the pesticide users health study 2013 uk = low cancer rates

7/28/2019 The Pesticide Users Health Study 2013 UK = Low Cancer Rates

http://slidepdf.com/reader/full/the-pesticide-users-health-study-2013-uk-low-cancer-rates 1/68

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

RR958Research Report



Health and Safety

Executive



Terry Brown

Anne-Helen Harding

Gillian Frost

Harpur HillBuxton

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 respiratorysystem, 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 necessarilyreflect HSE policy.

HSE Books



© Crown copyright 2013

First published 2013

You may reuse this information (not including logos) free of

charge in any format or medium, under the terms of the

Open Government Licence. To view the licence visit

www.nationalarchives.gov.uk/doc/open-government-licence/,

write to the Information Policy Team, The National Archives, Kew,

London TW9 4DU, or email [email protected].

Some images and illustrations may not be owned by the

Crown so cannot be reproduced without permission of the

copyright owner. Enquiries should be sent to

[email protected].

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 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, nonmalignant 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.

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, itwas not possible to investigate whether these were linked with particular jobs, working

practices or pesticides.

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”.

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 pesticidesthrough their work is maintained.

iii



iv



EXECUTIVE SUMMARY

Objectives

The overall objective of this report was to describe mortality among participants of the PesticideUsers Health Study (PUHS).

Study participants were men and women who have been certified to apply pesticides on acommercial basis in Great Britain under the 1986 Control of Pesticides Regulations and whoagreed to take part in HSE’s research into their health. These men and women thereforerepresent a cohort of individuals who were likely to have been occupationally exposed to

pesticides.

Main findings

There were 1,628 deaths among 59,085 male and 3,875 female pesticide users during thefollow-up period, 1987-2005.

The mean age at first certification was 32 years (sd 11), with women on average nearly 4years younger than men at entry.

At the end of the study, the mean length of time since first certification was 13 years, with arange of less than one year to 18.7 years.

The mean age at first certification for those who died was 46 years for men and 36 years for women.

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 0.520.63)

o Non-malignant diseases of the respiratory system (SMR 0.39, 95% CI 0.310.49)

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



The SMRs for some causes of death were higher than expected, though relatively smallnumbers of deaths, wide confidence intervals and statistical non-significance for someSMRs, mean that these need to be interpreted with caution. Only those causes of death withraised 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) washigher 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).

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 significantlydifferent from the general population. Among men “injury by machinery” was statisticallysignificantly higher than expected (SMR 4.21, 95% CI 2.11-8.42).

Recommendations

The PUHS is an important resource, but the information currently held on the PUHSdatabase is limited. As it stands, it is not possible to investigate whether occupationalexposures 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 affectmortality, such as diet and lifestyle, would permit an analysis to take these into account

before investigating the associations with occupational exposures. It is recommended thatthis type of information be collected on the pesticide users in future research.

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 respiratorysymptoms and diseases, which are not always fatal. A general health survey of the pesticideusers is recommended, in order to determine the occurrence and the associated risk factors of these health conditions among the pesticide users.

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 pesticidesthrough 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 PAGE1 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. Pesticideshave been used for centuries: the first recorded use was by the Sumerians who were usingsulphur as an insecticide in 2500 BC1. The Chinese were using pyrethrum as an insecticide by1200 BC and sulphur as a fumigant by 1000 BC. Arsenic-containing compounds were used asinsecticides in the 16

thcentury and as a weed killer in the late 19

thcentury. 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 19 th centurywith, 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-Diphenyl-

Trichloroethane) 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 fungicideson 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 focusof epidemiological investigations. This increased concern for human toxicity, potentialaddresses 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 determinationof 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 alsoto 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 symptomsinclude headache, aching limbs, runny nose, giddiness, muscle weakness, and fevers/chills, plusothers3. In a study of 4,108 individuals who had at some time used pesticides occupationally, therisk 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, troublegetting 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 allcategories of pesticide (sheep dip, other insecticides, herbicides, fungicides and wood

preservatives). However, in many cases the symptoms may have arisen through psychologicalrather than toxic mechanisms.

Existing reporting systems in the UK that collect data on incident illness associated withexposure 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 recentstudy to estimate the prevalence and incidence of pesticide-related illness presenting to GPs inGreat 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 pesticide-related symptoms were 2.7% and 1.6% respectively. Although small, these estimates translate torelatively large numbers of consultations annually.

Chronic health effects, such as cancer, and adverse reproductive outcomes, have beeninvestigated 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 humanhealth13. 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 fromvarious accidental injuries, from several occupationally related respiratory disorders, fromhernias (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 seenfor pesticide poisoning. A more detailed review of the published literature on epidemiologicalstudies, which investigate the association between occupational exposure to pesticides and morbidity or mortality, is given in Appendix 6.4.

Table 1 Mortali ty from selected causes in farmers: men aged 20-74, England and Wales, 1979-80 and 1982-90 (Source Drever et al, 1995)17 and 1991-

2000 (Source Coggan et al, 2009)18

Cause of death 1979-80 and 1982-90 1991-2000

Deaths PMR 95% CI Deaths PMR 95% CI

Farmers’ lung disease (495.0) 56 10.1 8.23-14.2 31 14.6 9.89-20.7Other and unspecified allergic 7 7.87 3.17-16.2 3 2.89 0.60-8.44

pneumonitis (495.1, 495.3-495.9)Inguinal hernia (550) 41 1.91 1.37-2.59 29 2.37 1.59-3.41Other hernia (551-553) 41 1.49 1.07-2.02 24 1.57 1.01-2.34Infections of skin, joints and 36 1.81 1.27-2.51

bone (680-686, 711, 730)Off-road motor vehicle accidents 38 2.55 1.80-3.50 23 2.80 1.78-4.20(E820-E825)Animal transport accidents 15 4.68 2.62-7.73 9 9.64 4.41-18.3(E827-E828)

Pesticide poisoning (E863) 4 14.6 3.96-37.24 4 13.5 3.68-34.6Poisoning by other gases (E869) 7 4.17 1.68-8.59 3 2.38 0.49-6.97Slipping and tripping (E885) 17 1.93 1.12-3.09 4 1.54 0.42-3.93Injury by animals and plants 21 7.75 4.79-11.9 16 10.3 5.90-16.8(E905-E906)Injury by falling object (E916) 35 1.56 1.09-2.17 17 2.20 1.28-3.52Injury by machinery (E919) 147 4.57 3.86-5.38 50 4.17 3.09-5.50Injury by firearms (E922) 23 6.70 4.24-10.2 12 8.13 4.20-14.2Injury by electric current (E925) 29 2.13 1.43-3.07 18 2.38 1.41-3.76Suicide (E950-E959) 1215 1.56 1.47-1.65 908 1.37 1.29-1.47

3



The most obvious groups in which to study the chronic effects of pesticides in humans are thoseoccupational groups or workers who apply pesticides in high doses as part of their dailyactivities. 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:

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 duringthese 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.

Floriculturists and greenhouse workers: Those involved in the production of flowers and ornamental plants that are commonly sprayed with pesticides in greenhouses. It has beensuggested that these groups of workers may potentially have an increased risk of cytogeneticdamage due to working in small confined areas, humid conditions and a potential continuousexposure through re-entry activities such as cutting and potting, all militating against theregular use of PPE 21 22. Additionally, compared to other classes of workers, floriculturistsmay be relatively highly exposed to pesticides during loading, mixing and application aswell 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 pesticidesthroughout the year, resulting in potentially continuous exposure.

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 arealso involved in the mixing and loading of the pesticides. Exposure to pesticides may belower than in other groups due to the seasonal application of pesticides and the working

environment, i.e. outdoors.

Forestry workers: Those involved in the spraying of trees and shrubs. In general,compared with other occupational groups, forestry workers use fewer active ingredients.

Production workers: Those involved in the manufacture of pesticides. The production of pesticides is undertaken throughout the year, as opposed to pesticide applications, which ingeneral, occur seasonally. Workers are therefore potentially exposed to pesticidescontinuously, 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, whohave taken certificates of competence in the use of agricultural pesticides and who thereforerepresent 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 thehealth of commercial pesticide users in Great Britain, and represent the first step in theinvestigation of the health effects of occupational exposure to pesticides.

Men and women in the PUHS had significantly lower mortality rates than the GB populationduring 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 thedigestive organs, cancers of the respiratory system, non-malignant diseases of the nervoussystem 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, mayexplain 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 mortalityanalysis for these excess deaths was relatively weak, but is strengthened when combined withthe reported statistically significant excess in the number of incident cases of multiple myelomaand 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 accuratemeasurement 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 pesticideDDT and testicular germ cell tumours has been reported in the literature24. Further research intothe observed excess of these cancers in the PUHS cohort may be warranted, particularly withrespect to occupational exposures and other potential explanatory factors.

Reported statistics for farmers, the occupational group most closely representative of the PUHScohort 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 Campaignand 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 astatistically 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 thePUHS, the only statistically significant increased risk of mortality from external causes wasobserved for “injury by machinery” in men. This self-selected cohort of workers trained in thesafe 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 maynot be exposed to the same range of risks as farmers.

5



3.1

3 METHODOLOGYTHE COHORT

Since 1986, anyone applying pesticides on a commercial basis in the UK must first gain acertificate of competence in their safe use. The City & Guilds Land Based Services (formerlythe 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 VeterinaryMedicines 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 acertificate 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 effectsof pesticide usage conducted by HSE. In 1998, the HSE’s Epidemiology and Medical StatisticsUnit (EMSU) conducted a feasibility study into using the City & Guilds Land Based Servicesdatabase, both for following up cancer incidence and mortality, and for collecting other data onhealth and on pesticide usage. They concluded that the database was “an excellent tool …. butcould be enhanced”, and committed HSE to a programme of work to achieve this. In February2005, the database was transferred from EMSU to the Health and Safety Laboratory (HSL) inBuxton, 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 achievethis, 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 partin HSE’s programme of medical research into the health of pesticide users. The first test dateincluded in the database was May 1987. Data for those who agreed to take part before March2003 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 individualor 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 registrationswas 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 wereeventually 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 pesticideusers or pesticide manufacturing workers was compiled and used as the outcomes for thisanalysis. The underlying cause of death reported on death certificates was used to define a casein 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 deathcertificate, coded according to ICD-9 or ICD-10. Person-years at risk and standardised mortalityratios (SMR) were calculated using Stata SE v11.125 26

. The start date for the cohort was the datemembers sat for their first certificate of competence, irrespective of what type it was. Personyears at risk accrued until the end of the study period (31 December 2005), or when anindividual 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, whichcompare mortality in the cohort with national mortality, were calculated. The SMRs werecalculated by sex-specific 5-year age and calendar periods. National mortality rates wereobtained from the Office for National Statistics (England and Wales) and from the GeneralRegister Officer for Scotland. If an SMR is greater than 1, there is an excess of deaths amongthe pesticide users, and if the SMR is less than 1, there are fewer deaths than expected amongthe 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 individualwas first certified was treated as a time dependent variable in the analysis. SMRs were alsostratified in relation to the region where an individual lived. The regions were based onGovernment 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, WestMidlands

• Eastern: Norfolk, Suffolk, Essex, Hertfordshire, Bedfordshire, Cambridgeshire

• South East: Sussex, Surrey, Hampshire, Berkshire, Buckinghamshire, Isle of Wight,Kent, Oxfordshire, Londonc

• 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



4.1

4 RESULTS THE COHORT

Altogether 63,493 of the 65,910 men and women on the PUHS database, were successfullytraced. Of these, a further 533 individuals were excluded from the analysis: 182 did not have adate 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 aFoundation 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 acommercial 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 differentregions of the country.

Table 2 Regional distr ibution of the cohort

Men Women Total Region

Number (%) Number (%) Number (%)

East 8,343 (13.2) 600 (1.0) 8,943 (14.2)South East 11,872 (18.9) 1,156 (1.8) 13,028 (20.7)South West 7,457 (11.8) 543 (0.9) 8,000 (12.7)Midlands 10,431 (16.6) 584 (0.9) 11,015 (17.5)

North 12,350 (19.6) 615 (1.0) 12,965 (20.6)Scotland 6,071 (9.6) 252 (0.4) 6,323 (10.0)Wales 2,561 (4.1) 125 (0.2) 2,686 (4.3)

Total 59,085 (100) 3,875 (100) 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 womenwere born in the 1960s and 1970s.

Table 3 Cohort distr ibution by year of birth

Year of Birth Men

Number %

Women

Number %

Total

Number %

Before 1930 618 (1.0) 4 (0.01) 622 (1.0)

1930-1939 3,532 (5.6) 48 (0.1) 3,580 (5.7)

1940-1949 8,344 (13.2) 290 (0.5) 8,634 (13.7)

1950-1959 13,264 (21.1) 598 (1.0) 13,862 (22.0)

1960-1969 21,347 (33.9) 1,698 (2.7) 23,045 (36.6)

1970-1979 10,607 (16.8) 1,157 (1.8) 11,764 (18.7)

1980- 1,373 (2.2) 80 (0.1) 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 distr ibution by year of and age at the firs t test date

Men Women Total Year of first test Number (%) Mean Number (%) Mean Number (%) Mean

age age age

1987-1990 29,742 (50.3) 33.4 1,366 (35.3) 28.3 31,108 (49.4) 33.1

1991-1994 16,465 (27.9) 31.1 1,419 (36.6) 27.9 17,884 (28.4) 30.8

1996-2000 10,149 (17.2) 32.1 835 (21.5) 29.6 10,984 (17.4) 31.9

2001-2003 2,729 (4.6) 33.7 255 (6.6) 32.5 2,984 (4.7) 33.6

Age at first test

<25 18,696 (29.7) 1,689 (2.7) 20,385 (32.4)

25-29 10,428 (16.6) 876 (1.4) 11,304 (18.0)

30-34 8,520 (13.5) 479 (0.8) 8,999 (14.3)

35-39 6,692 (10.6) 314 (0.5) 7,006 (11.1)

40-44 5,498 (8.7) 261 (0.4) 5,759 (9.2)

45-49 3,975 (6.3) 141 (0.2) 4,116 (6.5)

50- 5,276 (8.4) 115 (0.2) 5,391 (8.6)

Mean age at 32.5 (11.0) 28.7 (8.8) 32.3 (11.0)

first test

As outlined in section 3.2, job information was lacking on the PUHS database, although a totalof 8,270 were known to be definitely self-employed and 16,934 not. Table 5 gives informationof 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 handheld operator module. The table also shows the length of time a certificate had been held by theend of the study (31 December 2005). The overall mean was 13.2 years (sd 4.2), with a rangefrom less than one month to 18.7 years.

10



Table 5 Cohort distr ibution by City & Guilds Land Based Services modulestaken and number of years certif ied

Men Women Total Modules taken

Number (%) Number (%) Number (%)

Foundation Module (FM) 6,293 (10.7) 676 (17.5) 6,969 (11.1) FM + Ground Crop Sprayer, 16,640 (28.2) 207 (5.3) 16,847 (26.8) unspec.FM + Hand Held Applicators, 28,693 (48.6) 2,709 (69.9) 31,402 (49.9) unspec.All Three 2,711 (4.6) 73 (1.9) 2,784 (4.4) All others 4,748 (8.0) 210 (5.4) 4,958 (7.9) Total 59,085 (100) 3,875 (100) 62,960 (100) Years since first certification $

<=5 5,814 (9.8) 533 (13.8) 6,347 (10.1)

5-9 10,605 (18.0) 889 (22.9) 11,494 (18.3)

10-14 19,681 (33.3) 1,546 (39.9) 21,227 (33.7)

15+ 22,985 (38.9) 907 (23.4) 23,892 (38.0)

Total 59,085 (100) 3,875 (100) 62,960 (100)

Mean number of years certified 13.3 (sd 4.2) 12.2 (sd 4.2) 13.2 (sd 4.2)

$ Equivalent to length of follow-up

11



4.2 RESULTS FROM THE MORTALITY ANALYSIS

Altogether there were 829,709 person years at risk and 1,628 deaths among the cohort (1,591men, 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 wasapproximately 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 lessthan the cohort average. The mean age at death was 54.6 years (sd 13.7), with that for men (54.8years) 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 certi fied bysex for individuals who died during follow-up

Men Women Total

Age at first test 45.5 (12.5) 36.1 (11.0) 45.3 (12.6) p<0.001$

Number of years certified 9.4 (4.6) 8.8 (4.4) 9.4 (4.6) p = 0.43$

Age at death 54.8 (13.6) 44.9 (13.0) 54.6 (13.7) 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-causemortality (SMR 0.58, 95% CI 0.55-0.61) and mortality from all cancers (SMR 0.72, 95% CI0.66-0.78) were significantly less than expected when compared with the GB population. Inaddition, 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 nostatististically 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 over-interpreted in the absence of other supporting evidence, particularly where the number of deathsis 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 astatistically 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 wassome 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 significantexcess of multiple myelomas (observed deaths = 2, SMR 10.8, 95% CI 2.70-43.2) and nonsignificant 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 thesecancers means that the results should be treated with caution, and the role of chance cannot beexcluded.

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 bymachinery” (observed deaths = 8; SMR 4.21, 95% CI 2.11-8.42) and in women there was anexcess of deaths caused by slips, trips or stumbling (observed deaths = 1; SMR 123, 95% CI17.3-873). The latter, based on one death, should be interpreted with caution. External causesaccounted 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 agegroup, external causes accounted for 4% of deaths from all causes. Overall, suicide and self-inflicted injuries dominated the external cause of death category (39%), although the proportionvaried 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 3539 years. Among those aged less than 25 years at death, 48% of deaths from external causeswere 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



14

Table 7 Mortali ty in the Pesticide Users Health Study, 1987-2005

Cause of DeathObs

Men

SMR (95% CI) Obs

Women

SMR (95% CI) SMR

All

(95% CI)

All causes 1,591 0.58 (0.55-0.60) 37 0.71 (0.52-0.98) 0.58 (0.55-0.61)

Malignant neoplasms 583 0.71 (0.66-0.77) 19 0.85 (0.54-1.34) 0.72 (0.66-0.78)Malignant neoplasms (excl. NMSC) 580 0.71 (0.66-0.77) 19 0.85 (0.54-1.34) 0.71 (0.66-0.77)

Lip, oral cavity & pharynx 4 0.18 (0.07-0.49) 0 0.18 (0.07-0.48)Digestive organs 192 0.78 (0.68-0.90) 2 0.58 (0.14-2.30) 0.78 (0.68-0.90)

Oesophagus 46 0.89 (0.66-1.18) 0 0.88 (0.66-1.18)Stomach 30 0.88 (0.61-1.26) 1 2.33 (0.33-16.5) 0.90 (0.63-1.28)Colon 38 0.72 (0.53-1.00) 0 0.71 (0.52-0.98)Rectum & anus 22 0.64 (0.42-0.97) 0 0.63 (0.41-0.95)Liver & gall bladder 8 0.42 (0.21-0.85) 0 0.42 (0.21-0.84)Pancreas 38 1.02 (0.74-1.40) 1 1.55 (0.22-11.0) 1.03 (0.75-1.40)

Respiratory system 126 0.55 (0.46-0.66) 1 0.34 (0.05-2.42) 0.55 (0.46-0.65)Larynx 3 0.34 (0.11-1.05) 0 0.34 (0.11-1.05)Trachea, bronchus & lung 118 0.55 (0.46-0.66) 1 0.35 (0.05-2.51) 0.55 (0.46-0.66)

Skin 15 0.79 (0.48-1.32) 0 0.77 (0.46-1.28)Malignant melanoma 12 0.72 (0.41-1.27) 0 0.70 (0.40-1.23)

Non-melanoma skin cancer 3 1.34 (0.43-4.15) 0 1.33 (0.43-4.11)Connective & soft tissue 3 0.93 (0.30-2.87) 1 8.77 (1.24-62.3) 1.19 (0.44-3.18)Breast 1 1.24 (0.17-8.82) 6 0.94 (0.42-2.08) 0.97 (0.46-2.03)Female genital system - 2 0.60 (0.15-2.40) 0.60 (0.15-2.40)

Ovarian & other uterine adnexa - 1 0.60 (0.08-4.22) 0.60 (0.08-4.22)Male genital system 40 0.86 (0.63-1.18) - 0.86 (0.63-1.18)

Prostate 33 0.80 (0.57-1.12) - 0.80 (0.57-1.12)Testis 7 1.95 (0.93-4.09) - 1.95 (0.93-4.09)

Urinary system 34 0.72 (0.51-1.00) 0 0.71 (0.51-1.00)Kidney 18 0.72 (0.45-1.15) 0 0.71 (0.45-1.13)Bladder 14 0.66 (0.39-1.11) 0 0.65 (0.38-1.10)

Eye, brain & central nervous system 34 0.82 (0.58-1.14) 1 0.98 (0.14-6.95) 0.82 (0.59-1.14)Eye 0 0Brain 20 0.78 (0.51-1.22) 0 0.77 (0.49-1.19)Central nervous system & meninges 1 1.89 (0.27-13.4) 0 1.84 (0.26-13.0)

Thyroid 1 0.72 (0.10-5.09) 0 0.69 (0.10-4.93)Lymphohaematopoietic 73 0.94 (0.75-1.18) 6 3.48 (1.56-7.74) 1.00 (0.80-1.24)

Hodgkin’s disease 4 0.82 (0.31-2.20) 0 0.80 (0.30-2.12) Non-Hodgkins lymphoma 26 0.77 (0.53-1.14) 2 3.03 (0.76-12.1) 0.81 (0.56-1.18)Multiple myeloma 15 1.28 (0.77-2.12) 2 10.8 (2.70-43.2) 1.42 (0.89-2.30)Leukaemia 26 0.96 (0.66-1.42) 2 2.83 (0.71-11.3) 1.01 (0.70-1.47)

Diseases of the: Nervous system & sense organs 28 0.40 (0.28-0.59) 0 0.39 (0.27-0.57)Parkinson’s disease 0 0Motor neuron disease 9 0.81 (0.42-1.56) 0 0.80 (0.41-1.53)Alzheimer’s disease 3 0.95 (0.31-2.94) 0 0.93 (0.30-2.89)

Circulatory system 530 0.58 (0.53-0.63) 4 0.43 (0.16-1.14) 0.58 (0.52-0.63)Ischaemic heart disease 335 0.54 (0.48-0.60) 1 0.27 (0.04-1.90) 0.54 (0.48-0.60)Cerebrovascular disease 89 0.66 (0.54-0.82) 2 0.71 (0.18-2.85) 0.66 (0.54-0.82)

Respiratory system 75 0.39 (0.32-0.49) 1 0.32 (0.04-2.26) 0.39 (0.31-0.49)COPD 15 0.30 (0.18-0.49) 0 0.29 (0.18-0.49)Asthma 4 0.41 (0.15-1.08) 0 0.39 (0.15-1.04)Farmer’s Lung 0 0

Digestive System 39 0.23 (0.17-0.32) 2 0.56 (0.14-2.25) 0.24 (0.18-0.32)

Number of deaths observed; Standardised mortality ratio; 95% Confidence intervals



Table 8 External causes of mortality among men and women in the Pesticide Users Health Study database, 1987-2005

Cause of DeathObs

Men

SMR (95% CI) Obs

Women

SMR (95% CI) SMR

All

(95% CI)

External causes 264 0.69 (0.62-0.78) 6 0.96 (0.43-2.14) 0.70 (0.62-0.79)Transport accidents 67 0.74 (0.58-0.94) 1 0.74 (0.10-5.29) 0.74 (0.58-0.93)Accidental falls 17 0.74 (0.46-1.20) 1 3.14 (0.44-22.3) 0.78 (0.49-1.23)

Slips, trips or stumbling 1 1.66 (0.23-11.8) 1 123 (17.3-873) 3.28 (0.82-13.1)Injury by falling object 3 1.78 (0.57-5.51) 0 1.77 (0.57-5.49)Injury by machinery 8 4.21 (2.11-8.42) 0 4.21 (2.11-8.42)Injury by firearm 1 5.03 (0.71-35.8) 0 5.03 (0.71-35.7)Accidents by submersion, suffocation & 6 0.45 (0.20-1.00) 0 0.44 (0.20-0.98)

foreign bodiesInjury by electric current 2 1.33 (0.33-5.31) 0 1.32 (0.33-5.29)Accidental poisoning 6 0.34 (0.15-0.75) 0 0.33 (0.15-0.74)Suicide & self-inflicted injury 101 0.80 (0.66-0.97) 4 2.23 (0.84-5.93) 0.82 (0.68-0.99)Injury, undetermined intent 25 0.43 (0.29-0.64) 0 0.43 (0.29-0.63)


4.3 DISCUSSION OF RESULTS

This analysis of mortality among 62,960 pesticide users in the GB Pesticide Users Health Studyduring the period 1987-2005 demonstrated that all cause mortality, and mortality from allcancers combined, respiratory disease, circulatory disease, and non-malignant diseases of thedigestive system of the pesticide users were statistically significantly lower than expected whencompared 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 healthyworker 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 PUHSundertaken 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 thatsmoking is less prevalent in the cohort than in the GB population, where approximately 24% of the population were current smokers in 2005

2. Consequently, the lower mortality rates among

the pesticide users will be at least partially attributable to differences in smoking rates in thecohort 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, especiallywith respect to cardiovascular disease and diseases associated with heavy tobacco and alcoholuse

3 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% CI0.51-0.56) 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, thesimilarities 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 owndo 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 statisticallynon-significant excess of deaths from testicular cancer and from multiple myeloma suggest thatthere 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 tissuecancers and lymphohaematopoietic cancers, and within the group of lymphohaematopoieticcancers for multiple myeloma. The small number of deaths for each of these causes means thatthese 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 lymphohaematopoieticcancers 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 smallnumbers 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 germcell tumours (TGCT). A case-control study of 739 cases with TGCT and 915 matched controlsreported 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 4 th quartilevs 1st quartile)8. An earlier case-control study of 61 cases with TGCT and 58 matched controlsreported a statistically non-significantly raised odds ratio of 1.7 for blood p,p' -DDE levelshigher 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 notconclusive. Meta-analyses have been undertaken, with the meta-relative risk estimates rangingfrom 1.09-1.26, though many of these were not statistically significantly elevated (see Appendix6.4). 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 moreconsistent 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 anumber of external causes of death, including intentional suicide and self-inflicted injury, weresignificantly 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 externalcauses were either below one or not statistically significantly elevated. The only external causeof 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 HealthStudy reported a similarly raised SMR for “injury by machine” in men (SMR 4.15, 95% CI3.18-5.31), but for most external causes the SMRs were less than one5.

There are significant drawbacks with the information stored on the database. Only four causesof death (underlying cause plus up to three other contributory causes) are recorded for eachdeath. Thus, for any death where more causes are recorded, in either section one or two of thedeath certificate, the other causes are not recorded. This is especially important for causes thatare not directly related to the underlying cause of death. This may include asthma, farmer’slung 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 noregistration for it.

In the current analysis it was only possible to examine mortality within the cohort. A significantnumber of diseases, however, are not life threatening but may be associated with pesticideexposure and agricultural work where most exposure occurs. These include respiratory diseases,including a decrease in lung function; non-fatal accidents/injuries; incidence of acute symptomsfollowing exposure; musculoskeletal problems; and health in general. These health outcomescould 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 aresecondary data, not collected for research purposes. Although the employer’s address wasavailable, 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 onexposure to specific pesticides or on working practices, which would help in the interpretationof individual findings. The cohort includes a substantial number of men and women whoapplied 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. Consequentlyit 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. Thisinformation, in addition to information on other factors potentially associated with disease suchas diet, smoking, and alcohol intake, could be gathered as part of a general health survey of thePUHS cohort.

The cohort offers the opportunity to investigate actual exposures to pesticides. Laboratory

volunteer studies have been undertaken of exposure to various pesticides

12-14

, however, thesehave 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 thelaboratory 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 theseworkers. Consequently, members of the cohort are distributed geographically across the wholeof 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 likelyto 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 membersshould be encouraged to take part in further studies to help investigate the association betweenthe health of pesticide users in Great Britain and the pesticides they use. This is the onlynational study of men and women chronically exposed to pesticides as part of their work inGreat Britain. The findings from PUHS will make a substantial contribution to the scientificevidence 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 pesticideapplicators 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 Health1993;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 HealthOrganization, 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 Physician2007;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 nonHodgkin'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 DecennialSupplement 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):430436.

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 monitoringof a group of Italian floriculturists: no evidence of DNA damage related to pesticideexposure. 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 NatlCancer 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



6.1

6 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 C720-C729 MN of central nervous system and meninges

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 Non-Hodgkin's lymphoma

20



21

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



6.2 CITY & GUILDS LAND BASED SERVICES CERTIFICATES OFCOMPETENCE

The following table shows the City & Guilds Land Based Services certificates of competence,which are recorded in the PUHS database.

Certificate Module Grouping

PA01 Foundation FoundationPA02 Ground crop sprayer – unspecified Ground crop sprayer PA02A Ground crop sprayer – boom type hydraulic nozzle Ground crop sprayer PA02B Ground crop sprayer – boom type rotary atomiser Ground crop sprayer PA02C Ground crop sprayer – boom type twin fluid nozzle Ground crop sprayer PA02D Ground crop sprayer – electro-statically charged Ground crop sprayer PA02E Ground crop sprayer – boom type fitted with downward air Ground crop sprayer

assistancePA02F Wick applicator – boom or frame type Ground crop sprayer

PA02AR Vehicle mounted kerb sprayer – hydraulic nozzle type Ground crop sprayer PA02BR Vehicle mounted kerb sprayer – rotary atomiser type Ground crop sprayer PA02ST Spray trains – hydraulic nozzle and rotary atomiser Ground crop sprayer PA03 Air sprayer – unspecified Other PA03A Broadcast air blast sprayer – mounted or trailed Other PA03B Variable geometry boom air assisted sprayer – mounted or Other

trailed PA03C Variable geometry boom sprayer without air assistance Other PA04 Granule applicatory – mounted or trailed Other PA05A Boat mounted applicator – hydraulic nozzle boom Other PA05B Hand held applicators – application to water using viscous gel Other

applicatorsPA05C Boat mounted applicator – viscous gel applicator Other

PA06 Hand-held applicators – unspecified Hand-held operator PA06A Hand held applicators – hydraulic nozzle and/or rotary atomiser Hand-held operator

typesPA06AW Hand held applicators – application to water using hydraulic Hand-held operator

nozzle or rotary atomPA06B Hand held applicators – application to water using viscous gel Hand-held operator

applicatorsPA06C Handheld applications – granule applicator Hand-held operator PA06CW Hand held applicators – application to water using granule Hand-held operator

applicatorsPA06D Hand held applicators – requiring minimal calibration Hand-held operator PA07 Aerial application Other PA07A Aerial applicator – pilot Other

PA07B Aerial applicator – fieldsman/ground marker Other PA08 Mixer/loader Other PA09 Fogging, misting and smokes Other PA10 Dipping, bulbs, corms, plant material or containers Other PA11 Seed treating equipment – unspecified Other PA11A Seed treating equipment – mobile equipment Other PA11B Seed treating equipment – static equipment Other PA12 Application of pesticides to material as a continuous or batch Other

processPA13 Sub surface liquid applicator Other

22



6.3 STRATIFIED TABLES OF RESULTS

Standardised mortality ratios, stratified by a number of possible explanatory variables, werecalculated. 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 thestratified 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 mortalityin 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 thetype(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 explanatoryvariables. The majority of SMRs were not statistically significantly different to 1.00; someindicated that the number of deaths was statistically significantly smaller than expected whencompared with the GB population. In these stratified tables, only one statistically significantlyraised SMR was observed: SMR 1.51 (95% CI 1.09-2.11) for lymphohaematopoietic cancersamong 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 statisticallysignificant SMR should be interpreted with caution.

23



24

Table 9 Mortali ty amongst men by region, 1987-2005

Cause of Death

All causes

Malignant neoplasms (all)Digestive organsRespiratory systemSkinMale genital systemUrinary system

Eye, brain & CNSLymphohaematopoietic

Scotland North Midlands

Obs SMR Obs SMR Obs SMR

208 0.56 (0.49-0.64) 318 0.63 (0.56-0.70) 226 0.50 (0.44-0.5

84 0.83 (0.67-1.02) 120 0.81 (0.68-0.97) 73 0.54 (0.43-0.621 0.69 (0.45-1.06) 48 1.08 (0.82-1.44) 22 0.55 (0.36-0.826 0.79 (0.54-1.16) 22 0.55 (0.36-0.84) 21 0.58 (0.38-0.8

1 0.51 (0.07-3.62) 4 1.08 (0.40-2.87) 3 0.92 (0.30-2.84 0.76 (0.29-2.03) 4 0.49 (0.18-1.31) 5 0.67 (0.28-1.66 1.09 (0.49-2.42) 5 0.58 (0.24-1.41) 3 0.39 (0.12-1.2

3 0.64 (0.21-1.98) 8 0.99 (0.50-1.98) 2 0.28 90.07-1.12 1.60 (0.91-2.81) 17 1.13 (0.71-1.82) 5 0.38 (0.16-0.9

Diseases of the: Nervous system & sense organsCirculatory systemRespiratory systemDigestive system

External causes

5 0.61 (0.25-1.46) 5 0.37 (0.16-0.90) 5 0.43 (0.18-1.060 0.49 (0.38-0.64) 110 0.67 (0.56-0.81) 86 0.58 (0.47-0.7

9 0.38 (0.20-0.73) 16 0.47 (0.29-0.77) 7 0.23 (0.11-0.46 0.21 (0.09-0.47) 11 0.36 (0.20-0.65) 7 0.26 (0.12-0.5

36 0.67 (0.48-0.93) 45 0.59 (0.44-0.79) 38 0.58 (0.42-0.8




Table 9 (continued)

Cause of Death Obs

South East

SMR Obs

South West

SMR ObsAll causes 372 0.66 (0.60-0.73) 170 0.53 (45-0.61) 70

Malignant neoplasms (all) 135 0.79 (0.67-0.94) 63 0.66 (0.51-0.84) 26 Digestive organs 47 0.92 (0.69-1.22) 19 0.66 (0.42-1.04) 11 Respiratory system 21 0.45 (0.29-0.68) 14 0.54 (0.32-0.91) 4 Skin 0 2 0.88 (0.22-3.52) 1 Male genital system 15 1.50 (0.90-2.49) 3 0.54 (0.18-1.69) 1 Urinary system 9 0.90 (0.47-1.74) 3 0.54 (0.17-1.68) 0Eye, brain & CNS 9 1.05 (0.55-2.01) 6 1.21 (0.54-2.70) 2 Lymphohaematopoietic 18 1.10 (0.69-1.74) 8 0.85 (0.42-1.70) 4

Diseases of the: Nervous system & sense organs 6 0.43 (0.19-0.95) 2 0.24 (0.06-0.96) 0Circulatory system 119 0.62 (0.52-0.75) 52 0.49 (0.37-0.64) 26 Respiratory system 19 0.47 (0.30-0.74) 11 0.49 (0.27-0.89) 2 Digestive system 11 0.34 (0.19-0.61) 1 0.05 (0.01-0.38) 1

External causes 62 0.86 (0.67-1.10) 33 0.72 (0.51-1.01) 14


25



26

Table 10 Mortali ty in men by year of bir th, 1987-2005

Before 1930 1930-1939 Cause of Death

Obs SMR Obs SMR Obs

All causes 184 0.58 (0.50-0.67) 489 0.59 (0.54-0.65) 391

Malignant neoplasms (all) 68 0.65 (0.51-0.83) 232 0.77 (0.67-0.87) 163 Digestive organs 19 0.62 (0.40-0.97) 88 0.94 (0.77-1.17) 54 Respiratory system 11 0.32 (0.18-0.58) 59 0.61 (0.48-0.79) 39 Skin 2 1.92 (0.48-7.69) 4 1.01 (0.38-2.69) 3 Male genital system 7 0.65 (0.31-1.36) 23 1.08 (0.72-1.62) 3 Urinary system 4 0.60 (0.23-1.61) 12 0.65 (0.37-1.14) 12 Eye, brain & CNS 1 0.50 (0.07-3.52) 8 0.88 (0.44-1.75) 10 Lymphohaematopoietic 10 1.42 (0.77-2.64) 17 0.76 (0.47-1.22) 24

Diseases of the:

Nervous system & sense organs 4 0.71 (0.27-1.90) 7 0.50 (0.24-1.05) 5 Circulatory system 96 0.70 (0.57-0.85) 172 0.51 (0.44-0.59) 149 Respiratory system 11 0.30 (0.17-0.54) 36 0.50 (0.36-0.69) 12 Digestive system 1 0.10 (0.01-0.69) 8 0.24 (0.12-0.47) 20

External causes 2 0.40 (0.10-1.61) 11 0.50 (0.28-0.91) 27




Table 10 (continued)

Cause of DeathAll causes

Obs278

1950-1959

SMR0.62 (0.55-0.70)

Obs180

1960-1969

SMR0.49 (0.43-0.57)

Obs66

1970-1979

SMR0.62 (0.48

Malignant neoplasms (all)Digestive organsRespiratory systemSkinMale genital systemUrinary systemEye, brain & CNSLymphohaematopoietic

812414

4259

12

0.750.730.610.900.750.860.930.92

(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)

326304168

0.660.560.65

2.340.600.870.73

(0.47-0.94)(0.25-1.24)(0.21-2.01)

(0.84-5.96)(0.08-1.28)(0.39-1.94)(0.36-1.46)

71021002

0.770.84

3.292.30

0.70

(0.37(0.12

(0.82(0.32

(0.18

Diseases of the: Nervous system & sense organsCirculatory systemRespiratory systemDigestive system

78213

7

0.490.650.610.15

(0.23-1.02)(0.52-0.81)(0.35-1.05)(0.07-0.32)

425

33

0.260.470.220.11

(0.10-0.69)(0.32-0.70)(0.07-0.68)(0.04-0.36)

0600

0.76 (0.35

External causes 72 0.84 (0.67-1.06) 103 0.67 (0.55-0.81) 47 0.78 (0.58


27



Table 11 Mortali ty in men by age at first test, 1987-2005

Cause of DeathObs

<25

SMR Obs

25-29

SMR Obs

30-34

SMR

All causes 138 0.54 (0.46-0.64) 99 0.54 (0.44-0.65) 127 0.62 (0.52-

Malignant neoplasms (all) 15 0.60 (0.36-0.99) 19 0.72 (0.46-1.12) 31 0.77 (0.54-Digestive organs 2 0.49 (0.12-1.97) 4 0.63 (0.24-1.68) 7 0.61 (0.29-Respiratory system 1 0.69 (0.10-4.93) 2 0.69 (0.17-2.74) 2 0.29 (0.07-Skin 2 1.12 (0.28-4.46) 0 3 1.43 (0.46-Male genital system 2 1.75 (0.44-7.01) 3 3.21 (1.04-9.95) 0 Urinary system 0 1 1.00 (0.14-7.10) 3 1.51 (0.49-Eye, brain & CNS 2 0.51 (0.13-2.05) 3 0.82 (0.26-2.53) 4 0.90 (0.34-Lymphohaematopoietic 3 0.41 (0.13-1.27) 5 0.90 (0.37-2.16) 8 1.32 (0.66-

Diseases of the:

Nervous system & sense organs 2 0.18 (0.05-0.73) 3 0.39 (0.13-1.21) 6 0.78 (0.35-Circulatory system 14 0.60 (0.35-1.01) 14 0.46 (0.28-0.78) 33 0.68 (0.48-Respiratory system 0 4 0.55 (0.21-1.46) 4 0.44 (0.17-Digestive system 0 1 0.07 (0.01-0.49) 5 0.24 (0.10-

External causes 93 0.70 (0.57-0.86) 56 0.79 (0.61-1.03) 43 0.80 (0.59-


28




Cause of Death Obs

40-44

SMR Obs

45-49

SMR ObsAll causes 179 0.56 (0.48-0.64) 205 0.55 (0.48-0.63) 700

Malignant neoplasms (all) 78 0.75 (0.60-0.93) 85 0.63 (0.51-0.78) 307 Digestive organs 26 0.79 (0.54-1.16) 31 0.73 (0.52-1.16) 108 Respiratory system 18 0.64 (0.40-1.02) 21 0.52 (0.34-0.80) 71 Skin 2 0.70 (0.17-2.79) 0 7 Male genital system 1 0.31 (0.04-2.23) 2 0.35 (0.09-1.40) 30 Urinary system 5 0.83 (0.34-1.98) 4 0.50 (0.19-1.34) 19 Eye, brain & CNS 7 1.11 (0.53-2.33) 4 0.65 (0.24-1.72) 10 Lymphohaematopoietic 11 1.13 (0.62-2.03) 13 1.18 (0.68-2.02) 26

Diseases of the: Nervous system & sense organs 2 0.26 (0.06-1.03) 3 0.41 (0.13-1.26) 11 Circulatory system 54 0.48 (0.37-0.63) 85 0.61 (0.49-0.75) 286 Respiratory system 5 0.28 (0.12-0.66) 9 0.36 (0.19-0.70) 46 Digestive system 12 0.45 (0.26-0.80) 5 0.21 (0.09-0.51) 10

External causes 19 0.60 (0.38-0.94) 11 0.51 (0.28-0.92) 15


29



30

Table 12 Mortality in men by length of time since firs t licensed, 1987

Cause of Death

All causes

Malignant neoplasms (all)Digestive organsRespiratory systemSkinMale genital systemUrinary systemEye, brain & CNSLymphohaematopoietic

Diseases of the:

Nervous system & sense organsCirculatory systemRespiratory systemDigestive system

External causes

<5 years 5-9 years 10-14 year

Obs SMR Obs SMR Obs SM

341 0.49 (0.44-0.55) 501 0.60 (0.55-0.66) 563 0.62 (0.5

108 0.60 (0.50-0.73) 182 0.76 (0.65-0.87) 217 0.75 (0.642 0.81 (0.60-1.10) 57 0.79 (0.61-1.02) 75 0.86 (0.618 0.36 (0.23-0.57) 37 0.54 (0.39-0.75) 54 0.68 (0.54 0.80 (0.30-2.13) 2 0.34 (0.09-1.38) 7 1.16 (0.55 0.69 (0.29-1.66) 12 0.99 (0.56-1.74) 17 0.92 (0.57 0.72 (0.34-1.51) 11 0.80 90.44-1.44) 10 0.59 (0.3

11 0.97 (0.54-1.75) 6 0.47 (0.21-1.04) 13 0.99 (0.511 0.54 (0.30-0.97) 35 1.51 (1.09-2.11) 21 0.84 (0.5

3 0.16 (0.05-0.50) 5 0.25 (0.10-0.60) 13 0.58 (0.34114 0.53 (0.44-0.63) 169 0.61 (0.53-0.71) 187 0.61 (0.512 0.33 (0.19-0.58) 22 0.39 (0.26-0.59) 30 0.43 (0.3

6 0.18 (0.08-0.40) 9 0.18 (0.09-0.35) 19 0.30 (0.1

88 0.59 (0.48-0.73) 93 0.76 (0.62-0.93) 61 0.70 (0.54




Table 13 Mortali ty in men by modules taken, 1987-2005

Cause of DeathObs

Foundation only

SMR

Foundation + Ground crop sprayer

Obs SMR

Foundation + Hand-

Obs S

All causes 297 0.75 (0.67-0.84) 332 0.47 (0.42-0.52) 854 0.62 (0.5

Malignant neoplasms (all) 104 0.85 (0.70-1.02) 121 0.60 (0.50-0.72) 319 0.76 (0.6Digestive organs 33 0.90 (0.64-1.26) 35 0.59 (0.42-0.82) 113 0.90 (0.7Respiratory system 26 0.72 (0.49-1.06) 23 0.42 (0.28-0.64) 69 0.58 (0.4Skin 2 0.82 (0.21-3.29) 3 0.59 (0.19-1.83) 10 1.06 (0.5Male genital system 7 0.90 (0.42-1.89) 12 1.12 (0.64-1.97) 21 0.89 (0.5Urinary system 6 0.83 (0.37-1.86) 7 0.61 (0.29-1.29) 18 0.74 90.Eye, brain & CNS 3 0.56 (0.18-1.74) 12 1.08 (0.61-1.89) 16 0.77 (0.4Lymphohaematopoietic 12 1.11 (0.63-1.96) 18 0.89 (0.56-1.41) 35 0.91 (0.6

Diseases of the:

Nervous system & sense organs 3 0.33 (0.11-1.02) 8 0.42 (0.21-0.85) 12 0.36 (0.2Circulatory system 107 0.76 (0.63-0.92) 97 0.43 (0.36-0.53) 291 0.62 (0.5Respiratory system 19 0.63 (0.40-0.99) 11 0.24 (0.13-0.43) 43 0.44 (0.3Digestive system 7 0.32 (0.15-0.68) 3 0.07 (0.02-0.21) 27 0.32 (0.2

External causes 47 1.06 (0.80-1.41) 80 0.69 (0.55-0.86) 115 0.66 (0.5


31




Other Modules

Cause of Death Obs SMRAll causes 81 0.38 (0.30-0.47)

Malignant neoplasms (all) 30 0.48 (0.33-0.68)Digestive organs 9 0.90 (0.75-1.08)Respiratory system 8 0.46 (0.23-0.93)Skin 0Male genital system 0Urinary system 2 0.56 (0.14-2.22)Eye, brain & CNS 2 0.61 (0.15-2.43)Lymphohaematopoietic 5 0.82 (0.34-1.97)

Diseases of the: Nervous system & sense organs 3 0.54 (0.17-1.67)Circulatory system 27 0.38 (0.26-0.56)Respiratory system 1 0.07 (0.01-0.48)Digestive system 2 0.15 (0.04-0.61)

External causes 15 0.47 (0.29-0.79)


32



6.4 REVIEW OF THE LITERATURE

The body of evidence from studies of chronic disease in pesticide-exposed worker populationsgenerally report consistent findings in mortality patterns, despite a variety of methodological

issues15-21. Exposure data is frequently unavailable, but where it is, demonstrating a causalrelationship 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 exposuremay vary widely between applicators. Farmers and other agricultural workers, pesticidemanufacturers and applicators, the main worker groups that have been studied, tend to behealthier compared with the general population, especially with respect to cardiovascular disease and the diseases associated with heavy tobacco and alcohol use. They are, however, atan 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 respiratorydisease; to the extent that certain pesticides have immunologic effects, pesticide exposure maycontribute 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 casesfor 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 5-10times 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 alsomore 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 thanthose receiving compensation. Evidence from SWORD/OPRA suggests the number of newcases varied between about 20 and 50 per year over the last ten years with no obvious trendsd . Asignificant number of farmers develop mild chronic lung impairment, which is predominantlyobstructive airflow disease associated with mild emphysematous changes. Farmers lung diseaseis 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 pneumonitis

28. 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

http://www.hse.gov.uk/statistics/causdis/respiratorye 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 thedisease.

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 farmersin 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’ lungdisease 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, twocarbamate 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 theserisks 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. Pesticideshave been associated with cough and phlegm among participants in the Singapore ChineseHealth Study33. Also, in a study of non-smoking women in the AHS, chronic bronchitis wasassociated with exposure to dichlorvos, dichlorodiphenyl thrichloroethane (DDT), cyanazine,

paraquat and methyl bromide after multivariate adjustment34. A study of the baseline datacollected for the AHS reported that 11 pesticides were significantly associated with chronic

bronchitis, after adjustment for correlated pesticides and confounders

35

. 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 farming36 37, grain handling38, and livestock production39 40. A recent population-based survey of 1,258men and women in Austria found that 23% had any type of farming experience, and thatfarming was the only occupation with increased prevalence of chronic obstructive pulmonarydisease (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 betweenworking with pesticides and prevalence of cough and chronic phlegm43. In Saskatchewan,Canada, farmers working with carbamates and OPs have reported a higher prevalence of asthmathan other farmers44.

In the US AHS an increased odds of wheeze was associated with 11 of 40 pesticides amongmore than 20,000 farmer pesticide applicators45. Pesticides associated with increased wheezeincluded the herbicides paraquat, atrazine, alachlor and chlorimuron-ethyl (CME) and the OPinsecticides parathion and chlorpyrifos. Significant dose-response relationships were alsodemonstrated for chlorpyrifos, s-ethyl-dipropylthiocarbamate (EPTC), paraquat and parathion.

Later work showed a dose-response trend for CME and phorate46

.

34



6.4.2 Neurolog ical Diseases

6.4.2.1 Neurolog ical symptoms

The neurological consequences of high-level exposure to pesticides are well established 47 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, papillaryconstriction, and excessive sweating, tearing and salivation. High exposures can lead to muscleweakness and twitches, changes in heart rate, and bronchospasm and can progress toconvulsions and coma. Some patients may develop OP-induced delayed neuropathy two to fiveweeks 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 poisoning

49, suggesting that the residual damage is permanent.

In a recent study, the prevalence and pattern of neuropsychiatric symptoms were consistentlymore 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 betweenthe number of neurological symptoms experienced and cumulative lifetime days of insecticideuse, 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 historyof 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, manyof 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 exposuremay increase the risk of Parkinson’s disease51 60 63 64.

However, findings have been inconsistent, and a number of methodological difficulties wereidentified 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 pesticideshaving a similar toxicological action was noted.

In a case-control study in four European centres (Scotland, Sweden, Italy, Romania), 649 casesand 1,587 controls were recruited, and their lifetime occupational histories collected 67. Scottishdata 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 afurther 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. noexposure: 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 wereobserved (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 wereexamined 69. Overall, individuals with Parkinson’s disease were significantly more likely toreport 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 toinsecticides 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 neurologicaldisease is sparser. Several studies have suggested that the risk of amyotrophic lateral sclerosis isrelated to farming as an occupation, although the evidence for an increased risk with pesticideexposure 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 factorshave been identified including head injury, low serum levels of folate and vitamin B 12, 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 anincreased risk of Alzheimer’s disease for occupational exposures, including pesticides, isgenerally 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 designfound 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 (Group2A)16. However, epidemiological studies relating pesticide exposure and human cancer have

been inconsistent, and the evidence probably cannot be considered to establish a causalrelationship for any single pesticide at the present time16. According to IARC and the USEnvironment Protection Agency (EPA) the weight of evidence suggests that althoughoccupational exposure to other insecticides is probably associated with human cancer, therelationship is not considered causal because of the lack of high-quality evidence. The siteswhere 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’sdisease, 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 pesticideuse. The last published Occupational Health Decennial Supplement did not show any excessrisk 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 thehypothesised 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 beensuggested as risk factors for Non-Hodgkin’s lymphoma based on findings from studies of

pesticide applicators, pesticide manufacturers, chemical production workers, and militaryveterans who served in Vietnam

83. 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 lymphomarisk with pesticide exposure

83. The study populations included agriculture and applicators,

producers and manufacturers, case-control (incident) and cohort (incident) studies, proportionalmortality analyses, accidents and environmental exposures. The relative risks ranged from 0.3 to10.0, however, no summary statistic was estimated.

Blair and Zahm3 reviewed the literature and reported that Non-Hodgkin’s lymphoma has beenlinked with exposure to phenoxyacetic acid herbicides, OC and OP pesticides. In 18 of 29studies, farmers were observed to show excesses of Non-Hodgkin’s lymphoma compared to thegeneral population, but no excess was greater than twofold 84.

Population-based case-control studies have observed NHL risk with self-reported agriculturalexposures to specific pesticide groups23 85 86. A Canadian multi-centre population-based incidentcase-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 amidefungicides, 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’slymphoma risk

4.

Cohort and case-control studies that evaluated specific pesticides or classes of pesticidesgenerally have reported inconsistent findings. This may be due, in part, to studies investigatingdifferent exposure scenarios and using different variables to classify the exposures. Asexamples, reports from the US AHS that evaluated specific pesticides found no increased NonHodgkin’s lymphoma risk 90-95.

Various meta-analyses have examined the risk of Non-Hodgkin’s lymphoma among farmersand shown associations to be weak. In an analysis of 14 studies of farmers no significantassociation 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=1.171.55)97. The most comprehensive review, which looked at 36 studies published between 1982and 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 cohortstudies 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 thesummary 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. Metaregression showed that a long period of exposure (>10 years) was associated with an increase inthe 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 associationwas seen between crop farming and Non-Hodgkin’s lymphoma risk, but a greater risk wasobserved amongst livestock workers (meta-RR 1.31, 95% CI – 1.08-1.60). Diagnostic analysesdid not indicate the presence of publication bias, but there was significant heterogeneity. Theauthors concluded, “Overall, the available evidence supports the hypothesis of a weak association between farming and Non-Hodgkin’s lymphoma risk. Although the quantitativesummary estimate of the strength of the association is uncertain given the heterogeneity inexposure circumstances, it is unlikely that the excess risk in farmers is higher than 10% to15%”.

Findings from studies of occupationally exposed pesticide production/manufacturing workers,including studies among phenoxy or chlorophenol production and manufacturing workers

102-104,

triazine manufacturing workers105

, and alachlor manufacturing workers106

have generally been107 108. Inmixed. Studies of pesticide applicators have generally shown no excess risk a

multinational study of workers enrolled in the IARC cohort, no significant excess of NonHodgkin’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-analysisof mortality in crop protection product manufacturing workers identified 26 studies thatinvestigated NHL risk 110. The pooled estimate was 1.98 (95% CI=1.45-2.69), whereas instudies 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 lymphoid 112, chroniclymphoid 113 114, acute myeloid 115 and chronic myeloid 116, with pesticide exposure suggested asthe likely cause.

A number of meta-analyses have been undertaken. Keller-Byrne et al 117 investigated 19 studiesthat examined the association between leukaemia and farming. A random-effects meta-analysisyielded a relative risk of 1.09 (95% CI= 0.997-1.19). The meta-RR of 10 case-control studieswas 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 bystudy 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 exposureand leukaemia, all but one with statistical significance118. Exposure to specific pesticides,including mancozeb and toxaphane119, have been associated with excess mortality fromleukaemia. Evidence from a few studies of workers exposed to DDT provide limited support for an association with leukaemia113, and chronic lymphoid leukaemia120. Exposure to dichlorvosand other pesticides like nicotine and pyrethrins gave, after a 20-year latency, significantexcesses 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 risk 107 123.

A study by Jones et al 110 reviewed 30 studies of crop protection product manufacturing workersfrom Europe, USA and China, and obtained a pooled estimate of 1.08 (95% CI=0.81-1.44). In asub-group of 20 cohorts of workers involved in the manufacture of phenoxy herbicides thesummary risk estimate was 1.02 (95% CI=0.71-1.46). In contrast to this, a recent meta-analysisof 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 2005examining the association between myeloid leukaemia and occupational pesticide exposureestimated a meta-rate ratio for cohort studies of 1.21 (95% CI=0.99-1.48)125. The meta-RR was6.32 (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 Multip le Myeloma

The Occupational Health Decennial Supplement did not show an increased mortality frommyeloma among farmers but did show an increased risk of contracting myeloma among malefarmers (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 myelomahave generally reported estimates exceeding 1.0 overall and for specific subgroups, althoughthese were not always statistically significant96 128-136. However, interpretation of the resultsfrom studies examining the link between farming and myeloma is limited by the broad exposureclassification of farming as an occupational group. Farmers also perform activities such asmachine repair, carpentry, welding, painting, equipment operating, pesticide and fertiliser mixing and application, and livestock handling. These activities may involve contact withmultiple 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 to2.5, 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 obtained 137. 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 anon-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 authorsundertook 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-analysisof 25 cohorts from Europe, USA, China and New Zealand of pesticide production workersobtained 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 theaetiology of soft tissue sarcoma because of their relatively low incidence and inherentmisclassification of histology139. Also, because of the rarity, any study usually groups all thedifferent histological subtypes into one, resulting in a loss of specificity and possibly maskingthe behaviour of the different subtypes. Soft tissue sarcoma are made up of a heterogeneous mixof cancer subtypes and it has been suggested that occupational risk factors are not uniformacross subtypes

140. 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 associationof Karposi’s and AIDS is supportive of this hypothesis. Tobacco use has been inconsistentlyassociated with soft tissue sarcoma, and diet has been little studied. The role of therapeuticradiation in inducing soft tissue sarcomas is well established 139.

A number of studies have found an association between herbicide use and soft tissue sarcoma141

144, 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 malignantfibrohistiocytic sarcoma (OR=2.9, 95% CI=1.1-7.3) but not with liposarcoma.

6.4.3.5 Prostate Cancer

In the previous Occupational Health Decennial Supplement, mortality from prostate cancer wassignificantly increased (PMR=112, 95% CI=106-118) among farmers10.

Prostate cancer risk among farmers and other pesticide users has been examined in a largenumber of studies in Europe and US, with relative risks generally less than two

4 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 studyshowed use of chlorinated pesticides over 50 years of age and methyl bromide use weresignificantly associated with prostate cancer risk. Several other pesticides also showed asignificantly 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 beinconclusive150. 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 acombined 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 obtained 151.Significant heterogeneity was observed and the major sources were geographic location, studydesign and the healthy worker effect. A stratified analysis revealed a significant increase in therate ratio of pesticide applicators (RR=1.64, 95% CI=1.13-2.38), whereas this was not the casefor 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=1.051.58)152. In analyses stratified by specific chemical class, increases in prostate cancer risk wereseen in all groups, but statistical significance was only found for accidental or non-accidentalexposure to phenoxy herbicide contaminated with dioxins and furans. A more recent metaanalysis 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 phenoxyherbicides 110.

40



6.4.3.6 Pancreatic Cancer

The risk of pancreatic cancer and exposure to pesticides has been found to be elevated, butrarely statistically significant, in a number of occupational studies of agricultural workers and

pesticide users including: farmers153, agricultural pesticide applicators123 154 155, and productionworkers110. 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 fromlung cancer among male farmers (PMR=88, 95% CI=86-91)10. Lung cancer is causallyassociated with exposure to arsenical compounds156, and an excess risk has been observed among vineyard workers157, arsenical pesticide manufacturers158 159 and general pesticidemanufacturers110. Increased risk has also been observed amongst licensed pesticide applicatorsin the US and rose with the number of years licensed 160 161. Similar findings were also seen inGermany162. Studies have observed excesses with exposure to OP and carbamate insecticidesand phenoxyacetic acid herbicides160, phenoxy herbicides and/or contaminants(dioxins/furans)

109, and evidence of exposure response for others

163. However, in a review of

studies published in 1992-1997 (19 case-control & 21 cohort, not all investigating lungcancer)108, only one case-control study160 reported an excess risk of lung cancer. Farmers havenot been seen to be at risk of lung cancer 99, and neither have pesticide applicators studied in theAHS89 or from Florida4. However, lung cancer risk was increased with exposure to some OCinsecticides164, 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 toherbicides166 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. TheOccupational 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 themeta-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 wereobserved among farmers10.

The aetiology of brain cancer is still poorly understood. Brain tumours have been associated with several occupational and environmental exposures, including farming

168-170and

pesticides171

. A review of studies published before 1995 concluded that existing data wereinsufficient to demonstrate that exposure to pesticides is a clear risk factor for brain tumours 172.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 33studies, 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 alsomicroorganisms. 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=1.021.11)99, which was similar to that obtained in an earlier analysis96. A meta-analysis of 30 studiesof 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 breastcancer. 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 araised incidence, although this was not statistically significant

174, and mortality was below that

expected 89

. 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=0.781.13) 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 toadequately deal with potential confounding by sun exposure176. Case-control studies177 178 and studies on the incidence and/or mortality caused by cutaneous melanoma amongst agriculturalworkers and farmers or those otherwise exposed to pesticides (e.g. vets), found indication for anincreased risk 147 179-182, although another showed a decrease154.

Similarly, the main cause of non-melanoma skin cancer is sun exposure, in particular ultravioletradiation183, and exposure to ionising radiation has been shown to increase risk. Exposure toarsenic contaminated drinking water has be shown to increase the risk of non-melanoma skin

184 185cancer . However, in industries where arsenic exposure may occur, including themanufacture 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 rarelyfatal. Studies of farmers have generally shown them to be at an increased risk 84 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 takeninto 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 mostcommon fatal accidents in agriculture are those involving vehicles and machinery, falls fromheight 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 DangerousOccurrences Regulations (RIDDOR), the most frequent categories of fatal accident were thoseinvolving vehicles and machinery and falls from height. In addition, electrical injuries accountfor a relatively high proportion of deaths. Other less common accidents are asphyxiation and injury by an animal22. The Occupational Health Decennial Supplement also confirms thesefigures, 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. Farmershave, for a long time, been under considerable financial pressures especially as most are runningtheir own businesses, and it has been widely agreed that because of this the suicide rates aremuch 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 (70deaths). 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 mostcommon 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) wassuicide. 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 alsoindependent, and decisive. Although there is good information about suicide in farmers, the dataare 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 aetiologyis not well known. Non-occupational risk factors include light eye colour, hypertension, historyof cardiovascular disease, diabetes, sun exposure, and low antioxidant levels, but studies have

produced inconsistent results. Genetic susceptibility may play a role because familialaggregation has been demonstrated 191. Little is known about its relationship to occupational or environmental neurotoxic exposures, although the available evidence mainly concerns exposureto pesticides, primarily OP insecticides. In the AHS, retinal degeneration was associated withfungicide 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 carbamateinsecticides.

However, because retinal degeneration is very rarely fatal, it has not been possible to study thisdisease 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 Survey2007 . Newport: Office for National Statistics, 2007:62.

3. Blair A, Zahm SH. Agricultural exposures and cancer. Environmental Health Perspectives1995;103(suppl 8):205-208.

4. Fleming LE, Bean JA, Rudolph M, Hamilton K. Mortality in a cohort of licenced pesticideapplicators 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. Persistentorganochlorine 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 DecennialSupplement 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: ahuman volunteer study. Toxicol Lett 2002;134(1-3):115-8.

13. Garfitt SJ, Jones K, Mason HJ, Cocker J. Exposure to the organophosphate diazinon: datafrom a human volunteer study with oral and dermal doses. Toxicol Lett 2002;134(13):105-13.

14. Griffin P, Mason H, Heywood K, Cocker J. Oral and dermal absorption of chlorpyrifos: ahuman volunteer study. Occup Environ Med 1999;56(1):10-3.

15. Doe JE, Paddle GM. The Evaluation of Carcinogenic Risk to Humans - OccupationalExposures 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 HealthOrganization, 1990.

25. Zheng TZ, Blair A, Zhang YW, Weisenburger DD, Zahm SH. Occupation and risk of nonHodgkin's lymphoma and chronic lymphocytic leukemia. Journal of Occupational and


26. Moses M, Johnson ES, Anger WK, Burse VW, Horstman SW, Jackson RJ, et al.Environmental equity and pesticide exposure. Toxicology and Industrial Health1993;9(5):913-959.

27. Maroni M, Fait A. Health effects in a man from long-term exposure to pesticides. A reviewof 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 CriticalCare 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 DecennialSupplement for England and Wales. London: HMSO, 1995:23-43.

31. Alavanja MC, Sandler DP, McMaster SB, Zahm SH, McDonnell CJ, Lynch CF, et al. TheAgricultural 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 - TheSingapore Chinese Health Study. American Journal of Epidemiology2006;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 swineconfinement building environment: The adaptation to respiratory exposures in thechronically exposed worker. Journal of Agricultural Safety and Health 2003;9(3):185196.

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 bronchitisand 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 prevalenceof 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 FamilyHealth and Hazard Surveillance Project. American Journal of Industrial Medicine2000;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 agriculturalhealth 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 MC, 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 neurologicalsequelae 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 pastusers of sheep dip and other pesticides. Occupational and Environmental Medicine2007;64(4):259-266.

51. Kamel F, Engel LS, Gladen BC, Hoppin JA, Alavanja MCR, Sandler DP. Neurologicsymptoms 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 theAgricultural 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 occupationalexposure 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 applicatorsexposed to organophosphates. Occupational and Environmental Medicine1995;52(10):648-653.

55. Steenland K, Dick RB, Howell RJ, Chrislip DW, Hines CJ, Reid TM, et al. Neurologicfunction among termiticide applicators exposed to chlorpyrifos. Environmental HealthPerspectives 2000;108:293-300.

56. Pilkington A, Buchanan D, Jamal GA, Gillham R, Hansen S, Kidd M, et al. Anepidemiological study of the relations between exposure to organophosphate pesticides

and indices of chronic peripheral neuropathy and neuropsychological abnormalities insheep farmers and dippers. Occupational and Environmental Medicine2001;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 Physician2007;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 exposureand self-reported Parkinson's disease in the Agricultural Health Study. American


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 Journalof 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 Neurology2006;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 - isthere 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 animaldata associating pesticides with Parkinson's disease. Journal of Occupational and


67. Dick S, Semple S, Dick F, Seaton A. Occupational titles as risk factors for Parkinson'sdisease. 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. Pesticideexposure 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: acase-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 diseasein 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 case-control 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-controlstudy of amyotrophic lateral sclerosis. Neuroepidemiology 1991;10(5-6):242-245.

49



75. Cummings JL, Cole G. Alzheimer disease. Journal of the American Medical Association2002;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: areview 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 Investigation2005;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 theherbicide 2,4-D. International Journal of Toxicology 1992;11(5):559-664.

82. Descatha A, Jenabian A, Conso F, Ameille J. Occupational exposures and haematologicalmalignancies: overview on human recent data. Cancer Causes & Control2005;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 Reviews1991;6:335-354.

85. Woods JS, Polissar L, Severson RK, Heuser LS, Kulander BG. Soft tissue sarcoma and nonHodgkin’s lymphoma in relation to phenoxyherbicide and chlorinated phenol exposurein 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 case-control 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. NonHodgkin’s lymphoma and specific pesticide exposures in men: cross-Canada study of

pesticides and health. Cancer Epidemiology, Biomarkers & Prevention2001;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):279285.

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 cohortexposed 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. Malathionexposure and the incidence of cancer in the Agricultural Health Study. American


92. Bonner MR, Lee WJ, Sandler DA, Hoppin JA, Dosemeci M, Alavanja MCR. Occupationalexposure 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 HealthStudy. 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 incidenceamong 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 HealthStudy. 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 & Health1992;18(4):209-215.

97. Keller-Byrne J, Khuder SA, Schaub EA, McAfee O. A meta-analysis of non-Hodgkinlymphoma 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 amongfarmers: 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. Occupationalexposure to pesticides and risk of hematopoietic cancers: meta-analysis of case-controlstudies. Cancer Causes & Control 2007;18:1209-1226.

101. Boffetta P, de Vocht F. Occupation and the risk of non-Hodgkin lymphoma. Cancer Epidemiology, Biomarkers & Prevention 2007;16(3):369-372.

102. Burns CJ, Beard KK, Cartmill JB. Mortality in chemical workers potentially exposed to2,4-dichlorophenoxyacetic acid (2,4-D) 1945-94: an update. Occupational and


51



103. Coggon D, Pannett B, Winter PD. Mortality and incidence of cancer at four factoriesmaking phenoxy herbicides. British Journal of Industrial Medicine 1991;48(3):173178.

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):891901.

105. MacLennan PA, Delzell E, Sathiakumar N, Myers SL. Mortality among triazine herbicidemanufacturing workers. Journal of Toxicology and Environmental Health-Part a-Current Issues 2003;66(6):501-517.

106. Leet T, Acquavella J, Lynch C, Anne M, Weiss N, Vaugn T, et al. Cancer incidence amongalachlor manufacturing workers. American Journal of Industrial Medicine1996;30(3):300-306.

107. Swaen GMH, van Amelsvoort L, Slangen JJM, Mohren DCL. Cancer mortality in a cohortof 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. Cancer 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 populationand 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. Archivesof Environmental Health 1985;40(4):211-214.

115. Pearce NE, Sheppard RA, Howard JK, Fraser J, Lilley BM. Leukemia among NewZealand 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: TheOntario College of Family Physicians, 2004.

119. Mills PK, Yang R, Riordan D. Lymphohematopoietic cancers in the United Farm Workersof 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 engineexhausts, 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 rurallicensed pesticide users in the province of Rome. International Journal of Epidemiology1993;22(4):579-583.

124. Van Maele-Fabry G, Duhayon S, Mertens C, Lison D. Risk of leukaemia among pesticidemanufacturing 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. Multiplemyeloma: 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 & Control1992;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 theIllinois 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 studywith the use of death certificates. Journal of the National Cancer Institute1984;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 softtissue 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. Cancer 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 exposureto chemical substances: a case-referent study. British Journal of Industrial Medicine1981;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. Agriculturalherbicide 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 sarcomaand 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):634642.

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 Medicine1990;18(5):565-576.

154. Forastiere F, Quercia A, Miceli M, Settimi L, Terenzoni B, Rapiti E, et al. Cancer amongfarmers in central Italy. Scandinavian Journal of Work Environment & Health1993;19(6):382-389.

155. Zhong JP, Rafnsson V. Cancer incidence among Icelandic pesticide users. American Journal of Respiratory and Critical Care Medicine 1996;25:1117-1124.

156. IARC. Overall evaluations of carcinogenicity: An updating of IARC Monographs volumes1 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 toinorganic arsenicals. Archives of Environmental Health 1979;34(5):312-320.

159. Mabuchi K, Lilienfeld AM, Snell LM. Cancer and occupational exposure to arsenic: astudy 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 deathamong licensed pesticide applicators. Journal of the National Cancer Institute1983;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. Pesticidesand 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 toorganochlorine 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 incidenceamong 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 mesothelialtumors 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 herbicidesand 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 inEngland and Wales 1979-80, 1982-90. Occupational and Environmental Medicine1996;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 & Control2003;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, FraumeniJr 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 case-controlstudy 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 & Health1989;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 maleSwedish veterinarians and other workers of the veterinary industry: a record-linkagestudy. Cancer Causes & Control 2003;14(6):587-593.

182. Wesseling C, Ahlbom A, Antich D, Rodriguez AC, Castro R. Cancer in banana plantationworkers in Costa Rica. International Journal of Epidemiology 1996;25(6):1125-1131.

183. Karagas MR, Weinstock MA, Nelson HH. Keratinocyte carcinomas (basal and squamouscell 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 arsenicrelated 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 theskin 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 onthe 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. Retinaldegeneration in licensed pesticide applicators. American Journal of Industrial Medicine2000;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 (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 membersof 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.

the pesticide users health study 2013 uk = low cancer rates

Documents