Reply to 'Evaluation of sexual networks as a cause for disparate HIV prevalence between blacks and whites: more questions than answers'.

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Understanding disparities in HIV infection between
black and white MSM in the United States
Alexandra M. Ostera, Ryan E. Wieganda, Catlainn Sioneana,
Isa J. Milesa, Peter E. Thomasa, Lehida Melendez-Moralesa,
Binh C. Lea,band Gregorio A. Milletta
Objective: We evaluated several hypotheses for disparities in HIV infection between
black and white MSM in the United States, including incarceration, partner HIV status,
circumcision, sexual networks, and duration of infectiousness.
Design: The 2008 National HIV Behavioral Surveillance System (NHBS), a cross-
sectional survey conducted in 21 US cities.
Methods: MSM were interviewed and tested for HIV infection. For MSM not previously
diagnosed with HIV infection, we used logistic regression to test associations between
newly diagnosed HIV infection and incarceration history, partner HIV status, circumci-
sion status, and sexual networks (older partners, concurrency, and partner risk beha-
viors). For HIV-infected MSM, we assessed factors related to duration of infectiousness.
Results: Among 5183 MSM not previously diagnosed with HIV infection, incarceration
history, circumcision status, and sexual networks were not independently associated
with HIV infection. Having HIV-infected partners [adjusted odds ratio (AOR)¼1.9,
95% confidence interval (CI)¼1.2–3.0] or partners of unknown status (AOR¼1.4,
CI¼1.1–1.7) were associated with HIV infection. Of these two factors, only one was
more common among black MSM – having partners of unknown HIV status. Among
previously diagnosed HIV-positive MSM, black MSM were less likely to be on anti-
retroviral therapy (ART).
Conclusion: Less knowledge of partner HIV status and lower ART use among black
MSM may partially explain differences in HIV infection between black and white MSM.
Efforts to encourage discussions about HIV status between MSM and their partners and
decrease barriers to ART provision among black MSM may decrease transmission.
? 2011 Wolters Kluwer Health | Lippincott Williams & Wilkins
AIDS 2011, 25:1103–1112
Keywords: blacks/African–Americans, HIV risk, HIV/AIDS, homosexual, MSM,
race/ethnicity, United States
Introduction
In the United States, MSM represent the largest HIV
transmission category [1], accounting for 53% of
estimated incident infections in 2006 [2]. Among
MSM, blacks are disproportionately affected by HIV
and AIDS [3–5], and HIV prevalence among black MSM
has been found to be as high as 46% in some cities [5].
A literature review by Millett et al. [6] presented
12 hypotheses for the disparity in HIV infection between
black and other MSM. These hypotheses included factors
that affected likelihood of exposure to and acquisition of
HIV infection (among HIV-negative MSM) and like-
lihood of HIV transmission (among HIV-infected MSM;
Fig. 1) [6]. Some of these hypotheses are not supported
by evidence. For example, black MSM have comparable
aDivision of HIV/AIDS Prevention, Centers for Disease Control and Prevention, andbNorthrop Grumman Inc., Atlanta, Georgia,
USA.
Correspondence to Alexandra M. Oster, MD, 1600 Clifton Rd NE, MS E-46, Atlanta, GA 30333, USA.
Tel: +1 404 639 6141; fax: +1 404 639 8640; e-mail: AOster@cdc.gov
Received: 30 December 2010; revised: 17 March 2011; accepted: 24 March 2011.
DOI:10.1097/QAD.0b013e3283471efa
ISSN 0269-9370 Q 2011 Wolters Kluwer Health | Lippincott Williams & Wilkins
1103

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or lower numbers of sex partners and prevalence of
unprotected anal intercourse [6–10]. Other hypotheses
are supported by evidence. For example, higher rates of
other sexually transmitted infections may contribute to
racial disparities in HIV by increasing both acquisition
and transmissibility of HIV [6,8]. Likewise, HIV-infected
black MSM are less likely to be aware of their HIV status;
because many persons reduce their risk behaviors after
HIV diagnosis [11], this may contribute to HIV trans-
mission among black MSM.
For several hypotheses described by Millett et al. [6], there
was insufficient or conflicting evidence. Some of these
hypotheses relate to the likelihood of being exposed to
HIV and susceptibility to acquiring HIV. For instance,
in the United States, black men are more likely to be
incarcerated [12], and HIV prevalence is higher among
inmates of prisons and jails than in the general population
[13,14], yet studies have found no association between
incarceration and HIV infection among black MSM [15].
Likewise, differences in HIV status and other character-
istics of sex partners (such as age and drug use) may reflect
differences in HIV prevalence of one’s sexual network
and, therefore, affect likelihood of exposure to HIV.
In addition, circumcision, which has been shown to
reduce HIVacquisition among heterosexual populations
in Africa [16–18], is less common among black than
white men in the United States [19].
Other hypotheses relate to the possibility of increased
HIV transmission from HIV-infected black MSM to
their partners. For instance, use of antiretroviral therapy
(ART)reducesviralloadandinfectiousness[20],yetisless
common among black than white HIV-positive MSM
[8]. Because black MSM are more likely to have partners
of the same race [7,21–23], increased duration of
infectiousness due to lower ART use could contribute
to increased HIV prevalence among this population.
The National HIV Behavioral Surveillance System
(NHBS) is the largest and most geographically diverse
surveillance system to monitor HIV risk among MSM in
the United States [24]. We used data from the second
round of NHBS among MSM (NHBS-MSM2), con-
ducted during 2008, to assess whether hypotheses
described by Millett et al. [6] related to exposure to,
acquisition of, or transmission of HIV may partially
explain racial disparities in HIV infection among black
and white MSM.
Methods
National HIV behavioral surveillance system
NHBS-MSM2 was conducted in 21 metropolitan
statistical areas (MSAs), selected based on a high number
of people living with AIDS.1MSM were recruited using
venue-based,time-space
included formative research to identify venues and times
to recruit MSM [26]; development of sampling frames of
eligiblevenues and day-time periods; random selection of
sampling[25].Activities
1104 AIDS2011, Vol 25 No 8
Fig. 1. Factors affecting ongoing HIV transmission within a population. Listed are hypotheses described in a literature review on
disparities in HIV infection among MSM [6].
1Atlanta, Georgia; Baltimore, Maryland; Boston, Massachu-
setts; Chicago, Illinois; Dallas, Texas; Denver, Colorado;
Detroit, Michigan; Houston, Texas; Los Angeles, California;
Miami, Florida; Nassau, New York; Newark, New Jersey;
New Orleans, Louisiana; New York City, New York; Phila-
delphia, Pennsylvania; San Diego, California; San Francisco,
California; San Juan, Puerto Rico; Seattle, Washington; St.
Louis, Missouri; and Washington, District of Columbia.

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venues and day-time periods; and recruitment, inter-
viewing, and testing during sampled events.
The eligibility criteria included being male; at least
18 years of age; a resident of the MSA; able to complete
the survey in English or Spanish; and able to provide
informed consent. Trained interviewers used handheld
computers to administer a standardized questionnaire.
Anonymous HIV testing was offered to all participants
regardless of self-reported HIV infection status. Blood or
oral specimens were collected for either conventional
laboratory testing or rapid testing in the field followed
by laboratory confirmation. Activities for NHBS-MSM2
were approved by the Centers for Disease Control and
Prevention Institutional Review Board (IRB) and local
IRBs for each participating MSA.
Analysis inclusion criteria
Participants were included in this analysis if they had a
completed, valid survey; reported at least one male sex
partner in the past 12 months; had a positive or negative
HIV test result, and reported being either black or white.
MSM were considered white if they indicated they were
not Hispanic and only selected ‘White’ to define their
race. MSM were considered black if they selected ‘Black
or African–American’ to define their race alone or in
combination with any other racial or ethnic category.
Data show that persons who select black and additional
races or black race and Hispanic ethnicity have HIV
prevalence and HIV risk behaviors similar to those
who identify as black/African–American only [10].
Reanalysis of our data after exclusion of participants
that selected additional races or ethnicities did not
substantially alter findings from this analysis.
Exposure and acquisition analysis
We limited our analysis of risk factors for HIVexposure
and acquisition to MSM who were not previously
diagnosed with HIV infection. Hypothesis-related pre-
dictor variables assessed were incarceration during the
past 12 months (limited to participants incarcerated for
>1 day at last incarceration); HIV status of last male
partner; age of last male partner; last male partner
probably or definitely had concurrent relationships; last
male partner known to be at increased risk (ever
imprisoned, used crack, or injected drugs); having an
exchange partner during the past 12 months (i.e., giving
something like money or drugs in exchange for sex); and
circumcision status.
We determined prevalence of these factors among
black and white MSM with newly diagnosed infection
(those who first tested positive during NHBS). Addition-
ally, to assess differences between participants with newly
diagnosed HIV infection and HIV-negative participants,
we used logistic regression [27]. A univariable logistic
regression model was fit for each independent variable to
determine the unadjusted association with the outcome.
All variables were included in a multivariable logistic
regression model to determine associations with the
outcome aftercontrolling forall othercovariates. Because
the importance of partner’s age can be expected to vary
with the respondent’s age, an interaction term for
respondent’s age and partner’s age was included. We
controlled for number of unprotected anal sex partners
and whether the participant had been recently tested for
HIV infection. Other control variables included age,
education, income, and injection drug use. To determine
whether associations were influenced by race, we assessed
for interactions between race and all hypothesis variables.
A factor was considered to potentially explain a portion
of the disparity if the factor was associated with HIV
infection, and there was an interaction indicating that the
effect of that factor was stronger for black than white
MSM; or the factor was associated with HIV infection,
and there was not an interaction, but the factor was more
prevalent among black than white MSM.
Transmission analysis
To assess duration of infectiousness, we first assessed
factors that might influence the duration of time from
HIV acquisition to diagnosis among MSM with newly
diagnosed HIV infection. The variables evaluated were
health insurance; seeing a healthcare provider during the
past 12 months; being offered an HIV test by a healthcare
provider during the past 12 months; being tested for HIV
during the past 12 months; the number of tests received
during the past 2 years; and receiving all test results. Next,
to assess duration of infectiousness among previously
diagnosed HIV-positive MSM, we assessed factors that
might influence time from HIV diagnosis to viral
suppression on ART, including health insurance; seeing
a healthcare provider for HIV infection within 3 months
of diagnosis (necessary for timely initiation of ART);
seeing a healthcare provider for HIV during the past
6 months (necessary for continued provision of ART);
and being on ART. We also tested associations between
various factors and current ARTuse using a multivariable
model. After fitting a univariable model for current ART
use and race, we explored the changes in this effect after
additional covariates were added to the model.
Data analysis
For bivariate analyses, we used Pearson x2to test for
differences between groups. Responses to some covari-
ates were missing, and more black than white participants
had missing responses (8.5 vs. 5.7%, P<0.0001). As
a result, for all multivariate logistic regression analyses, we
used a multiple imputation approach to account for the
uncertainty in these missing responses [28]. Ten imputa-
tions were analyzed. Adaptive rounding was used for
dichotomous and categorical variables [28]. Model fit for
each imputation was evaluated with the Hosmer–
Lemeshow goodness-of-fit test and diagnostic statistics
[27]. Additionally, we explored accounting for clustering
at the venue level. Differences between the logistic
Disparities among black and white MSM Oster et al.1105

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regression model and one with venue-specific random
effects were trivial. Therefore, we present the former.
Analyses were completed using the LOGISTIC and
MIANALYZE procedures in SAS (version 9.2; SAS
Institute Inc., Cary, North Carolina, USA). All tests and
confidence intervals (CIs) are two-sided and based on the
5% level of significance.
Results
A total of 28468 persons were approached for
participation at 626 venues; 12325 (43%) persons were
screened for participation, 10493 (84%) of whom
completed the survey with valid responses. Of these,
9355 (89%) consented to HIV testing and had a valid
test result (59 of those excluded reported that they were
HIV-positive but tested negative), 8166 (87%) of whom
reported male–male sex during the past 12 months.
Among this group, 5855 were blackor white MSM; 4675
(80%) were HIV-negative, 508 (9%) had newly diagnosed
HIV infection, and 672 (11%) had previously diagnosed
HIV infection.
Median age was 36 years for white MSM and 28 years for
black MSM. Black MSM had lower levels of education
and income (Table 1). Larger proportions of black MSM
identified as bisexual, and fewer reported injection drug
use. Similar percentages of black and white MSM (11 vs.
12%) reported that they were HIV-positive at the time of
interview, but substantially more black than white MSM
had a positive NHBS test result (27 vs. 16%).
Exposure and acquisition analysis
Table 2 presents characteristics of black and white MSM
whowere newly diagnosed with HIV infection. Notably,
fewer black MSM reported having an HIV-positive last
male partner or being circumcised, whereas more black
MSM reported that they did not know the HIV status of
their last partner.
Multivariable analysis demonstrated that the control
variables of race, age, education, income, number of
unprotected anal sex partners, and not having an HIV test
during the past year were associated with newly
diagnosed HIV infection (Table 3). Having a last partner
who was HIV-positive or of unknown HIV status was
associated with HIV infection. Interactions between race
and hypothesis variables were not statistically significant.
Transmission analysis
Factors that might influence duration of time from HIV
acquisition to HIV diagnosis were similar between black
and white MSM newly diagnosed with HIV infection
(Table 4). However, black MSM were significantly more
likely to have been offered an HIV test by a provider.
Among previously diagnosed HIV-positive MSM,
significantly fewer black than white MSM reported
having health insurance, being seen by a healthcare
provider for HIV infection within 3 months of diagnosis,
or being on ART at the time of interview.
We performed additional modeling to understand
possible reasons for differences in ART use. Univariate
logistic regression demonstrated that black MSM were
less likely than white MSM to be on ART [adjusted
odds ratio (AOR)¼0.5, 95% CI¼0.4–0.8]. Adding
education, health insurance, and whether seen by a
provider for HIV care to the model had little effect on
the association between race and ART (AOR¼0.6,
CI¼0.4–0.8). We did not have CD4 cell count or other
clinical measures, but used time since diagnosis as a
surrogate for disease progression to the point at which
ART would be clinically indicated. Median time since
diagnosis was 6 years for black MSM and 10 years for
white MSM (Wilcoxon P<0.0001). Adding time since
HIV diagnosis to the model attenuated the association
between race and ART use (AOR¼0.7, CI¼0.5–
0.9995).
Discussion
We assessed whether hypotheses related to exposure to,
acquisition of, or transmission of HIV may partially
explain racial disparities in HIV infection among black
and white MSM. In general, we confirmed the findings
of a number of smaller or more geographically limited
studies. We found that incarceration, several character-
istics of sex partners (partner’s age, concurrency, and risk
behaviors), and circumcision status were not indepen-
dently associated with HIV infection, suggesting that
these factors do not explain the disparity in HIV infection
between black and white MSM. We also found that
reporting that one’s most recent partner was of unknown
HIV status was associated with HIV infection, and this
characteristic was more common among black MSM.
Finally, we found that black MSM who had been
previously diagnosed with HIV infection were less likely
to be on ART. This, in combination with the high
proportion unaware of their HIV infection, likely
contributes to increased duration of infectiousness and
ongoing HIV transmission among black MSM.
The prevalence of infection within one’s sexual network
may have greater influence than individual risk behavior
on the risk of HIV acquisition among MSM [29]. We
found that having a partner known to be HIV-infected or
a partner of unknown status was independent risk factor
for HIV infection. Black MSM with newly diagnosed
infection were less likely than white MSM to report
having a partner known to be HIV-infected; a previous
meta-analysis found no difference [8]. However, this is
limited by the extent to which MSM know their HIV
1106AIDS2011, Vol 25 No 8

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status and openly and honestly communicate with their
partners about HIV status. We found, as have others, that
black MSM are less likely to know the HIV status of their
partners [30]. Moreover, in our analysis, 59% of HIV-
infected black MSM and 25% of HIV-infected white
MSM were unaware of their HIV status, suggesting that
our estimate of the proportion of MSM with HIV-
positive partners is artificially low, particularly for
black MSM.
BlackMSMaremorelikely toselectpartnersof theirown
race than other MSM [7,21–23]. As a result, factors that
increasethelikelihoodthatHIV-infectedblackMSMwill
transmit HIV to their partners are likely to disproportio-
nately increase HIVacquisition among black MSM. We
assessed factors associated with duration of infectiousness,
including the time from HIV infection to diagnosis and
the time from HIV diagnosis toviral suppression on ART.
Black MSM are less likely to be aware of their HIV
infection than white MSM [4,5,31], and this was the case
in ourdata as well. Similar proportions of black and white
MSM with newly diagnosed HIV infection had health
insurance, had seen a provider, and had received HIV
testing. This suggests that universal recommendations for
HIV testing among MSM may not adequately address the
disparities in HIVincidenceamong different populations.
Recommending more frequent HIV testing for popu-
lations with high HIV incidence, including black MSM,
may reduce the time from HIV infection to diagnosis
for HIV-infected black MSM and, therefore, reduce the
duration of infectiousness.
Several measures suggested an increased duration of
infectiousness after HIV diagnosis for black MSM. Black
Disparities among black and white MSM Oster et al.1107
Table 1. Selected characteristics of black and white MSM, National HIV Behavioral Surveillance System, 2008.
Black (n¼2270) n (%)White (n¼3585) n (%)Total (n¼5855) n (%)
Age (years)
18–24
25–29
30–39
40–49
>50
Education
?High school diploma or equivalent
Some college
College graduate
Some graduate school or more
Annual household income
<$20000
$20000–39999
$40000–74999
>$75000
Sexual identity
Homosexual or gay
Bisexual
Heterosexual or straight
Injection drug use, past 12 months
No
Yes
Reported serostatus
Negative
Positive
Unknowna
HIV test results
Positive – previously diagnosed infection
Positive – newly diagnosed infection
Negative
Recruitment venue
Bar
Dance club
Social organization
Restaurant or cafe
Sex establishment or environment
Street location
Retail business
Gay pride or similar event
Fitness club or gym
Park or beach
Other
Total
842 (37)
702 (31)
487 (21)
201 (9)
38 (2)
503 (14)
1087 (30)
1045 (29)
642 (18)
308 (9)
1345 (23)
1789 (31)
1532 (26)
843 (14)
346 (6)
1039 (46)
802 (35)
318 (14)
111 (5)
674 (19)
1126 (31)
1174 (33)
611 (17)
1713 (29)
1928 (33)
1492 (25)
722 (12)
984 (43)
636 (28)
419 (18)
180 (8)
663 (18)
781 (22)
1042 (29)
1067 (30)
1647 (28)
1417 (24)
1461 (25)
1247 (21)
1573 (69)
647 (29)
45 (2)
3145 (88)
416 (12)
23 (1)
4718 (81)
1063 (18)
68 (1)
2256 (99)
14 (1)
3460 (97)
124 (3)
5716 (98)
138 (2)
1648 (73)
254 (11)
292 (13)
2822 (79)
418 (12)
280 (8)
4470 (76)
672 (11)
572 (10)
254 (11)
365 (16)
1651 (73)
418 (12)
143 (4)
3024 (84)
672 (11)
508 (9)
4675 (80)
877 (39)
574 (25)
253 (11)
77 (3)
167 (7)
83 (4)
32 (1)
51 (2)
29 (1)
49 (2)
78 (3)
2270 (100)
1939 (54)
563 (16)
274 (8)
212 (6)
157 (4)
114 (3)
99 (3)
65 (2)
74 (2)
48 (1)
40 (1)
3585 (100)
2816 (48)
1137 (19)
527 (9)
289 (5)
324 (6)
197 (3)
131 (2)
116 (2)
103 (2)
97 (2)
118 (2)
5855 (100)
aIncludes never tested, never received results, indeterminate, do not know.

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MSM previously diagnosed with HIV infection were
significantly less likely to have seen a provider for
HIV care within 3 months of their HIV diagnosis, which
suggests that they may be less likely to initiate ART in a
timely manner; they were also substantially less likely
to be on ART than white MSM. Logistic regression
analysis demonstrated that the difference in ART use is
likely partly explained by time since HIV diagnosis,
suggesting that black MSM in our sample, who were
more recently infected, may not yet have progressed
to stages of infection requiring ART. Nonetheless,
regardless of the reason for lower prevalence of ART,
this difference may be partially responsible for the
disparity in ongoing HIV transmission between black and
whiteMSM,asARThasbeenshowntoreduceviralload,
and reduced viral load is associated with markedly
diminished risk of transmission to one’s partners [20].
Observational data suggest that expanded HIV treatment
and resultant decreases in community viral load may lead
to decreased HIV incidence at the population level [32].
If these findings prove to be robust, expanded HIV
treatment may help to reduce HIV acquisition among
black MSM.
This analysis had several limitations. First, because of the
sensitive nature of HIV status, some participants who had
previously been diagnosed with HIV infection may not
have reported their positive HIV status, resulting in our
analysis considering them newly diagnosed when they
were not. Moreover, all of our survey data were self-
reported. This may have been particularly important
with respect to partner’s characteristics, and our analysis
may, therefore, underestimate the extent towhich certain
partner’s characteristics were present. Additionally,
because the NHBS-MSM2 questionnaire did not collect
partner’srace/ethnicity, wewerenotable toassesstherole
that partner race/ethnicity may play in racial disparities in
HIV infection. Finally, participants were recruited at
venuesin 21 US citieswith high AIDS prevalence and are
not representative of all MSM.
Strengths of this analysis include the size and geographic
diversity of the sample and the use of venue-based, time-
space sampling for recruitment. The breadth of the
NHBS questionnaire allowed us to present data on a
widevarietyof variables related to HIV infection, and the
large sample size allowed us to investigate the correlation
1108 AIDS2011, Vol 25 No 8
Table 2. Characteristics of newly diagnosed HIV-positive MSM related to exposure to or acquisition of HIV, by hypothesis, National HIV
Behavioral Surveillance System, 2008.
Black (n¼365) n (%)White (n¼143) n (%)Total (n¼508) nP
Incarceration history
Incarcerated >1 day, past 12 months
No
Yes
Partner HIV status
Last male partner
Negative
Positive
Unknown
Sexual networks
Last male partner ?2 years older
Among MSM aged 18–24 years
No
Yes
Among MSM aged 25–29 years
No
Yes
Among MSM aged 30þ years
No
Yes
Last partner had concurrent relationshipsa
Definitely or probably no
Definitely or probably yes
Do not know
Last male partner known to be at increased riskb
No
Yes
Had any exchange partners, past 12 months
No
Yes
Circumcision status
Circumcised
No
Yes
0.08
320 (88)
45 (12)
133 (93)
10 (7)
453
55
0.01
154 (42)
18 (5)
193 (53)
69 (48)
15 (10)
58 (41)
223
33
251
0.12
45 (48)
49 (52)
5 (28)
13 (72)
50
62
0.72
71 (50)
70 (50)
23 (53)
20 (47)
94
90
0.75
99 (76)
31 (24)
64 (78)
18 (22)
163
49
0.07
119 (35)
212 (62)
11 (3)
60 (45)
67 (50)
6 (5)
179
279
17
0.70
277 (76)
88 (24)
111 (78)
32 (22)
388
120
0.48
324 (89)
41 (11)
130 (91)
13 (9)
454
54
0.003
89 (24)
276 (76)
18 (13)
125 (87)
107
401
aThis question not asked if most recent partner was an exchange partner.
bLast partner known to ever inject drugs, use crack, or be incarcerated.

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Disparities among black and white MSM Oster et al.1109
Table 3. Covariates of newly diagnosed HIV infection among black and white MSM, National HIV Behavioral Surveillance System, 2008.
HIV-negative
no. (%)
Newly diagnosed
HIV-positive no. (%)UOR (95% CI) AORa(95% CI)
Control variables
Race
White
Black
Age (years)
18–24
25–29
30–39
40–49
?50
Education
?High school diploma or equivalent
Some college
College graduate
Some graduate school or more
Annual household income
<$20000
$20000–39999
$40000–74999
?$75000
Injection drug use, past 12 months
No
Yes
Number of unprotected anal sex partners
per increase of one unprotected anal sex partner
Tested for HIV infection, past 12 months
No
Yes
Hypothesis variables
Incarceration history
Incarcerated, past 12 months
No
Yes
Partner HIV status
Status of last male partner
Negative
Positive
Unknown
Sexual networks
Last partner ?2 years older
No
Yes
Last partner ?2 years older, by respondent age group
18–24 years
No
Yes
25–29 years
No
Yes
?30 years
No
Yes
Last partner had concurrent relationships
Definitely/probably no
Definitely/probably yes
Do not know
Last partner known to be at increased riskb
No
Yes
Exchange partners, past 12 months
No
Yes
Circumcision status
Circumcised
No
Yes
3024 (95)
1651 (82)
143 (5)
365 (18)
Ref Ref
4.7 (3.8–5.7)3.3 (2.6–4.2)
1176 (91)
865 (89)
1212 (89)
913 (89)
509 (94)
112 (9)
104 (11)
146 (11)
115 (11)
31 (6)
1.6 (1.0–2.4)
2.0 (1.3–3.0)
2.0 (1.3–3.0)
2.1 (1.4–3.1)
Ref
0.6 (0.4–1.02)
1.1 (0.6–1.8)
1.5 (0.97–2.4)
1.6 (1.03–2.5)
Ref
1268 (84)
1498 (90)
1277 (94)
632 (97)
235 (16)
172 (10)
79 (6)
22 (3)
Ref Ref
0.6 (0.5–0.8)
0.3 (0.3–0.4)
0.2 (0.1–0.3)
0.97 (0.8–1.2)
0.7 (0.5–1.03)
0.4 (0.3–0.7)
1176 (84)
1136 (90)
1223 (93)
1070 (95)
232 (16)
125 (10)
88 (7)
55 (5)
Ref Ref
0.6 (0.4–0.7)
0.4 (0.3–0.5)
0.3 (0.2–0.4)
0.8 (0.6–0.98)
0.6 (0.5–0.9)
0.7 (0.5–0.97)
4584 (90)
90 (88)
496 (10)
12 (12)
Ref Ref
1.2 (0.7–2.3)
Ref
1.03 (1.02–1.04)
1.1 (0.5–2.2)
Ref
1.02 (1.004–1.03)––
1678 (86)
2966 (93)
269 (14)
233 (7)
RefRef
0.5 (0.4–0.6) 0.5 (0.4–0.7)
4388 (91)
285 (84)
453 (9)
55 (16)
Ref Ref
1.9 (1.4–2.5)0.8 (0.6–1.2)
2838 (93)
207 (86)
1618 (87)
223 (7)
33 (14)
251 (13)
RefRef
2.0 (1.4–3.0)
2.0 (1.6–2.4)
1.9 (1.2–3.0)
1.4 (1.1–1.7)
3070 (91)
1571 (89)
307 (9)
201 (11)
RefRef
1.3 (1.1–1.5) 1.3 (0.99–1.8)
541 (92)
634 (91)
50 (8)
62 (9)
RefRef
1.1 (0.7–1.6)1.2 (0.8–1.9)
506 (91)
347 (86)
49 (9)
55 (14)
RefRef
1.6 (1.1–2.5)1.5 (0.8–1.8)
2023 (91)
590 (88)
208 (9)
84 (12)
Ref Ref
1.4 (1.1–1.8)1.0 (0.7–1.4)
2062 (92)
2181 (89)
247 (94)
179 (8)
279 (11)
17 (6)
RefRef
1.5 (1.2–1.8)
0.8 (0.5–1.3)
1.1 (0.9–1.4)
0.7 (0.4–1.2)
4003 (91)
663 (85)
388 (9)
120 (15)
RefRef
1.9 (1.5–2.3)1.2 (0.96–1.6)
4418 (91)
256 (83)
454 (9)
54 (17)
Ref Ref
2.1 (1.5–2.8)0.9 (0.6–1.4)
804 (88)
3869 (91)
107 (12)
401 (9)
RefRef
0.8 (0.6–0.98) 1.2 (0.9–1.5)
AOR, adjusted odds ratio; CI, confidence interval; UOR, unadjusted odds ratio.
aAdjusted for all variables in this table as well as site.
bLast partner known to ever inject drugs, use crack, or be incarcerated.

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1110AIDS 2011, Vol 25 No 8
Table 4. Factors affecting time from HIV acquisition to antiretroviral therapy among black and white MSM, National HIV Behavioral Surveillance System, 2008.
Newly diagnosed HIV-positive
Previously diagnosed HIV-positive
Black
(n¼365)
n (%)
White
(n¼143)
n (%)
Total
(n¼508)
n (%)
P
Black
(n¼254)
n (%)
White
(n¼418)
n (%)
Total
(n¼672)
n (%)
P
Duration of infectiousness
Factors affecting time from HIV acquisition to diagnosis
Health insurance
0.10
None
156 (43)
63 (44)
219
Private only
115 (32)
57 (40)
172
Public only
84 (23)
20 (14)
104
Other
9 (2)
3 (2)
12
Seen by healthcare provider in past 12 months
0.73
No
94 (26)
39 (27)
133
Yes
271 (74)
104 (73)
375
Offered HIV test
<0.0001
No
117 (43)
71 (68)
188
Yes
154 (57)
33 (32)
187
Tested for HIV infection, past 12 months
0.23
No
189 (52)
80 (56)
269
Yes
175 (48)
58 (41)
233
How many times tested in past 2 years
0.52
0
127 (35)
58 (41)
185
1
74 (20)
22 (15)
96
2
69 (19)
23 (16)
92
3 or 4
62 (17)
26 (18)
88
5 or more
30 (8)
9 (6)
39
Received all results, past 2 yearsz
0.66
No
34 (14)
10 (13)
44
Yes
201 (86)
70 (88)
271
Factors affecting time from HIV diagnosis to viral suppression
Health insurance
0.02
None
71 (28)
95 (23)
166
Private only
83 (33)
184 (44)
267
Public only
90 (35)
118 (28)
208
Other
10 (4)
21 (5)
31
Seen by a healthcare provider for HIV infection within 3 months of diagnosis
0.01
No
76 (30)
90 (22)
166
Yes
174 (69)
325 (78)
499
Seen by a healthcare provider for HIV infection within past 6 months
0.13
No
36 (14)
44 (11)
80
Yes
211 (83)
370 (89)
581
Currently on antiretroviral therapy
0.0003
No
108 (43)
121 (29)
229
Yes
145 (57)
296 (71)
441

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betweenthesefactors and newlydiagnosedHIVinfection
while controlling for possible confounders.
In summary, our analysis demonstrated that partner HIV
status and duration of infectiousness may partially explain
the disparity in HIV infection between black and white
MSM. Efforts to increase the proportion of HIV-infected
black MSM who are aware of their infection and
encourage open and honest discussions about HIV status
between MSM and their partners may decrease HIV
transmission among black MSM. Additional studies are
neededto determine reasons for the disparity in receipt of
ART between black and white MSM and to identify and
address barriers to provision of, acceptance of, and
adherence to ART. Finally, although they were con-
sidered control variables for the purposes of this analysis,
differences between black and white MSM with respect
to education and income, which are associated with HIV
infection, are important in their own right. Evaluation of
additional hypotheses for the disparity in HIV infection
between black and white MSM, including socioeco-
nomic and cultural factors, is needed [33].
Acknowledgement
The authors would like to thank all of the NHBS-MSM2
participants. They would also like to acknowledge Amy
Lansky, Damian Denson, and Elizabeth DiNenno for
their work on the early analysis and all members of the
project sites participating in the National HIV Behavioral
Surveillance System.
A.M.O., G.A.M., R.E.W., C.S., I.J.M., P.E.T., and
L.M-M. designed the analysis. R.E.W., B.C.L., and
A.M.O. analyzed the data. A.M.O., C.S., I.J.M., and
R.E.W. drafted the manuscript. All authors critically
revised the manuscript.
The National HIV Behavioral Surveillance System is
funded by the Centers for Disease Control and
Prevention.
The findings and conclusions in this report are those of
the authors and do not necessarily represent the official
position of the Centers for Disease Control and
Prevention.
Previous presentations of these data were presented at
the International AIDS Conference, Vienna, Austria, 21
July 2010.
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