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Systematic population-wide ecological analysis of regional variability in disease prevalence.
Lo Sardo, Donald Ruggiero; Thurner, Stefan; Sorger, Johannes; Heiler, Georgh; Gyimesi, Michael; Kautzky, Alexander; Leutner, Michael; Kautzky-Willer, Alexandra; Klimek, Peter.
Afiliação
  • Lo Sardo DR; Section for Science of Complex Systems, CeMSIIS, Medical University of Vienna, Spitalgasse 23, A-1090, Austria.
  • Thurner S; Complexity Science Hub Vienna, Josefst ädter Strasse 39, A-1080, Vienna, Austria.
  • Sorger J; Physics Department, Sapienza University of Rome, Piazzale Aldo Moro 2, 00185, Rome, Italy.
  • Heiler G; Section for Science of Complex Systems, CeMSIIS, Medical University of Vienna, Spitalgasse 23, A-1090, Austria.
  • Gyimesi M; Complexity Science Hub Vienna, Josefst ädter Strasse 39, A-1080, Vienna, Austria.
  • Kautzky A; IIASA, Schlossplatz 1, A-2361, Laxenburg, Austria.
  • Leutner M; Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM, 85701, USA.
  • Kautzky-Willer A; Complexity Science Hub Vienna, Josefst ädter Strasse 39, A-1080, Vienna, Austria.
  • Klimek P; Complexity Science Hub Vienna, Josefst ädter Strasse 39, A-1080, Vienna, Austria.
Heliyon ; 9(4): e15377, 2023 Apr.
Article em En | MEDLINE | ID: mdl-37123976
ABSTRACT
The prevalence of diseases often varies substantially from region to region. Besides basic demographic properties, the factors that drive the variability of each prevalence are to a large extent unknown. Here we show how regional prevalence variations in 115 different diseases relate to demographic, socio-economic, environmental factors and migratory background, as well as access to different types of health services such as primary, specialized and hospital healthcare. We have collected regional data for these risk factors at different levels of resolution; from large regions of care (Versorgungsregion) down to a 250 by 250 m square grid. Using multivariate regression analysis, we quantify the explanatory power of each independent variable in relation to the regional variation of the disease prevalence. We find that for certain diseases, such as acute heart conditions, diseases of the inner ear, mental and behavioral disorders due to substance abuse, up to 80% of the variance can be explained with these risk factors. For other diagnostic blocks, such as blood related diseases, injuries and poisoning however, the explanatory power is close to zero. We find that the time needed to travel from the inhabited center to the relevant hospital ward often contributes significantly to the disease risk, in particular for diabetes mellitus. Our results show that variations in disease burden across different regions can for many diseases be related to variations in demographic and socio-economic factors. Furthermore, our results highlight the relative importance of access to health care facilities in the treatment of chronic diseases like diabetes.
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Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Prevalence_studies / Risk_factors_studies Idioma: En Revista: Heliyon Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Áustria

Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Prevalence_studies / Risk_factors_studies Idioma: En Revista: Heliyon Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Áustria