Reserves and limitations of the gain in life expectancy at birth for people in an industrially developed region associated with losses due to circulatory diseases

Introduction. The current project activity of the state aimed to improve the medical and demographic situation in the country involves complex changes in many spheres of society activities including living conditions of working age population. The purpose of study. Identification of the working environment and labour process priority factors against the background of environmental factors system, according to the measure of their influence on age-specific mortality due to circulatory system diseases and estimation potential for increasing of life expectancy at birth for the industrialized region population. Materials and methods. Data were taken from state statistical reports issued in 2010–2019. They covered 206 indices, including factors related to workplace setting and work processes (20 items). Using a FA-ANN (factor analysis — artificial neural network) model as by 5-year age groups. Results. We established certain influence produced on LEB in total and working age population on the example of the Perm Krai by changes in environmental according to scenario forecasts, 75.87 and 67.81 years by 2030. Influence exerted on age-specific mortality rates due to circulatory diseases and LEB by changes in some specific groups of factors was assessed using retrospective data (between (–)48.6 days and 284.5 days), in particular, positive changes in workplace settings and work processes (between 11.1 and 30.3 days within different scenarios). According to our forecast, by 2030 the maximum effect of LEB growth for the population (total and working age) is expected to be associated with changes in sociodemographic indices (435.5 days), lifestyle indices (172.2 days), sanitary-epidemiologic welfare (105.1 days). Research limitations. The analyzed dataset, limitations of the applied model, approaches to setting scenario conditions for changes in analyzed indices. Conclusion. Priority factors have been identified on the example of an industrially developed region (the Perm Krai). Changes in them can help use the potential of LEB growth due to targeted interdepartmental project activities including improvement of workplace settings and work processes.

Authors

Institutions

Publication Details

Journal
Health Care of the Russian Federation
Published
2024-12-26
DOI
https://doi.org/10.47470/0044-197x-2024-68-6-480-487
Primary Topic
Healthcare Systems and Public Health
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Reserves and limitations of the gain in life expectancy at birth for people in an industrially developed region associated with losses due to circulatory diseases

V.G. Kostarev, Н.В. Зайцева, С В Клейн, Maxim V. Glukhikh et al.
Health Care of the Russian Federation
Healthcare Systems and Public Health
article

Reserves and limitations of the gain in life expectancy at birth for people in an industrially developed region associated with losses due to circulatory diseases

V.G. Kostarev, Н.В. Зайцева, С В Клейн, Maxim V. Glukhikh, D.А. Kiryanov
article en

Abstract

Introduction. The current project activity of the state aimed to improve the medical and demographic situation in the country involves complex changes in many spheres of society activities including living conditions of working age population. The purpose of study. Identification of the working environment and labour process priority factors against the background of environmental factors system, according to the measure of their influence on age-specific mortality due to circulatory system diseases and estimation potential for increasing of life expectancy at birth for the industrialized region population. Materials and methods. Data were taken from state statistical reports issued in 2010–2019. They covered 206 indices, including factors related to workplace setting and work processes (20 items). Using a FA-ANN (factor analysis — artificial neural network) model as by 5-year age groups. Results. We established certain influence produced on LEB in total and working age population on the example of the Perm Krai by changes in environmental according to scenario forecasts, 75.87 and 67.81 years by 2030. Influence exerted on age-specific mortality rates due to circulatory diseases and LEB by changes in some specific groups of factors was assessed using retrospective data (between (–)48.6 days and 284.5 days), in particular, positive changes in workplace settings and work processes (between 11.1 and 30.3 days within different scenarios). According to our forecast, by 2030 the maximum effect of LEB growth for the population (total and working age) is expected to be associated with changes in sociodemographic indices (435.5 days), lifestyle indices (172.2 days), sanitary-epidemiologic welfare (105.1 days). Research limitations. The analyzed dataset, limitations of the applied model, approaches to setting scenario conditions for changes in analyzed indices. Conclusion. Priority factors have been identified on the example of an industrially developed region (the Perm Krai). Changes in them can help use the potential of LEB growth due to targeted interdepartmental project activities including improvement of workplace settings and work processes.

Health Care of the Russian FederationVol. 68(6)
Federal Scientific Center for Medical and Preventive Health Risk Management Technologies (RU), Federal Service for Surveillance on Consumer Rights Protection and Human Wellbeing (RU)
Openalex Percentile: Top 64%
Healthcare Systems and Public Health
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.