A screening tool for the risk of disability retirement due to musculoskeletal disorders

• Published in: Scandinavian Journal of Work, Environment ＆ Health Environment ＆ Health, 2018-01, Vol.44 (1), p.37-46
• Main Authors: Rahman Shiri, Markku Heliövaara, Kirsi Ahola, Leena Kaila-Kangas, Eija Haukka, Johanna Kausto, Peppiina Saastamoinen, Päivi Leino-Arjas, Tea Lallukka
• Format: Article
• Language: English
• Subjects: Adult; Age Factors; Arthritis; Awards & honors; Calibration; Carpal tunnel syndrome; Chronic illnesses; Confidence intervals; Disability pensions; disability retirement; Disabled Persons - statistics & numerical data; Disorders; Education; Employees; Epidemiology; Finland - epidemiology; Health and safety screening; Humans; Male; Middle Aged; msd; musculoskeletal disease; Musculoskeletal diseases; Musculoskeletal Diseases - epidemiology; musculoskeletal disorder; Occupational Diseases - epidemiology; Overuse injuries; Pain; Polls & surveys; Population; Population studies; prediction; prevention; Public health; Registries; Retirement; Retirement - statistics & numerical data; Retirement planning; Risk Factors; screening; screening tool; Sex Factors; Sociodemographics; Statistical analysis; Surgery; Surveys and Questionnaires - standards; Survival analysis; Working conditions
• ISSN: 0355-3140; 1795-990X
• DOI: 10.5271/sjweh.3684

Objective This study aimed to develop and validate a risk screening tool using a points system to assess the risk of future disability retirement due to musculoskeletal disorders (MSD). Methods The development population, the Health 2000 Survey, consisted of a nationally representative sample of Finnish employees aged 30-60 years (N=3676), and the validation population, the Helsinki Health Study, consisted of employees of the City of Helsinki aged 40-60 years (N=6391). Both surveys were linked to data on disability retirement awards due to MSD from national register for an 11-year follow-up. Results The discriminative ability of the model with seven predictors was good (Gönen and Heller’s K concordance statistic=0.821). We gave points to seven predictors: sex-dependent age, level of education, pain limiting daily activities, multisite musculoskeletal pain, history of arthritis, and surgery for a spinal disorder or carpal tunnel syndrome. A score of ≥3 out of 7 (top 30% of the index) had good sensitivity (83%) and specificity (70%). Individuals at the top 30% of the risk index were at 29 [95% confidence interval (CI) 15-55) times higher risk of disability retirement due to MSD than those at the bottom 40%. Conclusion This easy-to-use screening tool based on self-reported risk factor profiles can help identify individuals at high risk for disability retirement due to MSD.