Asthma symptoms in Hispanic children and daily ambient exposures to toxic and criteria air pollutants.

Although acute adverse effects on asthma have been frequently found for the U.S. Environmental Protection Agency's principal criteria air pollutants, there is little epidemiologic information on specific hydrocarbons from toxic emission sources. We conducted a panel study of 22 Hispanic children with asthma who were 10-16 years old and living in a Los Angeles community with high traffic density. Subjects filled out symptom diaries daily for up to 3 months (November 1999 through January 2000). Pollutants included ambient hourly values of ozone, nitrogen dioxide, sulfur dioxide, and carbon monoxide and 24-hr values of volatile organic compounds (VOCs), particulate matter with aerodynamic diameter < 10 microm (PM10, and elemental carbon (EC) and organic carbon (OC) PM10 fractions. Asthma symptom severity was regressed on pollutants using generalized estimating equations, and peak expiratory flow (PEF) was regressed on pollutants using mixed models. We found positive associations of symptoms with criteria air pollutants (O3, NO2, SO2, PM10), EC-OC, and VOCs (benzene, ethylbenzene, formaldehyde, acetaldehyde, acetone, 1,3-butadiene, tetrachloroethylene, toluene, m,p-xylene, and o-xylene). Selected adjusted odds ratios for bothersome or more severe asthma symptoms from interquartile range increases in pollutants were, for 1.4 ppb 8-hr NO2, 1.27 [95% confidence interval (CI), 1.05-1.54]; 1.00 ppb benzene, 1.23 (95% CI, 1.02-1.48); 3.16 ppb formaldehyde, 1.37 (95% CI, 1.04-1.80); 37 microg/m3 PM10, 1.45 (95% CI, 1.11-1.90); 2.91 microg/m3 EC, 1.85 (95% CI, 1.11-3.08); and 4.64 microg/m3 OC, 1.88 (95% CI, 1.12-3.17). Two-pollutant models of EC or OC with PM10 showed little change in odds ratios for EC (to 1.83) or OC (to 1.89), but PM10 decreased from 1.45 to 1.0. There were no significant associations with PEF. Findings support the view that air toxins in the pollutant mix from traffic and industrial sources may have adverse effects on asthma in children

Use of Pharmacokinetic Modeling to Design Studies for Pathway-Specific Exposure Model Evaluation

Validating an exposure pathway model is difficult because the biomarker, which is often used to evaluate the model prediction, is an integrated measure for exposures from all the exposure routes and pathways. The purpose of this article is to demonstrate a method to use pharmacokinetic (PK) modeling and computer simulation to guide the design of field studies to validate pathway models. The children’s dietary intake model is discussed in detail as an example. Three important aspects are identified for a successful design to evaluate the children’s dietary intake model: a) longitudinally designed study with significant changes in the exposure for the route/pathway of interest, b) short biologic half-life of the selected chemical, and c) surface loading of the selected chemical at sufficient levels. Using PK modeling to guide a study design allowed a path-specific exposure model to be evaluated using urinary metabolite biomarkers

Identifying and Prioritizing Chemicals with Uncertain Burden of Exposure: Opportunities for Biomonitoring and Health-Related Research.

BackgroundThe National Institutes of Health's Environmental influences on Child Health Outcomes (ECHO) initiative aims to understand the impact of environmental factors on childhood disease. Over 40,000 chemicals are approved for commercial use. The challenge is to prioritize chemicals for biomonitoring that may present health risk concerns.ObjectivesOur aim was to prioritize chemicals that may elicit child health effects of interest to ECHO but that have not been biomonitored nationwide and to identify gaps needing additional research.MethodsWe searched databases and the literature for chemicals in environmental media and in consumer products that were potentially toxic. We selected chemicals that were not measured in the National Health and Nutrition Examination Survey. From over 700 chemicals, we chose 155 chemicals and created eight chemical panels. For each chemical, we compiled biomonitoring and toxicity data, U.S. Environmental Protection Agency exposure predictions, and annual production usage. We also applied predictive modeling to estimate toxicity. Using these data, we recommended chemicals either for biomonitoring, to be deferred pending additional data, or as low priority for biomonitoring.ResultsFor the 155 chemicals, 97 were measured in food or water, 67 in air or house dust, and 52 in biospecimens. We found in vivo endocrine, developmental, reproductive, and neurotoxic effects for 61, 74, 47, and 32 chemicals, respectively. Eighty-six had data from high-throughput in vitro assays. Positive results for endocrine, developmental, neurotoxicity, and obesity were observed for 32, 11, 35, and 60 chemicals, respectively. Predictive modeling results suggested 90% are toxicants. Biomarkers were reported for 76 chemicals. Thirty-six were recommended for biomonitoring, 108 deferred pending additional research, and 11 as low priority for biomonitoring.DiscussionThe 108 deferred chemicals included those lacking biomonitoring methods or toxicity data, representing an opportunity for future research. Our evaluation was, in general, limited by the large number of unmeasured or untested chemicals. https://doi.org/10.1289/EHP5133