All cities with a population > 1000 or seats of adm div (ca 80.000)Sources and ContributionsSources : GeoNames is aggregating over hundred different data sources. Ambassadors : GeoNames Ambassadors help in many countries. Wiki : A wiki allows to view the data and quickly fix error and add missing places. Donations and Sponsoring : Costs for running GeoNames are covered by donations and sponsoring.Enrichment:add country name

Laos LA: Population in Largest City data was reported at 657,108.000 Person in 2017. This records an increase from the previous number of 649,550.000 Person for 2016. Laos LA: Population in Largest City data is updated yearly, averaging 268,948.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 657,108.000 Person in 2017 and a record low of 75,908.000 Person in 1960. Laos LA: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Laos – Table LA.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

The World Cities Culture Forum, established in 2012, is a leading global network of civic leaders from over 40 creative cities across six continents, representing a combined population of over 245 million. The forum fosters collaborations to place culture at the core of urban development, addressing 21st-century challenges such as climate change, affordable workspaces, cultural tourism, and diversity in public spaces. Through its Global Summit, partnerships, and programs like the Leadership Exchange Programme and Digital Dialogue Masterclasses, the forum promotes cultural integration in city planning. The World Cities Culture Report 2022 provides comprehensive open-source data on culture, including over 60 datasets from 40 cities. Contextual Data: Includes demographics such as characteristics of the overall and working-age populations (including percent who were foreign born) and of the geographical area, such as the percentage of national population living in the city and the percentage of the area devoted to parks and other public green spaces. Cultural Infrastructure: Provides counts (and rates) of various facilities and venues, including art galleries, artists' studios, rehearsal spaces, bars, bookshops, cinemas, community centers, concert halls, museums, nightclubs, libraries, video game arcades, and theatres. Participation and Tourism: Focuses on cultural participation metrics, such as cinema and theatre admissions, festival attendance, museum visits, average daily attendance at the top five art exhibits, and international tourist numbers. Creative Economy: Encompasses data on book publishing, creative industries employment, film festivals, restaurant ratings, and performances. Education: Includes statistics on public library book loans, higher education levels, international student enrollment, and specialist institutes in art and design education. The source for each number is identified within the dataset. Data users can freely download selected datasets as .csv files.

• The current US Census Bureau world population estimate in June 2019 shows that the current global population is 7,577,130,400 people on Earth, which far exceeds the world population of 7.2 billion in 2015. Our estimate based on UN data shows the world's population surpassing 7.7 billion.
• China is the most populous country in the world with a population exceeding 1.4 billion. It is one of just two countries with a population of more than 1 billion, with India being the second. As of 2018, India has a population of over 1.355 billion people, and its population growth is expected to continue through at least 2050. By the year 2030, India is expected to become the most populous country in the world. This is because India’s population will grow, while China is projected to see a loss in population.
• The following 11 countries that are the most populous in the world each have populations exceeding 100 million. These include the United States, Indonesia, Brazil, Pakistan, Nigeria, Bangladesh, Russia, Mexico, Japan, Ethiopia, and the Philippines. Of these nations, all are expected to continue to grow except Russia and Japan, which will see their populations drop by 2030 before falling again significantly by 2050.
• Many other nations have populations of at least one million, while there are also countries that have just thousands. The smallest population in the world can be found in Vatican City, where only 801 people reside.
• In 2018, the world’s population growth rate was 1.12%. Every five years since the 1970s, the population growth rate has continued to fall. The world’s population is expected to continue to grow larger but at a much slower pace. By 2030, the population will exceed 8 billion. In 2040, this number will grow to more than 9 billion. In 2055, the number will rise to over 10 billion, and another billion people won’t be added until near the end of the century. The current annual population growth estimates from the United Nations are in the millions - estimating that over 80 million new lives are added yearly.
• This population growth will be significantly impacted by nine specific countries which are situated to contribute to the population growth more quickly than other nations. These nations include the Democratic Republic of the Congo, Ethiopia, India, Indonesia, Nigeria, Pakistan, Uganda, the United Republic of Tanzania, and the United States of America. Particularly of interest, India is on track to overtake China's position as the most populous country by 2030. Additionally, multiple nations within Africa are expected to double their populations before fertility rates begin to slow entirely.

Content

• In this Dataset, we have Historical Population data for every Country/Territory in the world by different parameters like Area Size of the Country/Territory, Name of the Continent, Name of the Capital, Density, Population Growth Rate, Ranking based on Population, World Population Percentage, etc. >Dataset Glossary (Column-Wise):
• Rank: Rank by Population.
• CCA3: 3 Digit Country/Territories Code.
• Country/Territories: Name of the Country/Territories.
• Capital: Name of the Capital.
• Continent: Name of the Continent.
• 2022 Population: Population of the Country/Territories in the year 2022.
• 2020 Population: Population of the Country/Territories in the year 2020.
• 2015 Population: Population of the Country/Territories in the year 2015.
• 2010 Population: Population of the Country/Territories in the year 2010.
• 2000 Population: Population of the Country/Territories in the year 2000.
• 1990 Population: Population of the Country/Territories in the year 1990.
• 1980 Population: Population of the Country/Territories in the year 1980.
• 1970 Population: Population of the Country/Territories in the year 1970.
• Area (km²): Area size of the Country/Territories in square kilometers.
• Density (per km²): Population Density per square kilometer.
• Growth Rate: Population Growth Rate by Country/Territories.
• World Population Percentage: The population percentage by each Country/Territories.

Hong Kong HK: Population in Largest City: as % of Urban Population data was reported at 99.637 % in 2017. This records an increase from the previous number of 99.540 % for 2016. Hong Kong HK: Population in Largest City: as % of Urban Population data is updated yearly, averaging 99.382 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 100.000 % in 2010 and a record low of 94.548 % in 1974. Hong Kong HK: Population in Largest City: as % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Hong Kong – Table HK.World Bank: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; Weighted average;

The "Major Cities" layer is derived from the "World Cities" dataset provided by ArcGIS Data and Maps group as part of the global data layers made available for public use. "Major cities" layer specifically contains National and Provincial capitals that have the highest population within their respective country. Cities were filtered based on the STATUS (“National capital”, “National and provincial capital”, “Provincial capital”, “National capital and provincial capital enclave”, and “Other”). Majority of these cities within larger countries have been filtered at the highest levels of POP_CLASS (“5,000,000 and greater” and “1,000,000 to 4,999,999”). However, China for example, was filtered with cities over 11 million people due to many highly populated cities. Population approximations are sourced from US Census and UN Data. Credits: ESRI, CIA World Factbook, GMI, NIMA, UN Data, UN Habitat, US Census Bureau Disclaimer: The designations employed and the presentation of material at this site do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.

Mexico MX: Population in Largest City data was reported at 21,500,251.000 Person in 2017. This records an increase from the previous number of 21,419,976.000 Person for 2016. Mexico MX: Population in Largest City data is updated yearly, averaging 15,225,498.500 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 21,500,251.000 Person in 2017 and a record low of 5,479,184.000 Person in 1960. Mexico MX: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mexico – Table MX.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

Description

This comprehensive dataset provides a wealth of information about all countries worldwide, covering a wide range of indicators and attributes. It encompasses demographic statistics, economic indicators, environmental factors, healthcare metrics, education statistics, and much more. With every country represented, this dataset offers a complete global perspective on various aspects of nations, enabling in-depth analyses and cross-country comparisons.

Key Features

Country: Name of the country.

Density (P/Km2): Population density measured in persons per square kilometer.

Abbreviation: Abbreviation or code representing the country.

Agricultural Land (%): Percentage of land area used for agricultural purposes.

Land Area (Km2): Total land area of the country in square kilometers.

Armed Forces Size: Size of the armed forces in the country.

Birth Rate: Number of births per 1,000 population per year.

Calling Code: International calling code for the country.

Capital/Major City: Name of the capital or major city.

CO2 Emissions: Carbon dioxide emissions in tons.

CPI: Consumer Price Index, a measure of inflation and purchasing power.

CPI Change (%): Percentage change in the Consumer Price Index compared to the previous year.

Currency_Code: Currency code used in the country.

Fertility Rate: Average number of children born to a woman during her lifetime.

Forested Area (%): Percentage of land area covered by forests.

Gasoline_Price: Price of gasoline per liter in local currency.

GDP: Gross Domestic Product, the total value of goods and services produced in the country.

Gross Primary Education Enrollment (%): Gross enrollment ratio for primary education.

Gross Tertiary Education Enrollment (%): Gross enrollment ratio for tertiary education.

Infant Mortality: Number of deaths per 1,000 live births before reaching one year of age.

Largest City: Name of the country's largest city.

Life Expectancy: Average number of years a newborn is expected to live.

Maternal Mortality Ratio: Number of maternal deaths per 100,000 live births.

Minimum Wage: Minimum wage level in local currency.

Official Language: Official language(s) spoken in the country.

Out of Pocket Health Expenditure (%): Percentage of total health expenditure paid out-of-pocket by individuals.

Physicians per Thousand: Number of physicians per thousand people.

Population: Total population of the country.

Population: Labor Force Participation (%): Percentage of the population that is part of the labor force.

Tax Revenue (%): Tax revenue as a percentage of GDP.

Total Tax Rate: Overall tax burden as a percentage of commercial profits.

Unemployment Rate: Percentage of the labor force that is unemployed.

Urban Population: Percentage of the population living in urban areas.

Latitude: Latitude coordinate of the country's location.

Longitude: Longitude coordinate of the country's location.

Potential Use Cases

Analyze population density and land area to study spatial distribution patterns.

Investigate the relationship between agricultural land and food security.

Examine carbon dioxide emissions and their impact on climate change.

Explore correlations between economic indicators such as GDP and various socio-economic factors.

Investigate educational enrollment rates and their implications for human capital development.

Analyze healthcare metrics such as infant mortality and life expectancy to assess overall well-being.

Study labor market dynamics through indicators such as labor force participation and unemployment rates.

Investigate the role of taxation and its impact on economic development.

Explore urbanization trends and their social and environmental consequences.

The urban–rural continuum classifies the global population, allocating rural populations around differently-sized cities. The classification is based on four dimensions: population distribution, population density, urban center location, and travel time to urban centers, all of which can be mapped globally and consistently and then aggregated as administrative unit statistics.Using spatial data, we matched all rural locations to their urban center of reference based on the time needed to reach these urban centers. A hierarchy of urban centers by population size (largest to smallest) is used to determine which center is the point of “reference” for a given rural location: proximity to a larger center “dominates” over a smaller one in the same travel time category. This was done for 7 urban categories and then aggregated, for presentation purposes, into “large cities” (over 1 million people), “intermediate cities” (250,000 –1 million), and “small cities and towns” (20,000–250,000).Finally, to reflect the diversity of population density across the urban–rural continuum, we distinguished between high-density rural areas with over 1,500 inhabitants per km2 and lower density areas. Unlike traditional functional area approaches, our approach does not define urban catchment areas by using thresholds, such as proportion of people commuting; instead, these emerge endogenously from our urban hierarchy and by calculating the shortest travel time.Urban-Rural Catchment Areas (URCA).tif is a raster dataset of the 30 urban–rural continuum categories for the urban–rural continuum showing the catchment areas around cities and towns of different sizes. Each rural pixel is assigned to one defined travel time category: less than one hour, one to two hours, and two to three hours travel time to one of seven urban agglomeration sizes. The agglomerations range from large cities with i) populations greater than 5 million and ii) between 1 to 5 million; intermediate cities with iii) 500,000 to 1 million and iv) 250,000 to 500,000 inhabitants; small cities with populations v) between 100,000 and 250,000 and vi) between 50,000 and 100,000; and vii) towns of between 20,000 and 50,000 people. The remaining pixels that are more than 3 hours away from any urban agglomeration of at least 20,000 people are considered as either hinterland or dispersed towns being that they are not gravitating around any urban agglomeration. The raster also allows for visualizing a simplified continuum created by grouping the seven urban agglomerations into 4 categories.Urban-Rural Catchment Areas (URCA).tif is in GeoTIFF format, band interleaved with LZW compression, suitable for use in Geographic Information Systems and statistical packages. The data type is byte, with pixel values ranging from 1 to 30. The no data value is 128. It has a spatial resolution of 30 arc seconds, which is approximately 1km at the equator. The spatial reference system (projection) is EPSG:4326 - WGS84 - Geographic Coordinate System (lat/long). The geographic extent is 83.6N - 60S / 180E - 180W. The same tif file is also available as an ESRI ArcMap MapPackage Urban-Rural Catchment Areas.mpkFurther details are in the ReadMe_data_description.docx

Panama PA: Population in Largest City data was reported at 1,745,913.000 Person in 2017. This records an increase from the previous number of 1,709,128.000 Person for 2016. Panama PA: Population in Largest City data is updated yearly, averaging 808,056.500 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 1,745,913.000 Person in 2017 and a record low of 282,895.000 Person in 1960. Panama PA: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Panama – Table PA.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

Cities ranking and mega citiesTokyo is the world’s largest city with an agglomeration of 37 million inhabitants, followed by New Delhi with 29 million, Shanghai with 26 million, and Mexico City and São Paulo, each with around 22 million inhabitants. Today, Cairo, Mumbai, Beijing and Dhaka all have close to 20 million inhabitants. By 2020, Tokyo’s population is projected to begin to decline, while Delhi is projected to continue growing and to become the most populous city in the world around 2028.By 2030, the world is projected to have 43 megacities with more than 10 million inhabitants, most of them in developing regions. However, some of the fastest-growing urban agglomerations are cities with fewer than 1 million inhabitants, many of them located in Asia and Africa. While one in eight people live in 33 megacities worldwide, close to half of the world’s urban dwellers reside in much smaller settlements with fewer than 500,000 inhabitants.About the dataThe 2018 Revision of the World Urbanization Prospects is published by the Population Division of the United Nations Department of Economic and Social Affairs (UN DESA). It has been issued regularly since 1988 with revised estimates and projections of the urban and rural populations for all countries of the world, and of their major urban agglomerations. The data set and related materials are available at: https://esa.un.org/unpd/wup/

Central African Republic CF: Population in Largest City data was reported at 985,965.000 Person in 2024. This records an increase from the previous number of 958,335.000 Person for 2023. Central African Republic CF: Population in Largest City data is updated yearly, averaging 487,345.000 Person from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 985,965.000 Person in 2024 and a record low of 94,350.000 Person in 1960. Central African Republic CF: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Central African Republic – Table CF.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.;United Nations, World Urbanization Prospects.;;

Japan JP: Population in Largest City data was reported at 37,397,437.000 Person in 2017. This records an increase from the previous number of 37,326,706.000 Person for 2016. Japan JP: Population in Largest City data is updated yearly, averaging 31,840,745.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 37,397,437.000 Person in 2017 and a record low of 16,678,821.000 Person in 1960. Japan JP: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

Poland PL: Population in Largest City data was reported at 1,758,551.000 Person in 2017. This records an increase from the previous number of 1,749,352.000 Person for 2016. Poland PL: Population in Largest City data is updated yearly, averaging 1,618,666.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 1,758,551.000 Person in 2017 and a record low of 1,119,181.000 Person in 1960. Poland PL: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Poland – Table PL.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

Switzerland Population in Largest City data was reported at 1,356,037.000 Person in 2017. This records an increase from the previous number of 1,341,453.000 Person for 2016. Switzerland Population in Largest City data is updated yearly, averaging 951,846.500 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 1,356,037.000 Person in 2017 and a record low of 535,471.000 Person in 1960. Switzerland Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Switzerland – Table CH.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

Background

Intentional self-harm is a common cause of hospital presentations in New Zealand and across the world, and self-poisoning is the most common method of self-harm. Paracetamol (acetaminophen) is frequently used in impulsive intentional overdoses, where ease of access may determine the choice of substance.

Objective

This cross-sectional study aimed to determine how much paracetamol is present and therefore accessible in urban New Zealand households, and sources from where it has been obtained. This information is not currently available through any other means, but could inform New Zealand drug policy on access to paracetamol.

Methods

Random cluster-sampling of households was performed in major urban areas of two cities in New Zealand, and the paracetamol-containing products, quantities, and sources were recorded. Population estimates of proportions of various types of paracetamol products were calculated.

Results

A total of 174 of the 201 study households (86.6%) had at least one paracetamol product. Study households had mostly prescription products (78.2% of total mass), and a median of 24.0 g paracetamol present per household (inter-quartile range 6.0-54.0 g). Prescribed paracetamol was the main source of large stock. Based on the study findings, 53% of New Zealand households had 30 g or more paracetamol present, and 36% had 30 g or more of prescribed paracetamol, specifically.

Conclusions

This study highlights the importance of assessing whether and how much paracetamol is truly needed when prescribing and dispensing it. Convenience of appropriate access to therapeutic paracetamol needs to be balanced with preventing unnecessary accumulation of paracetamol stocks in households and inappropriate access to it. Prescribers and pharmacists need to be aware of the risks of such accumulation and assess the therapeutic needs of their patients. Public initiatives should be rolled out at regular intervals to encourage people to return unused or expired medicines to pharmacies for safe disposal.

Methods The stocks of paracetamol-containing medicines (acetaminophen) held at a single time point in New Zealand households are described in this dataset. These data were collected via a cluster-sampling survey of two cities in New Zealand.

A door-to-door survey study with random, clustered sampling of consenting household members in two cities in New Zealand was designed. A total of 201 households in 40 meshblocks in two Major Urban Areas (MUAs; areas of 100,000 or more residents) of Dunedin and Auckland were sampled. Meshblocks are Statistics NZ’s smallest geographic unit, and roughly correspond to a city block or part of it. Random cluster-sampling of 20 meshblocks in each city was performed by deprivation level, where all eligible MUA meshblocks were stratified by their New Zealand Deprivation Index 2013 (NZDep2013) index scores, which describe the level of area deprivation by taking into account multiple relevant area and household variables. Six meshblocks were randomly selected from each city from NZDep2013 8-10 meshblocks (most deprived), eight from NZDep 4-7, and 6 from NZDep2013 1-2 (least deprived), for a total of 40 meshblocks. This was done to obtain a sample that would be representative of the general New Zealand population by levels of deprivation. Each meshblock was sampled by starting from a random end of the street and then tossing a dice to choose a house to approach, and repeating this until either five households were recruited or there were no more households to sample.

Trained Research Assistants (RAs) knocked on the doors of domiciles in each meshblock to be sampled, chosen by tossing a dice as described. Inclusion criteria: person present and usually residing in a domicile in a meshblock which was sampled, and aged 16 or over. Exclusion criteria: not able to give informed consent (intoxicated, aggressive, otherwise not safe to approach – nobody was excluded for this reason).

Household members aged 16 years and over were eligible to participate, and if consent was obtained, basic demographics were collected about the household (number of people usually residing in the household, their age, sex, ethnicity). Participants were then shown images of paracetamol-containing products (sole and combination), and requested to bring out all paracetamol products of their own, and any that were shared by the household in communal areas of the domicile. Private stock of any other residents of the household who were not present and were therefore unable to consent was not recorded for ethical reasons. If there were no paracetamol products present, that was recorded. If there were paracetamol products present, product type, strength, expiry date, purchase date and means of obtaining (by prescription, pharmacy over-the-counter [OTC], other retailer [i.e. not a pharmacy; e.g. supermarket, petrol station], other, unknown) were recorded.

The data were entered into a main database which is fully de-identified. Meshblock numbers are included in the dataset, but households are only given an identifier derived from the meshblock code. It would not be possible to identify a specific household from the data. Paracetamol product names were cleaned in the dataset (if there were any misspellings), and new variables were calculated to summarise the data (e.g. total household stock of prescribed paracetamol products, etc.).

Oman OM: Population in Largest City data was reported at 1,377,500.000 Person in 2017. This records an increase from the previous number of 1,311,734.000 Person for 2016. Oman OM: Population in Largest City data is updated yearly, averaging 300,762.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 1,377,500.000 Person in 2017 and a record low of 13,792.000 Person in 1960. Oman OM: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Oman – Table OM.World Bank: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

Ecuador EC: Population in Largest City data was reported at 2,844,281.000 Person in 2017. This records an increase from the previous number of 2,790,791.000 Person for 2016. Ecuador EC: Population in Largest City data is updated yearly, averaging 1,502,366.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 2,844,281.000 Person in 2017 and a record low of 456,225.000 Person in 1960. Ecuador EC: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ecuador – Table EC.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

Sweden SE: Population in Largest City: as % of Urban Population data was reported at 17.703 % in 2017. This records an increase from the previous number of 17.683 % for 2016. Sweden SE: Population in Largest City: as % of Urban Population data is updated yearly, averaging 15.683 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 17.703 % in 2017 and a record low of 14.346 % in 1981. Sweden SE: Population in Largest City: as % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sweden – Table SE.World Bank: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; Weighted average;

Kazakhstan KZ: Population in Largest City data was reported at 1,547,257.000 Person in 2017. This records an increase from the previous number of 1,534,894.000 Person for 2016. Kazakhstan KZ: Population in Largest City data is updated yearly, averaging 1,069,962.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 1,547,257.000 Person in 2017 and a record low of 528,653.000 Person in 1960. Kazakhstan KZ: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kazakhstan – Table KZ.World Bank: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;