Using administrative sickness absence data as a marker of future disability pension: the prospective DREAM study of Danish private sector employees.
OBJECTIVE
The aim of this study was to examine duration of sickness absence as a risk marker for future disability pension among all private sector employees in Denmark 1998-2004.


METHODS
All private sector employees receiving sickness absence compensation from the municipality in 1998, a total of 225 056 persons (39.2% women 61.8% men, age range 18-65, mean age 37.2), were followed in a national register to determine granted disability pension during the period 1 January 2001 through 31 December 2004. The authors excluded pensions in 1999 and 2000 to determine the status of sickness absence duration as an early risk marker.


RESULTS
5694 persons (2.5%) received disability pension during follow-up, more men (53.4%) than women (46.6%). There was a strong graded association between increasing length of absence and increasing risk of future disability pension. Significant differences were found between the younger and older age strata: men below 40 experiencing more than 26 weeks of sickness absence had a 16-fold risk of disability pension. The corresponding figure for men 40 years or older was approximately 7. For women, the corresponding figures were 12.6 and 6.7 respectively.


CONCLUSIONS
The findings suggest that administratively collected data on sickness absence compensation are an important predictor of disability pension among private sector employees. The use of information on sick leave may improve the effectiveness of early interventions by policy makers, case managing authorities, employers and physicians.
Lund
Thomas
T
Mr T Lund, National Research Center for the Working Environment, Lerso Parkallé 105, DK-2100 Copenhagen, Denmark. tlu@nrcwe.dk
Kivimäki
Mika
M
Labriola
Merete
M
Villadsen
Ebbe
E
Christensen
Karl Bang
KB
D000041:Absenteeism; D000293:Adolescent; D000328:Adult; D000368:Aged; D003718:Denmark; D004185:Disability Evaluation; D006233:Persons with Disabilities / Q000706:statistics & numerical data*; D005260:Female; D005544:Forecasting / Q000379:methods; D006801:Humans; D008297:Male; D008875:Middle Aged; D016272:Occupational Health / Q000706:statistics & numerical data*; D010415:Pensions / Q000145:classification / Q000706:statistics & numerical data*; D017149:Private Sector / Q000191:economics* / Q000706:statistics & numerical data; D011446:Prospective Studies; D018570:Risk Assessment / Q000379:methods* / Q000706:statistics & numerical data; D017678:Sex Distribution; D018582:Sick Leave / Q000706:statistics & numerical data*