Observed vs. self-reported agricultural activities: Evaluating 24-hr recall in a pilot study

Occupational farm work activities influence workers' indoor home microbiome

BACKGROUND

Farm work entails a heterogeneous mixture of exposures that vary considerably across farms and farmers. Farm work is associated with various health outcomes, both adverse and beneficial. One mechanism by which farming exposures can impact health is through the microbiome, including the indoor home environment microbiome. It is unknown how individual occupational exposures shape the microbial composition in workers' homes.

OBJECTIVES

We investigated associations between farm work activities, including specific tasks and pesticide use, and the indoor microbiome in the homes of 468 male farmers.

METHODS

Participants were licensed pesticide applicators, mostly farmers, enrolled in the Agricultural Lung Health Study from 2008 to 2011. Vacuumed dust from participants' bedrooms underwent whole-genome shotgun sequencing for indoor microbiome assessment. Using questionnaire data, we evaluated 6 farm work tasks (processing of either hay, silage, animal feed, fertilizer, or soy/grains, and cleaning grain bins) and 19 pesticide ingredients currently used in the past year, plus 7 banned persistent pesticide ingredients ever used.

RESULTS

All 6 work tasks were associated with increased microbial diversity levels, with a positive dose-response for the total number of tasks performed (P = 0.001). All tasks were associated with altered microbial compositions (weighted UniFrac P = 0.001) and with higher abundance of specific microbes, including soil-based commensal microbes such as Haloterrigena. Among the 19 pesticides, current use of glyphosate and past use of lindane were associated with increased microbial diversity (P = 0.02-0.04). Ten currently used pesticides and all 7 banned pesticides were associated with altered microbial composition (P = 0.001-0.04). Six pesticides were associated with differential abundance of certain microbes.

DISCUSSION

Different farm activities and exposures can uniquely impact the dust microbiome inside homes. Our work suggests that changes to the home microbiome could serve as one pathway for how occupational exposures impact the health of workers and their cohabitating family members, offering possible future intervention targets.

Occupational Farm Work Activities Influence Workers' Indoor Home Microbiome

Background

Farm work entails a heterogeneous mixture of exposures that vary considerably across farms and farmers. Farm work is associated with various health outcomes, both adverse and beneficial. One mechanism by which farming exposures can impact health is through the microbiome, including the indoor built environment microbiome. It is unknown how individual occupational exposures shape the microbial composition in workers' homes.

Objectives

We investigated associations between farm work activities, including specific tasks and pesticide use, and the indoor microbiome in the homes of 468 male farmers.

Methods

Participants were licensed pesticide applicators, mostly farmers, enrolled in the Agricultural Lung Health Study from 2008-2011. Vacuumed dust from participants' bedrooms underwent whole-genome shotgun sequencing for indoor microbiome assessment. Using questionnaire data, we evaluated 6 farm work tasks (processing of either hay, silage, animal feed, fertilizer, or soy/grains, and cleaning grain bins) and 19 pesticide ingredients currently used in the past year, plus 7 persistent banned pesticide ingredients ever used.

Results

All 6 work tasks were associated with increased within-sample microbial diversity, with a positive dose-response for the sum of tasks (p=0.001). All tasks were associated with altered overall microbial compositions (weighted UniFrac p=0.001) and with higher abundance of specific microbes, including soil-based microbes such as Haloterrigena. Among the 19 pesticides, only current use of glyphosate and past use of lindane were associated with increased within-sample diversity (p=0.02-0.04). Ten currently used pesticides and all 7 banned pesticides were associated with altered microbial composition (p=0.001-0.04). Six pesticides were associated with differential abundance of certain microbes.

Discussion

Specific farm activities and exposures can impact the dust microbiome inside homes. Our work suggests that occupational farm exposures could impact the health of workers and their families through modifying the indoor environment, specifically the microbial composition of house dust, offering possible future intervention targets.

Using a smartphone application to capture daily work activities: a longitudinal pilot study in a farming population

OBJECTIVES

Smartphones are increasingly used to collect real-time information on time-varying exposures. We developed and deployed an application (app) to evaluate the feasibility of using smartphones to collect real-time information on intermittent agricultural activities and to characterize agricultural task variability in a longitudinal study of farmers.

METHODS

We recruited 19 male farmers, aged 50-60 years, to report their farming activities on 24 randomly selected days over 6 months using the Life in a Day app. Eligibility criteria include personal use of an iOS or Android smartphone and >4 h of farming activities at least two days per week. We developed a study-specific database of 350 farming tasks that were provided in the app; 152 were linked to questions that were asked when the activity ended. We report eligibility, study compliance, number of activities, duration of activities by day and task, and responses to the follow-up questions.

RESULTS

Of the 143 farmers we reached out to for this study, 16 were not reached by phone or refused to answer eligibility questions, 69 were ineligible (limited smartphone use and/or farming time), 58 met study criteria, and 19 agreed to participate. Refusals were mostly related to uneasiness with the app and/or time commitment (32 of 39). Participation declined gradually over time, with 11 farmers reporting activities through the 24-week study period. We obtained data on 279 days (median 554 min/day; median 18 days per farmer) and 1,321 activities (median 61 min/activity; median 3 activities per day per farmer). The activities were predominantly related to animals (36%), transportation (12%), and equipment (10%). Planting crops and yard work had the longest median durations; short-duration tasks included fueling trucks, collecting/storing eggs, and tree work. Time period-specific variability was observed; for example, crop-related activities were reported for an average of 204 min/day during planting but only 28 min/day during pre-planting and 110 min/day during the growing period. We obtained additional information for 485 (37%) activities; the most frequently asked questions were related to "feed animals" (231 activities) and "operate fuel-powered vehicle (transportation)" (120 activities).

CONCLUSIONS

Our study demonstrated feasibility and good compliance in collecting longitudinal activity data over 6 months using smartphones in a relatively homogeneous population of farmers. We captured most of the farming day and observed substantial heterogeneity in activities, highlighting the need for individual activity data when characterizing exposure in farmers. We also identified several areas for improvement. In addition, future evaluations should include more diverse populations.

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.