A review of the strengths and weaknesses of quantitative methods used in health impact assessment.

OBJECTIVES To explore some of the strengths and weaknesses of purely quantitative approaches used in health impact assessment (HIA) and the implication of this for policy making. STUDY DESIGN The studies presented generally used a variety of quantitative risk assessment (QRA) methodologies. METHODS For each population, concentration-response (CR) or exposure-response (ER) functions, typically expressed as percentage change in health effect per unit change in concentration or exposure, were applied to estimates of population exposure and background rates of morbidity and mortality in order to calculate the attributable health impact or burden. In some cases, this burden was then costed according to standard economic models. RESULTS In most of the studies discussed, where a reliable CR or ER relationship was available, it was possible to quantify the impact(s) of the relevant environmental stressors on health, and to estimate the associated uncertainties. CONCLUSIONS QRA has an important role in producing estimates for the health impacts of those risk factors where there is a sufficient base of research to quantify relationships between population exposure and health, and to predict the effects of policies on population exposure. However, quantified HIA is not an infallible process and can give an illusion of certainty that belies the complexity of the interactions involved, particularly where multiple determinants of health are likely to be affected. It is important that any uncertainties associated with that which has been quantified, as well as the likely impacts of that which cannot be quantified, are assessed and represented comprehensively. A simplistic application of QRA estimates is an inadequate HIA, as it may encourage policy makers and others to attach more importance to those impacts that are easier to quantify but which do not necessarily have the greatest associated burden.

[1]  D. Dockery,et al.  Particulate air pollution as a predictor of mortality in a prospective study of U.S. adults. , 1995, American journal of respiratory and critical care medicine.

[2]  B. Oftedal,et al.  Urban air pollution and mortality in a cohort of Norwegian men. , 2004, Environmental health perspectives.

[3]  Alan D. Lopez,et al.  Potential health gains from reducing multiple risk factors , 2004 .

[4]  Bert Brunekreef,et al.  Association between mortality and indicators of traffic-related air pollution in the Netherlands: a cohort study , 2002, The Lancet.

[5]  Alan D. Lopez,et al.  The evolution of the Global Burden of Disease framework for disease, injury and risk factor quantification: developing the evidence base for national, regional and global public health action , 2005, Globalization and health.

[6]  Alan D. Lopez,et al.  Comparative quantification of health risks. Global and regional burden of disease attributable to selected major risk factors. Volume 1. , 2004 .

[7]  A Plasencia,et al.  Apheis: public health impact of PM10 in 19 European cities , 2004, Journal of Epidemiology and Community Health.

[8]  D. Bellinger,et al.  Low-level lead exposure, intelligence and academic achievement: a long-term follow-up study. , 1992, Pediatrics.

[9]  R. Burnett,et al.  Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. , 2002, JAMA.

[10]  Who Regional Office for Europe,et al.  Gothenburg Consensus Paper: Health Impact Assessment, Main Concepts and Suggested Approach , 1999 .

[11]  J. Kelton,et al.  Plasma glycocalicin. An aid in the classification of thrombocytopenic disorders. , 1987, The New England journal of medicine.

[12]  P. Succop,et al.  Low-level fetal lead exposure effect on neurobehavioral development in early infancy. , 1987, Pediatrics.

[13]  J. Lawson Comparative Quantification of Health Risks. Global and Regional Burden of Disease Attributable to Selected Major Risk Factors , 2006 .

[14]  Herbert L. Needleman,et al.  Low-Level Environmental Lead Exposure and Children’s Intellectual Function: An International Pooled Analysis , 2005, Environmental health perspectives.

[15]  F Kauffmann,et al.  Twenty five year mortality and air pollution: results from the French PAARC survey , 2005, Occupational and Environmental Medicine.

[16]  A. Rabl Air Pollution Mortality: Harvesting And Loss Of Life Expectancy , 2005, Journal of toxicology and environmental health. Part A.

[17]  Majid Ezzati,et al.  Estimates of global and regional potential health gains from reducing multiple major risk factors , 2003, The Lancet.

[18]  S. Médina,et al.  Apheis: Health Impact Assessment of Long-term Exposure to PM2.5 in 23 European Cities , 2006, European Journal of Epidemiology.

[19]  R. Cummins,et al.  Measuring health in a vacuum: examining the disability weight of the DALY. , 2003, Health policy and planning.

[20]  D. Dockery,et al.  An association between air pollution and mortality in six U.S. cities. , 1993, The New England journal of medicine.

[21]  J Schwartz,et al.  Low-level lead exposure and children's IQ: a meta-analysis and search for a threshold. , 1994, Environmental research.

[22]  Alistair Woodward,et al.  Introduction and methods: assessing the environmental burden of disease at national and local levels. , 2003 .

[23]  B. Brunekreef,et al.  The brave new world of lives sacrificed and saved, deaths attributed and avoided. , 2007, Epidemiology.

[24]  C. Corvalan,et al.  Health, environment and sustainable development: identifying links and indicators to promote action. , 1999, Epidemiology.

[25]  C Waternaux,et al.  Longitudinal analyses of prenatal and postnatal lead exposure and early cognitive development. , 1987, The New England journal of medicine.

[26]  M. Holland,et al.  ExternE: externalities of energy: volume 7: methodology, 1998 update , 1999 .

[27]  J. Schwartz,et al.  Reduction in fine particulate air pollution and mortality: Extended follow-up of the Harvard Six Cities study. , 2006, American journal of respiratory and critical care medicine.