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

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.

A comparison of four gravimetric fine particle sampling methods.

A study was conducted to compare four gravimetric methods of measuring fine particle (PM2.5) concentrations in air: the BGI, Inc. PQ200 Federal Reference Method PM2.5 (FRM) sampler; the Harvard-Marple Impactor (HI); the BGI, Inc. GK2.05 KTL Respirable/Thoracic Cyclone (KTL); and the AirMetrics MiniVol (MiniVol). Pairs of FRM, HI, and KTL samplers and one MiniVol sampler were collocated and 24-hr integrated PM2.5 samples were collected on 21 days from January 6 through April 9, 2000. The mean and standard deviation of PM2.5 levels from the FRM samplers were 13.6 and 6.8 microg/m3, respectively. Significant systematic bias was found between mean concentrations from the FRM and the MiniVol (1.14 microg/m3, p = 0.0007), the HI and the MiniVol (0.85 microg/m3, p = 0.0048), and the KTL and the MiniVol (1.23 microg/m3, p = 0.0078) according to paired t test analyses. Linear regression on all pairwise combinations of the sampler types was used to evaluate measurements made by the samplers. None of the regression intercepts was significantly different from 0, and only two of the regression slopes were significantly different from 1, that for the FRM and the MiniVol [beta1 = 0.91, 95% CI (0.83-0.99)] and that for the KTL and the MiniVol [beta1 = 0.88, 95% CI (0.78-0.98)]. Regression R2 terms were 0.96 or greater between all pairs of samplers, and regression root mean square error terms (RMSE) were 1.65 microg/m3 or less. These results suggest that the MiniVol will underestimate measurements made by the FRM, the HI, and the KTL by an amount proportional to PM2.5 concentration. Nonetheless, these results indicate that all of the sampler types are comparable if approximately 10% variation on the mean levels and on individual measurement levels is considered acceptable and the actual concentration is within the range of this study (5-35 microg/m3).