The average for 2024 based on 20 countries was 76.97 percent. The highest value was in Uruguay: 95.85 percent and the lowest value was in Guatemala: 53.54 percent. The indicator is available from 1960 to 2024. Below is a chart for all countries where data are available.

This statistic shows the degree of urbanization in Latin America & Caribbean from 2014 to 2024. Urbanization means the share of urban population in the total population of a country. In 2024, 82.04 percent of the total population of Latin America & Caribbean lived in urban areas and cities.

In 2025, the degree of urbanization worldwide was at 58 percent. North America, Latin America, and the Caribbean were the regions with the highest level of urbanization, with over four-fifths of the population residing in urban areas. The degree of urbanization defines the share of the population living in areas defined as "cities". On the other hand, less than half of Africa's population lives in urban settlements. Globally, China accounts for over one-quarter of the built-up areas of more than 500,000 inhabitants. The definition of a city differs across various world regions - some countries count settlements with 100 houses or more as urban, while others only include the capital of a country or provincial capitals in their count. Largest agglomerations worldwideThough North America is the most urbanized continent, no U.S. city was among the top ten urban agglomerations worldwide in 2023. Tokyo-Yokohama in Japan was the largest urban area in the world that year, with 37.7 million inhabitants. New York ranked 13th, with 21.4 million inhabitants. Eight of the 10 most populous cities are located in Asia. ConnectivityIt may be hard to imagine how the reality will look in 2050, with 70 percent of the global population living in cities, but some statistics illustrate the ways urban living differs from suburban and rural living. American urbanites may lead more “connected” (i.e., internet-connected) lives than their rural and/or suburban counterparts. As of 2021, around 89 percent of people living in urban areas owned a smartphone. Internet usage was also higher in cities than in rural areas. On the other hand, rural areas always have, and always will, attract those who want to escape the rush of the city.

La moyenne pour 2024 était de 76.97 pour cent. La valeur la plus élevée était au Uruguay: 95.85 pour cent et la valeur la plus basse était au Guatemala: 53.54 pour cent. Vous trouverez ci-dessous un graphique pour tous les pays où les données sont disponibles.

In 2025, approximately 23 million people lived in the São Paulo metropolitan area, making it the biggest in Latin America and the Caribbean and the sixth most populated in the world. The homonymous state of São Paulo was also the most populous federal entity in the country. The second place for the region was Mexico City with 22.75 million inhabitants. Brazil's cities Brazil is home to two large metropolises, only counting the population within the city limits, São Paulo had approximately 11.45 million inhabitants, and Rio de Janeiro around 6.21 million inhabitants. It also contains a number of smaller, but well known cities such as Brasília, Salvador, Belo Horizonte and many others, which report between 2 and 3 million inhabitants each. As a result, the country's population is primarily urban, with nearly 88 percent of inhabitants living in cities. Mexico City Mexico City's metropolitan area ranks sevenths in the ranking of most populated cities in the world. Founded over the Aztec city of Tenochtitlan in 1521 after the Spanish conquest as the capital of the Viceroyalty of New Spain, the city still stands as one of the most important in Latin America. Nevertheless, the preeminent economic, political, and cultural position of Mexico City has not prevented the metropolis from suffering the problems affecting the rest of the country, namely, inequality and violence. Only in 2023, the city registered a crime incidence of 52,723 reported cases for every 100,000 inhabitants and around 24 percent of the population lived under the poverty line.

The average for 2022 based on 12 countries was 76.7 percent. The highest value was in Chile: 99.4 percent and the lowest value was in Dominican Republic: 46.9 percent. The indicator is available from 2000 to 2022. Below is a chart for all countries where data are available.

Graph and download economic data for Consumer Unit Characteristics: Percent Hispanic or Latino by Type of Area: Urban: Other Urban (CXU980285LB1804M) from 2004 to 2020 about consumer unit, latino, hispanic, urban, percent, and USA.

The average for 2022 based on 8 countries was 79.3 percent. The highest value was in Chile: 99.4 percent and the lowest value was in Peru: 59.8 percent. The indicator is available from 2000 to 2022. Below is a chart for all countries where data are available.

Key Table Information.Table Title.Selected Characteristics of the Foreign-Born Population by Region of Birth: Latin America.Table ID.ACSST1Y2024.S0506.Survey/Program.American Community Survey.Year.2024.Dataset.ACS 1-Year Estimates Subject Tables.Source.U.S. Census Bureau, 2024 American Community Survey, 1-Year Estimates.Dataset Universe.The dataset universe of the American Community Survey (ACS) is the U.S. resident population and housing. For more information about ACS residence rules, see the ACS Design and Methodology Report. Note that each table describes the specific universe of interest for that set of estimates..Methodology.Unit(s) of Observation.American Community Survey (ACS) data are collected from individuals living in housing units and group quarters, and about housing units whether occupied or vacant. For more information about ACS sampling and data collection, see the ACS Design and Methodology Report..Geography Coverage.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year.Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Sampling.The ACS consists of two separate samples: housing unit addresses and group quarters facilities. Independent housing unit address samples are selected for each county or county-equivalent in the U.S. and Puerto Rico, with sampling rates depending on a measure of size for the area. For more information on sampling in the ACS, see the Accuracy of the Data document..Confidentiality.The Census Bureau has modified or suppressed some estimates in ACS data products to protect respondents' confidentiality. Title 13 United States Code, Section 9, prohibits the Census Bureau from publishing results in which an individual's data can be identified. For more information on confidentiality protection in the ACS, see the Accuracy of the Data document..Technical Documentation/Methodology.Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables.Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Weights.ACS estimates are obtained from a raking ratio estimation procedure that results in the assignment of two sets of weights: a weight to each sample person record and a weight to each sample housing unit record. Estimates of person characteristics are based on the person weight. Estimates of family, household, and housing unit characteristics are based on the housing unit weight. For any given geographic area, a characteristic total is estimated by summing the weights assigned to the persons, households, families or housing units possessing the characteristic in the geographic area. For more information on weighting and estimation in the ACS, see the Accuracy of the Data document.Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the na...

The share of Latin America's urban population with no access to electricity has remained below one percent for the past decade, averaging at 0.54 percent in 2019. Meanwhile, that same year, some 7.5 percent of Latin Americans residing in rural areas had no access to electric power, down from a share of roughly 28 percent in 2001.

IntroductionIn Latin America, 26 percent of women use sterilization to avert unwanted pregnancies. Although sterilization provides first-tier effectiveness, long-acting continuation over time, and life-long cost-benefit, previous research has documented persistent inequalities in access and use worldwide.MethodsThis study uses Demographic and Health Survey (DHS) data for Bolivia, Colombia, Guatemala, and Peru (1986-2015), to explore ethnoracial, geographic, socioeconomic, individual, and reproductive differences in female sterilization [N (level-1 women) = 112,135; N (level-2 clusters) = 4,946].ResultsResults from descriptive analyses and logistic multilevel regression models indicate that ethnoracial minorities and rural women had lower odds of reporting female sterilization as their current contraceptive method. Compared to Bolivian women, Colombian and Guatemalan women had higher odds of reporting sterilization, while Peruvian women had lower odds. Older, wealthier, more educated, and those employed outside the home had higher odds of reporting sterilization. Additionally, those older at first birth, with higher parity, with a longer interval since preceding birth, and with previous experience with unintended pregnancies had higher odds of reporting sterilization.DiscussionFindings suggest that social, geographic, and structural factors may shape equitable access to sterilization for some groups. Future efforts should prioritize reducing access gaps between ethnoracial groups and rural-urban populations by strengthening health systems and ensuring culturally appropriate, equitable care.

USA Census Block Groups (CBG) for Urban Search and Rescue. This layer can be used for search segment planning. Block groups generally contain between 600 and 5,000 people and the boundaries generally follow existing roads and waterways. The field segment_designation is the last 6 digits of the unique identifier and matches the field in the SARCOP Segment layer.Data download date: August 12, 2021Census tables: P1, P2, P3, P4, H1, P5, HeaderDownloaded from: Census FTP siteProcessing Notes:Data was downloaded from the U.S. Census Bureau FTP site, imported into SAS format and joined to the 2020 TIGER boundaries. Boundaries are sourced from the 2020 TIGER/Line Geodatabases. Boundaries have been projected into Web Mercator and each attribute has been given a clear descriptive alias name. No alterations have been made to the vertices of the data.Each attribute maintains it's specified name from Census, but also has a descriptive alias name and long description derived from the technical documentation provided by the Census. For a detailed list of the attributes contained in this layer, view the Data tab and select "Fields". The following alterations have been made to the tabular data:Joined all tables to create one wide attribute table:P1 - RaceP2 - Hispanic or Latino, and not Hispanic or Latino by RaceP3 - Race for the Population 18 Years and OverP4 - Hispanic or Latino, and not Hispanic or Latino by Race for the Population 18 Years and OverH1 - Occupancy Status (Housing)P5 - Group Quarters Population by Group Quarters Type (correctional institutions, juvenile facilities, nursing facilities/skilled nursing, college/university student housing, military quarters, etc.)HeaderAfter joining, dropped fields: FILEID, STUSAB, CHARITER, CIFSN, LOGRECNO, GEOVAR, GEOCOMP, LSADC, and BLOCK.GEOCOMP was renamed to GEOID and moved be the first column in the table, the original GEOID was dropped.Placeholder fields for future legislative districts have been dropped: CD118, CD119, CD120, CD121, SLDU22, SLDU24, SLDU26, SLDU28, SLDL22, SLDL24 SLDL26, SLDL28.P0020001 was dropped, as it is duplicative of P0010001. Similarly, P0040001 was dropped, as it is duplicative of P0030001.In addition to calculated fields, County_Name and State_Name were added.The following calculated fields have been added (see long field descriptions in the Data tab for formulas used): PCT_P0030001: Percent of Population 18 Years and OverPCT_P0020002: Percent Hispanic or LatinoPCT_P0020005: Percent White alone, not Hispanic or LatinoPCT_P0020006: Percent Black or African American alone, not Hispanic or LatinoPCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or LatinoPCT_P0020008: Percent Asian alone, Not Hispanic or LatinoPCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or LatinoPCT_P0020010: Percent Some Other Race alone, not Hispanic or LatinoPCT_P0020011: Percent Population of Two or More Races, not Hispanic or LatinoPCT_H0010002: Percent of Housing Units that are OccupiedPCT_H0010003: Percent of Housing Units that are VacantPlease note these percentages might look strange at the individual block group level, since this data has been protected using differential privacy.* *To protect the privacy and confidentiality of respondents, data has been protected using differential privacy techniques by the U.S. Census Bureau. This means that some individual block groups will have values that are inconsistent or improbable. However, when aggregated up, these issues become minimized. The pop-up on this layer uses Arcade to display aggregated values for the surrounding area rather than values for the block group itself.Download Census redistricting data in this layer as a file geodatabase.Additional links:U.S. Census BureauU.S. Census Bureau Decennial CensusAbout the 2020 Census2020 Census2020 Census data qualityDecennial Census P.L. 94-171 Redistricting Data Program

The share of population without access to electricity in Latin America has experienced a continual annual decline since the beginning of the century, to reach around two percent in 2019. Nevertheless, access to electricity in Latin America was still considerably higher in urban areas when compared to rural zones.

This dataset contains information on:

· Estimated resident population (ERP) at 30 June 1996, 2001, 2006, 2013, and 2018 for total population

· ERP at 30 June 2018 by ethnic groups (European or Other (including New Zealander), Māori, Pacific, Asian, and Middle Eastern/Latin American/African) – estimates and percentage

· Sex ratio – number of males per 100 females

· ERP at 30 June 2018 by broad age groups and median age

· Geographies available are regional council areas, territorial authority and Auckland local board areas, Statistical Area 2, and urban rural.

Note: The geography corresponds to 2020 boundaries

Note: -999 indicates data are not available.

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About the estimated resident population

The estimated resident population at 30 June in the census year is based on the census usually resident population count, with updates for:

· net census undercount (as measured by a post-enumeration survey)

· residents temporarily overseas on census night

· births, deaths and net migration between census night and 30 June

· reconciliation with demographic estimates at the youngest ages.

The estimated resident population is not directly comparable with the census usually resident population count because of these adjustments.

For more detailed information about the methods used to calculate each base population, see DataInfo+ Demographic estimates.

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Ethnic groups

It is important to note that these ethnic groups are not mutually exclusive because people can and do identify with more than one ethnicity. People who identify with more than one ethnicity have been included in each ethnic group.

The 'Māori', 'Pacific', 'Asian' and 'Middle Eastern/Latin American/African' ethnic groups are defined in level 1 of the Ethnicity New Zealand Standard Classification 2005. The estimates for the 'European or Other (including New Zealander)' group include people who belong to the 'European' or 'Other ethnicity' groups defined in level 1 of the standard classification. If a person belongs to both the 'European' and 'Other ethnicity' groups they have only been counted once. Almost all people in the 'Other ethnicity' group belong to the 'New Zealander' sub-group.

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Time series

This time series is irregular. Because the 2011 Census was cancelled after the Canterbury earthquake on 22 February 2011, the gap between the 2006-base and 2013-base estimated resident population is seven years. The change in data between 2006 and 2013 may be greater than in the usual five-year gap between censuses. Be careful when comparing trends.

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Rounding

Individual figures may not sum to stated totals due to rounding.

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More information

See Estimated resident population (2018-base): At 30 June 2018 for commentary about the 2018 ERP.

Subnational population estimates concepts – DataInfo+ provides definitions of terms used in the map.

Access more population estimates data in NZ.Stat:

Theme: Population estimates.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Total. Includes people who reported American Indian (including Canadian Indian), Latin American Indian, or Alaska Native only, regardless of whether they reported one or more American Indian, Latin American Indian, or Alaska Native tribes and villages.All other American Indian tribes (with only one tribe reported). Includes respondents who provided a response of another American Indian tribe not shown separately, such as Abenaki Nation of Missisquoi, Catawba Indian Nation, Kickapoo Tribe of Oklahoma, Mattaponi Indian Tribe, Piqua Shawnee Tribe, or Quapaw Nation. American Indian, not specified. Includes respondents who provided a response such as "American Indian."All other Latin American Indian (with only one group reported). Includes respondents who provided a response of another Latin American Indian group not shown separately, such as Arawak, Lenca, Pipil, Quechua, Toltec, or Zapotec.All other Alaska Native tribes and villages (with only one tribe or village reported). Includes respondents who provided a response of another Alaska Native tribe or village not shown separately, such as Aleut Corporation, Native Village of Unalakleet, Noorvik Native Community, Orutsararmiut Traditional Native Council, Sitka Tribe of Alaska, or Village of Kaltag. Alaska Native, not specified. Includes respondents who provided a response such as "Alaska Indian" or "Alaska Native".American Indian and Alaska Native, not specified. Includes respondents who selected the American Indian or Alaska Native response category on the ACS questionnaire and did not provide a specific group. Two or more American Indian and Alaska Native tribes and villages. Includes respondents who provided multiple American Indian or Alaska Native tribes and villages responses, such as Cherokee Nation and Hopi Tribe of Arizona; or Native Village of Barrow Inupiat Traditional Government and Arctic Slope Corporation; or Confederated Tribes of the Colville Reservation and Tlingit.".Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ende...

Abstract In order to determine and compare the efficiency of different urban cooling strategies in two Latin American cities (Mendoza, Argentina and Campinas, Brazil), 18 scenarios that modified their percentage of vegetation and albedo level in urban envelopment materials were analysed. The scenarios were simulated using a high-resolution microclimatic model -ENVI-met 3.1. The possible associations between variables were evaluated through Principal Components Analysis. The result showed that the percentage of vegetation and the average albedo of the urban opaque surfaces explain 71.5 % of the behaviours within the urban canyons in both cities. The increase in vegetation could decrease the average temperature in Mendoza by up to 2.0 ºC, while in Campinas by up to 5.0 ºC. Increasing the albedo level in the urban envelopment raises the air temperatures in high-density scenarios of Mendoza and Campinas by up to 1.0 ºC. However, in the case of high albedo scenarios in horizontal surfaces and low albedo in verticals, there were reductions of 2.0 ºC in the city of Mendoza and 3.0 ºC in Campinas.

Определение: Доля коренного населения, лиц африканского происхождения и некоренного населения, не имеющего африканского происхождения, проживающего в городских районах [Переведено с en: английского языка] Тематическая область: Демография (CELADE) [Переведено с en: английского языка] Область применения: Демография [Переведено с en: английского языка] Единица измерения: Процент [Переведено с en: английского языка] Источник данных: Демографический центр Латинской Америки и Карибского бассейна (CELADE) - Отдел народонаселения ЭКЛАК, на основе наборов микроданных национальных переписей населения [Переведено с es: испанского языка] Комментарии: Коренные народы определяются в зависимости от территории и особого способа их проживания. В общих чертах, их территории относятся к сельским территориям (совпадающим с землями их предков или теми, на которые они были переселены). Однако число городских поселений коренных народов увеличивается, в том числе из-за вторжения на их земли и их обнищания. Таким образом, это может быть показателем с негативным подтекстом, поскольку помимо того, что он связан с возможными насильственными перемещениями, существует идея о том, что смена места жительства между сельской местностью и городом приводит к ассимиляции и утрате культуры. К этому добавляется тот факт, что иммигранты из числа коренного населения, как правило, оказываются в наиболее маргинализированных секторах, воспроизводя, а иногда и усиливая неравенство в городских условиях. Однако существуют позиции, основанные на недавних исследованиях, которые признают возможности, открываемые этими изменениями в территориальном расположении. С одной стороны, признается, что процессы этнической перестройки происходят и в городских районах, и во многих случаях коренные жители городов продолжают сохранять свои социокультурные системы в городах и поддерживать связи со своими общинами происхождения. Кроме того, представлены преимущества улучшения доступа к государственным товарам и услугам. Характерной чертой населения африканского происхождения является то, что оно в основном проживает в городах. Как отмечает ЭКЛАК (2017): “Следует отметить, что даже численность этих групп в городах выше, чем у “белого” населения, чуть более чем в половине стран региона. Этот элемент следует учитывать при проведении этнических и расовых сравнений социально-экономических показателей в том смысле, что отсутствие различий на национальном уровне может быть результатом разницы между городским и сельским расположением и, следовательно, скрывать неравенство в ущерб населению африканского происхождения. Следовательно, необходимо дезагрегировать информацию таким образом, чтобы иметь возможность изучить различные ситуации, возникающие в результате пересечения неравенств” (стр. 56). Что касается обработки данных переписи, необходимо учитывать следующие соображения: Мексика (2000 и 2010 годы) и Панама (2000 и 2010 годы): население с неизвестным возрастом исключается из общих показателей и/или процентных соотношений, рассчитанных на их основе. Боливия (многонациональное государство) (2001 год), Бразилия (2000 и 2010 годы), Венесуэла (Боливарианская Республика), Колумбия (2005 и 2018 годы), Коста-Рика (2000 и 2011 годы), Мексика (2000 и 2010 годы), Никарагуа (2005 год), Перу (2017 год), Уругвай (2011 год) и Венесуэла (Боливарианская Республика) (2001 и 2011): Население с неизвестным этническим и расовым составом не фигурирует ни в общих данных о населении, ни в процентах, рассчитанных на их основе. Боливия (многонациональное государство) (2001 год) и Мексика (2000 и 2010 годы): Данные соответствуют численности населения, проживающего в занятых частных домохозяйствах. Бразилия (2010 год), Коста-Рика (2000 и 2011 годы), Парагвай (2002 год) и Венесуэла (Боливарианская Республика) (2001 и 2011 годы): в этих странах параллельно с общей переписью населения проводятся переписи коренных народов (территорий или общин). Используемые базы данных представляют собой интеграцию информации, собранной в обеих базах, когда это возможно. Аргентина (2010), Панама (2010), Уругвай (2011) и Мексика (2020): Этническая и расовая идентификация проводится комбинированным образом (коренные жители и лица африканского происхождения). В этих странах относительные показатели рассчитываются путем отнесения этих людей к этнической или расовой категории с наименьшим количеством случаев. Бразилия (2000 и 2010 годы) и Мексика (2000 и 2010 годы): Используемые базы данных соответствуют выборкам. В Бразилии расширенные данные округлены. Определение понятия "городской" было разработано в соответствии с критериями, представленными каждой страной. [Переведено с es: испанского языка] Последнее обновление: Jul 12 2023 5:28PM Организация-источник: Экономическая комиссия для Латинской Америки и Карибского бассейна [Переведено с en: английского языка] Definition: Proportion of the indigenous, Afro-descendant and non-indigenous neither Afro-descendant population residing in urban areas Thematic Area: Demographics (CELADE) Application Area: Demographics Unit of Measurement: Percentage Data Source: CELADE (Latin American & Caribbean Demographic Center)- Population Division of ECLAC, on the basis of national population censuses microdata sets Comments: Indigenous peoples are defined by reference to a territory and a particular way of inhabiting it. In general terms, their territories are inserted in rural spaces (coinciding with their ancestral lands or those to which they were reduced). However, urban indigenous settlements are increasing, because of the invasion and impoverishment of their lands, among other factors. Thus, this may be an indicator with negative connotations, since in addition to being linked to possible forced displacements, there is the idea that the change between the countryside and the city leads to assimilation and cultural loss. Added to this is the fact that indigenous immigrants tend to find themselves in the most marginalized sectors, reproducing and sometimes accentuating inequality in urban spaces. However, there are positions that, derived from recent studies, recognize the opportunities offered by these changes in territorial

As of the second month of 2025, more than * out of 10 people living in the Bahamas, Chile, Uruguay, Costa Rica, and Argentina were online, putting the countries in the top position regarding internet access in Latin America. Meanwhile, more than ** percent of the populations of the Dominican Republic, Puerto Rico, and Brazil were online. On the other hand, less than **** of the population of Haiti had access to the internet. Overall, the internet penetration rate in Latin America stood at **** percent. Growth in mobile connectivity… With investments in 4G infrastructure forecast to reach around ***** billion U.S. dollars by 2030, the improvement of mobile connectivity is radically changing the picture of access to the internet in Latin America and the Caribbean. One of the best examples is Peru, where the gap between urban and rural areas has greatly diminished in 2021, making its online audiences the fifth largest on the continent in 2025. …at an unequal rate Despite the improvements, Latin America and the Caribbean still face an enormous gap in internet access: the internet penetration rate in the subregion of South America was **** percent in 2025, while only **** percent of people in the Caribbean had access to the web. Despite its investments in mobile connectivity, most of the web traffic in Venezuela still originated from desktop devices in 2023, and only ***** Ecuadorians had access to mobile internet in 2025.

The US Census Bureau defines Hispanic or Latino as "Hispanic or Latino refers to a person of Cuban, Mexican, Puerto Rican, South or Central American, or other Spanish culture or origin regardless of race. This includes people who reported detailed Hispanic or Latino groups such as: Mexican, Puerto Rican, Cuban, Dominican Republic, Costa Rican, Guatemalan, Honduran, Nicaraguan, Panamanian, Salvadoran, Other Central American, Argentinian, Bolivian, Chilean, Colombian, Ecuadorian, Paraguayan, Peruvian, Uruguayan, Venezuelan, Other South American, Spaniard, All other Hispanic or Latino." Hispanic Latino population percentage was calculated based upon total Hispanic Latino population within the census block group divided the total population of the same census block group. 2020 Census block groups for the Wichita / Sedgwick County area, clipped to the county line. Features were extracted from the 2020 State of Kansas Census Block Group shapefile provided by the State of Kansas GIS Data Access and Support Center (https://www.kansasgis.org/index.cfm).Change in Population and Housing for the Sedgwick County area from 2010 - 2020 based upon US Census. Census Blocks from 2010 were spatially joined to Census Block Groups from 2020 to compare the population and housing figures. This is not a product of the US Census Bureau and is only available through City of Wichita GIS. Please refer to Census Block Groups for 2010 and 2020 for verification of all data Standard block groups are clusters of blocks within the same census tract that have the same first digit of their 4-character census block number. For example, blocks 3001, 3002, 3003… 3999 in census tract 1210.02 belong to Block Group 3. Due to boundary and feature changes that occur throughout the decade, current block groups do not always maintain these same block number to block group relationships. For example, block 3001 might move due to a change in the census tract boundary. Even if the block is no longer in block group 3, the block number (3001) will not change. However, the identification string (GEOID20) for that block, identifying block group 3, would remain the same in the attribute information in the TIGER/Line Shapefiles because block identification strings are always built using the decennial geographic codes.Block groups delineated for the 2020 Census generally contain between 600 and 3,000 people. Local participants delineated most block groups as part of the Census Bureau's Participant Statistical Areas Program (PSAP). The Census Bureau delineated block groups only where a local or tribal government declined to participate or where the Census Bureau could not identify a potential local participant.A block group usually covers a contiguous area. Each census tract contains at least one block group and block groups are uniquely numbered within census tract. Within the standard census geographic hierarchy, block groups never cross county or census tract boundaries, but may cross the boundaries of county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian, Alaska Native, and Native Hawaiian areas.Block groups have a valid range of 0 through 9. Block groups beginning with a zero generally are in coastal and Great Lakes water and territorial seas. Rather than extending a census tract boundary into the Great Lakes or out to the 3-mile territorial sea limit, the Census Bureau delineated some census tract boundaries along the shoreline or just offshore.

According to Cognitive Market Research, the global Door Handles market size is USD 7514.2 million in 2024 and will expand at a compound annual growth rate (CAGR) of 4.50% from 2024 to 2031.

North America holds the major market of more than 40% of the global revenue with a market size of USD 3005.68 million in 2024 and will grow at a compound annual growth rate (CAGR) of 2.7% from 2024 to 2031.
Europe accounted for a share of over 30% of the global market size of USD 2254.26 million.
Asia Pacific holds the market of around 23% of the global revenue with a market size of USD 1728.27 million in 2024 and will grow at a compound annual growth rate (CAGR) of 6.5% from 2024 to 2031.
Latin America holds the market of more than 5% of the global revenue with a market size of USD 375.71 million in 2024 and will grow at a compound annual growth rate (CAGR) of 3.9% from 2024 to 2031.
Middle East and Africa holds the major market of around 2% of the global revenue with a market size of USD 150.28 million in 2024 and will grow at a compound annual growth rate (CAGR) of 4.2% from 2024 to 2031.
The residential application held the highest Door Handles market revenue share in 2024.

Market Dynamics of Door Handles Market

Key Drivers for Door Handles Market

Rapid Pace of Urbanization to Increase the Demand Globally

The swift pace of urbanization serves as a primary catalyst propelling the growth of the global door handles market. With an increasing portion of the population residing in cities worldwide, the urban population share rose from 52.5 percent in 2012 to a projected 56.9 percent in 2022. Notably, developed regions exhibit a higher urbanization rate, reaching 79.7 percent in 2022 compared to 52.3 percent in developing countries. In Least Developed Countries (LDCs), urban dwellers constitute a minority at 35.8 percent. As urban areas expand and housing projects surge, there is a heightened demand for both residential and commercial spaces, consequently driving up the need for door hardware, including door handles. Furthermore, the urban lifestyle shift places significant importance on interior aesthetics, prompting consumers to seek door handle options that not only boast stylish designs but also offer functionality. This demand encompasses both traditional and innovative door handle designs, including smart door handles that provide enhanced security and convenience. With urbanization showing no signs of slowing down, the door handles market is poised for growth, driven by the sustained requirement for door hardware solutions in both new constructions and renovation projects within urban landscapes.

Rising Demand for Construction and Real Estate to Propel Market Growth

The demand for door handles is closely linked to the construction industry and real estate market dynamics. According to Savills India, there is a projected surge in real estate demand for data centers, expected to reach an increase of 15-18 million sq. ft. by 2025. Notably, luxury home sales in India experienced a remarkable spike, with a 130% rise in the first half of 2023 compared to the corresponding period of the previous year. Additionally, Private Equity Investments in India’s real estate sector reached US$ 4.2 billion in 2023. The growth in both residential and commercial construction projects, along with an uptick in renovations and remodeling endeavors, underscores the continuous necessity for door hardware, including handles.

Restraint Factor for the Door Handles Market

Potential for Frequent Door Handle Repairs Due To The Usage Of Low-Quality Raw Materials to Limit the Sales

One significant constraint facing the door handle industry stems from the likelihood of frequent repairs necessitated by the use of inferior raw materials during manufacturing. Such materials may result in malfunctioning or breakdown of door handles, thereby increasing maintenance expenses for consumers. This issue poses a substantial obstacle to industry expansion, as consumers may exhibit reluctance to invest in door handles if they foresee recurrent repair or replacement needs. Consequently, manufacturers must prioritize the adoption of superior-grade raw materials to mitigate instances of door handle repairs.

Impact of Covid-19 on the Door Handles Market

Supply chain disruptions have become a significant constraint affecting the growth of the global door handles market. The market's dependency on raw mat...