Suchergebnisse

Abstract
Asbestos fibre counting by phase-contrast microscope is subject to many sources of variation, including those dependent on the analyst. In this study, asbestos sample slides prepared with relocatable coverslips have been used for fibre counting among voluntary analysts to evaluate their proficiency. One slide of amosite and one of chrysotile were distributed to all the analysts, and three proficiency testing rounds were conducted for amosite and four for chrysotile. Each relocatable coverslip has a report in which are reported for each viewing field both the number of certified fibres (Verified Fibres) and a drawing representing the shape and position of the individual fibres. In the first round, the analysts were asked to report only the number of fibres counted in each of the predesignated fields of view. In the other rounds, subsequently developed, the analysts had to report the number and the position of the fibres for each field. The reported number of fibres and their position in each of the designed fields were evaluated against their respective verified fibres, to identify types of error. Discrepancies between reported fibres and verified fibres in each field of view have been used to evaluate the proficiency of the analysts. The discrepancies can be positive (D+) or negative (D−) depending on whether the analyst counts, for a specific field of view, more or less fibres compared to the verified fibres. The score is calculated using the following equation: Score = (1 − ∑D+ + ∑│D−│/VF) × 100. An analyst obtaining a score of ≥60, which corresponds to (∑D+ + ∑│D−│)/VF ≤ 0.40, is proficient. The number of laboratories that participating in this study varied from 13 to 17 depending on the rounds. For amosite fibre counts, the results were generally good compared to a proficiency score of 60. The major error made by analysts was the counting of fibres shorter than 5 µm, where this error was of 62% of extra fibres and accounted for 8% over-estimation of amosite fibres. For chrysotile, a score of ≥50 has been used to consider an analyst as proficient. The results of chrysotile fibres showed that in the first round all analysts counted less than fifty per cent of the verified fibres. In the second round 10 analysts out of 13 reached a score of ≥50, 8 of 16 in the third and 10 of 12 in the fourth. For chrysotile fibres, the error relating to the counting of fibres shorter than 5 µm was of 56% of extra fibres, but the error that most influenced the results was the number of oversight-missing fibres. This type of error accounted for 97% of the missing fibres and for the 29% under-estimation of the chrysotile fibres. For amosite fibre counting, results of this study show an improvement of the analyst's performance. For the chrysotile fibre count, although there is a significant improvement in the comparison between some rounds, this is not continuous over time.

Abstract

Objectives
This study was performed with the aim of investigating the temporal patterns and determinants associated with mortality from asbestosis among 21 cohorts of Asbestos-Cement (AC) workers who were heavily exposed to asbestos fibres.


Methods
Mortality for asbestosis was analysed for a cohort of 13 076 Italian AC workers (18.1% women). Individual cumulative asbestos exposure index was calculated by factory and period of work weighting by the different composition of asbestos used (crocidolite, amosite, and chrysotile). Two different approaches to analysis, based on Standardized Mortality Ratios (SMRs) and Age-Period-Cohort (APC) models were applied.


Results
Among the considered AC facilities, asbestos exposure was extremely high until the end of the 1970s and, due to the long latency, a peak of asbestosis mortality was observed after the 1990s. Mortality for asbestosis reached extremely high SMR values [SMR: males 508, 95% confidence interval (CI): 446–563; females 1027, 95% CI: 771–1336]. SMR increased steeply with the increasing values of cumulative asbestos exposure and with Time Since the First Exposure. APC analysis reported a clear age effect with a mortality peak at 75–80 years; the mortality for asbestosis increased in the last three quintiles of the cumulative exposure; calendar period did not have a significant temporal component while the cohort effect disappeared if we included in the model the cumulative exposure to asbestos.


Conclusions
Among heaviest exposed workers, mortality risk for asbestosis began to increase before 50 years of age. Mortality for asbestosis was mainly determined by cumulative exposure to asbestos.