Abstract
Ready mixed concrete (RMC) industry, one of the barebones of construction sector, has its distinctive occupational safety and health (OSH) risks. Employees experience risks that emerge during the fabrication of concrete, as well as its delivery to the construction site. Statistics show that usage and demand of RMC have been increasing along with the number of producers and workers. Unfortunately, adequate OSH measures to meet this rapid growth are not in place even in top RMC producing countries, such as Turkey. Moreover, lack of statistical data and academic research in this sector exacerbates this problem. This study aims to fill this gap by conducting data mining in Turkish Social Security Institution archives and performing univariate frequency and cross tabulation analysis on 71 incidents that RMC truck drivers were involved. Also, investigations and interviews were conducted in seven RMC plants in Turkey and Netherlands with OSH point of view. Based on the results of this research, problem areas were determined such as; cleaning truck mixer/pump is a hazardous activity where operators get injured frequently, and struck by falling objects is a major hazard at RMC industry. Finally, Job Safety Analyses were performed on these areas to suggest mitigation methods.
Keywords: Dust, Ergonomics, Industrial accidents, Occupational health and safety management system, Work environments, Ventilation, Risk management
Introduction
Occupational injuries and illnesses in high risk sectors are considerably prevented with the maturation of the legislation, improvement of technology and development of occupational safety culture. However, this is not always the case particularly in project-based sectors, where risks are constantly changing compared to factory based production. For instance, construction, which is a project-based sector, holds higher ranks in fatal occupational injuries compared to other sectors. In the United States of America (USA) Out of 4,251 worker fatalities in private industry in calendar year 2014, 874 or 20.5% of them were in construction―that is, one in five worker deaths were in construction. This amount holds the first place compared to the other sectors1). The situation is not so different in other countries. Bomel2) notes that in Japan, construction accidents account for 30%–40% of the overall industrial accidents, with the total being 50% in Ireland and 25% in the United Kingdom. In Italy, fatal accidents in the field of construction represent 25% of the total accidents occurring in the industry3). In China, there were an estimated 3,000 construction industry fatalities in 2003 alone4). Globally, construction workers are seemingly three times more likely to be killed and twice as likely to be injured as workers in other occupations. Thus, construction industry needs to be further analyzed for reducing accident rates. Analyses and improvement efforts should include not only construction but also other sub-sectors such as ready mixed concrete industry, prefabricated construction industry, brick plants etc. These sectors should be examined separately because production processes are different from each other, as well as the potential hazards and recommended measures.
Ready Mixed Concrete (RMC) industry, which is one of the most essential sub-sectors of modern construction, is responsible for producing a construction material crucial for constructing engineering structures, such as roads and bridges, homes and high-rises. Combining of fine and coarse aggregates, cement and water is creating this important building material5). Most developed countries prefer to use RMC instead of conventional concrete production because of the advantages of RMC such as: speedy construction through programmed delivery at site, consistency in quality through accurate & computerized control of sand aggregates and water as per mix designs, mechanized operation with consequent economy, minimizing cement wastage due to bulk handling, reducing the labor cost and site supervising cost, proper control and economy in use of raw material resulting in saving of natural resources and reducing project time resulting in savings in all aspects6). Due to the reasons listed above, this product is increasingly being preferred specifically in modern construction. Increasing of RMC production at different countries is shown in Table 17). According to country data, U.S.A. is the top RMC producer in the world, followed by Turkey and Japan.
Table 1. Country data (Source EUROSTAT: http://ec.europa.eu/eurostat).
| Country | Total RMC country millions of m3 | ||
|---|---|---|---|
| 2011 | 2012 | 2013 | |
| Austria | 10,5 | 10,6 | 10,5 |
| Belgium | 11,6 | 12,5 | 12,5 |
| Czech Republic | 7,5 | 6,9 | 6,5 |
| Denmark | 2,1 | 2,0 | 2,3 |
| Finland | 3,0 | 2,7 | 2,7 |
| France | 41,3 | 38,9 | 38,6 |
| Germany | 48,0 | 46,0 | 45,6 |
| Ireland | 2,4 | 2,4 | 2,4 |
| Israel | 12,0 | 13,0 | 14,0 |
| Italy | 52,6 | 39,9 | 31,7 |
| Japan | 88,0 | 92,0 | 99,0 |
| Netherlands | 8,8 | 7,3 | 6,6 |
| Norway | 3,5 | 3,7 | 3,8 |
| Poland | 23,7 | 19,5 | 18,0 |
| Portugal | 6,1 | 3,7 | 2,7 |
| Russia | 40,0 | 42,0 | 44,0 |
| Slovakia | 2,3 | 1,9 | 1,7 |
| Spain | 30,8 | 21,6 | 16,3 |
| Sweden | 3,3 | 3,3 | — |
| Switzerland | 12,5 | 13,0 | 12,0 |
| Turkey | 90,0 | 93,0 | 102,0 |
| United Kingdom | 19,2 | 17,6 | 19,6 |
| USA | 203,0 | 225,0 | 230,0 |
Ready mix concrete plants have many more components to it. In other words, it is the assembly of tools and machines such as mixers, cement batchers, aggregate batchers, conveyors, radial stackers, aggregate bins, cement bins, heaters, chillers and cement silos as shown in Fig. 1. So, operations partially take place in the production area, where RMC is produced and loaded into mixer trucks. The second part of the operations continues outside the production area, where truck mixer transports the materials to a construction site and truck operator assists with the casting process.
Fig. 1.
Ready Mix Concrete Production34)
Despite its increasing growth and popularity, RMC industry has its distinctive risks in terms of occupational safety. The employees of this sector experience the risks that emerge not only during the fabrication process of concrete, but also during its delivery to the construction site. Potential hazards for workers in concrete manufacturing can be listed as: Eye, skin and respiratory tract irritation from exposure to cement dust, overexertion and awkward postures (ergonomics), slips, trips and falls, chemical burns from wet concrete, loss of stability, cutting and severing, hazards generated by vibration and radiation. The source of these hazards are usually derived from system failure, inadequate safety guards on equipment, inadequate lockout/tag out systems on machinery (mechanical and electrical hazards), ejection of parts or material, shearing hazards generated by noise, stabbing or puncture, friction or abrasion, high pressure fluid injection, combined hazards8, 9).
RMC industry in U.S.A. still suffers from safety problems, regardless of leading the world in RMC production with 5,000 plants and 68,500 trucks5). According to OSHA, more than 250,000 people work in concrete manufacturing in US. Unfortunately, of the hundreds of thousands who work in concrete product manufacturing, tens of thousands have experienced a job-related injury, illness or death. Over 10 percent of those workers - 28,000 - experienced a job-related injury or illness and 42 died in just one year8). The latest Bureau of Labor Statistics data (as of October, 2013) shows the RMC industry with an incident rate of 4.810).
There has been a tremendous growth in RMC production, particularly in Turkey, the second largest RMC producer. The production volume in Turkey rose from 26.542.905 m3 to 107.000.000 m3 over a period of 16 years as seen in Table 2. The number of the RMC plants also rose from 341 to 1,080 in the same period of time11). Nevertheless, occupational safety and health measures in Turkish RMC were not adequate to meet this production growth12). There have been numerous injury cases over the last ten years that ready mix concrete truck drivers were involved. However, records of these incidents are not being properly reported and recorded for future analyses by majority of Turkish RMC companies. Since safety and health is a rather new topic in RMC industry, statistical and academic studies are rarely found. Besides, there is high demand for training and consultation regarding occupational safety by RMC companies.
Table 2. RMC Industry’s profile in Turkey.
| Data from year | Total RMC millions of m3 | Number of Producers | Number of Plants |
|---|---|---|---|
| 1988 | 1,5 | 25 | 30 |
| 1993 | 10 | 70 | 110 |
| 1998 | 26,5 | 166 | 341 |
| 2003 | 26,8 | 238 | 429 |
| 2005 | 46,3 | 277 | 568 |
| 2006 | 70,7 | 409 | 718 |
| 2007 | 74,4 | 477 | 845 |
| 2008 | 69,6 | 462 | 825 |
| 2009 | 66,4 | 467 | 845 |
| 2010 | 79,6 | 500 | 900 |
| 2011 | 90,0 | 520 | 945 |
| 2012 | 93,0 | 540 | 980 |
| 2013 | 102,0 | 580 | 1,040 |
| 2014 | 107,0 | 600 | 1,080 |
Academic studies on RMC safety are not abundant either in other countries. A state-of-the-art research was performed on this topic and no articles printed on scientific journals discussing safety problems in RMC industry were encountered. It was also observed that there is a lack of practical knowledge that contains a holistic assessment of hazards and risks that might occur during manufacturing and handling of RMC. Only, guidelines and manuals printed by associations such as OSHA, ACPA, NSCSA are available to build safety awareness for RMC producers8, 13, 14). These manuals and reports are also constituted upon European Commission (EC) directives and standards9). A database that contains RMC incidents for further analysis is not available either due to the lack of academic studies. Therefore, it is not possible to perform studies to determine root causes of incidents occurring in RMC industry.
This study aims to fill this gap described above by conducting data mining in Turkish Social Security Institution archives and performing univariate frequency and cross tabulation analysis on incidents that RMC truck drivers were involved. Also, seven ready mixed concrete plants in both Turkey and Netherlands were visited, interviews were conducted with the key personnel of these plants and each phase of the production was investigated with occupational safety point of view. Based on the results of this research, problem areas were determined and Job Safety Analyses were performed on these areas to suggest mitigation methods.
Methods
The methodology of this study consists of three major sections. The first section addresses the data acquisition process and how incident data pertaining RMC industry was obtained. The second section is the statistical analysis portion of the methodology and includes univariate and cross-tabulation analyses performed on the acquired data. The final section is dedicated to the Job Safety Analysis of selected activities typically performed by RMC truck drivers, which are based on the results of statistical analysis.
Data acquisition
Finding national work-related accident data is a serious challenge in Turkey. Social Security Institute (SSI) of Turkey publishes annual data on their website available for public access. However, it is not possible to obtain detailed data, specifically within the scope of one chosen industry. Therefore, database used in this study was obtained from SSI’s archives located in Izmir, Istanbul and Ankara in Turkey with special permit to work in their offices. Since, the SSI archives contained all work-related injury reports in a single room regardless of industry or injury categorization system, datamining was performed among 2024 injury cases reported between 2010 and 2012. As a result of this study, 71 report forms related with RMC industry were handpicked and root causes of accidents determined from real cases. There have been no important changes during this period in compensation practices or in the way that accident data were collected and reported. Izmir, Istanbul and Ankara, as a most crowded three cities of Turkey, constitute 31% of general population15). Physically, collecting data from all cities is not possible, so these three cities rapidly develop were focused for study.
A new taxonomy was created to rearrange and prepare the collected data for descriptive statistical analysis. A total of 15 research variables, which were grouped under three different categories according to their relevance to their characteristics, were chosen for this study. These categories are time, accident, and worker characteristics.
Time characteristics variables were organized according to the injury occurrence date and included variables such as hour of the day, days of the week (including weekend) and months of the year.
Accident characteristics variables reveal plenty of information regarding the accident; in other words, they define the accident. Variables such as nature of injury, types of injury, damaged body part, source of injury (unsafe act or condition) were examined within the scope of the study. Tools/equipment being used during the injury was being selected as an additional category to obtain detailed information to determine risky operations.
Worker characteristics variables, addressing victim’s personal information, were listed under this group. Workers’ age group, worker’s task and responsibility, educational background, and duration of work experience are variables that described workers’ profile.
Univariate analysis
Univariate analysis is the simplest form of statistical analysis which includes describing a case in terms of a single variable; specifically, the distribution of the levels that compose it16). Babbie in his book also mentions that primary purpose of univariate analysis is descriptive where multivariate analysis is geared more towards explanatory purposes. In other words, it explains data and tells the researcher what he/she has in hand17). In vast majority of the construction safety literature the findings are based on univariate analysis and aimed at shedding light on problematic areas in this field, especially for accident causation18, 19, 20). In this research, univariate analysis was adopted for frequency analysis. The aim of the analysis was not only for data screening purposes; but also for understanding what we have and choosing the right variables for explanatory data analysis. Frequency tables were utilized for reporting findings of univariate analysis for total of 15 variables in this paper. Statistical Package for Social Sciences (SPSS) software was used for univariate analyses.
Cross-tabulation analysis
After conducting the univariate analysis, cross tabulation analysis was carried out to investigate whether a significant relationship between pairs of variables existed. Cross tabulation analysis produces a contingency table displaying the relationship, in the form of joint frequencies, of two or more variables. The rows indicating one variable while the columns indicating the other.
Determination of whether the relationship variables are statistically independent the joint frequency distribution can be analyzed by the Pearson chi-square statistic. Pearson chi-square compares the observed counts with those that would be expected if there were no association between two variables35).
Pearson chi-square tests the hypothesis whether the row and column variables are independent or dependent. For this research study, the null hypothesis (H0 and H1) that formulated was;
H0= There is no association between the variable and degree of injury
H1= There is an association between the variable and degree of injury
The p-value is the probability value that is used for hypothesis testing by the Pearson chi-square test. After finding the p-value, one can decide whether the result is significant or not (commonly taken as 0.05). Therefore, a p-value less than 0.05 is accepted as significant and allows researcher to reject the null hypothesis (H0) of no association, and conclude that there is an association between variables17).
If the null hypothesis is rejected, the next step is to determine the strength of this relationship. Phi (Ф) or Cramer’s V (crv) values are used to evaluate the strength of association between the variables. Phi is a chi-square-based measure of association that involves dividing the Pearson (X2) chi-square value by the sample size (N) and taking the square root of the result. Phi value can be calculated for only 2x2 contingency tables while Cramer’s V value can be calculated for tables with more than 2x2 rows and columns. Phi or Cramer’s values from 0 to 0.1 show a weak relationship; from 0.1 to 0.3 indicate a moderate relationship; and values between 0.3 and 1.0 suggest a strong relationship21). Due to symmetry, negative values of Ф are viewed to be the same as positive values. In this research, cross tabulation analysis was performed to determine statistical relationship and its strength between types of injury and other nominal variables. Results of cross tabulation analysis were presented using tables. Statistical Package for Social Sciences (SPSS) software was used for both univariate and bivariate statistical analyses.
Job safety analysis
Job safety analysis (JSA), which focuses on the interrelation among worker, task, tool and workplace environment, aims to define the hazards at each work item before their occurrence and produces solutions to completely eliminate the risks or to reduce the risks to acceptable levels22). The ideal is to sub-classify the work after defining uncontrollable hazards in order to completely eliminate these hazards or to reduce their risks to acceptable levels23). JSA might be adapted to almost all occupational groups. However, the branches of industry in which repeated processes are dominant are better being chosen in order to obtain economical and effective outputs24). The most important advantage of this method is the fact that the method is not entirely based on personal assessments and the hazard analysis is performed simultaneously with the work itself25).
JSA, in this study, was performed based on findings coming from statistical analysis and site visits conducted at seven different RMC plants located in Turkey and Netherlands. The analysis was divided into two sections: “Production area” and “casting site”, and two different JSA forms were created accordingly, since, the processes are largely different from each other due to their nature. First column (operation) of the forms lists typical activities that workers engage in, either at production area or casting site. Variables used in “Responsibility” category were the primary source to determine typical activities. All possible hazards that workers could be exposed to during these operations are listed in the second column (hazard). Hazard related information was primarily obtained from observations and interviews with the key personnel of visited plants. In addition univariate analysis results were taken into consideration. Variables used in “Type of injury” category were integrated at this stage such as; falls, struck by falling objects, road accidents etc. Finally, third column (safety measure) on the forms suggested solutions for safety problems. Safety measures were mostly based on the information obtained from site visits to RMC plants. During these visits, safety managers and personnel were interviewed to understand proper safety measures. While some of these recommended measures were already in place, some did not exist due to budget restrictions. Also, observing the operations while they were being conducted and interviewing with the workers who performed the job played key roles to come up with some of the safety measures. In addition, searching the safety literature to find best practices helped supporting the suggested measures.
Results of Statistical Analysis
As addressed above, statistical analysis of the study focused on 71 work-related injury cases that occurred in three major cities (Izmir, Ankara and Istanbul) of Turkey. Findings of the analyses are summarized below:
Time characteristics (work hour, day and month) on which the injury occurred are demonstrated in Table 3. It was observed that a larger proportion of the RMC industry workers’ incidents occurred in the hours between 12:01 p.m. and 16:00 p.m. (26.8%). On Mondays and Thursdays, there was a slight increase in the number of injuries (23.9%) as demonstrated in Table 3. Furthermore, the rate of work-related occupational injuries was high during weekends, being 15.5% on Saturdays and 9.9% on Sundays. It also was determined that 16.9% of workers having work-related occupational injuries had been working on January (Table 3-Time Characteristics of RMC Industry Work-Related Accidents).
Table 3. Time characteristics of RMC Industry Work-Related Accidents.
| Hour of injury | No. of injury | % of injury | Month of injury | No. of injury | % of injury |
|---|---|---|---|---|---|
| 12.01–16.00 | 19 | 26.8 | January | 12 | 16.9 |
| 08.00–12.00 | 17 | 23.9 | October | 9 | 12.7 |
| 16.01–20.00 | 17 | 23.9 | March | 9 | 12.7 |
| 20.01–24.00 | 8 | 11.3 | December | 9 | 12.7 |
| Unknown | 6 | 8.5 | February | 7 | 9.9 |
| 24.01–08.00 | 4 | 5.6 | June | 6 | 8.5 |
| Day of injury | No. of injury | % of injury | November | 5 | 7.0 |
| Monday | 17 | 23.9 | July | 4 | 5.6 |
| Thursday | 17 | 23.9 | May | 4 | 5.6 |
| Saturday | 11 | 15.5 | April | 3 | 4.2 |
| Tuesday | 10 | 14.1 | August | 2 | 2.8 |
| Sunday | 7 | 9.9 | September | 1 | 1.4 |
| Wednesday | 5 | 7.0 | |||
| Friday | 4 | 5.6 | |||
The results of univariate analysis on accident characteristics are presented in Table 4. The evaluation of type of injuries in ready-mix concrete industry has revealed that in 22 cases (31.0%) falls, in 19 of cases (26.8%) struck by falling object, and in 12 cases (16.9%) caught in or between objects were the cause of accident. Most encountered nature of injury has been found to be superficial injury and open wound (28.2%). Upper extremity damage has caused 28 workers (39.4%) injury.
Table 4. Accident characteristics of RMC Industry Work-Related Accidents.
| Nature of injury | No. of injury | % of injury | Damaged body part | No. of injury | % of injury |
|---|---|---|---|---|---|
| Superficial Injury/Open Wound | 20 | 28.2 | Upper Extremity | 28 | 39.4 |
| Bruises | 9 | 12.7 | Lower Extremity | 16 | 22.5 |
| Fractures | 9 | 12.7 | Head | 14 | 19.7 |
| Ache/Pain | 8 | 11.3 | Multi-Injury | 7 | 9.9 |
| Cut | 7 | 9.9 | Whole Body | 3 | 4.2 |
| Foreign Body In Eyes | 7 | 9.9 | Back | 2 | 2.8 |
| Sprain/Dislocation | 4 | 5.6 | Innards | 1 | 1.4 |
| Concussion/Internal Bleeding | 3 | 4.2 | Tools/Equipment | No. of injury | % of injury |
| Fatality | 2 | 2.8 | Building Material | 25 | 35.2 |
| Electric Shock | 1 | 1.4 | Truck Mixer | 24 | 33.8 |
| Thermal/Chemical Burns | 1 | 1.4 | Concrete Pump | 7 | 9.9 |
| Type of injury | No. of injury | % of injury | No Tool | 6 | 8.5 |
| Fall | 22 | 31,0 | Manuel/Auto Hand Tools | 5 | 7.0 |
| Struck By Falling Object | 19 | 26.8 | Production Line | 4 | 5,6 |
| Caught In Or Between Objects | 12 | 16.9 | Unsafe Act/Condition | No. of injury | % of injury |
| Foreign Object In Body | 7 | 9.9 | Loss of Balance | 22 | 31.0 |
| Road Accident | 4 | 5.6 | Uncontrolled Object Movement | 15 | 21.1 |
| Inj. Resulting From Body Strain | 3 | 4.2 | No PPE Usage | 11 | 15.5 |
| Bite/Sting/Scratch | 2 | 2.8 | Wrong Working Methods | 10 | 14.1 |
| NSD Heat Exposure | 1 | 1.4 | Defective Equipment In Use | 4 | 5,6 |
| Electrocution | 1 | 1.4 | Inappropriate Position For Task | 3 | 4.2 |
| Unknown | 3 | 4.2 | |||
| Insufficient Housekeeping Prog. | 3 | 4.2 | |||
Tragically, in this study, it is determined that 15.5% of those who had occupational accidents did not use personal protective equipment, particularly workers who worked at high elevations. In addition, loss of balance has caused injuries to 22 workers (31.0%) (Table 4-Accidents Characteristics of RMC Industry Work-Related Accidents). The major tools that have caused the accident are and building materials (35.2%) and truck mixer (33.8%).
The age of injured workers has also been evaluated, and 21.1% of these workers belong to the age group of 30–34 as shown in Table 5. According to their task, the majority of victims (45.1%) was truck mixer operator and had elementary education as an educational background (35.2%). The most surprising record we have found was that 18 workers (%25.4) have injured after more than two years’ experience they started to work. It is also ascertained distribution of the causes of injuries in various responsibilities in the ready-mix concrete industry. The date showed that workers who made maintenance and repair had a significant risk (40.8%) at ready-mix concrete industry. In addition, workers who cleaned the truck mixer were second risky group that have injured at ready-mix concrete industry with 25.4% proportion of injury. The majority of the injured workers (70.4%) in the ready-mix concrete industry had been worked at production area with less than 50 workers (47.9%) (Table 5-Worker Characteristics of RMC Industry Work-Related Accidents).
Table 5. Worker Characteristics of RMC Industry Work-Related Accidents.
| Age groups | No. of injury | % of injury | Responsibility | No. of injury | % of injury |
|---|---|---|---|---|---|
| 30–34 | 15 | 21.1 | Maintenance/Repair | 29 | 40.8 |
| 40–44 | 14 | 19.7 | Mixer/Pump Cleaning | 18 | 25.4 |
| 25–29 | 12 | 16.9 | Control Of Mechanism | 7 | 9.9 |
| 35–39 | 12 | 16.9 | Concrete Casting | 7 | 9.9 |
| Unknown | 6 | 8.5 | Truck Mixer Traffic to Casting Site | 7 | 9,9 |
| 19–24 | 5 | 7.0 | Materials Carrying | 2 | 2.8 |
| 45–49 | 4 | 5.6 | Rest | 1 | 1.4 |
| 50–54 | 3 | 4.2 | Duration of work experience | No. of injury | % of injury |
| Educational background | No. of injury | % of injury | >24 Months | 18 | 25.4 |
| Elementary Education | 25 | 35.2 | 3–6 Months | 14 | 19.7 |
| Unknown | 18 | 25.4 | 31.D-3 Months | 11 | 15.5 |
| Post Primary Education | 12 | 16.9 | 6–12 Months | 10 | 14.1 |
| Higher Education | 9 | 12.7 | 12–24 Months | 7 | 9.9 |
| Lettered | 4 | 5.6 | Unknown | 5 | 7.0 |
| University | 2 | 2.8 | 2–4 Weeks | 3 | 4.2 |
| Non Lettered | 1 | 1.4 | 1. Week | 2 | 2.8 |
| Worker’s task | No. of injury | % of injury | Beginning At Same Day | 1 | 1.4 |
| Truck Mixer Operator | 32 | 45.1 | Working Environment | No. of injury | % of injury |
| Manufacturing/Maintainer | 22 | 31.0 | Production Area | 50 | 70.4 |
| Pump Operator | 17 | 23.9 | Casting Site | 15 | 21.1 |
| Number of Workers | No. of injury | % of injury | Transportation | 6 | 8.5 |
| <50 | 34 | 47.9 | |||
| >50 | 32 | 45.1 | |||
| Unknown | 5 | 7.0 | |||
In the cross tabulation analysis section of the study, the relationship between types of injury and other nominal variables were investigated and each analysis was interpreted. Only four of the variables (Working environment, tools, unsafe act/condition and responsibility) were found statistically significant as shown in Table 6. According to results (Cramer’s ν) one can say types of injury had strong relationship with working environment, tools, unsafe act/condition and worker’s responsibility. The second stage of cross tabulation analysis involved analyzing type of injury categories versus each statistically significant variable category. Thus, major factors and categories affecting the occurrence of accident were determined. The results of this stage are summarized below.
Table 6. Contingency table–Types of Injury vs. nominal variables.
| Variables | Pearson’s chi-square X2(df), probability (p) | Phi & Cramer’s V (crv) | |||
|---|---|---|---|---|---|
| Working Environment | X2(16)=33.970 | p=0.005 | crv(16)=0.692 | p=0.005 | |
| Tools | X2(40)=70.481 | p=0.002 | crv(40)=0.446 | p=0.002 | |
| Unsafe Act/condition | X2(56)=196.502 | p=0.000 | crv(56)=0,643 | p=0.000 | |
| Worker’s Responsibility | X2(48)=75.633 | p=0.005 | crv(48)=0.421 | p=0.005 | |
The cross tabulation analysis between working environment and types of injury showed that (Table 7), injury categories such as falls (77.3%), foreign object in body (85.7%) and struck by falling object (84.2%) were observed mostly at RMC production area, while road accidents were mostly observed during transportation as expected (75%). In addition, 50% of bite/sting/scratch typed injuries occurred at casting site.
Table 7. Contingency table–Types of Injury and Working Environment.
| Working Environment | Total | ||||
|---|---|---|---|---|---|
| Casting Site | Transportation | Production Area | |||
| Type of Injury |
Fall | 4 (18.2%) | 1 (4.5%) | 17 (77.3%) | 22 (100.0%) |
| Struck By Falling Object | 2 (10.5%) | 1 (5.3%) | 16 (84.2%) | 19 (100.0%) | |
| Caught In Or Between Objects | 4 (33.3%) | 1 (8.3%) | 7 (58.3%) | 12 (100.0%) | |
| Foreign Object In Body | 1 (14.3%) | 0 (0.0%) | 6 (85.7%) | 7 (100.0%) | |
| Road Accident | 1 (25.0%) | 3 (75.0%) | 0 (0.0%) | 4 (100.0%) | |
| Inj. Resulting From Body Strain | 1 (33.3%) | 0 (0.0%) | 2 (66.7%) | 3 (100.0%) | |
| Bite/Sting/Scratch | 1 (50.0%) | 0 (0.0%) | 1 (50.0%) | 2 (100.0%) | |
| NSD Heat Exposure | 0 (0.0%) | 0 (0.0%) | 1 (100.0) | 1 (100.0%) | |
| Electrocution | 1 (100.0%) | 0 (0.0%) | 0 (0.0%) | 1 (100.0%) | |
| Total | 15 (100.0%) | 6 (8.5%) | 50 (70.4%) | 71 (100.0%) | |
According to cross tabulation analysis between types of injury and tools, it was observed that 52.6% of struck by falling object injuries were caused by building materials as shown in Table 8. Truck mixers have caused 75% of road accidents, 50% of falls and 41.7% of caught in or between objects. Workers who worked close to production line got injured resulting from body strain (33.3%) and caught in or between objects (16.7%).
Table 8. Contingency table–Types of Injury and Tools/Equipment.
| Tools | Total | |||||||
|---|---|---|---|---|---|---|---|---|
| No Tool | Building Material |
Manuel/Auto Hand Tools |
Truck Mixer | Production Line |
Concrete Pump |
|||
| Type of Injury |
Fall | 5 (22.7%) | 2 (9.1%) | 0 (0.0%) | 11 (50.0%) | 1 (4.5%) | 3 (13.6%) | 22 (100.0%) |
| Struck By Falling Object | 0 (0.0%) | 10 (52.6%) | 3 (15.8%) | 5 (26.3%) | 0 (0.0%) | 1 (5.3%) | 19 (100.0%) | |
| Caught In Or Between Objects | 0 (0.0%) | 2 (16.7%) | 1 (8.3%) | 5 (41.7%) | 2 (16.7%) | 2 (16.7%) | 12 (100.0%) | |
| Foreign Object In Body | 0 (0.0%) | 7 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 7 (100.0%) | |
| Road Accident | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 3 (75.0%) | 0 (0.0%) | 1 (25.0%) | 4 (100.0%) | |
| Inj. Resulting From Body Strain | 1 (33.3%) | 1 (33.3%) | 0 (0.0%) | 0 (0.0%) | 1 (33.3%) | 0 (0.0%) | 3 (100.0%) | |
| Bite/Sting/Scratch | 0 (0.0%) | 2 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 2 (100.0%) | |
| NSD Heat Exposure | 0 (0.0%) | 1 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 1 (100.0%) | |
| Electrocution | 0 (0.0%) | 0 (0.0%) | 1 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 1 (100.0%) | |
| Total | 6 (100.0%) | 25 (100.0%) | 5 (100.0%) | 24 (100.0%) | 4 (100%) | 7 (100%) | 71 (100.0%) | |
The cross tabulation analysis between types of injury and unsafe act/condition was also performed. It was observed that 66.7% of injuries caused by inappropriate position for task and 33.3% of injuries caused by defective equipment in use resulted with body strain. When fall injuries were examined from unsafe act/condition point of view, it was seen that nearly all of (95.5%) loss of balance injuries resulted in falls. At the same time, as an unsafe act/condition, wrong working methods (50%) was the major factor for caught in or between objects (Table 9).
Table 9. Contingency table – Types of Injury and Unsafe Act/Condition.
| Unsafe Act/Condition | Total | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Inapp. Position For Task |
Wrong Working Methods |
Insufficient Housekeeping Prog. |
No PPE Usage |
Loss of Balance |
Defective Equipment In Use |
Uncontro. Object Movement |
Unknown | |||
| Type of Injury |
Fall | 0 (0.0%) | 0 (0.0%) | 1 (4.5%) | 0 (0.0%) | 21 (95.5%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 22 (100.0%) |
| Struck By Falling Object | 1 (5.3%) | 1 (5.3%) | 1 (5.3%) | 2 (10.5%) | 0 (0.0%) | 1 (5.3%) | 13 (68.4%) | 0 (0.0%) | 19 (100.0%) | |
| Caught In Or Between Objects | 0 (0.0%) | 6 (50.0%) | 1 (8.3%) | 1 (8.3%) | 0 (0.0%) | 2 (16.7%) | 2 (16.7%) | 0 (0.0%) | 12 (100.0%) | |
| Foreign Object In Body | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 7 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 7 (100.0%) | |
| Road Accident | 0 (0.0%) | 1 (25.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 3 (75.0%) | 4 (100.0%) | |
| Inj. Resulting From Body Strain | 2 (66.7%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 1 (33.3%) | 0 (0.0%) | 0 (0.0%) | 3 (100.0%) | |
| Bite/Sting/Scratch | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 1 (50.0%) | 1 (50.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 2 (100.0%) | |
| NSD Heat Exposure | 0 (0.0%) | 1 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 1 (100.0%) | |
| Electrocution | 0 (0.0%) | 0 (0.0%) | 1 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 1 (100.0%) | |
| Total | 3 (100.0%) | 9 (100.0%) | 4 (100.0%) | 11 (100.0%) | 22 (100.0%) | 4 (100.0%) | 15 (100.0%) | 3 (100.0%) | 71 (100.0%) | |
The cross tabulation analysis between worker’s responsibility and types of injury was performed as a final analysis (Table 10). The data showed that during the mixer/pump cleaning process foreign object in body (71.4%), bite/sting/scratch (50%) and struck by falling object (31.6%) were the three major types of injury. When maintenance/repair process was analyzed from type of injury point of view it is also observed that caught in or between objects (66.7%), struck by falling object (52.6%) and falls (36.4%) were the three major categories.
Table 10. Contingency table–Types of Injury and Responsibility.
| Responsibility | Total | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Control Of Mechanism |
Truck Mixer Traffic to Casting Site |
Materials Carrying |
Concrete Casting |
Rest | Mixer/Pump Cleaning |
Maintenance/ Repair |
|||
| Type of Injury |
Fall | 4 (18.2%) | 4 (18.2%) | 0 (0.0%) | 1 (4.5%) | 1 (4.5%) | 4 (18.2%) | 8 (36.4%) | 22 (100.0%) |
| Struck By Falling Object | 2 (10.5%) | 0 (0.0%) | 1 (5.3%) | 0 (0.0%) | 0 (0.0%) | 6 (31.6%) | 10 (52.6%) | 19 (100.0%) | |
| Caught In Or Between Objects | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 2 (16.7%) | 0 (0.0%) | 2 (16.7%) | 8 (66.7%) | 12 (100.0%) | |
| Foreign Object In Body | 1 (14.3%) | 0 (0.0%) | 0 (0.0%) | 1 (14.3%) | 0 (0.0%) | 5 (71.4%) | 0 (0.0%) | 7 (100.0%) | |
| Road Accident | 0 (0.0%) | 3 (75.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 1 (25.0%) | 4 (100.0%) | |
| Inj. Resulting From Body Strain | 0 (0.0%) | 0 (0.0%) | 1 (33.3%) | 1 (33.3%) | 0 (0.0%) | 0 (0.0%) | 1 (33.3%) | 3 (100.0%) | |
| Bite/Sting/Scratch | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 1 (50.0%) | 0 (0.0%) | 1 (50.0%) | 0 (0.0%) | 2 (100.0%) | |
| NSD Heat Exposure | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 1 (100.0%) | 1 (100.0%) | |
| Electrocution | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 1 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 1 (100.0%) | |
| Total | 7 (100.0%) | 7 (100.0%) | 2 (100.0%) | 7 (100.0%) | 1 (100.0%) | 18 (100.0%) | 29 (100.0%) | 71 (100.0%) | |
Results of Job Safety Analysis
JSA performed in this study generated two different forms that display potential hazards and their corresponding safety measures. Results of JSA pertaining operations at production area and casting site can be seen in Table 11 and Table 12 respectively.
Table 11. JSA of Operations at Production Area.
| Operation | Hazard | Safety Measure |
|---|---|---|
| Control/maintenance/repair -Aggregate belt conveyors and feeders |
Trapping between conveyor belts in motion and head/tail drums | Tail and head drums, moving parts should be protected |
| Warning signs to prohibit working on belts in motion should be installed | ||
| Single switch operation of belts and conveyors should be enabled | ||
| Emergency stop lines should be designed along length of conveyor belts | ||
| All staff should be trained in the isolation procedure which must be implemented before any guards or protection is removed | ||
| Falling from upper parts of belt | Walkways should be designed by grooved or perforated anti-slip floors | |
| Safety handrails along all walkways should be designed | ||
| Usage of firmly attached safety belts during maintenance should be controlled | ||
| Falling object | Trays/pans should be used to catch material falling from belts, | |
| Protective covers on undersides of conveyor belts should be supplied | ||
| Falls into hopper | Design barriers around grid and hoppers or grille over hoppers should be designed | |
| Production of dust | Protective covering should be supplied to conveyors to minimize dust | |
| Mixer/pump cleaning -Worker climbs to the top of truck mixer to clean up |
Falls from the top of mixer | Safe access platform in mixing area should be used |
| Warning signs to draw attention of drivers if slippery surfaces on site cannot be eliminated | ||
| Truck drivers should be informed about ergonomic risk factors | ||
| Ladders on truck mixers should be inspected for defects before every usage | ||
| Mixer/pump cleaning -Worker gets inside truck mixer drum to clean debris and remove hardened concrete |
Working at confined spaces and exposure to silica dust while removing hardened concrete inside the drum | Wet methods should be used during mixer drum cleaning |
| Ventilation should be used during mixer drum cleaning | ||
| Usage of water spray attachments for chipping tools and wetting procedures should be supplied and ensured | ||
| All activities staged inside mixer drums should be done with pneumatic chipping tools. | ||
| Supplement engineering and work practice controls with respirators should be supplied | ||
| Guard against heat stress when cleaning truck mixer drums should be supplied with air conditioning | ||
| Drivers should wear respiratory mask to avoid silica exposure when removing concrete residues from inside truck mixer drums | ||
| Chemical burns from cleaning operations. | Drivers should be trained to avoid direct contact with concrete during the removal of hardened concrete process and correct operation of truck mixers including maintenance and cleaning | |
| Protective clothing should be used for hands, eyes, ears, head during cleaning | ||
| Trapping, amputations by mixing mechanism | Implement programs for machine guarding and lockout/tag out should be designed | |
| All moving parts should be covered by protection covers | ||
Table 12. JSA of Operations at Casting Site.
| Operation | Hazard | Safety Measure |
|---|---|---|
| Transportation | Traffic Accidents | Truck mixer drivers should observe traffic rules when driving on road |
| Noise | Truck mixer drivers should be suggested listening to low tone music in the trucks in-stead of high tone | |
| Noise sources in the trucks should be reduced by installing noise transmission barriers and using preventive maintenance | ||
| Ergonomic risk factors | Install equipment that helps drivers minimize twisting and turning while in the cab | |
| Whole-body vibration in truck cabs should be reduced by methods such as isolating cab from vibrations, using air-ride suspended seats, and using adjustable, well-padded seats and backrests | ||
| Arrange implementation of frequent (hourly) rest breaks for drivers exposed to extensive whole-body vibration | ||
| Train the truck drivers to avoid awkward and fixed postures | ||
| Extremes of temperature | Air conditioner should be used | |
| Slump checking and adding water or admixtures to the mix | Falling Falls from the top of mixer during | A guard at the top opening of the mixer drum can protect drivers from falling into drums during checking slump |
| Concrete casting | Noise | Provide flat attenuation hearing protection devices and control the usage of them (PPE) |
| Repeat sound-level measurements and audiometric testing | ||
| Falling while climbing and descending truck cab and equipment | To eliminate the need to climb onto trucks and to minimize ladder use reconfiguration of water tanks and other truck equipment should be planned | |
| At the top opening of the mixer drum a protective guard should be installed | ||
| To enable drivers to reach the upper parts of trucks during washing and inspection activities elevated platform with stairways and guardrails should be installed | ||
| Drivers should be informed about ergonomic risks | ||
| Inspect the ladders on truck mixers for defects before every usage | ||
| Skin contact with concrete and admixtures, which may contain irritant and sensitizing materials | Implement a system that deals with selection and distribution of gloves and training of workers on proper usage of gloves during the discharge process. | |
| Instruct the truck drivers on personal hygiene particularly after the discharge process | ||
| Eye Injuries | Implement PPE usage for eye protection. | |
| Extremes of temperature | Regulate the truck drivers’ daily work schedule considering their previous shifts | |
| Rollovers while driving and unloading on unstable, uneven or steep ground at delivery sites | Train the operators not to start the discharging operation until safely park position of the truck has been secured | |
| Ergonomic Risk Factors | Train the truck drivers to avoid awkward and fixed postures | |
| Trapping, amputations by mixing mechanism. | Safety locks should be used on mixer operation | |
| Warning signs for not to work on mixers in motion should be used | ||
| On access hatches automatic mixer stop catches should be used | ||
| Security grids on observation windows to prevent access | ||
| All moving parts should be covered by protection covers | ||
It was observed that fall from elevated heights is an immediate hazard that needs to be dealt with in both production and casting process. Environmental hazards such as dust and noise is present in both processes with varying degrees of exposure. It was also determined that ergonomic risks during material handling, transportation and casting threaten workers’ health.
JSA tables revealed that mitigation methods exist for nearly all of the hazards, as long as the resources are allocated. Statistical analysis revealed that cleaning of truck mixers is a hazardous activity and source of many injuries. Therefore, installing guardrails against falls, using wet methods, ventilation and personal protective equipment where needed could prevent illnesses and injuries.
Discussions and Conclusion
Ready mix concrete, as shown in table 1, is rapidly developing in many countries while it is hard to find scientific accident database and academic studies related with potential hazards of industry in Turkey or in other countries. This study aimed to fulfill this gap and raise awareness.
Following findings were detected based on statistical analyses of 71 cases:
Generally, construction sites are known as one of the most dangerous working areas because of its dynamic, changeable nature and complex tasks. On the other hand RMC production areas are more systematic, repetitive and ordinate. However, surprisingly statistical analysis showed that 7 out of 10 RMC related accidents occurred at production area, while only 3 out of 10 occurred at casting sites.
However, the group with a considerable risk level is truck mixer operators. According to analysis it is determined that 45.1% of the victims were truck mixer operators. Truck mixer operators mostly got injured when they clean mixer/pump (37.5%) followed by transportation for concrete casting (18.8%) and maintenance/repair (18.8%). This result shows that operators are mostly under risk when they come back from casting to clean their truck mixers at production sites.
The evaluation of type of injuries in ready-mix concrete industry has revealed that in 22 cases (31.0%) falls, in 19 cases (26.8%) struck by falling object, and in 12 cases (16.9%) caught in or between objects were the cause of accident. Fall has been reported as the leading cause of accidents in construction industry (range from 22 to 33%) by many researchers19, 27, 28, 29). RMC industry shows similarity with construction sector when findings related with falls compared. However, struck by falling object category is frequently monitored at RMC industry. According to statistics reported by Indiana Department of Labor the three major types of injuries at ready-mixed concrete industry are falls, road accidents and struck by falling objects30). This result also complies with the findings of Arndt et al., who also found that one of the common causes of fatal injuries in the construction industry is struck by falling objects31).
Most encountered nature of injury has been found to be superficial injury and open wound (28.2%). Upper extremity damage has caused 28 workers (39.4%) injury. According to statistical findings reported by The Nova Scotia Construction Safety Association (NSCSA), the most frequently injured body part is back part of body (30.8%). Following part is legs with 19.5% and arms with 7.5%14). Within the scope of another report it is pointed that the most frequently injured body part is upper extremities30).
It was found that compared to the rest of the weekdays there were more accidents occurring on Monday and Thursday. Kazan17) and Akboğa&Baradan26) found the same results on their studies.
Various studies showed that workers with less work experience, particularly within the first month of employment, are more prone to injuries26, 32, 33). However, most surprisingly, findings of statistical analysis showed just the opposite. Working for many years at same company could be the reason of getting used to risks. Repeating safety training regularly could solve this problem.
Job Safety Analysis should not be performed based solely on site observations. Case histories (statistics of accidents records) should also be taken into consideration. JSA would be more realistic with the support of statistical analysis findings. JSA forms shall be ordered chronologically, the hazards for each step shall be defined, the methods for preventing/eliminating the hazard shall be defined, and required PPE shall be provided whenever there is a need. Hazard Identification and Control is the largest element in a company’s safety program. When completed thoroughly, it will be used as the foundation for all other areas of the program.
It is expected from the RMC producers to create an occupational safety and health department with a focus on training. It is best to determine training topics and contents based on JSA results and company based statistical database. JSA forms presented in this study could also be helpful for companies who want to establish a safety and health program.
The essential deficiency in the RMC industry is that the occupational injuries and illnesses are not recorded systematically, thus the potential of occupational accidents are neglected. Collecting statistics on safety activities will allow a company to identify common injuries and areas that may be lacking in their safety program.
References
- 1.Occupational Safety and Health Administration. Commonly used statistics. https://www.osha.gov/oshstats/commonstats.html. Accessed October 16, 2015.
- 2.Bomel Ltd (2001) Improving health and safety in construction phase 1: data collection, review and structuring. Contract Research Report 386/2001. Sudbury: HSE Books.
- 3.Baldacconi A, Santis PD (2000) Risk assessment in construction field in Italy. Rome, Italy: National Institute for Insurance against injuries at Work.
- 4.Fang DP, Huang XY, Hinze J (2004) Benchmarking studies on construction safety management in Chine. Journal of Cons. Eng. Man. 130, 424–32. [Google Scholar]
- 5.National Ready Mixed Concrete Association (2014) occupational exposure to respirable crystalline silica. OSHA Docket Office, Docket No. OSHA-2010-0034, February 11.
- 6.Ready Mix Concrete. http://www.civileblog.com/ready-mix-concrete/#Advantages. Accessed March 01, 2016.
- 7.European Ready Mixed Concrete Organization. (2014) Ready-Mixed Concrete Industry Statistics Year 2013.
- 8.Occupational Safety and Health Administration 3211. (2004) Workers Safety Series Concrete Manufacturing. Nov 12.
- 9.European Ready Mixed Concrete Organization (2006) Guidance on health and safety management in the european ready mixed concrete industry. October.
- 10.National Ready Mixed Concrete Association (2014) 2014 National Ready Mixed Concrete Association Excellence in Safety Awards. Office of Safety. [Google Scholar]
- 11.Turkish Ready Mixed Concrete Association. Statistics. http://www.thbb.org/en/industry/statistics/. Accessed January 26, 2015.
- 12.Turkish Ready Mixed Concrete Association. 2nd Blue Helmet Job Security Contest. http://www.thbb.org/en/activities/blue-helmet/2nd-blue-helmet/. Accessed March 28, 2016.
- 13.American Concrete Pumping Association. (2005) Safety manual for ready mixed concrete truck drivers: delivering to concrete pumps and crane lift buckets.
- 14.Nova Scotia Construction Safety Association. (2013) The concrete facts, a safety newsletter for the ready-mix concrete industry, March 12.
- 15.Turkish Statistical Institute Population Statistics. http://www.turkstat.gov.tr/UstMenu.do?metod=temelist. Accessed March 22, 2016.
- 16.Babbi ER. (2011) The basics of social research. 5tf Ed., Wadsworth Publishing, California. [Google Scholar]
- 17.Kazan E. (2013) Analysis of fatal and nonfatal accidents involving earthmoving equipment operators and on-foot workers. PhD Thesis, Submitted to the Graduate School of Wayne State University Detroit, Michigan, 173 p. [Google Scholar]
- 18.Hatipkarasulu Y. (2010) Project level analysis of special trade contractor fatalities using accident investigation reports. J Safety Res 41, 451–7. [DOI] [PubMed] [Google Scholar]
- 19.Hinze J, Pedersen C, Fredley J (1998) Identifying root causes of construction injuries. J Constr Eng Manage 124, 67–71. [Google Scholar]
- 20.Hinze J, Huang X, Terry L (2005) the nature of struck-by accidents. J Constr Eng Manage 131, 262–8. [Google Scholar]
- 21.Healey JF. (2011) Statistics: A tool for social research. 9th Ed., Wadsworth Publishing, California. [Google Scholar]
- 22.Canada’s National Occupational Health&Safety Resource. (1998) job hazard analysis. http://www.ccohs.ca/oshanswers/hsprograms/job-haz.html. Ontario, Accessed May 02, 2010.
- 23.Chao E, Henshaw J (2002) Job hazard analysis. Occupational Safety and Health Administration (OSHA), USA, 50 p. [Google Scholar]
- 24.Rausand M. (2005) Job safety analysis. System Reliability Theory (2nd edition), Wiley, 1/25 October 7.
- 25.Akboğa Ö. (2011) Safety Analysis of ready-mix concrete industry. Master Thesis, Submitted to the Graduate School of Ege University Izmir, Turkey, 113 p. [Google Scholar]
- 26.Akboğa Ö, Baradan S (2015) Investigating the characteristics of fatal construction injuries in İzmir, Turkey using descriptive statistics, Journal of Multidisciplinary Engineering Science and Technology (JMEST), ISSN: 3159-0040, Vol. 2 Issue 9, September.
- 27.Ore T, Stout NA (1996) Traumatic occupational fatalities in the U.S. and Australian construction industries. Am J Ind Med 30, 202–6. [DOI] [PubMed] [Google Scholar]
- 28.Jackson SA, Loomis D (2002) Fatal occupational injuries in the North Carolina construction industry, 1978–1994. Appl Occup Environ Hyg 17, 27–33. [DOI] [PubMed] [Google Scholar]
- 29.Fabrega V, Stakey S (2001) Fatal occupational injuries among Hispanic construction workers of Texas, 1997 to 1999. Hum Ecol Risk Assess 7, 1869–83. [Google Scholar]
- 30.Indiana Department of Labor. (2008) Select characteristics of U.S. ready-mix concrete manufacturing.
- 31.Arndt V, Rothenbacher D, Daniel U, Zschenderlein B, Schuberth S, Brenner H (2004) All-cause and cause specific mortality in a cohort of 20 000 construction workers; results from a 10 year follow up. Occup Environ Med 61, 419–25. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Colak B, Etiler N, Bicer U (2004) Fatal occupational injuries in the construction sector in Kocaeli, Turkey, 1990--2001. Ind Health 42, 424–30. [DOI] [PubMed] [Google Scholar]
- 33.Castejón E, Crespán X (2009) Accidents de treball: el per què de tot plegat [Occupational Injuries: Their Overall Reasons]. Engineers Industrials de Catalunya, Barcelona. [Google Scholar]
- 34.Ready Mic Concrete Plant in India, 2012, https://conmatindia.wordpress.com/. (Accessed: 02/05/2016)
- 35.Eliott AC, Woodward WA (2006). Statistical Analysis Quick Reference Guidebook with SPSS Examples, 1st Ed., SAGE Publications, Inc; California. [Google Scholar]