# Presentation: 541757

##  The Pervasiveness of 

**Cora Lee Wetherington, Ph.D.**
**Women & Gender Research Coordinator**
**National Institute on Drug Abuse**
**National Advisory Council on Drug Abuse**
**September 20, 2006**

-  The Pervasiveness of
- Sex/Gender Differences
-  in Drug Abuse

## Gender Differences in Drug Abuse

**  ****The Numbers**
**  ****Animal Models**
**  ****Menstrual Cycle**
**  ****Predictors**
**  ****Prevention**
**  ****Brain Imaging**
**   ****Prenatal Drug Exposure**
**   ****Treatment**

## Gender Differences in Drug Abuse

**  ****The Numbers**
**  ****Animal Models**
**  ****Menstrual Cycle**
**  ****Predictors**
**  ****Prevention**
**  ****Brain Imaging**
**   ****Prenatal Drug Exposure**
**   ****Treatment**

## Gender Differences:  The Numbers 

- Prevalence Data
-  Drug Use
-  Drug Dependence

## “Any Illicit Drug Use” among Ages 12 & Older

**0**

**10**

**20**

**30**

**40**

**50**

**60**

- “Any Illicit Drug Use” among Ages 12 & Older
-           Is Higher among Males than Females

*2004 National Survey on Drug Use and Health, SAMHSA, 2005*

- Lifetime

- Prescription
- Drug Abuse

- Males
- Females

- Past Year

- Past Month

**Percent**

- An exception:
*Prescription Drug*
*Abuse *where
- Past Month
- rates are similar** **

## Gender Differences:  The Numbers 

-      Prevalence of Drug Dependence:  greater for males than females
- 9.2% Males
- 5.6% Females       (1994 Nat’l Comorbidity Survey)

## Gender Differences:  The Numbers 

-      Prevalence of 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 

**Population prevalence**
**               ****vs**
**Conditional prevalence**

**Gender Differences:  The Numbers**

## Opportunity to Use Drugs

- 0

- 10

- 20

- 30

- 40

- 50

- 60

- 70

**Marijuana**

**Cocaine**

**Hallucinogens**

**Heroin**

**Percent**

**Male**

**Female**

- Van Etten et al. (1999) -- 1993 NHSDA

## Percent Use Given an Opportunity 

- Van Etten et al. (1999) -- 1993 NHSDA

## 
Calculate Dependence Only among Users:

- 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**

## Gender Differences:  The Numbers 

**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 

**Gender Differences:  The Numbers**

- Calculate Dependence Only among Users:

- 	Females more likely than males to become dependent on
-     the cluster of drugs
- 			**anxiolytics **
**	****	****sedatives  **
**	****	****hypnotics**
- 				 Anthony et al. (1994)
- 				 Data Source: National Comorbidity Survey

## All Age Groups 
vs.
 Adolescents

- vs.
-  Adolescents

**Gender Differences:  The Numbers**

## 
                   Monitoring the Future Survey
                         1975 - Present

-                    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**

## Slide 16

## Slide 17

## Slide 18

## Gender Differences:  The Numbers

**      ****Dependence Among Adolescents Users**
**                                 ****Aged 12-17**
- 	        Alcohol:       boys = girls
- 	   Marijuana:   boys = girls
- 	        Nicotine:      boys = girls
-      Cocaine : 	 girls > boys
- 			       17.4%  vs. 4.7%
- 	     Kandel et al. (1997 )
-            Data Source:  1991, 1992, 1993 NHSDA

## Why do adolescent girls have higher
 rates of cocaine dependence than boys?

-  rates of cocaine dependence than boys?

- They use cocaine more frequently
- They use a greater quantity of cocaine
- They report more symptoms at low use frequency

**Gender Differences:  The Numbers**

- Chen & Kandel (2002)
- 		         Data Source:  1991, 1992, 1993 NHSDA

## Risk of Becoming Cocaine-Dependent 
within 24 Months of First Use

**within 24 Months of First Use**

- Females were 3-4 times more likely than males to become dependent within 24 months of cocaine use onset.
-                                        O’Brien & Anthony (2005)
-                                                      Data Source: NHSDA 2000-2001

**Gender Differences:  The Numbers**

## Girls Develop Tobacco Dependence 
Symptoms Faster than Boys

**Symptoms Faster than Boys**

- Time from onset of monthly use to symptoms:
-   Girls:  3 weeks
-   Boys:  6 months
- # Symptoms among monthly users
-   Girls:  5.7
-   Boys:  4.0

**Gender Differences:  The Numbers**

- DiFranza et al. (2002)

## Gender Differences:  The Numbers

-    If given the opportunity, females are as likely as males
-   to use drugs
-   to become dependent

-     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
-   use more cocaine
-   use more frequently
-   develop nicotine dependency symptoms faster

**Gender Differences:  The Numbers**

## Gender Differences in Drug Abuse

**  ****The Numbers**
**  ****Animal Models**
**  ****Menstrual Cycle**
**  ****Predictors**
**  ****Prevention**
**  ****Brain Imaging**
**   ****Prenatal Drug Exposure**
**   ****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**

## Gender Differences:  Animal Models

**Drug Self-Administration Studies:**
**Amount of Drug Self-Administered**
**Reinforcing Effectiveness**
**Speed of Acquisition of Self-Administration**
**“****Prevalence” of Self-Administration**

**Gender Differences:  Animal Models**

## Gender Differences:  Animal Models

- 	1.  Amount of Drug Self-Administered
-       Females compared to males, self-administer more
- 	alcohol      Hill, 1978; Lancaster & Spiegel, 1992
- 	caffeine     Heppner et al., 1986
-       cocaine      Morse et al., 1993; Matthews et al., 1999;
- 		     Lynch & Carroll,1999; Hu et al., 2004
- 	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**

## Gender Differences:  Animal Models

-  2.  Reinforcing Effectiveness  (cocaine & nicotine)
-     Females reach higher progressive ratio breakpoint for
-  cocaine  (Roberts et al., 1989)
-  nicotine  (Donny et al., 2000)

**Gender Differences:  Animal Models**

-    Females acquire stronger cocaine-induced conditioned place preference quicker and at lower doses  (Russo et al., 2003a; Russo et al., 2003b)

## 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**

## Gender Differences:  Animal Models

- 4.  “Prevalence” of Self-Administration (SA)
-     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)
- Similar** **percentage of female rats acquire heroin SA:** **
-           90.0% females vs. 91.7% males   (Lynch & Carroll, 1999)

**Gender Differences:  Animal Models**

## Gender Differences:  Animal Models

**Drug Self-Administration Studies:**
**Amount of Drug Self-Administered**
**Reinforcing Effectiveness**
**Speed of Acquisition of Self-Administration**
**“****Prevalence” of Self-Administration**

**Gender Differences:  Animal Models**

## Gender Differences:  Animal Models

**Drug Self-Administration Studies:**
**Amount of Drug Self-Administered**
**Reinforcing Effectiveness**
**Speed of Acquisition of Self-Administration**
**“****Prevalence” of Self-Administration**
** ****Escalation of Cocaine Self-Administration**

**Gender Differences:  Animal Models**

## Gender Differences:  Animal Models

**                   ****Biological Basis?**
**    ****Circulating Gonadal Hormones**
**Estrogen  ******
**Progesterone ******

**Gender Differences:  Animal Models**

## Gender Differences:  Animal Models

**                   ****Biological Basis?**
**It’s more than circulating gonadal hormones**
**     ****Gonadectomized rats:  Females (vs Males)**
**acquire cocaine self-administration faster**
**self-administer more cocaine**
**   **
**                                                  ****Hu et al. (2004)**

**Gender Differences:  Animal Models**

## Gender Differences:  Animal Models

**                    ****Biological Basis?**
**If not circulating gonadal hormones, then what?**
**     ****Sexual dimorphism in brain organization during early development:**
** ****driven by gonadal hormones**
** ****driven by non-hormonal factors**
**   **
**                                                  **

**Gender Differences:  Animal Models**

## Gender Differences:  Animal Models

**                    ****Biological Basis?**
** ****Non-hormonal factors**
**     ****e.g., in mice & rats ****chromosomal sex (XX vs XY),**** not gonadal secretions, ****determines sexual dimorphism in embryonic mesencephalic dopamine neurons**
**	****	****	****	****Reisert et al. (1990)**
**	****	****	****	****Kolbinger et al. (1991)**
**	****	****	****	****Carruth et al. (2002)**
**                                                  **

**Gender Differences:  Animal Models**

## Gender Differences:  Animal Models

**Emerging research suggests that study of  **
**sexual dimorphism**** ****in **
**  ****brain organization **
**   ****gene expression**
**   ****knockout mice**
**are very promising areas to pursue.**

**Gender Differences:  Animal Models**

## Gender Differences in Drug Abuse

**  ****The Numbers**
**  ****Animal Models**
**  ****Menstrual Cycle**
**  ****Predictors**
**  ****Prevention**
**  ****Brain Imaging**
**   ****Prenatal Drug Exposure**
**   ****Treatment**

## Hormonal Changes

**During the**
**Menstrual Cycle**

## 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**

## Gender Differences: Menstrual Cycle

**ORAL *****d*****-AMPHETAMINE**
-   Positive 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**

## Gender Differences: Menstrual Cycle

- Can these findings be capitalized on
- in treatment settings?

**Gender Differences: Menstrual Cycle**

## Gender Differences: Menstrual Cycle

**NICOTINE**

**Gender Differences: Menstrual Cycle**

## Franklin et al. (2002)

## Gender Differences: Menstrual Cycle

**Nicotine: In the luteal phase**
-   More smoking
-   More cue-induced craving
-   During short-term abstinence
-   more withdrawal symptoms
-   more depressive symptomatology
-   more desire to smoke
-   more desire to relieve negative affect
-   more weight gain
-   Quitting during luteal phase produces poorer
-    short-term abstinence (preliminary data)

**Implications:  Quit smoking during the follicular phase**

**Gender Differences: Menstrual Cycle**

## Gender Differences in Drug Abuse

**  ****The Numbers**
**  ****Animal Models**
**  ****Menstrual Cycle**
**  ****Predictors**
**  ****Prevention**
**  ****Brain Imaging**
**   ****Prenatal Drug Exposure**
**   ****Treatment**

## Gender Differences:  Predictors

- Aggressiveness:
-   Predictor of drug use by boys, but not girls (Ensminger, 1992)
- Conduct Disorder:
-   Stronger predictor of drug use and dependence by female than
-       by male adolescents (Costello et al., 1999)

**Gender Differences:  Predictors**

## Gender Differences:  Predictors

- Smoking during pregnancy:
-   associated with smoking by preadolescent female
-      offspring, but not male (Kandel et al., 1994; Weissman et
-      al., 1999)
- Cigarette use:
-   stronger predictor of progression to illegal drug use by girls
-      than by boys  (Kandel et al., 1992,1998)

**Gender Differences:  Predictors**

## Gender Differences:  Predictors

- 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**

## Gender Differences:  Predictors

**   ****Peer Difficulties & Parental Stress:**
**       ****Predictors of  Monthly “Bursts” **
**in Use of Tobacco, Marijuana & Alcohol**

-   181 Oregon youth ages 11-14 in 1- vs. 2-parent families

- RESULTS:  Gender-Specific
-    _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**

## Gender Differences:  Predictors

-   **gender-sensitive**
**  ****gender-specific**

**Will addressing these gender-based predictors in treatment and prevention efforts improve outcomes for both males and females?**

**Gender Differences:  Predictors**

## Gender Differences in Drug Abuse

**  ****The Numbers**
**  ****Animal Models**
**  ****Menstrual Cycle**
**  ****Predictors**
**  ****Prevention**
**  ****Brain Imaging**
**   ****Prenatal Drug Exposure**
**   ****Treatment**

## Gender Differences:  Prevention

- #1:   Classroom skill-based
- #2:   #1 + school-wide, parent, and community

**Gender Differences:  Prevention**

**      **
**                                                           ****Flay et al. (2004)**

## Gender Differences:  Prevention

- #1:   Classroom skill-based
- #2:   #1 + school-wide, parent, and community

**Gender Differences:  Prevention**

-  1153 high-risk inner-city African American youth in Chicago
-   6 target behaviors:  drug abuse, violent beh, provoking beh, school
-     delinquency, recent sexual  intercourse, increase in condom use
-   Interventions lasted from four years:  5th – 8th grade

**      **
**                                                           ****Flay et al. (2004)**

## Gender Differences:  Prevention

- #1:   Classroom skill-based
- #2:   #1 + school-wide, parent, and community

**Gender Differences:  Prevention**

-  1153 high-risk inner-city African American youth in Chicago
-   6 target behaviors:  drug abuse, violent beh, provoking beh, school
-     delinquency, recent sexual  intercourse, increase in condom use
-   Interventions lasted from four years:  5th – 8th grade

**      **Results:
-   Significant improvement in all 6 target behaviors
-     compared to control
-   32% (#1) & 34% (#2) reduction in drug abuse
**                                                           ****Flay et al. (2004)**

## Gender Differences:  Prevention

- #1:   Classroom skill-based
- #2:   #1 + school-wide, parent, and community

**Gender Differences:  Prevention**

-  1153 high-risk inner-city African American youth in Chicago
-   6 target behaviors:  drug abuse, violent beh, provoking beh, school
-     delinquency, recent sexual  intercourse, increase in condom use
-   Interventions lasted from four years:  5th – 8th grade

**      **Results:
-   Significant improvement in all 6 target behaviors
-     compared to control
-   32% (#1) & 34% (#2) reduction in drug abuse
-   Only for boys.  No significant effects for girls.
**                                                           ****Flay et al. (2004)**

## Gender Differences:  Predictors

-   **gender-sensitive**
**  ****gender-specific**

**Will addressing these gender-based predictors in treatment and prevention efforts improve outcomes for both males and females?**

**Gender Differences:  Predictors**

## Gender Differences in Drug Abuse

**  ****The Numbers**
**  ****Animal Models**
**  ****Menstrual Cycle**
**  ****Predictors**
**  ****Prevention**
**  ****Brain Imaging**
**   ****Prenatal Drug Exposure**
**   ****Treatment**

## Gender Differences:  Brain Imaging

**  ****Cue-Induced Craving**
** **  **Brain Deficits**
**	****	****	****	****	**

**Gender Differences:  Brain Imaging**

## Female smokers are much more sensitive to cigarette cues than male smokers

***Female smokers are much more sensitive to cigarette cues than male smokers***

**N = 5 Female Smokers - 6 NonSmoking Females**

**3.5**
**3.0**
**2.5**
**2.0**
**1.5**
**1.0**
**  ****.5**
**  ****0**

**N = 6 Male Smokers - 5 NonSmoking Males**

**T Value**

**                  ****TERESA FRANKLIN, JASON GRAY, JOHN LISTERUD, **
**JOHN MONTEROSSO, CHARLES P. O’BRIEN, and ANNA ROSE CHILDRESS**

**Females**

**Males**

## Gender Differences:  Brain Imaging

-  **PET Imaging of Cocaine Cue-Induced Craving**
-  Common areas of activation in ♂ ♀** **
** **Many ♂ ♀ differences, e.g,
-  activation only in ♂
-   insula
-   ventral anterior cingulate
-   orbital frontal cortex
-   amygdala
**                                          ****Kilts et al. (2004)**
**	****	****	****	****	**

**Gender Differences:  Brain Imaging**

## Gender Differences:  Brain Imaging

-  **PET Imaging of Cocaine Cue-Induced Craving**
-  Common areas of activation in ♂ ♀** **
** **Many ♂ ♀ differences, e.g,
-  activation only in ♂
-   insula
-   ventral anterior cingulate
-   orbital frontal cortex
-   amygdala  (decrease in activity in ♀ )
**                                          ****Kilts et al. (2004)**
**	****	****	****	****	**

**Gender Differences:  Brain Imaging**

## Gender Differences:  Brain Imaging

** **
**       ****Cocaine-Dependent Subjects:**
**            ****Frontal Cortical Deficits**** **
**Perfusion abnormalities in ****men****,**
**     ****but not women   ****(Levin et al., 1994)**
** ****More neuronal damage in gray**
**      ****and white matter in ****men**** than women **
**                                  ****(Chang et al., 1999)**

## Gender Differences:  Brain Imaging

-                      **White Matter Hyperintensities (WMH) in **
**                       ****Methamphetamine Abusers (MA)**
**  **WMH:  imply structural white matter abnormalities
-   Evaluated with MRI: 33 MA & 32 controls
**  **
**  **
**	****	****	****	****	****Bae et al. (2006)**

**Gender Differences:  Brain Imaging**

## Gender Differences:  Brain Imaging

-                      **White Matter Hyperintensities (WMH) in **
**                       ****Methamphetamine Abusers (MA)**
**  **WMH:  imply structural white matter abnormalities
-   Evaluated with MRI: 33 MA & 32 controls
- Results**:**
**  ****Severity & prevalence WMH  > MA than controls**
**  ****Located predominately in frontal regions**
**  **
**	****	****	****	****	****Bae et al. (2006)**

**Gender Differences:  Brain Imaging**

## Gender Differences:  Brain Imaging

-                      **White Matter Hyperintensities (WMH) in **
**                       ****Methamphetamine Abusers (MA)**
**  **WMH:  imply structural white matter abnormalities
-   Evaluated with MRI: 33 MA & 32 controls
- Results**:**
**  ****Severity & prevalence WMH  > MA than controls**
**  ****Located predominately in frontal regions**
**  ****Only in males**
**	****	****	****	****	****Bae et al. (2006)**

**Gender Differences:  Brain Imaging**

## Gender Differences:  Brain Imaging

**  ****Cue-Induced Craving**
** **  **Brain Deficits**
**	****	****	****	****	**

**Gender Differences:  Brain Imaging**

## Gender Differences:  Brain Imaging

**  ****Cue-Induced Craving**
** **  **Brain Deficits**
**	****	****	****	****	**

**Gender Differences:  Brain Imaging**

**Do these outcomes have implications for treatment strategies for males and females?**

## Gender Differences in Drug Abuse

**  ****The Numbers**
**  ****Animal Models**
**  ****Menstrual Cycle**
**  ****Predictors**
**  ****Prevention**
**  ****Brain Imaging**
**   ****Prenatal Drug Exposure**
**   ****Treatment**

## Gender Differences in Prenatal Drug Exposure

-                      Upcoming Meeting:  Oct 7-8, 2006, RWJ Medical School
- 	                  Institute for the Study of Child Development
**  ****	**
**	****	****   **
**Gender Differences in Effects of **
**Prenatal Substance Exposure**

**Gender Differences in ****Prenatal Drug Exposure**

- Preclinical Researchers:
-   Diana Dow-Edwards
-   Laura Cousino Klein
-   Barbara Strupp
-   Theordore A. Slotkin

- Clinical Researchers:
-   Margaret Bendersky
-   Virginia Delaney-Black
-   Sydney Hans
-   Marilyn Lewis

## Gender Differences in Prenatal Drug Exposure

-    **“****Prenatal Drug Exposure” is used **
**     ****as a “gender-specific” term.**

**Gender Differences in ****Prenatal Drug Exposure**

## Gender Differences in Prenatal Drug Exposure

-    **“****Prenatal Drug Exposure” is used **
**     ****as a “gender-specific” term.**

**Gender Differences in ****Prenatal Drug Exposure**

**It is used to refer to maternal drug use during pregnancy.**

## Gender Differences in Prenatal Drug Exposure

-    **Consequences of Paternal Cocaine Exposure in Mice**
**  ****Reduction in head circumference**
**  ****Deficits in sustained attention & **
**    ****spatial working memory**
**  **** **
**  ****                ****	****	****	****He et al. (2006)**

**Gender Differences in ****Prenatal Drug Exposure**

## Gender Differences in Prenatal Drug Exposure

-    **Consequences of Paternal Cocaine Exposure in Mice**
**  ****Reduction in head circumference**
**  ****Deficits in sustained attention & **
**    ****spatial working memory**
**  **** ****Larger deficits in female offspring**
**  ****                ****	****	****	****He et al. (2006)**

**Gender Differences in ****Prenatal Drug Exposure**

## Gender Differences in Prenatal Drug Exposure

-    “**prenatal drug exposure”**
**                    ****                                                             **

**Gender Differences in ****Prenatal Drug Exposure**

## Gender Differences in Prenatal Drug Exposure

-    “**prenatal drug exposure”**
**                    ****                                                             **

**Gender Differences in ****Prenatal Drug Exposure**

**New Questions:**

- What are other effects of paternal drug use?

## Gender Differences in Prenatal Drug Exposure

-    “**prenatal drug exposure”**
**                    ****                                                             **

**Gender Differences in ****Prenatal Drug Exposure**

- What are the combined effects of maternal & paternal use?

**New Questions:**

- What are other effects of paternal drug use?

## Gender Differences in Prenatal Drug Exposure

-    “**prenatal drug exposure”**
**                    ****                                                             **

**Gender Differences in ****Prenatal Drug Exposure**

- What are the combined effects of maternal & paternal use?

**New Questions:**

- Is that combination playing a role in NIDA’s cohort studies?

- What are other effects of paternal drug use?

## Gender Differences in Prenatal Drug Exposure

-    “**prenatal drug exposure”**
**                    ****                                                             **

**Gender Differences in ****Prenatal Drug Exposure**

- What are the combined effects of maternal & paternal use?

**New Questions:**

- Is that combination playing a role in NIDA’s cohort studies?

- What is the impact on male versus female offspring?

- What are other effects of paternal drug use?

## Gender Differences in Drug Abuse

**  ****The Numbers**
**  ****Animal Models**
**  ****Menstrual Cycle**
**  ****Predictors**
**  ****Prevention**
**  ****Brain Imaging**
**   ****Prenatal Drug Exposure**
**   ****Treatment**

## Gender Differences in Treatment

-  **Disulfiram as a Treatment for**
**        ****Cocaine-Dependence**
**  ****Secondary data analysis: 2 RCT**
**  ****Carroll et al. (1998)**
**  ****Petrakis et al. (2000)**
**   **
**                                              ****Nich et al. (2004)**

**Gender Differences in Treatment**

## Gender Differences in Treatment

-  **Disulfiram as a Treatment for**
**        ****Cocaine-Dependence**
**  ****Secondary data analysis: 2 RCT**
**  ****Carroll et al. (1998)**
**  ****Petrakis et al. (2000)**
**   ****Disulfiram was efficacious only in males**
**                                              ****Nich et al. (2004)**

**Gender Differences in Treatment**

## Gender Differences:  Treatment

**           ****Meta-analysis of NRTs **
**           ****for Smoking Cessation**
** **21 DBPC randomized studies; 90 effect sizes
- 3, 6,12-mos follow-ups:
- 		Cepeda-Benito et al. (2004)

## Gender Differences:  Treatment

**           ****Meta-analysis of NRTs **
**           ****for Smoking Cessation**
** **21 DBPC randomized studies; 90 effect sizes
- At 3, 6,12-mos follow-ups:  NRT was more   effective in men than women
- 		Cepeda-Benito et al. (2004)

## Gender Differences:  Treatment

**           ****Meta-analysis of NRTs **
**           ****for Smoking Cessation**
** **21 DBPC randomized studies; 90 effect sizes
- At 3, 6,12-mos follow-ups:  NRT was more   effective in men than women
-   At 12 mos, NRT was effective only in men
- 		Cepeda-Benito et al. (2004)

## Gender Differences:  Treatment

-    Nicotine Metabolism
-   Faster in women than men
-   Equal in men and post-menopausal women
-   Faster in women on oral contraceptives (OC) than not on OC
-                                                                       Benowitz et al. (2006)

**Gender Differences:  Treatment**

## Gender Differences:  Treatment

-    Nicotine Metabolism
-   Faster in women than men
-   Equal in men and post-menopausal women
-   Faster in women on oral contraceptives (OC) than not on OC
-                                                                       Benowitz et al. (2006)
-    Faster in pregnant women than non-pregnant women
-   						Dempsey et al. (2002)

**Gender Differences:  Treatment**

## Gender Differences:  Treatment

-    Nicotine Metabolism
-   Faster in women than men
-   Equal in men and post-menopausal women
-   Faster in women on oral contraceptives (OC) than not on OC
-                                                                       Benowitz et al. (2006)
-    Faster in pregnant women than non-pregnant women
-   						Dempsey et al. (2002)
-    Why does this matter?

**Gender Differences:  Treatment**

## Gender Differences:  Treatment

-    Nicotine Metabolism
-   Faster in women than men
-   Equal in men and post-menopausal women
-   Faster in women on oral contraceptives (OC) than not on OC
-                                                                       Benowitz et al. (2006)
-    Faster in pregnant women than non-pregnant women
-   						Dempsey et al. (2002)
-    Why does this matter?
-  	Faster nicotine metabolizers have poorer smoking cessation
- 	outcomes from transdermal NRT.
-  						Lerman et al. (2006)

**Gender Differences:  Treatment**

## Gender Differences in Drug Abuse

**  ****The Numbers**
**  ****Animal Models**
**  ****Menstrual Cycle**
**  ****Predictors**
**  ****Prevention**
**  ****Brain Imaging**
**   ****Prenatal Drug Exposure**
**   ****Treatment**

##          Acknowledgment

##          Acknowledgment

- This presentation was made possible by researchers who conduct a sex/gender analysis of their data.

##          Acknowledgment

- This presentation was made possible by researchers who conduct a sex/gender analysis of their data.
- Without them, this presentation could not have occurred.

## The PromiseA sex/gender-based research approach in all areas of drug abuse research will lead to better prevention & treatment outcomes for both males and females.

- The PromiseA sex/gender-based research approach in all areas of drug abuse research will lead to better prevention & treatment outcomes for both males and females.

## Thank You

**Thank You**

## The Pervasiveness of Sex/Gender Differences in Drug Abuse

- Not conducting a gender analysis of data can lead to
- conclusion ERRORS:
- Conclude no effect:  when there is one, but only for one sex
- Conclude no effect:  when there are two – opposite directions
- Conclude an effect:  but effect is absent in one sex
- Gender analysis is not an end to itself, but a beginning:
- What does mean?
- What are the implications?
- What is the mechanism?
- Tool for understanding the subject matter under study
- Failure to find a gender difference in an outcome does not     mean that gender does not affect that outcome

##          Closing Comments

- Gender differences are pervasive in drug abuse.
- Gender matters in drug abuse.
- Conducting a sex/gender analysis of
-     data is a matter of doing good science.

- Unused

## Past Year Misuse of Prescription Drugs Ages 12 to 17:  Years 2002-2004  (NSDUH)

*****

*****

*****

*****

*****

*****

***  Statistically significant difference between rates for males and females**

## Sex/Gender Differences:  Animal Models

**Mechanisms?**
**Greater 5-HT2 receptor binding in men**
**       ****(Biver et al., 1996)**
**Greater D2 receptor affinity in men**
**      ****(Pohjalainen et al., 1998)**

**Sex/Gender Differences:  Animal Models**

## Neural Activation in Male Smokers

**-2mm                  2mm                  8mm             T Value**

**To Nicotine Cues Using BOLD fMRI**

**N = 6 Male Smokers - 5 NonSmoking Males**

**3.5**
**3.0**
**2.5**
**2.0**
**1.5**
**1.0**
**  ****.5**
**  ****0**

## Neural Activation in Females 

**      ****-2mm                   0mm                   2mm             T Value**

- Neural Activation in Females

**To Nicotine Cues Using BOLD fMRI**

**N = 5 Female Smokers - 6 NonSmoking Females**

**3.5**
**3.0**
**2.5**
**2.0**
**1.5**
**1.0**
**  ****.5**
**  ****0**

## Gender Differences:  Treatment

**   ****Compared to males, females are**
-   less sensitive to nicotine
-   more sensitive to stimuli associated with nicotine, e.g.,
-   sight, smell, taste
-   mouth, throat and respiratory irritation
-   social (e.g., presence of friends smoking)
-   drinking coffee, alcohol, etc.
-   mood states, stress

**Gender Differences:  Treatment**

**  ****more concerned about weight gain associated **
**   ****with smoking cessation**

## Gender Differences:  Treatment

**“****Cognitive-Behavioral Therapy to Reduce**
**Weight Concerns Improves Smoking Cessation Outcome**
** ****in Weight-Concerned Women”**
**Perkins et al. (2001)**
- Focusing on _concerns_ about weight gain
- more effective than focusing
- on the _weight gain_ itself.

**Gender Differences:  Treatment**

## Gender Differences in Drug Abuse

** ****The Numbers**
** ****Animal Models**
** ****Menstrual Cycle**
** ****Predictors**
**Psychiatric Comorbidity**
**Prevention**
** ****Treatment**

## Gender, Cannabis Use, Depression & Anxiety

- Neither depression nor anxiety predicted weekly or monthly cannabis use.

- Subjects:   1,601 20-21 yr olds followed for prior 7 years

- Patton et al. (2002)

- Results:

- Female daily cannabis users: 5.6 > risk
-    of depression & anxiety than nonsmokers.

- Female weekly users:  1.9 > risk

- No greater risk in male cannabis users.

**Gender Differences:  Psychiatric Comorbidity in Adolescents**

## Gender Differences:  Psychiatric Comorbidity in Adolescents

**                     ****Gender, Drugs, Sex, & Depression**
-                                   (NLSAH    N =13,491     Grades 7-11)

- Modest experimentation with drugs, sex, & alcohol
-   predicted 2-3 x > risk for depression in girls
-   not in boys

- High-risk behavior with drugs, sex, & alcohol** **
-   predicted depression in both girls & boys

- Depression did not increase the risk of drug use behavior.

- Hallfors et al. (2005)

## Gender Differences:  Prevention

**Gender Differences:  Prevention**

**      **
**                                                           **

## Gender Differences:  Prevention

**Gender Differences:  Prevention**

**      **
**                                                           **

**Would that mean that gender plays no role in prevention outcomes?**

## Gender Differences:  Prevention

**Gender Differences:  Prevention**

**      **
**                                                           **

**Would that mean that gender plays no role in prevention outcomes?**

**Will addressing gender-based predictors improve outcomes for both males and females?**

## Gender Differences: Treatment

**Are males and females equally likely to**
** ****drop out of  treatment?**
** ****relapse?**

**Gender Differences: Treatment**

## Gender Differences: Treatment

-    Variables that differentially predict relapse in men and women:
-   McKay et al. (1996)
- Prior to relapse
-    Women report
-  negative emotions and
-  interpersonal problems
-    Men report positive emotions

**Gender Differences: Treatment**

## Gender Differences: Treatment

**BETTER QUESTION**
**Are the predictors of these outcomes different for males and females?**
**  ****treatment retention**
**  ****relapse**

**Gender Differences: Treatment**

## Gender Differences: Treatment

**Suppose:**
**There’s no gender differences in **
**  ****treatment retention**
**  ****relapse**

**Gender Differences: Treatment**

**Can we conclude that gender does not play a role in these outcomes?**

## Gender Differences: Treatment

- Can retention and relapse rates for both males and females be improved by gender-sensitive strategies?

**Gender Differences: Treatment**