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Journal of Occupational Rehabilitation

, Volume 24, Issue 4, pp 747–754 | Cite as

Work Ability Index as Tool to Identify Workers at Risk of Premature Work Exit

  • Corné A. M. RoelenEmail author
  • Martijn W. Heymans
  • Jos W. R. Twisk
  • Jac J. L. van der Klink
  • Johan W. Groothoff
  • Willem van Rhenen
Article

Abstract

Purpose To investigate the Work Ability Index (WAI) as tool for identifying workers at risk of premature work exit in terms of disability pension, unemployment, or early retirement. Methods Prospective cohort study of 11,537 male construction workers (mean age 45.5 years), who completed the WAI at baseline and reported their work status (employed, unemployed, disability pension, or retired) after mean 2.3 years of follow-up. Associations between WAI scores and work status were investigated by multinomial logistic regression analysis. The ability of the WAI to discriminate between workers at high and low risk of premature work exit was analyzed by the area (AUC) under the receiver operating characteristic curve. Results 9,530 (83 %) construction workers had complete data for analysis. At follow-up, 336 (4 %) workers reported disability pension, 125 (1 %) unemployment, and 255 (3 %) retirement. WAI scores were prospectively associated with the risk of disability pension at follow-up, but not with the risk of unemployment and early retirement. The WAI showed fair discrimination to identify workers at risk of disability pension [AUC = 0.74; 95 % confidence interval (CI) 0.70–0.77]. The discriminative ability decreased with age from AUC = 0.78 in workers aged 30–39 years to AUC = 0.69 in workers ≥50 years of age. Discrimination failed for unemployment (AUC = 0.51; 95 % CI 0.47–0.55) and early retirement (AUC = 0.58; 95 % CI 0.53–0.61). Conclusions The WAI can be used to identify construction workers <50 years of age at increased risk of disability pension and invite them for preventive interventions.

Keywords

Discriminative ability Prognostic research ROC curve Sensitivity and specificity WAI 

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Corné A. M. Roelen
    • 1
    • 2
    • 3
    Email author
  • Martijn W. Heymans
    • 2
    • 4
  • Jos W. R. Twisk
    • 2
    • 4
  • Jac J. L. van der Klink
    • 3
  • Johan W. Groothoff
    • 3
  • Willem van Rhenen
    • 1
    • 5
  1. 1.ArboNed Occupational Health ServiceUtrechtThe Netherlands
  2. 2.Division Methodology and Applied Biostatistics, Department of Health SciencesVU UniversityAmsterdamThe Netherlands
  3. 3.Division Community and Occupational Medicine, Department of Health Sciences, University Medical Center GroningenUniversity of GroningenGroningenThe Netherlands
  4. 4.EMGO+ Institute for Health and Care ResearchVU University Medical CenterAmsterdamThe Netherlands
  5. 5.Center for Leadership and Management DevelopmentBusiness University NyenrodeBreukelenThe Netherlands

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