title: Cumulative risk and population attributable fraction in prevention.
abstract: Compares the use of relative risk versus population attributable fraction in determining the target population for multirisk prevention programs in psychology. Results show that relative risk generally increases as a function of cumulative risk. Guided by this measure, prevention programs should target populations with the largest cumulative risk. However, relative risk does not account for the prevalence of a particular level of cumulative risk in the population. Therefore, because the largest cumulative risk is experienced by only a small portion of the population, prevention programs guided by this measure will not always have the greatest public health benefit to reduce the incidence of problem outcomes in the population. On the other hand, the population attributable fraction, which does take into account the prevalence of a particular level of cumulative risk, does not increase appreciably after a cumulative risk of one, two, or three because the majority of people in the population will experience these levels of cumulative risk. Guided by this measure, prevention programs that target the higher proportion of people who have a more moderate level of risk would have the maximum impact on the population. National data sets from Great Britain (the British Births Cohort Study [BCS]) and the United States (National Longitudinal Study of Youth [NLSY]) are used to explore this pattern of effects.
authors.affiliation: Department of Psychology, Arizona State University, Tempe 85283, USA. caroline.davis@asu.edu
authors.forename: Caroline H
authors.initials: CH
authors.lastname: Davis
authors.forename: David P
authors.initials: DP
authors.lastname: MacKinnon
authors.forename: Amy
authors.initials: A
authors.lastname: Schultz
authors.forename: Irwin
authors.initials: I
authors.lastname: Sandler
mesh_terms: D000293:Adolescent; D002648:Child; D002653:Child Behavior Disorders / Q000453:epidemiology* / Q000209:etiology / Q000517:prevention & control; D015331:Cohort Studies; D003430:Cross-Sectional Studies; D003627:Data Interpretation, Statistical; D015340:Epidemiologic Research Design; D006801:Humans; D008137:Longitudinal Studies; D016017:Odds Ratio; D017063:Outcome Assessment, Health Care; D016730:Program Development / Q000706:statistics & numerical data; D012306:Risk; D006113:United Kingdom; D014481:United States