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Impact of socioeconomic inequalities on geographic disparities in cancer incidence: comparison of methods for spatial disease mapping

Juste Aristide Goungounga ; Jean Gaudart ; Marc Colonna ; Roch Giorgi

BMC medical research methodology, 01 October 2016, Vol.16(1), pp.1-14 [Rivista Peer Reviewed]

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  • Titolo:
    Impact of socioeconomic inequalities on geographic disparities in cancer incidence: comparison of methods for spatial disease mapping
  • Autore: Juste Aristide Goungounga ; Jean Gaudart ; Marc Colonna ; Roch Giorgi
  • Note di contenuto: Abstract Background The reliability of spatial statistics is often put into question because real spatial variations may not be found, especially in heterogeneous areas. Our objective was to compare empirically different cluster detection methods. We assessed their ability to find spatial clusters of cancer cases and evaluated the impact of the socioeconomic status (e.g., the Townsend index) on cancer incidence. Methods Moran’s I, the empirical Bayes index (EBI), and Potthoff-Whittinghill test were used to investigate the general clustering. The local cluster detection methods were: i) the spatial oblique decision tree (SpODT); ii) the spatial scan statistic of Kulldorff (SaTScan); and, iii) the hierarchical Bayesian spatial modeling (HBSM) in a univariate and multivariate setting. These methods were used with and without introducing the Townsend index of socioeconomic deprivation known to be related to the distribution of cancer incidence. Incidence data stemmed from the Cancer...
  • Fa parte di: BMC medical research methodology, 01 October 2016, Vol.16(1), pp.1-14
  • Soggetti: Spatial Analysis ; Cluster Detection ; Cancer ; Oblique Decision Tree ; Medicine
  • Lingua: Inglese
  • Tipo: Articolo
  • Identificativo: E-ISSN: 1471-2288 ; DOI: 10.1186/s12874-016-0228-x
  • Fonte: Directory of Open Access Journals (DOAJ)

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