Abstract
Background: The musculoskeletal (MSK) system, which includes muscles, bones, joints, and connective tissues, is susceptible to various risk factors that can lead to Work-Related Upper-Limb Disorders (WRULDs). WRULDs encompass degenerative and inflammatory conditions that can result in functional disability and discomfort, particularly among individuals in uncomfortable sitting positions. Research across diverse sectors reveals that physical risk factors, such as prolonged sitting and neck bending, are significant predictors of musculoskeletal issues in the neck, shoulders, and hands, with prevalence rates of 59.3%, 48.0%, and 28.0%, respectively. In the South African mining industry, a retrospective review showed that 16.2% of 1,235 medical records from a gold mine were related to WRMSDs, with 15% involving upper limbs. In a platinum mine, 41.3% of 75 records were WRMSDs, affecting 62% of upper limbs. A colliery analysis found 37% of WRMSDs associated with the upper limbs. Despite the importance of addressing Musculoskeletal Disorders (MSKD), research on WRULDs and their risk factors in South Africa remains limited, highlighting a need for better monitoring and management of these conditions. Aim: This study assessed the risk factors associated with WRULDs among employees of a selected mining company in Gauteng Province, South Africa.
Methodology: A cross-sectional research was conducted through a self-administered and anonymised questionnaire that assessed individual employees’ exposure to risk factors linked with WRULDs. The questionnaire comprised of 4 sections pertaining to information on questions to establish if inclusion criteria was met, demographics, exposure history/medical history and risk factors, and work environment and ergonomics characteristics. This questionnaire was administered in paper format to 168 employees of a selected mining company to gather data faster and optimise response rates. The employees considered in this study were comprised of administrative employees (including secretaries, receptionists, human resource staff, accountants, procurement, administrators, IT’s, etc.) and non-administrative employees (including fitters, electricians, mechanics, boilermakers, machine operators and all their respective assistants, etc). The sample size was obtained by using the EpiInfo programme Version 7.4.2.0, from a population size of 300 employees. However, the employees' response was higher than expected, and 232 questionnaires were collected. Descriptive analysis of the collected data was conducted using IBM SPSS Statistics software version 29.0, allowing for narrative interpretation and comparison of the responses. To quantify the prevalence of WRULDs among employees of the selected mining company in Gauteng Province, South
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Africa: frequency distribution table with percentages and frequencies was used and a bar graph was populated. To identify the risk factors for WRULDs among employees of a selected mining company in Gauteng Province, South Africa: binary logistic regression calculation was performed, and an odds ratio with a 95% confidence level and a p-value less than 0.05 was used to determine statistical significance. This analysis helps determine how various risk factors contribute to the likelihood of WRULDs within the single group of employees. Additionally, a Chi-square test was used to determine the associations between categorical risk factors and WRULDs. This test provides insights into the relationships between different risk factors within the same group. In this study, both binary logistic regression and chi-square tests serve complementary purposes: the regression analyses the impact of multiple risk factors on WRULDs, while the chi-square test assesses relationships between categorical variables related to these risk factors. This approach enhances the understanding of how specific conditions and behaviours may contribute to WRULDs among the mining company employees. To quantify the number of trained employees on WRULDs prevention and use of ergonomic equipment at a selected mining company in Gauteng Province, South Africa: frequency distribution table with percentages and frequencies was used and a bar graph was populated. Results: The results of this study indicated that regarding the prevalence of WRULDs among employees, it was found that 15 employees, comprising 6.5% of the sample, were diagnosed with WRULDs, while 217 employees, accounting for 93.5% of the sample, did not report diagnosed WRULDs. Neck and shoulder issues are among the most frequently reported, with high frequencies of 22.6% and 22.9%, respectively. These areas are notably prevalent, as the percentage of cases affecting the neck and shoulders is also high, at 64.7% and 65.5%. This suggests that neck and shoulder disorders are widespread relative to the total number of reported cases, highlighting the significant impact of these issues on the workforce. Furthermore, while the majority of participants reported exposure to various degrees of risk factors, no statistically significant relationships were found between any risk factor and WRULDs. Notably, the p-value for the ergonomic layout of work areas was 0.075, which is close to the conventional threshold for statistical significance (0.05). This suggests a potential association between ergonomically designed work environments and WRULDs, although it does not reach statistical significance. The p-value of 0.000 indicates a robust association between experiencing pain and diagnosed WRULDs, underscoring a significant link between the two. However, it is important to recognize that cross-sectional studies can reveal
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associations but do not confirm causation. In this study, the pain reported by individuals with WRULDs is likely a consequence of the disorder itself rather than a contributing risk factor.
Distinguishing between risk factors and outcomes is crucial for understanding the dynamics of WRULDs. While individuals with WRULDs experience pain, this pain likely results from the existing condition, rather than indicating an underlying risk that leads to its development.
Lastly, the study reveals that 33 participants, constituting a minority at 14.4%, received training in WRULD prevention and ergonomic equipment usage, whereas the majority, encompassing 196 participants or 85.6%, did not undergo such training. Conclusion: This study found that 6.5% of employees were diagnosed with WRULDs, while 93.5% did not report such diagnoses. Neck and shoulder issues were the most frequently reported among participants, with prevalence rates of 22.6% for neck problems and 22.9% for shoulder problems. Furthermore, of all diagnosed cases, 64.7% involved neck issues and 65.5% involved shoulder issues. This high prevalence indicates that neck and shoulder disorders are widespread among individuals diagnosed with WRULDs. Moreover, despite a majority of participants being exposed to various risk factors, including 68.3% reporting working more than eight hours per day, no significant relationship was found between these risk factors and WRULDs. The analysis also showed a p-value close to the threshold for statistical significance (0.075) concerning the ergonomic layout of work areas, suggesting a potential but not significant link between ergonomically designed environments and WRULDs. On the other hand, a significant association (p-value of 0.000) was observed between experiencing pain and having WRULDs, highlighting a strong association. However, since cross-sectional studies cannot establish causation, the reported pain might be a consequence rather than a risk factor for WRULDs. Additionally, only 14.4% of participants received training in WRULD prevention and ergonomic equipment usage, while 85.6% did not. This indicates a need for increased training efforts to potentially reduce WRULDs and improve workplace ergonomics. Lastly, 90% of the participants were not aware of any interventions that are currently in place to reduce occurrence of WRULDs. These findings present opportunities for the company to implement measures and initiatives to reduce WRULDs.
Keywords: Work-related Upper Limb Disorders, risk factors, mining.