The Need for Rural-Urban County Type in Centers for Disease Control and Prevention's Social Vulnerability Index Concerning Human Immunodeficiency Virus Reporting Data

Background: The Social Vulnerability Index (SVI) is the Centers for Disease Control and Prevention's premier measure of community resilience to trauma. The SVI has been used widely, with various public health issues, in order to assess community risk and to plan effectively for resource allocat...

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Veröffentlicht in:Traumatology (Tallahassee, Fla.) Fla.), 2024-09, Vol.30 (3), p.439-446
Hauptverfasser: McDaniel, Justin T., Tillewein, Heather, Wallace, Juliane P., Albright, David L., Henson, Harvey
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container_issue 3
container_start_page 439
container_title Traumatology (Tallahassee, Fla.)
container_volume 30
creator McDaniel, Justin T.
Tillewein, Heather
Wallace, Juliane P.
Albright, David L.
Henson, Harvey
description Background: The Social Vulnerability Index (SVI) is the Centers for Disease Control and Prevention's premier measure of community resilience to trauma. The SVI has been used widely, with various public health issues, in order to assess community risk and to plan effectively for resource allocation. Although rurality is an accepted risk factor for many health problems, the SVI does not include it. As such, the purpose of this study was to determine the psychometric properties of the SVI with rurality included and to assess the predictive power of the rurality-adjusted SVI relative to the original SVI in the case of human immunodeficiency virus (HIV) prevalence. Method: We performed confirmatory factor analysis on the 15 items of the SVI with the addition of rural-urban continuum codes (RUCCs) as a 16th variable (n = 2,226 counties). Subsequently, we regressed county-level HIV case rates per 100,000 on the original SVI and the RUCC-adjusted SVI. Results: The model fit statistics for the SVI were adequate with the inclusion of RUCCs (standardized root mean squared residual = 0.09; root mean square error of approximation = 0.08). Results showed that the R2 improved significantly from Model 1 (i.e., no SVI) to Model 2 (i.e., original SVI) (F = 26.58, p < .001); however, Model 3 (i.e., RUCC-adjusted SVI), compared to Model 1, demonstrated superior R2 value enhancement (F = 211.42, p < .001). Conclusion: The RUCC-adjusted SVI may be a better determinant of county-level risk for HIV cases per 100,000 than the original SVI; however, future research is needed with other health issues before the efficacy of the RUCC-adjusted SVI can be determined.
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The SVI has been used widely, with various public health issues, in order to assess community risk and to plan effectively for resource allocation. Although rurality is an accepted risk factor for many health problems, the SVI does not include it. As such, the purpose of this study was to determine the psychometric properties of the SVI with rurality included and to assess the predictive power of the rurality-adjusted SVI relative to the original SVI in the case of human immunodeficiency virus (HIV) prevalence. Method: We performed confirmatory factor analysis on the 15 items of the SVI with the addition of rural-urban continuum codes (RUCCs) as a 16th variable (n = 2,226 counties). Subsequently, we regressed county-level HIV case rates per 100,000 on the original SVI and the RUCC-adjusted SVI. Results: The model fit statistics for the SVI were adequate with the inclusion of RUCCs (standardized root mean squared residual = 0.09; root mean square error of approximation = 0.08). Results showed that the R2 improved significantly from Model 1 (i.e., no SVI) to Model 2 (i.e., original SVI) (F = 26.58, p &lt; .001); however, Model 3 (i.e., RUCC-adjusted SVI), compared to Model 1, demonstrated superior R2 value enhancement (F = 211.42, p &lt; .001). 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Results showed that the R2 improved significantly from Model 1 (i.e., no SVI) to Model 2 (i.e., original SVI) (F = 26.58, p &lt; .001); however, Model 3 (i.e., RUCC-adjusted SVI), compared to Model 1, demonstrated superior R2 value enhancement (F = 211.42, p &lt; .001). 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The SVI has been used widely, with various public health issues, in order to assess community risk and to plan effectively for resource allocation. Although rurality is an accepted risk factor for many health problems, the SVI does not include it. As such, the purpose of this study was to determine the psychometric properties of the SVI with rurality included and to assess the predictive power of the rurality-adjusted SVI relative to the original SVI in the case of human immunodeficiency virus (HIV) prevalence. Method: We performed confirmatory factor analysis on the 15 items of the SVI with the addition of rural-urban continuum codes (RUCCs) as a 16th variable (n = 2,226 counties). Subsequently, we regressed county-level HIV case rates per 100,000 on the original SVI and the RUCC-adjusted SVI. Results: The model fit statistics for the SVI were adequate with the inclusion of RUCCs (standardized root mean squared residual = 0.09; root mean square error of approximation = 0.08). Results showed that the R2 improved significantly from Model 1 (i.e., no SVI) to Model 2 (i.e., original SVI) (F = 26.58, p &lt; .001); however, Model 3 (i.e., RUCC-adjusted SVI), compared to Model 1, demonstrated superior R2 value enhancement (F = 211.42, p &lt; .001). Conclusion: The RUCC-adjusted SVI may be a better determinant of county-level risk for HIV cases per 100,000 than the original SVI; however, future research is needed with other health issues before the efficacy of the RUCC-adjusted SVI can be determined.</abstract><pub>Educational Publishing Foundation</pub><doi>10.1037/trm0000459</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0001-8008-1645</orcidid></addata></record>
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subjects Female
Government Agencies
HIV
Human
Male
Rural Health
Susceptibility (Disorders)
title The Need for Rural-Urban County Type in Centers for Disease Control and Prevention's Social Vulnerability Index Concerning Human Immunodeficiency Virus Reporting Data
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