title: Point and interval estimates of partial population attributable risks in cohort studies: examples and software.
abstract: The concept of the population attributable risk (PAR) percent has found widespread application in public health research. This quantity describes the proportion of a disease which could be prevented if a specific exposure were to be eliminated from a target population. We present methods for obtaining point and interval estimates of partial PARs, where the impact on disease burden for some presumably modifiable determinants is estimated in, and applied to, a cohort study. When the disease is multifactorial, the partial PAR must, in general, be used to quantify the proportion of disease which can be prevented if a specific exposure or group of exposures is eliminated from a target population, while the distribution of other modifiable and non-modifiable risk factors is unchanged. The methods are illustrated in a study of risk factors for bladder cancer incidence (Michaud DS et al., New England J Med 340 (1999) 1390). A user-friendly SAS macro implementing the methods described in this paper is available via the worldwide web.
authors: Department of Epidemiology, School of Public Health, Harvard University, 677 Huntington Avenue, Boston, MA 02115, USA. stdls@channing.harvard.edu
authors: D
authors: D
authors: Spiegelman
authors: E
authors: E
authors: Hertzmark
authors: H C
authors: HC
authors: Wand
mesh_terms: D000465:Algorithms; D015331:Cohort Studies; D017281:Cost of Illness; D004327:Drinking Behavior; D006293:Health Promotion; D006801:Humans; D008297:Male; D015233:Models, Statistical; D016012:Poisson Distribution; D015995:Prevalence; D011322:Primary Prevention; D012044:Regression Analysis; D012307:Risk Factors; D012907:Smoking / Q000009:adverse effects; D012984:Software; D001749:Urinary Bladder Neoplasms / Q000453:epidemiology / Q000517:prevention & control