Graduate Assistance

Challenges to School Success and the Role

of Adverse Childhood Experiences

Elizabeth Crouch, PhD; Elizabeth Radcliff, PhD; Peiyin Hung, PhD; Kevin Bennett, PhD

From the Rural and Minority Health Research Center (E Crouch, E Radcliff, and P Hung), Arnold School of Public Health, University of South Carolina, Columbia, SC; and Department of Family and Preventive Medicine (K Bennett), University of South Carolina School of Medicine, Columbia, SC The authors have no conflicts of interest to disclose. Address correspondence to Elizabeth Crouch, PhD, Rural and Minority Health Research Center, Arnold School of Public Health, University of South Carolina, 220 Stoneridge Drive, Suite 204, Columbia, SC 29210 (e-mail: [email protected]). Received for publication April 23, 2019; accepted August 8, 2019.

A

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TAGGEDPABSTRACT

OBJECTIVE: To examine the association between adverse childhood experiences (ACEs), by multiple types and counts

of ACEs, and challenges to school success.

METHODS: A cross-sectional study was conducted using data from the 2016 National Survey of Children’s Health using

the ACE module and 3 measures of challenges to school suc-

cess: lack of school engagement, school absenteeism, and

repeated grade.

RESULTS: In multivariable analysis adjusting for selected demographic and other characteristics, children with 4 or

more ACEs had higher odds of nonengagement in school

(adjusted odds ratio [aOR] 2.15; 95% confidence interval

[CI], 1.51−3.07), reported school absenteeism (aOR 1.75; 95% CI, 1.12−2.73), and of repeating a grade (aOR 1.71; 95% CI, 1.19−2.47, Table 4) than children with exposure to less than 4 ACEs. Risk factors for all 3 challenges to school

success included age of child and special health care needs,

with older children and children with special health care

CADEMIC PEDIATRICS

opyright © 2019 by Academic Pediatric Association 899

needs more likely to have challenges to school success,

across all 3 measures.

CONCLUSIONS: Our findings confirm that ACEs can have an impact in childhood and adolescence, not just later in adult-

hood, as demonstrated by the association between ACEs and

measures of school success. These findings further illuminate

the connection between ACEs and childhood outcomes of edu-

cation and health. Future research should examine frameworks

that effectively support collaboration between educators,

social service providers, and pediatricians as they seek to pre-

vent or reduce the impact of ACEs and other childhood

trauma.

TAGGEDPKEYWORDS: adverse childhood experiences; child develop- ment; school absenteeism; school engagement

ACADEMIC PEDIATRICS 2019;19:899−907

TAGGEDPWHAT’S NEW

Adverse childhood experiences, such as economic

hardship, living in disrupted households, and house-

hold violence, are associated with school absenteeism,

repeated grades, and nonengagement in school. Pedia-

tricians have a role to communicate with families

about childhood trauma and school performance.

TAGGEDPSUCCESS IN SCHOOL encompasses academic skills as well as social-emotional development, physical health,

language development, motivation, and creativity and is

important to a student’s well-being in both immediate-

and long-term measures. 1 Students who have higher edu-

cational goals and academic achievement are more likely

to have higher self-esteem, to delay sexual activity, to

engage in fewer risky health behaviors, and have less

young adult deviant behavior, such as criminal conduct

and alcohol or substance abuse. 2−4

Adolescents who drop

out of school have higher rates of chronic disease, sub-

stance abuse, and poorer mental health. 5 Students who

remain in school and obtain a high school diploma are

more likely to have higher long-term earnings potential

and overall better health than students who drop out of

school. 6,7

The American Academy of Pediatrics recently

published a policy statement on the link between school

attendance and good health, as school absenteeism puts

children at higher risk of poor school performance, which

puts them at higher risk for school dropout and poor long-

term health outcomes. 8 Thus, school success is important

as both an educational and a public health concern.

A child’s success in school may be put at risk by a num-

ber of factors. At the individual level, children with spe-

cial health care needs and overall poorer health are more

likely to have challenges to school success. 9 At the house-

hold and family level, children exposed to caregiver sub-

stance abuse, conflict, and poverty are more likely to have

school absenteeism. 5,9

Additional household or family

characteristics such as the early home environment, the

quality of early caregiving, and level of parent involve-

ment are associated with high school drop-out rates. 10

At

the neighborhood and community level, the safety and

security of the school climate and neighborhood also

affect school success. 9,11

Pediatricians also have a role in

Volume 19, Number 8

November−December 2019

TAGGEDEND900 CROUCH ET AL ACADEMIC PEDIATRICS

supporting school success by providing preventive care,

treatment, and screenings, as well as monitoring social-

emotional development, referring families and children to

family supports, and advocating for children to be in opti-

mal environments for learning and development. 1

Of particular interest is how childhood adversity risk

factors may be associated with many individual school

success metrics. Adverse childhood experiences (ACEs),

as described in a seminal manuscript, are experiences in

childhood that include exposure to traumatizing abuse

or household dysfunction. 12

Subsequent research has

expanded types of ACEs to include additional childhood

experiences such as neglect, economic hardship, and

racial discrimination. 13

Extensive evidence has associated

ACEs with poorer long term physical and mental health

conditions, as well as higher risk of chronic disease and

costs of care across the lifespan. 14

Prior research has examined the relationship between

ACEs and school success factors, such as school absentee-

ism, school engagement, school performance, and/or grade

repetition. 15−17

These findings demonstrated that children

with 2 or more ACEs were much more likely to repeat a

grade, compared to children with no ACEs, and that chil-

dren with no ACEs were more likely to be engaged in

school than children who had been exposed to 2 or more

ACEs. 15

By examining the association between challenges

to school success and ACE counts, this study will examine

the cumulative effect of ACE exposure on those school-

success-related challenges. We hypothesize that children

with higher counts of ACEs will be more likely to experi-

ence challenges to school success than their counterparts

exposed to fewer ACEs. Specific types of ACEs, such as

caregiver substance abuse and neighborhood violence, are

associated with higher school absenteeism. 5,16

Thus, we

hypothesize that specific types of ACEs may be stronger

risk factors for challenges to school success. 5,16

Previous studies examining ACEs and school success

factors used either older nationally representative datasets

(2011−12) or nonrepresentative national datasets and did not examine the association between ACEs, by both types

and counts, and challenges to school success. Our study

fills a gap in the literature by using a more recent nation-

ally representative dataset (the 2016 National Survey of

Children’s Health [NSCH]) to examine the relationship

between ACEs (type and count) and challenges to school

success, specifically lack of school engagement, school

absenteeism, and repeated grade, and subsequently pro-

vides more generalizable information that may be useful

for pediatricians and policymakers.

TAGGEDH1METHODS TAGGEDEND This cross-sectional study was conducted using data

from the 2016 NSCH, a mail and online survey conducted

by the Data Resource Center for Child and Adolescent

Health (DRC). Respondents had to have been a parent or

caregiver with at least 1 child between the ages of 0 and

17 living in the home during the time of the interview. For

both the mail and online survey, the parent or caregiver

fills out an initial screener with the age and sex of all chil-

dren in the household. From that screener, 1 child from

each household is randomly selected by the NSCH to be

the subject of the questionnaire. Participants then com-

plete 1 of 3 versions of the study, depending on the child’s

age. Information on the sampling methods and selection

of participants is available on the DRC website (http://

www.childhealthdata.org/learn/NSCH).

The 2016 NSCH had 50,212 complete interviews. Our

sample was limited to children whose parents or care-

givers answered the school age questions (ages 5 and up),

n = 35,718 children. An additional 4011 children were

excluded from the sample because of incomplete answers

to the ACE questions, demographic questions, or school

success questions. The final study sample included 31,707

respondents.

The NSCH asks 9 ACE questions about parental sepa-

ration or divorce, parental death, witnessing household

violence, witnessing neighborhood violence, household

mental illness, household incarceration, household sub-

stance abuse, racial/ethnic mistreatment, and economic

hardship (Table 1). Individual ACE counts were calcu-

lated and then categorized into less than 4 ACEs or 4 or

more ACEs. 12

The 4 or more cut off point for ACEs has

long been established among adults, but has also demon-

strated to be a significant cut point for higher likelihood

of at-risk social and developmental outcomes among chil-

dren using a variety of ACE screening devices: the

NSCH, Family Map Inventories, and the Child Behavior

Checklist. 18,19

Particularly for the NSCH ACE question-

naire, a response of 4 or more ACEs has been shown to be

a powerful predictor of emotional, mental, or behavioral

health conditions among children. 20

Furthermore, in order

to describe the exposure of children to particular catego-

ries of ACEs, the low prevalence ACEs were grouped into

categories. These categories, parental incarceration, vio-

lence, household mental illness, and substance abuse,

have been established by prior literature and are common

constructs to nearly all ACE assessment methods. 20

The

group “exposure to violence” comprises 2 ACEs: children

reported to have witnessed household or neighborhood

violence. The group “living in a disrupted household”

comprises 3 possible ACEs: children reported to have a

parent/guardian in jail, live with someone with mental ill-

ness, or live with someone with substance abuse.

Our 3 measures of challenges to school success included

lack of school engagement, school absenteeism, and

repeated grade. Lack of school engagement was measured

based on the response to the following question: “How well

do each of the following phrases describe this child?” The

phrases chosen for school engagement included “the child

cares about doing well in school” and “the child does all

required homework.” If caregivers responded, “not true to

any item,” then the child was categorized as lack of school

engagement. This measure of school engagement corre-

sponds with how school engagement has been measured in

earlier versions of the NSCH and with prior studies. 15

Repeated grade was measured as affirmative if the care-

giver responded yes to the following question: “since

Table 1. ACE Survey and Supplemental Questions Included in the 2016 National Survey of Children’s Health

Adverse Childhood Experience Survey Questions

Group To the best of your knowledge, has this child experienced any of the

following?

Parental separation/divorce 1) Parent or guardian divorced or separated?

Parental Death 2) Parent or guardian died

Living in a disrupted household Household incarceration 3) Parent or guardian served time in jail?

Household mental illness 4) Lived with anyone who was mentally ill, suicidal, or severely

depressed?

Household substance use 5) Lived with anyone who had a problem with alcohol or drugs?

Witness to violence Witnessing household violence 6) Saw or heard parents or adults slap, hit, kick, punch one another in

the home?

Witnessing neighborhood violence 7) Was a victim of violence or witnessed violence in the

neighborhood?

Racial/ethnic mistreatment 8) Treated or judged unfairly because of his or her race or ethnic

group?

Economic Hardship 9) Hard to get by on family’s income—hard to cover basics like food or housing?

ACE indicates adverse childhood experience.

TAGGEDENDACADEMIC PEDIATRICS CHALLENGES TO SCHOOL SUCCESS AND THE ROLE OF ACES 901

starting kindergarten, has this child repeated any grades?”

School absenteeism was quantified using the question

“during the past twelve months, about how many days did

this child miss school because of illness or injury?” If the

caregiver responded that the child missed 11 or more days,

the highest option given in the responses, then the child

was categorized as having school absenteeism.

Covariates in the model were included based on the

developmental-ecological child maltreatment model, which

encompasses both characteristics of the child and the care-

giver, as well as sociodemographic, household, caregiver-

child interactions, and neighborhood characteristics. 21

The

developmental-ecological child maltreatment model was

chosen as a framework for covariate selection. We chose

this model because, while the NSCH ACE questions do not

specifically ask about maltreatment due to the potential for

underreporting due to social desirability, the inter-related-

ness and validity of the ACE questions measured by NSCH

have demonstrated strong potential for maltreatment in the

household. 20

The child characteristics included sex, age,

race/ethnicity, and whether a child had special health care

needs. The age of the child was grouped into 2 categories:

6−12 or 13−17 years of age, per the NSCH interview ques- tionnaire ages. The race/ethnicity of the child was catego-

rized into the following: non-Hispanic White, non-Hispanic

Black, Hispanic, and Multiracial/Other, non-Hispanic. The

NSCH identifies children with special health care needs

using a 5-criteria tool. If a respondent provides a positive

response to any 1 of 5 questions related to prescription

medication, elevated used of services, functional limita-

tions, specialized therapy, and continuous emotional, devel-

opmental, or behavioral conditions, the child is flagged as

having special health care needs.

Characteristics of the caregiver or family included the

respondent’s relation to the child, the highest educational

attainment of a parent or guardian in the household, pri-

mary language spoken in the home, family structure, and

poverty/income level. The respondent’s relation to the child

was classified as mother, father, or other. The highest

educational attainment of a parent or guardian was grouped

into those with less than or equal to high school degree/

GED and those with some level of college education. The

primary language in the home was English or not English.

Family structure included the following: 2 parents, cur-

rently married; 2 parents, not currently married; and single

mother/other. Finally, poverty/income levels were 0%

−99% of the federal poverty level (FPL), 100%−199% FPL, 200%−300% FPL, and 400% FPL or above.

Analyses were performed using the survey sampling

weights, cluster, and stratum outlined in the NSCH code-

book, in order to account for distributions in race, ethnicity,

and gender of children in the United States. These weights,

cluster, and stratum were also used to account for nonre-

sponse. Further sampling plan information is documented on

the DRC website (http://www.childhealthdata.org/NSCH).

All analyses were completed using statistical software (SAS,

version 9.3; SAS Institute Inc, Cary, NC). Due to our large

sample size, the alpha value was set at .01. The study was

approved by the University of South Carolina institutional

review board as exempt.

For each variable, descriptive and bivariate analyses

were conducted to estimate the frequencies and propor-

tions between each variable and school success factor.

Multivariable logistic regression models were used to

examine the relationship between ACEs of 4 or more and

challenges to school success, and the relationship between

types of ACEs and challenges to school success.

Per NSCH guidelines, results are reported in terms of

the child instead of the caregiver or family. This NSCH

reporting guideline is based on the fact that the reporting

weights reflect the population of children in the United

States, not the population of caregivers or families (http://

www.childhealthdaa.org/learn/NSCH).

TAGGEDH1RESULTS TAGGEDEND The majority of our sample was male (51.0%), between

the ages of 6 and 12 years old (58.4%), and non-Hispanic

T AGGEDEND902 CROUCH ET AL ACADEMIC PEDIATRICS

white (53.0%, Table 2). Nearly a quarter (23.3%) of chil-

dren had special health care needs. Nearly two thirds

(64.1%) of children had their mother as the survey respon-

dent. Most children lived in a household with a guardian

who had some college education or more (70.4%) and had

2 parents who were currently married (66.8%). Over 10%

(13.8%) of children lived in a household where English

was not the primary language. One in 5 children (20.6%)

resided in households with income below the federal pov-

erty line.

Approximately 5.7% of children were reported as not

being engaged in school, with significant differences in

engagement reported by sex, age, special health care

needs, relation, guardian education, family structure, and

poverty/income level. Exactly 4.0% of children were

reported with chronic absenteeism. Significant differences

associated with chronic absenteeism included age of child,

special health care needs, respondent’s relation to child,

family structure, and poverty/income level. Over 6%

(6.6%) of children had repeated a grade, with a higher per-

centage of male children repeating a grade (8.1%) than

female children (5.1%, P < .0001). Other significant dif- ferences by repeated grade included age of child, special

Table 2. Characteristics of Respondents to the 2016 National Surve

Challenge, n = 31,707

Characteristic All (%)

Lack of School

Engagement (%)

5.7

Characteristics of child

Sex of child

Male 51.0 7.4

Female 49.0 3.9

Age of child

6−12 years old 58.4 4.4 13−17 years old 41.6 7.4

Race/Ethnicity of Child

Non-Hispanic White 53.0 5.4

Non-Hispanic African-American 12.4 6.6

Hispanic 24.5 5.8

“Other” Non-Hispanic 10.1 5.5

Special health care needs

Yes 23.3 15.6

Characteristics of parent/household

Respondent’s relation to child

Mother 64.1 5.7

Father 28.4 4.1

Other 7.4 10.8

Primary Language

Not English 13.8 5.6

Guardian Education

Less than high school or high school 29.6 7.3

Some college or more 70.4 5.0

Family Structure

Two parents, currently married 66.8 4.2

Two parents, not currently married 7.8 8.9

Single mother 16.9 7.8

Other 8.5 10.2

Poverty/income level

0%−99% federal poverty level 20.6 8.3 100%−199% federal poverty level 22.1 5.6 200%−399% federal poverty level 26.5 5.5 400% federal poverty level or above 30.8 4.1

health care needs, respondent’s relation to child, guardian

education, family structure, and poverty/income level

(Table 2).

The most prevalent types of ACE exposure were paren-

tal separation/divorce, economic hardship, and living in a

disrupted household; these were experienced across all

challenges to school success (Table 3). Children who

repeated a grade, as well as those with school absentee-

ism, were more likely to report each type of ACE than

their counterparts (P < .01), with the exception of racial/ ethnic mistreatment and parental death. Exposure to vio-

lence was highest among children with lack of school

engagement (21.6%).

In multivariable analysis adjusting for aforementioned

covariates, children with 4 or more ACEs had higher odds of

reported school absenteeism (adjusted odds ratio [aOR]

1.75; 95% confidence interval [CI], 1.12−2.73), nonengage- ment in school (aOR 2.15; 95% CI, 1.51−3.07), and of repeating a grade (aOR 1.71; 95% CI, 1.19−2.47, Table 4) than children with exposure to less than 4 ACEs. Risk fac-

tors for all 3 challenges to school success included age of

child and special health care needs, with older children and

children with special health care needs more likely to have

y of Children’s Health, in Total and Stratified by School Success

P value

School

Absenteeism (%) P value

Repeated

Grade (%) P value

4.0 6.6

<.0001 .4912 <.0001 4.1 8.1

3.8 5.1

<.0001 <.0001 <.0001 3.0 5.5

5.2 8.3

.7271 .5382 .0084

4.2 5.7

2.8 9.5

4.0 7.4

4.1 5.9

<.0001 10.7 <.0001 10.9 <.0001

<.0001 .0006 <.0001 4.7 6.6

2.4 4.9

4.0 13.7

.9681 .1840 .2005

2.5 5.1

.0026 .0642 <.0001 4.8 10.5

3.6 5.0

<.0001 .0010 <.0001 3.2 4.6

5.5 12.0

6.1 8.3

4.1 14.0

<.0001 <.0001 <.0001 6.3 11.3

3.7 7.4

3.5 5.2

3.0 4.1

Table 3. Types and Numbers of ACEs Reported by Respondents to the 2016 National Survey of Children’s Health, n = 31,707

ACE Exposure

Total Sample

Weighted %

Lack of School

Engagement (%) P value

School

Absenteeism (%) P value

Repeated

Grade (%) P value

ACE summary score <.0001 <.0001 <.0001 Zero 48.6 23.4 23.1 29.5

One to three 43.6 54.8 56.9 52.1

Four or more 7.8 21.8 20.0 18.4

ACE Types*

Parental separation/divorce 29.9 45.0 <.0001 43.6 <.0001 29.0 <.0001 Parental death 4.2 7.8 .0014 6.0 .0995 9.2 <.0001 Living in a disrupted household 20.5 43.0 <.0001 42.4 <.0001 37.0 <.0001 Exposure to violence 9.4 21.6 <.0001 17.3 <.0001 19.8 <.0001 Racial/ethnic mistreatment 4.9 10.1 .0003 9.4 .0152 5.7 .3781

Economic hardship †

25.9 43.9 <.0001 49.1 <.0001 39.8 <.0001

*First 8 items are responses to the stem question, “Has this child ever experienced. . .”

†The final item asks, “since this child was born, how often has it been very hard to get by on your family’s income − hard to cover the basics like food or housing? If the parent/guardian answered “somewhat often/very often hard to get by on family income” then the answer

was coded as a yes. Answers of “never/rarely hard to get by on family income” were coded as a no.

Table 4. Adjusted Odds Ratios* and 95% Wald Confidence Intervals Predicting Challenges to School Success by 4 or More Adverse Child-

hood Experiences (ACEs), Among Respondents to 2016 National Survey of Children’s Health survey, n = 31,707

Lack of School Engagement School Absenteeism Repeated Grade

Variable Point Estimate 95% CI Point Estimate 95% CI Point Estimate 95% CI

Four or more ACEs 2.15 1.51−3.07 1.75 1.12−2.73 1.71 1.19−2.47 Less than four ACEs Referent Referent Referent

Characteristics of child

Sex of child

Male Referent Referent Referent

Female 0.52 0.40−0.69 0.97 0.74−1.28 0.62 0.49−0.79 Age of Child

6−12 years old Referent Referent Referent 13−17 years old 1.77 1.38−2.26 1.71 1.30−2.26 1.55 1.22−1.97

Race/Ethnicity of Child

Non-Hispanic White Referent Referent Referent

Non-Hispanic African-American 0.85 0.59−1.21 0.45 0.28−0.73 1.12 0.80−1.56 Hispanic 0.99 0.73−1.35 1.06 0.73−1.55 1.25 0.88−1.79 “Other” Non-Hispanic 1.07 0.68−1.66 1.09 0.66−1.80 1.06 0.74−1.53

Special health care needs

Yes 6.18 4.76−8.03 5.45 4.10−7.25 1.84 1.42−2.39 Characteristics of Parent/Household

Respondent’s relation to child

Mother Referent Referent Referent

Father 0.93 0.70−1.25 0.68 0.45−1.04 0.91 0.69−1.19 Other 1.26 0.69−2.32 0.65 0.32−1.31 1.13 0.71−0.81

Primary language

English Referent Referent Referent

Not English 1.34 0.79−2.26 0.58 0.26−1.27 0.53 0.31−0.90 Guardian education

Less than high school or high school 1.25 0.93−1.68 1.20 0.91−1.60 1.76 1.36−2.29 Some college or more Referent Referent Referent

Family structure

Two parents, currently married Referent Referent Referent

Two parents, not currently married 1.74 1.05−2.90 1.24 0.69−2.25 1.92 1.27−2.89 Single mother 1.09 0.77−1.55 1.06 0.76−1.47 1.02 0.72−1.43 Other 1.49 0.86−2.57 1.07 0.51−2.24 1.82 1.13−2.94

Poverty/Income Level

0%−99% federal poverty level 1.32 0.86−2.02 1.89 1.23−2.90 1.76 1.19−2.60 100%−199% federal poverty level 1.08 0.71−1.62 1.18 0.79−1.76 1.31 0.95−1.81 200%−399% federal poverty level 1.24 0.92−1.68 1.12 0.78−1.63 1.07 0.79−1.44 400% federal poverty level Referent Referent Referent

*95% CI = 95% Wald confidence intervals; bold indicates significance.

TAGGEDENDACADEMIC PEDIATRICS CHALLENGES TO SCHOOL SUCCESS AND THE ROLE OF ACES 903

Table 5. Adjusted Odds Ratios* and 95% Wald Confidence Intervals Predicting Challenges to School Success by Types of Adverse Child-

hood Experiences (ACEs), Among Respondents to 2016 National Survey of Children’s Health survey, n = 31,707

Lack of School Engagement* School Absenteeism* Repeated Grade*

Variable Point Estimate 95% CI †

Point Estimate 95% CI †

Point Estimate 95% CI †

ACE types*

Parental separation/divorce 1.33 0.99−1.80 1.20 0.85−1.74 1.09 0.82−1.45 Parental death 1.20 0.75−2.33 1.02 0.60−1.73 1.45 0.92−2.29 Living in a disrupted household 2.30 1.75−3.04 2.06 1.41−3.00 1.71 1.26−2.31 Exposure to violence 1.68 1.24−2.29 1.18 0.84−1.64 1.60 1.15−2.22 Racial/ethnic mistreatment 1.96 1.18−3.25 1.71 0.96−3.05 0.96 0.62−1.49 Economic hardship† 1.70 1.28−2.28 2.12 1.52−2.95 1.30 0.99−1.70

*Adjusted for sex, age, race/ethnicity, and special health care needs of the child, as well as parent/household characteristics including

relation to the child, primary language, guardian education, family structure, and poverty/income level.

†95% CI = 95% Wald confidence intervals; bold indicates significance.

TAGGEDEND904 CROUCH ET AL ACADEMIC PEDIATRICS

challenges to school success, across all 3 categories. Chil-

dren 13−17 years of age had higher odds of school absentee- ism (aOR 1.71; 95% CI, 1.30−2.26), nonengagement in school (aOR 1.77; 95% CI, 1.38−2.26), and repeated grade (aOR 1.55; 95% CI, 1.22−1.97) than children 6−12 years old. Children with special health care needs were more likely

to have reported school absenteeism (aOR 5.45; 95% CI,

4.10−7.25), nonengagement in school (aOR 6.18; 95% CI, 4.76−8.03), and repeated grade (aOR 1.84; 95% CI, 1.42− 2.39) than children without special health care needs.

Children living in a disrupted household had higher odds

than children who did not, across all categories of chal-

lenges to school success. Children living in a disrupted

household had higher odds of school absenteeism (aOR

2.06; 95% CI, 1.41−3.00, Table 5), nonengagement in school (aOR 2.30; 95% CI, 1.75−3.04), and repeated grade (aOR 1.71; 95% CI, 1.26−2.31) than children not in a dis- rupted household. Children with economic hardship were

more likely to have reported school absenteeism (aOR

2.12; 95% CI, 1.52−2.95) and nonengagement in school (aOR 1.70; 95% CI, 1.28−2.28) than children without eco- nomic hardship. Children exposed to violence had higher

odds of nonengagement in school (aOR 1.68; 95% CI, 1.24− 2.29) than children not exposed to violence. Children

exposed to racial/ethnic mistreatment had higher odds of non-

engagement in school (aOR 1.96; 95% CI, 1.18−3.25) than children not exposed to racial/ethnic mistreatment.

TAGGEDH1DISCUSSION This study expands upon prior literature, examining the

relationship between ACEs and challenges to school suc-

cess, measured as school absenteeism, school engage-

ment, and repeated grade with a more recent dataset from

the NSCH. 15−17,22

In 2016, over half (51.2%) of children

and adolescents experienced ACEs, with nearly 8%

exposed to 4 or more ACEs. Rather than the presence (or

absence) of the 6 ACE types, we found that the exposure

to 4 or more ACEs had a consistently positive relationship

with children’s challenges to school success. Experienc-

ing 4 or more ACEs was strongly associated with the

experience of all 3 challenges to school success, adjusted

for various child and household characteristics. This study

explored the association between school success and by

both types of ACEs, as well as counts of ACEs. While

cumulative risk scoring is the strongest predictor of out-

comes such as school success or emotional, mental, or

behavioral health conditions among children, categories

of ACEs provide information for intervention opportuni-

ties. 20,23

Our findings confirm that ACEs can have an

impact in childhood and adolescence, not just later in

adulthood, as demonstrated by the association between

ACEs and school success factors. 15−17,22

Furthermore,

these findings further illuminate the connection between

ACEs and childhood outcomes of education and health. 22

Despite long-standing national prevention initiatives,

the rates of ACE exposures among children between the

ages of 0 and 17 were still 51.2% in 2016, increased from

47.9% in 2011. 15

How ACEs were associated with school

success depends on type of ACE exposure. We observed

that, on average, among the 6 ACE types, economic hard-

ship, living in a disrupted household, and exposure to vio-

lence were significantly associated with at least 2 school

success factors. Economic hardship, a top common ACE,

affected over a quarter of children in 2016. Children

experiencing economic hardship had substantially higher

rates of school absenteeism and nonengagement in school,

compared to their counterparts who might or might not

experience other types of ACEs. Because our variable

“living in a disrupted household” includes the ACE ques-

tion about living with someone who “has a problem with

alcohol or drugs,” our findings are consistent with previ-

ous findings that parental substance abuse is associated

with poorer school outcomes. 5,16

Children exposed to vio-

lence were more likely to be not engaged in school, again

supporting prior literature documenting the relationship

between neighborhood violence and lower school suc-

cess. 24

The investigation of particular types of ACEs is

important for pediatricians, as clinical practice guidelines

are geared towards the screening of particular ACEs upon

which there can be interventions. 25

TAGGEDH2IMPLICATIONS FOR POLICY AND PRACTICE

The findings from this study are relevant and important

for a pediatric provider audience, as the American Acad-

emy of Pediatrics recommends that pediatricians screen for

ACEs, as well as take a role in optimizing school readiness

and addressing challenges to school success such as chronic

TAGGEDENDACADEMIC PEDIATRICS CHALLENGES TO SCHOOL SUCCESS AND THE ROLE OF ACES 905

absenteeism. 1,8,25,26

The Bright Futures guidelines, a list of

guidelines for the screening of behavioral and psychosocial

risks, including ACEs, are supported by the American

Academy of Pediatrics and the federal Maternal and Child

Health Bureau. 27,28

These recommended screenings, assess-

ments, and examinations must be paid for by health insur-

ance plans under the Affordable Care Act and promote the

role of pediatricians and social workers in providing care

and addressing trauma. 29

However, there is concern about

the time required to address all that is included in the Bright

Futures guidelines. Because of time constraints, office-

based interventions and community resources can be of

benefit to pediatricians. Therefore, raising awareness

among pediatricians and other social service providers of

programs such as Help Me Grow, which is not currently in

all states but would be extremely beneficial for pediatri-

cians trying to connect their patients with support services,

can promote and simplify the process of connecting vulner-

able families to support services. 30

Pediatric visits can also provide an opportunity for

screening, prevention, and intervention, as pediatricians

often inquire about school performance at well-child vis-

its and provide guidance to children on attendance pat-

terns and healthy development. 31

Due to recent policy

changes, pediatricians now may be under more pressure

for school attendance. Since the fall of 2017, the major-

ity of states are required to report attendance for every

child, not just an aggregate number of average daily

attendance. 32,33

The Every Student Succeeds Act uses

chronic absence as top pick for the state indicator to

measure school quality and success. 33

Thus, pediatri-

cians may now be under more pressure from parents of

school age children to provide excuse notes so that

parents may avoid truancy court. The American Acad-

emy of Pediatrics recommends that pediatricians address

school attendance, and other related school success fac-

tors, using an office-based tiered approach including

front office staff, assistants, nurses, and care coordinators

to assist with the time burden on the pediatrician. The

first tier is office-based interventions for pediatricians,

such as asking about school attendance and other school

issues at preventive care visits, asking for school reports,

encouraging caregivers and patients when school is

going well, and educating themselves about appropriate

and inappropriate reasons that students may miss school.

The second portion of the tier 1 approach is population

based, such as collaborations with school professionals,

working with AAP chapter leaders for advocacy efforts,

supporting school districts as they improve children and

families’ access to health care services. Recommenda-

tions for tier 2 approaches include preventing and treat-

ing mental health issues that are contributing to lack of

school success and identifying psychosocial and health

factors of the patient’s caregiver that may contribute to

the child’s challenges at school. Finally, tier 3 approaches

include contacting the school district for case manage-

ment and support services. 8

These findings also provide further motivation for edu-

cation systems to intervene on ACEs. Schools are one

avenue to reach children and adolescents for childhood

trauma-informed welfare practice and services. 34 Methods

to introduce resilience-building techniques such as mind-

fulness training are being introduced in school settings. 35

School-based service delivery, such as the School-Wide

Positive Behavior Interventions and Supports framework

(www.pbis.org), has been shown to reduce reactions chil-

dren may have to traumatic stress. 36

Training of educators

on the role of trauma and adversity in learning may help

to create a better learning environment. 37

School policies

that create positive reinforcement for school attendance,

particularly for adolescents, could improve both school

absenteeism and school engagement. 38

TAGGEDH2STRENGTHS AND WEAKNESSES

This study uses a dataset that interviews parents and

caregivers, who may, due to social desirability and detec-

tion bias, underreport both childhood adversity and chal-

lenges to school success. The NSCH ACE questions do not

capture exposure to neglect, or emotional, physical, or sex-

ual abuse. This differs from the original Kaiser ACE

study. 12 Typical of most ACE surveys, the NSCH questions

do not measure severity or frequency of exposure to a spe-

cific ACE. The use of address-based sampling by the

NSCH misses households that are homeless or transient.

As well, there may be additional measures of challenges to

school success not captured in the NSCH. For example,

while we examine school absenteeism as 11 days or more

of missed school, as this is the highest category in the

NSCH, we recognize that the chronic absenteeism bench-

mark for school days is 15 or more days per year, per the

US Department of Education Office of Civil Rights

(https://www2.ed.gov/datastory/chronicabsenteeism.html).

Finally, this study is limited by the cross-sectional data of

the NSCH as there is no longitudinal population-based

dataset in the United States with information on adverse

childhood experiences, and thus no causal inferences on

why ACEs are associated with poor school success can be

made from this study.

There are several strengths to this study including the

use of a large, nationally representative dataset which is

weighted to be representative of the children in the United

States. To our knowledge, this study is the first using

2016 NSCH data to examine the association between

ACEs, by type and count, and challenges to school suc-

cess. The use of examination by both types and counts

may demonstrate the cumulative effect of ACE exposure,

with the examination by type providing additional infor-

mation to aid in the development of prevention and inter-

vention efforts. Also a strength is the use of interviews

with the parents of children, rather than interviews of

adults on their childhood. These interviews can provide

more timely information that can help shape current pol-

icy efforts. This study’s findings may contribute to the

development of prevention and interventions efforts to

reduce the prevalence of ACEs and mitigate their poten-

tial negative impact on school age children in the United

States.

T AGGEDEND906 CROUCH ET AL ACADEMIC PEDIATRICS

TAGGEDH1CONCLUSIONS School absenteeism, repeated grades, and nonengage-

ment in school are all challenges to a child’s school success,

potentially affecting long-term health outcomes. 39,40

The

findings from this nationally representative study confirm

prior findings that counts of 4 or more ACEs, as well as par-

ticular types of ACEs, such as economic hardship, exposure

to life in a disrupted household, and exposure to violence,

are associated with challenges to school success. By exam-

ining and understanding these issues within the context of

ACEs, rather than the factors themselves, we can begin to

better understand how they affect individuals long term and

how best to counteract their effects.

Educators, pediatricians, and social service providers

are all well-suited to engage with individuals, families,

and the community in conversations about childhood

trauma and school performance. Such conversations can

result in guidance for families on mitigating ACE expo-

sure and impact, and thus potentially improving the

child’s school performance and long-term well-being.

The continued support of policies and programs that work

to reduce the effects of childhood trauma are critical to

the well-being of our children. Future research should

examine frameworks that effectively support collabora-

tion between educators, social service providers, and

pediatricians as they seek to prevent or reduce the impact

of ACEs and other childhood trauma.

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