1998
DOI: 10.2105/ajph.88.1.15
|View full text |Cite
|
Sign up to set email alerts
|

Use and misuse of population attributable fractions.

Abstract: IntroductionHow much of the disease burden in a population could be eliminated if the effects of certain causal factors were eliminated from the population? To address this question, epidemiologists calculate the population attributable fraction. As noted in a recent editorial in the Journal, population attributable fraction estimates can help guide policymakers in planning public health interventions.' Despite numerous articles on population attributable fraction estimation, 2-7 errors in computation and inte… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

5
1,272
2
24

Year Published

2005
2005
2018
2018

Publication Types

Select...
10

Relationship

0
10

Authors

Journals

citations
Cited by 1,453 publications
(1,303 citation statements)
references
References 31 publications
5
1,272
2
24
Order By: Relevance
“…Furthermore, the prevalence of both depression and LBP concurrently is high, and the increased risk of LBP observed in our review can have substantial implications. If we apply our summary OR to the worldwide prevalence of depression, we can estimate the population proportional attributable risk as the following: prevalence of depression 3 (OR 2 1)/(1 1 prevalence of depression) 3 (OR 2 1) (45), where the OR, in this example, is the OR from our overall pooling results. Considering a 12-month prevalence of depression of 6% (46), the population attributable risk would be 3.4%.…”
Section: Discussionmentioning
confidence: 99%
“…Furthermore, the prevalence of both depression and LBP concurrently is high, and the increased risk of LBP observed in our review can have substantial implications. If we apply our summary OR to the worldwide prevalence of depression, we can estimate the population proportional attributable risk as the following: prevalence of depression 3 (OR 2 1)/(1 1 prevalence of depression) 3 (OR 2 1) (45), where the OR, in this example, is the OR from our overall pooling results. Considering a 12-month prevalence of depression of 6% (46), the population attributable risk would be 3.4%.…”
Section: Discussionmentioning
confidence: 99%
“…1 Second, the methods we used to calculate aggregate healthcare expenditures associated with excess body weight are widely accepted, 12,14,15,20,23 but those methods are more appropriately applied to incidentFnot prevalentFconditions and assume no confounding of the exposure-outcome relationship. 24 In this analysis, the obesity-expenditure relationship may be confounded by unmeasured health conditions (eg physical disability). Further research is needed to establish an unbiased method of calculating estimates of obesity-attributable expenditures, accounting for the complex causal relationships between body weight and chronic medical conditions.…”
Section: Discussionmentioning
confidence: 99%
“…We compared the prevalence of each AV category between the 5 identified trajectories in analyses adjusted for age, sex, race, and center. To determine the population attributable risk for AV dysfunction (sclerosis or stenosis) associated with low percentage attained CVHS (<50%, <60%, <70%, or <80%), we used the prevalence among cases and the odds ratio estimate to calculate the percentage population attributable risk using the following formulation23: population attributable risk%=pd i ×[RR i −1/RR i ], where pd i is the proportion of total cases in the population arising from the i th exposure category and RR i is the adjusted risk ratio for the i th exposure category. A 2‐sided P value of <0.05 was considered significant.…”
Section: Methodsmentioning
confidence: 99%