Perry W. Logan

Rating Exposure Control Using Bayesian Decision Analysis

A model is presented for applying Bayesian statistical techniques to the problem of determining, from the usual limited number of exposure measurements, whether the exposure profile for a similar exposure group can be considered a Category 0, 1, 2, 3, or 4 exposure. The categories were adapted from the AIHA exposure category scheme and refer to (0) negligible or trivial exposure (i.e., the true X 0.95 < 1%OEL), (1) highly controlled (i.e., X 0.95 < 10%OEL), (2) well controlled (i.e., X 0.95 < 50%OEL), (3) controlled (i.e., X 0.95 < 100%OEL), or (4) poorly controlled (i.e., X0.95 > 1%OEL) exposures. Unlike conventional statistical methods applied to exposure data, Bayesian statistical techniques can be adapted to explicitly take into account professional judgment or other sources of information. The analysis output consists of a distribution (i.e., set) of decision probabilities: e.g., 1%, 80%, 12%, 5%, and 2% probability that the exposure profile is a Category 0, 1, 2, 3, or 4 exposure. By inspection of these decision probabilities, rather than the often difficult to interpret point estimates (e.g., the sample 95th percentile exposure) and confidence intervals, a risk manager can be better positioned to arrive at an effective (i.e., correct) and efficient decision. Bayesian decision methods are based on the concepts of prior, likelihood, and posterior distributions of decision probabilities. The prior decision distribution represents what an industrial hygienist knows about this type of operation, using professional judgment; company, industry, or trade organization experience; historical or surrogate exposure data; or exposure modeling predictions. The likelihood decision distribution represents the decision probabilities based on an analysis of only the current data. The posterior decision distribution is derived by mathematically combining the functions underlying the prior and likelihood decision distributions, and represents the final decision probabilities. Advantages of Bayesian decision analysis include: (a) decision probabilities are easier to understand by risk managers and employees; (b) prior data, professional judgment, or modeling information can be objectively incorporated into the decision-making process; (c) decisions can be made with greater certainty; (d) the decision analysis can be constrained to a more realistic “parameter space” (i.e., the range of plausible values for the true geometric mean and geometric standard deviation); and (e) fewer measurements are necessary whenever the prior distribution is well defined and the process is fairly stable. Furthermore, Bayesian decision analysis provides an obvious feedback mechanism that can be used by an industrial hygienist to improve professional judgment. For example, if the likelihood decision distribution is inconsistent with the prior decision distribution then it is likely that either a significant process change has occurred or the industrial hygienists initial judgment was incorrect. In either case, the industrial hygienist should readjust his judgment regarding this operation.

Mortality and cancer incidence in ammonium perfluorooctanoate production workers

Objective To evaluate mortality and cancer incidence in a cohort of ammonium perfluorooctanoate (APFO) exposed workers. Methods We linked a combined cohort (n=9027) of employees from APFO and non-APFO production facilities in Minnesota to the National Death Index and to cancer registries of Minnesota and Wisconsin. Industrial hygiene data and expert evaluation were used to create a task-based job exposure matrix to estimate APFO exposure. Standardised mortality ratios were estimated using Minnesota population rates. HRs and 95% CIs for time-dependent cumulative APFO exposure were estimated with an extended Cox model. A priori outcomes of interest included cancers of the liver, pancreas, testes, kidney, prostate and breast, and mortality from cardiovascular, cerebrovascular and chronic renal diseases. Results Mortality rates in the APFO-exposed cohort were at or below the expected, compared with Minnesota. The HR for dying from the cancer and non-cancer outcomes of interest did not show an association with APFO exposure. Similarly, there was little evidence that the incident cancers were associated with APFO exposure. Compared to the non-exposed population, modestly elevated, but quite imprecise HRs were observed in the higher-exposure quartiles for bladder cancer (HR=1.66, 95% CI 0.86 to 3.18) and pancreatic cancer (HR=1.36, 95% CI 0.59 to 3.11). No association was observed between APFO exposure and kidney, prostate or breast cancers. Conclusions This analysis did not support an association between occupational APFO exposure and the evaluated health endpoints, however, the study had limited power to evaluate some conditions of interest.

Desktop Study of Occupational Exposure Judgments: Do Education and Experience Influence Accuracy?

This study examines the impact of several experience and education determinants on exposure judgment accuracy. The study used desktop assessments performed on several different tasks with different exposure profiles to identify correlations between determinants and judgment accuracy using logistic regression models. The exposure judgments were elicited from industrial hygienists with varying levels of experience, education, and training. Videos and written and oral information about the exposure tasks were presented to all participants as they documented a series of qualitative and quantitative exposure judgment probabilities in four exposure categories. Participants (n = 77) first documented their qualitative and then their quantitative exposure assessments after receiving the series of sampling data points. Data interpretation tests and training in simple rules-of-thumb for data interpretation were also given to each participant to investigate the impact of data interpretation skills on exposure judgment accuracy. Logistic regression analysis indicated “years of exposure assessment experience” (p < 0.05), “highest EHS degree” (p < 0.05), and a participants “data interpretation test score” (p < 0.05) directly impacted qualitative exposure judgment accuracy. Logistic regression models of quantitative judgment accuracy showed positive correlation with “greater than 10 years of exposure assessment experience” (p < 0.05), “highest EHS degree” (p < 0.05), a participants “data interpretation test score” (p < 0.001), rules-of-thumb data interpretation training (p < 0.001), and the number of sample data points available for a judgment (p < 0.005). Analyzing judgments in subsets for participants with less or more than 10 years’ experience indicated additional correlations with Certified Industrial Hygienist and Certified Safety Professional certifications, total number of task exposure assessments, and career number of air surveys. The correlation of qualitative and quantitative exposure judgment accuracy with “greater than 10 years experience” supports similar research findings from other fields. The results of this study indicate that several determinants of experience, education, and training, in addition to the availability of sampling data, significantly impact the accuracy of exposure assessments. The findings also suggest methods for enhancing exposure judgment accuracy through statistical tools, mathematical exposure modeling, and specific training.

Cohort Mortality Study of Roofing Granule Mine and Mill Workers. Part II. Epidemiologic Analysis, 1945–2004

The mortality of 2650 employees (93.4% males) in the mine and mill production of roofing granules at four plants was examined between 1945 and 2004. Hypotheses focused on diseases associated with exposure to silica: nonmalignant respiratory disease, lung cancer, and nonmalignant renal disease. Study eligibility required ≥ 1 year of employment by 2000. Work history and vital status were followed through 2004 with < 1% lost to follow-up. Industrial hygiene sampling data (1871 sampling measurements over a 32-year period) and professional judgment were used to construct 15 respirable crystalline silica exposure categories. A category was assigned to all plant-, department-, and time-dependent standard job titles. Cumulative respirable crystalline silica exposure (mg/m3-years) was calculated as the sum of the product of time spent and the average exposure for each plant-, department-, job-, and calendar-year combination. The cohort geometric mean was 0.17 mg/m3-years (geometric standard deviation 4.01) and differed by plant. Expected deaths were calculated using U.S. (entire cohort) and regional (each plant) mortality rates. Poisson regression was used for internal comparisons. For the entire cohort, 772 deaths (97.4% males) were identified (standardized mortality ratio 0.95, 95% CI 0.88–1.02). There were 50 deaths from nonmalignant respiratory diseases (1.14, 95% CI 0.85–1.51). Lagging exposure 15 years among the male cohort, the relative risks for nonmalignant respiratory disease were 1.00 (reference), 0.80, 1.94, and 2.03 (p value trend = 0.03) when cumulative exposure was categorized < 0.1, 0.1–<0.5, 0.5–<1.0, and ≥ 1.0 mg/m3-years, respectively. There was a total of 77 lung cancer deaths (1.11, 95% CI 0.88–1.39). Lagging exposure 15 years, the relative risks for males were 1.00 (reference), 1.83, 1.83, and 1.05 (p value trend = 0.9). There were 16 deaths from nonmalignant renal disease (1.76, 95% CI 1.01–2.86). This exposure-response trend was suggestive but imprecise. The study results are consistent with other cohorts with similar levels of exposure to respirable crystalline silica.

Isocyanate Exposure Assessment Combining Industrial Hygiene Methods with Biomonitoring for End Users of Orthopedic Casting Products

Previous studies have suggested a potential risk to healthcare workers applying isocyanate-containing casts, but the authors reached their conclusions based on immunological or clinical pulmonology test results alone. We designed a study to assess potential exposure to methylene diphenyl diisocyanate (MDI) among medical personnel applying orthopedic casts using two different application methods. Air, dermal, surface, and glove permeation sampling methods were combined with urinary biomonitoring to assess the overall risk of occupational asthma to workers handling these materials. No MDI was detected in any of the personal and area air samples obtained. No glove permeation of MDI was detected. A small proportion of surface (3/45) and dermal wipe (1/60) samples were positive for MDI, but were all from inexperienced technicians. Urinary metabolites of MDI [methylenedianiline (MDA)] were detected in three of six study participants prior to both a ‘dry’ and ‘wet’ application method, five of six after the dry method, and three of six after the wet method. All MDA results were below levels noted in worker or general populations. Our conclusion is that the risk of MDI exposure is small, but unquantifiable. Because there is some potential risk of dermal exposure, medical personnel are instructed to wear a minimum of 5-mil-thick (5 mil = 0.005 inches) nitrile gloves and avoid contact to unprotected skin. This could include gauntlets, long sleeves, and/or a laboratory coat.

Cohort Mortality Study of Roofing Granule Mine and Mill Workers. Part I: Estimation of Historical Crystalline Silica Exposures

A study was conducted to construct a job exposure matrix for the roofing granule mine and mill workers at four U.S. plants. Each plant mined different minerals and had unique departments and jobs. The goal of the study was to generate accurate estimates of the mean exposure to respirable crystalline silica for each cell of the job exposure matrix, that is, every combination of plant, department, job, and year represented in the job histories of the study participants. The objectives of this study were to locate, identify, and collect information on all exposure measurements ever collected at each plant, statistically analyze the data to identify deficiencies in the database, identify and resolve questionable measurements, identify all important process and control changes for each plant-department-job combination, construct a time line for each plant-department combination indicating periods where the equipment and conditions were unchanged, and finally, construct a job exposure matrix. After evaluation, 1871 respirable crystalline silica measurements and estimates remained. The primary statistic of interest was the mean exposure for each job exposure matrix cell. The average exposure for each of the four plants was 0.042 mg/m3 (Belle Mead, N.J.), 0.106 mg/m3 (Corona, Calif.), 0.051 mg/m3 (Little Rock, Ark.), and 0.152 mg/m3 (Wausau, Wis.), suggesting that there may be substantial differences in the employee cumulative exposures. Using the database and the available plant information, the study team assigned an exposure category and mean exposure for every plant-department-job and time interval combination. Despite a fairly large database, the mean exposure for >95% of the job exposure matrix cells, or specific plant-department-job-year combinations, were estimated by analogy to similar jobs in the plant for which sufficient data were available. This approach preserved plant specificity, hopefully improving the usefulness of the job exposure matrix.

Comparative Emissions of Random Orbital Sanding between Conventional and Self-Generated Vacuum Systems

Conventional abrasive sanding generates high concentrations of particles. Depending on the substrate being abraded and exposure duration, overexposure to the particles can cause negative health effects ranging from respiratory irritation to cancer. The goal of this study was to understand the differences in particle emissions between a conventional random orbital sanding system and a self-generated vacuum random orbital sanding system with attached particle filtration bag. Particle concentrations were sampled for each system in a controlled test chamber for oak wood, chromate painted (hexavalent chromium) steel panels, and gel-coated (titanium dioxide) fiberglass panels using a Gesamtstaub-Probenahmesystem (GSP) sampler at three different locations adjacent to the sanding. Elevated concentrations were reported for all particles in the samples collected during conventional sanding. The geometric mean concentration ratios for the three substrates ranged from 320 to 4640 times greater for the conventional sanding system than the self-generated vacuum sanding system. The differences in the particle concentration generated by the two sanding systems were statistically significant with the two sample t-test (P < 0.0001) for all three substances. The data suggest that workers using conventional sanding systems could utilize the self-generated vacuum sanding system technology to potentially reduce exposure to particles and mitigate negative health effects.