Abstract
In 2017, Florida ranked 2nd nationally in prevalence and incidence rates of HIV infections in the United States. Due to the high burden of HIV and low viral suppression in Florida, it is of increased importance to study methods of HIV prevention such as preexposure prophylaxis(PrEP) in this state. Our study aimed to examine correlates of PrEP awareness among PLWH in Florida and describe patterns of PrEP awareness/information sources. Using data collected from the Florida Cohort study between 2014−−2018, 530 PLWH answered items that were hypothesized to be correlated with PrEP awareness. Of our sample, 53.8% were aware of PrEP. Urban location of recruitment, sexual partner’s use of PrEP, use of viral suppression as an HIV prevention strategy, and engagement in transactional sex were all significantly associated with higher odds of PrEP awareness. Care providers and HIV/AIDS support groups were the most frequently listed sources of PrEP awareness, sources of future PrEP information, and most trusted sources for PrEP information. Findings from this study could inform future interventions that aim to increase PrEP awareness among PLWH to increase PrEP awareness and uptake among their HIV-negative social and sexual networks.
Keywords: Preexposure Prophylaxis, Awareness, HIV
Introduction
PrEP is part of the national HIV prevention strategy (Executive Office of the President & Office of National AIDS Policy, 2015), but PrEP uptake is low, especially in the South (Siegler et al., 2018). We need to identify new strategies to raise awareness and utilization of PrEP among those at risk for HIV. PLWH could be an important source of information for HIV-negative persons in their social and sexual networks. Two previous studies suggest low awareness of PrEP among PLWH (15.3—33.5%), but high willingness to recommend PrEP upon learning about it (88.8%−−90.7%)(Farthing et al., 2019; Jayakumaran, Aaron, Gracely, Schriver, & Szep, 2016); however, these findings were from single clinic samples.
The aims of this analysis were to identify factors associated with PrEP awareness and to describe sources of PrEP information among a statewide sample of PLWH in Florida. Based on previous findings, we used a socioecologial framework to model levels that may be associated with PrEP awareness including: community factors(urban/rural, primary care provider) (Dolezal et al., 2015; Strauss et al., 2017; Khanna et al., 2016), interpersonal factors(sexual behavior) (Garnett et al., 2018.; Strauss et al., 2017; Eaton, Driffin, Bauermeister, Smith, & Conway-Washington, 2015; Walters, Reilly, Neaigus, & Braunstein, 2017), and individual factors(sociodemographic, health history) (Garnett et al., 2018.; Misra & Udeagu, 2017; Krakower et al., 2012). Given the lack of data on attitudes towards PrEP among PLWH, the results may be vital in shaping future interventions targeting the PrEP attitudes among PLWH to increase PrEP uptake among their HIV-negative social and sexual networks.
Methods
We conducted a secondary data analysis using data collected by the Florida Cohort Study, which enrolled 932 PLWH from 9 public health clinics and settings throughout the state of Florida from 2014—2018 (Ibanez et al., [under review]). After providing informed consent, 569 participants completed both baseline and at a 6-month follow-up surveys.
Measures
The surveys used for this study can be found online at www.sharc-research.org. All variables were self-reported by participants, except for study site location and year of survey completion.
PrEP Awareness Measure
PrEP awareness was assessed by asking participants, “Prior to this survey, had you heard of PrEP?” Among those aware of PrEP, we also asked where they first heard about PrEP, what source they would most likely use to find further information about PrEP, which sources they would trust most for information about PrEP, and about their likelihood of suggesting PrEP to someone they know.
Individual Factors
Individual items included: age, sex, race/ethnicity, sexual orientation, education, marital status, HIV prevention strategy(condoms, viral suppression), and sexually transmitted infection(STI) history.
Interpersonal Factors
Interpersonal items included: recent transactional sex, number of recent male anal/vaginal sex partners, number of recent female anal/vaginal sex partners, partner PrEP use, and use of mobile applications(‘apps’) to find sexual partners, and HIV-related stigma.
Community Factors
Community factors included study site location rurality and having a primary care provider in the past 12 months. Study site rurality was determined per the 2010 U.S. Census Bureau’s classification (USCB, 2010).
Analysis
Data were analyzed using SAS(v9.4; SAS Institute Inc., Cary, NC). After excluding 22 persons who did not answer the PrEP awareness item, 11 who identified as transgender/gender non-conforming, and 6 with >50% of predictor variables missing, the final sample include 530 PLWH. For variables with ≥4% missingness, a ‘missing’ categorical level was created. Statistical significance for bivariate comparisons were assessed using Chi-Square and Fisher’s exact test as appropriate. Variables that were significant at p<0.10 were included in a multivariable model. Goodness-of-fit was determined using the Hosmer and Lemeshow test. Statistical significance was set at α=0.05.
Results
More than half (53.8%) of the sample were aware of PrEP prior to taking the survey. PrEP awareness was significantly more common in persons who were male (χ2=4.79,p=0.029), Hispanic (Fisher’s exact test, p=0.050), homosexual (χ2=16.57,p<0.001), >high school/GED educated (χ2=9.11,p=0.011), recruited at an urban study site (χ2=9.30,p=0.002), using partner PrEP use as an HIV prevention strategy (Fisher’s exact test, p<0.001), using viral suppression as an HIV prevention strategy (χ2=18.82,p<0.001), engaging in transactional sex (χ2=5.21,p=0.022), using mobile ‘apps’ to find sex partners (χ2=19.56,p<0.001), and previously diagnosed with an STI (χ2=8.78,p=0.032) in bivariate analyses (Table 1).
Table 1.
Demographics of 530 PLHIV who completed the Florida Cohort Follow-up
Total Sample (n=530) | Not aware of PrEP (n=245) | Aware of PrEP (n=285) | Χ2 | p-value | |
---|---|---|---|---|---|
n (%) | n (%) | ||||
Age group | 3.74 | 0.291 | |||
18–34 years old | 67 (12.6) | 24 (9.8) | 43 (15.1) | ||
35–44 years old | 89 (16.8) | 40 (16.3) | 49 (17.2) | ||
45–54 years old | 213 (40.2) | 102 (41.6) | 112 (39.0) | ||
≥55 years old | 161 (30.4) | 79 (32.2) | 82 (28.8) | ||
Biological sex | 4.79 | 0.029 | |||
Male | 325 (61.3) | 138 (56.3) | 187 (65.6) | ||
Female | 205 (38.7) | 107(43.7) | 98 (34.4) | ||
Race/Ethnicity | --a | 0.050 | |||
White, non-Hispanic | 96 (18.1) | 40 (16.3) | 56 (19.7) | ||
Hispanic | 109 (20.6) | 45 (18.4) | 64 (22.5) | ||
Black, non-Hispanic | 308 (58.1) | 156 (63.7) | 152 (53.3) | ||
Other | 17 (3.2) | 4 (1.6) | 13 (4.6) | ||
Sexual orientation | 16.57 | <0.001 | |||
Heterosexual | 295 (55.6) | 158 (64.5) | 137 (48.1) | ||
Homosexual | 165 (31.1) | 56 (22.9) | 109 (38.3) | ||
Bisexual | 44 (8.3) | 19 (7.8) | 25 (8.8) | ||
Missing | 26 (4.9) | 12 (4.9) | 14 (4.9) | ||
Education | 9.11 | 0.011 | |||
<High school | 180 (34.1) | 98 (40.0) | 82 (29.0) | ||
High school/GED | 162 (30.7) | 75 (30.6) | 87 (30.7) | ||
>High school/GED | 186 (35.2) | 72 (29.4) | 114 (40.3) | ||
Marital status | 0.04 | 0.848 | |||
Married | 101 (19.1) | 46 (18.8) | 55 (19.4) | ||
Single/divorced/widowed | 427 (80.9) | 199 (81.2) | 228 (80.6) | ||
Study site | 9.30 | 0.002 | |||
Urban | 477 (90.0) | 210 (85.7) | 267 (93.7) | ||
Rural | 53 (10.0) | 35 (14.3) | 18 (6.3) | ||
HIV-related stigma level | 1.32 | 0.516 | |||
No stigma | 248 (48.7) | 121 (51.3) | 127 (46.5) | ||
Moderate stigma | 201 (39.5) | 90 (38.1) | 111 (40.7) | ||
High stigma | 60 (11.8) | 25 (10.6) | 35 (12.8) | ||
Number of male anal/vaginal sex partners | 4.68 | 0.097 | |||
0 | 336 (63.4) | 167 (68.2) | 169 (59.3) | ||
1 | 123 (23.2) | 51 (20.8) | 72 (25.3) | ||
2+ | 71 (13.4) | 27 (11.0) | 44 (15.4) | ||
Number of female anal/vaginal sex partners | 0.49 | 0.782 | |||
0 | 450 (84.9) | 210 (85.7) | 240 (84.2) | ||
1 | 46 (8.7) | 19 (7.8) | 27 (9.5) | ||
2+ | 34 (6.4) | 16 (6.5) | 18 (6.3) | ||
Partner use of PrEP as an HIV prevention strategy | --a | <0.001 | |||
No | 498 (94.0) | 243 (99.2) | 255 (89.5) | ||
Yes | 32 (6.0) | 2 (0.8) | 30 (10.5) | ||
Use of condoms as an HIV prevention strategy | 0.08 | 0.784 | |||
No | 263 (49.6) | 120 (49.0) | 143 (50.2) | ||
Yes | 267 (50.4) | 125 (51.0) | 150 (49.8) | ||
Use of viral suppression as an HIV prevention strategy | 18.82 | <0.001 | |||
No | 333 (62.8) | 178 (72.7) | 155 (54.4) | ||
Yes | 197 (37.2) | 67 (27.3) | 130 (45.6) | ||
Engaged in transactional sex | 5.21 | 0.022 | |||
No | 505 (95.3) | 239 (97.5) | 266 (93.3) | ||
Yes | 25 (4.7) | 6 (2.5) | 19 (6.7) | ||
Mobile ‘app’ use for sex | 19.56 | <0.001 | |||
No | 421 (81.3) | 213 (89.5) | 208 (74.3) | ||
Yes | 97 (18.7) | 25 (10.5) | 72 (25.7) | ||
Primary care provider (PCP) | 5.31 | 0.070 | |||
No PCP | 88 (17.1) | 42 (17.4) | 46 (17.0) | ||
PCP different than HIV care provider | 142 (27.7) | 78 (32.2) | 64 (23.6) | ||
PCP same as HIV care provider | 283 (55.2) | 122 (50.4) | 161 (59.4) | ||
STI diagnosis | 8.78 | 0.032 | |||
Never | 214 (40.4) | 110 (44.9) | 104 (36.5) | ||
STI in the past year | 69 (13.0) | 23 (9.4) | 46 (16.1) | ||
STI more than a year ago | 221 (41.7) | 97 (39.6) | 124 (46.5) | ||
Missing | 26 (4.9) | 15 (6.1) | 11 (3.9) | ||
Year survey completed | 5.09 | 0.165 | |||
2015 | 186 (35.1) | 97 (39.6) | 89 (31.2) | ||
2016 | 176 (33.2) | 71 (29.0) | 105 (36.8) | ||
2017 | 135 (25.5) | 62 (25.3) | 73 (25.6) | ||
2018 | 33 (6.2) | 15 (6.1) | 18 (6.3) |
Bolded values are p<0.05
P-value was generated using Fisher’s exact test
After listwise deletion, 484 cases were included in the final model. The adjusted model found that engagement in transactional sex (AOR[CI]: 3.41[1.12, 10.33], p=0.030), use of viral suppression as an HIV prevention strategy (AOR[CI]: 1.63[1.06, 2.52], p=0.027), and partner’s PrEP use as an HIV prevention strategy (AOR[CI]: 7.63[1.69, 34.42], p=0.008) had significantly greater odds of PrEP awareness. Additionally, those recruited from a rural study site (AOR[CI]: 0.44[0.22, 0.88], p=0.020) had significantly lower odds of PrEP awareness (Table 2). Goodness-of-fit was found to be sufficient(Hosmer and Lemeshow test, p=0.191).
Table 2.
Adjusted logistic regression models of correlates to PrEP awareness among PLHIV in Florida
Adjusted OR | 95% C.I. | p-value | |
---|---|---|---|
Biological sex | |||
Male | -- | -- | -- |
Female | 1.10 | (0.67, 1.82) | 0.698 |
Race/Ethnicity | |||
White, non-Hispanic | -- | -- | -- |
Hispanic | 1.02 | (0.53, 1.97) | 0.956 |
Black, non-Hispanic | 0.95 | (0.55, 1.64) | 0.855 |
Other | 2.08 | (0.49, 8.82) | 0.322 |
Sexual orientation | |||
Heterosexual | -- | -- | -- |
Homosexual | 1.55 | (0.87, 2.76) | 0.141 |
Bisexual | 1.17 | (0.55, 2.50) | 0.680 |
Missing | 1.55 | (0.61, 3.95) | 0.354 |
Education | |||
<High school | -- | -- | -- |
High school/GED | 1.34 | (0.83, 2.16) | 0.237 |
>High school/GED | 1.34 | (0.81, 2.20) | 0.252 |
Study site | |||
Urban | -- | -- | -- |
Rural | 0.44 | (0.22, 0.88) | 0.020 |
Number of male anal/vaginal sex partners | |||
0 | -- | -- | -- |
1 | 0.95 | (0.57, 1.60) | 0.854 |
2+ | 0.79 | (0.40, 1.55) | 0.491 |
Partner used PrEP as an HIV prevention strategy | |||
No | -- | -- | -- |
Yes | 7.63 | (1.69, 34.42) | 0.008 |
Viral suppression as an HIV prevention strategy | |||
No | -- | -- | -- |
Yes | 1.63 | (1.06, 2.52) | 0.027 |
Engaged in transactional Sex | |||
No | -- | -- | -- |
Yes | 3.41 | (1.12, 10.33) | 0.030 |
Mobile ‘app’ use for sex | |||
No | |||
Yes | 1.73 | (0.96, 3.12) | 0.067 |
Primary care provider (PCP) | |||
No PCP | -- | -- | -- |
PCP different than HIV care provider | 0.85 | (0.47, 1.53) | 0.580 |
PCP same as HIV care provider | 1.31 | (0.77, 2.24) | 0.320 |
STI diagnosis | |||
Never | -- | -- | -- |
STI in the past year | 1.32 | (0.77, 2.59) | 0.421 |
STI more than a year ago | 1.12 | (0.73, 1.72) | 0.611 |
Missing | 1.20 | (0.48, 3.03) | 0.700 |
Bolded values are p<0.05
Among those aware of PrEP (n=285), 65.0% were ‘likely/somewhat likely’ to suggest PrEP to someone they knew, whereas 16.0% indicated they were ‘neutral’ and 19.0% said they were ‘unlikely/somewhat unlikely’ to recommend PrEP to others. A majority first heard about PrEP from their doctor (35.0%) and from HIV/AIDS support groups (28.6%). Additionally, a majority would use their doctor (61.7%) and HIV/AIDS support groups (34.1%) to find more information about PrEP. Moreover, a majority would trust information from their doctor (73.2%) and from HIV/AIDS support groups (30.3%) about PrEP (Table 3).
Table 3.
Descriptive statistics of PrEP awareness and information among 285 PLWH who were aware of PrEPa
Where did you first hear about PrEP? | What source would you most likely use to find further information about PrEP? | Which source would you trust most for information about PrEP? | |
---|---|---|---|
n (%) | n (%) | n (%) | |
The news (e.g. newspaper, TV, etc.) | 46 (17.3) | 32 (12.3) | 18 (6.9) |
HIV/AIDS support group | 76 (28.6) | 89 (34.1) | 79 (30.3) |
Spouse/main partner | 4 (1.5) | 8 (3.1) | 12 (4.6) |
Friend/family member | 22 (8.3) | 22 (8.4) | 14 (5.4) |
Public health organization | 51 (19.2) | 81 (31.0) | 71 (27.2) |
My doctor | 93 (35.0) | 161 (61.7) | 191 (73.2) |
The Internet (e.g., blogs, social media) | 39 (14.7) | 84 (32.2) | 28 (10.7) |
Other | 10 (3.8) | 4 (1.5) | 5 (1.9) |
The values presented are not reflective of the sample size but the frequencies of times that each option was mentioned.
Discussion
This study is among the first to examine correlates of PrEP awareness among PLWH. One primary finding was that the use of viral suppression and partner’s PrEP use as HIV prevention strategies had significantly greater odds of PrEP awareness. Since the landmark study HPTN-052 (Cohen, McCauley, & Gamble, 2012), treatment as prevention(TasP) was shown to be effective in preventing the transmission of HIV. Our finding may reflect the growing awareness in biomedical HIV prevention strategies among PLWH, including TasP and PrEP. Building support for the effectiveness of biomedical prevention strategies (Cohen et al., 2012; CDC, 2017; Baeten et al., 2012; Thigpen et al. 2012; UNAIDS, 2018) could increase the awareness of PrEP and TasP among PLWH.
Our study also found that between rural and urban study locations there were significant differences in PrEP awareness. Eight of the nine counties the study recruited from were urban, while Columbia County was the only county that was rural as defined by the U.S. Census Bureau (USCB, 2010). Four of our recruitment sites were the top 4 counties in Florida (Miami-Dade, Broward, Orange, and Hillsborough Counties, respectively) for new HIV infections in 2017, while Columbia County ranked 36th (FDOH, 2017). Lower burden of HIV and depressed HIV prevention resources in low prevalence areas may contribute to lower awareness of PrEP in rural areas. In the U.S., HIV infection rates are increasing in nonurban areas (Schafer et al., 2017). Previous research has found that PLWH in rural areas had lower retention in care and viral suppression than in urban areas (Nelson et al., 2018). Poorer retention in care and viral suppression among rural PLWH is concerning as it may highlight a gap in HIV prevention, as previous research has also found that people in rural areas also have barriers to sexual healthcare (Schafer et al., 2017; Hubach et al., 2017; Hallum-Montes et al., 2016), particularly in accessing PrEP (Hubach et al., 2017). Our findings support mounting calls for additional sexual health centered services developed for and targeted to rural populations.
The descriptive information among those aware of PrEP suggest that doctors and HIV/AIDS support groups are important sources of PrEP information. Previous research on correlates to PrEP uptake found that first hearing about PrEP from a care provider was associated with increased PrEP uptake (Algarin et al., 2019). Future research should examine if provider driven interventions that aim to educate PLWH about PrEP could result in increased PrEP uptake by HIV-negative people in PLWH’s social and sexual networks. Additionally high frequency of using HIV/AIDS support groups for PrEP awareness and PrEP information could imply that additional interventions that target HIV/AIDS support groups could supplement and enforce PrEP information PLWH learn from care providers.
Though 65% of those who were aware of PrEP were ‘likely/somewhat likely’ to suggest PrEP to someone they knew, around a third were ‘neutral’ or ‘somewhat unlikely/unlikely’ to suggest PrEP. Future qualitative research should examine barriers of PLWH in suggesting PrEP to someone they know.
Limitations
Due to small sample size, transgender/gender non-conforming individuals (n=11), were removed from analyses. Future studies should continue to measure PrEP awareness among this population. Additionally, our study used convenience sampling to recruit participants. Convenience sampling at majority community based organizations, clinics, and county health department settings could have made our sample more aware of PrEP as they may have exposure to materials that mention PrEP.
Conclusion
Despite the limitations, this study had important strengths. The Florida Cohort study recruited from 9 different locations that spanned the state of Florida, increasing future generalizability of findings for the state. Additionally, to the authors’ knowledge, this is the first study to examine the sources of PrEP awareness, most likely source of future PrEP information, and most trusted source for PrEP information among PLWH.
Acknowledgements
This work was supported by the NIH/NIAAA under Grant U24 AA022002. We would like to thank Katherine Huber for her contributions to the manuscript.
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