Angelo d'Errico1, Francesca Gallo2, Bradley A Evanoff3, Alexis Descatha4,5,6, Ann M Dale3. 1. Epidemiology Department, Local Health Unit TO3, Grugliasco, Italy. 2. National Institute of Statistics, ISTAT, Rome, Italy. 3. School of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA. 4. Inserm, Irset UMR1085 Equipe Ester, Université d'Angers, d'Angers, France. 5. Department of Occupational Medicine, Epidemiology and Prevention, Donald and Barbara Zucker School of Medicine, Hostra, Northwell, USA. 6. Centre Antipoison et de Toxicovigilance Grand Ouest, CDC (Centre de Données Cliniques), CHU, d'Angers, France.
Abstract
BACKGROUND: Comparison between cross-national job-exposure matrices (JEMs) may provide indications of their reliability, particularly if created using the same items. This study evaluated concordance between two JEMs created from United States (US) and Italian O*NET data, using job codes linked through international job codes. METHODS: Twenty-one physical exposures were obtained from the US and Italian O*NET databases. Italian O*NET items were direct translations of US O*NET items. Six hundred and eighty-four US and 586 Italian job codes were linked via crosswalks to 281 ISCO-08 job codes. A sensitivity study also assessed concordance on 258 jobs matched one-to-one across the two national job classifications. Concordance of US and Italian O*NET exposures was estimated by intraclass correlation coefficients (ICC) in multilevel models adjusted and not adjusted for country. RESULTS: ICCs showed moderate to poor agreement for all physical exposures in jobs linked through ISCO-08 codes. There was good to moderate agreement for 14 out of 21 exposures in models with one-to-one matched jobs between countries; greater agreement was found in all models adjusted for country. Exposure to whole-body vibration, time standing, and working outdoor exposed to weather showed the highest agreement. CONCLUSIONS: These results showed moderate to good agreement for most physical exposures across the two JEMs when US and Italian jobs were matched one-to-one and the analysis was adjusted for country. Job code assignments through crosswalks and differences in exposure levels between countries might greatly influence the observed cross-country agreement. Future multinational epidemiological studies should consider the quality of the cross-national job matching, and potential cross-national differences in exposure levels.
BACKGROUND: Comparison between cross-national job-exposure matrices (JEMs) may provide indications of their reliability, particularly if created using the same items. This study evaluated concordance between two JEMs created from United States (US) and Italian O*NET data, using job codes linked through international job codes. METHODS: Twenty-one physical exposures were obtained from the US and Italian O*NET databases. Italian O*NET items were direct translations of US O*NET items. Six hundred and eighty-four US and 586 Italian job codes were linked via crosswalks to 281 ISCO-08 job codes. A sensitivity study also assessed concordance on 258 jobs matched one-to-one across the two national job classifications. Concordance of US and Italian O*NET exposures was estimated by intraclass correlation coefficients (ICC) in multilevel models adjusted and not adjusted for country. RESULTS: ICCs showed moderate to poor agreement for all physical exposures in jobs linked through ISCO-08 codes. There was good to moderate agreement for 14 out of 21 exposures in models with one-to-one matched jobs between countries; greater agreement was found in all models adjusted for country. Exposure to whole-body vibration, time standing, and working outdoor exposed to weather showed the highest agreement. CONCLUSIONS: These results showed moderate to good agreement for most physical exposures across the two JEMs when US and Italian jobs were matched one-to-one and the analysis was adjusted for country. Job code assignments through crosswalks and differences in exposure levels between countries might greatly influence the observed cross-country agreement. Future multinational epidemiological studies should consider the quality of the cross-national job matching, and potential cross-national differences in exposure levels.
Authors: Jennifer C D'Souza; W Monroe Keyserling; Robert A Werner; Brenda Gillespie; Alfred Franzblau Journal: Am J Ind Med Date: 2007-08 Impact factor: 2.214
Authors: Ann Marie Dale; Angelique Zeringue; Carisa Harris-Adamson; David Rempel; Stephen Bao; Matthew S Thiese; Linda Merlino; Susan Burt; Jay Kapellusch; Arun Garg; Fred Gerr; Kurt T Hegmann; Ellen A Eisen; Bradley Evanoff Journal: Am J Epidemiol Date: 2015-02-19 Impact factor: 4.897
Authors: Bethany T Gardner; David A Lombardi; Ann Marie Dale; Alfred Franzblau; Bradley A Evanoff Journal: Occup Environ Med Date: 2010-04-21 Impact factor: 4.402
Authors: Ida E H Madsen; Nidhi Gupta; Esben Budtz-Jørgensen; Jens Peter Bonde; Elisabeth Framke; Esben Meulengracht Flachs; Sesilje Bondo Petersen; Annemette Coop Svane-Petersen; Andreas Holtermann; Reiner Rugulies Journal: Occup Environ Med Date: 2018-07-25 Impact factor: 4.402