| Literature DB >> 29269563 |
Alessandro Marinaccio1, Marisa Corfiati1, Alessandra Binazzi1, Davide Di Marzio1, Alberto Scarselli1, Pierpaolo Ferrante1, Michela Bonafede1, Marina Verardo2, Dario Mirabelli3, Valerio Gennaro4, Carolina Mensi5, Gert Schallemberg6, Guido Mazzoleni7, Enzo Merler8, Paolo Girardi8, Corrado Negro9, Flavia D'Agostin9, Antonio Romanelli10, Elisabetta Chellini11, Stefano Silvestri12, Cristiana Pascucci13, Roberto Calisti13, Fabrizio Stracci14, Elisa Romeo15, Valeria Ascoli16, Luana Trafficante17, Francesco Carrozza18, Italo Francesco Angelillo19, Domenica Cavone20, Gabriella Cauzillo21, Federico Tallarigo22, Rosario Tumino23, Massimo Melis24, Sergio Iavicoli1.
Abstract
INTRODUCTION: The epidemiology of gender differences for mesothelioma incidence has been rarely discussed in national case lists. In Italy an epidemiological surveillance system (ReNaM) is working by the means of a national register.Entities:
Keywords: asbestos; gender; mesothelioma
Mesh:
Substances:
Year: 2017 PMID: 29269563 PMCID: PMC5878657 DOI: 10.1136/oemed-2016-104119
Source DB: PubMed Journal: Occup Environ Med ISSN: 1351-0711 Impact factor: 4.402
Main characteristics of malignant mesothelioma cases (n=21,398) collected by the Italian national mesothelioma register (ReNaM) by cancer site and gender. Italy, incidence period: 1993–2012
| Pleural | Peritoneal | Pericardial | |||||||
| Females | Males | F/M | Females | Males | F/M | Females | Males | F/M | |
| Age classes | |||||||||
| | 100 | 213 | 0.47 | 39 | 52 | 0.75 | 1 | 6 | 0.17 |
| 45–64 | 1375 | 4281 | 0.32* | 203 | 284 | 0.71 | 6 | 10 | 0.60 |
| 65–84 | 3516 | 9182 | 0.38 | 314 | 467 | 0.67 | 8 | 19 | 0.42 |
| | 505 | 783 | 0.64* | 19 | 14 | 1.36 | 1 | – | – |
| Period of diagnosis | |||||||||
| 1993–1997 | 533 | 1511 | 0.35 | 66 | 93 | 0.71 | 3 | 5 | 0.60 |
| 1998–2002 | 1381 | 3610 | 0.38 | 144 | 189 | 0.76 | 6 | 13 | 0.46 |
| 2003–2007 | 1826 | 4712 | 0.39 | 192 | 271 | 0.71 | 5 | 7 | 0.71 |
| 2008–2012 | 1756 | 4626 | 0.38 | 173 | 264 | 0.66 | 2 | 10 | 0.20 |
| Diagnostic certainty | |||||||||
| MM certain | 4144 | 11 705 | 0.35* | 473 | 685 | 0.69 | 12 | 27 | 0.44 |
| MM probable | 660 | 1329 | 0.50* | 81 | 85 | 0.95* | 2 | 7 | 0.29 |
| MM possible | 692 | 1425 | 0.49* | 21 | 47 | 0.45 | 2 | 1 | 2.00 |
| Morphology | |||||||||
| Epithelioid | 3038 | 7733 | 0.39 | 301 | 478 | 0.63 | 5 | 12 | 0.42 |
| Fibrous | 313 | 1244 | 0.25* | 21 | 31 | 0.68 | 2 | 3 | 0.67 |
| Bifphasic | 513 | 1654 | 0.31* | 72 | 65 | 1.11* | 4 | 5 | 0.80 |
| MM NOS | 683 | 1805 | 0.38 | 141 | 154 | 0.92* | 3 | 11 | 0.27 |
| Not available | 949 | 2023 | 0.47* | 40 | 89 | 0.45* | 2 | 4 | 0.50 |
| Asbestos exposure† | |||||||||
| Occupational | 1321 | 9525 | 0.14* | 132 | 444 | 0.30* | 4 | 18 | 0.22 |
| Non-occupational | 1151 | 492 | 2.34* | 75 | 27 | 2.78* | 1 | – | – |
| Familial | 632 | 106 | 5.96* | 43 | 4 | 10.75* | – | – | – |
| Environmental | 368 | 285 | 1.29* | 24 | 16 | 1.50* | 1 | – | – |
| Leisure activities | 151 | 101 | 1.50* | 8 | 7 | 1.14 | – | – | |
| Unknown, not probable | 1497 | 1450 | 1.03* | 184 | 124 | 1.48* | 9 | 4 | 2.25* |
| Total | 3969 | 11 467 | 0.35 | 391 | 595 | 0.66 | 14 | 22 | 0.64 |
| Not available | 1527 | 2992 | 0.51 | 184 | 222 | 0.83 | 2 | 13 | 0.15 |
| Overall | 5496 | 14 459 | 0.38 | 575 | 817 | 0.70 | 16 | 35 | 0.46 |
*Gender ratio significantly different from the overall value (p<0.05).
†Asbestos exposure is available for 16 458 MM cases.
Economic sectors, jobs involved in asbestos exposure and gender ratio value (F/M) for malignant mesothelioma cases in women. Italy, 1993–2012, Italian national mesothelioma register. Only economic sectors with 20 exposures or more; only 5 (and equal) most frequent jobs
| Economic sector | Jobs (number of exposures) | Gender ratio (F/M) |
| Textile industry (no asbestos direct use) (528 exposures) | INDUSTRIAL WEAVER (90); MECHANICAL LOOM OPERATOR FOR CLOTHES AND BRAID MAKING (46); LABOURERS AND OTHER UNSKILLED INDUSTRIAL WORKERS (44); WINDING-MACHINE OPERATOR (40); AUTOMATIC WEAVING MACHINE OPERATOR (35) | 1.27* |
| Manufacture of wearing apparel (97) | TAILOR (46); DRESSMAKER TAILOR (8); TAILORS, HANDICRAFT CUTTERS, PATTERN-MAKERS AND HATTERS (6); LABOURERS AND OTHER UNSKILLED INDUSTRIAL WORKERS (6); UNDERGARMENT SEWER (5); PRESS OPERATOR (5); INDUSTRIAL GARMENT SEWING MACHINE OPERATOR (5) | 2.77* |
| Health and social work (94) | HAIRDRESSER (22); DRY CLEAN AND LAUNDRY PRESSER (12); HAND IRONER (10); PRESS OPERATOR (10); OPERA SINGER (3); CLOAKROOM ATTENDANT (3); HEALTHCARE AUXILIARY ASSISTANT (3) | 0.51* |
| Asbestos-cement industry (79) | ASBESTOS-CEMENT WORKER (49); CONCRETE MIXER MACHINE OPERATOR (5); CEMENT AND OTHER MINERAL PRODUCTS MACHINE OPERATOR (4); WAGES AND SALARIES CLERK (3); OFFICE CLERK (2); GRINDING, MILLING AND MIXING MACHINE OPERATOR (2); CEMENT PIPE FITTER (2) | 0.20 |
| Food and beverages industry (except sugar manufacture) (79) | LABOURERS AND OTHER UNSKILLED INDUSTRIAL WORKERS (8); OTHER HANDICRAFT AND INDUSTRIAL FOOD PROCESSING WORKERS (6); CHEESE RIPENER (INDUSTRIAL DIARY PRODUCTS MAKER) (3); STORE SALESPERSON (3); HANDICRAFT AND INDUSTRIAL FOOD PROCESSING WORKERS (3) FOOD INDUSTRY MACHINE-OPERATORS (3) | 0.34 |
| Manufacture of machinery and equipment (79) | LABOURERS AND OTHER UNSKILLED INDUSTRIAL WORKERS (14); HANDICRAFT AND INDUSTRIAL METAL ENGINEERING WORKERS (9); WELDER (3); ELECTRICAL AND ELECTRONIC EQUIPMENT ASSEMBLERS, REPAIRERS AND SERVICERS (EXCEPT PRODUCTION LINE WORKERS)(3); OTHER GENERAL OFFICE CLERICAL WORKERS (3) | 0.07 |
| Asbestos textile industry (72) | SPINNING MACHINE-OPERATOR (25); LABOURERS AND OTHER UNSKILLED INDUSTRIAL WORKERS (16); MECHANICAL LOOM OPERATOR FOR CLOTHES AND BRAID MAKING (7); INDUSTRIAL WEAVER (4); WEAVER OF SPECIAL TISSUES (4) | 3.08* |
| Agriculture and farming of animals (60) | FARMER (20); FARM HAND (12); FIELD CROP FARM WORKERS (7); FARMERS AND FARM WORKERS (4) | 0.27 |
| Wholesale and retail trade (58) | RAG COLLECTOR (8); SORTER (6); RETAILER (5); OTHER GENERAL OFFICE CLERICAL WORKERS (4); RAGMAN (4); SALESMAN AND SIMILAR JOBS (4); STORE SALESPERSON (4) | 0.17 |
| Manufacture of chemical and plastic products (54) | LABOURERS AND OTHER UNSKILLED INDUSTRIAL WORKERS (17); OTHER GENERAL OFFICE CLERICAL WORKERS (2); CHEMICAL PROCESSING PLANT WORKER (2); OFFICE CLERKS (2); PACKING MACHINE-OPERATOR (2); OTHER AUXILIARY PERSONNEL OF PRODUCTS PACKAGING, STORAGE AND DELIVERY (2); CHEMICAL, PETROLEUM REFINING AND CEMENT PRODUCTION PLANT OPERATOR (2); SPINNING AND SPOOLING MACHINE-OPERATOR (2); PHARMACEUTICAL- AND TOILETRY-PRODUCTS MACHINE OPERATOR (2); OTHER CHEMICAL PROCESSING PLANT OPERATOR (2) | 0.11 |
| Rubber industry (49) | LABOURERS AND OTHER UNSKILLED INDUSTRIAL WORKERS (14); RUBBER PRODUCTS MOULDER (5); OTHER RUBBER PRODUCTS PROCESSING OPERATOR (5); INDUSTRIAL QUALITY CONTROL TECHNICIAN (2); RUBBER MIXER (2); RUBBER ROLLING PRESS OPERATOR (2); INDUSTRIAL PLANT OPERATOR (2) | 0.36 |
| Other manufacturing industries (furniture, jewellery, musical instruments, sport goods, etc.) (43) | JEWELLERY AND PRECIOUS-METAL WORKER (10) OFFICE CLERK (3); WELDER (2); GOLD POLISHER (2) | 0.19 |
| Glass and ceramics production (42) | LABOURERS AND OTHER UNSKILLED INDUSTRIAL WORKERS (6); GLASS MAKERS, CUTTERS, GRINDERS AND FINISHERS (5); GLASS AND PORCELAIN DECORATIVE PAINTER (3); OTHER AUXILIARY PERSONNEL OF PRODUCTS PACKAGING, STORAGE AND DELIVERY (3); GLASS PRODUCTS SORTER (2); GLAZIER (2); POTTERS, FLASK BLOWERS, CUP-FORMERS AND GLASSWORKS WORKERS (2); CERAMIST (2) | 0.29 |
| Hotels, restaurants and bars (26) | COOK (4); DRY CLEAN AND LAUNDRY PRESSER (3); CANTEEN ASSISTANT (2); HOTEL CLEANER (2); HOTEL CLOAKROOM ATTENDANT AND PRESSER (2); HOTEL AND RESTAURANT COOK (2); PRESS OPERATOR (2) | 0.42 |
| Education (22) | PRIMARY SCHOOL TEACHER (4); TEACHER OF SPORTS, GYMNASTICS, PERSONAL HEALTH (MIDDLE SCHOOL) (3); SCHOOL PORTER AND SIMILARS (2); TEACHER OF NATURAL SCIENCES (2); HUMANITIES TEACHER (2). | 0.54* |
| Overall (of reported economic sectors) | 0.34 |
*Gender ratio significantly higher than the overall value (p<0.05)
Figure 1Crude incidence rates (*100 000 inhabitants) for malignant mesothelioma in women by municipalities of residence at diagnosis. Municipalities with significant number of cases and modalities of asbestos exposure in women. Italian national mesothelioma register (ReNaM), Italy, period of incidence 1993–2012. Labels are reported for municipalities with crude incidence rates>4 and at least 8 MM female cases with occupational or non-occupational (environmental, familial, leisure activities-related) exposure. Labels show the municipalities and the modalities of asbestos exposure: O(Ta) prevalently occupational exposure in asbestos textile sector; O(Tna) non-asbestos textile; O(AC) asbestos-cement plant; O(S) shipbuilding and repair; E environmental exposure; F familial exposure, due to cohabitation with exposed workers.
Number of MM cases, crude incidence rates (*100 000 inhabitants) for malignant mesothelioma in women, gender ratio (F/M) in the 13 Italian municipalities with the highest number of cases. Italy, Italian national mesothelioma register, period of incidence 1993–2012
| Municipality | Number of cases | Crude incidence rate in women | Gender ratio (F/M) |
| CASALE MONFERRATO | 255 | 71.5 | 0.8 |
| GENOVA | 227 | 4.0 | 0.2 |
| BRONI | 43 | 66.1 | 0.8 |
| COLLEGNO | 39 | 8.5 | 0.9 |
| STRADELLA | 33 | 44.6 | 1.6 |
| LA SPEZIA | 32 | 4.1 | 0.1 |
| GRUGLIASCO | 26 | 6.9 | 0.8 |
| MONFALCONE | 25 | 10.1 | 0.3 |
| RIVOLI | 24 | 4.9 | 0.9 |
| SARNICO | 14 | 35.2 | 1.4 |
| BIANCAVILLA | 13 | 7.5 | 0.9 |
| CIRIÈ | 13 | 7.3 | 1.2 |
| NOLE | 11 | 17.9 | 1.2 |
Figure 2Standardised mortality rates for malignant mesothelioma (both genders) and gender ratio (F/M). Based on ‘WHO mortality database’, year=2011; only countries with more than 20 cases.