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Published in: BMC Medical Research Methodology 1/2009

Open Access 01-12-2009 | Research article

An illustration of and programs estimating attributable fractions in large scale surveys considering multiple risk factors

Authors: Simon Rückinger, Rüdiger von Kries, André Michael Toschke

Published in: BMC Medical Research Methodology | Issue 1/2009

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Abstract

Background

Attributable fractions (AF) assess the proportion of cases in a population attributable to certain risk factors but are infrequently reported and mostly calculated without considering potential confounders. While logistic regression for adjusted individual estimates of odds ratios (OR) is widely used, similar approaches for AFs are rarely applied.

Methods

Different methods for calculating adjusted AFs to risk factors of cardiovascular disease (CVD) were applied using data from the National Health and Nutrition Examination Survey (NHANES). We compared AFs from the unadjusted approach using Levin's formula, from Levin's formula using adjusted OR estimates, from logistic regression according to Bruzzi's approach, from logistic regression with sequential removal of risk factors ('sequential AF') and from logistic regression with all possible removal sequences and subsequent averaging ('average AF').

Results

AFs following the unadjusted and adjusted (using adjusted ORs) Levin's approach yielded clearly higher estimates with a total sum of more than 100% compared to adjusted approaches with sums < 100%. Since AFs from logistic regression were related to the removal sequence of risk factors, all possible sequences were considered and estimates were averaged. These average AFs yielded plausible estimates of the population impact of considered risk factors on CVD with a total sum of 90%. The average AFs for total and HDL cholesterol levels were 17%, for hypertension 16%, for smoking 11%, and for diabetes 5%.

Conclusion

Average AFs provide plausible estimates of population attributable risks and should therefore be reported at least to supplement unadjusted estimates. We provide functions/macros for commonly used statistical programs to encourage other researchers to calculate and report average AFs.
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Metadata
Title
An illustration of and programs estimating attributable fractions in large scale surveys considering multiple risk factors
Authors
Simon Rückinger
Rüdiger von Kries
André Michael Toschke
Publication date
01-12-2009
Publisher
BioMed Central
Published in
BMC Medical Research Methodology / Issue 1/2009
Electronic ISSN: 1471-2288
DOI
https://doi.org/10.1186/1471-2288-9-7

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