You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Epidemiological patterns of asbestos exposure and spatial clusters of incident cases of malignant mesothelioma from the Italian national registry
|
|---|---|
| Published in |
BMC Cancer, April 2015
|
| DOI | 10.1186/s12885-015-1301-2 |
| Pubmed ID | |
| Authors |
Marisa Corfiati, Alberto Scarselli, Alessandra Binazzi, Davide Di Marzio, Marina Verardo, Dario Mirabelli, Valerio Gennaro, Carolina Mensi, Gert Schallemberg, Enzo Merler, Corrado Negro, Antonio Romanelli, Elisabetta Chellini, Stefano Silvestri, Mario Cocchioni, Cristiana Pascucci, Fabrizio Stracci, Elisa Romeo, Luana Trafficante, Italo Angelillo, Simona Menegozzo, Marina Musti, Domenica Cavone, Gabriella Cauzillo, Federico Tallarigo, Rosario Tumino, Massimo Melis, Sergio Iavicoli, Alessandro Marinaccio, ReNaM Working Group |
| Abstract |
Previous ecological spatial studies of malignant mesothelioma cases, mostly based on mortality data, lack reliable data on individual exposure to asbestos, thus failing to assess the contribution of different occupational and environmental sources in the determination of risk excess in specific areas. This study aims to identify territorial clusters of malignant mesothelioma through a Bayesian spatial analysis and to characterize them by the integrated use of asbestos exposure information retrieved from the Italian national mesothelioma registry (ReNaM). In the period 1993 to 2008, 15,322 incident cases of all-site malignant mesothelioma were recorded and 11,852 occupational, residential and familial histories were obtained by individual interviews. Observed cases were assigned to the municipality of residence at the time of diagnosis and compared to those expected based on the age-specific rates of the respective geographical area. A spatial cluster analysis was performed for each area applying a Bayesian hierarchical model. Information about modalities and economic sectors of asbestos exposure was analyzed for each cluster. Thirty-two clusters of malignant mesothelioma were identified and characterized using the exposure data. Asbestos cement manufacturing industries and shipbuilding and repair facilities represented the main sources of asbestos exposure, but a major contribution to asbestos exposure was also provided by sectors with no direct use of asbestos, such as non-asbestos textile industries, metal engineering and construction. A high proportion of cases with environmental exposure was found in clusters where asbestos cement plants were located or a natural source of asbestos (or asbestos-like) fibers was identifiable. Differences in type and sources of exposure can also explain the varying percentage of cases occurring in women among clusters. Our study demonstrates shared exposure patterns in territorial clusters of malignant mesothelioma due to single or multiple industrial sources, with major implications for public health policies, health surveillance, compensation procedures and site remediation programs. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| New Zealand | 1 | 25% |
| United Kingdom | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Practitioners (doctors, other healthcare professionals) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | <1% |
| Denmark | 1 | <1% |
| France | 1 | <1% |
| Brazil | 1 | <1% |
| Unknown | 100 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 21 | 20% |
| Student > Master | 12 | 12% |
| Student > Bachelor | 11 | 11% |
| Other | 9 | 9% |
| Student > Ph. D. Student | 7 | 7% |
| Other | 17 | 16% |
| Unknown | 27 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 37 | 36% |
| Environmental Science | 7 | 7% |
| Engineering | 7 | 7% |
| Nursing and Health Professions | 5 | 5% |
| Social Sciences | 3 | 3% |
| Other | 16 | 15% |
| Unknown | 29 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 June 2015.
All research outputs
#2,592,538
of 24,615,949 outputs
Outputs from BMC Cancer
#483
of 8,732 outputs
Outputs of similar age
#32,901
of 268,728 outputs
Outputs of similar age from BMC Cancer
#20
of 264 outputs
Altmetric has tracked 24,615,949 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,732 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 268,728 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 264 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.