Social Determinants of Health among Adults with Diagnosed HIV Infection, 2019: Technical Notes
A. Geocoding of HIV Surveillance Data Overview
CDC funds state and local health departments to conduct HIV surveillance, and jurisdictions geocode to the census tract level the address of residence at the time of diagnosis. This report includes data for adults aged 18 years and older whose HIV infection was diagnosed during 2019 and reported to the NHSS through June 2021 from the 50 states, the District of Columbia, and Puerto Rico.
After a census tract was assigned to each person’s residence at the time of HIV diagnosis (2019), data were linked with the ACS estimates for 2015–2019 to assign a value for each of the SDH indicator variables to each case. Cases or census tracts were excluded if the address was nonresidential (e.g., military base, corrections facility), a census tract could not be associated with the case, SDH information was not available for the census tract, or the assigned census tract could not be matched to a census tract provided by the ACS. Although HIV diagnosis data associated with these exclusions were not included in all SDH subpopulation totals, they were included in the overall subtotals stratified by sex at birth. Therefore, all tables display differing denominators for SDH subpopulation categories.
All data presented in this report are considered provisional and subject to change as additional reports are submitted for HIV cases and as HIV surveillance data quality improves with further evaluation of the surveillance system and data repository.
B. Social Determinants of Health Indicator Variables
SDH indicator variables  and definitions  were obtained from the U.S. Census Bureau’s ACS. This report uses data from the 2015–2019 ACS estimates. The 5-year estimates were used because census tract data are not available for 1-year estimates. The U.S. Census Bureau collected these data during the 5 years and created period estimates based on the information collected. Period estimates are estimates based on information collected over time (60 months for this report) . Period estimates were not calculated as an average of 60 monthly values; the U.S. Census Bureau collected survey information continuously and then aggregated the results over a specific period (5 years) . The data collection was spread evenly across the entire period so as not to over-represent any particular year within the period. All areas were sampled regardless of population size.
B1. SDH Variables and Definitions
For this report, the SDH indicator variables were categorized by using empirically derived quartiles, and each quartile cutpoint was rounded to the nearest integer. The quartile cutpoints were determined by using data from all census tracts in the 50 states, the District of Columbia, and Puerto Rico and not just from the data applicable to persons in this report (i.e., persons with an HIV diagnosis). This report presents 5 SDH indicator variables: federal poverty status, education level, median household income, health insurance coverage, and Gini index.
- Federal poverty status: proportion of residents in the census tract who were living below the U.S. poverty level (i.e., below a specified threshold) during the 12 months before the survey response (individuals aged 18 years and older)
- Education level: proportion of residents in the census tract with less than a high school diploma (individuals aged 18 years and older)
- Median household income: median income for a household within the census tract during the 12 months before the survey response
- Health insurance coverage: proportion of residents in the census tract without health insurance or health coverage plan (individuals aged 18 years and older)
- Gini index: proportion of household income distribution within the census tract during the 12 months before the survey response
B1.1 Poverty and Wealth
The percentage of the population aged 18 years and older who were living below the poverty level was determined by using the U.S. Census Bureau’s set of dollar-value thresholds (i.e., income cutoffs) that vary by family size and composition to determine who lives below the poverty level. A person’s poverty status is determined by comparing the person’s total family income during the 12 months before the survey response with the poverty threshold appropriate for that person’s family size and composition. If the total income of that person’s family is less than the threshold appropriate for that family, then the person, together with every member of his or her family, is considered “below the poverty level.” In the Census Bureau’s determination of poverty status, the following populations were excluded: (1) institutionalized persons, (2) persons residing in military group quarters, (3) persons in college dormitories, and (4) unrelated persons aged less than 15 years. The U.S. Census Bureau defines poverty areas as census tracts with poverty levels of 20% or more , whereas wealth is defined as a household net worth and is an important defining factor of economic well-being in the United States. In times of economic hardship, such as unemployment, illness, or divorce, a person’s or household’s financial assets (e.g., savings accounts) are an additional source of income to help pay expenses and bills.
The percentage of persons with less than a high school diploma was defined as the percentage of persons aged 18 years and older who were not enrolled in school and were not high school graduates. These people may be referred to as “high school dropouts.” No restriction is placed on when they “dropped out” of school; therefore, they may have dropped out before high school and never attended high school.
B1.3 Household Income
The median household income was determined by dividing the income distribution into 2 equal parts: one-half of the households in the census tract fall below the median income and one-half above the median. The median income was based on the income distribution of the total number of households, including those with no income.
B1.4 Health Insurance Coverage
The percentage of persons aged 18 years and older without health insurance coverage was determined based on the number of persons without plans or programs that provide comprehensive health coverage (both private health insurance and public coverage). Insured persons include: (1) insurance through a current or former employer (of this person or another family member) or union, (2) insurance purchased directly from an insurance company (by this person or another family member), (3) Medicare, for persons aged 65 years and older, or persons with certain disabilities, (4) Medicaid, Medical Assistance, or any kind of government-assistance plan for those with low income or a disability, (5) TRICARE or other military health care, and (6) U.S. Department of Veterans Affairs (VA), including those who have ever used or enrolled for VA health care. Persons who had no reported health coverage, or those whose only health coverage was Indian Health Service, were considered uninsured. Also, plans that provide insurance for specific conditions or situations, such as cancer and long-term care policies, are not considered coverage. Likewise, other types of insurance, like dental, vision, life, and disability insurance, are not considered health insurance coverage. The population estimates for health insurance coverage excludes active-duty military personnel and the population living in correctional facilities and nursing homes.
B1.5 Gini Index
The Gini index of income inequality measures the dispersion of the household income distribution. The Gini index, or index of income concentration, is a statistical measure of income inequality ranging from 0 (or 0%) to 1 (or 100%). A measure of 1 indicates perfect inequality; i.e., one household having all the income and rest having none. A measure of 0 indicates perfect equality; i.e., all households having an equal share of income. The Gini index is based on the difference between the Lorenz curve (the observed cumulative income distribution) and the straight line denoting a perfectly equal income distribution. This measure is presented for household income.
C. Tabulation and Presentation of Data
The data in this report include information received by CDC through June 2021, and include 2 data populations:
- Tables 1–8, S1–B include data for the 50 states, the District of Columbia, and Puerto Rico.
- ACS SDH data (Tables S1–S5) were obtained directly from the U.S. Census Bureau’s 2015–2019 ACS estimates .
- Diagnoses of HIV infection, by race/ethnicity, selected characteristics, and selected SDH are displayed in Tables A–B.
- Tables 9–12 (linkage to HIV medical care within 1 month of HIV diagnosis and viral suppression within 6 months of HIV diagnosis) include data for jurisdictions with complete laboratory reporting.
- As of December 2020, 45 jurisdictions (44 states and the District of Columbia) met the criteria for the collection and reporting of CD4 and viral load test results: The 44 states are Alabama, Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, Florida, Georgia, Hawaii, Illinois, Indiana, Iowa, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Washington, West Virginia, Wisconsin, and Wyoming.
- More information on calculating linkage to care can be found at Monitoring selected national HIV prevention and care objectives by using HIV surveillance data—United States and 6 dependent areas, 2019.
Please use caution when interpreting numbers less than 12, and rates and percentages based on these numbers.
C1. Definitions and Data Specifications
The term diagnosis of HIV infection is defined as a diagnosis of HIV infection regardless of the stage of disease (stage 0, 1, 2, 3 [AIDS], or unknown).
More information on counting diagnoses of HIV infection can be found in the Technical Notes of the 2019 HIV Surveillance Report.
C1.2 Linkage to HIV Medical Care and Viral Suppression
The data on linkage to HIV medical care were based on persons whose infection was diagnosed during 2019 and who resided at the time of diagnosis in any of 45 jurisdictions that reported complete CD4 and viral load laboratory results to CDC. Linkage to HIV medical care within 1 month after HIV diagnosis was measured by documentation of ≥ 1 CD4 (count or percentage) or viral load tests performed ≤ 1 month after HIV diagnosis, including tests performed on the same date as the date of diagnosis.
Viral suppression within 6 months of diagnosis was measured for persons whose infection was diagnosed during 2019 and who resided in any of the 45 jurisdictions at time of diagnosis. Viral suppression was defined as a viral load result of < 200 copies/mL at any viral load test within 6 months of an HIV diagnosis made during 2019.
More information on calculating linkage to HIV medical care and viral suppression can be found at Monitoring selected national HIV prevention and care objectives by using HIV surveillance data—United States and 6 dependent areas, 2019.
C1.3 Measures of Disparities
This report includes absolute and relative measures of disparities. The literature recommends use of at least one absolute and one relative disparity measure to monitor the magnitude and direction of disparities . The absolute rate difference and the relative disparities were chosen because these measures are used by federal initiatives—HHS core indicators, Healthy People 2030, NHSP, and EHE—to measure progress in the SDH and HIV diagnosis indicators.
Absolute disparity measures the simple difference between two rates. This report examines the disparity rate difference between SDH variable categories (highest quartile versus lowest quartile) within and between selected characteristics by sex at birth (i.e., Ratehighest quartile − Ratelowest quartile). The absolute difference measures the magnitude of the difference, which provides some indication of how many lives could be improved if the difference between the two rates were eliminated or reduced (i.e., preventable cases) .
Relative disparity measures the relative magnitude of the disparity. This report examines the relative difference as the rate ratio between SDH variable categories (highest quartile versus lowest quartile) within and between selected characteristics by sex at birth (i.e., Ratehighest quartile ÷ Ratelowest quartile).
Rates per 100,000 population were calculated for the numbers of diagnoses of HIV infection. The population denominators used to compute these rates for the 50 states, the District of Columbia, and Puerto Rico were based on the 5-year estimated total population for those areas . The denominators used for calculating age-, sex-, and race/ethnicity-specific rates were computed by applying the 5-year estimates for age, sex at birth, and race/ethnicity for these areas . Reported numbers less than 12, and rates and percentages based on these numbers, should be interpreted with caution.
Subpopulation stratifications of race data by [age group and] sex at birth from the 2015–2019 ACS estimates may include Hispanic/Latino persons for racial groups other than White persons. As a result, there may be overlap in populations for these racial groups and Hispanic/Latino persons and, therefore, diagnosis rates by race/ethnicity (Table 2) should be interpreted with caution. Of the denominator population from the ACS data in this report, for American Indian/Alaska Native persons, 21.5% were Hispanic/Latino (21.3% when Puerto Rico is excluded); for Asian persons, 1.2% were Hispanic/Latino (1.2 % when Puerto Rico is excluded); for Black/African American persons, 3.9% were Hispanic/Latino (3.0% when Puerto Rico is excluded); and for Native Hawaiian/other Pacific Islander persons, 9.9% were Hispanic/Latino (9.9% when Puerto Rico is excluded). Finally, the denominator population from the ACS is based on the entire population aged 18 years and older; the numerator population is limited to persons whose HIV infection had been diagnosed and reported, with complete residential address, to the NHSS. Because the ACS uses predetermined age categories and varying criteria for SDH variables, the denominators differ for some SDH variables.
D. Demographic Information
All tables in this report reflect data for persons aged 18 years and older (i.e., adults). This report was limited to adults aged 18 years and older with diagnosed HIV infection to align with the population from which data are collected for ACS SDH indicator variables. For tables that provide data by age group, the specific age-group assignment (e.g., 18–24 years) was based on the person’s age at the time of HIV diagnosis.
D2. Sex at Birth
Sex designations in this report are based on a person’s sex at birth.
D3. Race and Ethnicity
In the Federal Register for October 30, 1997, the Office of Management and Budget (OMB) announced the Revisions to the Standards for the Classification of Federal Data on Race and Ethnicity. Implementation by January 1, 2003, was mandated .
Hispanic and Latino persons can be of any race. Due to confidentiality concerns, the ACS [age- and] sex-specific population counts for racial groups other than White persons may include Hispanic/Latino persons. Therefore, race-specific diagnosis rates (except White persons) should be interpreted with caution. Also, the number of persons reported in each race category may include persons whose ethnicity was not reported.
More information on race and ethnicity can be found in the Technical Notes of the 2019 HIV Surveillance Report.
D4. Transmission Categories
Transmission category is the term for the classification of cases that summarizes an adult’s or adolescent’s possible HIV risk factors; the summary classification results from selecting, from the presumed hierarchical order of probability, the 1 (single) risk factor most likely to have been responsible for transmission.
More information on transmission categories can be found in the Technical Notes of the 2019 HIV Surveillance Report.
E. Geographic Designation
E1. Census Tract
Data presented in this report reflect the census tract of the person’s residential address at the time they received an HIV diagnosis. A census tract is a standard area used by the U.S. Census Bureau for the purpose of counting the population. Census tracts are small, relatively permanent statistical subdivisions of a county delineated by local participants as part of the U.S. Census Bureau’s Participant Statistical Areas Program. Census tracts must stay within a county and, therefore, a state. They do not necessarily coincide within any other geography. For example, although some census tracts follow place boundaries, there is no rule that says they must stay within a place. Census tracts are designed to be relatively homogeneous units with respect to population characteristics, economic status, and living conditions at the time of establishment. Each census tract generally contains 1,500 to 8,000 inhabitants (average, 4,000 inhabitants) .
CDC. Addressing social determinants of health: Accelerating the prevention and control of HIV/AIDS, viral hepatitis, STD and TB. External consultation, December 9–10, 2008. Published April 2009. Accessed February 8, 2022.
CDC. Social determinants of health among adults with diagnosed HIV infection, 2018. HIV Surveillance Supplemental Report 2020;25(No. 3). Published November 2020. Accessed February 8, 2022.
Gant Z, Johnson Lyons S, Jin C, Dailey A, Nwangwu-Ike N, Satcher Johnson A. Geographic differences in social determinants of health among US-born and non-US–born Hispanic/Latino adults with diagnosed HIV infection, United States and Puerto Rico, 2017external icon. Public Health Rep 2021;136(6):685–696. doi:10.1177/0033354920970539
Gillot M, Gant Z, Hu X, Satcher Johnson A. Linkage to HIV medical care and social determinants of health among adults with diagnosed HIV infection in 41 states and the District of Columbia, 2017external icon. Pub Health Rep 2021;333549211029971. doi:10.1177/00333549211029971
Inequality.org. Income Inequality in the United Statesexternal icon. Updated December 2021. Accessed February 8, 2022
Jin C, Nwangwu-Ike N, Gant Z, Johnson Lyons S, Satcher Johnson A. Geographic differences and social determinants of health among people with HIV attributed to injection drug use, United States, 2017external icon. Pub Health Rep 2021;333549211007168. doi:10.1177/00333549211007168
Johnson Lyons S, Gant Z, Jin C, Dailey A, Nwangwu-Ike N, Satcher Johnson A. A census tract-level examination of differences in social determinants of health among people with HIV, by race/ethnicity and geography, United States and Puerto Rico, 2017external icon. Pub Health Rep 2021;33354921990373. doi:10.1177/0033354921990373
Nwangwu-Ike N, Jin C, Gant Z, Johnson S, Balaji AB. An examination of geographic differences in social determinants of health among women with diagnosed HIV in the United States and Puerto Rico, 2017external icon. Open AIDS J 2021;10:10–20. doi:10.2174/1874613602115010010
Watson L, Gant Z, Hu X, Johnson AS. Exploring social determinants of health as predictors of mortality during 2012–2016 among Black women with diagnosed HIV infection attributed to heterosexual contact, United Statesexternal icon. J Racial Ethn Health Disparities 2019;6(5):892–899. doi:10.1007/s40615-019-00589-6
World Health Organization Commission on Social Determinants of Health. Closing the gap in a generation: Health equity through action on the social determinants of health. Final Report of the Commission on Social Determinants of Healthpdf iconexternal icon. Published 2008. Accessed February 8, 2022
- Valdiserri RO, Forsyth AD, Yakovchenko V, Koh HK. Measuring what matters: Development of standard HIV core indicators across the U.S. Department of Health and Human Servicesexternal icon. Public Health Rep 2013;128(5):354–359. doi:10.1177/003335491312800504
- U.S. Department of Health and Human Services. Common indicators for HHS-funded HIV programs and servicesexternal icon. Updated February 2017. Accessed February 8, 2022.
- Healthy People 2030. http://health.gov/healthypeople/objectives-and-data/browse-objectivesexternal icon. Updated January 15, 2021. Accessed February 8, 2022.
- U.S. Department of Health and Human Services. HIV National Strategic Plan for the United States: A roadmap to end the epidemic 2021–2025pdf iconexternal icon. Published December 2021. Accessed February 8, 2022.
- U.S. Department of Health and Human Services. What is ‘Ending the HIV Epidemic in the U.S.’?external icon Updated March 31, 2021. Accessed February 8, 2022.
- CDC. Establishing a holistic framework to reduce inequities in HIV, viral hepatitis, STDs, and tuberculosis in the United States: An NCHHSTP white paper on social determinants of health, 2010external icon. Published October 2010. Accessed February 8, 2022.
- Ladd, HF. Education and poverty: Confronting the evidenceexternal icon. J Pol Anal Manage 2012;31(2):203–227. doi:10.1002/pam.21615
- Egerter S, Braveman P, Sadegh-Nobari T, Grossman-Kahn R, Dekker M. Issue Brief 6: Education and Healthpdf iconexternal icon. Published September 2009. Accessed February 8, 2022.
- American Psychological Association. HIV/AIDS and Socioeconomic Statuspdf iconexternal icon. Published 2010. Accessed February 8, 2022.
- Gillespie S, Kadiyala S, Greener R. Is poverty or wealth driving HIV transmission? external iconAIDS 2007;21(Suppl 7):S5–S16. doi:10.1097/01.aids.0000300531.74730.72
- Merriam-Webster. Poverty. https://www.merriam-webster.com/dictionary/povertyexternal icon. Accessed February 8, 2022.
- Merriam-Webster. Wealth. https://www.merriam-webster.com/dictionary/wealthexternal icon. Accessed February 8, 2022.
- Global Partnership for Education. https://www.globalpartnership.org/blog/how-education-plays-key-role-fight-against-aidsexternal icon. Published December 01, 2018. Accessed February 8, 2022.
- Marmot M. Status syndrome. external iconSignificance 2004;1(4):150–154. doi:10.1111/j.1740-9713.2004.00058.x
- Naidu V, Harris G. The impact of HIV/AIDS morbidity and mortality on households—a review of household studiesexternal icon. South African J Econ 2005;73(S1):533–544. doi:10.1111/j.1813-6982.2005.00037.x
- Harrison KM, Ling Q, Song R, Hall HI. County-level socioeconomic status and survival after HIV diagnosis, United Statesexternal icon. Ann Epidem 2008;18(12):919–927. doi:10.1016/j.annepidem.2008.09.003
- Yehia BR, Fleishman JA, Agwu AL, et al. Health insurance coverage for persons in HIV care, 2006–2012external icon. J Acquir Immune Defic Syndr 2014;67(1):102–106. doi:10.1097/QAI.0000000000000251
- CDC. Diagnose and treat to save lives: Decreasing deaths among people with HIV. Published November 2020. Accessed February 8, 2022.
- Pickett KE, Wilkinson RG. Income inequality and health: A causal review. external iconSoc Sci Med 2015;128:316–326. doi:10.1016/j.socscimed.2014.12.031
- Kochhar R, Cilluffo A. Key findings on the rise in income inequality within America’s racial and ethnic groupsexternal icon. Published July 12, 2018. Accessed February 8, 2022.
- U.S. Department of Health and Human Services, Office of Disease Prevention and Health Promotion. Development of the National Health Promotion and Disease Prevention Objectives for 2030external icon. Updated August 2020. Accessed February 8, 2022.
- Penman-Aguilar A, Talih M, Huang D, Moonesinghe R, Bouye K, Beckles G. Measurement of health disparities, health inequities, and social determinants of health to support the advancement of health equityexternal icon. J Public Health Manag Pract 2016;22(Suppl 1):S33–S42. doi:10.1097/PHH.0000000000000373
- Williams DR, Jackson PB. Social sources of racial disparities in healthexternal icon. Health Aff 2005;24(2):325–334. doi:10.1377/hlthaff.24.2.325
- Fennie KP, Lutfi K, Maddox LM, Lieb S, Trepka MJ. Influence of residential segregation on survival after AIDS diagnosis among non-Hispanic blacksexternal icon. Ann Epidemiol 2015;25(2):113–119. doi:10.1016/j.annepidem.2014.11.023
- Keisler-Starkey K, Bunch LN. Health insurance coverage in the United States: 2019pdf iconexternal icon. Current Population Reports 2020;P60-271. Accessed February 8, 2022.
- Dawson P. Hispanics and health care in the United States: Access, information and knowledgepdf iconexternal icon. J Youth Dev 2012;7(3):114–116. doi:https://doi.org/10.5195/jyd.2012.134
- CDC. Monitoring selected national HIV prevention and care objectives by using HIV surveillance data—United States and 6 dependent areas, 2019. HIV Surveillance Supplemental Report 2021;26(No.2). Published May 2021. Accessed February 8, 2022.
- Williams D, Collins C. Racial residential segregation: A fundamental cause of racial disparities in healthexternal icon. Pub Health Rep 2001;116(5):404–416. doi:10.1093/phr/116.5.404
- U.S. Census Bureau. American Community Survey: 2015–2019 5-year estimatesexternal icon. Published December 2020. Accessed February 8, 2022.
- U.S. Census Bureau. American Community Survey and Puerto Rico Community Survey: 2019 subject definitionspdf iconexternal icon. Accessed February 8, 2022.
- U.S. Census Bureau. Understanding and using American Community Survey data: What all data users need to knowexternal icon. Accessed February 8, 2022.
- U.S. Census Bureau. Poverty glossaryexternal icon. Updated May 2016. Accessed February 8, 2022.
- Moonesinghe R, Beckles GL. Measuring health disparities: A comparison of absolute and relative disparities. PeerJ 2015;24(3):e1438. doi:10.7717/peerj.1438
- Pearcy JN, Keppel KG. A summary measure of health disparity. external iconPub Health Rep 2002;117(3):273–280. doi:10.1093/phr/117.3.273
- Office of Management and Budget. Revisions to the standards for the classification of federal data on race and ethnicityexternal icon. Federal Register 1997;62:58782–58790. Accessed February 8, 2022.
- U.S. Census Bureau. Glossary—census tractexternal icon. Updated September 2019. Accessed February 8, 2022.