The publisher regrets to inform that the corresponding author mentioned in the original article was incorrect. The corresponding author of this article is now corrected as Behdin Nowrouzi.

Time-loss injuries are still a major occurrence in Canada, injuring thousands of Canadian workers each year. With obesity rates on the rise across the country, as well as around the world, it is important that the possible effects of obesity in the workplace be fully understood, especially those effects linked to lost-time injuries. The aim of this paper was to evaluate predictors of workplace lost-time injuries and how they may be related to obesity or high body mass index by examining factors associated with lost-time injuries in the health care sector, a well-studied industry with the highest number of reported time loss injuries in Canada. A literature review focusing on lost-time injuries in Registered Nurses (RNs) was conducted using the keywords and terms: lost time injury, workers' compensation, occupational injury, workplace injury, injury, injuries, work, workplace, occupational, nurse, registered nurse, RN, health care, predictors, risk factors, risk, risks, cause, causes, obese, obesity, and body mass index. Data on predictors or factors associated with lost-time injuries in RNs were gathered and organized using Loisel's Work Disability Prevention Management Model and extrapolated upon using existing literature surrounding obesity in the Canadian workplace.
Body Mass Index ; Canada ; Delivery of Health Care ; Health Care Sector ; Obesity* ; Occupational Injuries ; Risk Factors* ; Workers' Compensation

Background: Sickness absenteeism is an area of concern in nursing and is more concerning given the recent impacts of the COVID-19 pandemic on healthcare. This study is one of two meta-analyses that examined sickness absenteeism in nursing. In this study, we examined demographic, lifestyle, and physical health predictors. Methods: We reviewed five databases (CINAHL, ProQuest Allied, ProQuest database theses, PsycINFO, and PubMed) for our search. We registered the systematic review (CRD de-identified) and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Additionally, we used the Population/Intervention/Comparison/Outcome Tool to improve our searches. Results: Following quality testing, 17 articles were used for quantitative synthesis. Female employees were at higher risks of sickness absenteeism than their male counterparts (OR = 1.73; 95% CI: 1.33–2.25). Nursing staff who rated their health as poor had a greater likelihood of experiencing sickness absence (OR = 1.38; 95% CI: 1.19-1.60). Also, previous sick leave predicted future leaves (OR = 3.35; 95% CI: 1.37–8.19). Moreover, experiencing musculoskeletal pain (OR = 2.41 95% CI: 1.77–3.27) increased the likelihood of sickness absence with greater odds when it is a back pain (OR = 3.05; 95% CI: 1.66–5.62). Increased age, physical activity, and sleep were not associated with sick leave. Conclusion Several variables were statistically associated with the occurrence of sickness absenteeism. One primary concern is the limited research in this area despite alarming rates of sick leave in healthcare. More research is required to identify predictors of sickness absence, and thereby, implement preventative measures.