%0 Journal Article
%T Comparative quantification of health risks: Conceptual framework and methodological issues
%A Christopher JL Murray
%A Majid Ezzati
%A Alan D Lopez
%A Anthony Rodgers
%A Stephen Vander Hoorn
%J Population Health Metrics
%D 2003
%I BioMed Central
%R 10.1186/1478-7954-1-1
%X In this paper, we discuss the conceptual and methodological issues for quantifying the population health effects of individual or groups of risk factors in various levels of causality using knowledge from different scientific disciplines. The issues include: comparing the burden of disease due to the observed exposure distribution in a population with the burden from a hypothetical distribution or series of distributions, rather than a single reference level such as non-exposed; considering the multiple stages in the causal network of interactions among risk factor(s) and disease outcome to allow making inferences about some combinations of risk factors for which epidemiological studies have not been conducted, including the joint effects of multiple risk factors; calculating the health loss due to risk factor(s) as a time-indexed "stream" of disease burden due to a time-indexed "stream" of exposure, including consideration of discounting; and the sources of uncertainty.Detailed description of the level (e.g. rates) and distribution of diseases and injuries, and their causes are important inputs to strategies for improving population health. Data on disease or injury outcomes alone, such as death or hospitalization, tend to focus on the need for palliative or curative services. Reliable and comparable analysis of risks to health, on the other hand, is key for preventing disease and injury. A substantial body of work has focused on the quantification of causes of mortality and more recently burden of disease [1,2]. Analysis of morbidity and mortality due to risk factors, however, has frequently been conducted in the context of methodological traditions of individual risk factors and in a limited number of settings [3-10]. As a result, in most such estimates:1) Causal attribution of morbidity and mortality to risk factors has been estimated relative to zero or some other constant level of population exposure. This single, constant baseline, although illustrating the t
%U http://www.pophealthmetrics.com/content/1/1/1