1

Advisory Board on Toxic Substances and Worker Health

Revised Recommendation: Jobs Presumed to have pre-1995 Asbestos Exposure

Recommendation

We recommend that the Department of Labor evaluate the job categories and associated 

aliases for all DOE sites in the Site Exposure Matrices and revise its list of occupations with 

presumed pre-1995 asbestos exposure (Exhibit 15-4) to reflect current knowledge as summarized 

in the rationale provided below and associated data and references. Supervisors of the listed job 

categories should also be considered for inclusion. For people who have other job titles with 

claims in relation to asbestos exposure, a careful investigation of possible occupational sources 

of asbestos exposure should be undertaken. In the case of mesothelioma, with greater than 90% 

linkage to asbestos exposure, all cases should have additional inquiry into potential asbestos 

exposure, even if their job titles are not among those that have presumed asbestos exposure. A 

Committee of the Board should work with the Department to conduct this exercise and achieve a 

consensus on a revised list of occupations with presumed pre-1995 asbestos exposure.

Rationale

The Board previously recommended that the EEOICP expand the list of presumed 

asbestos-exposed job titles as provided in EEOICP Procedure Manual (PM) 4.2, Appendix 1, 

Exhibit 15-4 to include additional titles that can be reasonably presumed to have had asbestos 

exposure prior to 1995. The current list is shown in Table 1.

The Board agrees that all of the job titles currently listed in PM 4.2 can be presumed to 

be exposed to asbetsos. The list includes mostly construction and maintenance occupations. It 

encompasses most, but not all, of the occupations listed as such under construction trades in the 

Census 2000 occupational coding system (Census 2000). There are also several job titles on the 

list that correspond to job titles under two other job groups of the Census 2000 occupatuional 

codes: 1) Installation, Maintenance, and Repair Workers , and 2) Production occupations 

(Census 2000). 

For the purposes of this recommendation, we refer to the names of job titles used by the 

Census 2000 occupational coding system , since they are standardized, are or were widely 

utilized, and most closely reflect the job titles used in the published medical literature and 

available databases. These job titles may differ somewhat from the categories used in the 

Department of Labor’s Site Exposuire Matrices (SEM). We note that the job categories and their 

aliases that appear in the SEM appear to vary appreciably by DOE site. The DOE Former 

Worker Programs have encountered similar challenges: a large number of job titles, which vary 

across DOE sites and evolve over time. We note that the claims evaluation process requires that 
2

the claims examiners or others conform the job title(s) reported by the claimants to the 

classification system used in the SEM in order to access the information about potential 

exposures contained in the SEM.

The Board was asked by the Department to provide medical evidence for its proposal to 

add job titles to the current list in Table 1. We found that available published medical studies 

and database information use job classification systems that generally corresponds to the U.S. 

Census occupational coding system (or the related SOC) that is widely used, including by the 

Census Bureau and the Department of Labor. Studies from other countries use different 

standardized classification systems that bear substantial similarities to the U.S. Census 

occupational coding system. Cross-walking job titles over system versions that evolve over time 

or differ by geography can be challenging. We note that the SEM has undoubtedly spent 

considerable effort deciding which job titles are equivalent (cross-walking), since the SEM has 

matched job titles with aliases to facilitate use of the SEM in the claims evaluation process. 

To identify job titles with presumed asbetsos exposure prior to 1995, we focused on 

available research and database information that link job titles with the cardinal asbetsos-related 

disease, malignant mesothelioma (MM). Since MM is very closely linked to a prior history of 

occupational asbestos exposure, and since it occurs with relatively modest level of asbestos 

exposure, MM is the best disease candidate for identifying at risk occupations for whom a 

presumption of sgnificant prior asbestos exposure can be made, per EEOICP PM 4.2. Any 

occupations that entail asbestos exposure and are associated with excess risk of asbestosis, lung 

cancer, ovarian cancer and laryngeal cancer would very likely also be identified in studies of 

occupation and MM, since the non-MM asbestos-related diseases generally require a higher dose 

of asbetsos exposure. In addition, the three other asbestos-related cancers have other causes, 

which can obfuscate the relationships between job titles, asbestos exposures, and these cancers. 

National Occupational Mortality System (NOMS)

The National Occupational Mortality Surveillance System (NOMS) is a compilation of 

causes of death (underlying cause) in the United States by NIOSH according to ICD codes 9 and 

10, together with usual occupation and industry of decedents as recorded on the death certificate,

and coded according to the U.S. Census occupational coding systems (NIOSH 2019). NIOSH 

has maintained this system for nearly three decades, collecting mortality data from 26 states,

according to a recent report (Robinson 2015) and the NOMS website 

(https://www.cdc.gov/niosh/topics/noms/about.html). A succinct description of NOMS and its

recent application to occupation- and industry-based risk of leukemia and heart disease are 

available (Robinson 2015). NOMS data have been used in over 140 publications since its 

inception. NOMS calculates occupation- and industry-specific proportionate mortality ratios 

(PMR) as a measure of risk. PMR is the ratio of the proportion of deaths caused by the disease of 

interest in the specified occupation of interest compared to the proportion of deaths caused by the 

disease of interest in the total population of decedents in the data set. A PMR above 100 
3

represents an increase in the proportion of the disease in the occupation of interest relative to the 

overall population.

In April 2020, Board member John Dement PhD queried the online NOMS data set to 

obtain proportionate mortality ratios for malignant mesothelioma (ICD code C45) by usual 

occupation of decedents for the years 1999, 2003-2004, and 2007-2014 in aggregate. Data 

included deaths for decedents aged 18-90 of all races and both sexes in 26 U.S. states, involving 

550 occupational categories (NIOSH 2019). The total number of deaths due to malignant 

mesothelioma (C45) in the NOMS data set was approximately 6,800. Note that not all 

mesotheliomas are included in ICD code C45, because some cases are instead coded as 

malignant neoplasm of the pleura or peritoneum (C384 and C48). However, ICD code C45 in 

NOMS includes at least three-quarters of the deaths due to malignant mesothelioma in the 

NOMS dataset.

Table 2 shows the 62 occupations (2000 Census codes) that had statistically significant 

excess mortality (elevated PMR’s) due to malignant mesothelioma in the combined years of 

1999, 2003-2004, and 2007-2014 in the 26 states included in NOMS. All occupations on the list 

have increased proportions of deaths due to malignant mesothelioma (All PMR’s with a lower 

95% confidence interval > 100 represent statistically significant excess PMR’s.) Table 2 shows 

the occupations with elevated PMR’s in the order in which the occupational titles appear in the 

2000 Census coding system. Table 2 color codes the occupations with excess PMR’s according 

to standardized hierarchy of job groupings used by the coding system. Major occupational 

groups (indicated in green) with excess PMR’s include: 1) Architecture and Engineering 

Occupations, 2) Life, Physical, and Social Science Occupations, 3) Construction and Extraction 

Occupations, 4) Installation, Maintenance, and Repair Occupations, 5) Production Occupations, 

and 6) Transportation and Material Moving Occupations. It should be noted that census 2000 

occupation classifications were based on the government-wide 2000 Standard Occupation 

Classification (SOC) system. In the SOC system supervisors of professional occupations are not 

coded separately and are assigned the same code as the occupation they supervise. Supervisors 

of professional occupations are classified with the occupations they supervise because they often 

need the same type of training, education, and experience as the workers they supervise.

Table 2 shows a significant number of occupations in engineering, maintenance and 

repair and production that are not included in PM 4.2, Appendix 1, Exhibit 15-4 (Table 1)

Table 3 shows the same NOMS occupations with elevated PMR’s in descending order of 

the magnitude of the PMR. This listing provides the usual way that occupational risks are 

illustrated. The top occupations in terms of MM risk are those that customarily demonstrate the 

highest risk of MM in the scientific literature

Strengths of the NOMS data, especially for the purpose of updating the EEOICP 

procedure Manual and the SEM include: 1) use of a national dataset; 2) inclusion of deaths from 
4

a time period that is both broad (1999 to 2014) and recent (2007-2014); 3) use of a well-tested 

methodology; 4) employment of a standardized and broadly used set of codes for cause of death 

and occupation; 5) access to a large and geographically diverse data set. The latter feature is 

important, because it provides increased statistical power and increases the representativeness of 

the data, features that are important to a national compensation program such as EEOICP. 

Other U.S. Studies of Malignant Mesothelioma

Attachment A includes excerpted Tables from published studies of occupational risk of 

MM. Copies of their source articles are also provided.

Mazurek and NIOSH colleagues combined a U.S. national mortality data set (CDC 

Wonder) with NOMS data to describe basic demographics of MM in the U.S. during 1999-2015 

and to evaluate occupational risk of malignant mesothelioma death (n = 1,830) in 23 states 

during 1999-2007 (Mazurek 2016). Results from their 2016 publication are shown in the table on 

Attachment A (p. 10). 17 occupations showed a statistically significant elevation in PMR for 

malignant mesothelioma. These titles are also seen among the titles on our NOMS analysis of 

MM deaths. The number of MM deaths in the dataset analyzed by Mazurek et al was one-third of 

the deaths in our NOMS analysis and thus limited statistical power. Additional job titles with 

elevated PMR’s may not have attained statistical significance. 

In 2006, Bang and NIOSH colleagues performed a similar analysis of MM that occurred 

in the U.S. during 1999-2001 (Bang 2006). Their overall data set was a smaller data set than the 

one used by Mazurek. They evaluated MM deaths (ICD-10 code C45) that occurred in 1999 in 

19 states for which occupation and industry data were available. The number of MM deaths 

analyzed for occupation is not provided. Four occupations demonstrated statistically significant 

PMR elevations [see Attachment A (p. 11)]. To gain a sense of the size and statistical power of 

the Bang and Mazurek analyses versus our NOMS query, compare the number of deaths that 

occurred among “plumber, pipefitters and steamfitters”: 18 deaths in the Bang study, 67 deaths 

in the Mazurek study, and 219 deaths in our NOMS analysis. 

Tomasallo and colleagues recently published a case control study, profiling occupational 

and industrial risks of MM incidence and mortality in Wisconsin from 1997 to 2013 (Tomasallo 

2018). They evaluated 1,083 deaths and 1,246 incident cases of MM. As indicated in the 

attached table [see Attachment A (p. 12)], constructions trades; installation, maintenance, repair 

workers; metal and plastics workers, and engineers showed significantly increased risk. The 

analysis was constrained by a relatively small number of cases of MM.

International Studies of Malignant Mesothelioma

We identified large case control and PMR studies from Great Britain, France, Canada, 

Spain, Germany, and Northern Ireland [see Attachment A (pp. 13-19)]. These will not be 

reveiwed individually in this summary. A perusal of the key publsihed tables from the relevant 
5

articles, as provided in Attachment A, pp. 10-20, indicates a relatively consistent increased MM 

risk for construction, maintenance, engineering, and selected production occupations.

Comments

Use of the NOMS results for the purpose of updating the list of job titles with 

presumptive asbestos exposure in EEOICP has several advantages. NOMS and DOE are both 

nationwide in scope and include many and varied facets of industry, so NOMS results may be 

more illustrative and relevant than more specific studies that reflect a single dominant 

geographic area or only one or a few industries. NOMS uses a standard classification system 

(Standard Occupational Classification, SOC) that is broadly used by agencies in the U.S. 

Government (U.S. Bureau of Labor Statistics, 2000). The SOC system includes detailed 

descriptions of each job title, which should facilitate cross-walking the NOMS job categories 

with SEM job categories and claimant-derived job titles. An additional Federal classification 

system, O*NET, which is based on the SOC, can also be used to classify job titles.

The NOMS –derived list of occupations at high risk of malignant mesothelioma differs 

from the current job list included in EEOICP, Exhibit 15-4 (Table 1) principally in adding titles 

in engineering, maintenance and repair, and selected production activities. The NOMS analysis 

represents an updated evaluation of the same type of national mortality data that was used in the 

data source for Exhibit 15-4, which is a 2014 report by ATSDR. The ATSDR report relied on 

NIOSH occupational mortality analyses; however, the ATSDR report had limited ability to 

address occupational mesothelioma risk as occupational data were only available for calendar 

year 1999. Advantages of the current NOMS analysis include 1) its inclusion of the most recent 

data available, i.e, the 1999-2014 period; and 2) the size of the NOMS data set, which includes 

many more mesothelioma deaths than previous analyses (and three times as many deaths as the 

most recent analysis published by Mazurek in 2016). The ability to examine large numbers of 

mesothelioma deaths adds statistical power, that is, the ability to understand the meaning of PMR

estimates (i.e., detect an effect) in a much greater number of occupations. 

Interestingly, the SEM currently recognizes that many of the additional job titles revealed 

by NOMS versus Exhibit 15-4 have potential exposure to asbestos. In the claims evaluation 

process, inclusion of a link between a job category and asbestos exposure in the SEM initiates 

consideration of the degree and extent of asbestos exposure by the claims examiner or industrial 

hygienist. Adding job titles to the list in Exhibit 15-4 based on results of NOMS and other 

studies recognizes that current scientific evidence justifies re-categorizing the asbestos exposure 

from “potential,” as in the SEM to “presumed to be significant,” as described in the EEOICP 

procedure manual.

Embedded in the list of job titles with elevated malignant mesothelioma risks in NOMS is 

the inclusion of numerous job titles that primarily have bystander exposure to asbestos, rather 

than direct asbestos exposure through manipulation of asbestos-containing materials. This is an 
6

important finding, because claimants may not report such exposure in completing the 

occupational health questionnaire as part of their claims submission. Industrial hygienists may 

also not factor in bystander exposure in their claims evaluations.

Conclusion

We recommend that the Department of Labor evaluate the job categories and associated 

aliases for all DOE sites in the Site Exposure Matrices and revise its list of occupations with 

presumed pre-1995 asbestos exposure (Exhibit 15-4) to reflect current knowledge as summarized 

in this rationale and associated data and references. Supervisors of the listed job categories 

should also be considered for inclusion. A Committee of the Board should work with the 

Department to conduct this exercise and achieve a consensus on a revised list of occupations 

with presumed pre-1995 asbestos exposure.
7

Table 1 

EEOICP Procedure Manual (PM) 4.2, Appendix 1, Exhibit 15-4
8

Table 2 Occupations with Elevated PMR’s for Malignant Mesothelioma according to 

Major and Specific Census Occupational Titles, (NOMS, 1999, 2003, 2004, 2007-2014)

2000 Census Major Occupational Groupings & NOMS 

Occupation Title

2000 Census 

Code

1990 Census 

Code

PMR Number 

of deaths

95% 

CI 

Lower

95% 

CI 

Upper

Architects, Surveyors, and Cartographers (17-1000)

Architects 130 43 337 19 203 526

Engineers (17-2000)

Marine Engineers & Naval Architects 144 58 1031 9 471 1957

Chemical Engineers 135 48 449 30 303 642

Materials Engineers 145 45 266 7 107 549

Industrial, Health, & Safety Engineers 143 56 259 30 175 370

Mechanical Engineers 146 57 253 50 187 333

Electrical & Electronic Engineers 141 55 207 43 150 279

Civil Engineers 136 53 176 36 123 243

Engineers, NEC 153 59 174 28 115 251

Drafters, Engineering, and Mapping Technicians (17-3000)

Engineering Technicians (except drafters) 155 214, 215, 216 228 38 161 312

Drafting Occupations 154 217 171 17 100 274

Life, Physical, and Social Science Technicians (19-4000)

Chemical Technicians 192 224 369 15 206 608

Supervisors, Protective Service Workers (33-1000)

Firefighters & Supervisors of Firefighters1 372, 374 413, 417 211 35 147 293

Law Enforcement Workers (33-3000)

Detectives, criminal investigators, police & sheriff's patrol 

officers 382, 385 418 140 49 104 185

Supervisors, Construction and Extraction Workers (47-1000)

First line Supervisors Const. & Ext Occupations 620 553-558, 613 215 97 174 262

Construction Trades Workers (47-2000)

Insulation Workers 640 593 3539 52 2643 4641

Plumbers, pipefitters, & steamfitters 644 557, 585, 587 642 219 560 733

Sheetmetal Workers 652 596 418 34 289 584

Drywall Installers 633 573 412 18 244 651

Electricians2 635, 713 555, 575-577 405 197 351 466

Structural Iron & Steel Workers 653 597 299 21 185 457

Brickmasons & Stonemasons 622 553, 563, 564 242 42 174 327

Carpenters 623 554, 567, 569 185 137 156 219

Painters, Paperhangers, & Plasterers 642-643, 646 556, 579-584 158 44 115 213

Boilermakers & Oper. Engineers 621, 632 643, 844 153 54 115 199

Supervisors of Installation, Maintenance, and Repair Workers (49-1000)

Supervisors of Mechanics & Repairers 700 503 275 47 202 366

Vehicle and Mobile Equipment Mechanics, Installers, and Repairers (49-3000)

Heavy Vehicle & Mobile Equipment Mechanics 722 516, 517 190 21 118 290

Other Installation, Maintenance, and Repair Occupations (49-9000)

Precision Instrument & Equipment Repairers 743 535 472 12 244 825

Heating, Air Conditioning, & Refrigeration Mechanics, 

Installers/Repairer 731 534 263 20 161 406

Maintenance and Repair: General and Helper 761-762, 734 865, 547, 549 199 54 149 260

Industrial & Refractory Machinery Mechanics3 733, 821 518 188 26 123 276
9

Supervisors, Production Workers (51-1000)

Supervisors, production occupations 770 628 207 138 174 245

Assemblers and Fabricators (51-2000)

Millwrights, Engine Installers4 773, 736 544 440 50 327 580

Aircraft & Structural Metal Fabricators 771, 774 636 186 15 104 308

Food Processing Workers (51-3000)

Furnace, Kiln, & Oven Operators, exc. Food5 783, 804, 873 766 374 15 209 617

Metal Workers and Plastic Workers (51-4000)

Lay-out Workers 816 646 752 5 244 1755

Molding & Casting Machine Operators 810 719 262 10 126 483

Welders & Cutters 814 783 250 98 203 304

Machinists 803 637, 639 196 110 161 237

Extruding/Drawing Machine Operators 792 755, 777 193 16 110 314

Tool & Die Makers 813 634, 635 151 27 100 220

Plant and System Operators (51-8000)

Stationary Engineers6 861, 965 696 453 55 341 589

Other Production Occupations (51-9000)

Separating, Filtering, & Clarifying Machine Operators 864 757 315 16 180 511

Mixing & Blending Machine Operators 865 756 291 11 146 522

Painting & Paint Spraying Machine Operators 881 759 202 14 110 338

Production Samplers & Weighers 874 798 148 38 105 203

Machine Operators, not specified 896 779 124 122 103 148

Water Transportation Workers (53-5000)

Ship Captains & Mates, Engineers exc. Fishing Boats 930-931 828, 833 293 19 176 458

Material Moving Workers (53-7000)

Crane & Tower Operators 951 849 183 15 103 302

1. Groups 372 in Supervisors, Protective Service Workers 33-1000 & 374 in Firefighting and Prevention Workers 33-2000

2. Groups 635 in Construction and Trades Workers 47-2000 & 713 in Electrical and Electronic Equipment Mechanics, Installers, and Repairers 

49-2000

3. Groups 733 in Other Installation, Maintenance, and Repair Occupations 49-9000 & 821 in Metal Workers and Plastic Workers 51-4000

4. Groups 773 in Assemblers and Fabricators 51-2000 & 736 in Other Installation, Maintenance, and Repair Occupations 49-9000

5. Groups 783 in Food Processing Workers 51-3000, 804 in Metal Workers and Plastic Workers 51-4000, & 873 in Other Production 

Occupations 51-9000

6. Groups 861 in Plant & System Operators 51-8000 & 965 in Material Moving Workers 53-7000
10

Table 3 Occupations with Elevated PMR’s for Malignant Mesothelioma in Descending 

Order of PMR, (NOMS, 1999, 2003, 2004, 2007-2014)

Census Occupational Code Job Titles

 As Used in NOMS 

2000 Census 

Code

1990 Census 

Code

PMR Number 

of deaths

95% CI 

Lower

95% CI 

Upper

Insulation Workers 640 593 3539 52 2643 4641

Marine Engineers & Naval Architects 144 58 1031 9 471 1957

Lay-out Workers 816 646 752 5 244 1755

Plumbers, pipefitters, & steamfitters 644 557, 585, 587 642 219 560 733

Precision Instrument & Equipment Repairers 743 535 472 12 244 825

Stationary Engineers 861, 965 696 453 55 341 589

Chemical Engineers 135 48 449 30 303 642

Millwrights, Engine Installers 773, 736 544 440 50 327 580

Sheetmetal Workers 652 596 418 34 289 584

Drywall Installers 633 573 412 18 244 651

Electricians 635, 713 555, 575-577 405 197 351 466

Furnace, Kiln, & Oven Operators, exc. Food 783, 804, 873 766 374 15 209 617

Chemical Technicians 192 224 369 15 206 608

Architects 130 43 337 19 203 526

Separating, Filtering, & Clarifying Machine Operators 864 757 315 16 180 511

Structural Iron & Steel Workers 653 597 299 21 185 457

Ship Captains & Mates, Engineers exc. Fishing Boats 930-931 828, 833 293 19 176 458

Mixing & Blending Machine Operators 865 756 291 11 146 522

Supervisors of Mechanics & Repairers 700 503 275 47 202 366

Materials Engineers 145 45 266 7 107 549

Heating, Air Conditioning, & Refrigeration Mechanics, 

Installers/Repairer

731 534 263 20 161 406

Molding & Casting Machine Operators 810 719 262 10 126 483

Industrial, Health, & Safety Engineers 143 56 259 30 175 370

Mechanical Engineers 146 57 253 50 187 333

Welders & Cutters 814 783 250 98 203 304

Brick masons & Stonemasons 622 553, 563, 564 242 42 174 327

Engineering Technicians (except drafters) 155 214, 215, 216 228 38 161 312

First line Supervisors Const. & Ext Occupations 620 553-558, 613 215 97 174 262

Firefighters & Supervisors of Firefighters 372, 374 413, 417 211 35 147 293

Electrical & Electronic Engineers 141 55 207 43 150 279

Supervisors, production occupations 770 628 207 138 174 245

Painting & Paint Spraying Machine Operators 881 759 202 14 110 338

Maintenance and Repair: General and Helper 761-762, 734 865, 547, 549 199 54 149 260

Machinists 803 637, 639 196 110 161 237

Extruding/Drawing Machine Operators 792 755, 777 193 16 110 314

Heavy Vehicle & Mobile Equipment Mechanics 722 516, 517 190 21 118 290

Industrial & Refractory Machinery Mechanics 733, 821 518 188 26 123 276

Aircraft & Structural Metal Fabricators 771, 774 636 186 15 104 308

Carpenters 623 554, 567, 569 185 137 156 219

Crane & Tower Operators 951 849 183 15 103 302

Civil Engineers 136 53 176 36 123 243

Engineers, NEC 153 59 174 28 115 251

Drafting Occupations 154 217 171 17 100 274

Painters, Paperhangers, & Plasterers 642-643, 646 556, 579-584 158 44 115 213

Boilermakers & Operating. Engineers 621, 632 643, 844 153 54 115 199

Tool & Die Makers 813 634, 635 151 27 100 220

Production Samplers & Weighers 874 798 148 38 105 203

Detectives, criminal investigators, police & sheriff's patrol 

officers

382, 385 418 140 49 104 185

Machine Operators, not specified 896 779 124 122 103 148
11

Attachment A

Case control and surveillance studies from various countries that identify occupations at 

high risk for malignant mesothelioma

1. US – Mazurek (2016), Bang (2016), Tomasallo (2018)

2. England- Peto (1995); McElvenny (2012)

3. France - Rolland (2010)

4. Canada – Teschke (1997)

5. Spain – Agudo (2000)

6. Germany - Rodelsperger (2001)

7. Northern Ireland - O’Reilly (1999) 
12
13
14
15

LANCET 1995
16
17
18
19
20
21
22

References

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Panades R., Turuguet D., Escoalr A., et al. Occupation and risks of malignant pleural 

mesothelioma: A case-control study in Spain. Am J Ind Med. 2000;37:159–168.

2. ATSDR (2014), Case Studies in Environmental Medicine – Asbestos Toxicity. Course 

WB 2344. U.S. Department of Health and Human Services, Public Health Service, 

Centers for Disease Control and Prevention, Agency for Toxic Substances and Disease 

Registry, Atlanta, Georgia.

3. Bang KM , Pinheiro GA, Wood JM, Syamlal G. Malignant Mesothelioma Mortality in 

the United States, 1999-2001 Int J Occup Environ Health Jan-Mar 2006;12(1):9-15.

4. Mazurek JM, Syamlal G, Wood JM, Hendricks SA, Weston A. Malignant Mesothelioma 

Mortality - United States, 1999-2015. MMWR Morb Mortal Wkly Rep. 2017;66(8):214‐

218. doi:10.15585/mmwr.mm6608a3.

5. McElvenny DM, Darnton AJ, Price MJ, Hodgson JT. Mesothelioma mortality in Great 

Britain from 1968 to 2001. Occup Med (Lond). 2005;55:79–87. doi: 

10.1093/occmed/kqi034.

6. NIOSH. Census 2000 Occupational Classification System. Industry and Occupation 

Coding: I&O Classifications. 

https://www.cdc.gov/niosh/topics/coding/nioccsuserdocumentation.html. Page last 

reviewed: March 6, 2019. Accessed May 1, 2020.

7. NIOSH (2019). National Occupational Mortality Surveillance (NOMS). U.S. Department 

of Health and Human Services, Public Health Service, Centers for Disease Control and 

Prevention, National Institute for Occupational Safety and Health, Division of Field 

Studies and Engineering, Health Informatics Branch. Date accessed May 1, 2020.

8. O’Reilly D, Reid J, Middleton R, Gavin AT. Asbestos related mortality in Northern 

Ireland. J Pub Health Med. 1999;21(1):95–101.

9. Peto J, Hodgson JT, Matthews FE, Jones JR. Continuing increase in mesothelioma 

mortality in Britain. Lancet. 1995;345:535–539. doi: 10.1016/S0140-6736(95)90462-X.

10. Robinson CF, Walker JT, Sweeney MH et al. Overview of the National Occupational 

Mortality Surveillance (NOMS) System: Leukemia and Acute Myocardial Infarction 

Risk by Industry and Occupation in 30 US States 1985-1999, 2003-2004, and 2007. 

AJIM 2015 Feb;58(2):123-37.

11. Rödelsperger K, Jöckel KH, Pohlabeln H, Römer W, Woitowitz HJ. Asbestos and manmade vitreous fibers as risk factors for diffuse malignant mesothelioma: results from a 

German hospital-based case–control study. Am J Ind Med. 2001;39:262–275.

12. Rolland P, Gramond C, Lacourt A, Astoul P, Chamming’s S, Ducamp S, Frenay C, 

Galateau-Salle F, Ilg AG, Imbernon E, Le Stang N, Pairon JC, Goldberg M, Brochard P, 

PNSM Study Group Occupations and industries in France at high risk for pleural 

mesothelioma: a population-based case-control study (1998–2002). Am J Ind Med. 

2010;53(12):1207–1219. doi: 10.1002/ajim.20895.

13. Teschke K, Morgan MS, Checkoway H, et al. Mesothelioma surveillance to locate 

sources of exposure to asbestos. Can J Public Health. 1997;88(3):163‐168. 

doi:10.1007/BF03403881.
23

14. Tomasallo CD, Christensen KY, Raymond M, Creswell PD, Anderson HA, Meiman JG. 

An occupational legacy: malignant mesothelioma incidence and mortality in Wisconsin. J 

Occup Environ Med. 2018;60(12):1143–1149.

15. U.S. Bureau of Labor Statistics, 2000 Standard Occupational Classification (SOC) User 

Guide. (https://www.bls.gov/soc/2000/socguide.htm). Accessed 5/20/2020.

16. United States Census. Census 2000 Occupational Categories, With Standard 

Occupational Classification (SOC) Equivalents: Census 2000 Code Order. Industry and 

Occupation Code Lists & Crosswalks. 

https://www.census.gov/topics/employment/industry-occupation/guidance/codelists.html. Page last revised: November 14, 2019. Accessed may 6, 2020.
1

Advisory Board for Toxic Substances and Worker Health

Parkinsonian Disorders in the Energy Employees Occupational lllness Compensation Program

In 2018, the Department of Labor requested that the Board assist in evaluating aspects of 

the recognition and causation of Parkinsonian disorders in the Energy Employees Occupational 

Illness Compensation Program. We list below the questions and our responses and 

recommendations. 

A. Diagnosis and Terminology in Parkinson’s-related Disorders

1. What are the appropriate aliases of Parkinson’s disease? 

2. Should Parkinsonism and/or Manganism be treated the same as Parkinson’s 

disease? What are the criteria for a finding that the diagnosis is appropriate? (For 

example, many claimants are symptomatic for “the shakes,” but what medical 

evidence allows for the diagnosis of Parkinsonism or other related diagnoses?) 

Inclusion of ICD-10 codes would be ideal for ascertaining coverage under such 

policy. 

Recommendation:

The Board recommends that the clinical diagnosis of Parkinsonism, as established primarily but 

not exclusively by a neurologist, is treated the same as the diagnosis of Parkinson disease 

throughout the EEOICP claim adjudication process, with respective entries of both terms and 

aliases recommended in the DOL’s Site Exposure Matrix (SEM). The Board has identified the 

following aliases that are in use for both terms with corresponding ICD 9 and ICD 10 codes 

ICD 9 332 - Parkinson’s Disease 

ICD 9 332.0 - Paralysis agitans, Parkinsonism or Parkinson’s Disease NOS – not 

otherwise specified, idiopathic, primary

ICD 9 332.1 - Secondary parkinsonism

ICD 10 G20 - Parkinson’s Disease, Hemiparkinsonism, Idiopathic Parkinsonism, 

Paralysis Agitans, Primary Parkinsonism

ICD 10 G21 - Secondary parkinsonism

Rationale:

Parkinsonism is a general term that refers to a group of related neurodegenerative movement 

disorders or syndromes affecting the extrapyramidal system. Impairment of motor function is a 

common clinical characteristic in these disorders which include several neurological entities 

with broad spectrum of clinical symptomatology, risk factors, pathological features, and rates of 

progression. As there are no biomarkers or clinically valid diagnostic tests to clearly 
2

differentiate between these disorders, the Board recommends combining these under a 

common diagnosis of Parkinsonism. 

The earliest and typically the most prominent symptom of motor function impairment in 

Parkinsonism is bradykinesia, a slowness in initiation and carrying out of movements. Often 

progressive, it may be accompanied by other motor symptoms, including muscle rigidity with 

involvement of individual or entire muscle groups, frequently asymmetric; resting “pill rolling” 

tremor, and postural instability, all presenting in any combination, and with varying degree of 

intensity over time (Postuma et al., 2015; Rizek et al., 2016).

Parkinsonian syndromes are classified based on clinical presentation with response/or lack 

thereof to known therapeutic agents (dopamine replacement therapy) as well potential risk 

factors. Medications (neuroleptics, antipsychotic, metoclopramide), drugs (synthetic 

meperidine, MPTP); infections (syphilis, post-encephalitis); metabolic (parathyroid, post-anoxic) 

and vascular abnormalities (strokes, i.e., lower body parkinsonism); as well as pathologic 

growth of, and/or injury to brain structures, have been known to result in parkinsonian 

symptoms (Rizek et al., 2016) and are classified as secondary parkinsonisms.

Inhalational exposures to toxic agents, including manganese (Mn) and carbon monoxide (CO), 

have also been known to present with motor abnormalities consistent with Parkinsonian 

symptomatology, and are classified under toxic effects of each exposure respectively, i.e., 

carbon monoxide poisoning (ICD-10 T58.94 vs ICD-9 332.1); manganese, manganism (ICD-10 

T57.2X1 vs ICD-9 332.1). These disorders may occur at any age, with motor function impairment 

typically within days to weeks following the exposures (Choi and Cheon, 1999; Choi, 2002). A 

longer latency, up to a decade or more, associated with low, chronic exposures is not 

uncommon in their pathogenesis (Huang et al. 1993; Huang et al., 1998). 

No biomarkers have been found to date to confirm the individual diagnoses of parkinsonism. 

Functional testing, including brain imaging techniques such as Magnetic Resonance Imaging 

(MRI), Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography 

(SPECT) have been increasingly used to assess neurochemical changes in the brain and 

differentiate among different types of parkinsonian disorders. Their clinical validity, however, is 

still under study (Loane and Politis, 2011; Politis, 2014; Rizek et al., 2016). The diagnostic gold 

standard is the post-mortem pathology.

Parkinson disease (PD) is the most common of all Parkinsonisms with estimates of up to 80% of 

all cases, (Schwartz and Henchcliffe, 2009). Frequently referred to in earlier literature as 

Parkinson’s disease, paralysis agitans, primary parkinsonism, idiopathic parkinsonism, or

hemiparkinsonism, Parkinson disease affects individuals primarily over the age of 50 with risk 

increasing with age and males predominantly over females with a 2:1 ratio. Early onset of this 

disease (<50 years) is rare, estimated at less than 5% of cases (Van Den Eeden et al., 2003; 

Ferguson et al., 2016). Genetic mutations have been identified in the etiology of Parkinson but 

are estimated to account for less than 15% of all PD cases, mostly early onset (Tanner et al., 

1999; Martin et al., 2011), A combination of genetic, environmental and occupational factors 

are thought to play a role in the etiology of the remainder 85% of cases of this disease (Caudle 

et al. 2012; Caudle, 2015). 
3

The clinical onset of motor function impairment in Parkinson Disease is typically over the age of 

50. Studies have shown that motor deficits may be preceded, up-to 20 years or more, by a 

prodromal stage of non-specific impairment in a sense of smell, chronic constipation, 

depression, and sleep disorders (Kalia and Lang, 2015). Research is underway to identify and 

evaluate clinical tests and biomarkers in this prodromal stage of the disease (Politis, 2014; Berg 

et al., 2015; Heinzel et al.,2019). 

The diagnostic gold standard in Parkinson disease is post-mortem pathology with degeneration 

of dopaminergic nerve cells in the basal ganglia, substantia nigra part of the mid-brain and

abnormal protein, α-synuclein depositions leading to impairment in the production of 

dopamine neurotransmitter (Dickson, 2012). 

Sets of diagnostic criteria have been developed including UK’s Parkinson Disease Society Brain 

Bank Clinical Diagnostic Criteria (Hughes et al. 1992) and, more recently, the International 

Parkinson and Movement Disorder Society (MDS) Clinical/Research Diagnostic Criteria (Table 1), 

to assist in the clinical and research diagnosis and differentiation of Parkinsonisms (Postuma et 

al., 2015). The primary diagnosis of bradykinesia accompanied by at least one of three other 

motor symptoms and an unequivocal response to dopaminergic therapy is supportive of the 

diagnosis of Parkinson disease. 

Parkinson-Plus syndromes are disorders that present with classical motor impairment 

symptoms of Parkinsonian syndromes but lack a response to dopamine substitute therapies. 

These disorders are sporadic, have additional (‘‘plus’’) clinical features and diverse pathology 

with neurodegeneration typically more extensive and progressive than that seen in classical PD.

Genetic mutations as well as other factors including brain injury have been shown to play a role 

in their pathogenesis (Wenning et al., 2011; Olfati et al., 2019; Armstrong and McFarland, 

2019). Parkinson-Plus syndromes are also known as Atypical Parkinsonisms and are classified as 

Multiple Systems Atrophy (MSA) (ICD-10 G13.8 vs ICD 9 333.0), Progressive Supranuclear Palsy 

(PSP) (ICD-10 G23.9 vs ICD 9 333.0), Corticobasal Degeneration (CBD) (ICD -10 G31.85 vs ICD-9 

331.6) and Lewy Body Dementia (LBD) (ICD -10 G31.83 vs ICD-9 331.82).

B. Causation and Presumptions

1) What toxins are associated with each of the diagnosis? (Any input would require 

supporting medical health science literature from peer reviewed human studies to 

support any proffered associations)

2) Are there any presumptions that the Board could offer regarding worker exposure to 

these toxins? For example, if the committee finds the exposure to manganese as a 

causal connection to Parkinson’s disease, are there certain labor categories or work 

processes that are associated with this exposure? 
4

3) Are there any causation presumptions that can be made? For example, when an 

employee has a diagnosis of X, exposure to Y, for a period of Q years, and a latency 

period of Z, DEEOIC should accept the claim.

Recommendation:

The Board recommends that in addition to carbon monoxide and steel/manganese products 

already included in the EEOICPA Procedure Manual and DOL Site Exposure Matrix, exposures to 

carbon disulfide (CS2) and trichloroethylene (TCE) be presumed to cause, contribute, or 

aggravate Parkinsonism claims. These exposures were present in the DOE weapons complex 

and have been shown to be associated with increased risk of Parkinsonism in human studies. 

The Board also recommends, based on epidemiologic studies, a minimum exposure duration of 

eight (8) years for Part E causation in adjudicating Parkinsonism claims with exposures to 

carbon disulfide and trichloroethylene.

At present, the Board issues no recommendations for methanol, toluene, n-hexane, and 

polychlorinated biphenyls (PCBs), or other work–related exposures common throughout the 

DOE weapons complex. The Board also issues no recommendation for pesticides or specific 

pesticide products that may have been used on DOE installations. Current evidence is not 

sufficient to support a presumption of these additional agents with regard to Parkinsonism. As 

new research is emerging, the Board recommends a periodic review of human studies literature 

on risk factors for Parkinsonism for DOL to provide updates in this field.

Presumption of causation implies the judgment that the literature at the current time is 

sufficient to support the statement that the exposure can contribute to causation of the disease

or aggravate the course of the disease in exposed populations, and the judgment that the 

degree of exposure in the individual is sufficient to have produced this contribution to 

causation in that individual. This use of presumptions is intended to identify the subset of 

people with the straightforward presentations to streamline the compensation process by 

eliminating the need for detailed causal evaluation by the physician and industrial hygienist. It 

must be emphasized that if an individual DOEs not meet the criteria for the presumption of 

causation, this DOEs not imply that there is not sufficient evidence of causation. It simply 

means that individuals who do not meet these presumptive criteria and would need to be 

evaluated through a fact-based process entailing industrial hygiene and medical review to make 

the judgment whether the exposure contributed to causation of the disease.

Rationale:

Inhalational exposures to carbon monoxide and manganese resulting in Parkinsonian type 

deficits have been well-documented in the literature and are included, along with related work 

processes, in the DOL’s EEOICP Procedure Manual and Site Exposure Matrix (SEM). Recent 

studies and case reports provide description of parkinsonian symptomatology following 

inhalational and dermal occupational exposures to carbon disulfide (CS2,) and trichloroethylene 

(TCE) solvents. There is also a growing body of epidemiological research showing exposures to 
5

trichloroethylene (TCE) to increase the risk of Parkinson Disease (PD) in occupationally exposed 

populations. These exposures and studies are briefly reviewed herein.

Solvents have been used commonly throughout industry, as degreasing agents and varnishes, in 

cleaning parts and machining equipment, in dry cleaning, in construction and as substrates in 

paints and paint thinners (Sainio, 2015). Unpublished former DOE worker medical screenings’ 

program data shows extensive use of organic (hydrocarbon) solvents in DOE weapons 

operations throughout the decades, primarily in degreasing and machining operations, with the 

highest exposed jobs including painters, equipment mechanics and production workers (BAECP 

FWP, 2011). A 2011 Bahr et al. study of DOE workers from Paducah Gaseous Diffusion Plant 

identified workers who worked in laboratory, in maintenance/electricians, in 

maintenance/lubrication, in waste or chemical operations as those with highest exposures to 

TCE. Solvents use has also been common in uranium and plutonium recovery processes in

nuclear weapons programs (Todd, 2011). The DOE’s Office of Health and Environmental 

Research Subsurface Science Program study identified TCE and toluene in most of soil, 

sediments and ground water samples collected from or near the disposal sites at eighteen (18)

DOE facilities within the weapons complex around the country (Riley et al. 1992).

Main routes of exposure to solvents are through inhalation, skin and/or ingestion uptake. Liver, 

kidney damage, depression of bone marrow and cancers (In some) have been reported 

following exposure to many organic solvents solvents, with other effects including respiratory 

impairment, reproductive system abnormalities and dermatitis following low-level exposures

(Dick, 2006). Organic solvents are also predominantly neurotoxic with acute, high concentration 

exposures leading to central nervous system suppression of respiration and long-term

exposures associated with chronic solvent encephalopathy (Bale et al., 2011; van Valen et 

al.,2012; Sainio, 2015) and Parkinsonian type deficits following chronic solvents abuse (Uitti et 

al., 1994; Pezzolli et al., 1996). A possible dose-response relationship with duration of exposure 

to solvents and increased risk of death from PD has been reported in a mortality study of 

20,256 Rolls-Royce plants workers from the UK (McDonnell et al., 2003). A recent meta-analysis 

of peer-reviewed epidemiological studies found an overall increase in risk for PD associated 

with exposure to solvents (OR=1.35 95%CI 1.09-1.67) (Pezzoli and Cereda, 2013).

Carbon disulfide (CS2) has been used as a solvent for phosphorus, asphalt, resins, and rubber 

and as a building block for other substances in organic chemistry. Primarily used in textile,

rubber and cellophane manufacture, this chemical has also been found in soils/sediments and 

ground water samples from DOE’s nuclear weapons facilities across the country (Riley et al.,

1992). According to Site Exposure Matrix, CS2 has been used at DOE sites for activities 

associated with chemistry laboratories, isotope separation, laser research and development, 

and medical equipment sterilization. It is also used in paints, enamels, varnishes, paint 

removers, explosives, rocket fuel, putty preservatives, and rubber cement as well as a solvent 

for waxes, lacquers, camphor, resins, and vulcanized rubber. CS2 is also used as an insecticide 

for soil treatment and grain storage to control insects and nematodes and as an overall process 

solvent (DEEOIC SEM, 2020).

Cardiovascular, developmental and neurotoxic effects have been described following exposures

to CS2 with neurotoxicity involving both central and peripheral nervous system (ATSDR, 1996). 
6

Case reports document four (4) cases of chronically exposed viscose rayon plants’ workers with 

Parkinsonian symptoms following presumably inhalational exposures to CS2. Each of those 

workers had 20 plus years of exposure with three of them working in jobs involving fiber cutting

and cellulose production and one as a painter (Hageman et al 1999; Huang et al., 2004). 

TCE has been widely used as a degreasing and cleaning agent, in metal fabrications, as an 

anesthetic and a building block for number of household chemicals (ATSDR, 2019). Its peak use 

occurred before 1970’s and DOE’s Subsurface Science Program reported TCE as the most 

commonly found solvent in ground water and soil samples collected from or near the disposal 

sites in the nuclear weapons facilities (Riley et al., 1992). SEM documents TCE’s use at DOE

sites for activities associated with boiler and pressure vessel erection, repair, and testing; 

chemistry laboratories; drum/box/container stenciling; dry cleaning; electrical maintenance; 

HVAC maintenance; machining; mechanical maintenance; metal degreasing; painting; 

plumbing/pipefitting; and sheet metal fabrication. Per SEM, Trichloroethylene has also been 

used as an extraction solvent for greases, oils, fats, waxes, and tars; by the textile processing 

industry to scour cotton, wool, and other fabrics; in dry cleaning operations; and as a 

component of adhesives, lubricants, paints, varnishes, paint strippers, pesticides, and cold 

metal cleaners (DEEOIC SEM, 2020)

A link between TCE exposure and Parkinson disease has been reported in case studies and 

epidemiologic observations (Guehl et al., 1999; Kochen et al., 2003). Gash et al. (2008) reported

most recently on a cluster of thirty (30) chronically TCE-exposed workers, all from a small 

measuring instruments manufacturing plant, with Parkinsonian type deficits, three of whom 

were eventually diagnosed with PD. This group of workers ranged in age from 46 to 67 years,

with exposure duration between 8 and 33 years and each of the three workers diagnosed with 

PD held jobs in degreasing metal parts involving daily work in TCE exposure for over 25 years.

The association between TCE exposure and increase in risk of PD has also been shown by 

Goldman et al. in their 2012 nested case - control study of twin pairs from the National 

Academy of Sciences/National Research Council World War II Veteran Twins Registry Cohort.

Ninety-nine (99) twin pair participants in this study who were discordant for diagnosis of PD,

and whose lifetime exposure to solvents was assessed based on self-reports and industrial 

hygiene guided interviews had greater than six-fold increase in risk for PD when exposed to TCE 

up to 2% of work time or one hour per week, compared to those never exposed to TCE (OR=6.1,

95% CI 1.2-33). The risk was also elevated for those exposed to either TCE or perchloroethylene 

(OR=8.9, 95% CI 1.7-47), as well as those with longer duration of TCE exposure (OR=3.2, 95% CI 

1.1-10 for TCE and OR=4.1 95% CI 1.4-11.8 for either TCE or PERC) and highest cumulative 

exposure dose (OR=5.2, 95% CI 1.03-26). Electricians, dry cleaners, industrial machinery 

repairmen and health workers were identified as at risk for most frequent TCE exposure.

In addition, in their assessment of evidence for TCE and tetrachloroethylene (PCE) exposures as 

drinking water contaminants at Camp Lejeune, the ATSDR (2017) concluded, based on animal, 

mechanistic studies and epidemiological evidence from Goldman’s 2012 twins study and Bove 

et al. (2014) study of mortality among Camp Lejeune workers, that the evidence for TCE is 

“equipoise and above for causation for TCE and Parkinson Disease”.
7

Although not yet a presumption, a brief review of up-to-date literature on pesticides is presented below 

to serve as a basis for further review and future recommendations in this area.

Pesticides are a group of chemical compounds used widely in farming, agricultural and 

household applications to control crop health and eliminate rodents (rodenticides), fungus 

(fungicides), plants/weeds (herbicides) and insects (insecticides). Exposure to pesticides has 

been associated with various health outcomes, description of which is beyond the scope of this 

review. However, over the last two decades, a growing number of epidemiological studies have 

been conducted showing these compounds to be a potential risk factor for Parkinson Disease,

with analyses of pooled data repeatedly showing increase in risk and incidence rates of this 

disease (Priyadarshi et al., 2000; Pezzoli and Cereda, 2013; Breckenridge et al.,2016; Ahmed et 

al., 2017; Gunnarson and Bodin, 2018), specifically with occupational exposures (van der Mark 

et al., 2012; Van Maele-Fabry et al., 2012). The systematic reviews also point to a potential 

dose-response relationship with duration of exposure (Yan et al, 2017). While these studies 

provide a wealth of information and identify jobs with highest exposure potential (farmers, 

pesticide applicators, workers in pesticide manufacturing, horticulturists, green house workers, 

and gardeners) the results demonstrate a high degree of variability in studies designs, exposure 

assessment methods, and/or case definitions. Additionally, most studied populations were 

exposed to numerous combinations of pesticides, making attribution of specific compounds 

problematic.

DOE Subsurface Science Research Program reported pesticides among the least commonly 

found compounds, shown in concentrations ranging from trace to parts per thousand in 

soil/sediment samples from two to five facilities and water samples from only one site under 

study (Riley et al. 1992). The use of pesticides throughout the DOE’s weapons complex has been 

documented in DOL’s SEM which provides listing of several products and chemical compounds. 

Some of these compounds, specifically in the insecticides and herbicides groups (paraquat, 

chlorpyriphos, rotenone, maneb, dieldrin, heptachlor and atrazine) have been shown previously 

in animal models to induce dopaminergic cell degeneration and α-synuclein deposition, 

consistent with Parkinsonian pathology (Betarbet et al., 2000; Caudle et al., 2005; Cichetti et al. 

2005; Filipov et al. 2007; Hatcher et al. 2007; Cannon et al. 2009). These compounds have been 

further studied in human studies over the years and while the results indicate increase in risk of 

Parkinson Disease associated with exposures to chlorpyriphos OR= 2.0, 95% CI 1.02–3.8 (Dhilon 

et al. 2008); 2,4-dichlorophenoxyacetic acid OR=2.59, 95% CI 1.03-6.48 (Tanner et al. 2009);

rotenone (OR= 2.5, 95% CI 1.3–4.7) and paraquat OR= 2.5, 95% CI 1.4–4.7 (Tanner et al. 2011),

and the combination of paraquat and maneb OR=1.75, 95% CI 1.13-2.73 (Costello et al. 2009)

the potential for co-exposures to additional pesticide compounds is present in most studies, 

making a conclusive link between any specific pesticide difficult to establish.
8
9
10

In: Postuma RB, Berg D, Stern M, et al. (2015) MDS clinical diagnostic criteria for Parkinson’s 

disease. Mov Disord; 12:1591-1601.
11

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