Acute symptom-reporting

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Acute symptom-reporting after routine exposure
to OP pesticides in sheep dip Using data
reduction to provide a clinical profile of
symptoms Prof. Craig A. Jackson
Division of Psychology Birmingham City University
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• Aims
• Using data reduction to provide a useful clinical
  profile of symptoms
• Subjectivity of objective methods even in
  quantitative studies
• Factor Analysis
• Kaiser Criteria
• Scree Analysis
• K-means Clustering

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Symptom reporting in society
Prevalence of non-specific symptoms (Western
Australia n 3016) Symptom Prevalence
Symptom Prevalence Stuffy nose 46.2 Headache
s 33.0 Tiredness 29.8 Cough 25.9 Itchy
eyes 24.7 Sore throat 22.4 Skin
rash 12.0 Wheezing 10.1 Respiratory 10.0 Naus
ea 9.0 Diarrhoea 5.7 Vomiting 4.0 Heywo
rth McCaul, 2001
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• Unexplained symptom syndromes

• Common Present Day Symptoms
• Multiple Chemical Sensitivity (MCS) 90s
• Chronic Fatigue Syndrome (formerly ME) 90s
• Sick Building Syndrome 80s
• Gulf War Syndrome 90s
• Musculoskeletal problems 90s
• Electrical Sensitivity 90s
• Historical Symptoms
• Railway Spine 1860s
• Combat Syndrome 1850s onward
• Wool sorters syndrome 1860s

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• Sheep Dipping

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• Sheep Dipping

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• Sheep Dipping

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• The UK Sheep Dipping Saga

Organophosphate Pesticides (OPs) Sheep
Dipping UK Sheep dipped twice yearly, and was
compulsory 19841988 OPs were the dip of choice
recommended by HSE Routine sheep dipping is
wet and messy work NOT usually an acute
exposure Chronic and low level
exposure Non-specific symptoms alleviate 48
hours post-dip Dippers Flu Anxiety Depress
ion Fatigue Aches Pains Headache Fever Ne
urobehavioural problems (memory, concentration)
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• Dippers Flu
• Dipping sheep with Organophosphate Pesticides
• Traditionally tied to collection of non-specific
  symptoms
• Manifests shortly after dipping
• Spontaneously remits usually after 48 hours

Is there really any truth in this collection of
symptoms? Or is it just background
symptomology
General weakness Muscle weakness Fever Aches and
pains Headaches Loss of appetite Does Dippers
Flu really exist?
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Past work Previous study Stephens et al.
1995 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 . . .
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Aims Objectives a) Establish a 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 (e.g. number of sheep, or years
dipping)
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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
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Individual symptoms at 24 hours after dipping
12 symptoms reported more by exposed than
controls 15 symptoms reported more by controls
than exposed
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Factor Analysis of all symptoms
Kaiser Criteria use factors with Eigenvalue gt1
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Factor Analysis of all symptoms
Twenty-one unwieldy factors
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Scree Analysis
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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

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Factor Analysis
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Kaiser Criteria versus Scree Analysis

• Twentyone factors representing 81 of variance
• or
• Six factors representing 46 of variance
• Dilemma!!!!!
• Kaiser criteria of gives too many factors
• Scree analysis often gives too few factors
• Both good under optimal conditions....
• This study not optimal 73 variables and 100
  cases!!!

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Dose-effect relationship?

• Weak association between 6 factors flock size
  (R20.4)
• Flock size as surrogate exposure estimate is too
  simplistic
• Statistical problem - 38 symptoms and only 82
  cases

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• K means Clustering
• A method for reducing data based on differences
  not similarities (as in Factor Analysis)
• Uses Euclidean Distances between factors
• All 73 symptoms
• 21 symptoms reported most frequently
• 12 symptoms reported sig more by dippers than
  controls
• Subjected to K-Means cluster analysis
• Produced 5 distinct symptom clusters
• With seemingly useful physiological explanations

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12 symptoms reported more K means Clustering

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12 symptoms reported more K means Clustering
12 symptoms reported more by dippers
than controls Subjected to K-Means cluster
analysis Produced 3 distinct symptom clusters
With seemingly useful physiological explanations
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Top 21 symptoms K means Clustering
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Top 21 symptoms K means Clustering
21 symptoms reported most frequently
Subjected to K-Means cluster analysis Produced
5 distinct symptom clusters With seemingly
useful physiological explanations
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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
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• 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

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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.