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. Author manuscript; available in PMC: 2026 Apr 1.
Published in final edited form as: Alcohol Clin Exp Res (Hoboken). 2025 Mar 27;49(4):818–828. doi: 10.1111/acer.70013

Abnormal neurobehavior profiles observed in the newborn period following low-to-moderate prenatal alcohol exposure

Jessie R Maxwell 1,2,*, Melissa H Roberts 3, Jean Lowe 1, Xingya Ma 3, Jillian F Kotulski 3, Amy L Salisbury 4, Ludmila Bakhireva 3
PMCID: PMC12014367  NIHMSID: NIHMS2063236  PMID: 40146015

Abstract

Background:

Prenatal alcohol exposure (PAE) has lifelong consequences on affected individuals with a range of physical, neurodevelopmental, learning, and behavioral adverse outcomes. There is no method to identify children at risk of these outcomes shortly after birth resulting in delayed diagnosis and access to therapeutic modalities. The Neonatal Intensive Care Unit (NICU) Network Neurobehavioral Scale, First Edition (NNNS-I) has demonstrated utility in risk stratification of substance-exposed infants but has not been previously used to assess infants with PAE. The purpose of this study was to assess utility of NNNS-I in identification of infants with low-to-moderate PAE.

Methods:

The Ethanol, Neurodevelopment, Infant and Child Health (ENRICH-2) prospective cohort included maternal assessments in the second and third trimesters of pregnancy, and infant assessments at birth. PAE was evaluated by prospective, repeated Timeline Follow Back interviews and a comprehensive panel of ethanol biomarkers. During the birth hospitalization, certified examiners completed the NNNS-I assessment, which included infant neurobehavioral organization summarized into 12 summary scores. Summary scores and profiles, generated by latent profile analysis (LPA), were compared among PAE and no-PAE groups.

Results:

This analysis included 130 caregiver-infant dyads (71 with PAE and 59 with no-PAE). The absolute alcohol ounces per day in the PAE group was 0.08 ± 0.11 on average, or ~1.1 standard drinks per week. In multivariable analysis, PAE was associated with lower attention (β=−0.79) and higher lethargy (β=−0.86) scores (P’s <0.05) on NNNS-I after controlling for maternal mental health, marijuana use during pregnancy, and family income. LPA identified 3 profiles of neurobehavior with a high-risk profile demonstrating poor infant self-regulation and decreased attention.

Conclusion:

Low-to-moderate PAE was associated with neurobehavioral findings identifiable on the NNNS-I assessment highlighting its potential utility for screening and risk stratification of infants with PAE shortly after birth.

Graphical Abstract

graphic file with name nihms-2063236-f0001.jpg

Infants with prenatal alcohol exposure (PAE) have lifelong consequences that are typically identified in later childhood. The Neonatal Intensive Care Unit Network Neurobehavioral Scale, First Edition (NNNS-I) is a valuable tool allowing for risk stratification in newborns with other substance exposures. We used the NNNS-I to assess infants with low-to-moderate PAE and found notable neurobehavioral abnormalities. Given these findings, future studies may focus on using NNNS-I for risk stratification and allowing earlier identification for individualized therapeutic interventions.

Introduction

Children with in utero substance exposure, including alcohol, are at increased risk of developmental delays (Bandoli et al., 2023, Subramoney et al., 2018). Prenatal alcohol use remains a significant public health problem, with 8% up to 14% of pregnant individuals reporting alcohol consumption in the past 30 days in the United States (Gosdin et al., 2022, Administration, 2023, Bandoli et al., 2023). Developmental delays following prenatal alcohol exposure (PAE) are broad, and the overarching diagnosis of Fetal Alcohol Spectrum Disorder (FASD) is used to describe those affected by PAE (Cook et al., 2016). When developmental delays are suspected, early identification is critical for optimizing the long-term outcomes (Abercrombie et al., 2022). The developmental delays associated with PAE impact cognition, behavior, and executive functioning. Commonly affected domains include increased impulsivity, intellectual and self-regulation impairments, deficits in attention, and difficulties with problem solving (Mattson et al., 2019, Gautam et al., 2014). Outward physical changes, including facial dysmorphology, may or may not be present, and the history of PAE is often unknown.

Adverse effects associated with a mild-to-moderate PAE are particularly challenging to diagnose (Akison et al., 2024), despite this level of exposure being the most prevalent. Of 9,719 participants in the Adolescent Brain Cognitive Development Study, 26% were exposed to alcohol in utero based on parental report, with the majority (62% of those with alcohol exposure) having light/mild exposure (Lees et al., 2020). Those with PAE, even the light/mild exposure, were significantly more likely to have higher impulsivity, separation anxiety disorder, and oppositional defiant disorder compared to those without PAE (Lees et al., 2020). Similarly, data from the Collaboration of FASD Prevalence study demonstrated that low PAE throughout pregnancy was associated with behavioral problems among first-grade children (Bandoli et al., 2022). There is no uniform definition of mild-to-moderate PAE, while some studies defined it as less than six drinks per week during the periconceptional period or during pregnancy (Flak et al., 2014). The proposed Diagnostic and Statistical Manual of Mental Illnesses (DSM-5) diagnosis of Neurodevelopmental Disorder associated with PAE (ND-PAE) defines more than minimal alcohol exposure as ≥ 13 drinks per 30-day period of pregnancy (Kable et al., 2016).

Given that symptoms may not be noted until later childhood, a FASD diagnosis is often not considered until behavioral and developmental delays are observed during school age (Mattson et al., 2019). Additionally, many children may not be appropriately diagnosed or may receive a diagnosis of a condition of overlapping symptoms, such as attention-deficit / hyperactivity disorder (ADHD) or oppositional defiant disorder (ODD) (Ergun et al., 2021). Thus, a major challenge in the field is to accurately diagnose the infant/child in a timely manner, allowing appropriate early interventions and other behavioral and developmental supports to be arranged.

One early assessment tool of neurobehavioral performance, the Neonatal Intensive Care Unit (NICU) Network Neurobehavioral Scale, First Edition (NNNS-I), can be completed in the newborn period (Tronick and Lester, 2013, Lester et al., 2004). The NNNS-I has been used in a variety of patients, and normative values have been well established (Tronick and Lester, 2013, Provenzi et al., 2018). Infants born preterm, very preterm, as well as full-term infants with known maternal adversity have been evaluated with the NNNS-I (McGowan et al., 2022, Parikh et al., 2022) with predictive value observed for outcomes at two years of age. Infants born preterm with a NNNS-I profile considered high-risk were found to have more adverse cognitive, motor, and behavioral outcomes (McGowan et al., 2022). Infants born to individuals with prenatal anxiety or depression were noted to have specific NNNS-I findings, such as less optimal attention and increased lethargy (Hofheimer et al., 2020). Indeed, infants with an “under-aroused” profile (including higher lethargy and lower attention scores) have been observed to be born to individuals with depression in multiple studies (Salisbury et al., 2011, Camerota et al., 2023). Additionally, adverse maternal psychosocial conditions predicted abnormalities on the infant’s NNNS-I assessment, including lower self-regulation (Hofheimer et al., 2020). Prenatal exposures, such as maternal tobacco (Stroud et al., 2020) and metal exposures (Tung et al., 2022) have also been associated with alterations on NNNS-I assessments. Tobacco exposure was associated with high arousal, excitability, and stress abstinence NNNS scores (Camerota et al., 2023), and cadmium or lead exposure assessed in placenta were associated with an atypical neurobehavior profile characterized by the highest arousal, excitability, hypertonicity, stress abstinence signs, and the lowest quality of regulation (Tung et al., 2022). Recently, an NNNS-I assessment study focusing on infants with prenatal opioid exposure revealed alterations in neurobehavior shortly after birth, such as poor self-regulation and quality of movements (Heller et al., 2017). Additionally, infants with neonatal abstinence syndrome assessed with the Child Behavior Checklist at 18 months of age were found to have externalizing, internalizing, and total behavior problems if they initially had an atypical NNNS profile during the newborn period compared to those with a typical NNNS profile (Czynski et al., 2020).

While the NNNS-I has been utilized in various high-risk populations, we are not aware of any prior studies utilizing NNNS-I for evaluation of infants with PAE. Identifying subtle changes in neurodevelopmental and behavioral outcomes associated with low-to-moderate PAE is particularly challenging, even in older children. The primary objectives of this study were to examine utility of NNNS-I, administered shortly after birth, in differentiating infants with low-to-moderate PAE from unexposed controls. We hypothesized the PAE would be associated with poorer arousal regulation in the newborn period, with additional associations observed between maternal mental health status, regardless of PAE status.

Materials and Methods

Ethanol, Neurodevelopment, Infant and Child Health (ENRICH-2) study design:

Following approval from the University of New Mexico Health Sciences Center Institutional Review Board (IRB), individuals were recruited in the study from 2018 to 2022. The pregnant persons were enrolled predominantly in their second trimester of pregnancy (gestational age at enrollment: 25.2±6.3 weeks) and followed until the infants were 6–9 months of age. The study consisted of four study visits (V1-V4) which incorporated maternal questionnaires, collection of biospecimens, assessment of physiological indices (e.g., heart rate variability) and neurodevelopmental assessments of the infant (e.g., NNNS-I) (Bakhireva et al., 2024, Maxwell et al., 2024, Wohrer et al., 2024). Maternal use of opioids and/or stimulants (methamphetamines, cocaine, 3,4-methylenedioxymethamphetamine [MDMA] during pregnancy, a serious mental health disorder (e.g., psychosis or schizophrenia), gestational age of delivery of less than 35 weeks, and severe structural anomaly or a health condition requiring prolonged hospitalization of a newborn were exclusionary criteria.

The first study visit was conducted during the second trimester. Maternal questionnaires queried socio-demographic and medical/reproductive health information, including participant age, marital status, education, employment, ethnic group self-identity, gravidity, parity, complications during the pregnancy, chronic health conditions, and medication used. The Perceived Stress Scale (PSS) questionnaire assessed maternal perception of psycho-social stress (Cohen et al., 1983). Participant’s blood and urine samples were collected and assayed for ethanol biomarkers (ethyl glucuronide and ethyl sulfate assessed in urine [uEtG/uEtS], γ-glutamyltranspeptidase [GGT], carbohydrate-deficient transferrin [%dCDT], and phosphatidylethanol [PEth] assessed in blood (Bakhireva et al., 2015, Bakhireva and Savage, 2011) and other substances (Urine Drug Panel-7:amphetamines, barbiturates, benzodiazepine, cannabinoid, cocaine, opiates, and propoxyphene use). Visit 2 occurred during the third trimester of pregnancy and included administration of validated questionnaires: the PSS, Generalized Anxiety Disorders-7 (GAD-7) (Simpson et al., 2014), Edinburgh Depression Scale (EDS) (Bergink et al., 2011, Gibson et al., 2009), modified Medical Outcomes Study Social Support (MOSS) (Sherbourne and Stewart, 1991), Posttraumatic Stress Disorder Checklist for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (PCL-5) (Levey et al., 2018), and the 10-item Adverse Childhood Experiences (ACE) checklist (Felitti et al., 1998). The PPS total score from the second study visit was used for analysis.

The third study visit occurred between admission for labor and delivery and the hospital discharge, or post hospital discharge (0–1 month of age). Maternal blood and urine samples, placenta, umbilical cord blood samples were collected. Additionally, infant dried blood spots (DBS) were collected via heel-lancing at the time of standard of care blood collection and assayed for PEth (PEth-DBS). The NNNS-I was administered by certified examiners to assess neurobehavior during birth hospitalization or shortly after discharge (described in greater details below). The final study visit (V4) occurred when the infant was 6–9 months of age and included measures of postnatal environment and infant development and behavior. This study includes the data derived from the first three visits (V1-V3).

Assignment to the PAE or no-PAE group involved a 3-tiered screening process (Maxwell et al., 2024). In Tier I, the AUDIT-C questionnaire was administered and binge drinking (≥4 drinks/occasion) in the periconceptional period was assessed. Participants scoring ≥2 on AUDIT-C and reporting ≥2 binge drinking episodes during a month around their last menstrual period were provisionally enrolled in the PAE group. Those with no binge drinking in periconceptional period and an AUDIT-C score <2 were provisionally enrolled in the no-PAE group. Tier II used 30-day TLFB interviews to obtain information on alcohol use during pregnancy. Participants who reported more than 13 standard drink unit (SDU) per month and/or at least one binge episode during pregnancy remained in the PAE group. Participants with no reported alcohol use remained in the no-PAE group. Tier III confirmed group assignment with ethanol biomarkers (described below). The PAE group included individuals who met criteria of ≥1 binge episode OR >13 drinks OR ≥1 positive biomarker. No-PAE group had to be negative on self-reported measures of alcohol use during pregnancy and be negative on all biomarkers. Participants provisionally classified into the no-PAE group who later tested positive for ethanol biomarkers were reclassified into the PAE group. Among 130 participants included in this analysis, 71 (54.6%) met criteria for the PAE group and 59 (45.3%) for the non-PAE group.

Additionally, the National Survey on Drug Use and Health questionnaire screened for self-reported drug use.

Ethanol biomarkers:

Maternal blood and urine specimens were collected at enrollment (V1) and admission for labor and delivery (V3). Urine and whole blood specimens were sent frozen to U.S. Drug Testing Laboratory (USDTL; Des Plaines, IL) and analyzed for ethylglucuronide (uEtG)/ethylsulfate (uEtS), and phosphatidylethanol (PEth) by LC-MS/MS, respectively. Serum specimens were analyzed for gamma-glutamyltranspeptidase (GGT) as part of a liver panel by the enzymatic rate method for GGT activity on a Beckman Synchron LX analyzer (Beckman Coulter Inc., Brea, CA) at the TriCore Reference Laboratory (Albuquerque, NM). Another serum aliquot was analyzed for carbohydrate-deficient transferrin (%dCDT) by an internationally validated HPLC and spectrophotometric detection method at the Medical University of South Carolina (Charlston, SC). Additionally, dry blood spots were collected from newborn participants at 24 hours after birth and analyzed for PEth (PEth-DBS) at USDTL. The following previously proposed cutoff concentrations were used to classify tests as positive: GGT > 40 U/L (Gutierrez et al., 2015, Hietala et al., 2005), %CDT > 2.0 (Gutierrez et al., 2015, Bakhireva et al., 2012, Kenan et al., 2011, Bianchi et al., 2011), PEth > 8.0 ng/mL (Gutierrez et al., 2015), uEtG > 38 ng/mL, uEtS > 25 ng/mL (Gutierrez et al., 2015, Bakhireva et al., 2014), PEth-DBS > 25 ng/mL (Gutierrez et al., 2015, Afshar et al., 2022). This comprehensive panel was selected to capture different level of exposure and is characterized by biomarkers with short, medium, and long detection windows (see review by Bakhireva and Savage, 2011).

Neonatal Intensive Care Unit (NICU) Network Neurobehavioral Scale (NNNS) I:

Three study evaluators obtained NNNS-I certification through the NNNS Assessment Training Program from Women & Infants’ Hospital at Brown University. The NNNS-I assessment resulted in 12 established summary scores: orientation/attention (sustained alertness), handling (amount of external input from examiner required to elicit infant’s attention), regulation (infant’s ability to regulate stress and soothe), arousal (how quickly infant becomes irritable or highly active), excitability (measure of high levels of motor and physiologic reactivity), lethargy (measure of low levels of motor and physiologic reactivity), hypertonicity (increased muscle tone), hypotonicity (decreased or low muscle tone), nonoptimal reflexes (non-optimal responses to newborn reflexes), asymmetric reflexes (number of times reflexes are stronger or weaker on one side of the body compared to the other), quality of movement (measure of motor maturity), and stress abstinence (stress response to manipulation) (Tronick and Lester, 2013, Coleman et al., 2013, Parikh et al., 2022, Lester et al., 2004). Habituation was not obtained in this cohort per recommendation during the NNNS Assessment Training Program.

The certified NNNS-I examiners, blinded to the exposure status, completed the NNNS-I assessment either during the birth hospitalization (n=126) or post hospital discharge within 1 month of age (n=4). Average age of assessment was 1.6 ± 3.0 days and typically lasted no more than 20 minutes. The average age of assessment for the 126 participants assessed during the birth hospitalization was 1.2 ± 0.8 days; the average age of assessment for the 4 participants assessed post hospital discharge was 15.8 ± 9.9 days. Inter-rater reliability was completed between examiners; a random participant was chosen per examiner, and 2 certified examiners were present for the assessment and then each completed the scoring individually. These were reviewed to ensure consistency of all summary scores assessed.

Statistical analysis:

Socio-demographic characteristics were summarized using means and standard deviation (SD) for continuous variable and counts and percentages for categorical variables. Differences in maternal socio-demographic characteristics, maternal assessments, infant sex, infant birth anthropomorphic measures, and NNNS-I summary scores between the PAE and no-PAE groups were analyzed using pooled variance t-test, Mann-Whitney test, or Fisher’s exact test, as appropriate. A sensitivity analysis was conducted for NNNS-I summary score comparisons that only included NNNS-I conducted prior to discharge from the delivery hospitalization, given the changes in summary scores that have been observed over the first few weeks of life (Provenzi et al., 2018). Statistical differences in the NNNS-I summary scores between PAE and no-PAE groups were further examined in generalized linear regression models after adjusting for marijuana use in pregnancy, depressive symptoms (EDS), and sociodemographic characteristics (family income) – factors which varied significantly between the PAE and no PAE groups.

Latent Profile Analysis (LPA):

LPA was used to identify groups of infants with similar response patterns on the items from the NNNS-I assessment following previously established methodology (Parikh et al., 2022, Sucharew et al., 2012, McGowan et al., 2022). LPA was implemented with the R package ‘tidyLPA’ which included the R package ‘mclust’ designed for model-based clustering, classification, and density estimation based on finite normal mixture modelling (Scrucca et al., 2016, Rosenberg, 2018). All 12 assessed NNNS-I items were utilized in the LPA. LPA models that identified from one to four latent classes (profiles) based on the set of NNNS-I item scores were investigated. An analytic hierarchy approach was used to identify the number of profiles for the best fit model based on several fit indices (Akaike’s Information Criterion [AIC], Bayesian Information Criterion [BIC], Approximate Weight of Evidence [AWE], Classification Likelihood Criterion [CLC], and Kullback Information Criterion [KIC]) (Akogul S, 2017). LPA results identified a model with three mutually exclusive profiles as the best solution (Supplemental Table 1). Assignment of infants to one of the three profiles was according to LPA probability estimates (Rosenberg, 2018). Z-scores for the 12 NNNS-I items, indicating positive/negative deviation from the overall mean for the study population, were summarized for each profile in the final model. Differences in maternal socio-demographic characteristics, maternal assessments (including PSS, GAD-7, EDS, MOSS, PCL-5, and ACE checklist), infant sex, birth anthropometric assessments, alcohol exposure, and NNNS-I summary scores between the profiles were analyzed using pooled variance t-test, Mann-Whitney test, Chi-Square or Fisher’s exact test, as appropriate. Pairwise comparisons were also conducted between LPA identified profiles.

SAS statistical software (version 9.4; Cary, North Carolina, United States) and R (Computing, 2021) were used for statistical analysis. Analyses were two-tailed, and statistical significance as determined with an alpha level of 0.05, however, findings with an alpha level of 0.10 are also reported.

Results

The sample included a large proportion of pregnant persons traditionally underrepresented in research (64.6% Hispanics/Latine, 5.4% American Indians, 4.6% multi-racial). There were no differences between the PAE and no-PAE groups in socio-demographic characteristics except for income distribution (Table 1). The no-PAE group had a higher percentage of participants with family income $70,000 or higher compared to PAE group (42.4% vs. 18.3%, P<0.01). With respect to maternal mental health, the PAE group had significantly higher scores on the PSS, the EDS, and the GAD-7 (Table 1, P’s<0.05). The average consumption of alcohol in the PAE group across periconceptional period and during pregnancy was 0.08 ± 0.11 absolute alcohol ounces per day (AAD), which is equivalent to approximately 1.1 drinks per week. Two-thirds of participants in the PAE group reported at least one binge episode during the periconceptional period or during pregnancy with the majority of those reporting at least one binge episode during the periconceptional period (57.7%; data not shown). Additionally, 57.7% of the participants in the PAE group had at least one positive ethanol biomarker. Marijuana (29.6% PAE group vs. 10.2% no-PAE group, P <0.01) and tobacco (14.1% PAE group vs. 3.4% no-PAE group, P=0.06) use were more prevalent in the PAE group compared to controls. As shown in Supplemental Table 2, no differences with respect to birth weight, length, head circumference (both absolute measures and percentiles), Apgar scores, gestational age at delivery, and infant sex were observed between the two groups.

Table 1.

Demographic and Maternal Characteristics by Study Group (n=130)

PAE
(n=71)		 No-PAE
(n =59)		 P-Value
N (%) N (%)
Marital status: 0.221
 Single/separated/divorced 20 (28.2) 11 (18.6)
 Married/cohabitating 51 (71.8) 48 (81.4)
Ethnicity (Hispanic/Latine) 50 (70.4) 34 (57.6) 0.141
Race:
 White 52 (73.2) 41 (69.5) 0.452
 Black or African American 3 (4.2) 1 (1.7)
 American Indian or Alaskan Native 3 (4.2) 4 (6.8)
 Multi-racial/other 9 (12.7) 11 (18.7)
 Prefer not to report 4 (5.6) 2 (3.4)
Education: 0.071
 High school or less 26 (36.6) 19 (32.2)
 Some college or vocational school 22 (31.0) 10 (16.9)
 College degree or higher 23 (32.4) 30 (50.8)
Family income: <0.011
 Under $30,000 22 (31.0) 19 (32.2)
 $30,000–49,000 23 (32.4) 8 (13.6)
 $50,000–69,000 12 (16.9) 6 (10.2)
 $70,000 or over 13 (18.3) 25 (42.4)
 Unknown 1 (1.4%) 1 (1.7%)
Currently employed 43 (60.6) 38 (64.4) 0.721
Health insurance: 0.292
 Employer-based insurance 29 (40.8) 28 (47.5)
 Medicaid 27 (38.0) 16 (27.1)
 Other 15 (21.2) 15 (25.4)
Substance use in pregnancy
 ≥ 1 binge drinking episode* 47 (66.2) 0 (0.0) <0.0011
 ≥ 1 positive ethanol biomarker 41 (57.7) 0 (0.0) <0.0011
 Marijuana use 21 (29.6) 6 (10.2) <0.011
 Tobacco use 10 (14.1) 2 (3.4) 0.06
Mean ± SD Mean ± SD
Age at enrollment (years) 29.4 ± 5.7 29.5 ± 5.4 0.833
 MOSS Social support 78.9 ± 23.0 86.7 ± 15.6 0.073
 EDS 7.3 ± 5.5 5.4 ± 5.3 0.023
 PSS 15.1 ± 7.7 11.5 ± 7.6 0.0043
 GAD-7 6.1 ± 5.1 4.4 ± 4.4 0.033
 Maternal ACE score 2.8 ± 2.9 1.9 ± 2.1 0.163
Alcohol use in periconceptional period and during pregnancy (AAD) 0.08 ± 0.11 0.00 ± 0.01 <0.0013
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ACE, Adverse Childhood Experiences; EDS, Edinburgh Postnatal Depression Scale; GAD-7, General Anxiety Disorder-7 score; MOSS, modified Medical Outcomes Study Social Support Survey; PSS, Perceived Stress Scale; AAD, absolute alcohol (ounces) per day [1 AA is equivalent to ~0.5 standard drinks]

*

Reported binge drinking includes the periconceptual period and during pregnancy

1

based on Chi-Square test

2

based on Fisher’s exact test

3

based on Mann-Whitney test

For the NNNS-I scores, missing values were present for some infants on self-regulation (n=3), attention (n=27), and handling (n=19). Missing values occurred if an infant was not able to complete that component of the assessment due to excess crying or drowsiness. Table 2 summarizes NNNS-I results by PAE compared to the no-PAE group. Infants in the PAE group had higher mean scores for lethargy (5.07 ± 2.02 vs. 4.47 ± 2.43, P=0.04) and hypertonicity (0.42 ± 0.50 vs. 0.20 ± 0.41, P=0.008), and lower scores for attention (4.41 ± 1.35 vs. 5.08 ± 1.41, P=0.02) and stress abstinence (0.04 ± 0.04 vs. 0.06 ± 0.06, P=0.04) compared to no-PAE group (Table 2). No significant differences were noted for other NNNS-I summary scores between PAE delineated groups. In the sensitivity analysis, exclusion of the 4 NNNS-I assessments obtained after birth hospitalization discharge did not change the above findings (data not shown). In multivariable regression analyses, PAE remained significantly associated with lethargy (P<0.01) and attention scales (P<0.05) after adjusting for marijuana use, maternal EDS, and family income (Table 3). The association between PAE and hypertonicity and stress abstinence became significant at alpha level of 0.10 (P<0.10) only. No independent effects of marijuana use, family income, or EDS were observed after adjusting for PAE (Table 3).

Table 2:

NNNS-I Summary Scores by Study Group (n=130)

NNNS-I Summary Score1 PAE No-PAE P-Value
(n=71) (n=59)
Self-regulation (69, 58) 5.53 ± 0.84 5.43 ± 0.74 0.452
Attention (57, 46) 4.41 ± 1.35 5.08 ± 1.41 0.023
Handling (61, 50) 0.32 ± 0.26 0.34 ± 0.33 0.703
Arousal 3.86 ± 0.63 3.90 ± 0.63 0.692
Excitability 2.35 ± 2.16 2.58 ± 2.27 0.593
Lethargy 5.07 ± 2.02 4.47 ± 2.43 0.043
Hypertonicity 0.42 ± 0.50 0.20 ± 0.41 0.0083
Hypotonicity 0.06 ± 0.23 0.08 ± 0.28 0.533
Nonoptimal reflexes 2.86 ± 1.56 3.14 ± 1.36 0.493
Asymmetric reflexes 0.41 ± 0.96 0.32 ± 0.68 0.883
Quality of movement 4.85 ± 0.50 4.66 ± 0.64 0.283
Stress abstinence 0.04 ± 0.04 0.06 ± 0.06 0.043
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PAE, prenatal alcohol exposure

1

(x, x) indicate n for (PAE, No-PAE) where different than (71, 59)

2

based on pooled variances t-test

3

based on Mann-Whitney test

Table 3:

Multivariate Regression Models for Selected NNNS-I Scales1

NNNS-I scales significantly different between PAE and no-PAE groups
Predictors Attention Hypertonicity Lethargy Stress abstinence
Estimate (SE) Estimate (SE) Estimate (SE) Estimate (SE)
PAE (any vs. none) −0.79 (0.30)*** 0.17 (0.09)* 0.86 (0.43)** −0.02 (0.01)*
Marijuana (any vs. none) 0.23 (0.41) 0.11 (0.11) −0.75 (0.52) −0.005 (0.01)
EDS (1-unit increase) 0.007 (0.03) −0.0006 (0.008) 0.03 (0.04) −0.0008 (0.0007)
Family income:
 <$30,000 (reference) -- -- -- --
 $30,000-$70,000 0.06 (0.33) 0.05 (0.10) 0.16 (0.48) 0.0003 (0.009)
 $70,000 or higher −0.30 (0.36) 0.01 (0.11) 0.76 (0.50) −0.001 (0.01)
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PAE, prenatal alcohol exposure; EDS, Edinburgh Depression Scale; SE, standard error

1

Summarized are 4 regression models – one model for each NNNS-I scale

*

P < 0.10;

**

P < 0.05;

***

P < 0.01

The LPA included the observations in which all 12 NNNS-I assessed items were documented (no missing values for any of the scales), thus included 103 subjects – 57 in the PAE group (80.3%) and 46 in the no-PAE group (80.7%). Figure 1 presents the Z-scores (positive or negative deviation from the overall mean for the study population) for each of NNNS-I scale by 3 Profiles derived from LPA. Profile 1 (n=28) emerged as a high behavioral risk profile given the poorly sustained attention and lower self-regulation as evidenced by higher arousal and excitability, increased handling assistance required, and poor quality of movements compared to the other two profiles. Profile 2 (n=22) appeared to be a mixed behavioral risk profile with poorly sustained attention but improved self-regulation. Finally, Profile 3 (n=53) appeared to be a low behavioral risk profile with improved self-regulation (lower excitability and arousal), no additional handling assistance required, and improved quality of movements.

Figure 1: Mean Z-Scores* for NNNS-I Summary Scores by Profile (n=103).

Figure 1:

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The mean z-scores, which indicates a positive or negative deviation from the overall mean for the study population, for the NNNS-I summary scores are shown. Profile 1 (dotted line) had higher arousal and excitability and overall had a high behavioral risk profile. Profile 2 (dashed line) was a mixed behavioral risk profile with poorly sustained attention. Profile 3 (solid line) was the low behavioral risk profile with lower excitability and arousal.

*Z-Scores indicate a positive or negative deviation from the overall mean for the study population.

As shown in Table 4, a higher proportion of individuals classified in the PAE group were represented in the NNNS-I Profile 1 (64.3%) as compared to Profile 2 (59.1%) or Profile 3 (49.1%); however, differences did not reach statistical significance and all three profiles included infants with PAE. Profile 1 also included a higher proportion of individuals with ≥1 positive ethanol biomarker compared to Profile 3 (42.9% vs. 22.9%; P=0.06). Mothers of infants classified in Profile 2 had higher EDS scores during pregnancy compared to Profile 3 (9.0 ± 6.0 vs. 6.4 ± 6.1; P<0.05). Additionally, GAD-7 and PCL-5 demonstrated a trend toward increased scores in Profile 2 compared to Profile 3 (P<0.10). Thus, maternal mental health scores appear to contribute to the Profile 2 observed in this cohort.

Table 4:

Maternal Sociodemographic Characteristics and Mental Health Assessments by the Infant’s NNNS-I Profile (n=103)

Maternal Characteristic Profile 1
(n=28)		 Profile 2
(n=22)		 Profile 3
(n=53)		 P-Value1
Mean ± SD Mean ± SD Mean ± SD
PSS 11.8 ± 5.2 16.2 ± 8.6 13.3 ± 9.1 0.23
GAD-7 5.1 ± 3.9 6.9 ± 5.7* 5.0 ± 5.2 0.24
EDS 5.5 ± 4.1 9.0 ± 6.0** 6.4 ± 6.1 0.09
PCL-5 12.1 ± 12.5 17.5 ± 16.3* 12.1 ± 16.2 0.23
ACE score 2.2 ± 2.4 2.7 ± 2.7 2.0 ± 2.6 0.46
Alcohol use in periconceptional period and during pregnancy 0.06 ± 0.15 0.04 ± 0.06 0.04 ± 0.06 0.92
N (%) N (%) N (%)
Marijuana use 4 (14.3) 5 (22.7) 9 (17.0) 0.70
Tobacco use 1 (3.6) 2 (9.1) 4 (7.5) 0.77
Positive ethanol biomarker(s) 12 (42.9)# 8 (36.4) 12 (22.6) 0.28
PAE group 18 (64.3) 13 (59.1) 26 (49.1) 0.41
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PSS, Perceived Stress Scale; GAD-7, General Anxiety Disorder-7 score; EDS, Edinburgh Postnatal Depression Scale; PCL-5, Posttraumatic Stress Disorder Checklist for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition; ACE, Adverse Childhood Experiences; AAD, absolute alcohol (ounces) per day [1 AA is equivalent to ~0.5 standard drinks]

1

Based on Kruskal-Wallis or Fisher’s exam tests for difference in continuous and categorical variables across the three Profiles

*

P < 0.10, Profile 2 vs. Profile 3 comparison

**

P < 0.05, Profile 2 vs. Profile 3 comparison

#

P < 0.10, Profile 1 vs. Profile 3 comparison

Discussion

Results of our study indicate that significant differences in the NNNS-I scores were evident shortly after birth for infants with mild-to-moderate PAE. Specifically, although no infants have received a diagnosis of FASD, infants in the PAE group demonstrated lower attention, lower stress abstinence, higher lethargy, and higher hypertonicity scores, which is a unique combination. The association between PAE and attention and lethargy scores remained significant after adjustment for maternal depressive symptoms, family income, and marijuana use in pregnancy. These findings, while novel are not unexpected, given the classifications of FASD originally proposed by Hoyme et al in 1996 (Hoyme et al., 2016, Hoyme et al., 2005). In diagnosing adverse outcomes associated with PAE, specific behavioral or cognitive abnormalities are assessed that can provide supportive evidence, such as but not limited to difficulties with self-soothing, decreased infant affective functioning (emotional withdrawal), delayed gross and fine motor milestones, poor feeding, and tremulousness and increased jitteriness (Hoyme et al., 2005). As abnormal lethargy scores have previously been associated with later language, motor delays, and lower cognitive scores as assessed by the Bayley Scales of Infant and Toddler Development at 2 years of age in infant born prematurely (Spittle et al., 2017), observing abnormal lethargy scores in this population may provide insight into potential adverse outcomes similar to those described by Hoyme et al (Hoyme et al., 2016). A well-recognized challenged in the field of fetal alcohol spectrum disorder (FASD) is that a diagnosis typically cannot be made until early pre-school age unless facial and growth features are present to support a diagnosis of FASD or partial FASD. The NNNS-I assessment includes summary scales of items similar to the factors that may be used in diagnosis of FASD. Specifically, the attention and regulation summary scores may suggest deficits for an infant to focus and maintain and modulate alertness, which are observed in high risk profiles associated with lower cognitive and motor scores in early childhood (McGowan et al., 2022). Thus, there appear to be on overlap between our findings and areas of brain vulnerability associated with FASD (Hoyme et al., 2016); however, direct comparisons are not warranted and NNNS-I is not a diagnostic tool. It is important to emphasize further that our study did not examine validity of NNNS-I assessment against FASD diagnosis, but rather identified a unique neurobehavioral profile associated with mild-to-moderate PAE, which is evident shortly after birth.

The LPA conducted in our study revealed 3 NNNS-I Profiles, with Profile 1 considered high behavioral risk due to the poorly sustained attention, less self-regulation (as evidenced by higher arousal and excitability), increased handling assistance required, and poor quality of movements. Infants with positive ethanol biomarkers were more likely to be in this higher behavioral risk profile, although the presence of infants with PAE were in all profiles, highlighting the variability of clinical outcomes following PAE. Additionally, infants in Profile 3, which appears to be the low behavioral risk profile, had higher quality of movements, increased self-regulation (with decreased arousal and excitability) and increased attention. A similar profile description was noted by Sucharew, et al in a low-risk cohort of 355 infants and had Bayley Scales of Infant and Toddler Development assessments at age 12, 24, and 36 months. Overall, there were low rates of neurobehavioral compromise in this low-risk cohort (Sucharew et al., 2012). Therefore, infants in Profile 3 would be expected to have the potential for the best neurobehavioral outcomes given these findings. Additionally, Profile 2 had the lowest arousal score of the 3 profiles described. A recent study of 1,112 infants found that infants with hypo-aroused profiles were more likely to have mothers who experienced depressive symptoms prenatally (Camerota et al., 2023). Indeed, mothers of infants classified in Profile 2 had the highest Edinburgh Depression Scale scores in our study. The finding of infants with the lowest attention and lowest arousal in the group with the highest maternal depressive symptoms is consistent with a recent review of findings from NNNS assessments, in which individuals with emotion dysregulation (including depression) and greater economic hardship had infants with a “hypo-aroused” phenotype. This phenotype consisted of low attention and low arousal (Conradt et al., 2024). When any provider is assessing newborns, it is critical to consider additional factors, such as maternal mental health, given the potential impact on infant neurobehavior.

We are not aware of any prior studies which evaluated utility of NNNS in risk stratification of infants with PAE. However, other infant scales, such as the Neonatal Behavioral Assessment Scale (NBAS), focused on infants with PAE. The NBAS, also known as the Brazelton Neonatal Assessment Scale, is a descriptive assessment focused on emerging behavioral patterns with repeat testing over several days adding more value than one assessment (Brazelton, 1973). It contains some items similar to NNNS, such as self-regulation; however, there are no normative values for NBAS (Tronick and Lester, 2013, Brazelton, 1973). Additionally, the NBAS primarily focuses on the infant/caregiver interactions and is used for longitudinal assessments rather than to directly compare between clinical populations (Barlow et al., 2018, Wolf et al., 2002, Brazelton, 1973). The NBAS studies in infant with PAE have demonstrated decreased arousal (Streissguth et al., 1983). The NBAS generally provides an indication of atypical functioning, and does not provide a specific profile that can be used to potentially aide in a diagnosis or to predict outcomes (Subramoney et al., 2018).

Previously, infants with prenatal opioid exposure have been found to have poor quality of movements and self-regulation scores (Heller et al., 2017). Our findings suggest that NNNS-I might be a valuable neonatal assessment tool capable of differentiating subtle neurobehavioral differences between infants with different exposure patterns early in life. However, future studies should incorporate direct comparison of infants with different prenatal exposures in the same cohort to further delineate NNNS-I profiles. While children with facial, growth, and developmental delays may be diagnosed earlier in life (Janczewska et al., 2019), the ability to identify subtle outcomes associated with even low-to-moderate PAE in the newborn period has significant clinical implications in the ability to provide supportive care much earlier in life, given that neurobehavioral functional impairments are not typically diagnosed until later in childhood. Additionally, children may have significant neurobehavioral functional impairment due to PAE and may or may not have facial features consistent with PAE. Therefore, tools to aide in potential neurodevelopmental alteration are critically important within this population.

It is interesting to consider the possible relationship between the NNNS-I findings and later development, especially given that the NNNS-I is a single assessment, without the need for repeated exams. Infant attention has been shown to have implications for both social-communication and cognitive development (Bradshaw et al., 2020, Li et al., 2022). Thus, lower attention scores on NNNS-I at birth, as observed in our PAE population, could be an early marker of neurodevelopmental and learning outcomes which emerge later in life, such as later difficulties in school (e.g., poor attention span or difficulty completing tasks). Lower attention scores have been observed in infants who are physiologically unstable and may reflect a low threshold for stimulation, while a high lethargy score reflects more effort by the examiner to bring the infant to a stable alert state (Boukydis et al., 2004). Not surprisingly, a study utilizing the NNNS-I in infants born preterm found that increased lethargy was present in the high-risk behavioral group, and those infants were more likely to have low cognitive and motor scores at 2 years of age (McGowan et al., 2022). Another study of preterm infants found that the NNNS-I hypertonicity score was related to motor milestone attainment, with increases in the hypertonicity scores increasing the odds of a lower motor quotient (Dorner et al., 2019). Given that children with PAE have cognitive and motor delays, the findings of lower attention, higher lethargy, and higher hypertonicity during infancy may serve as early markers of future neurodevelopmental deficits. This association between NNNS scores and neurodevelopmental and behavioral outcomes at an older age needs to be evaluated in future studies.

This study has many strengths. First, the study population includes a large proportion of minoritized populations historically underrepresented in research. Second, the study incorporated a comprehensive evaluation of PAE by prospective repeated TLFB interviews which captured four 30-day periods and a state-of-the-art panel of ethanol biomarkers assessed twice. A unique finding of this study includes utilization of the NNNS-I within a population not previously tested (infants with PAE). Specifically, the focus on low-to-moderate PAE is of high public health importance given the prevalent pattern of this exposure, and the finding of changes in infants’ neuro-organization. While many individuals may not consider low alcohol exposure a concern during pregnancy (Popova et al., 2022), this study is clinically relevant and important to allow for appropriate counseling to occur.

The results of the study should be considered in the context of the several limitations of the study design. First, a relatively small sample size might have impacted our ability to detect smaller effect sizes. It also did not allow for stratification of results by infant sex and examination of interaction effects among predictors. Second, while our sample closely represented a general New Mexico population, results cannot be generalizable to all infants with low-moderate PAE. Third, while we accounted for the effects of the key confounders differentially distributed between PAE and non-PAE groups (family income, depressive symptoms, use of cannabis during pregnancy), we acknowledge that other factors might affect infant neuro-organization. While every effort has been made to standardize the NNNS-I exam administration, we acknowledge limitations of one-time assessment of neurological integrity and behavioral function. Longitudinal studies with neurodevelopmental assessments at older ages are needed to characterize predictive utility of NNNS-I assessment. Additionally, use of the NNNS-II assessment can be considered for future studies, given the improvements to the assessment including a shorter administration time and refinement to the summary scales (Brown University 2020). In summary, this is the first report which demonstrates that the NNNS-I assessment, conducted shortly after birth, may be a useful screening tool for identification of infants with greater neurobehavioral risk requiring more intensive follow-up and monitoring.

Supplementary Material

Supinfo

Acknowledgments

The authors of the paper would like to thank Dominique Rodriguez, Rajani Rai, and Sharon Ruyak for their help with data collection.

Funding

Research reported in this publication was supported by the National Institute on Alcohol Abuse and Alcoholism of the National Institutes of Health under Award Number 2R01AA021771 (P.I.: Bakhireva). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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