The article presents the result produced by predicting growth potential in life expectancy at birth (LEB) of the RF Population. The predictions are based on scenario changes in social and hygienic determinants (SHD) identified by using an artificial neural network (ANN). This research is vital given the existing social strategies aimed at improving the medical and demographic situation in the Russian Federation. These strategies stipulate achieving targets set within the major national and federal projects. We identified an optimal ANN structure based on a four-layer perceptron with two inner layers containing eight and three neurons accordingly. This structure is able to produce results at the highest determination coefficient (R2= 0.78). Differences between actual LEB levels and predicted ones obtained by using the suggested model did not exceed 1.1 % (or 0.8 years). We established that average LEB in the RF would reach 75.06 years (by 2024) provided that the demographic situation in the country recovers in the nearest future, LEB level reaches its values detected in 2018–2019, and SHD values grow to their preset levels according to the target scenario. Therefore, the detected growth potential amounts to 3.0 years (1095 days) against 2018. “Lifestyle-related determinants” produce the greatest effects on the growth potential in LEB by 2024 (461 days). We also identified effects produced by such SHD groups as “Sanitary-epidemiological welfare on a given territory” (212 days), “Social and demographic indicators” (196 days), “Economic indicators” (131 days), “Indicators related to public healthcare” (70 days). An indicator that shows “A share of population doing physical exercises or sports” is the most significant determinant producing the greatest effects on potential changes in LEB. If it grows up to 55.0 %, a potential growth in LEB amounts to 243.5 days. If we do not consider COVID-related processes and rely only on the trends that are being observed now when predicting changes in the demographic situation by 2030, we can expect a possible additional growth in LEB that equals 286 days. The developed algorithm for determining growth potential in population LEB can be used as an instrument for determining and ranking priority health risk factors.
The current work supplements the results obtained in previous research on a relation between leading parameters of living conditions and life expectancy of the RF population; it dwells on the results obtained via analyzing a role played by sanitary and epidemiologic determinants. A sanitary-epidemiologic situation in certain RF regions is unfavorable and it makes our research truly vital; it is also necessary to work out and implement activities aimed at eliminating or minimizing adverse environmental factors that can produce negative effects on demographic situation in the country. Our primary goal was to study impacts exerted by sanitary-epidemiologic parameters on life expectancy in the RF and to obtain predicted values for its growth taking into account regional and sex differentiation. We examined domestic and foreign experience in researching relations between sanitary-epidemiologic welfare and life expectancy. All the RF regions were distributed into three clusters as per their sanitary-epidemiologic welfare. The third cluster that includes 11 regions is in much greater need for implementing activities aimed at reducing environmental contamination. Results obtained via regression and factor analysis revealed that should there be a scenario with an improvement in sanitary-epidemiologic parameters (by 10.0 %), the overall life expectancy for the RF population would increase by 140.39 days. An improvement in sanitary-epidemiologic situation taken as per sex differentiation indicated that a greater impact was expected on life expectancy growth among male population, as it would increase by 146.9 days (by 117.6 days for female population). We established that several parameters made the greatest contribution into life expectancy growth; they were "A share of population provided with high quality drinking water" (61.65 days); "Physical factors existing at workplaces" (35.83 days), "Sanitary-hygienic characteristics of objects under surveillance" (15.16 days), and "Sanitary-epidemiologic parameters of ambient air" (14.26 days). The current work does not cover extreme sanitary-epidemiologic situations related to pandemic spread of new infectious agents causing highly contagious diseases (Coronavirus infection).
The article presents the result produced by predicting growth potential in life expectancy at birth (LEB) of the RF Population. The predictions are based on scenario changes in social and hygienic determinants (SHD) identified by using an artificial neural network (ANN). This research is vital given the existing social strategies aimed at improving the medical and demographic situation in the Russian Federation. These strategies stipulate achieving targets set within the major national and federal projects. We identified an optimal ANN structure based on a four-layer perceptron with two inner layers containing eight and three neurons accordingly. This structure is able to produce results at the highest determination coefficient (R2= 0.78). Differences between actual LEB levels and predicted ones obtained by using the suggested model did not exceed 1.1 % (or 0.8 years). We established that average LEB in the RF would reach 75.06 years (by 2024) provided that the demographic situation in the country recovers in the nearest future, LEB level reaches its values detected in 2018–2019, and SHD values grow to their preset levels according to the target scenario. Therefore, the detected growth potential amounts to 3.0 years (1095 days) against 2018. “Lifestyle-related determinants” produce the greatest effects on the growth potential in LEB by 2024 (461 days). We also identified effects produced by such SHD groups as “Sanitary-epidemiological welfare on a given territory” (212 days), “Social and demographic indicators” (196 days), “Economic indicators” (131 days), “Indicators related to public healthcare” (70 days). An indicator that shows “A share of population doing physical exercises or sports” is the most significant determinant producing the greatest effects on potential changes in LEB. If it grows up to 55.0 %, a potential growth in LEB amounts to 243.5 days. If we do not consider COVID-related processes and rely only on the trends that are being observed now when predicting changes in the demographic situation by 2030, we can expect a possible additional growth in LEB that equals 286 days. The developed algorithm for determining growth potential in population LEB can be used as an instrument for determining and ranking priority health risk factors.
The article contains results of the research on a correlation between social and economic determinants and life expectancy of the RF population. The research is quite relevant at present as it is consistent with the goals set within the demographic policy in the RF, including searching for efficient tools aimed at solving tasks set in it and achieving its targets. Our research goal was to examine social and economic determinants and potential for a growth in life expectancy of the RF population taking into account regional differentiation.We analyzed world experience in examining effects produced by social and economic factors on life expectancy. Correlationregression analysis allowed us to detect that economic parameters, lifestyle-related ones, and parameters reflecting education and home comforts were the most significant modifiers (R 2 =0.06-0.43). We showed that aggregated changes in these parameters equal to 10.0 % could result in 460.5 days increase in life expectancy (1.3 years longer). The greatest contribution was made by population employment/unemployment taking into account their education (115.29 days); home comforts available in housing (86.9 days); economic parameters (74.09 days); psychosocial stress (54.58 days); alcohol drinks sales (49.57 days); basic food products consumption (46.23 days). These data are fully consistent with the already known results obtained by domestic and foreign researchers in the field and efficiently complement them. Our research results indicate that the current social policy that is being implemented in the RF is quite relevant as it is aimed at reducing social and economic inequality and eliminating a social gradient as regards health of various population groups. We are also sure it is necessary to perform further research in the sphere.
The present research focuses on estimating influence exerted by weather and climatic factors on life expectancy (LE) in the Russian Federation taking into account socioeconomic and sanitary-epidemiologic determinants. To estimate influence exerted by this factor on LE, a mathematic model was applied; the model was based on neuron networks and allowed taking into account emergence and variability of influence exerted on changes in LE by a set of heterogeneous factors including weather and climatic ones. It was established that over 2010–2018 climate changed in most RF regions as there was a growth in average monthly temperatures (temperature deviated from its long-term average monthly values by +1.2ºС in July, and by +1,5ºС in January),and changes in precipitations (deviations amounted to -1.9% in July and +13.0% in January). It was established that «average monthly temperature in July» exerted the greatest direct influence on LE; thus, if this parameter grows by 1%, it results in additional 1.7 days of LE. «Average precipitations quantity in January» turned out to be the most significant factor leading to a decrease in LE; a 1% growth in this parameter resulted in LE decrease by 0.12 days. It was shown that mathematical expectancy of LE loss variability in RF regions obtained basing on 85 scenarios of weather and climatic conditions ranged from -4.2 days to 348.7 days. Overall in the RF climate-associated losses in LE taken as weighted average as per population number amounted to 191.7 days. It was established that climate-associated losses in LE were authentically lower in North Caucasian regions than in regions located in temperate zone with Atlantic-continental and continental climate (by 1.6 and 1.8 times accordingly). We also comparatively analyzed losses in LE due to influence exerted by climate in RF regions distributed into different groups (clusters) as per socioeconomic parameters; the analysis revealed authentic differences between the second and the fourth cluster (p=0.01), and between the third and the fourth ones (p=0.006). We didn’t reveal any authentic differences in climate-associated losses in LE among clusters as per sanitary-epidemiologic parameters.
Introduction. At present it is especially vital to search for and test new analytical systems that can give a possibility to predict a medical and demographic situational lowing for multifactorial influence exerted by the environment. Our research goal was to establish regional peculiarities and predictive estimates of potential gain in such an important indicator as life expectancy at birth (LEB) depending on changes in socio-hygienic determinants potent of modifying it. To do that, we took data collected in a RF region where the current demographic situation was rather tense against the backdrop of stable economic conditions. Materials and methods. A potential of the gain in LEB was estimated by modelling cause-effects relations between environmental indicators and life-style related ones, or determinants that determined population health. Models were created by using artificial neural networks. Results. Our methodology was proven to be optimal and precise (differences are equal to 0.98%). It can be applied quite successfully to predict a potential gain in LEB at a regional level together with identifying what modifying factors should be considered priority ones. LEB on the analyzed territory (the Perm region) was established to likely grow by 661.6 days by 2024 and reach 73.12 years; by 855.7 days by 2030 and reach 73.65 years if the current trends related to changes in the analyzed determinants persisted and the achievement of target indicators of national projects and regional development programs. In case the relevant targets set within national projects and regional development programs were achieved, this indicator would grow by 661.6 days and reach 73.12 years. The most significant groups of factors that determine LEB on the analyzed territory against the backdrop of stable economic situation include sanitary-epidemiological welfare (working conditions et al.), public healthcare indicators (population provided with sufficient number of doctors), sociodemographic indicators (expenses on social policies), lifestyle factors (the proportion of the population involved in physical culture and sports; consumption of vegetables and fruits; retail sales of alcoholic beverages, etc.). Their contribution to the gain in LEB varies from 51.2 to 228.6 days. Limitations. Limitations of the study include the model being “stationary” due to its training relying on data collected in 2010-2019; use of a specific set of indicators; failure to consider the influence exerted by the current epidemiological processes (the COVID-19 pandemics). Conclusion. We analyzed data collected in an RF region with a rather tense demographic situation and established that by 2024 an adjusted target LEB value would be achieved there if the trend in changes in socio-hygienic determinants recovered to its pre-pandemic levels. Achievement of target LEB values by 2030 requires additional project activities that consider specific regional features and focus on managing priority determinants and reducing mortality among working age population.
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