Blog
About

  • Record: found
  • Abstract: found
  • Article: found
Is Open Access

Comparison of Prevalence, Awareness, Treatment, and Control of Cardiovascular Risk Factors in China and the United States

Read this article at

Bookmark
      There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

      Abstract

      Background

      The reasons for China's high stroke prevalence are not well understood. The cardiovascular risk factor profiles of China and the United States have not been directly compared in nationally representative population samples.

      Methods and Results

      Using data from the CHARLS (China Health and Retirement Longitudinal Study) and the NHANES ( US National Health and Nutrition Examination Survey), we compared cardiovascular risk factors from 2011 to 2012 among people aged 45 to 75 years between the 2 countries (China, 12 654 people; United States, 2607 people): blood pressure, cholesterol, body mass index, waist circumference, fasting plasma glucose, hemoglobin A1c, and high‐sensitivity C‐reactive protein. Compared with the United States, China had a lower prevalence of hypertension but a higher mean blood pressure and a higher proportion of patients with severe hypertension (≥160/100 mm Hg) (10.5% versus 4.5%). China had substantially lower rates of hypertension treatment (46.8% versus 77.9%) and control (20.3% versus 54.7%). Dyslipidemia was less common in China, but lipid levels were not significantly different because dyslipidemia awareness and control rates in China were 3‐ and 7‐fold lower than US rates, respectively. High‐sensitivity C‐reactive protein, body mass index, and waist circumference were significantly lower in China than in the United States. Clustering of hypertension with other cardiovascular risk factors was more common in China.

      Conclusions

      Hypertension is more common in the United States, but blood pressure levels are higher in China, which may be responsible for China's high stroke prevalence. The low rates of awareness, treatment, and control of hypertension provide an exceptional opportunity for China to reduce risk in its population.

      Related collections

      Most cited references 32

      • Record: found
      • Abstract: not found
      • Article: not found

      Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge.

        Bookmark
        • Record: found
        • Abstract: found
        • Article: not found

        Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.

        Up-to-date evidence on levels and trends for age-sex-specific all-cause and cause-specific mortality is essential for the formation of global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013) we estimated yearly deaths for 188 countries between 1990, and 2013. We used the results to assess whether there is epidemiological convergence across countries. We estimated age-sex-specific all-cause mortality using the GBD 2010 methods with some refinements to improve accuracy applied to an updated database of vital registration, survey, and census data. We generally estimated cause of death as in the GBD 2010. Key improvements included the addition of more recent vital registration data for 72 countries, an updated verbal autopsy literature review, two new and detailed data systems for China, and more detail for Mexico, UK, Turkey, and Russia. We improved statistical models for garbage code redistribution. We used six different modelling strategies across the 240 causes; cause of death ensemble modelling (CODEm) was the dominant strategy for causes with sufficient information. Trends for Alzheimer's disease and other dementias were informed by meta-regression of prevalence studies. For pathogen-specific causes of diarrhoea and lower respiratory infections we used a counterfactual approach. We computed two measures of convergence (inequality) across countries: the average relative difference across all pairs of countries (Gini coefficient) and the average absolute difference across countries. To summarise broad findings, we used multiple decrement life-tables to decompose probabilities of death from birth to exact age 15 years, from exact age 15 years to exact age 50 years, and from exact age 50 years to exact age 75 years, and life expectancy at birth into major causes. For all quantities reported, we computed 95% uncertainty intervals (UIs). We constrained cause-specific fractions within each age-sex-country-year group to sum to all-cause mortality based on draws from the uncertainty distributions. Global life expectancy for both sexes increased from 65.3 years (UI 65.0-65.6) in 1990, to 71.5 years (UI 71.0-71.9) in 2013, while the number of deaths increased from 47.5 million (UI 46.8-48.2) to 54.9 million (UI 53.6-56.3) over the same interval. Global progress masked variation by age and sex: for children, average absolute differences between countries decreased but relative differences increased. For women aged 25-39 years and older than 75 years and for men aged 20-49 years and 65 years and older, both absolute and relative differences increased. Decomposition of global and regional life expectancy showed the prominent role of reductions in age-standardised death rates for cardiovascular diseases and cancers in high-income regions, and reductions in child deaths from diarrhoea, lower respiratory infections, and neonatal causes in low-income regions. HIV/AIDS reduced life expectancy in southern sub-Saharan Africa. For most communicable causes of death both numbers of deaths and age-standardised death rates fell whereas for most non-communicable causes, demographic shifts have increased numbers of deaths but decreased age-standardised death rates. Global deaths from injury increased by 10.7%, from 4.3 million deaths in 1990 to 4.8 million in 2013; but age-standardised rates declined over the same period by 21%. For some causes of more than 100,000 deaths per year in 2013, age-standardised death rates increased between 1990 and 2013, including HIV/AIDS, pancreatic cancer, atrial fibrillation and flutter, drug use disorders, diabetes, chronic kidney disease, and sickle-cell anaemias. Diarrhoeal diseases, lower respiratory infections, neonatal causes, and malaria are still in the top five causes of death in children younger than 5 years. The most important pathogens are rotavirus for diarrhoea and pneumococcus for lower respiratory infections. Country-specific probabilities of death over three phases of life were substantially varied between and within regions. For most countries, the general pattern of reductions in age-sex specific mortality has been associated with a progressive shift towards a larger share of the remaining deaths caused by non-communicable disease and injuries. Assessing epidemiological convergence across countries depends on whether an absolute or relative measure of inequality is used. Nevertheless, age-standardised death rates for seven substantial causes are increasing, suggesting the potential for reversals in some countries. Important gaps exist in the empirical data for cause of death estimates for some countries; for example, no national data for India are available for the past decade. Bill & Melinda Gates Foundation. Copyright © 2015 Elsevier Ltd. All rights reserved.
          Bookmark
          • Record: found
          • Abstract: found
          • Article: not found

          Age-specific relevance of usual blood pressure to vascular mortality: a meta-analysis of individual data for one million adults in 61 prospective studies.

          The age-specific relevance of blood pressure to cause-specific mortality is best assessed by collaborative meta-analysis of individual participant data from the separate prospective studies. Information was obtained on each of one million adults with no previous vascular disease recorded at baseline in 61 prospective observational studies of blood pressure and mortality. During 12.7 million person-years at risk, there were about 56000 vascular deaths (12000 stroke, 34000 ischaemic heart disease [IHD], 10000 other vascular) and 66000 other deaths at ages 40-89 years. Meta-analyses, involving "time-dependent" correction for regression dilution, related mortality during each decade of age at death to the estimated usual blood pressure at the start of that decade. Within each decade of age at death, the proportional difference in the risk of vascular death associated with a given absolute difference in usual blood pressure is about the same down to at least 115 mm Hg usual systolic blood pressure (SBP) and 75 mm Hg usual diastolic blood pressure (DBP), below which there is little evidence. At ages 40-69 years, each difference of 20 mm Hg usual SBP (or, approximately equivalently, 10 mm Hg usual DBP) is associated with more than a twofold difference in the stroke death rate, and with twofold differences in the death rates from IHD and from other vascular causes. All of these proportional differences in vascular mortality are about half as extreme at ages 80-89 years as at ages 40-49 years, but the annual absolute differences in risk are greater in old age. The age-specific associations are similar for men and women, and for cerebral haemorrhage and cerebral ischaemia. For predicting vascular mortality from a single blood pressure measurement, the average of SBP and DBP is slightly more informative than either alone, and pulse pressure is much less informative. Throughout middle and old age, usual blood pressure is strongly and directly related to vascular (and overall) mortality, without any evidence of a threshold down to at least 115/75 mm Hg.
            Bookmark

            Author and article information

            Affiliations
            [ 1 ] Center for Outcomes Research and Evaluation Yale–New Haven Hospital Yale School of Medicine New Haven CT
            [ 2 ] Section of Cardiovascular Medicine Department of Internal Medicine Yale School of Medicine New Haven CT
            [ 3 ] Yale School of Public Health New Haven CT
            [ 4 ] National Clinical Research Center of Cardiovascular Diseases 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
            [ 5 ] Baptist Health South Florida Miami FL
            [ 6 ] Department of Health Policy and Management Yale School of Public Health New Haven CT
            Author notes
            [* ] Correspondence to: Harlan M. Krumholz, MD, SM, Yale School of Medicine, 1 Church St, Ste 200, New Haven, CT 06510. E‐mail: harlan.krumholz@ 123456yale.edu
            Contributors
            harlan.krumholz@yale.edu
            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
            26 January 2018
            February 2018
            : 7
            : 3 ( doiID: 10.1002/jah3.2018.7.issue-3 )
            29374046
            5850247
            10.1161/JAHA.117.007462
            JAH32904
            © 2018 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

            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.

            Counts
            Figures: 8, Tables: 3, Pages: 17, Words: 8196
            Product
            Categories
            Original Research
            Original Research
            Epidemiology
            Custom metadata
            2.0
            jah32904
            February 2018
            Converter:WILEY_ML3GV2_TO_NLMPMC version:version=5.3.2.2 mode:remove_FC converted:06.02.2018

            Comments

            Comment on this article