Relative excess measures of effect and their use in health impact assessment.

Abstract

Introduction: In health impact assessment, relative excess measures of effect are used in combination with exposure and outcome data to estimate the health impacts under an alternative exposure scenario. The aim of this study is to propose: a classification of relative excess measures of effect functional for health impact assessment; a standard and general framework for calculating health impacts; different approaches when using data at different spatial resolutions.

Methods and results: A classification of the relative excess measures of effect was presented, introducing a new measure. A standard framework for calculating attributable and preventable cases based on the nature of the exposure and the imagined change in exposure was described. The marginal and conditional approaches to calculate health impacts using data at different spatial resolutions were illustrated.

Conclusions: The proposed methods and frameworks are designed to be applicable to a range of different situations. As health impact assessment continues to evolve, the insights and tools provided in this paper could help guide effective and equitable assessments, ultimately contributing to better public health decisions and outcomes.