Draft

ADVISORY BOARD ON 

RADIATION AND WORKER HEALTH

National Institute for Occupational Safety and Health

COMMENTS ON NIOSH’S “DETERMINATION OF NTS BETATO-PHOTON RATIO AND BETA DOSE FOR 1963–1966, AND 

DETERMINATION OF AN EXTREMITY TO WHOLE-BODY 

RATIO USING QUANTILE REGRESSION AND IMPUTATION 

METHODS” (2017)

Contract No. 211-2014-58081 

SCA-TR-2018-SP002, Revision 0 PC-1 

Prepared by 

Lynn R. Anspaugh, PhD 

Robert B. Barton, III, CHP

SC&A, Inc.

2200 Wilson Boulevard, Suite 300 

Arlington, VA 22201-3324 

Saliant, Inc.

5579 Catholic Church Road 

Jefferson, Maryland 21755 

June 2018 

DISCLAIMER 

This is a working document provided by the Centers for Disease Control and Prevention (CDC) technical 

support contractor, SC&A for use in discussions with the National Institute for Occupational Safety and 

Health (NIOSH) and the Advisory Board on Radiation and Worker Health (ABRWH), including its 

Working Groups or Subcommittees. Documents produced by SC&A, such as memorandum, white paper, 

draft or working documents are not final NIOSH or ABRWH products or positions, unless specifically 

marked as such. This document prepared by SC&A represents its preliminary evaluation on technical 

issues.

NOTICE: This document has been reviewed to identify and redact any information that is protected by 

the Privacy Act 5 U.S.C. § 552a and has been cleared for distribution. 
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SC&A, INC.: Technical Support for the Advisory Board on Radiation and 

Worker Health Review of NIOSH Dose Reconstruction Program

DOCUMENT TITLE: Comments on NIOSH’s “Determination of NTS Beta-to-Photon 

Ratio and Beta Dose for 1963–1966, and Determination of an 

Extremity to Whole-Body Ratio Using Quantile Regression and 

Imputation Methods” (2017)

DOCUMENT NUMBER/

DESCRIPTION:

SCA-TR-2018-SP002

REVISION NO.: 0 PC-1 (Draft)

SUPERSEDES: 0

EFFECTIVE DATE: June 11, 2018

TASK MANAGER Arjun Makhijani, PhD [signature on file]

PROJECT MANAGER: John Stiver, MS, CHP [signature on file]

DOCUMENT 

REVIEWER(S):

John Stiver, MS, CHP [signature on file]

John Mauro, PhD, CHP [signature on file]

Record of Revisions

Revision 

Number

Effective 

Date

Description of Revision

0 (Draft) 4/20/2018 Initial issue

0 PC-1 (Draft) 6/11/2018 Corrects a typographical error in the document title on the 

title page
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TABLE OF CONTENTS

Abbreviations and Acronyms ......................................................................................................... 4

1 Introduction ............................................................................................................................. 5

2 Estimates of the Ratio of Beta-to-Gamma Dose at the Nevada Test Site Before the NIOSH 

(2017) Report .......................................................................................................................... 7

3 The NIOSH (2017) Report ...................................................................................................... 9

3.1 Coworker Dose 1963–1966 .......................................................................................... 10

3.2 Ratio of Beta Dose to Gamma Dose for Skin ............................................................... 11

3.3 Extremity-to-Whole Body Dose ................................................................................... 12

4 Discussion of the Relevant Claimant Populations ................................................................ 12

5 Conclusions ........................................................................................................................... 14

6 References ............................................................................................................................. 15

Attachment A: Overview and Sampling of Relevant Claimant Populations ................................ 19
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ABBREVIATIONS AND ACRONYMS

ABRWH Advisory Board on Radiation and Worker Health 

Ci curie

CL censor level

DTRA Defense Threat Reduction Agency

EEOICPA Energy Employees Occupational Illness Compensation Program Act

EPA U.S. Environmental Protection Agency 

GM geometric mean

GSD geometric standard deviation

H+12 12 hours after detonation of a nuclear device 

MDA minimum detectable activity

MDL minimum detectable level

mrem millirem

NIOSH National Institute for Occupational Safety and Health

NOCTS NIOSH OCAS Claims Tracking System

NRDS Nuclear Rocket Development Station

NTS Nevada Test Site

ORAUT Oak Ridge Associated Universities Team

POC probability of causation

SRDB Site Research Database

Sv sievert

TBD technical basis document
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1 INTRODUCTION

The primary issue behind the National Institute for Occupational Safety and Health’s (NIOSH’s)

2017 report, Determination of NTS Beta-to-Photon Ratio and Beta Dose for 1963–1966, and 

Determination of an Extremity to Whole-Body Ratio Using Quantile Regression and Imputation 

Methods, is quantification of beta dose to workers at the Nevada Test Site (NTS) during the 

period when personal dosimeters did not have the ability to record beta dose, but only gamma 

dose. Specifically, the period of interest in NIOSH (2017) is stated to be 1963–1966, so SC&A

assumes here that NIOSH (2017) is intended to be included as part of the site profile analysis of 

occupational environmental dose (NIOSH 2012a). However, we note that the discussions of beta 

dose concerning workers at NTS are given in the technical basis documents (TBDs) related to 

occupational external dose (NIOSH 2007, 2010, 2012b). Attachment A presents an overview of 

the affected claimant population for 1963–1965.

In general, environmental occupational radiation dose during the 1963–1966 period is being 

reconstructed based on NIOSH’s assumption that all such dose can be related to fallout from the 

Small Boy event that occurred on July 14, 1962 (NIOSH 2012a).

There are two reasons why the ratio of beta-to-gamma dose might change as a function of time 

following the deposition of nuclear explosion fallout on the ground. One is that the mixture of 

radionuclides changes with time following deposition, and the relative emissions of photons and 

betas also change. These changes in radionuclide mix as a function of time have been 

documented in calculations by H.G. Hicks (1981a–1981i, 1982, 1984, 1990). In addition, 

changes in the ratio of beta dose to gamma dose to the skin because of changes in the 

radionuclide mix have been documented in calculations by Barss and Weitz (2006) and by 

NIOSH (2007, 2010, 2012b).

The second and more important reason for a time-dependent change in the ratio of beta-togamma dose is that radionuclides deposited on a soil surface migrate into the soil column (see, 

e.g., the data in McArthur [1991] and in McArthur and Miller [1989]), and the emitted beta 

particles are more strongly absorbed by elements in soil than are the photons. There are no 

known tabulations showing the decrease in beta dose as a function of fallout weathering into soil; 

data for changes in photon exposure rate have been documented in Beck (1980). A commonly 

used assumption (UNSCEAR 1988) is that the relaxation depth of ground-deposited fallout is 

initially 0.1 cm (due to surface roughness), 1 cm at 1 month, and 3 cm at 1 year and thereafter.

The relaxation depth comes from the assumption that fallout activity, A, is exponentially 

distributed with depth, x, in soil, as shown in Equation (1):

A(x) = A(0)exp(−αx), (1)

where the relaxation depth is equal to 1/α.

Four methods could be used to evaluate the beta doses in the 1963–1966 time period. One could 

do this by calculation with the use of the Hicks tables (Hicks 1981a–1981i, 1982, 1984, 1990) 

and an assumed time-varying rate of radionuclide migration into the underlying soil (method 1).

These calculations would be complex and would require the use of sophisticated codes such as 

MCNP (LANL 2017) to follow the interaction of beta particles and photons with elements in 
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soil. This might be the best approach, but it would also be laborious. Calculations would also be 

needed to transform the beta dose recorded by a personal dosimeter to the dose to the skin cells 

at risk and to other possible cells at risk, such as the lens of the eye. Thus, consideration should 

be given to shielding by clothing and the layer of dead skin (usually taken to be 7 mg cm-2).

Two methods would depend upon empirical data in NIOSH (2015), which is a tabulation of 

gamma and beta doses for 1966 through 1986. The tricky part about using such data would be to 

carefully select data that would be known to have exposures to fallout of the same age that would 

be appropriate for the 1963–1965 time period. One possible method would be to select data 

known to be associated with fresh fallout laid down in the 1966–1986 period (method 2). 

Although aboveground testing had officially stopped at NTS with the Little Feller I event on 

July 17, 1962, the Plowshare program had been exempted, and there were also many unplanned 

releases. Table 1 lists unplanned releases during 1966–1970 that were detected off site 

(reproduced from Anspaugh [2008]). The fact that these releases were detected off site 

guaranties that large fallout deposits were on site.

Table 1. Unplanned Releases from Which Radionuclides Were Detected Off Site 

during the 1966 to 1970 Time Period 

Event Date Release, Ci at H+12

Red Hot Mar 5, 1966 1.0×106

Pin Stripe Apr 25, 1966 2.2×105

Double Play Jun 15, 1966 6.0×105

Derringer Sep 12, 1966 1.2×104

Nash Jan 19, 1967 6.9×104

Midi Mist Jun 26, 1967 1.3×103

Umber Jun 29, 1967 2.6×104

Door Mist Aug 31, 1967 4.0×105

Hupmobile Jan 18, 1968 1.2×105

Pod Jan 29, 1969 3.9×103

Scuttle Nov 13, 1969 2.1×102

Snubber Apr 21, 1970 5.5×104

Mint Leaf May 5, 1970 4.0×105

Baneberry Dec 18, 1970 6.7×106

Source: Reproduced from Anspaugh (2008), Table 4, derived from data in 

Hicks (1981i). 

Therefore, method 2 is to follow data from one or more of these large releases to examine the 

ratio of beta-to-gamma doses as a function of time. The activity related to the Baneberry event 

would be a good choice. 

Another possible choice would be to examine data from more than one event, but of different 

ages of fallout deposition, to determine the change in beta-to-gamma dose ratios as a function of 

age of fallout (method 3). 

For methods 2 and 3, it would still be necessary to correct the response of the personal dosimeter 

to dose to the skin (and perhaps other tissues) with consideration of shielding by clothing and the 

dead layer of skin. 
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Given the expected major change in the ratio of beta-to-gamma dose with time, it would not be 

useful to consider a large amount of data with no allowance for the dominating effect on the ratio 

of time since deposition due to weathering into soil.

A fourth method would be to plot the ratio of beta-to-gamma doses calculated from dosimeter 

data with positive beta and gamma doses (NIOSH 2015) on a log-probability plot, and to assume 

that the higher values represent values that could be associated with more recent fallout. Then, 

the assumption could be made that the ratio at the 95th or even higher percentile would be 

appropriate for extrapolation back to the 1963–1965-time period.

Because of the powerful effect of time since fallout deposition and the resultant rapid attenuation 

of beta dose due to weathering of fallout into soil, it would be extremely unfavorable to 

claimants to simply take the ratios of beta-to-gamma dose from the unselected 1966 and later 

time periods and to extrapolate those values backward in time. Nonetheless, in order to 

characterize the magnitude of actual observed beta-gamma empirical ratios, SC&A analyzed the 

individual dosimeter results from a semi-random sample of claimants during the period 1966–

1972. Attachment A discusses the results of this analysis. As opposed to a back-extrapolation 

approach, it would be very claimant favorable to extrapolate values observed over fresh fallout 

and to extrapolate forward in time.

2 ESTIMATES OF THE RATIO OF BETA-TO-GAMMA DOSE AT THE 

NEVADA TEST SITE BEFORE THE NIOSH (2017) REPORT

The NIOSH (2017) report was not the first attempt to estimate the ratio of beta-to-gamma dose 

for persons exposed to fallout from nuclear weapons tests. A major activity was sponsored by the 

Defense Threat Reduction Agency (DTRA) to calculate beta and gamma doses to military 

personnel. The results of these activities have been documented by Barss and Weitz (2006).

Calculations are presented for both the Pacific Proving Ground and NTS. The authors assumed 

that a microscopically thin layer of fallout is deposited upon the surface of an infinite flat plane 

of soil. They did not assume any effect due to surface roughness or weathering of the source into 

soil, so their calculations are claimant favorable. The calculations depended upon the 

radionuclide source terms provided by Hicks (1981a–1981h, 1982, 1984) and a code to calculate 

beta and gamma doses.

The results for NTS in Barss and Weitz (2006) for the ratios of beta-to-gamma dose to the skin at 

100 cm above the plane source start at 10.8 at 0.5 hour, decrease to 8.9 at 2 hours, increase to 

15.9 at 12 hours, decrease to 6.4 at 1 week, and then increase to reach a maximum of 96.1 at 

2 years. Due to the weathering of fallout into the soil surface, it is extremely unlikely that the 

ratios calculated for time periods beyond 1 month would be realized.

NIOSH performed a similar type of calculation, but using somewhat independent tools, in

Revision 01 to the occupational external dose TBD (NIOSH 2007, Attachment C). These 

calculations depended again upon the source terms calculated by Hicks (1981a–1981i, 1982,

1990), which provide estimates of radionuclide deposition density (microcuries per square meter) 

per 1.0 milliroentgen per hour at H+12 (12 hours after detonation). These deposition densities for 

each radionuclide were converted to estimates of beta and gamma dose by use of dose 

coefficients (sievert [Sv] per second per becquerel per square meter) calculated by Eckerman 
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(2006). The essential data from Eckerman apparently exist only in the form of an e-mail from 

Eckerman to R.V. Griffith of the Oak Ridge Associated Universities Team (ORAUT). 

Calculation of combined beta and gamma doses above an infinite plane are tabulated in the U.S. 

Environmental Protection Agency’s (EPA’s) Federal Guidance Report No. 12 (EPA 1993). The 

only document where the doses are broken out separately by beta and gamma is Eckerman 

(2006). 

The results obtained by NIOSH in the first revision to the NTS TBD for occupational external 

dose (NIOSH 2007) are quite similar to those obtained by Barss and Weitz (2006). NIOSH

provided the results of an extensive series of calculations for individual events that occurred 

during Operation Ranger in 1951, Operation Buster-Jangle in 1951, Operation Tumbler-Snapper 

in 1952, Operation Upshot-Knothole in 1953, and the Sedan shot in 1962 (NIOSH 2007, 

page 108). Values are given for discrete time periods of 0, 1, 2, and 12 hours; 1, 10, 50, and 

200 days; and 1, 2, 5, 10, 20, and 50 years post shot. The value for the first year for the 31 events 

considered varies from 18.9 to 32.9. As usual, these values are biased on the high side due to the 

lack of consideration of deposited radionuclides weathering into soil. 

Table 2 summarizes NIOSH’s results. Again, the results calculated for later times are not 

realistic because the weathering of fallout in soil is not considered. The main point of the 

calculations by Barss and Weitz (2006) and NIOSH (2007, Attachment C) is that beta dose to the 

skin at early times following an event can be an order of magnitude larger than the gamma dose. 

NIOSH published the second revision to the NTS TBD for occupational external dose in 2010. 

This second revision contained basically the same information as prepared by NIOSH 

previously, as summarized in Table 2. 

Table 2. Beta-Photon Ratios for Exposure from Surface Contamination 

Elapsed time following 

the production event

Beta/photon 

(Sv/Sv)

0 to 50 d 10

50 to 365 d 25

1 to 5 yr 60

>5 yr 25

Source: Reproduced from NIOSH (2010), page 51. 

However, there was additional material in the body of the report (NIOSH 2010, page 51): 

No routine beta monitoring data exists for NTS prior to 1966. For the time period 

from 1966 to 1987, 368 data pairs were identified from 84 claim files with 

positive beta and gamma results (i.e., results higher than the applicable MDA). 

Based on these data, a lognormal distribution was calculated with a 50th 

percentile beta to gamma ratio of 1.04, a 95th percentile of 4.59, a geometric 

standard deviation (GSD) of 2.41, and a mode value between 0.5 and 1. Thus the 

use of the 50th percentile value on an annual basis is assumed to be reasonable, 

yet favorable to claimants. 42 CFR Part 82 allows claims to be completed using 

efficiency methods when precise estimates cannot realistically be developed due 

to all the variables that modify the potential for exposure to beta radiation. 
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The recommendation was made to use this value for dose reconstruction for pre-1966 unless 

more specific data were available. The obvious problem with this approach is that no allowance 

was made for the fact that the dosimeter measurements were in general made many years after 

aboveground testing had ended in July 1962, and the beta doses recorded by the dosimeters 

would have been severely attenuated by movement of the fallout into the soil column.

The third revision to the NTS TBD for occupational external dose (NIOSH 2012b) contained 

much the same information. A ratio of 1.04 was again recommended, but the comment was made 

that, “If a more precise estimate is required, the values in Attachment C can be adjusted and 

used” (page 52). Attachment C contains the detailed calculations made by NIOSH (2007, 

Attachment C), which were discussed above. 

At a meeting of the NTS Work Group of the Advisory Board on Radiation and Worker Health 

(ABRWH) on January 5, 2017 (ABRWH 2017), the issue of beta doses to the skin was discussed 

extensively. A request had been made to NIOSH to provide the basis for the beta-to-gamma dose 

ratio of 1.04. The representative from NIOSH stated that: 

We had searched through several original files to derive a beta/gamma ratio of 

1.04 to 1 originally and that original file could not be located. NTS data from 

1966 to 1986 was reanalyzed using current EEOICPA data files and a value 

geometric mean of 1.16 with a GSD of 2.15 and a 95th percentile value of 4.09 

was derived from the data. [page 139]

The implication at that time was that NIOSH would use the ratio of 1.16 for their calculations of 

beta dose to the skin. Again, however, there is the same obvious problem that no allowance has 

been made for the fact that the measurements were made many years after the deposit of fallout, 

and that the later beta doses recorded by the dosimeters would have been severely attenuated by 

the movement of the fallout into the soil column. 

3 THE NIOSH (2017) REPORT

The introduction to the NIOSH (2017) report states that, “An updated method has been used to 

develop beta dose to Nevada Test Site (NTS) workers for 1963–1965 when no measurements of 

such dose are available” (page 2). This NIOSH report considers two topics in sequence: 

1. “Beta-Photon and Extremity-Whole Body Dose Relationships” 

2. “Coworker Dose 1963–1966” 

Although NIOSH first discusses the derivation of the relationship of beta dose to gamma dose, 

the analysis shown in Figure 1 of the report may have been done after they had dealt with 

coworker dose using a method similar to that shown in Figure 3 and Table 1 of the report. 

NIOSH states (page 2): “This method estimates or ‘imputes’ dose values when such values are 

censored (less than the limit of detection). A fit to the data is then developed using the quantile 

regression method and is shown in Figure 1.” This Figure 1 contains several vertical columns 

where it appears that beta doses vary over three orders of magnitude while the gamma dose is 

constant. This may be due to the various levels of imputed gamma dose. 
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3.1 COWORKER DOSE 1963–1966 

A problem with applying the concept of a beta-to-gamma dose ratio is that the process only 

works if there is a non-zero value of gamma dose. NIOSH (2017) explains a procedure for 

imputing a gamma dose based on an assumed distribution of the gamma doses in 1963–1966 and 

use of the non-zero values. NIOSH’s Figure 3 demonstrates the individual results of the

imputation process for all of the claimant gamma-dose data for 1963–1966. The figure includes 

the following information (page 5): 

GM = 3.22 

GSD = 6.35 

N Total = 40972 

N Censored = 37804 

CL = 30 

“GM” and “GSD” are assumed to represent the geometric mean and the geometric standard 

deviation of the fitted lognormal distribution. Although no units are given for the GM, the units 

must be in millirem (mrem). The distribution was fit to a highly censored distribution of 

40,972 – 37,804 = 3,168 measurements that were left above the censor level (CL) of 30 [mrem].

Thus, the fit started at 37,804 / 40,972 = 0.92, or the 92nd percentile level. According to the 

abscissa of NIOSH’s Figure 3, this would correspond to a “Standard Normal Quantile” of 1.40 

(Pagano and Gauvreau 2000, Table A.3, page A-11).

NIOSH then uses the data for individual years to derive GMs and GSDs for each year, as shown 

in NIOSH’s Table 1. A combination of the values above for the combined data for 1963–1966 

and the values for each year are shown in Table 3.

Table 3. Summary of the Fits Reported by NIOSH (2017) 

Year

Geometric 

mean 

(mrem)

Geometric 

standard 

deviation

50th % 

photon 

(rem)

95th % 

photon 

(rem)

1963–1966 3.22 6.35 0.00322 0.0674 a

1963 37.293 4.945 0.037 0.517

1964 44.172 3.7553 0.044 0.389

1965 50.662 4.7829 0.051 0.665

1966 55.299 4.3002 0.055 0.609 a

 Calculated for this report by SC&A. 

A major surprise from the now combined data reported in Table 3 is that the fit for all years 

produces a value that is more than an order of magnitude less than the values for each of the 

years from 1963 to 1965. This strongly suggests that the values are not fit well by a lognormal 

distribution. It is unfortunate that NIOSH did not display the graphs, such as in their Figure 3, for 

the individual years. The very high values of GSD also suggest a poor fit to all sets of data.

Further, it is most peculiar that the GMs calculated by NIOSH for the individual years are above 

the censor level of 30 mrem. It is also obvious that the display of five significant digits is not 

defensible.
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The bottom line for this method of computing coworker dose is that it is questionable and must 

be investigated further. It would be helpful if NIOSH would make this complete data file 

available for examination by SC&A.

3.2 RATIO OF BETA DOSE TO GAMMA DOSE FOR SKIN

The NIOSH (2017) report did not use any of the four possible methods recommended and 

discussed above. Rather, the report is based on all data on beta-to-gamma ratios available for the 

1966–1972 time period and apparently includes “imputed” doses. The number of data points is 

not specified. No consideration is given by NIOSH for the extremely important time dependence 

of the beta-to-gamma ratios due to fallout weathering into soil. As would be expected with the 

neglect of the most important variable, NIOSH’s Figure 1, which is a plot of beta dose versus 

gamma dose, shows a huge amount of scatter—about six orders of magnitude for beta dose and 

about three orders of magnitude for gamma dose. 

There are several features of NIOSH’s Figure 1 that are not understandable. First, individual data 

points are represented by small circles that are of two colors—black and yellow. There is no 

explanation of the meaning of the two colors. Second, the fit lines are said to be the result of a 

quantile regression analysis. The meaning of a quantile regression analysis is not explained, nor 

is a scientific reference provided. 

NIOSH does offer the explanation that the analysis followed the method used in Neutron/Photon 

Ratios at Portsmouth (LaBone 2016). This paper is very sketchy, and about half of the sevenpage document is taken up by the reproduction of computer code, which is not explained or even 

identified. We infer from other sources, including Chen (2005), that the code is written in the 

SAS language. 

The two linear fit lines shown in NIOSH’s Figure 1 are for the 50th and 95th percentiles. It can 

be inferred from LaBone (2016) that the yellow data points shown in Figure 1 are the data for the 

50th percentile fit, and the black data points were used for the 95th percentile fit. Examination of 

Figure 1 indicates that a curvilinear fit would have been a better treatment, especially for the 

lower values of beta dose. 

The consistently lower values of beta dose at lower values of gamma dose are consistent with 

beta dose declining more rapidly than gamma dose, due to the stronger attenuation of beta dose 

due to fallout weathering into soil with time following deposition. The data shown in NIOSH’s

Figure 1 also display an unusual feature in that there are nine vertical columns indicating that for 

a single value of gamma dose, the beta doses vary over about three orders of magnitude. This 

may be partially due to the questionable “imputation” process used by NIOSH. 

NIOSH states that separate analyses were done for each individual year for 1966–1972, and the 

results were similar for the combined data. It is unfortunate that the data for individual years 

were not shown. The results of NIOSH’s analysis for the combined 1966–1972 years are as 

follows (page 2): 

50th percentile: Y = 4.84 + 0.1893X 

95th percentile: Y = 41.429 + 1.8929X 
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where X is photon dose in mrem, and Y is presumed to be beta dose in mrem. These results are 

rather peculiar in the sense that a beta dose-to-gamma dose ratio was the required entity, but the 

results are shown as a linear dependence with an intercept. Again, the lack of consideration of 

the most important variable probably accounts for the peculiar results. Also, the provision of up 

to five significant digits is not scientifically valid given the enormous spread in the data. 

Another major reason to question the validity of these results for application to earlier times is 

the nature of the resulting fits. For example, if a gamma dose of 1,000 mrem is taken as an 

example, then the 50th percentile beta dose is calculated to be (4.84 + 189.3) mrem = 194 mrem, 

and the resulting ratio of beta dose-to-gamma dose would be 0.194. Based upon all the data and 

calculations before us, this would be an inappropriate value to be applied to the 1963–1965 time 

period. 

None of the four preferred methods discussed in the Introduction to this paper have been 

employed, and the results are seriously impacted by the lack of consideration of the weathering 

of fallout into the soil surface. The fourth possible alternative method would be to plot the results 

of beta-to-gamma dose ratios on a log-probability plot, similar to that shown in NIOSH’s

Figure 3. Then a claimant-favorable ratio could be deduced from the plot (or fit to the plot) at 

whatever percentile might be chosen, perhaps 95th. This would be simple and far more 

defensible than the procedure used by NIOSH (2017). 

3.3 EXTREMITY-TO-WHOLE BODY DOSE

It is not clear what is meant by “extremity dose.” It is possible that high beta doses to fingers 

might have occurred due to handling of materials, and that so-called finger dosimeters might 

have been used. It should be clarified exactly what is meant by an extremity dose. 

Again, there is a very large spread in the data shown in NIOSH’s Figure 2. The fitted curves 

shown in Figure 2 are curvilinear, whereas the derived equations are given as linear (page 3): 

50th percentile: Y = 450.137 + 0.3901X 

95th percentile: Y = 1493.402 + 2.8247X 

where X is gamma dose in mrem and Y is beta dose in mrem. In this case, a very low gamma 

dose could still provide a large beta dose, which might have occurred due to unique occupational 

exposures. 

Rather than use this similarly complicated analysis given by NIOSH, it would be preferable to 

simply assume a lognormal distribution and plot the ratios on a log-probability scale to derive a 

95th percentile value as a claimant-favorable value. 

4 DISCUSSION OF THE RELEVANT CLAIMANT POPULATIONS

As part of its review, SC&A examined the two relevant claimant populations for the proposed 

beta-to-gamma approach. The first claimant population represents those energy employees 

employed from the 1963–1965 period who require application of the calculated beta-to-gamma 

formulas in NIOSH (2017); this population is referred to as “the affected claimant population.” 
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The second claimant population represents those monitored claims from the 1966–1972 period 

that form the basis of the imputation method used in arriving at the beta-to-gamma formulas (this 

population is referred to as “the analyzed claimant population”). While the result of the claimant 

analysis is summarized here, the full analysis can be found in Attachment A. 

Analysis of the affected population is useful in that it answers the question: “Who does this 

method really affect and what is the potential magnitude of assigned doses as a result of the 

proposed method?” Based on its analysis of the available entries in the NIOSH OCAS Claims 

Tracking System (NOCTS), SC&A determined that there were 252 claimants with covered 

employment during the period from 1963 through 1965, had a probability of causation less than 

50%, and developed an illness requiring reconstruction of nonpenetrating radiation (i.e., beta 

dose). Although this only represents about 20% of the NTS claimant population during this time, 

it still is a relatively large number of claims affected by the beta-to-gamma methodology 

presented in NIOSH (2017). 

Observed job types varied significantly and contained a large percentage of jobs (~80%) that 

could be considered “radiological workers” (e.g., drillers, miners, various construction trades, 

test engineers, etc.). Approximately 95% of the affected worker population was monitored 

externally during the period of interest, with roughly 15% of that monitored population accruing 

positive measured gamma doses. Observed maximum gamma doses ranged from 600 to 

1,600 mrem; however, average annual doses were much less (25–63 mrem). As expected, the job 

categories of “engineer/scientist” and “driller/miner” had the highest percentage of positive 

measured doses among the affected population. 

For the analyzed claimant population, SC&A determined that there were 1,593 claimants with 

covered employment during the period from 1966 through 1972. SC&A semi-randomly1 selected 

100 claims from this population for analysis. The number of monitored workers among these 

100 claims ranged from 92.6% in 1971 to 99% in 1966. For the first 3 years during the period of 

interest, 26% to 29% of the monitored claims had positive measured doses (gamma, beta, or 

both). For the remaining years, the percentage of monitored claims with positive results ranged 

from 5.3% to 16.2%. However, the observed average empirical beta-to-gamma ratios on 

individual dosimetry cycles were higher in 1971 and 1972 (1.22 and 1.18, respectively) than in 

1966 and 1967 (0.79 and 0.70, respectively). The maximum observed beta-to-gamma ratio was 

10.21 in 1967. It is important to note that the rank ordering of the observed beta-to-gamma ratios 

shows that 26% of the data is less than 0.2, and 90% of the data is less than 2.00. These observed 

ratios can be compared with NIOSH (2017) beta-to-gamma ratios of 0.1893 and 1.893 at the 

50th and 95th percentile, respectively. 

1 As discussed in Attachment A, the claims were selected randomly for analysis. However, 11 originally selected 

claims were rejected from the analysis for having job types that were unlikely to have ever entered a radiological 

area at NTS.

An analysis of the issue location associated with each of the positive dosimeter cycles showed 

that average beta-to-gamma ratios were above 1.00 for Area 23 (2.55), Area 16 (1.14), and U-162

(2.10). The remaining 19 observed locations had average beta-to-gamma ratios less than 1.00.

The maximum observed beta-to-gamma ratio of 10.21 was for an unspecified issue location. 

 

2 Assumed to represent an underground issue location.
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There was no observed correlation between areas designated as “underground” and higher betato-gamma ratios as might be expected.

A plot of the 110 values examined that had positive results for both beta and gamma doses is 

shown in Figure 1, which is a modified version of Figure A2 in Attachment A. The data are well 

fit by a lognormal function with a GM of 1.21 and a GSD of exp(0.812) = 2.25. The 99th

percentile of this distribution is equal to 8.0, which is reasonably close to the suggested value of 

beta-to-gamma dose of 10 computed by NIOSH (2007, Attachment C, and reproduced as Table 2 

of this report).

Figure 1. Lognormal Fit Beta-to-Gamma Ratios Observed for 110 Positive Dosimeter 

Measurements Identified

0.1

1

10

100

.01 .1 1 5 10 20 30 50 70 80 90 95 99 99.9 99.99

y = 1.21 * e^(0.812norm(x)) R2= 0.972 

Ratio of beta-to-gamma dose

Cumulative percentage

5 CONCLUSIONS

SC&A’s review of NIOSH (2017) concludes the following:

1. NIOSH’s (2017) analysis of beta-to-gamma dose ratios has not considered the most 

important factor that causes the ratio to change with time: the weathering of fallout into 

soil with the subsequent stronger decrease in beta dose as compared to gamma dose.
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2. Four alternate methods of deriving claimant-favorable values of beta-to-gamma dose 

ratios have been described by SC&A in this report (see Section 1 and Section 3.2) that 

should be discussed with NIOSH and the Work Group. 

3. There may be serious errors in the evaluation of coworker dose for the years 1963–1966 

(see Section 3.1). 

4. SC&A described an alternate method of deriving claimant-favorable values of extremity 

dose-to-whole body dose ratios that should be discussed with NIOSH and the Work 

Group (see Section 3.3). 

5. The dosimetry files used by NIOSH have not been specified, and the files have not been 

made available to SC&A as of the issuance of this report. It would be helpful for any 

potential future discussions to have those calculation files made available.

6. SC&A notes that beta doses for the years 1951–1962 can be calculated by using the data 

in NIOSH (2012b), Attachment C, as an alternative to methods developed by DTRA for 

military personnel. 

6 REFERENCES

ABRWH 2017. Transcript: Meeting of the Advisory Board on Radiation and Worker Health, 

Nevada Test Site Work Group, Hebron, KY. January 5, 2017. 

Anspaugh 2008. L.R. Anspaugh, Comments on ORAUT-TKBS-0008-4, “Nevada Test Site–

Occupational Environmental Dose,” prepared for SC&A, Inc., Vienna, VA. October 21, 2008. 

Barss and Weitz 2006. N.M. Barss and R.L. Weitz, “Reconstruction of External Dose from Beta 

Radiation Sources of Nuclear Weapon Origin,” Health Physics, Vol. 91 (2006), pp. 379–389. 

[SRDB Ref. ID 26776] 

Beck 1980. H.L. Beck, Exposure Rate Conversion Factors for Radionuclides Deposited on the 

Ground, EML-378, Environmental Measurements Laboratory, U.S. Department of Energy, New 

York, NY. July 1980. [SRDB Ref. ID 35519] 

Chen 2005. C. Chen, “An Introduction to Quantile Regression and the QUANTREG Procedure,” 

Paper 213-30, Proceedings of the SAS Users Group International Conference, Philadelphia, PA, 

April 10–13, 2005. Available at http://www2.sas.com/proceedings/sugi30/213-30.pdf 

Eckerman 2006. Email from K.F. Eckerman, Oak Ridge National Laboratory, to R.V. Griffith, 

Oak Ridge Associated Universities Team, Subject: Re: Beta-Photon Dose-Rate Conversion 

Factors. August 3, 2006. [SRDB Ref. ID 40281] 

EPA 1993. Federal Guidance Report No. 12: External Exposure to Radionuclides in Air, Water, 

and Soil, EPA 402-R-93-081, U.S. Environmental Protection Agency, Washington, DC. 

September 1993. Available at https://www.epa.gov/sites/production/files/2015-

05/documents/402-r-93-081.pdf 
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Hicks 1981a. H.G. Hicks, Results of Calculations of External Gamma Radiation Exposure Rates 

from Fallout and the Related Radionuclide Compositions, Operation Ranger, 1951, UCRL53152 Pt. 1, Lawrence Livermore National Laboratory, Livermore, CA. July 1981. [SRDB Ref.

ID 1854]

Hicks 1981b. H.G. Hicks, Results of Calculations of External Gamma Radiation Exposure Rates 

from Fallout and the Related Radionuclide Compositions, Operation Buster-Jangle, 1951, 

UCRL-53152, Pt. 2, Lawrence Livermore National Laboratory, Livermore, CA. July 1981. 

[SRDB Ref. ID 1831]

Hicks 1981c. H.G. Hicks, Results of Calculations of External Gamma Radiation Exposure Rates 

from Fallout and the Related Radionuclide Compositions, Operation Tumbler-Snapper, 1952, 

UCRL-53152, Pt. 3, Lawrence Livermore National Laboratory, Livermore, CA. July 1981. 

[SRDB Ref. ID 1832]

Hicks 1981d. H.G. Hicks, Results of Calculations of External Gamma Radiation Exposure Rates 

from Fallout and the Related Radionuclide Compositions, Operation Upshot-Knothole, 1953, 

UCRL-53152, Pt. 4, Lawrence Livermore National Laboratory, Livermore, CA. July 1981. 

[SRDB Ref. ID 1835]

Hicks 1981e. H.G. Hicks, Results of Calculations of External Gamma Radiation Exposure Rates 

from Fallout and the Related Radionuclide Compositions, Operation Teapot, 1955, UCRL53152, Pt. 5, Lawrence Livermore National Laboratory, Livermore, CA. July 1981. [SRDB Ref.

ID 1838]

Hicks 1981f. H.G. Hicks, Results of Calculations of External Gamma Radiation Exposure Rates 

from Fallout and the Related Radionuclide Compositions, Operation Plumbob, 1957, UCRL53152, Pt. 6, Lawrence Livermore National Laboratory, Livermore, CA. July 1981. [SRDB Ref.

ID 1839]

Hicks 1981g. H.G. Hicks, Results of Calculations of External Gamma Radiation Exposure Rates 

from Fallout and the Related Radionuclide Compositions, Operation Hardtack II, 1958, UCRL53152, Pt. 7, Lawrence Livermore National Laboratory, Livermore, CA. July 1981. [SRDB Ref.

ID 1846]

Hicks 1981h. H.G. Hicks, Results of Calculations of External Gamma Radiation Exposure Rates 

from Fallout and the Related Radionuclide Compositions. Operations Nougat through Bowline, 

1962–1968, UCRL-53152, Pt. 8, Lawrence Livermore National Laboratory, Livermore, CA. 

July 1981. [SRDB Ref. ID 1851] 

Hicks 1981i. H.G. Hicks, Calculated Concentrations of any Radionuclide Deposited on the 

Ground by Release from Underground Nuclear Detonations, Tests of Nuclear Rockets, and Tests 

of Nuclear Ramjet Engines, UCRL-53228, Lawrence Livermore National Laboratory, 

Livermore, CA. November 1981. [SRDB Ref. ID 1828] 

Hicks 1982. H.G. Hicks, “Calculation of the Concentration of Any Radionuclide Deposited on 

the Ground by Offsite Fallout from a Nuclear Detonation,” Health Physics, Vol. 42 (1982), 

pp. 585–600. 
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Hicks 1984. H.G. Hicks, Results of Calculations of External Gamma Radiation Exposure Rates 

from Local Fallout and the Related Radionuclide Compositions of Selected U.S. Pacific Events, 

UCRL-53505, Lawrence Livermore National Laboratory, Livermore, CA. February 1984. 

[SRDB Ref. ID 1856] 

Hicks 1990. H.G. Hicks, “Additional Calculations of Radionuclide Production following Nuclear 

Explosions and Pu Isotopic Radios for Nevada Test Site Events,” Health Physics, Vol. 59 

(1990), pp. 515–523. 

LaBone 2016. T. LaBone, Neutron/Photon Ratios at Portsmouth. May 26, 2016. [SRDB Ref. 

ID 165497] 

LANL 2017. A General Monte Carlo N-Particle (MCNP) Transport Code, Los Alamos National 

Laboratory, Los Alamos, NM. November 21, 2017. Available at 

https://laws.lanl.gov/vhosts/mcnp.lanl.gov/index.shtml

McArthur 1991. R.D. McArthur, Radionuclides in Surface Soil at the Nevada Test Site, 

DOE/NV/10845-02, Desert Research Institute, University of Nevada System, Las Vegas, NV. 

August 1991. [SRDB Ref. ID 7872] 

McArthur and Miller 1989. R.D. McArthur and F.L. Miller, Jr., Off-Site Radiation Exposure 

Review Project. Phase II Soils Program, DOE/NV/10384–23 Rev., Desert Research Institute, 

University of Nevada System, Las Vegas, NV. December 1989. 

NIOSH 2007. Nevada Test Site – Occupational External Dose, ORAUT-TKBS-0008-6, 

Revision 01, National Institute for Occupational Safety and Health, Cincinnati, OH. July 30, 

2007. 

NIOSH 2010. Nevada Test Site – Occupational External Dose, ORAUT-TKBS-0008-6, 

Revision 02, National Institute for Occupational Safety and Health, Cincinnati, OH. April 15, 

2010. 

NIOSH 2012a. Nevada Test Site – Occupational Environmental Dose, ORAUT-TKBS-0008-4, 

Revision 03, National Institute for Occupational Safety and Health, Cincinnati, OH. August 24, 

2012. 

NIOSH 2012b. Nevada Test Site – Occupational External Dose, ORAUT-TKBS-0008-6, 

Revision 03, National Institute for Occupational Safety and Health, Cincinnati, OH. 

November 9, 2012. 

NIOSH 2015. Microsoft Excel® file, “Privacy Act Protected—NTS Beta Gamma Ratio rev 

2_1966 through 1986_for DCAS – FINAL 4-21-15.xlsx,” National Institute for Occupational 

Safety and Health, Cincinnati, OH. April 21, 2015. 

NIOSH 2017. Determination of NTS Beta-to-Photon Ratio and Beta Dose for 1963–1966, and 

Determination of an Extremity to Whole-Body Ratio Using Quantile Regression and Imputation 

Methods, National Institute for Occupational Safety and Health, Cincinnati, OH. November 14, 

2017. 
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Pagano and Gauvreau 2000. M. Pagano and K. Gauvreau, Principles of Biostatistics, 2nd

Edition, Duxbury, Pacific Grove, CA. 2000.

UNSCEAR 1988. United Nations Scientific Committee on the Effects of Atomic Radiation, 

“Exposures from the Chernobyl Accident,” Appendix D, in Sources, Effects and Risks of 

Ionizing Radiation. United Nations Scientific Committee on the Effects of Atomic Radiation 1988 

Report to the General Assembly, with Annexes, Volume II, United Nations, New York, NY.

1988.
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ATTACHMENT A: OVERVIEW AND SAMPLING OF RELEVANT 

CLAIMANT POPULATIONS

OVERVIEW OF AFFECTED CLAIMANT POPULATION (1963–1965) 

This attachment provides an overview of the NTS claimant population that would be affected by 

the proposed beta-to-gamma dose reconstruction methodology presented in NIOSH (2017). The 

purpose of this analysis is to answer the question: “Who does this method really affect and what 

is the potential magnitude of assigned doses as a result of the proposed method?” The affected 

claimant population, as defined in this section, consists of energy employees who have the 

following three characteristics:

• Covered employment at NTS during the 1963–1965 time period 

• Covered illness that requires dose reconstruction from nonpenetrating radiation (the 

majority consisting of various skin cancers)

• Previous dose reconstruction resulting in a probability of causation (POC) below 50% (or 

alternately, no dose reconstruction has yet been performed) 

Overall, there are 1,292 NTS claimants who were employed during 1963, 1964, and/or 1965 at 

NTS. Among this group of claimants, 474 (~37%) were diagnosed with a covered illness that 

required reconstruction of nonpenetrating external dose. Of these 474 claims, 252 did not have a 

dose reconstruction that resulted in a POC above 50%. These 252 claims are considered the 

affected claimant population for this analysis. 

There were 178 different job titles observed among the affected population; however, many were 

simply variants on the same general job category (e.g., metal worker, sheet metal worker, 

ironworker, etc.). Therefore, SC&A used professional judgment and categorized the 178 job 

titles into nine general categories, as shown in Table A1 and Figure A1. As seen in this table and 

figure, the “administrative” category made up the largest portion of the affected claimant 

population (~20%), which may be a reflection of the lower exposure potential expected for 

workers with POCs less than 50%. However, the category “drillers/miners” and 

“engineers/scientists” also made up a significant portion of the affected claimant population. 

This category of workers would likely experience the highest exposure potential because they 

would be directly involved in drill-back and reentry activities post shot. The remaining job 

categories would also likely enter radiological areas on at least a part-time basis and, thus, the 

development of a claimant-favorable method for assigning beta dose would likely have a direct 

effect on approximately 80% of the affected claimant population. 

SC&A also analyzed the dosimetry records for the 252 claimants in the affected population to 

determine the relative magnitude of annual gamma doses from 1963–1965 (see Table A2). As 

seen in the table, the percentage of monitored workers and those with positive recorded photon 

dose is remarkably consistent for each of the three years of interest. For the former category, 

generally 95% of the affected population was monitored, and roughly 15% of those monitored 

workers accrued positive gamma exposures. This indicates that while a large portion of the 
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affected population was monitored externally, only a small portion of that workforce was 

exposed to measurable levels of external photon dose. 

Table A1. Categorization of the Affected Population by Job Title

SC&A job title Total 

claims

Percent 

of total

Administrative 50 19.8%

Drillers/Miners 38 15.1%

Engineer/Scientists 38 15.1%

Electricians/Wiremen 37 14.7%

Equipment Operator/Repairman 28 11.1%

Other Construction 21 8.3%

Security/Firemen 19 7.5%

Ironworkers/Machinists 14 5.6%

Health Physicists 7 2.8%

Total 252 100%

Figure A1. Job Categorization for 252 Claimants in the Affected Population 

Recorded gamma doses were generally low on average (<100 mrem), with rank-order 95th

percentile doses ranging from 157 mrem to 412.5 mrem annually. The maximum observed 

annual dose was 1,600 mrem (1.6 rem) for a heavy-duty truck driver in 1965. The breakdown by 

job category of those workers who accrued positive gamma dose during the period from 1963 

through 1965 is shown in Table A3. Not surprisingly, the categories of “drillers/miners” and 

“engineers/scientists” made up the largest portions of affected claims with positive gamma 
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measurements. However, somewhat surprising is the number of “administrative” workers who 

accrued positive gamma dose during the period of interest. 

Table A2. Overview of Dosimetry Records among the Affected Claimant Population 

Category 1963 1964 1965

# claims in year 149 174 205

# of monitored workers 

(% of total) 142 (95.3%) 165 (94.8%) 200(97.6%)

# with positive gamma dose 

(% of monitored total) 22 (15.5%) 25 (15.2%) 31 (15.5%) 

Average gamma dose (mrem) 29.3 24.7 62.8

Ranked 95th percentile (mrem) 211 157 412

Maximum photon dose (mrem) 1,105 610 1,600

Table A3. Breakdown by Job Title for Affected Claimants with Positive Accrued Dose 

(1963–1965) 

SC&A job title

Total claim 

years with 

positive dose 

(1963–1965)

Percent 

of total

Engineers/Scientists 19 24.4%

Drillers/Miners 16 20.5%

Electricians/Wiremen 12 15.4%

Administrative 9 11.5%

Equipment Operator/Repairman 9 11.5%

Health Physicists 7 9.0%

Ironworkers/Machinists 3 3.8%

Security/Firemen 3 3.8%

Total 78 100%

In summary, the affected claimant population is relatively large (over 250 claimants). A 

significant portion of that population (95% or more) was monitored externally for gamma dose; 

however, only a small portion (~15 percent) accrued any measurable dose. The affected claimant 

population contained many workers who would be considered “radiological workers,” such as 

miners, drillers, engineers, and various construction trades. However, even those workers 

classified as “administrative” sometimes accrued positive doses (9 of 50, or approximately 18%, 

accrued positive dose during the period of interest). Accrued gamma doses were low on average 

and are approximately equivalent to the limit of detection for one or two badging cycles. 

However, 95th percentile doses could be several hundred millirem, with maximum annual doses 

above 1 rem.
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SAMPLING OF ANALYZED CLAIMANT POPULATION USED IN BETA-TO-GAMMA RATIO 

DEVELOPMENT (1966–1972) 

Unlike the previous section, where the affected claimant population is discussed, this section 

analyzes a sample of the claimant population from 1966 through 1972, which NIOSH (2017) 

uses to impute the gamma-dose values used to formulate the proposed beta-to-gamma

methodology (this claimant population is referred to as the “analyzed claimant population”). 

From available NOCTS data, SC&A determined there were 1,582 claimants who had covered 

employment during the period of interest. From this population, SC&A semi-randomly3 selected 

100 claimants for sampling analysis, with a bias toward claims for 1966 (the first year in which 

beta dose was measured by the dosimetry system at NTS). 

3 Eleven of the original random sample were rejected as not being germane to the study due to job types associated 

with cafeteria work (5), general administration (5), or because they were not actually at NTS during the period of 

interest (1).

Table A4 presents an overview of the badging practices among the sampled claims. As seen in 

the table, the number of externally monitored claimants among those reviewed ranged from 93% 

to 99%, which generally comports with the observed monitoring percentage for the affected 

population (see Table A2). In general, the average number of dosimeters per claim in a year was 

between 9 and 10, which suggests that most of the sampled population was on a monthly 

exchange schedule. The number of sampled claims with positive recorded dose (beta, gamma, or 

both) ranged from approximately 5% to nearly 30%. The highest proportion of positive recorded 

doses occurred in the first 3 years during the analyzed period of interest (1966–1968). 

Table A4. Overview of the Sampled Claimant Population

Year

# sampled 

claimants 

employed in 

year 

# monitored 

claimants

(% of total)

Total 

badges in 

year 

Average # 

dosimeters 

per claimant 

per year

# sampled claims 

with positive 

result in year 

(% of monitored 

total)

1966 100 99 (99.0%) 1,041 10.4 26 (26.3%)

1967 95 91 (95.8%) 966 10.2 26 (28.6%)

1968 89 83 (93.3%) 935 10.5 23 (27.7%)

1969 81 76 (93.8%) 749 9.1 4 (5.3%)

1970 72 68 (94.4%) 659 9.0 11 (16.2%)

1971 68 63 (92.6%) 689 10.1 9 (14.3%)

1972 63 59 (93.7%) 581 9.2 4 (6.8%)

Table A5 shows an analysis of the individual dosimeters that recorded positive doses. As seen in 

the table, the number of positive badges per year was around 10% for the first 2 years in the 

period of interest, at which point it drops to approximately 6% or less. Interestingly, the number 

of dosimeters in which a positive gamma (photon) dose was reported but the beta component 

was zero (231 total) far exceeds the number of dosimeters in which a positive beta was recorded 

but the gamma component was zero (only three total). This, at least partially, addresses the 

 
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concern raised during the January 2017 Work Group meeting (ABRWH 2017) concerning the 

potential for positive beta dose coupled with zero gamma dose in the empirical dose records. 

Table A5. Overview of Dosimeters with Positive Results by Year 

Year

Total 

badges in 

year 

Total positive 

badges in year 

(% of total)

# dosimeters 

with positive 

beta and zero 

gamma

# dosimeters 

with positive 

gamma and 

zero beta

1966 1,041 114 (11.0%) 1 68

1967 966 97 (10.0%) 0 64

1968 935 50 (5.3%) 0 42

1969 749 12 (1.6%) 0 10

1970 659 38 (5.8%) 1 27

1971 689 23 (3.3%) 1 14

1972 581 10 (1.7%) 0 6

All Years 5,620 344 (6.1%) 3 231

Table A6 shows the observed beta-to-gamma ratios by year for the sampled claimant population. 

For situations in which there was a positive measurement in one of the dose elements (beta or 

gamma) but a zero measurement in the other element, the zero element was adjusted to the 

minimum detectable level (MDL) divided by two. As seen in the second column of Table A6, the 

total summed beta-to-gamma ratio for all years was less than 1. On average, the individual 

dosimeters with positive measurements displayed a beta-to-gamma ratio less than 1 for all years 

except 1971 and 1972. The maximum beta-to-gamma ratio by year ranged from approximately 3 

to 10. Figure A2 displays the rank-ordered beta-to-gamma ratios for all dosimeters measuring a 

positive dose among the sampled claimant population. As seen in this figure, approximately 90% 

of the observed beta-to-gamma ratios were less than 2 (which can be compared with the 95th

percentile beta-to-gamma ratio of 1.893 in NIOSH 2017). However, only approximately 26% of 

the observed beta-to-gamma ratios were less than 0.2 (which can be compared to the 50th

percentile beta-to-gamma ratio 0.1893 in NIOSH 2017). 
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Table A6. Overview of Beta-to-Gamma Ratios Observed by Year for 1966–1972 

Year

Total summed 

beta-togamma for 

year

Minimum 

individual 

dosimeter 

beta-to-gamma

Maximum 

individual 

dosimeter betato-gamma

Average of 

individual 

dosimeter 

beta-to-gamma

1966 0.60 0.05 5.00 0.79

1967 0.88 0.03 10.21 0.70

1968 0.54 0.04 8.33 0.72

1969 0.57 0.07 3.14 0.67

1970 0.46 0.05 7.67 0.69

1971 0.93 0.06 9.33 1.22

1972 0.84 0.13 4.67 1.18

All Years 0.69 0.03 10.21 0.78

Note: Beta/gamma ratios calculated assuming MDL/2 is situations of zero recorded dose in one of the 

elements.

Figure A2. Rank Order of Observed Beta-to-Gamma Ratios for Individual Positive 

Dosimeters among Sampled Claimants (1966–1972) 
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Table A7 shows an analysis of the observed beta-to-gamma ratios by the area associated with the 

individual badges. On average, the observed beta-to-gamma ratios were less than one in 19 of 22 

locations (including the unspecified location). There does not appear to be a specific trend 

related to underground issue locations (assumed to be specified with a “U” preceding the area 

number) versus aboveground locations. Notably, Area 16 had some of the higher average betato-gamma ratios; however, the maximum observed beta-to-gamma ratio was for an unspecified 

location. Ironically, Area 23, which includes the headquarters town of Mercury, had the highest 

average ratio of beta-to-gamma dose.

Table A7. Observed Beta-to-Gamma Ratios by Area

Area 

designation 

on badge

Total 

badges

Minimum 

individual 

dosimeter 

beta/gamma

Maximum 

individual 

dosimeter 

beta/gamma

Average 

individual 

dosimeter 

beta/gamma

23 2 0.43 4.67 2.55

U-16 14 0.27 8.33 2.10

16 15 0.29 4.17 1.14

Unspecified 86 0.05 10.21 0.92

BLDG 1000 31 0.03 4.13 0.84

12 36 0.11 4.64 0.80

U-5 1 0.68 0.68 0.68

NRDS 58 0.09 3.32 0.64

U-12 45 0.06 3.47 0.62

E Tunnel 10 0.11 1.76 0.43

CP-2 16 0.07 1.18 0.38

3 1 0.38 0.38 0.38

5 1 0.38 0.38 0.38

2 4 0.17 0.50 0.28

U-10 4 0.09 0.50 0.28

U-2 4 0.04 0.38 0.27

9 3 0.09 0.43 0.25

U-20 1 0.21 0.21 0.21

24 1 0.17 0.17 0.17

8 2 0.06 0.25 0.16

20 7 0.04 0.27 0.14

U-11 2 0.07 0.08 0.07

Note: Ratios calculated by assuming MDL/2 in situations of zero recorded dose in one of the elements. 

In summary, a semi-random sample of 100 claimants during the period of interest showed that a 

higher percentage of monitored claims accrued positive measured doses during the first 3 years 

(1966–1968) than in the latter 4 years (1969–1972). However, observed beta-to-gamma ratios 

during these years were lower on average than later years (1971–1972). Overall, 80% of the 

individual dosimeter beta-to-gamma results were less than 1, and 90% were less than 2. 

However, only 8% of the observed beta/gamma ratios were less than 0.1, which is essentially the 

50th percentile ratio proposed in NIOSH (2017). A location-specific analysis of positive 

dosimeter badges did not indicate a bias toward either underground or aboveground issue 

locations. 
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It is very important to keep in mind that the results of the ratio of beta to gamma doses discussed 

in this attachment were measured in 1966–1972—many years after the atmospheric testing of 

nuclear weapons had stopped in July 1962. Because fallout deposited on the ground surface 

weathers into the soil and because beta particles are attenuated much more strongly than are 

gamma rays, the values of recorded ratios of beta to gamma doses should be considered as 

minimal values. The goal at hand is to evaluate the beta doses that could have been received by 

persons during the 1963–1965 period, when no such measurements were available and before 

more severe weathering had taken place.

Currently, it is not possible to specify why some of the ratios of beta to gamma doses were much 

higher than average—up to a ratio of 10. Such high values could have been due to exposure to 

fresh fallout resulting from leaks of underground tests. Underground tests continued to take place 

until September 1992.