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Systematic population-wide ecological analysis of regional variability in disease prevalence

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.

D. R. Lo Sardo, S. Thurner, J. Sorger, G. Heiler, M. Gyimesi, A. Kautzky, M. Leutner, A. Kautzky-Willer, P. Klimek, Systematic population-wide ecological analysis of regional variability in disease prevalence, Heliyon 9(4) (2023) e15377.

Stefan Thurner @ Franziska Liehl, President of the Complexity Science Hub

Stefan Thurner

Johannes Sorger

Georg Heiler © Stephanie Bourke Altmann.jpg

Georg Heiler

Peter Klimek, Faculty member at the Complexity Science Hub

Peter Klimek

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