Cross-sectional analysis reveals health and safety management crucial for safer indigenous construction practices.
While indigenous methods are often praised for their ecological sustainability, they are also perceived as physically demanding and potentially unsafe. Thus, this study aims to determine whether effective health and safety management (HSM) can transform these indigenous practices into safer, more sustainable construction systems that balance environmental responsibility with worker well-being. A cross-sectional analytical design was adopted to examine this relationship among construction professionals and site personnel in Nigeria. Ordinary Least Squares (OLS) regression was employed for hypothesis testing and moderation analysis, while machine learning techniques (Random Forest (RF), Decision Tree (DT), and Artificial Neural Network (ANN)) were applied to capture non-linear patterns, assess feature importance, and validate predictive robustness. Findings from both inferential and predictive models reveal that structured and effective HSM is the strongest and most consistent determinant of reduced MSK injuries. Indigenous sustainable practices, whether technological (β = -0.116, p ≈ 0.068), material (β = -0.063), or methodological (β = -0.046) show directionally protective but statistically weaker effects, and their influence becomes meaningful only within robust safety management systems. The study further establishes that HSM exerts a direct effect (β = -0.14 to -0.15, p < .05) on injury reduction rather than moderating the indigenous practice–injury relationship. The study concludes that while integrated indigenous sustainable practices contribute modestly to safety outcomes, institutionalized HSM remains the dominant mechanism for preventing MSK injuries.
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Olugboyega et al. (2026) studied this question.
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