| Abstract: | Objectives. We used individual participant data from multiple studies to conduct a comprehensive meta-analysis of mechanical exposures in the workplace and low back pain.Methods. We conducted a systematic literature search and contacted an author of each study to request their individual participant data. Because outcome definitions and exposure measures were not uniform across studies, we conducted 2 substudies: (1) to identify sets of outcome definitions that could be combined in a meta-analysis and (2) to develop methods to translate mechanical exposure onto a common metric. We used generalized estimating equation regression to analyze the data.Results. The odds ratios (ORs) for posture exposures ranged from 1.1 to 2.0. Force exposure ORs ranged from 1.4 to 2.1. The magnitudes of the ORs differed according to the definition of low back pain, and heterogeneity was associated with both study-level and individual-level characteristics.Conclusions. We found small to moderate ORs for the association of mechanical exposures and low back pain, although the relationships were complex. The presence of individual-level OR modifiers in such an area can be best understood by conducting a meta-analysis of individual participant data.In the past 4 decades there have been more than 30 systematic reviews of workplace biomechanical risk factors and low back pain (LBP).1–33 Although these reviews were rigorously done, controversy remains about the role of mechanical workplace exposures34 among other possible factors,35 and important gaps in our knowledge persist.36 To date, authors of comprehensive systematic reviews that include multiple definitions of LBP and mechanical exposures have not attempted to statistically combine data. This is likely attributable to the diversity of study designs, study populations, methods of exposure measurement, and assessments of LBP. Differences in the way mechanical exposure and LBP are reported make it difficult to comprehensively summarize this literature.To overcome these problems we developed methods to categorize “like” definitions of LBP that could be combined in a homogeneous meta-analysis37 and to create combinable mechanical exposure measures.38 We also obtained individual participant data for LBP studies in workers. We used these components to conduct an individual participant data meta-analysis. Use of individual participant data allowed us to go beyond the typical meta-analysis and make full use of all data collected. For example, we were not restricted to definitions of LBP reported in the published literature; instead, we were able to explore all definitions of LBP collected within a study. Individual participant data also enabled us to consistently adjust for potential confounding factors and explore individual-level odds ratio (OR) modifiers. |
