HSE Health & Safety

Executive

Questionnaire predictors of asthma and occupational asthma

Prepared by Institute of Occupational Medicine for the Health and Safety Executive 2003

RESEARCH REPORT 164

HSE Health & Safety

Executive

Questionnaire predictors of asthma and occupational asthma

BG Miller, MK Graham, KS Creely, HA Cowie, CA Soutar

Institute of Occupational Medicine 8 Roxburgh Place

Edinburgh EH8 9SU

This work was designed to investigate the identification by questionnaire of asthma in general, and work-related asthma in particular, to assist in producing a questionnaire to identify work-related asthma. A previous postal survey of a community in central Scotland provided a complete data set for almost 12,000 subjects of working age, with responses to a range of questions on respiratory symptoms and their relationship to occupation. For those subjects who had recorded the occupation held when symptoms began, the existing data were augmented by an exposure assessment to characterise exposures typical of those occupations. Certain symptoms were associated, tending to occur together, and a number of syndromes were defined in terms of these. Some limited associations between these syndromes and occupational exposures were identified, particularly with irritant and highly reactive chemicals, and exposure to proteins and other organic substances. Occupational histories from the postal survey have not yet been processed and future work on could provide further insight into occupational associations of syndromes. The syndromes suggested a much higher prevalence of work-related asthmatic symptoms than reported by the Labour Force Survey questions, but the reasons for this excess were not clear. For a few subjects, clinical assessments had been made, but from an initial look the agreement with the questionnaire-based syndromes was fairly poor. More intensive reworking of the clinical data revealed relationships with childhood asthma and exposure to known asthmagens that may help to guide future questionnaire design.

This report and the work it describes were funded by the Health and Safety Executive (HSE). Its contents, including any opinions and/or conclusions expressed, are those of the authors alone and do not necessarily reflect HSE policy.

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First published 2003

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CONTENTS SUMMARY v

1. INTRODUCTION 1

1.1 Background 1

1.2 Previous studies 1

1.3 Legacy of data 2

1.4 Unanswered questions & needs 2

2. OBJECTIVES 3

2.1 Detailed objectives 3

2.2 Plan of work 3

3. METHODS 5

3.1 Literature review 5

3.2 Data extraction & checking 5

3.3 Multivariate analyses: clusters and factors 13

3.4 Exposure Assessment 14

3.5 Statistical analysis of associations 20

4. RESULTS 21

4.1 Literature review 21

4.2 Analysis of symptoms data 25

4.3 Definition of syndromes 31

4.4 Exposures 37

4.5 Clinical records 45

5. DISCUSSION 52

5. Quality of available data 52

5. Exposure assessment 52

5. Symptom combinations 52

5. Defining syndromes 53

5. Associations between syndromes and occupational exposures 53

5. Comparisons with clinical examinations 54

5. Design of questionnaires 54

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5.8 Possibilities for future work 54

6. ACKNOWLEDGEMENTS 56

7. REFERENCES 58

APPENDIX 1 60

APPENDIX 2 70

APPENDIX 3 74

APPENDIX 4 76

APPENDIX 5 78

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SUMMARY

Introduction

Reported incidence of occupational asthma is greater than for other common occupational respiratory disorders. Epidemiological studies of occupational asthma rely on questionnaires on respiratory symptoms, but there is little agreement or standardisation on what questions best reveal occupational asthma.

A community study of respiratory health was carried out in central Scotland in the mid 1990s, in which almost 17,000 adult subjects completed postal questionnaires on self-reported work­related illness, respiratory symptoms, smoking habit and occupation. A small number of these (101) attended clinical examinations. The data from this study represent an important resource for understanding the relationships between symptom questions and their relationship with occupational disease. We report on a project involving detailed reanalysis of this data set, followed by a comparison with the clinical assessments. The study was intended to provide information towards the development of a questionnaire to identify work­related asthma.

Objectives

The detailed objectives were:

i. To investigate which groups of respiratory symptoms tend to be reported together.

ii. To identify clinically relevant syndromes based on these symptom clusters.

iii. To investigate whether and how these syndromes differentiate between individuals who were defined to have work-related and non-work related asthma in the previous questionnaire study.

iv. To investigate whether and how these syndromes differ by occupation and exposure, with particular reference to differences between probable irritant and allergic asthma.

v. To identify symptom combinations associated with clinical diagnosis of work-related asthma, and compare these to the syndromes identified by clustering.

vi. To identify any aspects of the clinical examination and diagnosis process that could usefully be incorporated into a self-administered questionnaire.

Methods

Recent literature on development and validation of questionnaires to identify asthma and other respiratory diseases was collected and reviewed.

Questionnaire data from the previous community study were extracted from computer files. Only the first two mailings used the complete questionnaire, giving data for 14,090 working­age adult subjects. Of these, 2,149 were omitted from statistical analysis because of missing data on individual questions.

The data from the community study included the job that was current when respiratory symptoms had first been experienced, and these had previously been coded to SIC and SOC classifications. Occupations were grouped and characterised in terms of likely exposure to a

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range of important asthmagens and respiratory irritants. Indices of exposure included presence or absence of each hazard, and likely frequency of exposure. An additional assessment was made of whether there was at least a moderate probability of accidental or periodic exposure to very high levels of irritant gases or fumes.

Statistical analyses of patterns amongst the symptoms used principal components and factor rotation to identify combinations of symptoms to form syndromes. Separate analyses used clustering techniques on the symptom variables, to identify combinations of responses that tended to occur together. Relationships between derived syndromes and exposure indices were calculated as log-odds ratios divided by their standard errors.

Records of the clinical examinations were reviewed twice by a chest physician, the first time for confirmation of the diagnoses recorded, and the second to investigate mechanistic hypotheses regarding the influences of stress or childhood asthma on the classifications, and to identify occupations with known asthmagen exposure.

Results

The literature review highlighted differences between research groups, in the emphasis they would give to different questions or symptoms. The presence of wheeze was believed to be most characteristic, but all single questions lacked specificity. Groups investigating bronchial hyper-reactivity found that it too lacked specificity. Current questionnaires were unreliable in distinguishing asthma caused by asthmagens or irritants in the workplace from existing asthma exacerbated by exposure to these. A few groups using principal components and factor rotation had identified some clustering of symptoms responses, and some syndromes constructed from multiple symptoms had better specificity, at some cost to sensitivity. No "gold standard" for the identification of occupational asthma had been found, and even clinical diagnosis was variable.

Examination of the data for subjects omitted from the full analyses showed that data were not missing at random, but that some subjects with symptoms had not filled in all the questions, and hence were omitted from the analysis data set. This meant that symptom prevalences were lower in the data set analysed than had previously been reported for the study as a whole. However, we have no reason to believe that the relationships reported below will have been seriously distorted by the non-randomness of the missing data.

Multivariate analysis of the symptoms data from the community study showed that certain groups of symptoms tended to occur together. From a principal component analysis on 20 symptom variables, followed by factor rotation, wheeze that improved when away from work or was made worse by a particular work-related place or activity accounted for 25% of the total variation, and had clinical plausibility, as did other symptom combinations. Cluster analysis produced results very similar to those from the factor rotations. Several relevant non-exclusive syndrome variables were defined and calculated:

· occupational asthma (based on wheeze) (Syndrome 1) · occupational asthma by LFS definition (Syndrome 5) · doctor-diagnosed occupational asthma · non-occupational asthma · all-cause asthma · allergic (extrinsic) asthma · chronic bronchitis · chronic bronchitis by LFS definition

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The syndromes labelled as occupational asthma based on wheeze and allergic asthma identified about ten times as many subjects as the LFS definition of occupational asthma.

Syndromes were analysed for their relationships to exposure indices in 1,301 subjects whose occupations had been coded from the descriptions recorded on their questionnaires. All syndromes were associated with exposure to irritants, and the wheeze-based definition was related to exposure to highly reactive chemicals and metal sensitisers. Chronic bronchitis was associated with exposure to metal sensitisers and to wood dust (LFS definition only). LFS­defined occupational asthma was associated with exposures to rodents, livestock, insects and flour or grain.

Clinical diagnoses and derived syndromes were available for 54 subjects. Cross-tabulation did not show very good relationships between diagnoses and syndromes. Reviewed by a chest physician, the details in the clinical records broadly confirmed the diagnoses made at the time, although the borderlines between diagnostic categories were indistinct and certainty was elusive. In a further re-examination, the presence was noted of statements regarding asthma during childhood and stress (which might mimic asthma or its exacerbation), plus mention of occupations that would involve exposure to known asthmagens.

These clinical variables were used to reclassify syndrome allocations, e.g. discounting a subject as "occupational asthma" if s/he had had asthma as a child. Inclusion of childhood asthma made some small improvement to the relationship between syndromes 1 and 5 and the clinical diagnoses. Stress had been recorded for few subjects, so its inclusion made little difference. However, when a stipulation was made that classification to syndrome 1 or 5 should require identification of a specific occupational asthmagen, there was a vast improvement in the agreement between syndromes and clinical diagnoses. When syndromes 1 and 5 were combined into one classification of occupational asthma, that classification correctly identified all five clinical cases of occupational asthma, and rejected most of the occupationally aggravated subjects and all of those with other diagnoses. Similar discrimination was achieved for syndromes 1 or 5 considered separately, if membership of these syndromes was mandatory on identification of a specific occupational asthmagen in a subject with asthma.

Conclusions

There is still considerable scope for further work on standardising the detection and characterisation of occupational asthma by questionnaire. There exists at present no "gold standard" and different research groups favour different definitions. However, our reanalysis of the questionnaire data for almost 12,000 subjects from the community study has confirmed that certain combinations of symptoms tend to occur together, and the similar results from two independent techniques add plausibility to the findings and to the symptoms derived as a result. Some of the syndromes used identified many more subjects than the LFS definitions.

Associations between defined syndromes and indices of likely occupational exposures showed a few plausible relationships, but fewer than might have been expected. This may be due to a mismatch in time between the symptoms reported and the single occupation recalled as being current when symptoms began.

Our re-examination of the clinical information has suggested that questionnaire design for the detection of occupational asthma might usefully incorporate:

· questions on wheeze, like those underlying syndrome 1 (wheeze-based occupational asthma);

· questions similar to the current LFS questions; · questions on childhood asthma;

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· investigation of occupation, and subsequent classification of occupations with known asthmagen exposure.

These results were based on very small numbers of subjects undergoing clinical assessment, and any new questionnaire would require pilot testing and validation, preferably in an occupational population. In addition, the design should pay attention to question routing and instructions, in order to minimise missing data; and to harmonising the time periods to which the questions refer.

Other further work from the present study could include the processing and analysis of complete occupational histories, which were taken but have not yet been coded and entered to computer. This could allow more searching analyses for relationships between the historical pattern of exposures and respiratory symptoms, and for influences of symptoms on subsequent employment patterns.

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1. INTRODUCTION

1.1 BACKGROUND

Incidence of occupational asthma is greater than other common occupational respiratory disorders today. In the UK, around 900 new cases of occupational asthma are reported each year under the Surveillance of Work-Related and Occupational Respiratory Disease (SWORD) scheme, with early results from the scheme suggesting an incidence of 22 new cases per million workers per year (Sallie et al, 1994; Ross et al, 1995). Information gathered during the 1990/1991 Department of Employment Labour Force Survey found a prevalence of ten cases of occupational asthma per 20,000 population which is equivalent to 12,500 cases in the UK working population of 25 million (Hodgson et al, 1993) .

1.2 PREVIOUS STUDIES

1.2.1 Community study

Between 1994 and 1997, the IOM carried out a community study of lung health in the West Lothian and Central regions of Scotland (Cowie et al, 1997). Almost 17,000 individuals completed a postal questionnaire containing questions on self-reported work-related illness, respiratory symptoms, smoking habit and occupation. A full occupational history was taken (but not processed).

Questionnaire responses were used to determine whether or not individuals had symptoms of asthma, and those with symptoms of asthma were further subdivided into those with work­related and those with non-work-related symptoms.

Two definitions of asthma were used:

i. ‘LFS’ asthma - defined using questions based closely on the Labour Force Survey questionnaire on self-reported work-related illness (Hodgson et al, 1993), adapted for self-administration.

ii. ‘Symptoms’ asthma - defined using combinations of positive answers to questions on wheezing and shortness of breath. This was further subdivided into work-related and non-work-related asthma depending on places and activities where symptoms got worse, and worsening of symptoms on work days compared to non-work days.

A total of 1607 respondents reported either LFS or symptoms asthma, or both, and 82 of these were selected to attend specially arranged medical clinics where they were examined by a consultant chest physician, using a structured examination procedure. Also examined were 19 additional cases reporting respiratory symptoms consistent with bronchitis.

1.2.2 Case-control study

A second study was based on the data from the postal questionnaires, using a case-control design (Buchanan et al, 1997). A total of 424 asthma cases were selected (224 work-related, 200 non-work-related) and compared with the same number of age-matched controls, and 408 chronic bronchitis cases (208 work-related, 200 non-work-related). The comparisons included the detailed occupational histories, which were coded and processed for only the selected cases and controls.

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The case-control study identified a number of occupations with raised risks for asthma symptoms, including bakers, meat processors, caterers, cleaners, textiles processors and general labourers, with some evidence for effects of print work, metal treatment and spray painting.

1.3 LEGACY OF DATA

Appendix 1 contains a copy of the postal questionnaire. After two mailings, this had been completed and returned by around 14,000 subjects. Because this represented a lower response rate than had been anticipated, a third mailing was sent out. However, in the belief that the response might be improved by a shorter questionnaire, the questionnaire was revised, principally by the omission of Section C on asthma, and Section F, the full occupational history. About 3,000 additional subjects returned the short questionnaire. Depending on sporadic patterns of missing data, questionnaire responses from all or some of the Sections are available for up to 16,990 subjects.

Because we wished to include the Section C questions, in the present study we have limited the analysis of symptom associations to the 14,000 who responded to either the first or second mailing. We hold full occupational histories for all these subjects, but (except for those selected for the case-control study of Buchanan et al, 1997) these exist only as paper records, and have not been processed to computer files.

Records are also held of the 101 clinical examinations, including the 82 asthmatic subjects described by Cowie et al (1997).

1.4 UNANSWERED QUESTIONS & NEEDS

The characterisation of asthma for epidemiological purposes commonly relies largely on subject responses to standardised questions. Much research work has focused on developing questionnaires for the detection of asthma in general, and on testing their repeatability and their validity against more objective measures such as bronchial challenge tests and spirometry (e.g. Burney et al, 1989). However, the development of questionnaires for the detection of work-related asthma is much less advanced. We report here on a study, based on data already collected, to investigate in more detail the identification of asthma in general, and work-related asthma in particular, using combinations of respiratory symptoms and questions on the work-relatedness of those symptoms. The present study was intended to provide information towards the production of a questionnaire to identify work-related asthma and additional information on the clinical relevance of clusters of self-reported symptoms.

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2. OBJECTIVES

2.1 DETAILED OBJECTIVES

This work was aimed at providing information towards the design of a questionnaire to identify work-related asthma. It was also intended to examine the potential for improved diagnostic accuracy of the condition, by examination of the data collected during the limited programme of clinical examinations.

The detailed objectives were:

vii. To investigate which groups of respiratory symptoms tend to be reported together.

viii. To identify clinically relevant syndromes based on these symptom clusters.

ix. To investigate whether and how these syndromes differentiate between individuals who were defined to have work-related and non-work related asthma in the previous questionnaire study.

x. To investigate whether and how these syndromes differ by occupation and exposure, with particular reference to differences between probable irritant and allergic asthma.

xi. To identify symptom combinations associated with clinical diagnosis of work-related asthma, and compare these to the syndromes identified by clustering.

xii. To identify any aspects of the clinical examination and diagnosis process that could usefully be incorporated into a self-administered questionnaire.

2.2 PLAN OF WORK

It was identified that, to meet the detailed objectives, it would be necessary to carry out the following tasks:

2.2.1 Literature Review

Review recent literature on development and validation of questionnaires to identify asthma and other respiratory diseases.

2.2.2 Cluster analysis of symptoms

Extract relevant questionnaire data from previous community-based project. Apply multivariate statistical methods to analyse the inter-relationships between questionnaire responses on symptoms of asthma and other respiratory conditions, and identify combinations of symptoms forming clinically relevant syndromes.

2.2.3 Exposure assessment

Extract data on jobs (current when first symptoms experienced) from community study project, including SIC and SOC codings. Characterise each job in terms of likely exposure to important asthmagens and/or respiratory irritants.

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2.2.4 Comparison of symptoms and exposure indices

Compare symptoms and syndromes with the exposure indices, to determine whether any particular exposures are associated with particular types of asthma.

2.2.5 Analysis of clinical data

Extract data from clinical examinations of 82 subjects who attended these. Compare clusters of symptoms to those in the whole study population, and review individual recording forms. Recommend or suggest any aspects that might usefully form part of a questionnaire

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3. METHODS

3.1 LITERATURE REVIEW

Searches were made of the databases on the OSH-ROM CD-ROM (which includes HSELINE, NIOSHTIC and CISDOC) and MEDLINE. Keywords used were “asthma”, “questionnaire”, “sensitivity” and “specificity”. A number of relevant papers were identified and copies of those not already held were obtained. Additional background information on asthma was obtained from open websites on the Internet.

3.2 DATA EXTRACTION & CHECKING

3.2.1 Getting the data

The data for this study were extracted from the final data set from the postal questionnaires for the IOM community study of lung health in the West Lothian and Central regions of Scotland conducted in 1997. In this study, as discussed previously, we limited the analysis of symptoms to only those 14,090 participants who had responded to the first or second mailing in the IOM community study.

3.2.2 Checking validity

Definition of ‘LFS’ variables

‘LFS’ allergy / rhinitis, ‘LFS’ chronic bronchitis and ‘LFS’ asthma were defined using questions based closely on the Labour Force Survey questionnaire on self-reported work­related illness (Hodgson et al, 1993), adapted for self-administration. Allergy / rhinitis was defined as symptoms of allergies, rhinitis or hayfever. Chronic bronchitis was defined as bronchitis, chronic obstructive airways disease (COAD), emphysema, cough and phlegm, persistent cough, phlegm from chest and other chronic obstructive pulmonary disease (COPD). The definition of asthma consisted only of participants who reported asthma.

Individuals were asked whether they had consulted a doctor about their most serious illness and if so to report the diagnosis given by the doctor. In addition, participants were asked to describe the illness in their own words. Up to three illnesses were coded for both the doctor’s diagnosis and the self-reported description for each individual. Symptoms were coded, for example, as ‘LFS’ asthma if a diagnosis of asthma was given for any of the three doctor’s diagnoses or any of the three self-reported descriptions. The classification of ‘LFS’ allergy / rhinitis and ‘LFS’ chronic bronchitis was done in an identical manner to that of ‘LFS’ asthma.

In the IOM postal community study of lung health, results were based on all 16990 individuals who participated in the 1st, 2nd and 3rd mailings of the questionnaire. Also, ‘LFS’ asthma included those individuals who reported allergies, rhinitis and hayfever, hence there was no separate allergy category for these. Symptoms were coded, for example, as ‘LFS’ asthma if a diagnosis of asthma was given for the doctor’s diagnosis. The self-reported diagnosis was only used if no doctor’s diagnosis had been used, in which case symptoms were coded as ‘LFS’ asthma if any of the three self-reported illness codes were described as asthma. The same approach was used to classify ‘LFS’ chronic bronchitis in the IOM community study.

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Definition of improvement in chest symptoms when away from work for a week or longer

Participants were asked to record what happened to their chest symptoms, as a whole in the last 12 months, when they were away from work for a week or longer (Q12). Initially, this question had four separate components, which were combined to form a single variable with four factors. Valid answers were accepted only if subjects gave one answer to either Q12A or Q12B or Q12C or Q12D. Combinations of two or more responses to Q12 were considered to be invalid thus could not be classified unambiguously. A total of 44 individuals gave more than one response to Q12 hence these responses were invalid and were treated as missing. Question 12 was dependent on whether the subjects had chest symptoms (Yes to any one of Q8-Q11), hence those subjects who had no chest symptoms were coded as not applicable.

Definition of symptoms brought on by being in a particular place

Individuals who had experienced chest symptoms were asked to give a Yes or No answer to the question “Have these symptoms been brought on by being in a particular place?” (Q14). Those who answered Yes to this question were then asked to give details of which places brought on their chest symptoms. A maximum of three places were given by each individual (Q14A, B and C). During the IOM community study of lung health these places were coded into those that were work-related and those that were non-work related. A variable was then derived to indicate whether participants’ chest symptoms were brought on by being in a particular work-related place or not.

The leading question (Q14) was dependent on whether individuals had experienced chest symptoms or not. Those who had not experienced chest symptoms were coded as “No chest symptoms”. For the remaining participants who had experienced chest symptoms, the supplementary questions (Q14A, B and C) were dependent on whether the individuals had answered Yes or No to the leading question. Hence those who had answered No to Q14 were coded as having chest symptoms that were not brought on by being in a particular place. Finally, for the participants who answered Yes to Q14, the place given was coded into work­related if one or more of the three places given were work-related and places were coded as non-work related otherwise. Where individuals gave no information on chest symptoms and no information on either Q14 or no information on all of Q14A, B, and C then these subjects were coded as missing.

Definition of symptoms brought on by carrying out a particular activity

The classification of chest symptoms brought on by carrying out a particular activity (Q15) was done in an identical manner to that for being in a particular place. Participants who had experienced no chest symptoms were coded as such. Individuals who had experienced chest symptoms that were not brought on by carrying out a particular activity were coded accordingly. Participants who answered Yes to Q15 were coded as having chest symptoms that were brought on by carrying out a particular activity if one or more of the three activities given were work-related and activities were coded as non-work related otherwise. Where individuals gave no information on chest symptoms and no information on either Q15 or no information on all of Q15A, B, and C then these subjects were coded as missing.

Re-coding of breathing problems

Individuals were asked, from a choice of three possible statements, which of them best described their breathing (Q22). This question, as mentioned, initially had three separate components, which were combined to form a single variable. Valid answers were accepted only if one answer was given to either Q22A or Q22B or Q22C. Responses were treated as invalid, and therefore could not be classified unambiguously if an answer was given to more

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than one of Q22A, Q22B or Q22C. Sixty three participants gave invalid responses to Q22 and hence their responses were treated as missing.

Definition of cough for as much as 3 months each year

The following questions regarding coughing up phlegm from the chest were asked:

“Do you usually cough up phlegm from your chest first thing in the morning?” (Q24A);

“Do you usually do so on most days for as much as three months each year?” (Q24B);

“Do you usually cough up phlegm from your chest during the rest of the day or at night (Q25A);

“Do you usually do so on most days for as much as three months each year?” (Q25B);

Questions 24A and 25A were combined to form an indicator variable denoting whether individuals did or did not cough up phlegm from their chest, regardless of the time. To form an indicator variable denoting whether a participant’s cough lasted for as much as three months each year, Q24B was then combined with Q25B. A new variable was then derived from this to indicate whether subjects had experienced a cough and whether this had gone on for as much as three months each year.

Forty nine subjects had answered No to having coughed up phlegm from their chest (i.e. No to both Q24A and Q25A) and Yes to usually coughing up phlegm from the chest like this on most days for as much as three months each year (i.e. Yes to both Q24B and Q25B). These subjects could not be classified unambiguously, so were treated as missing. Where Q24A and Q25A were both missing, therefore, individuals could not be classified unambiguously into those who cough and those who do not cough, regardless of the responses to Q24B and Q25B. These individuals were treated as missing. For participants who were classified as having a cough and who answered either No to Q24B and gave no information on Q25B or gave no information on Q24B and answered No to Q25B, their responses were also treated as missing. Finally, where individuals had given no information for all of Q24A, Q24B, Q25A and Q25B these individuals were treated as missing.

3.2.3 Missing data and the final data set

Missing data

Since this study was based on a large sample, for the small number of cases where the intention of an individual completing a particular question was not clear this was coded as missing and hence dropped from the analysis. Examples of this for derived variables and for variables that required to be recoded are described above.

Tables 3.1 to 3.7 show the amount of data availability for each symptom prior to principal components analysis, the factor analysis and the cluster analysis for all subjects who participated in mailing 1 or mailing 2. A total of 14,090 subjects participated in mailing 1 or 2.

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Table 3.1 Distribution of serious illnesses caused by or made worse by work (full data set of 14,090 subjects prior to analysis). Each cell contains the number of participants.

LFS & IOM coding for Yes No Not applicable Missing serious illnesses (not employed) allergy / rhinitis 9 13566 427 88 asthma 84 13491 427 88 chronic bronchitis 53 13522 427 88

Table 3.2 Distribution of relevant symptoms (full data set of 14,090 subjects prior to analysis).

Each cell contains the number of participants.

Symptoms Yes No Missing wheeze in last 12 months 2993 11029 68 chest tightness in last 12 months 1774 12216 100 spontaneous shortness of breath in last 12 months 1718 12289 83 nocturnal shortness of breath in last 12 months 975 12912 203 asthma attacks 1366 12634 90 current asthma 736 13144 210 medication for asthma 994 12892 204 doctor diagnosed asthma related to work 95 13766 229 chest tightness caused by dust 1106 12456 528 shortness of breath caused by dust 1383 12070 637

Table 3.3 Distribution of improvement in chest symptoms when away from work (full data set of

14,090 subjects prior to analysis). Each cell contains the number of participants.

Improvement in chest symptoms when away from Numbers of participants work for a week or longer Yes 651 No 2478 Not applicable (no chest symptoms) 10443 Missing 518

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Table 3.4 Distibution of chest symptoms brought on by being in a particular work-related place (full data set of 14,090 subjects prior to analysis). Each cell contains the number of

participants.

Chest symptoms have been brought on by being in a Numbers of participants particular work-related place No symptoms 10443 Chest symptoms, not brought on by a particular place 2846 Chest symptoms, non work-related place 298 Chest symptoms, work-related place 380 Missing 123

Table 3.5 Distribution of chest symptoms brought on by carrying out a particular work-related

activity (full data set of 14,090 subjects prior to analysis). Each cell contains the number of participants.

Chest symptoms have been brought on by carrying Numbers of participants out a particular work-related activity No symptoms 10443 Chest symptoms, not brought on by a particular activity 2618 Chest symptoms, non work-related activity 825 Chest symptoms, work-related activity 81 Missing 123

Table 3.6 Distribution of breathing trouble (full data set of 14,090 subjects prior to analysis).

Each cell contains the number of participants.

Regular breathing trouble that always gets Numbers of participants completely better No trouble 12012 Regular trouble 881 Breathing never quite right 839 Missing 358

Table 3.7 Distribution of cough (full data set of 14,090 subjects prior to analysis). Each cell

contains the number of participants.

Cough Numbers of participants No cough 11254 Cough, duration unknown 54 Cough (not as much as 3 mo/yr) 413 Cough (as much as 3 mo/yr) 1892 Missing 477

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Final data used in analysis

For the Principal Components analysis, Factor analysis and the Cluster analysis, where a participant had missing data for any one symptom, this participant was excluded from the analysis. Hence only those subjects who had complete data for 18 symptoms were included in the analyses. By taking all of the missing data into account, the final data set used in the analysis consisted of 11,941 participants. Tables 3.8 to 3.14 display data descriptions only for this group.

Table 3.8 Distribution of serious illnesses caused by or made worse by work (final data set of

11,941 subjects excluding all missing data). Each cell contains the number of participants.

LFS & IOM coding for serious illnesses Yes No Not applicable (not employed)

allergy / rhinitis 7 11581 353 asthma 56 11532 353 chronic bronchitis 23 11565 353

Table 3.9 Distribution of relevant symptoms (final data set of 11,941 subjects excluding all

missing data). Each cell contains the number of participants.

Symptoms Yes No wheeze in last 12 months 2136 9805 chest tightness in last 12 months 1295 10646 spontaneous shortness of breath in last 12 months 1192 10749 nocturnal shortness of breath in last 12 months 672 11269 ever had an asthma attacks 1021 10920 had an attack of asthma at any time in last 12 months 529 11412 currently taking medication for asthma (eg inhalers or tablets) 708 11233 ever been told by doctor that have asthma caused by or made worse by 72 11869 work

chest tightness caused by being in dusty part of house, with animals or 826 11115 near feathers

shortness of breath caused by being in dusty part of house, with 925 11016 animals or near feathers

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Table 3.10 Distribution of improvement in chest symptoms when away from work (final data set of

11,941 subjects excluding all missing data). Each cell contains the number of participants.

Improvement in chest symptoms when away from Numbers of participants work for a week or longer Yes 533 No 1985 Not applicable (no chest symptoms) 9423

Table 3.11 Distribution of chest symptoms brought on by being in a particular work-related place (final data set of 11,941 subjects excluding all missing data). Each cell contains the

number of participants.

Chest symptoms have been brought on by being in a Numbers of participants particular work-related place No symptoms 9423 Chest symptoms, not brought on by a particular place 2013 Chest symptoms, non work-related place 225 Chest symptoms, work-related place 280

Table 3.12 Distribution of chest symptoms brought on by carrying out a particular work-related

activity (final data set of 11,941 subjects excluding all missing data). Each cell contains the number of participants.

Chest symptoms have been brought on by carrying Numbers of participants out a particular work-related activity No symptoms 9423 Chest symptoms, not brought on by a particular activity 1855 Chest symptoms, non work-related activity 603 Chest symptoms, work-related activity 60

Table 3.13 Distribution of breathing trouble (final data set of 11,941 subjects excluding all missing

data). Each cell contains the number of participants.

Regular breathing trouble that always gets Numbers of participants completely better No trouble 10727 Regular trouble 639 Breathing never quite right 575

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Table 3.14 Distribution of cough (final data set of 11,941 subjects excluding all missing data).

Each cell contains the number of participants.

Cough Numbers of participants No cough 10127 Cough, duration unknown 33 Cough (not as much as 3 mo/yr) 332 Cough (as much as 3 mo/yr) 1449

3.2.4 A problem question

As we have shown, most of the replies to the questionnaire showed relatively good data quality, with few missing values. In so far as it was possible to tell, the answers also showed reasonable consistency between questions. There was, however, one place where a doubt was raised about the reliability of the responses.

This concerned questions 12 and 13. These were supplementary questions, to be answered only if at least one of questions 8 to 11 indicated that the subject had experienced chest symptoms in the last 12 months. The wording of the questions was:

12. Thinking about your chest symptoms on the whole in the last 12 months, what happened to them when you were away from work for a week or longer?

They improved/They stayed the same/ They got worse/I have not worked in the last 12 months

13. Thinking about your chest symptoms on the whole in the last 12 months, what happened to them on working days compared to non-working days?

They improved/They stayed the same/ They got worse/I have not worked in the last 12 months

Table 3.15 summarises the responses. A total of 10443 had no symptoms and legitimately omitted both the supplementaries, while 419 should have replied but did not to either. Another 869 replied to both questions that they had not worked in the relevant 12 months, while a very few gave this answer to one question but not the other. The important entries are in bold characters in the bottom right of the table. The largest part of these, 1466, reported no change either at holiday or at work. There were 174 whose symptoms improved away from work for more than a week and were worse at work, which is logically consistent; but almost the same number, 166, claimed an improvement both at work and away from work. Although not logically impossible, say if a weekend hobby involved exposure to an asthmagen, one would not expect the numbers to be so similar. On reflection, the wording of Q13, unlike Q12, mentions both working and non-working days; and improvements away from work would be answered in the opposite direction for Q13 from that for Q12. We therefore concluded that there was scope for confusion in Q13 about which condition (at work, away from work) an improvement referred to. There is no possible check that can now be done on this, but we believe that misinterpretation of the direction of Q13 is a plausible explanation for the apparently contradictory answers from these 166 participants, if some but not all had interpreted the question in the opposite direction from that intended. In the circumstances, we decided to omit Q13 from all the analyses. We would also recommend that this question should be redesigned and reworded before inclusion in any future questionnaire on occupational asthma.

12

Table 3.15 Combinations of replies to questionnaire replies to Questions 12 and 13

Q13: Q12: Symptom behaviour away from work for more than a week symptom No Notbehaviour Missing symptoms worked Worse Same Improved All at work

MissingNo symptoms Not worked Improved SameWorse

All

419

0

25 19 51 4

518

0

10443

0 0 0 0

10443

21

0

869 5

17 5

917

1

0

1 11 13 2

28

10

0

4 28

1466 25

1533

16

0

9 166 286 174

651

467

10443

908 229

1833 210

14,090

3.3 MULTIVARIATE ANALYSES: CLUSTERS AND FACTORS

The literature review identified few papers that had looked at the strength of associations or clustering between a set of symptoms. The few that had, used the multivariate techniques of principal components analysis and subsequent factor analysis. We have used this on the present data, and have also employed cluster analysis on the symptoms, as described below. For comparability, both sets of analyses were carried out on the same data set of 11941 subjects, after exclusions for missing data, described in Section 3.2.

3.3.1 Principal components and factor analysis

Principal components analysis is a descriptive technique for identifying the principal sources of variation in a multivariate data set (see, e.g., Chatfield and Collins, 1980), allowing for the possibility that some or all of the variables may be inter-correlated. The input to the procedure is a matrix either of variances and covariances, or (to standardise variables with different variances) of correlations. We have used correlations in our analyses.

The procedure identifies the linear combination of variables that account for the largest possible amount of the variation in the correlation matrix. This is the first principal component. The second component is the combination that has the next largest amount of variation and is uncorrelated with the first. There are as many components as there are input variables.

Often, the first few principal components contain enough variation to be of interest, and the rest are ignored as "noise". Interpretation of the components is often difficult, since each may have contributions from a large number of the input variables. A commonly used aid to interpretation is rotation; where a chosen (possibly small) number of the largest components are rotated algebraically in an attempt to find an arrangement that explains the same total amount of variation, but where the contributions of the input variables are either as large or as small as possible. The rotated components, or "factors", may then each be associated with just a few input variables, suggesting that these variables behave similarly.

The rotation of a selected few components is often described as "factor analysis". Chatfield and Collins (1980), amongst others, point out that this term was originally applied to a similar technique with a more explicit model structure and distributional assumptions. However, it

13

has attained common usage as a synonym for factor rotation, particularly in the social sciences.

3.3.2 Cluster analysis

Cluster analysis aims to find natural groupings of objects. The objects are often data units, e.g.subjects, species, etc, and they are clustered on the basis of their values on a number of variables. The present case, where it is the variables we wish to cluster, is less common but by no means unknown.

To begin a cluster analysis on variables, it is necessary to define a measure of similarity between variables. An obvious measure is some sort of correlation coefficient, since if two variables are highly correlated, they may be regarded as giving similar effects (Chatfield and Collins, 1980). For input, we have used the same matrix of correlations as was used for the principal components analysis.

The procedure identifies the two variables that are most similar (i.e. have the highest correlation) and combines them to form a cluster. The correlation between this cluster and the other variables is calculated, and henceforth the cluster is treated as a single object. The procedure repeats, combining variables into clusters and clusters with variables or other clusters.

Different results can be obtained depending on the method chosen for calculating the correlation of a cluster with other objects, known as the linkage method. In this work we have chosen a method of linkage based on defining the distance to a cluster as the distance to its nearest member, known as "single linkage". We have checked the sensitivity of the results to this assumption by repeating the analyses using a second method, "average linkage", where distance is measured between the means of the variables in clusters.

3.4 EXPOSURE ASSESSMENT

3.4.1 General approach

Because occupational asthma can be caused by exposure to many substances, we have characterised risks of exposure for several groups of asthmagenic and/or irritative agents. The data from the postal survey do not include self-reports of exposure to specific substances, but do include recall, from each individual reporting asthmatic symptoms, of the job held at the onset of those symptoms. We have therefore made an exposure assessment based on those jobs.

Kennedy et al (2000) developed a method suitable for estimating exposure risks to asthma based on job and industry titles (in their case, international standard classifications of occupations, ISCO-88: ILO, 1991). They constructed a job-exposure matrix (JEM), using expert judgement to attach likely exposures to the jobs, and we have used a similar approach here.

3.4.2 Grouping of occupations

At its simplest, a job-exposure matrix (JEM) is a two-dimensional matrix with the occupational grouping codes on one axis and categories for hazards to which those occupations might be exposed on the other. Here, occupations held at the time symptoms were first experienced had been coded during the original studies, using the Standardised Occupation Classification (SOC) and Standardised Industrial Classification (SIC). Inspection

14

of the data file showed that there were over 1000 combinations of SOC and SIC code, so that considerable grouping was required.

Jones et al (1998) used 29 groupings in a self-reported work-related illness household survey, but review of these by an occupational hygienist suggested that some groupings were too broad for the present study. For example, in the Jones et al (1998) original grouping, veterinarians were grouped in the “other education and welfare” category along with psychologists, clergy etc. Here, it was thought that the exposure of veterinarians would be significantly different from those other workers and they were therefore placed in a “veterinary” category. For the most part, it was judged that groupings of occupation, using simply major groupings of the SOC code, would be sufficient to characterise asthmagenic exposure for most occupations. However, some occupations could have different exposures in different industries, and in these cases the SOC grouping was differentiated by industry.

The 298 SOC codes present in the data set were grouped to produce the 107 occupational groups listed in Table 3.16. Nine of these groups (17, 25, 51, 54, 75, 77, 85, 86, 87) were subdivided according to distinctions between industries in the SIC code. Exposure assessments were made and entered to the JEM for each of the 220 resulting groups and subgroups.

15

Table 3.16 Asthmagenic hazards on the exposure axis of the job exposure matrix

Group Occupational group Subgroups number 1 Professional & related supporting management 1 2 Teaching 1 3 Medical practitioners 1 4 Radiographers 1 5 Nursing and midwifery 1 6 Dental / medical technicians 1 7 Ambulance staff 1 8 Dental 1 9 Other education and welfare 1

10 Physiotherapists 1 11 Chiropodists 1 12 Occupational and speech therapists, psychotherapists, therapists n.e.c 1 13 Environmental health officers 1 14 Driving instructors 1 15 Occupational hygienists and safety officers 1 16 Literary, artistic and sports 1 17 Science and engineering - laboratory work 17 18 Science and engineering - chemists 1 19 Science and engineering - physicist, geologists and meteorologists 1 20 Science and engineering - chemical engineering 1 21 Science and engineering - civil eng. 1 22 Science and engineering - mechanical eng 1 23 Science and engineering - electrical eng 1 24 Science and engineering - other design 1 25 Science and engineering - other process and planning 11 26 Science and engineering - Building 1 27 Science and engineering - other 1 28 Ship and hovercraft officers 1 29 Managerial - production, mining etc 1 30 Managerial - financial and similar 1 31 Managerial - warehouses and stores 1 32 Managerial - transport and garage 1 33 Managerial - food and accommodation 1 34 Managerial - other 1 35 Clerical and secretarial 1 36 Selling 1 37 Selling - outside 1 38 Police officers (inspector and above) 1 39 Police officers (sergeant and below) 1 40 Fire service officers (station officer and above) 1 41 Fire service officers (leading fire officer and below) 1 42 Prison service 1 43 Traffic wardens 1 44 Security services 1 45 Catering 1 46 Food service 1 47 Care workers - hospital 1 48 Care workers - children 1 49 Hair 1 50 Beauticians 1 51 Cleaners 27 52 Caretakers 1 53 Other personal services 1 54 Farming and horticulture 13 55 Fish hatcheries 1

16

56 Forestry 1 57 Window dressers 1 58 Veterinary 1 59 Metal processing - plumbers, heating engineers 1 60 Metal processing - welding 1 61 Metal processing - furnace and foundry 1 62 Metal processing - automobiles 1 63 Metal processing - other 1 64 Metal processing - Electroplaters 1 65 Electrical processing 1 66 Textile processing - bleaching, dyeing 1 67 Textile processing - production 1 68 Textile processing - cleaning 1 69 Textile production - other 1 70 Textile processing - others 1 71 Other processing - printing 1 72 Other processing - wood 1 73 Other processing - wood moulds 1 74 Other processing - bakers 1 75 Other processing - butchers 3 76 Other processing - fish and poultry 1 77 Other processing - other 11 78 Other processing - spray painting 1 79 Other processing - rubber & plastic 1 80 Other processing - glass 1 81 Other processing - chemical, glass and petroleum 1 82 Other processing - paper products 1 83 Other processing - chemical, plastics related 1 84 Other processing - mines, quarries 1 85 Other processing - other 12 86 Repetitive assembly line workers 14 87 Repetitive assembly inspectors 14 88 Repetitive assembly packing and weighing 1 89 Construction - painting, decorating 1 90 Construction - woodworking 1 91 Construction - building 1 92 Construction - plasterers 1 93 Construction - glaziers 1 94 Construction - scaffolders 1 95 Construction - floor, carpet fitters 1 96 Construction - water and sewerage 1 97 Construction - pipe layers 1 98 Construction - mine and quarry 1 99 Construction - other 1

100 Construction - not further classified 1 101 Coal mining 1 102 Road transport operatives 1 103 Rail transport operatives 1 104 Other transport and machine operatives 1 105 Materials moving and storing 1 106 Armed forces 1 107 Miscellaneous 1

Total occupational groups in JEM

17

220

3.4.3 List of hazards

For the hazards axis, we assigned a list of hazard types based on known risk factors for occupational asthma (Table 3.17). These were based on the hazard types used by Kennedy et al (2000), who chose to group exposures mainly over specific agents, as it was expected that most job codes would be too broad to allow valid exposure estimates for the many specific agents linked to asthma. The starting point for this grouping was the list from Chan Yeung and Malo (1993) in which over 150 chemicals and biological substances were stratified into high and low molecular weight agents. Kennedy et al also included specific agents and mixed environments because the exposure axis was based on both current knowledge about risk factors and the practical constraints imposed by both the coding systems. We have subdivided items in the list of Kennedy et al (2000) where it was felt that they were too broad.

A list of occupations where exposures to these hazards are common was developed to aid the assessors (Appendix 2). This list was developed after consulting various sources, for example HSE (1996, 1997) and Clinique des Maladies Respiratories (1999).

3.4.4 Indices of exposure

Completion of a JEM requires, for each combination of occupation and hazard, the assignment of an index or indices of exposure, whose form can range from a simple Yes/No classification, or probability of significant exposure, to a quantitative index of exposure such as mean airborne concentration. For the present study, quantitative concentrations were not available (and may anyway be less relevant for asthmagens). Instead, we have applied three separate indices for each of the hazards. The first was a simple binary variable indicating significant probability of exposure to the hazard. This was classified as positive where there was judged to be a high likelihood that over 50% of the subjects would work or come into contact with these substances as part of their normal, everyday work.

The other two indices concerned likely frequency of exposure, and were completed only where the first was positive. Frequency was estimated of days exposed per year (classified as daily, regularly, weekly, monthly, and coded as 240, 120, 40, 12), and hours per day (grouped as all the time, most of the day, half of the day or infrequently, and coded as 8, 6, 4 or 1). These codings permit the construction of a number of semi-quantitative indices of exposure.

Because peak exposures might be important for sensitisation, a further assessment was made, classified as positive if there was a moderate to high probability of accidental or periodic exposure to very high levels of irritant gases or fumes. The additional assessments of frequency were not relevant.

Notes of assumptions made when assessing categories of exposure were also kept.

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Table 3.17 Asthmagenic hazards assessed for the exposures axis of the Job Exposure Matrix

Low risk

1. General: exposure to all substances associated with risk of asthma or to other irritating chemicals.

2. Irritants but not high peaks 3. Exhaust fumes.

High risk

High molecular weight agents:

Derived from animals

4. Rodents, livestock 5. Fish, shellfish processing 6. Arthropods, mites or insect proteins

Derived from plants

7. Latex 8. Flour dust and grain 9. Other, miscellaneous e.g. soya bean dust, tea dust and green coffee bean dust 10. Bioaerosols (moulds, endotoxins, etc) 11. Biological enzymes (proteolytic enzymes)

Low molecular weight agents

12. Highly reactive chemicals (cross-linking agents)- anhydrides, amines, reactive dyes, glues, others excluding biocides.

13. Biocides, for example glutaraldehyde 14. Isocyanates 15. Sensitising drugs e.g. antibiotics, cimetidine, ispaghula powder, ipecacuanha

tablets. 16. Industrial cleaning agents 17. Wood dusts for example, hard wood (cedar, oak and mahogany) and soft 18. Metal sensitisers e.g chromium (VI) compounds, cobalt (metal and compounds)

Mixed environments or agents

19. Metal working fluids. 20. Organic particulate or exhaust fumes. 21. Textile industry exposures 22. Accidental or periodic exposure to very high levels of irritant gases or fumes

(peak exposures) 23. Solder / colophony fume 24. Welding fume (stainless steel welding)

19

3.5 STATISTICAL ANALYSIS OF ASSOCIATIONS

Principal analyses of associations were between symptoms and syndromes and aspects of occupation held when symptoms first appeared. Analyses used standard statistical models, the form and details depending on the nature of the variables involved. Classifications of health effects were always binary, i.e. classified as present or absent. Where they were analysed in relation to a binary exposure variable, such as whether or not an occupation implied exposure to a particular hazard, the analysis was that for association in a 2×2 contingency table. This is usually quantified by the odds-ratio: if the cells in the table are labelled a, b, c, d so that a and d are the diagonal terms, then the odds ratio is calculated as

OR = (ad)/(bc).

Its statistical significance can be tested (Breslow and Day, 1980) by noting that the natural logarithm of the odds ratio is approximately normally distributed, with standard error

stand. err. {loge(OR)} = sqrt(1/a + 1/b + 1/c + 1/d).

The exposure variables indicating duration of exposure in a typical year were expressed on a quantitative scale with many possible values, and were treated as if continuous. The standard analysis for these was to apply a logistic regression analysis, which relates the log of the odds ratio to a linear regression function. Here, the exposure variable was the sole predictor in the logistic regression model.

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4. RESULTS

4.1 LITERATURE REVIEW

4.1.1 Defining asthma and occupational asthma

Research into occupational asthma is hampered by multiple problems of definition. There is the diagnostic problem of defining exactly what constitutes asthma in an individual; and there is the further complication of defining what is meant by occupational asthma. For the latter question, it is pertinent to ask for what purpose the definition is needed. For example, for the operation of the SWORD scheme for the notification of new cases of occupational disease (Ross et al, 1995), it is appropriate to apply a definition of an asthmatic condition caused initially by exposures in the workplace. This definition would also be relevant for industrial compensation schemes.

Wagner and Wegman (1998) argue that, in the context of prevention, it is relevant to consider also episodes of asthma brought about by exposure to irritants in the workplace, even when the asthmatic condition pre-exists and may in fact be non-occupational in origin. Setting themselves the goal of "preventing all acute and chronic asthma-related conditions in all workers potentially at risk", they note that this goal implies that "there are two populations at risk for occupational asthma: those with apparently normal airways and those with hyper­responsive airways from whatever cause". This underlines the twin themes that asthma as a condition is characterised by serial events, labelled "attacks"; and that it is important to distinguish the prevalence of asthma (numbers or percentage of a population who have the condition) from its incidence (number or rate of new cases over a period).

Clarity over these issues is important to understanding occupational asthma, but all such distinctions require that asthma itself be clearly defined. However, this in itself is complicated by the episodic nature of the condition, by the wide range of exposures that can trigger attacks, and by wide variations between individuals in their sensitivity to these exposures and the severity of their reactions to them. All these complications are relevant for the reliable detection of asthma.

4.1.2 Development of modern questionnaires

Compared to other methods of detecting respiratory diseases and conditions, questionnaires have considerable advantages in cost terms. Notable successes in this area are respiratory questionnaires from the British Medical Research Council and from the American Thoracic Society. These have been used in many studies of respiratory health, in general and in occupational contexts. However, while their questions have been shown to be reproducible and valid for the characterisation of conditions such as chronic bronchitis and general breathlessness, they were not designed for the study of asthma and their questions were not designed to identify the symptoms of asthma.

Burney and Chinn (1987) describe the development of a self-adminstered questionnaire specifically aimed at measuring the prevalence and distribution of asthma, under the auspices of the International Union Against Tuberculosis (IUAT, now IUATLD with an interest including various lung diseases). They discuss a number of question types, and note that questions on self-awareness of asthma such as "Do you have asthma?" are open to a range of "cultural, psychologic and sociologic influences", and to biases in medical diagnosis. However, they note that more specific questions about typical asthmatic symptoms such as wheezing in the chest may not be sufficiently specific, since they are caused by many

21

conditions other than asthma. The IUAT questionnaire was designed with all these complications in mind. It is notable that most of the questions regarding the presence of asthmatic symptoms contain the qualifying phrase "in the last twelve months", which is consistent with attempts to measure disease prevalence. In this it differs from the ATS-DLD questionnaire, which asks e.g. "Does your chest ever sound wheezy or whistling?", and "For how many years has this been present".

Venables et al (1993) proposed a different set of nine questions, all qualified as current (during the last four weeks):

1 If you run, or climb stairs fast do you ever cough? YES / NO wheeze? YES / NO get tight in the chest? YES / NO

2 Is your sleep ever broken by wheeze? YES / NO difficulty with breathing? YES / NO

3 Do you ever wake up in the morning (or from your sleep if a shift worker) with wheeze? YES / NO difficulty with breathing? YES / NO

4 Do you ever wheeze if you are in a smoky room? YES / NO if you are in a dusty place? YES / NO

They do not discuss how these questions relate to those of the IUAT questionnaire, and in fact do not mention this attempt at standardisation, which was released publicly in 1986. It is not clear how the restriction of attention to the last four weeks rather than the last 12 months would affect agreement and validity.

Other attempts to characterise asthma include the addition of questions on asthmatic symptoms to the Medical Research Council and American Thoracic Society questionnaires (MRC, 1986; Ferris, 1978).

4.1.3 Validation

Burney and Chinn (1987) describe succinctly the requirements for acceptance of a questionnaire, notably repeatability and validity. Repeatability presents some difficulties, in that presence and severity of asthmatic symptoms can vary with time, perhaps through changes in exposure, or through the use of medication. Over short periods, however, the questions of the IUAT showed good repeatability, and this persisted after translation into French, German and Finnish (Burney et al, 1989b). Lebowitz and Burrows (1976) in comparing three respiratory symptoms questionnaires, concluded more generally that responses on particular symptoms showed little effect from "minor variations in wording, order of questions, method of administration, inclusion of other questions, or time between questionnaires (as long as this interval was less than a month)".

Burney and Chinn (1987) note that the issue of how to test validity, defined as "how far the questionnaire does or does not distinguish asthmatic patients from others", is more controversial than repeatability, because of the problems in defining the disease. Discussion of questionnaire validity presupposes "that asthmatic patients can be distinguished from normal subjects by some other method". They add that "it can be argued that, in any rigorous sense, this condition not only is not but cannot be met". Each candidate criterion for definition, which might be used as a standard for validation, is flawed in some way. A definition in terms of variable airway obstruction requires a decision on how much obstruction is abnormal and how variable it should be before being labelled as such. (This is

22

the familiar problem of the arbitrariness of discriminating within a population with a continuous distribution of the measured characteristic.) No single biochemical marker of asthma is available. Physicians' diagnoses are variable and therefore contentious.

Burney and Chinn (1987) report that all of the above were rejected for validation of the IUAT questionnaire. They describe testing the questionnaire against non-specific bronchial reactivity, which is "closely related to a number of the major features of asthma including bronchial response to exercise, diurnal variation in airway obstruction and requirements for bronchodilator drug therapy". They add that reactivity testing can be standardised and is not greatly affected by social or cultural influences. Typically, a positive response is recorded if a sufficiently large fall in lung function is induced by exposure to some standard dose of a substance such as histamine or methacholine. Others have noted that such a definition still requires the selection of arbitrary discrimination points in continuous distributions, both in selecting the dose and in the size of the measured effect.

In a validation study in two English villages, bronchial reactivity was compared with two questions in almost 400 adult subjects. The first, "Have you had an attack of asthma in the last 12 months?", showed a sensitivity of 50%, and a specificity of 90%. The question "Have you had wheezing or whistling in your chest at any time in the last 12 months?" was more sensitive at 86%, but less specific at 72%. The sample was not random, so these figures could not be extrapolated directly to the community at large.

Burney et al (1989a, 1989b) describe further validation of the IUAT questionnaire against reactivity to histamine in this community and across Europe, yielding a range of consistent values for sensitivity and specificity. In addition to validating individual questions, they also carried out a logistic regression analysis, from which they constructed a linear predictor, a weighted combination of the answers to four questions, that had slightly better sensitivity and specificity. Abramson et al (1991) also chose to validate the IUAT questions against bronchial hyperresponsiveness measured after challenge with methacholine. Again, the question on wheeze performed best, with a sensitivity of 49% and specificity 86%.

These results and those from several other studies are summarised in Table 6 of Torén et al (1993), who noted a range of sensitivities for a question on wheeze, 48-100%, mean 68%; and specificities ranging 78-100%, mean 78%. They note that because bronchial challenge produces effects in a proportion of subjects that show no asthmatic symptoms, it is a flawed standard and will underestimate sensitivity. They suggest that a better standard for validation is "a combination of clinical physiologic investigations and a clinical judgement of the symptoms".

Stenton et al (1993) validated the modified MRC questionnaire against hyperresponsiveness to methacholine challenge in over 1000 shipyard workers and job applicants, and found lower sensitivity and specificity (28% and 73%). They suggest that these and similar findings in other working populations may reflect both the narrow age range of the populations, and absence of asthmatics with the most disabling symptoms (a healthy worker effect).

Venables et al (1993) validated their set of nine questions in over 200 London office workers on three occasions, showing good repeatability. Their chosen index was the number of positive replies, and they validated this against bronchial reactivity and against "Asthma in the last year". They report that "Two or more, or three or more, symptoms gave increased specificity for a history of asthma (85% and 92%), for bronchial hyperresponsiveness (87% and 94%), and for either (90% and 96%) without unduly compromising sensitivity (91% and 78%, 79% and 69%, 78% and 65%)". All symptom combinations gave equal weight to a positive result from each of the nine questions.

23

4.1.4 Discriminating between occupational and non-occupational asthma

The results of Stenton et al (1993) warn that questionnaire-based detection of asthma in the workplace may be less reliable than in community studies. Cookson et al (1986) studied over 100 young subjects before and after a seven-week period of grain handling work, and examined the ability of asthmatic history, skin prick tests and methacholine challenge to predict answers to symptom questions from the MRC questionnaire. There is some discussion of the purpose of pre-employment medical examinations, but the results show that any of the above examinations would predict fewer than 50% of those who subsequently develop symptoms.

Baur et al (1998) studied 229 subjects (bakers or hairdressers, or in contact with isocyanates or latex gloves) referred to determine eligibility for compensation of occupational airways disease. They compared histories of repeated dyspnoea and wheeze in the workplace with challenge tests with methacholine and with specific suspected causative workplace agents. Taking the specific challenges as a standard for occupational asthma, they concluded that "the MC test is not capable of reliably sorting out asthma patients from occupationally exposed nonasthmatic symptomatic subjects, or differentiating clearly between occupational and nonoccupational asthma". However, combining MC with a history of work-related symptoms had much greater sensitivity, and such high specificity that it could be used to screen out negatives, reducing the number of necessary laborious specific challenge tests.

Axon et al (1995) compared symptoms in 26 patients with occupational asthma and 29 with non-occupational asthma. They noted a much higher mean age at onset (43 yrs, 21 yrs). Holiday improvement was a more sensitive discriminator between occupational and non­occupational asthma than work-day deterioration, which (against expectation) failed to discriminate the groups. They discuss the possibility that some of the non-occupational group may have had an occupational component, again pointing to the difficulty using clinical diagnosis as a standard.

4.1.5 Clustering of symptoms

Most of the studies of validity of asthma questionnaires have focussed on questions one at a time. Exceptions include the approach of Venables et al (1993) in counting positive responses, and the logistic regression and predictor function of Burney et al (1989a). However, a few studies have looked at how the answers to different questions on respiratory symptoms relate to each other, and to what extent the information they hold is independent or is measuring (aspects of) a common underlying concept.

Principal components analysis (PCA) is a technique for deconstructing the linear correlation among variables. It identifies components that are linear combinations of the original variables, and that embody the largest amounts of the variation in the data. A common use of this technique is to identify a few components that encapsulate a suitably large proportion of the variation, and to interpret the loadings, that is the contributions of the variables to the derived components. Interpretation is often preceded by a rotation step, which seeks to transform (rotate) the components in such a way as to emphasise large and small loadings. Then, if a rotated component has high loading on only a few variables, and those variables are judged to be aspects of some general underlying concept, it is natural to interpret the component as relating to that concept. (Chatfield and Collins (1980) note that the rotation step is sometimes described as factor analysis, but suggest that the term should be reserved for procedures based on a fully specified factor model. However, the usage is now quite wide.)

Bai et al (1998) applied this technique to answers to the IUAT questionnaire in over 1500 adult subjects in two regions of New South Wales. From 17 questions, they identified four components that together accounted for 60% of the observed variation. After rotation, the

24

loadings of these components displayed an impressive degree of separations and were interpreted as showing the separate and independent constructs "asthma", "cough", "urgent medical visits", and "breathlessness". Only one question, on being woken with cough, did not contribute strongly to any of the four components. Those with urgent medical visits were essentially a subset of those with one or more positive replies to the questions in the "asthma" group. Asthma defined by this criterion was validated against bronchial hyperreactivity, and shown to relate. Although sensitivity and specificity were not presented, the data in the paper suggest values of 77% and 70% respectively. It seems likely that higher specificity might be achieved, at the cost of sensitivity, by requiring more than one positive reply.

Abramson et al (1991) applied the same technique to data from 827 aluminium smelter workers, but they included questions from a modified MRC questionnaire. Five rotated components accounted for 60% of the total variation in 21 variables, and were interpreted as "asthma", "bronchitis", "wheeze", "shortness of breath", and "(reaction to) dust". The components gave very similar loadings to IUAT questions and their MRC equivalents. The analysis appears not to have been done on the IUAT responses alone, and there was no external validation of the constructed components, only of individual questions.

4.1.6 Conclusions

There is no "gold standard" test for asthma. Various research teams have attempted to validate questionnaires against general and specific challenge tests and clinical judgements. Bronchial hyperreactivity has been favoured as objective and repeatable, but can be demonstrated in a non-negligible proportion of individuals without any symptoms of asthma. Support for clinical diagnosis is sparse.

Of questionnaire topics, wheeze is considered the most characteristic, but all single topics lack sensitivity. Combinations of say two or three symptoms can improve sensitivity at some cost to specificity.

Mostly, comparisons between indicators of asthma in the same individuals are not confounded by variables such as sex or smoking habit.

Asthma observed in the workplace may be either caused or exacerbated by workplace exposures. Discrimination on the basis of questionnaires is unreliable.

For the investigation of association between symptoms in the IOM survey data set, it seems likely that a combination of direct examination of a matrix of correlations or associations, plus an analysis for dimension reduction such as PCA, will give useful insight into the structure of the associations. Discriminant analysis e.g. by logistic regression will not be possible in the main data set, because there is no external diagnosis to predict. However, some such approach could be used to relate the IUAT-based questions to the self­classification of asthma.

4.2 ANALYSIS OF SYMPTOMS DATA

4.2.1 Principal Components Analysis ("Factor Analysis")

Table 4.1 shows the prevalences of reported symptoms. Principal components analysis was carried out on the correlation matrix between all the questions, and the first six components accounted for 82% of all the total variance of all the questions combined. Factor rotation (sometimes referred to as "factor analysis") on the six-component solution showed very good results, in the sense of producing factors that had sensible interpretations as clinical

25

syndromes. Additional components appeared to be unnecessary, and results for rotations using fewer components were found to combine variables in less plausible combinations, so we show only the six-factor solution. Table 4.2 shows the coefficients for the symptoms in each factor.

Table 4.1 Prevalence of symptoms

Symptoms %

Allergy / rhinitis (derived from LFS & IOM codes for Q5 & Q6) 0.06

Chronic bronchitis (derived from LFS & IOM codes for Q5 & Q6) 0.19

Asthma (derived from LFS & IOM codes for Q5 & Q6) 0.47

Wheeze in last 12 months 17.9

Chest tightness in last 12 months 10.8

Spontaneous shortness of breath in last 12 months 10.0

Nocturnal shortness of breath in last 12 months 5.6

Improvement in chest symptoms when away from work for a week or longer 4.5

Chest symptoms have been brought on by being in a particular work-related place 2.3

Chest symptoms have been brought on by carrying out a particular work­related activity 0.5

Ever had an asthma attack 8.6

Had an asthma attack in the last 12 months 4.4

Currently taking medication for asthma 5.9

Been told by doctor that have had asthma caused by or related to work 0.60

Never / rarely get trouble with breathing 89.8

Regular breathing trouble that always gets completely better 5.4

Breathing never quite right 4.8

Chest tightness when in dusty part of the house, with animals or near feathers 6.9

Shortness of breath when in dusty part of the house, with animals or near feathers 7.8

Cough up phlegm (day and/or night) for as much as 3 months each year 12.1

The total number of subjects with complete data on all symptoms is 11941.

The first factor is dominated by the symptom of wheeze, and questions about relationships with work (improvement when away from work, symptoms brought on by being in a particular work-related place, or being brought on by a work-related activity). Only 18% of the population complained of wheeze, and only 0.5 to 4.5% complained of the work-related symptoms: those with wheeze and work-relatedness might be considered to include those most likely to have work-related asthma: those with wheeze but not work-relatedness obviously might include mostly people with non-work wheeze.

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The second factor is dominated by specific complaints of asthma (asthma attacks, medication for asthma), and by nocturnal shortness of breath. This factor appears to represent the common features of asthma of almost any causation.

Table 4.2 Component loadings (Correlations) between factors and variables for the 18 symptoms

in the principal components analysis (after varimax rotation)

Factor Symptoms 1 2 3 4 5 6 Allergy / rhinitis (derived from LFS & IOM -0.01 0.02 0.99 <0.01 <0.01 0.03 codes for Q5 & Q6) Chronic bronchitis (derived from LFS & IOM 0.01 0.02 0.98 0.01 0.02 0.01 codes for Q5 & Q6) Asthma (derived from LFS & IOM codes for 0.02 -0.06 0.96 -0.01 0.01 -0.09 Q5 & Q6)

Wheeze in last 12 months 0.85 -0.22 0.01 -0.20 0.13 -0.07 Chest tightness in last 12 months 0.61 -0.42 0.01 -0.16 0.23 0.04

Spontaneous shortness of breath in last 12 0.55 -0.54 <0.01 -0.03 0.22 0.06 months

Nocturnal shortness of breath in last 12 months 0.31 -0.69 0.02 -0.05 0.26 0.10

Improvement in chest symptoms when away 0.92 -0.16 0.02 -0.11 0.09 -0.06 from work for a week or longer

Chest symptoms have been brought on by being 0.88 -0.22 0.01 -0.20 0.07 -0.08 in a particular work-related place

Chest symptoms have been brought on by 0.90 -0.23 <0.01 -0.14 0.10 -0.03 carrying out a particular work-related activity

Ever had an asthma attack 0.20 -0.68 0 -0.40 -0.13 -0.18 Had an asthma attack in the last 12 months 0.19 -0.79 <0.01 -0.28 -0.06 -0.16 Currently taking medication for asthma 0.23 -0.76 <0.01 -0.33 -0.04 -0.14

Been told by doctor that have had asthma 0.08 -0.14 0.05 -0.03 0.07 -0.95 caused by or related to work

Breathing trouble 0.41 -0.55 0.03 -0.10 0.41 -0.01 Chest tightness when in dusty part of the house, 0.24 -0.30 <0.01 -0.83 0.09 -0.02 with animals or near feathers Shortness of breath when in dusty part of the 0.26 -0.33 -0.01 -0.82 0.11 -0.01 house, with animals or near feathers Cough up phlegm (day and/or night) for as 0.27 -0.03 0.02 -0.10 0.87 -0.08 much as 3 months each year

% Variance 25 18 16 10 7 6 The bold figures are the highest item loadings under the factors to which they belong.

The third factor is dominated by the LFS question responses indicating work-related allergy/rhinitis, chronic bronchitis and asthma. Prevalences of each of these symptoms were less than 1%, allergy/rhinitis being the least frequent (0.06%). Prevalence of LFS work­

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related asthma was 0.47%. While rhinitis and allergy are commonly associated with asthma, the association of chronic bronchitis with asthma is stronger than might be expected, even though some association is often found. This factor appears to be quite distinct from the work-related asthma described by the first factor, and this is consistent with the poor association between LFS-diagnosed asthma and symptoms-diagnosed asthma found in the original prevalence study (Cowie et al, 1997).

The fourth factor is dominated by chest tightness or shortness of breath when in a dusty part of the house, near animals or feathers. This represents allergic (extrinsic) asthma.

The fifth factor is dominated by persistent productive cough, and represents chronic bronchitis. Cowie et al (1997) noted the poor association between chronic bronchitis as reported by the LFS questions, and as defined by the reported symptoms.

The sixth and last factor is dominated by “having been told by a doctor of having asthma caused by or related to work”. Only 0.6% of subjects reported this, and it does not seem to be associated very strongly with any of the other symptoms (weakly with the questions specifically mentioning asthma).

4.2.2 Clustering of variables

The figure shows the results of the cluster analysis. The highest levels of similarity are shown at the bottom of this tree diagram, which shows which variables or groups of variables cluster together as we travel vertically upwards (or disaggregate as we travel downwards). These results are from using single linkage, but the results from using average linkage were almost identical.

LFS rhinitis or allergy, LFS chronic bronchitis, and LFS asthma were closely associated with each other, and weakly with doctor-diagnosed occupational asthma.

Secondly, wheeze, improvement when away from work, worsening by work-related activity or when in a work-related place, were closely associated, and more distantly with chest tightness, spontaneous breathlessness, breathing problems and nocturnal breathlessness. More distantly still they were associated with the third cluster, (asthma-like symptoms), described below, and with chronic productive cough.

Thirdly, asthma attacks, current asthma, medication for asthma, chest tightness due to dust etc, and shortness of breath due to dust etc, were closely linked. These together were linked more distantly with the second cluster (work-related wheeze, above), and then with chronic productive cough.

4.2.3 A note on missing data

Of the subjects who had responded to either of the first two questionnaire mailings, a total of 2149 subjects were omitted from the principal components analysis due to missing data. Of these, based on the questions they did answer, 221 had no symptoms and 1928 had at least one symptom. Thus the omitted group had a highly disproportionate number of symptoms, compared to the study group as a whole.

Investigation of the omitted subjects showed a mixture of patterns. Among the 221 "no­symptom" subjects, a majority missed out whole sections of the questionnaire, e.g. Section B or Section C (Appendix 1). Within the 1,928 who had at least one symptom, questions tended to be omitted more randomly. These subjects would sometimes answer only one part of a multi-part question, and there was no indication as to why this should be. In other cases,

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answers to some questions were ambiguous or contradictory (e.g. to the questions on persistent cough and/or phlegm).

It seems plausible that a subject who reports no respiratory symptoms will have an easier and shorter path through a questionnaire such as that used here, so the finding of greater losses among those with some symptoms is perhaps not surprising. However, the extent of the difference in rates of missing data in the present study was unexpected. It is possible that the instruction 3 of the questionnaire might have been interpreted by some subjects as implying that questions might be missed out, particularly if they concerned symptoms that the subject did not have. It is certainly plausible that most of the missing answers represent negative responses. However, it is usually considered unsafe to impute missing responses that cannot be verified, and we have not attempted this here.

An important implication of this pattern of missing data is that the prevalences of symptoms within the remaining data set are lower than those reported by Cowie et al (1997), who examined each symptom separately for the whole data set. We recommend that estimates of population prevalence of symptoms should be taken from the 1997 report. We have not attempted to adjust the prevalences of the syndromes defined in the present report.

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Figure 1 Dendrogram showing results of cluster analysis of symptoms (single linkage)

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4.3 DEFINITION OF SYNDROMES

Using the results of the six component factor analysis and the dendrogram for single linkage cluster analysis for the 11941 participants who were included in the analyses, seven clinically relevant syndromes were identified. These were occupational and non-occupational asthma, all-cause asthma, chronic bronchitis or asthma as defined by the LFS questionnaire, allergic asthma, symptoms of chronic bronchitis, and doctor diagnosed asthma caused by or related to work. The first two were based on the most widely used diagnostic symptom, wheezing or whistling in the chest, subdivided by whether there was evidence for an occupational connection; these were therefore mutually exclusive syndromes. However, all the other symptoms were assessed independently, and it is therefore possible for any individual to have any or all of these syndromes simultaneously; that is, the syndromes represent separate individual attributes rather than a classification of subjects. They are described in detail below.

In this section of the report, the number of participants reporting specific symptoms is based on the denominator of 11941 participants who had complete data for all 18 symptoms and were therefore used in all analyses.

4.3.1 Occupational asthma

Asthma is often characterised by symptoms of wheezing in the chest, and a definition of self­reported occupational asthma could plausibly be built around reports of wheezing associated with conditions of work. The occupational aspect could be characterised by association with particular workplace or activity, or relief from symptoms when away from work for at least a week. The latter may be too non-specific, in that subjects may feel better generally when on holiday, and this may induce a perception that symptoms are less troublesome. We have therefore applied two definitions of occupational asthma, one with and one without those who improved away from work.

Definition:

Participants were defined as having occupational asthma if they answered positively to: a) wheeze or whistling in chest at any time in the last 12 months (Q8);

and answered positively to any one of the following: b) Improvement in chest symptoms when away from work for a week or longer

(derived from Q12); c) Symptoms brought on by being in a particular work-related place (derived from

Q14); d) Symptoms brought on by carrying out a particular work-related activity (derived

from Q15).

Table 4.3 below shows the distribution of symptoms that make up the criteria for a definition of occupational (i.e. work-related) asthma.

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Table 4.3 Distribution of symptoms that make up criteria for a definition of occupational asthma.

Each cell contains the number and percentage of participants

Symptoms Number of % participants

Wheeze or whistling in chest at any time in last 12 months 2136 17.9 (Q8)

and Improvement in chest symptoms when away from work for a 533 4.5 week or longer (derived from Q12)

or Symptoms brought on by being in a particular work-related 280 2.3 place (derived from Q14)

or Symptoms brought on by carrying out a particular work-related 60 0.5 activity (derived from Q15)

Syndrome 1: occupational (i.e. work-related) asthma 622 5.2

Alternative definition for occupational asthma:

Participants were defined as having occupational asthma if they answered positively to: a) wheeze or whistling in chest at any time in last 12 months (Q8);

and answered positively to any one of the following: b) Symptoms brought on by being in a particular work-related place (derived from

Q14); c) Symptoms brought on by carrying out a particular work-related activity (derived

from Q15).

The distribution of symptoms that make up the criteria for an alternative definition of occupational asthma are shown in Table 4.4 below. We see that the prevalence of this alternatively defined syndrome was less than half that in table 4.3, which included improvement away from work.

Table 4.4 Distribution of symptoms that make up criteria for an alternative definition of

occupational asthma. Each cell contains the number and percentage of participants

Symptoms Number of % participants

Wheeze or whistling in chest at any time in last 12 months 2136 17.9 (Q8)

or Symptoms brought on by being in a particular work-related 280 2.3 place (derived from Q14)

or Symptoms brought on by carrying out a particular work-related 60 0.5 activity (derived from Q15)

Syndrome 1a: occupational asthma (alternative definition) 275 2.3

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4.3.2 Non-occupational asthma

Participants were defined as having non-occupational asthma if they answered positively to: a) wheeze or whistling in chest at any time in last 12 months (Q8);

and answered positively to all of the following: b) No improvement in wheeze or whistling in chest when away from work for a

week or longer (derived from Q12); c) Wheeze or whistling in chest brought on by being in a particular non-work related

place (derived from Q14); d) Wheeze or whistling in chest brought on by carrying out a particular non-work

related activity (derived from Q15).

Table 4.5 below shows the distribution of symptoms that make up the criteria for a definition of non-occupational asthma.

Table 4.5 Distribution of symptoms that make up criteria for a definition of non-occupational

asthma. Each cell contains the number and percentage of participants

Symptoms Number of % participants

Wheeze or whistling in chest at any time in last 12 months 2136 17.9 (Q8)

and No improvement in wheeze or whistling in chest when away 1690 14.2 from work for a week or longer (derived from Q12)

and Wheeze or whistling in chest brought on by being in a 1883 15.8 particular non-work related place or not brought on by a particular place (derived from Q14)

and Wheeze or whistling in chest brought on by carrying out a 2085 17.5 particular non-work related activity or not brought on by a particular activity (derived from Q15)

Syndrome 2: non-occupational asthma 1514 12.7

4.3.3 All cause asthma

Definition:

Participants were defined as having all cause asthma (i.e. the common features of asthma) if they answered positively to having any one of the following:

a) Ever had an attack of asthma (Q18); b) Had an attack of asthma at any time in the last 12 months (Q19); c) Currently taking medicines for asthma (including inhalers or tablets) (Q20).

The distribution of symptoms that make up the criteria for a definition of all cause asthma are shown in Table 4.6 below.

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Table 4.6 Distribution of symptoms that make up criteria for a definition of all cause asthma.

Each cell contains the number and percentage of participants

Symptoms Number of % participants

Ever had an attack of asthma (Q18) 1021 8.6 or Had an attack of asthma at any time in the last 12 months 529 4.4

(Q19) or Currently taking medicines for asthma (including inhalers or 708 5.9

tablets) (Q20)

Syndrome 3: all cause asthma (common features) 1111 9.3

4.3.4 Symptoms as defined in LFS questionnaire

These symptoms were derived from the coding systems used for the doctor’s diagnosis and the self-reported diagnosis reported by participants for their most serious illnesses. The coding systems were then combined with the definitions used for chronic bronchitis and asthma in the LFS questionnaire. Illnesses were categorised as allergy / rhinitis, chronic bronchitis, and asthma. At this stage of the study interest was focussed on chronic bronchitis and asthma but not on allergy / rhinitis.

Table 4.7 below shows the distribution of symptoms that make up the criteria for a definition of chronic bronchitis or asthma based on the IOM coding used to define the serious illnesses, combined with the LFS definition.

Table 4.7 Distribution of chronic bronchitis and asthma based on IOM coding and LFS definition.

Each cell contains the number and percentage of participants

Symptoms Number of % participants

Syndrome 4: Chronic bronchitis (LFS/IOM) 23 0.2 Syndrome 5: Asthma (LFS/IOM) 56 0.5

The responses to the subsidiary question 7, which distinguishes work-related cause of asthma from work-related aggravation of an existing asthmatic condition, were examined. Of the 23 subjects with LFS-defined chronic bronchitis, nine responded that it had been caused by work, and four of these reported also aggravation. Twelve subjects reported only aggravation, and for two subjects this question was not completed.

Of the 56 subjects with LFS-defined asthma, only 14 indicated work-related cause, and seven of these reported also aggravation. There were 39 subjects claiming work-related aggravation only, and another three with missing responses to question 7.

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4.3.5 Allergic asthma

Definition:

Participants were defined as having allergic (extrinsic) asthma if they answered positively to either of the following:

a) A feeling of tightness in the chest when in a dusty part of the house, with animals or near feathers (Q23a);

b) Feeling short of breath when in a dusty part of the house, with animals or near feathers (Q23b).

The distribution of symptoms that make up the criteria for a definition of allergic asthma are shown in Table 4.8 below.

Table 4.8 Distribution of symptoms that make up criteria for a definition of allergic (extrinsic)

asthma. Each cell contains the number and percentage of participants

Symptoms Number of % participants

Get a feeling of tightness in the chest when in a dusty part of 826 6.9 the house, with animals or near feathers (Q23a)

or Start to feel short of breath when in a dusty part of the house, 925 7.7 with animals or near feathers (Q23b)

Syndrome 6: allergic (extrinsic) asthma 1062 8.9

4.3.6 Symptoms of chronic bronchitis

Definition:

Participants were defined as having symptoms of chronic bronchitis if they answered positively to usually coughing up phlegm, either in the morning, or during the rest of the day or night, on most days for as much as 3 months each year (derived from Q24a, Q24b, Q25a & Q25b).

Table 4.9 Distribution of symptoms that make up criteria for a definition of chronic bronchitis.

Each cell contains the number and percentage of participants

Symptoms Number of % participants

Usually cough up phlegm (flem) from chest first thing in the 1340 11.2 morning and usually cough like this on most days for as much as 3 months each year.

or Usually cough up phlegm (flem) from chest during the rest of 726 6.1 the day or at night and usually cough like this on most days for as much as 3 months each year.

Syndrome 7: symptoms of chronic bronchitis 1449 12.1

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Table 4.9 above shows the distribution of symptoms that make up the criteria for a definition of symptoms of chronic bronchitis.

4.3.7 Doctor’s diagnosis

This is the variable representing whether a doctor has ever told participants that they have had asthma caused by or related to work.

The frequency of participants who had been told by a doctor that they had ever had asthma caused by or related to work is shown in Table 4.10 below.

Table 4.10 Frequency of being told by a doctor that have had asthma caused by or related to

work. Each cell contains the number and percentage of participants

Symptoms Number of % participants

Syndrome 8: Have ever been told by a doctor that have had 72 0.6 asthma caused by or related to work (Q21)

4.3.8 LFS syndrome and other syndromes

Table 4.7 showed that only 75 subjects were classified as having either asthma or chronic bronchitis on the basis of the LFS questions; 23 as LFS asthma, and 56 as LFS chronic bronchitis (3 subjects satisfied both definitions). Many of the other syndromes included considerably larger numbers of subjects. Table 4.11, shown below, gives details of the numbers of these participants who came under each of the other six syndrome definitions.

Table 4.11 Within 75 subjects defined as having chronic bronchitis (23) or asthma (56) based on

LFS definition and IOM coding, numbers (and %) also showing other syndromes.

Syndrome

Chronic Bronchitis (LFS) Syndrome 4

Number % (N=23)

Asthma (LFS) Syndrome 5

Number % (N=56)

Syndrome 1 – occupational asthma 14 61 32 57

Syndrome 1a – alternative occupational asthma 9 39 19 34

Syndrome 2 – non occupational asthma 7 30 21 38

Syndrome 3 – all cause asthma 8 35 53 95

Syndrome 6 – allergic asthma 6 26 36 64

Syndrome 7 – chronic bronchitis 17 74 28 50

Syndrome 8 – doctor-diagnosed occupational asthma 4 17 22 39

It is clear that the other syndromes overlapped with the LFS definitions to varying degrees, and that the prevalences in Table 4.11 are much larger than those in the whole study

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population. However, none of the syndromes included all of the LFS positives, so that the LFS are not a simple subset of any of the other syndromes. Within the 23 subjects classified as LFS Chronic Bronchitis, almost three quarters met the syndrome 7 definition of chronic bronchitis. Within the 56 subjects classified with LFS asthma, the largest overlap (95%) was with syndrome 3, all-cause asthma, followed by allergic asthma (64%) and syndrome 1, occupational asthma (57%). There was some evidence that the LFS questions were picking up preferentially associations with occupation; for example, syndromes 1 and 2 were in the ratio 32:19 in the LFS asthma subjects, compared to 622:1514 in the whole study, so it is perhaps surprising that the LFS asthma subjects overlap more with the all-cause and allergic varieties than with the occupational definition. Table 4.11 does not shed much light on the low prevalence of LFS positives compared to the other syndromes.

4.4 EXPOSURES

4.4.1 Exposures of individual subjects

Subjects who reported respiratory symptoms had been asked to record what, if any, employment they had at the time of first developing the symptoms, and the occupation and industry involved were subsequently coded according to the SIC and SOC. Section 3.6 has described how a systematic assessment was made of the SIC and SOC combinations, and how these combinations were assigned indicators of likely exposure to a list of potentially asthmagenic exposure categories.

A total of 1301 subjects had SIC and SOC codes recorded in the data files. When the corresponding exposure indices were applied, the numbers having any exposure to each hazard were as shown in Table 4.12.

Some exposures were much rarer in this group than others. No subject had any exposure to biological enzymes, and there were only three subjects with textile industry exposures. On the other hand, several hundred subjects had been exposed to irritant substances, exhaust fumes and/or highly reactive chemicals.

Likely exposures were classified also as to likely frequency (days per year) and daily duration (hours per day). Table 4.13 shows the distributions of the allocations to the categories of frequency for each of the hazards.

Table 4.14 shows the distributions of the allocations to the categories of likely duration of exposure within a working on which exposure occurred, for each of the hazards.

Exposures to peak levels of irritants were not assessed for frequency or duration, and so this hazard category does not appear in Table 4.13 or 4.14.

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Table 4.12 Distribution (number) of 1301 subjects, with SIC and SOC codes, assigned to each

exposure category.

Hazard category Exposure present

Yes No Any exposure 708 593 Irritants but not high peaks 503 798 Exhaust fumes 267 1034 Rodents, livestock 18 1283 Fish, shellfish processing 50 1251 Arthropods, mites or insect proteins 35 1266 Latex 113 1188 Flour dust and grain 78 1223 Miscellaneous dusts 42 1259 Bioaerosols 98 1203 Biological enzymes 0 1301 Highly reactive chemicals 226 1075 Biocides 66 1235 Isocyanates 75 1226 Sensitising drugs 61 1240 Industrial cleaning agents 86 1215 Wood dusts 35 1266 Metal sensitisers 98 1203 Metal working fluids. 61 1240 Organic particulate or exhaust fumes. 20 1281 Textile industry exposures 3 1298 Solder / colophony fume 95 1206 Welding fume 71 1230 Peak exposures to irritant gases or fumes 176 1125

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Table 4.13 Distributions (numbers) of 1301 subjects, with SIC and SOC codes, by frequency of

likely exposure.

Hazard category Frequency of exposure (days per year)

None 12 40 120 240 Irritants but not high peaks 798 10 54 14 425 Exhaust fumes 1045 0 41 21 194 Rodents, livestock 1283 1 0 1 16 Fish, shellfish processing 1251 2 8 39 1 Arthropods, mites or insect proteins 1266 3 0 1 31 Latex 1188 3 2 9 99 Flour dust and grain 1225 2 9 1 64 Miscellaneous dusts 1261 0 40 0 0 Bioaerosols 1203 3 1 14 80 Biological enzymes 1301 0 0 0 0 Highly reactive chemicals 1075 2 37 37 150 Biocides 1235 0 7 56 3 Isocyanates 1226 8 13 24 30 Sensitising drugs 1240 0 0 59 2 Industrial cleaning agents 1215 6 0 2 78 Wood dusts 1266 8 1 3 23 Metal sensitisers 1203 9 1 11 77 Metal working fluids. 1240 1 0 60 0 Organic particulate or exhaust fumes. 1281 0 0 1 19 Textile industry exposures 1298 1 0 0 2 Solder / colophony fume 1206 1 18 17 59 Welding fume 1230 32 4 21 14

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Table 4.14 Distributions (numbers) of 1301 subjects, with SIC and SOC codes, by daily duration of

likely exposure.

Hazard category Duration of exposure (hours per day) None 1 4 6 8

Irritants but not high peaks 798 181 165 47 110 Exhaust fumes 1045 114 97 0 45 Rodents, livestock 1283 1 1 1 15 Fish, shellfish processing 1251 24 24 1 1 Arthropods, mites or insect proteins 1266 13 2 1 19 Latex 1188 15 36 62 0 Flour dust and grain 1225 25 41 2 8 Miscellaneous dusts 1261 16 24 0 0 Bioaerosols 1203 45 19 3 31 Biological enzymes 1301 0 0 0 0 Highly reactive chemicals 1075 135 29 19 43 Biocides 1235 65 1 0 0 Isocyanates 1226 27 25 23 0 Sensitising drugs 1240 61 0 0 0 Industrial cleaning agents 1215 71 3 12 0 Wood dusts 1266 9 2 1 23 Metal sensitisers 1203 31 0 4 63 Metal working fluids. 1240 3 57 1 0 Organic particulate or exhaust fumes. 1281 0 3 1 16 Textile industry exposures 1298 0 0 1 2 Solder / colophony fume 1206 49 20 2 24 Welding fume 1230 61 0 2 8

4.4.2 Relationships of syndromes with exposures

Various syndromes were defined in Section 4.3, on the basis of specific combinations of symptom responses. The data on syndrome classifications were linked to the occupational exposure classifications defined in the previous section. Thus it was possible, within the 1301 subjects for whom exposure classifications existed, to look at the relationships between the syndromes and the exposures.

Table 4.15 shows the numbers of subjects, from within this 1301, classified as showing the various syndromes. The syndrome classifications are not mutually exclusive, so a subject could have more than one of the syndromes. The definitions of syndromes 1 and 1a imply that the subjects with syndrome 1a are a subset of those with syndrome 1. The table notes that 170 subjects were not classified as having any of the syndromes.

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Table 4.15 Numbers of subjects, with SIC and SOC codes, classified as having each syndrome

Syndrome Subjects 1 Occupational asthma 400 1a Occupational asthma (alternative definition) 161 2 Non-occupational asthma 655 3 All-cause asthma 354 4 Chronic bronchitis (LFS) 20 5 Asthma (LFS) 42 6 Allergic (extrinsic) asthma 361 7 Chronic bronchitis 463 8 Doctor-diagnosed occupational asthma 51 No syndrome 170

Because the question on occupation related to the onset of symptoms, we can deduce that the 170 subjects with no syndrome had respiratory symptoms, but not in a pattern that would fit any of the syndrome definitions. We note also that information on occupation is not available for subjects who were free of symptoms. This limits what comparisons can be made regarding syndromes and occupational exposures. For the present purposes, we have chosen to treat the 170 subjects with no syndrome as a control comparison group, on the principle that what symptoms they have do not indicate any of the varieties of asthma identified within the syndromes. We have then compared the occupational exposure data of those with each syndrome in turn with this control group.

Our first exposure assessment was a simple dichotomy, classifying the likelihood of each exposure category as Yes or No. We can represent the relationship between a syndrome and an exposure category in a 2×2 table such as Table 4.16, which shows the example of category 2, non-peak exposures to irritants, and syndrome 1, occupational asthma.

Table 4.16 Relationship between syndrome 1, occupational asthma, and exposure category 2,

irritants (non-peak).

Syndrome group Exposure to irritants

No Yes Total No syndrome 122 48 170 Syndrome 1 (occupational asthma) 233 167 400 Total 355 215 570

The degree of association in this table is summarised by the odds-ratio, (122×167) / (233×48) = 1.82. A standard test of the statistical significance of this association calculates the standard error of the natural log of the odds ratio as the square root of the sum of the reciprocals of the table entries (excluding totals) (Breslow and Day, 1980). This gives 0.600 / 0.198 = 3.02. In the case of a single table, this would be considered a z-statistic, expected under the null hypothesis to follow the normal distribution; it would be declared highly significant. Here, however, we have a need to compare several syndromes with a large number of exposure

41

hazards, and so we need to guard against the exaggeration of significance levels through multiple testing.

Leaving significance aside for the moment, similar tables can be formed and similar calculations carried out for all combinations of syndrome and exposure category. Table 4.17 summarises the results of doing this, and shows the value of the z-statistic for each combination. Values above 2 are highlighted in bold characters. (This is to show where the largest values and the strongest evidence of relationships lie, not to suggest that z=2.0 is a suitable critical value for statistical significance.)

Among subjects with no syndromes, there were no textile industry exposures, which led to all the statistics in that row having undefined values (since the result of a division by zero is undefined). It was possible to calculate the statistic for all the other exposure categories. Where values over 2.0 were obtained, they were all positive, and there were no values lower than -2.0. This in itself suggests that some of the larger positive values represent real relationships rather than random variation, and this was consistent with the shape of a probability plot of the values of Table 4.17 against expected normal order statistics, which showed that values above 2.0 were much larger than would be expected by chance.

All syndromes showed evidence of relationships with general exposure to irritant substances, and the largest statistic was for syndrome 7, chronic bronchitis. This syndrome was also related to highly reactive chemicals and to peak irritant exposure. Chronic bronchitis by the LFS definition, syndrome 4, was related to highly reactive chemicals and to exhaust fumes and metal sensitisers. For the last two exposures, the statistic for syndrome 7 was also just below 2, so the patterns for syndromes 4 and 7 were broadly similar, despite the small numbers involved. Syndrome 5, LFS asthma, was associated primarily with irritant exposures and with biological exposures such as livestock, insects, flour and grain (and was the only syndrome for which bioaerosol exposure approached 2). The relatively rare syndrome 7, doctor-diagnosed occupational asthma, was associated with rodent and livestock exposures and gave a statistic of 1.95 with insect exposures. There were no strong associations between any of the exposures except irritants and the non-LFS definitions of occupational and non­occupational asthma.

The occupational categories in Table 4.17 do not include any consideration of frequency or duration of exposure, but information on these was available from the exposure assessment exercise. For each occupation, we multiplied the assigned values of frequency (days per years) and duration (hours per day), to give an estimated total duration in hours per year. Each syndrome group was then compared to the no-syndrome group, using logistic regression on the total duration variable. Table 4.18 shows the values of the derived z-statistics that would, in the case of a single analysis, be used to test the statistical significance of the logistic regression coefficient. Again, this gives a measure of the strength of evidence for a relationship, but again consideration of significance must allow for the multiple testing involved. However, a probability plot showed that the statistics varied more than would be expected by chance, particularly for positive values. Duration was not estimated for peak exposures to irritants, and so this category does not appear in Table 4.18.

In general, the statistics showed similar patterns and trends to those of Table 4.17, with some differences in magnitude in the individual statistics. There was one value lower than -2.0, but a probability plot did not suggest this as particularly anomalous, so interest is only in the larger positive statistics. All of the syndromes again showed associations with general exposure to irritants. All of the syndromes showed some positive association with highly reactive chemicals, and several of these had statistics above 2, notably syndrome 4 (LFS chronic bronchitis), 1 and 1a (occupational asthma), and 7 (chronic bronchitis). The statistics for syndromes 2 and 8 lay just below 2. Very similar patterns were seen for associations with

42

metal sensitisers. Syndrome 4 was associated with wood dust, and syndrome 5 (LFS asthma) with exposures to livestock and insects.

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Table 4.17 Summary of analyses of association between syndromes and occupational exposure categories: table shows test statistic calculated as log(odds-ratio)/(standard error).

Hazard category 1 1a 2

Syndrome number 3 4 5 6 7 8

Irritants (not high peaks) 3.02 3.86 2.87 2.46 3.11 3.44 2.07 4.20 3.43 Exhaust fumes 0.10 0.66 1.31 -0.20 2.28 0.21 -0.29 1.90 0.63 Rodents, livestock 1.39 1.53 0.41 1.14 * 2.54 1.49 0.89 2.36 Fish, shellfish processing -0.15 -0.13 -1.40 -0.86 * 1.01 -0.44 -0.77 -0.96 Arthropods, mites or insect proteins 0.48 0.94 -0.76 0.43 * 2.69 0.39 -0.24 1.95 Latex -0.03 0.75 1.35 1.42 * 0.02 1.77 -0.07 0.19 Flour dust and grain -0.20 0.15 -1.86 -0.73 * 2.00 -0.30 -1.08 0.35 Miscellaneous dusts -0.53 -0.74 -1.29 -0.91 * 0.63 -0.45 -0.87 -0.84 Bioaerosols 0.07 -0.46 -1.02 -0.59 0.17 1.86 0.22 0.01 0.63 Highly reactive chemicals 1.06 1.39 1.11 -0.17 3.21 0.42 0.26 2.55 0.28 Biocides -0.21 0.62 1.05 1.50 * 0.19 1.46 -0.26 0.53 Isocyanates -0.43 -0.11 -0.04 -0.24 0.71 0.30 -0.16 0.46 0.50 Sensitising drugs 0.48 1.18 1.47 1.75 * 0.59 1.71 0.44 0.97 Industrial cleaning agents -0.58 -1.68 0.64 -0.37 * 0.69 0.31 0.47 -0.15 Wood dusts 1.09 1.07 0.42 0.72 1.93 0.26 0.34 1.38 0.09 Metal sensitisers 1.56 1.24 1.26 0.05 2.44 1.19 -0.45 1.98 1.33 Metal working fluids. 1.69 1.68 1.21 -0.07 0.68 0.83 -0.54 1.58 1.22 Organic particulate, exhaust fumes 0.19 0.45 -0.73 -0.06 * 1.74 0.52 -0.03 1.50 Textile industry exposures * * * * * * * * * Peak exposures to irritants 0.97 1.52 1.81 1.82 0.09 0.92 1.75 2.19 1.25 Solder / colophony fume -0.56 -0.64 -1.43 -1.31 * -1.39 -0.76 -0.66 -0.78 Welding fume 0.10 -0.40 -0.14 -0.86 -0.06 -0.14 -0.59 0.36 -0.96

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Table 4.18 Summary of analyses of association between syndromes and occupational exposure

total durations: table shows test statistic calculated as log(odds-ratio)/(standard error).

Hazard category 1 1a 2

Syndrome number 3 4 5 6 7 8

Irritants (not high peaks) 2.52 2.93 1.87 2.34 3.37 3.47 2.13 3.27 3.38 Exhaust fumes 0.32 0.58 1.14 -0.56 0.88 -0.20 -0.40 1.65 -0.18 Rodents, livestock 1.27 1.30 0.31 0.99 -0.27 2.20 1.49 0.90 2.03 Fish, shellfish processing -0.08 -1.63 -1.11 -1.25 -0.31 0.51 0.11 -0.24 -0.76 Arthropods, mites or insect proteins 0.83 0.83 -0.31 0.50 -0.44 2.31 0.96 0.49 1.80 Latex 0.10 0.72 1.47 1.53 -0.35 0.18 1.75 0.00 0.30 Flour dust and grain -0.99 -1.17 -2.12 -1.41 -0.31 0.69 -0.81 -1.72 -0.45 Miscellaneous dusts -0.88 -1.66 -1.09 -1.27 -0.43 0.44 -0.56 -0.98 -0.53 Bioaerosols 0.75 0.69 -0.38 0.05 1.44 0.98 0.56 0.66 0.48 Highly reactive chemicals 2.13 2.70 1.92 1.51 4.24 1.52 1.70 3.00 1.99 Biocides -1.07 -0.49 -0.56 -0.01 -0.36 -0.30 -0.04 -1.14 -0.35 Isocyanates 0.66 0.80 1.16 0.87 1.17 0.46 1.04 1.41 1.53 Sensitising drugs 0.48 1.18 1.55 1.78 -0.46 0.59 1.74 0.54 1.32 Industrial cleaning agents 0.46 -1.79 1.49 0.72 -0.32 1.31 0.95 1.66 0.55 Wood dusts 1.37 1.25 0.81 0.71 2.34 -0.41 1.03 1.65 -0.45 Metal sensitisers 2.27 1.98 1.82 0.86 2.14 1.79 0.62 2.27 2.03 Metal working fluids. 1.93 1.90 1.40 0.26 0.87 1.05 -0.21 1.78 1.45 Organic particulate, exhaust fumes 0.56 0.78 -0.56 0.21 -0.34 1.97 0.76 0.27 1.50 Textile industry exposures * * 0.68 0.54 * * * 0.63 * Solder / colophony fume 0.00 0.59 -0.95 -0.41 -0.35 -0.27 -0.57 -0.56 -0.34 Welding fume 1.31 0.86 0.81 0.98 0.49 -0.07 0.92 0.98 -0.73

4.5 CLINICAL RECORDS

From the original community study, 101 subjects were selected for clinical examination, and as a result were classified into one of seven diagnostic categories, namely asthma and chronic bronchitis, each assessed as occupational, aggravated by work, or non-occupational; plus a final category of other or non-respiratory diagnoses.

The clinical records were matched with the records of respiratory symptoms used to identify syndromes, and it was found that 54 of the clinically examined subjects lay within this group. This number was too small to attempt any formal cluster analyses of symptoms, but it was judged worthwhile to examine the relationships of the clinical judgements with the allocations to syndromes made on the basis of the self-reported symptoms.

4.5.1 Relationships of clinical judgements with syndromes

Table 4.19 shows the distribution of clinical diagnoses within each of the syndrome groups and overall for the 54 subjects for whom syndromes were defined, plus the 47 for whom no syndrome was defined. Most of the subjects with asthma symptoms were confirmed as

45

having asthma of some type. However, there was very little relationship between the clinical diagnoses and the syndromes, and very similar distributions of diagnoses regardless of syndrome.

Table 4.19 Cross-classification of syndromes and clinical diagnoses

Clinical diagnosis Syndrome number

1 1a 2 3 4 5 6 7 8 All None

1 Asthma: occupational 4 1 1 5 1 4 4 3 3 5 4

2 Asthma: aggravated by work 10 5 3 13 2 7 11 6 5 13 8

3 Asthma: not occupational 16 9 3 16 1 7 13 9 4 20 18

4 Chronic bronchitis: occupational 0 0 0 0 0 0 0 0 0 0 2

5 Chronic bronchitis: aggravated by work 3 3 1 2 3 1 3 4 0 4 0

6 Chronic bronchitis: not occupational 1 0 3 1 2 1 0 3 0 4 3

7 Other & non- respiratory 5 3 1 5 0 3 4 3 4 8 12

Total 39 21 12 42 9 23 35 28 16 54 47

4.5.2 Reappraisal of clinical diagnoses

The records from the clinical examinations were reviewed by a chest physician, partly to form an impression of the decision-making process leading to the diagnoses, and partly to see whether there were any diagnostic points that might usefully be incorporated into future questionnaires on occupational asthma.

Initially the clinical notes were scanned generally for any features that might generate hypotheses for possible improvements in the questionnaire. Nothing helpful was noted. Additionally the overall impression was that the borderlines between the diagnostic categories were indistinct, and that in a number of cases assignation to one category or another was difficult. This is consistent with the lack of clear association between the diagnoses and the self-reported syndromes, noted in the previous section.

Subsequently line by line re-inspection of Table 4.19 enabled some focussed questions to be formulated. In line 1, “Asthma: occupational”, there were five clinically diagnosed occupational asthma cases. Of these, four were identified as occupational asthma (syndrome 1), four as LFS-definition asthma (syndrome 4), and four as allergic asthma (syndrome 6), while all five also met the definition of "all-cause" asthma. In line 2, “Asthma: aggravated by work”, there were 13 clinically diagnosed cases, and ten and eleven cases respectively were identified as occupational asthma (syndrome 1) and allergic asthma (syndrome 6), while again all 13 were also identified as all-cause asthma. These are reasonably high positive

46

identification rates, but specificity cannot be calculated because no asymptomatic controls were included in the clinical study.

On the other hand, in line 3 “Asthma: not occupational”, 16 and nine of the 20 clinically diagnosed cases were misclassified by the questionnaires as occupational asthma syndromes 1 and 1a. Inspection of an informal sample of the clinical records of these cases showed that a high proportion had a history of childhood asthma (thus obviously pre-dating any occupational exposures). On the other hand, in an informal sample of clinically confirmed cases of occupational asthma, none gave a history of childhood asthma. It was noted that most questions in the questionnaire referred only to symptoms experienced in the previous 12 months. One question, on when symptoms were first experienced, had not been included in the Principal Components Analysis because the possible importance of this question had not been appreciated at the time. In view of this, the clinical records of all the 54 cases in Table 4.19 were reviewed again, blind to the questionnaire responses, recording evidence of childhood asthma or other relevant symptoms and age of onset of symptoms. Eighteen of the 101 clinical records mentioned symptoms of asthma, wheezing or chest problems beginning as a child (before age 16). In addition, we used the reported questionnaire date of first symptom occurrence and date of birth to calculate the age at which the questionnaire symptoms first developed. Of 1301 subjects analysed, only 9 reported that their symptoms started before age 16. It therefore seems that the subjects reporting symptoms were concentrating on recent symptom patterns, even if they had experienced asthmatic symptoms as a child.

Two additional hypotheses were investigated, that a clinician’s diagnosis would be influenced by evidence of occupational exposure to a known or likely asthmagen, and (prompted by the observation that stress was mentioned in several cases clinically diagnosed as non occupational asthma or other disease), whether “stress” or “anxiety” were mentioned positively in the records.

Table 4.19 shows that the correspondence between the syndrome-based classifications and the clinical diagnoses, for the small number of subjects where the comparison can be made, is not very good. In Table 4.20 we concentrate on syndrome 1, the wheeze-based definition of occupational asthma, and syndrome 5, occupational asthma by the LFS definition. The top half of the table shows the distribution to each of these syndromes and their correspondence with the clinical diagnosis, while the bottom half shows the same information, but where any subject whose clinical record suggests childhood asthma is classified as not having occupational asthma.

The tables in Appendix 5 give more details of similar breakdowns of all of the syndromes by variables assessed during the clinical examinations, namely childhood asthma, stress and occupational exposure to known asthmagens.

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Table 4.20 Effect of reclassification of syndromes, reclassifying those subjects with a history of

asthma in childhood.

Syndromes

Clinical diagnosis Occupational Asthma

(Syndrome 1)

Not syndrome

1

LFS Asthma (Syndrome

5)

Not syndrome

5

All

Prior to reclassification 1 Asthma: occupational 4 1 4 1 5

2 Asthma: aggravated by work 10 3 7 6 13

3 Asthma: not occupational 16 4 7 13 20

4 Chronic bronchitis: occupational 0 0 0 0 0

5 Chronic bronchitis: aggravated by work 3 1 1 3 4

6 Chronic bronchitis: not occupational 1 3 1 3 4

7 Other & non- respiratory 5 3 3 5 8

Total 39 15 23 31 54

After reclassification 1 Asthma: occupational 4 1 4 1 5

2 Asthma: aggravated by work 5 8 3 10 13

3 Asthma: not occupational 8 12 4 16 20

4 Chronic bronchitis: occupational 0 0 0 0 0

5 Chronic bronchitis: aggravated by work 3 1 1 3 4

6 Chronic bronchitis: not occupational 1 3 1 3 4

7 Other & non- respiratory 5 3 3 5 8

Total 26 28 16 38 54

We see that the reclassification removes a number of subjects from the syndrome groups, but has very little effect on the mis-classified subjects in the clinical categories other than asthma.

Table 4.21 shows similar information, but this time the smaller numbers of subjects whose clinical records suggested stress as contributory have been reclassified as not belonging to the syndromes

48

.

Table 4.21. Effect of reclassification of syndromes, reclassifying those subjects with stress.

Syndromes

Clinical diagnosis Occupational Asthma

(Syndrome 1)

Not syndrome

1

LFS Asthma (Syndrome

5)

Not syndrome

5 All

Prior to reclassification 1 Asthma: occupational 4 1 4 1 5

2 Asthma: aggravated by work 10 3 7 6 13

3 Asthma: not occupational 16 4 7 13 20

4 Chronic bronchitis: occupational 0 0 0 0 0

5 Chronic bronchitis: aggravated by work 3 1 1 3 4

6 Chronic bronchitis: not occupational 1 3 1 3 4

7 Other & non- respiratory 5 3 3 5 8

Total 39 15 23 31 54

After reclassification 1 Asthma: occupational 4 1 4 1 5

2 Asthma: aggravated by work 9 4 7 6 13

3 Asthma: not occupational 15 5 7 13 20

4 Chronic bronchitis: occupational 0 0 0 0 0

5 Chronic bronchitis: aggravated by work 3 1 1 3 4

6 Chronic bronchitis: not occupational 1 3 1 3 4

7 Other & non- respiratory 3 5 2 6 8

Total 35 19 22 32 54

Again, despite a small amount of redistribution from the syndromes, there is still considerable evidence of misclassification into the syndromes where the clinical judgements would rule out occupational asthma as a diagnosis.

Finally, Table 4.22 is similar but shows the effect of reclassifying based on information gained during the clinical examination about the subject's job, and the identification through that information of likely exposure to a known asthmagen (e.g. flour dust for bakers).

Here the results of the reclassification are quite dramatic. The majority of the syndrome cases are reclassified, but also those syndrome cases showing misclassification, by the clinical criteria, are also reclassified.

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Table 4.22 Effect of reclassification of syndromes, including in the syndromes only those subjects

where an occupational asthmagen was identified

Syndromes

Clinical diagnosis Occupational Asthma

(Syndrome 1)

Not syndrome

1

LFS Asthma (Syndrome

5)

Not syndrome

5 All

Prior to reclassification 1 Asthma: occupational 4 1 4 1 5

2 Asthma: aggravated by work 10 3 7 6 13

3 Asthma: not occupational 16 4 7 13 20

4 Chronic bronchitis: occupational 0 0 0 0 0

5 Chronic bronchitis: aggravated by work 3 1 1 3 4

6 Chronic bronchitis: not occupational 1 3 1 3 4

7 Other & non- respiratory 5 3 3 5 8

Total 39 15 23 31 54

After reclassification 1 Asthma: occupational 4 1 4 1 5

2 Asthma: aggravated by work 1 12 1 12 13

3 Asthma: not occupational 0 20 0 20 20

4 Chronic bronchitis: occupational 0 0 0 0 0

5 Chronic bronchitis: aggravated by work 0 4 0 4 4

6 Chronic bronchitis: not occupational 0 4 0 4 4

7 Other & non- respiratory 0 8 0 8 8

Total 5 49 5 49 54

The net effect is that there are now only a few cases defined by the syndrome classifications, and none of the subjects with a non-asthma clinical diagnosis is in either of the occupational asthma syndromes. Twelve subjects classified as having asthma aggravated by work were not included in the syndromes, and eleven of these were the same subject for both syndromes. For both syndromes, there is one subject belonging to the syndrome diagnosed with work­aggravated asthma, and only one subject clinically diagnosed but omitted by the syndrome definition; in each case, different individuals. Each of these cases corresponded to one of the asthma syndromes, and was exposed to a known occupational asthmagen (one baked bread, and the other worked in a flourmill). If exposure to a known allergen (in the presence of an asthma syndrome) was applied not only as an essential condition of membership of syndromes, but also as mandatory for inclusion, then the resulting classification is shown in Table 4.23. Now all five clinically diagnosed occupational asthma cases are classified correctly as syndrome 1 or 5. This classification rule also reduced the number of subjects

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with clinical asthma aggravated by work who were classified as occupational asthma. Many of these subjects referred to such causes as general dust or dustiness, stress, or cigarette smoke.

The results of Table 4.22 suggest that a questionnaire to identify occupational caused asthma and occupationally aggravated asthma might usefully incorporate

· questions on wheeze, like those underlying syndrome 1;

· questions similar to the current LFS questions;

· questions on childhood asthma;

· investigation of occupation, and subsequent classification of occupations with known asthmagen exposure.

Questions to identify asthma with onset in childhood might also be incorporated, to help interpret occupationally aggravated cases.

Table 4.23 Effect of reclassification of syndromes, including in the definition those asthmatic

subjects where an occupational asthmagen was identified

Syndromes

Clinical diagnosis Occupational

Asthma (Syndrome 1

or 5)

Not syndrome

1 or 5

After reclassification 1 Asthma: occupational 5 0

2 Asthma: aggravated by work 2 11

3 Asthma: not occupational 0 20

4 Chronic bronchitis: occupational 0 0

5 Chronic bronchitis: aggravated by work 0 4

6 Chronic bronchitis: not occupational 0 4

7 Other & non- respiratory 0 8

Total 7 47

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5. DISCUSSION

5.1 QUALITY OF AVAILABLE DATA

This project was designed around the reanalysis of an extensive body of questionnaire from a community study of asthma in West Lothian. The target population numbered 40,000, and the response rate, after three rounds of mailing, was almost 50%, which is respectable for a postal survey (although lower than achieved in a pilot study). Cowie et al (1997) thought it unlikely that the non-response would be an important source of bias in estimating prevalence of asthma and chronic bronchitis.

The data from that study form an important data set, with a large sample of the community having answered a range of questions on respiratory symptoms and on their relevant occupational status. The first two mailings used the full questionnaire and we have limited our analyses to that subset, omitting some subjects with missing or incorrect data. The final data set numbered almost 12,000 subjects, and was the basis for all the principal analyses, to ensure consistency across the various assessments. Few other studies have had the benefit of such an extensive data set.

The data set included males and females, and was restricted to the working-age (16-64 years) population of a defined geographical area of Central Scotland. Thus the data set included no children.

We have commented (Section 4.2.3) on the non-random patterns of missing data within the data set, and the effect this would have if estimates of prevalence were made from the reduced data set used in the principal components analysis. We believe that the conclusions drawn about relationships between responses are relatively robust to the missing data patterns. However, these patterns may be telling us something about respondents' difficulties in following the routing within the questionnaire, and the design of any future questionnaire might profitably consider this point carefully and critically

5.2 EXPOSURE ASSESSMENT

An important addition to the data set was an exposure assessment. Subjects had recorded the job (if any) they held when the respiratory symptoms were first experienced, and the entire list of jobs was assessed for likely exposure to a range of potential respiratory hazards; where exposure was likely, then likely frequency and duration of exposure were also assessed. A wide range of hazards were implicated. Thus, for the first time in these data, it was possible (for a proportion of subjects) to relate the onset of symptoms to the occupational and exposure status at the time of onset.

5.3 SYMPTOM COMBINATIONS

The literature review had the explicit objective of reviewing the work of other research groups in developing and validating questionnaires to identify asthma and other respiratory diseases. The results of these studies showed how difficult a task this is, primarily because there is no "gold standard" test for asthma which can be used as an objective benchmark for validation. Bronchial hyperreactivity has been favoured as objective and repeatable, but it is not sufficiently specific for asthma since it can be demonstrated in a proportion of subjects without any asthmatic symptoms. Single symptoms lack sensitivity, but those studies that have looked at combinations of symptoms suggest that combining two or three symptoms can improve sensitivity (at some cost to specificity).

52

Few studies had looked systematically at combinations of symptoms, although a few authors (Bai et al, 1998; Abramson et al, 1991) had used multivariate techniques to identify clustering of symptoms. The favoured technique had been the application of principal components analysis to encapsulate a large proportion of the variation in the data in a small number of factor dimensions, followed by factor rotation seeking to associate these with small numbers of important variates. This combination of techniques, often known as factor analysis, is common in the analysis of data from the social sciences, but has been criticised on theoretical grounds, particularly because the technique relies on no specific model and the final rotated factors can be arbitrary. However, the results in other studies have been plausible, and plausible results were produced in the present study also.

There does not appear to have been any prior attempt to apply variable-clustering techniques to similar data sets. Our attempts produced symptom groupings broadly similar to those from the factor analysis approach. Since the techniques are independent and use quite different methods, this gives added plausibility to the results. Output from cluster analyses can be sensitive to the method used for combining clusters, but we have demonstrated that our results were not sensitive to the method chosen.

5.4 DEFINING SYNDROMES

The definitions of syndromes from the symptoms was based on clinical judgement combined with the results of the multivariate analyses, and the plausibility of those syndromes provided additional reassurance that the process was reasonable. The syndromes included different types and definitions of occupational and non-occupational asthma, plus chronic bronchitis (defined by self-reported chronic bronchial hypersecretion).

It was notable that the proportion of subjects reporting some of the syndromes was much higher than prevalences using some existing definitions: In the whole study group, only 75 subjects had chronic bronchitis or asthma based on the LFS definition, and only 72 had ever been diagnosed by a doctor as having work-related asthma, but as many as 622 reported wheeze with an occupational association (syndrome 1). This suggests that there are large numbers of the general population who have respiratory symptoms associated with work that are not being diagnosed as occupational asthma by GPs, and that would not be detected by the LFS instrument. Even a more restricted definition of work-related asthma (syndrome 1a) identified 275 such cases.

5.5 ASSOCIATIONS BETWEEN SYNDROMES AND OCCUPATIONAL EXPOSURES

Associations between the syndromes and exposures were examined using odds ratios. Although formal significance tests were complicated by the simultaneous examination of multiple associations, there were a number of relatively large test statistics for positive associations and hardly any for negative associations, and this pattern was highly unlikely to have arisen by chance. All the syndromes showed associations with exposure to irritants; it is not surprising that such exposures should lead to increased reporting of respiratory symptoms. There were few other associations with binary exposure variables, but syndrome 4, LFS asthma or bronchitis, was associated with exposures to rodents, livestock, mites and insects; syndrome 6, chronic bronchitis, showed associations with highly reactive chemicals and peak exposure to irritants; and syndrome 7, doctor-diagnosed occupational asthma, was associated with rodent and livestock exposures. With exposures characterised by duration (equivalent whole days per year), many of the associations strengthened slightly. Syndrome 2, non­occupational asthma, had the weakest association with irritant exposures but had some association with flour and grain exposure, while syndromes 1, 1a, 4 and 6 were all associated

53

with highly reactive chemicals. Syndromes 1a, 4, 6 and 7 were all associated with metal sensitisers.

It is perhaps surprising that the syndromes 1 and 1a, which are based on reporting of wheeze in an occupational context, did not show more associations with specific exposures. However, the syndromes are based on combinations of symptoms which may not have been synchronous, and the context of the occupation leading to the exposure classification may have been different for the different components of each syndrome.

5.6 COMPARISONS WITH CLINICAL EXAMINATIONS

There were 54 subjects from our data set who had had clinical examinations. Comparison of the syndrome allocations with the clinical judgements made on these showed that the majority of those with asthmatic symptoms were clinically confirmed to have asthma of some kind; but that the distinctions between asthma and chronic bronchitis, and between occupational and non-occupational conditions, were very unclear. Again, this highlights the difficulty of definition surrounding asthma as a clinical entity.

Detailed re-examinations of the clinical records suggested that identifying childhood asthma may be important in considering the work-relatedness of recent symptoms. In addition, identification of occupations likely to involve exposure to known asthmagens proved very useful in reducing false positive attributions to the principal syndromes of interest, and in distinguishing work as a cause from work as an aggravating environment for asthma.

5.7 DESIGN OF QUESTIONNAIRES

The results of the LFS questions were surprisingly different from the other asthma questions. We wonder whether the requirement to say at the beginning of the questionnaire whether the illnesses and symptoms related to work tends to exclude a more contemplative approach, and therefore arrives at a different conclusion. Furthermore, the LFS questions focus on the "most severe illness caused by work", while the symptoms questions ask about symptoms relevant to asthma independent of other illness. Further investigation of the differences between the approaches would require questionnaire development and testing work. We have also highlighted that the patterns of missing data may suggest a need for care in designing the routing through the questionnaire and the instructions to respondents.

Some of the results of the comparisons with the clinical examinations have suggested that a redesigned questionnaire should include not only the questions defining our syndrome 1, but should also collect enough information about occupation to allow an assessment of whether exposure to known asthmagens was likely, and perhaps whether the respondent had asthma as a child.

5.8 POSSIBILITIES FOR FUTURE WORK

The work in the present study has taken our understanding of this extensive data set further than was possible in the previous report (Cowie et al, 1997). However, there is one aspect of the data that has not been explored extensively. Each questionnaire in the first two mailings included a complete occupational history (excluded from the third mailing in an attempt to improve response rate). For reasons of cost this was not processed in the original study, and subsequent work processed the work histories only for a small number of subjects as part of the case-control study (Buchanan et al, 1997).

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It would be possible to process all the job histories, which would involve having each job coded in a standard fashion (using e.g. SIC and SOC codes), and then having these punched to a computer file. The exposure assessment methods used in the present study could be used to build exposure profiles for each subject, and these could then be examined for relationships between exposures and respiratory symptoms, and for influences of symptoms on subsequent employment patterns. This would greatly strengthen the findings from the present study.

In addition, we have gained insights that could be useful in designing a revised questionnaire for occupational asthma, particularly from the comparisons with the clinical examinations. However, these comparisons were based on small numbers, and any new questionnaire should be validated on larger numbers of subjects during its development, before it could be considered for general use.

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6. ACKNOWLEDGEMENTS

The study was funded by the HSE, under contract no. 4359/R56.098. We are grateful to Dr John Cherrie for guidance on the exposure assessment strategy.

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APPENDIX 1 Reproduction of questionnaire used in postal survey

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61

62

63

64

65

66

67

68

69

APPENDIX 2 Examples of occupations associated with various categories of exposure

Category Description Occupations Low 2 Exposure to irritants but not high

peak See Appendix 3 for list of respiratory irritants

3 Exposure to exhaust fumes Any job involving use of vehicles which use fuel combustion

High 4 Rodents, livestock Animal laboratory technicians, scientists and

assistants Dairy and beef farmers Abattoir employees Animal breeder Pet shop employee Pharmaceutical industry Veterinary surgeon Groom Jockey Shepherd Stable hand Poulterer

5 Fish, shellfish processing Animal foodstuffs industry Cook Fishmonger Food industry Oyster sheller Shellfish workers

6 Arthropods, mites or insect proteins Poulterer Abattoir employees Farmer Gardener Wine grower Arboriculturist Food industry Insect breeding Laboratory staff Docker Pest control Fruit growing Biologist Cosmetics industry Dyeing industry Pharmaceutical industry Miller and baker

7 Latex Hospital staff Man. of surgical gloves

70

Medical staff Nurses and auxiliaries Surgeons Dentists Veterinary surgeons Funeral directors Laboratory technicians

8 Flour dust and grain Bakers Flour milling, transport and storage Farmers or farm workers e.g. sowing, cultivation, harvesting, drying, handling

9 Other, miscellaneous e.g. soya bean dust, tea dust and green coffee bean dust

Food industry Coffee industry Docker Seed packer Farmer

10 Bioaerosols (moulds, endotoxins, etc)

Food production Animal breeder Animal food stuffs industry Farmer Docker Miller Seed packer Coffee packer Refuse collectors Treatment plant operators Brewing

11 Biological enzymes (proteolytic enzymes)

Use in baking, brewing, fish, silk and leather industries Cosmetics industry Dairy workers Detergents manufacturer Dry cleaner Food industry Laboratory staff Laundry cleaner Pharmaceutical industry Textile industry

12 Highly reactive chemicals (cross­linking agents)- anhydrides, amines, reactive dyes, glues, others excluding biocides.

Metal and electrical processors, makers and repairers Construction and mining Other non-metal or electrical processors, makers or repairers, chemical processors Manufacture of adhesives, plastics, rubber, moulding resins, surface coatings Manufacture of textiles and clothing Cosmetics industry Electronics Furrier Petrochemical industry

71

Pharmaceutical industry Dyeing industry Food packer industry Electrical composant industry

13 Biocides, for example glutaraldehyde

Nurses Darkroom technicians Medical / pharmacological research Leather tanning

14 Isocyanates Spray painters Other metal or electrical processors, makers or repairers Manufacture of foam and coatings Manufacture of synthetic inks, paints and adhesives Automotive industry Carpenter Chemical industry Foundry worker Joiner Mechanic Painter Plastics industry

15 Sensitising drugs e.g. antibiotics, cimetidine, ispaghula powder, ipecacuanha tablets

Manufacture of these substances Dairy industry Chemist Doctor Laboratory staff Medical personnel Nurse Pharmaceutical industry Surgeon Veterinary surgeon

16 Industrial cleaning agents

17 Wood dusts for example, hard wood (cedar, oak and mahogany) and soft

Joiners Forestry workers Builder Carpenter Model builder Paper maker Polisher Sander Saw mill employee Wood cutter

18 Metal sensitisers e.g chromium (VI) compounds, cobalt (metal and compounds)

Used in plating and anodising solutions Production of pigments and dyestuffs, wood preservatives, tanning agents Electroplating Hard metal manufacture and use Production of metal from ore

72

Alloys used in the surgical replacement of joints Paint manufacture Glass industry Metallurgist

19 Jobs with high probability of exposure to components associated with metal working fluids

20 Jobs in agriculture with high probability of exposure to organic particulate or exhaust fumes

21 Textile industry production jobs

22 Jobs with moderate to high probability of accidental or periodic exposure to very high levels of irritant gases or fumes (peak exposures)

23 Solder / colophony fume Solderers or electronic assemblers Other metal or electrical processors, makers and repairers. Adhesives industry

24 Welding fume Stainless steel welding

73

APPENDIX 3 Examples of occupations associated with exposure to irritants

Manufacture of soft drinks and food

Vehicle manufacture and use

Manufacture and processing of plastics

Preparation of pharmaceutical products

Horticultural / farmers

Manufacture of agricultural chemicals, polishes, paints, cosmetics

Textile and leather production

Construction work

Petrochemical manufacture

Manufacture of waxes, natural resins, resins, paints and lacquers, printing inks

Manufacture of coatings, textiles, paper, adhesives, leather, polishes and sealants.

Synthesis of chemical intermediates

Manicuring

Dentistry

Surgery

Mortuaries

Manufacture of medical and dental applications.

Cleaners

Construction

Painters

Laboratory personnel

Pest control workers

74

75

APPENDIX 4 Symptoms Used in Analysis

· Have you consulted a doctor about an allergy / rhinitis that has been caused by or made worse by work? (derived from LFS and IOM codes for Q5 and Q6);

· Have you consulted a doctor about chronic bronchitis that has been caused by or made worse by work? (derived from LFS and IOM codes for Q5 and Q6);

· Have you consulted a doctor about asthma that has been caused by or made worse by work? (derived from LFS and IOM codes for Q5 and Q6);

· At any time in the last 12 months have you had wheezing or whistling in your chest? (Q8);

· At any time in the last 12 months have you had chest tightness? (Q9);

· At any time in the last 12 months have you had an attack of shortness of breath that came on during the day when you were not doing anything strenuous? (spontaneous breathlessness – Q10);

· At any time in the last 12 months have you been woken at night by an attack of shortness of breath? (nocturnal breathlessness – Q11);

· Do your chest symptoms improve when away from work for a week or more (improvement when away from work - derived from Q8-11 and Q12);

· Have these symptoms been brought on by being in a particular work-related place (Q14);

· Have these symptoms been brought on by carrying out a particular work-related activity (Q15);

· Have you ever had an attack of asthma? (Q18);

· Have you had an attack of asthma at any time in the last 12 months? (Q19)

· Are you currently taking medication for asthma? (Q20);

· Have you ever been told by a doctor that you have had asthma caused by or related to work? (Q21)

· Which of the following statements best describes your breathing? (breathing trouble – Q22)

I never or only rarely get trouble with my breathing;

I get regular trouble with my breathing, but it always gets completely better;

My breathing is never quite right.

76

· When you are in a dusty part of the house or with animals (for instance dogs, cats or horses) or near feathers (including pillows, quilts and eiderdowns) do you ever:

Get a feeling of tightness in your chest? (dust tightness – Q23);

Start to feel short of breath? (dust shortness of breath – Q23).

· Do you usually cough up phlegm (flem) from your chest on most days for as much as 3 months each year? (cough and duration of cough – derived from Q24a & b and Q25a & b);

77

APPENDIX 5 Extra tables

showing the breakdown of syndrome membership by variables assessed from clinical records: childhood asthma, stress and occupational exposure to known asthmagen

78

Table A5.1 Breakdown of syndrome membership by childhood asthma assessed from clinical

records

Childhood Asthma? Clinical diagnosis

1 1a 2 3 Syndrome

4 number

5 6 7 8 All

No

Yes

1

2

3

4

5

6

7

1

2

3

4

5

6

7

Asthma: occupational Asthma: aggravated by work Asthma: not occupational Chronic bronchitis: occupational Chronic bronchitis: aggravated by work Chronic bronchitis: not occupational Other & non­respiratory Asthma: occupational Asthma: aggravated by work Asthma: not occupational Chronic bronchitis: occupational Chronic bronchitis: aggravated by work Chronic bronchitis: not occupational Other & non­respiratory

4

5

8

0

3

1

5

0

5

8

0

0

0

0

1

2

5

0

3

0

3

0

3

4

0

0

0

0

1

2

1

0

1

3

1

0

1

2

0

0

0

0

5

7

7

0

2

1

5

0

6

9

0

0

0

0

1

2

1

0

3

2

0

0

0

0

0

0

0

0

4

3

4

0

1

1

3

0

4

3

0

0

0

0

4

5

6

0

3

0

4

0

6

7

0

0

0

0

3

5

6

0

4

3

3

0

1

3

0

0

0

0

3

4

3

0

0

0

4

0

1

1

0

0

0

0

5

7

10

0

4

4

8

0

6

10

0

0

0

0

Total 39 21 12 42 9 23 35 28 16 54

79

Table 5.2 Breakdown of syndrome membership by stress assessed from clinical records

Stress? Clinical diagnosis 1 1a 2 3

Syndrome4

number 5 6 7 8 All

No

Yes

1

2

3

4

5

6

7

1

2

3

4

5

6

7

Asthma: occupational Asthma: aggravated by work Asthma: not occupational Chronic bronchitis: occupational Chronic bronchitis: aggravated by work Chronic bronchitis: not occupational Other & non­respiratory Asthma: occupational Asthma: aggravated by work Asthma: not occupational Chronic bronchitis: occupational Chronic bronchitis: aggravated by work Chronic bronchitis: not occupational Other & non­respiratory

4

9

15

0

3

1

3

0

1

1

0

0

0

2

1

4

8

0

3

0

3

0

1

1

0

0

0

0

1

3

3

0

1

3

1

0

0

0

0

0

0

0

5

12

15

0

2

1

3

0

1

1

0

0

0

2

1

2

1

0

3

2

0

0

0

0

0

0

0

0

4

7

7

0

1

1

2

0

0

0

0

0

0

1

4

10

12

0

3

0

4

0

1

1

0

0

0

0

3

5

8

0

4

3

2

0

1

1

0

0

0

1

3

5

4

0

0

0

2

0

0

0

0

0

0

2

5

12

19

0

4

4

5

0

1

1

0

0

0

3

Total 39 21 12 42 9 23 35 28 16 54

80

Table A5.3 Breakdown of syndrome membership by occupational exposure to known asthmagen

assessed from clinical records

Asthmagen identified? Clinical diagnosis

1 1a 2 3 Syndrome

4 number

5 6 7 8 All

No

Yes

1

2

3

4

5

6

7

1

2

3

4

5

6

7

Asthma: occupational Asthma: aggravated by work Asthma: not occupational Chronic bronchitis: occupational Chronic bronchitis: aggravated by work Chronic bronchitis: not occupational Other & non­respiratory Asthma: occupational Asthma: aggravated by work Asthma: not occupational Chronic bronchitis: occupational Chronic bronchitis: aggravated by work Chronic bronchitis: not occupational Other & non­respiratory

0

9

16

0

3

1

5

4

1

0

0

0

0

0

0

5

9

0

3

0

3

1

0

0

0

0

0

0

0

2

3

0

1

3

1

1

1

0

0

0

0

0

0

11

16

0

2

1

5

5

2

0

0

0

0

0

0

2

1

0

3

2

0

1

0

0

0

0

0

0

0

6

7

0

1

1

3

4

1

0

0

0

0

0

0

10

13

0

3

0

4

4

1

0

0

0

0

0

0

5

9

0

4

3

3

3

1

0

0

0

0

0

0

3

4

0

0

0

4

3

2

0

0

0

0

0

0

11

20

0

4

4

8

5

2

0

0

0

0

0

Total 39 21 12 42 9 23 35 28 16 54

81

Printed and published by the Health and Safety ExecutiveC30 1/98

Printed and published by the Health and Safety Executive C1.10 09/03

ISBN 0-7176-2759-4

RR 164

9 78071 7 6275 92£15.00