Background
Alcohol is a teratogen, a substance that can alter growth and normal development in the central nervous system, including brain structure and other organs of a developing foetus [
1]. Fetal Alcohol Spectrum Disorder (FASD) is a condition characterised by a variety of cognitive, physical, emotional and behavioural difficulties resulting from prenatal alcohol exposure (PAE). A meta-analysis estimated the worldwide prevalence of FASD to be 0 to 176.7 per 1000 births [
2]. The prevalence rate of FASD in Australia is mainly monitored through passive case ascertainment; thus, the figures are likely to be an underestimate [
3]. In Western Australia (WA), the estimate in 2015 was 0.26 per 1000 births [
4]. While FASD is a condition that can potentially affect individuals from all socioeconomic and cultural backgrounds [
5,
6], some communities are more at risk. The rates of FASD in a group of remote Australian Aboriginal communities was the highest, with a reported prevalence of 194 per 1000 births [
7]. The causes of excessive drinking in Aboriginal communities are multifaceted and are a product of cultural dislocation due to colonisation, intergenerational trauma and social/economic marginalisation [
8,
9].
Children born with FASD often encounter a range of adverse psychosocial situations, such as having early childhood characterised by parental unemployment and substance/alcohol misuse, mental health problems, and child protection involvement [
10,
11]. In Australian Aboriginal children with FASD, these adverse environmental factors may also occur within the context of historical and intergenerational trauma [
12]. Price et al. proposed that when a child with FASD is born into a dysfunctional family characterised by substance misuse, family violence and lacking empathy/communication, the functional impairments as a result of PAE are likely to be exacerbated [
13]. Consequently, the expression of FASD could be characterised by a series of negative events starting from the initial PAE to the accumulation of adverse childhood experiences (ACEs) over the lifespan [
11]. ACEs are traumatic events that range from abuse (e.g., sexual, physical and emotional), neglect (e.g., emotional and physical) to household dysfunctions (e.g., parental separation/divorce, parental mental illness, domestic violence, household substance misuse, incarceration) [
14].
Importantly, individuals who endorsed four or more categories of ACEs were 4 to 12 times more likely to engage in health-risk behaviours (e.g., alcohol/substance misuse, suicide attempt) and have chronic health problems (e.g., cancer, coronary heart disease) in adulthood; while those with one to three ACEs did not fare as well as those who had experienced none [
14]. In the context of FASD, pregnant women who reported a higher number of ACEs were more likely to consume alcohol to cope with stress and anxiety associated with ongoing life stressors [
15]. In addition to the 10 categories of ACEs outlined above, individuals with FASD are also at an increased risk of experiencing other stressors in life such as coming into contact with the child protection and justice system [
16,
17]. For example, a recent study reported the prevalence rate of FASD among young people in an Australian youth detention centre as 36% [
18].
Further, the complex relationship between FASD and psychosocial vulnerabilities in the affected individual is also an important clinical risk factor for comorbidity [
19]. It is well-established that individuals with FASD are at risk of developing a range of comorbid disorders [
20]. For example, Weyrauch et al. found that they are 11 times more likely to experience an anxiety disorder and 10 times more likely to be diagnosed with attention-deficit-hyperactivity disorder (ADHD) than the general population [
21]. Other frequently occurring comorbidities include disorders of the nervous system, conduct disorder, receptive/expressive language disorders, hearing impairment and intellectual disabilities [
20]. In an Australian FASD sample, Connor et al. found ADHD, sleep disturbance and anxiety disorder were the three most common comorbidities reported [
5].
To date, a handful of studies [
13,
22] have explored the relationship between PAE and early life trauma, with four published papers using a standardised ACEs questionnaire in the FASD population [
11,
23‐
25]. These studies revealed high rates of early life adversity in individuals with FASD. Additionally, it was also documented that childhood trauma is associated with child protection or justice system involvement, especially among children with FASD [
11,
26]. However, little to no research has examined the ACEs profiles of those with FASD who have been in contact with these government systems. To our knowledge, this study is the first to explore ACEs in an Australian FASD sample characterised by a high proportion of individuals who had been involved with the child protection and/or justice systems. Notably, both (i.e., child protection/justice) represent priority populations for the reduction of ACEs given their psychosocial vulnerabilities. A better understanding of the frequency and type of ACEs in at-risk children is important to help improve their physical, social/emotional and behavioural outcomes through the development of better early screening tools, services and more targeted interventions [
27]. Consequently, this study aimed to (1) explore the ACEs and associated stressors in children and youth with FASD; (2) investigate the association between ACEs and negative outcomes, i.e., justice/child protection system involvement; (3) and examine the relationship between ACEs and comorbid conditions in the sample.
Method
Participants
Between November 2016 and June 2019, 480 individuals attended Patches Australia, a multidisciplinary FASD diagnostic assessment service operating across Western Australia (WA). A total of 226 participants met the Australian FASD diagnostic criteria [
28] and 254 individuals were not diagnosed with FASD. Participants’ files were reviewed retrospectively, and individuals were included if they had a diagnosis of FASD and were under 22 years of age. The age cut-off was determined using the median absolute deviation method. Specifically, young people with FASD who were above the age of 21 were excluded from the present study (
n = 15). This resulted in a final sample size of 211 individuals (151 males) with FASD aged 2 to 21 years old.
Diagnostic process
In the Patches multidisciplinary FASD clinics, referrals for the diagnostic assessment came from general practitioners, paediatricians, caseworkers and other health, justice or education service providers. A paediatrician and a neuropsychologist were always part of the team, while a speech pathologist was only usually present when the participant was a child/adolescent. Participants were diagnosed with FASD using the Australian FASD diagnostic guidelines [
28]. As part of the FASD diagnostic process, participants’ neurocognitive performances were assessed in multiple domains including executive functioning, cognition, memory, attention, academic achievement, language, motor, affect regulation and adaptive functioning. Participants’ medical, psychosocial and developmental history was gathered through clinical interviews with the client and/or parents/legal guardians and self-report/informant questionnaires.
Adverse Childhood Experiences (ACEs) and associated stressors
Psychologists or paediatricians on the Patches multidisciplinary team routinely gather information on early life adversities through a clinical interview with the carer/parent and the child which is then included in the FASD diagnostic reports. For example, when a child was suspected of having experienced sexual abuse, the topic was approached delicately by an experienced clinician on the diagnostic team during the clinical interview with the child. These reports and all other available source documents (e.g., allied health, medical and educational reports) were reviewed, and the presence of nine early life adversities (e.g., victim of physical abuse, sexual abuse, emotional/verbal abuse, physical neglect, emotional neglect) and household dysfunctions (e.g., exposure to domestic violence, drinking/substance misuse, incarcerated relative, mentally ill family members/family members who attempt suicide) were retrospectively coded by the researcher against the 10-item ACEs questionnaire (See
Supplementary Material) [
14]. No missing information apart from participants’ parental marital status was identified during the retrospective coding of data. This left only nine categories comprising the ACEs total score. Therefore, a maximum score of nine (range = 0–9) was attainable. A score of four or more indicated an increased risk of negative health outcomes [
14,
29]. The ACEs questionnaire has acceptable (i.e., 0.70 or higher) internal reliability consistency and test-retest reliability [
29,
30]. A satisfactory convergent validity with the Childhood Trauma Questionnaire has also been demonstrated in both clinical and non-clinical samples [
31]. Furthermore, the ACEs questionnaire has been widely used to capture childhood adversity in both adults [
14,
32] and paediatric samples (e.g., FASD, autism spectrum disorder, at-risk children) [
11,
24,
33].
Additional life stressors (i.e., involvement with child protection, justice systems, victims of bullying, homelessness, transiency, severe traumatic brain injury, disengagement from school) not included in the 10-item ACEs questionnaire were also gathered from the Patches team diagnostic reports.
Diagnosis of comorbid conditions
Information on participants’ pre-existing diagnoses of neurodevelopmental, medical or mental health conditions was gathered from allied health and medical reports. Additional diagnoses were given by the Patches diagnostic team if criteria according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) were met [
34]. Only comorbidities with a frequency of at least 10% were coded as binary variables (Yes/No) and included in the analysis. These included ADHD, sleep disorder, attachment disorder, anxiety disorder, hearing impairment, post-traumatic stress disorder (PTSD), intellectual disability (ID), substance use disorder, conduct disorder and depression.
Ethics and consent
This study was approved by the Human Ethics Committee from the University of Western Australia and the Western Australian Aboriginal Health Ethics Committee (HREC Approval Number: 901) in consultation with an Aboriginal community reference group. For participants who were over 18 and capable of providing informed consent, consent was obtained in writing or electronically from the participant at the time of assessment. For participants under 18, or who were 18 or older and not capable of providing informed consent, assent was obtained from the participant and consent was obtained in writing or electronically from each participant’s parent or legal guardian at the time of assessment. Consent/assent was provided by all participants for their data to be included in this study.
Statistical analysis
Data analysis was conducted using IBM SPSS-22. Descriptive analyses were conducted to examine the demographics of the total sample, demographics of the subgroups (i.e., child protection engagement, justice system involvement) as well as the frequency and proportion of ACEs scores/categories and associated stressors.
An alpha level of 0.05 was used for all statistical tests. Pearson’s correlation was employed to explore the relationship between the total ACEs scores of the overall sample and age. Point-biserial correlations were used to examine the association between total ACEs scores of the entire cohort and demographic variables such as sex (1 = Male, 0 = Female) and cultural background (1 = Australian Aboriginal, 0 = Caucasian). The relationship between child protection system involvement (1 = Yes, 0 = No involvement) and total ACEs scores was also explored using point-biserial correlations. Similarly, the same test was used to examine the relationship between justice system involvement (1 = Yes, 0 = No) and total ACEs scores. Only participants aged 10 and above were included in this test as the age of criminal responsibility in WA is 10 years old.
A series of logistic regressions were performed to investigate the predictors (age, sex, cultural backgrounds) of each ACEs category in the total sample. All assumptions for the regression analyses were checked and met unless otherwise stated. The relationships between each ACEs category and child protection system involvement were explored using a series of Phi coefficients. The associations between each category of ACEs and justice system involvement were also examined with Phi coefficients in individuals aged 10 and above.
Descriptive statistics were used to explore the mean ACEs scores and standard deviation for each stressor and comorbid condition. Pearson’s correlation was performed to investigate the relationship between the total ACEs scores and the total number of comorbidities across the sample. This was followed up by a series of point-biserial correlations to explore the relationship between the total ACEs scores and each comorbid condition. The Benjamini-Hochberg procedure [
35] was used to correct for multiple comparisons for each family of tests.
Results
Participant Demographics
The mean age of the total sample at the time of assessment was 11 years (SD = 5, range = 2–21). The majority were individuals aged below 18 (
n = 199, 94%). Most participants were males (
n = 151, 72%) and identified as Australian Aboriginal (
n = 163, 77%). Of the total sample, 137 (64.9%) came from regional or remote parts of WA, while 74 (35%) were from major cities. Across the entire sample, 147 (70%) had contact with the child protection system, and 85 (40%) were involved with the justice system. Demographic characteristics based on child protection/justice system involvement can be seen in Table
1.
Table 1
Participant demographics based on child protection/justice system involvement
Mean Age (SD) | 11 (4) | 15 (2) |
Sex |
Male | 102 (69) | 72 (85) |
Female | 45 (31) | 13 (15) |
Cultural Background |
Aboriginal | 113 (77) | 73 (86) |
Caucasian | 34 (23) | 12 (14) |
Geographical Area |
Major cities | 54 (37) | 32 (38) |
Regional/remote | 93 (63) | 53 (62) |
Adverse Childhood Experiences (ACEs) Scores
The mean ACEs scores for the entire cohort were 2.8 (SD = 1.9, range = 0–8). In the overall sample, 83 (39%) had four or more ACEs recorded (See Table
2). The total ACEs scores of the overall sample were significantly positively correlated with age, r(211) = .14,
p = .04. Specifically, there were more documented ACEs in the records of older children than younger children. However, there was no association between the total ACEs scores and sex, r(211) = .06,
p = .36. Similarly, no significant correlation was found between the total ACEs scores and cultural background, r(211) = .03,
p = .71. Point biserial correlation shows young people with FASD who had been involved with the child protection system had higher total ACEs scores, r(211) = .38,
p < .001. Similarly, this trend was also observed in those with justice system involvement, r(133) = .17,
p = .047.
Table 2
Frequency and proportion of nine categories of adverse childhood experiences (ACEs) in the overall sample and by groups
Drinking/substance misuse at home | 148 (70) | 117 (80) | 65 (77) |
Domestic Violence | 109 (52) | 83 (57) | 58 (68) |
Physical Neglect | 98 (46) | 86 (59) | 38 (45) |
Emotional Neglect | 97 (46) | 86 (59) | 37 (44) |
Physical Abuse | 42 (20) | 35 (24) | 18 (21) |
Parental Incarceration | 38 (18) | 31 (21) | 21 (25) |
Emotional/Verbal Abuse | 23 (11) | 18 (12) | 9 (11) |
Suicide attempt/mentally ill family | 22 (10) | 12 (8) | 15 (18) |
Sexual Abuse | 22 (10) | 18 (12) | 13 (15) |
Total ACEs Scores |
Zero | 31 (15) | 10 (7) | 5 (6) |
One to three | 97 (46) | 66 (45) | 42 (49) |
Four or more | 83 (39) | 71 (48) | 38 (45) |
ACEs Categories in the Total sample
The most common ACEs in the entire sample was exposure to drinking/substance misuse at home (70%). Other common ACEs included domestic violence (52%), physical neglect (46%), and emotional neglect (46%) – (Table
2). In the overall sample, logistic regression results (Table
3) show that age and being a male were associated with an increased risk of exposure to domestic violence, being a victim of sexual abuse and having a family member who was mentally ill or had attempted suicide. However, these results were no longer significant when the Benjamini-Hochberg corrections were applied.
Table 3
Logistic regressions predicting adverse childhood experiences (ACEs) categories from demographic variables in the overall sample
Model 1 |
Drinking/Substance misuse at home | 1.02 (.95, 1.09) | 1.30 (.67, 2.53) | 1.35 (.68, 2.69) |
Model 2 |
Domestic Violence | 1.09a (1.02, 1.17) | 2.37a (1.24, 4.53) | 1.41 (.71, 2.78) |
Model 3 |
Emotional Neglect | 1.00 (.94, 1.06) | .73 (.39, 1.36) | .92 (.48, 1.76) |
Model 4 |
Physical Neglect | 1.00 (.94, 1.07) | .74 (.40, 1.38) | .94 (.49, 1.80) |
Model 5 |
Physical Abuse | 1.01 (.93, 1.09) | 1.38 (.61, 3.14) | .49 (.23, 1.04) |
Model 6 |
Parental Incarceration | 1.02 (.94, 1.10) | 1.51 (.64, 3.60) | 1.67 (.65, 4.26) |
Model 7 |
Suicide attempt/mentally ill family members | 1.14a (1.02, 1.27) | 1.41 (.44, 4.50) | 1.91 (.52, 6.88) |
Model 8 |
Sexual Abuse | 1.15a (1.03, 1.28) | .37a (.14, .98) | 1.29 (.41, 4.10) |
Model 9 |
Emotional/Verbal Abuse | 1.02 (.92, 1.12) | .88 (.33, 2.34) | .63 (.24, 1.65) |
ACEs Categories and Child Protection System Involvement
Phi coefficient tests show that drinking/substance misuse at home (Φ = .31, p < .001, Hochberg threshold = .005), emotional neglect (Φ = .38, p < .001, Hochberg threshold = .005) and physical neglect (Φ = .37, p < .001, Hochberg threshold = .005) were positively associated with child protection system involvement. These associations remained significant even after applying the Benjamini-Hochberg corrections. However, domestic violence (Φ = .31, p = .034, Hochberg threshold = .015) and physical abuse (Φ = .15, p = .031, Hochberg threshold = .015) were no longer significant once corrections for multiple comparisons were applied. ACEs including parental incarceration (p = .078), suicide attempt/mentally ill family members (p = .104), sexual abuse (p = .192) and emotional abuse (p = .345) were not associated with child protection system involvement.
ACEs Categories and Justice System Involvement
For those aged 10 and above, documented exposure to domestic violence was positively associated with justice system involvement (Φ = .28, p = .001, Hochberg threshold = .005). However, the relationship between parental incarceration and justice system involvement was no longer significant once corrections were applied (Φ = .17, p = .046, Hochberg threshold = .010). Drinking/substance misuse at home (p = .051), suicide attempt/mentally ill family members (p = .066), sexual abuse (p = .434), emotional neglect (p = .476), physical neglect (p = .560), emotional abuse (p = .740) and physical abuse (p = .741) were not significantly associated with justice system involvement.
Associated Stressors
Other stressors in life not measured by the ACEs questionnaire were reported in Table
4. Almost half (43%) of the total sample disengaged from school. Other less common stressors recorded were transiency, documented victims of bullying, sustained a traumatic brain injury and homelessness.
Table 4
Frequency of associated stressors in the overall sample and the corresponding mean adverse childhood experiences (ACEs)
Disengagement from school | 91 (43) | 3.3 (1.8) |
Transiency | 40 (19) | 3.3 (1.8) |
Documented victims of bullying | 26 (12) | 2.5 (1.9) |
Sustained severe traumatic brain injury | 19 (9) | 3.2 (1.3) |
Homelessness | 11 (5) | 3.8 (1.7) |
Comorbid Conditions
The total number of comorbid conditions across all participants ranged from 0 to 8 (mean = 2.3, SD = 1.7) – See Table
5. Higher total ACEs scores in the overall sample were associated with an increased number of comorbidities, r(211) = .27,
p < .001. Specifically, those who had comorbidities such as substance use disorder r(211) = .19,
p = .006, Hochberg threshold = .015, attachment disorder r(211) = .24,
p = .001, Hochberg threshold = .010, and PTSD r(211) = .26,
p < .001, Hochberg threshold = .005, also had higher ACEs scores. Conversely, individuals with FASD who also had ID reported lower ACEs scores, r(211) = −.17,
p = .012, Hochberg threshold = .020. These correlations remained statistically significant even after the Benjamini-Hochberg corrections were applied.
Table 5
Mean adverse childhood experiences (ACEs) for the total sample by different comorbidities
ADHD | 89 (39) | 3.0 (2.0) |
Sleep disorder | 77 (34) | 3.0 (1.9) |
Attachment disorder | 65 (29) | 3.7 (1.7) |
Anxiety disorder | 61 (27) | 3.2 (1.9) |
Hearing impairment | 57 (25) | 2.9 (2.0) |
Post-traumatic stress disorder | 55 (24) | 3.9 (1.7) |
Intellectual disability | 48 (21) | 2.3 (1.8) |
Substance use disorder | 35 (15) | 3.6 (1.8) |
Conduct disorder | 27 (12) | 2.9 (1.8) |
Depression | 27 (12) | 3.5 (1.8) |
0 to 2 diagnoses | 127 (60) | 2.4 (1.8) |
3 to 5 diagnoses | 76 (36) | 3.3 (1.8) |
6 to 8 diagnoses | 8 (4) | 4.5 (1.6) |
Conclusions
Numerous studies have investigated the relationship between PAE and early life trauma. However, limited research has examined the ACEs profiles in individuals with FASD. Our study conducted a comprehensive examination of ACEs, associated stressors and comorbidities documented in children and youth with FASD in Australia. High rates of life adversity in this clinical population were associated with an increased number of comorbidities and negative outcomes, i.e., child protection/justice system engagement. Associated stressors (e.g., school disengagement, transiency, bullying, homelessness, traumatic brain injury) not captured by the ACEs questionnaire were also identified in this study. Overall, experiences of trauma are rarely an isolated event. Our results highlight a critical need for enhanced access to early diagnosis/services for children with FASD, particularly in higher-risk populations such as Aboriginal communities and those involved with child protection and/or the justice system to reduce the adverse impact of ACEs and the development of comorbid conditions. At a service provision level, it is crucial that clinicians/educators/child protection/justice workers routinely screen for, discuss, and provide psychoeducation around ACEs to promote better outcomes in vulnerable children (Fogliani, 2019).
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