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    Epidemiological methods and data analysis

    O3.1 ATTRIBUTABLE FRACTIONS IN MULTI-EXPOSED: QUANTIFYING CONTRIBUTIONS OF INDIVIDUAL RISK FACTORS

    G. E. Eide1, I. Heuch2.1Centre for Clinical Research, Haukeland University Hospital & Section for Epidemiology and Medical Statistics, Department of Public Health and Primary Health Care, University of Bergen; 2Department of Mathematics, University of Bergen, Bergen, Norway

    Introduction: Various methods have been proposed in the literature for quantifying the contributions of individual risk factors to a combined attributable fraction in a population, leading to concepts like the sequential attributable fractions, the average attributable fractions, the extra attributable fractions, and the rate fractions. It may be unclear how these concepts are to be interpreted and whether they apply also to attributable fractions in multi-exposed subpopulations.

    Methods: These issues are clarified by using probabilistic reasoning and application of the various methods to synthetic examples as well as two published data sets from occupational medicine.

    Results: Both theoretically and in practice the sequential and average attributable fractions have favourable properties compared with the extra attributable fractions and the rate fractions. Among these properties is additivity and completeness of partitioning. Also, a relation between the average attributable fractions in a population and in exposed is established.

    Conclusion: Average attributable fractions represent a coherent methodology for apportioning attributable fractions in individuals, groups of individuals, and populations.

    O3.2 META-ANALYSIS IN OCCUPATIONAL EPIDEMIOLOGY FOR RARE DISEASE OUTCOMES: WHAT TO DO WHEN THERE ARE NO EXPOSED CASES?

    D. M. McElvenny1, B. G. Armstrong.1Public and Environmental Health Research Unit, London School of Hygiene & Tropical Medicine, UK

    Introduction: Meta-analyses involving rare diseases, frequently involve cohort studies that report only a few observed cases with a correspondingly small expected number of cases. Problems occur when some studies report no observed cases (log(RR) is undefined), in particular if they do not provide an expected number of cases, or do not report a result for the disease of interest. The aim of this presentation is to examine the possible …

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