Predictors of working days lost due to sickness absence and disability pension
Objective To identify social and health-related predictors of the number of days lost due to sickness absence (SA) and disability pension (DP) among initially 55-year-old public-sector workers. Methods The data from the Finnish Helsinki Health Study included participants aged 55 years at the baselin...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Shiri, Rahman [verfasserIn] Hiilamo, Aapo [verfasserIn] Rahkonen, Ossi [verfasserIn] Robroek, Suzan J. W. [verfasserIn] Pietiläinen, Olli [verfasserIn] Lallukka, Tea [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s) 2021 |
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| Übergeordnetes Werk: |
Enthalten in: International archives of occupational and environmental health - Berlin : Springer, 1930, 94(2021), 5 vom: 12. Jan., Seite 843-854 |
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| Übergeordnetes Werk: |
volume:94 ; year:2021 ; number:5 ; day:12 ; month:01 ; pages:843-854 |
| Links: |
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| DOI / URN: |
10.1007/s00420-020-01630-6 |
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| Katalog-ID: |
SPR044417810 |
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| 245 | 1 | 0 | |a Predictors of working days lost due to sickness absence and disability pension |
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| 520 | |a Objective To identify social and health-related predictors of the number of days lost due to sickness absence (SA) and disability pension (DP) among initially 55-year-old public-sector workers. Methods The data from the Finnish Helsinki Health Study included participants aged 55 years at the baseline (in 2000–2002, N = 1630, 81% women), and were enriched with register-based information on SA and DP. The cumulative number of calendar days lost due to SA ≥ 1 day or DP between ages 55 and 65 was calculated. Negative binomial regression model was used to identify the predictors of days lost. Results The average calendar days lost was 316 days (about 220 working days) during a 10-year follow-up, and 44% were due to SA and 56% due to DP. Smoking [incidence rate ratio (IRR) = 1.19, 95% CI 1.01–1.40 for past and IRR = 1.30, CI 1.07–1.58 for current], binge drinking (IRR = 1.22, CI 1.02–1.46), lifting or pulling/pushing heavy loads (IRR = 1.35, CI 1.10–1.65), awkward working positions (IRR = 1.24, CI 1.01–1.53), long-standing illness limiting work or daily activities (IRR = 2.32, CI 1.93–2.79), common mental disorder (IRR = 1.52, CI 1.30–1.79), and multisite pain (IRR = 1.50, CI 1.23–1.84) increased the number of days lost, while high level of education (IRR = 0.66, CI 0.52–0.82) and moderate level of leisure-time physical activity (IRR = 0.80, CI 0.67–0.94) reduced the number of days lost. Conclusions Modifiable lifestyle risk factors, workload factors, common mental disorder, and multisite pain substantially increase the number of days lost. However, the findings of this study could be generalized to female workers in the public sector. Future research should also consider shorter SA spells in estimating working years lost and working life expectancy. | ||
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| 650 | 4 | |a Life expectancy |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Occupations |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Sick leave |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Workload |7 (dpeaa)DE-He213 | |
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| 700 | 1 | |a Rahkonen, Ossi |e verfasserin |4 aut | |
| 700 | 1 | |a Robroek, Suzan J. W. |e verfasserin |4 aut | |
| 700 | 1 | |a Pietiläinen, Olli |e verfasserin |4 aut | |
| 700 | 1 | |a Lallukka, Tea |e verfasserin |4 aut | |
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10.1007/s00420-020-01630-6 doi (DE-627)SPR044417810 (SPR)s00420-020-01630-6-e DE-627 ger DE-627 rakwb eng 610 ASE 44.12 bkl 44.13 bkl Shiri, Rahman verfasserin aut Predictors of working days lost due to sickness absence and disability pension 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2021 Objective To identify social and health-related predictors of the number of days lost due to sickness absence (SA) and disability pension (DP) among initially 55-year-old public-sector workers. Methods The data from the Finnish Helsinki Health Study included participants aged 55 years at the baseline (in 2000–2002, N = 1630, 81% women), and were enriched with register-based information on SA and DP. The cumulative number of calendar days lost due to SA ≥ 1 day or DP between ages 55 and 65 was calculated. Negative binomial regression model was used to identify the predictors of days lost. Results The average calendar days lost was 316 days (about 220 working days) during a 10-year follow-up, and 44% were due to SA and 56% due to DP. Smoking [incidence rate ratio (IRR) = 1.19, 95% CI 1.01–1.40 for past and IRR = 1.30, CI 1.07–1.58 for current], binge drinking (IRR = 1.22, CI 1.02–1.46), lifting or pulling/pushing heavy loads (IRR = 1.35, CI 1.10–1.65), awkward working positions (IRR = 1.24, CI 1.01–1.53), long-standing illness limiting work or daily activities (IRR = 2.32, CI 1.93–2.79), common mental disorder (IRR = 1.52, CI 1.30–1.79), and multisite pain (IRR = 1.50, CI 1.23–1.84) increased the number of days lost, while high level of education (IRR = 0.66, CI 0.52–0.82) and moderate level of leisure-time physical activity (IRR = 0.80, CI 0.67–0.94) reduced the number of days lost. Conclusions Modifiable lifestyle risk factors, workload factors, common mental disorder, and multisite pain substantially increase the number of days lost. However, the findings of this study could be generalized to female workers in the public sector. Future research should also consider shorter SA spells in estimating working years lost and working life expectancy. Chronic disease (dpeaa)DE-He213 Healthy lifestyle (dpeaa)DE-He213 Life expectancy (dpeaa)DE-He213 Occupations (dpeaa)DE-He213 Sick leave (dpeaa)DE-He213 Workload (dpeaa)DE-He213 Work engagement (dpeaa)DE-He213 Hiilamo, Aapo verfasserin aut Rahkonen, Ossi verfasserin aut Robroek, Suzan J. W. verfasserin aut Pietiläinen, Olli verfasserin aut Lallukka, Tea verfasserin aut Enthalten in International archives of occupational and environmental health Berlin : Springer, 1930 94(2021), 5 vom: 12. Jan., Seite 843-854 (DE-627)25372421X (DE-600)1459213-7 1432-1246 nnns volume:94 year:2021 number:5 day:12 month:01 pages:843-854 https://dx.doi.org/10.1007/s00420-020-01630-6 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_65 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_152 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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.12 ASE 44.13 ASE AR 94 2021 5 12 01 843-854 |
| spelling |
10.1007/s00420-020-01630-6 doi (DE-627)SPR044417810 (SPR)s00420-020-01630-6-e DE-627 ger DE-627 rakwb eng 610 ASE 44.12 bkl 44.13 bkl Shiri, Rahman verfasserin aut Predictors of working days lost due to sickness absence and disability pension 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2021 Objective To identify social and health-related predictors of the number of days lost due to sickness absence (SA) and disability pension (DP) among initially 55-year-old public-sector workers. Methods The data from the Finnish Helsinki Health Study included participants aged 55 years at the baseline (in 2000–2002, N = 1630, 81% women), and were enriched with register-based information on SA and DP. The cumulative number of calendar days lost due to SA ≥ 1 day or DP between ages 55 and 65 was calculated. Negative binomial regression model was used to identify the predictors of days lost. Results The average calendar days lost was 316 days (about 220 working days) during a 10-year follow-up, and 44% were due to SA and 56% due to DP. Smoking [incidence rate ratio (IRR) = 1.19, 95% CI 1.01–1.40 for past and IRR = 1.30, CI 1.07–1.58 for current], binge drinking (IRR = 1.22, CI 1.02–1.46), lifting or pulling/pushing heavy loads (IRR = 1.35, CI 1.10–1.65), awkward working positions (IRR = 1.24, CI 1.01–1.53), long-standing illness limiting work or daily activities (IRR = 2.32, CI 1.93–2.79), common mental disorder (IRR = 1.52, CI 1.30–1.79), and multisite pain (IRR = 1.50, CI 1.23–1.84) increased the number of days lost, while high level of education (IRR = 0.66, CI 0.52–0.82) and moderate level of leisure-time physical activity (IRR = 0.80, CI 0.67–0.94) reduced the number of days lost. Conclusions Modifiable lifestyle risk factors, workload factors, common mental disorder, and multisite pain substantially increase the number of days lost. However, the findings of this study could be generalized to female workers in the public sector. Future research should also consider shorter SA spells in estimating working years lost and working life expectancy. Chronic disease (dpeaa)DE-He213 Healthy lifestyle (dpeaa)DE-He213 Life expectancy (dpeaa)DE-He213 Occupations (dpeaa)DE-He213 Sick leave (dpeaa)DE-He213 Workload (dpeaa)DE-He213 Work engagement (dpeaa)DE-He213 Hiilamo, Aapo verfasserin aut Rahkonen, Ossi verfasserin aut Robroek, Suzan J. W. verfasserin aut Pietiläinen, Olli verfasserin aut Lallukka, Tea verfasserin aut Enthalten in International archives of occupational and environmental health Berlin : Springer, 1930 94(2021), 5 vom: 12. Jan., Seite 843-854 (DE-627)25372421X (DE-600)1459213-7 1432-1246 nnns volume:94 year:2021 number:5 day:12 month:01 pages:843-854 https://dx.doi.org/10.1007/s00420-020-01630-6 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_65 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_152 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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.12 ASE 44.13 ASE AR 94 2021 5 12 01 843-854 |
| allfields_unstemmed |
10.1007/s00420-020-01630-6 doi (DE-627)SPR044417810 (SPR)s00420-020-01630-6-e DE-627 ger DE-627 rakwb eng 610 ASE 44.12 bkl 44.13 bkl Shiri, Rahman verfasserin aut Predictors of working days lost due to sickness absence and disability pension 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2021 Objective To identify social and health-related predictors of the number of days lost due to sickness absence (SA) and disability pension (DP) among initially 55-year-old public-sector workers. Methods The data from the Finnish Helsinki Health Study included participants aged 55 years at the baseline (in 2000–2002, N = 1630, 81% women), and were enriched with register-based information on SA and DP. The cumulative number of calendar days lost due to SA ≥ 1 day or DP between ages 55 and 65 was calculated. Negative binomial regression model was used to identify the predictors of days lost. Results The average calendar days lost was 316 days (about 220 working days) during a 10-year follow-up, and 44% were due to SA and 56% due to DP. Smoking [incidence rate ratio (IRR) = 1.19, 95% CI 1.01–1.40 for past and IRR = 1.30, CI 1.07–1.58 for current], binge drinking (IRR = 1.22, CI 1.02–1.46), lifting or pulling/pushing heavy loads (IRR = 1.35, CI 1.10–1.65), awkward working positions (IRR = 1.24, CI 1.01–1.53), long-standing illness limiting work or daily activities (IRR = 2.32, CI 1.93–2.79), common mental disorder (IRR = 1.52, CI 1.30–1.79), and multisite pain (IRR = 1.50, CI 1.23–1.84) increased the number of days lost, while high level of education (IRR = 0.66, CI 0.52–0.82) and moderate level of leisure-time physical activity (IRR = 0.80, CI 0.67–0.94) reduced the number of days lost. Conclusions Modifiable lifestyle risk factors, workload factors, common mental disorder, and multisite pain substantially increase the number of days lost. However, the findings of this study could be generalized to female workers in the public sector. Future research should also consider shorter SA spells in estimating working years lost and working life expectancy. Chronic disease (dpeaa)DE-He213 Healthy lifestyle (dpeaa)DE-He213 Life expectancy (dpeaa)DE-He213 Occupations (dpeaa)DE-He213 Sick leave (dpeaa)DE-He213 Workload (dpeaa)DE-He213 Work engagement (dpeaa)DE-He213 Hiilamo, Aapo verfasserin aut Rahkonen, Ossi verfasserin aut Robroek, Suzan J. W. verfasserin aut Pietiläinen, Olli verfasserin aut Lallukka, Tea verfasserin aut Enthalten in International archives of occupational and environmental health Berlin : Springer, 1930 94(2021), 5 vom: 12. Jan., Seite 843-854 (DE-627)25372421X (DE-600)1459213-7 1432-1246 nnns volume:94 year:2021 number:5 day:12 month:01 pages:843-854 https://dx.doi.org/10.1007/s00420-020-01630-6 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_65 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_152 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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.12 ASE 44.13 ASE AR 94 2021 5 12 01 843-854 |
| allfieldsGer |
10.1007/s00420-020-01630-6 doi (DE-627)SPR044417810 (SPR)s00420-020-01630-6-e DE-627 ger DE-627 rakwb eng 610 ASE 44.12 bkl 44.13 bkl Shiri, Rahman verfasserin aut Predictors of working days lost due to sickness absence and disability pension 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2021 Objective To identify social and health-related predictors of the number of days lost due to sickness absence (SA) and disability pension (DP) among initially 55-year-old public-sector workers. Methods The data from the Finnish Helsinki Health Study included participants aged 55 years at the baseline (in 2000–2002, N = 1630, 81% women), and were enriched with register-based information on SA and DP. The cumulative number of calendar days lost due to SA ≥ 1 day or DP between ages 55 and 65 was calculated. Negative binomial regression model was used to identify the predictors of days lost. Results The average calendar days lost was 316 days (about 220 working days) during a 10-year follow-up, and 44% were due to SA and 56% due to DP. Smoking [incidence rate ratio (IRR) = 1.19, 95% CI 1.01–1.40 for past and IRR = 1.30, CI 1.07–1.58 for current], binge drinking (IRR = 1.22, CI 1.02–1.46), lifting or pulling/pushing heavy loads (IRR = 1.35, CI 1.10–1.65), awkward working positions (IRR = 1.24, CI 1.01–1.53), long-standing illness limiting work or daily activities (IRR = 2.32, CI 1.93–2.79), common mental disorder (IRR = 1.52, CI 1.30–1.79), and multisite pain (IRR = 1.50, CI 1.23–1.84) increased the number of days lost, while high level of education (IRR = 0.66, CI 0.52–0.82) and moderate level of leisure-time physical activity (IRR = 0.80, CI 0.67–0.94) reduced the number of days lost. Conclusions Modifiable lifestyle risk factors, workload factors, common mental disorder, and multisite pain substantially increase the number of days lost. However, the findings of this study could be generalized to female workers in the public sector. Future research should also consider shorter SA spells in estimating working years lost and working life expectancy. Chronic disease (dpeaa)DE-He213 Healthy lifestyle (dpeaa)DE-He213 Life expectancy (dpeaa)DE-He213 Occupations (dpeaa)DE-He213 Sick leave (dpeaa)DE-He213 Workload (dpeaa)DE-He213 Work engagement (dpeaa)DE-He213 Hiilamo, Aapo verfasserin aut Rahkonen, Ossi verfasserin aut Robroek, Suzan J. W. verfasserin aut Pietiläinen, Olli verfasserin aut Lallukka, Tea verfasserin aut Enthalten in International archives of occupational and environmental health Berlin : Springer, 1930 94(2021), 5 vom: 12. Jan., Seite 843-854 (DE-627)25372421X (DE-600)1459213-7 1432-1246 nnns volume:94 year:2021 number:5 day:12 month:01 pages:843-854 https://dx.doi.org/10.1007/s00420-020-01630-6 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_65 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_152 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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.12 ASE 44.13 ASE AR 94 2021 5 12 01 843-854 |
| allfieldsSound |
10.1007/s00420-020-01630-6 doi (DE-627)SPR044417810 (SPR)s00420-020-01630-6-e DE-627 ger DE-627 rakwb eng 610 ASE 44.12 bkl 44.13 bkl Shiri, Rahman verfasserin aut Predictors of working days lost due to sickness absence and disability pension 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2021 Objective To identify social and health-related predictors of the number of days lost due to sickness absence (SA) and disability pension (DP) among initially 55-year-old public-sector workers. Methods The data from the Finnish Helsinki Health Study included participants aged 55 years at the baseline (in 2000–2002, N = 1630, 81% women), and were enriched with register-based information on SA and DP. The cumulative number of calendar days lost due to SA ≥ 1 day or DP between ages 55 and 65 was calculated. Negative binomial regression model was used to identify the predictors of days lost. Results The average calendar days lost was 316 days (about 220 working days) during a 10-year follow-up, and 44% were due to SA and 56% due to DP. Smoking [incidence rate ratio (IRR) = 1.19, 95% CI 1.01–1.40 for past and IRR = 1.30, CI 1.07–1.58 for current], binge drinking (IRR = 1.22, CI 1.02–1.46), lifting or pulling/pushing heavy loads (IRR = 1.35, CI 1.10–1.65), awkward working positions (IRR = 1.24, CI 1.01–1.53), long-standing illness limiting work or daily activities (IRR = 2.32, CI 1.93–2.79), common mental disorder (IRR = 1.52, CI 1.30–1.79), and multisite pain (IRR = 1.50, CI 1.23–1.84) increased the number of days lost, while high level of education (IRR = 0.66, CI 0.52–0.82) and moderate level of leisure-time physical activity (IRR = 0.80, CI 0.67–0.94) reduced the number of days lost. Conclusions Modifiable lifestyle risk factors, workload factors, common mental disorder, and multisite pain substantially increase the number of days lost. However, the findings of this study could be generalized to female workers in the public sector. Future research should also consider shorter SA spells in estimating working years lost and working life expectancy. Chronic disease (dpeaa)DE-He213 Healthy lifestyle (dpeaa)DE-He213 Life expectancy (dpeaa)DE-He213 Occupations (dpeaa)DE-He213 Sick leave (dpeaa)DE-He213 Workload (dpeaa)DE-He213 Work engagement (dpeaa)DE-He213 Hiilamo, Aapo verfasserin aut Rahkonen, Ossi verfasserin aut Robroek, Suzan J. W. verfasserin aut Pietiläinen, Olli verfasserin aut Lallukka, Tea verfasserin aut Enthalten in International archives of occupational and environmental health Berlin : Springer, 1930 94(2021), 5 vom: 12. Jan., Seite 843-854 (DE-627)25372421X (DE-600)1459213-7 1432-1246 nnns volume:94 year:2021 number:5 day:12 month:01 pages:843-854 https://dx.doi.org/10.1007/s00420-020-01630-6 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_65 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_152 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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.12 ASE 44.13 ASE AR 94 2021 5 12 01 843-854 |
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English |
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Enthalten in International archives of occupational and environmental health 94(2021), 5 vom: 12. Jan., Seite 843-854 volume:94 year:2021 number:5 day:12 month:01 pages:843-854 |
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Chronic disease Healthy lifestyle Life expectancy Occupations Sick leave Workload Work engagement |
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International archives of occupational and environmental health |
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Shiri, Rahman @@aut@@ Hiilamo, Aapo @@aut@@ Rahkonen, Ossi @@aut@@ Robroek, Suzan J. W. @@aut@@ Pietiläinen, Olli @@aut@@ Lallukka, Tea @@aut@@ |
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2021-01-12T00:00:00Z |
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Methods The data from the Finnish Helsinki Health Study included participants aged 55 years at the baseline (in 2000–2002, N = 1630, 81% women), and were enriched with register-based information on SA and DP. The cumulative number of calendar days lost due to SA ≥ 1 day or DP between ages 55 and 65 was calculated. Negative binomial regression model was used to identify the predictors of days lost. Results The average calendar days lost was 316 days (about 220 working days) during a 10-year follow-up, and 44% were due to SA and 56% due to DP. Smoking [incidence rate ratio (IRR) = 1.19, 95% CI 1.01–1.40 for past and IRR = 1.30, CI 1.07–1.58 for current], binge drinking (IRR = 1.22, CI 1.02–1.46), lifting or pulling/pushing heavy loads (IRR = 1.35, CI 1.10–1.65), awkward working positions (IRR = 1.24, CI 1.01–1.53), long-standing illness limiting work or daily activities (IRR = 2.32, CI 1.93–2.79), common mental disorder (IRR = 1.52, CI 1.30–1.79), and multisite pain (IRR = 1.50, CI 1.23–1.84) increased the number of days lost, while high level of education (IRR = 0.66, CI 0.52–0.82) and moderate level of leisure-time physical activity (IRR = 0.80, CI 0.67–0.94) reduced the number of days lost. Conclusions Modifiable lifestyle risk factors, workload factors, common mental disorder, and multisite pain substantially increase the number of days lost. However, the findings of this study could be generalized to female workers in the public sector. 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Shiri, Rahman |
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Shiri, Rahman ddc 610 bkl 44.12 bkl 44.13 misc Chronic disease misc Healthy lifestyle misc Life expectancy misc Occupations misc Sick leave misc Workload misc Work engagement Predictors of working days lost due to sickness absence and disability pension |
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610 ASE 44.12 bkl 44.13 bkl Predictors of working days lost due to sickness absence and disability pension Chronic disease (dpeaa)DE-He213 Healthy lifestyle (dpeaa)DE-He213 Life expectancy (dpeaa)DE-He213 Occupations (dpeaa)DE-He213 Sick leave (dpeaa)DE-He213 Workload (dpeaa)DE-He213 Work engagement (dpeaa)DE-He213 |
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Predictors of working days lost due to sickness absence and disability pension |
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predictors of working days lost due to sickness absence and disability pension |
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Predictors of working days lost due to sickness absence and disability pension |
| abstract |
Objective To identify social and health-related predictors of the number of days lost due to sickness absence (SA) and disability pension (DP) among initially 55-year-old public-sector workers. Methods The data from the Finnish Helsinki Health Study included participants aged 55 years at the baseline (in 2000–2002, N = 1630, 81% women), and were enriched with register-based information on SA and DP. The cumulative number of calendar days lost due to SA ≥ 1 day or DP between ages 55 and 65 was calculated. Negative binomial regression model was used to identify the predictors of days lost. Results The average calendar days lost was 316 days (about 220 working days) during a 10-year follow-up, and 44% were due to SA and 56% due to DP. Smoking [incidence rate ratio (IRR) = 1.19, 95% CI 1.01–1.40 for past and IRR = 1.30, CI 1.07–1.58 for current], binge drinking (IRR = 1.22, CI 1.02–1.46), lifting or pulling/pushing heavy loads (IRR = 1.35, CI 1.10–1.65), awkward working positions (IRR = 1.24, CI 1.01–1.53), long-standing illness limiting work or daily activities (IRR = 2.32, CI 1.93–2.79), common mental disorder (IRR = 1.52, CI 1.30–1.79), and multisite pain (IRR = 1.50, CI 1.23–1.84) increased the number of days lost, while high level of education (IRR = 0.66, CI 0.52–0.82) and moderate level of leisure-time physical activity (IRR = 0.80, CI 0.67–0.94) reduced the number of days lost. Conclusions Modifiable lifestyle risk factors, workload factors, common mental disorder, and multisite pain substantially increase the number of days lost. However, the findings of this study could be generalized to female workers in the public sector. Future research should also consider shorter SA spells in estimating working years lost and working life expectancy. © The Author(s) 2021 |
| abstractGer |
Objective To identify social and health-related predictors of the number of days lost due to sickness absence (SA) and disability pension (DP) among initially 55-year-old public-sector workers. Methods The data from the Finnish Helsinki Health Study included participants aged 55 years at the baseline (in 2000–2002, N = 1630, 81% women), and were enriched with register-based information on SA and DP. The cumulative number of calendar days lost due to SA ≥ 1 day or DP between ages 55 and 65 was calculated. Negative binomial regression model was used to identify the predictors of days lost. Results The average calendar days lost was 316 days (about 220 working days) during a 10-year follow-up, and 44% were due to SA and 56% due to DP. Smoking [incidence rate ratio (IRR) = 1.19, 95% CI 1.01–1.40 for past and IRR = 1.30, CI 1.07–1.58 for current], binge drinking (IRR = 1.22, CI 1.02–1.46), lifting or pulling/pushing heavy loads (IRR = 1.35, CI 1.10–1.65), awkward working positions (IRR = 1.24, CI 1.01–1.53), long-standing illness limiting work or daily activities (IRR = 2.32, CI 1.93–2.79), common mental disorder (IRR = 1.52, CI 1.30–1.79), and multisite pain (IRR = 1.50, CI 1.23–1.84) increased the number of days lost, while high level of education (IRR = 0.66, CI 0.52–0.82) and moderate level of leisure-time physical activity (IRR = 0.80, CI 0.67–0.94) reduced the number of days lost. Conclusions Modifiable lifestyle risk factors, workload factors, common mental disorder, and multisite pain substantially increase the number of days lost. However, the findings of this study could be generalized to female workers in the public sector. Future research should also consider shorter SA spells in estimating working years lost and working life expectancy. © The Author(s) 2021 |
| abstract_unstemmed |
Objective To identify social and health-related predictors of the number of days lost due to sickness absence (SA) and disability pension (DP) among initially 55-year-old public-sector workers. Methods The data from the Finnish Helsinki Health Study included participants aged 55 years at the baseline (in 2000–2002, N = 1630, 81% women), and were enriched with register-based information on SA and DP. The cumulative number of calendar days lost due to SA ≥ 1 day or DP between ages 55 and 65 was calculated. Negative binomial regression model was used to identify the predictors of days lost. Results The average calendar days lost was 316 days (about 220 working days) during a 10-year follow-up, and 44% were due to SA and 56% due to DP. Smoking [incidence rate ratio (IRR) = 1.19, 95% CI 1.01–1.40 for past and IRR = 1.30, CI 1.07–1.58 for current], binge drinking (IRR = 1.22, CI 1.02–1.46), lifting or pulling/pushing heavy loads (IRR = 1.35, CI 1.10–1.65), awkward working positions (IRR = 1.24, CI 1.01–1.53), long-standing illness limiting work or daily activities (IRR = 2.32, CI 1.93–2.79), common mental disorder (IRR = 1.52, CI 1.30–1.79), and multisite pain (IRR = 1.50, CI 1.23–1.84) increased the number of days lost, while high level of education (IRR = 0.66, CI 0.52–0.82) and moderate level of leisure-time physical activity (IRR = 0.80, CI 0.67–0.94) reduced the number of days lost. Conclusions Modifiable lifestyle risk factors, workload factors, common mental disorder, and multisite pain substantially increase the number of days lost. However, the findings of this study could be generalized to female workers in the public sector. Future research should also consider shorter SA spells in estimating working years lost and working life expectancy. © The Author(s) 2021 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR044417810</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230519090815.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">210629s2021 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00420-020-01630-6</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR044417810</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s00420-020-01630-6-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.12</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.13</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Shiri, Rahman</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Predictors of working days lost due to sickness absence and disability pension</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2021</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s) 2021</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Objective To identify social and health-related predictors of the number of days lost due to sickness absence (SA) and disability pension (DP) among initially 55-year-old public-sector workers. Methods The data from the Finnish Helsinki Health Study included participants aged 55 years at the baseline (in 2000–2002, N = 1630, 81% women), and were enriched with register-based information on SA and DP. The cumulative number of calendar days lost due to SA ≥ 1 day or DP between ages 55 and 65 was calculated. Negative binomial regression model was used to identify the predictors of days lost. Results The average calendar days lost was 316 days (about 220 working days) during a 10-year follow-up, and 44% were due to SA and 56% due to DP. Smoking [incidence rate ratio (IRR) = 1.19, 95% CI 1.01–1.40 for past and IRR = 1.30, CI 1.07–1.58 for current], binge drinking (IRR = 1.22, CI 1.02–1.46), lifting or pulling/pushing heavy loads (IRR = 1.35, CI 1.10–1.65), awkward working positions (IRR = 1.24, CI 1.01–1.53), long-standing illness limiting work or daily activities (IRR = 2.32, CI 1.93–2.79), common mental disorder (IRR = 1.52, CI 1.30–1.79), and multisite pain (IRR = 1.50, CI 1.23–1.84) increased the number of days lost, while high level of education (IRR = 0.66, CI 0.52–0.82) and moderate level of leisure-time physical activity (IRR = 0.80, CI 0.67–0.94) reduced the number of days lost. Conclusions Modifiable lifestyle risk factors, workload factors, common mental disorder, and multisite pain substantially increase the number of days lost. However, the findings of this study could be generalized to female workers in the public sector. 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