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.

The Census Bureau determines that a person is living in poverty when his or her total household income compared with the size and composition of the household is below the poverty threshold. The Census Bureau uses the federal government's official definition of poverty to determine the poverty threshold. Beginning in 2000, individuals were presented with the option to select one or more races. In addition, the Census asked individuals to identify their race separately from identifying their Hispanic origin. The Census has published individual tables for the races and ethnicities provided as supplemental information to the main table that does not dissaggregate by race or ethnicity. Race categories include the following - White, Black or African American, American Indian or Alaska Native, Asian, Native Hawaiian or Other Pacific Islander, Some other race, and Two or more races. We are not including specific combinations of two or more races as the counts of these combinations are small. Ethnic categories include - Hispanic or Latino and White Non-Hispanic. This data comes from the American Community Survey (ACS) 5-Year estimates, table B17001. The ACS collects these data from a sample of households on a rolling monthly basis. ACS aggregates samples into one-, three-, or five-year periods. CTdata.org generally carries the five-year datasets, as they are considered to be the most accurate, especially for geographic areas that are the size of a county or smaller.Poverty status determined is the denominator for the poverty rate. It is the population for which poverty status was determined so when poverty is calculated they exclude institutionalized people, people in military group quarters, people in college dormitories, and unrelated individuals under 15 years of age.Below poverty level are households as determined by the thresholds based on the criteria of looking at household size, Below poverty level are households as determined by the thresholds based on the criteria of looking at household size, number of children, and age of householder.number of children, and age of householder.

In 2021, the city of Philadelphia in Pennsylvania had the highest family poverty rate of the 25 most populated cities in the United States. The city with the next highest poverty rate was Houston, Texas.

VITAL SIGNS INDICATOR Poverty (EQ5)

FULL MEASURE NAME The share of the population living in households that earn less than 200 percent of the federal poverty limit

LAST UPDATED December 2018

DESCRIPTION Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

DATA SOURCE U.S Census Bureau: Decennial Census http://www.nhgis.org (1980-1990) http://factfinder2.census.gov (2000)

U.S. Census Bureau: American Community Survey Form C17002 (2006-2017) http://api.census.gov

METHODOLOGY NOTES (across all datasets for this indicator) The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. Poverty rates do not include unrelated individuals below 15 years old or people who live in the following: institutionalized group quarters, college dormitories, military barracks, and situations without conventional housing. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or noncash benefits (such as public housing, Medicaid, and food stamps). For the national poverty level definitions by year, see: https://www.census.gov/hhes/www/poverty/data/threshld/index.html For an explanation on how the Census Bureau measures poverty, see: https://www.census.gov/hhes/www/poverty/about/overview/measure.html

For the American Community Survey datasets, 1-year data was used for region, county, and metro areas whereas 5-year rolling average data was used for city and census tract.

To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

In 2021, New York city had the highest number of people living below the poverty line, with 1.4 million people living in poverty. This is significantly higher than any of the other most populated cities.

VITAL SIGNS INDICATOR
Poverty (EQ5)

FULL MEASURE NAME
The share of the population living in households that earn less than 200 percent of the federal poverty limit

LAST UPDATED
January 2023

DESCRIPTION
Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

DATA SOURCE
U.S Census Bureau: Decennial Census - http://www.nhgis.org
1980-2000

U.S. Census Bureau: American Community Survey - https://data.census.gov/
2007-2021
Form C17002

CONTACT INFORMATION
vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator)
The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or non-cash benefits (such as public housing, Medicaid and food stamps).

For the national poverty level definitions by year, see: US Census Bureau Poverty Thresholds - https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-poverty-thresholds.html.

For an explanation on how the Census Bureau measures poverty, see: How the Census Bureau Measures Poverty - https://www.census.gov/topics/income-poverty/poverty/guidance/poverty-measures.html.

American Community Survey (ACS) 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.

To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

In 2023, Wildwood-The Villages metropolitan area in Florida was ranked first, with 39.3 percent of its population aged under 18 years living below the poverty level. McAllen-Edinburg-Mission metro area in Texas had the second-highest rate of child poverty in the nation.

This layer shows poverty status by age group. Data is from US Census American Community Survey (ACS) 5-year estimates.This layer is symbolized to show the percentage of the population whose income falls below the Federal poverty line. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online). To view only the census tracts that are predominantly in Tempe, add the expression City is Tempe in the map filter settings.A ‘Null’ entry in the estimate indicates that data for this geographic area cannot be displayed because the number of sample cases is too small (per the U.S. Census).Vintage: 2016-2020ACS Table(s): B17020 (Not all lines of these ACS tables are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Data Preparation: Data curated from Esri Living Atlas clipped to Census Tract boundaries that are within or adjacent to the City of Tempe boundaryDate of Census update: March 17, 2022National Figures: data.census.govAdditional Census data notes and data processing notes are available at the Esri Living Atlas Layer:https://tempegov.maps.arcgis.com/home/item.html?id=0e468b75bca545ee8dc4b039cbb5aff6 (Esri's Living Atlas always shows latest data)

The municipalities of Manapiare and Bolívar, located in the Venezuelan states of Amazonas and Falcón, respectively, registered the highest share of population living under the poverty line in the country in 2021. That year, almost the entire population of these municipalities was reported to be living in poverty. All the 25 Venezuelan cities listed in this statistic had at least 99.7 percent of their population living under the poverty line.

In 2023, around 27.4 percent of residents in Bremen were at risk of living in poverty. This list shows the 15 cities in Germany with the highest at-risk-of-poverty rates.

This map symbolizes the relative percentages of adults living below the poverty level for the City's 12 Data Divisions, aggregating the tract-level estimates from the the Census Bureau's American Community Survey 2018 five-year samples. Please refer to the map's legend for context to the color shading -- darker hues indicate a higher level of adults living below the poverty level.If you click on each Data Division, you can view other Census demographic information about that Data Division in addition to the population count.About the Census Data:The data comes from the U.S. Census Bureau's American Community Survey's 2014-2018 five-year samples. The American Community Survey (ACS) is an ongoing survey conducted by the federal government that provides vital information annually about America and its population. Information from the survey generates data that help determine how more than $675 billion in federal and state funds are distributed each year.For more information about the Census Bureau's ACS data and process of constructing the survey, visit the ACS's About page.About the City's Data Divisions:As a planning analytic tool, an interdepartmental working group divided Rochester into 12 “data divisions.” These divisions are well-defined and static so they are positioned to be used by the City of Rochester for statistical and planning purposes. Census data is tied to these divisions and serves as the basis for analyses over time. As such, the data divisions are designed to follow census boundaries, while also recognizing natural and human-made boundaries, such as the River, rail lines, and highways. Historical neighborhood boundaries, while informative in the division process, did not drive the boundaries. Data divisions are distinct from the numerous neighborhoods in Rochester. Neighborhood boundaries, like quadrant boundaries, police precincts, and legislative districts often change, which makes statistical analysis challenging when looking at data over time. The data division boundaries, however, are intended to remain unchanged. It is hoped that over time, all City data analysts will adopt the data divisions for the purpose of measuring change over time throughout the city.

This table contains data on the percentage of the total population living below 200% of the Federal Poverty Level (FPL), and the percentage of children living below 200% FPL for California, its regions, counties, cities, towns, public use microdata areas, and census tracts. Data for time periods 2011-2015 (overall poverty) and 2012-2016 (child poverty) and with race/ethnicity stratification is included in the table. The poverty rate table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Poverty is an important social determinant of health (see http://www.healthypeople.gov/2020/topicsobjectives2020/overview.aspx?topicid=39) that can impact people’s access to basic necessities (housing, food, education, jobs, and transportation), and is associated with higher incidence and prevalence of illness, and with reduced access to quality health care. More information on the data table and a data dictionary can be found in the About/Attachments section.

This layer shows poverty status by age group. Data is from US Census American Community Survey (ACS) 5-year estimates.This layer is symbolized to show the percentage of the population whose income falls below the Federal poverty line. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online). To view only the census tracts that are predominantly in Tempe, add the expression City is Tempe in the map filter settings.A ‘Null’ entry in the estimate indicates that data for this geographic area cannot be displayed because the number of sample cases is too small (per the U.S. Census).Vintage: 2017-2021ACS Table(s): B17020 (Not all lines of these ACS tables are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Data Preparation: Data curated from Esri Living Atlas clipped to Census Tract boundaries that are within or adjacent to the City of Tempe boundaryDate of Census update: December 8, 2022National Figures: data.census.govAdditional Census data notes and data processing notes are available at the Esri Living Atlas Layer:https://tempegov.maps.arcgis.com/home/item.html?id=0e468b75bca545ee8dc4b039cbb5aff6 (Esri's Living Atlas always shows latest data)

This poverty rate data shows what percentage of the measured population* falls below the poverty line. Poverty is closely related to income: different “poverty thresholds” are in place for different sizes and types of household. A family or individual is considered to be below the poverty line if that family or individual’s income falls below their relevant poverty threshold. For more information on how poverty is measured by the U.S. Census Bureau (the source for this indicator’s data), visit the U.S. Census Bureau’s poverty webpage.

The poverty rate is an important piece of information when evaluating an area’s economic health and well-being. The poverty rate can also be illustrative when considered in the contexts of other indicators and categories. As a piece of data, it is too important and too useful to omit from any indicator set.

The poverty rate for all individuals in the measured population in Champaign County has hovered around roughly 20% since 2005. However, it reached its lowest rate in 2021 at 14.9%, and its second lowest rate in 2023 at 16.3%. Although the American Community Survey (ACS) data shows fluctuations between years, given their margins of error, none of the differences between consecutive years’ estimates are statistically significant, making it impossible to identify a trend.

Poverty rate data was sourced from the U.S. Census Bureau’s American Community Survey 1-Year Estimates, which are released annually.

As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Poverty Status in the Past 12 Months by Age.

*According to the U.S. Census Bureau document “How Poverty is Calculated in the ACS," poverty status is calculated for everyone but those in the following groups: “people living in institutional group quarters (such as prisons or nursing homes), people in military barracks, people in college dormitories, living situations without conventional housing, and unrelated individuals under 15 years old."

Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (17 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (25 September 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (16 September 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).

This report was written in collaboration between the Mayor's Office of Innovation and the Rochester Monroe Anti-Poverty Initiative (RMAPI) and released in December 2019. Executive SummaryThe Rochester Monroe Anti-Poverty Initiative (RMAPI) has selected single female headed households with children as one of its key target populations in which to focus strategy and its next phase of initiatives. This report is intended to provide additional insight on this population to support the next phase of RMAPI’s strategic planning as well as broader advocacy efforts on behalf of this population.

We begin with a brief summary of historic policy and societal factors known to have contributed to the current day inequities, written in collaboration with content experts from RMAPI.

The core of this report is a fact sheet based on analysis of US Census data. Major findings include:

Finding 1: Families headed by unmarried parents are a significant segment of the city population and account for the majority of individuals living below the poverty level in the city.

Finding 2: Unmarried households with children experience lower incomes, lower rates of home ownership, and higher rent burdens compared to their married counterparts

Finding 3: Women and people of color are overrepresented among the heads of unmarried households with children.

Finding 4: Four in ten unmarried householders with children have less than a high school education. Nearly 80 percent of those without a high school education are in poverty.

Finding 5: Unmarried householders with children in poverty are more likely to be disabled or face other common barriers to employment.

Finding 6: The more adults present in unmarried households with children, the less likely that household is to be in poverty. This trend amplifies when considering the number of employed adults.

Finding 7: Unmarried parents under age 40 head the majority of all households with children in Rochester. Younger householders correlate with higher poverty rates regardless of marriage status.

Finding 8: A birth before age 20, being unmarried, and having not completed high school education are three factors that, when compounded, are associated with poor economic outcomes.

Finding 9: The highest densities of unmarried householders with children are clustered in the highest poverty neighborhoods in the city of Rochester

We end with a discussion of the gaps in available data, acknowledging that there is room for further investigation and interpretation, data collection, and insights. We recommend readers to think critically about what is presented and how it might impact their own work in poverty reduction efforts. We present a series of questions that are a jumping off point for new inquiry and reflection. Methodology can be found in the Appendix.

Data Source:2017 Census American Community Survey 5-Year Estimates, Public Microdata SampleData and documentation can be accessed here:https://www.census.gov/programs-surveys/acs/data/pums.html

2020 data excluded because the U.S. Census Bureau did not release 2020 ACS 1-year estimates due to COVID-19. Some racial and ethnic categories are suppressed to avoid misleading estimates when the relative standard error exceeds 30%.

Data Source: American Community Survey (ACS) 1-Year Estimates

Why This Matters

Poverty threatens the overall well-being of individuals and families, limiting access to stable housing, healthy foods, health care, and educational and employment opportunities, among other basic needs.Poverty is associated with a higher risk of adverse health outcomes, including chronic physical and mental illness, lower life expectancy, developmental delays, and others.

Racist policies and practices have contributed to racial economic inequities. Nationally, Black, Indigenous, and people of color experience poverty at higher rates than white Americans, on average.

The District's Response

Boosting assistance programs that provide temporary cash and health benefits to help low-income residents meet their basic needs, including Medicaid, TANF For District Families, SNAP, etc.

Housing assistance and employment and career training programs to support resident’s housing and employment security. These include the Emergency Rental Assistance Program, Permanent Supportive Housing vouchers, Career MAP, the DC Infrastructure Academy, among other programs and services.

Creation of the DC Commission on Poverty to study poverty issues, evaluate poverty reduction initiatives, and make recommendations to the Mayor and the Council.

This dataset provide the number of high-poverty, low-opportunity census tracts by town. These tracts were identified for PA 23-205 Section 101 as follows: "High poverty, low opportunity areas" mean a census tract in the state where thirty percent or more of the residents have incomes below the federal poverty level, according to the 2021 five-year United States Census Bureau American Community Survey.

The 2021 five-year American Community Survey estimates were used to identify the tracts.

Tabular data of population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2020 census tracts split by 2022 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/) released 2020 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Field:CT20: 2020 Census tractFIP22: 2022 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2022) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT20FIP22CSA: 2020 census tract with 2022 city FIPs for incorporated cities and unincorporated areas and LA neighborhoods. SPA22: 2022 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD22: 2022 Health District (HD) number: HD_NAME: Health District name.POP22_AGE_0_4: 2022 population 0 to 4 years oldPOP22_AGE_5_9: 2022 population 5 to 9 years old POP22_AGE_10_14: 2022 population 10 to 14 years old POP22_AGE_15_17: 2022 population 15 to 17 years old POP22_AGE_18_19: 2022 population 18 to 19 years old POP22_AGE_20_44: 2022 population 20 to 24 years old POP22_AGE_25_29: 2022 population 25 to 29 years old POP22_AGE_30_34: 2022 population 30 to 34 years old POP22_AGE_35_44: 2022 population 35 to 44 years old POP22_AGE_45_54: 2022 population 45 to 54 years old POP22_AGE_55_64: 2022 population 55 to 64 years old POP22_AGE_65_74: 2022 population 65 to 74 years old POP22_AGE_75_84: 2022 population 75 to 84 years old POP22_AGE_85_100: 2022 population 85 years and older POP22_WHITE: 2022 Non-Hispanic White POP22_BLACK: 2022 Non-Hispanic African AmericanPOP22_AIAN: 2022 Non-Hispanic American Indian or Alaska NativePOP22_ASIAN: 2022 Non-Hispanic Asian POP22_HNPI: 2022 Non-Hispanic Hawaiian Native or Pacific IslanderPOP22_HISPANIC: 2022 HispanicPOP22_MALE: 2022 Male POP22_FEMALE: 2022 Female POV22_WHITE: 2022 Non-Hispanic White below 100% Federal Poverty Level POV22_BLACK: 2022 Non-Hispanic African American below 100% Federal Poverty Level POV22_AIAN: 2022 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV22_ASIAN: 2022 Non-Hispanic Asian below 100% Federal Poverty Level POV22_HNPI: 2022 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV22_HISPANIC: 2022 Hispanic below 100% Federal Poverty Level POV22_TOTAL: 2022 Total population below 100% Federal Poverty Level POP22_TOTAL: 2022 Total PopulationAREA_SQMil: Area in square mile.POP22_DENSITY: Population per square mile.POV22_PERCENT: Poverty rate/percentage.How this data created?The tabular data of population by age groups, by ethnic groups and by gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2020 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Note:1. Population and poverty data estimated as of July 1, 2022. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundary are not the same because boundary is reviewed and updated annually.

This layer shows poverty status by age group. Data is from US Census American Community Survey (ACS) 5-year estimates.This layer is symbolized to show the percentage of the population whose income falls below the Federal poverty line. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online). To view only the census tracts that are predominantly in Tempe, add the expression City is Tempe in the map filter settings.A ‘Null’ entry in the estimate indicates that data for this geographic area cannot be displayed because the number of sample cases is too small (per the U.S. Census).Vintage: 2018-2022ACS Table(s): B17020 (Not all lines of these ACS tables are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community SurveyData Preparation: Data curated from Esri Living Atlas clipped to Census Tract boundaries that are within or adjacent to the City of Tempe boundaryDate of Census update: December 15, 2023National Figures: data.census.gov