%0 Journal Article
%T An illustration of and programs estimating attributable fractions in large scale surveys considering multiple risk factors
%A Simon R¨ąckinger
%A R¨ądiger von Kries
%A Andr¨¦ Toschke
%J BMC Medical Research Methodology
%D 2009
%I BioMed Central
%R 10.1186/1471-2288-9-7
%X 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').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%.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.The major burden of disease has shifted from communicable to non-communicable diseases in high-income countries during the past century [1,2]. Populations are aging in most high income countries, resulting in a further increase of non-communicable diseases [3]. This accumulation of prevalent non-communicable diseases and their sequelae represent a major challenge for health service capacities and financial resources. Policy makers need evidence based advice for decisions on potential interventions and population based prevention strategies.While public
%U http://www.biomedcentral.com/1471-2288/9/7