Review

Comparative quantification of health risks: Conceptual framework and methodological issues

Christopher JL Murray¹ , Majid Ezzati² , Alan D Lopez³ , Anthony Rodgers⁴ and Stephen Vander Hoorn⁴

¹  Evidence and Information for Health Policy, World Health Organization, CH-1211 Geneva 27, Switzerland

²  Risk, Resources and Environmental Management Division, Resources for the Future, 1616 P Street NW, Washington DC 20036, USA

³  School of Population Health, University of Queensland, Herston Road, Herston Qld 4006, Australia

⁴  Clinical Trials Research Unit (CTRU), University of Auckland, PB 92019, Auckland, New Zealand

author email corresponding author email

Population Health Metrics 2003, 1:1doi:10.1186/1478-7954-1-1

Published:	14 April 2003

Abstract

Reliable and comparable analysis of risks to health is key for preventing disease and injury. Causal attribution of morbidity and mortality to risk factors has traditionally been conducted in the context of methodological traditions of individual risk factors, often in a limited number of settings, restricting comparability.

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.