AHFE Open AccessThe Influence of Gender/Sex on Work-Related Musculoskeletal Disorders: A Systematic Review and Meta-Analysis
Abstract
This systematic review and meta-analysis examines the influence of gender/sex on the risk of developing work-related musculoskeletal disorders (WMSDs). Previous research has indicated a link between female gender/sex and increased WMSD risk, but findings have been inconsistent due to varying study designs and high null result rates. This study synthesized adjusted odds ratios (AORs) from 93 high-quality cross-sectional studies that examine WMSD risk while controlling for various confounding factors such as job exposure and environmental variables. The overall synthesized AOR for female gender/sex on WMSD risk was 1.50, and gender was a statistically significant predictor of risk for most but not all body parts and industries. High heterogeneity was present in the overall synthesis but recued when stratifying results by industry and body part. The results suggest a significant but low to moderate link between gender and WMSD incidence, with some variation by industry and body part.
Keywords: Systematic review, meta-analysis, gender, sex, work-related musculoskeletal disorder
DOI: 10.54941/ahfe1005717
Cite this paper
More from this volume
- Implementing an AI Fatigue Risk Management System for Aviation Maintenance SMS: A Technology Enhanced Critical Process Human Factors Safety Plan
- Deep Learning Forecast of Perceptual Load Using fNIRS Data
- Artificial intelligence in the function of improving port systems
- Formalizing Trust in Artificial Intelligence for Built Environment Decision-Making
- Artificial Intelligence and Design: Innovation, Practical Applications, and Future Creative Horizons
- Supporting Informal Sustainability Learning with AI-assisted Educational Technology
- An assessment of the maintenance of heritage buildings using AI and IoT: a South African perspective
- What if we Could Entangle Drones? Towards the Management of a Swarm of Drones as a Non-Local Quantum Object
- Engaging All Elderly Residents in Community Renewal: Designer Spotlight Interview Tool for LLM Building
- AI Play in Higher Education: Students’ perceptions of play and co-creation of knowledge with generative AI
- Optimizing AI Involvement in Engineering University Courses Based on Students' Personality
- Predictive Model for Partner Agencies Dependency on Food Banks