Paolo Girardi1, Enzo Merler1, Daniela Ferrante2,3, Stefano Silvestri3,4, Elisabetta Chellini5, Alessia Angelini5, Ferdinando Luberto6, Ugo Fedeli1, Enrico Oddone7, Massimo Vicentini6, Francesco Barone-Adesi3,8, Tiziana Cena2,3, Dario Mirabelli9, Lucia Mangone6, Francesca Roncaglia6, Orietta Sala10, Simona Menegozzo11, Roberta Pirastu12, Danila Azzolina2,3, Sara Tunesi2,3,9, Lucia Miligi5, Patrizia Perticaroli13, Aldo Pettinari13, Francesco Cuccaro14, Anna Maria Nannavecchia14, Lucia Bisceglia15, Alessandro Marinaccio16, Venere Leda Mara Pavone17, Corrado Magnani2,3. 1. Mesothelioma Register of the Veneto Region, Regional Epidemiological System, Azienda Zero, Padua, Italy. 2. Unit of Medical Statistics and Cancer Epidemiology, Department of Translational Medicine, University of Eastern Piedmont, Novara, Italy. 3. CPO-Piedmont, Novara, Italy. 4. Occupational Hygienists, Unit of Medical Statistics and Epidemiology, Department of Translational Medicine, University of Eastern Piedmont, Novara, Italy. 5. Occupational & Environmental Epidemiology Unit-Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy. 6. Epidemiology Service, Azienda Unità Sanitaria Locale-IRCCS, Montecchio Emilia, Reggio Emilia, Italy. 7. Department of Public Health, Experimental and Forensic Medicine, University of Pavia, Pavia, Italy. 8. Department of 'Scienze del Farmaco', University of Eastern Piedmont, Novara, Italy. 9. Unit of Cancer Epidemiology, CPO Piedmont and University of Turin, Turin, Italy. 10. Occupational Hygienist, Formerly: Regional Agency for Prevention, Environment and Energy Emilia-Romagna, Provincial Office of Reggio Emilia, Reggio Emilia, Italy. 11. National Cancer Institute IRCCS Fondazione Pascale, Naples, Italy. 12. Department of Biology and Biotechnologies 'Charles Darwin', Sapienza University, Rome, Italy. 13. Prevention Department, ASUR Marche, Senigallia, Ancona, Italy. 14. Unit of Epidemiology and Statistics-Local Health Unit of Barletta-Andria-Trani, Barletta, Italy. 15. Regional Agency of Health, ARES Puglia, Bari, Italy. 16. Italian Workers' Compensation Authority (INAIL), Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, Unit of Occupational and Environmental Epidemiology, Italian Mesothelioma Register, Rome, Italy. 17. Department of Public Health, Prevention and Security Area Work Environments, Local Health Authority, San Lazzaro di Savena, Italy.
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.
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 asbestosismortality 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.
Authors: Eduardo Algranti; Vilma S Santana; Felipe Campos; Leonardo Salvi; Cézar A Saito; Franciana Cavalcante; Heleno R Correa-Filho Journal: Saf Health Work Date: 2022-05-06