Cancer and mortality in relation to traffic-related air pollution among coronary patients: Using an ensemble of exposure estimates to identify high-risk individuals.

BACKGROUND: Moderate correlations were previously observed between individual estimates of traffic-related air pollution (TRAP) produced by different exposure modeling approaches. This induces exposure misclassification for a substantial fraction of subjects. AIM: We used an ensemble of well-established modeling approaches to increase certainty of exposure classification and reevaluated the association with cancers previously linked to TRAP (lung, breast and prostate), other cancers, and all-cause mortality in a cohort of coronary patients. METHODS: Patients undergoing percutaneous coronary interventions in a major Israeli medical center from 2004 to 2014 (n = 10,627) were followed for cancer (through 2015) and mortality (through 2017) via national registries. Residential exposure to nitrogen oxides (NOx) -a proxy for TRAP- was estimated by optimized dispersion model (ODM) and land use regression (LUR) (rPearson = 0.50). Mutually exclusive groups of subjects classified as exposed by none of the methods (high-certainty low-exposed), ODM alone, LUR alone, or both methods (high-certainty high-exposed) were created. Associations were examined using Cox regression models. RESULTS: During follow-up, 741 incident cancer cases were diagnosed and 3051 deaths occurred. Using a ≥25 ppb cutoff, compared with high-certainty low exposed, the multivariable-adjusted hazard ratios (95% confidence intervals) for lung, breast and prostate cancer were 1.56 (1.13-2.15) in high-certainty exposed, 1.27 (0.86-1.86) in LUR-exposed alone, and 1.13 (0.77-1.65) in ODM-exposed alone. The association of the former category was strengthened using more extreme NOx cutoffs. A similar pattern, albeit less strong, was observed for mortality, whereas no association was shown for cancers not previously linked to TRAP. CONCLUSIONS: Use of an ensemble of TRAP exposure estimates may improve classification, resulting in a stronger association with outcomes.

A hybrid model for evaluating exposure of the general population in Israel to air pollutants.

Exposure to air pollution is associated with a wide range of health effects, including increased respiratory symptoms, cancer, reproductive and birth defects, and premature death. Air quality measurements by standardized measuring equipment, although accurate, can only provide an estimate for part of the population, with decreasing accuracy further away from the monitoring sites. Estimating pollution levels over large geographical domains requires the use of air quality models which ideally incorporate air quality measurements. In order to estimate actual exposure of the population to air pollution (population-weighted concentrations of air pollutants), there is a need to combine data from air quality models with population density data. Here we present the results of exposure estimates for the entire population of Israel using a chemical transport model combined with measurements from the national monitoring network. We evaluated the individual exposure levels for the entire population to several air pollutants based on census tract units. Using this hybrid model, we found that the entire population of Israel is exposed to concentrations of PM10 and PM2.5 that exceed the target values but are below the environmental values according to the Israeli Clean Air Law. In addition, we found and that over 1.5 million residents are exposed to NOx at concentrations higher than the target values. This data may help decision makers develop targeted interventions to reduce the concentrations of specific pollutants, based on population-weighted exposure.

Robustness of Land-Use Regression Models Developed from Mobile Air Pollutant Measurements.

Land-use regression (LUR) models are useful for resolving fine scale spatial variations in average air pollutant concentrations across urban areas. With the rise of mobile air pollution campaigns, characterized by short-term monitoring and large spatial extents, it is important to investigate the effects of sampling protocols on the resulting LUR. In this study a mobile lab was used to repeatedly visit a large number of locations (∼1800), defined by road segments, to derive average concentrations across the city of Montreal, Canada. We hypothesize that the robustness of the LUR from these data depends upon how many independent, random times each location is visited (Nvis) and the number of locations (Nloc) used in model development and that these parameters can be optimized. By performing multiple LURs on random sets of locations, we assessed the robustness of the LUR through consistency in adjusted R2 (i.e., coefficient of variation, CV) and in regression coefficients among different models. As Nloc increased, R2adj became less variable; for Nloc = 100 vs Nloc = 300 the CV in R2adj for ultrafine particles decreased from 0.088 to 0.029 and from 0.115 to 0.076 for NO2. The CV in the R2adj also decreased as Nvis increased from 6 to 16; from 0.090 to 0.014 for UFP. As Nloc and Nvis increase, the variability in the coefficient sizes across the different model realizations were also seen to decrease.

Back-extrapolating a land use regression model for estimating past exposures to traffic-related air pollution.

Land use regression (LUR) models rely on air pollutant measurements for their development, and are therefore limited to recent periods where such measurements are available. Here we propose an approach to overcome this gap and calculate LUR models several decades before measurements were available. We first developed a LUR model for NOx using annual averages of NOx at all available air quality monitoring sites in Israel between 1991 and 2011 with time as one of the independent variables. We then reconstructed historical spatial data (e.g., road network) from historical topographic maps to apply the model's prediction to each year from 1961 to 2011. The model's predictions were then validated against independent estimates about the national annual NOx emissions from on-road vehicles in a top-down approach. The model's cross validated R2 was 0.74, and the correlation between the model's annual averages and the national annual NOx emissions between 1965 and 2011 was 0.75. Information about the road network and population are persistent predictors in many LUR models. The use of available historical data about these predictors to resolve the spatial variability of air pollutants together with complementary national estimates on the change in pollution levels over time enable historical reconstruction of exposures.

Beyond lung cancer: air pollution and bladder, breast and prostate cancer incidence.

BACKGROUND: The carcinogenicity of air pollution and its impact on the risk of lung cancer is well known; however, there are still knowledge gaps and mixed results for other sites of cancer. METHODS: The current study aimed to evaluate the associations between ambient air pollution [fine particulate matter (PM2.5) and nitrogen oxides (NOx)] and cancer incidence. Exposure assessment was based on historical addresses of >900 000 participants. Cancer incidence included primary cancer cases diagnosed from 2007 to 2015 (n = 30 979). Cox regression was used to evaluate the associations between ambient air pollution and cancer incidence [hazard ratio (HR), 95% CI]. RESULTS: In the single-pollutant models, an increase of one interquartile range (IQR) (2.11 µg/m3) of PM2.5 was associated with an increased risk of all cancer sites (HR = 1.51, 95% CI: 1.47-1.54), lung cancer (HR = 1.73, 95% CI: 1.60-1.87), bladder cancer (HR = 1.50, 95% CI: 1.37-1.65), breast cancer (HR = 1.50, 95% CI: 1.42-1.58) and prostate cancer (HR = 1.41, 95% CI: 1.31-1.52). In the single-pollutant and the co-pollutant models, the estimates for PM2.5 were stronger compared with NOx for all the investigated cancer sites. CONCLUSIONS: Our findings confirm the carcinogenicity of ambient air pollution on lung cancer and provide additional evidence for bladder, breast and prostate cancers. Further studies are needed to confirm our observation regarding prostate cancer. However, the need for more research should not be a barrier to implementing policies to limit the population's exposure to air pollution.

Residential greenness and lower breast and prostate cancer incidence: Evidence from a retrospective cohort study of 977,644 participants from Israel.

BACKGROUND: There is limited evidence on the associations between residential greenness and cancer incidence in longitudinal studies. OBJECTIVES: The aim of the study was to evaluate the associations between weighted mean residential greenness exposure and cancer incidence. METHODS: This is a registry based retrospective cohort study of 977,644 participants. The residential greenness exposure was estimated for every participant, as the weighted mean residential greenness exposure. This was based on the mean Normalized Difference Vegetation Index (NDVI) in the residential small geographic area and the duration of the residence in this area. Cancer incidence cases included consecutive newly diagnosed cases of primary cancer. Analyses were conducted for all cancer sites, lung cancer, bladder cancer, breast cancer, prostate cancer and melanoma-skin cancer. Cox regression models were used to evaluate the crude and adjusted associations (hazards ratios (HR) and its 95 % confidence intervals (CIs)) between tertiles of residential greenness and cancer incidence. Further adjusted models to nitrogen oxides (NOx) were estimated. RESULTS: After adjustment to covariates, exposure to the highest tertile of residential greenness, compared to the lowest, were associated with lower risk for all cancer sites (HR = 0.88, 95 % CI: 0.86-0.90), breast cancer (HR = 0.85, 95 % CI: 0.80-0.89) and prostate cancer (HR = 0.85, 95 % CI: 0.79-0.91). In addition, lower risk were observed for the middle tertile of exposure and all cancer sites (HR = 0.88, 95 % CI: 0.86-0.90), breast cancer (HR = 0.88, 95 % CI: 0.84-0.92) and prostate cancer (HR = 0.83, 95 % CI: 0.79-0.89). There was no evidence for mediation by air pollution (NOx). DISCUSSION: Residential greenness demonstrated beneficial associations with lower risk for all cancers, breast and prostate cancers. If our observations will be replicated, it may present a useful avenue for public-health intervention to reduce cancer burden through the provision of greenness exposure.

[Health Information Technology -where are we heading?].

The current issue of "Harefuah" dedicates a special corner to Health Information Technology (HIT), with a collection of five review papers discussing different areas of the field, focusing on its benefits to the quality of healthcare. In the first paper Topaz and Ash describe the United States MeaningfuL Use project, and list the lessons that the Israeli health system should learn from it. Zelingher and Ash analyze the decision of the Israeli Ministry of Health to move from the old coding system of ICD-9-CM to a combination of SNOMED-CT as a clinical terminology system and ICD-10-CM as the classification coding system. The authors conclude that achieving a standardized, homogenous and thorough coding of problems, diagnoses and procedures will enable interoperability in the Israeli health system. Shalom et al present us to the world of computerized clinical guidelines. They review the different projects that aim to bring tools and methods to transform the paper based guidelines to computer programs that support the everyday decisions that physicians take regarding their patients. The authors focus on their experience in developing methodology, tools and a library of computerized guidelines, and describe their evaluation in several projects. Shahar et al dive deeper to describe the challenge of representing time in cLinicaL guidelines and creating tools to discover new knowledge based on represented known knowledge. These two papers demonstrate the meaningful use of medicaL data. In the last article, Siegal addresses some legal concerns evolving from the HIT revolution, pointing to the emerging concepts in Israeli jurisprudence, which regards medical IT as an important contribution to patient empowerment, aspects of medical risk management and management of national health system resources. In the judgment of the Israeli court, a medical organization will possibly have to take the responsibiLity of not implementing a proven HIT system. This paper concludes with descriptions of two studies evaluating health information systems in Israel. These studies will be presented at the forthcoming conference of the IsraeLi Association of Medical Informatics (ILAMI).

Concentration-response relationships between hourly particulate matter and ischemic events: A case-crossover analysis of effect modification by season and air-mass origin.

Most studies linking cardiovascular disease with particulate matter (PM) exposures have focused on total mass concentrations, regardless of their origin. However, the origin of an air mass is inherently linked to particle composition and possible toxicity. We examine how the concentration-response relation between hourly PM exposure and ischemic events is modified by air-mass origin and season. Using telemedicine data, we conducted a case-crossover study of 1855 confirmed ischemic cardiac events in Israel (2005-2013). Based on measurements at three fixed-sites in Tel Aviv and Haifa, ambient PM with diameter < 2.5 µm (PM2.5) and 2.5-10 µm (PM10-2.5) concentrations during the hours before event onset were compared with matched control periods using conditional logistic regression that allowed for non-linearity. We also examined effect modification of these associations based on the geographical origin of each air mass by season. Independent of the geographical origin of the air mass, we observed concentration-response curves that were supralinear. For example, the overall odds ratios (ORs) of ischemic events for an increase of 10-µg/m3 in the 2-h average of PM10-2.5 were 1.08 (95% confidence interval (CI): 1.03-1.14) and 1.00 (0.99-1.01) at the median (17.8 µg/m3) and 95th percentile (82.3 µg/m3) values, respectively. Associations were strongest at low levels of PM10-2.5 when air comes from central Europe in the summer (OR: 1.27; 95% CI: 1.06, 1.52). Our study demonstrates that hourly associations between PM2.5 and PM10-2.5 and ischemic cardiac events are supralinear during diverse pollution conditions in a single population that experiences a wide range of exposure levels.

Carbohydrate binding modules: biochemical properties and novel applications.

Polysaccharide-degrading microorganisms express a repertoire of hydrolytic enzymes that act in synergy on plant cell wall and other natural polysaccharides to elicit the degradation of often-recalcitrant substrates. These enzymes, particularly those that hydrolyze cellulose and hemicellulose, have a complex molecular architecture comprising discrete modules which are normally joined by relatively unstructured linker sequences. This structure is typically comprised of a catalytic module and one or more carbohydrate binding modules (CBMs) that bind to the polysaccharide. CBMs, by bringing the biocatalyst into intimate and prolonged association with its substrate, allow and promote catalysis. Based on their properties, CBMs are grouped into 43 families that display substantial variation in substrate specificity, along with other properties that make them a gold mine for biotechnologists who seek natural molecular "Velcro" for diverse and unusual applications. In this article, we review recent progress in the field of CBMs and provide an up-to-date summary of the latest developments in CBM applications.

Emissions vs. turbulence and atmospheric stability: A study of their relative importance in determining air pollutant concentrations.

Air pollution in the urban environment is a major concern. The ambient concentrations depend on the levels of transboundary imported pollution, the intensity of local sources and the prevailing atmospheric conditions. This work studies the relative impact of two atmospheric variables-atmospheric stability and regional scale turbulence-in determining the air pollution concentrations. We considered a setting (downtown Haifa, Israel) impacted by a large variety of sources, emitting pollutants with different chemical attributes and atmospheric life times. We found that traffic accounts for most of the locally produced pollution in the study location. However, the meteorological factors can overwhelm its impact and dictate the concentrations. The switch from stable to convective conditions and the more vigorous daytime wind are associated with a premature end of the morning peak concentrations that result from rush hour emissions of NOx, Black Carbon (BC) and ultra-fine particles. It results in daytime concentration which are lower than (winter) or equal to (summer) those at night, in spite of the much lower night-time traffic volumes. Similar, albeit weaker, impact was detected in the benzene and toluene concentrations. Sources outside the study area are responsible for most of the CO, PM1 and PM2.5 concentrations but during winter nights, characterised by strong atmospheric stability and low turbulence, their concentrations are elevated due to the local emissions. We developed a diagnostic statistical nonlinear model for the pollutant concentrations, which points to a stronger association of the atmospheric stability with the concentrations during stable conditions but turbulence dominating during convective conditions. Our findings explain the relatively low overall concentrations of locally emitted pollutants in the study area but warn of the potential for high concentrations during night-time in locations with comparable meteorological conditions.

Preexisting coronary heart disease and susceptibility to long-term effects of traffic-related air pollution: A matched cohort analysis.

BACKGROUND: Individuals with coronary heart disease are considered susceptible to traffic-related air pollution exposure. Yet, cohort-based evidence on whether preexisting coronary heart disease modifies the association of traffic-related air pollution with health outcomes is lacking. AIM: Using data of four Israeli cohorts, we compared associations of traffic-related air pollution with mortality and cancer between coronary heart disease patients and matched controls from the general population. METHODS: Subjects hospitalized with acute coronary syndrome from two patient cohorts (inception years: 1992-1993 and 2006-2014) were age- and sex-matched to coronary heart disease-free participants of two cycles of the Israeli National Health and Nutrition Surveys (inception years: 1999-2001 and 2005-2006). Ambient concentrations of nitrogen oxides at the residential place served as a proxy for traffic-related air pollution exposure across all cohorts, based on a high-resolution national land use regression model (50 m). Data on all-cause mortality (last update: 2018) and cancer incidence (last update: 2016) were retrieved from national registries. Cox-derived stratum-specific hazard ratios with 95% confidence intervals were calculated, adjusted for harmonized covariates across cohorts, including age, sex, ethnicity, neighborhood socioeconomic status, smoking, diabetes, hypertension, prior stroke and prior malignancy (the latter only in the mortality analysis). Effect-modification was examined by testing nitrogen oxides-by-coronary heart disease interaction term in the entire matched cohort. RESULTS: The cohort (mean (standard deviation) age 61.5 (14) years; 44% women) included 2393 matched pairs, among them 2040 were cancer-free at baseline. During a median (25th-75th percentiles) follow-up of 13 (10-19) and 11 (7-17) years, 1458 deaths and 536 new cancer cases were identified, respectively. In multivariable-adjusted models, a 10-parts per billion nitrogen oxides increment was positively associated with all-cause mortality among coronary heart disease patients (hazard ratio = 1.13, 95% confidence interval 1.05-1.22), but not among controls (hazard ratio = 1.00, 0.93-1.08) (pinteraction = 0.003). A similar pattern was seen for all-cancer incidence (hazard ratioCHD = 1.19 (1.03-1.37), hazard ratioCHD-Free = 0.93 (0.84-1.04) (pinteraction = 0.01)). Associations were robust to multiple sensitivity analyses. CONCLUSIONS: Coronary heart disease patients might be at increased risk for traffic-related air pollution-associated mortality and cancer, irrespective of their age and sex. Patients and clinicians should be more aware of the adverse health effects on coronary heart disease patients of chronic exposure to vehicle emissions.

Surface chemical modification induces nanometer scale electron confinement in field effect device.

Design, preparation, and study of physicochemical properties of molecular assemblies are extremely challenging multidisciplinary research fields. Understanding the elementary principles that correlate these properties with molecular level of electronic behavior will enable us to control basic properties of molecule-based compounds as well as of classical semiconductors. In particular, chemical modification of field effect sensor devices where the metal gate is replaced with organic molecular layer, projects a crucial impact upon the electrical properties of the sensor. In these cases it is important to control the effects in order to ensure that the organic gate is optimized for sensing. Here we used fully depleted silicon-on-insulator (SOI) ion sensitive field effect transistor in order to analyze the projection of surface chemical modification on electronic performance. We suggest that surface activation and the application of 3-aminopropyltrimethoxysilane on top of the gate dielectric introduces negative charge at the Si/SiO(2) interface or/and on top of the gate dielectric and consequently an accumulation layer that confines the electrons to the bottom of the SOI channel. The transistor gain postmodification is characteristic of volume inversion, and therefore suggests that, following modification, the channel electrons are confined to SOI thickness of <10 nm. Finally, measurements of pH sensitivity indicate that the pH sensitivity post-UV/O(3) treatment is maximized suggesting that the negative charge is introduced during the activation process, where the density of the negatively charged amphoteric sites maximized.

Standard CMOS Fabrication of a Sensitive Fully Depleted Electrolyte-Insulator-Semiconductor Field Effect Transistor for Biosensor Applications.

Microfabricated semiconductor devices are becoming increasingly relevant for detection of biological and chemical components. The integration of active biological materials together with sensitive transducers offers the possibility of generating highly sensitive, specific, selective and reliable biosensors. This paper presents the fabrication of a sensitive, fully depleted (FD), electrolyte-insulator-semiconductor field-effect transistor (EISFET) made with a silicon-on-insulator (SOI) wafer of a thin 10-30 nm active SOI layer. Initial results are presented for device operation in solutions and for bio-sensing. Here we report the first step towards a high volume manufacturing of a CMOS-based biosensor that will enable various types of applications including medical and environmental sensing.

Node-to-node field calibration of wireless distributed air pollution sensor network.

Low-cost air quality sensors offer high-resolution spatiotemporal measurements that can be used for air resources management and exposure estimation. Yet, such sensors require frequent calibration to provide reliable data, since even after a laboratory calibration they might not report correct values when they are deployed in the field, due to interference with other pollutants, as a result of sensitivity to environmental conditions and due to sensor aging and drift. Field calibration has been suggested as a means for overcoming these limitations, with the common strategy involving periodical collocations of the sensors at an air quality monitoring station. However, the cost and complexity involved in relocating numerous sensor nodes back and forth, and the loss of data during the repeated calibration periods make this strategy inefficient. This work examines an alternative approach, a node-to-node (N2N) calibration, where only one sensor in each chain is directly calibrated against the reference measurements and the rest of the sensors are calibrated sequentially one against the other while they are deployed and collocated in pairs. The calibration can be performed multiple times as a routine procedure. This procedure minimizes the total number of sensor relocations, and enables calibration while simultaneously collecting data at the deployment sites. We studied N2N chain calibration and the propagation of the calibration error analytically, computationally and experimentally. The in-situ N2N calibration is shown to be generic and applicable for different pollutants, sensing technologies, sensor platforms, chain lengths, and sensor order within the chain. In particular, we show that chain calibration of three nodes, each calibrated for a week, propagate calibration errors that are similar to those found in direct field calibration. Hence, N2N calibration is shown to be suitable for calibration of distributed sensor networks.

Fine and Coarse Particulate Matter Exposures and Associations with Acute Cardiac Events among Participants in a Telemedicine Service: A Case-Crossover Study.

BACKGROUND: Subclinical cardiovascular changes have been associated with ambient particulate matter (PM) exposures within hours. Although the U.S. Environmental Protection Agency continues to look for additional evidence of effects associated with sub-daily PM exposure, this information is still limited because most studies of clinical events have lacked data on the onset time of symptoms to assess rapid increased risk. OBJECTIVE: Our objective was to investigate associations between sub-daily exposures to PM and acute cardiac events using telemedicine data. METHODS: We conducted a case-crossover study among telemedicine participants [Formula: see text] of age who called a service center for cardiac-related symptoms and were transferred to a hospital in Tel Aviv and Haifa, Israel (2002-2013). Ambient [Formula: see text] and [Formula: see text] measured by monitors located in each city during the hours before the patient called with symptoms were compared with matched control periods. We investigated the sensitivity of these associations to more accurate symptom onset time and greater certainty of diagnosis. RESULTS: We captured 12,661 calls from 7,617 subscribers experiencing ischemic (19%), arrhythmic (31%), or nonspecific (49%) cardiac events. PM concentrations were associated with small increases in the odds of cardiac events. For example, odds ratios for any cardiac event in association with a [Formula: see text] increase in 6-h and 24-h average [Formula: see text] were 1.008 [95% confidence interval (CI): 0.998, 1.018] and 1.006 (95% CI: 0.995, 1.018), respectively, and for [Formula: see text] were 1.003 (95% CI: 1.001, 1.006) and 1.003 (95% CI: 1.000, 1.007), respectively. Associations were stronger when using exposures matched to the call time rather than calendar date and for events with higher certainty of the diagnosis. CONCLUSIONS: Our analysis of telemedicine data suggests that risks of cardiac events in telemedicine participants [Formula: see text] of age may increase within hours of PM exposures. https://doi.org/10.1289/EHP2596.

Chronic exposure to traffic-related air pollution and cancer incidence among 10,000 patients undergoing percutaneous coronary interventions: A historical prospective study.

Background Exposure to traffic-related air pollution (TRAP) is considered to have a carcinogenic effect. The authors previously reported a nonsignificant association between TRAP and cancer risk in a relatively small cohort of myocardial infarction survivors. This study assessed whether TRAP exposure is associated with subsequent cancer in a large cohort of coronary patients. Methods & results Consecutive patients undergoing percutaneous coronary interventions in a major medical centre in central Israel from 2004 to 2014 were followed for cancer through 2015. Residential levels of nitrogen oxides (NOx) - a proxy for TRAP - were estimated based on a high-resolution national land use regression model. Cox proportional hazards models were constructed to study relationships with cancer. Among 12,784 candidate patients, 9816 had available exposure data and no history of cancer (mean age, 68 years; 77% men). During a median (25th-75th percentiles) follow-up of 7.0 (3.9-9.3) years, 773 incident cases of cancer (8%) were diagnosed. In a multivariable-adjusted model, a 10-ppb increase in mean NOx exposure was associated with hazard ratios (HRs) of 1.07 (95% confidence interval [CI] 1.00-1.15) for all-site cancer and 1.16 (95% CI 1.05-1.28) for cancers previously linked to TRAP (lung, breast, prostate, kidney and bladder). A stronger association was observed for breast cancer (HR = 1.43; 95% CI 1.12-1.83). Associations were slightly strengthened after limiting the cohort to patients with more precise exposure assessment. Conclusion Coronary patients exposed to TRAP are at increased risk of several types of cancer, particularly lung, prostate and breast. As these cancers are amenable to prevention strategies, identifying highly exposed patients may provide an opportunity to improve clinical care.

Improving modeled air pollution concentration maps by residual interpolation.

Models that are used to map air pollutant concentrations are not free of errors. A possible approach for improving the final concentration map is to interpolate the residuals of the initial model concentration estimates. Due to the possible spatial autocorrelation of the residuals of the initial model estimates, Bayesian inference schemes were suggested for this task, since they can correctly adjust the level of fitting of the residuals to the random measurement errors. However, the complexity of Bayesian methods often discourages their use. Here, we present an alternative and simpler approach, using a leave-one-out cross-validation to determine the optimal level of fitting of the residual correction. We show that the optimal correction level is related to the extent of the spatial autocorrelation of the cross-validated residuals. Namely, when the residuals are not autocorrelated residual correction is unnecessary, and if employed may actually degrade the quality of the final concentration map. Moreover, our approach enables to optimize the residual correction based on different target performance measures, with a possibly different optimal correction depending on the performance measure used. Hence, different target performance measures can be chosen to fit best the specific application of interest. The method is demonstrated using output of three different models used for estimating NOx and NO2 concentrations over Israel. We show that our approach can be used as an exploratory step, for assessing the potential benefit of residual correction, and as a simple alternative to Bayesian schemes.

Exposure estimation errors to nitrogen oxides on a population scale due to daytime activity away from home.

Accurate estimation of exposure to air pollution is necessary for assessing the impact of air pollution on the public health. Most environmental epidemiology studies assign the home address exposure to the study subjects. Here, we quantify the exposure estimation error at the population scale due to assigning it solely at the residence place. A cohort of most schoolchildren in Israel (~950,000), age 6-18, and a representative cohort of Israeli adults (~380,000), age 24-65, were used. For each subject the home and the work or school addresses were geocoded. Together, these two microenvironments account for the locations at which people are present during most of the weekdays. For each subject, we estimated ambient nitrogen oxide concentrations at the home and work or school addresses using two air quality models: a stationary land use regression model and a dynamic dispersion-like model. On average, accounting for the subjects' work or school address as well as for the daily pollutant variation reduced the estimation error of exposure to ambient NOx/NO2 by 5-10ppb, since daytime concentrations at work/school and at home can differ significantly. These results were consistent regardless which air quality model as used and even for subjects that work or study close to their home. Yet, due to their usually short commute, assigning schoolchildren exposure solely at their residential place seems to be a reasonable estimation. In contrast, since adults commute for longer distances, assigning exposure of adults only at the residential place has a lower correlation with the daily weighted exposure, resulting in larger exposure estimation errors. We show that exposure misclassification can result from not accounting for the subjects' time-location trajectories through the spatiotemporally varying pollutant concentrations field.

Long-term exposure to traffic-related air pollution and cancer among survivors of myocardial infarction: A 20-year follow-up study.

BACKGROUND: Previous studies suggested a carcinogenic effect of exposure to traffic-related air pollution. Recently, higher rates of cancer incidence were observed among myocardial infarction survivors compared with the general population. We examined the association between chronic exposure to nitrogen oxides, a proxy measure for traffic-related air pollution, and cancer incidence and mortality in a cohort of myocardial infarction patients. METHODS: Patients aged ≤65 years admitted to hospital in central Israel with a first myocardial infarction in 1992-1993 were followed to 2013 for cancer incidence and cause-specific mortality. Data on sociodemographic and cancer risk factors were obtained, including time-varying information on smoking. Using land use regression models, annual averages of nitrogen oxides during follow-up were estimated individually according to home addresses. Cox proportional hazards models were constructed to study the relationships with cancer outcomes. RESULTS: During a mean follow-up of 16 (SD 7) years, 262 incident cancers and 105 cancer deaths were identified among 1393 cancer-free patients at baseline (mean age 54 years; 81% men). In adjusted models, a 10 ppb increase in mean nitrogen oxide exposure was associated with a hazard ratio (HR) of 1.06 (95% confidence interval (CI) 0.96-1.18) for cancer incidence and HR of 1.08 (95% CI 0.93-1.26) for cancer mortality. The association with lung, bladder, kidney or prostate cancer (previously linked to air pollution) was stronger (HR 1.16; 95% CI 1.00-1.33). CONCLUSIONS: Chronic exposure to traffic-related air pollution may constitute an environmental risk factor for cancer post-myocardial infarction. Variation in the strength of association between specific cancers needs to be explored further.

Linkage between the Israeli Defense Forces primary care physician demographics and usage of secondary medical services and laboratory tests.

BACKGROUND: The primary care physicians in the Israeli Defense Forces, as in the Israeli civilian health system, have two major subpopulations. Graduates of Israeli schools of medicine, and graduates of foreign medical schools, most of them in Eastern Europe. OBJECTIVE: To evaluate differences in the referral patterns of primary care physicians according to their graduation institution and demographic characteristics. METHODS: The study took place in one primary care practice in central Israel. The referrals to consultations and laboratory tests over a period of 1 year were evaluated. Physicians that had less than 37 encounters were excluded from the study. Data were extracted from the central computerized databases of the Medical Corps and Israeli Defense Forces. RESULTS: Sixty-eight physicians had a total of 18,402 encounters that resulted in 23,845 outcomes. There were no associations between demographic and training backgrounds of the physicians and their actual referral rates to consultations and laboratory tests. CONCLUSION: The background data of the primary care physicians does not predict their referral patterns and their role as "gate keepers".