In 2023, 6.4 percent of Asian families in the United States were living below the poverty level. The poverty rate of Asian families in the U.S. peaked in 2003, when 10.2 percent of Asian families were living below the poverty level. Poverty is the state of one who lacks a certain amount of material possessions or money. Absolute poverty or destitution is inability to afford basic human needs, which commonly includes clean and fresh water, nutrition, health care, education, clothing and shelter.

This statistic shows the percentage of Asian-American adults living in poverty in the United States, as differentiated by specific Asian heritage groups in 2010. 15 percent of Korean-Americans lived in poverty in the United States as of 2010.

In 2023, 5.2 percent of married-couple Asian families were living below the poverty level in the United States.Poverty is the state of one who lacks a certain amount of material possessions or money. Absolute poverty or destitution is inability to afford basic human needs, which commonly includes clean and fresh water, nutrition, health care, education, clothing and shelter.

The average for 2021 based on 5 countries was 3.76 percent. The highest value was in India: 12.9 percent and the lowest value was in Malaysia: 0 percent. The indicator is available from 1963 to 2023. Below is a chart for all countries where data are available.

Data for the Asian alone population as reported by the US Census Bureau, American Community Survey (ACS) 5-year estimates. The year shown in the dataset referes to the final year of the five-year reporting period (ie "2019" refers to the 2015-2019 ACS).

Historical dataset showing South Asia poverty rate by year from 1981 to 2023.

In 2023, 9.1 percent of Asian families with a single father were living below the poverty level in the United States.Poverty is the state of one who lacks a certain amount of material possessions or money. Absolute poverty or destitution is inability to afford basic human needs, which commonly includes clean and fresh water, nutrition, health care, education, clothing and shelter.

Between 2019 and 2023, people living in households in the Asian and ‘Other’ ethnic groups were most likely to be in persistent low income before and after housing costs

Most remarkably, the poverty rate in East Asia & The Pacific fell from over ** percent in 1990 to *** percent in 2022, underlining the rapid increase of living standards in the region over the past three decades. Also, South Asia has seen a remarkable reduction in poverty during the period, from around ** percent in 1990 to less than ** percent in 2022. As of 2019, Sub-Saharan Africa was the region with the highest share of people living on less than 2.15 U.S. dollars per day, but also here, there has been a poverty reduction since 1990.

Historical dataset showing East Asia & Pacific poverty rate by year from 1981 to 2023.

Note. ***p

Malaysia Hardcore Poverty Rates: Chinese data was reported at 0.032 % in 2012. This records a decrease from the previous number of 0.082 % for 2009. Malaysia Hardcore Poverty Rates: Chinese data is updated yearly, averaging 0.200 % from Dec 1984 (Median) to 2012, with 12 observations. The data reached an all-time high of 2.190 % in 1984 and a record low of 0.032 % in 2012. Malaysia Hardcore Poverty Rates: Chinese data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Malaysia – Table MY.G064: Household Income and Basic Amenities Survey: Poverty Rates.

Over the past three decades, the number of people living on less than 2.15 U.S. dollars a day in terms of 2017 Purchasing Power Parities either dropped or remained stable across all regions except for Sub-Saharan Africa. On the continent, the number of people living on less than 2.15 U.S. dollars a day increased from 282.2 million in 1990 to nearly 411.15 million in 2019. East Asia & The Pacific saw the most significant poverty reduction, where 20.28 million lived in poverty in 2022 compared to more than one billion in 1990. Even though the absolute number of people living in poverty in Sub-Saharan Africa increased, the share fell during the same period, indicating that there has been poverty reduction in the region as well.

This dataset provides a detailed view of South Asian countries' socio-economic, environmental, and governance metrics from 2000 to 2023. It compiles key indicators like GDP, unemployment, literacy rates, energy use, governance measures, and more to facilitate a comprehensive analysis of each country’s growth, stability, and development trends over the years. The data covers Bangladesh, Bhutan, India, Pakistan, Nepal, Sri Lanka, Afghanistan, and Maldives.

Key Indicators Economic Metrics: Includes GDP (both total and per capita in USD), annual GDP growth rates, inflation, and foreign direct investment. These metrics offer insight into economic health, growth rate, and international investment trends across the region. Employment and Trade: Tracks unemployment rates as a percentage of the labor force and trade (as a percentage of GDP), helping assess workforce stability and international commerce engagement. Income and Poverty: Features the Gini index (for income inequality) and poverty headcount ratio at $2.15/day, showing income distribution and poverty levels. These indicators reveal disparities and poverty within each country. Population Statistics: Includes total population, annual population growth, and urban population percentage, capturing demographic trends and urbanization rates. Social Indicators: Covers literacy rates, school enrollment in primary education, life expectancy at birth, infant mortality rates, and access to electricity, basic water, and sanitation services. These data points help measure the population’s health, education levels, and access to essential services. Environmental and Energy Metrics: Tracks CO2 emissions, PM2.5 air pollution, renewable energy consumption, and forest area. This environmental data is crucial for analyzing air quality, sustainable energy use, and forest coverage trends. Governance Indicators: Includes metrics such as control of corruption, political stability, regulatory quality, rule of law, and voice and accountability. These indicators reflect each country’s governance quality and institutional stability. Digital and Technological Growth: Measures internet usage rates, research and development spending, and high-technology exports. These statistics indicate digital access, innovation, and technological progress. This dataset, sourced from the World Bank DataBank, provides a robust foundation for studying South Asia's socio-economic, environmental, and governance progress. By analyzing these diverse indicators, researchers and policymakers can gain a deeper understanding of the region’s development path and identify areas that need improvement.

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 2021 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 tractFIP21: 2021 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2021) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT20FIP21CSA: 2020 census tract with 2021 city FIPs for incorporated cities, 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.POP21_AGE_0_4: 2021 population 0 to 4 years oldPOP21_AGE_5_9: 2021 population 5 to 9 years old POP21_AGE_10_14: 2021 population 10 to 14 years old POP21_AGE_15_17: 2021 population 15 to 17 years old POP21_AGE_18_19: 2021 population 18 to 19 years old POP21_AGE_20_44: 2021 population 20 to 24 years old POP21_AGE_25_29: 2021 population 25 to 29 years old POP21_AGE_30_34: 2021 population 30 to 34 years old POP21_AGE_35_44: 2021 population 35 to 44 years old POP21_AGE_45_54: 2021 population 45 to 54 years old POP21_AGE_55_64: 2021 population 55 to 64 years old POP21_AGE_65_74: 2021 population 65 to 74 years old POP21_AGE_75_84: 2021 population 75 to 84 years old POP21_AGE_85_100: 2021 population 85 years and older POP21_WHITE: 2021 Non-Hispanic White POP21_BLACK: 2021 Non-Hispanic African AmericanPOP21_AIAN: 2021 Non-Hispanic American Indian or Alaska NativePOP21_ASIAN: 2021 Non-Hispanic Asian POP21_HNPI: 2021 Non-Hispanic Hawaiian Native or Pacific IslanderPOP21_HISPANIC: 2021 HispanicPOP21_MALE: 2021 Male POP21_FEMALE: 2021 Female POV21_WHITE: 2021 Non-Hispanic White below 100% Federal Poverty Level POV21_BLACK: 2021 Non-Hispanic African American below 100% Federal Poverty Level POV21_AIAN: 2021 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV21_ASIAN: 2021 Non-Hispanic Asian below 100% Federal Poverty Level POV21_HNPI: 2021 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV21_HISPANIC: 2021 Hispanic below 100% Federal Poverty Level POV21_TOTAL: 2021 Total population below 100% Federal Poverty Level POP21_TOTAL: 2021 Total PopulationAREA_SQMIL: Area in square milePOP21_DENSITY: Population per square mile.POV21_PERCENT: Poverty 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, 2021. 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 product has been archived in accordance with Federal Grant Compliance and is no longer actively updated. The site remains accessible for historical reference purposes.Disclaimer: This application is a DRAFT and is still under development. A look at the Equity Atlas Poverty indicator in Dallas using the methodology described below. Poverty (S1701)

Each scored category represents 20% of the total population of the City of Dallas.

A score of 5 represents that the percentage of people in poverty is between 23.4% - 80.4%..

A score of 4 represents the percentage of people in poverty is between 16.4% - 23.4%.

A score of 3 represents that the percentage of people in poverty is between 9.9% - 16.3%.

A score of 2 represents that the percentage of people in poverty is between 5.1% - 9.8%.

A score of 1 represents the percentage of people in poverty is between 0.4% - 5%.

Parameter

Data Field

Data Source

American Community Survey 5-Year Estimate 2018-2022

POVERTY STATUS IN THE PAST 12 MONTHS

U.S. Census Bureau, Table: S1701

All people that are living in poverty

Estimated percent of all people that are living in poverty as of 2018-2022

U.S. Census Bureau, Table: S1701

White people who lived in poverty

Estimated percent of all White people who lived in poverty between 2018-2022

U.S. Census Bureau, Table: S1701

Black or African American people who lived in poverty

Estimated percent of all Black or African American people who lived in poverty between 2018-2022

U.S. Census Bureau, Table: S1701

Asian people who lived in poverty

Estimated percentage of all Asian people who lived in poverty between 2018-2022

U.S. Census Bureau, Table: S1701

American Indian and Alaskan Native people who lived in poverty

Estimated percent of all American Indian and Alaskan Native people who lived in poverty between 2018-2022

U.S. Census Bureau, Table: S1701

Native Hawaiian and Other Pacific Islander people who were living in poverty

Estimated percent of all Native Hawaiian and Other Pacific Islander people who were living in poverty between 2018-2022

U.S. Census Bureau, Table: S1701

people of Some Other Race living in poverty

Estimated percent of all people of "Some Other Race" living in poverty between 2018-2022

U.S. Census Bureau, Table: S1701

people of two or more races living below the poverty level

Estimated percent of all people of "two or more races" living below the poverty level between 2018-2022

U.S. Census Bureau, Table: S1701

Hispanic or Latino people who were living in poverty

Estimated percentage of all Hispanic or Latino people who were living in poverty between 2018-2022

U.S. Census Bureau, Table: S1701

This report uses 2003 to 2011 National Survey on Drug Use and Health (NSDUH) to assess past year need for and receipt of alcohol use treatment and illicit drug use treatment among Asian Americans and Pacific Islanders aged 12 or older in comparison to persons of other racial and ethnic groups. Results are shown by age group, gender, federal poverty level and health insurance coverage status.

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 2010 census tracts split by 2018 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 2010 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:CT10: 2010 Census tractFIP18: 2018 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2018) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT10FIP18CSA: 2010 census tract with 2018 city FIPs for incorporated cities, unincorporated areas and LA neighborhoods. SPA12: 2012 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD12: 2012 Health District (HD) number: HD_NAME: Health District name.POP18_AGE_0_4: 2018 population 0 to 4 years oldPOP18_AGE_5_9: 2018 population 5 to 9 years old POP18_AGE_10_14: 2018 population 10 to 14 years old POP18_AGE_15_17: 2018 population 15 to 17 years old POP18_AGE_18_19: 2018 population 18 to 19 years old POP18_AGE_20_44: 2018 population 20 to 24 years old POP18_AGE_25_29: 2018 population 25 to 29 years old POP18_AGE_30_34: 2018 population 30 to 34 years old POP18_AGE_35_44: 2018 population 35 to 44 years old POP18_AGE_45_54: 2018 population 45 to 54 years old POP18_AGE_55_64: 2018 population 55 to 64 years old POP18_AGE_65_74: 2018 population 65 to 74 years old POP18_AGE_75_84: 2018 population 75 to 84 years old POP18_AGE_85_100: 2018 population 85 years and older POP18_WHITE: 2018 Non-Hispanic White POP18_BLACK: 2018 Non-Hispanic African AmericanPOP18_AIAN: 2018 Non-Hispanic American Indian or Alaska NativePOP18_ASIAN: 2018 Non-Hispanic Asian POP18_HNPI: 2018 Non-Hispanic Hawaiian Native or Pacific IslanderPOP18_HISPANIC: 2018 HispanicPOP18_MALE: 2018 Male POP18_FEMALE: 2018 Female POV18_WHITE: 2018 Non-Hispanic White below 100% Federal Poverty Level POV18_BLACK: 2018 Non-Hispanic African American below 100% Federal Poverty Level POV18_AIAN: 2018 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV18_ASIAN: 2018 Non-Hispanic Asian below 100% Federal Poverty Level POV18_HNPI: 2018 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV18_HISPANIC: 2018 Hispanic below 100% Federal Poverty Level POV18_TOTAL: 2018 Total population below 100% Federal Poverty Level POP18_TOTAL: 2018 Total PopulationAREA_SQMIL: Area in square milePOP18_DENSITY: Population per square mile.POV18_PERCENT: Poverty 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 2010 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, 2019. 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.

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 2010 census tracts split by 2017 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 2010 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:CT10: 2010 Census tractFIP17: 2017 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2017) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT10FIP17CSA: 2010 census tract with 2017 city FIPs for incorporated cities, unincorporated areas and LA neighborhoods. SPA12: 2012 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD12: 2012 Health District (HD) number: HD_NAME: Health District name.POP17_AGE_0_4: 2017 population 0 to 4 years oldPOP17_AGE_5_9: 2017 population 5 to 9 years old POP17_AGE_10_14: 2017 population 10 to 14 years old POP17_AGE_15_17: 2017 population 15 to 17 years old POP17_AGE_18_19: 2017 population 18 to 19 years old POP17_AGE_20_44: 2017 population 20 to 24 years old POP17_AGE_25_29: 2017 population 25 to 29 years old POP17_AGE_30_34: 2017 population 30 to 34 years old POP17_AGE_35_44: 2017 population 35 to 44 years old POP17_AGE_45_54: 2017 population 45 to 54 years old POP17_AGE_55_64: 2017 population 55 to 64 years old POP17_AGE_65_74: 2017 population 65 to 74 years old POP17_AGE_75_84: 2017 population 75 to 84 years old POP17_AGE_85_100: 2017 population 85 years and older POP17_WHITE: 2017 Non-Hispanic White POP17_BLACK: 2017 Non-Hispanic African AmericanPOP17_AIAN: 2017 Non-Hispanic American Indian or Alaska NativePOP17_ASIAN: 2017 Non-Hispanic Asian POP17_HNPI: 2017 Non-Hispanic Hawaiian Native or Pacific IslanderPOP17_HISPANIC: 2017 HispanicPOP17_MALE: 2017 Male POP17_FEMALE: 2017 Female POV17_WHITE: 2017 Non-Hispanic White below 100% Federal Poverty Level POV17_BLACK: 2017 Non-Hispanic African American below 100% Federal Poverty Level POV17_AIAN: 2017 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV17_ASIAN: 2017 Non-Hispanic Asian below 100% Federal Poverty Level POV17_HNPI: 2017 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV17_HISPANIC: 2017 Hispanic below 100% Federal Poverty Level POV17_TOTAL: 2017 Total population below 100% Federal Poverty Level POP17_TOTAL: 2017 Total PopulationAREA_SQMIL: Area in square milePOP17_DENSITY: Population per square mile.POV17_PERCENT: Poverty 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 2010 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, 2017. 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.

Tabular data of population by age groups, race and gender, and the poverty by ethnic groups is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2010 census tracts split by 2011 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 2010 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:CT10: 2010 Census tractFIP11: 2011 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2011) CT10FIP11: 2010 census tract with 2011 city FIPs for incorporated cities and unincorporated areas. SPA12: 2012 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD12: 2012 Health District (HD) number: HD_NAME: Health District name.POP11_AGE_0_4: 2011 population 0 to 4 years oldPOP11_AGE_5_9: 2011 population 5 to 9 years old POP11_AGE_10_14: 2011 population 10 to 14 years old POP11_AGE_15_17: 2011 population 15 to 17 years old POP11_AGE_18_19: 2011 population 18 to 19 years old POP11_AGE_20_44: 2011 population 20 to 24 years old POP11_AGE_25_29: 2011 population 25 to 29 years old POP11_AGE_30_34: 2011 population 30 to 34 years old POP11_AGE_35_44: 2011 population 35 to 44 years old POP11_AGE_45_54: 2011 population 45 to 54 years old POP11_AGE_55_64: 2011 population 55 to 64 years old POP11_AGE_65_74: 2011 population 65 to 74 years old POP11_AGE_75_84: 2011 population 75 to 84 years old POP11_AGE_85_100: 2011 population 85 years and older POP11_WHITE: 2011 Non-Hispanic White POP11_BLACK: 2011 Non-Hispanic African AmericanPOP11_AIAN: 2011 Non-Hispanic American Indian or Alaska NativePOP11_ASIAN: 2011 Non-Hispanic Asian POP11_HNPI: 2011 Non-Hispanic Hawaiian Native or Pacific IslanderPOP11_HISPANIC: 2011 HispanicPOP11_MALE: 2011 Male POP11_FEMALE: 2011 Female POV11_WHITE: 2011 Non-Hispanic White below 100% Federal Poverty Level POV11_BLACK: 2011 Non-Hispanic African American below 100% Federal Poverty Level POV11_AIAN: 2011 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV11_ASIAN: 2011 Non-Hispanic Asian below 100% Federal Poverty Level POV11_HNPI: 2011 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV11_HISPANIC: 2011 Hispanic below 100% Federal Poverty Level POV11_TOTAL: 2011 Total population below 100% Federal Poverty Level POP11_TOTAL: 2011 Total PopulationAREA_SQMIL: Area in square milePOP11_DENSITY: Population per square mile.POV11_PERCENT: Poverty 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 2010 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, 2011. 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.