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Socio-economic Indicators and Death Rates from Road Accidents in the Regions of Russia

Student: Kalanep Yuliya

Supervisor: Valeriy Yumaguzin

Faculty: Faculty of Social Sciences

Educational Programme: Demography (Master)

Year of Graduation: 2018

The paper studies the problem of mortality from road accidents, the study contains an interesting approach, the study of the topic occurs by combining several spheres of society. The study is based on socio-economic and demographic statistics and calculations. The main goal of the work is to study the relationship between socio-economic indicators and mortality from road accidents in the regions of Russia. The object of the study is the socio-economic situation of the regions and the death rate of the population from road accidents, and the subject is the relationship between socio-economic conditions and the death rate of the population from road accidents. As the basic data of the study, the requested mortality data for individual causes of road accidents for the period from 2011 to 2016 by regions of Russia from Rosstat. For the study, the demographic indicators of mortality for the regions of Russia for men and women were calculated for the period from 2011 to 2016: the average age of death from the individual death causes studied and the standardized death rates, and the decomposition method was also studied. To solve the set goal of the work, the correlation analysis and regression analysis were performed, on regional data, the Preston curve was tested, and the Smeed’s model on the dependence of transport and mortality from road accidents. As a result of the study, we found that the main contribution to reducing the mortality from road accidents was made by age groups of 10-14 years in men and 15-19 years in women. We found out that there is a relationship between socio-economic indicators and demographic variables, as a result, we succeeded in creating prediction models for demographic indicators of mortality from road traffic causes, which can describe from 9% to 50% of cases. This work was done for the first time and besides it has a large data coverage, includes different methods of study, thereby creating its own uniqueness.

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