Differential respiratory health effects from the 2008 northern California wildfires: A spatiotemporal approach.

We investigated health effects associated with fine particulate matter during a long-lived, large wildfire complex in northern California in the summer of 2008. We estimated exposure to PM2.5 for each day using an exposure prediction model created through data-adaptive machine learning methods from a large set of spatiotemporal data sets. We then used Poisson generalized estimating equations to calculate the effect of exposure to 24-hour average PM2.5 on cardiovascular and respiratory hospitalizations and ED visits. We further assessed effect modification by sex, age, and area-level socioeconomic status (SES). We observed a linear increase in risk for asthma hospitalizations (RR=1.07, 95% CI=(1.05, 1.10) per 5µg/m(3) increase) and asthma ED visits (RR=1.06, 95% CI=(1.05, 1.07) per 5µg/m(3) increase) with increasing PM2.5 during the wildfires. ED visits for chronic obstructive pulmonary disease (COPD) were associated with PM2.5 during the fires (RR=1.02 (95% CI=(1.01, 1.04) per 5µg/m(3) increase) and this effect was significantly different from that found before the fires but not after. We did not find consistent effects of wildfire smoke on other health outcomes. The effect of PM2.5 during the wildfire period was more pronounced in women compared to men and in adults, ages 20-64, compared to children and adults 65 or older. We also found some effect modification by area-level median income for respiratory ED visits during the wildfires, with the highest effects observed in the ZIP codes with the lowest median income. Using a novel spatiotemporal exposure model, we found some evidence of differential susceptibility to exposure to wildfire smoke.

Air Pollution, Neighbourhood Socioeconomic Factors, and Neural Tube Defects in the San Joaquin Valley of California.

BACKGROUND: Environmental pollutants and neighbourhood socioeconomic factors have been associated with neural tube defects, but the potential impact of interaction between ambient air pollution and neighbourhood socioeconomic factors on the risks of neural tube defects is not well understood. METHODS: We used data from the California Center of the National Birth Defects Study and the Children's Health and Air Pollution Study to investigate whether associations between air pollutant exposure in early gestation and neural tube defects were modified by neighbourhood socioeconomic factors in the San Joaquin Valley of California, 1997-2006. There were 5 pollutant exposures, 3 outcomes, and 9 neighbourhood socioeconomic factors included for a total of 135 investigated associations. Estimates were adjusted for maternal race-ethnicity, education, and multivitamin use. RESULTS: We present below odds ratios (ORs) that exclude 1 and a chi-square test of homogeneity P-value of <0.05. We observed increased odds of spina bifida comparing the highest to lowest quartile of particulate matter <10 µm (PM10 ) among those living in a neighbourhood with: (i) median household income of less than $30 000 per year [OR 5.1, 95% confidence interval (CI) 1.7, 15.3]; (ii) more than 20% living below the federal poverty level (OR 2.6, 95% CI 1.1, 6.0); and (iii) more than 30% with less than or equal to a high school education (OR 3.2, 95% CI 1.4, 7.4). The ORs were not statistically significant among those higher socioeconomic status (SES) neighbourhoods. CONCLUSIONS: Our results demonstrate effect modification by neighbourhood socioeconomic factors in the association of particulate matter and neural tube defects in California.

Spatiotemporal prediction of fine particulate matter during the 2008 northern California wildfires using machine learning.

Estimating population exposure to particulate matter during wildfires can be difficult because of insufficient monitoring data to capture the spatiotemporal variability of smoke plumes. Chemical transport models (CTMs) and satellite retrievals provide spatiotemporal data that may be useful in predicting PM2.5 during wildfires. We estimated PM2.5 concentrations during the 2008 northern California wildfires using 10-fold cross-validation (CV) to select an optimal prediction model from a set of 11 statistical algorithms and 29 predictor variables. The variables included CTM output, three measures of satellite aerosol optical depth, distance to the nearest fires, meteorological data, and land use, traffic, spatial location, and temporal characteristics. The generalized boosting model (GBM) with 29 predictor variables had the lowest CV root mean squared error and a CV-R2 of 0.803. The most important predictor variable was the Geostationary Operational Environmental Satellite Aerosol/Smoke Product (GASP) Aerosol Optical Depth (AOD), followed by the CTM output and distance to the nearest fire cluster. Parsimonious models with various combinations of fewer variables also predicted PM2.5 well. Using machine learning algorithms to combine spatiotemporal data from satellites and CTMs can reliably predict PM2.5 concentrations during a major wildfire event.

Framing air pollution epidemiology in terms of population interventions, with applications to multipollutant modeling.

Air pollution epidemiology continues moving toward the study of mixtures and multipollutant modeling. Simultaneously, there is a movement in epidemiology to estimate policy-relevant health effects that can be understood in reference to specific interventions. Scaling regression coefficients from a regression model by an interquartile range (IQR) is one common approach to presenting multipollutant health effect estimates. We are unaware of guidance on how to interpret these effect estimates as an intervention. To illustrate the issues of interpretability of IQR-scaled air pollution health effects, we analyzed how daily concentration changes in 2 air pollutants (nitrogen dioxide and particulate matter with aerodynamic diameter ≤ 2.5 µm) related to one another within 2 seasons (summer and winter), within 3 cities with distinct air pollution profiles (Burbank, California; Houston, Texas; and Pittsburgh, Pennsylvania). In each city season, we examined how realistically IQR scaling in multipollutant lag-1 time-series studies reflects a hypothetical intervention that is possible given the observed data. We proposed 2 causal conditions to explicitly link IQR-scaled effects to a clearly defined hypothetical intervention. Condition 1 specified that the index pollutant had to experience a daily concentration change of greater than 1 IQR, reflecting the notion that the IQR is an appropriate measure of variability between consecutive days. Condition 2 specified that the copollutant had to remain relatively constant. We found that in some city seasons, there were very few instances in which these conditions were satisfied (eg, 1 day in Pittsburgh during summer). We discuss the practical implications of IQR scaling and suggest alternative approaches to presenting multipollutant effects that are supported by empirical data.

Population intervention models to estimate ambient NO2 health effects in children with asthma.

Health effects of ambient air pollution are most frequently expressed in individual studies as responses to a standardized unit of air pollution changes (e.g., an interquartile interval), which is thought to enable comparison of findings across studies. However, this approach does not necessarily convey health effects in terms of a real-world air pollution scenario. In the present study, we use population intervention modeling to estimate the effect of an air pollution intervention that makes explicit reference to the observed exposure data and is identifiable in those data. We calculate the association between ambient summertime nitrogen dioxide (NO2) and forced expiratory flow between 25% and 75% of forced vital capacity (FEF25-75) in a cohort of children with asthma in Fresno, California. We scale the effect size to reflect NO2 abatement on a majority of summer days. The effect estimates were small, imprecise, and consistently indicated improved pulmonary function with decreased NO2. The effects ranged from -0.8% of mean FEF25-75 (95% confidence interval (CI): -3.4, 1.7) to -3.3% (95% CI: -7.5, 0.9). We conclude by discussing the nature and feasibility of the exposure change analyzed here given the observed air pollution profile, and we propose additional applications of population intervention models in environmental epidemiology.

Ambient polycyclic aromatic hydrocarbons and pulmonary function in children.

Few studies have examined the relationship between ambient polycyclic aromatic hydrocarbons (PAHs) and pulmonary function in children. Major sources include vehicular emissions, home heating, wildland fires, agricultural burning, and power plants. PAHs are an important component of fine particulate matter that has been linked to respiratory health. This cross-sectional study examines the relationship between estimated individual exposures to the sum of PAHs with 4, 5, or 6 rings (PAH456) and pulmonary function tests (forced expiratory volume in one second (FEV1) and forced expiratory flow between 25% and 75% of vital capacity) in asthmatic and non-asthmatic children. We applied land-use regression to estimate individual exposures to ambient PAHs for averaging periods ranging from 1 week to 1 year. We used linear regression to estimate the relationship between exposure to PAH456 with pre- and postbronchodilator pulmonary function tests in children in Fresno, California (N=297). Among non-asthmatics, there was a statistically significant association between PAH456 during the previous 3 months, 6 months, and 1 year and postbronchodilator FEV1. The magnitude of the association increased with the length of the averaging period ranging from 60 to 110 ml decrease in FEV1 for each 1 ng/m(3) increase in PAH456. There were no associations with PAH456 observed among asthmatic children. We identified an association between annual PAHs and chronic pulmonary function in children without asthma. Additional studies are needed to further explore the association between exposure to PAHs and pulmonary function, especially with regard to differential effects between asthmatic and non-asthmatic children.

Traffic-related air pollution and risk of preterm birth in the San Joaquin Valley of California.

PURPOSE: To evaluate associations between traffic-related air pollution during pregnancy and preterm birth in births in four counties in California during years 2000 to 2006. METHODS: We used logistic regression to examine the association between the highest quartile of ambient air pollutants (carbon monoxide, nitrogen dioxide, particulate matter <10 and 2.5 µm) and traffic density during pregnancy and each of five levels of prematurity based on gestational age at birth (20-23, 24-27, 28-31, 32-33, and 34-36 weeks) versus term (37-42 weeks). We examined trimester averages and the last month and the last 6 weeks of pregnancy. Models were adjusted for birthweight, maternal age, race/ethnicity, education, prenatal care, and birth costs payment. Neighborhood socioeconomic status (SES) was evaluated as a potential effect modifier. RESULTS: There were increased odds ratios (ORs) for early preterm birth for those exposed to the highest quartile of each pollutant during the second trimester and the end of pregnancy (adjusted OR, 1.4-2.8). Associations were stronger among mothers living in low SES neighborhoods (adjusted OR, 2.1-4.3). We observed exposure-response associations for multiple pollutant exposures and early preterm birth. Inverse associations during the first trimester were observed. CONCLUSIONS: The results confirm associations between traffic-related air pollution and prematurity, particularly among very early preterm births and low SES neighborhoods.

Exposure to airborne polycyclic aromatic hydrocarbons during pregnancy and risk of preterm birth.

BACKGROUND: Preterm birth is an important marker of health and has a prevalence of 12-13% in the U.S. Polycyclic aromatic hydrocarbons (PAHs) are a group of organic contaminants that form during the incomplete combustion of hydrocarbons, such as coal, diesel and gasoline. Studies suggest that exposure to PAHs during pregnancy is related to adverse birth outcomes. The aim of this study is to evaluate the association between exposure to PAHs during the pregnancy and preterm birth. METHODS: The study population included births from years 2001 to 2006 of women whose maternal residence was within 20km of the primary monitoring site in Fresno, California. Data in the Fresno area were used to form a spatio-temporal model to assign daily exposure to PAHs with 4, 5, or 6 rings at the maternal residence throughout pregnancy of all of the births in the study area. Gestational age at birth and relevant covariates were extracted from the birth certificate. RESULTS: We found an association between PAHs during the last 6 weeks of pregnancy and birth at 20-27 weeks (OR=2.74; 95% CI: 2.24-3.34) comparing the highest quartile to the lower three. The association was consistent when each quartile was compared to the lowest (OR2nd=1.49, 95% CI: 1.08-2.06; OR3rd=2.63, 95% CI:1.93-3.59; OR4th=3.94, 95% CI:3.03-5.12). Inverse associations were also observed for exposure to PAHs during the entire pregnancy and the first trimester and birth at 28-31 weeks and 20-27 weeks. CONCLUSION: An association between PAH exposure during the 6 weeks before delivery and early preterm birth was observed. However, the inverse association with early preterm birth offers an unclear, and potentially complex, inference of these associations.

Examining household asthma management behavior through a microeconomic framework.

National guidelines on the effective management of pediatric asthma have been promoted for over 20 years, yet asthma-related morbidity among low-income children remains disproportionately high. To date, household and clinical interventions designed to remediate these differences have been informed largely by a health behavior framework. However, these programs have not resulted in consistent sustained improvements in targeted populations. The continued funding and implementation of programs based on the health behavior framework leads us to question if traditional behavioral models are sufficient to understand and promote adaptation of positive health management behaviors. We introduce the application of the microeconomic framework to investigate potential mechanisms that can lead to positive management behaviors to improve asthma-related morbidity. We provide examples from the literature on health production, preferences, trade-offs and time horizons to illustrate how economic constructs can potentially add to understanding of disease management. The economic framework, which can be empirically observed, tested, and quantified, can explicate the engagement in household-level activities that would affect health and well-being. The inclusion of a microeconomic perspective in intervention research may lead to identification of mechanisms that lead to household decisions with regard to asthma management strategies and behavior. The inclusion of the microeconomic framework to understand the production of health may provide a novel theoretical framework to investigate the underlying causal behavioral mechanisms related to asthma management and control. Adaptation of an economic perspective may provide new insight into the design and implementation of interventions to improve asthma-related morbidity in susceptible populations.

Litigation in obstetrics: does defensive medicine contribute to increases in cesarean delivery?

OBJECTIVE: Obstetrics is one of the most sued subspecialties in the US. This study aimed to examine clinicians' medical-legal experience and its association with recommending cesarean delivery. DESIGN: Cross-sectional convenience survey. POPULATION OR SAMPLE: This is a survey study of clinicians in the US. METHODS: Survey included eight common obstetric clinical vignettes and 27 questions regarding clinicians' practice environment. Chi-square test, multivariable logistic regression models were used for statistical comparisons. MAIN OUTCOME MEASURES: Likelihood of recommending cesarean delivery. RESULTS: There were 1486 clinicians who completed the survey. Clinicians were categorized based on answers to clinical vignettes. Having had lawsuits and daily worry of suits were associated with higher likelihood of recommending cesarean, compared to those without lawsuits (17.2 versus 11.3%, respectively; p = 0.008) as was frequent worry of lawsuits (every day, 20.3% more likely; every week/month, 12.3%; few times a year/never, 11.4%, p < 0.001). CONCLUSION: Obstetric malpractice lawsuit and frequent worry about lawsuit are associated with higher propensity of recommending cesarean delivery in common obstetric settings.

Clinicians' practice environment is associated with a higher likelihood of recommending cesarean deliveries.

OBJECTIVE: Little data exist regarding clinicians' role in the rising annual incidence rate of cesarean delivery in the US. We aimed to examine if clinicians' practice environment is associated with recommending cesarean deliveries. STUDY DESIGN: This is a survey study of clinicians who practice obstetrics in the US. This survey included eight clinical vignettes and 27 questions regarding clinicians' practice environment. Chi-square test and multivariable logistic regression were used for statistical comparison. RESULTS: Of 27 675 survey links sent, 3646 clinicians received and opened the survey electronically, and 1555 (43%) participated and 1486 (94%) completed the survey. Clinicians were categorized into three groups based on eight common obstetric vignettes as: more likely (n = 215), average likelihood (n = 1099), and less likely (n = 168) to recommend cesarean. Clinician environment factors associated with a higher likelihood of recommending cesarean included Laborists/Hospitalists practice model (p < 0.001), as-needed anesthesia support (p = 0.003), and rural/suburban practice setting (p < 0.001). CONCLUSION: We identified factors in clinicians' environment associated with their likelihood of recommending cesarean delivery. The decision to recommend cesarean delivery is a complicated one and is likely not solely based on patient factors.

Traffic-related air pollution and selected birth defects in the San Joaquin Valley of California.

BACKGROUND: Birth defects are a leading cause of infant morbidity and mortality. Studies suggest associations between environmental contaminants and some structural anomalies, although evidence is limited and several anomalies have not been investigated previously. METHODS: We used data from the California Center of the National Birth Defects Prevention Study and the Children's Health and Air Pollution Study to estimate the odds of 26 congenital birth defect phenotypes with respect to quartiles of seven ambient air pollutant and traffic exposures in California during the first 2 months of pregnancy, 1997 to 2006 (874 cases and 849 controls). We calculated odds ratios (adjusted for maternal race/ethnicity, education, and vitamin use; aOR) for 11 phenotypes that had at least 40 cases. RESULTS: Few odds ratios had confidence intervals that did not include 1.0. Odds of esophageal atresia were increased for the highest versus lowest of traffic density (aOR = 2.8, 95% confidence interval [CI], 1.1-7.4) and PM10 exposure (aOR 4.9; 95% CI, 1.4-17.2). PM10 was associated with a decreased risk of hydrocephaly (aOR= 0.3; 95% CI, 0.1-0.9) and CO with decreased risk of anotia/microtia (aOR = 0.4; 95% CI, 0.2-0.8) and transverse limb deficiency (aOR = 0.4; 95% CI, 0.2-0.9), again reflecting highest versus lowest quartile comparisons. CONCLUSION: Most analyses showed no substantive association between air pollution and the selected birth defects with few exceptions of mixed results.

Ambient air pollution and traffic exposures and congenital heart defects in the San Joaquin Valley of California.

BACKGROUND: Congenital anomalies are a leading cause of infant morbidity and mortality. Studies suggest associations between environmental contaminants and some anomalies, although evidence is limited. METHODS: We used data from the California Center of the National Birth Defects Prevention Study and the Children's Health and Air Pollution Study to estimate the odds of 27 congenital heart defects with respect to quartiles of seven ambient air pollutant and traffic exposures in California during the first 2 months of pregnancy, 1997-2006 (n = 822 cases and n = 849 controls). RESULTS: Particulate matter < 10 microns (PM10 ) was associated with pulmonary valve stenosis [adjusted odds ratio (aOR)Fourth Quartile = 2.6] [95% confidence intervals (CI) 1.2, 5.7] and perimembranous ventricular septal defects (aORThird Quartile = 2.1) [95% CI 1.1, 3.9] after adjusting for maternal race/ethnicity, education and multivitamin use. PM2.5 was associated with transposition of the great arteries (aORThird Quartile = 2.6) [95% CI 1.1, 6.5] and inversely associated with perimembranous ventricular septal defects (aORFourth Quartile = 0.5) [95% CI 0.2, 0.9]. Secundum atrial septal defects were inversely associated with carbon monoxide (aORFourth Quartile = 0.4) [95% CI 0.2, 0.8] and PM2.5 (aORFourth Quartile = 0.5) [95% CI 0.3, 0.8]. Traffic density was associated with muscular ventricular septal defects (aORFourth Quartile = 3.0) [95% CI 1.2, 7.8] and perimembranous ventricular septal defects (aORThird Quartile = 2.4) [95% CI 1.3, 4.6], and inversely associated with transposition of the great arteries (aORFourth Quartile = 0.3) [95% CI 0.1, 0.8]. CONCLUSIONS: PM10 and traffic density may contribute to the occurrence of pulmonary valve stenosis and ventricular septal defects, respectively. The results were mixed for other pollutants and had little consistency with previous studies.

The association of ambient air pollution and traffic exposures with selected congenital anomalies in the San Joaquin Valley of California.

Congenital anomalies are a leading cause of infant mortality and are important contributors to subsequent morbidity. Studies suggest associations between environmental contaminants and some anomalies, although evidence is limited. We aimed to investigate whether ambient air pollutant and traffic exposures in early gestation contribute to the risk of selected congenital anomalies in the San Joaquin Valley of California, 1997-2006. Seven exposures and 5 outcomes were included for a total of 35 investigated associations. We observed increased odds of neural tube defects when comparing the highest with the lowest quartile of exposure for several pollutants after adjusting for maternal race/ethnicity, education, and multivitamin use. The adjusted odds ratio for neural tube defects among those with the highest carbon monoxide exposure was 1.9 (95% confidence interval: 1.1, 3.2) compared with those with the lowest exposure, and there was a monotonic exposure-response across quartiles. The highest quartile of nitrogen oxide exposure was associated with neural tube defects (adjusted odds ratio = 1.8, 95% confidence interval: 1.1, 2.8). The adjusted odds ratio for the highest quartile of nitrogen dioxide exposure was 1.7 (95% confidence interval: 1.1, 2.7). Ozone was associated with decreased odds of neural tube defects. Our results extend the limited body of evidence regarding air pollution exposure and adverse birth outcomes.

Hypertension and low HDL cholesterol were associated with reduced kidney function across the age spectrum: a collaborative study.

PURPOSE: To determine if the associations among established risk factors and reduced kidney function vary by age. METHODS: We pooled cross-sectional data from 14,788 nondiabetics aged 40 to 100 years in 4 studies: Cardiovascular Health Study, Health, Aging, and Body Composition Study, Multi-Ethnic Study of Atherosclerosis, and Prevention of Renal and Vascular End-Stage Disease cohort. RESULTS: Hypertension and low high-density lipoprotein (HDL) cholesterol were associated with reduced cystatin C-based estimated glomerular filtration rate (eGFR) across the age spectrum. In adjusted analyses, hypertension was associated with a 2.3 (95% confidence interval [CI], 0.1, 4.4), 5.1 (95% CI, 4.1, 6.1), and 6.9 (95% CI, 3.0, 10.4) mL/min/1.73 m(2) lower eGFR in participants 40 to 59, 60 to 79, and at least 80 years, respectively (P for interaction < .001). The association of low HDL cholesterol with reduced kidney function was also greater in the older age groups: 4.9 (95% CI, 3.5, 6.3), 7.1 (95% CI, 6.0, 8.3), 8.9 (95% CI, 5.4, 11.9) mL/min/1.73 m(2) (P for interaction < .001). Smoking and obesity were associated with reduced kidney function in participants under 80 years. All estimates of the potential population impact of the risk factors were modest. CONCLUSIONS: Hypertension, obesity, smoking, and low HDL cholesterol are modestly associated with reduced kidney function in nondiabetics. The associations of hypertension and HDL cholesterol with reduced kidney function seem to be stronger in older adults.

Mapping and modeling airborne urban phenanthrene distribution using vegetation biomonitoring.

To capture the spatial distribution of phenanthrene in an urban setting we used vegetation biomonitoring with Jeffrey pine trees (Pinus jeffreyi). The major challenge in characterizing spatial variation in polycyclic aromatic hydrocarbon (PAH) concentrations within a metropolitan area has been sampling at a fine enough resolution to observe the underlying spatial pattern. However, field and chamber studies show that the primary pathway through which PAHs enter plants is from air into leaves, making vegetation biomonitoring a feasible way to examine the spatial distribution of these compounds. Previous research has shown that phenanthrene has adverse health effects and that it is one of the most abundant PAHs in urban air. We collected 99 pine needle samples from 91 locations in Fresno in the morning on a winter day, and analyzed them for PAHs in the inner needle. All 99 pine needle samples had detectable levels of phenanthrene, with mean concentration of 41.0 ng g-1, median 36.9 ng g-1, and standard deviation of 28.5 ng g-1 fresh weight. The ratio of the 90th:10th percentile concentrations by location was 3.3. The phenanthrene distribution had a statistically significant Moran's I of 0.035, indicating a high degree of spatial clustering. We implemented land use regression to fit a model to our data. Our model was able to explain a moderate amount of the variability in the data (R 2 = 0.56), likely reflecting the major sources of phenanthrene in Fresno. The spatial distribution of modeled airborne phenanthrene shows the influences of highways, railroads, and industrial and commercial zones.

Exposure to traffic-related air pollution during pregnancy and term low birth weight: estimation of causal associations in a semiparametric model.

Traffic-related air pollution is recognized as an important contributor to health problems. Epidemiologic analyses suggest that prenatal exposure to traffic-related air pollutants may be associated with adverse birth outcomes; however, there is insufficient evidence to conclude that the relation is causal. The Study of Air Pollution, Genetics and Early Life Events comprises all births to women living in 4 counties in California's San Joaquin Valley during the years 2000-2006. The probability of low birth weight among full-term infants in the population was estimated using machine learning and targeted maximum likelihood estimation for each quartile of traffic exposure during pregnancy. If everyone lived near high-volume freeways (approximated as the fourth quartile of traffic density), the estimated probability of term low birth weight would be 2.27% (95% confidence interval: 2.16, 2.38) as compared with 2.02% (95% confidence interval: 1.90, 2.12) if everyone lived near smaller local roads (first quartile of traffic density). Assessment of potentially causal associations, in the absence of arbitrary model assumptions applied to the data, should result in relatively unbiased estimates. The current results support findings from previous studies that prenatal exposure to traffic-related air pollution may adversely affect birth weight among full-term infants.

The role of ambient ozone in epidemiologic studies of heat-related mortality.

BACKGROUND: A large and growing literature investigating the role of extreme heat on mortality has conceptualized the role of ambient ozone in various ways, sometimes treating it as a confounder, sometimes as an effect modifier, and sometimes as a co-exposure. Thus, there is a lack of consensus about the roles that temperature and ozone together play in causing mortality. OBJECTIVES: We applied directed acyclic graphs (DAGs) to the topic of heat-related mortality to graphically represent the subject matter behind the research questions and to provide insight on the analytical options available. DISCUSSION: On the basis of the subject matter encoded in the graphs, we assert that the role of ozone in studies of temperature and mortality is a causal intermediate that is affected by temperature and that can also affect mortality, rather than a confounder. CONCLUSIONS: We discuss possible questions of interest implied by this causal structure and propose areas of future work to further clarify the role of air pollutants in epidemiologic studies of extreme temperature.

Polycyclic aromatic hydrocarbon exposure and wheeze in a cohort of children with asthma in Fresno, CA.

Polycyclic aromatic hydrocarbons (PAHs) are found widely in the ambient air and result from combustion of various fuels and industrial processes. PAHs have been associated with adverse human health effects such as cognitive development, childhood IQ, and respiratory health. The Fresno Asthmatic Children's Environment Study enrolled 315 children aged 6-11 years with asthma in Fresno, CA and followed the cohort from 2000 to 2008. Subjects were evaluated for asthma symptoms in up to three 14-day panels per year. Detailed ambient pollutant concentrations were collected from a central site and outdoor pollutants were measured at 83 homes for at least one 5-day period. Measurements of particle-bound PAHs were used with land-use regression models to estimate individual exposures to PAHs with 4-, 5-, or 6-member rings (PAH456) and phenanthrene for the cohort (approximately 22,000 individual daily estimates). We used a cross-validation-based algorithm for model fitting and a generalized estimated equation approach to account for repeated measures. Multiple lags and moving averages of PAH exposure were associated with increased wheeze for each of the three types of PAH exposure estimates. The odds ratios for asthmatics exposed to PAHs (ng/m(3)) ranged from 1.01 (95% CI, 1.00-1.02) to 1.10 (95% CI, 1.04-1.17). This trend for increased wheeze persisted among all PAHs measured. Phenanthrene was found to have a higher relative impact on wheeze. These data provide further evidence that PAHs contribute to asthma morbidity.

Daytime secretion of salivary cortisol and alpha-amylase in preschool-aged children with autism and typically developing children.

We examined daytime salivary cortisol and salivary alpha-amylase (sAA) secretion levels and variability in preschool-aged children with autism (AUT) and typically developing children (TYP). Fifty-two subjects (26 AUT and 26 TYP) were enrolled. Salivary samples were obtained at waking, midday, and bedtime on two consecutive days at three phases (baseline, 3 months later, 6 months later). There were modest increases in waking cortisol and sAA levels in AUT relative to TYP, but the increases were not statistically significant. Important differences were observed in cortisol and sAA variability between AUT and TYP. There was also a graded response among AUT by functional status--cortisol and sAA secretion levels were higher when IQ was lower.