OCCUPATIONAL HAZARD EXPOSURES AND HEALTH OUTCOMES AMONG SANITARY WORKERS IN PUBLIC HOSPITALS, ETHIOPIA

Abstract

Background: Occupational hazards often jeopardize the health and safety of hospital staff, particularly sanitary workers (SWs) due to their working conditions, which are common problems in low-middle -income countries. The attributed factors are unhealthy and unsafe workplace, poor work design and conditions, inadequate safety measures such as lack of personal protective equipment (PPE) and weak occupational related infection prevention and control (IPC) service. In addition, institutional, behavioral and individual factors (knowledge and attitude [KA]) are underlined as other factors. Thus, all these aforementioned workplace problems can lead to occupational outcomes such as injuries and work-related musculoskeletal diseases (WMSDs), which are not well-identified among hospitals SWs in Ethiopia. Objective: The aim of the study was to assess occupational hazard exposures, health outcomes, and associated factors among sanitary workers in public hospitals, Ethiopia. Methods: Hospital-based cross-sectional study design with mixed quantitative and qualitative methods was conducted in eastern Ethiopia from 01st April to 30th August, 2023. A total of 809 SWs and 16 key informant Interview (KIIs) were participated in the quantitative and qualitative study, respectively. The quantitative study was conducted using a face-to-face interview. Qualitative study was done using KIIs and observations. Data were entered into Epi-Data 3.1 and then exported to STATA 17MP version. Uni-variate analysis was used to present the descriptive variables. While, the robust statistical models— Multi-level (MLM) binary logistic regression, Robust Modified Poisson (MP) regression, MLM ordinal logistic regression and structural equation modelling (SEM) were used for analytical analysis. MLM binary regression was used to explore the associated factors along with occupational hazard exposures and the PPE practice. MP logistic regression analysis was used to determine the relationship between predictors with occupational injuries and WMSDs. Meanwhile, MLM ordinal logistic regression was used to explore the associated factors along with IPC practice; knowledge, attitude about OHRs. The variables having p-value <0.20 at crude odds ratio (COR) were candidate for adjusted odds ratio (AOR) for each objective. Finally, SEM was used to determine the correlation of the objectives(dependents) between each other within the dissertation research. Dependent variables those met the model fits were considered for the interpretations along with confidence interval of 95%(CI:95%). Result: Out of 809 SWs, 729 (90.1%) were participated on the study. The self-reported occupational hazard exposures, occupational injuries and WMSD among SWs were 63.7% (60.0-67.0%), 44.0% (40.4-47.7%) and 51.2% (48.0-55.0%), respectively. Also, the level of poor knowledge and negative favored attitude about OHRs among SWs were 67.4% (63.8-70.8%) and 42.7% (39.0-46.3%). Moreover, the non-compliance to PPE and IPC practice among SWs were 53.2% (50.2-57.2%) and 36.8% (33.3-40.4%), respectively. The MLM regression model shows that SWs dissatisfied with their environment were with higher odds of occupational exposures (AOR: 5.71; 3.70, 21.35). However, those with had social recognition (AOR: 0.37; 0.14, 0.91) and safe workplace (AOR: 0.21; 0.10,0.91) were less likely to associated with occupational hazard exposures. The MP regression model found that SWs those acquired diseases after recruited in the hospitals (APR:1.30;1.11 xi 1.62), those had sleeping disorder (APR:1.21;1.11-1.53), those have workload (APR:1.33; 1.02-1.82), those didn’t get supervision (APR: 1.11; 1.04-1.44) and those non-adhered to PPE (APR:1.32;1.12-1.54) were more likely to associated with the risk of occupational injuries. In same analysis, SWs those acquired diseases after recruited in the hospitals (APR: 1.85, 1.62-2.12), didn’t get OHS training (APR:1.20;1.03-1.43), had workload (APR: 1.36;1.05-1.76) and non-adhered to PPE (APR: 1.17; 1.00-1.38) were more likely to associated with WMSD. The MLM ordinal regression shows that SWs those had un-favored attitude (AOR: 0.33; 0.17, 0.66) and poor IPC practice (AOR: 0.35; 0.20, 0.62) were less likely to associated with good knowledge about OHRs. However, those who trained on OHS service (AOR: 4.90; 3.10, 7.75), satisfied with their job (AOR: 1.88; 1.11, 3.75), and satisfied with environment (AOR: 2.57; 1.09, 6.05) were more likely to associated with good knowledge of SWs about OHRs. Similarly, those practiced good IPC (AOR: 20.43; 15.00, 35.84) and those trained OHS (AOR: 3.45; 1.51, 6.22) were associated with favored attitude about OHRs. MLM regression model found SWs those had daily supervision (AOR: 13.71;11.18-20.61), those favored attitude to the risks (AOR: 1.71;1.04-2.81) and those practiced good IPC (AOR: 11.34;4.65-17.44) were more likely to associated with adherence of PPE practice. MLM ordinal regression found that SWs those had good PPE knowledge (AOR: 4.70;2.11-10.46), those had social recognition (AOR: 6.08;4.24-8.71), those worked fewer working hrs./day (AOR: 1.46;1.10-2.30), those hadn’t job stress (AOR: 1.46; 1.03-2.48) and hadn’t workloads (AOR: 2.74, 1.56-4.82) were more likely to associated with adherence of IPC practice. The SEM shows that poor knowledge (β= 0.07; 0.01, 0.14) and unfavored attitude about the risks (β= 0.01; 0.01, 0.05), occupational hazard exposures (β = 0.16; 0.08, 0.23) have positive interactions with the injuries and indicating they are potential to increase the risks. But it found that compliance with PPE has negative impact on injuries (β = 0.03; -0.10, 0.04) and WMSDS (β = -0.10; -.17, -0.03) that indicates it has the potential to reduce these risks. Conclusion: The self-reported information obtained from SWs shows that more than six out of ten SWs were exposed with variety of occupational hazards within the public hospitals. The study also highlights that four and five out of ten SWs were reported that they had occupational injuries and WMSDs, respectively. The study also notes that non-adherence to safety measures, inadequate of knowledge and a negative attitude about OHRs, dissatisfied with job and environmental, lack of OHS training and workplace supervision were often highlights as attribute factors of exposures and outcomes. Thus, the study suggested that interventions like health and safety training, advocacy of safety compliance and workplace supervision should be applied in order to reduce these risks. This study also proposes the risk assessment and safety management (RASM) approach to handle occupationally associated outcomes including infections within the hospitals. Furthermore, the study provides piece of advice for national policy makers and pertinent ministries in order to use the current evidence for further occupational health and safety policy improvement at hospital settings.