Response rate 6.5.1
Of the original population (n=543), 432 gave their consent to receive another survey from the research team. The questionnaire was returned by 181 subjects only (response rate 41.9%).
In the first step of analysis, a comparison between responders and non-responders in demographic, health-related factors, and work duration was made to investigate any differences that may have caused bias.
Comparison of the characteristics of the responders and non-6.5.2
responders to work-practice questionnaire
As the table 6-20 and table 6-21 show, there was a significant difference between the responders and non-responders in median age, with responders being older, P = 0.02. In addition, responders reported more work-related symptoms than non-responders but this was of borderline significance. Non-responders, on the other hand, were more often smokers and atopic but this was not statistically significant.
167
Table 6-20 Comparison of the characteristics of responders and non-responders to work-practice questionnaire (categorical variables)
Characteristics٭ Responders 1
1 Total of 181 subjects who responded to the questionnaire, 2 Total of 251 subjects who did not responded to the questionnaire, ٭ The proportions of subjects with presented characteristics was calculated from valid number of subjects in each group which was slightly differed for each characteristic.
Table 6-21 Comparison of the characteristics of responders and non-responders to work-practice questionnaire (continuous variables)
Characteristics Responders 1 Non responders 2 p-value*
Age٭٭
Median (interquartile range)
52 (45.0, 58.0) 50 (42.0, 56.0) 0.02
Duration of work in cleaning ( years ) Median (interquartile range)
10 (4.0, 20.0) 10 (3.0, 17.8) 0.29
1 Total of 181 subjects who responded to the questionnaire, 2 Total of 251 subjects who did not respond to the questionnaire,* Mann-Whitney test, ٭٭ 35 subjects missed data on age (11 responders, 24 non-responders).
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Comparison of the characteristics of cases and controls 6.5.3
The characteristics of cases (n=50), defined as subjects with physician-
diagnosed asthma who used asthma medications or had symptoms in the last 12 months or those who reported at least three respiratory symptoms without having previous diagnosis of asthma, were compared to those of controls (n=
131) who were everyone else. This aim of this comparison is to recognize any significance differences that may bias the results.
Table 6-22 and table 6-23 shows that cases and controls were similar in age and gender. Half of the controls were non-smokers and this proportion was significantly higher than cases. Cases reported having COPD more often than controls, P < 0.001.
There were 16 subjects in the case group with other cardio-respiratory
conditions that might have caused symptoms similar to those of asthma. Ten of these reported physician-diagnosed asthma at the same time. Four cases, two with heart disease and two with COPD, attended for methacholine tests, and three had results suggestive of asthma. So 13 of 16 subjects with other cardio-respiratory disease were having asthma at the same time based on either self-reporting of physician-diagnosed asthma (n= 10) or on
methacholine tests (n=3). The simultaneous occurrence of asthma with COPD or heart disease is not uncommon, thus, it was decided to keep the three remaining subjects in the case group.
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Table 6-22 Comparison of the characteristics of cases and controls (categorical variables)
1 Total cases of 50, 2 Total controls of 131, # Questions about physician-diagnosed chronic bronchitis, COPD and heart disease in the work-practice questionnaire, *1 subject (control) with missing data on gender, **3 subjects (1case , 2 controls) with missing data on hay fever, ***4 subjects missing data on smoking status (2 cases, 2 controls).
Characteristics Cases 1 n (%)
Controls 2 n (%)
Difference in proportions
%
95% CI
Gender *
Female 45 (90.0) 117 (90.0) 0 - 9.8 to 9.8
Atopy**
Hay fever 17 (34.7) 30 (23.3) 11.4 - 3.8 to 26.6
Smoking status***
Current smokers 14 (29.2) 34 (26.4) 2.8 - 12.1 to 17.7
Former smoker 19 (39.6) 28 (21.7) 17.9 2.3 to 33.4
Never smoker 15 (31.2) 67 (51.9) - 20.7 - 36.4 to - 5.0
Other physician-diagnosed cardiorespiratory disease #
COPD 12 (24.0) 3 (2.3) 21.7 9.5 to 33.8
Heart disease 4 (8.0) 2 (1.5) 6.5 - 1.3 to 14.3
Previous exposure to fumes, vapours or dusts
Yes 16 (32.0) 27 (20.6) 11.4 - 3.3 to 26.1
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Table 6-23 Comparison of the characteristics of cases and controls (continuous variables)
Characteristics Cases 1 Controls 2 P-value*
Age٭٭
Median (interquartile range) 53 (48.0, 59.0) 52 (44.0, 57.0) 0.18 Duration of work in cleaning (years )
Median (interquartile range) 10.6 (4.8, 20.1) 9.9 (4.0, 20.0) 0.33
1 Total cases of 50, 2 Total controls of 131, * Mann-Whitney test. ٭٭11 subjects miss data on age (I case, 10 controls) .
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Association between asthma and performing cleaning tasks 6.5.4
The association between asthma and performing dusting, vacuum cleaning, cleaning windows and toilets is presented in table 6-24. Almost equal
proportions of cases and controls performed the tasks with the same frequency.
Table 6-24 Association between asthma and cleaning tasks
Risk factors** Cases 1
1 Total of 50 cases, 2 Total of 131 controls, *From multiple logistic regression adjusted for smoking, age and gender,# daily versus other categories (more than once a week, monthly and rarely), ** The proportions of subjects with presented risk factors was calculated from valid number of subjects in each group which was slightly differed for each risk factor.
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Association between asthma and the use of bleach, ammonia and 6.5.5
sprays
There was a significant association between asthma and the frequent use of bleach, OR 2.9 (95% CI 1.4 to 6.1). Using sprays frequently was also
associated with asthma with OR 1.9 but that was of borderline significance (OR 1.9, 95% CI 0.9 to 4.1), table 6-25.
Table 6-25 Association between asthma and the use of bleach and sprays
Risk factors** Cases 1
1 Total of 50 cases, 2 Total of 131 controls, *From multiple logistic regression adjusted for smoking, age and gender, # Regression analysis was not done due to the small number of subjects, ** The proportions of subjects with presented characteristics was calculated from valid number of subjects in each group which was slightly differed for each characteristic, *** High frequency defined as using the product every day or more than once a week
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As can be seen from the table below, there was no statistically significant difference in the average duration of the use of bleach or sprays between cases and controls.
Table 6-26 Association between duration of using bleach and spray (in years) and asthma
Products#
Cases 1 Median ( interquartile
range)
Controls 2 Median ( interquartile
range)
Crude OR*
95% CI
Adjusted OR**
95% CI
Bleach• 7 (3.8-13.5) 6.0 (2.0-18.0)
1.0 0.94 to 1.06
1.0 0.95 to 1.09 Spray••
10 (5.5-20.0) 6.0 (3.0-12.0)
1.06 1.0 to 1.12
1.06 0.99 to 1.13
# Analysis for ammonia was not done because of small number of subjects, 1 Total of 50 cases, 2 Total of 131 controls, * OR for one unit extra duration, ** From multiple logistic regression adjusted for smoking, age and gender,
•128 subjects missed data on duration of using bleach (28 cases, 100 controls), •• 91 subjects (66 cases, 25 controls) missed data on duration of using spray.
174
Association between asthma and work practices 6.5.6
From the data in table 6-27, it is apparent that diluting products was a common practice among cleaners but mixing chemicals was not. Cleaners involved in mixing chemicals very frequently had almost a three-fold risk of asthma compared with those who mixed less often. This reached statistical
significance, OR 2.7, 95% CI 1.2 to 6.1. There was no significant difference between cases and controls with regard to wearing gloves.
Table 6-27 Association between asthma and work practices
1 Total of 50 cases, 2 Total of 131 controls, • Defined as doing the task every day or more than once a week versus low exposure which included monthly, rarely or no use, ٭٭ From multiple logistic regression adjusted for smoking, age and gender, * The proportions of subjects with presented risk factors was calculated from valid number of subjects in each group which was slightly differed for each risk factor.
Risk factor* Cases 1
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As table 6-28 shows, the average duration of mixing products was longer among controls (5 years) compared to cases (2.5 years), however the difference was not statistically significant.
Table 6-28 Association between duration (in years) of dilution and mixing cleaning products and asthma
Work practice
Cases 1 Median (interquartile
range )
Controls 2 Median (interquartile
range )
Crude OR*
95% CI
Adjusted OR**
95% CI
Dilution• 5.0 (2.0-11.0) 6.3 (3.0-12.5) 0.99 0.94 to 1.04
1.0 0.95 to 1.06 Mixing•• 2.5 (2.0-8.0) 5.0 (2.0-9.5) 0.95
0.8 to 1.06
0.94 0.8 to 1.07
1 Total of 50 cases, 2 Total of 131 controls, * OR for one unit extra duration, ** From multiple logistic regression analysis adjusted for smoking, age and gender, • 52 subjects (11 cases, 41 controls) missed the data on duration of dilution, •• 146 subjects (35 cases, 111 controls) missed data on duration of mixing.
176
Level of knowledge about cleaning products in cases and controls 6.5.7
The response of 171 subjects to the question about knowledge of cleaning agents showed that 95% of cleaners including both cases and controls, (n=
163) felt they had sufficient knowledge. The level of knowledge of cleaners was not measured or tested by any means meaning that we relied on self-reported answers only.
The bar chart below shows that cleaners with possible asthma were more knowledgeable about cleaning products used, however, the differences did not reach statistical significance, P < 0.05 (chi square test, degree of freedom=3).
Figure 6-5 Level of knowledge about cleaning in cases and controls products
60%
35%
4% 0
46% 50%
5%
0 0%
10%
20%
30%
40%
50%
60%
70%
I know a lot I know as much as I need to
know
I know a bit I know nothing
Cases n= 48 Control n= 123
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Level of training received by cases and controls 6.5.8
One hundred sixty one (n=161) subjects answered the question about their training in dealing with chemical products. Of these, 124 (77%) reported that they had received training periodically. Figure 6-6 show that this was equally reported by cases and controls.
Figure 6-6 Level of training received by cases and controls
178
Key findings of phase-IV: Identifying risk factors for asthma in cleaners (nested case control study)
Cleaning tasks including dusting, vacuum cleaning, cleaning windows and toilets were not significantly associated with asthma in cleaners.
Frequent use of bleach was significantly associated with asthma (OR 2.9, 95% CI 1.4 to 6.1).
Asthma was significantly associated with mixing chemical products (OR 2.7, 95% CI 1.2 to 6.0).
179 Questions not used for analysis 6.5.9
A number of questions were not analysed for several reasons. Table 6-29 present these questions in themes with the justification for excluding them from further analysis.
Table 6-29 Questions not analysed and the reason for excluding them
Questions theme (code of
the questions)
Aim (s) Justification of excluding
Chemicals or products used in these tasks.
1. The researcher noticed that some cleaners reported using cleaning products that would not be used in the work place such as flash glass cleaner and vinegar. This most likely does not represent exposures to all cleaners.
2. General terms were used to describe the products used, such as detergents and descaler, and this did not help in identifying a particular material safety data sheet.
Previous jobs previously exposed to an agent that is well-known to induce asthma e.g.
isocyanates
Most of the cleaners wrote where they worked without describing the nature of the job, e.g. reporting work in a factory without writing in details the nature of their job such as working as a clerical or a manual worker.
This made it difficult to anticipate whether the cleaner has been exposed previously to asthma inducer (s).
Using bleach at home
(15 &15.1)
To investigate whether using bleach at home was a confounder agent.
More information was required to assess the difference between cases and controls such as the duration of exposure.
Number of
This might be misleading because cleaners might work less now due to the respiratory conditions. In addition, many cleaners were found to be a cleaner in more than one location, this would not be revealed by this question.
180