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Infant Mortality in Russia: Statistical Analysis and Forecasting of Main Trends

https://doi.org/10.21686/2500-3925-2025-5-19-29

Abstract

Purpose of the study. Infant mortality is included in the list of indexes for assessing the performance of executive authorities of the regions of the Russian Federation. Its reduction serves as target indicators for the implementation of the national projects «Healthcare» and «Family». The article presents the results of statistical analysis and forecasting of the main trends in the infant mortality rate in the Russian Federation to assess the possibility of achieving the planned values of the target indexes for the implementation of national projects.

Materials and methods. The theoretical basis of the study was the works of foreign and domestic authors devoted to the study of infant mortality and factors for its reduction. Methods of descriptive statistics, groupings, and the forecasting method based on the ARIMA model were used as the methodological basis of the study. The information base of the study is data from the Federal State Statistics Service.

The results of the study allowed us to identify the dynamics and structure of infant mortality for the period under review. An analysis of the dynamics of the infant mortality rate in Russia shows a decrease from 8.6 in 2012 to 4.2 per 1000 live births in 2023. Infant mortality among boys exceeds that among girls. The infant mortality rate in rural areas is higher than in urban areas: on average, infant mortality in the city is 5.5‰, in rural areas – 6.9‰. The presence of territorial differentiation in the level of infant mortality by regions of the Russian Federation. The results of grouping the regions of the Russian Federation made it possible to identify regions with low, medium, high and very high characteristics of infant mortality. The vast majority of Russian regions are characterized by an average infant mortality rate. Regions with low infant mortality rates include regions of the Far North (Nenets autonomous area, Khanty-Mansi autonomous area), central Russia (Kaluga district) and southern territories (Sevastopol city). Subjects with high infant mortality rates include the republics of the North Caucasus federal district (Karachay-Cherkess Republic, Chechen Republic, Republic of Dagestan), Siberia, and the Far East (Krasnoyarsk, Primorsky, Kamchatka and Zabaykalsky territories). The fourth group with very high infant mortality rates includes only the Chukotka autonomous area, where the index reaches an abnormal value of 19.1‰. Forecasting infant mortality rates based on the ARIMA model made it possible to assess the probability of achieving the target indexes for its reduction set by the national project «Healthcare» and the federal project «Maternity and Childhood Protection». According to the forecast, the infant mortality target index will be reached by 2027. With a probability of 95%, the infant mortality will be 3.9 cases per 1000 live births.

Conclusions. The analysis shows that achieving the target indexes for reducing infant mortality is realistic if current trends are maintained. To achieve the set goals, it is necessary to continue implementing state and regional programs and national projects aimed at increasing the birth rate, protecting motherhood and childhood, the availability and quality of medical care for children, developing children’s health care and stabilizing the demographic situation in the country.

About the Authors

M. V. Bikeeva
National Research Mordovia State University
Russian Federation

Marina V. Bikeeva, Cand. Sci. (Economics), Assistant professor of the Department of Statistics and Information Technologies in Economics and Management

Saransk



E. A. Sysoeva
National Research Mordovia State University
Russian Federation

Evgeniya A. Sysoeva, Dr. Sci. (Economics), Head of Department of Statistics and Information Technologies in Economics and Management

Saransk



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For citations:


Bikeeva M.V., Sysoeva E.A. Infant Mortality in Russia: Statistical Analysis and Forecasting of Main Trends. Statistics and Economics. 2025;22(5):19-29. (In Russ.) https://doi.org/10.21686/2500-3925-2025-5-19-29

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