In 2023, about 12 percent of California's population lived below the poverty line. This accounts for persons or families whose collective income in the preceding 12 months was below the national poverty level of the United States.

In 2023, the around 11.1 percent of the population was living below the national poverty line in the United States. Poverty in the United StatesAs shown in the statistic above, the poverty rate among all people living in the United States has shifted within the last 15 years. The United Nations Educational, Scientific and Cultural Organization (UNESCO) defines poverty as follows: “Absolute poverty measures poverty in relation to the amount of money necessary to meet basic needs such as food, clothing, and shelter. The concept of absolute poverty is not concerned with broader quality of life issues or with the overall level of inequality in society.” The poverty rate in the United States varies widely across different ethnic groups. American Indians and Alaska Natives are the ethnic group with the most people living in poverty in 2022, with about 25 percent of the population earning an income below the poverty line. In comparison to that, only 8.6 percent of the White (non-Hispanic) population and the Asian population were living below the poverty line in 2022. Children are one of the most poverty endangered population groups in the U.S. between 1990 and 2022. Child poverty peaked in 1993 with 22.7 percent of children living in poverty in that year in the United States. Between 2000 and 2010, the child poverty rate in the United States was increasing every year; however,this rate was down to 15 percent in 2022. The number of people living in poverty in the U.S. varies from state to state. Compared to California, where about 4.44 million people were living in poverty in 2022, the state of Minnesota had about 429,000 people living in poverty.

Percent of Population Below the Poverty Level (5-year estimate) in Sutter County, CA was 14.80% in January of 2023, according to the United States Federal Reserve. Historically, Percent of Population Below the Poverty Level (5-year estimate) in Sutter County, CA reached a record high of 17.80 in January of 2015 and a record low of 12.60 in January of 2021. Trading Economics provides the current actual value, an historical data chart and related indicators for Percent of Population Below the Poverty Level (5-year estimate) in Sutter County, CA - last updated from the United States Federal Reserve on July of 2025.

Percent of Population Below the Poverty Level (5-year estimate) in Solano County, CA was 9.70% in January of 2023, according to the United States Federal Reserve. Historically, Percent of Population Below the Poverty Level (5-year estimate) in Solano County, CA reached a record high of 13.40 in January of 2015 and a record low of 8.90 in January of 2021. Trading Economics provides the current actual value, an historical data chart and related indicators for Percent of Population Below the Poverty Level (5-year estimate) in Solano County, CA - last updated from the United States Federal Reserve on June of 2025.

Percentage of households at or below county poverty level and deep poverty level across systems in sample (n = 1501) and full community water system list with system boundaries (n = 2882), for 2015‡.

Percent of Population Below the Poverty Level (5-year estimate) in Mendocino County, CA was 15.20% in January of 2023, according to the United States Federal Reserve. Historically, Percent of Population Below the Poverty Level (5-year estimate) in Mendocino County, CA reached a record high of 20.40 in January of 2015 and a record low of 15.20 in January of 2023. Trading Economics provides the current actual value, an historical data chart and related indicators for Percent of Population Below the Poverty Level (5-year estimate) in Mendocino County, CA - last updated from the United States Federal Reserve on June of 2025.

In 2023, the resident population of California was ***** million. This is a slight decrease from the previous year, with ***** million people in 2022. This makes it the most populous state in the U.S. Californian demographics Along with an increase in population, California’s gross domestic product (GDP) has also been increasing, from *** trillion U.S. dollars in 2000 to **** trillion U.S. dollars in 2023. In the same time period, the per-capita personal income has almost doubled, from ****** U.S. dollars in 2000 to ****** U.S. dollars in 2022. In 2023, the majority of California’s resident population was Hispanic or Latino, although the number of white residents followed as a close second, with Asian residents making up the third-largest demographic in the state. The dark side of the Golden State While California is one of the most well-known states in the U.S., is home to Silicon Valley, and one of the states where personal income has been increasing over the past 20 years, not everyone in California is so lucky: In 2023, the poverty rate in California was about ** percent, and the state had the fifth-highest rate of homelessness in the country during that same year, with an estimated ** homeless people per 10,000 of the population.

Percent of Population Below the Poverty Level (5-year estimate) in Sacramento County, CA was 12.60% in January of 2023, according to the United States Federal Reserve. Historically, Percent of Population Below the Poverty Level (5-year estimate) in Sacramento County, CA reached a record high of 18.20 in January of 2015 and a record low of 12.60 in January of 2023. Trading Economics provides the current actual value, an historical data chart and related indicators for Percent of Population Below the Poverty Level (5-year estimate) in Sacramento County, CA - last updated from the United States Federal Reserve on July of 2025.

Summary statistics for water bills and income data in affordability study sample and full community water system list for 2015.

This layer shows poverty status by age group. This is shown by tract, county, and state boundaries. 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. Poverty status is based on income in past 12 months of survey. 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. Current Vintage: 2015-2019ACS Table(s): B17020Data 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 ready-to-use layer 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. For more information about ACS layers, visit the FAQ. 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.

Percent of Population Below the Poverty Level (5-year estimate) in Madera County, CA was 19.90% in January of 2023, according to the United States Federal Reserve. Historically, Percent of Population Below the Poverty Level (5-year estimate) in Madera County, CA reached a record high of 23.50 in January of 2015 and a record low of 19.00 in January of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for Percent of Population Below the Poverty Level (5-year estimate) in Madera County, CA - last updated from the United States Federal Reserve on June of 2025.

Poverty and low-income statistics by disability status, age group, sex and economic family type, Canada, annual.

Crude and adjusted mean affordability ratios by system size, for 2015‡.

The COVID-19 Vulnerability and Recovery Index uses Tract and ZIP Code-level data* to identify California communities most in need of immediate and long-term pandemic and economic relief. Specifically, the Index is comprised of three components — Risk, Severity, and Recovery Need with the last scoring the ability to recover from the health, economic, and social costs of the pandemic. Communities with higher Index scores face a higher risk of COVID-19 infection and death and a longer uphill economic recovery. Conversely, those with lower scores are less vulnerable.

The Index includes one overarching Index score as well as a score for each of the individual components. Each component includes a set of indicators we found to be associated with COVID-19 risk, severity, or recovery in our review of existing indices and independent analysis. The Risk component includes indicators related to the risk of COVID-19 infection. The Severity component includes indicators designed to measure the risk of severe illness or death from COVID-19. The Recovery Need component includes indicators that measure community needs related to economic and social recovery. The overarching Index score is designed to show level of need from Highest to Lowest with ZIP Codes in the Highest or High need categories, or top 20th or 40th percentiles of the Index, having the greatest need for support.

The Index was originally developed as a statewide tool but has been adapted to LA County for the purposes of the Board motion. To distinguish between the LA County Index and the original Statewide Index, we refer to the revised Index for LA County as the LA County ARPA Index.

*Zip Code data has been crosswalked to Census Tract using HUD methodology

Indicators within each component of the LA County ARPA Index are:Risk: Individuals without U.S. citizenship; Population Below 200% of the Federal Poverty Level (FPL); Overcrowded Housing Units; Essential Workers Severity: Asthma Hospitalizations (per 10,000); Population Below 200% FPL; Seniors 75 and over in Poverty; Uninsured Population; Heart Disease Hospitalizations (per 10,000); Diabetes Hospitalizations (per 10,000)Recovery Need: Single-Parent Households; Gun Injuries (per 10,000); Population Below 200% FPL; Essential Workers; Unemployment; Uninsured PopulationData are sourced from US Census American Communities Survey (ACS) and the OSHPD Patient Discharge Database. For ACS indicators, the tables and variables used are as follows:

Indicator

ACS Table/Years

Numerator

Denominator

Non-US Citizen

B05001, 2019-2023

b05001_006e

b05001_001e

Below 200% FPL

S1701, 2019-2023

s1701_c01_042e

s1701_c01_001e

Overcrowded Housing Units

B25014, 2019-2023

b25014_006e + b25014_007e + b25014_012e + b25014_013e

b25014_001e

Essential Workers

S2401, 2019-2023

s2401_c01_005e + s2401_c01_011e + s2401_c01_013e + s2401_c01_015e + s2401_c01_019e + s2401_c01_020e + s2401_c01_023e + s2401_c01_024e + s2401_c01_029e + s2401_c01_033e

s2401_c01_001

Seniors 75+ in Poverty

B17020, 2019-2023

b17020_008e + b17020_009e

b17020_008e + b17020_009e + b17020_016e + b17020_017e

Uninsured

S2701, 2019-2023

s2701_c05_001e

NA, rate published in source table

Single-Parent Households

S1101, 2019-2023

s1101_c03_005e + s1101_c04_005e

s1101_c01_001e

Unemployment

S2301, 2019-2023

s2301_c04_001e

NA, rate published in source table

The remaining indicators are based data requested and received by Advancement Project CA from the OSHPD Patient Discharge database. Data are based on records aggregated at the ZIP Code level:

Indicator

Years

Definition

Denominator

Asthma Hospitalizations

2017-2019

All ICD 10 codes under J45 (under Principal Diagnosis)

American Community Survey, 2015-2019, 5-Year Estimates, Table DP05

Gun Injuries

2017-2019

Principal/Other External Cause Code "Gun Injury" with a Disposition not "Died/Expired". ICD 10 Code Y38.4 and all codes under X94, W32, W33, W34, X72, X73, X74, X93, X95, Y22, Y23, Y35 [All listed codes with 7th digit "A" for initial encounter]

American Community Survey, 2015-2019, 5-Year Estimates, Table DP05

Heart Disease Hospitalizations

2017-2019

ICD 10 Code I46.2 and all ICD 10 codes under I21, I22, I24, I25, I42, I50 (under Principal Diagnosis)

American Community Survey, 2015-2019, 5-Year Estimates, Table DP05

Diabetes (Type 2) Hospitalizations

2017-2019

All ICD 10 codes under E11 (under Principal Diagnosis)

American Community Survey, 2015-2019, 5-Year Estimates, Table DP05

For more information about this dataset, please contact egis@isd.lacounty.gov.

Market Basket Measure (MBM) thresholds for the reference family by MBM region and base year. Total thresholds as well as thresholds for the food, clothing, transportation, shelter and other expenses components are presented, in current and constant dollars, annual.

Percent of Population Below the Poverty Level (5-year estimate) in Contra Costa County, CA was 8.30% in January of 2023, according to the United States Federal Reserve. Historically, Percent of Population Below the Poverty Level (5-year estimate) in Contra Costa County, CA reached a record high of 10.90 in January of 2015 and a record low of 8.20 in January of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for Percent of Population Below the Poverty Level (5-year estimate) in Contra Costa County, CA - last updated from the United States Federal Reserve on June of 2025.

Low income cut-offs (LICOs) before and after tax by community size and family size, in current dollars, annual.

Racially Concentrated Areas of Affluence (RCAA's)

The concept of Racially Concentrated Areas of Affluence (RCAAs) was originally developed by scholars at the University of Minnesota to illustrate the flip side of the Racially and Ethnically Concentrated Areas of Poverty (R/ECAPs) metric used by the California Department of Housing and Community Development (HCD) in the 2015 Affirmatively Furthering Fair Housing (AFFH) rule to more fully tell the story of segregation in the United States.

As stated in HCD’s AFFH Guidance Memo, when analyzing patterns and trends of segregation and proposing policy approaches in the Housing Element, localities should not only focus on communities of color. Segregation is a continuum, with polarity between race, poverty, and affluence, which can be a direct product of the same policies and practices. To better evaluate these conditions, both sides of the continuum should be considered and compare patterns within the community and across the region. This more holistic approach will better unveil deeply rooted policies and practices and improve identification and prioritization of contributing factors to inform more meaningful actions.

HCD has created a new version of the RCAA metric to better reflect California’s relative diversity and regional conditions, and to aid local jurisdictions in their analysis of racially concentrated areas of poverty and affluence pursuant to AB 686 and AB 1304. HCD’s RCAA metric is provided as a resource to be paired with local data and knowledge – jurisdictions are encouraged but not required to use the RCAA layer provided by HCD in their housing element analyses.

To develop the RCAA layer, staff first calculated a Location Quotient (LQ) for each California census tract using data from the 2015-2019 American Community Survey data. This LQ represents the percentage of total white population (White Alone, Not Hispanic or Latino) for each census tract compared to the average percentage of total white population for all census tracts in a given Council of Governments' (COG) region. For example, a census tract with a LQ of 1.5 has a percentage of total white population that is 1.5 times higher than the average percentage of total white population in the given COG region.

To determine the RCAAs, census tracts with a LQ of more than 1.25 and a median income 1.5 times higher than the COG Area Median Income (AMI) (or 1.5x the State AMI, whichever is lower) were assigned a numeric score of 1 (Is a RCAA). Census tracts that did not meet this criterion were assigned a score of 0 (Not a RCAA).

COG AMI was determined by averaging the 2019 ACS established AMI's for each county within the given COG region. 2019 ACS AMI limits can be found here: https://www.census.gov/quickfacts/fact/table/US/PST045219 [census.gov]. State AMI was based on the ACS 2019 California state AMI ($75,235), which can be found here: https://www.census.gov/quickfacts/fact/table/CA/INC110219 [census.gov].

Census tracts with a total population of less than 75 people, in which the census tract was also largely contained within a non-urbanized area such as a park, open space, or airport, were not identified as RCAAs.

Data Source: American Community Survey (ACS), 2015-2019

References: Wilson, William J. (1980). The Declining Significance of Race: Blacks and Changing American Institutions. Chicago: University of Chicago Press.

Damiano, T., Hicks, J., & Goetz, E. (2017). Racially Concentrated Areas of Affluence: A Preliminary Investigation.

To learn more about R/ECAPs visit: https://www.huduser.gov/portal/periodicals/cityscpe/vol21num1/ch4.pdf [huduser.gov]

Original data created by HCD, PlaceWorks 2021

Percent of Population Below the Poverty Level (5-year estimate) in Kern County, CA was 19.00% in January of 2023, according to the United States Federal Reserve. Historically, Percent of Population Below the Poverty Level (5-year estimate) in Kern County, CA reached a record high of 23.50 in January of 2015 and a record low of 19.00 in January of 2023. Trading Economics provides the current actual value, an historical data chart and related indicators for Percent of Population Below the Poverty Level (5-year estimate) in Kern County, CA - last updated from the United States Federal Reserve on July of 2025.

Percent of Population Below the Poverty Level (5-year estimate) in San Bernardino County, CA was 13.60% in January of 2023, according to the United States Federal Reserve. Historically, Percent of Population Below the Poverty Level (5-year estimate) in San Bernardino County, CA reached a record high of 19.50 in January of 2015 and a record low of 13.60 in January of 2023. Trading Economics provides the current actual value, an historical data chart and related indicators for Percent of Population Below the Poverty Level (5-year estimate) in San Bernardino County, CA - last updated from the United States Federal Reserve on July of 2025.