Organophosphate Pesticide Exposure in ... - Agrifutures Australia€¦ · Growers (QFVG) and the Aerial Agricultural Association of Australia (AAAA); their assistance was vital in

Organophosphate Pesticide Exposure in Agricultural

Workers Human exposure and risk assessment

By Kelly Johnstone, Michael Capra, Beth Newman

September 2007

RIRDC Publication No 07/154 RIRDC Project No QUT-5A

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© 2007 Rural Industries Research and Development Corporation. All rights reserved. ISBN 1 74151 550 5 ISSN 1440-6845 Organophosphate Pesticide Exposure in Agricultural Workers: Human exposure and risk assessment – Report Publication No. 07/154 Project No. QUT-5A The information contained in this publication is intended for general use to assist public knowledge and discussion and to help improve the development of sustainable regions. You must not rely on any information contained in this publication without taking specialist advice relevant to your particular circumstances.

While reasonable care has been taken in preparing this publication to ensure that information is true and correct, the Commonwealth of Australia gives no assurance as to the accuracy of any information in this publication.

The Commonwealth of Australia, the Rural Industries Research and Development Corporation (RIRDC), the authors or contributors expressly disclaim, to the maximum extent permitted by law, all responsibility and liability to any person, arising directly or indirectly from any act or omission, or for any consequences of any such act or omission, made in reliance on the contents of this publication, whether or not caused by any negligence on the part of the Commonwealth of Australia, RIRDC, the authors or contributors.

The Commonwealth of Australia does not necessarily endorse the views in this publication.

This publication is copyright. Apart from any use as permitted under the Copyright Act 1968, all other rights are reserved. However, wide dissemination is encouraged. Requests and inquiries concerning reproduction and rights should be addressed to the RIRDC Publications Manager on phone 02 6271 4165

Researcher Contact Details Professor Mike Capra Director WorkCover NSW Research Centre of Excellence School of Health Sciences Faculty of Health University of Newcastle PO Box127 Brush Rd, Ourimbah, NSW 2258 Phone: 02 4348 4021 Fax: 02 4348 4013 Email: [email protected]

In submitting this report, the researcher has agreed to RIRDC publishing this material in its edited form. RIRDC Contact Details Rural Industries Research and Development Corporation Level 2, 15 National Circuit BARTON ACT 2600 PO Box 4776 KINGSTON ACT 2604 Phone: 02 6271 4100 Fax: 02 6271 4199 Email: [email protected]. Web: http://www.rirdc.gov.au Published in September 2007

mailto:[email protected]

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Foreword

Various sectors of the Australian agricultural industry work with organophosphate (OP) pesticides. Exposure to OPs can result in both acute and chronic health effects. Pesticide exposure related illness has both economic and social affects for the ill farmers, their families and the rural community they support. It is important that agricultural workers be able to assess and manage their exposure to OP pesticides. The results of this research project will benefit farmers by providing them with a guide to completing an assessment of their exposure to OP pesticides; thereby allowing farmers to better manage their exposure. This publication reports on the findings of a research project aimed at investigating OP pesticide exposure and assessing the feasibility of using urine OP metabolite testing as a risk assessment tool for agricultural and related industry workers exposed to OP pesticides. The research method involved a cross-sectional study design with three exposure groups (fruit and vegetable farmers, agricultural pilots and their ground crew, and formulators) and a control group. Data was collected in Southern Queensland and Northern NSW, via interviewer- and self-administered questionnaires, and the collection of biological samples. The study found that workers with prolonged exposure to OP pesticides over several hours and consecutive days had the greatest potential to be at risk of acquiring pesticide exposure related illness. Fruit and vegetable farmers whose typical pattern of use was short (less than hour), infrequent and involved boom-type application methods had limited potential exposures to OP pesticides. The results of this study indicate that dietary and other environmental exposures to the parent compound, as well as to OP metabolites themselves, may contribute substantially to urine metabolite levels. The urine OP metabolite test was found to be a sensitive indicator of potential exposure to OP pesticides. Use of the urine metabolite test would be beneficial to farmers during the risk assessment process. Information from this report has been used to produce a “Users Guide to Assessing Exposure to Organophosphate Pesticides for Fruit and Vegetable Growers” (RIRDC publication number 07/155). This Guide is available from RIRDC. This project was funded by the RIRDC managed Joint Research Venture for Farm Health and Safety with the vision of enhancing the well being and productivity in rural industries through improved OHS status of Australian agriculture delivered by the establishment of safe systems of work on farms. The partners in the Joint Venture are:

• Grains Research and Development Corporation • Sugar Research and Development Corporation • Meat and Livestock Australia • Australian Wool Innovation • Cotton Research and Development Corporation • Rural Industries Research and Development Corporation

This report is an addition to RIRDC’s diverse range of over 1600 research publications. Most of our publications are available for viewing, downloading or purchasing online through our website: • downloads at www.rirdc.gov.au/fullreports/index.html • purchases at www.rirdc.gov.au/eshop Peter O’Brien Managing Director Rural Industries Research and Development Corporation

http://www.rirdc.gov.au/fullreports/index.html

http://www.rirdc.gov.au/eshop

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Acknowledgments The authors wish to sincerely thank all the study participants for the valuable time they gave up to be part of this project. Grateful acknowledgment is due to 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. Acknowledgement is also given to the two State Departments – Workplace Health and Safety Queensland and WorkCover NSW – they provided both financial and in-kind support.

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Abbreviations AAAA Aerial Agricultural Association of Australia ACh acetylcholine AChE acetylcholinesterase 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 disorder DAP dialkyl phosphate DMP dimethylphosphate DMTP dimethylthiophosphate DMDTP dimethyldithiophosphate DEP diethylphosphate DETP diethylthiophosphate DEDTP diethyldithiophosphate EVAO estimated value of agricultural output MSDS Material Safety Data Sheet NATA National Association of Testing Authorities ND not detected 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 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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Contents Foreword ............................................................................................................................................... iii Acknowledgments................................................................................................................................. iv Abbreviations......................................................................................................................................... v Executive Summary .............................................................................................................................. x 1. Introduction ....................................................................................................................................... 1

1.1 Background............................................................................................................................ 1 1.1.1 Public Health Significance ................................................................................................ 1

2. Objectives ........................................................................................................................................... 2 3. Literature Review.............................................................................................................................. 3

3.1 OP Pesticides ......................................................................................................................... 3 3.1.1 OP pesticide half-lives....................................................................................................... 3 3.1.2 Routes of Exposure............................................................................................................ 4 3.1.3 Health effects from exposure to OPs ................................................................................. 4

3.2 Biological Monitoring of OP Exposure ................................................................................. 8 3.2.1 Blood cholinesterase monitoring ....................................................................................... 9 3.2.2 Urine DAP metabolite monitoring................................................................................... 10 3.2.3 Correlation between blood cholinesterase level and DAP metabolites ........................... 13

3.3 Studies Investigating Farmers’ Self-Surveillance of Pesticide-Related Health Effects and Poisonings ............................................................................................. 14 3.4 Pesticide Poisoning Incidence Rates for the Agricultural Industry ..................................... 14 3.5 Current Health and Safety Pesticide Legislation in Queensland ......................................... 15 3.6 Conclusion ........................................................................................................................... 16

4. Methodology .................................................................................................................................... 17 4.1 Project Overview ................................................................................................................. 17 4.2 OP Pesticide Self-Administered Risk Factor Questionnaire................................................ 17

4.2.1 Fruit and vegetable farmers ............................................................................................. 18 4.2.2 Pilots and mixer/loaders .................................................................................................. 18 4.2.3 Formulator plant staff ...................................................................................................... 19 4.2.4 Toowoomba control group .............................................................................................. 20

4.3 Biological Sample Collection .............................................................................................. 21 4.3.1 Urine sample collection and transport ............................................................................. 21 4.3.2 Justification for number of urine samples and timing of collection ................................ 22 4.3.3 Urine sample analysis and quality control....................................................................... 22 4.3.4 Delivery of biological sample results to participants....................................................... 23 4.3.5 Blood sample collection and transport ............................................................................ 23 4.3.6 Blood sample analysis and quality control ...................................................................... 23

4.4 Statistical Analysis............................................................................................................... 24 5. Fruit and Vegetable Farmers and Pilot/Mixer/Loaders Urine Metabolite Results............... 25

5.1 Fruit and Vegetable Farmers Urine Metabolite Test Results ............................................... 25 5.1.1 OP pesticides sprayed and DAP metabolites................................................................... 28 5.1.2 Relationship between detectable DAP metabolite levels and other measures of exposure....................................................................................................... 29

5.2 Agricultural Pilots and Mixer/Loaders ................................................................................ 34 5.2.1 OP pesticides handled and DAP metabolites................................................................... 39

5.3 Toowoomba Rotary Club Control Group ............................................................................ 42 5.4 Comparison between Urine DAP Metabolite Results for the Three Groups ....................... 45 5.5 Summary of Results ............................................................................................................. 48

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6. Formulator Plant Workers’ Biological Sample Results........................................................... 50 6.1 Formulation Plant Worker Sample ...................................................................................... 50 6.2 Exposed Workers’ Urine DAP Metabolite Results.............................................................. 50 6.3...........................................................................Control Group Urine DAP Metabolite Results........................................................................................................................................................... 58 6.4 Comparison of Urine DAP Metabolite Levels between Formulator Plant Exposed Participants and Controls................................................................................................................... 60 6.5 Blood Cholinesterase Test Results....................................................................................... 60 6.6 Relationship between Urine DAP Metabolite Levels and Blood Cholinesterase Levels..... 62 6.7 Summary of Results ............................................................................................................. 67

7. Discussion..................................................................................................................................... 68 7.1 Summary of Major Research Findings ................................................................................ 68

7.1.1 Fruit and vegetable farmers ............................................................................................. 68 7.1.2 Pilots/mixer/loaders ......................................................................................................... 68 7.1.3 Formulators...................................................................................................................... 69

7.2 Farmers’ OP Pesticide-Handling Practices .......................................................................... 69 7.3 Farmers’ Knowledge and Use of Risk Assessment Techniques .......................................... 70 7.4 Farmers’ Use of PPE and DAP Metabolite Results ............................................................. 72 7.5 Comparison of Biological Sampling Results for the Three Exposed Groups...................... 74 7.6 Environmental Exposures to OPs and the DMTP Metabolite ............................................. 75 7.7 What do the DAP Metabolite Levels Mean in Terms of Health Effects?............................ 76 7.8 How do the Levels Observed Compare with International Research?................................. 77 7.9 Sample Collection Requirements......................................................................................... 78 7.10 Correlations Between Urine DAP Metabolite Levels and Blood Cholinesterase Activities........................................................................................... 79 7.11 Study Limitations................................................................................................................. 79 7.12 Study Validity ...................................................................................................................... 81

8. Conclusion and Recommendations ............................................................................................ 82 8.1 Future Research Directions and Advice to Farmers ............................................................ 83 8.2 Key Recommendations ........................................................................................................ 84

9. References .................................................................................................................................... 85

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List of Tables Table 3.1 Selected OP pesticide half-lives .................................................................................... 4 Table 3.2 Common OPs and their DAP metabolites ................................................................... 11 Table 5.1 Urine dimethyl alkyl phosphate metabolite results (μmol/mol creatinine) ................. 26 Table 5.2 Total dimethyl DAP concentrations for pre- and post-exposure samples ................... 27 Table 5.3 Cross-tabulation between detectable dimethyl DAP metabolites and spraying of

dimethyl DAP metabolites........................................................................................... 29 Table 5.4 Crude analyses of the relationships between exposure, measured as detectable DAP

metabolites, and risk factors related to potential exposure (n=32) .............................. 30 Table 5.5 Crude analyses of the relationships between exposure, measured as detectable DAP

metabolites, and demographic characteristics, knowledge, attitudes and risk perception..................................................................................................................................... 31

Table 5.6 Cross-tabulation for type of exposure (high measured as DAP metabolites over 50 μmol/mol creatinine) and various risk factors ............................................................. 32

Table 5.7 Pilot urine DAP metabolite results – μmol/mol creatinine.......................................... 35 Table 5.8 Mixer/loader urine DAP metabolite results - μmol/mol creatinine ............................. 36 Table 5.9 Cross-tabulation between OP handled during sample collection, prior to sample

collection and type of DAP metabolites detected........................................................ 39 Table 5.9 Cross-tabulation between OP handled during sample collection, prior to sample

collection and type of DAP metabolites detected........................................................ 40 Table 5.10 Crude analysis of the relationship between exposure, measured as detectable DAP

metabolites, and various risk factors (n=18)................................................................ 41 Table 5.11 Crude analysis of the relationship between detectable DAP metabolites (yes/no), and

various environmental risk factors (n=43)................................................................... 43 Table 5.12 Adjusted odds ratios for risk factors showing higher odds of having detectable DMTP

levels............................................................................................................................ 44 Table 5.13 Comparison of farmers, pilot/mixer/loaders and controls pre- and post-exposure DAP

metabolite results ......................................................................................................... 46 Table 6.1 Urine DAP metabolite results for formulator Staff exposed to Rametin (μmol/mol

creatinine) .................................................................................................................... 51 Table 6.2 Formulator plant exposed group DEP metabolite results (μmol/mol creatinine) ........ 52 Table 6.3 Formulator plant exposed group DMTP metabolite results (μmol/mol creatinine)..... 52 Table 6.4 Relationships between exposure, measured as detectable DAP metabolites, and

various occupational risk factors for the exposed group (n=9) ................................... 56 Table 6.5 Relationships between detectable metabolites (yes/no), and various environmental risk

factors for the exposed group (n=9) ............................................................................ 57 Table 6.6 Relationships between detectable metabolites (yes/no), and various environmental risk

factors for the formulator plant control group (n=11) ................................................. 59 Table 6.7 Formulator plant exposed group blood cholinesterase test results .............................. 61 Table 6.8 Formulator plant control group blood cholinesterase test results ................................ 61 Table 6.9 Comparison between exposed and control formulator plant groups’ blood

cholinesterase test results............................................................................................. 62 Table 7.1 Comparison of urine DAP metabolite results .............................................................. 78

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List of Figures Figure 3.1 Generic structure of OP pesticides ................................................................................ 3 Figure 3.2 Structure of the six main DAP metabolites ................................................................. 10 Figure 5.1 Farmers’ urine DMTP concentrations (μmol/mol creatinine) (n=17) ......................... 27 Figure 5.2 Total dimethyl DAP urine concentrations (μmol/L) (n=17)........................................ 28 Figure 5.3 Total dimethyl DAP metabolite results for pilots and mixer/loaders with detectable

levels (µmol/L) (n=13) ................................................................................................ 37 Figure 5.4 Total diethyl DAP metabolite results for pilots and mixer/loaders with detectable

levels (n= 8) (µmol/L) ................................................................................................. 37 Figure 5.5 Pilots and mixer/loader DMTP concentrations (µmol/mol creatinine)........................ 38

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Executive Summary What the report is about This report has been generated as a result of a PhD research project that aimed to investigate organophosphate (OP) pesticide exposure received by fruit and vegetable growers in South East Queensland. It is about the occupational health and safety issues associated with managing OP pesticide exposure within the fruit and vegetable industry and targets the areas of risk assessment and health surveillance of OP pesticides. In particular, the report presents the results of urine metabolite testing of three occupationally exposed groups (fruit and vegetable farmers, pilots and their ground crews and formulators) and two non-occupationally exposed groups. Who is the report targeted at? The report is targeted at those with an interest in the management of occupational exposure to organophosphate pesticides. The findings of the research may be of interest to: • health and safety professionals who work in industries involved with OP pesticide exposures • agricultural employers and workers who use OP pesticides • training organisations that offer health and safety related courses to the agricultural industry • workplace health and safety and other government departments. Background Organophosphate 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, 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.

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Aims/Objectives 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. The specific objectives of the study were: 1. to assess participant fruit and vegetable farmers’ knowledge and use of formal risk assessment

techniques 2. 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

3. to investigate sample collection requirements (e.g. sample collection frequency, number and timing in relation to exposure) for urine DAP metabolite monitoring

4. to investigate correlations between urine DAP metabolite levels and blood cholinesterase activities where blood sampling is possible.

Methods used 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 50 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. Key findings and their implications 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 rarely or never read and 88.2% of farmers rarely or never 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-quarters had never read about or been shown how to perform a formal risk assessment. 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 0.24-304.00 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 was expected from the literature. Such exposure is also 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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Based on the findings of this research project a guide has been developed to assist farmers in the completion of a risk assessment of their, and/or their employee’s exposure to organophosphate pesticides. The guide incorporates the use of the urine DAP metabolite test as part of the risk assessment process. The guide would also be of assistance in completing risk assessments for other chemical exposures on the farm. Although the Queensland rural industry is presently exempt from the hazardous substance provisions of the Queensland Workplace Health and Safety Legislation, it is likely that this exemption will be lifted in the near future. There may be some resistance in the rural industry to this change, but farmers should already be considering the risks to themselves and others from chemical exposures as part of their overall obligation to ensure health and safety on their farms. Generally speaking, all industries struggle with compliance with the hazardous substance legislation, for example the formulation plant which has no exemptions from the legislation struggled with no established baselines for their workers, ineffective PPE and poor hygiene practices of workers. Like many areas of occupational health, chemical exposures often do not receive the same level of attention as safety related issues due in part to the long latency periods between exposure and effect and also to the lack of workers compensation statistics. Therefore, there needs to be an added effort on behalf of the government and industry bodies to highlight the health related issues in industry and to improve the collection of data on the occurrences of health related incidents. Should the Queensland government remove the rural exemption, farmers will need further instruction in the requirements of the legislation and in particular, how to conduct a formal risk assessment for chemical exposure including OPs. Farmers in this study had a very limited understanding of what was involved in completing a formal risk assessment, and of MSDSs and their importance. Training organisations such as those that run the ChemCert training course may need to reassess both their approaches to teaching farmers about risk assessments and MSDSs and the availability and frequency of refresher training. The changes to the ChemCert course, other training courses and perhaps to legislation, which may be expected as a result of this study, will not only assist with OP exposures but with the management of all types of chemical exposures on the farm. Any such research into chemical exposures draws attention to the issues and although in this case farmers’ levels were low, the reported behavioural findings suggest there is still plenty of room for improvement in the management of farm chemical exposures. Recommendations The following key recommendations have been made based on the findings of the research project: 1. That the urinary metabolite test (dialkyl phosphate (DAP) metabolites) be considered as the

replacement for the blood cholinesterase, organophosphate (OP) insecticide exposure test where applicable.

2. A comprehensive review of current literature be undertaken to establish if there is sufficient data available to establish a Biological Occupational Exposure Limit (BOEL) /index for the urinary metabolite test.

3. Due consideration be given to the adoption or establishment of a BOEL for the urinary metabolites of organophosphate insecticides so that this metabolite test becomes the primary test for OP exposure.

4. In the mean time, a more detailed protocol be developed for the continuing use of the blood cholinesterase test when it is applied to the assessment of occupational exposure to OP insecticides such that: a) Base line values of cholinesterase be established for all individuals being assessed for

occupational OP exposure. b) The test be applied to plasma and red blood cells. c) An occupational physician or OHS professional be involved in the assessment of workers,

workplaces and work practices in which the cholinesterase test is being applied for occupational exposure assessment.

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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 the 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, 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 a risk management guide for use by agricultural workers potentially exposed to OP pesticides. On a broader

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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.

2. Objectives The broad aims of this study were 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. The specific objectives of the study were:

• to assess participant fruit and vegetable farmers’ knowledge and use of formal risk assessment techniques;

• 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;

• to investigate sample collection requirements (e.g. sample collection frequency, number and timing in relation to exposure) for urine DAP metabolite monitoring; and

• to investigate correlations between urine DAP metabolite levels and blood cholinesterase activities where blood sampling is possible.

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3. Literature Review 3.1 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 3.1. Figure 3.1 Generic structure of OP pesticides

3.1.1 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 3.1 lists the half-lives of some commonly used pesticides. 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.) • soil conditions (e.g. microbial populations, moisture, temperature, pH) (Cornell University, 2005) (University, 2005).

P

R1O O(S)

(OX or SX) R1O

Note: X is the leavening group

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Table 3.1 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, University). 3.1.2 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 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). 3.1.3 Health effects from exposure to OPs 3.1.3.1 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. 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.”

3.1.3.2 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). Atropine sulfate and glycopyrolate are drugs that can also 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.

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3.1.3.3 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.

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). 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 #421, London, 1997 #568, Cherry, 2002 #419, Sanchez-Santed, 2004 #571, Salvi, 2003 #591, Farahat, 2003 #592, 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

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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). 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 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 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

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by virtue of its nucleophilic serine, the essential feature for protein-OP covalent reaction” (Ray and Richards, 2001). 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. 3.1.3.4 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 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. 3.2 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 report. 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.

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3.2.1 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 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 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, 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. Seventeen of these were for activity levels below 50% of their plasma 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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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 • different laboratories may use different methods and the levels reported may therefore vary from

one laboratory to the next. 3.2.2 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 (DMDTP), diethyl phosphate (DEP), diethyl thiophosphate (DETP), and diethyl dithiophosphate (DEDTP)]. Figure 3.2 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 3.2 provides details of the metabolites for some commonly used OP pesticides. Figure 3.2 Structure of the six main DAP metabolites

Source: D. Gompertz in (WHO, 1996), page 241.

Dimethyl phosphate (DMP)

Dimethyl thiophosphate (DMTP)

Dimethyl dithiophosphate (DMDTP)

Diethyl phosphate (DEP)

Diethyl thiophosphate (DETP)

Diethyl dithiophosphate (DEDTP)

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Table 3.2 Common OPs and their DAP metabolites

OP Pesticide DMP DMTP DMDTP DEP DETP DEDTP azinphos-methyl chlorpyrifos chlorpyrifos-methyl diazinon dichlorvos dicrotophos dimethoate disulfoton ethion ethyl parathion fenitrothion fenthion malathion methidathion parathion methyl mevinphos phorate phosalone phosmet tetrachlorvinphos trichlorfon 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). 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

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(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 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. Currently, there are 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. To date only two Australian studies have used urine metabolite analysis; one investigated chlorpyrifos exposure among domestic pest control operators (Pisaniello, 2000) 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 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 research project. 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

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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 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). 3.2.3 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 individuals 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.

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3.3 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 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.

3.4 Pesticide Poisoning Incidence Rates for the Agricultural Industry

Specific incidence statistics for agricultural pesticide poisonings are difficult to obtain, as workers’ compensation data include them in the general category of agricultural industry chemical exposures. However, the following numbers of pesticide-related claims in the agricultural industry have been documented: 7 in Queensland in 1992/93; 9 in New South Wales (NSW) (four long-term and five single exposures) in 1991/92; 11 in South Australia (three long-term and eight single exposures to pesticides) from 1995/96 to 1997/98 at a cost of $99 733; and 11 in Western Australia in 1995/96 (Frager, 2000). As with all compensation statistics, the above figures are likely to represent an underestimation of the real number of poisonings and illnesses that resulted from pesticide and other chemical exposures in the agricultural industry. For example, in Ferguson’s Queensland study, there were five self reports of poisoning by agricultural chemicals during the period August to December 1998 that did not receive professional treatment and therefore are unlikely to have involved workers’ compensation (Ferguson, 2000). Apart from workers’ compensation claims there are other sources of hazardous substance and pesticide poisoning data. For example, it is estimated that each year Australia-wide there are approximately 30-40 hospital admissions for poisoning by agricultural chemicals (Frager, 2000). Hospital admissions data, like compensation data, have also been found to underestimate the incidence of injury/illness in the agricultural industry. Ferguson (1994) found that 18% of injuries/illnesses that required one full day off work or inhibited the person from working at a normal pace for five or more days did not receive professional treatment.

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Statistics for pesticide poisonings do not represent a large percentage of the overall number of injuries that occur in the agricultural industry; however, the cost of some of these claims can be significant. For example, three shearers in Wagga Wagga, New South Wales, were awarded $613,144.00 in October 1997 for health effects associated with exposure to OP pesticide applied to sheep (Dips, 2000). There are also growing health and safety concerns, in the industry and the general community regarding the use of pesticides and the potential for long-term chronic health effects. 3.5 Current Health and Safety Pesticide Legislation in Queensland Regulation of agricultural and veterinary (Agvet) chemicals in Australia occurs at both federal and state levels. Federally, the Australian Pesticides and Veterinary Medicines Authority (APVMA) (previously known as the National Registration Authority) controls the manufacture of Agvet chemicals, the evaluation of their safety for humans and the environment, their efficacy and their registration for use. States are responsible for regulating the actual use of Agvet chemicals. Each state has a combination of statutes, regulations and codes of practice that deal with two main areas of agricultural use of the chemicals (workplace health and safety and the Agvet system) and environmental impact of agricultural pesticides (food safety and environment protection). In Queensland, the Department of Primary Industries deals with the regulation of use of pesticides, and Workplace Health and Safety Queensland (WHSQ) under the Department of Industrial Relations regulates the occupational health and safety of employers and workers. Queensland Workplace Health and Safety legislation consists of the Workplace Health and Safety Act 1995, and the Workplace Health and Safety Regulation 1997. This Queensland legislation, as in other states, was designed to be all-encompassing and is based on a tripartite model involving government, employers and employees in complementary roles of identifying and controlling health and safety risks in the workplace. Despite the aim of the legislation to be all-encompassing, it is still very focused on an industrial model that does not apply to most agricultural workplaces, which are characterised by small, dispersed owner-operator and family businesses. Because of the problems of applying the legislation to the agricultural industry, Queensland currently gives agricultural workers exemptions from most provisions of the Regulation (Part 22, Section 229(2), Workplace Health and Safety Regulation 1997). The Queensland rural exemption includes Part 13 of the Regulation, which deals with employers’ responsibilities to control exposure to hazardous substances (e.g. Material Safety Data Sheets, registers, risk assessments, monitoring and health surveillance). Because of this exemption, employers, self-employed persons and workers in the agricultural industry in Queensland are very unlikely to receive health surveillance for their exposure to OPs. WHSQ would like to remove the rural exemptions covering hazardous substances, but there are concerns within the industry over the practical application and enforcement of the legislation as it currently stands (personal conversations had during meetings of the WHSQ Rural Industry Sector Standing Committee). In most other states in Australia, health surveillance is required if an agricultural industry employee is exposed to an OP and a risk assessment shows that health surveillance is warranted. The current style of workplace health and safety legislation relies on the fact that employers are able to conduct an accurate risk assessment of their and their employees’ exposures (which would be difficult without first conducting some kind of biological monitoring to aid in the assessment of exposure). Health surveillance data are not collected, stored or correlated in any central database or registry. It is therefore difficult to gauge the extent of exposure of Australian farmers. Aerial agricultural services are classified as a service to the agricultural industry and as such are not exempted from the provisions of the Workplace Health and Safety Regulation 1997 that pertain to hazardous substances and OP pesticides. Employers in this industry group as well as those in the pesticide formulation industry are therefore required to conduct a risk assessment of their employees’ exposures to OP pesticides and provide them with health surveillance if they are assessed to have ‘significant’ exposure.

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Part 13 of the Regulation classifies OPs as a hazardous substance and lists them in schedule 6, column 1 as a substance requiring health surveillance. Part 13 (s.109(1)) of the Regulation sets out requirements for health surveillance as follows: “An employer or self-employed person must arrange for health surveillance of the employer, self-employed person or a worker, who a risk assessment shows has been exposed to a hazardous substance:

a) if the substance is listed in schedule 6, column 1, and the degree of risk to the health of the employer, self-employed person or worker is significant…”.

The Regulation stipulates that if health surveillance relates to exposure to a substance mentioned in schedule 6, column 1, the surveillance must include the things stated in schedule 6, column 2, for the substance (s.109(2)). The current prescribed health surveillance for OP pesticides consists of: • “a baseline examination of RBC and plasma cholinesterase activity levels by the Ellman method; and • a demographic, medical and occupational history; and • estimation of RBC and plasma cholinesterase activity towards the end of a working day on which OP

pesticides have been used; and • health advice; and • a physical examination” (Schedule 6, Workplace Health and Safety Regulation 1997) 3.6 Conclusion Workers in the agricultural industry are exposed to numerous health and safety risks including exposure to OP pesticides. The acute effects from exposure to OPs are well documented. However, there is still uncertainty about the effects of long-term, low-level exposure to OPs as is commonly experienced in the agricultural industry. Blood testing has been used in Australia and overseas for more than 40 years to monitor the effects of OP exposure. A relatively new biological monitoring procedure, urine DAP metabolite testing, has been introduced in Australia by WorkCover NSW. This test is much more sensitive than the blood test and attempts to monitor actual exposure rather than the associated health effects of high-level exposure needed for blood cholinesterase monitoring. To date, there have been no Australian studies that have used urine metabolite testing to monitor agricultural industry workers’ exposure to OPs. There has been some research conducted overseas, but obviously there are still several questions left unanswered in regards to the use of the test and OP exposure in Australia, including:

• What health effects/symptoms are related to metabolite levels detected in the urine of OP-exposed workers?

• What is the correlation between urine metabolite levels and amount of exposure to OPs? • What are the health effects of long-term, low-level exposure to OPs? • What is the correlation between urine levels and neural system tissue reductions in AChE levels? • What is the correlation between blood (both RBC and plasma) cholinesterase levels and urine

metabolite levels? • Is it sufficient to perform urine DAP metabolite monitoring for health surveillance purposes, or

should blood testing still also be performed? • How can exposed persons effectively use urine metabolite testing to monitor their exposure to

OPs? • How practical is it to introduce mandatory health surveillance requirements for exposure to OPs in

the agricultural industry? • What requirements for frequency, sample size (i.e. 24-hour or spot samples), sample storage and

transport, etc., would be prescribed if urine sampling were to be introduced as the mandatory method of health surveillance?

Therefore this study aims to investigate the use of OP pesticides by the agricultural industry in South East Qld and to investigate the usability of the urine metabolite test as a risk assessment tool. Where possible the study will also attempt to investigate the correlation between blood cholinesterase levels and urine DAP metabolite levels. Issues such as the chronic health effects from low level exposures and the development of a BEI are beyond the scope of this study.

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4. Methodology 4.1 Project Overview The project’s overall methodological approach was a cross-sectional study involving the assessment of exposure to OP pesticides and related issues among four groups: fruit and vegetable farmers; agricultural applicators and their mixer/loaders; formulator plant staff; and a control group. The farmers were surveyed via an in-depth interviewer-administered questionnaire. However, only selected information is presented in this report with regards to the interviewer-administered questionnaire as it formed part of a larger QUT PhD thesis project. This report focuses on the biological monitoring component of the larger project. All participant groups were involved in the biological monitoring data collection component of the study, which is the main focus of this report and consisted of the collection of spot urine samples and completion of a specifically tailored self-administered, risk-factor questionnaire. Each exposure group completed a questionnaire relevant to their potential exposures to OPs. The formulator plant group also provided one whole-blood sample for cholinesterase analysis. It was not logistically possible to collect blood samples from the other three groups. Ethics approval for the research project was granted on 17 April 2002 by the QUT University Human Research Ethics Committee (Reference No QUT 2527H). 4.2 OP Pesticide Self-Administered Risk Factor Questionnaire This section presents the methods for assessing exposure through analysis of workplace activities. Each exposure group and the control group completed a self-administered questionnaire in association with biological sample collection. The following information provides some background to the development of the self-administered questionnaires. In July 2002, the author attended a conference on international pesticide exposure and health in Washington DC, USA. One of the presenters, Beth Baker, was involved with a farm family exposure study underway in Minnesota and South Carolina (Acquavella JF et al., 2004). The study was designed to characterise pesticide exposure received by the farm family around the time of pesticide application by measuring urinary pesticide levels, including DAPs, in the farmer, spouse and children. A Farm Family Study Field Form was used to record information about the pesticide application. Permission was obtained to use and adopt this field form for the current project. Subsequently the form was used as a basis in constructing the self-administered form completed by farmers and altered, where necessary, to suit the pilots and mixer/loaders, and the formulator plant staff. The main aim of the risk-factor questionnaire, for all groups, was to collect information about potential exposure to OPs that would allow for interpretation of the biological sample results. Therefore information was collected about any potential exposure that may have occurred in the five days preceding the collection of the first urine sample as well as detailed information about the work practices and potential exposures during sample collection. Unfortunately, it was not logistically possible to conduct direct observations of participants while they conducted mixing/loading and spraying activities. Therefore collection of the data via self-administered questionnaire was required. Such data collection methods therefore rely on the accuracy of reporting by the participant.

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4.2.1 Fruit and vegetable farmers With assistance from the Queensland Fruit and Vegetable Growers (QFVG), postcode areas were identified that were likely to contain eligible participants within a one-day drive of Brisbane. The following areas were selected: 4001–4179 Brisbane and surrounding areas (e.g. Redland Shire, Rochdale, Underwood, Runcorn, Waterford and Shailer Park); 4270–4280 Tamborine Mountain areas; 4285–4310 Beaudesert to Boonah; 4311–4344 and 4350 Lowood/Laidley and Gatton to Toowoomba; 4352–4361 and 4347 Granite Belt area, Grantham, Severnlea, Amiens and Pozieres. When the main study began in January 2003, the QFVG’s database contained all fruit and vegetable farmers in Queensland (membership of the QFVG was compulsory until 30 June 2003). There were 523 farms registered with the QFVG in the selected postcode areas, excluding the 60 farms contacted during the pilot study. Members of the QFVG could elect to not allow a third party to contact them via the QFVG; of the 523 farms, 263 had elected not to allow a third party to contact them. Therefore, we were unable to obtain contact information for these 263 farms. Consequently, contact details for 260 farms from within the identified postcode areas were provided. From the 260 contacts provided, lists of 50 randomly selected contacts were generated using the Excel random number generation tool. Information packages were mailed to 50 contacts at a time. The information package contained a covering letter from the QFVG on their letterhead, a covering letter from the author on QUT letterhead and an information leaflet that provided more in-depth information about the project. The package was mailed in a QFVG envelope to increase the likelihood of the information being read. Approximately one week after packages were mailed, farmers were contacted via phone by either the author or one of two research assistants who worked on the project. If the contact was eligible and decided to volunteer, the caller organised a convenient time and place for administration of the interview-administered questionnaire. To be eligible to participate in the study, the farmers had to be currently growing fruit and vegetables and they had to be likely to spray OP pesticides within the next 12 months. It was explained to participants that it was not necessary for them to have sprayed OP pesticides recently. Due to drought conditions being experienced in Queensland at the time of the study and the limited number of eligible participants, it was deemed necessary to attempt to contact all 260 farms in order to reach the target number of 50 participants. After completion of the questionnaire the farmer was invited to participate in the biological sample collection component of the study. The interviewer showed the farmer a kit for biological sample collection and explained the process involved. If the farmer was likely to spray OP pesticides in the next few months and was interested in participating the participant was left with the kit and told to contact the researcher when their samples were ready for collection or if the participant had any questions during the sample collection process. Thirty-five farmers provided pre- and post-exposure urine samples for analysis and a completed self-administered questionnaire. 4.2.2 Pilots and mixer/loaders A list of agricultural aerial applicator companies was constructed with assistance of the AAAA’s Executive Officer, one of WHSQ’s Rural Inspectors based in Toowoomba and the Yellow Pages. A list of 16 companies from around south-east Queensland and just over the border into New South Wales was constructed. The list was made as comprehensive as possible. Aerial applicators tend to apply to broad-acre crops, such as cotton, therefore most of the applicator companies are based around cotton-growing areas such as St George, Goondiwindi and Dalby.

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On the advice of the AAAA’s Executive Officer, the first point of contact with the aerial applicator companies was via telephone rather than mailed information packages. The author attempted to contact all 16 companies that ranged in size from larger firms employing 3-10 pilots to the more common smaller operator with 1-2 pilots. Once manager/owners had given permission for their company to be involved with the study, they were asked to identify some potential participants and to provide their names and positions (i.e. pilot or mixer/loader). A package was then mailed out to the company containing a cover letter for the manager/owner and individually sealed and named envelopes that contained participants’ sample packs. Each sample pack contained a letter for the individual participant explaining the project, an information leaflet complying with ethical requirements, an informed consent form, a set of instructions for urine sample collection, a questionnaire, a list of OP pesticides with brand name and active ingredient for referral, four labelled urine sample containers and four plastic bags in which to store the samples. Participants were asked to store their urine samples in a freezer as the timing between sample collection and pick-up by the researcher was uncertain given the distance from Brisbane. The companies were asked to contact the researcher when all the participants from that firm had provided samples. The main spray season for aerial applicators is between December and March. Recruitment of participants was conducted between November 2003 and January 2004, and urine samples were collected between 29th January and 24th March 2004. Pilots and their mixer/loader participants were asked to collect four urine samples each. The protocol for urine sample collection was based on that used for the farmers and is detailed in section 4.3 below. 4.2.3 Formulator plant staff Originally, it was planned to involve three formulation plants in data collection as one of the project. Unfortunately, just before data collection started the three plants were bought out by a new company. The new company was approached for their permission to involve their staff in the research project. Access to the employees was denied, despite several attempts to gain permission even with help from the pesticide formulation industry body. Eventually, a formulation plant in New South Wales was approached and granted permission for their employees to take part in the research. The plant had recently been down-sized and did not formulate many OP pesticides. Fortunately, just after granting permission the plant scheduled a run of an animal-health OP called Rametin (containing the active ingredient: naphthalophos). The author travelled to the plant and provided the staff with two presentations for recruitment purposes on Friday 30th April 2004. All of the staff were scheduled for biannual blood sampling on the following Thursday, 6th May. The run of Rametin formulation was planned for 4th to 7th of May. All interested staff received a participation pack containing an information leaflet providing details about the project, a consent form, a questionnaire, instructions for collection of samples, and identification-code-labelled urine sample containers and plastic bags in which to place the containers. All staff at the plant provided blood samples for cholinesterase and other analyses. Not all staff were involved with the formulation or handling of Rametin. Ten staff working with or in the area where Rametin was formulated and packaged provided pre- and post-shift spot urine samples for four consecutive days, as well as a blood sample and completed questionnaire. Eleven other staff not working with or in the area where Rametin was formulated provided one spot urine sample and completed an environmental and occupational exposure questionnaire and were used as controls for the ten formulation workers. The author toured the plant, paying particular attention to the shed and processes involved with the formulation, packaging and clean-up of Rametin. A key experienced staff member involved in the formulation process was interviewed and provided details used to refine the self-administered questionnaire to suit formulation type exposures. A section on potential environmental exposure was

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added to the exposed formulation plant participants’ questionnaire. This section was not incorporated in the farmers and pilot/mixer/loader self-administered questionnaires, as it was not known at that stage that a control group would be incorporated in the study. As discussed later in this chapter, the pre-exposure urine samples for the farmers and pilots were designed to be used as controls. The environmental and occupational exposure questionnaire completed by the 11 controls at the plant was very similar to the one used for the Toowoomba control group. 4.2.4 Toowoomba control group A control group of non-occupationally exposed persons was included in the study to assist in the interpretation of urine results from exposed individuals. Originally, it was thought that the first pre-exposure urine samples that were provided by the farmers and the pilots/mixer/loaders would act as a control for the 2-3 post-exposure samples collected by the participants in these groups. But the urine results for the farmers were lower than expected with the first pre-exposure sample sometimes containing higher results than the post-exposure samples despite no known exposure-related explanation. It was therefore decided to include a control group from a similar geographical area to help interpret these unexpected results. As all participants in the farmer and pilot groups were males living in rural areas surrounding Toowoomba, it was decided to recruit male non-occupationally exposed persons living in and around Toowoomba. Toowoomba was selected because it is the largest town in the geographical area that would contain men who would be unlikely to work with OP pesticides. Service clubs were thought to be a convenient method of recruiting a large group of men in a similar age group to participants. A long-standing Toowoomba Rotary club member was contacted and agreed to act as a go-between for the author and four of the Rotary clubs (Toowoomba, Toowoomba South, Toowoomba East and Toowoomba North). Each of the clubs holds a weekly meeting on a set night. The author attended each club’s meeting as a guest speaker, providing an overview of the project and an invitation for club members to participate in the study. At the end of each meeting, interested members received an information pack containing a letter from the author, an information leaflet, a consent form, a short self-administered questionnaire on environmental exposure to pesticides, an envelope for the completed questionnaire and consent form, and an identification-code-labelled urine container and plastic bag for storage in a fridge. Control group participants were asked to collect one spot urine sample. Club members who agreed to participate were asked to bring their completed questionnaire, consent form and urine sample to their next Rotary club meeting. The samples were transported on ice in an esky to QUT where they were frozen and then transported to the laboratory. The recruitment process was conducted between 15th and 18th March 2004 and the samples were picked up between 21st and 25th of March 2004. Several relatively large studies have been conducted overseas to investigate environmental exposure to OP pesticides using the urine DAP test (Lu et al., 2001, Oglobline et al., 2001, Curl et al., 2002a, Curl et al., 2002b, Koch et al., 2002, Fenske et al., 2003, Bravo et al., 2004). Some of these studies have been primarily interested in children’s exposure. The published list of questions used in one of these studies (Curl et al., 2002a) was used as a basis for construction of the environmental exposure questionnaire completed by the control group participants. Extra questions were added about potential occupational exposure of the participant and the participant’s partner. Confidentiality was ensured with only an identification code being recorded on the urine sample container and questionnaire. The front page of the questionnaire, which was removed after collection, included a space for participants to provide their name and mailing address if they wanted their results returned to them.

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4.3 Biological Sample Collection 4.3.1 Urine sample collection and transport Participants were provided with urine sample collection packages that contained an instruction leaflet, an information leaflet, a consent form, a self-administered questionnaire and plastic clip seal bags in which to store the urine specimen containers. All participants had had the project and the instructions for collection explained to them prior to receiving a sample collection kit. Participants were advised verbally and in writing to contact the researcher if they had any problems or questions about the sample collection process. Participants were asked to collect spot urine samples rather than full 24-hour urine voids. This sampling strategy was selected to improve participation rates and to encourage compliance. If 24-hour urine voids are required there is no guarantee that the samples will be complete and the process is onerous for the participant. As participants were asked to store their samples for short periods in their own refrigerators, 24-hour voids would have involved storage of large volumes of urine. Most occupational pesticide exposure studies employ spot urine sample collection (Drevenkar et al., 1991, Nutley and Cocker, 1993, Takamiya, 1994, Stephens et al., 1996, Azaroff, 1999, Simcox et al., 1999, Hatjian et al., 2000, Pisaniello, 2000, Mills, 2001). Because the samples are not collected as 24-hour urine voids they must be corrected for dilution. All urine samples were self-collected in 50 mL standard polyethylene, yellow-top specimen containers purchased from a medical supplier. No personal identification information was recorded on the specimen containers. All containers were labelled with the participants’ individual identification codes. For the occupationally exposed groups, each urine sample container was marked clearly with the sample number, using a black permanent marker, in three places - on the container’s lid, side and label. Because control group participants provided only one sample their containers did not need to be marked with the sample number. Contamination of samples by the OP pesticide being used does not interfere with the sample or the results as the test measures the DAP metabolites, not the parent compounds. Participants were, however, instructed to wash their hands before collecting their samples. The urine samples did not require the addition of a preservative. Participants were given instructions as to when to collect the samples in relation to exposure to OP pesticide; details of sample collection timing are provided in section 4.3.2. Participants were instructed to only fill the containers halfway and to immediately store the sample in a refrigerator or, if possible, a freezer. Once all samples had been collected, the participant contacted the researcher to arrange pick-up. On average, the samples were collected one day (range: same day – 7 days later) after the participant contacted the researcher. The samples were transported on ice in a small esky directly to QUT where they were immediately stored in a freezer awaiting shipment to WorkCover NSW Laboratory. Samples were stored at QUT for an average of 6 days (range: 0-24 days) before being couriered to the laboratory. Research has shown that urine DAP samples can be stored frozen for up to 20 weeks without the metabolites breaking down or disappearing (Ito, 1979). Samples were packed on ice into specifically designed transport containers, in compliance with IATA packing instructions 650 for non-restricted diagnostic specimens. The author delivered the sample packages to the TNT Brisbane airport depot as late in the afternoon as possible to ensure minimum time delays between drop off and loading onto a plane. The samples were flown overnight first class to Sydney airport were they were immediately couriered to the WorkCover NSW Laboratory in Thornleigh. The above process of sample transportation was followed for all urine samples except for those collected by the formulator plant group. This group was based in New South Wales and samples were collected from the one plant. The plant’s Occupational Health and Safety (OHS) Manager was instructed in the correct method of storing, packing and couriering the samples. The OHS Manager directed participants to store their samples immediately in a designated freezer and once all staff had

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collected and stored their samples she sent them directly to the WorkCover NSW Laboratory via road courier, a distance of approximately 80 km. 4.3.2 Justification for number of urine samples and timing of collection An extensive search of the literature was performed to investigate the half-life of the DAP metabolites and to examine sampling time frames used in similar field exposure studies. According to Griffin et al. (1999), who administered dermal doses of chlorpyrifos to volunteers, the maximum concentration measured in excreted urine was reached after 17–24 hours and the half-life was 30 hours. The half-life after an oral dose was 15.5 hours (Griffin, 1999). Griffin et al. (1999) therefore suggested that the best time to collect samples for biological monitoring was before the shift following the day of exposure. Garfitt et al. (2002) administered an oral and a dermal dose of diazinon to five volunteers and then measured exposure using blood cholinesterase and urinary DAP metabolites. The peak levels of excretion in urine for the oral and dermal routes occurred at 2 and 12 hours, respectively. Half-lives were 2 and 9 hours, respectively. Approximately 60% of the oral dose and 1% of the dermal dose were excreted as urinary DAP metabolites. These authors asserted that the best sample collection time is at the end of the shift.; however, for exposures expected to be predominantly by the dermal route and likely to continue beyond the end of the shift (for example, due to inadequate personal hygiene) they suggested that urine samples be collected pre-shift the day following exposure (Garfitt et al., 2002). The sampling protocol best suited to the type of exposures experienced by this project’s participants was thought to be one pre-exposure sample in the morning before any contact with OPs, one post-exposure sample at the end of the work day and one post-exposure sample the next morning. Therefore, the majority (74.3%) of farmers collected three samples each - one pre- and two post-exposure samples. Three-quarters of the way through the farmers’ study, examination of their urine sample results revealed that the DAP metabolite levels were much lower than expected. One possible cause for the low results was that samples were being collected too soon after exposure, given the long half-life for dermal exposure. It was decided that from that point onwards, farmers would be asked to provide four samples - one pre- and three post-exposure. The third post-exposure sample was to be collected in the afternoon of the day following exposure to the OP. It was decided that agricultural pilots and mixer/loaders would collect four samples (one pre- and three post-application/mixing exposure). The formulator plant exposed group worked eight-hour shifts, so it was much easier to apply the recommended procedure of collecting pre- and post-shift samples. The formulation, packing and cleaning process was conducted over a three-day period and the exposed plant staff collected pre- and post-shift samples for four consecutive days. The control groups (main control group and formulator plant control group) each collected a single spot urine sample. 4.3.3 Urine sample analysis and quality control All urine samples were analysed by the WorkCover NSW Laboratory in Thornleigh, Sydney. Once the urine samples were received at the laboratory they were stored immediately in a refrigerator and held at 40C until analysis. The method of analysis used by the laboratory was the basis of a Masters research project and has been previously published (Oglobline et al., 2001). The laboratory has offered the test since July 1999. The DAP analysis method used has been cited by various other international authors (Beike et al., 2002, Bravo et al., 2004, Kupfermann et al., 2004, Tarbah et al., 2004). The DAP analysis method is a modification of the method developed by Nutley and Cocker (1993) from the UK Health and Safety Executive. The WorkCover NSW Laboratory method utilises a freeze-drying technique for sample preparation, whereas Nutley and Cocker’s (1993) method uses an azeotropic distillation technique. The method involves derivatising the freeze-dried urine samples with pentaflurobenzyl bromide and then determining the metabolites using dual capillary column gas chromatography with flame photometric detection. The limits of detection for the six metabolites are: DMP–1.5 µmol/L (200 ppb); DEP-0.7 µmol/L (100 ppb); DETP, DEDTP, DMTP and DMDTP–0.2 µmol/L (25 ppb).

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To compensate for changes in urine volume and concentration, the urine results are corrected for creatinine if the concentrations are between 0.3 g/L (0.0027 mol/L) and 3 g/L (0.0265 mol/L). Samples that fall outside this range are not corrected and are reported as micromoles per litre (μmol/L). Creatinine assays are performed using the Jaffe reaction and measurements are done at 500 nm using spectrophotometry. The detection limit for the creatinine assay is 0.0005 mol/L. Creatinine-corrected results are presented as µmol/mol creatinine. To convert to uncorrected results, the corrected result is multiplied by the creatinine result, which is presented in mol/L. The WorkCover NSW Laboratory is accredited by the National Association of Testing Authorities (NATA). The DAP and creatinine analyses are performed in accordance with its terms of accreditation (NATA accreditation number 3726). To ensure quality control, the laboratory analyses laboratory and field blanks, and performs duplicate and repeat analyses of samples. Spiked quality assurance samples are included routinely in each run to ensure accuracy of results. The laboratory also participates in several national and international inter-laboratory comparison programs. 4.3.4 Delivery of biological sample results to participants A copy of the laboratory results accompanied by an explanatory letter from the author, were sent to each participant. Participants were advised that if they were concerned with their results, they could contact the author and be referred to the project’s Occupational Physician. Formulator plant workers’ blood cholinesterase results were returned to them by a plant representative. 4.3.5 Blood sample collection and transport Only the formulator plant group provided blood samples. It was not possible to collect blood samples from the other groups for several reasons:

• blood samples need to be collected by a trained phlebotomist; • blood samples must be immediately spun down and sent to a laboratory for analysis; • it would be difficult and expensive to have a phlebotomist travel to each location, or require

participants to travel to a pathology collection agency; • the need for a baseline to be calculated, which requires collection of two to three samples at

least 30 days since the last exposure; • pilots are not allowed to fly for a set period of time after having a blood sample collected; and • the concern that requiring a blood sample may have reduced study participation rates.

The blood sample collection process for the formulator plant workers followed the current practices of the plant. Staff have a whole-blood sample collected biannually at six-monthly intervals, timed to coincide with the formulation of OP pesticides. The research team had to fit in with the plant’s sample collection schedule. One sample was collected from each participant on the same designated day. A trained phlebotomist from a pathology company collected the samples. The blood samples were spun down and sent immediately to the WorkCover NSW Laboratory for analysis. 4.3.6 Blood sample analysis and quality control All blood samples were analysed by the WorkCover NSW Laboratory. The laboratory performs analyses for the following blood cholinesterase levels:

• butyrylcholinesterase, “pseudo” or “plasma” cholinesterase (PsChE), found predominantly in plasma;

• AChE or “true” cholinesterase (Ache), found attached to erythrocytes and to a lesser extent in plasma; and

• Whole blood cholinesterase. PsChE determination is performed using an adaptation of the method published by Knedel and Böttger (1967) which uses a butyrylthiocholine iodide substrate. AChE and whole-blood cholinesterase determination is performed using an adaptation of the method published by Ellman et al. (1961) using acetylthiocholine iodide substrate. Samples are analysed using a Roche Diagnostics Cobas Mira Plus CC Discrete Analyser. The detection limit for the analyses is 0.2 kU/L. Results are referenced to an individual’s baseline. If baseline values are not known, the approximate depression is calculated using

24

the lower limit of the normal population range. The normal population ranges for the WorkCover NSW Laboratory test method are: PsChE 5.4–10.9 kU/L; RBC Cholinesterase 9.6–17.7 kU/L; whole-blood cholinesterase 7.0-12.7 kU/L. 4.4 Statistical Analysis 4.4.1 Analysis of biological sample results and self-administered questionnaires As described in Section 4.3.3 the limits of detection for the six urine metabolites were: DMP–1.5 µmol/L (200 ppb); DEP-0.7 µmol/L (100 ppb); DETP, DEDTP, DMTP and DMDTP–0.2 µmol/L (25 ppb). To compensate for changes in urine volume and concentration, the urine results are corrected for creatinine if the concentrations are between 0.3 g/L (0.0027 mol/L) and 3 g/L (0.0265 mol/L). Samples that fall outside this range are not corrected and are reported as micromoles per litre (μmol/L). Of the 96 urine samples provided by farmers, 3 samples could not be creatinine corrected. Of the 72 samples provided by pilots and mixer loaders, 3 samples could not be creatinine corrected. All of the Toowoomba control group samples and all of the Formulation Plant participant samples could be creatinine corrected. Therefore, in total 6 samples could not be creatinine corrected. In the Results Chapters, urine metabolite levels are reported as both creatinine corrected and uncorrected results. All analyses performed using urine metabolite levels are performed either using uncorrected results or a dichotomised variable (metabolites detected or not detected). Descriptive statistics and graphs were used to explore the urine metabolite results for each participant group. Individual metabolite results were examined for each sample as well as total DAP (i.e. total concentration of all metabolites in a sample – without creatinine correction). Urine DAP results for all groups were not normally distributed, as is often found with occupational biological sampling. One dichotomous, categorical variable was created based on the presence of detectable concentrations of DAP metabolites in any sample (i.e. pre- and/or post-exposure samples). Crude odds ratios were calculated using the dependent categorical variable (detectable level – ‘yes’ or ‘no’) and various independent categorical variables from the interviewer-administered questionnaire and the self-administered questionnaire. No multivariate modelling was possible due to small sample sizes. The Kruskal-Wallis and Mann-Whitney U tests were used to examine the relationship between groups (i.e. farmers, pilots/mixer/loaders and controls). Spearman’s rho was used to examine the correlation between blood cholinesterase results and urine DAP results for the formulator plant staff. As above, the prescribed statistical level for all tests was set at a two-tailed p value of 0.05.

25

5. Fruit and Vegetable Farmers and Pilot/Mixer/Loaders Urine Metabolite Results

5.1 Fruit and Vegetable Farmers Urine Metabolite Test Results Thirty-five fruit and vegetable farmers provided pre- and post-exposure urine samples for analysis. Twenty-six farmers provided one pre- and two post-exposure samples and 9 farmers supplied one pre- and three post-exposure samples (see section 4.3.2). Because only 9 of the 35 farmers provided a third post-exposure sample and because only two of these contained detectable levels, the third post-exposure samples were excluded from statistical analysis. Three farmers sprayed exclusively either Monitor or Nitifol containing the active constituent, methamidophos, which does not metabolise into any of the six tested DAPs (DMP, DMTP, DMDTP, DEP, DETP and DEDTP). Two of these farmers had no detectable levels of any metabolites and the third had one sample containing a very low level of DMTP (0.34μmol/mol creatinine). These samples were therefore excluded from statistical analysis, leaving a total of 32 sets of urine samples. None of the farmers’ urine samples contained detectable levels of the three diethyl DAP metabolites (DEP, DETP and DEDTP). Seventeen of the 32 farmers (53%) had detectable levels of dimethyl DAP metabolites in one or more of the post-exposure samples and 8 (25%) had detectable levels of DAP metabolites in their pre-exposure sample. Excluding the 9 third post-exposure samples, 21 of the 64 post-exposure samples contained detectable levels of one or more of the dimethyl DAP metabolites. DMTP was the metabolite most frequently detected with 25% of pre-exposure samples and 31.2% of both the first and second post-exposure samples containing DMTP (Table 5.1). Figure 5.1 graphically presents the DMTP metabolite results for all 17 farmers with detectable levels, revealing two general patterns of excretion of DMTP. Seven farmers start off with non-detectable or low levels, which become detectable and subsequently return to lower levels for the third sample (many of which are non-detectable). Four farmers’ levels do the reverse; they start higher, drop to lower, often non-detectable levels, then return to a similar level as the first sample. Three farmers had a detectable result for the first sample only and three had a detectable result for the last sample only. The total dimethyl DAP concentrations were calculated by summing the non-creatinine-corrected metabolite concentrations: [Dimethyl DAP] = [DMP] + [DMTP] + [DMDTP], where metabolite concentrations are in units of μmol/L. Table 5.2 summarises the total dimethyl DAP concentrations for pre- and post-exposure samples. Figure 5.2 graphically presents results for farmers who had detectable levels of dimethyl DAP metabolites, excluding one farmer whose pre-exposure sample contained a DMP concentration of 704 μmol/mol creatinine. This was 10 times higher than the next highest level and excluding it here enabled clearer examination of the patterns of exposure in the graph.

26

Table 5.1 Urine dimethyl alkyl phosphate metabolite results (μmol/mol creatinine) DAP Metabolite and sample Number

of samples

>ND1

Range (μmol/mol creatinine)

Median (μmol/mol creatinine)

DMP2

Pre-exposure sample 1 - 704.00

1st Post-exposure sample 1 - 75.00

2nd Post-exposure sample 1 - 66.00

DMTP2

Pre-exposure sample 73 15.00 – 52.00 34.00

1st Post-exposure sample 94 9.00 - 116.00 19.00

2nd Post-exposure sample 10 13.00 – 62.00 29.50

DMDTP2

Pre-exposure sample 15 - 10.90

1st Post-exposure sample 0 - -

2nd Post-exposure sample 3 10.00 – 38.00 14.00 1 not detected 2Detection limits for DMP 1.5 μmol/L (200 ppb); DMTP & DMDTP 0.2 μmol/L (25 ppb). Note: Creatinine corrected detection limits for a urine sample with 1g/L (0.010 mol/L) creatinine are: DMP 150 μmol/mol creatinine; DMTP and DMDTP 20 μmol/mol creatinine. 4. One sample was not creatinine corrected and contained 0.40 μmol/L DMTP 5. One sample was not creatinine corrected and contained 0.53 μmol/L DMTP 6. One sample was not creatinine corrected and contained 0.24 μmol/L DMDTP

27

Figure 5.1 Farmers’ urine DMTP concentrations (μmol/mol creatinine) (n=17) Table 5.2 Total dimethyl DAP concentrations for pre- and post-exposure samples Sample Number

of samples

>ND1

Range total

dimethyl DAP

(μmol/L)2

Median total

dimethyl

DAP

(μmol/L) 2

Mean total

dimethyl

DAP

(μmol/L) 2

Pre exposure 8 0.21-11.64 0.57 1.92

1st Post Exposure 11 0.20-2.37 0.38 0.64

2nd Post Exposure 11 0.26-2.11 0.39 0.66

3rd Post Exposure 2 0.44-0.83 0.64 0.64 1 not detected 2 non-creatinine corrected values

DMTP Metabolites Levels

0.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

1 2 3

Sample (1-pre, 2-1st post, 3-2nd post)

DMTP

um

ol/m

ol c

reat

inin

e

28

Figure 5.2 Total dimethyl DAP urine concentrations (μmol/L) (n=17) Figure 5.2 reveals no noticeably distinct pattern of total dimethyl DAP metabolite excretion. Some farmers had detectable results for their second sample only. Some had detectable results for their first and last samples only and a couple had similar results for all three samples. Only two farmers’ samples displayed a pattern of excretion more like what would have been expected, with no result for the pre-exposure sample and detectable results for the post-exposure samples that peak at the first post-exposure sample. 5.1.1 OP pesticides sprayed and DAP metabolites Approximately 70% of the OPs used in Australia will metabolise into one or more of the six DAP metabolites. Exposure to dimethyl OPs (e.g. dimethoate, parathion methyl and azinphos-methyl) will produce only dimethyl metabolites (DMP, DMTP, DMDTP) just as exposure to diethyl OPs will produce only diethyl metabolites (DEP, DETP, DEDTP) (see Chapter 2 for more detail). Because none of the farmers had detectable levels of diethyl DAPs, a comparison using cross-tabulation was performed to investigate the association between type of OP pesticide sprayed by the farmer and dimethyl DAP metabolites detected in urine (Table 5.3). Fourteen farmers reported spraying only diethyl OP pesticides on the day of exposure, with the urine samples from half of these farmers yielding evidence of dimethyl DAPs, while the other half had no detectable levels of any DAP metabolite. All of the farmers who reported spraying only diethyl OPs reported no exposure to dimethyl OPs in the five days prior to sample collection. Eighteen farmers sprayed an OP producing only dimethyl metabolites, and 12 (66.7%) had detectable levels of dimethyl DAP metabolites in their urine; the remaining 6 had no detectable metabolites. Chi-square analysis, with Yates correction for continuity, was used to examine the difference between the two groups. There was no significant difference in prevalence of detectable DAP metabolite levels between those who sprayed a diethyl OP and those who sprayed a dimethyl OP (χ21df = 0.35, p=0.56). Five of the 12 farmers who sprayed a dimethyl OP and had detectable levels of DMTP also had detectable levels of either DMP or DMDTP. Only one of the 7 farmers who sprayed only diethyl OPs and had detectable levels of DMTP also had detectable levels of either DMP or DMDTP.

0.00

0.50

1.00

1.50

2.00

2.50

1 2 3

Sample (1-pre, 2-1st post, 3-2nd post)

Tota

l Dim

ethl

y-DA

P u

mol

/L

29

Table 5.3 Cross-tabulation between detectable dimethyl DAP metabolites and spraying of dimethyl DAP metabolites. No detectable

metabolites n (%)

Detectable dimethyl DAP metabolites

n (%)

Total Sprayed one or more diethyl OP only

7 (54.0) 7 (37.0) 14

Sprayed one or more dimethyl OP only

6 (46.0) 12 (63.0) 18

Total 13 (100) 19 (100) 32 Note: ‘Detectable dimethyl DAP metabolites’ refer to any sample (pre- or post-exposure) containing detectable metabolites. 5.1.2 Relationship between detectable DAP metabolite levels and other measures of exposure The 32 farmers who supplied urine samples and sprayed an OP that produces one or more of the six DAP metabolites were categorised into two groups based on whether they had any samples with detectable concentrations of one or more DAP metabolites. A dichotomous variable was used instead of the continuous total DAP metabolites variable, as originally planned, because of the small sample size and the non-normal distribution of results. The dichotomous variable was used to examine the relationships with various independent variables thought to be potential risk factors (e.g. PPE use, application duration, spray blow back, etc.) Binary logistic regression analyses were performed to calculate crude ORs for having detectable metabolites in relation to the various risk factors for exposure. None of the risk factors had a significant relationship with the dependent variable (detectable metabolites) (Table 5.4). In fact, a non-statistically significant, inverse relationship appeared present between use of PPE and exposure (i.e. detectable metabolites). For example, relative to those with a low PPE-use score while applying, the odds of having detectable levels of metabolites were 3.57 (1/0.28) times higher for farmers with high PPE-use scores while applying. The same unexpected negative association was seen when glove use of any type and mask/respirator use of any type were investigated as individual risk factors. Two small increased odds of exposure were observed for time spent applying OP pesticides and whether the participant ate, drank, smoked or talked on a phone during application. Relative to those who spent an hour or less applying, participants who spent 2.5 or more hours applying had 2.00 (95% CI, 0.36-11.2) times higher odds of having detectable metabolites. Relative to those who did not eat, drink, smoke or talk on a phone while applying, those who did had 2.50 (95% CI, 0.40-15.5) times higher odds of having detectable metabolites. Chi-square and binary logistic regression analyses were performed to investigate the relationships between detectable metabolites and knowledge, attitudes, beliefs, risk perception, education, land area and age as derived from the interviewer-administered questionnaire data. No significant relationships existed with any of the variables (Table 5.5). Several non-statistically significant increased odds were observed. Relative to those with primary school education only, the odds of having detectable metabolite levels were 5.88 (1/0.17) (95% CI, 0.33-107.42) times higher for those with TAFE, trade or university level education. Relative to those with a medium knowledge score, the odds of having detectable metabolite levels were 2.63 (1/0.38) (95% CI, 0.50-13.72) times higher for those with a high knowledge score. This same reverse trend was observed for those with more positive attitudes/beliefs toward PPE use. Farmers who had more positive attitudes toward PPE use were 4.54 (95% CI, 0.85-23.80) times more likely to have detectable metabolite levels relative to those with less positive attitudes and beliefs toward PPE use (computed by taking the inverse of the OR reported in Table 5.5, which show the relationship for less positive attitudes/beliefs toward PPE use).

30

Table 5.4 Crude analyses of the relationships between exposure, measured as detectable DAP metabolites, and risk factors related to potential exposure (n=32)

Detectable levels

Risk Factor

Category Yes (%) No (%)

Crude OR a

95%CI b

p

high score (9-16) 10 (55.6) 5 (35.7) 1.00 PPE use while mixing low score (1-8) 8 (44.4) 9 (64.3) 0.44 0.11-1.87 0.27 high score (9-16) 11 (61.1) 4 (30.8) 1.00 PPE use while applying low score (1-8) 7 (38.9) 9 (69.2) 0.28 0.06-1.28 0.10

yes 7 (38.9) 6 (42.9) 1.00 Wore gloves while mixing no 11 (61.1) 8 (57.1) 1.18 0.28-4.88 0.82

yes 7 (38.9) 3 (21.4) 1.00 Wore gloves while applying no 11 (61.1) 11 (78.6) 0.43 0.09-2.10 0.30

yes 10 (55.6) 6 (42.9) 1.00 Wore mask while mixing no 8 (44.4) 8 (57.1) 0.60 0.15-2.45 0.48 yes 12 (66.7) 7 (50) 1.00 Wore mask while

applying no 6 (33.3) 7 (50) 0.50 0.12-2.10 0.34 no 13 (86.7) 10 (76.9) 1.00 Breathed in OP during

mixing yes 2 (13.3) 3 (23.1) 0.51 0.07-3.68 0.51 1-14 min 5 (29.4) 5 (35.7) 1.00

15-30 min 7 (41.2) 4 (28.6) 1.75 0.31-10.0 0.53 Time spent mixing & loading

31-270 min 5 (29.4) 5 (35.7) 1.00 0.17-5.77 1.00 1-60 min 5 (27.8) 5 (35.7) 1.00

61-154 min 5 (27.8) 5 (35.7) 1.00 0.17-5.77 1.00 Time spent applying

155-570 min 8 (44.4) 4 (28.6) 2.00 0.36-11.2 0.43 boom on tractor 9 (50.0) 7 (53.8) 1.00 hand spray gun 1 (5.6) 0 0.00 1.00

back pack 0 2 (15.4) 0.00 1.00

Application equipment

mister/blower/ fogger

8 (44.4) 4 (30.8) 1.56 0.33-7.36 0.58

ground 11 (61.1) 9 (64.3) 1.00 cattle 0 1 (7.1) 0.00 1.00

Crop type

tree 7 (38.9) 4 (28.6) 1.43 0.32-6.49 0.64 no 12 (66.7) 7 (50) 1.00 OP skin contact while

applying yes 6 (33.3) 7 (50) 0.50 0.12-2.10 0.34 No, did none 12 (70.6) 12 (85.7) 1.00 Ate food, drank, smoke or

talked on phone while applying

Yes, did one or more 5 (29.4) 2 (14.3) 2.50 0.40-15.5 0.33

no 8 (47.1) 6 (42.9) 1.00 Spray blow back during application yes 9 (52.9) 8 (57.1) 0.84 0.20-3.50 0.81

Straightaway to 2 hours later

10 (55.6) 7 (50) 1.00 Time from applying to bathing/ showering 3-12 hours later 8 (44.4) 7 (50) 0.80 0.20-3.25 0.75 a OR of having detectable DAP metabolite levels b 95% Confidence interval for the crude OR

31

Table 5.5 Crude analyses of the relationships between exposure, measured as detectable DAP metabolites, and demographic characteristics, knowledge, attitudes and risk perception

Detectable levels

Variable


Crude

ORa

95% CIb

p

TAFE/trade or

university

6 (40) 2 (16.7) 1.00

senior high school 2 (13.3) 3 (25) 0.22 0.20-2.45 0.22

junior high school 6 (40) 5 (41.6) 0.40 0.05-2.93 0.37

Education

5-7 years primary 1 (6.7) 2 (16.7) 0.17 0.01-2.98 0.22

150-600 acres 2 (13.3) 2 (16.7) 1.00

50-145 acres 4 (26.7) 2 (16.7) 2.00 0.15-26.73 0.60

21-49 acres 4 (26.7) 6 (50.0) 0.67 0.06-6.87 0.73

Farm size

1-20 acres 5 (33.3) 2 (16.7) 2.50 0.19-32.19 0.48

high knowledge (14-

22)

7 (46.7) 3 (25.0) 1.00 Knowledge

medium knowledge (7-

13)

8 (53.3) 9 (75.0) 0.38 0.07-1.99 0.25

more positive attitudes/beliefs toward PPE use

9 (60) 3 (25) 1.00 Attitudes and beliefs

less positive attitudes/beliefs toward PPE use

6 (40) 9 (75) 0.22 0.04-1.17 0.08

high risk perception

(3.5-6)

7 (46.7) 6 (50) 1.00 Risk perception

low risk perception (1-

3)

8 (53.3) 6 (50) 1.14 0.25-5.22 0.86

1-20 years 8 (53.3) 7 (58.3) 1.00 Number of years

applying 20-53 years 7 (46.7) 5 (41.7) 1.22 0.26-5.67 0.79

49-66 years old 7 (46.7) 6 (50) 1.00 Age

31-48 years old 8 (53.3) 6 (50) 1.14 0.25-5.22 0.86

Note: n=27 farmers from main study, excluded 5 pilot study participants a OR of having detectable DAP metabolite levels b 95% Confidence Interval for the crude OR

32

Four farmers had elevated levels of DAP metabolites (i.e. above 0.90 μmol/L) compared with the 28 others. All four farmers used a mister/blower/fogger to apply the pesticide; three of these applied to tree crops and one to a ground crop. Three reported that the pesticide blew back onto them during application and that spray came into contact with their skin. Table 5.6 presents cross-tabulations for the type of exposure (none, low, high) with the various risk factors. One farmer’s two post-exposure samples were almost twice as high as the next highest levels (2.37 and 2.11 μmol/L). This farmer had a low PPE-use score for mixing and applying, did not wear a mask or gloves while mixing and applying and reported that he breathed in OP while mixing. Table 5.6 Cross-tabulation for type of exposure (high measured as DAP metabolites over 50 μmol/mol creatinine) and various risk factors

DAP Metabolite levels Risk Factor Category None (%) Low (%) High (%)

boom on tractor 6 (46.1) 10 (66.7) 0 mister/blower/

fogger 4 (30.8) 4 (26.7) 4 (100)

back pack 2 (15.4) 0 0 hand spray gun 0 1 (6.6) 0

Application equipment

other 1 (7.7) 0 0

ground 8 (61.5) 11 (73.3) 1 (25) tree 4 (30.8) 4 (26.7) 3 (75)

Crop type

cattle 1 (7.7) 0 0

no 6 (46.2) 12 (80) 1 (25) OP skin contact while applying yes 7 (53.8) 3 (20) 3 (75)

no 5 (38.5) 8 (57.1) 1 (25) Spray blow back during application yes 8 (61.5) 6 (42.9) 3 (75)

1-60 min 5 (38.5) 5 (33.3) 0 61-154 min 5 (38.5) 4 (26.7) 1 (25)

Time spent applying

155-570 min 3 (23.1) 6 (40.0) 3 (75)

straightaway to 2 hours later

6 (46.2) 8 (53.3) 3 (75) Time from applying to bathing/ showering 3-12 hours later

7 (53.8) 7 (46.7) 1 (25)

33

Table 5.6 Continued

DAP Metabolite levels Risk Factor Category

None (%) Low (%) High (%)

high score (9-16) 4 (30.8) 8 (53.3) 3 (75) PPE use while mixing low score (1-8) 9 (69.2) 7 (46.7) 1 (25)

high score (9-16) 3 (25) 10 (66.7) 2 (50) PPE use while applying low score (1-8) 9 (75) 5 (33.3) 2 (50)

yes 5 (38.5) 6 (40) 2 (50) Wore gloves while mixing no 8 (61.5) 9 (60) 2 (50)

yes 2 (15.4) 7 (46.7) 1 (25) Wore gloves while applying no 11 (84.6) 8 (53.3) 3 (75)

yes 5 (38.5) 8 (53.3) 3 (75) Wore mask while mixing no 8 (61.5) 7 (46.7) 1 (25)

yes 6 (46.2) 11 (73.3) 2 (50) Wore mask while applying no 7 (53.8) 4 (26.7) 2 (50)

no 9 (75) 11 (91.7) 3 (75) Breath in OP during mixing yes 3 (25) 1 (8.3) 1 (25)

1-14 min 5 (38.5) 4 (26.7) 1* (33.3) 15-30 min 4 (30.8) 6 (40) 1* (33.3)

Time spent mixing & loading

31-270 min 4 (30.8) 5 (33.3) 1* (33.3)

no, did not do any 11 (84.6) 11 (78.6) 2 (50) Ate food, drank, smoke or talked on phone while applying

yes, did one or more 2 (15.4) 3 (21.4) 2 (50)

*Note: The variable for time spent mixing and loading has only three farmers in the high metabolite level group due to missing data for the fourth high-exposure farmer.

34

5.2 Agricultural Pilots and Mixer/Loaders 5.2.1 Urine test results Sixteen agricultural aerial applicator companies were contacted; 11 agreed to participate in the study, three were not interested and two were non-contactable, giving an initial response rate of 68.8%. Seven of the 11 companies actually provided urine samples for analysis (response rate 44%). Urine samples were received from 8 mixer/loaders and 10 pilots. Three follow-up phone calls were made to the other four companies during March 2004 in an attempt to increase the sample response rate. Tables 5.7 and 5.8 present the urine DAP metabolite results for the pilots and mixer/loaders, respectively. Of the 18 individuals who provided samples, 13 (72.2%) had detectable levels of one or more DAP metabolite in one or more samples. Eight of the pre-exposure samples (n=18) and 28 of the post-exposure samples (n=54) contained detectable metabolites. Total dimethyl and diethyl DAP concentrations were calculated by summing the non-creatinine-corrected metabolite concentrations: [Dimethyl DAP] = [DMP] + [DMTP] + [DMDTP] and [Diethyl DAP] = [DEP] + [DETP] + [DEDTP], where metabolite concentrations are in units of μmol/L. Thirteen pilots and mixer/loaders (7 pilots and 6 mixer/loaders) had detectable levels of dimethyl DAPs and 8 pilots and mixer/loaders (3 pilots and 5 mixer/loaders) had detectable levels of diethyl DAPs. Figures 5.3 and 5.4 graphically present the total dimethyl and total diethyl DAP concentrations, respectively, for pre- and post-exposure samples.

35

Table 5.7 Pilot urine DAP metabolite results – μmol/mol creatinine DAP Metabolite and sample Number

of samples

>ND1



DMTP2 Pre-exposure sample 3 36.60 – 45.80 45.70 1st Post-exposure sample 3 20.50 – 38.00 21.90 2nd Post-exposure sample 3 16.80 – 28.20 17.20 3rd Post-exposure sample 3 19.30 – 34.40 24.10

DMDTP2 Pre-exposure sample 0 1st Post-exposure sample 1 - 29.1 2nd Post-exposure sample 0 3rd Post-exposure sample 0

DEP2 Pre-exposure sample 0 1st Post-exposure sample 0 2nd Post-exposure sample 0 3rd Post-exposure sample 1 - 79.40

DETP2 Pre-exposure sample 1 - 14.00 1st Post-exposure sample 13 - 18.00 2nd Post-exposure sample 1 - 18.80 3rd Post-exposure sample 2 10.00 – 35.50 22.75

DEDTP2 Pre-exposure sample 1 - 22.10 1st Post-exposure sample 0 2nd Post-exposure sample 1 - 23.20 3rd Post-exposure sample 0

1 not detected 2Detection limits for DMP 1.5 μmol/L (200 ppb); DEP 0.7μmol/L (100ppb) DETP, DEDTP, DMTP & DMDTP 0.2 μmol/L (25 ppb). Note: Creatinine corrected detection limits for a urine sample with 1 g/L (0.010 mol/L) creatinine are: DMP 150 μmol/mol creatinine; DEP 70 μmol/mol creatinine; DMTP, DMDTP, DETP and DEDTP 20 μmol/mol creatinine. 3. One sample was not creatinine corrected and contained 0.24 μmol/L DETP.

36

Table 5.8 Mixer/loader urine DAP metabolite results - μmol/mol creatinine DAP Metabolite and sample Number

of samples

>ND1



DMP2 Pre-exposure sample 1 - 304.00 1st Post-exposure sample 0 2nd Post-exposure sample 1 - 108.30 3rd Post-exposure sample 1 - 78.90

DMTP2 Pre-exposure sample 4 15.40 – 77.30 37.00 1st Post-exposure sample 5 8.40 – 67.50 50.20 2nd Post-exposure sample 43 33.70 – 66.90 50.35 3rd Post-exposure sample 54 15.80 – 72.70 25.90

DMDTP2 Pre-exposure sample 1 - 45.80 1st Post-exposure sample 2 31.90 – 39.80 35.85 2nd Post-exposure sample 25 69.40 – 105.00 87.20 3rd Post-exposure sample 26 42.00 – 137.00 89.50

DEP2 Pre-exposure sample 0 1st Post-exposure sample 0 2nd Post-exposure sample 1 - 38.9 3rd Post-exposure sample 1 - 29.50

DETP2 Pre-exposure sample 0 1st Post-exposure sample 2 26.70 – 26.90 26.80 2nd Post-exposure sample 3 11.40 – 50.50 21.60 3rd Post-exposure sample 37 10.50 – 28.70 20.50

DEDTP2 Pre-exposure sample 0 1st Post-exposure sample 0 2nd Post-exposure sample 1 - 0.46 3rd Post-exposure sample 18 - 27.40

1 not detected 2Detection limits for DMP 1.5 μmol/L (200 ppb); DEP 0.7μmol/L (100ppb) DETP, DEDTP, DMTP & DMDTP 0.2 μmol/L (25 ppb). 3. A sample could not be creatinine corrected and contained 0.77 μmol/L DMTP 4. A sample could not be creatinine corrected and contained 0.76 μmol/L DMTP 5. A sample could not be creatinine corrected and contained 0.27 μmol/L DMDTP 6. A sample could not be creatinine corrected and contained 0.46 μmol/L DMDTP 7. A sample could not be creatinine corrected and contained 0.28 μmol/L DETP 8. A sample could not be creatinine corrected and contained 0.57 μmol/L DETP

37

Figure 5.3 Total dimethyl DAP metabolite results for pilots and mixer/loaders with detectable levels (µmol/L) (n=13) Figure 5.4 Total diethyl DAP metabolite results for pilots and mixer/loaders with detectable levels (n= 8) (µmol/L)

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

1 2 3 4

Sample

Tota

l Dim

ethy

l um

ol/L

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

1 2 3 4

Sample

Tota

l Die

thyl

um

ol/L

38

As illustrated in Figure 5.3, there was no noticeably distinct pattern of total dimethyl DAP metabolite excretion. There was also no distinct pattern of excretion of diethyl DAP metabolites, with each participant having their own individual pattern of excretion (Figure 5.4). Eight participants had one or more samples that contained detectable levels of diethyl DAP metabolites. Two of these had only one and the other six had more than one post-exposure sample containing a detectable level of diethyl DAPs. DMTP was again the most frequently detected DAP metabolite in samples from both the pilots and the mixer/loaders. Seven of the participants’ pre-exposure samples contained detectable levels of DMTP, 8 of the first and second post-exposure samples and 9 of the third post-exposure samples contained detectable levels of DMTP. A total of 13 participants had one or more samples with detectable levels of DMTP. Four of the 13 had one sample only containing detectable levels of DMTP (all post-exposure samples) (Figure 5.5). Figure 5.5 Pilots and mixer/loader DMTP concentrations (µmol/mol creatinine)

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

90.00

1 2 3 4

Sample

DMTP

um

ol/m

ol c

reat

inin

e

39

5.2.1 OP pesticides handled and DAP metabolites As discussed in section 5.1.2, dimethyl OPs will metabolise into one or more of the three dimethyl DAPs and diethyl OPs will metabolise into diethyl DAPs. A comparison using cross-tabulations was performed to investigate the association between the type of OP pesticide the participants’ reported handling (mixing and loading and/or spraying) during sample collection and the type of DAP metabolites found in the participants’ samples. None of the participants in this group had detectable levels of only diethyl DAP metabolites; rather they had levels of both diethyl and dimethyl DAPs, only dimethyl DAPs, or no metabolites at all (Table 5.9). Eight participants reported only handling dimethyl OPs during sample collection and during the 10 days leading up to sample collection but three of these participants had detectable levels of both diethyl and dimethyl DAPs. Two of the three participants who only handled diethyl OPs during and for 10 days prior to sample collection had detectable levels of both diethyl and dimethyl DAPs. Table 5.9 Cross-tabulation between OP handled during sample collection, prior to sample collection and type of DAP metabolites detected

Type of DAP metabolites detected OP type handled

during sample collection

OP type handled in 1-10 days

prior to sample collection

No DAP metabolites

Dimethyl DAP metabolites

only

Both diethyl and dimethyl

DAP metabolites

diethyl OP 1 - 2

dimethyl OP - 2 1

diethyl OP only

no metabolites - - 2

dimethyl OP only dimethyl OP 3 2 3

no metabolites 1 - -

handled both dimethyl OP - 1 -

40

5.2.2 OP pesticides handled and DAP metabolites As discussed in section 5.1.2, dimethyl OPs will metabolise into one or more of the three dimethyl DAPs and diethyl OPs will metabolise into diethyl DAPs. A comparison using cross-tabulations was performed to investigate the association between the type of OP pesticide the participants’ reported handling (mixing and loading and/or spraying) during sample collection and the type of DAP metabolites found in the participants’ samples. None of the participants in this group had detectable levels of only diethyl DAP metabolites; rather they had levels of both diethyl and dimethyl DAPs, only dimethyl DAPs, or no metabolites at all (Table 5.9). Eight participants reported only handling dimethyl OPs during sample collection and during the 10 days leading up to sample collection but three of these participants had detectable levels of both diethyl and dimethyl DAPs. Two of the three participants who only handled diethyl OPs during and for 10 days prior to sample collection had detectable levels of both diethyl and dimethyl DAPs. Table 5.9 Cross-tabulation between OP handled during sample collection, prior to sample collection and type of DAP metabolites detected

Type of DAP metabolites detected OP type handled

during sample collection

OP type handled in 1-10 days

prior to sample collection

No DAP metabolites

Dimethyl DAP metabolites

only

Both diethyl and dimethyl

DAP metabolites

diethyl OP 1 - 2

dimethyl OP - 2 1

diethyl OP only

no metabolites - - 2

dimethyl OP only dimethyl OP 3 2 3

no metabolites 1 - -

handled both dimethyl OP - 1 -

5.2.3 Relationship between detectable DAP metabolites (exposure) and various risk factors for pilots and mixer/loaders The 18 pilots and mixer/loaders who supplied urine samples were categorised into two groups based on whether they had any samples with detectable concentrations of one or more DAP metabolites. A categorical variable was used instead of the continuous total DAP metabolite variable because of the small sample size and the non-normal distribution of results. This variable was used to examine the relationship between OP exposure defined as one or more samples containing detectable metabolite/s and various independent variables thought to be potential risk factors (e.g. PPE use, duration of exposure and tasks completed). Binary logistic regression analysis was performed to calculate crude ORs for having detectable metabolites in relation to the various potential risk factors. Only one of the risk factors had a statistically significant relationship with the dependent variable (detectable metabolites) (Table 5.10) and that was washing hands before continuing with other work activities, which was associated with a 14.30 times higher odds of having detectable metabolites. However, several non-statistically significant increased OR were observed. Relative to those with a high PPE use score, the odds of having detectable DAP metabolites were 1.75 (95% CI = 0.21-14.22) times higher for those with a low PPE-use score. Compared to those who reported not breathing in OP, the odds of having detectable metabolites were 5.00 (95% CI = 0.55-45.39) times higher for those who reported that they did breathe in OP while working with the pesticide. Some pilots were owner-operators or from small companies and also performed mixing and loading tasks. Performing mixing tasks was associated with 3.37 (95% CI = 0.40-28.74) times increased odds of having detectable DAP metabolites, relative to not performing the task. Three other tasks were also associated with increased odds of having detectable

41

DAP metabolites: cleaning down an aircraft that has sprayed an OP; rinsing out an application tank that has contained an OP; and rinsing out empty OP pesticide containers. Six of the 18 pilot/mixer/loaders from this group were classified as having high DAP metabolite levels (>1.00 µmol/L), 7 had lower levels and 5 had no detectable DAP metabolites. Of those with high levels, 4 were classified as mixer/loaders only; 5 performed mixing and loading during sample collection; 4 reported breathing in OP pesticide; 5 reported having no skin contact with OPs; 5 completed the following tasks: washed down the aircraft, rinsed out the application tank, and rinsed out an empty pesticide container; 5 wore gloves; and 4 washed/showered more than 2 hours after finishing work with OP pesticides. Table 5.10 Crude analysis of the relationship between exposure, measured as detectable DAP metabolites, and various risk factors (n=18)

Detectable levels

Risk factor


Crude

OR a

95% CI b

p

high score (8-14) 6 (46.2) 3 (60) 1.00 PPE use low score (1-7) 7 (53.8) 2 (40) 1.75 0.21-14.22 0.60

yes 8 (61.5) 2 (40) 1.00 Wore gloves while working with OP no 5 (38.5) 3 (60) 0.42 0.05-3.43 0.42

yes 0 0 Wore mask while working with OP no 13 (100) 5 (100) unable to

calculate

no 3 (23.1) 3 (60) 1.00 Breathed in OP during work with pesticide

yes 10 (76.9) 2 (40) 5.00 0.55-45.39 0.15

30-180 min 6 (46.2) 3 (60) 1.00 Time spent working with OP 240-600 min 7 (53.8) 2 (40) 1.75 0.21-14.22 0.60

no 10 (76.9) 5 (100) OP skin contact while working with pesticide

yes 3 (23.1) 0 unable to calculate

straightaway to 2 hours later

5 (38.5) 0 Time from applying to bathing/ showering 3-12 hours later

8 (61.5) 5 (100) unable to

calculate

pilot 7 (53.8) 3 (60) 1.00 Job mixer/loader 6 (46.2) 2 (40) 1.29 0.16-10.45 0.81

no 4 (30.8) 3 (60) 1.00 Performed mixing and loading yes 9 (69.2) 2 (40) 3.37 0.40-28.74 0.27

yes 12 (92.3) 2 (40) 1.00 Washed hands before continuing with other work

no 1 (7.7) 3 (60) 0.07 0.00-0.84 0.04

no 2 (15.4) 2 (40) 1.00 Cleaned aircraft after it sprayed an OP yes 11 (84.6) 3 (60) 3.67 0.35-38.03 0.28

no 4 (30.8) 3 (60) 1.00 Rinsed out OP application tank yes 9 (69.2) 2 (40) 3.37 0.40-28.74 0.27

no 4 (30.8) 3 (60) 1.00 Rinsed out empty OP container yes 9 (69.2) 2 (40) 3.37 0.40-28.74 0.27

no 8 (61.5) 3 (60) 1.00 Handled spray equipment, e.g. nozzles

yes 5 (38.5) 2 (40) 0.94 0.11-7.73 0.95

a OR of having detectable metabolite levels b 95% Confidence Interval for the crude OR

42

5.3 Toowoomba Rotary Club Control Group There were approximately 120 Toowoomba Rotary club members at the four meetings attended by the author. Of the 112 participation packs distributed, 44 urine samples and 43 completed questionnaires were returned (36% response rate). Each control participant provided one urine sample. Of the 44 urine samples, 11 contained detectable levels of one DAP metabolite – DMTP. The median concentration of DMTP was 35.8 μmol/mol creatinine with a minimum of 9.5 and a maximum of 91.3 μmol/mol creatinine. The participant whose sample contained the highest concentration of DMTP (91.3 μmol/mol creatinine) was a florist. Florists have regular contact with flowers that may have been sprayed with OP pesticides. The second highest result was 47.7 μmol/mol creatinine; this sample belonged to the one participant who did not return a completed questionnaire so his occupation is not known. The third highest result (46.0 μmol/mol creatinine) belonged to a medical practitioner. The control group participants completed a self-administered questionnaire that collected information about potential environmental exposures (e.g. keeping a pet that is treated for fleas, fruit and vegetable intake, use of pesticides around the home). Due to the small sample and non-normally distributed data, the dependent variable, DMTP concentration, was categorised into detectable level and non-detectable level. Chi-square and binary logistic regression analyses were performed to investigate the crude associations between detectable levels of metabolites and the various potential environmental exposure risk factors (Table 5.11).

43

Table 5.11 Crude analysis of the relationship between detectable DAP metabolites (yes/no), and various environmental risk factors (n=43)

Detectable levels Risk factor


Crude OR

95% CI

p

no 8 (80) 31 (93.9) 1.00 Contact with pesticides as part of occupation

yes 2 (20) 2 (6.1) 3.87 0.47-31.91 0.21 no 9 (90) 26 (96.3) 1.00 Partners occupation

involves contact with pesticides yes 1 (10) 1 (3.7) 2.89 0.16-51.13 0.47

no 9 (90) 29 (87.9) 1.00 Contact with farm during last 3 days yes 1 (10) 4 (12.1) 0.81 0.08-8.16 0.85

yes 1 (10) 11 (33.3) 1.00 Home vegetable garden no 9 (90) 22 (66.7) 4.50 0.050-10.17 0.18 no 1 (10) 2 (6.1) 1.00 0.67 Home has a garden yes 9 (90) 31 (93.9) 0.58 0.05-7.16 no 4 (40) 17 (51.5) 1.00 0.52 Ornamental plants kept

in home yes 6 (60) 16 (48.5) 1.59 0.38-6.71 no 6 (60) 24 (72.7) 1.00 Brought cut flowers in

house last 3 days yes 4 (40) 9 (27.3) 1.78 0.40-7.80 0.45 no 9 (90) 21 (63.6) 1.00 Domestic animals kept

in house yes 1 (10) 12 (36.4) 0.19 0.02-1.73 0.14 no 0 0 Pet in house receives

flea/tick treatment yes 1 (100) 12 (100) Unable to compute

no 6 (60) 15 (46.9) 1.00 Use pesticides in house yes 4 (40) 17 (53.1) 0.59 0.14-2.50 0.47 no 4 (40) 11 (33.3) 1.00 Use pesticides outside

house yes 6 (60) 22 (66.7) 0.75 0.17-3.22 0.70 no 8 (80) 29 (87.9) 1.00 Professional domestic

pest treatment in last month yes 2 (20) 4 (12.1) 1.81 0.28-11.75 0.53

small number of servings (1-3)

3 (30) 19 (59.4) 1.00 Fruit and veg consumed day before sample

collection high number of servings (4-10)

7 (70) 13 (40.6) 3.41 0.74-15.68 0.11


5 (50) 18 (58.1) 1.00 Fruit and veg consumed day of sample collection

high number of servings (4-10)

5 (50) 13 (41.9) 1.39 0.33-5.79 0.66

37-58 years old 3 (30) 19 (57.6) 1.00 Age 59-79 years old 7 (70) 14 (42.4) 3.17 0.69-14.46 0.14

Morning 2 (20) 5 (17.2) 1.00 afternoon 2 (20) 9 (31.0) 0.56 0.06-5.24 0.61

Time of day sample collected

evening 6 (60) 15 (51.7) 1.00 0.15-6.64 1.00

44

None of the risk factors investigated were significantly associated with detectable levels of DMTP; however, there were several factors that showed non-significant increased odds of having detectable levels. These factors were: having contact with pesticides as part of the participant’s occupation; not having a home vegetable garden; having brought cut flowers in the house; and having a higher number of servings of fruit and/or vegetables (4-10 servings) the day before sample collection. As all independent variables were of interest and none of the variables were statistically significantly associated with detection of metabolites it was decided to enter those risk factors that exhibited increased odds of detectable levels into a multivariate logistic regression model to examine the adjusted odds ratios (Table 5.12). The number of variables that could be entered into the model was limited in terms of the small sample sizes. After mutual adjustment for all the variables included in the model, not having a home vegetable garden and consuming a high number of servings of fruit and vegetables the day before sample collection, although still not significant, remained good predictors of detectable DMTP levels. Relative to those who have a home vegetable garden, the odds of having detectable levels of DMTP were 4.26 (95% CI=0.42 – 42.72) times higher for those who did not have a home vegetable garden. Compared to those with a low consumption of fruit and vegetables, the odds of having detectable DMTP levels were 3.19 (95% CI=0.63 – 16.31) times higher for those with a high consumption of fruit and vegetables. Table 5.12 Adjusted odds ratios for risk factors showing higher odds of having detectable DMTP levels

Risk factor

Category

Crude OR a

Adjusted OR b

95% CI c

p d

no 1.00 Contact with

pesticides as part of

occupation

yes 3.87 1.46 0.13 – 16.80 0.76

yes 1.00 Home vegetable

garden no 4.50 4.26 0.42 – 42.72 0.22

no 1.00 Brought cut flowers

in house last 3 days yes 1.78 1.33 0.22 – 7.91 0.76

small number of

servings (1-3)

1.00 Fruit and veg

consumed day before

sample collection high number of

servings (4-10)

3.41 3.19 0.63 – 16.31 0.16

37-58 years old 1.00 Age

59-79 years old 3.17 2.68 0.52 – 13.74 0.24 a OR of having detectable levels of DMTP b OR mutually adjusted for all other variables in the table c Confidence intervals for adjusted OR d Significance of the adjusted OR

45

5.4 Comparison between Urine DAP Metabolite Results for the Three Groups A comparison was made between the urinary DAP metabolite levels found for the Toowoomba control group and the two exposed groups: farmers and pilots/mixer/loaders. Continuous variables for total DAP metabolite levels were created using the results from the control group’s single sample and the exposed groups’ pre-exposure sample results. Another continuous variable was created using the mean metabolite level for the exposed groups’ first two post-exposure samples, and again using the control group’s single sample results. All variables were non-normally distributed. Figure 5.6 presents the mean total DAP urine results for the three groups and Table 5.13 presents a comparison of the three groups using descriptive statistics. Figure 5.6 Mean total DAP results (μmol/L) for farmers, pilots/mixer/loaders and controls

Farmer Pilot/Mixer/Loaders Control

Group

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Mea

n um

ol/L

tota

l DA

P

Pre-exposuere sampleFirst post-exposure sampleSecond post-exposure sampleMean of 1st and 2nd post-exposure samples

46

Table 5.13 Comparison of farmers, pilot/mixer/loaders and controls pre- and post-exposure DAP metabolite results

Pre-exposure sample (µmol/L)

Mean of first two post-exposure samples (µmol/L)

Group

Mean (+ SD)

Median (range)

Mean (+ SD)

Median (range)

Farmers (n=32)

0.46 (2.05) 0.00 (0.00-11.64) 0.21 (0.44) 0.01 (0.00-2.24)

Pilot/Mixer/Loaders (n=18)

0.63 (2.00) 0.00 (0.00-8.58) 0.49 (0.81) 0.14 (0.00-2.73)

Controls (n=44)

0.13 (0.30) 0.00 (0.00-1.57) 0.13 (0.30) 0.00 (0.00-1.57)

Note: Controls provided one sample only therefore the same results are presented in both the pre- and post-exposure columns. Figure 5.7 presents a box plot of the total urine DAP results for the pre- and first two post-exposure samples for the three groups. A box plot provides information about the distribution of the total DAP urine results and also allows a visual inspection of the difference between groups. The boxes and protruding lines represent the distribution of values with the box containing 50% of cases. The dark line across the inside of the box represents the median value (in several cases this is zero). The lines that go out from the box extend to the highest and lowest values. The circles with numbers attached are considered to be outliers by SPSS (the number is the cases ID number) and the asterisks (*) are considered to be extreme points (i.e. values that extend more than 3 box lengths from the edge of the box. The following points can be observed:

• all three groups have several outlying values and several extreme values for each sample; • the pilot/mixer/loader group has the greatest spread of results; • the highest result recorded among the three groups was for a pre-exposure sample from a

farmer; • farmers’ pre-exposure sample results look very similar to control sample results; • the median value for all three groups and for both pre- and post-exposure samples is zero or

very close to zero.

47

Figure 5.7 Total DAP results for the three groups for their pre-exposure sample and first two post-exposure samples

Farmers Pilot/Mixer/Loaders Controls

Group

0.00

2.00

4.00

6.00

8.00

10.00

12.00

92

34

92

15

33

928610

32

33

73836813

11

3833

738368

11

39

738368

Total DAP sample 1 umol/LTotal DAP first post-exposure sample umol/LTotal DAP 2nd post-exposure sample umol/L

Note: Controls provided one sample only so their results are repeated. The Kruskal-Wallis test, which is the non-parametric alternative to a one-way between-groups analysis of variance (ANOVA), was performed to examine the differences between the three groups. DAP metabolite levels were converted to ranks and each group’s mean rank was compared. There were no significant differences between the three groups for the pre-exposure samples. However, the pilot/mixer/loader group had a higher mean rank score (54.56) than the other two groups (farmers= 45.97 and control=45.73). The same result was found when DMTP levels were compared for pre-exposure samples across the three groups rather than the total DAP metabolite levels. There was a significant (p=0.02) difference between the three groups when the mean post-exposure sample results were compared with the control group’s sample results. Again, the pilot/mixer/loader group had the highest mean rank (59.56) followed by the farmers (49.84) and then the controls (40.86). The Mann-Whitney U test, which is the non-parametric alternative to a t-test, was used to look at the difference between two groups at a time. There were no significant differences between the two exposed groups (farmers and pilots/mixer/loaders) for either the pre-exposure or the post-exposure samples (p=0.20 and p=0.18, respectively). However, the pilot/mixer/loader group had the highest mean rank and therefore the highest levels for both the pre- and post-exposure comparisons. The two exposed groups (farmers and pilots/mixer/loaders) were also examined by creating three groups: farmers, pilots and mixer/loaders, but observed differences were still not significant.

48

A different picture emerged when the various exposure groups were compared to the controls. Using the Mann-Whitney U test, one exposure group at a time was compared to the control group. The difference between the farmers mean post-exposure sample results and the controls’ single sample results was marginally significant (p=0.09). The farmers’ mean rank score was 42.81 and the controls mean rank score was 35.36. There was a large significant difference between the pilot/mixer/loaders’ mean post-exposure sample results and the control group’s single sample results (mean rank = 40.06 and 28.00, respectively; p = 0.01). 5.5 Summary of Results The following points summarise the results presented in this chapter. Farmers’ results

• None of the 32 farmers’ urine samples contained detectable levels of the three diethyl DAP metabolites (DEP, DETP and DEDTP), despite 14 farmers reporting application of only diethyl OP pesticides.

• There were no clear patterns of excretion of metabolites observed for the three samples collected (one pre-exposure sample and two post-exposure samples).

• DMTP was the metabolite most frequently detected with 25% of pre-exposure samples and 31.2% of both the first and second post-exposure samples containing DMTP.

• Farmers’ DAP metabolite levels were typically low with median DMTP concentrations ranging from 18.00 – 29.50 (range: ND-116.00) μmol/mol creatinine.

• Examination of the relationship between detectable levels of DAP metabolites and exposure risk factor data (collected from the self-administered questionnaire) resulted in several non-statistically significant inverse relationships. For example, those farmers who had a high PPE-use score were 3.57 times more likely to have detectable levels of DAP metabolites than those with a low PPE-use score. Therefore, it would appear that those farmers using more PPE were more likely to be exposed, which is the reverse of what would be expected.

• Two risk factors showed positive associations with exposure: spending more time applying (i.e. 2.5 hours+), and eating, drinking, smoking or talking on a phone while applying the pesticide.

• When farmers were divided into three groups (no metabolites detected, low levels detected and higher levels detected), the four with higher levels of detectable DAPs all used a mister/blower/fogger and applied pesticide for longer time periods, and three of the four reported skin contact with OP while applying.

49

Pilots/mixer/loaders results • DMTP was again the metabolite most frequently detected in the pilot/mixer/loader group.

Seven (38.9%) of the participants’ pre-exposure samples, 8 (44.5%) of the first and second post-exposure samples and 9 (50%) of the third post-exposure samples contained detectable levels of DMTP. A total of 13 participants had one or more samples with detectable levels of DMTP.

• Again, type of OP sprayed was not a predictor of the type of metabolites detected (i.e. spraying only diethyl OPs did not produce only diethyl metabolites, etc.).

• Relationships between risk factors for exposure and having detectable DAP levels were as predicted for the pilot/mixer/loader group. For example, those participants with poor PPE use were 1.75 times more likely to have detectable levels than those with better PPE use. Participants who reported breathing in OP pesticide were 5 times more likely to have detectable levels than those who reported not breathing in OP. Performing measuring and mixing tasks was associated with a 3.37 times increased odds of having detectable levels of DAPs, relative to not performing the tasks.

Control group results

• The metabolite DMTP was the only one found in control group samples. • Eleven of the 44 control samples (25%) contained detectable levels of DMTP. • The median level detected for the control group was 35.8 µmol/mol creatinine (range=9.5–

91.3 µmol/mol creatinine). The sample containing 91.3 µmol/mol creatinine belonged to a florist and therefore occupational exposure may have contributed to the higher level observed. The next highest level was 47.7 µmol/mol creatinine.

• Risk factors that were associated with having detectable DAP levels included a higher consumption of fruit and vegetables and not having a home vegetable garden, however these results were not significant and the odds ratios had large confidence intervals.

Comparison between the three groups

• There were no significant differences between the exposed groups’ (farmers and pilots/mixer/loaders) pre-exposure sample results and the control group’s single sample results. Similarly, there was no difference between the farmers’ mean post-exposure results and the control group’s single sample results.

• There was a significant difference between the pilots/mixer/loaders’ mean post-exposure sample results and the controls’ single sample results.

• There was no significant difference between the two exposed groups (farmers and pilots/mixer/loaders) for either the pre- or post-exposure samples. However, the pilot/mixer/loader group had consistently higher levels of DAP metabolites than the farmers and controls.

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6. Formulator Plant Workers’ Biological Sample Results 6.1 Formulation Plant Worker Sample One formulation plant, situated in NSW, participated in the research project. The plant formulates several OP pesticides including an Agvet product called Rametin, which is a diethyl phosphate pesticide (i.e. will metabolise into diethyl DAPs). Twice a year staff working at the plant undergo routine health surveillance testing that includes blood cholinesterase analysis as well as other health-related blood tests. All 57 staff members routinely tested in May 2004 were invited to participate in this study either as an exposed or control participant. Twenty staff members - 9 (3 females and 6 males) of the Rametin exposed workers and 11 controls (4 females and 7 males) - provided urine and blood samples, and completed a questionnaire. The response rate for the exposed group was 90% (9/10) and for the control group it was 23.4% (11/47). 6.2 Exposed Workers’ Urine DAP Metabolite Results The 9 participants in the exposed group worked in the area where Rametin was being formulated. The formulation run occurred during the week of the 3-7 May 2004 and again on Monday 10 May 2004. Each of the exposed participants collected pre- and post-shift urine samples on the days they were working with Rametin either as a formulator (n=3) or a packer (n=6). Participants were asked to collect samples the day after they finished working with Rametin, but as this was a weekend for most staff, unfortunately these samples were not collected. Two participants provided 6 urine samples that were collected pre- and post-shift for three days and 7 participants provided 8 urine samples collected pre- and post-shift for four days. Table 6.1 presents the median and range values for samples that contained detectable concentrations of DAP metabolites for the exposed group.

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Table 6.1 Urine DAP metabolite results for formulator Staff exposed to Rametin (μmol/mol creatinine)

DAP Metabolite and sample Number of

samples >ND1



DMTP2 1st Pre-shift sample 3 13.20 – 36.70 25.20 1st Post-shift sample 1 - 11.60 2nd Pre-shift sample 3 14.30 – 36.50 18.60 2nd Post-shift sample 4 17.30 - 29.50 22.65 3rd Pre-shift sample 2 16.60 – 27.90 22.25 3rd Post-shift sample 2 27.60 – 32.20 29.90 4th Pre-shift sample 1 - 17.50 4th Post-shift sample 0 - -

DEP2 1st Pre-shift sample 1 - 125.00 1st Post-shift sample 1 - 53.40 2nd Pre-shift sample 3 85.70 – 167.20 96.40 2nd Post-shift sample 4 55.7 – 550.00 123.00 3rd Pre-shift sample 2 50.00 – 212.00 131.00 3rd Post-shift sample 4 106.00 – 472.00 149.00 4th Pre-shift sample 1 - 54.00 4th Post-shift sample 1 - 97.30

DEDTP2 1st Pre-shift sample 0 1st Post-shift sample 0 2nd Pre-shift sample 0 2nd Post-shift sample 0 3rd Pre-shift sample 0 3rd Post-shift sample 1 - 22.50 4th Pre-shift sample 0 4th Post-shift sample 0

1not detected 2Detection limits: DEP 0.7μmol/L (100 ppb) DMTP and DMDTP 0.2 μmol/L (25 ppb). Note: Creatinine corrected detection limits for a urine sample with 1g/L (0.010mol/L) creatinine are: DEP 70 μmol/mol creatinine; DMTP and DMDTP 20 μmol/mol creatinine.

52

The two most commonly detected metabolites were DMTP and DEP, with DEDTP being detected in one sample only. DEP was detected at the highest concentrations with maximums from 167.20-550.00 μmol/mol creatinine. Rametin is a diethyl phosphate pesticide and will therefore metabolise into diethyl DAPs only. Tables 6.2 and 6.3 present individual results for the two main metabolites detected, DEP and DMTP, respectively. Figures 6.1 and 6.2 graphically present the same results. Results are only presented for those participants with one or more samples with detectable levels. Table 6.2 Formulator plant exposed group DEP metabolite results (μmol/mol creatinine)

1st Shift 2nd Shift 3rd Shift 4th Shift

Pre Post Pre Post Pre Post Pre Post

Formulator 1 ND1 ND1 85.7 55.7 50.0 ND1 ns2 ns2

Formulator 2 125.0 53.4 96.4 550.0 ND1 472.0 ns2 ns2

Formulator 3 ND1 ND1 167.0 143.0 212.0 157.0 54.0 97.3

Packer 1 ND1 ND1 ND1 ND1 ND1 106.0 ND1 ND1

Packer 2 ND1 ND1 ND1 103.0 ND1 141.0 ND1 ND1 1 not detected 2 no sample provided Note: Results presented for participants with detectable levels only. Table 6.3 Formulator plant exposed group DMTP metabolite results (μmol/mol creatinine)

1st Shift 2nd Shift 3rd Shift 4th Shift Participant

Pre Post Pre Post Pre Post Pre Post

Formulator 2 36.7 11.6 36.5 23.6 27.9 32.2 ns2 ns2

Formulator 3 13.20 ND1 18.6 21.7 ND1 ND1 ND1 ND1

Packer 3 ND1 ND1 ND1 29.5 ND1 ND1 ND1 ND1

Packer 4 ND1 ND1 14.3 17.3 16.6 27.6 17.5 ND1

Packer 5 25.2 ND1 ND1 ND1 ND1 ND1 ND1 ND1 1 not detected 2 no sample provided Note: Results presented for participants with detectable levels only.

53

0

100

200

300

400

500

600

1 2 3 4 5 6

Sample (pre- post-shift sequence)

DEP

umol

/mol

cre

atin

ine

Figure 6.1 Urine DEP concentrations for formulator plant exposed group

Note: Results presented for participants with detectable levels only. In Figure 6.1 two patterns of metabolite excretion can be seen. Two workers’ results (maroon and dark green lines) generally are low for the pre-shift samples and high for the post-shift samples. The pattern of excretion for another two workers is the reverse (light blue and aqua lines) the pre-shift levels are higher than the post-shift levels. The fifth worker had only one sample with a detectable result for DEP and the remaining four participants had no detectable results for DEP. No clear patterns of excretion are seen for the metabolite DMTP, as illustrated in Figure 6.2.

54

0

5

10

15

20

25

30

35

40

1 2 3 4 5 6

Sample (pre- post-shift sequense)

DMTP

um

ol/m

ol c

reat

inin

eFigure 6.2 Urine DMTP concentrations for formulator plant exposed group Note: Results presented for participants with detectable levels only. The 9 exposed workers who supplied urine samples were categorised into two groups based on whether they had any samples with detectable concentrations of diethyl DAP metabolites. A categorical variable was used instead of the continuous total DAP metabolite variable because of the small sample size and the non-normal distribution of results. Presence of diethyl DAPs was chosen because the participants were working exclusively with Rametin, which only produces diethyl DAPs. This variable was used to examine the relationship between OP exposure, defined as one or more samples containing detectable metabolite/s, and various potential occupational risk factors (e.g. job, duration of exposure and tasks completed). A PPE-use score was not calculated because all staff wore nearly all items of PPE provided for their use; however, gloves were not worn by 3 people so use of gloves was examined as a risk factor. One question asked whether or not PPE items were removed during the shift and this variable was also used to assess risk based on PPE use. Crude odds ratios with their corresponding 95% confidence intervals were calculated via binary logistic regression to investigate the relationships between having detectable diethyl DAP metabolites and various potential occupational risk factors (Table 6.4). None of the risk factors had a significant relationship with the dependent variable (detectable diethyl metabolites). However, the cross tabulations reveal that job type was the best predictor of exposure by far. The 3 formulators all had detectable levels of diethyl DAP metabolites whereas only 2 of the 6 packers had detectable levels. All 3 formulators also worked overtime during sample collection. All three formulators and two packers spilled the OP on themselves. Four out of the five workers who spilled OP on their overalls had detectable DAP metabolite levels while only 1 of the 4 workers who did not spill OP had detectable levels. The odds of having detectable levels of diethyl metabolites were 12 times higher for those who spilled OP relative to those who did not. However, the range of the 95% confidence interval was very large (0.51-280.1) due to the small sample size. The formulators with the very highest levels and the second highest levels spilled OP on themselves and did not change clothes until the end of the shift. The other formulator changed his clothes after

55

finishing the task he was working on when the OP was spilled. However, of the two packers who spilled OP, the one with the highest levels changed after finishing the task and the one with no level changed at the end the shift. Of course the amount spilled in each case is not known. Environmental exposure was also examined with the formulator plant exposed group as they completed a short environmental exposure questionnaire similar to that completed by the Toowoomba Rotary Club control group and the formulator plant control group. Crude OR were calculated using the dichotomous variable exposed to dimethyl DAPs (yes/no) and the various potential environmental risk factors. None of the risk factors were significant; however, consuming more than 4.5 servings of fruit and vegetables per day and being younger (i.e. 21-41 years) were associated with a 4.5 times increased odds of having detectable metabolites (Table 6.5).

56

Table 6.4 Relationships between exposure, measured as detectable DAP metabolites, and various occupational risk factors for the exposed group (n=9)

Detectable levels of diethyl DAP

Risk factor

Category

Yes No

Crude OR

95% CI

p

packer 2 4 Job formulator 3 0

unable to compute

no 2 4 Worked overtime during sample collection

yes 3 0 unable to compute

11-14 hours 2 2 1.00 Number of hours worked with OP 15-29 hours 1 2 0.50 0.02-11.19 0.66

no 2 1 1.00 Removed PPE during work with OP yes 3 3 0.50 0.03-8.95 0.64

no 3 4 Used mobile phone at work yes 2 0

unable to compute

no 2 2 1.00 Smoked during shifts yes 3 2 1.50 0.11-21.31 0.77 no 0 0 Stopped to have a

drink yes 5 4 unable to compute

yes 4 3 1.00 Washed hands before going to toilette no 1 1 1.33 0.06-31.12 0.86

no 2 1 1.00 Breathed in OP during shifts yes 3 3 0.50 0.03-8.95 0.64

no 3 4 Got OP on skin yes 2 0

unable to compute

no 1 3 1.00 Spilled OP on overalls yes 4 1 12.00 0.51-280.1 0.12

straight after shift 4 2 1.00 Bathed and changed clothes later 1 2 0.25 0.01-4.73 0.36

yes 4 2 1.00 Used gloves no 1 2 0.25 0.01-4.73 0.36

57

Table 6.5 Relationships between detectable metabolites (yes/no), and various environmental risk factors for the exposed group (n=9)

Detectable levels of diethyl DAPs

Risk factor

Category

Yes No

Crude OR

95% CI

p

female 2 1 1.00 Gender

male 3 3 0.50 0.03-8.95 0.64

no 4 3 Partners occupation involves contact with

pesticides yes 0 0

unable to compute

no 4 4 Contact with farm during

last 5 days yes 1 0 unable to compute

yes 0 0 Home vegetable garden no 5 4

unable to compute

no 3 2 1.00 Home has a garden yes 2 2 0.67 0.05-9.47 0.76 no 4 3 1.00 Ornamental plants kept in

home yes 1 1 0.75 0.03-17.51 0.86 no 4 3 1.00 Brought cut flowers in

house last 3 days yes 1 1 0.75 0.03-17.51 0.86 no 2 1 1.00 Domestic animals kept in

house yes 3 3 0.50 0.03-8.95 0.64 no 0 0 Pet in house receives

flea/tick treatment yes 3 3 unable to compute

no 3 2 1.00 Use pesticides in house yes 2 2 0.67 0.05-9.47 0.76 no 3 2 1.00 Use pesticides outside

house yes 2 2 0.67 0.05-9.47 0.76 no 4 4 Professional domestic

pest treatment in last month yes 1 0

unable to compute


2 3 1.00 Fruit and veg consumed per day on average

high number of servings (4.5-7)

3 1 4.50 0.25-80.57 0.31

44-55 years old 2 3 1.00 Age 21-41 years old 3 1 4.50 0.25-80.57 0.31

58

6.3 Control Group Urine DAP Metabolite Results The 11 control group participants were plant staff who did not have direct contact with the formulation of any OP pesticides, for example, office staff, health and safety personnel and managers. Three formulators were also included in the control group because they have no contact with the formulation of OP pesticides. The controls each provided one urine sample and one blood sample for analysis. Of the 11 urine samples, 6 contained detectable levels of DAP metabolite. The only detectable metabolite was DMTP, with a median concentration of 25.00 μmol/mol creatinine (range: 17.20-57.30 μmol/mol creatinine). 6.3.1 Relationships between detectable DMTP levels and exposure risk factors The 11 control group participants completed a self-administered questionnaire similar to that completed by the Toowoomba control group participants. Chi-square and binary logistic regression analyses were performed to examine the relationship between detectable DAP metabolites and risk factors. No significant results were found (Table 6.4), however the sample was very small. Three non-statistically significant increased odds of having detectable levels of DMTP were observed; being male; consuming higher amounts of fruit and vegetables the day before and the day of sample collection; and being older than 41. Due to the small sample size, the 95% confidence intervals surrounding the odds ratios were very large (e.g. 0.5-127.9), therefore caution should be taken in interpreting the results.

59

Table 6.6 Relationships between detectable metabolites (yes/no), and various environmental risk factors for the formulator plant control group (n=11)

Detectable levels of DMTP

Risk factor

Category

Yes No

Crude OR

95% CI

p

female 1 3 1.00 Gender

male 5 2 7.50 0.46-122.7 0.16

no 4 2 1.00 Contact with pesticides as part of job

yes 2 3 0.33 0.03-3.93 0.38 no 6 3 Partners occupation

involves contact with pesticides yes 0 0

unable to compute

no 6 4 Contact with farm during

last 5 days yes 0 1 unable to compute

yes 2 1 1.00 Home vegetable garden no 4 4 0.50 0.03-8.00 0.62 no 2 0 Home has a garden yes 4 5

unable to compute

no 4 3 1.00 Ornamental plants kept in home yes 2 2 0.75 0.06-8.83 0.82

no 6 5 Brought cut flowers in house last 3 days yes 0 0

unable to compute

no 2 1 1.00 Domestic animals kept in house yes 4 4 0.50 0.03-8.00 0.62

no 0 1 Pet in house receives flea/tick treatment yes 4 3

unable to compute

no 2 0 Use pesticides in house yes 4 5

unable to compute

no 1 1 1.00 Use pesticides outside house yes 5 4 1.25 0.06-26.87 0.89

no 6 4 Professional domestic pest treatment in last

month yes 0 1

unable to compute


2 2 1.00 Fruit and veg consumed day before sample

collection high number of servings (4-6)

4 3 1.33 0.11-15.70 0.82


3 4 1.00 Fruit and veg consumed day of sample collection

high number of servings (3-5)

3 1 4.00 0.26-60.32 0.32

20-41 years old 2 4 1.00 Age 42-60 years old 4 1 8.00 0.50-127.9 0.14

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6.4 Comparison of Urine DAP Metabolite Levels between Formulator Plant Exposed Participants and Controls Two comparisons were made between the urinary DAP metabolite levels found for the exposed and control groups. Firstly, total DAP metabolite exposure from the control group’s single samples were compared with the exposed group’s pre-exposure sample results. Secondly, mean DAP metabolite levels for the exposed group’s post-exposure samples were compared with the control group’s single sample results. The DAP metabolite levels were not normally distributed. Therefore, the Mann-Whitney U test, which is the non-parametric alternative to a t-test, was used to look at the differences between the two groups. There were no significant differences between the two groups DMTP levels for either the pre-exposure or post-exposure samples (p=0.34 and p=0.72, respectively). DMTP levels were compared as an indicator of environmental exposure as Rametin does not metabolise into DMTP. None of the control group participants had detectable levels of the metabolite DEP (occupational exposure indicator), therefore unsurprisingly there was a significant difference (p=<0.01) between the exposed group’s mean post-exposure DEP levels and the control group’s levels. 6.5 Blood Cholinesterase Test Results All 20 formulator plant workers provided one blood sample for analysis on 6th May 2004, which was toward the end of the Rametin formulation run. The samples were analysed for their plasma cholinesterase activity and their erythrocyte cholinesterase activity. The detection limit for this analysis was 0.2 kU/L. Results should be referenced against an individual’s baseline values; however, the formulation plant did not have baseline activity levels for their employees. If baseline values are not known, the approximate depression in cholinesterase is calculated using the lower limit of the normal population range. The normal population ranges for the NSW Laboratory test method are as follows: Plasma Cholinesterase: 5.4 – 10.9 kU/L and Red Blood Cell Cholinesterase: 9.6 – 17.7 kU/L. As discussed in Chapter 2, other factors besides exposure to cholinesterase inhibitors, such as gender and illnesses, can influence a person’s red blood cell and plasma cholinesterase levels. 6.5.1 Blood cholinesterase test results for exposed group Two of the formulators’ plasma cholinesterase levels were below the normal population range and one of the packer’s plasma levels was close to the bottom of the normal range. The two formulators who had depressed plasma cholinesterase levels had levels slightly above the bottom end of the normal range for red blood cell cholinesterase. A third formulator’s red blood cell level was depressed compared to the normal population range, and his plasma level, although in the normal range, was very close to the bottom. Three of the packing staff had depressed RBC cholinesterase levels and one was borderline. Overall 6 of the 9 exposed group participants had at least one of the cholinesterase levels below the normal population range and 2 others were borderline (Table 6.7). All 3 exposed female workers had depressed or borderline values for one of the two cholinesterase test results, while 5 out of 6 of the male exposed workers had depressed levels for one of the two test results. 6.5.2 Blood cholinesterase test results for the control group One control group participant had depressed plasma cholinesterase levels in relation to the normal population range. Two other participants had levels that were close to the bottom end of the normal range for plasma cholinesterase. All three of these participants who had depressed or close-to-depressed plasma levels had normal red blood cell levels. One participant had depressed red blood cell cholinesterase levels and two had levels that were borderline. Two out of 11 participants had a single depressed level and 4 had one level that was borderline (Table 6.8). Among the 4 female controls, 1 had a depressed level and 1 had a borderline level, among the 7 male controls, 1 had a depressed level and 3 had a borderline level.

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Table 6.7 Formulator plant exposed group blood cholinesterase test results

Job Gender PsChE kU/L

RBC ChEkU/L

PcChE below normal

population (yes/no)

RBC ChE below normal

population (yes/no)

Formulator male 4.0 10.4 yes no Formulator male 5.2 9.8 yes no Formulator male 5.8 9.5 no yes Packer male 5.9 9.0 no yes Packer male 7.3 9.1 no yes Packer male 8.5 12.6 no no Packer female 5.6 11.3 borderline no Packer female 5.7 9.4 no yes Packer female 6.7 9.6 no borderline Table 6.8 Formulator plant control group blood cholinesterase test results

Job Gender PsChE kU/L

RBC ChEkU/L

PcChE below normal

population (yes/no)

RBC ChE below normal

population (yes/no)

Formulator male 6.2 11.3 no no Formulator male 8.5 8.0 no yes Formulator female 5.6 11.0 borderline no Maintenance staff male 6.2 9.7 no borderline Manager male 8.0 9.7 no borderline Manager male 8.9 9.9 no no Manager female 7.8 11.2 no no Packer male 8.2 11.7 no no Supervisor female 8.6 12.6 no no Laboratory staff male 5.5 11.8 borderline no Laboratory staff female 4.9 11.2 yes no

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6.5.3 Comparison between the two Groups’ blood cholinesterase levels The Mann-Whitney U test was used to compare the PsChE and RBC ChE results for the exposed and control groups. There were no significant differences between the two groups (PsChE p= 0.16, RBC ChE p= 0.14). However, the control group had the highest mean rank score for both blood cholinesterase levels, indicating that the exposed group had the lowest/most depressed levels on average (Table 6.9). Table 6.9 Comparison between exposed and control formulator plant groups’ blood cholinesterase test results

PsChE level (kU/L) RBC ChE level (kU/L) Group Mean (+ SD)

Median (range)

Mean (+ SD)

Median (range)

Exposed 6.08 (1.29) 5.80 (4.00-8.50) 10.08 (1.18) 9.60 (9.00-12.60)

Controls 7.13 (1.46) 7.80 (4.90-8.90) 10.74 (1.29) 11.20 (8.00-12.60)

6.6 Relationship between Urine DAP Metabolite Levels and Blood Cholinesterase Levels Spearman’s rho was used to examine the correlation between blood cholinesterase and urine DAP test results for the exposed and control groups. Spearman’s Rank Order Correlation was used as the non-parametric alternative to Pearson’s product-moment correlation. Non-parametric analyses are used when data is non-normally distributed and involves small sample sizes as is this case with this data. There were no statistically significant relationships between the control group participants’ blood cholinesterase test results and their total dimethyl DAP urine test results collected on the same day (Figures 6.3 and 6.4). Similarly, there were no significant relationships between RBC ChE or PsChE test results and exposed group participants’ urine DAP test results examined separately for total dimethyl DAP and total diethyl DAP. However, examination of scatter plots for the PsChE and urine level results revealed a slight negative relationship between the two (see Figures 6.5, 6.6, 6.7 and 6.8). Table 6.10 presents the results of all correlation analyses.

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Table 6.10 Correlation between urine DAP levels and red blood cell and plasma cholinesterase levels

PsChE RBC ChE Group Total dimethyl DAP Total diethyl DAP Total dimethyl

DAP Total diethyl DAP

Controls p=0.29, r= -0.35 p= 0.76, r = 0.11

Exposed p=0.18, r= -0.49 p=0.18, r= -0.49 p=0.35, r= 0.36 p= 0.76, r= 0.12

Figure 6.3 Scatter plot of PsChE level and total dimethyl DAP level for controls

0.00 0.10 0.20 0.30 0.40 0.50

Total Dimethyl DAP umol/L

4.0

5.0

6.0

7.0

8.0

9.0

Blo

od P

lasm

a C

holin

este

rase

Lev

el k

U/L

64

Figure 6.4 Scatter plot of RBC ChE level and total dimethyl DAP Level for controls

0.00 0.10 0.20 0.30 0.40 0.50

Total Dimethyl DAP umol/L

8.0

9.0

10.0

11.0

12.0

13.0

Red

Blo

od C

ell C

holin

este

rase

Lev

el k

U/L

Figure 6.5 Scatter plot of PsChE level and total diethyl DAP level for exposed group

0.00 5.00 10.00 15.00 20.00 25.00

Total Diethyl DAP Level umol/L

4.0

5.0

6.0

7.0

8.0

9.0

Blo

od P

lasm

a C

holin

este

rase

Lev

el k

U/L

65

Figure 6.6 Scatter plot of PsChE level and total dimethyl DAP level for exposed group

0.00 0.50 1.00 1.50 2.00 2.50 3.00

Total dimethyl DAP level umol/L

4.0

5.0

6.0

7.0

8.0

9.0

Blo

od P

lasm

a C

holin

este

rase

Lev

el k

U/L

Figure 6.7 Scatter plot of RBC ChE level and total diethyl DAP level for exposed group

0.00 5.00 10.00 15.00 20.00 25.00

Total Diethyl DAP umol/L

9.0

10.0

11.0

12.0

13.0

Red

Blo

od C

ell C

holin

este

rase

Lev

el k

U/L

66

Figure 6.8 Scatter plot of RBC ChE Level and total dimethyl DAP level for exposed group

0.00 0.50 1.00 1.50 2.00 2.50 3.00

Total dimethyl DAP umol/L

9.0

10.0

11.0

12.0

13.0

Red

Blo

od C

ell C

holin

este

rase

Lev

el k

U/L

67

6.7 Summary of Results The following points summarise the results presented in this chapter. • Of the 9 exposed formulation plant workers (3 formulators and 6 packers), 5 had detectable

levels of the metabolite DEP. The concentrations ranged from undetectable to 550.00 µmol/mol creatinine and median concentrations ranged from 53.40 to 149.00 µmol/mol creatinine.

• Two of the 3 formulators from the exposed group had high levels (i.e. > 100 µmol/mol creatinine) for more than half of the samples they provided.

• DMTP was also detected in the exposed formulation plant workers samples despite it not being a metabolite of Rametin (the pesticide being formulated).

• Two risk factors for exposure were positively associated with having detectable levels of DEP - being a formulator as opposed to a packer and spilling OP on one’s overalls - but statistical power was limited and neither result was significant.

• Consuming a higher number of servings of fruit and vegetables was associated with having detectable levels of the metabolite DMTP, but again this was not significant.

• Of the 11 control group urine samples, 6 contained detectable levels of the metabolite DMTP, with a median of 25 µmol/mol creatinine (range: 17.2-57.3 µmol/mol creatinine).

• For the control group, three environmental risk factors were associated with having detectable levels of DMTP (being male, consuming higher amounts of fruit and vegetables the day before and the day of sample collection, and being older than 41), but these were not significant.

• There were no significant differences between exposed and control group levels of DMTP for pre- and post-exposure samples.

• There was a significant difference between exposed and control group levels of DEP. • Six of the 9 exposed workers had at least one depressed cholinesterase level and 2 others were

borderline. • Two of the 11 controls had one depressed cholinesterase level and 4 others were borderline. • There was no significant difference between exposed and control group cholinesterase levels. • There were no significant relationships between total urine dimethyl or diethyl DAP levels for

the control and exposed groups and their blood cholinesterase levels (plasma or RBC).

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7. Discussion 7.1 Summary of Major Research Findings 7.1.1 Fruit and vegetable farmers The results of the interviewer-administered questionnaire were not presented in this report as they were part of larger QUT PhD thesis project. However, the main findings from the interview-administered questionnaire are provided here for discussion purposes. For further information about the interview-administered questionnaire please contact the author. A total of 51 fruit and vegetable farmers participated in the in-depth, interviewer-administered questionnaire. The participant farmers were drawn from farming areas surrounding Brisbane with more than half coming from the Laidley/Lowood and Gatton to Toowoomba areas. The participants were similar, based on two characteristics, to the other approximately 500 fruit and vegetable farmers in the selected study areas. The participant group was characterised by small owner-operator farmers who often had sole or primary responsibility for pesticide application. OP pesticide use among the group was generally infrequent and was performed mainly via boom application on the back of a tractor. Participants had good knowledge of pesticide-related safety precautions and more than three-quarters had completed the nationally accredited, chemical user course (ChemCert). Despite having high knowledge levels, use of PPE was not in compliance with pesticide label directions, with more than half of the farmers reporting infrequent use of respiratory protection, gloves and overalls. An exploration of the attitudes and beliefs toward PPE use showed that almost half of the farmers believed that wearing PPE during the warmer months was too hot and uncomfortable. Those farmers who reported good attitudes and beliefs toward the use of PPE were more likely to wear appropriate clothing and equipment. More than half of the participants indicated that they were concerned about their level of exposure to OP pesticides and most farmers agreed that exposure may result in long-term health effects. Farmers were not concerned about short-term health effects and very few reported experiencing any acute, short-term symptoms related to exposure. More than half of the farmers reported rarely or only sometimes reading OP pesticide labels. Very few ever read MSDSs for OP pesticides and there appeared to be an issue with the provision of MSDSs by suppliers. Very few farmers had any knowledge of formal risk assessment processes and the majority of farmers had never had any health surveillance completed. Analysis of the 32 sets of urine samples collected from the fruit and vegetable farmers revealed that DAP metabolite levels were generally low. None of the farmers’ samples contained detectable levels of the diethyl DAPs, despite almost half of the farmers reporting application of diethyl OPs. No clear pattern of excretion of DAP metabolites was observed in the farmers group. The metabolite most frequently detected was DMTP. An unexpected, inverse relationship with PPE use was observed (i.e. those farmers with better PPE use had increased odds of having detectable metabolite levels). Spending more time applying, using a mister/blower/fogger, and eating, drinking, smoking or talking on a phone while applying OP pesticides, were each associated with increased odds of having detectable metabolite levels. Pre-application DAP metabolite results for the farmers’ group indicate that there are measurable background exposures to OP pesticides and levels among community controls suggest the presence of environmental DAPs. Therefore, occupational exposure to OP pesticides may not be the main contributor to urine DAP metabolite levels among these farmers. 7.1.2 Pilots/mixer/loaders Seven aerial applicator companies from Southern Queensland and Northern New South Wales participated in the study. The urine DAP levels detected in this group were higher, on average, than

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those found in the farmers’ group, although there were no significant differences between the groups. The levels found in the pilot/mixer/loader group were higher than the control group’s samples and the difference was significant. DMTP was again the metabolite most frequently detected. Type of OP pesticide sprayed (i.e. diethyl or dimethyl OP) was not a predictor of type of metabolites observed. Poorer PPE use was associated with slightly increased odds of having detectable levels of metabolites, although this association was not significant. Breathing in OP pesticide and performing measuring and mixing tasks were also associated with increased chances of having detectable metabolite levels; however, again, these associations were not significant. 7.1.3 Formulators One New South Wales formulation plant participated in the research project with 9 exposed and 11 unexposed workers providing urine and blood samples and completing a questionnaire. The exposed formulation plant workers had the highest post-exposure DAP metabolite levels of all three exposure groups studied. DMTP was detected in the exposed group samples at similar levels to the control groups; this dimethyl metabolite was detected despite the group working only with a diethyl OP. Being a formulator as opposed to a packer and reporting OP spillage on overalls were associated with increased odds of having detectable levels, although the associations were not significant. More than half of the exposed workers had one or more of their cholinesterase levels depressed, however there were no observed associations between depressed cholinesterase levels and urine DAP metabolite levels. 7.1.4 Controls Both the Toowoomba community controls and the sample of workers in the formulation plant employed in non-exposure jobs had low urine DAP levels, with DMTP being the only metabolite detected. Consumption of a higher number of servings of fruit and vegetables and not having a home vegetable garden were associated with increased odds of detectable metabolite levels, however the associations were not significant. 7.2 Farmers’ OP Pesticide-Handling Practices Use of PPE is a key control measure or safe pesticide handling practice for mixing and application. PPE protects wearers at the points of potential absorption. Although PPE is considered to be at the bottom of the ‘Hierarchy of Control’, when working with toxic pesticides such as OPs there are not many other control options. All OP pesticide labels and MSDSs stipulate the use of at least minimum PPE, such as long-sleeved shirts and long pants, and for more toxic OPs, more protection is required such as respirators and gloves. A number of Australian and international researchers have investigated the beliefs, attitudes and knowledge of farmers in relation to the use of PPE and have identified several barriers to its use, including time constraints, economic considerations, poor design of equipment, and comfort issues particularly in hot climates (Cassell and Day, 1998, Gomes et al., 1999, Sandall, 2000). In this study the farmers’ interviewer-administered questionnaire collected data about these key issues. Participant farmers generally did not view time and economic issues as barriers to the use of PPE; 86.3% of farmers reported that they disagreed with the statement “I don’t have enough time to wear personal protective equipment when using pesticides” and 96.1% disagreed with the statement “Personal protective equipment is too expensive for me to purchase”. However, one of the main issues with PPE was the discomfort of use, with just under half of the farmers (41.2%) believing that PPE was too hot and uncomfortable to wear during the warmer months. According to the Australian Bureau of Meteorology, the mean daily temperatures measured at the weather station in Gatton, Queensland, during the summer months (December – February) range from 30.6-31.0 0C, with maximums ranging from 41.9-44.0 0C (http://www.bom.gov.au/climate/averages/tables/cw_040436.shtml, accessed 10th September 2005). In these types of temperatures it is not surprising that farmers find it too uncomfortable to wear PPE while applying OPs. The issue of PPE being uncomfortable and cumbersome has been reported elsewhere in the literature (Damalas et al., 2006, Yassin et al., 2002, Perry et al., 2002, Cassell, and Day, 1998). By far the main reason for not using PPE during pesticide

http://www.bom.gov.au/climate/averages/tables/cw_040436.shtml

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application reported by Greek tobacco farmers was that the ‘equipment was uncomfortable’ (Damalas et al., 2006). The finding of discomfort of PPE is not isolated to agricultural workers; studies of other industries have reported similar beliefs (Akbar-Khanzadeh et al., 1995, Abeysekera and Shahnavaz, 1990, Akbar-Khanzadeh, 1998). A study of 366 metal refining plant works reported that the most frequently cited factors contributing to discomfort or dissatisfaction of wearing PPE were related to the workers’ beliefs that the PPE was not needed, created a new hazard, interfered with work, was too heavy, was hard to wear, prohibited breathing or communicating, irritated skin, put pressure on the body, and was of an undesirable type or model (Akbar-Khanzadeh, 1998). The difference between other industries and farmers is that farmers are usually owner-operators and can chose whether or not they wear PPE were as other workers are employees and PPE use is often enforced as a mandatory safety requirement. In addition to the comfort factor some farmers (20%) in the current study reported believing “As long as you are careful when handling OP pesticides, it is not necessary to wear personal protective equipment such as a mask, gloves and overalls” and “Wearing personal protective equipment such as gloves and a mask is cumbersome, interferes with your work, and is more dangerous than not wearing the equipment”. Mekonnen and Agonafir (2002) also found data supporting this idea that farmers consider being careful when using pesticides as being more important than the use of PPE. Other barriers to more extensive use of PPE, verbalised by farmers during questionnaire administration, included concerns that residents in neighbouring homes would complain to the EPA or other authorities because, when wearing full PPE farmers are very conspicuous (they look like “an astronaut in a space suit”) and they “look like they must be spraying a poisonous chemical”. These types of beliefs were more pronounced in farming areas being encroached by residential development, such as the Redland Shire, Tambourine Mountains and Rochdale areas. Although most participant farmers wore some type of PPE while mixing and applying OP pesticides, PPE usage tended to be inadequate for compliance with MSDSs and OP pesticide label requirements. Disturbingly, more than half of the farmers reported never, rarely or only sometimes using a mask/respirator (56%) or gloves (54%) while mixing OP pesticides, a task that poses the highest level of risk because of potential exposure to concentrated pesticide. Approximately 65% of the respondents did not wear any type of overalls while mixing or applying. If farmers do not perceive time constraints and economic concerns to be barriers to the use of PPE, then it appears that issues such as comfort, the design of equipment (i.e. PPE interfering with safe use of pesticides) and concerns regarding neighbours, etc. play an important role in preventing them from using the equipment. Various studies have shown that while farmers generally have high levels of knowledge of pesticide health effects and the benefits of PPE usage, this knowledge does not translate into a high use of PPE (Cassell and Day, 1998, Elmore, 2001, Kishi, 2002, Yassin et al., 2002). This study showed a relationship between higher knowledge and a higher use of PPE while mixing; however, all farmers in the study scored very well on the knowledge scale with the median number of questions answered correctly being 12 out of 13 (range: 8-13). Despite this high level of knowledge, half of the farmers still did not use the required PPE when mixing and applying. The concept of farmers’ having knowledge about the need to wear PPE was further illustrated when they were asked to rate their risk from exposure to OP pesticides. Farmers who indicated that they believed they were at a higher risk of exposure to OP pesticides had a lower use of PPE and vice versa. During administration of the questionnaire, farmers would often remark to the effect that even though they knew that they should wear PPE they still didn’t wear it and therefore their exposure risk was higher.

7.3 Farmers’ Knowledge and Use of Risk Assessment Techniques The Queensland Workplace Health and Safety legislation requires employers to conduct a risk assessment of their and their employees’ exposure to hazardous substances as part of the risk management process. OP pesticides are a ‘schedule 6’ substance for which specific health surveillance must be provided if the results of a risk assessment show a ‘significant’ degree of risk. As previously

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explained, the rural industry is currently exempt from complying with the requirements concerning hazardous substances, including risk assessments and health surveillance. One of the objectives of this research was to asses the feasibility of removing the rural exemption, including how well the industry could comply with the requirements for risk assessments. Therefore, one of the sections in the interviewer-administrated questionnaire concerned farmers’ knowledge and use of formal risk assessment techniques as required by the legislation. Results showed that only 13 farmers (25.5%) had ever read about or been shown how to perform a risk assessment of their or their employees exposure to OP pesticides. Only 4 farmers had performed a risk assessment and 3 of them had done so as part of a training course. Research conducted with Irish farmers found that the levels of risk assessment and implementation of control measures were lower for farmers compared to other rural and urban workers (Hope, 1999). The farmers reported that fear of litigation as a result of writing down what was wrong with the farm and doubting the effectiveness of getting people to change behaviours were barriers to performing risk assessments (Hope, 1999). The prescribed risk assessment process involves consideration of the need to perform health surveillance, which for OPs includes a blood cholinesterase test. However, health surveillance is only required if the risk is assessed as ‘significant’. In the case of farmers’ use of OP pesticides, it may be more advisable to conduct biological monitoring such as urine DAP metabolite testing as part of the risk assessment process rather than as a result of a risk assessment. Information obtained from the biological monitoring would reveal elevations in DAP metabolite levels, indicating directly to a farmer that his/her risk of further exposure and/or health effects is real and that actions may need to be taken to reduce exposure. The majority of farmers (90.2%) reported that they had never undergone health surveillance for exposure to OP pesticides. Given the difficulties associated with the blood cholinesterase test, such as its insensitivity to low level exposures, its invasiveness and the potential difficulty of accessing a designated doctor3, this finding is not surprising. In addition to these drawbacks it was obvious that many participating farmers did not know they could have a blood test done to assess their exposure to OP pesticides. In order to complete a formal risk assessment of exposure to OPs, an MSDS for each pesticide used must be obtained along with information from the label. An MSDS provides important information about the safe storage and handling of substances as well as first aid and emergency information and should be used during the risk assessment process. Nearly half of the farmers (48%) reported that their chemical supplier did not provide them with MSDSs, despite this provision being a legislative requirement under the Workplace Health and Safety Regulation 1997. Other farmers (38%) reported that they were only given an MSDS by their supplier when they asked for it. Despite the fact that 40 farmers (78.4%) had completed the ChemCert training course, which provides discussion of safety issues such as PPE use, and reading and interpreting of an MSDS and pesticide labels, many farmers had to be given an explanation of what an MSDS was. Given this unfamiliarity, it is feasible that some farmers may have received MSDSs from their supplier but not known what they were. Regardless of the reason, it is of concern that nearly half of the farmers reported that they did not have MSDSs for the OP pesticides they store and use. Although all but 4 farmers reported that they had never completed a formal risk assessment, it was obvious that most farmers had considered the risks associated with the use of OPs and had implemented some controls to reduce exposures. For example, as mentioned above, 78% of farmers had completed the ChemCert course, 35% used an enclosed cab while applying pesticides, and many reported waiting until environmental conditions were suitable before applying OP pesticides (e.g. 64% always or nearly always waited for appropriate wind direction and 96% always or nearly always waited for appropriate wind speed). Often participants remarked that they did consider the risks associated with the use of OPs, but that this was not a formal documented process. 3 In Queensland health surveillance is required to be completed by a Designated Doctor (usually an Occupational Physician or GP who has completed specific training).

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There is an obvious need for further education of farmers about the completion of risk assessments and the requirements of the legislation regarding health surveillance, MSDS, registers, training and record keeping, particularly if the Government removes the rural exemptions. Currently offered courses such as the ChemCert course, Farmsafe’s Managing Farm Safety course and quality assurance courses, which are already attended by the majority of farmers should be reviewed and amended. Changes should include more information about the health and safety aspects of pesticide usage including a focus on personalisation of risk. As a result of this study, a guide on completing risk assessments for OP pesticide will be produced under the auspices of the RIRDC. This guide could be accessed and used by training organisations to teach farmers about completing risk assessments. However, as suggested by other research when attempting to influence the safety behaviours of farmers it is important to not only increase their level of knowledge but to also highlight an understanding of personal susceptibility (Hope et al, 1999, Arcury et al, 2002). Courses should not only teach farmers what they need to do to improve safety but why and how this should be done. Some research has shown that presenting real life stories of incidents can impact upon training participants safety related knowledge and behaviours (Helmkamp, et al, 2004). As many farmers have already completed courses such as the ChemCert course there may also be a need for a compulsory recertification of such courses so that when substantial changes in course material are made more farmers will be presented with the new information. In addition to training, some preliminary research has found that creating and facilitating social support groups of like farmers, who can assist each other on a longer term basis to manage farm related risks, is beneficial in eliciting changed safety related behaviours (Stave et al, 2007). 7.4 Farmers’ Use of PPE and DAP Metabolite Results Personal protective equipment is designed to reduce the chances of exposure to pesticides when used properly. Poor or incorrect use of PPE would be expected to result in a greater chance of exposure. In this study, we observed a consistent trend opposite to the hypothesis that poor PPE use would be associated with increased exposure was observed for the farmers’ group. For example, those with high PPE-use scores were 3.6 times more likely to have detectable levels of DAP metabolites than those with low PPE-use scores and those with more positive attitudes and beliefs toward PPE use were 4.5 times more likely to have detectable levels of DAP metabolites relative to those with less positive attitudes and beliefs about PPE use. One explanation for this is that the majority of DAP metabolites found in the farmers’ urine samples were due to background environmental exposures rather than occupational exposures. There are several factors that lead to this possible explanation:

• Farmers’ urine DAP metabolite results were generally low, in fact the average levels were only slightly higher than those measured in controls.

• In several cases the only sample that contained detectable levels was their pre-exposure sample.

• The majority of samples contained detectable levels of one DAP metabolite only, DMTP, which was the only DAP metabolite detected in the control group samples (only 8 farmers’ samples contained levels of a metabolite other than DMTP).

• There was no pattern in the excretion of DAP metabolites relative to occupational exposure. • Of the 14 farmers who sprayed only diethyl OPs, half had detectable levels of only dimethyl

OPs. In fact, no farmers had any detectable levels of diethyl metabolites as would be expected from using diethyl OPs.

Although PPE is used to minimise the chances of exposure to pesticides, there are limitations associated with the use of PPE that also may have contributed to the results found in this study. For example:

• PPE is the last resort in the Hierarchy of Control. To be effective, it needs to be fitted and maintained properly, and it should be the appropriate equipment for the type of substance.

• Some use of PPE may in fact increase exposure. For example, if gloves are not washed properly or disposed of after each use they may become contaminated with the chemical and wearing them against skin during mixing and/or application, particularly in hot weather, could lead to dermal uptake of pesticide.

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A UK study evaluating the effectives of protective gloves for pesticide use found that measurable contamination of inner cotton gloves (surrogate for skin) occurred in 25 out of 30 simulated tests. The PVC gloves commonly used by farmers were the least effective in preventing inner glove contamination, “probably because the glove was thick and fairly inflexible, causing more pesticide to enter the glove around the cuff” (Creely and Cherrie, 2001). The researchers also found that when their pesticide spray pump failed higher levels of inner glove contamination occurred, indicating that when problems occur the PPE that should provide protection is not working to prevent dermal exposure. Australian research employing a similar method of assessment found that Chlorpyrifos was detected on the inner cotton gloves of all but one of the domestic pest control participants (Cattani et al, 2001). The worst type of glove worn was riggers leather gloves, followed by rubber and then PVC gloves. In fact, wearing leather gloves resulted in a worse exposure than wearing the provided cotton gloves with contamination levels at 12.5 mg/h for leather gloves and 6.5 mg/h for cotton gloves (Cattani et al, 2001). Another study involving peach orchard workers in the US found that cotton gloves afforded better protection than waterproof cotton gloves, perhaps for the same reasons as above they are thick, fairly inflexible and uncomfortable to wear (Aprea et al, 1994). Farmers in the present study also reported poor maintenance of PPE including the changing of masks/respirators and the washing or changing of gloves which can increase exposure as found in the Australian study of domestic pest control applicators (Cattani et al, 2001). It has already been discussed that farmers have knowledge about the requirements to wear PPE and often go against this information choosing instead to take more care when mixing and applying OP pesticides. Such behaviour may have reduced farmers’ chances of exposure and therefore chances of having detectable DAP metabolites in their urine. Another explanation for the observed, unexpected association between PPE use and greater chances of having detectable urine DAP metabolite levels is the possibility that those farmers who more frequently used OP pesticides also were more likely to use PPE, but their higher biomarker levels suggest exposure is taking place. This would imply ineffective and/or inconsistent use of PPE and other safety precautions. So if poor use of PPE is not necessarily a predictor of exposure and therefore the presence of DAP metabolites, as found in this study, then what factors increase the chances of exposure to OP pesticide? The following work practices were associated with increased odds of having detectable levels of DAP metabolites:

• Spending longer than 2.5 hours applying OP pesticide was associated with a 2.0 times increased odds of having detectable levels of DAP metabolites than those who spent an hour or less applying (i.e. increased duration of potential exposure); and

• Eating, drinking, smoking or talking on a phone during application was associated with a 2.5 times increased odds of having detectable levels of DAP metabolites than those who reported that they did not do any of these things (i.e. increased chances of dermal and oral uptake).

There were four farmers who had higher levels of DAP metabolites than the rest of the group (i.e. total DAP levels > 0.90 μmol/L). These four farmers all used a mister/blower/fogger. This application method is usually used for tree crops, being used to force the pesticide up into the canopy of the tree. In contrast, of the 16 farmers who used a boom on a tractor to apply the pesticide, none had high DAP metabolite levels, 10 had low levels, and 6 had no detectable levels. Boom applications are close to the ground and, in good weather conditions, should not lead to spray drift that could expose the farmer to pesticide spray. In fact, three of the four farmers who had high DAP metabolite levels and used a mister/blower/fogger also reported skin contact with pesticide spray during application. The same four farmers also all reported application times in excess of one hour. One of these farmers also reported that he had problems with a hose during application and had got spray on his hands while fixing the

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hose. Issues such as longer application time, application method and poor hygiene practices could be examined further with a larger sample. In general, the farmers had a slightly higher OP load than the controls, however the difference was not statistically significant. It would seem that the farmers in this study, regardless of whether or not they use PPE, do not have very high exposures to OP pesticides during their normal application processes (i.e. infrequent use of OP pesticide, use of boom application in good weather conditions, etc.). It is only when application methods such as mister/blower/foggers are used, when there are increased exposure times (i.e. longer application times) or when there is potential skin or mouth contamination (from problems with equipment or eating, drinking, smoking, talking on a phone during application) that farmers have an increased chance of OP pesticide exposure and have DAP metabolite levels greater than background levels (i.e. greater than non-occupationally exposed groups). In other words, risky practices give rise to higher DAP metabolite levels. 7.5 Comparison of Biological Sampling Results for the Three Exposed Groups Based on the occupational exposure patterns of the three exposed groups and on the results of other studies as reported in the literature, it was thought that the formulators would have the highest average urine DAP metabolite levels, then pilots/mixer/loaders followed by farmers. Based on the results summarised below, the formulators did have the highest levels followed by the pilots/mixer/loaders and then the farmers. However, although formulators had the highest levels (excluding one outlying sample from a farmer), the pilot/mixer/loader group, and particularly the mixer/loaders had the greatest number of samples containing detectable levels of DAP metabolites and the greatest number of samples containing DAP metabolites other than DMTP. The results of this study are consistent with other research that has shown that formulators who are exposed to the concentrated pesticide have the greatest potential for exposure and therefore the highest DAP metabolite levels (Nutley and Cocker, 1993). There is however no available data in the literature to compare the urine DAP metabolite results for the agricultural pilots and their mixer loaders. Of 96 samples provided by 32 farmers (3 samples each), only 36 samples (37.5%) contained detectable levels of DAP metabolites. Of these, results ranged from 9.00-116 μmol/mol creatinine (with one outlier of 704.00 μmol/mol creatinine). The most frequently detected DAP metabolite was DMTP, with only 8 (8.3%) samples containing a DAP metabolite other than DMTP. Of the 72 samples provided by 18 pilot/mixer/loaders (4 samples each), 68 (94.4%) contained detectable levels of DAP metabolites. Of these, results ranged from 8.40-304.00 μmol/mol creatinine. Half of the samples contained DAP metabolites other than DMTP and 32 (44.4%) contained DMTP. Of the 68 samples provided by 9 formulator plant staff working in tasks at risk of exposure, half (34 samples) contained detectable levels of DAP metabolites. Of these, results ranged from 13.20-550.00 μmol/mol creatinine. Eighteen (26.5%) samples contained metabolites other than DMTP and 16 (23.5%) contained DMTP. Unlike the unexpected trends with PPE observed in the farmers’ group, analysis of data from the pilot/mixer/loader group produced results as hypothesised. Participants with higher potential exposures based on self-reported practices had greater odds of having detectable urine DAP metabolite levels. The following specific relationships were observed:

• Those with low PPE-use scores were 1.8 times more likely to have detectable levels than those with high PPE-use scores;

• Pilots/mixer/loaders who reported breathing in OP pesticide were 5 times more likely to have detectable levels than those who reported not breathing in OP pesticide; and

• Performing measuring and mixing tasks was associated with a 3.4 times increased odds of having detectable levels of DAPs, relative to not performing the tasks.

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The pilot/mixer/loader group had more samples with detectable levels of DAP metabolites and had higher levels than the farmers’ samples indicating occupational exposures in excess of background levels. These occupational exposure levels allowed the observation of the predicted relationship between poor PPE use and greater chances of occupational exposure to OP pesticides and therefore the presence of DAP metabolites in urine. 7.6 Environmental Exposures to OPs and the DMTP Metabolite In order to put the occupational results into perspective, two control groups were sampled. Eleven of the 44 samples provided by Toowoomba community Rotary Club controls and 6 of the 11 samples provided by the formulation plant controls contained detectable levels of DAP metabolites. The only DAP metabolite detected in the control samples was DMTP. DMTP was also detected in the formulator plant-exposed group samples in levels similar to the control groups, despite it not being a metabolite of the pesticide being formulated. No other OP pesticides were being formulated at the plant during this time nor had they been in the previous few months. DMTP was also the most frequently detected DAP metabolite in the farmer and pilot/mixer/loader samples. This is consistent with the results of several international occupational and environmental exposure studies which after testing for all six DAP metabolites, reported that DMTP was the metabolite most often detected or was detected in the highest concentrations (Aprea et al., 1996, Aprea, 2000, Lu et al., 2001, Mills, 2001, Curl et al., 2002a, Castorina et al., 2003, Barr et al., 2004). Curl, et al. (2002) who conducted a study investigating effects of organic and conventional foods on OP metabolite levels of 39 American school-aged children, reported that DMTP was by far dominant over the other metabolites and was found in 87% of children for whom levels were measured. Analysis of data from the environmental exposure questionnaire completed by control group participants revealed that, although not significant, there were two main factors associated with increased odds of having detectable levels of DAP metabolites- higher consumption of fruit and vegetables, and not having a home vegetable garden. The latter implies consumption of store-bought commercial produce, rather than home-grown produce, which is more likely to be sprayed with OP pesticides and have residues remaining when the produce is purchased. Curl et al. (2002) demonstrated that dietary choice can have a significant effect on children’s pesticide exposure. They found that children who consume primarily organic produce exhibit lower pesticide levels in their urine than children who consume conventional produce that has been sprayed with OP pesticides. In children eating conventional diets, DMTP values averaged 9 times higher than children eating organic diets. In Australia in order to control dietary pesticide exposure the Australian Pesticides and Veterinary Medicines Authority (APVMA) set maximum residue limits (MRL) and Food Standards Australia and New Zealand in turn set Acceptable Daily Intake (ADI) levels. MRLs are set using toxicological data submitted by the manufacturer/importer as part of the pesticide registration process. Withholding periods also apply to pesticides in order to ensure that maximum residue limits are not exceeded. In setting an MRL, an estimation of daily intake of the chemical over a lifetime is made assuming that all foods will contain residues at the MRL. The MRLs and ADIs are set from data that is derived from animal and, where available, human studies with a safety factor applied (e.g. divide by 10 for human studies and 100 or more for animal studies). In order to test compliance with these levels, the Australian Total Diet Survey, formally known as the Australian Market Basket Survey, is conducted approximately every two years. Results of the most recent survey showed that no MRLs had been exceeded. Chlorpyrifos was one of the more commonly found pesticides and its ADI is 0.003 mg/kg/day based on a no observable effect level (NOEL) in human studies of 0.03 mg/kg/day. In the most recent Total Diet Survey, Chlorpyrifos was found in unwashed apples (mean 0.005mg/kg; max. 0.090mg/kg), washed apples (mean 0.014mg/kg; max 0.170mg/kg), minced beef (mean 0.002mg/kg; max 0.050mg/kg), white bread (mean 0.002mg/kg; max. 0.060mg/kg), unwashed grapes (mean 0.008mg/kg; max. 0.100mg/kg), lettuce (mean 0.001mg/kg; max. 0.020mg/kg), unwashed pears (mean 0.004mg/kg; max. 0.060mg/kg) and washed pears (mean 0.003mg/kg; max. 0.030mg/kg) (accessed online: http://www.foodstandards.gov.au/_srcfiles/tables%2023-26.pdf). Other OPs residues found included chlorpyrifos-methyl, dimethoate, fenthion, methamidophos, mevinphos, omethoate, parathion

http://www.foodstandards.gov.au/_srcfiles/tables 23-26.pdf

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ethyl, parathion-methyl. Lettuce was one of the worst with fifteen different pesticide residues found including four different OPs. The urine DAP metabolite results found in the current study indicate low-level exposure to OPs with diet being a major contributor to the levels of DMTP found in all groups. DMTP is a metabolite of half the OPs detected in the Total Diet Survey. According to the available information the ADIs are safe levels of dietary exposure, however like any exposure standards they are not a clear line between safe and unsafe, with levels often being reduced as new research comes to light. Given the levels of DMTP reported in the current study, in all groups including the controls, there may be a need to reevaluate the MRL levels and further explore the health impacts that may result from the levels reported. The US Centre for Disease Control recently conducted a study in Mississippi, North Carolina and Virginia, USA, to investigate applicators’ exposure while completing ultra-low-volume (ULV) applications of pesticides, including OPs, to control mosquitos (CDC, 2005). Participants who ate fresh fruits or vegetables fewer than three days before completing the pre-spray (n = 58) or post-spray (n = 37) questionnaires had significantly higher urine concentrations of DMTP than participants who did not (n = 16 pre-spray and n = 37 post-spray). The study also found that pre-spray concentrations of DMTP were higher than post-spray applications (CDC, 2005). Similarly, in the current study, farmers’ pre-exposure samples often had the highest levels or were the only samples with a detectable result. Some researchers (Heudorf and Angerer, 2001, Cocker et al., 2002) have suggested that the presence of OP metabolites in the urine may be due to exposure to the DAP metabolite residues themselves rather than the parent OP compound. Until recently, no research had tested this hypothesis. In the US in 2005, Lu et al. investigated whether DAPs were present as a result of OP pesticide degradation in fresh 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. “The hydrolysis half-lives for chlorpyrifos and diazinon at pH 7 are 72 and 23 days, respectively. However, at pH 5 the half-life for chlorpyrifos remains the same but for diazinon it decreases to 2 days.” (Lu et al., 2005). The authors state that simple hydrolysis would primarily result in the formation of DETP (from diethyl OPs) and DMTP (from dimethyl OPs), which would support their finding of higher amounts of these two DAP metabolites. Therefore, it is plausible that OPs could be metabolised into DAPs in the environment and consequently be present on produce, in juices and in other places. Lu et al. (2005) and others have questioned whether the presence of DAPs in the diet and the environment provides an explanation for why research into environmental measurements of OP residues have found that they do not account for the levels of DAPs measured in urine. “The presence of DAPs in fresh fruit juices clouds the validity of using urinary DAP measurements for estimating OP pesticide exposures in humans, particularly in children.” (Lu et al., 2005). More research is required in this area so that a better understanding can be gained of the proportion of urine DAPs that are attributable to exposure to environmental DAPs, particularly through diet, as opposed to the parent compounds. 7.7 What do the DAP Metabolite Levels Mean in Terms of Health Effects? The relationship between urinary DAP metabolite levels and subsequent health effects is more challenging to establish and requires further research with controlled volunteer exposures and more epidemiological studies. Based on current research using volunteer exposures it would appear that the levels reported in this study are unlikely to be associated with any acute health effects. Based on the current discrepancies in the literature relevant to chronic health effects, it is difficult to say whether the results would be associated with any long-term, chronic health problems such as neurological symptoms. Cocker, et al. (2002) found that a 1mg oral dose of OP pesticide, administered to volunteers, resulted in mean peak values of 160, 750 and 404 μmol/mol creatinine and was not associated with a reduction

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in cholinesterase activity. In the current study, the highest level found was 704 μmol/mol creatinine from a farmer; this is below the highest 1mg oral dose level as reported by Cocker et al. (2002). Given that the majority of detectable samples were well below the lowest peak level of 160 μmol/mol creatinine, it is unlikely that the levels observed, particularly for farmers, would result in any acute, short-term health effects. Only one study could be found that attempted to link DAP metabolite levels with health effects and that was a Florida study of citrus workers. The research involved 1811 fieldworkers from 436 citrus groves and was designed to evaluate exposure to OP pesticides by analyzing the urine of workers for DAP metabolites, and to relate the findings to the reported occurrence of selected health symptoms associated with pesticide intoxication (Duncan and Griffith, 1985). The study reported that although there was clearly exposure to OPs among the citrus fieldworkers, there was no apparent association between the reported health symptoms and the relatively low levels of organophosphate metabolites found in the urine of the workers (Duncan and Griffith, 1985). In terms of neurological health effects, one study aimed to investigate neurophysiologigcal effects of low-level exposure to foliar OP residues during a season among agricultural workers (Engel et al, 1998). The research involved a cross-sectional study of 67 Hispanic farm workers and 69 age-, gender-, ethnicity-, and education-matched reference subjects. The results showed that exposure of farm workers to the low levels of organophosphate pesticides during one season was not associated with impaired peripheral neurophysiological function (Engel et al, 1998). There are a number of other studies that show no evidence of long-term neurological damage after chronic low-level exposure to OPs. However, there is also a growing body of knowledge linking low-level exposure to OP pesticides with subtle neurological health effects (Davies et al, 1999, Farahat et al, 2003, Horowits et al, 1999, Pilkington, 2001 and Stephens et al 1995). The mechanism for these subtle neurological deficits is still unclear and further research is required. Therefore, as stated, it is impossible to say whether or not the low-level results observed for all exposure groups in this study would result in any long-term adverse health outcomes. 7.8 How do the Levels Observed Compare with International Research? The UK Health & Safety Executive Laboratory has been involved with the monitoring of levels of exposure to OPs in workers and the general public for the last 10 years. One outcome of their research, which included volunteer studies, is the finding that “OP metabolites seen in urine from workers potentially exposed to OPs is generally low and unlikely to cause significant reduction in blood cholinesterase activity” (Cocker et al., 2002). Table 7.1 compares the results from the UK laboratory’s 10 years of sampling with the results of the current study. Cocker et al. (2002) report that their results are similar to those found in other published research. Cocker et al. (2002) found that occupational exposures were similar to non-occupational exposures and that most occupational exposures were low. The current research found a similar phenomenon. The maximum DAP metabolite level found in the 917 samples from the UK research was 915 μmol/mol creatinine, compared to 704μmol/mol creatinine in the current study. Cocker et al (2002) revealed that formulators had the highest levels due to their prolonged and repeated exposure (i.e. 8-hour day). Similarly, the formulators also had the highest levels in this study, however pilots and mixer/loaders, who also have prolonged and repeated exposures over several days, had high levels as well. Cocker et al. (2002) did not sample pilots and mixer/loaders.

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Table 7.1 Comparison of urine DAP metabolite results Cocker et. al.

(2002) Current Study

Sample size 463 samples 55 samples Median (μmol/mol creatinine) 16 0 Mean (μmol/mol creatinine) 22 11 90th percentile (μmol/mol creatinine) 51 42

Non-occupational exposure

95th percentile (μmol/mol creatinine) 72 50 Sample size 917 samplesa 150 samples (50

participants x 3 samples each)

Median (μmol/mol creatinine) 15 0 Mean (μmol/mol creatinine) 33 24 90th percentile (μmol/mol creatinine) 77 67

Occupational exposure (Farmers and Pilots/Mixer Loaders)

95th percentile (μmol/mol creatinine) 122 107 Sample size -b 54 samples

(9 persons x 6 samples)

Median (μmol/mol creatinine) - b 0 Mean (μmol/mol creatinine) - b 54 90th percentile (μmol/mol creatinine) 188 172

Exposed formulator plant staff

95th percentile (μmol/mol creatinine) 285 Sample size 917 samples* 204 samples Median (μmol/mol creatinine) 15 0 Mean (μmol/mol creatinine) 33 32 90th percentile (μmol/mol creatinine) 77 92

Occupational exposure (farmers, pilot/mixer loaders and exposed formulator plant staff)

95th percentile (μmol/mol creatinine) 122 164 a: The Cocker et al. (2002) data involved occupational exposure samples from farmers, pest control operators, sheep dippers and formulators. b: Insufficient data provided in the Cocker et al. (2002) article with regards to formulators. A comparison of the results from the current study was also made with the results of the large U.S. NHANES research involving 1949 urine samples of the general U.S population aged 6-59 years (Barr et al, 2004). In the Toowoomba control group, 11 of the 44 samples contained detectable levels of one metabolite DMTP. The detectable results ranged from 0.22 to 1.57 µmol/L, with a median of 0.42 µmol/L. In the NHANES study the levels were a lot lower with adults aged 20-59 years having a geometric mean DMTP of 0.01µmol/L and 95th percentile levels of 0.27-0.34 µmol/L. It should be noted however that the NHANES study used far more sensitive analysis techniques than employed in the current study and the authors also acknowledged that there results were much lower than those reported in other studies. In the farmers’ pre-exposure detectable samples, the median total Dimethyl DAP (DMAP) level was 0.57µmol/L (range: 0.27-11.64). The pilot and mixer loader median pre-exposure total DMAP level was 0.55µmol/L (range: 0.22-7.73µmol/L). In the NHANES study the geometric mean DMAP for adults aged 20-59 years was 0.04µmol/L (range: 0.03-0.05µmol/L) and the 95th percentile was 0.43µmol/L (range: 0.38-0.62µmol/L). Therefore, the median levels found in this study for controls and occupational pre-exposure samples were much higher than those observed in the NHANES study. In fact, they were equivalent to the NHANES 95th percentile levels. 7.9 Sample Collection Requirements Because this research was concerned with trialling the use of the urine metabolite test as a risk assessment tool for farmers, it was hoped that one outcome would be a suggestion for an optimal time period for urine sample collection. However, based on the fact that no clear pattern of excretion was observed for any of the occupational exposure groups in this study, it is difficult to recommend one particular time period, after exposure, as being more appropriate than any other. It is necessary to refer to previous research in which volunteers were dosed with precise amounts of OP pesticide and the

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excretion patterns observed. Such findings were used as a basis for selection of sample collection time frames in this study. Research suggests that the elimination half-lives of OP pesticides depend upon route of exposure, type of OP pesticide and individual metabolic rates (Griffin, 1999, Garfitt et al., 2002). For dermal exposure, often the main type of exposure in the occupational setting, elimination half-lives reported in the literature range from 9-30 hours (Griffin, 1999, Cocker et al., 2002, Garfitt et al., 2002). Consequently, samples collected the day following potential exposure should give a good indication of whether or not the person received exposure to OP pesticide. 7.10 Correlations Between Urine DAP Metabolite Levels and Blood Cholinesterase Activities The only group that provided blood samples for analysis of cholinesterase activities was the formulation plant staff (exposed workers and controls). However, baseline cholinesterase levels for staff at this plant had not been measured, and given the time period imposed by the plant for sample collection, it was not possible to obtain samples to assay baseline levels. Without baseline levels, the interpretation of blood cholinesterase levels has to be completed by comparison with laboratory normal population ranges, which is not the ideal method. Despite several formulation plant staff having depressed levels (i.e. below the lower limit of the normal population range), there were no significant relationships between total urine dimethyl or diethyl DAP levels for the control and exposed groups and their blood cholinesterase levels (plasma or RBC). Examination of scatter plots reveals a very slight inverse relationship (i.e. low cholinesterase levels are associated with high urine DAP levels). Perhaps with a larger sample a clearer relationship between the two biological monitoring tools may have been observed. Other field studies involving the collection of both blood and urine samples have also reported no relationship between the two sample types (Drevenkar et al., 1991, Aprea et al., 1994). Also pesticide poisoning studies in which blood and urine samples were collected have reported no relationship (Vasilic et al., 1992, Vasilic, 1993, Vasilic et al., 1999). 7.11 Study Limitations 7.11.1 The sample One of the main limitations of this study is the small sample size for all occupational and control groups. This can be attributed to a number of factors, including: the drought being experienced in Queensland during the study period meant many farmers were not farming and/or not spraying OP pesticides; the difficulty of recruiting small business owners (i.e. farmers and aerial agricultural companies) who have heavy time commitments; the unwillingness of most formulation companies to grant permission for this research to be conducted with their employees; the logistical limitations of travelling to rural locations; and the small agricultural pilot industry. Despite these limitations, the sample sizes achieved were comparable with several studies of a similar nature (McCurdy, 1994, Simcox et al., 1999, Hatjian et al., 2000, Pisaniello, 2000, Mills, 2001). To compensate for limited statistical power, results that appeared substantively meaningful were highlighted, in a cautious manner, despite wide confidence intervals and a lack of statistical significance. Some participation bias may have resulted due to potential differences between farmers who agreed to participate and those who did not. Participating farmers are representative of the target population in terms of the location of their farms and the type of crops they grow, it is not possible to assess other sources of participation bias, such as interest in health or safety practices. 7.11.2 Methods The unavailability of baseline blood cholinesterase levels for the formulation plant group meant that the interpretation of blood cholinesterase results for this group was not ideal. As discussed in the results and literature review chapters, baseline values are required for the meaningful interpretation of results due to the large inter- and intra-individual variation in levels. The logistical impracticality of collecting blood samples from the other groups limited the scope of this study. However, based on the literature (Drevenkar et al., 1991, Aprea et al., 1994), it is believed that blood cholinesterase levels

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would not have been depressed in most participants, particularly farmers whose urine DAP metabolite levels were very low. WorkCover NSW Laboratories analysed the urine samples in the present study. The detection limits employed in the WorkCover Laboratory method are not as sensitive as those employed by other environmental studies, especially those conducted in the USA. Therefore, it is possible that in both the control and the occupational exposure samples there were levels of other metabolites apart from DMTP that were below the WorkCover NSW Laboratories detection limits. Urine sample collection involved spot samples rather than 24-hour voids. As discussed in the methods chapter, 24-hour voids provide more complete data collection but unfortunately this method is very onerous on participants and can reduce participation. Therefore, a further limitation to the study methods was the use of spot samples. Given the low urine DAP levels found in the farmers’ group, it may have been beneficial to have incorporated environmental exposure questions in the farmers’ self-administered questionnaire. However, during study design and farmer sample collection, it was assumed that farmers’ main route of OP exposure would be occupational and that the first pre-exposure sample collected would serve as a baseline measurement. After observation of low DAP metabolite levels in the farmers’ samples, it was considered prudent to include an external control group of non-occupationally exposed persons. Inclusion of environmental exposure questions in the farmer questionnaire would have further elucidated the derivation of urine DAP metabolite levels. Assessment of factors such as PPE use is difficult because it involves various different forms of PPE, which offer different types and levels of protection combined with the frequency of use of each item. The data collection and analysis methods used in this study to assess PPE use were developed by the candidate in consultation with the projects academic supervisory team and industry experts. Data was collected on how frequently different items of PPE where worn (never, rarely, sometimes, nearly always or always) and this was multiplied by a protection factor developed by the candidate and based on pesticide label requirements (weighting of 1 to 5) (Section 3.5.1.2). Similar scales have been used in other studies to assess PPE usage (Perry et al., 2002, Schenker et al., 2002). However, the use of such scales are not without their limitations. For example, someone who always wore cotton overalls was weighted the same as someone who sometimes wore chemically resistant overalls. Assessing how closely these two scenarios are related in terms of level of protection is difficult. But despite such problems some form of technique must be used to consolidate the data into a usable variable for analysis. Due to the weaknesses associated with the scale for PPE use individual equipment use was also examined. The current study examined knowledge, attitudes and beliefs towards the use of PPE. The objective of the study was primarily descriptive with an aim of assessing farmers’ reported knowledge, attitudes and behaviours related to handling OP pesticides. However, the reported attitudes and behaviours were not observed in the field and therefore there may be some bias in the data presented depending on the honesty and memory of the participants. 7.11.3 Results Due to the small size of each study group, statistical power to conduct more high powered analyses such as multivariate modelling was limited. Multivariate modelling can help to adjust for confounding and is therefore useful in identifying the true relationship between the dependent variable or factor of interest and other study factors. As a consequence of the limited statistical power, many elevated odds ratios had wide confidence intervals and were not statistically significant. Nevertheless, indicative results, generally consistent with the available scientific literature, have been reported and help contribute to a better understanding of factors related to exposure to OP pesticides and their metabolites.

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7.12 Study Validity Study validity is usually viewed from two perspectives, internal and external validity. In relation to this study, internal validity refers broadly to the ability of the data collection tools to measure what they are designed to measure. Attempts to ensure internal validity of the measures used in this study included assessment of face and content validity via:

• Use of previously developed and tested questions from large published studies; • Completion of a pilot study; • Review by industry body and government representatives followed by focus group type

discussions; and • Assessment of the proposed methods and tools by industry and academic experts.

More detailed and specific investigations into the internal validity of the study were not completed, but based on what was performed; the study tools employed were valid methods of assessment. However, data collection was subject to a number of limitations as discussed above in Section 7.11. External validity refers to how well the study results generalize to the agricultural community to which the study population belongs and to the broader Australian farming population. The study population was similar for two characteristics (crops grown and farm location) to the broader fruit and vegetable farming community under study. This assessment was based on the entire population of fruit and vegetable farmers from within the chosen study areas of South East Qld, as listed with the QFVG. At the time of data collection, QFVG membership was compulsory and therefore the listing provided was considered to be complete. Random sampling was applied to the list of farmers provided but eventually contact was attempted with all farmers. Therefore, the sample was not biased by convenience-type sampling. Other issues such as participation bias (i.e. persons who are more interested in health and safety opting to participate) can not be assessed, but may play a role in reducing external validity. Approximately 10% of the study population participated and although this is a small sample size, available information indicates that the findings can be applied to fruit and vegetable farmers in South East Queensland. With respect to the urine sample results, of the farmers who completed the questionnaire those that farmed smaller lots (21-49 acres) were more likely to provide urine samples than those who farmed larger land areas (150-600 acres). This means that the urine sample results may be more related to farmers on smaller land areas than those who farm larger size farms (150-600 acres). As far as the broader farming community is concerned, it is hard to speculate. However, demographic characteristics can be used to compare the study group with the broader Queensland and Australian farming populations. The farm sizes and farm types captured in this study correspond to the general pattern of farming in Australia, whereby the majority of enterprises are small family farms (Productivity Commission, 2005). According to Australian Bureau of Statistics information, in 2001 the median age of all types of farmers across Australia was 50 years (Barr, 2004). The median age of persons working in agriculture in Qld was slightly younger at 44 years. The mean age of farmers in this study was 45.6 (SD=12) (range 16-67). In terms of education level, in 2001 23.6% of people employed in primary industries in Qld, and 29.7% employed in Australia, had an identifiable qualification beyond high school level (Qld DPI, 2005). In the current study, 23.5% of the farmers reported a qualification beyond high school level. Therefore, the study population was similar to both the broader Qld and Australian farming populations for farm management type, age and education level.

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8. Conclusion and Recommendations The findings from this study indicate that the sampled population of fruit and vegetable farmers generally have a good level of knowledge regarding OP pesticides and their recommended safe use. However, often they do not apply this knowledge; some farmers believe that the use of PPE is more likely to interfere with safety than provide protection from exposure, and many farmers believe PPE is too hot and uncomfortable to wear in the warmer months. Furthermore, some farmers feel that wearing PPE will bring unwanted attention from neighbours. Although a last resort in terms of control priorities, PPE can be an effective means of reducing the potential for exposure to OP pesticides if the correct PPE is used and it is maintained and used properly. Results from this study indicate that PPE is of particular benefit in protecting farmers when something goes wrong, such as a leaking hose or a change in wind direction, or when there is a need for longer application times. As one of the main barriers to PPE use was the comfort factor, it is recommended that new PPE designs be investigated. Such research should examine comfort and effectiveness, particularly of gloves. Because participant farmers have knowledge about the need to wear PPE but often choose to disregard this knowledge, training efforts should be directed at explaining the implications of not using PPE under changeable conditions and the need to correctly use and maintain PPE. Literature in the area of risk perception addresses the manner in which we perceive risk and how our perception impacts our behaviours (Hayes, 1998, Quandt, 1998, Perry, 2000, Sandall, 2000, Sodavy, 2000, Kishi, 2002, Hampson et al., 2003). Authors in this field of study suggest that the personalisation of risk (i.e. acceptance or understanding that, yes, it can happen to you) can be an effective training mechanism when attempting to influence safety behaviours. Pesticide handling courses such as the ChemCert course, should not only teach farmers what they need to do to improve safety but why and how this should be done. Research has also shown that presenting real life stories of incidents can help to impact upon training participants’ safety related knowledge and behaviours. Further research is required in the area of training and its impact on safety behaviours in the agricultural industry. The matter of OP pesticide exposure has been identified as an important occupational health and safety issue and as such is singled out as one of sixteen chemicals out of more than 100,000 chemicals potentially requiring health surveillance. The current research and indeed other international research has shown that DAP metabolite levels of agricultural pesticide applicators is generally low and unlikely to manifest as acute and possibly not chronic health effects. This finding may be a result of the heightened caution of applicators when using OP pesticides. Does this mean that the occupational exposure to OPs of persons in the agricultural industry is not as important as once presumed or is it that government and other industry bodies’ efforts are currently effective in controlling exposures? Although the rural industry is presently exempt from the hazardous substance provisions of the Qld Workplace Health and Safety Legislation, it is likely that this exemption will be lifted in the near future. There may be some resistance in the rural industry to this change, but farmers should already be considering the risks to themselves and others from chemical exposures as part of their overall obligation to ensure health and safety on their farms. Generally speaking, all industries struggle with compliance with the hazardous substance legislation, for example the formulation plant which has no exemptions from the legislation struggled; with no established baselines for their workers, ineffective PPE and poor hygiene practices of workers. Like many areas of occupational health, chemical exposures often do not receive the same level of attention as safety related issues due in part to the long latency periods between exposure and effect and the lack of workers compensation statistics. Therefore, there needs to be an added effort on behalf of the Government and industry bodies to highlight the health related issues in industry and to improve the collection of data on the occurrences of health related incidents. Should the government remove the rural exemption, farmers will need further instruction in the requirements of the legislation and in particular, how to conduct a formal risk assessment for chemical exposure including OPs. Farmers in this study had a very limited understanding of what was involved in completing a formal risk assessment, and of MSDSs and their importance. Training organisations

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such as those that run the ChemCert training course may need to reassess their approaches to teaching farmers about risk assessments and MSDSs and the availability and frequency of refresher training. The changes to the ChemCert course, other training courses and perhaps legislation, which may be expected as a result of this study, will not only assist with OP exposures but with the management of all types of chemical exposures on the farm. Any such research into chemical exposures draws attention to the issues and although in this case farmers’ levels were low the reported behavioural findings suggest there is still plenty of room for improvement in the management of farm chemical exposures. Urine DAP metabolite levels reported in this study are similar to those reported in the literature (Takamiya, 1994, Stephens et al., 1996, Simcox et al., 1999, Mills, 2001, Cocker et al., 2002). DAP levels reported are unlikely to be associated with a drop in cholinesterase activity and therefore are unlikely to be associated with any acute, short-term health effects. However, it is not known if the levels of DAP metabolites would be associated with any long-term, chronic health conditions such as neurological symptoms. Environmental background exposures to OPs producing the dimethyl metabolite DMTP appear to be of importance and may be related, in part, to consumption of contaminated fruit and vegetables. There is evidence to suggest that exposure to DAPs themselves through diet and other sources may contribute to the concentration of DAPs, such as DMTP, in the urine, potentially complicating assessment of occupational exposure levels. Nevertheless, the urine test did serve as a sensitive indicator of potential exposure to OP pesticides and was of particular use in the agricultural pilot industry and for formulation plant workers who have prolonged exposure to OPs throughout a shift and over several days in a row. Consequently, it may play a useful role in assisting in the risk assessment process, which requires an employer to assess the potential for ‘significant’ exposure to a hazardous substance. In 2005 the International Labour Organisation (ILO) (Organisation., 2005) highlighted work-related illnesses or diseases as a particular issue for concern: “of the 2.2 million work-related deaths a year, 1.7 million – or nearly four-fifths - are due to work-related disease…hazardous substances kill about 438,000 workers annually…it is estimated that pesticides alone annually cause some 70,000 acute and long-term poisoning cases leading to death and a much larger number of acute and long-term non-fatal illnesses” (ILO, 2005). Given the huge global impact of exposure to hazardous substances and the potential for the development of acute and, perhaps even more importantly, chronic health effects, it is hoped that the findings from this research and other similar projects in occupational health will receive due attention. Those organisations responsible for training and policy development in the rural industry can benefit from the information generated by this research. That farmers, for example, often fail to act on their knowledge of safety precautions, that they have a poor understanding of valuable tools such as MSDSs, and that these sheets are not consistently supplied to farmers are research outcomes that suggest there is room for improvement. The higher urine DAP metabolite levels recorded for the pilots and mixer/loader group and the formulator plant exposed group indicate these industry groups may need to further examine their work practices with the aim of identifying ways of reducing their exposures. In particular, higher order control options should be considered, for example better ventilation systems in mixing and loading areas as opposed to relying on PPE. Improved hygiene practices may also need to be considered for example, more regular washing of potentially exposed skin and immediate changing of contaminated clothing. 8.1 Future Research Directions and Advice to Farmers The Australian Centre for Agricultural Health and Safety investigated the usefulness of cholinesterase testing in the rural industry and concluded that a ‘practical unambiguous guide’ that covers health surveillance and when and how, etc., it should be performed is needed for rural employers and workers (Frager and Sankaran, 2004). As an outcome of this research, a guide to completing risk assessments for OP exposure will be developed and published under the auspices of the Rural Industries Research and Development Corporation (RIRDC). The guide will step farmers through the process of

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completing a formal risk assessment and will provide advice on having health surveillance completed as part of the risk assessment process. Urine DAP metabolite monitoring will be suggested as a convenient health surveillance tool for use in the risk assessment process and particularly with deciding wether or not risk of exposure is “significant”. DAP metabolite levels as discussed in the literature will be included to aid the interpretation of results from urine testing, as there is currently no biological exposure index for comparison. This study found that most fruit and vegetable farmers have limited potential exposure to OP pesticides, given their infrequent use, short durations of exposure and application method (i.e. boom on end of tractor). The results of this study indicate that environmental exposures to the parent compound, as well as to DAP metabolites themselves, may contribute substantially to urine DAP levels. Future research should be directed at examining routes of environmental exposure to both the parent OP pesticide (e.g. from consumption of contaminated foods) and the potential sources of environmental exposure to DAP metabolites. Some research has been conducted internationally on environmental exposures and this field is growing; however, to date there is only one published account of research on the environmental presence of degradation products of OP pesticides (i.e. DAPs). While there is extensive literature on the acute health effects from exposure to OP pesticides, limited research has been conducted on the potential health effects, if any, that may result from low DAP metabolite levels such as those found in both exposed and control groups in this study. Such research is important given the potential for a lifetime of environmental exposure in addition to any occupational exposures. Such research would aid in the development of a biological exposure index for the urine DAP metabolite test and therefore would result in a more usable risk assessment tool for occupationally exposed persons. 8.2 Key Recommendations The following key recommendations can be made based on the findings of this research project:

1. The urinary metabolite test (dialkyl phosphate (DAP) metabolites) be considered as the replacement for the blood cholinesterase, organophosphate (OP) insecticide exposure test where applicable.

2. A recent and comprehensive literature review be undertaken to establish if there is sufficient data available to establish a Biological Occupational Exposure Limit(BOEL) /index for the urinary metabolite test.

3. Due consideration be given to the adoption or establishment of a BOEL for the urinary metabolites of Organophosphate insecticides so that this metabolite test becomes the primary test for OP exposure.

4. In the mean time, a more detailed protocol be developed for the continuing use of the blood cholinesterase test when it is applied to the assessment of occupational exposure to OP insecticides such that:

a. Base line values of cholinesterase be established for all individuals being assessed for occupational OP exposure.

b. The test be applied to plasma and red blood cells. c. An occupational physician or OHS professional be involved in the assessment of

workers, workplaces and work practices in which the cholinesterase test is being applied for occupational exposure assessment.

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Fayomi, B. (1991) 'Agricultural organophosphate applicators cholinesterase activity and lipoprotein metabolism', Bulletin of Environmental Contamination & Toxicology, 46, 3, 351-60.

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Amati, R. and Sartorelli, E. (1994) 'Biological monitoring of exposure to organophosphorus insecticides by assay of urinary alkylphosphates: influence of protective measures during manual operations with treated plants', International Archives of Occupational & Environmental Health, 66, 5, 333-8.

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R. (1998) 'Determination of serum cholinesterase activity in healthy population and organophosphate poisoning in Iran', Toxicology Letters, 95, 1, 150.

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Organophosphate Pesticide Exposure in ... - Agrifutures Australia€¦ · Growers (QFVG) and the Aerial Agricultural Association of Australia (AAAA); their assistance was vital in