Пархоменко, О. Г.Яворська, Вікторія ВолодимирівнаParkhomenko, O. H.Yavorska, Viktoriia V.2025-09-042025-09-042025Пархоменко О. Г. Суспільно-географічний аналіз захворюваності населення Одеської області / О. Г. Пархоменко, В. В. Яворська // Вісник Одеського національного університету. Географічні та геологічні науки. – 2025. – Т. 30, вип. 1(46). – С. 160–170.2303-9914https://dspace.onu.edu.ua/handle/123456789/42225У статті проведено суспільно-географічний аналіз захворюваності населення Одеської області на основі статистичних даних, картографічного моделювання та територіального порівняння. Встановлено значну просторову нерівномірність поширення хвороб серед населення області. Виділено медико-географічні зони з різним ступенем епідеміологічної напруженості. Виявлено залежність між рівнем захворюваності та соціально-економічними умовами проживання, демографічною структурою населення, станом довкілля та інфраструктурою охорони здоров’я.Problem Statement and Purpose. Morbidity of the population, as one of the main indicators of public health, reflects both immediate medical and numerous socio-economic, demographic, behavioral and environmental factors. Special attention should be paid to regions with a high degree of social and demographic heterogeneity, in particular the Odesa region – a border, coastal region with significant ethnic, social and natural geographical mosaics. Taking into account theoretical developments, empirical and applied research within the medical and geographical direction, there is an objective need for further study of the morbidity of the population at the regional level. Data & Methods. The study used official statistical materials of the Main Department of Statistics in the Odesa region and the public health center of the Ministry of Health of Ukraine. The analysis was carried out at the level of enlarged administrative districts of the Odesa region. Methods of dynamic, comparative and spatial analysis, as well as graphical representation of data are applied. Results. A comparative analysis of the districts of the Odesa region by a combination of socio-economic, medical and environmental factors allows us to identify structural differences in factors that directly affect the level of morbidity of the population. In Odesa, at the same time, there is a rather unfavorable environmental situation associated with a high level of atmospheric pollution, dense buildings, population density (2,690 people/km^2), increased social load and psycho-emotional stress, which further increase the risks of deterioration of health. According to the results of the study, there is a clear correlation between the level of socio-economic development, medical infrastructure and the ecological state of territories and the level of morbidity. In urbanized areas with a high level of health care, more diseases are recorded, which is associated with greater detection, while peripheral, rural areas, on the contrary, have underestimated indicators, which probably do not reflect the real state of health of the population. This should be taken into account when planning preventive policies and regional development of the health system. The structure of morbidity is dominated by chronic noncommunicable diseases, which is typical for countries with transformational economies and demographic aging. At the same time, a significant proportion of respiratory diseases and mental disorders indicate the influence of current socio-economic and environmental factors. Thus, the overall picture of registered morbidity in the Odesa region demonstrates a significant territorial unevenness, which is due to both demographic characteristics and the level of urbanization, as well as spatial differentiation of access to medical resources. Such an analysis allows identifying areas of potential risk and forming priorities for Regional Health Policy.ukзахворюваністьмедико-географічний аналізОдеська областьдемографія здоров’ярегіональна диференціаціяпросторовий аналізmorbiditymedical and geographical analysisOdesa regionhealth demographyregional differentiationspatial analysisArticlehttps://doi.org/10.18524/2303-9914.2025.1(46).332400911.3https://orcid.org/0009-0000-8283-9982https://orcid.org/0000-0002-7449-79082415-315X