Overview of the EBoDE-project

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EBoDE project
This page is a product of the EBoDE project. The final report of the EBoDE project has been published as a report in 2011[1] and also as web pages in Opasnet. These links lead to parts of the report.

EBoDE project: main page | overview | contributors | data overview | Parma meeting | abbreviations | all pages

Methods: environmental burden of disease calculation | selection of exposures and health effects | data needed | impact calculation tool

Health effects in Europe: benzene | dioxins | formaldehyde | lead | ozone | particulate matter | radon | second-hand smoke | transport noise | environmental burden of disease | results by country


Exposures to many environmental stressors are known to endanger human health. Negative impacts on health can range from mild psychological effects (e.g. noise annoyance), to effects on morbidity (such as asthma caused by exposure to air pollution), and to increased mortality (such as lung cancer provoked by radon exposure). Properly targeted and followed-up environmental health policies, such as the coal burning ban in Dublin (1990) and the smoking ban in public places in Rome (2005) have demonstrated significant and immediate population level reductions in deaths and diseases. In order to develop effective policy measures, quantitative information about the extent of health impacts of different environmental stressors is needed.

As demonstrated by the examples above, health effects of environmental factors often vary considerably with regard to their severity, duration and magnitude. This makes it difficult to compare different (environmental) health effects and to set priorities in health policies or research programs. Public health policies generally aim to allocate resources effectively for maximum health benefits while avoiding undue interference with other societal functions and human activities. In order to develop such policies, it is necessary to know what ‘maximum health benefits’ are. Decades ago, such decisions tended to be made based on mortality statistics: which (environmental) factor causes most deaths? However, nowadays, most people get relatively old, and priority has shifted from quantity to quality of life. This has lead to the need to incorporate morbidity effects into public health decisions, and therefore to find a way of comparing dissimilar health effects.

Such comparison and prioritisation of environmental health effects is made possible by expressing the diverging health effects in one unit: the environmental burden of disease (EBD). Environmental burden of disease figures express both mortality and morbidity effects in a population in one number. They quantify and summarize (environmental) health effects and can be used for:

  • Comparative evaluation of environmental burden of disease (“how bad is it?”)
  • Evaluation of the effectiveness of environmental policies (largest reduction of disease burden)
  • Estimation of the accumulation of exposures to environmental factors (for example in urban areas)
  • Communication of health risks

An example of an integrated health measure that can be used to express the environmental burden of disease is the DALY (Disability Adjusted Life Years). DALYs combine information on quality and quantity of life. They give an indication of the (potential) number of healthy life years lost in a population due to premature mortality or morbidity, the latter being weighted for the severity of the disorder. The concept was first introduced by Murray and Lopez (1996) as part of the Global Burden of Disease study, which was launched by the World Bank. Since then, the World Health Organization (WHO) has endorsed the procedure, and the DALY approach has been used in various studies on a global, national and regional level.

WHO collects a vast set of data on the global burden of disease. The first study quantified the health effects of more than 100 diseases for eight regions of the world in 1990 (Murray and Lopez, 1996). It generated comprehensive and internally consistent estimates of mortality and morbidity by age, gender and region. In a former WHO study, it was shown that almost a quarter of all disease worldwide was caused by environmental exposure (Prüss-Üstün and Corvalán, 2006). In industrial sub-regions this estimate was about 16% (15–18%). These fractions, however, are dependent on the conclusiveness of the included environmental factors and health effects. The WHO programme on quantifying environmental health impacts has addressed more than a dozen stressors [2]. In order to support further applications of the environmental burden of disease (EBD) assessments, a methodological guidance has been published by WHO (Prüss-Üstün et al., 2003) and was followed here too.

In Europe, national environmental burden of disease (EBD) assessments are on-going in several countries. The work by RIVM was one of the first systematic European works in this area that utilized disability-adjusted life years (DALY) as a measure to compare the burden of different health outcomes related to the exposure of the population to environmental stressors (Hollander et al., 1999). The results highlighted that (i) a number of environmental stressors may cause chronic or acute diseases or death, (ii) a few top ranking stressors cause over 90% of the national EBD, and (iii) these top ranking stressors are not necessarily those that have drawn the most concern, regulatory action and/or preventive investment.[1]


The EBoDE-project was set up in order to guide environmental health policy making in the six participating countries (Belgium, Finland, France, Germany, Italy and the Netherlands) and potentially beyond. From a policy perspective, these insights from the EBoDE-project can be useful to evaluate past policies and to gain insight in setting the policy priorities for the future. We have calculated the total EBD associated with the nine environmental stressors. The total EBD is not identical to the avoidable burden of disease, because some exposures are not realistically reducible to zero (e.g. fine particles). Also, our estimates do not take into account the costs of reducing the EBD. Thus, the results are only one input into the full process of developing cost-effective policies to achieve better environmental health.

The objectives of the project were to update the available previous assessments, to focus on stressors relevant for the European region, to provide harmonized EBD assessments for participating countries, and to develop and make available the methodologies for further development and other countries. The specific objectives are to: • Provide harmonized environmental burden of disease (EBD) estimates for selected environmental stressors in the participating six countries; • Test the methodologies in a harmonized way across the countries. • Assess the comparability of the quantifications and ranking of the EBD • between countries • within countries • between environmental stressors; • Qualitative assessments of variation and uncertainty in the input parameters and results.

Environmental burden of disease estimates have been calculated for: • nine environmental stressors: benzene, dioxins (including furans and dioxin-like PCBs), second-hand smoke, formaldehyde, lead, noise, ozone, particulate matter (PM) and radon; • six European countries: Belgium, Finland, France, Germany, Italy and the Netherlands; • the year 2004 (and some trend estimates for the year 2010). As outlined above, the EBoDE study was carried out in order to test the environmental burden of disease methodology in various countries. The results of the studies are intended to allow comparison of the disease burden between different environmental stressors and between countries. Consequently, the study does not to identify the ‘reduction potential’. Our estimates should therefore not be interpreted as the ‘avoidable burden of disease’: most risks cannot realistically be completely removed by any policy measures. For some exposures, however, the numbers may nonetheless be interpretable as reduction potential, eg for dioxins, formaldehyde, benzene, etc, as these exposures could potentially be completely eliminated.[1]

Outline of this report

This report describes the methods, data and results of the EBoDE-project. Chapter 2 presents the methodology. The environmental stressors are introduced in Chapter 3, which also presents the data used (selected health endpoints, exposure data, exposure response functions). In Chapter 4, the results are presented and discussed. Chapter 5 gives information about uncertainties in the approach, and provides some alternative calculations using different input values. In Chapter 6 conclusions are drawn. The report ends with the references and two appendices: Appendix A presents country-specific results and Appendix B some considerations for using a life-table approach in EBD modelling.[1]

Uncertainties and limitations

Assessment of uncertainties is essential in a comparison of quantitative estimates that are based on data from heterogeneous sources and slightly varying methods. Due to the wide range of data sources and models and the limited resources within the EBoDE project, systematic analysis of all uncertainties was not possible. However, we were able to assess a number of specific sources of uncertainties in more detail as part of the work, yielding some insights into the reliability of the overall assessment. The studied health impacts span approximately four orders of magnitude in size from few DALYs per million to almost 10 000 DALYs per million. The overall ranking of the environmental stressors seems to be rather robust against the relatively large uncertainties in individual estimates or methodological choices like discounting and age-weighing. However, some of the estimated ranges are overlapping. This concerns especially second hand smoke, radon and transportation noise that compete for the questionable honour of being the second most important environmental stressor in the participating countries. Among these stressors the differences are smaller than the corresponding uncertainties of the estimates. The health state of an individual person is the result of a complex mixture of genetic, environmental and behavioural factors. In a typical case of death, numerous factors play together. This means, for example, that a single death caused by a cardiovascular disease could be avoided by either reducing air pollution, or a better diet, or more physical activity. Therefore, if the individual attributable fractions are summed over a number of risk factors, a value over 100% may sometimes be found. For this and other reasons, it has been argued that death counts are not suitable for quantification of the impacts (Brunekreef et al., 2007). Therefore the authors recommend to mainly use aggregate population measures of health like DALYs, YLLs and YLDs. This chapter presents the quantitative results for selected sources of uncertainties and discusses the project limitations and author judgment of the reliability of the ranking.

Uncertainties per stressor and comparison with other studies

A list of the most important sources of uncertainty for each stressor in the EBoDE calculations is provided in Table 5-1. Some of these are further explained below. In addition, we will compare our estimates to results of a selection of similar studies. Comparison of different studies on environmental burden of disease helps to understand the role of various methodological and strategic selections made in each study, like the selection of stressors or health endpoints.

Transportation noise

Burden of disease estimation for transportation noise is currently under active development. The estimates presented here were based on the only available international exposure data source, the first stage version of the European Noise Directive database (2007), which is not conclusive yet. Therefore it is clear that most of the exposures for transportation noise are underestimated. In some studies annoyance and cognitive impairment have been used as an additional health end-points for environmental noise. However, due to the selected more limited definition of ‘health’ as ICD-classified health states used in our assessment, annoyance and cognitive impairment were not included here. Only road, rail and air traffic exposures were included; many other sources also contribute to the noise exposures. Low exposures below the END data collection limits (50 and 55 dB) were not included. For these reasons it can be expected that when these limitations are solved, the impact estimates will increase. [1]

Excluded health endpoints and related assumptions Exposure data Exposure response function Calculation method Level of overall uncertainty a) Likely over- or underestimation b)
Transport noise Annoyance; cognitive impairment, tinnitus Small proportion of target population is covered. Conversion between different noise metrics. Different samples. Different data estimation years Disability weight for sleep disturbance is uncertain. MI vs IHD ** Underestimation due to uncovered populations and exclusion of low exposures, endpoints and noise sources

See also:

Health effects of Second-hand smoke in Europe

Health effects of benzene in Europe

Health effects of radon in Europe

Health effects of ozone in Europe

Health effects of dioxins in Europe

Health effects of formaldehyde in Europe

Health effects of lead in Europe

Health effects of particulate matter in Europe

Conclusions and recommendations

Development of efficient environment and health policies and evaluation of their success requires quantitative information about environmental exposures and their health impacts. Disability adjusted life years (DALYs) can be used as an indicator for the environmental burden of disease by expressing both morbidity and mortality effects in one number. World Health Organization Global Burden of Disease and Environmental Burden of Disease programmes have developed methodologies for estimating environmental burden of disease. However, harmonized exposure data and established methods are still lacking for a large number of stressors that have relevance in the developed world. The current study aimed to test the available methods in six European countries using a harmonized approach. Nine stressors were selected that were considered relevant and interesting for Europe. The selection was intended to cover the most important environmental causes of public health impacts, but also to cover less important exposures that have had high significance in public debate or policy development.

The results showed that the EBD methodology can be used to estimate the burden of disease in a harmonized way over a number of stressors and countries. The highest overall public health impact was estimated for ambient fine particles (PM2.5; annually 6000-9000 non-discounted DALYs per million in the six participating countries) followed by second-hand smoke (600-1200) transportation noise (500-1100), and radon (600-900). Lower impacts were estimated for dioxins and lead, followed by ozone, all containing also larger relative uncertainties. Lowest impacts were estimated for benzene and formaldehyde.

Quantitative assessment of the various factors affecting the relative ranking of the stressors based on their health impact indicated that the ranking of non-overlapping estimates seems rather robust, even when the exact numbers contain variable amount of uncertainties. The scientific evidence on the causality and quantitative understanding of the exposure-response relationship was considered to have highest reliability for fine particles, second-hand smoke, radon and benzene. Medium uncertainties in the exposures and exposure response-relationships were identified for noise, lead and ozone. Quantitative results for dioxins and formaldehyde were considered most uncertain when evaluating the scientific evidence base.

Differences in the representativity of the exposure data affect the comparability of estimates between the countries. Well comparable exposure data was available for particulate matter and ozone, followed by radon, second hand smoke, benzene, and dioxins. Lowest comparability was found for lead and formaldehyde. Transportation noise exposure data collection is well defined in the European Noise Directive (END), but the comparability of the data available from the first phase of data collection has not reached these standards yet. The comparability of estimates between the stressors is affected also by the selection of the health endpoints and the uncertainty in exposure response functions. It is unlikely that these differences in health response models could be solved in the near future.

Environmental burden of disease estimates support meaningful policy evaluation and resource allocation. Besides, policy analysis also needs to account for the reduction potential of exposures, and other factors such as costs of policy measures and equity issues. The proposed methods for burden of disease estimation should be developed further to cover a larger range of environmental factors and health impacts and to include a systematic evaluation of uncertainties.[1]

See also


  1. 1.0 1.1 1.2 1.3 1.4 1.5 Otto Hänninen, Anne Knol: European Perspectives on Environmental Burden of Disease: Esimates for Nine Stressors in Six European Countries, Authors and National Institute for Health and Welfare (THL), Report 1/2011 [1] [2] Cite error: Invalid <ref> tag; name "EBoDe" defined multiple times with different content Cite error: Invalid <ref> tag; name "EBoDe" defined multiple times with different content
  2. The WHO programme[3]