Estimation of Short-Term Effects of Air Pollution on Stroke Hospital Admissions in Wuhan, China

Background and Objective:High concentrations of air pollutants have been linked to increased incidence of stroke in North America and Europe but not yet assessed in mainland China. The aim of this study is to evaluate the association between stroke hospitalization and short-term elevation of air pollutants in Wuhan, China.Methods:Daily mean NO2, SO2 and PM10 levels, temperature and humidity were obtained from 2006 through 2008. Data on stroke hospitalizations (ICD 10: I60-I69) at four hospitals in Wuhan were obtained for the same period. A time-stratified case-crossover design was performed by season (April-September and October-March) to assess effects of pollutants on stroke hospital admissions.Results:Pollution levels were higher in October-March with averages of 136.1 μg/m3 for PM10, 63.6 μg/m3 for NO2 and 71.0 μg/m3 for SO2 than in April-September when averages were 102.0 μg/m3, 41.7 μg/m3 and 41.7 μg/m3, respectively (p<.001). During the cold season, every 10 μg/m3 increase in NO2 was associated with a 2.9% (95%C.I. 1.2%-4.6%) increase in stroke admissions on the same day. Every 10 ug/m3 increase in PM10 daily concentration was significantly associated with an approximate 1% (95% C.I. 0.1%-1.4%) increase in stroke hospitalization. A two-pollutant model indicated that NO2 was associated with stroke admissions when controlling for PM10. During the warm season, no significant associations were noted for any of the pollutants.Conclusions:Exposure to NO2 is significantly associated with stroke hospitalizations during the cold season in Wuhan, China when pollution levels are 50% greater than in the warm season. Larger and multi-center studies in Chinese cities are warranted to validate our findings. © 2013 Xiang et al

Air toxics and the risk of autism spectrum disorder: The results of a population based case-control study in southwestern Pennsylvania

Background: Autism spectrum disorders (ASD) constitute a major public health problem affecting one in 68 children. There is little understanding of the causes of ASD despite its serious social impact. Air pollution contains many toxicants known to have adverse effects on the fetus. We conducted a population based case-control study in southwestern Pennsylvania to estimate the association between ASD and 2005 US EPA modeled NATA (National Air Toxics Assessment) levels for 30 neurotoxicants. Methods: A total of 217 ASD cases born between 2005 and 2009 were recruited from local ASD diagnostic and treatment centers. There were two different control groups: 1) interviewed controls (N∈=∈224) frequency matched by child's year of birth, sex and race with complete residential histories from prior to pregnancy through the child's second birthday, and 2) 5,007 controls generated from a random sample of birth certificates (BC controls) using residence at birth. We used logistic regression analysis comparing higher to first quartile of exposure to estimate odds ratios (ORs) and 95 % confidence intervals (CI), adjusting for mother's age, education, race, smoking status, child's year of birth and sex. Results: Comparing fourth to first quartile exposures for all births, the adjusted OR for styrene was 2.04 (95 % CI∈=∈1.17-3.58, p∈=∈0.013) for the interviewed case-control analysis and 1.61 (95 % CI∈=∈1.08-2.40, p∈=∈0.018) for the BC analysis. In the BC comparison, chromium also exhibited an elevated OR of 1.60 (95 % CI∈=∈1.08-2.38, p∈=∈0.020), which was similarly elevated in the interviewed analysis (OR∈=∈1.52, 95 % CI∈=∈0.87-2.66). There were borderline significant ORs for the BC comparison for methylene chloride (OR∈=∈1.41, 95 % CI∈=∈0.96-2.07, p∈=∈0.082) and PAHs (OR∈=∈1.44, 95 % CI∈=∈0.98-2.11, p∈=∈0.064). Conclusions: Living in areas with higher levels of styrene and chromium during pregnancy was associated with increased risk of ASD, with borderline effects for PAHs and methylene chloride. These results are consistent with other studies. It is unclear, however, whether these chemicals are risk factors themselves or if they reflect the effect of a mixture of pollutants. Future work should include improved spatiotemporal estimates of exposure to air toxics, taking into account the dynamic movement of individuals during daily life

Association between overweight, obesity and self-perceived job insecurity in German employees

<p>Abstract</p> <p>Background</p> <p>Recent studies have shown an association between job insecurity and morbidity as well as mortality, however until now, knowledge about a potential association between job insecurity and overweight or obesity has been lacking.</p> <p>Methods</p> <p>In order to identify a possible association between job insecurity and overweight or obesity, we analysed data from the German Socioeconomic Panel (GSOEP) 2004/2005, a longitudinal study of private households in Germany. In this representative cohort of the German adult population, living and working conditions were observed. Data on Body Mass Index (BMI) and self-perceived probability of job loss within the next 2 years were available for 10,747 adults either employed or attending training programs.</p> <p>Results</p> <p>We identified 5,216 (49%) individuals as being overweight (BMI > 25 kg/m²) and 1,358(13%) individuals as being obese (BMI > 30 kg/m²). A total of 5,941 (55%) participants reported having concerns regarding job insecurity. In the multivariate analysis - after adjustment for relevant confounders - a statistically significant association between obesity and job insecurity (100% probability for losing the job in the following two years) could be observed with an adjusted odds ratio of 2.55 (95% confidence interval: 1.09-5.96).</p> <p>Conclusions</p> <p>Because of these results, we were able to conclude that overweight and obese persons perceive job insecurity more often than their normal weight counterparts in Germany and that the concurrence of obesity and job insecurity might lead employees into a vicious cycle. Further research with an emphasis on the occupational setting might be necessary in order to establish useful preventive programmes at the workplace.</p

Measurements of differential cross-sections in top-quark pair events with a high transverse momentum top quark and limits on beyond the Standard Model contributions to top-quark pair production with the ATLAS detector at √s = 13 TeV

Cross-section measurements of top-quark pair production where the hadronically decaying top quark has transverse momentum greater than 355 GeV and the other top quark decays into ℓνb are presented using 139 fb−1 of data collected by the ATLAS experiment during proton-proton collisions at the LHC. The fiducial cross-section at s = 13 TeV is measured to be σ = 1.267 ± 0.005 ± 0.053 pb, where the uncertainties reflect the limited number of data events and the systematic uncertainties, giving a total uncertainty of 4.2%. The cross-section is measured differentially as a function of variables characterising the tt¯ system and additional radiation in the events. The results are compared with various Monte Carlo generators, including comparisons where the generators are reweighted to match a parton-level calculation at next-to-next-to-leading order. The reweighting improves the agreement between data and theory. The measured distribution of the top-quark transverse momentum is used to search for new physics in the context of the effective field theory framework. No significant deviation from the Standard Model is observed and limits are set on the Wilson coefficients of the dimension-six operators OtG and Otq(8), where the limits on the latter are the most stringent to date. [Figure not available: see fulltext.]

Direct constraint on the Higgs–charm coupling from a search for Higgs boson decays into charm quarks with the ATLAS detector

A search for the Higgs boson decaying into a pair of charm quarks is presented. The analysis uses proton–proton collisions to target the production of a Higgs boson in association with a leptonically decaying W or Z boson. The dataset delivered by the LHC at a centre-of-mass energy of and recorded by the ATLAS detector corresponds to an integrated luminosity of 139 fb−1. Flavour-tagging algorithms are used to identify jets originating from the hadronisation of charm quarks. The analysis method is validated with the simultaneous measurement of WW, WZ and ZZ production, with observed (expected) significances of 2.6 (2.2) standard deviations above the background-only prediction for the (W/Z)Z(→cc¯) process and 3.8 (4.6) standard deviations for the (W/Z)W(→cq) process. The (W/Z)H(→cc¯) search yields an observed (expected) upper limit of 26 (31) times the predicted Standard Model cross-section times branching fraction for a Higgs boson with a mass of , corresponding to an observed (expected) constraint on the charm Yukawa coupling modifier |κc|<8.5 (12.4), at the 95% confidence level. A combination with the ATLAS (W/Z)H,H→bb¯ analysis is performed, allowing the ratio κc/κb to be constrained to less than 4.5 at the 95% confidence level, smaller than the ratio of the b- and c-quark masses, and therefore determines the Higgs-charm coupling to be weaker than the Higgs-bottom coupling at the 95% confidence level

Estimating misclassification error: a closer look at cross-validation based methods

<p>Abstract</p> <p>Background</p> <p>To estimate a classifier’s error in predicting future observations, bootstrap methods have been proposed as reduced-variation alternatives to traditional cross-validation (CV) methods based on sampling without replacement. Monte Carlo (MC) simulation studies aimed at estimating the true misclassification error conditional on the training set are commonly used to compare CV methods. We conducted an MC simulation study to compare a new method of bootstrap CV (BCV) to <it>k</it>-fold CV for estimating clasification error.</p> <p>Findings</p> <p>For the low-dimensional conditions simulated, the modest positive bias of <it>k</it>-fold CV contrasted sharply with the substantial negative bias of the new BCV method. This behavior was corroborated using a real-world dataset of prognostic gene-expression profiles in breast cancer patients. Our simulation results demonstrate some extreme characteristics of variance and bias that can occur due to a fault in the design of CV exercises aimed at estimating the true conditional error of a classifier, and that appear not to have been fully appreciated in previous studies. Although CV is a sound practice for estimating a classifier’s <it>generalization error</it>, using CV to estimate the <it>fixed misclassification error</it> of a trained classifier conditional on the training set is problematic. While MC simulation of this estimation exercise can correctly represent the average <it>bias</it> of a classifier, it will overstate the between-run <it>variance</it> of the bias.</p> <p>Conclusions</p> <p>We recommend <it>k</it>-fold CV over the new BCV method for estimating a classifier’s generalization error. The extreme negative bias of BCV is too high a price to pay for its reduced variance.</p