Methodological Considerations in the Use of Quality Adjusted Life Years (QALYs) and Dose Response Models in a Comparative Analysis of Fish Consumption. E. Y. Wong, R. A. Ponce, S. M. Bartell, E. M. Faustman, and P. M. Bolger; University of Washington, and USFDA
Comparative human health risk analyses are currently constrained by the lack of quantitative techniques that can accommodate diverse health endpoints. One option available for comparative risk analysis across disparate health effects is to weight the probability of disease by quality adjusted life years (QALYs). QALYs disaggregate health effects into two components: duration of impact and severity of impact. By using reported survey data as a means for estimating the severity weights for the considered health endpoints, and by using life table analysis to estimate the population-aggregated life years of impact, the QALYs can be fully specified. Use of QALYs to weight the dose-response model for each health effect (under specific constraining assumptions) provides a means for comparing disparate health policy options. To demonstrate the utility of this technique, a simplified analysis of the risks and benefits of fish consumption was performed as a case example. Reduced mortality from myocardial infarction was considered against neurodevelopmental delay due to methylmercury in children exposed in utero. In a population of all ages and genders, the benefits of fish consumption greatly outweigh the risks, though the relative benefits are strongly impacted by discounting life years. Key methodological considerations include the specification of the impacted population(s), choice of discounting rate, and the need for sensitivity and uncertainty analyses. Although the informational requirements for each considered health endpoint may restrict use of this method to those analyses where the policy implications justify the analytical cost, the proposed technique provides a rigorous basis for quantitative comparative risk analysis that avoids monetizing health and life.
This project was supported by the Center for the Study and Improvement of Regulation at Carnegie Mellon University.
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