Child Abuse and Other Traumatic Experiences, Alcohol Use Disorders,
and Health Problems in Adolescence and Young Adulthood
Duncan B. Clark, MD, PHD, Dawn L. Thatcher, and Christopher S. Martin
Pittsburgh Adolescent Alcohol Research Center, University of Pittsburgh
objective health indicators and consideration of alcohol use disorders (AUD).
(n¼668) were recruited from clinical and community sources. At baseline, we examined child abuse and other
traumas, AUD, health-related symptoms, physical findings, and blood assays. Subjects were assigned to Trauma
Classes (TC), including witnessing violence, physical abuse, and sexual abuse. Health outcomes were again
determined at 1-year and young adult follow-up.Results
with more health-related symptoms, increased age-adjusted body mass index, and stress-response immune
system indices. In adolescence and young adulthood, the relationships between TC and health-related symp-
toms were mediated by anxiety. AUD was associated with liver injury, and cigarette smoking with heart/lung
symptoms. ConclusionsChild abuse predicted persistently elevated health-related symptoms primarily
attributable to anxiety, and early signs of liver disease were attributable to AUD.
We prospectively examined the health effects of child abuse and other traumatic events, with
In adolescence, higher TC severity was associated
Key words adolescents; alcohol use; child abuse; health.
Child abuse has been found to predict mental disorders,
substance-related problems, and health risk behaviors
(Gilbert et al., 2009). Retrospective studies with adults
have suggested that child abuse leads to major physical
health problems (Brown, Young, Anda, Felitti, & Giles,
2006). Child abuse has been systematically related
to diminished subjective health quality and obesity
(Thomas, Hypponen, & Power, 2008). With some specific
conditions excepted (e.g., sexually transmitted diseases:
Wilson & Widom, 2009); however, few prospective
studies have examined whether child abuse leads to phys-
ical health problems. In addition, consideration of the
relationship between child abuse and later substance use
disorders is important for understanding health outcomes.
A few studies have examined the relationship between
child maltreatment and global health status. Hussey and
colleagues (Hussey, Chang, & Kotch, 2006) studied a
large sample of adolescents who, when follow-up in
young adulthood, completed a retrospective child abuse
questionnaire. Child abuse reports were associated with
poorer subjective health quality in adolescence. Among
378 adolescent enrolled in addictions treatment (Stevens,
Murphy, & McKnight, 2003), PTSD-like symptoms were
positively associated with subjective health symptoms.
Among 1041 children at high risk for child abuse and
neglect (Flaherty et al., 2006), child maltreatment at age
4 years predicted poorer overall child health at age 6 as
well as an increased incidence of illnesses requiring
Child abuse has been associated with overweight
status in some studies. In the Hussey study (2006), phys-
ical abuse, but not sexual abuse, was found to be asso-
ciated with overweight status by BMI in late adolescence.
Among 782 community subjects (Johnson, Cohen, Kasen,
& Brook, 2002), childhood sexual abuse (n¼22) was not
associated with adolescent or young adulthood obesity.
In a prospective study of female children with sexual
abuse (n¼84) and a comparison sample (n¼102),
those with a sexual abuse history showed a more rapid
increase in BMI during adolescence and a higher obesity
rate in young adulthood (Noll, Zeller, Tricket, & Putnam,
2007). Among over 9,000 children followed to middle
adulthood (Thomas et al., 2008), physical abuse, but not
sexual abuse, predicted increased BMI and higher rates of
All correspondence concerning this article should be addressed to Duncan B. Clark, MD, PhD, Western Psychiatric
Institute and Clinic, 3811 O’Hara Street, Pittsburgh, PA 1521, USA. E-mail: firstname.lastname@example.org
Journal of Pediatric Psychology 35(5) pp. 499–510, 2010
Advance Access publication December 4, 2009
Journal of Pediatric Psychology vol. 35 no. 5 ? The Author 2009. Published by Oxford University Press on behalf of the Society of Pediatric Psychology.
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obesity in middle adulthood. In the latter study, child
abuse did not predict type 2 diabetes in middle adulthood.
Comorbid obesity, high blood pressure, lipid abnormal-
ities, increased blood glucose, and diabetes mellitus have
been termed ‘‘metabolic syndrome’’ (Steinberger et al.,
2009). Given a relationship between child abuse and obes-
ity, one might expect that child abuse would predict
elevations in other metabolic syndrome indicators. This
possibility has not been studied.
Stressors have been found to induce changes in
immune functioning, and immune system indicators may
be relevant to understanding child abuse and health. In the
laboratory, immunoglobulin increases have been demon-
strated in response to acute stressors (Endresen et al.,
1991). Immunoglobulin increases have also been observed
in response to natural stressors. In young adults, school
exams predicted increases in plasma immunoglobulins
IgM, IgG, and IgA (Glaser, Mehl, Penn, & Speicher,
1986). A study comparing 14 girls with sexual abuse and
13 control girls (De Bellis, Burke, Trickett, & Putnam,
1996) did not observe significant group differences on
levels have not been previously studied in association
with child abuse.
While individuals with child abuse have not been
reported to have diagnosed medical diseases in adoles-
cence and young adulthood, studies in later adulthood
have noted an association between child abuse and some
specific medical disease outcomes. Adults with child
maltreatment histories have been reported to show ele-
vated rates of liver disease, lung cancer and heart disease
(Dong, Dube, Felitti, Giles, & Anda, 2003; Dong et al.,
2004; Brown et al., 2006). These medical diseases may be
an indirect result of risky health behaviors, particularly
substance use disorders.
Childhood abuse has been found to be associated with
or to predict adolescent substance use disorders. Among
3,559 students in grades 7 through 12, Hamburger, Leeb,
and Swahn (2008) found that sexual abuse, physical
abuse, and witnessing violence were associated with
increased preteen alcohol use. Using data from the
National Longitudinal Study
(n¼12,748), Shin, Edwards, and Heeren (2009) found
physical abuse and sexual abuse were associated with
binge drinking. In a subset of the subjects described
here, sexual abuse, physical abuse, and other stressors
were more common among adolescents with AUD than
among control adolescents (Clark, Lesnick, & Hegedus,
1997a). Physical or sexual abuse accelerated the onset
of AUD and accounted for the relationship between AUD
and major depressive disorder (Clark, De Bellis, Lynch,
Cornelius, & Martin, 2003).
The adverse health consequences associated with
AUD, reflected by organ pathology and disease history,
have been more systematically studied in adults than
in adolescents. In adults, abnormalities found to be
caused by chronic alcohol dependence include elevated
liver injury indices (Allen, Fertig, Litten, Sillanaukee, &
Anton, 1997), elevated immunoglobulins (Mili, Flanders,
Boring, Annest, & DeStefano, 1992), elevated erythrocyte
mean cell volume (MCV) (Seppa, Sillanaukee & Koivula,
1992), and decreased electrolytes, such as calcium,
magnesium, phosphate, and potassium (Elisaf, Bairaktari,
Kalaizidia, & Siamopoulos, 1998). The medical records
of 417 adolescents with substance use disorders and
2082 demographically matched subjects, those with sub-
stance use disorders had more abdominal pain, sleep dis-
orders, and asthma (Mertens, Fisher, Fleming, & Weisner,
2007). In some of the subjects described here (Clark,
Lynch, Donovan, & Block, 2001), 128 adolescents with
AUD (compared with 131 controls) showed more
health-related symptoms (HS), laboratory tests indicating
liver injury, and some physical exam abnormalities. Thus,
some health problems reported by adolescents with
AUD have been verified by objective findings and may be
attributable to toxic alcohol effects on the liver and other
While adolescents with AUD evidence objective
indicators of some health problems, their subjective HS
seem disproportionately elevated. These HS may, to some
extent, reflect somatic anxiety symptoms (Ginsburg,
Riddle, & Davies, 2006). In prior reports on the present
sample (Clark et al., 1997b), adolescents with AUD were
observed to have elevated rates of anxiety disorders, includ-
ing PTSD. In our study of health problems among adoles-
cents with AUD (Clark et al., 2001), we found that an
index of negative emotionality was highly correlated with
HS, mediated the relationship between AUD and HS, and
was not correlated with serum liver enzyme levels or phys-
ical exam abnormalities. Among adult women (Lang et al.,
2008), child abuse was observed to lead to mental and
physical health difficulties through anxiety disorder symp-
toms. Child abuse may induce HS, at least in part, through
Prior research has had several shortcomings. In most
studies, the relationship between child abuse and
health outcomes has been determined exclusively with
cross-sectional or retrospective methods. In some studies,
decades have passed between recalled childhood events
and the adulthood assessment, amplifying the potential
for recall bias. The available studies on adolescents have
Clark, Thatcher, and Martin
typically assessed health status with only a few global and
subjective questions. Some studies with large community
samples have included few subjects with child abuse
histories. Studies on child abuse have rarely examined
the effects of other traumatic experiences. Substance use
that may adversely influence health outcomes has typically
not been concurrently examined. The extent to which HS
may be attributable to anxiety has also been neglected in
child abuse studies.
The present study addresses several of these shortcom-
ings. We examined relationships among child abuse,
AUD, and physical health problems in adolescence, and
prospectively assessed later adolescent and young adult
health outcomes. This is the first study to examine these
relationships with a comprehensive physical health assess-
ment. The evaluation included questions on 136 health
symptoms, laboratory studies of blood including liver
injury and other objective indicators, and physical exam-
inations including blood pressure and body mass index
(BMI) measurements. Child abuse was considered in the
context of other traumatic experiences. We concurrently
measured AUD and cigarette smoking. The study con-
ducted 1-year follow-up and young adult outcome evalu-
ations. We hypothesized that child abuse and other
traumatic experiences would be associated with HS,
being overweight, and stress-related laboratory findings,
while AUD would be associated with liver injury. We
expected the relationship between child abuse and HS to
be mediated by anxiety.
Subjects were 668 adolescents (ages 12- to 18-years old)
participating in a longitudinal study at the Pittsburgh
Adolescent Alcohol Research Center recruited from clinical
(n¼455) and community (n¼213) sources. Clinical
sources included hospital-based out-patient and in-patient
addictions and psychiatric programs, free-standing addic-
tions programs, and residential programs for youth with
family difficulties. Community subjects were randomly
selected from the local area using survey methods. More
details on these methods have been presented in prior
publications (Clark et al., 2001). The subjects were 48%
female (n¼317), 16.2?1.5 years old, and 81% whites
(n¼541) and 19% African Americans (n¼127). Six sub-
jects from other races were excluded here. By Hollingshead
Two-Factor Index of Social Position (1975), socioeconomic
status (SES) determined by combining weighted education
and job status scores was 37.5?13.5. SES scores range
from 11 to 77, and middle class families score from 28 to
43 (Hong, Nelesen, Krohn, Mills, & Dimsdale, 2006).
The 1-year follow-up assessment was completed with
555 of these 668 subjects (83%). Subjects missing the
1-year follow-up, compared to those completing the
1-year follow-up assessment, were more likely to be male
(68% vs. 49% for subjects who missed the visit and those
who completed the visit, respectively; w2¼13.3, df¼1,
p<.001), not different on age at baseline (16.3?1.5 vs.
16.2?1.5, F¼0.0, df¼1,666, p¼.9), not different on
race (22% African American vs. 18% African American,
38.6?13.0, F¼19.0, df¼1,666, p<.001), less likely
to have been recruited from the community (18% vs.
35%, w2¼12.6, df¼1, p<.001), and more likely to
have had adolescent AUD (56% vs. 44%; w2¼5.4,
df¼1, p¼.02). The young adult assessment was com-
pleted with 439 of these 668 subjects (66%). Subjects
missing the young adult assessment, compared to those
completing the visit, were more likely to be male (65%
vs. 46%; w2¼23.5, df¼1, p<.001), were older at base-
line (16.5?1.5 vs. 16.1?1.5, F¼7.2, df¼1,666,
p¼.008), more likely to be African American (24% vs.
17%, df¼1, w2¼0.03), lower on SES (35.2?14.2 vs.
38.7?13.0, F¼10.3, df¼1,666, p¼.001), less likely to
have been recruited from the community (23% vs. 37%,
w2¼13.5, df¼1, p<.001), and more likely to have
had adolescent AUD (53% vs. 42%; w2¼6.9, df¼1,
w2¼0.9),loweron SES (32.6?14.7 vs.
Subjects were paid $125 in gift certificates for participating
in a protocol that characterized trauma history, substance
use disorders, other mental disorders, health status, and
other variables. The subject’s biological mother or other
caretaker confirmed the adolescent’s health history as
well as other information, and was paid $50 for participa-
tion. The study was approved by the University of
Pittsburgh Human Subjects Institutional Review Board.
Active participant and parental consent were required.
The follow-up assessments examined here were at 1-year
after the baseline and at age 25-years old.
A structured trauma interview was added to the Schedule
for Affective Disorders and Schizophrenia for School Age
Children (K-SADS) for DSM-IV (Kaufman et al., 1997).
Trauma was defined by PTSD Criterion A of the
Diagnostic and Statistical Manual of Mental Disorders
(DSM-IV: AmericanPsychiatricAssociation, 1994).
Health Problems in Adolescents
The interview included structured questions to determine
trauma characteristics, including sexual features, injuries,
and perpetrators. Sexual abuse was defined as forced or
illicit genital fondling, or oral, vaginal or anal intercourse in
a familial context. Similar experiences outside the family
context were labeled rape. Physical abuse was defined as
maltreatment in the family context with serious injury or
multiple instances with bruises. Violent victimization was
defined as traumatic injury sustained by interpersonal
violence outside the familial context. Witnessing violence
was indicated when the subject was not the victim.
Non-interpersonal traumatic events indicated accidents,
including motor vehicle accidents, where injuries were
not the result of interpersonal violence. After determining
their presence or absence, we examined the relationships
between PTSD symptoms and each of these traumatic
experiences to determine their relative severity. This pro-
cedure identified seven Trauma Classes (TCs) and each
subject was assigned to a TC group. Subjects with multiple
traumas were assigned to the highest applicable TC sever-
ity. The TC labels, PTSD symptom counts, and sample
sizes were as follows: (a): TC-0: No traumatic experiences:
(0 by definition; n¼100); (b) TC-1: Non-interpersonal
trauma: (0.5?1.7; n¼139); (c) TC-2: Witnessing vio-
lence: (1.0?2.3; n¼122); (d) TC-3: Violent victimiza-
tion: (1.1?2.4; n¼87); (e) TC-4: Physical abuse:
(1.7?3.1; n¼87); (f) TC-5: Sexual abuse: (3.4?4.6;
n¼81); (g) TC-6: Rape: (4.3?5.1; n¼52). To serve
as a reference group, TC-0 included only community-
recruited subjects with neither traumatic experiences nor
AUD. Excluding TC-0, TC was confirmed to be significant-
ly associated with PTSD symptoms (F¼18.5; df¼5,562;
p<.001). TC and AUD were also significantly associated
(w2¼29.6, df¼5, p<.001).
Substance Use Disorders
Information about substance use disorders, including
AUD, was gathered by revised sections of the Structured
Clinical Interview for DSM (Martin, Pollock, Lynch, &
Bukstein, 2000). Diagnoses were considered to be present
if the subject met the diagnostic criteria in the 6 months
prior to the interview. Cigarette use was determined by the
average number of cigarettes per day in the prior month.
HS were determined by a checklist (Arria, Dohey, Mezzich,
Bukstein, & Van Thiel, 1995). This questionnaire assessed
136 self-reported symptoms in 15 areas: General health
status (9 items), Sleep (5 items), Eating (10 items), Skin
(9 items), Eyes and Vision (11 items), Ears and Hearing
(4 items), Mouth (4 items), Nose (6 items), Throat and
Neck (7 items), Heart and Lungs (14 items), Abdomen
(26 items), Bleeding and Metabolism (10 items), Muscles
and Joints (6 items), Neurological (10 items), and Urinary
(5 items). One point was scored for each affirmative
response and the items were summed to construct the
HS Total Score (Clark et al., 2001).
Blood was collected in the morning after an overnight fast.
Assays were performed by a commercial or medical center
laboratory. Serum assays with abbreviations and normal
ranges were: (a) liver injury tests: gamma-glutamyl trans-
peptidase (gamma-GTP: normal range: females 5–29;
males 5–38U/l); glutamic-oxaloacetic transaminase (sgot,
a.k.a., aspartate aminotransaminase or AST: females: 9–25;
males: 10–40U/l); glutamic-pyruvic
(sgpt, a.k.a., alanine aminotransaminase or ALT: females
7–30; males 10–55U/l); (b) immunoglobulins: IGM
(56–352mg/dl); IGA (70–312); IGG (639–1349); (c) meta-
(Na: 135–145mEq/l); chloride (Cl: 96–106); potassium
(K: 3.5–5.0); phosphorous (PO4: 2.4–4.1mg/dl); calcium
(Ca: 8.5–10.5mg/dl); magnesium (Mg: 1.5–2.0mEq/l);
(e) hematologic indicators: cell counts (red: 4.1–6.1?
2–8%; lymphocytes: 20–40%; neutrophils: 40–60%);
hematocrit (female 37–48%; males 42–52%); mean red
cell corpuscular hemoglobin (MCH: 28–33pg/cell); mean
red cell corpuscular hemoglobin concentration (MCHC:
32–36g/dl). Part of a research project component com-
pleted in the initial phase of the overall project, the labora-
tory tests were conducted at baseline with a subject subset
Physical abnormalities were determined by a health care
practitioner examination performed by a physician, nurse
practitioner, or physician’s assistant. The exam results
were classified as normal or abnormal in 15 areas: (a) gen-
eral appearance, (b) eyes (including fundoscopic exam),
(c) ears (including otoscopic exam), (d) nose and pharynx,
(e) mouth (including dentition and oral mucosa), (f) neck
(including thyroid and lymph node exam), (g) respiratory,
(h) cardiovascular, (i) abdomen, (j) neurologic exam
(including cranial nerves, motor exam, sensory exam, cere-
bellar exam, involuntary movements, reflex exam), (k)
skin, (l) head, (m) thorax, (n) back, and (o) extremities.
Along with the laboratory tests, the health care practitioner
examinations were conducted at the baseline assessments
Clark, Thatcher, and Martin
with a subject subset. Height and weight, along with
systolic and diastolic blood pressures, were collected at
each assessment. For the adolescent measurements,
the age-adjusted BMI percentile was calculated using the
Centers for Disease Control computer program. For the
young adult assessment, age adjustment was not neces-
sary. A health history interview inquired about diagnosed
health problems, emergency department visits, medical
hospitalizations, and surgeries.
Anxiety was measured by the Hamilton Anxiety Rating
Scale (HARS: Hamilton, 1959). With a subset of the pre-
sent sample, the HARS was found to be a reliable and valid
measure of anxiety in adolescents (Clark & Donovan,
1994). The HARS Total Score was used as an indicator of
The HS scales, laboratory assays, and other continuous
variables were analyzed by ANCOVAs. Where applicable,
the analysis first examined the total score as the overall
model. Where multiple independent indicators examined
a construct (e.g., liver injury), a multivariate ANCOVA was
conducted. Where the overall model was statistically sig-
nificant, subscales were examined. Dichotomous variables
were analyzed by logistic regression analyses. We examined
the main effects of TC and AUD in statistical models
including demographic characteristics as covariates. The
extent to which anxiety mediated the relationship between
TC and HS was examined. The tested model specified
that TC (independent variable) caused anxiety (mediating
variable) and that anxiety causes HS (outcome variable).
For the model to be supported (Baron & Kenny, 1986;
MacKinnon & Luecken, 2008), TC must be significantly
related to anxiety, anxiety must be significantly related to
HS, and the relationship between TC and HS must have
changed when anxiety was added.
The demographic characteristics of the seven TC groups
are presented in Table I. Higher TC severity was significant-
ly associated with older age, lower SES, female gender, and
African-American ethnicity. In analyses excluding TC-0, TC
severity was associated with the presence of AUD and clin-
ical recruitment source. The presence of AUD was signifi-
cantly associated with older age, male gender, and white
ethnicity. Excluding TC-0, AUD was associated with clin-
ical recruitment source. Subsequent analyses included
these demographic characteristics as covariates.
The main effects of TC and AUD on HS at the baseline
assessment are presented in Table II. At baseline, highly
significant effects of TC were seen for the HS Total Score
and for many subscales. The effect of AUD on HS Total
Score was not significant. A significant effect of AUD was
noted for only one scale, HS Heart/Lung subscale
(w2¼92.6, p<.001). Examining health symptoms at the
one-year follow-up, TC did (F¼2.6, df¼6,476, p¼.02)
Table I. Baseline Demographic Characteristics of Adolescents by TC
n (%) n (%)n (%)n (%)n (%) n (%) n (%)
0 (0) 89 (58)
*p<.05; **p<.01; ***p<.001.
Health Problems in Adolescents
and AUD did not (F¼0.5, df¼1,476, p¼0.5) predict HS
Total Score. Examining health symptoms at the young
adult follow-up, TC did (F¼4.1, df¼6,420, p¼.001)
and AUD did not (F¼0.0, df¼1,420, p¼0.8) predict
HS Total Score.
At baseline, TC and HARS Total Score were statis-
tically associated (F¼16.9, df¼6,655, p<.001) after ac-
counting for demographic characteristics and AUD. In a
model including demographic characteristics and AUD,
HARS Total Score was (F¼205.8, df¼1,593; p<.001)
and TC was not (F¼1.2, df¼6,593, p¼.3) associated
with HS Total Score. At 1-year follow-up, HARS Total
Scoreat baseline predicted
p<.001) and TC did not predict (F¼0.7, df¼6,475,
p¼.7) 1-year follow-up HS Total Scores. At the young
adult assessment, HARS Total Score at baseline predicted
(F¼23.4, df¼1,341; p<.001) and TC did not predict
(F¼1.4, df¼5,341, p¼.2) young adult HS Total Scores.
These analyses demonstrated that HARS Total Score fully
mediated the relationships between TC and HS Total Score
at baseline, 1-year, and young adult assessments.
We examined whether cigarette use mediated the
relationship between AUD and heart/lung symptoms.
Controlling for demographic characteristics, TC was signifi-
cantly associated with cigarette use (F¼10.7, df¼6,673,
p<.001). In the mediation model, cigarette use was
(F¼11.3, df¼1,581; p<.001) and AUD was not
(F¼3.5, df¼1,581; p¼.06) significantly associated with
the HS Heart/Lung subscale. These analyses demonstrated
that cigarette use fully mediated the relationship between
AUD and heart/lung symptoms.
In the overall sample, the most common health problems
noted by history at baseline were fractures (i.e., broken
bones) in 225 or 668 cases (34%), head injury (n¼48
or 7%) and asthma (n¼106 or 16%). The proportion
of subjects with these health problems is presented in
Table III. Other noted health problems were relatively
rare, occurring at rates of <5%. Logistic regression anal-
yses were conducted with these outcomes as dependent
variables, and demographic characteristics as covariates.
At baseline, neither TC nor AUD were significantly asso-
ciated with fractures, head injures, or asthma. When added
to this model, cigarette use did not account for significant
variance on asthma. Similarly, at the 1-year follow-up,
neither TC nor AUD predicted fractures, head injury, or
asthma. Again, cigarette use at baseline did not predict
asthma at the 1-year follow-up. At the young adult
follow-up, again, neither TC nor AUD predicted fractures,
head injury, or asthma. Cigarette use at baseline did not
predict asthma at the young adult follow-up.
Table II. HS at Baseline in Adolescents by TC
TC-0 TC-1 TC-2 TC-3
HS Total Score
Eyes & vision
Ears & Hearing
Throat & Neck
Metabolism & Bleeding
Muscles & Joints
ANCOVA (F) results shown with covariates including gender, age, ethnic group, SES.
*p<.05; **p<.01; ***p<.001.
Clark, Thatcher, and Martin
For liver injury indicators overall at baseline (Table IV),
AUD was (F¼3.3, df¼3,312, p¼.02) and TC was not
df¼15,942, p¼.5). For individual indicators, the pres-
ence of AUD was associated with significantly higher
?-GTP, AST and ALT. At the 1-year follow-up assessment,
AUD was significantly associated with liver injury
overall (F¼5.3, df¼3,237, p¼.001) and TC were not
df¼18,717, p¼.5). For individual indicators, AUD
accounted for significant variance on ?-GTP (F¼10.3,
df¼1,250, p¼.002), and did not account for significant
variance on AST (F¼0.0, df¼1,250, p¼.9) and ALT
(F¼0.2, df¼1,250, p¼.6). At the young adult follow-up
assessment, neither AUD (F¼1.7, df¼3,178, p¼.2) nor
TC (F¼1.1, df¼18,540, p¼.3) were significantly asso-
ciated with liver injury overall.
At baseline (Table IV), TC and AUD were significantly
associated with overall immunoglobulin levels. For individ-
ual indicators, TC was significantly associated with IgM
and IgG and was not significantly associated with IgA.
More severe TC tended to be associated with higher IgM
and IgG. For individual indicators, AUD was significantly
associated with IgM and IGA and was not significantly
associated with IgG. The presence of AUD was associated
with higher IgM and IgA levels. At the 1-year follow-up,
neither TC (F¼1.0, df¼18,414, p¼.4) nor AUD
(F¼1.3, df¼3,136, p¼.3) were significantly associated
with overall immunoglobulin levels. Immunoglobulins
were not measured at the young adult assessment.
Metabolic Syndrome Indicators
At baseline (Table IV), TC was and AUD was not
significantly associated with overall metabolic syndrome
indicators. For individual indicators, TC was associated
with glucose levels and was not significantly assoc-
iated with triglyceride levels. At the one-year follow-up,
neither TC (F¼1.3, df¼12,444, p¼.2) nor AUD
(F¼0.1, df¼2,221, p¼.9) were significantly associated
with overall immunoglobulin levels. Metabolic syndrome
indicators were not measured at the young adult
At baseline (Table IV), TC was and AUD was not signifi-
cantly associated with overall electrolyte levels. For indi-
vidual indicators, TC was significantly associated with
chloride and calcium levels, and was not associated with
levels of sodium, potassium, phosphorous, or magnesium.
At the 1-year follow-up, neither TC (F¼1.3, df¼36,1296,
p¼.1) nor AUD (F¼1.7, df¼6,211, p¼.1) were signifi-
cantly associated with overall electrolyte levels. Electrolyte
levels were not measured at the young adult assessment.
At baseline (Table IV), neither TC nor AUD were signifi-
cantly associated with overall blood cell counts. Neither TC
nor AUD were significantly associated with WBC differen-
tial counts. Neither TC nor AUD were significantly
Table III. Health History and Physical Exam Indicators at Baseline for Adolescents by TC
TC-0 TC-1TC-2 TC-3
20 (53)Overweight 12.8*
M (SD)M (SD) M (SD)M (SD)M (SD) M (SD)M (SD)FF
Age-adjusted BMI %ile
# PE abnormalities
69 (27) 58 (29) 67 (28)61 (30)62 (28)62 (29)76 (25) 2.2*
Logistic regression (Wald w2) or ANCOVA (F) statistics are shown with covariates including gender, age, ethnic group, SES.
*p<.05; **p<.01; ***p<.001.
Health Problems in Adolescents
associated with RBC indices. These indices were not col-
lected at subsequent visits.
At baseline (Table III), TC was and AUD was not signifi-
cantly associated with age-adjusted BMI percentile. By
CDC criteria, 33% of subjects were classified as over-
weight. TC was and AUD was not associated with over-
weight status. At 1-year follow-up, neither TC (F¼1.2,
df¼6,326, p¼.3) nor AUD (F¼0.1, df¼1,326, p¼.7)
were significantly associated with age-adjusted BMI
percentile. At 1-year follow-up, 32% of the subjects were
overweight by CDC criteria. At 1-year follow-up, neither
TC (Wald w2¼10.2, df¼6, p¼.1) nor AUD were signifi-
cantly associated with overweight status (Wald w2¼0.2,
df¼1, p¼.6). At young adult follow-up, neither TC
df¼1,245, p¼.9) were significantly associated with
age-adjusted BMI percentile. At young adult follow-up,
58% of the subjects were overweight by CDC criteria. At
young adult follow-up, neither TC (Wald w2¼5.7, df¼6,
p¼.5) nor AUD were significantly associated with over-
weight status (Wald w2¼0.9, df¼1, p¼.3).
Table IV. Laboratory Blood Assays at Baseline for Adolescents by TC
ANCOVA (F) statistics are shown with covariates including gender, age, ethnic group, SES.
*p<.05; **p<.01; ***p<.001.
Clark, Thatcher, and Martin
At baseline (Table III), TC was and AUD was not asso-
ciated with overall blood pressure. Neither TC nor AUD
were significantly associated with systolic blood pressure,
whereas both TC and AUD were associated with diastolic
blood pressure. TC paired comparisons revealed that this
result was due to subjects in TC2 (i.e., Witnessing
Violence) having significantly higher diastolic blood pres-
sure than subjects in TC3, TC4 or TC6. Blood pressure
readings meeting medical criteria for hypertension were
present in only one case. At 1-year follow-up, neither TC
(F¼1.6, df¼6,270, p¼.2) nor AUD (F¼0.6, df¼1,270,
p¼.4) were significantly associated with systolic blood
pressure, and TC (F¼2.1, df¼6,270, p¼.049) but not
AUD (F¼0.0, df¼1,270, p¼.99) were significantly asso-
ciated with diastolic blood pressure. At 1-year follow-up,
TC paired comparisons revealed that this result was due to
subjects in TC2 (i.e., Witnessing Violence) having signifi-
cantly higher diastolic blood pressure than subjects in
TC0, TC3, TC4, or TC6. Hypertension was rare, with a
systolic reading over 150 in 0.4% of subjects and a diastol-
ic reading over 90 in 5% of subjects. At young adult
follow-up, neither TC (F¼1.0, df¼6,240, p¼.4) nor
AUD (F¼0.6, df¼1,240, p¼.4) were significantly asso-
ciated with systolic blood pressure and, similarly, neither
TC (F¼0.4, df¼6,240, p¼.9) nor AUD (F¼0.6,
df¼1,240, p¼.4) were significantly associated with dia-
stolic blood pressure. At the young adult assessment,
hypertension was uncommon, with a systolic reading
over 150 in 2% of subjects and a diastolic reading over
90 in 7% of subjects.
Health Care Practitioner Examination
At baseline, most of the abnormalities reported for the
health care practitioner exam were observed for the skin
(53%), with the main problem being acne; the ears (14%),
with the main problem being cerumen blockage or exces-
sive ear wax; and the mouth (11%), with the main problem
being severe caries or poor oral hygiene. At baseline, nei-
ther TC (F¼0.7, df¼6,216, p¼.6) nor AUD (F¼1.9,
df¼1,216, p¼.2) were significantly associated with the
sum of abnormalities on the health care practitioner
exam. The Health Care Practitioner examination was not
conducted at subsequent visits.
In this study, HS were strongly associated with TC severity
at baseline, 1-year follow-up and young adult assessments.
Examining a comprehensive assessment of HS organized
into 15 dimensions, we found that the total score, as well
as 12 of 15 dimensions, were significantly and systematic-
ally associated with TC severity. While few HS were
reported in the TC groups of lower severity, the two TC
groups with traumatic experiences involving sexual events
had average symptom counts in the 18–20 range. For ado-
lescents, this indicates a relatively high symptom level. The
relationship between TC and HSs persisted into young
adulthood. The results supported a mediation model
in which child abuse and other traumatic experiences
lead to anxiety and anxiety leads to HSs. The prominence
with anxiety disorders, such as abdominal complaints
(Ginsburg et al., 2006), along with the absence of objective
findings that would explain these symptoms, further valid-
ate the interpretation that these symptoms are primarily
somatic accompaniments of anxiety.
In some prior studies, physical abuse compared to
sexual abuse has shown a stronger relationship with over-
weight status. That distinction was not replicated here.
In the present study, baseline age-adjusted BMI and over-
weight status were significantly associated with TC. The
pattern of results did not suggest that those with physical
abuse, contrasted with those with sexual abuse, showed a
greater tendency toward being overweight. Furthermore,
the outcomes at 1-year and young adult follow-up assess-
ments did not evidence a relationship between TC and
overweight status. A significant relationship between
glucose level and TC was noted at baseline, with the two
less severe TC groups showing lower glucose. In general,
however, a propensity toward metabolic syndrome was not
associated with TC severity. We have previously noted that
adolescents with AUD, compared to controls, show less
regular exercise and poor eating habits (Thatcher &
Clark, 2006). Chronic effects of such lifestyle problems
may become more evident later in life.
Some laboratory tests and physical exam findings
may have reflected stress-related responses. TC severity
was associated with higher immunoglobulin levels, a find-
ing consistent with that observed in prior studies of labora-
tory induced and naturalistic stress. Among adolescents,
exposure to violence has been previously reported to be
associated with elevated blood pressure (Murali & Chen,
2005). Here, elevated diastolic blood pressure was
observed in the group of adolescents who reported
The observed effects of AUD included elevated liver
enzymes, elevated immunoglobulins, and HSs on the
heart/lung dimension. Alcohol induces acute liver in-
jury, so this finding was expected. Some studies have
suggested that higher levels of alcohol consumption
Health Problems in Adolescents
(Gonzalez-Quintela et al., 2007) as was the case here.
While we observed an association between AUD and HSs
referenced to the heart and lungs, cigarette use mediated
this relationship. These findings provide some support for
the hypothesis that the association between child abuse
and liver, heart and lung diseases may, as suspected, be
mediated by AUD and cigarette use. While few cases were
found to have medical diseases in this study, AUD and
cigarette use lead to medical diseases that become evident
later in adulthood.
The sampling approach taken in this study has advan-
tages and disadvantages. The inclusion of the community
sample of adolescent with neither traumatic experiences
nor AUD as a reference group afforded the opportunity
to examine the extent to which the health problems
evident in adolescents with traumatic experiences and/or
AUD were above expected levels. For adolescents with
traumatic experiences or AUD, we elected to include sub-
jects from both community and clinical sources. In design-
ing the study, we recognized that selection bias is often
present in clinical samples. The relatively low base rates of
AUD and severe child abuse among adolescents in the
general population, however, result in their being present
in small numbers in representative community samples.
The recruitment plan did not recruit directly from child
protective services agencies and may not have included a
substantial representation of adolescents with the most
severe forms of child abuse. In this study, the characteris-
tics of interest, TC and AUD, were highly co-linear with
recruitment source, making inclusion of recruitment
source in multivariate models problematic. The extent to
which these findings generalize to adolescents recruited by
other methods will need to be determined in subsequent
This study had other limitations. The assessment did
not include an evaluation of neglect. We recognize that
neglect would have been important to take into consider-
ation in this study, in that neglect experiences are among
the most common and severe forms of child maltreatment
(Dubowitz & Bennett, 2007). Future research may be
enhanced by obtaining records from child protective ser-
vices to identify neglect and provide other supplementary
information (Runyan et al., 2005). In addition, variation in
alcohol use proximal to the time of the assessment may
have influenced the results. In some adolescents, labora-
tory blood assays may have reverted to normal after a
period of alcohol abstinence in the days prior to testing.
This study did not provide interventions or systematic
referrals for treatment. Over the course of the study, how-
ever, many subjects received medical, psychological,
and/or addictions treatment. These treatments may have
mitigated the effect of child maltreatment or other traumas
on examined outcomes.
These findings have several clinical implications. HS
associated with child abuse were, to some extent, attribut-
able to anxiety. Health care practitioners providing services
to adolescents with histories of child abuse should
consider anxiety disorders in the differential diagnosis of
such symptoms. Nevertheless, conscientious medical care
dictates that the presentation of HS should be thoroughly
investigated. Child abuse was associated with being over-
weight at the initial assessment, and some adolescents will
need assistance in this area. Among overweight adoles-
cents, monitoring of metabolic syndrome indicators, such
as blood pressure and glucose, may facilitate the early iden-
tification of hypertension and diabetes. Chronic AUD and
cigarette use may lead to liver, cardiac or lung diseases. The
subclinical abnormalities that were observed here may, in
some cases, preface the onset of more serious organic path-
ology and medical diseases in middle adulthood. Early
intervention with children having abuse histories has
been shown to reduce adulthood medical disease rates
(Kessler et al., 2008). We recommend that health care
practitioners seeing adolescents with child abuse histories
regularly screen for alcohol, cigarette and other drug use,
monitor for weight gain, and provide treatments for
co-morbid mental disorders.
This research was supported by the following NIH
Grants from the National Institute on Alcohol Abuse and
Alcoholism (AA) and the National Institute on Drug Abuse
(DA): K02-AA-00291, R01-AA-13397, R01-DA-14635,
K01-DA-018698, P50-AA-08746, R21-AA-017312, U01-
Conflicts of interest: None declared.
The authors would like to thank the staff and faculty of the
Pittsburgh Adolescent Alcohol Research Center for their
contributions and support.
Received May 15, 2009; revisions received October 14,
2009; accepted October 29, 2009
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