Link to landing page referenced by identifier. Service Protocol: Link to landing page referenced by identifier. Link Function: information-- dc:identifier.

VITAL SIGNS INDICATOR Population (LU1)

FULL MEASURE NAME Population estimates

LAST UPDATED October 2019

DESCRIPTION Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region.

DATA SOURCES U.S Census Bureau: Decennial Census No link available (1960-1990) http://factfinder.census.gov (2000-2010)

California Department of Finance: Population and Housing Estimates Table E-6: County Population Estimates (1961-1969) Table E-4: Population Estimates for Counties and State (1971-1989) Table E-8: Historical Population and Housing Estimates (2001-2018) Table E-5: Population and Housing Estimates (2011-2019) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/

U.S. Census Bureau: Decennial Census - via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University Population Estimates (1970 - 2010) http://www.s4.brown.edu/us2010/index.htm

U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2011-2017) http://factfinder.census.gov

U.S. Census Bureau: Intercensal Estimates Estimates of the Intercensal Population of Counties (1970-1979) Intercensal Estimates of the Resident Population (1980-1989) Population Estimates (1990-1999) Annual Estimates of the Population (2000-2009) Annual Estimates of the Population (2010-2017) No link available (1970-1989) http://www.census.gov/popest/data/metro/totals/1990s/tables/MA-99-03b.txt http://www.census.gov/popest/data/historical/2000s/vintage_2009/metro.html https://www.census.gov/data/datasets/time-series/demo/popest/2010s-total-metro-and-micro-statistical-areas.html

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) All legal boundaries and names for Census geography (metropolitan statistical area, county, city, and tract) are as of January 1, 2010, released beginning November 30, 2010, by the U.S. Census Bureau. A Priority Development Area (PDA) is a locally-designated area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are current as of August 2019. For more information on PDA designation see http://gis.abag.ca.gov/website/PDAShowcase/.

Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970 -2010) and the American Community Survey (2008-2012 5-year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator.

Population estimates for Bay Area PDAs are from the decennial Census (1970 - 2010) and the American Community Survey (2006-2010 5 year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Population estimates for PDAs are derived from Census population counts at the tract level for 1970-1990 and at the block group level for 2000-2017. Population from either tracts or block groups are allocated to a PDA using an area ratio. For example, if a quarter of a Census block group lies with in a PDA, a quarter of its population will be allocated to that PDA. Tract-to-PDA and block group-to-PDA area ratios are calculated using gross acres. Estimates of population density for PDAs use gross acres as the denominator.

Annual population estimates for metropolitan areas outside the Bay Area are from the Census and are benchmarked to each decennial Census. The annual estimates in the 1990s were not updated to match the 2000 benchmark.

The following is a list of cities and towns by geographical area: Big Three: San Jose, San Francisco, Oakland Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside Inland, Delta and Coastal: American Canyon, Antioch, Benicia, Brentwood, Calistoga, Clayton, Cloverdale, Concord, Cotati, Danville, Dixon, Dublin, Fairfield, Gilroy, Half Moon Bay, Healdsburg, Lafayette, Livermore, Martinez, Moraga, Morgan Hill, Napa, Novato, Oakley, Orinda, Petaluma, Pittsburg, Pleasant Hill, Pleasanton, Rio Vista, Rohnert Park, San Ramon, Santa Rosa, Sebastopol, Sonoma, St. Helena, Suisun City, Vacaville, Walnut Creek, Windsor, Yountville Unincorporated: all unincorporated towns

Chart and table of population level and growth rate for the state of California from 1900 to 2024.

VITAL SIGNS INDICATOR Population (LU1)

FULL MEASURE NAME
Population estimates

LAST UPDATED
February 2023

DESCRIPTION
Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region.

DATA SOURCE
California Department of Finance: Population and Housing Estimates - http://www.dof.ca.gov/Forecasting/Demographics/Estimates/
Table E-6: County Population Estimates (1960-1970)
Table E-4: Population Estimates for Counties and State (1970-2021)
Table E-8: Historical Population and Housing Estimates (1990-2010)
Table E-5: Population and Housing Estimates (2010-2021)

Bay Area Jurisdiction Centroids (2020) - https://data.bayareametro.gov/Boundaries/Bay-Area-Jurisdiction-Centroids-2020-/56ar-t6bs
Computed using 2020 US Census TIGER boundaries

U.S. Census Bureau: Decennial Census Population Estimates - http://www.s4.brown.edu/us2010/index.htm- via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University
1970-2020

U.S. Census Bureau: American Community Survey (5-year rolling average; tract) - https://data.census.gov/
2011-2021
Form B01003

Priority Development Areas (Plan Bay Area 2050) - https://opendata.mtc.ca.gov/datasets/MTC::priority-development-areas-plan-bay-area-2050/about

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
All historical data reported for Census geographies (metropolitan areas, county, city and tract) use current legal boundaries and names. A Priority Development Area (PDA) is a locally-designated area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are current as of December 2022.

Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator.

Population estimates for Bay Area tracts and PDAs are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Population estimates for PDAs are allocated from tract-level Census population counts using an area ratio. For example, if a quarter of a Census tract lies with in a PDA, a quarter of its population will be allocated to that PDA. Estimates of population density for PDAs use gross acres as the denominator. Note that the population densities between PDAs reported in previous iterations of Vital Signs are mostly not comparable due to minor differences and an updated set of PDAs (previous iterations reported Plan Bay Area 2040 PDAs, whereas current iterations report Plan Bay Area 2050 PDAs).

The following is a list of cities and towns by geographical area:

Big Three: San Jose, San Francisco, Oakland

Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside

Inland, Delta and Coastal: American Canyon, Antioch, Benicia, Brentwood, Calistoga, Clayton, Cloverdale, Concord, Cotati, Danville, Dixon, Dublin, Fairfield, Gilroy, Half Moon Bay, Healdsburg, Lafayette, Livermore, Martinez, Moraga, Morgan Hill, Napa, Novato, Oakley, Orinda, Petaluma, Pittsburg, Pleasant Hill, Pleasanton, Rio Vista, Rohnert Park, San Ramon, Santa Rosa, Sebastopol, Sonoma, St. Helena, Suisun City, Vacaville, Walnut Creek, Windsor, Yountville

Unincorporated: all unincorporated towns

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census and beyond, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

This data comes from the 2010 Census Profile of General Population and Housing Characteristics. Zip codes are limited to those that fall at least partially within LA city boundaries. The dataset will be updated after the next census in 2020. To view all possible columns and access the data directly, visit http://factfinder.census.gov/faces/affhelp/jsf/pages/metadata.xhtml?lang=en&type=table&id=table.en.DEC_10_SF1_SF1DP1#main_content.

Human population density in 2000, by terrestrial ecoregion.

We summarized human population density by ecoregion using the Gridded Population of the World database and projections for 2015 (CIESIN et al. 2005). The mean for each ecoregion was extracted using a zonal statistics algorithm.

These data were derived by The Nature Conservancy, and were displayed in a map published in The Atlas of Global Conservation (Hoekstra et al., University of California Press, 2010). More information at http://nature.org/atlas.

Data derived from:

Center for International Earth Science Information Network (CIESIN), Columbia University; and Centro Internacional de Agricultura Tropical (CIAT). 2005. Gridded Population of the World Version 3 (GPWv3). Socioeconomic Data and Applications Center (SEDAC), Columbia University Palisades, New York. Available at http://sedac.ciesin.columbia.edu/gpw. Digital media.

United Nations Population Division (UNPD). 2007. Global population, largest urban agglomerations and cities of largest change. World Urbanization Prospects: The 2007 Revision Population Database. Available at http://esa.un.org/unup/index.asp.

For more about The Atlas of Global Conservation check out the web map (which includes links to download spatial data and view metadata) at http://maps.tnc.org/globalmaps.html. You can also read more detail about the Atlas at http://www.nature.org/science-in-action/leading-with-science/conservation-atlas.xml, or buy the book at http://www.ucpress.edu/book.php?isbn=9780520262560

The SCAG_ATDB_Demographics shapefile contains Census tract level population, race, employment, English speaking, income, and elderly data of the SCAG region. Race data includes the percentage of population that is white, black, Asian, Latino, Pacific Islander, Native American, multiple races, or other. Population data includes 2010 population 2015 population, and population density. Employment data includes 2015 employment, unemployment, and employment density. English speaking data includes the percentage of the population that speaks English well. This shapefile also includes median household income and percentage of the population that is 65 years or older. This data was sourced mostly from Census data as well as the Healthy Places Index (HPI). Original data sources are listed in the relevant fields.

The 2020 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some states and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census and beyond, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

This shapefile contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of California. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the state boundary of California. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) representative of conditions in the past 10 years, and (4) of sufficient spatial resolution that they could be used to make valid comparisons among local catchment units. In this data set, these variables are linked to the catchments of the National Hydrography Dataset Plus Version 1 (NHDPlusV1) using the COMID identifier. They can also be linked to the reaches of the NHDPlusV1 using the COMID identifier. Catchment attributes are available for both local catchments (defined as the land area draining directly to a reach; attributes begin with "L_" prefix) and network catchments (defined by all upstream contributing catchments to the reach's outlet, including the reach's own local catchment; attributes begin with "N_" prefix). This shapefile also includes habitat condition scores created based on responsiveness of biological metrics to anthropogenic landscape disturbances throughout ecoregions. Separate scores were created by considering disturbances within local catchments, network catchments, and a cumulative score that accounted for the most limiting disturbance operating on a given biological metric in either local or network catchments. This assessment only scored reaches representing streams and rivers (see the process section for more details). Please use the following citation: Esselman, P., D.M. Infante, L. Wang, W. Taylor, W. Daniel, R. Tingley, J. Fenner, A. Cooper, D. Wieferich, D. Thornbrugh and J. Ross. (April 2011) National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for California. National Fish Habitat Partnership Data System. http://dx.doi.org/doi:10.5066/F7JD4TSG

This map shows four of these densely populated areas are in California. The San Francisco-Oakland and San Jose Urban Areas rank second and third, respectively. That the New York Metropolitan area ranks fifth on this list shows that this density ranking is greatly affected by the nature of the land area designated as urban. Census Urban Areas comprise an urban core and associated suburbs. California's urban and suburban areas are more uniform in density when compared to New York's urban core and suburban periphery which have vastly different densities. Delano ranks fourth because it has a very small land area and its population is augmented by two large California State Prisons housing 10,000 inmates.

About this dataset

Context

The dataset tabulates the California household income by gender. The dataset can be utilized to understand the gender-based income distribution of California income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• California annual median income by work experience and sex dataset : Aged 15+, 2010-2022 (in 2022 inflation-adjusted dollars)
• California annual income distribution by work experience and gender dataset (Number of individuals ages 15+ with income, 2022)

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of California income distribution by gender. You can refer the same here

Analysis of ‘MSSA Detail 2010c1 public’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/493330c8-eda1-4c32-b839-09b08e144875 on 12 February 2022.

--- Dataset description provided by original source is as follows ---

Medical Service Study Areas - Census Detail, 2010

Medical Service Study Areas (MSSAs) are sub-city and sub-county geographical units used to organize and display population, demographic and physician data. MSSAs were developed in 1976 by the California Healthcare Workforce Policy Commission (formerly California Health Manpower Policy Commission) to respond to legislative mandates requiring it to determine "areas of unmet priority need for primary care family physicians" (Song-Brown Act of 1973) and "geographical rural areas where unmet priority need for medical services exist" (Garamendi Rural Health Services Act of 1976).

MSSAs are recognized by the U.S. Health Resources and Services Administration, Bureau of Health Professions' Office of Shortage Designation as rational service areas for purposes of designating Health Professional Shortage Areas (HPSAs), and Medically Underserved Areas and Medically Underserved Populations (MUAs/MUPs).

The MSSAs incorporate the U.S. Census total population, socioeconomic and demographic data and are updated with each decadal census. Office of Statewide Health Planning and Development provides updated data for each County's MSSAs to the County and Communities, and will schedule meetings for areas of significant population change. Community meetings will be scheduled throughout the State as needed.

Adopted by the California Healthcare Workforce Policy Commission on May 15, 2002.

Each MSSA is composed of one or more complete census tracts. MSSAs will not cross county lines. All population centers within the MSSA are within 30 minutes travel time to the largest population center.

Urban MSSA - Population range 75,000 to 125,000. Reflect recognized community and neighborhood boundaries. Similar demographic and socio-economic characteristics.

Rural MSSA - Population density of less than 250 persons per square mile. No population center exceeds 50,000.

Frontier MSSA - Population density of less than 11 persons per square mile.

--- Original source retains full ownership of the source dataset ---

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

For the past several censuses, the Census Bureau has invited people to self-respond before following up in-person using census takers. The 2010 Census invited people to self-respond predominately by returning paper questionnaires in the mail. The 2020 Census allows people to self-respond in three ways: online, by phone, or by mail.The 2020 Census self-response rates are self-response rates for current census geographies. These rates are the daily and cumulative self-response rates for all housing units that received invitations to self-respond to the 2020 Census. The 2020 Census self-response rates are available for states, counties, census tracts, congressional districts, towns and townships, consolidated cities, incorporated places, tribal areas, and tribal census tracts.The Self-Response Rate of Los Angeles County is 65.1% for 2020 Census, which is slightly lower than 69.6% of California State rate.More information about these data is available in the Self-Response Rates Map Data and Technical Documentation document associated with the 2020 Self-Response Rates Map or review FAQs.Animated Self-Response Rate 2010 vs 2020 is available at ESRI site SRR Animated Maps and can explore Census 2020 SRR data at ESRI Demographic site Census 2020 SSR Data.Following Demographic Characteristics are included in this data and web maps to visualize their relationships with Census Self-Response Rate (SRR).1. Population Density: 2020 Population per square mile,2. Poverty Rate: Percentage of population under 100% FPL,3. Median Household income: Based on countywide median HH income of $71,538.4. Highschool Education Attainment: Percentage of 18 years and older population without high school graduation.5. English Speaking Ability: Percentage of 18 years and older population with less or none English speaking ability. 6. Household without Internet Access: Percentage of HH without internet access.7. Non-Hispanic White Population: Percentage of Non-Hispanic White population.8. Non-Hispanic African-American Population: Percentage of Non-Hispanic African-American population.9. Non-Hispanic Asian Population: Percentage of Non-Hispanic Asian population.10. Hispanic Population: Percentage of Hispanic population.

Analysis of ‘MSSA Detail 2010c1 public’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/b0ad8a2d-468b-47bf-8c4e-270779b1d841 on 12 February 2022.

--- Dataset description provided by original source is as follows ---

Medical Service Study Areas - Census Detail, 2010

Medical Service Study Areas (MSSAs) are sub-city and sub-county geographical units used to organize and display population, demographic and physician data. MSSAs were developed in 1976 by the California Healthcare Workforce Policy Commission (formerly California Health Manpower Policy Commission) to respond to legislative mandates requiring it to determine "areas of unmet priority need for primary care family physicians" (Song-Brown Act of 1973) and "geographical rural areas where unmet priority need for medical services exist" (Garamendi Rural Health Services Act of 1976).

MSSAs are recognized by the U.S. Health Resources and Services Administration, Bureau of Health Professions' Office of Shortage Designation as rational service areas for purposes of designating Health Professional Shortage Areas (HPSAs), and Medically Underserved Areas and Medically Underserved Populations (MUAs/MUPs).

The MSSAs incorporate the U.S. Census total population, socioeconomic and demographic data and are updated with each decadal census. Office of Statewide Health Planning and Development provides updated data for each County's MSSAs to the County and Communities, and will schedule meetings for areas of significant population change. Community meetings will be scheduled throughout the State as needed.

Adopted by the California Healthcare Workforce Policy Commission on May 15, 2002.

Each MSSA is composed of one or more complete census tracts. MSSAs will not cross county lines. All population centers within the MSSA are within 30 minutes travel time to the largest population center.

Urban MSSA - Population range 75,000 to 125,000. Reflect recognized community and neighborhood boundaries. Similar demographic and socio-economic characteristics.

Rural MSSA - Population density of less than 250 persons per square mile. No population center exceeds 50,000.

Frontier MSSA - Population density of less than 11 persons per square mile.

--- Original source retains full ownership of the source dataset ---

This shapefile contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the California Fish Passage Forum. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the boundary of the California Fish Passage Forum. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) representative of conditions in the past 10 years, and (4) of sufficient spatial resolution that they could be used to make valid comparisons among local catchment units. In this data set, these variables are linked to the catchments of the National Hydrography Dataset Plus Version 1 (NHDPlusV1) using the COMID identifier. They can also be linked to the reaches of the NHDPlusV1 using the COMID identifier. Catchment attributes are available for both local catchments (defined as the land area draining directly to a reach; attributes begin with "L_" prefix) and network catchments (defined by all upstream contributing catchments to the reach's outlet, including the reach's own local catchment; attributes begin with "N_" prefix). This shapefile also includes habitat condition scores created based on responsiveness of biological metrics to anthropogenic landscape disturbances throughout ecoregions. Separate scores were created by considering disturbances within local catchments, network catchments, and a cumulative score that accounted for the most limiting disturbance operating on a given biological metric in either local or network catchments. This assessment only scored reaches representing streams and rivers (see the process section for more details). Please use the following citation: Esselman, P., D.M. Infante, L. Wang, W. Taylor, W. Daniel, R. Tingley, J. Fenner, A. Cooper, D. Wieferich, D. Thornbrugh and J. Ross. (April 2011) National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for California Fish Passage Forum. National Fish Habitat Partnership Data System. http://dx.doi.org/doi:10.5066/F7JD4TSG

Estimated number of persons by quarter of a year and by year, Canada, provinces and territories.

Medical Service Study Areas - Census Detail, 2010California Health & Human Services Agency Open Data Portal DescriptionMedical Service Study Areas (MSSAs) are sub-city and sub-county geographical units used to organize and display population, demographic and physician data. MSSAs were developed in 1976 by the California Healthcare Workforce Policy Commission (formerly California Health Manpower Policy Commission) to respond to legislative mandates requiring it to determine "areas of unmet priority need for primary care family physicians" (Song-Brown Act of 1973) and "geographical rural areas where unmet priority need for medical services exist" (Garamendi Rural Health Services Act of 1976).MSSAs are recognized by the U.S. Health Resources and Services Administration, Bureau of Health Professions' Office of Shortage Designation as rational service areas for purposes of designating Health Professional Shortage Areas (HPSAs), and Medically Underserved Areas and Medically Underserved Populations (MUAs/MUPs).The MSSAs incorporate the U.S. Census total population, socioeconomic and demographic data and are updated with each decadal census. Office of Statewide Health Planning and Development provides updated data for each County's MSSAs to the County and Communities, and will schedule meetings for areas of significant population change. Community meetings will be scheduled throughout the State as needed.Adopted by the California Healthcare Workforce Policy Commission on May 15, 2002.Each MSSA is composed of one or more complete census tracts. MSSAs will not cross county lines. All population centers within the MSSA are within 30 minutes travel time to the largest population center.Urban MSSA - Population range 75,000 to 125,000. Reflect recognized community and neighborhood boundaries. Similar demographic and socio-economic characteristics.Rural MSSA - Population density of less than 250 persons per square mile. No population center exceeds 50,000.Frontier MSSA - Population density of less than 11 persons per square mile.