Early life cognitive development trajectories and intelligence quotient in middle childhood and early adolescence in rural western china

ABSTRACT The relationship of cognitive developmental trajectories during the dynamic first years with later life development outcomes remains unclear in low- and middle-income countries.

1388 Children born to women who participated in a randomized trial of antenatal micronutrient supplementation in rural China were prospectively followed. Cognitive development was assessed

six times between 3 and 30 months of age using Bayley Scales of Infant Development, and then in mid-childhood (7–9 years) and early adolescence (10–12 years) using Wechsler Intelligence

Scale for Children. We identified four distinct infant cognitive development trajectory subgroups using group-based trajectory modeling: (i) consistently above average, (ii) consistently

average, (iii) started below average and then improved, and (iv) started below average and then declined. LBW infants (<2500 g) were 10.60 times (95% CI 3.57, 31.49) more likely to be in

the trajectory group that started below average and then declined, while each grade increase in maternal education decreased the risk of being in this group by 73% (95% CI 54%, 84%). Infants

who performed consistently above average had 8.02 (95% CI 1.46, 14.59) points higher IQ in adolescence versus the declining trajectory group. These findings suggest that interventions to

improve early child development trajectories may produce long-term human capital benefits. SIMILAR CONTENT BEING VIEWED BY OTHERS STRUCTURED EARLY CHILDHOOD EDUCATION EXPOSURE AND CHILDHOOD

COGNITION – EVIDENCE FROM AN INDIAN BIRTH COHORT Article Open access 05 June 2024 EARLY DIET IN PRETERM INFANTS AND LATER COGNITION: 10-YEAR FOLLOW-UP OF A RANDOMIZED CONTROLLED TRIAL

Article Open access 09 February 2021 DO THE PATHWAYS OF CHILD DEVELOPMENT BEFORE AGE THREE MATTER FOR DEVELOPMENT AT PRIMARY SCHOOL? EVIDENCE FROM RURAL CHINA Article Open access 20 November

2024 INTRODUCTION An estimated 250 million children under five years living in low- and middle- income countries (LMICs) failed to reach their full developmental potential1. Adversities and

risk factors during the first 1000 days of life lay the foundation for development and have long-term consequences across the lifecourse1,2,3,4. Studies have shown that suboptimal childhood

cognitive development is associated with higher risk of coronary heart disease, reduced human capital, and increased risk of mortality and poor health outcomes later in life5,6,7,8. A

number of modifiable risk factors for suboptimal development have been identified including poverty-related factors, inadequate stimulation, environmental and nutritional factors9,10.

Nevertheless, a limitation of studies that examined early life determinants of cognitive development typically only assess children at a single time-point, which does not capture the dynamic

process of child development. In fact, only a few studies from high-income countries focused on preterm infants have assessed cognitive development trajectories in early childhood. One

cohort study from UK and Ireland among 315 extremely preterm births found that impaired cognitive trajectory in infancy persisted into early adulthood and there was no evidence of

catch-up11. In contrast, a study in the US reported catch-up language trajectory from 3 to 12 years among very preterm infants12. To the best of our knowledge, no studies have examined the

relationship of early child development trajectories with later life development outcomes among the general population in LMICs. In this study, we used data from a rural Chinese birth

cohort, in which the cognitive development was assessed at 3, 6, 12, 18, and 24 months during the first two years of life and then at 30 months, middle childhood (7–9 years) and in

adolescence (10–12 years). The main aims of our analysis were to (1) identify distinct trajectories of cognitive development during the first two years of life, (2) examine predictors

associated with these trajectories, and (3) assess whether these trajectories were associated with long-term cognitive outcomes in middle childhood and early adolescence. RESULTS A total of

1388 children were included in group-based trajectory modelling (GBTM) analyses. Baseline characteristics of these participants are presented in Table 1. A total of 669 and 735 of these

participants were followed at middle childhood (7–9 years) and early adolescence (10–12 years), respectively (Supplementary Fig. S1). The mean age at middle childhood and adolescence were

7.8 years (SD ± 0.6) and 11.3 (SD ± 0.6) years, respectively. Most background characteristics were similar between individuals who completed the middle childhood and early adolescence

assessments and those who were lost to follow-up (Supplementary Table S1). IDENTIFICATION OF CHILD DEVELOPMENT TRAJECTORIES DURING THE FIRST TWO YEARS OF LIFE GBTM identified four trajectory

subgroups: (1) “Subgroup 1: Start below average-then decrease” (3.2% of all participants), (2) “Subgroup 2: Start below average-then increase” (10.2%), (3) “Subgroup 3: Consistently

average” (40.3%), (4) “Subgroup 4: Consistently above average” (46.3%). The fit indexes are presented in Supplementary Table S2 and Fig. 1 graphically presents the final trajectories of

cognitive test z scores during the first two years of life. PREDICTORS OF CHILD DEVELOPMENT TRAJECTORY GROUP We then compared the distribution of socioeconomic, pregnancy and birth outcome

characteristics between the trajectory groups (Supplementary Table S3 and Table 2).We determined that children born to mothers with increasing educational level were less likely to be in the

groups that started below average and then declined (RR 0.27, 95% CI 0.16, 0.46), started below average and then improved (RR 0.59, 95% CI 0.41, 0.85) and that performed consistently

average (RR 0.76, 95% CI 0.61, 0.94) than being in the group that performed consistently above average. Greater than 180 days of multiple micronutrients supplementation relative to folic

acid or folic acid plus iron supplementation <180 days during pregnancy was associated with decreased risk of being in group of children who started below average and then improved (RR

0.37, 95% CI 0.16, 0.90) and group of children who performed consistently average (RR 0.63, 95% CI 0.44, 0.89) compared to the group of children performing consistently above average.

Infants who were born low birth weight were 10.60 (95% CI 3.57, 31.49) times more likely to be in group of children who started below and then declined as compared to those who performed

consistently above average. We also examined these associations between Subgroup 1 and 2, and between Subgroup 3 and 4, respectively, and similar predictors were observed (Supplementary

Table S4). RELATIONSHIPS OF DEVELOPMENT TRAJECTORY GROUP WITH MIDDLE CHILDHOOD AND ADOLESCENT DEVELOPMENT OUTCOMES As shown in Table 3, the children who performed consistently above average

during the first 2 years of life had persistently higher test scores in middle childhood and early adolescence. Infants that were consistently above average during the first two years had

8.02 (95% CI 1.46, 14.59) and 2.52 (95% CI 0.62, 4.41) points higher cognitive test scores in adolescence as compared to those who started below average and then declined or those who were

consistently average, respectively. In the adjusted analyses (Table 3), infants in the trajectory group that started below average and then improved and the group that were consistently

average did not differ in cognitive outcomes in middle childhood or adolescence. However, the cognitive deficits of trajectory group that started below average and then declined relative to

group that started below average and then improved persisted into adolescence with an adjusted mean FISQ differences of −6.98 (95% CI −13.47, −0.49). We conducted a sensitivity analysis

using IPW to account for potential bias due to outcome censoring (loss to follow-up) and found there were no qualitative differences in our findings (Supplemental Table 5). We also examined

components of the FSIQ score and found similar associations within the VCI, WMI, PRI and PSI scores (Supplementary Tables S6 and Table S7). RELATIONSHIPS OF SINGLE-TIME POINT BSID-II SCORES

AT 12 AND 24 MONTHS WITH MIDDLE CHILDHOOD AND ADOLESCENT DEVELOPMENT OUTCOMES We observed statistically significant, but weaker correlations magnitude of association, between BSID-II

tertiles and development outcomes in middle childhood and early adolescence (Supplementary Table S8). Young children in the highest tertile of development scores at 12 and 24 months had 2.57

(95% CI: 0.31, 4.82) and 4.67 (95% CI: 2.01, 7.33) points higher scores in early adolescence as compared to those in the lowest tertile, respectively. DISCUSSION We identified four distinct

trajectories of infant cognitive development during the first two years of life in rural China: (1) children who started below average and then declined, (2) children who started below

average and then improved, (3) children who were consistently average and (4) children who performed consistently above average. Higher maternal education and supplementing antenatal

multiple micronutrients beyond 180 days were associated with reduced risk of being in suboptimal development trajectories; while, SGA and low birth weight birth increased the risk of being

in the suboptimal groups. The developmental advantages of Subgroup 4 (consistently above average) over the other three trajectory groups persisted through middle childhood into early

adolescence. In addition, the infants from subgroup 1 (started below average-then decreased) had the lowest test scores in middle childhood and early adolescence. These findings suggest that

infant cognitive development trajectories are robust predictors of children long-term development outcomes. We used a data-driven approach with five repeated measures in generally healthy

children to identify development trajectories. One longitudinal study from Australia reported similar trajectories in aspect of language development between 8 and 48 months of age, which

used the latent class analysis to address the categorized measures13. However, to the best of our knowledge, our study is the first to assess the relationship of early life development with

later life outcomes with these methods. This method advancement shows that trajectory modeling can identify subgroups of children who share similar important longitudinal changes in

development during the first two years of life. We also found the trajectory approach provided greater contrast between infants as compared to single time-point assessment of BSID-II scores.

These subgroups are also not distinct in studies that report development trajectory as age-specific averages11,12. As a result, trajectory modeling may better capture the dynamic process of

child development and thus provide stronger associations with long-term outcomes. We identified a pronounced catch-up pattern in Subgroup 2 (started below average-then increased) that would

have been missed with a single time point assessment. In this study, the catch-up development appeared to start early in infancy and provides additional evidence that the first two years of

life are critical for development. Of note, the catch-up pattern of cognitive development was similar to that of physical growth which also generally starts early in the first months of

life14,15. In addition, our risk factor analyses suggest that a combination of prenatal nutrition, socioeconomic, and environmental factors may affect catch-up development. Although this

finding requires replication in other studies, some studies reported that improvements in exclusive breastfeeding and longer partial breastfeeding were associated with better cognitive

development outcomes later in life16,17. In addition, the identification of Subgroup 1 (started below and then declined) indicates that the trajectory modeling can be used to identify

children with high risk of occurring delayed development. As a result, assessment of cognitive development trends may provide valuable information on children’s development and long-term

outcomes. Our study was also able to explore the early determinants that underlie the heterogeneity in these trajectories, which may help develop intervention strategies to reduce the risk

of high-risk children being in suboptimal trajectories. We found that infants from high-income household wealth were more likely to be in the above average group, which is similar to a study

conducted in the UK among subjects aged 2–1618. In addition, our finding that maternal education could independently act as a beneficial factor for child optimal development was in

agreement with previous studies19,20,21. It has been proposed that higher maternal education level was associated with less maternal depression, better child nutrition status, child-rearing

environment and ability to access and benefit from interventions. As described by the early nutrition programming22, antenatal micronutrient supplementation may improve child development,

but the evidence has been inconsistent in the studies that assessed outcome at a single point23,24,25. In the present study, infants born by women who consumed multiple micronutrients for

180 days or beyond during pregnancy were less likely to be in the suboptimal trajectories. This finding extends the current knowledge on mechanisms underlying the antenatal micronutrient

supplementation and long-term outcomes, which may have been linked during early life but would not be captured using the single-time assessment. We also identified SGA or LBW as another

predictor of development trajectories. These findings are consistent with prior studies26,27. Although some studies with short periods of follow-up reported that the influence of

intrauterine growth restriction on cognitive development appeared to diminish overt time28, our finding and another study from UK and Ireland supported that impaired cognitive trajectories

set in early life might persist into adolescence and early adulthood11. One recent systematic review from South Asia also reported that LBW children (<10 ys) relative to normal children

had 5 points lower cognitive scores with a dose-response relationship29. Further, the differences among them became bigger along with the increasing age29, which was similar to the tendency

observed in Subgroup 1 trajectory, i.e., linearly declining after birth. In the present study, this Subgroup 1 trajectory (started below average and then declined) was characterized by high

risk of occurring preterm, LBW, and/or SGA (Supplementary Table S3). Hence, these findings highlight the programs that aim to reduce the risk of adverse birth outcomes before and during

pregnancy. There remains debate as to the long-term functional outcomes of cognitive tests in infancy in LMIC settings30. After using structural equation model to account for measurement

error with 3 repeated measures among 130 infants, one longitudinal investigation from US reported that infant cognitive function moderately correlated with adolescent development outcomes

with a correlation coefficient of 0.5731, which was higher than that observed in our study (0.18 for 12 months and 0.30 for 24 months, respectively; Supplementary Table S8). Taken together,

these findings suggest that using single-time assessment of infant cognitive development has limitations to predict long-term outcomes and identify high-risk children for delayed

development. In the present study, adolescents from Subgroup 4 (consistently above average) had the highest cognitive test scores, suggesting that the developmental advantages established in

early life could persist through middle childhood into early adolescence. In addition, the infants from subgroup 1 (started below average-then decreased) had the lowest test scores in

middle childhood and early adolescence. These findings suggest that infant cognitive development trajectories are strong predictors of children long-term development outcomes, and highlight

the importance of providing appropriate interventions as early as possible, which could ameliorate restricted development and have important implications for human capital and well-being

across the life course. The results in the present study should be interpreted with a few limitations. First, the follow-up rate for children in middle childhood and adolescence in the

present study was approximately 50% of the original cohort and therefore bias due to dependent censoring is possible. Nevertheless, we found minimal to no differences in background

characteristics for children who had development assessed as compared to those who did not. Besides, a sensitivity analysis using IPW to account for outcome censoring also suggested the main

study findings were robust and the risk of bias due to censoring was likely minimal. Second, the use of data-driven approach allowed us to identify distinct cognitive trajectories over age

and was appropriate for several repeated measurements of the same individuals. However, the trajectory modelling approach shares inherent limitations including that extracting the optimal

number of subgroups, which is a process guided by statistical fit indices and some degree of investigators’ decision, and that the size of each trajectory was produced by the model that may

result in small sizes and consequently limited power to further analysis. Third, the cognitive development trajectories that we identified in our study population in rural China may not be

directly applicable to other settings. Finally, the underlying biological mechanisms between these predictors and cognitive trajectories cannot be examined in the present study. In summary,

we identified groups of distinct trajectories of cognitive development during the first two years of life in rural China. Prospectively, we found that these trajectory groups robustly

predicted development scores through middle childhood into adolescence. In addition, our risk factor analyses indicated that integrated of nutritional, environmental, and educational

interventions during the first 1,000 days of life may affect early life cognitive development trajectories and produce long-term effects on development and human capital across the life

course. METHODS PARTICIPANTS We used data from a prospective birth cohort of children born to women who participated in a randomized, double-blind trial of antenatal micronutrient

supplementation in rural western China. Children were followed in early childhood (age 3 to 30 months), middle childhood (age 7–9 years) and early adolescence (age 10–12 years). Details and

procedures of the trial and follow-up studies have been described elsewhere23,24,25,32. Briefly, all pregnant women across villages from two counties were randomized to take a daily capsule

of either folic acid, folic acid plus iron, or multiple micronutrients between August 2002 and February 2006. In the trial 4604 singleton births occurred, and 1400 births born in 2004–2006

were enrolled in long-term follow-up cohort. A total of 1388 was enrolled after excluding deaths (n = 3), birth defects (n = 7) and disabled parents (n = 2). Among them, 660 were followed at

7–9 years of age between October 2012 and September 2013, and 735 at 10–12 years of age between June 2016 and December 2016 for cognitive assessment. ASSESSMENTS OF COGNITIVE DEVELOPMENT At

the 3, 6, 12, 18, 24- and 30-month visit, mental development (MD) was assessed using a culturally appropriate, and locally validated Chinese version of Bayley Scales of Infant Development

(BSID-II)33. MD raw scores were transformed into age-standardized scores based on the data for infants in US34. In middle childhood and adolescence, we used the Wechsler Intelligence Scale

for Children, Fourth Edition (WISC-IV) to assess cognitive development35. According to Chinese norms of WISC-IV with satisfied reliability and validity, age-standardized full-scale

intelligence quotient (FSIQ), representing the general cognitive development, and aspects of verbal comprehension (VCI), perceptual reasoning (PRI), working memory (WMI), and processing

speed index (PSI) were derived36. Cognitive tests were standardly administered by public health graduates at subjects’ own home, local school or hospital meeting room that were free of

distractions. Field staff administering these cognitive tests were unaware of the socioeconomic background, randomized treatment allocation, birth outcomes or other health status of

participants. COVARIATES Information on socioeconomic status (parental age, occupation, education and household wealth), maternal nutrition status before pregnancy (mid-upper arm

circumference), randomized regimen (folic acid, folic acid plus iron, and multiple micronutrients), maternal parity and birth outcomes (preterm birth, low birth weight [LBW], small for

gestational age [SGA] birth and infant sex) was collected as part of the original trial using standard questionnaire, methods and/or procedures. These details are documented elsewhere23. A

wealth index was established from an inventory of 16 household assets or facilities by principal component analysis, which was then classified into thirds as an indicator of low-, middle-

and high-income households37. Preterm birth was defined as babies born alive before 37 weeks’ gestational age, and low birth weight was defined as a birth weight of less than 2500 g, as per

the World Health Organization (WHO) guidelines38,39. According to Intergrowth standards, SGA birth was defined as birth weight below the 10th percentile of weight-for-age and sex40. Given

our prior findings that multiple micronutrient supplementation could significantly improve cognitive development with the largest benefits observed with supplementation of at least 180

days25, we combined the randomized treatment regimens and duration into a categorical variable, i.e., folic acid or iron/folic acid lasting for <180 days (as reference), iron/folic acid

lasting for ≥180 days, multiple micronutrients lasting for <180 days, and multiple micronutrients lasting for ≥180 days. STATISTICAL ANALYSIS To increase comparability across ages, we

transformed the age-standardized cognitive test scores into z-scores based on age-specific medians and SD within the sample. We then used a group‐based trajectory modelling, specifically the

“traj” macro in Stata, to identify infant cognitive z-score developmental trajectories across 3, 6, 12, 18, and 24 months of age41,42,43. GBTM can identify subgroups of individuals who

share similar patterns of development42,43, and has been used to identify distinct trajectories of body composition and body mass index (BMI) that are associated with risks for obesity,

asthma, morbidity and mortality later in life44,45,46,47,48,49,50,51. Models with two or more subgroups were compared to identify the optimal number of subgroups and shapes that best

characterized the data, with maximum likelihood estimation accounting for missing z scores at any time point. The final model was selected based on general recommendations including: (i)

tests for parameter estimates for linear, quadratic and cubic terms, (ii) Bayesian and Akaike information criterion value, (ii) average of the posterior probabilities of group membership for

individuals assigned to each group, (iv) odds of correct classification based on the posterior probabilities of group membership, and (v) minimizing overlap in confidence intervals (CIs)

while summarizing the distinctive features of the data as parsimonious as possible43. Once the most appropriate trajectories were derived, the subgroup categories variable was used in all

subsequent analyses. Baseline characteristics by the trajectory groups were compared using Chi-squared tests or analysis of variance, and multivariate multinomial logistic regression models.

We then used generalized estimating equations with an independent correlation structure to assess the relationship of the trajectory groups with cognitive development outcomes at 30 months,

middle childhood and early adolescence. To hand the missing data of cognitive outcome in middle childhood and early adolescence and examine its potential to influence the results, we

applied the inverse probability weighting (IPW)52. We also conducted analyses using single-time point Bayley scores at 12 and 24 months to compare the magnitude of association for the GBTM

approach. Age-standardized FSIQ and VCI, WMI, PRI, and PSI scores were taken as the primary and secondary outcomes, respectively. All statistical analyses were performed using Stata 12.0

(Stata Corp, College Station, Texas, USA). ETHICAL APPROVAL The protocols of the original trial and all follow-up studies conformed to the ethical principles of the 1964 Declaration of

Helsinki, and were approved by UNICEF and the ethics committee of Xi’an Jiaotong University Health Science Center. Informed written content from pregnant women, and parents/caregivers, and

oral consent from children were obtained. DATA AVAILABILITY All data generated or analysed during this study are included in this published article (and its Supplementary Information files).

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field work was supported by the National Natural Science Foundation of China (Grant Number 81872633, Lingxia Zeng) and National Key Research and Development Program of China (Grant Number

2017YFC0907200 and 2017YFC0907201, Hong Yan). This study was also supported by the China Scholarship Council (Grant Number 201806280188, Zhonghai Zhu). We also thank Nandita Perumal, PhD

MPH, from the Department of Global Health and Population, Harvard TH Chan School of Public Health for helpful comments and suggestions on an earlier version of the manuscript. AUTHOR

INFORMATION Author notes * These authors contributed equally: Zhonghai Zhu and Suying Chang. AUTHORS AND AFFILIATIONS * Department of Epidemiology and Biostatistics, School of Public Health,

Xi’an Jiaotong University Health Science Center, Xi’an, Shaanxi, 710061, P.R. China Zhonghai Zhu, Qi Qi, Shaoru Li, Mohamed Elhoumed, Hong Yan & Lingxia Zeng * Department of Global

Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA Zhonghai Zhu, Wafaie W. Fawzi & Christopher R. Sudfeld * United Nations Children’s Fund, China Office,

Beijing, 100600, P.R. China Suying Chang * Department of Nutrition and Food Safety Research, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an, Shaanxi, 710061,

P.R. China Yue Cheng * Nutrition and Food Safety Engineering Research Center of Shaanxi Province, Xi’an, 710061, Shaanxi, China Hong Yan * Key Laboratory of Environment and Genes Related to

Diseases, Xi’an Jiaotong University, Ministry of Education, Xi’an, 710061, Shaanxi, China Hong Yan & Lingxia Zeng * School of Public Health, University of Sydney, Sydney, New South

Wales, Australia Michael J. Dibley Authors * Zhonghai Zhu View author publications You can also search for this author inPubMed Google Scholar * Suying Chang View author publications You can

also search for this author inPubMed Google Scholar * Yue Cheng View author publications You can also search for this author inPubMed Google Scholar * Qi Qi View author publications You can

also search for this author inPubMed Google Scholar * Shaoru Li View author publications You can also search for this author inPubMed Google Scholar * Mohamed Elhoumed View author

publications You can also search for this author inPubMed Google Scholar * Hong Yan View author publications You can also search for this author inPubMed Google Scholar * Michael J. Dibley

View author publications You can also search for this author inPubMed Google Scholar * Wafaie W. Fawzi View author publications You can also search for this author inPubMed Google Scholar *

Lingxia Zeng View author publications You can also search for this author inPubMed Google Scholar * Christopher R. Sudfeld View author publications You can also search for this author

inPubMed Google Scholar CONTRIBUTIONS Z.Z., S.C., Y.C., H.Y., M.J.D. and L.Z.: planned and designed the study; Z.Z., Q.Q., S.L. and M.E.: conducted the study; Z.Z., S.C., C.R.S. and W.W.F.:

analyzed data and interpreted results; Z.Z.: wrote the paper; L.Z.: had primary responsibility for final content; and all authors: reviewed, revised and approved the final paper.

CORRESPONDING AUTHOR Correspondence to Lingxia Zeng. ETHICS DECLARATIONS COMPETING INTERESTS Dr. Suying Chang is a nutrition specialist of UNICEF China Office. The other authors have no

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http://creativecommons.org/licenses/by/4.0/. Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Zhu, Z., Chang, S., Cheng, Y. _et al._ Early life cognitive development

trajectories and intelligence quotient in middle childhood and early adolescence in rural western China. _Sci Rep_ 9, 18315 (2019). https://doi.org/10.1038/s41598-019-54755-1 Download

citation * Received: 19 July 2019 * Accepted: 19 November 2019 * Published: 04 December 2019 * DOI: https://doi.org/10.1038/s41598-019-54755-1 SHARE THIS ARTICLE Anyone you share the

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