National Epidemiologic Survey on

Alcohol and Related Conditions

(NESARC): A CRITICAL REVIEW

Presenter: Amitkumar Chougule

INTRODUCTION

National Comorbidity Survey: Baseline (NCS-1) Conducted from

1990-1992 (NCS-2) was a follow up study conducted between 2001

and 2002

In 1992 United States conducted the National Longitudinal Alcohol

Epidemiologic Survey (NLAES)

The World Health Organization International Consortium in

Psychiatric Epidemiology (ICPE), 2000

2007 National Survey of Mental Health and Wellbeing, conducted by

the Australian Bureau of Statistics (ABS)

National Epidemiologic Survey on Alcohol

and Related Conditions (NESARC):

Household survey designed, conducted, and sponsored by

The National Institute on Alcohol Abuse and Alcoholism

(NIAAA)

Largest and most comprehensive survey conducted on

alcohol use, alcohol use disorders, and their physical and

psychiatric disabilities

WHAT IS THE NEED FOR STUDY?

1. To determine the prevalence of alcohol abuse and dependence

in disadvantaged groups

2. Accurate information on comorbidity of alcohol abuse and

dependence with other specific mental disorders is important

3. Comorbidity of alcohol abuse or dependence with other

disorders controlling for the comorbidity of these disorders with

each other has not been addressed

CONTINUED…

4.Recent US and international surveys deviated from DSM-IV

criteria by skipping alcohol dependence criteria if respondents

did not satisfy alcohol abuse criteria

5.This caused about one third of 12-month cases and about

15% of lifetime cases of alcohol dependence to be missed

6.Determining whether treatment needs that were unmet in the

early 1990s are now better served

NESARC’s Key Goals

1. To determine the extent of alcohol use disorders (AUDs)

and their associated disabilities in the general population

2. To estimate changes over time in AUDs

3. To determine treatment related factors

4. To determine the extent of major alcohol-related mental

and physical disabilities

First wave (Wave 1) 2001-2002 : baseline assessment for

prevalence data

Second wave(wave 2) 2004–2005: follow up data

Third wave: to be conducted……………

National Epidemiologic Survey on Alcohol and

Related Conditions (NESARC)

Methodology

The fieldwork for this survey was completed under NIAAA’s

direction by trained U.S. Census Bureau Field

Representatives through computer-assisted personal

interviews (CAPI) in face-to-face household settings

The sample included 43,093 respondents ages 18 and older,

representing the civilian, non institutionalized adult

population in the United States, including all 50 States and

the District of Columbia

The Wave 1 NESARC used a multistage stratified design in

which primary sampling units (PSUs) were stratified

according to Sociodemographic criteria

Data collection for Wave 2 began in August 2004 and was

completed by September 2005

The Wave 2 NESARC reinterviewed 34,653 of the 43,093

Wave 1 NESARC respondents

Response rate was 81 percent

Data Coverage

In both waves, the information was collected using the NIAAA

Alcohol Use Disorder and Associated Disabilities Interview

Schedule–Diagnostic and Statistical Manual of Mental

Disorders, Fourth Edition (DSM-IV) Version (AUDADIS-IV)

Fully structured diagnostic interview instrument

(questionnaire) designed for experienced lay interviewers

(Grant, Dawson, and Hasin 2001)

Measures used

NESARC Alcohol Items:

Primary focus of the NESARC is ALCOHOL

Which includes:

1. Amounts and patterns of consumption

2. Experiences associated with drinking

3. Classification of alcohol use disorders

4. Family history of alcohol problems

An alcoholic or problem drinker was defined for each

respondent during the interview as a person who has:

1. Physical or emotional problems because of drinking

2. Problems with a spouse, family, or friends because of drinking

3. Problems at work or school because of drinking

4. Problems with the police (like drunk driving) because of

drinking

5. Person who seems to spend a lot of time drinking or being

hung over

Alcohol Treatment

A respondent’s lifetime and past-year treatment seeking

status was determined

Other NESARC Items

1. Basic Demographic and Background Information

2. Tobacco Use Status

3. Drug Use Status

4. Medical Conditions

5. DSM-IV Mood and Anxiety Disorders

6. DSM-IV Personality and Conduct Disorders

NESARC's UNIQUE DESIGN

NESARC is unparalleled in a number of ways:

1. Large sample size of 43,093 people

2. Larger the sample size the more accurate the findings

3. Achievement of stable estimates of even rare conditions

4. Participants came from all walks of life and a variety of

ages

The investigators were able to obtain data on people not

typically captured by household surveys

To ensure that minority and special populations were well

represented in the sample, NESARC oversampled Blacks,

Hispanics, and young adults aged 18–24

Survey produced enough minority respondents to answer

questions of race/ethnic disparities in comorbidity and access

to health care services

NESARC’s unique design resulted in a rich dataset

Several sources of non sampling error could have occurred

such as:

1. Interviewers recording wrong answers

2. Respondents providing incorrect information

3. Respondents inaccurately estimating requested information

4. Unclear survey questions misunderstood by the respondent

(measurement error)

5. Missed individuals(coverage error)

6. Missing responses (nonresponse error)

7. Forms lost, and data incorrectly keyed, coded, or recoded

(processing error)

Prevalence, Correlates, Disability,

and Comorbidity of DSM-IV Alcohol Abuse

and Dependence in the United States:

Results from NESARC

Deborah S. Hasin, PhD; Frederick S. Stinson, PhD; Elizabeth Ogburn,

MS; Bridget F. Grant, PhD, PhD

The Magnitude of the Problem and Trends

over Time

Analysis using the data from NESARC and its predecessor

survey the 1991-1992 National Longitudinal Alcohol

Epidemiologic Survey (NLAES) showed trends in alcohol

abuse and dependence between 1991-1992 and 2001-2002

Results:

1. Alcohol abuse increased from 3.03 percent to 4.65 percent

2. Dependence declined from 4.38 percent to 3.81 percent

Increases in alcohol abuse were found in both men and

women, particularly among young Blacks and Hispanics

Rates of dependence increased among men overall, young

Black women, and Asian men

There was a decrease in the overall rate of dependence

The reasons behind this rise in rates of abuse and

dependence among minority young adults were unclear and

will need further investigation

This study underscores the importance of trends in alcohol

abuse and dependence

Prevalence OF AUDs

The 12-month prevalence of DSM-IV

1. alcohol abuse - 4.7%

2. dependence - 3.8%

12- month prevalence of any alcohol use disorder was 8.5%

The lifetime prevalence of DSM-IV

1. alcohol abuse- 17.8%

2. dependence - 12.5%

Total lifetime prevalence of any alcohol use disorder was 30.3%

Alcohol dependence was significantly more prevalent among:

1. Men

2. Whites

3. Native Americans

4. Younger and unmarried adults

5. Those with lower incomes

Current alcohol abuse was more prevalent among:

1. Men

2. Whites

3. Younger and unmarried individuals

Lifetime rates were highest among middle-aged Americans

According to NIAAA’s low-risk drinking guidelines:

Men may be at risk if they drink:

More than 14 drinks per week or more than 4 drinks on any

day

Women may be at risk if they drink:

More than 7 drinks per week or more than 3 drinks on any day

The prevalence of alcohol dependence with abuse increased

in a fairly linear fashion with frequency of exceeding daily

drinking limits

The prevalence of dependence alone (no abuse) and abuse

alone (no dependence) peaked among persons who

exceeded the daily limits twice a week and then leveled off

This data support the utility of the daily and weekly drinking

limits in predicting AUDs

Socio-demographic and clinical

characteristics

The risk of continued/recurrent dependence increased with:

1. Ethanol intake

2. People with 10 or more life-time dependence symptoms

3. Positive histories of illicit drug use and personality disorders

The risk of dependence decreased with:

1. Age

2. high-school graduation

3. reduced among women

4. non-Hispanic whites

5. married people

Evidence for a two-stage model of

dependence

Twin studies suggest that substance initiation and

dependence are part of a complex two-stage process

Some genetic influences are stage-specific acting on either

the transition from abstinence to initiation or on the transition

from use to dependence

Family history of drug or alcohol problems is significantly

associated with initiation that does not progress to

dependence (i.e., conditional initiation)

Family history of drug or alcohol problems is significantly

associated with dependence even after conditioning on

factors influencing initiation (i.e., conditional dependence)

These results suggest that substance initiation and

dependence involve at least partially distinct familial factors

The possibility that different genetic factors affect initiation

and dependence has important implications for control group

selection in case–control genetic association studies

The researchers identified 5 subgroups of alcoholism:

1."Young-adult" subtype (31.5% of US alcoholics):

Dependent on alcohol within 3 years of drinking onset

low rates of abuse of other substances and family alcoholism

2."Young-antisocial" subtype (21.1% of US alcoholics):

Dependent on alcohol within 3 years of drinking onset

They tend to have antisocial personality disorder, multiple psychiatric

comorbidities, problems with other types of substance abuse and a

family history of alcoholism

3."Functional" subtype (19.4% of US alcoholics):

middle-aged, well-educated, good jobs

dependent on alcohol for about 18 years

4."Intermediate-familial" subtype (18.8% of US alcoholics):

middle-aged dependent on alcohol for 15 years

family history of alcoholism and multiple comorbidities

5."Chronic-severe" subtype (9.2% of US alcoholics):

middle-aged

Dependent on alcohol for about 13 years

Tend to have a multigenerational family history of alcoholism

Highest rates of other psychiatric disorders

ONSET AND COURSE OF DSM-IV ALCOHOL USE

DISORDERS

Mean ages at onset of alcohol:

1. Abuse 22.5 years

2. Dependence 21.9 years

Hazard rates for onset peaked at age 19 years and

decreased thereafter

Mean durations of longest episodes of alcohol abuse and

dependence were 2.7 and 3.7 years

Onset of drinking at a young age(< 14 years) has much

higher risk of :

1. Developing a problem with alcohol later in life

2. Dependence within 10 years of beginning drinking i.e

before age 25

3. Multiple episodes of dependence

4. Episodes of dependence followed by non dependence

5. Delinquency and criminal activity

6. Drinking and driving

PRESCRIPTION DRUG MISUSE (PDM) AND ALCOHOL

DEPENDENCE:

Alcohol dependent and cannabis-users with (PDM) were

significantly more likely to report alcohol-related “risk-taking

behaviors” or “interpersonal troubles” than were those

without PDM

The mean number of episodes among respondents with

multiple episodes of abuse and dependence was 5.2 and 5.1

respectively

Mean duration of dependence episodes differed significantly

(P.01) between those with one episode (3.4 years) vs

multiple episodes (2.4 years)

TREATMENT FOR DSM-IV ALCOHOL USE

DISORDERS

Those with lifetime alcohol dependence only 24.1% ever

received treatment

Those with 12-month alcohol dependence only 12.1%

received alcohol treatment in the past year

Treatment rates were lower than treatment rates 10 years

earlier

Among those with 12-month alcohol dependence:

1. 7.4%received help from 12-step (self-help) groups

2. 10.0% from any health professional other than 12-step

groups employee assistance programs, or clergy

3. 6.7% from physicians or other health professionals

Of those with 12-month alcohol abuse:

1. 2.0% received help from 12-step groups

2. 0.0% (halfway houses) to 1.9% (any professional other

than 12-step groups, employee assistance programs, or

clergy)

Lifetime professional treatment rates were 4.5% among

respondents with alcohol abuse and 20.1% among

respondents with alcohol dependence

In the NESARC, the mean age of respondents first treatment

for dependence was 29.8 years

8-year mean lag between onset and treatment

The mean age of first treatment for abuse was 32.1years

10-year mean lag between onset and treatment

Characteristics that significantly (P.05) predicted

treatment:

1. For 12-month alcohol dependence the lowest income

category predicted treatment

2. For 12-month abuse those widowed, separated, or

divorced, those with less than high school education were

more likely to receive treatment

Reasons for not seeking alcohol

treatment

1. Should be strong enough to handle it alone

2. Thought problem would get better by itself

3. Stop drinking on my own

4. Did not think drinking problem was serious

5. Was too embarrassed to discuss it with anyone

RECOVERY

25.0% of all US adults with prior-to-past-year (PPY) alcohol

dependence were still dependent in the past year

27.3% were in partial remission

10.5% met the criteria for alcohol abuse

16.8% reported a subclinical array of dependence symptoms

Half of all people with PPY dependence met the criteria for

full remission

This includes asymptomatic risk drinkers (11.8%), low-risk

drinkers (17.7%) and abstainers (18.2%)

Combining low-risk drinkers (Non abstinent remission NR)

and (abstinent remission AR) more than one-third (35.9%)

had a past-year status indicative of full recovery

Among people with PPY dependence who were still

dependent in the year preceding interview just 28.8%

reported having received treatment

Nearly one-quarter of PPY alcohol-dependent individuals had

achieved NR or AR in the past year without benefit of

treatment

The rate of stable natural recovery (lasting 5 years) was

20.6%

Entry into and exit from a first marriage each increased the

likelihood of non-abstinent recovery during the first 3 years

after those events occurred

The likelihood of abstinent recovery was more than doubled

in the 3 years after first becoming a parent

AR was more common among:

1. Blacks

2. People with relatively severe dependence

3. life-time smokers

4. People with a history of treatment for alcohol problems

NR was more common among persons who:

1. Attended college

2. Reported non-dependent use of illicit drugs

There is a wide range of recovery from alcohol dependence

in the general population, from partial remission to full

abstinence

Track of this disease is not clear-cut

some people appear to recover from alcoholism without

formal treatment

Others may cycle into and out of dependence throughout

their lifetime despite repeated attempts to achieve sobriety

RELAPSE:

Relapse by wave 2:

1. 51.0% of the Wave 1 asymptomatic risk drinkers

2. 27.2% of low-risk drinkers

3. 7.3% of abstainers

Abstinence represents the most stable form of remission for

most recovering alcoholics

Need for better approaches for maintaining recovery among

young adults in remission who are at high risk of relapse

CRITIQUE

No conclusions can be drawn from findings regarding:

1. The effectiveness of treatment

2. Overall relationship between drinking status and treatment

status

It is not clear what constituted ‘treatment’ for the NESARC

respondents

There was a substantial recovery rate without treatment

About half of all recoveries involved low risk drinking rather

than abstinence

Necessity of a small intensively studied sample whom the

investigator has actually met in case of confidential

information

To study the information regarding return to controlled

drinking one needs to:

1. Include other informants

2. To conduct observations over time until the true

information emerges

3. Can be ruled out on a case-by-case basis

This study could not provide any guidelines concerning who

really must stop drinking in order to recover from

dependence, and who can recover stably from dependence

even while drinking moderately

What might constitute appropriate services:

1. Public information and education showing that recovery from

alcohol problems without treatment is not only possible but

also frequent

2. For those who are not successful the attempt may increase

their readiness to seek help

3. Further study alternatives to abstinence

4. Attracting people with less serious alcohol problems to

treatment

5. Training health-care providers and addiction counselors to

competently provide moderation services

ASSOCIATIONS BETWEEN DSM-IV

ALCOHOL USE DISORDERS AND

OTHER PSYCHIATRIC DISORDERS

CONTROLLING FOR SOCIODEMOGRAPHIC

CHARACTERISTICS AND OTHER COMORBIDITY

1. 12 month alcohol abuse remained strongly and significantly

associated with substance use disorders (OR 1.8)

2. But not with other Axis I disorders

3. Was negatively associated with schizoid PD and Bipolar I disorder

4. A similar pattern was observed for lifetime abuse

12 month alcohol dependence remained strongly

associated with:

1. Substance use disorders (ORs=3.4-7.5)

2. bipolar disorders but with lower ORs (1.9, 2.0)

Significant association with 2 Axis II disorders:

1. Histrionic PD

2. Antisocial PD

Lifetime DSM-IV alcohol dependence remained positively

although less strongly associated with :

1. Substance use disorders

2. Most mood and anxiety disorders

3. Paranoid, histrionic, and antisocial PDs

Rates of any PD were greater among respondents with any

drug abuse (37.8%) and any drug dependence (69.5%) than

among respondents with alcohol abuse (19.8%) and alcohol

dependence (39.5%)

Patients with comorbid alcohol and drug use disorders and

PDs can be expected to require treatment that is more

extensive and of longer duration

Modified psychoanalytic psychotherapy focused or targeted

on particular features of PDs should be used

Nicotine dependence was reported by 48% of the alcohol-

dependent respondents

They reported higher lifetime rates of:

1. Panic disorder

2. Specific and social phobia

3. Generalized anxiety disorder

4. Major depressive episode

5. Manic disorder

6. Suicide attempt

7. Antisocial personality disorder

8. All addictive disorders

Probability of transitioning to substance dependence

among substance users

1. After the first year of substance use onset the probability of

transition to dependence was highest for COCAINE users

2. The probability estimates of transition to dependence a

decade after use onset was highest for NICOTINE users

3. Lifetime cumulative estimated probability of use to

dependence was highest for NICOTINE users

Predictors of transition from substance use to

dependence

Socio-demographic predictors :

1. Females were more likely than males to transition from

nicotine use to dependence

2. Males were more likely to transition from alcohol and

cannabis use to dependence

3. US-born Individuals were more likely than foreign-born

individuals to report transition from nicotine and alcohol

use to dependence

Psychopathological and substance use-related

predictors

A history of any mental disorder strongly predicted the

development of substance dependence

Nicotine , alcohol, cannabis or cocaine users diagnosed with

a mood disorder or a PD were more likely to become

dependent on those substances

Nicotine, alcohol or cannabis users diagnosed with an

anxiety disorder showed an increased risk of becoming

dependent on these substances

A lifetime diagnosis of a psychotic disorder increased the

risk of developing nicotine dependence among nicotine users

Having a history of SUD predicted a further development of

an additional SUD

Individuals diagnosed with nicotine dependence were more

likely to develop alcohol dependence among alcohol users

and cannabis dependence among cannabis users

Family history of SUD increased the risk of transition from

nicotine or alcohol use to dependence

The cumulative probability of transition to dependence was

highest for nicotine users and least for cannabis users

The transition to cannabis or cocaine dependence occurred

faster than the transition to nicotine or alcohol dependence

Cannabis use:

Later onset cannabis use:

1. Religious and pro-social activities are negatively

associated

2. Divorce, alcohol and nicotine-related problems are

positively associated

Social anxiety disorder (SAD) was more likely to be related to

cannabis dependence than abuse

Substance use disorders among inhalant

users:

The lifetime prevalence of SUDs among adult inhalant users

was 96%

Compared with substance users without a history of inhalant

use inhalant users:

1. Initiated use of cigarettes, alcohol, and almost all other

drugs at younger ages

2. Higher lifetime prevalence of nicotine, alcohol, and any

drug use disorder

Nonmedical prescription drug use and drug

use disorders:

The odds of nonmedical prescription drug use and drug use

disorders were greater among:

1. men, Native Americans, young and middle-aged

2. widowed/separated/divorced or never married

Abuse/dependence liability was greatest for amphetamines

Nonmedical prescription drug use disorders were highly

comorbid with other Axis I and II disorders

The majority of individuals with nonmedical prescription drug

use disorders never received treatment

Epidemiology of MOOD

Disorders

Results From the National Epidemiologic

Survey on Alcoholism and Related Conditions

Deborah S. Hasin, PhD; Renee D. Goodwin, PhD; Frederick S. Stinson,

PhD; Bridget F. Grant, PhD, PhD

PREVALENCE AND SOCIODEMOGRAPHIC

CORRELATES

Prevalence rates of DSM-IV were:

Major depressive disorder:

1. Lifetime 13.23%

2. 12-month 5.28%

Bipolar 1 lifetime and 12-month were 3.3% and 2.0%

Bipolar 2 lifetime and 12-month rates were 1.1% and 0.8%

Women showed a significantly higher risk for MDD

MDD had strongest risk among those 45 to 64 years old

Risk of MDD did not differ by education, region, or urbanicity

ONSET, COURSE, AND TREATMENT

Mean age at onset of MDD was 30.4 years

The hazard for onset of MDD increased sharply between

ages 12 and 16 years and continued to increase up to the

early 40s when it began to decline

Among respondents with lifetime MDD a mean of 4.7

episodes was reported with median duration of 24.3 weeks

for the longest (or only) episode

PREVALENCE OF DSM-IV AXIS I AND II

DISORDERS AMONG RESPONDENTS WITH MDD

Among those with MDD in the prior 12 months:

1. 14.1% had an alcohol use disorder

2. 4.6% had a drug use disorder

3. 26.0% had nicotine dependence

4. 36.1% had at least 1 anxiety disorder

5. The prevalence of any PD was high (37.9%) and quite

variable from PD to PD

Among those with lifetime MDD:

1. 40.3% had an alcohol use disorder

2. 17.2% had a drug use disorder

3. 30.0% had nicotine dependence

4. 40% had an anxiety disorder

5. 30% had a PD

Conclusions about MDD from NESARC

Average duration was almost 6 months longer than the

previous estimate of 4 months

Almost half the respondents with MDD thought about suicide

or wanted to die

The findings disclose higher risk for MDD among Native

Americans

NESARC findings of lower risk for Hispanics and Asians

contributes new information

Strong association of MDD with dependence on alcohol,

drug, and nicotine, in contrast with a weak relationship of

MDD with substance abuse

These results highlight the importance of not lumping abuse

and dependence together when studying comorbidity

The comorbidity of substance dependence with MDD

predicts poor outcome among patients

Treating MDD that is comorbid with alcohol or drug

dependence is now recommended

Panic attacks and suicide:

Panic attacks appear to be an independent risk factor for

suicide attempt among depressed individuals with and

without suicidal ideation

Assessment panic symptoms may improve prediction of

suicide attempts

The presence of atypical features during an MOOD

DISORDER EPISODE (MDE) was associated with greater

rates of lifetime psychiatric comorbidity like:

1. Alcohol abuse

2. Drug dependence

3. Dysthymia

4. Social anxiety disorder

5. Specific phobia

6. Personality disorder

MDE with atypical features was associated with:

1. Female gender

2. Younger age at onset

3. More Mood disorder episodes

4. Greater episode severity and disability

Higher rates of:

1. Family history of depression

2. Bipolar I disorder

3. Suicide attempts

4. Larger mental health treatment-seeking rates

Variables determined to be predictors of BD I :

1. unemployment (OR = 0.6)

2. Taking medications for depression (OR = 1.7)

3. History of a suicide attempt (OR = 1.8)

4. weight gain (OR = 1.7)

5. Fidgeting (OR = 1.5)

6. Feelings of worthlessness (OR = 1.6)

7. Difficulties with responsibilities (OR = 2.2)

8. Presence of specific phobias (OR = 1.8)

9. Cluster C traits (OR = 1.4)

The mean age of BD-I subjects with CVD and HTN was 14

and 13 years younger, respectively, than controls with CVD

and HTN

Adults with BD-I are at increased risk of CVD and HTN,

prevalent over a decade earlier than non-BD adults

Role of self-medication in the development of

comorbid mood and drug use disorders

Self-medication with drugs among individuals with mood

disorders confers substantial risk of developing incident drug

dependence and is associated with the persistence of

comorbid mood and drug use disorders

The Intricate Link Between

Violence and Mental Disorder

Results From the National Epidemiologic Survey on

Alcohol and Related Conditions

Eric B. Elbogen, PhD; Sally C. Johnson, MD

Results provide empirical evidence that :

Severe mental illness is not a robust predictor of future

violence

People with co occurring severe mental illness and

substance abuse/ dependence have a higher incidence of

violence than people with substance abuse/dependence

alone

CRIMINAL VICTIMIZATION:

More than 1-in-25 adults in the United States (4.1%) reported

past-year criminal victimization

Risks for criminal victimization:

1. Lower levels of income

2. Living in urban areas

3. Separated or divorced

Crime victims evidenced significantly increased rates of:

1. alcohol, cocaine, and opioid use disorders

2. Paranoid personality disorder, major depressive disorder,

and a family history of antisocial behavior

Psychiatric disorders among foreign-born and US-

born Asian-Americans (AAs) in a US national survey

Foreign-born AAs had significantly lower risk for all classes of

disorder compared with US-born AAs (OR = 0.16–0.59)

Risk for all classes of disorder was lowest for those foreign-

born AAs who arrived in the US as adults

Developmental timing and the duration of experience in the

US contribute to increases in risk

An invariant dimensional liability model of

gender differences in mental disorder

prevalence: Evidence from NESARC

Gender differences in prevalence were systematic such that

women showed higher rates of mood and anxiety disorders,

and men showed higher rates of antisocial personality and

substance use disorders

women showed a higher mean level of internalizing, while

men showed a higher mean level of externalizing

Pathological gambling

Three classes (or subtypes) of gamblers:

1. Behaviorally conditioned

2. Emotionally vulnerable

3. Antisocial impulsivist

Blaszczynski and Nower's (2002) pathways model may

eventually contribute to the development of more reliable and

valid methods of identifying people who are at risk of

developing gambling problems

Physical Punishment and Mental Disorders:

Approximately 2% to 5% of Axis I disorders and 4% to 7% of

Axis II disorders were attributable to harsh physical

punishment.

Harsh physical punishment in the absence of child

maltreatment is associated with mood disorders, anxiety

disorders, substance abuse/dependence, and personality

disorders in a general population sample

Association Between Peptic Ulcer and

Personality Disorders:

All seven personality disorders were associated with stomach

ulcer

Participants with ulcer were five times more likely to have

more than three personality disorders than participants

without ulcer

CONCLUSION

NESARC is an example of a large, random, representative

survey of adults living in the United States

This survey addressed all aspects of alcohol use—from

determining when a respondent took his or her first drink to

discovering whether he or she had experienced co-occurring

mental health problems

NESARC data have several practical applications like

defining the intricate relationship between alcohol use and

comorbidity, to study high-risk drinking patterns, to design

better-targeted treatment approaches, and to monitor

recovery from AUDs

As more researchers take advantage of the richness of this

dataset, more knowledge will be gained, helping to advance

prevention efforts and treatment interventions in the alcohol

field