Older housing can impact the quality of the occupant's health in a number of ways, including lead exposure, housing quality, and factors that may exacerbate respiratory conditions, like asthma. Data from the U.S. Census Bureau contains Census Tract estimates of housing age, and Allegheny County assessment data provides parcel-level information on the year residential properties were built.

As of the first quarter 2021, there were over ***** senior housing communities in the Southeast region of the United States. This was the region with the most senior housing communities in the country. The Southeast region includes the following U.S. states: Alabama, DC, Florida, Georgia, Kentucky, Maryland, North Carolina, South Carolina, Tennessee, Virginia and West Virginia. Why are southern states so popular among retirees? The southern U.S. states are popular destinations for retirees due to the warm, sunny climate and relatively low crime rates. Average monthly rents for senior housing in that region are on the lower end of the scale, which is another advantage for retirees looking to relocate for their next life stage. The large number of senior housing communities in the region may be a reason for the lower costs. Future of seniors housing in the U.S. The number of Americans aged 65 years and older is forecast to rise until at least 2050, which indicates that demand for seniors housing will also continue to rise. Approximately 17 percent of North American respondents said that they would move into a senior living community in an urban environment if money is not an obstacle when they’re over 80 years old.

Welltower Inc., Ventas Inc., and Brookdale Senior Living were the senior housing owners with the most units owned as of 2025. Welltower Inc. had a total of nearly ******* units, while Ventas Inc. had approximately ****** units.

Welltower Inc., Ventas Inc., and Brookdale Senior Living were the top three senior housing owners in the United States as of June 1, 2025, when considering the number of properties owned. Welltower Inc. owned ***** properties.

In the first half of 2020, senior housing transactions in the United States saw a decline from the previous year. Under the effect of the coronavirus (COVID-19) pandemic, senior housing transactions fell to *** billion U.S. dollars, *** billion U.S. dollars less than the same period in 2019. The percentage of Americans aged 65 years and older is set to rise until at least 2050, which suggests that this market will remain popular among commercial investors in the years to come.

The majority of senior housing units owned by Acts Retirement Services were independent living units in 2024. About ***** of the total ****** units owned by the company fell within this category. Independent living is a housing arrangement designed for older adults, with a focus on the social needs of residents. Conversely, assisted living offers services for residents who need assistance, such as housekeeping, food, and personal care. In 2024, Acts Retirement Services was the ***** largest not-for-profit senior housing organization.

This statistic presents the number of social housing for the elderly in France in 2019, by region. At that date, we can see that Île-de-France had just over *** dwellings for the elderly.

This dataset allows users to map United States Department of Agriculture's (USDA's) rural development multi family housing assets. The USDA, Rural Development (RD) Agency operates a broad range of programs that were formally administered by the Farmers Home Administration to support affordable housing and community development in rural areas. RD helps rural communities and individuals by providing loans and grants for housing and community facilities. RD provides funding for single family homes, apartments for low-income persons or the elderly, housing for farm laborers, childcare centers, fire and police stations, hospitals, libraries, nursing homes and schools.

Financial overview and grant giving statistics of Washington Heights Elderly Housing Corporation

Family characteristics of seniors by housing indicators for Canada, provinces and territories, census metropolitan areas and census agglomerations. Includes age of seniors, tenure including presence of mortgage payments and subsidized housing, condominium status, value (owner-estimated) of dwelling and number of bedrooms.

The number of retirement communities businesses in the United States has increased since 2013. In 2024, there were ****** businesses active in the retirement communities sector, up from ****** businesses in 2023.

Graph and download economic data for Expenditures: Housing by Age: Age 65 or over (CXUHOUSINGLB0407M) from 1988 to 2023 about 65-years +, age, expenditures, housing, and USA.

Around half of all respondents to an *********** survey expected that interest rates for seniors housing in the United States would remain stable in the following 12 months. However, while ** percent believed interest rates would go up, ** percent of respondents believed the opposite to be the case.

Public Housing BuildingsThis National Geospatial Data Asset (NGDA) dataset, shared as a Department of Housing and Urban Development feature layer, displays the location of individual buildings within public housing units throughout the U.S. According to HUD's Public Housing Program, "Public Housing was established to provide decent and safe rental housing for eligible low-income families, the elderly, and persons with disabilities. Public housing comes in all sizes and types, from scattered single family houses to high-rise apartments for elderly families. HUD administers federal aid to local housing agencies that manage the housing for low-income residents at rents they can afford. HUD furnishes technical and professional assistance in planning, developing and managing these developments."Trenton Housing AuthorityData currency: current federal service (Public Housing Building)NGDAID: 130 (Assisted Housing - Public Housing Buildings - National Geospatial Data Asset (NGDA)OGC API Features Link: Not AvailableFor more information, please visit: Public Housing; PHA Contact InformationSupport documentation: DD Public Housing BuildingsFor feedback please contact: Esri_US_Federal_Data@esri.com NGDA Data SetThis data set is part of the NGDA Real Property Theme Community. Per the Federal Geospatial Data Committee (FGDC), Real Property is defined as "the spatial representation (location) of real property entities, typically consisting of one or more of the following: unimproved land, a building, a structure, site improvements and the underlying land. Complex real property entities (that is "facilities") are used for a broad spectrum of functions or missions. This theme focuses on spatial representation of real property assets only and does not seek to describe special purpose functions of real property such as those found in the Cultural Resources, Transportation, or Utilities themes."For other NGDA Content: Esri Federal Datasets

The 2015 American Housing Survey marks the first release of a newly integrated national sample and independent metropolitan area samples. The 2015 release features many variable name revisions, as well as the integration of an AHS Codebook Interactive Tool available on the U.S. Census Bureau Web site. This data collection provides information on representative samples of each of the 15 largest metropolitan areas across the United States, which are also included in the integrated national sample (available as ICPSR 36801). The metropolitan area sample also features representative samples of 10 additional metropolitan areas that are not present in the national sample. The U.S. Department of Housing and Urban Development (HUD) and the U.S. Census Bureau intend to survey the 15 largest metropolitan areas once every 2 years. To ensure the sample was representative of all housing units within each metro area, the U.S. Census Bureau stratified all housing units into one of the following categories: (1) A HUD-assisted unit (as of 2013); (2) Trailer or mobile home; (3) Owner-occupied and one unit in structure; (4) Owner-occupied and two or more units in structure; (5) Renter-occupied and one unit in structure; (6) Renter-occupied and two or more units in structure; (7) Vacant and one unit in structure; (8) Vacant and two or more units in structure; and (9) Other units, such as houseboats and recreational vehicles. The data are presented in three separate parts: Part 1, Household Record (Main Record); Part 2, Person Record; and Part 3, Project Record. Household Record data includes questions about household occupancy and tenure, household exterior and interior structural features, household equipment and appliances, housing problems, housing costs, home improvement, neighborhood features, recent moving information, income, and basic demographic information. The Household Record data also features four rotating topical modules: Arts and Culture, Food Security, Housing Counseling, and Healthy Homes. Person Record data includes questions about personal disabilities, income, and basic demographic information. Finally, Project Record data includes questions about home improvement projects. Specific questions were asked about the types of projects, costs, funding sources, and year of completion.

HUD Multifamily Housing Assisted Properties

Detailed Overview of Subsidized Aid Programs and Population Characteristics

By Matthew Schnars [source]

About this dataset

HUD’s Multifamily Housing property portfolio is integral in providing secure, affordable rental units for low-income households - including seniors, those with special needs, and disabled individuals. Our coverage includes apartments and townhouses but can also include nursing homes, hospitals, elderly housing centers, mobile home parks and retirement service centers. Through subsidies and grants to property owners and developers we further our mission of promoting the construction and preservation of low cost housing opportunities.

This dataset comprises such properties from across the United States; located via our enterprise geocoding service which uses latitude/longitude coordinates as well as associated attributes for those addresses that can be geocoded to an interpolated point along a street segment or a ZIP+4 centroid location. Ultimately this dataset provides key insights into multifamily housing availability throughout the U.S., providing valuable information regarding individual buildings associated with each property while also giving us direct insight into population serviced by such programs in terms of their developmental needs or disabilities which may exist. With these metrics in hand we are better equipped to identify areas where reduced prices on rental units may benefit local communities the most - aiding populations that require our assistance the most directly! Data Dictionary: DD_Multifamily Properties; Date of Coverage: 12/2017; Data Updated: Quarterly

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How to use the dataset

First, let's talk about what kind of information you can get from this dataset. The HUD Multifamily Housing property portfolio consists primarily of rental housing properties with five or more dwelling units such as apartments or town houses. It includes subsidies and grants provided by HUD in order to promote the development and preservation of affordable rental units for low-income populations, and those with special needs such as the elderly, and disabled.

The data contains geographic location information (latitude/longitude coordinates), city/state/ZIP code information as well as other internal identifiers for each property in the HUD portfolio. Additionally, there are columns related to different assistance programs which were previously noted above - Section 8 Project Based Assistance, Section 202 Supportive Housing for the Elderly and Section 811 Supportive Housing for Persons with Disabilities).

In terms of how to use the data itself: due its size it is best explored by importing into an existing database solution like PostgreSQL or MongoDB where you can create custom views based on query keywords that bring back more meaningful results upon execution. Once you define what properties fit your criteria of interest then further analysis can commence - statistical trending on occupancy rates among much else given that next level drilling tends to open up many interesting possibilities like revenue forecasts creating new business models etc.. And speaking of statistics one area worth noting here specifically is that location data provided by HUD may not always be 100% accurate so caution should be exercised when running analytics queries because incorrect locations will lead astray any conclusions reached after running said queries - so feel free to double check your results before leveraging them in any form whatsoever!

Finally keep in mind that since there has only been one version of this dataset released thus far it would probably beneficial if you checked back every quarter or so just incase any changes were made particularity related to program eligibility requirements / reporting requirements etc..

Hope this helps and good luck on your journey considering using 'Hud Multifamily Properties Data' for whatever project at hand 😊

Research Ideas

• To identify potential opportunities for developers looking to add affordable housing in underserved areas. Depending on different factors such as the income of the local population, geography, and the type of funding method used to support these projects, developers could be more likely to invest in those areas that have previously been assisted by HUD programs.
• To evaluate performance measures of existing affordable housing across different locations within a given region or state. This could help identify any discrepancies between properties or address any issues within a...

Financial overview and grant giving statistics of Maple Grove Elderly Housing Corporation

A little over half of investors believe the risk premium of seniors housing in the United States will increase in the next 12 months, according to a June 2022 survey. In this case, the risk premium refers to the spread between the risk-free ******* Treasury and seniors housing cap rates. The average United States risk market premium has hovered between *** and *** percent since 2011.

Number of persons aged 65-79 in special accommodation. 2013-2020 refers to the number of persons in special housing a monthly average of the number of users, from 2021 a municipality-individual median (from the National Board of Health and Welfare’s individual statistics). 2007-2012 the number of users is retrieved from the National Board of Health and Welfare’s individual statistics 1/10. Until 2006 from the National Board of Health and Welfare’s quantitative statistics. It refers to all directing. Data is available according to gender breakdown.