An exploratory study of the relationship between socioeconomic status and motor vehicle safety features

Traffic Inj Prev. 2010 Apr;11(2):151-5. doi: 10.1080/15389580903531598.


Objective: The purpose of this study was to assess the association between motor vehicle owners' socioeconomic status (SES) and the safety of their motor vehicles.

Methods: Truncated vehicle identification numbers (VINs) were obtained from the Maryland Motor Vehicle Administration office. ZIP code-level income and educational data were assigned to each VIN. Software was used to identify safety-related vehicle characteristics including crash test rating, availability of electronic stability control and side impact air bags, age, and weight. Correlations and analyses of variance were performed to assess whether a ZIP code's median household income and educational level were associated with its proportion of registered vehicles with safety features.

Results: For 13 of the 16 correlations performed, SES was significantly associated with the availability of vehicle safety features in a direction that favored upper-income individuals. Vehicle weight was not associated with income or education. When ZIP codes were divided into median household income quintiles, their mean proportions of safety features also differed significantly, in the same direction, for availability of electronic stability control, side impact air bags, vehicle age, and crash test ratings.

Conclusions: Safer motor vehicles appear to be distributed along socioeconomic lines, with lower income groups experiencing more risk. This previously unidentified mechanism of disparity merits further study and the attention of policy makers.

MeSH terms

  • Accidents, Traffic / prevention & control
  • Air Bags / statistics & numerical data
  • Analysis of Variance
  • Automobiles / standards*
  • Automobiles / statistics & numerical data
  • Educational Status
  • Humans
  • Income / statistics & numerical data
  • Maryland
  • Protective Devices / economics*
  • Protective Devices / statistics & numerical data
  • Risk Factors
  • Safety / economics*
  • Social Class*