Sex Differences in the Relationship Between Early Adverse Childhood Experiences,Delinquency,and Substance Use Initiation in High-Risk Adolescents

Abstract

Adverse childhood experiences (ACEs) have been linked to a host of subsequent negative health and behavioral problems. However, the role of sex in the ramifications of early ACEs remains unclear, particularly for delinquency and substance use initiation in adolescence. A small body of research has produced mixed findings on sex differences in the relationship between ACEs and antisocial outcomes in adolescence, resulting in uncertainty about whether and how ACEs may operate differently for boys and girls. The current study drew on a high-risk group of adolescents (N=2455; M_age=15.4; 48% female; 50% Black, 23% Hispanic) from the Fragile Families and Child Wellbeing Study to examine the associations between accumulated ACEs across early childhood, and delinquency and substance use initiation of alcohol, cigarette, and cannabis in adolescence. We utilized mother and father reports on the exposure to seven different types of ACEs (i.e., physical abuse, psychological abuse, neglect, parental substance misuse, parental mental illness, parental intimate partner violence, and parental criminal behavior) when adolescents were ages 1, 3, and 5. Total ACEs scores and their relationships with delinquency, and lifetime use of alcohol, cigarettes, and cannabis were assessed separately for girls and boys. Results suggested that accumulated ACEs during early childhood may be implicated in boys’ delinquency, while ACEs were not significantly associated with girls’ self-reported delinquency or for boys’ and girls’ substance use initiation. Findings suggest that the enduring consequences of ACEs may be sex-specific, and have implications for the development of policies to mitigate ACEs and their harms.

Keywords

adverse childhood experiences delinquency substance use initiation fragile families sex differences

Introduction

Experiences during early childhood have far-reaching implications for health and wellbeing throughout the life course (Masten & Gewitz, 2006; Masten & Cicchetti, 2010). Adversity experienced during this period increases children’s susceptibility to developmental problems (Cicchetti & Toth, 2016). Moreover, the early home environment is especially impactful on children, as experiences with parents and family play a critical role in shaping youth’s transition into adolescence (Guralnick, 2006). Adverse Childhood Experiences (ACEs) are a set of adverse and potentially traumatic experiences in the home environment that can have harmful consequences over the course of development. ACEs include various forms of household dysfunction (i.e., parent criminal behavior, substance abuse, mental illness, intimate partner violence) and maltreatment (i.e., abuse and neglect) during childhood (Felitti et al., 1998). The prevalence of ACEs is concerning, with approximately 60% of adults exposed to at least one ACE and 25% exposed to three or more ACEs (Merrick et al., 2018). A large body of research has shown that greater ACEs are associated with greater risk of a variety of problematic social and behavioral outcomes (for a review, see Hughes et al., 2017; Petruccelli et al., 2019), including delinquency and substance use in adolescence (Baglivio et al., 2014; Dube et al., 2003; Duke et al., 2010; Fagan & Novak, 2018; Garrido et al., 2018; Leban & Gibson, 2020; Mersky et al., 2013; Schilling et al., 2007; Rothman et al., 2008).

Despite the rapid increase in knowledge over the past two decades on the nature and outcomes of ACEs, the role of sex in ACEs and their ramifications remains unclear. The small body of research examining sex differences in the relation of ACEs to adolescent antisocial behavior has produced mixed findings, with some studies concluding that ACEs have a stronger impact on delinquency, violence, and substance use in boys compared to girls (Duke et al., 2010; Leban & Gibson, 2020; Schilling et al., 2007). Others have revealed contradictory findings, suggesting that ACEs are more salient for girls’ (vs. boys’) delinquency (Pierce & Jones, 2021) and substance use (Leban & Gibson, 2020). Yet, others have found no differences in the effects of ACEs on adolescent substance use (Schilling et al., 2007) and delinquency (Garrido et al., 2018). Debate remains about whether and how ACEs may differentially impact boys and girls, particularly for high-risk samples of youth (i.e., those born to single-parent households).

Current Study

ACEs are being increasingly recognized as important for the development of programs and policies to ensure the wellbeing of youth during adolescence and beyond (Baglivio, 2020; CDC, 2021; Marie-Mitchell et al., 2016). Understanding how ACEs operate for girls and boys is essential to develop effective programs to prevent their enduring harm. Despite this, research on sex differences in the relationship between ACEs and substance use and delinquency is scant. Prior studies have yielded mixed results, thereby leaving a gap in the knowledge of how ACEs operate differently by sex in relation to substance use and delinquency. The current study draws on a sample of at-risk youth predominately born to single-parent families from the Fragile Families and Child Wellbeing Study to examine the relationships between ACEs in early childhood and delinquency and substance use initiation in adolescent girls and boys.

Methods

Data

Data for the current study were drawn from the Fragile Families and Child Wellbeing Study (FFCWS). The FFCWS includes a cohort of approximately 4700 families (Reichman et al., 2001), intended to be representative of a nationally-based sample of non-marital births in large U.S. cities. At baseline, the sample included approximately 3600 unwed and 1100 married couples (see Reichman et al., 2001 for additional study design details). To date, the FFCWS has followed the original sample of children and their families up until the focal child has reached the teenage years (approximately age 15). Six waves of data have been collected, beginning in 1998–2000, approximately 48 hours after birth. The remaining waves were collected via telephone-based core interviews with mothers and fathers when the children were ages one (1999–2001), three (2001–2003), five (2003–2006), nine (2007–2010) and fifteen (2014–2017). A subset of primary caregivers (typically the biological mother) also participated in in-home interviews at years three, five, and nine. The de-identified data from the FFCWS are publicly available and approval for secondary data analyses was given by the University of Alabama Institutional Review Board (Protocol 19–11–2993).

Analytic Sample

In order to accurately examine exposure to ACEs during early childhood (ages 1–5), the analytic sample for the current study is based on the sample of adolescents whose primary caregivers completed the in-home interviews during years three and five (i.e., when reports of childhood abuse and neglect were reported). Based on the number of primary caregivers who completed the in-home surveys, 2455 adolescents were included in the analytic sample at the onset of the analyses. Moreover, relevant data from the core mother and father interviews during the baseline and years one, three, and five core telephone surveys, as well as the adolescent self-reported interviews at year 15 were used for the analyses. All available observations were used in estimations, yielding samples sizes ranging from 1679–2455 in the models. Adolescents in the analytic sample were 48% female, 50% Black, 23% Hispanic and ranged in age from 14–18 (M_age=15.4; see Table 1 for study descriptives).

Table 1.

Descriptive Statistics for Study Variables by Sex.

	Full Sample	Girls	Boys
Variables	Mean (SD)	Mean (SD)	Mean (SD)	T-statistic/χ²
Delinquency (1–13)	1.08 (1.65)	0.89 (1.48)	1.27 (1.77)	−5.23**
Lifetime alcohol use (% yes)	15.1%	14.6%	15.5%	0.33
Lifetime cigarette use (% yes)	5.0%	4.0%	6.0%	4.60*
Lifetime cannabis use (% yes)	20.1%	17.6%	22.5%	7.91**
ACEs score (0–7)	3.15 (1.35)	3.12 (1.35)	3.18 (1.35)	−0.96
4 ≥ ACEs	41.4%	40.8%	42.0%	0.32
Physical abuse (% yes)	60.4%	57.4%	62.9%	7.83**
Psychological abuse (% yes)	85.0%	84.5%	85.4%	0.44
Neglect (% yes)	4.0%	4.0%	3.9%	0.00
Parental substance misuse (% yes)	4.3%	3.9%	4.7%	0.88
Parental mental illness (% yes)	40.1%	39.3%	40.9%	0.61
Parental intimate partner violence (% yes)	74.1%	75.4%	73.0%	1.82
Parental criminal behavior (% yes)	48.2%	48.5%	47.8%	0.13
Number of ACEs experienced				1.31
0	2.9%	3.0%	2.8%	--
1	8.7%	9.0%	8.4%	--
2	19.4%	19.7%	19.2%	--
3	27.5%	27.4%	27.6%	--
4	24.9%	24.9%	24.9%	--
5	13.9%	13.6%	14.2%	--
6	2.5%	2.3%	2.7%	--
7	0.1%	0.1%	0.2%	--
Income	5.62 (2.55)	5.57 (2.56)	5.67 (2.53)	−0.82
Parent education	1.66 (0.99)	1.63 (0.99)	1.68 (0.98)	−1.16
Parent married (% yes)	40.3%	39.3%	41.2%	0.77
Age	15.45 (0.66)	15.42 (0.65)	15.47 (0.67)	−1.85
White	18.9%	19.4%	18.3%	0.44
Black	50.0%	50.4%	49.6%	0.14
Hispanic	23.2%	22.0%	24.4%	1.72
Other race	7.9%	8.2%	7.7%	0.16
Parental attachment	1.96 (0.73)	1.87 (0.75)	2.04 (0.70)	−5.55**
Parental monitoring	2.37 (0.44)	2.40 (0.44)	2.34 (0.45)	3.29**
Delinquent peers	1.61 (2.29)	1.59 (2.22)	1.63 (2.35)	−0.46
Depression	0.61 (0.60)	0.66 (0.62)	0.56 (0.58)	3.99**
Anxiety	0.82 (0.65)	0.86 (0.68)	0.79 (0.62)	2.38*
Low self-control	1.50 (0.69)	1.49 (0.72)	1.51 (0.67)	−0.82

Note. ACEs = Adverse Childhood Experiences; SD = standard deviation; **p ≤ 0.01; *p ≤ 0 .05.

Measures

Adverse Childhood Experiences

Ages at which early ACEs have been measured in the FFCWS data have varied, with studies assessing ACEs at age 3 (Wang & Maguire-Jack, 2018; Choi et al., 2019), age 5 (Jimenez et al., 2016), age 3 through 5 (Jimenez et al., 2016; Wang et al., 2020), and birth through age 5 (Hunt et al., 2017; Schroeder et al., 2020; 2020; Jones & Pierce, 2021; Pierce & Jones, 2021; Jones et al., 2021). To comprehensively measure the accumulation of ACEs during early childhood, we measure ACEs as having occurred from birth to age 5. Importantly, the current study differs from previous work that has examined ACEs with the FFCWS by restricting the analysis sample to the subset of youth and their families who were administered/completed the in-home interviews, which is when the available ACEs measures were assessed in the FFCWS. Indeed, prior analyses have imputed ACEs data for respondents who did not complete the in-home interviews when the ACEs questions were administered (e.g., Jones & Pierce, 2021; Jones et al., 2021; Pierce & Jones, 2021; Schroeder et al., 2020). Given this concern, the current study only includes the subset of youth and their families with complete ACEs data.

Physical Abuse

Children’s exposure to physical abuse was assessed with the physical assault subscale from the Parent-Child Conflict Tactics Scale (CTSPC) (Straus et al., 1998). During the in-home interviews at years three and five, primary caregivers (most often the child’s biological mother) reported on the child’s exposure to categories of child maltreatment in the past year. Physical abuse was assessed with five questions that were administered during both in-home interview years. Primary caregivers reported on how many times in the past year they “Spanked [Child] him/her on the bottom with their bare hand,” “Hit him/her on the bottom with something like a belt, hairbrush, a stick or some other hard object,” “Slapped him/her on the hand, arm, or leg,” “Pinched him/her,” or “Shook him/her.” Response categories included once, twice, 3–5 times, 6–10 times, 11–20 times, more than 20 times in the past year, has happened but not in the past year, or never. In order to capture whether children had experienced physical abuse “often or very often” (as recommended by previous research; e.g., Felitti et al., 1998; Leban & Gibson, 2020), each of the items were recoded as 1 (happened six or more times in the past year) or 0 (less than six incidents in the past year). All five items of the physical assault subscale were summed across both interview years and dichotomized, where a score of one indicated exposure to some form of physical abuse (0 = no exposure).

Psychological Abuse

During the in-home interviews at years three and five, five items of the psychological aggression subscale of the CTSPC (Straus et al., 1998) were administered to primary caregivers. The five items asked the primary caregiver to report on incidents of psychological abuse within the past year, including, “Shouted, yelled, or screamed at [Child],” “Threatened to spank or hit but didn’t actually do it,” “Swore or cursed at,” “Called him/her dumb or lazy or some other name like that,” and “Said they would send him/her away or would kick him/her out of the house.” Similar to the physical abuse ACE outlined above, each of the items were recoded as 1 (happened six or more times in the past year) or 0 (less than six incidents in the past year). All five items of the psychological abuse subscale were summed across both interview years and dichotomized, where a score of one indicated exposure to some form of psychological abuse (0 = no exposure).

Neglect

The neglect subscale of the CTSPC (Straus et al., 1998) was administered to primary caregivers during years three and five of the in-home interview. Primary caregivers indicated five types of neglect in the past year: “Had to leave their child home alone, even when they thought some adult should be with him/her,” “Was so caught up with their own problems that they were not able to show or tell their child that they loved him/her,” “Was not able to make sure their child got the food he/she needed,” “Was not able to make sure their child got to a doctor or hospital when he/she needed it,” “Was so drunk or high that they had a problem taking care of their child.” Each of the items was recoded as 1 (happened six or more times in the past year) or 0 (less than six incidents in the past year). All five items of the neglect subscale were summed across both interview years and dichotomized, where a score of one indicated exposure to some form of neglect (0 = no exposure).

Parental Substance Misuse: Alcohol and Drug Dependence

During the year three interview, mothers and fathers reported on their own history of alcohol and drug dependence with a subset of questions derived from the Composite International Diagnostic Interview-Short Form (CIDI-SF) (Kessler et al., 1998). The short form of the CIDI includes a portion of questions asked in the full CIDI and is used to generate the probability that the respondent would qualify as a “case” or be positively diagnosed with alcohol or drug dependence if administered the full CIDI interview. The constructed case variables (yes/no) for mother and father alcohol and drug dependence, respectively, were summarized to create a dichotomous measure of any exposure to parental substance misuse (1 = exposure to parental substance misuse, 0 = no exposure).

Parental Mental Illness: Depression and Anxiety

During the year one and year three interviews, mothers and fathers were administered questions derived from the CIDI-SF (Kessler et al., 1998) to measure the presence of a major depressive episode and Generalized Anxiety Disorder. Similar to the CIDI-SF measures of parental alcohol and drug dependence detailed above, constructed measured the probability that the respondent would be a “case,” or positively diagnosed with a major depressive episode (liberal caseness) or Generalized Anxiety Disorder if given the full CIDI interview. The probability of these two outcomes (yes/no) for both mothers and fathers were summarized across years one and three and used to create a dichotomous measure of any exposure to parental mental illness (1 = exposure to parental mental illness, 0 = no exposure).

Parental Intimate Partner Violence (IPV)

Mothers reported on their exposure to intimate partner violence with the child’s biological father (either currently married/romantically involved or no longer together) or their current partner during the years one, three, and five interviews.¹ Seven items assessed how the father/partner behaved toward the mother: “He insults or criticizes you or your ideas,” “He tries to keep you from seeing or talking with your friends or family,” “He tries to prevent you from going to work or school,” “He withholds money, makes you ask for money, or takes your money,” “He slaps or kicks you,” “He hits you with his fist or an object that could hurt you,” and “He tries to make you have sex or do sexual things you don’t want to do.” Moreover, the year five interview added four questions to the original seven items asked during previous waves. These included, “He withholds sex to try to control your behavior,” “He insults or criticizes you for not taking good enough care of the child or your home,” “He throws something at you,” and “He pushes, grabs, or shoves you.” All items were recoded as 1 (sometimes or often) or 0 (never) and summarized across years one, three, and five and then dichotomized to create a measure of the mother’s exposure to IPV (1 = exposure to IPV, 0 = no exposure).

Parental Criminal Behavior

During years three and five, mothers and fathers self-reported on their experiences with the criminal justice system. These items included: “Other than for a minor traffic violation, have you ever been stopped by the police (but not picked up or arrested)?” and “Not counting minor traffic offenses, have you ever been booked or charged with breaking the law? (including juvenile offenses).” Mothers’ and fathers’ yes/no responses for each of the items during both interview years were summarized and used to create a dichotomous measure of exposure to parental criminal behavior (1 = exposure to parental criminal behavior, 0 = no exposure).

A total of seven ACEs were assessed from the mother/father core interviews and the in-home surveys during early childhood (ages 1–5). These ACEs include physical abuse, psychological abuse, neglect, parental substance misuse, parental mental illness, parental intimate partner violence, and parental criminal behavior. If primary caregivers and mothers/fathers reported “yes” to any of the items within a given ACE domain (e.g., neglect) across the waves in which that ACE was assessed, adolescents were scored as having been exposed to that ACE. Dichotomous variables were created for each of the seven ACEs and the total ACEs score reflects a cumulative score due to the summing of the ACEs representative of the time points in which they were assessed. In the study sample, ACEs scores ranged between 0 (no exposure to ACEs) and 7 (exposed to all seven types of ACEs).²

Adolescent Outcomes.

Delinquency

During the year 15 interview, adolescents self-reported on their involvement in delinquent acts during the past 12 months. The FFCWS adopted the delinquency items from the National Longitudinal Study of Adolescent Health (ADD Health) (Harris, 2013). 13 items assessed vandalism, property damage, shoplifting, physical fighting, hurting someone badly enough to need bandages/seek medical care, driving a car without the owner’s permission, stealing something worth more than $50, going into a house/building to steal something, using/threatening to use a weapon, selling marijuana or other drugs, stealing something worth less than $50, taking part in a group fight, and disorderly conduct in public. A variety score was created given the low prevalence of delinquency items. Such an approach has been recommended to reduce bias and increase validity of estimates with skewed delinquency measures (Sweeten, 2012). Each item was recoded as 1 (engaged in the delinquent act in the past year) or 0 (did not engage in the act during the past year), before summing the items to create an index score of delinquency (α = 0.72). Higher scores correspond to participation in a greater number of delinquent activities over the past year.

Substance Use

Adolescents also self-reported on their lifetime use of alcohol, cigarettes, and cannabis during the year 15 interview. Lifetime alcohol use was assessed with the question, “Have you had a drink of beer, wine, or liquor—not just a sip or a taste of someone else’s drink—more than two or three times in your life when you were not with your parents?”. This item was coded as 1 = yes and 0 = no. Lifetime cigarette use as also asked with a single item, “Have you ever smoked an entire cigarette?” and coded as 1 = yes and 0 = no. Finally, lifetime cannabis use was assessed with the question, “Have you ever tried marijuana?” and was coded as 1 = yes and 0 = no.

Covariates.

Demographics

Sex (1 = male, 0 = female), age (Mage=15.4, SD=0.66), and self-reported race/ethnicity (1 = non-White, 0 = non-Hispanic White) at year 15 were included as covariates. Primary caregiver-reported annual household income (0 = under $5000 to 8 = greater than $60,000), primary caregivers’ highest level of education (0 = less than high school to 3 = college or graduate), and primary caregivers’ current marital status (0 = not married, 1 = married) were recorded at year 15 and also included as covariates.

Parental Attachment

During the year 15 interview, adolescents reported on their closeness to both their mother and father. Four items total (two items for each parent) asked the youth, “How close do you feel to your mom/dad?” and “How well do you and your mom/dad share ideas or talk about things that really matter?”. Both items were recoded as 0 = not very close/well to 3 = extremely close/well. The four items were summed to create an index score of parental attachment (α = 0.63) where higher scores are associated with greater parental attachment.

Parental Monitoring

At year 15, primary caregivers reported on the limits they set on their child’s behaviors, such as staying out late, watching TV and movies, and the teen peer group. The FFCWS adapted these items from the National Longitudinal Survey of Youth (1997) (NLSY97), Round One Parent Questionnaire-Child Family Background (PC12), and the Youth Self-Administered Questionnaire (YSAQ). Three items asked whether the parent decides, the youth decides, or the parent and youth jointly decide on: 1) How late the youth stays out at night, 2) What kinds of TV shows and movies the youth watches, and 3) Who the youth can hang out with. The items were recoded to 3 = the parent decides, 2 = the parent and youth jointly decide, and 1 = the youth decides. The items were summarized into an index score of parental monitoring (α = 0.48) so that higher scores correspond to greater parental monitoring.

Delinquent Peers

During year 15, adolescents answered questions about how often their friends engaged in delinquent activities during the past year. 11 items assessed peer cigarette smoking, alcohol use, marijuana use, illegal or prescription drug use, invitations to drink together, giving or selling marijuana to the youth, damaging property, stealing something worth more than $50, using or threatening to use a weapon, selling marijuana or other drugs, and stealing something worth less than $50. All 11 items were used to create a variety score of peer delinquency in the past year (α = 0.83) due to the low prevalence of peer delinquency. Each item was recoded as 1 (i.e., peer(s) engaged in the delinquent act in the past year) or 0 (peer(s) did not engage in the act during the past year). Higher scores correspond to greater peer participation in delinquent activities over the past year.

Depression

Teenage depression was assessed with items drawn from the Center for Epidemiologic Studies Depression Scale (CES-D) (Radloff, 1977) at year 15. Five items asked adolescents about their symptoms of depression during the past 4 weeks (e.g., could not shake off the blues, felt sad, felt happy (reverse coded), felt that life was not worth living, and felt depressed). Items were scored as 0 = strongly disagree, 1 = somewhat disagree, 2 = somewhat agree, and 3 = strongly agree. These items were averaged into an index to reflect an overall score of depression (α = 0.75).

Anxiety

Adolescents’ anxiety was assessed with a modified version of the Brief Symptom Inventory 18 (BSI 18) (Derogatis & Savitz, 2000). Teens reported on how they felt or behaved during the past 4 weeks on six items including having spells of terror or panic, feeling tense, suddenly scared for no reason, feeling nervous, fearful, and restless. Items were scored as 0 = strongly disagree, 1 = somewhat disagree, 2 = somewhat agree, and 3 = strongly agree. The six items were averaged in order to capture each subject’s general level of anxiety (α = 0.75).

Low Self-Control

Adolescent-reported impulsivity was assessed with six items from an abbreviated form of the Dickman’s impulsivity scale (Dickman, 1990). During the year 15 interview, youth were instructed to think about how they have behaved or felt during the past 4 weeks for the following statements: “Often, I don’t spend enough time thinking over a situation before I act,” “I often say and do things without considering the consequences,” “Many times, the plans I make don’t work out because I haven’t gone over them carefully enough in advance,” “I often make up my mind without taking the time to consider the situation from all angles,” “I often say whatever comes into my head without thinking first,” and “I often get into trouble because I don’t think before I act.” The six items were recoded as 0 = strongly disagree, 1 = somewhat disagree, 2 = somewhat agree, and 3 = strongly agree and averaged to create an index of teen impulsivity (α = 0.78), where higher scores represent greater impulsivity.

Statistical Analyses

Preliminary analyses involved assessing descriptive statistics for the study variables and the prevalence of ACEs, delinquency, and substance use initiation reported among the full sample and by sex. T-tests and chi-square tests of independence assessed sex differences in delinquency, substance use initiation, ACEs, and all study covariates. Bivariate Pearson correlations among the study variables are also reported by sex. Negative binomial regressions were used to predict Incident Risk Ratios (IRR) for the associations between delinquency, the total ACEs score, and remaining study covariates. Odds Ratios are reported from the logistic regressions predicting the association between the three separate types of substance use initiation (i.e., alcohol, cigarette, and cannabis use), total ACEs score, and study covariates. The negative binomial and logistic regression models are reported separately for girls and boys.

Results

Study Descriptives and Sex Differences in Exposure to ACEs

The descriptive results for sex differences in delinquency, substance use initiation, total ACEs scores, and in each type of ACE are reported in Table 1. The analysis sample reported a mean delinquency count of 1.08, with girls reporting a mean of 0.86 and boys 1.27. The mean delinquency score did significantly differ by sex (t = −5.23, p < 0.00). For the substance use outcomes, approximately 15% of the analytic sample reported lifetime alcohol use initiation (14.6% of girls and 15.5% of boys reporting alcohol use). Moreover, 4% and 17.6% of girls reported lifetime use of cigarettes and cannabis, respectively. For lifetime use of cigarettes and cannabis, 6% and 22.5% of boys reported substance use in each respective category. Chi-square tests of independence revealed that boys reported significantly more lifetime initiation of cigarette use (χ² (1) = 4.60, p = 0.03) and cannabis use (χ² (1) = 7.91, p < 0.01) compared to girls.

For the total ACEs score, the full analytic sample reported a mean of 3.15 ACEs, while girls reported a mean of 3.12 and boys a mean of 3.18. The mean score of total ACEs did not significantly differ by sex (t = −0.96, p = 0.34). Approximately 41% of the analytic sample reported experiencing four or more ACEs during early childhood (i.e., ages 1–5), while 40.8% of girls and 42% of boys experienced four or more ACEs during early childhood. Among the individually reported ACEs, psychological abuse was the most commonly reported ACE in the analytic sample (85%). A high prevalence of parental intimate partner violence (74.1%) and physical abuse (60.4%) were also reported in the analytic sample. The only ACE reported to significantly differ by sex was the experience of physical abuse (χ² (1) = 7.83, p < 0.01), where boys exhibited a higher prevalence of this ACE (i.e., 62.9% vs. 57.4% for girls).

The descriptive statistics and sex differences in the remaining study covariates are also presented in Table 1. Significant sex differences exist between four of the study covariates (i.e., parental attachment, parental monitoring, depression, and anxiety). Boys in the sample self-reported higher mean scores for parental attachment than did girls (t = −5.55, p < 0.00). Moreover, girls’ primary caregivers reported higher mean scores of parental monitoring than did boys’ primary caregivers (t = 3.29, p < 0.01). Finally, girls were also more likely to report higher mean scores of depression (t = 3.99, p < 0.00) and anxiety (t = 2.38, p = 0.02) than boys during the year 15 interview.

Bivariate Associations for Study Variables by Sex

The bivariate correlations for the total ACEs scores, delinquency, substance use initiation, and the remaining study covariates are reported for girls in Table 2 and for boys in Table 3. Among girls in the analytic sample, delinquency, cigarette use, and cannabis use were significantly related to the total ACEs score (r = 0.11, 0.11, 0.12, respectively). Boys’ total ACEs scores were also significantly correlated with delinquency (r = 0.16), as well as with all three types of substance use initiation, that is, alcohol, cigarette, and cannabis use (r = 0.07, 0.06, 0.11, respectively). Total ACEs scores were significantly related to household income, parent marital status, race, parental attachment, delinquent peers, and low self-control for both girls and boys (range r = −0.20–0.12). Notably, parental monitoring was not significantly related to total ACEs scores for girls nor for boys. However, depression and anxiety were significantly related to total ACEs scores among boys (both r = 0.11), but not for girls.

Table 2.

Bivariate Correlations of Study Variables for Girls.

	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16
1. Total ACEs	1.00
2. Income	−0.14*	1.00
3. Edu	−0.09*	0.32*	1.00
4. Married parent	−0.16*	0.38*	0.20*	1.00
5. Age	−0.01	−0.03	−0.10*	−0.07*	1.00
6. Race	0.09*	0.24*	−0.18*	−0.24*	0.11*	1.00
7. Attachment	−0.16*	0.08*	0.02	0.12*	0.01	−0.06	1.00
8. Monitoring	−0.04	−0.07*	−0.13*	−0.07*	−0.06*	0.17*	−0.01	1.00
9. Delinq. Peers	0.11*	−0.06	−0.04	−0.10*	0.04	0.02	−0.22*	−0.05	1.00
10. Depression	0.06	−0.13*	−0.10*	−0.11*	−0.02	0.01	−0.33*	0.03	0.25*	1.00
11. Anxiety	0.03	−0.07*	−0.09*	−0.06	−0.01	−0.01	−0.25*	0.03	0.21*	0.65*	1.00
12. LSC	0.12*	−0.15*	−0.14*	−0.15*	−0.02	0.13*	−0.22*	0.11*	0.24*	0.32*	0.44*	1.00
13. Delinq	0.11*	−0.17*	−0.08*	−0.16*	0.05	0.09*	−0.21*	−0.01	0.47*	0.22*	0.21*	0.32*	1.00
14. Alcohol use	0.04	−0.10*	−0.02	−0.06*	0.12*	−0.02	−0.14*	−0.08*	0.40*	0.15*	0.14*	0.17*	0.33*	1.00
15. Cigarette use	0.11*	−0.05	−0.02	−0.07*	0.02	−0.10*	−0.13*	0.01	0.30*	0.14*	0.09*	0.09*	0.29*	0.27*	1.00
16. Cannabis use	0.12*	−0.08*	−0.08*	−0.16*	0.10*	0.02	−0.18*	−0.07*	0.47*	0.19*	0.12*	0.19**	0.42*	0.43*	0.26*	1.00

Note. LSC = low self-control; Race/ethnicity is coded as 0=White, 1=Non-White; *p ≤ 0 .05.

Table 3.

Bivariate Correlations of Study Variables for Boys.

	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16
1. Total ACEs	1.00
2. Income	−0.07*	1.00
3. Edu	−0.04	0.31*	1.00
4. Married parent	−0.20*	0.38*	0.15*	1.00
5. Age	0.02	−0.10*	−0.09*	−0.10*	1.00
6. Race	0.09*	−0.21*	−0.25*	−0.24*	0.12*	1.00
7. Attachment	−0.12*	0.15*	0.09*	0.11*	−0.05	−0.03	1.00
8. Monitoring	0.02	−0.05	−0.03	−0.05	−0.08*	0.09*	0.05	1.00
9. Delinq. Peers	0.12*	0.02	−0.04	−0.05	0.12*	0.08*	−0.18*	−0.07*	1.00
10. Depression	0.11*	−0.11*	−0.09*	−0.11*	0.05	0.09*	−0.22*	−0.02	0.22*	1.00
11. Anxiety	0.11*	−0.06	−0.02	−0.07*	−0.00	0.02	−0.19*	0.02	0.18*	0.64*	1.00
12. LSC	0.11*	−0.02	−0.05	−0.08*	−0.06	0.05	−0.12*	0.07*	0.25*	0.30*	0.43*	1.00
13. Delinq	0.16*	−0.07*	−0.11*	−0.11*	0.05	0.11*	−0.18*	−0.01	0.55*	0.18*	0.15*	0.32*	1.00
14. Alcohol use	0.07*	−0.02	−0.07*	−0.05	0.14*	0.01	−0.09*	−0.08*	0.41*	0.15*	0.11*	0.13*	0.32*	1.00
15. Cigarette use	0.06*	−0.03	−0.07*	−0.04	0.10*	−0.04	−0.13*	−0.04	0.32*	0.14*	0.08*	0.09*	0.25*	0.35*	1.00
16. Cannabis use	0.11*	−0.06	−0.12*	−0.13*	0.22*	0.10*	−0.16*	−0.07*	0.47*	0.13*	0.07*	0.16*	0.43*	0.44*	0.37*	1.00

Note. LSC = low self-control; race/ethnicity is coded as 0=White, 1=Non-White; *p ≤ 0 .05.

Associations between ACEs, Delinquency, and Substance Use by Sex

Table 4 (girls) and Table 5 (boys) report the findings from the negative binomial regressions examining the associations between delinquency, the total ACEs score, and remaining study covariates. Moreover, logistic regressions predicted the associations between the three separate types of substance use initiation (i.e., alcohol, cigarette, and cannabis use), total ACEs score, and study covariates are reported in Tables 4 and 5. The estimates in Table 4 reveal that the total ACEs score was not significantly related to girls’ risk for delinquency or increased odds of initiating alcohol, cigarette, or cannabis use by age 15. However, greater family household income was associated with less risk for delinquency among girls (IRR = 0.95, p = 0.02), whereas delinquent peers (IRR = 1.24, p < 0.00) and low self-control (IRR = 1.69, p < 0.00) were significantly related to a greater risk for delinquency. Notably, associating with delinquent peers significantly increased the odds of initiating all three types of substance use among girls (range OR = 1.51–1.63, p < 0.00). Low self-control was also significantly associated with greater odds of initiating alcohol use (OR = 1.62, p = 0.01) and cannabis use (OR = 1.63, p = 0.01) by age fifteen.

Table 4.

Associations between Girls' ACEs, Delinquency, and Substance Use Initiation.

	Delinquency	Alcohol Use	Cigarette Use	Cannabis Use
	IRR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)
Total ACEs	1.07 (0.99, 1.15)	0.93 (0.78, 1.10)	1.38 (0.97, 1.97)	1.13 (0.95, 1.35)
Income	0.95* (0.91, 0.99)	0.86** (0.79, 0.95)	0.84 (0.70, 1.01)	0.99 (0.90, 1.08)
Parent education	0.98 (0.88, 1.10)	1.07 (0.83, 1.38)	1.03 (0.64, 1.67)	1.03 (0.80, 1.32)
Parent married	0.84 (0.67, 1.06)	1.35 (0.79, 2.28)	0.80 (0.27, 2.38)	0.54* (0.31, 0.92)
Age	1.00 (0.85, 1.19)	1.75** (1.23, 2.49)	1.36 (0.68, 2.71)	1.29 (0.90, 1.83)
Race/ethnicity	1.20 (0.90, 1.61)	0.64 (0.35, 1.17)	0.18** (0.06, 0.54)	0.95 (0.51, 1.76)
Parental attachment	0.90 (0.78, 1.03)	0.76 (0.54, 1.05)	0.60 (0.32, 1.15)	0.69* (0.49, 0.96)
Parental monitoring	0.95 (0.76, 1.19)	0.62 (0.37, 1.04)	1.60 (0.57, 4.51)	0.62 (0.37, 1.04)
Delinquent peers	1.24** (1.19, 1.29)	1.53** (1.39, 1.68)	1.51** (1.29, 1.76)	1.63** (1.48, 1.80)
Depression	1.06 (0.87, 1.30)	1.02 (0.65, 1.60)	1.75 (0.81, 3.79)	1.74* (1.11, 2.71)
Anxiety	1.02 (0.84, 1.25)	1.05 (0.67, 1.64)	0.86 (0.38, 1.91)	0.65 (0.41, 1.02)
Low self-control	1.69** (1.44, 1.98)	1.62** (1.12, 2.36)	1.97 (0.97, 4.01)	1.63** (1.14, 2.34)

Note. IRR = Incident risk ratio; OR = Odds ratio; **p ≤ 0.01; *p ≤ 0 .05, Significant findings are presented in bold.

Table 5.

Associations between Boys' ACEs, Delinquency, and Substance Use Initiation.

	Delinquency	Alcohol Use	Cigarette Use	Cannabis Use
	IRR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)
Total ACEs	1.10** (1.03, 1.17)	1.07 (0.91, 1.26)	1.17 (0.91, 1.51)	1.10 (0.95, 1.27)
Income	0.98 (0.95, 1.02)	1.00 (0.91, 1.09)	1.04 (0.90, 1.20)	1.00 (0.92, 1.08)
Parent education	0.92 (0.84, 1.01)	0.84 (0.67, 1.05)	0.68* (0.48, 0.95)	0.78* (0.63, 0.95)
Parent married	0.91 (0.75, 1.09)	0.94 (0.59, 1.50)	0.93 (0.44, 1.96)	0.58* (0.38, 0.90)
Age	1.01 (0.89, 1.15)	1.64** (1.23, 2.19)	1.80** (1.19, 2.74)	1.84** (1.40, 2.41)
Race/ethnicity	1.15 (0.90, 1.46)	0.88 (0.49, 1.58)	0.27** (0.12, 0.62)	1.17 (0.66, 2.09)
Parental attachment	0.87* (0.77, 0.99)	0.93 (0.67, 1.28)	0.47** (0.28, 0.77)	0.60** (0.45, .81)
Parental monitoring	0.99 (0.82, 1.19)	0.60* (0.38, 0.95)	1.31 (0.62, 2.75)	0.76 (0.50, 1.15)
Delinquent peers	1.22** (1.18, 1.27)	1.38** (1.28, 1.50)	1.45** (1.30, 1.62)	1.48** (1.365, 1.60)
Depression	0.99 (0.83, 1.18)	1.09 (0.70, 1.70)	1.49 (0.79, 2.82)	0.79 (0.52, 1.21)
Anxiety	1.00 (0.84, 1.19)	1.16 (0.75, 1.79)	0.88 (0.46, 1.69)	0.95 (0.63, 1.43)
Low self-control	1.63** (1.41, 1.87)	1.36 (0.95, 1.93)	0.90 (0.52, 1.53)	1.39* (1.01, 1.92)

Note. IRR = Incident risk ratio; OR = Odds ratio; **p ≤ 0.01; *p ≤ 0 .05, Significant findings are presented in bold.

The results in Table 5 reveal that boys’ total ACEs scores accumulated during early childhood significantly increased the risk for delinquency at age fifteen (IRR = 1.10, p < 0.01). However, boys’ total ACEs scores were not significantly associated with greater odds of any of the types of substance use initiation at year 15. Similar to the findings for girls, associating with delinquent peers was associated with increased odds of boys initiating all three types of substance use by age fifteen (range OR = 1.38–1.48, p < 0.00). Moreover, low self-control was associated with a greater risk for delinquency (IRR = 1.63, p < 0.00) and greater odds of initiating cannabis use among boys (OR = 1.39, p = 0.04).

Discussion

Few studies have investigated sex differences in the relationship between ACEs, delinquency, and substance use. This small body of research has produced mixed findings on the role of sex in the ramifications of ACEs for adolescent outcomes. The current study’s findings suggest that cumulative ACEs during ages 1–5 are implicated in risk for delinquency for adolescent boys, but not for girls. One possible explanation for why ACEs may be associated with delinquency in boys, but not girls, is that male adolescents with a history of ACEs may cope with externalizing behaviors, whereas girls may display internalizing symptoms, such as those related to mental health outcomes. Indeed, some evidence suggests that ACEs are more strongly related to delinquency and antisocial behavior for boys than for girls. Duke and colleagues’ (2010) analysis of a sample of students in sixth, ninth, and 12th grades showed ACEs were more strongly associated with violence for boys than girls. Leban and Gibson (2020) relied on a longitudinal sample of youth and found that ACEs were associated with increased delinquency at age 15 for boys, but not for girls. Others have similarly documented a stronger effect of ACEs on boys’ (compared to girls’) antisocial behavior (i.e., aggression and illegal acts) in late adolescence (Schilling et al., 2007). In contrast, a recent study found that ACEs in early childhood were related to delinquency for girls only (Pierce & Jones, 2021), while another study found no sex differences in the impact of ACEs on “risk behaviors” (i.e., violence, substance use, delinquency) in early adolescence (Garrido et al., 2018). Nonetheless, it is important to note that delinquent peers and reports of low self-control were both related to adolescent delinquency for girls and boys. These findings align with previous research demonstrating support for the role of self-control and peer influences on delinquency and offending behaviors (Pratt & Cullen, 2000).

The current study also reports that cumulative ACEs were not implicated in substance use initiation among girls or boys. Prior research has reported mixed findings on the relationship between ACEs and adolescent substance use. For example, ACEs have been shown to increase the odds of substance use for adolescent girls, but not for boys (Leban & Gibson, 2020), while another showed that ACEs increased the odds of substance use more for men than for women in early adulthood (Mersky et al., 2013), and yet another found no sex differences (Schilling et al., 2007). As with delinquency, associations with delinquent peers were implicated in all three substance use initiation types for girls and boys. These findings highlight the salience of peer risk behaviors on adolescent self-reported substance use and delinquency, even within the context of ACEs during early childhood.

Implications

The findings from the current study have the potential to inform prevention and intervention programs that target adolescent delinquency and substance use in high-risk populations of youth and their families. Prevention programs could screen for ACEs early in life, particularly among single-parent households. Moreover, interventions should consider sex-specific responses to ACEs (Leban & Gibson, 2020). For instance, these programs may benefit from recognizing that males may be more likely to cope with a history of ACEs through externalizing behaviors, such as delinquency. Sex-specific intervention strategies, such as those related to improving emotional regulation in boys, could improve relationships and behavioral outcomes across family, school, and peer contexts. Intervention programs that target youth with histories of ACEs may also benefit from supporting prosocial peer relationships during adolescence in order to reduce the risk of poor adolescent outcomes.

Limitations

Several limitations should be considered when interpreting our study’s findings. First, the FFCWS has limited data on sexual abuse, which prevented us from including this as an ACE in the current study.³ Although sexual abuse also has been excluded in ACE measures in other sample populations (e.g., Craig et al., 2017; Leban & Gibson, 2020; Mersky et al., 2013), we recognize that our inability to include this ACE may have potentially impacted our results, especially given that sexual abuse is more commonly experienced by girls compared to boys (Dierkhising et al., 2013; Felitti et al., 1998). This limitation may also be related to a more general issue of inconsistency in the measurement of ACEs within the literature. For example, prior studies have included additional ACEs, such as witnessing community violence, bullying, peer rejection, illness of parent or sibling, and food insecurity (e.g., Cronholm et al., 2015; Fagan & Novak, 2018; Finkelhor et al., 2013; Mersky et al., 2013). Others have been unable to or decided against including ACEs represented in Felitti et al.'s (1998) original ACEs model, such as divorce (Hunt et al., 2017) and sexual abuse (Leban & Gibson, 2020; Mersky et al., 2013). Despite this variation, these studies follow the similar logic of and build on the ACEs model. Moreover, the current study employed a measure of ACEs similar to other ACEs measures constructed with data from the FFCWS (e.g., Hunt et al., 2017; Jones & Pierce, 2021; Jones et al., 2021; Pierce & Jones, 2021). Second, the low prevalence of delinquency reported in the current study warrants the need to examine the implications of ACEs for externalizing behaviors (as well as sex differences in these relationships) in other at-risk populations of youth, as prior research has begun to do (e.g., Dierkhising et al., 2019; Leban & Masterson, 2021). Moreover, populations that exhibit a higher prevalence of delinquency would allow for the estimation of the variation in the frequency of delinquent behaviors and also permit the estimation of and comparison between different types of delinquent behaviors, such as general delinquency (e.g., property offenses) versus violent delinquency (e.g., physical assault) (Fagan & Wright, 2012). Third, low reports of cigarette use may have also influenced the ability to detect significant relationships between ACEs and cigarette use initiation, although these low rates were not surprising as cigarette use among adolescents has declined since the late 1990s (Johnson et al., 2019). E-cigarette use is now recognized as the most prevalent nicotine administration route among American adolescents (Office of the Surgeon General, 2018), therefore future research may wish to examine the influence of ACEs on e-cigarette use. It is also important to note that cannabis use yielded the highest prevalence of reported substance use in the study population (i.e., approximately 20% vs. 15% for alcohol use and 5% for cigarette use). In the current study, data collection on adolescent substance use behaviors occurred between 2014 and 2017, which coincided with the legalization of medicinal cannabis in several states, as well as the decriminalization of small amounts of cannabis, or the legalization of recreational cannabis use. Although we are unable to infer definitive conclusions about the effect that these laws might have had on adolescent cannabis use reported in the current study, some evidence suggests that adolescent cannabis use has increased due to this legislation (Cerdá et al., 2017; Miech et al., 2015), while others have found no impact on adolescent cannabis use (Midgette & Reuter, 2020). Perhaps one unintended consequence of cannabis legalization is the perception that cannabis use is less harmful than cigarette use, thus increasing the disparity in the prevalence of cannabis versus cigarette use. Future research may also seek to examine the impact of these trends on male versus female adolescent substance use. Indeed, recent research has begun to examine sex and racial/ethnic differences in the single use, as well as co-use, of alcohol, cigarettes, and cannabis in the FFCWS and in other high-risk populations of youth (Gajos et al., 2022; Purcell et al., 2021).

Conclusion

Despite these caveats, the current study provides a contribution to the existing literature on examining sex differences in the relationship between ACEs, adolescent delinquency, and substance use initiation among a high-risk population of youth. Our findings suggest that cumulative ACEs are associated with delinquency among adolescent boys. Prevention efforts may wish to screen for ACEs early on to reduce the risk of delinquency among at-risk youth, particularly for boys.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Funding for the Fragile Families and Child Wellbeing Study was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) of the National Institutes of Health under award numbers R01HD036916, R01HD039135, and R01HD040421, as well as a consortium of private foundations. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

ORCID iD

Jamie M. Gajos

Notes

Authors Biographies

Jamie M. Gajos, PhD, is an Assistant Professor in the Department of Human Development and Family Studies at the University of Alabama. Her research examines the influence of environmental and individual-level factors on the course and variability of substance use and other health-risk behaviors across time and within important proximal social contexts.

Lindsay Leban, PhD, is an Assistant Professor at the University of Alabama at Birmingham. She received her PhD in criminology from the University of Florida in 2018. Her research focuses on victimization, gender and crime, and substance/drug use.

Bridget B. Weymouth, PhD, is an Assistant Professor at the University of Alabama in the Department of Human Development and Family Studies. Her research focuses on social anxiety and substance use among adolescents and conflict within families.

Karen L. Cropsey, PsyD, is the Conatser Turner Endowed Professor in the Department of Psychiatry and Behavioral Neurobiology in the University of Alabama at Birmingham School of Medicine. Dr Cropsey’s research focuses on addiction and substance use treatment among vulnerable populations, including criminal justice populations.

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