In Duval County Florida, there are approximately 2, 360 persons living with HIV. Between an estimated 25.6% of persons aged 25 or older living in Duval County have obtained a college degree. Educational disparities may explain differences in prevalence of risk behaviors between groups. The goal of this research is to determine whether or not there is a positive statistically significant difference between the prevalence of HIV related risk behaviors between the college educated and non-college educated HIV patients in Duval County Florida. We used a cross-sectional study design and secondary data from the Florida Department of Public Health Database. This was used to measure the variables of risk behaviors and education level PURPOSE The goal of this research is to determine whether or not there is a positive statistically significant difference between the prevalence of HIV related risk behaviors between the college educated and non-college educated HIV patients in Duval County Florida. The objective is to compare prevalence of persons HIV-related risk factors between the college educated and non-college educated groups. We hypothesized that there would be a z statistic indicating a positive statistically significant difference between the prevalence of HIV-related risk factors between the college educated group and the non-college educated group INTRODUCTION METHODS In this study the Florida Department of Public Health Database was used. The statistical measure used to determine frequency was prevalence. Each variable was managed and analyzed with Excel The key research variables are education level and HIV risk related behavior. The prevalence of each variable is indicated in the Table 1 below. TABLE 1: Table 1: Prevalence HIV Risk Related Behavior Among Each Educational Level, (n=101) Education level was measured by the question, ““What was your highest level of education?” College education is defined as having attended college or graduated college. Those not having attended college were designated to the non- college educated group. HIV-related risk behavior was measured using three questions on the questionnaire: The first question was “Number of sex partners in the previous year?” If a person indicated more than four partners in a year this was considered a risky behavior. The second question was “Were you able to use condoms before HIV infection?” The answers to this question were: never, sometimes, and always. Answering sometimes or never was considered a risk factor. The final question was “Level of condom negotiation skill?” The answers to this question were: none (1), some skill (2), and skilled (3). Answers 1 and 2 indicated a risk factor. If a person had two or more of these risk factors they were counted as having HIV related risk behavior. The prevalence of persons with this behavior were used as a proxy for the frequency of these behaviors in each group. An upper-tailed test using a z statistic was used to determine whether or not there was a positive statistically significant difference in prevalence of HIV-related risk behavior between the two groups. I used a risk difference equation to determine an estimated difference in HIV-related risk behaviors. RESULTS The upper tailed z test indicated that there was a positive statically significant difference between the prevalence of HIV related risk behaviors in the two groups. The decision rule was to reject the possibility of the non-college educated group having a lesser prevalence than the college educated group of HIV-related risk behaviors if the z statistic was greater than The z statistic was 3.48 indicating that there is a statistically significant positive difference between the prevalence of HIV-related risk behaviors between the two groups. These results are summarized in Table 1 below. The risk difference equation indicated that while there is a difference between the two groups’ prevalence in HIV related risk behavior, the estimate is insignificant since the confidence interval includes the null value (1). The estimated risk difference between the college educated group and the non-college educated group was (95% CI ,.2021). DISCUSSION AND CONCLUSIONS The evidence supports our hypothesis that that there would be a z statistic indicating a positive statistically significant difference between the prevalence of risk factors between the college educated group and the non-college educated group Specifically this means that we have statistically significant evidence at a level of significance of 0.05 ( α=0.05) that the prevalence of risk factors among the non- college educated group is greater than the prevalence of risk factors in the college educated group. This information is important because it brings awareness to greater prevalence of HIV related–risk factors prevalent in less educated groups. Our study’s findings support the previous research in this area. We hope that our findings will encourage further exploration of education’s impact on HIV related risk behaviors. TABLE 1: Results of Upper Tailed Z-Test Comparing Prevalence of Risk Behaviors Between College Educated and Non-College Educated HIV Patients (n=101) The study did have two main limitations. The first limitation is that this was a cross sectional study design. This type of study design does not have a temporal element and thus cannot establish a causal relationship. The second issue is that the sample size was limited based on the amount of people who were counseled regarding their HIV status within the July January 2014 time frame. A larger sample size may have decreased the confidence interval resulting in a more specific and possibly more significant risk difference estimate LIMITATIONS INTRODUCTION METHODS CONCLUSIONS DISCUSSIONS AND Comparison of HIV-Related Risk Behaviors By Education Level Among Adult HIV Patients in Duval County, Florida Myers.K., Kakezai,I., Florida Department of Public Health in Duval County, 515 W 6th St Jacksonville, FL HIV-Risk Related Behavior No HIV-Risk Related- Behavior Total College Educated5(4.95%)24(23.73%)29(28.71%) Not College Educated15(14.85%)57(56.44%)72(71.29%) Total20(19.80%)81(80.20%)101(100%) equation Level of Significance α=0.05 Null Hypothesis H=p ₁ ≤p ₂ Tested Hypothesis H ₁ =p ₁ >p ₂ critical value1.645 Decision RuleReject H if z>1.645 Result3.48>1.645