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 μm; 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.Citation: Hänninen O, Knol AB, Jantunen M, Lim TA, Conrad A, Rappolder M, Carrer P, Fanetti AC, Kim R, Buekers J, Torfs R, Iavarone I, Classen T, Hornberg C, Mekel OC, EBoDE Working Group. 2014. Environmental burden of disease in Europe: assessing nine risk factors in six countries. Environ Health Perspect 122:439–446; http://dx.doi.org/10.1289/ehp.1206154

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Background: Numerous studies have shown a strong association between daily mortality and small particulate with a diameter of ,10 mm (PM 10 ) air pollution, but the effects of season have not always been well characterised. Aim: To study the shape of the association between short-term mortality and PM 10 across seasons and quintiles of outdoor temperature. Design, setting and participants: Daily data on mortality (n = 354 357), outdoor temperature and PM 10 in Flanders, Belgium, from January 1997 to December 2003, were analysed across warm versus cold periods of the year (April-September v October-March), with seasons and quintiles of outdoor temperature as possible effect modifiers.Results: There was a significant (p,0.001) interaction between PM 10 and period of the year in relation to mortality. To allow for non-linearity, daily mean PM 10 concentrations were categorised into quartiles. Seasonspecific PM 10 quartiles showed a strong and steep linear association between mortality and PM 10 in summer and a less linear association in spring and autumn, whereas in winter the association was less strong and mortality was only increased in the highest PM 10 quartile. The effect sizes expressed as the percentage increase in mortality on days in the highest season-specific PM 10 quartile versus the lowest season-specific PM 10 quartile were 7.8% (95% CI 6.1 to 9.6) in summer, 6.3% (4.7 to 7.8) in spring, 2.2% (0.58 to 3.8) in autumn and 1.4% (0.06 to 2.9) in winter. An analysis by quintiles of temperature confirmed these effect sizes. Conclusion: The short-term effect of particulate air pollution on mortality strongly depends on outdoor temperature, even in a temperate climate.

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This retrospective incidence-based cost-of-illness analysis aims to quantify the costs associated with female breast cancer in Flanders for the year prior to diagnosis and for each of the 5 years following diagnosis. A bottom-up analysis from the societal perspective included direct health care costs and indirect costs of productivity loss due to morbidity and premature mortality. A case-control study design compared total costs of breast cancer patients with costs of an equivalent standardised population with a view to calculating the additional costs that can be attributed to breast cancer. Total average costs of breast cancer amounted to 107,456 per patient over 6 years. Total costs consisted of productivity loss costs (89% of costs) and health care costs (11% of costs). Health care costs did not vary with age at diagnosis. Health care costs of breast cancer patients converged with those of the general population at 5 years following diagnosis. Patients with advanced breast cancer stadia had higher health care costs. Cost estimates provided by this analysis can be used to determine priorities for, and inform, future research on breast cancer. In particular, attention needs to be focussed on decreasing productivity loss from breast cancer.