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一种用于评估农业生物标志物暴露与效应研究中农民职业性(1→3)-β-D-葡聚糖暴露的特定任务算法。

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.

机构信息

Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.

Department of Environmental Health Sciences, Yale School of Public Health, Yale University, New Haven, CT, USA.

出版信息

Ann Work Expo Health. 2022 Oct 11;66(8):974-984. doi: 10.1093/annweh/wxac041.

Abstract

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.

摘要

目的

农民可能通过各种任务接触到葡聚糖(霉菌细胞的一种成分)。暴露的程度取决于每个农民的活动及其持续时间。我们开发了一种特定于任务的算法,该算法将(1→3)-β-D-葡聚糖的测量值与生物标志物暴露和农业影响(BEEA)研究中农民的问卷调查结果相结合,以估算葡聚糖的暴露量。

方法

为了开发该算法,我们首先使用先前空气监测研究中 32 名 BEEA 农民的可吸入个人空气采样数据,为农业任务推导基于任务的葡聚糖暴露几何平均值(GM)。接下来,将这些特定于任务的 GMs 乘以主题报告的三个时间窗口(过去 30 天、过去 7 天和过去 1 天)的活动频率,以获得针对主题、任务和时间窗口的葡聚糖分数。将这些分数加在一起,为每个主题和时间窗口获得总葡聚糖分数。我们检查了不同时间框架下的葡聚糖分数的任务内和任务间相关性。此外,我们还使用来自前一天参与空气监测的 32 名农民的全日浓度,使用多层次统计模型评估了针对“过去 1 天”时间窗口的算法,将测量的葡聚糖浓度与算法葡聚糖分数进行了比较。

结果

我们专注于五种暴露最高的任务:家禽饲养(300ng/m3)、猪饲养(300ng/m3)、清洁谷仓(200ng/m3)、磨碎饲料(100ng/m3)和储存种子或谷物(50ng/m3);其余任务的浓度均<50ng/m3,且彼此相似。总体而言,67%的参与者报告了至少一项此类任务。最常见的任务是储存种子或谷物(64%)。最高的中位数葡聚糖分数出现在家禽饲养和猪饲养中;这两个任务分别被 2%和 8%的参与者报告。对于同一任务但不同时间窗口的分数,猪饲养和家禽饲养的相关性较高,而清洁谷仓的相关性较低。特定任务的分数与其他任务的相关性较低。前一天的葡聚糖浓度与“过去 1 天”的总葡聚糖分数以及猪饲养和清洁谷仓任务的分数相关。

结论

本研究深入了解了美国农民群体中葡聚糖暴露的可变性和主要来源。它还为在流行病学研究中更好地评估葡聚糖暴露提供了框架,并且是评估该人群中葡聚糖相关健康风险的未来流行病学评估的重要起点。

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