Alters- und berufsgruppenabhängige Unterschiede in der Arbeitsunfähigkeit durch häufige Muskel-Skelett-Erkrankungen

ZusammenfassungMuskel-Skelett-Erkrankungen sind häufig Ursache für Arbeitsunfähigkeit (AU). Aufgrund der hohen Bedeutung von Rückenschmerzen und Kniegelenksarthrosen (ICD-10-Diagnosen M54 und M17) werden diese Erkrankungen im vorliegenden Beitrag näher betrachtet. Es ist zu klären, ob berufsspezifische Unterschiede im Auftreten von AU-Ereignissen aufgrund dieser Erkrankungen abhängig vom Lebensalter variieren. Die Untersuchungen basierten auf einer Sekundärdatenanalyse von AU-Daten fast aller gesetzlichen Krankenkassen für 2008. Der Datenbestand enthält aggregiert Angaben zur AU von 26,2 Mio. gesetzlich pflichtversicherten Erwerbstätigen. Zielgröße sind AU-Ereignisse durch die Diagnosen M54 und M17. Expositionsvariable ist die Zuordnung zu Berufsgruppen nach Blossfeld. Berechnet werden Morbiditätsratios (SMR) für AU-Ereignisse stratifiziert nach Geschlecht und Alter. Die Ergebnisse zeigen, dass bei beiden Geschlechtern und Diagnosen erhöhte AU-Risiken besonders in Berufsgruppen der Produktion und des Dienstleistungsbereichs mit geringem und mittlerem Qualifikationsniveau auch bei Stratifikation nach dem Lebensalter bestehen. Variationen der Effekte über das Alter sind nachweisbar. AU aufgrund dieser Diagnosen ist in diesen Berufen altersunabhängig relevant und unter sozialpolitischen und präventiven Aspekten zu berücksichtigen.AbstractMusculoskeletal disorders are the leading cause of sick leave. Because of the importance of back pain and knee osteoarthritis (ICD-10 diagnoses M54 and M17), these conditions are considered in detail. The aim of this study was to clarify whether job-specific differences in the incidence of sick leave events due to these disorders vary depending on age. The study was based on a secondary analysis of data on sick leave from almost all statutory health insurances in 2008. The database contains aggregated data on sick leave of approximately 26.2 million insured employees. The occurrence of sick leave events resulting from the M54 and M17 diagnoses was defined as the outcome variable. The assignment of employees to occupational groups (BLOSSFELD classification) was considered as the exposure variable. We calculated the morbidity ratios (SMR) of sick leave occurrence stratified by sex and age. The risk of sick leave was increased for both genders and for both diagnoses, particularly in the occupational groups of the production and service industries with low and medium skill level, even after stratification according to age. Sick leave due to these disorders is a significant issue in these occupations regardless of age, and must be considered with regard to social and preventive aspects.

[1]  F. Hoffmann,et al.  Validierung von Sekundärdaten , 2008, Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz.

[2]  Andreas Holtermann,et al.  Prognostic factors for long-term sickness absence among employees with neck-shoulder and low-back pain. , 2010, Scandinavian journal of work, environment & health.

[3]  F. Nijhuis,et al.  The influence of sick leave frequency determinants on homogeneous groups in two socio-economically comparable, but socio-culturally different regions in The Netherlands. , 2008, Central European journal of public health.

[4]  L. Straker,et al.  Thoracic spine pain in the general population: Prevalence, incidence and associated factors in children, adolescents and adults. A systematic review , 2009, BMC musculoskeletal disorders.

[5]  N. Breslow,et al.  Statistical methods in cancer research. Volume II--The design and analysis of cohort studies. , 1987, IARC scientific publications.

[6]  P. Côté,et al.  Low back pain and determinants of sickness absence , 2009, The European journal of general practice.

[7]  U. Latza.  Umgang mit Querschnittstudien in der Arbeitswelt , 2009 .

[8]  P. Than,et al.  Prevalence of low back pain and lumbar spine degenerative disorders. Questionnaire survey and clinical–radiological analysis of a representative Hungarian population , 2010, International Orthopaedics.

[9]  F. Schreyer,et al.  Berufe im Spiegel der Statistik : Beschäftigung und Arbeitslosigkeit 1985-1995 , 1996 .

[10]  C. Vetter.  Einfluss der Altersstruktur auf die krankheitsbedingten Fehlzeiten , 2003 .

[11]  M. Blagojevic,et al.  Risk factors for onset of osteoarthritis of the knee in older adults: a systematic review and meta-analysis. , 2010, Osteoarthritis and cartilage.

[12]  H. Heneweer,et al.  Physical activity and low back pain: a systematic review of recent literature , 2011, European Spine Journal.

[13]  E. Vieira,et al.  Risk factors for work-related musculoskeletal disorders: A systematic review of recent longitudinal studies. , 2009, American journal of industrial medicine.

[14]  Jan Nielsen,et al.  Pain in the lumbar, thoracic or cervical regions: do age and gender matter? A population-based study of 34,902 Danish twins 20–71 years of age , 2009, BMC musculoskeletal disorders.

[15]  E. Viikari-Juntura,et al.  The association between obesity and low back pain: a meta-analysis. , 2010, American journal of epidemiology.

[16]  Work participation and health status in early osteoarthritis of the hip and/or knee: A comparison between the cohort hip and cohort knee and the osteoarthritis initiative , 2010, Arthritis care & research.

[17]  Joshua A Hirsch,et al.  Comprehensive review of epidemiology, scope, and impact of spinal pain. , 2009, Pain physician.

[18]  H Hemingway,et al.  Sickness absence from back pain, psychosocial work characteristics and employment grade among office workers. , 1997, Scandinavian journal of work, environment & health.

[19]  M. Doherty,et al.  Occupational risk factors for osteoarthritis of the knee: a meta-analysis. , 2011, Osteoarthritis and cartilage.

[20]  S. Holmberg,et al.  Primary care consultation, hospital admission, sick leave and disability pension owing to neck and low back pain: a 12-year prospective cohort study in a rural population , 2006, BMC musculoskeletal disorders.

[21]  Jennifer M Muggleton,et al.  An objective spinal motion imaging assessment (OSMIA): reliability, accuracy and exposure data , 2006, BMC musculoskeletal disorders.

[22]  H. Burr,et al.  Transitions between sickness absence, work, unemployment, and disability in Denmark 2004-2008. , 2012, Scandinavian journal of work, environment & health.

[23]  Karl Bang Christensen,et al.  Physical work environment risk factors for long term sickness absence: prospective findings among a cohort of 5357 employees in Denmark , 2006, BMJ : British Medical Journal.

[24]  P. Mairiaux,et al.  Determinants of sickness absence duration after an occupational back injury in the Belgian population. , 2012, American journal of industrial medicine.

[25]  H.-P. Blossfeld,et al.  Bildungsexpansion und Berufschancen : empirische Analysen zur Lage der Berufsanfänger in der Bundesrepublik , 1985 .

[26]  O. Razum,et al.  Commentary: Rational decision-making. Does efficiency explain everything? , 2008, Journal of Public Health.

[27]  F. Nijhuis,et al.  A literature review on sick leave determinants (1984-2004). , 2009, International journal of occupational medicine and environmental health.