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The Association Between the Social Determinants of Health and HIV Control in Miami-Dade County ZIP Codes, 2017
BACKGROUND: There were 28,055 people living with HIV (PLWH) in Miami-Dade County (MDC) in 2017; 40.1% was either out of care or was not virally suppressed (uncontrolled HIV). The purpose of this study was to determine the association between the social determinants of health (SDOH) and the number of...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer International Publishing
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8102448/ https://www.ncbi.nlm.nih.gov/pubmed/32808192 http://dx.doi.org/10.1007/s40615-020-00838-z |
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author | Rojas, Dayana Melo, Anamarie Moise, Imelda K. Saavedra, Jorge Szapocznik, José |
author_facet | Rojas, Dayana Melo, Anamarie Moise, Imelda K. Saavedra, Jorge Szapocznik, José |
author_sort | Rojas, Dayana |
collection | PubMed |
description | BACKGROUND: There were 28,055 people living with HIV (PLWH) in Miami-Dade County (MDC) in 2017; 40.1% was either out of care or was not virally suppressed (uncontrolled HIV). The purpose of this study was to determine the association between the social determinants of health (SDOH) and the number of persons with uncontrolled HIV in MDC. SETTING: This cross-sectional study included PLWH 15 and older with uncontrolled HIV in MDC, 2017. Data on PLWH’s viral load, age, gender, mode of HIV transmission, and race/ethnicity were aggregated to the ZIP code level. All five SDOH per HealthyPeople 2020 were represented: economic stability, education, social and community context, health and healthcare, and neighborhood and built environment. METHODS: Descriptive analyses on all study variables and a principal component analysis on the SDOH variables were performed. To account for overdispersion, multivariate negative binomial regressions were run while controlling for confounders and testing for significant interactions. RESULTS: The results of the regression analysis indicated that an increase in Factor 1 (economic stability, education, and health and healthcare determinants) was associated with a statistically significant increase in the number of PLWH with uncontrolled HIV. Additionally, we found a significant interaction between Factor 1 and White race. Among persons of low socioeconomic status, White race is associated with a reduction in PLWH with uncontrolled HIV. CONCLUSIONS: These results suggest that reducing poverty and increasing education and rates of health insurance should result in significant reductions in PLWH with uncontrolled HIV. These results have the potential to influence future policy, interventions for retention, adherence, and continuity of care to improve suppression rates in MDC. |
format | Online Article Text |
id | pubmed-8102448 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-81024482021-05-11 The Association Between the Social Determinants of Health and HIV Control in Miami-Dade County ZIP Codes, 2017 Rojas, Dayana Melo, Anamarie Moise, Imelda K. Saavedra, Jorge Szapocznik, José J Racial Ethn Health Disparities Article BACKGROUND: There were 28,055 people living with HIV (PLWH) in Miami-Dade County (MDC) in 2017; 40.1% was either out of care or was not virally suppressed (uncontrolled HIV). The purpose of this study was to determine the association between the social determinants of health (SDOH) and the number of persons with uncontrolled HIV in MDC. SETTING: This cross-sectional study included PLWH 15 and older with uncontrolled HIV in MDC, 2017. Data on PLWH’s viral load, age, gender, mode of HIV transmission, and race/ethnicity were aggregated to the ZIP code level. All five SDOH per HealthyPeople 2020 were represented: economic stability, education, social and community context, health and healthcare, and neighborhood and built environment. METHODS: Descriptive analyses on all study variables and a principal component analysis on the SDOH variables were performed. To account for overdispersion, multivariate negative binomial regressions were run while controlling for confounders and testing for significant interactions. RESULTS: The results of the regression analysis indicated that an increase in Factor 1 (economic stability, education, and health and healthcare determinants) was associated with a statistically significant increase in the number of PLWH with uncontrolled HIV. Additionally, we found a significant interaction between Factor 1 and White race. Among persons of low socioeconomic status, White race is associated with a reduction in PLWH with uncontrolled HIV. CONCLUSIONS: These results suggest that reducing poverty and increasing education and rates of health insurance should result in significant reductions in PLWH with uncontrolled HIV. These results have the potential to influence future policy, interventions for retention, adherence, and continuity of care to improve suppression rates in MDC. Springer International Publishing 2020-08-17 2021 /pmc/articles/PMC8102448/ /pubmed/32808192 http://dx.doi.org/10.1007/s40615-020-00838-z Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Rojas, Dayana Melo, Anamarie Moise, Imelda K. Saavedra, Jorge Szapocznik, José The Association Between the Social Determinants of Health and HIV Control in Miami-Dade County ZIP Codes, 2017 |
title | The Association Between the Social Determinants of Health and HIV Control in Miami-Dade County ZIP Codes, 2017 |
title_full | The Association Between the Social Determinants of Health and HIV Control in Miami-Dade County ZIP Codes, 2017 |
title_fullStr | The Association Between the Social Determinants of Health and HIV Control in Miami-Dade County ZIP Codes, 2017 |
title_full_unstemmed | The Association Between the Social Determinants of Health and HIV Control in Miami-Dade County ZIP Codes, 2017 |
title_short | The Association Between the Social Determinants of Health and HIV Control in Miami-Dade County ZIP Codes, 2017 |
title_sort | association between the social determinants of health and hiv control in miami-dade county zip codes, 2017 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8102448/ https://www.ncbi.nlm.nih.gov/pubmed/32808192 http://dx.doi.org/10.1007/s40615-020-00838-z |
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