Theory and practice of assessing the quality of life of the population of russia over the current secular interval

Ю.Н. Сергеев, В.П. Кулеш, В.В. Дмитриев

Abstract


The objective of the present work is to develop and evaluate workable models for assessing population life quality (PLQ) in Russia based on the statistical theory of pattern recognition. To this end, the following tasks have been done: 1) developing of an alphabet of classes, which is algorithmically associated with the space of classification characteristics of PQL and gradations thereof (description of classes using characteristics vocabulary); 2) selecting of representative characteristics for assessing PLQ in Russia; 3) formulating and implementing of a series of workable statistical models for assessing PLQ in Russia (construction of recognition algorithms); 4) determining of PLQ classes at different stages of the foreign-policy and domestic socioeconomic development of Russia; and 5) developing of an algorithm for choosing an optimal criterion for PQL estimation out of a range of such criteria and for ranking the criteria according to their practical suitability. The suggested algorithm for PLQ recognition system includes training and recognition subsystems using various pattern recognition criteria: arithmetic mean, geometric mean, weighted mean for mortality factors and weighted mean for significance of life quality parameters. An algorithm for optimal selection of PLQ recognition criteria is proposed. To implement the selection of PLQ, a range of data reflecting the socioeconomic and environmental monitoring of the Russian Empire, the USSR and the Russian Federation in 1910 through 2015 were used. It is shown that the representative characteristics of PLQ in Russia differ from those adopted in the Human Development Index, i.e. life expectancy at birth, per capita gross national income, and expected years of schooling and average years of schooling. The PLQ characteristics representative for Russia are the levels of nutrition and health care and of the pollution of freshwater reservoirs and watercourses. The PLQ assessment algorithms using the weighted mean across the significance of life quality parameters and the weighted mean across the main factors of population mortality proved to be optimal. Apparently, the proposed methodology for assessing PLQ must be applicable to all member states of the Commonwealth of Independent States that emerged after the collapse of the USSR.

Keywords


quality of life, pattern recognition models, representative indicators of the quality of life, Russia


Как процитировать материал

References


Айвазян СА. Сравнительный анализ интегральных характеристик качества жизни населения субъектов Российской Федерации / Препринт # WP/2001/125. М.: ЦЭМИ РАН; 2001.

Беляев ВС. Теория сложных геосистем. Киев: Наукова думка; 1978.

Бобков ВН, Денисов НА, Маликов НС. Оценка качества жизни населения на основе системы социальных стандартов. Уровень жизни населения регионов России. 2009;(6):19-24.

Глухов ВВ, Окрепилов ВВ. Управление качеством жизни. СПб.: Наука; 2008.

Голубев АГ. Парниковые газы, культурные традиции и ожидаемая продолжительность жизни: история с географией. Биосфера 2012;4(4):474-87.

Голубев АГ. Куда нас выводит кривая Престона? Успехи геронтологии. 2018;31(5):616-27.

Гумилев ЛН. Этносфера. История людей и история природы. М.: Экопрос; 1993.

Калабеков ИГ. Россия и страны мира в цифрах. http://kaig.ru/

Кулеш ВП, Сергеев ЮН. Экологическая ниша Хатчинсона как показатель качества жизни населения. Вестник СПбГУ. 2016;7(4):66-81.

Лопатников ЛИ. Экономико-математический словарь: Словарь современной экономической науки. М.: Дело; 2003.

Мартинчик АН. Индексы качества питания как инструмент интегральной оценки рациона питания. Вопросы питания. 2019;88:5-12.

Многокритериальные географо-экологические оценки состояния и устойчивости природных и урбанизированных систем. Дмитриев ВВ, Хованов НВ (ред). Деп. ВИНИТИ 01.09.2000 № деп. 2342В00. https://proxy.library.spbu.ru:3693/item.asp?id=30689943.

Оленьев ВВ, Федоров АП. Глобалистика на пороге XXI века. Вопросы философии. 2003;(4):18-30.

Пастухов ЕВ, Соловьева АА, Волкова ЛД. Антропогенный фактор как ускоритель биотического и геохимического циклов лимнических систем. Пятый съезд Всесоюзного гидробиологического общества.Ч. 2 Куйбышев; 1986. С. 280-1.

Реймерс НФ. Природопользование. Словарь-справочник. М.: Мысль; 1990.

Сергеев ЮН, Лю С. Модели водных экосистем. Имитации антропогенного эвтрофирования водоемов. СПб.: ГеоГраф; 2005.

Сергеев ЮН, Денисенко АВ, Дмитриев ВВ, Кулеш ВП. Модель распознавания образов как инструмент для оценки качества вод Невской губы. Изв. РГО. 2018;150(5S):3-16. DOI: 10.1134/S0869607118050075.

Талалушкина ЮН. Анализ качества жизни населения в России. Экономический анализ: теория и практика. 2014;(2):28-36.

Урланис БЦ. Эволюция продолжительности жизни. М.: Статистика; 1978.

Форрестер Дж. Мировая динамика. М.: Наука; 1978.

Хованов НВ. Анализ и синтез показателей при информационном дефиците. СПб.; 1996.

Хованов НВ. Оценка сложных экономических объектов и процессов в условиях неопределенности: к 95-летию метода сводных показателей АН Крылова. Вестник СПбГУ. 2005;5(1):138-44.

Хит О. Фотосинтез (Физиологические аспекты). М.: Мир; 1972.

Чабан НП. Теория и алгоритмы распознавания образов. М.: МИИГАиК; 2004.

Aivazyan SA. Sravnitelny Analiz Integralnykh Kharakteristik Kachestva Zhizni Naseleniya Subyektov Rossiyskoy Federatsii. [Comparative Analysis of the Integral Characteristics of the Quality of Life of the Population of the Constituent Entities of the Russian Federation]. Preprint WP/2001/125. Moscow: TEMI RAN; 2005. (In Russ.)

Beliayev VS. Teoriya Slozhnykh Gyeosistem. [The Theory of Complex Geosystems]. Kiev: Naukova Dumka; 1978. (In Russ.)

Bobrov VN, Denisov NA, Malikov NS. [Assessment of the quality of life of the population based on the system of social standards]. Uroven Zhizni Naseleniya Regionov Rossii 2009;6:19-24. (In Russ.)

Glukhov VV, Okrepilov VV. Upravleniye Kachestvom Zhizni. [Quality of Life Management]. Saint Petersburg: Nauka; 2008. (In Russ.)

Golubev AG. [Greenhouse gases, cultural traditions and life expectancy: History and geography]. Biosfera. 2012;4:474-87. (In Russ.)

Golubev AG. [Where does the Preston curve take us?]. Uspekhi Gerontologii 2018;31(5):616-27. (In Russ.)

Gumilev LN. Etnosfera. Istoriya Liudey i Istoriya Prirody. [The Ethnosphere. The history of People and the History of Nature]. Moskva: Ekopros; 1993. (In Russ.)

Kaladekov IG. Rossiya i Strany Mira v Tsifrakh. [Russia and the Countries of the World by Numbers]. http://kaig.ru/ (In Russ.)

Kulesh VP, Sergeyev YuN. [Hutchinson's ecological niche as an indicator of the quality of life of the population]. Vestnik Sankt-Peterburgskogo Universiteta. 2006;7(4):66-81. (In Russ.)

Lopatnikov LI. Ekonomiko-Matematicheskiy Slovar’: Slovar’ Sovremennoy Ekonomicheskoy Nauki. Moscow: Delo; 2003.

Martinchik AN. Indices of diet quality as an instrument of the integral assessment of nutritional ration. Voprosy Pitaniya. 2019;88:5-12.

Mnogokriterialnaya Geografoekologicheskaya Otsenka Sostoyaniya i Ustoychivosti Prirodnykh i Urbanizirovannykh Sistem. [Multicriterial Geographic and Ecological Assessments of the State and Sustainability of Natural and Urbanized Systems]. Ed. by Dmitriev VV, Khovanov NV. Dep. VINITI 01.09.2000 № 2342V00. https://proxy.library.spbu.ru:3693/item.asp?id=30689943. (In Russ.)

Olenev VV, Fedorov AP. [Globalistics at the turn of the 21st century]. Voprosy Filosofii. 2003;(5):18-30. (In Russ.)

Pastukhov YeV, Solovyeva AA, Volkova LD. Antropogennye Faktory Kak Uskoritel Bioticheskogo i Geokhimicheskogo Tsiklov Limnitheskikh Sistem. [Anthropogenic factor as an accelerator of biotic and geochemical cycles of limnic systems]. In: 5th Syezd Vsesoyuznogo Gidrobiologitheskogo Obshchestva. Vol. 2. Kuybyshev; 1986. P. 280-1. (In Russ.)

Reymers NF. Prirodopolzovaniye. [Nature Management]. Mоscow: Mysl; 1990. (In Russ.)

Sergeyev YuN, Lu S. Modeli Vodnykh Ekosistem. Imitatsii Antropogennogo Evtrofirovaniya Vodoyemov. [Models of Aquatic Ecosystems. Simulation of Anthropogenic Eutrophication of Water Bodies]. Saint Petersburg: GeoGraf; 2005. (In Russ.)

Sergeyev YuN, Denisenko AV, Dmitriev VV, Kulesh VP. [Pattern recognition model as a tool for assessing water quality of Neva Bay]. Izvestiya RGO.2018;150(5S):3-16. DOI: 10.1134/S0869607118050075. (In Russ.)

TalalushkinaYuN. [Analysis of the quality of life of the population in Russia]. Ekonomicheskiy Analiz Teoriya i Praktika. 2014;2(353):28-36. (In Russ.)

Urlanis BTs. Evoliutsiya Prodolzhitelnosti Zhizni. [Lifespan Evolution]. Moscow: Statistika; 1978. (In Russ.)

Forrester DZh. Mirovaya Dinamika. [World dynamics]. Mocow: Nauka; 1978. (In Russ.)

Khovanov NV. Analiz i Sintez Pokazateley Pri Informatsionnom Defitsite. [Analysis and Synthesis of Indicators upon Information Deficit]. Saint Petersburg; 1996. (In Russ.)

Khovanov NV. [Assessment of complex economic objects and processes in conditions of uncertainty: To the 95th anniversary of the AN Krylov’s method of summary indicators]. Vestnik Sankt-Peterburgskogo Universiteta. 2005;5(1):138-44. (In Russ.)

Khit O. Fotosintez (Fiziologicheskie Aspekty). [Photosynthesis (Physiological Aspects)]. Moscow: Mir; 1972. (In Russ.)

Chaban NP. Teoriya i Algoritmy Raspoznavaniya Obrazov. [Pattern Recognition Theory and Algorithms]. Moscow: MIIGAIK; 2004. (In Russ.)

Bauer RA. Social Indicators. Cambridge, Mass., London: MIT Press; 1966.

Brousmiche D, Occelli F, Genin M, Cuny D, Deram A, Lanier C. Spatialized composite indices to evaluate environmental health inequalities: Meeting the challenge of selecting relevant variables. Ecological Indicators. 2020;111:106023.

Dmitriev VV, Kaledin NV. Russian Northwest: An integral assessment of the conditions of regional social, environmental and economic systems and quality of life. Baltic Region. 2016;8(2):87-98. DOI: 10.5922/2079-8555-2016-2-7.

Dmitriev V, Kulesh V, Sergeev Yu. Integral Assessment of the Sustainability of Socio-Ecological and Economic Systems and the Quality of Life of the Population in the Regions of the Arctic Zone of the Russian Federation. IOP Conf. Ser. Earth Environ. Sci. Vol. 302. IOP Publishing; 2019. DOI:10.1088/1755-1315/302/1/012135.

Galbraith JK. The Affluent Society. Boston: Houghton Mifflin; 1958.

Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388:1459-544. doi:10.1016/s0140-6736(16)31012-1.

Meadows DL, Meadows DH. Dynamics of Growth in a Finite World: Cambridge (Mass): Wright Allen Press Inc; 1974.

HELCOM. The fifth Baltic Sea Pollution Load Compilation (PLC-5). Baltic Sea Environment Proc. № 2011a.

HELCOM. Eutrophication Status of the Baltic Sea 2007-2011. A Concise Thematic Assessment of Baltic Sea Environment. 2011.

Odum EP Fundamentals of Ecology. W. B. Saunders Company, Philadelphia-London-Toronto; 1971.

Preston SH. The changing relation between mortality and level of economic development. Population Studies. 1975;29: 231-48.

Starodubov V et al. The burden of disease in Russia from 1980 to 2016: a systematic analysis for the Global Burden of Disease Study. The Lancet. 2016;392:1138-46. doi:10.1016/S0140-6736(18)31485-5.

Wheatcroft SG. (1999) The Great Leap Upward: Anthropometric Data and indicators of crises and secular change in Soviet welfare levels, 1880-1960. Slavic Review. 1999;58:27-60.




DOI: http://dx.doi.org/10.24855/biosfera.v13i3.590

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