There has been a growing interest in the literature on multiple environmental risk factors for diseases and an increasing emphasis on assessing multiple environmental exposures simultaneously in epidemiologic studies of cancer. One method used to analyze exposure to multiple chemical exposures is weighted quantile sum (WQS) regression. While WQS regression has been demonstrated to have good sensitivity and specificity when identifying important exposures, it has limitations including a two-step model fitting process that decreases power and model stability and a requirement that all exposures in the weighted index have associations in the same direction with the outcome, which is not realistic when chemicals in different classes have different directions and magnitude of association with a health outcome. Grouped WQS (GWQS) was proposed to allow for multiple groups of chemicals in the model where different magnitude and direction of associations are possible for each group. However, GWQS shares the limitation of WQS of a two-step estimation process and splitting of data into training and validation sets. In this paper, we propose a Bayesian group index model to avoid the estimation limitation of GWQS while having multiple exposure indices in the model. To evaluate the performance of the Bayesian group index model, we conducted a simulation study with several different exposure scenarios. We also applied the Bayesian group index method to analyze childhood leukemia risk in the California Childhood Leukemia Study (CCLS). The results showed that the Bayesian group index model had slightly better power for exposure effects and specificity and sensitivity in identifying important chemical exposure components compared with the existing frequentist method, particularly for small sample sizes. In the application to the CCLS, we found a significant negative association for insecticides, with the most important chemical being carbaryl. In addition, for children who were born and raised in the home where dust samples were taken, there was a significant positive association for herbicides with dacthal being the most important exposure. In conclusion, our approach of the Bayesian group index model appears able to make a substantial contribution to the field of environmental epidemiology.

Abstract Background There is increasing interest in using chemicals measured in carpet dust as indicators of chemical exposures. However, investigators have rarely sampled dust repeatedly from the same households and therefore little is known about the variability of chemical levels that exist within and between households in dust samples. Results We analyzed 9 polycyclic aromatic hydrocarbons, 6 polychlorinated biphenyls, and nicotine in 68 carpet-dust samples from 21 households in agricultural communities of Fresno County, California collected from 2003-2005. Chemical concentrations (ng per g dust) ranged from < 2-3,609 for 9 polycyclic aromatic hydrocarbons, from < 1-150 for 6 polychlorinated biphenyls, and from < 20-7,776 for nicotine. We used random-effects models to estimate variance components for concentrations of each of these carpet-dust chemicals and calculated the variance ratio, λ, defined as the ratio of the within-household variance component to the between-household variance component. Subsequently, we used the variance ratios calculated from our data, to illustrate the potential effect of measurement error on the attenuation of odds ratios in hypothetical case-control studies. We found that the median value of the estimated variance ratios was 0.33 (range: 0.13-0.72). Correspondingly, in case-control studies of associations between these carpet-dust chemicals and disease, given the collection of only one measurement per household and a hypothetical odds ratio of 1.5, we expect that the observed odds ratios would range from 1.27 to 1.43. Moreover, for each of the chemicals analyzed, the collection of three repeated dust samples would limit the expected magnitude of odds ratio attenuation to less than 20%. Conclusions Our findings suggest that attenuation bias should be relatively modest when using these semi-volatile carpet-dust chemicals as exposure surrogates in epidemiologic studies.

Individuals are exposed to a large number of diverse environmental chemicals simultaneously and the evaluation of multiple chemical exposures is important for identifying cancer risk factors. The measurement of a large number of chemicals (the exposome) in epidemiologic studies is allowing for a more comprehensive assessment of cancer risk factors than was done in earlier studies that focused on only a few chemicals. Empirical evidence from epidemiologic studies shows that chemicals from different chemical classes have different magnitudes and directions of association with cancers. Given increasing data availability, there is a need for the development and assessment of statistical methods to model environmental cancer risk that considers a large number of diverse chemicals with different effects for different chemical classes. The method of grouped weighted quantile sum (GWQS) regression allows for multiple groups of chemicals to be considered in the model such that different magnitudes and directions of associations are possible for each group of chemicals. In this paper, we assessed the ability of GWQS regression to estimate exposure effects for multiple chemical groups and correctly identify important chemicals in each group using a simulation study. We compared the performance of GWQS regression with WQS regression, the least absolute shrinkage and selection operator (lasso), and the group lasso in estimating exposure effects and identifying important chemicals. The simulation study results demonstrate that GWQS is an effective method for modeling exposure to multiple groups of chemicals and compares favorably with other methods used in mixture analysis. As an application, we used GWQS regression in the California Childhood Leukemia Study (CCLS), a population-based case-control study of childhood leukemia in California to estimate exposure effects for many chemical classes while also adjusting for demographic factors. The CCLS analysis found evidence of a positive association between exposure to the herbicide dacthal and an increased risk of childhood leukemia.

Background

Self-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.

Objective

We 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).

Methods

We 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.

Results

Permethrin, 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.

Conclusion

Our 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.

Background

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.

Methods

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.

Results

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.

Conclusions

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.

Active ingredients in residential and agricultural insecticides have changed over time, due in part to regulatory restrictions. Few studies have evaluated how changes in active ingredients have impacted insecticide levels measured in homes. We measured concentrations of insecticides in one carpet-dust sample from each of 434 homes in California from 2001 to 2006. Analytes included four insecticides sold for indoor home use during our study period (carbaryl, cypermethrin, permethrin, and propoxur) and four that are no longer sold for indoor use including dichlorodiphenyltrichloroethylene (DDT, removed from the market in 1972), chlordane (1988), chlorpyrifos (2001), and diazinon (2004). We considered other potential determinants of concentrations of insecticides in carpet dust, such as home and garden use, occupational exposure, and nearby agricultural applications. We calculated the percentage change in the concentration of each insecticide per year, adjusting for significant determinants. In adjusted models, concentrations of insecticides in carpet dust decreased for three of four insecticides no longer sold for residential use: chlordane (-15% per year), chlorpyrifos (-31%), diazinon (-48%), and propoxur (-34%), which is currently sold for residential use but with increased restrictions since 1997. Concentrations of other insecticides sold for indoor use (carbaryl, cypermethrin, and permethrin) and DDT did not change over time in our study population.

We evaluated the relationship between the risk of childhood acute lymphoblastic leukemia (ALL) and the levels of metals in carpet dust. A dust sample was collected from the homes of 142 ALL cases and 187 controls participating in the California Childhood Leukemia Study using a high volume small surface sampler (2001-2006). Samples were analyzed using microwave-assisted acid digestion in combination with inductively coupled plasma mass spectrometry for arsenic, cadmium, chromium, copper, lead, nickel, tin, tungsten, and zinc. Eight metals were detected in at least 85% of the case and control homes; tungsten was detected in <15% of homes. Relationships between dust metal loadings (μg metal per m(2) carpet) and ALL risk were modeled using multivariable logistic regression, adjusting for the child's age, sex, and race/ethnicity and confounders, including household annual income. A doubling of dust metal loadings was not associated with significant changes in ALL risk (odds ratio (95% confidence interval): arsenic: 0.96 (0.86, 1.07), cadmium: 0.92 (0.81, 1.05), chromium: 1.01 (0.90, 1.14), copper: 0.97 (0.91, 1.03), lead: 1.01 (0.93, 1.10), nickel: 0.95 (0.82, 1.09), tin: 0.96 (0.86, 1.08), and zinc: 0.94 (0.84, 1.05)). Our findings do not support the hypothesis that metals in carpet dust are risk factors for childhood ALL.

Background

Recent meta-analyses demonstrate an association between self-reported residential pesticide use and childhood leukemia risk. Self-reports may suffer from recall bias and provide information only on broad pesticide categories. We compared parental self-reported home and garden pest treatments to pesticides measured in carpet dust.

Methods

Parents of 277 children with leukemia and 306 controls in Northern and Central California (2001-2007) were asked about insect and weed treatments during the previous year. Carpet dust samples were analyzed for 47 pesticides. We present results for the 7 insecticides (carbaryl, propoxur, chlorpyrifos, diazinon, cyfluthrin, cypermethrin, permethrin), 5 herbicides (2,4-dichlorophenoxyacetic acid [2,4-D], chlorthal, dicamba, mecoprop, simazine), and 1 synergist (piperonyl butoxide) that were present in home and garden products during the study period and were detected in ≥25% of carpet dust samples. We constructed linear regression models for the relative change in pesticide concentrations associated with self-reported treatment of pest types in cases and controls separately and combined, adjusting for demographics, housing characteristics, and nearby agricultural pesticide applications.

Results

Several self-reported treatments were associated with pesticide concentrations in dust. For example, households with flea/tick treatments had 2.3 (95% Confidence Interval [CI]: 1.4, 3.7) times higher permethrin concentrations than households not reporting this treatment. Households reporting treatment for ants/cockroaches had 2.5 (95% CI: 1.5, 4.2) times higher cypermethrin levels than households not reporting this treatment. Weed treatment by a household member was associated with 1.9 (1.4, 2.6), 2.2 (1.6, 3.1), and 2.8 (2.1, 3.7) times higher dust concentrations of dicamba, mecoprop, and 2,4-D, respectively. Weed treatments by professional applicators were null/inversely associated with herbicide concentrations in dust. Associations were generally similar between cases and controls and were consistent with pesticide active ingredients in these products during the study time period.

Conclusions

Consistency between self-reported pest treatments, concentrations in dust, and pesticides in products lends credibility to the exposure assessment methods and suggests that differential recall by case-control status is minimal.

Background

Dioxins are persistent organic pollutants generated from industrial combustion processes such as waste incineration. To date, results from epidemiologic studies of dioxin exposure and breast cancer risk have been mixed.

Objectives

To prospectively examine the association between ambient dioxin exposure using a nationwide spatial database of industrial dioxin-emitting facilities and invasive breast cancer risk in the Nurses' Health Study II (NHSII).

Methods

NHSII includes female registered nurses in the US who have completed self-administered biennial questionnaires since 1989. Incident invasive breast cancer diagnoses were self-reported and confirmed by medical record review. Dioxin exposure was estimated based on residential proximity, duration of residence, and emissions from facilities located within 3, 5, and 10 km around geocoded residential addresses updated throughout follow-up. Cox regression models adjusted for breast cancer risk factors were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs).

Results

From 1989 to 2013, 3840 invasive breast cancer cases occurred among 112,397 participants. There was no association between residential proximity to any dioxin facilities (all facilities combined) and breast cancer risk overall. However, women who resided within 10 km of any municipal solid waste incinerator (MSWI) compared to none had increased breast cancer risk (adjusted HR = 1.15, 95% CI: 1.03, 1.28), with stronger associations noted for women who lived within 5 km (adjusted HR = 1.25, 95% CI: 1.04, 1.52). Positive associations were also observed for longer duration of residence and higher dioxin emissions from MSWIs within 3, 5, and 10 km. There were no clear differences in patterns of association for ER + vs. ER-breast cancer or by menopausal status.

Discussion

Results from this study support positive associations between dioxin exposure from MSWIs and invasive breast cancer risk.

Objective

This study describes associations of ozone and fine particulate matter with Parkinson's disease observed among farmers in North Carolina and Iowa.

Methods

We used logistic regression to determine the associations of these pollutants with self-reported, doctor-diagnosed Parkinson's disease. Daily predicted pollutant concentrations were used to derive surrogates of long-term exposure and link them to study participants' geocoded addresses.

Results

We observed positive associations of Parkinson's disease with ozone (odds ratio = 1.39; 95% CI: 0.98 to 1.98) and fine particulate matter (odds ratio = 1.34; 95% CI: 0.93 to 1.93) in North Carolina but not in Iowa.

Conclusions

The plausibility of an effect of ambient concentrations of these pollutants on Parkinson's disease risk is supported by experimental data demonstrating damage to dopaminergic neurons at relevant concentrations. Additional studies are needed to address uncertainties related to confounding and to examine temporal aspects of the associations we observed.