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

Biodistribution of gold nanoparticles in mouse lung following intratracheal instillation

<p>Abstract</p> <p>Background</p> <p>The fate of gold nanoparticles, 2, 40 and 100 nm, administered intratracheally to adult female mice was examined. The nanoparticles were traced by autometallography (AMG) at both ultrastructural and light microscopic levels. Also, the gold content was quantified by inductively coupled plasma mass spectrometry (ICP-MS) and neutron activation analysis (NAA). The liver is the major site of deposition of circulating gold nanoparticles. Therefore the degree of translocation was determined by the hepatic deposition of gold. Mice were instilled with 5 intratracheal doses of gold nanoparticles distributed over a period of 3 weeks and were killed 24 h after the last dose. One group of mice were given a single intratracheal dose and were killed after 1 h.</p> <p>Results</p> <p>The instilled nanoparticles were found in lung macrophages already 1 h after a single instillation. In mice instilled treated repeatedly during 3 weeks, the load was substantial. Ultrastructurally, AMG silver enhanced gold nanoparticles were found in lysosome-/endosome-like organelles of the macrophages and analysis with AMG, ICP-MS and NAA of the liver revealed an almost total lack of translocation of nanoparticles. In mice given repeated instillations of 2 nm gold nanoparticles, 1.4‰ (by ICP-MS) to 1.9‰ (by NAA) of the instilled gold was detected in the liver. With the 40 nm gold, no gold was detected in the liver (detection level 2 ng, 0.1‰) except for one mouse in which 3‰ of the instilled gold was found in the liver. No gold was detected in any liver of mice instilled with 100 nm gold (detection level 2 ng, 0.1‰) except in a single animal with 0.39‰ of the dose in the liver.</p> <p>Conclusion</p> <p>We found that that: (1) inert gold nanoparticles, administered intratracheally are phagocytosed by lung macrophages; (2) only a tiny fraction of the gold particles is translocated into systemic circulation. (3) The translocation rate was greatest with the 2 nm gold particles.</p

Associations between air temperature and cardio-respiratory mortality in the urban area of Beijing, China: a time-series analysis

<p>Abstract</p> <p>Background</p> <p>Associations between air temperature and mortality have been consistently observed in Europe and the United States; however, there is a lack of studies for Asian countries. Our study investigated the association between air temperature and cardio-respiratory mortality in the urban area of Beijing, China.</p> <p>Methods</p> <p>Death counts for cardiovascular and respiratory diseases for adult residents (≥15 years), meteorological parameters and concentrations of particulate air pollution were obtained from January 2003 to August 2005. The effects of two-day and 15-day average temperatures were estimated by Poisson regression models, controlling for time trend, relative humidity and other confounders if necessary. Effects were explored for warm (April to September) and cold periods (October to March) separately. The lagged effects of daily temperature were investigated by polynomial distributed lag (PDL) models.</p> <p>Results</p> <p>We observed a J-shaped exposure-response function only for 15-day average temperature and respiratory mortality in the warm period, with 21.3°C as the threshold temperature. All other exposure-response functions could be considered as linear. In the warm period, a 5°C increase of two-day average temperature was associated with a RR of 1.098 (95% confidence interval (95%CI): 1.057-1.140) for cardiovascular and 1.134 (95%CI: 1.050-1.224) for respiratory mortality; a 5°C decrease of 15-day average temperature was associated with a RR of 1.040 (95%CI: 0.990-1.093) for cardiovascular mortality. In the cold period, a 5°C increase of two-day average temperature was associated with a RR of 1.149 (95%CI: 1.078-1.224) for respiratory mortality; a 5°C decrease of 15-day average temperature was associated with a RR of 1.057 (95%CI: 1.022-1.094) for cardiovascular mortality. The effects remained robust after considering particles as additional confounders.</p> <p>Conclusions</p> <p>Both increases and decreases in air temperature are associated with an increased risk of cardiovascular mortality. The effects of heat were immediate while the ones of cold became predominant with longer time lags. Increases in air temperature are also associated with an immediate increased risk of respiratory mortality.</p

The Influence of Meteorology on the Spread of Influenza: Survival Analysis of an Equine Influenza (A/H3N8) Outbreak

The influences of relative humidity and ambient temperature on the transmission of influenza A viruses have recently been established under controlled laboratory conditions. The interplay of meteorological factors during an actual influenza epidemic is less clear, and research into the contribution of wind to epidemic spread is scarce. By applying geostatistics and survival analysis to data from a large outbreak of equine influenza (A/H3N8), we quantified the association between hazard of infection and air temperature, relative humidity, rainfall, and wind velocity, whilst controlling for premises-level covariates. The pattern of disease spread in space and time was described using extraction mapping and instantaneous hazard curves. Meteorological conditions at each premises location were estimated by kriging daily meteorological data and analysed as time-lagged time-varying predictors using generalised Cox regression. Meteorological covariates time-lagged by three days were strongly associated with hazard of influenza infection, corresponding closely with the incubation period of equine influenza. Hazard of equine influenza infection was higher when relative humidity was <60% and lowest on days when daily maximum air temperature was 20–25°C. Wind speeds >30 km hour−1 from the direction of nearby infected premises were associated with increased hazard of infection. Through combining detailed influenza outbreak and meteorological data, we provide empirical evidence for the underlying environmental mechanisms that influenced the local spread of an outbreak of influenza A. Our analysis supports, and extends, the findings of studies into influenza A transmission conducted under laboratory conditions. The relationships described are of direct importance for managing disease risk during influenza outbreaks in horses, and more generally, advance our understanding of the transmission of influenza A viruses under field conditions

Equivalence of using nested buffers and concentric adjacent rings as predictors in land use regression models.

Land use regression (LUR) models have been widely used to estimate traffic air pollution within cities taking into account spatial distributions. These prediction models are often built based on multiple linear models that regress concentrations measured at locations spread over the cities on land use characteristics of those locations. Land use variables, as for example total road length, are sometimes calculated in buffers of different radii that are then included simultaneously in the models to account for a distance gradient in the influence of sources. Some authors favour including disjoint concentric ring areas instead. Both approaches have their advantages, and adjacent concentric rings tend to make model interpretation more intuitive. The present paper shows that both approaches lead to identical models and the results achieved from one can be used to calculate the results of the other when absolute continuous exposure measures such as total length of roads are used. It is also shown that this holds as well for relative exposures such as area-weighted total length of streets, inhabitants per area, and % urban area, where the ;measure of interest is scaled by a constant factor