Wande Benka-Coker1, Lauren Hoskovec2, Rachel Severson3, John Balmes4, Ander Wilson2, Sheryl Magzamen5. 1. Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA. Electronic address: wande.benka-coker@colostate.edu. 2. Department of Statistics, Colorado State University, Fort Collins, CO, USA. 3. Colorado Department of Public Health and Environment; Denver, Colorado, USA. 4. Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA. 5. Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA.
Abstract
BACKGROUND: Ambient environmental pollutants have been shown to adversely affect respiratory health in susceptible populations. However, the role of simultaneous exposure to multiple diverse environmental pollutants is poorly understood. OBJECTIVE: We applied a multidomain, multipollutant approach to assess the association between pediatric lung function measures and selected ambient air pollutants and pesticides. METHODS: Using data from the US EPA and California Pesticide Use Registry, we reconstructed three months prior exposure to ambient air pollutants ((ozone (O3), nitrogen dioxide (NO2), particulate matter with a median aerodynamic diameter < 2.5 μm (PM2.5) and <10 μm (PM10)) and pesticides (organophosphates (OP), carbamates (C) and methyl bromide (MeBr)) for 153 children with mild intermittent or mild persistent asthma from the San Joaquin Valley of California, USA. We implemented Bayesian kernel machine regression (BKMR) to estimate the association between simultaneous exposures to air pollutants and pesticides and lung function measures (forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), and forced expiratory flow between 25% and 75% of vital capacity (FEF25-75)). RESULTS: In BKMR analysis, the overall effect of mixtures (pollutants and pesticides) was associated with reduced FEV1 and FVC, particularly when all the environmental exposures were above their 60th percentile. For example, the effect of the overall mixture at the 70th percentile (compared to the median) was a -0.12SD (-50 mL, 95% CI: -180 mL, 90 mL) change in the FEV1 and a -0.18SD (-90 mL, 95% CI: -240 mL, 60 mL) change in the FVC. However, 95% credible intervals around all of the joint effect estimates contained the null value. CONCLUSION: At this agricultural-urban interface, we observed results from multipollutant analyses, suggestive of adverse effects on some pediatric lung function measures following a cumulative increase in ambient air pollutants and agricultural pesticides. Given the uncertainty in effect estimates, this approach should be explored in larger studies.
BACKGROUND: Ambient environmental pollutants have been shown to adversely affect respiratory health in susceptible populations. However, the role of simultaneous exposure to multiple diverse environmental pollutants is poorly understood. OBJECTIVE: We applied a multidomain, multipollutant approach to assess the association between pediatric lung function measures and selected ambient air pollutants and pesticides. METHODS: Using data from the US EPA and California Pesticide Use Registry, we reconstructed three months prior exposure to ambient air pollutants ((ozone (O3), nitrogen dioxide (NO2), particulate matter with a median aerodynamic diameter < 2.5 μm (PM2.5) and <10 μm (PM10)) and pesticides (organophosphates (OP), carbamates (C) and methyl bromide (MeBr)) for 153 children with mild intermittent or mild persistent asthma from the San Joaquin Valley of California, USA. We implemented Bayesian kernel machine regression (BKMR) to estimate the association between simultaneous exposures to air pollutants and pesticides and lung function measures (forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), and forced expiratory flow between 25% and 75% of vital capacity (FEF25-75)). RESULTS: In BKMR analysis, the overall effect of mixtures (pollutants and pesticides) was associated with reduced FEV1 and FVC, particularly when all the environmental exposures were above their 60th percentile. For example, the effect of the overall mixture at the 70th percentile (compared to the median) was a -0.12SD (-50 mL, 95% CI: -180 mL, 90 mL) change in the FEV1 and a -0.18SD (-90 mL, 95% CI: -240 mL, 60 mL) change in the FVC. However, 95% credible intervals around all of the joint effect estimates contained the null value. CONCLUSION: At this agricultural-urban interface, we observed results from multipollutant analyses, suggestive of adverse effects on some pediatric lung function measures following a cumulative increase in ambient air pollutants and agricultural pesticides. Given the uncertainty in effect estimates, this approach should be explored in larger studies.
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