vs 3.01 ± 0.16 ng/ml, P=0.001). Based on quartile analysis of Ism1 level, the proportion of high circulating Ism1 levels in the control group increased while T2D group decreased, and the distribution difference was statistically significant (P=0.015). Logistic regression analysis indicated that the serum Ism1 level was an independent protective factor of type 2 diabetes (OR=0.69, 95%CI: 0.54-0.89). The decrease of Ism1 level did not increase the risk of non-alcoholic fatty liver disease in diabetic patients by Binary logistic regression analysis (OR=1.08, 95% CI: 0.69-1.69). CONCLUSIONS The increase of serum Ism1 was associated with a decreased risk of diabetes, and it did not reduce the risk of non-alcoholic fatty liver disease in diabetic patients.
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Affiliation(s)
| | | | | | | | - Xirong Guo
- *Correspondence: Xirong Guo, ; Wenyi Li, ; Shan Huang,
| | - Wenyi Li
- *Correspondence: Xirong Guo, ; Wenyi Li, ; Shan Huang,
| | - Shan Huang
- *Correspondence: Xirong Guo, ; Wenyi Li, ; Shan Huang,
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10
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Liu Q, Li X. The Interactions of Media Use, Obesity, and Suboptimal Health Status: A Nationwide Time-Trend Study in China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph182413214. [PMID: 34948822 PMCID: PMC8701945 DOI: 10.3390/ijerph182413214] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 12/13/2021] [Accepted: 12/13/2021] [Indexed: 12/19/2022]
Abstract
Obesity and suboptimal health status (SHS) have been global public health concerns in recent decades. A growing number of works have explored the relationships between media use and obesity, as well as SHS. This study aimed to examine the time trend of the associations between media use (including traditional media and new media) and obesity, as well as SHS. The data were derived from three national random samples of the Chinese General Social Survey (CGSS), which was separately conducted in 2013, 2015, and 2017. In total, 34,468 respondents were included in this study, consisting of 16,624 males and 17,844 females, and the average age was 49.95 years old (SD = 16.72). It found that broadcast use and television use were positively associated with obesity and showed an increasing trend over time. Cellphone use emerged as a risk factor for obesity in 2017 and showed an increasing trend. By contrast, newspaper use, television use, and internet use were negatively associated with SHS, and television use showed a decreasing trend in the association with SHS, while internet and newspaper use showed an increasing trend. In conclusion, media use was positively associated with obesity while negatively associated with SHS. It showed a decreasing trend in the associations between traditional media use and obesity, while revealing an increasing trend in the associations between new media use and obesity, as well as SHS. The practical implications of the findings are discussed.
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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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12
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Russell A, Wang W. The Rapidly Expanding Nexus of Immunoglobulin G N-Glycomics, Suboptimal Health Status, and Precision Medicine. EXPERIENTIA. SUPPLEMENTUM 2021; 112:545-564. [PMID: 34687022 DOI: 10.1007/978-3-030-76912-3_17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/14/2023]
Abstract
Immunoglobulin G is a prevalent glycoprotein, whose downstream immune responses are partially mediated by the N-glycans within the fragment crystallisable domain. Collectively termed the N-glycome, it is considered a complex intermediate phenotype: an amalgamation of genetic predisposition, environmental exposure, and health behaviours over the life-course. Thus, the immunoglobulin G N-glycome may provide an indication of health status on the spectrum from health to disease and infirmary. Although variability exists within and between populations, composition of the immunoglobulin G N-glycome remains stable over short periods of time. This underscores the potential of harnessing the immunoglobulin G N-glycome as an ideal tool for preclinical disease risk prediction, stratification, and prognosis through the development of precise dynamic biomarkers.
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Affiliation(s)
- Alyce Russell
- Centre for Precision Health, Edith Cowan University, Joondalup, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
| | - Wei Wang
- Centre for Precision Health, Edith Cowan University, Joondalup, Australia.
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia.
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13
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Adua E, Afrifa-Yamoah E, Frimpong K, Adama E, Karthigesu SP, Anto EO, Aboagye E, Yan Y, Wang Y, Tan X, Wang W. Construct validity of the Suboptimal Health Status Questionnaire-25 in a Ghanaian population. Health Qual Life Outcomes 2021; 19:180. [PMID: 34281537 PMCID: PMC8287694 DOI: 10.1186/s12955-021-01810-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 06/24/2021] [Indexed: 12/13/2022] Open
Abstract
Background The Suboptimal Health Status Questionnaire-25 (SHS-Q-25) developed to measure Suboptimal Health Status has been used worldwide, but its construct validity has only been tested in the Chinese population. Applying Structural Equation Modelling, we investigate aspects of the construct validity of the SHS-Q-25 to determine the interactions between SHS subscales in a Ghanaian population.
Methods The study involved healthy Ghanaian participants (n = 263; aged 20–80 years; 63% female), who responded to the SHSQ-25. In an exploratory factor and parallel analysis, the study extracted a new domain structure and compared to the established five-domain structure of SHSQ-25. A confirmatory factor analysis (CFA) was conducted and the fit of the model further discussed. Invariance analysis was carried out to establish the consistency of the instrument across multi-groups.
Results The extracted domains were reliable with Cronbach’s \documentclass[12pt]{minimal}
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\begin{document}$$\alpha$$\end{document}α of 0.846, 0.820 and 0.864 respectively, for fatigue, immune-cardiovascular and cognitive. The CFA revealed that the model fit indices were excellent \documentclass[12pt]{minimal}
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\begin{document}$$\left( {{\text{RMSEA}} = 0.049~ < ~0.08,\,{\text{CFI}} = 0.903 > 0.9,\,{\text{GFI}} = 0.880 < 0.9,\,{\text{TLI}} = 0.907 > 0.9} \right)$$\end{document}RMSEA=0.049<0.08,CFI=0.903>0.9,GFI=0.880<0.9,TLI=0.907>0.9. The fit indices for the three-domain model were statistically superior to the five-domain model. There were, however, issues of insufficient discriminant validity as some average variance extracts were smaller than the corresponding maximum shared variance. The three-domain model was invariant for all constrained aspects of the structural model across age, which is an important risk factor for most chronic diseases.
Conclusion The validity tests suggest that the SHS-Q25 can measure SHS in a Ghanaian population. It can be recommended as a screening tool to early detect chronic diseases especially in developing countries where access to facilities is diminished.
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Affiliation(s)
- Eric Adua
- Center for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, WA, Australia.,Shantou University of Medical College, Shantou, China.,Department of Biochemistry, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Ebenezer Afrifa-Yamoah
- School of Science, Edith Cowan University, 270 Joondalup Drive, Joondalup, WA, Australia
| | - Kwasi Frimpong
- School of Science, Edith Cowan University, 270 Joondalup Drive, Joondalup, WA, Australia.,Ghana Institute of Management and Public Administration, Accra, Ghana
| | - Esther Adama
- School of Nursing and Midwifery, Edith Cowan University, 270 Joondalup Drive, Joondalup, WA, Australia
| | - Shantha P Karthigesu
- Center for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, WA, Australia
| | - Enoch Odame Anto
- Center for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, WA, Australia.,Department of Medical Diagnostics, Faculty of Allied Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Emmanuel Aboagye
- Institute of Environmental Medicine, Karolinska Institute, Nobels Väg 13, 17177, Stockholm, Sweden
| | - Yuxiang Yan
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, 100069, China
| | - Youxin Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, 100069, China
| | - Xuerui Tan
- Shantou University of Medical College, Shantou, China
| | - Wei Wang
- Center for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, WA, Australia. .,Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, 100069, China.
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14
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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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15
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Wang H, Tian Q, Zhang J, Liu H, Zhang J, Cao W, Zhang X, Li X, Wu L, Song M, Kong Y, Wang W, Wang Y. Blood transcriptome profiling as potential biomarkers of suboptimal health status: potential utility of novel biomarkers for predictive, preventive, and personalized medicine strategy. EPMA J 2021; 12:103-115. [PMID: 34194583 DOI: 10.1007/s13167-021-00238-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Accepted: 03/01/2021] [Indexed: 02/06/2023]
Abstract
The early identification of Suboptimal Health Status (SHS) creates a window opportunity for the predictive, preventive, and personalized medicine (PPPM) in chronic diseases. Previous studies have observed the alterations in several mRNA levels in SHS individuals. As a promising "omics" technology offering comprehension of genome structure and function at RNA level, transcriptome profiling can provide innovative molecular biomarkers for the predictive identification and targeted prevention of SHS. To explore the potential biomarkers, biological functions, and signalling pathways involved in SHS, an RNA sequencing (RNA-Seq)-based transcriptome analysis was firstly conducted on buffy coat samples collected from 30 participants with SHS and 30 age- and sex-matched healthy controls. Transcriptome analysis identified a total of 46 differentially expressed genes (DEGs), in which 22 transcripts were significantly increased and 24 transcripts were decreased in the SHS group. A total of 23 transcripts were selected as candidate predictive biomarkers for SHS. Gene Ontology (GO) annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that several biological processes were related to SHS, such as ATP-binding cassette (ABC) transporter and neurodegeneration. Protein-protein interaction (PPI) network analysis identified 10 hub genes related to SHS, including GJA1, TWIST2, KRT1, TUBB3, AMHR2, BMP10, MT3, BMPER, NTM, and TMEM98. A transcriptome predictive model can distinguish SHS individuals from the healthy controls with a sensitivity of 83.3% (95% confidence interval (CI): 73.9-92.7%), a specificity of 90.0% (95% CI: 82.4-97.6%), and an area under the receiver operating characteristic curve of 0.938 (95% CI: 0.882-0.994). In the present study, we demonstrated that blood (buffy coat) samples appear to be a very promising and easily accessible biological material for the transcriptomic analyses focused on the objective identification of SHS by using our transcriptome predictive model. The pattern of particularly determined DEGs can be used as predictive transcriptomic biomarkers for the identification of SHS in an individual who may, subjectively, feel healthy, but at the level of subcellular mechanisms, the changes can provide early information about potential health problems in this person. Our findings also indicate the potential therapeutic targets in dealing with chronic diseases related to SHS, such as T2DM and CVD, and an early onset of neurodegenerative diseases, such as Alzheimer's and Parkinson's diseases, as well as the findings suggest the targets for personalized interventions as promoted in PPPM. Supplementary Information The online version contains supplementary material available at 10.1007/s13167-021-00238-1.
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Affiliation(s)
- Hao Wang
- Department of Clinical Epidemiology and Evidence-Based Medicine, National Clinical Research Center for Digestive Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.,Center for Precision Health, School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
| | - Qiuyue Tian
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Jie Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Hongqi Liu
- Student Healthcare Center, Weifang University, Weifang, China
| | - Jinxia Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Weijie Cao
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.,Center for Precision Health, School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
| | - Xiaoyu Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.,Department of Anesthesiology, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Xingang Li
- Center for Precision Health, School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
| | - Lijuan Wu
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Manshu Song
- Center for Precision Health, School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
| | - Yuanyuan Kong
- Department of Clinical Epidemiology and Evidence-Based Medicine, National Clinical Research Center for Digestive Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Wei Wang
- Center for Precision Health, School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
| | - Youxin Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
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16
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Wang X, Zhong Z, Balmer L, Wang W. Glycosylation Profiling as a Biomarker of Suboptimal Health Status for Chronic Disease Stratification. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1325:321-339. [PMID: 34495543 DOI: 10.1007/978-3-030-70115-4_16] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
WHO defines health as "a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity." We coined and defined suboptimal health status (SHS) as a subclinical, reversible stage of the pre-chronic disease. SHS is a physical state between health and disease, characterized by health complaints, general weakness, chronic fatigue, and low energy levels. We have developed an instrument to measure SHS, Suboptimal Health Status Questionnaire-25 (SHSQ-25), a self-reported survey assessing five health components that has been validated in various ethnical populations. Our studies suggest that SHS is associated with the major components of cardiovascular health and the early onset of metabolic diseases. Besides subjective measure of health (SHS), glycans are conceived as objective biomarkers of SHS. Glycans are complex and branching carbohydrate moieties attached to proteins, participating in inflammatory regulation and chronic disease pathogenesis. We have been investigating the role of glycans and SHS in multiple cardiometabolic diseases in different ethnical populations (African, Chinese, and Caucasian). Here we present case studies to prove that a combination of subjective health measure (SHS) with objective health measure (glycans) represents a window of opportunity to halt or reverse the progression of chronic diseases.
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Affiliation(s)
- Xueqing Wang
- School of Health and Medical Sciences, Edith Cowan University, Perth, Australia
- College of Basic Medical Sciences, Harbin Medical University, Harbin, China
| | - Zhaohua Zhong
- College of Basic Medical Sciences, Harbin Medical University, Harbin, China
| | - Lois Balmer
- School of Health and Medical Sciences, Edith Cowan University, Perth, Australia
| | - Wei Wang
- School of Health and Medical Sciences, Edith Cowan University, Perth, Australia.
- Centre for Precision Health, ECU Strategic Research Centre, Edith Cowan University, Perth, Australia.
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China.
- School of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Taian, China.
- First Affiliated Hospital, Shantou University Medical College, Shantou, China.
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17
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Xue Y, Huang Z, Liu G, Feng Y, Xu M, Jiang L, Xu J. Association analysis of Suboptimal health Status: a cross-sectional study in China. PeerJ 2020; 8:e10508. [PMID: 33365207 PMCID: PMC7735074 DOI: 10.7717/peerj.10508] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 11/16/2020] [Indexed: 12/15/2022] Open
Abstract
Background Suboptimal health status (SHS) among urban residents is commonplace in China. However, factors influencing SHS have not been thoroughly explored, especially with regard to the effects of internal factors (e.g., personality and health awareness) on SHS. Methods A cross-sectional study was conducted with a nationally representative sample of 5460 Chinese urban residents..SHS was measured using the Suboptimal Health Mesurement Scale Version 1.0. Demographic information, and information pertaining to lifestyle behaviors, environmental factors, and internal factors were abtained through a questionnaire. The associations between demographic information, lifestyle behaviors, environmental factors, internal factors and SHS were assessed using logistic regression. Results Of the 5460 participants (with a mean age of 41.56 ± 16.14 years), 2640 (48.4 %) were men. Out of 36 variables, 23 were significantly associated with SHS: age (odds ratio [OR]: 1.014), an education level of high school/junior college (OR: 1.443) , marital status (OR: 1.899), area of registered permanent residence (OR: 0.767), monthly household income (p < 0.001) , exposure to second-hand smoke (p = 0.001), alcohol drinking (OR: 1.284), bad eating habits (OR: 1.717), not sleeping before 11 p.m. every day (p = 0.002), spending time online more than five hours a day (OR: 1.526), having a good relationship with parents during one’s growth period (OR: 0.602), living with good quality air (OR:0.817), living in not crowded conditions (OR:0.636), having a harmonious neighborhood (OR:0.775), having adequate fitness facilities (OR:0.783), one’s health being affected by two-child policy (OR: 1.468) and medical policies (OR: 1.265) , high adverse quotient (OR: 0.488), many (≥3 kinds) interests and hobbies (OR: 0.617), mature and steady personality traits (OR: 0.469) , a high attention to one’s health (OR: 0.833), and effective health promotion induced by leading a leisurely lifestyle (OR: 0.466) were significantly associated with SHS. Conclusions All these variables were included demographic information, lifestyle behaviors, environmental factors and internal factors. Our study supports the benefits of controlling both internal and external factors in preventing suboptimal health.
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Affiliation(s)
- Yunlian Xue
- Department of Sanitation Economy Administration, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, China.,Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Guangzhou, Guangdong Province, China.,School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Zhuomin Huang
- Department of Sanitation Economy Administration, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, China.,School of Health Services Management, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Guihao Liu
- Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Guangzhou, Guangdong Province, China
| | - Yefang Feng
- Department of Sanitation Economy Administration, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, China.,School of Health Services Management, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Mengyao Xu
- Department of Sanitation Economy Administration, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, China.,School of Health Services Management, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Lijie Jiang
- Department of Sanitation Economy Administration, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, China.,School of Health Services Management, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Jun Xu
- Department of Sanitation Economy Administration, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, China
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18
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Zhu J, Ying W, Zhang L, Peng G, Chen W, Anto EO, Wang X, Lu N, Gao S, Wu G, Yan J, Ye J, Wu S, Yu C, Yue M, Huang X, Xu N, Ying P, Chen Y, Tan X, Wang W. Psychological symptoms in Chinese nurses may be associated with predisposition to chronic disease: a cross-sectional study of suboptimal health status. EPMA J 2020; 11:551-563. [PMID: 33078069 PMCID: PMC7556591 DOI: 10.1007/s13167-020-00225-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 09/28/2020] [Indexed: 02/05/2023]
Abstract
BACKGROUND Suboptimal health status (SHS) is a reversible state between ideal health and illness and it can be effectively reversed by risk prediction, disease prevention, and personalized medicine under the global background of predictive, preventive, and personalized medicine (PPPM) concepts. More and more Chinese nurses have been troubled by psychological symptoms (PS). The correlation between PS and SHS is unclear in nurses. The purpose of current study is to investigate the prevalence of SHS and PS in Chinese nurses and the relationship between SHS and PS along with predisposing factors as well as to discuss the feasibility of improving health status and preventing diseases according to PPPM concepts in Chinese nurses. METHODS A cross-sectional study was conducted with the cluster sampling method among 9793 registered nurses in Foshan city, China. SHS was evaluated with the Suboptimal Health Status Questionnaire-25 (SHSQ-25). Meanwhile, the PS of depression and anxiety were evaluated with Self-Rating Depression Scale (SDS) and Self-Rating Anxiety Scale (SAS) self-assessment questionnaires. The relationship between PS and SHS in Chinese nurses was subsequently analyzed. RESULTS Among the 9793 participants, 6107 nurses were included in the final analysis. The prevalence of SHS in the participants was 74.21% (4532/6107) while the symptoms of depression and anxiety were 47.62% (2908/6107) and 24.59% (1502/6107) respectively. The prevalence of SHS in the participants with depression and anxiety was significantly higher than those without the symptoms of depression (83.3% vs 16.7%, P < 0.001) and anxiety (94.2% vs 5.8%, P < 0.0001). The ratio of exercise habit was significantly lower than that of non-exercise habit (68.8% vs 78.4%, P < 0.001) in SHS group. CONCLUSIONS There is a high prevalence of SHS and PS in Chinese nurses. PS in Chinese nurses are associated with SHS. Physical exercise is a protective factor for SHS and PS so that the exercise should be strongly recommended as a valuable preventive measure well in the agreement with PPPM philosophy. Along with SDS and SAS, SHSQ-25 should also be highly recommended and applied as a novel predictive/preventive tool for the health measures from the perspectives of PPPM in view of susceptible population and individual screening, the predisposition to chronic disease preventing, personalization of intervention, and the ideal health state restoring.
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Affiliation(s)
- Jinxiu Zhu
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041 Guangdong China
- Institute of Clinical Electrocardiography, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041 Guangdong China
| | - Wenjuan Ying
- Nursing Research Institute, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041 Guangdong China
| | - Li Zhang
- Nursing Department, Foshan First People’s Hospital, Foshan, 528000 Guangdong China
| | - Gangyi Peng
- Division of Medical Administration, Health commission of Guangdong Province, Guangzhou, 510060 China
| | - Weiju Chen
- Nursing Department, The First Affiliated Hospital, Ji’nan University, Guangzhou, 510630 China
| | - Enoch Odame Anto
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA 6027 Australia
| | - Xueqing Wang
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA 6027 Australia
| | - Nan Lu
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041 Guangdong China
| | - Shanshan Gao
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041 Guangdong China
| | - Guihai Wu
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041 Guangdong China
| | - Jingyi Yan
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041 Guangdong China
| | - Jianfeng Ye
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041 Guangdong China
| | - Shenglin Wu
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041 Guangdong China
| | - Chengzhi Yu
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041 Guangdong China
| | - Minghui Yue
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041 Guangdong China
| | - Xiru Huang
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041 Guangdong China
| | - Nuo Xu
- Nursing Research Institute, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041 Guangdong China
| | - Pengxiang Ying
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041 Guangdong China
| | - Yanhong Chen
- Nursing Research Institute, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041 Guangdong China
| | - Xuerui Tan
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041 Guangdong China
- Clinical Research Center, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041 Guangdong China
| | - Wei Wang
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041 Guangdong China
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA 6027 Australia
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19
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Xue Y, Liu G, Feng Y, Xu M, Jiang L, Lin Y, Xu J. Mediating effect of health consciousness in the relationship of lifestyle and suboptimal health status: a cross-sectional study involving Chinese urban residents. BMJ Open 2020; 10:e039701. [PMID: 33109672 PMCID: PMC7592276 DOI: 10.1136/bmjopen-2020-039701] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Revised: 10/03/2020] [Accepted: 10/06/2020] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVE Suboptimal health status (SHS), a third state between good health and disease, can easily develop into chronic diseases, and can be influenced by lifestyle and health consciousness. No study has surveyed the intermediation of health consciousness on the relationship between lifestyle and SHS. This study aimed to analyse the association of lifestyle and SHS, and intermediation of health consciousness in Chinese urban residents. DESIGN A cross-sectional face-to-face survey using a four-stage stratified sampling method. PARTICIPANTS We investigated 5803 Chinese urban residents aged 18 years and over. We measured SHS using the Sub-Health Measurement Scale V1.0. We adopted a structural equation model to analyse relationships among lifestyle, health consciousness and SHS. We applied a bootstrapping method to estimate the mediation effect of health consciousness. RESULTS Lifestyle had stronger indirect associations with physical (β -0.185, 95% CI -0.228 to -0.149), mental (β -0.224, 95% CI -0.265 to -0.186) and social SHS (β -0.216, 95% CI -0.257 to -0.179) via health consciousness than direct associations of physical (β -0.144, 95% CI -0.209 to -0.081), mental (β -0.146, 95% CI -0.201 to -0.094) and social SHS (β -0.130, 95% CI -0.181 to -0.077). Health consciousness has a strong direct association with physical (β 0.360, 95% CI 0.295 to 0.427), mental (β 0.452, 95% CI 0.392 to 0.510) and social SHS (β 0.434, 95% CI 0.376 to 0.490). Ratio of mediating effect of health consciousness to direct effect of lifestyle with physical, mental and social SHS was 1.28, 1.53 and 1.66, respectively. CONCLUSIONS Health consciousness was more important in preventing physical, mental and social SHS than lifestyle. Therefore, it might be useful in changing unhealthy lifestyle and reducing the influence of poor lifestyle on physical, mental and social SHS.
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Affiliation(s)
- Yunlian Xue
- Department of Sanitation Economy Administration, Nanfang Hospital, Southern Medical University, Guangzhou, China
- Guangdong Provincial People's Hospital,Guangdong Academy of Medical Sciences, Guangzhou, China
- School of Public Health, Southern Medical University, Guangzhou, China
| | - Guihao Liu
- Guangdong Provincial People's Hospital,Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yefang Feng
- Department of Sanitation Economy Administration, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Mengyao Xu
- Department of Sanitation Economy Administration, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Lijie Jiang
- Department of Sanitation Economy Administration, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yuanqi Lin
- Department of Sanitation Economy Administration, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jun Xu
- Department of Sanitation Economy Administration, Nanfang Hospital, Southern Medical University, Guangzhou, China
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20
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Ding G, Zhao X, Wang Y, Song D, Chen D, Deng Y, Xing W, Dong H, Zhou Y, Li D, Hou H. Evaluation of the relationship between cognitive impairment and suboptimal health status in a northern Chinese population: a cross-sectional study. J Glob Health 2020; 10:010804. [PMID: 32257168 PMCID: PMC7101211 DOI: 10.7189/jogh.10.010804] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Background Suboptimal health status (SHS) is an intermediate health status between ideal health and illness. As a determinant of cardiovascular disease and stroke, SHS is hypothesized to be associated with the development of cognitive impairment and dementia. This study aimed to investigate whether individuals with SHS have poor cognitive ability based on a community-based cohort in northern Chinese population. Methods 3524 participants who were enrolled in Jidong cohort 2015 in Tangshan City were investigated in this study. Cognitive function was measured with the Mini-Mental State Examination (MMSE). SHS level was evaluated using a self-reporting Suboptimal Health Status Questionnaire-25 (SHSQ-25). The relationship between SHS and cognitive function was analyzed with logistic regression analysis, by which odds ratio (OR) and 95% confidence interval (CI) were calculated. Results The prevalence of cognitive impairment was 3.4% (121/3524) in our study, with the prevalence rates of 1.9% (34/1750) among men and 4.9% (87/1774) in women. The medians of total score of MMSE were 28 (interquartile range (IQR) = 27-29) in the SHS group, and 29 (IQR = 27-30) in the ideal health group. Logistic regression analysis showed that SHS was significantly correlated with cognitive impairment (adjusted OR = 2.936, 95% CI = 1.428-6.033). With regard to gender, the OR was 5.067 (95% CI = 1.346-19.068) in men, which was higher than that in women (OR = 2.324, 95% CI = 1.130-4.779). Conclusions SHS might be a risk factor for cognitive function in northern Chinese population. Early screening of SHS individuals, as well as urgent treatment of SHS might contribute to the prevention of cognitive impairment.
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Affiliation(s)
- Guoyong Ding
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong Province, China.,Equal authorship
| | - Xuan Zhao
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong Province, China.,Equal authorship
| | - Youxin Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.,Equal authorship
| | - Daiyu Song
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong Province, China
| | - Dongzhen Chen
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong Province, China
| | - Yang Deng
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong Province, China
| | - Weijia Xing
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong Province, China
| | - Hualei Dong
- Taishan Hospital of Shandong Province, Taian, Shandong Province, China
| | - Yong Zhou
- Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang Province, China
| | - Dong Li
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong Province, China
| | - Haifeng Hou
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong Province, China
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21
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Wang H, Tian Q, Zhang J, Liu H, Zhang X, Cao W, Zhang J, Anto EO, Li X, Wang X, Liu D, Zheng Y, Guo Z, Wu L, Song M, Wang Y, Wang W. Population-based case-control study revealed metabolomic biomarkers of suboptimal health status in Chinese population-potential utility for innovative approach by predictive, preventive, and personalized medicine. EPMA J 2020; 11:147-160. [PMID: 32549914 DOI: 10.1007/s13167-020-00200-7] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Accepted: 03/06/2020] [Indexed: 12/18/2022]
Abstract
Background Suboptimal health status (SHS) is a subclinical stage of chronic diseases, and the identification of SHS provides an opportunity for the predictive, preventive, and personalized medicine (PPPM) of chronic diseases. Previous studies have reported the associations between metabolic signatures and early signs of chronic diseases. Methods This study aimed to detect the metabolic biomarkers for the identification of SHS in a case-control study. SHS questionnaire-25 (SHSQ-25) was used in a population-based health survey to measure the SHS levels of participants. The liquid chromatography-mass spectrometry-based untargeted metabolomics analysis was conducted on plasma samples collected from 50 SHS participants and 50 age- and sex-matched healthy controls. Results After adjusting for the confounders, 24 significantly differential metabolites, such as sphingomyelin, sphingosine, sphinganine, progesterone, pregnanolone, and bilirubin, were identified as the candidate biomarkers for SHS. Pathway analysis revealed that sphingolipid metabolism, taurine metabolism, and steroid hormone biosynthesis are the disturbed metabolic pathways related to SHS. A combination of four metabolic biomarkers (sphingosine, pregnanolone, taurolithocholate sulfate, cervonyl carnitine) can distinguish SHS individuals from the controls with a sensitivity of 94.0%, a specificity of 90.0%, and an area under the receiver operating characteristic curve of 0.977. Conclusion Plasma metabolites are valuable biomarkers for SHS identification, and meanwhile, SHSQ-25 can be used as an alternative health screening tool in the population-based health survey. SHS-related metabolic disturbances could be detected at the early onset of SHS, and SHS-related metabolites could create a window opportunity for PPPM of chronic diseases.
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Affiliation(s)
- Hao Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA Australia
| | - Qiuyue Tian
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Jie Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Hongqi Liu
- Student Health Center, Weifang University, Weifang, China
| | - Xiaoyu Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Weijie Cao
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Jinxia Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Enoch Odame Anto
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA Australia
| | - Xingang Li
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA Australia
| | - Xueqing Wang
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA Australia
| | - Di Liu
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Yulu Zheng
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA Australia
| | - Zheng Guo
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA Australia
| | - Lijuan Wu
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Manshu Song
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA Australia
| | - Youxin Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Wei Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA Australia
- School of Public Health, Shandong First Medical University, Taian, China
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22
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Anto EO, Owiredu WKBA, Adua E, Obirikorang C, Fondjo LA, Annani-Akollor ME, Acheampong E, Asamoah EA, Roberts P, Wang W, Donkor S. Prevalence and lifestyle-related risk factors of obesity and unrecognized hypertension among bus drivers in Ghana. Heliyon 2020; 6:e03147. [PMID: 32042945 PMCID: PMC7002790 DOI: 10.1016/j.heliyon.2019.e03147] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Revised: 09/11/2019] [Accepted: 12/30/2019] [Indexed: 12/13/2022] Open
Abstract
Obesity and hypertension are public health problems associated with cardiovascular events worldwide. Bus drivers, whose lifestyle is primarily sedentary and characterized by poor eating habits are at increased risk. This study determined the prevalence and lifestyle-related risk factors of obesity and hypertension among Inter-Regional Metromass Bus Drivers (IRMBDs) in Ghana. This cross-sectional study recruited 527 professional drivers from Metromass Bus stations in Accra and Kumasi Metropolis, Ghana. Structured questionnaires were administered to obtain socio-demographic and lifestyle characteristics from all participants. Anthropometric measurements including body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) and blood pressure (BP) were determined. The prevalence of unrecognized hypertension was 38.7%. The prevalence of obesity using BMI, WC, and WHR as obesity indices were 19.0%, 19.9%, and 19.4%, respectively. Use of sleep inhibitors, long-duration sitting and eating late at night were independent risk factors for obesity, regardless of the obesity index used (p < 0.05). Physical inactivity, high caloric intake and eating at stressful periods were independent risk factors for obesity based on WC and WHR measurements (p < 0.05). Ageing, smoking history, alcoholic beverage intake, sleep inhibitor drug use, high calorie intake, long-duration sitting, eating late and under stressful conditions were independent risk factors for hypertension (p < 0.05). There is a high prevalence of unrecognized hypertension and obesity among IRMBDs which were associated with individual lifestyle and behaviours. Increased awareness through educational and screening programs will trigger lifestyle modifications that will reduce cardio-metabolic disease onset and offer clues for better disease predictive, preventive and personalized medicine.
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Affiliation(s)
- Enoch Odame Anto
- Department of Molecular Medicine, School of Medicine and Dentistry, College of Health Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.,School of Medical and Health Sciences, Edith Cowan University, 270 Joondalup Drive, Perth, WA, 6027, Australia
| | - W K B A Owiredu
- Department of Molecular Medicine, School of Medicine and Dentistry, College of Health Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Eric Adua
- School of Medical and Health Sciences, Edith Cowan University, 270 Joondalup Drive, Perth, WA, 6027, Australia
| | - Christian Obirikorang
- Department of Molecular Medicine, School of Medicine and Dentistry, College of Health Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Linda Ahenkorah Fondjo
- Department of Molecular Medicine, School of Medicine and Dentistry, College of Health Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Max Efui Annani-Akollor
- Department of Molecular Medicine, School of Medicine and Dentistry, College of Health Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Emmanuel Acheampong
- Department of Molecular Medicine, School of Medicine and Dentistry, College of Health Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.,School of Medical and Health Sciences, Edith Cowan University, 270 Joondalup Drive, Perth, WA, 6027, Australia
| | - Evans Adu Asamoah
- Department of Molecular Medicine, School of Medicine and Dentistry, College of Health Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Peter Roberts
- Department of Molecular Medicine, School of Medicine and Dentistry, College of Health Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Wei Wang
- School of Medical and Health Sciences, Edith Cowan University, 270 Joondalup Drive, Perth, WA, 6027, Australia.,School of Public Health, Taishan Medical University, Taian, Shandong, 271000, China
| | - Sampson Donkor
- Department of Molecular Medicine, School of Medicine and Dentistry, College of Health Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
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23
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Sun Q, Xu X, Zhang J, Sun M, Tian Q, Li Q, Cao W, Zhang X, Wang H, Liu J, Zhang J, Meng X, Wu L, Song M, Liu H, Wang W, Wang Y. Association of suboptimal health status with intestinal microbiota in Chinese youths. J Cell Mol Med 2020; 24:1837-1847. [PMID: 31808612 PMCID: PMC6991644 DOI: 10.1111/jcmm.14880] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 10/21/2019] [Accepted: 11/11/2019] [Indexed: 02/06/2023] Open
Abstract
Suboptimal health status (SHS), a physical state between health and disease, is a subclinical and reversible stage of chronic disease. Previous studies have shown alterations in the intestinal microbiota in patients with some chronic diseases. This study aimed to investigate the association between SHS and intestinal microbiota in a case-control study with 50 SHS individuals and 50 matched healthy controls. Intestinal microbiota was analysed by MiSeq 250PE. Alpha diversity of intestinal microbiota in SHS individuals was higher compared with that of healthy controls (Simpson index, W = 2238, P = .048). Beta diversity was different between SHS and healthy controls (P = .018). At the phylum level, the relative abundance of Verrucomicrobia was higher in the SHS group than that in the controls (W = 2201, P = .049). Compared with that of the control group, nine genera were significantly higher and five genera were lower in abundance in the SHS group (all P < .05). The intestinal microbiota, analysed by a random forest model, was able to distinguish individuals with SHS from the controls, with an area under the curve of 0.79 (95% confidence interval: 0.77-0.81). We demonstrated that the alteration of intestinal microbiota occurs with SHS, an early stage of disease, which might shed light on the importance of intestinal microbiota in the primary prevention of noncommunicable chronic diseases.
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Affiliation(s)
- Qi Sun
- Beijing Key Laboratory of Clinical EpidemiologySchool of Public HealthCapital Medical UniversityBeijingChina
- National Research Institute for Family PlanningBeijingChina
- Graduate School of Peking Union Medical CollegeBeijingChina
| | - Xizhu Xu
- School of Public HealthShandong First Medical University & Shandong Academy of Medical SciencesTaianChina
| | - Jie Zhang
- Beijing Key Laboratory of Clinical EpidemiologySchool of Public HealthCapital Medical UniversityBeijingChina
| | - Ming Sun
- Beijing Key Laboratory of Clinical EpidemiologySchool of Public HealthCapital Medical UniversityBeijingChina
| | - Qiuyue Tian
- Beijing Key Laboratory of Clinical EpidemiologySchool of Public HealthCapital Medical UniversityBeijingChina
| | - Qihuan Li
- Beijing Key Laboratory of Clinical EpidemiologySchool of Public HealthCapital Medical UniversityBeijingChina
| | - Weijie Cao
- Beijing Key Laboratory of Clinical EpidemiologySchool of Public HealthCapital Medical UniversityBeijingChina
| | - Xiaoyu Zhang
- Beijing Key Laboratory of Clinical EpidemiologySchool of Public HealthCapital Medical UniversityBeijingChina
| | - Hao Wang
- Beijing Key Laboratory of Clinical EpidemiologySchool of Public HealthCapital Medical UniversityBeijingChina
| | - Jiaonan Liu
- Beijing Key Laboratory of Clinical EpidemiologySchool of Public HealthCapital Medical UniversityBeijingChina
| | - Jinxia Zhang
- Beijing Key Laboratory of Clinical EpidemiologySchool of Public HealthCapital Medical UniversityBeijingChina
| | - Xiaoni Meng
- Beijing Key Laboratory of Clinical EpidemiologySchool of Public HealthCapital Medical UniversityBeijingChina
| | - Lijuan Wu
- Beijing Key Laboratory of Clinical EpidemiologySchool of Public HealthCapital Medical UniversityBeijingChina
| | - Manshu Song
- Beijing Key Laboratory of Clinical EpidemiologySchool of Public HealthCapital Medical UniversityBeijingChina
| | - Hongqi Liu
- University HospitalWeifang UniversityWeifangChina
| | - Wei Wang
- Beijing Key Laboratory of Clinical EpidemiologySchool of Public HealthCapital Medical UniversityBeijingChina
- School of Public HealthShandong First Medical University & Shandong Academy of Medical SciencesTaianChina
- School of Medical and Health SciencesEdith Cowan UniversityPerthWAAustralia
| | - Youxin Wang
- Beijing Key Laboratory of Clinical EpidemiologySchool of Public HealthCapital Medical UniversityBeijingChina
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Anto EO, Roberts P, Coall DA, Adua E, Turpin CA, Tawiah A, Wang Y, Wang W. Suboptimal health pregnant women are associated with increased oxidative stress and unbalanced pro- and antiangiogenic growth mediators: a cross-sectional study in a Ghanaian population. Free Radic Res 2019; 54:27-42. [PMID: 31814473 DOI: 10.1080/10715762.2019.1685668] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Optimal oxidative stress (OS) is important throughout pregnancy; however, an increased OS may alter placental angiogenesis culminating in an imbalanced of angiogenic growth mediators (AGMs). Suboptimal Health Status (SHS), a physical state between health and disease, may be associated with increased OS and unbalanced AGMs. In this study, we explored the association between SHS, biomarkers of OS (BOS) and AGMs among normotensive pregnant women (NTN-PW) in a Ghanaian Suboptimal Health Cohort Study (GHOACS). This comparative GHOACS recruited 593 NTN-PW from the Komfo Anokye Teaching Hospital, Ghana. SHS was measured using a Suboptimal Health Status Questionnaire-25 (SHSQ-25). Along with the subjective SHS measure, objective BOS: 8-hydroxy-2-deoxyguanosine (8-OHdG), 8-epiprostaglandinF2 alpha (8-epi-PGF2α), total antioxidant capacity (TAC), and AGMs: vascular endothelial growth factor-A (VEGF-A), soluble fms-like tyrosine kinase receptor 1 (sFlt-1), placental growth factor (PIGF) and soluble endoglin (sEng) were evaluated. Compared to optimal health NTN-PW, levels of PlGF, VEGF-A and TAC were significantly (p < 0.05) reduced and negatively associated with SHS whilst sEng, sFlt-1, 8-epiPGF2α, 8-OHdG, and combined ratios of sFlt-1/PlGF, 8-epiPGF2α/PlGF, 8-OHdG/PlGF, and sEng/PlGF were significantly increased and positively associated with SHS. The first quartile for PIGF (2.79-fold) and VEGF-A (5.35-fold), and the fourth quartile for sEng (4.31-fold), sFlt-1 (1.84-fold), 8-epiPGF2α (2.23-fold), 8-OHdG (1.90-fold) and urinary 8-OHdG (1.95-fold) were independently associated with SHS (p < 0.05). SHS is associated with increased OS and unbalanced AGMs. Early identification of SHS-related OS and unbalanced AGMs may inform clinicians of the need for therapeutic options.
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Affiliation(s)
- Enoch Odame Anto
- School of Medical and Health Sciences, Edith Cowan University, Perth, Australia.,Department of Molecular Medicine, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Peter Roberts
- School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
| | - David Antony Coall
- School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
| | - Eric Adua
- School of Medical and Health Sciences, Edith Cowan University, Perth, Australia
| | | | - Augustine Tawiah
- Department of Obstetrics and Gynaecology, Komfo Anokye Teaching Hospital, Kumasi, Ghana
| | - Youxin Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Wei Wang
- School of Medical and Health Sciences, Edith Cowan University, Perth, Australia.,School of Public Health, Taishan Medical University, Taian, China
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25
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Adua E, Memarian E, Russell A, Trbojević-Akmačić I, Gudelj I, Jurić J, Roberts P, Lauc G, Wang W. Utilization of N-glycosylation profiles as risk stratification biomarkers for suboptimal health status and metabolic syndrome in a Ghanaian population. Biomark Med 2019; 13:1273-1287. [DOI: 10.2217/bmm-2019-0005] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Aim: The study sought to apply N-glycosylation profiles to understand the interplay between suboptimal health status (SHS) and metabolic syndrome (MetS). Materials & methods: In this study, 262 Ghanaians were recruited from May to July 2016. After completing a health survey, plasma samples were collected for clinical assessments while ultra performance liquid chromatography was used to measure plasma N-glycans. Results: Four glycan peaks were found to predict case status (MetS and SHS) using a step-wise Akaike’s information criterion logistic regression model selection. This model yielded an area under the curve of MetS: 83.1% (95% CI: 78.0–88.1%) and SHS: 67.1% (60.6–73.7%). Conclusion: Our results show that SHS is a significant, albeit modest, risk factor for MetS and N-glycan complexity was associated with MetS.
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Affiliation(s)
- Eric Adua
- School of Medical & Health Sciences, Edith Cowan University, WA 6027, Australia
| | - Elham Memarian
- Genos Glycoscience Research Laboratory, Zagreb 10000, Croatia
| | - Alyce Russell
- School of Medical & Health Sciences, Edith Cowan University, WA 6027, Australia
| | | | - Ivan Gudelj
- Genos Glycoscience Research Laboratory, Zagreb 10000, Croatia
| | - Julija Jurić
- Genos Glycoscience Research Laboratory, Zagreb 10000, Croatia
| | - Peter Roberts
- School of Medical & Health Sciences, Edith Cowan University, WA 6027, Australia
| | - Gordan Lauc
- Genos Glycoscience Research Laboratory, Zagreb 10000, Croatia
- University of Zagreb, Faculty of Pharmacy & Biochemistry, Zagreb 10000, Croatia
| | - Wei Wang
- School of Medical & Health Sciences, Edith Cowan University, WA 6027, Australia
- School of Public Health, Taishan Medical University, Shandong, Taian 271000, PR China
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, PR China
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26
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Duan X, Li Y, Liu Q, Liu L, Li C. Epidemiological characteristics, medical costs and healthcare resource utilization of diabetes-related complications among Chinese patients with type 2 diabetes mellitus. Expert Rev Pharmacoecon Outcomes Res 2019; 20:513-521. [PMID: 31456456 DOI: 10.1080/14737167.2019.1661777] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Objectives: To estimate the direct medical costs (DMCs) and healthcare resource utilization (HRU) of type 2 diabetes mellitus (T2DM)-related complications in China. Methods: Data from a total of 74,507 patients were extracted from the 2015 China Health Insurance Research Association Claims Database. The complications determined by primary diagnoses were categorized into three groups: 1) for mild acute and local chronic complications, both outpatients and inpatients were considered; 2) for severe acute complications, only inpatiens were considered; 3) for systemic chronic complications, a 1:1 propensity-score matching was performed to calculate the incremental DMCs and HRU of preexisting and new-onset patients. Results: Among the mild acute and local chronic complications, the DMCs and HRU per event were the highest for gangrene and laser treatment. Of the severe acute complications, the DMCs and HRU per event were highest for hyperosmotic nonketonic diabetic coma (HNDC), followed by severe hypoglycemia and ketosis. For systemic chronic complications, the DMCs and HRU associated with dialysis and myocardial infarction were the highest both in patients with new-onset complications and preexisting complications. Conclusions: The estimated economic data are required for policy decisions to optimize resource allocation and to evaluate different approaches for disease management.
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Affiliation(s)
- Xiaotuo Duan
- Health Economics and Outcome Research, Beijing Brainpower Pharma Consulting Co. Ltd , Beijing, China
| | - Yunguang Li
- Medical Department, Sanofi , Shanghai, China
| | - Qingjing Liu
- Beijing North Medical & Health Economic Research Center , Beijing, China
| | - Li Liu
- Health Economics and Outcome Research, Sanofi , Shanghai, China
| | - Chaoyun Li
- Health Economics and Outcome Research, Sanofi , Shanghai, China
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27
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Anto EO, Roberts P, Coall D, Turpin CA, Adua E, Wang Y, Wang W. Integration of suboptimal health status evaluation as a criterion for prediction of preeclampsia is strongly recommended for healthcare management in pregnancy: a prospective cohort study in a Ghanaian population. EPMA J 2019; 10:211-226. [PMID: 31462939 DOI: 10.1007/s13167-019-00183-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Accepted: 07/18/2019] [Indexed: 12/14/2022]
Abstract
Background Normotensive pregnancy may develop into preeclampsia (PE) and other adverse pregnancy complications (APCs), for which the causes are still unknown. Suboptimal health status (SHS), a physical state between health and disease, might contribute to the development and progression of PE. By integration of a routine health measure in this Ghanaian Suboptimal Health Cohort Study, we explored the usefulness of a 25-question item SHS questionnaire (SHSQ-25) for early screening and prediction of normotensive pregnant women (NTN-PW) likely to develop PE. Methods We assessed the overall health status among a cohort of 593 NTN-PW at baseline (10-20 weeks gestation) and followed them at 21-31 weeks until 32-42 weeks. After an average of 20 weeks follow-up, 498 participants returned and were included in the final analysis. Hematobiochemical, clinical and sociodemographic data were obtained. Results Of the 498 participants, 49.8% (248/498) had 'high SHS' at baseline (61.7% (153/248) later developed PE) and 38.3% (95/248) were NTN-PW, whereas 50.2% (250/498) had 'optimal health' (17.6% (44/250) later developed PE) and 82.4% (206/250) were NTN-PW. At baseline, high SHS score yielded a significantly (p < 0.05) increased adjusted odds ratio, a wider area under the curve (AUC) and a higher sensitivity and specificity for the prediction of PE (3.67; 0.898; 91.9% and 87.8%), PE coexisting with intrauterine growth restriction (2.86, 0.838; 91.5% and 75.9%), stillbirth (2.52; 0.783; 96.6% and 60.0%), hemolysis elevated liver enzymes and low platelet count (HELLP) syndrome (2.08; 0.800; 97.2% and 63.8%), acute kidney injury (2.20; 0.825; 95.3% and 70.0%) and dyslipidaemia (2.80; 0.8205; 95.7% and 68.4%) at 32-42 weeks gestation. Conclusions High SHS score is associated with increased incidence of PE; hence, SHSQ-25 can be used independently as a risk stratification tool for adverse pregnancy outcomes thereby creating an opportunity for predictive, preventive and personalized medicine.
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Affiliation(s)
- Enoch Odame Anto
- 1School of Medical and Health Sciences, Edith Cowan University, Perth, WA Australia.,2Department of Molecular Medicine, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Peter Roberts
- 1School of Medical and Health Sciences, Edith Cowan University, Perth, WA Australia
| | - David Coall
- 1School of Medical and Health Sciences, Edith Cowan University, Perth, WA Australia
| | | | - Eric Adua
- 1School of Medical and Health Sciences, Edith Cowan University, Perth, WA Australia
| | - Youxin Wang
- 4Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China
| | - Wei Wang
- 1School of Medical and Health Sciences, Edith Cowan University, Perth, WA Australia.,4Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.,5School of Public Health, Taishan Medical University, Taian, China
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28
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Ge S, Xu X, Zhang J, Hou H, Wang H, Liu D, Zhang X, Song M, Li D, Zhou Y, Wang Y, Wang W. Suboptimal health status as an independent risk factor for type 2 diabetes mellitus in a community-based cohort: the China suboptimal health cohort study. EPMA J 2019; 10:65-72. [PMID: 30984315 DOI: 10.1007/s13167-019-0159-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Accepted: 01/11/2019] [Indexed: 12/17/2022]
Abstract
Background The prevalence of diabetes, constituted chiefly by type 2 diabetes mellitus (T2DM), is a global public health threat. Suboptimal health status (SHS), a physical state between health and disease, might contribute to the progression or development of T2DM. Methods We conducted a prospective cohort study, based on the China Suboptimal Health Cohort Study (COACS), to understand the impact of SHS on the progress of T2DM. We examined associations between SHS and T2DM outcomes using multivariable logistic regression models and constructed predictive models for T2DM onset based on SHS. Results A total of 61 participants developed T2DM after an average of 3.1 years of follow-up. Participants with higher SHS scores had more T2DM outcomes (p = 0.036). Moreover, compared with the lowest quartile of SHS scores, participants with fourth, third, and second quartile SHS scores were found to be associated with a 1.7-fold, 1.6-fold, and 1.5-fold risk of developing T2DM, respectively. The predictive model constructed with SHS had higher discriminatory power (AUC = 0.848) than the model without SHS (AUC = 0.795). Conclusions The present study suggests that a higher SHS score is associated with a higher incidence of T2DM. SHS is a new independent risk factor for T2DM and has the capability to act as a predictive tool for T2DM onset. The evaluation of SHS combined with the analysis of modifiable risk factors for SHS allows the risk stratification of T2DM, which may consequently contribute to the prevention of T2DM development. These findings might require further validation in a longer-term follow-up study.
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Affiliation(s)
- Siqi Ge
- 1Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China.,2Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Xizhu Xu
- 3School of Public Health, Taishan Medical University, Taian, 271000 China
| | - Jie Zhang
- 1Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China
| | - Haifeng Hou
- 3School of Public Health, Taishan Medical University, Taian, 271000 China
| | - Hao Wang
- 1Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China.,4School of Medical and Health Sciences, Edith Cowan University, Perth, WA6027 Australia
| | - Di Liu
- 1Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China
| | - Xiaoyu Zhang
- 1Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China
| | - Manshu Song
- 1Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China.,4School of Medical and Health Sciences, Edith Cowan University, Perth, WA6027 Australia
| | - Dong Li
- 3School of Public Health, Taishan Medical University, Taian, 271000 China
| | - Yong Zhou
- 5Department of Neurology, Sanbo Brain Hospital, Capital Medical University, Beijing, 100093 China
| | - Youxin Wang
- 1Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China.,4School of Medical and Health Sciences, Edith Cowan University, Perth, WA6027 Australia
| | - Wei Wang
- 1Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing, 100069 China.,3School of Public Health, Taishan Medical University, Taian, 271000 China.,4School of Medical and Health Sciences, Edith Cowan University, Perth, WA6027 Australia
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29
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Hou H, Feng X, Li Y, Meng Z, Guo D, Wang F, Guo Z, Zheng Y, Peng Z, Zhang W, Li D, Ding G, Wang W. Suboptimal health status and psychological symptoms among Chinese college students: a perspective of predictive, preventive and personalised health. EPMA J 2018; 9:367-377. [PMID: 30538788 DOI: 10.1007/s13167-018-0148-4] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2018] [Accepted: 08/13/2018] [Indexed: 12/08/2022]
Abstract
Background Suboptimal health status (SHS) is an intermediate health status between health and illness, a syndrome characterised by the perception of health complaints, general weakness and low energy. This study aimed to investigate the prevalence of SHS and the correlation between SHS and psychological symptoms among Chinese college students and to identify the SHS-related risk factors from the perspective of predictive, preventive and personalised medicine (PPPM). Methods A cross-sectional study was conducted among 4119 college students who were enrolled from Taishan Medical University and Baoji Vocational and Technical College in the eastern and western areas of China. SHS levels of the participants were measured by an established self-reporting Suboptimal Health Status Questionnaire-25 (SHSQ-25). Psychosomatic conditions were estimated by the self-rating Symptom Checklist-90 (SCL-90) scale. Spearman correlation analysis was applied to analyse the relationship between SHSQ-25 scores and SCL-90 estimates. Logistic regression analysis was applied for multivariate analysis. Results The prevalence of SHS was 21.0% (864/4119), with 23.3% (701/3005) for female students and 14.6% (163/1114) for male students. The prevalence of general positive psychological symptom was 14.2% (586/4119), with 15.6% (470/3005) for female students and 10.4% (116/1114) for male students. A strong correlation was identified between SHS score and SCL-90 estimates, with the correlation coefficient (r) of 0.719. Logistic regression showed that variables significantly associated with SHS were somatisation (adjusted odds ratio (aOR) = 3.185, 95% confidence interval [CI] = 2.048-4.953), obsessive-compulsive (aOR = 3.518, 95% CI = 2.834-4.368), interpersonal sensitivity (aOR = 1.883, 95% CI = 1.439-2.463) and depression (aOR = 1.847, 95% CI = 1.335-2.554). Conclusions Our findings confirm that there is a high prevalence of SHS among college students and there is a strong association between SHS and psychological symptoms among Chinese college students. High susceptibility of SHS occurs particularly in vulnerable groups: female students, sophomore students, medical students and students from rural area. Identification of SHS and prompt application of personalised psychological health-supporting activities will promote college students' health status.
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Affiliation(s)
- Haifeng Hou
- 1School of Public Health, Taishan Medical University, 619 Changcheng Road, Taian, 271016 People's Republic of China.,2School of Medical and Health Sciences, Edith Cowan University, Perth, WA 6027 Australia
| | - Xia Feng
- 1School of Public Health, Taishan Medical University, 619 Changcheng Road, Taian, 271016 People's Republic of China
| | - Yuejin Li
- 1School of Public Health, Taishan Medical University, 619 Changcheng Road, Taian, 271016 People's Republic of China
| | - Zixiu Meng
- 1School of Public Health, Taishan Medical University, 619 Changcheng Road, Taian, 271016 People's Republic of China
| | - Dongmei Guo
- Baoji Vocational and Technical College, Baoji, People's Republic of China
| | - Fang Wang
- 1School of Public Health, Taishan Medical University, 619 Changcheng Road, Taian, 271016 People's Republic of China
| | - Zheng Guo
- 2School of Medical and Health Sciences, Edith Cowan University, Perth, WA 6027 Australia
| | - Yulu Zheng
- 2School of Medical and Health Sciences, Edith Cowan University, Perth, WA 6027 Australia
| | - Zhiqi Peng
- Baoji Vocational and Technical College, Baoji, People's Republic of China
| | - Wangxin Zhang
- 4School of Basic Medical Science, Taishan Medical University, Taian, People's Republic of China
| | - Dong Li
- 1School of Public Health, Taishan Medical University, 619 Changcheng Road, Taian, 271016 People's Republic of China
| | - Guoyong Ding
- 1School of Public Health, Taishan Medical University, 619 Changcheng Road, Taian, 271016 People's Republic of China
| | - Wei Wang
- 1School of Public Health, Taishan Medical University, 619 Changcheng Road, Taian, 271016 People's Republic of China.,2School of Medical and Health Sciences, Edith Cowan University, Perth, WA 6027 Australia
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