<abstract xmlns="http://www.w3.org/1999/xhtml">

Health inequalities, which could be prevented by appropriate means in various areas, are generally perceived as a consequence of injustice in the society and are mostly the result of inequalities in social determinants. The main goal of this article is to determine health inequalities defined by demographic and socio-economic factors at the level of districts of the Czech Republic in the period 2007–2018(due to the specific differences in data, the Capital City of Prague region was not included). The following statistical methods were used to process the data: correlation analysis, principal component analysis, composite indicator, cluster analysis and multidimensional factor analysis. The value of the composite indicator shows a very favorable situation in the districts of Praha-východ and Praha-západ (especially high proportion of university students, low unemployment, age index, infant mortality, abortion rate and housing subsidies), and the unfavourable situation in the districts of Chomutov, Teplice and Most (especially high housing and unemployment subsidies, low rate of university students, negative migration balance, high rates of infant mortality and abortion). The results specify regional disparities of demographic and socio-economic indicators that can cause health inequalities: negative regional disparities (Most, Teplice, Děčín, Bruntál, Karviná, Ostrava-město and Jeseník districts) and positive regional disparities (Praha-západ, Praha-východ, Mladá Boleslav, Jihlava and Brno-venkov). The study presents the results of analyses based on the example of smaller territorial units (districts) and confirms the existence of regional disparities in accordance with research at the national and international level.
<bold>Highlights for public administration, management and planning:</bold>
<list list-type="bullet">
<list-item>• Demographic factors are connected to socio-economic environmental factors (poverty, education, social exclusion, unemployment, social security, family situation etc.) that lead to regional health inequalities.</list-item>
<list-item>• The regional disparities of selected demographic and socio-economic indicators of the districts of the Czech Republic that cause health inequalities were specified.</list-item>
</list>
</abstract>

Health inequalities, which could be prevented by appropriate means in various areas, are generally perceived as a consequence of injustice in the society and are mostly the result of inequalities in social determinants. The main goal of this article is to determine health inequalities defined by demographic and socio-economic factors at the level of districts of the Czech Republic in the period 2007–2018(due to the specific differences in data, the Capital City of Prague region was not included). The following statistical methods were used to process the data: correlation analysis, principal component analysis, composite indicator, cluster analysis and multidimensional factor analysis. The value of the composite indicator shows a very favorable situation in the districts of Praha-východ and Praha-západ (especially high proportion of university students, low unemployment, age index, infant mortality, abortion rate and housing subsidies), and the unfavourable situation in the districts of Chomutov, Teplice and Most (especially high housing and unemployment subsidies, low rate of university students, negative migration balance, high rates of infant mortality and abortion). The results specify regional disparities of demographic and socio-economic indicators that can cause health inequalities: negative regional disparities (Most, Teplice, Děčín, Bruntál, Karviná, Ostrava-město and Jeseník districts) and positive regional disparities (Praha-západ, Praha-východ, Mladá Boleslav, Jihlava and Brno-venkov). The study presents the results of analyses based on the example of smaller territorial units (districts) and confirms the existence of regional disparities in accordance with research at the national and international level.
Highlights for public administration, management and planning:

• Demographic factors are connected to socio-economic environmental factors (poverty, education, social exclusion, unemployment, social security, family situation etc.) that lead to regional health inequalities.
• The regional disparities of selected demographic and socio-economic indicators of the districts of the Czech Republic that cause health inequalities were specified.

Demographic and socio-economic factors influencing health inequalities in the Czech Republic

Department of Social Studies, Faculty of Regional Development and International Studies

GeoScape

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Health inequalities, which could be prevented by appropriate means in various areas, are generally perceived as a consequence of injustice in the society and...

Demographic and socio-economic factors influencing health inequalities in the Czech Republic

Online veröffentlicht: 03. Juli 2021

Seitenbereich: 53 - 65

Eingereicht: 23. Okt. 2020

Akzeptiert: 22. Apr. 2021

DOI: https://doi.org/10.2478/geosc-2021-0005

Schlüsselwörter
Health inequalities, Demographic and socio-economic factors, Regional disparities, Cluster analysis

© 2021 Dana Hübelová et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Demographic and socio-economic factors influencing health inequalities in the Czech Republic

Online veröffentlicht: 03. Juli 2021

Seitenbereich: 53 - 65

Eingereicht: 23. Okt. 2020

Akzeptiert: 22. Apr. 2021

DOI: https://doi.org/10.2478/geosc-2021-0005

SchlüsselwörterHealth inequalities, Demographic and socio-economic factors, Regional disparities, Cluster analysis

© 2021 Dana Hübelová et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Health inequalities, Demographic and socio-economic factors, Regional disparities, Cluster analysis