A Dynamic Risk Analysis Model Based on Workplace Ergonomics and Demographic-Cognitive Characteristics of Workers
Abstract
:1. Introduction
2. Method
2.1. Population Sample
2.2. Data Collection Tools
2.3. Research Hypothesis
2.4. Statistical Method
3. Results
4. Discussion
Limitations, Benefits and Future Directions
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Rikhotso, O.; Morodi, T.J.; Masekameni, D.M. The Extent of Occupational Health Hazard Impact on Workers: Documentary Evidence from National Occupational Disease Statistics and Selected South African Companies’ Voluntary Corporate Social Responsibility Disclosures. Sustainability 2022, 14, 10464. [Google Scholar] [CrossRef]
- Ji, Z.; Pons, D.; Su, Z.; Lyu, Z.; Pearse, J. Integrating Occupational Health and Safety Risk and Production Economics for Sustainable SME Growth. Sustainability 2022, 14, 14565. [Google Scholar] [CrossRef]
- Ergör, O.A.; Demiral, Y.; Piyal, Y.B. A Significant Outcome of Work Life: Occupational Accidents in a Developing Country, Turkey. J. Occup. Health 2003, 45, 74–80. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Oldenburg, M.; Baur, X.; Schlaich, C. Occupational Risks and Challenges of Seafaring. J. Occup. Health 2010, 52, 249–256. [Google Scholar] [CrossRef] [Green Version]
- Swat, K. Monitoring of Accidents and Risk Events in Industrial Plants. J. Occup. Health 2006, 39, 100–104. [Google Scholar] [CrossRef]
- Kortum, E. Perceptions of Psychosocial Hazards, Work-related Stress and Workplace Priority Risks in Developing Countries. J. Occup. Health 2011, 53, 144–155. [Google Scholar] [CrossRef] [Green Version]
- Arık, B.; Akçın, N.A. Iş Kazalarının Önlenmesi Ve Iş Güvenligi Analiz Tekniginin Uygulanması. In Proceedings of the Türkiye 13 Kömür Kongresi Bildiriler Kitabı, Zonguldak, Türkiye, 29–31 May 2002. [Google Scholar]
- Erginel, N.; Toptancı, Ş. Iş Kazası Verilerinin Olasılık Dagılımları ile Modelenmesi. Mühendislik Bilim. Tasarım Derg. 2016, 5, 201–212. [Google Scholar] [CrossRef]
- Kahraman, E.; Akay, Ö.; Kılıç, A.M. Investigation into the relationship between fatal work accidents, national income, and employment rate in developed and developing countries. J. Occup. Health 2019, 61, 213–218. [Google Scholar] [CrossRef]
- Thepaksorn, P.; Thongjerm, S.; Incaroen, S.; Siriwong, W.; Harada, K.; Koizumi, A. Job safety analysis and hazard identification for work accident prevention in para rubber wood sawmills in southern Thailand. J. Occup. Health 2017, 59, 542–551. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Camkurt, M.Z. Çalışanların Kişisel Özelliklerinin Iş Kazalarının Meydana Gelmesi Üzerindeki Etkisi. TÜHIS Hukuku Iktisat Derg. 2013, 24, 70–101. [Google Scholar]
- Kajiki, S.; Mori, K.; Kobayashi, Y.; Hiraoka, K.; Fukai, N.; Uehara, M.; Adi, N.P.; Nakanishi, S. Developing a global occupational health and safety management system model for Japanese companies. J. Occup. Health 2019, 62, e12081. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Nakata, A.; Ikeda, T.; Takahashi, M.; Haratani, T.; Hojou, M.; Swanson, N.G.; Fujioka, Y.; Araki, S. The Prevalence and Correlates of Occupational Injuries in Small-Scale Manufacturing Enterprises. J. Occup. Health 2006, 48, 366–376. [Google Scholar] [CrossRef] [Green Version]
- Okubo, T. Recent State and Future Scope of Occupational Health in Japan. J. Occup. Health 2006, 40, 161–167. [Google Scholar] [CrossRef]
- Sanmiquel, L.; Bascompta, M.; Rossell, J.; Anticoi, H.; Guash, E. Analysis of Occupational Accidents in Underground and Surface Mining in Spain Using Data-Mining Techniques. Int. J. Environ. Res. Public Health 2018, 15, 462. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zhou, L.; Cao, Q.; Yu, K.; Wang, L.; Wang, H. Research on Occupational Safety, Health Management and Risk Control Technology in Coal Mines. Int. J. Environ. Res. Public Health 2018, 15, 868. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Muthelo, L.; Mothiba, T.M.; Malema, N.R.; Mbombi, M.O.; Mphekgwana, P.M. Exploring Occupational Health and Safety Standards Compliance in the South African Mining Industry, Limpopo Province, Using Principal Component Analysis. Int. J. Environ. Res. Public Health 2022, 19, 10241. [Google Scholar] [CrossRef]
- Niu, L.; Zhao, R. The Effect of Safety Attitudes on Coal Miners’ Human Errors: A Moderated Mediation Model. Sustainability 2022, 14, 9917. [Google Scholar] [CrossRef]
- Małysa, T.; Gajdzik, B. Predictive Models of Accidents at Work in the Steel Sector as a Framework for Sustainable Safety. Energies 2020, 14, 129. [Google Scholar] [CrossRef]
- Zhang, S.; Hua, X.; Huang, G.; Shi, X.; Li, D. What Influences Miners’ Safety Risk Perception? Int. J. Environ. Res. Public Health 2022, 19, 3817. [Google Scholar] [CrossRef]
- Silva, A.F.; Dalri, R.C.M.B.; Eckeli, A.L.; Sousa-Uva, A.; Mendes, A.C.; Robazzi, M.L.C.C. Sleep quality, personal and work variables and life habits of hospital nurses. Rev. Latino-Am. Enferm. 2022, 30, e3538. [Google Scholar] [CrossRef]
- Buysse, D.J.; Reynolds, C.F.; Monk, T.H. The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. Psychiatry Res. 1989, 28, 193–213. [Google Scholar] [CrossRef]
- Agargun, M.Y.; Kara, H.; Anlar, O. Pittsburgh Uyku Kalitesi İndeksi’nin Geçerligi ve Güvenirligi. Turk. Psikiyatr. Derg. 1996, 7, 107–111. [Google Scholar]
- Arias-Castro, E. Principles of Statistical Analysis: Learning from Randomized Experiments (Institute of Mathematical Statistics Textbooks) Kindle Edition; Cambridge Press: Cambridge, UK, 2022. [Google Scholar]
- Alves, A.M.S.; Gonçalves Filho, C.; Santos, N.M.; Souki, G.Q. Factors influencing occupational accidents: A multidimensional analysis in the electricity sector. Gestão Produção 2020, 27, e4609. [Google Scholar] [CrossRef]
- Baradan, S.; Akboga, Ö.; Çetinkaya, U.; Usmen, M.A. Ege Bölgesindeki Inşaat Iş Kazalarının Sıklık ve Çapraz Tablolama Analizleri. Tek. Dergi 2016, 27, 7345–7370. [Google Scholar]
- Ilsoon, S.; Jun-Byoung, O.H.; Kwan Hyung, Y.I. Workers’ Compensation Insurance and Occupational Injuries. Saf. Health Work. 2011, 2, 148–157. [Google Scholar]
- Hoła, B.; Nowobilski, T. Analysis of the influence of socioeconomic factors on occupational safety in the construction industry. Sustainability 2019, 111, 4469. [Google Scholar] [CrossRef] [Green Version]
- Amponsah-Tawiah, K.; Mensah, J. Occupational health and safety and organizational commitment: Evidence from the Ghanaian mining industry. Saf. Health Work. 2016, 7, 225–230. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sadullah, Ö. İş kazası istatistikleri ve olay oranı. I.Ü. Işletme Fakültesi Derg. 1997, 26, 109–113. [Google Scholar]
- Eskandari, D.; Jafari, M.J.; Mehrabi, Y.; Kian, M.P.; Charkhand, H.; Mirghotbi, M. A qualitative study on organizational factors affecting occupational accidents. Iran. J. Public Health 2017, 46, 380–388. [Google Scholar]
- Yi, K.H.; Lee, S.S. A policy intervention study to identify high-risk groups to prevent industrial accidents in Republic of Korea. Saf. Health Work. 2016, 7, 213–217. [Google Scholar] [CrossRef] [Green Version]
- Khanzode, V.V.; Maiti, J.; Ray, P.K. A methodology for evaluation and monitoring of recurring hazards in underground coal mining. Saf. Sci. 2011, 49, 1172–1179. [Google Scholar] [CrossRef]
- Bernackie, E.J. Factors influencing the costs of workers’ compensation. Clin. Occup. Environ. Med. 2004, 4, 249–257. [Google Scholar] [CrossRef] [PubMed]
- Liu, H.-T.; Tsai, Y.-L. A fuzzy risk assessment approach for occupational hazards in the construction industry. Saf. Sci. 2012, 50, 1067–1078. [Google Scholar] [CrossRef]
Company | Mine (N = 30) | Metal (N = 23) | Total (N = 53) | Test Value | p-Value |
---|---|---|---|---|---|
Age (Mean ± SD) | 31.37 ± 4.85 | 38.61 ± 7.48 | 34.51 ± 7.11 | 69,457.500 | 0.000 *a |
Education, n (%) | |||||
Primary school or below | 1 (3.3) | 9 (39.1) | 10 (18.9) | ||
High school | 6 (20.0) | 4 (17.4) | 10 (18.9) | 12.099 | 0.002 c |
University and above | 23 (76.7) | 10 (43.5) | 33 (62.3) | ||
Sector year, mean ± SD | 6.02 ± 4.57 | 14.61 ± 7.39 | 9.75 ± 7.32 | 47,407.500 | 0.000 *a |
Department year, mean ± SD | 5.18 ± 4.01 | 5.17 ± 4.40 | 5.18 ± 4.18 | 132,961.500 | 0.000 *a |
Company year, mean ± SD | 3.48 ± 2.18 | 5.17 ± 4.40 | 4.22 ± 0.3 | 141,120.000 | 0.035 a |
Marital status, n (%) | |||||
Single | 21 (70.0) | 9 (39.1) | 30 (56.6) | (50.51) | 0.024 b |
Married | 9 (30.0) | 14 (60.9) | 23 (43.4) | ||
Previous accident, n (%) | |||||
No | 25 (83.3) | 20 (87.0) | 45 (84.9) | 0.133 | 0.514 b |
Yes | 5 (16.7) | 3 (13.0) | 8 (15.1) | ||
Number of previous accident experiences | 0.27 ± 0.77 | 0.57 ± 2.06 | 0.40 ± 1.48 | 148,176.000 | 0.230 a |
Previous near-miss, n (%) | |||||
No | 23 (76.7) | 16 (69.6) | 39 (73.6) | 0.338 | 0.393 b |
Yes | 7 (23.3) | 7 (30.4) | 14 (26.4) | ||
Previous near-misses, mean ± SD | 0.77 ± 1.57 | 1.83 ± 3.32 | 1.23 ± 2.54 | 145,089.000 | 0.087 a |
Instantaneous pulse, mean ± SD | 89.90 ± 17.90 | 91.19 ± 18.27 | 90.46 ± 18.07 | 145,821.000 | 0.234 a |
Daily pulse, mean ± SD | 89.34 ± 17.08 | 91.07 ± 17.75 | 90.09 ± 17.39 | 143,452.000 | 0.102 a |
Deep sleep, mean ± SD | 1.54 ± 0.87 | 1.47 ± 0.86 | 1.51 ± 0.87 | 145,277.500 | 0.196 a |
REM, mean ± SD | 0.92 ± 0.54 | 0.92 ± 0.51 | 0.92 ± 0.53 | 151,962.500 | 0.973 a |
Mild sleep, mean ± SD | 2.74 ± 1.48 | 3.01 ± 1.61 | 2.86 ± 1.54 | 138,274.500 | 0.009 a |
Active time, mean ± SD | 0.75 ± 0.44 | 0.74 ± 0.43 | 0.74 ± 0.44 | 151,206.000 | 0.860 a |
Mean ± SD | Mining (N = 30) | Metal (N= 23) | Total (N = 53) | Value of the Test | p-Value a |
---|---|---|---|---|---|
Correct answer | 10.75 ± 2.92 | 12.52 ± 3.04 | 11.52 ± 3.10 | 104,253.000 | 0.000 |
Correct time | 2.88 ± 0.66 | 2.99 ± 0.42 | 2.93 ± 0.57 | 127,825.000 | 0.000 |
Correct score | 51.21 ± 13.63 | 59.63 ± 14.47 | 54.86 ± 14.60 | 103,747.000 | 0.000 |
Incorrect answer | 5.79 ± 3.33 | 5.78 ± 2.48 | 5.79 ± 2.99 | 149,581.500 | 0.628 |
Incorrect time | 2.93 ± 1.21 | 3.41 ± 0.68 | 3.14 ± 1.04 | 108,080.500 | 0.000 |
Incorrect score | 27.59 ± 15.87 | 27.52 ± 11.83 | 27.56 ± 14.25 | 149,581.500 | 0.628 |
Unanswered question | 4.46 ± 3.32 | 2.69 ± 2.07 | 3.69 ± 2.98 | 105,635.000 | 0.000 |
Unanswered time | 4.54 ± 1.45 | 4.91 ± 0.68 | 4.70 ± 1.19 | 140,973.000 | 0.000 |
Unanswered score | 21.22 ± 15.82 | 12.80 ± 9.88 | 17.56 ± 14.19 | 105,957.500 | 0.000 |
Total score | 0.49 ± 0.10 | 0.54 ± 0.05 | 0.51 ± 0.08 | 103,534.500 | 0.000 |
ST | 9.13 ± 2.95 | 9.18 ± 1.87 | 9.16 ± 2.54 | 150,892.000 | 0.812 |
PSQI | 13.78 ± 2.18 | 13.18 ± 2.86 | 13.52 ± 2.51 | 130,301.500 | 0.000 |
Number of Previous Accidents | r | p |
---|---|---|
Education level | 0.060 * | 0.045 |
Age | −0.017 | 0.572 |
Sector years | −0.052 | 0.084 |
Department years | 0.139 ** | 0.000 |
Company years | 0.109 ** | 0.000 |
Marital status | 0.280 ** | 0.000 |
Previous near-miss | 0.477 ** | 0.000 |
Number of previous near-miss incidents | 0.600 ** | 0.000 |
Instantaneous pulse | −0.018 | 0.540 |
Daily pulse | 0.036 | 0.233 |
Deep sleep | −0.020 | 0.507 |
REM | −0.019 | 0.527 |
Mild sleep | −0.009 | 0.773 |
Active time | −0.046 | 0.122 |
Company | −0.036 | 0.230 |
Measurement | 0.000 | 10.000 |
Correct answers | 0.001 | 0.963 |
Correct time | −0.054 | 0.071 |
Correct score | 0.002 | 0.940 |
Incorrect answers | −0.078 ** | 0.009 |
Incorrect time | −0.009 | 0.766 |
Incorrect score | −0.078 ** | 0.009 |
Unanswered question | 0.037 | 0.220 |
Unanswered time | 0.077 | 0.011 |
Unanswered score | 0.037 | 0.212 |
Total score | 0.004 | 0.896 |
ST | 0.038 | 0.211 |
PSQI | −0.036 | 0.225 |
Parameter Name | B | Std. Error | 95% Wald Confidence Interval | Hypothesis Tests | ||
---|---|---|---|---|---|---|
Minimum | Maximum | Wald x2 | p | |||
(Intercept) | −0.042 | 0.1201 | −0.277 | 0.193 | 0.122 | 0.727 |
[Education = primary school and below] | 0.235 | 0.0938 | 0.051 | 0.419 | 6.272 | 0.012 |
[Education = high school] | 0.710 | 0.0935 | 0.527 | 0.893 | 57.632 | 0.000 |
[Education = university] | 0 | - | - | - | - | - |
Marital status: single | −0.291 | 0.0734 | −0.435 | −0.147 | 15.730 | 0.000 |
Marital status: married | 0 | - | - | - | - | - |
Department years | 0.027 | 0.0115 | 0.004 | 0.049 | 5.389 | 0.020 |
Company years | −0.034 | 0.0139 | −0.062 | −0.007 | 6.141 | 0.013 |
Number of near-miss incidents | 0.354 | 0.0140 | 0.326 | 0.381 | 636.794 | 0.000 |
Incorrect score | −5.769 × 10−5 | 0.0024 | −0.005 | 0.005 | 0.001 | 0.981 |
Scale | 1.226 | −0.0520 | 1.129 | 1.333 |
Number of Previous Near-Misses | r | p |
---|---|---|
Education level | 0.174 ** | 0.000 |
Age | −0.070 * | 0.020 |
Sector years | 0.050 | 0.094 |
Department years | −0.059 | 0.050 |
Company years | −0.025 | 0.403 |
Marital status | 0.186 ** | 0.000 |
Previous accident | 0.587 ** | 0.000 |
Instantaneous pulse | −0.004 | 0.897 |
Daily pulse | 0.017 | 0.561 |
Deep sleep | 0.015 | 0.624 |
REM | −0.001 | 0.980 |
Mild sleep | 0.015 | 0.627 |
Active time | −0.040 | 0.187 |
Company | 0.051 | 0.087 |
Measurement | 0.000 | 1.000 |
Correct question. | 0.131 ** | 0.000 |
Correct time | −0.073 * | 0.014 |
Correct score | 0.132 | 0.000 |
Incorrect question | −0.033 | 0.274 |
Incorrect time | 0.113 ** | 0.000 |
Incorrect score | −0.033 | 0.274 |
Unanswered question | −0.123 ** | 0.000 |
Unanswered time | 0.022 | 0.464 |
Unanswered Score | −0.122 ** | 0.000 |
Total Score | 0.050 | 0.093 |
Week | 0.000 | 1.000 |
ST | 0.047 | 0.116 |
PSQI | 0.047 | 0.113 |
Parameters | B | Std. Error | 95% Wald Confidence Interval | Hypothesis Tests | ||
---|---|---|---|---|---|---|
Minimum | Maximum | Wald x2 | p | |||
Intercept | 1.199 | 0.5098 | 0.200 | 2.199 | 5.536 | 0.019 |
[Education = primary school and below] | −1.533 | 0.1692 | −1.864 | −1.201 | 82.000 | 0.000 |
[Education = high school] | −0.062 | 0.1607 | −0.377 | 0.254 | 0.146 | 0.702 |
[Education = university and above] | 0 a | - | - | - | - | - |
[Accident = no accident] | −3.654 | 0.1758 | −3.999 | −3.310 | 431.951 | 0.000 |
[Accident = accident] | 0 a | - | - | - | - | - |
[Marital status = single] | −0.134 | 0.1310 | −0.391 | 0.123 | 1.048 | 0.306 |
[Marital status = married] | 0 a | - | - | - | - | - |
Age | 0.074 | 0.0092 | 0.056 | 0.092 | 63.629 | 0.000 |
Correct score | 0.014 | 0.0047 | 0.005 | 0.023 | 8.529 | 0.003 |
Incorrect time | 0.228 | 0.0610 | 0.109 | 0.348 | 14.016 | 0.000 |
Unanswered score | −0.029 | 0.0052 | −0.039 | −0.019 | 31.088 | 0.000 |
Scale | 3.754 b | 0.1591 | 3.455 | 4.079 |
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Tasdelen, A.; Özpinar, A.M. A Dynamic Risk Analysis Model Based on Workplace Ergonomics and Demographic-Cognitive Characteristics of Workers. Sustainability 2023, 15, 4553. https://doi.org/10.3390/su15054553
Tasdelen A, Özpinar AM. A Dynamic Risk Analysis Model Based on Workplace Ergonomics and Demographic-Cognitive Characteristics of Workers. Sustainability. 2023; 15(5):4553. https://doi.org/10.3390/su15054553
Chicago/Turabian StyleTasdelen, Ahmet, and Alper M. Özpinar. 2023. "A Dynamic Risk Analysis Model Based on Workplace Ergonomics and Demographic-Cognitive Characteristics of Workers" Sustainability 15, no. 5: 4553. https://doi.org/10.3390/su15054553