Return to search

Assessment of long-term occupational pesticide exposure and its application to an epidemiological study on ill-health among UK farmers

In the UK, dipping sheep with pesticides for treating ectoparasites has been one of the main pesticide applications and it was compulsory between 1984 and 1991 when organophosphates (OPs) were the main ingredients of sheep dips. As a result many current elderly sheep farmers have been exposed to OPs. The acute health effects of many pesticides especially OPs are very well documented, while the effects of long-term exposure are still unclear. Difficulties in assessing past pesticide exposure have been suggested to be one of the main reasons for this uncertainty. The overall aim of this PhD was to develop long-term occupational pesticide exposure models for UK farmers, specifically for OP exposure among sheep dippers, and to apply them to the Study of Health in Agricultural Work (SHAW) in order to examine the associations between long-term pesticide exposure and neuropsychiatric ill-health. A comprehensive conceptual exposure model to assess pesticide exposure during sheep dipping was developed and included five sources of pesticide exposure; handling the concentrate, dipping sheep in the bath, handling sheep after dipping, disposal of sheep dip, and any incidental exposure. Dermal, ingestion and inhalation routes were described for each source and different modifying factors for each route were identified. A semi-quantitative exposure algorithm was developed and all sources, routes and modifying factors were assigned scores and weights by assessment of the literature and expert judgement. The new model was evaluated by comparing its estimates of diazinon exposure among dippers who participated in the Health and Sheep Dipping Survey (HSDS) with diazinon urinary metabolite levels in spot urines collected after the dipping session. The model estimates generally did not correlate well with metabolite levels though there was evidence of an association between total metabolites and ordinal categories of exposure intensity. The uncontrolled conditions of the HSDS and the lack of 24 hr urine collections may have contributed to these results. A probabilistic model was also developed from the conceptual model and indicated that although handling the concentrate and dipping sheep are the most important exposure sources, other sources like handling dipped sheep and disposal of sheep dip should not be neglected. This probabilistic model was applied to different scenarios: probabilistic estimates may give a more comprehensive description of exposures than deterministic estimates as they take into account all conceptual variables. Occupational pesticide exposure among UK farmers in the SHAW study was then estimated using simple surrogates and more sophisticated models. The validity of self-reported exposure history among SHAW farmers was investigated by making comparison with data collected contemporaneously by the June Census. Farmers recall was generally reliable especially for a specific type of livestock or crop rather than the number of livestock or acreage. Associations between screen-identified ill-health and pesticide exposure were only demonstrated by using more developed metrics. Exposure to pesticides but not specifically OPs in sheep farming was associated with neuropathy and Parkinsonism. Exposure to OPs in sheep dipping was associated with a decrease risk of dementia. Depression was not associated with any exposure. In conclusion, this thesis developed a comprehensive model for pesticide exposure from sheep dipping and simpler exposure models for other farming sectors. The application of these models to the SHAW study suggests that long term pesticide exposure among farmers mainly via sheep dipping may result in ill- health; however the associations between exposure and outcomes may only be revealed by the use of more sophisticated exposure models rather than simple exposure surrogates. The study also indicates that even the use of well-derived deterministic estimates might lead to exposure misclassification. This misclassification may be investigated by using probabilistic approaches.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:686717
Date January 2013
CreatorsAlhamwi, Haytham
ContributorsPovey, Andrew ; Stocks, Jill ; De Vocht, Frank
PublisherUniversity of Manchester
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttps://www.research.manchester.ac.uk/portal/en/theses/assessment-of-longterm-occupational-pesticide-exposure-and-its-application-to-an-epidemiological-study-on-illhealth-among-uk-farmers(36d5d4f3-cdf6-478f-a224-cdeacda7555f).html

Page generated in 0.0023 seconds