TY - JOUR
T1 - How do social capital and HIV/AIDS outcomes geographically cluster and which sociocontextual mechanisms predict differences across clusters?
AU - Ransome, Yusuf
AU - Dean, Lorraine T.
AU - Crawford, Natalie D.
AU - Metzger, David S.
AU - Blank, Michael B.
AU - Nunn, Amy S.
N1 - Funding Information:
Y.R. was supported in part by the Clinical and Community-Based HIV/AIDS Research Training Program at Brown University and the Miriam Hospital (R25 MH083620), The HIV Prevention Trials Network (HPTN) Scholars Program, and by the National Institute of Mental Health (K01 MH111374). L.T.D. was supported by the National Institutes of Health/ National Cancer Institute (K01 CA184288) and the National Institutes for Allergy and Infection Disease Grant (Johns Hopkins University Center for AIDS Research; P30 AI094189). D.S.M. and M.B.B. was supported in part by the Penn Center for AIDS Research (P30 AI45008), the Penn Mental Health AIDS Research Center (P30 MH097488) and the National Institute on Drug Abuse (R01 DA036503). N.D.C. was supported by the Emory Center for AIDS Research (P30 AI050409) and the HIV/AIDS Substance use and Trauma Training Program. A.S.N. was supported by National Institute of Mental Health (R25 MH083620; 1R34 MH109371).
Publisher Copyright:
Copyright © 2017 Wolters Kluwer Health, Inc. All rights reserved.
PY - 2017/9/1
Y1 - 2017/9/1
N2 - Background: Place of residence has been associated with HIV transmission risks. Social capital, defined as features of social organization that improve efficiency of society by facilitating coordinated actions, often varies by neighborhood, and hypothesized to have protective effects on HIV care continuum outcomes. We examined whether the association between social capital and 2 HIV care continuum outcomes clustered geographically and whether sociocontextual mechanisms predict differences across clusters. Methods: Bivariate Local Moran's I evaluated geographical clustering in the association between social capital (participation in civic and social organizations, 2006, 2008, 2010) and [5-year (2007-2011) prevalence of late HIV diagnosis and linkage to HIV care] across Philadelphia, PA, census tracts (N = 378). Maps documented the clusters and multinomial regression assessed which sociocontextual mechanisms (eg, racial composition) predict differences across clusters. Results: We identified 4 significant clusters (high social capital-high HIV/AIDS, low social capital-low HIV/AIDS, low social capital-high HIV/AIDS, and high social capital-low HIV/AIDS). Moran's I between social capital and late HIV diagnosis was (I = 0.19, z = 9.54, P < 0.001) and linkage to HIV care (I = 0.06, z = 3.274, P = 0.002). In multivariable analysis, median household income predicted differences across clusters, particularly where social capital was lowest and HIV burden the highest, compared with clusters with high social capital and lowest HIV burden. Discussion: The association between social participation and HIV care continuum outcomes cluster geographically in Philadelphia, PA. HIV prevention interventions should account for this phenomenon. Reducing geographic disparities will require interventions tailored to each continuum step and that address socioeconomic factors such as neighborhood median income.
AB - Background: Place of residence has been associated with HIV transmission risks. Social capital, defined as features of social organization that improve efficiency of society by facilitating coordinated actions, often varies by neighborhood, and hypothesized to have protective effects on HIV care continuum outcomes. We examined whether the association between social capital and 2 HIV care continuum outcomes clustered geographically and whether sociocontextual mechanisms predict differences across clusters. Methods: Bivariate Local Moran's I evaluated geographical clustering in the association between social capital (participation in civic and social organizations, 2006, 2008, 2010) and [5-year (2007-2011) prevalence of late HIV diagnosis and linkage to HIV care] across Philadelphia, PA, census tracts (N = 378). Maps documented the clusters and multinomial regression assessed which sociocontextual mechanisms (eg, racial composition) predict differences across clusters. Results: We identified 4 significant clusters (high social capital-high HIV/AIDS, low social capital-low HIV/AIDS, low social capital-high HIV/AIDS, and high social capital-low HIV/AIDS). Moran's I between social capital and late HIV diagnosis was (I = 0.19, z = 9.54, P < 0.001) and linkage to HIV care (I = 0.06, z = 3.274, P = 0.002). In multivariable analysis, median household income predicted differences across clusters, particularly where social capital was lowest and HIV burden the highest, compared with clusters with high social capital and lowest HIV burden. Discussion: The association between social participation and HIV care continuum outcomes cluster geographically in Philadelphia, PA. HIV prevention interventions should account for this phenomenon. Reducing geographic disparities will require interventions tailored to each continuum step and that address socioeconomic factors such as neighborhood median income.
KW - HIV care continuum
KW - HIV/AIDS
KW - United States
KW - neighborhoods
KW - social capital
KW - social determinants
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U2 - 10.1097/QAI.0000000000001463
DO - 10.1097/QAI.0000000000001463
M3 - Article
C2 - 28797017
AN - SCOPUS:85027872998
SN - 1525-4135
VL - 76
SP - 13
EP - 22
JO - Journal of Acquired Immune Deficiency Syndromes and Human Retrovirology
JF - Journal of Acquired Immune Deficiency Syndromes and Human Retrovirology
IS - 1
ER -