Spatial Visualization of Multivariate Data Sets: An Analysis of STD and HIV/AIDS Diagnosis Rates and Socioeconomic Context Using Ring Maps
Document Type
Article
Subject Area(s)
Public Health
Abstract
Objectives. We used existing data systems to examine sexually transmitted disease (STD) and HIV/AIDS diagnosis rates and explore potential county-level associations between HIV/AIDS diagnosis rates and socioeconomic disadvantage.Methods. Using South Carolina county data, we constructed multivariate ring maps to spatially visualize syphilis, gonorrhea, chlamydia, and HIV/AIDS diagnosis rates; gender- and race-specific HIV/AIDS diagnosis rates; and three measures of socioeconomic disadvantage—an unemployment index, a poverty index, and the Townsend index of social deprivation. Statistical analyses were performed to quantitatively assess potential county-level associations between HIV/AIDS diagnosis rates and each of the three indexes of socioeconomic disadvantage. Results. Ring maps revealed substantial spatial association in STD and HIV/AIDS diagnosis rates and highlighted large gender and racial disparities in HIV/AIDS across the state. The mean county-level HIV/AIDS diagnosis rate (per 100,000 population) was 24.2 for males vs. 11.2 for females, and 34.8 for African Americans vs. 5.2 for white people. In addition, ring map visualiza-tion suggested a county-level association between HIV/AIDS diagnosis rates and socioeconomic disadvantage. Significant positive bivariate relationships were found between HIV/AIDS rate categories and each increase in poverty index category (odds ratio [OR] 5 2.03; p50.006), as well as each increase in Townsend index of social deprivation category (OR54.98; p0.001). A multivariate ordered logistic regression model in which all three socioeconomic disadvantage indexes were included showed a significant positive associa-tion between HIV/AIDS and Townsend index categories (adjusted OR56.10; p0.001). Conclusions. Ring maps graphically depicted the spatial coincidence of STD and HIV/AIDS and revealed large gender and racial disparities in HIV/AIDS across South Carolina counties. This spatial visualization method used existing data systems to highlight the importance of social determinants of health in program planning and decision-making processes.
Digital Object Identifier (DOI)
Publication Info
Published in Public Health Reports, Volume 126, Issue 3, 2011, pages 115-126.
APA Citation
Lòpez-DeFede, A., Stewart, J. E., Hardin, J. W., Mayfield-Smith, K., & Sudduth, D. (2011). Spatial visualization of multivariate data sets: An analysis of STD and HIV/AIDS diagnosis rates and socioeconomic context using ring maps. Public Health Reports, 126(Suppl. 3), 115-126.
Rights
© 2011 Association of Schools of Public Health