Distance-Weighted Traffic Density in Proximity to a Home Is a Risk Factor for Leukemia and Other Childhood Cancers

190

135

Motor vehicles are the main source of many hazardous air pollutants in California. Previous studies have shown that low-income and minority populations are more likely to live near industrial sources of pollution and in areas that do not meet national air quality standards. We estimated neighborhood exposures to motor vehicle emissions from a road network with daily traffic counts using a geographic information system. To calculate traffic density, we summed the average daily vehicle miles of travel per square mile of land area for each census block group in the state. We used 1990 census data to characterize the population by age, race and socioeconomic status in block groups with high traffic density. Block groups with more than 500,000 vehicle miles of travel per square mile were defined to be high traffic density. Statewide, about 5% of all block groups met this criterion and more than 215,000 children under 15 years of age lived in these high traffic density areas. Block groups in the lowest quartile of median family income were three times more likely to have high traffic density than block groups in the highest income quartile. The percentage of children living in high traffic density block groups increased with decreasing median family income for all race and ethnicities except White. Overall, children of color were about three times more likely to live in high-traffic areas than were white children. Based on this analysis, low-income and children of color have higher potential exposure to vehicle emissions. Future exposure assessment studies should target the highest traffic density areas, and health studies should consider the differences by income and race or ethnicity during design.

Section: Introductionmentioning

confidence: 99%

Traffic density in California: Socioeconomic and ethnic differences among potentially exposed children

Gunier

Hertz

Behren

et al. 2003

190

135

“…Nuisances perception at home was also suggested as a good proxy for traffic -related air pollution in Switzerland (Oglesby et al, 2000 ). Following the same rationale as the VESTA ''traffic density'' index, some studies combined traffic and distance data (Wilkinson et al, 1999;Pearson et al, 2000). In a recent case -control study of air pollution from traffic and childhood cancer, two cumulated exposure indices were also accommodated, as in the present study, with the same Danish OSPM software that is built in the ExTra model (Raaschou -Nielson et al, 2000;RaaschouNielson et al, 2001 ).…”

Section: Discussionmentioning

confidence: 99%

Five Epidemiological Studies on Transport and Asthma: Objectives, design and descriptive results

Zmirou¹,

Gauvin²,

et al. 2002

A case -control study was conducted in five French metropolitan areas in order to assess the role of traffic -related air pollution in the occurrence of childhood asthma. This paper presents the study design and describes the distribution of key exposure variables. A set of 217 pairs of matched 4 -to 14 -year -old cases and controls were investigated ( matching criteria: city, age, and gender ). Current and past environmental smoke exposures, indoor allergens or air pollution sources, and personal and family atopy were assessed by standard questionnaires. When possible, direct measurements were done to check the validity of this information, on current data: skin prick tests, urine cotinine, house dust mites densities, personal exposures to, and home indoor concentrations of NO x and PM 2.5 . Cumulative exposure to traffic -related pollutants was estimated through two indices: ''traffic density'' refers to a time -weighted average of the traffic density -to -road distance ratio for all home and school addresses of each child's life; ''air pollution'' index combines lifelong time -activity patterns and ambient air concentration estimates of NO x , using an air dispersion model of traffic exhausts. Average current PM 2.5 personal exposure is 23.8 g / m 3 ( SD = 17.4 ), and average indoor concentrations = 22.5 g / m 3 ( 18.2 ); corresponding values for NO 2 are 31.4 ( 13.9 ) and 36.1 ( 21.4 ) g / m 3 . Average lifelong calculated exposures to traffic -related NO x emissions are 62.6 g / m 3 ( 43.1 ). The five cities show important contrasts of exposure to traffic pollutants. These data will allow comparison of lifelong exposures to indicators of traffic exhausts between cases and controls, including during early ages, while controlling for a host of known enhancers or precipitators of airway chronic inflammation and for possible confounders.

“…Continuous long-term exposure to low environmental concentrations of benzene is an issue of special public health concern, as several investigations so far reported positive associations between residence near potential hydrocarbon emission sources (e.g., oil raffineries) or indicators of automotive emissions and acute childhood leukaemia (Knox, 1994;Lyons et al, 1995;Sans et al, 1995;Knox and Gilman, 1997;Harrison et al, 1999;Wilkinson et al, 1999). Moreover, five out of six case-control studies showed a positive association between different indicators of air pollution or heavy traffic in the vicinity of children's homes and acute leukaemia (Savitz and Feingold, 1989;Nordlinder and Jarvholm, 1997;Feychting et al, 1998;Harrison et al, 1999;Pearson et al, 2000;Raaschou-Nielsen et al, 2001;Langholz et al, 2002;Crosignani et al, 2004), whereas in three of these studies, this association turned out to be significant (Nordlinder and Jarvholm, 1997;Pearson et al, 2000;Crosignani et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

A biomarker approach to estimate the daily intake of benzene in non-smoking and smoking individuals in Germany

Schettgen

Ochsmann

Alt

et al. 2009

Owing to its carcinogenic properties, benzene is one of the most important environmental air pollutants. We have applied a simple pharmacokinetic model to estimate the individual daily exposure of persons of the general population to benzene using their urinary excretion of S-phenylmercapturic acid as biomarker of exposure. On the basis of a non-representative convenience sample of the general population, spontaneous urine samples of 43 non-smoking persons, 13 persons with exposure to environmental tobacco smoke (ETS) (as determined by urinary cotinine) and 72 smokers were analyzed for S-phenylmercapturic acid, and benzene exposure was back calculated on the basis of the results. The pharmacokinetic model was based either on estimated daily urinary volume or creatinine excretion. Median daily exposure of non-smokers was calculated to be 47 mg/day (volume-based model) and 63 mg benzene/day (creatinine-based model). ETS-exposed persons had a slightly higher median daily exposure of 65 mg/day (volume-based model) and 72 mg benzene/day (creatinine-based model). The daily exposure of smokers was significantly higher with median values of 491 mg benzene/day (volumebased model) and 693 mg benzene/day (creatinine-based model). Our biomarker-based model gave plausible results for daily benzene exposure that were in good agreement with exposure estimations published earlier. As it is purely based on the determination of individual internal dose, our model provides a powerful tool for the risk assessment of environmental benzene.