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An algorithm for quantitatively estimating non-occupational pesticide exposure intensity for spouses in the Agricultural Health Study.

ABSTRACT: Residents of agricultural areas experience pesticide exposures from sources other than direct agricultural work. We developed a quantitative, active ingredient-specific algorithm for cumulative (adult, married lifetime) non-occupational pesticide exposure intensity for spouses of farmers who applied pesticides in the Agricultural Health Study (AHS). The algorithm addressed three exposure pathways: take-home, agricultural drift, and residential pesticide use. Pathway-specific equations combined (i) weights derived from previous meta-analyses of published pesticide exposure data and (ii) information from the questionnaire on frequency and duration of pesticide use by applicators, home proximity to treated fields, residential pesticide usage (e.g., termite treatments), and spouse's off-farm employment (proxy for time at home). The residential use equation also incorporated a published probability matrix that documented the likelihood active ingredients were used in home pest treatment products. We illustrate use of these equations by calculating exposure intensities for the insecticide chlorpyrifos and herbicide atrazine for 19,959 spouses. Non-zero estimates for ?1 pathway were found for 78% and 77% of spouses for chlorpyrifos and atrazine, respectively. Variability in exposed spouses' intensity estimates was observed for both pesticides, with 75th to 25th percentile ratios ranging from 7.1 to 7.3 for take-home, 6.5 to 8.5 for drift, 2.4 to 2.8 for residential use, and 3.8 to 7.0 for the summed pathways. Take-home and drift estimates were highly correlated (?0.98), but were not correlated with residential use (0.01?0.02). This algorithm represents an important advancement in quantifying non-occupational pesticide relative exposure differences and will facilitate improved etiologic analyses in the AHS spouses. The algorithm could be adapted to studies with similar information.

SUBMITTER: Deziel NC

PROVIDER: S-EPMC6470005 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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An algorithm for quantitatively estimating non-occupational pesticide exposure intensity for spouses in the Agricultural Health Study.

Deziel Nicole C NC Beane Freeman Laura E LE Hoppin Jane A JA Thomas Kent K Lerro Catherine C CC Jones Rena R RR Hines Cynthia J CJ Blair Aaron A Graubard Barry I BI Lubin Jay H JH Sandler Dale P DP Chen Honglei H Andreotti Gabriella G Alavanja Michael C MC Friesen Melissa C MC

Journal of exposure science & environmental epidemiology 20181030 3

Residents of agricultural areas experience pesticide exposures from sources other than direct agricultural work. We developed a quantitative, active ingredient-specific algorithm for cumulative (adult, married lifetime) non-occupational pesticide exposure intensity for spouses of farmers who applied pesticides in the Agricultural Health Study (AHS). The algorithm addressed three exposure pathways: take-home, agricultural drift, and residential pesticide use. Pathway-specific equations combined ( ...[more]

PMID: 30375516

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Project description:The accuracy of the exposure assessment is a critical factor in epidemiological investigations of pesticide exposures and health in agricultural populations. However, few studies have been conducted to evaluate questionnaire-based exposure metrics. The Agricultural Health Study (AHS) is a prospective cohort study of pesticide applicators who provided detailed questionnaire information on their use of specific pesticides. A field study was conducted for a subset of the applicators enrolled in the AHS to assess a pesticide exposure algorithm through comparison of algorithm intensity scores with measured exposures. Pre- and post-application urinary biomarker measurements were made for 2,4-D (n=69) and chlorpyrifos (n=17) applicators. Dermal patch, hand wipe, and personal air samples were also collected. Intensity scores were calculated using information from technician observations and an interviewer-administered questionnaire. Correlations between observer and questionnaire intensity scores were high (Spearman's r=0.92 and 0.84 for 2,4-D and chlorpyrifos, respectively). Intensity scores from questionnaires for individual applications were significantly correlated with post-application urinary concentrations for both 2,4-D (r=0.42, P<0.001) and chlorpyrifos (r=0.53, P=0.035) applicators. Significant correlations were also found between intensity scores and estimated hand loading, estimated body loading, and air concentrations for 2,4-D applicators (r-values 0.28-0.50, P-values<0.025). Correlations between intensity scores and dermal and air measures were generally lower for chlorpyrifos applicators using granular products. A linear regression model indicated that the algorithm factors for individual applications explained 24% of the variability in post-application urinary 2,4-D concentration, which increased to 60% when the pre-application urine concentration was included. The results of the measurements support the use of the algorithm for estimating questionnaire-based exposure intensities in the AHS for liquid pesticide products. Refinement of the algorithm may be possible using the results from this and other measurement studies.

Project description:The relationship between pesticide exposures and metabolomics biomarkers is not well understood. We examined the changes in the serum metabolome (early biomarkers) and the metabolic pathways associated with various pesticide exposure scenarios (OPE: overall exposure, PEM: exposure in months, PEY: exposure in years, and PEU: reported specific pesticides use) using data from the Northern Finland Birth Cohort 1966 31-year cross-sectional examination. We utilized questionnaire data on pesticide exposures and serum samples for nuclear magnetic resonance (NMR)-based metabolomics analyses. For exposures and metabolites associations, participants size varied between 2,361 and 5,035. To investigate associations between metabolomics biomarkers and exposure to pesticide scenarios compared to those who reported no exposures multivariable regression analyses stratified by sex and adjustment with covariates (season of pesticide use, socioeconomic position (SEP), alcohol consumption, BMI, and latitude of residence) were performed. Multiple testing by Benjamini-Hochberg false discovery rate (FDR) correction applied. Pesticide exposures differed by sex, season of pesticide use, alcohol, SEP, latitude of residence. Our results showed that all pesticide exposure scenarios were negatively associated with decreased HDL concentrations across all lipoprotein subclasses in women. OPE, PEY, and PEU were associated with decreased branched-chain amino acid concentrations in men and decreased albumin concentrations in women. OPE, PEY and PEU were also associated with changes in glycolysis metabolites and ketone bodies in both sexes. Specific pesticides exposure was negatively associated with sphingolipids and inflammatory biomarkers in men. In women, OPE, PEM, and PEU were associated with decreased apolipoprotein A1 and increased apolipoprotein B/apolipoprotein A1 ratio. Our findings suggest that identification of early biomarkers of disease risk related to pesticide exposures can inform strategies to reduce exposure and investigate causal pathways. Women may be more susceptible to non-occupational pesticide exposures when compared to men, and future sex-specific studies are warranted.

Project description:Intensive pesticide use increased concern about the potential acute and chronic health effects of pesticides in general and among applicators in particular. This study aims to explore occupational and environmental pesticide exposure and health risks among pesticide applicators and residents. A community-based cross-sectional study was conducted involving 1,073 individuals. We examined the health effects potentially attributable to pesticide exposure using regression to estimate prevalence ratios (PR). A higher proportion of good knowledge of pesticides [75 vs. 14%; APR = 1.542 (1.358-1.752), p < 0.001] and a higher mean score of perceived health risk of pesticide use [4.21 vs. 3.90; APR = 1.079 (1.004-1.159), p < 0.05] were observed among applicators than residents. A significantly higher proportion of applicators experienced health effects presumably related to pesticide exposure among themselves (36%) than residents (16%), and a higher proportion of them used prescribed drugs in the past 12 months [51 vs. 32%; APR = 1.140 (1.003-1.295), p < 0.05]. Skin irritation, shortness of breath, cough, and dizziness were more likely reported by applicators than residents. Perceived toxicity of currently applied pesticide products, mix pesticides without gloves, regularly maintain and wash sprayer tank after application, occurrence of an incidental splash during mixing and application, and using home-based care after experiencing a symptom presumably due to pesticide exposure were significantly associated with health effects among applicators. Use of face mask and visiting health facility when experiencing a symptom presumably due to pesticide exposure were significantly positively correlated with attending training on the health risks and use of pesticides. A substantial proportion of applicators reported improper use of preventive measures and methods of pesticide waste disposal. These observations point out that applicators can face high health risks of occupational pesticide exposure in Ethiopia. Even trained applicators pursued poor preventive practices; hence, comprehensive practice-oriented in-depth training focusing on safety precautions and proper use of personal protective equipment, and provision of adequate pesticide waste disposal means are crucial interventions.

Dataset Information

An algorithm for quantitatively estimating non-occupational pesticide exposure intensity for spouses in the Agricultural Health Study.

Publications

An algorithm for quantitatively estimating non-occupational pesticide exposure intensity for spouses in the Agricultural Health Study.

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