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Am J Ind Med. Author manuscript; available in PMC 2023 May 22.
Published in final edited form as:
Am J Ind Med. 2022 November ; 65(11): 898–912. doi:10.1002/ajim.23418.

Working hours, sleep, and fatigue in the agriculture, forestry,
and fishing sector: A scoping review
K. C. Elliott, MA, MPH1, Jennifer M. Lincoln, PhD, CSP1, Michael A. Flynn, MA2, Jeffrey L.
Levin, MD, MSPH, DrPH, FACOEM, FACP3, Mathew Smidt, PhD4, Jerry Dzugan, MS5, Athena
K. Ramos, PhD, MBA, MS, CPM6
1Office of Agriculture Safety and Health, Office of the Director, National Institute for Occupational

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Safety and Health (NIOSH), Cincinnati, Ohio, USA
2Division of Science Integration, NIOSH, Cincinnati, Ohio, USA
3Department of Occupational and Environmental Medicine, The University of Texas at Tyler

Health Science Center, Tyler, Texas, USA
4Southern Research Station, USDA Forest Service, Auburn, Alabama, USA
5Alaska Marine Safety Education Association, Sitka, Alaska, USA
6Department of Health Promotion, Center for Reducing Health Disparities, College of Public

Health, University of Nebraska Medical Center, Omaha, Nebraska, USA

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Abstract
Introduction: Agriculture, forestry, and fishing industry (AgFF) workers often work extremely
long hours during peak production seasons, resulting in sleep deprivation and fatigue. The
National Occupational Research Agenda has classified fatigue as a “significant safety issue” and
area of concern for many industry sectors, including AgFF. This review explores current research
and practice in AgFF and proposes next steps.
Methods: We conducted a scoping literature review to examine the extent and nature of research
in this area. Article inclusion criteria included peer-reviewed journal articles written in English;

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Correspondence: K. C. Elliott, MA, MPH, Office of Agriculture Safety and Health, National Institute for Occupational Safety and
Health (NIOSH), 4230 University Dr Suite 310, Anchorage, AK 99508, USA. [email protected].
AUTHOR CONTRIBUTIONS
K. C. Elliott and Jennifer Lincoln created the review criteria along with feedback from Laura Syron (in acknowledgments). Screening
and selection of texts were finalized by K. C. Elliott and Jennifer Lincoln, as well as an initial draft with feedback from Laura Syron
(in acknowledgments). Michael Flynn, Jeffrey Lavin, Mathew Smidt, Jerry Dugan, and Athena Ramos reviewed search results and
revised critically for important intellectual content. Subsequent revisions were completed by K. C. Elliott and Jennifer Lincoln and
then reviewed again by Michael Flynn, Jeffrey Lavin, Mathew Smidt, Jerry Dugan, and Athena Ramos.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
DISCLOSURE BY AJIM EDITOR OF RECORD
John Meyer declares that he has no conflict of interest in the review and publication decision regarding this article.
ETHICS APPROVAL AND INFORMED CONSENT
There was no ethics review and approval/or consent as this is a review of the literature.
DISCLAIMER
The findings and conclusions in this review are those of the author(s) and do not necessarily represent the views of the National
Institute for Occupational Safety and Health.

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published after 1989; covering AgFF workers in high-income countries; with data on working
hours/schedules and sleep related to safety and health.
Results: Limited research has addressed long hours and sleep deprivation among AgFF workers.
We identified 8350 articles for title and abstract review. Among those, 407 underwent full-text
review and 96 met all inclusion criteria (67% agriculture, 25% fishing/seafood processing, 8%
forestry). The literature provided some evidence fatigue contributes to fatalities, injuries, and
illnesses in AgFF. Older, new, young, foreign-born, and female workers, as well as those who
work in small organizations or longer hours (40+) may be at higher risk for fatigue-related injury
and illness. Few studies have developed or evaluated interventions to control risks.

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Discussion: Given that fatigue is a factor in injury and illness for this sector, future AgFF
surveillance and research should increase efforts to capture fatigue and sleep data, directly
investigate the role of long hours and nonstandard work schedules in the sector, and most
importantly, create practical interventions to manage fatigue.
Keywords
agriculture; aquaculture; commercial fishing; extended shift; fatigue; forestry; irregular schedules;
seafood processing; sleep; work hours

1|

INTRODUCTION

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The agriculture, forestry, and fishing (AgFF) industry sector has approximately 2.4 million
workers.1 Agriculture includes both crop and animal production, as well as animal products
such as milk and eggs. Forestry includes logging operations and businesses that grow trees
and gather forest products. Fishing includes a variety of commercial fishing operations
offshore and onshore. AgFF workers face serious safety and health challenges potentially
compounded by long hours, limited sleep, and fatigue. AgFF has the highest fatal injury
rate among all industry sectors, at 23.4 per 100,000 full-time equivalent workers (FTEs),
over six times higher than the all-worker rate of 3.5 per 100,000 FTEs.2 Likewise, AgFF
workers are at high risk for nonfatal injury and illness, with a rate of 5.3 per 100 FTEs,
compared to the all-worker rate of 2.8 per 100 FTEs.3 Furthermore, the nonfatal injury and
illness rate likely severely underestimates the true injury and illness burden in this sector,
due to limitations in reporting and methodology of surveying employers (e.g., exclusion of
self-employed workers, which constitute a significant portion of this workforce).4 At the
same time, most AgFF workers are specifically exempted from policies regulating maximum
hours per shift, overtime pay, minimum wage, child labor restrictions, as well as health and
safety enforcement.5–7

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Across the AgFF sector, long work hours and fatigue-related injury and illness have been
identified as topics of concern. In 2008, the National Occupational Research Agenda
(NORA) for AgFF stated fatigue was a “significant safety issue” and is a “cultural norm.”8
The current NORA for AgFF also described it as an area of concern and includes a priority
to explore risk factors for fatigue and to develop interventions.9 US agriculture workers
do work longer hours on average, but hours can vary by the type of commodity produced
and by season. The National Agricultural Workers Survey reported that in 2015–2016,

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agricultural crop production workers on average worked 38–54 h/week10; whereas, the
national average for all US workers was 34.5 h/week.11 In 2019, agriculture and related
industry full-time workers on average worked 47.6 h/week compared to 42.5 h/week for
nonagricultural workers, and 19.3% of agriculture workers reported 60 h or over per week
compared to 6.4% of nonagricultural workers.12
Studies have shown overtime, extended work shifts, and lack of sufficient sleep are known
risk factors for injury and illness.13 For example, workers who lack sufficient sleep are at
higher risk of vehicle crashes, obesity, psychological disorders, musculoskeletal disorders,
reproductive problems, diminished immune response, and chronic disease.14–17 Fatigue, as
a result of long hours and sleep deprivation, leads to decreases in cognitive performance
which may affect attention, executive function, reaction time, short-term memory, and other
factors.18–28

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The National Institute for Occupational Safety and Health (NIOSH) is dedicated to reducing
the health and safety risks associated with shift work, long work hours, and other sources
of fatigue. NIOSH has facilitated a variety of teams to identify research gaps/needs related
to working hours, sleep, and fatigue in industries across the US. This manuscript is part of
series of papers developed following the NIOSH Working Hours, Sleep and Fatigue Forum
on September 13–14, 2019.29 The objective of this scoping review was to identify available
occupational safety and health research related to extended working hours, sleep deprivation,
and fatigue-related injury and illness in the AgFF industry through a scoping literature
review. Moreover, this paper identifies key cross-industry issues and knowledge gaps and
suggests future research directions to identify effective fatigue-mitigation interventions
tailored to the AgFF industry.

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2|

METHODS

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As our goal for this review was to gather, describe, and categorize available research on
work hours, sleep, and fatigue specifically within the AgFF sector, we conducted a scoping
review informed by methodology described in Arksey and O’Malley, Peters et al., and
Munn et al.30–32 Scoping reviews, while often still rigorous and replicable, focus on a
broader topic rather than an individual research question (or questions).32 Likewise, scoping
reviews seek to characterize the available types of research data, describe/contextualize key
concepts and factors, and propose future research areas related to the topic; however, they
do not generally go on to assess strengths or weaknesses in the methodology of individual
articles as in a systematic review.31,32 Our scoping review process included the following
steps: (1) developing case definition and inclusion/exclusion criteria; (2) conducting an
initial pilot search to identify keywords and representative papers; (3) identifying relevant
studies through a title and abstract search; (4) selecting studies for a full-text review; (5)
recording relevant attributes of the papers; (6) collating, summarizing, and reporting results.
The research team was comprised of individuals familiar with the various aspects of the
agriculture, forestry, and fishing sector, epidemiology, and literature synthesis. The team
worked with Centers for Disease Control and Prevention librarians to finalize search terms
and selection of databases to search.

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2.1 |

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Case definition

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We first defined fatigue as a decrease in mental or physical ability as a result of irregular
schedules, extended work hours (8 or more hours worked in a shift), and/or sleep deprivation
(sleeping less than recommended33 sleep duration). Self-reported feelings of “fatigue,”
“tiredness,” “sleepiness,” and other related terms were included, as were studies in which
participants’ fatigue/sleepiness was quantifiably measured (e.g., Epworth Sleepiness Scale).
Studies that did not specify the source of fatigue (physical labor, sleep deprivation, work
schedule) were included in the review. Articles with discussions of fatigue in relation
to factors which did not result in longer hours or irregular schedules (vibration, noise,
pesticide, or chemical exposure, etc.) were excluded. While these factors are important areas
of study, our focus was specifically to look at the effects of work hours (extended, irregular,
early/late start) on fatigue and adverse outcomes. The search terms included: Sleep* OR
(“work” within five words of “shift*”) OR fatigue* OR exhaustion OR tired OR work
schedule OR (work* ADJ5 hour*) OR wakefulness OR rotating shift* OR (long* ADJ5
hour*). The AgFF industry included any industry subsector listed under North American
Industry Classification System (NAICS) code 11, as well as seafood processing (NAICS
3117) due to it occurring on fishing vessels. Our search terms included Fishery OR Fisheries
OR Fish processing OR fish processor* OR seafood processing OR seafood processor*
OR agriculture OR agricultural OR poultry production OR egg production OR commercial
fishing OR fishermen OR (fishers NOT (fishers ADJ2 test*) OR forestry OR logging OR
aquaculture OR mariculture OR crop production OR farming OR farmer* OR farm-hand*
OR farmhand* OR farm work* OR ranch*).

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Concurrently, seven databases were searched for publications during the years 1990–
2019: Medline, Embase, PsychInfo, CAB Abstracts (OVID), Scopus, Agricultural and
Environmental Science Collection (ProQuest), and Web of Science. All records were
then placed into EndNote X9 bibliographic management software34 and uploaded
into Covidence,35 an online systematic review management software. Duplicates were
automatically removed.
2.2 |

Inclusion/exclusion criteria

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Peer-reviewed papers, regardless of study design, were included. We did not include gray
literature such as presentations, unpublished reports, trade journal articles, or government
documents. Articles were written in English; published 1990–2019; covering AgFF workers
(NAICS 11) or Seafood Processors (NAICS 3117), from high-income countries as defined
by the World Bank36 which generally more closely resemble US industry practices; and
included data on working hours, schedules, sleep, and reported feelings of fatigue-related
terms, for example, “fatigue,” “tiredness,” “sleepiness,” or other related terms as they relate
to worker safety and health.
2.3 |

Analysis
Articles were reviewed by three study team members. After two recorded the same decision,
the article was put through to the next step or removed. If, however, the decision was not
the same, the third reviewer resolved the conflict. If the third reviewer could not resolve
the conflict, it was decided by consensus among the three reviewers. Full-text review
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of articles was completed in the same fashion. Relevant data were then extracted and
subsequently categorized by industry subsector, year, country, study design, key findings,
common themes, possible interventions, identified research gaps, and recommendations for
future research.

3|

RESULTS

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The initial search returned 9217 articles to which we added 66 articles from the pilot
review, plus one article from a search of the reference sections in our pilot review. This
yielded a total of 9284 articles. Using the Covidence application, 934 duplicates were
automatically removed, leaving 8350 articles for title and abstract review. Among those, 407
were determined to be relevant and underwent full-text review. After the full-text review,
only 96 met all inclusion criteria. The other 311 were rejected in accordance with the
exclusion criteria: 208 not pertaining to relevant exposure and outcomes, 70 incorrect worker
population, 17 not a peer-reviewed article, 9 duplicate, 3 unable to obtain copy of full text, 2
not in English, and 2 before 1990 (Figure 1).

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By industry, 64 articles referenced agriculture and none in aquaculture (67%), 22 referenced
fishing and 2 seafood processing (25%), and 8 in forestry (8%). By study design, there were
58 cross-sectional, 10 cohort, 10 qualitative, 6 literature reviews, 3 case control, 3 mixed
methods, 3 interventional, 2 editorials, and 1 theoretical (model). By country, 45 papers
featured workers in the United States, 45 were outside of the United States, and 6 were
multi-country or global in scope. Overall, the review confirms there has been little research
specifically on work hours, sleep, and fatigue in the AgFF sector compared to other sectors.
Most articles did not focus on sleep deprivation, work hours, or work schedules among
AgFF workers, but instead discussed fatigue in the context of a broader investigation of
occupational injury and illness. Twenty-two studies included quantitative data on work hours
and sleep in relation to injury and are included in Table 1; however, these studies relied on
self-report surveys and interviews and mainly focused on farm owners and farm households.
There were no studies in industries other than crop and livestock production agriculture.
While a few studies focused on younger farm workers37–39 and older owners/workers,40,41
only two of the studies focused on migrant/immigrant populations.39,42
3.1 |

Evidence of injury and illness

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The review did provide some quantitative evidence of long work hours, insufficient
sleep, and sleep disorders contributing to increased injury and illness in the AgFF sector
specifically, but not in all studies43 (see Table 1). For work hours, studies generally indicated
that with an increase in hours, injuries increased44–49; however, some studies showed a
decreased rate at higher hours.50,51 Four studies captured reports of insufficient sleep (less
than 8 h of sleep per night), and all found increased risk of injury37,39,51,52 or back pain.42
Of the three studies which measured sleepiness using the Epworth Sleepiness Scale, two
studies did not find a statistically significant risk of injury,53,54 and one study found a score
of >10 to be protective.43 For sleep disorder, studies found increased risk of injury for those
who reported symptoms of sleep apnea40,41,51,52,55 or used sleep medication51, but one
study found decreased risk for those who reported diagnosed sleep apnea.55

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In agriculture, long hours and fatigue were thought to be risk factors for injury
and illness.37,44,45,47–50,53,56–62 Sleep disorders63 and increased work hours,64,65 were
associated with depression. A survey of farmers in the United Kingdom found they believed
fatigue was the main factor in quad-bike (four-wheeler) loss-of-control incidents,56 and a
survey of farmers in the United States found “hurry, fatigue, and stress” to be the top reasons
for a work-related injury.66 Other effects of sleep loss/poor sleep in the agriculture industry
included decreased balance,67 weakened hand grip,68 and a weak relationship between
self-reported ill health and daytime sleepiness.69 Among loggers, self-reported near-miss
injury reports were more common among those also reporting a “high level” of fatigue.70
In a series of interviews with loggers in Idaho, respondents reported “production pressure,
fatigue, and inexperience as the most common factors contributing to logging injuries”
with “working long hours, long commutes, and few days off” as the most frequently stated
reasons for participants feeling fatigue.71 Reviews of fishing industry literature identified
only a few articles and proposed fatigue as a major factor in fishing vessel disasters,72,73
but much more research is needed to thoroughly understand the impact of fatigue on vessel
disasters and what can be done to mitigate it.74 Fishing industry75,76 studies also reported a
high prevalence of obesity which may be related to fatigue.

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3.2 |

Cross-cutting issues
We identified several issues across AgFF industries which may contribute to fatigue:
extended work hours and irregular schedules, economic and organizational factors, housing
and psychosocial factors, and co-occurring health disparities (older workers, new workers,
young workers, foreign-born workers, female workers, and workers in small operations).
Across all sectors, few studies developed or evaluated interventions to control risks, but
recommendations for possible interventions and future research were identified.

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3.3 |

Work hours/schedule

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The review confirmed workers in the AgFF sector often work long hours (sometimes up
to 16+ h per day) and experience fatigue, especially during peak harvest and production
seasons.48,75,77–85 Operations frequently run 24-h per day, and shift work is prevalent,
especially in forestry86 and seafood processing.77,78 The seasonal nature of AgFF work
can contribute to fatigue in various ways. Light and darkness can negatively affect workers
because they primarily work outside.86 Exposure to heat87 and cold stress may also increase
fatigue due to physiological energy expenditures, or start shifts earlier or later to avoid
extreme conditions. Harvests are frequently dependent on weather, which often results in
working longer hours when the weather is good or when there is impending bad weather.
Bell and Helmkamp found logging worker compensation claims in West Virginia (1995–
2001) steadily increased from January to September and then decreased for the rest of the
year, which the authors attribute to working longer hours in late summer to ensure sawmills
would be supplied through winter.89 However, Lilley et al. found while decreased sleep
during peak production times did not increase risk for injury, those who slept less than 5
h during nonpeak production times were at increased risk of injury (OR: 2.42, 95% CI:
1.04–5.59).52 Authors found working irregular schedules may contribute to injuries89 and
mental health disorders65 among fishermen.

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Organizational and economic factors

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Economic and time pressures related to seasonal peaks (e.g., planting, harvesting) may
result in shortcuts and working despite high levels of fatigue. Some articles noted that
workers in the AgFF sector are often paid by how quickly they work (piece-rate) and/or
the size of the harvest, leading to fast-paced work, long hours, and less sleep.90 Lizer
and Petrea found while increased hours among older farmers did not increase injury risk,
financial stress did.91 Increased hours working with animals also was a risk factor,45,46 but
studies did not specifically compare extended schedules (40+ h/week) to handling livestock.
Fishermen often work irregular and extremely long shifts during harvests.89 When stocks
are depleted, fishermen must travel further and log longer hours for harvests.92,93 Farmers
facing economic difficulty may understaff, diversify their business,94 and work at night,95
leading to increased hours, burnout, and depression. Farm workers may start at earlier times
to avoid the hottest part of the day, but this may lead interfere with natural circadian rhythms
leading to less sleep.96
3.5 |

Housing, family, and psychosocial factors

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AgFF workers often live where they work, or commute long distances to and from remote
worksites.71 Living and working in the same place means it is often hard to truly be
“off the clock” and disengage from work, especially for crewmembers at sea who cannot
“walk-off” the vessel to escape worksite stressors.77,93 At the same time, many workers
in the sector work weeks, even months away from family, which several studies reported
as a stressor.85,92,93,97 On family farms, owner/operators,51 their spouses, or their older
children may work an additional job off the farm, which was shown to increase risk of
injury.98,99 Children who work on farms may be more sleep-deprived than their nonfarm
peers.100 Women who live on farms may work especially long hours as they may work an
additional job off the farm, and help out on the farm, in addition to household/child-rearing
duties.101 Farm owner-operators’ and their spouses who worked longer hours were more
likely to say their children were involved in activities/tasks which are known causes of
farm injury.80 Fishermen and offshore seafood processors sleep aboard vessels and may be
bothered by vibration, noises, and constant moving of the working platform.76 Likewise,
agricultural workers and onshore seafood processors often live onsite, and congregate
housing conditions can contribute to poor sleep and fatigue, especially with poor or cramped
housing conditions.75–77,90,102,103 However, one study found fishermen working 6-h shifts
for up to 3 months did not show signs of increased physiological stress via cortisol, blood
pressure, and blood lipids, but attributed the findings to “regular working hours, regular
healthy meals, predictable tasks, and social well-being on board, as well as healthy worker
affect.”104

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3.6 |

Co-occurring health disparities
Among AgFF workers, there are disparities related to work hours, sleep, and fatigue among
older workers,75,105–108 younger workers,37,39,98,100 new workers,71,86 and foreign-born
workers96,102,108,109 putting these populations at higher risk for fatigue related injury and
illness. Lizer and Petrea found older farmers worked longer hours than expected compared
to those age 55+ in other occupations, especially during the spring and fall seasons,

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averaging 10–12h days,105 but longer work hours were not associated with increased injury
in the same sample.91 However, in other studies, decreased sleep duration111 and “restless”
sleep41 in older farmers was associated with increased risk of injury. For adolescent
agricultural workers, lack of sleep39 and holding multiple jobs98 had increased rates
of injury. Psychosocial problems such as stress, anxiety, depression,63,65,112 and family
separation84,96 for extended periods also play a part in sleep deprivation and fatigue, with
these potentially being more prevalent among foreign-born workers.97,109 One study of
migrant workers found 45% experienced elevated depressive symptoms and 20% excessive
sleepiness.109 Migrant farm workers with extended shifts had significantly more hand
problems,64 and those who slept less than 8 h were at increased risk of chronic back pain.42
Female workers reported more daytime sleepiness than men in one study.109
3.7 |

Interventions

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For the logging industry, multiple studies showed a reduction in productivity for both
extended shifts and second/third shifts,86,113 which resulted in some companies eliminating
extended shifts as an economic measure, but not for safety reasons.86 However, during
night shifts, logging companies increased lighting and purchased two-way radios in an
effort to increase visibility and communication after dark.86 Another logging industry study
evaluating caffeine intake and comparing shift work found caffeine consumption can reduce
risks but had “little benefit for a night of no sleep after a buildup of severe sleep debt”.114
Another study found access to air-conditioning was a key factor in better sleep quality
when looking at housing quality of Latino farmworkers.103 A study of attitudes and beliefs
among Vietnamese shrimp fishermen in the Gulf of Mexico demonstrated fatigue was a
perceived risk factor and risk perceptions could be altered by knowledge and awareness of
interventions influencing intent to change behavior.115

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The two studies in this review that evaluated the effectiveness of fatigue interventions
showed mixed results. Bowen et al. hoped to use real-time monitoring technology to
measure fatigue in the logging industry, but found, “it may not be possible to identify
correlations between workloads and fatigue measures using in-situ measurements as results
are highly personalized to individual workers and can be misleading if the wider context is
not also taken into consideration.”116 On the other hand, Levin et al. found “[s]imple, yet
culturally appropriate training and awareness measures in the form of visual and written
safety messages favorably influence attitudes, beliefs, and behavioral intent related to
priority risk factors.”115 These safety messages included a fatigue awareness message as
fatigue was a primary concern of one study subgroup.115

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3.8 |

Research gaps and possible interventions
In all industries, the lack of both data and existing interventions for fatigue were mentioned,
with a consensus that workers were aware of the hazards and realize the risks, but both
the nature of the work and the organizational culture of AgFF industries are barriers to
fatigue mitigation.117,118 Studies also mentioned a need for quality surveillance data to
better understand the potential adverse outcomes of extended hours,57,89 irregular schedules,
sleep disorder/deprivation119 on injury and illness specifically in AgFF. Screening for
sleep disorders to improve sleep quality was mentioned.63,75 Further exploration of the

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relationship between sleep and injury and illness specifically for this sector was a suggested
topic of future research.63,120–123 Suggestions for future research also focused on targeting
interventions,49,124 the effect of mood disorders on fatigue and injury,125 exploring the
relationship of policies and regulations,126 and testing a causal link between vessel disasters
and fatigue.74
Studies stressed interventions must address the effects of long hours and fatigue, not
necessarily create prescriptive rules in an effort to prevent it.90,117,127,128 Suggested
interventions included focusing training on near misses,129 scheduling targeted fatigue
and safety training,66 especially before or outside of busy times of the year,56 promoting
awareness of problematic social norms which encourage longer hours and fatigue,94
adopting best practices from other industries,81 and using a community-based approach.118

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4|

DISCUSSION

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Although long work hours, irregular schedules, and fatigue contribute to fatalities, injuries,
and illnesses in the AgFF sector, little research has (1) quantified the extent to which they
are contributing factors, especially on workers’ health over their life course, (2) developed
interventions for hazard mitigation, or (3) evaluated existing interventions and programs.
Most studies published on the AgFF sector focus on describing or measuring factors which
may lead to fatigue, rather than developing and evaluating interventions. However, there is
at least one research project on the effects of sleep deprivation in US fishermen currently
underway (J. Sorensen, personal communication, August 13, 2020). Also, some government
agencies have created educational materials for industry and workers addressing this,123,130
but there are no evaluations of their effectiveness. As fatigue is a major factor in injury and
illness for this sector, future AgFF surveillance and research efforts should expand efforts
to capture fatigue and sleep data, better understand fatigue in unique AgFF workspaces, and
most importantly, create practical interventions to manage fatigue.

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At the same time, there are significant challenges to collecting data on fatigue in the AgFF
sector, such as logistical problems involving the rural and often remote nature of AgFF
work, difficulty in how fatigue is conceptualized, measured, and recorded,131 as well as
partnering with small businesses and part-time/seasonal employees. Due to regulatory and
organizational barriers, reliable employment numbers, hours worked, and even injury and
illness data in this sector are more difficult to obtain.132 One possible solution could be
adding questions on sleep habits and work schedules to existing and future surveys of
worker demographics and employment, such as the USDA’s National Agricultural Statistics
Service (NASS) surveys and the DOL National Agricultural Workers’ Survey (NAWS).
Incident, injury, and near-miss reports should clearly and specifically ask questions about
hours worked, time of day, feelings of fatigue, hours of sleep, and related information
to better document the role of fatigue as a risk factor for injury in this sector. Likewise,
commute times to and from workplaces should be documented and factored into hours
worked, even though they are often unpaid.
Future research must also address the unique nature of work in AgFF, workers’ economic
and psychosocial stressors (e.g., substandard housing, extended family separation), as well

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as the pervasive attitude that working long hours or with fatigue is to be expected, even
valued or rewarded. Regulatory and employer policies which incentivize working extended
shifts should also be examined specifically in the unique regulatory context of the AgFF
sector, but could draw on existing research54 and best practices133 from other occupations
such as commercial truck drivers and nurses. Much of the manual labor and high-risk
tasks in AgFF are performed by immigrant and foreign-born workers,134 who have known
health disparities and risk factors135 which put them at higher risk of injury and illness
due to fatigue; and therefore, this underserved population is in particular need of study.
Likewise, the average age of the AgFF workforce is increasing, and research on the impact
fatigue may have on older workers is needed—especially interventions which specifically
and appropriately focus on this population.108

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Community-based participatory research may also help to better understand and overcome
the many systemic barriers such as regulatory, organizational, and work culture to addressing
risks. Increased access to medical care and sleep disorder testing may also mitigate risk
of fatigue.63 Anecdotal evidence from researchers and safety practitioners suggests AgFF
workers use caffeine, energy drinks, and so on, or even prescription or illegal drugs to
manage fatigue, but has not been studied. Many offshore fishing vessel profits are generally
based on the value of the catch minus vessel expenses and then divided into “crew shares”
and distributed. This often leads to smaller crews and longer work hours for the crew
who remain.9 In both agriculture and seafood processing, some workers are paid by piece
rate, and more research is needed on the effects of this administrative policy. Finally, there
are no federal regulations mandating rest times, watchkeeping standards on vessels, or
minimal levels of staffing for this sector, except for some of the largest of commercial
fishing vessels.136 The effect of regulatory policy/agricultural exemptions, on work hours,
sleep, and fatigue is another area of needed research. Finally, more research is needed
to develop practical, relevant fatigue recognition indices and management strategies, and
evaluate existing interventions.

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Future interventions to address fatigue must move past generalized training on healthy
sleep habits and the dangers of fatigue. Stakeholders have noted AgFF workers typically
expect and are resigned to long work hours, sleep deprivation, and fatigue as an inevitable
and ubiquitous hazard. To address this expectation, peer-to-peer and culturally competent
education should be implemented to more effectively address AgFF’s unique culture and
work environments. To develop and evaluate practical fatigue risk management strategies,
however, researchers and practitioners cannot focus solely on educational/awareness efforts.
They must also address the economic and structural influences on workplace organization,
established culture and beliefs, and psychosocial factors that increase fatigue-related
risks. Interventions which use the principles of harm reduction and social marketing to
address long hours and fatigue may prove beneficial. Research assisting AgFF stakeholders
in addressing this culture of resignation and reward, and providing practical solutions
to manage fatigue, particularly during peak seasons, could lead to a change in work
organization and processes, policies, and regulations, which ultimately may prevent
fatalities, injuries, and illnesses among these high-risk workers.

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ACKNOWLEDGMENTS
The authors would like to thank Laura Syron for her work on this review as well as insight as the review criteria
were developed and screening process progressed. We also would like to thank the participants of the 2019 NIOSH
Working Hours, Sleep, and Fatigue AgFF breakout session for their comments and experiences which helped to
shape the scope of the review as well as the final recommendations. Finally, we’d like to thank Imelda Wong, Mary
O’Connor, and Kyla Retzer for offering feedback on the manuscript.

DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the corresponding author
upon reasonable request.

APPENDIX
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Search terms:
(Fishery OR Fisheries OR Fish processing OR fish processor* OR seafood processing
OR seafood processor* OR agriculture OR agricultural OR poultry production OR egg
production OR commercial fishing OR fishermen OR (fishers NOT (fishers ADJ2 test*))
OR forestry OR logging OR aquaculture OR mariculture OR crop production OR farming
OR farmer* OR farm-hand* OR farmhand* OR farm work* OR ranch*)
AND
Sleep* OR (work ADJ5 shift*) OR fatigue* OR exhaustion OR tired OR work schedule OR
(work* ADJ5 hour*) OR wakefulness OR rotating shift* OR (long* ADJ5 hour*)
NOT

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exp animals/NOT exp humans/
Limit to English; 1990 -; Abstract Available

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Elliott et al.

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Author Manuscript
Author Manuscript
Author Manuscript

FIGURE 1.

Scoping literature review process

Author Manuscript
Am J Ind Med. Author manuscript; available in PMC 2023 May 22.

Author Manuscript

2015

2008

1998

2010

2001

2019

2012

2004

2012

2006

Erkal

Gerberich

Heaton

Hwang

Ichihara

Lilley

McCurdy

McCurdy

Paulson

2013

DeWit

Browning

Work hours

Year

Am J Ind Med. Author manuscript; available in PMC 2023 May 22.
16,538

489

135

4439

337

1706

756

13,144

32,602

1135

1149

Sample

USA (Minnesota,
Wisconsin, North
Dakota, South

USA (California)

USA (California)

Canada
(Saskatchewan)

Japan

USA (New York)

USA (Kentucky and
South Carolina)

USA (Minnesota,
Wisconsin, North
Dakota, South
Dakota, and
Nebraska)

USA (Minnesota,
Wisconsin, North
Dakota, South
Dakota, and
Nebraska)

Canada
(Saskatchewan)

USA (Kentucky)

Country (region)

e,f

Farmers aged 50 and

Farm households

c

Youth (grades 9–12)
enrolled in agriculture
sciences curriculum

Farm operators

aged 16 and older

b

Farm owners/workers

Farm workers

Farm owners/workers

older

g

Self-report
(interview)

d

Farm households

Self-report
(interview)

Self-report
(survey)

Self-report
(survey)

Self-report
(survey)

Self-report
(survey)

Self-report
(interview)

Self-report
(survey)

Self-report
(interview)

Self-report
(survey)

Self-report
(survey)

Method of
report

c

Farm households

adults, 12–29

b

Farm youth and young

Beef cattle operators
and workers

Population
description

Author Manuscript

Study

Fall-related injuries

Risk factors for injury

Nonfatal occupational
injury

Relationship between
fatigue-related factors
and work-related
injuries

Risk factors for
occupational accidents

Severe farm injuries

Sleep apnea indicators
and injury

Machine-related
injuries

Animal-related injuries

Farm activities and
agricultural injuries

Cattle-related injuries
and farm management
practices

Stated study focus

Author Manuscript

Work hours and sleep in relation to injury
a

Fall-related injury event rate per 1000 persons per year:
>40–60 h/week = 49.2, 95% CI (38.6–62.6)

OR = 5.09 injury for those who worked 1501+ h/year, 95% CI
(1.61–16.1)

OR = 2.63 injury farmed 1441–3500 h in the last year, 95% CI
(1.43–4.83)
OR = 3.77 injury farmed >3500 h in the last year, 95% CI (1.63–
8.69)

Percentage of workers injured in peak season by work hours:
30–59 h/week = 6.7%, 60–79 = 9.1%, ≥80 = 10.1% (p = <0.0001)
Percentage of workers injured in nonpeak season by work hours:
30–59 h/week = 2.6%, 60–79 = 4.6%, ≥80 = 2.6% (p = <0.001)

OR = 1.76 occupational accidents for those working ≥8 h/day, 95%
CI (1.15–2.68)

OR = 9.54 injury for those working >8 h/day (54.0% of
participants), 95% CI (4.48–21.2), (p = <0.0001)

OR = 1.017 injury per 1-h increase in work hours, 95% CI not
given (p = 0.0047) (found to be not statistically significant in final
multivariable logistic regression model)

Machine-related injury rate per 100,000 persons: 40–59 h/week =
2254, rate ratio: 12.52, 95% CI (6.20–25.29)
60–79 h/week = 3664, rate ratio: 20.66, 95% CI (10.50–40.62)
80+h/week = 2716, rate ratio: 15.16, 95% CI (6.91–33.26)

Animal-related injury event rates per 1000 persons per year:
>40–60 h/week = 55.9, 95% CI (47.0–66.6)
>60–80 h/week = 78.5, 95% CI (66.9–92.1)
>80 h/week = 100.9, 95% CI (78.4–130.0)

Risk ratio = 10.3 injury for hours of farm work, 30+ h/week, 95%
CI (2.2–47.5), (p = 0.003)

OR = 2.01 injury for principal operator when 40+ h/week, 95% CI
(1.3–3.24)
OR = 1.72 injury for all workers when 36–60 h/week, 95% Cl
(1.05–2.81)
OR = 2.52 injury for all workers when 60+ h/week, 95% CI (1.55–
4.09)

Findings related to work hours, sleep

Author Manuscript

TABLE 1
Elliott et al.
Page 19

2003

2014

Spince

Svendsen

2699

431

1004

32,598

600

Norway (2 counties)

USA (Iowa)

USA (Kentucky)

USA (Minnesota,
Wisconsin, North
Dakota, South
Dakota, and
Nebraska)

USA (New York)

Am J Ind Med. Author manuscript; available in PMC 2023 May 22.

2012

2004

2009

2013

Lilley

Spengler

Shipp

Shipp

410

390

1004

4439

1135

Epworth Sleepiness Scale (ESS)

2015

DeWit

USA (Texas)

USA (Texas)

USA (Kentucky)

Canada
(Saskatchewan)

Canada
(Saskatchewan)

Insufficient sleep (less than 8h of sleep per night)

2004

2016

Reiner

Spengler

1992

Author Manuscript

Pratt

Country (region)
Dakota, and
Nebraska)

b

Farmworkers aged 13–
19 years

Migrant farm worker
families

19 and older

e

Part-time farmers age

aged 16 and older

Farm owners/workers

adults, 12–29

b

Farm youth and young

Farmers

Farmers

19 and older

e

Part-time farmers age

Farm households

c

Dairy farm owners/
workers

Population
description

Author Manuscript
Sample

Self-report
(survey)

Self-report
(interview and
survey)

Self-report
(interview)

Self-report
(survey)

Self-report
(survey)

Self-report
(survey)

Self-report
(interview)

Self-report
(interview)

Self-report
(interview)

Self-report
(interview)

Method of
report

Acute occupational
injury

Chronic back pain and
associated work and
nonwork variables

Sleep deprivation and
injuries

Relationship between
fatigue-related factors
and work-related
injuries

Farm activities and
agricultural injuries

Risk factors for injury

Risk factors for injury

Sleep deprivation and
injuries

Large machineryrelated injuries

Risk factors for
occupational accidents

Stated study focus

Author Manuscript

Year

HR = 2.10 injury for <8 per night, 95% CI (1.09–4.04), (p = 0.026)

OR = 2.26 chronic back pain for <8 h/day sleep at home, 95% CI
(1.16–8.12), (p = 0.024)
OR = 3.25 chronic back pain for fairly bad/very bad quality of
sleep while migrating, 95% CI (1.78–10.25), (p = 0.001)

OR = 1.01 injury for 7 h/day average sleep past year, 95% CI
(0.64–1.59)
OR = 1.25 injury for 6 h/day average sleep past year, 95% CI
(0.73–2.15)
OR = 1.12 injury for ≤5 h/day average sleep past year, 95% CI
(0.47–2.64)

OR = 1.43 injury for 7–6 h per night sleep during peak season,
95% CI (0.96–2.12)
OR = 1.48 injury for ≤5 h per night sleep during peak season, 95%
CI (0.93–2.34)
OR = 1.41 injury for 7–6 h per night sleep during nonpeak season,
95% CI (0.86–2.32)
OR = 2.40 injury for ≤5 h per night sleep during nonpeak season,
95% CI (1.02–5.68), (p = 0.04)

9.5% injury rate for ≤6 h sleep per night, CI (6.3–12.6), (p =
0.0002)

OR = 1.54 injury for working >3500 h at farm, 95% CI not given
(p = <0.01)

OR = 1.65 injury for farmers working >50 h/week in the last year,
95% CI (1.23–2.21)

OR = 1.43 injury for 41–50 h/week, 95% CI (0.73–2.80)
OR = 1.02 injury for >50 h/week, 95% CI (0.44–2.39)

Large machine-related injury events per year per 1000 persons:
20–39 h/week = 18.88, 95% CI (14.93–23.88)
40–59 h/week = 40.25, 95% CI (32.83–49.35)
60–79 h/week = 43.15, 95% CI (35.17–52.92)
80+ h/week = 43.19, 95% CI (30.56–61.05)

Relative risk = 2.76 injury for owners who worked more than 60
h/week and had 30+ acres under tillage/worker.
Injured workers were: older (p = 0.01), worked more hours (p =
0.001), and had heavier workloads than noninjured workers (p =
0.001)

a
Findings related to work hours, sleep
>60–80 h/week = 52.1, 95% CI (40.6–66.8)
>80 h/week = 55.6, 95% CI (37.9–81.6)

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Study

Elliott et al.
Page 20

Am J Ind Med. Author manuscript; available in PMC 2023 May 22.

2003

Spince

431

2392

USA (Iowa)

Canada
(Saskatchewan)

Australia (Victoria)

2013

2010

2012

2014

2011

2004

Dosman

Heaton

Lilley

King

Marcum

Spengler

1004

1394

2392

4439

756

5502

USA (Kentucky)

USA (Kentucky and
South Carolina)

Canada
(Saskatchewan)

Canada
(Saskatchewan)

USA (Kentucky and
South Carolina)

Canada
(Saskatchewan)

f

Regional Rural Injury Study I (RRIS-I) Cohort.

b

b

b

b

19 and older

e

Part-time farmers age

older

e,f

Farmers aged 50 and

aged 16 and older

Farm owners/workers

aged 16 and older

Farm owners/workers

older

e,f

Farmers aged 50 and

Farm owners/workers

Farmers

aged 16 and older

Farm owners/workers

Farm owners/workers
aged 16 and older

Population
description

Self-report
(interview)

Self-report
(survey)

Self-report
(survey)

Self-report
(survey)

Self-report
(survey)

Self-report
(survey)

Self-report
(interview)

Self-report
(survey)

Self-report
(interview)

Method of
report

African-American farmers from the Kentucky and South Carolina Agricultural Statistics Services.

Kentucky Farm Family Health and Hazard Surveillance Project.

e

d

c
Regional Rural Injury Study II (RRIS-II) Cohort.

Saskatchewan Farm Injury Cohort.

b

Adjusted values used when available.

a

2014

King

252

Sleep disorder (diagnosed and symptoms)

2009

Author Manuscript

Day

Country (region)

Author Manuscript
Sample

Sleep deprivation and
injuries

Injury among farmers
50 years and older

Impact of excessive
daytime sleepiness on
safety and health

Relationship between
fatigue-related factors
and work-related
injuries

Sleep apnea indicators
and injury

Loud snoring and
occupational injury

Risk factors for
agricultural injury

Impact of excessive
daytime sleepiness on
safety and health

Risk factors for work
related injury among
male farmers

Stated study focus

Author Manuscript

Year

OR = 2.28 injury for sleep medication used in the past month, 95%
CI (1.67–4.47)
OR = 2.17 injury for three sleep apnea signs and symptoms, 95%
CI (1.03–4.56)

OR = 1.32 injury for 1–2 days restless nights in past week, 95% CI
(0.96–1.81), (p = 0.0883)
OR = 2.02 injury for 3–4 days restless nights in past week, 95% CI
(1.32–3.09), (p = 0.0011)
OR = 1.89 injury for 5–7 days restless nights in past week, 95% CI
(1.28–2.80), (p = 0.0012)

OR = 0.96 injury for diagnosed sleep apnea, 95% CI (0.47–1.96)

OR = 1.20 injury for loud snoring, 95% CI (0.79–1.83)

OR = 1.861 injury for stop breathing while sleeping, 95% CI
(1.035–3.346), (p = 0.038)
OR = 2.246 injury for problems staying awake last month, 95% CI
(1.244–4.055), (p = 0.007)

HR = 0.79 injury for diagnosed sleep apnea, 95% CI (0.43–1.47)
HR = 1.45 injury for loud snoring, 95% CI (1.07–1.99)

OR = 1.27 injury for ESS > 15, 95% CI (0.98–1.66)

OR = 1.34 injury for ESS > 10, 95% CI (0.92–1.96)

OR = 0.51 injury for ESS > 10, 95% CI (0.32–0.82)

a
Findings related to work hours, sleep

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Study

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g

Author Manuscript

New York State Farm Family Health and Hazard Surveillance Project.

Elliott et al.

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Author Manuscript
Author Manuscript
Am J Ind Med. Author manuscript; available in PMC 2023 May 22.