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Multicenter Study
. 2014 Jul;7(4):597-602.
doi: 10.1161/CIRCOUTCOMES.113.000531. Epub 2014 Jul 1.

Prediction of 30-year risk for cardiovascular mortality by fitness and risk factor levels: the Cooper Center Longitudinal Study

Chanaka D Wickramasinghe  1 , Colby R Ayers  1 , Sandeep Das  1 , James A de Lemos  1 , Benjamin L Willis  1 , Jarett D Berry  2
Affiliations
Multicenter Study

Prediction of 30-year risk for cardiovascular mortality by fitness and risk factor levels: the Cooper Center Longitudinal Study

Chanaka D Wickramasinghe et al. Circ Cardiovasc Qual Outcomes. 2014 Jul.

Abstract

Background: Fitness and traditional risk factors have well-known associations with cardiovascular disease (CVD) death in both short-term (10 years) and across the remaining lifespan. However, currently available short-term and long-term risk prediction tools do not incorporate measured fitness.

Methods and results: We included 16 533 participants from the Cooper Center Longitudinal Study (CCLS) without prior CVD. Fitness was measured using the Balke protocol. Sex-specific fitness levels were derived from the Balke treadmill times and categorized into low, intermediate, and high fit according to age- and sex-specific treadmill times. Sex-specific 30-year risk estimates for CVD death adjusted for competing risk of non-CVD death were estimated using the cause-specific hazards model and included age, body mass index, systolic blood pressure, fitness, diabetes mellitus, total cholesterol, and smoking. During a median follow-up period of 28 years, there were 1123 CVD deaths. The 30-year risk estimates for CVD mortality derived from the cause-specific hazards model demonstrated overall good calibration (Nam-D'Agostino χ(2) [men, P=0.286; women, P=0.664] and discrimination (c statistic; men, 0.81 [0.80-0.82] and women, 0.86 [0.82-0.91]). Across all risk factor strata, the presence of low fitness was associated with a greater 30-year risk for CVD death.

Conclusions: Fitness represents an important additional covariate in 30-year risk prediction functions that may serve as a useful tool in clinical practice.

Keywords: cardiovascular diseases; mortality; risk factors.

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Figures

Figure 1:
Figure 1:
Calibration by deciles of predicted 30 year risk of CVD for Men and Women; CVD: cardiovascular disease.
Figure 1:
Figure 1:
Calibration by deciles of predicted 30 year risk of CVD for Men and Women; CVD: cardiovascular disease.
Figure 2:
Figure 2:
Risk for CVD mortality (%) according to selected risk factors and fitness strata in 50 year-old men (2a) and women (2b) over 30 years. Figure 2 reflects estimated 30-year risk for CVD mortality adjusted for competing risk in 50 year old man with systolic blood pressure of 160mmHg according to low, intermediate, and high fitness levels (in METs); Figure 2 reflects estimated 30-year risk for CVD mortality adjusted for competing risk in 50 year old woman with diabetes mellitus according to low, intermediate, and high fitness levels (in METs). CVD: cardiovascular disease; METs = metabolic equivalents.
Figure 3:
Figure 3:
Estimated 30-year risk for CVD Mortality for 50-year old men and women by risk factor and fitness categories. Risk estimates are derived from risk calculator according to the presence (+) or absence (−) of risk factors (as defined below) and stratified by high fitness (men: 12 METs; women 10 METs) or low fitness (men 8 METs; women 6 METs). CVD: cardiovascular disease; HTN: hypertension (160 mmHg); DM: diabetes mellitus (present); T.Chol: total cholesterol (240mg/dl) Smoking: (present), and BMI: body mass index (25kg/m2).
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References

    1. Lloyd-Jones DM, Wilson PWF, Larson MG, Beiser A, Leip EP, D’Agostino RB, Levy D . Framingham Risk Score and Prediction of Lifetime Risk for Coronary Heart Disease. Am J Cardiol. 2004;94:20–24. - PubMed
    1. Lloyd-Jones DM, Dyer AR, Wang R, Daviglus ML, Greenland P. Risk factor burden in middle age and lifetime risks for cardiovascular and non-cardiovascular death (Chicago Heart Association Detection Project in Industry). Am J Cardiol. 2007;99:535–40. - PMC - PubMed
    1. Berry JD, Liu K, Folsom AR, et al..Prevalence and progression of subclinical atherosclerosis in younger adults with low short-term but high lifetime estimated risk for cardiovascular disease: the coronary artery risk development in young adults study and multi-ethnic study of atherosclerosis. Circulation. 2009;119:382–9. - PMC - PubMed
    1. Berry JD, Dyer A, Cai X, Garside DB, Ning H, Thomas Greenland P, Horn LV, Tracy RP, Lloyd-Jones DM. Lifetime Risks of Cardiovascular Disease. N Engl J Med. 2012; 366:321–329. - PMC - PubMed
    1. Mosca L, Benjamin EJ, Berra K, Bezanson JL, Dolor RJ, Lloyd-Jones DM, Newby LK, Piña IL, Roger VL, Shaw LJ, Zhao D, Beckie TM, Bushnell C, D’Armiento J, Kris-Etherton PM, Fang J, Ganiats TG, Gomes AS, Gracia CR, Haan CK, Jackson EA, Judelson DR, Kelepouris R, Lavie CJ, Moore A, Nussmeier NA, Ofili E, Oparil S, Ouyang P, Pinn VW, Sherif K, Smith SC, Sopko G, Chandra-Strobos N, Urbina EM, Vaccarino V, Wenger NK. Effectiveness-Based Guidelines for the Prevention of Cardiovascular Disease in Women - 2011 Update: A Guideline From the American Heart Association. Circulation. 2011;123:1243–1262. - PMC - PubMed

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