Equity Indicator Report Methods

This section reviews the methods used to select indicators, identify data sources, and analyze data. Considerations for selecting indicators of equity in San Diego County included whether they are actionable, comprehensive, timely, and reflect the priorities of community members.

Indicator Selection

Local, regional, and national equity reports and models were reviewed to identify possible indicators. These reports and models included:
  • United Nations (UN) Sustainable Development Goals[1]
  • Equity articles from the Organization for Economic Co-operation and Development (OECD) (e.g. income inequality[2] measures)
  • Urban Institute’s Mobility Metrics[3]
  • National Equity Atlas[4]
  • King County’s Equity & Social Justice initiatives[5]
  • Oakland’s Equity Scorecard[6]
  • California Healthy Places Index 2.0 and 3.0[7]
  • Live Well San Diego indicators[8]
 To prioritize and tailor these frameworks and indicators for the San Diego community, listening sessions were held with San Diego County residents, community-based organizations, government agencies and other stakeholders from various sectors. Across three virtual forums[9], over one hundred participants provided feedback on indicators that were important to their communities and discussed how to prioritize indicators across several initial themes: health, education, economic opportunity, environment, infrastructure, community, and safety.
 County of San Diego staff members who attended the community listening sessions and researchers on the SDRPIC team reviewed a list of over 120 indicators that were identified through the review of existing equity reports and by members of the community. Indicators were sorted on how frequently they were mentioned. Indicators that were used in other published equity reports were flagged. The following considerations were prioritized by the project team to narrow the list down to 50 indicators:
  • Actionable, reliable, timely, and quality data
  • Comparable to indicators used by other jurisdictions or organizations
  • Preferred or favored by the community
 Indicators that met all three criteria were prioritized, followed by indicators that met at least two criteria. Then, a qualitative thematic analysis was conducted to organize indicators into themes and limit overlap between indicators. This review considered 1) which facet(s) of the theme each indicator addressed, 2) what other themes each indicator may be related to, and 3) any concerns about the indicators or organization of themes.

Data Selection

As mentioned above, indicators were selected partly based on data availability and quality. The following factors were prioritized when identifying and selecting the data source(s) for each indicator:
  • High quality and reliable
  • Updated annually, with exceptions for some indicators where the best available data are updated less frequently
  • Consistent with other equity reports and/or highly regarded source within the field
  • Robust data collection and/or sampling practices
  • Sufficiently large sample size to meaningfully interpret data
  • Clear descriptions about data collection, analysis, and reporting methods
  • Publicly available data
  • Data collected and managed by the County of San Diego were preferred over other sources
 Thirteen of the 34 indicators (38%) use data from the American Community Survey (ACS) conducted annually by the U.S. Census Bureau. Information about this highly regarded survey is below to provide context and aid in interpretation of the indicators. Applicable information about other data sources used in this report are included in the narrative for each indicator.
American Community Survey
The ACS is a nationally representative survey that samples 1% of the U.S. population each year. Respondents are asked to self-report a variety of information, including demographic and family characteristics, income, housing characteristics, employment status, and more. The ACS is commonly used by local, state, and national government organizations as well as researchers to understand population characteristics and inform decisions that impact the community.
 Data tables for frequently accessed information, such as race and ethnicity and economic characteristics, are available from the U.S. Census Bureau.[10] ACS tables are usually available at the county level to summarize a single variable, such as poverty in San Diego County.[11] Anonymized individual responses that have been processed to protect the confidentiality of respondents, called microdata by the U.S. Census Bureau, are available to conduct custom analysis. Possibilities for additional analysis using microdata include disaggregation to smaller subgroups, limiting to specific relevant populations (such as adults or employed residents), and creating measures based on the relationship between multiple variables. IPUMS USA,[12] an integrator for ACS microdata, was used for analysis of ACS data unless otherwise stated. The estimates presented in this report based on ACS microdata from IPUMS USA may differ slightly from pre-tabulated ACS estimates on data.census.gov because microdata are based on about 30% of the full ACS sample and because the Census Bureau takes steps to protect respondent confidentiality.
 ACS data are available as 1-year or 5-year estimates. The 5-year estimates are a combination of the most recent five annual surveys. The 5-year estimates for 2021 (including 2017-2021) were selected for this report to ensure a larger sample size and more reliable estimates for smaller populations. However, the 5-year estimates should not be used to compare year-to-year changes because much of the data between neighboring 5-year estimates are the same. For example, the 2020 5-year estimates (2016-2020) and 2021 5-year estimates (2017-2021) estimates both contain the years 2017-2020. Instead, the U.S. Census Bureau recommends only comparing non-overlapping 5-year estimates and using 1-year estimates for year-to-year comparisons.[13]
 Since the ACS is a sample of the population, the data presented are estimates and may differ from values that would be obtained if the entire population was surveyed. Due to the uncertainty associated with complex sample surveys and necessary lag between data collection and reporting, the estimates may under- or overestimate the current population percentages. Small numbers and percentages at or near 0% or 100% should therefore be interpreted with caution. The U.S. Census Bureau does not define a threshold for when small numbers may be unreliable or associated with a high level of uncertainty. Margins of error are not included in this report, but the margins of error for established tables and guidance for calculating margins of error for custom analysis are available on the U.S. Census Bureau website.

Data Analysis

Generally, this report reflects data for 2021 or the most recently available data prior to 2021. Indicator data were disaggregated by demographic characteristics and geography when possible. The selection of characteristics and unit of geography for analysis was guided by data availability and standard practice within each subject area. Demographic characteristics examined included race and ethnicity, sex, disability status, immigration status, and location of residence. The choice of disaggregated data can be found in the narrative for each indicator.
 The specific data processing steps varied by indicator and by data source. Descriptions of the methods used for each indicator can be found within the respective narratives.
Race and Ethnicity Classification
As stated in Appendix A: Key Concepts & Terms, race and ethnicity are social constructs and do not have biological meaning. Many people have more than one racial or ethnic identity and/or may not distinguish between the terms race and ethnicity. Consequently, how race and ethnicity are understood, quantified, and reported varies considerably by field of study and industry depending on historical practices and other factors.
 The most frequently used method for reporting race and ethnicity data in this report follows the standards established by the Office of Management and Budget (OMB) in 1997[14], which were based on extensive research and public comment. All federal agencies are required to follow these standards. Many state and local governments, academic and research institutions, non-profits, and others, including most departments, offices, and programs within the County of San Diego, also follow these standards. However, it is broadly recognized that these standards may not fully reflect the diversity of the American people nor the current discourse and sentiments about race and ethnicity. There is currently a formal process underway to revise the OMB standards with anticipated completion by summer of 2024.[15],[16]
 For the data sources that follow the 1997 OMB standards, self-reported race and ethnicity are collected by two separate questions. Respondents are asked to select all racial and ethnic categories that apply to them. Persons who report themselves as Hispanic can be of any race. The OMB defines minimum categories for each question:
  • Ethnicity: Hispanic or Latino or Not Hispanic or Latino
  • Race: White, Black or African American, American Indian or Alaska Native, Asian, and Native Hawaiian or Other Pacific Islander
 Many organizations include additional options and allow write-in responses. For example, the U.S. Census Bureau revised the questions for the 2020 decennial census based on research to better reflect the diversity of the American people, as shown in the figure below.[17] These questions were also used for the 2021 ACS.[18]
Snapshot of Census questions 6 about Ethnicity and 7 about Race
Although this detailed information is collected by the U.S. Census Bureau and sometimes other organizations, it is common practice to process these data for reporting purposes. Detailed categories and write-in responses are aggregated from smaller groups to larger groups to protect confidentiality and achieve consistency with other reported data. Race and Hispanic origin are often cross tabulated into a single variable by assigning people to one mutually exclusive (non-overlapping) category. Each person is counted once, and the sum of the categories equals the total population. The U.S. Census Bureau and other organizations, including the County of San Diego, typically use the following categories for analysis and reporting (long label with a short label option in parenthesis; the labels may vary):
  • Hispanic or Latino
  • White alone, non-Hispanic (White)
  • Black or African American alone, non-Hispanic (Black or African American)
  • American Indian and Alaska Native alone, non-Hispanic (AIAN)
  • Asian alone, non-Hispanic (Asian)
  • Native Hawaiian and Other Pacific Islander alone, non-Hispanic (NHPI)
  • Some Other Race alone, non-Hispanic (Some Other Race)
  • Multiracial, non-Hispanic (Multiracial)
Until new standards are established and adopted, this report adheres to the 1997 OMB standards when feasible. Due to the breadth of data examined and included in this equity report, it is not possible to follow these standards for some data sources because of how the data were collected and/or made publicly available. Caution must be taken when comparing race and ethnicity data across indicators using different data sources and classification methods because the populations may not be the same. The methods used for each indicator can be identified by reviewing the corresponding narrative, table and figure labels, and footnotes.

Geographic Regions

Geographic data were analyzed when it was feasible and relevant to outcomes. The type of geographic area used for analysis was selected based on data availability and quality. Smaller geographic areas were preferred over larger areas for closer examination of possible geographic inequities. Most continuous data were grouped into five equal categories based on the data values (quintiles); the exception to this is Low Birthweight (three equal categories).

The following geographic area types are presented in this report, listed from smallest to largest areas:
  • Census Tracts are geographic areas defined by the U.S. Census Bureau.[19] They are reviewed and updated every 10 years to reflect population changes recorded by the decennial census. There were 628 census tracts in San Diego County defined by the 2010 census; census tracts from the 2020 census were not yet utilized by the data sources in this report.
  • ZIP Codes are used by the United States Postal Service to identify a particular postal delivery area in the U.S.[20] The codes are represented by five digits in this report.
  • ZIP Code Tabulation Areas (ZCTAs) are geographic areas created by the U.S. Census Bureau to approximate ZIP codes used by the United States Postal Service.[21] The differences between ZIP codes and ZCTAs are not meaningful at the level of the maps created for this report and are explained in detail by the Census Bureau. Like ZIP codes, some ZCTAs cross county borders and are part of more than one county. In this report, the San Diego County border is shown in the maps and ZCTAs that extend beyond county boundaries are not excluded because the data in those ZCTAs reflect some people living in other counties. The U.S. Census Bureau does not define ZCTAs for some areas if there are few or no households in the area. There are 116 ZCTAs in San Diego County.
  • Subregional Areas (SRAs) are sets of census tracts used by the San Diego Association of Governments (SANDAG), Live Well San Diego, and many programs within the County of San Diego.[22] There are 41 SRAs in San Diego County.
  • Public Use Microdata Areas (PUMAs) are areas with at least 100,000 people and are developed by the U.S. Census Bureau.[23] There are 22 PUMAs in San Diego County. Like census tracts, they are reviewed and updated every 10 years to reflect the decennial census. PUMAs from the 2010 census are used in this report.
  • Health and Human Services Agency Regions are six areas of aggregated ZIP codes in San Diego County that were created by the County of San Diego Health and Human Services Agency to assist with the organization and provision of services locally. [24] They are updated as need to reflect changes in ZIP codes.


  1.   THE 17 GOALS | Sustainable Development. (n.d.). Retrieved November 22, 2022, from https://sdgs.un.org/goals
  2.   Inequality—Income inequality—OECD Data. (n.d.). Retrieved November 22, 2022, from https://data.oecd.org/inequality/income-inequality.htm
  3.   Mobility Metrics Framework | Urban Institute. (n.d.). Retrieved September 20, 2022, from https://upward-mobility.urban.org/mobility-metrics-framework
  4.   National Equity Atlas Indicators (n.d.) Retrieved September 20, 2022, from Indicators | National Equity Atlas
  5.   Equity and Social Justice—King County. (n.d.). Retrieved September 20, 2022, from https://kingcounty.gov/elected/executive/equity-social-justice.aspx
  6.   Oakland Equity Indicators: Measuring Change Toward Greater Equity in Oakland. (n.d.). https://cao-94612.s3.amazonaws.com/documents/2018-Equity-Indicators-Full-Report.pdf
  7.   Public Health Alliance of Southern California. (n.d.). Healthy Places Index. Retrieved September 20, 2022, from https://www.healthyplacesindex.org/
  8.   Top 10 Live Well Indicators. (n.d.). Retrieved September 20, 2022, from https://www.livewellsd.org/i-want-to/learn-more/data-indicators
  9.   Listening sessions were conducted online to increase safety and accessibility while COVID-19 was circulating.
  10.   U.S. Census Bureau. (n.d.). American Community Survey Data Tables. Retrieved May 3, 2023, from https://www.census.gov/programs-surveys/acs/data/data-tables.html
  11.   U.S. Census Bureau. (n.d.). S1701: Poverty Status in the Past 12 Months - Census Bureau Table. Retrieved April 12, 2023, from https://data.census.gov/table?q=poverty+in+San+Diego&tid=ACSST1Y2021.S1701
  12.   Ruggles, Steven, Flood, Sarah, Goeken, Ronald, Schouweiler, Megan, & Sobek, Matthew. (2022). IPUMS USA: Version 12.0 (12.0) [Data set]. Minneapolis, MN: IPUMS. https://doi.org/10.18128/D010.V12.0
  13.   Raglin, D. (2022). Period Estimates in the American Community Survey. United States Census Bureau. https://www.census.gov/newsroom/blogs/random-samplings/2022/03/period-estimates-american-community-survey.html
  14.   Office of Management and Budget (1997). Revisions to the Standards for the Classification of Federal Data on Race and Ethnicity. Federal Registrar 62(210)58782-58790. https://www.govinfo.gov/content/pkg/FR-1997-10-30/pdf/97-28653.pdf
  15.   Orvis, K. Initial Proposals for Revising the Federal Race and Ethnicity Standard. (2023, January 26). The White House. https://www.whitehouse.gov/omb/briefing-room/2023/01/26/initial-proposals-for-revising-the-federal-race-and-ethnicity-standards/
  16.   Initial Proposals For Updating OMB’s Race and Ethnicity Statistical Standards. (2023, January 27). Federal Register. https://www.federalregister.gov/documents/2023/01/27/2023-01635/initial-proposals-for-updating-ombs-race-and-ethnicity-statistical-standards
  17.   Improvements to the 2020 Census Race and Hispanic Origin Question Designs, Data Processing, and Coding Procedures. (n.d.).  United States Census Bureau. Retrieved August 24, 2023, from https://www.census.gov/newsroom/blogs/random-samplings/2021/08/improvements-to-2020-census-race-hispanic-origin-question-designs.html
  18.   Sample ACS & PRCS Forms and Instructions 2021. (n.d.) United States Census Bureau. Retrieved August 24, 2023, from https://www.census.gov/programs-surveys/acs/about/forms-and-instructions.2021.html#list-tab-9466845
  19.   United States Census Bureau. (n.d) History. Tracts and Block Numbering Areas. Retrieved August 24, 2023, from https://www.census.gov/history/www/programs/geography/tracts_and_block_numbering_areas.html
  20.   United States Postal Service. (n.d.) ZIP Code – The Basics. Retrieved August 24, 2023, from https://faq.usps.com/s/article/ZIP-Code-The-Basics
  21.   ZIP Code Tabulation Areas (ZCTAs). (n.d.) U.S. Census Bureau. Retrieved April 12, 2023, from https://www.census.gov/programs-surveys/geography/guidance/geo-areas/zctas.html
  22.   Subregional Areas (SRAs) | Subregional Areas (SRAs) | San Diego Open Data Portal. (n.d.). Retrieved April 12, 2023, from https://sdgis-sandag.opendata.arcgis.com/datasets/subregional-areas-sras/explore?showTable=true
  23.   Public Use Microdata Areas (PUMAS). (n.d.) United States Census Bureau. Retrieved August 24, 2023, from https://www.census.gov/programs-surveys/geography/guidance/geo-areas/pumas.html#overview
  24.   Health and Human Service Regions CN. (2022, November 14). Sandag. Retrieved August 24, 2023, from https://rdw.sandag.org/file_store/District/HEALTH_AND_HUMAN_SERVICE_REGIONS_CN.pdf
Updated February 7, 2024
If you have any questions, contact: OERJ@sdcounty.ca.gov