Hospital admissions for asthma and chronic obstructive airways disease in east London hospitals and proximity of residence to main roads

Evaluation of Health Economic Loss Due to Particulate Matter Pollution in the Seoul Subway, South Korea

Evaluating an illness's economic impact is critical for developing and executing appropriate policies. South Korea has mandatory national health insurance in the form of NHIS that provides propitious conditions for assessing the national financial burden of illnesses. The purpose of our study is to provide a comprehensive assessment of the economic impact of PM_2.5 exposure in the subway and a comparative analysis of cause-specific mortality outcomes based on the prevalent health-risk assessment of the health effect endpoints (chronic obstructive pulmonary disease (COPD), asthma, and ischemic heart disease (IHD)). We used the National Health Insurance database to calculate the healthcare services provided to health-effect endpoints, with at least one primary diagnosis in 2019. Direct costs associated with health aid or medicine, treatment, and indirect costs (calculated based on the productivity loss in health effect endpoint patients, transportation, and caregivers, including morbidity and mortality costs) were both considered. The total cost for the exposed population for these endpoints was estimated to be USD 437 million per year. Medical costs were the largest component (22.08%), followed by loss of productivity and premature death (15.93%) and other costs such as transport and caregiver costs (11.46%). The total incurred costs (per 1000 persons) were accounted to be USD 0.1771 million, USD 0.42 million, and USD 0.8678 million for COPD, Asthma, and IHD, respectively. Given that the economic burden will rise as the prevalence of these diseases rises, it is vital to adopt effective preventative and management methods strategies aimed at the appropriate population.

Residential Links to Air Pollution and School Children with Asthma in Vilnius (Population Study)

Background and objectives: Many studies have been carried out on the negative health effects of exposure to PM₁₀, PM _2.5, NO₂, CO, SO₂ and B[a]P for small populations. The main purpose of this study was to explore the association of air pollution to diagnosis of asthma for the whole huge population of school children between 7–17 years in Vilnius (Lithuania) using geographical information system analysis tools. Material and Methods: In the research, a child population of 51,235 individuals was involved. From this large database, we identified children who had asthma diagnosis J45 (ICD-10 AM). Residential pollution concentrations and proximity to roads and green spaces were obtained using the ArcGIS spatial analysis tool from simulated air pollution maps. Multiple stepwise logistic regression was used to explore the relation between air pollution concentration and proximity between the roads and green spaces where children with asthma were living. Further, we explored the interaction between variables. Results: From 51,235 school children aged 7–17 years, 3065 children had asthma in 2017. We investigated significant associations, such as the likelihood of getting sick with age (odds ratio (OR) = 0.949, p < 0.001), gender (OR = 1.357, p = 0.003), NO₂ (OR = 1.013, p = 0.019), distance from the green spaces (OR = 1.327, p = 0.013) and interactions of age × gender (OR = 1.024, p = 0.051). The influence of gender on disease is partly explained by different age dependency slopes for boys and girls. Conclusions: According to our results, younger children are more likely to get sick, more cases appended on the lowest age group from 7 to 10 years (almost half cases (49.2%)) and asthma was respectively nearly twice more common in boys (64.1%) than in girls (35.9%). The risk of asthma is related to a higher concentration of NO₂ and residence proximity to green spaces.

Small-area methods for investigation of environment and health

Small-area studies offer a powerful epidemiological approach to study disease patterns at the population level and assess health risks posed by environmental pollutants. They involve a public health investigation on a geographical scale (e.g. neighbourhood) with overlay of health, environmental, demographic and potential confounder data. Recent methodological advances, including Bayesian approaches, combined with fast-growing computational capabilities, permit more informative analyses than previously possible, including the incorporation of data at different scales, from satellites to individual-level survey information. Better data availability has widened the scope and utility of small-area studies, but has also led to greater complexity, including choice of optimal study area size and extent, duration of study periods, range of covariates and confounders to be considered and dealing with uncertainty. The availability of data from large, well-phenotyped cohorts such as UK Biobank enables the use of mixed-level study designs and the triangulation of evidence on environmental risks from small-area and individual-level studies, therefore improving causal inference, including use of linked biomarker and -omics data. As a result, there are now improved opportunities to investigate the impacts of environmental risk factors on human health, particularly for the surveillance and prevention of non-communicable diseases.

Perinatal factors and the development of childhood asthma

BACKGROUND

Perinatal factors are suspected to have a significant impact on the development of asthma; however, sufficiently powered studies have not been performed to investigate this issue.

OBJECTIVE

To evaluate whether perinatal factors and other risk factors have an independent or combined effect on the development of asthma.

METHODS

This study involved 3,770 children (mean age 9.1 years, range 5.68-12.16 years; 51.9% boys) who were enrolled in the Elementary School Student Cohort (2009-2014) in Ulsan University Hospital (Ulsan, Korea). Subjects were divided into an asthma group (n = 514) and a non-asthma group (n = 3,256).

RESULTS

Multivariate analyses showed that early life (within first week) oxygen therapy (adjusted odds ratio [aOR] 1.864, 95% confidence interval [CI] 1.156-3.004) and breastfeeding (aOR 0.763, 95% CI 0.606-0.960) were 2 significant perinatal factors influencing the development of asthma. Environmental tobacco smoke (aOR 1.634, 95% CI 1.298-2.058) and parental allergic disease (aOR 1.882, 95% CI 1.521-2.328) also were identified as risk factors. Using subgroup analyses, combined effects on asthma development were observed between perinatal factors (early life oxygen therapy and breastfeeding) and other risk factors (vicinity to major roadway [traffic-related air pollution], environmental tobacco smoke, parental allergic disease, and atopy).

CONCLUSION

Early life oxygen therapy and breastfeeding were identified as 2 important perinatal factors influencing the development of asthma. Furthermore, these factors showed combined effects with other risk factors (environmental tobacco smoke, traffic-related air pollution, parental allergic disease, and atopy) on the development of asthma.

Alternative treatment for asthma: case study of success of traditional chinese medicine treatment of children from urban areas with different levels of environmental pollution

The present study examined efficacy of traditional Chinese medicine (TCM) treatment in Dutch children with asthma in areas with differing air pollution. The study results indicate that TCM treatment of children living in more polluted urban area is less successful then that of children living in cleaner air area.

A review of spatial methods in epidemiology, 2000-2010

Understanding the impact of place on health is a key element of epidemiologic investigation, and numerous tools are being employed for analysis of spatial health-related data. This review documents the huge growth in spatial epidemiology, summarizes the tools that have been employed, and provides in-depth discussion of several methods. Relevant research articles for 2000-2010 from seven epidemiology journals were included if the study utilized a spatial analysis method in primary analysis (n = 207). Results summarized frequency of spatial methods and substantive focus; graphs explored trends over time. The most common spatial methods were distance calculations, spatial aggregation, clustering, spatial smoothing and interpolation, and spatial regression. Proximity measures were predominant and were applied primarily to air quality and climate science and resource access studies. The review concludes by noting emerging areas that are likely to be important to future spatial analysis in public health.

Air toxics exposure from vehicle emissions at a U.S. border crossing: Buffalo Peace Bridge Study

The Peace Bridge in Buffalo, New York, which spans the Niagara River at the east end of Lake Erie, is one of the busiest U.S. border crossings. The Peace Bridge plaza on the U.S. side is a complex of roads, customs inspection areas, passport control areas, and duty-free shops. On average 5000 heavy-duty diesel trucks and 20,000 passenger cars traverse the border daily, making the plaza area a potential "hot spot" for emissions from mobile sources. In a series of winter and summer field campaigns, we measured air pollutants, including many compounds considered by the U.S. Environmental Protection Agency (EPA*) as mobile-source air toxics (MSATs), at three fixed sampling sites: on the shore of Lake Erie, approximately 500 m upwind (under predominant wind conditions) of the Peace Bridge plaza; immediately downwind of (adjacent to) the plaza; and 500 m farther downwind, into the community of west Buffalo. Pollutants sampled were particulate matter (PM) < or = 10 microm (PM10) and < or = 2.5 microm (PM2.5) in aerodynamic diameter, elemental carbon (EC), 28 elements, 25 volatile organic compounds (VOCs) including 3 carbonyls, 52 polycyclic aromatic hydrocarbons (PAHs), and 29 nitrogenated polycyclic aromatic hydrocarbons (NPAHs). Spatial patterns of counts of ultrafine particles (UFPs, particles < 0.1 microm in aerodynamic diameter) and of particle-bound PAH (pPAH) concentrations were assessed by mobile monitoring in the neighborhood adjacent to the Peace Bridge plaza using portable instruments and Global Positioning System (GPS) tracking. The study was designed to assess differences in upwind and downwind concentrations of MSATs, in areas near the Peace Bridge plaza on the U.S. side of the border. The Buffalo Peace Bridge Study featured good access to monitoring locations proximate to the plaza and in the community, which are downwind with the dominant winds from the direction of Lake Erie and southern Ontario. Samples from the lakeside Great Lakes Center (GLC), which is upwind of the plaza with dominant winds, were used to characterize contaminants in regional air masses. On-site meteorologic measurements and hourly truck and car counts were used to assess the role of traffic on UFP counts and pPAH concentrations. The array of parallel and perpendicular residential streets adjacent to the plaza provided a grid on which to plot the spatial patterns of UFP counts and pPAH concentrations to determine the extent to which traffic emissions from the Peace Bridge plaza might extend into the neighboring community. For lake-wind conditions (southwest to northwest) 12-hour integrated daytime samples showed clear evidence that vehicle-related emissions at the Peace Bridge plaza were responsible for elevated downwind concentrations of PM2.5, EC, and benzene, toluene, ethylbenzene, and xylenes (BTEX), as well as 1,3-butadiene and styrene. The chlorinated VOCs and aldehydes were not differentially higher at the downwind site. Several metals (aluminum, calcium, iron, copper, and antimony) were two times higher at the site adjacent to the plaza as they were at the upwind GLC site on lake-wind sampling days. Other metals (beryllium, sodium, magnesium, potassium, titanium, manganese, cobalt, strontium, tin, cesium, and lanthanum) showed significant increases downwind as well. Sulfur, arsenic, selenium, and a few other elements appeared to be markers for regional transport as their upwind and downwind concentrations were correlated, with ratios near unity. Using positive matrix factorization (PMF), we identified the sources for PAHs at the three fixed sampling sites as regional, diesel, general vehicle, and asphalt volatilization. Diesel exhaust at the Peace Bridge plaza accounted for approximately 30% of the PAHs. The NPAH sources were identified as nitrate (NO3) radical reactions, diesel, and mixed sources. Diesel exhaust at the Peace Bridge plaza accounted for 18% of the NPAHs. Further evidence for the impact of the Peace Bridge plaza on local air quality was found when the differences in 10-minute average UFP counts and pPAH concentrations were calculated between pairs of sites and displayed by wind direction. With winds from approximately 160 degrees through 220 degrees, UFP counts adjacent to the plaza were 10,000 to 20,000 particles/cm3 higher than those upwind of the plaza. A similar pattern was displayed for pPAH concentrations adjacent to the plaza, which were between 10 and 20 ng/m3 higher than those at the upwind GLC site. Regression models showed better correlation with traffic variables for pPAHs than for UFPs. For pPAHs, truck counts and car counts had significant positive correlations, with similar magnitudes for the effects of trucks and cars, despite lower truck counts. Examining all traffic variables, including traffic counts and counts divided by wind speed, the multivariate regression analysis had an adjusted coefficient of determination (R2) of 0.34 for pPAHs, with all terms significant at P < 0.002. Study staff members traversed established routes in the neighborhood while carrying instruments to record continuous UFP and pPAH values. They also carried a GPS, which was used to provide location-specific time-stamped data. Analyses using a geographic information system (GIS) demonstrated that emissions at the Peace Bridge plaza, at times, affected ambient air quality over several blocks (a few hundred meters). Under lake-wind conditions, overall spatial patterns in UFP and pPAH levels were similar for summer and winter and for morning and afternoon sampling sessions. The Buffalo Peace Bridge Study demonstrated that a concentration of motor vehicles resulted in elevated levels of mobile-source-related emissions downwind, to distances of 300 m to 600 m. The study provides a unique data set to assess interrelationships among MSATs and to ascertain the impact of heavy-duty diesel vehicles on air quality.

Asthma exacerbation and proximity of residence to major roads: a population-based matched case-control study among the pediatric Medicaid population in Detroit, Michigan

BACKGROUND

The relationship between asthma and traffic-related pollutants has received considerable attention. The use of individual-level exposure measures, such as residence location or proximity to emission sources, may avoid ecological biases.

METHOD

This study focused on the pediatric Medicaid population in Detroit, MI, a high-risk population for asthma-related events. A population-based matched case-control analysis was used to investigate associations between acute asthma outcomes and proximity of residence to major roads, including freeways. Asthma cases were identified as all children who made at least one asthma claim, including inpatient and emergency department visits, during the three-year study period, 2004-06. Individually matched controls were randomly selected from the rest of the Medicaid population on the basis of non-respiratory related illness. We used conditional logistic regression with distance as both categorical and continuous variables, and examined non-linear relationships with distance using polynomial splines. The conditional logistic regression models were then extended by considering multiple asthma states (based on the frequency of acute asthma outcomes) using polychotomous conditional logistic regression.

RESULTS

Asthma events were associated with proximity to primary roads with an odds ratio of 0.97 (95% CI: 0.94, 0.99) for a 1 km increase in distance using conditional logistic regression, implying that asthma events are less likely as the distance between the residence and a primary road increases. Similar relationships and effect sizes were found using polychotomous conditional logistic regression. Another plausible exposure metric, a reduced form response surface model that represents atmospheric dispersion of pollutants from roads, was not associated under that exposure model.

CONCLUSIONS

There is moderately strong evidence of elevated risk of asthma close to major roads based on the results obtained in this population-based matched case-control study.

Geographical information system and environmental epidemiology: a cross-sectional spatial analysis of the effects of traffic-related air pollution on population respiratory health

BACKGROUND

Traffic-related air pollution is a potential risk factor for human respiratory health. A Geographical Information System (GIS) approach was used to examine whether distance from a main road (the Tosco-Romagnola road) affected respiratory health status.

METHODS

We used data collected during an epidemiological survey performed in the Pisa-Cascina area (central Italy) in the period 1991-93. A total of 2841 subjects participated in the survey and filled out a standardized questionnaire on health status, socio-demographic information, and personal habits. A variable proportion of subjects performed lung function and allergy tests. Highly exposed subjects were defined as those living within 100 m of the main road, moderately exposed as those living between 100 and 250 m from the road, and unexposed as those living between 250 and 800 m from the road. Statistical analyses were conducted to compare the risks for respiratory symptoms and diseases between exposed and unexposed. All analyses were stratified by gender.

RESULTS

The study comprised 2062 subjects: mean age was 45.9 years for men and 48.9 years for women. Compared to subjects living between 250 m and 800 m from the main road, subjects living within 100 m of the main road had increased adjusted risks for persistent wheeze (OR = 1.76, 95% CI = 1.08-2.87), COPD diagnosis (OR = 1.80, 95% CI = 1.03-3.08), and reduced FEV1/FVC ratio (OR = 2.07, 95% CI = 1.11-3.87) among males, and for dyspnea (OR = 1.61, 95% CI = 1.13-2.27), positivity to skin prick test (OR = 1.83, 95% CI = 1.11-3.00), asthma diagnosis (OR = 1.68, 95% CI = 0.97-2.88) and attacks of shortness of breath with wheeze (OR = 1.67, 95% CI = 0.98-2.84) among females.

CONCLUSION

This study points out the potential effects of traffic-related air pollution on respiratory health status, including lung function impairment. It also highlights the added value of GIS in environmental health research.

Exposure to traffic: lung function and health status in adults with asthma

BACKGROUND

Exposure to traffic has been associated with asthma outcomes in children, but its effect on asthma in adults has not been well studied.

OBJECTIVE

To test the hypothesis that lung function and health status are associated with traffic exposures.

METHODS

We measured FEV(1) % predicted, general health status using the Physical Component Scale of the 12-item Short Form (SF-12 PCS), and quality of life (QoL) using the Marks Asthma Quality of Life questionnaire in a cohort of adults with asthma or rhinitis (n = 176; 145 with asthma). We assessed exposures to traffic by geocoding subjects' residential addresses and assigning distance to roadways. Associations between distance to nearest roadway and distance to nearest major roadway and FEV(1) % predicted or SF-12 PCS were studied by using linear regression.

RESULTS

FEV(1) % predicted was positively associated with distance from both nearest roadway (P = .01) and nearest major roadway (P = .02). SF-12 PCS and QoL were not significantly associated with either traffic variable. Adjustment for income, smoking, and obesity did not substantively change the associations of the traffic variables with FEV(1) % predicted (P = .04 for nearest roadway and P = .02 for nearest major roadway) and did not cause associations with either SF-12 PCS or QoL to become significant.

CONCLUSIONS

Traffic exposure was associated with decreased lung function in adults with asthma.

Error and bias in determining exposure potential of children at school locations using proximity-based GIS techniques

BACKGROUND

The widespread availability of powerful tools in commercial geographic information system (GIS) software has made address geocoding a widely employed technique in spatial epidemiologic studies.

OBJECTIVE

The objective of this study was to determine the effect of the positional error in geocoding on the analysis of exposure to traffic-related air pollution of children at school locations.

METHODS

For a case study of Orange County, Florida, we determined the positional error of geocoding of school locations through comparisons with a parcel database and digital orthophotography. We used four different geocoding techniques for comparison to establish the repeatability of geocoding, and an analysis of proximity to major roads to determine bias and error in environmental exposure assessment.

RESULTS

RESULTS INDICATE THAT THE POSITIONAL ERROR IN GEOCODING OF SCHOOLS IS VERY SUBSTANTIAL: We found that the 95% root mean square error was 196 m using street centerlines, 306 m using TIGER roads, and 210 and 235 m for two commercial geocoding firms. We found bias and error in proximity analysis to major roads to be unacceptably large at distances of < 500 m. Bias and error are introduced by lack of positional accuracy and lack of repeatability of geocoding of school locations.

CONCLUSIONS

These results suggest that typical geocoding is insufficient for fine-scale analysis of school locations and more accurate alternatives need to be considered.

Influence of geocoding quality on environmental exposure assessment of children living near high traffic roads

Background

The widespread availability of powerful geocoding tools in commercial GIS software and the interest in spatial analysis at the individual level have made address geocoding a widely employed technique in epidemiological studies. This study determined the effect of the positional error in street geocoding on the analysis of traffic-related air pollution on children.

Methods

For a case-study of a large sample of school children in Orange County, Florida (n = 104,865) the positional error of street geocoding was determined through comparison with a parcel database. The effect of this error was evaluated by analyzing the proximity of street and parcel geocoded locations to road segments with high traffic volume and determining the accuracy of the classification using the results of street geocoding. Of the original sample of 163,886 addresses 36% were not used in the final analysis because they could not be reliably geocoded using either street or parcel geocoding. The estimates of positional error can therefore be considered conservative underestimates.

Results

Street geocoding was found to have a median error of 41 meters, a 90^th percentile of 100 meters, a 95^th percentile of 137 meters and a 99^th percentile of 273 meters. These positional errors were found to be non-random in nature and introduced substantial bias and error in the estimates of potential exposure to traffic-related air pollution. Street geocoding was found to consistently over-estimate the number of potentially exposed children at small distances up to 250 meters. False positives and negatives were also found to be very common at these small distances.

Conclusion

Results of the case-study presented here strongly suggest that typical street geocoding is insufficient for fine-scale analysis and more accurate alternatives need to be considered.

Traffic, susceptibility, and childhood asthma

Results from studies of traffic and childhood asthma have been inconsistent, but there has been little systematic evaluation of susceptible subgroups. In this study, we examined the relationship of local traffic-related exposure and asthma and wheeze in southern California school children (5-7 years of age). Lifetime history of doctor-diagnosed asthma and prevalent asthma and wheeze were evaluated by questionnaire. Parental history of asthma and child's history of allergic symptoms, sex, and early-life exposure (residence at the same home since 2 years of age) were examined as susceptibility factors. Residential exposure was assessed by proximity to a major road and by modeling exposure to local traffic-related pollutants. Residence within 75 m of a major road was associated with an increased risk of lifetime asthma [odds ratio (OR)=1.29; 95% confidence interval (CI), 1.01-1.86], prevalent asthma (OR=1.50; 95% CI, 1.16-1.95), and wheeze (OR=1.40; 95% CI, 1.09-1.78). Susceptibility increased in long-term residents with no parental history of asthma for lifetime asthma (OR=1.85; 95% CI, 1.11-3.09), prevalent asthma (OR=2.46; 95% CI, 0.48-4.09), and recent wheeze (OR=2.74; 95% CI, 1.71-4.39). The higher risk of asthma near a major road decreased to background rates at 150-200 m from the road. In children with a parental history of asthma and in children moving to the residence after 2 years of age, there was no increased risk associated with exposure. Effect of residential proximity to roadways was also larger in girls. A similar pattern of effects was observed with traffic-modeled exposure. These results indicate that residence near a major road is associated with asthma. The reason for larger effects in those with no parental history of asthma merits further investigation.

Report of workshop on traffic, health, and infrastructure planning

Recent air pollutant measurement data document unique aspects of the air pollution mixture near roadways, and an expanding body of epidemiological data suggests increased risks for exacerbation of asthma and other respiratory diseases, premature mortality, and certain cancers and birth outcomes from air pollution exposures in populations residing in relatively close proximity to roadways. The Workshop on Traffic, Health, and Infrastructure Planning, held in February 2004, was convened to provide a forum for interdisciplinary discussion of motor vehicle emissions, exposures and potential health effects related to proximity to motor vehicle traffic. This report summarizes the workshop discussions and findings regarding the current science on this issue, identifies planning and policy issues related to localized motor vehicle emissions and health concerns, and provides recommendations for future research and policy directions.