Guida, Florence PharmD; Paget-Bailly, Sophie PhD; Lamkarkach, Farida MS; Gaye, Oumar MS; Ducamp, Stéphane MS; Menvielle, Gwenn PhD; Papadopoulos, Alexandra PhD; Matrat, Mireille MD; Févotte, Joëlle MS; Cénée, Sylvie MS; Cyr, Diane MS; Schmaus, Annie MS; Carton, Matthieu MD; Radoï, Loredana DMD; Lapôtre-Ledoux, Bénédicte MD; Molinié, Florence MD; Luce, Danièle PhD; Stücker, Isabelle PhD
Although tobacco smoking is the leading cause of lung cancer, exposure to occupational carcinogens is an important preventable cause of lung cancer (attributable fractions [AFs] estimated between 13% and 30% in France).1 The most frequent man-made vitreous fibers are glass, rock, and slag wools grouped under the term mineral wools (MWs), which do not include glass filaments or refractory ceramic fibers. MWs are widely used for thermal and acoustic insulation in residential and commercial construction. Because of their similarity in shape with asbestos, they have been suspected of causing cancer of the respiratory system.
In 2002, the International Agency for Research on Cancer categorized MWs in Group 3 (not classifiable as to their carcinogenicity to humans) on the basis of limited evidence in experimental animals and inadequate evidence in humans.2 The monograph concluded that the risks for workers using MWs (as opposed to production workers) who may have experienced higher, but perhaps more intermittent, exposure to MWs are of some concern. However, the data available to evaluate cancer risks because of exposure to MWs in these populations are limited.
Since then, several population-based case–control studies have investigated the carcinogenic role of MWs in lung cancer, but the results remain unclear.3–6 The most recent meta-analysis of risks of lung cancer associated with exposure to MWs found an elevated risk of lung cancer (meta Relative Risk = 1.2; 95% confidence interval [CI]: 1.1 to 1.3).7 Nevertheless, some methodological pitfalls such as the lack of a dose–response relation, the likelihood of detection bias, and the possibility of residual confounding by smoking and asbestos exposure should be resolved before concluding that there is a true association between MWs exposure and lung cancer risk.
The Investigation on CAncers of the Respiratory tract and Environment (ICARE) study is a large, multicenter, population-based, case–control study conducted in France to examine the occupational risk factors of lung cancer. Using the ICARE's data, our aim was to investigate lung cancer risk associated with MWs exposure. The analysis will attempt to carefully take into account smoking and the main occupational exposures that are known to be associated with lung cancer and are widely present among workers exposed to MWs, namely asbestos and crystalline silica.
The ICARE study is a large, multicenter, population-based, case–control study conducted in France from 2001 through 2007 that has been previously described in detail.8 Briefly, the study was conducted in 10 French departments (geographic and administrative areas) with a general cancer registry. All cases of lung and upper aerodigestive tract cancers, aged 18 to 75 years, identified during the study period in each registry were eligible for the study. This analysis focused on lung cancer cases and the controls.
The cases were all incident primary lung cancers (codes C33 and C34, according to the International Classification of Diseases for Oncology, third edition, regardless of histological type) that were diagnosed in each department and histologically confirmed. Of the 4865 eligible cases identified, 486 could not be located, 781 died before any contact could be made, and 238 could not be contacted because of their health status. Accordingly, 3360 patients were asked to participate, and 434 refused.
Population controls with no history of previous respiratory cancer were randomly selected in the same departments as the cases through incidence-density sampling. The controls were frequency-matched to the cases by gender, age (using four age groups: younger than 40, 40 to 54, 55 to 64, and 65 years and older), and department. Additional stratification was used to achieve a distribution by socioeconomic status among the controls comparable to that of the general population in each department. Of the 4673 eligible controls, we managed to contact 4411, and 3555 agreed to participate. The study included 6481 participants: 2926 cases and 3555 controls. Men accounted for 78% of the study population (5056 men: 2276 cases and 2780 controls).
Trained interviewers used standardized questionnaires in face-to-face interviews. Information was collected about demographic characteristics, residential history, education, lifelong cigarette smoking, alcohol drinking, and lifetime occupational history covering all jobs held for at least 1 month. Trained coders blinded to case or control status coded occupations according to the International Standard Classification of Occupations of the International Labour Organization, 1968 revision,9 and branches of industry according to the French Nomenclature of Activities (Nomenclature d'activités Françaises) of the National Institute for Statistics and Economic Studies, 2000 edition.10
Each job was described by using a general questionnaire, including questions about the company, the subject's main and subsidiary tasks, exposures of interest, and work environment. In addition, for 20 job titles or tasks of interest, we also had supplementary job-specific questionnaires. These specific questionnaires consisted of a list of questions regarding the main tasks performed for this job by the worker himself or neighboring workers.
When the subjects were too tired to answer the complete questionnaire, interviewers used a summary version of the questionnaire that included mainly smoking data and occupational history but not the description of each job period. This short version was used for 5% of the men and 3% of the women.
Task-Exposure Matrices for MWs and asbestos
The ICARE's questionnaires were designed with multiple closed questions allowing the identification of exposing tasks or exposure circumstances. On the basis of the general questionnaire and on 11 of the 20 job-specific questionnaires (namely, work on building sites or civil engineering, plumbers and pipefitters, welding/brazing/cutting metal pieces, vehicle maintenance, chemical industry, rubber and plastic industry, glass industry, mining and quarrying, foundry, steel industry/blast furnace/coking plant/steel factory/rolling mill, manufacture of materials for building and civil engineering), three trained hygienists (F.L., O.G., S.D.) constructed task-exposure matrices (TEMs) specific for MWs and asbestos. Those TEMs assigned to each question of interest, according to the period of time and the different possible responses:
1. A probability of exposure, expressing the hygienists' certainty in the assessment, on a three-point scale (possible, probable, and definite), and
2. An intensity of exposure noted on a three-point scale (0.001 to 0.1, 0.1 to 1, 1 or more fibers/cm3) for MWs and on a four-point scale (0.001 to 0.1, 0.1 to 1, 1 to 10, 10 or more fibers/cm3) for asbestos.
The probability of exposure of a job was defined as the maximum of probability among all tasks described in this job. The intensity assigned to a job was defined as the maximum of intensity among all tasks whose probability was equal to the maximum of probability.
Because we could not be sure that all subjects answered all relevant job-specific questionnaires, we improved the specificity of the definition of nonexposure by using two job-exposure matrices (JEMs) specific for each substance.11 Nonexposed jobs were thus defined as not exposed according to the TEM and not exposed according to the JEM. Jobs that were not exposed by the TEM but potentially exposed by the JEM were left as missing data.
JEM for Assessment of Silica Exposure
Crystalline silica exposure was assessed by using a silica-specific JEM.11 For each combination of International Standard Classification of Occupations and French Nomenclature of Activities codes, three parameters of exposure were assigned: a probability of exposure (less than 1, 1 to 5, 6 to 10, 11 to 20; up to 91% to 100% of exposed workers in this combination), an intensity of exposure (0.02 or less, 0.02 to 0.1, 0.1 to 0.5, 0.5 to 1, more than 1 mg/m3), and a frequency of exposure (less than 1, 1 to 5, 6 to 10, 11 to 20, up to 81% to 90% of working time).
The indices were provided for different calendar periods between 1947 and 2007 to account for the change in exposure over time. Because the first job period in our data was 1937, exposure information for the year 1947 was also used for the periods before 1947.
Individual Assessment of Exposure
For each subject and each substance, we have thus assigned to a job i: a probability of exposure Pi and an intensity of exposure Ii. A frequency of exposure Fi was also assigned for silica exposure. Each subject's exposure to each substance was then summarized by the following exposure scores: “ever” exposed versus never exposed (subjects having at least one job period with a probability of exposure different from zero compared with subjects never exposed to the substance), maximum probability of exposure and maximum intensity of exposure among all jobs, and Cumulative Exposure Index (CEI), which was calculated as follows:
Equation (Uncited)Image Tools
where Di is the duration of a job period and using weights for Pi, Ii, and Fi. For asbestos and MWs, Pi was weighted as follows: 0.1 for possible, 0.5 for probable, and 1 for definite (according to the hygienists' judgement). For Ii and Fi, weights corresponded to the center of the class. The duration of exposure was calculated by summing the working periods with an exposure to the substance.
Given the small proportion of women exposed to MWs (14 women, 1.1%), the study population was restricted to men. We also restricted our population to men with a complete questionnaire who described at least one job period (4783 men; 2063 cases and 2720 controls) and for which the three exposures were assessable (3262 men; 1350 cases and 1912 controls).
Lifelong cigarette smoking was assessed with the Comprehensive Smoking Index (CSI),12 which aggregates measures of total duration of smoking, time since cessation, and the average number of cigarettes smoked per day. In our data, the CSI varied linearly with lung cancer risk and was used as a continuous variable for adjustment. The CSI of never smokers is null.
The respective CEIs of each agent were transformed into qualitative variables according to the quartile or quintiles of the exposure distribution among the controls.
We used unconditional logistic regression models to investigate the association between occupational exposure to each substance and the risk of lung cancer, using subjects who were never exposed to the specific substance studied as the reference. We estimated odds ratios (ORs) and corresponding 95% CIs by using models adjusted for age at interview (five quintiles), departments, lifelong cigarette smoking (CSI), the number of jobs held (1, 2, 3, 4, 5 or more), and the CEI of the two other substances. Analyses were repeated with different hypothetical lag times, that is, when the last 10, 20, 30, or 40 years of employment before interview were considered unexposed. Polytomous logistic regression was used to assess the risk of lung cancer associated with MWs exposure for the main histological subtypes (adenocarcinoma, squamous cell carcinoma, and small cell carcinoma).
The AFs were estimated by using Miettinen formula, allowing adjustment for confounders: AF = PEC × (OR − 1)/OR, where OR was the adjusted and PEC was the proportion of “ever” exposed cases.13 The confidence limits of the AF were calculated by using the method described by Greenland14 that accounts for the variability in the exposure prevalence estimates and the risk estimates.
Because the “ever exposed” definition strictly means having held a least one job with a probability of exposure different from zero, which is clearly a broad definition of exposure that mixes subjects with low and high probabilities of exposure, it did not precisely reflect the lifelong exposure prevalence in the French population. This exposure prevalence was estimated by multiplying the number of exposed subjects in each class of maximum probability of exposure by a weight assigned to that class: 0.1 for possible, 0.5 for probable, and 1 for definite (according to the hygienists' judgement). Nonexposed subjects were then recalculated accordingly. All P values were two-sided. The analyses were performed with STATA® software version 10.0 (Stata Corp, TX).
Table 1 summarizes the main characteristics of the 3262 men (1350 cases and 1912 controls) included in the analyses. Cases had a mean age of 60 years compared with 57.5 years for controls and had a lower educational level than controls. Only 2.4% of cases had never smoked compared with 30% of the controls. As expected, we observed a clear increase in the risk of lung cancer with the cumulative smoking level assessed by the CSI. Squamous cell carcinomas and adenocarcinomas each accounted for approximately 35% of cases. These 3262 men described a total of 14,287 job periods. The mean number of jobs held was similar among cases (4.3) and controls (4.4), with a mean duration of roughly 35 years of employment.
Risk of Lung Cancer Associated With Exposure to Asbestos and Silica
The lifelong exposure prevalence among controls was estimated at 23.2% for asbestos and 13.1% for silica. The ORs of lung cancer associated with exposure to asbestos and silica are shown in Table 2. Having had at least one job with a probability of exposure to asbestos different from zero (“ever”) was associated with a significantly increased risk of lung cancer even when adjusted for the two other substances (OR = 1.46; 95% CI: 1.17 to 1.83). The corresponding AF was 24.0% (95% CI: 10.8 to 35.3). At a given probability level, the ORs increased slightly among those exposed to asbestos for more than 15 years compared with those exposed for less than 15 years. We observed a dose–response relation between the CEI levels of asbestos and lung cancer risk. The ORs were slightly decreased when adjusted for silica exposure. Conversely, adjustment for MWs exposure did not modify the associations except for the highest class of CEI.
Similar results were found for silica exposure with an OR of 1.4 for “ever” exposed and a corresponding AF of 8.3% (95% CI: 4.3 to 12.2). We also found a dose–response relationship with duration of exposure and CEI levels.
Risk of Lung Cancer Associated With Exposure to MWs
The prevalence of lifelong MWs exposure was estimated at 13.4% among controls. Crude associations showed significantly increasing lung cancer risk with increasing probability, intensity, and duration of exposure to MWs (Table 3). A dose–response relation by using the CEI was also found.
Adjustment for coexposure to asbestos and silica decreased all the tested associations, which became not significant. Nevertheless, we showed ORs around 1.4 for the highest level of exposure to MWs for all of the tested variables. Although not significant, the ORs adjusted for asbestos and silica increased with intensity at a given probability and duration level (and with duration at a given probability and intensity level) up to an OR of 2.1 (95% CI: 0.8 to 5.6) for subjects with definite exposure for more than 15 years and with a maximum of intensity more than 1 fibers/cm3.
When lag times were applied, associations adjusted for asbestos and silica were not significant and close to 1 for CEI tertiles with 10 and 20 years of latency (Table 4). With a lag time of 30 years, an OR of 1.5 borderline of significance was found for the highest tertile of the CEI that increased up to 1.9 (95% CI: 1.2 to 3.2) for 40 years of latency.
Lung cancer risk associated with exposure to MWs stratified by level of asbestos exposure is shown in Table 5. We observed elevated ORs associated with exposure to MWs (increasing with the level of cumulative exposure to MWs) only when asbestos exposure is less than quintile 4.
Risk of Lung Cancer by Main Histological Types
Analysis by histological subtypes did not provide evidence of a specific relation between any of the three substances and a particular histology (see Table 1 from the Supplementary Material).
Joint Effects of Exposure to MWs, Silica, and Asbestos on Lung Cancer Risk
Only one subject had at least one job with a probability of exposure to MWs different from zero and was never exposed to asbestos and silica, which did not allow the calculation of an OR. The OR for joint exposure to the three substances was around 3 (Table 6).
Most Frequent Occupations and Industries Entailing Joint Exposures to MWs, Silica, and Asbestos
Table 7 shows the occupations or industries representing more than 2% of those with potential exposure to MWs, asbestos, and silica jointly. Bricklayers, carpenters, and other construction crafts represent more than 40% of the exposed occupations. Consistently, construction sector represents the majority (76%) of the exposed industries.
The population-based design of the ICARE study allowed us to reach MWs users. Nevertheless, we were not able to distinguish rock wool, slag wool, and glass wools. After careful adjustment for smoking and coexposure to asbestos and silica, our results showed mostly not significant associations between MWs exposure and lung cancer. However, a significant increased risk of lung cancer for men with high levels of exposure to MWs, using a lag time of 40 years, was observed. Our findings also provide robust evidence that past occupational exposure to asbestos and silica contributes substantially to the current lung cancer burden in men with AFs of 24% and 8%.
These results should be interpreted within the context of the ICARE study. Collaboration with the French network of cancer registries allowed us to recruit lung cancer cases in almost all of the different health care establishments in the departments covered by the registries. The study used a single control group, randomly sampled from the population, for both types of cancer (lung and upper aerodigestive tract). This design explains the statistically different age distribution between cases and controls. Nevertheless, the large number of subjects in each age group allowed satisfactory adjustment. The participation rate was satisfactory and comparable for cases and controls.
To minimize recall bias, the study was presented as an investigation of environment and health not specifically focused on occupational exposures. We can thus expect similar reports between cases and controls, exemplified by a similar average number of jobs reported. Moreover, trained interviewers carefully collected detailed information during a face-to-face interview with a standardized questionnaire. Although self-reported job history is considered fairly reliable, we cannot completely exclude the possibility of recall bias, but we believe the effect would be small and nondifferential.
Adjustment for socioeconomic status in occupational cancer studies is controversial. Indeed, such an adjustment may allow to control for differential participation between cases and controls or for unmeasured confounders but may also lead to underestimation of the occupational risks.15,16 We repeated our analyses after adjusting for educational level (elementary school or less, middle school, high school or more) as a surrogate for socioeconomic status, and this did not change any of the tested associations between lung cancer and MWs exposure. The associations between lung cancer and asbestos or silica exposure were still found, although the ORs were slightly decreased.
When adjusted for cigarette smoking, asbestos, and silica exposure, ORs of lung cancer associated with MWs exposure ranged from 0.8 to 2.1, mostly not significant. Interestingly the OR went up to approximately 1.4 for subjects exposed to the highest level of MWs for all of the tested variables. Nevertheless, no clear dose–response relation was found, although the ORs increased both with intensity and duration. Moreover, we showed an elevated OR of 2.1 (95% CI: 0.8 to 5.6) at a high-exposure level (definite MWs exposure for more than 15 years, with an intensity more than 1 fiber/cm3). When different lag times were applied, we did not find any association between MWs exposure and lung cancer with latencies of 10 and 20 years, whereas we observed significant or borderline associations when using latencies more than 30 years. Indeed, we observed ORs of 1.5 (95% CI: 0.95 to 2.3) and 1.9 (95% CI: 1.2 to 3.2) for the highest tertile of exposure to MWs when a lag time of 30 and 40 years, respectively, were considered. We observed elevated OR associated with exposure to MWs (increasing with the level of cumulative exposure to MWs) only when asbestos exposure was low. One hypothesis to explain such result might be that MWs contribution is undetectable among subjects who have been highly exposed to asbestos. We did not see clear differences between the three main histological types.
Since the International Agency for Research on Cancer evaluation in 2002,2 several population-based case–control studies have been published. Among them, two did not find any relation between MWs and lung cancer4,6 and two found not significant associations.3,5 It is important to note that Pintos et al5 was able to isolate a group of workers who were exposed to MWs and not to asbestos (48 cases and 40 controls), and they found a corresponding OR of 1.5 (95% CI: 0.9 to 2.4), which is close to our estimate in the highest-exposure category after adjustment for asbestos and silica. Besides, our finding of an association only with latencies of more than 30 years is completely coherent with the carcinogenic mechanisms known for other fibers like asbestos for which a long latency (more than 30 years) is known to be required before mesothelioma development.17
Exposure misclassifications inevitably occurred when attempting to retrospectively estimate a subject's exposure to a specific substance. Nevertheless, applying a JEM or a TEM, which links job titles or questions in a systematic way, is unlikely to result in differential misclassification. Moreover, the occupational coders were blind as to the case–control status. Still, nondifferential misclassification could result in an average bias toward the null.18 Nevertheless, we showed a dose–response relationship between asbestos exposure and lung cancer risk. This is consistent with the fact that asbestos has long been recognized as a lung carcinogen.17 Moreover, the exposure prevalence found among controls (23%) is similar to that found by the French Institute for Public Health Surveillance (Institut de Veille Sanitaire) for a French sample of 10,000 subjects representative of the French population in 2007 (26.9%).19 Our AF (24%) for asbestos is a bit higher than the range found in other European countries (10% to 20%)20 or in Italy (18%)21 and is lower than the one found in a recent French study (31%) by using a similar methodology.6 Our evaluation of asbestos exposure, therefore, seems reliable and, by extension, provides confidence in our methodology of exposure assessment by TEM.
Because of our strict definition of nonexposure, we had a high number of subjects with missing data for exposure to asbestos and MWs. Although the analyses were performed on a subset of men for which the three exposures were assessable, the distribution of subjects according to the characteristics described in Table 1 was similar to the initial population of 4783 men. In addition, we repeated the analyses with a definition of nonexposure to asbestos and MW based only on the TEM. Results remained unchanged, although the magnitude of the associations was lowered for asbestos exposure.
When the assessment is based on job titles, distinguishing between exposure to asbestos and that to MWs is problematic because asbestos has progressively been substituted by MWs in many industries, although MWs were already in use since the 1950s. Consequently, performances of JEMs are generally limited by their inability to account for variability in exposures within jobs. Although expert assessment is usually considered the gold standard for determining retrospective exposure, we could not consider it for the ICARE study because of the large number of subjects included and jobs described. A TEM was thus constructed by three trained hygienists as a surrogate for case-by-case expertise. Because it assigns exposure in a standardized and reproducible way, drift in judgment during the expertise process cannot occur, contrary to expert assessment.22
Nevertheless, we were not able to identify enough workers who were exposed to MWs and never to asbestos. Indeed, because of the tremendous use of asbestos in the past in a wide variety of sectors, its exposure remains elevated among our study population. Our subjects were aged 60 years on average, and almost all began their working life before the ban on asbestos in France in 1997.
Considering this, we cannot completely exclude the possibility that the increased ORs for the highest levels of exposure to MWs are due to residual confounding by asbestos or silica exposures. However, a special effort was made to adjust as precisely as possible for those exposures. Different methods for taking asbestos and silica exposure into account were tested such as CEI or ln(CEI + 1) as a continuous variable, but neither of them varied linearly with lung cancer probability. Adjustment using these continuous variables did not modify the associations between lung cancer risk and MWs exposure, suggesting that these confounders were not fully adjusted for. We thus adjusted for asbestos exposure with CEI transformed into qualitative variables according to the exposure distribution among the controls. We chose the categorization that gave the best goodness of fit (the lowest Akaike Information Criterion).
Specific attention should also be paid to the results for silica exposure. The carcinogenicity of crystalline silica has been widely discussed, even after it was classified as a human carcinogen by International Agency for Research on Cancer in 1997.23,24 Most of the debate concerns the failure to observe a dose–response relationship for crystalline silica, which has been shown in relatively few studies and mostly in studies published recently.25–27 All of these studies reported significant trends and ORs between 1.5 and 2 for their highest-exposure groups. This study also showed a significantly increased risk of lung cancer associated with exposure to crystalline silica after accurate control for smoking and asbestos. The prevalence of exposure estimated among our controls (13%) is also in the range of percentages of exposed controls found in these studies (6% to 20%). We estimated an AF of 8% for silica, a bit higher but close to the 3% to 5% recently reported,21,25,26,28 although estimations stretch to 17%.6 Our findings emphasize the high public health impact of silica exposure, which is currently estimated to be the most common occupational exposure worldwide, involving tens of millions of workers, especially in the construction sector.29
Interestingly, we showed an OR of almost 3 for workers who were jointly exposed to the three substances, although we used the broad “ever” exposure definition. Those who were exposed to the three substances were also those who had the highest levels of exposure to each of the three substances. In our population, construction was the main sector entailing exposure to those substances. Construction workers are also known to be exposed to other known or potential lung carcinogens, such as diesel fumes, cement dust, and wood dust.29 Considering the high number of construction workers in France (1.4 million workers in 2010, 6% of wage earners, according to the National Institute for Statistics and Economic Studies) and around the world (more than 11 million30), potential exposures to carcinogens among these workers seems to be an important public health concern that should be investigated further.
This study is one of the most detailed studies about MWs and lung cancer. We found a consistent set of results suggesting that a potential carcinogenic effect of MWs cannot be excluded. Given the high number of potentially exposed workers, it will be necessary to replicate these analyses in a future further removed from the asbestos ban.
Our results also suggest that a focus on the work environment of construction workers may provide a further opportunity for lung cancer prevention.
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