Health-Related Exposures and Conditions among US Fishermen

ABSTRACT

Commercial fishing is a high-risk occupation, yet there is a lack of surveillance documenting health conditions, health behaviors, and health care coverage among US fishermen. We used publicly available data sources to identify exposures and health outcomes common among fishermen. We utilized the National Institute for Occupational Safety and Health–Worker Health Charts to estimate the prevalence of general exposures, psychosocial exposures, health behaviors, and health conditions from the national surveys National Health Interview Survey – Occupational Health Supplement (NHIS-OHS, 2015) and Behavioral Risk Factor Surveillance System (BRFSS) (2013–2015). We compared fishing workers with both agricultural workers and all-workers. Fishermen commonly reported general exposures, psychosocial exposures, non-standard work arrangements, frequent night shifts, and shift work. The prevalence of musculoskeletal conditions such as carpal tunnel syndrome (33%) and severe low-back pain (27%) was also high. Smoking (45%) and second-hand smoke exposure (25%) were widespread, and 21% reported no health care coverage. National household surveys such as NHIS-OHS, and BRFSS can be utilized to describe the health status of fishermen. This workforce would benefit from increased access to health care and health promotion programs. More comprehensive evaluations of existing data can help to identify occupation-specific health challenges.

KEYWORDS:

• Fishermen
• musculoskeletal conditions
• worker health
• surveillance
• health promotion

Background

Commercial fishing poses numerous hazards to workers that may result in injuries and chronic health problems. US occupational surveillance and intervention efforts have reduced fatal and non-fatal injuries.^1,2 However, health and well-being concerns within fishing communities such as general physical health, mental health, lifestyle and behavioral factors, and healthcare access remain less explored.^1–4 Work-related risk factors may contribute to obesity, cardiovascular disease, depression, sleep disorders, and other health disorders previously considered unrelated to work.^5–10 Surveillance in England and Wales found fishing amongst the top industries with the poorest general health and the highest incidence of long-term work-limiting illness.¹¹ However, analyses of US household-based national surveys (National Health Interview Survey [NHIS] and Behavioral Risk Factor Surveillance System [BRFSS]) that document worker health trends have not focused on fishermen.^3,4,12

We used the National Institute for Occupational Safety and Health – Worker Health Charts (NIOSH-WHC) interactive online tool to create customized charts to obtain occupation-specific estimates of workplace exposures, safety behaviors, health status, illnesses, and injuries, as well as working and employment conditions. We sought to determine if NIOSH-WHC national survey data could identify risk factors and health outcomes disproportionately affecting fishermen, and identify opportunities for future research, training, and engagement with fishing communities.

Methods

Data sources

The NIOSH-WHC webpage comprises multiple recent national case reports and survey data. We selected the NHIS Occupational Health Supplement (NHIS-OHS, 2015) and BRFSS (2013–2015) data since the NIOSH-WHC reported participant responses for occupational sub-categories (using Standard Occupational Classification [SOC] codes) from both surveys.¹³

NIOSH-WHC data reporting

The NIOSH-WHC web interactive tool yields custom charts categorized by sociodemographic characteristics such as age, gender, education, race, or occupation. We generated occupation-specific charts and reported the adjusted prevalence estimates with 95% confidence intervals (CI) as well as estimated population (annual average), and estimated population with health conditions. The NIOSH-WHC provided prevalence estimates adjusted for age, sex, and race based on the 2000 U.S. population which did not require further analysis or formatting. The sample sizes are currently not available through NIOSH-WHC but can be obtained from the original datasets. For example, a recent study analyzed NHIS-OHS (2015) and reported 179 workers in the farming, fishing, and forestry occupation category.¹⁴ However, this was beyond the scope of this report, which sought to review the available information in the NIOSH-WHC. We compared prevalence estimates for three worker categories: (1) all occupations, (2) agricultural workers, and (3) fishing-hunting workers. We could not determine the number of fishermen within the fishing-hunting worker category (SOC code – 45-3031.00) since the fishing-specific SOC subcategory – 45-3011.00 (Fishers and Related Fishing Workers) is no longer available in the worker health datasets.¹⁵ Nevertheless, the Bureau of Labor Statistics (BLS) recently published a detailed distribution of workers in subcategories, and amongst the fishing-hunting category, none were hunters and trappers indicating they are relatively rare compared to fishermen.¹⁶ We, therefore, concluded that the fishing-hunting category is dominated by commercial fishermen and referred to them as fishermen throughout the text.

We explored worker health themes pertinent to fishermen including exposures, chronic health conditions, and health care access from participant survey responses to the NHIS-OHS (2015) and BRFSS (2013–2015). The exposure category included psychosocial occupational exposures, health behaviors (lifestyle), work organization characteristics, and general exposures (see Tables 1 & 2). We compared the prevalence estimates and 95% confidence intervals (CI) between groups and report differences where the 95% CIs did not overlap.

Table 1. Adjusted prevalence of occupational exposures, health behavior, and health status among currently employed fishing and hunting workers, agricultural workers, and all workers who participated in the National Health Interview Survey – Occupational Health Supplement (NHIS-OHS, 2015).

	Fishing and Hunting Workers			Agricultural Workers			All Employed Adults (a)
Participant responses	Unadjusted – Estimated Population with Condition/Total Estimated Population (in thousands) ^(b)	Adjusted Prevalence (%) ^(c, d) (95% CI)	Unadjusted – Estimated Population with Condition/Total Estimated Population (in thousands) ^(b)		Adjusted Prevalence (%) ^(c, d) (95% CI)	Unadjusted – Estimated Population with Condition/Total Estimated Population (in thousands) ^(b)		Adjusted Prevalence (%) ^(c, d) (95% CI)
Work organization characteristics
Non-standard work arrangement (independent contractor)	4/29	29.0 (27.8–30.3)	131/919		10.9 (4.9–22.2)	14,573/145,791		11.3 (10.5–12.1)
Non-standard work arrangement (temporary agency or sub-contractor)	-/29	N/A	141/919		13.4 (5.4–29.8)	4,131/145,791		2.8 (2.5–3.2)
Frequent night work	14/29	40.3 (33.1–48.0)	84/919		7.9 (4.0–15.0)	10,834/145,575		6.9 (6.4–7.5)
Shift work (any alternative shift)	28/29	98.9 (98.7–99.1)	224/919		24.9 (15.8–36.9)	38,793/145,794		27.1 (26.1–28.1)
Supervisory responsibility	16/29	68.9 (66.0–71.6)	172/928		17.8 (10.3–28.9)	47,734/145,891		31.5 (30.5–32.4)
Psychosocial occupational exposures
High job demands	13/29	29.5 (22.8–37.1)	76/900		12.3 (5.2–26.3)	20,893/145,546		13.8 (13.0–14.6)
Hostile work environment	0.8/29	7.6 (7.1–8.2)	15/919		1.5 (0.6–3.6)	10,024/145,760		6.7 (6.2–7.3)
Low job control	12/29	27.5 (24.5–30.7)	228/907		23.2 (16.1–32.1)	19,865/145,380		13.3 (12.6–14.1)
Low supervisory support	1/15	34.9 (34.9–34.9)	33/811		7.1 (3.9–12.9)	13,086/131,890		9.6 (9.0–10.2)
Poor safety climate (excludes self-employed)	-/15	N/A	29/815		3.8 (1.5–9.0)	7,360/132,459		5.3 (4.9–5.8)
Work-life interference	28/29	81.8 (68.7–90.2)	294/907		36.6 (26.5–48.1)	37,060/145,472		24.2 (23.4–25.0)
Workplace perceived as unsafe	11/29	20.4 (19.8–21.1)	96/919		10.6 (6.6–16.4)	6,496/145,635		4.2 (3.9–4.6)
Worry about losing job	12/29	16.5 (13.5–20.1)	105/918		10.5 (5.5–19.0)	16,013/145,498		10.1 (9.5–10.8)
General exposures (NHIS-OHS 2015)
Frequent lifting, pulling, or bending	29/29	100.0 (N/A)	686/919		76.4 (68.7–82.7)	60,471/145,777		40.0 (39.0–41.0)
Frequent standing or walking	29/29	100.0 (N/A)	832/919		91.1 (85.8–94.6)	97,314/145,818		66.1 (65.0–67.1)
Frequent workplace secondhand smoke exposure	2/15	24.9 (11.3–46.2)	74/772		8.3 (5.1–13.3)	12,532/124,080		9.5 (8.9–10.1)
Musculoskeletal conditions (NHIS-OHS 2015)
Carpal tunnel syndrome (ever)	2/29	33.2 (23.7–44.3)	35/928		5.3 (2.1–12.8)	8,821/145,769		6.4 (5.9–6.9)
Carpal tunnel syndrome (current)	1/29	14.0 (6.3–28.3)	13/928		N/A	3,890/145,752		2.8 (2.4–3.1)
Carpal tunnel syndrome (due to work)	1/29	14.0 (6.3–28.3)	10/928		N/A	2,445/145,699		1.7 (1.4–2.0)
Severe low-back pain	12/29	27.5 (24.5–30.7)	55/928		8.1 (5.2–12.6)	11,882/145,804		8.2 (7.6–8.8)
Low-back pain (due to work)	2/29	11.8 (6.1–21.6)	25/928		4.2 (3.1–5.7)	8,274/145,742		5.3 (4.9–5.7)
a. All employed adult group estimates included both fishing and hunting worker category and the agricultural worker category b. The total estimated population and the estimated population with conditions were unadjusted estimates and will not yield adjusted prevalence estimates. c. Prevalence estimates are based on a sample of us adults rather than the entire population. Comparisons between adjusted prevalence rates for different groups should take into account the 95% confidence limits. d. Prevalence estimates adjusted for age, sex, and race using the projected 2000 U.S. Population as the standard population.

Table 2. Adjusted prevalence of occupational exposures, health behavior, and health status among currently employed fishing and hunting workers, agricultural workers, and all workers who participated in the Behavioral Risk Factor Surveillance System (BRFSS) (2013–2015).

	Fishing and hunting workers		Agricultural workers		All Employed adults (a)
Participant responses	Unadjusted – Estimated Population with Condition/Total Estimated Population (in thousands) (b)	Adjusted Prevalence (%) (c, d) (95% CI)	Unadjusted – Estimated Population with Condition/Total Estimated Population (in thousands) (b)	Adjusted Prevalence (%) (c, d) (95% CI)	Unadjusted – Estimated Population with Condition/Total Estimated Population (in thousands) (b)	Adjusted Prevalence (%) (c, d) (95% CI)
Health Behaviors
Alcohol Use – Binge Drinking	6/26	15.1 (8.8–24.6)	167/597	19.7 (15.0–25.4)	17,363/81,753	20.0 (19.6–20.4)
Alcohol Use – Heavy Drinking	2/26	8.9 (4.1–18.3)	49/596	5.0 (3.2–7.7)	5,476/81,692	6.8 (6.5–7.0)
Current Smoker	12/27	44.7 (34.1–55.8)	93/604	12.9 (9.3–17.7)	13,668/83,693	15.6 (15.3–16.0)
Did not get the Flu vaccine	23/27	81.2 (66.7–90.2)	495/592	76.5 (70.7–81.4)	51,882/78,773	63.5 (63.0–64.0)
Does not always wear seatbelt	6/27	30.1 (22.4–39.1)	100/592	14.8 (11.0–19.6)	9,516/78,847	12.0 (11.7–12.4)
Obesity	3/27	9.2 (5.6–14.8)	139/543	26.2 (19.9–33.5)	22,566/82,355	26.8 (26.3–27.2)
Health Status
Rated health as fair or poor	3/26	9.4 (4.7–17.8)	164/610	24.5 (18.8–31.3)	9,043/88,417	9.8 (9.5–10.2)
No health care coverage	5/27	21.5 (11.8–35.8)	315/611	35.8 (29.3–42.8)	13,072/88,300	12.8 (12.4–13.2)
Chronic Conditions
Asthma	2/26	8.2 (4.5–14.6)	62/616	9.4 (6.5–13.5)	10,866/88,404	12.7 (12.4–13.0)
CVD (Stroke, Heart Attack, or CHD/Angina)	0.25/27	N/A	12/607	2.5 (1.6–4.0)	3,200/88,162	4.5 (4.3–4.7)
Diabetes	2/27	4.0 (1.6–9.6)	31/615	5.6 (3.7–8.3)	5,286/88,470	6.7 (6.5–7.0)
Arthritis	3/27	18.7 (10.2–32.0)	56/615	16.0 (11.5–21.8)	13,922/88,239	18.6 (18.2–18.9)
Depression	5/27	14.8 (8.1–25.4)	58/612	11.5 (7.5–17.1)	11,593/88,282	13.9 (13.5–14.2)
All employed adult group estimates included both fishing and hunting worker category and the agricultural worker category The total estimated population and the estimated population with conditions were unadjusted estimates and will not yield adjusted prevalence estimates Prevalence estimates are based on a sample of US adults rather than the entire population. Comparisons between adjusted prevalence rates for different groups should take into account the 95% confidence limits. Prevalence estimates adjusted for age, sex, and race using the projected 2000 U.S. population as the standard population.

Results

NHIS-OHS (2015) survey found fishermen had a higher prevalence of non-standard work arrangements (independent contractor) (29%), frequent night shifts (40%), shift work (99%), and supervisory responsibility (69%) relative to agricultural workers and all occupations combined. Fishermen commonly reported psychosocial exposures such as high job demands, low supervisory support, work-life interference, workplace perceived as unsafe, and worry about losing a job (Table 1).

NHIS-OHS (2015) also showed that fishermen reported universal exposure to frequent lifting, pulling, or bending, and frequent standing or walking, higher than agricultural workers and all-workers. Musculoskeletal conditions such as low-back pain and carpal tunnel syndrome, which can result from those work task exposures, were also common in fishermen and more prevalent than in all worker populations (Table 1).

The prevalence of excessive alcohol use (binge drinking and heavy drinking) was similar (8.9 vs. 5.0 and 6.8) across all three groups in the BRFSS (2013–2015) survey. But more fishermen reported current smoking (BRFSS 2013–2015) and exposure to second-hand smoke (NHIS-OHS 2015) than their counterparts (Tables 1 & 2).

BRFSS (2013–2015) survey found one in ten fishermen rated their health as fair or poor, and about one in five reported no health care coverage, both lower than agriculture workers. Fewer than one in five fishermen reported influenza vaccination. The self-reported prevalence of chronic health conditions was similar across all three groups except obesity, which was lower amongst the fishermen (Table 2).

Discussion

While fishermen had rates of chronic medical conditions comparable to all-workers, they more often reported chronic musculoskeletal conditions, including back pain and carpal tunnel syndrome and the frequent lifting, pulling, or bending which can underlie such conditions.^17–19 Commercial fishing is physically demanding and strenuous work where the tasks often comprise continuous repetitive activities (e.g. using a line with a net, hooks, or pots to harvest the fish) in long cycles.²⁰ Routine tasks include loading bait, hauling frozen blocks, unloading the catch, and boat clean-up.^21,22 Repeated strenuous movements contribute to musculoskeletal conditions including low-back pain and carpal tunnel syndrome, and fishing tasks with ergonomic stressors have been associated with low-back pain.^22–27 Other low-back pain risk factors include age, work-years, fishing and gear type, job title, and fishing part-time or multiple jobs.^22,26 Obesity is a risk factor for musculoskeletal conditions but prevalence was lower among fishermen than all workers.^28,29

Psychosocial exposures are associated with musculoskeletal conditions; a study using NHIS-OHS found independent associations between low-back pain and work-family imbalance, job insecurity, and hostile work environments.³⁰ Others have reported associations between musculoskeletal conditions and psychosocial exposures as well as work organization characteristics such as non-standard work arrangements, multiple jobs, and long work hours.^18,19,31 The high prevalence of musculoskeletal conditions among US fishermen could be related to commonly reported psychosocial exposures such as work-life interference, high job demand, low job control, low supervisory control, and workplaces perceived as unsafe.

Work-life interference can be associated with unhealthy behaviors and negative health outcomes and may be linked to mental strain leading to muscle tension or other physiological processes, resulting in low-back injury/pain.^32,33 The work organization characteristics of fishing – including seasonal work, quotas or permitting seasons, competition for limited catches, weather patterns, crew availability, boat size, crew size, and distant fishing grounds – lead to a high prevalence of non-standard work arrangements.^3,20 The fluctuating economics of commercial fishing may contribute to increased job insecurity, anxiety, and unusual work hours.^20,34 Therefore, prevention strategies for musculoskeletal conditions among fishers need to address both individual physical and psychosocial exposures as well as address fishery-wide working conditions.

Both smoking and second-hand smoke exposures were relatively common among fishermen, increasing the risk of smoking-associated health disorders, including musculoskeletal conditions.^35–37 Fishing generally requires continuous work for extended hours that may promote smoking.^20,38 A study in Washington State found significantly higher cigarette and marijuana smoking rates among fishers compared to the general population.⁴

Our research had limitations, several of which are inherent in health surveys: uncertainty of diagnosis for reported conditions, and reliance on subjective perceptions. None of the NHIS-OHS or BRFSS surveys were designed to produce representative samples of each occupational category hence the small subsamples for fishermen may have led to unreliable estimates. Moreover, the NHIS-OHS and BRFSS do not survey fishermen independently from professional hunters;¹⁵ though hunters may be relatively rare compared to fishermen since a recent BLS report observed no hunters and trappers amongst the fishing-hunting subcategory.¹⁶ Conducting national surveys with a representative sample of fishermen would be expensive and logistically challenging whereas general population surveys can provide insights with little effort. We could not associate the exposure data with health conditions since NIOSH-WHC charts yielded prevalence estimates but not the individual-level data., BRFSS only included data from the states that voluntarily collected industry and occupation information, which excluded the coastal states of Alaska, Texas, and South Carolina.¹⁶

Despite these limitations, we identified important indicators of health status among US fishermen, including high rates of musculoskeletal conditions. We also identified key aspects of employment conditions, such as the unpredictability of working arrangements and the work itself, which may underlie both exposures and health status. Our review indicates access to health care and health promotion programs should be prioritized. Our findings also demonstrated the utility of national household surveys (i.e., NHIS-OHS, BRFSS) to examine fishermen’s health, though the estimates should be interpreted with caution. A more comprehensive evaluation of available data for individual occupation categories can provide a robust understanding of work-associated health and wellbeing.

Disclosure of potential conflicts of interest

The authors declare that there are no relevant financial or non-financial competing interests to report.

Additional information

Funding

This work was supported by the National Institute for Occupational Safety and Health Grant #2U54OH007544-16 awarded to the Pacific Northwest Agricultural Safety and Health Center.