The Use of Individual Participant Data (IPD) for Examining Heterogeneity in Meta-analysis of Observational Studies: An Application to Biomechanical Workplace Risk Factors and Low Back Pain
type: CreativeWork
description: Background: The use of meta-analysis to combine the results of observational studies is controversial. Despite its common use, methodological work in this area is lacking. Because of the diversity of study designs, exposure and outcome measures, and differential adjustment for confounding variables, the identification of sources of heterogeneity among study effect estimates is particularly important when combining data from observational studies. This thesis presents the results of a study that examines the relative ability of individual participant data (IPD) meta-analysis (which was considered a “gold standard”) and traditional aggregate data (AD) meta-analysis to identify sources of heterogeneity among studies examining mechanical exposure and low back pain (LBP) in workers. Materials and Methods: A systematic literature search was conducted to identify relevant articles. The corresponding author of each article was contacted to request their individual-level data. Because the outcome definitions and exposure measures were not uniform across studies, two sub-studies were conducted 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. IPD analyses were conducted using generalized estimating equation (GEE) regression to identify variables that acted as strong confounders and effect modifiers. Traditional AD meta-analysis was also conducted and potential sources of heterogeneity were tested using meta-regression. Key Findings: (1) Overall, we found an association between both forces and postures on LBP, although the magnitude varied depending on the exposure-outcome combination. Among the outcomes, the ORs tended to be highest for sick leave due to LBP. (2) There was very little evidence of strong confounders in the relationship between mechanical exposure and LBP; thus differential adjustment for confounders in studies would not likely be an important sou…
abstract: Background: The use of meta-analysis to combine the results of observational studies is controversial. Despite its common use, methodological work in this area is lacking. Because of the diversity of study designs, exposure and outcome measures, and differential adjustment for confounding variables, the identification of sources of heterogeneity among study effect estimates is particularly important when combining data from observational studies. This thesis presents the results of a study that examines the relative ability of individual participant data (IPD) meta-analysis (which was considered a “gold standard”) and traditional aggregate data (AD) meta-analysis to identify sources of heterogeneity among studies examining mechanical exposure and low back pain (LBP) in workers. Materials and Methods: A systematic literature search was conducted to identify relevant articles. The corresponding author of each article was contacted to request their individual-level data. Because the outcome definitions and exposure measures were not uniform across studies, two sub-studies were conducted 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. IPD analyses were conducted using generalized estimating equation (GEE) regression to identify variables that acted as strong confounders and effect modifiers. Traditional AD meta-analysis was also conducted and potential sources of heterogeneity were tested using meta-regression. Key Findings: (1) Overall, we found an association between both forces and postures on LBP, although the magnitude varied depending on the exposure-outcome combination. Among the outcomes, the ORs tended to be highest for sick leave due to LBP. (2) There was very little evidence of strong confounders in the relationship between mechanical exposure and LBP; thus differential adjustment for confounders in studies would not likely be an important sou…
author: Griffith, Lauren
language: en_ca
keywords: low back pain, meta-analysis, heterogeneity, individual participant data
date published: 2009-09-24T15:36:15Z
date modified: 2026-07-27T21:28:13Z
provider: University of Toronto
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Toronto

PropertyValue
property ID: Handle
value: http://hdl.handle.net/1807/17767