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Population attributable fraction of indicators for musculoskeletal diseases: a cross-sectional study of fishers in Korea

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dc.contributor.authorLee, Jaehoo-
dc.contributor.authorSim, Bohyun-
dc.contributor.authorJu, Bonggyun-
dc.contributor.authorLee, Chul Gab-
dc.contributor.authorPark, Ki-Soo-
dc.contributor.authorKim, Mi-Ji-
dc.contributor.authorKim, Jeong Ho-
dc.contributor.authorKim, Kunhyung-
dc.contributor.authorSong, Hansoo-
dc.date.accessioned2023-01-03T01:34:01Z-
dc.date.available2023-01-03T01:34:01Z-
dc.date.issued2022-09-
dc.identifier.issn1225-3618-
dc.identifier.issn2052-4374-
dc.identifier.urihttps://scholarworks.gnu.ac.kr/handle/sw.gnu/29735-
dc.description.abstractBackground: The musculoskeletal disease (MSD) burden is an important health problem among Korean fishers. We aimed to investigate the indicators of the prevalence of MSD and contributions of significant indicators to MSD in Korean fishers.Methods: This cross-section study included 927 fishers (male, 371; female, 556) aged 40 to 79 years who were enrolled from 3 fishery safety and health centers. The outcome variable was one-year prevalence of MSD in 5 body parts (the neck, shoulder, hand, back, and knee). Independent variables were sex, age, educational attainment, household income, job classification, employment xlink:type, hazardous working environment (cold, heat, and noise), ergonomic risk by the 5 body parts, anxiety disorder, depression, hypertension, diabetes, and hyperlipidemia. The adjusted odds ratio of MSDs by the 5 body parts were calculated using multiple logistic regression analysis. We computed the population attributable fraction (PAF) for each indicators of MSDs using binary regression models.Results: The one-year prevalence of MSD in the neck, shoulder, hand, back, and knee was 7.8%, 17.8%, 7.8%, 27.2%, and 16.2% in males vs. 16.4%, 28.1%, 23.0%, 38.7%, and 30.0% in females, respectively. The ergonomic risk PAF according to the body parts ranged from 22.8%-59.6% in males and 22.8%-50.3% in female. Mental diseases showed a significant PAF for all body parts only among female (PAF 9.1%-21.4%). Cold exposure showed a significant PAF for the neck, shoulder, and hand MSD only among female (25.6%-26.8%). Age was not a significant indicator except for the knee MSD among female.Conclusions: Ergonomic risk contributed majorly as indicators of MSDs in both sexes of fishers. Mental disease and cold exposure were indicators of MSDs only among female fishers. This information may be important for determining priority risk groups for the prevention of work-related MSD among Korean fishers.-
dc.format.extent14-
dc.language영어-
dc.language.isoENG-
dc.publisherBioMed Central-
dc.titlePopulation attributable fraction of indicators for musculoskeletal diseases: a cross-sectional study of fishers in Korea-
dc.title.alternativePopulation attributable fraction of indicators for musculoskeletal diseases: a cross-sectional study of fishers in Korea-
dc.typeArticle-
dc.publisher.location대한민국-
dc.identifier.doi10.35371/aoem.2022.34.e23-
dc.identifier.scopusid2-s2.0-85140727279-
dc.identifier.wosid000859635100001-
dc.identifier.bibliographicCitationAnnals of Occupational and Environmental Medicine, v.34, no.1, pp 1 - 14-
dc.citation.titleAnnals of Occupational and Environmental Medicine-
dc.citation.volume34-
dc.citation.number1-
dc.citation.startPage1-
dc.citation.endPage14-
dc.type.docTypeArticle-
dc.identifier.kciidART002904082-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscopus-
dc.description.journalRegisteredClassesci-
dc.description.journalRegisteredClasskci-
dc.relation.journalResearchAreaPublic, Environmental & Occupational Health-
dc.relation.journalWebOfScienceCategoryPublic, Environmental & Occupational Health-
dc.subject.keywordPlusGLOBAL BURDEN-
dc.subject.keywordPlusPAIN-
dc.subject.keywordPlusDEPRESSION-
dc.subject.keywordPlusDISORDER-
dc.subject.keywordPlusWORK-
dc.subject.keywordPlusCOLD-
dc.subject.keywordAuthorErgonomic risk-
dc.subject.keywordAuthorFisher-
dc.subject.keywordAuthorMusculoskeletal disease-
dc.subject.keywordAuthorPopulation attributable fraction-
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