Abstract
Assessing pre-exposure prophylaxis (PrEP) coverage and identifying reasons for disproportionate uptake among the varied social and cultural sub-groups of men who have sex with men (MSM) and transgender women who have sex with men (TWSM) are necessary precursors to setting attainable local PrEP. We report on findings of a cross-sectional survey among MSM/TWSM attending Gay pride events in Atlanta, Georgia, in 2018. Associations between PrEP awareness, uptake, and respondent characteristics were assessed using logistic regression. PrEP awareness did not differ by race, but current use was significantly lower among Blacks at substantial risk of HIV (p = .008). In multivariate analysis, clinician encounter in the past year was associated with awareness while age, income, drug use, sero-discordant sex, and multiple male partners were associated with current use. Among PrEP-naïve MSM/TWSM, the most common reasons for nonuse differed by race (poor knowledge of PrEP: Black—45% vs. non-Black—27%, p = .010, low perception of risk: Black—26% vs. non-Black—52%, p = .001). Key racial and socioeconomic disparities in active PrEP use and reasons for nonuse remain despite the recent increases in PrEP awareness and use among MSM/TWSM in Atlanta. Achieving overall improvement in uptake among all MSM/TWSM sub-groups will require tailoring PrEP educational messaging, optimizing communication modalities, expanding provider outreach, and identifying ways to defray costs for high-risk, underserved sub-groups in these populations.
Keywords: Men who have sex with men (MSM), Transgender women who have sex with men (TWSM), PrEP, Geographic hotspots, Transgender, Sexual orientation
Introduction
Increasing use of pre-exposure prophylaxis (PrEP) among priority populations like men who have sex with men (MSM) and transgender women who have sex with men (TWSM) who have been hardest hit by the HIV epidemic in the U.S. is one of the four pillars of the new federal initiative to combat HIV—Ending the HIV Epidemic (EHE) Campaign (Fauci, Redfield, Sigounas, Weahkee, & Giroir, 2019; US Department of Health and Human Services, 2019). Despite the substantial volume of research demonstrating the efficacy of PrEP, analyses of aggregated pharmacy prescription data show that PrEP use has not been commensurate with underlying need (AIDSVu, 2018; Cooley et al., 2014; Sullivan et al., 2018). This disparity has been most severe in the U.S. South which has accounted for over half of all new HIV diagnoses in the U.S. over the past 2 years (Huang, Zhu, Smith, Harris, & Hoover, 2018; Rolle et al., 2017; Sullivan et al., 2018; Wu et al., 2017). In recognition of the need for a geographically focused approach to ending the HIV epidemic, the federal EHE plan has rolled out detailed proposals to focus treatment and prevention efforts on priority populations within specific geographic areas known to have high HIV burdens (Fauci et al., 2019).
In addition to federal efforts, locally developed initiatives to tackle HIV prevention are also being implemented in various localities. Fulton County, one of the four counties in the metropolitan Atlanta area that were included as geographic “hotspots” in the federal EHE plan, developed and implemented a local campaign—the STOPHIVATL campaign—in 2018 to improve HIV testing, treatment and uptake of PrEP among priority populations affected by HIV in metro Atlanta (Fulton County Board of Health, STOPHIVATL, 2018). These priority populations include Black and Latino MSM who together accounted for 77% of prevalent HIV and 82% of new HIV diagnoses in Atlanta in 2017 (AIDSVu, 2019; Georgia Department of Public Health, 2019). It also includes Black and Latino transgender persons (specifically transgender women) who have been estimated to have high prevalence of HIV (Black 44%, Latino 26%) in the South (Centers for Disease Control and Prevention [CDC], 2020). Fulton County Board of Health (FCBOH) also adopted a status-neutral approach to HIV testing in the same year, requiring and ensuring that all health department funded HIV testing activities among these priority populations are directly linked with a referral to the relevant HIV service area, irrespective of the outcome of the testing encounter (Myers et al., 2018). Individuals who are HIV-positive are linked with Ryan White services while those who are negative (and are at increased risk of acquiring HIV) are referred for PrEP.
A necessary precursor to measuring the success of a HIV prevention campaign in any local jurisdiction is an assessment of relevant “baseline” metrics of disease prevalence and uptake of prevention measures among the populations of interest. For the PrEP uptake goals of the STOPHIVATL campaign, accurate assessments of PrEP coverage allow setting of attainable local PrEP uptake goals and development of strategies to address challenges unique to the jurisdiction’s local context. For estimates of PrEP coverage in Atlanta specifically, previous studies have shown that PrEP use ranges from 4 to 28%, estimates which lag behind PrEP use in other urban cities in the US that also have large communities of MSM and transgender women like San Francisco (61%), Chicago (47%), New York (41%), and Los Angeles (37%) (Eaton et al., 2017; Finlayson et al., 2019; Rolle et al., 2017). However, PrEP awareness, active use and reasons for nonuse among MSM and TWSM in Atlanta have not been measured since the initiation of highly visible, proactive prevention campaigns like STOPHIVATL. Here we report findings from a 2018 cross-sectional survey examining PrEP awareness, active use, interest in PrEP and reasons for nonuse of PrEP among MSM and TWSM participating in Atlanta’s Gay Pride Festivals in 2018.
Method
Participants
In 2018, FCBOH developed and administered an anonymous, cross-sectional survey to individuals attending the two annual Atlanta Gay Pride Festivals—Black Gay Pride and Atlanta Gay Pride. Recruitment of survey respondents was by in-person intercept where recruitment staff, dispersed throughout the venue of the Pride festivals, approached individuals participating in various attractions and asked about their willingness to participate in the survey. Interested and willing individuals were screened for eligibility (eligibility criteria included being 18 years of age or older and residing in the Georgia) and verbally consented. Individuals who completed the survey were offered a $5 gift card to a local grocery store as compensation for their time.
Measures and Procedure
The survey tool was a four-page-long self-administered questionnaire composed of 43 questions on sociodemographic characteristics, HIV testing and risk behaviors, PrEP awareness and status on use, reasons for nonuse of PrEP and details of active PrEP use. All respondents completed questions on sociodemographic characteristics, HIV testing and risk behaviors and PrEP awareness and use status. Respondents who indicated never using PrEP (PrEP-naïve respondents) completed survey questions regarding reasons for nonuse of PrEP while those who reported ever using PrEP completed the section on current use, PrEP-associated costs and reasons for discontinuation (if applicable). The full survey instrument is available in “Supplementary Material: FCBOH Pride Survey 2018.”
Two primary outcomes were explored: (1) awareness of PrEP and (2) active use of PrEP. Awareness of PrEP was ascertained by the survey participant’s response to the question “Before today, have you heard of PrEP?” [Response options: Yes, No, Somewhat/I think so]. Responses were collapsed to obtain the odds ratio of being aware of PrEP (Yes) vs not aware (No/Maybe). Active use of PrEP was assessed by asking survey respondents who indicated ever using PrEP if they were currently taking PrEP or have discontinued use.
Having male sex partners does not always translate to self-identification as “gay,” “homosexual” or “bisexual (Grey et al., 2016). Therefore, to avoid miscategorizing cis-gender men or transgender women who have sex with men and do not identify as “gay,” “homosexual” or “bisexual,” we created a definition of MSM that was inclusive of sexual behavior and irrespective of sexual identity by using responses from three separate questions that focused on gender identity and sexual behavior—(1) “What gender do you identify as?” Response responses: Male, Female, Non-binary, Male to Female transgender, Female to male transgender, other (a free text option)], (2) “Who have you had sex with in the past 12 months?” Response options: Males only, Females only, Both males and females, Other [a free text option]), and (3) “In the past 6 months, how many men have you had sex with?” Response options: None, no sex in 6 months, 1–5, 6–10, More than 10. Respondents were classified as MSM if they self-identified as “Male” and reported having sex with either “Males only” or “Both males and females” in the past 12 months or indicated having sex with one or more male sex partners in the past 6 months. Respondents who self-identified as “Male to Female transgender” and reported having sex with either “Males only” or “Both males and women” or indicated having sex with one or more male partners were classified as transgender women who had sex with men (TWSM).
Two questions—“Are you visiting Atlanta, or are you an Atlanta resident?” and “What is the zip code of where you currently live?” were used to identify respondents who resided within metropolitan Atlanta. To dichotomize the income variable, we used a cutoff figure ($60,000) that corresponded to an income within 500% of the 2018 federal poverty guidelines (FPG) for one individual in the 48 contiguous states (which included Georgia State). This criterion (500% of FPG) was selected because it is the income criterion used to determine eligibility for Truvada (for PrEP) medical assistance program enrollment at FCBOH PrEP clinic.
All sociodemographic characteristics (age, current gender identity, race, ethnicity, highest level of education attained, employment status, income, zip code, health insurance status, housing status, most recent clinical encounter) and HIV risk factors (number of male sexual partners, sex with a HIV-positive partner, any drug use [includes injection and non-injection drug use], any recent bacterial sexually transmitted infections [specifically syphilis, gonorrhea and chlamydia], diagnoses and consistency of condom use during penetrative sexual encounters) measured in the survey were included as covariates in adjusted analyses.
Data Analysis
Respondents who were not MSM/TWSM or who reported having a positive test at their most recent HIV testing encounter or reported living in a ZIP code outside the Atlanta area were excluded from analysis. Criteria for PrEP recommendation as outlined in the 2017 update of the U.S. Public Health Service’s (US PHS) Clinical Practice Guidelines for PrEP were used to identify MSM/TWSM at “substantial risk” of acquiring HIV infection (Centers for Disease Control and Prevention [CDC], 2017). HIV-uninfected MSM/TWSM who reported having one or more HIV-positive sex partners or a bacterial STI within the past 6 months or inconsistent condom use during sex with casual partners were categorized as being at substantial risk of HIV infection. Due to the large proportion of Black/African Americans in the study cohort, all eligible persons who identified as non-Hispanic Whites, Hispanics/Latino of all races, Asian, Native American, Mixed races, etc. were grouped together as “non-Black.”
Chi-square or Fisher’s exact tests were used to examine the differences in sociodemographic characteristics, HIV risk behaviors and testing frequencies between Black (Non-Hispanic) and non-Black PrEP-eligible MSM/TWSM. Independent associations between study outcomes and covariates were assessed using unadjusted logistic regression models. Odds ratios adjusted for all measured sociodemographic characteristics and HIV risk factors were calculated to assess associations with PrEP awareness and current use. Distributions of reasons cited for nonuse of PrEP and interest in initiating PrEP among PrEP-naïve respondents in the study cohort were also described using frequencies/percentages, and the racial differences in the reasons for nonuse were assessed using chi-square or Fisher’s exact tests. For all statistical tests performed, p values < .05 were considered to indicate significant associations.
All statistical analyses were performed in SAS v 9.3 (SAS Institute, Cary, NC).
Results
Study Sample Description
A total of 782 adults completed the survey, and 361 (46%) were MSM/TWSM who resided within Atlanta (Black: 220 [61%], non-Black: 141 [39%]). Three (0.8%) had missing HIV status, 81 (22%) reported being HIV positive (Black: 67 (30%), non-Black: 14 (10%), p < .0001) and 277 (77%) reported being HIV negative, never being tested for HIV or not able to recollect the result of their most recent HIV test. All 277 MSM/TWSM who did not report being HIV positive were included in the study cohort.
The median age was 31 years (Table 1), and 54% were Black/African American. The majority reported having college or advanced education (77%), being employed (90%), possessing health insurance (81%), having stable housing (89%) and having had a clinician encounter within the past year (85%). Six percent reported being diagnosed with a bacterial STI (syphilis, gonorrhea or chlamydia) within the previous 6 months, and 11% reported use of illicit drugs (injection or non-injection—crack cocaine, heroin or methamphetamines) within same duration. There were statistically significant differences in the income, possession of health insurance, history of stable housing and consistency of condom use at casual sex encounters among Blacks and non-Blacks. Sixty-five percent of the sample met the criteria for substantial risk of HIV acquisition according to the U.S. PHS/CDC guidelines, and a significantly higher proportion of Black MSM/TWSM met those criteria compared to non-Blacks (Black: 71% vs. non-Black: 58%, p = .03).
Table 1.
Sociodemographic characteristics and HIV risk behaviors among PrEP-eligible men who have sex with men (MSM) and transgender women who have sex with men (TWSM) attending Gay Pride events in Atlanta, GA, 2018
| Total (n = 277) |
Black (n = 150) |
Non-Black (n = 127) |
p value* | |
|---|---|---|---|---|
| n (%) | n (%) | n (%) | ||
|
| ||||
| Sociodemographic characteristics | ||||
| Gender | ||||
| Cis-gender men | 266 (96) | 141 (94) | 125 (98) | .060 |
| Transgender women | 11 (4) | 9 (6) | 2 (2) | |
| Age | ||||
| Median (IQR) | 31 (15) | 32 (15) | 29 (14) | |
| < 30 y.o. | 126 (46) | 62 (42) | 64 (50) | .144 |
| ≥ 30 y.o. | 150 (54) | 87 (58) | 63 (50) | |
| Race/ethnicity | ||||
| Black, non-hispanic | 150 (54) | 150 (100) | – | – |
| White, non-hispanic | 94 (34) | – | 94 (74) | |
| Other, non-Hispanic | 17 (6) | – | 17 (13) | |
| Hispanic, all races | 16 (6) | – | 16 (13) | |
| Education | ||||
| No collegea | 62 (23) | 38 (25) | 24 (19) | .239 |
| College/advanced | 212 (77) | 112 (75) | 100 (81) | |
| Employment status | ||||
| Not employed | 29 (10) | 13 (9) | 16 (13) | .287 |
| Employed | 248 (90) | 137 (91) | 111 (87) | |
| Incomeb | ||||
| < $60,000 annually | 199 (72) | 116 (77) | 83 (65) | .027 |
| ≥ $60,000 annually | 78 (28) | 34 (23) | 44 (35) | |
| Has health insurance? | ||||
| No | 52 (19) | 36 (24) | 16 (13) | .019 |
| Yes | 219 (81) | 112 (76) | 107 (87) | |
| Type: government assisted (medicaid/medicare) | 38 (17) | 24 (21) | 14 (13) | |
| Private/commercial | 173 (79) | 84 (75) | 89 (83) | |
| Veterans administration | 8 (4) | 4 (4) | 4 (4) | |
| Homeless in past yearc | ||||
| No | 246 (89) | 128 (85) | 118 (93) | .046 |
| Yes | 31 (11) | 22 (15) | 9 (7) | |
| Saw a clinician in past yeard | ||||
| No | 38 (14) | 19 (13) | 19 (15) | .580 |
| Yes | 239 (86) | 131 (87) | 108 (85) | |
| Place of residence | ||||
| Fulton County | 133 (48) | 72 (48) | 61 (48) | .996 |
| Rest of Atlanta MSA | 144 (52) | 78 (52) | 66 (52) | |
| HIV risk behaviors (past 6 months) | ||||
| Number of male sex partners | ||||
| ≤ 5 partners | 233 (86) | 128 (87) | 105 (84) | .471 |
| ≥ 6 partners | 39 (14) | 19 (13) | 20 (16) | |
| Condomless sex with a casual partner | ||||
| No | 104 (40) | 46 (33) | 58 (47) | .024 |
| Yes | 159 (60) | 93 (67) | 66 (53) | |
| Sex with a HIV-positive partner | ||||
| No | 222 (81) | 117 (79) | 105 (83) | .314 |
| Yes | 53 (19) | 32 (21) | 21 (17) | |
| Any bacterial STIe | ||||
| No | 257 (94) | 140 (95) | 117 (94) | .555 |
| Yes | 15 (6) | 7 (5) | 8 (6) | |
| Any recent drug usef | ||||
| No | 246 (89) | 132 (89) | 114 (90) | .612 |
| Yes | 29 (11) | 17 (11) | 12 (10) | |
| HIV risk categories | ||||
| At substantial risk of HIV (US PHS criteria)g | ||||
| No | 97 (35) | 44 (29) | 53 (42) | .031 |
| Yes | 180 (65) | 106 (71) | 74 (58) | |
| HIV testing | ||||
| Life-time HIV testing (ever had a HIV test) | ||||
| No | 11 (4) | 3 (2) | 8 (6) | .119 |
| Yes | 266 (96) | 147 (98) | 119 (94) | |
| Recent testing (past 6 months) | ||||
| No | 40 (15) | 18 (12) | 22 (18) | .171 |
| Yes | 226 (85) | 129 (88) | 97 (82) | |
| PrEP awareness and use | ||||
| Aware of PrEPh | ||||
| No | 22 (8) | 17 (11) | 5 (4) | .082 |
| Yes | 240 (87) | 126 (84) | 114 (90) | |
| I think so | 9 (3) | 5 (3) | 4 (3) | |
| Life-time use of (ever used) PrEP | ||||
| No | 196 (71) | 114 (76) | 82 (65) | .046 |
| Yes | 78 (28) | 35 (23) | 43 (34) | |
| Current use of PrEP | ||||
| Entire sample | ||||
| No | 220 (79) | 125 (83) | 95 (75) | .080 |
| Yes | 57 (21) | 25 (17) | 32 (25) | |
| Persons at substantial risk of HIV (met US PHS criteria) | ||||
| No | 133 (74) | 86 (81) | 47 (64) | .008 |
| Yes | 47 (26) | 20 (19) | 27 (36) | |
| Persons not at substantial risk | ||||
| No | 87 (90) | 39 (89) | 48 (91) | .756 |
Had high school education only or less
Income before taxes at end of 2017
Respondents who reported sleeping on the streets, shelter, motel or car in the past 12 months
Respondents who reported visiting a health-care facility for medical care within the previous year (primary care, urgent care, hospital, emergency room or service organization)
Any bacterial sexually transmitted diseases—syphilis, gonorrhea or chlamydia
Any illicit drug use (methamphetamines, cocaine, crack and heroin)
Criteria outlined on pp. 13, 36, United States Public Health Service, Clinical Practice Guidelines for PrEP, 2017 update
Survey question “Before today, have you heard of PrEP?”
Fisher’s exact test | statistically significant p values have been bolded for ease of interpretation
PrEP Awareness and Active Use
Overall, 87% reported being aware of PrEP (Table 1, Fig. 1). There was no statistically significant difference in PrEP awareness between Black and non-Black MSM/TWSM (p = .08). Awareness was, however, considerably lower than the overall cohort estimate among persons who reported being homeless within the previous year (65%), having a recent history of illicit drug use (66%), having a high school education or less (71%), no health insurance (73%) and no contact with a health-care provider in the past year (74%) (Table 2).
Fig. 1.
Awareness and uptake of PrEP among men who have sex with men (MSM) and transgender women who have sex with men (TWSM) participating in Atlanta Gay Pride Festivals, 2018
Table 2.
HIV risk, PrEP awareness, life-time use and current use among PrEP-eligible men who have sex with men (MSM) and transgender women who have sex with men (TWSM) attending Gay Pride Festivals, in Atlanta, GA 2018
| Total (n=277) |
Aware (n = 240) |
At risk (n = 180) |
Ever used (n = 78) |
Active users (n = 57) |
|
|---|---|---|---|---|---|
| n | n (%) | n (%) | n (%) | n (%) | |
|
| |||||
| Gender | |||||
| Cis-gender men | 266 | 231 (87) | 172 (65) | 77 (29) | 56 (21) |
| Transgender women | 11 | 9 (82) | 8 (73) | 1 (9) | 1 (9) |
| Race | |||||
| Black | 150 | 126 (84) | 106 (71) | 35 (23) | 25 (17) |
| Non-black | 127 | 114 (90) | 74 (58) | 43 (34) | 32 (25) |
| Age | |||||
| 18–29 years old | 126 | 111 (88) | 84 (67) | 25 (20) | 16 (13) |
| ≥ 30 years old | 150 | 128 (85) | 96 (64) | 53 (36) | 41 (27) |
| Education | |||||
| No college | 62 | 44 (71) | 46 (74) | 11 (18) | 9 (15) |
| College/advanced | 212 | 193 (91) | 134 (63) | 66 (31) | 47 (22) |
| Employment status | |||||
| Not employed | 29 | 22 (76) | 18 (62) | 4 (14) | 3 (10) |
| Employed | 248 | 218 (88) | 162 (65) | 74 (30) | 54 (22) |
| Income | |||||
| < $60,000 annually | 199 | 165 (83) | 132 (66) | 44 (22) | 31 (16) |
| ≥ $60,000 annually | 78 | 75 (96) | 48 (62) | 34 (44) | 26 (33) |
| Insurance | |||||
| No | 52 | 38 (73) | 30 (58) | 9 (17) | 5 (10) |
| Yes | 219 | 199 (91) | 146 (67) | 69 (32) | 52 (24) |
| Homeless in past year | |||||
| No | 246 | 220 (89) | 156 (63) | 72 (30) | 53 (22) |
| Yes | 31 | 20 (65) | 24 (77) | 6 (19) | 4 (13) |
| Saw a clinician in past year | |||||
| No | 38 | 28 (74) | 25 (66) | 7 (18) | 5 (13) |
| Yes | 239 | 212 (89) | 155 (65) | 71 (30) | 52 (22) |
| Place of residence | |||||
| Fulton County | 133 | 120 (90) | 85 (64) | 44 (33) | 29 (22) |
| Rest of Atlanta | 144 | 120 (83) | 95 (66) | 34 (24) | 28 (19) |
| Male sex partners in 6 months | |||||
| ≤ 5 partners | 233 | 201 (86) | 139 (60) | 54 (23) | 37 (16) |
| ≥ 6 partners | 39 | 36 (92) | 39 (100) | 23 (59) | 19 (49) |
| Unprotected sex with a casual partner | |||||
| No | 104 | 94 (90) | 15 (14) | 22 (21) | 12 (12) |
| Yes | 159 | 136 (86) | 159 (100) | 53 (34) | 43 (27) |
| Sex with a HIV-positive partner | |||||
| No | 222 | 192 (86) | 127 (57) | 45 (20) | 31 (14) |
| Yes | 53 | 46 (87) | 53 (100) | 31 (60) | 25 (47) |
| Any recent bacterial STI | |||||
| No | 257 | 226 (88) | 161 (63) | 70 (27) | 49 (19) |
| Yes | 15 | 12 (80) | 15 (100) | 7 (47) | 7 (47) |
| Any recent drug use | |||||
| No | 246 | 220 (89) | 156 (63) | 71 (29) | 54 (22) |
| Yes | 29 | 19 (66) | 23 (79) | 6 (21) | 3 (10) |
Twenty-eight percent of the sample reported ever using PrEP, and a significantly lower proportion of Blacks (23%) reported ever using PrEP compared to non-Blacks (34%) (p = .046). About one-fifth (21%) of the PrEP-eligible cohort were actively using PrEP at the time of the survey. A lower proportion of Blacks (17%) reported active use of PrEP compared to non-Blacks (25%), but this was not statistically significant (p = .08). However, among those who met the US PHS/CDC criteria for substantial risk of HIV acquisition, a significantly lower proportion of Blacks reported current PrEP use compared to non-Blacks (p = .008).
In unadjusted analysis (Table 3), being aware of PrEP was independently associated with higher level of education, being employed, having an income over $60,000, possession of health insurance, having a history of stable housing, reporting an encounter with a clinician in the previous year and recent use of illicit drugs. Only encounter with a clinician within the past year remained significantly associated with PrEP awareness in the multivariate model, with MSM/TWSM who reported having no encounter with a clinician in the preceding 12 months showing significantly lower odds (74% lower) of being aware of PrEP compared to those who reported having a clinician encounter in the past year (adjusted OR [aOR]: 0.26 [95% CI]: 0.08, 0.78, p = .016).
Table 3.
Bivariate and multivariate logistic regression analyses of PrEP awareness and current use among PrEP-eligible men who have sex with men (MSM) and transgender women who have sex with men (TWSM) attending Atlanta Gay Pride Festivals, 2018
| Aware of PrEP |
Current use of PrEP |
|||||||
|---|---|---|---|---|---|---|---|---|
| Unadjusted OR |
Adjusted OR |
Unadjusted OR |
Adjusted OR |
|||||
| cOR (95% CI) | p value | aOR (95% CI) | p value | cOR (95% CI) | p value | aOR (95% CI) | p value | |
|
| ||||||||
| Sociodemographic characteristics | ||||||||
| Gender | ||||||||
| Cis-gender men | 1.77 (0.37, 8.60) | .479 | 1.07 (0.18, 6.32) | 0.942 | 2.67 (0.34, 21.27) | .355 | 2.44 (0.18, 33.94) | .507 |
| Transgender women | Ref | Ref | Ref | Ref | ||||
| Race | ||||||||
| Black | 0.45 (0.20, 1.02) | .057 | 0.61 (0.20, 1.81) | 0.372 | 0.60 (0.33, 1.07) | .082 | 0.61 (0.29, 1.29) | .196 |
| Non-black | Ref | Ref | Ref | Ref | ||||
| Age | ||||||||
| 18–29 years old | 1.20 (0.56 (2.56) | .636 | 2.04 (0.75, 5.57) | 0.164 | 0.39 (0.21, 0.73) | .004 | 0.39 (0.17, 0.87) | .022 |
| ≥ 30 years old | Ref | Ref | Ref | Ref | ||||
| Education | ||||||||
| No collegea | 0.24 (0.11, 0.53) | < .001 | 0.64 (0.21, 1.96) | 0.435 | 0.60 (0.28, 1.30) | .193 | 1.08 (0.36, 3.20) | .897 |
| College/advanced | Ref | Ref | Ref | Ref | ||||
| Employment status | ||||||||
| Not employed | 0.35 (0.13, 0.89) | .028 | 0.83 (0.20, 3.48) | 0.799 | 0.42 (0.13, 1.43) | .162 | 0.82 (0.17, 3.93) | .795 |
| Employed | Ref | Ref | Ref | Ref | ||||
| Incomeb | ||||||||
| < $60,000 annually | 0.07 (0.01, 0.55) | .011 | 0.13 (0.02, 1.13) | 0.064 | 0.37 (0.21, 0.68) | .002 | 0.38 (0.16, 0.90) | .029 |
| ≥ $60,000 annually | Ref | Ref | Ref | Ref | ||||
| Insurance | ||||||||
| No | 0.22 (0.10, 0.50) | < .001 | 0.48 (0.17, 1.37) | 0.171 | 0.35 (0.13, 0.91) | .031 | 0.82 (0.25, 2.73) | .748 |
| Yes | Ref | Ref | Ref | Ref | ||||
| Homeless in past year | ||||||||
| No | 5.24 (2.17, 12.65) | < .001 | 1.62 (0.41, 6.44) | 0.496 | 1.86 (0.63, 5.54) | .269 | 0.83 (0.17, 4.10) | .822 |
| Yesc | Ref | Ref | Ref | Ref | ||||
| Saw a clinician in past year | ||||||||
| No | 0.28 (0.12, 0.65) | .003 | 0.26 (0.08, 0.78) | 0.016 | 0.55 (0.21, 1.47) | .230 | 1.09 (0.32, 3.70) | .886 |
| Yesd | Ref | Ref | Ref | Ref | ||||
| Place of residence | ||||||||
| Fulton County | 1.60 (0.74, 3.43) | .231 | 0.93 (0.35, 2.49) | 0.887 | 1.16 (0.65, 2.07) | .628 | 0.65 (0.30, 1.40) | .272 |
| Rest of Atlanta | Ref | Ref | Ref | Ref | ||||
| HIV risk factors (past 6 months) | ||||||||
| Male sex partners | ||||||||
| ≤ 5 partners | Ref | Ref | Ref | Ref | ||||
| ≥ 6 partners | 1.55 (0.45, 5.40) | .489 | 2.25 (0.46, 10.97) | 0.317 | 5.04 (2.46, 10.34) | < .001 | 3.86 (1.50, 9.91) | .005 |
| Unprotected sex with a casual partner | ||||||||
| No | Ref | Ref | Ref | Ref | ||||
| Yes | 0.65 (0.28, 1.49) | .311 | 0.60 (0.20, 1.78) | 0.359 | 2.85 (1.42, 5.70) | .004 | 2.00 (0.87, 4.56) | .101 |
| Sex with a HIV-positive partner | ||||||||
| No | Ref | Ref | Ref | Ref | ||||
| Yes | 1.26 (0.45, 3.42) | .670 | 1.61 (0.43, 6.01) | 0.483 | 5.51 (2.85, 10.64) | < .001 | 5.38 (2.34, 12.37) | < .001 |
| Any bacterial STI diagnosede | ||||||||
| No | Ref | Ref | Ref | Ref | ||||
| Yes | 1.54 (0.19, 12.28) | .684 | 1.68 (0.09, 30.75) | 0.728 | 3.72 (1.29, 10.74) | .016 | 2.84 (0.61, 13.36) | .185 |
| Any drug usef | ||||||||
| No | Ref | Ref | Ref | Ref | ||||
| Yes | 0.25 (0.10, 0.63) | .003 | 0.33 (0.09, 1.19) | 0.089 | 0.41 (0.12, 1.41) | .157 | 0.17(0.03, 0.87) | .034 |
Statistically significant odds ratios and p values have been bolded for ease of interpretation
Had high school education only or less
Income before taxes at end of 2017
Respondents who reported sleeping on the streets, shelter, motel or car in the past 12 months
Respondents who reported visiting a health-care facility for medical care within the previous year (primary care, urgent care, hospital, emergency room or service organization)
Any bacterial sexually transmitted diseases: syphilis, gonorrhea or chlamydia
Any illicit drug use (methamphetamines, cocaine, crack and heroin)
Criteria outlined in Pages 13&36, United States Public Health Service, Clinical Practice Guidelines for PrEP, 2017 update
Survey question “Before today, have you heard of PrEP?”
Significant independent associations were also observed between being on PrEP and age, income, insurance status, number of male sexual partners, consistency of condom use during casual sex, recent bacterial STI history and sex with a HIV-positive partner. In multivariate analysis, younger age (aOR [95% CI]: 0.39 [0.17, 0.87], p = .022), lower income (aOR [95% CI]: 0.38 [0.16, 0.90], p = .029), increased number of male sex partners (aOR [95% CI]: 5.38 [2.34, 12.37], p < .001) and history of drug use (aOR [95% CI]: 0.17; [0.03, 0.87], p = .034) were significantly associated with active PrEP use.
PrEP Interest and Reasons for Never Using PrEP Among PrEP-Naïve MSM/TWSM
Interest in initiating PrEP was expressed by one-third of the respondents who reported never using PrEP, and there were no differences in interest between Black (38%) and non-Blacks (35%) in the sample (p = .41) (Table 4). The top five reasons for never using PrEP were low perception of personal risk (37%), poor knowledge of PrEP (37%), concern about potential side effects (15%), financial costs of PrEP (13%) and no knowledge of where to get PrEP (7%). Appreciable differences were observed in the commonest reasons selected by the two racial groups. Among Blacks, poor knowledge of PrEP (45%), low perception of risk (26%), fear of side effects (15%) were the top three reasons selected while low perception of risk (52%), poor knowledge of PrEP (27%) and financials costs of PrEP (18%) were the top three reasons selected among non-Blacks.
Table 4.
Reasons for not taking PrEP among PrEP-naïve men who have sex with men (MSM) and transgender women who have sex with men (MSM/TWSM) attending Gay pride events in Atlanta, Georgia, 2018
| Total (n = 196) |
Black (n=114) |
Non-black (n = 82) |
p value | |
|---|---|---|---|---|
| n (%) | n (%) | n (%) | ||
|
| ||||
| Reasons for not taking PrEP | ||||
| I don’t know enough about PrEP | ||||
| No | 122 (63) | 62 (55) | 60 (73) | .010 |
| Yes | 73 (37) | 51 (45) | 22 (27) | |
| I am at low risk of HIV | ||||
| No | 123 (63) | 84 (74) | 39 (48) | .001 |
| Yes | 72 (37) | 29 (26) | 43 (52) | |
| Too expensive | ||||
| No | 169 (87) | 102 (90) | 67 (82) | .083 |
| Yes | 26 (13) | 11 (10) | 15 (18) | |
| I don’t know where to get PrEP | ||||
| No | 181 (93) | 104 (92) | 77 (94) | .619 |
| Yes | 14 (7) | 9 (8) | 5 (6) | |
| Afraid of the side effects | ||||
| No | 166 (85) | 96 (85) | 70 (85) | .937 |
| Yes | 29 (15) | 17 (15) | 12 (15) | |
| Afraid people will judge me | ||||
| No | 192 (98) | 111 (98) | 81 (99) | .758 |
| Yes | 3 (2) | 2 (2) | 1 (1) | |
| PrEP provider is too far from me | ||||
| No | 193 (99) | 112 (99) | 81 (99) | .819 |
| Yes | 2 (1) | 1 (1) | 1 (1) | |
| I won’t be consistent in taking it | ||||
| No | 188 (96) | 107 (95) | 81 (99) | .130 |
| Yes | 7 (4) | 6 (5) | 1 (1) | |
| Taking PrEP is a hassle | ||||
| No | 190 (97) | 110 (97) | 80 (98) | .925 |
| Yes | 5 (3) | 3 (3) | 2 (2) | |
| PrEP interest | ||||
| Interested in taking PrEP | ||||
| No | 64 (34) | 40 (37) | 24 (30) | .407 |
| Yes | 69 (37) | 41 (38) | 28 (35) | |
| Not sure | 55 (29) | 28 (26) | 27 (34) | |
Significant p values have been bolded for ease of interpretation
Discussion
Achieving a discernible reduction in HIV incidence in priority groups through PrEP will require adequate PrEP coverage at the population level (Jenness et al., 2016). However, populations united by certain key features are seldom uniform on others. Our study lends support to the observation that differing socioeconomic and cultural characteristics make access to and use of PrEP notably different even within key at-risk sub-groups of MSM and TWSM.
We found high awareness of PrEP among both Black and non-Black groups of MSM/TWSM that was commensurate with the national estimates of PrEP awareness reported by the CDC (Finlayson et al., 2019). Given the importance of awareness in increasing uptake of preventive measures (Hoots, Finlayson, Nerlander, & Paz-Bailey, 2016; Kelley et al., 2015), knowing that awareness is high generally offers a promising foundation for PrEP promotion activities among Atlanta’s MSM and TWSM. However, the lower estimates of PrEP awareness found among individuals reporting no college education, unstable housing, illicit drug use and structural challenges to health-care access indicate that more nuanced disparities in PrEP awareness still remain. Deliberate efforts to tailor PrEP messaging to reach educationally and economically disadvantaged individuals who may not have regular access to health care may help bridge this gap in PrEP awareness among these sub-groups of MSM/TWSM.
Regarding active PrEP use, we found marked racial disparities among MSM/TWSM despite high estimates of PrEP awareness. These findings are commensurate with previous studies (Eaton et al., 2017; Finlayson et al., 2019; Hoots, Finlayson, Nerlander, & Paz-Bailey, 2016; Rolle et al., 2017), but the significant associations found between active use and the underlying socioeconomic and health access characteristics again provide additional insight. Differences were observed in reported income, possession of health insurance and access to stable housing among Black and non-Black MSM/TWSM all of which were also independently associated with current PrEP use. This suggests that the lower economic ability of Black MSM/TWSM compared to non-Blacks to effectively access and afford the costs of taking PrEP (which include the cost of regular STD screenings, provider cost and medication cost) may be strong contributors to the observed racial disparity in active PrEP use.
Based on our findings, there is a strong need for existing and future efforts related to PrEP promotion among at-risk MSM/TWSM residing within a Southern HIV “hotspot” like Atlanta to focus on young, lower-income earners who experience structural barriers to adequate health-care access. This may include individuals likely to seek and access health care at local health departments or community clinics as opposed to private health-care providers (Rolle et al., 2019). Employing different approaches to PrEP promotion tailored to these sub-groups of MSM/TWSM may also be beneficial in improving awareness and active use of PrEP among at-risk MSM/TWSM. In Fulton County, Georgia, the STOPHIVATL campaign is diversifying its PrEP promotion efforts among at-risk MSM/TWSM by crafting culturally nuanced messages targeted these exact sub-groups and propagating them through locally known social influencers. Furthermore, because the top reason cited by participants in our study for not using PrEP also varied by race, FCBOH is considering PrEP messaging to Black MSM/TWSM that stresses on the personal benefits and safety of using PrEP to prevent HIV and messaging to non-Black MSM/TWSM that educates on appropriate personal risk assessment.
While surveying individuals at gay pride events offers health officials a premiere opportunity to gain insights into the sexual health of target populations, (Barrientos, Silva, Catalan, Gomez, & Longueira, 2010; Dubov, Galbo, Altice, & Fraenkel, 2018; Iniesta et al., 2018; Storholm et al., 2010), event-based recruitment has its limitations. First, this sampling method may favor selection of MSM/TWSM at higher risk of HIV assuming pride event attendees are more socially outgoing than those who choose not to attend gay pride events. While this may limit the representativeness of this sample to the entire MSM/TWSM community in Atlanta, Georgia or the US South, it yields a sample of MSM/TWSM that the health department may want the most to target prevention strategies toward. Second, HIV status and other risk behaviors used in the analysis were self-reported and were therefore subject to recall and social desirability biases, issues which may have influenced the findings of this study.
Conclusion
By collecting data during two major Atlanta-based pride festivals held in 2018, 3 months after the launch of the STOPHIVATL campaign, we were able to gather updated data on PrEP use and awareness among populations epidemiologically important to target for stemming the HIV epidemic in Atlanta. These data will serve as an important baseline from which to assess the effectiveness of what are likely to be many public health campaigns associated with EHE initiative. Furthermore, the more nuanced findings on structural challenges like lower socioeconomic status and poor access to health care that underpin the well-known racial differences in PrEP awareness and use are particularly actionable, allowing public health officials to more appropriately tailor PrEP messages, optimize communication modalities, engage providers and explore ways to defray costs for high-risk underresourced populations.
Supplementary Material
Acknowledgements
This work was assisted in part by a developmental grant from the NIH Center for AIDS Research (CFAR) at Emory University (P30AI050409). We also acknowledge all Sexual Health Promotion staff at Fulton County Board of Health, the #STOPHIVATL team, the Fulton County HIV/AIDS Advisory committee, the Georgia Department of Public Health and all Board of Health-affiliated community-based organizations for their spirited contributions toward ending the HIV epidemic in Fulton County and the City of Atlanta, Georgia.
Funding
This work was assisted in part by a developmental Grant from the NIH Center for AIDS Research (CFAR) at Emory University (P30AI050409).
Footnotes
Conflict of interest Author ATC received a developmental grant from the NIH Center for AIDS Research (CFAR) at Emory University (P30AI050409) in August 2018 for the purpose of this study. All other authors have no conflict of interest to declare.
Compliance with Ethical Standards
Ethical Approval The study protocol and survey instrument used in this study were reviewed and approved by the institutional review boards (IRB) of the Georgia Department of Public Health (Project #:180602) and Emory University.
Informed Consent Survey data collection was completely anonymous, and the requirement for written informed consent was waived by both IRBs. Verbal consent was obtained from all individual participants included in the study.
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10508-020-01711-0) contains supplementary material, which is available to authorized users.
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