Russia Population: 100 Years and Older data was reported at 17,580.000 Person in 2017. This records an increase from the previous number of 15,703.000 Person for 2016. Russia Population: 100 Years and Older data is updated yearly, averaging 7,993.000 Person from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 17,580.000 Person in 2017 and a record low of 5,814.000 Person in 1997. Russia Population: 100 Years and Older data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Demographic and Labour Market – Table RU.GA005: Population: by Age: 0 to 100 Years.

This statistic depicts the age distribution of Russia from 2013 to 2023. In 2023, about 17.51 percent of Russia's population fell into the 0-14 year category, 65.88 percent into the 15-64 age group and 16.6 percent were over 65 years of age.

Russia Population: Male: 100 Years and Older data was reported at 5,892.000 Person in 2018. This records an increase from the previous number of 4,743.000 Person for 2017. Russia Population: Male: 100 Years and Older data is updated yearly, averaging 1,389.000 Person from Dec 1990 (Median) to 2018, with 29 observations. The data reached an all-time high of 5,892.000 Person in 2018 and a record low of 1,003.000 Person in 2002. Russia Population: Male: 100 Years and Older data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Demographic and Labour Market – Table RU.GA006: Population: by Age: 0 to 100 Years: Male.

In all age groups until 29 years old, there were more men than women in Russia as of January 1, 2024. After that age, the female population outnumbered the male population in each category. The most represented age group in the country was from 35 to 39 years old, with approximately *** million women and *** million men. Male-to-female ratio in Russia The number of men in Russia was historically lower than the number of women, which was a result of population losses during World War I and World War II. In 1950, in the age category from 25 to 29 years, ** men were recorded per 100 women in the Soviet Union. In today’s Russia, the female-to-male ratio in the same age group reached *** women per 1,000 men. Russia has the highest life expectancy gender gap The World Health Organization estimated the average life expectancy of women across the world at over five years longer than men. In Russia, this gap between genders exceeded 10 years. According to the study “Burden of disease in Russia, 1980-2016: A systematic analysis for the Global Burden of Disease Study 2016,” Russia had the highest gender difference in life expectancy worldwide.

A data set of cross-nationally comparable microdata samples for 15 Economic Commission for Europe (ECE) countries (Bulgaria, Canada, Czech Republic, Estonia, Finland, Hungary, Italy, Latvia, Lithuania, Romania, Russia, Switzerland, Turkey, UK, USA) based on the 1990 national population and housing censuses in countries of Europe and North America to study the social and economic conditions of older persons. These samples have been designed to allow research on a wide range of issues related to aging, as well as on other social phenomena. A common set of nomenclatures and classifications, derived on the basis of a study of census data comparability in Europe and North America, was adopted as a standard for recoding. This series was formerly called Dynamics of Population Aging in ECE Countries. The recommendations regarding the design and size of the samples drawn from the 1990 round of censuses envisaged: (1) drawing individual-based samples of about one million persons; (2) progressive oversampling with age in order to ensure sufficient representation of various categories of older people; and (3) retaining information on all persons co-residing in the sampled individual''''s dwelling unit. Estonia, Latvia and Lithuania provided the entire population over age 50, while Finland sampled it with progressive over-sampling. Canada, Italy, Russia, Turkey, UK, and the US provided samples that had not been drawn specially for this project, and cover the entire population without over-sampling. Given its wide user base, the US 1990 PUMS was not recoded. Instead, PAU offers mapping modules, which recode the PUMS variables into the project''''s classifications, nomenclatures, and coding schemes. Because of the high sampling density, these data cover various small groups of older people; contain as much geographic detail as possible under each country''''s confidentiality requirements; include more extensive information on housing conditions than many other data sources; and provide information for a number of countries whose data were not accessible until recently. Data Availability: Eight of the fifteen participating countries have signed the standard data release agreement making their data available through NACDA/ICPSR (see links below). Hungary and Switzerland require a clearance to be obtained from their national statistical offices for the use of microdata, however the documents signed between the PAU and these countries include clauses stipulating that, in general, all scholars interested in social research will be granted access. Russia requested that certain provisions for archiving the microdata samples be removed from its data release arrangement. The PAU has an agreement with several British scholars to facilitate access to the 1991 UK data through collaborative arrangements. Statistics Canada and the Italian Institute of statistics (ISTAT) provide access to data from Canada and Italy, respectively. * Dates of Study: 1989-1992 * Study Features: International, Minority Oversamples * Sample Size: Approx. 1 million/country Links: * Bulgaria (1992), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/02200 * Czech Republic (1991), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06857 * Estonia (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06780 * Finland (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06797 * Romania (1992), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06900 * Latvia (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/02572 * Lithuania (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03952 * Turkey (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03292 * U.S. (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06219

Abstract (en): The Research on Early Life and Aging Trends and Effects (RELATE) study compiles cross-national data that contain information that can be used to examine the effects of early life conditions on older adult health conditions, including heart disease, diabetes, obesity, functionality, mortality, and self-reported health. The complete cross sectional/longitudinal dataset (n=147,278) was compiled from major studies of older adults or households across the world that in most instances are representative of the older adult population either nationally, in major urban centers, or in provinces. It includes over 180 variables with information on demographic and geographic variables along with information about early life conditions and life course events for older adults in low, middle and high income countries. Selected variables were harmonized to facilitate cross national comparisons. In this first public release of the RELATE data, a subset of the data (n=88,273) is being released. The subset includes harmonized data of older adults from the following regions of the world: Africa (Ghana and South Africa), Asia (China, India), Latin America (Costa Rica, major cities in Latin America), and the United States (Puerto Rico, Wisconsin). This first release of the data collection is composed of 19 downloadable parts: Part 1 includes the harmonized cross-national RELATE dataset, which harmonizes data from parts 2 through 19. Specifically, parts 2 through 19 include data from Costa Rica (Part 2), Puerto Rico (Part 3), the United States (Wisconsin) (Part 4), Argentina (Part 5), Barbados (Part 6), Brazil (Part 7), Chile (Part 8), Cuba (Part 9), Mexico (Parts 10 and 15), Uruguay (Part 11), China (Parts 12, 18, and 19), Ghana (Part 13), India (Part 14), Russia (Part 16), and South Africa (Part 17). The Health and Retirement Study (HRS) was also used in the compilation of the larger RELATE data set (HRS) (N=12,527), and these data are now available for public release on the HRS data products page. To access the HRS data that are part of the RELATE data set, please see the collection notes below. The purpose of this study was to compile and harmonize cross-national data from both the developing and developed world to allow for the examination of how early life conditions are related to older adult health and well being. The selection of countries for this study was based on their diversity but also on the availability of comprehensive cross sectional/panel survey data for older adults born in the early to mid 20th century in low, middle and high income countries. These data were then utilized to create the harmonized cross-national RELATE data (Part 1). Specifically, data that are being released in this version of the RELATE study come from the following studies: CHNS (China Health and Nutrition Study) CLHLS (Chinese Longitudinal Healthy Longevity Survey) CRELES (Costa Rican Study of Longevity and Healthy Aging) PREHCO (Puerto Rican Elderly: Health Conditions) SABE (Study of Aging Survey on Health and Well Being of Elders) SAGE (WHO Study on Global Ageing and Adult Health) WLS (Wisconsin Longitudinal Study) Note that the countries selected represent a diverse range in national income levels: Barbados and the United States (including Puerto Rico) represent high income countries; Argentina, Cuba, Uruguay, Chile, Costa Rica, Brazil, Mexico, and Russia represent upper middle income countries; China and India represent lower middle income countries; and Ghana represents a low income country. Users should refer to the technical report that accompanies the RELATE data for more detailed information regarding the study design of the surveys used in the construction of the cross-national data. The Research on Early Life and Aging Trends and Effects (RELATE) data includes an array of variables, including basic demographic variables (age, gender, education), variables relating to early life conditions (height, knee height, rural/urban birthplace, childhood health, childhood socioeconomic status), adult socioeconomic status (income, wealth), adult lifestyle (smoking, drinking, exercising, diet), and health outcomes (self-reported health, chronic conditions, difficulty with functionality, obesity, mortality). Not all countries have the same variables. Please refer to the technical report that is part of the documentation for more detail regarding the variables available across countries. Sample weights are applicable to all countries exc...

Russia Paid Services Rendered to Population Structure: Social Services to Aged and Disabled data was reported at 0.300 % in Dec 2018. This stayed constant from the previous number of 0.300 % for Sep 2018. Russia Paid Services Rendered to Population Structure: Social Services to Aged and Disabled data is updated quarterly, averaging 0.200 % from Mar 2012 (Median) to Dec 2018, with 28 observations. The data reached an all-time high of 0.300 % in Dec 2018 and a record low of 0.100 % in Sep 2013. Russia Paid Services Rendered to Population Structure: Social Services to Aged and Disabled data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Global Database’s Russian Federation – Table RU.HG009: Paid Services Rendered to Population Structure.

Accessing governmental and municipal services in an electronic form was particularly popular in Russia among young adults, with approximately ** percent of the population aged 25 to 29 years who received public services in the country in 2023. The figures were significantly lower among the elderly people between 60 and 72 years old, measuring at nearly ** percent.

BackgroundIn migration and health research, the healthy migrant effect has been a common finding, but it usually pertains to specific contexts only. Existing findings are inconsistent and inconclusive regarding the cognitive functioning of the (aging) foreign-origin population relative to the populations of their host and sending countries. Moreover, this comparison is an understudied design setting.ObjectiveWe analyze the outcomes and associations of cognitive functioning outcomes of the non-institutionalized middle-aged and older population, comparing the Russian-origin population in Estonia with Estonians in Estonia and Russians in Russia in a cross-sectional design. We aim to estimate the (long-term) effects of migration on cognitive functioning in later life, contextualizing the findings in previous research on the healthy migrant effect.Data and methodsWe use data from face-to-face interviews conducted within the SHARE Estonia (2010–2011) and SAGE Russia (2007–2010) surveys. Respondents aged 50+ living in urban areas were grouped by self-identified ethnicity, including 2,365 Estonians, 1,373 Russians in Estonia, and 2,339 Russians in Russia (total N = 6,077). Cognitive functioning was measured using a 25-percentile cut-off threshold for the results of two cognition outcomes - immediate recall and verbal fluency - and the odds of impairment were estimated using binary logistic regression.ResultsRussian men and women living in Estonia have significantly higher odds of impairment in immediate recall than Estonian men and women, though they do not differ from Russians in Russia in the final adjusted models. The differences between all groups are non-significant if age at migration is considered. There are no significant differences between the groups in verbal fluency.ConclusionContrary to the commonly found healthy migrant effect, the middle-aged and older foreign-origin population in Estonia fares initially worse than the native population in the immediate recall outcome, but does not differ from their sending country population, possibly due to Russia’s higher mortality rate and therefore the selective survival of healthier people. Different results depending on the cognitive functioning outcome suggest that migration may affect temporary memory more than crystallized knowledge. However, there are no differences between the groups if defined based on age at migration, which suggests that the age profile differences explain most of the groups’ differences in cognitive functioning.

In 2022, the largest share of employed persons in Russia were aged from 30 to 39 years, measuring at over ** percent. To compare, 20-to-24-year-old Russians occupied less than **** percent of the total number of people aged 15 years and older employed in the country.

As of October 2024, the largest user share of VKontakte (VK) was aged between 35 and 44 years. The second-major age cluster on the website were 25-to-34 year-olds, occupying around ** percent of the total over the period under consideration. Social media in Russia Russia is one of the leading countries in Europe by social media usage and the volume of active users. Thus, after a consistent annual growth over the last years, the number of active social media users in the country amounted to *** million. Younger people are particularly active on social media, with ** percent of Russians aged between 25 and 34 years using apps and websites for regular communication. VKontakte's growth Following the departure of Meta platforms Facebook and Instagram, as well as Twitter, from the Russian market, the daily audience of VK grew by four million users between February 24 and March 15, 2022. The number of friend requests on the social media in question grew by *** percent, while both feed views and comments increased by more than ** percent. New VK app downloads were particularly noticeable in Russia.