Measures
State-based federal funding data for HIV were obtained through a special data request to State Health Facts, a project of the Henry J. Kaiser Family Foundation (KFF). The KFF maintains a large collection of data from a variety of sources, including total federal HIV grant funding to US states, territories, and the District of Columbia. The data originated from the National Alliance of State & Territorial AIDS Directors (NASTAD), which tracks this information over time and reports it to KFF. The data included state-based HIV funding from the Centers for Disease Control and Prevention (CDC), Housing Opportunities for Persons with AIDS (HOPWA), Substance Abuse and Mental Health Services Administration (SAMHSA), the U.S. Office of Minority Health (OMH), and the Ryan White HIV/AIDS Program.
In a sub-analysis, total state-based federal funding for HIV were separated into two categories based on the primary use of the funding. Funding for HIV prevention included funding primarily for direct-service programs designed to reduce the number of new HIV infections. Funding for HIV treatment included funding primarily for direct-service programs designed to increase treatment access, improve health outcomes, and address other health issues for People Living With HIV (PLWH). In order to determine the primary use of the funding, web pages, Requests for Proposals, award notices, and other information on the funder’s web sites were consulted. In several cases, state-based federal funding for HIV could not be easily categorized into prevention or treatment categories primarily because the funds could be used to support HIV activities in both areas. Only funds that were clearly designated as prevention or treatment were categorized as such in the sub-analysis (see Additional file 1 for categorization of funding in the sub-analysis).
HIV diagnosis and prevalence rates were obtained through a special data request to ATLAS, a project of the National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP). ATLAS was created by NCHHSTP to provide the public with interactive maps, graphs, tables, and figures showing geographic patterns and time trends of HIV and other diseases [3]. The data included state-level HIV diagnosis and prevalence rates for the 40 states with confidential name-based HIV infection reporting during the time horizon of the study (2006–2009). These states included AL, AK, AZ, AR, CO, CT, FL, GA, ID, IL, IN, IA, KS, KY, LA, ME, MI, MN, MS, MO, NE, NV, NH, NJ, NM, NY, NC, ND, OH, OK, PA, SC, SD, TN, TX, UT, VA, WV, WI, and WY. States without confidential name-based HIV infection reporting systems during the time horizon of the study were excluded from analysis due to concerns over the accuracy and reliability of information. In addition, AIDS prevalence and new AIDS case rates were not included in the analysis because the number of people living with an AIDS diagnosis are already included in the HIV rates and because the funding from programs used in the analysis, particularly treatment funding, benefit all PLWH, not just those with an AIDS diagnosis. Lastly, case counts were not used in the analysis, since case rates are a more widely used metric in the scientific literature and supported by the U.S. National HIV/AIDS Strategy [4].
Analysis procedures
Descriptive statistics were performed to describe total state-based federal funding for HIV, state-based funding for HIV prevention, state-based funding for HIV treatment, HIV diagnosis rates, and HIV prevalence rates. Bivariate analyses using Pearson’s correlation and Spearman’s rank correlation were conducted to assess the association between funding for HIV and HIV diagnosis and prevalence rates. Pearson’s correlation was selected so that results could be compared to the Mansergh article [2]. However, tests of normality using Kolmogorov-Smirnov and Shapiro-Wilk revealed that the data were not normally distributed (significance set at p < .05), so Spearman’s rank correlations were also performed. All correlation coefficients in our analysis were significant at p < .01.
Hypothesis
The hypotheses for the bivariate analyses were:
H
0
: There is no correlation between total state-based federal funding for HIV and HIV diagnosis rates.
H
0
: There is no correlation between total state-based federal funding for HIV and HIV prevalence rates.
H
0
: There is no correlation between total state-based federal funding for HIV prevention and HIV diagnosis rates.
H
0
: There is no correlation between total state-based federal funding for HIV prevention and HIV prevalence rates.
H
0
: There is no correlation between total state-based federal funding for HIV treatment and HIV diagnosis rates.
H
0
: There is no correlation between total state-based federal funding for HIV treatment and HIV prevalence rates.