Exclusive Human Milk Diet Is Associated with Lower Risk of Motor Function Impairment by Three Years of Age

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Methods: We conducted a retrospective study between 2018 and 2021. Infants who received an EHMD for > 75% of days between first day of diet fortification and 33 6/7 weeks postmenstrual age were assigned to the EHMD group. We used inverse propensity sores to balance potential confounders and developed a mixed-effects logistic regression model to assess the association. Results: After adjusting for demographics and morbidities, an EHMD was found to be associated with a reduced risk of motor function impairment, with an odds ratio of 0.74 (95% confidence interval of 0.56–0.98, p-value = 0.033). Conclusions: An EHMD is associated with a decrease in early childhood motor function impairment among infants born at less than 32 weeks of gestation. Health sciences/Diseases/Neurological disorders/Neurodevelopmental disorders Health sciences/Risk factors Figures Figure 1 INTRODUCTION Human milk-based nutrition is the standard of care for infants born under 32 weeks and very low birth weight infants [ 1 ]. To meet the unique nutritional needs and growth of these infants, multi-nutrient fortification of either mother’s own milk (MOM) or donor human milk (DHM) is recommended [ 2 , 3 ]. Evidence suggests that multi-nutrient fortification reduces the morbidities associated with prematurity and improves neurodevelopmental outcomes. Fortification of MOM or DHM can be achieved using either bovine milk-based fortifier (BMBF) or human milk-based fortifier (HMBF). An exclusive human milk diet (EHMD) consists of MOM or DHM as the primary milk source, which is supplemented with HMBF. EHMD was found to be associated with a decrease in the incidence of necrotizing enterocolitis (NEC), especially in those settings where the NEC rates are high, as well as other morbidities such as late-onset sepsis, days on mechanical ventilation, retinopathy of prematurity (ROP), and bronchopulmonary dysplasia (BPD) [ 4 – 10 ]. There is conflicting evidence on the relationship between EHMD and short-term postnatal growth, with numerous studies showing reduced growth associated with EHMD use [ 7 , 8 , 11 – 14 ]. Using a recent cohort of infants born < 32 weeks at Kaiser Permanente Southern California (KPSC), we also showed reduced length growth associated with an EHMD. In a post-hoc analysis, we observed comparable length growth and improved weight growth associated with EHMD fortified directly to a caloric density of 26 kcal/oz, after accounting for confounders and adjusting for neonatal morbidities.[ 15 ] Neurodevelopmental outcomes in early childhood are often used as indicators to evaluate the quality of care given to preterm infants in NICUs. The late second and early third trimesters are crucial for rapid brain development, which is significantly interrupted by preterm birth before 32 weeks of gestation. Various factors, such as prolonged respiratory support, illness severity, acute brain injury, nutritional intake, and growth during this critical period, influence neurodevelopmental outcomes. Slower growth has been correlated with higher risks of NDI [ 16 , 17 ]. In contrast, the use of human milk and breastfeeding have been shown to improve neurodevelopmental outcomes in both term and preterm infants [ 18 – 20 ]. Specific components of human milk, such as long-chain polyunsaturated fatty acids (LC-PUFA), lactoferrin, and human milk oligosaccharides (HMOs), are believed to play a role in supporting favorable neurodevelopmental outcomes [ 18 , 21 – 23 ]. The impact of an EHMD on early childhood neurodevelopmental outcomes has been reported in the literature, with conflicting results[ 12 , 24 – 26 ]. In a pragmatic trial by Hopperton et al., infants weighing less than 1,250 g between 2014 and 2016 were block-randomized to receive either a human milk-based fortifier (HMBF) or a bovine milk-based fortifier (BMBF). Neurodevelopmental outcomes assessed at 18 months of corrected age revealed no significant differences between the two groups [ 24 ]. Conversely, a multicenter retrospective study conducted across six NICUs between 2006 and 2010 reported superior cognitive outcomes at 18–22 months of age, assessed by the Bayley Scales of Infant and Toddler Development (BSID), among infants fed an EHMD. However, no significant differences were observed in language or motor outcomes, and these findings remained consistent in both univariate analyses and after adjusting for factors such as birth weight, sex, enteral feeding, and NEC [ 26 ]. Additionally, Colacci et al. found no differences in BSID cognitive scores between groups [ 12 ], while the study by Bergner et al. did not include a non-EHMD comparison group [ 25 ]. In this study, we leverage an established KPSC cohort to examine the association between EHMD and motor function impairment by three years of age. METHODS Study Design, Eligibility Criteria, and Oversight We conducted a multicenter retrospective study involving infants born at less than 32 weeks of gestation between January 1, 2018, and June 30, 2021, across 13 NICUs within KPSC [ 15 ]. This cohort represents a subset of our previously published study, including only those infants who had reached three years of corrected age by the time of analysis. Infants with major congenital anomalies or those who were no longer Kaiser Permanente members by six months of corrected age, either due to mortality or member attrition, were excluded. Additionally, we excluded infants without documented feeding information at 34 weeks postmenstrual age (PMA) or with missing data on feeding caloric density. The study was approved by the KPSC Institutional Review Board (IRB), which waived the requirement for informed consent (IRB #: 13350). Data Collection Demographic and morbidity data were collected from the Clarity database, a reporting database of Epic electronic healthcare records, or the research database at KPSC. No artificial intelligence or natural language processing algorithms were used for data extraction. Morbidity and outcome diagnoses were based on international classification of diseases-tenth edition (ICD-10) codes. Maternal variables collected include age, smoking status during pregnancy, delivery modes, antenatal corticosteroid administration, hypertensive disorders of pregnancy (HDP, including preeclampsia, eclampsia, HELLP syndrome), fetal growth restriction (FGR), gestational diabetes mellitus (GDM), obesity, and placental abruption. Neonatal variables extracted include birth hospital, sex, race/ethnicity, gestational age (GA), length of stay, APGAR scores at 1 and 5 minutes, IVH, ROP, NEC, spontaneous intestinal perforation (SIP), and BPD (based on the 2019 Jensen criteria[ 27 ]). NEC and SIP diagnoses were further evaluated by manual chart review. Anthropometric data collected include weight, length, and head circumference measurements from birth to 33 6/7 weeks PMA. Weight was typically measured daily, whereas length and head circumference were typically measured weekly, but the frequency may change depending on clinical needs. The method for conducting the measurements was unavailable. The birth measurements were the measurements closest to the infants’ birth dates. Birth measurement percentiles as well as weight and length growth trajectory percentiles were calculated based on the 2023 Postnatal Growth Charts for Preterm Infants [ 28 ]. The differences between birth and trajectory percentiles were calculated to represent the quality of growth in the NICUs. EHMD was made possible by using the Prolacta® products. Since NICUs that implemented an EHMD transitioned infants from HMBF to BMBF at varying postmenstrual ages (PMAs) after 34 0/7 weeks, we limited our analysis to diet data collected before 34 0/7 weeks PMA to assign infants to either the EHMD or non-EHMD group. Daily diet order was used to determine whether the infant received EHMD for the day or not. The percentage of EHMD was calculated as follows: $$\:\frac{Total\:days\:receiving\:EHMD}{Total\:days\:between\:the\:day\:of\:the\:first\:fortified\:feed\:and\:33\:6/7\:weeks\:PMA}\times\:100\:\left(\%\right)$$ Based on our previous study, infants who received EHMD for ≥ 75% of the days were assigned to the EHMD group [ 15 ]. The remainder of the infants were assigned to the non-EHMD group regardless of whether the non-EHMD feeds were preterm formula or MOM/DHM fortified with BMBF. Caloric density data were collected from nursing documentation of each feed in the flowsheet. Infants were classified as having motor function impairment if they had any of the following ICD-10 codes in their medical charts―M62.9 (hypotonia), G80.X (cerebral palsy), or F82 (specific developmental disorder of motor function)―before reaching 3 years of corrected age. Statistical analysis Continuous variables were presented as median [interquartile range (IQR)]. Categorical variables were presented as number (percentage). The rank sum test was used to compare continuous variables, and the Chi-squared test was used for categorical variables. Standardized mean differences (SMD) were presented in demographic summarization of the confounders. P-values were presented for all comparisons. A P-value < 0.05 was considered statistically significant. To account for perinatal confounders between the EHMD vs. non-EHMD groups due to variations in EHMD implementation protocols across NICUs, we used inverse propensity weighting (IPW) to balance potential confounders. Propensity scores were derived using generalized boosted regression modeling to estimate the population average treatment effect [ 29 ]. Variables used for propensity score estimation were potential confounders before the beginning of diet fortification in typical modern neonatal practices, including maternal age, maternal obesity, HDP, GDM, FGR, chorioamnionitis, antenatal corticosteroids, infant race/ethnicity, birth GA, infant sex, birth measurement (weight, length, and head circumference) percentiles, as well as 1- and 5-min APGAR scores. A weighted mixed-effects logistic regression model was developed to assess the risk of motor function impairment. Fixed-effect covariates include GA (categorized into 22–25, 26–27, 28–29, and 30–31 groups to improve model fit), infant sex, ROP ≥ stage 2, grade 3/4 IVH, grade 2/3 BPD, total antibiotics days, difference in trajectory and birth percentiles for weight and length. Medical centers were included as a random-effect term to account for outcome variations among centers. The risk of motor function impairment was presented as odds ratio (OR) and its 95% confidence interval (CI). RESULTS Infant characteristics We identified 1,210 infants who met the selection criteria, with 916 infants in the non-EHMD group and 294 in the EHMD group. Infants in the EHMD group were born earlier (median GA of 27 weeks for the EHMD group vs. 30 weeks for the non-EHMD group). Their perinatal characteristics are listed in Table 1 . Birth weight and length percentiles were significantly lower among infants in the EHMD group. More infants in the EHMD group were small for gestational age (SGA) and fewer were large for gestational age (LGA). Both 1-min and 5-min APGAR scores were lower in the EHMD group. After IPW, the weighted population had 1,976 infants, with 1,142 in the non-EHMD group and 834 in the EHMD group. The perinatal characteristics of the weighted population are listed in Table 2 . The SMD of GA became much smaller (from 0.797 to 0.118). However, the difference between the two groups remained statistically significant (median GA of 29 weeks in the non-EHMD group vs. 28 weeks in the EHMD group). Birth weight and length, as well as APGAR scores were well balanced. Table 1 Perinatal characteristics of the non-weighted cohort. Variables Non-EHMD (n = 916) EHMD (n = 294) p-value* Standardized Mean Difference Maternal Age (year), median [IQR] 32 [ 28 , 35 ] 33 [ 29 , 36 ] 0.007 0.181 Hypertensive disorder of pregnancy, n (%) 274 (29.9) 87 (29.6) 0.975 0.007 Gestational diabetes mellitus, n (%) 104 (11.4) 32 (10.9) 0.908 0.015 Obesity, n (%) 318 (34.7) 86 (29.3) 0.097 0.117 Placental abruption, n (%) 142 (15.5) 47 (16.0) 0.915 0.013 Chorioamnionitis, n (%) 72 (7.9) 34 (11.6) 0.066 0.125 Antenatal corticosteroids, n (%) 862 (94.1) 286 (97.3) 0.046 0.157 Non-smoker during pregnancy, n (%) 846 (92.4) 264 (89.8) 0.523 0.096 Vaginal delivery, n (%) 287 (31.3) 69 (23.5) 0.012 0.177 Fetal growth restriction, n (%) 13 (1.4) 7 (2.4) 0.388 0.07 Neonatal Gestational age (week), median [IQR] 30 [ 28 , 31 ] 27 [ 25 , 29 ] < 0.001 0.797 Hispanic, n (%) 511 (55.8) 172 (58.5) 0.114 0.239 § Male Sex, n (%) 470 (51.3) 154 (52.4) 0.801 0.021 Birth weight percentile, median [IQR] 55.2 [30.0, 77.0] 46.0 [17.1, 68.2] < 0.001 0.336 Birth length percentile, median [IQR] 52.8 [32.2, 73.8] 45.9 [18.1, 73.0] 0.004 0.195 Birth head circumference percentile, median [IQR] 52.6 [32.8, 74.8] 50.1 [25.4, 74.8] 0.055 0.129 SGA, n (%) 82 (9.0) 56 (19.0) < 0.001 0.294 LGA, n (%) 89 (9.7) 8 (2.7) < 0.001 0.293 1-min APGAR, median [IQR] 7 [ 5 , 8 ] 6 [ 4 , 7 ] < 0.001 0.249 5-min APGAR, median [IQR] 8 [ 8 , 9 ] 8.0 [ 7 , 9 ] 0.005 0.189 EHMD: exclusive human milk diet; SGA: small for gestational age; LGA: large for gestational age; IQR: interquartile range. *Chi-squared test for categorical variables, rank-sum test for non-parametric continuous variables. § Statistical test performed for comparing race/ethnicity assignment among White, Hispanic, Black, Asian, Pacific Islander, Multiple, and Other. Table 2 Perinatal characteristics of the weighted population. Variables Non-EHMD (n = 1,142) EHMD (n = 834) p-value* Standardized Mean Difference Maternal Age (year), median [IQR] 32 [ 28 , 35 ] 33 [ 28 , 36 ] 0.831 0.010 Hypertensive disorder of pregnancy, n (%) 344 (30.1) 252 (30.3) 0.976 0.003 Gestational diabetes mellitus, n (%) 123 (10.7) 78 (9.4) 0.558 0.046 Obesity, n (%) 389 (34.1) 240 (28.8) 0.160 0.114 Placental abruption, n (%) 174 (15.3) 134 (16.1) 0.780 0.022 Chorioamnionitis, n (%) 95 (8.3) 79 (9.5) 0.566 0.041 Antenatal corticosteroids, n (%) 1,081 (95) 817 (98.0) 0.007 0.180 Non-smoker during pregnancy, n (%) 1,055 (92.4) 767 (91.9) 0.974 0.029 Vaginal delivery, n (%) 343 (30.1) 205 (24.6) 0.142 0.122 Fetal growth restriction, n (%) 18 (1.6) 20 (2.4) 0.416 0.062 Neonatal Gestational age (week), median [IQR] 29 [ 27 , 31 ] 28 [ 26 , 30 ] 0.010 0.118 Hispanic, n (%) 640 (56.0) 472 (56.6) 0.543 0.178 § Male Sex, n (%) 583 (51.1) 427 (51.2) 0.984 0.002 Birth weight percentile, median [IQR] 53.9 [27.2, 75.4] 49.5 [21.6, 71.6] 0.052 0.089 Birth length percentile, median [IQR] 52.4 [31.1, 73.0] 51.5 [26.7, 73.0] 0.431 0.036 Birth head circumference percentile, median [IQR] 52.1 [27.1, 74.8] 50.1 [26.2, 71.5] 0.547 0.027 SGA, n (%) 122 (10.7) 112 (13.4) 0.204 0.084 LGA, n (%) 96 (8.4) 40 (4.8) 0.179 0.147 1-min APGAR, median [IQR] 7 [ 5 , 8 ] 7 [ 5 , 7 ] 0.130 0.069 5-min APGAR, median [IQR] 8 [ 7 , 9 ] 8 [ 7 , 9 ] 0.262 0.051 EHMD: exclusive human milk diet; SGA: small for gestational age; LGA: large for gestational age; IQR: interquartile range. *Chi-squared test for categorical variables, rank-sum test for non-parametric continuous variables. § Statistical test performed for comparing race/ethnicity assignment among White, Hispanic, Black, Asian, Pacific Islander, Multiple, and Other. Postnatal morbidity and diet characteristics are listed in Table 3 . In the weighted population, most infants in the EHMD group had more than 90% of days on EHMD. Their maximum caloric intake was significantly higher in the EHMD group compared to that in the non-EHMD group (26 kcal/oz in EHMD vs. 25 kcal/oz in non-EHMD, p < 0.001). Infants in the EHMD group were more likely to have IVH (33% in the EHMD group vs. 20% in the non-EHMD group, p < 0.001), although the differences in grade 3/4 IVH were non-significant between the two groups. Infants in the EHMD group were also more likely to have grade 2/3 BPD (14.5% in EHMD vs. 9.1% in non-EHMD, p = 0.010). Length of stay was longer among infants in the EHMD group (59.1 days) than in the non-EHMD group (51.0 days), with a p-value of 0.002. Infants in the EHMD group overall appeared to have more morbidities related to prematurity. Table 3 Neonatal morbidities of the weighted population. Variables Non-EHMD (n = 1,142) § EHMD (n = 834) § p-value* Intraventricular hemorrhage, n (%) Any grade 226 (19.8) 274 (32.9) < 0.001 Grade 3/4 55 (4.8) 57 (6.8) 0.197 Necrotizing enterocolitis, n (%) 7 (0.6) 12 (1.4) 0.129 Spontaneous intestinal perforation, n (%) 18 (1.5) 12 (1.5) 0.935 Total days of antibiotics (day), mean [IQR] 3 [ 3 , 7 ] 3 [ 2 , 7 ] 0.564 Bronchopulmonary dysplasia, n (%) 0.035 No 869 (76.1) 622 (74.6) Grade 1 169 (14.8) 90 (10.8) Grade 2 93 (8.1) 109 (13.1) Grade 3 12 (1.0) 12 (1.5) Retinopathy of prematurity ³ stage 2, n (%) 167 (14.6) 111 (13.3) 0.565 Hypotonia (M69.2), n (%) 41 (3.6) 27 (3.2) 0.798 Cerebral palsy (G80.X), n (%) 31 (2.7) 25 (3.0) 0.824 Specific developmental disorder of motor function (F82), n (%) 221 (19.4) 128 (15.4) 0.165 Any motor function impairment, n (%) 237 (20.8) 151 (18.2) 0.385 EHMD: exclusive human milk diet; IQR: interquartile range. *Chi-squared test for categorical variables, rank-sum test for non-parametric continuous variables. § Counts are rounded to the nearest integers. Assessing the risks of motor function impairment After adjusting for GA groups, sex, grade 3/4 IVH, stage 2/3 NEC or SIP, grade 2/3 BPD, ROP ≥ stage 2, as well as differences between birth and trajectory weight and length percentiles, the OR of motor function impairment was 0.74 (95% CI: 0.56–0.98, p = 0.033) in the EHMD group compared to the non-EHMD group (Fig. 1 ). Additionally, lower GA, male sex, grade 3/4 IVH, grade 2/3 BPD, and ROP ≥ stage 2, were each independently associated with significantly higher risks of motor function impairment. DISCUSSION In this study, we assessed the association between EHMD and motor function impairment, defined based on having a documented diagnosis of hypotonia, cerebral palsy, or specific developmental disorder of motor function by 3 years of corrected age. We applied IPW to balance potential perinatal confounders and used a mixed-effects model to adjust for covariates and account for outcome variations across medical centers. Our analysis showed that EHMD was significantly associated with a reduced risk of motor function impairment, independent of GA, sex, grade 3/4 IVH, NEC/SIP, ROP ≥ stage 2, grade 2/3 BPD, total antibiotic days, and weight and length growth. The model also identified certain covariates, including lower GA, male sex, grade 3/4 IVH, ROP ≥ stage 2, and grade 2/3 BPD, as being significantly associated with increased risks of motor function impairment. Human milk influences neurodevelopment through multiple mechanisms mediated by the gut-brain axis [ 23 ]. Among its components, lactoferrin, one of the most abundant whey proteins, has been linked to brain size in preterm infants [ 30 ]. Its anti-inflammatory properties may help mitigate adverse neurodevelopmental outcomes associated with systemic inflammation [ 31 , 32 ]. Another critical group of components in human milk is LC-PUFA, including docosahexaenoic acid (DHA) and arachidonic acid (ARA), which are key structural components of central nervous system cell membranes and play a significant role in regulating their function [ 33 ]. ARA and DHA accumulate rapidly during the third trimester and the first postnatal months in term infants. De novo synthesis of ARA exceeds that of DHA in preterm infants, making DHA more of an essential fatty acid in these vulnerable infants [ 34 ]. High-dose DHA supplementation in infants born at < 29 weeks has been associated with improved full-scale intelligence quotient at 5 years of corrected age [ 35 ]. HMOs are another group of molecules implicated in human milk’s contribution to neurodevelopment [ 23 , 36 ]. With over 200 identified structures, HMO concentrations vary depending on geographic location, maternal genetics, and the lactation period. Indigestible by infants, HMOs are instead utilized by the neonatal gut microbiome to suppress pathogenic microorganism growth. They also exhibit anti-inflammatory properties by downregulating pro-inflammatory cytokine secretion by intestinal epithelial cells, and play a role in strengthening the intestinal epithelial barrier [ 37 ]. Functionally, human milk use is associated with increased white matter development, cortical thickness, as well as better BSID and intelligence quotient scores [ 18 ]. Despite the presence of various components in human milk that are associated with improved neurodevelopment, the benefits of an EHMD remain a subject of debate. An EHMD comprises MOM or DHM fortified with HMBF, with the fortifier derived from banked DHM. Compared to mature MOM, banked DHM has reduced macro- and micronutrient content as well as lower caloric density. [ 38 – 41 ]. The concentrations of anti-inflammatory lactoferrins and immunoglobulins were also substantially reduced in banked DHM [ 40 ]. Moreover, the human milk microbiome is likely inactivated during the pasteurization process, leading to distinct intestinal microbiome signatures in preterm infants fed MOM-based diets compared to those fed DHM-based diets [ 42 ]. Nonetheless, a recent biochemical study demonstrated that DHM fortified with HMBF restored certain components, including lactoferrin, and achieved higher concentrations of protein and fat [ 43 ]. Demonstrating a correlation between an EHMD and reduced motor function impairment, our current study suggests that the bioactive components in an EHMD collectively offer significant benefits to preterm infants. In this study, we used physician-entered diagnostic codes in the electronic health record to identify motor function impairment. Although the list of diagnostic codes is not exhaustive, and this approach differs from conventional methods such as BSID or other standardized tests to evaluate motor developmental milestones, it may offer a more pragmatic alternative. Physician diagnoses are likely informed by a combination of assessment modalities, including standardized testing, parental or caregiver input, and physical examinations. Notably, the prevalence of motor function impairment in our cohort aligns with published rates based on standardized testing [ 44 ]. We focused on motor function impairment because, based on developmental cascades, motor development tends to present earlier than language and cognitive development, and contributes to language development [ 45 , 46 ]. Furthermore, early motor impairments appears to correlate with later deficits in high-level functioning, likely due to damage to shared neural pathways caused by prematurity [ 47 ]. Motor impairment is also less influenced by social determinant of health [ 48 ]. This study had several limitations. Its retrospective design inherently restricted the availability of detailed enteral and parenteral nutrition data for adjustment and was compounded by the absence of a standardized protocol for introducing an EHMD across NICUs. While confounder balancing was conducted to weight-adjust each infant, GA remained significantly different between the non-EHMD and EHMD groups in the weighted population. Lastly, as previously noted, using diagnostic codes to define motor function impairment has its advantages, but the diagnosis itself may be subjective and subject to the biases of the diagnosing physician. CONCLUSION After adjusting for demographic, morbidity, and growth factors, infants born at less than 32 weeks and fed an EHMD demonstrate reduced risks of motor function impairment, highlighting its benefits beyond the NICU hospitalization for this vulnerable population. A prospective study is warranted to further validate these findings. Additionally, identifying the bioactive components in an EHMD that contribute to its neurodevelopmental advantages could provide valuable insights into the unique composition of the banked DHM concentrate used in EHMD. Declarations CONFLICT OF INTEREST DISCLOSURES The authors declare no competing financial interests in relation to the work described herein. Ethics approval and consent to participate This data-only study was approved by the Institutional Review Board of Southern California Kaiser Permanente, with an exemption from the requirement for informed consent. FUNDING Dr. Fu-Sheng Chou is supported by the Clinician Investigator Program (2023-2024) by the Division of Clinician Research of the Department of Research and Evaluation at Kaiser Permanente Southern California. AVAILABILITY OF DATA AND MATERIALS Deidentified individual participant data may be requested with a formal utilization plan, pending approval by the Institutional Review Board of Southern California Kaiser Permanente. AUTHOR CONTRIBUTION FC conceptualized and designed the study, supervised data collection, performed the initial analysis, interpreted data, and drafted the initial manuscript. JZ collected data, assisted in data analysis, and critically reviewed the manuscript. MFBV and KBD contributed to data interpretation and critically reviewed the manuscript for important intellectual content. AL participated in study design, supervised data interpretation, and critically reviewed the manuscript. References Parker MG, Stellwagen LM, Noble L, Kim JH, Poindexter BB, Puopolo KM, et al. Promoting human milk and breastfeeding for the very low birth weight infant. Pediatrics. 2021;148: e2021054272. Brown JVE, Lin L, Embleton ND, Harding JE, McGuire W. 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JAMA Netw Open. 2022;5: e2221608. Zhang R, Ying E, Wu X, Qin H, Guo Y, Guo X, et al. A systematic review and meta-analysis of breastfeeding and neurodevelopmental outcomes in preterm infant. Front Public Health. 2024;12: 1401250. Silveira RC, Corso AL, Procianoy RS. The influence of early nutrition on neurodevelopmental outcomes in preterm infants. Nutrients. 2023;15: 4644. Berger PK, Ong ML, Bode L, Belfort MB. Human milk oligosaccharides and infant neurodevelopment: A narrative review. Nutrients. 2023;15. doi: 10.3390/nu15030719 Perez KM, Strobel KM, Hendrixson DT, Brandon O, Hair AB, Workneh R, et al. Nutrition and the gut-brain axis in neonatal brain injury and development. Semin Perinatol. 2024;48: 151927. Hopperton KE, O’Connor DL, Bando N, Conway AM, Ng DVY, Kiss A, et al. Nutrient enrichment of human milk with human and bovine milk-based fortifiers for infants born < 1250 g: 18-month neurodevelopment follow-up of a randomized clinical trial. Curr Dev Nutr. 2019;3: nzz129. Bergner EM, Shypailo R, Visuthranukul C, Hagan J, O’Donnell AR, Hawthorne KM, et al. Growth, body composition, and neurodevelopmental outcomes at 2 years among preterm infants fed an exclusive human milk diet in the neonatal intensive care unit: A pilot study. Breastfeed Med. 2020;15: 304–311. Hair AB, Patel AL, Kiechl-Kohlendorfer U, Kim JH, Schanler RJ, Hawthorne KM, et al. Neurodevelopmental outcomes of extremely preterm infants fed an exclusive human milk-based diet versus a mixed human milk + bovine milk-based diet: a multi-center study. J Perinatol. 2022;42: 1485–1488. Jensen EA, Dysart K, Gantz MG, McDonald S, Bamat NA, Keszler M, et al. The diagnosis of bronchopulmonary dysplasia in very preterm infants. An evidence-based approach. Am J Respir Crit Care Med. 2019;200: 751–759. Chou F-S, Yeh H-W, Clark RH. A comparative study of postnatal anthropometric growth in very preterm infants and intrauterine growth. Nat Commun. 2023;14: 5626. twang: Toolkit for Weighting and Analysis of Nonequivalent Groups. In: Comprehensive R Archive Network (CRAN) [Internet]. [cited 10 Oct 2024]. Available: https://cran.r-project.org/web/packages/twang/index.html Atayde AMP, Kapoor NR, Cherkerzian S, Olson I, Andrews C, Lee ACC, et al. Lactoferrin intake from maternal milk during the neonatal hospitalization and early brain development among preterm infants. Pediatr Res. 2024;96: 159–164. O’Shea TM, Allred EN, Kuban KCK, Dammann O, Paneth N, Fichorova R, et al. Elevated concentrations of inflammation-related proteins in postnatal blood predict severe developmental delay at 2 years of age in extremely preterm infants. J Pediatr. 2012;160: 395–401.e4. Dammann O, Leviton A. Intermittent or sustained systemic inflammation and the preterm brain. Pediatr Res. 2014;75: 376–380. Georgieff MK, Innis SM. Controversial nutrients that potentially affect preterm neurodevelopment: essential fatty acids and iron. Pediatr Res. 2005;57: 99R-103R. Lapillonne A, Moltu SJ. Long-chain polyunsaturated fatty acids and clinical outcomes of preterm infants. Ann Nutr Metab. 2016;69 Suppl 1: 35–44. Gould JF, Makrides M, Gibson RA, Sullivan TR, McPhee AJ, Anderson PJ, et al. Neonatal docosahexaenoic acid in preterm infants and intelligence at 5 years. N Engl J Med. 2022;387: 1579–1588. Soyyılmaz B, Mikš MH, Röhrig CH, Matwiejuk M, Meszaros-Matwiejuk A, Vigsnæs LK. The mean of milk: A review of human milk oligosaccharide concentrations throughout lactation. Nutrients. 2021;13: 2737. Rousseaux A, Brosseau C, Le Gall S, Piloquet H, Barbarot S, Bodinier M. Human milk oligosaccharides: Their effects on the host and their potential as therapeutic agents. Front Immunol. 2021;12: 680911. Wojcik KY, Rechtman DJ, Lee ML, Montoya A, Medo ET. Macronutrient analysis of a nationwide sample of donor breast milk. J Am Diet Assoc. 2009;109: 137–140. COMMITTEE ON NUTRITION, SECTION ON BREASTFEEDING, COMMITTEE ON FETUS AND NEWBORN. Donor human milk for the high-risk infant: Preparation, safety, and usage options in the United States. Pediatrics. 2017;139: e20163440. Hård A-L, Nilsson AK, Lund A-M, Hansen-Pupp I, Smith LEH, Hellström A. Review shows that donor milk does not promote the growth and development of preterm infants as well as maternal milk. Acta Paediatr. 2019;108: 998–1007. Gates A, Hair AB, Salas AA, Thompson AB, Stansfield BK. Nutrient composition of donor human milk and comparisons to preterm human milk. J Nutr. 2023;153: 2622–2630. Parra-Llorca A, Gormaz M, Alcántara C, Cernada M, Nuñez-Ramiro A, Vento M, et al. Preterm gut microbiome depending on feeding type: Significance of donor human milk. Front Microbiol. 2018;9. doi: 10.3389/fmicb.2018.01376 Philip RK, Romeih E, Bailie E, Daly M, McGourty KD, Grabrucker AM, et al. Exclusive human milk diet for extremely premature infants: A novel fortification strategy that enhances the bioactive properties of fresh, frozen, and pasteurized milk specimens. Breastfeed Med. 2023;18: 279–290. Evensen KAI, Ustad T, Tikanmäki M, Haaramo P, Kajantie E. Long-term motor outcomes of very preterm and/or very low birth weight individuals without cerebral palsy: A review of the current evidence. Semin Fetal Neonatal Med. 2020;25: 101116. Valentini NC, de Borba LS, Panceri C, Smith BA, Procianoy RS, Silveira RC. Early detection of cognitive, language, and motor delays for low-income preterm infants: A Brazilian cohort longitudinal study on infant neurodevelopment and maternal practice. Front Psychol. 2021;12: 753551. Kobaş M, Kızıldere E, Doğan I, Aktan-Erciyes A, Demir-Lira ÖE, Akman İ, et al. Motor skills, language development, and visual processing in preterm and full-term infants. Curr Psychol. 2023;42: 12463–12475. Van Hus JW, Potharst ES, Jeukens-Visser M, Kok JH, Van Wassenaer-Leemhuis AG. Motor impairment in very preterm-born children: links with other developmental deficits at 5 years of age. Dev Med Child Neurol. 2014;56: 587–594. Brumbaugh JE, Vohr BR, Bell EF, Bann CM, Travers CP, McGowan EC, et al. Early-life outcomes in relation to social determinants of health for children born extremely preterm. J Pediatr. 2023;259: 113443. Additional Declarations There is NO conflict of interest to disclose. Cite Share Download PDF Status: Published Journal Publication published 21 Apr, 2025 Read the published version in Journal of Perinatology → Version 1 posted Editorial decision: revise 24 Feb, 2025 Review # 1 received at journal 24 Feb, 2025 Review # 2 received at journal 30 Jan, 2025 Reviewer # 2 agreed at journal 30 Jan, 2025 Reviewer # 1 agreed at journal 28 Jan, 2025 Reviewers invited by journal 28 Jan, 2025 Submission checks completed at journal 27 Jan, 2025 Editor assigned by journal 26 Jan, 2025 First submitted to journal 26 Jan, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-5908077","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":408226979,"identity":"bb60275e-8936-491a-9bbf-bd8b07a657b6","order_by":0,"name":"Fu-Sheng Chou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYBAC+wMMzJ/BLIkERhBDToKQFgMGBjZpqBZmEMOYKC3MYBbPATZuIJU4g6AWiQQ25oKKO3YN7A0gxuH0mbMbGB9X/MLjF6B7Ps848yy5gRlo3Ywzh3NnyxxgNjzbh8+W/A/SvG2HkxlAWoCM3HlAeyUbe/A6jEGa9x9QC8hhQC3pcsRpaThsB/Y+UEuCNEhLww88WngesEnzHDucwCaR2CzNcybdcOacg82GjQ14tLADvc9Tc9ieXyL54GeeCmt5idvNBx82/MGtBQYS2xgYoSZLABmMbYS12COY4OgnwpZRMApGwSgYMQAApXVI4Xf2U2MAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-5770-0580","institution":"Kaiser Permanente Riverside Medical Center","correspondingAuthor":true,"prefix":"","firstName":"Fu-Sheng","middleName":"","lastName":"Chou","suffix":""},{"id":408226980,"identity":"0370c260-2fd8-425f-888a-e558f50ec0bc","order_by":1,"name":"Jing Zhang","email":"","orcid":"","institution":"Kaiser Permanente Southern California","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Zhang","suffix":""},{"id":408226981,"identity":"95883213-1c21-499e-8031-d5d14b96b43f","order_by":2,"name":"Maria Fe Villosis","email":"","orcid":"","institution":"Southern Calirfornia Permanente Medical Group/Kaiser Permanente Panorama City Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Fe","lastName":"Villosis","suffix":""},{"id":408226982,"identity":"ff533dd5-a032-4bc2-a984-185c35bae833","order_by":3,"name":"Ashwini Lakshmanan","email":"","orcid":"","institution":"Kaiser Permanente","correspondingAuthor":false,"prefix":"","firstName":"Ashwini","middleName":"","lastName":"Lakshmanan","suffix":""}],"badges":[],"createdAt":"2025-01-26 19:25:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5908077/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5908077/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41372-025-02296-z","type":"published","date":"2025-04-21T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":75188254,"identity":"009139fd-f410-422c-a4a1-01793712a964","added_by":"auto","created_at":"2025-01-31 18:01:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":237458,"visible":true,"origin":"","legend":"\u003cp\u003eResults of the weighted multivariable mixed model showing the odds ratio (black dots) and 95% confidence intervals (whiskers) for motor function impairment in association with an exclusive human milk diet. The odds ratios and the corresponding 95% confidence intervals for the covariates are also shown.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5908077/v1/ec2e57f18c6814c10512ffab.png"},{"id":81090600,"identity":"2f8539be-44fa-48cf-a38a-4983b8abe332","added_by":"auto","created_at":"2025-04-22 07:08:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1017207,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5908077/v1/b92928ce-5e65-4904-be0f-21b81b472829.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Exclusive Human Milk Diet Is Associated with Lower Risk of Motor Function Impairment by Three Years of Age","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eHuman milk-based nutrition is the standard of care for infants born under 32 weeks and very low birth weight infants [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. To meet the unique nutritional needs and growth of these infants, multi-nutrient fortification of either mother\u0026rsquo;s own milk (MOM) or donor human milk (DHM) is recommended [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Evidence suggests that multi-nutrient fortification reduces the morbidities associated with prematurity and improves neurodevelopmental outcomes. Fortification of MOM or DHM can be achieved using either bovine milk-based fortifier (BMBF) or human milk-based fortifier (HMBF). An exclusive human milk diet (EHMD) consists of MOM or DHM as the primary milk source, which is supplemented with HMBF. EHMD was found to be associated with a decrease in the incidence of necrotizing enterocolitis (NEC), especially in those settings where the NEC rates are high, as well as other morbidities such as late-onset sepsis, days on mechanical ventilation, retinopathy of prematurity (ROP), and bronchopulmonary dysplasia (BPD) [\u003cspan additionalcitationids=\"CR5 CR6 CR7 CR8 CR9\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. There is conflicting evidence on the relationship between EHMD and short-term postnatal growth, with numerous studies showing reduced growth associated with EHMD use [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Using a recent cohort of infants born\u0026thinsp;\u0026lt;\u0026thinsp;32 weeks at Kaiser Permanente Southern California (KPSC), we also showed reduced length growth associated with an EHMD. In a \u003cem\u003epost-hoc\u003c/em\u003e analysis, we observed comparable length growth and improved weight growth associated with EHMD fortified directly to a caloric density of 26 kcal/oz, after accounting for confounders and adjusting for neonatal morbidities.[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eNeurodevelopmental outcomes in early childhood are often used as indicators to evaluate the quality of care given to preterm infants in NICUs. The late second and early third trimesters are crucial for rapid brain development, which is significantly interrupted by preterm birth before 32 weeks of gestation. Various factors, such as prolonged respiratory support, illness severity, acute brain injury, nutritional intake, and growth during this critical period, influence neurodevelopmental outcomes. Slower growth has been correlated with higher risks of NDI [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In contrast, the use of human milk and breastfeeding have been shown to improve neurodevelopmental outcomes in both term and preterm infants [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Specific components of human milk, such as long-chain polyunsaturated fatty acids (LC-PUFA), lactoferrin, and human milk oligosaccharides (HMOs), are believed to play a role in supporting favorable neurodevelopmental outcomes [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe impact of an EHMD on early childhood neurodevelopmental outcomes has been reported in the literature, with conflicting results[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In a pragmatic trial by Hopperton et al., infants weighing less than 1,250 g between 2014 and 2016 were block-randomized to receive either a human milk-based fortifier (HMBF) or a bovine milk-based fortifier (BMBF). Neurodevelopmental outcomes assessed at 18 months of corrected age revealed no significant differences between the two groups [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Conversely, a multicenter retrospective study conducted across six NICUs between 2006 and 2010 reported superior cognitive outcomes at 18\u0026ndash;22 months of age, assessed by the Bayley Scales of Infant and Toddler Development (BSID), among infants fed an EHMD. However, no significant differences were observed in language or motor outcomes, and these findings remained consistent in both univariate analyses and after adjusting for factors such as birth weight, sex, enteral feeding, and NEC [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Additionally, Colacci et al. found no differences in BSID cognitive scores between groups [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], while the study by Bergner et al. did not include a non-EHMD comparison group [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In this study, we leverage an established KPSC cohort to examine the association between EHMD and motor function impairment by three years of age.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design, Eligibility Criteria, and Oversight\u003c/h2\u003e \u003cp\u003eWe conducted a multicenter retrospective study involving infants born at less than 32 weeks of gestation between January 1, 2018, and June 30, 2021, across 13 NICUs within KPSC [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This cohort represents a subset of our previously published study, including only those infants who had reached three years of corrected age by the time of analysis. Infants with major congenital anomalies or those who were no longer Kaiser Permanente members by six months of corrected age, either due to mortality or member attrition, were excluded. Additionally, we excluded infants without documented feeding information at 34 weeks postmenstrual age (PMA) or with missing data on feeding caloric density. The study was approved by the KPSC Institutional Review Board (IRB), which waived the requirement for informed consent (IRB #: 13350).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003eDemographic and morbidity data were collected from the Clarity database, a reporting database of Epic electronic healthcare records, or the research database at KPSC. No artificial intelligence or natural language processing algorithms were used for data extraction. Morbidity and outcome diagnoses were based on international classification of diseases-tenth edition (ICD-10) codes. Maternal variables collected include age, smoking status during pregnancy, delivery modes, antenatal corticosteroid administration, hypertensive disorders of pregnancy (HDP, including preeclampsia, eclampsia, HELLP syndrome), fetal growth restriction (FGR), gestational diabetes mellitus (GDM), obesity, and placental abruption. Neonatal variables extracted include birth hospital, sex, race/ethnicity, gestational age (GA), length of stay, APGAR scores at 1 and 5 minutes, IVH, ROP, NEC, spontaneous intestinal perforation (SIP), and BPD (based on the 2019 Jensen criteria[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]). NEC and SIP diagnoses were further evaluated by manual chart review.\u003c/p\u003e \u003cp\u003eAnthropometric data collected include weight, length, and head circumference measurements from birth to 33 6/7 weeks PMA. Weight was typically measured daily, whereas length and head circumference were typically measured weekly, but the frequency may change depending on clinical needs. The method for conducting the measurements was unavailable. The birth measurements were the measurements closest to the infants\u0026rsquo; birth dates. Birth measurement percentiles as well as weight and length growth trajectory percentiles were calculated based on the 2023 Postnatal Growth Charts for Preterm Infants [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The differences between birth and trajectory percentiles were calculated to represent the quality of growth in the NICUs.\u003c/p\u003e \u003cp\u003eEHMD was made possible by using the Prolacta\u0026reg; products. Since NICUs that implemented an EHMD transitioned infants from HMBF to BMBF at varying postmenstrual ages (PMAs) after 34 0/7 weeks, we limited our analysis to diet data collected before 34 0/7 weeks PMA to assign infants to either the EHMD or non-EHMD group. Daily diet order was used to determine whether the infant received EHMD for the day or not. The percentage of EHMD was calculated as follows:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\frac{Total\\:days\\:receiving\\:EHMD}{Total\\:days\\:between\\:the\\:day\\:of\\:the\\:first\\:fortified\\:feed\\:and\\:33\\:6/7\\:weeks\\:PMA}\\times\\:100\\:\\left(\\%\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eBased on our previous study, infants who received EHMD for \u0026ge;\u0026thinsp;75% of the days were assigned to the EHMD group [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The remainder of the infants were assigned to the non-EHMD group regardless of whether the non-EHMD feeds were preterm formula or MOM/DHM fortified with BMBF. Caloric density data were collected from nursing documentation of each feed in the flowsheet.\u003c/p\u003e \u003cp\u003eInfants were classified as having motor function impairment if they had any of the following ICD-10 codes in their medical charts―M62.9 (hypotonia), G80.X (cerebral palsy), or F82 (specific developmental disorder of motor function)―before reaching 3 years of corrected age.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were presented as median [interquartile range (IQR)]. Categorical variables were presented as number (percentage). The rank sum test was used to compare continuous variables, and the Chi-squared test was used for categorical variables. Standardized mean differences (SMD) were presented in demographic summarization of the confounders. P-values were presented for all comparisons. A P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003cp\u003eTo account for perinatal confounders between the EHMD vs. non-EHMD groups due to variations in EHMD implementation protocols across NICUs, we used inverse propensity weighting (IPW) to balance potential confounders. Propensity scores were derived using generalized boosted regression modeling to estimate the population average treatment effect [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Variables used for propensity score estimation were potential confounders before the beginning of diet fortification in typical modern neonatal practices, including maternal age, maternal obesity, HDP, GDM, FGR, chorioamnionitis, antenatal corticosteroids, infant race/ethnicity, birth GA, infant sex, birth measurement (weight, length, and head circumference) percentiles, as well as 1- and 5-min APGAR scores.\u003c/p\u003e \u003cp\u003eA weighted mixed-effects logistic regression model was developed to assess the risk of motor function impairment. Fixed-effect covariates include GA (categorized into 22\u0026ndash;25, 26\u0026ndash;27, 28\u0026ndash;29, and 30\u0026ndash;31 groups to improve model fit), infant sex, ROP\u0026thinsp;\u0026ge;\u0026thinsp;stage 2, grade 3/4 IVH, grade 2/3 BPD, total antibiotics days, difference in trajectory and birth percentiles for weight and length. Medical centers were included as a random-effect term to account for outcome variations among centers. The risk of motor function impairment was presented as odds ratio (OR) and its 95% confidence interval (CI).\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eInfant characteristics\u003c/h2\u003e \u003cp\u003eWe identified 1,210 infants who met the selection criteria, with 916 infants in the non-EHMD group and 294 in the EHMD group. Infants in the EHMD group were born earlier (median GA of 27 weeks for the EHMD group vs. 30 weeks for the non-EHMD group). Their perinatal characteristics are listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Birth weight and length percentiles were significantly lower among infants in the EHMD group. More infants in the EHMD group were small for gestational age (SGA) and fewer were large for gestational age (LGA). Both 1-min and 5-min APGAR scores were lower in the EHMD group. After IPW, the weighted population had 1,976 infants, with 1,142 in the non-EHMD group and 834 in the EHMD group. The perinatal characteristics of the weighted population are listed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The SMD of GA became much smaller (from 0.797 to 0.118). However, the difference between the two groups remained statistically significant (median GA of 29 weeks in the non-EHMD group vs. 28 weeks in the EHMD group). Birth weight and length, as well as APGAR scores were well balanced.\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\u003ePerinatal characteristics of the non-weighted cohort.\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\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-EHMD (n\u0026thinsp;=\u0026thinsp;916)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEHMD (n\u0026thinsp;=\u0026thinsp;294)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStandardized \u003c/p\u003e \u003cp\u003eMean Difference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eMaternal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (year), median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.181\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertensive disorder of pregnancy, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e274 (29.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87 (29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational diabetes mellitus, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e104 (11.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (10.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e318 (34.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86 (29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.117\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlacental abruption, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142 (15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.915\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChorioamnionitis, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72 (7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntenatal corticosteroids, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e862 (94.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e286 (97.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-smoker during pregnancy, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e846 (92.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e264 (89.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaginal delivery, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e287 (31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69 (23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFetal growth restriction, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eNeonatal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational age (week), median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.797\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e511 (55.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e172 (58.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.239\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale Sex, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e470 (51.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e154 (52.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth weight percentile, median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55.2 [30.0, 77.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.0 [17.1, 68.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.336\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth length percentile, median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.8 [32.2, 73.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.9 [18.1, 73.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.195\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth head circumference percentile, median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.6 [32.8, 74.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.1 [25.4, 74.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSGA, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82 (9.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (19.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.294\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLGA, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89 (9.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.293\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1-min APGAR, median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.249\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-min APGAR, median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.0 [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.189\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eEHMD: exclusive human milk diet; SGA: small for gestational age; LGA: large for gestational age; IQR: interquartile range.\u003c/p\u003e \u003cp\u003e*Chi-squared test for categorical variables, rank-sum test for non-parametric continuous variables.\u003c/p\u003e \u003cp\u003e\u003csup\u003e\u0026sect;\u003c/sup\u003eStatistical test performed for comparing race/ethnicity assignment among White, Hispanic, Black, Asian, Pacific Islander, Multiple, and Other.\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 \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\u003ePerinatal characteristics of the weighted population.\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\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-EHMD (n\u0026thinsp;=\u0026thinsp;1,142)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEHMD (n\u0026thinsp;=\u0026thinsp;834)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStandardized \u003c/p\u003e \u003cp\u003eMean Difference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eMaternal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (year), median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.831\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertensive disorder of pregnancy, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e344 (30.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e252 (30.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.976\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational diabetes mellitus, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e123 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78 (9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e389 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e240 (28.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlacental abruption, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e174 (15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e134 (16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChorioamnionitis, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntenatal corticosteroids, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,081 (95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e817 (98.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-smoker during pregnancy, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,055 (92.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e767 (91.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.974\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaginal delivery, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e343 (30.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e205 (24.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFetal growth restriction, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eNeonatal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational age (week), median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e640 (56.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e472 (56.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.178\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale Sex, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e583 (51.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e427 (51.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth weight percentile, median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53.9 [27.2, 75.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.5 [21.6, 71.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth length percentile, median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.4 [31.1, 73.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.5 [26.7, 73.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth head circumference percentile, median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.1 [27.1, 74.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.1 [26.2, 71.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSGA, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e122 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112 (13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLGA, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96 (8.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1-min APGAR, median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-min APGAR, median [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eEHMD: exclusive human milk diet; SGA: small for gestational age; LGA: large for gestational age; IQR: interquartile range.\u003c/p\u003e \u003cp\u003e*Chi-squared test for categorical variables, rank-sum test for non-parametric continuous variables.\u003c/p\u003e \u003cp\u003e\u003csup\u003e\u0026sect;\u003c/sup\u003eStatistical test performed for comparing race/ethnicity assignment among White, Hispanic, Black, Asian, Pacific Islander, Multiple, and Other.\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\u003ePostnatal morbidity and diet characteristics are listed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. In the weighted population, most infants in the EHMD group had more than 90% of days on EHMD. Their maximum caloric intake was significantly higher in the EHMD group compared to that in the non-EHMD group (26 kcal/oz in EHMD vs. 25 kcal/oz in non-EHMD, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Infants in the EHMD group were more likely to have IVH (33% in the EHMD group vs. 20% in the non-EHMD group, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), although the differences in grade 3/4 IVH were non-significant between the two groups. Infants in the EHMD group were also more likely to have grade 2/3 BPD (14.5% in EHMD vs. 9.1% in non-EHMD, p\u0026thinsp;=\u0026thinsp;0.010). Length of stay was longer among infants in the EHMD group (59.1 days) than in the non-EHMD group (51.0 days), with a p-value of 0.002. Infants in the EHMD group overall appeared to have more morbidities related to prematurity.\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\u003eNeonatal morbidities of the weighted population.\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-EHMD (n\u0026thinsp;=\u0026thinsp;1,142) \u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEHMD (n\u0026thinsp;=\u0026thinsp;834) \u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntraventricular hemorrhage, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAny grade\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e226 (19.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e274 (32.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGrade 3/4\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 (6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.197\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNecrotizing enterocolitis, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpontaneous intestinal perforation, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.935\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal days of antibiotics (day), mean [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.564\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBronchopulmonary dysplasia, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNo\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e869 (76.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e622 (74.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGrade 1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e169 (14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90 (10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGrade 2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93 (8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109 (13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGrade 3\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetinopathy of prematurity \u0026sup3; stage 2, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e167 (14.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e111 (13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.565\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypotonia (M69.2), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.798\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCerebral palsy (G80.X), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecific developmental disorder of motor function (F82), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e221 (19.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e128 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.165\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny motor function impairment, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e237 (20.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e151 (18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.385\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eEHMD: exclusive human milk diet; IQR: interquartile range.\u003c/p\u003e \u003cp\u003e*Chi-squared test for categorical variables, rank-sum test for non-parametric continuous variables.\u003c/p\u003e \u003cp\u003e\u003csup\u003e\u0026sect;\u003c/sup\u003eCounts are rounded to the nearest integers.\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=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAssessing the risks of motor function impairment\u003c/h2\u003e \u003cp\u003eAfter adjusting for GA groups, sex, grade 3/4 IVH, stage 2/3 NEC or SIP, grade 2/3 BPD, ROP\u0026thinsp;\u0026ge;\u0026thinsp;stage 2, as well as differences between birth and trajectory weight and length percentiles, the OR of motor function impairment was 0.74 (95% CI: 0.56\u0026ndash;0.98, p\u0026thinsp;=\u0026thinsp;0.033) in the EHMD group compared to the non-EHMD group (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Additionally, lower GA, male sex, grade 3/4 IVH, grade 2/3 BPD, and ROP\u0026thinsp;\u0026ge;\u0026thinsp;stage 2, were each independently associated with significantly higher risks of motor function impairment.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn this study, we assessed the association between EHMD and motor function impairment, defined based on having a documented diagnosis of hypotonia, cerebral palsy, or specific developmental disorder of motor function by 3 years of corrected age. We applied IPW to balance potential perinatal confounders and used a mixed-effects model to adjust for covariates and account for outcome variations across medical centers. Our analysis showed that EHMD was significantly associated with a reduced risk of motor function impairment, independent of GA, sex, grade 3/4 IVH, NEC/SIP, ROP\u0026thinsp;\u0026ge;\u0026thinsp;stage 2, grade 2/3 BPD, total antibiotic days, and weight and length growth. The model also identified certain covariates, including lower GA, male sex, grade 3/4 IVH, ROP\u0026thinsp;\u0026ge;\u0026thinsp;stage 2, and grade 2/3 BPD, as being significantly associated with increased risks of motor function impairment.\u003c/p\u003e \u003cp\u003eHuman milk influences neurodevelopment through multiple mechanisms mediated by the gut-brain axis [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Among its components, lactoferrin, one of the most abundant whey proteins, has been linked to brain size in preterm infants [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Its anti-inflammatory properties may help mitigate adverse neurodevelopmental outcomes associated with systemic inflammation [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Another critical group of components in human milk is LC-PUFA, including docosahexaenoic acid (DHA) and arachidonic acid (ARA), which are key structural components of central nervous system cell membranes and play a significant role in regulating their function [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. ARA and DHA accumulate rapidly during the third trimester and the first postnatal months in term infants. \u003cem\u003eDe novo\u003c/em\u003e synthesis of ARA exceeds that of DHA in preterm infants, making DHA more of an essential fatty acid in these vulnerable infants [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. High-dose DHA supplementation in infants born at \u0026lt;\u0026thinsp;29 weeks has been associated with improved full-scale intelligence quotient at 5 years of corrected age [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. HMOs are another group of molecules implicated in human milk\u0026rsquo;s contribution to neurodevelopment [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. With over 200 identified structures, HMO concentrations vary depending on geographic location, maternal genetics, and the lactation period. Indigestible by infants, HMOs are instead utilized by the neonatal gut microbiome to suppress pathogenic microorganism growth. They also exhibit anti-inflammatory properties by downregulating pro-inflammatory cytokine secretion by intestinal epithelial cells, and play a role in strengthening the intestinal epithelial barrier [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Functionally, human milk use is associated with increased white matter development, cortical thickness, as well as better BSID and intelligence quotient scores [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the presence of various components in human milk that are associated with improved neurodevelopment, the benefits of an EHMD remain a subject of debate. An EHMD comprises MOM or DHM fortified with HMBF, with the fortifier derived from banked DHM. Compared to mature MOM, banked DHM has reduced macro- and micronutrient content as well as lower caloric density. [\u003cspan additionalcitationids=\"CR39 CR40\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The concentrations of anti-inflammatory lactoferrins and immunoglobulins were also substantially reduced in banked DHM [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Moreover, the human milk microbiome is likely inactivated during the pasteurization process, leading to distinct intestinal microbiome signatures in preterm infants fed MOM-based diets compared to those fed DHM-based diets [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Nonetheless, a recent biochemical study demonstrated that DHM fortified with HMBF restored certain components, including lactoferrin, and achieved higher concentrations of protein and fat [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Demonstrating a correlation between an EHMD and reduced motor function impairment, our current study suggests that the bioactive components in an EHMD collectively offer significant benefits to preterm infants.\u003c/p\u003e \u003cp\u003eIn this study, we used physician-entered diagnostic codes in the electronic health record to identify motor function impairment. Although the list of diagnostic codes is not exhaustive, and this approach differs from conventional methods such as BSID or other standardized tests to evaluate motor developmental milestones, it may offer a more pragmatic alternative. Physician diagnoses are likely informed by a combination of assessment modalities, including standardized testing, parental or caregiver input, and physical examinations. Notably, the prevalence of motor function impairment in our cohort aligns with published rates based on standardized testing [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. We focused on motor function impairment because, based on developmental cascades, motor development tends to present earlier than language and cognitive development, and contributes to language development [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Furthermore, early motor impairments appears to correlate with later deficits in high-level functioning, likely due to damage to shared neural pathways caused by prematurity [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Motor impairment is also less influenced by social determinant of health [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study had several limitations. Its retrospective design inherently restricted the availability of detailed enteral and parenteral nutrition data for adjustment and was compounded by the absence of a standardized protocol for introducing an EHMD across NICUs. While confounder balancing was conducted to weight-adjust each infant, GA remained significantly different between the non-EHMD and EHMD groups in the weighted population. Lastly, as previously noted, using diagnostic codes to define motor function impairment has its advantages, but the diagnosis itself may be subjective and subject to the biases of the diagnosing physician.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eAfter adjusting for demographic, morbidity, and growth factors, infants born at less than 32 weeks and fed an EHMD demonstrate reduced risks of motor function impairment, highlighting its benefits beyond the NICU hospitalization for this vulnerable population. A prospective study is warranted to further validate these findings. Additionally, identifying the bioactive components in an EHMD that contribute to its neurodevelopmental advantages could provide valuable insights into the unique composition of the banked DHM concentrate used in EHMD.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCONFLICT OF INTEREST DISCLOSURES\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing financial interests in relation to the work described herein.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis data-only study was approved by the Institutional Review Board of Southern California Kaiser Permanente, with an exemption from the requirement for informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFUNDING\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDr. Fu-Sheng Chou is supported by the Clinician Investigator Program (2023-2024) by the Division of Clinician Research of the Department of Research and Evaluation at Kaiser Permanente Southern California.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAVAILABILITY OF DATA AND MATERIALS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDeidentified individual participant data may be requested with a formal utilization plan, pending approval by the Institutional Review Board of Southern California Kaiser Permanente.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAUTHOR CONTRIBUTION\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFC conceptualized and designed the study, supervised data collection, performed the initial analysis, interpreted data, and drafted the initial manuscript.\u003c/p\u003e\n\u003cp\u003eJZ collected data, assisted in data analysis, and critically reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003eMFBV and KBD contributed to data interpretation and critically reviewed the manuscript for important intellectual content.\u003c/p\u003e\n\u003cp\u003eAL participated in study design, supervised data interpretation, and critically reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eParker MG, Stellwagen LM, Noble L, Kim JH, Poindexter BB, Puopolo KM, et al. 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J Pediatr. 2023;259: 113443.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-perinatology","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"jp","sideBox":"Learn more about [Journal of Perinatology](http://www.nature.com/jp/)","snPcode":"41372","submissionUrl":"https://mts-jper.nature.com/cgi-bin/main.plex","title":"Journal of Perinatology","twitterHandle":"@jperinatology","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5908077/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5908077/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjectives:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo evaluate the association of an exclusive human milk diet (EHMD) with motor function by three years of corrected age among infants born at less than 32 weeks of gestation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted a retrospective study between 2018 and 2021. Infants who received an EHMD for \u0026gt; 75% of days between first day of diet fortification and 33 6/7 weeks postmenstrual age were assigned to the EHMD group. We used inverse propensity sores to balance potential confounders and developed a mixed-effects logistic regression model to assess the association.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter adjusting for demographics and morbidities, an EHMD was found to be associated with a reduced risk of motor function impairment, with an odds ratio of 0.74 (95% confidence interval of 0.56–0.98, p-value = 0.033).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn EHMD is associated with a decrease in early childhood motor function impairment among infants born at less than 32 weeks of gestation.\u003c/p\u003e","manuscriptTitle":"Exclusive Human Milk Diet Is Associated with Lower Risk of Motor Function Impairment by Three Years of Age","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-31 18:01:02","doi":"10.21203/rs.3.rs-5908077/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2025-02-24T16:30:23+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-02-24T06:14:56+00:00","index":1,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-01-30T21:22:20+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-01-30T20:20:34+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-01-28T14:33:40+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-01-28T14:06:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-01-27T10:46:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-01-26T19:20:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Perinatology","date":"2025-01-26T19:20:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-perinatology","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"jp","sideBox":"Learn more about [Journal of Perinatology](http://www.nature.com/jp/)","snPcode":"41372","submissionUrl":"https://mts-jper.nature.com/cgi-bin/main.plex","title":"Journal of Perinatology","twitterHandle":"@jperinatology","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b1dc543b-fc7c-4af0-a71e-67b72daea8eb","owner":[],"postedDate":"January 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":43525081,"name":"Health sciences/Diseases/Neurological disorders/Neurodevelopmental disorders"},{"id":43525082,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2025-04-22T07:08:07+00:00","versionOfRecord":{"articleIdentity":"rs-5908077","link":"https://doi.org/10.1038/s41372-025-02296-z","journal":{"identity":"journal-of-perinatology","isVorOnly":false,"title":"Journal of Perinatology"},"publishedOn":"2025-04-21 04:00:00","publishedOnDateReadable":"April 21st, 2025"},"versionCreatedAt":"2025-01-31 18:01:02","video":"","vorDoi":"10.1038/s41372-025-02296-z","vorDoiUrl":"https://doi.org/10.1038/s41372-025-02296-z","workflowStages":[]},"version":"v1","identity":"rs-5908077","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5908077","identity":"rs-5908077","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}