Welding fume exposure and chronic obstructive pulmonary disease in welders

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1 Occupational Medicine 2015;65:72 77 Advance Access publication 16 October 2014 doi: /occmed/kqu136 Welding fume exposure and chronic obstructive pulmonary disease in welders D.-H. Koh, 1 J.-I. Kim, 2 K.-H. Kim 3 and S.-W. Yoo, 4 on behalf of the Korea Welders Cohort Group 1 National Cancer Control Institute, National Cancer Center, Goyang , Korea, 2 Department of Occupational and Environmental Medicine, Dong-A University, Busan , Korea, 3 Department of Occupational and Environmental Medicine, Busan Paik Hospital, Inje University, Busan , Korea, 4 Occupational Safety and Health Research Institute, Korea Occupational Safety and Health Agency, Incheon , Korea. Correspondence to: J.-I. Kim, Department of Occupational and Environmental Medicine, College of Medicine, Dong-A University, 26 Daesingongwon-ro, Seo-gu, Busan , Korea. Tel: ; fax: ; kimji@dau.ac.kr Background Occupational exposure is estimated to contribute 15% to the burden of chronic obstructive pulmonary disease (COPD). Welding fumes are suspected to accelerate the decline of lung function and development of COPD. Aims Methods Results To examine the relationship between welding fume exposure and COPD in Korean shipyard welders. The study involved a group of male welders working at two shipyards who underwent an annual health examination in Subjects completed a questionnaire about smoking habits and occupational history and a pulmonary function test (PFT) was carried out with strict quality control measures. Welding fume exposure concentrations were estimated using 884 measurements taken between 2002 and 2009 in one of the shipyards. Multiple linear and logistic regression was employed to evaluate the association between cumulative fume exposure and lung function parameters, controlling for age, height and cigarette smoking. Two hundred and forty subjects participated, with a mean age of 48 and mean work duration of 15 years. The mean cumulative fume exposure was 7.7 mg/m 3. The prevalence of COPD was 15%. FEV 1 and FVC showed non-significant negative correlations with cumulative fume exposure. Odds ratios of COPD were significantly elevated for the middle (3.9; 95% CI ) and high exposure groups (3.8; 95% CI ) compared with the low fume exposure group. Conclusions Our findings support an association between welding fume exposure and increased risk of COPD. Further prospective study is needed to investigate whether this is a causal relationship. Key words Chronic obstructive pulmonary disease; metal fume; occupation; welder; welding. Introduction Chronic obstructive pulmonary disease (COPD) is a disease characterized by persistent airflow limitation that is usually progressive and associated with an enhanced chronic inflammatory response to noxious particles or gases in the airways and the lung [1]. COPD is a preventable disease but in 2020 COPD is projected to rank fifth in terms of the global burden of disease and third in global causes of mortality [1]. Occupational and environmental factors may contribute to 15% of cases of COPD, according to a consensus report of the American Thoracic Society (ATS [2]), and also contribute to increased COPD mortality [1]. Occupational and environmental factors causing COPD include organic and inorganic dusts, metal fumes, chemicals and gases [3,4]. Welding fume is known to cause adverse health effects including pulmonary siderosis and fibrosis [5]. It is also a possible human carcinogen (IARC group 2B) causing lung cancer [6,7]. In addition several studies have reported a negative impact of welding fume exposure on lung function [8,9]. In spite of the established toxicity of welding fume to the lungs, epidemiological studies of COPD have shown inconsistent results. Bogadi-Sare [10] and Wang et al. [11] reported significant reduction of FEV 1 /FVC (forced expiratory volume in one second/ forced vital capacity) ratio. Chinn et al. [12,13] reported that welding fume exposure significantly increased the The Author Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please journals.permissions@oup.com

2 D.-H. KOH ET AL.: WELDING FUME EXPOSURE AND COPD IN WELDERS 73 rate of lung function decline. Christensen et al. [14] and Erkinjuntti-Pekkanen et al. [15] reported significantly increased lung function decline only in smokers, or smokers working without local exhaust ventilation or respiratory protection. Meanwhile Gennaro et al. [16] reported no significant association between job title in shipyard workers and obstructive pulmonary function, but reported an increased odds ratio for >20 compared with <20 years work experience. Lou et al. [17] reported only a borderline linear trend of FEV 1 decline in automobile spot welders. Mur et al. [18] and Rossinol et al. [19] reported no significantly increased lung function decline in welders. In this study, we examined the dose-related association between welding fume exposure and COPD in Korean shipyard welders, controlling for cigarette smoking. Methods Male welders working in two shipyards located on the south coast of Korea participated in this study. They underwent a periodic health examination, including pulmonary function testing, between April and June Subjects completed a self-administered questionnaire asking about smoking habits, occupational history and past medical history which was used for calculating smoking pack-years and cumulative fume exposure. A flow-type spirometer, Flow Screen spirometer (VIASYS Healthcare GmbH, Germany), was used for measuring lung function parameters. Calibration with a 3-L syringe was conducted every morning, and whenever experienced technicians thought it was needed. A standard pulmonary function test (PFT) procedure, without bronchodilator, according to the ATS/ERS (European Respiratory Society) guidelines [20 22], was employed, except that the PFT was ended if two trials met quality criteria instead of three, because it was difficult to conduct multiple tests in the field survey. Two experts in PFT (DHK, TKK) carefully examined the quality of the test in terms of acceptability and reproducibility by reviewing volume-time and flow-volume curves. If the test started with extrapolated volume <5% of FVC or 0.15 L, whichever was greater, and ended with exhalation duration 6 seconds or a plateau in the volume-time curve, and the curves had no artifacts, the test met the acceptability criteria [21]. If the two values of FVC and the two values of FEV 1 were each within 0.15 L of each other, the test met the reproducibility criteria [21]. The best value selection method was employed to determine the best values of the PFT for each subject. Study subjects were welders working inside or outside the ship. They were exposed to metal fume during welding and cutting metals. To assess fume exposure concentrations we collected environmental monitoring records from one of the two companies from 2002 to Welding fume concentrations were measured twice yearly by industrial hygienists in work environment monitoring agencies. A standard sampling and analytical method was employed according to relevant regulations [23]. Personal fume samples were collected for one worker in every five classified into a similar exposure group. Samples were collected during full shifts (>6 hours) by drawing a volume of air through a 37-mm diameter, 5 μm mixed cellulose ester membrane filter. Filter cassettes were placed in the breathing zone behind the welding helmet. Samples were then dried and weighed in a climate-controlled room. We categorized welding fume-exposed jobs as arc welding, tack welding (fit-up) and cutting, and calculated mean exposure concentrations for each job. Mean fume concentrations for arc welding, tack welding, and cutting were 2.7, 1.6 and 1.2 mg/m 3, respectively (Table 1). We calculated cumulative fume exposures for workers by multiplying mean exposures for each job title by duration of work in the job(s) concerned, using the occupational history obtained in the questionnaire survey. After calculating cumulative exposure, we categorized workers into low, intermediate and high exposure groups by tertile values of cumulative fume exposure. Multiple linear regression was employed to examine the associations between FEV 1 and FVC and cumulative fume exposure, controlling for age, height and smoking amount. In the multiple regression model, the values of FEV 1 and FVC were incorporated as dependent variables, age and height were incorporated as continuous independent variables, and tertiles of the smoking amount and cumulative fume exposure were incorporated as categorical independent variables. COPD was defined as an FEV 1 /FVC ratio less than lower limit of normal (LLN) for the Korean male population [24]. LLN values are based on a normal distribution and define the bottom 5% of the healthy population as abnormal. Logistic regression was employed to examine the excess risk of COPD by cumulative fume exposure, controlling for age, height and smoking status. COPD was incorporated as a binary dependent variable, age and height were incorporated as continuous independent variables, and tertiles of the smoking amount and cumulative fume exposure were incorporated as categorical independent variables. We repeated those analyses for workers aged Table 1. Metal fume concentrations by job title (mg/m 3 ) Task n Mean SD GM GSD Median Min Max Arc welding Tack welding < Cutting n, number of measurements; SD, standard deviation, GM, geometric mean; GSD, geometric deviation; Min, minimum concentration; Max, maximum concentration.

3 74 OCCUPATIONAL MEDICINE 40 or over because COPD is uncommon in younger individuals. In addition, we repeated the analyses for a group of never-smokers. This study protocol was reviewed and approved by the Institutional Review Boards of the Occupational Safety and Health Research Institute (OSHRI) and of Dong-A University Hospital. All participants gave written informed consent. Results In total 306 welders were recruited. Of these 22 were excluded because their PFT results did not meet the quality control criteria and an additional 44 because of missing questions or errors in their questionnaire responses, leaving 240 welders exposed to welding fume selected for analysis of the dose-related relationship between welding fume exposure and COPD. The mean age of the 240 study subjects was 48, and average fume exposure duration was 15 years. The most numerous age group was and the most common work duration period was <10 years (Table 2). The prevalence of COPD was 15%. The mean ages of non-copd and COPD were 46.5 (SD = 11.8) and 55 (SD = 8), respectively. The average exposure duration of non-copd and COPD was 16.5 (SD = 11.7) and 27.9 (SD = 9.5), respectively. The proportion of never-smokers was 32%, while current and ex-smokers were 53% and 15%, respectively (Table 2). The distributions of smoking status and smoking amounts did not differ between non- COPD and COPD subjects, according to the results of chi-square tests. The average cumulative fume exposure was 7.7 mg/m 3 -years (max 22.8), and for non-copd and COPD subjects was 7 mg/m 3 -years (SD = 6) and 11.4 mg/m 3 -years (SD = 5.9), respectively. There was no statistically significant difference in mean height between non-copd and COPD subjects. For all welders the intermediate and high fume exposure groups showed negative correlations with FEV 1 and FVC compared to the low exposure group; however, those associations were not statistically significant (Table 3). For welders aged 40 and over or never-smokers these associations were generally consistent but still statistic ally non-significant. For all welders a statistically significant excess risk was found in the intermediate (odds ratio [OR] = 3.9, 95% CI ) and high exposure group (OR = 3.8, 95% CI ), compared with the low exposure group (Table 4). For welders aged 40 or over the risk was not statistically significant. For never-smokers the risk was also statistically non-significant. Discussion In this study workers with intermediate and high fume exposure showed significant excess risk of COPD compared with the low exposure group. Our findings suggest a potential relationship between welding fume exposure and COPD but this relationship was statistically nonsignificant when we repeated the analysis for those aged 40 or over. Smoking showed no significant or consistent association with COPD in logistic regression, in spite of its Table 2. General characteristics of study subjects Variable Category Non-COPD, n (%) COPD, n (%) Total, n (%) Age (years) (12) 2 (5) 26(11) (19) 6 (16) 45(19) (24) 4 (11) 52(22) (30) 18 (49) 78(33) 60 32(16) 7 (19) 39(16) Exposure duration (years) <10 83(41) 8 (22) 91(38) (21) 8 (22) 51(21) (25) 9 (24) 60(25) 30 26(13) 12 (32) 38(16) Smoking status Never 62(31) 14 (38) 76(32) Current 109(54) 19 (51) 128(53) Ex-smoker 32(16) 4 (11) 36(15) Smoking amount (pack-years) (34) 14 (38) 84(350) (36) 11 (30) 84(35) (30) 12 (32) 72(30) (37) 5 (14) 80(33) (35) 18 (49) 89(37) (28) 14 (38) 71(30) Total 203(85) 37 (15) 240(100) n, number of subjects.

4 D.-H. KOH ET AL.: WELDING FUME EXPOSURE AND COPD IN WELDERS 75 Table 3. The results of multiple linear regression adjusted for age and height Variable FEV 1 (L) FVC (L) β slope SE P-value β slope SE P-value All (n = 240) Smoking (pack-years) Ref: < NS NS NS NS Ref: < NS NS NS NS Age 40 (n = 169) Smoking (pack-years) Ref: < NS NS NS NS Never smoker (n = 76) β slope, regression coefficient; SE, standard error; n, number of subjects. Ref: < < NS NS NS NS Ref: < NS NS NS NS Table 4. The results of logistic regression adjusted for age and height Variable OR (95% CI) All (n = 240) Smoking (pack-years) Ref: < ( ) ( ) Ref: < ( ) ( ) Age 40 (n = 169) Smoking (pack-years) Ref: < ( ) ( ) Never smoker (n = 76) OR, odds ratio; n, number of subjects. Ref: < ( ) ( ) Ref: < ( ) ( ) well-known effect on COPD development. This discrepancy may be a result of the healthy worker effect (both hiring and survivor effect [9]). For instance a worker who suffered COPD symptoms such as shortness of breath may be more likely to stop smoking or leave the job. Accordingly there was no significant difference in smoking amounts between non-copd and COPD subjects. The healthy worker effect might have contributed to moving the COPD risk toward the null. According to a nationwide COPD prevalence study (PFT without bronchodilator, diagnosed by fixed FEV 1 /FVC ratio [25]), COPD prevalence in Korean men aged was reported as 17%. COPD prevalence by fixed FEV 1 /FVC ratio in our subjects aged was 26%, which is higher than in the general population in spite of the potential healthy worker effect. Both smoking and welding fume exposure showed no significant association with COPD in linear regression which may indicate the study was under powered due to the small number of subjects. In analyses for neversmokers the COPD risk was slightly elevated and a negative correlation between FEV 1 and FVC, and cumulative fume exposure was found, but the number of COPD cases (14) was insufficient to examine the relationship between COPD and welding fume exposure. Our findings indicate a study with a larger number of subjects is required to elucidate the association. As far as possible injury mechanisms

5 76 OCCUPATIONAL MEDICINE are concerned, oxidative damage caused by heavy metals is one plausible mechanism [26]. Estimates of the prevalence of COPD depend on the definition and criteria used. A clinical diagnosis of COPD should be considered in any patient who has relevant symptoms and spirometry is required to make the diagnosis in the clinical context [1]. However, this was a population study in an occupational setting so we defined COPD using spirometry only, as is common practice in epidemiological studies [27]. In questionnaire responses one subject reported pre-existing COPD and four reported asthma. Because analyses excluding these five welders resulted in no significant difference compared with analysis of data for all subjects, and because COPD and asthma can be affected by welding fume exposure, the results presented here are based on analysis of data from all subjects. The strengths of our study include the quantitative fume exposure assessment. This is essential to test doserelated health effects. We used 884 fume measurements spanning 8 years to estimate exposed fume concentrations. Although the measurements came from only one of two shipyards and there was great variability within job title (GSD: ) which suggests a better exposure grouping is required, the data do permit cumulative exposure estimates and hence the ability to detect an exposure-disease association. Other strengths include the strict quality control of PFT. Well-trained technicians conducted PFT according to the ATS/ERS guidelines and two experts reviewed the test results and excluded unacceptable trials. These quality control processes may increase the validity of PFT results. In addition, we used the LLN as an indicator of COPD. Previous studies examining the relationship between welding fume exposure and COPD have used fixed FEV 1 /FVC ratios (without bronchodilator) for defining COPD [10,11,16,17]; but using fixed FEV 1 /FVC ratios may result in underdiagnosis in younger and over-diagnosis in older age groups [1]. Therefore using updated diagnostic criteria might improve our ability to detect any relationship between welding fume exposure and COPD. Our study has some limitations. Firstly, there was no control group not exposed to welding fumes and this may lead to a potential underestimate of the impact of welding fume exposure on lung function. Secondly, we did not collect detailed information on the welding methods and metals used. Most of the subjects welded mild steel using a CO 2 welding process, which is the most common type of welding in a shipyard. However, some welders may perform stainless steel welding, which involves more toxic metals, such as chromium and nickel, than mild steel welding [6,18]. Thirdly, our study was a cross-sectional one so we could not examine any longitudinal change in lung function associated with welding fume exposure. Fourthly, we did not account for other exposure predictors, such as personal protective equipment (PPE) use, work in confined spaces, and use of control measures. For instance workers welding in a confined space without local exhaust ventilation are more heavily exposed to welding fume than in outdoor welding [14]. And finally we did not account for co-exposures that may affect lung function. For instance welders can be indirectly exposed to coarse dusts generated by nearby grinders. Deposition of inhaled particles in the lung is primarily determined by particle size [28]. Grinding dust particles are much larger than welding fume particles and are mainly deposited in the upper respiratory tract, where they are cleared, swallowed and moved to the gastrointestinal tract [29]. In contrast, the smaller welding fume particles reach terminal bronchiol and alveoli and may result in more toxic effects than the larger dust particles. Therefore, co-exposure to coarse dusts may not substantially influence the decline of lung function in welders. In summary, we examined the association between metal fume exposure and COPD in shipyard welders. Our findings suggest an association between welding fume exposure and increased risk of COPD, but a longitudinal study with a larger number of subjects is needed to confirm any causal association. Key points This study examined the relationship between cumulative welding fume exposure, based on workplace measurement data, and chronic obstructive pulmonary disease. Our findings support an association between welding fume exposure and increased risk of chronic obstructive pulmonary disease in Korean shipyard welders. Measures to control welders exposure to welding fume are required to prevent chronic obstructive pulmonary disease. Funding This study was supported by the Occupational Safety and Health Research Institute ( ), Korea Occupational Safety and Health Agency. Acknowledgement The authors are grateful to Dr. Tae-Kyun Kim for his excellent quality control of PFT. Conflicts of interest None declared. References 1. Vestbo J, Hurd SS, Agustí AG et al. Global strategy for the diagnosis, management, and prevention of chronic

6 D.-H. KOH ET AL.: WELDING FUME EXPOSURE AND COPD IN WELDERS 77 obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med 2013;187: Balmes J, Becklake M, Blanc P et al. American Thoracic Society Statement: Occupational contribution to the burden of airway disease. Am J Respir Crit Care Med 2003;167: Balmes JR. Occupational contribution to the burden of chronic obstructive pulmonary disease. J Occup Environ Med 2005;47: Blanc PD, Menezes AM, Plana E et al. Occupational exposures and COPD: an ecological analysis of international data. Eur Respir J 2009;33: Antonini JM, Taylor MD, Zimmer AT, Roberts JR. Pulmonary responses to welding fumes: role of metal constituents. J Toxicol Environ Health A 2004;67: Sørensen AR, Thulstrup AM, Hansen J et al. Risk of lung cancer according to mild steel and stainless steel welding. Scand J Work Environ Health 2007;33: IARC. IARC Monographs on the Evaluation of Carcinogenic Risks to Humans Chromium, Nickel and Welding. Lyon: IARC, Omland O, Würtz ET, Aasen TB et al. Occupational chronic obstructive pulmonary disease: a systematic literature review. Scand J Work Environ Health 2014;40: Szram J, Schofield SJ, Cosgrove MP, Cullinan P. Welding, longitudinal lung function decline and chronic respiratory symptoms: a systematic review of cohort studies. Eur Respir J 2013;42: Bogadi-Sare A. Respiratory disorders in stainless steel workers. Arh Hig Rada Toksikol 1990;41: Wang ML, McCabe L, Hankinson JL et al. Longitudinal and cross-sectional analyses of lung function in steelworkers. Am J Respir Crit Care Med 1996;153: Chinn DJ, Stevenson IC, Cotes JE. Longitudinal respiratory survey of shipyard workers: effects of trade and atopic status. Br J Ind Med 1990;47: Chinn DJ, Cotes JE, el Gamal FM, Wollaston JF. Respiratory health of young shipyard welders and other tradesmen studied cross sectionally and longitudinally. Occup Environ Med 1995;52: Christensen SW, Bonde JP, Omland O. A prospective study of decline in lung function in relation to welding emissions. J Occup Med Toxicol 2008;3: Erkinjuntti-Pekkanen R, Slater T, Cheng S et al. Two year follow up of pulmonary function values among welders in New Zealand. Occup Environ Med 1999;56: Gennaro V, Baser ME, Costantini M, Merlo F, Robutti P, Tockman MS. Effects of smoking and occupational exposures on pulmonary function impairment in Italian shipyard workers. Med Lav 1993;84: Luo JC, Hsu KH, Shen WS. Pulmonary function abnormalities and airway irritation symptoms of metal fumes exposure on automobile spot welders. Am J Ind Med 2006;49: Mur JM, Pham QT, Teculescu D et al. Arc welders respiratory health evolution over five years. Int Arch Occup Environ Health 1989;61: Rossignol M, Seguin P, DeGuire L. Evaluation of the utility of spirometry in a regional public health screening program for workers exposed to welding fumes. J Occup Environ Med 1996;38: Miller MR, Crapo R, Hankinson J et al. General considerations for lung function testing. Eur Respir J 2005;26: Miller MR, Hankinson J, Brusasco V et al. Standardisation of spirometry. Eur Respir J 2005;26: Pellegrino R, Viegi G, Brusasco V et al. Interpretative strategies for lung function tests. Eur Respir J 2005;26: NIOSH. NIOSH Manual of Analytic Methods. 4th ed. National Institute of Occupational Safety and Health. Washington, DC: U.S. Government Printing Office, Hwang YI, Kim CH, Kang HR et al. Comparison of the prevalence of chronic obstructive pulmonary disease diagnosed by lower limit of normal and fixed ratio criteria. J Korean Med Sci 2009;24: Kim DS, Kim YS, Jung KS et al. Prevalence of chronic obstructive pulmonary disease in Korea: a populationbased spirometry survey. Am J Respir Crit Care Med 2005;172: Cullinan P. Occupation and chronic obstructive pulmonary disease (COPD). Br Med Bull 2012;104: Mannino DM, Homa DM, Akinbami LJ, Ford ES, Redd SC. Chronic obstructive pulmonary disease surveillance United States, MMWR Surveill Summ 2002;51: Choi JI, Kim CS. Mathematical analysis of particle deposition in human lungs: an improved single path transport model. Inhal Toxicol 2007;19: Koh DH, Bhatti P, Coble JB et al. Calibrating a populationbased job-exposure matrix using inspection measurements to estimate historical occupational exposure to lead for a population-based cohort in Shanghai, China. J Expo Sci Environ Epidemiol 2014;24:9 16.

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