Volume 16, Issue 3 (2019)
ioh 2019, 16(3): 47-57 |
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Soltanzadeh A, Heidari H R, Mahdinia M, mohammadi H, Mohammad beighi A, mohammadfam I. Path analysis of occupational injuries based on the structural equation modeling approach: a retrospective study in the construction industry. ioh 2019; 16 (3) :47-57
URL: http://ioh.iums.ac.ir/article-1-2542-en.html
URL: http://ioh.iums.ac.ir/article-1-2542-en.html
Ahmad Soltanzadeh 
, Hamid reza Heidari , Mohsen Mahdinia , Heidar Mohammadi , Abolfazal Mohammad beighi , Iraj Mohammadfam *
, Hamid reza Heidari , Mohsen Mahdinia , Heidar Mohammadi , Abolfazal Mohammad beighi , Iraj Mohammadfam *
Hamadan Medical Science University , mohammadfam@umsha.ac.ir
Abstract: (4464 Views)
Background and aims:
The construction industry, sites, and projects are the most dangerous industries in terms of the risk of occupational accidents and injuries. Important factors that have led the industry as a health, safety, environment (HSE) high-risk industry in the world can be cited such as continuous changes in construction projects, using a lot of resources, poor working conditions, non-continuous employment, and cross-seasonal work, harsh environment. Risk of a variety of occupational accidents (e.g., fall, throwing objects, Slipping, Collision and crash, chemicals, electrical shock, Abrasion, and manual material handling, etc.), inherently exist in all construction projects. Given the existence of such risks, construction sites often fail to achieve their goals, such as the completion of the project, the estimated budget, project quality and expected extent of accidents and damages. In general, some studies have shown that the use of risk management systems in construction sites as each title and model, led to risk reduction in construction projects and sites. Also, this is a systematic approach and reasonable alternative to traditional and non-systematic methods used by many contractors. Risk management strategy in the construction industry can lead to efficient and effective results in terms of safety to construction sites including risk avoidance, risk transfer, reduce deaths and injuries, risk prevention and etc. Modeling and analysis of the indicators of the construction HSE risk management system to reduce the incidents and consequences of accidents, as well as its relationship with accidents, can be a very good self-monitoring approach, as has been shown in some studies, defects in the HSE management Risk system had allocated a high proportion (84%) in construction accidents. The analysis of occupational accidents and injuries could improve safety and health in the construction industry. Occupational safety and health challenges are tied largely to the construction industry. Various studies have reported catastrophic statistical data despite the many efforts made in this industry to reduce occupational accidents and injuries. The reported injury rate for the construction industry is higher than its average rate across all other industries and workers’ compensation costs of treatment, injuries, and fines in the construction industry are 4 times higher than those in other industries. However, construction workers make up only 5% of the US workforce, this industry accounts for 20% of all work-related deaths and 9% of disabling injuries. In developed countries, the rate of occupational accidents in the construction industry is 17%. This rate is 45% in Iran which is 2.6 times the global rate. Although construction workers make up less than 12% of Iran’s workforce, the rate of injuries caused by accidents in this industry is high. Identifying the factors affecting occupational injuries is a retrospective approach to analyze, prevent and reduce these injuries. However, researchers in various fields have attempted to describe various types of injury to analyze the factors affecting them, the significant point in most of the previous studies is that only some causes of accidents and injuries are addressed and the interaction of these variables are not investigated, nor the path analysis for the incidence of injuries or accidents is provided. One of the most effective accident analysis techniques developed to understand and explain the causes of events and analyze the path leading to accidents and their consequences is RCA (Root Cause Analysis). The use of software modeling approaches that can identify and analyze the relationship between variables and factors involved in the process of causative events as well as identifying the causes of accidents can be useful. Accordingly, the purpose of this study is to analyze the path of causes resulting in occupational injuries involved in construction work by using structural equation modeling.
Method:
This study was a cross-sectional retrospective analysis of occupational injuries that occurred in 82 small and medium-sized construction projects during the 11 years (2007-2017). The statistical population included all occupational injuries that occurred in construction projects. The main variables in this study were different types of injuries caused by occupational accidents. The initial size of the statistical population was 1328 accidents. Therefore, 1232 accidents were selected as the study sample based on the inclusion and exclusion criteria. It should be noted that the minimum sample size for analysis of a structural model should not be less than 200. The main tool for collecting data in this study was a checklist for reporting occupational accidents in construction projects. Interviews and records were also used to complete the data.
The implementation of the study included "five steps".
Step 1: Primary data (1328 accidents) were collected. Then, screening was done based on the inclusion/exclusion criteria and finally, 1232 accidents leading to injuries were selected as the final sample of the study.
Step 2: occupational injuries were analyzed based on Root Cause Analysis (RCA). In this analysis, three questions were answered: “What happened?", "how?" and "why?". The executive stages of answering the three questions included a descriptive examination of the injury, sequencing of the events, identifying the factors affecting the incidence, collecting complementary data and identifying the causal chain.
Step 3: Different dimensions of various factors affecting occupational injuries in the construction projects were identified, evaluated and classified. This step aimed at preparing the data for promoting the capability of the conceptual model for structural equation modeling (SEM).
Step 4: A conceptual model for analyzing the causes of construction injuries was drawn following the chain of events and path analysis.
Step 5: Finally, the associations, interactions, and effects of all factors and variables were analyzed using the structural equation modeling.
Applying IBM SPSS AMOS version 0.22, the structural equation modeling was used for data analysis. It is noteworthy that the structural equation modeling is a general and powerful multivariate analysis technique within the family of multiple regression analysis. In other words, it is the extension of the general linear model that allows a set of regression equations to be simultaneously tested. Structural equation modeling is a comprehensive statistical approach for testing hypotheses about relationships among visible and latent variables. It is called covariance structure modeling, causal modeling or structural equation modeling.
Results:
Generally, the results of structural equation modeling showed that occupational injuries are reversely related to individual factors, organizational factors, safety training, and risk management, whereas they are positively related to unsafe conditions and actions and the type of accident. The descriptive results of the factors and variables are shown that the average age and work experience of the injured workers were 6.24 ±33.41 and 3.14 ±5.75 years, respectively. Approximately, two-thirds of the accidents had occurred during construction activities and more than 70% of the accidents had occurred for small contractors. The desirability degrees of two key safety program parameters i.e. duration and content of the programs (quantity and quality) were estimated to be 23.5% and 12.0%, respectively. The highest degree of the desirability of risk management variables belonged to safety checklist (28.7%) and usage of personal protective equipment (PPE) (22.1%). Workplace hazards (63.6%) and dangerous work methods (56.1%) caused the highest share of accidents. The majority of unsafe actions were linked to inadequate knowledge and awareness (65.5%) and non-usage of Personal Protective Equipment (PPE) (57.9%). The most common accidents fell from height (31.2%) and falling objects (27%). The analysis of occupational injuries showed that 1.5% of the accidents had resulted in death and 10.4% had led to physical limb deformation. Path analysis of construction injuries based on SEM revealed that occupational injuries had a significant inverse relationship with individual and organizational factors, safety education and risk management (p<0.05). Also, occupational injuries had a significant positive relationship with unsafe conditions, unsafe actions and type of accidents (p <0.05) (Fig. 1). The values of the goodness of fit, χ2/df, RMSEA, CFI, and NNFI (TLI) were calculated to be 2.79, 0.059, 0.894, and 912 /, respectively. Therefore, based on these results and comparing them with the desired criteria, this model is acceptable.
Conclusion:
The findings of the study demonstrated that constructional injuries could be affected by a variety of factors and indicator variables with different sizes. Moreover, the application of path analysis approach using structural equation modeling can be a useful method for analysis, modeling, and prediction of occupational accidents and injuries. As the results of this study show, modeling based on path analysis can support the multiple causation theory of occupational accidents. Also, the use of software techniques and models such as SEM shows the correlation and interaction of different variables and factors as well as the numerical degree of their effects on ultimate injuries. This (as an indicator or parameter for decision-making) can contribute to macro safety management in construction projects. The findings of this study showed that different causative factors and related indicative variables including individual and organizational factors, safety education, risk management, unsafe conditions, and unsafe acts and the type of accident as a set of causes, have been involved in the chain and process leading to injuries caused by construction accidents. Regarding the type of accident, fall from height is considered as the most important indicative variable, so this variable is important for construction injury analysis. For decades, "fall from a height" has been at the top of the list of accident types among construction accidents. Unsafe working conditions in construction projects are among the most important factors in construction injury analysis. Also, as the results of this study show, some factors such as imperfect and weak risk management and organizational factors can contribute to the creation of these unsafe conditions. The results of some studies indicate that a worker or work team is involved in 70% of construction accidents due to human error and unsafe acts. Also, unsafe acts can be influenced by other variables and factors such as individual and demographic factors and safety education. Individual and demographic factors and their indicative variables are among the most important causes of occupational accidents, especially in the construction industry. Among the basic factors associated with occupational accidents and injuries are workplace management and organizational factors including organizational, physical and operational characteristic variables. These variables can cause problems for the safe implementation of the project and affect the events directly or indirectly (under the influence or in interaction with other factors). Inadequate and inefficient education can lead to imprecision, dangerous behaviors and various types of human error and affect the type and degree of injuries in construction activities. Some studies have also shown that risk identification and perception can be improved by educational interventions. Accordingly, paying attention to safety education and promoting education indicators will enhance risk perception and identification, improve safety and reduce the incidence of injury on the site. Based on the results, occupational injuries had significant correlations with hazard identification in construction, various types of risk assessment, accident analysis and effective event reporting, as well as implementing a variety of control measures such as personal protective equipment, practicing and supervising discipline on the construction site and holding safety-related meetings on the construction site. Considering that environmental construction projects are always accompanied by high risks, a systematic and efficient approach to identify, assess, control and reduce risks can be useful for optimal safety system performance and reduction of construction injuries. Consequently, the new and different perspective of this study on various variables (in the form of macro organizational factors, safety education and risk management) along with settling the construction affairs including unsafe conditions and unsafe acts, as well as analyzing the type of accident based on the center of incidence represent an important finding: promoting safety in the construction sector requires a comprehensive planning. This planning should be based on an intelligent model using all variables and factors affecting occupational injuries. A general overview of the findings of this study shows that inter and intra-factor relationships are always effective in occupational injuries in the construction or any other industrial environment. Therefore, accidents and injuries should be analyzed via modern scientific approaches and techniques and the decisions to increase safety and reduce injuries should be made based on the results of this type of modeling.
The construction industry, sites, and projects are the most dangerous industries in terms of the risk of occupational accidents and injuries. Important factors that have led the industry as a health, safety, environment (HSE) high-risk industry in the world can be cited such as continuous changes in construction projects, using a lot of resources, poor working conditions, non-continuous employment, and cross-seasonal work, harsh environment. Risk of a variety of occupational accidents (e.g., fall, throwing objects, Slipping, Collision and crash, chemicals, electrical shock, Abrasion, and manual material handling, etc.), inherently exist in all construction projects. Given the existence of such risks, construction sites often fail to achieve their goals, such as the completion of the project, the estimated budget, project quality and expected extent of accidents and damages. In general, some studies have shown that the use of risk management systems in construction sites as each title and model, led to risk reduction in construction projects and sites. Also, this is a systematic approach and reasonable alternative to traditional and non-systematic methods used by many contractors. Risk management strategy in the construction industry can lead to efficient and effective results in terms of safety to construction sites including risk avoidance, risk transfer, reduce deaths and injuries, risk prevention and etc. Modeling and analysis of the indicators of the construction HSE risk management system to reduce the incidents and consequences of accidents, as well as its relationship with accidents, can be a very good self-monitoring approach, as has been shown in some studies, defects in the HSE management Risk system had allocated a high proportion (84%) in construction accidents. The analysis of occupational accidents and injuries could improve safety and health in the construction industry. Occupational safety and health challenges are tied largely to the construction industry. Various studies have reported catastrophic statistical data despite the many efforts made in this industry to reduce occupational accidents and injuries. The reported injury rate for the construction industry is higher than its average rate across all other industries and workers’ compensation costs of treatment, injuries, and fines in the construction industry are 4 times higher than those in other industries. However, construction workers make up only 5% of the US workforce, this industry accounts for 20% of all work-related deaths and 9% of disabling injuries. In developed countries, the rate of occupational accidents in the construction industry is 17%. This rate is 45% in Iran which is 2.6 times the global rate. Although construction workers make up less than 12% of Iran’s workforce, the rate of injuries caused by accidents in this industry is high. Identifying the factors affecting occupational injuries is a retrospective approach to analyze, prevent and reduce these injuries. However, researchers in various fields have attempted to describe various types of injury to analyze the factors affecting them, the significant point in most of the previous studies is that only some causes of accidents and injuries are addressed and the interaction of these variables are not investigated, nor the path analysis for the incidence of injuries or accidents is provided. One of the most effective accident analysis techniques developed to understand and explain the causes of events and analyze the path leading to accidents and their consequences is RCA (Root Cause Analysis). The use of software modeling approaches that can identify and analyze the relationship between variables and factors involved in the process of causative events as well as identifying the causes of accidents can be useful. Accordingly, the purpose of this study is to analyze the path of causes resulting in occupational injuries involved in construction work by using structural equation modeling.
Method:
This study was a cross-sectional retrospective analysis of occupational injuries that occurred in 82 small and medium-sized construction projects during the 11 years (2007-2017). The statistical population included all occupational injuries that occurred in construction projects. The main variables in this study were different types of injuries caused by occupational accidents. The initial size of the statistical population was 1328 accidents. Therefore, 1232 accidents were selected as the study sample based on the inclusion and exclusion criteria. It should be noted that the minimum sample size for analysis of a structural model should not be less than 200. The main tool for collecting data in this study was a checklist for reporting occupational accidents in construction projects. Interviews and records were also used to complete the data.
The implementation of the study included "five steps".
Step 1: Primary data (1328 accidents) were collected. Then, screening was done based on the inclusion/exclusion criteria and finally, 1232 accidents leading to injuries were selected as the final sample of the study.
Step 2: occupational injuries were analyzed based on Root Cause Analysis (RCA). In this analysis, three questions were answered: “What happened?", "how?" and "why?". The executive stages of answering the three questions included a descriptive examination of the injury, sequencing of the events, identifying the factors affecting the incidence, collecting complementary data and identifying the causal chain.
Step 3: Different dimensions of various factors affecting occupational injuries in the construction projects were identified, evaluated and classified. This step aimed at preparing the data for promoting the capability of the conceptual model for structural equation modeling (SEM).
Step 4: A conceptual model for analyzing the causes of construction injuries was drawn following the chain of events and path analysis.
Step 5: Finally, the associations, interactions, and effects of all factors and variables were analyzed using the structural equation modeling.
Applying IBM SPSS AMOS version 0.22, the structural equation modeling was used for data analysis. It is noteworthy that the structural equation modeling is a general and powerful multivariate analysis technique within the family of multiple regression analysis. In other words, it is the extension of the general linear model that allows a set of regression equations to be simultaneously tested. Structural equation modeling is a comprehensive statistical approach for testing hypotheses about relationships among visible and latent variables. It is called covariance structure modeling, causal modeling or structural equation modeling.
Results:
Generally, the results of structural equation modeling showed that occupational injuries are reversely related to individual factors, organizational factors, safety training, and risk management, whereas they are positively related to unsafe conditions and actions and the type of accident. The descriptive results of the factors and variables are shown that the average age and work experience of the injured workers were 6.24 ±33.41 and 3.14 ±5.75 years, respectively. Approximately, two-thirds of the accidents had occurred during construction activities and more than 70% of the accidents had occurred for small contractors. The desirability degrees of two key safety program parameters i.e. duration and content of the programs (quantity and quality) were estimated to be 23.5% and 12.0%, respectively. The highest degree of the desirability of risk management variables belonged to safety checklist (28.7%) and usage of personal protective equipment (PPE) (22.1%). Workplace hazards (63.6%) and dangerous work methods (56.1%) caused the highest share of accidents. The majority of unsafe actions were linked to inadequate knowledge and awareness (65.5%) and non-usage of Personal Protective Equipment (PPE) (57.9%). The most common accidents fell from height (31.2%) and falling objects (27%). The analysis of occupational injuries showed that 1.5% of the accidents had resulted in death and 10.4% had led to physical limb deformation. Path analysis of construction injuries based on SEM revealed that occupational injuries had a significant inverse relationship with individual and organizational factors, safety education and risk management (p<0.05). Also, occupational injuries had a significant positive relationship with unsafe conditions, unsafe actions and type of accidents (p <0.05) (Fig. 1). The values of the goodness of fit, χ2/df, RMSEA, CFI, and NNFI (TLI) were calculated to be 2.79, 0.059, 0.894, and 912 /, respectively. Therefore, based on these results and comparing them with the desired criteria, this model is acceptable.
Conclusion:
The findings of the study demonstrated that constructional injuries could be affected by a variety of factors and indicator variables with different sizes. Moreover, the application of path analysis approach using structural equation modeling can be a useful method for analysis, modeling, and prediction of occupational accidents and injuries. As the results of this study show, modeling based on path analysis can support the multiple causation theory of occupational accidents. Also, the use of software techniques and models such as SEM shows the correlation and interaction of different variables and factors as well as the numerical degree of their effects on ultimate injuries. This (as an indicator or parameter for decision-making) can contribute to macro safety management in construction projects. The findings of this study showed that different causative factors and related indicative variables including individual and organizational factors, safety education, risk management, unsafe conditions, and unsafe acts and the type of accident as a set of causes, have been involved in the chain and process leading to injuries caused by construction accidents. Regarding the type of accident, fall from height is considered as the most important indicative variable, so this variable is important for construction injury analysis. For decades, "fall from a height" has been at the top of the list of accident types among construction accidents. Unsafe working conditions in construction projects are among the most important factors in construction injury analysis. Also, as the results of this study show, some factors such as imperfect and weak risk management and organizational factors can contribute to the creation of these unsafe conditions. The results of some studies indicate that a worker or work team is involved in 70% of construction accidents due to human error and unsafe acts. Also, unsafe acts can be influenced by other variables and factors such as individual and demographic factors and safety education. Individual and demographic factors and their indicative variables are among the most important causes of occupational accidents, especially in the construction industry. Among the basic factors associated with occupational accidents and injuries are workplace management and organizational factors including organizational, physical and operational characteristic variables. These variables can cause problems for the safe implementation of the project and affect the events directly or indirectly (under the influence or in interaction with other factors). Inadequate and inefficient education can lead to imprecision, dangerous behaviors and various types of human error and affect the type and degree of injuries in construction activities. Some studies have also shown that risk identification and perception can be improved by educational interventions. Accordingly, paying attention to safety education and promoting education indicators will enhance risk perception and identification, improve safety and reduce the incidence of injury on the site. Based on the results, occupational injuries had significant correlations with hazard identification in construction, various types of risk assessment, accident analysis and effective event reporting, as well as implementing a variety of control measures such as personal protective equipment, practicing and supervising discipline on the construction site and holding safety-related meetings on the construction site. Considering that environmental construction projects are always accompanied by high risks, a systematic and efficient approach to identify, assess, control and reduce risks can be useful for optimal safety system performance and reduction of construction injuries. Consequently, the new and different perspective of this study on various variables (in the form of macro organizational factors, safety education and risk management) along with settling the construction affairs including unsafe conditions and unsafe acts, as well as analyzing the type of accident based on the center of incidence represent an important finding: promoting safety in the construction sector requires a comprehensive planning. This planning should be based on an intelligent model using all variables and factors affecting occupational injuries. A general overview of the findings of this study shows that inter and intra-factor relationships are always effective in occupational injuries in the construction or any other industrial environment. Therefore, accidents and injuries should be analyzed via modern scientific approaches and techniques and the decisions to increase safety and reduce injuries should be made based on the results of this type of modeling.
Type of Study: Applicable |
Subject:
Safety
Received: 2018/06/4 | Accepted: 2018/12/8 | Published: 2019/08/31
Received: 2018/06/4 | Accepted: 2018/12/8 | Published: 2019/08/31
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