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- Original article Sex difference in musculoskeletal disabilities among Korean fishers: a cross-sectional study
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Hye-min Kim1
, Soo Hyeong Park1, Bong Gyun Joo1, Ki-Soo Park2, Jeong Ho Kim3, Hansoo Song1,* -
Annals of Occupational and Environmental Medicine 2025;37:e18.
DOI: https://doi.org/10.35371/aoem.2025.37.e18
Published online: July 7, 2025
1Department of Occupational and Environmental Medicine, Chosun University Hospital, Gwangju, Korea
2Department of Preventive Medicine, College of Medicine and Institute of Health Science, Gyeongsang National University, Jinju, Korea
3Department of Occupational and Environmental Medicine & Institute of Environmental and Occupational Medicine, Inje University Busan Paik Hospital, Busan, Korea
- *Corresponding author: Han Soo Song Department of Occupational and Environmental Medicine, Chosun University Hospital, 365 Pilmun-daero, Dong-gu, Gwangju 61453, Korea E-mail: oemsong@chosun.ac.kr
• Received: May 3, 2025 • Revised: June 27, 2025 • Accepted: June 30, 2025
© 2025 Korean Society of Occupational & Environmental Medicine
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Abstract
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Background Fishing is a physically demanding occupation with a high risk of musculoskeletal disabilities (MSDs). Although previous studies have focused on ergonomic risk factors, little attention has been paid to sex differences in the prevalence of MSDs among fishers. This study aimed to assess whether female fishers experience a higher prevalence of MSDs than male fishers and to examine whether this difference persists after adjusting for socioeconomic and occupational factors.
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Methods We analyzed cross-sectional data from 898 Korean fishers (513 men and 385 women) who participated in the 2021–2022 Fisher Health Survey. MSDs in the upper extremities, lower back, and knees were defined as scores in the top 25% of the Quick Disabilities of the Arm, Shoulder, and Hand (QuickDASH), Oswestry Disability Index, and Western Ontario and McMaster Universities Arthritis Index Short Form (WOMAC-SF), respectively. Modified Poisson regression was used to calculate the prevalence ratios (PRs) by sex, with stepwise adjustments for age, socioeconomic factors, and occupational factors.
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Results Female fishers had significantly higher MSD risk than male fishers across all body regions (fully adjusted PRs: upper extremity, 1.59; lower back, 1.63; knee, 1.44). Sex disparities were most pronounced among those under 60 years of age and remained significant even in older age groups.
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Conclusions The elevated MSD risk among female fishers persisted despite adjusting for conventional risk factors, suggesting the influence of additional factors such as biological susceptibility, domestic labor, and gendered health reporting. Therefore, MSD prevention strategies should include sex-sensitive multidimensional approaches beyond ergonomic interventions.
BACKGROUND
Fishing is a primary industry associated with a high risk of accidents and musculoskeletal disabilities (MSDs).1-4 Fishing activities involve significant physical demands, including repetitive lifting or pulling of heavy loads and forceful hand gripping, which frequently lead to MSDs in the upper extremities, lower back, and knees.5-7 Certain fishing activities, such as aquaculture, require workers to perform tasks in unstable environments and maintain physically disadvantageous postures for prolonged periods.8 Numerous epidemiological studies have confirmed that excessive ergonomic stress is a significant contributor to MSDs in fishers.9,10
In Korea, the fisheries sector is broadly divided into commercial fisheries and artisanal small-scale fisheries. The latter includes coastal fisheries and aquaculture and, as of 2023, comprises approximately 42,000 fishing households with 87,000 fishers.11 However, governmental support policies have primarily focused on commercial fishing, and the majority of household heads in the artisanal sector are men. As a result, women engaged in artisanal small-scale fishing face a double burden of marginalization.12,13 This marginalization often leads to increased labor burdens for women, providing a plausible explanation for the higher prevalence of musculoskeletal disorders among female fishers.
In addition, the artisanal fishing population shows signs of rapid aging, with 29.7% aged 70 or older and 35.5% in their 60s.11 Since age is one of the most critical risk factors for degenerative musculoskeletal diseases, the aging demographic poses a significant occupational health concern for this sector.
Consequently, recent research has started to examine not only traditional ergonomic risk factors but also socioeconomic conditions, limited access to healthcare and welfare services, and sociocultural factors such as sex-based labor divisions and patriarchal norms.14,15 In this context, the necessity of research addressing sex differences and occupational characteristics specific to women fishers has been increasingly emphasized.12,16 Furthermore, the sex gap in MSD prevalence is believed to be influenced by multiple factors, including socioeconomic status, occupational environment, and biological characteristics.17
This study aimed to examine sex differences in the prevalence of MSDs in the upper extremities, lower back, and knees among fishers, and to identify the factors contributing to these disparities. In particular, we aimed to contribute to the development of sex-sensitive intervention strategies for preventing MSDs among fishers through detailed analyses of these sex-related differences.
METHODS
The study participants consisted of 898 Korean fishers (513 men and 385 women) who participated in the Fishers Health Survey conducted at three Fisheries Safety and Health Centers from 2021 to 2022. Fisheries safety and health centers, designated by the Ministry of Oceans and Fisheries under the Special Act on Improving the Quality of Life of Farmers and Fishermen and Promoting Rural Development, currently number only three nationwide. However, these centers cover the key fishing regions of Korea, particularly in the Jeolla and Gyeongsang provinces.
Data were collected through one-on-one interviews, using structured questionnaires. The questionnaire included questions on socioeconomic factors, occupational factors, and assessment tools for physical strain and MSDs. The MSD assessment tools consisted of Quick Disabilities of the Arm, Shoulder, and Hand (QuickDASH), for upper extremity, Oswestry Disability Index (ODI), for lower back, and Western Ontario and McMaster Universities Arthritis Index Short Form (WOMAC-SF), for the knee. The scores from each assessment tool were converted to a 0–100 scale. MSDs were defined as scores of 25 or higher for each body region.18-20 The cut-off score of 25 was established through expert consensus, based on a review of prior studies that used the same assessment tools in patients with musculoskeletal disorders both before and after surgery. These studies reported minimal clinically important differences or threshold values that distinguished between preoperative and postoperative recovery states. Based on these findings, we concluded that a score of 25 appropriately differentiates individuals with MSD from those without.21-23
The independent variables were categorized into socioeconomic and occupational factors. Socioeconomic factors included age (years), educational level, annual household income (10,000 KRW), concurrent employment status (fishing-only vs. concurrent employment), and ownership status (yes vs. no). Occupational factors included the type of fishery (vessel, aquaculture, diving/bare-handed, or mixed), fishing labor (hour/year), total labor (hour/year), and physical strain levels (upper extremity, back, and knee).
The ergonomic risk score was calculated using the “Face-to-Face Questionnaire for the Assessment of Ergonomic Risk,” developed by Lee et al.10 This tool evaluates cumulative physical burden over the past year by assessing five body parts based on three components: task intensity, average daily working hours, and the number of working days in the past year. The ergonomic risk score was calculated using the following formula:
Ergonomic risk score = Task intensity × Average daily working hours × Number of working days in the past year.
Task intensity was categorized as mild (0.5), moderate (1.0), or severe (1.5). Average daily working hours were scored as follows: less than 2 hours (1), 2–3 hours (2), 4–5 hours (3), 6–7 hours (4), and 8 hours or more (5).
A threshold score of 250 points was defined as indicating a significant physical burden. This threshold was established based on official guidelines issued by the Korean Ministry of Employment and Labor, which require ergonomic hazard assessments when physically demanding tasks are performed for more than two hours per day.24
Because the ergonomic risk score reflects cumulative burden over one year, the threshold was set using the national average of 250 working days per year for Korean workers. A score below 250 was considered the reference level for physical strain.
Sex differences in independent variables were assessed using the chi-square (χ²) test, with categorical variables presented as frequencies (%). A modified Poisson regression analysis was conducted to evaluate sex differences in the prevalence of MSDs.25 Initially, the unadjusted prevalence ratios (PRs) were calculated. Subsequently, four sequentially adjusted models were constructed to assess how socioeconomic and occupational factors, including physical strain level, influenced sex differences in the prevalence of MSDs. The adjustment variables for each model were as follows: model 1 was adjusted for age; model 2 was adjusted for socioeconomic factors (age, education level, annual income, concurrent employment status, and ownership status); model 3 was adjusted for socioeconomic factors (model 2) and occupational factors (type of fishery, fishing labor hour/year); and model 4 was adjusted for socioeconomic factors (model 2) and physical strain level (upper extremity, back, and knee). The PRs and their corresponding 95% confidence intervals (CIs) for MSDs were calculated and reported for each model. All statistical analyses were performed using Stata version 18.0 (StataCorp LLC., College Station, TX, USA).
The study protocol was reviewed and approved by the Institutional Review Board of Chosun University Hospital (approval number: CHOSUN-2021-04-015). Written informed consent was obtained from all participants prior to their participation in the study.
RESULTS
Table 1 presents the socioeconomic and occupational characteristics of the participants (n=898; 513 men and 385 women). Women fishers were more likely to have lower education levels (elementary school or lower: 44.9% women and 21.4% men) and lower annual incomes (<20 million KRW annually: 37.9% women and 25.5% men) than men. The proportion of non-owners (without vessel ownership) was significantly higher among women than men (70.7% women and 15.4% men). Regarding fishery type, women engaged more frequently in diving/bare-handed (19.7% women and 7.2% men) and mixed fishery (38.4% women and 29.8% men). Additionally, women reported significantly shorter annual fishing labor hours and total labor hours than men.
Table 2 presents the physical strain levels reported by participants. Overall, no significant sex differences were observed in the physical strain levels of the upper extremity (hand and shoulder), back, and knee regions.
Table 3 presents the prevalence of MSD among the participants according to sex, age group, and body region. Woman fishers were more likely to report MSDs than men fishers across all body regions, particularly the back (34.8% female and 19.3% male), knees (33.5% female and 20.3% male), and upper extremities (31.4% female and 18.7% male). Although MSD prevalence generally increased with age, sex differences were more prominent among participants under 60 years of age than among those aged 70 years or older.
Table 4 presents the PRs of MSD by sex, estimated using a modified Poisson regression analysis. In the unadjusted model, woman fishers had a significantly higher prevalence of MSDs compared to man fishers in upper extremity (PR: 1.68; 95% CI: 1.33–2.12), back (PR: 1.80; 95% CI: 1.44–2.26), and knee (PR: 1.65; 95% CI: 1.32–2.06). In model 1, which was adjusted for age, sex-specific PRs slightly increased across all regions (upper extremity, 1.72; back, 1.88; knee, 1.72). In model 2, which was additionally adjusted for socioeconomic factors, PRs modestly decreased (upper extremity, 1.52; back, 1.63; knee, 1.50). In model 3, which was further adjusted for occupational factors, the PRs decreased slightly (upper extremity, 1.46; back, 1.57; knee, 1.47). Finally, in model 4, which was further adjusted for physical strain level, PRs slightly increased again for the upper extremity and back, whereas knee PR decreased marginally (upper extremity, 1.59; back, 1.63; knee, 1.44).
Table 5 presents the PRs of MSD according to sex, stratified by age group, based on model 4 (adjusted for socioeconomic factors and physical strain level). Overall, woman fishers exhibited higher PRs of MSDs across all body regions than man fishers. Among participants younger than 60 years, woman fishers showed significantly higher PRs in back (PR: 2.73; 95% CI: 1.50–4.97) and knee (PR: 1.71; 95% CI: 1.00–2.90). In the 60–69 age group, woman fishers also had significantly higher PRs in upper extremity (PR: 1.66; 95% CI: 1.07–2.59) and knee (PR: 1.58; 95% CI: 1.02–2.44). Although PRs was higher among women aged ≥70 years in all regions (upper extremity, back, and knee), the differences were not significant. Overall, sex disparities in PRs tended to be more pronounced in the younger age groups.
DISCUSSION
This study analyzed the prevalence of MSDs in the upper extremities, back, and knees in Korean fishers. Women fishers exhibited consistently higher PRs than men fishers across all body regions. Even after sequential adjustment for age, socioeconomic and occupational factors, and physical strain levels, women maintained significantly elevated PRs, ranging from 1.44 to 1.59. The sex difference was most pronounced among those under the age of 60 years; although it slightly narrowed among those aged 70 years and older, the PRs remained higher in women across all age groups.
Given the physically demanding nature of fishery work, it has generally been assumed that men fishers would have a higher risk of developing MSDs than women fishers. However, the findings of the present study contradict this assumption, indicating a marked vulnerability among female fishers. Previous studies have shown that men tend to have higher MSD risk in the manufacturing and construction industries, which are man-dominated and involve more hazardous tasks.26-29 In contrast, studies in agriculture, forestry, and fisheries-industries characterized by relatively balanced sex ratios and similar occupational tasks between sexes, have consistently reported higher MSD prevalence among women.30-33 Park et al.26 reported that women had higher MSD risks than men despite similar exposure levels to occupational risk factors within the same industry. Similarly, Osborne et al.,31 in their systematic review, found that the 1-year prevalence of MSDs among women agricultural workers was approximately 10% higher than men. Furthermore, Baek et al.33 reported that although male farmers experienced higher ergonomic burdens, female farmers were more adversely affected by musculoskeletal pain. These findings align with our results, suggesting that sex differences in MSD prevalence are also evident in the fishery sector.
Biological vulnerability may partly explain the higher MSD risk observed in women fishers.17,34,35 Postmenopausal declines in estrogen are known to accelerate the degeneration of bone density and soft tissues and increase pain sensitivity.36 Experimental and clinical studies have repeatedly demonstrated that females generally have lower pain thresholds and less effective pain modulation mechanisms than males.37-39 However, considering that the largest sex differences were observed among participants younger than 60 years, biological factors alone seem insufficient to fully explain these findings.
A more comprehensive explanation involves the “double burden” of labor experienced by many women fishers. In rural settings, women often perform both paid fishery work and unpaid domestic labor, including household chores and caregiving responsibilities for their children and elderly family members.15,30,40-43 This additional unpaid labor may contribute to cumulative physical strain and reduce opportunities for adequate rest and recovery, potentially exacerbating the risk of MSDs. For instance, Osinuga et al.42,43 reported that higher intensities of domestic work among rural Nigerian women were associated with up to a fourfold increase in the risk of lower back, neck, and upper extremity pain. Studies conducted in sex-equal countries such as Sweden, Spain, and New Zealand have also demonstrated that the unequal distribution of domestic labor negatively impacts women's health,40,44,45 suggesting that similar patterns may apply to woman fishers in Korea.
Sex bias in occupational environments and tool design may also contribute to sex differences in the prevalence of MSDs. A survey of workers in New Zealand revealed that even within the same occupation, men and women were exposed to different ergonomic risks. Women were more frequently assigned repetitive or precise tasks that required muscular endurance than those that required brute strength.45 Fishing gear and onboard equipment are typically designed based on the average male body dimensions, potentially causing greater biomechanical strain among females. In a study by Kim and Shin,30 while men handled heavier loads, women often performed tasks requiring kneeling or squatting, which placed more stress on their lower extremities and joints.
Additionally, sex differences in symptom reporting behaviors should be considered.15,46 As Pedulla et al.46 noted that men might perceive pain reporting as a sign of weakness and thus underreport their symptoms, whereas women tend to report symptoms more openly and seek social support. Since our study relied on self-reported survey data, reporting bias may have contributed to the overestimation of sex-related differences. Nonetheless, the persistence of disparities after multiple adjustments supports the presence of genuine differences in the MSD risk between women and men.
Interestingly, sex differences were not significant among participants aged 70 years. Several factors could explain this finding. First, there may be a healthy worker survival effect. Men who perform more physically demanding work may have left fishing earlier because of accidents and illnesses. Second, the negative effects of menopause may diminish with age. Third, the burden of housework may have been reduced because of the growing economic independence of children or overtime for additional income. Among the three body regions, only the upper extremities did not show a significant difference by age group. This may be explained by the fact that unlike the back and knee, the upper extremity joints are non-weight-bearing and, therefore, are relatively less affected by aging.
The strengths of this study include the use of a large data from the fisher health survey, which enabled robust stratification analyses by sex and age. However, the limitations include the cross-sectional design, which precludes causal inference and potential information bias arising from self-reported data. The prevalence estimates are based on a non-representative, voluntary sample of fishers, which may limit the generalizability of the findings to the entire fishing population. Additionally, this study did not quantify key sex-related variables, such as time spent on domestic labor, menopausal status, or muscle mass, limiting our ability to fully explain the underlying mechanisms.
Future studies should incorporate biomechanical exposure assessments and longitudinal designs to clarify the impact of sex-related factors. Intervention studies are also needed to evaluate the effects of multilevel strategies, such as redesigning fishing gear to accommodate female body dimensions, adjusting work schedules to account for domestic labor demands, and ensuring adequate rest periods. Such evidence-based interventions may help prevent MSDs in physically demanding occupations and contribute to protecting the labor and health rights of woman workers.
CONCLUSIONS
This study confirmed that women fishers in Korea have a consistently higher risk of MSDs than man fishers, even after adjusting for age, socioeconomic status, and occupational factors. These findings indicate that sex differences in MSD prevalence arise from a complex interplay of factors, including biological vulnerability, the double burden of paid and unpaid labor, sex-biased occupational tasks and equipment design, and differences in symptom-reporting behaviors. Therefore, preventive and management strategies for MSDs in fishers should integrate sex-sensitive, multidimensional approaches that address both occupational exposure and broader social determinants of health.
Abbreviations
CI
confidence interval
MSD
musculoskeletal disability
ODI
Oswestry Disability Index
PR
prevalence ratio
QuickDASH
Quick Disabilities of the Arm, Shoulder, and Hand
WOMAC-SF
Western Ontario and McMaster Universities Arthritis Index Short Form
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Funding
This study was supported by research funds from the Ministry of Oceans and Fisheries Affairs of the Republic of Korea.
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Competing interests
Hansoo Song contributing editors of the Annals of Occupational and Environmental Medicine, was not involved in the editorial evaluation or decision to publish this article. All remaining authors have declared no conflicts of interest.
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Author contributions
Conceptualization: Song H. Data curation: Song H, Kim HM, Ju BG, Park SH. Formal analysis: Song H. Funding acquisition: Song H. Investigation: Song H, Ju BG, Kim HM, Park SH, Park KS, Kim JH. Methodology: Song H. Software: Kim HM. Validation: Song H, Kim HM. Visualization: Song H. Writing - original draft: Kim HM. Writing - review & editing: Song H, Park KS, Kim JH.
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Acknowledgments
The authors thank the Ministry of Oceans and Fisheries Affairs of the Republic of Korea.
NOTES
Table 1.
General characteristics of study participants by sex
Table 2.
Physical strain levels of the study participants according to sex
Table 3.
Prevalence of MSD by sex, age, and body region
Table 4.
Multivariate modified Poisson regression analysis of musculoskeletal disability according to sex
Model 1: adjusted for age.
Model 2: adjusted for age, education, annual household income, concurrent employment, and ownership status.
Model 3: adjusted for model 2 + fishery type and fishing labor hour/year.
Model 4: adjusted for model 2 + physical strain level (upper extremity: hand and shoulder strain levels, back: back strain level, knee: knee strain level).
PR: prevalence ratio; CI: confidence interval calculated using modified Poisson regression with robust variance.
Table 5.
Adjusted prevalence ratios of musculoskeletal disability in women compared to men by age group (model 4)
Men served as the reference group (PR = 1.00).
The PRs and 95% CIs were calculated using Poisson regression.
Adjusted for education level, annual household income, concurrent employment status, ownership status, and physical strain level (upper extremities: hand and shoulder strain level; back: back strain level; knee: knee strain level).
PR: prevalence ratio; CI: confidence interval.
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Sex difference in musculoskeletal disabilities among Korean fishers: a cross-sectional study
Sex difference in musculoskeletal disabilities among Korean fishers: a cross-sectional study
| Variable | Men | Women | Total | p-value |
|---|---|---|---|---|
| Age (years) | ||||
| <60 | 156 (30.4) | 144 (37.4) | 300 (33.4) | 0.074 |
| 60–69 | 245 (47.8) | 171 (44.4) | 416 (46.3) | |
| ≥70 | 112 (21.8) | 70 (18.2) | 182 (20.3) | |
| Mean ± SD | 62.4 ± 9.4 | 61.7 ± 8.1 | 62.1 ± 8.9 | |
| Education level | ||||
| High school | 259 (50.5) | 136 (35.3) | 395 (44.0) | <0.001 |
| Middle school | 144 (28.1) | 76 (19.7) | 220 (24.5) | |
| Elementary | 110 (21.4) | 173 (44.9) | 283 (31.5) | |
| Annual household income (10,000 KRW) | ||||
| ≥5,000 | 141 (27.5) | 79 (20.5) | 220 (24.5) | <0.001 |
| 2,000–4,999 | 241 (47.0) | 160 (41.6) | 401 (44.7) | |
| <2,000 | 131 (25.5) | 146 (37.9) | 277 (30.8) | |
| Concurrent employment status | ||||
| Fishing only | 252 (49.1) | 181 (47.0) | 433 (48.2) | 0.531 |
| Concurrent employment | 261 (50.9) | 204 (53.0) | 465 (51.8) | |
| Ownership status | ||||
| Owner | 434 (84.6) | 113 (29.4) | 547 (60.9) | <0.001 |
| Non-owner | 79 (15.4) | 272 (70.6) | 351 (39.1) | |
| Type of fishery | ||||
| Vessel | 250 (48.7) | 119 (30.9) | 369 (41.1) | <0.001 |
| Aquaculture | 73 (14.2) | 42 (10.9) | 115 (12.8) | |
| Diving/bare-handed | 37 (7.2) | 76 (19.7) | 113 (12.6) | |
| Mixed | 153 (29.8) | 148 (38.4) | 301 (33.5) | |
| Fishing labor (hour/year) | ||||
| <1,000 | 363 (70.8) | 303 (78.7) | 666 (74.2) | 0.011 |
| 1,000–1,999 | 83 (16.2) | 53 (13.8) | 136 (15.1) | |
| ≥2,000 | 67 (13.1) | 29 (7.5) | 96 (10.7) | |
| Mean ± SD | 983.9 ± 1,236.3 | 688.4 ± 690.9 | 857.2 ± 1,047.9 | |
| Total labor (hour/year) | ||||
| <1,000 | 273 (53.2) | 234 (60.8) | 507 (56.5) | 0.029 |
| 1,000–1,999 | 150 (29.2) | 105 (27.3) | 255 (28.4) | |
| ≥2,000 | 90 (17.5) | 46 (11.9) | 136 (15.1) | |
| Mean ± SD | 1,265.9 ± 1,211.1 | 1,001.1 ± 748.6 | 1,152.3 ± 1,046.1 | |
| Total | 513 (57.1) | 385 (42.9) | 898 (100.0) |
| Body region | Strain score (points) | Men (n = 513, 57.1%) | Women (n = 385, 42.9%) | Total (n = 898) | p-value |
|---|---|---|---|---|---|
| Upper extremity: hand | <250 | 224 (43.7) | 155 (40.3) | 379 (42.2) | 0.672 |
| 250–499 | 127 (24.8) | 94 (24.4) | 221 (24.6) | ||
| 500–749 | 61 (11.9) | 51 (13.3) | 112 (12.5) | ||
| ≥750 | 101 (19.7) | 85 (22.1) | 186 (20.7) | ||
| Mean ± SD | 447.7 ± 476.8 | 476.4 ± 459.6 | 460.0 ± 469.4 | ||
| Upper extremity: shoulder | <250 | 211 (41.1) | 172 (44.7) | 383 (42.7) | 0.363 |
| 250–499 | 121 (23.6) | 92 (23.9) | 213 (23.7) | ||
| 500–749 | 79 (15.4) | 44 (11.4) | 123 (13.7) | ||
| ≥750 | 102 (19.9) | 77 (20.0) | 179 (19.9) | ||
| Mean±SD | 476.8 ± 490.2 | 439.9 ± 458.7 | 461.0 ± 477.0 | ||
| Back | <250 | 214 (41.7) | 147 (38.2) | 361 (40.2) | 0.461 |
| 250–499 | 114 (22.2) | 102 (26.5) | 216 (24.1) | ||
| 500–749 | 67 (13.1) | 46 (12.0) | 113 (12.6) | ||
| ≥750 | 118 (23.0) | 90 (23.4) | 208 (23.2) | ||
| Mean±SD | 492.0 ± 497.2 | 487.4 ± 460.9 | 490.0 ± 481.6 | ||
| Knee | <250 | 259 (50.5) | 159 (41.3) | 418 (46.6) | 0.056 |
| 250–499 | 113 (22.0) | 101 (26.2) | 214 (23.8) | ||
| 500–749 | 60 (11.7) | 51 (13.3) | 111 (12.4) | ||
| ≥750 | 81 (15.8) | 74 (19.2) | 155 (17.3) | ||
| Mean ± SD | 396.5 ± 483.8 | 429.1 ± 423.4 | 410.5 ± 458.9 |
| Age (years) | No. | Upper extremity | Back | Knee | |||
|---|---|---|---|---|---|---|---|
| No. (%) | p-value | No. (%) | p-value | No. (%) | p-value | ||
| Man | |||||||
| <60 | 156 | 22 (14.1) | 0.203 | 15 (9.6) | <0.001 | 20 (12.8) | <0.001 |
| 60–69 | 245 | 50 (20.4) | 49 (20.0) | 47 (19.2) | |||
| ≥70 | 112 | 24 (21.4) | 35 (31.3) | 37 (33.0) | |||
| Total | 513 | 96 (18.7) | 99 (19.3) | 104 (20.3) | |||
| Woman | |||||||
| <60 | 144 | 37 (25.7) | 0.132 | 37 (25.7) | 0.013 | 35 (24.3) | 0.012 |
| 60–69 | 171 | 62 (36.3) | 67 (39.2) | 66 (38.6) | |||
| ≥70 | 70 | 22 (31.4) | 30 (42.9) | 28 (40.0) | |||
| Total | 385 | 121 (31.4) | 134 (34.8) | 129 (33.5) | |||
| Model | Upper extremity | Back | Knee | ||||
|---|---|---|---|---|---|---|---|
| PR | 95% CI | PR | 95% CI | PR | 95% CI | ||
| Unadjusted | Men | 1.00 | 1.00 | 1.00 | |||
| Women | 1.68 | 1.33–2.12 | 1.80 | 1.44–2.26 | 1.65 | 1.32–2.06 | |
| Model 1 | Men | 1.00 | 1.00 | 1.00 | |||
| Women | 1.72 | 1.36–2.16 | 1.88 | 1.51–2.34 | 1.72 | 1.38–2.14 | |
| Model 2 | Men | 1.00 | 1.00 | 1.00 | |||
| Women | 1.52 | 1.14–2.05 | 1.63 | 1.25–2.14 | 1.50 | 1.14–1.97 | |
| Model 3 | Men | 1.00 | 1.00 | 1.00 | |||
| Women | 1.46 | 1.09–1.97 | 1.57 | 1.20–2.05 | 1.47 | 1.11–1.94 | |
| Model 4 | Men | 1.00 | 1.00 | 1.00 | |||
| Women | 1.59 | 1.19–2.13 | 1.63 | 1.25–2.11 | 1.44 | 1.10–1.88 | |
| Age (years) | Upper extremity | Back | Knee | |||
|---|---|---|---|---|---|---|
| PR | 95% CI | PR | 95% CI | PR | 95% CI | |
| <60 | 1.66 | 0.98–2.84 | 2.73 | 1.50–4.97 | 1.71 | 1.00–2.90 |
| 60–69 | 1.66 | 1.07–2.59 | 1.45 | 0.96–2.18 | 1.58 | 1.02–2.44 |
| ≥70 | 1.5 | 0.82–2.74 | 1.36 | 0.89–2.08 | 1.31 | 0.83–2.08 |
| Total | 1.59 | 1.19–2.13 | 1.63 | 1.25–2.11 | 1.44 | 1.10–1.88 |
Table 1. General characteristics of study participants by sex
Values are presented as number (%). SD: standard deviation.
Table 2. Physical strain levels of the study participants according to sex
Values are presented as number (%). SD: standard deviation.
Table 3. Prevalence of MSD by sex, age, and body region
MSD: musculoskeletal disability.
Table 4. Multivariate modified Poisson regression analysis of musculoskeletal disability according to sex
Model 1: adjusted for age. Model 2: adjusted for age, education, annual household income, concurrent employment, and ownership status. Model 3: adjusted for model 2 + fishery type and fishing labor hour/year. Model 4: adjusted for model 2 + physical strain level (upper extremity: hand and shoulder strain levels, back: back strain level, knee: knee strain level). PR: prevalence ratio; CI: confidence interval calculated using modified Poisson regression with robust variance.
Table 5. Adjusted prevalence ratios of musculoskeletal disability in women compared to men by age group (model 4)
Men served as the reference group (PR = 1.00). The PRs and 95% CIs were calculated using Poisson regression. Adjusted for education level, annual household income, concurrent employment status, ownership status, and physical strain level (upper extremities: hand and shoulder strain level; back: back strain level; knee: knee strain level). PR: prevalence ratio; CI: confidence interval.
