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Most studies of the etiology and prevention of disease do not adequately address the quantitative implications of their findings for the population. This report presents a method of combining observational and experimental data to estimate the overall impact of a risk factor modification program. After the terminology is introduced, the model is applied to a categoric risk factor (serum cholesterol) for coronary heart disease, with data from the Pooling Project (1964-1974) and the Lipid Research Clinics studies (1972-1983). With optimistic assumptions about the impact of cholestyramine treatment at various cholesterol levels, about 5% of the cases of coronary heart disease in middle-aged men in the United States could be prevented; more realistic assumptions reduce that estimate by more than half. The model emphasizes the importance of estimating and comparing the overall impact of available risk factor modification programs when planning public health strategies.
Warren S. Browner (Wed,) studied this question.