Risk factors for progression of atherosclerosis measured at multiple sites in the arterial tree: the Rotterdam Study.
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BACKGROUND AND PURPOSE: Studies investigating determinants of atherosclerotic disease progression are relatively rare. Moreover, although atherosclerotic disease can be assessed noninvasively in different vascular beds, previous studies have not considered progression of atherosclerosis at >1 site. The present study was designed to identify risk factors for progression of atherosclerosis measured at multiple sites in the arterial tree. METHODS: The Rotterdam Study is a population-based cohort study of 7983 men and women > or =55 years of age. Carotid plaques and intima-media thickness were assessed by ultrasound, aortic atherosclerosis by x-ray, and lower-extremity atherosclerosis by the ankle-arm index. Data on progression of atherosclerosis over an average period of 6.5 years were available for 3409 participants. Associations of established cardiovascular risk factors with mild, moderate, and severe progression of atherosclerosis were investigated through multinomial regression analysis. RESULTS: Age, smoking, total cholesterol, and systolic blood pressure and/or hypertension were strong, independent predictors of moderate and severe progression of atherosclerosis at multiple sites. Diabetes mellitus predicted only severe progression of atherosclerosis. Associations of sex with progression of atherosclerosis were remarkably modest. CONCLUSIONS: Age, smoking, total cholesterol, and systolic blood pressure and/or hypertension strongly predict progression of extracoronary atherosclerosis in the elderly, but sex remarkably does not. These results emphasize the need for prevention of progression of extracoronary atherosclerotic disease in men and women alike.
- Cohort Studies
- Research Support, Non-U.S. Gov't
- Sex Distribution
- Follow-Up Studies
- Prospective Studies
- Risk Factors
- Middle Aged
- Sex Factors
- Disease Progression
- Odds Ratio
- Risk Assessment
- Diagnostic Techniques, Cardiovascular/statistics & numerical data