Brian O'Neill1, Sergey Y Kyrychenko. 1. Insurance Institute for Highway Safety, Arlington, Virginia 22201, USA. brianoneill@cox.net
Abstract
OBJECTIVES: The objectives of the article are to assess the extent to which comparisons of motor-vehicle crash death rates can be used to determine the effectiveness of highway-safety policies over time in a country or to compare policy effectiveness across countries. METHODS: Motor-vehicle crash death rates per mile traveled in the 50 U.S. states from 1980 to 2003 are used to show the influence on these rates of factors independent of highway-safety interventions. Multiple regression models relating state death rates to various measures related to urbanization and demographics are used. RESULTS: The analyses demonstrate strong relationships between state death rates and urbanization and demographics. Almost 60% of the variability among the state death rates can be explained by the independent variables in the multiple regression models. When the death rates for passenger vehicle occupants (i.e., excluding motorcycle, pedestrian, and other deaths) are used in the regression models, almost 70% of the variability in the rates can be explained by urbanization and demographics. CONCLUSIONS: The analyses presented in the article demonstrate that motor-vehicle crash death rates are strongly influenced by factors unrelated to highway-safety countermeasures. Overall death rates should not be used as a basis for judging the effectiveness (or ineffectiveness) of specific highway-safety countermeasures or to assess overall highway-safety policies, especially across jurisdictions. There can be no substitute for the use of carefully designed scientific evaluations of highway-safety interventions that use outcome measures directly related to the intervention; e.g., motorcyclist deaths should be used to assess the effectiveness of motorcycle helmet laws. While this may seem obvious, there are numerous examples in the literature of death rates from all crashes being used to assess the effectiveness of interventions aimed at specific subsets of crashes.
OBJECTIVES: The objectives of the article are to assess the extent to which comparisons of motor-vehicle crash death rates can be used to determine the effectiveness of highway-safety policies over time in a country or to compare policy effectiveness across countries. METHODS: Motor-vehicle crash death rates per mile traveled in the 50 U.S. states from 1980 to 2003 are used to show the influence on these rates of factors independent of highway-safety interventions. Multiple regression models relating state death rates to various measures related to urbanization and demographics are used. RESULTS: The analyses demonstrate strong relationships between state death rates and urbanization and demographics. Almost 60% of the variability among the state death rates can be explained by the independent variables in the multiple regression models. When the death rates for passenger vehicle occupants (i.e., excluding motorcycle, pedestrian, and other deaths) are used in the regression models, almost 70% of the variability in the rates can be explained by urbanization and demographics. CONCLUSIONS: The analyses presented in the article demonstrate that motor-vehicle crash death rates are strongly influenced by factors unrelated to highway-safety countermeasures. Overall death rates should not be used as a basis for judging the effectiveness (or ineffectiveness) of specific highway-safety countermeasures or to assess overall highway-safety policies, especially across jurisdictions. There can be no substitute for the use of carefully designed scientific evaluations of highway-safety interventions that use outcome measures directly related to the intervention; e.g., motorcyclist deaths should be used to assess the effectiveness of motorcycle helmet laws. While this may seem obvious, there are numerous examples in the literature of death rates from all crashes being used to assess the effectiveness of interventions aimed at specific subsets of crashes.
Authors: Yinan Peng; Namita Vaidya; Ramona Finnie; Jeffrey Reynolds; Cristian Dumitru; Gibril Njie; Randy Elder; Rebecca Ivers; Chika Sakashita; Ruth A Shults; David A Sleet; Richard P Compton Journal: Am J Prev Med Date: 2017-06 Impact factor: 5.043
Authors: James C Fell; Deborah A Fisher; Robert B Voas; Kenneth Blackman; A Scott Tippetts Journal: Alcohol Clin Exp Res Date: 2009-04-09 Impact factor: 3.455