Evidence map›Paper›PMID 34526026›Full record

ArticleEnvironmental health : a global access science source2021

Environmental asbestos exposure and clustering of malignant mesothelioma in community: a spatial analysis in a population-based case-control study.

C Airoldi, C Magnani, F Lazzarato, D Mirabelli, S Tunesi, D Ferrante

Open access · goldAbstract read
In one paragraph

Article in Environmental health : a global access science source, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.2field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 19 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Current causes of mesothelioma: how has the asbestos ban changed the perspective?Biomedical papers of the Medical Faculty of the University Palacky, Olomouc, Czechoslovakia · 2023
    Review
  6. Article
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

C AiroldiMedical Statistics, Department of Translational Medicine, Università Degli Studi del Piemonte Orientale, Via Solaroli 17, 28100, Novara, NO, Italy. chiara.airoldi@uniupo.it.ORCID 0000-0002-9114-5816
C MagnaniMedical Statistics, Department of Translational Medicine, Università Degli Studi del Piemonte Orientale, Via Solaroli 17, 28100, Novara, NO, Italy.
F LazzaratoUnit of Cancer Epidemiology, "Città Della Salute E Della Scienza" Hospital, Turin, Italy.
D MirabelliCancer Epidemiology Unit, CPO-Piemonte, Novara, Italy.
S TunesiMedical Statistics, Department of Translational Medicine, Università Degli Studi del Piemonte Orientale, Via Solaroli 17, 28100, Novara, NO, Italy.
D FerranteMedical Statistics, Department of Translational Medicine, Università Degli Studi del Piemonte Orientale, Via Solaroli 17, 28100, Novara, NO, Italy.
Università degli Studi del Piemonte Orientale “Amedeo Avogadro” · ITAzienda Ospedaliera Citta' della Salute e della Scienza di Torino · ITPiedmont Reference Center for Epidemiology and Cancer Prevention · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNeighborhood exposure to asbestos increases the risk of developing malignant mesothelioma (MM) in residents who live near asbestos mines and asbestos product plants. The area of Casale Monferrato (Northwest Italy) was impacted by several sources of asbestos environmental pollution, due to the presence of the largest Italian asbestos cement (AC) plant. In the present study, we examined the spatial variation of MM risk in an area with high levels of asbestos pollution and secondly, and we explored the pattern of clustering.

methodsA population-based case-control study conducted between 2001 and 2006 included 200 cases and 348 controls. Demographic and occupational data along with residential information were recorded. Bivariate Kernel density estimation was used to map spatial variation in disease risk while an adjusted logistic model was applied to estimate the impact of residential distance from the AC plant. Kulldorf test and Cuzick Edward test were then performed.

resultsOne hundred ninety-six cases and 322 controls were included in the analyses. The contour plot of the cases to controls ratio showed a well-defined peak of MM incidence near the AC factory, and the risk decreased monotonically in all directions when large bandwidths were used. However, considering narrower smoothing parameters, several peaks of increased risk were reported. A constant trend of decreasing OR with increasing distance was observed, with estimates of 10.9 (95% CI 5.32-22.38) and 10.48 (95%CI 4.54-24.2) for 0-5 km and 5-10 km, respectively (reference > 15 km). Finally, a significant (p < 0.0001) excess of cases near the pollution source was identified and cases are spatially clustered relative to the controls until 13 nearest neighbors.

conclusionsIn this study, we found an increasing pattern of mesothelioma risk in the area around a big AC factory and we detected secondary clusters of cases due to local exposure points, possibly associated to the use of asbestos materials.

Indexed as

AgedAsbestosCase-Control StudiesCluster AnalysisEnvironmental ExposureFemaleHumansItalyMaleMesothelioma, MalignantMiddle AgedPleural NeoplasmsSpatial AnalysisAsbestosAsbestosMesotheliomaSpatial analysis

Identifiers

PMID34526026
PMCPMC8444609
OpenAlexW3201346595

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.