Early childhood

New Insights Into Early Childhood Language Learning

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Summary: A new study explores how infants and toddlers acquire language. The research challenges preconceived notions about language development, particularly in low-income families, by analyzing daylong audio recordings of 1,001 children from diverse backgrounds.

Findings reveal early comprehension begins around 6-7 months, and significant improvements in language understanding occur around a child’s first birthday. The work aims to broaden the scope of language development research to include more diverse populations and to understand the mechanisms of language acquisition in children, including those who are deaf or blind.

Key Facts:

  1. Bergelson’s research refutes the assumption that socio-economic status significantly impacts a child’s language development.
  2. Early language comprehension in babies begins as young as 6 months, with a notable improvement around the first birthday.
  3. The study utilizes machine learning to analyze audio recordings from 1,001 children across 12 countries and 43 languages, providing a diverse and comprehensive dataset.

Source: Harvard

Growing up amid a swirl of Russian, Hebrew, and English fed Elika Bergelson’s passion for language development.

Her parents had emigrated in the 1970s from the Soviet Union to Israel, where they began their family. Bergelson and her youngest sibling were born in the 1980s after the family settled in Columbus, Ohio. Even back then, she noticed generational differences around grammar, accents, and vocabularies that left her asking how the kids had outpaced the adults.

“What is it about language acquisition that makes younger minds — which are usually less good at everything — actually better at this particular process?” she remembered wondering.

This shows a child and a book.
It’s as though children around age 1 go from just barely grasping the mechanics of language to suddenly becoming true communicative partners.

Today, the newly appointed associate professor of psychology studies how infants and toddlers learn language from the world around them. The developmental psychologist specifically strives to parse the various theories that account for the onset and eventual mastery of language comprehension and production.

Bergelson’s latest paper, published last month in the Proceedings of the National Academy of Sciences, takes a global approach to developing and testing such theories, with the results refuting common critiques of low-income parents and caregivers. 

“Our results question some of the received wisdom, certainly in the American policy space, that families in certain socioeconomic circumstances are providing less or less ‘good’ language input to their kids,” she said. 

As a language scientist, Bergelson has a history of generating such myth-busting insights. Her first experiments on early word-learning, performed 15 years ago when she was a graduate student at the University of Pennsylvania, revealed that comprehension begins at a far younger age than previously thought. “Around 6 or 7 months, babies are starting to understand some really common nouns,” she said. 

Scientists have long acknowledged the burst of word production that occurs around age 18 months, Bergelson explained. In follow-up studies, she and her colleagues found a similar qualitative improvement in language comprehension near a child’s first birthday, around the time the first bona fide words arrive. It’s as though children around age 1 go from just barely grasping the mechanics of language to suddenly becoming true communicative partners.

Could this be because parents talked more or differently to older babies? Bergelson investigated this theory as a postdoc and research professor at the University of Rochester, where she led the creation of a large naturalistic data set that tracked babies from 6 to 18 months old with audio and video recordings, eye tracking, and more.

“It doesn’t seem like there’s something fundamentally different in how parents or caretakers interact with 6- versus 12-month-olds,” she concluded. 

With a grant from the National Institute of Health, Bergelson’s new Harvard lab recently embarked on a project designed to test what she calls the “better learner models” of language acquisition. The comprehension tipping point is ascribed by these theories to the baby’s growing social, cognitive, or linguistic abilities, rather than just their accumulation of more input from caretakers. 

But what, exactly, are the skills that support word learning? Bergelson and her colleagues plan to test comprehension indicators that appear sooner than talking itself, such as pointing or looking in the direction of a mentioned object. This research holds the long-term potential of improving early interventions for children who struggle with language acquisition.

Bergelson has the additional goal of growing the pool of children whom language scientists study. “One really important shift in the field recently has been a much more serious reckoning with the fact that we tend to study white, middle-class Americans,” she said. 

Her recent PNAS paper, written with senior co-author Alejandrina Cristia at France’s École Normale Supérieure, PSL University, is based on a large sample of 2- to 48-month-olds. Daylong audio recordings captured the babbling and baby talk of 1,001 children representing 12 countries and 43 languages. Financial support for this work was provided by the National Science Foundation, National Institutes of Health, and the National Endowment for the Humanities, among others.

Analyzing the recordings was completed with the help of machine learning. Bergelson called it a “coarse-grained” approach to studying the topic. “It’s the algorithm’s estimate of how much speech the kid is hearing or producing,” she said. “But I think it’s a complementary approach to what otherwise is very, very time-consuming and sample-limiting work.”

The results show that the main predictors of language development globally are age, clinical factors such as prematurity or dyslexia, and how much speech children receive from the world around them. In contrast to previous research, no effects were found related to gender, multilingualism, or socioeconomic.

“There’s been much debate and discussion in the literature in recent years about how socioeconomic status does or doesn’t link to language input and language output,” noted Bergelson, who is immersed personally in early development baby babble, having given birth to her second child last year.

“We looked in many, many, many different ways … In no form did we ever find evidence that moms with more education had kids who produced more speech in these tens of thousands of hours of recordings from daily life.”

With a grant from the National Science Foundation, Bergelson is also pursuing new research on language development in children who are deaf or blind. The case of blindness is especially interesting, she noted. 

“Blind adults’ language skills are largely indistinguishable from sighted folks’,” she said. “But a lot of our theories about early language learning rely on children seeing others to refer to things in the world. So there’s a mystery — how does that happen? And what does that tell us about how language develops for everybody?”

Abstract

Everyday language input and production in 1,001 children from six continents

Language is a universal human ability, acquired readily by young children, who otherwise struggle with many basics of survival. And yet, language ability is variable across individuals. Naturalistic and experimental observations suggest that children’s linguistic skills vary with factors like socioeconomic status and children’s gender. But which factors really influence children’s day-to-day language use?

Here, we leverage speech technology in a big-data approach to report on a unique cross-cultural and diverse data set: >2,500 d-long, child-centered audio-recordings of 1,001 2- to 48-mo-olds from 12 countries spanning six continents across urban, farmer-forager, and subsistence-farming contexts. As expected, age and language-relevant clinical risks and diagnoses predicted how much speech (and speech-like vocalization) children produced.

Critically, so too did adult talk in children’s environments: Children who heard more talk from adults produced more speech. In contrast to previous conclusions based on more limited sampling methods and a different set of language proxies, socioeconomic status (operationalized as maternal education) was not significantly associated with children’s productions over the first 4 y of life, and neither were gender or multilingualism.

These findings from large-scale naturalistic data advance our understanding of which factors are robust predictors of variability in the speech behaviors of young learners in a wide range of everyday contexts.

Early childhood fish consumption shields against neurodevelopmental delays

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In today’s digital age, conversations surrounding neurodevelopment, particularly neurodivergence, have become increasingly prevalent.  This growing discourse challenges the conventional understanding that all brains develop along a standardized trajectory.  Rather, the spectrum of neurodevelopment is richly varied, with each individual’s journey shaped by a myriad of factors, including genetics, environment, and, most notably, diet.

A recent in-depth study conducted by the Penn State College of Medicine and prominently featured in the journal Microorganisms delves into the profound impact of early childhood nutrition on neurodevelopmental outcomes.  The research sheds light on a compelling hypothesis: specific dietary choices during formative years may either bolster or hinder cognitive growth, potentially influencing an individual’s learning pace and overall neurological health.

This revelation prompts a critical reevaluation of our approach to early nutrition.  Could there be a direct correlation between certain dietary patterns and the incidence of neurodevelopmental delays?

Dietary choices in childhood influence brain development

Scientists insist neurodevelopment is one part nature and one part nurture.  Though one cannot change his or her genetics, neurodevelopment is affected by environmental variables.  Nutrition is especially important for neurodevelopment.

The longitudinal cohort study linked above included 142 infants.  The study tested the hypothesis that microbial activity changes the impact of nutrition on a growing toddler’s brain.  The scientists measured salivary microbiome activity to determine how it modulates the impact of nutrition on brain development.

The Penn State scientists used RNA sequencing to measure salivary microbiome actions at the 6-month mark.  The nutritional intake of babies was analyzed longitudinally (an assessment of variables across a period of time) using a survey that gathered information about infant feeding.

How fish consumption early on shapes neurodevelopment

The study emphasizes the profound impact of early-life dietary choices, particularly the benefits of fish consumption, on brain development.  The research underscores a consistent link between fish intake and reduced neurodevelopmental delays, even when considering social and environmental factors.

Terrah Keck-Kester, an assistant professor of pediatrics at Penn State, emphasized that alongside genetic factors, environmental and social elements, such as dietary habits like consuming fish, can significantly impact neurodevelopmental outcomes.

Further insights from Penn State researchers revealed the importance of microbial diversity in enhancing the benefits of fish consumption on brain growth.  Intriguingly, even early indicators like salivary microbe activity at six months could predict neurodevelopmental trajectories.

In essence, the study affirms that early introduction and consistent inclusion of fish in a toddler’s diet may offer protective benefits against neurodevelopmental delays, with the child’s microbiome playing a supportive role.

Creative ways to introduce fish to your baby

Navigating the world of baby food introduces a blend of excitement and responsibility for parents.  As you seek to offer nutritious and delicious options, fish emerges as a powerhouse ingredient.  However, introducing it to your baby’s diet requires thoughtful preparation and creative approaches to ensure a smooth transition.

Here are some inventive ways to incorporate this food into your little one’s meals, making it an enjoyable culinary journey for both parent and baby.

Fish puree:  Steam mild fish like cod and blend with breast milk or formula for a smooth introduction.

Homemade fish sticks:  Coat soft strips in breadcrumbs and bake until golden for a tasty finger food.

Fish cakes:  Combine wild fish with organic mashed potatoes and veggies into small patties, then lightly cook.

Fish-veggie blend:  Mix steamed fish with soft-cooked vegetables for a nutrient-packed puree.

Always choose wild-caught fish and ensure it’s well-cooked and deboned.  Naturally, even if your child does not like fish, you should consider other healthy fat options to help feed the neurological system what’s needed.  Bottom line: don’t avoid healthy fats if you want a healthy nervous system.

Acute respiratory failure in early childhood may affect long-term neurocognitive outcomes

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In a new study, survival of ICU hospitalization for acute respiratory failure and discharge without severe cognitive dysfunction in early childhood was associated with significantly lower subsequent IQ scores compared with matched siblings.

“Outcomes of adults with respiratory failure are affected by adult-onset comorbidities and age-related frailty and diminished cognitive capacity,” R. Scott Watson, MD, MPH, professor in the department of pediatrics at the University of Washington and the Center for Child Health, Behavior and Development at Seattle Children’s Research Institute, and colleagues wrote in JAMA. “In contrast, little data exist regarding long-term neurocognitive outcomes after respiratory failure in infants and children without prenatal problems or identified cognitive dysfunction.”

brain
Source: Adobe Stock.

The researchers conducted a prospective cohort study that enrolled 121 sibling pairs from September 2014 to December 2017 from 31 U.S. pediatric ICUs (PICU) and associated neuropsychology testing centers. All pairs underwent neurocognitive testing beginning March 2015 with final follow-up in November 2018.

Patients with acute respiratory failure were aged 8 years or younger with a Pediatric Cerebral Performance Category score of 1, indicating normal neurocognitive function, before PICU admission and a score of 3 or less after discharge, indicating no worse than moderate neurocognitive dysfunction. The study excluded children with a history of neurocognitive deficits and those who required readmission and mechanical ventilation. Siblings were aged 4 to 16 years with a Pediatric Cerebral Performance Category score of 1 without a history of mechanical ventilation or general anesthesia.

The primary outcome was IQ score, which was estimated by age-appropriate Vocabulary and Block Design subtests of the Wechsler Intelligence Scale. Secondary outcomes were measures of attention, processing speed, learning, memory, visuospatial and motor skills, language and executive function.

Patients with acute respiratory failure underwent PICU care at a median age of 1 year (45% female). These children received a median of 5.5 days of invasive mechanical ventilation.

The children with acute respiratory failure were tested at a median age of 6.6 years and matched siblings were tested at a median age of 8.4 years.

Compared with matched siblings, children with acute respiratory failure had a lower mean estimated IQ score (104.3 vs. 101.5).

“The magnitude of the difference was small and of uncertain clinical importance,” the researchers wrote.

Children with acute respiratory failure also had significantly lower scores on nonverbal memory (mean difference, –0.9), visuospatial skills (mean difference, –0.9) and fine motor control (mean difference, –3.1) with significantly higher scores for processing speed (mean difference, 4.4) compared with matched siblings.

Researchers observed no significant differences in the remaining secondary outcomes.

“The much greater rates of patients with estimated IQs less than or equal to 85 and of estimated IQ at least 15 points below their siblings demonstrates an overall downward shift in estimated IQ among patients,” the researchers wrote. “These findings may have important academic, social and economic implications for young children surviving acute respiratory failure and are consistent with a 2020 study that found school problems among 13% of all pediatric ICU survivors in Finland.”

Breastfeeding, Cognitive and Noncognitive Development in Early Childhood: A Population Study

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Abstract

BACKGROUND AND OBJECTIVES: There is mixed evidence from correlational studies that breastfeeding impacts children’s development. Propensity score matching with large samples can be an effective tool to remove potential bias from observed confounders in correlational studies. The aim of this study was to investigate the impact of breastfeeding on children’s cognitive and noncognitive development at 3 and 5 years of age.

METHODS: Participants included ∼8000 families from the Growing Up in Ireland longitudinal infant cohort, who were identified from the Child Benefit Register and randomly selected to participate. Parent and teacher reports and standardized assessments were used to collect information on children’s problem behaviors, expressive vocabulary, and cognitive abilities at age 3 and 5 years. Breastfeeding information was collected via maternal report. Propensity score matching was used to compare the average treatment effects on those who were breastfed.

RESULTS: Before matching, breastfeeding was associated with better development on almost every outcome. After matching and adjustment for multiple testing, only 1 of the 13 outcomes remained statistically significant: children’s hyperactivity (difference score, –0.84; 95% confidence interval, –1.33 to –0.35) at age 3 years for children who were breastfed for at least 6 months. No statistically significant differences were observed postmatching on any outcome at age 5 years.

CONCLUSIONS: Although 1 positive benefit of breastfeeding was found by using propensity score matching, the effect size was modest in practical terms. No support was found for statistically significant gains at age 5 years, suggesting that the earlier observed benefit from breastfeeding may not be maintained once children enter school.

 

  • Abbreviations:
    DHA —
    docosahexaenoic
    PSM —
    propensity score matching
    SDQ —
    strengths and difficulties questionnaire
    SEM —
    structural equation modeling

 

What’s Known on This Subject:

The medical benefits of breastfeeding for mother and child are considered numerous, yet the effect of breastfeeding on cognitive abilities remains largely debated given selection into breastfeeding. The effect on behavior is even less well understood.

What This Study Adds:

In applying quasi-experimental techniques which mimic random assignment, this study supports limited positive impacts of breastfeeding for children’s cognitive and noncognitive development. Although significant, the effect of breastfeeding on noncognitive development is small in practical terms.

The medical benefits of breastfeeding for both mother and child are considered numerous and well documented.1–5 Yet the effect of breastfeeding on general cognitive abilities has been a topic of debate for nearly a century.6 The mechanism argued to be responsible for these effects is the nutrients found in breast milk.7,8 Two specific types of long-chain polyunsaturated fatty acids, namely docosahexaenoic (DHA) and arachidonic acid, have been implicated in both visual and neural development and functioning through neural maturation, which is important for cognitive abilities, such as problem solving.9–11

The link with nutrients may also impact specific cognitive abilities like language development. For example, language abilities, such as vocabulary, are highly dependent on working and long-term memory given the consolidation and retrieval processes needed during acquisition.12,13 In rats, deficiency of fatty acids, such as DHA, during lactation resulted in poor memory retention during learning tasks, whereas supplementation of DHA had reversal effects.14 If the hypothesized “causal” mechanism of superior nutrition in breast milk is true, coupled with the specific impact of DHA on memory, breastfeeding should also impact language abilities. To date, ∼20 studies have investigated this association and all but 115 examined a combined measure of language (receptive and expressive) or receptive language only. There remains debate as to whether expressive and receptive language in early childhood form distinct modalities of language,16,17 raising the question of whether breastfeeding would be equally beneficial to each modality in the case of a 2-factor language model.

Less studied is the impact of breastfeeding on behavior. Breastfeeding may lead to reduced behavioral problems as a result of early skin-to-skin contact, which helps form a secure mother-infant bond.18 Any effects of breastfeeding on cognitive and language development could also prevent the development of behavior problems. The absence of early behavior problems has social, economic, and medical value to society through reduced prevalence of delinquency, incarceration rates, and substance abuse,19–21 making this an important area of research. With few exceptions, there remains a dearth of high-quality studies examining behavior,22–25 and among them, consensus is not evident.

Without randomization of mothers to breastfeeding and formula conditions, it is challenging to confirm the causal impact of these hypotheses. One study randomized the provision of a breastfeeding intervention, modeled on the Baby-Friendly Hospital Initiative, and found that the children of mothers in the intervention group had higher intelligence scores compared with controls at age 6 years.26 The strongest effects were for verbal intelligence. This study offers the best support to date for a causal link between breastfeeding and cognitive development. However, it is the only cluster randomized trial on human lactation.

The majority of studies in this field are observational, thus the causal implications of breastfeeding are questionable given the inherent difficulty in controlling for selection into breastfeeding. For example, initial associations with cognitive development are often reduced after adjustments for confounders, such as parental education/IQ (ie, from an average 5-point to 3-point difference27), and, in some cases, the associations are no longer statistically significant.28 A variety of observational studies now apply quasi-experimental methods to better address the issue of selection bias, making inroads toward a better understanding of potential causal paths. The techniques used include propensity score matching (PSM), instrument variables, and sibling pair models. This study uses PSM because the sibling pair model limits the available pool of participants and instrument variables are extremely sensitive to the validity of the chosen instrumentation, which should be associated with the exposure but not with the outcome except for via the exposure.

Using a large longitudinal population sample, we applied PSM, which mimics random assignment, in an effort to investigate the potential impacts of breastfeeding on children’s cognitive ability, expressive vocabulary, and behavior problems. Both breastfeeding duration and intensity were examined. Significant advantages for children who were breastfed, after matching, were expected for all outcomes. Grounded in the recommendations of the World Health Organization,29 it was expected that larger effect sizes would be observed for children who were fully breastfed and for longer durations.

Methods

Participants

Participants included families enrolled in the Growing Up in Ireland infant cohort. Families with infants born between December 2007 and May 2008 were identified from the Child Benefit Register and randomly selected to participate. The overall recruitment response rate was 65% (N = 11 134). A detailed description of the study design can be found elsewhere.30 We used data collected at 9 months and 3 and 5 years of age. Only families with complete data for all confounders when children were 9 months and children who were born full term were included (N = 9854; 88.5% of the initial sample). Boys represented 50.6% (N = 4991) of the sample. Attrition across waves reduced the sample size to 8715 children at 3 years and 8032 at 5 years. Some children had missing data on the cognitive and vocabulary scales, resulting in 8535 and 8241 children respectively at age 3 and 7972 and 7942 children respectively at age 5. Additionally, missing teacher reports for behavior at age 5 years resulted in 7478 children being included in these analyses. Demographic characteristics of the families and rates of breastfeeding engagement can be found in Table 1 and Fig 1. Ethics approval was obtained from the Research Ethics Committee, Department of Children and Youth Affairs Ireland, and written consent was collected from parents/guardians before data collection.

TABLE 1

Family, Maternal, Infant, and Medical Characteristics: Infant Cohort at 9 Months

The category “1” on the x-axis represents breastfeeding up to 31 days; “2” represents between 32 and 180 days; and “3” represents ≥181 days.

“>FIGURE 1

FIGURE 1

The category “1” on the x-axis represents breastfeeding up to 31 days; “2” represents between 32 and 180 days; and “3” represents ≥181 days.

Measures

Children’s cognitive abilities and expressive vocabulary were measured by using 2 scales from the British Abilities Scale31. The pictures similarities scale assessed problem-solving skills and the naming vocabulary scale assessed expressive vocabulary. The construct validity of each scale was derived by using the Wechsler Preschool and Primary Scale of Intelligence-Revised (r = 0.74 and 0.83, respectively).31 Standardized scores that adjusted for performance as compared with other children of the same age, with a mean of 50 and a SD of 10, were used. Age was adjusted in 3-month age bands.

The Strengths and Difficulties Questionnaire (SDQ32) was used to assess children’s problem behaviors. The parent version was used at age 3 years and both the parent and teacher versions were used at age 5 years. The SDQ is comprised of 5 scales (emotional symptoms, conduct problems, hyperactivity/inattention, peer relationship problems, and prosocial behavior) with ratings of applicability of behaviors on a 3-point scale. A total difficulties scale is included, combining the 4 problem scales, to yield an overall difficulties score. We used the conduct problems, hyperactivity/inattention, and difficulties scales given our focus on externalizing problems. Validation of the SDQ has been extensively documented.33Table 2 reports the correlations between parent and teacher SDQ reports and the means and SDs for all child outcomes.

Breastfeeding information was collected retrospectively when infants were 9 months old via maternal report. Support for the reliability of recall in previous breastfeeding studies has been established.34 However, given the lower reliability regarding the timing of the introduction of additional fluids/solids, Labbok and Krasovec’s definition of full (ie, exclusive or almost exclusive) and partial breastfeeding are used.35 Two breastfeeding variables were created to assess whether the infant was fully or partially breastfed and the duration of each. Mothers were asked 4 questions: “Was <baby> ever breastfed,” “How old was <baby> when he/she completely stopped being breastfed,” “Was <baby> ever exclusively breastfed,” and “How old was <baby> when he/she completely stopped being exclusively breastfed?” First, infants were grouped by breastfeeding status, both full and partial (5940) and never breastfed (3914). Of those who had ever been breastfed, 4795 had full breastfeeding at some point. Next, breastfeeding duration was grouped into 3 intervals; breastfed up to 31 days, 32 to 180 days, and ≥181 days. Each category of duration was treated as mutually exclusive, dummy coded, and compared against infants who had never been breastfed for the purpose of matching.

Confounders have been suggested in part to account for the associations found between breastfeeding and child outcomes. We matched groups (breastfed, never breastfed) on 14 of the most pertinent factors. At the child level, factors included sex (boy/girl), birth weight (≥2500 g), and having neonatal intensive care (yes/no). At the maternal level, factors included age (≤24 years, 25–29 years, 30–34 years, or ≥35 years), highest level of education (primary level/no education, second level, or third level), working status before pregnancy (yes/no), ethnicity (Irish, any other white background, African or any other black background, Asian background, or other, including mixed background), depression (a score of ≥11 on the Center for Epidemiologic Studies Depression Scale), and type of delivery (vaginal or caesarean). Family-level factors included having a partner in the residence (yes/no), social class (professional/managerial, other nonmanual/skilled manual, or semiskilled/unskilled), medical card status (free medical care, free general practitioner care, or no free medical care), total number of household members who smoked during the pregnancy (none, or ≥1), and whether the cohort infant had siblings living in the household.

Statistical Analysis

PSM reduces selection bias by matching children who were breastfed to children who were not, but who had a similar probability of being breastfed based on their measured characteristics. We used PSM logit models with nearest neighbor 1:1 matching techniques. In nearest neighbor matching, the sample is randomly ordered with matching occurring sequentially between the treatment (breastfed) and control (not breastfed) group based on participants’ propensity scores. Typically, the pair is then removed from the list and the next match is created. To ensure optimal matches, we imposed a caliper so that pairs could only be matched if the propensity score was within a tenth of a SD of the other. We also allowed matching with replacement given the low rates of longer durations and full breastfeeding in this cohort. Although matching with replacement has been argued to increase variance in the data, it also arguably reduces bias in the sample by ensuring better quality of matches.36 Balance checks in all models revealed substantial reductions of bias between matched groups on all individual confounders (ie, 0%–13.9% remaining bias in partial breastfeeding models, 0%–18.1% remaining bias in full models; data available on request). The remaining overall mean bias across models ranged from 3.2% to 8.5%. The ≤20% remaining bias has been suggested as the acceptable cutoff after matching.37 Thus, we concluded that the analytic matching technique resulted in good matches between conditions. Matching resulted in all participants falling within the area of common support. The average treatment effect on those who were treated (ie, children who were breastfed) is reported. Adjustments were made for multiple hypothesis testing by using the Holmes-Bonferroni method. All statistical analyses for PSM were conducted by using Stata version 13 software (Stata Corp, College Station, TX).

To note, although PSM is advantageous in mimicking random assignment, a drawback is the challenge in evaluating a linear dose-response association, which has previously been found. Structural equation modeling (SEM) offers an alternative approach to examining this dose-response association. Additionally, SEM uses the full sample and has greater power. Thus, the data were also modeled by using SEM, where confounders were treated as correlated exogenous variables, the duration of breastfeeding was treated as a continuous mediating variable, and child outcomes were treated as correlated, which could be influenced by both breastfeeding and confounders. These results can be found in the Supplemental Material.

Results

Postmatching results for children fully breastfed up to 31 days revealed no statistically significant differences between groups on any outcome at age 3 or 5 years (Table 3). Similarly, for children who were fully breastfed between 32 and 180 days, no statistically significant differences were found for any outcomes at either age postmatching (Table 4). Finally, for children who were fully breastfed for ≥6, statistically significant differences were found postmatching for only 2 outcomes, problem solving and hyperactivity at age 3 years. Children who were fully breastfed scored 2.95 (SE = 1.39, P = .048) points higher on the problem-solving scale compared with children who were never breastfed and –0.84 (SE = 0.25, P ≤ .001) points lower on the hyperactivity scale. After adjustment for multiple testing, cognition was no longer statistically significant. However, children who were fully breastfed had slightly lower parent-rated hyperactivity compared with controls, and this remained statistically significant after adjustment (Table 5). Of note, results of the partial breastfeeding models were similar to the full models, however, after adjustment for multiple testing, neither cognitive ability nor hyperactivity at age 3 years remained statistically significant. These results can be found in the Supplemental Material.

Discussion

Without randomized controlled trials, the issue of causality will necessarily remain open, however the present results contribute important insights to the long-standing debate of potential “causal effects” versus artifacts of confounding that are not properly accounted for. This study also provides new perspectives on breastfeeding and children’s externalizing behavior. To the best of our knowledge, this is among the first studies to examine expressive vocabulary as an individual outcome and to consider externalizing behavior. It should be noted that our results apply only to infants born full term.

After adjustment for multiple testing, the initial support found for breastfeeding and better problem solving at age 3 years if the child was breastfed for a minimum of 6 months was no longer statistically significant. In addition, no statistically significant effects were found for cognitive ability at age 5 years. These results are in contrast to some studies that have used PSM techniques to examine the effects of breastfeeding and general cognitive abilities.38–40However, differences in both analytical choices of the PSM approach used (eg, replacement, calipers) and differing selection of covariates may help to explain these differences across studies. Nonetheless, our findings were surprising in the context of the nutrients in breast milk being responsible for increased cognitive development. Regarding expressive vocabulary, no statistically significant advantages were observed for children who were breastfed at either age 3 or age 5.

The limited research on breastfeeding and behavior problems is inconsistent, despite the relatively consistent reliance on the SDQ. Of interest, studies that have dichotomized the SDQ scales into abnormal scores (ie, at the 85th or 90th percentile) have not found statistically significant differences,23–25 suggesting that breastfeeding is not likely to be a contributor to behavioral problems at clinical levels. When the SDQ scales are treated as continuous, small effects under certain conditions have been found.22 In this study, we treated all 3 scales as continuous and found that children who were fully breastfed for ≥6 months had lower parent-rated scores on the hyperactivity scale at age 3 years only. This result remained statistically significant after adjustment for multiple testing. Our results suggest that longer durations of breastfeeding might help to reduce hyperactive behaviors for children who display mild to moderate levels in the short term, but that these benefits are not maintained even in the medium term. This result would seemingly support the recommendation of the World Health Organization, suggesting that breastfeeding for at least 6 months is necessary for early gains to be observed.

The inherent strengths of this study include the use of a particularly large longitudinal developmental dataset, the use of a quasi-experimental statistical approach, the use of a repeated measures design, the use of multiple informants and simultaneous standardized assessments thereby limiting potential shared method variance, the comparatively large number of confounders controlled (ie, 14) in contrast to previous studies (ie, an average of 7.7 ± 3.4 in higher-quality studies28;), and assessments in both cognitive and noncognitive domains of child development. Despite these strengths, some limitations must be noted. First, information on breastfeeding was collected retrospectively. Although the reliability of recall has been established,34 it must be acknowledged that recall bias may nevertheless be present, particularly regarding the duration of full breastfeeding. Second, only parent-reported SDQs were collected when children were 3 years of age. Studies have found that parents typically rate their children as having higher levels of problem behaviors as compared with teacher reports, with weak associations between these 2 types of informants,24 as was found in the current study for behavior ratings at age 5 years between parents and teachers. Having access to child care staff reports at age 3 years would have increased the reliability of the maternal-rated hyperactivity finding. Third, no information pertaining to direct breastfeeding versus expressed breast milk feeding was collected. Thus, it is not possible to investigate whether the association with reduced hyperactivity at age 3 years was the result of skin-to-skin contact or due to the nutrients in breast milk. This is an important direction for future studies examining behavioral outcomes. Fourth, although maternal education was included as a confounder, maternal IQ was not collected in this cohort. In the few studies that controlled for maternal IQ, the findings suggested that it accounted for a large part of the association between breastfeeding and cognitive outcomes.39,41 Thus, the inclusion of maternal IQ in future studies that employ PSM is warranted. Finally, PSM does not address selection on unobservables. Causal estimates may only be estimated by using PSM if selection is on observable characteristics or, in cases where unobservable factors influence selection into breastfeeding, the balancing on observables also balances on these unobservables. Despite these limitations, the results of this study add to the growing literature by showing that some statistically significant positive noncognitive benefits may result from longer durations of breastfeeding. Yet, beyond the statistical implications, the practical implications appear minimal and short lived. It is important to note, however, that these findings do not contradict the many medical benefits afforded to both mother and child as a result of breastfeeding.

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    Source:The American Academy of Pediatrics
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