Predictors of risk level for developing cardiovascular disease in patient with hypertension
Keywords:
cardiovascular risk factors, Framingham risk score, hypertensionAbstract
This observation and crossectional study aimed to examine whether the major and minor risk factors predicted the risk level for developing CVD in person with hypertension. Participants were 492 patients attending four rural health promotion hospital in Nakhon Si Thammarat. CVD risk levels were classified into mild, moderate and high-risk groups based on the Framingham Global Risk Scoring algorithms. CVD risk scoring was calculate based on each individual six major risk factors included age, systolic blood pressure (SBP), high-density lipoprotein (HDL), total cholesteral (CHO), diabetes (DM), and smoking. Only one minor risk factor was negatively correlation Minor risk factors were boy mass index (BMI), waist circumference (WC), low-density lipoprotein (LDL), and triglyceride. Logistic regression analysis was used to test the predictive model with an odds ratio and 95% confident interval.
We found that two-fifth of the sample were at the high-risk level, three-fouth had hypertension stage 1. Over a half were older adult, had high cholesteral, hyperglycemia and low HDL. One-fouth (23.9%) of the high-risk group were current smokers. Univarite model found that all six major risk factors were positivtly correlated with high-risk level. Increment risk was found in advanced age, higher SBP, higher CHO, lower HDL, DM and smoking. Only one minor risk factor, waist circumference (WC) was negatively correlated with a high-risk level. Persons with abdominal obese had lower risk than those with normal waist. A model of the major risk factor was accounted for 82.5% of the variance explained on the high risk for CVD. When the four minor risk factors were added to the major risk factors model, the variance of the predictive model was increased to 84.1%.
This study suggests that health care providers should develop CVD risk prevention program in persons with hypertension by reduce of these major and minor risk factors. Raising risk awareness
should be more consider in non-elder and non-obse, those who had higher risk for developing CVD.
References
World Health Organization (WHO). Global status report on noncommunicable diseases 2014. Geniva, Switzerland: WHO; 2014.
International Health Policy Program. Disability-adjust life year: DALY report 2013. Burden of Disease Research Program Thailand (BOD Thailand), Nonthaburi: Ministry of Public Health Thailand; 2013. (in Thai)
Bureua of Non Communicable Disease. Annual Report 2016 NCD. Bureua of Non Communicable Disease, Nonthaburi: Ministry of Public Health Thailand; 2016. (in Thai)
Chookheaw J, Suwanno J, Sameanphet T. Predictors of risk level of developing coronary heart disease in women with hypertension attending a rural community hospital. Journal of Nursing Division. 2013; 40(1) :39-56. (in Thai)
Kaewbangpood T, Suwanno J, Thiamwong L. Predictors of the ten-year risk level for developing coronary heart disease in rural older adults. Journal of Nursing and Health Science. 2015; 33(3): 174-84. (in Thai)
Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL, et al. for the National Heart, Lung, and Blood Institute Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure; National High Blood Pressure Education Program Coordinating Committee. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 Report. JAMA. 2003; 289(19): 2560-72.
D'Agostino RB, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM, et al. General cardiovascular risk profile for use in primary care: the Framingham Heart study. Circulation. 2008; 117(6): 743-53.
Asia Pacific Cohort Studies Collaboration. Central obesity and risk of cardiovascular disease in the Asia Pacific Region. Asia Pac J Clin Nutr. 2006; 15(3): 287-92.
Ni Mhurchu C, Rodgers A, Pan WH, Gu DF, Woodward M, for the Asia Pacific Cohort Studies Collaboration. Body mass index and cardiovascular disease in the Asia-Pacific Region: an overview of 33 cohorts involving 310 000 participants. Int J Epidemiol. 2004; 33(4): 751-8.
Grundy SM, Becker D, Clark LT, Cooper RS, Denke MA, Howard JW, et al. for the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). The Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) Final Report. Circulation. 2002; 106(25): 3143-421.
Damen JAAE, Hooft L, Schuit E, Debray TPA, Collins GS, Tzoulaki L, et al. Prediction models for cardiovascular disease risk in the general population: systematic review. BMJ. 2016; 353: i2416. doi:https://doi.org/10.1136/bmj.i2416.
Grundy SM, Pasternak R, Greenland P, Smith S, Fuster V. Assessment of cardiovascular risk by use of multiple-risk-factor assessment equations: a Statement for Healthcare Professionals from the American Heart Association and the American College of Cardiology. Circulation. 1999; 100: 1481-92.
Conroy RM, Pyörälä K, Fitzgerald AP, Sans S, Menotti A, De Backer G, et al. on behalf of the SCORE project group. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J. 2003; 24(11): 987-1003.
Mendis S, Lindholm LH, Mancia G, Whitworth J, Alderman M, Lim S, et al. World Health Organization (WHO) and International Society of Hypertension (ISH) risk prediction charts: assessment of cardiovascular risk for prevention and control of cardiovascular disease in low and middle-income countries. J Hypertens. 2007; 25(8): 1578-82.
Selvarajah S, Kaur G, Haniff J, Cheong KC, Hiong TG, van der Graaf Y, et al. Comparison of the Framingham Risk Score, SCORE and WHO/ISH cardiovascular risk prediction model in an Asian population. Int J Cardiol. 2014; 176(1): 211-8.
Neuman B. The Neuman Systems Model (3rd ed.). Norwalk, CT: Appleton & Lange; 1995.
Brandes RP. Endothelial dysfunction and hypertension. Hypertension. 2014; 64(5): 924-8.
Marinou K, Tousoulis D, Antonopoulos AS, Stafanadi E, Stafanadis C. Obesity and cardiovascular disease: from pathophysiology to risk stratification. Int J Cardiol. 2010; 138(1): 3-8.
Yamane T. Statistics: An introductory analysis. NY: New York Harper and Row; 1973.
Zhou M, Offer A, Yang G, Smith M, Hui G, Whitlock G, et.al. Body mass index, blood pressure, and mortality from stroke: a nationally representative prospective study of 212,000 Chinese men. Stroke. 2008; 39(3): 753-9.
Lavie CJ, Milani RV, Ventura HC. Obesity and cardiovascular disease risk factor, paradox, and impact of weight loss. J Am Coll Cardiol. 2009; 53(21): 1925-32.
RAMA-EGAT Cohort Study. RAMA-EGAT Heart Score. [cited 2019, August 16]. Available from: https://med.mahidol.ac.th/cvmc/th/event/ramaegatheartscore (in Thai).
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