Displacement risk indicator showing how many households within the specified groups are facing housing cost burden (contributing more than 30% of monthly income toward housing costs).

Displacement risk indicator showing how many households within the specified groups are facing severely housing cost burden (contributing more than 50% of monthly income toward housing costs).

This Indicator measures the percent of renter households that are considered rent burdened by the race/ethnicity of the householder. Households that rent their homes are considered to be cost burdened when a household spends more than 30% of its annual household income on rent.

The U.S. Department of Housing and Urban Development (HUD) maintains that tenants are rent burdened if more than 30 percent of household income is used for rent. Data is collected via the US Census ACS 5-year estimates.

In 2023, there were approximately **** million housing cost burdened households among renters in the United States. A household is considered to be moderately burdened when the housing costs exceed 30 percent of the family income. Severely burdened households, on the other hand, spend more than 50 percent of their income on rent.

This data layer depicts, by census tracts, gross rent as a percentage of household income in the past 12 months for the San Francisco Bay Region. The source data, from the United States Census Bureau, has been reprocessed by the Metropolitan Transportation Commission.

To produce this feature set, the Metropolitan Transportation Commission downloaded American Community Survey (ACS) table B25070 to create a feature set representing rent as a percentage of household income by the following categories: ● Rent less than 30% of household income ● Rent is 30.0% to 49.9% of household income ● Rent is greater than or equal to 50% of household income

The resulting attribute table had all margin of error fields deleted, percentage fields added, county code field added, jurisdiction name added, and the source field names were changed.

The source table used to develop this feature service is from the United States Census Bureau, 2015-2019 American Community Survey 5-Year Estimates and can be downloaded from https://data.census.gov/cedsci/table?q=B25070%3A%20GROSS%20RENT%20AS%20A%20PERCENTAGE%20OF%20HOUSEHOLD%20INCOME%20IN%20THE%20PAST%2012%20MONTHS&g=0400000US06%241500000&tid=ACSDT5Y2019.B25070

In 2021, there were approximately **** million housing cost burdened renter households in the United States, with close to ** million being severely burdened. About *** million households with an annual income below ****** U.S. dollars were severely burdened. A household is considered to be moderately cost burdened when the housing costs exceed ** percent of the family income. Severely burdened households, on the other hand, spend over ** percent of their income on rent.

This statistic shows the share of income spent on rent by 22 to 30 year olds in the United States as of 2018, by generation. Millennials aged 22 to 30 years old, had the largest rent burden and spent ** percent of their income on rent.

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This layer shows housing costs as a percentage of household income, by census tracts in the City of Los Angeles. This contains the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Income is based on earnings in past 12 months of survey.

Households by burden of housing costs (mortgage or rent, heating, electricity, etc.) by number of recipients. National.

This table contains data on the percent of households paying more than 30% (or 50%) of monthly household income towards housing costs for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Department of Housing and Urban Development (HUD), Consolidated Planning Comprehensive Housing Affordability Strategy (CHAS) and the U.S. Census Bureau, American Community Survey (ACS). The table is part of a series of indicators in the [Healthy Communities Data and Indicators Project of the Office of Health Equity] Affordable, quality housing is central to health, conferring protection from the environment and supporting family life. Housing costs—typically the largest, single expense in a family's budget—also impact decisions that affect health. As housing consumes larger proportions of household income, families have less income for nutrition, health care, transportation, education, etc. Severe cost burdens may induce poverty—which is associated with developmental and behavioral problems in children and accelerated cognitive and physical decline in adults. Low-income families and minority communities are disproportionately affected by the lack of affordable, quality housing. More information about the data table and a data dictionary can be found in the Attachments.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

Information is derived from the ACS Housing Costs feature layer, which contains the most current release of data from the American Community Survey (ACS) about housing costs as a percentage of household income.

In April 2020, almost half of night-time economy sector businesses in the UK were receiving no support from landlords during the COVID-19 outbreak. Out of the share of businesses receiving rent relief, the most common option was deferred rent agreement with landlord, with 31 percent of the total number of respondents.

Graph and download economic data for Burdened Households (5-year estimate) in Kalamazoo County, MI (DP04ACS026077) from 2010 to 2023 about Kalamazoo County, MI; Kalamazoo; burdened; MI; 5-year; households; and USA.

Information about number of households by annual income level and housing costs as a percentage of total income. Housing costs include mortgage/rent and utilities. Data sourced by US Census American Community Survey (ACS) 5-Year Estimates. See ACS Table B25106 "Tenure by Housing Costs as a Percentage of Household Income in the Past 12 Months"; Universe: Occupied housing units. This dataset's API field names match the US Census Variable / API names (see also metadata spreadsheet in attachments section).

Graph and download economic data for Burdened Households (5-year estimate) in San Francisco County, CA (DP04ACS006075) from 2010 to 2023 about San Francisco County/City, CA; burdened; San Francisco; 5-year; CA; households; and USA.

This map shows housing costs as a percentage of household income. Severe housing cost burden is described as when over 50% of income in a household is spent on housing costs. For renters it is over 50% of household income going towards gross rent (contract rent plus tenant-paid utilities). Miami, Florida accounts for the having the highest population of renters with severe housing burden costs.The map's topic is shown by tract and county centroids. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Income is based on earnings in past 12 months of survey. Current Vintage: 2015-2019ACS Table(s): B25070, B25091Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 10, 2020National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis map can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census: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 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 Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Data from the U.S. Department of Housing and Urban Development Office of Policy Development and Research (HUD PD&R) and American Community Survey provided by the Urban Institute. This metric reports the share of low-income households at three income levels, low-income (below 80 percent of area median income, or AMI), very low-income (below 50 percent of AMI), and extremely low-income (below 30 percent of AMI), that spend more than half (>50%) of their household income on rent.