Transcript Gender Differences: Treatment

Cora Lee Wetherington, Ph.D.
Women & Gender Research Coordinator
National Institute on Drug Abuse
Women Across the Life Span
Conference
July 12-13, 2004
Baltimore Marriott Inner Harbor
Gender Differences in Drug Abuse
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Gender Differences: The Numbers
Gender Differences: Animal Models
Gender Differences: Menstrual Cycle
Gender Differences: Predictors & Progression
Gender Differences: Treatment
Past Month Illicit and Prescription
Drug Use by Gender: 2002
12%
Males
10%
Females
8%
6%
4%
2%
0%
Any Illicit
Prescription
Prescription
Drug Use
Drug Abuse
Drug Abuse
12 & older
12 & older
12 – 17 yrs
2002 National Survey on Drug Use and Health, SAMHSA, 2003.
Gender Differences: The Numbers
Population prevalence data

Drug use: greater for males than females

Drug dependence: greater for males than females
 9.2% Males

5.6% Females
(1994 Nat’l Comorbidity Survey)
Are females less vulnerable to drug abuse than males?
Gender Differences: The Numbers
Calculate use prevalence only among
individuals with opportunity to use
Van Etten et al. (1999)
Study drugs: Marijuana, Cocaine, Heroin, Hallucinogens
Data Source: 1993 NHSDA
Findings:
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
Opportunity to use: greater for males than for females.
Among individuals with opportunity to use :
males and females are equally likely to initiate use.
Percent
70
Opportunity to Use Drugs
60
Male
50
Female
40
30
20
10
0
Marijuana
Cocaine
Hallucinogens
Heroin
Percent Use Given an Opportunity
80
Male
Female
70
Percent
60
50
40
30
20
10
0
Marijuana
Cocaine
Hallucinogens
Heroin
Gender Differences: The Numbers
Calculate Dependence Only among Users:

Males and females = likely to become dependent on
cocaine
tobacco
heroin
inhalants
hallucinogens
analgesics
Anthony et al. (1994)
(Data Source: National Comorbidity Survey)
Gender Differences: The Numbers
Calculate Dependence Only among Users:

Males more likely than females to become dependent on
marijuana
alcohol
Anthony et al. (1994)
Data Source: National Comorbidity Survey
Gender Differences: The Numbers
Calculate Dependence Only among Users:
•
Females more likely than males to become dependent on
anxiolytics or
sedatives or
hypnotics
Anthony et al. (1994)
(Data Source: National Comorbidity Survey)
Gender Differences: The Numbers
Do prevalence data, adjusted for opportunity,
suggest that females are less vulnerable to
drugs than males ?
No. If females are offered drugs, they are as likely as males to
use them: marijuana, cocaine, heroin, hallucinogens.
No. If females use drugs, they are as likely as males to
become dependent; exceptions in both directions.
Caveat: Females are less likely to receive drug offers.
Gender Differences: The Numbers
All Age Groups
vs.
Adolescents
Gender Differences: The Numbers
Monitoring the Future Survey
1975 - Present
Annual prevalence of “illicit drug use other than marijuana”
• 12th graders:
> for boys than girls
(exceptions: 1975 & 1981 girls > boys)
• 10th graders:
> for girls than boys (since 1991)
• 8th graders:
> for girls than boys (since 1991)
Gender Differences: The Numbers
Dependence Among Adolescents Users:
(Aged 12-17)
Alcohol:
males = females
Marijuana: males = females
Nicotine:
males = females
Cocaine : females > males
17.4% vs. 4.7%
Kandel et al. (1997 )
Data Source: 1991, 1992, 1993 NHSDA
Gender Differences: The Numbers
Patterns of Drug Use
After Initial Drug Use, Females May Proceed
To Addiction More Rapidly and Use Drugs
More Often Than Males…
Women are more likely than men to be daily users:
Cocaine
Heroin
Sedatives & Barbiturates
Wechsberg
DATOS
(1998) -- DATOS
al. (1998)
et al.
Wechsberg et
Women use cocaine & heroin more times per week than men:
Women
Men
Cocaine Heroin
6.7
5.4
5.2
4.6
Fiorentine
(1997)
al. (1997)
et al.
Fiorentine et
Women use more grams of cocaine per week than men:
Women: 14.0 grams
9.5 grams
Men:
Hayes
(1999)
al. (1999)
et al.
Hayes et
Gender Differences: The Numbers
CAVEAT: Usage data are from treatment samples.
Perhaps female heavy users are more likely than male
heavy users to present for treatment.
Gender Differences: The Numbers
DATOS Intake Data (n=10,010, 96 programs, 11 cities, 4 modalities)
Women, compared to men, were
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
less likely to have graduated from high school
almost half as likely to be employed
more likely to report
• prior drug treatment
• depression, suicidal attempts & thoughts
• being troubled over current emotional/psychological problems
• health problems
• weekly or daily illegal activity (but < likely to be CJ involved)
more likely to report physical, sexual abuse or both
•
in year prior to treatment
•
occurring more than a year prior to treatment
Wechsberg et al. (1998)
Gender Differences: The Numbers
Myth: Females are less vulnerable to drugs than males
1. If given the opportunity, females are as likely as males
• to use drugs
• to become dependent
2. Adolescent females, compared to males,
• in 8th and 10th grades are more likely to use “any illicit
drugs other than marijuana”
• are more likely to become dependent on cocaine
Gender Differences: The Numbers
Myth: Males are more vulnerable than females
3. Use patterns suggest that women
•
are more likely to use daily – cocaine, heroin, barbiturates
•
use more times per week – cocaine & heroin
•
use more grams per week – cocaine
4. Women presenting for treatment have poorer levels of functioning.
• Does this reflect a greater vulnerability to the impact of drugs
on women? (i.e., consequence)
• Are women with poorer levels of functioning more vulnerable to drugs
than men with poorer levels of functioning? (i.e., etiologic)
Gender Differences in Drug Abuse
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Gender Differences: The Numbers
Gender Differences: Animal Models
Gender Differences: Menstrual Cycle
Gender Differences: Predictors & Progression
Gender Differences: Treatment
Gender Differences: Animal Models
Do data from animal behavioral
models suggest that males are
more vulnerable to drugs than
females?
Gender Differences: Animal Models
Behavioral Models:
1. Amount of Drug Self-Administered
2. Reinforcing Effectiveness
3. Speed of Acquisition of Self-Administration
4. “Prevalence” of Self-Administration
5. Relapse: Reinstatement following Extinction
Gender Differences: Animal Models
1. Amount of Drug Self-Administered
Females, compared to males, self-administer more
alcohol
caffeine
cocaine
Hill, 1978; Lancaster & Spiegel, 1992
Heppner et al., 1986
Morse et al., 1993; Matthews et al., 1999;
Lynch & Carroll,1999
fentanyl Klein et al., 1997
heroin
Carroll et al., 2001
morphine Alexander et al, 1978; Hill, 1978;
Cicero et al, 2000
nicotine
Donny et al., 2000
Gender Differences: Animal Models
2. Reinforcing Effectiveness
•
Females reach higher progressive ratio breakpoint for
cocaine (Roberts et al., 1989)
nicotine (Donny et al., 2000)
• Females have shorter latency for first nicotine infusion of
the session (Donny et al., 2000)
Gender Differences: Animal Models
Progressive ratio breakpoint (BP) (Roberts et al., 1989)
•
•
•
•
Males: 48.2
Females: 264.1
Females during estrus: approx. 400
Estrus BP > metestrous/diestrous or proestrus BP
Gender Differences: Animal Models
3. Speed of Acquisition of Self-Administration
Females acquire self-administration faster than males
• cocaine - approx 1/2 the # sessions (Lynch & Carroll, 1999)
• heroin - approx 2/3 the # sessions (Lynch & Carroll, 1999)
• nicotine - at lowest dose only (Donny et al., 2000)
Gender Differences: Animal Models
4. “Prevalence” of Self-Administration (SA)
 Similar percentage of female rats acquire heroin SA:
90.0% females vs. 91.7% males
(Lynch & Carroll, 1999)
 More female rats acquire cocaine SA:
70% females vs. 30% males
(Lynch & Carroll, 1999)
 More female Rhesus monkeys acquire PCP SA:
100% females vs. 36.4% males
(Carroll et al., 2000)
Gender Differences: Animal Models
5. Relapse: Reinstatement following Extinction of
Cocaine SA
Females, compared to males,
•
•
exhibit greater reinstatement of extinguished
responding
“relapse” with a lower priming dose
Lynch & Carroll (2000)
Gender Differences: Animal Models
Behavioral Models:
1. Amount of Drug Self-Administered
2. Reinforcing Effectiveness
3. Speed of Acquisition of Self-Administration
4. “Prevalence” of Self-Administration
5. Relapse: Reinstatement following Extinction
Gender Differences in Drug Abuse
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Gender Differences: The Numbers
Gender Differences: Animal Models
Gender Differences: Menstrual Cycle
Gender Differences: Predictors & Progression
Gender Differences: Treatment
Hormonal Changes
During the
Menstrual Cycle
Gender Differences: Menstrual Cycle
Pharmacokinetics (Humans) : Cocaine

Pharmacokinetics of i.v. 0.2 and 0.4 mg/kg cocaine:
• peak plasma levels
• time to reach peak plasma level (Tmax)
• elimination half life
• AUC

No differences among males, females (luteal), females (follicular)
Exception: Tmax for 0.4 mg/kg
• Females
• follicular phase: 4.0 min
• luteal phase: 6.7 min
• Males: 8.0 min
Mendelson et al. (1999)
Gender Differences: Menstrual Cycle
ORAL d-AMPHETAMINE
• Subjective effects > follicular than luteal:
> feeling of “high”
> euphoria (ARCI MBG)
> energy & intellectual efficiency (ARCI BG)
> liking the drug
> wanting the drug
Justice & de Wit (1999)
Gender Differences: Menstrual Cycle
SMOKED COCAINE
• Repeated doses smoked cocaine (0, 6, 12.5 or 25 mg)
• In follicular phase (v. luteal phase)
• Higher ratings of “high”
• Higher ratings of “good drug effect”
Evans et al. (2002)
Gender Differences: Menstrual Cycle
NICOTINE CESSATION STUDY
• Quitters in the late luteal phase, vs follicular phase:
• more withdrawal symptoms
• more depressive symptomatology
• Implications for timing of initiation of cessation
Perkins (2000)
Gender Differences: Menstrual Cycle
CUE-INDUCED NICOTINE CRAVING
Follicular phase females reported significantly less
craving than
• luteal phase females
• males
Franklin et al. (2004)
Difference Scores in Cue-Induced Craving
C
R
A
V
I
N
G
S
C
O
R
E
2.5
1
p < .04
All
2
2
3
1.5
Males
5
1
Females
0.5
0
1
-0.5
4
2
3
4
5
6
7
F
L
8
6
7
F = Follicular 8
9
L = Luteal
9
10
Early F Late L
On a scale of 1 to 10, how much do you
desire a cigarette at this moment?
10
Gender Differences: Menstrual Cycle
NICOTINE CESSATION
Greater abstinence when cessation is initiated in
the follicular phase.
Abstinence rates at 9 weeks post-quit date:
• All women: 46%
• Follicular phase quit date: 69%
• Luteal phase quit date: 29%
Franklin et al. (CPDD, 03)
Gender Differences: Menstrual Cycle
SHORT-TERM ABSTINENCE & WEIGHT GAIN
• 20 highly dependent women, not planning to quit
• Engaged in 1 wk abstinence
Results:
• Mean weight gain in abstainers: 3.1 lbs
• Abstinent in luteal phase: 5.3 lbs.
• Abstinent in follicular phase: 1.5 lbs
Pomerleau et al., 2000
Gender Differences: Menstrual Cycle
Smoking Cessation Implications:
Quit in the Follicular Phase
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•
•
•
•
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Less desire to smoke
Less desire to relieve negative affect
Fewer withdrawal symptoms
Less depressive symptomatology
Less cue-induced craving
Less weight gain
• Better abstinence
Gender Differences in Drug Abuse
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Gender Differences: The Numbers
Gender Differences: Animal Models
Gender Differences: Menstrual Cycle
Gender Differences: Predictors & Progression
Gender Differences: Treatment
Gender Differences:
Predictors & Progression
• Depression: greater predictor of drug use by male than
by female adolescents (Costello et al., 1999)
• Conduct disorders: greater predictor of drug use and
dependence by female than by male adolescents
(Costello et al., 1999)
• Aggressiveness: predictor of drug use by boys, but not
girls (Ensminger, 1992)
Gender Differences:
Predictors & Progression
• Cigarette use: greater predictor of progression to illegal
drug use by girls than by boys (Kandel et al., 1992,1998)
• Smoking during pregnancy: associated with smoking by
preadolescent female offspring, but not male (Kandel et al.,
1994; Weissman et al., 1999)
Gender Differences:
Predictors & Progression
• Early vs. Late Initiators of Drug Use
- Boys who develop abuse or dependence:
initiate drug use earlier than boys who do not
develop abuse or dependence
- Girls who develop abuse or dependence:
initiate drug use later than girls who do not
develop abuse or dependence
Costello et al. (1999)
Gender Differences:
Predictors & Progression
• Among youth who became dependent before age 16,
boys used earlier than girls:
• Cannabis
• Smoking
• Any substance
2.0 years earlier
3.5 years earlier
2.5 years earlier
• Among youth who did not become dependent before
age 16, no gender differences in age of onset of first use.
Costello et al. (1999)
Gender Differences:
Predictors & Progression
Family characteristics more predictive of drug use in
females than males:
• Maternal
• alcoholism (Boyd et al., 1993)
• drug abuse (Boyd et al., 1993)
• Low parental
• attachment (Ensminger et al., 1982; Brook et al., 1993)
• monitoring (Krohn et al., 1986)
• concern (Murray et al., 1983)
• Unstructured home environment (Block et al., 1988)
• Dysfunctional family (Chatham et al., 1999)
Gender Differences: Predictors
& Progression
Peer Difficulties & Parental Stress as Predictors of Monthly
“Bursts” in Use of Tobacco, Marijuana & Alcohol
• 181 Oregon adolescents aged 11-14 in 1- vs. 2-parent families
RESULTS
Peer Difficulties
• Predictor for boys in both family types
• Not a predictor for girls
Parental stress
• Predictor for girls in 1-parent, but not 2-parent, families
• Not a predictor for boys
Dishion & Skaggs (2000)
Gender Differences:
Predictors & Progression
Childhood Sexual Abuse (CSA)
Very high rates of CSA reported by women in treatment.
Does this mean that CSA plays an etiologic role in drug dependence?
Gender Differences:
Predictors & Progression
Wilsnack et al. (1997)
Population-based face-to-face survey
• 1,099 women age 21 older
• 278 (25%) reported childhood sexual abuse
CSA respondents were more likely to report
• lifetime use of prescribed psychoactive drugs
(63.4% vs. 52.9%)
• lifetime depressive episode (44.3% vs. 23.2%)
• lifetime use of illicit drugs (34.9% vs. 13.5%)
Gender Differences:
Predictors & Progression
“Childhood Sexual Abuse and Adult Psychiatric and Substance Use
Disorders in Women,” Kendler et al. (2000)
• Population-based Virginia Twin Registry (1,411 female twins)
• 3 types of childhood sexual abuse (CSA)
• Nongenital
• Genital
• Intercourse
• 6 disorders: drug dependence, alcohol dependence,
major depression, GAD, panic disorder, bulimia nervosa
Results:
• All 6 disorders significantly correlated with intercourse
• Only 2 disorders significantly correlated with all 3 types of CSA:
drug dependence & alcohol dependence
Gender Differences:
Predictors & Progression
Females may use for a shorter period of time than males
before becoming dependent
•
Cocaine
Griffin et al., 1989
•
Heroin
Hser, 1990
•
Marijuana
Mezzich et al. 1994
•
Alcohol
Blume, 1986; Mezzich et al. 1994
Females gamble for a shorter period of time than males
before becoming dependent (Tavares et al., 2001)
Gender Differences:
Predictors & Progression
Adolescent Smoking in Girls:
•
•
•
•
•
•
Dieting
Rebelliousness
Stress – relieve or avoid
Home alone
Parental approval
Parental stress
Adolescent Smoking in Boys:
•
•
•
•
Shy, lonely, socially awkward
Depression
Peer approval
Peer difficulties
Gender Differences:
Predictors & Progression
Predictors of drug use, progression, and
dependence are often
• gender-sensitive
• gender-specific
Will addressing these gender-based
predictors in treatment and prevention
efforts improve outcomes for both men and
women?
Gender Differences in Drug Abuse
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Gender Differences: The Numbers
Gender Differences: Animal Models
Gender Differences: Menstrual Cycle
Gender Differences: Predictors & Progression
Gender Differences: Treatment
Gender Differences: Treatment
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Pharmacotherapies
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Treatment Engagement
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Women-Only vs Mixed-Gender
Treatment Programs
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Relapse
Gender Differences: Treatment
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Pharmacotherapies
• Nicotine Dependence
• Depression
• Buprenorphine
Gender Differences: Treatment
NICOTINE DEPENDENCE PHARMACOTHERAPIES
Better outcomes in men than women
• Nicotine Replacement Therapies
• Patch
• Gum
• Spray
Better outcomes in women than men
• Nicotine inhaler
Efficacious only in women
• Mecamylamine + nicotine patch
• Clonidine (more effective w depression history)
• Naltrexone (depression history only)
Gender Differences: Treatment
CHRONIC DEPRESSION: IMIPRAMINE VS SERTRALINE
(400 women & 235 men)
Men: Better outcome with imipramine (TCA)
• Imipramine: 61% response
• Sertraline: 56% response
Women: Better outcome with sertraline (SSRI)
• Sertraline: 56% response
• Imipramine: 45% response
Kornstein et al. (2001)
Gender Differences: Treatment
EARLY TREATMENT TERMINATION
•
104 patients in a buprenorphine-maintenance tx program
•
Early termination = remaining in tx for < 30 days
•
Early termination more likely in ♀: 13% ♂
•
Predictors of early termination for both ♂ & ♀
25% ♀
• less severe legal problems
• greater employment problems
•
♀-only predictor of early termination: high hostility
•
Implications for tx retention efforts
Petry & Bickel (2000)
Gender Differences: Treatment

Pharmacotherapies

Treatment Engagement

Women-Only vs Mixed-Gender
Treatment Programs

Relapse
Gender Differences: Treatment

Treatment Engagement
Several studies suggest that women are more likely
than men to terminate early from drug abuse treatment
programs:
Levy & Doyle (1974)
Anglin et al. (1987)
Guttierres & Todd (1997)
Gender Differences: Treatment
TREATMENT ENGAGEMENT FACTORS
For both men & women
• Perceived utility of treatment
• Ancillary services
Men respond more favorably to an authoritarian counseling style
Women respond more favorably to an empathetic counseling style
Fiorentine et al. (1999)
Gender Differences: Treatment

Pharmacotherapies

Treatment Engagement

Women-Only vs Mixed-Gender
Treatment Programs

Relapse
Gender Differences: Treatment Issues
WOMEN-ONLY vs. MIXED-GENDER PROGRAMS
Dahlgren & Willander (1989): Female alcoholics
• 200 women randomly assigned women-only or mixed-gender
program
• In-patient followed by out-patient – duration of at least 1 year
Two-year follow up: Women-only program (vs. mixed-gender)
•
•
•
•
better abstinence rates
consumed less alcohol per day during relapse
fewer blackouts
less reports of irritation and anger while intoxicated
Gender Differences: Treatment
WOMEN-ONLY PROGRAMS
Grella et al. (1999)
• Tx outcomes in 4,117 women treated in publicly-funded
residential treatment programs in Los Angeles County.
• Compared women-only programs (vs. mixed-gender)
• time in treatment
• treatment completion
Gender Differences: Treatment
WOMEN-ONLY PROGRAMS
Grella et al. (1999)
Women in women-only programs (vs. mixed-gender)
• spent more time in treatment
• were over twice as likely to complete treatment
Questions
•
Results hold for males?
•
•
Results hold under random assignment? (v. matching)
Relevant components of the women-only programs?
•
Similar benefit occur in mixed-sex programs with a
gender-sensitive approach?
Gender Differences: Treatment

Pharmacotherapies

Treatment Engagement

Women-Only vs Mixed-Gender
Treatment Programs

Relapse
Gender Differences: Treatment
RELAPSE
Are women more likely to relapse than men ?
Yes
Wong et al. (1997)
Less likely
Weiss et al. (1997)
Equally likely
Kosten et al. (1993); Lundy et al., (1995)
Do male and females relapse for the same reasons?
Gender Differences: Treatment
Variables that differentially predict relapse in men and women:
• Fiorentine et al., 1997
• Depression in past 6 mos: female-only predictor
• Anxiety in past 6 mos: male-only predictor
• McKay et al., 1996
Prior to relapse
• Women report
• negative emotions and
• interpersonal problems
• Men report positive emotions
Gender Differences: Treatment
Can retention, treatment completion,
and relapse for both males and females
be improved by gender-sensitive
strategies?
Gender Differences:
Summary & Conclusions
FIVE MAJOR POINTS
1. Neither epidemiological data nor animal models data
support the notion that males are more vulnerable to
drug use or dependence than females.
2. Menstrual and estrous cycle phase is a determinant of
the drug response. Its role in treatment is largely
unexplored.
3. Hormonal and pharmacokinetic factors may underlie
some sex differences.
Gender Differences:
Summary & Conclusions
4.
Some of the predictors of drug use, progression, and
dependence are gender-sensitive or gender-specific.
•
Do these gender-based predictors affect prevention
and treatment outcomes?
•
Can prevention and treatment outcomes for both
males and females be improved by addressing
them?
5. Retention, treatment outcome, relapse are affected by
gender and may be improved by gender-sensitive
strategies.
Thank You