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      Cardiovascular Diseases and Risk‐Factor Burden in Urban and Rural Communities in High‐, Middle‐, and Low‐Income Regions of China: A Large Community‐Based Epidemiological Study

      research-article
      , BSc 1 , , PhD 1 , , , PhD 1 , , MSc 1 , , BSc 1 , PURE‐China Investigators , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
      Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
      John Wiley and Sons Inc.
      cardiovascular disease, prevalence, risk‐factor burden, socioeconomic region, urban and rural, Cardiovascular Disease, Epidemiology, Risk Factors

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          Abstract

          Background

          Most cardiovascular diseases occur in low‐ and middle‐income regions of the world, but the socioeconomic distribution within China remains unclear. Our study aims to investigate whether the prevalence of cardiovascular diseases differs among high‐, middle‐, and low‐income regions of China and to explore the reasons for the disparities.

          Methods and Results

          We enrolled 46 285 individuals from 115 urban and rural communities in 12 provinces across China between 2005 and 2009. We recorded their medical histories of cardiovascular diseases and calculated the INTERHEART Risk Score for the assessment of cardiovascular risk‐factor burden, with higher scores indicating greater burden. The mean INTERHEART Risk Score was higher in high‐ and middle‐income regions than in low‐income regions (9.47, 9.48, and 8.58, respectively, P<0.0001). By contrast, the prevalence of total cardiovascular disease (stroke, ischemic heart disease, and other heart diseases that led to hospitalization) was lower in high‐ and middle‐income regions than in low‐income regions (7.46%, 7.42%, and 8.36%, respectively, P trend=0.0064). In high‐ and middle‐income regions, urban communities have higher INTERHEART Risk Score and higher prevalent rate than rural communities. In low‐income regions, however, the prevalence of total cardiovascular disease was similar between urban and rural areas despite the significantly higher INTERHEART Risk Score for urban settings.

          Conclusions

          We detected an inverse trend between risk‐factor burden and cardiovascular disease prevalence in urban and rural communities in high‐, middle‐, and low‐income regions of China. Such asymmetry may be attributed to the interregional differences in residents’ awareness, quality of healthcare, and availability and affordability of medical services.

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          Most cited references17

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          A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010

          The Lancet, 380(9859), 2224-2260
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            Development, validation and utilisation of food-frequency questionnaires - a review.

            The purpose of this review is to provide guidance on the development, validation and use of food-frequency questionnaires (FFQs) for different study designs. It does not include any recommendations about the most appropriate method for dietary assessment (e.g. food-frequency questionnaire versus weighed record). A comprehensive search of electronic databases was carried out for publications from 1980 to 1999. Findings from the review were then commented upon and added to by a group of international experts. Recommendations have been developed to aid in the design, validation and use of FFQs. Specific details of each of these areas are discussed in the text. FFQs are being used in a variety of ways and different study designs. There is no gold standard for directly assessing the validity of FFQs. Nevertheless, the outcome of this review should help those wishing to develop or adapt an FFQ to validate it for its intended use.
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              Agreement between self-report questionnaires and medical record data was substantial for diabetes, hypertension, myocardial infarction and stroke but not for heart failure.

              Questionnaires are used to estimate disease burden. Agreement between questionnaire responses and a criterion standard is important for optimal disease prevalence estimates. We measured the agreement between self-reported disease and medical record diagnosis of disease. A total of 2,037 Olmsted County, Minnesota residents > or =45 years of age were randomly selected. Questionnaires asked if subjects had ever had heart failure, diabetes, hypertension, myocardial infarction (MI), or stroke. Medical records were abstracted. Self-report of disease showed >90% specificity for all these diseases, but sensitivity was low for heart failure (69%) and diabetes (66%). Agreement between self-report and medical record was substantial (kappa 0.71-0.80) for diabetes, hypertension, MI, and stroke but not for heart failure (kappa 0.46). Factors associated with high total agreement by multivariate analysis were age 12 years, and zero Charlson Index score (P < .05). Questionnaire data are of greatest value in life-threatening, acute-onset diseases (e.g., MI and stroke) and chronic disorders requiring ongoing management (e.g.,diabetes and hypertension). They are more accurate in young women and better-educated subjects.
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                Author and article information

                Contributors
                liwei@mrbc-nccd.com
                Journal
                J Am Heart Assoc
                J Am Heart Assoc
                10.1002/(ISSN)2047-9980
                JAH3
                ahaoa
                Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
                John Wiley and Sons Inc. (Hoboken )
                2047-9980
                06 February 2017
                February 2017
                : 6
                : 2 ( doiID: 10.1002/jah3.2017.6.issue-2 )
                : e004445
                Affiliations
                [ 1 ] State Key Laboratory of Cardiovascular Disease Fuwai Hospital National Center for Cardiovascular Diseases Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China
                Author notes
                [*] [* ] Correspondence to: Wei Li, PhD, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Room 101, Block A, Xishan Institute of Fuwai Hospital, Yongding Town, Mentougou District, Beijing 102300, China. E‐mail: liwei@ 123456mrbc-nccd.com
                [†]

                A complete list of the PURE‐China Investigators can be found in the Appendix at the end of the manuscript.

                Article
                JAH31974
                10.1161/JAHA.116.004445
                5523752
                28167497
                f1c14d6a-d512-425e-b6ca-9b61823761bc
                © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

                This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 05 August 2016
                : 09 December 2016
                Page count
                Figures: 4, Tables: 5, Pages: 17, Words: 9912
                Funding
                Funded by: Population Health Research Institute, Hamilton
                Funded by: Canadian Institutes of Health Research
                Funded by: Heart and Stroke Foundation of Ontario
                Funded by: National Center for Cardiovascular Diseases
                Categories
                Original Research
                Original Research
                Epidemiology
                Custom metadata
                2.0
                jah31974
                February 2017
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.1.3 mode:remove_FC converted:11.07.2017

                Cardiovascular Medicine
                cardiovascular disease,prevalence,risk‐factor burden,socioeconomic region,urban and rural,epidemiology,risk factors

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