University of South Carolina, Institute for Families in Society, Policy and Research Unit on Medicaid and Medicare, Columbia, SC 29208, USA.
Public Health Rep. 2011 Sep-Oct;126 Suppl 3(Suppl 3):115-26. doi: 10.1177/00333549111260s316.
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.
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.
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 visualization 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] = 2.03; p=0.006), as well as each increase in Townsend index of social deprivation category (OR=4.98; p<0.001). A multivariate ordered logistic regression model in which all three socioeconomic disadvantage indexes were included showed a significant positive association between HIV/AIDS and Townsend index categories (adjusted OR=6.10; p<0.001).
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.
我们利用现有的数据系统，检查性传播疾病（STD）和艾滋病/艾滋病诊断率，并探索艾滋病/艾滋病诊断率与社会经济劣势之间可能存在的县级关联。
使用南卡罗来纳州各县的数据，我们构建了多变量环图，以空间可视化梅毒、淋病、衣原体和艾滋病/艾滋病的诊断率；按性别和种族划分的艾滋病/艾滋病诊断率；以及三个社会经济劣势指标——失业率指数、贫困指数和汤森德社会剥夺指数。进行了统计分析，以定量评估艾滋病/艾滋病诊断率与三个社会经济劣势指标之间的潜在县级关联。
环图揭示了 STD 和艾滋病/艾滋病诊断率之间存在大量的空间关联，并突出了该州艾滋病/艾滋病在性别和种族方面的巨大差异。平均县级艾滋病/艾滋病诊断率（每 10 万人）为男性 24.2 例，女性 11.2 例，非裔美国人 34.8 例，白人 5.2 例。此外，环图可视化显示艾滋病/艾滋病诊断率与社会经济劣势之间存在县级关联。在贫困指数每增加一个类别时，艾滋病/艾滋病的分类与每个类别的比值比（OR）增加 2.03（p=0.006），以及汤森德社会剥夺指数每增加一个类别时，OR 增加 4.98（p<0.001），都发现了显著的正相关关系。在一个包含所有三个社会经济劣势指标的多变量有序逻辑回归模型中，艾滋病/艾滋病与汤森德指数类别之间存在显著的正相关关系（调整后的 OR=6.10；p<0.001）。
环图直观地描绘了 STD 和艾滋病/艾滋病的空间重合，并揭示了南卡罗来纳州各县艾滋病/艾滋病的巨大性别和种族差异。这种空间可视化方法利用现有的数据系统，突出了健康社会决定因素在规划和决策过程中的重要性。
