This map shows how many housing units are owner-occupied without a mortgage in the United States. The maps shows this as a percentage of all owner-occupied housing units, and also shows it as a count of how many housing units are owned without a mortgage. The areas in bright yellow have the highest percentage of non-mortgage owned homes. The pop-up provides additional information about owner-occupied units in each area. Search for any area within the US or Puerto Rico to see local or regional patterns. The data comes from the most current American Community Survey (ACS) data, and gets updated annually when the US Census Bureau releases their newest ACS estimates. To see the full documentation for the layer used in this map, click here. To find detailed ACS data for other topics, find them here in ArcGIS Living Atlas of the World.

This dataset provides values for HOME OWNERSHIP RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

California Household Crowding

2006-2010 Risk Ratios and Percentages

By Health [source]

About this dataset

This table provides an overview of the prevalence of household overcrowding and severe overcrowding in California from 2006-2010. Data on relative Standard Error (RSE), California decimal, and California Risk Ratio (RR) are also included. Residential crowding has serious health consequences, including increased risk of infection from communicable diseases, higher prevalence of respiratory ailments, and greater vulnerability to homelessness among the poor. This dataset can be used to identify demographics that may be disproportionately affected by crowded housing situation such as older immigrant communities, households with low income, renter-occupied dwellings and those that engage in doubling up. Furthermore, this data can help policy makers allocate resources to improve living conditions for affected individuals. An understanding of these household characteristics is essential for creating more equitable living conditions throughout California

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How to use the dataset

This dataset provides detailed data on the populations experiencing overcrowding and severe overcrowding in California, its regions, counties, and cities/towns. It is essential to understand household crowding in order to better target governmental efforts towards the most affected communities. To use this dataset, you'll need to first become familiar with some of the key fields included and what they mean:

• ind_definition: This field provides a definition of the indicator which indicates whether we are looking at data for households experiencing overcrowding or severe overcrowding.
• reportyear: This field contains information about what year the report was published for.
• race_eth_code: This field contains a numerical code which describes race/ethnicity information for each area included in the dataset.
• race_eth_name: This field provides additional descriptive information about each area's racial/ethnic makeup based off of their race/ethnicity code in this database.
• income_level: This field displays income level measurements as specified by HUD categories such as Very Low Income (VLI) and Extremely Low Income (ELI).

• tenure: Tenure is broken down into rental households vs owner occupied households - this is an important factor when considering household crowding as renters are more likely to experience it than people who own their home outright due to cost criteria so they may be more likely living with other people or living close quarters just to save money on rent payments upfront or security deposits. - crowding cat: Describes whether we are measuring overall household crowding or severe overcrowded houses according to HUD definitions (see above). - geotype & geotypevalue : These two fields contain specific geographic data for each area that can be used for mapping analysis etc.. The geotype contains information about what type of geography we're looking at i.e., county/city etc., while geotypevalue contains ID values associated with those types allowing further analysis based off these IDs if necessary! - countyfips & regionname provide useful labels when attempting geographical analysis; regionname will describe high level geography such as state boundaries etc., while countyfips allow us more precise locations within states thus enabling precision query analysis into localized areas using tools such as ArcGIS' statistical functions etc..

    The totalhshlds column shows us exactly how many homes are present across California regions counties or cities whereas crowdedhshlds tells us
  

Research Ideas

• Analyzing and mapping regional variations in overcrowding and how it is related to regional economic conditions.
• Identifying which race/ethnicities are most likely to experience overcrowding, and why this might be the case.
• Examining how overcrowding affects housing affordability in California, and adapting public policy to address the issue where needed

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even comm...

This feature layer represents the proportion of the population who own their home (owned outright or owned with mortgage or loan). The layer has been developed as a proxy to represent SDG 1.4.2 ‘Proportion of Total Adult Population with Secure Tenure Rights to Land' for Ireland. Census 2016 data produced by the Central Statistics Office (CSO) and NUTS 3 boundary data produced by Tailte Éireann were used to create this feature layer.In 2015 UN countries adopted a set of 17 goals to end poverty, protect the planet and ensure prosperity for all as part of a new sustainable development agenda. Each goal has specific targets to help achieve the goals set out in the agenda by 2030. Governments are committed to establishing national frameworks for the achievement of the 17 Goals and to review progress using accessible quality data. With these goals in mind the CSO and Tailte Éireann are working together to link geography and statistics to produce indicators that help communicate and monitor Ireland’s performance in relation to achieving the 17 sustainable development goals.The indicator displayed supports the efforts to achieve goal number 1 which aims to end poverty in all its forms everywhere.This indicator was previously named 1.4.2, however we have now published two datasets to measure progress towards Target 1.4, therefore this dataset will be 1.4.2a and the second dataset is called 1.4.2b.

Этот набор данных содержит статистические данные о количестве комнат на душу населения, количестве домовладельцев и стоимости жилья в процентах от располагаемого дохода в субнациональных регионах. Определение и источник данных Количество комнат на душу населения - это среднее количество комнат, доступных на одного человека в домохозяйстве. Комната обычно определяется как пространство в жилом помещении, предназначенное для проживания, такое как спальни, гостиные, столовые и другие помещения, за исключением ванных комнат, кухонь, коридоров и подсобных помещений. Доля домовладельцев относится к проценту людей, владеющих домом, в котором они живут (полностью или с залогом). Расходы на жилье в процентах от располагаемого дохода учитывают расходы домохозяйств на жилье, такие как ипотека и арендная плата, и содержание дома, включая воду, электричество, газ и другие виды топлива, а также мебель, бытовую технику и повседневные расходы. техническое обслуживание дома. Подробная информация об источниках данных приведена в Краткий обзор регионов и городов ОЭСР за 2024 год - Приложение B Определение регионов Регионы - это субнациональные единицы, расположенные за пределами национальных границ. Страны ОЭСР имеют два региональных уровня: крупные регионы (территориальный уровень 2 или TL2) и небольшие регионы (территориальный уровень 3 или TL3). Регионы ОЭСР представлены в территориальной сетке ОЭСР (pdf) и в таблице территориального соответствия ОЭСР (xlsx). Процитируйте этот набор данных База данных ОЭСР по регионам, городам и локальным районам (Жилье - регионы), http://oe.cd/geostats. Контактное лицо: RegionStat@oecd.org Этот набор данных содержит статистические данные о количестве комнат на душу населения, количестве домовладельцев и стоимости жилья в процентах от располагаемого дохода в субнациональные регионы. Определение и источник данных Количество комнат на душу населения - это среднее количество комнат, доступных на одного человека в домохозяйстве. Комната обычно определяется как пространство в жилом помещении, предназначенное для проживания, такое как спальни, гостиные, столовые и другие помещения, за исключением ванных комнат, кухонь, коридоров и подсобных помещений. Доля домовладельцев относится к проценту людей, владеющих домом, в котором они живут (полностью или с залогом). Расходы на жилье в процентах от располагаемого дохода учитывают расходы домохозяйств на жилье, такие как ипотека и арендная плата, и содержание дома, включая воду, электричество, газ и другие виды топлива, а также мебель, бытовую технику и повседневные расходы. техническое обслуживание дома. Подробная информация об источниках данных приведена в Краткий обзор регионов и городов ОЭСР за 2024 год - Приложение B Определение регионов Регионы - это субнациональные единицы, расположенные за пределами национальных границ. Страны ОЭСР имеют два региональных уровня: крупные регионы (территориальный уровень 2 или TL2) и небольшие регионы (территориальный уровень 3 или TL3). Регионы ОЭСР представлены в территориальной сетке ОЭСР (pdf) и в таблице территориального соответствия ОЭСР (xlsx). Процитируйте этот набор данных База данных ОЭСР по регионам, городам и локальным районам (Жилье - регионы), http://oe.cd/geostats. Контактное лицо: RegionStat@oecd.org This dataset provides statistics on rooms per capita, home ownership rate and housing costs as a percentage of disposable income in subnational regions. Data definition and source Rooms per capita is the average number of rooms available per person in a household. A room is typically defined as a space in a dwelling intended for habitation, such as bedrooms, living rooms, dining rooms, and other spaces, excluding bathrooms, kitchens, hallways, and utility rooms. Home ownership rate refers to the percentage of people who own the home where they live (own outright and with a morgage). Housing costs as a percentage of disposable income considers the expenditure of households in housing - such as mortgages and rents - and maintenance of the house - including water, electricity, gas and other fuels, as well as furnishings, household equipment and routine maintenance of the house. Data sources are detailled in OECD Regions and Cities at a Glance 2024 - Annex B Definition of regions Regions are subnational units below national boundaries. OECD countries have two regional levels: large regions (territorial level 2 or TL2) and small regions (territorial level 3 or TL3). The OECD regions are presented in the OECD Territorial grid (pdf) and in the OECD Territorial correspondence table (xlsx). Cite this dataset OECD Regions, cities and local areas database (Housing - Regions), http://oe.cd/geostats. Contact: RegionStat@oecd.org This dataset provides statistics on rooms per capita, home ownership rate and housing costs as a percentage of disposable income in subnational regions. Data definition and source Rooms per capita is the average number of rooms available per person in a household. A room is typically defined as a space in a dwelling intended for habitation, such as bedrooms, living rooms, dining rooms, and other spaces, excluding bathrooms, kitchens, hallways, and utility rooms. Home ownership rate refers to the percentage of people who own the home where they live (own outright and with a morgage). Housing costs as a percentage of disposable income considers the expenditure of households in housing - such as mortgages and rents - and maintenance of the house - including water, electricity, gas and other fuels, as well as furnishings, household equipment and routine maintenance of the house. Data sources are detailled in OECD Regions and Cities at a Glance 2024 - Annex B Definition of regions Regions are subnational units below national boundaries. OECD countries have two regional levels: large regions (territorial level 2 or TL2) and small regions (territorial level 3 or TL3). The OECD regions are presented in the OECD Territorial grid (pdf) and in the OECD Territorial correspondence table (xlsx). Cite this dataset OECD Regions, cities and local areas database (Housing - Regions), http://oe.cd/geostats. Contact: RegionStat@oecd.org