Shortened version of the work ability index to identify workers at risk of long-term sickness absence.
BACKGROUND
The Work Ability Index (WAI) identifies non-sicklisted workers at risk of future long-term sickness absence (LTSA). The WAI is a complicated instrument and inconvenient for use in large-scale surveys. We investigated whether shortened versions of the WAI identify non-sicklisted workers at risk of LTSA.


METHODS
Prospective study including two samples of non-sicklisted workers participating in occupational health checks between 2010 and 2012. A heterogeneous development sample (N= 2899) was used to estimate logistic regression coefficients for the complete WAI, a shortened WAI version without the list of diseases, and single-item Work Ability Score (WAS). These three instruments were calibrated for predictions of different (≥2, ≥4 and ≥6 weeks) LTSA durations in a validation sample of non-sicklisted workers (N= 3049) employed at a steel mill, differentiating between manual (N= 1710) and non-manual (N= 1339) workers. The discriminative ability was investigated by receiver operating characteristic analysis.


RESULTS
All three instruments under-predicted the LTSA risks in both manual and non-manual workers. The complete WAI discriminated between individuals at high and low risk of LTSA ≥2, ≥4 and ≥6 weeks in manual and non-manual workers. Risk predictions and discrimination by the shortened WAI without the list of diseases were as good as the complete WAI. The WAS showed poorer discrimination in manual and non-manual workers.


CONCLUSIONS
The WAI without the list of diseases is a good alternative to the complete WAI to identify non-sicklisted workers at risk of future LTSA durations ≥2, ≥4 and ≥6 weeks.
1 ArboNed Occupational Health Service, Utrecht, The Netherlands.
Lianne S
LS
Schouten
2 Division of Community and Occupational Medicine, Department of Health Sciences, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Ute
U
Bültmann
3 Department of Epidemiology and Biostatistics, VU University Medical Center, VU University, Amsterdam, The Netherlands.
Martijn W
MW
Heymans
1 ArboNed Occupational Health Service, Utrecht, The Netherlands.
Catelijne I
CI
Joling
3 Department of Epidemiology and Biostatistics, VU University Medical Center, VU University, Amsterdam, The Netherlands.
Jos W R
JW
Twisk
1 ArboNed Occupational Health Service, Utrecht, The Netherlands 2 Division of Community and Occupational Medicine, Department of Health Sciences, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands 3 Department of Epidemiology and Biostatistics, VU University Medical Center, VU University, Amsterdam, The Netherlands corne.roelen@arboned.nl.
Corné A M
CA
Roelen
D000041:Absenteeism; D000328:Adult; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D016272:Occupational Health; D009790:Occupations / Q000706:statistics & numerical data*; D011446:Prospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D018582:Sick Leave / Q000706:statistics & numerical data*; D014938:Work Capacity Evaluation