A Spatio-Temporal Analysis of the Health Situation in Poland Based on Functional Discriminant Coordinates

Bibliographic Data

ID15469267
AuthorsMirosław Krzyśko (0000-0001-8075-4432, Institute of Mathematics), Waldemar Wołyński (0000-0002-0777-9163, Faculty of Mathematics and Computer Science, Adam Mickiewicz University, 61-614 Poznań, Poland), Waldemar Wołyńki (Adam Mickiewicz University in Poznań, corresponding author), Marcin Szymkowiak (0000-0003-3432-4364, Poznań University of Economics and Business), Andrzej Wojtyła (0000-0003-2692-487X, Uniwersytet Kaliski im. Prezydenta Stanisława Wojciechowskiego)
Year2021
Volume18
Issue3
Pages1109-1109
Publication date2021-01-27
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph18031109
PMID33513775
OpenAlexW3125196068
LanguageEN
References cited37

The aim of this study was to investigate if the provinces of Poland are homogeneous in terms of the observed spatio-temporal data characterizing the health situation of their inhabitants. The health situation is understood as a set of selected factors influencing inhabitants' health and the healthcare system in their area of residence. So far, studies concerning the health situation of selected territorial units have been based on data relating to a specific year rather than longer periods. The task of assessing province homogeneity was carried out in two stages. In stage one, the original spatio-temporal data space (space of multivariate time series) was transformed into a functional discriminant coordinates space. The resulting functional discriminant coordinates are synthetic measures of the health situation of inhabitants of particular provinces. These measures contain complete information regarding 8 diagnostic variables examined over a period of 6 years. In the second stage, the Ward method, commonly used in cluster analysis, was applied in order to identify groups of homogeneous provinces in the space of functional discriminant coordinates. Sixteen provinces were divided into four clusters. The homogeneity of the clusters was confirmed by the multivariate functional coefficient of variation

Cluster (spacecraft · Combinatorics · Discriminant · Geography · Homogeneity (statistics · Homogeneous · Linear discriminant analysis · Multivariate analysis · Multivariate statistics · Principal component analysis · Residence · Sociology · Statistics · Computer Science · Demography · Global Health Care Issues · Health disparities and outcomes · Mathematics · Nutritional Studies and Diet · Artificial Intelligence

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