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Racial/Ethnic Disparities in HIV infection among people who inject drugs: An international systematic review and meta-analysis

by: Don C. Des Jarlais, Heidi A. Bramson, Cherise Wong, Karla Gostnell, Javier Cepeda, Kamyar Arasteh, Holly Hagan
Addiction (2012), pp. n/a-n/a, doi:10.1111/j.1360-0443.2012.04027.x  Key: citeulike:11180160

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Abstract

Aims 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. Methods Standard systematic review/meta-analysis methods were utilized, including searching for, screening, and coding published and unpublished reports, and meta-analytic statistics. We followed the PRISMA Statement and MOOSE Guidelines for reporting methods. Disparities were measured with the odds ratio for HIV prevalence among ethnic minority PWID compared to ethnic majority PWID; an odds ratio> 1.0 indicated higher prevalence among ethnic minorities. Results 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% 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 US, pooled OR = 2.22 (95% CI 2.03 - 2.44). There was substantial variation in ORs—I squared = 75.3%: IQR = 1.38 - 3.56—and an approximate Gaussian distribution of the log ORs. Conclusions 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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