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. 2019 May 3;2(5):e192914. doi: 10.1001/jamanetworkopen.2019.2914

Association of Socioeconomic Status and Brain Injury With Neurodevelopmental Outcomes of Very Preterm Children

Isabel Benavente-Fernández 1,2,3, Anne Synnes 4, Ruth E Grunau 4, Vann Chau 1,2, Chantel Ramraj 5,6, Torin Glass 1,2, Dalit Cayam-Rand 1,2, Arjumand Siddiqi 5,6, Steven P Miller 1,2,3,✉
PMCID: PMC6503490  PMID: 31050776

Key Points

Question

Does the association of brain injury with adverse neurodevelopmental outcome in preterm neonates vary by the socioeconomic status of the parents?

Findings

In this cohort study of 226 preterm neonates, cognitive and motor outcomes were associated with different prenatal and postnatal clinical factors, with maternal education and brain injury having similar effect sizes for cognitive outcomes. Importantly, cognitive scores in preterm children in the higher-status group did not differ between those with and without brain injury.

Meaning

Maternal education is associated with cognitive outcome in preterm neonates, with higher status appearing to attenuate the association of brain injury with neurodevelopmental outcome.

This cohort study evaluates the association of maternal education and brain injury with neurodevelopmental outcomes in children born very prematurely in Canada.

Abstract

Importance

Studies of socioeconomic status and neurodevelopmental outcome in very preterm neonates have not sensitively accounted for brain injury.

Objective

To determine the association of brain injury and maternal education with motor and cognitive outcomes at age 4.5 years in very preterm neonates.

Design, Setting, and Participants

Prospective cohort study of preterm neonates (24-32 weeks’ gestation) recruited August 16, 2006, to September 9, 2013, at British Columbia Women's Hospital in Vancouver, Canada. Analysis of 4.5-year outcome was performed in 2018.

Main Outcomes and Measures

At age 4.5 years, full-scale IQ assessed using the Wechsler Primary and Preschool Scale of Intelligence, Fourth Edition, and motor outcome by the percentile score on the Movement Assessment Battery for Children, Second Edition.

Results

Of 226 survivors, neurodevelopmental outcome was assessed in 170 (80 [47.1%] female). Based on the best model to assess full-scale IQ accounting for gestational age, standardized β coefficients demonstrated the effect size of maternal education (standardized β = 0.21) was similar to that of white matter injury volume (standardized β = 0.23) and intraventricular hemorrhage (standardized β = 0.23). The observed and predicted cognitive scores in preterm children born to mothers with postgraduate education did not differ in those with and without brain injury. The best-performing model to assess for motor outcome accounting for gestational age included being small for gestational age, severe intraventricular hemorrhage, white matter injury volume, and chronic lung disease.

Conclusions and Relevance

At preschool age, cognitive outcome was comparably associated with maternal education and neonatal brain injury. The association of brain injury with poorer cognition was attenuated in children born to mothers of higher education level, suggesting opportunities to promote optimal outcomes.

Introduction

While improved intensive care therapies have increased the survival of critically ill neonates, preterm birth remains a leading cause of lifelong neurodevelopmental disability globally and in North America.1,2,3,4,5,6 While we understand much more about the association of brain injury with neurodevelopmental disability, we know far less about the role of environments and experiences in moderating these associations. In this article, we examine the association of neurodevelopment with brain injury in the context of socioeconomic status (SES), a factor that previous literature suggests systematically patterns environments and experiences of children.

Neurodevelopmental disabilities in preterm neonates are associated with white matter injury (WMI) and severe intraventricular hemorrhage (IVH).6,7 The role of experiential factors, such as SES, in mitigating or exacerbating risk for negative outcomes in preterm infants with brain injuries is incompletely understood. However, the neuroscience literature suggests many examples through which enriched environments can mitigate the impact of early-life brain injuries.8,9,10,11,12

In normative populations, many studies demonstrate associations between SES, as measured by maternal education, and poorer cognitive development, language skills, and academic achievement.13,14,15,16,17,18,19,20 In children born preterm, similar associations are recognized.13,14,21 Importantly, however, specific interventions to address these issues that are beneficial in children born at term are not necessarily effective in preterm-born children.22 This discrepancy may reflect the existence of brain injury in the preterm population. Furthermore, studies of children born preterm with brain injury have not sensitively accounted for the contribution of SES to neurodevelopmental outcomes or have considered SES without contemporary measures of brain injury.23,24,25

We sought to address the hypothesis that high SES, reflected by maternal education, would mitigate the association of brain injury with adverse neurodevelopmental outcome in the preterm neonate. We addressed this hypothesis in a prospective cohort of preterm neonates studied in Vancouver, Canada, a high-resource setting with a single-payer provincial health care system with uniform access to health care services across the range of SES.

Methods

The University of British Columbia Clinical Research Ethics Board approved this study. Parental written informed consent was given following the recommendations of the board. This study follows the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies.26

Study Population

Newborns were eligible if they were born between 24 and 32 weeks’ gestational age (GA). As reported previously,27 exclusion criteria were (1) congenital malformation or syndrome, (2) antenatal congenital infection, or (3) large periventricular hemorrhagic infarction (>2 cm) on clinical ultrasonography.

Study participants were recruited prospectively from August 6, 2006, to September 9, 2013, at the British Columbia Women's Hospital, the major provincial tertiary-level neonatal intensive care unit (NICU) (eFigure 1 in the Supplement). From January 2011 until the end of enrollment, with a change in clinical practice and grant funding, we only enrolled newborns exposed antenatally to magnesium sulfate for fetal neuroprotection or for the treatment of maternal preeclampsia. Some data from the same cohort at earlier ages of follow-up were described previously.7,27,28,29,30,31,32,33

Clinical Data Collection

Systematic detailed medical record reviews were performed for clinical information about pregnancy, delivery, and NICU course. For this study, we focused on previously recognized factors associated with neurodevelopmental outcome in this population (Table 1).1,7,29,34 Chronic lung disease (CLD) was defined as the need for oxygen therapy at 36 weeks’ postmenstrual age.

Table 1. Clinical Factors and 4.5 Year Outcomes by Level of Maternal of Education.

Clinical Factor Maternal Level of Education, No./Total No. (%) P Value
Primary or Secondary School (n = 29) Undergraduate Degree (n = 134) Postgraduate Degree (n = 34)
Prenatal
Maternal age, median (IQR), y 30.5 (27-36.8) 32.1 (28.3-36.9) 32.4 (30.6-36.6) .28
Preeclampsia 7/29 (24.1) 36/134 (26.9) 6/34 (17.7) .51
Gestational diabetes 4/29 (13.8) 11/134 (8.2) 0 .40
Prenatal steroids 25/29 (86.2) 123/134 (91.8) 29/34 (85.3) .30
Prenatal magnesium sulfate 8/29 (27.6) 27/134 (20.2) 6/34 (17.7) .66
Histological chorioamnionitis 12/27 (44.4) 47/132 (35.6) 12/33 (36.4) .69
Small for gestational age 7/29 (24.1) 24/134 (17.9) 3/34 (8.8) .25
Birth and neonatal intensive care unit course
Male 17/29 (58.6) 71/134 (53.0) 18/34 (52.9) .78
Gestational age, mean (SD), wk 28.0 (2.1) 27.9 (2.2) 28.4 (2.6) .53
Birth weight, mean (SD), g 1046.7 (303.6) 1038.3 (318.7) 1132.4 (347.9) .31
Total ventilation, median (IQR), d 5.5 (1.5-37.0) 7.0 (1.0-35.0) 2.0 (1.0-29.0) .60
Chronic lung disease, defined as oxygen at 36 weeks’ postmenstrual age 5 (16.7) 25 (18.7) 7 (20.6) .69
Retinopathy of prematurity 12/24 (50.0) 51/109 (46.8) 7/27 (25.9) .11
Postnatal infection 14/29 (48.3) 76/133 (57.1) 14/34 (41.2) .23
Postnatal dexamethasone 7/29 (24.1) 24/134 (17.9) 8/33 (24.2) .60
Punctate white matter injury present 11/29 (37.9) 37/134 (27.6) 8/34 (23.5) .49
Punctate white matter injury volume, median (IQR), mm3 39.4 (20.3-95.5) 64.0 (19.5-431.9) 28.2 (15.2-253.9) .56
Severe intraventricular hemorrhage (grade 3 or periventricular hemorrhagic infarction >2 cm) 1/26 (3.9) 3/128 (2.4) 2/33 (6.1) .59
Outcome at 4.5 y
Full-scale IQ, mean (SD) 99.6 (13.6) 101.0 (15.7) 108.3 (9.5) .02
Wechsler Primary and Preschool Scale of Intelligence verbal IQ, mean (SD) 99.0 (15.5) 100.5 (16.1) 108.4 (12.2) .02
Wechsler Primary and Preschool Scale of Intelligence performance IQ, mean (SD) 103.8 (11.2) 103.7 (13.8) 107.5 (8.1) .01
Wechsler Primary and Preschool Scale of Intelligence processing speed, mean (SD) 94.4 (9.9) 96.8 (14.5) 100.7 (10.4) .09
Movement Assessment Battery for Children percentile score, median (IQR) 25 (5-50) 25 (2-63) 56 (16-91) .04
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Abbreviation: IQR, interquartile range.

Socioeconomic Status

We used maternal education at the time of NICU admission as our primary measure of SES35,36 given prior literature to support this being the most informative measure of SES in children born preterm in Canada.37 Taking the number of years of education into account, we categorized the level of maternal education as primary or secondary school, undergraduate degree, or postgraduate degree. We also collected paternal years of education and the occupation of both parents.

Magnetic Resonance Imaging Studies

Detailed imaging methods applied in this cohort have been described previously.29,30 Using an isolette compatible with magnetic resonance imaging (MRI) (Lammers Medical Technology) and specialized neonatal head coil (Advanced Imaging Research), newborns underwent MRI first within several weeks after birth, as soon as they were deemed clinically stable, and again at term-equivalent age. We performed MRI studies without pharmacologic sedation on a Siemens 1.5-T Avanto scanner with 3-dimensional coronal volumetric T1-weighted images and axial fast spin echo T2-weighted images. An experienced neuroradiologist who was blinded to the newborn's medical history rated the severity of IVH, classifying severe IVH as grade 3 or periventricular hemorrhagic infarction larger than 2 cm.38 White matter injury volume was calculated as described previously.7

Neurodevelopmental Outcomes

Ages 18 Months and 36 Months

At 18 months’ corrected age, children underwent a first neurodevelopmental assessment conducted by examiners unaware of MRI findings. Median (interquartile range [IQR]) age at this first examination was 18.65 (18.3-19.4) months. At 36 months’ corrected age (median [IQR] age, 35 [33.9-37.1] months), children underwent a second assessment. Examiners assessed neurodevelopment using the Bayley Scales of Infant and Toddler Development, Third Edition (Bayley-III),39 which yields composite scores (standardized with mean [SD] of 100 [15]) for cognitive and motor skills.

Age 4.5 Years

At age 4.5 years (median [IQR] age, 4.8 [4.8-4.9] years), neurodevelopmental outcomes were assessed by PhD-trained psychology staff, plus 1 highly experienced master’s degree–level psychologist, at British Columbia Children's and Women's Hospitals.

The Wechsler Primary and Preschool Scale of Intelligence, Fourth Edition (WPPSI-IV)40 was performed to provide an overall full-scale intelligence quotient (FSIQ) as well as scores for verbal comprehension, perceptual reasoning, working memory, and processing speed. Overall indices are standard scores with mean (SD) of 100 (15).

Motor function was assessed using the Movement Assessment Battery for Children–Second Edition (M-ABC2),41 which assesses manual dexterity, aiming and catching, and balance domains. The total test score was standardized and converted to a percentile rank.42

Statistical Analysis

Statistical analysis was performed using Stata statistical software version 15.0 (StataCorp LLC) during 2018 when the 4.5-year outcome measures were available for the whole cohort. Clinical characteristics were compared by maternal level of education using 2-tailed Fisher exact tests and Kruskal-Wallis tests for categorical and continuous data, respectively. A nonparametric test for trends across ordered groups was performed to examine the association of maternal and paternal level of education.

Using multivariable linear models to account for GA, we examined clinical variables associated with M-ABC2 and FSIQ at 4.5 years. Prenatal and postnatal clinical variables examined are listed in Table 1. Selection of the best model was performed through the method of all possible equations, which identifies the best subset for linear regression.43 We then assessed our final models using generalized estimating equations using an independent correlation structure with robust standard errors estimation to account for correlation within twin pairs in the cohort. We then performed mixed linear regression models to test the selected model for the longitudinal measurements of cognition (18- and 36-month Bayley-III and 4.5-year WPPSI-IV FSIQ) and mixed-effects logistic regression analysis for the longitudinal trajectory of motor function (eMethods in the Supplement). A P value less than .05 was considered statistically significant. A detailed description of the missing data approach, including multiple imputation, can be found in the eMethods in the Supplement.

Results

Of 226 survivors, 88% (199 children; 96 [48.2%] female) were assessed at 18 months, 83% (187 children; 90 [48.1%] female) at 36 months, and 75% (170 children; 80 [47.1%] female) at 4.5 years. Two hundred eight children (92%) in the cohort had at least 1 assessment, 191 (85%) had 2, and 157 (70%) had all 3. For a detailed cohort flow, see eFigure 1 in the Supplement. Available and missing values on cognitive outcomes are described in eTable 1 in the Supplement.

SES and Clinical Factors

Maternal level of education was available for 197 patients (84.2%). Approximately two-thirds of the mothers completed an undergraduate degree (Table 1). Prenatal and postnatal characteristics did not differ between the groups of maternal levels of education. Maternal level of education was associated with paternal level of education (z = 5.33; P = .001). In only 3 children, the maternal level of education changed from NICU admission to the 4.5-year assessment: 2 in the undergraduate degree group obtained postgraduate degrees and 1 in the secondary education group obtained an undergraduate degree. Agreement of the cognitive scores at different points is shown in eTable 2 in the Supplement.

Maternal Level of Education and Outcome Measures

Cognitive Outcome

The mean (SD) FSIQ at 4.5 years was 102.0 (14.6). The mean (SD) FSIQ score in children whose mothers had a postgraduate degree (108.30 [9.45]) was significantly higher than the mean (SD) FSIQ scores of both the undergraduate degree group (98.66 [19.65]; P = .01) and the primary or secondary school group (96.24 [19.96]; P = .02); the mean FSIQ scores of the undergraduate and primary or secondary school groups did not differ (Figure 1).

Figure 1. Distribution of Cognitive and Motor Scores at 4.5 Years by Maternal Level of Education.

Figure 1.

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Distribution of cognitive (A) and motor (B) scores at age 4.5 years across the cohort divided by maternal level of education. The postgraduate group achieved a mean IQ and a median Movement Assessment Battery for Children (M-ABC2) score higher than the undergraduate degree group and primary or secondary school group (P = .01 and P = .02, respectively). Bars indicate the distribution of the studied variable for the whole cohort. Lines indicate the distribution of the studied variable by maternal level of education. WPPSI-IV indicates Wechsler Primary and Preschool Scale of Intelligence, Fourth Edition.

Motor Outcome

The median (IQR) M-ABC2 percentile score at age 4.5 years was 37 (5-63). The median (IQR) M-ABC2 percentile score was significantly higher in children whose mothers had a postgraduate degree (56.5 [16-91]) than in those in the undergraduate degree group (25 [2-63]) (P = .03) (Figure 1).

Clinical Factors Associated With the 4.5-Year Outcome and Longitudinal Neurodevelopmental Outcomes

Cognitive Outcome

The best model for cognitive outcome tested using the WPPSI-IV FSIQ at 4.5 years, adjusting for GA, included severe IVH, WMI volume, CLD, and maternal level of education. When examining maternal level of education, with undergraduate degree as the reference category, the cognitive outcome of the postgraduate degree group was higher (β = 7.13; 95% CI, 1.53-12.73; P = .01) (Table 2). (See eTable 3 and eTable 4 in the Supplement for a detailed description of missing values and the estimated model obtained after performing multiple imputation.) The cohort included 38 twin pairs. Using generalized estimating equations to account for twin pairs in the data structure resulted in a strengthening of these coefficients.

Table 2. Estimated Models of Wechsler Primary and Preschool Scale of Intelligence Full-Scale IQ Score and Movement Assessment Battery for Children Percentile Score at 4.5 Years.
Factor β Coefficient (95% CI) P Value Standardized β Accounting for Twin Pairs (n = 38 Pairs)
β Coefficient (95% CI) P Value
Cognitive (n = 162)a
Gestational age 0.50 (−0.53 to 1.53) .34 0.05 0.30 (−0.97 to 1.57) .64
Chronic lung disease −7.89 (−13.81 to −1.97) .009 0.17 −7.96 (−15.24 to −0.67) .03
Severe intraventricular hemorrhage(grade 3) −9.69 (−21.29 to 1.90) .10 0.23 −23.5 (−37.76 to −9.23) .001
Punctate white matter injury volume −0.01 (−0.01 to −0.003) .001 0.23 −0.01 (−0.02 to −0.004) .001
Maternal level of education
Primary or secondary school −1.48 (−7.78 to 4.83) .64 0.21 −2.63 (−10.39 to 5.13) .51
Undergraduate degree 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference]
Postgraduate degree 7.13 (1.53 to 12.73) .01 10.14 (3.26 to 17.03) .004
Motor (n = 159)b
Gestational age 3.01 (0.67 to 5.35) .01 0.21 3.01 (0.74 to 5.28) .009
Chronic lung disease −18.70 (−32.05 to 5.35) .006 0.22 −18.70 (−31.70 to −5.71) .005
Severe intraventricular hemorrhage(grade 3) −37.43 (−65.24 to −9.62) .009 0.20 −37.43 (−64.50 to −10.37) .007
Punctate white matter injury volume −0.03 (−0.05 to −0.01) .003 0.21 −0.03 (−0.04 to −0.01) .002
Small for gestational age −17.62 (−29.9 to −5.35) .005 0.21 −17.62 (−29.56 to −5.67) .004
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a

Cognitive model: F5,156 = 6.07; P < .001. Mallow Cp statistic: 4.84; adjusted R2=0.14; Akaike information criteria: 1355.5; Schwarz Bayesian criterion: 1373.0. See eMethods in the Supplement for a detailed description of this model after multiple imputation (n = 170).

b

Motor model: F5,137 = 9.43; P < .001; Mallow Cp statistic: 0.72; adjusted R2=0.21; Akaike information criteria: 1189.9; Schwarz Bayesian criterion: 1206.0.

When examining the standardized β coefficients, maternal level of education (standardized β = 0.21) had an association with cognitive outcomes that was similar to that of WMI (standardized β = 0.23) and severe IVH (standardized β = 0.23), and greater than that of CLD (Table 2).

When SES was operationalized by other factors (eg, years of education, occupation), associations of our primary clinical conditions with cognitive outcome at 4.5 years were similar (eTable 5 in the Supplement). The same model was tested for the 18-month and 36-month cognitive outcomes (eTable 6 in the Supplement).

Cognitive Trajectory 18 Months, 36 Months, and 4.5 Years

Cognitive scores were positively associated with increasing maternal level of education and negatively associated with brain injury and CLD at all points using mixed-effects models to examine the association with cognitive scores longitudinally (eTable 7 in the Supplement).

SES Modifies the Association Between Brain Injury and Outcome in Children Born Preterm

When comparing cognitive scores in children with and without brain injury (Table 3 and Figure 2), SES was associated with modified cognitive outcomes of both groups of children. In the absence of brain injury, the higher SES group achieved a predicted FSIQ that is 7.4 points higher (95% CI, 6.99-8.83; P < .001) than the lower SES group. In the presence of brain injury, the association with SES increased, with the higher SES group having a mean increase of 13.7 points (95% CI, 13.34-14.25; P < .001) relative to the lower SES group.

Table 3. Estimated Cognitive Scores in Children With and Without Brain Injury at Different Points.
Variable No Brain Injurya Brain Injuryb
Cognitive Score, Mean (95% CI) P Value Cognitive Score, Mean (95% CI) P Value
Cognitive score at 18 moc 102.2 (96.3 to 108.2) .001 97.2 (89.1 to 105.3) .001
Cognitive score at 36 moc 99.7 (93.7 to 105.7) .001 94.2 (86.1 to 102.4) .001
Cognitive score at 4.5 yc 99.5 (93.5 to 105.5) .001 94.2 (85.9 to 102.5) .001
Gestational age (centered at 28 wk) 1.3 (0.5 to 2.1) .002 0.3 (−1.3 to 1.9) .69
Maternal education
Primary or secondary schoold [Reference] [Reference] [Reference] [Reference]
Undergraduate degreed 2.0 (−4.3 to 8.3) .54 5.6 (−3.6 to 14.8) .23
Postgraduate degreed 7.4 (0.01 to 14.8) .05 13.7 (2.2 to 25.1) .02
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a

The group with no brain injury included 344 observations and 124 patients. Log likelihood = −1321.17; P = .001.

b

The group with brain injury included 170 observations and 62 patients. Log likelihood = −648.38; P = .001.

c

Mean (95% CI) of the cognitive scores at each occasion.

d

Associated increment in cognitive scores with maternal level of education.

Figure 2. Estimated IQ in Neonates With and Without Brain Injury by Maternal Level of Education.

Figure 2.

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Mean difference of IQ scores by groups of maternal level of education.

When comparing the estimated cognitive scores of children in different SES groups, brain injury exhibited a nonuniform association. In the higher SES group, the presence of brain injury was not associated with FSIQ (absolute mean difference = 0.7; 95% CI, −1.4 to 0.1; P = .09); the association of brain injury and FSIQ was stronger across the undergraduate group (absolute mean difference = 1.6; 95% CI, 1.2-1.9; P < .001) and the primary or secondary school group (absolute mean difference = 5.2; 95% CI, 4.6-5.9; P < .001) (Figure 2 and eFigure 2 in the Supplement).

Motor Outcome at 4.5 Years

The best model for motor outcome (measured using the M-ABC2 percentile score) at 4.5 years, adjusting for GA, included being small for GA and having severe IVH, WMI volume, and CLD (F5,137 = 9.43; P < .001; R2Adj = 0.21). When examining the standardized β coefficients, these 3 variables exhibited similar associations to motor outcomes (Table 2). Maternal level of education was not associated with motor outcome when included in this final model (β = 4.02; 95% CI, −1.23 to 9.27; P = .24). This model applied to the longitudinal motor scores is described in eTable 8 in the Supplement.

Discussion

In this study of children born very preterm, maternal education, brain injury, and CLD were the most significant factors associated with cognitive outcome at preschool age. Maternal education, an important indicator of SES, had the same statistical association with cognitive outcome as brain injury, including quantitative measures of WMI. Importantly, the association of brain injury and CLD with cognitive outcome was modified by SES such that these postnatal complications were not found to be associated with lower FSIQ in preterm children born to mothers with postgraduate education. Prior literature indicates an association of social inequities with brain maturation and neurodevelopmental outcomes in children; however, previous studies typically addressed SES in the context of poverty.18,19,44,45 The present study evaluated the role of SES in a relatively affluent geographical location with universal medical care. Our findings highlight the potential of higher SES to mitigate the consequence of neonatal brain injury in children born preterm.

Maternal education did not have the same association with motor outcomes, a finding consistent with previous studies.46 Motor outcomes were significantly associated with lower GA at birth, GA at birth, developing CLD, and brain injury. At age 4.5 years, the best models for motor and cognitive outcomes suggest some distinction in the pathways mediating these important aspects of neurodevelopmental outcome. These findings also reinforce the importance of prenatal and postnatal risk factors when considering interventions to improve neurodevelopment of children born preterm.47,48

Although the nature of preterm brain injury has evolved over the past decades, its association with neurodevelopmental outcome remains strong. Despite advances in perinatal care, cognitive outcomes among children born preterm have not improved since the 1990s.2,3,49,50 Preterm-born children still perform almost 1 SD below full-term children on intelligence tests.2 With the decline of cystic periventricular leukomalacia,51 the implications of the more recently recognized patterns of injury, such as punctate WMI, are shifting our focus to modifiable risk factors that might allow clinicians and parents to enhance brain development and improve functional outcomes.

Even in normative populations, contemporary brain imaging studies have demonstrated the association of SES factors with brain structure and development.44,52,53 For example, in a study44 of 1500 children in Los Angeles County, parental education was robustly associated with children’s total brain surface area. It has been suggested that the developing brain’s capacity for repair provides opportunities for interventions to dampen or even reverse the effects of early adversity, whether environmental or medical. The beneficial effects of early childhood intervention programs on later function are promising.54,55 In the Carolina Abecedarian Project, children from low-income families who were randomized to receive early educational intervention had greater developmental and education achievements56 and a lower prevalence of cardiovascular and metabolic disease in their mid-30s.54 Importantly, attempts to replicate these findings in children born preterm have not been as successful.22 Other interventions based on social risk have yielded better early cognition in preterm infants.57 Observational studies in preterm infants suggest a beneficial association between early cognition and interventions that promote sensitive parenting58 and increase access to resources such as high-quality day care.59 Together with the strong effect sizes of the Carolina Abecedarian trial and our new data, these findings support the importance of early experience and education to promote optimal neurodevelopmental outcomes following early-life adversity.

A possible explanation for our findings is that mothers with postgraduate education confer genes for higher intelligence to their offspring. In a recent meta-analysis, only up to 4.8% of the variance in intelligence is explained by genome-wide association study results.60 Furthermore, the genetic contributions to cognition appear to differ across SES in some cohorts. For example, in one study, the heritability of IQ is estimated at 5% in low-SES families, but up to 50% in high-SES families.61 In contrast, in a large representative cohort of twins in the United Kingdom, the estimated association of genetic factors with intelligence was similar in low- and high-SES families.62 In a sample of 11 000 pairs of twins from 4 countries, heritability of general cognitive ability was correlated with age: 41% at age 9 years to 66% at age 17 years.63 In children born at extremely low GA, those whose mothers received advanced education demonstrated improved inhibitory control and processing speed at age 10 years.13 Taken together, these findings suggest that the outcomes observed in our cohort of preschool children are not explained by genetic factors alone.

Robust neuroscience studies in animal models demonstrate that animals raised in enriched environments that include social stimulation, exercise, and novelty have improved brain structure and functional outcomes, including learning, memory, and plasticity.64,65,66,67,68 In a rodent model of neonatal seizures, even following status epilepticus, an enriched environment enhanced cognitive function, likely through an increase in neurogenesis.12 These experimental findings are congruent with our finding of higher SES modifying the association of early-life brain injury with preschool age cognitive outcome. In our clinical study, we used maternal education at the time of NICU admission as our primary measure of SES. When examining associations with other measures of SES, consistent with a prior study across Canadian centers, we found that maternal education is the most robust measure.37 The urgent challenge is now to identify the specific elements that differ in the experience of children born to mothers with higher educational attainment so that effective and efficient interventions can be evaluated.

Our findings also highlight the importance of postnatal illness as a contributor to neurodevelopmental outcomes in children born preterm. Postnatal comorbidities, including infections, retinopathy of prematurity, and CLD, as well as brain injury,34,50,69 are recognized to have negative associations with the long-term outcome of this population. In our study, together with brain injury, CLD was the most important postnatal comorbidity associated with cognitive outcomes. This finding is consistent with the association of CLD with white matter maturation at term equivalent age70 and long-term cognitive outcomes of preterm children.2 The importance of CLD is particularly reinforced in this cohort, in which the incidence of CLD (18%) was lower than the 27% incidence reported in the literature.2,50,71,72,73,74,75,76 Importantly, SES was associated with cognitive outcomes even when accounting for brain injury and CLD. Our findings are also consistent with earlier observations in this cohort that optimal parent-infant interaction might mitigate neurodevelopmental consequences of early-life procedural pain.77 Together, these findings highlight the potential to favorably affect trajectories of neurodevelopmental outcome by reducing exposure to early-life morbidities (eg, CLD) and enhancing the postnatal experience.

While prior studies of preterm children demonstrated that intelligence is negatively associated with GA,3,49,78 in our cohort, GA is only an important factor associated with outcome in those without brain injury. In the presence of brain injury and CLD, GA was not independently associated with cognitive outcomes. This finding is consistent with a recent meta-analysis2 in which the association between CLD and outcome was not confounded by GA, and with a brain imaging study79 of preterm neonates in which the association of very preterm birth with adverse white matter maturation was mediated by postnatal illness rather than extreme preterm birth itself. These findings reinforce that GA is not a fixed determinant of neurodevelopmental outcome and instead acts through potentially modifiable comorbidities that explain the wide variability in neurodevelopmental outcomes among children born at the same GA.

Limitations

Our study has several limitations. Data on maternal level of education were missing in 14% of the cohort, creating the potential for selection bias.14 Nevertheless, it is likely that this potential selection bias would have resulted in underestimation of the association of SES with cognitive outcome because children lost to follow-up tend to be from lower SES groups.80 If those in the lower maternal education group who were seen in follow-up were the most organized, we would expect the differences observed in our study to be further attenuated. We also recognize the use of different cognitive scores at ages 1.5 and 3 years relative to 4.5 years. Prior evidence81 and the intraclass correlation coefficients support the use of these scores in a longitudinal analyses. Assessment of cognition in young children becomes more complete with age, as more domains can be assessed.24,81 Thus, some change in scores within an individual may reflect better assessment of cognition rather than differences in the scoring tool. Our cohort was recruited from a high-resource setting with uniform access to health care. Further research could help identify determinants in more heterogeneous settings. In British Columbia, although there is universal coverage for health care and early intervention services, access to allied health care services may vary by region. Given available data, we were unable to adjust for individual patient interventions. We found a tight correlation of maternal and paternal education and occupation. As such, we did not distinguish specific factors associated with maternal rather than paternal education contributing to cognitive outcomes of children born preterm.

Conclusions

In children born preterm, preschool age cognitive outcome was associated with maternal level of education, an important measure of SES, with an effect size similar to that of neonatal brain injury. The association of brain injury with adverse cognitive outcomes in children born preterm was attenuated in children born to mothers of higher education level. While we recognize that both brain injury and lower SES were associated with neurodevelopmental disability in children born preterm, we found that both of these issues are of comparable importance and have the potential to influence each other. Our findings highlight that the neurodevelopmental sequelae of preterm birth are not static, but rather evolve through early childhood, offering the potential for modification by factors such as brain injury and SES. Future studies are needed to identify which aspects of higher SES have the greatest association with cognitive outcomes so that potential interventions and policies can be optimized for beneficial impact.

Supplement.

eMethods. Statistical Analysis

eFigure 1. Cohort Flow

eFigure 2. Predicted IQ According to Maternal Level of Education and the Presence of Brain Injury (Adjusted for GA)

eTable 1. Missing Values on the Dependent Variables

eTable 2. Agreement of the Cognitive Scores at Different Time Points

eTable 3. Missing Data of Independent Variables in the Model Related to Cognitive Scores at 4.5 Years (n=170) as Dependent Variable

eTable 4. Estimated Model After Multiple Imputation

eTable 5. Other Indexes of SES and Maternal Ethnicity Tested as Independent Variables With White Matter Injury, Severe Intraventricular Hemorrhage, Chronic Lung Disease and Gestational Age at Birth for the Prediction of FSIQ at 4.5 Years

eTable 6. Regression Model Obtained for the 4.5 Year-Outcome Final Model Applied to the 18 and 36 Months Cognitive Outcome

eTable 7. Estimated Cognitive Outcome Across Different Assessment Times Through Mixed Effects Models

eTable 8. Estimated Odds Ratio (OR) and 95% Confidence Intervals of the Motor Outcome Associated Variables Across Time Through Mixed-Effects Logistic Regression

eReferences

Click here for additional data file. (212.6KB, pdf)

References

  • 1.Synnes AR, Anson S, Arkesteijn A, et al. . School entry age outcomes for infants with birth weight ≤800 grams. J Pediatr. 2010;157(6):-. doi: 10.1016/j.jpeds.2010.06.016 [DOI] [PubMed] [Google Scholar]
  • 2.Twilhaar ES, Wade RM, de Kieviet JF, van Goudoever JB, van Elburg RM, Oosterlaan J. Cognitive outcomes of children born extremely or very preterm since the 1990s and associated risk factors: a meta-analysis and meta-regression. JAMA Pediatr. 2018;172(4):361-367. doi: 10.1001/jamapediatrics.2017.5323 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Kerr-Wilson CO, Mackay DF, Smith GC, Pell JP. Meta-analysis of the association between preterm delivery and intelligence. J Public Health (Oxf). 2012;34(2):209-216. doi: 10.1093/pubmed/fdr024 [DOI] [PubMed] [Google Scholar]
  • 4.Miller SP, Ferriero DM, Leonard C, et al. . Early brain injury in premature newborns detected with magnetic resonance imaging is associated with adverse early neurodevelopmental outcome. J Pediatr. 2005;147(5):609-616. doi: 10.1016/j.jpeds.2005.06.033 [DOI] [PubMed] [Google Scholar]
  • 5.Grunau RE, Whitfield MF, Fay TB. Psychosocial and academic characteristics of extremely low birth weight (< or =800 g) adolescents who are free of major impairment compared with term-born control subjects. Pediatrics. 2004;114(6):e725-e732. doi: 10.1542/peds.2004-0932 [DOI] [PubMed] [Google Scholar]
  • 6.Back SA, Miller SP. Brain injury in premature neonates: a primary cerebral dysmaturation disorder? Ann Neurol. 2014;75(4):469-486. doi: 10.1002/ana.24132 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Guo T, Duerden EG, Adams E, et al. . Quantitative assessment of white matter injury in preterm neonates: association with outcomes. Neurology. 2017;88(7):614-622. doi: 10.1212/WNL.0000000000003606 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Kazl C, Foote LT, Kim MJ, Koh S. Early-life experience alters response of developing brain to seizures. Brain Res. 2009;1285:174-181. doi: 10.1016/j.brainres.2009.05.082 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Alvarez PS, Simão F, Hemb M, Xavier LL, Nunes ML. Effects of undernourishment, recurrent seizures and enriched environment during early life in hippocampal morphology. Int J Dev Neurosci. 2014;33:81-87. doi: 10.1016/j.ijdevneu.2013.12.004 [DOI] [PubMed] [Google Scholar]
  • 10.van Praag H, Kempermann G, Gage FH. Neural consequences of environmental enrichment. Nat Rev Neurosci. 2000;1(3):191-198. doi: 10.1038/35044558 [DOI] [PubMed] [Google Scholar]
  • 11.Nithianantharajah J, Hannan AJ. Enriched environments, experience-dependent plasticity and disorders of the nervous system. Nat Rev Neurosci. 2006;7(9):697-709. doi: 10.1038/nrn1970 [DOI] [PubMed] [Google Scholar]
  • 12.Faverjon S, Silveira DC, Fu DD, et al. . Beneficial effects of enriched environment following status epilepticus in immature rats. Neurology. 2002;59(9):1356-1364. doi: 10.1212/01.WNL.0000033588.59005.55 [DOI] [PubMed] [Google Scholar]
  • 13.Joseph RM, O’Shea TM, Allred EN, Heeren T, Kuban KK. Maternal educational status at birth, maternal educational advancement, and neurocognitive outcomes at age 10 years among children born extremely preterm. Pediatr Res. 2018;83(4):767-777. doi: 10.1038/pr.2017.267 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Wong HS, Edwards P. Nature or nurture: a systematic review of the effect of socio-economic status on the developmental and cognitive outcomes of children born preterm. Matern Child Health J. 2013;17(9):1689-1700. doi: 10.1007/s10995-012-1183-8 [DOI] [PubMed] [Google Scholar]
  • 15.Noble KG, Norman MF, Farah MJ. Neurocognitive correlates of socioeconomic status in kindergarten children. Dev Sci. 2005;8(1):74-87. doi: 10.1111/j.1467-7687.2005.00394.x [DOI] [PubMed] [Google Scholar]
  • 16.Noble KG, McCandliss BD, Farah MJ. Socioeconomic gradients predict individual differences in neurocognitive abilities. Dev Sci. 2007;10(4):464-480. doi: 10.1111/j.1467-7687.2007.00600.x [DOI] [PubMed] [Google Scholar]
  • 17.Farah MJ, Shera DM, Savage JH, et al. . Childhood poverty: specific associations with neurocognitive development. Brain Res. 2006;1110(1):166-174. doi: 10.1016/j.brainres.2006.06.072 [DOI] [PubMed] [Google Scholar]
  • 18.Brito NH, Noble KG. Socioeconomic status and structural brain development. Front Neurosci. 2014;8:276. doi: 10.3389/fnins.2014.00276 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Johnson SB, Riis JL, Noble KG. State of the art review: poverty and the developing brain. Pediatrics. 2016;137(4):e20153075. doi: 10.1542/peds.2015-3075 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.von Stumm S, Plomin R. Socioeconomic status and the growth of intelligence from infancy through adolescence. Intelligence. 2015;48:30-36. doi: 10.1016/j.intell.2014.10.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Burnett AC, Cheong JLY, Doyle LW. Biological and social influences on the neurodevelopmental outcomes of preterm infants. Clin Perinatol. 2018;45(3):485-500. doi: 10.1016/j.clp.2018.05.005 [DOI] [PubMed] [Google Scholar]
  • 22.McCormick MC, Brooks-Gunn J, Buka SL, et al. . Early intervention in low birth weight premature infants: results at 18 years of age for the Infant Health and Development Program. Pediatrics. 2006;117(3):771-780. doi: 10.1542/peds.2005-1316 [DOI] [PubMed] [Google Scholar]
  • 23.Kidokoro H, Anderson PJ, Doyle LW, Woodward LJ, Neil JJ, Inder TE. Brain injury and altered brain growth in preterm infants: predictors and prognosis. Pediatrics. 2014;134(2):e444-e453. doi: 10.1542/peds.2013-2336 [DOI] [PubMed] [Google Scholar]
  • 24.Nguyen TN, Spencer-Smith M, Zannino D, et al. . Developmental trajectory of language from 2 to 13 years in children born very preterm. Pediatrics. 2018;141(5):e20172831. doi: 10.1542/peds.2017-2831 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Joseph RM, O’Shea TM, Allred EN, et al. ; ELGAN Study Investigators . Neurocognitive and academic outcomes at age 10 years of extremely preterm newborns. Pediatrics. 2016;137(4):e20154343. doi: 10.1542/peds.2015-4343 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative . The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies. Int J Surg. 2014;12(12):1495-1499. doi: 10.1016/j.ijsu.2014.07.013 [DOI] [PubMed] [Google Scholar]
  • 27.Chau V, Synnes A, Grunau RE, Poskitt KJ, Brant R, Miller SP. Abnormal brain maturation in preterm neonates associated with adverse developmental outcomes. Neurology. 2013;81(24):2082-2089. doi: 10.1212/01.wnl.0000437298.43688.b9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Duerden EG, Guo T, Dodbiba L, et al. . Midazolam dose correlates with abnormal hippocampal growth and neurodevelopmental outcome in preterm infants. Ann Neurol. 2016;79(4):548-559. doi: 10.1002/ana.24601 [DOI] [PubMed] [Google Scholar]
  • 29.Chau V, Poskitt KJ, McFadden DE, et al. . Effect of chorioamnionitis on brain development and injury in premature newborns. Ann Neurol. 2009;66(2):155-164. doi: 10.1002/ana.21713 [DOI] [PubMed] [Google Scholar]
  • 30.Chau V, Brant R, Poskitt KJ, Tam EW, Synnes A, Miller SP. Postnatal infection is associated with widespread abnormalities of brain development in premature newborns. Pediatr Res. 2012;71(3):274-279. doi: 10.1038/pr.2011.40 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Glass TJA, Chau V, Gardiner J, et al. . Severe retinopathy of prematurity predicts delayed white matter maturation and poorer neurodevelopment. Arch Dis Child Fetal Neonatal Ed. 2017;102(6):F532-F537. doi: 10.1136/archdischild-2016-312533 [DOI] [PubMed] [Google Scholar]
  • 32.Adams E, Chau V, Poskitt KJ, Grunau RE, Synnes A, Miller SP. Tractography-based quantitation of corticospinal tract development in premature newborns. J Pediatr. 2010;156(6):882-888.e1. doi: 10.1016/j.jpeds.2009.12.030 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Brummelte S, Grunau RE, Chau V, et al. . Procedural pain and brain development in premature newborns. Ann Neurol. 2012;71(3):385-396. doi: 10.1002/ana.22267 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Schmidt B, Roberts RS, Davis PG, et al. ; Caffeine for Apnea of Prematurity (CAP) Trial Investigators; Caffeine for Apnea of Prematurity CAP Trial Investigators . Prediction of late death or disability at age 5 years using a count of 3 neonatal morbidities in very low birth weight infants. J Pediatr. 2015;167(5):982-6.e2. doi: 10.1016/j.jpeds.2015.07.067 [DOI] [PubMed] [Google Scholar]
  • 35.Cirino PT, Chin CE, Sevcik RA, Wolf M, Lovett M, Morris RD. Measuring socioeconomic status: reliability and preliminary validity for different approaches. Assessment. 2002;9(2):145-155. doi: 10.1177/10791102009002005 [DOI] [PubMed] [Google Scholar]
  • 36.Hollingshead AB. Four factor index of social status. https://sociology.yale.edu/sites/default/files/files/yjs_fall_2011.pdf. Accessed August 1, 2018.
  • 37.Asztalos EV, Church PT, Riley P, Fajardo C, Shah PS; Canadian Neonatal Network and Canadian Neonatal Follow-up Network Investigators . Association between primary caregiver education and cognitive and language development of preterm neonates. Am J Perinatol. 2017;34(4):364-371. [DOI] [PubMed] [Google Scholar]
  • 38.Papile LA, Burstein J, Burstein R, Koffler H. Incidence and evolution of subependymal and intraventricular hemorrhage: a study of infants with birth weights less than 1,500 gm. J Pediatr. 1978;92(4):529-534. doi: 10.1016/S0022-3476(78)80282-0 [DOI] [PubMed] [Google Scholar]
  • 39.Bayley N. Bayley Scales of Infant and Toddler Development. 3rd ed San Antonio, TX: Harcourt Assessments; 2006. [Google Scholar]
  • 40.Wechsler D. Wechsler Preschool and Primary Scale of Intelligence. 4th ed San Antonio, TX: Pearson; 2002. [Google Scholar]
  • 41.Henderson SE, Sugden DA, Barnett AL. Movement Assessment Battery for Children. San Antonio, TX: Psychological Corp; 2007. [Google Scholar]
  • 42.Griffiths A, Morgan P, Anderson PJ, Doyle LW, Lee KJ, Spittle AJ. Predictive value of the Movement Assessment Battery for Children—Second Edition at 4 years, for motor impairment at 8 years in children born preterm. Dev Med Child Neurol. 2017;59(5):490-496. doi: 10.1111/dmcn.13367 [DOI] [PubMed] [Google Scholar]
  • 43.Doménech Massons JM, Navarro Pastor JB Find the best subset for linear, logistic and Cox regression: user-written command allsets for Stata. V1.2.0. http://www.graunt.cat/stata. Accessed September 1, 2017.
  • 44.Noble KG, Houston SM, Brito NH, et al. . Family income, parental education and brain structure in children and adolescents. Nat Neurosci. 2015;18(5):773-778. doi: 10.1038/nn.3983 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Laucht M, Esser G, Schmidt MH. Developmental outcome of infants born with biological and psychosocial risks. J Child Psychol Psychiatry. 1997;38(7):843-853. doi: 10.1111/j.1469-7610.1997.tb01602.x [DOI] [PubMed] [Google Scholar]
  • 46.Grunau RE, Whitfield MF, Petrie-Thomas J, et al. . Neonatal pain, parenting stress and interaction, in relation to cognitive and motor development at 8 and 18 months in preterm infants. Pain. 2009;143(1-2):138-146. doi: 10.1016/j.pain.2009.02.014 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Barros FC, Papageorghiou AT, Victora CG, et al. ; International Fetal and Newborn Growth Consortium for the 21st Century . The distribution of clinical phenotypes of preterm birth syndrome: implications for prevention. JAMA Pediatr. 2015;169(3):220-229. doi: 10.1001/jamapediatrics.2014.3040 [DOI] [PubMed] [Google Scholar]
  • 48.Marlow N, Wolke D, Bracewell MA, Samara M; EPICure Study Group . Neurologic and developmental disability at six years of age after extremely preterm birth. N Engl J Med. 2005;352(1):9-19. doi: 10.1056/NEJMoa041367 [DOI] [PubMed] [Google Scholar]
  • 49.Bhutta AT, Cleves MA, Casey PH, Cradock MM, Anand KJ. Cognitive and behavioral outcomes of school-aged children who were born preterm: a meta-analysis. JAMA. 2002;288(6):728-737. doi: 10.1001/jama.288.6.728 [DOI] [PubMed] [Google Scholar]
  • 50.Groenendaal F, Termote JU, van der Heide-Jalving M, van Haastert IC, de Vries LS. Complications affecting preterm neonates from 1991 to 2006: what have we gained? Acta Paediatr. 2010;99(3):354-358. doi: 10.1111/j.1651-2227.2009.01648.x [DOI] [PubMed] [Google Scholar]
  • 51.Hamrick SE, Miller SP, Leonard C, et al. . Trends in severe brain injury and neurodevelopmental outcome in premature newborn infants: the role of cystic periventricular leukomalacia. J Pediatr. 2004;145(5):593-599. doi: 10.1016/j.jpeds.2004.05.042 [DOI] [PubMed] [Google Scholar]
  • 52.Noble KG, Korgaonkar MS, Grieve SM, Brickman AM. Higher education is an age-independent predictor of white matter integrity and cognitive control in late adolescence. Dev Sci. 2013;16(5):653-664. doi: 10.1111/desc.12077 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.McDermott CL, Seidlitz J, Nadig A, et al. . Longitudinally mapping childhood socioeconomic status associations with cortical and subcortical morphology. J Neurosci. 2019;39(8):1365-1373. doi: 10.1523/JNEUROSCI.1808-18.2018 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Campbell F, Conti G, Heckman JJ, et al. . Early childhood investments substantially boost adult health. Science. 2014;343(6178):1478-1485. doi: 10.1126/science.1248429 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Heckman J, Pinto R, Savelyev P. Understanding the mechanisms through which an influential early childhood program boosted adult outcomes. Am Econ Rev. 2013;103(6):2052-2086. doi: 10.1257/aer.103.6.2052 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Campbell FA, Ramey CT. Effects of early intervention on intellectual and academic achievement: a follow-up study of children from low-income families. Child Dev. 1994;65(2, spec No.):684-698. doi: 10.2307/1131410 [DOI] [PubMed] [Google Scholar]
  • 57.Spittle A, Orton J, Anderson PJ, Boyd R, Doyle LW. Early developmental intervention programmes provided post hospital discharge to prevent motor and cognitive impairment in preterm infants. Cochrane Database Syst Rev. 2015;11(11):CD005495. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58.Wolke D, Jaekel J, Hall J, Baumann N. Effects of sensitive parenting on the academic resilience of very preterm and very low birth weight adolescents. J Adolesc Health. 2013;53(5):642-647. doi: 10.1016/j.jadohealth.2013.06.014 [DOI] [PubMed] [Google Scholar]
  • 59.Vandell DL, Belsky J, Burchinal M, Steinberg L, Vandergrift N; NICHD Early Child Care Research Network . Do effects of early child care extend to age 15 years? results from the NICHD study of early child care and youth development. Child Dev. 2010;81(3):737-756. doi: 10.1111/j.1467-8624.2010.01431.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Sniekers S, Stringer S, Watanabe K, et al. . Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence. Nat Genet. 2017;49(7):1107-1112. doi: 10.1038/ng.3869 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61.Tucker-Drob EM, Rhemtulla M, Harden KP, Turkheimer E, Fask D. Emergence of a gene x socioeconomic status interaction on infant mental ability between 10 months and 2 years. Psychol Sci. 2011;22(1):125-133. doi: 10.1177/0956797610392926 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62.Hanscombe KB, Trzaskowski M, Haworth CM, Davis OS, Dale PS, Plomin R. Socioeconomic status (SES) and children’s intelligence (IQ): in a UK-representative sample SES moderates the environmental, not genetic, effect on IQ. PLoS One. 2012;7(2):e30320. doi: 10.1371/journal.pone.0030320 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.Haworth CM, Wright MJ, Luciano M, et al. . The heritability of general cognitive ability increases linearly from childhood to young adulthood. Mol Psychiatry. 2010;15(11):1112-1120. doi: 10.1038/mp.2009.55 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64.Diamond MC, Krech D, Rosenzweig MR. The effects of an enriched environment on the histology of the rat cerebral cortex. J Comp Neurol. 1964;123:111-120. doi: 10.1002/cne.901230110 [DOI] [PubMed] [Google Scholar]
  • 65.Kempermann G, Kuhn HG, Gage FH. More hippocampal neurons in adult mice living in an enriched environment. Nature. 1997;386(6624):493-495. doi: 10.1038/386493a0 [DOI] [PubMed] [Google Scholar]
  • 66.Bennett EL, Rosenzweig MR, Diamond MC. Rat brain: effects of environmental enrichment on wet and dry weights. Science. 1969;163(3869):825-826. doi: 10.1126/science.163.3869.825 [DOI] [PubMed] [Google Scholar]
  • 67.Leger M, Paizanis E, Dzahini K, et al. . Environmental enrichment duration differentially affects behavior and neuroplasticity in adult mice. Cereb Cortex. 2015;25(11):4048-4061. doi: 10.1093/cercor/bhu119 [DOI] [PubMed] [Google Scholar]
  • 68.Brenes JC, Lackinger M, Höglinger GU, Schratt G, Schwarting RK, Wöhr M. Differential effects of social and physical environmental enrichment on brain plasticity, cognition, and ultrasonic communication in rats. J Comp Neurol. 2016;524(8):1586-1607. doi: 10.1002/cne.23842 [DOI] [PubMed] [Google Scholar]
  • 69.Schmidt B, Asztalos EV, Roberts RS, Robertson CM, Sauve RS, Whitfield MF; Trial of Indomethacin Prophylaxis in Preterms (TIPP) Investigators . Impact of bronchopulmonary dysplasia, brain injury, and severe retinopathy on the outcome of extremely low-birth-weight infants at 18 months: results from the trial of indomethacin prophylaxis in preterms. JAMA. 2003;289(9):1124-1129. doi: 10.1001/jama.289.9.1124 [DOI] [PubMed] [Google Scholar]
  • 70.Neubauer V, Junker D, Griesmaier E, Schocke M, Kiechl-Kohlendorfer U. Bronchopulmonary dysplasia is associated with delayed structural brain maturation in preterm infants. Neonatology. 2015;107(3):179-184. doi: 10.1159/000369199 [DOI] [PubMed] [Google Scholar]
  • 71.Grisaru-Granovsky S, Reichman B, Lerner-Geva L, et al. ; Israel Neonatal Network . Population-based trends in mortality and neonatal morbidities among singleton, very preterm, very low birth weight infants over 16 years. Early Hum Dev. 2014;90(12):821-827. doi: 10.1016/j.earlhumdev.2014.08.009 [DOI] [PubMed] [Google Scholar]
  • 72.Chen F, Bajwa NM, Rimensberger PC, Posfay-Barbe KM, Pfister RE; Swiss Neonatal Network . Thirteen-year mortality and morbidity in preterm infants in Switzerland. Arch Dis Child Fetal Neonatal Ed. 2016;101(5):F377-F383. doi: 10.1136/archdischild-2015-308579 [DOI] [PubMed] [Google Scholar]
  • 73.Fanaroff AA, Stoll BJ, Wright LL, et al. ; NICHD Neonatal Research Network . Trends in neonatal morbidity and mortality for very low birthweight infants. Am J Obstet Gynecol. 2007;196(2):147.e1-147.e8. doi: 10.1016/j.ajog.2006.09.014 [DOI] [PubMed] [Google Scholar]
  • 74.Costeloe KL, Hennessy EM, Haider S, Stacey F, Marlow N, Draper ES. Short term outcomes after extreme preterm birth in England: comparison of two birth cohorts in 1995 and 2006 (the EPICure studies). BMJ. 2012;345:e7976. doi: 10.1136/bmj.e7976 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 75.Shah PS, Sankaran K, Aziz K, et al. ; Canadian Neonatal Network . Outcomes of preterm infants <29 weeks gestation over 10-year period in Canada: a cause for concern? J Perinatol. 2012;32(2):132-138. doi: 10.1038/jp.2011.68 [DOI] [PubMed] [Google Scholar]
  • 76.Ancel PY, Goffinet F, Kuhn P, et al. ; EPIPAGE-2 Writing Group . Survival and morbidity of preterm children born at 22 through 34 weeks’ gestation in France in 2011: results of the EPIPAGE-2 cohort study. JAMA Pediatr. 2015;169(3):230-238. doi: 10.1001/jamapediatrics.2014.3351 [DOI] [PubMed] [Google Scholar]
  • 77.Vinall J, Miller SP, Synnes AR, Grunau RE. Parent behaviors moderate the relationship between neonatal pain and internalizing behaviors at 18 months corrected age in children born very prematurely. Pain. 2013;154(9):1831-1839. doi: 10.1016/j.pain.2013.05.050 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 78.Garfield CF, Karbownik K, Murthy K, et al. . Educational performance of children born prematurely. JAMA Pediatr. 2017;171(8):764-770. doi: 10.1001/jamapediatrics.2017.1020 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 79.Bonifacio SL, Glass HC, Chau V, et al. . Extreme premature birth is not associated with impaired development of brain microstructure. J Pediatr. 2010;157(5):726-32.e1. doi: 10.1016/j.jpeds.2010.05.026 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 80.Callanan C, Doyle L, Rickards A, Kelly E, Ford G, Davis N. Children followed with difficulty: how do they differ? J Paediatr Child Health. 2001;37(2):152-156. doi: 10.1046/j.1440-1754.2001.00621.x [DOI] [PubMed] [Google Scholar]
  • 81.Bode MM, DʼEugenio DB, Mettelman BB, Gross SJ. Predictive validity of the Bayley, Third Edition at 2 years for intelligence quotient at 4 years in preterm infants. J Dev Behav Pediatr. 2014;35(9):570-575. doi: 10.1097/DBP.0000000000000110 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement.

eMethods. Statistical Analysis

eFigure 1. Cohort Flow

eFigure 2. Predicted IQ According to Maternal Level of Education and the Presence of Brain Injury (Adjusted for GA)

eTable 1. Missing Values on the Dependent Variables

eTable 2. Agreement of the Cognitive Scores at Different Time Points

eTable 3. Missing Data of Independent Variables in the Model Related to Cognitive Scores at 4.5 Years (n=170) as Dependent Variable

eTable 4. Estimated Model After Multiple Imputation

eTable 5. Other Indexes of SES and Maternal Ethnicity Tested as Independent Variables With White Matter Injury, Severe Intraventricular Hemorrhage, Chronic Lung Disease and Gestational Age at Birth for the Prediction of FSIQ at 4.5 Years

eTable 6. Regression Model Obtained for the 4.5 Year-Outcome Final Model Applied to the 18 and 36 Months Cognitive Outcome

eTable 7. Estimated Cognitive Outcome Across Different Assessment Times Through Mixed Effects Models

eTable 8. Estimated Odds Ratio (OR) and 95% Confidence Intervals of the Motor Outcome Associated Variables Across Time Through Mixed-Effects Logistic Regression

eReferences

Click here for additional data file. (212.6KB, pdf)

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