California Children's Health Study Research Articles

Chronic effects of air pollution on respiratory health in Southern California children: findings from the Southern California Children's Health Study.

Outdoor air pollution is one of the leading contributors to adverse respiratory health outcomes in urban areas around the world. Children are highly sensitive to the adverse effects of air pollution due to their rapidly growing lungs, incomplete immune and metabolic functions, patterns of ventilation and high levels of outdoor activity. The Children's Health Study (CHS) is a continuing series of longitudinal studies that first began in 1993 and has focused on demonstrating the chronic impacts of air pollution on respiratory illnesses from early childhood through adolescence. A large body of evidence from the CHS has documented that exposures to both regional ambient air and traffic-related pollutants are associated with increased asthma prevalence, new-onset asthma, risk of bronchitis and wheezing, deficits of lung function growth, and airway inflammation. These associations may be modulated by key genes involved in oxidative-nitrosative stress pathways via gene-environment interactions. Despite successful efforts to reduce pollution over the past 40 years, air pollution at the current levels still brings many challenges to public health. To further ameliorate adverse health effects attributable to air pollution, many more toxic pollutants may require regulation and control of motor vehicle emissions and other combustion sources may need to be strengthened. Individual interventions based on personal susceptibility may be needed to protect children's health while control measures are being implemented.

A longitudinal cohort study of body mass index and childhood exposure to secondhand tobacco smoke and air pollution: the Southern California Children's Health Study.

Background:Childhood body mass index (BMI) and obesity prevalence have been associated with exposure to secondhand smoke (SHS), maternal smoking during pregnancy, and vehicular air pollution. There has been little previous study of joint BMI effects of air pollution and tobacco smoke exposure.Methods:Information on exposure to SHS and maternal smoking during pregnancy was collected on 3,318 participants at enrollment into the Southern California Children’s Health Study. At study entry at average age of 10 years, residential near-roadway pollution exposure (NRP) was estimated based on a line source dispersion model accounting for traffic volume, proximity, and meteorology. Lifetime exposure to tobacco smoke was assessed by parent questionnaire. Associations with subsequent BMI growth trajectory based on annual measurements and attained BMI at 18 years of age were assessed using a multilevel modeling strategy.Results:Maternal smoking during pregnancy was associated with estimated BMI growth over 8-year follow-up (0.72 kg/m2 higher; 95% CI: 0.14, 1.31) and attained BMI (1.14 kg/m2 higher; 95% CI: 0.66, 1.62). SHS exposure before enrollment was positively associated with BMI growth (0.81 kg/m2 higher; 95% CI: 0.36, 1.27) and attained BMI (1.23 kg/m2 higher; 95% CI: 0.86, 1.61). Growth and attained BMI increased with more smokers in the home. Compared with children without a history of SHS and NRP below the median, attained BMI was 0.80 kg/m2 higher (95% CI: 0.27, 1.32) with exposure to high NRP without SHS; 0.85 kg/m2 higher (95% CI: 0.43, 1.28) with low NRP and a history of SHS; and 2.15 kg/m2 higher (95% CI: 1.52, 2.77) with high NRP and a history of SHS (interaction p-value 0.007). These results suggest a synergistic effect.Conclusions:Our findings strengthen emerging evidence that exposure to tobacco smoke and NRP contribute to development of childhood obesity and suggest that combined exposures may have synergistic effects.Citation:McConnell R, Shen E, Gilliland FD, Jerrett M, Wolch J, Chang CC, Lurmann F, Berhane K. 2015. A longitudinal cohort study of body mass index and childhood exposure to secondhand tobacco smoke and air pollution: the Southern California Children’s Health Study. Environ Health Perspect 123:360–366; http://dx.doi.org/10.1289/ehp.1307031

Estimation of Parameters in the Two-Compartment Model for Exhaled Nitric Oxide

The fractional concentration of exhaled nitric oxide (FeNO) is a biomarker of airway inflammation that is being increasingly considered in clinical, occupational, and epidemiological applications ranging from asthma management to the detection of air pollution health effects. FeNO depends strongly on exhalation flow rate. This dependency has allowed for the development of mathematical models whose parameters quantify airway and alveolar compartment contributions to FeNO. Numerous methods have been proposed to estimate these parameters using FeNO measured at multiple flow rates. These methods—which allow for non-invasive assessment of localized airway inflammation—have the potential to provide important insights on inflammatory mechanisms. However, different estimation methods produce different results and a serious barrier to progress in this field is the lack of a single recommended method. With the goal of resolving this methodological problem, we have developed a unifying framework in which to present a comprehensive set of existing and novel statistical methods for estimating parameters in the simple two-compartment model. We compared statistical properties of the estimators in simulation studies and investigated model fit and parameter estimate sensitivity across methods using data from 1507 schoolchildren from the Southern California Children's Health Study, one of the largest multiple flow FeNO studies to date. We recommend a novel nonlinear least squares model with natural log transformation on both sides that produced estimators with good properties, satisfied model assumptions, and fit the Children's Health Study data well.

Determinants of the spatial distributions of elemental carbon and particulate matter in eight Southern Californian communities

Emerging evidence indicates that near-roadway pollution (NRP) in ambient air has adverse health effects. However, specific components of the NRP mixture responsible for these effects have not been established. A major limitation for health studies is the lack of exposure models that estimate NRP components observed in epidemiological studies over fine spatial scale of tens to hundreds of meters. In this study, exposure models were developed for fine-scale variation in biologically relevant elemental carbon (EC). Measurements of particulate matter (PM) and EC less than 2.5 μm in aerodynamic diameter (EC2.5) and of PM and EC of nanoscale size less than 0.2 μm were made at up to 29 locations in each of eight Southern California Children's Health Study communities. Regression-based prediction models were developed using a guided forward selection process to identify traffic variables and other pollutant sources, community physical characteristics and land use as predictors of PM and EC variation in each community. A combined eight-community model including only CALINE4 near-roadway dispersion-estimated vehicular emissions accounting for distance, distance-weighted traffic volume, and meteorology, explained 51% of the EC0.2 variability. Community-specific models identified additional predictors in some communities; however, in most communities the correlation between predicted concentrations from the eight-community model and observed concentrations stratified by community was similar to those for the community-specific models. EC2.5 could be predicted as well as EC0.2. EC2.5 estimated from CALINE4 and population density explained 53% of the within-community variation. Exposure prediction was further improved after accounting for between-community heterogeneity of CALINE4 effects associated with average distance to Pacific Ocean shoreline (to 61% for EC0.2) and for regional NOx pollution (to 57% for EC2.5). PM fine spatial scale variation was poorly predicted in both size fractions. In conclusion, models of exposure that include traffic measures such as CALINE4 can provide useful estimates for EC0.2 and EC2.5 on a spatial scale appropriate for health studies of NRP in selected Southern California communities.

Bayesian mixed hidden Markov models: a multi-level approach to modeling categorical outcomes with differential misclassification

Questionnaire-based health status outcomes are often prone to misclassification. When studying the effect of risk factors on such outcomes, ignoring any potential misclassification may lead to biased effect estimates. Analytical challenges posed by these misclassified outcomes are further complicated when simultaneously exploring factors for both the misclassification and health processes in a multi-level setting. To address these challenges, we propose a fully Bayesian mixed hidden Markov model (BMHMM) for handling differential misclassification in categorical outcomes in a multi-level setting. The BMHMM generalizes the traditional hidden Markov model (HMM) by introducing random effects into three sets of HMM parameters for joint estimation of the prevalence, transition, and misclassification probabilities. This formulation not only allows joint estimation of all three sets of parameters but also accounts for cluster-level heterogeneity based on a multi-level model structure. Using this novel approach, both the true health status prevalence and the transition probabilities between the health states during follow-up are modeled as functions of covariates. The observed, possibly misclassified, health states are related to the true, but unobserved, health states and covariates. Results from simulation studies are presented to validate the estimation procedure, to show the computational efficiency due to the Bayesian approach and also to illustrate the gains from the proposed method compared to existing methods that ignore outcome misclassification and cluster-level heterogeneity. We apply the proposed method to examine the risk factors for both asthma transition and misclassification in the Southern California Children's Health Study.

Efficient Two‐Step Testing of Gene‐Gene Interactions in Genome‐Wide Association Studies

Exhaustive testing of all possible SNP pairs in a genome-wide association study (GWAS) generally yields low power to detect gene-gene (G × G) interactions because of small effect sizes and stringent requirements for multiple-testing correction. We introduce a new two-step procedure for testing G × G interactions in case-control GWAS to detect interacting single nucleotide polymorphisms (SNPs) regardless of their marginal effects. In an initial screening step, all SNP pairs are tested for gene-gene association in the combined sample of cases and controls. In the second step, the pairs that pass the screening are followed up with a traditional test for G × G interaction. We show that the two-step method is substantially more powerful to detect G × G interactions than the exhaustive testing approach. For example, with 2,000 cases and 2,000 controls, the two-step method can have more than 90% power to detect an interaction odds ratio of 2.0 compared to less than 50% power for the exhaustive testing approach. Moreover, we show that a hybrid two-step approach that combines our newly proposed two-step test and the two-step test that screens for marginal effects retains the best power properties of both. The two-step procedures we introduce have the potential to uncover genetic signals that have not been previously identified in an initial single-SNP GWAS. We demonstrate the computational feasibility of the two-step G × G procedure by performing a G × G scan in the asthma GWAS of the University of Southern California Children's Health Study.

Birth Weight and Carotid Artery Intima-Media Thickness

To determine the association between birth weight and carotid artery intima-media thickness (CIMT), a measure of atherogenesis, in a population of 11-year-old children. CIMT measured by high-resolution ultrasound, and birth registry data were available for 670 children of the Southern California Children's Health Study. Multivariate regression analyses were performed to investigate the association between birth weight and CIMT, with adjustment for child's health status and lifestyle, pregnancy information, and parental health. Mean CIMT was 0.57 mm (SD 0.04). We found a nonlinear association between birth weight and CIMT, with an increase in CIMT of 0.014 mm in the fifth (P value .01) compared with the third birth weight quintile. These associations were robust in subsample analyses in children considered normal-weight by gestational age or in term-born children. No significant association with CIMT was found for the lowest quintile. Greater birth weight was significantly associated with increased CIMT at age 11 years. No evidence for an impact of lower birth weight was found. The predictive value of childhood CIMT on future cardiovascular outcomes is largely unknown, but strong associations between childhood cardiovascular disease risk factors and adult vascular disease suggest that increased CIMT in childhood may be clinically important.

Pediatric Idiopathic Intracranial Hypertension and Extreme Childhood Obesity

To estimate the magnitude of the association between overweight, moderate, and extreme childhood obesity and the risk of idiopathic intracranial hypertension (IIH). Risk estimates were obtained from the Kaiser Permanente Southern California Children's Health Study (n = 913 178). Weight classes were assigned by body mass index specific for age and sex. A combination of electronic database searches followed by complete medical records review was used to identify all children diagnosed with IIH between 2006 and 2009. We identified 78 children with IIH, the majority of whom were girls (n = 66, 84.5%), age 11-19 (n = 66, 84.5%), non-Hispanic Whites (n = 37, 47.4%), and overweight or obese (n = 57, 73.1%). The adjusted ORs and 95% CIs of IIH with increasing weight class were 1.00, 3.56 (1.72-7.39), 6.45 (3.10-13.44), and 16.14 (8.18-31.85) for underweight/normal weight (reference category), overweight, moderately obese and extremely obese 11-19 year olds, respectively (P for trend < .001). Other independent IIH risk factors included White non-Hispanic race/ethnicity for all age groups and female sex, but only in older children. Overweight/obese children also had more IIH symptoms at onset than normal weight children. We found that childhood obesity is strongly associated with an increased risk of pediatric IIH in adolescents. Our findings suggest that the childhood obesity epidemic is likely to lead to increased morbidity from IIH particularly among extremely obese, White non-Hispanic teenage girls. Our findings also suggest careful screening of these at risk individuals may lead to earlier detection and opportunity for treatment of IIH.

Joint Analysis for Integrating Two Related Studies of Different Data Types and Different Study Designs Using Hierarchical Modeling Approaches

Background: A chronic disease such as asthma is the result of a complex sequence of biological interactions involving multiple genes and pathways in response to a multitude of environmental exposures. However, methods to model jointly all factors are still evolving. Some of the current challenges include how to integrate knowledge from different data types and different disciplines, as well as how to utilize relevant external information such as gene annotation to identify novel disease genes and gene-environment inter-actions. Methods: Using a Bayesian hierarchical modeling framework, we developed two alternative methods for joint analysis of an epidemiologic study of a disease endpoint and an experimental study of intermediate phenotypes, while incorporating external information. Results: Our simulation studies demonstrated superior performance of the proposed hierarchical models compared to separate analysis with the standard single-level regression modeling approach. The combined analyses of the Southern California Children's Health Study and challenge study data suggest that these joint analytical methods detected more significant genetic main and gene-environment interaction effects than the conventional analysis. Conclusion: The proposed prior framework is very flexible and can be generalized for an integrative analysis of diverse sources of relevant biological data.

Parental Stress Increases the Detrimental Effect of Traffic Exposure on Children's Lung Function

Emerging evidence indicates that psychosocial stress enhances the effect of traffic exposure on the development of asthma. We hypothesized that psychosocial stress would also modify the effect of traffic exposure on lung function deficits. We studied 1,399 participants in the Southern California Children's Health Study undergoing lung function testing (mean age, 11.2 yr). We used hierarchical mixed models to assess the joint effect of traffic-related air pollution and stress on lung function. Psychosocial stress in each child's household was assessed based on parental response to the perceived stress scale (range, 0-16) at study entry. Exposures to nitric oxide, nitrogen dioxide, and total oxides of nitrogen (NOx), surrogates of the traffic-related pollution mixture, were estimated at schools and residences based on a land-use regression model. Among children from high-stress households (parental perceived stress scale > 4) deficits in FEV1 of 4.5 (95% confidence interval, -6.5 to -2.4) and of 2.8% (-5.7 to 0.3) were associated with each 21.8 ppb increase in NOx at homes and schools, respectively. These pollutant effects were significantly larger in the high-stress compared with lower-stress households (interaction P value 0.007 and 0.05 for residential and school NOx, respectively). No significant NOx effects were observed in children from low-stress households. A similar pattern of association was observed for FVC. The observed associations for FEV1 and FVC remained after adjusting for sociodemographic factors and after restricting the analysis to children who do not have asthma. A high-stress home environment is associated with increased susceptibility to lung function effects of air pollution both at home and at school.

Ethnic Differences in the Effect of Asthma on Pulmonary Function in Children

The impact of asthma on chronic lung function deficits is well known. However, there has been little study of ethnic differences in these asthma-associated deficits. To examine whether there are ethnic differences in the effects of asthma on children's lung function. We evaluated the impact of asthma on lung function in 3,245 Hispanic and non-Hispanic white school children (age 10-18 yr) in a longitudinal analysis of the Southern California Children's Health Study. Sex-specific mixed-effects regression spline models were fitted separately for each ethnic group. Large deficits in flows were observed among children with asthma diagnosed before age 4 years regardless of ethnicity. Hispanic girls with asthma had greater deficits in flows than non-Hispanic girls and were largest for maximal midexpiratory flow (-5.13% compared with -0.58%, respectively). A bigger impact of asthma in Hispanic girls was also found for FEV(1), FEF(75), and PEF (P value 0.04, 0.07, and 0.005, respectively). These ethnic differences were limited to girls diagnosed after age 4 years. In boys, asthma was also associated with greater deficits in flows among Hispanic than in non-Hispanic white children (differences that were not statistically significant). Ethnic differences in prevalence of pets and pests in the home, health insurance coverage, parental education, and smoking did not explain the pattern of lung function differences. Larger asthma-associated lung function deficits in Hispanics, especially among girls, merit further investigation to determine public health implications and to identify causes amenable to intervention.

Childhood Incident Asthma and Traffic-Related Air Pollution at Home and School

BackgroundTraffic-related air pollution has been associated with adverse cardiorespiratory effects, including increased asthma prevalence. However, there has been little study of effects of traffic exposure at school on new-onset asthma.ObjectivesWe evaluated the relationship of new-onset asthma with traffic-related pollution near homes and schools.MethodsParent-reported physician diagnosis of new-onset asthma (n = 120) was identified during 3 years of follow-up of a cohort of 2,497 kindergarten and first-grade children who were asthma- and wheezing-free at study entry into the Southern California Children’s Health Study. We assessed traffic-related pollution exposure based on a line source dispersion model of traffic volume, distance from home and school, and local meteorology. Regional ambient ozone, nitrogen dioxide (NO2), and particulate matter were measured continuously at one central site monitor in each of 13 study communities. Hazard ratios (HRs) for new-onset asthma were scaled to the range of ambient central site pollutants and to the residential interquartile range for each traffic exposure metric.ResultsAsthma risk increased with modeled traffic-related pollution exposure from roadways near homes [HR 1.51; 95% confidence interval (CI), 1.25–1.82] and near schools (HR 1.45; 95% CI, 1.06–1.98). Ambient NO2 measured at a central site in each community was also associated with increased risk (HR 2.18; 95% CI, 1.18–4.01). In models with both NO2 and modeled traffic exposures, there were independent associations of asthma with traffic-related pollution at school and home, whereas the estimate for NO2 was attenuated (HR 1.37; 95% CI, 0.69–2.71).ConclusionsTraffic-related pollution exposure at school and homes may both contribute to the development of asthma.

Prenatal and Secondhand Tobacco Smoke Exposures and Bronchitic Symptoms in Children and Adolescents

RATIONALE: Because the effects of prenatal and secondhand (SHS) tobacco smoke exposures on bronchitic symptoms in children and adolescent have not been studied extensively, we evaluated these associations among 12,033 subjects (5-18 years) who participated in the southern California Children's Health Study in 1993-1996 and in 2003. METHODS: At study entry, bronchitic symptoms during the previous year was determined based on parental report of a daily cough for 3 months in a row, congestion or phlegm for at least 3 months in a row, or bronchitis. Information on maternal smoking during pregnancy, lifetime history of SHS exposure, number of household smokers (none, 1, 2 or more) and number of cigarettes smoked/day at home (none, <10, and ≥10) was based on parental report at cohort entry. We computed adjusted odds ratios (ORs) and 95% confidence intervals (CIs) controlling for potential confounders. Because bronchitic symptoms were common in subjects with asthma, we further evaluated these associations among subjects without asthma. RESULTS: Exposures to maternal smoking in utero was associated with increased risk of bronchitic symptoms (OR=1.18; 95% CI: 1.02-1.36). The risk of bronchitic symptoms increased significantly with increasing number of household smokers and number of cigarette smoked/day (both P-trend=0.02). These findings remained unchanged after restricting the analyses to subjects without asthma. CONCLUSIONS: Both in utero and secondhand tobacco smoke exposures increase the risk of bronchitic symptoms in children and adolescents. The findings, which have clinical and public health implications, highlight the need for implementing preventive interventions to reduce tobacco smoke exposures in all children and adolescents.

Role of inducible nitric oxide synthase in asthma risk and lung function growth during adolescence

BackgroundInducible nitric oxide (NO) synthase (iNOS, encoded by NOS2A) produces NO in response to environmental stimuli, which can result in nitrosative stress. Because nitrosative stress affects respiratory health, it was...

Traffic-Related Air Pollution and Asthma Onset in Children: A Prospective Cohort Study with Individual Exposure Measurement

BackgroundThe question of whether air pollution contributes to asthma onset remains unresolved.ObjectivesIn this study, we assessed the association between asthma onset in children and traffic-related air pollution.MethodsWe selected a sample of 217 children from participants in the Southern California Children’s Health Study, a prospective cohort designed to investigate associations between air pollution and respiratory health in children 10–18 years of age. Individual covariates and new asthma incidence (30 cases) were reported annually through questionnaires during 8 years of follow-up. Children had nitrogen dioxide monitors placed outside their home for 2 weeks in the summer and 2 weeks in the fall–winter season as a marker of traffic-related air pollution. We used multilevel Cox models to test the associations between asthma and air pollution.ResultsIn models controlling for confounders, incident asthma was positively associated with traffic pollution, with a hazard ratio (HR) of 1.29 [95% confidence interval (CI), 1.07–1.56] across the average within-community interquartile range of 6.2 ppb in annual residential NO2. Using the total interquartile range for all measurements of 28.9 ppb increased the HR to 3.25 (95% CI, 1.35–7.85).ConclusionsIn this cohort, markers of traffic-related air pollution were associated with the onset of asthma. The risks observed suggest that air pollution exposure contributes to new-onset asthma.

A Bayesian approach to functional-based multilevel modeling of longitudinal data: applications to environmental epidemiology.

Flexible multilevel models are proposed to allow for cluster-specific smooth estimation of growth curves in a mixed-effects modeling format that includes subject-specific random effects on the growth parameters. Attention is then focused on models that examine between-cluster comparisons of the effects of an ecologic covariate of interest (e.g. air pollution) on nonlinear functionals of growth curves (e.g. maximum rate of growth). A Gibbs sampling approach is used to get posterior mean estimates of nonlinear functionals along with their uncertainty estimates. A second-stage ecologic random-effects model is used to examine the association between a covariate of interest (e.g. air pollution) and the nonlinear functionals. A unified estimation procedure is presented along with its computational and theoretical details. The models are motivated by, and illustrated with, lung function and air pollution data from the Southern California Children's Health Study.

Parental Stress and Childhood Wheeze in a Prospective Cohort Study

Background. Although studies indicate that psychological stress is linked with asthma morbidity, it is unknown whether stress is associated with the incidence of asthma symptoms. Method. In a cohort of 5-to 6-year-old school children participating in the southern California Children's Health Study, we evaluated parent-reported wheeze in the child using a standardized questionnaire and perceived parental stress at study entry. Wheeze in the child was evaluated one year later. Analyses were restricted to children without asthma at study entry (N = 2,888, of whom 286 had wheeze at follow-up). Results. There was an increase in wheeze across an interquartile range of parent stress (odds ratio [OR] 1.18; 95% confidence interval [CI] 0.99, 1.42). Parent stress was associated with wheeze among children with no parental asthma (OR 1.24; CI 0.99, 1.55) and among boys (OR 1.34; CI 1.04, 1.74), but not among girls or children with parental asthma. Among boys with no parental asthma there was a strong dose-response relationship, and in the top quartile of stress the OR was 2.76 (CI 1.39, 5.51) compared to the bottom quartile. Conclusion. Parental stress increases the risk of childhood wheeze among children with no parental history of asthma, especially among boys. These results suggest that the influence of psychosocial factors on asthma, such as stress and social environment, deserve increased attention.

Assessing Uncertainty in Spatial Exposure Models for Air Pollution Health Effects Assessment

BackgroundAlthough numerous epidemiologic studies now use models of intraurban exposure, there has been little systematic evaluation of the performance of different models.ObjectivesIn this present article we proposed a modeling framework for assessing exposure model performance and the role of spatial autocorrelation in the estimation of health effects.MethodsWe obtained data from an exposure measurement substudy of subjects from the Southern California Children’s Health Study. We examined how the addition of spatial correlations to a previously described unified exposure and health outcome modeling framework affects estimates of exposure–response relationships using the substudy data. The methods proposed build upon the previous work, which developed measurement–error techniques to estimate long-term nitrogen dioxide exposure and its effect on lung function in children. In this present article, we further develop these methods by introducing between- and within-community spatial autocorrelation error terms to evaluate effects of air pollution on forced vital capacity. The analytical methods developed are set in a Bayesian framework where multistage models are fitted jointly, properly incorporating parameter estimation uncertainty at all levels of the modeling process.ResultsResults suggest that the inclusion of residual spatial error terms improves the prediction of adverse health effects. These findings also demonstrate how residual spatial error may be used as a diagnostic for comparing exposure model performance.

Parental Stress, Traffic, and New Onset Asthma in a Cohort of Children

SM4-PD-10 Recent literature suggests that both traffic-related pollutant exposure and psychosocial stress are risk factors for childhood asthma. However, there has been little study of synergistic effects or of associations of these risk factors with new onset asthma in prospective studies. We examined the relationship of local traffic-related exposure and of parental stress to the risk of incident asthma in the southern California Children's Health Study. A cohort of 5- to 7-year-old children was recruited in 2003, and a parent of each child completed a questionnaire on the child's history and symptoms of asthma and relevant risk factors. Parental stress at study entry was assessed using a well-validated 4-question perceived stress scale. The child's residential exposure was assessed by modeling exposure to local traffic-related pollutants. A yearly parent-completed questionnaire identified children with new-onset asthma through 2005. The relative risk of new onset childhood asthma associated with parental stress was 1.19 over the interquartile range of stress in the study population (95% CI, 1.00–1.41). There was no association of incident asthma with traffic modeled pollution by itself, but there was a significant interaction of parental stress with the child's residential traffic exposure. The relative risk of asthma associated with the interquartile range of traffic-modeled pollutant exposure was 2.48 (1.37–4.50) among children with parents in the upper quartile of perceived stress. The pattern of effects was similar among children with no lifetime history of wheeze at study entry, indicating that the associations with incident asthma did not merely reflect exacerbation of preexisting (but undiagnosed) asthma. These results suggest that parental stress may make children more susceptible to traffic-related asthma.

Health effects of the 2003 Southern California wildfires on children.

In late October 2003, Southern California wildfires burned more than 3,000 km2. The wildfires produced heavy smoke that affected several communities participating in the University of Southern California Children's Health Study (CHS). To study the acute effects of fire smoke on the health of CHS participants. A questionnaire was used to assess smoke exposure and occurrence of symptoms among CHS high-school students (n = 873; age, 17-18 yr) and elementary-school children (n = 5,551; age, 6-7 yr), in a total of 16 communities. Estimates of particulate matter (PM10) concentrations during the 5 d with the highest fire activity were used to characterize community smoke level. All symptoms (nose, eyes, and throat irritations; cough; bronchitis; cold; wheezing; asthma attacks), medication usage, and physician visits were associated with individually reported exposure differences within communities. Risks increased monotonically with the number of reported smoky days. For most outcomes, reporting rates between communities were also associated with the fire-related PM10 levels. Associations tended to be strongest among those without asthma. Individuals with asthma were more likely to take preventive action, such as wearing masks or staying indoors during the fire. Exposure to wildfire smoke was associated with increased eye and respiratory symptoms, medication use, and physician visits.