Applying the China-PAR Risk Algorithm to Assess 10-year Atherosclerotic Cardiovascular Disease Risk in Populations Receiving Routine Physical Examinations in Eastern China
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摘要
Objective To assess the 10-year Atherosclerotic Cardiovascular Disease(ASCVD) risk score among adults in eastern China using the China-PAR equation which formulated primarily for the Chinese population. Methods Data from 72,129 individuals from 35-74 years old who received routine physical examinations in eastern China were analyzed in this study. The 10-year risk scores were calculated using the China-PAR equation. The chi-square test and logistic regression were then performed to evaluate the association between the selected risk factors and overall CVD risk. Results The mean 10-year ASCVD risk scores were 3.82% ± 3.76% in men and 1.30% ± 1.65% in women based on the China-PAR equation. Overall, 20% of men and 3.5% of women were intermediate-risk, and 7.3% of men and 0.3% of women were high-risk. Waist to hip ratio(WHR) [OR = 1.16(CI 95% = 1.06-1.26)], waist to height ratio(WHtR) [OR = 1.16(CI 95% = 1.05-1.28)], non-high-density lipoprotein cholesterol(non-HDL-C) [OR = 1.23(CI 95% = 1.09-1.39)], and total cholesterol(TC)/HDL-C [OR = 1.68(CI 95% = 1.46-1.94)] were more strongly associated with CVD risk than body-mass index(BMI), waist circumference(WC), and TC alone. Conclusion Male-specific prevention and treatment strategies for ASCVD are needed in eastern China. In addition, WHR, WHtR, non-HDL-C, and TC/HDL-C which not included in the the China-PAR equation were also independently associated with 10-year ASCVD risk score categories.
Objective To assess the 10-year Atherosclerotic Cardiovascular Disease(ASCVD) risk score among adults in eastern China using the China-PAR equation which formulated primarily for the Chinese population. Methods Data from 72,129 individuals from 35-74 years old who received routine physical examinations in eastern China were analyzed in this study. The 10-year risk scores were calculated using the China-PAR equation. The chi-square test and logistic regression were then performed to evaluate the association between the selected risk factors and overall CVD risk. Results The mean 10-year ASCVD risk scores were 3.82% ± 3.76% in men and 1.30% ± 1.65% in women based on the China-PAR equation. Overall, 20% of men and 3.5% of women were intermediate-risk, and 7.3% of men and 0.3% of women were high-risk. Waist to hip ratio(WHR) [OR = 1.16(CI 95% = 1.06-1.26)], waist to height ratio(WHtR) [OR = 1.16(CI 95% = 1.05-1.28)], non-high-density lipoprotein cholesterol(non-HDL-C) [OR = 1.23(CI 95% = 1.09-1.39)], and total cholesterol(TC)/HDL-C [OR = 1.68(CI 95% = 1.46-1.94)] were more strongly associated with CVD risk than body-mass index(BMI), waist circumference(WC), and TC alone. Conclusion Male-specific prevention and treatment strategies for ASCVD are needed in eastern China. In addition, WHR, WHtR, non-HDL-C, and TC/HDL-C which not included in the the China-PAR equation were also independently associated with 10-year ASCVD risk score categories.
Objective To assess the 10-year Atherosclerotic Cardiovascular Disease(ASCVD) risk score among adults in eastern China using the China-PAR equation which formulated primarily for the Chinese population. Methods Data from 72,129 individuals from 35-74 years old who received routine physical examinations in eastern China were analyzed in this study. The 10-year risk scores were calculated using the China-PAR equation. The chi-square test and logistic regression were then performed to evaluate the association between the selected risk factors and overall CVD risk. Results The mean 10-year ASCVD risk scores were 3.82% ± 3.76% in men and 1.30% ± 1.65% in women based on the China-PAR equation. Overall, 20% of men and 3.5% of women were intermediate-risk, and 7.3% of men and 0.3% of women were high-risk. Waist to hip ratio(WHR) [OR = 1.16(CI 95% = 1.06-1.26)], waist to height ratio(WHtR) [OR = 1.16(CI 95% = 1.05-1.28)], non-high-density lipoprotein cholesterol(non-HDL-C) [OR = 1.23(CI 95% = 1.09-1.39)], and total cholesterol(TC)/HDL-C [OR = 1.68(CI 95% = 1.46-1.94)] were more strongly associated with CVD risk than body-mass index(BMI), waist circumference(WC), and TC alone. Conclusion Male-specific prevention and treatment strategies for ASCVD are needed in eastern China. In addition, WHR, WHtR, non-HDL-C, and TC/HDL-C which not included in the the China-PAR equation were also independently associated with 10-year ASCVD risk score categories.
引文
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26.Sarwar N,Danesh J,Eiriksdottir G,et al.Triglycerides and the risk of coronary heart disease:10,158 incident cases among262,525 participants in 29 Western prospective studies.Circulation,2007;115,450-8.
27.Bansal S,Buring JE,Rifai N,et al.Fasting compared with nonfasting triglycerides and risk of cardiovascular events in women.JAMA,2007;298,309-16.
28.Jun M,Foote C,Lv J,et al.Effects of fibrates on cardiovascular outcomes:a systematic review and meta-analysis.Lancet,2010;375,1875-84.
29.Würtz P,Kangas A,Soininen P,et al.Lipoprotein subclass profiling reveals pleiotropy in the genetic variants of lipid risk factors for coronary heart disease:a note on Mendelian randomization studies.J Am Coll Cardiol,2013;62,1906-8.
30.Ridker PM,Rifai N,Cook NR,et al.Non-HDL cholesterol,apolipoproteins A-I and B100,standard lipid measures,lipid ratios,and CRP as risk factors for cardiovascular disease in women.JAMA,2005;294,326-33.
31.Catapano AL,Graham I,De Backer G,et al.2016 ESC/EASGuidelines for the Management of Dyslipidaemias.Eur Heart J,2016;37,2999-3058.
32.McQueen MJ,Hawken S,Wang X,et al.Lipids,lipoproteins,and apolipoproteins as risk markers of myocardial infarction in52 countries(the INTERHEART study):a case-control study.Lancet,2008;372,224-33.
33.Elshazly MB,Quispe R,Michos ED,et al.Patient-Level Discordance in Population Percentiles of the Total Cholesterol to High-Density Lipoprotein Cholesterol Ratio in Comparison With Low-Density Lipoprotein Cholesterol and Non-HighDensity Lipoprotein Cholesterol:The Very Large Database of Lipids Study(VLDL-2B).Circulation,2015;132,667-76.
34.Borghi C,Rodriguez-Artalejo F,De Backer G,et al.Serum uric acid levels are associated with cardiovascular risk score:A post hoc analysis of the EURIKA study.Int J Cardiol,2018;253,167-73.
35.Li X,Meng X,Timofeeva M,et al.Serum uric acid levels and multiple health outcomes:umbrella review of evidence from observational studies,randomised controlled trials,and Mendelian randomisation studies.BMJ,2017;357,j2376.
36.Liu XZ,Li HH,Huang S,et al.Association between hyperuricemia and nontraditional adiposity indices.Clin Rheumatol,2018 Nov 29.[Epub ahead of print]
37.Ndrepepa G.Uric acid and cardiovascular disease.Clin Chim Acta,2018;484,150-63.
2.Goff DC Jr,Lloyd-Jones DM,Bennett G,et al.2013 ACC/AHAguideline on the assessment of cardiovascular risk:a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines.J Am Coll Cardiol,2014;63,2935-59.
3.Liu J,Hong Y,D'Agostino RB Sr,et al.Predictive value for the Chinese population of the Framingham CHD risk assessment tool compared with the Chinese Multi-Provincial Cohort Study.JAMA,2004;291,2591-9.
4.Yang X,Li J,Hu D,et al.Predicting the 10-Year Risks of Atherosclerotic Cardiovascular Disease in Chinese Population:The China-PAR Project(Prediction for ASCVD Risk in China).Circulation,2016;134,1430-40.
5.Zhang M,Jiang Y,Wang LM,et al.Prediction of 10-year Atherosclerotic Cardiovascular Disease Risk among Adults Aged 40-79 Years in China:a Nationally Representative Survey.Biomed Environ Sci,2017;30,244-54.
6.WHO Expert Consultation.Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies.Lancet,2004;363,157-63.
7.American Diabetes Association.Standards of Medical Care in Diabetes-2018.Diabetes Care,2018;41,S144-51.
8.Liu XZ,Gao Y,Fan J,et al.Metabolic abnormalities in rheumatoid arthritis patients with comorbid diabetes mellitus.Clin Rheumatol,2018;37,219-26.
9.Li HH,Fan J,Huang S,et al.The prevalence of obesity and metabolic abnormalities in eastern China:A cross-sectional study.Int J Diabetes Dev Ctries,2019 Feb 20.[Epub ahead of print]
10.Johansson HE,W?hlén A,Aldenb?ck E,et al.Platelet Counts and Liver Enzymes After Gastric Bypass Surgery.Obes Surg,2018;28,1526-31.
11.Guerra-Silva NM,Santucci FS,Moreira RC,et al.Coronary disease risk assessment in men:Comparison between ASCVD Risk versus Framingham.Int J Cardiol,2017;228,481-7.
12.Yang XL,Chen JC,Li JX,et al.Risk stratification of atherosclerotic cardiovascular disease in Chinese adults.Chronic Dis Transl Med,2016;2,102-9.
13.Winham SJ,de Andrade M,Miller VM.Genetics of cardiovascular disease:Importance of sex and ethnicity.Atherosclerosis,2015;241,219-28.
14.Sun C,Xu F,Liu X,et al.Comparison of validation and application on various cardiovascular disease mortality risk prediction models in Chinese rural population.Sci Rep,2017;7,43227.
15.Colafella KMM,Denton KM.Sex-specific differences in hypertension and associated cardiovascular disease.Nat Rev Nephrol,2018;14,185-201.
16.Bray GA,Smith SR,de Jonge L,et al.Effect of dietary protein content on weight gain,energy expenditure,and body composition during overeating:a randomized controlled trial.JAMA,2012;307,47-55.
17.Paniagua L,Lohsoonthorn V,Lertmaharit S,et al.Comparison of waist circumference,body mass index,percent body fat and other measure of adiposity in identifying cardiovascular disease risks among Thai adults.Obes Res Clin Pract,2008;2,I-II.
18.Ouyang X,Lou Q,Gu L,et al.Anthropometric parameters and their associations with cardio-metabolic risk in Chinese working population.Diabetol Metab Syndr,2015;7,37.
19.Schneider HJ,Glaesmer H,Klotsche J,et al.Accuracy of anthropometric indicators of obesity to predict cardiovascular risk.J Clin Endocrinol Metab,2007;92,589-94.
20.Caan B,Armstrong MA,Selby JV,et al.Changes in measurements of body fat distribution accompanying weight change.Int J Obes Relat Metab Disord,1994;18,397-404.
21.Shao J,Yu L,Shen X,et al.Waist-to-height ratio,an optimal predictor for obesity and metabolic syndrome in Chinese adults.J Nutr Health Aging,2010;14,782-5.
22.Ashwell M,Gibson S.Waist to height ratio is a simple and effective obesity screening tool for cardiovascular risk factors:Analysis of data from the British National Diet And Nutrition Survey of adults aged 19-64 years.Obes Facts,2009;2,97-103.
23.Ashwell M,Gunn P,Gibson S.Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors:systematic review and meta-analysis.Obes Rev,2012;13,275-86.
24.Browning LM,Hsieh SD,Ashwell M.A systematic review of waist-to-height ratio as a screening tool for the prediction of cardiovascular disease and diabetes:0.5 could be a suitable global boundary value.Nutr Res Rev,2010;23,247-69.
25.Parish S,Offer A,Clarke R,et al.Lipids and lipoproteins and risk of different vascular events in the MRC/BHF Heart Protection Study.Circulation,2012;125,2469-78.
26.Sarwar N,Danesh J,Eiriksdottir G,et al.Triglycerides and the risk of coronary heart disease:10,158 incident cases among262,525 participants in 29 Western prospective studies.Circulation,2007;115,450-8.
27.Bansal S,Buring JE,Rifai N,et al.Fasting compared with nonfasting triglycerides and risk of cardiovascular events in women.JAMA,2007;298,309-16.
28.Jun M,Foote C,Lv J,et al.Effects of fibrates on cardiovascular outcomes:a systematic review and meta-analysis.Lancet,2010;375,1875-84.
29.Würtz P,Kangas A,Soininen P,et al.Lipoprotein subclass profiling reveals pleiotropy in the genetic variants of lipid risk factors for coronary heart disease:a note on Mendelian randomization studies.J Am Coll Cardiol,2013;62,1906-8.
30.Ridker PM,Rifai N,Cook NR,et al.Non-HDL cholesterol,apolipoproteins A-I and B100,standard lipid measures,lipid ratios,and CRP as risk factors for cardiovascular disease in women.JAMA,2005;294,326-33.
31.Catapano AL,Graham I,De Backer G,et al.2016 ESC/EASGuidelines for the Management of Dyslipidaemias.Eur Heart J,2016;37,2999-3058.
32.McQueen MJ,Hawken S,Wang X,et al.Lipids,lipoproteins,and apolipoproteins as risk markers of myocardial infarction in52 countries(the INTERHEART study):a case-control study.Lancet,2008;372,224-33.
33.Elshazly MB,Quispe R,Michos ED,et al.Patient-Level Discordance in Population Percentiles of the Total Cholesterol to High-Density Lipoprotein Cholesterol Ratio in Comparison With Low-Density Lipoprotein Cholesterol and Non-HighDensity Lipoprotein Cholesterol:The Very Large Database of Lipids Study(VLDL-2B).Circulation,2015;132,667-76.
34.Borghi C,Rodriguez-Artalejo F,De Backer G,et al.Serum uric acid levels are associated with cardiovascular risk score:A post hoc analysis of the EURIKA study.Int J Cardiol,2018;253,167-73.
35.Li X,Meng X,Timofeeva M,et al.Serum uric acid levels and multiple health outcomes:umbrella review of evidence from observational studies,randomised controlled trials,and Mendelian randomisation studies.BMJ,2017;357,j2376.
36.Liu XZ,Li HH,Huang S,et al.Association between hyperuricemia and nontraditional adiposity indices.Clin Rheumatol,2018 Nov 29.[Epub ahead of print]
37.Ndrepepa G.Uric acid and cardiovascular disease.Clin Chim Acta,2018;484,150-63.