Nickel and Tungsten
On the basis of the dichotomized exposure to tungsten less than 0.1 and more than 0.1 mg/m3, all sites analyzed according to both cumulative exposures and mean exposures and classified in quartiles. No SMRs exceeding 1 were determined from the exposure mean analyses (data not in the table), for the high exposure group, but the cumulative exposure were significant in the high exposed group, SMR (1.94, CI 1.22 to 2.94). On the contrary, tungsten exposure was highly correlated to cobalt, according to parametric (Pearson and) and nonparametric (Spearman) methods. Exposure data regarding nickel only existed for company C in a particular process, the hot rolls production. We analyzed 18 cases of lung cancer based on dichotomized nickel exposure less than 0.01 and more than 0.01 mg/m3. No statistically significant excess lung cancer mortality was identified on the basis of SMR analysis, although almost all the SMRs were exceeding 1 (data not in the table).
A response rate of 31% (total number of answered questionnaires, 2746; distributed 8992) was achieved from the questionnaires distributed to the living persons in the cohort, and the average percentage of smokers in this group was 45%; 39% ex-smokers were included in the smokers group (data not in the table). The corresponding figures for the deceased members were 17% (245; distributed 1473) and 59% smokers. When smoking habits were analyzed by duration of exposure in five groups, from less than 1 year to more than 20 years, the percentage of smokers in the groups ranged from 41% to 48%, with an average of 46%. Among the short-term workers with less than 1 year of exposure, 48% were smokers, that is, this group did not differ much from workers with more than 1 year of exposure.
When the analysis was restricted to blue-collar workers with more than 1 year of exposure, and evaluated year of birth by decades from the 1930s to 1990, the overall percentage of smokers ranged from 65% to 27%. When job class was included, workers who had worked several jobs had a range of 31% to 73%, powdering from 25% to 63%, pressing 11% to 72%, slow moving operations 23% to 70%, coating 22% to 75%, and grinding 20% to 59%.
When the analysis was focused on smoking incidence data and cumulative exposure, the overall cumulative mean cobalt exposure for ever smokers was 0.054 mg/m3 years and for never smokers was 0.048 mg/m3 years. The difference was small but stable regardless of duration of exposure. However, no statistically significant difference could be determined.
Our cohort of Swedish hardmetal showed a significant excess mortality for all causes, all heart diseases (ischemic heart disease), malignant neoplasms (lung cancer, liver cirrhosis), as well as some external causes. The increased mortality was strongly associated with the short -term workers and one of the plants. For lung cancer, a negative exposure–response was determined for duration of exposure and latency. An exposure–response was also determined when cumulative and mean cobalt exposure was analyzed by quartiles, but not for high, medium, or low exposure classes. Internal comparison analysis using proportional hazard showed no exposure–response. No exposure–response through an internal comparison analysis using Cox proportional hazard regression was determined.
Personal Data and Register Qualities
Our cohort encompasses a large number of workers and person years, and thus provides a sufficient number of deaths and lung cancer cases for exposure–response analysis, even though there was a high number of short-term employed workers, reflected by a the low average employment time.
The Swedish Population and National Cause of Death registers are well known for their quality; they employ use of personal identification numbers to enable national and regional tracking.26 We have evaluated mortality patterns in the cohort by time period to ensure the completeness of the company personnel registers. Lost to follow-up due to missing personal identification number or incomplete date of employment was only about 10%; all of the cohort members for mortality analysis were identified in the mortality registers.
Exposure Assessment and Exposure Measures
We have used standard exposure measures to evaluate our cohort (ever/never exposed, duration of exposure including latency, and cumulative and mean cobalt exposure) for exposure–response analysis.27,28 It is important to note that when cumulative dose is strongly related to the duration of exposure or other mechanisms related to high exposure at shorter time periods, it is also useful to include mean as an exposure measure.29 Our aggregated job classes reflect the job titles occurring in the company data files and registers accurately, as do data in our historical measurement database. The aggregation of job titles comes out of necessity, and the resolution of jobs in the company records and the measurement database show poor agreement. The within aggregated job class variability by time period are in the same order of magnitude as for job classes in other cohort studies; clarifying data will be presented in the exposure assessment paper.25 Our quantitative cobalt exposure measures are based on log linear modeling, including company, job class, and time period by decade, from 1970.30 As a large group of our cohort was included in the national mortality registers starting in the early 1950s, we have used our modeling of cobalt exposure to estimate the periods 1950 to 1959 an 1960 to 1969 rather than applying data from 1970 to 1979 for these earlier years. Our model shows decreasing exposure concentration levels at a rate of 2% to 3% per year, in line with trends reported in several other industrial cohorts.31,32 Our cohort consisted of many workers with short duration employments, even when restricted to blue-collar workers with more than 1 year of exposure, implying rather low cumulative and mean exposures. A standard categorization by quartiles would give even the high quartile low cumulative and mean exposures. To compare with risk expressed as a working life at the present OELs for cobalt and to compare the exposure measures with data in earlier mortality lung cancer studies, we also presented data by three exposure groups, the highest representing 40 years of exposure at half the present Swedish OEL for cobalt.
However, we have also provided a sensitivity analysis where we based our model data before 1970 on exponential extrapolation, as suggested by others.33 This provided higher cumulative and mean exposures, but no change in the SMR pattern was found when analyzed by exposure class or quartiles.
Lung Cancer and Exposure to Cobalt
We have presented mortality data using national rates for mortality even though two of the plants are rurally located, and one urban. Our reasons for this were justified by an initial comparison of mortality, all causes as well as lung cancer, where the differences between mortality for national and regional rates were small and insignificant.
Our initial analysis of lung cancer risk based on duration of exposure and latency showed an almost negative exposure–response, even though all the SMRs exceeded 1 (nonsignificant). Given the age of the cohort, we still have a large number of lung cancer cases, characterized by both high duration of exposure and latency to evaluate, that is, 35 lung cancer cases with more than 20 years of exposure and 20 years of latency for the whole cohort. This supports the robustness of our lung cancer mortality data when evaluated for the high exposure group.
To refine the analysis of cobalt and lung cancer, we restricted the duration of employment to more than 1 year. Furthermore, we analyzed blue-collar jobs in addition to all jobs in the exposure–response analyses, and thereby improved our model data, and exposure measures and information regarding the effects of cobalt exposure for different jobs.
We have analyzed dose–response by SMR using two different dose groups for the cumulative and mean exposures measures, one based on quartiles and the other based on exposure grouping (low, medium, and high) related to 40 years exposure at 50% of the current Swedish OEL, 0.02 mg/m3. The latter grouping was performed for reasons of comparison with the earlier studies and OELs, in particular the Swedish study.10
The analysis of all jobs with more than 1 year of exposure gives us significant risk for lung cancer (SMR 1.52), and an exposure–response pattern with significant SMRs for the third and fourth quartiles, of cumulative dose corresponding to more than 0.001 mg/m3 for 40 years. Only the third quartile, however, deviates significantly from the reference group. No exposure–response pattern could be identified in the high exposure group, although all the SMRs were more than 1, significant only for the exposure group characterized by less than 0.005 mg/m3 in 40 years. However, when mean exposure values were used in the analysis, a significant excess risk was determined in the high exposed group. When restricted to blue-collar workers with more than 1 year of exposure, a similar pattern, including an excess SMR of 1.4, was noticed for the blue-collar workers, but the exposure–response was weaker, and the significant findings for mean values have disappeared. We consider cumulative dose measures the most relevant for lung cancer. These findings might appear contradictory, but no adjustments for smoking or lifestyle factors have been performed.
Our data were not adjusted for smoking, nor have we adjusted for differences in socioeconomic or lifestyle factors, that is, we are still comparing our data with the national population. These issues, as well as the data from our questionnaires, are discussed in separate paragraphs. However, the lack of individual smoking data and other potential differences between our hardmetal workers and the general population necessitates an internal comparison, and is why we performed a Cox proportional hazard regression analysis (Tables 9 and 10). No statistically significant increased hazard ratios (hazard ratios >1) were determined for cumulative or mean exposures, when the analysis included all jobs. Our exposure grouping initially used quartiles, the highest cumulative exposure group representing 0.002 mg/m3 for 25 years. For blue-collar workers, the hazard ratio exceeded 1 for the highest quartiles for both exposure measures, cumulative and mean exposure. It could be argued that by using quartiles, we are only internally comparing rather low exposures. For this reason therefore, we have applied Cox analysis using our exposure classes already applied when we analyzed the lung cancer by SMR. These Cox analyses all showed hazard ratios below 1.
The evaluation of exposure–response analyses for the exposure measures ever/never employed, duration of exposure, cumulative and mean exposure to cobalt, and comparing our lung cancer mortality with the general population, an internal comparison failed to provide a consistent exposure–response relationship. Our high exposure group represents cumulative exposures more than 0.4 mg/ m3 years.
Tobacco smoke, tobacco smoking, and involuntary smoking are all considered to be carcinogenic (group 1) to humans.34 Any occupational epidemiology study addressing lung cancer as one of the endpoints must investigate, or clarify smoking data and employ to indirect or direct adjustment methods. Initially, lung cancer cases and appropriate number of controls were supposed to be analyzed in a nested case–control study, in which both cases and controls answered an extensive questionnaire on smoking and other lifestyle factors as well as competing occupational exposures by telephonic interviews by our National Bureau of Statistics. However, certain incompleteness of the personal identification numbers during matching our cohort with the Swedish Mortality register restricted our study, and it was not possible to identify cases and controls in our population registers to carry planned telephonic interviews.
As an alternative, we used questionnaires, distributed to living cohort members with a response rate of 31%, and an average percentage of smokers of 45%. The corresponding figures for the deceased cohort members were 17% and 59%, respectively. Among the short-term workers with less than 1 year of exposure, 48% were smokers; this group did not differ much from workers with more than 1 year of exposure. We consider the response rates poor, and our intentions to use questionnaire data for individual smoking data in a case–control study or other adjustments were not possible. We could not establish any statistically significant difference in cumulative exposures when smokers and nonsmokers were compared. If any increased lung cancer risk could be determined in an exposure–response analysis, it could not be attributed to differences in smoking habits between exposure groups.
However, we used our data on smoking habits to compare the reference and the exposure groups regarding smoking habits, in particular, if excess hazard ratios were determined through the Cox regression analysis.
Nickel and Tungsten
Metallic nickel and chromium could be present in certain hardmetal grades during the production of hardmetal products. Our site questionnaire was not specific enough to resolve whether nickel was used, but additional data from the Swedish plants indicated that nickel was used at all three Swedish plants.
As measurement data were restricted to company C, we performed an exposure–response analysis of lung cancer and nickel exposure for that plant. Our analysis included only 18 cases of lung cancer and showed increased SMRs (>1), however not statistically significant. Our SMR analysis and the exposure estimates were based on a very crude dichotomized nickel exposure level for the cumulative and mean exposure estimates. The underlying measurement data are sparse and unevenly distributed between jobs, company, and time period, resulting in residual confounding. Data must be carefully interpreted and considered indicative. No further analysis regarding nickel exposure and lung cancer was performed and the potential Cox regression analysis was left out. Our historical measurement database showed low levels of nickel; only 6% exceeded 0.1 mg/m3 and just 1% exceeded 0.5 mg/m3.
Our historical measurement database showed that only 6% exceeded 0.1 mg/m3 and just 1% exceeded 0.5 mg/m3. The Swedish OEL19 for nickel in the metal state is currently 0.5 mg/m3, and the metal is not classified as carcinogenic; the corresponding ACGIH TWA is 1.5 mg/m3.35 Within the EU, insoluble and soluble compounds are considered carcinogenic and addressed with low recommended OELs; however, metallic nickel is excluded, as neither animal experiment nor human epidemiological studies have indicated any carcinogenicity.36 IARC classifies metallic nickel as possibly carcinogenic to humans (group 1), based on “sufficient evidence in humans for carcinogenicity of mixtures that include nickel and nickel compounds”17 Our evaluation of nickel exposure and lung cancer is restricted to the only plant that has measurement data. Only a few cases of lung cancer were available and the lack of measurement data necessary to perform exposure modeling makes any conclusions limited. However, our finding is somewhat supported by the exposure measurement data for nickel, well below current OELs. Tungsten exposure measurement data were highly correlated to cobalt, and given the sparse number and distribution over time and jobs, any exposure–response findings would be difficult to interpret.
A large proportion of our cohort represents workers with a duration of employment less than 1 year due to the inclusion criteria set in the international study group and having the possibility to use the short-term exposed workers as a reference group. Short-term workers comprised 42% (6568) of our cohort, with skewed representation between company A (31%), company B (17%), and company C (67%). For our analysis, in particular lung cancer, this implies that 153 lung cancer cases with more than 1 year of exposure out of originally 298 cases represented workers with less than 1 year of exposure. The potential exposure factors when analyzing and explaining increased morality in short-term workers have been have been extensively discussed in two previous industrial cohorts.37 In principal, the high mortality for short-term workers could be explained by exposure to the highest concentration levels, a subgroup with higher susceptibility, quitting jobs sooner, and experiencing more hazardous exposure in other occupations. Lifestyle factors, such as not only smoking, which is especially relevant for lung cancer, but also drinking habits and other socioeconomic factors could be involved. In our study, the short-term (<1 year) workers showed excess risk for mortality for all causes when compared with the total cohort, in addition to the increased risk as for malignant neoplasms, buccal cavity, esophagus, larynx, lung, and bladder, cardiovascular disease, heart disease, nonmalignant respiratory disease, cirrhosis, and all external causes of death, including suicide. The very high mortality for the short-term workers, especially liver cirrhosis, indicated an enhanced pattern of alcohol consumption as an indicator of socioeconomic factors that affects health. However, no such difference was noted when we investigated the differences between smoking habits based on data from our self-administered questionnaire. In fact, 49% of the workers with less than 1year of exposure were smokers, only slightly higher than the rate of the total group, 46%. All other groups based on duration of employment showed only slightly lower smoking rates (41% to 47%). These data are in line with findings from other large industrial cohorts.38
Our findings imply other explanations than differences in smoking habits, which were only slightly higher for the short-term workers, to explain the differences in lung cancer outcome.
Our findings show a similar mortality pattern to the earlier published data from an original cohort of Swedish hardmetal workers (3163 male workers), evaluated for the period 1940 to 1982.10 The overall mortality was found to be less than 1. However, when lung cancer mortality was evaluated for members with more than 10 years of exposure and 20 years of latency, a nonsignificant exposure–response based on low and high exposure group was found, SMR (2.3, 3.3, respectively). When more than 10 years of exposure and more than 20 years of latency was applied for our data (Table 6), no consistent exposure–response could be determined, and applying cumulative cobalt exposure estimates for blue-collar workers and internal comparison showed similar results (Tables 8 and 10).
A French cohort of 709 hardmetal workers employed between 1956 and 1989 was analyzed for mortality and exposure–response patterns.11 The high exposed group showed a significant SMR of 5.03, but including smoking habits, the risks among the current smokers, increased the SMRs to 9.2 and 15 for the medium and high exposed group, respectively. Analyses of duration of employment and latency showed no exposure–response trends. Our findings, which did not identify any exposure–response for internal comparison, may reflect the decreased exposure levels in our study, which included the period from 1990 onwards. It should be noted that our high exposure group, more than 0.4 mg/m3 • year, reflects a 40-year exposure to 0.010 mg/m3 of cobalt, to be comparable with exposure group 2 of the French study.
In another French multicenter study, a cohort was formed from 10 different plants, with an inclusion criteria more than 3 months exposure and a mortality follow-up from 1968 to 1991.13 The cohort included 7459 men and women. An increasing trend for the SMR was determined by an increased duration of exposure. The overall analysis in the case–control study showed an excess risk (OR 1.93, statistically significant). However, when adjusting for smoking, smokers (OR 3.62) showed a significantly increased risk, and workers who had never smoked (OR 1.21) showed a nonsignificant risk. The high-dose group in the analysis consisted of more than 164 or more than 299 level ·months; according to the given job exposure levels in the study, it would, for example, correspond to 40 months (3.3 years) at level 4, 0.06 mg/m3, that is, 0.20 mg/ m3 • years. These exposure levels are in the same order of magnitude as the high exposure group in our study. The finding in the French case–control study implicates dose levels about 0.2 mg/ mg/m3 • years, as they potentially generate an increased risk of lung cancer.
Another cohort study from a French plant producing hardmetal and other cobalt products included 2860 workers.12 The company started in 1940, and the follow-up period was 1968 to 1992. The mortality pattern showed excess SMRs for lung cancer in men. Smoking data were retrieved from colleagues. An analysis based on exposure scores and weighted and unweighted cumulative exposures showed significant SMRs (2.36, 2.06) for both the high exposure groups, which had been adjusted for smoking. However, no quantitative data are provided for the different exposure groups. The follow-up period of this study deviates from ours, reflecting different exposure periods.
Other Mortality Causes
Our data showed overall significant excess risks both for ischemic and cerebrovascular disease. A negative exposure response was also identified when analyzed by duration of exposure. In the original Swedish cohort,10 an excess risk for ischemic heart disease was determined for the high exposure group, but no excess risk was determined in the other studies (Lasfargues, SMR 0.82; Moulin, SMR 0.88 to 0.90; Wild, SMR 0.91). However, the relationship between particle exposure and cardiovascular disease is an emerging area of interest, and the mechanisms for inflammatory response to exposure have been established.39
Nonmalignant Respiratory Disease
We determined excess mortality for certain nonmalignant respiratory disease, such as bronchitis, emphysema, and pneumonia, strongly associated with the urban plant. However, the total mortality showed negative exposure response when analyzed by duration of exposure. As expected, the number of cases of nonmalignant respiratory disease was substantially higher than that of the French studies and earlier Swedish study.
In our cohort of Swedish hardmetal workers, we have determined a statistically significant excess mortality for all causes, all heart disease (ischemic heart disease), malignant neoplasms (lung cancer, liver cirrhosis) as well as some external causes. The increased mortality was strongly associated with the short-term employed workers and one of the plants. For lung cancer, a negative exposure–response was found for duration of exposure. For cumulative and mean cobalt exposure by quartiles, an exposure–response was determined, but not for high, medium, and low exposure classes. Smoking was not adjusted for. By internal comparison analysis using Cox proportional hazard regression for cumulative and mean exposure, no exposure response was shown. No exposure–response was determined for cobalt, nickel, and tungsten.
We would like to acknowledge the cooperation and assistance of the representatives from the industry and their Swedish sites. In particular, we would like to thank all the employees who provided assistance throughout the study.
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