Statistical model for prediction of retrospective exposure to ethylene oxide in an occupational mortality study
| Autor: | V. Ringenburg, J. Morawetz, Robert F. Herrick, Richard W. Hornung, N. K. Steenland, A. L. Greife, Leslie T. Stayner, Larry J. Elliott |
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| Rok vydání: | 1994 |
| Předmět: |
Ethylene Oxide
medicine.medical_specialty Models Statistical Time Factors business.industry Exposure Category Public Health Environmental and Occupational Health Regression analysis Statistical model Standard deviation Occupational Diseases Data set Occupational medicine Occupational Exposure Statistics Linear regression Humans Medicine business Exposure assessment |
| Zdroj: | American Journal of Industrial Medicine. 25:825-836 |
| ISSN: | 1097-0274 0271-3586 |
| DOI: | 10.1002/ajim.4700250607 |
| Popis: | Since direct measures of individual exposure seldom exist for the entire period of an occupational mortality study, retrospective exposure estimates are necessary. This is often done in a subjective manner involving a consensus of opinion from a panel of epidemiologists and industrial hygienists. An alternative method utilizing a statistical model provides a more objective procedure for retrospective exposure assessment. The development of a weighted multiple regression model is presented for estimation of exposure levels to ethylene oxide (ETO) for inclusion in a cohort mortality study of workers in the sterilization industry. Three steps in development of the model are described: (1) data acquisition and assessment, (2) model building, and (3) evaluation of the model. The final model explained a remarkable 85% of the variability in 205 average measurements of ETO levels. Exposure factors included in the model were exposure category, product type, size of the sterilization unit, selected engineering controls, days after sterilization, and calendar year. The model was evaluated in two ways: against a set of measurement data not used to develop the model and a panel of 11 industrial hygienists representing the sterilization industry. The model predicted ETO exposures within 1.1 ppm of the validation data set with a standard deviation of 3.7 ppm. The arithmetic and geometric means of the 46 measurements in the validation data set were 4.6 and 2.2 ppm, respectively. The model also outperformed the panel of industrial hygienists relative to the validation data in terms of both bias and precision. |
| Databáze: | OpenAIRE |
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