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Geographical differences in cancer incidence in the Belgian province of Limburg. 2003

F Buntinx, and H Geys, and D Lousbergh, and G Broeders, and E Cloes, and D Dhollander, and L Op De Beeck, and J Vanden Brande, and A Van Waes, and G Molenberghs
Limburg Cancer Registry (LIKAR), Limburgse Kankerstichting, Stadsomvaart 9, 3500, Hasselt, Belgium. frank.buntinx@med.kuleuven.ac.be

Correctly addressing the questions of worried citizens with respect to possible clusters of cancer occurrence requires a risk communication strategy that is informed by a previously established analytical procedure. The aim of this study was to analyse cancer registration data in order to identify municipalities or clusters of municipalities with an increased incidence of one or more cancer types, adjusted for background characteristics at the same level. Ideally, the approach is proactive, straightforward, and easy for untrained citizens to follow and imprecision effects are taken into account. For all municipalities and most cancers, all relevant calculations were performed proactively and all methods and decision thresholds were defined beforehand. For each municipality, standardised incidence ratios (SIRs) were calculated and smoothed using a Poisson-gamma (PG) and a conditional autoregressive (CAR) model. Clusters were confirmed using the Spatial scan statistic of Kulldorff. Identified clusters were tested for possible confounders using all information that was available for each municipality. The Limburg Cancer Registry, serving the population of the Belgian province of Limburg (n=781 759) was used. We identified a possible cluster of increased prostate cancer incidence (smoothed SIRs around 1.2) and a cluster of increased bladder cancer incidence in males that included seven municipalities with CAR-smoothed SIRs between 1.5 and 2.1. SIRs followed a more or less circular decrease around the centre that was situated in Alken and Hasselt, the provincial capital. Bladder cancer incidence was positively related to an index of socio-economic status (SES) per municipality. No relationship was found with the other indexes that were available. 82% of all bladder cancers were transitional cell carcinomas (TCC). A repeated analysis based on TCCs only resulted in similar results with CAR-smoothed relative risks that tended to be even higher in the cluster zone. A pre-emptive analysis of possible cancer incidence clustering on the municipality level proved to be feasible.

UI MeSH Term Description Entries
D008297 Male Males
D009369 Neoplasms New abnormal growth of tissue. Malignant neoplasms show a greater degree of anaplasia and have the properties of invasion and metastasis, compared to benign neoplasms. Benign Neoplasm,Cancer,Malignant Neoplasm,Tumor,Tumors,Benign Neoplasms,Malignancy,Malignant Neoplasms,Neoplasia,Neoplasm,Neoplasms, Benign,Cancers,Malignancies,Neoplasias,Neoplasm, Benign,Neoplasm, Malignant,Neoplasms, Malignant
D012042 Registries The systems and processes involved in the establishment, support, management, and operation of registers, e.g., disease registers. Parish Registers,Population Register,Parish Register,Population Registers,Register, Parish,Register, Population,Registers, Parish,Registers, Population,Registry
D012111 Residence Characteristics Elements of residence that characterize a population. They are applicable in determining need for and utilization of health services. Community,Domicile,Living Arrangements,Neighborhood,Place of Birth,Residential Selection,Arrangement, Living,Birth Place,Communities,Domiciles,Living Arrangement,Neighborhoods,Residence Characteristic
D001749 Urinary Bladder Neoplasms Tumors or cancer of the URINARY BLADDER. Bladder Cancer,Bladder Neoplasms,Cancer of Bladder,Bladder Tumors,Cancer of the Bladder,Malignant Tumor of Urinary Bladder,Neoplasms, Bladder,Urinary Bladder Cancer,Bladder Cancers,Bladder Neoplasm,Bladder Tumor,Cancer, Bladder,Cancer, Urinary Bladder,Neoplasm, Bladder,Neoplasm, Urinary Bladder,Tumor, Bladder,Tumors, Bladder,Urinary Bladder Neoplasm
D005260 Female Females
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D001530 Belgium A country in Western Europe, bordering the North Sea, between France and the Netherlands. The capital is Brussels.
D012307 Risk Factors An aspect of personal behavior or lifestyle, environmental exposure, inborn or inherited characteristic, which, based on epidemiological evidence, is known to be associated with a health-related condition considered important to prevent. Health Correlates,Risk Factor Scores,Risk Scores,Social Risk Factors,Population at Risk,Populations at Risk,Correlates, Health,Factor, Risk,Factor, Social Risk,Factors, Social Risk,Risk Factor,Risk Factor Score,Risk Factor, Social,Risk Factors, Social,Risk Score,Score, Risk,Score, Risk Factor,Social Risk Factor
D015994 Incidence The number of new cases of a given disease during a given period in a specified population. It also is used for the rate at which new events occur in a defined population. It is differentiated from PREVALENCE, which refers to all cases in the population at a given time. Attack Rate,Cumulative Incidence,Incidence Proportion,Incidence Rate,Person-time Rate,Secondary Attack Rate,Attack Rate, Secondary,Attack Rates,Cumulative Incidences,Incidence Proportions,Incidence Rates,Incidence, Cumulative,Incidences,Person time Rate,Person-time Rates,Proportion, Incidence,Rate, Attack,Rate, Incidence,Rate, Person-time,Rate, Secondary Attack,Secondary Attack Rates

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