As expected, road and traffic density values were highest for children living in metropolitan areas of California and lowest for children living in the state’s rural areas. Median road density was 21.7 mi/mi2 in metropolitan areas, 21.2 mi/mi2 in smaller cities, and 10.7 mi/mi2 in rural areas. The difference between urbanized and rural areas was more pronounced for traffic density. The median traffic density value was approximately 53,000 vehicle miles traveled per square mile in metropolitan areas, approximately 22,000 vehicle miles traveled per square mile in smaller cities, and zero in rural areas (most rural children had no measured road segments within a 500-foot radius of their residence). Road density values were distributed similarly for cases and control subjects (Table 3); 9% of cases and 10% of controls fell into the highest road density category. Results were similar for traffic density. The distributions of road and traffic density were also similar between cases of leukemia and CNS tumors and their respective control subjects.
Table 4 shows ORs for our traffic measures and childhood cancers. For all cancer sites combined, the OR for the highest road density exposure category (compared with the lowest) was 0.87 (CI = 0.75–1.00). The OR for leukemia was also below 1.0 (0.80; 0.64–1.01). For CNS tumors, the OR for the highest road density exposure was 1.03 (0.75–1.43). The ORs were also below 1.0 for the highest traffic density exposure for all sites combined (0.92; 0.80–1.06) and for leukemias (0.92; 0.73–1.15). For CNS tumors, the OR was 1.22 (0.87–1.70) based on a 1% difference in number of cases and controls in the highest exposure category (10% vs. 9%). Additional adjustment for maternal age, birth weight, and neighborhood income had little effect on point estimates for road and traffic density (data not shown). We also examined ORs for the 2 major leukemia types, acute lymphocytic leukemia and acute nonlymphocytic leukemia. The point estimates for road density and traffic density exposure categories were similar to those for all leukemias combined and all the confidence intervals included 1.0 (data not shown).
We repeated our analyses for traffic density within a 1000-foot radius of subjects’ birth residences to evaluate the sensitivity of our findings on the definition of road proximity. The ORs in these analyses were similar to those for our 500-foot radius analyses. The ORs for all traffic density categories, for all cancer sites combined, were slightly below 1.0, with an OR of 0.95 for the highest category (CI = 0.82–1.09). For leukemias, the OR for the highest traffic density category was 1.01 (CI = 0.82–1.29). The OR for the highest traffic density category for CNS cancer in this larger area was also below 1.0 (OR = 0.88; CI = 0.63–1.24).
Based on county-level benzene emissions data and land area, the most urban areas of California ranked highest in regional, traffic-related pollution levels. When we added our 4-level categorical variable for benzene emissions to the models, adjusting for differences in background levels of air pollution based on the subject’s county of residence, the resulting traffic-related point estimates for cancer risk did not change (data not shown).
In this large population-based study, we found little or no evidence for increased cancer risk among children born in high-traffic areas. For all sites combined and for the leukemias, the ORs were at or below unity for all exposure categories. For the CNS tumors, the OR for the highest traffic density exposure was elevated (1.2), but there was no dose-response pattern with increasing exposure categories. This finding was based on a very small difference (1%) between number of cases and controls in the highest exposure category. Two previous studies have reported positive associations between CNS cancers and traffic.4,13 Estimates were only slightly elevated13 or based on small numbers of cases in the highest exposure group.4
Although several studies of childhood cancer and traffic have reported increased risk with higher proxy exposures,1–7 the 4 most recently published studies on this topic have not.11–14 These 4 recent studies (3 from California) comprise much larger samples than earlier studies; the Danish study14 incorporated more rigorously modeled traffic attributes. The only positive association from the United States comes from 2 analyses of data from Denver, Colorado.1,5 A major methodologic improvement in our current study over this previous study was in the selection procedure for controls; the other researchers used random-digit dial (RDD), which tends to result in control subjects with higher socioeconomic status (SES), especially in children.24,25 In California, lower SES children are much more likely than upper SES children to live in high traffic areas.26 In addition, the Denver analyses examined traffic patterns near the diagnosis residence, whereas our study assessed traffic near the birth address.
Our findings were similar to those reported by Langholz et al.12 in their case-control study of childhood leukemia in Los Angeles County, which included cases from a broader age range and earlier time period. Although the Los Angeles County study found somewhat elevated risk ratios, ours were mostly below 1.0. The null results from these 2 case-control studies are consistent with those from a statewide ecologic study of childhood cancer rates by neighborhood measures of traffic volume.13
Because we know little about the causes of childhood cancer, it is not clear which time windows of exposure could be most important. Most studies of traffic and childhood cancer have examined exposure potential based on a child’s residence at diagnosis or current residence for control children.1,2,4–6,12 Studies of parental hydrocarbon-related occupational exposures have based their analyses largely on birth certificate data8,9; to the extent that occupations do not change, these studies can also reflect exposures closer to the time of diagnosis. It is worth noting that the most recent studies of traffic-related associations have produced generally null results, whether measuring exposure for recent residence,12,13 birth residence,11 or a child’s complete residential history encompassing an exposure window from 9 months before birth through the child’s date of diagnosis.14
Measures of traffic intensity have been of interest in childhood cancer studies because they provide proxy measures of exposures to chemical mixtures from mobile sources. Because ambient air quality data are scarce, it is often difficult to assess the degree to which proxy measures actually inform such exposures in residential areas. In Denmark, an evaluation of traffic exposure estimates using measured levels of benzene found correlation coefficients (r) of 0.55 for traffic density, which improved to 0.68 when using a model that included meteorologic data and background pollution levels.27 Using the methods described for the Danish analysis, we found a similar correlation (r = 0.69) between measured benzene and traffic density levels within a 500-foot radius of monitoring sites.13 Traffic volume is also associated with other neighborhood characteristics. Statewide data suggest that traffic density is higher in areas of California that are more urban, more industrial, more socioeconomically disadvantaged, and more likely to be populated by people of color.26 Further adjustment for these factors, or for background measures of air quality, did not change the results of our analyses.
It is possible that populations living near roadways in California, compared with other areas of the world, have very different exposures to mobile source pollutants. Traffic levels in California’s urban areas tend to be much higher than those reported in the earlier studies on this topic. Although the traffic exposure measure used in our current study is not identical to those used in previous childhood cancer studies, precluding direct comparisons, estimates of relative traffic levels could be informative. In the original Denver study,1 traffic volume on the subject’s road for the highest exposure category was greater than 10,000 cars per day. The percentage of subjects in this highest exposure category was 4% in Denver1 and 2% in Denmark.14 A reanalysis of the Denver study found that 8% of subjects, using the original control subjects, and 19% of subjects, using citywide control subjects, had distance weighted-traffic density greater than 10,000 cars per day within a 500-foot radius circle of their residence,28 whereas in Los Angeles, 30% of the subjects were at or above this exposure level.12 A traffic density of 10,000 cars per day in our study would be 67,000 vehicle miles traveled per square mile. Thus, more than one third (35%) of our subjects had a traffic density value above this level, similar to the percentage in Los Angeles. Based on this indirect comparison, it is unlikely that the traffic levels in our study were too low to detect the same effect as in the Denver study. However, emissions per vehicle have varied over time and could also be considerably different in California, Denver, and Denmark. California has some of the most stringent fuel and emission control standards in the world. Vehicle miles increased 26% in California from 1988 to 1997, but during the same period, ambient air concentrations decreased 30% on average for traffic-related pollutants such as carbon monoxide, ozone, and particulate matter.29
In a separate analysis, we recently evaluated childhood cancer incidence rates in California by census tract-based hazardous air pollutant levels as modeled by the U.S. Environmental Protection Agency (EPA).30 Unlike our proxy measure of traffic density for air contaminant exposure, the hazardous air pollutant models provided overall ambient air quality estimates that incorporated emissions from multiple sources, including traffic, large industrial manufacturing facilities, small area sources (such as dry cleaners and gas stations), and residential solvent use. Although the hazardous air pollutant study found no significant childhood cancer excess (for all sites combined) in census tracts with the highest exposure levels, the rate ratios for leukemia did appear elevated in these areas. These findings suggest that traffic-related pollutants in combination with pollutants from other sources could require further study in relation to childhood cancer.
One limitation of this study was our assignment of exposure based solely on residence at birth. Although we did not have residential history information for our study subjects, it was possible to compare address information for 2 points in time for case subjects. Many of our case families moved during the child’s gestation and in the first years after birth. When we compared cases’ birth addresses to their addresses at diagnosis, we found the 2 were the same for only 50% of cases. Because our study relied only on existing records, we could not obtain potentially useful information on parental occupational exposures, the amount of time children spent commuting, and other sources of air toxicants such as environmental tobacco smoke, which is known to contain benzene and other carcinogenic chemicals. Additionally, we did not have access to individualized air monitoring or other direct measures of subjects’ individual personal exposure. Although such direct measuring methods can provide significant predictive data, the literature suggests that even measured concentrations of air pollutants in children’s homes can only partially explain their personal exposures to combustion-related air pollutants.31,32
The records-based nature of our study affords several advantages over traditional interview studies. Both our cases and control subjects were population-based, eliminating common problems of selection or participation bias. Exposures were not self-reported, removing potential recall bias. Our study was population-based for the entire state of California and included a large number of subjects with a wide variety of traffic exposures ranging from rural areas to very urban inner cities, thus offering considerable heterogeneity in exposure potential.
We did not find evidence of increased cancer risk among young children born in high traffic areas in California. We also found no increased risk for traffic exposure and leukemias, the most common type of childhood cancer. We observed a slight increase for CNS tumors among offspring of mothers living in high traffic density areas, with no evidence of a dose-response. These data, along with recent results from other research in this area suggest that traffic-related exposures, in particular those in California during recent decades, are not associated with childhood cancer occurrence. However, other important influences on air quality can present risks for the development of cancer in young children, either alone or in combination with mobile source pollutants. Studies that can better characterize patterns of residential mobility and measured air quality will be important in further elucidating these risk relationships.
We thank Theresa Saunders for manuscript preparation and Sarah Hines-Stephans for providing the photograph used in this article.
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