Evidence map›Paper›PMID 22852770›Full record

ArticleBMC public health2012

Colorectal cancer mortality and industrial pollution in Spain.

Gonzalo López-Abente, Javier García-Pérez, Pablo Fernández-Navarro, Elena Boldo, Rebeca Ramis

Abstract read
In one paragraph

Article in BMC public health, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
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

20 citing papers in PubMed.

  1. Article
  2. Potential Exposure to Environmental Toxic Emissions and Increased Cancer Risk in Puerto Rico.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
    Article
  3. Review
  4. Geographical Distribution of Colorectal Cancer in Southwestern Iran Between Years 2011 and 2019.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2023
    Article
  5. Review
  6. Article
  7. Review
  8. Cancer Incidence Trends in the Oil Shale Industrial Region in Estonia.International journal of environmental research and public health · 2020
    Article
  9. Clinical, histopathological and immunohistochemical features of brain metastases originating in colorectal cancer: a series of 27 consecutive cases.Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologie · 2020
    Article
  10. Colorectal cancer-associated microbiota contributes to oncogenic epigenetic signatures.Proceedings of the National Academy of Sciences of the United States of America · 2019
    Article
  11. Colorectal cancer: The epigenetic role of microbiome.World journal of clinical cases · 2019
    Review
  12. Article
  13. Spatial heterogeneity ofCancer management and research · 2019
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Observational
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

5 authors.

Gonzalo López-AbenteCancer and Environmental Epidemiology Unit, National Centre for Epidemiology, Carlos III Institute of Health, Monforte de Lemos 5, 28029, Madrid, Spain. glabente@isciii.es
Javier García-Pérez
Pablo Fernández-Navarro
Elena Boldo
Rebeca Ramis

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecords kept as a result of the implementation of Integrated Pollution Prevention and Control (IPPC) and the European Pollutant Release and Transfer Register (E-PRTR) constitute a public inventory of industries, created by the European Commission, which is a valuable resource for monitoring industrial pollution. Our objective is to ascertain whether there might be excess colorectal cancer mortality among populations residing in the vicinity of Spanish industrial installations that are governed by the IPPC Directive and E-PRTR Regulation and report their emissions to air.

methodsAn ecological study was designed to examine colorectal cancer mortality at a municipal level (8098 Spanish towns), over the period 1997-2006. We conducted an exploratory "near vs. far" analysis to estimate the relative risks (RR) of towns situated at a distance of less than 2 km from industrial installations. The analysis was repeated for each of the 24 industrial groups. RR and their 95% credible/confidence intervals (95%CI) were estimated on the basis of Poisson regression models, using two types of modelling: a) the conditional autoregressive Bayesian model proposed by Besag, York and Mollié, with explanatory variables; and b) a mixed regression model. Integrated nested Laplace approximations were used as a Bayesian inference tool.

resultsStatistically significant RRs were detected in the vicinity of mining industry (RR 1.258; 95%CI 1.082 - 1.463), paper and wood production (RR 1.071; 95%CI 1.007 - 1.140), food and beverage sector (RR 1.069; 95%CI 1.029 - 1.111), metal production and processing installations (RR 1.065; 95% CI 1.011 - 1.123) and ceramics (RR 1.050 ; 95%CI 1.004 - 1.099).

conclusionsGiven the exploratory nature of this study, it would seem advisable to check in other countries or with other designs, if the proximity of industries that emit pollutants into the air could be an added risk factor for colorectal cancer mortality. Nevertheless, some of the differences between men and women observed in the analyses of the industrial groups suggest that there may be a component of occupational exposure, little-studied in the case of cancers of the digestive system.

Indexed as

IndustryAir PollutionColorectal NeoplasmsEnvironmental ExposureEnvironmental MonitoringFemaleGovernment RegulationHumansMaleRegistriesRiskSex DistributionSpain

Identifiers

PMID22852770
PMCPMC3490748

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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.