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• W2899310229 abstract "Surveys estimating chronic obstructive pulmonary disease (COPD) prevalence are unevenly distributed in the Americas, which make it difficult to estimate accurately its geographical distribution. The geographic information system inverse distance weighted (IDW) interpolation technique has proved to be an effective tool in spatial distribution estimation of epidemiological variables, even when real data are few or widely spread. We aimed to represent cartographically the COPD prevalence in the Americas by means of a blue to red scale representation of the prevalence data, where different values are represented as different colours, and a population density filtered IDW interpolation mapping, where areas with a population density <0.1 inhabitants/km2 are hidden. We systematically searched for prevalence rates from population surveys of individuals 40 years and older, and a COPD diagnosis confirmed by spirometry. Interpolation maps were obtained for the whole Americas, even from extensive areas lacking real data. Maps showed high prevalence values in the Southeast and Southwest regions of Canada bordering the United States; in several states of the Great Lakes region, and in the lower Missouri, Ohio and Mississippi basins of the United States; in the coastal regions of south-eastern and southern Brazil; Uruguay, and the Argentine Pampas. In general, most of the remaining American regions showed intermediate values of COPD prevalence. IDW interpolation seems to be a suitable tool to visually display estimates of COPD prevalence, and it may be a valuable help to draw attention about the worrying prevalence of this preventable and treatable disease." @default.
• W2899310229 created "2018-11-09" @default.
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• W2899310229 date "2018-07-04" @default.
• W2899310229 modified "2023-10-18" @default.
• W2899310229 title "Geographical Distribution of COPD Prevalence in the Americas" @default.
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• W2899310229 doi "https://doi.org/10.1080/15412555.2018.1481936" @default.
• W2899310229 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30375898" @default.
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