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Bayesian Approaches to Racial Disparities in HIV Risk Estimation Among Men Who Have Sex with Men
by
Welles, Seth L.
, Goldstein, Neal D.
, Burstyn, Igor
in
African Americans - statistics & numerical data
/ Bayes Theorem
/ Ethnic Groups - statistics & numerical data
/ European Continental Ancestry Group - statistics & numerical data
/ Health Status Disparities
/ HIV Infections - epidemiology
/ Humans
/ Infectious Diseases
/ Male
/ Odds Ratio
/ Prevalence
/ Sexual and Gender Minorities - statistics & numerical data
2017
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Bayesian Approaches to Racial Disparities in HIV Risk Estimation Among Men Who Have Sex with Men
by
Welles, Seth L.
, Goldstein, Neal D.
, Burstyn, Igor
in
African Americans - statistics & numerical data
/ Bayes Theorem
/ Ethnic Groups - statistics & numerical data
/ European Continental Ancestry Group - statistics & numerical data
/ Health Status Disparities
/ HIV Infections - epidemiology
/ Humans
/ Infectious Diseases
/ Male
/ Odds Ratio
/ Prevalence
/ Sexual and Gender Minorities - statistics & numerical data
2017
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Do you wish to request the book?
Bayesian Approaches to Racial Disparities in HIV Risk Estimation Among Men Who Have Sex with Men
by
Welles, Seth L.
, Goldstein, Neal D.
, Burstyn, Igor
in
African Americans - statistics & numerical data
/ Bayes Theorem
/ Ethnic Groups - statistics & numerical data
/ European Continental Ancestry Group - statistics & numerical data
/ Health Status Disparities
/ HIV Infections - epidemiology
/ Humans
/ Infectious Diseases
/ Male
/ Odds Ratio
/ Prevalence
/ Sexual and Gender Minorities - statistics & numerical data
2017
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Bayesian Approaches to Racial Disparities in HIV Risk Estimation Among Men Who Have Sex with Men
Journal Article
Bayesian Approaches to Racial Disparities in HIV Risk Estimation Among Men Who Have Sex with Men
2017
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Overview
BACKGROUND:Men who have sex with men (MSM) continue to be overrepresented for new HIV infections compared with non-MSM. This disparity becomes even more alarming when considering racial groups. We describe the race-specific effects in HIV prevalence among MSM relative to non-MSM and explore the causes of disagreement among estimates.
METHODS:We used data from the National Epidemiologic Survey on Alcohol and Related Conditions, a nationally representative longitudinal survey conducted in the US Bayesian learning corrected for potential misclassification of MSM status and adjusted for residual confounding, hypothesized to explain the MSM racial disparity in HIV. We articulated the structure and strength of the latent confounders that would make race-specific risk gradients equivalent.
RESULTS:Compared with non-MSM, the adjusted prevalence odds ratio (POR) and 95% credible interval for black MSM having self-reported HIV infection was 5.8 (2.0, 16), while the POR for white MSM was 12 (4.2, 31). For all MSM, the POR for HIV infection was 9.3 (3.6, 23) with black men having 2.6 times the odds of prevalent infection compared with white men.
CONCLUSIONS:The observed race-specific associations in MSM are likely not due to misclassification alone, but represent a constellation of factors that differ between racial groups. We recommend specific risk factors in surveys needed to further identify the behavioral characteristics that lead to the observed differences when the estimates are stratified by race.
Publisher
Wolters Kluwer Health, Inc,Copyright Wolters Kluwer Health, Inc. All rights reserved
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