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BackgroundEmerging experimental evidence suggests that air pollution may contribute to development of obesity and diabetes, but studies of children are limited.ObjectivesWe hypothesized that pollution effects would be magnified after bariatric surgery for treatment of obesity, reducing benefits of surgery.MethodsIn 75 obese adolescents, excess weight loss (EWL), high-density lipoprotein (HDL) cholesterol, triglycerides, alkaline phosphatase (ALP) and hemoglobin A1c (HbA1c ) were measured prospectively at baseline and following laparoscopic adjustable gastric banding (LAGB). Residential distances to major roads and the average two-year follow-up exposure to particulate matter

Summary: Objective: Studies suggest that prenatal exposure to traffic‐related air pollution (TRAP) may contribute to childhood obesity. While exact mechanisms for this association are unknown, circulating adipokines are hypothesized to contribute to early‐life weight gain. Methods: The Maternal and Child Health Study birth cohort included 136 women from the Los Angeles County + University of Southern California Medical Center. This study estimated prenatal residential TRAP exposure and used linear regression analysis to examine associations between adipokines with TRAP exposure and infant weight change (birth to 6 months). Results: A one standard deviation (1‐SD: 2 ppb) increase in prenatal non‐freeway nitrogen oxides was associated with 33% (P = 0.01) higher leptin and 9% higher high molecular weight adiponectin levels (P = 0.07) in cord blood. Leptin levels were 71% higher in mothers who lived <75 m than those living >300 m from major roadways (P = 0.03). A 1‐SD (10 ng mL−1) increase in leptin was associated with a significant increase in infant weight change in female infants (0.62 kg, P = 0.02) but not male infants (0.11 kg, P = 0.48). Conclusions: Higher TRAP exposures were associated with higher cord blood levels of leptin and high molecular weight adiponectin. These adipokines were associated with increased infant weight change in female infants, which may have implications for future obesity risk. [ABSTRACT FROM AUTHOR]

BACKGROUND: Asthma is the most important chronic disease of childhood. The U.S. Environmental Protection Agency has concluded that children with asthma continue to be susceptible to ozone-associated adverse effects on their disease. OBJECTIVES: This study was designed to evaluate time trends in associations between declining warm-season [O.sub.3] concentrations and hospitalization for asthma in children. METHODS: We undertook an ecologic study of hospital discharges for asthma during the high [O.sub.3] seasons in California's South Coast Air Basin (SoCAB) in children who ranged in age from birth to 19 years from 1983 to 2000. We used standard association and causal statistical analysis methods. Hospital discharge data were obtained from the State of California; air pollution data were obtained from the California Air Resources Board, and demographic data from the 1980, 1990, and 2000 U.S. Census. SoCAB was divided into 195 spatial grids, and quarterly average [O.sub.3], sulfur dioxide, particulate matter with aerodynamic diameter ≤ 10 µm, nitrogen dioxide, and carbon monoxide were assigned to each unit for 3-month periods along with demographic variables. RESULTS: [O.sub.3] was the only pollutant associated with increased hospital admissions over the study period. Inclusion of a variety of demographic and weather variables accounted for all of the non- [O.sub.3] temporal changes in hospitalizations. We found a time-independent, constant effect of ambient levels of [O.sub.3[ and quarterly hospital discharge rates for asthma. We estimate that the average effect of a 10-ppb mean increase in any given mean quarterly 1-hr maximum [O.sub.3] over the 18-year median of 87.7 ppb was a 4.6% increase in the same quarterly outcome. CONCLUSIONS: Our data indicate that at current levels of [O.sub.3] experienced in southern California, [O.sub.3] contributes to an increased risk of hospitalization for children with asthma., Commentary As mentioned previously, the rates of asthma have been increasing dramatically around the globe for the last couple of decades. These increases have been associated with both outdoor and [...]

Background: Although numerous epidemiologic studies now use models of intra-urban exposure, there has been little systematic evaluation of the performance of different models. Objectives: In this paper we proposed a modeling framework for assessing exposure model performance and the role of spatial autocorrelation in health effects estimation. Methods: Data was obtained from an exposure measurement substudy of subjects from the Southern California Children's Health Study. We examine 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 authors' previous work, which developed measurement-error techniques to estimate long-term nitrogen dioxide (NO2) exposure and its effect on lung function in children. This paper further develops these methods by introducing between and within-community spatial autocorrelation error terms to evaluate effects of air pollution on forced vital capacity (FVC). The analytical methods developed are set in a Bayesian framework where multi-stage models are fitted jointly, properly incorporating parameter estimation uncertainty at all levels of the modeling process. Results: Findings suggest that the inclusion of residual spatial error terms improves the prediction of health effects. The results also demonstrate how residual spatial error may be used as a diagnostic for comparing exposure model performance. [ABSTRACT FROM AUTHOR]

Rationale: 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).Objectives: To study the acute effects of fire smoke on the health of CHS participants.Methods: 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.Main Results: 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.Conclusions: Exposure to wildfire smoke was associated with increased eye and respiratory symptoms, medication use, and physician visits. [ABSTRACT FROM AUTHOR]

The National Children's Study is considering a wide spectrum of airborne pollutants that are hypothesized to potentially influence pregnancy outcomes, neurodevelopment, asthma, atopy, immune development, obesity, and pubertal development. In this article we summarize six applicable exposure assessment lessons learned from the Centers for Children's Environmental Health and Disease Prevention Research that may enhance the National Children's Study: a) Selecting individual study subjects with a wide range of pollution exposure profiles maximizes spatial-scale exposure contrasts for key pollutants of study interest. b) In studies with large sample sizes, long duration, and diverse outcomes and exposures, exposure assessment efforts should rely on modeling to provide estimates for the entire cohort, supported by subject-derived questionnaire data. c) Assessment of some exposures of interest requires individual measurements of exposures using snapshots of personal and microenvironmental exposures over short periods and/or in selected microenvironments. d) Understanding issues of spatial-temporal correlations of air pollutants, the surrogacy of specific pollutants for components of the complex mixture, and the exposure misclassification inherent in exposure estimates is critical in analysis and interpretation. e) 'Usual' temporal, spatial, and physical patterns of activity can be used as modifiers of the exposure/outcome relationships. f) Biomarkers of exposure are useful for evaluation of specific exposures that have multiple routes of exposure. If these lessons are applied, the National Children's Study offers a unique opportunity to assess the adverse effects of air pollution on interrelated health outcomes during the critical early life period. [ABSTRACT FROM AUTHOR]

Population growth and the proliferation of roadways in Southern California have facilitated a glut of mobile air pollution sources (cars and trucks), resulting in substantial atmospheric pollution. Despite successful efforts over the past 40 years to reduce pollution, an alarming set of health effects attributable to air pollution have been described in Southern California. The Children's Health Study indicates that reduced lung function growth, increased school absences, asthma exacerbation, and new-onset asthma are occurring at current levels of air pollution, with sizable economic consequences. We describe these findings and urge a more aggressive effort to reduce air pollution exposures to protect our children's health. Lessons from this 'case study' have national implications. [ABSTRACT FROM AUTHOR]

Abstract Background Diverse environmental exposures, studied separately, have been linked to health outcomes in adult asthma, but integrated multi-factorial effects have not been modeled. We sought to evaluate the contribution of combined social and physical environmental exposures to adult asthma lung function and disease severity. Methods Data on 176 subjects with asthma and/or rhinitis were collected via telephone interviews for sociodemographic factors and asthma severity (scored on a 0-28 point range). Dust, indoor air quality, antigen-specific IgE antibodies, and lung function (percent predicted FEV1) were assessed through home visits. Neighborhood socioeconomic status, proximity to traffic, land use, and ambient air quality data were linked to the individual-level data via residential geocoding. Multiple linear regression separately tested the explanatory power of five groups of environmental factors for the outcomes, percent predicted FEV1 and asthma severity. Final models retained all variables statistically associated (p < 0.20) with each of the two outcomes. Results Mean FEV1 was 85.0 ± 18.6%; mean asthma severity score was 6.9 ± 5.6. Of 29 variables screened, 13 were retained in the final model of FEV1 (R2 = 0.30; p < 0.001) and 15 for severity (R2 = 0.16; p < 0.001), including factors from each of the five groups. Adding FEV1 as an independent variable to the severity model further increased its explanatory power (R2 = 0.25). Conclusions Multivariate models covering a range of individual and environmental factors explained nearly a third of FEV1 variability and, taking into account lung function, one quarter of variability in asthma severity. These data support an integrated approach to modeling adult asthma outcomes, including both the physical and the social environment.