Fatigue as a Predictor of Medical Utilization, Occupational Accident and Sickness Absence.
- Author:
Sei Jin CHANG
1
;
Sang Baek KOH
;
Dongmug KANG
;
Seong Ah KIM
;
Jin Joo CHUNG
;
Chul Gab LEE
;
Myung Geun KANG
;
Sook Jung HYUN
;
Jung Jin CHO
;
Bong Suk CHA
;
Jong Ku PARK
Author Information
1. Department of Preventive Medicine and Institute of Occupational Medicine, Wonju College of Medicine, Yonsei University. chang@wonju.yonsei.ac.kr
- Publication Type:Original Article
- Keywords:
Fatigue;
Medical utilization;
Occupational accident;
Sickness absence
- MeSH:
Accidents, Occupational*;
Classification;
Fatigue*;
Humans;
Inpatients;
Logistic Models;
Odds Ratio;
Outpatients
- From:Korean Journal of Occupational and Environmental Medicine
2005;17(4):318-332
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
OBJECTIVES: This study examined the relationship of fatigue to medical utilization, occupational accident and sickness absence. Subjects and METHODS: Data were obtained from the National Study for Development and Standardization of Occupational Stress (NSDSOS Project, 2002~2004). A total of 30,146 employees categorized within the Korean Standard Industrial Classification and the Korean Standard Occupational Classification were recruited. A structured-questionnaire was used to assess the participants' sociodemographics, job-related factors, health-related behaviors, personality trait, self-perceived fatigue (MFS) and the frequency of medical utilization, occupational accident and sickness absence. Data on medical utilization and occupational accident were confirmed from company health records. Chi-square test and logistic regression analysis were used to elucidate the relationship of self-perceived fatigue to medical utilization, occupational accident and sickness absence. RESULTS: In logistic regression analyses, self-perceived fatigue was associated with medical utilization (outpatient), occupational accident and sickness absence although the strength of the associations was higher in the blue collar workers except for medical utilization. For medical utilization, the white collar workers' adjusted odds ratios of outpatient utilization for workers scoring in the third quartile and the highest quartile, compared to workers scoring in the lowest quartile were 1.50 (95% CI: 1.20-1.87) and 2.16 (95% CI: 1.69-2.75), respectively. The blue collar workers' adjusted odds ratios of outpatient utilization for workers scoring in the second (OR: 1.23, 95% CI: 1.06-1.43), third (OR: 1.42, 95% CI: 1.22- 1.66) and highest quartile (OR: 1.83, 95% CI: 1.55-2.17), respectively, compared to workers scoring in the lowest quartile were statistically significant. However, no associations were found between fatigue and inpatient utilization for either the white or blue collar workers. The blue collar workers' adjusted odds ratios of being injured for workers scoring in the second, third and highest quartile were 1.41 (95% CI: 1.00-2.00), 1.57 (95% CI: 1.10-2.22) and 2.41 (95% CI: 1.69-3.44), respectively, compared to those scoring in the lowest quartile, but, those of the white collar workers were not significant. There was more likely to an increased risk of sickness absence in workers scoring in the second, third and highest quartile compared to those scoring in the lowest quartile in both white and blue collar workers, but the magnitudes of risk were higher in the blue collar workers than the white collars workers. CONCLUSION: This result suggests that fatigue is a determinant predictor of medical utilization, occupational accident and sickness absence, and that the pattern of risks for the three outcomes differs according to the occupational type. Some limitations of this study and considerations for future study were also discussed.
