2020European Journal of Public HealthOpen access

Occupational asbestos exposure after the ban: a job exposure matrix developed in Italy

Alberto Scarselli, Alessandro Marinaccio, Marisa Corfiati, Davide Di Marzio, Sergio Iavicoli

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Abstract

BACKGROUND: Asbestos is a well-known carcinogen for humans. The aim of this study is to develop a tool to estimate occupational asbestos exposure in Italy after the ban using information collected in a national dataset. METHODS: Data were collected from firm registries of workers exposed to asbestos in the period 1996-2016. Descriptive statistics (arithmetic mean, standard deviation, geometric mean and geometric standard deviation) were calculated for the main exposure-related variables (activity sector, occupational group and exposure period). An estimate of workers potentially exposed to asbestos was also performed. RESULTS: A total of 19 704 airborne measurements of asbestos exposure was selected from the national database of occupational exposures in the sectors of asbestos abatement. Overall, a geometric mean of 7.93 f l-1 was found, and chrysotile was the asbestos type that had more exposures (41%). A total of 46 422 workers was estimated to be potentially at asbestos exposure risk. Exposure data were summarized by calendar period, activity sector and occupational group. CONCLUSIONS: The construction of a job exposure matrix for different occupation/industry combinations may allow the assessment of occupational exposure to asbestos in several removal and disposal activities, and the estimate of the risks associated with asbestos-related diseases in epidemiological studies.

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BACKGROUND: Asbestos is a well-known carcinogen for humans. The aim of this study is to develop a tool to estimate occupational asbestos exposure in Italy after the ban using information collected in a national dataset. METHODS: Data were collected from firm registries of workers exposed to asbestos in the period 1996-2016. Descriptive statistics (arithmetic mean, standard deviation, geometric mean and geometric standard deviation) were calculated for the main exposure-related variables (activity sector, occupational group and exposure period). An estimate of workers potentially exposed to asbestos was also performed. RESULTS: A total of 19 704 airborne measurements of asbestos exposure was selected from the national database of occupational exposures in the sectors of asbestos abatement. Overall, a geometric mean of 7.93 f l-1 was found, and chrysotile was the asbestos type that had more exposures (41%). A total of 46 422 workers was estimated to be potentially at asbestos exposure risk. Exposure data were summarized by calendar period, activity sector and occupational group. CONCLUSIONS: The construction of a job exposure matrix for different occupation/industry combinations may allow the assessment of occupational exposure to asbestos in several removal and disposal activities, and the estimate of the risks associated with asbestos-related diseases in epidemiological studies.

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Available abstract

BACKGROUND: Asbestos is a well-known carcinogen for humans. The aim of this study is to develop a tool to estimate occupational asbestos exposure in Italy after the ban using information collected in a national dataset. METHODS: Data were collected from firm registries of workers exposed to asbestos in the period 1996-2016. Descriptive statistics (arithmetic mean, standard deviation, geometric mean and geometric standard deviation) were calculated for the main exposure-related variables (activity sector, occupational group and exposure period). An estimate of workers potentially exposed to asbestos was also performed. RESULTS: A total of 19 704 airborne measurements of asbestos exposure was selected from the national database of occupational exposures in the sectors of asbestos abatement. Overall, a geometric mean of 7.93 f l-1 was found, and chrysotile was the asbestos type that had more exposures (41%). A total of 46 422 workers was estimated to be potentially at asbestos exposure risk. Exposure data were summarized by calendar period, activity sector and occupational group. CONCLUSIONS: The construction of a job exposure matrix for different occupation/industry combinations may allow the assessment of occupational exposure to asbestos in several removal and disposal activities, and the estimate of the risks associated with asbestos-related diseases in epidemiological studies.

Key concepts: Asbestos, Environmental health, Chrysotile, Occupational exposure, Job-exposure matrix, Exposure assessment, Geometric mean, Medicine

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