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BackgroundPesticide 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.MethodsWe 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.ResultsChlorpyrifos 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.ConclusionsAgricultural 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.

BackgroundSelf-reported residential use of pesticides has consistently been associated with increased risk of childhood leukemia. However, these studies were limited in their ability to identify specific insecticide active ingredients that were associated with risk.ObjectiveWe used household carpet dust measurements of 20 insecticides (two carbamate, 10 organophosphate, two organochlorine, and six pyrethroid) as indicators of exposure and evaluated associations with the risk of childhood acute lymphoblastic leukemia (ALL).MethodsWe conducted a population-based case-control study of 252 ALL cases diagnosed from 1999 to 2007 and 306 birth certificate controls from 35 counties in Central and Northern California. Carpet dust was collected at a second interview (2001-2007) for cases who had not moved since diagnosis (comparable reference date for controls) using a specialized vacuum cleaner in the room where the child spent most of their time or from the household vacuum. Insecticides were categorized as detected (yes/no), or as tertiles or quartiles of their distributions among controls. We calculated odds ratios (OR) and 95% confidence intervals (CI) using unconditional logistic regression adjusting for demographic characteristics, interview year, and season of dust collection.ResultsPermethrin, chlorpyrifos, diazinon, and carbaryl were the most frequently detected insecticide active ingredients. When we compared the highest quartile to the lowest or to non-detections, there was no association with ALL for permethrin (OR Q4 vs. Q1 = 0.81; 95% CI 0.50-1.31), carbaryl (OR Q4 vs. non-detects = 0.61, 95% CI 0.34-1.08) or chlorpyrifos (OR Q4 vs. Q1 = 0.60; 95% CI 0.36-1.00). The highest quartile of diazinon concentration was inversely associated with risk in the single pesticide model but without a monotonic exposure-response (p-trend = 0.14). After adjusting for other common insecticides, the OR was not significant (OR Q4 vs. Q1 = 0.58; 95% CI 0.33-1.05). None of the other insecticides were associated with risk.ConclusionOur results should be interpreted within the limitations of the case-control study design including the use of a single post-diagnosis dust sample and restriction to residentially stable participants, which may have resulted in selection bias. Although difficult to implement, additional studies with assessment of exposure to insecticide active and non-active ingredients are necessary to elucidate the role of these common exposures in childhood leukemia risk.