| Literature DB >> 31278218 |
Nazanin Izadi1, Omid Aminian1, Bahador Esmaeili2.
Abstract
BACKGROUND: Although much is known about the distribution of occupational accidents in the world, less is known about occupational injuries in developing countries. Therefore, the aim of this study was to investigate the trend of occupational accidents during 10 years (2007-2016) and to find factors affecting the accident outcome. STUDYEntities:
Keywords: Epidemiology; Injury; Occupational Accident; Worker
Mesh:
Year: 2019 PMID: 31278218 PMCID: PMC7183544
Source DB: PubMed Journal: J Res Health Sci ISSN: 2228-7795
Occupational accident characteristics
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| Inside workplace | 195,908 | 94.4 |
| Outside workplace | 9,595 | 5.6 |
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| Equipment malfunction | 8,070 | 3.7 |
| Unprotected safeguards | 11,850 | 5.4 |
| Unsafe work environment | 2,593 | 1.2 |
| Improper management and training | 4,197 | 2.0 |
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| Incaution and lack of attention | 1,301,754 | 60.0 |
| Failure to use protective equipment | 4,780 | 2.2 |
| Adopt safety rules | 11,604 | 5.3 |
| Others | 44,136 | 20.2 |
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| Collision, hit and trapping | 131,935 | 59.3 |
| Falling | 40,738 | 18.3 |
| Burning | 6,231 | 2.8 |
| Acute accidents | 31,500 | 14.2 |
| Electrical shock | 1,595 | 0.7 |
| Others | 8,709 | 3.9 |
| Poisoning | 1,306 | 0.6 |
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| Head& neck | 11,497 | 5.2 |
| upper extremity | 80,439 | 36.1 |
| lower extremity | 75,663 | 34.0 |
| spine | 40,297 | 18.1 |
| Trunk | 734 | 0.3 |
| Abdomen & pelvic | 421 | 0.2 |
| whole body | 2,625 | 1.2 |
| Others | 10,836 | 4.9 |
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| Death | 1,079 | 0.5 |
| Total disability | 2,050 | 1.0 |
| Incomplete disability | 3,401 | 1.7 |
| Minor disability | 10,237 | 4.9 |
| Recovery | 190,837 | 91.9 |
Figure 1
Figure 2
Figure 3
Figure 5Relationship between demographic and occupational characteristics with accident outcome
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| Male | 203,322 | 1074 | 1,997 | 3,317 | 9,967 | 186,967 | |
| Female | 4,281 | 5 | 53 | 84 | 270 | 3,869 | |
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| Single | 46,874 | 133 | 468 | 767 | 2,362 | 43,144 | |
| Married | 160,730 | 946 | 1,582 | 2,634 | 7,875 | 147,693 | |
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| Agriculture | 5,279 | 43 | 78 | 143 | 370 | 4,645 | |
| Industry | 149,083 | 605 | 1,324 | 2,333 | 7,577 | 137,244 | |
| Service | 53,242 | 431 | 648 | 925 | 2,290 | 48,948 | |
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| Spring | 45,331 | 251 | 504 | 891 | 2,294 | 41,391 | |
| Summer | 52,329 | 272 | 527 | 841 | 2,479 | 48,210 | |
| Autumn | 54,043 | 255 | 485 | 833 | 2,744 | 497,26) | |
| Winter | 55,901 | 301 | 534 | 836 | 2,720 | 51,510 | |
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| Inside | 195,908 | 817 | 1,720 | 2,981 | 9,426 | 180,964 | |
| Outside | 11,696 | 262 | 330 | 420 | 811 | 9,873 | |
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| Fix | 193,392 | 720 | 1,398 | 2,334 | 6,744 | 127,318 | |
| Rotatory | 14,212 | 359 | 652 | 1,067 | 3,493 | 63,519 |
Relationship between different factors and accidents with outcomes: adjusted odds ratio and 95% confidence interval with multinomial logistic regression (the reference category is recovery)
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| Age | 1 | 1.03 (1.02, 1.03) | 1.02 (1.02, 1.03) | 1.02 (1.02, 1.03) | 1.01 (1.01, 1.02) |
| Sex | 1 | 0.25 (0.10, 0.59) | 1.18 (0.89, 1.60) | 1.14 (0.98, 1.43) | 1.25 (1.10, 1.40) |
| Marital status | 1 | 1.34 (1.09, 1.63) | 0.78 (0.69, 0.87) | 0.78 (0.70, 0.86) | 0.85 (0.80, 0.90) |
| Shift work | 1 | 1.01 (0.91, 1.10) | 0.95 (0.88, 1.02) | 0.95 (0.89, 1.00) | 1.01 (0.98, 1.04) |
| Job category | 1 | 1.29 (1.15, 1.46) | 1.05 (0.97, 1.20) | 0.89 (0.83, 0.96) | 0.79 (0.75, 0.82) |
| Season | 1 | 0.99 (0.94, 1.05) | 0.95 (0.91, 0.99) | 0.92 (0.89, 0.95) | 0.99 (0.98, 1.01) |
| Accident location | 1 | 4.88 (0.42, 5.64) | 3.31 (2.90, 3.70) | 2.52 (2.26, 2.80) | 1.63 (1.51, 1.76) |