1. The following lecture has been approved for University Undergraduate Students This lecture may contain information, ideas, concepts and discursive anecdotes that may be thought provoking and challenging It is not intended for the content or delivery to cause offence Any issues raised in the lecture may require the viewer to engage in further thought, insight, reflection or critical evaluation

2. Acute symptom-reporting after routine exposure to organophosphate pesticides in sheep dip Institute of Occupational Health University of Birmingham for the Health and Safety Executive C.A.Jackson & A.Spurgeon

4. Dippers’ Flu Dipping sheep with Organophosphate Pesticides Dipping sheep with Organophosphate Pesticides Traditionally tied to collection of non-specific symptoms Traditionally tied to collection of non-specific symptoms Manifests shortly after dipping Manifests shortly after dipping Alleviation usually after 48 hours Alleviation usually after 48 hours Is there really any truth in this collection of symptoms? General weakness Muscle weakness Fever Aches and pains Headaches Loss of appetite

5. Past work Previous study Investigated symptom reports in 82 farmers recently exposed to OPs when dipping sheep, compared with controls (quarry workers) Overall symptom reporting, and reporting of symptom groups was not elevated in exposed relative to controls This was not consistent for all symptoms. Possible that this (intuitive) grouping of symptoms may mask some genuine symptom patterns. A statistical approach was needed...

6. Aims & Objectives a) Establish plausible basis for grouping of symptoms b) Identify recognisable core-symptoms consistently present in exposed workers c) Determine if exposed and controls differ in these core-symptoms e) Determine if any excess in core-symptoms is dose- related

7. Strategy for Re-analysis a) Cluster analysis of symptom data using original symptom groups b) Rank individual symptoms by frequency c) Chi square analyses of individual symptoms d) Factor analysis of 73 original symptoms e)Investigation of dose-effect relationships f)Cluster analysis of the symptom data

8. Ranking individual symptoms

9. Rank individual symptoms cont.

10. Individual symptoms at 24 hours after dipping 12 symptoms reported more by exposed than controls 15 symptoms reported more by controls than exposed

11. Factor Analysis of all symptoms Twenty-one unwieldy factors

12. Scree Analysis

13. Factor Analysis 6 factors remained as the best representation of symptom data The product of 38 individual symptoms Accounted for 47% of the variance in symptom scores

14. Factor Analysis Little physiological commonality between symptoms in each factor

15. Dose-effect relationship? Weak association between 6 factors & flock size (R 2 =0.4) Weak association between 6 factors & flock size (R 2 =0.4) Flock size as surrogate exposure estimate is too simplistic Flock size as surrogate exposure estimate is too simplistic Statistical problem - 38 symptoms and only 82 cases Statistical problem - 38 symptoms and only 82 cases

16. Top 21 symptoms 21 symptoms reported most frequently Subjected to “K-Means” cluster analysis Produced 5 distinct symptom clusters With seemingly useful physiological explanations “Gross” “Shiver” “Flu-like” “Muscular” “Global”?

17. Testing the 5 cluster model Scores on the 5 clusters compared between exposed and controls Significant differences were consistently to the detriment of the exposed shivermuscularglobal

18. Conclusions High frequency of symptoms in both occupational groups (approx. 50-50) No evidence of more dippers’ flu symptoms in exposed than the controls No plausible pattern was evident in symptoms reported by the exposed Cluster analysis of the original 9 symptom groups showed globalized and non-specific symptoms were being reported more than localised specific symptoms - suggesting general malaise than specific target organ systems Factor analysis provided little clarification of the data - it reduced 21 unwieldy factors down to 6 factors, though with little physiological plausibility in the grouping together of some symptoms K means cluster analysis identified 5 distinct symptom clusters of better plausibility, 3 of which were significantly worse in exposed

19. Summary Tentative support for the view that certain symptoms can be identified occurring more frequently in those exposed to OPs. Such symptoms are consistent with a flu like illness. Further verification is needed from studies specifically targeted at a definition of symptom groups following acute OP exposure.