The McAllen-Edinburg-Mission metropolitan area in Texas was ranked first with 27.2 percent of its population living below the poverty level in 2023. Eagle Pass, Texas had the second-highest poverty rate, at 24.4 percent.

In 2021, Philadelphia, Pennsylvania was the city with the highest poverty rate of the United States' most populated cities. In this statistic, the cities are sorted by poverty rate, not population. The most populated city in 2021 according to the source was New York city - which had a poverty rate of 18 percent.

These are the data for the Demographic Profiles displayed on austintexas.gov/demographics. These profiles were published in 2025, but display data from 2023 and 2024.

Most data are from the 2023 American Community Survey (the most recent available at the time of publication), but some data have other sources. All data come from the American Community Survey estimates except for:

Total Population - City of Austin Planning Department (2023) (City and Council Districts only) Population Low-Moderate Income - Dept. of Housing and Urban Development LMISD Summary Data (5 year 2016-2020) Occupied Housing Units - City of Austin Planning Department (2023) (City and Council Districts only) Median Home Closing Price - Austin Board of Realtors (2024) Average Monthly Rent - ApartmentTrends.com by Austin Investor Interests (Q4 2024) Income Restricted Units - City of Austin Affordable Housing Inventory (March 2025) Housing Units - City of Austin Planning Department (2023)(City only) Population Density - Esri Updated Demographics (2024) (County, MSA, Council Districts) Daytime Population Density - Esri Updated Demographics (2024) (County, MSA, Council Districts) Population Density - Calculation derived from 2023 Population Estimates, City of Austin Demographics & Data Division (City only) Daytime Population Density - 2023 Population Estimates, City of Austin Demographics & Data Division (City only) Selected Land Use Percentages - City of Austin Land Use Inventory (2024) Transit Stops - Capital Metro (January 2025)

City, County, and MSA data are 1-Year ACS estimates. Council Districts are 5-year ACS estimates.

Some datapoints may not be available for all geographies.

More information and links to these alternate sources, when available, can be found at austintexas.gov/demographics.

These profiles are updated annually.

City of Austin Open Data Terms of Use – https://data.austintexas.gov/stories/s/ranj-cccq

DeprecatedUpdated for PY-2023 (effective March 1, 2023, to September 30, 2024). Deprecated October 1, 2024.What does the data represent?These are named polygons that follow block group boundaries that contain 51% or greater low-to-moderate income persons as published by HUD from 2011-2015 ACS data. That data has been superseded by data developed from 2016-2020 ACS data by HUD and published at https://services.arcgis.com/VTyQ9soqVukalItT/ArcGIS/rest/services/LMISD_layers/FeatureServer/4. Target areas primarily served residential areas, and each target area ideally could self-identify as the named community.Where were they located?Target Areas of Harris County fit within the Harris County Service Area, which was the unincorporated land of Harris County, Texas plus then-cooperative cities. Any portions of otherwise qualified block groups that extended into non-service area were excluded from the target area. This prevented “double-dipping” community development resource entitlements.How accurate are they?Block group boundaries in Harris County follow visual cues such as roadways and streams. Census Bureau linework attempts to delineate these bounding features but they are seldom more accurate than within thirty feet of ground truth.Full-service city boundaries determine whether an incorporated area is within the Harris County Service Area or the non-service area. These are updated roughly quarterly in the Harris County GIS Repository layer managed by the Harris County Appraisal District. Target areas have been updated each year using this data from the late autumn to the end of each calendar year.When were they collected?When HCCSD updated the Service Area and Target Areas of Harris County in the latter part of each Program Year, it uses the current HUD LMISD dataset and HCAD full-service city boundaries to perform the update. HUD publishes an updated LMISD dataset every year, but the data HUD analyzes to create these updates only changes when an additional five-year period of American Community Survey data has accumulated. Therefore the survey data reported in the HUD LMISD were collected from 4 to 8 years prior (PY2019) to as much as 9 to 13 years prior to publishing the results (PY2023). Unless a local income survey was conducted more recently between one and four years ago, each Program Year’s target area boundaries reflect LMISD block group information collected at least four to as much as thirteen years ago.Who collected them?Harris County Community Services Department (HCCSD) collected and Harris County Housing & Community Development (HCHCD) maintains Harris County Service Area and Target Area information. As representative of one of the largest urban counties in the U.S. and the largest in Texas, the Highest Elected Official in Harris County has delegated HCHCD to implement HUD-assisted community development activities on unincorporated land and on behalf of the cooperative cities. Cooperative cities are generally those of insufficient size to become entitled to HUD funds on their own, i.e. less than 50,000 population. Through 9/30/2024 Harris County maintained agreements with 12 cooperative cities, including: Deer Park, Galena Park, Humble, Jacinto City, Katy, La Porte, Morgan's Point, Seabrook, Shoreacres, South Houston, Tomball, and Webster in PY2023. Tomball ended its agreement 9/30/2024, thereafter becoming part of the non-service area.

This is a historical measure for Strategic Direction 2023. For more data on Austin demographics please visit austintexas.gov/demographics.​

Austin's share of regional households whose income is less than $40,000 and the change since 2016​. Austin's share of regional households whose income is less than $40,000 and the change in that share since 2016. This metric helps us to understand where low income households live in the Austin area since some lower income households may be forced to move from the city to the outskirts in order to seek more affordable housing opportunities.

Of the most populous cities in the U.S., San Jose, California had the highest annual income requirement at ******* U.S. dollars annually for homeowners to have an affordable and comfortable life in 2024. This can be compared to Houston, Texas, where homeowners needed an annual income of ****** U.S. dollars in 2024.

This annual study provides selected income and tax items classified by State, ZIP Code, and the size of adjusted gross income. These data include the number of returns, which approximates the number of households; the number of personal exemptions, which approximates the population; adjusted gross income; wages and salaries; dividends before exclusion; and interest received. Data are based who reported on U.S. Individual Income Tax Returns (Forms 1040) filed with the IRS. SOI collects these data as part of its Individual Income Tax Return (Form 1040) Statistics program, Data by Geographic Areas, ZIP Code Data.

These are the data for displayed in the Demographic Profiles displayed on austintexas.gov/demographics. These profiles were published in 2024, but display data from 2022 and 2023.

Most data are from the 2022 American Community Survey (the most recent available at the time of publication), but some data have other sources. All data come from the American Community Survey estimates except for:

Total Population - City of Austin Planning Department (2023) Population Low-Moderate Income - Dept. of Housing and Urban Development LMISD Summary Data (2022) Occupied Housing Units - City of Austin Planning Department (2023) Median Home Closing Price - Austin Board of Realtors (2023) Average Monthly Rent - Austin Investor Interests (Q4 2023) Income Restricted Units - City of Austin Affordable Housing Inventory Housing Units-City of Austin Planning Department (2023) Population Density - Esri Updated Demographics Daytime Population Density - Esri Updated Demographics Selected Land Use Percentages - City of Austin Land Use Inventory Transit Stops - Capital Metro (2023)

City, County, and MSA data are 1-Year ACS estimates. Council Districts are 5-year ACS estimates.

More information and links to these alternate sources, when available, can be found at austintexas.gov/demographics.

These profiles are updated annually.

City of Austin Open Data Terms of Use – https://data.austintexas.gov/stories/s/ranj-cccq

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 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, 2018-2022 American Community Survey 5-Year Estimates.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..Respondents could report more than one major for their bachelor's degree. This table only counts the first major that was reported and does not necessarily reflect the first degree earned..The 2018-2022 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..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-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

This graph shows the Percentage of households led by a female householder with no spouse present with own children under 18 years living in the household in the U.S. in 2021, by state. In 2021, about 4.24 percent of Californian households were single mother households with at least one child.

Additional information on single mother households and poverty in the United States

For most single mothers a constant battle persists between finding the time and energy to raise their children and the demands of working to supply an income to house and feed their families. The pressures of a single income and the high costs of childcare mean that the risk of poverty for these families is a tragic reality. Comparison of the overall United States poverty rate since 1990 with that of the poverty rate for families with a female householder shows that poverty is much more prevalent in the latter. In 2021, while the overall rate was at 11.6 percent, the rate of poverty for single mother families was 23 percent. Moreover, the degree of fluctuation tends to be lower for single female household families, suggesting the rate of poverty for these groups is less affected by economic conditions.

The sharp rise in the number of children living with a single mother or single father in the United States from 1970 to 2022 suggests more must be done to ensure that families in such situations are able to avoid poverty. Moreover, attention should also be placed on overall racial income inequality given the higher rate of poverty for Hispanic single mother families than their white or Asian counterparts.

Out of all 50 states, New York had the highest per-capita real gross domestic product (GDP) in 2023, at 90,730 U.S. dollars, followed closely by Massachusetts. Mississippi had the lowest per-capita real GDP, at 39,102 U.S. dollars. While not a state, the District of Columbia had a per capita GDP of more than 214,000 U.S. dollars. What is real GDP? A country’s real GDP is a measure that shows the value of the goods and services produced by an economy and is adjusted for inflation. The real GDP of a country helps economists to see the health of a country’s economy and its standard of living. Downturns in GDP growth can indicate financial difficulties, such as the financial crisis of 2008 and 2009, when the U.S. GDP decreased by 2.5 percent. The COVID-19 pandemic had a significant impact on U.S. GDP, shrinking the economy 2.8 percent. The U.S. economy rebounded in 2021, however, growing by nearly six percent. Why real GDP per capita matters Real GDP per capita takes the GDP of a country, state, or metropolitan area and divides it by the number of people in that area. Some argue that per-capita GDP is more important than the GDP of a country, as it is a good indicator of whether or not the country’s population is getting wealthier, thus increasing the standard of living in that area. The best measure of standard of living when comparing across countries is thought to be GDP per capita at purchasing power parity (PPP) which uses the prices of specific goods to compare the absolute purchasing power of a countries currency.