BACKGROUND: Few quantitative health impact assessments (HIAs) of transport policies have been published so far and there is a lack of a common methodology for such assessments. OBJECTIVE: To evaluate the usability of existing HIA methodology to quantify health effects of transport policies at the local level. METHODS: Health impact of two simulated but realistic transport interventions - speed limit reduction and traffic re-allocation - was quantified by selecting traffic-related exposures and health endpoints, modelling of population exposure, selecting exposure-effect relations and estimating the number of local traffic-related cases and disease burden, expressed in disability-adjusted life-years (DALYs), before and after the intervention. RESULTS: Exposure information was difficult to retrieve because of the local scale of the interventions, and exposure-effect relations for subgroups and combined effects were missing. Given uncertainty in the outcomes originating from this kind of missing information, simulated changes in population health by two local traffic interventions were estimated to be small (<5%), except for the estimated reduction in DALYs by less traffic accidents (60%) due to speed limit reduction. CONCLUSIONS: Quantitative HIA of transport policies at a local scale is possible, provided that data on exposures, the exposed population and their baseline health status are available. The interpretation of the HIA information should be carried out in the context of the quality of input data and assumptions and uncertainties of the analysis.
BACKGROUND: Few quantitative health impact assessments (HIAs) of transport policies have been published so far and there is a lack of a common methodology for such assessments. OBJECTIVE: To evaluate the usability of existing HIA methodology to quantify health effects of transport policies at the local level. METHODS: Health impact of two simulated but realistic transport interventions - speed limit reduction and traffic re-allocation - was quantified by selecting traffic-related exposures and health endpoints, modelling of population exposure, selecting exposure-effect relations and estimating the number of local traffic-related cases and disease burden, expressed in disability-adjusted life-years (DALYs), before and after the intervention. RESULTS: Exposure information was difficult to retrieve because of the local scale of the interventions, and exposure-effect relations for subgroups and combined effects were missing. Given uncertainty in the outcomes originating from this kind of missing information, simulated changes in population health by two local traffic interventions were estimated to be small (<5%), except for the estimated reduction in DALYs by less traffic accidents (60%) due to speed limit reduction. CONCLUSIONS: Quantitative HIA of transport policies at a local scale is possible, provided that data on exposures, the exposed population and their baseline health status are available. The interpretation of the HIA information should be carried out in the context of the quality of input data and assumptions and uncertainties of the analysis.
Authors: Rosemary Hiscock; Pierpaolo Mudu; Matthias Braubach; Marco Martuzzi; Laura Perez; Clive Sabel Journal: Int J Environ Res Public Health Date: 2014-11-28 Impact factor: 3.390