HSA/Doris Duke 2014-2015 Newsletter

The Doris Duke Charitable Foundation Clinical Research Experiences for High School Students 2014 - 2015 Grant# 201111

Asthma Medication Adherence and Symptom Control in a Predominantly Black Pediatric Population Student Researchers: L-R) Marcell Howard, Susan Schaefer and Momina Tariq

Once again AAIUH is delighted to publish the work of our Health Science Academy (HSA) students who participated in the Doris Duke Charitable Foundation’s (DDCF) CREHSS program 2014/15. This is the third of five cohorts supported by DDCF’s generous funding. CREHSS supported 10 of our juniors to engage in clinical research experiences examining health disparities and to be mentored by SUNY Downstate faculty. In summer 2014, the Duke interns did a PowerPoint presentation of their research and presented their research posters during our partner, SUNY Downstate Medical Center’s, Annual Research Day April 2015. These students are now HSA alumni completing their freshmen year in college – including a Posse Foundation Scholar at Brandies University, and other alumni at universities including Fordham, Case Western Reserve, St. Joseph – we are proud of all of them. One of these Duke interns volunteered to assist with the summer 2016 cohort.

Such service embodies the spirit of our founder, Arthur Ashe to “…do what you can.”

AAIUH is very grateful to DDCF and the SUNY Downstate senior faculty, graduate students, and staff that served as mentors and provided our students with educational hands-on clinical research experiences. We are also very grateful to the summer instructors, Cassandra Raphael, now in medical school (2017 MD candidate), Yamina Kezadri, Manpreet Kaur and intern Rubama Haque. Thanks also to Dr. McIntyre of Kings County Medical Center and other staff for providing great enrichment activities during the summer component of our CREHSS program.

Mary Valmont, PhD Health Science Academy Associate Director for Health Science Education Arthur Ashe Institute for Urban Health

Faculty Mentors: Suzanne Burke-McGovern, MD, Fellow and Rauno Joks, MD, Associate Professor of Clinical Medicine, Chief, Division of Allergy and Immunology; Director, Allergy and Immunology Fellowship

Effects of Anxiety and Depression on Medication Adherence in ESRD Patients Student Researchers: L-R) Zekaiah Fox, Aija Jones & Annecia Diamond Faculty Mentor: Daniel Cukor, PhD, Psychiatry & Behavioral Sciences, Anxiety Disorder Clinic

Effects of Decreased HbA1c Levels on the Weight of Newly Diagnosed Diabetics Student Researchers: L-R) Malik Johnson and Kenyetta Smith Faculty Mentor: MaryAnn Banerji, MD Program Chief and Director Diabetes Treatment Center, Endocrinology Department

Perceptions of Health and HIV Testing Status Among Heterosexual African American Males in Brooklyn, NY Student Researchers: L-R) Jean Poulard and Joshua Germain Faculty Mentor: Michael Joseph, PhD Interim Chair, Assistant Professor Environmental and Occupational Health Science School of Public Health

Asthma Medication Adherence and Symptom Control in a Predominantly Black Pediatric Population Marcell Howard, Susan Schaefer and Momina Tariq

Results

The four graphs display Concern vs. Asthma Control, Commitment vs. Asthma Control, Cost vs. Asthma Control and the overall Adherence Score vs. Asthma Control. The average ACT score was 20.6 and the mean score on the AE was 4. There was a weak relationship because the r-values of the four graphs are .007, .0412, .0458, and .0084 and the R2 are 5e-5, .0017, .0021, and 7e-5 respectively. There are negative correlations between Commitment vs. Asthma Control and the Composite vs. Asthma Control and there are positive correlations between Concern vs. Asthma Control and Cost vs. Asthma Control. We used the linear regression because it is the best way to show the relationship between adherence and asthma control. Our results indicate that high AE scores is associated with less well controlled asthma .

30

y = 0.0107x + 20.607 R² = 5.1E-05

Asthma Control

15

15 10

Asthma Control

5

0

2

4

6

8

10

12

14

16

AE Concern

Conclusion Our data supported our hypothesis that good medication adherence is associated with higher ACT scores and better controlled asthma and high AE scores were associated with less well controlled asthma.

Patients’ concerns about the harmful effects of their medications and their commitment to take their asthma medications was associated with lower ACT scores and less well controlled asthma based on ACT scoring criteria. Cost was not a factor in medication adherence and asthma control. This may be due to the fact that the majority of participants in this study are enrolled in Medicaid, or some form of a public insurance program and do not need to pay for medications.

This study illustrates that by addressing the importance of a patient’s commitment to take their asthma medications and addressing their concerns of potential side effects of their medications may facilitate better asthma control. This may reduce the morbidity and mortality associated with asthma especially in the African/Caribbean American population.

References 1. Staff, T. M. (2014). Asthma Causes - Diseases and Conditions. Mayo Clinic

20

20

0

y = -0.1053x + 20.737 r = .0412 R² = 0.0017 p = .43

30 25

25

2.CDC. (2012). Trends in Asthma Prevalence, Health Care, and Mortality in the United States. CDC.

10 5

Asthma Control

0

Linear (Asthma Control)

0

2

4

AE Commitment

6

8

3.Health, O. (2012-2013). Asthma and African Americans.

Center for Disease Control.

4.Global Initiative for Asthma. (2012). Global Strategy for Asthma Management and Prevention.

30

Hypothesis Good medication adherence (measured by the Adherence Estimator (AE)) is associated with better controlled asthma (measured by their ACT scores) in the African/Caribbean American pediatric population.

y = 0.4035x + 20.526 r = .0458 R² = 0.0021 p = .42

25

Asthma Control

.

Asthma is a chronic respiratory condition marked by bronchial hyper-responsiveness, increased mucous production and respiratory distress. The symptoms include wheezing, coughing, breathlessness and chest tightness. Asthma is triggered by airborne allergens, respiratory infections, cold air, air pollutants, and physical activity (1).

Asthma is the most common chronic disease of childhood (2). The incidence of asthma in Black children is 16.4 percent higher compared to Caucasians (3). The majority of morbidity and mortality associated with asthma may be due to poor asthma control. Asthma control is the degree to which the manifestations of asthma are minimized by therapeutic interventions. Asthma is treated with two types of medicines: long-acting and short acting medications.

Adherence to asthma medication regimens tends to be very poor in the United States ; with reported rates of non-adherence ranging from 30 to 70% (4). Adherence is a major problem in African/ Caribbean American patient populations which is the dominant ethnicity at SUNY Downstate’s Pediatric Asthma Center.

There is little to no research that has investigated the correlation between medication adherence and asthma control in asthmatic children of African/ Caribbean American descent. This study looks at three major factors that may affect medication adherence. These include the financial burden of medication cost, perception of medication importance, and concerns about side effects of the medication(s). Identifying and addressing factors that affect medication adherence and the effect they have on asthma control can help clinicians design interventions to overcome barriers to adherence in affected populations.

Methodology

Suzanne Burke McGovern, M.D., Fellow, and Rauno Joks, M.D., Associate Professor of Clinical Medicine, Division Chief of Allergy & Immunology at SUNY Downstate our mentors, recommended using the Adherence Estimator™ (AE) by Merck and Company Inc. and the Asthma Control Test (ACT). This was an IRB approved study. Twenty –two patients ages 4-21, all of African/Caribbean American descent were surveyed. A consent form and two surveys were distributed to the patient’s and their caregivers prior to their asthma visit at SUNY Downstate’s Pediatric Asthma Center. The AE measures the patient’s level medication adherence based on 3 factors; Cost- the financial burden of their medications, Concern- concern their medications will do more harm than good, and Commitment-the commitment they have to take their medications as prescribed. This AE questionnaire has been validated and utilized as a measure of medication adherence in many chronic diseases such as hypertension and diabetes. The Asthma Control Test (ACT) measures patients’ asthma control and has been approved by the American Lung Association as a measure of asthma control in children and adults. Asthma control is defined by three categories; well controlled, not well controlled and very poorly controlled based upon symptoms, interference with normal activity and exacerbations requiring steroids. Using these tools, we were able to observe a correlation between medication adherence and asthma control.

Our independent variable was medication adherence and our dependent variable was asthma control. Barriers to adherence were measured by the AE. Good medication adherence was defined as having a score of less than eight on the AE. Well controlled asthma was defined as a score greater than 19 on the ACT. Data was analyzed with regression analysis.

Asthma Control

Introduction

20

Special thanks to Doris Duke Charitable Foundation, the Arthur Ashe Institute of Urban Health, and our mentors Dr. Susan Burke Mc-Govern and Dr. Rauno Joks.

15 10

Asthma Control

5

Linear (Asthma Control)

0

Acknowledgement

0

0.5

1

1.5

AE Cost

2

2.5

This work was supported by Doris Duke Charitable Foundation Grant #2011111

03272015FINAL.PPT

Introduction End Stage Renal Disease (ESRD), the final stage of chronic kidney disease (CKD), is marked by too little or complete loss of function in both kidneys. As a result, toxins are not properly filtered from blood. Decreased kidney function causes accumulation of extra fluid in the body, and decreased production of hormones that regulate blood pressure, make red blood cells and keep bones healthy.

Symptoms of ESRD may include nausea, vomiting, loss of appetite, fatigue and weakness, decreased urine output, and decreased mental sharpness. Smoking, obesity, high cholesterol and a family history of chronic kidney disease increase one’s risk of developing chronic kidney disease and eventually ESRD. Patients with ESRD undergo dialysis, the clinical purification of blood, to replace the lost function of the kidneys. The process involves creating a port through which blood leaves the body and returns. ESRD patients must complete the rigorous dialysis treatment three days a week, ideally for four hours a day. In addition to dialysis, ESRD patients must take medications regularly and follow a strict diet. This diet includes decreased fluid intake, eating foods high in protein, and lower in sodium, potassium and phosphorus. In addition, they have to increase carbohydrate intake.

The incidence and prevalence of ESRD have both increased during the past 30 years. Though, CKD is mostly seen in persons aged 65 and older, the National Health and Nutrition Examination survey (NHANES) reports that 16.8% of the United States population above the age of 20 has ESRD. Furthermore, men are at higher risk of getting ESRD than women. In terms of race and ethnicity, African Americans and Hispanics have the highest ESRD incidence rate. This may be related to the fact that these same groups are disparately affected by diabetes and hypertension.

It is common for ESRD patients to show changes in mood after the start of dialysis. This strenuous treatment may be the cause of depression and anxiety. Depression is a mood disorder that causes one to feel persistent hopelessness, unhappiness and inadequacy, and anxiety is a psychosomatic disorder can manifest itself in physical ways making dialysis hard or uncomfortable. Because dialysis patients must be stationary, being nervous or agitated can prevent completion of the treatment and can have adverse effects on health.

If mental health conditions such as anxiety and depression are barriers to treatment adherence in ESRD patients, this project hopes to bring attention to the impact of such mood disorders in order to help the patients do better overall.

Conclusion

Methodology

Dr. Daniel Cukor, Associate Professor in the Department of Psychiatry and Behavioral Science at SUNY Downstate Medical Center, was our mentor, and we used his data to study treatment adherence and mental health. Dr. Cukor’s data was previously collected from the ESRD patients in the Parkside Dialysis Clinic of SUNY Downstate Medical Center as part of a larger study on the treatment adherence in mental health. The data was collected from 57 Afro- Caribbean patients at the Parkside Dialysis Center. All 57 patients completed the surveys. The independent variables depression and anxiety are measured by the Becks Depression Inventory (BDI) with a score of 15 or greater, they were considered depressed. The State Trait Anxiety Inventory (STAI) with a score that was greater than or equal to 40, while medication adherence is measured by the Medication Adherence Reasons Scale (MARS) and the End Stage Renal Disease Adherence Questionnaire (ESRD-AQ). We were researching to determine the effects of anxiety and depression on medication adherence. We observed whether having depression, anxiety, or having both mental conditions has the greatest effect on medication adherence. The variables were measured by the Becks Depression Inventory (BDI), State Trait Anxiety Inventory (STAI) and the Medication Adherence Rating Scale (MARS). The BDI measures the level of depression. Higher scores indicate higher levels of depression. STAI measures the level of anxiety in an individual. For this research, the STAI’s “trait” component will measure a predisposition to react with anxiety in stressful situations. MARS measures how well patients adhere to their medications.

References

Results Our hypothesis was partially supported when looking at the results of the ESRD-AQ, but not the MARS. The ITAS did show differences, but they were not significant. The Adherence Questionnaire for behavior showed a statistically significant difference between the groups, both depressed and anxious had the largest significant difference between not depressed and anxious (p=.009) and either depressed and anxious (p=.080) and a p-value of .033. The ESRD-AQ (attitude) analysis indicated the greatest difference between the groups not depressed or anxious and either depressed or anxious with a significant difference of a p-value of .040 and a p-value of .113. The MARS shows that there is no statistical difference between the groups with a p-value of 0.419. The greatest difference is shown between the group not depressed or anxious and either depressed or anxious with a p-value of 0.177

• Asher, D.R., Ver Halen, N., & Cukor, D. (2012). Depression and non-adherence predict mortality in hemodialysis treated ESRD patients. Hemodialysis International. 16(3), 387-393. doi: 10.1111/j.1542-4758.2012.00688.x • Cukor, D., Ver Halen, N., Asher, D.R., Coplan, J.D., Weedon, J., Wyka, K.E., Saggi, S.J., & Kimmel, P.L. (2014).

Psychosocial intervention improves depression, quality of life, and fluid adherence in hemodialysis. Journal of the American Society of Nephrology. 25(1), 196-206. doi: 10.1681/ASN.2012111134.

• Preljwvic, V.T., Østhus, T.B., Sandvik, L., Opjordsmoen, S., Nordhus, I.H., & Dammen, T. (2013). Anxiety and depressive disorders in dialysis patients: association to health-related quality of life and mortality. General Hospital Psychiatry. 35(6), 619-624. doi: 10.1016/j.genhosppsych.

2013.05.006.

• Simic-Ogrizovic, S., Jemcov, T., Pejanovic, S., Stosovic, M., Radovic, M., & Djukanovic, L. (2009) Health-related quality of life, treatment efficacy, and hemodialysis patient outcome.

Renal Failure. 31(3), 201-206. doi: 10.1080/08860220802669842.

• Ver Halen, N., Cukor, D., Constantiner, M., & Kimmel, P. L. (2012). Depression and mortality in end-stage renal disease.

Current Psychiatry Reports. 14(1), 36-44. doi: 10.1007/ s11920-011-0248-5

Hypothesis Depression and anxiety would have a negative effect on dialysis patients’ adherence to medication. Higher rates of these mood disorders would cause a decrease in adherence as measured by the Medication Adherence Rating Scale (MARS).

Our hypothesis was only partially supported by the ESRDAQ analysis, but not the MARS. The direction of ITAS analysis supported the hypothesis, but it was not significant. Future research should use a larger sample size to examine whether treating anxiety and depression would result in significant findings. This research is important because early detection of anxiety and depression may limit negative outcomes of depression in dialysis patients.

Previous studies have focused on successful interventions in depressed ESRD patients which improved adherence. If we can address their fears of anxiety and depression the longer-term goal is to improve adherence to dialysis treatment. Furthermore, clinicians may benefit from an improved patient-doctor relationship with the ESRD patients and may be better equipped to discuss the importance of treatment adherence with patients. Also it will help doctors to know how to treat future patients who develop depression and anxiety.

Acknowledgements Special thanks to Doris Duke Charitable Foundation, Arthur Ashe Institute for Urban Health, and our mentor Dr. Daniel Cukor.

ESRD-AQ (Behavior)

ESRD-AQ (Attitude)

This work was supported by Doris Duke Charitable Foundation Grant #2011111 03272015 FINAL.PPT

Introduction

Diabetes Mellitus (DM) is a chronic condition which affects the body’s glucose (sugar) metabolism. Glucose is the primary source of energy for all cells in the body and it is also the brain's main source of fuel. If one does not maintain a healthy lifestyle, the chances for DM is increased. DM occurs when the pancreas begins to produce little to no insulin.

Therefore, when the body consumes too much sugar, the insulin in your bloodstream will not be able to absorb all of the sugar. Some risk factors for DM include obesity, environmental factors, family or personal history, dietary factors, inactivity, chronic diseases.

There are three types of DM: Type I, Type II, and gestational. Type II is the most common form of the disease which results in a decrease in the production of insulin by the pancreas and children and adults are affected due to growing rates of the obesity epidemic. Its symptoms include but are not limited to polyuria, polydipsia and polyphagia.

Diabetes Mellitus is becoming an increasing public health concern. As of 2012, 1.7 million new cases of its three variants have increased on a yearly basis. According to the CDC, 29.1 million Americans had diabetes within 2012, with 21 million diagnosed and another 8.1 million remained undiagnosed. Furthermore, 2014 statistics from the American Diabetes Association suggests that African Americans, Asian Americans, American Indians, Hispanics, and Pacific Islanders living in America have a higher prevalence of diabetes when compared to Caucasians5.

We studied under the guidance of our mentor, Dr. MaryAnn Banerji, MD- Chief Endocrinologist at the Diabetes Clinic at the SUNY Downstate University Hospital of Brooklyn. Dr. Banerji and her research team had previously conducted studies with patients diagnosed with diabetes. During one of the studies, Dr. Banerji noticed that some of her diabetic patients experienced an event, near-normoglycaemic remission, in which patients showed little to no symptoms of diabetes. They were given a strict health regimen which comprised of oral medication, exercise, and a healthy diet.

Many of the patients who had entered remission reportedly lowered their HbA1c (sugar) levels and their BMI.

Methodology

Conclusion

Using data collected by Dr. MaryAnn Banerji, and her endocrinology research fellows, we analyzed data from patients’ files in her clinic. We used the data of 50 of her patients were newly diagnosed with Diabetes Mellitus. We conducted descriptive statistics by using Paired Student’s t-test to compare pre- and post-BMI and HbA1c levels. We also conducted Independent Samples Student’s ttest. Data was calculated using SPSS and Microsoft Excel.

Results

Twenty-one of the 50 patients experienced remission; 29 of 50 patients did not. There was a mean pre-HbA1c level of 11.71% at Time 1 and post-HbA1c level of 8.332% at Time 2. We were 95% confident that the difference between these levels lies between 2.45 and 4.33. The average BMI at Time 1 and Time 2 ranged from 29.93 to 30.5. We were 95% confident that the difference between the BMI levels lie between 2.39 and 9.75. With a p-value of 0.494, there was no significant difference between BMI levels at Time 1 and Time 2. Our results showed those who experienced remission had an average gain in BMI of 0.16 and those who did not had a gain in BMI of 0.87. We are 95% confident that the difference between these 2 groups lies between 2.68 and 4.1. However, as the p-value is 6.7 this proves that there was no correlation between those who experienced remission and their change in BMI.

Pre-BMI Levels vs. Post-BMI Levels

Remission vs. Average ∆ in BMI

References 1. Mayo Clinic. (2013). Diabetes: Definition Retrieved from http://www.mayoclinic.org/diseases-conditions/diabetes/ basics/definition/con-2003309.

2. Mayo Clinic. (2013). Diabetes: Causes. Retrieved from http://www.mayoclinic.org/diseases-conditions/diabetes/ basics/causes/con-2003309.

3. Centers for Disease Control (2014). National diabetes statistics report, 2014. Retrieved from http://www.cdc.gov/ diabetes/pubs/statsreport14.htm//.

4. Genevra Pittman. (2012 December 18) Diabetes remission possible with diet, exercise. Reuters. Retrieved from http:// www.reuters.com/article/2012/12/18/us-diabetes-remissionidUSBRE8BH18Z20121218.

5. Banerji M.A., & Lebovitz, H.E. (1990). Remission in non-insulin-dependent diabetes mellitus: clinical characteristics of remission and relapse in black patients.

Medicine., 69(3), 176-185. Retrieved from http:// www.ncbi.nlm.nih.gov/pubmed/2345523.

6. Centers for Disease Control (2011). New cases of diagnosed diabetes among US patients adults aged 18-79 years, 1980-2009. Retrieved from http://www.cdc.gov/ chronicdisease/resources/publications/aag/ddt.htm

Acknowledgement Special thanks to our mentor, Dr. Banerji, and her fellows, Dr. Anthony Uglialoro, Ms. Amanda Alverado, MS2. The Arthur Ashe Institute for Urban Health (AAIUH) staff, Dr. Mary Valmont, Ms. Cassandra Raphael, Ms. Manpreet Kaur and Ms. Yamina Kezadri. We also wish to thank the Doris Duke Charitable Foundation’s Clinical Research Experiences for High School Students (CREHSS) Program for creating this opportunity for aspiring doctors and providing us with experiences and helping us develop our research skills.

Hypothesis

Newly diagnosed diabetic patients who go into nearnormoglycaemic remission will show greater weight loss than patients who do not show remission.

Dr. Banerji’s (2001) previous study showed that 42% of the population in her controlled experiment experienced remission. In our data set, patients were not in a controlled experiment (in a real world clinical setting); their time 2 testing wasn’t a set time. Our hypothesis was that patients who experience remission showed greater decreases in BMI; these results do not support our hypothesis. Remission is not associated with greater decreases in body weight.

Pre-HbA1c Levels vs. Post-HbA1c Levels

This work was supported by the Doris Duke Charitable Aug 26 2015 FINAL.PPT Foundation Grant # 2011111.

Perceptions of Health and HIV Testing Status Among Heterosexual African American Males in Brooklyn, NY Jean Poulard and Joshua Germain

Introduction The Human Immunodeficiency Virus (HIV) is one of the most discussed Sexually Transmitted Infections (STIs) in the United States today. This retro virus attacks the CD4+, T-cells of the immune system and decreasing the body’s ability to fight infections. A cure for this virus has not yet been discovered; however, it can be treated with anti-retroviral therapy (ART), a treatment which uses multiple antiretroviral drugs to control HIV infection.

Persons living with HIV are more vulnerable to diseases than individuals with normally functioning immune systems. Statistics from the Centers for Disease Control and Prevention suggest that in 2010, individuals infected with HIV through heterosexual sex make up 25% of all new infections. This is the second most prominent route of HIV-transmission in the United States. In fact, this issue has given a rise to the need of awareness in the community, especially in disproportionately affected areas such as Brooklyn, New York.

According to the Centers for Disease Control and Prevention, approximately 44% of these new Brooklyn cases of HIV were among African Americans. Within the Flatbush neighborhood , it has been reported that less than 1 in 3 individuals have been tested for HIV. In 2010, less than half of the population who have had multiple sex partners did not use a condom. This reveals a need for more research in order to devise strategies to increase testing.

Barbershop Talks with Brothers (BTWB) is a research projected conducted by SUNY Downstate’s School of Public Health in collaboration with the Arthur Ashe Institute for Urban Health (AAIUH). BTWB is a barbershop-based intervention to reach African American men in Central Brooklyn with HIV/AIDS risk-reduction messages.

BTWB reaches out to African American males and teaches them different ways of becoming proactive advocates for the prevention of HIV/AIDS and the promotion of health in the community. The program also seeks to help raise awareness of the disparities and incidences of the infection. Hopefully, with access to this information more African Americans will be vigilant and cautious with regards to HIV/AIDS.

Methodology

This study was part of the larger BTWB project of Dr. Tracey Wilson, Ph.D. Professor at SUNY Downstate Medical Center, School of Public Health and Dr. Michael Joseph, Ph.D., MPH, Interim Chair, Department of Environmental and Occupational Health Sciences and Assistant Professor at SUNY Downstate, School of Public Health. Dr. Michael Joseph, Dr. Yolene Gousse, Director of Community Based Research of SUNY Downstate Medical Center-STAR Program, and Brignel Camilien, Program Coordinator, BTWB, AAIUH, were our mentors for this project. This data was collected through recruitment in barbershops. The recruiters approached the customers and asked them to take a screener to qualify them for participation. The focus population for this study were African American males who were sexually active, heterosexual, and 18 years or over. If eligible, they were recruited to come to SUNY Downstate Medical Center, where they took an Audio Computer Assisted Self Interview baseline survey which was created from the HIV Knowledge Questionnaire 4+ (HIV KQ4+) and they were provided with a monetary incentive. They were then given an intervention based on the themes of “Wake-Up, Gear-Up and Build-Up.” The intervention included a one-on-one group interaction where an instructor (a BTWB researcher) explained the different types of transmission, effects, and prevention methods of HIV/AIDS to the participants. The same survey was administered to these participants three months and again six months later.

The categorical data was used to assess how factors (such as education, health insurance, and living status) could be used as support for the participant’s perception of health. The perception of health was used as the independent variable and compared with the likelihood of these participants seeking to get tested to find whether there is any association. We looked at each of the covariates to see whether associations existed using a Chi Square. To determine the magnitude and direction of associations, odds ratios and associated 95% confidence intervals were calculated.

Results

Our results indicate that there was not a significant association between attitudes towards perceptions of health and HIV testing status [χ₂=0.20, p= 0.65, OR=0.73, 95% CI (0.15, 2.81)] (see Figure 1). Fifty-nine of the participants, 74% , had been tested, 21 men, 26% , had not (Figure 2). “My own health is important to my community” (See Figure 3). This indicates that those who agreed that their health is important to their community were 27% less likely to get tested than those who disagreed.

There were also non-significant associations for: “I Can Make a Difference in my Community,” 76% agreed with this statement, 16% were unsure, 8% disagreed. χ₂= 0.37, p=0.55OR=1.41, 95% CI (0.43, 4.37); Education status [(χ₂=0.81, p=0.36, OR=1.86, 95% CI (0.50, 8.91)]; and Health insurance status [χ₂=0.94, p=0.33, OR= 1.41, 95% CI (0.58, 4.58)].

Figure 1

Displays an independent variable’s (My own health is important to my community) effect on HIV testing.

Conclusion Our hypothesis, that men with positive attitudes towards the importance of health are more likely to report getting tested for HIV, was not supported. A small sample size is one explanation for these findings.

However, HIV continues to be a prevalent issue in our community. It is important to address it in order to prevent further transmission of the infection. Members of the community can benefit by receiving the tools and the resources to be able to not only reduce their own risks, but also be advocates for prevention in their own communities.

The research supports the idea that insurance is not necessarily a significant factor in a person’s decision to get tested for HIV.

References

• Adaora, A.A., & Schoenbach. V.J. (2005). Social context, sexual networks, and racial disparities in rates of sexually transmitted infections. The Journal of Infectious Diseases, 191:S115-S122.

Retrieved from http://jid.oxfordjournals.org/content/191/ Supplement_1/S115.full.pdf.

• Bout, M.L., Docena, J.P., Ratemo, B.K., Bittner, M.J., Burlew, J.T., Nuritdinov, A.R., & Robbins, J.R. (2014). Beyond race and place: distal sociological determinants of HIV disparities. PLoS One, 9(4), e91711. doi: 10.1371/journal.pone.0091711.

• Centers for Disease Control. (2014). Basic Statistics. Retrieved from http://www.cdc.gov/hiv/basics/statistics.html • Frye, V., Henny, K., Bonner, S., Williams, K., Bond, K.T., Hoover, D.R, … Koblin, B.A. & the Straight Talk Study Team. (2012).

“Straight Talk” for African American heterosexual men: results of a single arm behavioral intervention trial. AIDS Care, 25(5): 627-¬631. doi: 10.1080/09540121.2012.722605.

• Olson E.C., Van Wye G., Kerker B., Thorpe L., & Frieden T.R. Take Care Flatbush. NYC Community Health Profiles, Second Edition: 2006; 14(42):1-16. Retrieved from http://www.nyc.gov/html/ doh/downloads/pdf/data/2006chp-207.pdf.

• Van Ryn, M., & Fu, S.S. (2003) Paved with good intentions: do public health and human service providers contribute to racial/ethnic disparities in health?. American Journal of Public Health, 93(2), 248-255. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/ PMC1447725/.

Acknowledgements

Hypothesis Men with positive attitudes towards the importance of health are more likely to report getting tested for HIV. Figure 2

Represents the dependent variable among the study population (n=80)

Figure 3

Represents the independent variable among the study population (n=80) that measures men’s perception of health in their community

Special thanks to our mentors Dr. Michael A Joseph, Dr. Yolene Gousse, Mr. Brignel Camilien, and other BTWB staff, the Doris Duke Charitable Foundation, and the Arthur Ashe Institute for Urban Health staff that worked with us summer 2014.

This work was supported by Doris Duke Charitable Foundation Grant #2011111 03302015 FINAL

Duke Alumni Spotlight (L-R) NY1 Newcaster Cheryl Willis with the CVS $2000 Scholarship recipient Genesis Smith (Duke 2013/2014) at the institute’s gala Sportsball 2014.

Chief Executive Officer, Ruth C. Browne, Sc.D Deputy Director of Research & Training Marilyn A. Fraser White, MD

HSA Staff: Associate Director for Health Science Education Mary Valmont, Ph.D Communications Director Catherine Herrera High School Education Coordinator Vanessa Vales, MAT Middle School Education Coordinator Alexander Joseph Middle School Assistant Coordinator Peradeba Raventhirarajah

Newsletter Design Catherine Herrera Editor Mary Valmont, Ph.D

(L-R) Likowsky Desir (Duke 2013/14) with Katrina Adams, USTA, at the institutute’s annual gala, Sportsball 2014. Mr. Desir was the recipient of the USTA’s $1968 award which commemorates the first year that Arthur Ashe won the US Open.

(L-R) Asia Wynn (Duke 2012/13), Nicole Mclean (HSA Alumna 2009), Dr. Michael Joseph (Duke mentor since 2014), Frederique Jean Baptiste and Genesis Smith (Duke 2013/14), at SUNY Downstate’s Annual Research Day 2016. Genesis and Asia are Dr. Joseph’s undergrad research interns on a 2 year NIH funded grant.

Clinical Research Experiences for High School Students 2014 - 2015 Grant# 201111

Student Researchers: Annecia Diamond Zekaiah Fox Joshua Germain Marcell Howard Malik Johnson Aija Jones Jean Poulard Susan Schaefer Kenyetta Smith Momina Tariq