Environmental Burden of Disease in Europe: Assessing Nine Risk Factors in Six Countries

Background: Environmental health effects vary considerably with regard to their severity, type of disease, and duration. Integrated measures of population health, such as environmental burden of disease (EBD), are useful for setting priorities in environmental health policies and research. This review is a summary of the full Environmental Burden of Disease in European countries (EBoDE) project report. Objectives: The EBoDE project was set up to provide assessments for nine environmental risk factors relevant in selected European countries (Belgium, Finland, France, Germany, Italy, and the Netherlands). Methods: Disability-adjusted life years (DALYs) were estimated for benzene, dioxins, secondhand smoke, formaldehyde, lead, traffic noise, ozone, particulate matter (PM2.5), and radon, using primarily World Health Organization data on burden of disease, (inter) national exposure data, and epidemiological or toxicological risk estimates. Results are presented here without discounting or age-weighting. Results: About 3-7% of the annual burden of disease in the participating countries is associated with the included environmental risk factors. Airborne particulate matter (diameter <= 2.5 mu m; PM2.5) is the leading risk factor associated with 6,000-10,000 DALYs/year and 1 million people. Secondhand smoke, traffic noise (including road, rail, and air traffic noise), and radon had overlapping estimate ranges (600-1,200 DALYs/million people). Some of the EBD estimates, especially for dioxins and formaldehyde, contain substantial uncertainties that could be only partly quantified. However, overall ranking of the estimates seems relatively robust. Conclusions: With current methods and data, environmental burden of disease estimates support meaningful policy evaluation and resource allocation, including identification of susceptible groups and targets for efficient exposure reduction. International exposure monitoring standards would enhance data quality and improve comparability.