Work-related musculoskeletal disorders and associated factors among hospital sanitary workers in public hospitals of Eastern Ethiopia

Abstract

Introduction: Work-related Musculoskeletal disorders (WMSDs) are serious problems of public health at health care facilities that reduce health quality of the workers. These issues arise from poor work design, unsafe and unhygienic conditions, lack of ergonomic practices, and inadequate occupational health and safety (OHS) services, which are common in low-middle-income countries, which remain underexamined among hospital sanitation workers (SWs) in eastern Ethiopia.

Objective: This study aimed to assess WMSDs and associated factors among public hospital SWs in eastern Ethiopia.

Methods: Hospital based cross sectional study was conducted in eastern Ethiopia in 2023. A well-structured questionnaire prepared. The internal consistency (α value) for the prepared questions was 0.95. Simple random sampling was used to choose eight hospitals among a total of fourteen public hospitals in these areas. A single proportion formula long with design effect of 2.0 and 5% of non-response rate was calculate the sample size and obtained 791 SWs, which is approaching actual number of SWs within selected hospitals. Thus, all (809) of SWs were recruited for the study. Face-to-face interview was conducted. Epi Data version 3.1 was used for data entry and Stata version 17MP was used for the data analysis. Data quality was ensured through training of data collectors, language translation, pretesting, and adjusting for confounders. The robust Modified Poisson/MP regression was used to identify predictors of WMSDs. Bi-variate MP model was used to perform un-adjusted prevalence ratio (UPR). While, MP multi-variable was used to analysis the adjusted prevalence ratio (APR) for predictors with significant values of p ≤ 0.20. The results were deemed statistically significant at the two-tailed level with a 95% confidence interval (CI:95%) and a p-value of 0.05. Finally, seven variables those have ≤ p-value 0.05 at APR were candidate for Structural equation modeling (SEM) to estimate the correction and direction of risk factors for WMSDs.

Result: Out of a total of 809 SWs, 729 (90.11%) of them responded. The current study found self-reported WMSDs among SWs was 51.17% (95% CI: 0.48, 0.55). Multivariable MP regression model shows that SWs with acquired diseases (APR: 1.85; 95% CI: 1.62, 2.12), SWs with occupational injuries (APR: 1.16, 95% CI: 1.04, 1.33) and those exposed with occupational hazards (APR:1.42; 95% CI: 1.18, 1.70) were more likely to report WMSDs. Similarly, those didn't get health and safety training (APR:1.20; 95% CI: 1.03, 1.43), those had workload (APR: 1.36; 95% CI: 1.05, 1.76) and non-adhered to personal protective equipment [PPE] (APR: 1.17; 95% CI: 1.00, 1.38) were more likely to report high WMSDs. SEM found that hazards exposures (β = 0.25; 95% CI: 0.18, 0.33) and workload (β = 0.06; 95% CI: 0.03,0.15) were positive correlations. While, compliance with PPE (β= -0.09; -0.16, -0.01) and provide OHS training (β= -0.23; 95% CI: -0.342, -0.03) have negative correlation with WMSDs (p-value < 0.05).

Conclusion: The study found that more than half of SWs were suffered with WMSDs. The main attributed risk factors were poor work conditions, lack of ergonomic applications, a lack of institutional supports, and behavioral factors. Thus, the study highlights the critical policy requirement to enhance ergonomic application and health and safety improvement in order to lower WMSDs. The hospitals should provide interventions such as training on ergonomic concepts, adapt the guideline and adhere the ergonomic policies and regulations. Federal ministry of health and Federal ministry of labor and social affairs should cooperatively set standards, support and monitoring compliance, provide resources and enforce protocols in order to lower WMSDs among these vulnerable work-forces.

Keywords: Ergonomics; Occupational health; Public hospitals; Sanitation workers; Work-related musculoskeletal disorders.

Fig. 1

Conceptual framework of WRMSDs and associated factors among SWs 2023

Fig. 2

Map of study areas created in 2023 from national GIS databases free access [40]

Fig. 3

Graphic abstract for conceptual framework of WMSDs those significantly associated factors it among sanitation workers, eastern Ethiopia, 2023 (Derived from Table 4)