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( Springer-Verlag 1997
Int Arch Occup Environ Health (1997) 69:350—353
OR IGIN A L A R TI C LE
Christian Wolf · Christian Pirich · Eva Valic Thomas Waldhoer
Pulmonary function and symptoms of welders
Received: 20 April 1996/Accepted: 13 May 1996
Abstract Objectives: As the findings on changes in pulmonary function of welders have been inconsistent, this study aimed to analyze respiratory symptoms and pulmonary function among welders and controls with particular emphasis on small airways dysfunction. Methods: Cross-sectional analysis, using spirometry and a standardized questionnaire, was used to evaluate 521 participants, 166 of whom (64 welders and 102 controls) were evaluated for pulmonary symptoms, occupational inhalative exposures, leisure time activities, and anamnestic data. Results: The welders reported more pulmonary symptoms than the controls. They exhibited a decreased mean expiratory flow (MEF) at 25% and 50% of vital capacity (MEF , MEF ) while 25 50 the other parameters tested (forced vital capacity, forced expiratory volume in 1 s) were unchanged compared with the controls. Multivariate regression analysis revealed that smoking explained the observed variance; only in MEF the duration of welding 25 exposure had a significant influence on this parameter. Conclusions: The significantly reduced flow values among the welders compared with the controls indicates the presence of small airways disease. Differences in smoking habits accounted for more than double the differences in MEF than did chronic welding fume 25 exposure, confirming the role of the former as the main risk factor leading to the decline in lung function. Longitudinal studies are needed to evaluate the long-term effects of chronic welding fume exposure, in
C. Wolf ( ) · C. Pirich · E. Valic Department of Occupational Medicine, Clinic of Internal Medicine IV, University of Vienna, Wa¨hringer Gu¨rtel 18-20, A-1090 Vienna, Austria. FAX: #43 1408 8011 T. Waldhoer Department of Epidemiology, Institute of Tumor Biology, University of Vienna, Vienna, Austria
particular with a view to identifying especially susceptible workers.
Introduction Opinions about the respiratory effects of welding differ, and the influence on small airways lung function remains to be established. Welding fumes contain various gases and particles of metals and oxides. The size of those particles is in the order of 0.01—1 lm [7]. Manual metal welding produces airborne particles, 50% of which are 0.3—0.6 lm in diameter. Small airways are defined as (2 mm in diameter [15]; it is known that small airways dysfunction may develop into chronic obstructive pulmonary disease [10]. It is accepted that conventional spirometry and measurements of breathing mechanics are not sensitive enough to detect obstruction in the peripheral small airways [9]. This is mainly because the resistance is very low in that part of the bronchial tree, constituting only about one-tenth to one-fifth of total airways resistance. It is therefore conceivable that previous conflicting results of spirometric studies comparing welders and controls were due partly to lack of sensitivity of the methods used because small airways function was measured in only a few studies, the main parameters used instead by previous investigators being forced expiratory volume in 1 s (FEV ) or the volume of trapped 1 gas. It is widely accepted that cigarette smoking may induce small airways dysfunction [12]; however, welding particles are also reported to produce a variety of symptoms including wheezing, coughing and dyspnea [6—8]. This cross-sectional study was performed to analyze spirometric data and symptoms of 521 men undergoing annual spirometric evaluation as required by the Austrian protection of labor statute. The questionnaire,
351
circulated in January 1995, was returned by 166 participants and the results were linked to their spirometric data. The eligible study population comprised 64 welders and 102 controls. The controls did not show any occupational inhalative exposure but underwent lung function testing to determine if they could safely wear respiratory equipment.
Materials and methods Materials We used the spirometric data of 521 individuals who had to undergo mandatory preventive examinations between 1992 and 1994. Of these 521 individuals, 250 were welders and 271 were tested to determine if they qualified for participation in rescue operations requiring the wearing of respiratory equipment. In the absence of any occupational inhalative exposure, these latter cases were used as controls. If a subject was examined more than once, the latest available data were used. All subjects received a questionnaire (31 items); 11 questions regarding respiratory symptoms and medications were drawn from the main questionnaire of the European Community Respiratory Health Survey [3]. The detailed wording of the questionnaire is listed in the Results section. Our questionnaire was supplemented by job-specific questions about the duration and extent of welding fume exposure, mechanical and personal work protection devices, the specific welding process, leisure activities, and cigarette consumption. The spirometric data of 521 eligible participants were analyzed. The questionnaire was completed and returned by 166 participants (64 welders and 102 controls) within 4 weeks of its circulation. Methods Spirometry was performed using a 6200 Autobox DL spirometer (Sensormedics, USA) by two experienced technical assistants. The following parameters were examined: forced vital capacity (FVC); FEV ; FEV /FVC; maximum expiratory flow when 75% of the vital 1 1 capacity remained to be expired (MEF ); maximum expiratory flow when 50% of the vital capacity 75 remained to be expired (MEF ); and maximum expiratory flow when 25% of the vital 50 remained to be expired (MEF ). All pulmonary data were capacity 25 standardized according to the Austrian reference values for spirometry [1] and are given as percentages thereof. Statistics Statistical analysis was performed using the SAS system. Differences between the mean values of age, height and nicotine consumption (given in pack-years) for both groups were tested by Wilcoxon’s signed-rank test. In order to include the effects of both smoking and welding and their corresponding interaction, a multivariate regression analysis was conducted with spirometric parameters as dependent variables. A logistic regression model with smoking and welding exposure as independent variables was used to estimate possible effects of welding and smoking on both respiratory symptoms and intake of drugs. Statistical significance was assessed at the 5% two-sided level.
Results Table 1 shows descriptive data of all 166 participants, and Table 2 shows pertinent results of the question-
naire. The logistic regression model with smoking and welding exposure as independent variables showed that the symptoms revealed by the following questions were significantly increased among the welders: Do you bring up phlegm like this on most days for as much as 3 months each year? (P"0.0498) Have you woken up with a feeling of tightness in your chest at any time in the last 12 months? (P"0.0103) Have you been woken by an attack of shortness of breath at any time in the last 12 months? (P"0.0555) Have you been woken by an attack of coughing at any time in the last 12 months? (P"0.0046) Have you had pain, chills or fever a few hours after welding that were gone on the next day? (P"0.0011) Pulmonary function was within the reference range in the majority of subjects (Table 3). In the multivariate regression model with parameter MEF as dependent 25 variable, smoking accounted for twice as much of the observed variance as duration of welding exposure (smoking: P"0.0002, welding exposure: P"0.0374). For parameter MEF , welding exposure had a bor50 derline impact (P"0.0571); smoking showed a significant effect (P"0.0004). For parameter MEF , 75 welding exposure failed to reveal a significant effect but cigarette consumption still showed a significant impact (MEF : P"0.0031). There was no significant impact 75 of either smoking and welding on any of the other variables of respiratory function. The fully evaluable subjects (n"166) did not differ from those who failed to return the questionnaire (n"355). These latter workers (mean age 36$10 years) showed FVC 105$15%, FEV 90$13%, 1 MEF 99$23%, MEF 81$24% and MEF 75 50 25 54$22%. The type of the welding process (shielded arc welding, arc welding, autogenous cutting and welding) was not found to have an impact on any pulmonary parameter nor on the prevalence of clinical symptoms (data not shown). However, the statistical power was inadequate due to the small number of participants per group.
Table 1 Descriptive data. Values are given as means and standard deviations. Welding exposure: working hours/day]years worked as a welder. P-values refer to Wilcoxon’s signed-rank test Welders (n"64) Age Height (cm) Weight (kg) Smoking (pack-years) Welding exposure
41$9 177$6 85$12 27.7$23, 4 91 (0.5—400)
Controls (n"102) 35$10 178$8 82$14 17.4$13 —
P value 0.0001 n.s. n.s. 0.0071 —
352 Table 2 Pulmonary symptoms in welders and controls. Values are given as a percentage of subjects who had symptoms
Symptoms experienced during observation period
Welders (n"64)
Controls (n"102)
1. Have you had wheezing or whistling in your chest at any time in the last 12 months prior to the examination?
22
15
2. Have you had an attack of shortness of breath that came on during the day when you were at rest at any time within the last 12 months? 3. Do you usually cough during the day, or at night in the last 12 months? 4. Do you cough on most days for as much as 3 months each year? 5. Do you usually bring up phlegm from your chest during the day or at night? 6. Do you bring up phlegm like this on most days for as much as 3 months each year? 7. Have you woken up with a feeling of tightness in your chest at any time in the last 12 months? 8. Have you been woken by an attack of shortness of breath at any time in the last 12 months? 9. Have you been woken by an attack of coughing at any time in the last 12 months prior to the examination? 10. Have you had ever pain, chills or fever a few hours after welding which were gone on the next day? Have you taken any drugs for respiratory disease in the last 12 months prior to the examination?
17
6
25
16
31
10
29
13
30
7
14
3
12
4
16
3
20
3
9
3
Table 3 Pulmonary function. Data are given as a mean percentage$SD of the reference value
FVC FEV 1 FEV /FVC 1 MEF 75 MEF 50 MEF 25
Welders (n"64)
Controls (n"102)
106$14 89$14 93$ 8 99$22 75$23 49$21
107$12 92$12 94$ 8 101$24 82$24 56$20
Discussion Comparative measurements of lung function in the welders and controls revealed a significant change of parameters of the flow-volume curve. Other variables of respiratory function tested i.e., FVC and FEV , 1 failed to reveal any differences. Subgroup analysis of the welders demonstrated a significant difference between smokers and nonsmokers. Statistical analysis revealed that smoking contributed more than twice as much to the variation in MEF as chronic exposure to 25 welding fumes. However, some respiratory symptoms were significantly increased among the welders, as was the reported use of anti-obstructive drugs and the prevalence of metal fume fever.
This seems plausible because accumulation of welding particles in small airways can increase mucus production and leads to stagnation of secretion [8]. Welding particles were also reported to give rise to a variety of symptoms including wheezing, coughing and dyspnea [6—8], and in many surveys of welders, an increase in the prevalence of symptoms was the most frequently found abnormality of the respiratory system [4], which might also be reflected in our results. However, in our logistic regression the number of subjects with symptoms was small and therefore the statistical power of our findings is low. For this reason a more thorough differentiation was not possible, but it is known that respiratory symptoms may be increased in welders who smoke compared with nonsmoking welders of similar age [5]. Subjectively, the majority of both welders and controls believed that their exposure to welding fumes had a negative effect on their health. Our data are in agreement with Keimig et al. [10] who reported higher frequencies of respiratory symptoms in welders, but comparing smoking welders and controls no significant differences were found in the prevalence of respiratory symptoms. FVC and FEV 1 were not different in welders and controls [2]. Our results are also in agreement with most other previous studies, which have not revealed any increased prevalence of pronounced airways obstruction in welders [5, 14]. However, Akbarkhanzadeh
353
[1] and Kilburn and Warshaw [11] reported a decrease in FEV among welders irrespective of 1 whether they smoked. Kilburn and Warshaw [11] analyzed a group of welders with at least 15 years of exposure to welding fumes and found FEV , FVC and 1 MEF to be decreased. O®zdemir et al. [14] re25~75 ported a reduction in FVC, FEV and maximal mid1 expiratory flow (MMEF) in welders who smoked whereas there was no significant difference in pulmonary function tests between nonsmoking welders and nonsmoking controls. These findings cannot be translated to our study because of different working conditions. O®zdemir et al. characterized them as inadequate because all welders had been working in confined spaces with poor ventilation and without any respiratory protective devices. Zober and Weltle [16] showed that exposure to welding fumes and gases did not appear to have resulted in a remarkable increase in respiratory diseases. However, welders who smoked showed a combined deleterious effect of smoking and welding [13]. Smoking and welding in combination resulted in a restrictive pattern of lung function, and forced mid-expiratory flow (FMF) was also significantly reduced under these conditions. That our results could be biased by self-selection of less susceptible workers (‘‘healthy worker effect’’) appears unlikely for several reasons. First, regular spirometric examination of welders is mandatory in Austria: if FEV is shown to be (80% of the reference 1 value, the test must be repeated within 3 months. In our sample, such repeated tests were performed in (5% of all participants, and there was no significant difference between welders and controls. Only seven individuals (four welders and three controls) reported to have discontinued their occupation during the observation period. Second, there was no difference in pulmonary function between those welders who completed the questionnaire and those who did not. Clearly, the ideal form of approaching the issue would be to conduct measurements years before, during and at the end of welding exposure in a longitudinal study, whereas our study design was cross-sectional. In conclusion, we found a small decrease in MEF 25 and a higher prevalence of respiratory symptoms among welders compared with controls, which could be explained in part by welding fume exposure, the contribution of smoking habits being greater than that
of welding fume exposure. As both the change in lung function and the development of respiratory symptoms can only partly be explained by smoking and welding, further studies are needed to define factors that make some workers more susceptible to the effects of chronic welding fume exposure than others.
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