Jakovljevic Mihajlo, Kozlova Olga, Makarova Maria, Neklyudova Natalia, Pyshmintseva Olga
Institute of Advanced Manufacturing Technologies, Peter the Great St. Petersburg Polytechnic University, 195251 St Petersburg, Russia.
Institute of Comparative Economic Studies, Hosei University, Tokyo 194-0298, Japan.
Healthcare (Basel). 2023 May 22;11(10):1507. doi: 10.3390/healthcare11101507.
This study's relevance lies in the need to assess the role of socioeconomic, medical, and demographic factors on working-age population mortality in Russia. The purpose of this study is to substantiate the methodological tools for the assessment of the partial contribution of the most important factors that determine the dynamics of the mortality of the working-age population. Our hypothesis is that the factors determining the socioeconomic situation in the country affect the level and dynamics of mortality of the working-age population, but to a different extent in each separate period. To analyse the impact of the factors, we used official Rosstat data for the period from 2005 to 2021. We used the data that reflect the dynamics of socioeconomic and demographic indicators, including the dynamics of mortality of the working-age population in Russia as a whole and in its 85 regions. First, we selected 52 indicators of socioeconomic development and then grouped them into four factor blocks (working conditions, health care, life security, living standards). To reduce the level of statistical noise, we carried out a correlation analysis, which allowed us to narrow down the list to 15 key indicators with the strongest association with the mortality rate of the working-age population. The total period of 2005-2021 was divided into five segments of 3-4 years each, characterising the picture of the socioeconomic state of the country during the period under consideration. The socioeconomic approach used in the study made it possible to assess the extent to which the mortality rate was influenced by the indicators adopted for analysis. The results of this study show that over the whole period, life security (48%) and working conditions (29%) contributed most to the level and dynamics of mortality in the working-age population, while factors determining living standards and the state of the healthcare system accounted for much smaller shares (14% and 9%, respectively). The methodological apparatus of this study is based on the application of methods of machine learning and intelligent data analysis, which allowed us to identify the main factors and their share in the total influence on the mortality rate of the working-age population. The results of this study show the need to monitor the impact of socioeconomic factors on the dynamics and mortality rate of the working-age population in order to improve the effectiveness of social programme. When developing and adjusting government programmes to reduce mortality in the working-age population, the degree of influence of these factors should be taken into account.
本研究的意义在于有必要评估社会经济、医疗和人口因素对俄罗斯劳动年龄人口死亡率的作用。本研究的目的是证实用于评估决定劳动年龄人口死亡率动态变化的最重要因素的部分贡献的方法工具。我们的假设是，决定该国社会经济状况的因素会影响劳动年龄人口的死亡率水平和动态变化，但在每个不同时期的影响程度有所不同。为了分析这些因素的影响，我们使用了俄罗斯国家统计局2005年至2021年期间的官方数据。我们使用了反映社会经济和人口指标动态变化的数据，包括俄罗斯整体及其85个地区劳动年龄人口的死亡率动态变化。首先，我们选取了52个社会经济发展指标，然后将它们分为四个因素组（工作条件、医疗保健、生活保障、生活水平）。为了降低统计噪声水平，我们进行了相关性分析，这使我们能够将指标清单缩小到与劳动年龄人口死亡率关联最强的15个关键指标。2005年至2021年的整个时期被分为五个时间段，每个时间段为3至4年，描绘了所考虑时期该国的社会经济状况图景。本研究中使用的社会经济方法使得能够评估所采用的分析指标对死亡率的影响程度。本研究结果表明，在整个时期内，生活保障（48%）和工作条件（29%）对劳动年龄人口死亡率的水平和动态变化贡献最大，而决定生活水平和医疗保健系统状况的因素所占份额要小得多（分别为14%和9%）。本研究的方法体系基于机器学习和智能数据分析方法的应用，这使我们能够识别主要因素及其在对劳动年龄人口死亡率的总体影响中所占份额。本研究结果表明，有必要监测社会经济因素对劳动年龄人口动态变化和死亡率的影响，以提高社会项目的有效性。在制定和调整政府降低劳动年龄人口死亡率的项目时，应考虑这些因素的影响程度。
