Association of Antenatal Micronutrient Supplementation With Adolescent Intellectual Development in Rural Western China: 14-Year Follow-up From a Randomized Clinical Trial

Zhonghai Zhu; Yue Cheng; Lingxia Zeng; Mohamed Elhoumed; Guobin He; Wenhao Li; Min Zhang; Wenjing Li; Danyang Li; Sintayehu Tsegaye; Suying Chang; Hong Yan; Emma Yu Wang; Duolao Wang; Shabbar Jaffar; Michael J Dibley

doi:10.1001/jamapediatrics.2018.1401

. 2018 Jul 9;172(9):832–841. doi: 10.1001/jamapediatrics.2018.1401

Association of Antenatal Micronutrient Supplementation With Adolescent Intellectual Development in Rural Western China

14-Year Follow-up From a Randomized Clinical Trial

Zhonghai Zhu ¹, Yue Cheng ², Lingxia Zeng ^1,^✉, Mohamed Elhoumed ¹, Guobin He ¹, Wenhao Li ¹, Min Zhang ¹, Wenjing Li ¹, Danyang Li ¹, Sintayehu Tsegaye ¹, Suying Chang ³, Hong Yan ^1,⁴, Emma Yu Wang ⁵, Duolao Wang ⁶, Shabbar Jaffar ⁷, Michael J Dibley ⁸

¹Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an, Shaanxi, China

²Department of Nutrition and Food Safety Research, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an, Shaanxi, China

³United Nations Children’s Fund, China Office, Beijing, China

⁴Nutrition and Food Safety Engineering Research Center of Shaanxi Province, Xi’an, Shaanxi, China

⁵Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, London, United Kingdom

⁶Department of Clinic Science, Liverpool School of Tropical Medicine, Liverpool, United Kingdom

⁷Department of International Public Health, Liverpool School of Tropical Medicine, Liverpool, United Kingdom

⁸The Sydney School of Public Health, Faculty of Medicine, The University of Sydney, New South Wales, Australia

Accepted for Publication: April 19, 2018.

^✉

Corresponding Author: Lingxia Zeng, PhD, Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Yanta West Road, Xi’an, Shaanxi 710061, China (tjzlx@mail.xjtu.edu.cn).

Correction: This article was corrected on September 4, 2018, to fix a degree error in the byline, an author affiliation, and an author conflict of interest.

Published Online: July 9, 2018. doi:10.1001/jamapediatrics.2018.1401

Author Contributions: Dr Zeng had full access to all of the data and takes responsibility for the integrity of the data and the accuracy of the data analysis. Mr Zhu and Dr Cheng contributed equally to this work.

Study concept and design: Zhu, Cheng, Zeng, Elhoumed, He, Chang, Yan, D. Wang, Dibley.

Acquisition, analysis, or interpretation of data: Zhu, Cheng, Zeng, Elhoumed, He, Wenhao Li, Zhang, Wenjing Li, D. Li, Tsegaye, Chang, E. Y. Wang, D. Wang, Jaffar.

Drafting of the manuscript: Zhu, Zeng, Elhoumed, He, D. Li, Tsegaye, D. Wang, Jaffar.

Critical revision of the manuscript for important intellectual content: Zhu, Cheng, Zeng, Elhoumed, He, Wenhao Li, Zhang, Wenjing Li, Chang, Yan, E. Y. Wang, D. Wang, Jaffar, Dibley.

Statistical analysis: Zhu, Cheng, Zeng, Elhoumed, He, Tsegaye, E. Y. Wang, D. Wang, Dibley.

Obtained funding: Zeng.

Administrative, technical, or material support: Zhu, Cheng, Zeng, Elhoumed, D. Li, Chang.

Study supervision: Zeng, Dibley.

Conflict of Interest Disclosures: Dr Chang reported being a nutrition specialist at UNICEF (United Nations International Children’s Emergency Fund). China Office. No other disclosures were reported.

Funding/Support: This study was funded by grant 201606285114 from the China Scholarship Council. The field work for this study was funded by UNICEF and by grants 81373019 and 81230016 from the National Natural Science Foundation of China.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: We thank all the women and adolescents who participated in this survey and their families. We are grateful for the support of the local government and the local education bureau. We thank all the field work team members who contributed to the successful implementation of the follow-up study in burning hot summer and chilly winter. Yu Lu, BSc, and Siyuan Ma, BSc, both from the Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, helped with data entry.

^✉

Corresponding author.

PMCID: PMC6143069 PMID: 29987336

Key Points

Question

What is the long-term association of micronutrient supplementation during pregnancy with adolescent offspring intellectual development?

Findings

In this follow-up study of 2118 adolescent offspring of mothers who received supplementation in a randomized clinical trial in rural China, micronutrient supplementation during pregnancy was associated with a significant increase in intellectual development for teenaged children compared with folic acid or folic acid plus iron supplements.

Meaning

These findings suggest that multiple micronutrients need to be considered in the current guidelines revision of antenatal supplementation.

Abstract

Importance

The association of micronutrient supplementation during pregnancy with the intellectual development of adolescent offspring is unknown.

Objective

To assess the long-term association of antenatal micronutrient supplementation with adolescent intellectual development.

Design, Setting, and Participants

This 14-year follow-up study of a randomized clinical trial of micronutrient supplementation in pregnancy was conducted in 2 counties in rural western China in 2118 adolescent offspring (aged 10 to 14 years) of mothers who were randomized to take a daily capsule of either folic acid, folic acid plus iron, or multiple micronutrients from August 1, 2002, through February 28, 2006. Follow-up was conducted from June 1, 2016, through December 31, 2016. Data analyses took place from April 1, 2017, to June 20, 2017.

Main Outcomes and Measures

Adolescent full-scale intelligence quotient and aspects of verbal comprehension, working memory, perceptual reasoning, and processing speed indexes were assessed by the Wechsler Intelligence Scale for Children.

Results

Of 2118 adolescent offspring, 1252 (59.1%) were boys and 866 (40.9%) were girls, with a mean (SD) age of 11.7 (0.87) years, representing 47.2% of the 4488 single live births that were eligible to participate. Compared with folic acid supplementation, multiple micronutrient supplementation was associated with a 1.13-point higher full-scale intelligence quotient (95% CI, 0.15-2.10) and a 2.03-point higher verbal comprehension index (95% CI, 0.61-3.45); similar results were found in comparison with folic acid plus iron. When mothers initiated supplementation early (<12 weeks of gestation) and had an adequate dose (≥180 capsules), multiple micronutrient capsules were associated with a 2.16-point higher full-scale intelligence quotient (95% CI, 0.41-3.90) and 4.29-point higher verbal comprehension index (95% CI, 1.33-7.24) compared with folic acid capsules. The mean test scores were lower in the substratum of supplementation initiated late (≥12 weeks of gestation) and with an inadequate dose (<180 capsules). The multiple micronutrient group had higher scores than the other 2 treatment groups, and significant differences were observed for full-scale intelligence quotient (adjusted mean difference, 2.46; 95% CI, 0.98-3.94) when compared with the folic acid plus iron group.

Conclusions and Relevance

Compared with folic acid plus iron or folic acid capsules supplementation, antenatal multiple micronutrient supplementation appeared to be associated with increased adolescent intellectual development; initiating supplementation in the first trimester and then continuing for at least 180 days were associated with the greatest rewards.

Trial Registration

isrctn.org Identifier: ISRCTN08850194

This follow-up study of a randomized clinical trial examines the association between the micronutrient supplementation received by pregnant mothers in rural western China and the intelligence level of their offspring 14 years later.

Introduction

Two hundred fifty million children in low- and middle-income countries are at risk for intellectual impairment.¹ Nutrition plays a key role in the structural and functional development of the human brain from conception to adolescence. In countries where micronutrient deficiencies are common,² the inability to fulﬁll the increased requirements for micronutrients during pregnancy is potentially adverse to child development.^2,3

Nutritional intervention is a cost-effective approach to improving child development.⁴ Interventions can be introduced at any stage, but evidence shows that antenatal micronutrient supplementation would help maximize cognitive development throughout life.⁵ The association of micronutrients with birth outcomes and infancy development has been examined in a systematic review⁶ and many randomized clinical trials, including a cluster, randomized, double-blind clinical trial conducted in rural western China.^7,8,9,10

Key findings from this trial—antenatal micronutrient supplements significantly reduce the risk of adverse birth outcomes, including low birth weight and neonatal death, with the largest advantages seen in poor households—are reported elsewhere.^7,8 Further evaluations of these findings were planned to examine the long-term association of supplementation with child development. At age 1 year, children who received multiple micronutrient supplementation demonstrated substantial improvements in mental development compared with those who received folic acid or folic acid plus iron.⁹ However, at the second follow-up evaluation conducted at age 7 to 10 years, no substantial association was found between micronutrient supplementation and cognitive function.¹⁰

The third follow-up evaluation, discussed in this article, was conducted at age 10 to 14 years. Regular observations over time have enabled the reduction of recall bias. To our knowledge, few cohort studies of micronutrient interventions have been conducted, let alone studies that span more than 14 years. For the present study, our primary aims were to assess the long-term association of antenatal micronutrient supplementation with adolescent intellectual development and to evaluate the evidence of a dose-response association between the initiation of supplementation and the total number of supplements consumed. Modified effects by household wealth were also evaluated.

Methods

Ethics Approval

The adolescent development evaluation for the study was approved by UNICEF (United Nations International Children's Emergency Fund) and the ethics committee of the Xi’an Jiaotong University Health Science Center in Xi’an, Shaanxi, China. Written patient informed consent was obtained from each parent or caregiver, and oral consent was received from the adolescent participants after the purpose of the study was explained.

Study Design and Participants

Adolescent offspring of women who participated in the cluster, randomized, double-blind clinical trial of micronutrient supplementation in pregnancy (http://www.isrctn.com/ Identifier: ISRCTN08850194) were recruited. All pregnant women in the villages in 2 rural counties in western China were randomized to take a daily capsule of either folic acid, folic acid plus iron, or multiple micronutrients from August 1, 2002, through February 28, 2006. These details have been described elsewhere.⁸

Follow-up was conducted from June 1, 2016, through December 31, 2016, when the offspring were in early adolescence (aged 10-14 years). Information on the children, including name (and parent name), birth date, sex, address, and telephone number, was sent to the village physicians and was used to confirm offspring survival and school and to seek consent from parents or guardians to enroll in the present study. The local education bureau in Binxian and Changwu counties gave us permission to conduct the study in schools. Offspring with a major congenital abnormality, who died, or from multiple births were excluded.

Scale for Intellectual Development Evaluation

The Wechsler Intelligence Scale for Children, Fourth Edition (WISC-IV)¹¹ was used to assess intellectual development. The WISC-IV has 10 subtests (block design, similarities, digit span, picture concepts, coding, vocabulary, letter-number sequencing, matrix reasoning, comprehension, and symbol search) and 4 supplementary subtests (picture completion, cancellation, information, and arithmetic). These subtests yield 4 scores (verbal comprehension index, perceptual reasoning index, working memory index, and processing speed index) and a full-scale intelligence quotient (FSIQ), which represents general cognitive ability. The norms of the WISC-IV were established in China in a nationally representative sample of children aged 6 to 16 years, approximating the population structure on sex, race, parent educational level, and geographic region.¹²

The intelligence tests were administered to study participants by public health postgraduate students trained in the Chinese WISC-IV technical manual. Most assessments were conducted in a school meeting room that was free of distractions. Weekend assessments for the 56 adolescents absent from school during testing took place in a hospital where blood samples were collected.

Data Collection: Related Covariates

Anthropometric parameters were measured with standardized techniques and expressed in SDs from age- and sex-specific references for World Health Organization growth standards, including body mass index (calculated as weight in kilograms divided by height in meters squared) for age z score and height for age z score.¹³

Maternal demographic and household information were collected at enrollment.⁸ The initiation of micronutrient supplementation was determined by the first time the micronutrient capsules were distributed to the women. The total supplements consumed were calculated by the number of capsules the women took.⁸ For the present study, we interviewed participants to collect current characteristics, household wealth status, and type of school (village, town, or county level).

Participants, fieldworkers, and statisticians were blinded to the treatment group status until the primary analyses of follow-up data, based on the dummy treatment codes, were complete. Data analyses took place from April 1, 2017, to June 20, 2017.

Statistical Analysis

Primary analyses were based on intention-to-treat principles. Multiple imputation was used to attribute values for the missing outcomes (n = 27), taking the adolescent offspring’s age, sex, type of school, household wealth, and treatments as covariates with 20 imputed data sets.¹⁴ Characteristics of lost and followed-up participants as well as those across treatment groups were compared using analyses of variance and χ² tests. Mean differences and 95% CIs between groups for intellectual development were calculated, using generalized estimating equations with an independent correlation structure to adjust for assessors of intelligence tests.

We fitted Poisson regression models with log-link and independent correlation structures to estimate adjusted relative risks (RRs) and 95% CIs for delayed intellectual development, defined as test scores below the 20th population percentile according to the norm of the Chinese WISC-IV.¹² The possible covariates we considered were parental age, educational level, and occupation; household wealth; maternal mid–upper arm circumference at enrollment, parity, and small-for-gestational-age outcome at birth; and adolescent sex and type of school. Small for gestational age was defined as birth weight below the 10th percentile of weight for age and sex according to the International Fetal and Newborn Growth Consortium for the 21st Century standards.¹⁵ Household wealth was estimated from an inventory of 17 household assets or ownership of goats, cattle, horses, and poultry by principal component analysis.¹⁶ Wealth was classified into tertiles of poorest, middle, and richest.

To examine the modifying effects of micronutrients, we stratified by initiation time of micronutrient supplementation (<12 weeks of gestation vs ≥12 weeks of gestation), total number of consumed capsules (≥180 vs <180), and household wealth during pregnancy or currently after statistical tests for the interaction terms between treatments and modifiers.

All analyses were determined a priori. Statistical significance was set at a 2-sided P < .05. The FSIQ was taken as the primary outcome, and aspects of verbal comprehension, working memory, perceptual reasoning, and processing speed indexes were taken as the secondary outcomes. All analyses were conducted using Stata, version 12 (StataCorp LLC).

Results

Followed Participants

Figure 1 shows the flow of participants. Most baseline characteristics were balanced between lost and followed participants except for paternal educational level, gestation weeks at enrollment, and parity (Table 1). In total, 2118 adolescent offspring (1252 [59.1%] were boys and 866 [40.9%] were girls, with a mean [SD] age of 11.7 [0.87] years) were followed, representing 47.2% of the 4488 eligible single live births that were eligible to participate in this follow-up study.

Table 1. Comparison of Baseline Characteristics of the Adolescent Offspring Followed and Lost to Follow-up^a.

Variable	Adolescents Followed-up	Adolescents Lost to Follow-up	P Value^b
All pregnant women, No.	2118	2370
Maternal age, mean (SD), y	24.6 (4.3)	24.7 (4.3)	.42
Maternal educational level, No. (%)			.06
<3 y	119 (5.6)	131 (5.6)
Primary school	578 (27.4)	591 (25.0)
Secondary school	1094 (51.8)	1318 (55.8)
>High school diploma	320 (15.2)	322 (13.6)
Maternal occupation, No. (%)			.27
Farmer	1752 (83.2)	1989 (84.5)
Others	353 (16.8)	366 (15.5)
Paternal age, mean (SD), y	27.8 (4.1)	27.9 (4.1)	.57
Paternal educational level, No. (%)			.005
<3 y	28 (1.3)	32 (1.4)
Primary school	297 (14.1)	278 (11.8)
Secondary school	1251 (59.2)	1519 (64.3)
>High school diploma	536 (25.4)	532 (22.5)
Paternal occupation, No. (%)			.22
Farmer	1563 (74.0)	1789 (75.6)
Others	549 (26.0)	577 (24.4)
Household wealth index, mean (SD)	0.01 (1.5)	0.05 (1.5)	.37
Poor	671 (31.7)	763 (32.2)	.74
Not poor	1447 (68.3)	1610 (67.9)	.74
Gestation at enrollment, mean (SD), wk	13.9 (5.6)	14.4 (5.8)	.006
Parity, No. (%)			.009
0	1403 (66.2)	1527 (64.4)
1	617 (29.1)	768 (32.4)
>2	98 (4.6)	78 (3.3)
Height, mean (SD), cm	158.7 (5.3)	159.0 (5.0)	.09
Weight, mean (SD), kg	52.6 (6.2)	52.8 (6.0)	.21
BMI, mean (SD)	20.9 (2.3)	20.9 (2.2)	.63
MUAC, mean (SD), cm	23.2 (2.2)	23.1 (2.1)	.30

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Abbreviations: BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); MUAC, mid–upper arm circumference.

^{^a}

The original trial had 4604 single live births; 116 were excluded for death or birth defects, and 1041 of the 2370 participants lost to follow-up were adopted by others or moved out of the study area.

^{^b}

Comparisons used analysis of variance for continuous variables and χ² test for categorical variables.

Baseline Maternal, Adolescent, and Household Characteristics

Table 2 and Table 3 present baseline characteristics, which were balanced across treatment groups except for paternal education and adolescent mid–upper arm circumference. From grade 4 through grade 9, the mean FSIQ scores in adolescents increased by 2.52 points per school year.

Table 2. Comparison of Baseline Characteristics of Mothers and Fathers During Pregnancy^a.

Variable	Folic Acid Treatment Group	Folic Acid Plus Iron Treatment Group	MMN Treatment Group	P Value^b
All pregnant women, No.	733	677	708	.49
Maternal age, mean (SD), y	24.6 (4.4)	24.4 (4.3)	24.6 (4.3)	.67
Maternal educational level, No. (%)				.10
<3 y	44 (6.0)	29 (4.3)	46 (6.5)
Primary school	203 (27.8)	192 (28.5)	183 (25.9)
Secondary school	391 (53.6)	348 (51.6)	355 (50.2)
>High school diploma	92 (12.6)	105 (15.6)	123 (17.4)
Maternal occupation, No. (%)				.21
Farmer	617 (84.9)	562 (83.4)	573 (81.4)
Others	110 (15.1)	112 (16.6)	131 (18.6)
Paternal age, mean (SD), y	27.8 (4.1)	27.8 (4.1)	27.9 (4.0)	.69
Paternal educational level, No. (%)				.01
<3 y	8 (1.1)	5 (0.7)	15 (2.1)
Primary school	97 (13.3)	108 (16.0)	92 (13.0)
Secondary school	448 (61.3)	408 (60.5)	395 (55.9)
>High school diploma	178 (24.4)	153 (22.7)	205 (29.0)
Paternal occupation, No. (%)				.92
Farmer	542 (74.2)	503 (74.4)	518 (73.5)
Others	189 (25.9)	173 (25.6)	187 (26.5)
Household wealth index, mean (SD)	−0.05 (1.4)	0.04 (1.5)	0.04 (1.6)	.40
Poor	228 (31.1)	213 (31.5)	230 (32.5)	.05
Not poor	505 (68.9)	464 (68.5)	478 (67.5)	.05
Gestation at enrollment, mean (SD), wk	14.2 (5.8)	13.6 (5.6)	14.1 (5.4)	.11
Parity, No. (%)				.11
0	467 (63.7)	450 (66.5)	486 (68.6)
1	225 (30.7)	204 (30.1)	188 (26.6)
>2	41 (5.6)	23 (3.4)	34 (4.8)
Height
No.	725	675	704
Mean (SD), cm	158.9 (5.3)	158.7 (5.1)	158.6 (5.5)	.49
Weight
No.	717	668	697
Mean (SD), kg	52.7 (6.4)	52.4 (6.1)	52.6 (6.2)	.53
BMI
No.	716	667	696
Mean (SD)	20.9 (2.3)	20.8 (2.2)	20.9 (2.3)	.37
MUAC
No.	720	673	701
Mean (SD), cm	23.2 (2.2)	23.2 (2.2)	23.2 (2.1)	.83
Initiation time and total consumption, mean (SD)				.51
<Week 12 of gestation and ≥180 consumption	250 (34.1)	249 (36.8)	233 (32.9)
≥Week 12 of gestation and <180 consumption	361 (49.3)	308 (45.5)	348 (49.2)
Other^c	122 (16.6)	120 (17.7)	127 (17.9)

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Abbreviations: BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); MMN, multiple micronutrient; MUAC, mid–upper arm circumference.

^{^a}

Data are missing for maternal educational level (n = 7), paternal educational level (n = 6), maternal occupation (n = 13), paternal occupation (n = 6), maternal MUAC (n = 24), birth weight (n = 92), small for gestational age (n = 135), adolescent height (n = 26), weight (n = 26), and MUAC (n = 41).

^{^b}

Comparisons used analysis of variance for continuous variables and χ² test for categorical variables.

^{^c}

“Other” refers to adolescents whose mothers initiated supplementation after week 12 of gestation and consumed 180 or more capsules or initiated supplementation before week 12 of gestation and consumed fewer than 180 capsules.

Table 3. Comparison of Baseline Characteristics of Adolescent Offspring.

Variable	Folic Acid Treatment Group	Folic Acid Plus Iron Treatment Group	MMN Treatment Group	P Value^a
All adolescents	733	677	708	.49
Age, mean (SD), y	11.7 (0.9)	11.7 (0.9)	11.7 (0.9)	.62
Sex, No. (%)				.91
Boy	432 (58.9)	397 (58.6)	423 (59.8)
Girl	301 (41.1)	280 (41.4)	285 (40.3)
School type, No. (%)				.32
Village	116 (15.8)	106 (15.7)	87 (12.3)
Township	293 (40.0)	278 (41.1)	301 (42.5)
County	324 (44.2)	293 (43.3)	320 (45.2)
Primary	423 (57.7)	373 (55.1)	391 (55.2)	.53
Secondary	310 (42.3)	304 (44.9)	317 (44.8)	.53
Current household wealth, No. (%)				.74
Poor	253 (34.5)	235 (34.7)	233 (32.9)
Not poor	480 (65.5)	442 (65.3)	475 (67.1)
Birth weight, mean (SD), g	3198 (414)	3200 (397)	3220 (422)	.54
Gestation at birth, mean (SD), wk	39.8 (1.6)	39.9 (1.5)	39.9 (1.6)	.23
Preterm birth, No. (%)	33 (4.5)	23 (3.4)	27 (3.8)	.56
Low birth weight, No. (%)	24 (3.5)	25 (3.9)	17 (2.5)	.37
Small for gestational age, No. (%)	87 (12.8)	71 (11.2)	82 (12.3)	.65
Weight, mean (SD), kg	39.6 (8.4)	39.0 (8.6)	39.5 (9.0)	.36
Height, mean (SD), cm	149.4 (8.5)	148.9 (8.3)	149.3 (8.7)	.47
MUAC, mean (SD), cm	20.0 (2.5)	19.7 (2.4)	19.9 (2.5)	.049
BMI, mean (SD), kg/m²	17.6 (2.5)	17.4 (2.6)	17.6 (2.9)	.51
BMI for age z score, mean (SD)	−0.19 (1.1)	−0.27 (1.2)	−0.26 (1.2)	.33
Height for age z score, mean (SD)	0.18 (1.1)	0.10 (1.1)	0.13 (1.1)	.40

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Abbreviations: BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); MMN, multiple micronutrient; MUAC, mid–upper arm circumference.

^{^a}

Comparisons used analysis of variance for continuous variables and χ² test for categorical variables.

Micronutrient Supplementation and Intellectual Development

Table 4 shows mean intellectual scores by treatment. The mean (SD) intelligence scores were higher in the multiple micronutrient treatment group (98.5 [12.7]) compared with the folic acid plus iron group (96.9 [11.6]) or the folic acid group (97.2 [12.4]). After adjusting for covariates, the multiple micronutrient treatment group was significantly higher for FSIQ (adjusted mean difference, 1.13; 95% CI, 0.15-2.10) and verbal comprehension index (adjusted mean difference, 2.03; 95% CI, 0.61-3.45) compared with the folic acid group. In addition, the multiple micronutrient group was significantly higher for FSIQ (adjusted mean difference, 1.37; 95% CI, 0.43-2.32) and verbal comprehension index (adjusted mean difference, 1.71; 95% CI, 0.21-3.20) compared with the folic acid plus iron group. The unadjusted results were similar to the adjusted result patterns.

Table 4. Comparisons of Mean, SD, and 95% CI of Wechsler Intelligence Scale for Children, Fourth Edition, Test Scores of Adolescent Offspring.

WISC-IV Test	Treatment Group	No.	Mean (SD)	Adjusted Mean Difference (95% CI)^a
WISC-IV Test	Treatment Group	No.	Mean (SD)	MMNs vs Folic Acid Plus Iron or Folic Acid	MMNs vs Folic Acid Plus Iron
FSIQ	Folic acid	733	97.2 (12.4)	0 [Reference]
	Folic acid plus iron	677	96.9 (11.6)	−0.25 (−1.32 to 0.83)	0 [Reference]
	MMNs	708	98.5 (12.7)	1.13 (0.15 to 2.10)	1.37 (0.43 to 2.32)
VCI	Folic acid	733	101.5 (15.6)	0 [Reference]
	Folic acid plus iron	677	101.7 (15.1)	0.32 (−0.76 to 1.40)	0 [Reference]
	MMNs	708	103.6 (16.1)	2.03 (0.61 to 3.45)	1.71 (0.21 to 3.20)
WMI	Folic acid	733	93.8 (10.6)	0 [Reference]
	Folic acid plus iron	677	93.9 (10.9)	−0.15 (−1.06 to 0.76)	0 [Reference]
	MMNs	708	95.0 (11.5)	0.89 (−0.19 to 1.96)	1.03 (−0.04 to 2.11)
PRI	Folic acid	733	95.5 (12.5)	0 [Reference]
	Folic acid plus iron	677	95.8 (11.5)	0.34 (−1.14 to 1.83)	0 [Reference]
	MMNs	708	96.2 (12.0)	0.66 (−0.65 to 1.98)	0.32 (−0.75 to 1.39)
PSI	Folic acid	733	99.5 (13.9)	0 [Reference]
	Folic acid plus iron	677	98.4 (12.7)	−1.13 (−2.77 to 0.51)	0 [Reference]
	MMNs	708	99.7 (13.9)	−0.05 (−1.07 to 0.97)	1.08 (−0.14 to 2.30)

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Abbreviations: FSIQ, full-scale intelligence quotient; MMNs, multiple micronutrients; PRI, perceptual reasoning index; PSI, processing speed index; VCI, verbal comprehension index; WISC-IV, Wechsler Intelligence Scale for Children, Fourth Edition; WMI, working memory index.

^{^a}

Adjusted for assessors and covariates (including parental age, educational level, and occupation; maternal mid–upper arm circumference at enrollment, parity, and small-for-gestational age outcome at birth; adolescent sex, school type, and categorical body mass index for age z score; and current household wealth) in general estimating equation linear models.

In terms of delayed intellectual development, results were similar with the lowest proportion in the multiple micronutrient group. A substantial protective association of multiple micronutrients with verbal comprehension index was observed only in the multiple micronutrient group (adjusted RR, 0.78; 95% CI, 0.63-0.96) compared with the folic acid group (eTable 1 in the Supplement).

Initiation Time and Total Consumption

The P values for interaction between treatments and modifier were significant for FSIQ and verbal comprehension index (t = –2.06; P = .04 and t = –2.42; P = .02) (eTable 2 in the Supplement). The highest intellectual scores were observed when the women initiated supplementation before week 12 of gestation and consumed 180 or more capsules. As shown in Figure 2 (eTable 3 in the Supplement), among this substratum, multiple micronutrient supplementation was associated with a 2.16-point higher FSIQ (95% CI, 0.41-3.90) and a 4.29-point higher verbal comprehension index (95% CI, 1.33-7.24) compared with folic acid supplementation. Conversely, when micronutrient supplementation was initiated late (≥12 weeks of gestation) and with an inadequate dose (<180 capsules), the multiple micronutrient group had significantly higher intelligence scores than the folic acid plus iron group except for perceptual reasoning index. The adjusted mean difference score for FSIQ was 2.46 (95% CI, 0.98-3.94) and for verbal comprehension index was 2.45 (95% CI, 0.20-4.70). In this substratum, mean scores in the folic acid plus iron group were lowest, and the estimated association approached significance for FSIQ (adjusted mean difference, –1.49; 95% CI, –2.86 to –0.12) and processing speed index (adjusted mean difference, –1.80; 95% CI, –3.39 to –0.19) compared with the folic acid group. No substantial differences were found between the multiple micronutrient and folic acid groups. Among the “other” substratum, no substantial associations were observed.

Figure 2. — FSIQ indicates full-scale intelligence quotient; MMN, multiple micronutrient; PRI, perceptual reasoning index; PSI, processing speed index; VCI, verbal comprehension index; and WMI, working memory index.

^aAdjusted for assessors and covariates (including parental age, occupation, and educational level; current household wealth; maternal mid–upper arm circumference at enrollment, parity, and small-for-gestational-age outcome at birth; and offspring sex, school type, and categorical body mass index for age z score) in general estimating equation linear models.

^b“Other” refers to adolescents whose mothers initiated supplementation after week 12 of gestation and consumed 180 or more capsules or initiated supplementation before week 12 of gestation and consumed fewer than 180 capsules.

When delayed intellectual development was considered (eTable 4 in the Supplement), similar patterns of modification by initiation and total supplements consumed were observed. Multiple micronutrients were associated with the decreased risk of delayed intellectual development on the FSIQ and verbal comprehension index.

To ascertain the modifying effects of initiation and total consumption, we stratified analyses by these factors (eTable 5 and eTable 6 in the Supplement). When mothers initiated supplementation before week 12 of gestation or consumed 180 or more capsules, the multiple micronutrient group had substantially higher scores than did the folic acid group, but the significant differences on FSIQ were found only in the substratum of initiation before week 12 of gestation. Among mothers who initiated supplementation after week 12 of gestation or consumed fewer than 180 capsules, the mean differences in some scores were significant between the multiple micronutrient group and the folic acid plus iron group, and the scores in the folic acid plus iron group were lowest.

Modifying Effect of Household Wealth

Although the P values for interaction between treatments and household wealth during the mothers’ pregnancies were not significant (eTable 2 in the Supplement), the adolescent offspring from wealthier households in all treatment groups scored approximately 5 points higher on all intellectual tests (eTable 7 in the Supplement). In addition, substantial association among treatments was found only in wealthier households.

Discussion

Multiple micronutrient supplementation was associated with a significant increase in FSIQ for adolescents aged 10 to 14 years compared with folic acid with or without iron capsules. Moreover, the intellectual development advantages of antenatal multiple micronutrient supplementation could be doubled within the substratum of supplementation initiated early (<week 12 of gestation) and with adequate dose (≥180 capsules) compared with folic acid alone.

Interpretation of the Findings and Comparison With Other Studies

In the present study, the FSIQ scores increased by a mean of 2.52 points per school year. From this perspective, the advantages of antenatal multiple micronutrient supplementation, when compared with those of folic acid or folic acid plus iron, were equivalent to the increase in scores for approximately half a year of school. In addition, the findings that multiple micronutrients could significantly reduce the risk of delayed intellectual development on verbal comprehension index suggests that the association of multiple micronutrients with cognitive development has a clinical significance.

Only 2 similar randomized trials have examined the effects of micronutrient supplementation on intellectual development in older children aged 9 to 12 years.^17,18 The results from the Indonesia trial¹⁷ showed that antenatal multiple micronutrients compared with folic acid plus iron, supplements among the substratum of anemic mothers were beneficial to children’s general intellectual ability. However, another follow-up study from Nepal, based on a smaller sample size, did not observe the benefits of multiple micronutrients compared with folic acid plus iron on children’s overall intelligence.¹⁸

Other randomized trials that examined the effects of maternal micronutrient supplementation on cognitive development among younger children had inconsistent findings. In a study in Indonesia, with a sample size of 487 children aged 3½ years, significant benefits of multiple micronutrients were observed but only in high-risk subpopulations, including undernourished or anemic mothers.¹⁹ Similar patterns were evident from randomized trials in Bangladesh and Tanzania, although their effects were not statistically significant.^20,21 In our study, the dose-response association of supplementation and the inconsistent results from other studies suggest that multiple micronutrients supplementation may provide long-term positive outcomes only with sufficient dose—namely, initiating supplementation early and continuing it for at least 180 days (≥180 capsules consumption). A recent meta-analysis of 17 randomized trials showed that the association of multiple micronutrients with birth outcomes was greater with high supplementation adherence (≥95%).²² Furthermore, the separately stratified analyses by initiation time and total consumption (eTable 5 and eTable 6 in the Supplement) show that the significant differences in FSIQ scores between multiple micronutrients and folic acid supplementation were found in the substratum of initiation before week 12 of gestation but not in the substratum of consumption of more than 180 capsules, which emphasizes early initiation on improving cognitive development.

One study reported contradictory finding that antenatal folic acid plus iron, but not multiple micronutrients, was positively associated with intellectual functioning in early school-aged children.²³ Whether iron supplementation has an association with child mental development (iron is needed for proper neurogenesis and myelination during fetal neurodevelopment) is a controversial topic. In the present study, the advantages of multiple micronutrients supplementation compared with folic acid plus iron became insignificant within the substratum of initiation before week 12 of gestation and with consumption of more than 180 capsules, which suggests that folic acid plus iron may be associated with mental development under some conditions. A previous study found that antenatal iron-deficiency anemia was negatively associated with infancy mental development and that sufficient iron supplementation protected child development even when antenatal iron-deficiency anemia was not corrected.²⁴ A study from Nepal did not assess the outcome of supplements in anemic mothers,²³ although it found that 244 women (72.6%) in the study were anemic and 271 (80.6%) had an iron deficiency.²⁵ In accordance with findings from the Nepal study²³ and those of another report,²⁴ we hypothesize that prenatal iron supplements are beneficial to child intellectual development in subpopulations with a high prevalence of iron-deficiency anemia. This hypothesis is supported by a systematic review that concluded that iron supplementation in nonanemic pregnant women did not alter child mental development.²⁶

In this context, the intellectual test scores of adolescents in the folic acid plus iron group were the lowest among the substratum of initiation in or after week 12 of gestation and with consumption of fewer than 180 capsules; this finding is unlikely to be attributable to the negative outcomes of iron supplementation. In a previous report, folic acid plus iron was associated with reduced early neonatal mortality compared with folic acid alone, regardless of infant intelligence.⁸ The iron dose in the present study was insufficient to correct intellectual levels. Consequently, the findings suggest that folic acid plus iron had a larger association with birth outcomes than with subsequent mental development with the dose of 60 mg per day examined in the original trial.⁸ The findings also suggest that multiple micronutrients supplementation was better than folic acid plus iron at improving cognitive development in offspring when mothers initiate supplementation late and/or do not receive enough micronutrients.

The nonsignificant interactions between treatments and household wealth suggested that the long-term outcomes of micronutrient supplementation were not modified by family economy. However, the stratified analyses (eTable 7 in the Supplement) showed that adolescents from wealthier households in all treatment groups scored approximately 5 points higher on all intellectual tests compared with those from poor households, which were higher than the effect sizes that supplementation achieved. Given that poor women have less adequate diets and greater micronutrient deficiencies²⁷ and richer families may have more stimulating environments, we assume that micronutrient supplementation may not be sufficient for improving adolescent intellectual ability in poor households and that other interventions after birth (eg, promoting exclusive breastfeeding) may be essential for reaching child development potential.

Implications for Public Health Interventions

To address the widespread micronutrient and iron deficiencies, especially for pregnant women, in low- and middle-income countries, UNICEF and the World Health Organization have, over the past decade, been conducting a series of trials that compare antenatal multiple micronutrients with folic acid plus iron supplementation.²⁸ Recent systematic evaluations support the part that multiple micronutrients, containing iron and folic acid, play in improving birth outcomes⁶ and reducing 6-month mortality rates with indicators of nutritional deficiency.²² The systematic evaluation of 6 randomized trials found no consistent differences in cognitive function between the multiple micronutrient and folic acid plus iron groups,²⁹ but the present study’s robust results, together with findings from the study in Indonesia,¹⁷ provide evidence for policymakers to consider recommending micronutrient supplementation as routine antenatal care.

Strengths and Limitations

To our knowledge, this 14-year follow-up is the longest study of its kind, spanning a period from pregnancy to the early adolescence of children from that pregnancy. Set in rural western China, this study has comprehensively examined the association of micronutrient supplementation with adolescent intellectual development. The original trial was a large randomized clinical trial with assessors and participants blinded to the treatment allocations. The WISC-IV is a widely accepted evaluation tool, was culturally appropriate as it was localized in China, and could assess not only general intellectual ability but also aspects of cognitive ability. In addition, the adolescent participants were sensitive to intellectual tests, which guaranteed enough power to detect the associations of micronutrient supplementation.

Our findings should be considered within the context of some limitations. In the present study, 2370 (52.8%) of 4488 adolescents were lost to follow-up, a rate that is higher than the 30% lost rate in the Indonesia study.¹⁷ The mean ages were approximately 1 year younger than in our study, but the total sample size assessed by intellectual tests was larger than in other studies.^18,19,21,23 Because of the rapid economic development and massive migration in rural China, many mothers and their offspring have moved out of the study areas. However, our results are still representative because neither loss of subjects nor baseline characteristics between treatment groups was biased. In addition, both the subgroup analyses (Figure 2) and sensitivity analyses (eFigure in the Supplement) show that our results were robust. One weakness of this study was the heterogeneity between the assessors who administered the intellectual tests. The assessors were trained, and the scores were checked by the field team leader, but we found significant associations between the assessors and the FSIQ scores. We mitigated this problem by adjusting for assessors as a group variable in generalized estimating equation models. Another weakness was that we did not include all possible covariates, such as consumption of alcohol and drugs in adolescence, mainly because of the low levels of alcohol and drug use by the adolescents in our study areas. The generally positive findings in this follow-up study were different from the insignificant findings from the previous follow-up, when the children were aged 7 to 10 years.¹⁰ This findings may be a result of the larger sample size in the present study (2118 vs 1744), and older children are more sensitive to intellectual tests and free from the floor effects.¹¹

Conclusions

Antenatal multiple micronutrient supplementation was associated with a significant improvement in adolescent intellectual development compared with folic acid plus iron or folic acid alone. Initiating supplementation in the first trimester (before week 12) of pregnancy and continuing it for at least 180 days were associated with the greatest advantages for offspring.

Supplement.

eTable 1. Comparisons of RR and 95% CI of Delayed Intellectual Development on WISC-IV Tests of Adolescents Whose Mother Enrolled in the Micronutrient Supplementation Trial by Maternal Supplementation Groups in Shaanxi Province, China 2002-2016

eTable 2. P Values for Interaction Terms Between Treatments and Modified Categories

eTable 3. Comparisons of Mean, SD and 95% CI of WISC-IV Test Scores of Adolescents Whose Mother Enrolled in the Micronutrient Supplementation Trial by Maternal Supplementation Groups, and Initial Time and Total Consumed of Supplements in Shaanxi Province, China 2002-2016

eTable 4. Comparisons of RR and 95% CI of Delayed Development of WISC-IV Tests of Adolescents Whose Mother Enrolled in the Micronutrient Supplementation Trial by Maternal Supplementation Groups, and Initial Time and Total Consumed of Supplements in Shaanxi Province, China 2002-2016

eTable 5. Comparisons of Mean, SD and 95% CI of WISC-IV Test Scores of Adolescents Whose Mother Enrolled in the Micronutrient Supplementation Trial by Maternal Supplementation Groups, and Initial Time in Shaanxi Province, China 2002-2016

eTable 6. Comparisons of Mean, SD and 95% CI of WISC-IV Test Scores of Adolescents Whose Mother Enrolled in the Micronutrient Supplementation Trial by Maternal Supplementation Groups, and Total Supplements Consumed in Shaanxi Province, China 2002-2016

eTable 7. Comparisons of Mean, SD and 95% CI of WISC-IV Test Scores of Adolescents Whose Mother Enrolled in the Micronutrient Supplementation Trial by Maternal Supplementation Groups and Household Wealth in Shaanxi Province, China 2002-2016

eFigure. Comparisons of Mean and 95% CI of WISC-IV Test Scores Among Adolescents Sampled Randomly from Followed Participants Whose Mother Enrolled in the Micronutrient Supplementation Trial in Shaanxi Province, China 2002-2016

Click here for additional data file.^{(470.8KB, pdf)}

References

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement.

eTable 2. P Values for Interaction Terms Between Treatments and Modified Categories

Click here for additional data file.^{(470.8KB, pdf)}

[poi180033r1] 1.Black MM, Walker SP, Fernald LCH, et al. ; Lancet Early Childhood Development Series Steering Committee . Early childhood development coming of age: science through the life course. Lancet. 2017;389(10064):77-90. doi: 10.1016/S0140-6736(16)31389-7 [DOI] [PMC free article] [PubMed] [Google Scholar]

[poi180033r2] 2.Black RE, Victora CG, Walker SP, et al. ; Maternal and Child Nutrition Study Group . Maternal and child undernutrition and overweight in low-income and middle-income countries. Lancet. 2013;382(9890):427-451. doi: 10.1016/S0140-6736(13)60937-X [DOI] [PubMed] [Google Scholar]

[poi180033r3] 3.Berti C, Biesalski HK, Gärtner R, et al. Micronutrients in pregnancy: current knowledge and unresolved questions. Clin Nutr. 2011;30(6):689-701. doi: 10.1016/j.clnu.2011.08.004 [DOI] [PubMed] [Google Scholar]

[poi180033r4] 4.Ruel MT, Alderman H; Maternal and Child Nutrition Study Group . Nutrition-sensitive interventions and programmes: how can they help to accelerate progress in improving maternal and child nutrition? Lancet. 2013;382(9891):536-551. doi: 10.1016/S0140-6736(13)60843-0 [DOI] [PubMed] [Google Scholar]

[poi180033r5] 5.Fox SE, Levitt P, Nelson CA III. How the timing and quality of early experiences influence the development of brain architecture. Child Dev. 2010;81(1):28-40. doi: 10.1111/j.1467-8624.2009.01380.x [DOI] [PMC free article] [PubMed] [Google Scholar]

[poi180033r6] 6.Haider BA, Bhutta ZA. Multiple-micronutrient supplementation for women during pregnancy. Cochrane Database Syst Rev. 2017;4:CD004905. doi: 10.1002/14651858.CD004905.pub5 [DOI] [PMC free article] [PubMed] [Google Scholar]

[poi180033r7] 7.Zeng L, Yan H, Cheng Y, Dibley MJ. Modifying effects of wealth on the response to nutrient supplementation in pregnancy on birth weight, duration of gestation and perinatal mortality in rural western China: double-blind cluster randomized controlled trial. Int J Epidemiol. 2011;40(2):350-362. doi: 10.1093/ije/dyq262 [DOI] [PubMed] [Google Scholar]

[poi180033r8] 8.Zeng L, Dibley MJ, Cheng Y, et al. Impact of micronutrient supplementation during pregnancy on birth weight, duration of gestation, and perinatal mortality in rural western China: double blind cluster randomised controlled trial. BMJ. 2008;337:a2001. doi: 10.1136/bmj.a2001 [DOI] [PMC free article] [PubMed] [Google Scholar]

[poi180033r9] 9.Li Q, Yan H, Zeng L, et al. Effects of maternal multimicronutrient supplementation on the mental development of infants in rural western China: follow-up evaluation of a double-blind, randomized, controlled trial. Pediatrics. 2009;123(4):e685-e692. doi: 10.1542/peds.2008-3007 [DOI] [PubMed] [Google Scholar]

[poi180033r10] 10.Li C, Zeng L, Wang D, et al. Prenatal micronutrient supplementation is not associated with intellectual development of young school-aged children. J Nutr. 2015;145(8):1844-1849. doi: 10.3945/jn.114.207795 [DOI] [PubMed] [Google Scholar]

[poi180033r11] 11.Wechsler D. The Wechsler Intelligence Scale for Children. 4th ed London: Pearson; 2004. [Google Scholar]

[poi180033r12] 12.Chen H, Keith TZ, Weiss L, Zhu J, Li Y. Testing for multigroup invariance of second-order WISC-IV structure across China, Hong Kong, Macau, and Taiwan. Pers Individ Dif. 2010;49(7):677-682. doi: 10.1016/j.paid.2010.06.004 [DOI] [Google Scholar]

[poi180033r13] 13.Butte NF, Garza C, de Onis M. Evaluation of the feasibility of international growth standards for school-aged children and adolescents. J Nutr. 2007;137(1):153-157. doi: 10.1093/jn/137.1.153 [DOI] [PubMed] [Google Scholar]

[poi180033r14] 14.Sterne JA, White IR, Carlin JB, et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ. 2009;338:b2393. doi: 10.1136/bmj.b2393 [DOI] [PMC free article] [PubMed] [Google Scholar]

[poi180033r15] 15.Villar J, Cheikh Ismail L, Victora CG, et al. ; International Fetal and Newborn Growth Consortium for the 21st Century (INTERGROWTH-21st) . International standards for newborn weight, length, and head circumference by gestational age and sex: the Newborn Cross-Sectional Study of the INTERGROWTH-21st Project. Lancet. 2014;384(9946):857-868. doi: 10.1016/S0140-6736(14)60932-6 [DOI] [PubMed] [Google Scholar]

[poi180033r16] 16.Filmer D, Pritchett LH. Estimating wealth effects without expenditure data—or tears: an application to educational enrollments in states of India. Demography. 2001;38(1):115-132. [DOI] [PubMed] [Google Scholar]

[poi180033r17] 17.Prado EL, Sebayang SK, Apriatni M, et al. Maternal multiple micronutrient supplementation and other biomedical and socioenvironmental influences on children’s cognition at age 9-12 years in Indonesia: follow-up of the SUMMIT randomised trial. Lancet Glob Health. 2017;5(2):e217-e228. doi: 10.1016/S2214-109X(16)30354-0 [DOI] [PubMed] [Google Scholar]

[poi180033r18] 18.Dulal S, Liégeois F, Osrin D, et al. Does antenatal micronutrient supplementation improve children’s cognitive function? evidence from the follow-up of a double-blind randomised controlled trial in Nepal. BMJ Glob Health. 2018;3(1):e000527. doi: 10.1136/bmjgh-2017-000527 [DOI] [PMC free article] [PubMed] [Google Scholar]

[poi180033r19] 19.Prado EL, Alcock KJ, Muadz H, Ullman MT, Shankar AH; SUMMIT Study Group . Maternal multiple micronutrient supplements and child cognition: a randomized trial in Indonesia. Pediatrics. 2012;130(3):e536-e546. doi: 10.1542/peds.2012-0412 [DOI] [PubMed] [Google Scholar]

[poi180033r20] 20.Tofail F, Persson LA, El Arifeen S, et al. Effects of prenatal food and micronutrient supplementation on infant development: a randomized trial from the Maternal and Infant Nutrition Interventions, Matlab (MINIMat) study. Am J Clin Nutr. 2008;87(3):704-711. doi: 10.1093/ajcn/87.3.704 [DOI] [PubMed] [Google Scholar]

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[poi180033r22] 22.Smith ER, Shankar AH, Wu LS, et al. Modifiers of the effect of maternal multiple micronutrient supplementation on stillbirth, birth outcomes, and infant mortality: a meta-analysis of individual patient data from 17 randomised trials in low-income and middle-income countries. Lancet Glob Health. 2017;5(11):e1090-e1100. doi: 10.1016/S2214-109X(17)30371-6 [DOI] [PubMed] [Google Scholar]

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PERMALINK

Association of Antenatal Micronutrient Supplementation With Adolescent Intellectual Development in Rural Western China

Zhonghai Zhu, MSc

Yue Cheng, PhD

Lingxia Zeng, PhD

Mohamed Elhoumed, MSc

Guobin He, BSc

Wenhao Li, BSc

Min Zhang, MSc

Wenjing Li, BSc

Danyang Li, MSc

Sintayehu Tsegaye, BSc

Suying Chang, PhD

Hong Yan, PhD

Emma Yu Wang, PhD

Duolao Wang, PhD

Shabbar Jaffar, PhD

Michael J Dibley, MB, BS, MPH

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Main Outcomes and Measures

Results

Conclusions and Relevance

Trial Registration

Introduction

Methods

Ethics Approval

Study Design and Participants

Scale for Intellectual Development Evaluation

Data Collection: Related Covariates

Statistical Analysis

Results

Followed Participants

Figure 1. Participant Flowchart by Treatment Groups.

Table 1. Comparison of Baseline Characteristics of the Adolescent Offspring Followed and Lost to Follow-upa.

Baseline Maternal, Adolescent, and Household Characteristics

Table 2. Comparison of Baseline Characteristics of Mothers and Fathers During Pregnancya.

Table 3. Comparison of Baseline Characteristics of Adolescent Offspring.

Micronutrient Supplementation and Intellectual Development

Table 4. Comparisons of Mean, SD, and 95% CI of Wechsler Intelligence Scale for Children, Fourth Edition, Test Scores of Adolescent Offspring.

Initiation Time and Total Consumption

Figure 2. Comparison of Mean and Adjusted Mean Difference (95% CI)a Wechsler Intelligence Scale for Children, Fourth Edition (WISC-IV) Test Scores of Adolescent Offspring, by Their Mothers’ Treatment Group, Initiation Time, and Total Consumption .

Modifying Effect of Household Wealth

Discussion

Interpretation of the Findings and Comparison With Other Studies

Implications for Public Health Interventions

Strengths and Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases

Table 1. Comparison of Baseline Characteristics of the Adolescent Offspring Followed and Lost to Follow-up^a.

Table 2. Comparison of Baseline Characteristics of Mothers and Fathers During Pregnancy^a.

Figure 2. Comparison of Mean and Adjusted Mean Difference (95% CI)^a Wechsler Intelligence Scale for Children, Fourth Edition (WISC-IV) Test Scores of Adolescent Offspring, by Their Mothers’ Treatment Group, Initiation Time, and Total Consumption .