Characterizing the joint effects of pesticide exposure and criteria ambient air pollutants on pediatric asthma morbidity in an agricultural community

Abstract

Background: Environmental contributions to pediatric asthma morbidity have been studied extensively in urban settings; exposures characteristic of agricultural and rural communities have received less attention despite a comparable burden of morbidity.

Methods: We obtained repeated urine samples (n = 139) from 16 school-age children with asthma in the Yakima Valley of Washington State between July and October 2012. Biomarkers of organophosphate (OP) pesticide exposure (dialkyl phosphates [DAPs]) and asthma exacerbation (leukotriene E4 [LTE4]) were analyzed in samples. Corresponding 24-hour average particulate matter <2.5 μg (PM_2.5) and maximum 8-hour ozone concentration data for the study period were available from local monitoring stations. We evaluated the independent and multi-pollutant associations between LTE4 and exposure to ambient air pollutants and DAPs using generalized estimating equations. For multi-domain and multi-pollutant models, we created categorized pollution combination levels and estimated the relative health impact of exposure to pollutant mixtures.

Results: In single-pollutant models, an interquartile range increase in exposures to DAPs was associated with increase in LTE4 levels (β: 4.1 [0.6-7.6] pg/mg). PM_2.5 and ozone were also associated with increase in LTE4, though confidence intervals contained the null value. Increase in LTE4 levels was consistently associated with increase in median-dichotomized multi-pollutant combination exposures; the highest effect estimates were observed with joint highest (vs. the lowest) category of the three-pollutant exposure (PM_2.5, ozone, and OP; β: 53.5, 95% confidence interval = 24.2, 82.8 pg/mg).

Conclusion: Concurrent short-term exposure to criteria air pollutants and OPs in an agricultural community was associated with an increase in a marker of asthma morbidity.

Keywords: Agricultural settings; Biomarkers; Pediatric asthma; Pollutant mixtures.

Figure 1.

Creatinine-adjusted urinary LTE4 levels for study participants over the study period. Vertical lines represent the beginning of a new month. Observed LTE4 series for one participant (15) is highlighted.

Figure 2.

Air pollutant and pesticide exposure levels for study participants over the study period. Numbers in plot area indicate participant IDs. Horizontal line represents US National Ambient Air Quality Standard. A, Creatinine-adjusted urinary log OP (DAP, OP) levels. B, Maximum 8-hour ambient ozone levels. C, 24-hour average ambient PM_2.5 concentrations.

Figure 3.

Estimated effects (β change and 95% CIs) of pollutants on creatinine-adjusted LTE4 levels (in pg/mg creatinine). A, Single-pollutant and multi-pollutant models using the median cutoff for categorization. B, Multi-pollutant models using median cutoff for categorization, excluding observations below EPA cutoff values. All models were adjusted for sex, age, use of inhaled corticosteroids at baseline, number of individuals in household, temperature, wind speed, precipitation, and relative humidity. PM_2.5 indicates 24-hour-average exposure to particulate matter <2.5 µm in diameter; ozone, 8-hour maximum concentration of ozone; OP, urinary measure of metabolite of OP exposure, total DAP.

Figure 4.

Estimated effects (β change and 95% CIs) on creatinine-adjusted LTE4 levels (in pg/mg creatinine) from two-pollutant models indicating specific pollutant contribution to exposure mixture categories. Letter in parenthesis indicates pollutant with highest exposure level; PM_2.5, particulate matter <2.5 µm in diameter; O₃, ozone; OP, total DAP (OP). Horizontal lines indicate level of effect estimates of single pollutant in comparison to multi-pollutants.