Absence from work and return to work in people with back pain: a systematic review and meta-analysis. Issue 6 (1st November 2013)

• Record Type: Journal Article
• Authors: Wynne-Jones, Gwenllian; Cowen, Jemma; Jordan, Joanne L; Uthman, Olalekan; Main, Chris J; Glozier, Nick; van der Windt, Danielle
• Is Part Of: Occupational and environmental medicine. Volume 71:Issue 6(2014)
• Page Start: 448
• Page End: 456
• Publication Date: 2013-11-01
• Subjects: Medicine, Industrial -- Periodicals; Environmental health -- Periodicals; 616.980305
• DOI: 10.1136/oemed-2013-101571
• Languages: English
• ISSNs: 1351-0711

Abstract

Abstract : Background: A considerable proportion of work absence is attributed to back pain, however prospective studies in working populations with back pain are variable in setting and design, and a quantitative summary of current evidence is lacking. Objective: To investigate the extent to which differences in setting, country, sampling procedures and methods for data collection are responsible for variation in estimates of work absence and return to work. Methods: Systematic searches of seven bibliographic databases. Inclusion criteria were: adults in paid employment, with back pain, work absence or return to work during follow-up had been reported. Random effects meta-analysis and meta-regression analysis was carried out to provide summary estimates of work absence and return to work rates. Results: 45 studies were identified for inclusion in the review; 34 were included in the meta-analysis. The pooled estimate for the occurrence of work absence in workers with back pain was 15.5% (95% CI 9.8% to 23.6%, n=17 studies, I 2 98.1%) in studies with follow-up periods of ≤6 months. The pooled estimate for the proportion of people with back pain returning to work was 68.2% (95% CI 54.8% to 79.1%, n=13, I 2 99.2%), 85.6% (95% CI 78.2% to 90.7%, n=13, I 2 98.7%) and 93.3% (95% CI 84.0% to 94.7%, n=10, I 2 99%), at 1 month, 1–6 months and ≥6 months, respectively. Differences in setting, risk of participation bias and method of assessing work absence explained some of the heterogeneity. Conclusions: Pooled estimates suggest high return to work rates, with wide variation in estimates of return to work only partly explained by a priori defined study-level variables. The estimated 32% not back at work at 1 month are at a crucial point for intervention to prevent long term work absence.