# An Examination of Geographic Differences in Social Determinants of Health Among Women with Diagnosed HIV in the United States and Puerto Rico, 2017

Ndidi Nwangwu-Ike1, *, Chan Jin2, Zanetta Gant1, Shacara Johnson1, Alexandra B. Balaji1
1 National Center for HIV/AIDS, Viral Hepatitis, STD and TB Prevention, Division of HIV/AIDS Prevention, Atlanta, GA, USA
2 ICF, Atlanta, GA, USA

© 2021 Nwangwu-Ike et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the National Center for HIV/AIDS, Viral Hepatitis, STD and TB Prevention, Division of HIV/AIDS Prevention, Atlanta, GA, USA; Tel: 404-639-1811; Fax: 404-639-2980; E-mail: hhp9@cdc.gov

## Abstract

### Objective:

To examine differences, at the census tract level, in the distribution of human immunodeficiency virus (HIV) diagnoses and social determinants of health (SDH) among women with diagnosed HIV in 2017 in the United States and Puerto Rico.

### Background:

In the United States, HIV continues to disproportionately affect women, especially minority women and women in the South.

### Methods:

Data reported in the National HIV Surveillance System (NHSS) of the Centers for Disease Control and Prevention were used to determine census tract-level HIV diagnosis rates and percentages among adult women (aged ≥18 years) in 2017. Data from the American Community Survey were combined with NHSS data to examine regional differences in federal poverty status, education level, income level, employment status, and health insurance coverage among adult women with diagnosed HIV infection in the United States and Puerto Rico.

In the United States and Puerto Rico, among 6,054 women who received an HIV diagnosis in 2017, the highest rates of HIV diagnoses generally were among those who lived in census tracts where the median household income was less than $40,000; at least 19% lived below the federal poverty level, at least 18% had less than a high school diploma, and at least 16% were without health insurance. ### Conclusion: This study is the first of its kind and gives insight into how subpopulations of women are affected differently by the likelihood of an HIV diagnosis. The findings show that rates of HIV diagnosis were highest among women who lived in census tracts having the lowest income and least health coverage. Keywords: HIV, Census tract, Healthcare, Poverty, Social determinants of health, Women. ## 1. INTRODUCTION Although the rates of new Human Immunodeficiency Virus (HIV) infections in the United States have declined greatly, women are still affected heavily, especially Black/ African American (here inafter referred to as Black) women and women living in the South [1]. HIV among Black women has decreased [1], but the rate among Black women is on average 5 times the rate among White women [2, 3]. In the United States, HIV diagnosis rates vary across the states and regions. Although only 37% of the United States population lives in the South, that region accounted for 53% (19,968 of 37,377) of HIV diagnoses in 2017 [1, 4]. More specifically, women who lived in the southern region had the highest rates of diagnosis of HIV infection in 2017 (4,010/6,986), with the highest rates being among Blacks (26.2), followed by Hispanics/Latinos (5.8), and Whites (2.4) [1]. Several factors, commonly referred to as social determinants of health (SDH), contribute to these disparities. The World Health Organization (WHO) defines SDH as the conditions in which people are born, grow, live, work, and age [ 5 ]. Economic and social stressors, such as lack of transportation, lack of childcare, and transient housing are additional factors that can cause disparities among women, particularly minority women [ 2-7]. A report from the Centers for Disease Control and Prevention (CDC) identified several factors common among women who had the highest HIV diagnosis rates [2]. In general, those women had less than a high school diploma, had incomes below the federal poverty level, had the lowest median household income, were unemployed, did not have health insurance or a health coverage plan, and lived in areas with the highest percentage of vacant housing units [2]. Much research has been conducted to better understand and highlight how HIV affects women [8-11]. Disparities in HIV infection, access to care, and subsequent viral suppression differ among women of color. Therefore, a federal initiative, Ending the HIV Epidemic: A Plan for America (EHE), and CDC’s HIV/AIDS Strategic Plan [12, 13], are addressing the need to reduce health disparities among certain populations, such as women. Additionally, the CDC HIV/AIDS prevention goals target specific populations, including Black women (reducing the rate of diagnoses by at least 15%) and people in the South (reducing the rate of new diagnoses by 15%) [13]. To achieve the goals set forth by these federal initiatives, an improved understanding of the social determinants that affect the health of women, particularly minority women, is important. Therefore, this analysis examined the differences, at the census tract level, in the distribution of HIV diagnosis and SDH among women with diagnosed HIV infection in 2017, by region, as specified in the U.S. Census Bureau’s division of the 50 states [14]. ## 2. METHODS Data from CDC’s National HIV Surveillance System (NHSS) and the U.S. Census Bureau’s American Community Survey (ACS) were used for this analysis. ### 2.1. NHSS Numbers, rates, and percentages of diagnoses of HIV infection for 2017 were based on cases reported to NHSS from 2017 to December 2018. Those include cases among women aged 18 years and older whose HIV infection was diagnosed during 2017, regardless of the stage of disease at diagnosis. HIV surveillance data were geocoded to the census tract level for addresses of residence at the time of diagnosis and linked at the census tract level to the SDH indicator variable data from the ACS. The NHSS is a population-based database of all persons in the United States and Puerto Rico with diagnosed HIV infection, based on standard, robust statistical methodology. Annual evaluation of NHSS data show that as of December 2017, the completeness of reporting of HIV infection was estimated to be at least 85% [1]. Because NHSS is a comprehensive national surveillance system that contains data on nearly all people with diagnosed HIV in the United States, no statistical tests of significance were applied to the data. ### 2.2. ACS Census tract level SDH data on federal poverty status, education level, median household income, employment status, and health insurance coverage were obtained from the ACS 2013–2017, with 5-year estimates [15]. Those five SDH indicator variables are generally recognized as key determinants that affect women in the United States [16-18]. The selected SDH variables were categorized by using empirically derived quartiles, determined based on data from all census tracts in the United States and Puerto Rico. ### 2.3. Analysis This ecological analysis used NHSS data from the 50 states, the District of Columbia, and Puerto Rico to examine distributions of HIV diagnoses by age group, race/ethnicity, transmission category, residence at time of diagnosis, and SDH indicators among women with a diagnosis of HIV infection in 2017. Because a substantial proportion of cases of HIV infection are reported to CDC without an identified risk factor, multiple imputation was used to assign a transmission category [19]. Percentages and rates of HIV diagnoses per 100,000 population were calculated by region for adult women (aged ≥18 years). Distributions were assessed by age group, race/ethnicity, transmission category, residence at the time of diagnosis (urban, suburban, rural, or unknown), and SDH indicator variables in each census tract. The denominators used for calculating age and race/ethnicity-specific rates were computed by applying the 5-year (2013–2017) estimates for age, sex, and race/ethnicity for these areas [20]. The denominator population from the ACS was based on all women aged 18 years and older. ACS uses predetermined age categories and varying criteria for SDH variables, so the denominators differ for some SDH variables. The numerator population was limited to women aged 18 years and older whose HIV infection had been diagnosed and reported with complete residential address information that could be geocoded to the census tract level. Cases or census tracts were excluded if 1) the address was nonresidential (e.g., military base, corrections facility, etc.), 2) no census tract was associated with the case, 3) no SDH information was available for the census tract, or 4) the census tract from the surveillance data could not be matched to a census tract provided by ACS. Regions were based on the U.S. Census Bureau’s division of the 50 states [15] and one U.S. territory: Puerto Rico. Area of residence was defined as urban (metropolitan area ≥500,000 population), suburban (metropolitan area of 50,000–499,999 population), or rural (nonmetropolitan population) [14]. SAS version 9.4 (SAS Institute, Inc., Cary, NC) was used to conduct all analyses. ## 3. RESULTS This analysis used data on 6,054 adult women with HIV infection diagnosed in 2017 that included sufficient residential address information for geocoding to census tracts for 5,972 women in the United States and 82 women in Puerto Rico. The overall rate (per 100,000 population) of diagnoses of HIV infection among women in the United States and Puerto Rico was 2.4. Because of the small cell sizes, results stratified by demographic and SDH characteristics for women in Puerto Rico are not discussed. In terms of the U.S. region, the overall rate of diagnosis was highest in the South (2.4), followed by the Northeast (1.5), the Midwest (1.0) and the West (0.9) (Table 1). By age, the highest rates were among women aged 35–44 years for the Northeast (3.5), and West (1.9) and among women aged 25–34 years in the Midwest (2.8) and the South (5.7). By race/ethnicity, Black women had the highest HIV diagnosis rates in every region: Northeast (22.5), Midwest (17.7), South (24.4), and West (18.2). By transmission category, in every region, the largest percentages of HIV diagnoses were among women with HIV infection attributed to heterosexual contact: Northeast (83.3%), Midwest (83.3%), South (90.1%), and West (80.9%). By residence area, in every region, the largest percentages were in urban areas: Northeast (92.3%), Midwest (79.5%), South (76.2%), and West (88.3%) (Table 1). Table 1. Diagnoses of HIV infection among adult women, by U.S. Census regiona and selected characteristics, 2017─United States, the District of Columbia and Puerto Rico.  - Northeast Midwest South West Subtotal Puerto Rico Total - No. % Rate No. % Rate No. % Rate No. % Rate No. % Rate No. % Rate No. % Rate Age group at diagnosis (yrs.) - - - - - - - - - - - - - - - - - - - - - 18–24 101 9.5 1.9 123 15.9 1.9 469 13.9 4.1 100 13.3 1.4 793 13.3 2.6 * * * 797 13.2 5.2 25–34 253 23.8 3.3 245 31.6 2.8 943 27.9 5.7 200 26.5 1.8 1,641 27.5 3.7 17 20.7 3.5 1,658 27.4 7.5 35–44 245 23.0 3.5 178 23.0 2.2 775 23.0 4.9 186 24.6 1.9 1,384 23.2 3.4 17 20.7 3.4 1,401 23.1 6.8 45–54 250 23.5 3.0 124 16.0 1.4 647 19.2 3.9 148 19.6 1.5 1,169 19.6 2.7 25 30.5 4.8 1,194 19.7 5.4 55–64 166 15.6 2.1 86 11.1 0.9 407 12.1 2.6 102 13.5 1.1 761 12.7 1.8 14 17.1 2.8 775 12.8 3.6 65+ 50 4.7 0.5 19 2.5 0.2 136 4.0 0.7 19 2.5 0.2 224 3.8 0.4 * * * 229 3.8 0.9 Race - - - - - - - - - - - - - - - - - - - - - American Indian/Alaska Native * * * * * * * * * 12 1.6 2.6 27 0.5 2.8 * * * 27 0.5 — Asian 14 1.3 0.9 16 2.1 1.9 30 0.9 1.8 44 5.8 1.3 104 1.7 1.4 * * * 104 1.7 — Black/African American 617 57.9 22.5 483 62.3 17.7 2,273 67.3 24.4 241 31.9 18.2 3,614 60.5 22.4 * * * 3,614 59.7 — Hispanic/Latinob 246 23.1 8.7 54 7.0 3.4 415 12.3 5.9 229 30.3 3.0 944 15.8 5.0 81 98.8 5.6 1,025 16.9 — Native Hawaiian/Other Pacific Islander * * * * * * * * * * * * * * * * * * * * * White 148 13.9 0.9 195 25.2 0.9 584 17.3 2.0 200 26.5 1.3 1,127 18.9 1.4 * * * 1,128 18.6 — Multiple races 38 3.6 8.7 23 3.0 5.3 61 1.8 7.0 25 3.3 2.4 147 2.5 5.3 * * * 147 2.4 — Transmission categoryc - - - - - - - - - - - - - - - - - - - - - Injection drug use 173 16.3 — 122 15.7 — 326 9.6 — 139 18.4 — 760 12.7 — * * — 769 12.7 — Hetrosexual contactd 887 83.3 — 645 83.3 — 3,042 90.1 — 611 80.9 — 5,184 86.8 — 75 91.6 — 5,263 86.9 — Othere * * — * * — * * — * * — 28 0.5 — * * — 33 0.6 — Residence area at diagnosis f - - - - - - - - - - - - - - - - - - - - - Urban 983 92.3 — 616 79.5 — 2,574 76.2 — 667 88.3 — 4,840 81.0 — 56 68.3 — 4,896 80.9 — Suburban 68 6.4 — 108 13.9 — 524 15.5 — 67 8.9 — 767 12.8 — 25 30.5 — 792 13.1 — Rural 14 1.3 — 51 6.6 — 239 7.1 — 21 2.8 — 325 5.4 — * * — 326 5.4 — Unknown * * — * * — 40 1.2 — * * — 40 0.7 — * * — 40 0.7 — Social Determinants of Health - - - - - - - - - - - - - - - - - - - - - Below federal poverty level (%) - - - - - - - - - - - - - - - - - - - - - <7 169 15.9 0.6 87 11.2 0.3 385 11.4 1.1 111 14.7 0.4 752 12.6 0.7 * * * 752 12.4 1.0 7.00–10.99 131 12.3 0.9 93 12.0 0.5 492 14.6 1.7 140 18.5 0.7 856 14.3 1.0 * * * 856 14.1 1.5 11.00–18.99 245 23.0 1.8 215 27.7 1.1 987 29.2 2.3 213 28.2 0.9 1,660 27.8 1.6 * * * 1,662 27.5 2.4 ≥19 520 48.8 4.2 380 49.0 2.6 1,513 44.8 4.4 291 38.5 1.6 2,704 45.3 3.4 80 97.6 1.9 2,784 46.0 5.0 Less than high school diploma (%) - - - - - - - - - - - - - - - - - - - - - <6 85 8.0 0.4 107 13.8 0.4 325 9.6 1.1 98 13.0 0.4 615 10.3 0.6 * * * 617 10.2 0.9 6.00–10.99 169 15.9 0.8 178 23.0 0.6 615 18.2 1.8 146 19.3 0.7 1,108 18.6 1.1 * * * 1,110 18.3 1.6 11.00–17.99 275 25.8 2.0 224 28.9 1.3 913 27.0 2.3 145 19.2 0.8 1,557 26.1 1.8 14 17.1 1.4 1,571 26.0 2.7 ≥18 536 50.3 4.3 266 34.3 2.6 1,524 45.1 3.8 366 48.5 1.6 2,692 45.1 3.1 64 78.1 2.0 2,756 45.5 4.7 Median household income (U.S.$) - - - - - - - - - - - - - - - - - - - - - <40,000 440 41.3 4.3 388 50.1 2.6 1,549 45.9 4.2 222 29.4 1.7 2,599 43.5 3.5 81 98.8 1.9 2,680 44.3 5.1 40,000–53,999 234 22.0 1.8 197 25.4 0.9 861 25.5 2.2 187 24.8 1.0 1,479 24.8 1.6 * * * 1,480 24.5 2.4 54,000–74,999 218 20.5 1.1 132 17.0 0.5 629 18.6 1.8 191 25.3 0.8 1,170 19.6 1.1 * * * 1,170 19.3 1.7 ≥75,000 173 16.2 0.6 58 7.5 0.3 337 10.0 1.1 155 20.5 0.5 723 12.1 0.7 * * * 723 11.9 1.0 Unemployed (%) - - - - - - - - - - - - - - - - - - - - - <2 45 4.2 0.5 80 10.3 0.5 252 7.5 1.1 50 6.6 0.5 427 7.2 0.7 * * * 430 7.1 1.0 2.00–3.99 238 22.4 0.8 173 22.3 0.5 862 25.5 1.5 214 28.3 0.6 1,487 24.9 1.0 * * * 1,493 24.7 1.5 4.00–5.99 258 24.2 1.4 169 21.8 1.1 1,022 30.3 2.7 260 34.4 1.0 1,709 28.6 1.8 14 17.1 1.5 1,723 28.5 2.7 ≥6 524 49.2 4.2 353 45.6 2.8 1,241 36.8 4.9 231 30.6 1.2 2,349 39.3 3.4 59 72.0 2.0 2,408 39.8 5.1 Without health insurance (%) - - - - - - - - - - - - - - - - - - - - - <6 223 20.9 0.7 101 13.0 0.3 195 5.8 1.0 83 11.0 0.4 602 10.1 0.6 20 24.4 1.0 622 10.3 0.9 6.00–9.99 214 20.1 1.2 176 22.7 0.8 361 10.7 1.4 155 20.5 0.7 906 15.2 1.0 34 41.5 1.8 940 15.5 1.6 10.00–15.99 309 29.0 2.8 229 29.6 1.4 710 21.0 1.8 165 21.9 0.7 1,413 23.7 1.6 21 25.6 3.0 1,434 23.7 2.4 ≥16 319 30.0 4.1 269 34.7 2.7 2,111 62.5 3.7 352 46.6 1.6 3,051 51.1 3.2 * * * 3,058 50.5 4.8 Totalg 1,065 100 1.5 775 100 1.0 3,377 100 2.4 755 100 0.9 5,972 100 1.6 82 100 1.8 6,054 100 2.4
Abbreviation: Asterisk (*) indicates cell too small (<12 diagnoses during the year) and data has been suppressed. Dash (—) indicates absence of denominator data and rate is not calculated.
Note: Rates are per 100,000 population. Rates are not calculated by transmission category because of the lack of denominator data. The American Community Survey does not provide age- and sex-specific social determinants of health variables stratified by race and ethnicity for racial groups except Whites (i.e., White, not-Hispanic/Latino). Therefore, the denominators used for computing race-specific rates may include Hispanics/Latinos and should be interpreted with caution.
a Northeast: Connecticut, Maine, New Hampshire, New Jersey, New York, Pennsylvania, and Rhode Island; Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin; South: Alabama, Arkansas, Delaware, Florida, Georgia, Kentucky, Louisiana, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia; West: Alaska, Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming.
b Hispanics/Latinos can be of any race.
c Data have been statistically adjusted to account for the missing transmission category.
d Heterosexual contact with a person known to have, or to be at high risk for, HIV infection.
e Includes hemophilia, blood transfusion, perinatal exposure, and risk factor not reported or not identified.
f Urban: population of ≥500,000. Suburban: population of 50,000– 499,999. Rural: nonmetropolitan area (<50,000)
g Totals do not represent all adults whose HIV infection was diagnosed during 2017 in these areas.

By race/ethnicity and age, among white women, those aged 25–34 years had the highest rates of HIV diagnoses (in every region) (Table 2). Among Black women, those aged 25–34 years in the Midwest and South and those aged 35–44 years in the Northeast and West had the highest rates. Among Hispanic/Latino women, those aged 45–54 years had the highest rates in all regions except for the South, where those aged 25–34 years had the highest rate (Table 2). By race/ethnicity and transmission category, the largest percentages of HIV diagnoses were among women with HIV infection attributed to heterosexual contact, regardless of region or race/ethnicity. By race/ethnicity and residence area, the largest percentages were among women who lived in urban areas.

Table 2. Percentages and rates of diagnoses of HIV infection among women, by U.S. Census regiona, race/ethnicity and selected characteristics, 2017─United States, the District of Columbia and Puerto Rico.
 - White - Northeast Midwest South West Puerto Rico - % Rate % Rate % Rate % Rate % Rate Age group at diagnosis (yrs.) - - - - - - - - - - 18–24 10.1 0.9 15.4 1.3 12.7 2.6 8.5 1.1 0.0 0.0 25–34 26.4 1.7 30.3 1.9 28.8 3.9 32.0 2.6 0.0 0.0 35–44 16.9 1.2 22.1 1.4 24.3 3.4 23.0 2.0 0.0 0.0 45–54 29.1 1.5 15.9 0.9 19.5 2.3 20.5 1.6 100.0 43.1 55–64 14.9 0.8 15.4 0.8 12.0 1.3 13.5 0.9 0.0 0.0 65+ 2.7 0.1 1.0 0.0 2.7 0.2 2.5 0.1 0.0 0.0 Transmission categoryc - - - - - - - - - - Injection drug use 40.1 - 33.1 - 26.4 - 32.5 - 0.0 - Heterosexual contactd 59.6 - 66.5 - 73.5 - 66.7 - 100 - Other e 0.3 - 0.5 - 0.2 - 0.8 - 0.0 - Residence area at diagnosis f - - - - - - - - - - Urban 79.1 - 70.8 - 65.2 - 82.5 - 100 - Suburban 15.5 - 18.5 - 22.6 - 12.0 - 0.0 - Rural 5.4 - 10.8 - 11.3 - 5.5 - 0.0 - Unknown 0.0 - 0.0 - 0.9 - 0.0 - 0.0 - Social Determinants of Health - - - - - - - - - - Below the federal poverty level (%) - - - - - - - - - - <7 32.4 0.6 15.4 0.4 17.8 1.3 20.5 0.8 0.0 0.0 7.00–10.99 14.2 0.6 16.9 0.6 20.4 1.8 25.5 1.2 0.0 0.0 11.00–18.99 26.4 1.4 30.8 1.2 31.5 2.1 22.5 1.1 0.0 0.0 ≥19 27.0 2.8 36.9 2.8 30.3 3.5 31.5 3.0 100 10.7 Less than high school diploma (%) - - - - - - - - - - <6 19.6 0.5 19.0 0.5 12.7 1.0 22.0 0.7 0.0 0.0 6.00–10.99 32.4 0.8 26.7 0.7 25.3 2.0 26.0 1.1 0.0 0.0 11.00–17.99 22.3 1.1 26.7 1.2 31.3 2.3 18.0 1.2 100 48.7 ≥18 25.7 3.4 27.7 3.3 30.7 3.0 34.0 3.6 0.0 0.0 Median household income (U.S. $) - - - - - - - - - - <40,000 18.9 2.3 38.5 2.7 31.2 3.2 24.5 3.0 100 10.9 40,000–53,999 25.0 1.4 28.2 0.9 30.5 2.1 19.5 1.2 0.0 0.0 54,000–74,999 26.4 0.8 24.6 0.7 24.8 1.9 30.0 1.3 0.0 0.0 ≥75,000 29.7 0.6 8.7 0.3 13.5 1.1 26.0 0.8 0.0 0.0 Unemployed (%) - - - - - - - - - - <2 8.1 0.5 18.0 0.7 12.2 1.2 9.5 0.7 0.0 0.0 2.00–3.99 39.9 0.8 28.2 0.6 38.0 1.8 33.0 1.0 0.0 0.0 4.00–5.99 29.7 1.1 23.1 1.1 28.9 2.4 31.5 1.5 0.0 0.0 ≥6 22.3 2.1 30.8 3.0 20.9 3.7 26.0 2.3 100 17.9 Without health insurance (%) - - - - - - - - - - <6 46.0 0.8 19.5 0.4 10.5 1.2 19.0 0.8 0.0 0.0 6.00–9.99 23.7 0.9 28.7 0.9 16.8 1.5 29.0 1.3 100 25.0 10.00–15.99 19.6 1.5 26.7 1.3 27.9 1.8 19.0 0.9 0.0 0.0 ≥16 10.8 2.3 25.1 3.0 44.9 3.1 33.0 2.9 0.0 0.0 Totalg 100 0.9 100 0.9 100 2.0 100 1.3 100 9.3 - Black - Northeast Midwest South West Pureto Rico - % Rate % Rate % Rate % Rate % Rate Age group at diagnosis (yrs.) - - - - - - - - - - 18–24 9.9 16.0 16.4 19.3 14.0 24.0 12.9 16.4 0.0 0.0 25–34 22.5 27.1 33.8 31.4 28.0 35.6 20.8 19.0 0.0 0.0 35–44 24.3 32.6 22.8 23.6 22.6 31.4 25.3 27.4 0.0 0.0 45–54 21.6 26.8 13.5 14.0 18.7 25.8 19.5 19.9 0.0 0.0 55–64 16.1 23.4 11.0 12.4 12.4 19.1 17.8 20.8 0.0 0.0 65+ 5.7 7.5 2.7 3.0 4.3 6.9 3.7 4.3 0.0 0.0 Transmission categoryc - - - - - - - - - - Injection drug use 11.4 - 9.5 - 5.5 - 10.7 - 0.0 - Heterosexual contactd 88.2 - 89.1 - 94.1 - 87.9 - 0.0 - Other e 0.4 - 1.4 - 0.4 - 1.4 - 0.0 - Residence area at diagnosis f - - - - - - - - - - Urban 95.0 - 85.1 - 77.3 - 95.0 - 0.0 - Suburban 5.0 - 11.4 - 14.9 - 3.7 - 0.0 - Rural 0.0 - 3.5 - 6.4 - 1.2 - 0.0 - Unknown 0.0 - 0.0 - 1.4 - 0.0 - 0.0 - Social Determinants of Health - - - - - - - - - - Below federal poverty level (%) - - - - - - - - - - <7 13.6 17.7 8.7 13.4 9.6 15.7 10.8 10.9 0.0 0.0 7.00–10.99 11.7 17.8 9.1 13.5 12.6 20.4 19.1 17.6 0.0 0.0 11.00–18.99 23.0 21.1 24.6 18.8 28.0 23.3 29.5 18.1 0.0 0.0 ≥19 51.7 26.8 57.6 19.1 49.9 30.0 40.7 22.7 0.0 0.0 Less than high school diploma (%) - - - - - - - - - - <6 6.0 13.4 10.6 12.6 8.6 16.9 8.3 9.7 0.0 0.0 6.00–10.99 14.3 16.2 20.5 16.3 16.5 18.9 21.6 19.0 0.0 0.0 11.00–17.99 29.7 21.9 31.3 18.0 26.7 22.3 25.7 20.6 0.0 0.0 ≥18 50.1 28.3 37.7 20.8 48.2 31.8 44.4 19.6 0.0 0.0 Median household income (U.S.$) - - - - - - - - - - <40,000 45.9 27.3 58.2 19.0 51.6 29.5 30.7 24.2 0.0 0.0 40,000–53,999 21.4 21.9 22.4 17.8 22.8 22.3 27.0 20.1 0.0 0.0 54,000–74,999 18.5 19.3 13.9 16.1 16.9 21.3 22.8 14.8 0.0 0.0 ≥75,000 14.3 17.4 5.6 12.4 8.6 16.7 19.5 14.6 0.0 0.0 Unemployed (%) - - - - - - - - - - <2 2.8 13.4 6.4 16.9 5.7 17.6 5.4 16.6 0.0 0.0 2.00–3.99 17.8 18.1 16.8 15.7 20.6 18.7 27.0 19.3 0.0 0.0 4.00–5.99 23.3 20.1 21.1 19.1 29.6 25.3 38.6 22.6 0.0 0.0 ≥6 56.1 26.7 55.7 18.0 44.1 29.5 29.1 14.0 0.0 0.0 Without health insurance (%) - - - - - - - - - - <6 17.8 19.8 9.7 11.4 5.0 15.8 6.6 8.2 0.0 0.0 6.00–9.99 18.5 16.4 20.1 15.7 9.8 17.5 19.1 17.5 0.0 0.0 10.00–15.99 31.9 23.0 31.3 17.2 20.1 18.2 25.3 16.5 0.0 0.0 ≥16 31.8 30.8 38.9 22.9 65.2 30.8 49.0 23.7 0.0 0.0 Totalg 100 22.5 100 17.7 100 24.4 100 18.2 0.0 0.0 - Hispanic/Latinob - Northeast Midwest South West Pureto Rico - % Rate % Rate % Rate % Rate % Rate Age group at diagnosis (yrs.) - - - - - - - - - - 18–24 8.1 4.5 14.8 2.7 15.7 5.8 18.8 3.2 4.9 2.4 25–34 24.4 9.6 27.8 3.9 27.0 7.2 27.1 3.6 21.0 7.7 35–44 23.6 10.2 16.7 2.5 23.1 6.4 23.1 3.4 21.0 7.5 45–54 25.6 12.8 29.6 6.3 18.8 6.5 20.5 3.7 29.6 10.0 55–64 14.6 10.4 3.7 1.2 10.8 5.5 8.7 2.3 17.3 6.0 65+ 3.7 2.6 7.4 3.0 4.6 2.2 1.8 0.5 6.2 1.4 Transmission categoryc - - - - - - - - - - Injection drug use 13.9 - 12.2 - 7.3 - 16.2 - 8.5 - Heterosexual contactd 85.4 - 87.6 - 92.7 - 83.7 - 91.5 - Other e 0.7 - 0.2 - 0.1 - 0.1 - 0.0 - Residence area at diagnosis f - - - - - - - - - - Urban 93.5 - 68.5 - 85.8 - 86.9 - 67.9 - Suburban 4.1 - 14.8 - 8.7 - 11.4 - 30.9 - Rural 2.4 - 16.7 - 4.8 - 1.8 - 1.2 - Unknown 0.0 - 0.0 - 0.7 - 0.0 - 0.0 - Social Determinants of Health - - - - - - - - - - Below the federal poverty level (%) - - - - - - - - - - <7 8.9 4.0 14.8 2.4 11.6 3.8 11.4 2.2 0.0 0.0 7.00–10.99 13.0 7.3 16.7 2.8 16.1 5.3 12.7 2.1 0.0 0.0 11.00–18.99 19.9 7.1 38.9 4.1 30.4 5.7 32.3 3.0 2.5 2.5 ≥19 58.1 12.4 29.6 3.8 41.9 7.5 43.7 4.0 97.5 5.9 Less than high school diploma (%) - - - - - - - - - - <6 6.5 4.9 14.8 3.0 9.4 4.3 8.7 2.4 2.5 4.7 6.00–10.99 8.5 4.5 24.1 3.7 17.4 5.9 11.4 2.3 2.5 2.2 11.00–17.99 16.3 7.1 22.2 3.6 22.7 6.0 12.7 2.1 16.1 4.3 ≥18 68.7 11.5 38.9 3.3 50.6 6.3 67.3 3.6 79.0 6.4 Median household income (U.S. $) - - - - - - - - - - <40,000 46.8 12.6 33.3 4.5 38.3 7.1 34.1 4.3 98.8 5.9 40,000–53,999 21.1 8.5 40.7 4.2 32.5 6.8 28.8 3.2 1.2 1.4 54,000–74,999 21.5 8.0 14.8 1.9 16.6 4.3 23.1 2.6 0.0 0.0 ≥75,000 10.6 4.1 11.1 2.5 12.5 4.4 14.0 2.0 0.0 0.0 Unemployed (%) - - - - - - - - - - <2 4.5 5.7 13.0 3.6 10.6 4.7 4.4 2.0 3.7 6.6 2.00–3.99 21.5 6.5 38.9 4.0 32.3 5.0 25.8 2.8 7.4 2.9 4.00–5.99 23.6 7.3 22.2 2.8 35.9 7.1 32.3 3.1 17.3 4.8 ≥6 50.4 12.1 25.9 3.2 21.2 6.7 37.6 3.4 71.6 6.4 Without health insurance (%) - - - - - - - - - - <6 13.4 5.3 13.0 2.4 4.1 4.4 5.7 1.6 24.7 3.3 6.00–9.99 18.3 8.2 20.4 3.6 6.3 4.2 14.0 2.7 40.7 5.7 10.00–15.99 28.5 10.5 25.9 3.9 15.7 5.3 21.0 2.5 25.9 9.6 ≥16 39.8 9.9 40.7 3.5 74.0 6.4 59.4 3.7 8.6 19.5 Totalg 100 8.7 100 8.7 100 5.9 100 3.0 100 5.6 Abbreviation: Dash (-) indicates absence of denominator data and rate is not calculated. Note: Rates are per 100,000 population. Rates are not calculated by transmission category because of the lack of denominator data. The American Community Survey does not provide age- and sex-specific social determinants of health variables stratified by race and ethnicity for racial groups except Whites (i.e., White, not-Hispanic/Latino). Therefore, the denominators used for computing race-specific rates may include Hispanics/Latinos and should be interpreted with caution. a Northeast: Connecticut, Maine, New Hampshire, New Jersey, New York, Pennsylvania, and Rhode Island; Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin; South: Alabama, Arkansas, Delaware, Florida, Georgia, Kentucky, Louisiana, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia; West: Alaska, Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming. b Hispanics/Latinos can be of any race. c Data have been statistically adjusted to account for the missing transmission category. d Heterosexual contact with a person known to have, or to be at high risk for, HIV infection. e Includes hemophilia, blood transfusion, perinatal exposure, and risk factor not reported or not identified. f Urban: population of ≥500,000. Suburban: population of 50,000– 499,999. Rural: nonmetropolitan area, (<50,000) g Totals do not represent all adults whose HIV infection was diagnosed during 2017 in these areas. By SDH for each race/ethnicity group and across all regions, the highest rates of HIV diagnoses were among women who lived in census tracts where at least 19% of residents had incomes below the federal poverty level. The one exception was Hispanic/Latino women in the Midwest, for whom the highest rate was among those women who lived in census tracts where at least 11% but fewer than 19% of the residents had incomes below the federal poverty level. Women with the highest HIV rates lived in census tracts where at least 18% of residents had less than a high school diploma. An exception was Black women in the West, for whom the highest rates were among women living in census tracts where at least 11% but fewer than 18% of the residents had less than a high school diploma. Another exception was Hispanic/Latino women in the Midwest, for whom the highest rates were among women living in census tracts where at least 6% but fewer than 11% of the residents had less than a high school diploma. Women with the highest HIV diagnosis rates also lived in census tracts where the median household income was less than$40,000, and at least 16% were without health insurance. The exception was Hispanic/Latino women in the Northeast and Midwest, among whom the highest diagnosis rates were in census tracts where at least 10% but fewer than 16% of the residents were uninsured. Among White women, those who lived in census tracts where at least 6% of the residents were unemployed accounted for the highest HIV diagnosis rates in every region; no clear pattern was observed for Black and Hispanic/Latino women (Table 2).

By residence area and race/ethnicity, the largest number of HIV diagnoses (2,984) was among Black women in urban areas (Table 3). By age and residence area, the largest percentages of HIV diagnoses were among women aged 25–34 years, regardless of race/ethnicity (except for Hispanic/Latinos in rural areas). By residence area and transmission category, the largest percentage was among women with HIV infection attributed to heterosexual contact, regardless of race/ethnicity. By residence area and SDH, regardless of race/ethnicity, the highest percentages were among those who lived in census tracts where at least 19% of the residents lived below the federal poverty level (except White women in rural areas), at least 18% of the residents had less than high school diploma (except White women in suburban areas), the median household income was less than $40,000 a year (except White women in urban areas) and 16% or more of the residents did not have health insurance or a health coverage plan (Table 3). Table 3. Count and percentages of diagnoses of HIV infection among women, by race/ethnicity, area of residence and selected characteristics, 2017─United States, the District of Columbia and Puerto Rico.  - White Black Hispanic/Latinoa - Urban Suburban Rural Urban Suburban Rural Urban Suburban Rural - # % # % # % # % # % # % # % # % # % Age group at diagnosis (yr) - - - - - - - - - - - - - - - - - 18-24 102 12.7 21 9.8 12 11.3 380 12.7 76 17.5 28 17.0 120 13.7 8 7.6 10 25.0 25-34 232 28.9 64 29.8 33 31.1 794 26.6 128 29.5 56 33.9 225 25.7 30 28.6 10 25.0 35-44 175 21.8 59 27.4 22 20.8 700 23.5 99 22.8 32 19.4 208 23.7 19 18.1 6 15.0 45-54 165 20.6 40 18.6 24 22.6 564 18.9 73 16.8 27 16.4 189 21.6 28 26.7 11 27.5 55-64 111 13.8 25 11.6 11 10.4 415 13.9 41 9.5 16 9.7 100 11.4 15 14.3 2 5.0 65+ 17 2.1 6 2.8 4 3.8 131 4.4 17 3.9 6 3.6 35 4.0 5 4.8 1 2.5 Transmission categoryb - - - - - - - - - - - - - - - - - - Injection drug use 251 31.3 59 27.4 32 30.5 229 7.7 28 6.5 10 6.0 99 11.3 15 14.0 1 3.3 Heterosexual contactc 547 68.3 156 72.6 73 69.3 2,737 91.7 404 93.1 155 93.9 777 88.6 89 85.1 39 96.5 Otherd 3 0.4 0 0.1 0 0.3 19 0.6 1 0.3 0 0.1 1 0.1 1 1.0 0 0.3 Social Determinants of Health - - - - - - - - - - - - - - - - - - Below federal poverty level (%) - - - - - - - - - - - - - - - - - - <7 185 23.1 35 16.3 * * 338 11.3 27 6.2 * * 90 10.3 * * * * 7.00–10.99 154 19.2 51 23.7 18 17.0 394 13.2 36 8.3 14 8.5 119 13.6 * * * * 11.00–18.99 224 27.9 56 26.1 45 42.5 801 26.8 106 24.4 52 31.5 230 26.2 27 25.7 15 37.5 ≥19 239 29.8 73 34.0 41 38.7 1,451 48.6 265 61.1 95 57.6 438 49.9 58 55.2 15 37.5 Less than high school diploma (%) - - - - - - - - - - - - - - - - - - <6 146 18.2 34 15.8 * * 255 8.6 40 9.2 * * 75 8.6 * * * * 6.00–10.99 217 27.1 63 29.3 18 17.0 536 18.0 61 14.1 14 8.5 108 12.3 17 16.2 * * 11.00–17.99 201 25.1 64 29.8 38 35.9 815 27.3 128 29.5 51 30.9 154 17.6 22 21.0 * * ≥18 238 29.7 54 25.1 46 43.4 1,378 46.2 205 47.2 94 57.0 540 61.6 58 55.2 20 50.0 Median household income (U.S.$) - - - - - - - - - - - - - - - - - - <40,000 212 26.4 77 35.8 46 43.4 1,412 47.3 267 61.5 113 68.5 381 43.4 51 48.6 17 42.5 40,000–53,999 202 25.2 59 27.4 45 42.5 678 22.7 103 23.7 36 21.8 228 26.0 33 31.4 15 37.5 54,000–74,999 213 26.6 63 29.3 14 13.2 552 18.5 52 12.0 12 7.3 159 18.1 16 15.2 * * ≥75,000 175 21.8 16 7.4 * * 341 11.4 12 2.8 * * 109 12.4 * * * * Unemployed (%) - - - - - - - - - - - - - - - - - - <2 83 10.4 39 18.1 15 14.2 138 4.6 31 7.1 21 12.7 56 6.4 14 13.3 * * 2.00–3.99 277 34.5 71 33.0 53 50.0 572 19.2 97 22.4 46 27.9 236 26.9 21 20.0 16 40.0 4.00–5.99 238 29.7 57 26.5 24 22.6 839 28.1 118 27.2 46 27.9 269 30.7 26 24.8 * * ≥6 204 25.4 48 22.3 14 13.2 1,435 48.1 188 43.3 52 31.5 316 36.0 44 41.9 * * Without health insurance (%) - - - - - - - - - - - - - - - - - - <6 162 20.2 36 16.7 * * 259 8.7 23 5.3 * * 70 8.0 18 17.1 * * 6.00–9.99 175 21.8 49 22.8 23 21.7 407 13.6 54 12.4 17 10.3 113 12.9 23 21.9 * * 10.00–15.99 190 23.7 55 25.6 36 34.0 715 24.0 94 21.7 52 31.5 189 21.6 20 19.1 * * ≥16 275 34.3 75 34.9 41 38.7 1,603 53.7 263 60.6 92 55.8 505 57.6 44 41.9 20 50.0 Totalf 802 100 215 100 106 100 2,984 100 434 100 165 100 877 100.0 105 100 40 100
Abbreviation: Asterisk (*) indicates cell too small (<12 diagnoses during the year) and data has been suppressed.
Rates are per 100,000 population. Rates are not calculated by transmission category because of the lack of denominator data.
a Hispanics/Latinos can be of any race.
b Data have been statistically adjusted to account for the missing transmission category.
d Heterosexual contact with a person known to have, or to be at high risk for, HIV infection.
d Includes hemophilia, blood transfusion, perinatal exposure, and risk factor not reported or not identified.
e Urban: population of ≥500,000. Suburban: population of 50,000– 499,999. Rural: nonmetropolitan area (<50,000).
fTotals do not represent all adults whose HIV infection was diagnosed during 2017 in these areas..

## 4. DISCUSSION

The results of this study are supported by findings in the previous research [ 21-24]. Overall, women who lived in areas with the highest poverty, highest unemployment, lowest incomes, and those without health insurance coverage were more likely to have higher rates of HIV infection than did women who lived in the higher favorable quartiles. The South followed the national trends in having the highest number of HIV diagnoses and the highest rates of HIV infection among women in the SDH examined. Overall, women in the least favorable quartiles in every region, regardless of race/ethnicity, tended to have the highest diagnosis rates. However, patterns in the SDH categories varied among Hispanic/Latino women in the Midwest. Across regions, higher rates of diagnoses were seen among White women aged 25–34 years. Among Blacks and Hispanics/Latinos, higher rates were seen in women aged 35 years and older for certain regions. Additionally, Black women in every area of residence had the highest percentages of HIV diagnoses in the least favorable SDH quartiles. Overall, across all races/ethnicities and regions, rates of HIV diagnoses were highest among women residing in the census tracts with the lowest median household income and lacking health insurance coverage.

The results of this study showed that women who receive an HIV diagnosis, regardless of race/ethnicity and region, are generally in the least favorable quartiles of each SDH analyzed (barring a few exceptions). Research has shown an association between poor health and living in areas with high poverty levels, having low income, lacking health insurance coverage, lacking education, and lacking employment [25-27]. This is more pronounced among women, who often put their health needs aside to meet other priorities to survive and take care of their families [28, 29]. When race is considered, we find that there are more pervasive disparities in access to health insurance coverage among minority women [30, 31]. The Coverage and Access to Care Under the Affordable Care Act reports that overall, 86% of Black women (ages 18–64 years) had health insurance in 2017, compared with nearly 92% of white women [32]. Moreover, Black women are more likely to hold low-wage jobs that might not provide adequate health benefits [33].

The results of this study also showed that the highest rates of HIV diagnoses among white women were seen in a younger age group (25–34 years). In contrast, Black and Hispanic/Latino women mostly had the highest rates of HIV diagnoses in older age groups. This might be a result of Black and Hispanic/Latinos receiving a late HIV diagnosis. Previous studies show that Black and Hispanic/Latino women tend to present at later stages in their HIV diagnosis [34-36]. This could be attributed to varying attitudes towards sexual and reproductive health among younger women of certain racial/ethnic origins. Among Black and Hispanic/Latino women, stigma might restrain young unmarried women from going for an HIV test [37, 38]. The fear of being HIV positive and fear of the social consequences, such as rejection by loved ones, loss of employment or housing, and the fear of discrimination and violence, can lead to delays in testing for HIV [37-39]. This concurs with a study involving Black and Latino women at risk for HIV, which showed that stigma and the perception that these women were engaging in risky behaviors influenced their decision to visit a clinic to receive an HIV vaccine in a vaccine trial study [39]. Through the decades, Black and Hispanic/Latino women also have had less access to treatment and prevention services [40-42].

The results of this study showed that Black women in every type of residence area had the highest HIV diagnosis percentages in the least favorable quartile of each SDH. However, this does not hold the same for White and Hispanic/Latino women. This might be because Black women often experience multiple SDH that might negatively affect their health. For instance, Black women experience poverty at higher rates than do Black men and women from all other racial/ethnic groups [42, 43]. One study reported that non Hispanic Black women were most likely to be single heads of households with family members present (27.5%), and non Hispanic Asian and non-Hispanic White women were least likely (7.5% and 9.4%, respectively) [43]. More than 30% of female single heads of households with family members had household incomes below the poverty level, contributing further to worse health outcomes [43]. However, White women had the highest percentages of HIV diagnoses in the second most favorable unemployment level, regardless of region. This suggests that being unemployed for White women is not necessarily a factor for poor health. It is possible that White women are more likely to be employed than women of other races [2, 26], but we cannot explain why they had higher rates of HIV diagnosis in the more favorable unemployment census tracts.

The results of this study showed that regardless of race/ethnicity, women who lived in a census tract with the lowest median household income and the highest percentage of uninsured residents (except for Hispanic/Latino women in the Northeast and Midwest) generally had the highest HIV diagnosis rates. Several studies have shown that women with low incomes might have poorer health outcomes and are unable to afford health insurance coverage might have poorer health outcomes [44-46]. Previous research has given important insights into how health care coverage affects health care use, disease treatment and outcomes, self-reported health, and mortality [47]. Women in worse health and those with low incomes, or those uninsured, are more likely than others to delay or forgo health services because of the costs associated with health coverage. Women in low-income households tend to decline needed health care screenings to keep income within the household [27, 28]. There is also strong evidence that health insurance coverage increases access to preventive services, such as pre-exposure prophylaxis, which can directly maintain or improve health and reduce the chances of being infected with HIV [47, 48].

This analysis is subject to at least four limitations. First, diagnoses of HIV do not represent incidence of HIV or new infections. The time from infection to diagnosis will differ with each woman and the residence at HIV diagnosis might not be the same as when HIV was acquired. Second, data were limited to women with a complete residential address that could be geocoded; therefore, the results might not be representative of all women receiving an HIV diagnosis in the United States in 2017. Third, because SDH information is not available at the individual level, census tract-level data were used as a snapshot of the environment in which women lived at the time of HIV diagnosis. Conclusions and findings should be interpreted with caution and not inferred at the individual level. Fourth, some SDH indicators (e.g., lack of health coverage) are associated with low income and poverty in the United States [27, 49, 50], but correlations between SDH indicators were not analyzed for this report.

## CONCLUSION

This publication is the first of its kind to examine the distribution of census tract-level SDH among women receiving an HIV diagnosis in the 50 states, DC, and Puerto Rico. The results show that the burden of HIV among women by region is affected by race/ethnicity and SDH. By identifying the SDH that are strong indicators for a diagnosis of HIV among select populations of women, and the distribution of HIV by geography, targeted interventions can be tailored to those specific populations, which might yield better health outcomes. Future interventions should take into consideration SDH, such as income and health insurance coverage, among women with respect to race/ethnicity, region and area of residence. Examining these will allow appropriate allocation of resources to the geographic areas where they are needed the most, thereby meeting the objectives outlined in the federal initiatives.

### AUTHORS’ CONTRIBUTIONS

All authors contributed to the design of the study, analysis, interpretation, and write up of the manuscript. All authors read and approved the final manuscript.

Not applicable.

Not applicable.

Not applicable.

### AVAILABILITY OF DATA AND MATERIALS

The authors confirm that the data supporting the findings of this study are available within the article.

None.

### CONFLICT OF INTEREST

The authors herein declare that, in the conception, ethics, data collection, and the drafting of this paper, they have no conflicts of interest in any form.

## ACKNOWLEDGEMENTS

Publication of this article was made possible with the contributions of the state and territorial health departments and the HIV surveillance programs that provided surveillance data to CDC. The authors thank CDC colleagues for their review of and feedback on this article.

We thank the state and territorial health departments for their contributions to HIV surveillance data provided to the CDC. We also thank our CDC colleagues for their review and feedback on this paper.

## REFERENCES

 [1] Centers for Disease Control and Prevention. HIV Surveillance Report 2017; 29http://www.cdc.gov/hiv/library/reports/hiv-surveillance.html [2] Centers for Disease Control and Prevention. Social determinants of health among adults with diagnosed HIV infection, 2016. Part A: Census tract-level social determinants of health among adults with diagnosed HIV infection—13 states, the District of Columbia, and Puerto Rico HIV Surveillance Supplemental Report 2016; 23(6, pt A) Available from: https://www.cdc.gov/hiv/pdf/library/reports/surveillance/cdc-hiv-surveillance-supplemental-report-vol-23-6.pdf [3] Bradley ELP, Williams AM, Green S, et al. Disparities in incidence of human immunodeficiency virus infection among Black and white women—United States, 2010–2016. MMWR Morb Mortal Wkly Rep 2019; 68(18): 416-8. [4] Watson M, Johnson SD, Zhang T, Oster AM. Characteristics of and trends in HIV diagnoses in the Deep South region of the United States, 2012–2017. AIDS Behav 2019; 23(3)(Suppl. 3): 224-32. [5] 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 Health 2008. Available from: https://www.who.int/publications/i/item/WHO-IER-CSDH-08.1 [6] De Jesus M, Williams DR. The care and prevention in the United States demonstration project: a call for more focus on the social determinants of HIV/AIDS Public Health Rep 2018; 133(2): 28S-33S. [7] Arya M, Behforouz HL, Viswanath K. African American women and HIV/AIDS: a national call for targeted health communication strategies to address a disparity. AIDS Read 2009; 19(2): 79-84, C3. [8] McCree DH, Chesson H, Bradley ELP, Lima A, Fugerson AG. US regional changes in racial/ethnic disparities in HIV diagnoses among women in the United States, 2012 and 2017. AIDS Behav 2020; 24(4): 1118-23. [9] Stone VE. HIV/AIDS in women and racial/ethnic minorities in the U.S. Curr Infect Dis Rep 2012; 14(1): 53-60. [10] Demeke HB, Johnson AS, Wu B, Moonesinghe R, Dean HD. Unequal declines in absolute and relative disparities in HIV diagnoses among BlackBlack women, United States, 2008 to 2016. Am J Public Health 2018; 108(S4): S299-303. [11] May S, Murray A, Sutton MY. HIV infection among women in the United States: 2000-2017. AIDS Care 2020; 32(4): 522-9. [12] Fauci AS, Redfield RR, Sigounas G, Weahkee MD, Giroir BP. Ending the HIV epidemic: a plan for the United States. JAMA 2019; 321(9): 844-5. [13] Centers for Disease Control and Prevention. Division of HIV/AIDS prevention strategic plan 2017–2020. Atlanta, GA: US Department of Health and Human Services, CDC. 2017. Available from: https://www.cdc.gov/hiv/dhap/strategicplan/index.html [14] Ratcliffe M, Burd C, Holder K, Fields A. Defining rural at the US Census Bureau 2016.https://www.census.gov/content/dam/Census/library/publications/2016/acs/acsgeo-1.pdf [accessed 16 Dec 2020] [15] US Census Bureau. 2013‐2017 American Community Survey 5‐year estimates. Washington, DC: US Census Bureau; . 2018. Available from: https://www.census.gov/programs-surveys/acs/news/data-releases/2017/release.html [16] Gupta GR, Parkhurst JO, Ogden JA, Aggleton P, Mahal A. Structural approaches to HIV prevention. Lancet 2008; 372(9640): 764-75. [17] Williams DR, Jackson PB. Social sources of racial disparities in health. Health Aff (Millwood) 2005; 24(2): 325-34. [18] Braveman P, Gottlieb L. The social determinants of health: it's time to consider the causes of the causes. Public Health Rep 2014; 129(2): 19-31. [19] Harrison KM, Kajese T, Hall HI, Song R. Risk factor redistribution of the national HIV/AIDS surveillance data: an alternative approach. Public Health Rep 2008; 123(5): 618-27. [20] US Census Bureau. Census regions and divisions of the United States 2015. Available from: https://www2.census.gov/geo/pdfs/maps-data/maps/reference/us_regdiv.pdf [21] Probst C, Simbayi LC, Parry CDH, Shuper PA, Rehm J. Alcohol use, socioeconomic status and risk of HIV infections. AIDS Behav 2017; 21(7): 1926-37. [22] Sharpe TT, Voûte C, Rose MA, Cleveland J, Dean HD, Fenton K. Social determinants of HIV/AIDS and sexually transmitted diseases among black women: implications for health equity. J Womens Health (Larchmt) 2012; 21(3): 249-54. [23] Geter A, Sutton MY, Hubbard McCree D. Social and structural determinants of HIV treatment and care among black women living with HIV infection: a systematic review: 2005-2016. AIDS Care 2018; 30(4): 409-16. [24] Cianelli R, Villegas N. Social determinants of health for HIV among Hispanic women. Hisp Health Care Int 2016; 14(1): 4-9. [25] Gay J. The health of women: a global perspective 2018. [26] Frew PM, Parker KA, Vo L, et al. The intersection of women’s health and poverty.Poverty in the United States 2017; 25-49. [27] Jacobson JL. Women’s health: the price of poverty–women’s health at the crossroad 1992; 1-0. [28] Stevens PE, Keigher SM. Systemic barriers to health care access for U.S. women with HIV: the role of cost and insurance. Int J Health Serv 2009; 39(2): 225-43. [29] Langer A, Meleis A, Knaul FM, et al. Women and Health: the key for sustainable development. Lancet 2015; 386(9999): 1165-210. [30] US Census Bureau. Income, poverty and health insurance coverage in the United States: 2018. Washington, DC: US Census Bureau. 2019. Available from: https://www.census.gov/newsroom/press-releases/2019/income-poverty.html [31] National Patnership for Women and Families. Black women experience pervasive disparities in access to health insurance 2019. Available from: https://www.nationalpartnership.org/our-work/resources/health-care/Black-womens-health-insurance-coverage.pdf [32] McMorrow S, Polsky D. Insurance coverage and access to care under the Affordable Care Act. LDI Issue Brief 2016; 21(2): 1-8. [33] Toossi M, Morisi TL. Women in the workforce before, during, and after the Great Recession 2017.https://www.bls.gov/spotlight/2017/women-in-the-workforce-before-during-and-after-the-great-recession/home.htm [cited: 16 Dec 2020] [34] Lopez-Quintero C, Rojas P, Dillon FR, Varga LM, De La Rosa M. HIV testing practices among Latina women at risk of getting infected: a five-year follow-up of a community sample in South Florida. AIDS Care 2016; 28(2): 137-46. [35] Clark HJ, Lindner G, Armistead L, Austin BJ. Stigma, disclosure, and psychological functioning among HIV-infected and non-infected African-American women. Women Health 2003; 38(4): 57-71. [36] Darlington CK, Hutson SP. Understanding HIV-related stigma among women in the southern United States: a literature review. AIDS Behav 2017; 21(1): 12-26. [37] Earnshaw VA, Bogart LM, Dovidio JF, Williams DR. Stigma and racial/ethnic HIV disparities: moving toward resilience. Stigma Health 2015; 1(S): 60-74. [38] Stringer KL, Turan B, McCormick L, et al. HIV-related stigma among healthcare providers in the deep south. AIDS Behav 2016; 20(1): 115-25. [39] Newman PA, Duan N, Roberts KJ, et al. HIV vaccine trial participation among ethnic minority communities: barriers, motivators, and implications for recruitment. J Acquir Immune Defic Syndr 2006; 41(2): 210-7. [40] Espinoza L, Hall HI, Selik RM, Hu X. Characteristics of HIV infection among Hispanics, United States 2003-2006. J Acquir Immune Defic Syndr 2008; 49(1): 94-101. [41] Noonan AS, Velasco-Mondragon HE, Wagner FA. Improving the health of African Americans in the USA: an overdue opportunity for social justice. Public Health Rev 2016; 37(1): 12. [42] Semega JL, Fontenot KR, Kollar MA. Income and poverty in the United States: 2016 2017.https://www.census.gov/content/dam/Census/library/publications/2017/demo/P60-259.pdf [accessed 16 Dec 2020] [43] Wallace PA. A research agenda on the economic status of Black women. Slipping through the cracks: the status of Black women Simms MC, Malveaux J. 1986. [44] Khullar D, Chokshi DA. Health, income, and poverty: Where we are and what could help. Health Aff (Millwood) 2018; 10https://www.healthaffairs.org/do/10.1377/hpb20180817.901935/full/ [cited 16 Dec 2020]. [45] Marmot M. The influence of income on health: views of an epidemiologist. Health Aff (Millwood) 2002; 21(2): 31-46. [46] Reid C. The wounds of exclusion: poverty, women’s health, and social justice Abingdon-on-Thames 2017. [47] Sommers BD, Blendon RJ, Orav EJ, Epstein AM. Changes in utilization and health among low-income adults after Medicaid expansion or expanded private insurance. JAMA Intern Med 2016; 176(10): 1501-9. [48] Sudano JJ Jr, Baker DW. Intermittent lack of health insurance coverage and use of preventive services. Am J Public Health 2003; 93(1): 130-7. [49] Caliendo SM. Income and wealth.Inequality in America: Race, poverty, and fulfilling democracy’s promise 2018; 43-71. [50] Quinn TC, Overbaugh J. HIV/AIDS in women: An expanding epidemic. Science 2005; 308(5728): 1582-3.