The Scientific Basis of Uncertainty Factors Used in Setting Occupational Exposure Limits

Figures & data

Table 1 UFs Used in OEL-setting, and the Rationale for Their Use

Factor	Area of Uncertainty	Basic Principle
UFA	Animal to Human	Adjusts for differences in sensitivity between animals and the average human, when the PoD is based on animal studies
UFH	Average Human to Sensitive Human	Adjusts the PoD for the difference between the average human and the most sensitive applicable subpopulation
UFL	LOAL-to-NOAEL	Adjusts for uncertainty in the value of the PoD as an estimate of the threshold for the onset of effects, if based on a LOAEL rather than a benchmark dose or a NOAEL
UFS	Short-term to Long-term Exposure	Adjusts for the possibility of identifying a lower PoD for chronic toxicity when extrapolating from a study of shorter duration
UFD	Database Insufficiency	Adjusts for the possibility of identifying a lower PoD (or more sensitive effect) if additional studies were available

Table 2 Default Uncertainty/Assessment Factors for Workers^A

Factor	ECHA	ECETOC	TNO/RIVM	Other^B
UFA	AS–BW^0.75 2.5 (TD)	AS–BW^0.75	AS 3 (TD)	NS
UFH	5	3	3	NS
UFL	1	3 or BMD	1–10 or BMD	NS
UFS	2–6	2–6	10–100	NS
UFD	1	NA	1	NS
MF	NA	NA	NS	NS

^AAdapted from ECHA (2008) Table R.8-19. Guidance on information requirements and chemical safety assessment. Chapter R.8: Characterization of dose [concentration]-response for human health.^(41)BACGIH—American Conference of Governmental Industrial Hygienists Threshold Limit Values; American Industrial Hygiene Association Guideline Foundation Workplace Environmental Exposure Levels; SCOEL—Scientific Committee on Occupational Exposure LimitsAbbreviations: ECHA—European Chemicals Agency; ECETOC – European Centre for Ecotoxicology and Toxicology of Chemicals; TNO/RIVM—National Institute of Public Health and the Environment (in cooperation with TNO Nutrition and Food research); AS—Allometric Scaling (BW^0.75); NS – Not Specified; TD – Toxicodynamics

Figure 1 A conceptual illustration of uncertainties that are commonly considered in noncancer risk assessment for OEL setting. UFs are seen as differing extrapolations among dose response curves for either experimental animal to human (UF_A), average to sensitive humans (UF_H), LOAEL to NOAEL (UF_L), shorter-term to longer-term (UF_S), or as an adjustment for database insufficiency (UF_D).

Table 3 Merits and Limitations of Alternative UF Documentation Approaches

Factor Application and Multiplication Approach

Description: specific default values are assigned for preselected areas of uncertainty. The composite UF is calculated as the product of the default values that are pertinent to the specific data sets being evaluated. Rules for modifying the resulting composite UF may be specified to address overlapping uncertainties.

Advantages:

• Transparency in OEL calculation improves user ability to interpret the OEL and its uncertainties and supports worker risk communication

• Relative impact of different uncertainties on the OEL are clear, allowing for a determination of the value or impact of collecting new data to relieve uncertainty

Disadvantages:

• Rigorous application of default values limits the value offered through the use of expert scientific judgment

• Multiplying default values may yield a composite UF which does not align with the totality of the data set, often requiring significant effort and potential user confusion in explaining departures from pre-assigned defaults

Uncertainty Weight of Evidence Approach

Description: areas of uncertainty are considered in an integrated approach, with particular focus on potential overlapping considerations and the optimum protective composite UF derived when balancing the data from all lines of evidence.

Advantages:

• Provides greater flexibility in deriving the composite UF that takes into account all aspects of the available data using a weight of evidence approach

• Avoids pitfalls of setting OELs that are not appropriate that can result from misapplication of default UF values or overlapping areas of uncertainty

Disadvantages:

• Absence of specific defaults limits transparency in the basis for the OEL, with resulting limitations for user communication and data collection

• Requires a high degree of scientific expertise in OEL development, because the approach is less prescriptive

Figure 2 Derivation of a chemical-specific adjustment factor (CSAF) from a unimodal distribution.⁽⁷³⁾ © Taylor & Francis. Reproduced by permission of Taylor & Francis. Permission to reuse must be obtained from the rightsholder.

Figure 3 Derivation of a chemical-specific adjustment factor (CSAF) from a bimodal distribution.⁽⁷³⁾ © Taylor & Francis. Reproduced by permission of Taylor & Francis. Permission to reuse must be obtained from the rightsholder.

Figure 4 Application of the CSAF approach with additional uncertainty factors for exposure limit setting. Adapted from WHO/IPCS (2005).⁽²¹⁾

Figure 5 Hierarchy of approaches to address uncertainty, and the correspondence of greater scientific certainty to an increased requirement for the incorporation of chemical- and species-specific data into the risk assessment process.

Naumann, B.D., P.A. Weideman, R. Dixit, S.J. Grossman, C.F. Shen, and E.V. Sargent: Use of toxicokinetic and toxicodynamic data to reduce uncertainties when setting occupational exposure limits for pharmaceuticals. Hum. Ecol. Risk Assess. 3(4):555–565 (1997).

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