Interregional differences of life expectancy in rural Russia - Assessment of socio-economic, demographic, behavioural and ecological factors
The article is aimed at studying the effects of social, economic, demographic, behavioural and environmental factors on the life expectancy of rural people in different types of regions. Using cluster analysis, we identified four relatively homogeneous groups of Russian regions in terms of life expectancy. The impact of socio-economic, demographic and environmental indicators on life expectancy of the rural population was assessed using regression models. We identified regions with low life expectancy for the rural population, and factors that have negative effect on life expectancy at birth. The main ones were alcohol abuse, high unemployment and emissions of pollutants into the air. The regression analysis showed that investments aimed at the development of health care, provision of social services and improvement of residential premises contributed to an increase in life expectancy. Significant factors in regions with high life expectancy were a lower number of recorded crimes per 100,000 of the population and a decrease in high unemployment, as well as an increase in educational expenses. In the group of regions where life expectancy of the rural population was approaching the average level in Russia, an important factor was also an increase in the level of education. We conclude that a regionally differentiated approach is necessary when introducing social policy changes, and measures aimed at increasing the life expectancy of the rural population should take into account the distinctive differences in socioeconomic development of the various regions of Russia.
Barlow R, Vissandjee B, 1999. Determinants of national life expectancy. Can J Dev Stud 20:9-28. DOI: https://doi.org/10.1080/02255189.1999.9668787
Bayati M, Akbarian R, Kavosi Z, 2013. Determinants of life expectancy in Eastern Mediterrane-an Region: a health production function. Int J Health Policy Manage 1:57-61. DOI: https://doi.org/10.15171/ijhpm.2013.09
Bilas V, Franc S, Bošnjak M, 2014. Determinant factors of life expectancy. Coll Antropol 38:1-9.
Blinova T, Bylina S, Rusanovskiy V, 2020. Factors affecting the life expectancy at birth of the rural population in Russia. Ponte 78:9-18. DOI: https://doi.org/10.21506/j.ponte.2020.1.2
Canudas-Romo V, Becker S, 2011.The crossover between life expectancies at birth and at age one: the imbalance in the life table. Demogr Res 24:113-44. DOI: https://doi.org/10.4054/DemRes.2011.24.4
Chou AK, Chen D-R, 2019. Socioeconomic status and deaths due to unintentional injury among children: A socio-spatial analysis in Taiwan. Geospat Health 14:25-34. DOI: https://doi.org/10.4081/gh.2019.736
Costa-Font J, Hernandez-Quevedo C, 2012. Measuring inequalities in health: what do we know? What do we need to know? Health Policy 106:195-206. DOI: https://doi.org/10.1016/j.healthpol.2012.04.007
Cutler D, Lleras-Muney A, 2010. Understanding differences in health behaviours by education. J Health Econ 29:1-28. DOI: https://doi.org/10.1016/j.jhealeco.2009.10.003
Duque AM, Peixoto MV, Lima SVMA, Goes MAO, Santos AD Araújo KCGM, Nunes MAP, 2019. Analysis of the relationship between life expectancy and social determinants in a north-eastern region of Brazil, 2010-2017. Geospat Health 13:345-52. DOI: https://doi.org/10.4081/gh.2018.702
Footman K, Roberts B, Mills A, Richardson E, McKee M, 2013. Public satisfaction as a meas-ure of health system performance: a study of nine countries in the former Soviet Union. Health Policy 112:62-9. DOI: https://doi.org/10.1016/j.healthpol.2013.03.004
Higuchi S, Moriguchi Y, Tan KHX, 2020. Psychometric validation of the Japanese version of alcohol quality of life scale (AQoLS-Japan) in the treatment of patients with alcohol use disorder. Qual Life Res 1:223-35. DOI: https://doi.org/10.1007/s11136-019-02310-w
Hilz R, Wagner M, 2018. Marital status, partnership and health behaviour: findings from the German Ageing Survey (DEAS). Comp Popul Stud 43:65-98. DOI: https://doi.org/10.12765/CPoS-2018-08
Kelly M, Barker M, 2016. Why is changing health-related behaviour so difficult? Public Health 136:109-16. DOI: https://doi.org/10.1016/j.puhe.2016.03.030
Marmot M, Wilkinson, RG (Eds.), 2006. Social determinants of health. Oxford University Press, Oxford, UK, pp 376. DOI: https://doi.org/10.1093/acprof:oso/9780198565895.001.0001
Ministry of Health Care of the Russian Federation, 2018. National project “Health care”. Avail-able from: http://government.ru/info/35561/
Nixon J, Ulmann P, 2006.The relationship between health care expenditure and health outcomes. Eur J Health Econ 7:7-18. DOI: https://doi.org/10.1007/s10198-005-0336-8
Rayhan I, Hasan R, Akter M, 2019. Estimating Health Production Function for the South Asian Countries. Int J Econometr Financial Manage 7:12-9.
Rosstat, 2018a. Regions of Russia. Socio-economic indicators. 2018: statistical book. Rosstat, Moscow, Russia.
Rosstat, 2019b. Russian statistical yearbook. 2018: statistical book. Rosstat, Moscow, Russia.
Rosstat, 2019a. Russia in Figures. 2019: statistical handbook. Rosstat, Moscow, Russia.
Rosstat, 2019b. Demographic yearbook of Russia. 2019: statistical book. Rosstat, Moscow, Russia.
Robards J, Falkingham J, Evandrou M, Vlachantoni A, 2012. Marital status, health and mortali-ty. Maturit 73:295-9. DOI: https://doi.org/10.1016/j.maturitas.2012.08.007
Sasson I, 2016. Trends in life expectancy and lifespan variation by educational attainment: Unit-ed States, 1990-2010. Demography 53:269-93. DOI: https://doi.org/10.1007/s13524-015-0453-7
Shkolnikov V, Andreev E, McKee M, Leon D, 2013. Components and possible determinants of decrease in Russian mortality in 2004-2010. Demogr Res 28:917-50. DOI: https://doi.org/10.4054/DemRes.2013.28.32
Shaw JW, Horrace WC, Vogel RJ, 2005. The determinants of life expectancy: an analysis of the OECD Health Data. South Econ J 71:768-83. DOI: https://doi.org/10.2307/20062079
Wilkinson R, Marmot M, 2003. Social determinants of health: the solid facts. 2nd ed. World Health Organization, Geneva, Switzerland, Publ. no. 31.
Yeom Y, 2019. Population-level alcohol consumption and suicide mortality rate in South Korea: An application of multivariable spatial regression model. Geospat Health 14:163-70. DOI: https://doi.org/10.4081/gh.2019.746
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