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dc.creatorOmić, Snežana
dc.creatorSpasojević Brkić, Vesna
dc.creatorGolubović, Tamara
dc.creatorBrkić, Aleksandar
dc.creatorKlarin, Milivoj
dc.date.accessioned2022-09-19T18:12:30Z
dc.date.available2022-09-19T18:12:30Z
dc.date.issued2017
dc.identifier.issn1051-9815
dc.identifier.urihttps://machinery.mas.bg.ac.rs/handle/123456789/2600
dc.description.abstractBACKGROUND: There are recent studies using new industrial workers' anthropometric data in different countries, but for Serbia such data are not available. OBJECTIVE: This study is the first anthropometric study of Serbian metal industry workers in the country, whose labor force is increasingly employed both on local and international markets. The metal industry is one of Serbia's most important economic sectors. METHODS: To this end, we collected the basic static anthropometric dimensions of 122 industrial workers and used principal components analysis (PCA) to obtain multivariate anthropometric models. To confirm the results, the dimensions of an additional 50 workers were collected. The PCA methodology was also compared with the percentile method. RESULTS: Comparing both data samples, we found that 96% of the participants are within the tolerance ellipsoid. According to this study, multivariate modeling covers a larger extent of the intended population proportion compared to percentiles. CONCLUSIONS: The results of this research are useful for the designers of metal industry workstations. This information can be used in dimensioning the workplace, thus increasing job satisfaction, reducing the risk of injuries and fatalities, and consequently increasing productivity and safety.en
dc.publisherIOS Press, Amsterdam
dc.rightsrestrictedAccess
dc.sourceWork-A Journal of Prevention Assessment & Rehabilitation
dc.subjectprincipal components analysisen
dc.subjectpercentilesen
dc.subjectAnthropometric measurementsen
dc.titleAn anthropometric study of Serbian metal industry workersen
dc.typearticle
dc.rights.licenseARR
dc.citation.epage265
dc.citation.issue2
dc.citation.other56(2): 257-265
dc.citation.rankM23
dc.citation.spage257
dc.citation.volume56
dc.identifier.doi10.3233/WOR-172482
dc.identifier.pmid28211833
dc.identifier.scopus2-s2.0-85015452076
dc.identifier.wos000396548900009
dc.type.versionpublishedVersion


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