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Addiction. 2012 Dec;107(12):2087-95. doi: 10.1111/j.1360-0443.2012.04027.x. Epub 2012 Oct 18.

Racial/ethnic disparities in HIV infection among people who inject drugs: an international systematic review and meta-analysis.

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The Baron Edmond de Rothschild Chemical Dependency Institute, Beth Israel Medical Center, New York, NY 10038, USA.



The Ethnic Minority Meta-Analysis (EMMA) aims to assess racial/ethnic disparities in HIV infection among people who inject drugs (PWID) across various countries. This is the first report of the data.


Standard systematic review/meta-analysis methods were utilized, including searching for, screening and coding published and unpublished reports and meta-analytical statistics. We followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement and Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines for reporting methods. Disparities were measured with the odds ratio (OR) for HIV prevalence among ethnic minority PWID compared to ethnic majority PWID; an OR >1.0 indicated higher prevalence among ethnic minorities.


Racial/ethnic disparities in HIV prevalence among PWID were examined in 131 prevalence reports, with 214 racial/ethnic minority to majority comparisons, comprising 106 715 PWID. Overall, the pooled OR indicates an increased likelihood of higher HIV prevalence among racial/ethnic minority compared to racial/ethnic majority PWID [OR = 2.09, 95% confidence interval (CI): 1.92-2.28]. Among 214 comparisons, 106 produced a statistically significant higher OR for minorities; in 102 comparisons the OR was not significantly different from 1.0; six comparisons produced a statistically significant higher OR for majority group members. Disparities were particularly large in the United States, pooled OR = 2.22 (95% CI: 2.03-2.44). There was substantial variation in ORs-I(2)  = 75.3%: interquartile range = 1.38-3.56-and an approximate Gaussian distribution of the log ORs.


Among people who inject drugs, ethnic minorities are approximately twice as likely to be HIV seropositive than ethnic majorities. The great heterogeneity and Gaussian distribution suggest multiple causal factors and a need to tailor interventions to local conditions.

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