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![Page 1: Arnold School of Public Health Health Services, Policy, and Management 1 Drug Treatment Disparities Among African Americans Living with HIV/AIDS Carleen.](https://reader035.fdocuments.us/reader035/viewer/2022062517/56649f005503460f94c157e9/html5/thumbnails/1.jpg)
1Arnold School of Public HealthHealth Services, Policy, and Management
Drug Treatment Disparities Among African Americans
Living with HIV/AIDS
Carleen H. Stoskopf, Sc.D.
William Pearson, Ph.D.
Jong Deuk Baek, Ph.D.
Yunho Jeon, M.S.
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2Arnold School of Public HealthHealth Services, Policy, and Management
Background
• Many studies have identified disparities in health status, health care access, and health care utilization by race/ethnicity.
• In the late 1990s, clinical trials found the high efficacy of Highly Active Antiretroviral Therapy (HAART).
• Researchers found that African Americans were significantly less likely to use newer antiretroviral regimens (e.g., protease inhibitors and NNRTIs).
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3Arnold School of Public HealthHealth Services, Policy, and Management
Background continued
• Several studies found that racial/ethnic minorities were less likely to use drugs for opportunistic diseases than whites (e.g., PCP and TB/MAC prophylaxis).
• This study explores changes in use of HAART and drugs for opportunistic diseases and to determine factors that influence the use of HAART by race/ethnicity.
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4Arnold School of Public HealthHealth Services, Policy, and Management
HIV Cost and Services Utilization Study (HCSUS) data
• Nationally representative sample
• Adults in care for HIV
• Multi-stage design (n = 4,042)– Geographical– Medical provider– Patients
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5Arnold School of Public HealthHealth Services, Policy, and Management
HCSUS data
• Panel study– Baseline: January ’96 - March ’97
• N = 2,864 (71%)
– First follow-up: December ’96 - July ’97• N = 2,466 (61%)
– Second follow-up: August ’97 - January ’98• N = 2,267 (56%))
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6Arnold School of Public HealthHealth Services, Policy, and Management
Independent Variables
• Age
• Gender
• Race
• Mode of HIV exposure
• Household composition
• Employment status
• Educational attainment
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7Arnold School of Public HealthHealth Services, Policy, and Management
Independent Variables
• Insurance status
• Household income
• Lowest reported CD4 cell count
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8Arnold School of Public HealthHealth Services, Policy, and Management
Dependent Variables
• HAART: Coded as a positive response if the person indicated taking HAART in the past six months– Combinations of NRTI plus certain PI or NNRTI
– 99% of the sample met the published eligibility criteria in 1996 for HAART
• CD4 < 500 cells/μl OR HIV RNA > 10,000 copies/ml OR symptomatic HIV or AIDS
• Handout 1
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9Arnold School of Public HealthHealth Services, Policy, and Management
Dependent VariablesOpportunistic Infections Rx
• Cytomegalovirus (CMV)– Common herpes virus causing retinitis and colitis
• Pneumocystic Carinii Pneumonia (PCP)– Infection of the lungs caused by Pneumocystis carinii
• Tuberculosis (TB)– Bacterial infection, Mycobacterium tuberculosis
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10Arnold School of Public HealthHealth Services, Policy, and Management
Dependent VariablesOpportunistic Infections Rx
• Mycobacterium Avium Complex– Bacterial infections, Mycobacterium avium,
Mycobacterium intracellulare
• Fungal Infections
• Herpes Simplex Viruses – HSV-1, HSV-2
• Immune System Boosters
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11Arnold School of Public HealthHealth Services, Policy, and Management
Analysis
• Description of Sample
• National estimates
• Bivariate analysis
• Multivariate analysis (Odds Ratio)
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12Arnold School of Public HealthHealth Services, Policy, and Management
Results of Analyses
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13Arnold School of Public HealthHealth Services, Policy, and Management
Sample Characteristics of Respondents
• Distribution of the sample respondents is consistent for all three surveys
• All sample frequencies decrease across surveys except for Medicare recipients and some CD4 counts.
– Table 1
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14Arnold School of Public HealthHealth Services, Policy, and Management
Age (Baseline)
50+ 11.42%
18-34 34.18%
35-49 54.39%
Sample Characteristics of Respondents
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15Arnold School of Public HealthHealth Services, Policy, and Management
Gender (Baseline)
Male 77.44%
Female 22.56%
Sample Characteristics of Respondents
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16Arnold School of Public HealthHealth Services, Policy, and Management
Race (Baseline)
White 49.24%
Blk/Afr.A32.77%
Other 3.22% Hispanic
14.77%
Sample Characteristics of Respondents
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17Arnold School of Public HealthHealth Services, Policy, and Management
Exposure (Baseline)
Heterosexual
18.42%
Other8.87% IVDA
24.12%
M sx M 48.59%
Sample Characteristics of Respondents
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18Arnold School of Public HealthHealth Services, Policy, and Management
Living With (Baseline)
With other 47.51%
Female part 5.18%
Male part 31.89%
Spouse 15.42%
Sample Characteristics of Respondents
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19Arnold School of Public HealthHealth Services, Policy, and Management
Employment (Baseline)
Not work 8.23%
Disabled 47.42% Unemployed
7.08%
Full/part 37.28%
Sample Characteristics of Respondents
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20Arnold School of Public HealthHealth Services, Policy, and Management
Education (Baseline)
BA, BS 19.26%
Some HS, 24.94%
Some college 28.36%
HS deg 27.44%
Sample Characteristics of Respondents
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21Arnold School of Public HealthHealth Services, Policy, and Management
Insurance (Baseline)
Medicare 19.16%
No Insurance
19.76%
Private 16.53%
Private (HMO) 15.33%
Medicaid 29.22%
Sample Characteristics of Respondents
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22Arnold School of Public HealthHealth Services, Policy, and Management
Income (Baseline)
$10000-$25000 25.99%
$5000-$10000 25.82%
$0-$5000 19.72%
>$25000 28.47%
Sample Characteristics of Respondents
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23Arnold School of Public HealthHealth Services, Policy, and Management
CD 4 Cell Count (Baseline)
0-49 23.59%
>=500 9.49%
200-499 37.45%50-199
29.48%
Sample Characteristics of Respondents
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24Arnold School of Public HealthHealth Services, Policy, and Management
HAART Use in the Three Consecutive Surveys
• Test of Independence (Chi square)– Proportions of HAART use were dramatically
increased (sample frequencies and estimated population weighted percentages) across all three surveys.
– All independent variables are statistically significant except age in the two follow-ups.
– Table 2
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25Arnold School of Public HealthHealth Services, Policy, and Management
Weighted Population Estimate (%) of HAART Use by Race/Ethnicity
0%
25%
50%
75%
100%
White 33.16% 47.88% 65.35%
African American 9.82% 24.15% 50.95%
Hispanic 20.56% 38.68% 60.40%
Other 27.41% 50.67% 61.78%
Baseline 1st Follow-up 2nd Follow-up
• African Americans are less likely to use HAART than other racial/ethnic groups.
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26Arnold School of Public HealthHealth Services, Policy, and Management
0%
25%
50%
75%
100%
Male 26.00% 41.96% 62.33%
Female 14.77% 28.38% 51.45%
Baseline 1st Follow-up 2nd Follow-up
Weighted Population Estimate (%) of HAART Use by Gender
• Females are less likely to use HAART than males, but the gap closes over the three surveys.
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27Arnold School of Public HealthHealth Services, Policy, and Management
Weighted Population Estimate (%) of HAART Use by Employment Status
0%
25%
50%
75%
100%
Full/ part 26.36% 43.63% 61.80%
Unemployed 4.68% 22.77% 44.66%
Disabled 25.97% 38.75% 61.74%
Not work 12.08% 29.87% 52.58%
Baseline 1st Follow-up 2nd Follow-up
• Those who are employed full time, or those who are disabled, are more likely to use HAART.
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28Arnold School of Public HealthHealth Services, Policy, and Management
Weighted Population Estimate (%) of HAART Use by Education
0%
25%
50%
75%
100%
Some HS, 13.40% 26.63% 53.96%
HS deg 23.87% 36.85% 57.89%
Some college 25.04% 41.11% 60.27%
BA, BS 33.59% 53.98% 69.21%
Baseline 1st Follow-up 2nd Follow-up
• Those who are more highly educated are more likely to use HAART.
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29Arnold School of Public HealthHealth Services, Policy, and Management
Weighted Population Estimate (%) of HAART Use by Insurance Status
0%
25%
50%
75%
100%
No Insurance 10.09% 32.25% 55.49%
Medicaid 17.40% 32.57% 54.74%
Private (HMO) 29.94% 43.64% 64.96%
Private 40.49% 56.22% 68.19%
Medicare 26.65% 36.67% 60.00%
Baseline 1st Follow-up 2nd Follow-up
• Those persons who have private insurance are more likely to use HAART.
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30Arnold School of Public HealthHealth Services, Policy, and Management
Weighted Population Estimate (%) of HAART Use by Income
0%
25%
50%
75%
100%
$0-5000 11.16% 30.27% 49.84%
$5000-10000 19.36% 31.09% 57.68%
$10000-25000 22.84% 38.64% 59.63%
>$25000 36.28% 51.68% 68.55%
Baseline 1st Follow-up 2nd Follow-up
• Those with higher incomes are more likely to use HAART.
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31Arnold School of Public HealthHealth Services, Policy, and Management
Weighted Population Estimate (%) of HAART Use by CD 4 Cell Count
0%
25%
50%
75%
100%
>=500 8.38% 15.77% 31.68%
200-499 14.44% 30.08% 52.31%
50-199 30.60% 47.93% 67.24%
0-49 34.94% 48.97% 67.80%
Baseline 1st Follow-up 2nd Follow-up
• Those with lower CD4 counts are more likely to use HAART.
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32Arnold School of Public HealthHealth Services, Policy, and Management
Rx for Opportunistic Diseases in the Three Consecutive Surveys
• Test of Independence (Chi square) for Race/Ethnicity– African Americans are the least likely group to use
drugs for opportunistic diseases.– This finding is true across all three surveys, except
for TB treatment in the second follow-up survey.
– Table 3
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33Arnold School of Public HealthHealth Services, Policy, and Management
Multivariate Logistic RegressionUse of HAART
• The multivariate logistic Regression allows for controlling the influence of the various independent variables.
• Race (being African American) is consistently statistically significant across all three surveys. When compared to Whites, AA are significantly less likely to have used HAART in the last six months.– Odds ratios are 0.32, 0.54, and 0.70, respectively
– Table 4
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34Arnold School of Public HealthHealth Services, Policy, and Management
Multivariate Logistic RegressionUse of HAART
• Other significant findings include:– Men having sex with men are more likely to use
HAART at the second follow-up– Those who are unemployed or not working are less
likely to use HAART at the baseline survey, those not working are still less likely to use HAART at the first follow-up.
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35Arnold School of Public HealthHealth Services, Policy, and Management
Multivariate Logistic RegressionUse of HAART
– As compared to the uninsured, those with Medicaid, private insurance, private HMO, or Medicare were significantly more likely to be receiving HAART at the baseline survey.
– At the second survey (first follow-up) only those with private insurance had a statistically significant advantage
– As expected, those with the lowest CD4 counts were significantly more likely to receive HAART therapy.
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36Arnold School of Public HealthHealth Services, Policy, and Management
Multivariate Logistic Regression Rx for Opportunistic Diseases
Baseline Survey
African Americans were significantly less likely than Whites to receive drug treatment for these disease categories:
Cytomegalovirus Pneumocystis
Tuberculosis Fungal Infections
Herpes Immune System Booster
Table 5 - 10
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37Arnold School of Public HealthHealth Services, Policy, and Management
Multivariate Logistic Regression Rx for Opportunistic Diseases
• Second survey (first follow-up)– At the second survey, African Americans were
significantly less likely to receive drug treatment for all disease except pneumocystis. These include:
– Cytomegalovirus Tuberculoses– Fungal Infections Herpes
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38Arnold School of Public HealthHealth Services, Policy, and Management
Multivariate Logistic Regression Rx for Opportunistic Diseases
• Third survey (second follow-up)– By the third survey, African Americans were still
significantly less likely than Whites to receive drug treatment for:
Cytomegalovirus Tuberculosis
Fungal Infections
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39Arnold School of Public HealthHealth Services, Policy, and Management
Conclusions
• African Americans were consistently less likely to receive appropriate treatment for HIV/AIDS and other infections associated with this disease as HAART was introduced.
• Over time, the racial disparities in HAART use decrease, but statistical differences remain between African Americans and Whites.