Population attributable fraction

Alternatively, one can directly estimate the PAF original formula “(O − E)/O” using results from a multivariable logistic regression model.7 As an example of the latter approach, the authors of a recent BMJ paper8 calculated the population attributable fraction (PAF) of concurrent benzodiazepine/opi...

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Bibliographic Details
Published in:BMJ (Online) Vol. 360; p. k757
Main Authors: Mansournia, Mohammad Ali, Altman, Douglas G
Format: Journal Article
Language:English
Published: England British Medical Journal Publishing Group 22.02.2018
BMJ Publishing Group LTD
Subjects:
Data Interpretation, Statistical
Environmental Exposure
Epidemiologic Methods
Epidemiology
Health risk assessment
Humans
Infant mortality
Lung cancer
Narcotics
Obesity
Public Health
Research Methods & Reporting
Risk Assessment
Risk Factors
England
Sweden
United Kingdom > UK
Greenland
Wales
ISSN:0959-8138, 1756-1833, 1756-1833
Online Access:Get full text
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Summary:Alternatively, one can directly estimate the PAF original formula “(O − E)/O” using results from a multivariable logistic regression model.7 As an example of the latter approach, the authors of a recent BMJ paper8 calculated the population attributable fraction (PAF) of concurrent benzodiazepine/opioid use for the risk of opioid overdose in a retrospective analysis of claim data. The PAF estimate was 15% (95% confidence interval 14 to 16%).8 Valid 95% confidence intervals for PAF should take into account the uncertainty in both the observed and expected number of cases.7 The PAF formula with adjusted RR is easily generalised to exposures with more than two levels.9 In a cohort study the PAF for the effect of maternal overweight and obesity on infant mortality in relation to normal weight was estimated as 11%.10 Similarly, we can calculate PAF for the joint effects of two or more exposures. [...]for preventive exposures one can reverse the coding: RR is now the adjusted risk ratio for no exposure and pc is the prevalence of no exposure among cases.
Bibliography:Statistics Notes
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ISSN:0959-8138
1756-1833
1756-1833
DOI:10.1136/bmj.k757