TY - JOUR T1 - Absence from work and return to work in people with back pain: a systematic review and meta-analysis JF - Occupational and Environmental Medicine JO - Occup Environ Med SP - 448 LP - 456 DO - 10.1136/oemed-2013-101571 VL - 71 IS - 6 AU - Gwenllian Wynne-Jones AU - Jemma Cowen AU - Joanne L Jordan AU - Olalekan Uthman AU - Chris J Main AU - Nick Glozier AU - Danielle van der Windt Y1 - 2014/06/01 UR - http://oem.bmj.com/content/71/6/448.abstract N2 - 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, I2 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, I2 99.2%), 85.6% (95% CI 78.2% to 90.7%, n=13, I2 98.7%) and 93.3% (95% CI 84.0% to 94.7%, n=10, I2 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. ER -