Russia's capital, Moscow, was the largest city in the country with over **** million residents as of January 1, 2024. Less than a half of Moscow's population resided in Saint Petersburg, the second-most populous city in the country. The third-largest city, Novosibirsk, was located in the Siberian Federal District, being the highest-populated city in the Asian part of Russia. Why is Moscow so populated? The Russian capital is the center of political, industrial, business, and cultural life in Russia. Despite being one of the most expensive cities worldwide, it continues to attract people from Russia and abroad, with its resident population following a generally upward trend over the past decade. Wages in Moscow are higher than in Russia on average, and more opportunities for employment and investment are available in the capital. Furthermore, the number of people living in Moscow was forecast to continue rising, exceeding **** million by 2035. Urbanization in Russia In 2024, around *** million Russian residents lived in cities. That was approximately three-quarters of the country’s population. The urbanization rate increased steadily over the 20th century, leading to a decline in the rural population. Among the country’s regions, the Northwestern Federal District had the highest share of residents in urban areas, measured at ** percent. In the Central Federal District, the tendency was that more people moved to Moscow and cities in the Moscow Oblast.

Among Russian cities with more than one million inhabitants, the country's capital Moscow received the highest urban environmental quality index score of *** out of 360 points in 2024, based on six criteria and six types of area. The second-leading city in this category was Saint Petersburg, Russia's second-largest city, while Kazan ranked third.

This database provides construction of Large Urban Regions (LUR) in Russia. A Large Urban Region (LUR) can be defined as an aggregation of continuous statistical units around a core that are economically dependent on this core and linked to it by economic and social strong interdependences. The main purpose of this delineation is to make cities comparable on the national and world scales and to make comparative social-economic urban studies. Aggregating different municipal districts around a core city, we construct a single large urban region, which allows to include all the area of economic influence of a core into one statistical unit (see Rogov & Rozenblat, 2020 for more details) thus, changing a city position in a global urban hierarchy. In doing so we use four principal urban concepts (Pumain et al., 1992): political definition, morphological definition, functional definition and conurbation that we call Large Urban Region. We constructed Russian LURs using criteria such as population distribution, road networks, access to an airport, distance from a core, presence of multinational firms. In this database, we provide population data for LURs and their administrative units.

Population in largest city in Russia was reported at 12712305 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Russia - Population in largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

On Sunday, September 12, 2021, the highest self-isolation index among Russian cities with over one million inhabitants was measured in Omsk at 2.8 points, indicating that there was a high number of people on the streets. In the capital Moscow, where most COVID-19 cases in Russia were recorded, the index reached two points. The non-working period in Russia ended on May 12, 2020.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Population in the largest city (% of urban population) in Russia was reported at 11.76 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Russia - Population in the largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

Among Russian cities with 100,000 to 250,000 inhabitants, Reutov, located in the Moscow Oblast, received the highest urban environmental quality index score of 301 out of 360 points in 2024, based on six criteria and six types of area. The second-leading city in this category was Krasnogorsk.

With a score of 23.62, Moscow was the leading city for startups in Russia in 2024. Saint Petersburg followed, having earned a score of 1.66 in the period observed. Furthermore, the Russia's capital ranked the major city for startups in Central and Eastern Europe (CEE). The score was based on several indicators, such as the number of startups in each city, the startups' qualitative results, and the cities' business and economic indicators.

Two Russian cities were included in the Top 100 Super Cities list of Tholons Globalization Services Index in 2020. The capital Moscow was the most attractive for business innovations in the country, ranked 23rd worldwide in 2019 and improving its position reaching 18 on the list by 2020. Russian second largest city Saint Petersburg was placed 51st. The rank of Saint Petersburg dropped by almost 20 positions compared to the previous year.

As of September 2020, Moscow had the biggest amount of public routes, among which the largest number was accounted for bus routes and tram lines. The Russian northern capital Saint Petersburg, followed next with a total number of 838 routes of public transport.

Russia Number of Foreign Capital Enterprises: BM: CF: City of Moscow data was reported at 4,047.000 Unit in Dec 2016. This records an increase from the previous number of 3,882.000 Unit for Sep 2016. Russia Number of Foreign Capital Enterprises: BM: CF: City of Moscow data is updated quarterly, averaging 3,473.000 Unit from Jun 2000 (Median) to Dec 2016, with 67 observations. The data reached an all-time high of 4,751.000 Unit in Dec 2012 and a record low of 2,046.000 Unit in Mar 2014. Russia Number of Foreign Capital Enterprises: BM: CF: City of Moscow data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Investment – Table RU.OE001: Number of Foreign Capital Enterprises: Big and Medium: by Region (Discontinued).

The data is to evaluate the impact of restrictive measures introduced in connection with COVID-19 on consumption and, accordingly, on electricity generation in Russian cities, which were most susceptible to outbreaks of the coronavirus infection (Moscow, St. Petersburg, Yekaterinburg and Nizhny Novgorod). Currently, based on available data, the mobility of the population has decreased resulting in lower demand for electricity during self-isolation. Therefore, the study will be based on the hypothesis that similar changes in human behavior can be expected in the future with further spread of COVID-19 and/or the introduction of additional quarantine measures in major cities around the world. The analysis also yielded additional results: the strongest reductions in energy generation occurred in cities with high building density (7% in Moscow, 14% in Yekaterinburg). Furthermore, the decrease in energy generation in cities with low building density was not so dramatic (1% in St. Petersburg, 0% - Nizhny Novgorod). The study uses two models created with Keras LSTM. The first model forecasts power generation and uses 76 parameters. The second LSTM model forecasts new COVID-19 cases across countries, in which 10 parameters are involved.

Russia Number of Employees: Foreign Capital Enterprises: BM: CF: City of Moscow data was reported at 545.700 Person th in Dec 2016. This records an increase from the previous number of 542.000 Person th for Sep 2016. Russia Number of Employees: Foreign Capital Enterprises: BM: CF: City of Moscow data is updated quarterly, averaging 514.800 Person th from Jun 2000 (Median) to Dec 2016, with 67 observations. The data reached an all-time high of 681.200 Person th in Dec 2012 and a record low of 146.000 Person th in Jun 2000. Russia Number of Employees: Foreign Capital Enterprises: BM: CF: City of Moscow data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Investment – Table RU.OE002: Number of Employees in Foreign Capital Enterprises: Big and Medium: by Region (Discontinued).

Among Russian cities with 250,000 to one million inhabitants, Tyumen received the highest urban environmental quality index score of *** out of 360 points in 2024, based on six criteria and six types of area. Ryazan and Yaroslavl followed with scores of *** and *** points, respectively.

About this dataset

Context

The dataset tabulates the Russia median household income by race. The dataset can be utilized to understand the racial distribution of Russia income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Russia, OH median household income breakdown by race betwen 2011 and 2021
• Median Household Income by Racial Categories in Russia, OH (2021, in 2022 inflation-adjusted dollars)

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Russia median household income by race. You can refer the same here

Russia Number of Foreign Capital Enterprises: BM: NW: City of St Petersburg data was reported at 1,605.000 Unit in Dec 2016. This records an increase from the previous number of 1,589.000 Unit for Sep 2016. Russia Number of Foreign Capital Enterprises: BM: NW: City of St Petersburg data is updated quarterly, averaging 777.000 Unit from Jun 2000 (Median) to Dec 2016, with 67 observations. The data reached an all-time high of 1,605.000 Unit in Dec 2016 and a record low of 564.000 Unit in Mar 2001. Russia Number of Foreign Capital Enterprises: BM: NW: City of St Petersburg data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Investment – Table RU.OE001: Number of Foreign Capital Enterprises: Big and Medium: by Region (Discontinued).

Loss Amount: Big & Medium Enterprises: Year to Date: SF: City of Sevastopol data was reported at 2,905.000 RUB mn in Jul 2023. This records an increase from the previous number of 2,599.000 RUB mn for Jun 2023. Loss Amount: Big & Medium Enterprises: Year to Date: SF: City of Sevastopol data is updated monthly, averaging 1,118.626 RUB mn from Jan 2015 (Median) to Jul 2023, with 103 observations. The data reached an all-time high of 5,702.000 RUB mn in Jan 2023 and a record low of 273.615 RUB mn in Jan 2018. Loss Amount: Big & Medium Enterprises: Year to Date: SF: City of Sevastopol data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Investment – Table RU.OD008: Enterprises Balance (Profit less Loss): Big and Medium: ytd: Loss: by Region.

Large Towns of the Russian Empire, as depicted on the Geographical Atlas of the Russian Empire produced by the Military-Topographical Depot of His Imperial Majesty's General Staff, 1820-1827. Component of the Imperiia Project. Documentation and analysis available here (http://dighist.fas.harvard.edu/projects/imperiia/items/show/649)

Customers of bookstores located in Moscow and Saint Petersburg spent more than those in other regions of Russia in January 2023. Over 60 percent of consumers in the country's two largest cities spent at least 501 Russian rubles on average in bookstores, while the largest share of buyers in other localities nationwide expended less than 300 Russian rubles.

Data format and access

The database consists of full-text patient reviews, reflecting their dissatisfaction with healthcare quality. Materials in Russian have been posted in the «Review list» of the site infodoctor.ru. Publication period: July 2012 to August 2023. The database consists of 18,492 reviews covering 16 Russian cities with population of over one million. Data format: .xlsx.

Data access: 10.5281/zenodo.15257447

Data collection methodology

Based on the fact that negative reviews may be more reliable than positive ones, the authors carried out negative reviews from 16 Russian cities with a population of over one million, for which it was possible to collect representative samples (at least 1000 reviews for each city). We have extracted reviews from the one-star section of this site's guestbook, as they are reliably identified as negative. Duplicates were removed from the database. Personal data in comment texts have been replaced with "##########". The author's gender was determined manually based on his/her name or gender endings in the texts of reviews. Otherwise, we indicated "0" - gender cannot be determined.

For Moscow reviews, classification was carried out using manual markup methods - based on the majority of votes for the review class from 3 annotators (if at least one annotator indicated that it was impossible to determine, the review was classified as #N/A - impossible to clearly determine). For reviews from other cities, classification was made into 3 classes using machine learning methods based on logistic regression. The classification accuracy was 88%.

The medical specialties were distributed into large groups for the convenience of further analysis. The correspondence of medical specialties to large groups is presented in detail in Appendix 1.

Sample structure and description of variables

· CITY – the name of a city with a population of over a million (on a separate sheet – Moscow), the other 15 are Volgograd, Voronezh, Yekaterinburg, Kazan, Krasnodar, Krasnoyarsk, Nizhny Novgorod, Novosibirsk, Omsk, Perm, Rostov-on-Don, Samara, St. Petersburg, Ufa, Chelyabinsk

· TEXT – review text

· GENDER – gender of the review author (2 – female, 1 – male, 0 – cannot be determined)

· CLASS_1 – group of reasons for dissatisfaction with medical care (M – issues of medical content, O – issues of organizational support and economic aspect, C – mixed (combined) class, #N/A – cannot be clearly determined)[1]

· CLASS_2 – group of reasons for dissatisfaction with medical care (0 – issues of medical content, 1 – issues of organizational support and economic aspect, 2 – mixed (combined) class, #N/A – cannot be clearly determined)

· DAY – day of the month the review was posted

· MONTH – month the review was posted

· YEAR – year the review was posted

· DOCTOR_OR_CLINIC – what or who is the review dedicated to – the doctor or the clinic

· SPEC – physician specialty (for observations where the review is dedicated to the physician)

· GROUP_SPEC – a large group of a physician’s specialty

· ID – observation identifier

Database application

The data are suitable for analyzing patient dissatisfaction trends with medical services in Russia over the period from July 2012 to August 2023. This dataset could be particularly useful for healthcare providers, policymakers, and researchers interested in understanding patient experiences and identifying areas for quality improvement in Russian healthcare. Some potential applications include:

• Analyzing geographic patterns of patient complaints across different cities in Russia
• Examining trends in patient dissatisfaction over time
• Identifying common reasons for dissatisfaction with medical care
• Comparing dissatisfaction levels between different medical specialties
• Assessing gender differences in patient complaints

The database provides rich qualitative data through full-text review texts, allowing for in-depth analysis of patient experiences. The structured variables like city, date, doctor/clinic information, etc. enable quantitative analysis as well. This combination of qualitative and quantitative data makes it possible to gain a comprehensive understanding of patient dissatisfaction patterns in Russia's healthcare system over more than a decade.

For researchers specifically interested in healthcare quality issues, this dataset could serve as an important resource for studying patient experiences and outcomes in Russia's medical system. The longitudinal nature of the data (2012-2023) also allows for analysis of changes over time in patient satisfaction.

Overall, this database provides valuable insights into patient perceptions of healthcare quality that could inform policy decisions, quality improvement