Background: Socioeconomic differences in health are a major challenge for public health. However, realistic estimates to what extent they are modifiable are scarce. This problem can be met through the systematic application of the population attributable fraction (PAF) to socioeconomic health inequalities. Methods: The authors used cause-specific mortality data by educational level from Belgium, Norway and Czech Republic and data on the prevalence of smoking, alcohol, lack of physical activity and high body mass index from national health surveys. Information on the impact of these risk factors on mortality comes from the epidemiological literature. The authors calculated PAFs to quantify the impact on socioeconomic health inequalities of a social redistribution of risk factors. The authors developed an Excel tool covering a wide range of possible scenarios and the authors compare the results of the PAF approach with a conventional regression. Results: In a scenario where the whole population gets the risk factor prevalence currently seen among the highly educated inequalities in mortality can be reduced substantially. According to the illustrative results, the reduction of inequality for all risk factors combined varies between 26% among Czech men and 94% among Norwegian men. Smoking has the highest impact for both genders, and physical activity has more impact among women. Conclusions: After discussing the underlying assumptions of the PAF, the authors concluded that the approach is promising for estimating the extent to which health inequalities can be potentially reduced by interventions on specific risk factors. This reduction is likely to differ substantially between countries, risk factors and genders.,
Journal of Epidemiology and Community Health
Erasmus MC: University Medical Center Rotterdam

Hoffmann, R., Eikemo, T., Kulhánová, I., Dahl, E., Deboosere, P., Dźurov́, D., … Mackenbach, J. (2013). The potential impact of a social redistribution of specific risk factors on socioeconomic inequalities in mortality: Illustration of a method based on population attributable fractions. Journal of Epidemiology and Community Health, 67(1), 56–62. doi:10.1136/jech-2011-20088