Comparative Analysis of the National Fatality Rate in Construction Industry Using Time-Series Approach and Equivalent Evaluation Conditions
Abstract
:1. Introduction
2. Investigation of the Fatality Rate of Various Countries
2.1. South Korea
2.2. Japan
2.3. China
2.4. Singapore
2.5. Mexico
2.6. The United Kingdom
2.7. Comparison of the National Fatality Rate Data for Various Countries
3. Materials and Methods
3.1. Collection of Data
3.2. Analysis of the Fatality Rate Based on the Full-Time Equivalent Workers
3.2.1. Calculation of the Full-Time Equivalent Workers
3.2.2. Comparison of the Fatality Rate by Countries Using Time-Series Analysis
3.3. Normalization of the Fatality Rate under National Data and Equivalent Conditions
3.4. Comparison of the Fatality Rate of Various Countries
4. Results and Discussion
4.1. Comparison of the Fatality Rate in Terms of the National Data of Various Countries
- (I)
- The annual number of fatal accidents in South Korea was between a minimum of 434 and a maximum of 516, with an average of 477. When compared with other countries, it was at the highest level, except for China, which had the highest number of fatal accidents.
- (II)
- The annual number of fatal accidents in Japan was between a minimum of 294 and a maximum of 377, with an average of 334. Japan ranked third in the number of fatal accidents.
- (III)
- The annual number of fatal accidents in China was between a minimum of 1891 and a maximum of 3843, with an average of 2880. China had the highest number of fatal accidents among the compared countries. When compared with the figure for Singapore, which had the lowest number of fatal accidents, it was approximately 125 times higher.
- (IV)
- The annual number of fatal accidents in Singapore was between a minimum of 12 and a maximum of 34, with an average of 23. Singapore had the lowest number of fatal accidents among the compared countries.
- (V)
- The annual number of fatal accidents in Mexico was between a minimum of 150 and a maximum of 220, with an average of 187, which ranked fourth among the compared countries.
- (VI)
- The annual number of fatal accidents in the United Kingdom was between a minimum of 31 and a maximum of 47, with an average of 38. When compared with the figure for Singapore, it was approximately 1.5 times higher, ranking fifth among the compared countries.
- (I)
- The FRFEW of South Korea was between 1.30‱ and 2.01‱, and the FRFEW based on the time-series data was 1.54‱. South Korea ranked second in the number of fatal accidents but had the highest risk level from the perspective of the FRFEW.
- (II)
- The FRFEW of Japan was between 0.88‱ and 1.10‱, and the FRFEW based on the time-series data was 0.87‱. Japan ranked second after South Korea.
- (III)
- The FRFEW of China was between 0.37‱ and 0.74‱, and the FRFEW based on the time-series data was 0.71‱. Compared with other countries, China had the highest number of fatal accidents. However, when the number of workers provided in Table S1 was considered, the number was up to 100 times higher than that of other countries. Therefore, although the number of fatal accidents was large, the risk level was lower than that of other countries if the number of workers was considered in the comparison.
- (IV)
- The FRFEW of Singapore was between 0.26‱ and 0.72‱, and the FRFEW based on the time-series data was 0.13‱. Singapore had the lowest number of fatal accidents and FRFEW compared with other countries.
- (V)
- The FRFEW of Mexico was between 0.91‱ and 1.59‱, and the FRFEW based on the time-series data was 0.82‱. When compared with the number of fatal accidents, Mexico’s FRFEW indicated a higher risk level because the number of fatal accidents was high relative to the number of workers.
- (VI)
- The FRFEW of the United Kingdom was between 0.14‱ and 0.21‱, and the FRFEW based on the time-series data was 0.15‱, indicating a higher risk level than Singapore.
4.2. Comparison of the Fatality Rate of Various Countries in Terms of Equivalent Conditions
- (I)
- In South Korea, the FRFEW was between 1.71‱ and 2.12‱, and the FRFEW based on the time-series data was 2.05‱. The number of workers in South Korea decreased compared with that in the national data, thereby increasing the FRFEW. However, unlike the result above, in which the risk level was the highest, the risk level of South Korea was the second highest.
- (II)
- In Japan, the FRFEW was between 0.88‱ and 1.22‱, and the FRFEW based on the time-series data was 0.80‱. It was lower than the FRFEW of the national data of Japan. However, the risk level decreased.
- (III)
- In China, the FRFEW was between 1.07‱ and 2.14‱, and the FRFEW based on the time-series data was 2.29‱. The comparison of Table S1 and Table S5 shows that the annual number of workers based on the equivalent condition decreased more than twice compared with the annual number of workers based on the national data. Thus, China had the highest FRFEW compared with other countries.
- (IV)
- In Singapore, the FRFEW was between 0.90‱ and 1.75‱, and the FRFEW based on the time-series data was 0.98‱, indicating a large increase in the risk level compared with the national-data-based FRFEW. Thus, the risk level was higher than that of Japan and the United Kingdom.
- (V)
- In Mexico, the FRFEW was between 1.25‱ and 1.89‱, and the FRFEW based on the time-series data was 1.23‱. Mexico’s risk level increased slightly compared with the national-data-based FRFEW above, but the risk level by country was at an equivalent level.
- (VI)
- In the United Kingdom, the FRFEW was between 0.44‱ and 0.67‱, and the FRFEW based on the time-series data was 0.47‱. The risk level of the United Kingdom increased slightly compared with the national-data-based FRFEW, but the national risk level decreased to the lowest level.
4.3. Comparison of the Fatality Rate between the National Data and Equivalent Evaluation Conditions
4.4. Comparison of the Normalized Fatality Rate between the National Data and Equivalent Conditions
4.5. Discussion
5. Conclusions
- (i)
- Collection of data: Data were collected to calculate the number of fatal accidents, number of workers, and the number of full-time equivalent workers in the construction industry of South Korea, Japan, China, Singapore, Mexico, and the United Kingdom.
- (ii)
- The calculation of the full-time equivalent workers: The fatality per 10,000 full-time equivalent workers (FRFEW) was calculated based on the number of full-time equivalent workers to calculate the FR of each country under the equivalent condition. Furthermore, a time-series approach was used to resolve the uncertainty problem of the FR.
- (iii)
- The comparison of the FR of various countries: The FRFEW was compared based on the national data and equivalent conditions. Subsequently, the requirement for the calculation of the risk level of each country under the equivalent evaluation condition was presented.
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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South Korea | Japan | China | Singapore | Mexico | United Kingdom | |
---|---|---|---|---|---|---|
Fatal accident | Total inspection (information on industrial accident compensation insurance) | Total inspection (report to the administration) | Total inspection (report to the administration) | Total inspection (report to the administration) | Total inspection (report to the administration) | Total inspection (report to the administration) |
Full-time equivalent workers | Calculation of the full-time equivalent workers | Sampling inspection | Sampling inspection | Sampling inspection | Sampling inspection | Sampling inspection |
Classification | South Korea | Japan | China | Singapore | Mexico | United Kingdom |
---|---|---|---|---|---|---|
Fatal accident | MOEL | MHLW | MEM | MOM | IMSS | HSE |
Full-time equivalent workers | MOEL | SBJ | NBSC | MOM | IMSS | ONS |
Construction revenue | KOSIS | SBJ | NBSC | DOS | INEGI | ONS |
Labor ratio | MOEL | - | - | - | - | - |
Monthly wage of construction workers | MOEL | MHLW | NBSC | DOS | INEGI | ONS |
Year | South Korea | Japan | China | Singapore | Mexico | United Kingdom |
---|---|---|---|---|---|---|
Fatal Accidents | Fatal Accidents | Fatal Accidents | Fatal Accidents | Fatal Accidents | Fatal Accidents | |
2012 | 461 | 367 | 2431 | 26 | 196 | 40 |
2013 | 516 | 342 | 2489 | 34 | 193 | 44 |
2014 | 434 | 377 | 2197 | 27 | 193 | 35 |
2015 | 437 | 327 | 1891 | 27 | 220 | 47 |
2016 | 499 | 294 | 3806 | 24 | 192 | 31 |
2017 | 506 | 323 | 3843 | 12 | 162 | 37 |
2018 | 485 | 309 | 3504 | 14 | 150 | 31 |
Average | 477 | 334 | 2880 | 23 | 187 | 38 |
Min | 434 | 294 | 1891 | 12 | 150 | 31 |
Max | 516 | 377 | 3843 | 34 | 220 | 47 |
Rank | 2 | 3 | 1 | 6 | 4 | 5 |
Year | South Korea | Japan | China | Singapore | Mexico | United Kingdom |
---|---|---|---|---|---|---|
FRFEW (‱) | FRFEW (‱) | FRFEW (‱) | FRFEW (‱) | FRFEW (‱) | FRFEW (‱) | |
2012 | 1.65 | 1.08 | 0.57 | 0.59 | 1.58 | 0.19 |
2013 | 2.01 | 1.00 | 0.56 | 0.72 | 1.59 | 0.21 |
2014 | 1.34 | 1.10 | 0.49 | 0.55 | 1.41 | 0.16 |
2015 | 1.30 | 0.96 | 0.37 | 0.54 | 1.55 | 0.21 |
2016 | 1.58 | 0.88 | 0.74 | 0.49 | 1.26 | 0.14 |
2017 | 1.66 | 0.96 | 0.70 | 0.26 | 1.04 | 0.16 |
2018 | 1.65 | 0.90 | 0.62 | 0.31 | 0.91 | 0.14 |
Evaluation | 1.54 | 0.87 | 0.71 | 0.13 | 0.82 | 0.15 |
Min | 1.30 | 0.88 | 0.37 | 0.26 | 0.91 | 0.14 |
Max | 2.01 | 1.10 | 0.74 | 0.72 | 1.59 | 0.21 |
Rank | 1 | 2 | 4 | 6 | 3 | 5 |
Year | South Korea | Japan | China | Singapore | Mexico | United Kingdom |
---|---|---|---|---|---|---|
FRFEW (‱) | FRFEW (‱) | FRFEW (‱) | FRFEW (‱) | FRFEW (‱) | FRFEW (‱) | |
2012 | 1.78 | 1.22 | 1.23 | 1.31 | 1.49 | 0.65 |
2013 | 2.02 | 1.03 | 1.32 | 1.56 | 1.53 | 0.67 |
2014 | 1.71 | 1.1 | 1.26 | 1.17 | 1.63 | 0.5 |
2015 | 1.87 | 0.97 | 1.07 | 1.75 | 1.89 | 0.65 |
2016 | 2.12 | 0.89 | 2.14 | 1.64 | 1.64 | 0.44 |
2017 | 2.06 | 0.91 | 2.12 | 0.91 | 1.36 | 0.51 |
2018 | 1.98 | 0.88 | 1.82 | 0.9 | 1.25 | 0.44 |
Evaluation | 2.05 | 0.80 | 2.29 | 0.98 | 1.23 | 0.47 |
Min | 1.71 | 0.88 | 1.07 | 0.90 | 1.25 | 0.44 |
Max | 2.12 | 1.22 | 2.14 | 1.75 | 1.89 | 0.67 |
Rank | 2 | 5 | 1 | 4 | 3 | 6 |
National Data | Fatal Accident | Full-Time Equivalent Workers | Fatality Rate | Normalized Fatality Rate | ||||
---|---|---|---|---|---|---|---|---|
Nation | Estimation | Max | Min | Estimation | Max | Min | Estimation (‱) | |
South Korea | 490 | 516 | 434 | 3,123,661 | 3,358,813 | 2,566,832 | 1.54 | 0.98 |
Japan | 293 | 377 | 293 | 3,377,841 | 3,430,000 | 3,350,000 | 0.87 | 0.00 |
China | 4093 | 4093 | 1891 | 59,404,154 | 55,399,100 | 42,439,900 | 0.70 | 0.76 |
Singapore | 11 | 34 | 11 | 442,464 | 501,200 | 440,700 | 0.13 | 0.00 |
Mexico | 145 | 220 | 145 | 1,707,758 | 1,643,363 | 1,211,501 | 0.82 | 0.00 |
United Kingdom | 36 | 47 | 31 | 2,366,658 | 2,313,000 | 2,062,000 | 0.15 | 0.24 |
Equivalent Condition | Fatal Accident | Full-Time Equivalent Workers | Fatality Rate | Normalized Fatality Rate | ||||
Nation | Estimation | Max | Min | Estimation | Max | Min | Estimation (‱) | |
South Korea | 490 | 516 | 434 | 2,387,242 | 2,584,749 | 2,308,052 | 2.15 | 3.60 |
Japan | 293 | 377 | 293 | 3,607,727 | 3,607,727 | 3,008,072 | 1.22 | 0.00 |
China | 4093 | 4093 | 1891 | 19,175,850 | 19,767,905 | 17,462,867 | 2.29 | 1.35 |
Singapore | 11 | 34 | 11 | 113,867 | 231,309 | 113,867 | 0.98 | 0.00 |
Mexico | 145 | 220 | 145 | 1,186,246 | 1,313,237 | 1,165,728 | 1.23 | 0.00 |
United Kingdom | 36 | 47 | 31 | 722,636 | 722,636 | 612,849 | 0.47 | 0.30 |
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Shim, Y.; Jeong, J.; Jeong, J.; Lee, J.; Kim, Y. Comparative Analysis of the National Fatality Rate in Construction Industry Using Time-Series Approach and Equivalent Evaluation Conditions. Int. J. Environ. Res. Public Health 2022, 19, 2312. https://doi.org/10.3390/ijerph19042312
Shim Y, Jeong J, Jeong J, Lee J, Kim Y. Comparative Analysis of the National Fatality Rate in Construction Industry Using Time-Series Approach and Equivalent Evaluation Conditions. International Journal of Environmental Research and Public Health. 2022; 19(4):2312. https://doi.org/10.3390/ijerph19042312
Chicago/Turabian StyleShim, Yukyung, Jaemin Jeong, Jaewook Jeong, Jaehyun Lee, and Yongwoo Kim. 2022. "Comparative Analysis of the National Fatality Rate in Construction Industry Using Time-Series Approach and Equivalent Evaluation Conditions" International Journal of Environmental Research and Public Health 19, no. 4: 2312. https://doi.org/10.3390/ijerph19042312
APA StyleShim, Y., Jeong, J., Jeong, J., Lee, J., & Kim, Y. (2022). Comparative Analysis of the National Fatality Rate in Construction Industry Using Time-Series Approach and Equivalent Evaluation Conditions. International Journal of Environmental Research and Public Health, 19(4), 2312. https://doi.org/10.3390/ijerph19042312