Epidemiologic Health Impact Assessment: Estimation of Attributable Cases and Application to Decision Making

OBJECTIVES: The epidemiologic Health Impact Assessment (eHIA) process is receiving growing attention in Italy. In the context of such an approach, the present paper has three objectives: to review the computational aspects of eHIA for stressing strengths and weaknesses of methods and formulas; to discuss which rate at baseline could be used for the estimation of attributable cases; how to use the results of eHIA to make decisions regarding the realization of industrial projects. METHODS AND RESULTS: Using a linear formulation of the relationship between exposure and disease occurrence: a) formulas have been derived to compute attributable cases (AC) using both Relative Risk (RR) and Excess Risk (ER) approaches; b) a discussion is made of the use as baseline rate of the rate that is caused by all the risk factors for a particular disease and a suggestion is made to use the rate that is caused simply by the risk factors that are under evaluation; c) under assumptions and approximations that must be validated in any specific situation, formulas are derived to compute Incremental Lifetime Cumulative Risk (ILCR), an indicator that can be used to compare the results coming from the eHIA approach with the levels of action used by USEPA and others (10(−6), 10(−5), 10(−4)). CONCLUSION: In this paper, the methodology and the formulas commonly used in eHIA have been enlarged to consider the case in which the baseline rate is equal to zero, suggesting to use Excess Risk (ER) estimates instead of Relative Risk (RR) estimates. Using different baseline rates produces very different estimates of AC, and work needs to be done on this topic. Lastly, due to assumptions, approximations, and uncertainty of eHIA computations, prudence and caution should be exercised in using eHIA results in decision making, particularly if hard decisions have to be made.