Occup Environ Med 66:797-804 doi:10.1136/oem.2008.045047
  • Original article

Traffic particles and occurrence of acute myocardial infarction: a case–control analysis

Open Access
  1. C Tonne1,
  2. J Yanosky2,
  3. A Gryparis3,
  4. S Melly2,
  5. M Mittleman4,5,
  6. R Goldberg6,
  7. S von Klot2,7,
  8. J Schwartz2
  1. 1
    Environmental Research Group, King’s College London, London, UK
  2. 2
    Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA
  3. 3
    Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA
  4. 4
    Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
  5. 5
    Beth Israel Deaconess Medical Center, Boston, MA, USA
  6. 6
    University of Massachusetts Medical School, Worcester, MA, USA
  7. 7
    Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
  1. Correspondence to Cathryn Tonne, Environmental Research Group, King’s College London, 150 Stamford Street, London SE1 9NH, UK; ctonne{at}
  • Accepted 10 May 2009
  • Published Online First 23 June 2009


Objectives: We modelled exposure to traffic particles using a latent variable approach and investigated whether long-term exposure to traffic particles is associated with an increase in the occurrence of acute myocardial infarction (AMI) using data from a population-based coronary disease registry.

Methods: Cases of individually validated AMI were identified between 1995 and 2003 as part of the Worcester Heart Attack Study. Population controls were selected from Massachusetts, USA, resident lists. NO2 and PM2.5 filter absorbance were measured at 36 locations throughout the study area. The air pollution data were used to estimate exposure to traffic particles using a semiparametric latent variable regression model. Conditional logistic models were used to estimate the association between exposure to traffic particles and occurrence of AMI.

Results: Modelled exposure to traffic particles was highest near the city of Worcester. Cases of AMI were more exposed to traffic and traffic particles compared to controls. An interquartile range increase in modelled traffic particles was associated with a 10% (95% CI 4% to 16%) increase in the odds of AMI. Accounting for spatial dependence at the census tract, but not block group, scale substantially attenuated this association.

Conclusions: These results provide some support for an association between long-term exposure to traffic particles and risk of AMI. The results were sensitive to the scale selected for the analysis of spatial dependence, an issue that requires further investigation. The latent variable model captured variation in exposure, although on a relatively large spatial scale.


  • See Commentary, p 787

  • Funding This study was supported by grants RO1 ES011636 and T32 ES07155 from the National Institute of Environmental Health Sciences.

  • Competing interests None.

  • Ethics approval The study was approved by the Committee for the Protection of Human Subjects at the University of Massachusetts Medical School and the Human Subjects Committee at the Harvard School of Public Health.

  • Provenance and peer review Not commissioned; externally peer reviewed.