PPT details findings of 2013 study, with link to paper here: https://psyarxiv.com/u3hg9/

1. Trauma and
Alcoholism
By Colleen M. Farrelly

2. Alcoholism and Trauma
• Trauma as a risk factor
o Common experience for soldiers
and civilians in United States
• 25-50% of adolescents have
experienced 1+ traumatic
event
• 50-75% of adults
o Childhood, adulthood, both
o Post-traumatic stress disorder and
relapse link found in veteran
populations
o Trauma cycle (more likely to
experience again if experienced
once)
o Worse alcoholism treatment
response for those with PTSD
• Alcoholism affects roughly 7%
of the United States population
at a given time.
o Higher lifetime prevalence
o Treatment efficacy lower for earlier-
onset disease
• Genetic risk
o GWAS identification
• DRD2, ADH1B, GABRA2, ALDH2,
ADH4, AUTS2, MAOA, 5-HTTLPR
o Evidence of genetic link to early-onset
alcoholism
o Twin studies of Vietnam veterans and
PTSD
• Environmental risk
o Age, gender, age of first use
o Trauma
• Civilians and returning veterans of
OIF/OEF

3. Specific Aims
• Aim 1
o To examine which traumatic experience types are
associated with alcoholism
• Childhood physical or sexual abuse
• Adulthood assault, non-assault, or sexual trauma
• Aim 2
o To examine whether childhood trauma predicts age of
onset of alcoholism
• Childhood physical abuse
• Childhood sexual abuse

4. Measurements
• Other environmental
variables
• Demographics
• Age
• Income
• Education level
• Size of childhood town
• Use of alcohol
• Onset of symptoms
• Diagnosis
• Family history
• Mother and father history of
alcohol abuse and dependence
• Trauma Types
• Childhood physical abuse
• Hurt the next day or had to visit
doctor
• Broken bones, bruises, scalding,
burns inflicted by an adult
• Childhood sexual abuse
• Before 16 sexual contact, including
touching and intercourse with
someone 5+ years older
• Adult non-assault trauma
• Natural disasters
• Adult assault trauma
• Military combat, legal definition of
assault
• Adult sexual assault
• Attempted or completed
• Forced unwanted sexual contact

5. Sample
• Median education: 1 year of
college
• Median income: $20,000-
$29,000
• Family history of alcoholism
o 11 reported maternal alcoholism
o 19 reported paternal alcoholism
• Trauma history
o 52.1% reported a positive history of
trauma
o 25.7% reported more than 1 type of
trauma
o Adulthood non-assault trauma most
common
• Participants from
Collaborative Studies on
Genetics of Alcoholism
Study
o Case-Control
• 167 Caucasian adults
• 85 cases, 82 controls
o Case definition: DSM-IV criteria
met at some point during lifetime
• 84 women, 83 men
• Ages 18-70 years,
mean=41 years

6. Analysis
• Aim 1
o Logistic regression models for each trauma type, as well as
logistic regression on total number of trauma types experienced
• Aim 2
o Kaplan-Meier curve and log-rank test of proportional hazards
assumption
o Univariate Cox regression for relative risk
o Multivariate Cox regression adjusting for family history of
alcoholism and demographic factors

7. Results: Aim 1 Regression Models
* p<0.05, ** p<0.01, *** p<0.001 under Bonferroni correction. Significant predictors
include any other significant factors identified in the logistic regression model.
.
Regression
Trauma
Number (%)
Reporting
Trauma
Wald X2 Odds Ratio
(OR)
95% CI of OR p-value Significant
Predictors
Childhood
Physical
Abuse
33 (19.8%) 7.84 6.68 1.77-25.27 0.005** Education*,
Income***
Childhood
Sexual Abuse
38 (22.8%) 11.86 8.83 2.56-30.47 <0.001*** Education*,
income***,
Gender*
Adulthood
Non-Assault
50 (30.0%) 3.14 2.45 0.91-6.61 0.076 Income***,
Education*
Adulthood
Physical
22 (13.2%) 7.93 12.03 2.13-67.93 0.005** Income***
Adulthood
Sexual
15 (9.0%) 2.99 4.67 0.81-26.84 0.084 Education*,
Income***
Total Trauma 87 (52.1%)
reporting 1+
16.58 Significant
for 0 vs. 1+
traumas
Significant for
0 vs. 1+
traumas
<0.001*** Education*,
Income***

8. Aim 2: Age to Onset of Cases
Case Onset Quantiles
Percent Point
Estimate
95% Confidence Interval
[Lower Upper)
75% 30 28 33
50% 23 22 26
25% 20 19 21

9. Kaplan-Meier Survival Curves by Childhood
Physical Abuse Status

10. Kaplan-Meier Survival Curves by Childhood
Sexual Abuse Status

11. Summary of Univariate and Multivariate Cox
Regression Models
Log-rank
X2
p-
value
Univariate
Hazard Ratio
(95% CI)
Multivariate
Hazard
Ratio (95%
CI)
Other
Significant
Predictors
Physical
Abuse
35.67 <0.001 3.87 (2.41-
6.24)
2.14 (1.27-
3.61)
Age,
Education,
Gender,
Paternal
History
Sexual
Abuse
31.05 <0.001 3.51 (2.20-
5.61)
2.71 (1.62-
4.55)
Age,
Education,
Gender,
Income

12. Genetic Risk
Log-rank
X2
p-
value
Univariate
Hazard Ratio
(95% CI)
Maternal
History
17.36 <0.001 3.80 (1.94-
7.43)
Paternal
History
22.88 <0.001 3.62 (2.06-
6.33
• Possible more
complicated model
of trauma, genetic
risk, and
demographic factors
• Future work to
examine
interactions and
mediation planned

13. Discussion of Results
• Both childhood traumas
increased risk of earlier-
onset alcoholism
o Adjusted relative risk >2.0
• Also found strong family
history association with
possible complex
relationship to risk
o Suggests a genetic component to
age-of-onset with physical trauma
o Further study needed to test age-
of-onset and specific single
nucleotide polymorphisms
• Trauma related to
alcoholism for many
types of trauma
• Number of types of
trauma showed no dose-
response
o But higher odds ratios for no
trauma vs. increasing number of
traumas
• Important to consider in
prevention and treatment
of alcoholism

14. Limitations/Next Steps
Limitations Future Studies
• No data on frequency or severity
of traumatic events
o Previous research suggests importance of
these
• No data on diagnosed PTSD
o Numerous studies of PTSD and alcoholism
risk in combat veterans
• Case-control nature of this study
• Small sample size
• Caucasian sample
• No genomic data used
• Fairly simple statistical methods
that may miss complex
interactions between risk
factors.
• Genomic and gene x
environment studies of
alcoholism risk and age-of-onset
o Few/no existing studies on this
• Diverse population
• Civilian and military populations
o Different types of traumatic events
o Civilian assaults vs. combat
• Utilizing more information about
types, frequencies, and severity
of traumatic events
• Use of machine-learning-based
survival analysis tools

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