Interpretation of airborne asbestos measurements

Our plain-English summary of Interpretation of airborne asbestos measurements, by J. Chesson, J.D. Rench, B.D. Schultz, et al (Risk Analysis, 1990).

The study

• Authors: J. Chesson, J.D. Rench, B.D. Schultz, K.L. Milne
• Journal: Risk Analysis
• Published: 1990;10(3):437-47
• Cited by: 5 articles, as counted by NIH iCite
• Read it: PubMed · Publisher
• In J-M's library: Johns-Manville's company medical library held a copy (J-M no. 004446).

Abstract

Transmission electron microscopy (TEM) is the preferred method of measuring airborne asbestos in buildings, but TEM measurements cannot be used directly in the existing equations relating risk to exposure because the equations are based on measurements made with a different technique--phase contrast microscopy (PCM). Comparison between measurements made by different methods is not simple because the methods differ in the size of particles they can detect, and the relationship between exposure and disease is thought to depend on, among other things, asbestos fiber size. Previous suggestions for converting TEM measurements to PCM equivalents lack generality because they fail to take into account the size distribution of the asbestos particles and the expectation that fiber-size distributions in current nonoccupational environments could differ from the workplaces of the past on which the risk equations are based. A mathematical model is presented for investigating the conversion of airborne asbestos measurements made by one method to an equivalent measurement made by another method. "Equivalent" means having the same potential to cause disease. The model clarifies the issues of concern and suggests approaches for obtaining meaningful conversion factors that will allow TEM measurements to be used in PCM-based risk equations.

In plain English

This paper studied no people. The authors presented a mathematical model for converting transmission electron microscopy (TEM) asbestos measurements into phase contrast microscopy (PCM) equivalents. Existing workplace-based risk equations rely on PCM. "Equivalent" meant having the same potential to cause disease. The model combined each setting's fiber-size mix, each size's relative potency, and which sizes each method detects. No single conversion factor, they found, fits every situation. Matching published fiber-size data to the EPA's worker studies, they estimated optical (PCM-visible) fiber shares from 0.01 for mining and milling to 0.36 for amosite insulation manufacture. In a hypothetical example, a TEM reading of 0.02 structures per cubic centimeter became 0.003 fibers per cubic centimeter, which the authors called an overestimate. Without quantitative potency data, the authors recommended checking that the TEM fiber-size mix is qualitatively less potent than the workplace exposures behind the risk equation. When that condition holds, and assuming TEM detects essentially all structures, multiplying TEM results by the workplace optical-fiber share would, they concluded, overestimate exposure. They noted that fiber-size distributions for the worker groups are essentially unknown.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Methodological paper presenting a mathematical model, with an illustrative worked example using published fiber-size data
• Who was studied: No human subjects. The authors matched published asbestos fiber-size distribution data to the epidemiologic studies of workers listed in the 1986 EPA Airborne Asbestos Health Assessment Update and used for lung cancer dose-response. These studies covered textile, friction products, mining and milling, insulation, and cement work.
• Exposure: Airborne asbestos measured by TEM in buildings versus PCM in past occupational settings. PCM counts only fibers longer than 5 micrometers and thicker than about 0.25 micrometers ("optical" fibers). Workplace exposure types in the example included amosite insulation manufacture, textile production, friction products, and mining and milling.
• Main results:
  • The conversion factor depends on the fiber-size distributions and is expected to vary between situations. No single conversion factor applies universally.
  • Using the same measurement technique in two different environments does not necessarily give comparable measurements of exposure.
  • The simplified overestimate of the conversion factor, the proportion of optical structures in the historical workplace, rests on two assumptions. The first is that the current method (TEM) detects all or essentially all structures. The second is that the current size distribution is less potent than the historical one.
  • The estimated proportions of optical fibers in the historical environments were: 0.36 for amosite insulation manufacture, 0.13 for textile production, 0.07 for friction products, and 0.01 for mining and milling.
  • After adjustment, the rankings suggested the highest relative potency for amosite insulation manufacturing, followed by asbestos textile production, then mining and friction products. Mining was 3 to 4 orders of magnitude lower than amosite insulation manufacturing. The authors said this could reflect fiber size, fiber type or other factors.
  • In a hypothetical nonoccupational example, a TEM measurement of 0.02 structures per cubic centimeter was multiplied by 0.15, the average optical-fiber proportion for the non-mining studies. This gave 0.003 fibers per cubic centimeter, which the authors described as an overestimate of exposure. For lifetime exposure from birth, this corresponded to an EPA-table lifetime lung cancer death risk per 100,000 persons of 16 for females and 51 for males.
  • If the proportion of nonasbestos fibers in the optical size range is less than 0.1, their effect on the conversion factor will be small relative to other sources of uncertainty.
• The authors' conclusion: Without quantitative information on relative potency, the authors recommended checking that the TEM fiber-size distribution qualitatively represents a lower potency than the occupational exposures behind the risk equation. When this is true, multiplying the TEM measurement by the proportion of optical structures in the occupational environment will overestimate exposure.
• Limitations the authors state:
  • Fiber-size distributions are essentially unknown for the worker cohorts in the epidemiologic studies. Later samples may not represent past exposures.
  • The choice of which size-distribution data set to link to each epidemiologic study was somewhat arbitrary.
  • No existing study provides a good data set for estimating relative potency for specific fiber-size categories.
  • The example assumed TEM detects all structure sizes, although small structures are known to be detected with probability less than 1. The authors called this assumption adequate only for illustration.
  • How sensitive the conversion factor is to uncertainty in its inputs was left for future research.
  • The overestimation approach does not give a good basis for comparing two risk estimates, because the degree of overestimation varies between environments.

Topics

Medical terms in this study, explained in our Lexicon: Transmission Electron Microscopy (TEM), phase contrast microscopy (PCM).

Related studies

• Comments on Chesson et al. Interpretation of airborne asbestos measurements — K.S. Crump (1991)
• Real-time measurement of fibers using an HY-differential mobility analyzer with an optical particle counter (KOFAM) — S. Choi, K. Jang, et al. (2017)
• Reconstruction of a century of airborne asbestos concentrations — J.S. Webber, K.W. Jackson, et al. (2004)
• Evidence and reconstruction of airborne asbestos from unconventional environmental samples — J.S. Webber, M. Getman, et al. (2006)
• Airborne concentrations of asbestos in non-occupational environments — M. Corn (1994)
• Composition of heavy metals and airborne fibers in the indoor environment of a building during renovation — M.T. Latif, N.H. Baharudin, et al. (2011)

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