Hezekiah Oluwole ADEYEMİ, Olatilewa Rapheal ABOLADE, Ajibola Oluwafemi OYEDEJI, Olanrewaju Bilikis OLATUNDE

Modelıng Occupatıonal Health And Safety Rısks Among Unskılled Workers In Constructıon Industry

To enhance workers’ protection in construction tasks, Occupational Health and Safety Risks (OHSR) needs to be properly recognized, assessed and controlled. This study modeled Health and Safety Risk (HSR) among unskilled workers in construction works. Data was collected from 150 subjects in 12 construction sites located in Southwest Nigeria. Variables considered to play key roles in HSR causation were measured with questionnaire. All variables that correlated significantly (p≤ 0.05) to HSR on the tasks were noted by Spearman’s rho correlation (Src) using SPSS software. The model prediction was by adjusted R2 and was validated by comparison with Human Professionals’ Predictions (HPP). Model Cook’s distance and its closeness to being normally distributed were evaluated. 37 attributes variables were initially collated with 13 predictor variables remained in the optimum model. Wrong work-methods, lack of work-control and harsh outdoor environment ranked among the strongest positive β coefficients (0.217, 0.127 and 0.126 respectively). The maximum coefficient of the adjusted R2 determination was 0.708. The histogram of the residuals suggested closeness to being normally distributed and 0.930 as the maximum Cook’s distance. Comparison between the OHSR model and the HPP had Src strength of 0.965 (p<.01). The OHSR showed statistically significantly higher level of hazards’ rating (3.7533 ± 0.233) compared to HPP (3.2667 ± 0.18097), t(28) = -1.648, p = 0.197. OHSR model was developed and the performance was rated good, satisfied the study’s objectives. The author recommended development of measures at reducing β coefficients of all the predictor variables to minimize workplaces OHSR

Modelling occupational health and safety risks among unskilled workers in construction industry

Keywords:

Unskilled safety, model, predictor, variables,

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