Single-industry municipalities with the most difficult socio-economic situation
These data show the population of monotowns in the most difficult socio-economic situations from 2017 to 2021. The table includes 383 municipalities, providing annual population figures for each. Rows are categorized by region and city name, allowing for comparison of trends within and between different monotowns. The indicator is presented on an annual basis over a five-year period, enabling the tracking of changes for each city
- Amur Region — urban okrug — Svobodny — Population of working age as of 1 January
- Amur Region — Svobodny — Population of working age as of 1 January
- Amur Region — urban okrug — town of Raichikhinsk — Population of working age as of 1 January
- Arkhangelsk Region — Onezhskoye urban locality — Population of working age as of 1 January
- Arkhangelsk Region — Onega — Population of working age as of 1 January
- Amur Region — Raychikhinsk — Population of working age as of 1 January
- Vladimir Region — Kameshkovo urban locality — Population of working age as of 1 January
- Vladimir Region — town of Kameshkovo — Population of working age as of 1 January
- Vladimir Region — urban settlement of Gorokhovets town — Population of working age as of 1 January
- Vladimir Region — town of Gorokhovets — Population of working age as of 1 January
Population chart of monotowns in the most difficult socio-economic situations, 2017–2021
Who grew, who fell: 2017 → 2021
See also
- Infant mortality in Russia by year long time series by year
- Life expectancy in Russia by year long time series by year
- Population of Russia by year long time series by year
- Urban population of Russia by year long time series by year
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- Демография России: главные цифры и графики Росстата indicator breakdown
- Продолжительность жизни мужчин и женщин в России 2026 indicator breakdown
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- Сельское население России по годам: данные Росстата indicator breakdown
Set in numbers
Rosstat data for 2017–2021. Series: 383, periods: 5. Breakdown: Amur Oblast — urban okrug — city of Raichikhinsk — Number…; Amur Oblast — city of Raichikhinsk — Population…; Amur Oblast — urban okrug — city of Svobodny — Number…; Amur Oblast — city of Svobodny — Population in …; Arkhangelsk Oblast — urban settlement Onezhskoye — Number… and others
Amur Oblast — urban okrug — city of Svobodny — Population: the indicator increased from 30,184 to 30,972 over 2017–2021 — by 2.61%. The highest value was 30,972 (2020), the lowest was 29,592 (2019). This is an average annual growth of 0.65%. Out of 25 largest series, 4 increased, 21 decreased
All table numbers are series: 383
How to read this table
The rows list single-industry municipalities from the list of those in the most difficult socio-economic situations. They are categorized by region and city name, making it possible to compare population decline or stability across different locations. Annual values from 2017 to 2021 are provided, allowing for an assessment of trends within and between each monotown
What is visible in these numbers
The five highest values: Amur Oblast — urban okrug — city of Svobodny (30,972), Amur Oblast — city of Svobodny — Population (30,972), Amur Oblast — urban okrug — city of Raichikhinsk (10,505), Arkhangelsk Oblast — urban settlement Onezhskoye (10,313), Arkhangelsk Oblast — city of Onega — Population (10,313). The gap between the highest and lowest is 23.7 times. The top five account for 54.9% of the total across all entries — the distribution is heavily skewed toward the top
Annual observations, 5 periods in the dataset. Out of 125 possible values, 100 are filled (80%). Some cells are empty — individual entries were not observed in every period
The same indicator in other breakdowns (1)
More in the section Demography»
Period and application
This reference covers five years of observations from 2017 to 2021, encompassing 383 monotowns. Rosstat produces these indicators annually, providing up-to-date information for specialists in regional socio-economic development, municipal management, and demographic research requiring precise population data for settlements with special status
How it is calculated
Data on birth rates, mortality, and age structure are required for planning social infrastructure, calculating pension system burdens, and regional forecasts
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