Use of a total traffic count metric to investigate the impact of roadways on asthma severity: a case-control study

<p>Abstract</p> <p>Background</p> <p>This study had two principal objectives: (i) to investigate the relationship between asthma severity and proximity to major roadways in Perth, Western Australia; (ii) to demonstrate a more accurate method of exposure assessment for traffic pollutants using an innovative GIS-based measure that fully integrates all traffic densities around subject residences.</p> <p>Methods</p> <p>We conducted a spatial case-control study, in which 'cases' were defined as individuals aged under 19 years of age with more severe asthma (defined here as two or more emergency department contacts with asthma in a defined 5-year period) versus age- and gender-matched 'controls' with less severe asthma (defined here as one emergency department contact for asthma). Traffic exposures were measured using a GIS-based approach to determine the lengths of the roads falling within a buffer area, and then multiplying them by their respective traffic counts.</p> <p>Results</p> <p>We examined the spatial relationship between emergency department contacts for asthma at three different buffer sizes: 50 metres, 100 metres and 150 metres. No effect was noted for the 50 metre buffer (OR = 1.07; 95% CI: 0.91-1.26), but elevated odds ratios were observed with for crude (unadjusted) estimates OR = 1.21 (95% CI: 1.00-1.46) for 100 metre buffers and OR = 1.25 (95% CI: 1.02-1.54) for 150 metre buffers. For adjusted risk estimates, only the 150 metre buffer yielded a statistically significant finding (OR = 1.24; 95% CI:1.00-1.52).</p> <p>Conclusions</p> <p>Our study revealed a significant 24% increase in the risk of experiencing multiple emergency department contacts for asthma for every log-unit of traffic exposure. This study provides support for the hypothesis that traffic related air pollution increases the frequency of health service contacts for asthma. This study used advanced GIS techniques to establish traffic-weighted buffer zones around the geocoded residential location of subjects to provide an accurate assessment of exposure to traffic emissions, thereby providing a quantification of the ranges over which pollutants may exert a health effect.</p

Associations between outdoor temperature and markers of inflammation: a cohort study

<p>Abstract</p> <p>Background</p> <p>Associations between ambient temperature and cardiovascular mortality are well established. This study investigated whether inflammation could be part of the mechanism leading to temperature-related cardiovascular deaths.</p> <p>Methods</p> <p>The study population consisted of a cohort of 673 men with mean age of 74.6 years, living in the greater Boston area. They were seen for examination roughly every 4 years, and blood samples for inflammation marker analyses were drawn in 2000-2008 (total of 1254 visits). We used a mixed effects model to estimate the associations between ambient temperature and a variety of inflammation markers (C-reactive protein, white blood cell count, soluble Vascular Cell Adhesion Molecule-1, soluble Intercellular Adhesion Molecule-1, tumor necrosis factor alpha, and interleukins -1β, -6 and -8). Random intercept for each subject and several possible confounders, including combustion-related air pollution and ozone, were used in the models.</p> <p>Results</p> <p>We found a 0 to 1 day lagged and up to 4 weeks cumulative responses in C-reactive protein in association with temperature. We observed a 24.9% increase [95% Confidence interval (CI): 7.36, 45.2] in C-reactive protein for a 5°C decrease in the 4 weeks' moving average of temperature. We observed similar associations also between temperature and soluble Intercellular Adhesion Molecule-1 (4.52%, 95% CI: 1.05, 8.10, over 4 weeks' moving average), and between temperature and soluble Vascular Cell Adhesion Molecule-1 (6.60%, 95% CI: 1.31, 12.2 over 4 weeks' moving average). Penalized spline models showed no deviation from linearity. There were no associations between temperature and other inflammation markers.</p> <p>Conclusions</p> <p>Cumulative exposure to decreased temperature is associated with an increase in inflammation marker levels among elderly men. This suggests that inflammation markers are part of intermediate processes, which may lead to cold-, but not heat-, related cardiovascular deaths.</p

Determination of sin2 θeff w using jet charge measurements in hadronic Z decays

The electroweak mixing angle is determined with high precision from measurements of the mean difference between forward and backward hemisphere charges in hadronic decays of the Z. A data sample of 2.5 million hadronic Z decays recorded over the period 1990 to 1994 in the ALEPH detector at LEP is used. The mean charge separation between event hemispheres containing the original quark and antiquark is measured for bb̄ and cc̄ events in subsamples selected by their long lifetimes or using fast D*'s. The corresponding average charge separation for light quarks is measured in an inclusive sample from the anticorrelation between charges of opposite hemispheres and agrees with predictions of hadronisation models with a precision of 2%. It is shown that differences between light quark charge separations and the measured average can be determined using hadronisation models, with systematic uncertainties constrained by measurements of inclusive production of kaons, protons and A's. The separations are used to measure the electroweak mixing angle precisely as sin2 θeff w = 0.2322 ± 0.0008(exp. stat.) ±0.0007(exp. syst.) ± 0.0008(sep.). The first two errors are due to purely experimental sources whereas the third stems from uncertainties in the quark charge separations

Measurement of the W mass by direct reconstruction in e+e−e^+ e^- collisions at 172 GeV

The mass of the W boson is obtained from reconstructed invariant mass distributions in W-pair events. The sample of W pairs is selected from 10.65~pb$^{-1}$ collected with the ALEPH detector at a mean centre-of-mass energy of 172.09 \GEV. The invariant mass distribution of simulated events are fitted to the experimental distributions and the following W masses are obtained: $WW \to q\overline{q}q\overline{q } m_W = 81.30 +- 0.47(stat.) +- 0.11(syst.) GeV/c^2$, $WW \to l\nu q\overline{q}(l=e,\mu) m_W = 80.54 +- 0.47(stat.) +- 0.11(syst.) GeV/c^2$, $WW \to \tau\nu q\overline{q} m_W = 79.56 +- 1.08(stat.) +- 0.23(syst.) GeV/C62$. The statistical errors are the expected errors for Monte Carlo samples of the same integrated luminosity as the data. The combination of these measurements gives: $m_W = 80.80 +- 0.11(syst.) +- 0.03(LEP energy) GeV/^2$