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      Clustering of risk factors and the risk of incident cardiovascular disease in Asian and Caucasian populations: results from the Asia Pacific Cohort Studies Collaboration

      research-article
      1 , 2 , 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 2 , 2 , 1 , 9 , 10
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      BMJ Open
      BMJ Publishing Group
      epidemiology, preventive medicine, myocardial infarction, stroke

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          Abstract

          Objective

          To assess the relationship between risk factor clusters and cardiovascular disease (CVD) incidence in Asian and Caucasian populations and to estimate the burden of CVD attributable to each cluster.

          Setting

          Asia Pacific Cohort Studies Collaboration.

          Participants

          Individual participant data from 34 population-based cohorts, involving 314 024 participants without a history of CVD at baseline.

          Outcome measures

          Clusters were 11 possible combinations of four individual risk factors (current smoking, overweight, blood pressure (BP) and total cholesterol). Cox regression models were used to obtain adjusted HRs and 95% CIs for CVD associated with individual risk factors and risk factor clusters. Population-attributable fractions (PAFs) were calculated.

          Results

          During a mean follow-up of 7 years, 6203 CVD events were recorded. The ranking of HRs and PAFs was similar for Australia and New Zealand (ANZ) and Asia; clusters including BP consistently showed the highest HRs and PAFs. The BP–smoking cluster had the highest HR for people with two risk factors: 4.13 (3.56 to 4.80) for Asia and 3.07 (2.23 to 4.23) for ANZ. Corresponding PAFs were 24% and 11%, respectively. For individuals with three risk factors, the BP–smoking–cholesterol cluster had the highest HR (4.67 (3.92 to 5.57) for Asia and 3.49 (2.69 to 4.53) for ANZ). Corresponding PAFs were 13% and 10%.

          Conclusions

          Risk factor clusters act similarly on CVD risk in Asian and Caucasian populations. Clusters including elevated BP were associated with the highest excess risk of CVD.

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          Most cited references13

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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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            The prevalence of chronic diseases and major disease risk factors at different ages among 150 000 men and women living in Mexico City: cross-sectional analyses of a prospective study

            Background While most of the global burden from chronic diseases, and especially vascular diseases, is now borne by low and middle-income countries, few large-scale epidemiological studies of chronic diseases in such countries have been performed. Methods From 1998–2004, 52 584 men and 106 962 women aged ≥35 years were visited in their homes in Mexico City. Self reported diagnoses of chronic diseases and major disease risk factors were ascertained and physical measurements taken. Age- and sex-specific prevalences and means were analysed. Results After about age 50 years, diabetes was extremely common – for example, 23.8% of men and 26.9% of women aged 65–74 reported a diagnosis. By comparison, ischaemic heart disease was reported by 4.8% of men and 3.0% of women aged 65–74, a history of stroke by 2.8% and 2.3%, respectively, and a history of cancer by 1.3% and 2.1%. Cancer history was generally more common among women than men – the excess being largest in middle-age, due to breast and cervical cancer. At older ages, the gap narrowed because of an increasing prevalence of prostate cancer. 51% of men and 25% of women aged 35–54 smoked cigarettes, while 29% of men and 41% of women aged 35–54 were obese (i.e. BMI ≥30 kg/m2). The prevalence of treated hypertension or measured blood pressure ≥140/90 mmHg increased about 50% more steeply with age among women than men, to 66% of women and 58% of men aged 65–74. Physical inactivity was highly prevalent but daily alcohol drinking was relatively uncommon. Conclusion Diabetes, obesity and tobacco smoking are highly prevalent among adults living in Mexico City. Long-term follow-up of this and other cohorts will establish the relevance of such factors to the major causes of death and disability in Mexico.
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              Impact of multiple risk factor profiles on determining cardiovascular disease risk.

              We examined the association between clustering of risk factors and the risk for coronary heart disease, stroke, and all-cause mortality. Data from the First National Health and Nutrition Examination Survey Epidemiologic Follow-Up Study (N = 12,932) were used to estimate the relative risk for coronary heart disease (N = 2,255), stroke (N = 929), and death from any cause (N = 4,506) by the number of cardiovascular disease risk factors present. Risk factors included current smoking, overweight, hypertension, high blood cholesterol, and diabetes. The proportions of respondents with 0, 1, 2, 3, or > or = 4 risk factors were 25.0, 32.8, 27.8, 12.3, and 2.1%, respectively. Relative risks for coronary heart disease associated with having 1, 2, 3, and > or = 4 risk factors were 1.6 (95% confidence interval [CI] 1.4, 1.9), 2.2 (95% CI 1.9, 2.6), 3.1 (95% CI 2.6, 3.6), and 5.0 (95% CI 3.9, 6.3), respectively. Relative risks for stroke associated with the same risk levels were 1.4 (95% CI 1.1, 1.8), 1.9 (95% CI 1.5, 2.4), 2.3 (95% CI 1.7, 3.0), and 4.3 (95% CI 3.0, 6.3), respectively. Similar results were observed for all-cause mortality. Risk for cardiovascular disease and all-cause mortality increased substantially with each additional risk factor. This supports the continued need for primary prevention of cardiovascular disease risk factors.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2018
                6 March 2018
                : 8
                : 3
                : e019335
                Affiliations
                [1 ] departmentGeorge Institute for Global Health , University of Oxford , Oxford, UK
                [2 ] departmentJulius Center for Health Sciences and Primary Care , University Medical Center Utrecht , Utrecht, The Netherlands
                [3 ] The First Hospital of Jilin University , Changchun, China
                [4 ] departmentSchool of Public Health , University of Hong Kong , Hong Kong, China
                [5 ] Yonsei University College of Medicine , Seoul, Republic of Korea
                [6 ] departmentJC School of Public Health and Primary Care , Faculty of Medicine, The Chinese University of Hong Kong , Hong Kong, China
                [7 ] departmentDepartment of Epidemiology and Public Health , Kyushu University , Fukuoka, Japan
                [8 ] departmentSchool of Population Health , University of Western Australia , Perth, Western Australia, Australia
                [9 ] departmentDepartment of Epidemiology , Johns Hopkins University , Baltimore, Maryland, USA
                [10 ] departmentThe George Institute for Global Health , University of New South Wales , Sydney, NSW, Australia
                Author notes
                [Correspondence to ] Professor Mark Woodward; markw@ 123456georgeinstitute.org.au
                Article
                bmjopen-2017-019335
                10.1136/bmjopen-2017-019335
                5855160
                29511013
                9d43d4cf-7288-4b66-9f27-2ad6c1225509
                © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

                History
                : 29 August 2017
                : 01 December 2017
                : 22 January 2018
                Categories
                Epidemiology
                Research
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                1692
                655
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                Medicine
                epidemiology,preventive medicine,myocardial infarction,stroke
                Medicine
                epidemiology, preventive medicine, myocardial infarction, stroke

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