Cited by 174Cardiovascular Disease and AdiposityDiabetes, Cardiovascular Risks, and LipoproteinsCardiovascular Health and Risk Factors

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Prediction of First Events of Coronary Heart Disease and Stroke With Consideration of Adiposity

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Wilson, Peter W.F., Bozeman, Samuel R., Burton, Tanya M., Hoaglin, David C., Ben-Joseph, Rami, Pashos, Chris L.·2008·Circulation

DOI 10.1161/circulationaha.108.772962

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Abstract

Background— Prediction of coronary heart disease (CHD) and cerebrovascular disease (CeVD) can aid healthcare providers and prevention programs. Previous reports have focused on traditional cardiovascular risk factors; less information has been available on the role of overweight and obesity. Methods and Results— Baseline data from 4780 Framingham Offspring Study adults with up to 24 years of follow-up were used to assess risk for a first CHD event (angina pectoris, myocardial infarction, or cardiac death) alone, first CeVD event (acute brain infarction, transient ischemic attack, and stroke-related death) alone, and CHD and CeVD events combined. Accelerated failure time models were developed for the time of first event to age, sex, cholesterol, high-density lipoprotein cholesterol, diabetes mellitus (DM), systolic blood pressure, smoking status, and body mass index (BMI). Likelihood-ratio tests of statistical significance were used to identify the best-fitting predictive functions. Age, sex, smoking status, systolic blood pressure, ratio of cholesterol to high-density lipoprotein cholesterol, and presence of DM were highly related ( P <0.01 for all) to the development of first CHD events, and all of the above except sex and DM were highly related to the first CeVD event. BMI also significantly predicted the occurrence of CHD ( P =0.05) and CeVD ( P =0.03) in multivariable models adjusting for traditional risk factors. The magnitude of the BMI effect was reduced but remained statistically significant when traditional variables were included in the prediction models. Conclusions— Greater BMI, higher systolic blood pressure, higher ratio of cholesterol to high-density lipoprotein cholesterol, and presence of DM were all predictive of first CHD events, and all but the presence of DM were predictive of first CeVD events. These results suggest that common pathophysiological mechanisms underlie the roles of BMI, DM, and systolic blood pressure as predictors for first CHD and CeVD events.

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Applied logistic regression
(1990) · Choice Reviews Online · doi:10.5860/choice.27-3338 · Cited by 35,305
Summary of the second report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel II)
Grundy, S. M., Bilheimer, D. W., Chait, A., Clark, L. T., Denke, M. A., Havel, R. J., Hazzard, W. R., Hulley, S. B., Hunninghake, D. B., Kreisberg, R. A., et al. (1993) · JAMA · doi:10.1001/jama.269.23.3015 · Cited by 27,944
Executive Summary of 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)
Expert Panel on Detection, E. (2001) · JAMA: The Journal of the American Medical Association · doi:10.1001/jama.285.19.2486 · Cited by 26,011
Applied Logistic Regression
Hosmer, D. W., & Lemeshow, S. (2000) · doi:10.1002/0471722146 · Cited by 20,302
Prediction of coronary heart disease using risk factor categories
Wilson, P. W. F., D’Agostino, R. B., Levy, D., Belanger, A. M., Silbershatz, H., & Kannel, W. B. (1998) · Circulation · doi:10.1161/01.cir.97.18.1837 · Cited by 9,581
Self-citation
Regression Modeling Strategies
Harrell, F. E. (2001) · Springer series in statistics · doi:10.1007/978-1-4757-3462-1 · Cited by 9,270
General Cardiovascular Risk Profile for Use in Primary Care: The Framingham Heart Study
D’Agostino, R. B., Vasan, R. S., Pencina, M. J., Wolf, P. A., Cobain, M., Massaro, J. M., & Kannel, W. B. (2008) · Circulation · doi:10.1161/circulationaha.107.699579 · Cited by 7,491
Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project
Conroy, R. (2003) · European Heart Journal · doi:10.1016/s0195-668x(03)00114-3 · Cited by 5,290
Validation of the Framingham Coronary Heart Disease Prediction Scores: Results of a Multiple Ethnic Groups Investigation
D'Agostino, R. B., Grundy, S., Sullivan, L. M., Wilson, P., & for the CHD Risk Prediction Group (2001) · JAMA · doi:10.1001/jama.286.2.180 · Cited by 2,108
Self-citation
An updated coronary risk profile. A statement for health professionals.
Anderson, K. M., Wilson, P. W., Odell, P. M., & Kannel, W. B. (1991) · Circulation · doi:10.1161/01.cir.83.1.356 · Cited by 1,834
Self-citation

Show all 19 references

Research works printed but not linked: 3

10.1161/circ.105.3.310 · DOI
10.1161/circ.97.18.1837 · DOI
Rothman KJ Greenland S. Modern Epidemiology. 2nd ed. Philadelphia Pa: Lippincott Williams and Wilkins; 1998.

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Authors: Wilson, P. W. F., Bozeman, S. R., Burton, T. M., Hoaglin, D. C., Ben-Joseph, R., & Pashos, C. L.
Affiliations: Emory University (US)
ORCID: Wilson, Peter W.F.
Hoaglin, David C.
Ben-Joseph, Rami
Pashos, Chris L.
Venue: Circulation
Publisher: Ovid Technologies (Wolters Kluwer Health)
Published: 2008-07-08
Volume: 118
Issue: 2
Pages: 124-130
ISSN: 0009-7322 (ISSN-L)
1524-4539
DOI: 10.1161/circulationaha.108.772962
OpenAlex: W2007287562
Cited by: 174
References: 19
Citations by year: 2026: 8 · 2025: 11 · 2024: 7 · 2023: 8 · 2022: 7 · 2021: 11 · 2020: 5 · 2019: 3 · 2018: 5 · 2017: 13 · 2016: 12 · 2015: 7 · 2014: 7 · 2013: 7 · 2012: 13
FWCI: 11.80
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: Circulation (publishedVersion)
PubMed (publishedVersion)
Funders: Sanofi
Topics: Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Disease and Adiposity
Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
Keywords: coronary artery disease, stroke, cerebrovascular disease, adiposity, body mass index, cardiovascular risk prediction, accelerated failure time model, Framingham Offspring Study, systolic blood pressure, diabetes mellitus, TC/HDL-C ratio, angina pectoris, myocardial infarction, transient ischemic attack, premature atherosclerosis
MeSH terms: Adult, Cholesterol, Coronary Disease, Diabetes Mellitus, Humans, Hypertension, Male, Middle Aged, Predictive Value of Tests, Risk Factors, Body Mass Index, Risk Assessment, Stroke, Adiposity

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Prediction of First Events of Coronary Heart Disease and Stroke With Consideration of Adiposity

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