Transcript Gender differences in the rates and correlates of HIV risk

Audrey J. Brooks, PhD
University of Arizona
CA-AZ node
Gender SIG Collaborators
• Christina S. Meade, Ph.D., NNE node
• Jennifer Sharpe Potter, Ph.D., M.P.H., NNE node
• Yuliya Lokhnygina, Ph.D. , DCRI
• Donald A. Calsyn, Ph.D. , PNW node
• Shelly Greenfield, M.D., M.P.H., NNE node
• Paul Wakim, PhD, NIDA representative
Background
 Rising rates of HIV in women highlight the need to
identify unique factors associated with risk behaviors
in women to help inform risk reduction interventions.
 Evidence of gender differences in frequency of HIV
risk behaviors.
 Multiple risk factors associated with HIV risk
behaviors have been identified in the literature.
 Few studies have examined whether risk factors vary
by gender.
Purpose
 To examine gender differences in the rates and correlates of
HIV sexual and drug risk behaviors in a sample of clients
participating in 5 multi-site trials of the NIDA Clinical
Trials Network.
 To test whether multiple risk factors for HIV risk behaviors
differ by gender.
 Does gender moderate the impact of stimulant use, alcohol
and drug severity, psychiatric severity, abuse history,
family/social relationships, legal status and housing stability?
Methods
 Secondary data analysis of baseline CAB data from
www.ctndatashare.org
 CTN-0001/ CTN-0002 - Buprenorphine/Naloxone
versus Clonidine for Inpatient/ Outpatient Opiate
Detoxification (Ling et al., 2005)
 CTN-0005 – Motivational Interviewing to Improve
Treatment Engagement and Outcome in Outpatient
Substance Users (Carroll et al., 2006)
 CTN-0006 / CTN-0007 - Motivational Incentives for
Enhanced Recovery in Stimulant Users in Drug Free
Methadone Maintenance Clinics (Petry et al., 2005;
Pierce et al., 2006)
Measures
 HIV Risk Behavior Scale (HRBS)
 Sex and Drug Risk Behaviors Composites
 Individual sex and drug risk items
 ASI-Lite Composites
 Alcohol, Drug, and Psychiatric Symptom Severity,
Family/Social Relationships, Legal Problems
 ASI-Lite derived variables
 Demographics
 Housing Stability (length at address)
 Stimulant use:

stimulant only, stimulants + opioids, opioids only, other drug use
 Lifetime abuse:
 physical only, sexual only, both physical + sexual
Statistical Analysis
 Gender differences in sociodemographic characteristics and HIV
risk behaviors
 Chi-square tests for categorical variables and Wilcoxon two-sample
tests for continuous variables
 Gender differences in risk factors associated with HIV risk
behaviors
 Ordinal logistic regression analysis using partial proportional odds
model were conducted to identify variables associated with HIV sex
risk composite
 Linear regression models were conducted to identify variables
associated with HIV drug risk composite


Models adjusted for age, gender, education, ethnicity, living
arrangements
Gender interaction tested first
 The ASI composite results are described using a clinically
meaningful difference unit (0.1) as the measurement unit
Participant Characteristics
Characteristic
Male
N=790 (55%)
Female
N=790 (45%)
Total
N=1429
Age
37.6 ±10.2
36.6 ±9.1
37.2 ±9.7
Education
12.2 ±1.9
12.0 ±2.1
12.1 ±2.0
White
371 (47.0%)
325 (50.9%)
696 (48.7%)
African-American
276 (34.9%)
251 (39.3%)
527 (36.9%)
Hispanic
68 (8.6%)
13 (2.0%)
81 (5.6%)
Other
75 (9.5%)
50 (7.8%)
125 (8.8%)
306 (38.7%)
244 (38.2%)
550 (38.5%)
Ethnicity*
Living with Partner
*p<.0001
Participant Characteristics
Characteristic
Male
N=790 (55%)
Female
N=790 (45%)
Total
N=1429
Full-time
431 (54.6%)
270 (42.3%)
701 (49.1%)
Part-time
122 (15.4%)
110 (17.2%)
232 (16.2%)
Other
237 (30.0%)
259 (40.5%)
496 (34.7%)
Heroin/Opiates
144 (18.2%)
99 (15.5%)
243 (17.0%)
Stimulants
144 (18.2%)
161 (25.2%)
305 (21.3%)
Stimulants/Opiates 315 (39.9%)
247 (38.6%)
562 (39.4%)
Other drug
132 (20.7%)
319(22.3%)
Employment**
Primary Drug*
*p<.0001; +p<.01
187 (23.7%)
Percent of Sample
HIV Sex Risk Behaviors Past 30-days
70
60
50
40
30
20
10
0
64
61
Males
N=790
N=639
N=504
Sexually Active N=892
*p<.008
13
20*
N=388
≥ 2 Partners N=144*
Females
Unprotected Sex
90
80
70
60
50
40
30
20
10
0
75*
84
82*
77
64
N=484
54
49 49
N=31
N=39
N=357
N=83
N=41
N=31
Females
N=82
Regular
Partner
N=659*
*p<.016
Casual
Trading Sex
Partner N=81
N=47
Males
Anal
Intercourse
N=50
HIV Drug Risk Behaviors Past 30-days
80
68
Percent of Sample
70
62
60
60
N=250
50
40
32 *
30
20
10
54
N=151
33 36
24*
N=227
N=132
N=221
N=790
N=639
Females
N=129
0
Any IDU*
N=401
*p<.0008
Daily IDU
N=264
Needle
Sharing
N=118
Males
Inconsistent
Cleaning
N=206
HIV Risk Composites
10
9
8
7
6
5
4
3
2
1
0
8.7 8.4
N=208
6.1*
N=488
N=124
N=379
Drug Risk N=332
*p<.043
5.8 *
Sex Risk* N=867
Males
Females
Sex Risk Behavior Gender Effects
Variable
High risk:
OR (95% CI)
High or moderate
risk: OR (95% CI)
2
χ (df)
p-value
7.77 (1)
0.005
0.32 (1)
0.57
11.45 (1)
0.0007
0.84 (1)
0.36
1.01 (0.91-1.11)
0.23 (1)
0.89
1.01 (0.91-1.13)
11.1 (2)
0.004
Alcohol use composite
women
1.11 (1.03-1.20)
men 0.98 (0.90-1.06)
Psychiatric composite
women 1.14 (1.06-1.23)
men 0.96 (0.89-1.04)
Family/social composite
women 1.03 (0.92-1.14)
men 0.80 (0.70-0.93)
Drug Risk Behavior Gender Effects
Variable
Linear regression
coefficient (SD)
Alcohol use composite
women
0.56 (0.28)
men
-0.24 (0.21)
t
p-value
2.01
-1.14
0.045
0.26
Main Effects
 Sex Risk Behaviors
 Stimulant use
 Drug use severity
 Sexual abuse history only
 Sexual and physical abuse history
 Legal problems
 Drug Risk Behaviors
 Drug use severity
 Sexual abuse history negatively related
Summary of Findings
 Women engaged in higher risk sexual behavior overall,





were more likely to have multiple partners, and have
unprotected sex with regular partners.
Alcohol and psychiatric severity were associated with
engaging in higher risk sexual behaviors for women.
Alcohol use severity associated with engaging in higher risk
drug behaviors for women.
Men with impaired family/social relationships were less
likely to engage in high risk sexual behavior.
Men more likely to inject drugs.
Confirmed relationship between stimulant use, drug
severity, abuse history, and legal severity and risk behaviors
in treatment-seeking sample.
Conclusions
 Findings consistent with other studies reporting
higher rates of high risk sexual behavior for women.
 Studies incorporating gender into the analyses have found
similar relationships between gender and HIV risk factors.
 Underscores the importance of examining the role of
gender in studies of HIV risk behavior.
 Comprehensive assessment of HIV risk behaviors needs to
occur at treatment entry.
 In addition to targeting women and men separately, the
content of the intervention may need to reflect the unique
risk factors.