Land use regression modeling of intra-urban residential variability in multiple traffic-related air pollutants

Background: There is a growing body of literature linking GIS-based measures of traffic density to asthma and other respiratory outcomes. However, no consensus exists on which traffic indicators best capture variability in different pollutants or within different settings. As part of a study on childhood asthma etiology, we examined variability in outdoor concentrations of multiple traffic-related air pollutants within urban communities, using a range of GIS-based predictors and land use regression techniques. Methods: We measured fine particulate matter (PM2.5), nitrogen dioxide (NO2), and elemental carbon (EC) outside 44 homes representing a range of traffic densities and neighborhoods across Boston, Massachusetts and nearby communities. Multiple three to four-day average samples were collected at each home during winters and summers from 2003 to 2005. Traffic indicators were derived using Massachusetts Highway Department data and direct traffic counts. Multivariate regression analyses were performed separately for each pollutant, using traffic indicators, land use, meteorology, site characteristics, and central site concentrations. Results: PM2.5 was strongly associated with the central site monitor (R2 = 0.68). Additional variability was explained by total roadway length within 100 m of the home, smoking or grilling near the monitor, and block-group population density (R2 = 0.76). EC showed greater spatial variability, especially during winter months, and was predicted by roadway length within 200 m of the home. The influence of traffic was greater under low wind speed conditions, and concentrations were lower during summer (R2 = 0.52). NO2 showed significant spatial variability, predicted by population density and roadway length within 50 m of the home, modified by site characteristics (obstruction), and with higher concentrations during summer (R2 = 0.56). Conclusion: Each pollutant examined displayed somewhat different spatial patterns within urban neighborhoods, and were differently related to local traffic and meteorology. Our results indicate a need for multi-pollutant exposure modeling to disentangle causal agents in epidemiological studies, and further investigation of site-specific and meteorological modification of the traffic-concentration relationship in urban neighborhoods

Respiratory symptoms in children living near busy roads and their relationship to vehicular traffic: results of an Italian multicenter study (SIDRIA 2)

BACKGROUND: Epidemiological studies have provided evidence that exposure to vehicular traffic increases the prevalence of respiratory symptoms and may exacerbate pre-existing asthma in children. Self-reported exposure to road traffic has been questioned as a reliable measurement of exposure to air pollutants. The aim of this study was to investigate whether there were specific effects of cars and trucks traffic on current asthma symptoms (i.e. wheezing) and cough or phlegm, and to examine the validity of self-reported traffic exposure. METHODS: The survey was conducted in 2002 in 12 centers in Northern, Center and Southern Italy, different in size, climate, latitude and level of urbanization. Standardized questionnaires filled in by parents were used to collect information on health outcomes and exposure to traffic among 33,632 6-7 and 13-14 years old children and adolescents. Three questions on traffic exposure were asked: the traffic in the zone of residence, the frequency of truck and of car traffic in the street of residence. The presence of a possible response bias for the self-reported traffic was evaluated using external validation (comparison with measurements of traffic flow in the city of Turin) and internal validations (matching by census block, in the cities of Turin, Milan and Rome). RESULTS: Overall traffic density was weakly associated with asthma symptoms but there was a stronger association with cough or phlegm (high traffic density OR = 1.24; 95% CI: 1.04, 1.49). Car and truck traffic were independently associated with cough or phlegm. The results of the external validation did not support the existence of a reporting bias for the observed associations, for all the self-reported traffic indicators examined. The internal validations showed that the observed association between traffic density in the zone of residence and respiratory symptoms did not appear to be explained by an over reporting of traffic by parents of symptomatic subjects. CONCLUSION: Children living in zones with intense traffic are at higher risk for respiratory effects. Since population characteristics are specific, the results of validation of studies on self-reported traffic exposure can not be generalized

Temporal and spatial analysis of the 2014-2015 Ebola virus outbreak in West Africa

West Africa is currently witnessing the most extensive Ebola virus (EBOV) outbreak so far recorded. Until now, there have been 27,013 reported cases and 11,134 deaths. The origin of the virus is thought to have been a zoonotic transmission from a bat to a two-year-old boy in December 2013 (ref. 2). From this index case the virus was spread by human-to-human contact throughout Guinea, Sierra Leone and Liberia. However, the origin of the particular virus in each country and time of transmission is not known and currently relies on epidemiological analysis, which may be unreliable owing to the difficulties of obtaining patient information. Here we trace the genetic evolution of EBOV in the current outbreak that has resulted in multiple lineages. Deep sequencing of 179 patient samples processed by the European Mobile Laboratory, the first diagnostics unit to be deployed to the epicentre of the outbreak in Guinea, reveals an epidemiological and evolutionary history of the epidemic from March 2014 to January 2015. Analysis of EBOV genome evolution has also benefited from a similar sequencing effort of patient samples from Sierra Leone. Our results confirm that the EBOV from Guinea moved into Sierra Leone, most likely in April or early May. The viruses of the Guinea/Sierra Leone lineage mixed around June/July 2014. Viral sequences covering August, September and October 2014 indicate that this lineage evolved independently within Guinea. These data can be used in conjunction with epidemiological information to test retrospectively the effectiveness of control measures, and provides an unprecedented window into the evolution of an ongoing viral haemorrhagic fever outbreak.status: publishe

Serum GADD45a methylation is a useful biomarker to distinguish benign vs malignant prostate disease

Prostate-specific antigen (PSA) screening for prostate cancer results in a large number of unnecessary prostate biopsies. There is a need for specific molecular markers that can be used in combination with PSA to improve the specificity of PSA screening. We examined GADD45a methylation in blood DNA as a molecular marker for prostate cancer diagnosis. The study included 82 men, with PSA levels >4 ng ml(-1) and/or abnormal digital rectal exam, who underwent prostate biopsy. We compared GADD45a methylation in DNA from serum and buffy coat in 44 patients (22 prostate cancer and 22 benign). GADD45a methylation in serum DNA was examined in 82 patients (34 cancer and 48 benign). There was no significant difference in buffy coat GADD45a methylation between cancer and benign patients. Serum GADD45a methylation was significantly higher in cancer than in benign patients. Classification and regression tree predictive model for prostate cancer including risk groups defined by PSA, free circulating DNA (fcDNA) level and GADD45a methylation yielded specificity of 87.5%, sensitivity of 94.1% and receiver operator characteristic curve area of 0.937. Serum GADD45a methylation in combination with PSA and fcDNA level was useful in distinguishing benign from prostate cancer patients

Aberrant promoter methylation in serum of prostate cancer patients and controls

e16046 Background: The current screening method for prostate cancer (PC), which is based on prostate specific antigen (PSA) level lacks specificity and sensitivity. Previous studies have reported that increased levels of free circulating DNA (fcDNA) and hypermethylation of genes are associated with several cancers. In this study we evaluated the use of fcDNA level and aberrant promoter methylation of 4 genes in serum as biomarkers for PC. Methods: 89 PC patients, 59 with prostatitis (PT) and 104 with benign prostatic hyperplasia (BPH) were enrolled. Serum DNA was analyzed for methylation of GSTPi, RARB, RASSF1A and ECAD by methylation-specific PCR. FcDNA level was analyzed by quantitative PCR. We examined the effect of methylation and fcDNA on PC risk by fitting two logistic regression models, one comparing PC vs BPH and PT vs BPH and the other comparing PC vs PT+BPH. Models were adjusted for age, race, and log 2 PSA, and tested for variation in effect of methylation by race. Similar analyses assessed the effect of fcDNA as continuous variable, after log2 transformation, and as dichotomous variable with cutpoint near the upper quartile for BPH controls. Results: When adjusted for age and log 2 PSA, positive GSTPi methylation was associated with increased risk of PC in whites (OR = 6.11, p < 0.001, PC vs BPH; OR = 3.93, p = 0.001, PC vs BPH + PT). Methylation of RARB was associated with PT independent of race (OR = 2.85, p = 0.032, PT vs BPH). Patients with fcDNA ≥180ng/ml were at twice the risk of PC compared to those with levels <180ng/ml, and this result did not vary by race. Models including both GSTPi and fcDNA confirmed the independent effect of these two factors in whites (high fcDNA OR = 3.77, p = 0.002, positive GSTPi methylation OR = 5.41, p < 0.001, PC v. BPH + PT). Although high fcDNA also increased risk of PC in blacks, the effect was not statistically significant (OR = 1.91, p = 0.189, PC vs BPH + PT). Conclusions: Our results suggest that aberrant promoter methylation of GSTPi in serum is a potential biomarker for prostate cancer in whites. Level of fcDNA in serum also appears to be an independent diagnostic marker in whites. No significant financial relationships to disclose