Linton Sabriya L, Cooper Hannah L F, Kelley Mary E, Karnes Conny C, Ross Zev, Wolfe Mary E, Des Jarlais Don, Semaan Salaam, Tempalski Barbara, DiNenno Elizabeth, Finlayson Teresa, Sionean Catlainn, Wejnert Cyprian, Paz-Bailey Gabriela
Sabriya L. Linton, Hannah L. F. Cooper, Mary E. Kelley, Conny C. Karnes, and Mary E. Wolfe are with The Rollins School of Public Health at Emory University, Atlanta, GA. Zev Ross is with ZevRoss SpatialAnalysis, Ithaca, NY. Don Des Jarlais is with The Baron Edmond de Rothschild Chemical Dependency Institute, Mount Sinai Beth Israel, New York, NY. Barbara Tempalski is with The Institute for Infectious Disease Research, National Development and Research Institutes, New York, NY. Salaam Semaan, Elizabeth DiNenno, Teresa Finlayson, Catlainn Sionean, Cyprian Wejnert, and Gabriela Paz-Bailey are with the Centers for Disease Control and Prevention, Atlanta.
Am J Public Health. 2015 Dec;105(12):2457-65. doi: 10.2105/AJPH.2015.302861. Epub 2015 Oct 15.
We explored how variance in HIV infection is distributed across multiple geographical scales among people who inject drugs (PWID) in the United States, overall and within racial/ethnic groups.
People who inject drugs (n = 9077) were recruited via respondent-driven sampling from 19 metropolitan statistical areas (MSAs) for the Centers for Disease Control and Prevention's 2009 National HIV Behavioral Surveillance system. We used multilevel modeling to determine the percentage of variance in HIV infection explained by zip codes, counties, and MSAs where PWID lived, overall and for specific racial/ethnic groups.
Collectively, zip codes, counties, and MSAs explained 29% of variance in HIV infection. Within specific racial/ethnic groups, all 3 scales explained variance in HIV infection among non-Hispanic/Latino White PWID (4.3%, 0.2%, and 7.5%, respectively), MSAs explained variance among Hispanic/Latino PWID (10.1%), and counties explained variance among non-Hispanic/Latino Black PWID (6.9%).
Exposure to potential determinants of HIV infection at zip codes, counties, and MSAs may vary for different racial/ethnic groups of PWID, and may reveal opportunities to identify and ameliorate intraracial inequities in exposure to determinants of HIV infection at these geographical scales.
我们探讨了美国注射吸毒者(PWID)中,HIV感染差异在多个地理尺度上的分布情况,包括总体情况以及不同种族/族裔群体内部的情况。
通过应答驱动抽样,从19个大都市统计区(MSA)招募了注射吸毒者(n = 9077),用于疾病控制和预防中心2009年的全国HIV行为监测系统。我们使用多层次模型来确定PWID居住的邮政编码区、县和MSA所解释的HIV感染差异百分比,包括总体情况以及特定种族/族裔群体的情况。
总体而言,邮政编码区、县和MSA解释了HIV感染差异的29%。在特定种族/族裔群体中,所有这三个尺度都解释了非西班牙裔/拉丁裔白人PWID中HIV感染的差异(分别为4.3%、0.2%和7.5%),MSA解释了西班牙裔/拉丁裔PWID中的差异(10.1%),县解释了非西班牙裔/拉丁裔黑人PWID中的差异(6.9%)。
对于不同种族/族裔的PWID群体,在邮政编码区、县和MSA接触HIV感染潜在决定因素的情况可能有所不同,这可能揭示了在这些地理尺度上识别和改善种族内部在接触HIV感染决定因素方面不平等现象的机会。