title: Quantitative health impact assessment of transport policies: two simulations related to speed limit reduction and traffic re-allocation in the Netherlands.
abstract: 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.affiliation: National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA Bilthoven, The Netherlands. dieneke.schram@rivm.nl
authors.forename: D
authors.initials: D
authors.lastname: Schram-Bijkerk
authors.forename: E
authors.initials: E
authors.lastname: van Kempen
authors.forename: A B
authors.initials: AB
authors.lastname: Knol
authors.forename: H
authors.initials: H
authors.lastname: Kruize
authors.forename: B
authors.initials: B
authors.lastname: Staatsen
authors.forename: I
authors.initials: I
authors.lastname: van Kamp
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000393:Air Pollutants / Q000009:adverse effects / Q000032:analysis; D002318:Cardiovascular Diseases / Q000453:epidemiology / Q000209:etiology; D002648:Child; D004779:Environment Design; D004781:Environmental Exposure / Q000009:adverse effects / Q000032:analysis*; D004784:Environmental Monitoring / Q000379:methods; D062665:Epidemiological Monitoring; D006801:Humans; D008875:Middle Aged; D008962:Models, Theoretical; D018986:Motor Vehicles; D009426:Netherlands / Q000453:epidemiology; D011640:Public Policy; D012120:Respiration Disorders / Q000453:epidemiology / Q000209:etiology; D012893:Sleep Wake Disorders / Q000453:epidemiology / Q000209:etiology; D055815:Young Adult
chemical_list: D000393:Air Pollutants