The burden of occupational cancer in Great Britain Non-Hodgkin’s Lymphoma

Health and Safety
Executive
The burden of occupational cancer
in Great Britain
Non-Hodgkin’s Lymphoma
Prepared by the Health and Safety Laboratory,
the Institute of Occupational Medicine and
Imperial College London
for the Health and Safety Executive 2012
RR864
Research Report
Health and Safety
Executive
The burden of occupational cancer
in Great Britain
Non-Hodgkin’s Lymphoma
Terry Brown
Health and Safety Laboratory
Harpur Hill, Buxton
Derbyshire SK17 9JN
John Cherrie, Martie Van Tongeren
Institute of Occupational Medicine
Research Avenue North
Riccarton
Edinburgh EH14 4AP
Léa Fortunato, Sally Hutchings, Lesley Rushton
Department of Epidemiology and Biostatistics
Imperial College London
Norfolk Place
London W2 1PG
The aim of this project was to produce an updated estimate of the current burden of cancer for Great Britain
resulting from occupational exposure to carcinogenic agents or exposure circumstances. The primary measure
of the burden of cancer was the attributable fraction (AF) being the proportion of cases that would not have
occurred in the absence of exposure; and the AF was used to estimate the number of attributable deaths and
registrations. The study involved obtaining data on the risk of the cancer due to the exposure of interest, taking
into account confounding factors and overlapping exposures, as well as the proportion of the target population
exposed over the relevant exposure period. Only carcinogenic agents, or exposure circumstances, classified
by the International Agency for Research on Cancer (IARC) as definite (Group 1) or probable (Group 2A) human
carcinogens were considered. Here, we present estimates for non-Hodgkin’s lymphoma (NHL) that have been
derived using incidence data for calendar year 2004, and mortality data for calendar year 2005.
The estimated total (male and female) attributable fractions, deaths and registrations for NHL related to overall
occupational exposure is 1.74% (95% Confidence Interval (CI)= 0.03-5.35), which equates to 57 (95%CI=
1-176) attributable deaths and 140 (95%CI= 3-430) attributable registrations.
This report and the work it describes were funded by the Health and Safety Executive (HSE). Its contents,
including any opinions and/or conclusions expressed, are those of the authors alone and do not necessarily
reflect HSE policy.
HSE Books
© Crown copyright 2012
First published 2012
You may reuse this information (not including logos) free of
charge in any format or medium, under the terms of the
Open Government Licence. To view the licence visit
www.nationalarchives.gov.uk/doc/open-government-licence/,
write to the Information Policy Team, The National Archives, Kew,
London TW9 4DU, or email [email protected].
Some images and illustrations may not be owned by the
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ACKNOWLEDGEMENTS
Funding was obtained from the Health and Safety Executive
(HSE). Andrew Darnton from the HSE was responsible for the
work on mesothelioma. The contributions to the project and
advice received from many other HSE and Health and Safety
Laboratory staff is gratefully acknowledged. Two workshops
were held during the project bringing together experts from the
UK and around the world. We would like to thank all those who
participated and have continued to give advice and comment
on the project. We would also like to thank Helen Pedersen
and Gareth Evans for their help in editing and formatting the
reports.
ii
EXECUTIVE SUMMARY
The aim of this project was to produce an updated estimate of the current burden of cancer for Great
Britain resulting from occupational exposure to carcinogenic agents or exposure circumstances. The
primary measure of the burden of cancer used in this project was the attributable fraction i.e. the
proportion of cases that would not have occurred in the absence of exposure; this was then used to
estimate the attributable numbers. This involved obtaining data on the risk of the disease due to the
exposure of interest, taking into account confounding factors and overlapping exposures, and the
proportion of the target population exposed over the period in which relevant exposure occurred.
Estimation was carried out for carcinogenic agents or exposure circumstances classified by the
International Agency for Research on Cancer (IARC) as definite (Group 1) or probable (Group 2A)
human carcinogens. Here, we present estimates for non-Hodgkin’s lymphoma (NHL) that have been
derived using incidence data for calendar year 2004, and mortality data for calendar year 2005.
Dioxins have been classified by the IARC as a definite human carcinogen for NHL and nonarsenical insecticides, tetrachloroethylene, trichloroethylene and occupation as a hairdresser or
barber have been classified by IARC as probable human carcinogens. Occupational exposure to
dioxins can occur in the pulp and paper industry, as a contaminant in the manufacturing process of
certain chlorinated organic chemicals including pesticides, at metal recycling and landfill sites,
during cement manufacture, and at municipal waste incinerators. Occupational exposure to nonarsenical insecticides occurs in farming, forestry and horticulture, in the flour and grain milling
industry and during pesticide manufacture. Occupational exposure to tetrachloroethylene occurs in
the dry cleaning industry and during metal degreasing in manufacturing industries. Occupational
exposure to trichloroethylene also occurred in the dry cleaning industry until the 1950s but has now
been largely replaced by other solvents. The widest use of trichloroethylene is in metal degreasing
in manufacturing industries.
Due to assumptions made about cancer latency and working age range, only cancers in ages 15-84
for men and 15-79 in 2005/2004 could be attributable to occupation. For Great Britain in 2005, there
were 2008 total deaths in men aged 15-84 and 1273 in women aged 15-79 from NHL; in 2004 there
were 4767 total registrations for NHL in men aged 15-84 and 3469 in women aged 15-79.
The estimated total (male and female) attributable fractions, deaths and registrations for NHL
related to occupational exposure is 1.74% (95% Confidence Interval (CI)=0.03-5.35), which equates
to 57 (95%CI=1-176) attributable deaths and 140 (95%CI=3-430) attributable registrations. Results
for individual carcinogenic agents for which the attributable fraction was determined are as follows:
• Dioxins: The estimated total (male and female) attributable fraction for NHL for occupational exposure to dioxins is 0.86% (95%CI=0.00-4.00), which equates to 31
(95%CI=0-142) deaths and 74 (95%CI=0-346) registrations. • Non-arsenical insecticides: The estimated total (male and female) attributable fraction for NHL for occupational exposure to non-arsenical insecticides is 0.38% (95%CI=0.19-0.58),
which equates to 13 (95%CI=7-21) deaths and 33 (95%CI=16-50) registrations. • Tetrachloroethylene: The estimated total (male and female) attributable fraction for NHL for occupational exposure to tetrachloroethylene is 0.20% (95%CI=0.00-1.12), which equates to 7 (95%CI=0-38) deaths and 17 (95%CI=0-94) registrations. • Trichloroethylene: The estimated total (male and female) attributable fraction for NHL for occupational exposure to trichloroethylene is 0.03% (95%CI=0.00-0.07), which equates to 1 (95%CI=0-2) death and 3 (95%CI=0-6) registrations. • Work as hairdresser or barber: The estimated total (male and female) attributable
fraction for NHL for occupation as a hairdresser or barber is 0.19% (95%CI=0.00-0.63), which equates to 5 (95%CI=0-18) deaths and 14 (95%CI=0-48) registrations. iii
iv
CONTENTS 1
INCIDENCE AND TRENDS
1
2
OVERVIEW OF AETIOLOGY
4
2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5
2.1.6
3
Exposures
TCDD (2,3,7,8-tetrachlorodibenzo-para-dioxin)
Non-arsenical Insecticides
Tetrachloroethylene
Trichloroethylene
Hairdressers and Barbers
Other Exposures
7
7
9
10
12
13
15
ATTRIBUTABLE FRACTION ESTIMATION
18
3.1
3.2
General Considerations
TCDD (2,3,7,8-tetrachlorodibenzo-para-dioxin)
3.2.1 Risk estimate:
3.2.2 Numbers exposed:
3.2.3 AF calculation:
3.3
Non-arsenical insecticides
3.3.1 Risk estimate:
3.3.2 Numbers exposed:
3.3.3 AF calculation:
3.4
Tetrachloroethylene (PERC)
3.4.1 Risk estimate:
3.4.2 Numbers exposed:
3.4.3 AF calculation:
3.5
Trichloroethylene (TCE)
3.5.1 Risk estimate:
3.5.2 Numbers exposed:
3.5.3 AF calculation:
3.6
Hairdressers and barbers
3.6.1 Risk estimate:
3.6.2 Numbers exposed
3.6.3 AF calculation
18
19
19
20
21
23
23
23
24
26
26
26
26
29
29
29
31
33
33
33
33
4
OVERALL ATTRIBUTABLE FRACTION
35
4.1
4.2
Summary of results
Exposures by industry/job
35
37
5
BIBLIOGRAPHY
40
6 STATISTICAL APPENDIX
49
v
vi
1 INCIDENCE AND TRENDS Non-Hodgkin’s lymphoma (NHL) (ICD-10 C82-C85; ICD-9 200, 202) is one of two types of cancers of the lymphatic system, the network of lymph glands and channels that occur throughout the body, the other being Hodgkin’s lymphoma (HL). The latter is distinguishable from all other types of lymphoma by the presence of a distinctive abnormal lymphocyte called a Reed-Sternberg
cell (Ekstrom-Smedby, 2006). NHL is not considered to be a single disease but a mixture of
different entities of potentially varying aetiologies (Zinzani, 2005). The majority of NHL arises in
the lymph nodes (70-80%), the remainder are extranodal (Grulich and Vajdic, 2005). Detailed classification of NHL is very complex, and for many years there existed a number of different classification systems that were not easily comparable. Currently, the most widely used is the Revised European American Lymphoma (REAL)/WHO classification (Herrinton, 1998). The system incorporates information on the following features of the tumour: • Morphological: cases of NHL are grouped as being either indolent (slow-progressing or low
grade) or aggressive (high grade);
• Immunological: – allows NHL to be classed as either B-cell, T/NK-cell in origin - over 90%
are B-cell in origin (LRF, 2006);
• Cytogenetic: chromosome translocations are also used to classify the type of NHL, e.g. the
t(8;14) translocation is very strongly associated with Burkitt’s lymphoma.
The REAL/WHO classification system recognises 36 sub-types of NHL (21 of B-cell and 15 of Tcell) that relate to different classes and stages of development of lymphocytes (Ekstrom-Smedby,
2006). In clinical practice NHLs are grouped on morphology and patients are informed whether
their form of lymphoma is indolent (slow growing) or aggressive (Table 1).
Table 1 Grouping of non-Hodgkin’s lymphoma (Source: LRF (2006))
Indolent
Aggressive
Percentage of cases
Curable
30-40%
Rarely with standard treatment
Progression
Morphology
Slow, may not require treatment initially
Usually follicular
60-70%
Potentially with standard
treatment
Rapidly fatal if untreated
Usually diffuse
Internationally, it appears incidence varies in different parts of the world, especially between the
developed and developing world (Ferlay et al, 2001, Grulich and Vajdic, 2005). The highest rates
are thought to exist in the US (17.1 per 100,000), Canada (14.8), New Zealand (14.4) and Australia
(14.3), whereas in developing countries in Western Africa (5.8), the Middle East (6.6) and Eastern
and Southern Central Asia (3.6/3.4) the incidence is much lower. Variations in rates suggest the
importance of environmental effects (Hartge et al, 2006), some known, such as human T-cell
leukaemia virus type 1 (HTLV-1) in the Caribbean and Japan, or HIV in San Francisco, but most
remain unknown. The patterns in the US suggest that the underlying environmental and behavioural
factors are likely to be common to men and women. Some of the areas with the highest mortality
rates are heavily agricultural, so pesticides or other farm-related exposures may play a role. The
main sub-types that occur in developed countries are diffuse B-cell lymphoma (about 30%) and
follicular lymphoma (about 20%), whereas Burkitt’s lymphoma is more common in African
countries (approx. 25-44% of all NHL in Africa).
In the UK, NHL is about seven times more common than HL, with over 8,500 new cases each year
in the UK (Cartwright et al, 2005, LRF, 2006), about 85% of which were seen in England (Table 2).
It is the sixth most common cancer in men, and the seventh most common cancer in women in the
1
UK, the male:female ratio being approximately 1.13:1 (ONS, 2006a). The numbers of cases and
age-standardised incidence rate have shown a steady increase over the past ten years (Table 2).
The UK male age-standardised incidence rate per 100,000 population in 2004 was 15.6 compared to
11.3 for women (ONS, 2006a). NHL incidence rates are more common in older age groups,
increasing sharply in people over 50 years of age, with an average age at diagnosis around 65 (LRF,
2006). Worldwide, the incidence of NHL has progressively increased across all age groups in both
sexes since the 1970s (Grulich and Vajdic, 2005). In England and Wales the age-standardised
incidence rates increased around three-fold in both sexes between 1971 and the late 1990s
(Cartwright et al, 2005), whilst in the GB the rate increased by 6% between 1995 and 2004 (ONS,
2006a), and, given the ageing population this is likely to increase further in the foreseeable future.
NHL incidence rates in each sex show an increase over time in all age groups, most notably in those
over 35 years (Swerdlow et al, 2001). Incidence rates in Wales (Men: 16.0; Women: 10.6) 1 and
Scotland (Men: 16.0; Women: 11.7) 2 are lower than those in England (Men: 17.9; Women: 15.2)3,
with above average rates in London and the South West/East of England (Cartwright et al, 2005).
In 2004 there were a total of 9681 (Men: 5132; Women: 4549) NHL registrations in Great Britain.
Table 2 Number (age-standardised rate, per 100,000) of non-Hodgkin lymphoma
registrations in England, Scotland and Wales, 1995-2005.
Year
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
Average
1995-2005
Men
England3
3427 (14.3)
3428 (14.2)
3492 (14.4)
3725 (15.3)
3980 (16.2)
4084 (17.1)
4146 (17.2)
4117 (17.0)
4280 (17.5)
4399 (17.9)
4622 (18.7)
3973 (16.3)
Scotland2
410 (16.1)
403 (15.4)
408 (15.7)
427 (16.2)
398 (15.0)
396 (14.8)
434 (16.0)
413 (15.1)
468 (16.7)
451 (16.0)
421 (15.7)
Wales1
Women
Total England
Scotland
242 (15.0)
256 (16.0)
223 (13.7)
260 (15.7)
205 (12.3)
209 (12.9)
249 (14.9)
269 (15.6)
288 (16.6)
284 (16.2)
281 (15.7)
4079
4087
4123
4412
4583
4689
4829
4799
2979 (12.0)
2955 (11.8)
3057 (12.2)
3331 (13.3)
3520 (14.0)
3595 (14.3)
3648 (14.4)
3621 (14.3)
384 (11.7)
400 (11.6)
426 (11.8)
430 (12.4)
449 (12.8)
445 (12.7)
372 (10.5)
434 (12.2)
5036
5134
3810 (15.0)
3882 (15.2)
3907 (15.2)
415 (11.6)
427 (11.7)
251 (15.0)
4577
3482 (13.8)
418 (11.9)
Wales
Total
196 (9.7)
202 (10.6)
193 (9.1)
235 (11.3)
219 (11.2)
218 (10.4)
240 (10.8)
251 (12.0)
244 (11.3)
240 (10.7)
267 (12.2)
3559
3557
3676
3996
4188
4258
4260
4306
228 (10.8)
4128
4469
4549
The number of deaths from NHL in Great Britain is consistently around 4,400 per year over the past seven years (Table 3), and in 2005 there were 4,359 deaths. Trends in mortality approximately
follow those in incidence. Since 1960-64, rates in both sexes have more than tripled at ages 70-84,
more than doubled at ages 50-69, and increase by about a half at ages 35-49 (Swerdlow et al, 2001).
Below 35 there has been no change, and in children there has been a large decline. However, since the mid-1990s the rates peaked in the UK and for the last few years have been showing signs of
decrease, currently reaching 6.5 per 100,000 males and 4.3 per 100,000 females in 2005 (ONS, 2006b). The majority of deaths occur in older people (74% in those aged 65 and over). 1
http://www.wales.nhs.uk/sites3/page.cfm?orgid=242&pid=27758
http://www.isdscotland.org/isd/1483.html
3
http://www.statistics.gov.uk/StatBase/Product.asp?vlnk=8843&Pos=&ColRank=1&Rank=240
2
2
Table 3 Number of non-Hodgkin’s lymphoma deaths in England and Wales 1999-2005 (Source: ONS DH2 Series 4 )
Year
1999
2000
2001
2002
2003
2004
2005
2006
Average
1999-2006
England &
Wales
Men
Scotland
Number
Number
(Crude
(Crude
Rate, /100000) Rate, /100000)
2122 (8.4)
201 (7.5)
2091 (8.2)
190 (6.8)
2133 (8.8)
204 (7.4)
2250 (9.3)
200 (7.0)
206 (7.2)
2208 (9.0)
2075 (8.5)
176 (5.9)
2102 (8.5)
194 (5.9)
2122 (6.5)
202 (6.7)
2138 (8.4))
197 (6.8)
Great
Britain
England &
Wales
Women
Scotland
Number
Number
Number
(Crude
(Crude
Rate, /100000) Rate, /100000)
2323
1925 (7.2)
219 (5.7)
2281
1936 (7.3)
229 (5.6)
2337
1932 (7.6)
215 (5.3)
2450
1967 (7.8)
217 (5.1)
211 (5.4)
2414
1922 (7.6)
2351
1863 (7.3)
192 (4.6)
2296
1854 (7.2)
209 (4.8)
2324
1865 (4.2)
195 (4.5)
2335
1908 (7.0)
211 (5.1)
Great
Britain
Number
2144
2165
2147
2184
2133
2055
2063
2060
2119
Mortality rates by country and region of England broadly reflect those for incidence (Cartwright et
al, 2005), although there is less variation. Again mortality rates are above average in London and
the South West/East. Rates in Wales are markedly below those of England and Scotland.
The five-year relative survival rate for NHL in England and Wales was around 50% for patients
diagnosed in the 1990s (ONS, 2003), a significant improvement on the 30% in the early 1970s.
Similar rates are seen in Scotland 5 . Survival rates are consistently higher in women than men.
Cancer mortality to incidence ratios for NHL are 0.44 for men and 0.45 for women.
4
5
http://www.statistics.gov.uk/StatBase/Product.asp?vlnk=618
http://www.isdscotland.org/isd/cancer
3
2 OVERVIEW OF AETIOLOGY The cause of NHL cannot be identified in the majority of cases (COC, 2007, LRF, 2006), and
although many epidemiological studies have been undertaken to investigate the risk factors involved
in the development of NHL summarising the findings from them has proven difficult for a number
of reasons. These include poor exposure classification, poorly defined study populations, small
sample sizes, lack of adjustment for confounding by known risk factors, and lack of studies
examining risk factors by NHL subtype (COC, 2007). One clearly defined risk factor includes
certain viral infections, and those implicated are the Epstein-Barr virus (EBV), the HIV (AIDS)
virus, and human T-cell leukaemia/lymphoma virus (HTLV-1) (Grulich and Vajdic, 2005).
Bacterial infection with Helicobacter pylori is strongly associated with MALT lymphoma affecting
the stomach (gastric maltoma), a rare form of lymphoma that accounts for only ten per cent of cases
(Farinha and Gascoyne, 2005). A strong and well established set of risk factors are characterised by
the dysregulation or suppression of T-cell function, i.e. factors/conditions that precipitate chronic
antigenic stimulation or immunosuppression (COC, 2007, Ekstrom-Smedby, 2006).
Immunosuppressed patients develop NHL at a much higher rate than the general population,
probably because B-cells multiply rapidly in response to certain stimuli and control of this process
relies on the normal function of T-lymphocytes. When this function is disrupted B-cell proliferation
may progress to malignant transformation resulting in a lymphoma. NHL is also seen significantly
more often in patients who are receiving drugs to prevent rejection of a transplanted organ. Obesity
is associated with an increased risk of NHL, because it alters immune and inflammatory responses
and may therefore influence NHL risk. A recent meta-analysis of 16 studies obtained a summary
RR of 1.07 (95%CI – 1.01-1.14) for overweight individuals (BMI 25-30) and 1.20 (95%CI – 1.07­
1.34) for obese individuals (BMI ≥30) (Larsson and Wolk, 2007). Obesity was associated with a
statistically significant increased risk of diffuse large B-cell lymphoma.
A correlation between incidence and ambient solar ultraviolet radiation (UVR) has been
demonstrated in several Western populations (McMichael and Giles, 1996) and in England and
Wales (Bentham, 1996) although the overall evidence for an association between UVR and NHL is
inconsistent. It is proposed that non-ionising radiation (e.g. from mobile phones) may increase the
risk of developing NHL, but again the evidence is very weak (Karipidis et al, 2007).
The Occupational Health Decennial Supplement that examined deaths in England and Wales
between 1979-80 and 1982-90 (Drever, 1995) found that the risk was greater in teachers (in higher
education and not classified) and vocational trainers/social scientists, which is suggestive of the
involvement of a viral factor (Table 4). Industries, including electrical and electronic engineers,
telephone fitters, and radio and TV mechanics, with exposure to electromagnetic fields were also
found to be at a greater risk. In the most recent study that examined deaths between 1991 and 2000,
female schoolteachers were again shown to have an increased risk (Table 5) (Coggon et al, 2009)
together with male telephone fitters and other electrical/electronic trades.
A large US study used death certificates to identify excess NHL mortality among farm managers,
fire-fighters, aircraft mechanics, electronic repairers, mining machine operators and crane/tower
operators (Figgs et al, 1995). In a Canadian case-control study NHL risk was elevated in farmers,
horticulturists, artists, chefs, leather workers, textile workers, rubber workers and janitors (Fritschi
and Siemiatycki, 1996). Studies in Switzerland and the Nordic countries also found excess mortality
in those working in agriculture, physicians, dentists, veterinarians, pharmacists, chemists, butchers
and related occupations, teachers and chemists (Andersen et al, 1999, Bouchardy et al, 2002).
4
Table 4 Job codes with significantly high proportional registration (PRR) and proportional
mortality (PMR) rates for non-Hodgkin’s lymphoma. Men and women aged 20-74 years,
England, 1981-87 (Source: Drever et al. (1995)).
Job group
SIC
Description
code
Men
009
Other administrators
010
Teachers in higher education
011
Teachers, nec
012
Vocational trainers, social scientists,
etc.
015
Doctors
029
Electrical and electronic engineers
(professional)
054
Postal workers
063
Railway station workers
079
Paper manufacturers
087
Man-made fibre makers
135
Office machinery mechanics
139
Telephone fitters
141
Radio and TV Mechanics
142
Other electronic maintenance
engineers
143
Electrical engineers (so described)
163
Assemblers (vehicles and other metal
goods)
169
Builders, etc.
172
Sewage plant attendants
Women
010
Teachers in higher education
011
Teachers, nec
012
Vocational trainers, social scientists,
etc.
047
Farmers
* Number observed
Registrations
Obs*
PRR 95%CI
48
50
3
5
142
139
616
Deaths
Obs
PMR
95%CI
105-189
69
201
54
146
135
134
114-185
117-155
101-175
59
190
145-245
158
60
14
133
142
203
113-155
108-183
111-341
7
73
19
32
299
145
113
161
120-616
113-182
68-176
110-228
68
49
123
148
96-156
109-195
183
16
119
182
103-138
104-295
9
180
111
118
51-211
101-137
104-184
127-1862
8
271
117-535
25
166
108-246
Table 5 Job codes with significantly high proportional mortality rates (PMR) for non­
Hodgkin’s lymphoma. Men and women aged 20-74 years, England, 1991-2000 (Source: Coggon et al, 2009) Job group
SIC code
Description
Number of
Deaths
PMR
95%CI
Men
002
014
041
047
054
063
068
097
104
124
139
142
195
Women
011
014
019
164
188
Accountants & Finance Managers
Clergy
General & Office Managers
Farmers
Postal Workers, Mail Sorters
Railway Station Staff
Leather & Shoe Workers
Printers
Carpenters & Joiners
Machine Tool Operatives
Telephone Fitters
Other Electrical/Electronic Trades
Beauticians & Related Occupations
246
60
233
487
144
41
43
102
259
314
52
131
3
120
139
119
112
127
142
166
129
117
115
152
149
717
106-136
106-178
104-135
102-123
107-150
102-192
120-224
105-156
103-132
103-128
114-200
125-177
148-2096
School Teachers
Clergy
Medical Radiographers
Packers, Sorters & Testers
Fork Lift & Mechanical Truck Drivers
295
18
11
120
3
123
178
239
123
619
110-138
105-281
119-427
102-147
128-1810
IARC have assessed the carcinogenicity of a number of chemicals and those classified as causing
non-Hodgkin’s lymphoma (Group 1), or possibly causing Non-Hodgkin’s lymphoma (Group 2A),
are given in Table 6. From the information included in the IARC assessments Siemiatycki et al.
(2004) further classified the evidence as strong or suggestive, which can also be found in Table 6. In
addition, exposures that have been associated with an increased risk of NHL include radiation,
fumes, organic solvents, PCBs and PBBs, or employment as a teacher or in the woodworking
industry (Hartge et al, 2006).
6
Table 6 Occupational agents, groups of agents, mixtures, and exposure circumstances
classified by the IARC Monographs, Vols 1-98 (IARC, 1972-2007), into Groups 1 and 2A,
which have the NHL as the target organ.
Agents, Mixture,
Circumstance
Main industry, Use
Evidence of
carcinogenicity
in humans
Strength
of
evidence
Other
target
organs
Limited
Suggestive
All sites
Lung
Sarcoma
Group 2A: Probably Carcinogenic to Humans
Agents & groups of agents
Non-arsenical
Production; pest control &
insecticides
agricultural workers; flour
& grain mill workers
Limited
Suggestive
Tetrachloroethylene
Limited
Suggestive
Limited
Suggestive
Brain
Leukaemia
Myeloma
Lung
Cervix
Oesophagus
Liver &
biliary tract
Renal cell
Limited
Suggestive
Group 1: Carcinogenic to Humans
Agents, groups of agents
2,3,7,8­
Production; use of
Tetrachlorodibenzo-para­
chlorophenols &
dioxin (TCDD)
chlorophenoxy herbicides;
waste incineration; PCB
production; pulp & paper
bleaching
Exposure circumstances
None identified
Trichloroethylene
Production; dry cleaning;
metal degreasing
Production; dry cleaning;
metal degreasing
Exposure circumstances
Hairdressers & barbers
Dyes (aromatic amines,
amino-phenols with
hydrogen peroxide);
solvents; propellants;
aerosols
2.1
EXPOSURES
2.1.1
TCDD (2,3,7,8-tetrachlorodibenzo-para-dioxin)
Bladder
Lung
Ovary
TCDD is a member of polychlorinated dibenzodioxins, a group of halogenated organic compounds
that are significant because they act as environmental pollutants. TCDD is the most toxic dioxin,
and became well known as a contaminant of Agent Orange, a herbicide used in the Vietnam War
and when residents of Seveso, Italy, were exposed following a factory explosion in 1976 (Bertazzi
et al, 2001). TCDD has no known commercial applications, but it is used as a research chemical.
TCDD may be formed during the chlorine bleaching process used by pulp and paper mills, and as a
contaminant in the manufacturing process of certain chlorinated organic chemicals, such as
chlorinated phenols and the herbicide 2,4,5-T. TCDD and polychlorinated dioxins (CDD) in
general, are primarily released into the environment during combustion of fossil fuels and wood,
and during incineration processes (although levels are extremely low). A recent report suggested
that potential dioxin production could occur at metal recycling sites, during cement manufacture, at
municipal waster incinerators and landfill sites and during the use of thermal oxygen lances
(Sweetman et al, 2004). A previous study also showed emissions occurred during coke production;
the combustion of coal, waste oil, wood, straw, tyres, chemical and clinical waste; in sinter plants;
7
manufacture of non-ferrous metals, lime, glass, ceramics, halogenated chemicals and pesticides
(Eduljee and Dyke, 1996).
IARC have concluded the strongest evidence for the carcinogenicity of TCDD, based on four highly
exposed cohorts, is for all cancers combined rather than for any specific site (IARC, 1997). The
carcinogenicity of TCDD has been assessed in numerous case-control and mortality cohort studies
of chemical manufacturing and processing workers, and phenoxy herbicide and chlorophenols
applicators. However, epidemiological studies published since 1997 do not provide concrete
evidence concerning the alleged human carcinogenicity of TCDD (Cole et al, 2003).
Numerous studies have examined occupational groups and those accidentally exposed to TCDD and
other dioxins, but as it is mainly a contaminant of industrial processes it is difficult to measure
TCDD exposure directly. Following the industrial accident in Seveso, Italy in 1976 when
substantial quantities of TCDD were vented directly into the atmosphere, the local population have
been extensively studied. The most recent has followed-up the population for 25-years and observed
no increase in all-cause and all-cancer mortality (Consonni et al, 2008). Previous studies have
shown that, after 20-years follow-up, the risk for NHL was non-significantly elevated in the
population of the highest exposed zone (RR=3.3, 95%CI=0.8-13.1) and the lower exposed zone
(RR=1.2, 95%CI=0.5-3.0) (Bertazzi et al, 2001). The latest report indicates a significant excess risk
in the highest exposed zone (RR=3.35, 95%CI=1.07-10.46), but still a non-significant risk in the
lower exposed zone (RR=1.23, 95%CI=0.58-2.60) (Consonni et al, 2008).
In the occupational setting the literature linking TCDD and NHL gives varied risk. A retrospective
mortality cohort study of 5172 workers at 12 plants that produced chemicals contaminated with
TCDD found a non-significant excess of NHL (Fingerhut et al, 1991). Further follow-up of the
cohort identified a total of 12 NHL deaths resulting in a SMR of 1.10 (95%CI=0.56-1.91)
(Steenland et al, 1999).
A Dutch study of 1129 workers exposed to phenoxy herbicides, chlorophenols and contaminants
(including TCDD), employed between 1955 and 1985, and followed-up to the end of 1991,
observed a total of three NHL deaths (Hooiveld et al, 1998). This was among 549 male exposed
workers and resulted in a SMR of 3.8 (95%CI=0.8-11.0).
A German study of 2479 workers exposed to phenoxy herbicides and dioxins at four plants
observed a total of six NHL deaths through 1992 (Becher et al, 1996). This resulted in an overall
SMR of 3.26 (95%CI=1.19-7.10), with increases after ten-years since first exposure (10-<20:
SMR=3.64, 95%CI=0.44-13.14; 20+: SMR=4.25, 95%CI=1.15-10.88).
A New Zealand study of production workers (n=1025) and sprayers (n=703) followed-up from 1969
to 2000 resulted in only two deaths, one in each group of workers (Mannetje et al, 2005). The
SMRs were 0.87 (95%CI=0.02-4.87) and 0.69 (95%CI=0.02-3.84), respectively.
In an IARC historical cohort study of 21,863 workers in 36 cohorts in 12 countries, subjects were
followed from 1939 to 1992 (Kogevinas et al, 1997). A total of 24 NHL deaths were observed in
workers exposed to TCDD or higher chlorinated dioxins (SMR=1.39, 95%CI=0.89-2.00) compared
to nine with no exposure (SMR=1.00, 95%CI=0.46-1.90). The risk of NHL increased with years
since first exposure, but decreased with year of first exposure. Again, no dose-response relationship
was observed with duration of exposure as the metric.
Jones et al. (2009) have carried out a systematic review and meta-analysis in 26 studies of crop
protection production manufacturing workers. The study included the IARC cohort of Kogevinas,
plus a number of others from Europe, USA and China. The summary risk estimate for NHL was
8
1.98 (95%CI=1.45-2.69). In a sub-group of 20 cohorts of workers involved in the manufacture of
phenoxy herbicides the summary risk estimate was 2.01 (95%CI=1.38-2.93).
Bodner et al. (2003) examined the long term mortality of a cohort of 2187 male chemical
production workers previously exposed to substantial levels of dioxin. The cohort was followed-up
between 1940 and 1994 and there were eight NHL deaths observed (SMR=1.4, 95%CI=0.6-2.7). All
exposure to dioxins occurred before 1983. No dose-response relationship was observed, the greater
risk being seen in those with very low exposures.
Studies of cancer risk in the pulp and paper industry have reported no overall increase in cancer
(Langseth and Andersen, 2000, McLean et al, 2006, Rix et al, 1998). In a cohort of 23,718 male
workers employed continuously for at least one year between 1920 and 1993 in Norway there was a
deficit in NHL mortality (<3 years: SMR=0.7, 95%CI=0.29-1.48; >=3 years: SMR=0.9,
95%CI=0.71-1.15) (Langseth and Andersen, 2000). A cohort of 20,953 men and 4,415 women who
worked in Danish paper mills between 1943 and 1990 and followed up to 1993 found a SIR of 1.21
(95%CI=0.80-1.76) among men and 0.55 (95%CI=0.11-1.61) among women (based on 27 and 3
cases, respectively) (Rix et al, 1998). A recent international collaborative study of workers
employed between 1920 and 1996 in 11 countries consisted of 60,468 workers (including the above
two studies) (McLean et al, 2006). The study observed 52 deaths among workers ever exposed to
volatile organochlorines (SMR=0.86, 95%CI=0.64-1.13), and 11 deaths among those with high
exposure (SMR=0.84, 95%CI=0.42-1.51). Among those exposed to non-volatile organochlorine
compounds 25 deaths were observed (SMR=0.86, 95%CI=0.55-1.26). Weighted cumulative
exposure to volatile organochlorines did not show a linear trend with NHL risk.
2.1.2
Non-arsenical Insecticides
Many studies have shown farmers to be at an increased risk of NHL (Descatha et al, 2005).
However, the specific practices associated with the risk vary. In addition, pesticides have been
suggested as risk factors for NHL based on findings from studies of pesticide applicators, pesticide
manufacturers, chemical production workers and military veterans who served in Vietnam
(Alexander et al, 2007). Findings from studies of humans have been inconsistent, and collectively
the epidemiological data do not provide powerful evidence for a causal association between
pesticides and NHL. A recent review of the literature listed over 100 papers reporting an NHL risk
with pesticide exposure (Alexander et al, 2007). The study populations included agriculture and
applicators, producers and manufacturers, case-control (incident) and cohort (incident) studies,
proportional mortality analyses, accidents and environmental exposures. The relative risks ranged
from 0.3 to 10.0; however, no overall summary risk was estimated.
Various meta-analyses have examined the risk of NHL among farmers and shown associations to be
weak. In an analysis of 14 studies of farmers no significant association between farming and NHL
risk was reported (meta-RR=1.05, 95%CI=0.98-1.12) (Blair et al, 1992), whereas an analysis of six
studies among farmers in the central United States found a weak but significant increase in risk
(meta-RR=1.34, 95%CI=1.17-1.55) (Keller-Byrne et al, 1997). The most comprehensive review,
which looked at 36 studies, reported a significant positive association (meta-RR=1.10, 95%CI=1.03­
1.19) (Khuder et al, 1998). However, findings across studies were heterogeneous, and when studies
were analysed according to study design, only the results from case-control studies produced a
significant summary estimate (meta-RR=1.19, 95%CI=1.06-1.33). The summary estimate based on
cohort studies was 0.95 (95%CI=0.85-1.07). Another meta-analysis study on a smaller number of
studies obtained similar summary estimates for eight case-control studies of farmers. The summary
RR was marginally significant (meta-RR=1.13, 95%CI=1.00-1.27), whereas the association based
on eight cohort studies was negative (meta-RR=0.95, 95%CI=0.90-1.00) (Acquavella et al, 1998).
A more recent meta-analysis of 13 case-control studies estimated a meta-RR of 1.35 (95%CI=1.17­
1.55), but found significant heterogeneity and detected publication bias (Merhi et al, 2007). Meta­
9
regression showed that a long period of exposure (>10 years) gave an increase in the risk for NHL
of 1.65 (95%CI=1.08-2.51). Boffetta and de Vocht (2007) identified 50 studies of farmers and
obtained a summary RR of 1.11 (95%CI=1.05-1.17), similar to the results of Khuder et al. (1998).
No association was seen between crop farming and NHL risk, but a greater risk was observed
amongst livestock workers (meta-RR 1.31, 95%CI – 1.08-1.60). Diagnostic analyses did not
indicate the presence of publication bias, but there was significant heterogeneity.The authors
concluded, “Overall, the available evidence supports the hypothesis of a weak association between
farming and NHL risk. Although the quantitative summary estimate of the strength of the
association is uncertain given the heterogeneity in exposure circumstances, it is unlikely that the
excess risk in farmers is higher than 10% to 15%”.
Cohort and case-control studies that evaluated specific pesticides or classes of pesticides generally
have reported inconsistent findings. This may be due, in part, to studies investigating different
exposure scenarios and using different variables to classify the exposures. As examples, reports
from the US Agricultural Health Study that evaluated specific pesticides found no increased NHL
risk (Beane-Freeman et al, 2005, Blair et al, 2005, Bonner et al, 2005, de Roos et al, 2005, Fritschi
et al, 2005a, Mills et al, 2005, Rusiecki et al, 2004, Rusiecki et al, 2006).
Findings from studies of occupationally exposed pesticide production/manufacturing workers,
including studies among phenoxy or chlorophenol production and manufacturing workers (Burns et
al, 2001, Coggon et al, 1991, Hooiveld et al, 1998, Mannetje et al, 2005), triazine manufacturing
workers (MacLennan et al, 2002, Sathiakumar et al, 1996), and alachlor manufacturing workers
(Acquavella et al, 2004) have generally been mixed. Studies of pesticide applicators have generally
shown no excess risk (Cantor and Silberman, 1999, Figa-Talamanca et al, 1993, Swaen et al, 2004,
Zahm, 1997). In a multinational study of workers enrolled in the IARC cohort no significant excess
of NHL mortality was found among workers exposed to phenoxy herbicides or chlorophenols was
reported (SMR=1.27, 95%CI=0.88-1.78), with no exposure-response relationship based on duration
of exposure (Kogevinas et al, 1997).
In the flour and grain industry there is a problem with the use of pesticides to control insect
infestation, which can cause serious financial losses. All areas of the industry are therefore treated
with insecticides to minimise these losses (including grain elevators, mills and processing plants). A
cohort study of 22,938 members of the American Federation of Grain Millers were followed from
1955 to 1985 and observed 21 deaths amongst workers in flourmills (SMR=1.49, 95%CI=0.92­
2.28) and three among workers in other grain industries (SMR=0.30, 95%CI=0.06-0.88) (Alavanja
et al, 1990). A significant trend was found between duration of follow-up and NHL risk, both when
unadjusted and adjusted for age. Furthermore, a significant increased risk was also found in workers
in the maintenance department (OR=8.1, 95%CI=1.4-47.7). Workers in the grain industry as a
whole showed no increased risk of NHL (Observed=24, Expected=24.1; SMR=0.996, 95%CI=0.64­
1.48).
2.1.3
Tetrachloroethylene
Tetrachloroethylene, or perchloroethylene (PERC), is a manufactured chemical compound that is
widely used for the dry cleaning of fabrics and for metal-degreasing in the automotive and other
metalworking industries. It also appears in a few consumer products including paint strippers. It is
extensively used as an intermediate in the manufacture of refrigerants, and in electrical
transformers, printing inks, adhesive formulations, paper coatings, and leather treatments, in aerosol
formulations such as water repellents, automotive cleaners, silicone lubricants and spot removers
(ATSDR, 1997a, IARC, 1995).
In 1995 IARC stated there was limited evidence in humans for the carcinogenicity of PERC and that
it was probable carcinogenic to humans (IARC, 1995). It was classed a Group 2A carcinogen on the
10
basis that there was sufficient evidence in experimental animals. Studies of dry cleaners primarily
exposed to PERC have found an excess risk of NHL. A NIOSH study of 1,708 workers in the US
employed for at least one year before 1960 and followed-up through 1996 observed seven NHL
deaths, with an SMR of 1.39 (95%CI=0.56-2.86) (Ruder et al, 2001). A National Cancer Institute
study of 5,369 members of a dry cleaning union in St. Louis, USA were followed-up through 1993
(Blair et al, 2003). During the period 1948 to 1993 12 deaths from NHL were observed (SMR=0.9,
95%CI=0.5-1.6). A Nordic nested case-control study of laundry and dry-cleaning workers
(N=46768) observed 42 NHL cases belonged to the dry-cleaner group, giving an RR of 0.95
(95%CI=0.65-1.41) (Lynge et al, 2006). When an analysis of risk was carried out by length of
employment no relationship was observed. Walker et al. (1997) investigated 8,163 deaths among
persons formerly employed as laundering and dry cleaning workers in 28 US States between 1979
and 1990. However they did not present any results for NHL.
Katz et al. (1981) analysed the death certificates of 671 female laundry and dry cleaning workers in
Wisconsin, working in the period 1963-1977. Dry cleaning workers, who are more likely to be
exposed to chemicals, could not be separated from laundry workers since they share the same
occupation code. Non-white females accounted for fewer than 3% of all the workers in Wisconsin,
thus were excluded from the analysis for homogeneity reasons. Therefore the cohort consisted of all
white females over the age of 18 years. In addition information on marital status, age at death and
year of death was collected but no adjusted estimates were reported as there were no appreciable
changes in mortality estimates. Firstly, mortality of laundry and dry cleaning workers was compared
to mortality for all other working females during the same time period, but since differences in
mortality patterns may be due to socioeconomic status, mortality of the cohort was secondly
compared to mortality of other, low wage, working females. There was a non-significant elevated
risk of NHL when compared to all other occupations (PMR=1.79); this was similar when the
reference group was altered to include only lower wage occupations (PMR=1.75).
Duh et al. (1984) examined the mortality experiences of 440 laundry and dry cleaning workers in
Oklahoma for the period 1975-1981. Data on age, gender and race were abstracted from death
certificates and mortality estimates were subsequently adjusted. Results are given in terms of an “all
other diseases” reference group, although an additional analysis was conducted using an “all
circulatory disease” reference group, which yielded similar estimates. A decreased risk of NHL was
found amongst the laundry and dry cleaning workers, resulting in SMOR of 0.8 (95%CI=0.1-5.6).
Anttila et al. (1995) conducted a cancer incidence study of 3,974 (2050 males, 1924 females)
Finnish workers exposed to three halogenated hydrocarbons (trichloroethylene (TCE), PERC, 1,1,1­
trichloroethane). Of these 949 (292 males, 557 females) were exposed to PERC. For the whole
cohort exposed to any of the hydrocarbons the SIR was 2.13 (95%CI=1.06-3.80). For those exposed
to PERC over the whole period there were three cases of NHL giving a SIR of 3.76 (95%CI=0.77­
11.0).
In a cohort study of workers at an aircraft maintenance facility there were four deaths from NHL
amongst those exposed to PERC (SMR=3.2, 95%CI=1.2-7.1) (Spirtas et al, 1991). A study of
aircraft manufacturing workers with potential exposure to compounds containing chromate, TCE,
PERC and mixed solvents included 77,965 workers employed for at least one year on or after 1
January 1960 and followed-up through 31 December 1996 (Boice et al, 1999). A total of 215 NHL
deaths were observed (SMR=0.93, 95%CI=0.81-1.06), with 137 occurring amongst factory workers
(SMR=0.94, 95%CI=0.79-1.11). Amongst factory workers there was also a significant trend
between NHL risk and length of employment. Process equipment workers, who worked on tank
lines and received the heaviest exposure to PERC and other chemicals, experienced no significant
increase in NHL (SMR=0.98, 95%CI=0.47-1.81). Process operators and helpers and electroplaters
who routinely worked with vapour degreasers and metal processing tanks where exposure to PERC
and other chemicals was likely showed a non-significant excess of NHL risk (SMR=1.88,
11
95%CI=0.81-3.71). Workers who were routinely exposed to PERC also showed a non-significant
excess NHL risk (SMR=1.70, 95%CI=0.73-3.34). In this group there was no evidence of significant
increase in risk with increasing years of exposure, for those with five-years or more exposure the
risk was 1.41 (95%CI=0.67-3.00).
Two case-control studies found an excess risk of NHL in individuals exposed to chlorinated
hydrocarbons (CH).Fritschi et al. (2005b) identified all incident NHLs between 2000 and 2001 in
two regions of Australia. A total of 694 cases were interviewed, and 43 were found to have been
exposed to CHs. When compared to the unexposed an OR of 1.11 (95%CI=0.70-1.73) was obtained.
Miligi et al. (2006) identified all newly diagnosed cases of malignant lymphomas in men and
women aged 20 to 74 between 1991 and 1993 in eight areas of Italy. A total of 1,428 NHL cases
were interviewed, with 32 having some exposure to PERC. There was no evidence for increased
NHL risk from “very low/low” intensity exposure to PERC (OR=0.6, 95%CI=0.3-1.2) and a non­
significant increased risk from “medium/high” intensity exposure (OR=1.2, 95%CI=0.6-2.5).
In all these studies confidence in the data is low primarily because multiple and overlapping
exposure to more than one chemical was considerable. In addition lifestyle factors, e.g. smoking and
alcohol consumption, were not considered. There was also widespread lack of valid exposure
measurements or other adequate indicators of potential for exposure were also consistent limitation.
A recent critical review of the epidemiological literature on occupational exposure to PERC and
cancer concluded that the current evidence does not support the premise that occupational exposure
to PERC is a risk factor for cancer of any specific site (Mundt et al, 2003).
2.1.4
Trichloroethylene
Trichloroethylene (TCE) is a chlorinated hydrocarbon commonly used as an industrial solvent for a
variety of organic materials. TCE has been widely used in the past as a degreaser for metal parts but
since the 1950s this has declined, although recently there has been resurgence in its use. Five main
industrial groups use TCE in vapour or cold degreasing operations: furniture and fixtures, fabricated
metal products, electrical and electrician equipment, transport equipment, and miscellaneous
manufacturing industries (IARC, 1995). TCE can be used as an extraction solvent and a chemical
intermediate, and as a component in adhesives, lubricants, paints, varnishes, paint strippers,
pesticides and cold metal cleaners (ATSDR, 1997b). From the 1930s to the 1960s TCE was used as
a volatile gas anaesthetic. The current 8-hour TWA Workplace Exposure Limit is 100ppm, and 15
minute maximum is 150ppm. According the CAREX there were 16,336 workers exposed to TCE
between 1990 and 1993.
In 1995 IARC stated there was limited evidence in humans for the carcinogenicity of TCE and that
it was probable carcinogenic to humans (IARC, 1995). It was classified as a Group 2A on the basis
that there was sufficient evidence in experimental animals.
Epidemiological studies of TCE have included occupational cohort studies, nested and populationbased case-control studies. The main occupations involving TCE-exposure that have been studied
involve metal degreasing and aircraft/aerospace maintenance or manufacturing work. Other
industries with potential exposure to TCE include the iron/steel industries, painting, the electronics
industry, the chemical industry, the printing, shoe manufacturing and jewellery manufacturing,
where it has been used as a degreaser and as a general solvent. In all of the studies few, if any, of the
workers were exposed to TCE exclusively.
Three cohort studies have investigated workers exposed to TCE in cleaning of metal parts in the
aircraft industry. Garabrant et al. (1988) investigated 14,067 workers in San Diego, California
between 1958 and 1982. A total of 13 NHL deaths were observed in the cohort with an SMR of 0.8
(95%CI=0.4-1.4). However, only 37% of the jobs held in the plant, entailed exposure to TCE. A
12
second study included 20,535 employees from Tucson, Arizona from 1958 to 1987 (Wong and
Morgan, 1990). All subjects were apparently potentially exposed to TCE through the drinking
water, but 4,733 were also potentially exposed occupationally. Among the cohort three NHL deaths
were observed resulting in an SMR of 1.1 (95%CI=0.3-3.2). A more recent follow-up of the cohort
through 1993 resulted in an additional six deaths and an SMR of 1.01 (95%CI=0.46-1.92) (Morgan
et al, 1998). A study was carried out of 14,457 civilians employed in Utah from 1952-1956, and
followed-up to the end of 1982 (Spirtas et al, 1991, Stewart et al, 1991). Of these, 7,282 were
known to have been exposed to TCE, amongst whom there were 14 NHL deaths (SMR=1.3,
95%CI=0.7-2.2). Further follow-up of the cohort through 1990 resulted in an additional 14 deaths
amongst the exposed workers (Blair et al, 1998). An SMR was not reported for this group overall
but a rate ratio of 2.0 (95%CI=0.9-4.6) for the whole follow-up period was estimated comparing
those exposed with workers not exposed to any chemicals. No dose-response relationship was seen
between NHL risk and cumulative exposure to TCE (in unit-years).
In the Finnish study of workers exposed to halogenated hydrocarbons (see PERC section) 3089 (1,699 males, 1,391 females) were exposed to TCE (Anttila et al, 1995). In this sub-cohort over the whole follow-up period the SIR was 1.81 (95%CI=0.78-3.56). The study also found an increasing
NHL risk with years since first measurement, but not with mean personal urinary trichloroacetic acid (Table 7). Table 7: Mean personal levels of urinary trichloroacetic acid and risk of NHL
Years since first
measurement
0-9
10-19
20+
SIR (95%CI)
Urinary
trichloroacetic acid
(µmol/L)
SIR (95%CI)
0.83 (0.02-4.64)
1.75 (0.48-4.47)
3.24 (0.67-9.45)
<100
100+
2.01 (0.65-4.69)
1.40 (0.17-5.04)
Source: Anttila et al. (1995)
A study of workers at Danish companies using TCE did not find any significant excess of NHL
incidence (Raaschou-Nielsen et al, 2003). Cancer incidence between 1968 and 1997 was evaluated
in a cohort of 41,049 blue-collar workers in 347 Danish companies with documented TCE use. In
men the SIR was 1.2 (95%CI=0.98-1.52) and in women it was 1.4 (95%CI=0.73-2.34). The study
showed a clear relationship between NHL risk and duration of employment in both men and
women.
In a comprehensive review of over 80 published papers (including cohort, case-control, communitybased and case series studies) and letters there was evidence of excess cancer incidence among
occupational cohorts with the most rigorous exposure assessment for NHL (RR=1.5, 95%CI=0.9­
2.3; weighted average) (Wartenberg et al, 2000). However, the authors noted that many of the
results were likely to be confounded by exposure to other solvents and other risk factors not
accounted for in the analysis. A more recent meta-analysis of 14 cohort and four case-control
studies of workers exposed to TCE estimated a summary RR of 1.29 (95%CI=1.00-1.66) from the
cohort studies that had more detailed information on TCE-exposure (Mandel et al, 2006). For the
studies (n=7) that identified a specific TCE-exposed sub-cohort the SRR was 1.59 (95%CI=1.21­
2.08). No significant dose-response relationship was found. Scott and Chiu (2006) reviewed studies
and literature reviews published since 2000 and concluded that the lymphatic system was a target of
TCE toxicity suggesting a moderately elevated risk (typically 1.5-2.0).
2.1.5
Hairdressers and Barbers
Population-based studies of the use of hair dyes have shown conflicting results regarding risk from
NHL. A case-control study conducted in Connecticut in 1996-2002 of 601 female NHL cases found
13
an increased risk among those who reported use of hair-colouring products before 1980 (OR=1.3,
95%CI=1.0-1.8) (Zhang et al, 2004). The odds ratios were 2.1 (95%CI=1.0-4.0) for those using
darker permanent hair-colouring products for more than 25-years and 1.7 (95%CI=1.0-2.8) for those
who had more than 200 applications. Another study of 2,544 NHL cases in the San Francisco Bay
area found risks were not elevated for women for use of any hair-colour products; men who ever
used semi-permanent hair colour had slightly elevated risks, with trends associated with greater
lifetime frequency of use and frequency of use per year (Holly et al, 1998).
A large prospective study of over 500,000 US women showed an increased risk of NHL in those
who used dyes for 10 or more years (Altekruse et al, 1999). They found an age-adjusted RR of 1.0
for those who ever used hair dyes. The RR was further adjusted for other factors including smoking,
education and other exposures, but no change in risk was found (RR=1.0; 95%CI=1.0-1.3). Miligi et
al. (2005) interviewed 2737 NHL cases and found no association with hair dye use and NHL risk. A
review of ten studies in hair dyes and lymphomas found no association with ever use of dyes and
inconsistent associations with the use of permanent dyes (Correa et al, 2000). A meta-analysis of 14
cohort and case-control studies, however, obtained a meta-RR of 1.16 (95%CI=1.07-1.26; fixedeffects) and meta-RR of 1.23 (95%CI=1.07-1.42; random-effects) (Takkouche et al, 2005). The
authors concluded that evidence for a causal effect was too weak for this to represent a major public
health concern.
In 1983, Kono published a report investigating causes of death among Japanese female beauticians
(Kono et al, 1983). Information was collected on 7,736 female beauticians who were registered
between 1948 and 1960 in Fukuoka Prefecture at the Department of Public Health. The follow-up
period was from 1953 to 1978, in which time 488 deaths (5 due to ovarian cancer) were recorded.
The general Fukuoka Prefecture population was used for reference. However, no cases of NHL were
reported.
Spinelli collected information on all deaths occurring in the province of British Columbia over the
period 1950 through 1978 from the Canadian Division of Vital Statistics (Spinelli et al, 1984). All
subjects that were over 20 years of age at death with complete records were included in the analysis.
The cohort consisted of 254,901 males and 165,913 females. Again no NHL cases were reported
Teta et al. (1984) examined cancer incidence in 13,650 (11,845 female and 1,805 male) Connecticut
cosmetologists, who had held a hairdressing licence for more than 5 years and had trained before
1966. The follow-up for cancer began in 1935 and continued to 1978. The general Connecticut
population was used for comparison. An elevated risk of NHL was reported with SIR of 1.29
(95%CI=0.81-1.95). Examining incidence by year of entry, showed females entering the occupation
in the period 1925-1934 had an SIR of 0.95 (95%CI= 0.31-2.22), whereas for females with a first
licence after 1935 the SIR was 1.44 (95%CI=0.84-2.30).
A cohort of 3,637 female and 168 male hairdressers in Finland from the Finnish Cancer Registry
were followed up for cancer incidence throughout the period 1970-1987 (Pukkala et al, 1992). The
study was restricted to members of the association who were born in or before 1946 and were
members between 1970 and 1982. Risk estimates were age adjusted. During the 18-year follow-up
there were no cases of NHL reported.
In 1994, Boffetta et al. (1994) conducted an incidence study on 29,279 female hairdressers
identified from the 1970 censuses of Sweden, Norway, Finland (age 25-64 years), and Denmark
(age 20-64 years). A National Cancer Registry exists in these four countries from which 36 NHL
cases were identified (Denmark: 16, Sweden: 8, Norway: 5 and Finland: 7). The all-female
population from the censuses was used as the reference and all estimates were age adjusted. Data
from Sweden, Norway and Finland covered the period 1971 to 1985, whereas data from Denmark
covered the period 1971 to 1987. The overall SIR was elevated with value 1.20 (95%CI=0.84-1.66).
14
The excess was observed in all countries with the exception of Sweden (SIR=0.63, 95%CI=0.27­
1.24).
In a study of 7.2 million death certificates in 24 US States from 1984 to 1995, 38,721 were among
hairdressers and barbers (Lamba et al, 2001). A significant excess of NHL was found amongst
white men and women, whereas a non-significant excess was found for black men, and no excess in
black women (only one death), who were hairdressers. No excess was seen amongst barbers. A
follow-up of a cohort of over 45,000 (38,806 females, 6,824 males) Swedish hairdressers followedup between 1960 and 1998, however, did not find any excess risk (Czene et al, 2003). A total of 93
NHL cases were observed (29 male, 64 female) for individuals who stated that they were a
hairdresser at any census. The NHL risk was not raised for both males (SIR=0.91, 95%CI=0.61­
1.31) and females (SIR=0.94, 95%CI=0.72-1.20).
2.1.6
Other Exposures
Animals
Occupations that involve exposure to animals warrant attention because of the plausibility of
transmission of zoonotic infections. Abattoir workers have shown increased NHL risk in some
studies (Johnson et al, 1995, Metayer et al, 1998, Pearce et al, 1988), as have workers involved in
farm animal breeding and raising cattle (Fritschi et al, 2002, McDuffie et al, 2002). A recent meta­
analysis detected no overall association (meta-RR: 0.99; 95%CI: 0.77-1.29), but exposure
circumstances of studies included in the analysis were highly heterogeneous, and suggested it is
premature to decide on the presence and absence of risk of NHL among meat workers (Boffetta and
De Vocht, 2007). The analysis included a study of a cohort of 1610 UK meat workers in which the
RR for NHL was 0.7 (95%CI=0.0-3.8) (Coggon et al, 1989).
Wood Work
Occupations involving contact with wood and wood products have been associated with increased
NHL risk in a number of studies conducted in U.S., New Zealand, Finland and Sweden (Persson,
1996, Reif et al, 1989). It is not clear whether the risk is due to wood itself, to chemicals applied to
wood (e.g. wood preservatives), or other chemicals used for woodwork. Some have suggested that
exposure to wood preservatives, such as chlorophenols, causes an increased risk (Scherr and
Mueller, 1996). The increased risk has been attributed to the contaminant TCDD and other dioxins,
which are present at varying concentrations in chlorophenols depending upon production methods.
Demers et al. (1995) carried out a pooled analysis of five cohort studies and found an SMR of 1.1
(95%CI=0.8-1.4) amongst workers occupationally exposed to wood dust. A meta-analysis of 11
studies estimated a summary RR of 1.15 (95%CI: 1.00-1.31) (Boffetta and De Vocht, 2007).
However, there was significant publication bias.
Printers
A number of population-based case-control studies have investigated the association between NHL
and employment in the printing industry, all showing an increased risk (Boffetta and De Vocht,
2007). Two cohort studies have also shown an increased NHL risk (Cano and Pollan, 2001,
Rafnsson, 2001). Similar workers in the US were observed to have a significant excess risk,
especially those with more than 10 years employment (OR=1.48; 95%CI=0.87-2.52) (Dryver et al,
2004). A recent meta-analysis of seven studies obtained a summary RR of 1.86 (95%CI: 1.37-2.52)
and found no evidence of publication bias and heterogeneity (Boffetta and De Vocht, 2007).
15
Teaching
An association between employment as a teacher and increased risk of NHL has been suggested in
several studies (Alexander et al, 2007, Grulich and Vajdic, 2005). A meta-analysis of 13 studies
(RR range: 0.31-3.60) provided a summary RR of 1.36 (95%CI: 1.13-1.62) (Baker et al, 1999).
However, the authors suggested that results may have been affected by publication bias. A more
recent study of 19 studies obtained a summary RR of 1.47 (95%CI: 1.34-1.61) (Boffetta and De
Vocht, 2007). These results lend support for an association between teaching and increased risk for
NHL, but heterogeneity and evidence of publication bias suggest the summary RR might be
inflated. However, the association supports the hypothesis of a viral aetiology of NHL.
Asbestos
Asbestos exposure was originally linked to NHL in early studies, but subsequently no association
was found (Becker et al, 2001).
Benzene
Benzene has the potential to produce chromosome changes and other genetic changes of importance
in NHL induction. A recent review identified 43 case-control studies of NHL outcomes that
included subjects with probable occupational exposure to benzene, but no meta-analysis was carried
out (Smith et al, 2007). Forty of these 43 studies showed an elevation of NHL risk, with 23 finding
a statistically significant association between NHL risk and probable benzene exposure. The review
also identified 26 studies of petroleum refinery workers reporting morbidity or mortality for
lymphomas and found that in 23 the risk for lymphomas was greater than that for all neoplasms.
The authors stated that these findings, coupled with those in experimental animal and clinical
studies, suggest further work is needed to elucidate the mechanisms involved. A previous review of
21 study groups pooled data from all the studies and found an observed to expected numbers of
cases ratio of 1.04 (95%CI=0.94-1.14) (Lamm et al, 2005). After removal of studies with multiple
chemical exposure problems the OR was reduced to 0.96 (95%CI=0.86-1.06).
Electrical Workers
Several studies have investigated the potential roles of electromagnetic fields in causation of NHL.
Two recent studies found positive associations between extremely low frequency (60Hz) magnetic
fields and NHL, with an apparent threshold (>40V/m) in one study (OR=3.57, 95%CI=1.30-9.80)
(Villeneuve et al, 2000) and without a clear dose-response in the other (Schroeder and Savitz,
1997). Schroeder and Savitz (1997) suggest that results from earlier studies were suggestive of an
association although, more recent studies (employing individual exposure assessment) did not
confirm this.
Radiation
A review published over 15 years ago concluded that exposure to radiation has rarely been
implicated as a cause of lymphomas (Boice, 1992). Atkinson et al (2004) reported no significant
excess of NHL death among radiation workers (SMR=1.12, 95%CI=0.84-1.40) or internally
monitored radiation workers (SMR=0.88, 95%CI=0.49-1.46) in an updated cohort study of the UK
Atomic Energy Authority workforce. No significant associations were reported in Sellafield, the
Atomic Weapons Establishment, Hanford, Japanese or combined US, UK and Canadian cohorts
(Cardis et al, 1995, Carpenter et al, 1994, Carpenter et al, 1998, Douglas et al, 1994, Kendall et al,
1992, Muirhead et al, 1999, Omar et al, 1999). Studies of radiologists and radiology technicians
have given contrasting results with reports from the US reporting no significant associations (Doody
et al, 1998, Linet et al, 2005, Matanoski et al, 1975, Mohan et al, 2003, Sigurdson et al, 2003),
whereas a significant excess of NHL deaths was reported among British radiologists (Berrington et
al, 2001).
16
Polychlorinated Biphenyls and Polybrominated Biphenyls
Polychlorinated Biphenyls (PCB) and Polybrominated Biphenyls (PBB) are industrial chemicals
that were used extensively until their production and certain uses were banned in the 1970s and
1980s. Polychlorinated biphenyls (PCBs) were widely used as a capacitor filling fluid due to its
electrical isolation properties, as well as fire resistance and very slow degradation. They have also
been used as plasticizers in furnishers, in building construction, in paints, in self-carbonising copy
paper and as lubricants. These lipophilic chemicals tend to persist in the environment, have long
biological half-lives, and bio-accumulate in the food chain. As a result, exposure of the general
population to these chemicals has occurred primarily through diet and through employment in
certain occupations. PCBs are carcinogenic to experimental animals, and are classified as probably
carcinogenic to humans by IARC (IARC, 1987). Exposure to PCBs was associated with increased
risk of NHL in two case-control studies (Hardell et al, 1997, Rothman et al, 1997). However, as
reviewed by Rothman et al. (1997) other studies on NHL and PCB have produced mixed results.
Recent reviews of the carcinogenicity of PCBs reported no excess risk of NHL among exposed
cohorts (Knerr and Schrenk, 2006), indicating a summary SMR of 1.04 (95%CI=0.91-1.19).
17
3 ATTRIBUTABLE FRACTION ESTIMATION
3.1
GENERAL CONSIDERATIONS
Substances and Occupations
IARC have assessed the carcinogenicity of a number of substances and occupational circumstances
with those classified as Group 1 having sufficient evidence in humans and those classified as Group
2A having limited evidence in humans. Table 8 shows agents and exposure circumstances classified
as Group 1 or 2A for leukaemia.
Table 8 Substances considered in the estimation of the attributable fraction for non­
Hodgkin’s lymphoma.
Agents, Mixture, Circumstance
Group 1: Carcinogenic to Humans
Agents, groups of agents
2,3,7,8-Tetrachlorodibenzo-para­
dioxin (TCDD)
Exposure circumstances
None identified
AF
calculation
Y
Comments
Comments
Suggestive
Group 2A: Probably Carcinogenic to Humans
Agents & groups of agents
Non-arsenical insecticides
Y
Tetrachloroethylene
Y
Trichloroethylene
Y
Exposure circumstances
Hairdressers & barbers
Y
Suggestive
Suggestive
Suggestive
Suggestive
Data Relevant to the Calculation of AF
The two data elements required are an estimate of relative risk (RR), and either (1) an estimate of
the proportion of the population exposed (Pr(E)) from independent data for Great Britain, or (2) an
estimate of the proportion of cases exposed (Pr(E|D)) from population based study data.
The RR chosen from a ‘best study’ source is described for each exposure, with justification of its
suitability. Information on the ’best study’ and independent data sources for the proportion of the
population exposed are also summarised for each exposure in the appropriate section below. In the
absence of more precise knowledge of cancer latency, for haematopoietic malignancies a latency of
between 0 and 20 years has been assumed for all types of the cancer. Therefore it is assumed that
exposure at any time between 1986 and 2005 (the Risk Exposure Period, REP) can result in a cancer
being recorded in 2004 as a registration or in 2005 as an underlying cause of death. Although
strictly speaking the REP for cancer registrations recorded in 2004, the year for which estimation
has been carried out, would be 1985-2004, for simplification the years 1986 to 2005 have also been
used, as for deaths, as the proportion exposed will not be affected. For an independent estimate of
the proportion of the population exposed, numbers of workers ever exposed during this period are
counted using a point estimate of exposed workers taken from the period. A point estimate is used
that is as close as possible to the mid-point of the REP for estimating numbers ever exposed across
the period (for which a linear change in employment levels is implicitly assumed). If this is from
CAREX relating to 1990-93, an adjustment is made to take account of gross changes in employment
levels which have occurred particularly in manufacturing industry and the service sector across the
18
REP. Where the LFS is used 1991 is used. A turnover factor is applied to estimate numbers ever
exposed during the REP, determined mainly by the estimate of staff turnover per year during the
period. For each exposure therefore, if an AF has been based on independent estimates of numbers
exposed, the table of results includes the point estimate of numbers employed, the adjustment factor
for CAREX if applicable, the staff turnover estimate, and the resulting estimate of numbers ever
exposed during the REP. Other estimates used in the calculations that remain constant across
exposures (unless otherwise stated) are given below:
• Number of years in REP = 20 Proportion in the workplace ever exposed is set to one, i.e. all
are assumed to be exposed, in the absence of more detailed information. Where sources
other than CAREX are used for the point estimate of numbers exposed, such as the LFS or
Census of Employment, a precise as possible definition of workers exposed is sought.
• Numbers ever of working age during the target REP = 23.0 million men, 23.1 million
women. This is the denominator for the proportion of the population exposed, and is based
on population estimates by age cohort in the target year.
• Total deaths from NHL, Great Britain, 2005 = 2008 for men aged 15-84 (1830 in England
and Wales, 178 in Scotland), 1273 for women aged 15-79 (1145 in England and Wales, 128
in Scotland).
• Total registrations for NHL, Great Britain, 2004 = 4767 for men aged 15-84 (4078 in
England, 263 Wales, 426 in Scotland), 3469 for women aged 15-79 (2953 in England, 179
Wales, 337 in Scotland).
Attributable numbers are estimated by multiplying the AF by the total number of cancers in GB.
Only cancers which could have been initiated during the risk exposure period are counted, taking
normal retirement age into account. Therefore for solid tumour cancers, total deaths or registrations
recorded at all adult ages (25+) are used to estimate attributable numbers, and for short latency
cancers, deaths and registrations for ages 15-84 for men and 15-79 for women are used.
For each agent where data on worker numbers are only available for men and women combined
(CAREX data), the assumed percentage of men is given in addition to the numbers exposed. The
allocation to high and low, and occasionally negligible, exposure level categories, or division into
separate exposure scenarios, is also included in these tables. Where no separate estimate of relative
risk is available for the low exposure level category, an estimate is based on an average of the
high/low ratios for cancer-exposure pairs for which data were available.
Full details of the derivation of the above factors and the methods of calculating AF are published
separately. Unless otherwise stated, Levin’s method is used for estimates using independent
estimates of numbers exposed, and Miettinen’s method is used for study based estimates. A
summary of the methodology is given in the Statistical Appendix.
3.2
3.2.1
TCDD (2,3,7,8-TETRACHLORODIBENZO-PARA-DIOXIN)
Risk estimate:
Only a small proportion of workers in agricultural occupations (Farmers, etc.) and in the
manufacture of pesticides will be exposed to dioxins as contaminants of phenoxy-herbicides and for
only a few days in the year. Therefore, these occupations will not be considered under this section
but under non-arsenical insecticides, which will be the predominant exposure.
For workers in pulp manufacture the international collaborative study of 98,665 workers employed
between 1920 and 1996 in 11 countries, including Scotland, Japan, New Zealand, United States, and
19
Europe (8), found an overall risk for NHL of less than unity (McLean et al, 2006). Therefore, for
this group a RR of 1.0 will be used (risk estimate M in Table 10).
Sweetman et al. (2004) and Eduljee and Dyke (1996) identified a number of work sites in the UK
where occupational exposure to dioxins could occur. The sites with possibly the highest exposures,
greater than in pesticide production, included metal recycling, ferrous metal production, zinc
smelting, cement manufacture, municipal waste incinerators, coal power stations and workers on
landfill site. The NHL risk in workers at these sites is unknown. A number of studies have reported
an excess NHL risk in workers exposed to TCDD contaminated chemicals (section 2.1.1). Bodner et
al. (2003) examined NHL mortality in a cohort of 2187 workers from the Dow chemical company
involved in production and exposed to dioxins. The cohort was followed-up between 1940 and 1994
and observed eight NHL deaths. A SMR of 1.4 (95%CI=0.6-2.7) was obtained which will be used
for all the other occupational groups (risk estimate K in Table 10). Using this risk value involves the
assumption that dioxin exposures in this cohort are similar to those of the workers at the various UK
work sites.
Jones et al. (2009) have carried out a systematic review and meta-analysis in 26 studies of crop
protection production manufacturing workers. The study included the IARC cohort of Kogevinas,
plus a number of others from Europe, USA and China. The summary risk estimate for NHL was
1.98 (95%CI=1.45-2.69) and has been used for this group of workers (risk estimate J in Table 10).
3.2.2
Numbers exposed:
Table 9 gives the numbers of workers possibly exposed to dioxins in the production of pesticides,
pulp manufacture and the other industries listed above according to the LFS for 1991. A screening
of a range of industrial processes operating in the UK for the potential to release dioxins, shortlisted 23 processes for consideration as potential emitters (Eduljee and Dyke, 1996). They include
the combustion of coal (industrial/commercial, power generation), waste oil, municipal waste,
wood, straw, tyres, landfill gas, chemical waste, clinical waste and sewage sludge. Other processes
included industries involved in treated wood, gas production, sinter plants iron and steel, non­
ferrous metals, manufacture of cement, lime, glass and ceramics, halogenated chemicals, carbon
regeneration, asphalt mixing and PCP in timber processes, and pesticide production. According to
this study pesticide production had an emission factor of 0.01-0.025 µg I-TEQ of dioxin per tonne
of product produced. They estimated that about 12,950 tonnes of product were produced in a year,
which equated to between 130 and 325 µg I-TEQ of dioxin. On the basis of emission factors from
the study by Eduljee and Dyke (1996) the occupations with the potential for exposure to dioxins
greater than those in pesticide production are given in the lower half of table 9.
20
Table 9 Number of workers in different industries with potential for exposure to TCDD in
1991 (Source: Labour Force Survey)
SOC/SIC
Code
1991
0100
0200
Job Title
Number employed
Agriculture & horticulture
Forestry
Gardeners & Groundsmen
Risk
estimate
Men
421820
19012
131962
Women
118624
4318
7459
Total
540444
23330
139421
1343
1084
2427
J
2568
Formulated pesticide manufacture
4710
Pulp manufacture
40620
12579
53199
M
4610
2512
2471
2478
2479
2481
2489
2420
2210
2220
2234
2235
2245
2246
2247
Wood sawmill planning impregnation
Organic chemical manufacture
Flat glass manufacture
Glass containers
Other glass products
Refractory goods
Ceramic goods
Cement, lime, & plaster manufacture
Iron & steel industry
Steel tubes
Steel wire & wire products
Other drawing cold rolling forming of steel
Aluminium & aluminium alloys
Copper, brass & other copper alloys
Other non-ferrous metals & their alloys
Scrap dealers & metal merchants
9191
5472
15158
5489
20647
7731
24447
9434
90164
30233
15225
8146
19969
9228
6863
7152
1172
3881
2559
6531
1113
18338
1195
9395
3612
2989
799
3704
4467
657
9191
6644
19039
8048
27178
8844
42785
10629
99559
33845
18214
8945
23673
13695
7520
7152
K
K
K
K
K
K
K
K
K
K
K
K
K
K
K
K
3.2.3
AF calculation:
The estimated total (male and female) attributable fraction for NHL for occupational exposure to dioxins is 0.86% (95%CI= 0.00-4.00), which equates to 31 (95%CI=0-142) deaths and 74
(95%CI=0-346) registrations. The estimated AF for men is 1.27% (95% CI=0-5.9) resulting in 25
(95% CI=0-118) attributable deaths and 61 (95% CI=0-281) attributable registrations, and for women the AF is 0.40% (95% CI=0-1.88) resulting in 5 (95% CI=0-24) attributable deaths and 14
(95% CI=0-65) attributable registrations (Table 10). 21
Table 10 Summary results for occupational exposure to TCDD
Men
Risk Estimate
Reference
Exposure
Jones et al. (2009)
J
J
Main
Industry
Sector1
C-E
All
M
M
Data
2
3
RR
Ne
Carex
adj4
Calculations
5
6
NeREP
TO
7
PrE
Attributable Fraction
8
(Lenvins ) and Monte
Carlo Confidence Interval
AF
LL
UL
Attributable
Registrations
Attributable
Deaths
AN
LL
UL
AR
LL
UL
1.98
1343
1343
1
0.09
3450
3450
0.0002
0.0002
0.0001
0.0001
0.0001
0.0001
0.0003
0.0003
0
0
0
0
1
1
1
1
0
0
1
1
C-E
All
1
40620
40620
1
0.09
104359
104359
0.0045
0.0045
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0
0
0
0
0
0
0
0
0
0
0
0
K
K
All
J
J
C-E
All
All
C-E
All
1.4
284549
284549
326512
1084
1084
1
0.09
1
0.14
731053
731053
838863
3993
3993
0.0318
0.0318
0.0365
0.0002
0.0002
0.0126
0.0126
0.0127
0.0002
0.0002
0.0000
0.0000
0.0000
0.0001
0.0001
0.0588
0.0588
0.0590
0.0003
0.0003
25
25
25
0
0
0
0
0
0
0
118
118
118
0
0
60
60
61
1
1
0
0
0
0
0
280
280
281
1
1
M
M
C-E
All
12579
12579
1
0.14
46338
46338
0.0020
0.0020
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0
0
0
0
0
0
0
0
0
0
0
0
K
C-E
1.4
60412
K
All
60412
All
All
74075
1. Specific scenario or main industry code (Table A1)
2. Relative risks selected from the best study
3. Numbers exposed, allocated to men/women
4. CAREX adjustment factor to mid-REP (Table A1)
5. Staff turnover (TO, Table A1)
6. Number ever exposed during the REP (Statistical Appendix equation 3)
7. Proportion of the population exposed (Pr(E), Statistical Appendix equation 4)
8. Statistical Appendix equation 1 1
0.14
222542
222542
272873
0.0096
0.0096
0.0118
0.0038
0.0038
0.0040
0.0000
0.0000
0.0000
0.0186
0.0186
0.0188
5
5
5
0
0
0
24
24
24
13
13
14
0
0
0
65
65
65
McLean et al,
2006
Bodner et al.
(2003)
Women
Jones et al. (2009)
McLean et al,
2006
Bodner et al.
(2003)
1.98
1
22
3.3
3.3.1
NON-ARSENICAL INSECTICIDES
Risk estimate:
A number of meta-analysis studies have been undertaken over the past 25-years examining the
risk of NHL among farmers, the occupational group that have the greatest risk of exposure to
non-arsenical insecticides, have shown a weak positive association (Acquavella et al, 1998,
Blair et al, 1992, Boffetta and De Vocht, 2007, Keller-Byrne et al, 1997, Khuder et al, 1998,
Merhi et al, 2007). Boffetta and de Vocht (2007) concluded that overall the available evidence
supports the association, and that as the quantitative summary estimate of the strength of the
association is uncertain given the heterogeneity in exposure circumstances, it is unlikely that the
excess risk in farmers is higher than 10% to 15%. The summary RR obtained by Boffetta and de
Vocht (RR=1.11, 95%CI=1.05-1.17) will be used in the AF calculation because the studies
included in the analysis were large and mainly of Western populations (exposure group A in
Table 12).
The result of the meta-analysis of crop protection product manufacturing workers of Jones et al.
(2009) will be used for workers employed in pesticide manufacturing (meta-RR=1.98,
95%=1.45-2.69) (exposure group M in Table 12). The analysis included 26 studies from around
the world, USA, Europe and one from New Zealand.
Workers in the grain industry as a whole do not appear to have an increased risk of NHL
according to Alavanja et al. (1990): RR=1.00, 95%CI=0.64-1.48 (exposure group G in Table
12).
3.3.2
Numbers exposed:
The number of workers employed in the occupations above, is given below in Table 11 and was
obtained from the LFS.
Table 11 Numbers of workers exposed to non-arsenical insecticides in 1991 (Source:
Labour Force Survey).
SIC Code
LFS 1991
Job Title
Farm owners & managers,
horticulturalists
Other managers farming, horticulture,
forestry & fishing
Farm workers
Agricultural machinery drivers &
operators
Other occupations in farming and
related
Forestry workers
Horticultural trades
Gardeners, Groundsmen,
Groundswomen
2568
4160
Formulated pesticides
Grain milling
23
Number employed
Men
Women
206038
29240
Total
235278
A
11066
6497
17563
A
100734
20233
41772
358
142506
20591
A
A
17271
19345
36616
A
19254
17816
131964
709
12555
7459
19963
30371
139423
A
A
A
524376
117935
642311
1343
6187
1084
1197
2427
7384
M
G
3.3.3
AF calculation:
The estimated total (male and female) attributable fraction for NHL for occupational exposure
to non-arsenical insecticides is 0.38% (95%CI=0.19-0.58), which equates to 13 (95%CI=7-21)
deaths and 33 (95%CI=16-50) registrations. The estimated AF for men is 0.56% (95% CI=0.27­
0.86) resulting in 11 (95%CI=5-17) attributable deaths and 27 (95%CI=13-41) attributable
registrations; and for women the AF is 0.18% (95%CI=0.09-0.27) resulting in 2 (95%CI=1-3)
attributable deaths and 6 (95%CI=3-9) attributable registrations (Table 12).
24
Table 12 Summary results for occupational exposure to non-arsenical insecticides
Data
Risk Estimate
Reference
Men
Boffetta and de Vocht
(2007)
Alavanja et al. (1990)
Jones et al. (2009)
Women
Boffetta and de Vocht
(2007)
Alavanja et al. (1990)
Jones et al. (2009)
Exposure
Main
Industry
1
Sector
A
A
G
G
M
M
All
A-B
All
C-E
All
C-E
All
All
A
A
G
G
M
M
All
A-B
All
C-E
All
C-E
All
All
RR2
1.11
1
1.98
1.11
1
1.98
Calculations
Ne3
524376
524376
6187
6187
1343
1343
531906
117935
117935
1197
1197
1084
1084
120216
Carex
4
adj
TO5
1
0.07
1
0.09
1
0.09
1
0.1
1
0.14
1
0.14
1. Specific scenario or main industry code (Table A1)
2. Relative risks selected from the best study
3. Numbers exposed, allocated to men/women
4. CAREX adjustment factor to mid-REP (Table A1)
5. Staff turnover (TO, Table A1)
6. Number ever exposed during the REP (Statistical Appendix equation 3)
7. Proportion of the population exposed (Pr(E), Statistical Appendix equation 4)
8. Statistical Appendix equation 1 25
NeREP6
PrE7
Attributable Fraction
8
(Levins ) and Monte Carlo
Confidence Interval
AF
LL
UL
Attributable
Deaths
Attributable
Registrations
AN
LL
UL
AR
LL
UL
1139943
1139943
15895
15895
3450
3450
1159288
0.0496
0.0496
0.0007
0.0007
0.0002
0.0002
0.0504
0.0054
0.0054
0.0000
0.0000
0.0001
0.0001
0.0056
0.0025
0.0025
0.0000
0.0000
0.0001
0.0001
0.0027
0.0084
0.0084
0.0004
0.0004
0.0003
0.0003
0.0086
11
11
0
0
0
0
11
5
5
0
0
0
0
5
17
17
1
1
1
1
17
26
26
0
0
1
1
27
12
12
0
0
0
0
13
40
40
2
2
1
1
41
340563
340563
4409
4409
3993
3993
348966
0.0147
0.0147
0.0002
0.0002
0.0002
0.0002
0.0151
0.0016
0.0016
0.0000
0.0000
0.0002
0.0002
0.0018
0.0008
0.0008
0.0000
0.0000
0.0001
0.0001
0.0009
0.0025
0.0025
0.0001
0.0001
0.0003
0.0003
0.0027
2
2
0
0
0
0
2
1
1
0
0
0
0
1
3
3
0
0
0
0
3
6
6
0
0
1
1
6
3
3
0
0
0
0
3
9
9
0
0
1
1
9
3.4
3.4.1
TETRACHLOROETHYLENE (PERC)
Risk estimate:
PERC exposure has consistently been associated with an increased risk of NHL (Fritschi et al,
2005b, Katz and Joyce, 1981, Miligi et al, 2006, Ruder et al, 2001). For the purposes of the
calculations that follow, the US study followed by Ruder was chosen as the best study to base risk
estimates on (Ruder et al, 2001). The population case-control study (Lynge et al, 2006) was
excluded due to the small numbers of exposed cases, and the study by Walker et al. (1997) was
considered inappropriate, as there was no overall mixed-race estimate given and did not report any
NHL Cases. The two larger American studies (Blair et al, 2003, Ruder et al, 2001) had extended
follow-up periods with larger numbers of exposed cases. However, overall, the study by Ruder was
chosen because this had the most recent follow-up (until 1996 vs. 1993), involved good exposure
assessment (from visiting the workplaces where possible), and excluded any individuals that had
ever been exposed to carbon tetrachloride (the primary solvent used in dry cleaning until the
1950s). The corresponding risk estimate to be used for burden estimation is SMR=1.39
(95%CI=0.56-2.86). All the studies mentioned in this report relating to PERC are based on cohorts
of dry cleaning and laundry workers. However IARC state that workers in dry cleaning and
degreasing are the most heavily exposed (IARC, 1995). Also, in a European Union report (ECB,
2005) it is believed that metalworking is the second major industrial use of the chemical in the EU
and UK. Therefore the subsequent analysis will be based on all workers exposed to PERC, not just
dry cleaners.
Due to the absence of sufficient dose-response data the risk estimate for low exposure was based
on a harmonic mean of the high/low ratios across all other cancer-exposure pairs in the overall
project where data were available. As this was less than 1 the RR for low exposure has been set to
1.
3.4.2
Numbers exposed:
CAREX estimated about 120,000 workers were exposed to PERC in Great Britain between 1990
and 1993. Table 13 shows the numbers of workers exposed to PERC in the various industries. For
the male/female split all are assumed to be “blue collar” workers in SOC major groups 5, 8 and 9.
3.4.3
AF calculation:
The estimated total (male and female) attributable fraction for NHL for occupational exposure to
tetrachloroethylene is 0.20% (95%CI=0.00-1.12), which equates to 7 (95%CI=0-38) deaths and 17
(95%CI=0-94) registrations. The estimated AF for men is 0.25% (95%CI=0 -1.35) resulting in 5
(95%CI=0-27) attributable deaths and 12 (95%CI=0-64) attributable registrations; and for women
the AF is 0.16% (95%CI=0-0.85) resulting in 2 (95%CI=0-11) attributable deaths and 5 (95%CI=
0-30) attributable registrations (Table 14).
26
Table 13 Numbers of workers exposed to tetrachloroethylene according to CAREX in
1990-1993 Industry
Exposure
Level
CAREX Data 1990-1993
Number
Exposed
Crude Petroleum and Natural Gas Production
Food manufacturing
Beverage industries
Tobacco manufacture
Manufacture of textiles
Manufacture of wearing apparel, except footwear
Manufacture of leather and products of leather or
of its
Manufacture of paper and paper products
Printing, publishing and allied industries
Petroleum refineries
Manufacture of pottery, china and earthenware
Manufacture of glass and glass products
Iron and steel basic industries
Non-ferrous metal basic industries
Manufacture of fabricated metal products, except
machinery & equipment
Manufacture of machinery except electrical
Manufacture of electrical machinery, apparatus,
appliances & supplies
Manufacture of transport equipment
Electricity, gas and steam
Water works and supply
Construction
Land transport
Water transport
Air transport
Services allied to transport
Communication
Education services
Research and scientific institutes
Personal and household services
Total
Main Industry Sector
Agriculture, hunting and forestry; fishing High
Low
Mining/quarrying, electricity/gas/steam,
High
manufacturing industry
Low
Construction
High
Low
Service industries
High
Low
62
2236
351
24
3182
4127
114
Number
in
Industry
53300
414150
88100
9950
182000
189500
16825
Proportion
in
industry
0.12
0.54
0.40
0.24
1.75
2.18
0.68
L
L
L
L
L
L
L
2206
2826
4
30
230
942
675
6002
119050
354750
18075
54450
43275
48425
79325
292200
1.85
0.80
0.02
0.06
0.53
1.95
0.85
2.05
L
L
L
L
L
L
L
H
8566
3238
692275
473750
1.24
0.68
H
H
2626
3173
332
15085
5970
171
1325
324
340
61
88
55165
119475
456900
140975
45175
1753450
671050
68175
95700
180725
459425
1455875
91100
686750
0.58
2.25
0.74
0.86
0.89
0.25
1.39
0.18
0.07
0.004
0.10
8.03
H
L
L
L
L
L
L
L
L
L
L
H
% Male
0
0
20432
20514
15085
55165
8279
27
76%
76%
99%
65%
65%
Table 14 Summary results for occupational exposure to tetrachloroethylene
Risk Estimate
Reference
Men
Women
Ruder et al . (2001)
Ruder et al. (2001)
Exposure
H
H
H
L
L
L
L
All
H
H
H
L
L
L
L
All
Main
Industry
Sector1
C-E
G-Q
All
C-E
F
G-Q
All
All
C-E
G-Q
All
C-E
F
G-Q
All
All
Data
RR2 Ne3
1.39
1.39
1
1
1
1.39
1.39
1
1
1
15528
35857
51386
15591
14934
5381
35906
87292
4904
19308
24211
4923
151
2898
7972
32183
Calculations
5
Carex
TO
adj4
1
1
0.09
0.11
1
1
1
0.09
0.12
0.11
1
1
0.14
0.15
1
1
1
0.14
0.15
0.15
1. Specific scenario or main industry code (Table A1)
2. Relative risks selected from the best study
3. Numbers exposed, allocated to men/women
4. CAREX adjustment factor to mid-REP (Table A1)
5. Staff turnover (TO, Table A1)
6. Number ever exposed during the REP (Statistical Appendix equation 3)
7. Proportion of the population exposed (Pr(E), Statistical Appendix equation 4)
8. Statistical Appendix equation 1 28
NeREP6
39895
106296
146191
40055
47223
15953
103230
249421
18064
74967
93031
18136
586
11251
29973
123004
PrE7
0.0017
0.0046
0.0064
0.0017
0.0021
0.0007
0.0045
0.0108
0.0008
0.0032
0.0040
0.0008
0.0000
0.0005
0.0013
0.0053
Attributable Fraction
(Levins8) and Monte Carlo
Confidence Interval
AF
LL
UL
0.0007
0.0018
0.0025
0.0000
0.0000
0.0000
0.0000
0.0025
0.0003
0.0013
0.0016
0.0000
0.0000
0.0000
0.0000
0.0016
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0037
0.0098
0.0135
0.0000
0.0000
0.0000
0.0000
0.0135
0.0017
0.0069
0.0085
0.0000
0.0000
0.0000
0.0000
0.0085
Attributable
Deaths
AN LL UL
1
4
5
0
0
0
0
5
0
2
2
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
7
20
27
0
0
0
0
27
2
9
11
0
0
0
0
11
Attributable
Registrations
AR LL
UL
3
9
12
0
0
0
0
12
1
4
5
0
0
0
0
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
18
47
64
0
0
0
0
64
6
24
30
0
0
0
0
30
3.5
3.5.1
TRICHLOROETHYLENE (TCE)
Risk estimate:
A number of cohort and case-control studies have evaluated the association between TCE
exposure in occupations involving use of TCE as a dry cleaning agent and as a metal degreasant
(in aerospace, cardboard and other industries) and incidence of/mortality from NHL.
Wartenberg et al. (2000) evaluate many of these studies, including 20 cohort and 40 casecontrol studies, dividing the cohort studies into three tiers based on the specificity of the
exposure information. Tier 1 studies are those that provide the best characterisation of TCE
exposure through the use of biomarkers and job-exposure matrices. Across the Tier 1 studies, an
average standardised incidence ratio (SIR) of 1.5 (95%CI=0.9-2.3) and an average standardised
mortality ratio (SMR) of 1.2 (95%CI=0.9-1.7) were obtained. As the SIR and SMR were
derived from the studies Wartenberg and co-workers identify as the best quality cohort studies
with sufficient follow-up periods (17-38 years), the values are particularly suitable for use as
estimates of relative risk (RR) for AF calculation. It must be noted, however, that the risk
estimates have some limitations. Firstly, the calculated risk is dependent upon the selection of
cohorts in each tier. As the methodology reported by Wartenberg and colleagues is suitably
robust and the studies used are highly regarded, it can be assumed that this limitation has a
minimal effect on the reliability of the estimate. It must be noted that the risk estimates obtained
through case-control studies are much higher than the risks from cohort studies, a point
recognised by Wartenberg and colleagues. Secondly, there is no adjustment for confounders.
This is common to the majority of epidemiologic studies evaluating the association between
TCE exposure and NHL due to the difficulty in separating TCE exposure from exposures to
other organic solvents including PERC. As such, it is perhaps more accurate to define the
exposure as being to organic solvents including TCE. Other confounding variable such as
smoking, alcohol consumption and other ‘lifestyle’ confounders are rarely considered by any of
the studies, making the Wartenberg risk estimate no better or worse than other risk estimates.
Few studies provide any indication of a dose-response relationship between TCE-dominated
organic solvent exposure and kidney cancer, so the Wartenberg and co worker estimates do not
simplify what would otherwise be more complex data.
The average risk calculated by Wartenberg was a weighted average of the individual measures
of effect, where the weights are the inverse of the variance of the individual measures. They
calculated variances where studies did not report one or where CIs were not symmetrical about
reported ORs. A comprehensive, quantitative meta-analysis was not applied to NHL and TCE
exposure. Therefore, Mandel et al. (2006) conducted a review and meta-analysis, and included
more recent published studies not considered in previous quantitative and qualitative reviews.
The summary RRs for the group of cohort studies that had more detailed information on TCE
exposure was 1.29 (95%CI=1.00-1.66) for the total cohort that will be used for the high
exposure group in the AF calculation. Due to the absence of sufficient dose-response data the
risk estimate for low exposure was based on a harmonic mean of the high/low ratios across all
other cancer-exposure pairs in the overall project where data were available. As this was less
than 1 the RR for low exposure has been set to 1.
3.5.2
Numbers exposed:
The numbers of workers exposed to TCE in various industries according to CAREX for 1990­
93 are given in Table 15. Exposures in the textile/clothing industries and in the manufacture of
finished metal products were allocated to the ‘higher’ category, as it was assumed that these
occupations were where use of TCE as a metal degreasant was more likely. The textile industry
may also have been exposed to TCE as a spot-cleaning agent, along with dry cleaners who were
considered to fall in the personal and household services category. TCE used in dry cleaning
until 1950s/1960s when predominant use was as a metal degreasant. Use as a solvent for
29
oils/resins is less common. Despite declining use during early part of current burden
assessment (1956-1996), high exposures have been allocated to dry cleaners.
Workers in the metal manufacturing industries can be expected to be predominantly male but clothing manufacture will include a high proportion of women. Numbers are allocated between
men and women in mining and manufacturing, assuming that all the exposed were employed in “blue collar” occupations (SOC major groups 5, 8 and 9). It can therefore be assumed that 76% of workers in the manufacturing industries are male. It has been assumed that 25% of service
workers were male, based on numbers of drycleaners/launderers provided in the LFS 1979-2003 (19% male workers in 1979, 25% in 1991 and increasing to 38% in 2003). These data were used
to estimate Pr(E) for Levin’s calculation of AF. Table 15 Numbers of workers exposed to trichloroethylene according to CAREX in 1990-1993 Industry
CAREX Data 1990-1993
Number
Number
Proportion
Exposed in Industry in Industry
Beverage industries
92
88100
0.10
Tobacco manufacture
40
9950
0.40
Manufacture of wearing apparel, except footwear
117
189500
0.06
Manufacture of leather and products of leather or
8
16825
0.05
of its substitutes
Manufacture of glass and glass products
130
43275
0.30
Manufacture of other non-metallic mineral
50
70875
0.07
products
Manufacture of fabricated metal products, except
2139
292200
0.73
machinery & equipment
Manufacture of machinery except electrical
3041
692275
0.44
Manufacture of electrical machinery, apparatus,
1852
473750
0.39
appliances & supplies
3anufacture of transport equipment
2949
456900
0.65
Sanitary and similar services
117
274225
0.04
Education services
122
1455875
0.01
Research and scientific institutes
88
91100
0.10
Recreational and cultural services
74
534600
0.01
Personal and household services
5517
686750
0.80
Total
16336
Main Industry Sector
Agriculture, hunting and forestry; fishing
High
% Male
0
0
Low
Mining/quarrying, electricity/gas/steam,
High
manufacturing industry
Construction
Service industries
High
10098
320
76%
0
5517
401
99%
25%
Low
Low
30
Exposure
Level
L
L
H
L
L
L
H
H
H
H
L
L
L
L
H
3.5.3
AF calculation:
The estimated total (male and female) attributable fraction for NHL for occupational exposure
to trichloroethylene is 0.03% (95%CI=0.00-0.07), which equates to 1 (95%CI=0-2) death and 3
(95%CI=0-6) registrations. The estimated AF for men is 0.03% (95%CI=0-0.07) resulting in 1
(95%CI=0-1) attributable death and 1 (95%CI=0-3) attributable registration; and for women the
AF is 0.03% (95% CI=0-0.07) resulting in 0 (95%CI=0-1) attributable deaths and 1 (95%CI=0­
2) attributable registration (Table 16).
31
Table 16 Summary results for occupational exposure to trichloroethylene
Data
Risk Estimate
Reference
Men
Women
Mandel et al. (2006)
Mandel et al. (2006)
Exposure
H
H
H
L
L
L
All
H
H
H
L
L
L
All
Main
Industry
1
Sector
C-E
G-Q
All
C-E
G-Q
All
All
C-E
G-Q
All
C-E
G-Q
All
All
RR2
Ne3
1.29
1.29
7674
1379
9054
243
100
343
9397
2424
4138
6561
77
301
378
6939
1
1
1.29
1.29
1
1
Calculations
Carex
4
adj
TO5
1
1
0.09
0.11
1
1
0.09
0.11
1
1
0.14
0.15
1
1
0.14
0.15
NeREP6
19717
4089
23806
625
297
922
24728
8928
16066
24993
283
1168
1451
26444
1. Specific scenario or main industry code (Table A1)
2. Relative risks selected from the best study
3. Numbers exposed, allocated to men/women
4. CAREX adjustment factor to mid-REP (Table A1)
5. Staff turnover (TO, Table A1)
6. Number ever exposed during the REP (Statistical Appendix equation 3)
7. Proportion of the population exposed (Pr(E), Statistical Appendix equation 4)
8. Statistical Appendix equation 1 32
PrE7
0.0009
0.0002
0.0010
0.0000
0.0000
0.0000
0.0011
0.0004
0.0007
0.0011
0.0000
0.0001
0.0001
0.0011
Attributable Fraction
(Levins8) and Monte Carlo
Confidence Interval
AF
LL
UL
0.0002
0.0001
0.0003
0.0000
0.0000
0.0000
0.0003
0.0001
0.0002
0.0003
0.0000
0.0000
0.0000
0.0003
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0006
0.0001
0.0007
0.0000
0.0000
0.0000
0.0007
0.0003
0.0005
0.0007
0.0000
0.0000
0.0000
0.0007
Attributable
Deaths
Attributable
Registrations
AN
LL
UL
AR
LL
UL
0
0
1
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1
0
0
0
1
0
1
1
0
0
0
1
1
0
1
0
0
0
1
0
1
1
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
1
3
0
0
0
3
1
2
2
0
0
0
2
3.6
3.6.1
HAIRDRESSERS AND BARBERS
Risk estimate:
Exposure as a hairdresser or beautician has been associated with an increased risk of ovarian
cancer (Boffetta et al, 1994, Lamba et al, 2001, Teta et al, 1984). For the purpose of the
calculations that follow, a European study was deemed more appropriate; therefore the studies
by Teta et al. (1984) and Lamba et al. (2001) were excluded. The SIR=1.20 (95% CI=0.84­
1.66) from the study conducted by Boffetta was chosen as this paper gave more details of the
methodology, adjusted for age and covered four European countries.
3.6.2
Numbers exposed
According to the Labour Force Survey there was 119,648 workers (15,425 males and 104,223
females) employed as a hairdresser or barber (including managers) in 1991 (Table 17).
Table 17 Numbers of workers employed as hairdressers or barbers according
to LFS in 1991 SIC code
6221
3.6.3
Description
Hairdressers and Barbers
Male
15,425
Female
104,223
Total
119,648
AF calculation
The estimated total (male and female) attributable fraction for NHL for occupation as a
hairdresser or barber is 0.19% (95%CI=0.00-0.63), which equates to 5 (95%CI=0-18) deaths
and 14 (95%CI=0-48) registrations. The estimated AF for men is 0.04% (95% CI=0-0.14)
resulting in 1 (95%CI=0-3) attributable death and 2 (95%CI=0-6) attributable registrations; and
for women the AF is 0.35% (95%CI=0-1.19) resulting in 4 (95%CI=0-15) attributable deaths
and 12 (95%CI=0-41) attributable registrations (Table 18).
33
Table 18 Summary results for workers employed as hairdressers and barbers
Risk Estimate
Reference
Main
Industry
Sector1
G-Q
All
All
G-Q
All
All
Ne3
H
1.2
15425
H
15425
All
15425
H
1.2
104223
Women Boffetta et al. (1994)
H
104223
All
104223
1. Specific scenario or main industry code (Table A1)
2. Relative risks selected from the best study
3. Numbers exposed, allocated to men/women
4. CAREX adjustment factor to mid-REP (Table A1)
5. Staff turnover (TO, Table A1)
6. Number ever exposed during the REP (Statistical Appendix equation 3)
7. Proportion of the population exposed (Pr(E), Statistical Appendix equation 4)
8. Statistical Appendix equation 1 Men
Boffetta et al. (1994)
Exposure
Data
RR2
Calculations
TO5
Carex
4
adj
1
0.11
1
0.15
NeREP6
45726
45726
45726
404672
404672
404672
34
PrE7
0.0020
0.0020
0.0020
0.0175
0.0175
0.0175
Attributable Fraction
8
(Levins ) and Monte Carlo
Confidence Interval
AF
LL
UL
0.0004
0.0004
0.0004
0.0035
0.0035
0.0035
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0014
0.0014
0.0014
0.0119
0.0119
0.0119
Attributable
Deaths
AN
LL
UL
1
1
1
4
4
4
0
0
0
0
0
0
3
3
3
15
15
15
Attributable
Registrations
AR
LL
UL
2
2
2
12
12
12
0
0
0
0
0
0
6
6
6
41
41
41
4 OVERALL ATTRIBUTABLE FRACTION
4.1
SUMMARY OF RESULTS
The results are summarised in Tables 19 and 20.
Table 19 Summary of relative risks used to calculate AF
Agent
Hairdressers and barbers
Non-arsenical insecticides (Farmers)
Non-arsenical insecticides (Pesticide manufacturers)
Non-arsenical insecticides (Grain Millers)
TCDD
TCDD
TCDD
Tetrachloroethylene
Tetrachloroethylene
Trichloroethylene
Trichloroethylene
35
Exposure
H
A
M
G
K
J
M
H
L
H
L
RR
1.2
1.11
1.98
1
1.4
1.98
1
1.39
1
1.29
1
LL
0.84
1.05
1.45
0.64
0.6
1.45
1
0.56
1
1
1
UL
1.66
1.17
2.69
1.48
2.7
2.69
1
2.86
1
1.66
1
Table 20 Results
Agent
Hairdressers and
barbers
Non-arsenical
insecticides
Numbers
of Men
Ever
Exposed
Numbers
of Women
Ever
Exposed
Proportion
of Men
Ever
Exposed
Proportion
of Women
Ever
Exposed
AF
Men
MCLL
Men
MCUL
Men
AF
Women
MCLL
Women
MCUL
Women
Attributab
le Deaths
(Men)
Attributable
Deaths
(Women)
Attributable
Registrations
(Men)
Attributable
Registrations
(Women)
45726
404672
0.0020
0.0175
0.0004
0.0000
0.0014
0.0035
0.0000
0.0119
1
4
2
12
1159288
348966
0.0504
0.015
0.0056
0.0027
0.0086
0.0018
0.0009
0.0027
11
2
27
6
TCDD
838863
272873
0.0036
0.0018
0.013
0.0000
0.0590
0.0040
0.0000
0.0019
25
5
61
14
Tetrachloroethylene
249421
123004
0.011
0.0053
0.0025
0.0000
0.0135
0.0016
0.0000
0.0085
5
2
12
5
24728
26444
0.0011
0.0011
0.0003
0.0000
0.0007
0.0003
0.0000
0.0007
1
0
1
1
0.0021
0.0000
0.0069
0.0011
0.0009
0.0029
43
14
102
39
Trichloroethylene
Totals*
*Totals are the product sums and are not therefore equal to the sums of the separate estimates of attributable fraction, deaths and registrations for each
agent. The difference is especially notable where the constituent AFs are large.
36
4.2
EXPOSURES BY INDUSTRY/JOB
Table 21 shows for industry categories from CAREX and job categories from LFS, attributable registrations in 2004 and attributable deaths in 2005 by agent.
Table 21 Industry/occupation codes by agent
Agent
Industry
Number
Ever
Exposed
over REP
(Men)
Number
Ever
Exposed
over REP
(Women)
45,726
404,672
2
1
12
4
14
5
447,907
84,437
10
4
1
1
12
5
24,056
18,762
1
0
0
0
1
0
218,986
120,626
5
2
2
1
7
3
43,985
1,034
1
0
0
0
1
0
37,545
55,863
1
0
1
0
2
1
Forestry workers
41,856
2,047
1
0
0
0
1
0
Horticultural trades
Gardeners, Groundsmen,
groundswomen
38,730
36,255
1
0
1
0
1
1
286,877
21,539
7
3
0
0
7
3
3,450
3,993
1
0
1
0
1
1
15,895
4,409
0
0
0
0
0
0
1,159,288
348,966
27
11
6
2
33
13
3,450
3,993
1
0
1
0
1
1
Hairdressers and
barbers
Non-arsenical
insecticides
Non-arsenical
insecticides
Non-arsenical
insecticides
Non-arsenical
insecticides
Non-arsenical
insecticides
Non-arsenical
insecticides
Non-arsenical
insecticides
Non-arsenical
insecticides
Non-arsenical
insecticides
Non-arsenical
insecticides
Non-arsenical
insecticides
Total
TCDD
Formulated pesticides
Hairdressers and Barbers
Farm owners & managers,
horticulturalists
Other managers farming, horticulture,
forestry & fishing
Farm workers
Agricultural machinery drivers &
operators
Other occupations in farming and
related
Formulated pesticides
Grain milling
Attributable Attributable Attributable Attributable
Registrations
Deaths
Registrations
Deaths
(Men) (2004) (Men) (2005)
(Women)
(Women)
(2004)
(2005)
37
Attributable
Attributable
Registrations Deaths (Total)
(Total) (2004)
(2005)
Agent
TCDD
Industry
Wood sawmill planning impregnation
Number
Ever
Exposed
over REP
(Men)
Number
Ever
Exposed
over REP
(Women)
23,613
0
Attributable Attributable Attributable Attributable
Registrations
Deaths
Registrations
Deaths
(Men) (2004) (Men) (2005)
(Women)
(Women)
(2004)
(2005)
2
1
0
0
Attributable
Attributable
Registrations Deaths (Total)
(Total) (2004)
(2005)
2
1
TCDD
Organic chemical manufacture
14,058
4,317
1
0
0
0
1
1
TCDD
Flat glass manufacture
38,943
14,297
3
1
1
0
4
2
TCDD
Glass containers
14,102
9,427
1
0
1
0
2
1
TCDD
Other glass products
53,046
24,059
4
2
1
1
6
2
TCDD
Refractory goods
19,862
4,100
2
1
0
0
2
1
TCDD
Ceramic goods
62,808
67,553
5
2
4
1
9
4
TCDD
Cement, lime, & plaster manufacture
24,237
4,402
2
1
0
0
2
1
TCDD
Iron & steel industry
231,646
34,609
19
8
2
1
21
9
TCDD
Steel tubes
77,674
13,306
6
3
1
0
7
3
TCDD
39,116
11,011
3
1
1
0
4
2
TCDD
Steel wire & wire products
Other drawing cold rolling forming of
steel
20,928
2,943
2
1
0
0
2
1
TCDD
Aluminium & aluminium alloys
51,304
13,645
4
2
1
0
5
2
TCDD
Copper, brass & other copper alloys
23,708
16,455
2
1
1
0
3
1
TCDD
Other non-ferrous metals & their alloys
17,632
2,420
1
1
0
0
2
1
TCDD
Scrap dealers & metal merchants
18,375
0
2
1
0
0
2
1
TCDD
838,863
272,873
61
25
14
5
74
31
11,719
5,306
1
0
0
0
1
1
16,726
7,573
1
1
0
0
2
1
Tetrachloroethylene
Total
Manufacture of fabricated metal
products. except machinery and
equipment
Manufacture of machinery except
electrical
Manufacture of electrical machinery.
apparatus. appliances
6,322
2,863
1
0
0
0
1
0
Tetrachloroethylene
Manufacture of transport equipment
Tetrachloroethylene
Personal and household services
Tetrachloroethylene
Total
Tetrachloroethylene
Tetrachloroethylene
5,127
2,322
0
0
0
0
1
0
106,296
74,967
9
4
4
2
13
5
249,421
123,004
12
5
5
2
17
7
38
Agent
Industry
Trichloroethylene
Personal and household services
Trichloroethylene
Total
Number
Ever
Exposed
over REP
(Men)
Number
Ever
Exposed
over REP
(Women)
Attributable Attributable Attributable Attributable
Registrations
Deaths
Registrations
Deaths
(Men) (2004) (Men) (2005)
(Women)
(Women)
(2004)
(2005)
4,089
16,066
0
0
1
0
1
0
24,728
26,444
1
1
1
0
3
1
39
Attributable
Attributable
Registrations Deaths (Total)
(Total) (2004)
(2005)
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48
6 STATISTICAL APPENDIX Formulae used in the estimation of AF
Levin’s equation
AF = Pr(E)*(RR-1)/{1+Pr(E)*(RR-1)}
(1)
where RR = relative risk, Pr(E) = proportion of the population exposed
A common denominator is used across exposure levels and industries for each exposure
Miettinen’s equation
AF = Pr(E|D)*(RR-1)/RR
where Pr(E|D) = proportion of cases exposed (E = exposed, D = case)
(2)
Turnover equation to estimate numbers ever employed during the REP
i=b
Ne(REP) =
∑l
(adj15)i
* n0/(R-15)}
i=a
k =(age(u )−age(1)) j=d +k
+
∑
k =0
∑
{l(adj15)j *n0 * TO /(age(u)-age(l)+1)}
(3)
j=c+k
where Ne(REP) = numbers ever employed in the REP
n0 = numbers employed in the exposed job/industry at a mid-point in the REP
TO = staff turnover per year
R = retirement age (65 for men, 60 for women)
l(adj15)i = the proportion of survivors to age i of those alive at age 15 (from GB life
tables)
a to b = age range achieved by the original cohort members by the target year (2005)
(e.g. 35 to 84 (men, 79 women) for the short latency REP)
c to d = age range achieved by the turnover recruited cohort members by the target year
(15 to 34 for the short latency REP) age(u) and age(l) = upper and lower recruitment age limits (24 and 15)
The derivation and assumptions underlying this formula are described in the methodology
technical report, available on the HSE website. The equation can be represented as a single
factor acting as a multiplier for n0, calculated by setting n0 to 1 in the above equation, so that the
factor varies only with TO see Table A1 below.
Equation to estimate the proportion of the population exposed
Pr(E) = Ne(REP) / Np(REP)
(4)
where Np(REP) = numbers ever of working age during the REP from population estimates
for the relevant age cohorts in the target year
Equation for combining AFs where exposed populations overlap but are independent and risk
estimates are assumed to be multiplicative:
AFoverall = 1- Πk(1-AFk) for the k exposures in the set
49
(5)
Table A1 Employment level adjustment and turnover factors used in the calculation of AF
Main Industry Sector
Men
A-B
C-E
F
G-Q
Women
A-B
C-E
F
G-Q
Agriculture, hunting and forestry; fishing
Mining and quarrying, electricity, gas and
water; manufacturing industry
Construction
Service industries
Total
Agriculture, hunting and forestry; fishing
Mining and quarrying, electricity, gas and
water; manufacturing industry
Construction
Service industries
Total
Adjustment factor
for change in
employment levels*
1
1.4
Turnover
per year
7%
9%
1
0.9
1
0.75
1.5
12%
11%
10%
10%
14%
0.67
0.8
0.9
15%
15%
14%
* Applied to CAREX data for the solid tumour REP only. Exposed numbers are obtained for a mid-point year in the
REP where national employment data sources have been used (the LFS or CoE).
Published by the Health and Safety Executive
06/12
Health and Safety
Executive
The burden of occupational cancer in Great Britain
Non-Hodgkin’s Lymphoma
The aim of this project was to produce an updated
estimate of the current burden of cancer for Great
Britain resulting from occupational exposure to
carcinogenic agents or exposure circumstances.
The primary measure of the burden of cancer was
the attributable fraction (AF) being the proportion of
cases that would not have occurred in the absence
of exposure; and the AF was used to estimate the
number of attributable deaths and registrations.
The study involved obtaining data on the risk of
the cancer due to the exposure of interest, taking
into account confounding factors and overlapping
exposures, as well as the proportion of the target
population exposed over the relevant exposure
period. Only carcinogenic agents, or exposure
circumstances, classified by the International Agency
for Research on Cancer (IARC) as definite (Group 1)
or probable (Group 2A) human carcinogens were
considered. Here, we present estimates for non­
Hodgkin’s lymphoma (NHL) that have been derived
using incidence data for calendar year 2004, and
mortality data for calendar year 2005.
The estimated total (male and female) attributable
fractions, deaths and registrations for NHL related
to overall occupational exposure is 1.74% (95%
Confidence Interval (CI)= 0.03-5.35), which equates
to 57 (95%CI= 1-176) attributable deaths and 140
(95%CI= 3-430) attributable registrations.
This report and the work it describes were funded
by the Health and Safety Executive (HSE). Its
contents, including any opinions and/or conclusions
expressed, are those of the authors alone and do
not necessarily reflect HSE policy.
RR864
www.hse.gov.uk