Audrey J. Brooks, PhDUniversity 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

BackgroundRising 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.

PurposeTo 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?

MethodsSecondary data analysis of baseline CAB data

from www.ctndatashare.orgCTN-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)

MeasuresHIV Risk Behavior Scale (HRBS)

Sex and Drug Risk Behaviors CompositesIndividual sex and drug risk items

ASI-Lite CompositesAlcohol, Drug, and Psychiatric Symptom Severity,

Family/Social Relationships, Legal ProblemsASI-Lite derived variables

DemographicsHousing 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 variablesGender 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%)

FemaleN=790 (45%)

TotalN=1429

Age 37.6 ±10.2 36.6 ±9.1 37.2 ±9.7Education 12.2 ±1.9 12.0 ±2.1 12.1 ±2.0Ethnicity* 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%)Living with Partner

306 (38.7%) 244 (38.2%) 550 (38.5%)

*p<.0001

Participant CharacteristicsCharacteristic Male

N=790 (55%)

FemaleN=790 (45%)

TotalN=1429

Employment** 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%)Primary Drug* 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 187 (23.7%) 132 (20.7%) 319(22.3%)*p<.0001; +p<.01

HIV Sex Risk Behaviors Past 30-days

64

13

61

20

010203040506070

Sexually Active N=892 ≥ 2 Partners N=144*

Perc

ent o

f Sam

ple

Males

Females*

*p<.008

N=790N=639

N=504N=388

Unprotected Sex75

49

64

8482

4954

77

0102030405060708090

Regular Partner N=659*

Casual Partner N=81

Trading Sex N=47

Anal Intercourse

N=50

MalesFemales

*p<.016

**

N=484

N=357 N=83

N=31

N=39

N=41

N=82

N=31

HIV Drug Risk Behaviors Past 30-days

32

68

33

60

24

62

36

54

0 10 20 30 40 50 60 70 80

Any IDU* N=401

Daily IDU N=264

Needle Sharing N=118

Inconsistent Cleaning N=206

Perc

ent o

f Sam

ple

MalesFemales

*p<.0008

**

N=790

N=639

N=250

N=151

N=221

N=129

N=227

N=132

HIV Risk Composites 8.7

5.8

8.4

6.1

0123456789

10

Drug Risk N=332 Sex Risk* N=867

MalesFemales

*p<.043

**N=208

N=124N=488

N=379

Sex Risk Behavior Gender EffectsVariable

High risk:OR (95% CI)

High or moderate risk: OR (95% CI)

χ2 (df) p-value

Alcohol use composite  women 1.11 (1.03-

1.20)7.77 (1) 0.005

men 0.98 (0.90-1.06)

0.32 (1) 0.57

Psychiatric compositewomen 1.14 (1.06-

1.23) 11.45

(1)0.0007

men 0.96 (0.89-1.04)

0.84 (1) 0.36

Family/social compositewomen 1.03 (0.92-

1.14)1.01 (0.91-

1.11) 0.23 (1) 0.89

men 0.80 (0.70-0.93)

1.01 (0.91-1.13)

11.1 (2) 0.004

Drug Risk Behavior Gender Effects

Variable Linear regression

coefficient (SD)

t p-value

Alcohol use compositewomen 0.56 (0.28) 2.01 0.045

men -0.24 (0.21) -1.14 0.26

Main EffectsSex Risk Behaviors

Stimulant useDrug use severitySexual abuse history onlySexual and physical abuse historyLegal problems

Drug Risk BehaviorsDrug use severitySexual abuse history negatively related

Summary of FindingsWomen 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.

ConclusionsFindings 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.