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      Association between sociodemographic status and cardiovascular risk factors burden in community populations: implication for reducing cardiovascular disease burden

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          Abstract

          Background:

          We aimed to evaluate the burden of cardiovascular (CV) risk factors in the community populations of Guangdong Province and its association with sociodemographic status (SDS).

          Method:

          The data were from the community populations of Guangdong Province who have participated in the China PEACE Million Persons Project between 2016 and 2020 (n = 102,358, women 60.5% and mean age 54.3 years). The prevalence of CV risk factors (smoking, drinking, overweight/obesity, hypertension, dyslipidemia and diabetes mellitus) and its association with SDS (age, sex and socioeconomic status [SES]) was evaluated cross-sectionally.

          Results:

          The prevalence of overweight/obesity was 48.9%, hypertension 39.9%, dyslipidemia 18.6%, smoking 17.2%, diabetes mellitus 16.1% and drinking 5.3%. Even in young adults (aged 35–44), nearly 60% had at least 1 CV risk factor. Overweight/obesity often coexisted with other risk factors, including smoking, hypertension, dyslipidemia and diabetes mellitus. The proportion of people with no risk factor decreased with increasing age. Women were more likely than men to have no CV risk factor (29.4% vs. 12.7%). People with ≥ high school degree were more likely than those with < high school to have no risk factor (28.5% vs. 20.4%), and farmers were less likely than non-farmers to have no risk factor (20.8% vs. 23.1%).

          Conclusion:

          The burden of CV risk factors is high and varied by SDS in the community populations of Guangdong Province. Cost-effective and targeted interventions are needed to reduce the burden of CV risk factors at the population level.

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          Most cited references31

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          The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies.

          Much biomedical research is observational. The reporting of such research is often inadequate, which hampers the assessment of its strengths and weaknesses and of a study's generalizability. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Initiative developed recommendations on what should be included in an accurate and complete report of an observational study. We defined the scope of the recommendations to cover 3 main study designs: cohort, case-control, and cross-sectional studies. We convened a 2-day workshop in September 2004, with methodologists, researchers, and journal editors, to draft a checklist of items. This list was subsequently revised during several meetings of the coordinating group and in e-mail discussions with the larger group of STROBE contributors, taking into account empirical evidence and methodological considerations. The workshop and the subsequent iterative process of consultation and revision resulted in a checklist of 22 items (the STROBE Statement) that relate to the title, abstract, introduction, methods, results, and discussion sections of articles. Eighteen items are common to all 3 study designs and 4 are specific for cohort, case-control, or cross-sectional studies. A detailed Explanation and Elaboration document is published separately and is freely available at http://www.annals.org and on the Web sites of PLoS Medicine and Epidemiology. We hope that the STROBE Statement will contribute to improving the quality of reporting of observational studies.
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            Mortality, morbidity, and risk factors in China and its provinces, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

            Summary Background Public health is a priority for the Chinese Government. Evidence-based decision making for health at the province level in China, which is home to a fifth of the global population, is of paramount importance. This analysis uses data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to help inform decision making and monitor progress on health at the province level. Methods We used the methods in GBD 2017 to analyse health patterns in the 34 province-level administrative units in China from 1990 to 2017. We estimated all-cause and cause-specific mortality, years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life-years (DALYs), summary exposure values (SEVs), and attributable risk. We compared the observed results with expected values estimated based on the Socio-demographic Index (SDI). Findings Stroke and ischaemic heart disease were the leading causes of death and DALYs at the national level in China in 2017. Age-standardised DALYs per 100 000 population decreased by 33·1% (95% uncertainty interval [UI] 29·8 to 37·4) for stroke and increased by 4·6% (–3·3 to 10·7) for ischaemic heart disease from 1990 to 2017. Age-standardised stroke, ischaemic heart disease, lung cancer, chronic obstructive pulmonary disease, and liver cancer were the five leading causes of YLLs in 2017. Musculoskeletal disorders, mental health disorders, and sense organ diseases were the three leading causes of YLDs in 2017, and high systolic blood pressure, smoking, high-sodium diet, and ambient particulate matter pollution were among the leading four risk factors contributing to deaths and DALYs. All provinces had higher than expected DALYs per 100 000 population for liver cancer, with the observed to expected ratio ranging from 2·04 to 6·88. The all-cause age-standardised DALYs per 100 000 population were lower than expected in all provinces in 2017, and among the top 20 level 3 causes were lower than expected for ischaemic heart disease, Alzheimer's disease, headache disorder, and low back pain. The largest percentage change at the national level in age-standardised SEVs among the top ten leading risk factors was in high body-mass index (185%, 95% UI 113·1 to 247·7]), followed by ambient particulate matter pollution (88·5%, 66·4 to 116·4). Interpretation China has made substantial progress in reducing the burden of many diseases and disabilities. Strategies targeting chronic diseases, particularly in the elderly, should be prioritised in the expanding Chinese health-care system. Funding China National Key Research and Development Program and Bill & Melinda Gates Foundation.
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              2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease

              Circulation
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                Author and article information

                Contributors
                fyq1819@163.com
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                31 October 2022
                31 October 2022
                2022
                : 22
                : 1996
                Affiliations
                [1 ]GRID grid.410643.4, Department of Cardiology, Hypertension Research Laboratory, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, , Guangdong Academy of Medical Sciences, ; 510080 Guangzhou, China
                [2 ]GRID grid.410643.4, Department of Epidemiology, Global Health Research Center, Guangdong Provincial People’s Hospital, , Guangdong Academy of Medical Sciences, ; 510080 Guangzhou, China
                [3 ]Community Health Center of Liaobu County, Dongguan, Guangdong China
                [4 ]Community Health Center of Xiaolan County, Zhongshan, Guangdong China
                [5 ]Center for Disease Control and Prevention of Jiangmen, Jiangmen, Guangdong China
                [6 ]GRID grid.410643.4, Guangdong Provincial People’s Hospital, , Guangdong Academy of Medical Sciences, ; No.106, Zhongshan 2nd Road, 510080 Yuexiu District, Guangzhou China
                Article
                14374
                10.1186/s12889-022-14374-4
                9624018
                36316767
                2d30193d-7a35-4e90-8bac-c1391129267c
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

                History
                : 22 June 2022
                : 20 September 2022
                : 18 October 2022
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Public health
                epidemiology,risk factor,cardiovascular disease,sociodemographic status
                Public health
                epidemiology, risk factor, cardiovascular disease, sociodemographic status

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