Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Nov 15;19(11):e0310970.
doi: 10.1371/journal.pone.0310970. eCollection 2024.

Occupational injuries and associated factors among sanitary workers in public hospitals, eastern Ethiopia: A modified Poisson regression model analysis

Affiliations

Occupational injuries and associated factors among sanitary workers in public hospitals, eastern Ethiopia: A modified Poisson regression model analysis

Sina Temesgen Tolera et al. PLoS One. .

Abstract

Background: Occupational or work-related injuries are mostly common among hospitals' sanitary workers (SWs) in developing countries like Ethiopia. This is due to improper practiced of devices, unhygienic workplace, neglected and undermined risk factors, as well as due to lack of policy initiatives; but not studied well.

Objective: The aim of the study was to assess the occupational injuries and its associated factors among SWs in public hospitals, eastern Ethiopia: A Modified Poisson regression Model Analysis.

Methods: An institution-based cross-sectional study was conducted in eight public hospitals in eastern Ethiopia from May 2023 to August 30th, 2023. Out of fourteen hospitals, eight of them were selected randomly. Eight data collectors and 4 supervisors were assigned. Face-to-face interview was conducted. Eight hundred hospital SWs were recruited for the study. Occupational injury was measured using Boolean logic questionnaire either YES [1] or NO [0] for the last 12 months and the 7 days. Descriptive statistical was used for means, medians, standard deviations, and frequencies, proportions, and percentages. Modified Poisson regression was used to explore the relationship of outcome and independent variables. Accordingly, bi-variable analysis was performed to estimate unadjusted prevalence ratio (UPR). While, multi-variable model was used adjusted PR(APR) for those variables have significant values of p ≤0.20 at bi-variate analysis with confidence interval of 95% (CI:95%).

Result: Out of eight hundred nine SWs, 729(90.1%) were participated on the study. Self-reported occupational injuries among SWs in the last 12 months were 44.0% (95% CI: 40.4, 47.7). Of these, 92.2% (95%CI: 88.7,94.90%) and 7.8% (95%CI: 5.1, 11.3%) occupational injuries was reported from the cleaners and waste collectors, respectively. The model found that SWs those acquired diseases after recruited in the hospitals (APR:1.3;95%CI:1.1,1.6), those had sleeping disorder (APR:1.2;95%CI:1.0,1.), those had workload (APR:1.3; 95%CI:1.0, 1.8), those exposed with occupational hazards (APR:1.4; 95%CI:1.3, 1.7) were at the risk of occupational injuries as compared to their counter parts. Meanwhile, SWs those didn't get supervision (APR: 1.0;95%CI: 1.0, 1.2) and those non-adherence to personal protective equipment (PPE) (APR:1.3;95%CI:1.0,1.5) were more likely to at the risk of occupational injuries.

Conclusion: The current study concluded that there was a high prevalence of occupational injuries among SWs in the current selected public hospitals. The study also found that non-compliant with PPE, work load, sleeping disorders, attitude towards workplace safety and unsupervised activities and working in high-risk environment tends to increase the risk for occupational injuries. In addition to occupational injuries the study found that SWs those acquired occupational diseases such as asthma, respiratory tract problems, allergy, infections, kidney problems and dermatology problems after recruited in hospitals.

PubMed Disclaimer

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Map of Ethiopia, selected eastern Ethiopia and selected public hospitals for the study created using ARCGIS from free access of Ethiopia GIS datasets [46].
Fig 2
Fig 2. Schematic representative of selection procedure of SWs, eastern Ethiopia, 2023.

Similar articles

References

    1. Gorman T. Kamen J. Nimbalkar S. Zuckerman N. Lowe T. Controlling Health Hazards to Hospital Workers. New Solut, 2013. 23 Suppl: p. 1–167. doi: 10.2190/NS.23.Suppl - DOI - PubMed
    1. Dancer S.J. Controlling Hospital-Acquired Infection: Focus on the Role of the Environment and New Technologies for Decontamination. Clin Microbiol Rev, 2014. 27(4): p. 665–90. doi: 10.1128/CMR.00020-14 - DOI - PMC - PubMed
    1. Gomathi P., Kamala K. Threatening Health Impacts and Challenging Life of Sanitary Workers.J. Evolution Med. Dent. Sci., 2020. 9(41): p. 3061
    1. Kabir A.,Farhana N, Akter Sweeping Practices, Knowledge About Osh Hazards in Dhaka City, Bangladesh:.Aa qualitative inquiry, 2015. 2(3): p. 237–243.
    1. WHO. World Health Organization: New Report Exposes Horror of Working Conditions for Millions of Sanitation Workers in the Developing World. 2019. June 12th, 2022; Available from: https://www.who.int/news/item/14-11-2019.