SPATIAL-TEMPORAL ANALYSIS OF MORBIDITY OF CHERNIHIV REGION (OBLAST) POPULATION

Abstract

The article deals with the dynamics and territorial features analysis of morbidity of the population of Chernihiv Region (Oblast) in 2010-2018 in terms of main classes of diseases. The study of the current state of morbidity of the region (oblast) population within its administrative units has allowed identifying eight administrative districts of the region (oblast) and the city of Chernihiv, which have morbidity rates that differ significantly from the regional average. Since these areas are not territorially connected, it can be argued about the complex impact of various factors on the morbidity of the region (oblast) population.

The morbidity structure of the Chernihiv Region (Oblast) population by classes of diseases within the period of 2010–2018 has not changed. It is traditionally formed by diseases of the respiratory system, circulatory system and skin. The article reviews the measurement and the analysis of quantitative indicators of changes in the region population morbidity in terms of main diseases in the region as a whole and in its districts in particular.

To determine the spatial differentiation of the morbidity of the Chernihiv Region (Oblast) population, a cluster analysis has been performed by combining two methods – hierarchical clustering and k-means clustering. For clustering, eight indicators of population morbidity have been selected according to the classes of diseases that have the largest share in the structure of morbidity. These are indicators such as general morbidity, cardiovascular disease, tumors, diseases of the respiratory, blood and hematopoietic organs, circulatory system, skin and endocrine system. Five clusters within the region have been identified and characterized in terms of morbidity. A clustering map has been designed on the basis of the cluster analysis data.

The study of the population territorial morbidity provides an opportunity to predict the health status and develop measures to improve the health of the population.