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Percentage of owner-occupied housing units. The 2023 County Health Rankings used data from 2017-2021 for this measure.

Housing is central to opportunities for living long and well, and stable and affordable housing is an essential element of healthy communities. Homeownership is associated with better health, fewer illnesses, and lower rates of depression and anxiety.1 Homeownership has historically been a springboard for families to enter the middle class. Owning a home can, over time, help build savings for education or for other opportunities important to health and future family wealth. High levels of homeownership are associated with more stable housing and more tightly knit communities.

Find strategies to address Homeownership*

Data and methods

Data Source

American Community Survey, 5-year estimates

The American Community Survey (ACS) is a nationwide survey designed to provide communities with a fresh look at how they are changing. It is a critical element in the Census Bureau's reengineered decennial census program. The ACS collects and produces population and housing information every year instead of every ten years, and publishes both one-year and five-year estimates. The County Health Rankings use American Community Survey data to obtain measures of social and economic factors.

Website to download data
For more detailed methodological information

Key Measure Methods

Homeownership is a percentage

Homeownership is the percentage of occupied housing units that are owned.


The numerator is the total number of owner-occupied housing units in a county.


The denominator is the total occupied housing units in a county.

Can This Measure Be Used to Track Progress

This measure can be used to track progress with some caveats. It is important to note that the estimate provided in the County Health Rankings is a 5-year average. However, for counties with a population greater than 20,000, single-year estimates can be obtained from the resource listed below.

Finding More Data

Disaggregation means breaking data down into smaller, meaningful subgroups. Disaggregated data are often broken down by characteristics of people or where they live. Disaggregated data can reveal inequalities that are otherwise hidden. These data can be disaggregated by:

  • Age
  • Race
  • Education
  • Income
  • Subcounty Area

This measure can be calculated for census tracts and census block groups using table B25003. It can be calculated by race using tables B25003A-I; by age, table B25007; by education, table B25013; and by income, table B25118. These tables can be accessed at https://data.census.gov/.


1 Macintyre S, Hiscock R, Kearns A, Ellaway A. Housing, tenure and health inequalities: A three-dimensional perspective on people, homes, and neighbourhoods. In: Graham H, ed. Understanding Health Inequalities. New York: Open University Press; 2000.