Abstract
Background: Globally, children still face challenges of early developmental delays. The characteristics and differences of early childhood development (ECD) in economically developed regions remain unclear. Conducting ECD-related analyses based on existing child health management system databases can provide child health care physicians with more rapid and efficient precise monitoring guidance for ECD.
Objective: This study aims to evaluate and compare the ECD characteristics and their influencing factors in megacities of economically developed regions in China.
Methods: This study is a retrospective cohort study, selecting 13,436 children aged 0-3 years registered in the child health management systems of Shanghai and Shenzhen from 2017 to 2020 as the study subjects. Child health care physicians assessed the children's basic demographic information, birth status, and early developmental characteristic data. Comprehensive early childhood development indicators include physical development, gross motor development, and composite developmental indicators of cognition/language/social-emotion/fine motor skills. Statistical analysis methods including descriptive analysis, univariate tests, and multivariate tests were employed to analyze the ECD characteristics in the two regions of Shanghai and Shenzhen, and to compare the consistency and differences in ECD between the two cities.
Results: Among the 13,436 children aged 0-3 years, 10,890 (81.1%) were from Shanghai and 2,546 (18.9%) were from Shenzhen. In terms of physical development, Shenzhen children had higher height and weight development scores and a higher proportion of abnormal anterior fontanelle closure time than Shanghai children (P<0.05). For other dimensions of ECD, only the Shanghai regional database provided coverage, with results showing that Shanghai children's gross motor and composite development levels of cognition/language/social-emotion/fine motor skills were below the expected age-adjusted ability levels. Multiple linear and multivariate Logistic regression analysis results showed that summer or winter birth, birth height, birth weight, and preterm birth were common influencing factors for height development in children from both cities (P<0.05); among these, multiple births had the greatest impact on Shanghai children's height development (β=-0.067), while preterm birth had the greatest impact on Shenzhen children's height development (β=0.094). Winter birth, birth height, and preterm birth were common influencing factors for weight development in children from both cities (P<0.05); among these, multiple births had the greatest impact on Shanghai children's weight development (β=-0.070), while preterm birth had the greatest impact on Shenzhen children's weight development (β=0.066). Paternal occupation, birth season, birth weight, and gravidity were influencing factors for anterior fontanelle closure time in Shanghai children (P<0.05); among these, summer birth had the greatest impact (B=2.104). Child foreign nationality, unknown paternal occupation, summer or autumn birth, birth height, gestational weeks, and preterm birth were influencing factors for early gross motor development in Shanghai children (P<0.05); among these, preterm birth had the greatest impact (β=0.291). Child migrant population or foreign nationality, mother engaged in professional/technical work, maternal age, birth height, birth weight, gestational weeks, gravidity, cesarean section, preterm birth, and multiple births were influencing factors for early composite development of cognition/language/social-emotion/fine motor skills in Shanghai children (P<0.05); among these, preterm birth had the greatest impact (β=0.310).
Conclusion: The ECD levels in megacities represented by Shanghai and Shenzhen exhibit certain differences; although the influencing mechanisms differ, there are certain commonalities among the influencing factors. Child health care professionals can strengthen monitoring, intervention, and follow-up for children based on parental occupation, household registration type, maternal age, gestational weeks, preterm birth status, etc. Implementing early intervention during pregnancy and immediately after birth may reduce the potential adverse effects of risk factors.
Full Text
Introduction
Early childhood development (ECD) encompasses the holistic development of children across physical, socio-emotional, cognitive, language, and motor domains from conception to age 8 \cite{1}. Research demonstrates that ECD is intimately linked to lifelong health, individual achievement, and overall societal productivity, ultimately shaping intergenerational cycles of national health and social well-being \cite{2}. Consequently, ECD represents a critical global public health priority \cite{3}. Even in developed nations, children remain at risk for developmental delays \cite{4}, while approximately 250 million children under age 5 (43%) in low- and middle-income countries fail to achieve their developmental potential \cite{5}. In China, although substantial progress has been made since 2000 in reducing child malnutrition and developmental stunting \cite{6,7}, challenges persist, including growth retardation and wasting, overweight and obesity \cite{8}, cognitive delays \cite{9}, and motor developmental delays \cite{10}.
Addressing poor ECD outcomes requires identifying risk factors \cite{2,11}. While previous research has extensively examined factors influencing ECD \cite{12}, most studies have focused on single dimensions of ECD \cite{13}, particularly cognitive and motor development, rather than exploring ECD comprehensively. Furthermore, existing research has predominantly concentrated on vulnerable regions \cite{14,15}, with limited investigation of economically developed areas that represent more advanced ECD management practices. Evidence suggests that urbanization may negatively impact ECD, as children in economically developed megacities face more complex environments—such as poorer natural environments and more complicated social and living conditions \cite{16}—creating uncertain effects on ECD. Therefore, in-depth exploration of early developmental characteristics among children in megacities is essential for promoting healthy early development in such contexts.
This study analyzed and compared comprehensive ECD levels and potential influencing factors among children aged 0–3 years in Shanghai and Shenzhen, aiming to provide new evidence for ECD promotion in economically developed regions of China.
1.1 Study Population
Data were extracted from the child health management systems in Shanghai and Shenzhen from 2017 to 2020. Shanghai data were obtained from two administrative districts representing urban, suburban, and peri-urban areas, while Shenzhen data came from a specialized maternal and child healthcare hospital serving children citywide, ensuring balanced and comparable datasets. Based on a 95% confidence level, 0.01 margin of error, and an estimated ECD delay rate of 16.0% in China's most developed regions \cite{6}, the minimum required sample size was calculated as 5,164. Ultimately, using convenience sampling, 13,436 children aged 0–3 years were included, with 10,890 from Shanghai and 2,546 from Shenzhen.
Inclusion criteria were: (1) continuous, complete records in the system; (2) absence of major diseases or disabilities. Exclusion criterion was incomplete system records. The study was approved by the Ethics Committee of the School of Public Health, Shanghai Jiao Tong University School of Medicine (Approval No.: SJUPN-202109), with informed consent waived.
1.2 Data Collection
Given that China's ECD database has not yet achieved national standardization, this study extracted the following indicators monitored in Shanghai and Shenzhen for comparison: demographic information, birth status indicators, and comprehensive ECD indicators. Demographic information included child sex, household registration type, parental occupation, and parental age. Birth status indicators comprised birth season, birth height, birth weight, gestational weeks, gravidity, parity, delivery mode, premature birth status, and multiple birth status. Comprehensive ECD indicators encompassed physical development, gross motor development, and integrated cognitive/language/socio-emotional/fine motor development.
1.3 ECD Assessment
All comprehensive ECD assessment results included in this study were obtained through professional evaluation by child healthcare physicians. Physicians conducting ECD assessments in both Shanghai and Shenzhen were systematically educated, trained, and certified. Physical development indicators in early childhood included height, weight, and anterior fontanelle closure time. Height and weight for children under 6 were evaluated using the "Shanghai-2015" and "WHO-2006" standards, respectively—both well-established, locally validated standards supported by years of practice and research \cite{17,18}. Since children were assessed at different ages with varying numerical values, comparing only the latest or average values would be inappropriate. Therefore, this study employed percentile scoring and weighting methods to eliminate comparability issues arising from age differences.
1.3.1 Height and Weight
In the child health management systems of Shanghai and Shenzhen, each monitoring value automatically corresponded to a percentile interval: P97. Based on these percentiles, each monitoring value was assigned a score: -1 for height/weight below P3, 0–4 for P3–P10 through P80–P97, and 5 for values above P97. For a child with N height or weight measurements, the total score was (X1+X2+…+Xn), with the maximum possible score of 4N within the normal range (P3–P97). Thus, a child's height or weight development level was calculated as (X1+X2+…+Xn)/4N, representing the developmental level relative to the maximum score. This scoring and calculation method enabled comparison across children of different ages, with higher scores indicating greater height or weight.
1.3.2 Anterior Fontanelle Closure Time
Anterior fontanelle development was assessed based on closure time. Evidence from nine Chinese cities indicates normal closure occurs between 6.6 and 22.4 months of age \cite{19}. Closure within this range was considered normal development. For children under 22.4 months without observed closure, this was assessed as a normal non-closure stage. Closure before 6.6 months was classified as premature, while closure after 22.4 months was considered delayed.
1.3.3 Gross Motor and Integrated Cognitive/Language/Socio-emotional/Fine Motor Development
Early gross motor development and integrated cognitive/language/socio-emotional/fine motor development were assessed by physicians using the Denver Development Screening Test II (DDST-II) \cite{20}, a scale whose sensitivity, specificity, false positive rate, false negative rate, correct diagnosis rate, and concordance rate have been validated internationally and domestically \cite{21}. Physicians recorded children's ability levels and corresponding chronological age (i.e., "measurement age") at each assessment, enabling calculation of the difference between measurement age and actual age as the ability development score. Gross motor and integrated development levels were calculated as the mean of scores across assessments, with negative scores indicating developmental delay, positive scores indicating advanced development, and higher scores representing better developmental levels.
1.4 Statistical Methods
Statistical analysis was performed using IBM SPSS Statistics (v.22.0). Descriptive analysis characterized children's basic features. Continuous data following normal distribution were expressed as (x̄±s), with independent samples t-tests for between-group comparisons. Categorical data were presented as frequencies and percentages, with chi-square tests for group comparisons. Univariate analysis using t-tests, one-way ANOVA, Pearson correlation, and chi-square tests examined associations between individual factors and ECD. Finally, factors with statistical significance in univariate analysis were included in multiple linear regression or logistic regression models to analyze ECD influencing factors. Multicollinearity was assessed using variance inflation factor (VIF), with VIF <5 indicating no significant multicollinearity. P<0.05 was considered statistically significant.
Results
2.1 Comparison of Basic Characteristics Between Shanghai and Shenzhen Children
Among 13,436 children aged 0–3 years, 10,890 (81.1%) were from Shanghai and 2,546 (18.9%) from Shenzhen. No significant differences were found in sex or birth height between Shanghai and Shenzhen children (P>0.05). However, significant differences were observed in household registration type, maternal occupation, maternal age, birth season, birth weight, gestational weeks, gravidity, delivery mode, premature birth status, and multiple birth status (P<0.05) [TABLE:1].
2.2 Comparison of ECD Characteristics Between Shanghai and Shenzhen Children
In physical development, significant differences were found in height development scores, weight development scores, and anterior fontanelle closure time proportions between Shanghai and Shenzhen children (P<0.05). Specifically, Shenzhen children had higher height and weight development scores and higher rates of abnormal anterior fontanelle closure times compared to Shanghai children (P<0.05). In other ECD dimensions, only the Shanghai database provided coverage. Results showed that Shanghai children's gross motor development (-0.2±0.3) and integrated cognitive/language/socio-emotional/fine motor development (-0.2±0.5) both lagged behind age-adjusted expected levels (0.0) [TABLE:2].
2.3 Influencing Factors of ECD
2.3.1 Influencing Factors of Early Height Development
Univariate analysis showed Shanghai children's height development scores were correlated with sex, household registration type, paternal occupation, maternal occupation, birth season, birth height, birth weight, gestational weeks, gravidity, parity, delivery mode, premature birth status, and multiple birth status (P<0.05) [TABLE:3]. Multivariate analysis with VIF values <5 (1.012–3.530) revealed that child sex, floating population status, summer or winter birth, birth height, birth weight, gestational weeks, gravidity, parity, multiple births, and premature birth were influencing factors for Shanghai children's height development (P<0.05), with multiple births having the greatest effect (β=-0.067) [TABLE:4].
Univariate analysis showed Shenzhen children's height development scores were correlated with maternal occupation, birth season, birth height, birth weight, gestational weeks, gravidity, and premature birth status (P<0.05) [TABLE:3]. Multivariate analysis with VIF values <5 (1.005–4.402) indicated that summer or winter birth, birth height, birth weight, and premature birth were influencing factors for Shenzhen children's height development (P<0.05), with premature birth having the greatest effect (β=0.094) [TABLE:5].
2.3.2 Influencing Factors of Early Weight Development
Univariate analysis revealed Shanghai children's weight development scores were correlated with household registration type, paternal occupation, maternal occupation, birth season, birth height, gestational weeks, gravidity, parity, delivery mode, premature birth status, and multiple births (P<0.05) [TABLE:3]. Multivariate analysis with VIF values <5 (1.004–3.520) showed that winter birth, birth height, gestational weeks, parity, premature birth status, and multiple births influenced Shanghai children's weight development (P<0.05), with multiple births having the greatest effect (β=-0.070) [TABLE:4].
Univariate analysis indicated Shenzhen children's weight development scores were correlated with maternal occupation, birth season, birth height, birth weight, gestational weeks, gravidity, and premature birth status (P<0.05) [TABLE:3]. Multivariate analysis with VIF values <5 (1.005–4.402) demonstrated that summer or winter birth, birth height, birth weight, and premature birth influenced Shenzhen children's weight development (P<0.05), with premature birth having the greatest effect (β=0.066) [TABLE:5].
2.3.3 Influencing Factors of Anterior Fontanelle Closure Time
Univariate analysis showed Shanghai children's anterior fontanelle closure time was correlated with household registration type, paternal occupation, maternal occupation, maternal age, birth season, birth weight, gravidity, and delivery mode (P<0.05) [TABLE:3]. Multivariate analysis with VIF values <5 (1.060–2.784) revealed that paternal occupation in business/services or production/transport operations, birth in summer/autumn/winter, birth weight, and gravidity influenced Shanghai children's anterior fontanelle closure time (P<0.05), with summer birth having the greatest effect (B=2.104) [TABLE:4].
Univariate analysis found no correlation between Shenzhen children's anterior fontanelle closure time and any factors (P>0.05) [TABLE:3].
2.3.4 Influencing Factors of Early Gross Motor Development
Univariate analysis indicated Shanghai children's early gross motor development scores were correlated with household registration type, paternal occupation, maternal occupation, birth season, birth height, gestational weeks, gravidity, parity, delivery mode, premature birth status, and multiple births (P<0.05) [TABLE:3]. Multivariate analysis with VIF values <5 (1.095–3.524) showed that foreign nationality, unknown paternal occupation, summer or autumn birth, birth height, gestational weeks, and premature birth influenced Shanghai children's early gross motor development (P<0.05), with premature birth having the greatest effect (β=0.291) [TABLE:4].
2.3.5 Influencing Factors of Integrated Cognitive/Language/Socio-emotional/Fine Motor Development
Univariate analysis revealed Shanghai children's integrated cognitive/language/socio-emotional/fine motor development scores were correlated with household registration type, paternal occupation, maternal occupation, maternal age, birth season, birth height, birth weight, gestational weeks, gravidity, parity, premature birth status, and multiple births (P<0.05) [TABLE:3]. Multivariate analysis with VIF values <5 (1.144–3.327) demonstrated that floating population or foreign nationality, maternal professional/technical work, maternal age, birth height, birth weight, gestational weeks, gravidity, cesarean delivery, premature birth, and multiple births influenced Shanghai children's integrated development (P<0.05), with premature birth having the greatest effect (β=0.310) [TABLE:4].
Discussion
This study focused on ECD in megacities, describing and comparing the current status and influencing factors in representative metropolitan areas to provide new evidence for ECD promotion in economically developed regions of China. The findings revealed that Shenzhen children had higher height and weight development scores and higher rates of abnormal anterior fontanelle closure times compared to Shanghai children. Shanghai children lagged behind age-adjusted standards in both gross motor development and integrated cognitive/language/socio-emotional/fine motor development. While mechanisms underlying these differences varied, influencing factors showed certain commonalities, primarily related to children's and parents' demographic characteristics, birth characteristics, and maternal factors.
Consistent with previous research, maternal age, birth weight, and premature birth status were widely recognized as key influencing factors for ECD \cite{12,22-24}. However, unlike other studies, this research utilized existing child health management system databases rather than surveys of socioeconomic and family environmental factors, enabling healthcare professionals in other regions to more rapidly and conveniently identify children at high risk for developmental delays based on their own administrative data.
The study found that children whose mothers worked in professional/technical positions and those whose fathers worked in business/services or production/transport operations were more likely to experience delays in integrated cognitive/language/socio-emotional/fine motor development and abnormal anterior fontanelle closure. Parental occupation has been identified as an important predictor of ECD \cite{25}, likely related to family socioeconomic status and time spent in parent-child interaction. Parents in high-skill occupations may have stronger capacities to absorb new knowledge and parenting information, potentially paying greater attention to children's holistic development \cite{26}. However, parents in lower-status, lower-wage, less stable jobs often have reduced time for child accompaniment \cite{27}, negatively impacting language, mathematics, and social development \cite{28}. Therefore, parental investment in parenting, particularly ensuring adequate parent-child interaction time, generally positively affects child development \cite{29}. Child healthcare professionals should implement precise, differentiated interventions based on parental occupation and family background. For parents in professional/technical occupations who may face challenges of long or irregular working hours reducing interaction time, healthcare providers could consider community-based parenting activities, training, supervision, home visits, or communication feedback to ensure these parents devote more time to interacting with their children \cite{30}. For parents in business/services or production/transport operations, high-quality electronic media content may be beneficial \cite{31}, though frequent electronic media exposure without parent-child interaction can completely offset these benefits and significantly negatively impact ECD \cite{32,33}, with these adverse effects being more pronounced in low socioeconomic status families \cite{34}. Therefore, child healthcare professionals should provide more professional guidance on parent-child interaction and media application when recommending electronic media to promote ECD in such families \cite{30}.
Notably, the impact of paternal occupation on ECD is not highly consistent across countries and regions, with conflicting findings. For example, a survey across 12 Chinese cities found no significant effect of paternal occupation type on early socio-emotional development \cite{35}; a Philippine study indicated no significant role of paternal occupation in early cognitive development \cite{36}; and a Canadian cohort study concluded paternal occupation was not a predictor of early socio-emotional development \cite{37}. Given that missing paternal occupational data in Shenzhen limited analysis and comparison, and considering the general neglect of paternal occupation in most existing research \cite{38}, further evidence and discussion from more regions are needed regarding paternal occupation's influence on ECD.
In Shenzhen, where height and weight development scores were higher, the proportion of abnormal anterior fontanelle closure times was also higher, indirectly suggesting an association between fontanelle development and physical growth in early childhood. While previous research on this association is limited and lacks consistent conclusions, a retrospective cohort study of 140,000 preschool children in China found that earlier anterior fontanelle closure was associated with faster early height development \cite{39}, and a cross-sectional study across nine Chinese cities also indicated that children with earlier fontanelle closure had significantly greater height and weight than those with later closure \cite{40}. These findings align with our results: Shenzhen children had earlier anterior fontanelle closure times and correspondingly higher height development scores. This suggests child healthcare professionals could implement more targeted interventions for early height development by monitoring fontanelle closure time, such as enhanced nutritional interventions for children with early closure and dietary and exercise interventions for those with delayed closure to reduce potential height delays \cite{39}. Additionally, this study found significant associations between anterior fontanelle closure time and birth season, birth weight, gravidity, and paternal occupation in Shanghai, though these were not verified in Shenzhen, and existing research has not adequately explored these factors. Further evidence from different countries and regions is needed to substantiate these findings.
Maternal characteristics represent a particularly critical factor requiring attention in ECD, as their adverse effects may be reduced or eliminated through effective education and intervention. First, older maternal age was a protective factor for comprehensive child development, possibly because these mothers had more years of parenting education and experience, promoting healthier prenatal environments and postnatal environments more conducive to early development \cite{41}. Second, higher gravidity negatively impacted ECD, potentially related to maternal nutritional status \cite{42}, making women with more pregnancies priority targets for ECD interventions \cite{43}. Third, parity showed opposite effects to gravidity, with multiparous women more likely to achieve early breastfeeding initiation after delivery. This finding highlights the multiple benefits of breastfeeding for immune, cognitive, and motor development \cite{44}, underscoring the need for more effective breastfeeding education during prenatal care and parenting support to help mothers provide high-quality infant feeding at appropriate times.
In addition to these modifiable factors, the study identified several difficult-to-intervene risk factors. (1) Although premature birth significantly negatively impacted all dimensions of early child development \cite{45,46}, few interventions can prevent preterm birth. To minimize these adverse effects, child healthcare professionals should implement early intervention as soon as possible after preterm infants' birth—even within hours or days—as this can significantly reduce early emotional and behavioral problems and improve motor and/or cognitive abilities \cite{47,48}. (2) Birth weight, birth height, and delivery mode also influenced ECD levels. Expanding the timeframe for prenatal and postpartum 42-day visits with more precise interventions could yield additional benefits. For example, nutritional interventions and dietary/exercise guidance for high-risk pregnant women can help prevent low birth weight and macrosomia, effectively reducing cesarean delivery rates and improving neonatal outcomes \cite{49}. (3) For birth season, which was associated with poorer ECD outcomes, early postnatal intervention could enhance parenting guidance and follow-up for children born in different seasons. For instance, infants born in winter have more opportunities for environmental stimulation and sustained outdoor activities at 6 months, contributing to higher cognitive and motor development \cite{50}, whereas summer-born infants may require more interventions to mitigate seasonal disadvantages.
This study included only 34 foreign children in Shanghai, and although these children showed generally poor ECD outcomes except in physical development, the small sample size necessitates further validation.
Limitations
This study has several limitations. (1) As data were derived from existing child health management system databases, some factors with significant impact on ECD were not included. (2) The lack of national standardization for child health management systems limited comparisons to physical development characteristics between Shanghai and Shenzhen; comparisons in other dimensions could not be completed. (3) Quality variations across regional systems led to missing important data (e.g., paternal occupation and age, maternal parity in Shenzhen) and unreasonable data entry settings (e.g., unspecified maternal occupation types), reducing accuracy and comparability of some findings. (4) ECD assessment data recorded in current management systems did not distinguish among cognitive, language, socio-emotional, and fine motor development, limiting precise evaluation. (5) The Shanghai-to-Shenzhen sample ratio was approximately 4:1, with Shenzhen's sample size being relatively small. While this ratio meets minimum requirements for statistical power \cite{51} and the overall sample size was large, expanding Shenzhen's sample size in future research would enhance statistical power. (6) The study only compared two coastal megacities (Shanghai and Shenzhen), lacking comparative evidence from other megacities in central and western China (e.g., Beijing), which somewhat limits the generalizability of findings. Future research should introduce operationally feasible assessment tools for both providers and users within current management systems and expand application to more regions to enable multi-dimensional, multi-regional ECD evaluation and multi-center comparisons. (7) The study only included 34 foreign children in Shanghai, and although these children showed poor ECD outcomes beyond physical development, the small sample size requires further validation.
Conclusion
ECD levels in Chinese megacities such as Shanghai and Shenzhen demonstrate notable variations: Shenzhen children had higher height and weight scores with higher rates of abnormal anterior fontanelle closure, while Shanghai children lagged behind age-adjusted standards in gross motor and integrated cognitive/language/socio-emotional/fine motor development. Influencing factors show certain commonalities despite differing mechanisms, primarily related to biological factors (premature birth, birth weight and height, delivery mode, birth season) and social-environmental factors (maternal age, parental occupation). Child healthcare professionals should implement more precise interventions for more vulnerable children, parents in high-risk occupations, and high-risk mothers based on factor-specific mechanisms and effect sizes. For risk factors that are difficult to prevent, early intervention during pregnancy and immediately after birth may reduce adverse effects.
Author Contributions: LIU Xiang conceptualized the study, designed the research protocol, proposed the comparative research proposition for megacity ECD, oversaw implementation, validated statistical results, and drafted the manuscript. CHEN Hong performed data cleaning, descriptive, univariate, and multivariate statistical analyses, and revised the manuscript. CUI Rui, GUO Zhichao, LI Panpan, CAO Zilong, and JI Yiqing contributed to data collection, validation, cleaning, and manuscript revision. YU Wenya was responsible for final version revision and overall accountability for the manuscript.
Conflict of Interest: The authors declare no conflict of interest.
ORCID IDs: LIU Xiang https://orcid.org/0009-0009-1412-602X; YU Wenya https://orcid.org/0000-0003-4605-9158
References
\cite{1} UNICEF. Integrated approaches to early childhood development: 0-3 years\allowbreak[EB/OL]. (2017-09)\allowbreak[2025-03-14]. https://www.unicef.cn/en/reports/integrated-approaches-early-childhood-development-0-3-years.
\cite{2} GRANTHAM-MCGREGOR S, CHEUNG Y B, CUETO S, et al. Developmental potential in the first 5 years for children in developing countries\allowbreak[J]. Lancet, 2007, 369(9555): 60-70. DOI: 10.1016/S0140-6736(07)60032-4.
\cite{3} BLACK M M, WALKER S P, FERNALD L C H, et al. Early childhood development coming of age: science through the life course\allowbreak[J]. Lancet, 2017, 389(10064): 77-90. DOI: 10.1016/S0140-6736(16)31389-7.
\cite{4} BRIAN A, PENNELL A, TAUNTON S, et al. Motor competence levels and developmental delay in early childhood: a multicenter cross-sectional study conducted in the USA\allowbreak[J]. Sports Med, 2019, 49(10): 1609-1618. DOI: 10.1007/s40279-019-01150-8.
\cite{5} DAELMANS B, DARMSTADT G L, LOMBARDI J, et al. Early childhood development: the foundation of sustainable development\allowbreak[J]. Lancet, 2017, 389(10064): 9-11. DOI: 10.1016/S0140-6736(16)31659-2.
\cite{6} ZHANG Y T, KANG L, ZHAO J, et al. Assessing the inequality of early child development in China - a population-based study\allowbreak[J]. Lancet Reg Health West Pac, 2021, 14: 100221. DOI: 10.1016/j.lanwpc.2021.100221.
\cite{7} WANG Y P, LI X H, ZHOU M G, et al. Under-5 mortality in 2851 Chinese Counties, 1996-2012: a subnational assessment of achieving MDG 4 goals in China\allowbreak[J]. Lancet, 2016, 387(10015): 273-283. DOI: 10.1016/S0140-6736(15)00554-1.
\cite{8} LIU Y, WANG Y Y, CHENG Y, et al. Growth and development of children and related influencing factors: a cross-sectional study of the families with children aged 0-6 years in Jiangsu Province\allowbreak[J]. Chin J Contemp Pediatr, 2022, 24(6): 693-698. DOI: 10.7499/j.issn.1008-8830.2202072.
\cite{9} JOHNSTONE H, YANG Y, XUE H, et al. Infant cognitive development and stimulating parenting practices in rural China\allowbreak[J]. Int J Environ Res Public Health, 2021, 18(10): 5277. DOI: 10.3390/ijerph18105277.
\cite{10} LUO R F, SHI Y J, ZHOU H, et al. Micronutrient deficiencies and developmental delays among infants: evidence from a cross-sectional survey in rural China\allowbreak[J]. BMJ Open, 2015, 5(10): e008400. DOI: 10.1136/bmjopen-2015-008400.
\cite{11} GUO Z C, CUI D, BAO J J, et al. Influence of family cognitive environment on early language development in children: a retrospective case-control study in Shanghai\allowbreak[J]. Chin Gen Pract, 2025, 28(1): 53-58.
\cite{12} SANIA A, SUDFELD C R, DANAEI G, et al. Early life risk factors of motor, cognitive and language development: a pooled analysis of studies from low/middle-income countries\allowbreak[J]. BMJ Open, 2019, 9(8): e026449.
\cite{13} CHENG Z X, SHI L, LI Y, et al. Using structural equation modelling to assess factors influencing children's growth and nutrition in rural China\allowbreak[J]. Public Health Nutr, 2018, 21(6): 1167-1175. DOI: 10.1017/S1368980017003494.
\cite{14} IMTIAZ A, HAQ Z U, DOI S A R, et al. Effectiveness of lipid-based nutrient supplementation during the first 1000 days of life for early childhood development: a community-based trial from Pakistan\allowbreak[J]. Matern Child Nutr, 2025, 21(1): e13727. DOI: 10.1111/mcn.13727.
\cite{15} BERLINSKI S, SANZ-DE-GALDEANO A, SÓÑORA-NOYA A. Gender gaps in early childhood development in Latin America and the Caribbean\allowbreak[J]. Econ Hum Biol, 2025, 57: 101472. DOI: 10.1016/j.ehb.2025.101472.
\cite{16} LIU W. The developmental trap, justice crisis, and reflective critique of capitalist "over-urbanization"\allowbreak[J]. J Hebei Agric Univ (Soc Sci Ed), 2025, 27(3): 10-19.
\cite{17} WHO. WHO Child Growth Standards: Length/Height-for-Age, Weight-for-Age, Weight-for-Length, Weight-for-Height and Body Mass Index-for-Age\allowbreak[J]. 2006.
\cite{18} Shanghai Municipal Health and Family Planning Commission. Key points of Shanghai public health (disease prevention and control, maternal and child health, food safety, and health emergency) system construction in 2015\allowbreak[EB/OL]. (2015-03-19)\allowbreak[2025-03-20]. https://wsjkw.sh.gov.cn/zxghjh/20180815/0012-59083.html.
\cite{19} LIU Y, LI H, ZHANG Y Q, et al. Development of anterior fontanelle in Chinese children in 2015\allowbreak[J]. Chin J Pediatr, 2017, 55(8): 602-607. DOI: 10.3760/cma.j.issn.0578-1310.2017.08.011.
\cite{20} SPERHAC A M, SALZER J L. The Denver II\allowbreak[J]. J Am Acad Nurse Pract, 1991, 3(4): 152-157. DOI: 10.1111/j.1745-7599.1991.tb01094.x.
\cite{21} CHEN J Y, WEI M, HE L, et al. Adaptability study of Denver II developmental screening scale in Shanghai\allowbreak[J]. Chin J Child Health Care, 2008, 16(4): 393-394.
\cite{22} OUMER A, FIKRE Z, GIRUM T, et al. Stunting and underweight, but not wasting are associated with delay in child development in southwest Ethiopia\allowbreak[J]. Pediatric Health Med Ther, 2022, 13: 1-12. DOI: 10.2147/PHMT.S344715.
\cite{23} RAO N, COHRSSEN C, SUN J, et al. Early child development in low- and middle-income countries: Is it what mothers have or what they do that makes a difference to child outcomes\allowbreak[J]. Adv Child Dev Behav, 2021, 61: 255-277. DOI: 10.1016/bs.acdb.2021.04.002.
\cite{24} WANG L, CHEN Y F, SYLVIA S, et al. Trajectories of child cognitive development during ages 0-3 in rural Western China: prevalence, risk factors and links to preschool-age cognition\allowbreak[J]. BMC Pediatr, 2021, 21(1): 199. DOI: 10.1186/s12887-021-02650-y.
\cite{25} BRADLEY R H, CORWYN R F. Socioeconomic status and child development\allowbreak[J]. Annu Rev Psychol, 2002, 53: 371-399. DOI: 10.1146/annurev.psych.53.100901.135233.
\cite{26} MCHOME Z, BAILEY A, DARAK S, et al. "A child may be tall but stunted." Meanings attached to childhood height in Tanzania\allowbreak[J]. Matern Child Nutr, 2019, 15(3): e12769. DOI: 10.1111/mcn.12769.
\cite{27} LIANG W Y, YE X M, LI T. How does Parental Involvement Affect the Cognitive Ability of Migrant Children: An Empirical Study Based on CEPS Database\allowbreak[J]. Journal of Educational Studies, 2021, 17(3): 85-96.
\cite{28} YEO L S, ONG W W, NG C M. The home literacy environment and preschool children's reading skills and interest\allowbreak[J]. Early Child Dev Care, 2014, 184(12): 1911-1924. DOI: 10.1080/10409289.2014.862147.
\cite{29} DEL BOCA D, MONFARDINI C, NICOLETTI C. Parental and child time investments and the cognitive development of adolescents\allowbreak[J]. J Labor Econ, 2017, 35(2): 565-608. DOI: 10.1086/689479.
\cite{30} JEONG J, BLIZNASHKA L, AHUN M N, et al. A pilot to promote early child development within health systems in Mozambique: a qualitative evaluation\allowbreak[J]. Ann N Y Acad Sci, 2022, 1509(1): 161-183. DOI: 10.1111/nyas.14718.
\cite{31} RICE M L, HUSTON A C, TRUGLIO R, et al. Words from "Sesame Street"\allowbreak[J]. 1990.
\cite{32} MADIGAN S, BROWNE D, RACINE N, et al. Association between screen time and children's performance on a developmental screening test\allowbreak[J]. JAMA Pediatr, 2019, 173(3): 244-250. DOI: 10.1001/jamapediatrics.2018.5056.
\cite{33} POULAIN T, VOGEL M, NEEF M, et al. Reciprocal associations between electronic media use and behavioral difficulties in preschoolers\allowbreak[J]. Int J Environ Res Public Health, 2018, 15(4): 814. DOI: 10.3390/ijerph15040814.
\cite{34} Guidelines on physical activity, sedentary behaviour and sleep for children under 5 years of age\allowbreak[M]. Geneva: World Health Organization, 2019. PMID: 31091057.
\cite{35} LIU C, WU X C, ZOU S Q. Parents' relative socioeconomic status and paternal involvement in Chinese families: the mediating role of coparenting\allowbreak[J]. Front Psychol, 2016, 7: 940. DOI: 10.3389/fpsyg.2016.00940.
\cite{36} NORORI N, BARRASS L, REDANIEL M T, et al. Assessing the impact of paternal emigration on children 'left-behind'-a cohort analysis\allowbreak[J]. J Migr Health, 2025, 11: 100308. DOI: 10.1016/j.jmh.2025.100308.
\cite{37} STEPHENSON N, TOUGH S, MCMORRIS C, et al. Childcare use and the social-emotional and behavioural outcomes of late-preterm and early-term born children at age 5: an analysis of the All Our Families longitudinal cohort\allowbreak[J]. Can J Public Health, 2024, 115(6): 980-991. DOI: 10.17269/s41997-024-00891-8.
\cite{38} PERRY-JENKINS M, LAWS H B, SAYER A, et al. Parents' work and children's development: a longitudinal investigation of working-class families\allowbreak[J]. J Fam Psychol, 2020, 34(3): 257-268. DOI: 10.1037/fam0000580.
\cite{39} MEI H, CAI X N, XIA Z G, et al. Association between anterior fontanelle closure timing and height development trajectory in preschool children\allowbreak[J]. Mod Prev Med, 2021, 48(19): 3509-3514, 3523. DOI: 10.20043/j.cnki.mpm.2021.19.012.
\cite{40} LIU Y, LI H, ZHANG Y Q, et al. Investigation on anterior fontanelle development in infants and young children in nine cities in 2015\allowbreak[J]. Chin J Pediatr, 2017, 55(8): 602-607. DOI: 10.3760/cma.j.issn.0578-1310.2017.08.011.
\cite{41} DUNCAN G J, LEE K T H, ROSALES-RUEDA M, et al. Maternal age and child development\allowbreak[J]. Demography, 2018, 55(6): 2229-2255. DOI: 10.1007/s13524-018-0730-3.
\cite{42} MCLENNAN A S, GYAMFI-BANNERMAN C, ANANTH C V, et al. The role of maternal age in twin pregnancy outcomes\allowbreak[J]. Am J Obstet Gynecol, 2017, 217(1): 80.e1-80.e8. DOI: 10.1016/j.ajog.2017.03.002.
\cite{43} NEVES R O, BERNARDI J R, SILVA C H D, et al. Can parity influence infant feeding in the first six months of life\allowbreak[J]. Cien Saude Colet, 2020, 25(11): 4593-4600. DOI: 10.1590/1413-812320202511.32882018.
\cite{44} HERNÁNDEZ LUENGO M, ÁLVAREZ-BUENO C, POZUELO-CARRASCOSA D P, et al. Relationship between breast feeding and motor development in children: protocol for a systematic review and meta-analysis\allowbreak[J]. BMJ Open, 2019, 9(9): e029063. DOI: 10.1136/bmjopen-2019-029063.
\cite{45} MANACERO S, NUNES M L. Longitudinal study of sleep behavior and motor development in low-birth-weight preterm children from infancy to preschool years\allowbreak[J]. J Pediatr (Rio J), 2021, 97(1): 44-51. DOI: 10.1016/j.jped.2019.10.010.
\cite{46} CHEONG J L, DOYLE L W, BURNETT A C, et al. Association between moderate and late preterm birth and neurodevelopment and social-emotional development at age 2 years\allowbreak[J]. JAMA Pediatr, 2017, 171(7): 678-687. DOI: 10.1001/jamapediatrics.2016.4805.
\cite{47} SILVEIRA R C, MENDES E W, FUENTEFRIA R N, et al. Early intervention program for very low birth weight preterm infants and their parents: a study protocol\allowbreak[J]. BMC Pediatr, 2018, 18(1): 268. DOI: 10.1186/s12887-018-1240-6.
\cite{48} DENNEY J M, CULHANE J F, GOLDENBERG R L. Prevention of preterm birth\allowbreak[J]. Womens Health (Lond), 2008, 4(6): 625-638. DOI: 10.2217/17455057.4.6.625.
\cite{49} ZHANG X F, WU Y D, MIAO L Y. Study on the effects of individualized nutritional intervention on pregnancy outcome and neonatal immune function in patients with gestational diabetes mellitus\allowbreak[J]. Biomed Res Int, 2022, 2022: 3246784. DOI: 10.1155/2022/3246784.
\cite{50} BAI Y, SHANG G, WANG L, et al. The relationship between birth season and early childhood development: Evidence from northwest rural China\allowbreak[J]. PLoS One, 2018, 13(10): e0205281. DOI: 10.1371/journal.pone.0205281.
\cite{51} LIANG Q H, YU X L, AN S L. Impact of sample size in each group on test power under unbalanced design of quantitative data\allowbreak[J]. J South Med Univ, 2020, 40(5): 754-757.
(Received: 2025-04-02; Revised: 2025-09-22)
(Editor: KANG Yanhui)