Characteristics Associated With HIV Infection Among Heterosexuals in Urban Areas With High AIDS Prevalence -- 24 Cities, United States, 2006-2007
August 12, 2011
For the first NHBS survey of heterosexuals, described in this report, a high percentage of participants with low SES and high HIV prevalence were enrolled from 24 MSAs. The overall 2.0% HIV prevalence among survey participants is 10 to 20 times the 0.1%-0.2% estimated for all non-IDU heterosexuals in the United States (CDC, unpublished data, 2011). HIV prevalence was higher among those participants with lower SES. Low SES and other adverse social conditions can increase the risk for HIV infection through sexual exploitation, marital instability, unstable sexual partnerships, poor mental health, substance abuse, and limited access to health care and preventive services.4,5 In addition, socioeconomic segregation confines low-SES persons to sexual networks with high underlying rates of HIV and other STDs, thereby further increasing their risk for HIV infection.6
Among participants in this NHBS survey, racial/ethnic disparities in HIV prevalence were not as great as those found in the overall U.S. population. Nationally, HIV prevalence among blacks (1.7%) is more than eight times that among whites (0.2%), and HIV prevalence among Hispanics (0.6%) is three times that among whites.7 The findings in this report suggest that poverty-related factors might account for some of the racial/ethnic disparities in HIV prevalence observed nationally. Compared with whites, blacks and Hispanics are approximately four times as likely to live in low-income areas such as the ones in the NHBS survey that were shown to have high HIV prevalence.8 When whites live in low-income communities and are exposed to the same socioeconomic conditions and sexual networks as blacks and Hispanics, their risk for HIV infection might be similar to that of blacks and Hispanics.
The findings in this report are subject to at least three limitations. First, because NHBS participants were recruited from 24 urban MSAs with high AIDS prevalence, participants likely are not representative of all low-income heterosexuals in the United States. Second, because the survey targeted census tracts with high rates of HIV diagnoses in addition to high rates of poverty, the former might have led to an overestimation of HIV prevalence in the 24 MSAs. Finally, because of fear of stigma, some participants who said they had not engaged in injection-drug use or male-male sex might actually have done so. Inclusion of IDUs and MSM, who are known to have high HIV prevalence, could have resulted in an overestimation of HIV prevalence. However, of the 18,377 persons who were initially eligible and completed the survey, a large proportion were excluded after acknowledging injection-drug use (14%) or male-male sex (9% of men), making it unlikely that these stigmatized behaviors were markedly underreported.
Based on the association observed between HIV prevalence and SES in the NHBS survey, HIV prevention activities targeted at heterosexuals in urban areas with high AIDS prevalence should focus on those in low-income communities. To reduce new HIV infections, the National HIV/AIDS Strategy§§ calls for intensifying HIV prevention efforts in communities where HIV is most heavily concentrated. The strategy also advocates adopting community-level approaches to prevention in high-risk communities. Structural interventions, which address adverse social, economic, policy, and environmental conditions within communities, have been shown to be effective public health interventions.9,10 The association between HIV prevalence and low SES in the NHBS survey suggests that improvements in educational and employment opportunities in low-income communities, along with concomitant reductions in poverty, could reduce new HIV infections. Without effective approaches to HIV prevention in low-income communities, new HIV infections will continue among these most vulnerable populations.
Local National HIV Behavioral Surveillance System staff members Luke Shouse, Laura Salazar, Atlanta, Georgia; Colin Flynn, Frangiscos Sifakis, Baltimore, Maryland; Debbie Isenberg, Maura Driscoll, Elizabeth Hurwitz, Boston, Massachusetts; Carol Cieselski, Nikhil Prachand, Nanette Benbow, Chicago, Illinois; Sharon Melville, Richard Yeager, Jim Dyer, Nandita Chaudhuri, Alicia Novoa, Dallas, Texas; Mark Thrun, Doug Richardson, Beth Dillon, Denver, Colorado; Renee McCoy, Vivian Griffin, Eve Mokotoff, Detroit, Michigan; Marcia Wolverton, Jan Risser, Hafeez Rehman, Paige Padgett, Houston, Texas; Bob Salcido, Jay DiCotignano, SaBrina Hagan-Finks, Las Vegas, Nevada; Trista Bingham, Ekow Kwa Sey, Los Angeles, California; Marlene LaLota, Dano Beck, Stefanie White, Lisa Metsch, David Forrest, Fort Lauderdale and Miami, Florida; Chris Nemeth, Carol-Ann Watson, Nassau-Suffolk, New York; Aaron Roome, Margaret Weeks, New Haven, Connecticut; William Robinson, DeAnn Gruber, New Orleans, Louisiana; Chris Murrill, Samuel Jenness, Holly Hagan, Travis Wendel, New York, New York; Helene Cross, Barbara Bolden, Sally D'Errico, Henry Godette, Newark, New Jersey; Dena Bensen, Judith Bradford, Norfolk, Virginia; Kathleen Brady, Althea Kirkland, Philadelphia, Pennsylvania; Vanessa Miguelino, Al Velasco, Rosana Scolari, San Diego, California; Henry Raymond, Willi McFarland, San Francisco, California; Sandra Miranda De León, Yadira Rolón-Colón, San Juan, Puerto Rico; Maria Courogen, Hanne Thiede, Nadine Snyder, Richard Burt, Seattle, Washington; Yelena Friedberg, Dean Klinkenberg, LaBraunna Friend, St. Louis, Missouri; Tiffany West-Ojo, Manya Magnus, Irene Kuo, Washington, DC.
* Respondent-driven sampling: Boston, Massachusetts; Dallas, Texas; Denver, Colorado; Detroit, Michigan; Houston, Texas; Los Angeles, California; Nassau/Suffolk Counties, New York; New Haven, Connecticut; New Orleans, Louisiana; New York, New York; Norfolk, Virginia; St. Louis, Missouri; San Diego, California; San Francisco, California; and Washington, DC. Venue-based sampling: Atlanta, Georgia; Baltimore, Maryland; Chicago, Illinois; Fort Lauderdale, Florida; Las Vegas, Nevada; Miami, Florida; Newark, New Jersey; Philadelphia, Pennsylvania; San Juan, Puerto Rico; and Seattle, Washington.
§ Models used marginal Poisson regression and generalized estimating equations. In addition, a variance correction was employed to account for the small number of MSAs in the sample.3
†† Additional information available at www.census.gov/hhes/www/poverty/data/threshld/thresh07.html.
§§ Available at www.whitehouse.gov/administration/eop/onap/nhas.
This article was provided by U.S. Centers for Disease Control and Prevention. Visit the CDC's website to find out more about their activities, publications and services.
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