Evidence map›Paper›PMID 19570225›Full record

ArticleInternational journal of health geographics2009

Geographical clustering of lung cancer in the province of Lecce, Italy: 1992-2001.

Massimo Bilancia, Alessandro Fedespina

Abstract readComparative Study
In one paragraph

Article in International journal of health geographics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Article
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  6. Exploring Spatial Patterns of Colorectal Cancer in Tehran City, IranAsian Pacific journal of cancer prevention : APJCP · 2018
    Article
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  12. Review
  13. Developing the atlas of cancer in Queensland: methodological issues.International journal of health geographics · 2011
    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

2 authors.

Massimo BilanciaDepartment of Statistical Sciences Carlo Cecchi, University of Bari, 70124 Bari, Italy. mabil@dss.uniba.it
Alessandro Fedespina

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe triennial mortality rates for lung cancer in the two decades 1981-2001 in the province of Lecce, Italy, are significantly higher than those for the entire region of Apulia (to which the Province of Lecce belongs) and the national reference rates. Moreover, analyzing the rates in the three-year periods 1993-95, 1996-98 and 1999-01, there is a dramatic increase in mortality for both males and females, which still remains essentially unexplained: to understand the extent of this phenomenon, it is worth noting that the standardized mortality rate for males in 1999-01 is equal to 13.92 per 10000 person-years, compared to a value of 6.96 for Italy in the 2000-2002 period.These data have generated a considerable concern in the press and public opinion, which with little scientific reasoning have sometimes identified suspected culprits of the risk excess (for example, the emission caused by a number of large industrial sites located in the provinces of Brindisi and Taranto, bordering the Province of Lecce). The objective of this paper is to study on a scientifically sound basis the spatial distribution of risk for lung cancer mortality in the province of Lecce. Our goal is to demonstrate that most of the previous explanations are not supported by data: to this end, we will follow a hybrid approach that combines both frequentist and Bayesian disease mapping methods. Furthermore, we define a new sequential algorithm based on a modified version of the Besag-York-Mollié (BYM) model, suitably modified to detect geographical clusters of disease.

resultsStandardized mortality ratios (SMRs) for lung cancer in the province of Lecce: For males, the relative risk (measured by means of SMR, i.e. the ratio between observed and expected cases in each area under internal standardization) was judged to be significantly greater than 1 in many municipal areas, the significance being evaluated under the null hypothesis of neutral risk on the ground of area-specific p-values (denoted by rhoi); in addition, it was seen that high risk areas were not randomly distributed within the province, but showed a sharp clustering. The most perceptible cluster involved a collection of municipalities around the Maglie area (Istat code: 75039), while the association among the municipalities of Otranto, Poggiardo and Santa Cesarea Terme (Istat codes: 75057, 75061, 75072) was more ambiguous. For females, it was noteworthy the significant risk excess in the city of Lecce (Istat code: 75035), where an SMR of 1.83 and rhoi < 0.01 have been registered. BYM model for the province of Lecce: For males, Bayes estimates of relative risks varied around an overall mean of 1.04 with standard deviation of 0.1, with a minimum of 0.77 and a maximum of 1.25. The posterior relative risks for females, although smoothed, showed more variation than for males, ranging form 0.74 to 1.65, around a mean of 0.90 with standard deviation 0.12. For males, 95% posterior credible intervals of relative risks included unity in every area, whereas significantly elevated risk of mortality was confirmed in the Lecce area for females (95% posterior CI: 1.33 - 2.00). BYM model for the whole Apulia: For males, internally standardized maps showed several high risk areas bordering the province of Lecce, belonging to the province of Brindisi, and the presence of a large high risk region, including the southern part of the province of Brindisi and the eastern and southern part of the Salento peninsula, in which an increasing trend in the north-south direction was found.Ecological correlation study with deprivation (Cadum Index): For males, posterior mean of the ecological regression coefficient beta resulted to be 0.04 with 95% posterior credible interval equal to (-0.01, 0.08); similarly, beta was estimated as equal to -0.03 for females (95% posterior credible interval: -0.16, 0.10). Moreover, there was some indication of nonlinearly increasing relative risk with increasing deprivation for higher deprivation levels. For females, it was difficult to postulate the existence of any association between risk and deprivation.Cluster detection: cluster detection based on a modified BYM model identified two large unexplained increased risk clusters in the central-eastern and southern part of the peninsula. Other secondary clusters, which raise several complex interpretation issues, are present.

conclusionOur results reduce the alleged role of the industrial facilities located around the province of Taranto: in particular, air pollution produced around the city of Taranto (which lies to the west of the province of Lecce) has been often identified as the main culprit of the mortality excess, a conclusion that was further supported by a recent study on the direction of prevailing winds on Salento. This hypothesis is contradicted by the finding that those municipalities that directly border on the province of Taranto (belonging to the so-called "Jonico-Salentina" band) are those that present low mortality rates (at least for males). In the same way, the responsibilities of energy production plants located in the province of Brindisi (Brindisi province lies to the north) appear to be of little relevance. For females, given the situation observed in the city of Lecce, and given the substantial increase in mortality observed in younger age classes, further investigation is required into the role played by changes in lifestyle, including greater net propensity to smoke that women have shown since the 80s onwards (a phenomenon which could be amplified in a city traditionally cultured and modern as Lecce, as the tobacco habit is a largely cultural phenomenon). For males, the presence of high levels of deprivation throughout the eastern and southern Salento is likely to play an important role: those with lower socio-economic status smoke more, and gender differences may be explained on the basis of the fact that in less developed areas women have less habit to tobacco smoking and alcohol drinking (and other harmful lifestyles), which are seen as purely masculine behaviour: research into the role of material deprivation and individual lifestyle differences between genders should be further developed.

Indexed as

DemographyAdolescentAdultAgedChildChild, PreschoolCluster AnalysisEnvironmental ExposureFemaleHumansInfantItalyLung NeoplasmsMaleMiddle AgedRisk Factors

Identifiers

PMID19570225
PMCPMC2718871

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LicenceCC BY
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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.