The influence of early nutrition intake and clinical factors on the brain development of preterm infants with intrauterine growth restriction

Introduction

Intrauterine growth restriction (IUGR) refers to a pathological condition in which the fetus is in a state of long-term hypoxia and nutrient deficiency due to factors related to the placenta, fetus, and maternal health, failing to reach the biological potential of normal fetal growth (1,2). IUGR is the primary cause of preterm birth and intrapartum asphyxia, also it is one of the main causes of perinatal death (1,2). Statistics show that IUGR occurs in 10–20% of all pregnancies worldwide (3,4), and the relative incidence is higher in low- and middle-income countries (LMICs) (5).

The critical processes of brain development and maturation occur in the middle and advanced stages of pregnancy, making the brain particularly vulnerable to perinatal growth defects during this period (6). Due to intrauterine malnutrition, infants with IUGR are often preterm and small for gestational age (SGA). Fetal magnetic resonance imaging (MRI) has confirmed that IUGR can lead to reduced brain volume and organizational differences in various brain regions (6,7). After birth, IUGR infants are prone to feeding intolerance and complications. Compared with appropriate for gestational age (AGA) infants of the same gestational age, IUGR infants are more likely to experience extrauterine growth restriction (EUGR) and have smaller head circumferences and brain volumes (8,9). Literature reports that fetal brain injury and poor brain development are closely related to long-term neurodevelopmental adverse outcomes in motor ability, cognitive function, and behavioral disorders, which then extend to childhood and adolescence (10,11). This suggests that there may be an association between abnormal brain growth trajectories during pregnancy and after birth. It is worthy to further evaluate the influencing factors of the development of different brain regions in IUGR infants at term-equivalent age (TEA).

Active and reasonable nutritional strategies can reduce the incidence of early complications and mortality, meanwhile improving early growth and long-term neurodevelopmental outcomes (12-14). Therefore, separate analysis of the associations of macronutrients (protein, fat, carbohydrates) and energy supply on brain development can help pediatricians better formulate nutritional plans.

Quantifying the brain growth of high-risk populations by separately measuring different regions of the brain MRI is a reliable and easily applicable biometric method (15). This study collected the basic clinical characteristics and the intake of macronutrients in the first week of preterm infants with and without IUGR. The sizes of various brain regions were measured on head magnetic resonance images obtained at TEA. This study aimed: (I) to evaluate the differences in the sizes of various brain regions between preterm infants with and without IUGR at TEA; (II) to evaluate the association between the macronutrient intake in the first week of life and the size of various brain regions at TEA in two groups of preterm infants; (III) to identify the main independent factors that affect cerebral growth at TEA in preterm infants. We present this article in accordance with the STROBE reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-2025-432/rc).

Methods

This is a retrospective study of preterm infants who were hospitalized in the department of pediatrics, The Second Xiangya Hospital of Central South University from January 1, 2015, to December 31, 2019. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The research protocol was approved by the Clinical Research Ethics Committee of The Second Xiangya Hospital of Central South University [(2020) approval No. K004] and individual consent for this retrospective analysis was waived.

Objects

Inclusion criteria: (I) hospitalized within 24 hours after birth; (II) gestational age of the infants <37 weeks. Exclusion criteria: (I) congenital malformations; (II) congenital metabolic defects; (III) congenital central nervous system infections; (IV) failure to undergo cranial MRI examination at TEA or missing important data.

According to the definition in the 2021 Practice Bulletin on Fetal Growth Restriction of the American College of Obstetricians and Gynecologists (ACOG), infants whose prenatal ultrasound results indicated that the fetal abdominal circumference or weight <10^th percentile were defined as the IUGR group, and the rest were the non-IUGR group (15).

Clinical parameters

Clinical data were retrieved from the medical record database of The Second Xiangya Hospital of Central South University. Infants with a birth weight of <10^th percentile for gestational age were categorized as SGA, and those with birth weights within the 10–90^th percentile were categorized as AGA using the Fenton growth chart for weight and sex (16,17). The z-scores for weight, length, and head circumference at birth or discharge were calculated using the Fenton 2013 growth curve.

Nutrient intake and calculation

Data on daily cumulative parenteral and enteral protein, fat, carbohydrate, and caloric intake during the first week of life were retrieved from electronic medical records. Enteral nutrition from preterm human milk and preterm formulas were recorded separately. The preterm human milk intake was assumed to be 65 kcal/100 mL, 1.5 g protein/100 mL, 3.5 g fat/100 mL, and 6.9 g of carbohydrates/100 mL (18,19). Caloric data of formula was calculated as: 3.4, 9 and 4 kcal calories provided per 1 g of fat, carb, and protein, respectively. Macronutrient content of formula, breast milk fortifiers, and parenteral nutrition was calculated based on the published manufacturer’s records. Enteral and parenteral daily protein, fat, and carbohydrate intake (g/kg per day) and energy intake (kcal/kg per day) were calculated in the first week of life.

MRI and linear measurements

All enrolled infants underwent cerebral MRI scans during TEA, and brain region structural changes between the two study groups were evaluated using T1-weighted anatomical images. The changes in the brain regions were assessed by brain “tissue” linear measurements, following previously published methods (20-22). Brain metrics included: the bifrontal diameter (BFD), left and right frontal lobe heights (were defined as FH-L and FH-R, respectively), corpus callosum (CC) thickness (genu, body, and splenium), and transverse cerebellar diameter (TCD). To correct for differences in head size, the biparietal diameter (BPD) and occipitofrontal diameter (OFD) were used to calculate the cephalic index (CI): CI=BPD/OFD ×100. All brain metrics were adjusted using the CI (23,24).

Statistical analysis

The reliability between the measurements was obtained by two radiologists who were blinded to the study protocol and aims. The intraclass correlation coefficients (ICC) for consistency (2-way random model, single measure) were calculated to analyze the inter-observer agreement.

The Shapiro-Wilk test was used to assess normality, and the Levene’s test was used to assess the homogeneity of variance. Quantitative data were reported as mean and standard deviation (SD) or median and interquartile range (IQR), as appropriate, and adjusted by the t-test or Mann-Whitney U test. Categorical variables were reported as frequencies and percentages using the Chi-squared (χ²) test. Pearson’s correlation coefficient or Spearman’s correlation coefficient were calculated to quantify the strength of the correlation between brain metrics and nutritional intake in the first week of life, or other clinical parameters. Subsequently, the simultaneous influence of confounding variables on the brain metrics of the dependent outcome variables was assessed using multiple regression analysis.

The level of significance for all statistical tests were two-sided, P<0.05 was considered significant. All tests were performed using IBM SPSS Statistics for Windows version 26.

Results

Clinical characteristics of the study population

Here, 222 infants were eligible, and 192 cases were enrolled as shown in Figure 1. Excluded cases included: 12 due to lack of ultrasound data at gestation; one due to death; 10 due to transfer to another hospital or unavailable MRI data; five due to congenital malformation; one due to Down syndrome; and one due to congenital infections of the central nervous system. Seventy-four cases were classified into the IUGR group, and 118 cases were classified into the non-IUGR group.

Figure 1 The flowchart of the patient enrollment. IUGR, intrauterine growth restriction; MRI, magnetic resonance imaging; TEA, term-equivalent age.

Table 1 presents how the two groups differed markedly in baseline clinical features. Overall, the growth and developmental indicators of IUGR infants lagged behind those of non-IUGR infants both at birth and at discharge. In addition, the incidence of SGA was higher in the IUGR group [60 (81.1%) vs. 6 (5.1%), P<0.001], and preterm infants with IUGR also had lower 1-minute Apgar scores [7 (IQR, 6–7) vs. 8 (IQR, 7–8), P=0.02], and longer length of hospital stay [40 (IQR, 33–50) vs. 35 (IQR, 29–39), P=0.003].

Differences in maternal characteristics, incidence of eclampsia, hypertension during gestation, and use of antenatal steroids were higher in the IUGR group than in the non-IUGR group [40 (54.1%) vs. 14 (11.9%), P<0.001; 42 (56.8%) vs. 12 (10.2%), P<0.001; 70 (94.6%) vs. 88 (74.6%), P=0.01, respectively]. There was no statistically significant difference in the frequency of perinatal outcomes between the two groups (P>0.05). Regarding the feeding protocol, the duration of artificial feeding was longer in the IUGR group [32 (IQR, 18–39) days vs. 20 (IQR, 8–34) days, P=0.04] than in the non-IUGR group. Furthermore, there was no significant difference in gestational age between the two groups of infants who underwent MRI (P>0.05).

Correlation between brain metrics and early nutrition intake

The interobserver reliability was excellent for all cerebral structure measurements, and the minimum ICC was 0.862 (Table 2). A comparison of the cerebral structural linear measurements between the IUGR and non-IUGR groups is shown in Table 3. The results showed that infants with IUGR had a reduced median (IQR) OFD [10.68 (IQR, 10.21–11.11) vs. 9.83 (IQR, 9.50–10.39) cm, P=0.008]. Among other linear measures of brain structure, the mean ± SD or median (IQR) of BFD, FH-L, FH-R, TCD, genu and body of CC (all adjusted for CI) in the IUGR group were lower than those in the non-IUGR group [7.87±0.69 vs. 7.40±0.85 mm, P=0.004; 5.64±0.78 vs. 5.33±0.82 mm, P=0.04; 5.72±0.78 vs. 5.36±0.79 mm, P=0.04; 5.83 (IQR, 5.57–6.16) vs. 5.59 (IQR, 5.35–5.86 mm), P=0.049; 0.0266 (IQR, 0.0232–0.0292) vs. 0.0240 (IQR, 0.0214–0.0262) mm, P=0.02; 0.0188 (IQR, 0.0149–0.0223) vs. 0.0161 (IQR, 0.0146–0.0197) mm, P=0.02, respectively].

The relationship between cerebral structure measurements and macronutrient intake in the first week of life is shown in Table 4. This study observed that protein intake (g/kg per day) in the first week of life was positive associated with BFD/CI, FH-L/CI and FH-R/CI in the non-IUGR group (r=0.269, P=0.04; r=0.302, P=0.02; r=0.286, P=0.03, respectively). No correlation between cerebral structure measurements and early nutrition intake was observed in the IUGR group.

Multiple linear regression analysis of brain metrics at TEA

The potential correlations between clinical parameters with measurements of different cerebral structures were examined. Variables with P values <0.1 in these analyses were considered for multiple regression analysis, the results of which are shown in Table 5.

Three parameters, namely length at discharge z-score (B=0.286, P<0.001), duration of breastfeeding (B=0.040, P=0.003) and head circumference at discharge z-score (B=0.154, P=0.01), were independently and significantly associated with BFD/CI at TEA, and multiple regression analysis revealed a coefficient of determination of R²=0.558.

The multiple regression analysis model of FH-L/CI at TEA included two identical variables: length at discharge z-score (B=0.279, P<0.001), duration of breastfeeding (B=0.044, P=0.004), the coefficient of determination R²=0.437. Meanwhile, the model of FH-R/CI included three identical variables: length at discharge (B=0.151, P<0.001), duration of breastfeeding (B=0.041, P=0.005), head circumference at discharge z-score (B=0.025, P=0.03), the coefficient of determination R²=0.481.

Three parameters including, the length at discharge z-score (B=0.168, P=0.01), gestational age (B=0.245, P=0.02), and respiratory distress syndrome (RDS) (B=-0.363, P=0.02) were independently and significantly associated with TCD/CI at TEA. The parameters differentially influenced the TCD/CI. The length at discharge z-score and gestational age were positively correlated, whereas RDS weas negatively correlated. Multiple regression analysis revealed a coefficient of determination R² of 0.399.

The multiple regression analysis model of the genus CC/CI consisted of two variables, birth weight (B=0.004, P=0.02) and gestational diabetes mellitus (GDM) (B=−0.003, P=0.02). Birth weight showed a positive correlation, whereas GDM was negative correlated, the coefficient of determination was R²=0.344. The model of the body of the CC/CI involved two parameters, birth weight (B=0.003, P=0.007) and intraventricular hemorrhage (IVH) (B=−0.002, P=0.01). Among them, birth weight was positive correlated, and IVH was negative correlated, the coefficient of determination R²=0.403. Three parameters included IVH (B=−0.003, P=0.002), birth weight (B=0.003, P=0.01) and gestational age (B=0.001, P=0.01) were independently and significantly associated with the splenium CC/CI. Among them, IVH showed a negative correlation, whereas birth weight and gestational age were positive correlated, the coefficient of determination for the model was R²=0.452.

Discussion

IUGR is a pathological state of restricted fetal growth and development, which has a profound impact on the brain development of newborns. This study investigated the differences in the brain development at TEA between IUGR infants and AGA infants of the same gestational age. It also revealed multiple factors affecting the development of various brain regions at TEA, including length at discharge z-score, head circumference at discharge z-score, length at discharge, gestational age, birth weight, duration of breastfeeding, GDM, RDS, and IVH.

Previous studies have shown that adjusting the CI can reduce the errors caused by the head size of fetuses with IUGR (23,24). Therefore, all the measurements of the intracranial regions in this study were adjusted for CI. This study observed that compared with AGA preterm infants without IUGR, the BFD/CI, FH-L/CI, FH-R/CI, TCD/CI, genu of CC/CI, and body of CC/CI in the IUGR group were reduced at TEA. This result once again confirms that IUGR infants were still under the influence of abnormal growth trajectories after birth, and the delayed brain development during the fetal period can continue after birth. Reports have indicated that compared with AGA preterm infants, preterm infants with IUGR exhibited a relative volumetric decrease in gray matter in limbic regions and had lower cognitive and motor scores in toddlerhood (9). Furthermore, children born with IUGR still demonstrated smaller total intracranial volumes and persisting impaired cognitive outcome (8,25). Previous literature reported that fetuses or infants in the early postnatal life with IUGR had thinner genu, body, and splenium of the CC, and shorter length of the CC (26,27). The results of this study verify that the CC of IUGR infants at TEA still lagged behind that of non-IUGR infants.

Protein essentially serves as the structural scaffolds for all human cells. Therefore, the growth and development of the brain rely on a high rate of protein synthesis. Previous literature reported that adequate protein intake in the early stages of life was beneficial for maintaining the integrity of brain white matter and promoting its maturation (12), and showed a positive correlation with higher cognitive and motor scores (28). However, there is also evidence reported the uncertainty of the impact of early protein intake on brain development. No significant correlation between higher protein intake and brain volume or improvement in long-term cognitive and motor development was observed (29,30). A possible explanation for these contradictory results is that different protein intake routes contribute differently to brain development (13). Compared with parenteral protein intake, enteral protein intake may promote white matter formation by increasing the level of insulin like growth factor-1 (IGF-1) and reducing inflammation through the communication of the microbiome-gut-brain axis (13,28). This study reported that in non-IUGR infants, the protein intake in the first postnatal week (g/kg per day) was positively correlated with BFD/CI, FH-L/CI, and FH-R/CI. While no such association was observed in IUGR infants. A possible explanation is that IUGR infants mainly obtain nutrition through parenteral routes in the early stages of life due to diseases and intolerance to enteral feeding. The impact of parenteral protein intake on brain development may be confounded by insufficient nutritional intake caused by fluid restriction and other diseases. Secondly, IUGR infants are also considered a high-risk group for impaired brain development, and are prone to brain injury and delayed brain development. Some research had also reported negative correlation between parenteral protein intake and brain measurements (31). The association of micronutrients to the early brain development of preterm infants is also worth exploring. Iron is a critical nutrient for brain development because it has a direct synthetic role in basic neuronal processes such as myelination, energy metabolism, and neurotransmitter synthesis (28). Postnatal iron deficiency demonstrates negative effects on short and long-term brain development and function (28,32). Zinc is considered essential for various biological and physiological processes in neurobiology such as oligodendrocyte genesis, neurogenesis, neuronal differentiation, white matter growth (28,33). Long-chain polyunsaturated fatty acids (LC-PUFAs) are important structural components of neural cellular membranes. In particular, docosahexaenoic acid (DHA) is crucial for the brain development of fetal and infant (34). A double-blind, randomized controlled trial showed that early enteral supplementation of arachidonic acid and DHA in preterm infants improves brain white matter maturation. Due to insufficient reserves and the dynamic changes in intake requirements with rapid postnatal growth (35), preterm infants have an increased risk of micronutrient deficiency, which is worthy of further exploration in future research.

This study reveals the importance of length and head circumference at discharge in predicting brain development. The length at discharge z-score is positively correlated with three brain measurements: BFD/CI, FH-L/CI, and TCD/CI. The length at discharge is positively correlated with the FH-R/CI. The head circumference at discharge z-score is positively correlated with the BFD/CI and FH-R/CI. There is a positive association between head circumference at discharge and deep gray matter volume (31). Infants with smaller head circumference at birth (<−2SD) or poor head circumference growth (dZ score <−2SD) have higher risk of adverse neurodevelopmental outcomes at 2 years of age (36). In the study by Egashira et al. (37), it was observed that larger head circumference z-score and body length z-score at full term were important indicators of better psychomotor development in very low birth weight infants at 3 years of age. The study by Cordova et al. (38) showed that poor growth of head circumference and body length was a risk factor for lower neurodevelopmental scores in infants at 18 months of age. This study showed birth weight is positively associated with the genu of CC/CI, body of CC/CI, and splenium of CC/CI, and gestational age is positively associated with the TCD/CI and the splenium of CC/CI. Previous studies have suggested that the gestational age at birth is positively correlated with the development of the CC and cerebellum (24). Meanwhile, various perinatal injuries and neonatal diseases included GDM, RDS, IVH can induce a reduction in brain volume and were unfavorable for the development of the nervous system (39,40). The results of this study were basically consistent with the descriptions in the literature. This study showed that the duration of breastfeeding is positively associated with the measurements of three brain regions. Breast milk has a positive effect on the total brain volume, regional brain volume, and white matter development in premature infants (41). Breast milk contains many bioactive components and substrates such as human milk oligosaccharides and fatty acids, which support the development of a healthy gut microbiota and immune system, reduce inflammation in white matter development, and facilitate the maturation and connection of white matter (41,42).

There are some limitations in this study. First, this study did not consider the influence of social determinants of health (SDOH) on health inequities, which may lead to results that inadequately reflect actual health disparities. Second, the coverage of prenatal diseases related to IUGR in this study was not comprehensive enough. The limitations of the included variables may introduce bias. Third, health care providers who cared for these infants may have provided different nutritional plans based on the IUGR status of infants, while the effects of varying nutrition intake routes and micronutrients intake were not fully considered, which requires further exploration in future studies. Finally, this study was a single-center observational study with a small sample size, and the generalizability of its results may be limited by variations in medical resource allocations or population demographics. Despite these limitations, the results of this study can still be generalized to be applicable in clinical practice through the following paths: firstly, all associated factors are routine clinical indicators applicable in medical institutions at all levels. The factors can serve as potential predictors in risk prediction models, facilitating early rapid screening of high-risk populations in clinical practice. Secondly, associations between the development of different brain regions and distinct clinical factors can provide a targeted assessment basis for clinicians and optimize follow-up strategies. Thirdly, exploring multidimensional factors associated with brain development delay in IUGR preterm infants can facilitate the establishment of a multidisciplinary collaborative management model involving neonatology, neurology, nutrition, and other disciplines. Lastly, it offers preliminary evidence and research directions for future multi-center studies.

Conclusions

IUGR infants were more likely to have smaller brain measurements at TEA, and the correlation of early macronutrients to brain development may be confounded by the effects of nutrition regimens and neonatal morbidities. Although the present study showed that no association was observed between IUGR and the brain development at TEA, the relevant growth indicators of the infant were correlated with the brain measurements. Therefore, while IUGR increased the risk of SGA or EUGR in neonate, it also increased the risk of delayed brain development.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-432/rc

Data Sharing Statement: Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-432/dss

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-432/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-2025-432/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The research protocol was approved by the Clinical Research Ethics Committee of The Second Xiangya Hospital of Central South University [(2020) approval No. K004] and individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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