Original Article
DOI: 10.15586/jptcp.v27i3.718
1Department of Pediatrics & Child Health, University of Manitoba, Winnipeg, Manitoba, Canada
2Manitoba FASD Centre/MB FASD Network, Winnipeg, Manitoba, Canada
3Department of Clinical Health Psychology, University of Manitoba, Winnipeg, Manitoba, Canada
4Program of Genetics and Metabolism, Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, Manitoba, Canada
Submitted: 14 June 2020. Accepted: 20 July 2020. Published: 27 July 2020.
ABSTRACT
The assessment of preschoolers with prenatal alcohol exposure (PAE) is challenging for many diagnostic teams and clinicians. The 2016 Canadian Fetal Alcohol Spectrum Disorder (FASD) diagnostic guidelines describe the assessments recommended for individuals with PAE in various age groups. Interpretation of brain domains constituting global impairment in preschoolers is not well described in the literature, and there has been clinical reluctance to consider the interpretation of clinical assessments as definitively diagnostic in this age group. This study describes the results of 10-year retrospective clinical data of over 300 preschoolers with PAE referred to the Manitoba FASD Centre for assessment of FASD. Preschoolers who met the criteria for a diagnosis of FASD showed significantly greater global developmental impairment, compared with those with PAE alone. They also demonstrated poorer receptive and expressive language abilities when compared with preschoolers who were not diagnosed. Preschoolers with FASD were rated as having more difficulties with executive functioning skills and adaptive functioning skills, compared to their counterparts. Significant deficits were found in fine-motor, visual-motor, and components of gross-motor skills. Importantly, significant sensory processing differences are particularly evident in preschoolers and are important in understanding behavior and in intervention planning. Together, standardized assessment of motor and sensory processing skills, with a comprehensive assessment of language, are significant predictors of FASD diagnosis for preschoolers with PAE.
Keywords: Canadian; diagnostic assessment; Fetal Alcohol Spectrum Disorder (FASD); prenatal alcohol exposure preschool child
INTRODUCTION
Fetal Alcohol Spectrum Disorder (FASD), a diagnostic term, describes the physical and neurocognitive effects of prenatal alcohol exposure (PAE) 1. Although there is extensive research on school-age children and adolescents, there is a limited body of research describing the assessment of neurobehavioral patterns seen in preschoolers with PAE. While the impact of PAE on preschool developmental domains can be challenging to assess, quantifiable clinical changes have been observed, and research has shown that many of these changes worsen over time 2-4. Early intervention and diagnosis are important in reducing the effects of FASD on children and ameliorating developmental patterns as the children age. The assessment of preschoolers with PAE should be a priority to support understanding of the current behavior and development, identify needs for supportive services and therapies, and support positive long-term outcomes.
BACKGROUND
Clinicians are often asked to assess preschoolers with PAE with developmental delays and challenging behaviors; however, clinicians and researchers have expressed several concerns around diagnosing FASD in the preschool population. Concerns include risk determination based on PAE alone, neuroplasticity, and the potential for the developmental impacts of both ameliorating factors and postnatal risk factors. The sensitivity of preschool assessments to later functioning is often cited clinically. Clinicians may express concerns about determining risk based on the level of confirmation of PAE, and often central to these concerns is the discomfort of attributing multiple factors to PAE alone 5.
Diagnostic assessment of preschoolers with PAE should consider differences in brain development as well as the interpretation and availability of standardized assessment tools. Brain development of infants and preschoolers is typically highlighted by thinner cortical structures, reduced cortical volume, and reduced myelination of white matter 6, 7. PAE negatively impacts neuronal migration and its genetic signaling, with direct consequences on the development of gray and white matter integrity, as well as changes in neurochemistry and intrinsic networks of connectivity 8-11. The impact of these neurological changes influences multiple brain domains of functioning, including cognitive, adaptive, motor, language, and sensory processing, which also potentially impact the assessment of brain structure and growth 10, 11. Neuroplasticity and postnatal development may ameliorate some of the negative effects of PAE. However, these studies suggest changes to neural formation as a result of PAE, which are apparent early in life, have a lasting impact, and may be sensitive indicators of that exposure 11. Therefore, clinicians should be attentive to children at risk based on PAE and refer them for early neurobehavioral assessment.
There are relevant concerns regarding preschool assessment practices required to describe the multiple brain domains defined in current guidelines, as well as in the attribution of difficulties to PAE (4, 12–14). In 2016, a Canadian updated set of guidelines were published to describe the multidisciplinary diagnosis of FASD, which acknowledged differences in preschool assessment while recognizing the limitations in existing evidence 1. The Canadian guidelines define both functional and structural brain domains to be assessed in the multidisciplinary diagnostic evaluation, including motor skills; neuroanatomy/neurophysiology; cognition; language; academic achievement; memory; attention; executive functioning, including impulse control and hyperactivity; affect regulation; and adaptive behavior, social skills, or social communication 1. An FASD diagnosis may be made when there is severe impairment (typically defined as below 2 standard deviations (SD) on standardized testing) in three or more of the neurodevelopmental domains in the presence of PAE and when other neurodevelopmental disorders are excluded 1.
The multidisciplinary diagnostic team examines sentinel facial features (SFF) and other dysmorphology, including microcephaly. Differential diagnosis is specifically considered and may include diagnostic explanations related to genetics or the social and environmental factors of the child. Young children may not meet FASD diagnostic criteria because the currently used tests may not be sensitive to these differences at young ages, including variability in learning profiles or subtler neurobehavioral problems individually, and because the team may attribute the children’s difficulties to other explanations such as trauma or attachment difficulties 2.
Therefore, a diagnosis in preschool children is often deferred 15. A deferral often means that preschoolers and their families are not able to access early intervention and supports specific to PAE. Despite concerns about assessing neurodevelopment in preschoolers, some research has shown that children who have an FASD diagnosis display neurobehavioral impairments that are consistent with deficits found in older children and adolescents with FASD 4. Furthermore, the neurobehavioral impairments displayed by children with PAE often persist into adulthood, particularly in the absence of informed early intervention and supports 4. Taken together, these observations support early identification and comprehensive assessment of preschoolers with PAE to advocate for appropriate early intervention and thereby improve outcomes.
Hypothesis and Objectives
The purpose of this study is to provide clinical evidence for conducting diagnostic assessments of preschool children for FASD by identifying clinical predictive features that support early diagnosis of FASD and offering a clinically experienced interpretation from a multidisciplinary team over the last decade. The main objectives of this study are to: (1) describe data on preschool multidisciplinary assessment of preschool children with PAE seen through the Manitoba FASD Centre between 2005 and 2016; (2) describe characteristics in the brain domains considered for an FASD diagnosis; (3) model predictive characteristics of FASD in preschoolers; and (4) propose improved clinical practices for the assessment of preschoolers with PAE.
METHODS
Design
This study is a retrospective chart review of 340 preschool assessment data on children aged 3–6 years seen at the Manitoba FASD Centre between 2005 and 2016. Children were assessed by a multidisciplinary team that consisted of a developmental pediatrician, geneticist, occupational therapist, speech-language pathologist, and psychologist.
Retrospective data from the multidisciplinary assessments of these children were collected, including demographic data, multidisciplinary assessment data (language, motor, sensory, behavioral, and developmental assessments), diagnostic data, and comorbidities. Some missing data on early assessments are present for different domains, as earlier assessments completed prior to the Canadian guidelines may have included different subtest combinations, resulting in slightly different total numbers. In the case of repeat assessments, the most recent data were used in this analysis, making 332 the total number of complete assessments.
Population
The study data came from children referred for assessment at the Manitoba FASD Centre and provincial network, which is the central diagnostic program serving the provincial population in Manitoba, Canada. It was established in 1999 and works with diagnostic coordinators throughout the province using a centralized coordinated model. The Manitoba FASD Centre has assessed over 4000 children since its inception, at a rate of approximately 200–240 assessments per year. Consistently since 2005, approximately 60% of the children seen at the Manitoba FASD Centre are in agency care, 30% are with birth families, and 10% have been adopted. The Manitoba FASD Centre has a screening and intake process, which carefully considers PAE, consent, the timing of the assessment, the social situation, and the neurodevelopmental difficulties. In this study, all children assessed had confirmed PAE in keeping with the recommendations of the Canadian diagnostic guidelines 1.
Preschoolers were diagnosed using Canadian diagnostic guideline nomenclature of FASD with or without SFF 1. In addition, all children received a 4-digit diagnostic code following Astley’s extensively validated 4-digit code, first established with the Washington Diagnostic & Prevention Network in 1997, and currently released in 2004 with multiple validations published since 16, 17. This code describes the physical, facial, and neurocognitive features, and a measure of prenatal alcohol confirmation using a 4-digit series in the order of: growth, face, brain, and alcohol. Each characteristic is ranked on a 5-point Likert Scale. Team members of the Manitoba FASD Centre have over 20 years’ experience in its use.
Clinical Tools Used in Assessments
Developmental Scales
Gesell Developmental Schedules. Preschoolers are clinically assessed by developmental pediatricians using the Revised Gesell Developmental Schedules 18. These clinical scales measure developmental status of infants and preschoolers up to 72 months. The scales provide developmental quotients (DQs) in cognitive, language, and motor domains, from which a DQ of developmental age to chronologic age can be calculated. The standardization sample is weak although newer revisions have improved the standardization.
Language
Clinical Evaluation of Language Fundamentals Preschool-2nd Edition (CELF-P2). The CELF-P2 is a standardized assessment tool used to identify and diagnose language deficits in children aged 3–6 years 19. Normative data for this test are derived from the 2000 U.S. Census population and includes preschoolers with developmental delays as well as those who have received specialized clinical services. Scoring categories include the “Core Language Score,” which measures general language ability and determines a child’s overall language performance, and a second category, including four “Language Index Scores,” which provides more comprehensive information on language and communication, including receptive language, expressive language, language content, and language structure. These indices are calculated using different combinations of the seven different subtest scores, which include sentence structure, word structure, expressive vocabulary, concepts and following directions, basic concepts, recalling sentences, and word classes (both receptive and expressive).
Preschool Language Scale-4th Edition (PLS-4). The PLS-4 is a standardized tool used to identify children from birth to 6 years of age who have a language deficit 20. Normative data are also derived from the 2000 U.S. Census population, including a representative sample of preschoolers with developmental delays. The PLS-4 reports two subscales: auditory comprehension (AC) and expressive communication (EC). A total test score is derived by combining the AC and EC subscales.
The severity of the language deficit for both the PLS-4 and the CELF-P2 was determined using the following scale: severe (standard score <70); moderate (standard scores between 71 and 77); mild (standard scores between 78 and 85); average (standard scores between 86 and 114); and above average (standard scores >114).
Sensory Processing
Sensory Profile (SP). The SP is a standardized tool designed to evaluate children’s sensory processing skills and how it impacts their participation in meaningful and daily tasks 21. The SP assesses for sensory processing difficulties in young children, in combination with other assessments in the early diagnosis of children affected by PAE. Normative data on 1037 children include smaller samples of children with developmental disabilities. The SP is a clinically based caregiver questionnaire where the caregiver rates the frequency of the child’s behavior from “never” (0% of the time), “seldom” (about 25% of the time), “occasionally” (about 50% of the time), “frequently” (about 75% of the time), to “always” (100% of the time). Results from the ratings are put into a classification system, which organizes the scores into three groups: Typical Performance (score at or above 1 SD below the mean), Probable Difference (scores at or above 2 SDs below the mean but lower than 1 SD below the mean), and Definite Difference (scores below 2 SDs below the mean). Scores are reported in the data per section and as an overall total score. It is possible to have a Definite Difference score in one area but a total score in the Probable Difference range.
The Short Sensory Profile (SSP) is a 38-item caregiver questionnaire designed for use in screening and research protocols 21. In the preschool years, the SSP can also be completed by daycare and preschool staff to provide information on sensory processing skills in different environments. A rigorous process was used to develop the SSP from the full form SP using a data sample of 117 children, both with typical development and neurodevelopmental disabilities.
Motor Assessments
Movement Assessment Battery for Children – 2 (MABC-2). The MABC-2 is a standardized tool that assists in identifying children who have motor function impairment 22. The MABC-2 reports a standard score for three components: Manual Dexterity, Aiming & Catching, and Balance, as well as a Total Test Score, with a mean standard score of 10 and standard deviation of 3. Interpretation of individual component scores and the total test score is critical and may guide intervention planning.
The Beery–Buktenica Test of Visual-Motor Integration (Beery VMI). The Beery VMI is a standardized tool that assesses visual-motor integration abilities in children 23. The Visual Perception (VP) and Motor Coordination (MC) subtests break down two important building blocks for visual motor integration (visual vs. motor functioning). For standardized administration, the Beery VMI is first followed by the VP, and finally the MC. It uses a mean standard score of 100 and a standard deviation of 15.
Executive Functioning
The Behavior Rating Inventory of Executive Function – Preschool Version (BRIEF-P). The BRIEF-P is used to measure executive functioning 24. The BRIEF-P converts caregiver ratings into one global composite score, and three broad indexes: (a) Inhibitory Self-Control; (b) Flexibility; and (c) Emergent Metacognition. Scores are presented as T scores, where T scores ≥70 are indicative of severe impairment.
Adaptive Assessment
The Adaptive Behavior Assessment System, Third Edition (ABAS-3). The ABAS-3 is a caregiverrated measure used to assess adaptive behaviors that are age-appropriate behaviors necessary for meeting the demands of everyday living 25. The ratings from the ABAS-3 create an overall general adaptive skills score (General Adaptive composite; GAC), and scores for each adaptive domain: (a) conceptual skills; (b) social skills; and (c) practical skills. Standard scores <70 are indicative of severe impairment.
Statistical Analysis
Descriptive statistical and multivariate analyses for prediction modeling were conducted with the support of the Centre for Healthcare Innovation (CHI) at the University of Manitoba. Independent sample t-tests were used to calculate differences in assessment results between preschoolers with and without FASD. For prediction analysis, missing data were predicted using regression models, with the variable in question being regressed upon every other variable in the data in an iterative process to create informed estimates of the predicted value. Following this, the separate imputed datasets were analyzed, and the results were pooled into one inference. Lastly, CHI created multivariate analyses of the data by creating a pooled logistic regression model, with FASD as the dependent variable, and multiple predictors. Results at P < 0.05 were considered statistically significant.
Ethics approval was received from the University of Manitoba Health Research Ethics Board #HS19754 (H2016:195).
RESULTS
Demographics and Diagnosis
There was a 1.4 male:1 female ratio in the data. An FASD diagnosis was made in 48% of males and 49% of females. The prenatal use of other substances was common in 91% of the total preschool group with PAE. Most preschoolers resided with foster families of nonkinship care at the time of the assessment (77%). An equal number of preschoolers resided with biological families (11%) and foster families of kinship care (11%), and about 1% of preschoolers lived with adoptive families.
Approximately, half of the preschoolers with PAE (51%) met clinical criteria for a diagnosis of FASD, 6% of children were diagnosed with FASD with SFF, and 43% of children were diagnosed with FASD without SFF (Figure 1).
FIG 1. FASD Diagnosis for Total Sample (n = 340). SFF = sentinel facial features; w/ = with; w/o = without; FASD = Fetal Alcohol Spectrum Disorder.
Table 1 shows that most preschoolers did not meet the growth criteria using the 4-digit code, unless they were diagnosed with FASD (4.1%). 15.7% of preschoolers with PAE met either level 3 or 4 facial criteria, and of this group, the majority (87% of those with face coded 3 or 4) met criteria for FASD. 52.1% of preschoolers with PAE met either level 3 or 4 brain criteria, and of this group, the majority (86.4% with face coded 3 or 4) met criteria for FASD. PAE was confirmed in all children with an equal distribution between those who met the criteria for a diagnosis and those who did not.
TABLE 1. FASD diagnosis by 4-Digit Code: PAE No FASD Versus FASD (% Total).
| Code | Growth | Face | Brain | Alcohol | ||||
| PAE no FASD (% Total) | FASD (% Total) | PAE no FASD* (% Total) | FASD (% Total) | PAE no FASD (% Total) | FASD (% Total) | PAE no FASD (% Total) | FASD (% Total) | |
| 1 | 158 (46.4) | 134 (39.4) | 133 (39.2) | 88 (25.9) | 17 (5.0) | 3 (0.9) | 1 (0.3) | 0 (0.0) |
| 2 | 4 (1.2) | 12 (3.5) | 27 (8.0) | 38 (11.2) | 127 (37.4) | 16 (4.7) | 7 (2.1) | 3 (0.9) |
| 3 | 3 (0.9) | 12 (3.5) | 5 (1.5) | 21 (6.2) | 21 (6.2) | 121 (35.6) | 83 (24.4) | 75 (22.1) |
| 4 | 3 (0.9) | 14 (4.1) | 2 (0.6) | 25 (7.4) | 3 (0.9) | 32 (9.4) | 77 (22.6) | 94 (27.6) |
| Subtotals | 168 (49.4) | 172 (50.6) | 167 (49.3) | 172 (50.7) | 168 (49.4) | 172 (50.6) | 168 (49.4) | 172 (50.7) |
| Totals | 340 | 339 | 340 | 340 | ||||
*N=339, as the face code could not be calculated for one patient with PAE due to craniofacial difference.
PAE = prenatal alcohol exposure; FASD = Fetal alcohol Spectrum Disorder.
Physical Features
Figure 2 shows that microcephaly was found in 10.6% of the clinical preschool population with PAE. Of these preschoolers with microcephaly, over half (57.6%) also had all three SFF. Of the group with both microcephaly and all three SFF, 94.7% also met the criteria for an FASD diagnosis.
FIG 2. FASD Diagnosis by the Presence of SFF and Microcephaly (Head Circumference – HC < 3rd Percentile). PF = palpebral fissures; FASD = Fetal Alcohol Spectrum Disorder; HC = head circumference.
Neurodevelopmental Assessments
Developmental Scales
Figure 3 shows that preschoolers with PAE and FASD have below average DQs. There was a significant difference in cognitive DQ for preschoolers with (M = 82.89, SD = 13.57) and without (M = 91.20, SD = 10.02) FASD; t(267.15) = 6.06, P < 0.001. Similarly, the mean language DQ was significantly lower in preschoolers with (M = 79.90, SD = 16.10) than without (M =89.83, SD = 13.15) FASD; t(144.42) = 4.55, P < 0.001. Motor scores also showed lower DQs in the preschoolers with FASD (M = 85.74, SD = 13.07), compared with those with PAE alone (M = 95.12, SD = 8.22); t(83.12) = 4.94, P < 0.001. Finally, the mean Global DQ (reflecting the combination of cognitive, language, and motor DQs) was significantly lower in preschoolers with (M = 82.78, SD = 13.54) than without (M = 91.04, SD = 10.15) FASD; t(267.35) = 6.01, P < 0.001.
FIG 3. Global DQ by FASD Diagnostic Status. DQ = developmental quotient; FASD = Fetal Alcohol Spectrum Disorder. The black line represents the mean score of the measure. The error bars represent the SD.
Language Scales
The mean Auditory Scores for preschoolers with FASD (M = 73.41, SD = 13.34) were lower than those without (M = 83.89, SD = 13.65), t(77.00) = 3.45, P < 0.001 (Figure 4). Preschoolers with FASD (M = 74.42, SD = 11.81) also obtained significantly lower Expressive Scores than preschoolers without FASD (M = 82.58, SD = 13.53), t(72.00) = 2.77, P = 0.007. The mean Total Language Score was also lower for preschoolers with (M = 71.47, SD = 12.58) than without (M = 81.06, SD = 14.32) FASD, t(71.00) = 3.04, P < 0.001.
FIG 4. Distribution of PLS-4 Scale Scores by FASD Diagnostic Status. The black line represents the mean score of the measure. The error bars represent the standard deviation. PLS-4 = Preschool Language Scale-4th Edition; FASD = Fetal Alcohol Spectrum Disorder.
To look more closely at language function, Figure 5 displays the distribution of CELF-P2 scale scores by FASD diagnostic status. Overall, the mean Core Language Index Score for those with FASD (M = 77.69, SD =14.95) was significantly lower than those without FASD (M = 86.51, SD = 14.18); t(160.00) = 3.79, P < 0.001. Similarly, there were significant differences in the Receptive Language Index Score for preschoolers with (M = 78.60, SD = 14.34) and without (M = 86.91, SD = 13.90) FASD; t(142.00) = 3.41, P < 0.001. The Expressive Language Index Score also was significantly different between those with (M = 76.82, SD = 14.75) and without (M = 84.78, SD = 14.04) FASD; t(149.00) = 3.31, P = 0.001. Preschoolers diagnosed with FASD also showed lower scores on language content (t142.00= 3.17, P = 0.002) and structure (t148.00 = 3.67, P < 0.001) than those not diagnosed with FASD.
FIG 5. Distribution of Core Language and Index Scores for the CELF-P2 Scales by FASD Diagnostic Status. The black line represents the mean score of the measure. The error bars represent the standard deviation. CELF-P2 = Clinical Evaluation of Language Fundamentals Preschool-2nd Edition; FASD = Fetal Alcohol Spectrum Disorder.
Motor Assessment
The total MABC-2 scores obtained by preschoolers with FASD (M = 6.58, SD = 2.84) were significantly lower than those without FASD (M = 8.44, SD = 2.95), t(151.00) = 3.86, P < 0.001 (Figure 6). There were also significant group differences for the Manual Dexterity score (t159.00 = 3.52, P < 0.001) and the Balance score (t155.00 = 2.80, P = 0.006), with preschoolers with FASD obtaining lower scores (M = 5.77, SD = 2.65; M = 7.49, SD = 2.72, respectively) than their counterparts (M = 7.49, SD = 3.28; M = 8.90, SD = 3.26, respectively). The Aiming and Catching score was similar for preschoolers with (M = 9.57, SD = 3.25) and without (M = 10.44, SD = 2.91) FASD, t(157.00) = 1.75, P = 0.082.
FIG 6. Distribution of MABC-2 Scores by FASD Diagnostic Status. MABC-2 = Movement Assessment Battery for Children-2nd Edition; FASD = Fetal Alcohol Spectrum Disorder. The black line represents the mean score of the measure. The error bars represent the standard deviation.
Figure 7 shows that mean VMI score for preschoolers with FASD (M = 91.96, SD = 12.24) was significantly lower compared with those with PAE alone (M = 97.51, SD = 11.63), t(172.00) = 3.06, P = 0.003. The mean VP subtest score was also significantly lower for those with FASD (M = 85.10, SD = 17.92), compared to those without FASD (M = 99.92, SD = 17.26), t(68.00) = 3.51, P < 0.001. Group difference across mean MC subtest score between those with (M = 82.58, SD = 10.63) and without (M = 86.76, SD = 14.24) FASD were nonsignificant, t(66.00) = 1.35, P = 0.182.
FIG 7. Distribution of Beery VMI Scales by FASD Diagnostic Status. MC = motor coordination; VMI = visual-motor integration; VP = visual perception; Beery VMI = Beery–Buktenica Test of Visual Motor-Integration; FASD = Fetal Alcohol Spectrum Disorder. The black line represents the mean score of the measure. The error bars represent the standard deviation.
Sensory Processing
Figure 8 displays the risk of receiving an FASD diagnosis by SSP total score. Small cell numbers precluded in-depth analysis of sensory patterns and responses. However, there was a large difference in the number of children observed to demonstrate typical sensory response patterns with only 24% of preschoolers with FASD showing typical response patterns, compared to 76% of preschoolers with PAE. Within the category of “definite differences,” there was a more even split with 51% of preschoolers with FASD versus 49% of those with PAE alone, clearly showing different response patterns.
FIG 8. Risk of FASD Diagnosis by SSP Total Score. NA = score not available; SSP = Short Sensory Profile; FASD = Fetal Alcohol Spectrum Disorder.
Behavior: Executive Functioning
Figure 9 shows that all preschoolers with PAE had challenges applying executive functioning skills, irrespective of an FASD diagnosis. There were significant differences in the mean Global Index score between preschoolers with (M = 79.46, SD = 13.94) and without (M = 73.47, SD = 16.17) FASD, t(158.80) = –2.58, P = 0.011. Preschoolers with FASD had significantly higher scores on the Metacognition Index (M = 78.45, SD = 14.16), compared to their counterparts (M = 70.88, SD = 15.89), t(169.00) = –3.30, P = 0.001. The Inhibitory Index (t169.00 = –1.80, P = 0.074) and the Flexibility Index (t155.16 = –1.97, P = 0.051) scores were comparable across groups.
FIG 9. Distribution of Mean T-scores Across BRIEF-P Scales by FASD Diagnostic Status. The black line represents the mean score of the measure. The error bars represent the standard deviation. BRIEF-P = Behavior Rating Inventory of Executive Functioning – Preschool; FASD = Fetal Alcohol Spectrum Disorder.
Adaptive Functioning
Figure 10 shows that the GAC reported for preschool children with FASD (M = 67.32, SD = 12.74) was significantly lower than those without FASD (M = 75.34, SD =13.75), t(94.00) = 2.80, P = 0.006. Similar patterns were noted for preschoolers with FASD across the Conceptual (t96.00 = 2.89, P = 0.005) and Practical (t96.00 = 2.57, P = 0.012) skill domains, with preschoolers with FASD (M = 69.03, SD = 13.39; M = 66.46, SD = 14.02, respectively) obtaining lower scores than preschoolers with PAE alone (M = 77.46, SD = 14.35; M = 73.84, SD = 13.65, respectively). Reported social skills were found to be comparable between preschoolers with (M = 75.48, SD = 15.80) and without (M = 79.00, SD = 13.97) FASD, t(99.00) = 1.18, P = 0.242.
Fig 10. Distribution of Scores on the ABAS-3 Scales by FASD Diagnostic Status. The black line represents the mean score of the measure. The error bars represent the standard deviation. ABAS-3 = Adaptive Behavior Assessment System, Third Edition; FASD = Fetal Alcohol Spectrum Disorder; PAE = prenatal alcohol exposure.
Predictive multivariate regression analysis. Table 2 shows the results of pooled multivariate analysis modeling of domain variables predictive of FASD diagnosis in preschoolers. Motor functioning (Total MABC-2 score), language skills (Core Language Score; CELF-P2), and the presence of sensory processing differences (SSP Total) were found to be significant predictors of FASD diagnosis. Significant strength reflected in the sensory variable was also found, supporting global sensory processing differences as a particularly important predictor of FASD diagnosis in preschoolers.
Table 2. Pooled multivariate analyses: significant factors upon mutual adjustment.
| Odds ratio (95% CI) | df | P | nmis | |
| Total MABC2 score | 0.88 (0.76, 1.0) | 26.79 | 0.067 | 80 |
| Core Language score | 0.95 (0.93, 0.98) | 62.90 | <0.001 | 63 |
| Sensory 2 | 3.13 (1.62, 6.05) | 194.63 | <0.001 | NA |
df = degrees of freedom; nmis = number of missing observations.
Source: Adapted from FASD prediction models from CHI.
DISCUSSION
This study presents data underscoring the importance of early diagnostic multidisciplinary assessment of preschoolers with PAE. It shows that in combination, clinically significant deficits in communication, motor skills, and sensory processing are predictive of a diagnosis of FASD and can, therefore, be clinically used to support early diagnosis in the preschool period. Clinicians can then improve management by offering areas for targeted intervention to improve outcomes from an early age and reduce the burden of care on families.
In Manitoba, preschoolers make up 19% of the children seen for the assessment of FASD. Of these preschoolers, 23% received a diagnosis of FASD with SFF, 22% received a diagnosis of FASD without facial features, and 55% did not receive an FASD diagnosis. Commonest concerns prompting referral of preschoolers with PAE in Manitoba included dysregulation (77%) and developmental delays (57%). Brain domain impairments that were found to be the most prevalent in preschoolers diagnosed with FASD were executive functioning (76%), attention (72%), motor (62%), adaptive (55%), and language (52%). Impairments in the motor domain distinguished those preschoolers who met the criteria for a diagnosis of FASD from those who did not. Among preschoolers who were not diagnosed, only 21% demonstrated impairment in attention, and 13% had executive functioning impairments. Only children who met the criteria for a diagnosis showed significant impairments in the adaptive domain. Children with an at-risk designation tended to have slightly higher rates of impairments in adaptive functioning (17%) and executive functioning (17%), and slightly lower impairment in attention (17%).
The following discussion reflects the results of our study organized by brain domains:
Measurement of occipitofrontal diameter plotted on standardized head circumference curves is a good proxy measure of brain growth and volume. Microcephaly was originally described as a feature of Fetal Alcohol Syndrome (FAS) by Jones and Smith 26, and Lemoine et al. 27. Microcephaly was seen in approximately 10% of our sample of preschoolers with PAE. Of this group, 83% met criteria for FASD, making microcephaly a clinically significant early finding. This also means that most preschoolers have normal head circumferences and show impairments in other neurobehavioral domains, necessitating a comprehensive multidisciplinary assessment.
Our clinical data show a correlation between sensory processing differences with FASD diagnosis; 83% of preschoolers seen for an FASD assessment in Manitoba were found to have significant differences in sensory sensitivities and processing, while only 58% of at-risk preschoolers and 38% of preschoolers with no FASD diagnosis showed significant differences. Sensory processing differences in visual, auditory, tactile, auditory filtering, under-responsiveness to sensory information, and sensation-seeking behaviors have been shown to be clinically significant in children with FASD (33–36). The neurologic correlates of sensory processing behaviors relate to white matter development, which is sensitive to PAE (37–40). In a therapeutic environment, understanding sensory processing patterns can contribute to a better understanding of unregulated behavior and foster the development of self-regulation and adaptive behaviors in toddlers 41. Currently, the Canadian guidelines do not include sensory processing as a brain domain for the assessment of FASD. Our results support the inclusion of sensory processing in the preschool battery of assessments in the Canadian guidelines for FASD diagnosis as an independent and sensitive measure, reflecting neurological integrity in young children informing a comprehensive and developmentally appropriate assessment profile.
Other Clinical Considerations
Clinical confidence in the assessment of preschoolers is affected by clinician experience and described patterns in large cohorts of clinical samples 52. This study describes a large, 10-year cohort of children clinically assessed by a multidisciplinary team experienced in the assessment of children with PAE and in FASD diagnosis. All children seen in this clinic have undergone rigorous confirmation of PAE and have presented with neurobehavioral concerns at the time of assessment. In our cohort, approximately half of the children aged 3–6 years met the criteria for a diagnosis of FASD. In preschoolers with PAE, microcephaly and all three SFF are sensitive signs distinguishing those who meet the criteria for an FASD diagnosis.
In addition to the consideration of clinically significant domain scores in preschoolers, it is important not to dismiss scores that do not reach clinical significance but are informative for intervention. Our study found that functional domains of global development, language, motor skills, executive functioning, and adaptive functioning were consistently lower for children with PAE than those without PAE. Furthermore, when comparing children with PAE who did not receive an FASD diagnosis to those who did receive a FASD diagnosis, those with FASD consistently showed poorer functioning. This finding suggests either a grading of effects related to the specifics of PAE (such as dose or timing) or preclinical effects in at-risk children supporting longitudinal follow-up.
Elevations in scores that do not meet clinical thresholds are still important to inform early intervention and longitudinal monitoring, as many of these factors are associated with a future diagnosis of FASD. Almost half of the children that had a probable difference and a definite difference are at risk of being diagnosed with FASD in the future. Even among predictive factors, such as sensory processing, lower scores were of significance, and about 30% of those who had a positive sensory score were at risk of receiving an FASD diagnosis in the future.
Limitations
This study is a 10-year retrospective review of clinical data and not a prospective study of developmental outcomes of PAE in preschoolers. Our results are therefore limited by the clinical data available, including missing data due to assessment and guideline changes. The clinical data do not include imaging or genetic findings, which would be important additional investigations for future study. Although our overall sample size was large, some of the nonsignificant findings may be due to low numbers in specific variables (low power). A larger sample size with more detailed data collected would allow for analysis of the impacts of multiple exposures and adverse childhood experiences on developmental outcomes. Finally, our sample only consisted of preschool children with PAE. A comparison with comprehensive assessments of children with other neurodevelopmental disabilities would inform both assessment as well as intervention strategies.
IMPLICATIONS AND FUTURE RESEARCH
Early intervention is important in reducing the impact of risk factors such as PAE on neurobehavioral outcomes of children while supporting and enhancing protective factors 2. A multidisciplinary team is recommended in the assessment of preschoolers at risk, as this assessment will inform a spectrum of individually and developmentally appropriate interventions. The assessment of preschoolers with PAE demonstrating neurobehavioral deficits should include specialized assessments of communication, motor skills, cognitive development, sensory processing, and neurobehavioral functioning, including executive and adaptive functioning. Sensory processing is a measure of neurological development and integrity, and our study further demonstrated that sensory processing is particularly important in the assessment of young children, where the relative importance of these neurological tracts clearly impacts behavior. The functional impact of these skills is reflected in subsequent measures of adaptive functioning, and this should be carefully and clinically assessed.
There is a need for multisite longitudinal studies on preschool-aged children, as well as on interventions they receive to show the differences made in the children’s lives 53, 54. There is also a need for further study of appropriate assessment procedures for preschool children undergoing FASD assessment 4. Prospective studies on preschoolers exposed to complex risk factors are important to further our understanding of the impacts of these factors and, most importantly, to inform societal understanding and appropriate supports to families who care for them.
The assessment of preschoolers at risk based on a history of exposures to substances, trauma, and toxic stressors is critical to inform early intervention, potentially decrease the severity of deficits later in life, and improve outcomes. Preschool children with confirmed PAE who demonstrate difficulties in motor, language, and behaviors, which may be attributable to differences in sensory responsivity, should be considered for comprehensive FASD diagnostic assessment. Early recognition and diagnostic assessment are critical for providing appropriate management and dedicated support to these children and their families.
CONCLUSIONS
This study describes the multidisciplinary assessment of the largest cohort of preschool children with PAE published till date. Clinical data show that preschoolers with FASD demonstrate global impairments in functioning, which is greater than in those with PAE alone. Data also provide new evidence for including sensory processing in the diagnostic guidelines as a sensitive measure of FASD in the preschool population. Importantly, this study also shows that the combination of significant impairments in motor, language, and sensory processing is able to predict FASD diagnosis in preschoolers. The evidence in this study supports early comprehensive assessment of cognitive and behavioral functioning in preschoolers with PAE to inform appropriate diagnosis, intervention, and to support optimal outcomes.
ACKNOWLEDGMENTS
We are grateful to the children and families who are seen through the Manitoba FASD Centre for clinical assessment by the multidisciplinary team; the Rehabilitation Centre for Children in Specialized Services for Children and Youth (SSCY) Centre; and Jenny Soriano, Marvin Routley, and Harrison Grogan with various aspects of the project. We would also like to thank the Centre for Health Innovation at the University of Manitoba for support with statistical analysis.
CONFLICT OF INTEREST
The authors declare no conflicts of interest.
FUNDING
A. Hanlon-Dearman receives research funding support as a diagnostic lead from CanFASD.
DATA AVAILABILITY STATEMENT
The clinical data are the property of the Manitoba FASD Centre/Rehabilitation Centre for Children.
COMPLIANCE WITH ETHICAL STANDARDS
This study was approved by the University of Manitoba Health Research Ethics Board (HREB).
REFERENCES
1.Cook JL, Green CR, Lilley CM, Anderson SM, Baldwin ME, Chudley AE, et al. Fetal alcohol spectrum disorder: A guideline for diagnosis across the lifespan. CMAJ. 2016;188(3):191–7. https://doi.org/10.1503/cmaj.141593
2.Olson HC, Jirikowic T, Kartin D, Astley S. Responding to the challenge of early intervention for fetal alcohol spectrum disorders. Infants & Young Children. 2007;20(2):172–89. https://doi.org/10.1097/01.IYC.0000264484.73688.4a
3.Proven S, Ens C, Beaudin PG. The language profile of school-aged children with Fetal Alcohol Spectrum Disorder (FASD). Can J Speech-Lang Pathol Audiol.. 2014;37(4):268–79.
4.McLachlan K, Andrew G, Pei J, Rasmussen C. Assessing FASD in young children: Exploring clinical complexities and diagnostic challenges. J Popul Ther Clin Pharmacol. 2015;22(1):e108–e124.
5.Bakhireva LN, Garrison L, Shrestha S, Sharkis J, Miranda R, Rogers K. Challenges of diagnosing fetal alcohol spectrum disorders in foster and adopted children. Alcohol. 2018;67:37–43. https://doi.org/10.1016/j.alcohol.2017.05.004
6.Brown TT. Individual differences in human brain development. Wiley Interdiscip Rev Cogn Sci. 2017;8(1–2):e1389. https://doi.org/10.1002/wcs.1389
7.Mills KL, Goddings AL, Herting MM, Meuwese R, Blakemore SJ, Crone EA, et al. Structural brain development between childhood and adulthood: Convergence across four longitudinal samples. Neuroimage. 2016;141:273–81. https://doi.org/10.1016/j.neuroimage.2016.07.044
8.Donald KA, Ipser JC, Howells FM, Roos A, Fouche JP, Riley EP, et al. Interhemispheric functional brain connectivity in neonates with prenatal alcohol exposure: Preliminary findings. Alcohol Clin Exp Res. 2016;40(1):113–21. https://doi.org/10.1111/acer.12930
9.Donald KA, Fouche JP, Roos A, Koen N, Howells FM, Riley EP, et al. Alcohol exposure in utero is associated with decreased gray matter volume in neonates. Metab Brain Dis. 2016;31(1):81–91. https://doi.org/10.1007/s11011-015-9771-0
10.Hwang HM, Ku RY, Hashimoto-Torii K. Prenatal environment that affects neuronal migration. Front Cell Dev Biol. 2019;7:138. https://doi.org/10.3389/fcell.2019.00138
11.Donald KA, Eastman E, Howells FM, Adnams C, Riley EP, Woods RP, et al. Neuroimaging effects of prenatal alcohol exposure on the developing human brain: a magnetic resonance imaging review. Acta Neuropsychiatr. 2015;27(5):251–69. https://doi.org/10.1017/neu.2015.12
12.Lebel CA, McMorris CA, Kar P, Ritter C, Andre Q, Tortorelli C, et al. Characterizing adverse prenatal and postnatal experiences in children. Birth Defects Res. 2019;111(12):848–58. https://doi.org/10.1002/bdr2.1464
13.McLennan JD, Braunberger P. A critique of the New Canadian Fetal Alcohol Spectrum Disorder guideline. J Can Acad Child Adolesc Psychiatry. 2017;26(3):179–83.
14.McLennan JD. Misattributions and potential consequences: The case of child mental health problems and Fetal Alcohol Spectrum Disorders. Can J Psychiatry. 2015;60(12):587–90. https://doi.org/10.1177/070674371506001210
15.Flannigan K, Gill K, Pei J, Andrew G, Rajani H, McFarlane A, et al. Deferred diagnosis in children assessed for fetal alcohol spectrum disorder. Appl Neuropsychol Child. 2019;8(3):213–22. https://doi.org/10.1080/21622965.2018.1427094
16.Astley S.
17.Astley SJ. Validation of the Fetal Alcohol Spectrum Disorder (FASD): 4-Digit diagnostic code. J Popul Ther Clin Pharmacol. 2013;20(3):e416–e467.
18.Knobloch H, Stevens MF, Malone AF.
19.Wiig EH, Semel EM, Secord W,
20.Zimmerman IL, Steiner VG, Pond RE,
21.Dunn W. Sensory profile: User’s manual. San Antonio, TX: Psychological Corp.; 1999. https://doi.org/10.1037/t15155-000
22.Henderson SE, Sugden DA, Barnett AL, Petermann F, Bös K, Jascenoka J. Movement assessment battery for children-2: (Movement ABC-2) – Manual. Frankfurt am Main: Pearson; 2015.
23.Beery KE, Beery NA. The Beery-Buktenica developmental test of Visual Motor Integration (Beery VMI). Bloomington, MN: Pearson; 2010. https://doi.org/10.1037/t48947-000
24.Gioia GA, Epsy KA, Isquith PK. BRIEF: Behavior rating inventory of executive function – Preschool version. Lutz, FL: Psychological Assessment Resources; 2003.
25.Harrison PL, Oakland T. Adaptive behavior assessment system.
26.Jones KL, Smith DW. Recognition of the fetal alcohol syndrome in early infancy. Lancet. 1973;302(7836):999–1001. https://doi.org/10.1016/S0140-6736(73)91092-1
27.Lemoine P HH, Borteryu JT, Menuet JC. Les Enfants des parents alcoholiques: anomalies observees a propos de 127 cas. Ouest Medical. 1968;21:476–82.
28.Maatta S, Laakso ML, Tolvanen A, Ahonen T, Aro T. Developmental trajectories of early communication skills. J Speech Lang Hear Res. 2012;55(4):1083–96. https://doi.org/10.1044/1092-4388(2011/10-0305)
29.de Beer M, Kritzinger A, Zsilavecz U. Young children with fetal alcohol spectrum disorder – communication profiles. S Afr J Commun Disord. 2010;57:33–42. https://doi.org/10.4102/sajcd.v57i1.47
30.Kalberg WO, Buckley D. Educational planning for children with fetal alcohol syndrome. Ann Ist Super Sanita. 2006;42(1):58–66.
31.Doney R, Lucas BR, Watkins RE, Tsang TW, Sauer K, Howat P, et al. Visual-motor integration, visual perception, and fine motor coordination in a population of children with high levels of Fetal Alcohol Spectrum Disorder. Res Dev Disabil. 2016;55:346–57. https://doi.org/10.1016/j.ridd.2016.05.009
32.Doney R, Lucas BR, Jones T, Howat P, Sauer K, Elliott EJ. Fine motor skills in children with prenatal alcohol exposure or fetal alcohol spectrum disorder. J Dev Behav Pediatr. 2014;35(9):598–609. https://doi.org/10.1097/DBP.0000000000000107
33.Stephen JM, Kodituwakku PW, Kodituwakku EL, Romero L, Peters AM, Sharadamma NM, et al. Delays in auditory processing identified in preschool children with FASD. Alcohol Clin Exp Res. 2012;36(10):1720–7. https://doi.org/10.1111/j.1530-0277.2012.01769.x
34.Jirikowic T, Olson HC, Kartin D. Sensory processing, school performance, and adaptive behavior of young school-age children with fetal alcohol spectrum disorders. Phys Occup Ther Pediatr. 2008;28(2):117–36. https://doi.org/10.1080/01942630802031800
35.Wengel T, Hanlon-Dearman AC, Fjeldsted B. Sleep and sensory characteristics in young children with fetal alcohol spectrum disorder. J Dev Behav Pediatr. 2011;32(5):384–92. https://doi.org/10.1097/DBP.0b013e3182199694
36.Fjeldsted B, Xue L. Sensory processing in young children with fetal alcohol spectrum disorder. Phys Occup Ther Pediatr. 2019;39(5):553–65. https://doi.org/10.1080/01942638.2019.1573775
37.Tavassoli T, Brandes-Aitken A, Chu R, Porter L, Schoen S, Miller LJ, et al. Sensory over-responsivity: Parent report, direct assessment measures, and neural architecture. Mol Autism. 2019;10(1):4. https://doi.org/10.1186/s13229-019-0255-7
38.Brandes-Aitken A, Anguera JA, Chang YS, Demopoulos C, Owen JP, Gazzaley A, et al. White matter microstructure associations of cognitive and visuomotor control in children: A sensory processing perspective. Front Integr Neurosci. 2018;12:65. https://doi.org/10.3389/fnint.2018.00065
39.Pryweller JR, Schauder KB, Anderson AW, Heacock JL, Foss-Feig JH, Newsom CR, et al. White matter correlates of sensory processing in autism spectrum disorders. Neuroimage Clin. 2014;6:379–87. https://doi.org/10.1016/j.nicl.2014.09.018
40.Owen JP, Marco EJ, Desai S, Fourie E, Harris J, Hill SS, et al. Abnormal white matter microstructure in children with sensory processing disorders. Neuroimage Clin. 2013;2:844–53. https://doi.org/10.1016/j.nicl.2013.06.009
41.Jaegermann N, Klein PS. Enhancing mothers’ interactions with toddlers who have sensory-processing disorders. Infant Ment Health J. 2010;31(3):291–311. https://doi.org/10.1002/imhj.20257
42.Huhdanpaa H, Klenberg L, Westerinen H, Bergman PH, Aronen ET. Impairments of executive function in young children referred to child psychiatric outpatient clinic. Clin Child Psychol Psychiatry. 2019;24(1):95–111. https://doi.org/10.1177/1359104518786537
43.McKinnon RD, Blair C, Family Life Project I. Does early executive function predict teacher-child relationships from kindergarten to second grade? Dev Psychol. 2018;54(11):2053–66. https://doi.org/10.1037/dev0000584
44.Fuglestad AJ, Whitley ML, Carlson SM, Boys CJ, Eckerle JK, Fink BA, et al. Executive functioning deficits in preschool children with fetal alcohol spectrum disorders. Child Neuropsychol. 2015;21(6):716–31. https://doi.org/10.1080/09297049.2014.933792
45.Rasmussen C, Bisanz J. Executive functioning in children with Fetal Alcohol Spectrum Disorders: Profiles and age-related differences. Child Neuropsychol.2009;15(3):201–15. https://doi.org/10.1080/09297040802385400
46.Rasmussen C, Horne K, Witol A. Neurobehavioral functioning in children with fetal alcohol spectrum disorder. Child Neuropsychol. 2006;12(6):453–68. https://doi.org/10.1080/09297040600646854
47.Taylor NM, Enns LN. Factors predictive of a fetal alcohol spectrum disorder diagnosis: Parent and teacher ratings. Child Neuropsychol. 2018;12:1–21.
48.Greenbaum RL, Stevens SA, Nash K, Koren G, Rovet J. Social cognitive and emotion processing abilities of children with fetal alcohol spectrum disorders: A comparison with attention deficit hyperactivity disorder. Alcohol Clin Exp Res. 2009;33(10):1656–70. https://doi.org/10.1111/j.1530-0277.2009.01003.x
49.O’Connor MJ, Frankel F, Paley B, Schonfeld AM, Carpenter E, Laugeson EA, et al. A controlled social skills training for children with fetal alcohol spectrum disorders. J Consult Clin Psychol. 2006;74(4):639–48. https://doi.org/10.1037/0022-006X.74.4.639
50.Rasmussen C, Becker M, McLennan J, Urichuk L, Andrew G. An evaluation of social skills in children with and without prenatal alcohol exposure. Child Care Health Dev. 2011;37(5):711–18. https://doi.org/10.1111/j.1365-2214.2010.01152.x
51.Molteno CD, Jacobson JL, Carter RC, Dodge NC, Jacobson SW. Infant emotional withdrawal: A precursor of affective and cognitive disturbance in fetal alcohol spectrum disorders. Alcohol Clin Exp Res. 2014;38(2):479–88. https://doi.org/10.1111/acer.12240
52.Zoorob R, Aliyu MH, Hayes C. Fetal alcohol syndrome: Knowledge and attitudes of family medicine clerkship and residency directors. Alcohol. 2010;44(4):379–85. https://doi.org/10.1016/j.alcohol.2009.10.012
53.Zarnegar Z, Hambrick EP, Perry BD, Azen SP, Peterson C. Clinical improvements in adopted children with fetal alcohol spectrum disorders through neurodevelopmentally informed clinical intervention: A pilot study. Clin Child Psychol Psychiatry. 2016;21(4):551–67. https://doi.org/10.1177/1359104516636438
54.Rasmussen C, Kully-Martens K, Denys K, Badry D, Henneveld D, Wyper K, et al. The effectiveness of a community-based intervention program for women at-risk for giving birth to a child with Fetal Alcohol Spectrum Disorder (FASD). Community Ment Health J. 2012;48(1):12–21. https://doi.org/10.1007/s10597-010-9342-0