Model for assessing the influence of quality of life indicators on the breast cancer incidence

Abstract

Introduction. Malignant neoplasms of the breast are the leading oncological pathology among the female population of the Primorsky region. Identification of the relationship between the incidence rate and quality of life indicators, along with modern diagnostic methods, makes it possible to improve preventive measures to reduce the prevalence in the population at the regional level. Purpose. Development of a regression model that describes the impact of socio-economic indicators of quality of life on the incidence of breast cancer in the population of the Primorsky region. Materials and methods. The initial data sample consisted of seventeen indicators of the quality of life in the population of Primorsky region for the period from 1994 to 2020. To reduce the dimensionality of the data, the principal component method was used, and regression analysis was used to build the model. The quality of the constructed model was checked on the base of the calculation of the coefficient of determination, the standard error, and the approximation error. Results. There were identified 15 indicators of the quality of life in the population that significantly affect the pathology of breast cancer in the Primorsky region. Principal component analysis has made it possible to group the quality of life indicators into three major compartments. The first component explains 80.8% of the variance, the second — 10%, the third — 4%. The first compartment included indicators characterizing the socio-economic aspects of the life of the population, the second — medical and social, and the third — statistical indicators of inequality in monetary incomes of the population, characterizing the social differentiation of society. A regression model has been developed on the principal compartments. Research limitations. The research materials are limited to the results of statistical analysis of 17 indicators of the quality of life of the population of the Primorsky region for the period from 1994 to 2020 and the application of the developed regression model at the regional level. Conclusion. The results of this study made it possible to identify the relationship between the incidence of breast cancer and risk factors and develop a predictive model, which can be useful in planning preventive measures to improve the quality of life and reduce the incidence at the regional level.