Abstract
This study assesses the causal relationships between public health and the growth of anthropogenic activities within environmental management systems using linear mathematical models based on long-term statistical data. By enhancing the validity of measures aimed at preventing and reducing morbidity, the research aims to improving the health situation in the region. The study examines the health of the population in spatial and temporal aspects to theoretically demonstrate the applicability of a linear correlation model as an integral medical-demographic indicator. The methods employed include system analysis, mathematical statistics, and time series analysis, which together facilitate the identification of trends in public health through graphical representations. The novelty of this research lies in the development of one-parameter models that improve the accuracy of predictive and retrospective calculations based on inherently uncertain and probabilistic medical and demographic indicators. The resulting linear correlation model of morbidity, grounded in a comprehensive database of medical and demographic data from the Kyzylorda region, offers a broad understanding of the trends and outcomes associated with this process