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Neurodevelopmental Variations Cascading from Age 10 Months to 3 Years Leading to Attention-Deficit Hyperactivity Disorder/Autism Traits at Age 9 in a General Population

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Title: Neurodevelopmental Variations Cascading from Age 10 Months to 3 Years Leading to Attention-Deficit Hyperactivity Disorder/Autism Traits at Age 9 in a General Population
Language: English
Authors: Kenji J. Tsuchiya (ORCID 0000-0002-1314-4199), Nagahide Takahashi (ORCID 0000-0002-7711-0297), Yoko Nomura (ORCID 0000-0002-2143-3257), Jeffrey H. Newcorn, Shigenobu Toda, Yuuka Ishikawa-Omori, Akemi Okumura, Mohammad Shafiur Rahman, Toshiki Iwabuchi, Taeko Harada, Ikue Hirata, Chikako Nakayasu, Yuko Amma, Haruka Suzuki, Tomoko Nishimura (ORCID 0000-0002-4776-5153)
Source: JCPP Advances. 2026 6(2).
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 10
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Descriptors: Autism Spectrum Disorders, Neurodevelopmental Disorders, Attention Deficit Hyperactivity Disorder, Children, Young Children, Motor Development, Cognitive Ability, Foreign Countries
Geographic Terms: Japan
Assessment and Survey Identifiers: Mullen Scales of Early Learning, Social Responsiveness Scale
DOI: 10.1002/jcv2.70053
ISSN: 2692-9384
Abstract: Background: Neurodevelopmental delay precedes attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) diagnoses. However, exactly when this emerges in association with these outcomes remains unclear. We investigated (1) the earliest representations of neurodevelopmental variation and (2) what neurodevelopmental variations at an early age (10 months to 3 years) are specifically associated with the emergence of parentally reported behavioral traits of ADHD, ASD, and related disorders at age 9. Methods: Children from the Hamamatsu Birth Cohort of Mothers and Children (HBC Study) born between December 2007 and March 2012 were enrolled and followed from birth to age 9. Standardized scores of neurodevelopment across five domains (gross motor, visual reception, fine motor, receptive language, and expressive language) were calculated using the Mullen Scales of Early Learning at ages 10, 14, 18, 24, 32, and 40 months. ADHD and ASD traits were ascertained as Z-scores using the ADHD-Rating Scale and Social Responsiveness Scale-2 at age 9. To explore the earliest recognition of neurodevelopmental variation with credibility, structural equation modeling (SEM) was used to estimate the total effects of the linear associations between exposures and outcomes. Results: 836 children (405 females, 48%) were enrolled in the analysis. The ADHD trait was associated with visual reception score before age 1 and was concurrent with both fine motor and receptive language scores between ages 1-2. The ASD trait was associated with gross motor score before age 1 and expressive language score between ages 1.5 and 3. Conclusion: Suboptimal visual-motor coordination can be a prototype of the ADHD trait, while a cascading pattern of suboptimalities from gross motor to language domains can be a prototype of the ASD trait. The distinct neurodevelopmental variations related to ADHD and ASD traits running in the general population can be found before age 1.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1508683
Database: ERIC
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  Value: <anid>AN0194549431;[n7e5]01jun.26;2026Jun16.03:41;v2.2.500</anid> <title id="AN0194549431-1">Neurodevelopmental variations cascading from age 10 months to 3 years leading to attention‐deficit hyperactivity disorder/autism traits at age 9 in a general population </title> <p>Background: Neurodevelopmental delay precedes attention‐deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) diagnoses. However, exactly when this emerges in association with these outcomes remains unclear. We investigated (<reflink idref="bib1" id="ref1">1</reflink>) the earliest representations of neurodevelopmental variation and (<reflink idref="bib2" id="ref2">2</reflink>) what neurodevelopmental variations at an early age (10 months to 3 years) are specifically associated with the emergence of parentally reported behavioral traits of ADHD, ASD, and related disorders at age 9. Methods: Children from the Hamamatsu Birth Cohort of Mothers and Children (HBC Study) born between December 2007 and March 2012 were enrolled and followed from birth to age 9. Standardized scores of neurodevelopment across five domains (gross motor, visual reception, fine motor, receptive language, and expressive language) were calculated using the Mullen Scales of Early Learning at ages 10, 14, 18, 24, 32, and 40 months. ADHD and ASD traits were ascertained as Z‐scores using the ADHD‐Rating Scale and Social Responsiveness Scale‐2 at age 9. To explore the earliest recognition of neurodevelopmental variation with credibility, structural equation modeling (SEM) was used to estimate the total effects of the linear associations between exposures and outcomes. Results: 836 children (405 females, 48%) were enrolled in the analysis. The ADHD trait was associated with visual reception score before age 1 and was concurrent with both fine motor and receptive language scores between ages 1–2. The ASD trait was associated with gross motor score before age 1 and expressive language score between ages 1.5 and 3. Conclusion: Suboptimal visual‐motor coordination can be a prototype of the ADHD trait, while a cascading pattern of suboptimalities from gross motor to language domains can be a prototype of the ASD trait. The distinct neurodevelopmental variations related to ADHD and ASD traits running in the general population can be found before age 1.</p> <p>Key Points: What's known?Neurodevelopmental delay during infancy and early childhood, including motor delay, is associated with attention‐deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) traits, although the findings are inconsistent.The earliest timing of the emergence of the delay is not precisely known. What's new?In a representative birth cohort of a general population (N = 836), variations in visual reception before age 1 and in both fine motor and receptive language between ages 1–2 were associated with the ADHD trait at age 9.Variations in gross motor before age 1 and in expressive language between ages 1.5 and 3 were associated with the ASD trait at age 9. What's relevant?The earliest representations of ADHD and ASD traits can be recognized before age 1, cascading separate sets of suboptimal neurodevelopment.</p> <p>Keywords: attention deficit hyperactivity disorder; autism spectrum disorder; Birth Cohort; developmental coordination disorder; intellectual developmental disorder; neurodevelopment</p> <p>Associations of neurodevelopmental measures (<emph>Z</emph>‐scores of gross motor, visual reception, fine motor, receptive language, expressive language) at ages 10, 14, 18, 24, 32, and 40 months with (a) attention‐deficit/hyperactivity disorder trait, (b) autism spectrum disorder trait, (c) developmental coordination disorder trait, and (d) intellectual developmental disorder trait at age 9 years.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/N7E5/01jun26/jcv270053-toc-0001.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jcv270053-toc-0001.jpg" title="." /> </p> <p></p> <hd id="AN0194549431-3">INTRODUCTION</hd> <p>Attention‐deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are defined in the Diagnostic and Statistical Manual of Mental Disorder, 5th Edition Text Revision (DSM‐5‐TR): ADHD is characterized by inattention and hyperactivity, while ASD is characterized by social impairments and repetitive and restricted patterns of behaviors (American Psychiatric Association, [<reflink idref="bib2" id="ref3">2</reflink>]). Despite the differences, distinguishing between the two conditions remain challenging, as they often coexist (Shoaib et al., [<reflink idref="bib38" id="ref4">38</reflink>]). Both belong to a supra‐category of neurodevelopmental disorders (NDDs) that have common features of atypical neurodevelopment and poor functioning in early childhood (Finlay‐Jones et al., [<reflink idref="bib14" id="ref5">14</reflink>]; Thapar & Rutter, [<reflink idref="bib42" id="ref6">42</reflink>]). In particular, the neurobiological changes occurring in children with ADHD and/or ASD may involve overlapping features, often referred to as endophenotypes (Johnson et al., [<reflink idref="bib25" id="ref7">25</reflink>]). Moreover, suboptimal neurodevelopmental patterns, when considered as candidate early markers of NDDs, can be confirmed well before formal diagnoses (Kaczkurkin et al., [<reflink idref="bib26" id="ref8">26</reflink>]).</p> <p>Recent studies examining the underlying pathophysiology of ADHD and/or ASD have focused on non‐specific neurodevelopmental delay, particularly motor skills. Studies have shown that motor difficulties are frequently found in children and adolescents with ADHD and ASD, and that the types of motor difficulties differ between ADHD and ASD (Ament et al., [<reflink idref="bib1" id="ref9">1</reflink>]; Biscaldi et al., [<reflink idref="bib7" id="ref10">7</reflink>]; De Francesco et al., [<reflink idref="bib12" id="ref11">12</reflink>]). In turn, motor delay in infancy can serve as the earliest representation of NDDs, the ASD trait in particular (Estes et al., [<reflink idref="bib13" id="ref12">13</reflink>]; Iverson et al., [<reflink idref="bib24" id="ref13">24</reflink>]; Ozonoff et al., [<reflink idref="bib35" id="ref14">35</reflink>]), a protype cascading suboptimal neurodevelopment across more than one neurodevelopmental domains (Athanasiadou et al., [<reflink idref="bib3" id="ref15">3</reflink>]; Bowler et al., [<reflink idref="bib8" id="ref16">8</reflink>]; Lim et al., [<reflink idref="bib29" id="ref17">29</reflink>]; Shephard et al., [<reflink idref="bib37" id="ref18">37</reflink>]; West, [<reflink idref="bib47" id="ref19">47</reflink>]). Motor skills are divided into two domains: the gross motor domain of body movements using major skeletal muscles and the fine motor domain of hand and finger movements that require visual processing (Mullen, [<reflink idref="bib30" id="ref20">30</reflink>]). An association of gross motor delay with ADHD was indicated, although the effect size was small (Bowler et al., [<reflink idref="bib8" id="ref21">8</reflink>]), whereas the association of gross motor delay with ASD was consistent and the effect size became larger as the child became older (≥ age 2) (Lim et al., [<reflink idref="bib29" id="ref22">29</reflink>]; West, [<reflink idref="bib47" id="ref23">47</reflink>]). Inconsistencies remain in studies of the association of fine motor skills with ADHD and ASD symptoms or diagnoses (Havmoeller et al., [<reflink idref="bib22" id="ref24">22</reflink>]; Kaiser et al., [<reflink idref="bib27" id="ref25">27</reflink>]; Lim et al., [<reflink idref="bib29" id="ref26">29</reflink>]). This suggests that early motor skills are not directly related to outcomes such as ADHD and/or ASD but instead connected with delays in different neurodevelopmental domains that cascade with age.</p> <p>To analyze this, we need further research in several areas. First, the specific timing of when neurodevelopmental delay occurs. What are the earliest representations? Can we confirm the association of neurodevelopmental delay to outcomes at specific ages? This requires: (<reflink idref="bib1" id="ref27">1</reflink>) A longitudinal design with a large sample of children in early childhood. Trajectory studies based on mixed modeling (Nishimura et al., [<reflink idref="bib33" id="ref28">33</reflink>]; Nishimura et al., [<reflink idref="bib34" id="ref29">34</reflink>]) provided statistical indices such as slope and intercept. However, these statistics have not elucidated the exact timing of the suboptimality. Additionally, correlations among a series of measures of neurodevelopmental variations measures should be taken into consideration; without such a consideration, the magnitude of the associations of neurodevelopmental delay with the later emergence of ADHD and/or ASD may be overestimated along with age. To address this issue, structural equation modeling (SEM) is needed instead of an iteration of independent regression analyses. (<reflink idref="bib2" id="ref30">2</reflink>) Cross‐domain specificity. It has been suggested that delay in motor skill‐related domains—visuomotor and audiomotor integration and language in particular (Bhat, [<reflink idref="bib6" id="ref31">6</reflink>]; Carsone et al., [<reflink idref="bib9" id="ref32">9</reflink>]; Hadar et al., [<reflink idref="bib20" id="ref33">20</reflink>]; Kaiser et al., [<reflink idref="bib27" id="ref34">27</reflink>]; Tirosh et al., [<reflink idref="bib43" id="ref35">43</reflink>])—are associated with ADHD, ASD, and other NDDs (Nishimura et al., [<reflink idref="bib33" id="ref36">33</reflink>]; Nishimura et al., [<reflink idref="bib34" id="ref37">34</reflink>]; Takahashi et al., [<reflink idref="bib40" id="ref38">40</reflink>]). To examine this delay, standardized child composite scales to measure gross and fine motor domains, as well as visual and language domains, throughout childhood are needed (Mullen, [<reflink idref="bib30" id="ref39">30</reflink>]). (<reflink idref="bib3" id="ref40">3</reflink>) An examination of outcome‐specificity. Are neurodevelopmental domains associated with either ADHD or ASD, or both? Considering that the majority of children with a clinical diagnosis of a specific NDD have a co‐existing trait of another NDD diagnosis (Hong et al., [<reflink idref="bib23" id="ref41">23</reflink>]; Shoaib et al., [<reflink idref="bib38" id="ref42">38</reflink>]), we would expect dimensional measures of ADHD and ASD traits to be the outcome of interest instead of a formal diagnosis. Indeed, studies based on clinical diagnoses of ADHD and/or ASD might have obscured the trait‐specific relevance of neurodevelopment to the emergence of the ADHD and ASD traits (Goulardins et al., [<reflink idref="bib17" id="ref43">17</reflink>]; Havmoeller et al., [<reflink idref="bib22" id="ref44">22</reflink>]). This approach would further allow us to detect patterns of suboptimal neurodevelopmental variations leading to multiple traits of NDDs, as well as traits of other overlapping NDDs, such as developmental coordination disorder (DCD) and intellectual developmental disorder (IDD) (Verbecque et al., [<reflink idref="bib45" id="ref45">45</reflink>]).</p> <p>This study followed a large general population sample from infancy to late childhood to examine whether early neurodevelopmental variations from age 10 months to 3 years are linearly associated with parentally reported behavioral traits of ADHD and/or ASD at age 9. We also examined whether the variations could also be related to the DCD and IDD traits as reference.</p> <hd id="AN0194549431-4">METHODS</hd> <p></p> <hd id="AN0194549431-5">Participants</hd> <p>A total of 836 infants born between December 24, 2007, and March 9, 2012, who originally participated in the Hamamatsu Birth Cohort for Mothers and Children (HBC Study) (Takagai et al., [<reflink idref="bib39" id="ref46">39</reflink>]; Tsuchiya et al., [<reflink idref="bib44" id="ref47">44</reflink>]), and were followed up to age 9, were regarded eligible and thus included in the analysis. All the participating children were born in the university hospital of the Hamamatsu University School of Medicine. 99% of the participating children speak Japanese as their first language. Participating children included 80 sibling pairs (14 twin pairs) and 1 set of a sibling trio, which were accounted for in the SEM analysis using robust standard errors.</p> <hd id="AN0194549431-6">Measures of interest</hd> <p>The ADHD, ASD, DCD, and IDD traits were ascertained as dimensional measures of outcome at age 9 using the ADHD‐Rating Scale (ADHD‐RS), Social Responsiveness Scale‐2 (SRS‐2), Developmental Coordination Disorder Questionnaire (DCDQ), and the Wechsler Intelligence Scale for Children, 4th version (WISC‐IV). All the rating scales have been standardized for Japanese children (Kamio et al., [<reflink idref="bib28" id="ref48">28</reflink>]; Nakai et al., [<reflink idref="bib31" id="ref49">31</reflink>]; Nihonban WISC‐IV Kankō Iinkai, [<reflink idref="bib32" id="ref50">32</reflink>]; Tanaka et al., [<reflink idref="bib41" id="ref51">41</reflink>]). To compare across measures, we made a single index from each of the scales: standardized percentile score of ADHD‐RS (range 0 to 100) for the measure of the ADHD trait, standardized total <emph>T</emph>‐score of SRS‐2 (range 40 to 90) for the ASD trait, DCDQ total score (range 15 to 75) for the DCD trait, and full‐scale IQ (range 47 to 145) as measured by the WISC‐IV for the IDD trait. We further converted these scores into <emph>Z</emph>‐scores with a mean of 0 and standard deviation of 1. In addition, high scores on the ADHD‐RS and SRS‐2 represented suboptimal outcomes, with the DCDQ and WISC‐IV scales reflecting the opposite. For comparability, we reversed the signs of ADHD and ASD trait scores. This gave us four <emph>Z</emph>‐converted measures of ADHD, ASD, DCD, and IDD traits at age 9, with a lower score indicating more prone to suboptimality, to use in the analyses. The correlation matrix of the trait measures is provided in Table S1. The distribution of the trait measures is provided in Figure S1.</p> <p>We measured the neurodevelopmental variations of the participating children at approximately 10, 14, 18, 24, 32, and 40 months after birth using the Mullen Scales of Early Learning (MSEL) (Mullen, [<reflink idref="bib30" id="ref52">30</reflink>]). The MSEL provides standardized scores in five domains of neurodevelopment (gross motor, visual reception, fine motor, receptive language, and expressive language). The mean standard <emph>T</emph>‐score of each domain for every month between 1 and 50 after birth was set at 50, with an SD of 10, standardized for Japanese children (Nishimura et al., [<reflink idref="bib34" id="ref53">34</reflink>]). The MSEL assessment was conducted through a face‐to‐face interview by well‐trained examiners blind to the previous status of the assessments. This gave us <emph>T</emph>‐scores of the five domains for six time points (<reflink idref="bib10" id="ref54">10</reflink>, 14, 18, 24, 32, and 40 months). Examples of items included in the MSEL are shown in Table S2. The <emph>T</emph>‐scores were further converted to <emph>Z</emph>‐scores with a mean of 0 and standard deviation of 1 throughout the analyses below. The distribution of the <emph>Z</emph>‐converted domain scores is provided in Figure S2.</p> <p>Child's sex, birth order, and maternal educational achievement in years were included in the analyses as covariates as they showed potential associations with neurodevelopment, related to the ADHD, ASD, DCD, and IDD traits.</p> <hd id="AN0194549431-7">Analytical plan</hd> <p>To minimize the number of statistical tests as well as handle missingness (approximately 5% to 10% occurring at each wave), SEM with the full‐information maximum likelihood option, with robust standard errors applied for a consideration of clustering effects of siblings and twins, was applied to the analyses. Linear associations between the neurodevelopmental measures and the outcomes of interest were assessed using SEM in four separate longitudinal models. Neurodevelopmental measures in five domains at any age were assumed to predict all the <emph>Z</emph>‐scores of all the domains as the child grew. As such, all the possible paths across the domains and timings are drawn. A summary scheme of the analysis is shown in a directed acyclic graph (Figure 1). As we were not interested in segregating direct and indirect pathways leading to a trait of specific NDD, we reported total effects based on standardized regression coefficients with robust standard errors, adjusted for covariates. This also allowed us to account for any clustering effect of siblings or twins. The cutoff for two‐sided <emph>p</emph>‐values was set at 0.05. All analyses were conducted using Stata version 18.0 (Stata Corp).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/N7E5/01jun26/jcv270053-fig-0001.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jcv270053-fig-0001.jpg" title="1 The analyses plan of this study using a directed acyclic graph. Each observation through 10–40 months (green ovals with triangles, exposure variables) involves face‐to‐face observation of developmental measures in domains of gross motor, visual reception, fine motor, receptive language, and expressive language using Mullen Scales of Early Learning. The T‐scores provided of the five domains were converted to Z‐score before analyses. For the ease of comprehension, we denoted each observation as one oval, although the actual analyses were conducted in the manner that all the five Z‐scores from the five neurodevelopmental domains were separately entered into the model. The outcome variables (blue ovals with I) involve attention‐deficit/hyperactivity disorder, autism spectrum disorder, DCD, and IDD trait scores. Potential confounding was considered: three covariates (child sex, birth order, maternal educational history in years, shown in pink ovals) were adjusted for in every association between any of the exposure and of outcome variable that emerged in this structural equation modeling. DCD, developmental coordination disorder; IDD, intellectual developmental disorder." /> </p> <p></p> <hd id="AN0194549431-9">RESULTS</hd> <p></p> <hd id="AN0194549431-10">Participants and sample</hd> <p>Table 1 shows the characteristics of the participating children (<emph>N</emph> = 836). We observed no predominance in female or male participants, history of premature birth, or underachievement in maternal educational history. The overall sample characteristics corresponded well with Japanese children of equivalent ages: the ADHD, ASD, DCD, and IDD trait scores showed no departure from the population norm (Table 2).</p> <p>1 TABLE Characteristics of the participating children (N = 836).</p> <p> <ephtml> <table><thead valign="bottom"><tr><th /><th align="left"><italic>N</italic> (%) or mean (SD)</th></tr></thead><tbody valign="top"><tr><td>Demographic data</td></tr><tr><td>Number of children</td><td>836</td></tr><tr><td>Child sex (female)</td><td>405 (48%)</td></tr><tr><td>Birth order (first‐born)</td><td>420 (50%)</td></tr><tr><td>Gestational age at birth (weeks)</td><td>38.9 (1.6)</td></tr><tr><td>Prematurity (<37 weeks)</td><td>62 (7%)</td></tr><tr><td>Maternal education (years)</td><td>14.0 (1.9)</td></tr><tr><td>Behavioral representations at age 9</td></tr><tr><td>ADHD trait (ADHD‐RS, total percentile score before conversion to inverted Z‐score)</td><td>51.8 (29.0)</td></tr><tr><td>ASD trait (SRS‐2, standardized total T‐score before conversion to inverted Z‐score)</td><td>51.0 (9.9)</td></tr><tr><td>DCD trait (DCDQ, total score before conversion to Z‐score)</td><td>57.7 (10.0)</td></tr><tr><td>IDD trait (WISC‐IV, full‐scale IQ before conversion to Z‐score)</td><td>101.0 (14.0)</td></tr></tbody></table> </ephtml> </p> <p>1 Abbreviations: ADHD, attention‐deficit/hyperactivity disorder; ASD, autism spectrum disorder; DCD, developmental coordination disorder; IDD, intellectual developmental disorder; WISC‐IV, the Wechsler Intelligence Scale for Children, 4th version.</p> <p>2 TABLE Neurodevelopmental domain scores of the participating children at 10, 14, 18, 24, 32, and 40 months (N = 836).</p> <p> <ephtml> <table><thead valign="bottom"><tr><th /><th>Mean (SD)</th></tr><tr><th>Neurodevelopmental domains</th><th align="left">10 months</th><th align="left">14 months</th><th align="left">18 months</th><th align="left">24 months</th><th align="left">32 months</th><th align="left">40 months</th></tr></thead><tbody valign="top"><tr><td>Gross motor at 10 months (N = 797)</td><td align="char" char="(">46.9 (9.6)</td><td align="char" char="(">48.3 (10.6)</td><td align="char" char="(">49.2 (9.8)</td><td align="char" char="(">48.7 (10.0)</td><td align="char" char="(">49.0 (10.3)</td><td align="char" char="(">49.7 (10.0)</td></tr><tr><td>Visual reception at 10 months (N = 796)</td><td align="char" char="(">48.3 (10.6)</td><td align="char" char="(">48.8 (9.6)</td><td align="char" char="(">48.7 (9.7)</td><td align="char" char="(">49.6 (10.3)</td><td align="char" char="(">49.1 (9.5)</td><td align="char" char="(">50.2 (10.3)</td></tr><tr><td>Fine motor at 10 months (N = 796)</td><td align="char" char="(">48.1 (10.2)</td><td align="char" char="(">48.8 (9.8)</td><td align="char" char="(">49.5 (9.8)</td><td align="char" char="(">48.4 (9.7)</td><td align="char" char="(">49.4 (10.2)</td><td align="char" char="(">50.8 (10.3)</td></tr><tr><td>Receptive language at 10 months (N = 794)</td><td align="char" char="(">48.0 (10.0)</td><td align="char" char="(">49.7 (9.7)</td><td align="char" char="(">48.7 (9.7)</td><td align="char" char="(">50.1 (10.0)</td><td align="char" char="(">49.7 (9.3)</td><td align="char" char="(">50.0 (9.8)</td></tr><tr><td>Expressive language at 10 months (N = 788)</td><td align="char" char="(">47.9 (9.6)</td><td align="char" char="(">49.3 (10.3)</td><td align="char" char="(">48.8 (9.3)</td><td align="char" char="(">49.4 (9.8)</td><td align="char" char="(">49.2 (9.9)</td><td align="char" char="(">50.0 (10.2)</td></tr></tbody></table> </ephtml> </p> <p>2 <emph>Note</emph>: <emph>T</emph>‐scores of Mullen Scales of Early Learning with a population mean set of 50 and SD of 10 before conversion to <emph>Z</emph>‐score.</p> <hd id="AN0194549431-11">Main analysis</hd> <p>Figure 2A shows that a gross motor domain score was not associated with the ADHD trait at age 9. However, scores in visual reception (10 and 40 months), in fine motor (<reflink idref="bib14" id="ref55">14</reflink>, 18, 40 months), and in receptive language (14 months) domains were associated with the ADHD trait at age 9.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/N7E5/01jun26/jcv270053-fig-0002.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jcv270053-fig-0002.jpg" title="2 Associations of neurodevelopmental measures (Z‐scores of gross motor, visual reception, fine motor, receptive language, expressive language) at ages 10, 14, 18, 24, 32, and 40 months with (A) ADHD trait, (B) ASD trait, (C) DCD trait, and (D) IDD trait at age 9 years. Circles with colors indicate statistically significant associations with p <.05. Size of the circles represent standardized regression coefficients. Hollow circles indicate inverse associations. (A) ADHD trait (green): inverted Z‐converted ADHD‐RS percentile score. (B) ASD trait (blue): inverted Z‐converted SRS‐2 total T‐score. (C) DCD trait (yellow): Z‐converted Developmental Coordination Disorder Questionnaire total score. (D) IDD trait (red): Z‐converted full‐scale IQ. ADHD, attention‐deficit/hyperactivity disorder; ASD, autism spectrum disorder; DCD, developmental coordination disorder; IDD, intellectual developmental disorder." /> </p> <p></p> <p>Figure 2B shows that scores in gross motor (10 and 18 months), in fine motor (40 months), and in expressive language (<reflink idref="bib18" id="ref56">18</reflink>, 24, 32 months) domains were associated with the ASD trait at age 9.</p> <p>Figure 2C shows that scores in gross motor (<reflink idref="bib10" id="ref57">10</reflink>, 14, 18 months), in visual reception (18 months), and in fine motor (<reflink idref="bib32" id="ref58">32</reflink>, 40 months) domains were associated with the DCD trait at age 9.</p> <p>Figure 2D shows that scores in visual reception (<reflink idref="bib18" id="ref59">18</reflink>, 24, 32, 40 months), in fine motor (<reflink idref="bib14" id="ref60">14</reflink>, 24, 32, 40 months), in receptive language (40 months) and in expressive language (<reflink idref="bib10" id="ref61">10</reflink>, 18, 32, 40 months) domains were associated with the IDD trait (<emph>Z</emph>‐score of full‐scale IQ) at age 9. Gross motor score at 24 months were inversely associated with the IDD trait.</p> <p>The full results of the findings above are presented in Table S3. Also, the full results of the analysis using separate linear regression analyses instead of SEM are presented in Table S4. To see whether children with a suboptimal neurodevelopmental status potentially exhibited clinical concerns, proportions of children with subthreshold ADHD, ASD, DCD, and IDD trait scores (threshold set at −1.5 SD at age 9) by neurodevelopmental status (< −1SD, within ± 1SD, > +1SD) in five neurodevelopmental domains at ages 10–40 months are presented in Table S5.</p> <hd id="AN0194549431-13">DISCUSSION</hd> <p></p> <hd id="AN0194549431-14">Main findings</hd> <p>Based on our longitudinal study, with its large representative sample, we found that (<reflink idref="bib1" id="ref62">1</reflink>) variations in early (<age 2) visual reception, in fine motor and receptive language between ages 1–2, and in late (≥age 3) visual reception, were specifically associated with the ADHD trait at age 9; (<reflink idref="bib2" id="ref63">2</reflink>) variations in early (<age 2) gross motor and expressive language between ages 1.5–3 were specifically associated with the ASD trait at age 9; (<reflink idref="bib3" id="ref64">3</reflink>) variation in late (≥age 3) fine motor was associated with ADHD, ASD, DCD, and IDD traits. As expected, gross motor and fine motor were both associated with the DCD trait, and neurodevelopmental variation in all the domains except for gross motor was associated with the IDD trait (IQ). Considering the direction of the linear associations, early visual reception suboptimality followed by fine motor and receptive language suboptimalities were associated with an elevated level of the ADHD trait, and early gross motor suboptimality followed by expressive language suboptimality were associated with an elevated level of the ASD trait.</p> <hd id="AN0194549431-15">Suboptimal neurodevelopmental variations leading to the ADHD trait</hd> <p>Our study did not support an association of early gross motor delay with the ADHD trait, unlike an early study (Gurevitz et al., [<reflink idref="bib19" id="ref65">19</reflink>]). Explanations for the inconsistency include lack of consideration of DCD in children diagnosed for ADHD in early studies (Havmoeller et al., [<reflink idref="bib22" id="ref66">22</reflink>]), and a reflection of a concurrent link between hyperactivity and activities involving gross motor skills (Goulardins et al., [<reflink idref="bib17" id="ref67">17</reflink>]). In the present study, an inverse association of gross motor development, though insignificant, was observed at 14 months (Table S1)—an inverse direction of gross motor influence before age 1 (Havmoeller et al., [<reflink idref="bib22" id="ref68">22</reflink>])—implying that a link between early gross motor skills and the ADHD trait is not supported in a general population.</p> <p>In turn, fine motor delay, measured with activities that involve visual information processing coordinated with motor skills (Goto et al., [<reflink idref="bib16" id="ref69">16</reflink>]), has been consistently reported in cross‐sectional and case‐control studies (Kaiser et al., [<reflink idref="bib27" id="ref70">27</reflink>]). Our findings were consistent with these, as early fine motor delay before age 2 was associated with the ADHD trait. Beyond the limitation of cross‐sectional and case‐control studies, one prospective study suggested that children who are later diagnosed as ADHD are likely to show fine motor delay as early as age 1 (Gurevitz et al., [<reflink idref="bib19" id="ref71">19</reflink>]). The present study is in line with the above finding.</p> <p>Our analysis found that visual reception delay, which involves the ability to decode visual input, during very early life (<age 1) and later (>age 3) was associated with the ADHD trait. Furthermore, we found a progressive pattern of very early visual reception delay leading to fine motor delay between ages 1–2. We assume these progressive patterns will also affect development of visual‐motor integration (VMI). VMI skills emerge in early childhood and are a key component leading to meaningful activities (Dankert et al., [<reflink idref="bib11" id="ref72">11</reflink>]). In composite scales like MSEL, the fine motor domain can capture VMI skills in items such as "imitates four‐block train using blocks" (Mullen, [<reflink idref="bib30" id="ref73">30</reflink>]). Of note, delays in both visual reception and fine motor domains after age 1 are consistently associated with the IDD trait (lower IQ) in the present study; this is in line with studies including IDD that have reported difficulties in VMI (Carsone et al., [<reflink idref="bib9" id="ref74">9</reflink>]), and point to the relevance of early suboptimal VMI skills as a prototype of the ADHD and IDD traits later in childhood.</p> <p>One meta‐analytic study suggested that language delay below age 5 is associated with an ADHD diagnosis (Shephard et al., [<reflink idref="bib37" id="ref75">37</reflink>]). However, the studies included in the meta‐analysis did not separate the influence derived from co‐existing conditions such as ASD, raising the possibility that the association between language delay and an ADHD diagnosis might reflect a co‐existing ASD trait: our data supports this interpretation.</p> <p>We can also present a novel finding: neurodevelopmental delay specifically in receptive language development at only 14 months is uniquely associated with the later ADHD trait. This may reflect underlying attention network development (Posner et al., [<reflink idref="bib36" id="ref76">36</reflink>]), as receptive language skills require sustained attention to others' verbal output and aligns with theoretical frameworks suggesting that early executive dysfunction, particularly in attention and response regulation, represents a core feature of ADHD (Christoforou et al., [<reflink idref="bib10" id="ref77">10</reflink>]; Posner et al., [<reflink idref="bib36" id="ref78">36</reflink>]).</p> <hd id="AN0194549431-16">Suboptimal neurodevelopmental variations leading to the ASD trait</hd> <p>In line with early reviews (Lim et al., [<reflink idref="bib29" id="ref79">29</reflink>]; West, [<reflink idref="bib47" id="ref80">47</reflink>]), early gross motor delay—"a base for learning" in early childhood (Mullen, [<reflink idref="bib30" id="ref81">30</reflink>])—was associated with the ASD trait. However, the association was supported only before age 2. The most likely explanation for no association for ≥ age 2 is that we ran SEM to consider earlier neurodevelopmental measures that might explain later ones (Tables S3 and S4). This left the possibility that gross motor domain scores at ≥ age 2 are associated with the ASD trait if the scores before age 2 are not considered and that our study is not necessarily inconsistent with early studies. Nevertheless, our study design allows us to assert that gross motor delay emerging as early as < age 1 can be the earliest presentation of the ASD trait seen later in life.</p> <p>In MSEL, language skills are measured in two domains: receptive and expressive language. The receptive language domain concerns the ability to respond to and decode other's verbal outputs, whereas the expressive language domain covers the auditory processes coupled with the use of vocal responses and spoken language (Mullen, [<reflink idref="bib30" id="ref82">30</reflink>]). Early studies have suggested that language delay is associated with the emergence of ASD symptoms or diagnosis later in life (Hansen et al., [<reflink idref="bib21" id="ref83">21</reflink>]; Zwaigenbaum et al., [<reflink idref="bib49" id="ref84">49</reflink>]). Our data provided support for the relevance of delayed expressive language development observed between ages 1.5 to 3, specifically to the ASD trait in a general population. Intriguingly, expressive language delay does not emerge before age 1 and appears to follow the gross motor delay that emerges at 10 months (Figure 2B), which is in line with results of a meta‐analytic study supporting neurodevelopmental delay in both gross motor and expressive language domains in children at an increased risk of ASD (Garrido et al., [<reflink idref="bib15" id="ref85">15</reflink>]), and with a longitudinal study showing that gross motor delay precedes expressive language delay (Bedford et al., [<reflink idref="bib5" id="ref86">5</reflink>]). We suggest that a progression from an early gross motor delay to expressive language delay is a specific underpinning, or prototype, of the ASD trait.</p> <p>Visual reception delay was not specifically associated with the ASD trait in our study, despite the existing literature consistently demonstrating the relevance of delayed VMI development in children with ASD (Bhat, [<reflink idref="bib6" id="ref87">6</reflink>]; Carsone et al., [<reflink idref="bib9" id="ref88">9</reflink>]; Wu et al., [<reflink idref="bib48" id="ref89">48</reflink>]). Of note, an early study pointed out that young children with ASD symptoms showed lower scores in VMI skills, although the scores were independent of language skills (Barbeau et al., [<reflink idref="bib4" id="ref90">4</reflink>]). Our understanding of this apparent inconsistency is that children with the ASD trait later in life may have concurrent but distinct neurodevelopmental processes of visual‐motor delay and audio‐motor delay, including delayed language production.</p> <hd id="AN0194549431-17">Non‐specific suboptimal neurodevelopmental variations</hd> <p>Fine motor delay at 40 months was related to NDD traits in general. At 40 months, 50% of children are expected to achieve "cuts with scissors" or "draws line in paths" (Mullen, [<reflink idref="bib30" id="ref91">30</reflink>]). Clearly, skills that develop at this late stage require visual and auditory processes as well as motor coordination to sensory processes. Since these items do not specifically assess fine motor skills nor VMI skills, we should not treat fine motor skills at 40 months in line with early fine motor skills before age 2.</p> <p>Of note, the measures for ADHD and ASD traits are significantly correlated with each other with <emph>r</emph> = 0.49 (Table S1), indicating that the variance of one measure accounts for approximately 25% of the other. The overlapping construct of the two traits may be predicted by non‐specific suboptimal neurodevelopmental variations such as fine motor delay at 40 months.</p> <hd id="AN0194549431-18">Clinical implications</hd> <p>The present study provides valuable information for developmental medicine. First, to date the early neurodevelopmental indicators leading to ADHD are not well understood (Visser et al., [<reflink idref="bib46" id="ref92">46</reflink>]). Our results imply that it is possible to identify children as young as age 2 who are later found to have possible ADHD. This highlights the importance of transdiagnostic observation and flexible intervention strategies that accommodate behavioral profiles, rather than relying solely on categorical diagnoses in early childhood. Second, studies have argued whether gross motor delay found in children with ADHD may or may not be accounted for by co‐existing DCD (Goulardins et al., [<reflink idref="bib18" id="ref93">18</reflink>]; Goulardins et al., [<reflink idref="bib17" id="ref94">17</reflink>]). Since our data suggest that gross motor delay was not associated with the ADHD trait, early gross motor delay found in children who later have an ADHD diagnosis are likely to develop DCD trait. Third, since our study design is free from clinical diagnostic categories, an early neurodevelopmental course leading to multiple NDD presentations can be extracted simply by superimposing the neurodevelopmental courses for each of the specific NDD traits. For instance, gross motor delay together with visual reception delay before age 1 and without delay in any other domain may suggest a later emergence of both ADHD and ASD traits; the additional observation of delays in gross motor, fine motor, and language domains between ages 1–1.5, further supports the likelihood of the emergence and co‐occurrence of the two traits.</p> <hd id="AN0194549431-19">Limitations</hd> <p>Since our findings are based on the total effects of SEM models, with earlier neurodevelopmental measures explaining later ones, and since our outcomes of interest were not clinical diagnoses, the assessment of predictive validity for clinical populations using the developmental measures was not allowed. Indeed, the associations we found were linear in nature and the proportion of children who showed ASD trait score below −1.5SD among those with neurodevelopmental scores below −1SD was approximately 10%–20% (Table S5). Also, the assessments of the NDD traits were parent‐reported and questionnaire‐based, which might have introduced information biases.</p> <hd id="AN0194549431-20">CONCLUSION</hd> <p>Early suboptimal neurodevelopmental variations or delay, as early as age 1, are connected with ADHD and ASD traits in a general population. Trait‐specific cascading patterns leading to the ADHD trait can be seen in visual motor integration skills: early visual reception delay, before age 1, is followed by delays in fine motor and receptive language domains before age 2. The corresponding pattern leading to the ASD trait was shown in a progressive pattern in motor and language development: gross motor delay before age 1 followed by expressive language delay between ages 1.5 to 3.</p> <hd id="AN0194549431-21">AUTHOR CONTRIBUTIONS</hd> <p> <bold>Kenji J. Tsuchiya</bold>: Conceptualization; methodology—protocol; data curation; formal analysis; investigation; writing—original draft, reviewing and editing; funding acquisition. <bold>Nagahide Takahashi</bold>: Conceptualization; methodology—reviewing; investigation; writing—original draft, reviewing and editing. <bold>Yoko Nomura, Jeffrey H. Newcorn, Shigenobu Toda</bold>: Methodology—reviewing; investigation—interpretation of the data; writing—reviewing and editing. <bold>Yuuka Ishikawa‐Omori, Akemi Okumura, Mohammad Shafiur Rahman</bold>: Methodology—reviewing; data curation; writing—reviewing and editing; funding acquisition. <bold>Toshiki Iwabuchi, Taeko Harada, Ikue Hirata, Chikako Nakayasu, Yuko Amma, Haruka Suzuki</bold>: Methodology—reviewing; data curation; writing—reviewing and editing. <bold>Tomoko Nishimura</bold>: Conceptualization; methodology—reviewing; data curation; investigation; writing—reviewing and editing; project administration and supervision; funding acquisition. <bold>Tomoko Nishimura</bold> also served as the statistical expert for this research.</p> <hd id="AN0194549431-22">ACKNOWLEDGMENTS</hd> <p>The authors thank the children and families who participated in the study. The authors thank Drs. Manabu Wakuta, Yosuke Kameno, Daisuke Kurita, Kiyokazu Takebayashi, Masamichi Yokokura, Tomoyasu Wakuda, Thanseem Ismail, Keiko Iwata, Yasuhide Iwata, Emiko Kawai, Masayoshi Kawai, Yujin K Kuroda, Tsuruko Mori, Kyoko Nakaizumi, Anitha A Pillai, Yui Seno, Chie Shimmura, Genichi Sugihara, Katsuaki Suzuki, Kohei Yamada, Shigeyuki Yamamoto, Yujiro Yoshihara, Kazunao Suzuki, Kyuya Hirai, Toshiyuki Uchida, Hirotake Murakami, Toshiaki Shibata, Chizuko Yaguchi, Professor Hideo Matsuzaki, Professor Hidenori Yamasue, Professor Atsushi Senju, Professor Kazuhiko Nakamura, Professor Shiro Suda, Professor Norio Mori, Professor Nori Takei, Professor Hitoshi Kuwabara, Professor Masatsugu Tsujii, Professor Toshiro Sugiyama, Professor Naohiro Kanayama, for data management, administrative and academic supports. The authors are also grateful to Mr. Charles Davey for his professional editing support in English. The HBC Study Team include Ms. Emi Higashimoto, Noriko Kodera, Atsuko Nakamura, Yumeno Kugizaki, Yukiko Suzuki, Riyo Takabayashi, Maiko Honda, Hiroko Muraki, Makiko Narumiya, Eriko Sato, Tomoyo Isobe, Mana Yamashita, Mr. Ryuji Nakahara, Drs. Kaori Matsumoto, Takanobu Horikoshi, Takeo Kato, Ryosuke Asano, Keisuke Wakusawa, Taishi Miyachi, Yusaku Endoh, Koichi Hirano, Teruhiko Suzuki, Professor Shu Takagai, and Professor Hirotaki Itoh. This work was supported by AMED (24gn0110079h0002 and 24gn0110088s0401 for K.J.T.), by the Japan Society for the Promotion of Science, Grants‐in‐Aid for Scientific Research (22H00492 and 25K00778 for K.J.T., 23K12745 for Y.I.‐O., 24K05810 for A.O., 24K05786 for T.N.), by the Smoking Research Foundation (2022G028 for K.J.T. and M.S.R.), and by a grant from SENSHIN Medical Research Foundation (for K.J.T.). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.</p> <hd id="AN0194549431-23">CONFLICT OF INTEREST STATEMENT</hd> <p>The authors declare no conflicts of interest.</p> <hd id="AN0194549431-24">DATA AVAILABILITY STATEMENT</hd> <p>The consent given by the participants does not allow publicly delivering/sharing data on an individual level in repositories or journals. Researchers who would like to access to HBC Study datasets for replication should apply to tsuchiya@hama-med.ac.jp. Access to the datasets requires approval from HBC Study Executive Committee, Hamamatsu University School of Medicine.</p> <hd id="AN0194549431-25">ETHICAL CONSIDERATIONS</hd> <p>The study was conducted in accordance with the guidelines proposed in the World Medical Association Declaration of Helsinki. All the enrolled pregnant individuals were given a complete description of the study and provided written informed consent to participate for both them and their children. The study protocol was approved by the Ethical Committee of Hamamatsu University School of Medicine, Japan (approval number 18–166 on March 14, 2007 and 20–233 on November 5, 2020). The present study conforms to the STrengthening the Reporting of OBservational studies in Epidemiology statement.</p> <p>GRAPH: Supporting Information S1</p> <ref id="AN0194549431-26"> <title> REFERENCES </title> <blist> <bibl id="bib1" idref="ref1" type="bt">1</bibl> <bibtext> Ament, K., Mejia, A., Buhlman, R., Erklin, S., Caffo, B., Mostofsky, S., & Wodka, E. (2015). Evidence for specificity of motor impairments in catching and balance in children with autism. 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Newcorn; Shigenobu Toda; Yuuka Ishikawa‐Omori; Akemi Okumura; Mohammad Shafiur Rahman; Toshiki Iwabuchi; Taeko Harada; Ikue Hirata; Chikako Nakayasu; Yuko Amma; Haruka Suzuki and Tomoko Nishimura</p> <p>Reported by Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib38" firstref="ref4"></nolink> <nolink nlid="nl2" bibid="bib14" firstref="ref5"></nolink> <nolink nlid="nl3" bibid="bib42" firstref="ref6"></nolink> <nolink nlid="nl4" bibid="bib25" firstref="ref7"></nolink> <nolink nlid="nl5" bibid="bib26" firstref="ref8"></nolink> <nolink nlid="nl6" bibid="bib12" firstref="ref11"></nolink> <nolink nlid="nl7" bibid="bib13" firstref="ref12"></nolink> <nolink nlid="nl8" bibid="bib24" firstref="ref13"></nolink> <nolink nlid="nl9" bibid="bib35" firstref="ref14"></nolink> <nolink nlid="nl10" bibid="bib29" firstref="ref17"></nolink> <nolink nlid="nl11" bibid="bib37" firstref="ref18"></nolink> <nolink nlid="nl12" bibid="bib47" firstref="ref19"></nolink> <nolink nlid="nl13" bibid="bib30" firstref="ref20"></nolink> <nolink nlid="nl14" bibid="bib22" firstref="ref24"></nolink> <nolink nlid="nl15" bibid="bib27" firstref="ref25"></nolink> <nolink nlid="nl16" bibid="bib33" firstref="ref28"></nolink> <nolink nlid="nl17" bibid="bib34" firstref="ref29"></nolink> <nolink nlid="nl18" bibid="bib20" firstref="ref33"></nolink> <nolink nlid="nl19" bibid="bib43" firstref="ref35"></nolink> <nolink nlid="nl20" bibid="bib40" firstref="ref38"></nolink> <nolink nlid="nl21" bibid="bib23" firstref="ref41"></nolink> <nolink nlid="nl22" bibid="bib17" firstref="ref43"></nolink> <nolink nlid="nl23" bibid="bib45" firstref="ref45"></nolink> <nolink nlid="nl24" bibid="bib39" firstref="ref46"></nolink> <nolink nlid="nl25" bibid="bib44" firstref="ref47"></nolink> <nolink nlid="nl26" bibid="bib28" firstref="ref48"></nolink> <nolink nlid="nl27" bibid="bib31" firstref="ref49"></nolink> <nolink nlid="nl28" bibid="bib32" firstref="ref50"></nolink> <nolink nlid="nl29" bibid="bib41" firstref="ref51"></nolink> <nolink nlid="nl30" bibid="bib10" firstref="ref54"></nolink> <nolink nlid="nl31" bibid="bib18" firstref="ref56"></nolink> <nolink nlid="nl32" bibid="bib19" firstref="ref65"></nolink> <nolink nlid="nl33" bibid="bib16" firstref="ref69"></nolink> <nolink nlid="nl34" bibid="bib11" firstref="ref72"></nolink> <nolink nlid="nl35" bibid="bib36" firstref="ref76"></nolink> <nolink nlid="nl36" bibid="bib21" firstref="ref83"></nolink> <nolink nlid="nl37" bibid="bib49" firstref="ref84"></nolink> <nolink nlid="nl38" bibid="bib15" firstref="ref85"></nolink> <nolink nlid="nl39" bibid="bib48" firstref="ref89"></nolink> <nolink nlid="nl40" bibid="bib46" firstref="ref92"></nolink>
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  Data: Neurodevelopmental Variations Cascading from Age 10 Months to 3 Years Leading to Attention-Deficit Hyperactivity Disorder/Autism Traits at Age 9 in a General Population
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  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Kenji+J%2E+Tsuchiya%22">Kenji J. Tsuchiya</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-1314-4199">0000-0002-1314-4199</externalLink>)<br /><searchLink fieldCode="AR" term="%22Nagahide+Takahashi%22">Nagahide Takahashi</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-7711-0297">0000-0002-7711-0297</externalLink>)<br /><searchLink fieldCode="AR" term="%22Yoko+Nomura%22">Yoko Nomura</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-2143-3257">0000-0002-2143-3257</externalLink>)<br /><searchLink fieldCode="AR" term="%22Jeffrey+H%2E+Newcorn%22">Jeffrey H. Newcorn</searchLink><br /><searchLink fieldCode="AR" term="%22Shigenobu+Toda%22">Shigenobu Toda</searchLink><br /><searchLink fieldCode="AR" term="%22Yuuka+Ishikawa-Omori%22">Yuuka Ishikawa-Omori</searchLink><br /><searchLink fieldCode="AR" term="%22Akemi+Okumura%22">Akemi Okumura</searchLink><br /><searchLink fieldCode="AR" term="%22Mohammad+Shafiur+Rahman%22">Mohammad Shafiur Rahman</searchLink><br /><searchLink fieldCode="AR" term="%22Toshiki+Iwabuchi%22">Toshiki Iwabuchi</searchLink><br /><searchLink fieldCode="AR" term="%22Taeko+Harada%22">Taeko Harada</searchLink><br /><searchLink fieldCode="AR" term="%22Ikue+Hirata%22">Ikue Hirata</searchLink><br /><searchLink fieldCode="AR" term="%22Chikako+Nakayasu%22">Chikako Nakayasu</searchLink><br /><searchLink fieldCode="AR" term="%22Yuko+Amma%22">Yuko Amma</searchLink><br /><searchLink fieldCode="AR" term="%22Haruka+Suzuki%22">Haruka Suzuki</searchLink><br /><searchLink fieldCode="AR" term="%22Tomoko+Nishimura%22">Tomoko Nishimura</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-4776-5153">0000-0002-4776-5153</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22JCPP+Advances%22"><i>JCPP Advances</i></searchLink>. 2026 6(2).
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  Group: Avail
  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
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  Label: Peer Reviewed
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  Data: Y
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  Label: Page Count
  Group: Src
  Data: 10
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  Label: Publication Date
  Group: Date
  Data: 2026
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Autism+Spectrum+Disorders%22">Autism Spectrum Disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Neurodevelopmental+Disorders%22">Neurodevelopmental Disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Attention+Deficit+Hyperactivity+Disorder%22">Attention Deficit Hyperactivity Disorder</searchLink><br /><searchLink fieldCode="DE" term="%22Children%22">Children</searchLink><br /><searchLink fieldCode="DE" term="%22Young+Children%22">Young Children</searchLink><br /><searchLink fieldCode="DE" term="%22Motor+Development%22">Motor Development</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+Ability%22">Cognitive Ability</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Japan%22">Japan</searchLink>
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  Label: Assessment and Survey Identifiers
  Group: Su
  Data: <searchLink fieldCode="SU" term="%22Mullen+Scales+of+Early+Learning%22">Mullen Scales of Early Learning</searchLink><br /><searchLink fieldCode="SU" term="%22Social+Responsiveness+Scale%22">Social Responsiveness Scale</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1002/jcv2.70053
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 2692-9384
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Background: Neurodevelopmental delay precedes attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) diagnoses. However, exactly when this emerges in association with these outcomes remains unclear. We investigated (1) the earliest representations of neurodevelopmental variation and (2) what neurodevelopmental variations at an early age (10 months to 3 years) are specifically associated with the emergence of parentally reported behavioral traits of ADHD, ASD, and related disorders at age 9. Methods: Children from the Hamamatsu Birth Cohort of Mothers and Children (HBC Study) born between December 2007 and March 2012 were enrolled and followed from birth to age 9. Standardized scores of neurodevelopment across five domains (gross motor, visual reception, fine motor, receptive language, and expressive language) were calculated using the Mullen Scales of Early Learning at ages 10, 14, 18, 24, 32, and 40 months. ADHD and ASD traits were ascertained as Z-scores using the ADHD-Rating Scale and Social Responsiveness Scale-2 at age 9. To explore the earliest recognition of neurodevelopmental variation with credibility, structural equation modeling (SEM) was used to estimate the total effects of the linear associations between exposures and outcomes. Results: 836 children (405 females, 48%) were enrolled in the analysis. The ADHD trait was associated with visual reception score before age 1 and was concurrent with both fine motor and receptive language scores between ages 1-2. The ASD trait was associated with gross motor score before age 1 and expressive language score between ages 1.5 and 3. Conclusion: Suboptimal visual-motor coordination can be a prototype of the ADHD trait, while a cascading pattern of suboptimalities from gross motor to language domains can be a prototype of the ASD trait. The distinct neurodevelopmental variations related to ADHD and ASD traits running in the general population can be found before age 1.
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  Data: 2026
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  Data: EJ1508683
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1508683
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        Value: 10.1002/jcv2.70053
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      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 10
    Subjects:
      – SubjectFull: Autism Spectrum Disorders
        Type: general
      – SubjectFull: Neurodevelopmental Disorders
        Type: general
      – SubjectFull: Attention Deficit Hyperactivity Disorder
        Type: general
      – SubjectFull: Children
        Type: general
      – SubjectFull: Young Children
        Type: general
      – SubjectFull: Motor Development
        Type: general
      – SubjectFull: Cognitive Ability
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      – SubjectFull: Foreign Countries
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      – SubjectFull: Japan
        Type: general
      – SubjectFull: Mullen Scales of Early Learning
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      – SubjectFull: Social Responsiveness Scale
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    Titles:
      – TitleFull: Neurodevelopmental Variations Cascading from Age 10 Months to 3 Years Leading to Attention-Deficit Hyperactivity Disorder/Autism Traits at Age 9 in a General Population
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