Decision-Making in Environmental Health: From Evidence to Action

By C. Corvalán; D. Briggs et al. | Go to book overview

Chapter 4*


METHODS FOR BUILDING ENVIRONMENTAL HEALTH INDICATORS

4.1The challenge of environmental health indicators

As the previous chapter has illustrated, the development of reliable and effective environmental health indicators is not a trivial task. To be effective, they must meet a range of criteria (as outlined in Box 3.1). They must be matched to their purpose: i.e. they must address the problem of concern, at the appropriate point in the environment-health chain, and at appropriate geographical and temporal scales and resolution. Both the data and the computational methods and models needed to construct them must be available at an acceptable cost. They must be expressed and presented in an easily understandable and usable form, and must be scientifically valid and testable. Moreover, if the results of indicators are to be more widely applicable, if the indicators themselves are to be accepted by the many stakeholders concerned (e.g. scientists, politicians, the public), and if lessons are to learned from the collective experience in developing and using indicators, it is important that all these issues of design are carefully documented and open to scrutiny.

The above requirements have significant implications for the way in which indicators are designed and constructed. Many of the criteria are also to some extent mutually incompatible; that is one reason why indicators are difficult to design. The ultimate need for cost-effectiveness, for example, often means that indicators must be developed on the basis of data that already exist or which (if newly collected) can also be used for other purposes. Unfortunately, many of the data that do exist have been collected for specific purposes, and are therefore not ideal for other applications. The need for clarity and ease of understanding also implies that indicators must often condense large volumes of data into a brief overview, and reduce the complexities of the world to a simple and unambiguous message. The need for scientific validity, on the other hand, requires that this process of précis must not go too far. Indicators must simplify without distorting the underlying truth, or losing the vital connections and interdependencies which

*This chapter was prepared by D. Briggs

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