International Journal of COPD (Dec 2017)

Geographical distribution of COPD prevalence in Europe, estimated by an inverse distance weighting interpolation technique

  • Blanco I,
  • Diego I,
  • Bueno P,
  • Fernández E,
  • Casas-Maldonado F,
  • Esquinas C,
  • Soriano JB,
  • Miravitlles M

Journal volume & issue
Vol. Volume 13
pp. 57 – 67

Abstract

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Ignacio Blanco,1 Isidro Diego,2 Patricia Bueno,3 Eloy Fernández,4 Francisco Casas-Maldonado,5 Cristina Esquinas,6 Joan B Soriano,7 Marc Miravitlles6 1Alpha1-Antitrypsin Deficiency Spanish Registry, Lung Foundation Breathe, Spanish Society of Pneumology, Barcelona, 2Materials and Energy Department, School of Mining Engineering, Oviedo University, 3Internal Medicine Department, County Hospital of Jarrio, 4Clinical Analysis Laboratory, University Hospital of Cabueñes, Principality of Asturias, 5Pneumology Department, University Hospital San Cecilio, Granada, 6Pneumology Department, Hospital Universitari Vall d’Hebron, CIBER de Enfermedades Respiratorias (CIBERES), Barcelona, 7Instituto de Investigación Hospital Universitario de la Princesa, Universidad Autónoma de Madrid, Madrid, Spain Abstract: Existing data on COPD prevalence are limited or totally lacking in many regions of Europe. The geographic information system inverse distance weighted (IDW) interpolation technique has proved to be an effective tool in spatial distribution estimation of epidemiological variables, when real data are few and widely separated. Therefore, in order to represent cartographically the prevalence of COPD in Europe, an IDW interpolation mapping was performed. The point prevalence data provided by 62 studies from 19 countries (21 from 5 Northern European countries, 11 from 3 Western European countries, 14 from 5 Central European countries, and 16 from 6 Southern European countries) were identified using validated spirometric criteria. Despite the lack of data in many areas (including all regions of the eastern part of the continent), the IDW mapping predicted the COPD prevalence in the whole territory, even in extensive areas lacking real data. Although the quality of the data obtained from some studies may have some limitations related to different confounding factors, this methodology may be a suitable tool for obtaining epidemiological estimates that can enable us to better address this major public health problem. Keywords: epidemiology, geographic information system, GIS, Geographic Resources Analysis Support System

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