Cancer Causes & Control

, Volume 18, Issue 5, pp 571–579

Point and interval estimates of partial population attributable risks in cohort studies: examples and software

Authors

    • Departments of Epidemiology, School of Public HealthHarvard University
    • Departments of Biostatistics, School of Public HealthHarvard University
  • E. Hertzmark
    • Departments of Epidemiology, School of Public HealthHarvard University
  • H. C. Wand
    • National Center in HIV Epidemiology and Clinical ResearchUniversity of New South Wales
Original Paper

DOI: 10.1007/s10552-006-0090-y

Cite this article as:
Spiegelman, D., Hertzmark, E. & Wand, H.C. Cancer Causes Control (2007) 18: 571. doi:10.1007/s10552-006-0090-y

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.

Keywords

Population attributable riskRelative riskEpidemiologic methodsCohort studiesStatisticsBurden of disease

Copyright information

© Springer Science+Business Media B.V. 2007