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Perinatal, neonatal, developmental and demographic predictors of intelligence at iv years of age amid depression birth weight children: a panel written report with a 2-year follow-upwards

BMC Pediatrics volume 22, Article number:88 (2022) Cite this article

Abstract

Intoduction

Childhood intelligence is an important predictor of later outcomes in life such as socioeconomic status or health. Hence, a deeper understanding of predictors of child intelligence should suggest points of intervention for children facing adversities.

Objectives

The purpose of this study is to examine the predictive value of demographic, perinatal and neonatal variables after birth and developmental characteristics at age ii for 4-yr intelligence as issue among depression nascence weight children.

Methods

Nosotros designed a panel study with a ii-twelvemonth follow-up with 114 child-mother pairs. The event variable was IQ intelligence caliber at four years of historic period of LBW low nativity weight children measured by the Wechsler Master and Preschool Scales of Intelligence. Potential predictors were maternal pedagogy, family wealth, indigenous identity; sex, twin pregnancy, gestational age, nascence weight, Apgar scores, maternal smoking during pregnancy; diagnosis of intravetricular haemorrhage, retinopathy of prematurity, bronchopulmonary dysplasia afterwards birth and cerebral, language and motor development at historic period 2 measured by one composite score of the three Bayley Scales of Infant and Toddler Development aggregated.

Results

Stepwise backward regression was carried out including significant variables from the bivariate assay. The all-time model included iv predictors which accounted for 57% of the variance of the total IQ intelligence at iv-years of age. Maternal college didactics was significant positive, beneath boilerplate family wealth and neonatal diagnosis of bronchopulmonary dysplasia were significant negative predictors in the model after nativity. 2-year developmental characteristics such as cognitive, motor and language skills were positive predictors of the IQ intelligence at age four.

Determination

Sociodemographic cess at nascence and developmental assessment at two years of age are of crucial importance to recognize children at high risk for delayed cognitive development. High-risk children should be directed to supportive interventions and their development should be regulary monitored.

Peer Review reports

Introduction

Cognitive skills operacionalized as childhood intelligence quotient (IQ) incorporate one of the most important predictors of later outcomes in life such as socioeconomic status or health [1,2,3]. Hence, a deeper agreement of predictors of child intelligence should provide points of prevention for children facing adversities.

A large body of original articles across various types of written report populations suggests that parental education, family unit income, and maternal intelligence are dominant predictors of childhood intelligence. Eriksen et al. (2013) [4] institute that parental education, maternal IQ and the child's gender accounted for 24% of the variance in IQ at 5 years of age [4]. Other studies reported similar results: maternal and paternal education together was considered as a strong predictor (R 2  = 0.19) of IQ at age viii [5], while the sociodemographic status of the family at birth explained nearly 10% of the variance in IQ at ages betwixt seven – xi [6]. Inaddition to parental demographic factors, postnatal factors such as breastfeeding[vii] and physical growth of the child during the first year of life [8] were found to be significantly associated with later IQ [vii, 8]. Previous studies of children with low nascency weight accept constitute associations betwixt birth weight, low intelligence and attention deficits [9, 10]. These unfavourable outcomes may in part be due to premature gestational age, but other neonatal factors such as chronic diseases and social factors including parental intelligence, parental education, and family wealth may likewise affect the cognitive outcomes of the child. Early developmental milestones take been identified in several studies as of import predictors of developed IQ [11]. The impact of these early developmental characteristics vary across studies which may reflect differences between written report samples and investigated predictors. Resolution of many of the complex questions well-nigh the later consequences of preterm nativity and low birth weight requires prospective follow-upwardly studies investigating potential determinant variables. The present study aims to contribute to this resolution.

The principal purpose of the current study is to examine the predictive value of demographic, perinatal and neonatal variables at childbirth and developmental characteristics at age 2 for 4-twelvemonth intelligence every bit the outcome among low birth weight (LBW) children.

Methods

Ethics approval and consent to participate

The study received permission from the Hungarian Medical Inquiry Quango (33176–2/2017/EKU) following the ethical principles of the WMA Declaration of Helsinki. Written informed consent was obtained from all parent(s)/ legal guardians.

Written report design and participants

We designed a panel report with a ii-twelvemonth follow-up. The sampling frame consisted of children born in the Department of Obstetrics and Gynaecology of the Clinical Center of the University of Debrecen in Hungary between June 2014 – August 2016 with nativity weight below 2500 grand and no visual damage due to severe retinopathy of prematurity. Neonates born with visual impairment of prematurity were excluded since diagnostic tools used to measure developmental characteristics and IQ are not suitable for children with visual impairment. Mothers of the invited children made the determination to participate by providing written informed consent. Inclusion was further differentiated by birth weight. All children born below 1500 g without the exclusion criterion were invited to participate, whereas children between 1500–2500 g birthweight were selected to produce a subsample that fit the gender distribution of the very low birth weight (< 1500 grand) group. Data of these ii groups were analysed together in this paper.

Sources of information

Data collection was carried out between September 2016 and January 2020. Perinatal and neonatal information were obtained from the final reports of children in the database of the Neonatology Unit of the Department of Obstetrics and Gynaecology. Measurement data at two and iv years of age were collected by the starting time author, a trained psychologist, by individually assessing children nether the supervision of the senior writer. All assessments took place at the Pediatric Psychology and Psychosomatic Unit of measurement of the Department of Pediatrics of the Clinical Center of the University of Debrecen.

Timeline of data collection

Three hundred five mother–kid pairs with children 2 years of age were recruited in the first flow of study (September 2016—August 2018) when the Bayley Scales of Infant and Toddler Development 3rd Edition test [12] was administered. Of those, 114 mothers whose children reached iv years of age agreed to participate in the second study flow – between September 2018 and January 2020 – when the Wechsler Principal and Preschool Scales of Intelligence 4th Edition IQ test [13] was administered.

Iv hundred and forty-half dozen children and their mothers befitting to the inclusion criteria were asked between September 2016 and August 2018 to participate in the study when the children were 2 years of age. Of those invited, 305 (68.3%) participated in the showtime study menstruum when the Bayley Scales of Infant and Toddler Evolution 3rd Edition test [12] was administered. Of the mother–child pairs assessed in the first study menstruum, 158 children reached 4 years of age between September 2018 and Jan 2020. All were invited and 114 (72.1%) agreed to participate in the 2nd cess, when the Wechsler Primary and Preschool Scales of Intelligence ivth Edition IQ test [13] was administered (second study period).

Outcome variable

The outcome variable was divers as the children'southward IQ at 4-years of historic period measured by the Wechsler Primary and Preschool Scales of Intelligence – 4th edition (WPPSI-IV [13]). The validated Hungarian version of WPPSI-4 was used which measures IQ consistently and accurately attested past its reliability (Chronbach α = 0.86–0.95) calculated during the accommodation process [14]. All 5 primary subtests were completed: Verbal Comprehension (VCI), Fluid Reasoning (FRI), Visual-Spatial ability (VSI), Processing Speed (PSI), and Working Retentivity (WMI) from which the score of the Total Scale IQ (FSIQ) was calculated. FSIQ reflects the performance in distinct cerebral domains and is considered the most representative indicator of global intellectual functioning. The theoretical hateful score of all subtest indices and the FSIQ are normalized (mean: 100; standard departure: fifteen [13]).

Predictor variables by domains

  • Demographic variables: Information on maternal education (primary/ secondary/ higher) and subjective family unit wealth (below average/ boilerplate/ to a higher place average) were obtained past a questionnaire completed by the mothers at follow-upward. Indigenous identity was classified by one external observer (Hungarian/ Roma).

  • Perinatal characteristics: The child'south sexual activity, twin pregnancy (yes/no), gestational age (months), birth weight (grams) and Apgar scores at 1 and 5 min (0–10) were obtained from the neonatal final reports retrospectively. The Apgar-score is calculated for newborns at 1 and 5 min later on nascence based on pare color, heart rate, reflex irritability, muscle tone and respiratory endeavor ranging betwixt 0–10 where a score of eight or to a higher place reflects good wellness [15]. Information on maternal smoking during pregnancy was assessed by a cocky-written report question and included as binary variable (aye/no) in the statistical analysis.

  • Neonatal variables: Information on any of iii postnatal illnesses—intravetricular bleeding (IVH), retinopathy of prematurity (ROP) and bronchopulmonary dysplasia (BPD)—was obtained from the neonatal final reports as described elsewhere [16].

  • Developmental characteristics at 2 years: Neurodevelopmental characteristics of the children were measured by the Bayley Scales of Babe and Toddler Development, threerd Edition (BSID-III [12]). The test measures the infants's abilities by five subscales and provides objective information on cerebral, expressive and receptive language likewise every bit fine and gross motor development. Raw scores of each subscale are normalized to a hateful of 10 and standard departure of 3. Raw scores can be transformed into iii composite scores (Q values), which are normalized to a mean of 100 and standard deviation of xv and refer to the cognitive, language and motor performance. Composite scores betwixt 85 lxx and lxx 85 (and raw scores betwixt four and 7) with -2 SD to -1SD reflect mild filibuster, while composite scores below 70 (and raw scores below 4) and more than -2 SD place children with severe filibuster [12, 17]. For statistical analysis, an aggregated value was calculated from the mean of the 3 composite scores (∑Cog-Lang-Mot).

Statistical analysis

Statistical analyses were carried out with IBM SPSS Statistics v23 and Stata/IC 16.i. Univariate analysis of variance was used for calculating the power of the sample and probability of type 2 fault. Pearson correlation was used to test bivariate association with all variables. Signal biserial correlation was also carried out to account for binary variables (coded as exposed – i or not-exposed – 0) that yielded the same results as Pearson. 2nd, linear regression analysis and stepwise astern regression were conducted with variables of the 4 predictor domains (demographic, perinatal, neonatal and developmental characteristics) for the event variable. Subscales of the BSID-3 were tested separately, and also as aggregate measure. Significance level was set at blastoff = 0.05. The models were evaluated by explained variance (R2), mensurate of residuals (root mean square mistake), and measure of the models' fit (Akaike's information criterion). Third, predictors of the best fitting model were identified by stepwise backward regression analysis, setting alpha for the removal of predictors at 0.05.

Patient and public Involvement

The enquiry question addressed patients' priorities and interests since low birth weight with its consequences has been an of import public wellness issue in Hungary. Republic of hungary had the sixth highest rate of low birth weight among OECD countries in 2018. Participants were involved neither in study design nor in recruitment. Diagnostic tests at two years of historic period are performed as part of the two-year status examination of premature infants in outpatient intendance offered to all LBW children. However, IQ assessment at 4 years of age is not role of the routine assessment of LBW children, this was offered merely to participants in the report the results of which were fed back to parents of participating children. Results of the children'due south assessments at 2 and 4 years of age were discussed with parents. In cases of mild developmental filibuster, parents were shown developmental exercises to be performed with the child at dwelling house. In cases of severe developmental delay, parents were referred to specialist care for farther diagnostic tests and intervention. The assessments performed in the study served equally of import timepoints for psychological and developmental screening of children at run a risk and their families. Sure results have already been presented to customs health workers in bear upon with families at loftier risk of LBW birth. Findings volition exist disseminated to the professional and lay public in the form of conference presentations and health education materials.

Results

Characteristics of the sample

Four hundred and twoscore-6 children and their mothers were invited to participate in the study when the children were 2 years of historic period. Of those, 305 (68.three%) mother–child pairs agreed to participate in the first study period. Of those, 158 children reached four years of age in the 2d study menstruum, all of whom were invited and 114 (72.ane%) agreed to participate. The most common reason for non-participation in the first phase and driblet-out in the second phase of the study were relocation to a distant office of the land and not willing to travel back.

Univariate analysis of variance was used for calculating the ability of the sample and probability of type II error. The observed ability was 96% with p-value < 0.001; Beta value was three%. Of all children included in the study, 114 participated in both assessments at two and also at four years of historic period (l boys, 44%). The children's birth weight ranged between 450 and 2480 grand (One thousand = 1310.08 ± 545.72 1000). The mean gestational age (M = 30.00 ± 3.85 months; 22–37 months) reflected the prematurity of the children. Apgar-scores were low at one min (M = vi.97 ± 1.74), still, the five-min values (One thousand = 8.34 ± one.02) were significantly improved (p < 0.001). Perinatal, neonatal, developmental and demographic characterestics of the sample are shown in Table one.

Table i Characteristics of the sample by predictor domains and their correlations with IQ at 4 years of age

Total size table

Bivariate correlations

The full-calibration IQ (FSIQ) performance at 4 years of historic period showed significant correlation with all just 2 predictor variables (sex of kid, twin pregnancy) as shown in Table one. The strongest correlations were constitute with developmental charachteristics at 2 years of age (cognitive: p < 0.001, finemotor: p < 0.001 and receptive communication skills: p < 0.001) and maternal educational activity (p < 0.001). Significant association of FSIQ was establish with maternal smoking during pregnancy (p < 0.001), nativity weight (p < 0.001), gestational age (p = 0.001), neonatal diagnosis of BPD (p < 0.001), ROP (p < 0.001) and IVH (p = 0.010), Apgar-scores (at i min.: p = 0.014; at 5 min.: p = 0.010), and demographic variables such as ethnicity (p = 0.001) and family unit wealth (p < 0.001).

Model selection

Total-scale IQ at 4 years of historic period was found to be normally distributed so information technology was appropriate for linear regression modeling. Contained variables significantly correlated with the outcome variable were included in the models as predictors. Maternal teaching and family wealth were transformed into binary variables (maternal education: higher education/below; family wealth: below boilerplate/higher). Neonatal morbities such as BPD, ROP and IVH were included in the model as binary varibles (yes/no). A series of regression analysis were conducted in gild to find the all-time model.

First, linear regression was conducted with all 16 predictor variables that showed bivariate correlation with the outcome. The 5 BSID subscales (raw scores) were included separately in this model (Model i in Table 2). In this model, only maternal education was predictor for FSIQ. Stepwise backward regression with the same fix of variables yielded a slightly stronger model in which five variables (maternal didactics, family wealth, fine motor, gross motor and receptive communication skills at 2 years of historic period) remained as significant predictors (Model ii).

Table 2 Linear regression modeling

Full size table

Adjacent, linear regression (Model 3) and stepwise backward regression (Model iv) were carried out with the same variables every bit in Model 1 and 3 except for the Bayley subscales which were included every bit ane aggregate measure calculated equally described in methods. As Table 2 shows, the apply of the aggregate BSID score resulted in better models than including the subscales separately. Model 3 identified maternal instruction and the 2-twelvemonth developmental score every bit significant predictors of intelligence at 4 years of age. Model iv was identified as the best model based on the highest proportion of explained variance, everyman measure out of residuals (RMSE), and lowest AIC reflecting all-time fit out of the 4 models.

Predictors in the best model

Our all-time model included 4 predictors which accounted for 57% of the variance of the full IQ at 4-years of age (Table iii). Of the four predictors, 3 were assessed at birth (maternal pedagogy, subjective family wealth, bronchopulmonary dysplasia [BPD] at birth), and 1 (the aggregated developmental score based on BSID-III) at age 2. Of the four predictors, two were related to the socio-economic status of the family: maternal teaching and family wealth. Children of higher educated mothers had an average of eight.8 points higher IQ at age iv than their peers born to primary or secondary educated mothers. Of the socio-demographic factors, the strongest clan was establish between beneath-average family wealth and the children'southward IQ at iv years. Preemies of families with below-average wealth scored on average 11.9 points lower in terms of cognitive skills at age 4. Bronchopulmonary dysplasia later birth predicted an average of 8.four points lower IQ performance at 4 years of age.

Table iii Predictors in Model iv

Total size tabular array

Out of the predictors in our final model, developmental characteristics at 2 years of historic period was found to be a strong predictor of later IQ: 1-signal increment of the Q-value in two-year-former BSID average performance results in a 0.77-indicate IQ increase at 4 years of historic period (Table three).

Discussion

Low birthweight children were followed in our birth accomplice study in order to identify significant predictors of cognitive performance assessed as IQ at iv years of historic period. 57% of the variance in iv-year IQ was explained by two parental variables (maternal teaching and subjective family unit wealth), bronchopulmonary dysplasia after birth, and developmental characteristics of the child at 2 years of age. Higher pedagogy of the mother was a meaning positive, lower family wealth was a significant negative predictor in the final model. Developmental characteristics assessed at ii years of age such as cognitive, motor and linguistic communication skills were strong positive predictors of the IQ at age 4.

Strengths of our study are the panel design with two years of follow-upwards, and the relatively big sample size. The wide range of collected data including parental and familial factors, perinatal information and developmental assessment at two years of historic period immune multiple regression modeling of the cerebral issue at 4 years of age. One limitation of our study is the limited range of parental information. We had neither data on relevant maternal conditions such as nutritional status or illicit drug apply, nor on whatever information nearly the fathers or the quality of the parental relationship that all potentially accept an impact on intrauterine growth. An age-fitted command grouping could have enabled us to compare the developmental filibuster of our cohort. Still, the evolution of LBW children should primarily exist compared to their ain previous status so the lack of control does non hinder the interpretation of our findings.

In contrast with other researchers [4, 18, xix] we did not find nascency weight or gestational age to be significant predictors of later IQ among LBW children. In nearly of these studies no data was provided on parental characteristics which might explain the different results. When evaluating our results it is crucial to consider the fact that our predictors are sequential in the sense of providing a longitudinal perspective. Thus, as opposed to many other studies that looked at socio-demographic and perinatal predictors, our study too included developmental measurements at the cease of the second year of life. Our final model shows the direct effect of the selected variables on IQ at four years and non whatever indirect impact mediated by fators during the first ii years of life. This might explain why perinatal factors that showed significant correlation with the effect in bivariate analysis did non remain in the final model. It is notable that birth weight was not a pregnant predictor in any of our models.

Maternal education and family unit wealth have been shown to exist substantial predictors of later IQ amid healthy children (4–6). Our study, similarly to others, identified this relationship not only amid healthy children but also in low birth weight children. Regarding maternal education, a college or university caste proved to be a positive factor for the kid'due south IQ, while beneath-average subjective family wealth was an important negative predictor for intelligence at historic period four. The neonatal diagnosis of bronchopulmonary dysplasia was a risk gene for the outcome in our study, consequent with the finding of other groups [xx, 21].

Exploring the underlying causes for delayed intelligence among LBW children with chronic lung disease, it must be noted that preterm birth itself disturbs corticogenesis in the encephalon [22] with later consequences in the grade of behavioral and emotional problems which are compounded if clinical atmospheric condition including bronchopulmonary dysplasia are also present in the neonates [23]. Newer research specifically showed that preterm infants with BPD had smaller cerebral white matter volumes and dumb cerebellar development compared to preemies with no BPD [24].

Our findings regarding association between demographic factors of the family and the kid'due south IQ are in alignment with previous enquiry [4, 5, 25]. Children of highly educated parents tend to accept better outcomes along several dimensions of life, such every bit noesis, instruction, and health [26, 27]. The underlying reasons for this association are manifold: higher educated parents are more knowledgeable, accept better job opportunities, generate college income, take better living weather which all contribute to them being able to provide more than nurturing environments and better educational opportunities for their children [27, 28] equally opposed to families with depression income [29]. Parental college education is as well linked to greater knowledge virtually parenting behaviours, educational and wellness-promoting factors as well [30]. Our results ostend previous findings regarding the significant positive association between paternal income, family wealth, and the kid's working memory and cerebral proficiency [31, 32].

The field of research in early on babyhood development has seen a not bad expansion of knowledge in the by 30 years. Increasing attention is existence directed to the importance of the early years of babyhood, from the Carnegie Report of 1994 in the USA [33] to the seminal publication of the World Wellness Organisation [34], and the establishment in 2006 of the Center on the Developing Child at Harvard Academy [35]. More and more than national and international bodies recognize the vital importance of early childhood, peculiarly the first three years, in the creation of healthy adults. However, children cannot live and cannot be helped without parents or caretakers. Our study, along with many others, points to the primal importance of the quality of the family environment and maternal education as major predictors of the cognitive evolution of the child. We did not detect depression nascency weight to be the predictor of 4-yr intelligence which raises the possibility that LBW may non be a mediator of later intelligence of which the socioeconomic condition of the family is determinant, just equally LBW is not a mediator between higher socioeconomic level of the family and decreased infant mortality [36].

Interactions between biological (e.g. genetics or heredity; in this case BPD due to prematurity as biological vulnerability) and ecology (eastward.g. micro- and macro-environment; such as parental instruction or poverty) factors lead to loftier variability in developmental outcomes. Tucker-Drob, Briley & Harden (2013) [ highlight that "genetic influences on noesis are maximized by environmental opportunity" [37]. The chore of researchers is to uncover the determinants of child evolution and identify constructive ways to ameliorate developmental processes. Withal, planning and implementing interventions by which all families tin can meliorate the conditions in which they raise their children is a task for policy makers. A recent publication of the World Health Organization provides guidelines for improving early childhood evolution based on a review of scientific evidence [38]. Interventions teaching responsive caregiving to parents improve early kid outcomes, amongst others cerebral development measured by the same tool which we used (Bayley Scale of Infant Development), and language and motor development. In Hungary, early babyhood development has been helped in a number of ways. An extensive system of maternal benefits enables mothers to care for their children while on paid exit up to the child'southward 3 years of age. Kindergarten education became mandatory from age 3 in 2015 (earlier that, mandatory age was 5 years). Comeback of parental caregiving is one of the goals of a nationwide government-funded initiative launched in 2004 which was modelled on the Certain Start Programme of the Uk. Notwithstanding, this Programme has less professionals than information technology would demand particularly in geographical areas in which the proportion of vulnerable populations in low socio-economic strata tend to exist high [39].

I of our findings is neonatal bronchopulmonary dysplasia as a significant predictor of the developmental and cognitive performance of the kid in later years. The incidence of BPD increases with decreasing gestational age and decreasing birth weight. BPD is the virtually prevalent complication of prematury amid infants built-in before 28 weeks of gestational historic period ranging between xi–50%, and this constitutes the major cause of mortality [forty]. BPD presents a medical challenge for which a number of treatment modalities have been tried with limited success [41]. The public health approach to decrease BPD is to increment gestational historic period and decrease low birth weight as detailed in a policy cursory of the Globe Health Arrangement [42].

Our findings bear witness that developmental assessment at two years of age is crucially important to recognize delays and arbitrate to preclude farther delays in later cerebral functioning, a risk factor for learning difficulties. Our information help prioritize those children who should be regularly monitored and supported in their cognitive development: those with mothers having less than college educational activity, those in families with below-average subjective wealth, and those with BPD with our without the previous two gamble factors. Improving the skills of caregiving persons and the quality of the caregiving surround for all infants but especially for those of depression birth weight by effective interventions not only reduces inequalities and is the humane thing to practise but information technology is too cost-effective from a societal indicate of view [43].

Availability of data and materials

Additional data are bachelor from the corresponding author on reasonable asking.

Abbreviations

BPD:

Bronchopulmonary Dysplasia

BSID:

Bayley Scales of Infant and Toddler Development

ELBW:

Extremely Depression Birthweight

FSIQ:

Full Scale IQ

IQ:

Intelligence Quotient

IVH:

Intraventricular Haemorrhage

LBW:

Depression Birthweight

ROP:

Retinopathy of Prematurity

VLBW:

Very Low Birthweight

WHO:

World Health Organization

WPPSI:

Wechsler Preschool Main Scales of Intelligence

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Acknowledgements

We would like to give thanks all the children and mothers for their cooperation in data collection. We are grateful to prof. György Balla, prof. Gábor Veres, and prof. Tamás Szabó for authorizing our enquiry.

Statement on dual publication

The descriptive statistics of the sample and the 4-year IQ results have been published but the analysis and modelling presented in this manuscript has neither been published nor submitted elsewhere.

Funding

Flóra Kenyhercz and Karolina Kósa were supported by the GINOP-2.3.2–fifteen-2016–00005 project during the training and writing of the manuscript.

Author data

Affiliations

  1. Faculty of Medicine, Section of Behavioural Sciences, Academy of Debrecen, Debrecen, Hungary

    Flóra Kenyhercz & Karolina Kósa

  2. Faculty of Medicine, Department of PediatricsPediatric Psychology and Psychosomatic Unit, University of Debrecen, Debrecen, Hungary

    Beáta Erika Nagy

Contributions

FK contributed to written report blueprint, carried out all assessments and information collection, analysed the information, and drafted the manuscript. KK performed the modeling, edited and approved the final version of the manuscript. BEN initiated the research, designed the report, provided supervision to FK, and approved the final version of the manuscript. The writer(s) read and approved the concluding manuscript.

Corresponding writer

Correspondence to Flóra Kenyhercz.

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Ideals blessing and consent to participate

The study received permission from the Hungarian Medical Research Council (33,176–2/2017/EKU) following the upstanding principles of the WMA Declaration of Helsinki. Written informed consent was obtained from all parent(s)/ legal guardians.

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All authors canonical the final version of the manuscript and consented for publication.

Competing interests

Authors have no competing interests.

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Kenyhercz, F., Kósa, Chiliad. & Nagy, B.Eastward. Perinatal, neonatal, developmental and demographic predictors of intelligence at 4 years of age among low birth weight children: a panel report with a 2-year follow-up. BMC Pediatr 22, 88 (2022). https://doi.org/10.1186/s12887-022-03156-x

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Keywords

  • Babe
  • Depression birth weight
  • Neonatal Prematurity
  • Intelligence
  • Growth & Development
  • Bronchopulmonary dysplasia

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