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      China suboptimal health cohort study: rationale, design and baseline characteristics

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          Abstract

          Background

          Suboptimal health status (SHS) is a physical state between health and disease, characterized by the perception of health complaints, general weakness, chronic fatigue and low energy levels. SHS is proposed by the ancient concept of traditional Chinese medicine (TCM) from the perspective of preservative, predictive and personalized (precision) medicine. We previously created the suboptimal health status questionnaire 25 (SHSQ-25), a novel instrument to measure SHS, validated in various populations. SHSQ-25 thus affords a window of opportunity for early detection and intervention, contributing to the reduction of chronic disease burdens.

          Methods/design

          To investigate the causative effect of SHS in non-communicable chronic diseases (NCD), we initiated the China suboptimal health cohort study (COACS), a longitudinal study starting from 2013. Phase I of the study involved a cross-sectional survey aimed at identifying the risk/protective factors associated with SHS; and Phase II: a longitudinal yearly follow-up study investigating how SHS contributes to the incidence and pattern of NCD.

          Results

          (1) Cross-sectional survey: in total, 4313 participants (53.8 % women) aged from 18 to 65 years were included in the cohort. The prevalence of SHS was 9.0 % using SHS score of 35 as threshold. Women showed a significantly higher prevalence of SHS (10.6 % in the female vs. 7.2 % in the male, P < 0.001). Risk factors for chronic diseases such as socioeconomic status, marital status, highest education completed, physical activity, salt intake, blood pressure and triglycerides differed significantly between subjects of SHS (SHS score ≥35) and those of ideal health (SHS score <35). (2) Follow up: the primary and secondary outcomes will be monitored from 2015 to 2024.

          Conclusions

          The sex-specific difference in prevalence of SHS might partly explain the gender difference of incidence of certain chronic diseases. The COACS will enable a thorough characterization of SHS and establish a cohort that will be used for longitudinal analyses of the interaction between the genetic, lifestyle and environmental factors that contribute to the onset and etiology of targeted chronic diseases. The study together with the designed prospective cohort provides a chance to characterize and evaluate the effect of SHS systemically, and it thus generates an unprecedented opportunity for the early detection and prevention of chronic disease.

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          Most cited references31

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          Global mortality, disability, and the contribution of risk factors: Global Burden of Disease Study.

          Prevention and control of disease and injury require information about the leading medical causes of illness and exposures or risk factors. The assessment of the public-health importance of these has been hampered by the lack of common methods to investigate the overall, worldwide burden. The Global Burden of Disease Study (GBD) provides a standardised approach to epidemiological assessment and uses a standard unit, the disability-adjusted life year (DALY), to aid comparisons. DALYs for each age-sex group in each GBD region for 107 disorders were calculated, based on the estimates of mortality by cause, incidence, average age of onset, duration, and disability severity. Estimates of the burden and prevalence of exposure in different regions of disorders attributable to malnutrition, poor water supply, sanitation and personal and domestic hygiene, unsafe sex, tobacco use, alcohol, occupation, hypertension, physical inactivity, use of illicit drugs, and air pollution were developed. Developed regions account for 11.6% of the worldwide burden from all causes of death and disability, and account for 90.2% of health expenditure worldwide. Communicable, maternal, perinatal, and nutritional disorders explain 43.9%; non-communicable causes 40.9%; injuries 15.1%; malignant neoplasms 5.1%; neuropsychiatric conditions 10.5%; and cardiovascular conditions 9.7% of DALYs worldwide. The ten leading specific causes of global DALYs are, in descending order, lower respiratory infections, diarrhoeal diseases, perinatal disorders, unipolar major depression, ischaemic heart disease, cerebrovascular disease, tuberculosis, measles, road-traffic accidents, and congenital anomalies. 15.9% of DALYs worldwide are attributable to childhood malnutrition and 6.8% to poor water, and sanitation and personal and domestic hygiene. The three leading contributors to the burden of disease are communicable and perinatal disorders affecting children. The substantial burdens of neuropsychiatric disorders and injuries are under-recognised. The epidemiological transition in terms of DALYs has progressed substantially in China, Latin America and the Caribbean, other Asia and islands, and the middle eastern crescent. If the burdens of disability and death are taken into account, our list differs substantially from other lists of the leading causes of death. DALYs provide a common metric to aid meaningful comparison of the burden of risk factors, diseases, and injuries.
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            Major causes of death among men and women in China.

            With China's rapid economic development, the disease burden may have changed in the country. We studied the major causes of death and modifiable risk factors in a nationally representative cohort of 169,871 men and women 40 years of age and older in China. Baseline data on the participants' demographic characteristics, medical history, lifestyle-related risk factors, blood pressure, and body weight were obtained in 1991 with the use of a standard protocol. The follow-up evaluation was conducted in 1999 and 2000, with a follow-up rate of 93.4 percent. We documented 20,033 deaths in 1,239,191 person-years of follow-up. The mortality from all causes was 1480.1 per 100,000 person-years among men and 1190.2 per 100,000 person-years among women. The five leading causes of death were malignant neoplasms (mortality, 374.1 per 100,000 person-years), diseases of the heart (319.1), cerebrovascular disease (310.5), accidents (54.0), and infectious diseases (50.5) among men and diseases of the heart (268.5), cerebrovascular disease (242.3), malignant neoplasms (214.1), pneumonia and influenza (45.9), and infectious diseases (35.3) among women. The multivariate-adjusted relative risk of death and the population attributable risk for preventable risk factors were as follows: hypertension, 1.48 (95 percent confidence interval, 1.44 to 1.53) and 11.7 percent, respectively; cigarette smoking, 1.23 (95 percent confidence interval, 1.18 to 1.27) and 7.9 percent; physical inactivity, 1.20 (95 percent confidence interval, 1.16 to 1.24) and 6.8 percent; and underweight (body-mass index [the weight in kilograms divided by the square of the height in meters] below 18.5), 1.47 (95 percent confidence interval, 1.42 to 1.53) and 5.2 percent. Vascular disease and cancer have become the leading causes of death among Chinese adults. Our findings suggest that control of hypertension, smoking cessation, increased physical activity, and improved nutrition should be important strategies for reducing the burden of premature death among adults in China. Copyright 2005 Massachusetts Medical Society.
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              Stroke--1989. Recommendations on stroke prevention, diagnosis, and therapy. Report of the WHO Task Force on Stroke and other Cerebrovascular Disorders.

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                Author and article information

                Contributors
                wangy@ccmu.edu.cn
                gesky90@sina.com
                yanyxepi@ccmu.edu.cn
                anxin0907@163.com
                yao_abcde@163.com
                yuxinweigongzuo@163.com
                qiu199008jing@163.com
                mohali@163.com
                wanghaostudy@163.com
                fanghonghong79@sina.com
                shouyigaoqing@163.com
                songms@ccmu.edu.cn
                zhangjie@ccmu.edu.cn
                Yongzhou78214@163.com
                wei.wang@ecu.edu.au
                Journal
                J Transl Med
                J Transl Med
                Journal of Translational Medicine
                BioMed Central (London )
                1479-5876
                13 October 2016
                13 October 2016
                2016
                : 14
                : 291
                Affiliations
                [1 ]Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, 100069 China
                [2 ]Global Health and Genomics, School of Medical and Health Sciences, Edith Cowan University, Perth, 6027 Australia
                [3 ]Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100050 China
                [4 ]School of Public Health, Ningxia Medical University, Yinchuan, 750021 China
                [5 ]Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029 China
                [6 ]Department of Neurology, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100027 China
                Article
                1046
                10.1186/s12967-016-1046-y
                5064923
                27737677
                96d032a0-b52e-4306-a634-7434cf6b0b35
                © The Author(s) 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 11 June 2016
                : 3 October 2016
                Funding
                Funded by: National Key Technology Support Program of China
                Award ID: 2012BAI37B03
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81273170
                Award ID: 81370083
                Award ID: 81573215
                Award ID: 81673247
                Award Recipient :
                Funded by: the Joint Project of the Australian National Health and Medical Research Council and the National Natural Science Foundation of China
                Award ID: NHMRC APP1112767 - NSFC 81561128020
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100005090, Beijing Nova Program;
                Award ID: Z141107001814058
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2016

                Medicine
                suboptimal health status (shs),non-communicable chronic disease (ncd),cardiovascular events,cerebrovascular events,cohort study

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