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Research Article

Materials and Methods Top

Population.

A new cohort was recruited in 2003 from schools in 13 southern California communities (shown in Figure 1). Nine communities were the same as in the original Children’s Health Study cohorts, and four were new. All students present in 2003 in all kindergarten and first grade classrooms (5–7 years of age) in participating schools were given a questionnaire and informed consent to take home for parents to complete. Informed consent, approved for this study by the University of Southern California Institutional Review Board, was obtained, and questionnaires were completed and returned for 5,341 (65%) of 8,193 eligible children.

Assessment of exposure to traffic-related pollutants.

We estimated distance of each participant’s residence to the nearest major road, including freeways, other highways, and arterial roads. Participant residence addresses were standardized, and their locations were geocoded to 13 m perpendicular to the side of the adjacent road, using the Tele Atlas Multinet road network data (Tele Atlas Inc., Menlo Park, CA). Distance to the nearest major road was estimated using ArcGIS software (version 8.3; Environmental Systems Research Institute Inc., Redlands, CA). Each direction of travel was represented as a separate roadway, and the shortest distance was estimated from the residence to the middle of the nearest side of the freeway or major road. We included in the analysis only children with addresses that could be accurately geocoded. Specifically, only residential addresses for which the Tele Atlas geocoding software assigned its highest-quality match code were included. These addresses are located on the correct side of the street with their relative position between cross-streets determined by linear interpolation of residence number between the nearest intersections.

Residential distance to a major road was categorized as < 75 m, 75–150 m, > 150–300 m, and > 300 m, based on results of previous studies showing markedly increased exposure and risk of asthma within 75 m of large roadways, which decreased to background levels by 150–300 m (Gilbert et al. 2005; van Vliet et al. 1997; Venn et al. 2001; Zhu et al. 2002). We also estimated residential exposure to fresh traffic-modeled pollutants from local freeway and nonfreeway sources, accounting for traffic volume, wind speed, and direction in each community, using a line source dispersion model, as described in the accompanying online supplemental material (http://www.ehponline.org/members/2006/85​94/suppl.pdf ).

Health outcomes and other questionnaire information.

We classified lifetime asthma based on a questionnaire response to the question “Has a doctor ever diagnosed this child as having asthma?” Current wheeze was defined to include children with any wheezing in the previous 12 months [International Study of Asthma and Allergies in Children (ISAAC) Steering Committee 1998]. Prevalent asthma was defined as the reported use of controller medications for asthma (inhaled corticosteroids, leukotriene inhibitors, cromolyn sodium, or long-acting beta agonists) in the previous year or lifetime asthma with any wheeze in the previous year. In addition, children without a physician’s diagnosis who had severe wheeze in the previous 12 months were included as prevalent asthmatics to identify asthma undiagnosed because of poor access to medical care. Severe wheeze included four or more attacks of wheeze, one or more nights per week of wheeze, or wheeze with shortness of breath so severe as to interfere with speech (ISAAC Steering Committee 1998).

We collected personal and family covariates and housing characteristics by questionnaire, including child’s race and date of birth and the language in which the questionnaire was completed (Spanish or English). Potentially susceptible groups were identified based on child’s sex, allergic characteristics defined as a history of hay fever or a problem with sneezing or runny or blocked nose when the child did not have a cold, parental history of asthma, and residence (exposure) in the current home since 2 years of age or earlier. Information on potentially confounding exposures or characteristics included maternal smoking while pregnant with the child, current second-hand tobacco smoke exposure, family income and responding parent’s education, current coverage of the child by a health insurance plan, and housing characteristics, which included pets inside the home (dog, cat, bird, other furry or hairy pets, or other pets), cockroaches, rats or mice, carpeting, water damage or mold or mildew in the home since the child lived there, use of an air conditioner, second-hand tobacco smoke, and a combustion source for nitrogen dioxide in the home (a gas oven or stove or heating unit with a pilot light).

Statistical analysis.

The odds ratio (OR) for each distance category was estimated with residences further than 300 m as the reference group, using logistic regression. All models were adjusted for the child’s age, sex, race, community, and language of questionnaire completion. To assess the effect of long-term and early-life exposure, some analyses were stratified into children living since 2 years of age or younger at the same residence and those moving to the current residence at a later age. Confounding was evaluated by assessing whether the coefficient of the log OR for exposure changed by > 10% after adding an additional covariate to this basic model. We assessed effect modification by parental history of asthma and the child’s history of allergic symptoms and sex by modeling the interaction of the potential effect modifier with exposure category (or with traffic-modeled exposure, as described in the online supplemental material) and by examining the effects of exposure by strata.

We also fitted logistic additive models (Hastie and Tibshirani 1990) to assess the functional relationship between childhood asthma and proximity to major roads. These models used the smoothing spline with 3 degrees of freedom for the continuous distance from major road and used the same adjustment variables as in the linear logistic models described above.

Significance was defined as two-sided p < 0.05 for all analyses. The logistic additive models were fitted using the S-plus programming language (Venables et al. 2002). All other analyses were performed using the Statistical Analysis System (SAS version 9.0; SAS Institute Inc., Cary, NC).

Results Top

Of the 5,341 children completing a questionnaire and informed consent, 4,762 had an address that could be accurately matched and geocoded. Among these, there were 650 reports of ever physician-diagnosed asthma (14%); 577 cases of prevalent asthma (13%) based on current severe symptoms, use of controller medications, or lifetime asthma with current wheeze; and 682 children with current wheeze during the previous year (15%). Although there was some overlap of these phenotypes, 38% of children with lifetime asthma had no current wheeze, 16% with prevalent asthma had no current wheeze (based primarily on use of controller medications in prevalent asthma), and 17% of prevalent asthma cases had no lifetime reported doctor diagnosis of asthma. The mean (± SD) age was 6.5 ± 0.68 years. The frequency of other characteristics of children, parents, and households is shown in Table 1. Most children were Hispanic, and almost one-quarter of parents completed a questionnaire in Spanish. Eighteen percent of parents reported that annual household income was < $15,000, and 22% had less than a high school education. Forty-two percent of children had lived at the same address since 2 years of age or younger.

The mean (± SD) distance from the child’s residence to a major road was 418 ± 519 m (median, 254 m; range, 0.02–7,516 m). (Error in precisely locating homes and roadways accounted for distances less than the 13-m offset from the street used in geocoding residences.) Most residences (56.6%) were within 300 m of a major road: 25.2% were between 150 and 300 m, 16.4% between 75 and 150 m, and 15% within 75 m.

The risk of asthma-related outcomes was associated with residential distance to a major road (Table 2). Compared with those living at least 300 m from a major road, there were increased risks for all three outcomes among children within 75 m. For both prevalent asthma and current wheeze, there was increasing risk with decreasing residential distance to the roadway. Among long-term residents (living since 2 years of age at the same home), risk was increased only among those living within 75 m of a major road, and the ORs were slightly larger than the corresponding ORs in the entire population. Confounding by housing characteristics or other covariates from Table 1 was assessed among long-term residents, and the effect of living within 75 m of a major road was not substantially changed.

We examined interactions of exposure with the susceptibility factors in the sample restricted to long-term residents, because exposure in this group was more likely to have been accurately assigned for the period during which asthma developed than for children moving later. Parental asthma modified the effect of living within 75 m of a major road (Table 3). There were almost 2-fold (lifetime asthma) to almost 3-fold increased risks (current wheeze) associated with this exposure, but only among those children without a parental history of asthma. The interaction of parental history with residential proximity within 75 m was significant for prevalent asthma (1 degree of freedom, Wald chi-square 4.39; p = 0.04) and for current wheeze (p = 0.01), but not for lifetime asthma.

Among long-term residents who had no allergic symptoms, greater than 2-fold increased risks of all three outcomes were associated with living in a residence within 75 m of a major road (Table 4). However, there were no significant interactions of allergy with this exposure for any of the three outcomes.

Among boys, there was little evidence of increased risk associated with residential distance to a major road (Table 5). Among girls, strong associations with living within 75 m of a major road were observed for all three outcomes, and the difference between boys and girls was significant for lifetime asthma (1 degree of freedom interaction, p = 0.02).

Among children with no family history of asthma, we examined further the relationship of asthma and distance to a major road within 500 m of the home, using smoothed models. Among long-term residents, an increasing rate of prevalent asthma was observed with residential proximity to the nearest major road, and the risk decreased to background levels at 150–200 m (Figure 2). This trend was observed only among children living at the same address since 2 years of age. Children moving to the current residence after 2 years of age showed no effect of proximity to a major road. A similar pattern of effects was observed for lifetime asthma and wheeze (data not shown).

The effects of pollutants in fresh traffic exhaust modeled from traffic volume, distance, and meteorology were generally consistent with those observed for proximity to a major road (see online supplemental material). There were significant associations of nonfreeway (but not of freeway or total) traffic-modeled exposure with prevalent asthma and current wheeze, and these effects were stronger in long-term residents (Table S-2 in the online supplemental material). The stratum-specific pattern of traffic-modeled effects was also stronger in those with no parental history and with no allergic symptoms and among girls (Table S-3 in the online supplemental material).

Discussion Top

Asthma and wheeze were strongly associated with residential proximity to a major road. These associations were strongest among children with no parental history of asthma who had lived at the same address since early in life. In this group, the highest risk occurred adjacent to the major road, and risk decreased to background rates at 150–200 m from the road. Larger risks of asthma associated with long-term residence within 75 m of a major road were observed among girls than among boys.

If traffic-related pollutants were responsible for the observed associations with asthma, the increased risk among the longer-term residents might be expected because they had a larger cumulative exposure to the pollutant indicators used in this analysis. However, the absence of any effect of a major road among children moving to their residence after 2 years of age (Figure 2) may indicate vulnerability during the prenatal period or infancy. Although the study design did not allow us to distinguish between these two possibilities, there is evidence that other early-life exposures may increase the risk of asthma (Martinez 1999). Recent case–control and cohort studies have found an increased risk of asthma with early-life exposure to local residential traffic-related pollutants (Brauer et al. 2002; Zmirou et al. 2004). In addition, several recent studies suggest that early-life (especially in utero) exposure to tobacco smoke, which like fresh vehicular exhaust is a complex mixture of air pollutants, is more strongly associated with increased risk of subsequent asthma than is exposure later in childhood (Gilliland et al. 2001, 2002). The larger effect of proximity to a major roadway among girls in our study also is consistent with previous reports (Oosterlee et al. 1996; Pershagen et al. 1995; Shima et al. 2003; van Vliet et al. 1997; Venn et al. 2001).

We previously found that children with an increased risk of incident asthma associated with exercise in high-ozone environments were less likely to have a parental history of asthma (McConnell et al. 2002), and another recent study found that the risk of traffic-associated prevalent asthma was larger in children without parental history (Gordian et al. 2005). However, both family history of asthma and child allergy are strong risk factors for asthma independent of exposure to air pollution (London et al. 2001; Peden 2000). In our study, among long-term residents living > 300 m from a major road, parental history was associated with a 3.6-fold increased risk of prevalent asthma [95% confidence interval (CI), 2.3–5.8] and child symptoms of allergy with a 6.4-fold increased risk (95% CI, 4.5–9.1). Therefore, one possible explanation for the larger effects of traffic exposure in children without these strong risk factors is that other risks, for example, dietary factors, indoor allergens, or other environmental exposures, produced asthma in the high-risk group, regardless of traffic-related exposures. It is possible that, among those with parental asthma or allergic symptoms, there was no additional risk of childhood asthma associated with traffic or that any small additional effect of traffic was undetectable in the high background rate of asthma in these children.

Parental history of asthma is an indication of genetic susceptibility, so the absence of risk among those with parental history may also indicate that asthma caused by pollutants in fresh traffic exhaust is less likely to be inherited, or at least is not mediated through the same genetic pathways that account for asthma in the parents of these children. Nonallergic asthma is one possible alternative pathway, which may be consistent with the stronger observed effect of traffic among children without hay fever or other allergic symptoms. Like parental history of asthma, allergic symptoms are associated with atopic asthma (Peden 2000). Atopy is characterized by a positive skin test or immunoglobulin E–specific response to environmental allergens. Recent studies indicate that nonallergic asthma (without airway eosinophilia or atopy) may account for as much as half of all asthma (Beasley et al. 2001; Douwes et al. 2002; Pearce et al. 1999), and it has been suggested that risk factors for this asthma phenotype, including particulate air pollution, may differ from those for allergic asthma (Douwes et al. 2002). Some studies of the risk of asthma and wheeze due to second-hand smoke, another mix of oxidant pollutants, have shown stronger effects among children without atopy or atopic symptoms (Kershaw 1987; Palmieri et al. 1990; Strachan and Cook 1998; Strachan et al. 1996a, 1996b). In addition, drug-induced and occupational asthma commonly occur in the absence of atopy, and many of the exposures responsible for “irritant-induced asthma” in the workplace are also present in the general population (Gautrin et al. 2003; Kitani et al. 1993). However, in other studies, stronger associations of asthma and wheeze with traffic-related pollutants were found among atopic children (Janssen et al. 2003; Zmirou et al. 2004) and with second-hand tobacco smoke exposure among children with an atopic parent (Jaakkola et al. 2001). In addition, laboratory evidence suggests that exposure to oxidant air pollution promotes the effect of allergens on asthma severity and on the pathogenesis of asthma (Jenkins et al. 1999; Kehrl et al. 1999; Li et al. 2003; Schelegle et al. 2003). Based on these studies, an effect of traffic-related pollutants might have been expected to be stronger among children with allergy. Further investigation is warranted to identify the reason for the apparent susceptibility of children without allergy and parental history of asthma in our study. Better phenotypic characterization of atopy both in the study children and in their parents and of allergen exposure in children would be useful to interpret the relationship of these characteristics to traffic and asthma.

In a previous cohort in the Children’s Health Study, we observed strong associations of lifetime asthma with residential ambient NO₂, an indicator of variability within communities of traffic-related pollutants, which was measured at a sample of homes (Gauderman et al. 2005). Measured NO₂ was moderately correlated with total traffic-modeled pollution (R = 0.59). Strong associations also were observed with residential distance to a freeway and with traffic-modeled exposure from freeways (but not from non-freeway traffic–modeled pollution). We have now extended these observations to a larger population and to residential distance to other major roadways. The association of asthma in our new cohort with non-freeway traffic–modeled exposure, but not with freeway-modeled exposure, may reflect differences in the distribution of freeways and major roads around homes in the different cohorts. The association of asthma with non-freeway traffic–modeled exposure is consistent with the observed association with distance to a major road, because there were few children within 75 m of a freeway in our study. Residential distance to a major roadway also is computationally easier to estimate from data that are more readily available than the meteorologic and traffic volume data required to model exposure. An increased risk associated with proximity to a major roadway also is more easily explained to policy makers and to the general public than is the risk associated with traffic-modeled exposure.

Our results are also consistent with several European studies that found increased risks of childhood asthma with increased traffic counts in close proximity to the home (Morris et al. 2000; Nicolai et al. 2003; van Vliet et al. 1997; Venn et al. 2001; Zmirou et al. 2004). One large British study that focused on traffic within 150 m of children’s homes found a gradient in risk that increased markedly with decreasing residential distance to a main road (Venn et al. 2001). There have been few other studies of traffic and childhood asthma in the United States. A recent study in northern California found an association between measured traffic-related pollutants at schools and childhood asthma (Kim et al. 2004). However, another large study in southern California based on records of children covered by Medicaid (public insurance for low-income persons) found no association between asthma prevalence and traffic counts within 168 m of the home, although an association with asthma medication was observed (English et al. 1999). Some of the inconsistencies in the literature could perhaps be explained by the failure of many studies to account for the pattern of effect modification by parental history of asthma and by age and duration of residential exposure to traffic-related pollutants that vary markedly at different locations. The larger effects of traffic in girls has been observed in previous studies of traffic and asthma and related symptoms, but the reason for the apparent susceptibility of girls is not known (Oosterlee et al. 1996; Pershagen et al. 1995; Shima et al. 2003; van Vliet et al. 1997; Venn et al. 2001).

A causal relationship between asthma and traffic-related exposures is biologically plausible, because ambient particulate matter and other oxidant pollutants have been shown to elicit responses relevant to the pathogenesis of asthma (Li et al. 2003). In addition, studies in southern California and elsewhere have shown that the largest gradients in traffic-related pollutants occur within the 150–200 m from roadways over which we saw decreasing risk of asthma (Gilbert et al. 2003; Zhu et al. 2002). In studies in which NO₂ and other markers of traffic-related exposure have been measured in close proximity to major roadways, variability has usually been best explained by traffic volume within 300 m (Briggs et al. 2000; Gilbert et al. 2003; Ross et al. 2005), although weaker correlations have also been observed over longer distances from the highest volume traffic corridors (Gauderman et al. 2005; Gilbert et al. 2003, 2005; Ross et al. 2005).

We considered bias as an explanation for our results. Parents with asthma who were susceptible to environmental triggers might have selected homes away from major roads, perhaps even before the children were born. If the children of these parents had high rates of asthma, this might have explained the observed lack of effect of a major road in families with parental asthma. There is some evidence that parents may intervene to reduce household exposure to indoor allergens, another perceived risk for asthma and asthma severity (Almqvist et al. 2003; van Strien et al. 2002). However, this bias is unlikely to explain our results, because we examined and found no significant differences in rates of parental history of asthma by exposure to a major road (data not shown). Selection bias related to factors influencing participation could not be evaluated, because characteristics of nonparticipants are not known. However, there were some modest differences between participants whose addresses could be geocoded, who were of higher socioeconomic status than were participants whose addresses could not be geocoded. For example, of those with family income < $7,500, 85% could be geocoded, compared with 93% of those with ≥$100,000. Of those without insurance, 85% could be geocoded, compared with 90% of those with insurance. The differences between those whose homes could and could not be geocoded were heavily influenced by 299 subjects (of 579 total that could not be geocoded) who completed a questionnaire but did not provide an address. However, none of the three asthma outcomes was associated with absence of a home geocode, and the associations of asthma with traffic were robust to our adjustment for socioeconomic status. It has also been suggested that traffic-related noise might cause asthma through a pathway mediated by stress (Ising and Ising 2002). However, to date there is little evidence to support this hypothesis. Other potential confounders, including sociodemographic factors, second-hand or in utero tobacco smoke exposure, or housing characteristics that are commonly associated with asthma also did not explain our results. A final possible limitation to the interpretation of these results is the assessment of asthma by questionnaire. However, self-report of physician-diagnosed asthma has been reported to accurately reflect what physicians have told the patient, at least in adults, and validity of questionnaires as reported by repeatability of response is good (Ehrlich et al. 1995). For these reasons, self-report of physician-diagnosed asthma has been widely used in epidemiologic studies and has been recommended as the preferred outcome assessment for use in large population-based studies, because a more precise diagnosis is not available (Burr 1992). In addition, the consistency of associations with lifetime asthma, prevalent asthma based on a combination of symptoms reporting and doctor diagnosis, and recent wheezing suggests that diagnostic bias is unlikely to have explained the observed results.

We conclude that living in a residence with more nearby traffic increases the risk of childhood asthma. Children with no parental history of asthma who had long-term residential exposure (or early-life exposure) constituted a susceptible population, and the risk was larger for girls than for boys. Because a substantial number of southern California children live near a major road, this exposure is potentially an important public health problem that could be remediable by transportation and residential development policy and by more effective control of vehicular emissions. Among those long-term residents with no parental history of asthma who lived within 75 m of a major road, 59% of asthma was attributable to residential proximity to the road. Further investigation is warranted to understand why the absence of parental asthma history increased susceptibility to traffic-related exposure.

Supplemental Material Top

(232 KB) PDF.

Figures and Tables Top

Figure 1.

Location of study communities.

Figure 2.

Prevalence of asthma by distance of residence to a major road within 500 m, among long-term (A) and short-term (B) residents with no family history of asthma. Dotted lines indicate 95% confidence interval.

Table 1.

Demographic characteristics and potential confounders or susceptibility factors.

Table 2.

Association of asthma and wheeze with distance to a major road [OR (95% CI)].^a

Table 3.

Association of asthma and wheeze with distance to a major road among long-term residents, by parental history of asthma [OR (95% CI)].^a

Table 4.

Association of asthma and wheeze with distance to a major road among long term residents, by child’s history of allergy [OR (95% CI)].^a

Table 5.

Association of asthma and wheeze with distance to a major road among long term residents, by child’s sex [OR (95% CI)].^a

References Top

1. Almqvist C, Egmar AC, van Hage-Hamsten M, Berglind N, Pershagen G, Nordvall SL, et al. 2003. Heredity, pet ownership, and confounding control in a population-based birth cohort J Allergy Clin Immunol 111(4):800–806.12704361 Find this article online
2. Beasley R, Pekkanen J, Pearce N 2001. Has the role of atopy in the development of asthma been over-emphasized? Pediatr Pulmonol 23(suppl):149–150.11886123 Find this article online
3. Brauer M, Hoek G, Van Vliet P, Meliefste K, Fischer PH, Wijga A, et al. 2002. Air pollution from traffic and the development of respiratory infections and asthmatic and allergic symptoms in children Am J Respir Crit Care Med 166(8):1092–1098.12379553 Find this article online
4. Briggs DJ, de Hoogh C, Gulliver J, Wills J, Elliott P, Kingham S, et al. 2000. A regression-based method for mapping traffic-related air pollution: application and testing in four contrasting urban environments Sci Total Environ 253(1–3):151–167.10843339 Find this article online
5. Burr ML 1992. Diagnosing asthma by questionnaire in epidemiological surveys [editorial] Clin Exp Allergy 22(5):509–510.1628247 Find this article online
6. Douwes J, Gibson P, Pekkanen J, Pearce N 2002. Non-eosinophilic asthma: importance and possible mechanisms Thorax 57(7):643–648.12096210 Find this article online
7. Ehrlich RI, Du Toit D, Jordaan E, Volmink JA, Weinberg EG, Zwarenstein M 1995. Prevalence and reliability of asthma symptoms in primary school children in Cape Town Int J Epidemiol 24(6):1138–1145.8824855 Find this article online
8. English P, Neutra R, Scalf R, Sullivan M, Waller L, Zhu L 1999. Examining associations between childhood asthma and traffic flow using a geographic information system Environ Health Perspect 107:761–767.10464078 Find this article online
9. Gauderman WJ, Avol E, Lurmann F, Kuenzli N, Gilliland F, Peters J, et al. 2005. Childhood asthma and exposure to traffic and nitrogen dioxide Epidemiology 16(6):737–743.16222162 Find this article online
10. Gautrin D, Newman-Taylor AJ, Nordman H, Malo JL 2003. Controversies in epidemiology of occupational asthma Eur Respir J 22(3):551–559.14516150 Find this article online
11. Gilbert NL, Goldberg MS, Beckerman B, Brook JR, Jerrett M 2005. Assessing spatial variability of ambient nitrogen dioxide in Montreal, Canada, with a land-use regression model J Air Waste Manag Assoc 55(8):1059–1063.16187576 Find this article online
12. Gilbert NL, Woodhouse S, Stieb DM, Brook JR 2003. Ambient nitrogen dioxide and distance from a major highway Sci Total Environ 312(1–3):43–46.12873397 Find this article online
13. Gilliland FD, Li YF, Dubeau L, Berhane K, Avol E, McConnell R, et al. 2002. Effects of glutathione S-transferase M1, maternal smoking during pregnancy, and environmental tobacco smoke on asthma and wheezing in children Am J Respir Crit Care Med 166(4):457–463.12186820 Find this article online
14. Gilliland FD, Li YF, Peters JM 2001. Effects of maternal smoking during pregnancy and environmental tobacco smoke on asthma and wheezing in children Am J Respir Crit Care Med 163(2):429–436.11179118 Find this article online
15. Gordian ME, Haneuse S, Wakefield J 2005. An investigation of the association between traffic exposure and the diagnosis of asthma in children. J Expo Anal Environ Epidemiol doi:10.1038/sj.jea.7500436 [Online 29 June 2005]
16. Hastie TJ, Tibshirani RJ 1990. Generalized Additive Models. London:Chapman & Hall
17. ISAAC Steering Committee 1998. International Study of Asthma and Allergies in Children: Phase II Modules. Muenster, Germany:Institute of Epidemiology and Social Medicine, University of Muenster
18. Ising H, Ising M 2002. Chronic cortisol increases in the first half of the night caused by road traffic noise Noise Health 4(16):13–21.12537837 Find this article online
19. Jaakkola JJ, Nafstad P, Magnus P 2001. Environmental tobacco smoke, parental atopy, and childhood asthma Environ Health Perspect 109:579–582.11445511 Find this article online
20. Janssen NA, Brunekreef B, van Vliet P, Aarts F, Meliefste K, Harssema H, et al. 2003. The relationship between air pollution from heavy traffic and allergic sensitization, bronchial hyperresponsiveness, and respiratory symptoms in Dutch schoolchildren Environ Health Perspect 111:1512–1518.12948892 Find this article online
21. Jenkins HS, Devalia JL, Mister RL, Bevan AM, Rusznak C, Davies RJ 1999. The effect of exposure to ozone and nitrogen dioxide on the airway response of atopic asthmatics to inhaled allergen: dose- and time-dependent effects Am J Respir Crit Care Med 160(1):33–39.10390376 Find this article online
22. Kehrl HR, Peden DB, Ball B, Folinsbee LJ, Horstman D 1999. Increased specific airway reactivity of persons with mild allergic asthma after 7.6 hours of exposure to 0.16 ppm ozone J Allergy Clin Immunol 104(6):1198–1204.10589001 Find this article online
23. Kershaw CR 1987. Passive smoking, potential atopy and asthma in the first five years J R Soc Med 80(11):683–688.3694614 Find this article online
24. Kim JJ, Smorodinsky S, Lipsett M, Singer BC, Hodgson AT, Ostro B 2004. Traffic-related air pollution near busy roads: the East Bay Children’s Respiratory Health Study Am J Respir Crit Care Med 170(5):520–526.15184208 Find this article online
25. Kitani H, Kajimoto K, Sugimoto K, Mifune T, Mitsunobu F, Yokota S, et al. 1993. IgE-mediated allergic reaction in drug-induced asthma Acta Med Okayama 47(5):317–321.7505995 Find this article online
26. Künzli N, McConnell R, Bates D, Bastain T, Hricko A, Lurmann F, et al. 2003. Breathless in Los Angeles: the exhausting search for clean air Am J Public Health 93(9):1494–1499.12948969 Find this article online
27. Li N, Hao M, Phalen RF, Hinds WC, Nel AE 2003. Particulate air pollutants and asthma. A paradigm for the role of oxidative stress in PM-induced adverse health effects Clin Immunol 109(3):250–265.14697739 Find this article online
28. London SJ, Gauderman WJ, Avol E, Rappaport EB, Peters JM 2001. Family history and the risk of early-onset persistent, early-onset transient, and late-onset asthma Epidemiology 12(5):577–583.11505179 Find this article online
29. Martinez FD 1999. Maturation of immune responses at the beginning of asthma J Allergy Clin Immunol 103(3 pt 1):355–361.10069865 Find this article online
30. McConnell R, Berhane K, Gilliland F, London SJ, Islam T, Gauderman WJ, et al. 2002. Asthma in exercising children exposed to ozone: a cohort study Lancet 359(9304):386–391.11844508 Find this article online
31. Morris SE, Sale RC, Wakefield JC, Falconer S, Elliott P, Boucher BJ 2000. Hospital admissions for asthma and chronic obstructive airways disease in east London hospitals and proximity of residence to main roads J Epidemiol Community Health 54(1):75–76.10692969 Find this article online
32. Nicolai T, Carr D, Weiland SK, Duhme H, von Ehrenstein O, Wagner C, et al. 2003. Urban traffic and pollutant exposure related to respiratory outcomes and atopy in a large sample of children Eur Respir J 21(6):956–963.12797488 Find this article online
33. Oosterlee A, Drijver M, Lebret E, Brunekreef B 1996. Chronic respiratory symptoms in children and adults living along streets with high traffic density Occup Environ Med 53(4):241–247.8664961 Find this article online
34. Palmieri M, Longobardi G, Napolitano G, Simonetti DM 1990. Parental smoking and asthma in childhood Eur J Pediatr 149(10):738–740.2209669 Find this article online
35. Pearce N, Pekkanen J, Beasley R 1999. How much asthma is really attributable to atopy? Thorax 54(3):268–272.10325905 Find this article online
36. Peden DB 2000. Development of atopy and asthma: candidate environmental influences and important periods of exposure Environ Health Perspect 108(suppl 3):475–482.10852847 Find this article online
37. Pershagen G, Rylander E, Norberg S, Eriksson M, Nordvall SL 1995. Air pollution involving nitrogen dioxide exposure and wheezing bronchitis in children Int J Epidemiol 24(6):1147–1153.8824856 Find this article online
38. Ross Z, English PB, Scalf R, Gunier R, Smorodinsky S, Wall S, et al. 2006. Nitrogen dioxide prediction in southern California using land use regression modeling: potential for environmental health analyses J Expo Sci Environ Epidemiol 16(2):106–114.16047040 Find this article online
39. Schelegle ES, Miller LA, Gershwin LJ, Fanucchi MV, Van Winkle LS, Gerriets JE, et al. 2003. Repeated episodes of ozone inhalation amplifies the effects of allergen sensitization and inhalation on airway immune and structural development in rhesus monkeys Toxicol Appl Pharmacol 191(1):74–85.12915105 Find this article online
40. Shima M, Nitta Y, Adachi M 2003. Traffic-related air pollution and respiratory symptoms in children living along trunk roads in Chiba Prefecture, Japan J Epidemiol 13(2):108–119.12675120 Find this article online
41. Strachan DP, Butland BK, Anderson HR 1996a. Incidence and prognosis of asthma and wheezing illness from early childhood to age 33 in a national British cohort BMJ 312(7040):1195–1199.8634562 Find this article online
42. Strachan DP, Cook DG 1998. Health effects of passive smoking. 6. Parental smoking and childhood asthma: longitudinal and case-control studies Thorax 53(3):204–212.9659358 Find this article online
43. Strachan DP, Griffiths JM, Johnston ID, Anderson HR 1996b. Ventilatory function in British adults after asthma or wheezing illness at ages 0–35 Am J Respir Crit Care Med 154(6 pt 1):1629–1635.8970346 Find this article online
44. van Strien RT, Koopman LP, Kerkhof M, Spithoven J, de Jongste JC, Gerritsen J, et al. 2002. Mite and pet allergen levels in homes of children born to allergic and nonallergic parents: the PIAMA study Environ Health Perspect 110:A693–A698.12417497 Find this article online
45. van Vliet P, Knape M, de Hartog J, Janssen N, Harssema H, Brunekreef B 1997. Motor vehicle exhaust and chronic respiratory symptoms in children living near freeways Environ Res 74(2):122–132.9339225 Find this article online
46. Venables WN, Ropley BD, Ripley BD 2002. Modern Applied Statistics with S-Plus. New York:Springer Verlag
47. Venn A, Lewis S, Cooper M, Hubbard R, Hill I, Boddy R, et al. 2000. Local road traffic activity and the prevalence, severity, and persistence of wheeze in school children: combined cross sectional and longitudinal study Occup Environ Med 57(3):152–158.10810096 Find this article online
48. Venn AJ, Lewis SA, Cooper M, Hubbard R, Britton J 2001. Living near a main road and the risk of wheezing illness in children Am J Respir Crit Care Med 164(12):2177–2180.11751183 Find this article online
49. Waldron G, Pottle B, Dod J 1995. Asthma and the motorways—one district’s experience J Public Health Med 17(1):85–89.7540398 Find this article online
50. Wjst M, Reitmeir P, Dold S, Wulff A, Nicolai T, von Loeffelholz-Colberg EF, et al. 1993. Road traffic and adverse effects on respiratory health in children BMJ 307(6904):596–600.7691304 Find this article online
51. Zhu Y, Hinds WC, Kim S, Sioutas C 2002. Concentration and size distribution of ultrafine particles near a major highway J Air Waste Manag Assoc 52(9):1032–1042.12269664 Find this article online
52. Zmirou D, Gauvin S, Pin I, Momas I, Sahraoui F, Just J, et al. 2004. Traffic related air pollution and incidence of childhood asthma: results of the Vesta case-control study J Epidemiol Community Health 58(1):18–23.14684722 Find this article online