Predicting the Risk of Incident Hypertension in a Korean Middle-aged Population: Korean Genome and Epidemiology Study

Overview

Journal J Clin Hypertens (Greenwich)

Specialty Cardiology & Vascular Diseases

Date 2013 Apr 26

PMID 23614850

Citations 26

Authors

Nam-Kyoo Lim

Kuk-Hui Son

Kwang-Soo Lee

Hyeon-Young Park

Myeong-Chan Cho

Affiliations

Soon will be listed here.

Abstract

The objectives of this study were to construct a risk score for predicting incident hypertension by using the Korean Genome and Epidemiology Study (KoGES) data and to compare the performance between KoGES and the Framingham model. A total of 4747 participants were analyzed. The entire cohort was randomly assigned to derivation and validation sets at a ratio of 6:4. A hypertension risk score was developed based on the derivation cohort, using the same risk factors that were used for developing the Framingham hypertension risk score. The accuracy of KoGES and Framingham models was evaluated in terms of calibration and discrimination. The area under receiver operating characteristic (AROC) curves were 0.789 for the Framingham model and 0.791 for the KoGES model. The AROC calculated for the point-based risk score was 0.790, which is almost identical to that for the KoGES model. The Framingham model showed poor agreement (χ(2) =29.73, P=.0002) and underestimated the risk of hypertension in most deciles of predicted risk. The model based on KoGES yielded results similar to the observed risk of hypertension (χ(2) =4.17, P=.8415). This study demonstrates that the Framingham risk score based on data from a non-Korean population can lead to the underestimation of the prediction risk of hypertension.

Citing Articles

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References

Chen J . Epidemiology of hypertension and chronic kidney disease in China. Curr Opin Nephrol Hypertens. 2010; 19(3):278-82. PMC: 2911788. DOI: 10.1097/MNH.0b013e328337f921. View

Kyrou I, Chrousos G, Tsigos C . Stress, visceral obesity, and metabolic complications. Ann N Y Acad Sci. 2006; 1083:77-110. DOI: 10.1196/annals.1367.008. View

Lee L, Watson M, Mulvaney C, Tsai C, Lo S . The effect of walking intervention on blood pressure control: a systematic review. Int J Nurs Stud. 2010; 47(12):1545-61. DOI: 10.1016/j.ijnurstu.2010.08.008. View

Muntner P, Woodward M, Mann D, Shimbo D, Michos E, Blumenthal R . Comparison of the Framingham Heart Study hypertension model with blood pressure alone in the prediction of risk of hypertension: the Multi-Ethnic Study of Atherosclerosis. Hypertension. 2010; 55(6):1339-45. PMC: 3023992. DOI: 10.1161/HYPERTENSIONAHA.109.149609. View

Fuchs F, Fuchs S, Moreira L, Gus M, Nobrega A, Poli-de-Figueiredo C . Prevention of hypertension in patients with pre-hypertension: protocol for the PREVER-prevention trial. Trials. 2011; 12:65. PMC: 3059277. DOI: 10.1186/1745-6215-12-65. View

Shin C, Abbott R, Lee H, Kim J, Kimm K . Prevalence and correlates of orthostatic hypotension in middle-aged men and women in Korea: the Korean Health and Genome Study. J Hum Hypertens. 2004; 18(10):717-23. DOI: 10.1038/sj.jhh.1001732. View

Chien K, Hsu H, Su T, Chang W, Sung F, Chen M . Prediction models for the risk of new-onset hypertension in ethnic Chinese in Taiwan. J Hum Hypertens. 2010; 25(5):294-303. DOI: 10.1038/jhh.2010.63. View

Wofford M, Hall J . Pathophysiology and treatment of obesity hypertension. Curr Pharm Des. 2004; 10(29):3621-37. DOI: 10.2174/1381612043382855. View

Parikh N, Pencina M, Wang T, Benjamin E, Lanier K, Levy D . A risk score for predicting near-term incidence of hypertension: the Framingham Heart Study. Ann Intern Med. 2008; 148(2):102-10. DOI: 10.7326/0003-4819-148-2-200801150-00005. View

10.

DAgostino Sr R, Grundy S, Sullivan L, Wilson P . Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. JAMA. 2001; 286(2):180-7. DOI: 10.1001/jama.286.2.180. View

11.

Djousse L, Mukamal K . Alcohol consumption and risk of hypertension: does the type of beverage or drinking pattern matter?. Rev Esp Cardiol. 2009; 62(6):603-5. DOI: 10.1016/s1885-5857(09)72223-6. View

12.

Kshirsagar A, Chiu Y, Bomback A, August P, Viera A, Colindres R . A hypertension risk score for middle-aged and older adults. J Clin Hypertens (Greenwich). 2010; 12(10):800-8. PMC: 3683833. DOI: 10.1111/j.1751-7176.2010.00343.x. View

13.

Kivimaki M, Batty G, Singh-Manoux A, Ferrie J, Tabak A, Jokela M . Validating the Framingham Hypertension Risk Score: results from the Whitehall II study. Hypertension. 2009; 54(3):496-501. PMC: 2828464. DOI: 10.1161/HYPERTENSIONAHA.109.132373. View

14.

Franklin S, Gustin 4th W, Wong N, Larson M, Weber M, Kannel W . Hemodynamic patterns of age-related changes in blood pressure. The Framingham Heart Study. Circulation. 1997; 96(1):308-15. DOI: 10.1161/01.cir.96.1.308. View

15.

Haslam D, James W . Obesity. Lancet. 2005; 366(9492):1197-209. DOI: 10.1016/S0140-6736(05)67483-1. View

16.

Schultz M, Hordern M, Leano R, Coombes J, Marwick T, Sharman J . Lifestyle change diminishes a hypertensive response to exercise in type 2 diabetes. Med Sci Sports Exerc. 2010; 43(5):764-9. DOI: 10.1249/MSS.0b013e3181fcf034. View

17.

Hosmer D, Hosmer T, le Cessie S, Lemeshow S . A comparison of goodness-of-fit tests for the logistic regression model. Stat Med. 1997; 16(9):965-80. DOI: 10.1002/(sici)1097-0258(19970515)16:9<965::aid-sim509>3.0.co;2-o. View

18.

DeLong E, Delong D, Clarke-Pearson D . Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988; 44(3):837-45. View

19.

Lawes C, Vander Hoorn S, Rodgers A . Global burden of blood-pressure-related disease, 2001. Lancet. 2008; 371(9623):1513-8. DOI: 10.1016/S0140-6736(08)60655-8. View

20.

Gaziano T, Bitton A, Anand S, Weinstein M . The global cost of nonoptimal blood pressure. J Hypertens. 2009; 27(7):1472-7. DOI: 10.1097/HJH.0b013e32832a9ba3. View