Multifactorial Predictors of Infant Neurodevelopment at Six Months: A Hierarchical Regression Analysis

Multifactorial Predictors of Infant Neurodevelopment at Six Months: A Hierarchical Regression Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Multifactorial Predictors of Infant Neurodevelopment at Six Months: A Hierarchical Regression Analysis Tatyana Itova This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9075705/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Early neurodevelopment results from the interaction between biological conditions at birth and the postnatal caregiving environment. Understanding the relative contribution of these factors during early infancy may improve early identification of children at developmental risk. Objective To investigate the influence of biological, familial, and environmental predictors on neurodevelopmental outcomes at six months of age. Methods A cross-sectional study was conducted among 124 healthy term infants aged six months. Neurodevelopment was assessed using the Ages and Stages Questionnaire, Third Edition (ASQ-3), covering five developmental domains: communication, gross motor, fine motor, problem solving, and personal–social development. Predictors were grouped into biological factors (sex, birth weight, gestational age, exclusive breastfeeding, prenatal alcohol exposure), maternal factors (maternal education and early postpartum return to employment), and environmental factors (language environment and duration of language stimulation). Hierarchical multiple regression analyses were performed to evaluate the independent contribution of each predictor group. Results Biological factors demonstrated the strongest and most consistent associations with early developmental outcomes. Birth weight emerged as the most stable predictor , showing significant positive associations with communication, gross motor, problem-solving, and personal–social development. Prenatal alcohol exposure was independently associated with lower personal–social scores. Sex differences were observed in communication outcomes, with female infants demonstrating slightly higher scores. Maternal and environmental factors contributed only modestly to explained variance and were not retained as independent predictors in the final regression models. Conclusion Early neurodevelopment at six months appears to be primarily influenced by biological characteristics at birth , particularly birth weight, while prenatal alcohol exposure represents a specific risk factor for early social development. Infant neurodevelopment Birth weight Prenatal alcohol exposure ASQ-3 Early development Developmental screening Figures Figure 1 1. Introduction Early neurodevelopment results from a complex interaction between biological conditions at birth and the postnatal caregiving environment. The sixth month of life represents a critical developmental milestone, as early cognitive, motor, and social trajectories become measurable through observable behavioral markers during this period. According to the Developmental Origins of Health and Disease (DOHaD) framework, biological parameters at birth—such as birth weight and gestational age—serve as important predictors of later neurodevelopmental outcomes [ 1 , 2 ]. Even within the normative range among term-born infants, higher birth weight is frequently associated with better outcomes in communication and problem-solving abilities, whereas lower gestational age may contribute to subtle developmental differences during early infancy [ 3 , 4 ]. One of the most significant challenges to optimal neurodevelopment is prenatal alcohol exposure. Large-scale meta-analyses demonstrate that prenatal alcohol exposure is associated with persistent impairments in sensory processing and cognitive functioning [ 5 , 6 ]. Importantly, these adverse effects may be moderated by the biological sex of the infant. Accumulating evidence suggests greater neurological vulnerability among males, with boys demonstrating lower communicative abilities than girls when exposed to comparable levels of prenatal risk [ 7 , 8 ]. Despite the impact of biological risk factors, the postnatal environment possesses a substantial capacity to compensate through mechanisms of neuroplasticity. Breastfeeding and adequate early nutrition support myelination and early cognitive development, while parental stimulation functions as a major driver of developmental progress [ 9 , 19 ]. In particular, the duration of daily language stimulation and the educational level of the mother have emerged as key determinants positively associated with infant communication abilities and fine motor development [ 11 , 12 ]. These environmental determinants may therefore play an important role in shaping early developmental outcomes [ 13 – 15 ]. To our knowledge, evidence from Eastern European populations regarding early developmental determinants during infancy remains limited. In addition, the application of the Ages and Stages Questionnaire, Third Edition (ASQ-3), in population-based studies from this region has been relatively scarce. The aim of the present study was to investigate the influence of multifactorial predictors on neurodevelopment at six months of age. Predictors were categorized into three conceptual groups: biological factors (including sex, birth weight, gestational age, and prenatal exposures), family-related factors (parental education and employment status), and environmental factors (language environment and duration of language stimulation). Infant development was assessed across the five developmental domains of the Ages and Stages Questionnaire (ASQ-3). 2. Materials and Methods 2.1. Study Design and Participants This observational cross-sectional study was conducted between August and December 2025 at the University Multiprofile Hospital for Active Treatment “Medica Ruse” Ltd., Bulgaria. Infants were recruited during routine 6-month pediatric health examinations. A total of 159 infants were initially screened. Following the exclusion of four cases due to incomplete developmental domain responses, 155 valid Ages and Stages Questionnaire, Third Edition (ASQ-3) forms were obtained. To ensure a homogeneous study population of full-term infants, a further 31 infants were excluded: 13 due to preterm birth (gestational age < 37 weeks) and/or low birth weight (< 2500 g), and 18 due to incomplete data regarding predictor variables. The final analytic sample consisted of 124 full-term infants (gestational age ≥ 37 weeks; birth weight ≥ 2500 g) with a chronological age of 6 months (± 2 weeks) at the time of assessment. 2.2. Ethical Considerations The study protocol was approved by the Ethics Committee of the University Multiprofile Hospital for Active Treatment “Medica Ruse” Ltd. (Approval No. A-471/01.08.2025). The research was conducted in strict accordance with the Declaration of Helsinki. Written informed consent was obtained from all parents or legal guardians prior to enrollment. 2.3. Developmental Assessment Neurodevelopmental outcomes were evaluated using the 6-month form of the ASQ-3, a validated parent-completed screening tool [ 14 , 15 ]. The instrument assesses five domains: Communication, Gross Motor, Fine Motor, Problem Solving, and Personal-Social. Each domain comprises six items scored as 0 (“Not yet”), 5 (“Sometimes”), or 10 (“Yes”), with a maximum score of 60 per domain. Higher scores indicate more advanced developmental performance. To ensure standardized timing of developmental assessment, parents completed the questionnaire in close temporal proximity to the routine six-month pediatric examination. 2.4. Predictor Variables Predictor variables were categorized into three conceptual groups: biological, maternal, and environmental factors. Biological factors : Infant sex, Birth weight (kg), Gestational age (weeks), Exclusive breastfeeding (yes/no), Prenatal alcohol exposure (yes/no) Maternal factors : Maternal education (primary/secondary/university), Early postpartum return to employment (yes/no). Early postpartum return to employment was conceptualized as a proxy indicator of reduced maternal availability for direct infant caregiving during early infancy. Environmental factors : Language environment (monolingual/bilingual), Duration of daily caregiver language stimulation. Language stimulation referred to the average daily time caregivers spent talking, reading, or verbally interacting with the infant. 2.5. Statistical Analysis Data were analyzed using IBM SPSS Statistics (Version 19; IBM Corp., Armonk, NY, USA). Data distribution was assessed for normality. Continuous variables (e.g., birth weight, gestational age, and ASQ-3 scores) are presented as mean ± standard deviation (SD). Binary and categorical variables (e.g., sex, prenatal alcohol exposure) were dummy-coded (0, 1) for regression purposes and are reported as frequencies and percentages (%). Pearson correlation coefficients were calculated to examine bivariate associations, with effect sizes interpreted according to Cohen’s guidelines. Confidence intervals were derived using Fisher’s z transformation. Two-tailed p-values were used to determine statistical significance. Regression analysis: To evaluate the relative contribution of biological, maternal, and environmental predictors, hierarchical multiple linear regression models were constructed separately for each ASQ-3 developmental domain. Multicollinearity among predictors was assessed using variance inflation factors (VIF). Predictors were entered sequentially in three hierarchical blocks (Fig. 1 ). Model 1 – Biological factors sex, birth weight, gestational age, exclusive breastfeeding, and prenatal alcohol exposure. Model 2 – Biological + maternal factors Model 1 variables plus maternal education and early postpartum return to employment. Model 3 – Biological + maternal + environmental factors Model 2 variables plus language environment and duration of caregiver language stimulation. This hierarchical approach allowed assessment of the incremental explanatory contribution of each conceptual group of predictors. Model fit was evaluated using the coefficient of determination (R²) and adjusted R² values. Standardized regression coefficients (β) were used to assess the strength of individual predictors. Statistical significance was set at p < 0.05. Given the relatively low frequency of early postpartum return to employment in the sample, findings related to this variable were interpreted with caution. To account for multiple testing, statistical significance was additionally evaluated using Bonferroni-adjusted p-values. 3. Results 3.1. Sample Characteristics and Developmental Outcomes The final analytic sample comprised 124 full-term infants. The mean birth weight was 3.28 ± 0.41 kg, and the mean gestational age was 39.1 ± 1.2 weeks. Males represented 55.6% of the cohort. Regarding early nutrition, 74.2% of infants were exclusively breastfed. Prenatal alcohol exposure was reported in 14.5% of pregnancies. Detailed demographic and clinical characteristics are summarized in Table 1 . Table 1 Sample Characteristics (N = 124) Variable Value Sex Male Female 69 (55.6) 55 (44.4) Birth weight (kg) 3.28 ± 0.41 Gestational age (weeks) 39.1 ± 1.2 Exclusive breastfeeding (yes) 92 (74.2) Prenatal alcohol exposure (yes) 18 (14.5) Maternal education Primary Secondary University 1 (0.8) 47 (37.9) 76 (61.3) Early postpartum return to paid employment (yes) 2 (1.6) Time spent with child ≥ 30 min/day 102 (82.3) Bilingual environment (yes) 25 (20.2) Notes Data are presented as n (%) unless otherwise indicated. Continuous variables are presented as mean ± SD. Developmental scores across all ASQ-3 domains were within expected normative ranges. The highest mean scores were observed in Problem Solving (53.39 ± 8.50), followed by Fine Motor (50.27 ± 11.89). The Gross Motor domain exhibited the lowest mean score (42.94 ± 11.93) and the highest inter-individual variability. Clinical risk for developmental delay (scores below standardized cut-offs) was low, ranging from 0.8% in Problem Solving to 6.5% in Gross Motor (Table 2 ). Table 2 Developmental outcomes at 6 months (N = 124) Domain Mean ± SD 95% CI Below Cut-off n (%) Communication 49.76 ± 8.41 48.28–51.24 2 (1.6) Gross Motor 42.94 ± 11.93 40.85–45.03 8 (6.5) Fine Motor 50.27 ± 11.89 48.19–52.35 5 (4.0) Problem Solving 53.39 ± 8.50 51.90–54.88 1 (0.8) Personal–Social 48.75 ± 9.38 47.11–50.39 3 (2.4) 3.2. Correlation Analysis Pearson correlation analysis revealed several significant associations between developmental outcomes and the examined predictors (Table 3 ). Table 3 Pearson Correlations Between Developmental Domains and Significant Predictors with 95% CI (N = 124) Domain Predictor r 95% CI p Effect size Communication Sex −.181 −.343 to − .009 .044 small Birth weight .186 .014 to .348 .038 small Language stimulation .188 .016 to .350 .036 small Gross Motor Birth weight .253 .084 to .405 .002 small–moderate Exclusive breastfeeding .177 .004 to .339 .025 small Fine Motor Exclusive breastfeeding .216 .047 to .373 .016 small Problem Solving Birth weight .212 .043 to .370 .018 small Personal–Social Birth weight .248 .079 to .400 .006 small–moderate Prenatal alcohol exposure −.288 −.436 to − .128 .002 upper small (approaching moderate) Notes : Pearson correlation coefficients (two-tailed). 95% confidence intervals were calculated using Fisher’s z transformation. Only statistically significant associations (p < .05) are presented. Birth weight showed consistent positive correlations with several developmental domains, including communication, gross motor, problem-solving, and personal–social development. Exclusive breastfeeding showed modest positive correlations with gross motor and fine motor development. Prenatal alcohol exposure was negatively associated with personal–social development. Most associations were small in magnitude, with several approaching moderate effect sizes. 3.3. Hierarchical Regression Analyses Hierarchical multiple regression analyses were conducted separately for each ASQ-3 developmental domain to examine the incremental contributions of biological, maternal, and environmental predictors. Three models were constructed for each domain: Model 1 : biological factors Model 2 : biological + maternal factors Model 3 : biological + maternal + environmental factors Detailed hierarchical model statistics are presented in Table 4 . Table 4 Hierarchical Regression Models Across Developmental Domains (N = 124) Domain Model k df R² Adj. R² ΔR² F p f² Δf² Communication M1 5 5,118 .110 .073 — 2.93 .016 .124 — M2 7 7,116 .120 .067 .010 2.25 .035 .136 .011 M3 9 9,114 .145 .078 .025 2.15 .031 .170 .028 Gross Motor M1 5 5,118 .113 .076 — 3.02 .013 .127 — M2 7 7,116 .137 .085 .024 2.63 .015 .159 .027 M3 9 9,114 .140 .072 .003 2.06 .039 .163 .003 Fine Motor M1 5 5,118 .077 .038 — 1.96 .089 .083 — M2 7 7,116 .100 .045 .023 1.83 .088 .111 .025 M3 9 9,114 .115 .045 .015 1.65 .111 .130 .017 Problem Solving M1 5 5,118 .090 .051 — 2.32 .047 .099 — M2 7 7,116 .095 .040 .005 1.73 .108 .105 .006 M3 9 9,114 .095 .024 .000 1.33 .228 .105 .000 Personal–Social M1 5 5,118 .159 .124 — 4.48 .001 .189 — M2 7 7,116 .160 .109 .001 3.16 .004 .190 .001 M3 9 9,114 .167 .101 .007 2.54 .011 .200 .008 Notes : M1 – biological factors, M2 – biological + maternal factors, M3 – biological + maternal + environmental factors. Effect size interpretation (Cohen) : f² = 0.02 small, f² = 0.15 medium, f² = 0.35 large Across domains, biological factors explained a modest proportion of variance in developmental outcomes. The inclusion of maternal and environmental variables resulted in only small increases in explained variance. 3.3.1 Communication Development The hierarchical regression models predicting communication development were statistically significant across all three steps. The biological model explained 11.0% of the variance , increasing to 14.5% in the final model . In the fully adjusted model, sex , birth weight , and gestational age emerged as significant independent predictors. Male sex and lower gestational age were associated with lower communication scores, whereas higher birth weight was associated with better communication performance. 3.3.2 Gross Motor Development For gross motor development, all three models reached statistical significance. The biological model explained 11.3% of the variance , with the final model explaining 14.0% . Across all hierarchical steps, birth weight remained the only significant independent predictor. Higher birth weight was consistently associated with improved gross motor performance at six months. 3.3.3 Fine Motor Development Hierarchical regression models for fine motor development did not reach statistical significance. Although exclusive breastfeeding showed a modest positive association in the biological model, this effect was not maintained after the inclusion of additional predictors. Overall, the examined biological, maternal, and environmental variables did not significantly explain variability in fine motor development at six months. 3.3.4 Problem-Solving Development The biological model predicting problem-solving development reached statistical significance and explained 9.0% of the variance. However, the addition of maternal and environmental factors did not improve model fit. In the final model, birth weight and gestational age remained significant predictors. Higher birth weight was associated with better problem-solving performance, while lower gestational age was associated with poorer outcomes. 3.3.5 Personal–Social Development Personal–social development demonstrated the strongest regression model among all domains. The biological model explained 15.9% of the variance , increasing slightly to 16.7% in the final model . In the fully adjusted model, birth weight and prenatal alcohol exposure emerged as significant independent predictors. Higher birth weight was associated with improved personal–social development, whereas prenatal alcohol exposure was associated with lower personal–social scores. 3.4 Significant Independent Predictors Significant independent predictors identified across hierarchical models are summarized in Table 5 . Table 5 Significant Independent Predictors Across Hierarchical Models Domain Model Significant Predictor(s) β p Communication M1 Sex −.182 .039 Birth weight .293 .005 Gestational age −.221 .035 M2 Sex −.194 .030 Birth weight .293 .005 Gestational age −.227 .034 M3 Sex −.194 .030 Birth weight .278 .008 Gestational age −.212 .048 Gross Motor M1 Birth weight .324 .002 M2 Birth weight .322 .002 M3 Birth weight .322 .002 Fine Motor M1 Exclusive breastfeeding .182 .048 Problem Solving M1 Birth weight .326 .002 Gestational age −.235 .027 M2 Birth weight .328 .002 Gestational age −.249 .022 M3 Birth weight .331 .002 Gestational age −.252 .023 Personal–Social M1 Birth weight .281 .006 Prenatal alcohol exposure −.264 .002 M2 Birth weight .280 .006 Prenatal alcohol exposure −.262 .003 M3 Birth weight .266 .010 Prenatal alcohol exposure −.273 .002 Birth weight emerged as the most consistent predictor , demonstrating significant associations across multiple developmental domains. Gestational age contributed to communication and problem-solving outcomes, while prenatal alcohol exposure showed a specific negative association with personal–social development. Exclusive breastfeeding was associated with fine motor development only in the initial biological model. 3.5 Comparison of Explanatory Strength Across Domains Pairwise comparisons of the explanatory strength of the biological models (Model 1) across developmental domains were conducted using Fisher’s z tests. As shown in Table 6 , none of the pairwise comparisons reached statistical significance, indicating that the explanatory contribution of biological predictors was comparable across domains. Table 6 Pairwise comparisons of Model 1 explanatory strength across developmental domains (Fisher’s z tests) Comparison z p Communication vs Gross Motor −0.09 .93 Communication vs Fine Motor 0.51 .61 Communication vs Problem Solving 0.31 .76 Communication vs Personal–Social −0.73 .46 Gross Motor vs Fine Motor 0.60 .55 Gross Motor vs Problem Solving 0.40 .69 Gross Motor vs Personal–Social −0.64 .52 Fine Motor vs Problem Solving −0.20 .84 Fine Motor vs Personal–Social −1.24 .21 Problem Solving vs Personal–Social −1.04 .30 Similarly, pairwise comparisons of the explanatory strength of the final hierarchical models (Model 3) also revealed no statistically significant differences after Bonferroni correction (Table 7 ). Table 7 Pairwise Comparisons of Model 3 Explanatory Strength Across Developmental Domains Domain Comparison z_diff p-value Bonferroni-adjusted p Communication vs Gross Motor 0.08 .94 1.000 Communication vs Fine Motor 0.47 .64 1.000 Communication vs Problem Solving 0.81 .42 1.000 Communication vs Personal–Social −0.29 .77 1.000 Gross Motor vs Fine Motor 0.40 .69 1.000 Gross Motor vs Problem Solving 0.74 .46 1.000 Gross Motor vs Personal–Social −0.37 .71 1.000 Fine Motor vs Problem Solving 0.35 .73 1.000 Fine Motor vs Personal–Social −0.76 .45 1.000 Problem Solving vs Personal–Social −1.11 .27 1.000 Although personal–social development showed the highest explained variance, these differences were not statistically significant. 3.6 Summary of Key Findings Across the examined developmental domains, biological factors demonstrated the strongest and most consistent associations with early neurodevelopment . Birth weight emerged as the most stable predictor across domains, while gestational age and prenatal alcohol exposure showed domain-specific effects. Maternal and environmental variables contributed minimally to the explanatory power of the models at six months of age. 4. Discussion The present study examined the relative contributions of biological, prenatal, and environmental factors to developmental outcomes at six months of age. Birth weight emerged as the most consistent predictor across developmental domains, while prenatal alcohol exposure demonstrated a specific negative association with personal–social development. 4.1. Biological risk factors and early development The findings of the present study confirm the central role of biological factors in shaping early neurodevelopment. Risks associated with low birth weight represent a global phenomenon, and neurodevelopmental deficits among these children have been consistently documented across diverse populations [ 2 ]. Both low birth weight and lower gestational age are well-established predictors of neurological outcomes and are frequently associated with an increased risk of later cognitive and motor impairments [ 16 ]. Importantly, developmental variability is not restricted to extremely preterm or very low birth weight infants. Evidence indicates that even among term-born infants, developmental outcomes follow a gradient pattern related to birth weight [ 17 ]. Each additional increment in birth weight and each additional week of gestation contribute to more favorable outcomes in communication, problem solving, and gross motor development [ 18 ]. These findings suggest that infants born close to term but with relatively lower birth weight may already exhibit subtle developmental differences by six months of age and therefore warrant careful developmental monitoring. Early somatic growth parameters are closely linked to cognitive development. In particular, the rate of head circumference growth during the first six months reflects ongoing neuronal maturation and has been identified as a predictor of future cognitive capacity [ 19 ]. Motor development represents another important indicator of neurological maturation. Delays in gross motor development during the first year have been identified as early markers for later difficulties in fine motor skills and academic functioning [ 20 ]. Even small differences in gestational age among term infants may be associated with slower maturation of cortical structures and motor milestones during infancy [ 21 ]. Taken together, these findings suggest that biological parameters at birth retain prognostic value even among infants born at term. Higher birth weight and longer gestation appear to support more mature neural networks involved in communication and social cognition [ 4 , 18 ]. 4.2. Prenatal alcohol exposure The significant negative association between prenatal alcohol exposure and personal–social development observed in this study is strongly supported by contemporary literature. Even low to moderate levels of prenatal alcohol exposure have been associated with poorer early cognitive and behavioral outcomes due to disruptions in neural systems involved in attention, emotional regulation, and social cognition [ 5 ]. Prenatal alcohol exposure interferes with mechanisms of sensory processing and behavioral regulation. Effective social interaction during infancy requires the integration of multiple external stimuli, including vocal signals, facial expressions, and tactile input. Disruption of these regulatory processes may therefore limit the development of typical social responses during early infancy [ 6 ]. Neuroimaging studies demonstrate that prenatal alcohol exposure is associated with structural alterations in cortical and subcortical brain regions and reduced white matter integrity—areas that are essential for social cognition and rapid processing of social stimuli [ 22 ]. These alterations may manifest functionally during infancy as reduced social engagement and impaired self-regulation. Combined toxic exposures may exert cumulative effects on emotional reactivity and social participation during early development [ 23 ]. Even subclinical levels of prenatal alcohol exposure may therefore produce measurable effects on early social neurofunction, emphasizing the importance of early screening and monitoring of exposed infants. 4.3. Effect of exclusive breastfeeding Infant feeding during the first six months of life represents an important modulator of early neurodevelopment. Breast milk contains a unique combination of bioactive nutrients—including long-chain polyunsaturated fatty acids, oligosaccharides, and choline—that support myelination and structural maturation of white matter pathways in the developing brain [ 10 ]. Evidence indicates that breastfeeding is associated with improved cognitive outcomes, even after adjusting for socioeconomic variables [ 9 ]. These mechanisms may explain the more favorable developmental tendencies observed among breastfed infants in our study, particularly in early motor domains. However, these associations did not remain significant after adjustment for additional predictors. Nevertheless, breastfeeding remains an important component of early nutritional support and may contribute to optimal neurodevelopment, particularly among infants with biological vulnerabilities. Previous research demonstrates that optimal early feeding practices are associated with earlier achievement of gross motor milestones and improved hand–eye coordination in fine motor tasks [ 24 ]. Maternal nutrition during pregnancy also plays an important role in establishing the foundations of neurogenesis and synaptogenesis, suggesting that prenatal and postnatal nutritional influences operate along a continuous developmental pathway [ 25 ]. Adequate nutrition may also partially mitigate the negative effects of prenatal exposures through mechanisms of neural plasticity [ 26 ]. Given the high plasticity of the nervous system during early infancy, optimal nutrition may therefore represent both a preventive and potentially compensatory factor. 4.4. Sex differences The present study identified sex-related differences in communication outcomes within the regression models. Previous research indicates that female infants exhibit earlier maturation of social–communication neural networks during the first year of life [ 8 ]. These differences may reflect faster cortical organization and earlier integration of frontotemporal connections among girls. In contrast, male fetal brains appear more sensitive to prenatal stressors and toxic exposures, resulting in more pronounced structural alterations in brain regions associated with social communication [ 7 ]. Boys also tend to exhibit slower maturation of language-related cortical networks, which may increase vulnerability to developmental delays when additional prenatal risk factors are present. These findings highlight the importance of sex-sensitive approaches in early developmental screening and monitoring. 4.5. Environmental influences and integrative perspective Environmental and caregiving factors also play an important role in shaping early developmental outcomes. Correlation analyses suggested a positive association between caregiver language stimulation and communication abilities at six months, although this effect did not remain significant in multivariable models. This observation confirms the well-established relationship between parental linguistic input and early communicative behaviors [ 27 ]. Although maternal education did not emerge as an independent predictor in the regression models, previous research suggests that enriched home environments associated with higher educational attainment may contribute to improved developmental stimulation [ 28 ]. Responsive parenting behaviors—including shared attention, reading, and sustained verbal interaction—have been identified as strong predictors of improved communication outcomes [ 29 ]. Family resources and stable caregiving environments facilitate responsive parenting styles that support both cognitive and personal–social development [ 30 ]. Importantly, not only the amount of time spent with caregivers but also the quality of interaction appears crucial for early cognitive development [ 31 ]. Our findings support contemporary developmental frameworks emphasizing the dynamic interaction between biological vulnerability and environmental context. According to the Developmental Origins of Health and Disease (DOHaD) paradigm, early development emerges through continuous interaction between prenatal biological programming and postnatal environmental influences [ 1 ]. Similarly, models of early brain architecture highlight the role of responsive caregiver–infant interactions in shaping neural development [ 32 ]. Language stimulation represents an active reciprocal process rather than passive exposure, strengthening synaptic connections within social–communication networks [ 33 ]. Early investments in communication and social interaction therefore generate long-term developmental benefits [ 34 ]. 5. Strengths and limitations The present study has several strengths. Developmental outcomes were assessed using the validated screening instrument ASQ-3, which allows reliable identification of early developmental differences across multiple domains [ 35 ]. Previous studies have demonstrated good agreement between ASQ-3 and standardized developmental assessments such as the Bayley Scales [ 36 ]. The hierarchical analytical approach allowed simultaneous examination of biological, prenatal, and environmental determinants of development, providing a comprehensive perspective on early developmental influences. Several limitations should also be considered. First, the cross-sectional design limits conclusions regarding long-term developmental trajectories. Second, developmental screening relied on parental report, which may introduce reporting bias, although previous validation studies indicate high reliability of parent-completed developmental questionnaires [ 37 ]. Finally, certain prenatal exposures were based on self-reported data and may therefore be subject to underreporting. 6. Clinical implications The findings highlight the importance of routine developmental screening during the first year of life. Early identification of subtle developmental differences at six months may allow timely support and intervention before more pronounced delays emerge later in childhood. Infants exposed to prenatal risk factors—particularly prenatal alcohol exposure or lower birth weight—may benefit from closer developmental monitoring. Pediatric health professionals should also encourage early parent–infant interaction, responsive communication, and optimal infant nutrition as part of preventive developmental care. 7. Conclusion Developmental outcomes at six months of age appear to be shaped by a complex interaction between biological characteristics at birth and the quality of the early caregiving environment. Biological factors such as birth weight, gestational age, and prenatal exposures contribute to early developmental variability, while postnatal factors—including breastfeeding and caregiver interaction—may function as protective influences. Early developmental screening at six months therefore represents an important opportunity to identify infants at increased developmental risk and to support optimal neurodevelopmental trajectories. Declarations Author Contribution Tatyana Itova: Conceptualization; Methodology; Investigation; Data curation; Formal analysis; Writing – original draft; Writing – review & editing; Supervision. Funding Statement: This study was conducted under the project “WORKSHOP FOR ADVANCED MEDICAL TECHNOLOGIES”, No. Д-ФВП-03/04.03.2025, and was financed by the European Union – NextGenerationEU, through the National Recovery and Resilience Plan of the Republic of Bulgaria, within the framework of the project “Scientific University of Ruse”, Contract No. BG-RRP-2.013-0001. References Roseboom TJ, Painter RC, de Rooij SR (2023) Developmental origins of health and disease: mechanisms and future perspectives. Nat Rev Endocrinol 19(1):15–28 Zhang W et al (2022) Birth weight and neurodevelopmental outcomes in early childhood: a population-based cohort study. J Pediatr 246:45–52 Hwang SS et al (2024) Gestational age and neurodevelopmental outcomes in early infancy. Pediatrics 153(2):e2023067453 Boyle EM et al (2023) Effects of gestational age at birth on early childhood development. BMJ 380:e072948 Akison LK et al (2024) Prenatal alcohol exposure and infant neurodevelopment: a meta-analysis. 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Early Child Res Q 67:101–112 Hart AR et al (2024) Time spent with caregivers and early cognition. Child Dev 95(1):198–212 Shonkoff JP et al (2022) Lifelong effects of early childhood adversity and toxic stress. Pediatrics 149(S1):S8–S15 Center on the Developing Child at Harvard University (2024) Serve and return interaction shapes early brain development. Harvard University Heckman JJ (2006) Early investments in human capital. Science 312(5782):1900–1902 Squires J et al (2023) Ages & Stages Questionnaires (ASQ-3): updated normative data and validation. J Dev Behav Pediatr 44(2):95–102 Backer L et al (2022) Comparison of ASQ-3 and Bayley Scales in infant developmental screening. Infant Behav Dev 67:101713 Steenis LJ et al (2025) Reliability of parental-report developmental screening tools. J Pediatr Psychol 50(3):276–286 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9075705","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":607078205,"identity":"ee7e4e83-810e-468b-8ef3-f24a44369660","order_by":0,"name":"Tatyana Itova","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyElEQVRIiWNgGAWjYDACZjBpA2MwMBgQ0sHDDFaaRooWiNLDCBGCWuzZ+Q8+5qk5n7idnYHtM88fGwZz/gUEHcZszHPsduLOZgbm2bxtaQyWMx4Q1MImOYPtduKGw/yfmXkbDjMY3DhAjJZ/54BaGJiZef78J06LxMe2A1AtbAcYDM43ENBymNnY4GNfsjFIC+PctmQeyxn4dTCw9x98+CDhm53shvMHmBne/LGTM+cn4DBMaxkkEkjUwsBAsi2jYBSMglEw3AEAI+o5w2E1aUIAAAAASUVORK5CYII=","orcid":"","institution":"Angel Kanchev University of Ruse","correspondingAuthor":true,"prefix":"","firstName":"Tatyana","middleName":"","lastName":"Itova","suffix":""}],"badges":[],"createdAt":"2026-03-09 17:10:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9075705/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9075705/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104876953,"identity":"dfcb8b46-dfa5-43ea-9faf-a4bc93cc7d55","added_by":"auto","created_at":"2026-03-18 08:44:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":65875,"visible":true,"origin":"","legend":"\u003cp\u003eHierarchical structure of predictors included in Models 1–3\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9075705/v1/a3ecbe22380b1643efce313c.png"},{"id":105049698,"identity":"7f4b11d2-a178-40ea-bf28-71c04e04e6d1","added_by":"auto","created_at":"2026-03-20 09:56:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1647111,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9075705/v1/82c8f506-b83f-4630-a0bb-896d6d0836ac.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Multifactorial Predictors of Infant Neurodevelopment at Six Months: A Hierarchical Regression Analysis","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eEarly neurodevelopment results from a complex interaction between biological conditions at birth and the postnatal caregiving environment. The sixth month of life represents a critical developmental milestone, as early cognitive, motor, and social trajectories become measurable through observable behavioral markers during this period. According to the Developmental Origins of Health and Disease (DOHaD) framework, biological parameters at birth\u0026mdash;such as birth weight and gestational age\u0026mdash;serve as important predictors of later neurodevelopmental outcomes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Even within the normative range among term-born infants, higher birth weight is frequently associated with better outcomes in communication and problem-solving abilities, whereas lower gestational age may contribute to subtle developmental differences during early infancy [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOne of the most significant challenges to optimal neurodevelopment is prenatal alcohol exposure. Large-scale meta-analyses demonstrate that prenatal alcohol exposure is associated with persistent impairments in sensory processing and cognitive functioning [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Importantly, these adverse effects may be moderated by the biological sex of the infant. Accumulating evidence suggests greater neurological vulnerability among males, with boys demonstrating lower communicative abilities than girls when exposed to comparable levels of prenatal risk [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the impact of biological risk factors, the postnatal environment possesses a substantial capacity to compensate through mechanisms of neuroplasticity. Breastfeeding and adequate early nutrition support myelination and early cognitive development, while parental stimulation functions as a major driver of developmental progress [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In particular, the duration of daily language stimulation and the educational level of the mother have emerged as key determinants positively associated with infant communication abilities and fine motor development [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. These environmental determinants may therefore play an important role in shaping early developmental outcomes [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo our knowledge, evidence from Eastern European populations regarding early developmental determinants during infancy remains limited. In addition, the application of the Ages and Stages Questionnaire, Third Edition (ASQ-3), in population-based studies from this region has been relatively scarce. The aim of the present study was to investigate the influence of multifactorial predictors on neurodevelopment at six months of age. Predictors were categorized into three conceptual groups: biological factors (including sex, birth weight, gestational age, and prenatal exposures), family-related factors (parental education and employment status), and environmental factors (language environment and duration of language stimulation). Infant development was assessed across the five developmental domains of the Ages and Stages Questionnaire (ASQ-3).\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Design and Participants\u003c/h2\u003e \u003cp\u003eThis observational cross-sectional study was conducted between August and December 2025 at the University Multiprofile Hospital for Active Treatment \u0026ldquo;Medica Ruse\u0026rdquo; Ltd., Bulgaria. Infants were recruited during routine 6-month pediatric health examinations.\u003c/p\u003e \u003cp\u003eA total of 159 infants were initially screened. Following the exclusion of four cases due to incomplete developmental domain responses, 155 valid Ages and Stages Questionnaire, Third Edition (ASQ-3) forms were obtained. To ensure a homogeneous study population of full-term infants, a further 31 infants were excluded: 13 due to preterm birth (gestational age\u0026thinsp;\u0026lt;\u0026thinsp;37 weeks) and/or low birth weight (\u0026lt;\u0026thinsp;2500 g), and 18 due to incomplete data regarding predictor variables. The final analytic sample consisted of 124 full-term infants (gestational age\u0026thinsp;\u0026ge;\u0026thinsp;37 weeks; birth weight\u0026thinsp;\u0026ge;\u0026thinsp;2500 g) with a chronological age of 6 months (\u0026plusmn;\u0026thinsp;2 weeks) at the time of assessment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Ethical Considerations\u003c/h2\u003e \u003cp\u003e The study protocol was approved by the Ethics Committee of the University Multiprofile Hospital for Active Treatment \u0026ldquo;Medica Ruse\u0026rdquo; Ltd. (Approval No. A-471/01.08.2025). The research was conducted in strict accordance with the Declaration of Helsinki. Written informed consent was obtained from all parents or legal guardians prior to enrollment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Developmental Assessment\u003c/h2\u003e \u003cp\u003eNeurodevelopmental outcomes were evaluated using the 6-month form of the ASQ-3, a validated parent-completed screening tool [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The instrument assesses five domains: Communication, Gross Motor, Fine Motor, Problem Solving, and Personal-Social. Each domain comprises six items scored as 0 (\u0026ldquo;Not yet\u0026rdquo;), 5 (\u0026ldquo;Sometimes\u0026rdquo;), or 10 (\u0026ldquo;Yes\u0026rdquo;), with a maximum score of 60 per domain. Higher scores indicate more advanced developmental performance. To ensure standardized timing of developmental assessment, parents completed the questionnaire in close temporal proximity to the routine six-month pediatric examination.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Predictor Variables\u003c/h2\u003e \u003cp\u003ePredictor variables were categorized into three conceptual groups: biological, maternal, and environmental factors.\u003c/p\u003e \u003cp\u003e \u003cb\u003eBiological factors\u003c/b\u003e:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eInfant sex,\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eBirth weight (kg),\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eGestational age (weeks),\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eExclusive breastfeeding (yes/no),\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePrenatal alcohol exposure (yes/no)\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eMaternal factors\u003c/b\u003e:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eMaternal education (primary/secondary/university),\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eEarly postpartum return to employment (yes/no).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eEarly postpartum return to employment was conceptualized as a proxy indicator of reduced maternal availability for direct infant caregiving during early infancy.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEnvironmental factors\u003c/b\u003e:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eLanguage environment (monolingual/bilingual),\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDuration of daily caregiver language stimulation.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e Language stimulation referred to the average daily time caregivers spent talking, reading, or verbally interacting with the infant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Statistical Analysis\u003c/h2\u003e \u003cp\u003eData were analyzed using IBM SPSS Statistics (Version 19; IBM Corp., Armonk, NY, USA). Data distribution was assessed for normality. Continuous variables (e.g., birth weight, gestational age, and ASQ-3 scores) are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). Binary and categorical variables (e.g., sex, prenatal alcohol exposure) were dummy-coded (0, 1) for regression purposes and are reported as frequencies and percentages (%).\u003c/p\u003e \u003cp\u003e Pearson correlation coefficients were calculated to examine bivariate associations, with effect sizes interpreted according to Cohen\u0026rsquo;s guidelines. Confidence intervals were derived using Fisher\u0026rsquo;s z transformation. Two-tailed p-values were used to determine statistical significance.\u003c/p\u003e \u003cp\u003eRegression analysis: To evaluate the relative contribution of biological, maternal, and environmental predictors, hierarchical multiple linear regression models were constructed separately for each ASQ-3 developmental domain. Multicollinearity among predictors was assessed using variance inflation factors (VIF).\u003c/p\u003e \u003cp\u003ePredictors were entered sequentially in three hierarchical blocks (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eModel 1 \u0026ndash; Biological factors\u003c/strong\u003e \u003cp\u003esex, birth weight, gestational age, exclusive breastfeeding, and prenatal alcohol exposure.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eModel 2 \u0026ndash; Biological\u0026thinsp;+\u0026thinsp;maternal factors\u003c/strong\u003e \u003cp\u003eModel 1 variables plus maternal education and early postpartum return to employment.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eModel 3 \u0026ndash; Biological\u0026thinsp;+\u0026thinsp;maternal\u0026thinsp;+\u0026thinsp;environmental factors\u003c/strong\u003e \u003cp\u003eModel 2 variables plus language environment and duration of caregiver language stimulation.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThis hierarchical approach allowed assessment of the incremental explanatory contribution of each conceptual group of predictors.\u003c/p\u003e \u003cp\u003eModel fit was evaluated using the coefficient of determination (R\u0026sup2;) and adjusted R\u0026sup2; values. Standardized regression coefficients (β) were used to assess the strength of individual predictors. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Given the relatively low frequency of early postpartum return to employment in the sample, findings related to this variable were interpreted with caution. To account for multiple testing, statistical significance was additionally evaluated using Bonferroni-adjusted p-values.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Sample Characteristics and Developmental Outcomes\u003c/h2\u003e \u003cp\u003eThe final analytic sample comprised 124 full-term infants. The mean birth weight was 3.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41 kg, and the mean gestational age was 39.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2 weeks. Males represented 55.6% of the cohort. Regarding early nutrition, 74.2% of infants were exclusively breastfed. Prenatal alcohol exposure was reported in 14.5% of pregnancies. Detailed demographic and clinical characteristics are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSample Characteristics (N\u0026thinsp;=\u0026thinsp;124)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69 (55.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55 (44.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBirth weight (kg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGestational age (weeks)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eExclusive breastfeeding (yes)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92 (74.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrenatal alcohol exposure (yes)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18 (14.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMaternal education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47 (37.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e76 (61.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEarly postpartum return to paid employment (yes)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (1.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTime spent with child\u0026thinsp;\u0026ge;\u0026thinsp;30 min/day\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e102 (82.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBilingual environment (yes)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25 (20.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eNotes\u003c/strong\u003e \u003cp\u003e \u003cem\u003eData are presented as n (%) unless otherwise indicated. Continuous variables are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD.\u003c/em\u003e \u003c/p\u003e \u003c/p\u003e \u003cp\u003eDevelopmental scores across all ASQ-3 domains were within expected normative ranges. The highest mean scores were observed in \u003cem\u003eProblem Solving\u003c/em\u003e (53.39\u0026thinsp;\u0026plusmn;\u0026thinsp;8.50), followed by \u003cem\u003eFine Motor\u003c/em\u003e (50.27\u0026thinsp;\u0026plusmn;\u0026thinsp;11.89). The \u003cem\u003eGross Motor\u003c/em\u003e domain exhibited the lowest mean score (42.94\u0026thinsp;\u0026plusmn;\u0026thinsp;11.93) and the highest inter-individual variability. Clinical risk for developmental delay (scores below standardized cut-offs) was low, ranging from 0.8% in \u003cem\u003eProblem Solving\u003c/em\u003e to 6.5% in \u003cem\u003eGross Motor\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDevelopmental outcomes at 6 months (N\u0026thinsp;=\u0026thinsp;124)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDomain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBelow Cut-off n (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCommunication\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e49.76\u0026thinsp;\u0026plusmn;\u0026thinsp;8.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.28\u0026ndash;51.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2 (1.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGross Motor\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e42.94\u0026thinsp;\u0026plusmn;\u0026thinsp;11.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.85\u0026ndash;45.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8 (6.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFine Motor\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e50.27\u0026thinsp;\u0026plusmn;\u0026thinsp;11.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.19\u0026ndash;52.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5 (4.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProblem Solving\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e53.39\u0026thinsp;\u0026plusmn;\u0026thinsp;8.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51.90\u0026ndash;54.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (0.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePersonal\u0026ndash;Social\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e48.75\u0026thinsp;\u0026plusmn;\u0026thinsp;9.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.11\u0026ndash;50.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3 (2.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Correlation Analysis\u003c/h2\u003e \u003cp\u003ePearson correlation analysis revealed several significant associations between developmental outcomes and the examined predictors (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePearson Correlations Between Developmental Domains and Significant Predictors with 95% CI (N\u0026thinsp;=\u0026thinsp;124)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDomain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEffect size\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCommunication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;.343 to \u0026minus;\u0026thinsp;.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003esmall\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBirth weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.014 to .348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003esmall\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLanguage stimulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.016 to .350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003esmall\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGross Motor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBirth weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.084 to .405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003esmall\u0026ndash;moderate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExclusive breastfeeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.004 to .339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003esmall\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFine Motor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExclusive breastfeeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.047 to .373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003esmall\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProblem Solving\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBirth weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.043 to .370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003esmall\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePersonal\u0026ndash;Social\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBirth weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.079 to .400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003esmall\u0026ndash;moderate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrenatal alcohol exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;.288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;.436 to \u0026minus;\u0026thinsp;.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eupper small\u003c/p\u003e \u003cp\u003e(approaching moderate)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eNotes\u003c/b\u003e: \u003cem\u003ePearson correlation coefficients (two-tailed).\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e95% confidence intervals were calculated using Fisher’s z transformation.\u003c/h3\u003e\n\u003cp\u003e \u003cem\u003eOnly statistically significant associations (p \u0026lt; .05) are presented.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eBirth weight showed consistent positive correlations with several developmental domains, including communication, gross motor, problem-solving, and personal\u0026ndash;social development. Exclusive breastfeeding showed modest positive correlations with gross motor and fine motor development. Prenatal alcohol exposure was negatively associated with personal\u0026ndash;social development.\u003c/p\u003e \u003cp\u003eMost associations were small in magnitude, with several approaching moderate effect sizes.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Hierarchical Regression Analyses\u003c/h2\u003e \u003cp\u003eHierarchical multiple regression analyses were conducted separately for each ASQ-3 developmental domain to examine the incremental contributions of biological, maternal, and environmental predictors. Three models were constructed for each domain:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eModel 1\u003c/b\u003e: biological factors\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eModel 2\u003c/b\u003e: biological\u0026thinsp;+\u0026thinsp;maternal factors\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eModel 3\u003c/b\u003e: biological\u0026thinsp;+\u0026thinsp;maternal\u0026thinsp;+\u0026thinsp;environmental factors\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eDetailed hierarchical model statistics are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHierarchical Regression Models Across Developmental Domains (N\u0026thinsp;=\u0026thinsp;124)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDomain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ek\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAdj. R\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eΔR\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ef\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eΔf\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5,118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7,116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9,114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGross Motor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5,118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7,116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9,114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFine Motor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5,118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7,116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9,114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProblem Solving\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5,118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7,116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9,114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePersonal\u0026ndash;Social\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5,118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7,116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9,114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003cb\u003eNotes\u003c/b\u003e: \u003cem\u003eM1 \u0026ndash; biological factors, M2 \u0026ndash; biological\u0026thinsp;+\u0026thinsp;maternal factors, M3 \u0026ndash; biological\u0026thinsp;+\u0026thinsp;maternal\u0026thinsp;+\u0026thinsp;environmental factors. Effect size interpretation (Cohen)\u003c/em\u003e: \u003cb\u003ef\u0026sup2; = 0.02 small, f\u0026sup2; = 0.15 medium, f\u0026sup2; = 0.35 large\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAcross domains, biological factors explained a modest proportion of variance in developmental outcomes. The inclusion of maternal and environmental variables resulted in only small increases in explained variance.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.3.1 Communication Development\u003c/h2\u003e \u003cp\u003eThe hierarchical regression models predicting communication development were statistically significant across all three steps. The biological model explained \u003cb\u003e11.0% of the variance\u003c/b\u003e, increasing to \u003cb\u003e14.5% in the final model\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eIn the fully adjusted model, \u003cb\u003esex\u003c/b\u003e, \u003cb\u003ebirth weight\u003c/b\u003e, and \u003cb\u003egestational age\u003c/b\u003e emerged as significant independent predictors. Male sex and lower gestational age were associated with lower communication scores, whereas higher birth weight was associated with better communication performance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2 Gross Motor Development\u003c/h2\u003e \u003cp\u003eFor gross motor development, all three models reached statistical significance. The biological model explained \u003cb\u003e11.3% of the variance\u003c/b\u003e, with the final model explaining \u003cb\u003e14.0%\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eAcross all hierarchical steps, \u003cb\u003ebirth weight\u003c/b\u003e remained the only significant independent predictor. Higher birth weight was consistently associated with improved gross motor performance at six months.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e3.3.3 Fine Motor Development\u003c/h2\u003e \u003cp\u003eHierarchical regression models for fine motor development did not reach statistical significance. Although exclusive breastfeeding showed a modest positive association in the biological model, this effect was not maintained after the inclusion of additional predictors.\u003c/p\u003e \u003cp\u003eOverall, the examined biological, maternal, and environmental variables did not significantly explain variability in fine motor development at six months.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e3.3.4 Problem-Solving Development\u003c/h2\u003e \u003cp\u003eThe biological model predicting problem-solving development reached statistical significance and explained 9.0% of the variance. However, the addition of maternal and environmental factors did not improve model fit.\u003c/p\u003e \u003cp\u003eIn the final model, \u003cb\u003ebirth weight\u003c/b\u003e and \u003cb\u003egestational age\u003c/b\u003e remained significant predictors. Higher birth weight was associated with better problem-solving performance, while lower gestational age was associated with poorer outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e3.3.5 Personal\u0026ndash;Social Development\u003c/h2\u003e \u003cp\u003ePersonal\u0026ndash;social development demonstrated the strongest regression model among all domains. The biological model explained \u003cb\u003e15.9% of the variance\u003c/b\u003e, increasing slightly to \u003cb\u003e16.7% in the final model\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eIn the fully adjusted model, \u003cb\u003ebirth weight\u003c/b\u003e and \u003cb\u003eprenatal alcohol exposure\u003c/b\u003e emerged as significant independent predictors. Higher birth weight was associated with improved personal\u0026ndash;social development, whereas prenatal alcohol exposure was associated with lower personal\u0026ndash;social scores.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Significant Independent Predictors\u003c/h2\u003e \u003cp\u003eSignificant independent predictors identified across hierarchical models are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSignificant Independent Predictors Across Hierarchical Models\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDomain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSignificant Predictor(s)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;.182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.039\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBirth weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGestational age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;.221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;.194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.030\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBirth weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGestational age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;.227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.034\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;.194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.030\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBirth weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGestational age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGross Motor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBirth weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBirth weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBirth weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFine Motor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExclusive breastfeeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProblem Solving\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBirth weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGestational age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;.235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBirth weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGestational age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;.249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBirth weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGestational age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePersonal\u0026ndash;Social\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBirth weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrenatal alcohol exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;.264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBirth weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrenatal alcohol exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBirth weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrenatal alcohol exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;.273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBirth weight emerged as the \u003cb\u003emost consistent predictor\u003c/b\u003e, demonstrating significant associations across multiple developmental domains. Gestational age contributed to communication and problem-solving outcomes, while prenatal alcohol exposure showed a specific negative association with personal\u0026ndash;social development.\u003c/p\u003e \u003cp\u003eExclusive breastfeeding was associated with fine motor development only in the initial biological model.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Comparison of Explanatory Strength Across Domains\u003c/h2\u003e \u003cp\u003ePairwise comparisons of the explanatory strength of the \u003cb\u003ebiological models (Model 1)\u003c/b\u003e across developmental domains were conducted using Fisher\u0026rsquo;s z tests. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, none of the pairwise comparisons reached statistical significance, indicating that the explanatory contribution of biological predictors was comparable across domains.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePairwise comparisons of Model 1 explanatory strength across developmental domains (Fisher\u0026rsquo;s z tests)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComparison\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ez\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunication vs Gross Motor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunication vs Fine Motor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunication vs Problem Solving\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunication vs Personal\u0026ndash;Social\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGross Motor vs Fine Motor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGross Motor vs Problem Solving\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGross Motor vs Personal\u0026ndash;Social\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFine Motor vs Problem Solving\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFine Motor vs Personal\u0026ndash;Social\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProblem Solving vs Personal\u0026ndash;Social\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSimilarly, pairwise comparisons of the explanatory strength of the \u003cb\u003efinal hierarchical models (Model 3)\u003c/b\u003e also revealed no statistically significant differences after Bonferroni correction (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePairwise Comparisons of Model 3 Explanatory Strength Across Developmental Domains\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDomain Comparison\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ez_diff\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBonferroni-adjusted p\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunication vs Gross Motor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunication vs Fine Motor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunication vs Problem Solving\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunication vs Personal\u0026ndash;Social\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGross Motor vs Fine Motor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGross Motor vs Problem Solving\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGross Motor vs Personal\u0026ndash;Social\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFine Motor vs Problem Solving\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFine Motor vs Personal\u0026ndash;Social\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProblem Solving vs Personal\u0026ndash;Social\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAlthough personal\u0026ndash;social development showed the highest explained variance, these differences were not statistically significant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Summary of Key Findings\u003c/h2\u003e \u003cp\u003eAcross the examined developmental domains, \u003cb\u003ebiological factors demonstrated the strongest and most consistent associations with early neurodevelopment\u003c/b\u003e. Birth weight emerged as the most stable predictor across domains, while gestational age and prenatal alcohol exposure showed domain-specific effects.\u003c/p\u003e \u003cp\u003eMaternal and environmental variables contributed minimally to the explanatory power of the models at six months of age.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe present study examined the relative contributions of biological, prenatal, and environmental factors to developmental outcomes at six months of age. Birth weight emerged as the most consistent predictor across developmental domains, while prenatal alcohol exposure demonstrated a specific negative association with personal\u0026ndash;social development.\u003c/p\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Biological risk factors and early development\u003c/h2\u003e \u003cp\u003eThe findings of the present study confirm the central role of biological factors in shaping early neurodevelopment. Risks associated with low birth weight represent a global phenomenon, and neurodevelopmental deficits among these children have been consistently documented across diverse populations [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Both low birth weight and lower gestational age are well-established predictors of neurological outcomes and are frequently associated with an increased risk of later cognitive and motor impairments [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eImportantly, developmental variability is not restricted to extremely preterm or very low birth weight infants. Evidence indicates that even among term-born infants, developmental outcomes follow a gradient pattern related to birth weight [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Each additional increment in birth weight and each additional week of gestation contribute to more favorable outcomes in communication, problem solving, and gross motor development [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. These findings suggest that infants born close to term but with relatively lower birth weight may already exhibit subtle developmental differences by six months of age and therefore warrant careful developmental monitoring.\u003c/p\u003e \u003cp\u003eEarly somatic growth parameters are closely linked to cognitive development. In particular, the rate of head circumference growth during the first six months reflects ongoing neuronal maturation and has been identified as a predictor of future cognitive capacity [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Motor development represents another important indicator of neurological maturation. Delays in gross motor development during the first year have been identified as early markers for later difficulties in fine motor skills and academic functioning [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEven small differences in gestational age among term infants may be associated with slower maturation of cortical structures and motor milestones during infancy [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Taken together, these findings suggest that biological parameters at birth retain prognostic value even among infants born at term. Higher birth weight and longer gestation appear to support more mature neural networks involved in communication and social cognition [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Prenatal alcohol exposure\u003c/h2\u003e \u003cp\u003eThe significant negative association between prenatal alcohol exposure and personal\u0026ndash;social development observed in this study is strongly supported by contemporary literature. Even low to moderate levels of prenatal alcohol exposure have been associated with poorer early cognitive and behavioral outcomes due to disruptions in neural systems involved in attention, emotional regulation, and social cognition [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrenatal alcohol exposure interferes with mechanisms of sensory processing and behavioral regulation. Effective social interaction during infancy requires the integration of multiple external stimuli, including vocal signals, facial expressions, and tactile input. Disruption of these regulatory processes may therefore limit the development of typical social responses during early infancy [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNeuroimaging studies demonstrate that prenatal alcohol exposure is associated with structural alterations in cortical and subcortical brain regions and reduced white matter integrity\u0026mdash;areas that are essential for social cognition and rapid processing of social stimuli [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. These alterations may manifest functionally during infancy as reduced social engagement and impaired self-regulation.\u003c/p\u003e \u003cp\u003eCombined toxic exposures may exert cumulative effects on emotional reactivity and social participation during early development [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Even subclinical levels of prenatal alcohol exposure may therefore produce measurable effects on early social neurofunction, emphasizing the importance of early screening and monitoring of exposed infants.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Effect of exclusive breastfeeding\u003c/h2\u003e \u003cp\u003eInfant feeding during the first six months of life represents an important modulator of early neurodevelopment. Breast milk contains a unique combination of bioactive nutrients\u0026mdash;including long-chain polyunsaturated fatty acids, oligosaccharides, and choline\u0026mdash;that support myelination and structural maturation of white matter pathways in the developing brain [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Evidence indicates that breastfeeding is associated with improved cognitive outcomes, even after adjusting for socioeconomic variables [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThese mechanisms may explain the more favorable developmental tendencies observed among breastfed infants in our study, particularly in early motor domains. However, these associations did not remain significant after adjustment for additional predictors. Nevertheless, breastfeeding remains an important component of early nutritional support and may contribute to optimal neurodevelopment, particularly among infants with biological vulnerabilities.\u003c/p\u003e \u003cp\u003ePrevious research demonstrates that optimal early feeding practices are associated with earlier achievement of gross motor milestones and improved hand\u0026ndash;eye coordination in fine motor tasks [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Maternal nutrition during pregnancy also plays an important role in establishing the foundations of neurogenesis and synaptogenesis, suggesting that prenatal and postnatal nutritional influences operate along a continuous developmental pathway [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdequate nutrition may also partially mitigate the negative effects of prenatal exposures through mechanisms of neural plasticity [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Given the high plasticity of the nervous system during early infancy, optimal nutrition may therefore represent both a preventive and potentially compensatory factor.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Sex differences\u003c/h2\u003e \u003cp\u003eThe present study identified sex-related differences in communication outcomes within the regression models. Previous research indicates that female infants exhibit earlier maturation of social\u0026ndash;communication neural networks during the first year of life [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. These differences may reflect faster cortical organization and earlier integration of frontotemporal connections among girls.\u003c/p\u003e \u003cp\u003eIn contrast, male fetal brains appear more sensitive to prenatal stressors and toxic exposures, resulting in more pronounced structural alterations in brain regions associated with social communication [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Boys also tend to exhibit slower maturation of language-related cortical networks, which may increase vulnerability to developmental delays when additional prenatal risk factors are present.\u003c/p\u003e \u003cp\u003eThese findings highlight the importance of sex-sensitive approaches in early developmental screening and monitoring.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e4.5. Environmental influences and integrative perspective\u003c/h2\u003e \u003cp\u003eEnvironmental and caregiving factors also play an important role in shaping early developmental outcomes. Correlation analyses suggested a positive association between caregiver language stimulation and communication abilities at six months, although this effect did not remain significant in multivariable models. This observation confirms the well-established relationship between parental linguistic input and early communicative behaviors [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough maternal education did not emerge as an independent predictor in the regression models, previous research suggests that enriched home environments associated with higher educational attainment may contribute to improved developmental stimulation [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Responsive parenting behaviors\u0026mdash;including shared attention, reading, and sustained verbal interaction\u0026mdash;have been identified as strong predictors of improved communication outcomes [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Family resources and stable caregiving environments facilitate responsive parenting styles that support both cognitive and personal\u0026ndash;social development [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Importantly, not only the amount of time spent with caregivers but also the quality of interaction appears crucial for early cognitive development [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur findings support contemporary developmental frameworks emphasizing the dynamic interaction between biological vulnerability and environmental context. According to the Developmental Origins of Health and Disease (DOHaD) paradigm, early development emerges through continuous interaction between prenatal biological programming and postnatal environmental influences [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Similarly, models of early brain architecture highlight the role of responsive caregiver\u0026ndash;infant interactions in shaping neural development [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Language stimulation represents an active reciprocal process rather than passive exposure, strengthening synaptic connections within social\u0026ndash;communication networks [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Early investments in communication and social interaction therefore generate long-term developmental benefits [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Strengths and limitations","content":"\u003cp\u003eThe present study has several strengths. Developmental outcomes were assessed using the validated screening instrument ASQ-3, which allows reliable identification of early developmental differences across multiple domains [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Previous studies have demonstrated good agreement between ASQ-3 and standardized developmental assessments such as the Bayley Scales [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe hierarchical analytical approach allowed simultaneous examination of biological, prenatal, and environmental determinants of development, providing a comprehensive perspective on early developmental influences.\u003c/p\u003e \u003cp\u003eSeveral limitations should also be considered. First, the cross-sectional design limits conclusions regarding long-term developmental trajectories. Second, developmental screening relied on parental report, which may introduce reporting bias, although previous validation studies indicate high reliability of parent-completed developmental questionnaires [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Finally, certain prenatal exposures were based on self-reported data and may therefore be subject to underreporting.\u003c/p\u003e"},{"header":"6. Clinical implications","content":"\u003cp\u003eThe findings highlight the importance of routine developmental screening during the first year of life. Early identification of subtle developmental differences at six months may allow timely support and intervention before more pronounced delays emerge later in childhood.\u003c/p\u003e \u003cp\u003eInfants exposed to prenatal risk factors\u0026mdash;particularly prenatal alcohol exposure or lower birth weight\u0026mdash;may benefit from closer developmental monitoring. Pediatric health professionals should also encourage early parent\u0026ndash;infant interaction, responsive communication, and optimal infant nutrition as part of preventive developmental care.\u003c/p\u003e"},{"header":"7. Conclusion","content":"\u003cp\u003eDevelopmental outcomes at six months of age appear to be shaped by a complex interaction between biological characteristics at birth and the quality of the early caregiving environment. Biological factors such as birth weight, gestational age, and prenatal exposures contribute to early developmental variability, while postnatal factors\u0026mdash;including breastfeeding and caregiver interaction\u0026mdash;may function as protective influences.\u003c/p\u003e \u003cp\u003eEarly developmental screening at six months therefore represents an important opportunity to identify infants at increased developmental risk and to support optimal neurodevelopmental trajectories.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eTatyana Itova: Conceptualization; Methodology; Investigation; Data curation; Formal analysis; Writing \u0026ndash; original draft; Writing \u0026ndash; review \u0026amp; editing; Supervision.\u003c/p\u003e\n\u003ch2\u003eFunding Statement:\u003c/h2\u003e\n\u003cp\u003eThis study was conducted under the project \u0026ldquo;WORKSHOP FOR ADVANCED MEDICAL TECHNOLOGIES\u0026rdquo;, No. Д-ФВП-03/04.03.2025, and was financed by the European Union \u0026ndash; NextGenerationEU, through the National Recovery and Resilience Plan of the Republic of Bulgaria, within the framework of the project \u0026ldquo;Scientific University of Ruse\u0026rdquo;, Contract No. BG-RRP-2.013-0001.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRoseboom TJ, Painter RC, de Rooij SR (2023) Developmental origins of health and disease: mechanisms and future perspectives. Nat Rev Endocrinol 19(1):15\u0026ndash;28\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang W et al (2022) Birth weight and neurodevelopmental outcomes in early childhood: a population-based cohort study. J Pediatr 246:45\u0026ndash;52\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHwang SS et al (2024) Gestational age and neurodevelopmental outcomes in early infancy. Pediatrics 153(2):e2023067453\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoyle EM et al (2023) Effects of gestational age at birth on early childhood development. BMJ 380:e072948\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkison LK et al (2024) Prenatal alcohol exposure and infant neurodevelopment: a meta-analysis. BMC Med 22:118\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePruner IM et al (2024) Sensory and behavioral outcomes following prenatal alcohol exposure. Dev Med Child Neurol 66(3):315\u0026ndash;323\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLombardo MV et al (2024) Sex-specific neurodevelopmental trajectories following prenatal adversity. Nat Commun 15:1872\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAadland KN et al (2024) Sex differences in early communication and social development: a longitudinal study. Infancy 29(2):241\u0026ndash;258\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang L et al (2024) Breastfeeding and infant neurodevelopment: a systematic review and meta-analysis. JAMA Pediatr 178(1):52\u0026ndash;61\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGilbreath D et al (2024) Early infant diet and neurodevelopment: neuroimaging insights. Nutrients 16(4):612\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCavicchiolo ME et al (2023) Early stimulation and language outcomes in infancy: a meta-analysis. 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Pediatr Neurol 141:35\u0026ndash;42\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmith A et al (2025) Birth weight gradients and developmental outcomes in term infants. Early Hum Dev 187:105756\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen X et al (2024) Gestational age, birth weight, and early developmental outcomes. Front Pediatr 12:1269814\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee HY et al (2023) Growth parameters and cognitive development in infancy. Child Dev 94(4):1223\u0026ndash;1237\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartinez P et al (2024) Early motor delays as predictors of later academic performance. Dev Psychol 60(2):275\u0026ndash;287\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeo KH et al (2025) Gestational age and cortical maturation during infancy. Neuroimage Clin 36:103224\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSilva PL et al (2023) Prenatal exposures and early brain structure: fetal MRI findings. Neuroimage Clin 39:103497\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eClark JP et al (2025) Combined prenatal exposures and neurodevelopmental outcomes. Neurotoxicol Teratol 92:107123\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSilveira RC et al (2023) Early feeding practices and motor outcomes in infancy. Front Pediatr 11:1198754\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReis A et al (2024) Maternal diet and fetal brain development. J Nutr 154(2):451\u0026ndash;459\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSerwatka L et al (2023) Nutrient supplementation in substance-using pregnancies. Nutrients 15(5):1103\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGillet F et al (2024) Daily parental linguistic input and communicative intent at six months. J Child Lang 51(2):312\u0026ndash;327\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVargas S, Morris L (2023) Maternal education and infant fine motor development. Pediatr Res 94(3):857\u0026ndash;864\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrown JVE et al (2023) Parenting behaviors and developmental outcomes at six months. Dev Psychol 59(10):1854\u0026ndash;1866\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLopez JW et al (2024) Family structure, childcare, and early developmental outcomes. Early Child Res Q 67:101\u0026ndash;112\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHart AR et al (2024) Time spent with caregivers and early cognition. Child Dev 95(1):198\u0026ndash;212\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShonkoff JP et al (2022) Lifelong effects of early childhood adversity and toxic stress. Pediatrics 149(S1):S8\u0026ndash;S15\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCenter on the Developing Child at Harvard University (2024) Serve and return interaction shapes early brain development. Harvard University\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeckman JJ (2006) Early investments in human capital. Science 312(5782):1900\u0026ndash;1902\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSquires J et al (2023) Ages \u0026amp; Stages Questionnaires (ASQ-3): updated normative data and validation. J Dev Behav Pediatr 44(2):95\u0026ndash;102\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBacker L et al (2022) Comparison of ASQ-3 and Bayley Scales in infant developmental screening. Infant Behav Dev 67:101713\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSteenis LJ et al (2025) Reliability of parental-report developmental screening tools. J Pediatr Psychol 50(3):276\u0026ndash;286\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Infant neurodevelopment, Birth weight, Prenatal alcohol exposure, ASQ-3, Early development, Developmental screening","lastPublishedDoi":"10.21203/rs.3.rs-9075705/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9075705/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEarly neurodevelopment results from the interaction between biological conditions at birth and the postnatal caregiving environment. Understanding the relative contribution of these factors during early infancy may improve early identification of children at developmental risk.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate the influence of biological, familial, and environmental predictors on neurodevelopmental outcomes at six months of age.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA cross-sectional study was conducted among 124 healthy term infants aged six months. Neurodevelopment was assessed using the Ages and Stages Questionnaire, Third Edition (ASQ-3), covering five developmental domains: communication, gross motor, fine motor, problem solving, and personal–social development. Predictors were grouped into biological factors (sex, birth weight, gestational age, exclusive breastfeeding, prenatal alcohol exposure), maternal factors (maternal education and early postpartum return to employment), and environmental factors (language environment and duration of language stimulation). Hierarchical multiple regression analyses were performed to evaluate the independent contribution of each predictor group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBiological factors demonstrated the strongest and most consistent associations with early developmental outcomes. Birth weight emerged as the most stable predictor\u003cstrong\u003e,\u003c/strong\u003e showing significant positive associations with communication, gross motor, problem-solving, and personal–social development. Prenatal alcohol exposure was independently associated with lower personal–social scores. Sex differences were observed in communication outcomes, with female infants demonstrating slightly higher scores. Maternal and environmental factors contributed only modestly to explained variance and were not retained as independent predictors in the final regression models.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEarly neurodevelopment at six months appears to be primarily influenced by biological characteristics at birth\u003cstrong\u003e,\u003c/strong\u003e particularly birth weight, while prenatal alcohol exposure represents a specific risk factor for early social development.\u003c/p\u003e","manuscriptTitle":"Multifactorial Predictors of Infant Neurodevelopment at Six Months: A Hierarchical Regression Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-18 08:43:26","doi":"10.21203/rs.3.rs-9075705/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"08d03196-7074-48f8-9044-e65cee6919b1","owner":[],"postedDate":"March 18th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-20T09:55:48+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-18 08:43:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9075705","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9075705","identity":"rs-9075705","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}