Recent studies, primarily in Europe, have reported associations between respiratory symptoms and residential proximity to traffic; however, few have measured traffic pollutants or provided information about local air quality. We conducted a school-based, crosssectional study in the San Francisco Bay Area in 2001. Information on current bronchitis symptoms and asthma, home environment, and demographics was obtained by parental questionnaire (n ϭ 1,109). Concentrations of traffic pollutants (particulate matter, black carbon, total nitrogen oxides [NO X ], and nitrogen dioxide [NO 2 ]) were measured at 10 school sites during several seasons. Although pollutant concentrations were relatively low, we observed differences in concentrations between schools nearby versus those more distant (or upwind) from major roads. Using a two-stage multiple-logistic regression model, we found associations between respiratory symptoms and traffic-related pollutants. Among those living at their current residence for at least 1 year, the adjusted odds ratio for asthma in relationship to an interquartile difference in NO X was 1.07 (95% confidence interval, 1.00-1.14). Thus, we found spatial variability in traffic pollutants and associated differences in respiratory symptoms in a region with good air quality. Our findings support the hypothesis that traffic-related pollution is associated with respiratory symptoms in children.

Residential proximity to busy roads has been associated with adverse health outcomes, and school location may also be an important determinant of children's exposure to traffic-related pollutants. The goal of this study was to examine the characteristics of public schools (grades K-12) in California (n = 7,460) by proximity to major roads. We determined maximum daily traffic counts for all roads within 150 m of the school using a statewide road network and a geographic information system. Statewide, 173 schools (2.3%) with a total enrollment of 150,323 students were located within 150 m of high-traffic roads (greater than or equal to 50,000 vehicles/day); 536 schools (7.2%) were within 150 m of medium-traffic roads (25,000-49,999 vehicles/day). Traffic exposure was related to race/ethnicity. For example, the overall percentage of nonwhite students was 78% at the schools located near high-traffic roads versus 60% at the schools with very low exposure (no streets with counted traffic data within 150 m). As the traffic exposure of schools increased, the percentage of both non-Hispanic black and Hispanic students attending the schools increased substantially. Traffic exposure was also related to school-based and census-tract-based socioeconomic indicators, including English language learners. The median percentage of children enrolled in free or reduced-price meal programs increased from 40.7% in the group with very low exposure to 60.5% in the highest exposure group. In summary, a substantial number of children in California attend schools close to major roads with very high traffic counts, and a disproportionate number of those students are economically disadvantaged and nonwhite.

We modeled the intraurban distribution of nitrogen dioxide (NO(2)), a marker for traffic pollution, with land use regression, a promising new exposure classification technique. We deployed diffusion tubes to measure NO(2) levels at 39 locations in the fall of 2003 in San Diego County, CA, USA. At each sample location, we constructed circular buffers in a geographic information system and captured information on roads, traffic flow, land use, population and housing. Using multiple linear regression, we were able to predict 79% of the variation in NO(2) levels with four variables: traffic density within 40-300 m of the sampling location, traffic density within 300-1000 m, length of road within 40 m and distance to the Pacific coast. Applying this model to validation samples showed that the model predicted NO(2) levels within, on average, 2.1 p.p.b for 12 training sites initially excluded from the model. Our evaluation of this land use regression model showed that this method had excellent prediction and robustness in a North American context. These models may be useful tools in evaluating health effects of long-term exposure to traffic-related pollution.

This study examines all intimate partner homicides in California during 1996 (N=186), and differences between intimate partner homicides with and without perpetrator suicide are compared. The study found that 40 percent of perpetrators committed suicide subsequent to the homicide. Variables examined in the analysis include type of weapon used, race, age, sex of perpetrators and victims, and location of the homicide. Significant differences were found between homicides with perpetrator suicide and those without. The results lend support to previous research suggesting that intimate partner homicide and homicide followed by suicide have different characteristics and possibly distinct etiologies.

BackgroundLiving near traffic has been associated with asthma and other respiratory symptoms. Most studies, however, have been conducted in areas with high background levels of ambient air pollution, making it challenging to isolate an independent effect of traffic. Additionally, most investigations have used surrogates of exposure, and few have measured traffic pollutants directly as part of the study.ObjectiveWe conducted a cross-sectional study of current asthma and other respiratory symptoms in children (n = 1,080) living at varying distances from high-traffic roads in the San Francisco Bay Area, California, a highly urbanized region characterized by good regional air quality due to coastal breezes.MethodsWe obtained health information and home environmental factors by parental questionnaire. We assessed exposure with several measures of residential proximity to traffic calculated using geographic information systems, including traffic within a given radius and distance to major roads. We also measured traffic-related pollutants (nitrogen oxides and nitrogen dioxide) for a subset of households to determine how well traffic metrics correlated with measured traffic pollutants.ResultsUsing multivariate logistic regression analyses, we found associations between current asthma and residential proximity to traffic. For several traffic metrics, children whose residences were in the highest quintile of exposure had approximately twice the adjusted odds of current asthma (i.e., asthma episode in the preceeding 12 months) compared with children whose residences were within the lowest quintile. The highest risks were among those living within 75 m of a freeway/highway. Most traffic metrics correlated moderately well with actual pollutant measurements.ConclusionOur findings provide evidence that even in an area with good regional air quality, proximity to traffic is associated with adverse respiratory health effects in children.