Exposure to cadmium, cobalt, lead, and manganese has been associated with decreased pulmonary function in adults. Little is known about the magnitude of these associations among children in the United States. We evaluated cross-sectional associations of blood and urinary concentrations of cadmium, cobalt, lead, and manganese with pulmonary function measures [forced expiratory volume in one second (FEV1; milliliters), forced vital capacity (FVC; milliliters), ratio of FEV1 to FVC (FEV1:FVC), and mid-exhalation forced expiratory flow rate (FEF 25-75%; milliliters/second)] in a sample of 1234 6-17 year olds, who participated in the 2011-2012 survey cycle of the National Health and Nutrition Examination Survey (NHANES). Survey-weighted linear regression was used to estimate beta coefficients and 95% confidence intervals (CIs) for the associations between metal exposure tertiles or quartiles and pulmonary function test parameters, with adjustment for relevant covariates. Blood manganese concentration was inversely associated with FVC (β for highest versus lowest quartile = -97.1, 95% CI = -230.6, 36.4; p for trend = 0.03). Urinary manganese was inversely associated with FEV1:FVC and FEF 25-75% (p for trend = 0.05 and 0.02, respectively). Urinary lead was inversely associated with FEF 25-75% (p for trend = 0.01). The associations between blood manganese and both FEV1 and FVC differed by age (p for interaction = 0.04 and 0.04, respectively), indicating an inverse trend that was strongest among older youth. Environmental exposure to manganese and lead may adversely impact the pulmonary function of young people in the United States. Our findings highlight a need to prioritize children's environmental health and evaluate these associations prospectively.

Background: Industrial facilities are not located uniformly across communities in the United States, but how the burden of exposure to carcinogenic air emissions may vary across population characteristics is unclear. We evaluated differences in carcinogenic industrial pollution among major sociodemographic groups in the United States and Puerto Rico. Methods: We evaluated cross-sectional associations of population characteristics including race and ethnicity, educational attainment, and poverty at the census tract level with point-source industrial emissions of 21 known human carcinogens using regulatory data from the US Environmental Protection Agency. Odds ratios and 95% confidence intervals comparing the highest emissions (tertile or quintile) to the referent group (zero emissions [ie, nonexposed]) for all sociodemographic characteristics were estimated using multinomial, population density–adjusted logistic regression models. Results: In 2018, approximately 7.4 million people lived in census tracts with nearly 12 million pounds of carcinogenic air releases. The odds of tracts having the greatest burden of benzene, 1,3-butadiene, ethylene oxide, formaldehyde, trichloroethylene, and nickel emissions compared with nonexposed were 10%-20% higher for African American populations, whereas White populations were up to 18% less likely to live in tracts with the highest emissions. Among Hispanic and Latino populations, odds were 16%-21% higher for benzene, 1,3-butadiene, and ethylene oxide. Populations experiencing poverty or with less than high school education were associated with up to 51% higher burden, irrespective of race and ethnicity. Conclusions: Carcinogenic industrial emissions disproportionately impact African American and Hispanic and Latino populations and people with limited education or experiencing poverty thus representing a source of pollution that may contribute to observed cancer disparities.

Pesticide exposure has been associated with adverse health effects. We evaluated relationships between proximity to agricultural insecticide applications and insecticides in household dust, accounting for land use and wind direction. We measured concentrations (ng/g) of nine insecticides in carpet-dust samples collected from 598 California homes. Using a geographic information system (GIS), we integrated the California Pesticide Use Reporting (CPUR) database to estimate agricultural use within residential buffers with radii of 0.5 to 4 km. We calculated the density of use (kg/km²) during 30-, 60-, 180-, and 365-day periods prior to dust collection and evaluated relationships between three density metrics (CPUR unit-based, agricultural land area adjusted, and average daily wind direction adjusted) and dust concentrations. We modeled natural-log transformed concentrations using Tobit regression for carbaryl, chlorpyrifos, cypermethrin, diazinon, and permethrin. Odds of detection were modeled with logistic regression for azinphos-methyl, cyfluthrin, malathion, and phosmet. We adjusted for season, year, occupation, and home/garden uses. Chlorpyrifos use within 1-4 km was associated with 1 to 2-times higher dust concentrations in both the 60- and 365-day periods. Carbaryl applications within 2-4 km of homes 60-days prior to dust collection were associated with 3 to 7-times higher concentrations and the 4 km trend was strongest using the wind-adjusted metric (p-trend = 0.04). For diazinon, there were 2-times higher concentrations for the 60-day metrics in the 2 km buffer and for the CPUR and wind-adjusted metrics within 4 km. Cyfluthrin, phosmet, and azinphos-methyl applications within 4 km in the prior 365-days were associated with 2-, 6-, and 3-fold higher odds of detection, respectively. Agricultural use of six of the nine insecticides within 4 km is an important determinant of indoor contamination. Our findings demonstrated that GIS-based metrics for quantifying potential exposure to fugitive emissions from agriculture should incorporate tailored distances and time periods and support wind-adjustment for some, but not all insecticides.