Document 1802169

Health and Safety
Executive
The Pesticide Users’ Health Study
An analysis of mortality (1987-2005)
Prepared by the Health and Safety Laboratory
for the Health and Safety Executive 2013
RR958
Research Report
Health and Safety
Executive
The Pesticide Users’ Health Study
An analysis of mortality (1987-2005)
Terry Brown
Anne-Helen Harding
Gillian Frost
Harpur Hill
Buxton
Derbyshire
SK17 9JN
The Pesticide Users Health Study (PUHS) was established so as to monitor the health of men and women who
are certified to apply pesticides on a commercial basis under the 1986 Control of Pesticides Regulations. An
analysis of deaths occurring between 1987 and 2005 among members of the PUHS is presented in this report.
There were 1,628 deaths among 59,085 male and 3,875 female pesticide users during the follow-up period.
Compared with the population of Great Britain, the pesticide users had lower than expected mortality from all
causes, and in particular from all cancers combined, cancers of the digestive organs, cancers of the respiratory
system, and non-malignant diseases of the nervous system and sense organs, and of the circulatory,
respiratory, and digestive systems. There was some evidence of excess deaths from multiple myeloma in men
and women, and possibly also from testicular cancer.
Deaths from all external causes (accidents and injuries) combined were lower than expected when compared
with the general population. However in men, deaths from ‘injury by machinery’ were higher than expected.
Continuing recruitment into the PUHS will enable HSE to monitor the health of these pesticide users as
regulations and exposures change over time.
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 2013
First published 2013
You may reuse this information (not including logos) free of
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ACKNOWLEDGEMENTS
Acknowledgements go to Steve Hewitt and Kate Hopkins
at City & Guilds Land Based Services for their advice and
support for the database. The authors would also like to thank
Paul Buckley, John Osman, and John Hodgson at the Health
and Safety Executive for their assistance on how the study
was established and previous work that had been carried
out. The authors would also like to thank Adrian Cassidy
and Yiqun Chen of the Health & Safety Executive for their
contributions. Lastly, the authors wish to thank the staff at the
National Health Service Information Centre for their support.
ii
KEY MESSAGES ƒ
Overall, men and women in the Pesticide Users Health Study (PUHS) had statistically
significantly lower than expected mortality from all causes, all cancers combined, cancers of
the lip, oral cavity and pharynx, of the digestive organs, and of the respiratory system, non­
malignant diseases of the nervous system and sense organs, and non-malignant diseases of
the circulatory, respiratory and digestive systems, when compared with the GB population.
ƒ
There was some evidence of excess deaths from multiple myeloma among men and women,
and possibly also some excess of testicular cancer deaths. With the limited data available, it
was not possible to investigate whether these were linked with particular jobs, working
practices or pesticides.
ƒ
There was lower than expected mortality from all external causes (accidents and injuries)
combined in both men and women. In men only, there was an excess of deaths due to “injury
by machinery”.
ƒ
It is recommended that recruitment into the PUHS cohort and follow-up of the PUHS cohort
be continued, so that this system for monitoring the health of workers exposed to pesticides
through their work is maintained.
iii
iv
EXECUTIVE SUMMARY
Objectives
The overall objective of this report was to describe mortality among participants of the Pesticide
Users Health Study (PUHS).
Study participants were men and women who have been certified to apply pesticides on a
commercial basis in Great Britain under the 1986 Control of Pesticides Regulations and who
agreed to take part in HSE’s research into their health. These men and women therefore
represent a cohort of individuals who were likely to have been occupationally exposed to
pesticides.
Main findings
ƒ
There were 1,628 deaths among 59,085 male and 3,875 female pesticide users during the
follow-up period, 1987-2005.
ƒ
The mean age at first certification was 32 years (sd 11), with women on average nearly 4
years younger than men at entry.
ƒ
At the end of the study, the mean length of time since first certification was 13 years, with a
range of less than one year to 18.7 years.
ƒ
The mean age at first certification for those who died was 46 years for men and 36 years for
women.
ƒ
ƒ
For those who died, the mean length of time since first certification was 9 years.
All cause mortality was substantially lower among the pesticide users than in the general
population (standardised mortality ratio (SMR) 0.58, 95% CI 0.55-0.61), as was mortality for
a number of the major disease groups:
o All cancers combined (SMR 0.72, 95% CI 0.66-0.78),
o Cancers of the lip, oral cavity and pharynx (SMR 0.18, 95% CI 0.07-0.48),
o Cancers of the digestive organs (SMR 0.78, 95% CI 0.68-0.90),
o Cancers of the respiratory system (SMR 0.55, 95% CI 0.46-0.65),
o Non-malignant diseases of the nervous system and sense organs (SMR 0.39,
95% CI 0.27-0.57),
o Non-malignant diseases of the circulatory system (SMR 0.58, 95% CI 0.52­
0.63)
o Non-malignant diseases of the respiratory system (SMR 0.39, 95% CI 0.31­
0.49)
o Non-malignant diseases of the digestive system (SMR 0.24, 95% CI 0.18-0.32)
The healthy worker effect, together with higher occupational physical activity levels and
lower smoking rates in this group of workers, to some degree may explain these lower than
expected mortality rates.
v
ƒ
The SMRs for some causes of death were higher than expected, though relatively small
numbers of deaths, wide confidence intervals and statistical non-significance for some
SMRs, mean that these need to be interpreted with caution. Only those causes of death with
raised SMRs in this analysis and statistically significantly higher than expected cancer
incidence in the parallel analysis of cancer incidence a in the PUHS cohort are listed here:
o There was some evidence that mortality from multiple myeloma (SMR 1.28,
95% CI 0.77-2.12 for men and SMR 10.8, 95% CI 2.70-43.2 for women) was
higher than expected in this cohort.
o There may be some evidence of an excess of deaths from testicular cancer
(SMR 1.95, 95% CI 0.93-4.09).
ƒ
Mortality from all external causes (accidents and injuries) combined was significantly lower
than expected in men (SMR 0.69, 95% CI 0.62-1.78), but for women it was not significantly
different from the general population. Among men “injury by machinery” was statistically
significantly higher than expected (SMR 4.21, 95% CI 2.11-8.42).
Recommendations
ƒ
The PUHS is an important resource, but the information currently held on the PUHS
database is limited. As it stands, it is not possible to investigate whether occupational
exposures at any level – industry, job, specific pesticide or working practice – are associated
with an increased risk of mortality. In addition, information on factors that may affect
mortality, such as diet and lifestyle, would permit an analysis to take these into account
before investigating the associations with occupational exposures. It is recommended that
this type of information be collected on the pesticide users in future research.
ƒ
At present only information on mortality and cancer incidence among the pesticide users is
available. Concern has been raised in the published literature about possible links between
pesticide exposure and non-malignant conditions, such as neurological and respiratory
symptoms and diseases, which are not always fatal. A general health survey of the pesticide
users is recommended, in order to determine the occurrence and the associated risk factors of
these health conditions among the pesticide users.
ƒ
It is recommended that recruitment into the PUHS cohort and follow-up of the PUHS cohort
be continued, so that this system for monitoring the health of workers exposed to pesticides
through their work is maintained.
a
Frost, G. The Pesticide Users Health Study: an analysis of cancer incidence (1987-2004). 2011. HSE Research
Report (in preparation)
vi
CONTENTS PAGE
1
INTRODUCTION......................................................................................... 2
2
IMPLICATIONS .......................................................................................... 5
3 METHODOLOGY........................................................................................ 6
3.1
The Cohort............................................................................................... 6
3.2
The Pesticide Users Health Study Database........................................... 7
3.3
Follow-Up ................................................................................................ 7
3.4
Case definition......................................................................................... 7
3.5
Data Analysis........................................................................................... 7
4 RESULTS ................................................................................................... 9
4.1
The Cohort............................................................................................... 9
4.2
Results from the Mortality Analysis........................................................ 12
4.3
Discussion of results.............................................................................. 15
5
REFERENCES.......................................................................................... 18
6 APPENDICES........................................................................................... 20
6.1
Causes of death selected for analysis ................................................... 20
6.2
City & Guilds Land Based Services certificates of competence............. 22
6.3
Stratified tables of results ...................................................................... 23
6.4
Review of the literature .......................................................................... 33
6.5
References cited in the appendices....................................................... 45
1
1
INTRODUCTION A pesticide is any physical, chemical or biological agent that will kill an undesirable plant,
fungal or animal pest. Therefore, pesticides are almost as diverse as their targets. Pesticides
have been used for centuries: the first recorded use was by the Sumerians who were using
sulphur as an insecticide in 2500 BC1. The Chinese were using pyrethrum as an insecticide by
1200 BC and sulphur as a fumigant by 1000 BC. Arsenic-containing compounds were used as
insecticides in the 16th century and as a weed killer in the late 19th century. By the 1920s the
extensive use of arsenicals caused public concern because some fruit and vegetables were found
to contain toxic residues. The use of chemicals for pest control in crops began in the 19th century
with, firstly, the introduction of lime-based fungicides and insecticides and, secondly, the use of
copper sulphate in fungicide mixtures2. The 1930s saw the development of a variety of synthetic
pesticides such as alkyl thiocyanate insecticides, dithiocarbamates and ethylene dibromide,
some of which have been superseded by numerous new compounds developed in the post-war
era. Pesticide use increased with the introduction of the insecticide DDT (Dichloro-DiphenylTrichloroethane) and growth-regulating herbicides in the 1940s. Organomercury has been used
since the 1950s to control seed and soil-borne fungal diseases, while the use of foliar fungicides
on cereals began in the 1970s. At the same time, the use of organochlorines (OCs),
organophosphates (OPs) and later, carbamates for insect pest control became more widespread.
Since the late 1970s, control of insects in arable crops via chemicals has become commonplace,
helped by the introduction of synthetic pyrethroids.
Potential associations between pesticide exposure and human diseases are increasingly the focus
of epidemiological investigations. This increased concern for human toxicity, potential
addresses differing levels of exposure occurring through various routes (food, air, water, soil).
The process of identifying causes of disease within pesticide-exposed populations is complex,
primarily because pesticides are merely one of many environmental exposures that people may
encounter. Therefore, to say that a pesticide is associated with increased adverse health effects –
cancer, respiratory problems, immune disorders, birth defects, etc. – requires the determination
of a positive association between pesticide exposure and a specific disease; and that other
known causes can be ruled out. For instance, farmers are not only exposed to pesticides, but also
to other potential risk factors such as fertilisers, nitrates, fuels and engine exhausts, solvents,
organic and inorganic dusts, electromagnetic and ultraviolet radiation, and animal pathogens.
Behavioural, dietary, and genetic factors may also have a bearing on their risk of disease.
The acute health effects of pesticides in humans are well documented; common symptoms
include headache, aching limbs, runny nose, giddiness, muscle weakness, and fevers/chills, plus
others3. In a study of 4,108 individuals who had at some time used pesticides occupationally, the
risk of pesticide-related symptoms increased with somatizing tendency b (somatic symptoms
include: faintness or dizziness, pains in the heart or chest, nausea or upset stomach, trouble
getting breath, hot or cold spells, numbness and tingling in parts of the body, and feeling weak
in parts of the body). The risk was also higher in men who had used pesticides more often and
who had worked with concentrates. The relative frequency of symptoms was similar for all
categories of pesticide (sheep dip, other insecticides, herbicides, fungicides and wood
preservatives). However, in many cases the symptoms may have arisen through psychological
rather than toxic mechanisms.
Existing reporting systems in the UK that collect data on incident illness associated with
exposure to pesticides, focus on acute episodes of ill health such as poisonings, caused by either
misuse or abuse. Much less is known about the incidence of ill health due to low-levels of
b
Somatization is the tendency to express psychological factors such as anxiety or stress through bodily symptoms.
2
pesticides and in the UK there is currently no surveillance scheme within primary care. A recent
study to estimate the prevalence and incidence of pesticide-related illness presenting to GPs in
Great Britain, suggested the former to be 0.07% and latter 0.04% of consultations, because of
concern about pesticide exposure4. Estimates of prevalence and incidence of possible pesticiderelated symptoms were 2.7% and 1.6% respectively. Although small, these estimates translate to
relatively large numbers of consultations annually.
Chronic health effects, such as cancer, and adverse reproductive outcomes, have been
investigated extensively5-12. Results have been interpreted in various ways as evidence that
pesticides are safe or that they are a cause for concern because they can be detrimental to human
health13. Genotoxicity studies and some recent epidemiological studies in occupationally exposed populations, point to the real possibility of carcinogenic health effects in humans exposed to pesticides 5-7 9 10 12 14-16. The Occupational Health Decennial Supplement showed that farmers had high death rates from
various accidental injuries, from several occupationally related respiratory disorders, from
hernias (which may result from the extremely heavy lifting in agriculture, especially in the past),
and from suicide (Table 1)17. The highest Proportional Mortality Ratio (PMR) (1455) was seen
for pesticide poisoning. A more detailed review of the published literature on epidemiological
studies, which investigate the association between occupational exposure to pesticides and
morbidity or mortality, is given in Appendix 6.4.
Table 1
Mortality from selected causes in farmers: men aged 20-74, England and Wales, 1979-80 and 1982-90 (Source Drever et al, 1995)17 and 19912000 (Source Coggan et al, 2009)18
Cause of death
1979-80 and 1982-90
Deaths
Farmers’ lung disease (495.0)
Other and unspecified allergic
pneumonitis (495.1, 495.3-495.9)
Inguinal hernia (550)
Other hernia (551-553)
Infections of skin, joints and
bone (680-686, 711, 730)
Off-road motor vehicle accidents
(E820-E825)
Animal transport accidents
(E827-E828)
Pesticide poisoning (E863)
Poisoning by other gases (E869)
Slipping and tripping (E885)
Injury by animals and plants
(E905-E906)
Injury by falling object (E916)
Injury by machinery (E919)
Injury by firearms (E922)
Injury by electric current (E925)
Suicide (E950-E959)
PMR
1991-2000
95% CI
Deaths
PMR
95% CI
56
7
10.1
7.87
8.23-14.2
3.17-16.2
31
3
14.6
2.89
9.89-20.7
0.60-8.44
41
41
36
1.91
1.49
1.81
1.37-2.59
1.07-2.02
1.27-2.51
29
24
2.37
1.57
1.59-3.41
1.01-2.34
38
2.55
1.80-3.50
23
2.80
1.78-4.20
15
4.68
2.62-7.73
9
9.64
4.41-18.3
4
7
17
21
14.6
4.17
1.93
7.75
3.96-37.24
1.68-8.59
1.12-3.09
4.79-11.9
4
3
4
16
13.5
2.38
1.54
10.3
3.68-34.6
0.49-6.97
0.42-3.93
5.90-16.8
35
147
23
29
1215
1.56
4.57
6.70
2.13
1.56
1.09-2.17
3.86-5.38
4.24-10.2
1.43-3.07
1.47-1.65
17
50
12
18
908
2.20
4.17
8.13
2.38
1.37
1.28-3.52
3.09-5.50
4.20-14.2
1.41-3.76
1.29-1.47
3
The most obvious groups in which to study the chronic effects of pesticides in humans are those
occupational groups or workers who apply pesticides in high doses as part of their daily
activities. Individuals working with pesticides can be categorised into a number of groups,
depending on their place of work and/or activity with the active ingredients:
ƒ
Pesticide sprayers and applicators: Those involved directly in the preparation and
application of pesticides to crops and who potentially represent the most exposed group of
workers. However, as the potential for direct contact with pesticides is anticipated during
these activities, the use of personal protective equipment (PPE) is frequently a condition of
use and is thought to be more commonplace than in those working with the sprayed crops,
which may impact on outcomes 19 20.
ƒ
Floriculturists and greenhouse workers: Those involved in the production of flowers and
ornamental plants that are commonly sprayed with pesticides in greenhouses. It has been
suggested that these groups of workers may potentially have an increased risk of cytogenetic
damage due to working in small confined areas, humid conditions and a potential continuous
exposure through re-entry activities such as cutting and potting, all militating against the
regular use of PPE 21 22. Additionally, compared to other classes of workers, floriculturists
may be relatively highly exposed to pesticides during loading, mixing and application as
well as during manual activities following regular contact with flowers and ornamental
plants. Furthermore, the climatic conditions within greenhouses allow for the continuous
production of fruits, vegetables and flowers, requiring a regular application of pesticides
throughout the year, resulting in potentially continuous exposure.
ƒ
Agricultural workers and farmers: Those involved in the production of crops, fruits and
vegetables and hence indirectly exposed to pesticides. In most instances, such workers are
also involved in the mixing and loading of the pesticides. Exposure to pesticides may be
lower than in other groups due to the seasonal application of pesticides and the working
environment, i.e. outdoors.
ƒ
Forestry workers: Those involved in the spraying of trees and shrubs. In general,
compared with other occupational groups, forestry workers use fewer active ingredients.
ƒ
Production workers: Those involved in the manufacture of pesticides. The production of
pesticides is undertaken throughout the year, as opposed to pesticide applications, which in
general, occur seasonally. Workers are therefore potentially exposed to pesticides
continuously, as well as to the raw materials such as formaldehyde, toluene and benzene,
some of which also have genotoxic activity.
The overall objective of this report was to describe mortality up to the end of 2005 among
participants of the Pesticide Users Health Study. Study participants were men and women, who
have taken certificates of competence in the use of agricultural pesticides and who therefore
represent a cohort of individuals who were likely to have been occupationally exposed to
pesticides.
4
2
IMPLICATIONS The Pesticide Users Health Study (PUHS) is the only national study monitoring the health of
men and women who are chronically exposed to pesticides as a part of their work. As such, and
in the absence of a requirement for health surveillance of these workers, the PUHS is the
principle means by which HSE can assess whether occupational exposure to pesticides is linked
to ill health. The findings of the mortality analysis thus provide an important insight into the
health of commercial pesticide users in Great Britain, and represent the first step in the
investigation of the health effects of occupational exposure to pesticides.
Men and women in the PUHS had significantly lower mortality rates than the GB population
during the period 1987-2005. Mortality from all causes, and from major disease groups,
including all cancers combined, cancers of the lip, oral cavity and pharynx, cancers of the
digestive organs, cancers of the respiratory system, non-malignant diseases of the nervous
system and sense organs, and non-malignant diseases of the circulatory, respiratory and
digestive systems, were statistically significantly lower than mortality in the GB population,
after taking age, year of death and sex into account. The healthy worker effect, and higher
occupational physical activity levels and lower smoking rates in this group of workers, may
explain these lower than expected mortality rates to some degree.
There was some evidence that there were excess deaths from multiple myeloma in both men and
women, and possibly also an excess of testicular cancer deaths. The evidence from the mortality
analysis for these excess deaths was relatively weak, but is strengthened when combined with
the reported statistically significant excess in the number of incident cases of multiple myeloma
and testicular cancer in the PUHS cohort during the period 1987-200423. The published
evidence for a link between pesticide use and multiple myeloma is conflicting; more accurate
measurement of exposure to specific pesticides may help clarify whether there is a causal
association. An association between blood levels of a metabolite of the organochlorine pesticide
DDT and testicular germ cell tumours has been reported in the literature24. Further research into
the observed excess of these cancers in the PUHS cohort may be warranted, particularly with
respect to occupational exposures and other potential explanatory factors.
Reported statistics for farmers, the occupational group most closely representative of the PUHS
cohort in official Standard Occupational Classifications, indicate that farmers are at increased
risk of mortality from a range of external causes, including transport, falling from height, struck
by moving or falling objects, asphyxiation/drowning, trapped by something collapsing or
overturning, contact with machinery, livestock related fatalities, and contact with electricity.
The HSE focused on safe working practices among farmers in their 2009 Agriculture Campaign
and it regularly runs Farm Safety Health Awareness Days in an attempt to reduce the
disproportionately high number of deaths from accidents and injuries in agriculture. There was a
statistically significantly lower risk of mortality from all external causes (accidents and injuries)
combined in the PUHS cohort than expected when compared with the GB population. In the
PUHS, the only statistically significant increased risk of mortality from external causes was
observed for “injury by machinery” in men. This self-selected cohort of workers trained in the
safe use of pesticides may be more health and safety aware than the wider group of farmers.
Alternatively, as only a proportion of the cohort are farmers, non-farming cohort members may
not be exposed to the same range of risks as farmers.
5
3
3.1
METHODOLOGY
THE COHORT
Since 1986, anyone applying pesticides on a commercial basis in the UK must first gain a
certificate of competence in their safe use. The City & Guilds Land Based Services (formerly
the National Proficiency Test Council (NPTC)), in Stoneleigh, has been at the forefront of
developments for craftsmen awards under the Agricultural Wages Order, statutory and code of
practice qualifications for the safe use of pesticides, sheep dipping, chainsaw operation and
transport of livestock, required by the Chemicals Regulation Directorate (CRD), the Veterinary
Medicines Directorate (VMD), Department for Environment Food and Rural Affairs (Defra),
the Health and Safety Executive (HSE) and other government agencies and national bodies.
The City & Guilds Land Based Services maintains a database of individuals who hold a
certificate of competence in the use of agricultural pesticides. At the time of their training,
individuals were invited to participate in a programme of medical research on the health effects
of pesticide usage conducted by HSE. In 1998, the HSE’s Epidemiology and Medical Statistics
Unit (EMSU) conducted a feasibility study into using the City & Guilds Land Based Services
database, both for following up cancer incidence and mortality, and for collecting other data on
health and on pesticide usage. They concluded that the database was “an excellent tool …. but
could be enhanced”, and committed HSE to a programme of work to achieve this. In February
2005, the database was transferred from EMSU to the Health and Safety Laboratory (HSL) in
Buxton, and the programme of work continues at HSL.
The Pesticide Users Health Study (PUHS) cohort consists of those individuals on the City &
Guilds Land Based Services database who consented to taking part in HSE’s medical research
programme. The overall objectives of the work involving the PUHS were to fill the gaps in
knowledge about the extent and nature of pesticide-related ill health, especially chronic
pesticide-related ill health, which is not the focus of current surveillance schemes. To achieve
this, the overall aims of the study are:
• To augment the information stored in the City & Guilds Land Based Services database,
by conducting surveys to collect data on:
o The extent and nature of current and historical pesticide usage;
o The health of cohort members; and
o Other relevant factors (but not health outcomes), e.g. work practices.
• To maintain the cohort so that it remains available for future research, by adopting
procedures to optimise:
o Recruitment to the study;
o Retention and tracking of study members; and
o Good survey practice.
6
3.2
THE PESTICIDE USERS HEALTH STUDY DATABASE
The PUHS database contains personal details of all 65,910 individuals who agreed to take part
in HSE’s programme of medical research into the health of pesticide users. The first test date
included in the database was May 1987. Data for those who agreed to take part before March
2003 were available for this analysis. The details include:
• Full name
• Maiden/previous name
• Sex
• Date of birth
• Address
• Employer name, background and address
• Test details: certificate received, date, centre name, county
• National insurance number
• National health service number
• Death details
• Cancer registration details
Although the database contains the employer’s name and background, the job of each individual
or the industry in which they worked cannot be ascertained from this information.
3.3
FOLLOW-UP
A request to flag the 65,910 men and women in the PUHS for cancer and death registrations
was made to the National Health Service Central Register (NHSCR) or the General Register
Office for Scotland (GROS) for those based in Scotland. For individuals not immediately traced
by NHSCR or GROS, further information was requested from the National Insurance office in
Newcastle-upon-Tyne, and passed back to NHSCR. A total of 63,493 individuals were
eventually traced, a rate of 96.3%. The NHSCR and GROS notify HSL, on a quarterly basis, of
any cancer or death registrations among the PUHS participants who were successfully traced.
3.4
CASE DEFINITION
The causes of death selected for the analysis were determined from a comprehensive review of
the literature. A list of the diseases or conditions considered in previous studies of pesticide
users or pesticide manufacturing workers was compiled and used as the outcomes for this
analysis. The underlying cause of death reported on death certificates was used to define a case
in this analysis. A full list of the causes selected and their associated International Classification
of Diseases (ICD) revisions 9 and 10 codes is given in Appendix 6.1.
3.5
DATA ANALYSIS
The outcome for the mortality analysis was the underlying cause of death recorded on the death
certificate, coded according to ICD-9 or ICD-10. Person-years at risk and standardised mortality
ratios (SMR) were calculated using Stata SE v11.125 26. The start date for the cohort was the date
members sat for their first certificate of competence, irrespective of what type it was. Person
years at risk accrued until the end of the study period (31 December 2005), or when an
individual died or emigrated.
Individuals were excluded from the analysis if they were not successfully traced by the NHSCR
or GROS, they were not resident in Great Britain, they had withdrawn from the study, or had
7
missing or invalid information recorded in the database on date of birth, date of first test, date of
death (if applicable), and region.
Standard methods for analysing cohort studies were used. Standardised mortality ratios, which
compare mortality in the cohort with national mortality, were calculated. The SMRs were
calculated by sex-specific 5-year age and calendar periods. National mortality rates were
obtained from the Office for National Statistics (England and Wales) and from the General
Register Officer for Scotland. If an SMR is greater than 1, there is an excess of deaths among
the pesticide users, and if the SMR is less than 1, there are fewer deaths than expected among
the pesticide users when compared with the national population.
Potential trends within the overall SMRs were examined by stratifying the SMRs by year of
birth, year of the first test, age at the first test, and the modules for which an individual had
received a certificate of competence (Appendix 6.2). The number of years since an individual
was first certified was treated as a time dependent variable in the analysis. SMRs were also
stratified in relation to the region where an individual lived. The regions were based on
Government Office Regions, defined as:
• Scotland
• North: Durham, Cleveland, Cheshire, Lancashire, Humberside, Northumberland,
Yorkshire, Cumbria, Yorkshire, Tyne & Wear, Merseyside
• Midlands:
Leicestershire,
Derbyshire,
Nottinghamshire,
Lincolnshire,
Northamptonshire, Hereford, Worcester, Shropshire, Staffordshire, Warwickshire, West
Midlands
• Eastern: Norfolk, Suffolk, Essex, Hertfordshire, Bedfordshire, Cambridgeshire
• South East: Sussex, Surrey, Hampshire, Berkshire, Buckinghamshire, Isle of Wight,
Kent, Oxfordshire, London c
• South West: Cornwall, Devon, Dorset, Somerset, Gloucestershire, Avon, Wiltshire
• Wales
c
London is a separate Government Office Region; for the purpose of this analysis it was combined with ‘South-East’
because there was a comparatively small number of pesticide users in London.
8
4
4.1
RESULTS THE COHORT
Altogether 63,493 of the 65,910 men and women on the PUHS database, were successfully
traced. Of these, a further 533 individuals were excluded from the analysis: 182 did not have a
date on which they took the first test, 344 lived outside the boundaries of England, Wales and
Scotland, and 7 emigrated before the first test date. Men and women who only held a
Foundation Module were included in the analysis, because they are permitted to apply
pesticides under the supervision of an individual who is fully qualified to apply pesticides on a
commercial basis. Thus, 62,960 members of the cohort were included in the analysis: 59,085
(93.8%) men and 3,875 (6.2%) women. Table 2 gives numbers of individuals in the different
regions of the country.
Table 2
Region
East
South East
South West
Midlands
North
Scotland
Wales
Total
Regional distribution of the cohort
Men
Number (%)
8,343
(13.2)
11,872
(18.9)
7,457
(11.8)
10,431
(16.6)
12,350
(19.6)
6,071
(9.6)
2,561
(4.1)
59,085
(100)
Women
Number (%)
600
(1.0)
1,156
(1.8)
543
(0.9)
584
(0.9)
615
(1.0)
252
(0.4)
125
(0.2)
(100)
3,875
Total
Number (%)
8,943
(14.2)
13,028
(20.7)
8,000
(12.7)
11,015
(17.5)
12,965
(20.6)
6,323
(10.0)
2,686
(4.3)
62,960
(100)
Table 3 gives information about the year of birth of the cohort as a whole (men and women).
The majority of the cohort was born in the 1950s and 1960s, though the majority of women
were born in the 1960s and 1970s.
Table 3
Year of Birth
Before 1930
1930-1939
1940-1949
1950-1959
1960-1969
1970-1979
1980-
Cohort distribution by year of birth
Men
Number
618
3,532
8,344
13,264
21,347
10,607
1,373
%
(1.0)
(5.6)
(13.2)
(21.1)
(33.9)
(16.8)
(2.2)
Women
Number
%
4
(0.01)
48
(0.1)
290
(0.5)
598
(1.0)
1,698
(2.7)
1,157
(1.8)
80
(0.1)
Total
Number
%
622
(1.0)
3,580
(5.7)
8,634
(13.7)
13,862
(22.0)
23,045
(36.6)
11,764
(18.7)
1,453
(2.3)
Table 4 gives details of the year in which individuals were first given a certificate of
competence and the age they were when issued the certificate. As expected, the majority of
certificates were first issued in the 1980s when the certification scheme was established. In each
9
year group, the mean age of men was significantly greater than the mean age of women. The
average age of the cohort at the date they received their first certificate of competence was 32.3 years (standard deviation: 11.0; range: 16.2-74.3), and almost 50% were under the age of 30 years. At the end of follow-up, the mean age for men was 45.7 years (standard deviation (sd)
11.7), compared to 40.8 years (sd 9.3) for women. Table 4
Cohort distribution by year of and age at the first test date
Year of first test
Men
Number (%)
1987-1990
1991-1994
1996-2000
2001-2003
29,742
16,465
10,149
2,729
(50.3)
(27.9)
(17.2)
(4.6)
Mean
age
33.4
31.1
32.1
33.7
Women
Number (%)
Mean
age
1,366 (35.3)
28.3
1,419 (36.6)
27.9
835 (21.5)
29.6
255
(6.6)
32.5
Total
Number (%)
31,108
17,884
10,984
2,984
(49.4)
(28.4)
(17.4)
(4.7)
Mean
age
33.1
30.8
31.9
33.6
Age at first test
<25
25-29
30-34
35-39
40-44
45-49
50Mean age at
first test
18,696
10,428
8,520
6,692
5,498
3,975
5,276
(29.7)
(16.6)
(13.5)
(10.6)
(8.7)
(6.3)
(8.4)
32.5 (11.0)
1,689
876
479
314
261
141
115
(2.7)
(1.4)
(0.8)
(0.5)
(0.4)
(0.2)
(0.2)
28.7 (8.8)
20,385
11,304
8,999
7,006
5,759
4,116
5,391
(32.4)
(18.0)
(14.3)
(11.1)
(9.2)
(6.5)
(8.6)
32.3 (11.0)
As outlined in section 3.2, job information was lacking on the PUHS database, although a total
of 8,270 were known to be definitely self-employed and 16,934 not. Table 5 gives information
of the modules passed by the cohort: 6,969 individuals completed only the foundation module,
while 48,249 completed the foundation module and either the ground crop sprayer or the hand­
held operator module. The table also shows the length of time a certificate had been held by the
end of the study (31 December 2005). The overall mean was 13.2 years (sd 4.2), with a range
from less than one month to 18.7 years.
10 Table 5
Cohort distribution by City & Guilds Land Based Services modules
taken and number of years certified
Men
Modules taken
Number
Women
(%)
Number
Total
(%)
Number
(%)
Foundation Module (FM)
FM + Ground Crop Sprayer,
unspec.
FM + Hand Held Applicators,
unspec.
All Three
All others
6,293
16,640
(10.7)
(28.2)
676
207
(17.5)
(5.3)
6,969
16,847
(11.1) (26.8)
28,693
(48.6)
2,709
(69.9)
31,402
(49.9)
2,711
4,748
(4.6)
(8.0)
73
210
(1.9)
(5.4)
2,784
4,958
Total
59,085
(100)
3,875
(100)
62,960
(100) <=5
5-9
10-14
15+
Total
5,814
10,605
19,681
22,985
59,085
(9.8)
(18.0)
(33.3)
(38.9)
(100)
533
889
1,546
907
3,875
(13.8)
(22.9)
(39.9)
(23.4)
(100)
6,347
11,494
21,227
23,892
62,960
(10.1)
(18.3)
(33.7)
(38.0)
(100)
Mean number of years certified
13.3
(sd 4.2)
13.2
(sd 4.2)
(4.4) (7.9) Years since first certification$
$
(sd 4.2)
Equivalent to length of follow-up
11 12.2
4.2
RESULTS FROM THE MORTALITY ANALYSIS
Altogether there were 829,709 person years at risk and 1,628 deaths among the cohort (1,591
men, 37 women). The mean age at which those individuals who died took their first test was
45.3 years, approximately 13 years older than the cohort average. The mean age of men was
approximately ten years greater than that for women. The number of years those individuals,
who died during follow-up, had held a certificate (9.4 years, sd 4.6) was some four years less
than the cohort average. The mean age at death was 54.6 years (sd 13.7), with that for men (54.8
years) being significantly greater than that for women (44.9 years) (Table 6).
Table 6
Mean age at death, age at first test and number of years certified by
sex for individuals who died during follow-up
Age at first test
Number of years certified
Age at death
Men
45.5 (12.5)
9.4 (4.6)
54.8 (13.6)
Women
36.1 (11.0)
8.8 (4.4)
44.9 (13.0)
Total
45.3 (12.6)
9.4 (4.6)
54.6 (13.7)
p<0.001$
p = 0.43$
p<0.001$
$ Difference between men and women
Table 7 shows the mortality pattern for men and women and the cohort as a whole. All-cause
mortality (SMR 0.58, 95% CI 0.55-0.61) and mortality from all cancers (SMR 0.72, 95% CI
0.66-0.78) were significantly less than expected when compared with the GB population. In
addition, cancers of the lip, oral cavity, pharynx, digestive organs, and respiratory system, and
diseases of the nervous system, sense organs, circulatory system, respiratory system, and
digestive system were all statistically significantly lower than expected.
In men, the SMRs for the majority of causes of death were less than one. There was no
statististically significant excess of deaths from any of the individual causes of death analysed.
There were statistically non-significantly raised SMRs for pancreatic cancer (observed deaths =
38, SMR 1.02), non-melanoma skin cancer (observed deaths = 2, SMR 1.92), breast cancer
(observed deaths = 1, SMR 1.24), testicular cancer (observed deaths = 7, SMR 1.95), cancer of
the central nervous system (observed deaths = 1, SMR 3.32), and multiple myeloma (observed
deaths = 15, SMR 1.28). These statistically non-significant excesses should not be overinterpreted in the absence of other supporting evidence, particularly where the number of deaths
is small, the excess is small, and/or the confidence interval is very wide.
On the whole, no real patterns could be discerned for women because of the small number of
deaths and the resulting wide confidence intervals for many SMRs (Table 7). There was a
statistically significant excess of connective and soft tissue cancers (observed deaths = 1; SMR
8.77, 95% CI 1.24-62.3) and the SMRs for lymphohaematopoietic cancers suggested there was
some evidence of an excess of deaths from this group of cancers in women. The SMR for
lymphohaematopoietic cancers was 3.48 (95% CI 1.56-7.74), with a statistically significant
excess of multiple myelomas (observed deaths = 2, SMR 10.8, 95% CI 2.70-43.2) and non­
significant excesses of non-Hodgkins lymphoma (observed deaths = 2, SMR 3.03) and
leukaemia (observed deaths = 2, SMR 2.83). The small number of deaths for each of these
cancers means that the results should be treated with caution, and the role of chance cannot be
excluded.
The SMR for mortality from all external causes was also statistically significantly lower than
expected when compared with the GB population (SMR 0.70, 95% CI 0.62-0.79) (Table 8). In
12 men only, there was a statistically significant excess of the external cause of death “injury by
machinery” (observed deaths = 8; SMR 4.21, 95% CI 2.11-8.42) and in women there was an
excess of deaths caused by slips, trips or stumbling (observed deaths = 1; SMR 123, 95% CI
17.3-873). The latter, based on one death, should be interpreted with caution. External causes
accounted for 82% of deaths from all causes among those aged under 25-years at death. The
proportion declined steadily with age at death to the extent that in the over 50-year old age
group, external causes accounted for 4% of deaths from all causes. Overall, suicide and selfinflicted injuries dominated the external cause of death category (39%), although the proportion
varied by age at death. In individuals aged less than 25 years at death, 18% of external causes of
death were suicides or self-inflicted injuries, whereas the proportion was 59% in those aged 35­
39 years. Among those aged less than 25 years at death, 48% of deaths from external causes
were due to transport accidents, whereas this proportion was less than 25% in those aged over
30 years at death.
The SMRs for men, stratified by region of residence, year of birth, age at first certification,
length of time since first certification, and type(s) of certificate held, are shown in Table 9 to
Table 13 in Appendix 6.3. Overall there were no discernable trends in mortality with any of
these possible explanatory variables.
13 Table 7
Mortality in the Pesticide Users Health Study, 1987-2005
Cause of Death
Obs
1,591
All causes
Malignant neoplasms
Malignant neoplasms (excl. NMSC)
Lip, oral cavity & pharynx
Digestive organs
Oesophagus
Stomach
Colon
Rectum & anus
Liver & gall bladder
Pancreas
Respiratory system
Larynx
Trachea, bronchus & lung
Skin
Malignant melanoma
Non-melanoma skin cancer
Connective & soft tissue
Breast
Female genital system
Ovarian & other uterine adnexa
Male genital system
Prostate
Testis
Urinary system
Kidney
Bladder
Eye, brain & central nervous system
Eye
Brain
Central nervous system & meninges
Thyroid
Lymphohaematopoietic
Hodgkin’s disease
Non-Hodgkins lymphoma
Multiple myeloma
Leukaemia
583
580
4
192
46
30
38
22
8
38
126
3
118
15
12
3
3
1
40
33
7
34
18
14
34
0
20
1
1
73
4
26
15
26
Diseases of the:
Nervous system & sense organs
Parkinson’s disease
Motor neuron disease
Alzheimer’s disease
Circulatory system
Ischaemic heart disease
Cerebrovascular disease
Respiratory system
COPD
Asthma
Farmer’s Lung
Digestive System
28
0
9
3
530
335
89
75
15
4
0
39
Men
SMR
(95% CI)
0.58
(0.55-0.60)
0.71
0.71
0.18
0.78
0.89
0.88
0.72
0.64
0.42
1.02
0.55
0.34
0.55
0.79
0.72
1.34
0.93
1.24
(0.66-0.77)
(0.66-0.77)
(0.07-0.49)
(0.68-0.90)
(0.66-1.18)
(0.61-1.26)
(0.53-1.00)
(0.42-0.97)
(0.21-0.85)
(0.74-1.40)
(0.46-0.66)
(0.11-1.05)
(0.46-0.66)
(0.48-1.32)
(0.41-1.27)
(0.43-4.15)
(0.30-2.87)
(0.17-8.82)
0.86
0.80
1.95
0.72
0.72
0.66
0.82
(0.63-1.18)
(0.57-1.12)
(0.93-4.09)
(0.51-1.00)
(0.45-1.15)
(0.39-1.11)
(0.58-1.14)
0.78
1.89
0.72
0.94
0.82
0.77
1.28
0.96
(0.51-1.22)
(0.27-13.4)
(0.10-5.09)
(0.75-1.18)
(0.31-2.20)
(0.53-1.14)
(0.77-2.12)
(0.66-1.42)
0.40
(0.28-0.59)
0.81
0.95
0.58
0.54
0.66
0.39
0.30
0.41
(0.42-1.56)
(0.31-2.94)
(0.53-0.63)
(0.48-0.60)
(0.54-0.82)
(0.32-0.49)
(0.18-0.49)
(0.15-1.08)
0.23
(0.17-0.32)
Obs
37
19
19
0
2
0
1
0
0
0
1
1
0
1
0
0
0
1
6
2
1
0
0
0
1
0
0
0
0
6
0
2
2
2
0
0
0
0
4
1
2
1
0
0
0
2
Women
SMR
(95% CI)
0.71
(0.52-0.98)
0.85
0.85
(0.54-1.34)
(0.54-1.34)
0.58
(0.14-2.30)
2.33
(0.33-16.5)
1.55
0.34
(0.22-11.0)
(0.05-2.42)
0.35
(0.05-2.51)
8.77
0.94
0.60
0.60
(1.24-62.3)
(0.42-2.08)
(0.15-2.40)
(0.08-4.22)
0.98
(0.14-6.95)
3.48
(1.56-7.74)
3.03
10.8
2.83
(0.76-12.1)
(2.70-43.2)
(0.71-11.3)
All
(95% CI)
(0.55-0.61)
0.72
0.71
0.18
0.78
0.88
0.90
0.71
0.63
0.42
1.03
0.55
0.34
0.55
0.77
0.70
1.33
1.19
0.97
0.60
0.60
0.86
0.80
1.95
0.71
0.71
0.65
0.82
(0.66-0.78)
(0.66-0.77)
(0.07-0.48)
(0.68-0.90)
(0.66-1.18)
(0.63-1.28)
(0.52-0.98)
(0.41-0.95)
(0.21-0.84)
(0.75-1.40)
(0.46-0.65)
(0.11-1.05)
(0.46-0.66)
(0.46-1.28)
(0.40-1.23)
(0.43-4.11)
(0.44-3.18)
(0.46-2.03)
(0.15-2.40)
(0.08-4.22)
(0.63-1.18)
(0.57-1.12)
(0.93-4.09)
(0.51-1.00)
(0.45-1.13)
(0.38-1.10)
(0.59-1.14)
0.77
1.84
0.69
1.00
0.80
0.81
1.42
1.01
(0.49-1.19)
(0.26-13.0)
(0.10-4.93)
(0.80-1.24)
(0.30-2.12)
(0.56-1.18)
(0.89-2.30)
(0.70-1.47)
0.39
(0.27-0.57)
(0.41-1.53)
(0.30-2.89)
(0.52-0.63)
(0.48-0.60)
(0.54-0.82)
(0.31-0.49)
(0.18-0.49)
(0.15-1.04)
(0.18-0.32)
0.43
0.27
0.71
0.32
(0.16-1.14)
(0.04-1.90)
(0.18-2.85)
(0.04-2.26)
0.80
0.93
0.58
0.54
0.66
0.39
0.29
0.39
0.56
(0.14-2.25)
0.24
Number of deaths observed; Standardised mortality ratio; 95% Confidence intervals
14
SMR
0.58
Table 8
External causes of mortality among men and women in the Pesticide Users Health Study database, 1987-2005 Cause of Death
External causes
Transport accidents
Accidental falls
Slips, trips or stumbling
Injury by falling object
Injury by machinery
Injury by firearm
Accidents by submersion, suffocation &
foreign bodies
Injury by electric current
Accidental poisoning
Suicide & self-inflicted injury
Injury, undetermined intent
Obs
264
67
17
1
3
8
1
6
2
6
101
25
Men
SMR
0.69
0.74
0.74
1.66
1.78
4.21
5.03
0.45
1.33
0.34
0.80
0.43
(95% CI)
(0.62-0.78)
(0.58-0.94)
(0.46-1.20)
(0.23-11.8)
(0.57-5.51)
(2.11-8.42)
(0.71-35.8)
(0.20-1.00)
Obs
6
1
1
1
0
0
0
0
(0.33-5.31)
(0.15-0.75)
(0.66-0.97)
(0.29-0.64)
0
0
4
0
Women
SMR
(95% CI)
0.96
(0.43-2.14)
0.74
(0.10-5.29)
3.14
(0.44-22.3)
123
(17.3-873)
2.23
(0.84-5.93)
SMR
0.70
0.74
0.78
3.28
1.77
4.21
5.03
0.44
All
(95% CI)
(0.62-0.79)
(0.58-0.93)
(0.49-1.23)
(0.82-13.1)
(0.57-5.49)
(2.11-8.42)
(0.71-35.7)
(0.20-0.98)
1.32
0.33
0.82
0.43
(0.33-5.29)
(0.15-0.74)
(0.68-0.99)
(0.29-0.63)
Number of deaths observed; Standardised mortality ratio; 95% Confidence intervals
4.3
DISCUSSION OF RESULTS
This analysis of mortality among 62,960 pesticide users in the GB Pesticide Users Health Study
during the period 1987-2005 demonstrated that all cause mortality, and mortality from all
cancers combined, respiratory disease, circulatory disease, and non-malignant diseases of the
digestive system of the pesticide users were statistically significantly lower than expected when
compared with the GB population. In men, all cause mortality was 42% lower than expected
and in women it was 29% lower than expected. This may in part reflect the well-known healthy
worker effect, but it may also reflect relatively higher occupational physical activity levels and
lower tobacco consumption among these workers. A survey of the members of the PUHS
undertaken in 2004-2006 showed that 14% of the 8,073 respondents were current smokers1.
Although this represents only 13% of the whole cohort of pesticide users, it does suggest that
smoking is less prevalent in the cohort than in the GB population, where approximately 24% of
the population were current smokers in 20052. Consequently, the lower mortality rates among
the pesticide users will be at least partially attributable to differences in smoking rates in the
cohort and the reference population.
These findings are consistent with the published literature on farmers and pesticide applicators,
which indicates that these workers tend to be healthier than the general population, especially
with respect to cardiovascular disease and diseases associated with heavy tobacco and alcohol
use3 4. For example, in the US Agricultural Health Study of 52,394 pesticide applicators
followed up from 1993 to 2007, the SMR was 0.54 (95% CI 0.52-0.55) for all cause mortality,
0.61 (95% CI 0.58-0.64) for all cancers, 0.43 (95% CI 0.39-0.47) for lung cancer, 0.54 (95% CI
0.51-0.56) for heart diseases, 0.52 (95% CI 0.45-0.59) for cerebrovascular disease, and 0.60
(95% CI 0.32-0.46) for non-malignant diseases of the digestive system5. Overall, 17% of these
pesticide applicators were current smokers compared with 25% of the US population in 19956.
Although SMRs are generally not directly comparable between different populations, the
similarities observed between the Agricultural Health Survey and the PUHS results does
provide evidence of consistency in their reported associations.
In men there were a number of statistically non-significantly raised SMRs, which on their own
do not provide evidence of an increased risk of mortality. However, a parallel analysis of cancer
incidence in this cohort was undertaken, and this analysis found statistically significantly raised
incidence of testicular cancer (observed cases = 102; Standardised Incidence Rate (SIR) 1.26,
15 95 % CI 1.04-1.53) and multiple myeloma (observed cases = 31; SIR 1.49, 95% CI 1.05-2.13)7.
Taken together, the significant excess in the number of incident cancers and the statistically
non-significant excess of deaths from testicular cancer and from multiple myeloma suggest that
there may be some increase in the risk of these two cancers in men.
In women there were statistically significantly raised SMRs for connective and soft tissue
cancers and lymphohaematopoietic cancers, and within the group of lymphohaematopoietic
cancers for multiple myeloma. The small number of deaths for each of these causes means that
these excesses must be treated with caution. In the analysis of cancer incidence in this cohort,
no soft tissue cancers were observed in women, and the raised SIR for lymphohaematopoietic
cancers was not statistically significant7. However, there were four cases of multiple myeloma,
and the SIR of 10.0 (95% CI 2.72-25.6) was statistically significant (p < 0.01). Despite the small
numbers involved, the consistency of the findings in the incidence and the mortality analysis
provides some evidence of an increased risk of multiple myeloma in these women.
Few studies have investigated the association between pesticides and the risk of testicular germ
cell tumours (TGCT). A case-control study of 739 cases with TGCT and 915 matched controls
reported a significantly increased risk of TGCT associated with exposure to a metabolite (p,p'­
DDE) of the organochlorine pesticide DDT (odds ratio 1.71, 95% CI 1.23-2.38 for 4th quartile
vs 1st quartile)8. An earlier case-control study of 61 cases with TGCT and 58 matched controls
reported a statistically non-significantly raised odds ratio of 1.7 for blood p,p'-DDE levels
higher than the median compared with those less than the median9.
There is substantial literature on the association between agricultural work or pesticide-related
occupations and the risk of multiple myeloma, but the evidence in the literature is not
conclusive. Meta-analyses have been undertaken, with the meta-relative risk estimates ranging
from 1.09-1.26, though many of these were not statistically significantly elevated (see Appendix
6.4). As with all studies investigating occupational groups such as “farmers” or “pesticide
users”, the ability to identify particular exposures that may be causal is limited given the broad
range of activities, and hence the exposures connected with these occupations. Reported
associations between specific exposures and a disease, such as multiple myeloma, may be more
consistent if it were possible to classify the exposures more accurately.
In official publications reporting occupational health statistics for the periods 1979-1980 and
1982-199010 and for the period 1991-200011, the proportional mortality ratios (PMR) for a
number of external causes of death, including intentional suicide and self-inflicted injury, were
significantly elevated. These external causes of death were investigated in the cohort of
pesticide users, but the SMR for all external causes of death and for most individual external
causes were either below one or not statistically significantly elevated. The only external cause
of death with a significantly raised SMR in men was “injury by machinery” (SMR 4.21, 95% CI
2.11-8.42) and in women was “slips, trips and falls” (SMR 123, 95% CI 17.3-873). The latter
was based on one death and the confidence interval was very wide. The Agricultural Health
Study reported a similarly raised SMR for “injury by machine” in men (SMR 4.15, 95% CI
3.18-5.31), but for most external causes the SMRs were less than one5.
There are significant drawbacks with the information stored on the database. Only four causes
of death (underlying cause plus up to three other contributory causes) are recorded for each
death. Thus, for any death where more causes are recorded, in either section one or two of the
death certificate, the other causes are not recorded. This is especially important for causes that
are not directly related to the underlying cause of death. This may include asthma, farmer’s
lung disease and other respiratory diseases, and neurological conditions such as Parkinson’s and
Alzheimer’s Diseases. However, there are no national data for the rates of death from
contributory causes of death, although these data could be useful in an internal analysis,
16 especially where cancer is mentioned as a contributory cause of death and there is no
registration for it.
In the current analysis it was only possible to examine mortality within the cohort. A significant
number of diseases, however, are not life threatening but may be associated with pesticide
exposure and agricultural work where most exposure occurs. These include respiratory diseases,
including a decrease in lung function; non-fatal accidents/injuries; incidence of acute symptoms
following exposure; musculoskeletal problems; and health in general. These health outcomes
could be examined by means of a general health survey of the PUHS cohort members.
The most important information that is lacking on the PUHS database is some indication of the
job/industry in which each individual was employed. This reflects the fact that the data are
secondary data, not collected for research purposes. Although the employer’s address was
available, it provided little information about actual occupation. Death certificates contained
information about occupation but the occupations of those who were still alive were unknown.
Thus, it was not possible to present any analysis by occupation. Related to the lack of
information on the individual’s job and industry, there was no information available on
exposure to specific pesticides or on working practices, which would help in the interpretation
of individual findings. The cohort includes a substantial number of men and women who
applied pesticides on a commercial basis before the introduction of the 1986 Control of
Pesticides Regulations, and the types of pesticides in use have changed over time. Consequently
it would not be possible to rule out exposure to certain pesticides by the first date of
certification. Availability of exposure data is critical when investigating causality. This
information, in addition to information on other factors potentially associated with disease such
as diet, smoking, and alcohol intake, could be gathered as part of a general health survey of the
PUHS cohort.
The cohort offers the opportunity to investigate actual exposures to pesticides. Laboratory
volunteer studies have been undertaken of exposure to various pesticides12-14, however, these
have not been validated in the field. Biological sampling following pesticide spraying would
allow us to determine whether individuals have been significantly exposed to pesticides, or
whether working practices, e.g. use of personal protective equipment, have prevented them
being exposed. The work would also allow exposure models that have been developed in the
laboratory to be validated.
The PUHS cohort includes all those who hold a certificate of competency in the use of
pesticides and who agreed to take part in HSE’s programme of research into the health of these
workers. Consequently, members of the cohort are distributed geographically across the whole
of Great Britain, and represent men and women working in a broad range of jobs and industries.
However, the cohort is self-selected, and it is possible that those who agreed to participate in the
research are not fully representative in terms of age, sex, attitudes towards health and safety, and
other attributes. As a consequence of their training, the men and women in this cohort are likely
to understand the risks associated with pesticide use and employ best practice when applying
pesticides. Those who apply pesticides without a certificate of competence, for example under
‘grandfather rights’, may be at greater risk of any harmful effects associated with pesticide use.
The PUHS database is an important resource that needs to be utilised, and cohort members
should be encouraged to take part in further studies to help investigate the association between
the health of pesticide users in Great Britain and the pesticides they use. This is the only
national study of men and women chronically exposed to pesticides as part of their work in
Great Britain. The findings from PUHS will make a substantial contribution to the scientific
evidence base about the role of pesticides in human health, and complement the results of other
studies such as the US Agricultural Health Study.
17 5
REFERENCES 1. USACHPPM. Entomological science programs. Pesticide timeline: US Army Center for
Health Promotion and Preventive Medicine, 2010.
2. Mellanby K. The New Naturalist. London: Collins, 1981.
3. Solomon C, Poole J, Palmer KT, Peveler R, Coggon D. Acute symptoms following work with
pesticides. Occupational Medicine-Oxford 2007;57:505-511.
4. Rushton L, Mann V. Estimating the prevalence and incidence of pesticide-related illness
presented to General Practitioners in Great Britain. Research Report 608: HSE Books,
2008.
5. Fleming LE, Bean JA, Rudolph M, Hamilton K. Mortality in a cohort of licenced pesticide
applicators in Florida. Occupational and Environmental Medicine 1999;56(1):14-21.
6. IARC. Occupational exposure in insecticide application and some pesticides, volume 53.
IARC Monograph on Evaluating the Carcinogenic Risks to Humans. Lyon:
International Agency for Research on Cancer, 1991:1-587.
7. Jeyaratnam J. Health problems of pesticide usage in the Third World. British Journal of
Industrial Medicine 1985;42:505-506.
8. Levine RS, Doull J. Global estimates of acute pesticide morbidity and mortality. Reviews of
Environmental Contamination and Toxicology 1992;129:29-50.
9. Maroni M, Fait A. Health effects in a man from long-term exposure to pesticides. A review
of the 1975-1991 literature. Toxicology 1993;78(1-3):1-180.
10. Moses M, Johnson ES, Anger WK, Burse VW, Horstman SW, Jackson RJ, et al.
Environmental equity and pesticide exposure. Toxicology and Industrial Health
1993;9(5):913-959.
11. O'Malley M. Clinical evaluation of pesticide exposure and poisonings. Lancet
1997;349(9059):1161-1166.
12. WHO. Public health impact of pesticides used in agriculture. Geneva: World Health
Organization, 1990.
13. Sanborn M, Kerr KJ, Sanin LH, Cole DC, Bassil KL, Vakil C. Non-cancer health effects of
pesticides: systematic review and implications for family doctors. Can Fam Physician
2007;53(10):1712-20.
14. Blair A, Malker H, Cantor KP, Burmeister L, Wiklund K. Cancer among farmers: A review.
Scandinavian Journal of Work Environment & Health 1985;11(6):397-407.
15. CSA. Cancer risk of pesticides in agricultural workers. Council on Scientific Affairs.
Journal of the American Medical Association 1988;260(7):959-966.
16. Zheng TZ, Blair A, Zhang YW, Weisenburger DD, Zahm SH. Occupation and risk of non­
Hodgkin's lymphoma and chronic lymphocytic leukemia. Journal of Occupational and
Environmental Medicine 2002;44(5):469-474.
18 17. Drever F. Occupational Health Decennial Supplement: The Registrar General's Decennial
Supplement for England and Wales. London: HMSO, 1995.
18. Coggan D, Harris EC, Brown TB, Rice S, Palmer KT. Occupational mortality in England
and Wales, 1991-2000. Newport: Office for National Statistics, 2009:52.
19. Lander F, Ronne M. Frequency of sister chromatid exchange and hematological effects in
pesticide-exposed greenhouse sprayers. Scandinavian Journal of Work &
Environmental Health 1995;21(4):283-288.
20. Undeger U, Basaran N. Assessment of DNA damage in workers occupationally exposed to
pesticide mixtures by the alkaline comet assay. Archives of Toxicology 2002;76(7):430­
436.
21. Bolognesi C, Landini E, Perrone E, Roggieri P. Cytogenetic biomonitoring of a floriculturist
population in Italy: micronucleus analysis by fluorescence insitu hybridization (FISH)
with an all-chromosome centromeric probe. Mutation Research 2004;557(2):109-117.
22. Scarpato R, Migliore L, Angotzi G, Fedi A, Miligi L, Loprieno N. Cytogenetic monitoring
of a group of Italian floriculturists: no evidence of DNA damage related to pesticide
exposure. Mutation Research 1996;367(2):73-82.
23. Frost G. The Pesticide Users Health Study: an analysis of cancer incidence (1987-2004).
Bootle: Health & Safety Executive, 2011 (under review).
24. McGlynn KA, Quraishi SM, Graubard BI, Weber JP, Rubertone MV, Erickson RL.
Persistent organochlorine pesticides and risk of testicular germ cell tumors. J Natl
Cancer Inst 2008;100(9):663-71.
25. Stata statistical software SE version: Release 11.1 [program]: College Station, TX:
StataCorp LP, 2010.
26. Juul S. An Introduction to Stata for Health Researchers. Texas: Stata Press, 2006.
19 6
6.1
APPENDICES
CAUSES OF DEATH SELECTED FOR ANALYSIS
ICD-9 codes
ICD-10 codes
Cause of death group
0010-7999 E800-E999 A000-R990 V010-Y899 All causes
1400-2089
C000-C970
Malignant neoplasms
1400-1729 1740-2089 C000-C439 C450-C979 Malignant neoplasms excl NMSC
1400-1499
C000-C148
MN of lip, oral cavity and pharynx
1500-1599
C150-C260
MN digestive organs
1500-1509
C150-C159
MN of oesophagus
1510-1519
C160-C169
MN of stomach
1530-1539
C180-C189
MN of colon
1540-1548
C190-C218
MN of rectum and anus
1550-1569
C220-C249
MN of liver and gall bladder
1570-1579
C250-C259
MN of pancreas
1600-1659
C300-C399
MN respiratory system
1610-1619
C320-C329
MN of larynx
1620-1629
C330-C349
MN of trachea, bronchus and lung
1720-1739
C430-C449
MN skin
1720-1729
C430-C439
Malignant melanoma of skin
1730-1732
C440-C449
Non melanoma skin cancer (NMSC)
1710-1713
C490-C499
MN other connective and soft tissue
1740-1759
C500-C509
MN of breast
1790-1849
C510-C589
MN female genital organs
1830-1839
C560-C579
MN of ovarian and uterine adnexa
1850-1879
C600-C639
MN male genital system
1850-1850
C610-C610
MN of prostate
1860-1869
C620-C629
MN testis
1880-1899
C640-C689
MN urinary system
1890-1890
C640-C640
MN of kidney, except renal pelvis
1880-1889
C670-C679
MN of bladder
1900-1929
C690-C729
MN eye, meninges, brain & central nervous system
1903-1904
C690-C699
MN of eye and adnexa
1910-1916
C710-C719
MN of brain
1920-1929
C700-C709
1930-1939
C730-C739
MN thyroid
2000-2089
C810-C969
MN of lymphoid, haematopoietic and related tissue
2014-2019
C810-C819
Hodgkin's disease
2020-2029 2000-2009 C820-C859
C720-C729 MN of central nervous system and meninges
Non-Hodgkin's lymphoma
20 ICD-9 codes
ICD-10 codes
Cause of death group
2030-2039
C900-C900
Multiple myeloma
2040-2089
C910-C959
Leukaemia
2900-3190
F000-F999
Mental and behavioural disorders
3200-3899
G000-H959
Diseases of the nervous system and the sense organs
3352-3352
G122-G122
Motor neuron disease
3320-3320
G200-G209
Parkinson's disease
3310-3310
G300-G309
Alzheimer's disease
3200-3790
H000-H599
Diseases of eye and adnexa
3900-4599
I000-I990
Diseases of the circulatory system
4100-4149
I200-I259
Ischaemic heart diseases
4200-4239 4250-4299 I300-I339
I390-I528
Other heart diseases
4300-4380
I600-I698
Cerebrovascular diseases
4600-5199
J000-J998
Diseases of the respiratory system
4900-4929
J400-J449
Bronchitis, emphysema and other COPD
4930-4939
J450-J460
Asthma
4950-4950
J670-J670
Farmer's lung disease
5200-5799
K000-K938
Diseases of the digestive system
E800-E999
V010-Y980
External causes of morbidity and mortality
E800-E848
V010-V999
Transport accidents
E880-E888
W000-W199
Accidental falls
E885-E885
W010-W010
Slips, trips or stumbling
E916-E916
W200-W209
Injury by falling object
E919-E919
W300-W319
Injury by machinery
E922-E922
W320-W339
Injury by firearm
E910-E915
W650-W849
Accidents by submersion, suffocation & foreign bodies
E925-E925
W850-W879
Injury by electric current
E850-E863
X480-X499
Accidental poisoning
E950-E959
X600-X840
Suicide & self-inflicted injury
E980-E989
Y100-Y349
Injury, undetermined intent
21 6.2
CITY & GUILDS LAND BASED SERVICES CERTIFICATES OF
COMPETENCE
The following table shows the City & Guilds Land Based Services certificates of competence,
which are recorded in the PUHS database.
Certificate
PA01
PA02
PA02A
PA02B
PA02C
PA02D
PA02E
PA02F
PA02AR
PA02BR
PA02ST
PA03
PA03A
PA03B
PA03C
PA04
PA05A
PA05B
PA05C
PA06
PA06A
PA06AW
PA06B
PA06C
PA06CW
PA06D
PA07
PA07A
PA07B
PA08
PA09
PA10
PA11
PA11A
PA11B
PA12
PA13
Module
Foundation
Ground crop sprayer – unspecified
Ground crop sprayer – boom type hydraulic nozzle
Ground crop sprayer – boom type rotary atomiser
Ground crop sprayer – boom type twin fluid nozzle
Ground crop sprayer – electro-statically charged
Ground crop sprayer – boom type fitted with downward air
assistance
Wick applicator – boom or frame type
Vehicle mounted kerb sprayer – hydraulic nozzle type
Vehicle mounted kerb sprayer – rotary atomiser type
Spray trains – hydraulic nozzle and rotary atomiser
Air sprayer – unspecified
Broadcast air blast sprayer – mounted or trailed
Variable geometry boom air assisted sprayer – mounted or
trailed
Variable geometry boom sprayer without air assistance
Granule applicatory – mounted or trailed
Boat mounted applicator – hydraulic nozzle boom
Hand held applicators – application to water using viscous gel
applicators
Boat mounted applicator – viscous gel applicator
Hand-held applicators – unspecified
Hand held applicators – hydraulic nozzle and/or rotary atomiser
types
Hand held applicators – application to water using hydraulic
nozzle or rotary atom
Hand held applicators – application to water using viscous gel
applicators
Handheld applications – granule applicator
Hand held applicators – application to water using granule
applicators
Hand held applicators – requiring minimal calibration
Aerial application
Aerial applicator – pilot
Aerial applicator – fieldsman/ground marker
Mixer/loader
Fogging, misting and smokes
Dipping, bulbs, corms, plant material or containers
Seed treating equipment – unspecified
Seed treating equipment – mobile equipment
Seed treating equipment – static equipment
Application of pesticides to material as a continuous or batch
process
Sub surface liquid applicator
22 Grouping
Foundation
Ground crop sprayer
Ground crop sprayer
Ground crop sprayer
Ground crop sprayer
Ground crop sprayer
Ground crop sprayer
Ground crop sprayer
Ground crop sprayer
Ground crop sprayer
Ground crop sprayer
Other
Other
Other
Other
Other
Other
Other
Other
Hand-held operator
Hand-held operator
Hand-held operator
Hand-held operator
Hand-held operator
Hand-held operator
Hand-held operator
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
6.3
STRATIFIED TABLES OF RESULTS
Standardised mortality ratios, stratified by a number of possible explanatory variables, were
calculated. The number of deaths among women was small, so stratified analyses are presented
only for men. In order to reduce the number of very small counts and empty cells within the
stratified tables, SMRs are presented by grouped causes of death rather than individual causes.
Table 9 shows the mortality pattern among men by region of residence, Table 10 gives mortality
in men by year of birth, Table 11 gives mortality patterns by age at the first test, Table 12
presents mortality by length of time since the first licence, and Table 13 shows mortality by the
type(s) of module for which each cohort member had received a certificate of competence.
Overall, there were no obvious associations between mortality and the possible explanatory
variables. The majority of SMRs were not statistically significantly different to 1.00; some
indicated that the number of deaths was statistically significantly smaller than expected when
compared with the GB population. In these stratified tables, only one statistically significantly
raised SMR was observed: SMR 1.51 (95% CI 1.09-2.11) for lymphohaematopoietic cancers
among men who had held a licence for 5-9 years. In the context of the number of statistical tests
presented, and without further evidence of an excess of these cancers in men, this statistically
significant SMR should be interpreted with caution.
23 Table 9
Cause of Death
All causes
Obs
208
Mortality amongst men by region, 1987-2005
Scotland
SMR
0.56 (0.49-0.64)
Obs
318
North
SMR
0.63 (0.56-0.70)
Obs
226
Midlands
SMR
0.50 (0.44-0.57)
Obs
227
Eastern
SMR
0.52 (0.46-0.60)
Malignant neoplasms (all)
Digestive organs
Respiratory system
Skin
Male genital system
Urinary system
Eye, brain & CNS
Lymphohaematopoietic
84
21
26
1
4
6
3
12
0.83
0.69
0.79
0.51
0.76
1.09
0.64
1.60
(0.67-1.02)
(0.45-1.06)
(0.54-1.16)
(0.07-3.62)
(0.29-2.03)
(0.49-2.42)
(0.21-1.98)
(0.91-2.81)
120
48
22
4
4
5
8
17
0.81
1.08
0.55
1.08
0.49
0.58
0.99
1.13
(0.68-0.97)
(0.82-1.44)
(0.36-0.84)
(0.40-2.87)
(0.18-1.31)
(0.24-1.41)
(0.50-1.98)
(0.71-1.82)
73
22
21
3
5
3
2
5
0.54
0.55
0.58
0.92
0.67
0.39
0.28
0.38
(0.43-0.69)
(0.36-0.83)
(0.38-0.89)
(0.30-2.86)
(0.28-1.61)
(0.12-1.20)
90.07-1.13)
(0.16-0.90)
82
24
18
4
8
8
4
9
0.61
0.60
0.48
1.35
0.99
1.02
0.62
0.71
(0.49-0.76)
(0.40-0.89)
(0.30-0.76)
(0.51-3.60)
(0.50-1.98)
(0.51-2.03)
(0.23-1.65)
(0.37-1.37)
Diseases of the:
Nervous system & sense organs
Circulatory system
Respiratory system
Digestive system
5
60
9
6
0.61
0.49
0.38
0.21
(0.25-1.46)
(0.38-0.64)
(0.20-0.73)
(0.09-0.47)
5
110
16
11
0.37
0.67
0.47
0.36
(0.16-0.90)
(0.56-0.81)
(0.29-0.77)
(0.20-0.65)
5
86
7
7
0.43
0.58
0.23
0.26
(0.18-1.03)
(0.47-0.72)
(0.11-0.48)
(0.12-0.55)
5
77
11
2
0.47
0.51
0.34
0.08
(0.20-1.13)
(0.41-0.64)
(0.19-0.62)
(0.02-0.33)
External causes
36
0.67 (0.48-0.93)
45
0.59 (0.44-0.79)
38
0.58 (0.42-0.80)
36
0.69 (0.50-0.96)
Number of deaths observed; Standardised mortality ratio; 95% Confidence intervals
24
Table 9 (continued)
Cause of Death
Obs
372
All causes
South East
SMR
0.66 (0.60-0.73)
Malignant neoplasms (all)
Digestive organs
Respiratory system
Skin
Male genital system
Urinary system
Eye, brain & CNS
Lymphohaematopoietic
135
47
21
0
15
9
9
18
1.50
0.90
1.05
1.10
Diseases of the:
Nervous system & sense organs
Circulatory system
Respiratory system
Digestive system
6
119
19
11
0.43
0.62
0.47
0.34
External causes
62
0.79 (0.67-0.94)
0.92 (0.69-1.22)
0.45 (0.29-0.68)
Obs
170
South West
SMR
0.53 (45-0.61)
Obs
70
Wales
SMR
0.61 (0.49-0.78)
(0.90-2.49)
(0.47-1.74)
(0.55-2.01)
(0.69-1.74)
63
19
14
2
3
3
6
8
0.66
0.66
0.54
0.88
0.54
0.54
1.21
0.85
(0.51-0.84)
(0.42-1.04)
(0.32-0.91)
(0.22-3.52)
(0.18-1.69)
(0.17-1.68)
(0.54-2.70)
(0.42-1.70)
26
11
4
1
1
0
2
4
(0.19-0.95)
(0.52-0.75)
(0.30-0.74)
(0.19-0.61)
2
52
11
1
0.24
0.49
0.49
0.05
(0.06-0.96)
(0.37-0.64)
(0.27-0.89)
(0.01-0.38)
0
26
2
1
0.68 (0.46-1.00)
0.25 (0.06-1.00)
0.15 (0.02-1.06)
0.86 (0.67-1.10)
33
0.72 (0.51-1.01)
14
0.92 (0.54-1.55)
Number of deaths observed; Standardised mortality ratio; 95% Confidence intervals
25 0.76
1.07
0.43
1.24
0.51
(0.52-1.11)
(0.59-1.93)
(0.16-1.14)
(0.17-8.78)
(0.07-3.63)
1.14 (0.28-4.54)
1.20 (0.45-3.20)
Table 10
Cause of Death
Mortality in men by year of birth, 1987-2005
Obs
184
All causes
Before 1930
SMR
0.58 (0.50-0.67)
Obs
489
1930-1939
SMR
0.59 (0.54-0.65)
Obs
391
1940-1949
SMR
0.56 (0.51-0.62)
Malignant neoplasms (all)
Digestive organs
Respiratory system
Skin
Male genital system
Urinary system
Eye, brain & CNS
Lymphohaematopoietic
68
19
11
2
7
4
1
10
0.65
0.62
0.32
1.92
0.65
0.60
0.50
1.42
(0.51-0.83)
(0.40-0.97)
(0.18-0.58)
(0.48-7.69)
(0.31-1.36)
(0.23-1.61)
(0.07-3.52)
(0.77-2.64)
232
88
59
4
23
12
8
17
0.77
0.94
0.61
1.01
1.08
0.65
0.88
0.76
(0.67-0.87)
(0.77-1.17)
(0.48-0.79)
(0.38-2.69)
(0.72-1.62)
(0.37-1.14)
(0.44-1.75)
(0.47-1.22)
163
54
39
3
3
12
10
24
0.66
0.70
0.55
0.55
0.32
0.84
0.81
1.14
(0.57-0.77)
(0.54-0.92)
(0.40-0.75)
(0.18-1.70)
(0.10-1.00)
(0.48-1.47)
(0.43-1.50)
(0.76-1.70)
Diseases of the:
Nervous system & sense organs
Circulatory system
Respiratory system
Digestive system
4
96
11
1
0.71
0.70
0.30
0.10
(0.27-1.90)
(0.57-0.85)
(0.17-0.54)
(0.01-0.69)
7
172
36
8
0.50
0.51
0.50
0.24
(0.24-1.05)
(0.44-0.59)
(0.36-0.69)
(0.12-0.47)
5
149
12
20
0.34
0.59
0.27
0.41
(0.14-0.81)
(0.50-0.69)
(0.16-0.48)
(0.27-0.64)
0.40 (0.10-1.61)
11
0.50 (0.28-0.91)
27
External causes
2
Number of deaths observed; Standardised mortality ratio; 95% Confidence intervals
26 0.54 (0.37-0.79)
Table 10 (continued)
Cause of Death
All causes
Obs
278
1950-1959
SMR
0.62 (0.55-0.70)
Obs
180
1960-1969
SMR
0.49 (0.43-0.57)
Obs
66
Malignant neoplasms (all)
Digestive organs
Respiratory system
Skin
Male genital system
Urinary system
Eye, brain & CNS
Lymphohaematopoietic
81
24
14
4
2
5
9
12
0.75
0.73
0.61
0.90
0.75
0.86
0.93
0.92
(0.60-0.93)
(0.49-1.09)
(0.36-1.03)
(0.34-2.39)
(0.19-3.01)
(0.36-2.05)
(0.48-1.79)
(0.52-1.61)
32
6
3
0
4
1
6
8
0.66 (0.47-0.94)
0.56 (0.25-1.24)
0.65 (0.21-2.01)
2.34
0.60
0.87
0.73
(0.84-5.96)
(0.08-1.28)
(0.39-1.94)
(0.36-1.46)
7
1
0
2
1
0
0
2
Diseases of the:
Nervous system & sense organs
Circulatory system
Respiratory system
Digestive system
7
82
13
7
0.49
0.65
0.61
0.15
(0.23-1.02)
(0.52-0.81)
(0.35-1.05)
(0.07-0.32)
4
25
3
3
0.26
0.47
0.22
0.11
(0.10-0.69)
(0.32-0.70)
(0.07-0.68)
(0.04-0.36)
0
6
0
0
External causes
72
0.84 (0.67-1.06)
103
0.67 (0.55-0.81)
47
1970-1979
SMR
0.62 (0.48-0.78)
0.77 (0.37-1.62)
0.84 (0.12-6.00)
3.29 (0.82-13.2)
2.30 (0.32-16.3)
0.70 (0.18-2.82)
0.76 (0.35-1.73)
0.78 (0.58-1.03)
Number of deaths observed; Standardised mortality ratio; 95% Confidence intervals
27 Obs
3
1980SMR
0.52 (0.17-1.60)
0
0
0
0
0
0
0
0
1
0
0
0
3.32 (0.49-23.6)
2
0.56 (0.14-2.22)
Table 11
Cause of Death
All causes
Obs
138
Mortality in men by age at first test, 1987-2005 <25
SMR
0.54 (0.46-0.64)
Malignant neoplasms (all)
Digestive organs
Respiratory system
Skin
Male genital system
Urinary system
Eye, brain & CNS
Lymphohaematopoietic
15
2
1
2
2
0
2
3
0.60
0.49
0.69
1.12
1.75
Diseases of the:
Nervous system & sense organs
Circulatory system
Respiratory system
Digestive system
2
14
0
0
External causes
93
(0.36-0.99)
(0.12-1.97)
(0.10-4.93)
(0.28-4.46)
(0.44-7.01)
Obs
99
25-29
SMR
0.54 (0.44-0.65)
19
4
2
0
3
1
3
5
3.21
1.00
0.82
0.90
0.18 (0.05-0.73)
0.60 (0.35-1.01)
3
14
4
1
0.39
0.46
0.55
0.07
0.70 (0.57-0.86)
56
0.51 (0.13-2.05)
0.41 (0.13-1.27)
0.72 (0.46-1.12)
0.63 (0.24-1.68)
0.69 (0.17-2.74)
Obs
127
30-34
SMR
0.62 (0.52-0.74)
0.77
0.61
0.29
1.43
(1.04-9.95)
(0.14-7.10)
(0.26-2.53)
(0.37-2.16)
31
7
2
3
0
3
4
8
(0.13-1.21)
(0.28-0.78)
(0.21-1.46)
(0.01-0.49)
0.79 (0.61-1.03)
28 35-39
SMR
0.60 (51-0.70)
1.51 (0.49-4.69)
0.90 (0.34-2.40)
1.32 (0.66-2.64)
48
14
11
1
2
2
4
7
0.76
0.72
0.77
0.42
1.30
0.57
0.77
0.99
(0.57-1.01)
(0.43-1.22)
(0.42-1.39)
(0.06-3.00)
(0.32-5.18)
(0.14-2.29)
(0.29-2.06)
(0.47-2.07)
6
33
4
5
0.78
0.68
0.44
0.24
(0.35-1.75)
(0.48-0.95)
(0.17-1.18)
(0.10-0.58)
1
44
7
6
0.14
0.61
0.59
0.25
(0.02-0.98)
(0.45-0.82)
(0.28-1.24)
(0.11-0.55)
43
0.80 (0.59-1.08)
27
0.68 (0.46-0.99)
Number of deaths observed; Standardised mortality ratio; 95% Confidence intervals
(0.54-1.09)
(0.29-1.27)
(0.07-1.15)
(0.46-4.43)
Obs
143
Table 11 (continued)
Cause of Death
Obs
179
All causes
40-44
SMR
0.56 (0.48-0.64)
Obs
205
45-49
SMR
0.55 (0.48-0.63)
50+
Obs
700
SMR
0.59 (0.55-0.64)
0.73
0.84
0.53
1.31
0.92
0.73
0.84
0.85
(0.65-0.81)
(0.69-1.01)
(0.42-0.66)
(0.62-2.75)
(0.64-1.31)
(0.46-1.14)
(0.45-1.56)
(0.58-1.24)
0.53
0.58
0.41
0.21
(0.30-0.96)
(0.52-0.65)
(0.31-0.55)
(0.11-0.38)
Malignant neoplasms (all)
Digestive organs
Respiratory system
Skin
Male genital system
Urinary system
Eye, brain & CNS
Lymphohaematopoietic
78
26
18
2
1
5
7
11
0.75
0.79
0.64
0.70
0.31
0.83
1.11
1.13
(0.60-0.93)
(0.54-1.16)
(0.40-1.02)
(0.17-2.79)
(0.04-2.23)
(0.34-1.98)
(0.53-2.33)
(0.62-2.03)
85
31
21
0
2
4
4
13
0.63 (0.51-0.78)
0.73 (0.52-1.16)
0.52 (0.34-0.80)
0.35
0.50
0.65
1.18
(0.09-1.40)
(0.19-1.34)
(0.24-1.72)
(0.68-2.02)
307
108
71
7
30
19
10
26
Diseases of the:
Nervous system & sense organs
Circulatory system
Respiratory system
Digestive system
2
54
5
12
0.26
0.48
0.28
0.45
(0.06-1.03)
(0.37-0.63)
(0.12-0.66)
(0.26-0.80)
3
85
9
5
0.41
0.61
0.36
0.21
(0.13-1.26)
(0.49-0.75)
(0.19-0.70)
(0.09-0.51)
11
286
46
10
External causes
19
0.60 (0.38-0.94)
11
0.51 (0.28-0.92)
15
Number of deaths observed; Standardised mortality ratio; 95% Confidence intervals
29 0.51 (0.31-0.85)
Table 12
Mortality in men by length of time since first licensed, 1987-2005
15+ years
SMR
0.56 (0.48-0.65)
Obs
341
<5 years
SMR
0.49 (0.44-0.55)
Obs
501
5-9 years
SMR
0.60 (0.55-0.66)
Obs
563
10-14 years
SMR
0.62 (0.57-0.67)
Malignant neoplasms (all)
Digestive organs
Respiratory system
Skin
Male genital system
Urinary system
Eye, brain & CNS
Lymphohaematopoietic
108
42
18
4
5
7
11
11
0.60
0.81
0.36
0.80
0.69
0.72
0.97
0.54
(0.50-0.73)
(0.60-1.10)
(0.23-0.57)
(0.30-2.13)
(0.29-1.66)
(0.34-1.51)
(0.54-1.75)
(0.30-0.97)
182
57
37
2
12
11
6
35
0.76
0.79
0.54
0.34
0.99
0.80
0.47
1.51
(0.65-0.87)
(0.61-1.02)
(0.39-0.75)
(0.09-1.38)
(0.56-1.74)
90.44-1.44)
(0.21-1.04)
(1.09-2.11)
217
75
54
7
17
10
13
21
0.75
0.86
0.68
1.16
0.92
0.59
0.99
0.84
(0.66-0.86)
(0.68-1.07)
(0.52-0.88)
(0.55-2.44)
(0.57-1.47)
(0.32-1.09)
(0.58-1.71)
(0.55-1.29)
76
18
17
2
6
6
4
6
0.69
0.53
0.56
0.97
0.71
0.90
0.92
0.66
(0.55-0.86)
(0.34-0.85)
(0.35-0.90)
(0.24-3.87)
(0.32-1.59)
(0.40-2.00)
(0.34-2.46)
(0.30-1.47)
Diseases of the:
Nervous system & sense organs
Circulatory system
Respiratory system
Digestive system
3
114
12
6
0.16
0.53
0.33
0.18
(0.05-0.50)
(0.44-0.63)
(0.19-0.58)
(0.08-0.40)
5
169
22
9
0.25
0.61
0.39
0.18
(0.10-0.60)
(0.53-0.71)
(0.26-0.59)
(0.09-0.35)
13
187
30
19
0.58
0.61
0.43
0.30
(0.34-1.00)
(0.53-0.70)
(0.30-0.61)
(0.19-0.48)
7
60
11
5
0.83
0.51
0.39
0.22
(0.40-1.75)
(0.40-0.66)
(0.22-0.70)
(0.09-0.53)
0.59 (0.48-0.73)
93
0.76 (0.62-0.93)
61
0.70 (0.54-0.89)
22
0.99 (0.65-1.50)
Cause of Death
All causes
External causes
88
Number of deaths observed; Standardised mortality ratio; 95% Confidence intervals
30 Obs
186
Table 13
Cause of Death
All causes
Obs
297
Foundation only
SMR
0.75 (0.67-0.84)
Mortality in men by modules taken, 1987-2005 Foundation + Ground crop sprayer
Obs
SMR
332
0.47 (0.42-0.52)
Foundation + Hand-held operator
Obs
SMR
854
0.62 (0.58-0.66)
Obs
27
All three
SMR
0.44 (0.31-0.65)
Malignant neoplasms (all)
Digestive organs
Respiratory system
Skin
Male genital system
Urinary system
Eye, brain & CNS
Lymphohaematopoietic
104
33
26
2
7
6
3
12
0.85
0.90
0.72
0.82
0.90
0.83
0.56
1.11
(0.70-1.02)
(0.64-1.26)
(0.49-1.06)
(0.21-3.29)
(0.42-1.89)
(0.37-1.86)
(0.18-1.74)
(0.63-1.96)
121
35
23
3
12
7
12
18
0.60
0.59
0.42
0.59
1.12
0.61
1.08
0.89
(0.50-0.72)
(0.42-0.82)
(0.28-0.64)
(0.19-1.83)
(0.64-1.97)
(0.29-1.29)
(0.61-1.89)
(0.56-1.41)
319
113
69
10
21
18
16
35
0.76
0.90
0.58
1.06
0.89
0.74
0.77
0.91
(0.68-0.85)
(0.75-1.08)
(0.46-0.74)
(0.57-1.98)
(0.58-1.36)
90.47-1.18)
(0.47-1.26)
(0.65-1.26)
9
2
0
0
0
1
1
3
Diseases of the:
Nervous system & sense organs
Circulatory system
Respiratory system
Digestive system
3
107
19
7
0.33
0.76
0.63
0.32
(0.11-1.02)
(0.63-0.92)
(0.40-0.99)
(0.15-0.68)
8
97
11
3
0.42
0.43
0.24
0.07
(0.21-0.85)
(0.36-0.53)
(0.13-0.43)
(0.02-0.21)
12
291
43
27
0.36
0.62
0.44
0.32
(0.20-0.63)
(0.55-0.70)
(0.33-0.60)
(0.22-0.46)
2
8
1
0
1.05 (0.26-4.21)
0.51 (0.25-1.02)
0.32 (0.04-2.27)
1.06 (0.80-1.41)
80
0.69 (0.55-0.86)
115
0.66 (0.55-0.80)
7
0.48 (0.23-1.00)
External causes
47
Number of deaths observed; Standardised mortality ratio; 95% Confidence intervals
31 0.62 (0.32-1.20)
0.48 (0.12-1.91)
1.30 (0.18-9.25)
0.94 (0.13-6.70)
1.74 (0.56-5.38)
Table 13 (continued)
Cause of Death
Obs
81
All causes
Other Modules
SMR
0.38 (0.30-0.47)
Malignant neoplasms (all)
Digestive organs
Respiratory system
Skin
Male genital system
Urinary system
Eye, brain & CNS
Lymphohaematopoietic
30
9
8
0
0
2
2
5
0.48 (0.33-0.68)
0.90 (0.75-1.08)
0.46 (0.23-0.93)
Diseases of the:
Nervous system & sense organs
Circulatory system
Respiratory system
Digestive system
3
27
1
2
0.54
0.38
0.07
0.15
External causes
15
0.47 (0.29-0.79)
0.56 (0.14-2.22)
0.61 (0.15-2.43)
0.82 (0.34-1.97)
(0.17-1.67)
(0.26-0.56)
(0.01-0.48)
(0.04-0.61)
Number of deaths observed; Standardised mortality ratio; 95% Confidence intervals
32 6.4
REVIEW OF THE LITERATURE
The body of evidence from studies of chronic disease in pesticide-exposed worker populations
generally report consistent findings in mortality patterns, despite a variety of methodological
issues15-21. Exposure data is frequently unavailable, but where it is, demonstrating a causal
relationship with a specific pesticide may still present difficulties: the data may lack detail,
many pesticide applicators use a variety of pesticides and work practices, and hence exposure
may vary widely between applicators. Farmers and other agricultural workers, pesticide
manufacturers and applicators, the main worker groups that have been studied, tend to be
healthier compared with the general population, especially with respect to cardiovascular
disease and the diseases associated with heavy tobacco and alcohol use. They are, however, at
an increased risk from accidents and fatal injuries 22, some of this possibly pesticide-related (e.g.
aerial sprayers). Farmers are also more likely to die of infectious and non-malignant respiratory
disease; to the extent that certain pesticides have immunologic effects, pesticide exposure may
contribute toward these risks, although this aspect has not been studied rigorously 3 4 16 21 23-27.
Exposure to pesticides has been linked to increased risk of incidence/mortality from a number
of diseases and also a number of cancers. The diseases include respiratory (e.g. chronic
bronchitis and asthma), neurological (e.g. Parkinson’s and Alzheimer’s disease), and
poisonings. Cancers include brain, breast, pancreas, prostate, non-Hodgkin’s lymphoma
(NHL), leukaemia and multiple myeloma. A review of the major findings in the published
literature follows.
6.4.1
Respiratory Diseases
6.4.1.1
Farmers lung disease
Farmers’ lung disease, or hypersensitivity pneumonitis, is an important source of respiratory
morbidity among farmers. There have typically been around five or fewer new assessed cases
for disablement benefit each year over the last few years, though in 2007 there were 20 cases d .
Farmers’ lung disease was recorded as the underlying cause of death typically between 5-10
times per year over the last few years e . The prevalence of farmers’ lung disease in the United
Kingdom has been reported to be 420-3,000 cases per 100,000 at risk persons, and incidence
between 8-540 cases per 100,000. Incidence is highly variable and depends on multiple factors,
such as intensity, frequency, and duration of exposure, type of farming, and climate. It is also
more common in the northern latitudes and among dairy farmers. Farmers’ lung disease rarely
progresses to a life-threatening level, which suggests that there are substantially more cases than
those receiving compensation. Evidence from SWORD/OPRA suggests the number of new
cases varied between about 20 and 50 per year over the last ten years with no obvious trendsd. A
significant number of farmers develop mild chronic lung impairment, which is predominantly
obstructive airflow disease associated with mild emphysematous changes. Farmers lung disease
is an immune complex hypersensitivity (Type III hypersensitivity): thermoactinomycetes and
other bacteria in mouldy hay are well-established causes of hypersensitivity pneumonitis28 29.
Other factors, such as isocyanates, have also been hypothesised to influence the development of
hypersensitivity pneumonitis28. Pesticides have been suggested as a risk factor but this
hypothesis has rarely been explored.
The disease was recognised as a significant cause of death among farmers in the last published
Occupational Health Decennial Supplement (PMR=1089, 95% CI=823-1416)30. Analysis of
data by region showed a more than 20-fold variation with particularly high proportions in
d
e
http://www.hse.gov.uk/statistics/causdis/respiratory
http://www.statistics.gov.uk/statbase/Product.asp?vlnk=618
33
farmers from Wales and the North-east of England. These areas have extensive hill farming and
a relatively damp climate predisposing the formation of the moulds in hay that cause the
disease.
The US Agricultural Health Study (AHS) is a prospective cohort study of farmers and their
spouses in Iowa and North Carolina 31. Hoppin et al 32 analysed cross-sectional enrolment data
between 1993-7 from the AHS, and observed 427 cases of farmers’ lung disease among farmers
in the study and 38 cases among spouses. Compared to 17,952 and 26,011 controls,
respectively, these cases were more likely to be exposed to pesticides over their lifetime, in
particular among the farmers, a history of a high pesticide exposure event (OR=1.75, 95%
CI=1.39-2.21), use ever of organochlorine (OC) pesticides (OR=1.34, 95% CI=1.04-1.74) and
use ever of carbamate pesticides (OR=1.32, 95% CI=1.03-1.68). Analysis of individual
pesticides showed variable results. Two organochlorine pesticides associated with farmers’ lung
disease were lindane (OR=1.25, 95% CI 0.98-1.60) and dichlorodiphenyl trichloroethan (DDT)
(OR=1.25, 95% CI 0.95-1.65), although these results were not statistically significant. Also, two
carbamate pesticides were associated with farmers’ lung disease, but in opposite directions;
aldicarb, an insecticide, had a positive association (OR=1.65, 95% CI 1.04-2.61), whereas
benomyl, a fungicide, had an inverse association (OR=0.60, 95% CI 0.33-1.07). Although these
risks were observed, confounding by historic farm activities could not be ruled out.
6.4.1.2
Chronic obstructive pulmonary disease
Studies have suggested that pesticide use may increase the risk of chronic bronchitis. Pesticides
have been associated with cough and phlegm among participants in the Singapore Chinese
Health Study33. Also, in a study of non-smoking women in the AHS, chronic bronchitis was
associated with exposure to dichlorvos, dichlorodiphenyl thrichloroethane (DDT), cyanazine,
paraquat and methyl bromide after multivariate adjustment34. A study of the baseline data
collected for the AHS reported that 11 pesticides were significantly associated with chronic
bronchitis, after adjustment for correlated pesticides and confounders35. These included
carbamates, OCs, organophosphates (OPs) and pyrethroid insecticides, and herbicides (2,4,5-T;
2,4,5-TP; chlorimuron-ethyl (CME), petroleum oil). However, farmers undertake a variety of
activities that potentially put them at risk of chronic bronchitis, including confinement farming
36 37
, grain handling38, and livestock production39 40. A recent population-based survey of 1,258
men and women in Austria found that 23% had any type of farming experience, and that
farming was the only occupation with increased prevalence of chronic obstructive pulmonary
disease (COPD)41. Substantially more farmers had at least mild COPD compared to non-farmers
(30% compared to 22%), and proportionally they also exhibited more severe COPD symptoms
(14% compared to 8%).
6.4.1.3
Other respiratory symptoms
In the US, applying pesticides to livestock has been found to be associated with a high
prevalence of respiratory symptoms42, and there is some evidence of an association between
working with pesticides and prevalence of cough and chronic phlegm43. In Saskatchewan,
Canada, farmers working with carbamates and OPs have reported a higher prevalence of asthma
than other farmers44.
In the US AHS an increased odds of wheeze was associated with 11 of 40 pesticides among
more than 20,000 farmer pesticide applicators45. Pesticides associated with increased wheeze
included the herbicides paraquat, atrazine, alachlor and chlorimuron-ethyl (CME) and the OP
insecticides parathion and chlorpyrifos. Significant dose-response relationships were also
demonstrated for chlorpyrifos, s-ethyl-dipropylthiocarbamate (EPTC), paraquat and parathion.
Later work showed a dose-response trend for CME and phorate46.
34 6.4.2
Neurological Diseases
6.4.2.1
Neurological symptoms
The neurological consequences of high-level exposure to pesticides are well established47 and
symptoms can result from exposure to most types of compounds (for example, OPs, carbamates,
OCs, fungicides and fumigants)48. However, only OPs have been studied in detail. Mild
exposures lead to symptoms including dizziness, headache, nausea and vomiting, papillary
constriction, and excessive sweating, tearing and salivation. High exposures can lead to muscle
weakness and twitches, changes in heart rate, and bronchospasm and can progress to
convulsions and coma. Some patients may develop OP-induced delayed neuropathy two to five
weeks after exposure, which involves sensory abnormalities, muscle cramps, weakness and
even paralysis. In some cases of acute OP poisoning, neurological effects were observed ten or
more years after poisoning49, suggesting that the residual damage is permanent.
In a recent study, the prevalence and pattern of neuropsychiatric symptoms were consistently
more common in past users of sheep dip and other pesticides than in those who had never
worked with pesticides50. A study of applicators in the AHS observed an association between
the number of neurological symptoms experienced and cumulative lifetime days of insecticide
use, fumigant use, and weaker relationships for cumulative lifetime days of herbicide use and
fungicide use51. Beseler et al 52 noted that depression was significantly associated with a history
of pesticide poisoning in female spouses of applicators in the AHS.
Chronic low-level exposure is associated with a broad range of non-specific symptoms,
including headache, dizziness, insomnia, confusion, and difficulty concentrating47. Men and
women who applied OPs, including greenhouse workers53, farmers and pesticide applicators54,
commercial termiticide applicators55 and sheep dippers56, all reported higher symptom
prevalence than non-exposed. In a review of the health effects of chronic exposure to pesticides,
39 out of 41 studies showed a positive increase in one or more neurological abnormalities
(including malaise, depression, mood changes, cognitive dysfunction) with pesticide exposure57.
6.4.2.2
Parkinson’s disease
There is extensive literature suggesting that pesticide exposure may increase the risk of
Parkinson’s disease58-61. Numerous case-control studies have suggested an association between
pesticide exposure and Parkinson’s disease with ORs ranging from 1.6 to 7.062. However, many
of the studies defined exposure as ever exposed to any pesticide, a broad definition that could
give rise to significant misclassification, which might weaken the association. The results of
cohort studies indicate that employment in certain occupations involving pesticide exposure
may increase the risk of Parkinson’s disease51 60 63 64.
However, findings have been inconsistent, and a number of methodological difficulties were
identified that might account for them65 66. These include: variation in diagnostic criteria for
Parkinson’s disease, limitations in exposure assessment and variable adjustment for other
potential risk factors. In particular, Parkinson’s disease risk is related to living in rural areas,
drinking well water and pesticide exposure. With regards to the latter, and the wide range of
compounds subsumed under the title ‘pesticide’, the biological implausibility of all pesticides
having a similar toxicological action was noted.
In a case-control study in four European centres (Scotland, Sweden, Italy, Romania), 649 cases
and 1,587 controls were recruited, and their lifetime occupational histories collected 67. Scottish
data showed a non-significant increased risk for agriculture (Dictionary of Occupational Titles
[DOT]: OR= 1.32, 95% CI=0.81-2.16; International Standard Industrial Classification [ISIC]:
OR=1.30, 95% CI=0.84-2.02). Analysis of information from all four centres resulted in a
35 reduced risk (DOT: OR=1.02, 95% CI=0.82-1.28; ISIC: OR=1.05, 95% CI=0.85-1.31). In a
further analysis these data were added to cases from Malta68, giving a total of 959 cases with
parkinsonism, 767 with Parkinson’s disease, and 1,989 controls. Logistic regression analysis of
all cases noted a significant risk with any exposure to pesticides (OR=1.29, 95% CI=1.02-1.63),
and an exposure-response when average annual intensity of exposure was the metric (low vs. no
exposure: OR=1.13, 95% CI=0.82-1.57; high vs. no exposure: OR=1.41, 95% CI=1.06-1.88).
When only Parkinson’s disease cases were considered, similar but slightly lower risks were
observed (any exposure: OR=1.25, 95% CI=0.97-1.61; low vs. no exposure: OR=1.09, 95%
CI=0.77-1.55; high vs. no exposure: OR=1.39, 95% CI=1.02-1.89).
In a case-control study from the US, 319 cases and 296 relative and other controls were
examined69. Overall, individuals with Parkinson’s disease were significantly more likely to
report direct pesticide application than their unaffected relatives (OR=1.61, 95% CI=1.13-2.29).
Significant exposure-response relationships with frequency and duration of pesticide use, and
cumulative exposure were reported. Excess risk was observed in individuals exposed to
insecticides and herbicides, and specifically OC and organophosphorous compounds.
Among male farmers in the Occupational Health Decennial Supplement, a significant excess of
Parkinson’s disease was observed (PMR=125, 95% CI=110-142)10.
6.4.2.3
Amyotrophic lateral sclerosis
Information on the association between pesticide exposure and the risk of other neurological
disease is sparser. Several studies have suggested that the risk of amyotrophic lateral sclerosis is
related to farming as an occupation, although the evidence for an increased risk with pesticide
exposure is inconclusive 70-74.
6.4.2.4
Alzheimer’s disease
Alzheimer’s disease is the most common cause of dementia in the elderly. Several risk factors
have been identified including head injury, low serum levels of folate and vitamin B12, raised
plasma and total homocysteine levels, a family history of Alzheimer’s disease or dementia,
fewer years of education, lower income and lower occupational status75. The evidence for an
increased risk of Alzheimer’s disease for occupational exposures, including pesticides, is
generally not consistent61 76-78. A recent review of both case-control and cohort studies published
up to June 2003 found that for pesticides, studies of greater quality and prospective design
found increased and statistically significant associations79.
6.4.3
Cancer
The International Agency for Research on Cancer (IARC) has classified occupational exposures
in spraying and application of non-arsenical insecticides as probable human carcinogens (Group
2A)16. However, epidemiological studies relating pesticide exposure and human cancer have
been inconsistent, and the evidence probably cannot be considered to establish a causal
relationship for any single pesticide at the present time16. According to IARC and the US
Environment Protection Agency (EPA) the weight of evidence suggests that although
occupational exposure to other insecticides is probably associated with human cancer, the
relationship is not considered causal because of the lack of high-quality evidence. The sites
where evidence supports an association with pesticides include: non-Hodgkin’s lymphoma,
leukaemia, multiple myeloma, soft-tissue sarcoma, prostate, pancreas and lung3 15 16 26 27 80 81.
Cancers less frequently associated with pesticide exposures include: breast, testis, Hodgkin’s
disease, liver, kidney, rectum, brain and neurological systems.
36 6.4.3.1
Non-Hodgkin’s Lymphoma
Non-Hodgkin’s lymphoma is among the most widely studied cancers in relation to pesticide
use. The last published Occupational Health Decennial Supplement did not show any excess
risk among farmers10. They also plotted the rates of phenoxy herbicide usage by Ministry of
Agriculture (now Defra) region against the mortality from Non-Hodgkin’s lymphoma, but could
not find a significant correlation thus concluding the data provided little support for the
hypothesised association 30.
Many studies have shown farmers to be at an increased risk of Non-Hodgkin’s lymphoma82.
However, the specific practices associated with the risk vary. In addition, pesticides have been
suggested as risk factors for Non-Hodgkin’s lymphoma based on findings from studies of
pesticide applicators, pesticide manufacturers, chemical production workers, and military
veterans who served in Vietnam83. 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 Non-Hodgkin’s lymphoma
risk with pesticide exposure83. 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 summary statistic was estimated.
Blair and Zahm3 reviewed the literature and reported that Non-Hodgkin’s lymphoma has been
linked with exposure to phenoxyacetic acid herbicides, OC and OP pesticides. In 18 of 29
studies, farmers were observed to show excesses of Non-Hodgkin’s lymphoma compared to the
general population, but no excess was greater than twofold84.
Population-based case-control studies have observed NHL risk with self-reported agricultural
exposures to specific pesticide groups23 85 86. A Canadian multi-centre population-based incident
case-control study found the risk of Non-Hodgkin’s lymphoma was increased with exposure to
phenoxy and benzoic acid (dicamba) herbicides, to carbamate and OP insecticides, to amide
fungicides, and to the fumigant carbon tetrachloride 87. However, the AHS has not observed
any excess Non-Hodgkin’s lymphoma risk in the cohort as a whole88 89, and a similar study of
licensed pesticide applicators in Florida also did not observe an increased Non-Hodgkin’s
lymphoma risk4.
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 AHS that evaluated specific pesticides found no increased Non­
Hodgkin’s lymphoma risk 90-95.
Various meta-analyses have examined the risk of Non-Hodgkin’s lymphoma among farmers
and shown associations to be weak. In an analysis of 14 studies of farmers no significant
association between farming and Non-Hodgkin’s lymphoma risk was reported (meta-RR=1.05,
95% CI=0.98-1.12)96, whereas in an analysis of six studies among farmers in the central United
States a weak but significant increase in risk was obtained (meta-RR=1.34, 95% CI=1.17­
1.55)97. The most comprehensive review, which looked at 36 studies published between 1982
and 1997, reported a significant positive association (meta-RR=1.10, 95% CI=1.03-1.19)98.
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 on a smaller number of studies
37 obtained similar summary estimates for eight case-control studies of farmers, although the
summary RR was only marginally significant (meta-RR=1.13, 95% CI=1.00-1.27). In contrast,
the association based on eight cohort studies was inverse (meta-RR=0.95, 95% CI=0.90-1.00)99.
A more recent meta-analysis of 13 case-control studies observed a meta-OR of 1.35 (95%
CI=1.17-1.55), but found significant heterogeneity and detected publication bias100. Meta­
regression showed that a long period of exposure (>10 years) was associated with an increase in
the odds for Non-Hodgkin’s lymphoma of 1.65 (95% CI=1.08-2.51). Boffetta & De Vocht101
obtained a pooled RR (from 50 studies of farmers) of 1.11 (95% CI=1.05-1.17). No association
was seen between crop farming and Non-Hodgkin’s lymphoma 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 Non-Hodgkin’s lymphoma 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%”.
Findings from studies of occupationally exposed pesticide production/manufacturing workers,
including studies among phenoxy or chlorophenol production and manufacturing workers102-104,
triazine manufacturing workers 105, and alachlor manufacturing workers 106 have generally been
mixed. Studies of pesticide applicators have generally shown no excess risk 107 108. In a
multinational study of workers enrolled in the IARC cohort, no significant excess of Non­
Hodgkin’s lymphoma mortality was observed among workers exposed to phenoxy herbicides or
chlorophenols (SMR=1.27, 95% CI=0.88-1.78), with no exposure-response relationship based
on duration of exposure109. However, a recently published systematic review and meta-analysis
of mortality in crop protection product manufacturing workers identified 26 studies that
investigated NHL risk110. The pooled estimate was 1.98 (95% CI=1.45-2.69), whereas in
studies of phenoxy-herbicide workers the estimate was 2.01 (95% CI=1.38-2.93).
6.4.3.2
Leukaemia
Investigations have shown some negative, but mainly positive associations between farming and
leukaemia111. Leukaemia types linked with farming include acute lymphoid112, chronic
lymphoid113 114, acute myeloid115 and chronic myeloid116, with pesticide exposure suggested as
the likely cause.
A number of meta-analyses have been undertaken. Keller-Byrne et al 117 investigated 19 studies
that examined the association between leukaemia and farming. A random-effects meta-analysis
yielded a relative risk of 1.09 (95% CI= 0.997-1.19). The meta-RR of 10 case-control studies
was 1.23 (95% CI=1.17-1.29). Another meta-analysis of 27 studies obtained a meta-RR of 1.10
(95% CI=1.02-1.18) for white male farmers99. There was a small difference in the meta-RR by
study type: in cohort studies it was 1.00 (95% CI=0.91-1.11); in PMR studies it was 1.17 (95%
CI=1.07-1.28); whilst in case-control studies it was 1.11 (95% CI=0.96-1.27).
In a comprehensive review, 14 of 16 studies showed an association between pesticide exposure
and leukaemia, all but one with statistical significance118. Exposure to specific pesticides,
including mancozeb and toxaphane119, have been associated with excess mortality from
leukaemia. Evidence from a few studies of workers exposed to DDT provide limited support for
an association with leukaemia113, and chronic lymphoid leukaemia120. Exposure to dichlorvos
and other pesticides like nicotine and pyrethrins gave, after a 20-year latency, significant
excesses of leukaemia 113.
38 Findings from studies of occupationally exposed pesticide production/manufacturing workers,
including studies among phenoxy or chlorophenol production and manufacturing workers102 104,
triazine manufacturing workers105 121, and alachlor manufacturing workers122 have generally
been mixed. Studies of pesticide applicators have generally shown no excess risk107 123.
A study by Jones et al 110 reviewed 30 studies of crop protection product manufacturing workers
from Europe, USA and China, and obtained a pooled estimate of 1.08 (95% CI=0.81-1.44). In a
sub-group of 20 cohorts of workers involved in the manufacture of phenoxy herbicides the
summary risk estimate was 1.02 (95% CI=0.71-1.46). In contrast to this, a recent meta-analysis
of 12 cohort studies published between 1984 and 2004 obtained a fixed effects meta-RR of 1.43
(95% CI=1.05-1.94) for pesticide manufacturing workers124. Also, a systematic review and
meta-analysis of 17 cohort and 16 case-control studies published between 1979 and 2005
examining the association between myeloid leukaemia and occupational pesticide exposure
estimated a meta-rate ratio for cohort studies of 1.21 (95% CI=0.99-1.48)125. The meta-RR was
6.32 (95% CI=1.90-21.01) for manufacturing workers and 2.14 (95% CI=1.39-3.31) for
pesticide applicators. Among case-control studies a meta-RR of 1.39 was obtained (95%
CI=1.03-1.88) for men, and 1.38 (95% CI=1.06-1.79) for farmers and agricultural workers.
6.4.3.3
Multiple Myeloma
The Occupational Health Decennial Supplement did not show an increased mortality from
myeloma among farmers but did show an increased risk of contracting myeloma among male
farmers (PRR=126, 95% CI=105-151)10.
Many epidemiological studies, both cohort and case-control, have investigated the relationship
between agricultural work and myeloma126 127. Studies that have reported a risk for myeloma
have generally reported estimates exceeding 1.0 overall and for specific subgroups, although
these were not always statistically significant96 128-136. However, interpretation of the results
from studies examining the link between farming and myeloma is limited by the broad exposure
classification of farming as an occupational group. Farmers also perform activities such as
machine repair, carpentry, welding, painting, equipment operating, pesticide and fertiliser
mixing and application, and livestock handling. These activities may involve contact with
multiple chemicals and microorganisms, including solvents, fuels and oils, lubricants, wood
preservatives, engine exhausts, dusts, zoonotic viruses and other microbes.
A number of meta-analyses have been carried out. In one that included 12 studies published
between 1977 and 1990 with farmers as an occupational group, RR estimates ranged from 0.4 to
2.5, with a summary RR of 1.12 (95% CI=1.04-1.21)96. In a second analysis of 32 studies
published between 1981 and 1996, a random-effects summary RR of 1.23 (95% CI=1.14-1.32)
was obtained137. In a third analysis of 22 studies (16 follow-up; 11 PMR; 7 case-control, and 1
other) published through 1994, a summary RR of 1.09 (95% CI=0.99-1.19) was recorded, and
the risk was greater than 1.0 irrespective of the study design99. No heterogeneity was observed.
The authors also re-analysed the information using 10 studies examined by Blair et al 96, and
obtained a summary RR of 1.10 (95% CI=1.01-1.21).
A recent study of 13 case-control studies that examined pesticide-related occupations observed a
non-significant increase in myeloma risk (OR=1.16, 95% CI=0.99-1.36)100. Although there was
no sign of heterogeneity there was an indication that publication bias existed. The authors
undertook a process to correct for this with the result of a decrease in the OR to 1.12 (95%
CI=0.96-1.30). Nevertheless, only two studies were included in their analysis. A meta-analysis
of 25 cohorts from Europe, USA, China and New Zealand of pesticide production workers
obtained a pooled estimate of 1.26 (95% CI=0.89-1.77)110. In a sub-group of 20 cohorts of
39 workers involved in the manufacture of phenoxy-herbicides the summary risk estimate was 1.24
(95% CI=0.82-1.86).
6.4.3.4
Soft Tissue Sarcoma
Soft tissue sarcoma is a rare heterogeneous group of tumours that show a broad range of
differentiation that may reflect aetiologic distinction138 139. However, it is difficult to study the
aetiology of soft tissue sarcoma because of their relatively low incidence and inherent
misclassification of histology139. Also, because of the rarity, any study usually groups all the
different histological subtypes into one, resulting in a loss of specificity and possibly masking
the behaviour of the different subtypes. Soft tissue sarcoma are made up of a heterogeneous mix
of cancer subtypes and it has been suggested that occupational risk factors are not uniform
across subtypes140. A number of factors have been implicated in the aetiology of soft tissue
sarcomas. Viruses have long been suspected as causal in their development, and the association
of Karposi’s and AIDS is supportive of this hypothesis. Tobacco use has been inconsistently
associated with soft tissue sarcoma, and diet has been little studied. The role of therapeutic
radiation in inducing soft tissue sarcomas is well established 139.
A number of studies have found an association between herbicide use and soft tissue sarcoma141­
, although, others have not 85 145 146. However, in most of these studies the assumed aetiologic
agent is dioxin. The problem with histological subtypes was highlighted by Hoppin and
colleagues140, who observed self-reported herbicide use was associated with malignant
fibrohistiocytic sarcoma (OR=2.9, 95% CI=1.1-7.3) but not with liposarcoma.
144
6.4.3.5
Prostate Cancer
In the previous Occupational Health Decennial Supplement, mortality from prostate cancer was
significantly increased (PMR=112, 95% CI=106-118) among farmers10.
Prostate cancer risk among farmers and other pesticide users has been examined in a large
number of studies in Europe and US, with relative risks generally less than two4 84 99 147 148. A
recent analysis of the AHS cohort observed an SIR of 1.14 (95% CI=1.05-1.24)149. The study
showed use of chlorinated pesticides over 50 years of age and methyl bromide use were
significantly associated with prostate cancer risk. Several other pesticides also showed a
significantly increased risk, especially among subjects with a family history of prostate cancer,
including carbofuran, coumaphos, fonofos, permethrin and phorate.
A previous literature review of prostate cancer and occupation found the evidence to be
inconclusive150. Various reports have, however, shown small excesses among exposed workers.
A meta-analysis of 24 studies, published between 1983 and 1994, estimated the relative risk to
be 1.12 (95% CI=1.01-1.24)148, whereas a meta-analysis of 30 studies of farmers obtained a
combined RR of 1.07 (95% CI=1.02-1.13)99. In another analysis of 22 studies published
between 1995 and 2001 an estimated RR of 1.13 (95% CI=1.04-1.22) was obtained151.
Significant heterogeneity was observed and the major sources were geographic location, study
design and the healthy worker effect. A stratified analysis revealed a significant increase in the
rate ratio of pesticide applicators (RR=1.64, 95% CI=1.13-2.38), whereas this was not the case
for farmers (RR=0.97, 95% CI=0.92-1.03). In a review of 18 studies of pesticide manufacturers
published between 1984 and 2004, the meta-RR estimate for all studies was 1.28 (95% CI=1.05­
1.58)152. In analyses stratified by specific chemical class, increases in prostate cancer risk were
seen in all groups, but statistical significance was only found for accidental or non-accidental
exposure to phenoxy herbicide contaminated with dioxins and furans. A more recent meta­
analysis of manufacturers obtained a pooled estimate of 1.03 (95% CI=0.80-1.33; 29 studies)
for all cohorts, and 1.16 (95% CI=0.85-1.57; 20 studies) for cohorts exposed to phenoxy
herbicides 110.
40 6.4.3.6
Pancreatic Cancer
The risk of pancreatic cancer and exposure to pesticides has been found to be elevated, but
rarely statistically significant, in a number of occupational studies of agricultural workers and
pesticide users including: farmers153, agricultural pesticide applicators123 154 155, and production
workers110. However, a meta-analysis of 28 studies of farmers obtained a summary RR of 0.94
(95% CI=0.86-1.02)99.
6.4.3.7
Lung Cancer
The Occupational Health Decennial Supplement noted a significantly decreased mortality from
lung cancer among male farmers (PMR=88, 95% CI=86-91)10. Lung cancer is causally
associated with exposure to arsenical compounds156, and an excess risk has been observed
among vineyard workers157, arsenical pesticide manufacturers158 159 and general pesticide
manufacturers110. Increased risk has also been observed amongst licensed pesticide applicators
in the US and rose with the number of years licensed160 161. Similar findings were also seen in
Germany162. Studies have observed excesses with exposure to OP and carbamate insecticides
and phenoxyacetic acid herbicides160, phenoxy herbicides and/or contaminants
(dioxins/furans)109, and evidence of exposure response for others163. However, in a review of
studies published in 1992-1997 (19 case-control & 21 cohort, not all investigating lung
cancer)108, only one case-control study160 reported an excess risk of lung cancer. Farmers have
not been seen to be at risk of lung cancer99, and neither have pesticide applicators studied in the
AHS89 or from Florida4. However, lung cancer risk was increased with exposure to some OC
insecticides164, diazinon90 and chlorpyrifos165. A recent systematic review and meta-analysis of
mortality in crop production product manufacturing workers, reported a pooled risk estimate of
1.22 (95% CI=1.05-1.41) in 32 studies, and of 1.28 (95% CI=1.08-1.52) in 20 studies of
phenoxy herbicide exposed cohorts 110.
6.4.3.8
Ovarian Cancer
Two Italian case-control studies have shown an excess risk among women exposed to
herbicides166 167. Previous analysis of the AHS cohort of pesticide applicators showed increased
mortality of ovarian cancer among female private applicators, but not among spouses of male
private applicators89. However, the study of Florida applicators did not provide any data4. The
Occupational Health Decennial Supplement reported a 23% increase in mortality (PMR=123,
95% CI=100-151)10. However, the meta-analysis of production workers by Jones et al 110 used
10 studies and did not observe any excess risk (meta-RR=0.93, 95% CI=0.52-1.68), and the
meta-analysis by Acquavella et al 99 did not provide any data.
6.4.3.9
Brain Cancer
In the Occupational Health Decennial Supplement no excess deaths from brain cancer were
observed among farmers10.
The aetiology of brain cancer is still poorly understood. Brain tumours have been associated
with several occupational and environmental exposures, including farming168-170 and
pesticides171. A review of studies published before 1995 concluded that existing data were
insufficient to demonstrate that exposure to pesticides is a clear risk factor for brain tumours172.
The authors suggested that it seemed more plausible that exposure to multiple agents and/or
other factors are most relevant with respect to brain tumour pathogenesis. A meta-analysis of 33
studies, published between 1981 and 1996, examining the association between brain cancer and
farming, yielded a summary RR of 1.30 (95% CI=1.09-1.56)173, which the authors suggested
was evidence for a weak association that may be at least partially caused by pesticides and also
microorganisms. In the AHS, there was no excess in brain cancer incidence or mortality89 174. A
41 second meta-analysis of 28 studies of farmers reported a summary RR of 1.06 (95% CI=1.02­
1.11)99, which was similar to that obtained in an earlier analysis96. A meta-analysis of 30 studies
of pesticide production workers reported a pooled estimate of 1.01 (95% CI=0.75-1.36)110,
however, the pooled risk for phenoxy-herbicide cohorts was 0.93 (95% CI=.0.64-1.36).
6.4.3.10
Breast Cancer
The Occupational Health Decennial Supplement reported breast cancer mortality was lower
than expected among female farmers, with a PMR of 85 (95% CI=74-98)10. However, it has
been suggested that some pesticides have an oestrogenic effect thus increasing the risk of breast
cancer. Studies that have analysed the association between pesticide exposure and breast cancer
have mostly supported an association175. In the AHS, private applicators were seen to have a
raised incidence, although this was not statistically significant174, and mortality was below that
expected89. Pesticide manufacturers were seen to be at a 14% greater risk of breast cancer
(meta-SMR=1.14, 95% CI=0.81-1.61)110.
6.4.3.11
Skin Cancer
Proportional cancer mortality analysis of the Decennial Supplement data (1979-90 and 1982-90)
observed no significant excess of melanoma among male farmers (PCMR=0.94, 95% CI=0.78­
1.13) or female farmers (PCMR=1.01, 95% CI=0.48-1.85)169. In contrast, there were excesses of
non-melanoma skin cancer (male farmers: 1.27, 95% CI=0.95-1.66; female farmers: 4.22, 95%
CI=1.70-8.70).
The main cause of melanoma is sun exposure. A number of occupations (airline flight crews,
polyvinyl chloride manufacture, employment in the oil industry) or occupational exposures
(ionising radiation, extremely low frequency electromagnetic fields, polychlorinated biphenyls)
have been linked with melanoma but most cohort studies in these areas have been unable to
adequately deal with potential confounding by sun exposure176. Case-control studies177 178 and
studies on the incidence and/or mortality caused by cutaneous melanoma amongst agricultural
workers and farmers or those otherwise exposed to pesticides (e.g. vets), found indication for an
increased risk147 179-182, although another showed a decrease154.
Similarly, the main cause of non-melanoma skin cancer is sun exposure, in particular ultraviolet
radiation183, and exposure to ionising radiation has been shown to increase risk. Exposure to
arsenic contaminated drinking water has be shown to increase the risk of non-melanoma skin
cancer184 185. However, in industries where arsenic exposure may occur, including the
manufacture of glass and nonferrous alloys, smelting and where wood preservatives are used,
the risk of non-melanoma skin cancer is rarely presented as in the majority of cases it is rarely
fatal. Studies of farmers have generally shown them to be at an increased risk84 99 186 187, and
others have reported an association with agricultural chemicals including paraquat188. However,
several studies have not included non-melanoma skin cancer in their reports 88 105. The use of
arsenic in sheep dip, and other pesticides, has long since disappeared in farming and the use of
these chemicals was also intermittent, but due to the long latency, cases may still be the result of
exposure. Agricultural workers are also exposed regularly to UV radiation that must be taken
into account in any interpretation of results.
6.4.4
Accidents, Injuries and Poisonings
Agriculture has higher rates of occupational accidents than most industries in the UK. The most
common fatal accidents in agriculture are those involving vehicles and machinery, falls from
height and electrocution189, and according to the HSE, the main causes of death continue to be f :
f
http:/www.hse.gov.uk/statistics/industry/hsagriculture.htm#fatal
42 •
•
•
•
•
•
•
•
Transport (being run over or vehicle overturns);
Falling from height (through fragile roofs, trees, etc.);
Struck by moving or falling objects (bales, trees, etc.);
Asphyxiation/drowning;
Trapped by something collapsing or overturning;
Contact with machinery;
Livestock related fatalities;
Contact with electricity.
According to reports submitted under the Reporting of Injuries, Disease and Dangerous
Occurrences Regulations (RIDDOR), the most frequent categories of fatal accident were those
involving vehicles and machinery and falls from height. In addition, electrical injuries account
for a relatively high proportion of deaths. Other less common accidents are asphyxiation and
injury by an animal22. The Occupational Health Decennial Supplement also confirms these
figures, with the highest risk being from pesticide poisoning (PMR=1455, 95% CI=396-3724),
injury by animals and plants (PMR=775, 95% CI 479-1186), injury by firearms (PMR=670,
95% CI=424-1006), and animal transport accidents (PMR=468, 95% CI=262-773)10. Farmers
have, for a long time, been under considerable financial pressures especially as most are running
their own businesses, and it has been widely agreed that because of this the suicide rates are
much higher among the group. Among self-employed farmers, the PMR was 193 (415 deaths),
whereas among employees it was 136 (498 deaths), and managers/foremen it was 134 (70
deaths). In addition to financial constraints other factors may include ready access to means of
successful suicide such as guns and poisons30.
The rate of occupational accidents in British agriculture is higher than in most other industries.
According to the HSE, the rate of fatal injury to workers in 2006/7 was 8.1 deaths per 100,000 g ,
the numbers fluctuating over the last decade with no overall trend. In 2006/7, the number of
reported major injuries to employees decreased by 6% to 437 from 465 in 2005/6 (a decrease in
rate of 11% to 191.1), slips and trips accounted for 20% (86) of major injuries. The next most
common cause of major injuries were being hit by a moving or falling object at 17% (76)
followed by falls from height 14% (63). The rate of reportable non-fatal injury was 2000 per
100,000 workers in 2005/6, double that of the average for all industries.
In farmers under 45 years, the second most common cause of death (after accidents) was
suicide. They are twice as likely to commit suicide as the average member of the public190.
Suicide among farmers is not just because they have easy access to the means, they are also
independent, and decisive. Although there is good information about suicide in farmers, the data
are poor on agricultural workers, geographical and sectoral variations, and about other physical,
psychological and behavioural effects, and requires further investigation190.
6.4.5
Retinal Degeneration
Retinal degeneration is the leading cause of visual impairment in older adults, but its aetiology
is not well known. Non-occupational risk factors include light eye colour, hypertension, history
of cardiovascular disease, diabetes, sun exposure, and low antioxidant levels, but studies have
produced inconsistent results. Genetic susceptibility may play a role because familial
aggregation has been demonstrated191. Little is known about its relationship to occupational or
environmental neurotoxic exposures, although the available evidence mainly concerns exposure
to pesticides, primarily OP insecticides. In the AHS, retinal degeneration was associated with
fungicide use (OR=1.8, 95% CI=1.3-2.6)192. Risk was seen to increase with cumulative day of
fungicide use and was greater when application methods involving greater personal exposure
g
http://www.hse.gov.uk/statistics/industry/agriculture.htm
43 were used. Retinal degeneration was also related to a lesser extent with use of OC or carbamate
insecticides.
However, because retinal degeneration is very rarely fatal, it has not been possible to study this
disease in the current analysis, and a more general survey is required.
44 6.5
REFERENCES CITED IN THE APPENDICES
1. Holmes EM. The Pesticide Users' Health Study: Survey of Pesticide Usage: HSE, 2011.
2. Robinson S, Lader D. Smoking and drinking among adults, 2007. General Household Survey
2007. Newport: Office for National Statistics, 2007:62.
3. Blair A, Zahm SH. Agricultural exposures and cancer. Environmental Health Perspectives
1995;103(suppl 8):205-208.
4. Fleming LE, Bean JA, Rudolph M, Hamilton K. Mortality in a cohort of licenced pesticide
applicators in Florida. Occupational and Environmental Medicine 1999;56(1):14-21.
5. Waggoner JK, Kullman GJ, Henneberger PK, Umbach DM, Blair A, Alavanja MC, et al.
Mortality in the Agricultural Health Study, 1993-2007. Am J Epidemiol;173(1):71-83.
6. Centers for Disease Control and Prevention. Cigarette smoking among adults - United States,
1995. Morbidity and Mortality Weekly Report 1997;46(51):1217-1220.
7. Frost G. The Pesticide Users Health Study: an analysis of cancer incidence (1987-2004).
Bootle: Health & Safety Executive, 2011 (under review).
8. McGlynn KA, Quraishi SM, Graubard BI, Weber JP, Rubertone MV, Erickson RL. Persistent
organochlorine pesticides and risk of testicular germ cell tumors. J Natl Cancer Inst
2008;100(9):663-71.
9. Hardell L, van Bavel B, Lindstrom G, Carlberg M, Dreifaldt AC, Wijkstrom H, et al.
Increased concentrations of polychlorinated biphenyls, hexachlorobenzene, and
chlordanes in mothers of men with testicular cancer. Environ Health Perspect
2003;111(7):930-4.
10. Drever F. Occupational Health Decennial Supplement: The Registrar General's Decennial
Supplement for England and Wales. London: HMSO, 1995.
11. Coggan D, Harris EC, Brown TB, Rice S, Palmer KT. Occupational mortality in England
and Wales, 1991-2000. Newport: Office for National Statistics, 2009:52.
12. Garfitt SJ, Jones K, Mason HJ, Cocker J. Oral and dermal exposure to propetamphos: a
human volunteer study. Toxicol Lett 2002;134(1-3):115-8.
13. Garfitt SJ, Jones K, Mason HJ, Cocker J. Exposure to the organophosphate diazinon: data
from a human volunteer study with oral and dermal doses. Toxicol Lett 2002;134(1­
3):105-13.
14. Griffin P, Mason H, Heywood K, Cocker J. Oral and dermal absorption of chlorpyrifos: a
human volunteer study. Occup Environ Med 1999;56(1):10-3.
15. Doe JE, Paddle GM. The Evaluation of Carcinogenic Risk to Humans - Occupational
Exposures in the Spraying and Application of Insecticides. Regulatory Toxicology and
Pharmacology 1994;19(3):297-308.
16. IARC. Occupational exposure in insecticide application and some pesticides, volume 53.
IARC Monograph on Evaluating the Carcinogenic Risks to Humans. Lyon:
International Agency for Research on Cancer, 1991:1-587.
45 17. Blair A, Zahm SH. Herbicides and cancer: A review and discussion of methodologic issues.
Recent Results in Cancer Research 1990;120:132-145.
18. Blair A, Zahm SH. Methodologic issues in exposure assessment for case-control studies of
cancer and herbicides. American Journal of Industrial Medicine 1990;18(3):285-293.
19. Blondell JM. Problems encountered in the design of epidemiologic studies of cancer in
pesticide users. La Medicina del Lavoro 1990;81(6):524-529.
20. Cordes DH, Rea DF. Farming: a hazardous occupation. Occupational Medicine - State of
the Art Reviews 1991;6(3):327-334.
21. CSA. Cancer risk of pesticides in agricultural workers. Council on Scientific Affairs.
Journal of the American Medical Association 1988;260(7):959-966.
22. HSE. Fatal injuries in farming, forestry horticulture and associated industries 2007/2008.
2008.
23. Cantor KP, Blair A, Everett GD, Gibson R, Burmeister LF, Brown LM, et al. Pesticides and
other agricultural risk factors for non-Hodgkin's Lymphoma among men in Iowa and
Minnesota. Cancer Research 1992;52(9):2447-2455.
24. WHO. Public health impact of pesticides used in agriculture. Geneva: World Health
Organization, 1990.
25. Zheng TZ, Blair A, Zhang YW, Weisenburger DD, Zahm SH. Occupation and risk of non­
Hodgkin's lymphoma and chronic lymphocytic leukemia. Journal of Occupational and
Environmental Medicine 2002;44(5):469-474.
26. Moses M, Johnson ES, Anger WK, Burse VW, Horstman SW, Jackson RJ, et al.
Environmental equity and pesticide exposure. Toxicology and Industrial Health
1993;9(5):913-959.
27. Maroni M, Fait A. Health effects in a man from long-term exposure to pesticides. A review
of the 1975-1991 literature. Toxicology 1993;78(1-3):1-180.
28. Schenker MB, Christiani D, Cormier Y, Dimich-Ward H, Doekes G, Dosman J, et al.
Respiratory health hazards in agriculture. American Journal of Respiratory and Critical
Care Medicine 1998;158(5):S1-S76.
29. Fink JN, Ortega HG, Reynolds HY, Cormier YF, Fan LL, Franks TJ, et al. Needs and
opportunities for research in hypersensitivity pneumonitis. American Journal of
Respiratory and Critical Care Medicine 2005;171(7):792-798.
30. Coggon D, Inskip H, Winter P, Pannett B. Occupational mortality of men. In: Drever F,
editor. Occupational Health, Decennial Supplement. The Registrar General's Decennial
Supplement for England and Wales. London: HMSO, 1995:23-43.
31. Alavanja MC, Sandler DP, McMaster SB, Zahm SH, McDonnell CJ, Lynch CF, et al. The
Agricultural Health Study. Environmental Health Perspectives 1996;104(4):362-369.
32. Hoppin JA, Umbach DM, Kullman GJ, Henneberger PK, London SJ, Alavanja MCR, et al.
Pesticides and other agricultural factors associated with self-reported farmer's lung
among farm residents in the Agricultural Health Study. Occupational and
Environmental Medicine 2007;64(5):334-342.
46 33. LeVan TD, Koh WP, Lee HP, Koh D, Yu MC, London SJ. Vapor, dust, and smoke
exposure in relation to adult-onset asthma and chronic respiratory symptoms - The
Singapore Chinese Health Study. American Journal of Epidemiology
2006;163(12):1118-1128.
34. Valcin M, Henneberger PK, Kullman GJ, Umbach DM, London SJ, Alavanja MCR, et al.
Chronic bronchitis among nonsmoking farm women in the agricultural health study.
Journal of Occupational and Environmental Medicine 2007;49(5):574-583.
35. Hoppin JA, Valcin M, Henneberger PK, Kullman GJ, Umbach DM, London SJ, et al.
Pesticide use and chronic bronchitis among farmers in the Agricultural Health Study.
American Journal of Industrial Medicine 2007;50:969-979.
36. Von Essen S, Romberger DJ. The respiratory inflammatory response to the swine
confinement building environment: The adaptation to respiratory exposures in the
chronically exposed worker. Journal of Agricultural Safety and Health 2003;9(3):185­
196.
37. Monso M, Riu E, Radon K, Magarolas R, Danuser B, Iversen M, et al. Chronic obstructive
pulmonary disease in never-smoking animal farmers working inside confinement
buildings. American Journal of Industrial Medicine 2004;46(4):357-362.
38. Chen Y, Horne SL, McDuffie HH, Dosman JA. Combined effect of grain farming and
smoking on lung function and the prevalence of chronic bronchitis. International
Journal of Epidemiology 1991;20(2):416-423.
39. Melbostad E, Wijnand E, Magnus P. Chronic bronchitis in farmers. Scandinavian Journal of
Work, Environment & Health 1997;23(4):271-280.
40. Vohlonen I, Tupi K, Terho EO, Husman K. Prevalence and incidence of chronic bronchitis
and farmer’s lung with respect to the geographical location of the farm and the work of
farmers. European Journal of Respiratory Diseases Supplement 1987;152:37-46.
41. Lamprecht B, Schirnhofer L, Kaiser B, Studnicka M, Buist AS. Farming and the prevalence
of non-reversible airways obstruction – results from a population-based study.
American Journal of Industrial Medicine 2007;50(6):421-426.
42. Sprince NL, Lewis MQ, Whitten PS, Reynolds SJ, Zwerling C. Respiratory symptoms:
Associations with pesticides, silos, and animal confinement in the Iowa Farm Family
Health and Hazard Surveillance Project. American Journal of Industrial Medicine
2000;38(4):455-462.
43. Wilkins JR, Engelhardt HL, Rublaitus SM, Crawford JM, Fisher JL, Bean TL. Prevalence of
chronic respiratory symptoms among Ohio cash grain farmers. American Journal of
Industrial Medicine 1999;35(2):150-163.
44. Senthilselvan A, McDuffie HH, Dosman JA. Association of asthma with use of pesticides.
Results of a cross-sectional survey of farmers. American Review of Respiratory
Diseases 1992;146(4):884-887.
45. Hoppin JA, Umbach DM, London SJ, Alavanja MCR, Sandler DP. Chemical predictors of
wheeze among farmer pesticide applicators in the Agricultural Health Study. American
Journal of Respiratory and Critical Care Medicine 2002;165(5):683-689.
47 46. Hoppin JA, Umbach DM, London SJ, Lynch CF, Alavanja MCR, Sandler DP. Pesticides
associated with wheeze among commercial pesticide applicators in the agricultural
health study. American Journal of Epidemiology 2006;161(11):S85-S85.
47. Alavanja MCR, Hoppin JA, Kamel F. Health effects of chronic pesticide exposure: Cancer
and neurotoxicity. Annual Review of Public Health 2004;25:155-197.
48. Keifer M
C, Mahurin RK. Chronic neurologic effects of pesticide overexposure.
Occupational Medicine - State of the Art Reviews 1997;12(2):291-304.
49. Savage EP, Keefe TJ, Mounce LM, Heaton RK, Lewis JA, Burcar PJ. Chronic neurological
sequelae of acute organophosphate pesticide poisoning. Archives of Environmental
Health 1988;43(1):38-45.
50. Solomon C, Poole J, Palmer KT, Peveler R, Coggon D. Neuropsychiatric symptoms in past
users of sheep dip and other pesticides. Occupational and Environmental Medicine
2007;64(4):259-266.
51. Kamel F, Engel LS, Gladen BC, Hoppin JA, Alavanja MCR, Sandler DP. Neurologic
symptoms in licensed private pesticide applicators in the Agricultural Health Study.
Environmental Health Perspectives 2005;113(7):877-882.
52. Beseler C, Stallones L, Hoppin JA, Alavanja MCR, Blair A, Keefe T, et al. Depression and
pesticide exposures in female spouses of licensed pesticide applicators in the
Agricultural Health Study cohort. Journal of Occupational and Environmental
Medicine 2006;48(10):1005-1013.
53. Bazylewicz-Walczak B, Majczakowa W, Szymczak M. Behavioural effects of occupational
exposure to organophosphorous pesticides in females greenhouse planting workers.
Neurotoxicology 1999;20(5):819-826.
54. Stokes L, Stark A, Marshall E, Narang A. Neurotoxicity among pesticide applicators
exposed to organophosphates. Occupational and Environmental Medicine
1995;52(10):648-653.
55. Steenland K, Dick RB, Howell RJ, Chrislip DW, Hines CJ, Reid TM, et al. Neurologic
function among termiticide applicators exposed to chlorpyrifos. Environmental Health
Perspectives 2000;108:293-300.
56. Pilkington A, Buchanan D, Jamal GA, Gillham R, Hansen S, Kidd M, et al. An
epidemiological study of the relations between exposure to organophosphate pesticides
and indices of chronic peripheral neuropathy and neuropsychological abnormalities in
sheep farmers and dippers. Occupational and Environmental Medicine
2001;58(11):702-710.
57. Sanborn M, Kerr KJ, Sanin LH, Cole DC, Bassil KL, Vakil C. Non-cancer health effects of
pesticides: systematic review and implications for family doctors. Can Fam Physician
2007;53(10):1712-20.
58. Hoogenraad TU. Dithiocarbamates and Parkinson’s disease. Lancet 1988;1(8588):767.
59. Priyadarshi A, Khuder SA, Schaub EA, Priyadarshi SS. Environmental risk factors and
Parkinson's disease: a metaanalysis. Environmental Research Section A 2001;86(2):122­
7.
48 60. Kamel F, Tanner C, Umbach D, Hoppin J, Alavanja M, Blair A, et al. Pesticide exposure
and self-reported Parkinson's disease in the Agricultural Health Study. American
Journal of Epidemiology 2007;165(4):364-74.
61. Baldi I, Lebailly P, Mohammed-Brahim B, Letenneur L, Dartiigues J-F, Brochard P.
Neurodegenerative diseases and exposure to pesticides in the elderly. American Journal
of Epidemiology 2003;157(5):409-414.
62. Le Couteur DG, McLean AJ, Taylor MC, Woodham BL, Board PG. Pesticides and
Parkinson’s disease. Biomedicine & Pharmacotherapy 1999;53(3):122-130.
63. Ascherio A, Chen H, Weisskopf MG, O'Reilly E, McCullough ML, Calle EE, et al.
Pesticide exposure and risk for Parkinson's disease. Annals of Neurology
2006;60(2):197-203.
64. Tüchsen F, Jensen AA. Agricultural work and the risk of Parkinson’s disease in Denmark,
1981-1993. Scandinavian Journal of Work Environment & Health 2000;26(4):359-362.
65. Brown T, Rumsby P, Capleton A, Rushton L, Levy L. Pesticides and Parkinson's disease - is
there a link? Environmental Health Perspectives 2006;114(2):156-64.
66. Li AA, Mink PJ, McIntosh LJ, Teta MJ, Finley B. Evaluation of epidemiologic and animal
data associating pesticides with Parkinson's disease. Journal of Occupational and
Environmental Medicine 2005;47(10):1059-1087.
67. Dick S, Semple S, Dick F, Seaton A. Occupational titles as risk factors for Parkinson's
disease. Occupational Medicine 2007;57(1):50-56.
68. Dick FD, De Palma G, Ahmadi A, Scott NW, Prescott GJ, Bennett J, et al. Environmental
risk factors for Parkinson's disease and parkinsonism: the Geoparkinson study.
Occupational and Environmental Medicine 2007;64(10):666-672.
69. Hancock DB, Martin ER, Mayhew GM, Stajich JM, Jewett R, Stacy MA, et al. Pesticide
exposure and risk of Parkinson's disease: A family-based case-control study. BMC
Neurology 2008;8:6.
70. Chancellor AM, Slattery JM, Fraser H, Warlow CP. Risk factors for motor neuron disease: a
case-control study based on patients from the Scottish Motor Neuron Disease Register.
Journal of Neurology, Neurosurgery and Psychiatry 1993;56(11):1200-1206.
71. Gunnarsson LG, Bodin L, Soderfeldt B, Axelson O. A case-control study of motor neuron
disease: its relation to heritability, and occupational exposures, particularly to solvents.
British Journal of Industrial Medicine 1992;49(11):791-798.
72. Granieri E, Carreras M, Tola R, Paolino E, Tralli G, Eleopra R, et al. Motor neuron disease
in the province of Ferrara, Italy, in 1964-1982. Neurology 1988;38(10):1604-1608.
73. McGuire V, Longstreth WT, Nelson LM, Koepsell TD, Checkoway H, Morgan MS, et al.
Occupational exposures and amyotrophic lateral sclerosis - A population-based casecontrol study. American Journal of Epidemiology 1997;145(12):1076-1088.
74. Savettieri G, Salemi G, Arcara A, Cassata M, Castiglione MG, Fierro B. A case-control
study of amyotrophic lateral sclerosis. Neuroepidemiology 1991;10(5-6):242-245.
49 75. Cummings JL, Cole G. Alzheimer disease. Journal of the American Medical Association
2002;287(18):2335-2338.
76. McDowell I, Hill G, Lindsay J, Helliwell B, Costa L. The Canadian study of health and
aging: risk factors for Alzheimer’s disease in Canada. Neurology 1994;44:2073-2080.
77. Gauthier E, Fortier I, Courchesne F, Pepin P, Mortimer J, Gauvreau D. Environmental
pesticide exposure as a risk factor for Alzheimer's disease: A case-control study.
Environmental Research Section A 2001;86(1):37-45.
78. Van Duijn CM. Epidemiology of the dementias: Recent developments and new approaches.
Journal of Neurology, Neusurgery,a dn Psychiatry 1996;60(5):478-488.
79. Santibanez M, Bolumar F, Garcia AM. Occupational risk factors in Alzheimer's disease: a
review assessing the quality of published epidemiological studies. Occupational and
Environmental Medicine 2007;64:723-732.
80. Alavanja MCR, Bonner MR. Pesticides and human cancers. Cancer Investigation
2005;23(8):700-711.
81. Munro IC, Carlo GL, Orr JC, Sund KG, Wilson RM, Kennepohl E, et al. A comprehensive,
integrated review and evaluation of the scientific evidence relating to the safety of the
herbicide 2,4-D. International Journal of Toxicology 1992;11(5):559-664.
82. Descatha A, Jenabian A, Conso F, Ameille J. Occupational exposures and haematological
malignancies: overview on human recent data. Cancer Causes & Control
2005;16(8):939-953.
83. Alexander D, Mink PJ, Adami HO, Chang ET, Cole P, Mandel JS, et al. The non-Hodgkin
lymphomas: a review of the epidemiologic literature. International Journal of Cancer
2007;120(suppl 23):1-39.
84. Blair A, Zahm SH. Cancer among farmers. Occupation Medicine - State of the Art Reviews
1991;6:335-354.
85. Woods JS, Polissar L, Severson RK, Heuser LS, Kulander BG. Soft tissue sarcoma and non­
Hodgkin’s lymphoma in relation to phenoxyherbicide and chlorinated phenol exposure
in western Washington. Journal of the National Cancer Institute 1987;78(5):899-910.
86. Zahm SH, Weisenburger DD, Babbit PA, Saal RC, Vaught JB, Cantor KP, et al. A casecontrol study of non-Hodgkin’s lymphoma and the herbicide 2,4-dichlorophenoxyacetic
acid (2,4-D) in eastern Nebraska. Epidemiology 1990;1(5):349-356.
87. McDuffie HH, Pahwa P, McLaughlin JR, Spinelli JJ, Fincham S, Dosman JA, et al. Non­
Hodgkin’s lymphoma and specific pesticide exposures in men: cross-Canada study of
pesticides and health. Cancer Epidemiology, Biomarkers & Prevention
2001;10(11):1155-1163.
88. Alavanja MCR, Sandler DP, Lynch CF, Knott C, Lubin JH, Tarone R, et al. Cancer
incidence in the Agricultural Health Study. Scandinavian Journal of Work Environment
& Health 2005;31(suppl 1):39-45.
50 89. Blair A, Sandler DP, Tarone R, Lubin J, Thomas K, Hoppin JA, et al. Mortality among
participants in the Agricultural Health Study. Annals of Epidemiology 2005;15(4):279­
285.
90. Beane Freeman LE, Bonner MR, Blair A, Hoppin JA, Sandler DP, Lubin JH, et al. Cancer
incidence among male pesticide applicators in the Agricultural Health Study cohort
exposed to diazinon. American Journal of Epidemiology 2005;162(11):1070-1079.
91. Bonner MR, Coble J, Blair A, Beane Freeman LE, Hoppin JA, Sandler DP, et al. Malathion
exposure and the incidence of cancer in the Agricultural Health Study. American
Journal of Epidemiology 2007;166(9):1023-1034.
92. Bonner MR, Lee WJ, Sandler DA, Hoppin JA, Dosemeci M, Alavanja MCR. Occupational
exposure to carbofuran and the incidence of cancer in the Agricultural Health Study.
Environmental Health Perspectives 2005;113(3):285-289.
93. Rusiecki JA, De Roos A, Lee WJ, Dosemeci M, Lubin JH, Hoppin JA, et al. Cancer
incidence among pesticide applicators exposed to atrazine in the Agricultural Health
Study. Journal of the National Cancer Institute 2004;96(18):1375-1382.
94. Rusiecki JA, Hou LF, Lee WJ, Blair A, Dosemeci M, Lubin JH, et al. Cancer incidence
among pesticide applicators exposed to metolachlor in the Agricultural Health Study.
International Journal of Cancer 2006;118(12):3118-3123.
95. Rusiecki JA, Patel R, Koutros S, Beane-Freeman L, Landgren O, Bonner MR, et al. Cancer
incidence among pesticide applicators exposed to permethrin in the Agricultural Health
Study. Environmental Health Perspectives 2009;117(4):581-586.
96. Blair A, Zahm SH, Pearce N, Heineman EF, Fraumeni Jr JF. Clues to cancer etiology from
studies of farmers. Scandinavian Journal of Work Environment & Health
1992;18(4):209-215.
97. Keller-Byrne J, Khuder SA, Schaub EA, McAfee O. A meta-analysis of non-Hodgkin
lymphoma among farmers in the Central United States. American Journal of Industrial
Medicine 1997;31:442-4.
98. Khuder SA, Schaub EA, Keller-Byrne J. Meta-analyses of non-Hodgkin lymphoma and
farming. Scandinavian Journal of Work Environment & Health 1998;24(4):255-261.
99. Acquavella J, Olsen G, Cole P, Ireland B, Kaneene J, Schuman S, et al. Cancer among
farmers: A meta-analysis. Annals of Epidemiology 1998;8(1):64-74.
100. Merhi M, Raynal H, Cahuzac E, Vinson F, Cravedi JP, Gamet-Payrastre L. Occupational
exposure to pesticides and risk of hematopoietic cancers: meta-analysis of case-control
studies. Cancer Causes & Control 2007;18:1209-1226.
101. Boffetta P, de Vocht F. Occupation and the risk of non-Hodgkin lymphoma. C
ancer
Epidemiology, Biomarkers & Prevention 2007;16(3):369-372.
102. Burns CJ, Beard KK, Cartmill JB. Mortality in chemical workers potentially exposed to
2,4-dichlorophenoxyacetic acid (2,4-D) 1945-94: an update. Occupational and
Environmental Medicine 2001;58(1):24-30.
51 103. Coggon D, Pannett B, Winter PD. Mortality and incidence of cancer at four factories
making phenoxy herbicides. British Journal of Industrial Medicine 1991;48(3):173­
178.
104. Hooiveld M, Heederik DJJ, Kogevinas M, Boffetta P, Needham LL, Patterson DG, et al.
Second follow-up of a Dutch cohort occupationally exposed to phenoxy herbicides,
chlorophenols, and contaminants. American Journal of Epidemiology 1998;147(9):891­
901.
105. MacLennan PA, Delzell E, Sathiakumar N, Myers SL. Mortality among triazine herbicide
manufacturing workers. Journal of Toxicology and Environmental Health-Part aCurrent Issues 2003;66(6):501-517.
106. Leet T, Acquavella J, Lynch C, Anne M, Weiss N, Vaugn T, et al. Cancer incidence among
alachlor manufacturing workers. American Journal of Industrial Medicine
1996;30(3):300-306.
107. Swaen GMH, van Amelsvoort L, Slangen JJM, Mohren DCL. Cancer mortality in a cohort
of licensed herbicide applicators. International Archives of Occupational and
Environmental Health 2004;77(4):293-295.
108. Dich J, Zahm SH, Hanberg A, Adami HO. Pesticides and cancer. C
ancer Causes &
Control 1997;8(3):420-443.
109. Kogevinas M, Becher H, Benn T, Bertazzi PA, Boffetta P, BuenodeMesquita HB, et al.
Cancer mortality in workers exposed to phenoxy herbicides, chlorophenols, and dioxins
- An expanded and updated international cohort study. American Journal of
Epidemiology 1997;145(12):1061-1075.
110. Jones DR, Sutton AJ, Abrams KR, Fenty J, Warren F, Rushton L. Systematic review and
meta-analysis of mortality in crop protection product manufacturing workers.
Occupational and Environmental Medicine 2009;66(1):7-15.
111. Linet MS, Devesa S, Morgan GJ. The Leukaemias. In: Schottenfeld D, Fraumeni Jr JF,
editors. Cancer Epidemiology and Prevention. Oxford: Oxford University Press,
2006:841-871.
112. Donham KJ, Berg JW, Sawin RS. Epidemiologic relationships of the bovine population
and human leukemia in Iowa. Am J Epidemiol 1980;112(1):80-92.
113. Brown LM, Blair A, Gibson R, Everett GD, Cantor KP, Schuman LM, et al. Pesticide
exposures and other agricultural risk factors for leukemia among men in Iowa and
Minnesota. Cancer Research 1990;50(20):6585-6591.
114. Blair A, White DW. Leukemia cell types and agricultural practices in Nebraska. Archives
of Environmental Health 1985;40(4):211-214.
115. Pearce NE, Sheppard RA, Howard JK, Fraser J, Lilley BM. Leukemia among New
Zealand agricultural workers. A cancer registry-based study. American Journal of
Epidemiology 1986;124(3):402-409.
116. Blair A, White DW. Death certificate study of leukemia among farmers from Wisconsin.
Journal of the National Cancer Institute 1981;66(6):1027-1030.
52 117. Keller-Byrne JE, Khuder SA, Schaub EA. Meta-analysis of leukemia and farming.
Environmental Research 1995;71(1):1-10.
118. Sanborn M, Cole D, Kerr K, Vakil C, Sanin LH, Bassil K. Pesticides literature review: The
Ontario College of Family Physicians, 2004.
119. Mills PK, Yang R, Riordan D. Lymphohematopoietic cancers in the United Farm Workers
of America (UFW), 1988-2001. Cancer Causes & Control 2005;16(7):823-830.
120. Flodin U, Fredrisksson M, Persson B, Axelson O. Chronic lymphatic leukaemia and engine
exhausts, fresh wood, and DDT: a case-referent study. British Journal of Industrial
Medicine 1988;45(1):33-38.
121. Sathiakumar N, Delzell E. A review of epidemiologic studies of triazine herbicides and
cancer. Critical Reviews in Toxicology 1997;27(6):599-612.
122. Acquavella JF, Delzell E, Cheng H, Lynch CF, Johnson G. Mortality and cancer incidence
among alachlor manufacturing workers 1968-99. Occupational and Environmental
Medicine 2004;61(8):680-685.
123. Figa-Talamanca I, Mearelli I, Valente P, Bascherini S. Cancer mortality in a cohort of rural
licensed pesticide users in the province of Rome. International Journal of Epidemiology
1993;22(4):579-583.
124. Van Maele-Fabry G, Duhayon S, Mertens C, Lison D. Risk of leukaemia among pesticide
manufacturing workers: A review and meta-analysis of cohort studies. Environmental
Research 2008;106(1):121-137.
125. Van Maele-Fabry G, Duhayon S, Lison D. A systematic review of myeloid leukemias and
occupational pesticide exposure. Cancer Causes & Control 2007;18(5):457-478.
126. Alexander D, Mink PJ, Adami HO, Cole P, Mandel JS, Oken MM, et al. Multiple
myeloma: A review of the epidemiologic literature. International Journal of Cancer
2007;120(suppl12):40-61.
127. De Roos AJ, Baris D, Weiss NS, Herrinton LJ. Multiple myeloma. In: Schottenfeld D,
Fraumeni Jr JF, editors. Cancer Epidemiology and Prevention. Oxford: Oxford
University Press, 2006:919-945.
128. Cuzick J, De Stavola B. Multiple myeloma – a case-control study. British Journal of
Cancer 1988;57(5):516-520.
129. La Vecchia C, Negri E, D'Avanzo B, Franceschi S. Occupation and lymphoid neoplasms.
British Journal of Cancer 1989;60(3):385-388.
130. Reif J, Pearce N, Fraser J. Cancer risks in New Zealand farmers. International Journal of
Epidemiology 1989;18(4):768-774.
131. Heineman EF, Olsen JH, Pottern LM, Gomez M, Raffin E, Blair A. Occupational risk
factors for multiple myeloma among Danish men. Cancer Causes & Control
1992;3(6):555-568.
132. Franceschi S, Barbone F, Bidoli E, Guarneri S, Serraino D, Talamini R, et al. Cancer risk
in farmers: results from a multi-site case-control study in north-eastern Italy.
International Journal of Cancer 1993;53(5):740-745.
53 133. Keller JE, Howe HL. Case-control studies of cancer in Illinois farmers using data from the
Illinois State Cancer Registry and the U.S. Census of Agriculture. European Journal of
Cancer 1994;30A(4):469-473.
134. Lee E, Burnett CA, Lalich N, Cameron LL, Sestito JP. Proportionate mortality of crop and
livestock farmers in the United States, 1984-1993. American Journal of Industrial
Medicine 2002;42(5):410-420.
135. Baris D, Silverman DT, Brown LM, Swanson GM, Hayes RB, Schwartz AG, et al.
Occupation, pesticide exposure and risk of multiple myeloma. Scandinavian Journal of
Work Environment & Health 2004;30(3):215-222.
136. Cantor KP, Blair A. Farming and mortality from multiple myeloma: a case-control study
with the use of death certificates. Journal of the National Cancer Institute
1984;72(2):251-255.
137. Khuder SA, Mutgi AB. Meta-analyses of multiple myeloma and farming. American
Journal of Industrial Medicine 1997;32(5):510-516.
138. Toro JR, Travis LB, Wu HJ, Zhu K, Fletcher CDM, Devesa S. Incidence patterns of soft
tissue sarcomas, regardless of primary site, in the Surveillance, Epidemiology and End
Results program, 1978-2001: an analysis of 26,758 cases. International Journal of
Cancer 2006;119(12):2922-2930.
139. Berwick M. Soft tissue sarcoma. In: Schottenfeld D, Fraumeni Jr JF, editors. C
ancer
Epidemiology and Prevention. Oxford: Oxford University Press, 2006:959-974.
140. Hoppin JA, Tolbert PE, Flanders WD, Zhang RH, Daniels DS, Ragsdale BD, et al.
Occupational risk factors for sarcoma subtypes. Epidemiology 1999;10(3):300-306.
141. Hardell L, Sandstrom A. Case-control study: soft-tissue sarcomas and exposure to
phenoxyacetic acids or chlorophenols. British Journal of Cancer 1979;39:711-717.
142. Eriksson M, Hardell L, Berg NO, Moller T, Axelson O. Soft-tissue sarcomas and exposure
to chemical substances: a case-referent study. British Journal of Industrial Medicine
1981;38(1):27-33.
143. Hardell L, Eriksson M. The association between soft-tissue sarcoma and exposure to
phenoxyacetic acids: a case-referent study. Cancer 1988;62(3):652-656.
144. Wingren G, Fredrikson M, Brage H, Nordenskjold B, Axelson O. Soft tissue sarcoma and
occupational exposures. Cancer 1990;66:806-811.
145. Hoar SK, Blair A, Holmes FF, Boysen CD, Robel RJ, Hoover R, et al. Agricultural
herbicide use and risk of lymphoma and soft tissue sarcoma. Journal of the American
Medical Association 1986;256(9):1141-1147.
146. Smith AH, Pearce NE, Fisher DO, Giles HJ, Teague CA, Howard JK. Soft tissue sarcoma
and exposure to phenoxyherbicides and chlorophenols in New Zealand. Journal of the
National Cancer Institute 1984;73(5):1111-1117.
147. Cerhan JR, Cantor KP, Williamson K, Lynch CF, Torner JC, Burmeister LF. Cancer
mortality among Iowa farmers: Recent results, time trends, and lifestyle factors (United
States). Cancer Causes & Control 1998;9(3):311-319.
54 148. Keller-Byrne JE, Khuder SA, Schaub EA. Meta-analyses of prostate cancer and farming.
American Journal of Industrial Medicine 1997;31(5):580-586.
149. Alavanja MCR, Samanic C, Dosemeci M, Lubin J, Tarone R, Lynch CF, et al. Use of
agricultural pesticides and prostate cancer risk in the Agricultural Health Study cohort.
American Journal of Epidemiology 2003;157(9):800-814.
150. Muir KR, Harriss C. Prostate cancer and occupation: A literature review. Contract
Research Report 191/1998: HSE Books, 1998.
151. Van Maele-Fabry G, Willems JL. Occupation related pesticide exposure and cancer of the
prostate: a meta-analysis. Occupational and Environmental Medicine 2003;60(9):634­
642.
152. Van Maele-Fabry G, Libotte V, Willems J, Lison D. Review and meta-analysis of risk
estimates for prostate cancer in pesticide manufacturing workers. Cancer Causes &
Control 2006;17(4):353-373.
153. Falk RT, Pickle LW, Fontham ET, Correa P, Morse A, Chen V, et al. Occupation and
pancreatic cancer in Louisiana. American Journal of Industrial Medicine
1990;18(5):565-576.
154. Forastiere F, Quercia A, Miceli M, Settimi L, Terenzoni B, Rapiti E, et al. Cancer among
farmers in central Italy. Scandinavian Journal of Work Environment & Health
1993;19(6):382-389.
155. Zhong JP, Rafnsson V. Cancer incidence among Icelandic pesticide users. A
merican
Journal of Respiratory and Critical Care Medicine 1996;25:1117-1124.
156. IARC. Overall evaluations of carcinogenicity: An updating of IARC Monographs volumes
1 to 42. Lyon: International Agency for Research on Cancer, 1987.
157. Lüchtrath H. The consequences of chronic arsenic poisoning among Moselle wine growers.
Pathoanatomical investigations of post-mortem examinations between 1960 and 1977.
Journal of Cancer Research and Clinical Oncology 1983;105(2):173-182.
158. Mabuchi K, Lilienfeld AM, Snell LM. Lung cancer among pesticide workers exposed to
inorganic arsenicals. Archives of Environmental Health 1979;34(5):312-320.
159. Mabuchi K, Lilienfeld AM, Snell LM. Cancer and occupational exposure to arsenic: a
study of pesticide workers. Preventative Medicine 1980;9(1):51-77.
160. Pesatori AC, Sontag JM, Lubin JH, Consonni D, Blair A. Cohort mortality and nested
case-control study of lung cancer among structural pest control workers in Florida
(United States). Cancer Causes & Control 1994;5(4):310-318.
161. Blair A, Grauman DJ, Lubin JH, Fraumeni Jr JF. Lung cancer and other causes of death
among licensed pesticide applicators. Journal of the National Cancer Institute
1983;71(1):31-37.
162. Barthel E. Increased risk of lung cancer in pesticide-exposed male agricultural workers.
Journal of Toxicology and Environmental Health 1981;8(5-6):1027-1040.
55 163. Alavanja MCR, Dosemeci M, Samanic C, Lubin J, Lynch CF, Knott C, et al. Pesticides
and lung cancer risk in the Agricultural Health Study cohort. American Journal of
Epidemiology 2004;160(9):876-885.
164. Purdue MP, Hoppin JA, Blair A, Dosemeci M, Alavanja MCR. Occupational exposure to
organochlorine insecticides and cancer incidence in the Agricultural Health Study.
International Journal of Cancer 2007;120(3):642-649.
165. Lee WJ, Blair A, Hoppin JA, Lubin JH, Rusiecki JA, Sandler DP, et al. Cancer incidence
among pesticide applicators exposed to chlorpyrifos in the agricultural health study.
Journal of the National Cancer Institute 2004;96(23):1781-1789.
166. Donna A, Betta P, Robutti F, Crosignani P, Berrino F, Bellingeri D. Ovarian mesothelial
tumors and herbicides: a case-control study. Carcinogenesis 1984;5(7):941-942.
167. Donna A, Cosignani P, Robutti F, Betta PG, Bocca R, Mariana N, et al. Triazine herbicides
and ovarian epithelial neoplasms. Scandinavian Journal of Work Environment & Health
1989;15(1):47-53.
168. Firth HM, Cooke KR, Herbison GP. Male cancer incidence by occupation: New Zealand,
1972-1984. International Journal of Epidemiology 1996;15(1):14-21.
169. Inskip H, Coggon D, Winter P, Pannett B. Mortality of farmers and farmers' wives in
England and Wales 1979-80, 1982-90. Occupational and Environmental Medicine
1996;53(11):730-735.
170. De Roos AJ, Stewart PA, Linet MS, Heineman EF, Dosemeci M, Wilcosky T, et al.
Occupation and the risk of adult glioma in the United States. Cancer Causes & Control
2003;14(2):139-150.
171. Musicco M, Sant M, Molinari S, Filippini G, Gatta G, Berrino F. A case-control study of
brain gliomas and occupational exposure to chemical carcinogens: the risk to farmers.
American Journal of Epidemiology 1988;128(4):778-785.
172. Bohnen NI, Kurland LT. Brain tumor and exposure to pesticides in humans: a review of
the epidemiologic data. Journal of the Neurological Sciences 1995;132(2):110-121.
173. Khuder SA, Mutgi AB, Schaub EA. Meta-analyses of brain cancer and farming. American
Journal of Industrial Medicine 1998;34(3):252-260.
174. Alavanja MC, Sandler DP, Lynch CF, Knott C, Lubin JH, Tarone R, et al. Cancer
incidence in the agricultural health study. Scandinavian Journal of Work &
Environmental Health 2005;31(suppl 1):39-45; discussion 5-7.
175. Bassil KL, Vakil C, Sanborn M, Cole DC, Kaur JS, Kerr KJ. Cancer health effects of
pesticides - Systematic review. Canadian Family Physician 2007;53(10):1705-1711.
176. Gruber SB, Armstrong BK. Cutaneous and ocular melanoma. In: Schottenfeld D, Fraumeni
Jr JF, editors. Cancer Epidemiology and Prevention. Oxford: Oxford University Press,
2006:1196-1229.
177. Green A, McCredie M, MacKie RM, Giles G, Young P, Morton C, et al. A c ase-control
study of melanomas of the soles and palms (Australia and Scotland). Cancer Causes &
Control 1999;10(1):21-25.
56 178. Settimi L, Comba P, Carrieri P, Boffetta P, Magnani C, Terracini B, et al. Cancer risk
among female agricultural workers: A multi-center case-control study. American
Journal of Industrial Medicine 1999;36(1):135-141.
179. Corrao G, Calleri M, Carle F, Russo R, Bosia S, Piccioni P. Cancer risk in a cohort of
licensed pesticide users. Scandinavian Journal of Work Environment & Health
1989;15(3):203-209.
180. Pukkala E, Notkola V. Cancer incidence among Finnish farmers, 1979-93. Cancer Causes
& Control 1997;8(1):25-33.
181. Travier N, Gridley G, Blair A, Dosemeci M, Boffetta P. Cancer incidence among male
Swedish veterinarians and other workers of the veterinary industry: a record-linkage
study. Cancer Causes & Control 2003;14(6):587-593.
182. Wesseling C, Ahlbom A, Antich D, Rodriguez AC, Castro R. Cancer in banana plantation
workers in Costa Rica. International Journal of Epidemiology 1996;25(6):1125-1131.
183. Karagas MR, Weinstock MA, Nelson HH. Keratinocyte carcinomas (basal and squamous
cell carcinomas of the skin). In: Schottenfeld D, Fraumeni Jr JF, editors. Cancer
Epidemiology and Prevention. Oxford: Oxford University Press, 2006:1230-1250.
184. Cantor KP. Drinking water and cancer. Cancer Causes & Control 1997;8:292-308.
185. IARC. Volume 84: Some drinking-water disinfectants and contaminants, including arsenic
related nitrosamines. IARC Monographs on the Evaluation of Carcinogenic Risks to
Humans. Lyon: International Agency for Research on Cancer, 2004.
186. Hogan DJ, To T, Gran L, Wong D, Lane PR. Risk factors for basal cell carcinoma.
International Journal of Dermatology 1989;28(9):591-594.
187. Hogan DJ, Lane PR, Gran L, Wong D. Risk factors for squamous cell carcinoma of the
skin in Saskatchewan, Canada. Journal of Dermatological Science 1990;1(2):97-101.
188. Jee SH, Kuo HW, Su WP, Chang CH, Sun CC, Wang JD. Photodamage and skin cancer
among paraquat workers. International Journal of Dermatology 1995;34(7):466-469.
189. Solomon C. Accidental injuries in agriculture in the UK. Occupational Medicine-Oxford
2002;52(8):461-466.
190. HSC. Report of a conference on occupational health in agriculture. London,: Health &
Safety Commission, 2001.
191. Scholl HPN, Fleckenstein M, Issa PC, Keilhauer C, Holz FG, Weber BHF. An update on
the genetics of age-related macular degeneration. Molecular Vision 2007;13:196-205.
192. Kamel F, Boyes WK, Gladen BC, Rowland AS, Alavanja MC, Blair A, et al. Retinal
degeneration in licensed pesticide applicators. American Journal of Industrial Medicine
2000;37(6):618-628.
57 58
59
Published by the Health and Safety Executive
03/13
Health and Safety
Executive
The Pesticide Users’ Health Study
An analysis of mortality (1987-2005) The Pesticide Users Health Study (PUHS) was
established so as to monitor the health of men
and women who are certified to apply pesticides
on a commercial basis under the 1986 Control
of Pesticides Regulations. An analysis of deaths
occurring between 1987 and 2005 among members
of the PUHS is presented in this report.
There were 1,628 deaths among 59,085 male and
3,875 female pesticide users during the followup period. Compared with the population of
Great Britain, the pesticide users had lower than
expected mortality from all causes, and in particular
from all cancers combined, cancers of the digestive
organs, cancers of the respiratory system, and
non-malignant diseases of the nervous system and
sense organs, and of the circulatory, respiratory,
and digestive systems. There was some evidence of
excess deaths from multiple myeloma in men and
women, and possibly also from testicular cancer.
Deaths from all external causes (accidents and
injuries) combined were lower than expected when
compared with the general population. However in
men, deaths from ‘injury by machinery’ were higher
than expected.
Continuing recruitment into the PUHS will enable
HSE to monitor the health of these pesticide users
as regulations and exposures change over time.
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.
RR958
www.hse.gov.uk