Annals of Occupational and Environmental Medicine

Original Article

The Effect of Socio-Economic Factors on Occupational Injuries in Korea: A Time Series Analysis: Ye Won Bang, Hyoung June Im, Young Jun Kwon, Seong Sik Cho, Tae Kyung Lee, In Ki Yoon, Young Su Ju; Korean Journal of Occupational and Environmental Medicine 2011;23(4):397-406. Published online December 31, 2011; DOI: https://doi.org/10.35371/kjoem.2011.23.4.397

OBJECTIVES
We performed a time series analysis in order to identify the relationship between the occupational injury rate and socio-economic factors, and through this predict the occupational injury occurrence rate.
METHODS
We reviewed 168 sets of monthly data. For the statistical analysis, we used the economic index data provided by Statics Korea and the occupational injury index provided by the Workers' Compensation & Welfare Service gathered from 1994 to 2007. We performed a correlation analysis to find relationship between the occupation injury rate and economic factors. Using the correlation analysis result, we used time series analysis for the data in order to find out the association between occupational injuries and socio-economic indicators. We performed time series analysis to find out association occupation injury rate with socio-economic factors. In addition we ran a prediction occupational injury rate for 2008 and compared the result to the actual value.
RESULTS
The factors associated with occupational injuries were the daily worker index (b=0.394, p<0.0001), the mechanical index (b=-0.023, p=0.0043), the manufacturing operation index (b=0.152, p<0.0001), the workers compensation coverage expansion (b=1.189, p=0.015), the IMF index (b=-2.05, p<0.0001), and the after IMF index (b=-1.565, p=0.01). The daily worker index, manufacturing operation index, and workers compensation coverage expansion had an effect that increased the occupational injury rate. Conversely, the mechanical index and IMF variable tended to decrease the occupational injury rate.
CONCLUSIONS
This study suggests that the daily worker index, manufacturing operation index, workers compensation coverage expansion, and IMF variables are related factors in regards to occupational injury.

Citations

Citations to this article as recorded by

Business Cycle and Occupational Accidents in Korea
Dong Koo Kim, Sunyoung Park
Safety and Health at Work.2020; 11(3): 314. CrossRef
The Prediction of Industrial Accident Rate in Korea: A Time Series Analysis
Eunsuk Choi, Gyeong-Suk Jeon, Won Kee Lee, Young Sun Kim
Korean Journal of Occupational Health Nursing.2016; 25(1): 65. CrossRef

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Original Article

Time Series Analysis between the Concentration of Air Pollutants and the Number of Respiratory Disease Outpatients in Seoul: Byeong Chul Choi, Jung Wan Koo, Sung Kyun Park, Hyun Woo Yim, Kang Sook Lee, Won Chul Lee, Chung Yill Park; Korean Journal of Occupational and Environmental Medicine 2000;12(1):70-80. Published online March 31, 2000; DOI: https://doi.org/10.35371/kjoem.2000.12.1.70

Abstract PDF

OBJECTIVES
This study was conducted to investigate whether air pollution levels in Seoul have short term effects on respiratory disease outpatients.
METHODS
We analyzed five air pollutants (CO, NOy, Oy, SOp, PMyp) and daily counts of outpatient for respiratory disease divided by age group ((15yrs, 15-64yrs, 65+yrs) during the period of July 1997-June 1998 using Generalized Additive Model(GAM).
RESULTS
After controlling for seasonal trends, day of the week, week of the month, temperature and humidity, CO (RR=1. 041 ~ l. 051, 0-day lag) and NOy (RR=1. 024~1. 050, 3-day lag) were significantly associated with daily counts for respiratory disease in all age groups. 0, and SO, were associated, with a 3-day lag in the age group under 15 years (O RR=1. 047, 95% CI=1. 045- 1. 049 i SOp RR=1. 018, 95% CI=1. 017- l. 020) and with a 0-day lag in the age group 15 to 64 years (0, RR=1. 035, 95% CI=1. 032-1. 037; SO, RR=1. 037, 95% CI=1. 035-1. 039), in the age group over 65 years (O RR=1. 042, 95% CI=1. 033-1. 051; SO RR=1.029, 95% CI=1.022-1.036). PM was weakly associated, with a 1-day lag in the age group under 15 years (RR=1.011, 95% CI=1.010-1.013) and with a 0-day lag in the age group 15 to 64 years (RR=1. 021, 95% CI=1. 019-1. 023), in the age group over 65 years (RR=1. 025, 95% CI=1. 018-1. 032). In the two pollutant model, the magnitudes of the relative risk for CO, NOy and Oq were maintained, but SOy was not associated with daily counts for respiratory disease in the age group under 15 years after controlling for NO,. PMyp was not associated in all age groups after controlling for CO, so the association with PMyp in the single pollutant model might be confounded by CO. In this study, the impact Of PMyp on the respiratory disease was not large as compared with other pollutants.
CONCLUSIONS
Air pollution in Seoul may increase the incidence of the respiratory disease, so more positive attention for the control of air pollution should be paid.

Citations

Citations to this article as recorded by

Impact of environmental factors on pulmonary tuberculosis in multi-levels industrial upgrading area of China
Xiang Yi, Shixiao Liu
Environmental Research.2021; 195: 110768. CrossRef

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