Statistical model for prediction of retrospective exposure to ethylene oxide in an occupational mortality study

Abstract

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.

Modeling long-term average exposure in occupational exposure-response analysis

“…Empirical modeling of exposure can be used to predict exposure in situations where limited numbers of exposure measurements are available with the use of using simple measurable exposure surrogates in the models (7,8). So far, some researchers have reported the use of statistical models to predict occupational exposures.…”

“…So far, some researchers have reported the use of statistical models to predict occupational exposures. Several studies were undertaken for industrial hygiene purposes (8)(9)(10)(11)(12). In some studies historical exposure was modeled by job, department, production process, and the like for application in epidemiologic exposure-response analyses (8,(13)(14)(15)(16)(17).…”

“…Several studies were undertaken for industrial hygiene purposes (8)(9)(10)(11)(12). In some studies historical exposure was modeled by job, department, production process, and the like for application in epidemiologic exposure-response analyses (8,(13)(14)(15)(16)(17). Application of this technique to obtain an estimate of individual, current long-term average exposure has, to our knowledge, not been reported.…”

Fetal Exposure to Carcinogens With Tobacco Use in Pregnancy: Phase 1 MAW Study Findings

“…Following convention, a value equal to the limits of quantification divided by the square root of two was used as a constant to maximize sample size when concentrations were below limits of quantification. 22 The relationship between creatinine-normalized maternal cotinine and infant NNAL levels were analyzed using Spearman correlation coefficients, best suited for nonparametric data. P-values < .05 were considered statistically significant.…”

Evaluating OSHA's ethylene oxide standard: exposure determinants in Massachusetts hospitals

“…24 Seven years later, the ethylene oxide standard incorporated various engineering and other exposure prevention and control recommendations from NIOSH, ethylene oxide users, ethylene oxide equipment manufacturers, and others into a nonmandatory appendix. 17 These recommendations have continued to evolve since the passage of the standard, 25 in part supported by a steady stream of NIOSH research 14,[26][27][28][29][30][31][32] and public communications 24,[33][34][35][36] on the subject over a 23-year period. Our results show widespread implementation by 1993 of most of the ethylene oxide engineering controls that NIOSH and others 27,34,35 had previously shown in smaller-scale studies to be effective in controlling ethylene oxide exposures (Table 2).…”