Dealing with complex exposures
- The text on this page is taken from an equivalent page of the IEHIAS-project.
Traditional methods of risk assessment tended to focus on singular exposures and health effects. Many of the issues that are the focus of integrated environmental health impact assessments, however, concern more complex situations, where people are exposed to multiple hazards either in succession (e.g. on different days or at different times of life) or in combination (i.e. as mixtures). Examples of exposure mixtures include the classical situation of multiple chemicals, but also the combination of chemical and other exposures (e.g. ozone in outdoor air and allergens in the home).
It is not easy to estimate the effects of mixtures, for the necessary data on the collective relationships between exposures and response (i.e. exposure-response functions for mixtures) are often lacking. Various methods have, however, been devised to allow for these types of exposures in epidemiological and toxicological studies, and to a varying degree these can be used as a basis for health impact assessment.
Indicators
One method that has been widely used in epidemiological studies is to select an individual indicator (e.g. pollutant species), which characterises the mixture of interest. Ozone might thus be used as an indicator for photochemical smog; PM10 is used to represent the wide variety of atmospheric particulate matter; trihalomethanes (THMs) are employed as a proxy for the much wider mix of disinfection by-products that occur in drinking water (see example); distance from source has been widely used as an indicator of exposure to complex pollution mixtures (e.g. from road traffic, landfill sites).
Using indicators is simple and has many advantages, but the approach clearly works well only when the indicator represents the mixture equally well in all the different settings of relevance (i.e. if it has a close and consistent relationship with the exposure mixture), which is not always the case. It is therefore sometimes better to use a number of indicators, selected to represent different sources or environmental processes and settings (e.g. PM10, N0<sub<2 and O3 as indicators of general air pollution). This has a danger, however, for it can result in ‘double-counting’, because each indicator is being treated as though it had an independent (and additive) effect, whereas in practice at least part of the apparent effect seen in epidemiological studies might be shared. More generally, it always has to be remembered that the species used as the indicator might not be (and probably is not) the causative agent. This can have serious limitations when indicators are used in impact assessments, because it is likely to be misleading to assume that changes in the exposure indicator (e.g. under a policy scenario) would imply changes in health impact.
Interaction effects
Another well-established method in epidemiological studies is to allow for interaction effects in the quantitative analysis. Ideally, this is done by designing the studies specifically to detect interaction effects - e.g. by studying populations variously exposed to the pollutants both separately and in combination. This is often difficult to do, however, so more commonly some form of post hoc analysis is done, by testing for interactions in the statistical analysis - though the power of this is nevertheless limited by the small sample size of many studies.
Because of these difficulties, detailed information on interactive effects is rare. It exists for a few, well-established mixtures - e.g. asbestos and smoking, radon and tobacco smoke, diesel and some allergens - but in most cases the information needed to allow for interactive effects in health impact assessments is lacking
Toxicological approaches
For practical reasons it is often easier to explore interactive effects using toxicological methods, where greater control can be exerted on the exposure mixtures being studied. Interactions can then be quantified in the form of relative potency factors, of which toxicity equivalence factors (TEF) are a special case. This approach is most azppropriate for the well-defined class of agents that operate through a common mode of action for the same health outcome. Examples include the relative potency factors for some carcinogenic polycyclic aromatic hydrocarbons (PAHs) and the TEF for dioxin-like compounds. The difficulty, however, is in translating these measures into dose-response functions that can be applied to large and heterogeneous population groups, and varied exposures, as part of an impact assessment (see example of THMs in drinking water).
Biomarkers
Biomarkers offer a further approach to assessing effects of mixtures. Different types of biomarker may be useful in this respect. Biomarkers of exposure are useful when exposures occur though multiple environmental media, such as air, food, drinking water and absorption through the skin. These allow the collective exposure through all the different routeways to be assessed, without the need to measure or model each one separately. One example where this has been documented is for lead (Pb): exposure-response functions for lead are thus typically formulated as the effect (e.g. on learning abilities) per unit concentration of lead in blood, which integrates the different exposure routes. Biomarkers of early, physiological effect can also be used. These are especially important when a large number of components are present in the exposure mixture, such that their interactions are too complicated to be modelled explicitly.
While biomarkers are valuable as part of the epidemiological or toxicological analysis used to develop understanding of dose-response relationships, however, their use in health impact assessments is inevitably more limited, because of the need (in many assessments) to estimate effects of changes in exposure in response to some form of intervention (e.g. a change in policy). To enable this, models are also needed, indicating how the measured levels of the biomarkers might vary under the assessment scenarios. This, in turn, usually implies an ability to model the different sources and exposure pathways.
Example for water
As part of the EU-funded INTARESE project, which contribued to the development of this Toolbox, a case study was done to assess the health impacts of domestic water supply and use
After the initial screening phase, the majority of the case study was focused on disinfection by-products (DBPs). These serve as an example of a complex exposure. Moreover, in contrast to many other drinking water contaminants, populations served with disinfected water supplies are exposed to some DBP components irrespective of their water ingestion habits: volatile components such as THMs are absorbed through the skin (percutaneous absorption) and through the lungs (inhalation). This near-ubiquitous exposure in areas served with disinfected water makes the assessment of health impacts of DBP exposure particularly relevant and of considerable policy interest.
Over 600 disinfection by-products have been identified. Epidemiological evidence has been suggestive of an association between exposure to DBPs and bladder cancer, adverse birth outcomes related to prematurity and growth, and birth defects. In the vast majority of epidemiological studies these health outcomes have been linked to concentrations of total trihalomethanes (a marker of DBP exposure that is used in monitoring) at place of residence (or place of residence of the mother in the case of birth outcomes). Total trihalomethanes may not be the best marker of exposure to the whole chemical mixture, particularly since they may exhibit threshold carcinogenic properties and are only weakly correlated to many other, more mutagenic chemicals in the mixture. Their advantage, however, is that they they are routinely measured as part of drinking water monitoring programmes in most developed countries. This helps to increase the statistical power of the analyses, by allowing investigation of larger study populations. On the other hand, this benefit may be outweighed by the uncertainties that arise from using an exposure metric that fails completely to capture the true exposure of the population.
Toxicological studies, in contrast, have focused on individual chemical constituents of the DBP mixture. This clearly helps to improve the specificity of the analysis, but in doing so creates uncertainties of interpretation when dealing with chemical mixtures in which the putative agent is unknown or under some dispute. Other assessments of cancer risk associated with exposure to DBPs have employed cancer potency factors attributed to THMs. This approach, however, can lead to a highly overexaggerated estimate of risk, which may in fact be zero.