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Background:
Systematic Review

Perinatal and Childhood Risk Factors of Adverse Early Childhood Developmental Outcomes: A Systematic Review Using a Socioecological Model

by
Kendalem Asmare Atalell
1,2,*,
Gavin Pereira
1,3,
Bereket Duko
1,4,
Sylvester Dodzi Nyadanu
1,5 and
Gizachew A. Tessema
1,3,6
1
Curtin School of Population Health, Curtin University, Perth, WA 6102, Australia
2
College of Medicine and Health Sciences, University of Gondar, Gondar 196, Ethiopia
3
enAble Institute, Curtin University, Kent Street, Bentley, Perth, WA 6102, Australia
4
Research Centre for Public Health, Equity and Human Flourishing (PHEHF), Torrens University Australia, Adelaide, SA 5000, Australia
5
Healthy Environments and Lives (HEAL) National Research Network, Canberra, ACT 2617, Australia
6
School of Public Health, University of Adelaide, Adelaide, SA 5005, Australia
*
Author to whom correspondence should be addressed.
Children 2025, 12(8), 1096; https://doi.org/10.3390/children12081096
Submission received: 25 June 2025 / Revised: 1 August 2025 / Accepted: 2 August 2025 / Published: 20 August 2025
(This article belongs to the Section Pediatric Mental Health)
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Abstract

Background: Adverse early childhood developmental outcomes across physical, cognitive, language, communication, and socioemotional domains are major global health concerns. This systematic review aimed to synthesise perinatal and childhood risk factors using a socioecological model. Methods: We searched six databases for cohort, case–control, and cross-sectional studies published between January 2000 and January 2024. Studies reporting risk factors for adverse developmental outcomes were included. Findings were organised across individual, interpersonal, community, and societal levels using a socioecological model. The protocol was registered in PROSPERO (CRD42023447352). Results: A total of 175 studies were included. Individual-level risk factors, including preterm birth, low birth weight, male sex, chronic illness, undernutrition, and excessive screen use, were associated with adverse developmental outcomes, while exclusive breastfeeding, reading books, and storytelling were protective factors. Interpersonal risks included maternal age, education, mental health, and pregnancy complications. Community and societal risks include environmental pollution, access to education, conflict, and healthcare access. Conclusions: Improving early childhood developmental outcomes may require intervention at multiple levels. Future studies may need to focus on the influence of culturally and linguistically diverse backgrounds and environmental exposures on early childhood developmental outcomes.

1. Introduction

Globally, an estimated 250 million children fail to achieve their full developmental potential by the age of five [1]. Early childhood, defined by the World Health Organisation (WHO) as the period from prenatal development to eight years of age, is a critical window for human development [2,3]. This period lays the foundation for lifelong learning, school readiness, economic participation, and health outcomes [4,5,6]. Developmental outcomes during early childhood span across multiple domains, including physical, cognitive, language, communication, and socioemotional development [7,8,9,10]. Adverse developmental outcomes during this period, manifested as delays or difficulties in achieving developmental milestones, can lead to long-term consequences such as mental health problems, poor literacy, reduced employment opportunities, and an increased risk of involvement in criminal and violent activities [10].
A wide range of interconnected factors influence early childhood developmental outcomes, from genetic and biological characteristics to maternal health during pregnancy, child nutrition, exposure to toxic substances, accessibility and quality of healthcare services [11,12,13]. Maternal morbidity, such as hypertension, diabetes mellitus, and infectious diseases during pregnancy, can affect foetal development, which again leads to adverse childhood developmental outcomes [14,15]. Similarly, inadequate nutrition and limited access to healthcare services are associated with poor developmental trajectories [16].
Beyond individual-level determinants, broader socio-environmental contexts, including environmental pollution, neighbourhood safety, and the quality of early childhood education, critically influence developmental outcomes. These risk factors are often amplified by social inequalities and systemic barriers that disproportionately affect vulnerable populations [11,12,17,18,19,20].
Children’s optimal development is shaped by the complex interaction of biological, environmental, sociocultural, economic, political, and legal factors [21]. Given the complex and multilevel nature of these factors affecting early childhood developmental outcomes, a comprehensive approach is essential for effectively synthesising and summarising evidence from diverse and methodologically heterogeneous studies.
The socioecological model offers a flexible and structured framework for analysing risk factors at multiple levels, including individual (child), interpersonal (maternal, paternal, and household), community (school, peers, neighbourhood, and environmental factors), and societal (policy, programs, and systemic influences). Closely related to Bronfenbrenner’s ecological model, the socioecological model is widely used in public health to conceptualise interactions between social determinants of health and developmental outcomes [22]. It also guides the identification of targeted interventions to reduce developmental risks and improve outcomes.
While previous systematic reviews have examined risk factors for early childhood developmental outcomes, many have been limited by a narrow focus on single exposures or developmental domains, failing to capture the interconnected nature of these factors [18,23,24,25,26].
Grounded in the socioecological model, this systematic review examines how multilevel risk factors spanning the perinatal period to early childhood (≤8 years) influence developmental outcomes. By synthesising evidence on these exposures, the review aims to inform holistic, evidence-based strategies to prevent adverse developmental outcomes [1].

2. Materials and Methods

This systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines [27] and the Joanna Briggs Institute (JBI) manual for evidence synthesis [28,29].

2.1. Inclusion and Exclusion Criteria

We included observational studies (cohort, case–control, and cross-sectional) reporting the risk factors of adverse early childhood developmental outcomes. Eligibility was determined using the population, exposure, comparison, outcome, and study design (PECOS) criteria: (1) Population: The population included in this systematic review were children who underwent early childhood developmental assessments before the age of 8 years [20]. (2) Exposure: This includes perinatal and early childhood risk factors of adverse early childhood developmental outcomes, which include biological, psychosocial, behavioural, and environmental risk factors. (3) Comparator: These are children with no or low levels of exposure (if an environmental exposure) to the above risk factors. (4) Outcome: The primary outcome was adverse early childhood developmental outcomes, which include adverse outcomes of physical, cognitive, language, communication, and socioemotional development [30,31]. (5) Study design: These include observational studies such as cohort, case–control, and cross-sectional studies reporting the risk factors of adverse early childhood developmental outcomes. While there were no restrictions by geography, studies published in the English language between 1 January 2000 and 1 January 2024 were included. The year 2000 was considered due to technological change, social media use, social and cultural contexts, early childhood education, and environmental exposures over time. It is important to incorporate more recent and up-to-date knowledge in the field. There have been substantial changes in policies, interventions, and programs over the last two decades, all aimed at addressing early childhood developmental outcomes.
We excluded studies conducted exclusively among children with special health conditions such as prematurity, low birth weight, congenital anomalies, and other specific health conditions. We excluded studies such as commentaries, letters to editors, conference proceedings, case reports, case series, correspondence, descriptive statistics, interventional studies, non-human studies (e.g., animal model and in vitro), systematic review meta-analyses, and abstracts without full texts.

2.2. Search Strategy and Data Extraction

A comprehensive search strategy was developed collaboratively by the authors and implemented across EMBASE, PubMed, Global Health, PsycINFO, CINAHL, Web of Science Core Collection, and Google Scholar for grey literature. Search terms encompassed children’s developmental outcomes and relevant risk factors [32]. The full search terms are provided in the Supplementary Materials (Supplementary Material Table S1). The retrieved records were exported to EndNote version 20 [33], deduplicated, and exported to Rayyan [34], a systematic review management software. Initial screening (title and abstract) and subsequent full-text evaluations were primarily conducted by the first Author (KAA), with 20% independently assessed by co-authors (GAT and SDN). Data extraction, conducted by KAA using Microsoft Excel 2019 with regular discussions among the research team, included study details (author, year, country, design), sample size, age at developmental assessment, measurement tools, developmental domains, and associated risk factors. Authors were contacted for clarification or missing data when necessary.

2.3. Quality or Risk of Bias Assessment

Methodological quality was assessed using the updated JBI critical appraisal checklist [35,36]. Studies were classified as low, moderate, or high risk of bias based on checklist scores. Each study was rated by assigning one for yes if the paper met the criteria and zero for no/unclear if the paper did not meet the criteria listed in the JBI checklist as applied elsewhere [37].

2.4. Data Synthesis

Given substantial methodological outcome and risk factors measurement heterogeneity across studies, we performed a narrative synthesis informed by a socioecological model as a conceptual framework. This conceptual framework considers the complex interplay between personal, interpersonal, community, and societal factors, facilitating a multilevel understanding of risk and helping to identify the various determinants of early childhood developmental adversities. By acknowledging the interconnected factors at the individual, interpersonal, community context, and societal factors that contribute to early childhood developmental outcomes, the framework enables a comprehensive analysis essential for developing targeted interventions that address multiple layers of influences [33]. Risk factors were synthesised into individual (child-related) factors, interpersonal (family-related) factors, community factors, and societal-level influences [38,39,40]. We presented study characteristics and developmental outcomes in a tabular format, summarising the results across physical, cognitive, socioemotional, and language and communication domains. Many studies reported multiple risk factors or examined a single risk factor across multiple outcomes. The directions of association between the risk factors and outcome were assessed using the p-values or the confidence interval of the effect measures, such as odds ratio, relative risk, coefficient, etc.

3. Results

3.1. Study Selection and Characteristics

A total of 27,277 records were identified through databases and grey literature searches. After removing 2571 duplicates, 24,706 titles and abstracts were screened. Of these, 637 full-text articles were assessed for eligibility, and 175 studies met the inclusion criteria for the final review (Figure 1).
The 175 included studies were conducted in more than 80 countries. Nearly half of them (n = 89) originated from four countries: Australia (n = 33), the United States (n = 19), Canada (n = 18), and China (n = 17). Cohort design accounted for over three-quarters of the studies (n = 141). Forty-seven studies assessed childhood developmental vulnerability in multiple domains. A variety of early childhood developmental assessment tools were used. The most common was the Early Developmental Vulnerability Instrument (EDI), employed in 47 studies, followed by the Bayley Scales of Infant Development, used in 38 studies (Table 1 and Supplementary Material Table S2).

3.2. Adverse Early Childhood Developmental Outcomes

Nine studies [16,41,42,43,44,45,46,47,48] specifically quantified adverse developmental outcomes. In studies reporting early childhood developmental vulnerability across one or more domains, the prevalence was 28.1% in Vancouver, Canada [48], 30.2% in British Columbia, Canada [44], and 49% in Western Australia among Aboriginal children [46]. Studies from India, Kenya, and Turkey documented the prevalence of developmental delay as 6.6% [49], 16.5% [16], and 27% [42], respectively. Using the UNICEF Early Development Index, developmental vulnerability ranged from 25.1% to 34.5% in Bangladesh [41,43] and 35.0% in Nepal [45].
Across the 175 included studies, 115 examined risk factors for physical developmental vulnerability, 120 for cognitive outcomes, 90 for language and communication, and 96 for social–emotional domains; 37 studies did not specify sub-domains (Table 2).

3.3. Risk Factors of Adverse Early Childhood Developmental Outcomes

3.3.1. Individual-Level Risk Factors

Ninety-four studies examined demographic, perinatal, health-related, nutritional, and lifestyle factors [9,11,16,31,40,41,44,45,46,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98]. Males and those speaking English as a second language were consistently linked to poorer developmental outcomes, whereas two studies reported a lower risk with increasing child age. Low birth weight (8 studies), preterm birth (15 studies), and post-term birth (3 studies) showed a positive association with adverse developmental outcomes. For example, an Irish cohort study reported higher odds of childhood developmental vulnerability among low birth weight (OR = 2.6; 95% CI: 1.3, 5.0) and males (OR = 2.7, 95% CI: 1.8, 3.9) compared to their counterparts [51].
Childhood medical conditions such as infectious diseases, chronic illness, anaemia, hearing loss, plagiocephaly, untreated dental issues, childhood cancer, hospitalisation, surgery, and exposure to anaesthesia are linked with adverse developmental outcomes. Perinatal HIV exposure was associated with a marked reduction in cognitive performance, while having smaller effects on other developmental domains [81,82].
Undernutrition (underweight and stunting) increased risk, whereas exclusive breastfeeding for six months and early consumption of animal-sourced foods were protective [91]. Lifestyle factors such as access to books, storytelling, iron supplementation, and deworming were beneficial, while corporal punishment, excessive screen use, physical inactivity, and inadequate sleep heighten the risk of adverse early childhood developmental outcomes (Figure 2 and Supplementary Material Table S3).

3.3.2. Interpersonal and Household-Level Risk Factors

One hundred and thirty studies evaluated the maternal, paternal, and home environment influences of early childhood developmental adversities [14,15,16,41,42,43,46,47,48,49,50,51,52,53,55,63,69,90,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183]. Five studies showed both young (<20 years) and advanced (>35 Years) maternal age increased risk, and eleven studies reported the protective effect of maternal education [42,46,184]. In a Canadian study, children of less educated mothers had 11-fold higher odds of developmental delays (OR: 11.12; 95% CI: 4.2, 29.3) [42]. Low socioeconomic status, consanguineous marriage, and larger sibship were also detrimental [42,48].
Among the 26 studies that assessed the link between maternal mental health and developmental adversities, 19 studies reported a positive association with poorer developmental outcomes. A study from Norway showed an elevated socioemotional risk with prenatal depression (OR: 3.4; 95% CI: 1.4, 8.0), and even higher odds with post-partum depression (OR: 3.8; 95% CI: 1.7, 8.6) [63]. Five studies [128,129,130,131] linked prolonged use of psychiatric medication during pregnancy to adverse developmental outcomes. For instance, children prenatally exposed to long-term use of Selective Serotonin Reuptake Inhibitors (SSRIS) had a significantly increased risk of fine motor developmental delays (OR: 1.5; 95% CI: 1.12, 1.94) [129].
Pregnancy complications such as anaemia, gestational diabetes, pre-eclampsia, and unhealthy behaviours such as smoking and alcohol use, extreme interpregnancy intervals, and abnormal prepregnancy BMI were linked to developmental adversities [151,153,185]. Maternal nutrition and physical activities during pregnancy play a significant role in reducing early childhood development [161].
Fifteen studies assessed prenatal exposure to insecticides, corticosteroids, mercury, and second-hand tobacco smoke with adverse developmental outcomes. Paternal conviction, mental illness, tobacco smoking, and alcohol were linked with developmental adversities, whereas higher paternal education was linked to favourable developmental outcomes in children. Positive parenting behaviours, including parental encouragement, engagement, and stimulation, reduced developmental adversities. For example, a study from China showed that having fine-motor toys at home reduced the risk of motor development issues by 67% (OR: 0.33; 95% CI: 0.22, 0.49) [180]. In contrast, poor child stimulation and low parental satisfaction were associated with an increased risk of adverse developmental outcomes. Three studies linked indoor air pollution from cooking fuels with an increased risk of childhood developmental adversities. A study by Grippo et al. found significantly higher odds of developmental adversities associated with indoor air pollution (OR: 1.3; 95% CI: 1.1, 1.53) [182].

3.3.3. Community/Organisational-Level Factors

Thirty-six studies evaluated broader community influences [11,12,41,46,51,61,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202]. Aboriginal children in Australia had greater developmental vulnerability, especially in social competence [40,46,61,187]. Living in remote areas and being in the lower quintiles of the socioeconomic index for areas increased developmental vulnerability. Among studies that evaluated community influences, 26 studies examined the link between air pollution exposure and adverse early childhood developmental outcomes, of which 26 studies reported increased risk. For example, children prenatally exposed to PM2.5 had higher odds of adverse developmental outcomes (OR: 1.5; 95% CI: 1.2, 2.1) [197]. Conversely, factors such as attending early childhood education and care, preschools, and being in proximity to school grounds and parks were inversely associated with developmental adversities.

3.3.4. Societal, Policy/Program-Level Factors

Seven studies examined societal-level determinants [11,17,203,204,205,206,207]. Armed conflict elevated risk in low- and middle-income settings [203]. Human Development Index (HDI), and the availability of education and health services reduced early childhood developmental vulnerability. A study by Taylor et al. reported that the odds of childhood developmental vulnerability were significantly higher among children from families with low uptake of health and education services than among children from families with regular access (OR: 1.5; 95% CI: 1.2, 1.8) [205]. Canadian programs such as the Family First Home Visiting Program and the Healthy Baby Prenatal Benefit Program showed no association with developmental adversities in early childhood.
Figure 3 summarises the 20 risk factors most frequently examined across the included studies and indicates whether each factor was associated with increased (“Positive”) or decreased (“Inverse”) developmental adversities. Maternal mental health problems emerged as the most consistently reported risk factor, with 22 studies finding a positive association with developmental vulnerability. Other highly cited exposures included ambient air pollution (21 studies) and non-optimal gestational age (pre- or post-term birth; 18 studies). Several socioeconomic determinants, particularly low maternal education and low household economic status, also featured prominently, but with inverse directionality, indicating that higher education and higher income were protective.

3.4. Quality or Risk of Bias Assessment

Application of the JBI critical-appraisal checklists indicated that most studies were of high methodological quality. Specifically, 98 studies (70.9%) were rated as low risk of bias, 41 (26.3%) as moderate risk, and 6 (2.8%) as high risk (Figure 4 and Supplementary Material Table S4).

4. Discussion

This review synthesised perinatal and childhood risk factors for adverse early childhood developmental outcomes through the socioecological framework. Findings highlight the multifactorial nature of developmental adversities, spanning individual, interpersonal, community, and societal levels.
Birth characteristics such as low birth weight, prematurity, post-term birth, and male sex were consistently associated with developmental vulnerability, reflecting their impact on neural maturation and organ development [208,209,210,211,212,213]. Additional health-related risks included chronic illness, anaemia, hearing loss, plagiocephaly, untreated dental diseases, childhood cancer, and exposure to anaesthesia, which interrupts learning opportunities and or compromises neurocognitive function [16,46,53,69,70,71].
Modifiable lifestyle factors such as undernutrition, excessive screen time, physical inactivity, inadequate sleep, and punitive parenting similarly predict delays across physical, cognitive, and socioemotional development [50,214,215,216,217,218,219,220,221]. Moreover, protective factors such as exclusive breastfeeding, iron supplementation, deworming, book reading, and storytelling fostered healthy growth and language and cognitive development [91,94,181,222,223,224].
More than 80% of the included studies examined interpersonal-level factors, including maternal, paternal, and household-level influences. Extreme maternal age (<20 years or >35 years) increased risk, as did maternal mental illness, substance use, gestational complications such as anaemia, diabetes, pre-eclampsia, and short or long interpregnancy intervals [225,226,227,228,229,230,231]. Socioeconomic disadvantage, low maternal education, poverty, and single parenthood limited access to healthcare, nutrition, safe housing, and stimulating environments, whereas higher maternal education and economic stability were protective [232,233]. Paternal smoking, alcohol use, conviction, and mental illness were detrimental [234], while paternal education and active involvement in childcare supported language and socioemotional growth [235,236]. Positive parenting practices (engagement, stimulation, availability of toys) reduced risk by up to 67% [179]. Indoor air pollution from cooking fuels also emerged as a significant risk factor. In contrast, poor child stimulation and low parental satisfaction were associated with an increased risk of adverse developmental outcomes.
Remoteness, Aboriginality, and air pollution were linked to poorer developmental outcomes at the community level, reflecting structural inequities [237,238]. Conversely, participation in early childhood education and care consistently enhanced development, emphasising the value of early learning environments.
Societal-level determinants such as armed conflicts and national-level socioeconomic development (Human Development Index) also shaped early childhood outcomes [239]. Reliable access to health and education services during the first five years of life was strongly protective, whereas Canadian programs such as Family First Home Visiting and the Baby Parental Benefit programs showed no measurable effect [204,240].
Importantly, risk factors interact and compound across socioecological levels [241,242]. For example, maternal mental depression within low-income households can restrict access to healthcare and early intervention services, increasing the likelihood of adverse birth outcomes and subsequently developmental delays. Similarly, maternal smoking during pregnancy, when combined with environmental pollutants, heightens foetal exposure to neurotoxic substances and further compromises brain development.
Despite the wide range of determinants identified in this review, several critical evidence gaps remain. Research has yet to clarify how cultural and linguistic diversity (CALD) modifies developmental risk or resilience, while the cumulative effects of climate change, air pollution, and related stressors on child development are still poorly understood. Few studies map developmental vulnerability across neighbourhoods or regions, limiting the design of geographically targeted interventions. Finally, predictive modelling with routinely collected data remains underutilised, even though such approaches could facilitate earlier identification and tailored support for at-risk children.

4.1. Research and Policy Implications

This review identified several priority areas for future research aimed at addressing the existing evidence gaps. First, more nuanced studies are needed to explore how cultural and linguistic diversity (CALD) influences early developmental trajectories, including the identification of potential protective factors within CALD communities. Second, longitudinal studies might examine the cumulative impact of climate change and chronic exposure to environmental pollutants on neurodevelopment, acknowledging that such exposures can begin in utero and continue throughout early childhood. Third, incorporating geospatial analyses will help to identify neighbourhood-level “hot spots” of developmental vulnerability, enabling geographically targeted interventions tailored to local environmental and socioeconomic contexts. Finally, the development and validation of predictive models using routinely collected administrative and health data could facilitate early identification of children at risk of adverse developmental outcomes, enabling timely and targeted support before delays become entrenched.
Policy responses must be as multi-layered as the risk factors themselves. At the individual and family level, governments should expand universal access to high-quality antenatal care, integrate routine developmental screening into paediatric health services, and provide targeted home-visiting or parenting-support programmes for families facing psychosocial or economic disadvantage. At the community level, investment in affordable, high-quality early childhood education and care, especially in remote, low-income, and minority communities, can buffer many of the identified risks. Concurrently, local authorities should prioritise safe housing, green spaces, and clean air initiatives to reduce children’s exposure to environmental hazards. At the societal level, cross-sector policies that improve maternal education, strengthen income support, and extend paid parental leave promise long-term developmental benefits. Embedding equity metrics into health, education, and environmental policy will help direct resources to CALD and Indigenous populations, narrowing disparities in developmental outcomes.

4.2. Strengths and Limitations

A key strength of this review is its comprehensive and theory-informed approach, applying the socioecological model to examine a broad range of perinatal and childhood risk factors across multiple developmental domains: physical, cognitive, language and communication, and socioemotional development. This framework enables the identification of leverage points at the individual, interpersonal, community, and societal levels, offering actionable insights for policymakers and researchers addressing early childhood developmental adversity.
However, the review is constrained by notable heterogeneity in outcome measures and timing of developmental assessments. The 175 included studies utilised over 43 distinct developmental assessment tools, each with different scoring systems and age ranges, which limits direct comparability and precludes meaningful meta-analysis. Moreover, restricting the search to English-language publications may have introduced language bias, potentially underrepresenting evidence from non-English-speaking countries. Variability in data quality and reporting standards across studies further complicates cross-study comparisons. Finally, due to the heterogeneity in study designs and outcome definitions, a formal assessment of publication bias was not feasible. As a result, the findings should be interpreted with caution. Future research would benefit from greater standardisation in developmental assessment tools and reporting practices to enhance comparability and reduce bias.

5. Conclusions

This review shows that adverse early childhood developmental outcomes arise from a complex web of perinatal and postnatal exposures spanning individual, interpersonal, community, and societal spheres. Addressing these adversities, therefore, demands holistic, multilevel action. At the individual level, interventions should target modifiable child exposures, (e.g., nutrition, infections, and lifestyle). At the interpersonal level, programs might support maternal, paternal, and household determinants such as mental health, education, and parenting practices. Community-level strategies may expand access to quality early-childhood education, promote healthy behaviours, and improve neighbourhood environments. Finally, societal policies need to tackle structural drivers, including geographic inequities, human-development disparities, political and economic stability, and universal access to health and education services. Only an integrated approach that combines targeted support for vulnerable groups, sustained investment in early education, and robust environmental health initiatives can yield meaningful, equitable gains in children’s developmental trajectories.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/children12081096/s1.

Author Contributions

K.A.A., G.P., S.D.N., and G.A.T. conceived the study, developed a preliminary search strategy, and drafted the protocol. S.D.N. and B.D. participated in developing the search strategy and in writing the protocol. All authors have read and agreed to the published version of the manuscript.

Funding

GAT received funding support from the Australian National Health and Medical Research Council (Grant #1195716).

Data Availability Statement

All relevant data are included in the manuscript.

Conflicts of Interest

The authors declared that there were no conflicts of interest.

References

  1. Black, M.M.; Walker, S.P.; Fernald, L.C.H.; Andersen, C.T.; DiGirolamo, A.M.; Lu, C.; McCoy, D.C.; Fink, G.; Shawar, Y.R.; Shiffman, J.; et al. Early childhood development coming of age: Science through the life course. Lancet 2017, 389, 77–90. [Google Scholar] [CrossRef] [PubMed]
  2. World Health Organization. Early Child Development: A Powerful Equalizer; Final Report for the World Health Organization’s Commission on the Social Determinants of Health; World Health Organization: Geneva, Switzerland, 2007. [Google Scholar]
  3. World Health Organization. Early Childhood Development and Disability; World Health Organization: Geneva, Switzerland, 2012. [Google Scholar]
  4. Sartika, R.; Ismail, D.; Rosida, L. Factors that affect cognitive and mental emotional development of children: A scoping review. J. Health Technol. Assess. Midwifery 2021, 2620, 5653. [Google Scholar] [CrossRef]
  5. Panjeti-Madan, V.N.; Ranganathan, P. Impact of screen time on children’s development: Cognitive, language, physical, and social and emotional domains. Multimodal Technol. Interact. 2023, 7, 52. [Google Scholar] [CrossRef]
  6. Wang, S.-H.; Lin, K.-L.; Chen, C.-L.; Chiou, H.; Chang, C.-J.; Chen, P.-H.; Wu, C.-Y.; Lin, K.-C. Sleep problems during early and late infancy: Diverse impacts on child development trajectories across multiple domains. Sleep Med. 2024, 115, 177–186. [Google Scholar] [CrossRef]
  7. Reynolds, A.J.; Temple, J.A.; Robertson, D.L.; Mann, E.A. Long-term effects of an early childhood intervention on educational achievement and juvenile arrest: A 15-year follow-up of low-income children in public schools. JAMA 2001, 285, 2339–2346. [Google Scholar] [CrossRef] [PubMed]
  8. Coates, S.; Gaensbauer, T.J. Event trauma in early childhood: Symptoms, assessment, intervention. Child Adolesc. Psychiatr. Clin. N. Am. 2009, 18, 611–626. [Google Scholar] [CrossRef]
  9. Crockett, L.K.; Ruth, C.A.; Heaman, M.I.; Brownell, M.D. Education Outcomes of Children Born Late Preterm: A Retrospective Whole-Population Cohort Study. Matern Child Health J. 2022, 26, 1126–1141. [Google Scholar] [CrossRef] [PubMed]
  10. D’Angiulli, A.; Warburton, W.; Dahinten, S.; Hertzman, C. Population-level associations between preschool vulnerability and grade-four basic skills. PLoS ONE 2009, 4, e7692. [Google Scholar] [CrossRef] [PubMed]
  11. Brinkman, S.A.; Gialamas, A.; Rahman, A.; Mittinty, M.N.; Gregory, T.A.; Silburn, S.; Goldfeld, S.; Zubrick, S.R.; Carr, V.; Janus, M.; et al. Jurisdictional, socioeconomic and gender inequalities in child health and development: Analysis of a national census of 5-year-olds in Australia. BMJ Open 2012, 2, e001075. [Google Scholar] [CrossRef] [PubMed]
  12. Ha, S.; Yeung, E.; Bell, E.; Insaf, T.; Ghassabian, A.; Bell, G.; Muscatiello, N.; Mendola, P. Prenatal and early life exposures to ambient air pollution and development. Environ. Res. 2019, 174, 170–175. [Google Scholar] [CrossRef]
  13. Ialongo, N.S.; Domitrovich, C.; Embry, D.; Greenberg, M.; Lawson, A.; Becker, K.D.; Bradshaw, C. A randomized controlled trial of the combination of two school-based universal preventive interventions. Dev. Psychol. 2019, 55, 1313–1325. [Google Scholar] [CrossRef] [PubMed]
  14. Duko, B.; Gebremedhin, A.T.; Tessema, G.A.; Dunne, J.; Alati, R.; Pereira, G. The effects of pre-eclampsia on social and emotional developmental vulnerability in children at age five in Western Australia: A population data linkage study. J. Affect. Disorders 2024, 352, 349–356. [Google Scholar] [CrossRef]
  15. Duko, B.; Gebremedhin, A.T.; Tessema, G.A.; Pereira, G. Influence of preterm birth on the association between gestational diabetes mellitus and childhood developmental vulnerability: A causal mediation analysis. World J. Pediatr. 2023, 20, 54–63. [Google Scholar] [CrossRef]
  16. Abubakar, A.; Holding, P.; Van de Vijver, F.J.R.; Newton, C.; Van Baar, A. Children at risk for developmental delay can be recognised by stunting, being underweight, ill health, little maternal schooling or high gravidity. J. Child Psychol. Psychiatry 2010, 51, 652–659. [Google Scholar] [CrossRef]
  17. Collier, L.R.; Gregory, T.; Harman-Smith, Y.; Gialamas, A.; Brinkman, S.A. Inequalities in child development at school entry: A repeated cross-sectional analysis of the Australian Early Development Census 2009–2018. Lancet Reg. Health–West. Pac. 2020, 4, 100057. [Google Scholar] [CrossRef] [PubMed]
  18. Batchelor, J.M.; Thomas, K.S.; Akram, P.; Azad, J.; Bewley, A.; Chalmers, J.R.; Cheung, S.T.; Duley, L.; Eleftheriadou, V.; Ellis, R.; et al. Home-based narrowband UVB, topical corticosteroid or combination for children and adults with vitiligo: HI-Light Vitiligo three-arm RCT. Health Technol. Assess 2020, 24, 1–128. [Google Scholar] [CrossRef] [PubMed]
  19. Atalell, K.A.; Pereira, G.; Duko, B.; Nyadanu, S.D.; O’donnell, M.; Tessema, G.A. Prenatal and early childhood exposure to biothermal stress and developmental vulnerability at school entry in Western Australia: A population-based cohort study. Environ. Int. 2025, 202, 109642. [Google Scholar] [CrossRef]
  20. Atalell, K.A.; Pereira, G.; Duko, B.; Nyadanu, S.D.; Skirbekk, V.; Tessema, G.A. Developmental vulnerability in children from culturally and linguistically diverse backgrounds in Western Australia: A population-based study. World J. Pediatr. 2025, 21, 744–754. [Google Scholar] [CrossRef] [PubMed]
  21. Almasri, N.A.; Saleh, M.; Abu-Dahab, S.; Malkawi, S.H.; Nordmark, E. Development of a Cerebral Palsy Follow-up Registry in Jordan (CPUP-Jordan). Child Care Health Dev. 2018, 44, 131–139. [Google Scholar] [CrossRef] [PubMed]
  22. Centers for Disease Control and Prevention. Taking Action with Social Determinants of Health Frameworks and Tools; Centers for Disease Control and Prevention: Atlanta, GA, USA, 2023. [Google Scholar]
  23. Boonzaaijer, M.; Suir, I.; Mollema, J.; Nuysink, J.; Volman, M.; Jongmans, M. Factors associated with gross motor development from birth to independent walking: A systematic review of longitudinal research. Child Care Health Dev. 2021, 47, 525–561. [Google Scholar] [CrossRef] [PubMed]
  24. Cage, J.; Kobulsky, J.M.; McKinney, S.J.; Holmes, M.R.; Berg, K.A.; Bender, A.E.; Kemmerer, A. The Effect of Exposure to Intimate Partner Violence on Children’s Academic Functioning: A Systematic Review of the Literature. J. Fam. Violence 2022, 37, 1337–1352. [Google Scholar] [CrossRef]
  25. Carvalho Ferreira, R.D.; Alves, C.R.L.; Guimaraes, M.A.P.; Menezes, K.K.P.D.; Castro Magalhaes, L.D. Effects of early interventions focused on the family in the development of children born preterm and/or at social risk: A meta-analysis. J. Pediatr. 2020, 96, 20–38. [Google Scholar] [CrossRef]
  26. Chan, E.; Leong, P.; Malouf, R.; Quigley, M.A. Long-term cognitive and school outcomes of late-preterm and early-term births: A systematic review. Child Care Health Dev. 2016, 42, 297–312. [Google Scholar] [CrossRef] [PubMed]
  27. Brain Development Cooperative Group. Total and regional brain volumes in a population-based normative sample from 4 to 18 Years: The NIH MRI Study of Normal Brain Development. Cereb. Cortex 2012, 22, 1–12. [Google Scholar] [CrossRef] [PubMed]
  28. Moola, S.; Munn, Z.; Tufanaru, C.; Aromataris, E.; Sears, K.; Sfetcu, R.; Currie, M.; Lisy, K.; Qureshi, R.; Mattis, P.; et al. Chapter 7: Systematic Reviews of Etiology and Risk; JBI Manual for Evidence Synthesis; Joanna Briggs Institute: Adelaide, Australia, 2020. [Google Scholar]
  29. Munn, Z.; Moola, S.; Lisy, K.; Riitano, D.; Tufanaru, C. Methodological guidance for systematic reviews of observational epidemiological studies reporting prevalence and cumulative incidence data. Int. J. Evid.-Based Healthc. 2015, 13, 147–153. [Google Scholar] [CrossRef] [PubMed]
  30. Aboud, F.E.; Bougma, K.; Lemma, T.; Marquis, G.S. Evaluation of the effects of iodized salt on the mental development of preschool-aged children: A cluster randomized trial in northern Ethiopia. Matern Child Nutr. 2017, 13, e12322. [Google Scholar] [CrossRef]
  31. Dhamrait, G.K.; Christian, H.; O’Donnell, M.; Pereira, G. Gestational age and child development at school entry. Sci. Rep. 2021, 11, 14522. [Google Scholar] [CrossRef]
  32. Atalell, K.A.; Pereira, G.; Duko, B.; Nyadanu, S.D.; Tessema, G.A. Perinatal and early life risk factors of adverse early childhood developmental outcomes: Protocol for systematic review using socioecological model. PLoS ONE 2024, 19, e0311500. [Google Scholar] [CrossRef]
  33. Gotschall, T. EndNote 20 desktop version. J. Med. Libr. Assoc. JMLA 2021, 109, 520. [Google Scholar] [CrossRef]
  34. Ouzzani, M.; Hammady, H.; Fedorowicz, Z.; Elmagarmid, A. Rayyan—A web and mobile app for systematic reviews. Syst. Rev. 2016, 5, 210. [Google Scholar] [CrossRef]
  35. Buccheri, R.K.; Sharifi, C.O. Critical Appraisal Tools and Reporting Guidelines for Evidence-Based Practice. Worldviews Evid.-Based Nurs. 2017, 14, 463–472. [Google Scholar] [CrossRef] [PubMed]
  36. Porritt, K.P.; Gomersall, J.J.; Lockwood, C.P. JBI’s Systematic Reviews: Study Selection and Critical Appraisal. Am. J. Nurs. 2014, 114, 47–52. [Google Scholar] [CrossRef]
  37. Nyadanu, S.D.; Dunne, J.; Tessema, G.A.; Mullins, B.; Kumi-Boateng, B.; Lee Bell, M.; Duko, B.; Pereira, G. Prenatal exposure to ambient air pollution and adverse birth outcomes: An umbrella review of 36 systematic reviews and meta-analyses. Environ. Pollut. 2022, 306, 119465. [Google Scholar] [CrossRef] [PubMed]
  38. Schölmerich, V.L.; Kawachi, I. Translating the socio-ecological perspective into multilevel interventions: Gaps between theory and practice. Health Educ. Behav. 2016, 43, 17–20. [Google Scholar] [CrossRef] [PubMed]
  39. Lane, H.; Porter, K.; Estabrooks, P.; Zoellner, J. A systematic review to assess sugar-sweetened beverage interventions for children and adolescents across the socioecological model. J. Acad. Nutr. Diet. 2016, 116, 1295–1307.e6. [Google Scholar] [CrossRef] [PubMed]
  40. Leonard, D.; Buettner, P.; Thompson, F.; Makrides, M.; McDermott, R. Early childhood anaemia more than doubles the risk of developmental vulnerability at school-age among Aboriginal and Torres Strait Islander children of remote Far North Queensland: Findings of a retrospective cohort study. Nutr. Diet. 2020, 77, 298–309. [Google Scholar] [CrossRef]
  41. Hasan, M.N.; Babu, M.R.; Chowdhury, M.A.B.; Rahman, M.M.; Hasan, N.; Kabir, R.; Uddin, J. Early childhood developmental status and its associated factors in Bangladesh: A comparison of two consecutive nationally representative surveys. BMC Public Health 2023, 23, 687. [Google Scholar] [CrossRef] [PubMed]
  42. Ozkan, M.; Senel, S.; Arslan, E.A.; Karacan, C.D. The socioeconomic and biological risk factors for developmental delay in early childhood. Eur. J. Pediatr. 2012, 171, 1815–1821. [Google Scholar] [CrossRef] [PubMed]
  43. Rana, J.; Luna-Gutiérrez, P.; Haque, S.E.; Nazif-Muñoz, J.I.; Mitra, D.K.; Oulhote, Y. Associations between household air pollution and early child development among children aged 36–59 months in Bangladesh. J. Epidemiol. Community Health 2022, 76, 667–676. [Google Scholar] [CrossRef]
  44. Razaz, N.; Cnattingius, S.; Persson, M.; Tedroff, K.; Lisonkova, S.; Joseph, K. One-minute and five-minute Apgar scores and child developmental health at 5 years of age: A population-based cohort study in British Columbia, Canada. BMJ Open 2019, 9, e027655. [Google Scholar] [CrossRef]
  45. Shrestha, M.L.; Perry, K.E.; Thapa, B.; Adhikari, R.P.; Weissman, A. Malnutrition matters: Association of stunting and underweight with early childhood development indicators in Nepal. Matern. Child Nutr. 2022, 18, e13321. [Google Scholar] [CrossRef] [PubMed]
  46. Strobel, N.A.; Richardson, A.; Shepherd, C.C.J.; McAuley, K.E.; Marriott, R.; Edmond, K.M.; McAullay, D.R. Modelling factors for aboriginal and Torres strait islander child neurodevelopment outcomes: A latent class analysis. Paediatr. Perinat. Epidemiol. 2020, 34, 48–59. [Google Scholar] [CrossRef]
  47. Wall-Wieler, E.; Roos, L.L.; Gotlib, I.H. Maternal depression in early childhood and developmental vulnerability at school entry. Pediatrics 2020, 146, e20200794. [Google Scholar] [CrossRef]
  48. Webb, S.; Duku, E.; Brownell, M.; Enns, J.; Forer, B.; Guhn, M.; Minh, A.; Muhajarine, N.; Janus, M. Sex differences in the socioeconomic gradient of children’s early development. SSM-Popul. Health 2020, 10, 100512. [Google Scholar] [CrossRef]
  49. Sukanya, G.; Prabha, S.; Samsuzzaman, M.; Niladri, B.; Das, D.K. Developmental delay among children under two years of age in slums of Burdwan municipality: A cross.sectional study. J. Fam. Med. Prim. Care 2021, 10, 1945–1949. [Google Scholar]
  50. Kerai, S.; Almas, A.; Guhn, M.; Forer, B.; Oberle, E. Screen time and developmental health: Results from an early childhood study in Canada. BMC Public Health 2022, 22, 310. [Google Scholar] [CrossRef] [PubMed]
  51. Curtin, M.; Madden, J.; Staines, A.; Perry, I.J. Determinants of vulnerability in early childhood development in Ireland: A cross-sectional study. BMJ Open 2013, 3, e002387. [Google Scholar] [CrossRef] [PubMed]
  52. Ma, C.; Iwai-Shimada, M.; Nakayama, S.F.; Isobe, T.; Kobayashi, Y.; Tatsuta, N.; Taniguchi, Y.; Sekiyama, M.; Michikawa, T.; Yamazaki, S.; et al. Association of prenatal exposure to cadmium with neurodevelopment in children at 2 years of age: The Japan Environment and Children’s Study. Environ. Int. 2021, 156, 106762. [Google Scholar] [CrossRef] [PubMed]
  53. De Moura, D.R.; Costa, J.C.; Santos, I.S.; Barros, A.J.D.; Matijasevich, A.; Halpern, R.; Dumith, S.; Karam, S.; Barros, F.C. Risk factors for suspected developmental delay at age 2 years in a Brazilian birth cohort. Paediatr. Perinat. Epidemiol. 2010, 24, 211–221. [Google Scholar] [CrossRef] [PubMed]
  54. Razaz, N.; Boyce, W.T.; Brownell, M.; Jutte, D.; Tremlett, H.; Marrie, R.A.; Joseph, K.S. Five-minute Apgar score as a marker for developmental vulnerability at 5 years of age. Arch. Dis. Child.-Fetal Neonatal Ed. 2016, 101, F114–F120. [Google Scholar] [CrossRef]
  55. Halpern, R.; Barros, A.J.; Matijasevich, A.; Santos, I.S.; Victora, C.G.; Barros, F.C. Developmental status at age 12 months according to birth weight and family income: A comparison of two Brazilian birth cohorts. Cad Saude Publica 2008, 24, S444–S450. [Google Scholar] [CrossRef]
  56. Rocha, H.A.L.; Sudfeld, C.R.; Leite, A.J.M.; Machado, M.M.T.; Rocha, S.G.M.O.; Campos, J.S.; Silva, A.C.E.; Correia, L.L. Maternal and neonatal factors associated with child development in Ceara, Brazil: A population-based study. BMC Pediatr. 2021, 21, 163. [Google Scholar] [CrossRef]
  57. Wang, P.; Hao, M.; Han, W.; Yamauchi, T. Factors associated with nutritional status and motor development among young children. Nurs. Health Sci. 2019, 21, 323–329. [Google Scholar] [CrossRef]
  58. Smithers, L.G.; Searle, A.K.; Chittleborough, C.R.; Scheil, W.; Brinkman, S.A.; Lynch, J.W. A whole-of-population study of term and post-term gestational age at birth and children’s development. BJOG-Int. J. Obstet. Gynaecol. 2015, 122, 1303–1311. [Google Scholar] [CrossRef]
  59. Ballantyne, M.; Benzies, K.M.; McDonald, S.; Magill-Evans, J.; Tough, S. Risk of developmental delay: Comparison of late preterm and full term Canadian infants at age 12 months. Early Hum. Dev. 2016, 101, 27–32. [Google Scholar] [CrossRef] [PubMed]
  60. Gleason, J.L.; Gilman, S.E.; Sundaram, R.; Yeung, E.; Putnick, D.L.; Vafai, Y.; Saha, A.; Grantz, K.L. Gestational age at term delivery and children’s neurocognitive development. Int. J. Epidemiol. 2021, 50, 1814–1823. [Google Scholar] [CrossRef]
  61. Hanly, M.; Falster, K.; Chambers, G.; Lynch, J.; Banks, E.; Homaira, N.; Brownell, M.; Eades, S.; Jorm, L. Gestational Age and Child Development at Age Five in a Population-Based Cohort of Australian Aboriginal and Non-Aboriginal Children. Paediatr. Perinat. Epidemiol. 2018, 32, 114–125. [Google Scholar] [CrossRef] [PubMed]
  62. Hua, J.; Barnett, A.L.; Lin, Y.; Guan, H.Y.; Sun, Y.J.; Williams, G.J.; Fu, Y.; Zhou, Y.; Du, W. Association of Gestational Age at Birth With Subsequent Neurodevelopment in Early Childhood: A National Retrospective Cohort Study in China. Front. Pediatr. 2022, 10, 860192. [Google Scholar] [CrossRef] [PubMed]
  63. Junge, C.; Garthus-Niegel, S.; Slinning, K.; Polte, C.; Simonsen, T.B.; Eberhard-Gran, M. The Impact of Perinatal Depression on Children’s Social-Emotional Development: A Longitudinal Study. Matern. Child Health J. 2017, 21, 607–615. [Google Scholar] [CrossRef]
  64. Kerstjens, J.M.; de Winter, A.F.; Bocca-Tjeertes, I.F.; Ten Vergert, E.M.; Reijneveld, S.A.; Bos, A.F. Developmental delay in moderately preterm-born children at school entry. J. Pediatr. 2011, 159, 92–98. [Google Scholar] [CrossRef]
  65. Richards, J.L.; Drews-Botsch, C.; Sales, J.M.; Flers, W.D.; Kramer, M.R. Describing the Shape of the Relationship Between Gestational Age at Birth and Cognitive Development in a Nationally Representative U.S. Birth Cohort. Paediatr. Perinat. Epidemiol. 2016, 30, 571–582. [Google Scholar] [CrossRef]
  66. Sansavini, A.; Savini, S.; Guarini, A.; Broccoli, S.; Alessroni, R.; Faldella, G. The effect of gestational age on developmental outcomes: A longitudinal study in the first 2 years of life. Child Care Health Dev. 2011, 37, 26–36. [Google Scholar] [CrossRef]
  67. Kennedy, A.L.; Vollenhoven, B.J.; Hiscock, R.J.; Stern, C.J.; Walker, S.P.; Cheong, J.L.Y.; Quach, J.L.; Hastie, R.; Wilkinson, D.; McBain, J.; et al. School-age outcomes among IVF-conceived children: A population-wide cohort study. PLoS Med. 2023, 20, e1004148. [Google Scholar] [CrossRef] [PubMed]
  68. Lindquist, A.; Hastie, R.; Kennedy, A.; Gurrin, L.; Middleton, A.; Quach, J.; Cheong, J.; Walker, S.P.; Hiscock, R.; Tong, S. Developmental outcomes for children after elective birth at 39 weeks’ gestation. JAMA Pediatr. 2022, 176, 654–663. [Google Scholar] [CrossRef] [PubMed]
  69. Green, M.J.; Kariuki, M.; Dean, K.; Laurens, K.R.; Tzoumakis, S.; Harris, F.; Carr, V.J. Childhood developmental vulnerabilities associated with early life exposure to infectious and noninfectious diseases and maternal mental illness. J. Child Psychol. Psychiatry Allied Discip. 2018, 59, 801–810. [Google Scholar] [CrossRef] [PubMed]
  70. Kariuki, M.; Raudino, A.; Green, M.J.; Laurens, K.R.; Dean, K.; Brinkman, S.A.; Lenroot, R.K.; Liu, E.; Harris, F.; Luo, L.; et al. Hospital admission for infection during early childhood influences developmental vulnerabilities at age 5 years. J. Paediatr. Child Health 2016, 52, 882–888. [Google Scholar] [CrossRef] [PubMed]
  71. Fardell, J.E.; Hu, N.; Wakefield, C.E.; Marshall, G.; Bell, J.; Lingam, R.; Nassar, N. Impact of Hospitalizations due to Chronic Health Conditions on Early Child Development. J. Pediatr. Psychol. 2023, 48, 799–811. [Google Scholar] [CrossRef] [PubMed]
  72. Bell, M.F.; Bayliss, D.M.; Glauert, R.; Harrison, A.; Ohan, J.L. Chronic illness and developmental vulnerability at school entry. Pediatrics 2016, 137, e20152475. [Google Scholar] [CrossRef] [PubMed]
  73. Janus, M.; Reid-Westoby, C.; Lee, C.; Brownell, M.; Maguire, J.L. Association between severe unaddressed dental needs and developmental health at school entry in Canada: A cross-sectional study. BMC Pediatr. 2019, 19, 481. [Google Scholar] [CrossRef]
  74. Simpson, A.; Šarkić, B.; Enticott, J.C.; Richardson, Z.; Buck, K. Developmental vulnerability of Australian school-entry children with hearing loss. Aust. J. Prim. Health 2020, 26, 70–75. [Google Scholar] [CrossRef] [PubMed]
  75. Morris, J.N.; Roder, D.; Turnbull, D.; Hunkin, H. The impact of cancer on early childhood development: A linked data study. J. Pediatr. Psychol. 2021, 46, 49–58. [Google Scholar] [CrossRef]
  76. Rohde, J.F.; Goyal, N.K.; Slovin, S.R.; Hossain, J.; Pachter, L.M.; Di Guglielmo, M.D. Association of positional plagiocephaly and developmental delay within a primary care network. J. Dev. Behav. Pediatr. 2021, 42, 128–134. [Google Scholar] [CrossRef] [PubMed]
  77. Graham, M.R.; Brownell, M.; Chateau, D.G.; Dragan, R.D.; Burchill, C.; Fransoo, R.R. Neurodevelopmental Assessment in Kindergarten in Children Exposed to General Anesthesia before the Age of 4 Years. Anesthesiology 2016, 125, 667–677. [Google Scholar] [CrossRef]
  78. O’Leary, J.D.; Janus, M.; Duku, E.; Wijeysundera, D.N.; To, T.; Li, P.; Maynes, J.T.; Faraoni, D.; Crawford, M.W. Influence of Surgical Procedures and General Anesthesia on Child Development Before Primary School Entry Among Matched Sibling Pairs. JAMA Pediatr 2019, 173, 29–36. [Google Scholar] [CrossRef]
  79. O’Leary, J.D.; Janus, M.; Duku, E.; Wijeysundera, D.N.; To, T.; Li, P.; Maynes, J.T.; Crawford, M.M.W. A population-based study evaluating the association between surgery in early life and child development at primary school entry. Anesthesiology 2016, 125, 272–279. [Google Scholar] [CrossRef] [PubMed]
  80. Flick, R.P.; Katusic, S.K.; Colligan, R.C.; Wilder, R.T.; Voigt, R.G.; Olson, M.D.; Sprung, J.; Weaver, A.L.; Schroeder, D.R.; Warner, D.O. Cognitive and behavioral outcomes after early exposure to anesthesia and surgery. Pediatrics 2011, 128, e1053–e1061. [Google Scholar] [CrossRef]
  81. Roux, S.M.L.; Donald, K.A.; Brittain, K.; Phillips, T.K.; Zerbe, A.; Nguyen, K.K.; Andrea, S.; Max, K.; Elaine, J.A.; Landon, M. Neurodevelopment of breastfed HIV-exposed uninfected and HIV-unexposed children in South Africa. AIDS 2018, 32, 1781–1791. [Google Scholar] [CrossRef] [PubMed]
  82. Wu, J.; Li, J.; Li, Y.; Loo, K.; Yang, H.; Wang, Q.; Duan, R.; Xiao, X.; Song, X.; Yang, S.; et al. Neurodevelopmental outcomes in young children born to HIV-positive mothers in rural Yunnan, China. Pediatr. Int. 2018, 60, 618–625. [Google Scholar] [CrossRef] [PubMed]
  83. Chaudhury, S.; Mayondi, G.K.; Williams, P.L.; Leidner, J.; Shapiro, R.; Diseko, M.; Ajibola, G.; Holding, P.; Tepper, V.; Makhema, J.; et al. In-utero exposure to antiretrovirals and neurodevelopment among HIV-exposed-uninfected children in Botswana. AIDS 2018, 32, 1173–1183. [Google Scholar] [CrossRef]
  84. Luo, R.; Shi, Y.; Zhou, H.; Yue, A.; Zhang, L.; Sylvia, S.; Medina, A.; Rozelle, S. Micronutrient deficiencies and developmental delays among infants: Evidence from a cross-sectional survey in rural China. BMJ Open 2015, 5, e008400. [Google Scholar] [CrossRef]
  85. O’Neill, S.M.; Hannon, G.; Khashan, A.S.; Hourihane, J.O.; Kenny, L.C.; Kiely, M.; Murray, D.M. Thin-for-gestational age infants are at increased risk of neurodevelopmental delay at 2 years. Arch. Dis. Child Fetal. Neonatal. Ed. 2017, 102, F197–F202. [Google Scholar] [CrossRef]
  86. Pearce, A.; Scalzi, D.; Lynch, J.; Smithers, L.G. Do thin, overweight and obese children have poorer development than their healthy-weight peers at the start of school? Findings from a South Australian data linkage study. Early Child. Res. Q. 2016, 35, 85–94. [Google Scholar] [CrossRef] [PubMed]
  87. Wei, X.; Hu, J.; Yang, L.; Gao, M.; Li, L.; Ding, N.; Ma, Y.; Wen, D. Bidirectional association of neurodevelopment with growth: A prospective cohort study. BMC Pediatr. 2021, 21, 203. [Google Scholar] [CrossRef]
  88. Allel, K.; Abou Jaoude, G.; Poupakis, S.; Batura, N.; Skordis, J.; Haghparast-Bidgoli, H. Exploring the Associations between Early Childhood Development Outcomes and Ecological Country-Level Factors across Low- and Middle-Income Countries. Int. J. Environ. Res. Public Health 2021, 18, 3340. [Google Scholar] [CrossRef] [PubMed]
  89. Pokharel, A.; Webb, P.; Miller, L.C.; Zaharia, S.; Shrestha, R.; Davis, D.; Trevino, J.A.; Baral, K.P.; Paudel, K.; Ghosh, S. Relationship between Animal Sourced Food Consumption and Early Childhood Development Outcomes. Nutrients 2023, 15, 315. [Google Scholar] [CrossRef] [PubMed]
  90. Utami, N.H.; ayani Sekartini, R.; Kolopaking, R.; Besral Khusun, H. Cognitive performance of 4 to 6-year-old children: A longitudinal study. Paediatr. Indones. 2023, 63, 65–72. [Google Scholar] [CrossRef]
  91. Eickmann, S.H.; de Lira, P.I.; Lima Mde, C.; Coutinho, S.B.; Teixeira Mde, L.; Ashworth, A. Breast feeding and mental and motor development at 12 months in a low-income population in northeast Brazil. Paediatr. Perinat. Epidemiol. 2007, 21, 129–137. [Google Scholar] [CrossRef] [PubMed]
  92. Jedrychowski, W.; Perera, F.; Jankowski, J.; Butscher, M.; Mroz, E.; Flak, E.; Kaim, I.; Lisowska-Miszczyk, I.; Skarupa, A.; Sowa, A. Effect of exclusive breastfeeding on the development of children’s cognitive function in the Krakow prospective birth cohort study. Eur. J. Pediatr. 2012, 171, 151–158. [Google Scholar] [CrossRef] [PubMed]
  93. Wallenborn, J.T.; Levine, G.A.; Carreira dos Santos, A.; Grisi, S.; Ra Brentani, A.; Fink, G. Breastfeeding, Physical Growth, and Cognitive Development. Pediatrics 2021, 147, e2020008029. [Google Scholar] [CrossRef] [PubMed]
  94. Gao, Y.Q.; Wang, Y.P.; Zou, S.Y.; Mi, X.Y.; Kc, A.; Zhou, H. Association of iron supplementation and deworming with early childhood development: Analysis of Demographic and Health Surveys in ten low- and middle-income countries. Eur. J. Nutr. 2021, 60, 3119–3130. [Google Scholar] [CrossRef]
  95. Leao, O.A.D.; Bertoldi, A.D.; Domingues, M.R.; Murray, J.; Santos, I.S.; Barros, A.J.D.; Matijasevich, A.; Mielke, G.I. Cross-sectional and prospective associations between screen time and childhood neurodevelopment in two Brazilian cohorts born 11 years apart. Child Care Health Dev. 2023, 5, e13165. [Google Scholar]
  96. Rithipukdee, N.; Kusol, K. Factors Associated with the Suspected Delay in the Language Development of Early Childhood in Southern Thailand. Children 2022, 9, 662. [Google Scholar] [CrossRef] [PubMed]
  97. Rocha, H.A.L.; Correia, L.L.; Leite, A.M.; Machado, M.M.T.; Lindsay, A.C.; Rocha, S.G.M.O.; Campos, J.S.; Silva, A.C.E.; Sudfeld, C.R. Screen time and early childhood development in Ceara, Brazil: A population-based study. BMC Public Health 2021, 21, 2072. [Google Scholar] [CrossRef]
  98. Varadarajan, S.; Venguidesvarane, A.G.; Ramaswamy, K.N.; Rajamohan, M.; Krupa, M.; Christadoss, S.B.W. Prevalence of excessive screen time and its association with developmental delay in children aged <5 years: A population-based cross-sectional study in India. PLoS ONE 2021, 16, e0254102. [Google Scholar]
  99. Demirci, A.; Kartal, M. The prevalence of developmental delay among children aged 3-60 months in Izmir, Turkey. Child Care Health Dev. 2016, 42, 213–219. [Google Scholar] [CrossRef] [PubMed]
  100. Falster, K.; Hanly, M.; Banks, E.; Lynch, J.; Chambers, G.; Brownell, M.; Eades, S.; Jorm, L.; Myers, J.E. Maternal age and offspring developmental vulnerability at age five: A population-based cohort study of Australian children. PLoS Med. 2018, 15, e1002558. [Google Scholar] [CrossRef]
  101. Liu, Y.; Li, X.N.; Sun, X.R.; Liu, Q.L.; Zha, S.W.; Chen, Y.H.; Mao, C.; Xu, X. Prenatal and neonatal risk factors associated with children’s developmental status at ages 4–7: Lessons from the Jiangsu China birth defects prevention cohort. Child Care Health Dev. 2015, 41, 712–721. [Google Scholar] [CrossRef] [PubMed]
  102. Moreno-Giménez, A.; Campos-Berga, L.; Nowak, A.; Sahuquillo-Leal, R.; D’Ocon, A.; Hervás, D.; Navalón, P.; Vento, M.; García-Blanco, A. Impact of maternal age on infants’ emotional regulation and psychomotor development. Psychol. Med. 2022, 52, 3708–3719. [Google Scholar] [CrossRef]
  103. Syrengelas, D.; Kalampoki, V.; Kleisiouni, P.; Konstantinou, D.; Siahanidou, T. Gross motor development in full-term Greek infants assessed by the Alberta Infant Motor Scale: Reference values and socioeconomic impact. Early Hum. Dev. 2014, 90, 353–357. [Google Scholar] [CrossRef] [PubMed]
  104. Taylor, C.L.; Christensen, D.; Stafford, J.; Venn, A.; Preen, D.; Zubrick, S.R. Associations between clusters of early life risk factors and developmental vulnerability at age 5: A retrospective cohort study using population-wide linkage of administrative data in Tasmania, Australia. BMJ Open 2020, 10, e033795. [Google Scholar] [CrossRef]
  105. Peterson, C.C.; Riggs, J.; Guyon-Harris, K.; Harrison, L.; Huth-Bocks, A. Effects of Intimate Partner Violence and Home Environment on Child Language Development in the First 3 Years of Life. J. Dev. Behav. Pediatr. JDBP 2019, 40, 112–121. [Google Scholar] [CrossRef] [PubMed]
  106. Trumpff, C.; De Schepper, J.; Erfaeillie, J.; Vercruysse, N.; Van Oyen, H.; Moreno-Reyes, R.; Tafforeau, J.; Vanderpas, J.; Vandevijvere, S. Thyroid-Stimulating Hormone (TSH) Concentration at Birth in Belgian Neonates and Cognitive Development at Preschool Age. Nutrients 2015, 7, 9018–9032. [Google Scholar] [CrossRef] [PubMed]
  107. Smith, T.A.; Kievit, R.A.; Astle, D.E. Maternal mental health mediates links between socioeconomic status and child development. Curr. Psychol. 2023, 42, 21967–21978. [Google Scholar] [CrossRef]
  108. Bell, M.F.; Glauert, R.; Roos, L.L.; Wall-Wieler, E. Examining the relationship between maternal mental health-related hospital admissions and childhood developmental vulnerability at school entry in Canada and Australia. Bjpsych Open 2023, 9, e29. [Google Scholar] [CrossRef] [PubMed]
  109. Burger, M.; Einspieler, C.; Niehaus, D.J.; Unger, M.; Jordaan, E.R. Maternal mental health and infant neurodevelopment at 6 months in a low-income South African cohort. Infant Ment. Health J. 2022, 43, 849–863. [Google Scholar] [CrossRef]
  110. Cornish, A.M.; McMahon, C.A.; Ungerer, J.A.; Barnett, B.; Kowalenko, N.; Tennant, C. Postnatal depression and infant cognitive and motor development in the second postnatal year: The impact of depression chronicity and infant gender. Infant Behav. Dev. 2005, 28, 407–417. [Google Scholar] [CrossRef]
  111. Deave, T.; Heron, J.; Evans, J.; Emond, A. The impact of maternal depression in pregnancy on early child development. BJOG-Int. J. Obstet. Gynaecol. 2008, 115, 1043–1051. [Google Scholar] [CrossRef] [PubMed]
  112. González, G.; Moraes, M.; Sosa, C.; Umpierrez, E.; Duarte, M.; Cal, J.; Ghione, A. Maternal postnatal depression and its impact on child neurodevelopment: A cohort study. Rev. Chil. Pediatr.-Chile 2017, 88, 360–365. [Google Scholar] [CrossRef]
  113. Gül, H.; Gül, A.; Kara, K. Maternal depression, anxiety, psychoticism and paranoid ideation have effects on developmental delay types of infants: A study with clinical infant-mother dyads. Arch. Psychiatr. Nurs. 2020, 34, 184–190. [Google Scholar] [CrossRef] [PubMed]
  114. Ibanez, G.; Bernard, J.Y.; Rondet, C.; Peyre, H.; Forhan, A.; Kaminski, M.; Saurel-Cubizolles, M.-J.; EDEN mother-child cohort study group. Effects of Antenatal Maternal Depression and Anxiety on Children’s Early Cognitive Development: A Prospective Cohort Study. PLoS ONE 2015, 10, e0135849. [Google Scholar] [CrossRef] [PubMed]
  115. Keim, S.A.; Daniels, J.L.; Dole, N.; Herring, A.H.; Siega-Riz, A.M.; Scheidt, P.C. A prospective study of maternal anxiety, perceived stress, and depressive symptoms in relation to infant cognitive development. Early Hum. Dev. 2011, 87, 373–380. [Google Scholar] [CrossRef]
  116. Mensah, F.K.; Kiernan, K.E. Parents’ mental health and children’s cognitive and social development: Families in England in the Millennium Cohort Study. Soc. Psychiatry Psychiatr. Epidemiol. 2010, 45, 1023–1035. [Google Scholar] [CrossRef] [PubMed]
  117. Neamah, H.H.; Sudfeld, C.; McCoy, D.C.; Fink, G.; Fawzi, W.W.; Masanja, H.; Danaei, G.; Muhihi, A.; Kaaya, S.; Fawzi, M.C.S. Intimate partner violence, depression, and child growth and development. Pediatrics 2018, 142, e20173457. [Google Scholar] [CrossRef] [PubMed]
  118. Polte, C.; Junge, C.; von Soest, T.; Seidler, A.; Eberhard-Gran, M.; Garthus-Niegel, S. Impact of Maternal Perinatal Anxiety on Social-Emotional Development of 2-Year-Olds, A Prospective Study of Norwegian Mothers and Their Offspring: The Impact of Perinatal Anxiety on Child Development. Matern. Child Health J. 2019, 23, 386–396. [Google Scholar] [CrossRef] [PubMed]
  119. Quevedo, L.; Silva, R.; Godoy, R.; Jansen, K.; Matos, M.; Tavares Pinheiro, K.; Pinheiro, R.T. The impact of maternal post-partum depression on the language development of children at 12 months. Child Care Health Dev. 2012, 38, 420–424. [Google Scholar] [CrossRef] [PubMed]
  120. Ramchani, P.; Stein, A.; Evans, J.; O’Connor, T.G.; Team, A.S. Paternal depression in the postnatal period and child development: A prospective population study. Lancet 2005, 365, 2201–2205. [Google Scholar] [CrossRef]
  121. Rogers, A.M.; Youssef, G.J.; Teague, S.; Sunderl, M.; Le Bas, G.; Macdonald, J.A.; Mattick, R.P.; Allsop, S.; Elliott, E.J.; Olsson, C.A.; et al. Association of maternal and paternal perinatal depression and anxiety with infant development: A longitudinal study. J. Affect. Disord. 2023, 338, 278–288. [Google Scholar] [CrossRef]
  122. Roy, R.; Chakraborty, M.; Bhattacharya, K.; Roychoudhury, T.; Mukherjee, S. Impact of perinatal maternal depression on child development. Indian J. Psychiatry 2022, 64, 284–288. [Google Scholar] [CrossRef] [PubMed]
  123. Shuffrey, L.C.; Sania, A.; Brito, N.H.; Potter, M.; Springer, P.; Lucchini, M.; Rayport, Y.K.; Du Plessis, C.; Odendaal, H.J.; Fifer, W.P. Association of maternal depression and anxiety with toddler social-emotional and cognitive development in South Africa: A prospective cohort study. BMJ Open 2022, 12, e058135. [Google Scholar] [CrossRef]
  124. Smith-Nielsen, J.; Lange, T.; Wendelboe, K.I.; von Wowern, R.K.; Væver, M.S. Associations Between Maternal Postpartum Depression, Infant Social Behavior With a Stranger, and Infant Cognitive Development. Infancy 2019, 24, 663–670. [Google Scholar] [CrossRef]
  125. Tran, T.D.; Biggs, B.-A.; Tran, T.; Simpson, J.A.; Hanieh, S.; Dwyer, T.; Fisher, J.; Nizami, Q. Impact on infants’ cognitive development of antenatal exposure to iron deficiency disorder and common mental disorders. PLoS ONE 2013, 8, e74876. [Google Scholar] [CrossRef]
  126. Urizar, G.G.; Muñoz, R.F., Jr. Role of Maternal Depression on Child Development: A Prospective Analysis from Pregnancy to Early Childhood. Child Psychiatry Hum. Dev. 2022, 53, 502–514. [Google Scholar] [CrossRef] [PubMed]
  127. Zheng, S.; Bishop, S.L.; Ceja, T.; Hanna-Attisha, M.; LeWinn, K. Neurodevelopmental profiles of preschool-age children in Flint, Michigan: A latent profile analysis. J. Neurodev. Disord. 2021, 13, 29. [Google Scholar] [CrossRef] [PubMed]
  128. Dean, J.C.S.; Hailey, H.; Moore, S.J.; Lloyd, D.J.; Turnpenny, P.D.; Little, J. Long term health and neurodevelopment in children exposed to antiepileptic drugs before birth. J. Med. Genet. 2002, 39, 251–259. [Google Scholar] [CrossRef] [PubMed]
  129. Handal, M.; Skurtveit, S.; Furu, K.; Hernandez-Diaz, S.; Skovlund, E.; Nystad, W.; Selmer, R. Motor development in children prenatally exposed to selective serotonin reuptake inhibitors: A large population-based pregnancy cohort study. BJOG Int. J. Obstet. Gynaecol. 2016, 123, 1908–1917. [Google Scholar] [CrossRef] [PubMed]
  130. Van der Veere, C.N.; de Vries, N.K.S.; van Braeckel, K.; Bos, A.F. Intra-uterine exposure to selective serotonin reuptake inhibitors (SSRIs), maternal psychopathology, and neurodevelopment at age 2.5 years-Results from the prospective cohort SMOK study. Early Hum. Dev. 2020, 147, 105075. [Google Scholar] [CrossRef]
  131. Singal, D.; Chateau, D.; Struck, S.; Lee, J.B.; Dahl, M.; Derksen, S.; Katz, L.Y.; Ruth, C.; Hanlon-Dearman, A.; Brownell, M. In utero antidepressants and neurodevelopmental outcomes in kindergarteners. Pediatrics 2020, 145, e20191157. [Google Scholar] [CrossRef]
  132. Chen, C.; Lu, D.; Xue, L.; Ren, P.; Zhang, H.; Zhang, J. Association between Placental Inflammatory Pathology and Offspring Neurodevelopment at 8 Months and 4 and 7 Years of Age. J. Pediatr. 2020, 225, 132–137.e2. [Google Scholar] [CrossRef] [PubMed]
  133. Berglund, S.K.; Torres-Espínola, F.J.; García-Valdés, L.; Segura, M.T.; Martínez-Zaldívar, C.; Padilla, C.; Rueda, R.; García, M.P.; McArdle, H.J.; Campoy, C. The impacts of maternal iron deficiency and being overweight during pregnancy on neurodevelopment of the offspring. Br. J. Nutr. 2017, 118, 533–540. [Google Scholar] [CrossRef]
  134. Smithers, L.G.; Gialamas, A.; Scheil, W.; Brinkman, S.; Lynch, J.W. Anaemia of Pregnancy, Perinatal Outcomes and Children’s Developmental Vulnerability: A Whole-of-Population Study. Paediatr. Perinat. Epidemiol. 2014, 28, 381–390. [Google Scholar] [CrossRef]
  135. Nelson, S.; Lerner, E.; Needlman, R.; Salvator, A.; Singer, L.T. Cocaine, anemia, and neurodevelopmental outcomes in children: A longitudinal study. J. Dev. Behav. Pediatr. 2004, 25, 1–9. [Google Scholar] [CrossRef] [PubMed]
  136. Ghassabian, A.; Sundaram, R.; Wylie, A.; Bell, E.; Bello, S.C.; Yeung, E. Maternal medical conditions during pregnancy and gross motor development up to age 24 months in the Upstate KIDS study. Dev. Med. Child Neurol. 2016, 58, 728–734. [Google Scholar] [CrossRef] [PubMed]
  137. Warshafsky, C.; Pudwell, J.; Walker, M.; Wen, S.W.; Smith, G.N.; Preeclampsia New Emerging, T. Prospective assessment of neurodevelopment in children following a pregnancy complicated by severe pre-eclampsia. BMJ Open 2016, 6, e010884. [Google Scholar] [CrossRef] [PubMed]
  138. Holst, C.; Jorgensen, S.E.; Wohlfahrt, J.; Nybo Andersen, A.-M.; Melbye, M. Fever during pregnancy and motor development in children: A study within the Danish National Birth Cohort. Dev. Med. Child Neurol. 2015, 57, 725–732. [Google Scholar] [CrossRef] [PubMed]
  139. Bin, Y.S.; Cistulli, P.A.; Roberts, C.L.; Ford, J.B. Childhood health and educational outcomes associated with maternal sleep apnea: A population record-linkage study. Sleep 2017, 40, zsx158. [Google Scholar] [CrossRef] [PubMed]
  140. Razaz, N.; Joseph, K.; Boyce, W.T.; Guhn, M.; Forer, B.; Carruthers, R.; Marrie, R.A.; Tremlett, H. Children of chronically ill parents: Relationship between parental multiple sclerosis and childhood developmental health. Mult. Scler. J. 2016, 22, 1452–1462. [Google Scholar] [CrossRef]
  141. Motoki, N.; Inaba, Y.; Shibazaki, T.; Misawa, Y.; Ohira, S.; Kanai, M.; Kurita, H.; Tsukahara, T.; Nomiyama, T.; Kamijima, M.; et al. Insufficient maternal gestational weight gain and infant neurodevelopment at 12 months of age: The Japan Environment and Children’s Study. Eur. J. Pediatr. 2022, 181, 921–931. [Google Scholar] [CrossRef]
  142. Hao, X.M.; Lu, J.R.; Yan, S.Q.; Tao, F.B.; Huang, K. Maternal Pre-Pregnancy Body Mass Index, Gestational Weight Gain and Children’s Cognitive Development: A Birth Cohort Study. Nutrients 2022, 14, 4613. [Google Scholar] [CrossRef] [PubMed]
  143. Hinkle, S.N.; Schieve, L.A.; Stein, A.D.; Swan, D.W.; Ramakrishnan, U.; Sharma, A.J. Associations between maternal prepregnancy body mass index and child neurodevelopment at 2 years of age. Int. J. Obes. 2012, 36, 1312–1319. [Google Scholar] [CrossRef]
  144. Huang, L.; Yu, X.; Keim, S.; Li, L.; Zhang, L.; Zhang, J. Maternal prepregnancy obesity and child neurodevelopment in the Collaborative Perinatal Project. Int. J. Epidemiol. 2014, 43, 783–792. [Google Scholar] [CrossRef]
  145. Widen, E.M.; Nichols, A.R.; Kahn, L.G.; Factor-Litvak, P.; Insel, B.J.; Hoepner, L.; Dube, S.M.; Rauh, V.; Perera, F.; Rundle, A. Prepregnancy obesity is associated with cognitive outcomes in boys in a low-income, multiethnic birth cohort. BMC Pediatr. 2019, 19, 507. [Google Scholar] [CrossRef]
  146. Jang, M.; Molino, A.R.; Ribeiro, M.V.; Mariano, M.; Martins, S.S.; Caetano, S.C.; Surkan, P.J. Maternal Pregnancy Intention and Developmental Outcomes in Brazilian Preschool-Aged Children. J. Dev. Behav. Pediatr. JDBP 2021, 42, e15–e23. [Google Scholar] [CrossRef] [PubMed]
  147. Saleem, H.T.; Surkan, P.J. Parental pregnancy wantedness and child social-emotional development. Matern Child Health J. 2014, 18, 930–938. [Google Scholar] [CrossRef]
  148. Islam, M.M.; Khan, M.N. Early childhood development and its association with maternal parity. Child Care Health Dev. 2023, 49, 80–89. [Google Scholar] [CrossRef]
  149. Dhamrait, G.K.; Taylor, C.L.; Pereira, G. Interpregnancy intervals and child development at age 5: A population data linkage study. BMJ Open 2021, 11, e045319. [Google Scholar] [CrossRef] [PubMed]
  150. Dhamrait, G.; O’Donnell, M.; Christian, H.; Pereira, G. Is early childhood development impeded by the birth timing of the younger sibling? PLoS ONE 2022, 17, e0268325. [Google Scholar] [CrossRef]
  151. Duko, B.; Gebremedhin, A.T.; Tessema, G.A.; Alati, R.; Pereira, G. Average treatment effect of maternal prenatal tobacco smoking on offspring developmental vulnerability in early childhood. Ann. Epidemiol. 2023, 78, 35–43. [Google Scholar] [CrossRef] [PubMed]
  152. Julvez, J.; Ribas-Fito, N.; Torrent, M.; Forns, M.; Garcia-Esteban, R.; Sunyer, J. Maternal smoking habits and cognitive development of children at age 4 years in a population-based birth cohort. Int. J. Epidemiol. 2007, 36, 825–832. [Google Scholar] [CrossRef] [PubMed]
  153. Slykerman, R.F.; Thompson, J.M.D.; Clark, P.M.; Becroft, D.M.O.; Robinson, E.; Pryor, J.E.; Wild, C.J.; Mitchell, E.A. Determinants of developmental delay in infants aged 12 months. Paediatr. Perinat. Epidemiol. 2007, 21, 121–128. [Google Scholar] [CrossRef]
  154. Wehby, G.L.; Prater, K.; McCarthy, A.M.; Castilla, E.E.; Murray, J.C. The Impact of Maternal Smoking during Pregnancy on Early Child Neurodevelopment. J. Hum. Cap. 2011, 5, 207–254. [Google Scholar] [CrossRef]
  155. McCormack, C.; Hutchinson, D.; Burns, L.; Youssef, G.; Wilson, J.; Elliott, E.; Allsop, S.; Najman, J.; Jacobs, S.; Rossen, L.; et al. Maternal and partner prenatal alcohol use and infant cognitive development. Drug Alcohol. Depend 2018, 185, 330–338. [Google Scholar] [CrossRef] [PubMed]
  156. Bell, M.F.; Bayliss, D.M.; Glauert, R.; Ohan, J.L. Using linked data to investigate developmental vulnerabilities in children of convicted parents. Dev. Psychol. 2018, 54, 1219–1231. [Google Scholar] [CrossRef] [PubMed]
  157. Russell, A.L.; Hentschel, E.; Fulcher, I.; Rava, M.S.; Abdulkarim, G.; Abdalla, O.; Said, S.; Khamis, H.; Hedt-Gauthier, B.; Wilson, K. Caregiver parenting practices, dietary diversity knowledge, and association with early childhood development outcomes among children aged 18–29 months in Zanzibar, Tanzania: A cross-sectional survey. BMC Public Health 2022, 22, 762. [Google Scholar] [CrossRef] [PubMed]
  158. Saha, K.; Tofail, F.; Frongillo, E.; Rasmussen, K.; Arifeen, S.; Persson, L.; Huda, S.N.; Hamadani, J.D. Household food security is associated with early childhood language development: Results from a longitudinal study in rural Bangladesh. Child Care Health Dev. 2010, 36, 309–316. [Google Scholar] [CrossRef]
  159. Basnet, S.; Frongillo, E.A.; Nguyen, P.H.; Moore, S.; Arabi, M. Maternal resources for care are associated with child growth and early childhood development in Bangladesh and Vietnam. Child Care Health Dev. 2022, 48, 120–128. [Google Scholar] [CrossRef]
  160. Cruz-Rodríguez, J.; Díaz-López, A.; Canals-Sans, J.; Arija, V. Maternal Vitamin B12 Status during Pregnancy and Early Infant Neurodevelopment: The ECLIPSES Study. Nutrients 2023, 15, 1529. [Google Scholar] [CrossRef]
  161. Domingues, M.R.; Matijasevich, A.; Barros, A.J.; Santos, I.S.; Horta, B.L.; Hallal, P.C. Physical activity during pregnancy and offspring neurodevelopment and IQ in the first 4 years of life. PLoS ONE 2014, 9, e110050. [Google Scholar] [CrossRef]
  162. Turunç, G.; Kisbu-Sakarya, Y. Parents’ Attitudes Toward Domestic Violence as a Risk Factor for Early Childhood Development: Testing an Actor-Partner Interdependence Model Using UNICEF MICS. J. Interpers. Violence 2022, 37, NP21476–NP21501. [Google Scholar] [CrossRef]
  163. Whitten, T.; Green, M.J.; Tzoumakis, S.; Laurens, K.R.; Harris, F.; Carr, V.J.; Dean, K. Early developmental vulnerabilities following exposure to domestic violence and abuse: Findings from an Australian population cohort record linkage study. J. Psychiatr. Res. 2022, 153, 223–228. [Google Scholar] [CrossRef] [PubMed]
  164. Jeong, J.; Adhia, A.; Bhatia, A.; Charles, D.; Yousafzai, A.K. Intimate partner violence, maternal and paternal parenting, and early child development. Pediatrics 2020, 145, e20192955. [Google Scholar] [CrossRef] [PubMed]
  165. Horton, M.K.; Rundle, A.; Camann, D.E.; Boyd Barr, D.; Rauh, V.A.; Whyatt, R.M. Impact of prenatal exposure to piperonyl butoxide and permethrin on 36-month neurodevelopment. Pediatrics 2011, 127, e699–e706. [Google Scholar] [CrossRef] [PubMed]
  166. Tofail, F.; Vahter, M.; Hamadani, J.D.; Nermell, B.; Huda, S.N.; Mohammad, Y.; Rahman, M.; Grantham-McGregor, S.M. Effect of arsenic exposure during pregnancy on infant development at 7 months in rural Matlab, Bangladesh. Environ. Health Perspect. 2009, 117, 288–293. [Google Scholar] [CrossRef]
  167. Perera, F.P.; Rauh, V.; Whyatt, R.M.; Tsai, W.; Tang, D.; Diaz, D.; Hoepner, L.; Barr, D.; Tu, Y.-H.; Camann, D.; et al. Effect of prenatal exposure to airborne polycyclic aromatic hydrocarbons on neurodevelopment in the first 3 years of life among inner-city children. Environ. Health Perspect. 2006, 114, 1287–1292. [Google Scholar] [CrossRef]
  168. Tao, S.Y.; Du, J.B.; Chi, X.; Zhu, Y.Y.; Wang, X.Y.; Meng, Q.X.; Ling, X.; Diao, F.; Song, C.; Jiang, Y.; et al. Associations between antenatal corticosteroid exposure and neurodevelopment in infants. Am. J. Obstet. Gynecol. 2022, 227, 759.e1–759.e15. [Google Scholar] [CrossRef] [PubMed]
  169. Morrow, C.E.; Stra, E.S.; Anthony, J.C.; Ofir, A.Y.; Xue, L.; Reyes, M.B. Influence of prenatal cocaine exposure on early language development: Longitudinal findings from four months to three years of age. J. Dev. Behav. Pediatr. 2003, 24, 39–50. [Google Scholar] [CrossRef] [PubMed]
  170. Wang, A.; Wan, Y.; Mahai, G.; Qian, X.; Li, Y.; Xu, S.; Xia, W. Association of Prenatal Exposure to Organophosphate, Pyrethroid, and Neonicotinoid Insecticides with Child Neurodevelopment at 2 Years of Age: A Prospective Cohort Study. Environ. Health Perspect. 2023, 131, 107011. [Google Scholar] [CrossRef] [PubMed]
  171. Reardon, A.J.F.; Hajihosseini, M.; Dinu, I.; Field, C.J.; Kinniburgh, D.W.; MacDonald, A.M.; Dewey, D.; England-Mason, G.; Martin, J.W. Maternal co-exposure to mercury and perfluoroalkyl acid isomers and their associations with child neurodevelopment in a Canadian birth cohort. Environ. Int. 2023, 178, 108087. [Google Scholar] [CrossRef]
  172. Chen, M.H.; Ha, E.H.; Liao, H.F.; Jeng, S.F.; Su, Y.N.; Wen, T.W.; Lien, G.W.; Chen, C.Y.; Hsieh, W.S.; Chen, P.C. Perfluorinated compound levels in cord blood and neurodevelopment at 2 years of age. Epidemiology 2013, 24, 800–808. [Google Scholar] [CrossRef] [PubMed]
  173. Kim, J.H.; Moon, N.; Ji, E.; Moon, H.B. Effects of postnatal exposure to phthalate, bisphenol a, triclosan, parabens, and per- and poly-fluoroalkyl substances on maternal postpartum depression and infant neurodevelopment: A korean mother-infant pair cohort study. Environ. Sci. Pollut. Res. 2023, 30, 96384–96399. [Google Scholar] [CrossRef]
  174. Mora, A.M.; Cordoba, L.; Cano, J.C.; Hern ez-Bonilla, D.; Pardo, L.; Schnaas, L.; Smith, D.R.; Menezes-Filho, J.A.; Mergler, D.; Lindh, C.H.; et al. Prenatal mancozeb exposure, excess manganese, and neurodevelopment at 1 year of age in the Infants’ Environmental Health (ISA) study. Environ. Health Perspect. 2018, 126, EHP1955. [Google Scholar] [CrossRef] [PubMed]
  175. Guo, J.; Zhang, J.; Wu, C.; Lv, S.; Lu, D.; Qi, X.; Jiang, S.; Feng, C.; Yu, H.; Liang, W.; et al. Associations of prenatal and childhood chlorpyrifos exposure with Neurodevelopment of 3-year-old children. Environ. Pollut. 2019, 251, 538–546. [Google Scholar] [CrossRef] [PubMed]
  176. He, Y.; Luo, R.F.; Wang, T.Y.; Gao, J.J.; Liu, C.F. Prenatal Exposure to Environmental Tobacco Smoke and Early Development of Children in Rural Guizhou Province, China. Int. J. Environ. Res. Public Health 2018, 15, 2866. [Google Scholar] [CrossRef] [PubMed]
  177. Polanska, K.; Krol, A.; Merecz-Kot, D.; Ligocka, D.; Mikolajewska, K.; Mirabella, F.; Chiarotti, F.; Calamandrei, G.; Hanke, W. Environmental Tobacco Smoke Exposure during Pregnancy and Child Neurodevelopment. Int. J. Environ. Res. Public Health 2017, 14, 796. [Google Scholar] [CrossRef] [PubMed]
  178. Rivero, M.; Vilaseca, R.; Cantero, M.-J.; Valls-Vidal, C.; Leiva, D. Relations between Positive Parenting Behavior during Play and Child Language Development at Early Ages. Children 2023, 10, 505. [Google Scholar] [CrossRef] [PubMed]
  179. Rocha, H.A.L.; Correia, L.L.; Leite, Á.J.M.; Rocha, S.G.M.O.; Albuquerque, L.d.S.; Machado, M.M.T.; Campos, J.S.; e Silva, A.C.; Sudfeld, C.R. Positive Parenting Behaviors and Child Development in Ceará, Brazil: A Population-Based Study. Children 2022, 9, 1246. [Google Scholar] [CrossRef] [PubMed]
  180. Cao, Z.; Su, X.; Ni, Y.; Luo, T.; Hua, J. Association between the home environment and development among 3- to 11-month infants in Shanghai, China. Child Care Health Dev. 2022, 48, 45–54. [Google Scholar] [CrossRef] [PubMed]
  181. Drago, F.; Scharf, R.J.; Maphula, A.; Nyathi, E.; Mahopo, T.C.; Svensen, E.; Mduma, E.; Bessong, P.; McQuade, E.T.R. Psychosocial and environmental determinants of child cognitive development in rural South Africa and Tanzania: Findings from the mal-ed cohort. BMC Public Health 2020, 20, 505. [Google Scholar] [CrossRef] [PubMed]
  182. Grippo, A.; Zhu, K.X.; Yeung, E.H.; Bell, E.M.; Bonner, M.R.; Tian, L.L.; Mendola, P.; Mu, L. Indoor air pollution exposure and early childhood development in the Upstate KIDS Study. Environ. Res. 2023, 234, 116528. [Google Scholar] [CrossRef]
  183. Vrijheid, M.; Martinez, D.; Aguilera, I.; Bustamante, M.; Ballester, F.; Estarlich, M.; ernandez-Somoano, A.; Guxens, M.; Lertxundi, N.; Martinez, M.D.; et al. Indoor air pollution from gas cooking and infant neurodevelopment. Epidemiology 2012, 23, 23–32. [Google Scholar] [CrossRef]
  184. Demirci, A.; Kartal, M. Sociocultural risk factors for developmental delay in children aged 3-60 months: A nested case-control study. Eur. J. Pediatr. 2018, 177, 691–697. [Google Scholar] [CrossRef]
  185. Girchenko, P.; Tuovinen, S.; Lahti-Pulkkinen, M.; Lahti, J.; Savolainen, K.; Heinonen, K.; Pyhälä, R.; Reynolds, R.M.; Hämäläinen, E.; Villa, P.M.; et al. Maternal early pregnancy obesity and related pregnancy and pre-pregnancy disorders: Associations with child developmental milestones in the prospective PREDO Study. Int. J. Obes. 2018, 42, 995–1007. [Google Scholar] [CrossRef]
  186. Christian, H.; Ball, S.J.; Zubrick, S.R.; Brinkman, S.; Turrell, G.; Boruff, B.; Foster, S. Relationship between the neighbourhood built environment and early child development. Health Place 2017, 48, 90–101. [Google Scholar] [CrossRef]
  187. Williamson, A.; Gibberd, A.; Hanly, M.J.; Banks, E.; Eades, S.; Clapham, K.; Falster, K. Social and emotional developmental vulnerability at age five in Aboriginal and non-Aboriginal children in New South Wales: A population data linkage study. Int. J. Equity Health 2019, 18, 120. [Google Scholar] [CrossRef] [PubMed]
  188. Falster, K.; Hanly, M.; Edwards, B.; Banks, E.; Lynch, J.W.; Eades, S.; Nickel, N.; Goldfeld, S.; Biddle, N. Preschool attendance and developmental outcomes at age five in Indigenous and non-Indigenous children: A population-based cohort study of 100,357 Australian children. J. Epidemiol. Community Health 2021, 75, 371–379. [Google Scholar] [CrossRef]
  189. Rao, N.; Richards, B.; Sun, J.; Webers, A.; Sincovich, A. Early childhood education and child development in four countries in East Asia and the Pacific. Early Child. Res. Q. 2019, 47, 169–181. [Google Scholar] [CrossRef]
  190. Ahmed, S.M.; Mishra, G.D.; Moss, K.M.; Yang, I.A.; Lycett, K.; Knibbs, L.D. Maternal and Childhood Ambient Air Pollution Exposure and Mental Health Symptoms and Psychomotor Development in Children: An Australian Population-Based Longitudinal Study. Environ. Int. 2022, 158, 107003. [Google Scholar] [CrossRef] [PubMed]
  191. Shih, P.; Chiang, T.L.; Wu, C.D.; Shu, B.C.; Lung, F.W.; Guo, Y.L. Air pollution during the perinatal period and neurodevelopment in children: A national population study in Taiwan. Dev. Med. Child Neurol. 2023, 65, 783–791. [Google Scholar] [CrossRef]
  192. Chiu, Y.H.M.; Hsu, H.H.L.; Coull, B.A.; Bellinger, D.C.; Kloog, I.; Schwartz, J.; Wright, R.O.; Wright, R.J. Prenatal particulate air pollution and neurodevelopment in urban children: Examining sensitive windows and sex-specific associations. Environ. Int. 2016, 87, 56–65. [Google Scholar] [CrossRef]
  193. Jarvis, I.; Davis, Z.; Sbihi, H.; Brauer, M.; Czekajlo, A.; Davies, H.W.; Gergel, S.E.; Guhn, M.; Jerrett, M.; Koehoorn, M.; et al. Assessing the association between lifetime exposure to greenspace and early childhood development and the mediation effects of air pollution and noise in Canada: A population-based birth cohort study. Lancet Planet. Health 2021, 5, e709–e717. [Google Scholar] [CrossRef]
  194. Lertxundi, A.; Baccini, M.; Lertxundi, N.; Fano, E.; Aranbarri, A.; Martínez, M.D.; Ayerdi, M.; Álvarez, J.; Santa-Marina, L.; Dorronsoro, M.; et al. Exposure to fine particle matter, nitrogen dioxide and benzene during pregnancy and cognitive and psychomotor development in children at 15 months of age. Environ. Int. 2015, 80, 33–40. [Google Scholar] [CrossRef] [PubMed]
  195. Odo, D.B.; Yang, I.A.; Dey, S.; Hammer, M.S.; van Donkelaar, A.; Martin, R.V.; Dong, G.-H.; Yang, B.-Y.; Hystad, P.; Knibbs, L.D. A cross-sectional analysis of long-term exposure to ambient air pollution and cognitive development in children aged 3–4 years living in 12 low- and middle-income countries. Environ. Pollut. 2023, 318, 120916. [Google Scholar] [CrossRef]
  196. Porta, D.; Narduzzi, S.; Badaloni, C.; Bucci, S.; Cesaroni, G.; Colelli, V.; Davoli, M.; Sunyer, J.; Zirro, E.; Schwartz, J.; et al. Air pollution and cognitive development at age 7 in a prospective Italian birth cohort. Epidemiology 2016, 27, 228–236. [Google Scholar] [CrossRef] [PubMed]
  197. Wang, P.P.; Zhao, Y.Y.; Li, J.L.; Zhou, Y.H.; Luo, R.R.; Meng, X.; Zhang, Y. Prenatal exposure to ambient fine particulate matter and early childhood neurodevelopment: A population-based birth cohort study. Sci. Total Environ. 2021, 785, 147334. [Google Scholar] [CrossRef] [PubMed]
  198. Wang, H.J.; Zhang, H.L.; Li, J.X.; Liao, J.Q.; Liu, J.T.; Hu, C.; Sun, X.; Zheng, T.; Xia, W.; Xu, S.; et al. Prenatal and early postnatal exposure to ambient particulate matter and early childhood neurodevelopment: A birth cohort study. Environ. Res. 2022, 210, 112946. [Google Scholar] [CrossRef]
  199. Kim, E.; Park, H.; Hong, Y.C.; Ha, M.; Kim, Y.; Kim, B.N.; Kim, Y.; Roh, Y.M.; Lee, B.E.; Ryu, J.M.; et al. Prenatal exposure to PM10 and NO2 and children’s neurodevelopment from birth to 24 months of age: Mothers and Children’s Environmental Health (MOCEH) study. Sci. Total. Environ. 2014, 481, 439–445. [Google Scholar] [CrossRef] [PubMed]
  200. Freire, C.; Ramos, R.; Puertas, R.; Lopez-Espinosa, M.J.; Julvez, J.; Aguilera, I.; Cruz, F.; Fernandez, M.-F.; Sunyer, J.; Olea, N. Association of traffic-related air pollution with cognitive development in children. J. Epidemiol. Community Health 2010, 64, 223–228. [Google Scholar] [CrossRef]
  201. Yu, T.; Zhou, L.L.; Xu, J.; Kan, H.D.; Chen, R.J.; Chen, S.W.; Hua, H.; Liu, Z.; Yan, C. Effects of prenatal exposures to air sulfur dioxide/nitrogen dioxide on toddler neurodevelopment and effect modification by ambient temperature. Ecotoxicol. Environ. Saf. 2022, 230, 113118. [Google Scholar] [CrossRef]
  202. Bai, Y.; Shang, G.; Wang, L.; Sun, Y.; Osborn, A.; Rozelle, S. The relationship between birth season and early childhood development: Evidence from northwest rural China. PLoS ONE 2018, 13, e0205281. [Google Scholar] [CrossRef] [PubMed]
  203. Goto, R.; Frodl, T.; Skokauskas, N. Armed Conflict and Early Childhood Development in 12 Low- and Middle-Income Countries. Pediatrics 2021, 148, e2021050332. [Google Scholar] [CrossRef] [PubMed]
  204. Bornstein, M.H.; Rothenberg, W.A.; Lansford, J.E.; Bradley, R.H.; Deater-Deckard, K.; Bizzego, A.; Esposito, G. Child Development in Low- and Middle-Income Countries. Pediatrics 2021, 148, e2021053180. [Google Scholar] [CrossRef] [PubMed]
  205. Taylor, C.L.; Christensen, D.; Venn, A.J.; Preen, D.B.; Stafford, J.; Hansen, E.; Jose, K.; Zubrick, S. Use of administrative record linkage to examine patterns of universal early childhood health and education service use from birth to Kindergarten (age four years) and developmental vulnerability in the Preparatory Year (age five years) in Tasmania, Australia. Int. J. Popul. Data Sci. 2021, 6, 1681. [Google Scholar]
  206. Chartier, M.J.; Brownell, M.D.; Isaac, M.R.; Chateau, D.; Nickel, N.C.; Katz, A.; Sarkar, J.; Hu, M.; Taylor, C. Is the Families First Home Visiting Program Effective in Reducing Child Maltreatment and Improving Child Development? Child Maltreatment 2017, 22, 121–131. [Google Scholar] [CrossRef]
  207. Enns, J.E.; Nickel, N.C.; Chartier, M.; Chateau, D.; Campbell, R.; Phillips-Beck, W.; Sarkar, J.; Burland, E.; Katz, A.; Santos, R.; et al. An unconditional prenatal income supplement is associated with improved birth and early childhood outcomes among First Nations children in Manitoba, Canada: A population-based cohort study. BMC Pregnancy Childbirth 2021, 21, 312. [Google Scholar] [CrossRef]
  208. Christians, J.K.; Ahmadzadeh-Seddeighi, S.; Bilal, A.; Bogdanovic, A.; Ho, R.; Leung, E.V.; MacGregor, M.A.; Nadasdy, N.M.; Principe, G.M. Sex differences in the effects of prematurity and/or low birthweight on neurodevelopmental outcomes: Systematic review and meta-analyses. Biol. Sex Differ. 2023, 14, 47. [Google Scholar] [CrossRef] [PubMed]
  209. Davis, B.E.; Leppert, M.O.C.; German, K.; Lehmann, C.U.; Adams-Chapman, I.; Council on Children with Disabilities; Committee on Fetus and Newborn. Primary Care Framework to Monitor Preterm Infants for Neurodevelopmental Outcomes in Early Childhood. Pediatrics 2023, 152, e2023062511. [Google Scholar] [CrossRef] [PubMed]
  210. Hong, Y.M.; Cho, D.H.; Kim, J.K. Developmental outcomes of very low birth weight infants with catch-up head growth: A nationwide cohort study. BMC Pediatr. 2023, 23, 392. [Google Scholar] [CrossRef] [PubMed]
  211. Jańczewska, I.; Wierzba, J.; Jańczewska, A.; Szczurek-Gierczak, M.; Domżalska-Popadiuk, I. Prematurity and Low Birth Weight and Their Impact on Childhood Growth Patterns and the Risk of Long-Term Cardiovascular Sequelae. Children 2023, 10, 1599. [Google Scholar] [CrossRef] [PubMed]
  212. Glover Williams, A.; Odd, D. Investigating the association between post-term birth and long term cognitive, developmental and educational impacts: A systematic review and Meta-analysis. J. Matern. Fetal Neonatal. Med. 2020, 33, 1253–1265. [Google Scholar] [CrossRef]
  213. Jenabi, E.; Farashi, S.; Salehi, A.M.; Parsapoor, H. The association between post-term births and autism spectrum disorders: An updated systematic review and meta-analysis. Eur. J. Med. Res. 2023, 28, 316. [Google Scholar] [CrossRef] [PubMed]
  214. De Oliveira, K.H.D.; de Almeida, G.M.; Gubert, M.B.; Moura, A.S.; Spaniol, A.M.; Hernandez, D.C.; Pérez-Escamilla, R.; Buccini, G. Household food insecurity and early childhood development: Systematic review and meta-analysis. Matern. Child Nutr. 2020, 16, e12967. [Google Scholar] [CrossRef] [PubMed]
  215. Tandon, P.S.; Tovar, A.; Jayasuriya, A.T.; Welker, E.; Schober, D.J.; Copeland, K.; Dev, D.A.; Murriel, A.L.; Amso, D.; Ward, D.S. The relationship between physical activity and diet and young children’s cognitive development: A systematic review. Prev. Med. Rep. 2016, 3, 379–390. [Google Scholar] [CrossRef]
  216. Irigaray, T.Q.; Pacheco, J.B.; Grassi-Oliveira, R.; Fonseca, R.P.; Leite, J.C.d.C.; Kristensen, C.H. Child maltreatment and later cognitive functioning: A systematic review. Psicol. Reflexão E Crítica 2013, 26, 376–387. [Google Scholar] [CrossRef]
  217. Madigan, S.; McArthur, B.A.; Anhorn, C.; Eirich, R.; Christakis, D.A. Associations between screen use and child language skills: A systematic review and meta-analysis. JAMA Pediatr. 2020, 174, 665–675. [Google Scholar] [CrossRef] [PubMed]
  218. Ren, W. The Influence of Screen Media Usage on Child Social Development: A Systematic Review. J. Educ. Humanit. Soc. Sci. 2023, 8, 2110–2117. [Google Scholar] [CrossRef]
  219. Carson, V.; Hunter, S.; Kuzik, N.; Wiebe, S.A.; Spence, J.C.; Friedman, A.; Tremblay, M.S.; Slater, L.; Hinkley, T. Systematic review of physical activity and cognitive development in early childhood. J. Sci. Med. Sport 2016, 19, 573–578. [Google Scholar] [CrossRef] [PubMed]
  220. Zeng, N.; Ayyub, M.; Sun, H.; Wen, X.; Xiang, P.; Gao, Z. Effects of physical activity on motor skills and cognitive development in early childhood: A systematic review. BioMed Res. Int. 2017, 2017, 2760716. [Google Scholar] [CrossRef]
  221. McDonough, D.J.; Liu, W.; Gao, Z. Effects of physical activity on children’s motor skill development: A systematic review of randomized controlled trials. BioMed Res. Int. 2020, 2020, 8160756. [Google Scholar] [CrossRef] [PubMed]
  222. McCann, S.; Perapoch Amadó, M.; Moore, S.E. The Role of Iron in Brain Development: A Systematic Review. Nutrients 2020, 12, 2001. [Google Scholar] [CrossRef]
  223. Gutema, B.T.; Sorrie, M.B.; Megersa, N.D.; Yesera, G.E.; Yeshitila, Y.G.; Pauwels, N.S.; De Henauw, S.; Abbeddou, S.; Metwally, A.M. Effects of iron supplementation on cognitive development in school-age children: Systematic review and meta-analysis. PLoS ONE 2023, 18, e0287703. [Google Scholar] [CrossRef] [PubMed]
  224. Giugliani, E.; Horta, B.; Loret de Mola, C.; Lisboa, B.; Victora, C. Effect of breastfeeding promotion interventions on child growth: A systematic review and meta-analysis. Acta Paediatr. 2015, 104, 20–29. [Google Scholar] [CrossRef]
  225. Amaral, M.M.; Herrin, W.E.; Gulere, G.B. Using the Uganda National Panel Survey to analyze the effect of staple food consumption on undernourishment in Ugandan children. BMC Public Health 2017, 18, 32. [Google Scholar] [CrossRef] [PubMed]
  226. Carson, V.; Stearns, J.; Janssen, I. The Relationship Between Parental Physical Activity and Screen Time Behaviors and the Behaviors of their Young Children. Pediatr. Exerc. Sci. 2015, 27, 390–395. [Google Scholar] [CrossRef]
  227. Astiz, M.; Heyde, I.; Fortmann, M.I.; Bossung, V.; Roll, C.; Stein, A.; Grüttner, B.; Göpel, W.; Härtel, C.; Obleser, J.; et al. The circadian phase of antenatal glucocorticoid treatment affects the risk of behavioral disorders. Nat Commun. 2020, 11, 3593. [Google Scholar] [CrossRef] [PubMed]
  228. Kerz, A.; Bell, K.; White, M.; Thompson, A.; Suter, M.; McKechnie, R.; Gallegos, D. Development and preliminary validation of a brief household food insecurity screening tool for paediatric health services in Australia. Health Soc. Care Community 2021, 29, 1538–1549. [Google Scholar] [CrossRef] [PubMed]
  229. Iglesias, L.; Canals, J.; Arija, V. Effects of prenatal iron status on child neurodevelopment and behavior: A systematic review. Crit. Rev. Food Sci. Nutr. 2018, 58, 1604–1614. [Google Scholar] [CrossRef] [PubMed]
  230. Camprubi Robles, M.; Campoy, C.; Garcia Fernandez, L.; Lopez-Pedrosa, J.M.; Rueda, R.; Martin, M.J. Maternal Diabetes and Cognitive Performance in the Offspring: A Systematic Review and Meta-Analysis. PLoS ONE 2015, 10, e0142583. [Google Scholar] [CrossRef]
  231. Arrobas Velilla, T.; Varo Sánchez, G.; Romero García, I.; Melguizo Madrid, E.; Rodríguez Sánchez, F.I.; León Justel, A. Prevalence of severe hypercholesterolemia observed in different hospitals in Andalusia and Ceuta. Clin. Investig. Arter. 2021, 33, 217–223. [Google Scholar] [CrossRef]
  232. Rezaeizadeh, G.; Mansournia, M.A.; Keshtkar, A.; Farahani, Z.; Zarepour, F.; Sharafkhah, M.; Kelishadi, R.; Poustchi, H. Maternal education and its influence on child growth and nutritional status during the first two years of life: A systematic review and meta-analysis. eClinicalMedicine 2024, 71, 102574. [Google Scholar] [CrossRef]
  233. Brooks-Gunn, J.; Klebanov, P.; Smith, J.R.; Lee, K. Effects of combining public assistance and employment on mothers and their young children. Women Health 2001, 32, 179–210. [Google Scholar] [CrossRef] [PubMed]
  234. Sarkadi, A.; Kristiansson, R.; Oberklaid, F.; Bremberg, S. Fathers’ involvement and children’s developmental outcomes: A systematic review of longitudinal studies. Acta Paediatr. 2008, 97, 153–158. [Google Scholar] [CrossRef] [PubMed]
  235. Emmers, D.; Jiang, Q.; Xue, H.; Zhang, Y.; Zhang, Y.; Zhao, Y.; Liu, B.; Dill, S.-E.; Qian, Y.; Warrinnier, N.; et al. Early childhood development and parental training interventions in rural China: A systematic review and meta-analysis. BMJ Glob Health 2021, 6, e005578. [Google Scholar] [CrossRef] [PubMed]
  236. Zhang, L.; Ssewanyana, D.; Martin, M.C.; Lye, S.; Moran, G.; Abubakar, A.; Marfo, K.; Marangu, J.; Proulx, K.; Malti, T. Supporting Child Development Through Parenting Interventions in Low- to Middle-Income Countries: An Updated Systematic Review. Front Public Health 2021, 9, 671988. [Google Scholar] [CrossRef] [PubMed]
  237. Clifford, H.; Telethon Kids, I. Environmental Health Challenges in Remote Aboriginal Australian Communities: Clean Air, Clean Water, and Safe Housing; Telethon Kids Institute: Subiaco, Western Australia, 2013. [Google Scholar]
  238. Ninti One, L. Culture, Housing, Remoteness and Aboriginal and Torres Strait Islander Child Development: Evidence from the Longitudinal Study of Indigenous Children; Ninti One Limited: Alice Springs, Australia, 2017. [Google Scholar]
  239. Kadir, A.; Shenoda, S.; Goldhagen, J.; Pitterman, S. The Effects of Armed Conflict on Children. Pediatrics 2018, 142, e20182586. [Google Scholar] [CrossRef] [PubMed]
  240. Nores, M.; Barnett, W.S. Benefits of early childhood interventions across the world: (Under) Investing in the very young. Econ. Educ. Rev. 2010, 29, 271–282. [Google Scholar] [CrossRef]
  241. Sameroff, A.J. Environmental context of child development. J. Pediatr. 1986, 109, 192–200. [Google Scholar] [CrossRef] [PubMed]
  242. Hagenlocher, M.; Renaud, F.G.; Haas, S.; Sebesvari, Z. Vulnerability and risk of deltaic social-ecological systems exposed to multiple hazards. Sci. Total Environ. 2018, 631, 71–80. [Google Scholar] [CrossRef] [PubMed]
Children 12 01096 g001
Figure 1. Flow diagram of investigating perinatal and early childhood risk factors for adverse early childhood developmental outcomes.
Figure 1. Flow diagram of investigating perinatal and early childhood risk factors for adverse early childhood developmental outcomes.
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Children 12 01096 g002
Figure 2. Summary of risk factors using the socioecological model at the individual, interpersonal, community, and societal levels.
Figure 2. Summary of risk factors using the socioecological model at the individual, interpersonal, community, and societal levels.
Children 12 01096 g002
Children 12 01096 g003
Figure 3. Top 20 most frequently reported risk factors affecting developmental adversities in our systematic review.
Figure 3. Top 20 most frequently reported risk factors affecting developmental adversities in our systematic review.
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Children 12 01096 g004
Figure 4. Risk of bias assessment result of 175 included studies.
Figure 4. Risk of bias assessment result of 175 included studies.
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Table 1. Study characteristics (n = 175).
Table 1. Study characteristics (n = 175).
Study CharacteristicsNumber of Studies Percent
Year of publication
  2021–20247241.14
  2011–20208749.7
  2002–2010169.2
Study country
  Australia3318.9
  Canada1910.9
  US2011.4
  China179.7
  Multi-country ***126.9
  Brazil116.3
  Spain84.6
  UK74
  Bangladesh52.9
  Norway42.3
  Others *3922.3
Study design
  Cohort14482.3
  Cross-sectional1810.3
  Survey126.9
  Case–control10.57
Measurement tools
  Early developmental vulnerability instrument4726.9
  Early development index116.3
  Bayley Scales of Infant Development3821.7
  Age and stage questionnaire2011.4
  Wechsler intelligence, preschool and primary scale 74
  Others **5229.7
* Includes countries with studies less than 4; ** includes measurement tools used in less than 7 studies; *** Lower- and middle-income countries, Canada and Australia, Vietnam and Bangladesh, South Africa and Tanzania, and East Asia and the Pacific: Cambodia, China, Mongolia, and Vanuatu.
Table 2. Adverse Early Childhood Developmental Outcome (n = 175).
Table 2. Adverse Early Childhood Developmental Outcome (n = 175).
Developmental Domains and Specific Outcomes Reported in Each Study Number of Studies
Physical development (n = 115 studies)
Physical health and well-being28
Physical development3
Motor development22
Gross motor development29
Fine motor development 24
Psychomotor developmental index9
Cognitive development (n = 120 studies)
Language and cognitive 28
Cognitive development34
Mental developmental index13
Learning and learning disability, literacy, and numeracy 9
Problem-solving13
Full-scale IQ 10
Verbal IQ 7
Performance IQ6
Language and communication development (n = 90 studies)
Communication and general knowledge 28
Language 27
Expressive language10
Receptive language9
Communication16
Social–emotional development (n = 96 studies)
Social competence30
Emotional maturity 30
Social–emotional development22
Personal social development16
Unspecified subdomains (n = 37 studies)
Developmental vulnerability17
Developmental delay20
The sum of the studies is greater than 175 since some investigated two or more developmental domains.
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Atalell, K.A.; Pereira, G.; Duko, B.; Nyadanu, S.D.; Tessema, G.A. Perinatal and Childhood Risk Factors of Adverse Early Childhood Developmental Outcomes: A Systematic Review Using a Socioecological Model. Children 2025, 12, 1096. https://doi.org/10.3390/children12081096

AMA Style

Atalell KA, Pereira G, Duko B, Nyadanu SD, Tessema GA. Perinatal and Childhood Risk Factors of Adverse Early Childhood Developmental Outcomes: A Systematic Review Using a Socioecological Model. Children. 2025; 12(8):1096. https://doi.org/10.3390/children12081096

Chicago/Turabian Style

Atalell, Kendalem Asmare, Gavin Pereira, Bereket Duko, Sylvester Dodzi Nyadanu, and Gizachew A. Tessema. 2025. "Perinatal and Childhood Risk Factors of Adverse Early Childhood Developmental Outcomes: A Systematic Review Using a Socioecological Model" Children 12, no. 8: 1096. https://doi.org/10.3390/children12081096

APA Style

Atalell, K. A., Pereira, G., Duko, B., Nyadanu, S. D., & Tessema, G. A. (2025). Perinatal and Childhood Risk Factors of Adverse Early Childhood Developmental Outcomes: A Systematic Review Using a Socioecological Model. Children, 12(8), 1096. https://doi.org/10.3390/children12081096

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