10885044.pdf

Organophosphate Exposure in Australian
Agricultural Workers: Human Exposure and Risk
Assessment
Kelly Johnstone
Bachelor of Applied Science (Occupational Health and Safety)
Bachelor of Health Sciences (Honours)
A thesis submitted for the degree of Doctor of Philosophy
Centre for Health Research – Public Health
Queensland University of Technology
December 2006

OP Exposure in Agricultural Workers: Human Exposure and Risk
Assessment
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KEY WORDS
• OP pesticide
• DAP metabolites
• Risk assessment
• Workplace Health and Safety (WHS)
• Fruit and vegetable farmer
• Agricultural pilot
• Agricultural mixer/Loader
• Formulator
• Biological monitoring

Organophosphate Exposure in Australian Agricultural Workers: Human Exposure and
Risk Assessment
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ABSTRACT
Organophosphate (OP) pesticides, as a group, are the most widely used
insecticides in Australia. Approximately 5 000 tonnes of active ingredient are
used annually (Radcliffe, 2002). The OP pesticide group consists of around 30
identifiably distinct chemicals that are synthesised and added to approximately
700 products (Radcliffe, 2002). OP pesticides are used on fruit, vegetable, grain,
pasture seed, ornamental, cotton, and viticultural crops, on livestock and
domestic animals, as well as for building pest control.
OP pesticides all act by inhibiting the nervous system enzyme
acetylcholinesterase (AChE) and as such are termed anticholinesterase
insecticides. The phosphorylation of AChE and the resultant accumulation of
acetylcholine are responsible for the typical symptoms of acute poisoning with
OP compounds. In addition to acute health effects, OP compound exposure can
result in chronic, long-term neurological effects.
The traditional method of health surveillance for OP pesticide exposure is blood
cholinesterase analysis, which is actually biological effect monitoring. However,
there are several drawbacks associated with the use of the blood cholinesterase
test, including its invasive nature, the need for baseline levels and a substantial
exposure to OP pesticide before a drop in cholinesterase activity can be detected.
OP pesticides are metabolised fairly rapidly by the liver to form alkyl phosphates
(DAPs). Approximately 70% of OP pesticides in use in Australia will metabolise
into one or more of six common DAPs. During the last 30 years, scientists have
developed a urine test that detects these six degradation products. However,
unlike the blood cholinesterase test, there is currently no Biological Exposure
Index (BEI) for the urine DAP metabolite test.
Workers in the agricultural industry - particularly those involved with mixing,
loading and application tasks - are at risk of exposure to OP pesticides. It is
therefore important that these workers are able to assess their risk of health
effects from exposure to OP pesticides. However, currently in Queensland,

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workplace health and safety legislation exempts the agricultural industry from
hazardous substance legislation that incorporates the requirement to perform risk
assessments and health surveillance (blood cholinesterase testing) for OP
pesticide exposure.
The specific aim of this research was to characterise OP pesticide exposure and
to assess the feasibility of using urine DAP metabolite testing as a risk
assessment tool for agricultural and related industry workers exposed to OP
pesticides. An additional aim among farmers was to conduct an in-depth
evaluation of their knowledge, attitudes and behaviours related to handling OP
pesticides and how they assess the risks associated with their use of OPs.
A cross-sectional study design was used to assess exposure to OP pesticides and
related issues among four groups: fruit and vegetable farmers, pilots and
mixer/loaders, formulator plant staff and a control group. The study involved 51
farmers in the interviewer-administered questionnaire and 32 in urine sample
provision. Eighteen pilots and mixer/loaders provided urine samples and 9
exposed formulation plant staff provided urine and blood samples. Community
controls from Toowoomba Rotary clubs provided 44 urine samples and 11 non-
exposed formulation plant staff provided blood and urine samples; all groups
also provided responses to a self-administered questionnaire.
Participant farmers were drawn from the main cropping areas in south-east
Queensland – Laidley/Lowood, Gatton, and Stanthorpe. The farmer group was
characterised by small owner-operators who often had primary responsibility for
OP pesticide mixing and application. Farmers had good knowledge of pesticide-
related safety practices; however, despite this knowledge, use of personal
protective equipment (PPE) was low. More than half of the farmers did not often
wear a mask/respirator (56%), gloves (54%) or overalls (65%). Material Safety
Data Sheets were never or rarely read and 88.2% of farmers never or rarely read
OP pesticide labels before application. There were also problems with chemical
suppliers providing farmers with MSDSs. The majority of farmers (90.2%)
reported that they had never had any health surveillance performed and three-

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quarters had never read about or been shown how to perform a formal risk
assessment.
The main inhibitors to the use of PPE in the farmers’ group included the
uncomfortable and cumbersome nature of PPE, especially in hot weather
conditions, and the fear of PPE use triggering neighbours’ complaints to
Government authorities. Factors associated with better PPE use included having
positive attitudes and beliefs toward PPE use, higher knowledge scores and low
risk perception.
Farmers’ use of OP pesticides was infrequent, of short duration and involved
application via a boom on a tractor, a lower risk application method.
Consequently, urine DAP metabolite levels in this group were generally low,
with 36 out of 96 samples (37.5%) containing detectable levels. Detectable
results ranged from 9.00-116.00 μmol/mol creatinine.
Formulators exposed to OP pesticides were found to have the highest urine DAP
metabolite levels (detectable levels 13.20-550.00 μmol/mol creatinine), followed
by pilots and mixer/loaders (detectable levels 8.40-304.00 μmol/mol creatinine)
and then farmers. Despite this, pilots and mixer/loaders (particularly
mixer/loaders) had the greatest number of samples containing detectable levels
(94.4% of samples). The DAP metabolite most frequently detected across all
groups was DMTP, which was the only metabolite found in control samples.
Levels found in this study are similar to those reported in international research
(Takamiya, 1994, Stephens et al., 1996, Simcox et al., 1999, Mills, 2001, Cocker
et al., 2002). The observed DAP levels were not associated with a drop in
cholinesterase activity among the formulation plant workers, as expected from
the literature. Such exposure also is unlikely to be associated with acute health
effects. In contrast, there is insufficient scientific knowledge to know whether
levels recorded in this study and elsewhere may be associated with long-term,
chronic health effects.

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Notably, DMTP levels also were observed among the presumably ‘unexposed’
comparison groups. Environmental background level exposures to OPs
producing the DAP metabolite DMTP are therefore of potential significance and
may be related, at least in part, to consumption of contaminated fruit and
vegetables. There is also emerging evidence to suggest that exposure to DAP
metabolites themselves through diet and other sources may contribute to the
concentration of DAPs, including DMTP in urine, potentially complicating
assessment of occupational exposures. Nevertheless, the urine DAP metabolite
test was a useful, sensitive indicator of occupational OP pesticide exposure
among agricultural workers and may be of use to the industry as part of the risk
assessment process. Future research should aim to establish a BEI for the urine
DAP test.

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TABLE OF CONTENTS
CHAPTER 1: INTRODUCTION.......................................................................1
1.1 BACKGROUND...............................................................................................................1
1.2 AIMS AND OBJECTIVES .................................................................................................3
1.4 THESIS OVERVIEW........................................................................................................4
CHAPTER 2: LITERATURE REVIEW...........................................................6
2.1 OP PESTICIDES..............................................................................................................6
2.2 BIOLOGICAL MONITORING OF OP EXPOSURE .............................................................19
2.3 STUDIES INVESTIGATING FARMERS’ SELF-SURVEILLANCE OF PESTICIDE-RELATED
HEALTH EFFECTS AND POISONINGS............................................................................31
2.4 FARMERS’ KNOWLEDGE, BELIEFS, ATTITUDES, BEHAVIOURS AND RISK PERCEPTION
RELATING TO SAFE PESTICIDE HANDLING PRACTICES ................................................32
2.5 HEALTH AND SAFETY IN THE AUSTRALIAN AGRICULTURAL INDUSTRY .....................37
2.6 CURRENT HEALTH AND SAFETY PESTICIDE LEGISLATION AND POLICY IN QUEENSLAND42
2.7 CONCLUSION ..............................................................................................................45
CHAPTER 3: METHODS ................................................................................48
3.1 PROJECT OVERVIEW ...................................................................................................48
3.2 FRUIT AND VEGETABLE FARMERS’ STUDY.................................................................52
3.3 BIOLOGICAL SAMPLE COLLECTION.............................................................................58
3.4 OP PESTICIDE SELF-ADMINISTERED RISK FACTOR QUESTIONNAIRE..........................64
3.5 DATA MANAGEMENT..................................................................................................70
3.6 STATISTICAL ANALYSIS..............................................................................................77
CHAPTER 4: INTERVIEWER-ADMINISTERED QUESTIONNAIRE
RESULTS: FRUIT AND VEGETABLE FARMERS ....................................79
4.1 SAMPLE ......................................................................................................................79
4.2 FARMERS’ USE OF OP PESTICIDES..............................................................................87
4.3 PERSONAL PROTECTIVE EQUIPMENT USE ...................................................................89
4.4 FARMERS’ PESTICIDE SAFETY KNOWLEDGE...............................................................93
4.5 BELIEFS, ATTITUDES AND RISK PERCEPTION..............................................................94
4.6 SAFE PESTICIDE HANDLING PRACTICES......................................................................97
4.7 RISK ASSESSMENTS AND HEALTH SURVEILLANCE ...................................................103
4.8 POISONING EPISODES AND ACUTE HEALTH EFFECTS................................................104
4.9 INVESTIGATION OF RELATIONSHIPS BETWEEN PPE USE AND VARIOUS INDEPENDENT
VARIABLES ...............................................................................................................106

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4.10 SUMMARY OF RESULTS.............................................................................................112
CHAPTER 5: FARMER AND PILOT/MIXER/LOADER GROUPS
BIOLOGICAL SAMPLE RESULTS.............................................................115
5.1 FRUIT AND VEGETABLE FARMERS ............................................................................115
5.2 AGRICULTURAL PILOTS AND MIXER/LOADERS.........................................................127
5.3 TOOWOOMBA ROTARY CLUB CONTROL GROUP .......................................................136
5.4 COMPARISON BETWEEN URINE DAP METABOLITE RESULTS
FOR THE THREE GROUPS…………………………………………………………....140
CHAPTER 6: FORMULATOR PLANT WORKERS’ BIOLOGICAL
SAMPLE RESULTS........................................................................................147
6.1 FORMULATION PLANT WORKER SAMPLE .................................................................147
6.2 EXPOSED WORKERS’ URINE DAP METABOLITE RESULTS........................................147
6.3 CONTROL GROUP URINE DAP METABOLITE RESULTS .............................................155
6.4 COMPARISON OF URINE DAP METABOLITE LEVELS BETWEEN FORMULATOR PLANT
EXPOSED PARTICIPANTS AND CONTROLS .................................................................157
6.5 BLOOD CHOLINESTERASE TEST RESULTS .................................................................157
6.6 RELATIONSHIP BETWEEN URINE DAP METABOLITE LEVELS AND BLOOD
CHOLINESTERASE LEVELS ........................................................................................160
CHAPTER 7: DISCUSSION ..........................................................................167
7.1 SUMMARY OF MAJOR RESEARCH FINDINGS..............................................................167
7.2 FARMERS’ OP PESTICIDE-HANDLING PRACTICES.....................................................170
7.3 FARMERS’ KNOWLEDGE AND USE OF RISK ASSESSMENT TECHNIQUES....................172
7.4 FARMERS’ USE OF PPE AND DAP METABOLITE RESULTS........................................176
7.5 COMPARISON OF BIOLOGICAL SAMPLING RESULTS FOR THE .........................................
THREE EXPOSED GROUPS…………………………………………………………...179
7.6 ENVIRONMENTAL EXPOSURES TO OPS AND THE DMTP METABOLITE .....................181
7.7 WHAT DO THE DAP METABOLITE LEVELS MEAN IN TERMS OF HEALTH EFFECTS? .185
7.8 HOW DO THE LEVELS OBSERVED COMPARE WITH INTERNATIONAL RESEARCH?......186
7.9 SAMPLE COLLECTION REQUIREMENTS .....................................................................189
7.10 CORRELATIONS BETWEEN URINE DAP METABOLITE LEVELS AND BLOOD
CHOLINESTERASE ACTIVITIES ..................................................................................189
7.11 STUDY LIMITATIONS.................................................................................................191
7.12 STUDY VALIDITY......................................................................................................194
CHAPTER 8: CONCLUSION........................................................................196

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LIST OF TABLES
Table 2.1 Selected OP pesticide half-lives.................................................................................9
Table 2.2 Common OPs and their DAP metabolites.................................................................23
Table 3.2 Weighting for clothing and PPE ...............................................................................76
Table 4.1 Breakdown of 260 fruit and vegetable farmer contacts ............................................80
Table 4.2 Comparison of crops grown by participants and non-participants............................81
Table 4.3 Comparison of farm location for participants and non-participants..........................82
Table 4.4 Comparison of crops grown by participants and non-approachable farmers............83
Table 4.5 Comparison of farm location for participants and non-approachable farmers..........83
Table 4.6 Acres of land used for crop production.....................................................................85
Table 4.7 List of crops grown during the last 12 months..........................................................86
Table 4.8 Application methods used for OP pesticides ............................................................87
Table 4.9 OP pesticides applied to crops during the 12 months prior to interview ..................89
Table 4.10 Items of clothing and PPE worn during mixing OP pesticides...............................90
Table 4.11 Items of clothing and PPE worn during OP pesticides application.........................91
Table 4.12 Low and high-risk groups for three types of PPE while mixing and applying .......92
Table 4.13 Knowledge statements............................................................................................94
Table 4.14 Responses to beliefs and attitudes questions...........................................................96
Table 4.15 Environmental parameters ......................................................................................98
Table 4.16 Potential oral exposure to OP pesticides by interrupting application to eat, drink
smoke or talk on a phone ......................................................................................102
Table 4.17 Training courses completed by farmers................................................................103
Table 4.18 Frequency of acute symptoms experienced by farmers ........................................105
Table 4.19 Severity of acute symptom by perceived association ...........................................106
Table 4.20 Crude relationship between PPE use while mixing and various factors...............107
Table 4.21 Crude and adjusted OR for factors associated with high PPE-use scores while
mixing OP pesticides ............................................................................................109
Table 4.22 Crude relationship between PPE use while applying and various factors ............110
Table 4.23 Crude and adjusted OR for factors associated with high PPE use scores while
applying OP pesticides..........................................................................................111
Table 5.1 Urine dimethyl alkyl phosphate metabolite results (μmol/molcreatinine).............117
Table 5.2 Total dimethyl DAP concentrations for pre- and post-exposure samples...............118
Table 5.3 Cross-tabulation between detectable dimethyl DAP metabolites and spraying of
dimethyl DAP metabolites......................................................................................121
Table 5.4 Crude analyses of the relationships between exposure, measured as detectable DAP
metabolites, and risk factors related to potential exposure (n=32)..........................123

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Table 5.5 Crude analyses of the relationships between exposure, measured as detectable DAP
metabolites, and demographic characteristics, knowledge, attitudes and risk
perception ...............................................................................................................124
Table 5.6 Cross-tabulation for type of exposure (high measured as DAP metabolites over 50
μmol/mol creatinine) and various risk factors ........................................................125
Table 5.7 Pilot urine DAP metabolite results - μmol/mol creatinine......................................128
Table 5.8 Mixer/loader urine DAP metabolite results - μmol/mol creatinine.........................129
Table 5.9 Cross-tabulation between OP handled during sample collection, prior to sample
collection and type of DAP metabolites detected ...................................................132
Table 5.10 Crude analysis of the relationship between exposure, measured as detectable DAP
metabolites, and various risk factors (n=18)...........................................................135
Table 5.11 Crude analysis of the relationship between detectable DAP metabolites (yes/no), and
various environmental risk factors (n=43)..............................................................137
Table 5.12 Adjusted odds ratios for risk factors showing higher odds of having detectable
DMTP levels...........................................................................................................139
Table 5.13 Comparison of farmers, pilot/mixer/loaders and controls pre- and post-exposure
DAP metabolite results...........................................................................................141
Table 6.1 Urine DAP metabolite results for formulator Staff exposed to Rametin (μmol/mol
reatinine).................................................................................................................148
Table 6.2 Formulator plant exposed group DEP metabolite results (μmol/mol creatinine)...149
Table 6.3 Formulator plant exposed group DMTP metabolite results (μmol/mol creatinine)149
Table 6.4 Relationships between exposure, measured as detectable DAP metabolites, and
various occupational risk factors for the exposed group (n=9)..............................153
Table 6.5 Relationships between detectable metabolites (yes/no), and various environmental
risk factors for the exposed group (n=9).................................................................154
Table 6.6 Relationships between detectable metabolites (yes/no), and various environmental
risk factors for the formulator plant control group (n=11)......................................156
Table 6.7 Formulator plant exposed group blood cholinesterase test results..........................159
Table 6.8 Formulator plant control group blood cholinesterase test results ...........................159
Table 6.9 Comparison between exposed and control formulator plant groups’ blood
cholinesterase test results........................................................................................160
Table 6.10 Correlation between urine DAP levels and red blood cell and plasma cholinesterase
levels.......................................................................................................................161
Table 7.1 Comparison of urine DAP metabolite results .........................................................188

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LIST OF FIGURES
Figure 2.1 Generic structure of OP pesticides.................................................................................6
Figure 2.2 A: Reaction of AChE with ACh. B: Reactions of AChE with OP pesticides. C:
Reactivation of AChE by pralidoxime. ...................................................................12
Figure 2.3 Structure of the six main DAP metabolites.............................................................23
Figure 4.1 Highest level of education completed by participant farmers .................................84
Figure 4.2 Last OP application prior to interview ....................................................................88
Figure 4.3 Number of farmers reporting pesticide contact with specific body parts................99
Figure 5.1 Farmers’ urine DMTP concentrations (μmol/mol creatinine) (n=17)..................118
Figure 5.2 Total dimethyl DAP urine concentrations (μmol/L) (n=17) ................................119
Figure 5.3 Total dimethyl DAP metabolite results for pilots and mixer/loaders with detectable
levels (µmol/L) (n=13).........................................................................................130
Figure 5.4 Total diethyl DAP metabolite results for pilots and mixer/loaders with detectable
levels (n= 8) (µmol/L)..........................................................................................130
Figure 5.5 Pilots and mixer/loader DMTP concentrations (µmol/mol creatinine) ................131
Figure 5.6 Mean total DAP results (μmol/L) for farmers, pilots/mixer/loaders and controls.140
Figure 5.7 Total DAP results for the three groups for their pre-exposure sample and first two
post-exposure samples ..........................................................................................142
Figure 6.1 Urine DEP concentrations for formulator plant exposed group ............................150
Figure 6.2 Urine DMTP concentrations for formulator plant exposed group.........................151
Figure 6.3 Scatter plot of PsChE level and total dimethyl DAP level for controls.................161
Figure 6.4 Scatter plot of RBC ChE level and total dimethyl DAP Level for controls ..........162
Figure 6.5 Scatter plot of PsChE level and total diethyl DAP level for exposed group .........162
Figure 6.6 Scatter plot of PsChE level and total dimethyl DAP level for exposed group ......163
Figure 6.7 Scatter plot of RBC ChE level and total diethyl DAP level for exposed group....163
Figure 6.8 Scatter plot of RBC ChE Level and total dimethyl DAP level for exposed group164

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LIST OF ABBREVIATIONS
AAAA Aerial Agricultural Association of Australia
ACh acetylcholine
AChE acetylcholinesterase
ADI acceptable daily intake
Agvet agricultural and veterinary
APVMA Australian Pesticides and Veterinary Medicines Authority
BEI biological exposure index
ChE cholinesterase
CI confidence interval
COPIND chronic OP-induced neuropsychiatric discorder
DAP dialkyl phosphate
DMP dimethylphosphate
DMTP dimethylthiophosphate
DMDTP dimethyldithiophosphate
DEP diethylphosphate
DETP diethylthiophosphate
DEDTP diethyldithiophosphate
EVAO estimated value of agricultural output
MRL maximum residue limit
MSDS Material Safety Data Sheet
NATA National Association of Testing Authorities
ND not detected
NOEL no observable effect level
NOHSC National Occupational Health and Safety Commission
NSW New South Wales
NTE neuropathy target esterase
OHS Occupational Health and Safety
OP organophosphate
ppb parts per billion
PPE personal protective equipment
ppm parts per million

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PsChE plasma cholinesterase
QA quality assurance
QFVG Queensland Fruit and Vegetable Growers
Qld Queensland
QUT Queensland University of Technology
RBC red blood cell
RIRDC Rural Industries Research and Development Corporation
SD standard deviation
SPSS Statistical Package for Social Sciences
TEPP tetraethylpyrophosphate
WHO World Health Organisation
WHS Workplace Health and Safety
WHSQ Workplace Health and Safety Queensland

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STATEMENT OF ORIGINAL AUTHORSHIP
The work contained in this thesis has not been previously submitted for a degree
or diploma at any other higher education institution. To the best of my
knowledge and belief, the thesis contains no material previously published or
written by another person except where due reference is made.
Signed: __________________________
Date: __________________________

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ACKNOWLEDGEMENTS
I would like to gratefully acknowledge my supervisors Professor Mike Capra,
Professor Beth Newman and Dr Keith Adam for all their help, encouragement
and understanding. I would also like to thank the QUT School of Public Health
staff and students, especially Senior Lecturer Terry Farr and fellow PhD student
Jeong-ah Kim, for their support and friendship.
My sincere thanks and appreciation go to all the participants for the valuable
time they gave up to be part of this project. In particular, thanks to the
Toowoomba Rotary club members who volunteered to participate as study
controls.
I would like to acknowledge the in-kind support provided by Queensland Fruit
and Vegetable Growers (QFVG) and the Aerial Agricultural Association of
Australia (AAAA); their assistance was vital in the recruitment of participants. I
would like to thank the two State Departments - Workplace Health and Safety
Queensland and WorkCover NSW - that provided both financial and in-kind
support. Grateful appreciation is also due to the Rural Industries Research and
Development Corporation for project funding.
Finally, heartfelt thanks to my loving husband Robert and my darling son John
for their support, patience and understanding; without their help I could not have
completed this thesis. Special thanks also go to my parents and parents-in-law
who cared for John when I needed time for my PhD.

Organophosphate Exposure in Australian Agricultural Workers: Human Exposure and Risk
Assessment
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Chapter 1:
INTRODUCTION
1.1 Background
OP (OP) pesticides are a group of commonly used insecticides. OPs are nerve
poisons that kill target pests, usually insects. However, they also act on the
nervous systems of humans. Exposure to OPs can cause both acute and chronic
health effects. Agricultural workers, particularly those exposed to concentrated
OPs, such as mixers and loaders, are at increased risk.
Acute poisoning by OPs may result in nausea, vomiting, diarrhoea, abdominal
cramps, general weakness, headache, poor concentration, tremors, excessive
sweating, salivation and lachrymation. In serious cases, respiratory failure and
death can occur. Chronic health effects also have been documented, with two
main types suggested: after-effects from one or more acute poisoning incidents;
and after-effects that result from long-term, low-level exposure with no acute
poisoning incident. Effects are generally neuropsychological and neurological in
nature. Examples include OP-induced delayed polyneuropathy (OPIDP), which
is an uncommon sequela to acute poisoning, and chronic OP-induced
neuropsychiatric disorder (COPIND) (Davies et al., 1999).
Because OP pesticides are rapidly absorbed through the skin, biological
monitoring is an essential tool for the assessment of exposure. The health
surveillance method used currently throughout the world to monitor biological
effects is measurement of the reduction of blood cholinesterase activity. This
method involves the measurement of plasma cholinesterase and erythrocyte
acetylcholinesterase as a surrogate measurement of the reduction in
acetylcholinesterase activity in neural tissue and neuromuscular junctions.
However, the method has several well-recognised drawbacks, including its
insensitivity at low-level exposures (Drevenkar et al., 1991, Nutley and Cocker,

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1993, Hardt and Angerer, 2000), the invasiveness of the sampling procedure, and
the requirement of a baseline for the meaningful interpretation of results.
An alternative biological monitoring tool based on the measurement of OP
metabolites in urine is now available in Australia through the WorkCover NSW
laboratory. The test measures the concentration of six common OP degradation
products called dialkyl phosphate (DAP) metabolites. Advantages of this method
over the blood cholinesterase test include the test’s sensitivity to low-level
exposures, and a less invasive and easier collection technique.
1.1.1 Public Health Significance
Organophosphate pesticides are used widely throughout the world including
Australia. OPs are used to control pests on fruit and vegetables, livestock,
flowers and other crops, and in both industrial and domestic building pest control
applications. This wide spread use of OPs means that the Australian population
has potential exposure to OPs on a daily basis. Exposure can be defined as
human contact with a chemical with the potential for absorption (Krieger, 2002).
OPs may be effectively absorbed through the skin from contact with the pesticide
or contaminated surfaces, via inhalation and ingestion. Once absorbed into the
body they can have acute and / or chronic health effects depending on the dose.
Research has been conducted internationally to examine the exposures to OPs of
various groups including the general public, children and occupationally exposed
persons and their families in the agricultural industry, and to a lesser extent pest
control and formulation industries. However, currently there are no published
data about the levels of OP exposure experienced by Australian agricultural
workers. There are also no published Australian data on the field-based use of the
urine DAP test by agricultural workers.
The findings of this project will constitute a step forward in our knowledge of
Australian agricultural workers’ exposure to OP pesticides and to the
international body of knowledge on OP pesticide exposure. More specifically,
the study findings will aid the development of Queensland policy in the area of
agricultural industry workers’ health and safety, and assist in the development of

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a risk management guide for use by agricultural workers potentially exposed to
OP pesticides. On a broader public health level the research will assist farmers to
better manage their exposure to OP pesticides and therefore the potential for
adverse health outcomes from exposure and will further highlight the need to
examine the public health impacts of lifetime low level exposures to OPs through
diet and other sources.
1.2 Aims and Objectives
The broad aims of this study are to characterise OP pesticide exposure and to
assess the feasibility of using urine metabolite testing as a risk assessment tool
for agricultural and related industry workers exposed to OP pesticides. An
additional aim is to conduct an in-depth evaluation of farmers’ knowledge,
attitudes and behaviours related to handling OP pesticides and how they assess
the risks associated with their use of OPs.
The specific objectives of the study are:
1. to assess participant fruit and vegetable farmers’ attitudes, behaviours and
knowledge of safe OP pesticide handling practices;
2. to assess participant fruit and vegetable farmers’ knowledge and use of
formal risk assessment techniques;
3. to investigate the OP exposure levels of four groups – fruit and vegetable
farmers; agricultural pilots and their mixer/loaders; formulator plant staff;
and controls – using urine DAP metabolite analysis and, where possible,
blood cholinesterase testing;
4. to investigate sample collection requirements (e.g. sample collection
frequency, number and timing in relation to exposure) for urine DAP
metabolite monitoring; and
5. to investigate correlations between urine DAP metabolite levels and
blood cholinesterase activities where blood sampling is possible.

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1.3 Hypotheses
The project hypotheses are:
1. Participant fruit and vegetable farmers who have greater knowledge,
more positive attitudes and more appropriate practices will:
• use personal protective equipment when handling OP pesticides
more often than other participants; and
• have lower urine DAP metabolite levels than other participants.
2. A small proportion of farmers will have carried-out formal risk
assessments of their exposure to OP pesticides.
3. Higher potential exposure levels to OP pesticides will result in higher
urine metabolite levels. Potential exposure will be evaluated via two
methods: group membership and self-reported practices. The following
specific hypotheses relate to these measures of exposure:
• Formulators will have higher average exposures than pilots and
their ground crews who will have higher average exposures than
farmers, which will be reflected in their urine metabolite levels;
• Individual participants with higher potential exposures based on
self-reported practices will have higher urine metabolite levels.
4. The results of single and multiple urine DAP sample analyses will be
indistinguishable.
5. There will be no relationship between urine DAP metabolite levels and
blood cholinesterase activities.
1.4 Thesis Overview
Chapter 2 presents a summary of the relevant literature pertaining to OP
pesticides, including their history, acute and chronic health effects and
monitoring methods, and farmers’ knowledge, attitudes and beliefs relating to
safe pesticide handling practices. This chapter includes a brief overview of the
Australian agricultural industry and the Queensland health and safety legislation
and policy surrounding pesticide use.
Chapter 3 details the research methods used in the study. The fruit and vegetable
farmers’ study component is outlined, including details of questionnaire

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development and piloting, selection of the sample population and participant
recruitment, data collection and analysis. This chapter also describes the
biological sampling component of the study, including participant recruitment,
data collection and analysis methods.
Chapters 4, 5 and 6 present the study results. The fruit and vegetable farmers’
self-administered questionnaire results include a description of the participants,
their use of OP pesticides, and an examination of the key issues, including the
relationships between farmers’ knowledge, attitudes/beliefs, risk perception and
PPE use. The biological sample results from all four groups are presented in
chapters 5 and 6 and include an exploration of the relationships between
detectable levels of urine DAP metabolites and risk factors for each of the
exposure groups.
Chapter 7 summarises the results presented in chapters 4, 5 and 6 and then
offers an interpretation and discussion of the results in light of the project’s
objectives and hypotheses. The first section highlights the major findings of the
research project. The second makes comparisons between the results of this study
and previous research. A discussion of the strengths and limitations of the
research project concludes the chapter.
Chapter 8 concludes the thesis with an assessment of the implications of the
findings on public health policy and the practice of occupational health and
safety in the agricultural industry. Recommendations are made for future
research.

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Chapter 2:
LITERATURE REVIEW
2.1 OP Pesticides
Organophosphates (OPs) are esters of phosphoric or phosphorothioic acid that exist
in two forms: -thion (sulfur containing) and -oxon (oxygen containing) (LaDou,
2004). The -oxon OPs have a greater toxicity than -thion OPs. However, -thion OPs
readily undergo conversion to -oxons once in the environment. The -thion OPs also
undergo conversion into -oxons in vivo (LaDou, 2004). The majority of OP
pesticides in use are dimethyl compounds (two [-O-CH3] groups attached to the
phosphorus) or diethyl compounds (two [-O-C2H5] groups attached to the
phosphorus) represented by R1 in Figure 2.1.
Figure 2.1 Generic structure of OP pesticides
2.1.1 The history of OPs
OP insecticides were first synthesised in 1937 by German chemists. Many of these
first OPs were extremely toxic and some were developed into potential warfare
agents during World War II (e.g. chemicals such as soman, sarin, and tabun)
(Amdur, 1991). The first OP to be used commercially was tetraethlypyrophosphate
P
R1O O(S)
(OX or SX)
R1O
Note: X is the leavening group

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7
(TEPP); although effective, it was extremely toxic and not very stable, as it
hydrolysed in the presence of moisture (Amdur, 1991).
Further development gave rise to parathion (O,O-diethyl-O-p-nitrophenyl
phosphorothioate, E-605) in 1944 and subsequently the oxygen analog, paraoxon
(O,O-diethyl-O-p-nitrophenyl phosphate). Although these chemicals were stable,
they “exhibited a marked mammalian toxicity and were unselective with respect to
target and non-target species” (Amdur, 1991).
Currently in Australia, there are approximately 700 different commercially available
products containing OP pesticides (Oglobline, 2001). OPs are the most widely used
group of insecticides in Australia, each year around 5 000 tonnes of active
ingredients are used. (Radcliffe, 2002). The most used active ingredient from the OP
group has been parathion methyl, with over 1 000 tonnes used per annum. A
generally similar amount of chlorpyriphos is used widely on a range of fruit, nut,
viticultural, grain, cotton and ornamental crops and for termite control in the
building industry. Other major OP pesticides include dimethoate and forms of
profenofos (Radcliffe, 2002). Despite the wide spread use of OP pesticides, during
the last 10 years or so there has been a noticeable movement away from broad
spectrum, generally more toxic or ‘hard’ pesticides, such as OPs, to those which
target pests more specifically, are more efficacious and generally less toxic and
therefore ‘soft’ (Radcliffe, 2002). These more target specific pesticides are usually
still under patent and are therefore more expensive. Australian farmers are also
increasingly adopting integrated pest management (IMP) farming practices
(Radcliffe, 2002). Australian primary producers are also increasingly becoming
conscious of pesticide residue standards and quality assurance requirements. Due to
the adoption of IPM practices, the trend towards ‘softer’ pesticides and produce
quality assurance issues Australian farmers are using less OP pesticides than 10-20
years ago. While published sales figures for OP pesticides in Australia are
unavailable, published data does exist on the sales of insecticides as a group. In
2002, 959 different insecticide products were sold, compared to 811 in 1998 (NRA,

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8
1999, APVMA, 2003). Consequently, over a four-year period the number of
different insecticide products sold increased by 148 products, indicating a trend
toward the use of more non-OP, species-specific insecticides. However, OP
pesticides are still likely to be used for many years to come in the Australian fruit
and vegetable sector because of their effectiveness and affordability. Furthermore, in
developing countries OP pesticides are still very widely used.
2.1.2 OP pesticide half-lives
Unlike organochlorine pesticides, OP pesticides are non-persistent and break down
fairly rapidly once in the environment. One way to report the level of persistence of
a pesticide is to report its environmental half-life. A half-life is the period of time it
takes for one-half of the amount of OP pesticide to degrade. Non-persistent
pesticides have a half-life of up to 30 days, moderately persistent pesticides have a
half-life of 31 - 99 days, and persistent pesticides have a half-life of 100 days or
longer (Deer, 2004). Table 2.1 lists the half-lives of some commonly used OP
pesticides.
OP pesticides begin to break down as soon as they are mixed in an application tank.
Factors that can influence the rate at which a pesticide breaks down and therefore its
half-life include:
• the chemistry of the pesticide;
• chemical and physical properties of spray additives;
• chemistry (pH, hardness) of the spray water;
• a multitude of environmental factors (e.g. temperature, humidity, rainfall);
• factors relating to the plant (surface chemistry, waxiness, etc.); and
• soil conditions (e.g. microbial populations, moisture, temperature, pH)
(Cornell University, 2005).

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Table 2.1 Selected OP pesticide half-lives
OP PESTICIDE HALF-LIFE (T1/2) IN
SOIL (DAYS)
HUMAN OR ANIMAL
HALF-LIFE (T1/2)
(HOURS)
Acephate 3
Azinphos-methyl 10
Chlorpyrifos 30 27 - 30a
Diazinon 17-39 9a
Dimethoate 7
Fenamiphos 15.7
Fenthion 34 11b
Maldison 25 8b
Methamidophos 1.9 - 12
Methidathion 7
Parathion methyl 5
a
human elimination half-life
b
animal elimination half-life (e.g. rat and rabbit)
Source: (Emteres et al., 1985, Deer, 2004, Cornell University, 2005).
2.1.3 Routes of Exposure
OP pesticides can be absorbed via dermal exposure, inhalation (particularly when
fine mists, dusts or fumigants are used), or ingestion. In the occupational setting, the
dermal route of exposure is often the most significant. As OPs and many other
pesticides are absorbed across the external surfaces of insects and plants, they are
also effectively absorbed across intact human skin. Absorption may be increased
during hot weather when the skin is wet with perspiration. In a human volunteer
study conducted by Griffin et al., (1999), the absorption rate through the skin of a
28.59 mg dermal dose of chlorpyrifos was calculated to be 456 ng/cm2
/h. The fact
that many pesticides, including OPs, have high lipid solubilities and low molecular
weights enables them to be absorbed across intact skin (LaDou, 2004). A lower

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10
dermal LD50 value1
indicates greater OP absorption across the skin (LaDou, 1997).
For example, the OP mevinphos has a reported dermal LD50 value of 1-10 mg/kg.
Several other OPs such as parathion, azinphos-ethyl, and fensulfothion have low
dermal LD50 values, making them extremely toxic chemicals. Dermal absorption will
often go unnoticed until symptoms develop (Broadley, 2000).
2.1.4 Health effects from exposure to OPs
2.1.4.1 OP absorption and metabolism
Once an OP has been absorbed by the body it can be converted to its oxon form
enzymatically. In its oxon form it can react via phosphorylation with any available
cholinesterase (Wessels et al., 2003). “The oxon can also be enzymatically or
spontaneously hydrolysed to form a dialkyl-phosphate (DAP) metabolite and a
specific moiety” (Wessels et al., 2003). There are six main DAP metabolites of OP
pesticides; these will be discussed later in this chapter. If the OP is not converted to
its oxon form, it can undergo hydrolysis to form its specific metabolite and dialkly-
thionate metabolites (i.e. dialkylthiophosphate and/or dialkyldithiophosphate)
(Wessels et al., 2003). The metabolites are then excreted in urine. The specific
metabolites of many OPs are known and can be tested for in conjunction with, or
independent of, the six main DAP metabolites.
In their volunteer study, Griffin et al., (1999), calculated that the elimination half-life
of the urinary metabolites after a dermal dose of chlorpyrifos was 30 hours (95% CI:
25-39h). After an oral dose of chlorpyrifos, the calculated elimination half-life was
15.5 hours. A similar volunteer study conducted with diazinon reported oral and
dermal dose urinary DAP elimination half-lives occurring at 2 and 9 hours,
respectively (Garfitt et al., 2002).
1
LD50 is the lethal dose in terms of milligrams active ingredient per kilogram body weight for 50% of a sample
of test subjects. As LD50 values increase toxicity decreases.

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All OPs have the same general structure and mode of toxicity. The mode of toxicity
for OP pesticides involves the inhibition, via phosphorylation, of the nervous tissue
enzyme acetylcholinesterase (AChE) (LaDou, 2004). AChE destroys the
neurotransmitter acetylcholine (ACh) which transmits electrochemical signals across
neuronal synapses and neuromuscular junctions (LaDou, 2004). The
phosphorylation of AChE by OPs produces an accumulation of free unbound
neurotransmitter-ACh at the nerve endings of cholinergic nerves, resulting in
continual stimulation of electrical activity. Once the AChE has undergone
phosphorylation it can be spontaneously dephosphorylated and reactivated or aged
through the hydrolysis of an alkyl group, resulting in irreversible inactivation
(LaDou, 2004). The dephosphorylation process can take hours to days to occur, and
if the enzyme is irreversibly inactivated, enzyme activity can only return to its
normal state by the synthesis of new AChE. The new enzyme synthesis process can
take up to 60 days to complete (LaDou, 2004). Chronic depression of AChE can
result from repeated exposures during this 60-day period. Figure 2.2 (A) illustrates
the normal reaction of AChE with ACh, and Figure 2.2 (B) illustrates the reactions
of AChE with OP pesticides.

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Figure 2.2 A: Reaction of AChE with ACh. B: Reactions of AChE with OP
pesticides. C: Reactivation of AChE by pralidoxime.
Source: (LaDou, 2004), page 565.
The type and extent of ill-health effects that result from exposure to an OP pesticide
depend on several factors. Karalliedde et al. (2003) reported on the different
variables that influence the toxic response of humans to OP exposure. They divided
the process into five steps:
1. “Exposure dose - is the amount and concentration of the toxic agent in
contact with the point(s) of uptake into the body and the duration of the
contact.
2. Absorbed dose - is the amount and time over which the agent is taken up by
the body.
3. Target dose - is the concentration and time for which the target site(s) are in
contact with the agent.
4. Target effect - is the response of the target to the target dose of the toxic
agent.
5. Ill-health - is the final effect of the exposure on the well-being of the
exposed person.”
This figure is not available online.
Please consult the hardcopy thesis
available from the QUT Library

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13
2.1.4.2 Acute health effects
Exposure to OP pesticides can result in two main types of health effects, acute and
chronic. Acute effects occur rapidly after exposure. The clinical manifestations of
acute OP poisoning will depend on the affected organs where ACh is the transmitter
of nerve impulses. The symptoms of acute poisoning are well documented
(Klaassen, 2001, LaDou, 2004); they may include blurred vision, lachrymation,
salivation, bronchorrhea, pulmonary oedema, nausea, vomiting, diarrhoea, urination,
perspiration, incontinence, bradycardia, arrhythmias, heart block, cramps, headache,
dizziness, malaise, apprehension, confusion, hallucinations, manic or bizarre
behaviour, convulsions, loss of consciousness, and respiratory depression. Acute
intoxication may cause death; however, with appropriate emergency treatment, death
is less likely.
Treatment for acute poisoning can include the administration of pralidoxime, a drug
that works by reactivating the AChE as well as slowing the ‘aging’ process of
phosphorylated AChE to a non-reactivatable form (Reigart, 1999). Figure 2.2 (C)
illustrates the reactivation of AChE by pralidoxime. Atropine sulfate and
glycopyrolate are also drugs that can be administered to antagonise the effects of
excessive concentrations of ACh at end-organs having muscarinic receptors
(Reigart, 1999). Gastrointestinal decontamination is necessary if the OP-poisoned
person has ingested the pesticide and skin decontamination is important if the person
has had dermal exposure.
2.1.4.3 Chronic health effects
There are three types of chronic health effects from OP poisoning. These can be due
to:
1. repeated exposures over a short time period;
2. an acute poisoning episode; or
3. as a result of low-level, long-term exposure without any acute poisoning
episodes.

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The first type of chronic health effect results from repetitive small effects on specific
organs; if the damage is not repaired before the next dose adds to it (i.e. if the next
exposure occurs within approximately 60 days of the previous one, the destroyed
AChE will not be completely replaced). Chronic health effects are hard to diagnose
because they occur gradually and may be confused with other conditions causing
tiredness, headaches and other flu-like symptoms (LaDou, 2004).
The second type of chronic health effect occurs after an acute OP exposure episode.
These health effects are apparently non-reversing and have been investigated in
studies using humans reporting chronic OP neurotoxicity following acute episode/s
along with matched control groups (Savage, 1988, Rosenstock et al., 1990,
Rosenstock, 1991, McConnell et al., 1994). Earlier studies investigated chronic
health effects in acutely poisoned persons but did not utilise controls (Jamal et al.,
2002). All of these studies reported a positive link between acute episodes and
subsequent development of chronic effects. They also demonstrated that “neither the
incidence nor the severity of development of chronic neurotoxicity had any relation
with either the number or severity of the acute cholinergic episodes” (Jamal et al.,
2002).
The chronic health effects experienced have been well characterised and include a
range of secondary consequences to acute exposure episodes, such as intermediate
syndrome or OP-induced delayed polyneuropathy (OPIDP), an uncommon sequela
to acute poisoning by certain OPs. OPIDP is due to effects of neuropathy target
esterase (a protein distinct from AChE) inhibition (McConnell et al., 1994).
Evidence of this syndrome was first documented in 1963 by Spiegelberg, who
observed health effects such as lowered vitality and ambition, as well as intolerance
to alcohol, nicotine and various medicines among workers involved in the
production and handling of highly toxic OP nerve gases in Germany during World
War II (Klaassen, 2001).

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Rosenstock (1991) conducted a study of 36 men approximately two years after
poisoning to see whether single-dose episodes of acute unintentional OP intoxication
lead to chronic neuropsychological dysfunction. The study found that there was a
persistent decrease in neuropsychological performance among individuals with
previous intoxication. The poisoned subjects performed significantly worse than
controls on five of six subsets of a World Health Organization neuropsychological
test battery and on three of six additional tests that assessed verbal and visual
attention, visual memory, visuomotor speed, sequencing and problem solving, and
motor steadiness and dexterity (Rosenstock, 1991).
In a study conducted to evaluate effects from acute OP poisoning episodes, 36 male
Nicaraguan farmers were compared with matched controls (McConnell et al., 1994).
The authors found differences in vibrotactile threshold between the previously
poisoned workers and the controls. Abnormal vibrotactile threshold was common,
affecting more than one-quarter of the previously poisoned cohort (McConnell et al.,
1994).
The third type of chronic health effect has been increasingly reported following
long-term, low-level exposure without acute poisoning (Kedzierski, 1990, Stephens
et al., 1995, Beach, 1996, Fiedler et al., 1997, London, 1998, Jackson, 2001,
London, 1997, Cherry, 2002 , Sanchez-Santed, 2004 , Salvi, 2003, Farahat, 2003,
Horowitz, 1999). These studies have been less successful in finding evidence of
permanent neurological health effects than those involving farmers with past
poisoning episodes. Most of the research in the field of chronic, long-term, low-level
exposure has been conducted in the UK with farmers who dipped sheep in OP
pesticides for many years. The term “dipper’s flu” was coined in the UK to describe
flu-like symptoms reported by sheep farmers as a result of chronic exposure to OP
pesticides at levels which do not result in a significant cholinergic response as
measured by changes in blood cholinesterase levels (Jackson, 2001).

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Davies et al. (1999), identified the syndrome chronic OP-induced neuropsychiatric
disorder (COPIND) that can result from both long-term exposure to subclinical
doses of OPs and after acute intoxication. There are ten symptoms: severe,
incapacitating episodes of “dipper’s flu”; personality change with mood
destabilisation; impulsive suicidal thinking; memory and attention impairment;
language disorder; alcohol intolerance; heightened olfactory acuity; extreme
sensitivity to OPs; handwriting deterioration and impaired ability to sustain muscular
activity (Davies et al., 1999). As a result of a mailed survey to 400 UK farmers listed
in the Yellow Pages (44.6% response rate), the authors estimated that the prevalence
of COPIND in those exposed to OPs was around 10%.
Davies et al. (1999), described mood instability and impulsive suicidal thinking as
integral to COPIND. In the UK in 1997, mood disorder and cognitive impairment
were found legally valid by Justice Smith in her judgement in the case of Hill v.
Tomkins (LaDou, 2004). A Spanish retrospective study showed a marked increase in
suicide rates in farmers using OP pesticides compared to the rest of the population
and established a strong link between mood instability and suicide cases. (Parron et
al., 1996).
Horowitz et al, (1999) studied pesticide applicators with more than 20 years of
exposure to OPs and concluded that OPs are toxic to the peripheral nervous system
at levels of exposure that do not induce acute or subacute symptomology. A
relatively recent Egyptian study of cotton farmers and matched controls found that
occupational exposure to OPs was associated with deficits in a wider array of
neurobehavioral functions than previously reported (Farahat et al., 2003). Moderate
chronic exposure was reported to potentially affect not only visuomotor speed, but
also verbal abstraction, attention, and memory.
A recent study conducted in the UK aimed to investigate whether repeated exposures
to OPs cause cumulative and irreversible nervous tissue damage, which eventually
becomes clinically detectable (Pilkington, 2001). Although, this study found a weak

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positive association between cumulative exposure to OPs from sheep dipping and
neurological symptoms, there was a less consistent association with sensory
thresholds and cumulative OP exposure. The study concluded “long term health
effects may occur in at least some sheep dippers exposed to OPs over a working life,
although the mechanisms are unclear” (Pilkington, 2001). Stephens et al. (1995)
concluded that chronic neurological effects had occurred within a group of sheep
dippers studied, but that the effects were subtle in nature and, although identifiable
with sensitive neuropsychological tests, were unlikely to manifest as clinical
symptoms.
London et al. (1998) investigated vibration sense and tremor outcomes after control
for acute exposure and past pesticide poisoning among South African farm workers.
Although the study concluded that the data did not demonstrate consistent adverse
effects of long-term OP exposure it found that current employment as a spray
applicator appeared to be associated with an increase in neurological symptoms and
a non-significant increase in the prevalence of clinical neurological deficits.
Engel et el (1998) set out to determine whether peripheral neurophysiological
abnormalities were present in farm workers (apple tree thinners) after one season of
low-level OP pesticide exposure. Their results indicated that the low-level exposure,
experienced during one growing season, was not related to detectable impairment in
peripheral nerve conduction or neuromuscular function. The study also concluded
that no dose-response relationship was present based on time spent working in OP-
sprayed orchards.
One study has suggested that the health effects reported from low-dose, long-term
exposure may be due to the interaction of OPs with other brain proteins rather than
AChE (Ray and Richards, 2001). “It can be expected that any serine hydrolase can
be a potential target protein for the action of OP esters by virtue of its nucleophilic
serine, the essential feature for protein-OP covalent reaction” (Ray and Richards,
2001).

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These studies of low-level, chronic neurological symptoms, have found it difficult to
eliminate all subjects with a past acute pesticide-poisoning episode, especially
considering that they rely on participant recall of previous exposures. These studies
have also had difficulty quantifying or defining past exposure to OP pesticides. The
lack of standardisation in the protocols used in these studies to assess
neurobehavioral functioning make it difficult to directly compare findings (Colosio
et al., 2003).
In summary, there appears to be a link between an acute poisoning episode and the
subsequent development of chronic neurological health effects. There is a growing
body of knowledge linking low-level exposure to OP pesticides with subtle
neurological health effects. However, there are also a number of studies that show
no evidence of long-term neurological damage after chronic low-level exposure to
OPs. Due to the inconsistency of findings further research is required in this area.
Future research will need to employ standardised protocols for testing neurological
functioning.
2.1.4.4 Other non-acetylcholinesterase related health effects of OP exposure
Several researchers have attempted to investigate health effects from exposure to OP
pesticides other than those related to AChE inhibition (Padungtod, 1998, Compston,
1999, Queiroz et al., 1999, Crumpton, 2000, Padungtod, 2000, Giri et al., 2002).
Chlorpyrifos has been shown to interfere with brain development, “in part by
multiple alterations in the activity of transcription factors involved in the basic
machinery of cell replication and differentiation” (Crumpton, 2000). Occupational
exposure to methamidophos and ethyl parathion has been shown to have a
moderately adverse effect on semen quality in 32 exposed Chinese workers
(Padungtod, 2000). Human sperm chromatin has been shown to be sensitive to OP
exposure; changes in chromatin may contribute to adverse reproductive outcomes
(Sanchez-Pena et al., 2004). Occupational OP exposure has been shown to have a
small effect on male reproductive hormones (Padungtod, 1998). A study involving

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40 workers occupationally exposed to carbamates and OPs showed that neutrophil
function may be affected in males exposed to levels below that required to inhibit
cholinesterase activity (Queiroz et al., 1999). Compston et al. (1999), found reduced
bone formation, at the tissue and cellular levels, after chronic exposure to OPs
during sheep dipping and suggested that AChE is present in bone matrix and may
therefore play a role in bone formation (Compston, 1999). Although there is some
evidence that a few OPs may be genotoxic (Saxena et al., 1997, Lieberman, 1998,
Hatjian et al., 2000, Giri et al., 2002), there is a general lack of research in the area
of OP genotoxicity.
2.2 Biological Monitoring of OP Exposure
Biological monitoring of OP exposure is the best method of evaluating occupational
risk because it takes into account all routes of exposure. Other monitoring methods
such as air sampling (Kennedy, 1994) or dermal sampling (Soutar, 2000, Kromhout,
2001) only assess individual routes of exposure. There are two main types of
biological monitoring used to evaluate OP exposure: blood cholinesterase testing,
and urine metabolite analysis. Apart from blood and urine sampling, there are some
other available human specimens that can be tested, including postpartum
meconium, saliva, and amnionic fluid however, these are not commonly used and
will not be discussed in this thesis. Also, the parent OP compound is sometimes
monitored in blood or blood products (e.g. serum, plasma) (Lewalter and Leng, 1999
); however, OPs are broken down readily and this type of sampling would need to be
completed shortly after exposure. For example, the attempts of Morgan et al. (1977)
to find parathion methyl in blood 15 min – 2h after ingestion of a 4 mg dose were
unsuccessful.
2.2.1 Blood cholinesterase monitoring
Blood cholinesterase level monitoring has been used for more than 40 years to
monitor exposure to OPs (Oglobline, 1999) and is also a mandatory component of

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health surveillance in Queensland legislation2
. Blood cholinesterase monitoring
involves taking a whole blood sample and measuring the plasma and red blood cell
(RBC) cholinesterase activity. Blood testing is in fact biological-effect monitoring
rather than biological-exposure monitoring because it measures the effect of OP
pesticides on the body, rather than the actual amount of exposure. There are two
main laboratory methods for the analysis of blood samples, the Michel and Ellman
methods. The Ellman method of analysis is prescribed by Queensland legislation and
will be discussed here; no discussion of the Michel method is provided.
Since 1961, when Ellman et al. (Ellman et al., 1961), published a spectrophotometric
method that measured the activity of cholinesterases on ACh or butrylthiocholine as
substrates, this method has been commonly used throughout the world to monitor
exposure to OPs and to diagnose OP-poisoning cases. An automated version of the
Ellman method has been developed which separates the erythrocytes from the
thiocholine prior to the reaction (Coye, 1986a). The Ellman method is rapid,
convenient and dependable for screening and research purposes (Coye, 1986a). The
only equipment required is a standard spectrophotometer.
Generally, the acute cholinergic effects of severe OP poisoning correlate well with
blood cholinesterase inhibition; (Coye, 1986a) however, chronic moderate exposure
results in a cumulative inhibition of blood cholinesterase levels (Coye, 1986a). The
appearance of symptoms depends more on how quickly the levels drop, rather than
on the actual level reached. Workers may experience a drop of 70-80% of their
baseline after weeks of low-level exposure and never develop symptoms.
Conversely, a worker without previous exposure to OPs may develop symptoms
2
Section 109 of the Workplace Health and Safety Regulation 1997 requires health surveillance for schedule 6 chemicals if a
risk assessment indicates exposure is ‘significant’.

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after sudden exposure and a rapid drop of only 30% in cholinesterase activity or less
(Coye, 1986a). The inhibition of RBC cholinesterase is generally a better indicator
of biologic effect than plasma cholinesterase, because it is analogous to the enzyme
found in nervous system tissue (Coye, 1986a). Different OPs will preferentially
affect RBC or plasma cholinesterase levels; consequently, exposure to different OPs
may have a synergistic effect. Field-based research has failed to show a correlation
between the presence or severity of symptoms from low-level OP exposure with
blood cholinesterase activity (Levin and Rodnitzky, 1976, Quinones et al., 1976,
Brown et al., 1978, Fillmore, 1993, Cornell University, 2005).
Baseline cholinesterase activity should not be assessed until the worker has been free
from exposure to OPs for at least 30 days (Coye, 1986a). A minimum of two pre-
exposure tests should be conducted at least 3 days apart but not more than 14 days
apart. If the two tests differ by more than 20%, a third sample should be taken. The
average of the two to three tests will give the baseline level. Blood cholinesterase
measurements including whole blood and test kit sampling methods have been used
extensively in workplace occupational monitoring and occupational epidemiological
studies (Ames et al., 1989, Abiola et al., 1991, McConnell, 1992, Fillmore, 1993,
Kocabiyik et al., 1995, Azizi et al., 1998, Tinoco-Ojanguren, 1998, Barnes, 1999,
van der Merwe, 1999, Srivastava, 2000, Dyer, 2001, Prakasam. A., 2001, He et al.,
2002, Zeren et al., 2002).
Fillmore (1993) conducted a retrospective cohort study, which drew on data from
the records of a private physician in California who performed biological monitoring
for rural workers exposed to OPs. The blood samples were analysed using the
Ellman method. Ongoing monitoring was conducted for 79 employees who had
baselines established between 1989 and 1990. During this time only one worker had
RBC cholinesterase levels below 70% of his baseline (i.e. a 30% drop); however, 24
of the monitored workers had to be removed from their duties due to plasma
cholinesterase levels below 60% of their baselines. Five of the 24 workers had to be
removed twice during the same year resulting in a total of 29 worker removals.

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Seventeen of these were for activity levels below 50% of their plasma baseline (i.e.,
toxic levels by WHO standards). Only two of the 17 cases with ‘toxic levels’
reported symptoms of cholinesterase exposure. However, some workers with non-
‘toxic level’ reductions in plasma activity reported symptoms (Fillmore, 1993). One
of the major problems with blood cholinesterase monitoring is that the interpretation
of the results relies heavily on the baseline levels calculated for the worker. If the
baseline levels are calculated at a time when the worker has lower levels than normal
(due to OP exposure or other non-related reasons), the subsequent monitoring may
be wrongly interpreted as being safe to return to work.
There are numerous other problems with blood cholinesterase monitoring including:
• the baseline level of cholinesterase activity must be calculated prior to exposure
to OP pesticides and this may be difficult if work with OPs does not allow a
sufficient period of non-exposure;
• normal workers not exposed to OP pesticides may unpredictably show a large
variation in blood cholinesterase activity from one sample to the next (Coye,
1986a), therefore it is difficult to establish an accurate baseline level;
• plasma cholinesterase levels are sex- and age-dependent (Coye, 1986a);
• the test can only monitor effects from moderate to high exposures;
• the test requires a blood sample to be taken, which is invasive, and a trained
person to take the sample; and
• different laboratories may use different methods and the levels reported may
therefore vary from one laboratory to the next.
2.2.2 Urine DAP metabolite monitoring
Once an OP has been absorbed into the body, hepatic esterases rapidly hydrolyse OP
esters yielding alkyl phosphates and phenols, which have little toxicologic activity
and are rapidly excreted (LaDou, 1997). There are six main dialkyl phosphate (DAP)
metabolites that can be measured in the urine of exposed workers [dimethyl
phosphate (DMP), dimethyl thiophosphate (DMTP), dimethyl dithiophosphate

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(DMDTP), diethyl phosphate (DEP), diethyl thiophosphate (DETP), and diethyl
dithiophosphate (DEDTP)]. Figure 2.3 presents the chemical structure of the six
main DAP metabolites. Approximately 70% of the OPs registered for use in
Australia will produce one or more of the six common degradation products of OP
pesticides. Table 2.2 provides details of the metabolites for some commonly used
OP pesticides.
Figure 2.3 Structure of the six main DAP metabolites
Source: D. Gompertz in (WHO, 1996), page 241.
Table 2.2 Common OPs and their DAP metabolites

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Source: (Wessels et al., 2003)
Urinary DAP metabolite testing has been available for more than 30 years. Until the
early 1990s, however urine DAP testing was not used very extensively because of
problems with complex sample preparation, the use of carcinogenic reagents, and/or
the inability of the various forms of the test to detect all six of the major metabolites
of OP pesticides. Since then, Nutley & Cocker (1993), Aprea et al. (Aprea, 1996),
Moate et al. (1999) and, in Australia, Oglobline et al. (2001) have reported on new
methods of urine sample analysis that do not have the aforementioned problems and
urine analysis has been used more extensively. At least seven laboratories in North
America and Europe routinely analyse DAPs in urine for epidemiologic studies
(Wessels et al., 2003).
The urine metabolite test (test for presence of the six common DAP metabolites)
provides information about exposure to OP pesticides as a class. Although it is
known which of the six DAP metabolites are formed by an OP, it is not possible to
say exactly which OP a person has been exposed to based on the results of the
metabolite test alone. Other exposure information is required. The presence of one or
more of the main metabolites in urine may also be due to exposure to environmental
DAPs, that is exposure to the breakdown products of OP pesticides in the
environment (Barr et al., 2004). Although only limited published studies have
documented the environmental presence or biologic absorption of environmental
DAPs or their contribution to urinary DAP concentrations in humans, researchers
widely recognise their potential contributions to urinary levels largely based on data
demonstrating similar environmental exposures, absorption, and excretion for more
selective OP metabolites (Barr et al., 2004). In the US in 2005, Lu et al. investigated
whether DAPs were present as a result of OP pesticide degradation in fresh

Risk Assessment
25
conventional and organic fruit juices. Results revealed DAPs present in both forms
of juices though original levels were higher in conventional than in organic juices.
The study found higher amounts of DMTP and DETP than other DAP metabolites in
the juices. OP pesticides can degrade in the environment or be metabolised by
plants; Lu et al. (2005) attribute the likely cause of OP pesticide degradation in juice
to simple hydrolysis. DAPs found in urine may also be metabolites of some
industrial chemicals and pharmaceuticals, but it is generally believed that most
DAPs result from exposure to OP pesticides (Wessels et al., 2003). Levels of DMP
and DEP metabolites in urine indicate exposure to OPs which could have potentially
inhibited AChE, whereas levels of DMTP, DMDTP, DETP and DEDTP indicate
that the OP has been detoxified protecting against any internal level of active OP
(Cocker et al., 2002).
Urinary metabolites may be detected for several days after exposure and in
association with lower levels of exposure than those required for cholinesterase
inhibition (Coye, 1986b). Sequential urine samples collected during a period of OP
application and until 24 hours after the end of the sampling day is the optimal
method of urine sample collection (Coye, 1986b). However, this method is often not
practical in the field as 24-hour urine sample collection is difficult to impose on
participants and compliance is hard to obtain. Spot urine samples of approximately
50 mL can be collected in plastic containers without the addition of any preservative
(Oglobline, 1999). Samples should be kept cool and, if delays are expected in
transporting the samples to the laboratory, they should be frozen (Oglobline, 1999).
Several epidemiological and scientific studies have utilised urine metabolite analysis
and recommended sampling periods based on observed metabolite excretion rates.
Griffin et al. (1999) observed that the best time to collect biological samples was
before the start of the shift the day following dermal exposure. Based on the
elimination kinetics observed for diazinon (elimination half-lives of 2 and 9h for oral
and dermal doses, respectively), Garfitt et al. (2002) recommended occupational
exposure samples be collected at the end of a shift. In a comprehensive study of
peach orchard workers involving 24-hour urine collection, it was found that the

Risk Assessment
26
excretory peaks occurred during the night following exposure, i.e. during the
subsequent 15 hours (Aprea et al., 1994). Nutley and Cocker (1993) collected urine
samples for 8-hours following OP exposure and suggested that the peak excretion of
metabolites occurs 8-16 hours after exposure. Different OP pesticides have been
reported to have different metabolic dispositions; for example, parathion methyl was
shown to metabolise and completely excrete in urine as DMP, hours faster than ethyl
parathion metabolised and completely excreted in urine as DEP (Morgan, 1977).
Given the potential for different metabolic rates based on type of OP pesticide and
route of exposure, occupational exposure assessment would need to include samples
collected at the end of the shift and before the start of work the following day.
To date only two Australian studies have used urine metabolite analysis; one
investigated chlorpyrifos exposure among domestic pest control operators (Cattani,
2001) and the other measured urine metabolite levels in non-exposed members of
the public (Oglobline, 2001). Numerous studies investigating occupational OP
exposure in the agricultural industry using urine metabolite testing have been
conducted overseas (Shafik et al., 1973, Duncan and Griffith, 1985, Kaloianova et
al., 1989, Drevenkar et al., 1991, Nutley and Cocker, 1993, Aprea et al., 1994,
McCurdy, 1994, Takamiya, 1994, Sanderson et al., 1995, Stokes et al., 1995,
Stephens et al., 1996, Azaroff, 1999, Simcox et al., 1999). Some of these studies
have completed both urine and blood testing and have concluded that urinary
metabolite testing was the most sensitive indicator of recent exposure (e.g. Nutley &
Cocker, 1993 and McCurdy et al. 1994).
There has been extensive research conducted on environmental exposure to OP
pesticides (Aprea et al., 1996, Heudorf and Angerer, 2001, Castorina et al., 2003,
Barr et al., 2004), especially children’s exposure (Eskenazi, 1999, Aprea, 2000,
Adgate et al., 2001, Lu et al., 2001). Most studies involving children have reported
that their exposures were higher than those of adults in the same population (Aprea
et al., 1996, Aprea, 2000, Barr et al., 2004). Reasons for this have included the
influence of creatinine correction, because creatinine concentrations are influenced

Risk Assessment
27
by muscle mass, and the fact that children have greater potential for exposure due to
their eating and playing habits. Environmental exposure studies, especially those
completed in the last few years, have employed extremely sensitive techniques for
sample analysis and are able to report DAP levels well below those possible via the
technique used in this thesis. Appendix 1 summarises the methods and results from
studies that have used alkyl phosphate metabolite testing.
Several occupational and environmental studies that have tested for all six DAP
metabolites have reported that DMTP was the metabolite most often detected or was
detected in the highest concentrations (Aprea et al., 1996, Aprea, 2000, Mills, 2001,
Castorina et al., 2003, Barr et al., 2004). In most of these studies, specific OP
exposure information was unavailable, but the DMTP finding would indicate higher
exposures to dimethyl OPs (e.g. dimethoate, parathion methyl and azinphos-methyl)
as dimethyl OPs produce only dimethyl metabolites (DMP, DMTP, DMDTP) just as
diethyl OPs produce only diethyl metabolites (DEP, DETP, DEDTP).
Scientists from the Health and Safety Laboratory, Sheffield UK, completed a wide
range of occupational, environmental and human volunteer studies using a urine
DAP metabolite test developed in their laboratory. Cocker et al. (2002) published a
review of the laboratory’s work in this area covering a 10-year period. They report
that in non-occupationally exposed people, 90% of total urinary DAPs are <50
μmol/mol creatinine and 95% are <72 μmol/mol creatinine. In occupationally
exposed people, 90% of the total urinary DAPs are <77 μmol/mol creatinine and
95% are <122 μmol/mol creatinine. In the human volunteer studies completed, 1 mg
oral doses of chlorpyrifos, diazinon and propetamphos were administered yielding
mean peak values of 160, 750 and 404 μmol/mol creatinine, respectively. These
mean peak values were not associated with any reduction in blood cholinesterase
activity. During the 10 years the total number of occupational exposure samples was
917. The maximum occupational value found was 915 μmol/mol creatinine and the
mean and median were 33 and 15 μmol/mol creatinine, respectively. The group with

Risk Assessment
28
the highest levels of DAPs were the formulators with 90% of their results being
<188 μmol/mol creatinine. The authors commented that “the levels of OP
metabolites seen in urine from workers potentially exposed to OPs are generally low
and unlikely to cause significant reduction in blood cholinesterase activity” (Cocker
et al., 2002).
The largest public health study conducted thus far, involving analysis of DAP
metabolite levels, was completed in the U.S. as part of their National Health and
Nutrition Examination Survey (NHANES). The Centres for Disease Control and
Prevention (CDC) conducted the research in 1999 and 2000 in 26 locations
throughout the U.S. The DAP metabolite measurements were completed on a subset
of the 9,282 persons involved in the main study. Over the two years 1,949 valid
samples were analysed for DAP metabolite levels (Barr et al., 2004). The metabolite
DEP was detected with the highest frequency in 70% of the samples tested;
however, DMTP was detected in the highest concentrations. The geometric mean for
all DAPs and all samples was 0.0763 µmol/L (range 0.065-0.0896), the 25th
, 50th
and
90th
percentile values were 0.0311µmol/L, 0.0817µmol/L and 0.399µmol/L,
respectively. The concentrations of DAP metabolites found in the U.S. population
were lower than those reported elsewhere in the literature although peak
concentrations observed were similar to other studies. The research found that
children sampled (6-11 years) had statistically significantly (p < 0.007) higher
concentrations of DAPs than adults and sometimes adolescents, even after correcting
for all covariates including creatinine. Adolescents also had higher levels than adults
but not significantly higher. The authors suggest that differences in children’s
samples are likely because of increased opportunities for exposure based on their
dietary and physical behaviours (Barr et al., 2004). However, it is not known what
health impacts, if any, are associated with the levels of DAP metabolites reported in
the U.S study or any other as insufficient data exists on the link between DAP levels
and health effects.

Risk Assessment
29
Despite the large number of international studies that have used urine DAP
metabolite monitoring to assess exposures to OPs, there are currently no Australian
or international exposure guidelines or biological exposure index (BEI) for urinary
DAP metabolites, making it complicated to interpret the results in terms of health
risks. The development of a BEI requires better correlation between metabolite
levels and observed short- and long-term health effects as well as improved
understanding of the relationship between exposure and excretion of metabolites. As
remarked by Robert Krieger, (2002) an experienced toxicologist “it is remarkable
that Biological Exposure Indices (BEI) based upon pesticide biomarkers have not
been used to assess the significance of pesticide exposures of humans…The BEI
concept could be implemented and evaluated using organophosphate pesticides”.
Krieger also commented that more specific biological exposure data will improve
the quality of risk assessment for handlers and harvesters, but the data will probably
not impact the pesticide risk management process unless it is coupled with medical
evaluation of worker health. Therefore, it is vital that more research is conducted
which involves urine DAP metabolite monitoring of workers and medical
assessment to link exposure levels with health outcomes.
Another issue with the currently available urine DAP metabolite data is that it is
reported in differing units making it difficult to compare the results across studies.
The occupational studies have generally been completed with specific populations
and small sample sizes ranging from 1 to 500, with typical sizes being around 20 to
150. Non-occupational exposure studies generally employ more participants, with
two studies having over 1000; a German study of residents in former US military
housing with 1146 participants (Heudorf and Angerer, 2001) and the U.S. NHANES
study with 1949 samples (Barr et al, 2004). The studies all use different sampling
strategies and differing sample analysis techniques which impact on the
comparability of the data. In addition to these issues, there are confounding factors
associated with the presence of environmental DAPs that contribute to the
difficulties reported in linking exposures with biological monitoring results. In
summary more research is required to enhance and better utilize the existing data.

Risk Assessment
30
2.2.3 Correlation between blood cholinesterase level and DAP
metabolites
Several occupational exposure studies that examined both blood cholinesterase and
urine DAP metabolite levels reported no correlation between the two measurements
(Drevenkar et al., 1991) or were unable to investigate a correlation because
cholinesterase levels were not depressed (Aprea et al., 1994). However, two
occupational exposure studies have reported a good correlation between blood
cholinesterase and urinary DAP levels (Nutley and Cocker, 1993, McCurdy, 1994).
Given the sensitivity of the urine DAP test, it is not surprising that authors report
detectable levels of DAPs but no drop in cholinesterase levels. The authors who
reported a correlation between the two tests observed the relationship due to high
urinary DAP levels in test subjects. OPs rapidly metabolise and are excreted in urine
over a period of hours to days, however, cholinesterase levels can remain depressed
for up to 60 days and can be depressed further over a series of exposures to OPs
during this time. Therefore, urine levels are a good short-term indicator of exposure.
Cholinesterase levels can be an indicator of short-term exposure (e.g. serum
cholinesterase levels are a good indicator of the previous 72-hours), but are usually
an indicator of slightly longer-term exposure (e.g. RBC levels give an interpretation
of the previous 2 months) (van der Merwe, 1999).
Studies involving OP-pesticide-poisoned indivuduals in hospital care have reported
a poor correlation between blood cholinesterase levels and urine metabolite levels
(Vasilic et al., 1992, Vasilic, 1993, Vasilic et al., 1999). This may be partially due to
a lack of baseline information for poisoned patients. Further research is required in
this area and would be most useful with subjects who are likely to have high
occupational exposure to OPs and have an established baseline, for example
formulation plant workers.

Risk Assessment
31
2.3 Studies Investigating Farmers’ Self-Surveillance of
Pesticide-Related Health Effects and Poisonings
The prevalence of acute and particularly chronic pesticide-related health effects in
Australia and internationally is unknown due to inadequate surveillance systems;
consequently several researchers have attempted to obtain data on the prevalence of
pesticide-related health effects via surveys of self-reported symptoms among
farming populations (Kishi, 1995, Perry and Layde, 1998, Murphy et al., 2002,
Strong et al., 2004). In an Indonesian study, 21% of spray operations resulted in
three or more neurobehavioural, respiratory, and intestinal signs and symptoms
(Kishi, 1995). The number of spray operations per week, the use of hazardous
pesticides, and skin and clothes being wetted with the spray solution were
significantly and independently associated with the number of signs and symptoms.
A Northern Vietnamese research project, conducted over a 12-month period, aimed
to investigate a self-surveillance program for farmers (Murphy et al., 2002). The
participants (50 farmers and 50 controls) were asked to record any adverse health
effects and the type of pesticide used after every spraying session. Of the 1,798
recorded spray operations, 8% were asymptomatic, 61% were associated with vague
ill-defined or localised minor effects, and 31% were accompanied by a least one or
more clearly defined sign or symptom of poisoning. The most common complaint
was headache, which was associated with 51% of the spray operations (Murphy et
al., 2002).
Very few OP exposure studies have investigated the relationship between biological
monitoring results (blood and/or urine) and self-reported acute and chronic health
symptoms. A study conducted in eastern Washington State, USA, with 211 farm
workers found that the following health symptoms were most commonly reported:
headaches (50%); burning eyes (39%); pain in muscles, joints or bones (35%); a rash
or itchy skin (25%); and blurred vision (23%) (Strong et al., 2004). The researchers
collected urine samples to test for DAP levels. No significant associations were

Risk Assessment
32
found between reported health symptoms and the proportion of detectable urinary
metabolites. The researchers concluded that although certain self-reported symptoms
in farm workers may be associated with indicators of exposure to pesticides,
longitudinal studies with more precise health symptom data are needed to explore
the relationship further.
2.4 Farmers’ Knowledge, Beliefs, Attitudes, Behaviours
and Risk Perception relating to Safe Pesticide
Handling Practices
Use of OP pesticides can result in both acute short-term and chronic long-term
health effects. It is important therefore to employ good health and safety practices in
order to minimise exposure to OP pesticides. It is well recognised and widely taught
in pesticide use training courses that personal protective equipment (PPE) such as a
mask/respirator, gloves, overalls, eye protection, a hat and boots should be employed
to reduce exposure. Farmers using tractors or trucks to apply pesticides would also
benefit from enclosed cabs with air-filtration systems, which can aid in the reduction
of both dermal and inhalation exposure during application. As mixing and loading
involve contact with the pesticide concentrate these tasks present the greatest
potential for exposure. Good hygiene practices are also important in preventing
exposure (e.g. washing after pesticide use, washing hands before eating or drinking,
appropriate clothes washing practices, etc.). Despite the health risks, many farmers
still do not use all (or any) PPE when mixing, loading and applying pesticides.
Numerous articles report poor safety behaviours and, in particular, poor use of PPE
(Perry and Layde, 1998, Gomes et al., 1999, Carpenter et al., 2002, Perry, 2002,
Yassin et al., 2002). Australian and international studies have attempted to obtain
information on the barriers to the use of PPE and other safe behaviours. The key
concepts researched in this area are knowledge of, and attitudes and beliefs
surrounding safe pesticide-handling practices.

Risk Assessment
33
In an Australian study, involving interviews with key informants from the farmer
training and education field, several themes emerged regarding possible reasons for
farmers’ reluctance to adopt safe pesticide-handling behaviours (Cassell and Day,
1998). The first referred to a low perception of personal risk of farm accidents, the
‘it won’t happen to me’ theory. One informant stated that “Farmers…regard
themselves as indestructible, they think they can do anything and get away with it”.
Another theme involved the machismo attitude of farmers with an informant stating
“….only bloody softies go and get the overalls and put the mask on to use
chemicals”. Time constraints also emerged as a barrier to safety: “They’re concerned
about safety but when it comes to factoring it into a task….they think about
efficiency rather than risk” (Cassell and Day, 1998). Uncertain economic conditions,
particularly due to drought, impact on farmers’ ability to maintain and replace
outdated farm machinery and equipment, to employ labour and to outlay direct costs
to improve safety or purchase protective equipment (Cassell and Day, 1998). Poor
design of equipment and PPE also impact on farmers’ use of safety items; for
example the suitability of disposable overalls and other PPE items is questioned in
Australia’s hot climate. Similarly, overseas research in a tropical and semi-desert
environment found that farmers viewed PPE as ‘non-essential and cumbersome’
(Gomes et al., 1999).
In an Australian qualitative study, focus groups of farmers discussed their
perceptions of health and safety risks: “while there was a general agreement that
there had been an increase in the use of protective clothing compared to twenty years
ago, it appeared that group members preferred to use alternative methods of
avoiding contact with chemicals” (Sandall, 2000). Issues with the use of PPE raised
by the focus group participants included: other people believing you were going
‘over the top’ if you used PPE; protective clothing being hot and uncomfortable; and
PPE being impractical. The majority of participants concurred that they were
generally uncertain about how safe chemicals really are, even when used according
to instructions (Sandall, 2000).

Risk Assessment
34
Age has been related to the level of knowledge and safety behaviours, with younger
farmers exhibiting a higher level of knowledge and better practices. Resistance to
adopting safer work systems and practices was reported to be strong among older
Australian farmers on small-to-medium-sized farms (Cassell and Day, 1998). A
study of New York farmers found that substitutions with less dangerous chemicals
were more likely to be reported by younger owner/operators than older farmers and
that being younger and educational level (at least high school) were associated with
the belief that PPE is useful (Hwang et al., 2000). A longitudinal study of Pilipino
farmers’ behaviours and belief systems with regards to the purchasing and use of
PPE found that younger farmers working on larger farm areas were more willing to
pay for masks and gloves (Palis, 2006).
It is generally believed that increasing farmers’ knowledge through education and
training regarding the health effects from exposure to pesticides will improve their
safety-related behaviours. This belief is based on the assumption that, given
appropriate education, farmers will change their behaviours. However, there is a
growing body of evidence that suggests that farmers are at least generally aware of
the health dangers of pesticides and that improvements in knowledge do not
necessarily correlate to actual positive behaviour changes (Cassell and Day, 1998,
Elmore, 2001, Kishi, 2002). For example, pesticide research in the Gaza Strip
showed that despite high levels of knowledge on health impacts of pesticides and
correct PPE to be used during application, the actual use of protective measures was
poor (Yassin et al., 2002). Reasons for non-use suggested by the authors included
carelessness, discomfort, cost, or unavailability of protective devices, however these
factors were not investigated further (Yassin et al., 2002). The researchers also
reported that a high percentage of the farmers believed that their bodies could
develop a resistance against pesticides and that such an attitude could contribute to
carelessness with pesticide use (Yassin et al., 2002). It appears that knowledge of
safety measures and health effects alone is insufficient to ensure adoption of safe
practices.

Risk Assessment
35
Risk perception - influenced by experience of health problems and / or a belief in
one’s susceptibility to disease from pesticides - seems to be strongly associated with
heightened awareness of the seriousness of effects from pesticide application and
improved safety behaviours (Perry, 1998, Lichtenberg, 1999, Carpenter et al., 2002,
Schenker et al., 2002). In a study of Irish farmers, researchers found that though
there was a high level of awareness of most hazards associated with the farming
industry, many farmers did not see themselves as personally susceptible to risk and
this impacted on their willingness to implement control measures (Hope, 1999).
According to the Health Belief Model, persons must perceive themselves susceptible
to risk in order to take positive action:“This relationship is modified by self-efficacy,
recognizing one’s ability to control exposure to harm, and cues to action, such as
knowledge and training.” (Arcury, 2002). As stated, knowledge alone, through
education and training, is not responsible for causing behavioural change; however,
for education to be successful in eliciting behavioural change Arcury et al, suggest
that it must address farmworkers’ control of pesticide safety. They suggest that
control has two dimensions: content and process. “The control content of pesticide
safety education means that farmworkers should not only be told what they must do
to reduce their exposure to pesticides, but why and how these behaviours will reduce
their exposure” (Arcury, 2002).
Some research does support the theory that higher levels of knowledge influence
behaviour. Perry et al (2000) reported that confidence to engage in a protective
behaviour was influenced by overall knowledge about safety hazards. Coronado et
al. (2004) investigated pesticide take-home patterns in farm workers in Washington
State via the analysis of house and vehicle dust samples and farmer and child urine
DAP levels. They found that dust and urine samples from pesticide mixers, loaders
and applicators were less likely to contain azinphos-methyl and its metabolites,
respectively, than other farm workers who performed tasks like thinning. The
authors speculated that the training of mixers, loaders and applicators in pesticide

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