An algorithm for quantitatively estimating occupational endotoxin exposure in the Biomarkers of Exposure and Effect in Agriculture (BEEA) study: I. Development of task-specific exposure levels from published data

BACKGROUND/OBJECTIVE

Farmers conduct numerous tasks with potential for endotoxin exposure. As a first step to characterize endotoxin exposure for farmers in the Biomarkers of Exposure and Effect in Agriculture (BEEA) Study, we used published data to estimate task-specific endotoxin concentrations.

METHODS

We extracted published data on task-specific, personal, inhalable endotoxin concentrations for agricultural tasks queried in the study questionnaire. The data, usually abstracted as summary measures, were evaluated using meta-regression models that weighted each geometric mean (GM, natural-log transformed) by the inverse of its within-study variance to obtain task-specific predicted GMs.

RESULTS

We extracted 90 endotoxin summary statistics from 26 studies for 9 animal-related tasks, 30 summary statistics from 6 studies for 3 crop-related tasks, and 10 summary statistics from 5 studies for 4 stored grain-related tasks. Work in poultry and swine confinement facilities, grinding feed, veterinarian services, and cleaning grain bins had predicted GMs > 1000 EU/m3 . In contrast, harvesting or hauling grain and other crop-related tasks had predicted GMs below 100 EU/m3 .

SIGNIFICANCE

These task-specific endotoxin GMs demonstrated exposure variability across common agricultural tasks. These estimates will be used in conjunction with questionnaire responses on task duration to quantitatively estimate endotoxin exposure for study participants, described in a companion paper.

An algorithm for quantitatively estimating occupational endotoxin exposure in the biomarkers of exposure and effect in agriculture study: II. Application to the study population

BACKGROUND

We developed an algorithm to quantitatively estimate endotoxin exposure for farmers in the Biomarkers of Exposure and Effect in Agriculture (BEEA) Study.

METHODS

The algorithm combined task intensity estimates derived from published data with questionnaire responses on activity duration to estimate task-specific cumulative endotoxin exposures for 13 tasks during four time windows, ranging from "past 12 months" to "yesterday/today." We applied the algorithm to 1681 participants in Iowa and North Carolina. We examined correlations in endotoxin metrics within- and between-task. We also compared these metrics to prior day full-shift inhalable endotoxin concentrations from 32 farmers.

RESULTS

The highest median task-specific cumulative exposures were observed for swine confinement, poultry confinement, and grind feed. Inter-quartile ranges showed substantial between-subject variability for most tasks. Time window-specific metrics of the same task were moderately-highly correlated. Between-task correlation was variable, with moderately-high correlations observed for similar tasks (e.g., between animal-related tasks). Prior day endotoxin concentration increased with the total metric and with task metrics for swine confinement, clean other animal facilities, and clean grain bins.

SIGNIFICANCE

This study provides insight into the variability and sources of endotoxin exposure among farmers in the BEEA study and summarizes exposure estimates for future investigations in this population.

A Task-Specific Algorithm to Estimate Occupational (1→3)-β-D-glucan Exposure for Farmers in the Biomarkers of Exposure and Effect in Agriculture Study

OBJECTIVES

Farmers may be exposed to glucans (a cell component of molds) through a variety of tasks. The magnitude of exposure depends on each farmer's activities and their duration. We developed a task-specific algorithm to estimate glucan exposure that combines measurements of (1→3)-β-D-glucan with questionnaire responses from farmers in the Biomarkers of Exposure and Effect in Agriculture (BEEA) study.

METHODS

To develop the algorithm, we first derived task-based geometric means (GMs) of glucan exposure for farming tasks using inhalable personal air sampling data from a prior air monitoring study in a subset of 32 BEEA farmers. Next, these task-specific GMs were multiplied by subject-reported activity frequencies for three time windows (the past 30 days, past 7 days, and past 1 day) to obtain subject-, task-, and time window-specific glucan scores. These were summed together to obtain a total glucan score for each subject and time window. We examined the within- and between-task correlation in glucan scores for different time frames. Additionally, we assessed the algorithm for the 'past 1 day' time window using full-shift concentrations from the 32 farmers who participated in air monitoring the day prior to an interview using multilevel statistical models to compare the measured glucan concentration with algorithm glucan scores.

RESULTS

We focused on the five highest exposed tasks: poultry confinement (300 ng/m3), swine confinement (300 ng/m3), clean grain bins (200 ng/m3), grind feed (100 ng/m3), and stored seed or grain (50 ng/m3); the remaining tasks were <50 ng/m3 and had similar concentrations to each other. Overall, 67% of the participants reported at least one of these tasks. The most prevalent task was stored seed or grain (64%). The highest median glucan scores were observed for poultry confinement and swine confinement; these tasks were reported by 2% and 8% of the participants, respectively. The correlation between scores for the same task but different time windows was high for swine confinement and poultry confinement, but low for clean grain bins. Task-specific scores had low correlation with other tasks. Prior day glucan concentration was associated with the total glucan 'past 1 day' score and with swine confinement and clean grain bin task scores.

CONCLUSIONS

This study provides insight into the variability and key sources of glucan exposure in a US farming population. It also provides a framework for better glucan exposure assessment in epidemiologic studies and is a crucial starting point for evaluating health risks associated with glucans in future epidemiologic evaluations of this population.

The association of self-reported respiratory system diseases with farming activity among farmers of greenhouse vegetables

Objectives

Several studies have investigated the link between agricultural activities of open-field farmers and the prevalence of respiratory diseases, but the relationship with greenhouse vegetable farmers remains unclear.

Methods

A total of 1,366 participants from four villages in China provided information about their agricultural activities and symptoms of diagnosed respiratory system diseases. The Poisson regression model and zero-inflated Poisson regression model were used to assess the association between diseases, symptoms, and agricultural activities.

Results

The prevalence of respiratory diseases was 3.59%, and the rates of four main symptoms (cough, tachypnea, chest distress, and hemoptysis) were 17.21%, 8.56%, 10.25%, and 1.61%, respectively. Mix spray of pesticides associated with cough, tachypnea and chest distress, 1.740-, 3.385- and 2.882-fold likelihood were found than hand spray, and the significant association were detected in empty, general information, life-style information adjusted models.

Conclusions

The relationship between agricultural activities and respiratory diseases is unclear. However, use of the mix spray method of pesticide application may increase the risk of cough, tachypnea, and chest distress.