Workers’ Health Surveillance in the Meat Processing Industry: Work and Health Indicators Associated with Work Ability

Abstract Background Workers’ health surveillance (WHS) programs commonly measure a large number of indicators addressing health habits and health risks. Recently, work ability and functional capacity have been included as important risk measures in WHS. In order to address work ability appropriately...
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Autor*in:	van Holland, Berry J. [verfasserIn] Soer, Remko [verfasserIn] de Boer, Michiel R. [verfasserIn] Reneman, Michiel F. [verfasserIn] Brouwer, Sandra [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2015

Schlagwörter:	Occupational health Health risk appraisal Work ability Functional capacity evaluation Meat-packing industry

Übergeordnetes Werk:	Enthalten in: The journal of occupational rehabilitation - Dordrecht [u.a.] : Springer Science + Business Media B.V., 1991, 25(2015), 3 vom: 13. Feb., Seite 618-626
Übergeordnetes Werk:	volume:25 ; year:2015 ; number:3 ; day:13 ; month:02 ; pages:618-626

Links:	Volltext

DOI / URN:	10.1007/s10926-015-9569-2

Katalog-ID:	SPR014691043

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520			\|a Abstract Background Workers’ health surveillance (WHS) programs commonly measure a large number of indicators addressing health habits and health risks. Recently, work ability and functional capacity have been included as important risk measures in WHS. In order to address work ability appropriately, knowledge of associations with work and health measures is necessary. The objective of this study was to evaluate which of the factors measured in a WHS are independently associated with work ability in a group of meat processing workers. Methods A cross-sectional study was performed in a large meat processing company in The Netherlands. Data were collected during a WHS between February 2012 and March 2014. Personal characteristics, health habits and health-risk indicators, functional capacity, and work-related factors were measured. Work ability was measured with the Work Ability Index and was used as dependent variable. Univariable and multivariable logistic regression analyses were conducted, a receiver operating characteristic curve was constructed and the area under the curve (AUC) was calculated. Results Data sets from 230 employees were used for analyses. The average age was 53 years and the average work ability index score was 39.3. In the final multivariable model age (OR 0.94), systolic blood pressure (OR 1.03), need for recovery (OR 0.56), and overhead work capacity (OR 3.95) contributed significantly. The AUC for this model was 0.81 (95 % CI 0.75–0.86). Conclusion Findings from the current study indicate that multifactorial outcomes (age, systolic blood pressure, need for recovery, and overhead work capacity) from a WHS were independently associated with work ability. These factors can be used to assess employees at risk for low work ability and might provide directions for interventions.
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650		4	\|a Meat-packing industry \|7 (dpeaa)DE-He213
700	1		\|a Soer, Remko \|e verfasserin \|4 aut
700	1		\|a de Boer, Michiel R. \|e verfasserin \|4 aut
700	1		\|a Reneman, Michiel F. \|e verfasserin \|4 aut
700	1		\|a Brouwer, Sandra \|e verfasserin \|4 aut
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allfields	10.1007/s10926-015-9569-2 doi (DE-627)SPR014691043 (SPR)s10926-015-9569-2-e DE-627 ger DE-627 rakwb eng 610 ASE 44.52 bkl van Holland, Berry J. verfasserin aut Workers’ Health Surveillance in the Meat Processing Industry: Work and Health Indicators Associated with Work Ability 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Workers’ health surveillance (WHS) programs commonly measure a large number of indicators addressing health habits and health risks. Recently, work ability and functional capacity have been included as important risk measures in WHS. In order to address work ability appropriately, knowledge of associations with work and health measures is necessary. The objective of this study was to evaluate which of the factors measured in a WHS are independently associated with work ability in a group of meat processing workers. Methods A cross-sectional study was performed in a large meat processing company in The Netherlands. Data were collected during a WHS between February 2012 and March 2014. Personal characteristics, health habits and health-risk indicators, functional capacity, and work-related factors were measured. Work ability was measured with the Work Ability Index and was used as dependent variable. Univariable and multivariable logistic regression analyses were conducted, a receiver operating characteristic curve was constructed and the area under the curve (AUC) was calculated. Results Data sets from 230 employees were used for analyses. The average age was 53 years and the average work ability index score was 39.3. In the final multivariable model age (OR 0.94), systolic blood pressure (OR 1.03), need for recovery (OR 0.56), and overhead work capacity (OR 3.95) contributed significantly. The AUC for this model was 0.81 (95 % CI 0.75–0.86). Conclusion Findings from the current study indicate that multifactorial outcomes (age, systolic blood pressure, need for recovery, and overhead work capacity) from a WHS were independently associated with work ability. These factors can be used to assess employees at risk for low work ability and might provide directions for interventions. Occupational health (dpeaa)DE-He213 Health risk appraisal (dpeaa)DE-He213 Work ability (dpeaa)DE-He213 Functional capacity evaluation (dpeaa)DE-He213 Meat-packing industry (dpeaa)DE-He213 Soer, Remko verfasserin aut de Boer, Michiel R. verfasserin aut Reneman, Michiel F. verfasserin aut Brouwer, Sandra verfasserin aut Enthalten in The journal of occupational rehabilitation Dordrecht [u.a.] : Springer Science + Business Media B.V., 1991 25(2015), 3 vom: 13. Feb., Seite 618-626 (DE-627)320575802 (DE-600)2017035-X 1573-3688 nnns volume:25 year:2015 number:3 day:13 month:02 pages:618-626 https://dx.doi.org/10.1007/s10926-015-9569-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.52 ASE AR 25 2015 3 13 02 618-626
spelling	10.1007/s10926-015-9569-2 doi (DE-627)SPR014691043 (SPR)s10926-015-9569-2-e DE-627 ger DE-627 rakwb eng 610 ASE 44.52 bkl van Holland, Berry J. verfasserin aut Workers’ Health Surveillance in the Meat Processing Industry: Work and Health Indicators Associated with Work Ability 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Workers’ health surveillance (WHS) programs commonly measure a large number of indicators addressing health habits and health risks. Recently, work ability and functional capacity have been included as important risk measures in WHS. In order to address work ability appropriately, knowledge of associations with work and health measures is necessary. The objective of this study was to evaluate which of the factors measured in a WHS are independently associated with work ability in a group of meat processing workers. Methods A cross-sectional study was performed in a large meat processing company in The Netherlands. Data were collected during a WHS between February 2012 and March 2014. Personal characteristics, health habits and health-risk indicators, functional capacity, and work-related factors were measured. Work ability was measured with the Work Ability Index and was used as dependent variable. Univariable and multivariable logistic regression analyses were conducted, a receiver operating characteristic curve was constructed and the area under the curve (AUC) was calculated. Results Data sets from 230 employees were used for analyses. The average age was 53 years and the average work ability index score was 39.3. In the final multivariable model age (OR 0.94), systolic blood pressure (OR 1.03), need for recovery (OR 0.56), and overhead work capacity (OR 3.95) contributed significantly. The AUC for this model was 0.81 (95 % CI 0.75–0.86). Conclusion Findings from the current study indicate that multifactorial outcomes (age, systolic blood pressure, need for recovery, and overhead work capacity) from a WHS were independently associated with work ability. These factors can be used to assess employees at risk for low work ability and might provide directions for interventions. Occupational health (dpeaa)DE-He213 Health risk appraisal (dpeaa)DE-He213 Work ability (dpeaa)DE-He213 Functional capacity evaluation (dpeaa)DE-He213 Meat-packing industry (dpeaa)DE-He213 Soer, Remko verfasserin aut de Boer, Michiel R. verfasserin aut Reneman, Michiel F. verfasserin aut Brouwer, Sandra verfasserin aut Enthalten in The journal of occupational rehabilitation Dordrecht [u.a.] : Springer Science + Business Media B.V., 1991 25(2015), 3 vom: 13. Feb., Seite 618-626 (DE-627)320575802 (DE-600)2017035-X 1573-3688 nnns volume:25 year:2015 number:3 day:13 month:02 pages:618-626 https://dx.doi.org/10.1007/s10926-015-9569-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.52 ASE AR 25 2015 3 13 02 618-626
allfields_unstemmed	10.1007/s10926-015-9569-2 doi (DE-627)SPR014691043 (SPR)s10926-015-9569-2-e DE-627 ger DE-627 rakwb eng 610 ASE 44.52 bkl van Holland, Berry J. verfasserin aut Workers’ Health Surveillance in the Meat Processing Industry: Work and Health Indicators Associated with Work Ability 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Workers’ health surveillance (WHS) programs commonly measure a large number of indicators addressing health habits and health risks. Recently, work ability and functional capacity have been included as important risk measures in WHS. In order to address work ability appropriately, knowledge of associations with work and health measures is necessary. The objective of this study was to evaluate which of the factors measured in a WHS are independently associated with work ability in a group of meat processing workers. Methods A cross-sectional study was performed in a large meat processing company in The Netherlands. Data were collected during a WHS between February 2012 and March 2014. Personal characteristics, health habits and health-risk indicators, functional capacity, and work-related factors were measured. Work ability was measured with the Work Ability Index and was used as dependent variable. Univariable and multivariable logistic regression analyses were conducted, a receiver operating characteristic curve was constructed and the area under the curve (AUC) was calculated. Results Data sets from 230 employees were used for analyses. The average age was 53 years and the average work ability index score was 39.3. In the final multivariable model age (OR 0.94), systolic blood pressure (OR 1.03), need for recovery (OR 0.56), and overhead work capacity (OR 3.95) contributed significantly. The AUC for this model was 0.81 (95 % CI 0.75–0.86). Conclusion Findings from the current study indicate that multifactorial outcomes (age, systolic blood pressure, need for recovery, and overhead work capacity) from a WHS were independently associated with work ability. These factors can be used to assess employees at risk for low work ability and might provide directions for interventions. Occupational health (dpeaa)DE-He213 Health risk appraisal (dpeaa)DE-He213 Work ability (dpeaa)DE-He213 Functional capacity evaluation (dpeaa)DE-He213 Meat-packing industry (dpeaa)DE-He213 Soer, Remko verfasserin aut de Boer, Michiel R. verfasserin aut Reneman, Michiel F. verfasserin aut Brouwer, Sandra verfasserin aut Enthalten in The journal of occupational rehabilitation Dordrecht [u.a.] : Springer Science + Business Media B.V., 1991 25(2015), 3 vom: 13. Feb., Seite 618-626 (DE-627)320575802 (DE-600)2017035-X 1573-3688 nnns volume:25 year:2015 number:3 day:13 month:02 pages:618-626 https://dx.doi.org/10.1007/s10926-015-9569-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.52 ASE AR 25 2015 3 13 02 618-626
allfieldsGer	10.1007/s10926-015-9569-2 doi (DE-627)SPR014691043 (SPR)s10926-015-9569-2-e DE-627 ger DE-627 rakwb eng 610 ASE 44.52 bkl van Holland, Berry J. verfasserin aut Workers’ Health Surveillance in the Meat Processing Industry: Work and Health Indicators Associated with Work Ability 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Workers’ health surveillance (WHS) programs commonly measure a large number of indicators addressing health habits and health risks. Recently, work ability and functional capacity have been included as important risk measures in WHS. In order to address work ability appropriately, knowledge of associations with work and health measures is necessary. The objective of this study was to evaluate which of the factors measured in a WHS are independently associated with work ability in a group of meat processing workers. Methods A cross-sectional study was performed in a large meat processing company in The Netherlands. Data were collected during a WHS between February 2012 and March 2014. Personal characteristics, health habits and health-risk indicators, functional capacity, and work-related factors were measured. Work ability was measured with the Work Ability Index and was used as dependent variable. Univariable and multivariable logistic regression analyses were conducted, a receiver operating characteristic curve was constructed and the area under the curve (AUC) was calculated. Results Data sets from 230 employees were used for analyses. The average age was 53 years and the average work ability index score was 39.3. In the final multivariable model age (OR 0.94), systolic blood pressure (OR 1.03), need for recovery (OR 0.56), and overhead work capacity (OR 3.95) contributed significantly. The AUC for this model was 0.81 (95 % CI 0.75–0.86). Conclusion Findings from the current study indicate that multifactorial outcomes (age, systolic blood pressure, need for recovery, and overhead work capacity) from a WHS were independently associated with work ability. These factors can be used to assess employees at risk for low work ability and might provide directions for interventions. Occupational health (dpeaa)DE-He213 Health risk appraisal (dpeaa)DE-He213 Work ability (dpeaa)DE-He213 Functional capacity evaluation (dpeaa)DE-He213 Meat-packing industry (dpeaa)DE-He213 Soer, Remko verfasserin aut de Boer, Michiel R. verfasserin aut Reneman, Michiel F. verfasserin aut Brouwer, Sandra verfasserin aut Enthalten in The journal of occupational rehabilitation Dordrecht [u.a.] : Springer Science + Business Media B.V., 1991 25(2015), 3 vom: 13. Feb., Seite 618-626 (DE-627)320575802 (DE-600)2017035-X 1573-3688 nnns volume:25 year:2015 number:3 day:13 month:02 pages:618-626 https://dx.doi.org/10.1007/s10926-015-9569-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.52 ASE AR 25 2015 3 13 02 618-626
allfieldsSound	10.1007/s10926-015-9569-2 doi (DE-627)SPR014691043 (SPR)s10926-015-9569-2-e DE-627 ger DE-627 rakwb eng 610 ASE 44.52 bkl van Holland, Berry J. verfasserin aut Workers’ Health Surveillance in the Meat Processing Industry: Work and Health Indicators Associated with Work Ability 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Workers’ health surveillance (WHS) programs commonly measure a large number of indicators addressing health habits and health risks. Recently, work ability and functional capacity have been included as important risk measures in WHS. In order to address work ability appropriately, knowledge of associations with work and health measures is necessary. The objective of this study was to evaluate which of the factors measured in a WHS are independently associated with work ability in a group of meat processing workers. Methods A cross-sectional study was performed in a large meat processing company in The Netherlands. Data were collected during a WHS between February 2012 and March 2014. Personal characteristics, health habits and health-risk indicators, functional capacity, and work-related factors were measured. Work ability was measured with the Work Ability Index and was used as dependent variable. Univariable and multivariable logistic regression analyses were conducted, a receiver operating characteristic curve was constructed and the area under the curve (AUC) was calculated. Results Data sets from 230 employees were used for analyses. The average age was 53 years and the average work ability index score was 39.3. In the final multivariable model age (OR 0.94), systolic blood pressure (OR 1.03), need for recovery (OR 0.56), and overhead work capacity (OR 3.95) contributed significantly. The AUC for this model was 0.81 (95 % CI 0.75–0.86). Conclusion Findings from the current study indicate that multifactorial outcomes (age, systolic blood pressure, need for recovery, and overhead work capacity) from a WHS were independently associated with work ability. These factors can be used to assess employees at risk for low work ability and might provide directions for interventions. Occupational health (dpeaa)DE-He213 Health risk appraisal (dpeaa)DE-He213 Work ability (dpeaa)DE-He213 Functional capacity evaluation (dpeaa)DE-He213 Meat-packing industry (dpeaa)DE-He213 Soer, Remko verfasserin aut de Boer, Michiel R. verfasserin aut Reneman, Michiel F. verfasserin aut Brouwer, Sandra verfasserin aut Enthalten in The journal of occupational rehabilitation Dordrecht [u.a.] : Springer Science + Business Media B.V., 1991 25(2015), 3 vom: 13. Feb., Seite 618-626 (DE-627)320575802 (DE-600)2017035-X 1573-3688 nnns volume:25 year:2015 number:3 day:13 month:02 pages:618-626 https://dx.doi.org/10.1007/s10926-015-9569-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.52 ASE AR 25 2015 3 13 02 618-626
language	English
source	Enthalten in The journal of occupational rehabilitation 25(2015), 3 vom: 13. Feb., Seite 618-626 volume:25 year:2015 number:3 day:13 month:02 pages:618-626
sourceStr	Enthalten in The journal of occupational rehabilitation 25(2015), 3 vom: 13. Feb., Seite 618-626 volume:25 year:2015 number:3 day:13 month:02 pages:618-626
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Occupational health Health risk appraisal Work ability Functional capacity evaluation Meat-packing industry
dewey-raw	610
isfreeaccess_bool	true
container_title	The journal of occupational rehabilitation
authorswithroles_txt_mv	van Holland, Berry J. @@aut@@ Soer, Remko @@aut@@ de Boer, Michiel R. @@aut@@ Reneman, Michiel F. @@aut@@ Brouwer, Sandra @@aut@@
publishDateDaySort_date	2015-02-13T00:00:00Z
hierarchy_top_id	320575802
dewey-sort	3610
id	SPR014691043
language_de	englisch
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Recently, work ability and functional capacity have been included as important risk measures in WHS. In order to address work ability appropriately, knowledge of associations with work and health measures is necessary. The objective of this study was to evaluate which of the factors measured in a WHS are independently associated with work ability in a group of meat processing workers. Methods A cross-sectional study was performed in a large meat processing company in The Netherlands. Data were collected during a WHS between February 2012 and March 2014. Personal characteristics, health habits and health-risk indicators, functional capacity, and work-related factors were measured. Work ability was measured with the Work Ability Index and was used as dependent variable. Univariable and multivariable logistic regression analyses were conducted, a receiver operating characteristic curve was constructed and the area under the curve (AUC) was calculated. Results Data sets from 230 employees were used for analyses. The average age was 53 years and the average work ability index score was 39.3. In the final multivariable model age (OR 0.94), systolic blood pressure (OR 1.03), need for recovery (OR 0.56), and overhead work capacity (OR 3.95) contributed significantly. The AUC for this model was 0.81 (95 % CI 0.75–0.86). Conclusion Findings from the current study indicate that multifactorial outcomes (age, systolic blood pressure, need for recovery, and overhead work capacity) from a WHS were independently associated with work ability. 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author	van Holland, Berry J.
spellingShingle	van Holland, Berry J. ddc 610 bkl 44.52 misc Occupational health misc Health risk appraisal misc Work ability misc Functional capacity evaluation misc Meat-packing industry Workers’ Health Surveillance in the Meat Processing Industry: Work and Health Indicators Associated with Work Ability
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topic_title	610 ASE 44.52 bkl Workers’ Health Surveillance in the Meat Processing Industry: Work and Health Indicators Associated with Work Ability Occupational health (dpeaa)DE-He213 Health risk appraisal (dpeaa)DE-He213 Work ability (dpeaa)DE-He213 Functional capacity evaluation (dpeaa)DE-He213 Meat-packing industry (dpeaa)DE-He213
topic	ddc 610 bkl 44.52 misc Occupational health misc Health risk appraisal misc Work ability misc Functional capacity evaluation misc Meat-packing industry
topic_unstemmed	ddc 610 bkl 44.52 misc Occupational health misc Health risk appraisal misc Work ability misc Functional capacity evaluation misc Meat-packing industry
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title	Workers’ Health Surveillance in the Meat Processing Industry: Work and Health Indicators Associated with Work Ability
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title_full	Workers’ Health Surveillance in the Meat Processing Industry: Work and Health Indicators Associated with Work Ability
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author_browse	van Holland, Berry J. Soer, Remko de Boer, Michiel R. Reneman, Michiel F. Brouwer, Sandra
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title_sort	workers’ health surveillance in the meat processing industry: work and health indicators associated with work ability
title_auth	Workers’ Health Surveillance in the Meat Processing Industry: Work and Health Indicators Associated with Work Ability
abstract	Abstract Background Workers’ health surveillance (WHS) programs commonly measure a large number of indicators addressing health habits and health risks. Recently, work ability and functional capacity have been included as important risk measures in WHS. In order to address work ability appropriately, knowledge of associations with work and health measures is necessary. The objective of this study was to evaluate which of the factors measured in a WHS are independently associated with work ability in a group of meat processing workers. Methods A cross-sectional study was performed in a large meat processing company in The Netherlands. Data were collected during a WHS between February 2012 and March 2014. Personal characteristics, health habits and health-risk indicators, functional capacity, and work-related factors were measured. Work ability was measured with the Work Ability Index and was used as dependent variable. Univariable and multivariable logistic regression analyses were conducted, a receiver operating characteristic curve was constructed and the area under the curve (AUC) was calculated. Results Data sets from 230 employees were used for analyses. The average age was 53 years and the average work ability index score was 39.3. In the final multivariable model age (OR 0.94), systolic blood pressure (OR 1.03), need for recovery (OR 0.56), and overhead work capacity (OR 3.95) contributed significantly. The AUC for this model was 0.81 (95 % CI 0.75–0.86). Conclusion Findings from the current study indicate that multifactorial outcomes (age, systolic blood pressure, need for recovery, and overhead work capacity) from a WHS were independently associated with work ability. These factors can be used to assess employees at risk for low work ability and might provide directions for interventions.
abstractGer	Abstract Background Workers’ health surveillance (WHS) programs commonly measure a large number of indicators addressing health habits and health risks. Recently, work ability and functional capacity have been included as important risk measures in WHS. In order to address work ability appropriately, knowledge of associations with work and health measures is necessary. The objective of this study was to evaluate which of the factors measured in a WHS are independently associated with work ability in a group of meat processing workers. Methods A cross-sectional study was performed in a large meat processing company in The Netherlands. Data were collected during a WHS between February 2012 and March 2014. Personal characteristics, health habits and health-risk indicators, functional capacity, and work-related factors were measured. Work ability was measured with the Work Ability Index and was used as dependent variable. Univariable and multivariable logistic regression analyses were conducted, a receiver operating characteristic curve was constructed and the area under the curve (AUC) was calculated. Results Data sets from 230 employees were used for analyses. The average age was 53 years and the average work ability index score was 39.3. In the final multivariable model age (OR 0.94), systolic blood pressure (OR 1.03), need for recovery (OR 0.56), and overhead work capacity (OR 3.95) contributed significantly. The AUC for this model was 0.81 (95 % CI 0.75–0.86). Conclusion Findings from the current study indicate that multifactorial outcomes (age, systolic blood pressure, need for recovery, and overhead work capacity) from a WHS were independently associated with work ability. These factors can be used to assess employees at risk for low work ability and might provide directions for interventions.
abstract_unstemmed	Abstract Background Workers’ health surveillance (WHS) programs commonly measure a large number of indicators addressing health habits and health risks. Recently, work ability and functional capacity have been included as important risk measures in WHS. In order to address work ability appropriately, knowledge of associations with work and health measures is necessary. The objective of this study was to evaluate which of the factors measured in a WHS are independently associated with work ability in a group of meat processing workers. Methods A cross-sectional study was performed in a large meat processing company in The Netherlands. Data were collected during a WHS between February 2012 and March 2014. Personal characteristics, health habits and health-risk indicators, functional capacity, and work-related factors were measured. Work ability was measured with the Work Ability Index and was used as dependent variable. Univariable and multivariable logistic regression analyses were conducted, a receiver operating characteristic curve was constructed and the area under the curve (AUC) was calculated. Results Data sets from 230 employees were used for analyses. The average age was 53 years and the average work ability index score was 39.3. In the final multivariable model age (OR 0.94), systolic blood pressure (OR 1.03), need for recovery (OR 0.56), and overhead work capacity (OR 3.95) contributed significantly. The AUC for this model was 0.81 (95 % CI 0.75–0.86). Conclusion Findings from the current study indicate that multifactorial outcomes (age, systolic blood pressure, need for recovery, and overhead work capacity) from a WHS were independently associated with work ability. These factors can be used to assess employees at risk for low work ability and might provide directions for interventions.
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container_issue	3
title_short	Workers’ Health Surveillance in the Meat Processing Industry: Work and Health Indicators Associated with Work Ability
url	https://dx.doi.org/10.1007/s10926-015-9569-2
remote_bool	true
author2	Soer, Remko de Boer, Michiel R. Reneman, Michiel F. Brouwer, Sandra
author2Str	Soer, Remko de Boer, Michiel R. Reneman, Michiel F. Brouwer, Sandra
ppnlink	320575802
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hochschulschrift_bool	false
doi_str	10.1007/s10926-015-9569-2
up_date	2024-07-04T02:43:56.032Z
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Recently, work ability and functional capacity have been included as important risk measures in WHS. In order to address work ability appropriately, knowledge of associations with work and health measures is necessary. The objective of this study was to evaluate which of the factors measured in a WHS are independently associated with work ability in a group of meat processing workers. Methods A cross-sectional study was performed in a large meat processing company in The Netherlands. Data were collected during a WHS between February 2012 and March 2014. Personal characteristics, health habits and health-risk indicators, functional capacity, and work-related factors were measured. Work ability was measured with the Work Ability Index and was used as dependent variable. Univariable and multivariable logistic regression analyses were conducted, a receiver operating characteristic curve was constructed and the area under the curve (AUC) was calculated. 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Workers’ Health Surveillance in the Meat Processing Industry: Work and Health Indicators Associated with Work Ability

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