Title

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

UMMS Affiliation

Department of Medicine, Division of Cardiovascular Medicine

Date

6-26-2009

Document Type

Article

Medical Subject Headings

Aged; Aged, 80 and over; Air Pollutants; Case-Control Studies; Environmental Exposure; Environmental Monitoring; Female; Humans; Male; Massachusetts; Middle Aged; Myocardial Infarction; Sensitivity and Specificity; Socioeconomic Factors; Urban Health; Vehicle Emissions

Disciplines

Bioinformatics | Biostatistics | Epidemiology | Health Services Research

Abstract

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. NO(2) and PM(2.5) 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.

Rights and Permissions

Citation: Occup Environ Med. 2009 Dec;66(12):797-804. Epub 2009 Jun 23. Link to article on publisher's site

Related Resources

Link to Article in PubMed