eli rosenberg

Race and Age Disparities in HIV Incidence and Prevalence Among

MSM in Atlanta, GA

Eli RosenbergPatrick Sullivan, Colleen Kelley, Travis Sanchez, Nicole Luisi, Carlos del Rio, Laura Salazar, Paula Frew, John Peterson

Center for AIDS ResearchEmory University Atlanta, GA

CROI 2014 March 4, 2014

Emory University

Center for AIDS Research

Dr. Rosenberg has no financial relationships with commercial entities to disclose.

Disclosures

• HIV prevalence among MSM is high and MSM continue to bear the burden of new infections in the US and Atlanta, GA

• Black MSM (BMSM), particularly young BMSM, continue to be overrepresented among new HIV infections

• Similar patterns for other sexually transmitted infections (STI)

• Reasons for these racial disparities remain unclear

• Prospective, racially comparative studies are needed

HIV and MSM

Study Design• Prospective HIV/STI incidence cohort study: 2009-2014

▫ Sexually active black and white MSM in Atlanta▫ Ages 18 - 39

• Recruitment▫ Venue-time-space sampling, Facebook

• Procedures▫ Testing: HIV, Chlamydia, Gonorrhea, Syphilis▫ Behavioral questionnaire

• Enrollment▫ 803 men enrolled▫ 30% HIV-positive (BMSM: 44%, WMSM: 13%)

▫ 562 HIV-negative MSM followed for 832 person-years▫ 79% retention at 24-months

Baseline

Month 3

Month 6

Month 12

Month 18

Month 24

HIV/STI testing,Questionnaire






Demographic characteristics of cohortBMSM (n=260) WMSM (n=302) P-value

Age at enrollment col % col % < .000118 – 24 years 50% 33%25 + years 50% 67%

Education < .0001High school or less 24% 11%Some college 40% 33%College degree 35% 56%

Sexual Identity < .0001Homosexual, Gay 76% 92%Bisexual 20% 6%Heterosexual, Other 4% 2%

Health insurance 54% 76% < .0001Poverty 29% 13% < .0001

STI Incidence

1.7 / 100 PY8 infections

Cum. Inc. (2-yr): 3.6%


Cum. Inc. (2-yr): 3.6%


Cum. Inc. (2-yr): 11.3%


Cum. Inc. (2-yr): 11.3%

Log-Rank P = 0.0005Log-Rank P = 0.0005P

rop

ort

ion

HIV

In

fect

ed

Log-Rank P < 0.0001Log-Rank P < 0.0001P

rop

ort

ion

HIV

In

fect

ed


Cum. Inc. (2-yr): 6.0%


Cum. Inc. (2-yr): 6.0%

1.0 / 100 PY 1 infection

Cum. Inc. (2-yr): 1.6%

1.0 / 100 PY 1 infection

Cum. Inc. (2-yr): 1.6%


Cum. Inc. (2-yr): 4.5%


Cum. Inc. (2-yr): 4.5%


Cum. Inc (2-yr): 16.6%


Cum. Inc (2-yr): 16.6%

HIV incidence

FactorIncidence/100 PY

Rate Ratio (95% CI)

Black participant 6.6 3.8 (1.7, 9.9)

White participant 1.7 ref.

Health Insurance 2.6 ref.

No health Insurance 6.3 2.4 (1.2, 5.0)

UAI 5.3 4.8 (1.5, 24)

No UAI 1.1 ref.

Older partners (≥10 y) 8.6 2.8 (1.2, 6.1)

No older partners 3.1 ref.

Black partners 8.6 4.5 (2.1, 10)

No black partners 1.9 ref.

Social determinants

Social determinants

Partner pool / network

Partner pool / network

Individual risk behaviors

Individual risk behaviors

HIV incidenceCovariateHealth InsuranceUAIOlder partners (≥10 y)Black partners

HRRace = 1

HRRace = 2.9 (1.3, 6.5) (no covariate adjustment)

Age-scaled Cox PH modelsBlack vs. White HR (95% CI):

2.6

HRRace = 3.3 (1.4, 7.5)(UAI)

HRRace = 2.6 (1.3, 6.5)(Health Ins.)

HRRace = 3.0 (1.3, 6.7)(Older partners)

HRRace = 1.6 (0.6, 4.2)(Black partners)

HRRace = 1.5 (0.6, 3.9)(Black P, Health Ins.)

Conclusions

• In Atlanta, MSM and BMSM face multiple high-incidence epidemics of HIV/STI ▫>1 in 10 YBMSM acquire HIV per year

• Individual behavioral risk factors associated with HIV incidence, but do not account for race disparity

•Partner pool/network and structural factors help to explain HIV race disparity

STI-HIV EffectPoster #1028

Thursday, P-W9

STI-HIV EffectPoster #1028

Thursday, P-W9

Sexual network factors and social determinants may

supersede individual characteristics and behaviors as

drivers of HIV disparities.

Relevance

The InvolveMENt Team:•Investigators•Recruiters•Event staff•Retention specialists•Data team

•Our participants

Eli [email protected]

Thank You!

Supported by NIH #:

eli rosenberg

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