Document ID: EPA-HQ-OPP-2006-0856-0005
Agency: epa
Document Type: Supporting & Related Material
Title: 
Posted Date: 2006-12-18T05:00Z

UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

WASHINGTON, D.C.  20460

OFFICE OF

PREVENTION, PESTICIDES, AND

TOXIC SUBSTANCES

Memorandum 

DATE: 	December 13, 2006 

SUBJECT: 	Transmission of Background Materials and Charge to the Panel
for the January 9-12, 2007 Session of the FIFRA Scientific Advisory
Panel (SAP) Entitled “Review of Worker Exposure Assessment Methods”

FROM: 	Jeff Evans, Biologist

		Health Effects Division (7509P)

TO: 		Myrta Christian

Designated Federal Official 

FIFRA Scientific Advisory Panel 

Office of Science Coordination and Policy (7201M) 

    Attached are 30 compact discs and 2 paper copies of all background
documents and the charge to the panel for the January 9-12, 2007 FIFRA
SAP session.  These materials do not contain any information protected
under statute as Confidential Business Information (CBI).  These
materials do not contain information protected from disclosure to
foreign and multi-national pesticide producers under FIFRA Section
10(g).  In addition, these materials include information protected by
copyright.  The attached documents and/or electronic files include the
following:

Document Title	Author(s)	Date	Indicate Whether FIFRA 10(g) or ©
Protected

Transmission of Background Materials and Charge to the Panel for the
January 9-12, 2007 Session of the FIFRA Scientific Advisory Panel (SAP)
Entitled “Review of Worker Exposure Assessment Methods”	Jeff Evans
12/13/06

	Review of Worker Exposure Assessment Methods	U.S. EPA et al.	12/13/06

	Excel Spreadsheet With Filename:

ExhibitA.PHEDCaseStudy.v102006	U.S. EPA	12/13/06

	Excel Spreadsheet With Filename:

ExhibitB.HandMethodsAnalysisPtA.102306	U.S. EPA	12/13/06

	Excel Spreadsheet With Filename:

ExhibitB.HandMethodsAnalysisPtB.110106	U.S. EPA	12/13/06

	Excel Spreadsheet With Filename:

ExhibitC_I_a_ML_DF_RawData.xls	U.S. EPA	12/13/06

	Excel Spreadsheet With Filename:

ExhibitC_I_b_ML_DF_outer.xls	U.S. EPA	12/13/06

	Excel Spreadsheet With Filename:

ExhibitC_I_c_ML_DF_inner.xls	U.S. EPA	12/13/06

	Excel Spreadsheet With Filename:

ExhibitC_II_a_L_Gran_RawData.xls	U.S. EPA	12/13/06

	Excel Spreadsheet With Filename:

ExhibitC_II_b_L_Gran_outer.xls	U.S. EPA	12/13/06

	Excel Spreadsheet With Filename:

ExhibitC_II_c_L_Gran_inner.xls	U.S. EPA	12/13/06

	Excel Spreadsheet With Filename:

ExhibitC_III_a_ML_Liq_RawData.xls	U.S. EPA	12/13/06

	Excel Spreadsheet With Filename:

ExhibitC_III_b_ML_Liq_outer.xls	U.S. EPA	12/13/06

	Excel Spreadsheet With Filename:

ExhibitC_III_c_ML_Liq_inner.xls	U.S. EPA	12/13/06

	Excel Spreadsheet With Filename:

ExhibitC_IV_a_APP_Open-CabAirblast_RawData.xls	U.S. EPA	12/13/06

	Excel Spreadsheet With Filename:

ExhibitC_IV_b_APP_Open-CabAirblast_outer.xls	U.S. EPA	12/13/06

	Excel Spreadsheet With Filename:

ExhibitC_IV_c_APP_Open-CabAirblast_inner.xls	U.S. EPA	12/13/06

	Excel Spreadsheet With Filename:

ExhibitC_V_a_APP_Closed-CabAirblast_RawData.xls	U.S. EPA	12/13/06

	Excel Spreadsheet With Filename:

ExhibitC_V_b_APP_Closed-CabAirblast_outer.xls	U.S. EPA	12/13/06

	Excel Spreadsheet With Filename:

ExhibitC_V_c_APP_Closed-CabAirblast_inner.xls	U.S. EPA	12/13/06

	Excel Spreadsheet With Filename:

ExhibitC_VI_a_APP_Open-CabSolidSpreader_RawData.xls	U.S. EPA	12/13/06

	Excel Spreadsheet With Filename:

ExhibitC_VI_c_APP_Open-CabSolidSpreader_inner.xls	U.S. EPA	12/13/06

	Agricultural Handlers Exposure Task Force (AHETF) Technical Summary
Document For a Multi-Year Pesticide Handler Worker Exposure Monitoring
Program	AHETF	12/06/06

	The Conservative Nature of the Current Practice in Estimating Pesticide
Handler and Reentry Dermal Exposures and Doses	AHETF	12/07/06

	Passive Dosimetry Data Derived from the Outdoor Residential Exposure
Task Force & Pesticide Handler Exposure Databases - Comparisons to
Biomonitoring Data (Sponsor:  AHETF & ORETF)	AHETF	12/07/06

	Summary  Comparative Evaluation of Absorbed Dose Estimates Derived From
Passive Dosimetry Measurements With Those Derived From Biological
Monitoring : Validation of Exposure Monitoring Methodologies (Sponsor
AHETF)	AHETF	12/07/06

	Procedures for Determining the Required Number of Clusters and
Monitoring Units per Cluster to Achieve Benchmark Adequacy	AHETF
12/07/06

	Comparative Evaluation of Absorbed Dose Estimates Derived From Passive
Dosimetry Measurements With Those Derived From Biological Monitoring :
Validation of Exposure Monitoring Methodologies (Sponsor AHETF)	AHETF
12/08/06

	AEATF II Background and Scoping Summary	AEATF	11/28/06

	Data Review and Study Acceptance Criteria: For Inclusion of Existing
Antimicrobial Exposure Monitoring Studies in the Antimicrobial Exposure
Assessment Task Force II (AEATFII) Database	AEATF	11/28/06

	Glossary of Terms	AEATF	11/28/06

	



Charge to the Panel: January 9-12, 2007 FIFRA Scientific Advisory Panel

	EPA has prepared a document, dated December 12, 2006, that contains the
Agency’s technical review of worker exposure methods.  This memo
contains the questions and issues posed by EPA to the panel for
discussion.  In addition to this memo, several documents/files are
provided as supporting information.

I.  Overview of EPA’s Approach to Estimating Handler Exposure

	    The Agency defines individuals involved in pesticide applications
as handlers.   Handler tasks (e.g., aerial application of pesticides)
are routinely evaluated in exposure assessments using dermal and
inhalation variables referred to as unit exposures.   Unit exposures are
normalized values calculated from handler exposure studies described in
the 1986 Pesticide Assessment Guidelines, Subdivision U – Applicator
Exposure Monitoring (currently referred to as Series 875, Group A).   A
unit exposure (mg/lb active ingredient) is calculated by dividing the
pesticide residues (mg) measured using dosimetry, worn by a volunteer
performing a certain handler activity (scenario) by the number of pounds
of pesticide active ingredient (ai) used by that volunteer.  In exposure
assessments, scenario-specific unit exposures are multiplied by
estimates of the amount of ai handled for a given handler scenario
(e.g., number of pounds ai sprayed to wheat per day for an aerial
applicator).  These simple calculations are daily exposure estimates
(mg/day) which can then be adjusted by body weight (kg) and dermal
absorption if necessary.   The resulting metric (mg/kg/day) is then
compared to doses from toxicity studies (mg/kg/day) in Agency risk
assessments.  

	A. The PHED database

The Agency relies on the Pesticide Handlers Exposure Database (PHED) as
a source of generic unit exposure estimates.  PHED was designed by a
task force of representatives from the U.S. EPA, Health Canada, the
California Department of Pesticide Regulation, and member companies of
the American Crop Protection Association.  PHED is a software system
consisting of two parts -- a database of measured exposure values for
workers involved in the handling of pesticides under actual field
conditions and a set of computer algorithms used to segment and
statistically summarize the selected data. Currently, the database
contains values for over 1,700 individual monitoring events (i.e.,
monitoring units).  Once the data for a given exposure scenario have
been selected, the data are typically normalized (i.e., divided) by the
amount of pesticide handled resulting in standard unit exposures. 
Following normalization, the data are statistically summarized.  The
distribution of exposure values for each body part (e.g., chest, upper
arm) is categorized as normal, lognormal, or “other” (i.e., neither
normal nor lognormal).  A central tendency value is then selected from
the distribution of the exposure values for each body part.  These
values are the arithmetic mean for normal distributions, the geometric
mean for lognormal distributions, and the median for all “other”
distributions.  Once selected, the central tendency values for each body
part are summed to define the exposure for the entire body

The data in PHED are based on the use of passive dosimetry methods
(e.g., patches, gloves, wholebody dosimeters or washes) to estimate the
magnitude of, and patterns of exposure resulting from various handling
activities.  Knowledge of exposure patterns by body part is critical for
risk managers making exposure mitigation decisions.  For example, EPA
may require chemical resistant gloves if exposure is primarily to the
hands.   

One of the fundamental limitations of PHED is the data come from
multiple study designs.  PHED contains studies that were conducted from
1977 to 1994.  Prior to the development of the Subdivision U guidelines,
investigators limited the collection of measurements to areas of the
body they believed to have the greatest potential for exposure.  After
the guidelines were established in 1986, measurements representing the
head, neck, chest, back, arms, legs and hands were more routinely
collected.  Consequently in PHED, a unit exposure for a given scenario
has the potential for a different number of observations and
distribution per body part when their central values are summed for a
total body estimate as described above.  For example a unit exposure for
a given scenario could include studies in which only the hands were
measured; plus studies in which only the hands and forearms were
measured, and so on. 

The material and methods of collecting residues from volunteers
participating in handler studies have evolved over time, and these
competing study designs have a confounding effect on PHED outputs.  Like
the studies with differing body part measurements, the studies in the
database for a given scenario could also be based on studies having
differing dosimetry methods (e.g., patches or whole body dosimeters). 
These methods are described in the background document.  One of the
primary concerns regarding competing monitoring methods is the putative
differences in the performance of cotton gloves and hand rinses used to
collect pesticide residues from hands.  A fundamental question is: do
estimates of exposure based on using cotton gloves as dosimeters
overestimate hand measurements?  Conversely; do estimates of exposure
based on hand rinses underestimate hand measurements?   

The Agency has investigated the performance of various techniques for
measuring hand exposure and other biases of passive dosimetry for
underestimating exposure in a number of ways. First, a review of
available peer reviewed literature on the subject of hand rinses was
conducted.  Second, an analysis was performed comparing hand
measurements made with varying techniques based on data available in
PHED.  Third, comparisons were made of estimates of exposure made with
passive dosimetry and a more chemical-specific method - measuring
internal metabolites of pesticides in urine referred to as biological
monitoring. 

B.  Exploring the Relationship of Handler Exposure to Amount of
Pesticide Handled

Since the establishment of the guidelines, the Agency has assumed that
the magnitude of exposure is proportional to the amount of active
ingredient handled (AaiH) and, that scenario and activity are
independent variables.  In a regulatory setting, the assumption of
proportionality is useful because it enables risk managers to mitigate
risk by reducing labeled application rates if mitigation involving
Personal Protective Equipment or engineering controls continue to
indicate risks of concern.

EPA analyzed and examined PHED data for six different handler scenarios
with respect to the relationship between AaiH and exposure.  Improving
our understanding of this phenomenon with the available data in PHED
will help the Agency 1) to determine the need for additional data and 2)
gain insight when evaluating data to populate a new database.  The AHETF
is proposing as part of its future studies to investigate
proportionality as a secondary objective of its study protocols.  They
intend to incorporate more advanced statistical concepts and designs in
their analysis to distinguish between complete proportionality and
complete independence of exposure and AaiH.  An important document to
consider is the AHETF document: Procedures for Determining the Required
Number of Clusters and Monitoring Units per Cluster to Achieve Benchmark
Adequacy.

.  

C.  EPA Exposure Assessments (EA)

EPA currently conducts deterministic risk assessments by relying on
central tendency PHED unit exposures coupled with high-end label use
rates and work hours for each relevant handler scenario /activity.  As
the tools and techniques for performing probabilistic assessments
improve, the limitations of PHED become more apparent.  Chief among them
is the inability to construct individual full body exposure estimates
and develop ranges and distributions of AaiH.

II. Development of an Improved Approach

A.  PHED database limitations

PHED has been a valuable scientific and regulatory tool but has several
limitations.  These include scenarios consisting of values taken from
studies having multiple study designs,  compositing varying numbers of
body parts in a given unit exposure, and the inability to evaluate
inter- and intra- personal variability since varying numbers of
individuals were used in the sample collection process.  PHED has
limited (and in some cases is lacking) studies representing advances in
agricultural equipment, pesticide formulations and application
techniques.    

B.  EPA desire to have more refined Exposure Assessments

The Agency envisions the next generation handler database to be one that
can be used to describe more fully the range of potential handler
exposures and that can produce inputs for use in probabilistic exposure
assessments.  We recognize that improvements in pesticide use
information (i.e., the amount of active ingredient handled) will also
need to be made.  However, until those advances are made, we believe it
is desirable to have scenario specific values that can be used to
develop distributions representing the advances made in pesticide
application equipment and techniques.   

   

C.  Criticisms from stakeholders

Our exposure assessments generate a number of criticisms from important
stakeholders that the Agency would like to address.  Some of the
criticisms include the use of central tendency values, the potential for
certain passive dosimetry techniques to underestimate exposure, and that
the studies are based on activities involving outdated equipment. 
Ideally a new database would consist of handler scenarios that would
have sufficient samples representative of as many monitoring activities
performed by as many different individuals and at as many different
locations as possible.  It is also important that the samples be
collected in as consistent a manner as possible such that confounding by
the use of multiple methods is minimized.  

D.  Human Subject Review Board review

In June 2006, the AHETF submitted five protocols for field trials for an
ethics review by the Human Subjects Review Board (HSRB) pursuant to 40
CFR 26, subpart K.  The protocols described five field trials that were
part of their 2006 data collection efforts.  These trials are part of
multi-year effort to develop data to populate the Agricultural Handlers
Exposure Database (AHED).  In their review, the HSRB identified many
issues relating to dermal exposure collection methods selected by the
AHETF and noted that they did not adequately indicate how their sample
size was derived.  In addition, they asserted that the Agency had not
articulated the need for these data with respect to its current database
PHED. Consequently, the HSRB were unable to evaluate the ethical merits
of the AHETF protocols since key scientific issues were not addressed. 
The report for this meeting of the HSRB can be found at     HYPERLINK
"http://www.epa.gov/osa/hsrb/files/june2006mtgreportfinal100606.pdf" 
http://www.epa.gov/osa/hsrb/files/june2006mtgreportfinal100606.pdf .  
Since the HSRB identified key scientific issues impacting many data
generating efforts such as the AHETF and Antimicrobial Exposure
Assessment Task Force (AEATF), the Agency believes the timing is
appropriate for a scientific review of the methods and data analysis
approaches that are to be used for the next generation of exposure data.

III. Charge questions

1) Data Needs

	EPA believes that many studies within our current database have
limitations.  In some cases, the Agency is lacking data to address
modern pesticide application equipment and techniques.  EPA believes
that additional data could significantly improve our ability to estimate
and better characterize the range of worker exposure with greater
certainty. 

	Please comment on these limitations and EPA’s conclusion that
additional data could improve significantly the Agency’s ability to
assess worker exposure.  Also, please comment on the selection criteria
proposed by the AHETF and AEATF in their respective submissions for
evaluating the extent to which existing data would meet EPA’s exposure
assessment needs.

2) Passive Dosimetry Performance

The common approach for conducting dermal exposure monitoring studies
relies on the use of whole-body dosimetry, handwashing, and facial/neck
wipes.  In some cases, biological monitoring is also used as an
alternative method.  Exposure estimates in Agency risk assessments;
however, typically rely on “to the skin” measurements (i.e.,
potential dose) coupled with dermal absorption data or dermal toxicity
studies in order to calculate risks.  The Agency believes that these
methods are complementary and that they can provide appropriate
estimates for exposure assessment but that the results directly relate
to the reliability of the inputs used.  Please comment on the Agency’s
conclusion regarding passive dosimetry and biological monitoring,
including whether a systematic bias exists in either approach.

Based on the information presented, the Agency has particular concerns
over three specific aspects of how these studies are conducted including
(1) the possible need to correct for the efficiency of the handwashing
technique; (2) compensating for absorption of residues through the skin
during sample collection periods; and (3) the breakthrough of residues
under whole-body dosimeter garments. Please comment on the need to
systematically account for residue losses due to these potential method
biases.  If there is a need, please describe how these corrections
should be accomplished in a way that could reduce uncertainties in the
resulting exposure estimates.

3) Passive Dosimetry vs. Biomonitoring

EPA believes that a comparison of exposure estimates derived from data
collected through biomonitoring with data collected through passive
dosimetry is the most appropriate way to assess the predictive nature of
a passive dosimetry-based approach for estimating worker exposure. 
Please comment on the strengths and limitations of this kind of
comparison for judging the potential utility of passive dosimetry data
in conducting exposure assessments.

EPA has conducted such a comparison using available data and believes
that the comparison shows sufficient concordance of estimates based on
biomonitoring data and passive dosimetry data to support the conclusion
that a passive dosimetry-based approach can generate data that can be
used to develop relatively predictive estimates of worker exposure for a
wide variety of scenarios and activities.  Please comment on the
adequacy of the analysis to support EPA’s conclusion.

	

4) Normalization of Exposure by Amount of Active Ingredient Handled
(AaiH)

The normalization of exposure by AaiH - the unit exposure - has, since
the mid-1980s, been the principle relationship underlying the use of
exposure data in the Agency's pesticide handler exposure assessments. 
It is based on the assumption that the two variables are proportional. 
That is, if one doubles the amount of pesticide they handled or applied,
the resultant exposure will be doubled as well.

The Agency is unsure whether the results of our exploratory work showing
that proportionality between exposure and AaiH is reasonable in some but
not all cases, is a function of limitations of the data within PHED or
whether this relationship is in fact not a reasonable assumption for all
scenarios.  It may be the case that an additional ancillary variable
(e.g., boom length, # of tank mixes, or # de-couplings in a closed
loading system), in addition to or in place of AaiH, may improve the
predictive capabilities of our exposure model.

Though it is recognized that neither the studies in our current database
nor the proposed studies by the AHETF were designed for the primary
purpose of examining proportionality between exposure and AaiH or to
determine the extent to which other parameters influence exposure,
compared with our current database, the Agency believes that the
proposed AHETF studies will generate data that will reinforce the
assumption of proportionality between exposure and AaiH or,
alternatively, inform the applicability of another variable as a more
appropriate predictor of exposure.

 

Based on the themes presented on this topic including its historical
precedent, its application in risk assessment and subsequent risk
management decisions, the Agency’s exploratory work using the six PHED
scenarios in the case study, and the study design and objectives of the
AHETF, please comment on the assumption of proportionality between
exposure and AaiH, as a default.   Also, please provide comments on
whether the proposed AHETF study design is adequate to evaluate
proportionality between exposure and AaiH?  What other parameters should
AHETF study designs measure in order to improve the prediction
capabilities of our exposure model?

5) Within-worker and Between-worker Variability

The proposed AHETF study design does not include true worker replicates
and is not intended to examine the issue of variability within workers. 
The AHETF notes that to appropriately investigate this issue would
require significantly more sampling and resources.  They propose,
however, that their single-day exposure distribution results can be used
to evaluate longer term multiple day exposures by placing reasonable
limits on expected intra-class correlation coefficients (ICC):  they
indicate that, from their own research and review of the literature, the
ICC is likely to be between 0.3 and 0.5 over relatively short periods of
time (e.g., seasonal), and likely to be even lower over longer periods
of time.  

Please comment on the AHETF’s approach to estimating the number of
samples (MU) needed to determine within worker variability and their
conclusion on the importance of measuring such variability in their
proposed studies.  

6) Sample Size: Number of Sites and Subjects per Scenario/Activity

The Agency’s goal is to ensure that monitoring studies rely on sample
sizes that adequately represent the range of exposure of people who
engage in a particular handler scenario and activity.  It is also
recognized that occupational monitoring studies are costly and have many
logistical obstacles.  The Agency is also concerned about limiting the
numbers of participants in these types of studies in accordance with the
ethical requirements described in Subpart K (40CFR26) and the recent
criteria outlined by the Agency’s Human Studies Review Board.  The
Agency’s current guidelines recommend 15 monitoring units for each
scenario.  In addition, the AHETF has provided a rationale for the
number of samples in their study design.

	Please comment on the uncertainties associated with the Agency’s and
AHETF’s recommended number of monitoring units.  In your comments,
please include any recommendations you may have regarding specific
statistical analyses that may assist the Agency in developing better
understanding of these uncertainties and characterizing them in a
complete and transparent manner in Agency assessments based on these
data.

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