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Developing a Semi-Quantitative Occupational Risk Prediction Model for Chemical Exposures and Its Application to a National Chemical Exposure Databank

Author

Listed:
  • Shih-Min Wang

    (Department of Occupational Safety and Health, College of Public Health, China Medical University, 91 Hsueh-Shih Road, Taichung 40402, Taiwan)

  • Trong-Neng Wu

    (Graduate Institute of Biostatistics, China Medical University, 91 Hsueh-Shih Road, Taichung 40402, Taiwan)

  • Yow-Jer Juang

    (Department of Occupational Safety and Health, Chung Hwa University of Medical Technology, 89, Wenhwa 1st St., Rende District, Tainan 71701, Taiwan)

  • Yu-Tung Dai

    (Department of Occupational Safety and Health, Chang Jung Christian University, 1 Changda Rd., Gueiren District, Tainan 71101, Taiwan)

  • Perng-Jy Tsai

    (Department of Occupational Safety and Health, College of Public Health, China Medical University, 91 Hsueh-Shih Road, Taichung 40402, Taiwan
    Department of Environmental and Occupational Health, Medical College, National Cheng Kung University, 138 Sheng-Li Road, Tainan 70403, Taiwan)

  • Chiu-Ying Chen

    (Department of Public Health, College of Public Health, China Medical University, 91 Hsueh-Shih Road, Taichung 40402, Taiwan)

Abstract

In this study, a semi-quantitative occupational chemical exposure risk prediction model, based on the calculation of exposure hazard indexes, was proposed, corrected, and applied to a national chemical exposure databank. The model comprises one factor used to describe toxicity ( i.e. , the toxicity index), and two factors used to reflect the exposure potential ( i.e. , the exposure index and protection deficiency index) of workers exposed to chemicals. An expert system was used to correct the above proposed model. By applying the corrected model to data obtained from a national occupational chemical hazard survey program, chemical exposure risks of various manufacturing industries were determined and a national control strategy for the abatement of occupational chemical exposures was proposed. The results of the present study would provide useful information for governmental agencies to allocate their limited resources effectively for reducing chemical exposures of workers.

Suggested Citation

  • Shih-Min Wang & Trong-Neng Wu & Yow-Jer Juang & Yu-Tung Dai & Perng-Jy Tsai & Chiu-Ying Chen, 2013. "Developing a Semi-Quantitative Occupational Risk Prediction Model for Chemical Exposures and Its Application to a National Chemical Exposure Databank," IJERPH, MDPI, vol. 10(8), pages 1-15, July.
  • Handle: RePEc:gam:jijerp:v:10:y:2013:i:8:p:3157-3171:d:27502
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