Prenatal Multiple Micronutrient Supplementation and Child Neurodevelopment: A Systematic Review and Meta-analysis.

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Amsalu Taye Wondemagegn, Soressa Abebe Geneti This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7713425/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract There are various inconclusive individual studies that have reported the association between child neurodevelopment and prenatal multiple micronutrient supplementation during pregnancy. Hence, the main aim of the current systematic review and meta-analysis is to determine the pooled effect size of prenatal multiple micronutrients supplementation on different neurodevelopmental outcomes in children. Systematic electronic search of PubMed/MEDLINE, Web of Science, Cochrane Library, CINAHL, Science Direct, and Google Scholar was conducted to access relevant articles to the current systematic review and meta-analysis. Eligible articles were selected based on predefined eligibility criteria, and data from the selected articles were extracted using Excel templates. Data analysis was performed using R and STATA software. Statistically significant heterogeneity among included studies was assessed using Cochran’s Q-test and I 2 statistics. Potential publication bias was evaluated by examining asymmetry in the funnel plots. Pooled Odds Ratios and Pooled Mean Differences, along with the corresponding 95% confidence intervals for prenatal micronutrient supplementation on neurodevelopmental outcomes in children, were calculated using a random-effects meta-analysis model. Statistical significance was defined as a p-value of < 0.05. The present systematic review and meta-analysis revealed that prenatal multiple micronutrients supplementation is significantly associated with autistic-like behavior (pooled Odds Ratio: 0.44, 95%CI: 0.30, 0.63), cognitive development (pooled mean difference: 0.18, 95%CI; 0.02, 0.34), and psychomotor development (pooled mean difference: 0.73, 95%CI: 0.19, 1.27) in children during postnatal life. The present systematic review and meta-analysis revealed that multiple micronutrients supplementation during pregnancy significantly reduces the risk of autistic-like behavior in children by 56% as compared to no supplementation or supplementations with iron and folic acid. The present meta-analysis also demonstrates a significant association between multiple micronutrient supplementation and improvements in cognitive and psychomotor development. Micronutrients macronutrients supplementation pregnancy neurodevelopment birth outcomes children systematic review meta-analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Optimizing outcomes across pregnancy, neonatal, and early childhood stages requires the provision of comprehensive care and support throughout the prenatal, intrapartum, and postpartum periods. Additionally, enhancing women’s health during the preconception phase is essential. Evidence indicates that poor maternal nutritional status during both the preconception and prenatal periods adversely affects fetal and neonatal outcomes, including neurodevelopment, physical growth, cardiometabolic health, and immune function [1]. Existing scientific evidence demonstrates that good nutritional status of women both before and during pregnancy is vital for promoting normal fetal physical growth and brain development [2]. It also plays a critical role in preventing the occurrence of adverse pregnancy outcomes, congenital anomalies [3], and non-communicable diseases throughout the lifespan of the newborn [4-8]. More importantly, inadequate and/or excessive nutrient intake has been associated with adverse long-term outcomes and noncommunicable diseases in offspring [5]. Fetal development within the intrauterine environmentcan irreversibly change individual genetic and metabolic pathways, leading to adaptive pathophysiological changes in offspring and an increased risk of non-communicable diseases later in life [9]. For example, one adverse pregnancy outcome, low birth weight (LBW), has been associated with an increased risk of cardiovascular disease[10], respiratory problems [11], and polycystic ovary syndrome[12] later in life. Pregnancy is a period of significant changes in a woman’s physiological status and involves increased nutritional demands to support the growth of the fetus and placenta. As a result, metabolic requirements increase substantially. Therefore, the physiological demands of pregnancy can exacerbate existing nutrient deficiencies, leading to serious health consequences for both the fetus and the newborn [1]. Moreover, studies have consistently reported a frequent co-occurrence of multiple nutrient deficiencies among women of reproductive age, particularly those living in poor socioeconomic settings [13], where diets often lack diversity and fortified foods are less available and consumed [14]. Hence, Hence, ensuring adequate intake of vitamins and minerals (micronutrients)[15], along with other essential nutrients during pregnancy, may require supplementation. This is especially important for women who are undernourished or have inadequate dietary intake due to poverty, disease, lifestyle-related factors, or other conditions. In addition, evidence suggests that supplementation with multiple micronutrients (MMN) during pregnancy reduces the risk of deficiencies and contributes to improved fetal outcomes[16]. Available scientific evidence indicates that certain nutrients play a critical role in regulating brain development, particularly during the fetal and early postnatal periods. Accordingly, studies have identified that the developing brain is especially susceptible to nutritional deprivation due to its impact on the rapid progression of several neurodevelopmental processes, including synapse formation, neuronal myelination, and the synthesis of neurometabolic and neurotransmitter systems [17-19]. It has been reported that the most important micronutrients for brain development include omega-3 fatty acids, folic acid, iron, zinc, copper, iodine, selenium, vitamin A, and choline [20]. Various individual studies have demonstrated an association between child neurodevelopment and selected micronutrients such as iron, folic acid, zinc, and multiple micronutrient (MMN) supplementation during pregnancy. However, findings from these studies regarding the impact of micronutrient supplementation on child health outcomes, including neurodevelopment, remain inconsistent. Some studies have reported that supplementation during pregnancy is associated with improved child neurodevelopment, while others have found no association and a few have even reported potential risks. For example, a study conducted in Indonesia [21] found that MMN supplementation during pregnancy significantly improved children’s motor and cognitive abilities at 42 months of age compared to iron and folic acid (IFA) supplementation, but showed no significant difference in communication and personal-social skills. A study conducted in China [22] reported significant improvements in communication, gross motor, fine motor, problem-solving, and personal-social skills among the MMN-supplemented group compared to the folic acid plus iron group at 3 years of age. On the other hand, another study in China [23] revealed prenatal MMN supplementation had significantly improved communication skill among children aged 6 to 24 months compared to non-supplemented groups but no significant difference in cognitive, motor, and social-emotional skills between supplemented and non-supplemented groups. In contrary, a study in rural Nepal [24] found that iron and folic acid supplementation, compared to MMN supplementation, led to greater improvements in intellectual, motor, and executive functioning in children aged 7–9 years. Similarly, a study in Viet Nam [25] reported prenatal IFA supplementation significantly improved cognitive development at 6 months of age compared to MMN supplementation. On the other hand, a study conducted in Bangladesh [26] revealed MMN supplementation as compared to iron and folic acid supplementation significantly improved problem-solving skill, motor development and behavior in infants at the age of 7 months. In contrary, a study in China [27] did not find a significant difference on intellectual development between prenatal MMN and IFA or folic acid alone supplementation in early school aged children (aged 7-10 years). Several studies revealed that iodine supplementation during pregnancy improved motor and cognitive development in children[28-30]. A study reported no significant differences in children’s cognitive development born from mothers of supplemented and non-supplemented groups with iodine in the preconception period living in the same locality [31]. According to Iannotti et al [32], zinc supplementation during pregnancy improved motor development. On the other hand, other studies done in Bangladeshi and England indicated that zinc supplementation during pregnancy did not improve motor development in children [33, 34]. Similarly, another study revealed that zinc plasma concentration level during pregnancy had a slight long-lasting effect on child’s cognitive development [35]. A study also revealed that MMN supplementation as compared to folic acid alone or folic acid plus iron supplementation did not significantly improve psychomotor and cognitive development of infants at 6 months of age and did not significantly improve psychomotor development at 1 year of age [36], but revealed a significant improvement in cognitive development at 1 year of age. In contrary, a study done in Tanzania [37] showed a significant improvement in psychomotor development but not cognitive development among multivitamin supplemented groups compared with none supplemented groups of infants at the age of both 6 and 12 months of age. On the other hand, a trial study in Bangladesh [38] showed prenatal MMN supplementation had no significant effect on cognitive, language and motor development and function at 2 years of age as compared to folic acid plus iron supplementations. More importantly, individual articles may not have enough statistical power to assess the effects on child health outcomes. An all-inclusive review scoping all aspects of effects of prenatal MMN supplementations on children’s neurodevelopment has not been well established so far. Previous reviews have mainly focused on the impacts of prenatal nutrition supplementation, including both single vitamins and multivitamin combinations, on autism spectrum disorders[39-41]. However, a comprehensive review that specifically examines the effects of multiple micronutrient supplementation alone is still urgently needed. Furthermore, most of existed findings regarding the effects of MMN supplementation on communication skill, cognitive skill, motor development and personal social interaction skill has not been yet synthesized and meta-analyzed. Hence, the aim of the current study is to systematically synthesize existing evidence on the association between prenatal multiple micronutrient supplementation during pregnancy and child neurodevelopment. This review uniquely applies updated methodological frameworks, namely the Risk of Bias 2.0 tool and the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach, which to our knowledge have not been previously employed in this context. In addition, the study quantitatively analyzes pooled effect sizes to assess the impact of prenatal multiple micronutrient intake on neurodevelopmental outcomes in children. Methods The current systematic review and meta-analysis is prepared and presented based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline[42]. The protocol of this review was not registered in PROSPERO. Search strategies A comprehensive search with no date limit of all relevant studies were carried out in the following electronic databases: PubMed/MEDLINE, Web of Science, Scopus, Cochrane Library, CINAHL, Science Direct, and Google Scholar ( Table 1 ). The search was limited to studies that were conducted in humans and were reported in the English language. In addition, relevant grey literatures such as dissertations, thesis, conference abstracts and others were searched and checked through the access of various subject-specific databases and websites. The search of literatures was used the following keywords individually and in combination through “AND” or “OR” Boolean operators as follows: “effect”, “prenatal”, “antenatal”, “micronutrients”, “trace elements”, “supplement”, “supplementation”, “status”, “children” and “neurodevelopment”. The search of the study findings was conducted between March 1 to April 1, 2022. All articles published until April 1, 2022 were included in the current study. At last, reference lists of accessed studies and related review reports were also examined to identify more eligible articles. The primary authors of few articles were contacted for missing data or to clarify vague methods or results reported, and accordingly most responded to the request and given raw data from which necessary analysis was performed, and those studies with no reply were excluded. Identified researches by our search strategy were collected and managed by using EndNote library. Eligibility criteria and study selection Inclusion criteria: Studies included in this systematic review and meta-analysis were conducted on human children under 18 years of age. Eligible designs included observational studies (cross-sectional, case-control, and cohort) and interventional studies (randomized controlled trials) that evaluated the association between prenatal multiple micronutrient supplementation and neurodevelopmental outcomes in children. Only studies published in English were considered. Importantly, studies were included if they assessed the effects of prenatal supplementation with at least three micronutrients, including formulations such as the United Nations International Multiple Micronutrient Preparation (UNIMMAP)[43], compared to supplementation with two or fewer micronutrients, no supplementation, or placebo. Included studies had no limits on time of initiation of supplement and duration of supplementations for micronutrients during pregnancy. Exclusion criteria: studies were excluded if they were animal studies, reviews, editorials, clinical answers, case reports or case series, commentaries, or letters to the editor. A small number of studies were excluded due to incomplete data, despite at least three attempts to contact the corresponding authors. These exclusions were necessary because the lack of complete data prevented proper quality assessment. Studies in which the intervention included fewer than three micronutrients were excluded. Outcome measures The outcomes measured in this study are various types of child neurodevelopmental outcomes, including autistic-like behaviors, cognitive development, language and communication development, psychomotor development, and social-emotional and behavioral development. These outcomes were assessed among children under 18 years of age. Child neurodevelopmental status was evaluated using the Ages and Stages Questionnaire – Third Edition (ASQ-3) [44], Bayley Scale of Infant Development (BSID) [45], International Classification of Diseases (ICD) criteria, Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria, and other tools ( Table 2 ). Data abstraction Data were extracted using a standardized template developed in Microsoft Excel, adapted from the Cochrane Review Group (CRG). Two authors of this review (ATW and SAG) independently extracted the following information from each study: first author’s name, year of publication, study country, study design, sample size, assessment methods for prenatal micronutrient intake, duration of intake, intake levels/dose, offspring’s age at assessment, outcome assessment method, types of neurodevelopmental outcomes, adjusted and crude risk estimates with corresponding 95% confidence intervals (CIs), and adjusted confounders. Any discrepancies between the two authors during data extraction were resolved through discussion until consensus was reached. Risk of bias assessment in included studies Two review authors (ATW and SAG) independently assessed the risk of bias for each study included in this systematic review and meta-analysis using a predetermined assessment form. Any disagreements were resolved through discussion, and in a few cases, study authors were contacted for clarification. Quality indicators were adapted from the Cochrane Handbook for Systematic Reviews of Interventions [46] and used to determine the risk of bias level for each included study. For randomized controlled trials (RCTs), the following criteria were used: 1. Method of sequence generation; 2. Allocation concealment; 3. Blinding of participants; 4. Method of outcome assessment; 5. Incomplete outcome data; 6. Selective outcome reporting; 7. Other potential sources of bias. Based on the reviewers’ judgments, studies were categorized as having high, low, or unclear risk of bias. Moreover, the quality of observational studies was assessed through Newcastle-Ottawa Quality Assessment parameters [47]. Accordingly, selection procedures, comparability issues and outcome measures were considered, to assess the quality of included cross-sectional and cohort studies. Selection procedures, comparability and exposure parameters were also considered for quality assessment of case-control studies. Based on the parameters’ studies are classified as low, medium and high-quality studies. Certainty of Evidence Assessment: The certainty of evidence for each outcome was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework. This approach evaluates the quality of evidence across five domains: risk of bias, inconsistency, indirectness, imprecision, and publication bias. For randomized controlled trials, the initial rating was high, while observational studies began as low certainty. Downgrading or upgrading decisions were made based on predefined criteria. Summary of Findings tables were generated using GRADEpro GDT software, presenting pooled effect estimates, number of studies and participants, and the final certainty rating for each outcome. The GRADE assessments were conducted independently by two reviewers, with discrepancies resolved through discussion or consultation with a third reviewer. Data processing and analysis Extracted data in Microsoft Excel spreadsheet software were imported into R (version 4.1.3) software and STATA version 14 software. Using R (version 4.1.3) software, we have demonstrated the association between prenatal multiple micronutrients supplementation of women and children’s neurodevelopment consequences which include cognitive development skills, socioemotional and behavioral skills, language and communication development skills, and psychomotor development skills. STATA version 14 software was used to reveal the association between multiple micronutrients supplementation during pregnancy and autistic-like behavior in children. In the current analysis, the reference category was the lowest category of micronutrients supplementation or no supplementations. Statistical heterogeneity among included studies were assessed using Cochran’s Q-test and I 2 statistics. I 2 value ranges from 0% to 100%[48], where 0% indicates no observed heterogeneity and large values indicate increasing heterogeneity. An I 2 value of less than 25%, 25-50%, 50-75% and greater than 75% is considered as very low, low, moderate and high heterogeneity respectively[48]. Since the test statistic showed statistically significant heterogeneity among the studies on cognitive, language, psychomotor and behavioral development (I 2 = 42.2%, p<0.05; 53.98%, p<0.05; 95%, p<0.01; 87%, p<0.01 respectively), a random-effects meta-analysis model was used to estimate the DerSimonian and Laird's pooled size effects. To decrease random variations of primary studies, we conducted subgroup analyses based on study design, study settings, sample size, and year of publication. Meta-regression analysis was also performed to investigate the possible sources of heterogeneity among subgroups. At last, we performed sensitivity analyses to explore whether individual study strongly affected the results of the meta-analysis, by deleting one study at a time. Publication bias was assessed via visual inspection of traditional and Begg’s funnel plots for asymmetry. In addition, publication bias was also assessed using both Egger’s[49] and Begg’s test [50], and for both tests statistically significant publication bias was declared at a p-value < 0.05. Results Study selection processes With electronic and manual searches, a total of 9,150 study titles were identified, including 667 duplicates, leaving 8,483 articles for screening (Figure 1). Of these, 8,401 were excluded based on title and abstract review, resulting in 82 articles for full-text assessment. These full-text articles were evaluated using predetermined eligibility criteria. Of the 82 articles, 56 were excluded due to irrelevant exposures and/or outcomes. Specifically, some studies examined micronutrient supplementation combined with macronutrients but did not analyze the effects of micronutrients separately. Others focused solely on iron and folic acid supplementation, which did not meet the criteria for multiple micronutrient exposure. Several studies described the exposure as “dietary supplements” without clarifying whether these were micronutrient-based. Additionally, a number of studies reported outcomes related to child growth such as weight, height, length, and other anthropometric indices, rather than neurodevelopmental outcomes. After full-text review, 26 articles remained. Of these, 24 met the inclusion criteria for both the systematic review and meta-analysis. The remaining two were included only in the systematic synthesis but excluded from meta-analysis: one study [51] had a somewhat vague definition of micronutrient exposure, and the other [52] used a reference category that was neither low nor no supplement use. Brief description of included studies The characteristics of the included studies are presented in detail in Table 2. Of the 26 studies included in this systematic review and meta-analysis, 9 were randomized controlled trials (RCTs), 11 cohort studies, 5 case-control studies, and 1 cross-sectional study, published between 2006 and 2020. The sample sizes of the included studies ranged from 209 to 273,107 participants. Approximately 46% of the studies were conducted in the USA (6 studies) and China (6 studies). The remaining studies were conducted in Denmark (2), New Zealand (2), Bangladesh (2), Indonesia (2), Norway (1), Vietnam (1), Sweden (1), Nepal (1), Israel (1), and Tanzania (1). Results of neurodevelopmental outcomes Meta-analysis results of autistic-like behavior Thirteen studies met the inclusion criteria for the meta-analysis of autistic-like behavior (Figure 2), including nine cohort studies and four case-control studies. The overall meta-analysis result showed a statistically significant association between prenatal multiple micronutrients supplementation and the risk of autistic-like behavior in children during the postnatal period, the pooled OR 0.44 with 95%CI:0.3, 0.63. Statistically significant heterogeneity is not observed (I 2 =0%, p-value=0.883). We performed sensitivity analysis and found significant pooled OR for all of the omitted studies. Similarly, meta-analysis of both cohort and case-control studies showed a significant association between prenatal multiple micronutrients supplementation and risk of autistic-like behavior in children ( Figure 3 ). Meta-analysis of cohort studies found pooled OR with 95%CI, 0.49: 0.3, 0.78 and found no significant heterogeneity (I 2 =0%, p-value=0.912). Sensitivity analysis was performed and found significant pooled OR except Levine et al, 2018 study. Pooled OR with 95%CI after omitting Levine et al, 2018 study is 0.64: 0.32, 1.17. The traditional funnel plot showed a little bit asymmetric distribution of included studies and hence there may be of publication bias due to few studies. Meta-analysis of case-control studies found pooled OR with 95%CI, 0.38: 0.21, 0.67 and found no significant heterogeneity (I 2 =0%, p-value=0.421). Sensitivity analysis was performed and for all of the omitted studies, we found significant pooled OR. The traditional funnel plot showed a little bit asymmetric distribution of included studies and hence there may be publication bias due to few studies. GRADE Assessment : The certainty of evidence for the outcome of autistic-like behavior was rated as moderate. Although the pooled effect was statistically significant and consistent across study designs, the rating was downgraded by one level due to suspected publication bias and reliance on observational studies, which inherently begin at a lower certainty level. No downgrades were made for inconsistency, indirectness, or imprecision, given the narrow confidence intervals and low heterogeneity. The moderate certainty suggests that prenatal multiple micronutrient supplementation is likely associated with reduced risk of autistic-like behavior, but further high-quality randomized trials are needed to strengthen confidence in this finding. Meta-analysis results of cognitive development Eleven studies were included in the meta-analysis to evaluate the association between prenatal multiple micronutrients supplementation and the cognitive development of children. The overall analysis showed a statistically significant association between multiple micronutrients supplementation during pregnancy and the cognitive development of children in the postnatal period, pooled mean difference estimates of 0.18 with 95%CI: 0.02, 0.34 ( Figure 4 ). We perform analysis using a random-effects model since heterogeneity between included studies were noticed (I 2 =42.2%, p-value=0.05). Sensitivity analysis was performed and most significant and some insignificant pooled mean differences were obtained following omitting of studies. Except omitting of Cheng et al, 2019; Prado et al, 2017; Tofail et al, 2008 and Prado et al, 2012, omitting of other included studies yield significant pooled mean differences. Pooled mean difference after omitting Cheng et al, 2019; Prado et al, 2017; Tofail et al, 2008 and Prado et al, 2012 respectively were 0.14, -0.05, 0.34; 0.18, -0.05, 0.42;0.16, -0.07, 0.39 and 0.14, -0.04, 0.31. In our meta-analysis, the traditional funnel plot did not reveal noticeable publication bias. GRADE Assessment: The certainty of evidence for the cognitive development outcome was rated as moderate. Although the pooled effect was statistically significant and supported by multiple studies, the rating was downgraded by one level due to inconsistency (moderate heterogeneity) and imprecision in sensitivity analyses, where exclusion of certain studies led to loss of statistical significance. No downgrades were made for risk of bias or publication bias, as most studies were well-conducted and the funnel plot showed symmetry. The moderate certainty indicates that prenatal multiple micronutrient supplementation is likely beneficial for cognitive development, but further high-quality randomized trials are needed to confirm the magnitude and consistency of the effect. Meta-analysis results of language and communication development Seven studies were included in this meta-analysis to evaluate the association between multiple micronutrients supplementation during pregnancy on children’s language and communication development. The current meta-analysis did not show a significant association between prenatal multiple micronutrients supplementation and children’s language and communication skills development, pooled mean difference estimates of 0.18 with 95%CI: -0.03, 0.4 ( Figure 5 ). A random-effects model analysis was performed due to the moderate heterogeneity distinguished between included studies (I 2 =53.98%, p-value<0.05). Sensitivity analysis was performed and insignificant pooled mean differences were observed in omitting of all included studies. Publication bias was observed in the traditional funnel plot, which may be attributed to a few studies. GRADE Assessment: The certainty of evidence for the outcome of language and communication development was rated as low. The rating was downgraded due to inconsistency (moderate heterogeneity) and imprecision, as the confidence interval crossed the line of no effect and sensitivity analyses yielded non-significant results throughout. Additionally, publication bias was suspected based on funnel plot asymmetry. No upgrades were applied, as the included studies were observational and the effect size was small and uncertain. The low certainty suggests that current evidence is insufficient to determine whether prenatal multiple micronutrient supplementation has a meaningful impact on language and communication development in children. Meta-analysis results of psychomotor development Eleven studies were evaluated to reveal the association between multiple micronutrients supplementation during gestation and children’s gross and fine motor skills. Our meta-analysis result shown that prenatal multiple micronutrients supplementation during gestation were significantly associated with psychomotor skill development of children, pooled mean difference of 0.73 with 95%CI:0.19, 1.27 ( Figure 6 ). A random-effects model analysis was performed due to the sizeable heterogeneity distinguished between included studies (I 2 =95.08%, p-value<0.01). We performed sensitivity analysis and found statistically significant pooled mean differences by omitting of all included studies sequentially. There was no observable publication bias seen in the traditional funnel plot. GRADE Assessment: The certainty of evidence for the outcome of gross and fine motor skills development was rated as low. Although the pooled effect was statistically significant and sensitivity analyses supported the robustness of the findings, the rating was downgraded due to serious inconsistency (very high heterogeneity) and the observational nature of most included studies. No downgrades were made for publication bias, as the funnel plot appeared symmetrical. The low certainty indicates that while prenatal multiple micronutrient supplementation may improve motor development, the magnitude and consistency of the effect remain uncertain, and further high-quality randomized trials are needed to strengthen the evidence base. Meta-analysis results of socioemotional and behavioral development Nine studies were evaluated in the current meta-analysis to see the association between multiple micronutrients supplementation during pregnancy and children socioemotional and behavioral development in the postnatal period. Our meta-analysis result showed no significant association between prenatal multiple micronutrients supplementation and socioemotional and behavioral developments of children, pooled mean difference of 0.23 with 95%CI: -0.02, 0.48 ( Figure 7 ). A random-effects model analysis was performed due to the high heterogeneity distinguished between included studies (I 2 =87.23%, p-value<0.01). Sensitivity analysis was performed and observed non-significant pooled mean differences in omitting one at a time of all included studies. Noticeable publication bias was not found in the traditional funnel plot. GRADE Assessment: The certainty of evidence for the outcome of socioemotional and behavioral development was rated as low. The rating was downgraded due to serious inconsistency (high heterogeneity) and imprecision, as the confidence interval crossed the line of no effect and sensitivity analyses consistently yielded non-significant results. Although no publication bias was detected, the evidence base consisted primarily of observational studies, which begin at a lower certainty level. The low certainty indicates that current evidence is insufficient to determine whether prenatal multiple micronutrient supplementation has a meaningful impact on socioemotional and behavioral development in children. Discussion Women’s well-being, nutrition, and health from preconception through pregnancy are critical for supporting successful pregnancy and long-term outcomes for both mother and child. Convincing epidemiological studies have documented that poor nutrition during pregnancy, particularly in the form of insufficient or deficient micronutrient intake, is associated with adverse neurodevelopmental outcomes in children, including lower cognitive functioning, deficits in social communication, and disruptive behavioral problems [53]. The present systematic review and meta-analysis is comprehensive, up-to-date, and field advancing in nature, presenting systematically synthesized and meta-analyzed evidence on the association between prenatal multiple micronutrients supplementation and neurodevelopmental outcomes such as autistic-like behaviors, cognitive development, language and communication development, psychomotor development and socioemotional and behavioral development in children in comparison to no supplementation or low supplementation. Our meta-analysis result showed prenatal micronutrients supplementations had an effect in neurodevelopment of children in later life. Our finding is in agreement with the previous study findings conducted elsewhere [17, 54, 55]. Accordingly, our meta-analysis result revealed that prenatal multiple micronutrients supplementation has a statistically significant association with autistic-like behavior in children as compared to no supplementation or supplementation with only IFA. Children born from mothers with multiple micronutrients supplementation during pregnancy will have a 56% chance of reduction in autistic-like behavior as compared to those children born from mothers with no supplementation or supplementation with only IFA. Our meta-analysis also found multiple micronutrients supplementation significantly associated with cognitive and psychomotor development of children as compared to those with no supplementation or IFA supplementation only. This may be due to the fact that brain development will be affected by inadequate nutrient intake. It is assumed that all nutrients are important for neuronal and supporting cell growth and development, but some have more well-defined impacts during the prenatal period, explicitly on brain circuitry involved in basic neurocognitive processes [56]. Across brain areas, deficits in relevant specific maternal nutrient intake in early gestation have an immense effect on cell proliferation, and thus, cell number. While deficits later in gestation impact cell differentiation, including size and complexity, which, in the case of neurons, will also affect synaptogenesis and dendritic arborization [56]. Micronutrients, such as FA, iron, zinc, and other vitamins, contribute to genome changes in the growing embryo during the critical period of embryogenesis [57], which in turn influences cognitive function [58]. In case of no supplementation of micronutrients during pregnancy, there may be a deficiency in iron or folic acid, which are very important for brain development and methylation. Whereas, in case of only IFA supplementations during gestation there may be deficient in zinc and vitamin B12 which are more important for brain DNA and RNA synthesis, which begins early in gestation [59] as well as more important for cognition, memory and motor development [60]. Our meta-analysis showed no significant differences in language and communication skills, as well as socioemotional and behavioral development, among children born to mothers who received multiple micronutrient (MMN) supplementation during pregnancy compared to those born to non-supplemented or iron and folic acid (IFA) supplemented mothers. Researchers in nearly all included studies attempted to control for potential confounding factors using various methods to better clarify the association between maternal micronutrient supplementation during gestation and neurodevelopmental outcomes in children. However, since most studies relied on self-reported intake, which is subject to recall and reporting bias, there may still be unaccounted maternal and paternal characteristics that confound the observed associations. Additionally, there may be no significant differences in body concentrations of micronutrients between supplemented and non-supplemented groups due to contextual variations in baseline nutrient status across study populations. In some cases, the non-supplemented group may have compensated through dietary intake or food fortification [61]. More importantly, the timing, duration, and dose of supplementation of micronutrient may contribute to the lack of observed differences. For example, supplementation after the first trimester of pregnancy may result in lack of certain micronutrients which may be required in the periconceptional period so as to promote normal embryogenesis, hence the full effect of nutrients may not be realized. It has been revealed that periconceptional supplementation of micronutrients significantly influenced neurodevelopment in children as compared to other period of supplementations[62]. It has been also reported that, the impact of prenatal micronutrients supplementation on offspring’s neurodevelopment differs for different time of embryo development [40]. Specific areas of the human brain develop quickly with neurogenesis and migration of neural cells starting early in the first months of pregnancy[63]. The brain and spinal cord are particularly susceptible to environmental stimuli, such as nutrition, during this critical period of growth, proliferation, and differentiation [17]. Similar to other systematic reviews, this systematic review and meta-analysis has its own limitation. Therefore, these limitations should be considered before the interpretation of the findings. The major limitation of this study is only those studies reported in English language were considered to conduct this review; hence, the finding of the current review may be affected by those reports published in other languages. In addition, in this study moderate to high heterogeneity were observed among included studies in most of analyzed neurodevelopmental outcomes. Hence, a random-effects model and sensitivity analysis were performed to adjust the issue of heterogeneity. The major factor for heterogeneity across included studies may be differences in contextual nutrients status [61]. The other possible justifications of the observed heterogeneity may be variability in the study area, sample size, design, exposure initiation time, exposure duration, outcome measurement approaches and others. But the current systematic review and meta-analysis has strengths. The first strength is that this review and meta-analysis is primary in terms of systematically synthesizing and meta analyzing of existed individual studies in a comprehensive manner which revealed the association between multiple micronutrients supplementation and neurodevelopmental outcomes like autistic-like behavior, cognitive, language and communication, psychomotor, socioemotional and behavioral development in children in comparison to no prenatal supplementation or low prenatal supplementation. In addition, the strength of the present systematic review and meta-analysis is the use of the largest sample size which has high statistical power to reveal the association between prenatal multiple micronutrients supplementation on child health outcomes in the postnatal period; because individual articles may not have enough statistical power to assess the effects of supplementation on child health outcomes. Conclusion The present systematic review and meta-analysis found that multiple micronutrients supplementation during pregnancy significantly reduced the risk of autistic-like behavior in children. By multiple micronutrients supplementation during gestation, it is possible to reduce the risk of autistic-like behavior in children by 56% as compared to no supplementation or supplementations with IFA. The present meta-analysis also indicated a significant association between multiple micronutrients supplementation and cognitive development in children and revealed a significant association between multiple micronutrients supplementation and psychomotor development in children. On the other hand, our meta-analysis showed no significant association between multiple micronutrients supplementation and language and communication development and socioemotional and behavioral skills development in children. Micronutrients supplementation needs to be strengthened particularly in low-income countries where maternal undernutrition is high. The association between prenatal multiple micronutrients supplementation and language and behavioral development in children needs further investigation. Abbreviations ASQ-3: Ages and Stages Questionnaire – Third Edition BMI: Body Mass Index BSID: Bayley Scale of Infant Development CI: Confidence Interval DSM: Diagnostic and Statistical Manual of Mental Disorders ICD: International Classification of Diseases IFA: Iron and Folic Acid MMN: Multiple Micronutrients OR: Odds Ratio RCT: Randomized Controlled Trial UNIMMAP: United Nations International Multiple Micronutrient Antenatal Preparation Declarations Authors’ contribution A.T.W.: Conception of review protocol, study design, literature review, data extraction, data analysis, interpretation and drafting the manuscript. S.A.G.: Literature review, data analysis, data extraction, quality assessment and reviewing the manuscript. All authors contributed equally and have read and approved the manuscript. Availability of data and material Data will be available upon request of the corresponding author. Declaration of conflicting interests The author(s) declared no potential conflicts of interest. Ethical approval Not applicable. Funding The author(s) received no financial support for this article. Informed consent Not applicable. Consent for publication Not applicable. Acknowledgements Not applicable. References Gernand AD, Schulze KJ, Stewart CP, West KP, Jr., Christian P: Micronutrient deficiencies in pregnancy worldwide: health effects and prevention . Nature reviews Endocrinology 2016, 12 (5):274-289. Bourre JM: Dietary omega-3 fatty acids for women . Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie 2007, 61 (2-3):105-112. Fowles ER: What's a Pregnant Woman to Eat? 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Tables Table 1: Searches performed in PubMed, Web of Science, and other databases to examine the effect of prenatal multiple micronutrients supplementation on child neurodevelopment. Databases searched Searching terms Number of identified studies PubMed /MEDLINE Effect[All Fields] AND prenatal[All Fields] AND ("trace elements"[All Fields] OR "micronutrients"[All Fields] OR "trace elements"[MeSH Terms] OR ("trace"[All Fields] AND "elements"[All Fields]) OR "trace elements"[All Fields] OR "micronutrient"[All Fields] OR "micronutrients"[MeSH Terms] OR "micronutrients"[All Fields]) AND supplementation[All Fields] AND status[All Fields] AND children's[All Fields] AND neurodevelopment[All Fields] 618 Web of Science Core Collection Search Query : TS=("prenatal micronutrient supplementation" AND "child neurodevelopment") AND TS=("systematic review" OR "meta-analysis") 10 Google Scholar “Effect” and “prenatal” and “micronutrient” and “supplementation” and “status” and “children” and “neurodevelopment” 8450 From other sources 72 Total accessed articles 9150 Final full-text articles relevant to current study 26 Table 2: Background characteristics of included studies in the current systematic review and meta-analysis. Studies Samples and study Country Intake and dose intervention/MMN group Intake and dose control group Initiation and duration of exposure and methods of exposure assessment Types of neuro development assessed and assessment methods Adjusted confounders Li et al, 2009 [36]/RCT 5828 sample in China UNIMMAP Received 400 µg of folic acid and 60mg of iron per day From 14 weeks of gestation until delivery assessed through allocation Cognitive development and psychomotor development assessed through BSID at the age of 6 and 12 months Infant’s age, gender, gestational age at birth, Apgar scores at 1 and 5 minutes after birth, birth weight, history of pathological jaundice, history of pneumonia, mother’s age at delivery, BMI at enrollment, educational level, occupational class, number of supplement tablets consumed, father’s educational level and occupational class, and family socioeconomic status. He et al, 2020 [23]/cross sectional 446 samples taken in China Vitamins and minerals taken for at least three times a week None taken In the first three months of pregnancy assessed by interview using structured questionnaire Communication skill, motor, problem solving and personal social development through BSID-III by the age of 6-24 months Gender, age, birth weight, and height-for age of child, age and education of mother, whether mother is primary caregiver, family income, home parenting environment, duration of breastfeeding in month, complementary feeding when child aged above 6 months, and village fixed effect. Cheng et al, 2019 [22]/Cohort 939 samples in China Mothers who took iron, FA, multivitamin, and zinc supplements Mothers who used both iron and FA supplements During pregnancy known by face-to-face intervein using questionnaire Communication, gross motor, fine motor, problem solving and personal social assessed by ASQ-3 at 3 years of age Maternal age, maternal education, average monthly household income, maternal postpartum BMI, maternal height, maternal calcium supplementation, gestational dietary intake, passive smoking during pregnancy, alcohol use during pregnancy, maternal parity, infant gender, infant birthweight, length at birth, gestational age, infant feeding practices, infant supplement use, and infant dietary intake. Christian et al, 2016 [38]/RCT 8529 samples in Bangladesh 13 micronutrients in addition to the IFA at the same amount in the control supplement Iron (27 mg) and folic acid (600 mg) supplement daily From 10.9 week through 3 months postpartum during allocation Cognitive, communication and psychomotor development by BSID-III at the age of 2 years Household demographic and socioeconomic statuses, maternal husband’s and their own education and occupation, pregnancy history, breastfeeding and complementary feeding practices, morbidity histories, treatments sought, and vaccinations status. Prado et al, 2017 [64]/RCT 19 274 sample in Indonesia UNIMMAP Mothers who used IFA capsule contained 30 mg iron and 400 μg folic acid MMN or IFA capsules taken daily throughout the duration of pregnancy and until 3 months postpartum known during allocation Cognitive development, motor (fine & gross), and personal social assessed using set of specific tests adapted to local context by the age of 9-12 years Maternall and paternal education, maternal MUAC, maternal haemoglobin, height, wealth index, preterm birth, small for gestational age, postnatal growth, child haemoglobin, child age and sex, HOME inventory score, and maternal depression score. Tofail et al, 2008 [26]/RCT 2853 sample in Bangladesh MM group took UNIMMAP package IFA group received 30 mg Fe and 400 μg folate Daily supplementation from week 14 of gestation until delivery assessed during allocation Problem-solving, motor development and behavior/ personal social assessed by problem-solving support and cover tests, Psychomotor Developmental Index (PDI) of the Bayley Scales of Infant Development-II and Wolke’s behavior ratings at the age of 7 months Maternal age, mothers’ BMI, hemoglobin, parity, parents’ education and employment, housing quality, family wealth, food groups, and sex and birth weight of infants. Li et al, 2015 [27]/RCT 1744 sample in China UNIMMAP package 400 μg/d folic acid and 30mg/d Fe Daily supplementation from week 14 of gestation until delivery assessed during allocation Cognitive development assessed by Wechsler Intelligence Scale for Children Fourth Edition (WISC-IV) at the age of 7-10 years Age of children, household wealth index, fathers’ educational level, maternal occupation, child school level, number of supplement tablets consumed, birth weight, history of anemia, gestational weeks, and respiratory tract infection. Christian et al, 2010 [24]/RCT 676 sample in Nepal UNIMMAP package Folic acid (400 μg) plus iron (60 mg) Daily supplementation from 11 weeks of pregnancy through 3 months postpartum assessed during allocation Cognitive development and motor development assessed by Universal Nonverbal Intelligence Test (UNIT); Movement Assessment Battery for Children (MABC) by the age of 7 to 9 years Design effect, age, sex, schooling status, asset score, diary product intake, meat/chicken/fish intake, lower respiratory tract infection, and diarrhea/dysentery. McGrath et al, 2006 [37]/RCT 681 sample in Tanzania Multivitamins which include vitamin A (30 mg of beta-carotene plus 5000 IU preformed vitamin A);20 mg of B1, 20 mg of B2, 25 mg of B6, 100mg of niacin, 50 μg of B12, 500 mg of C, 30 mg of E, and 0.8 mg of folic acid. None taken (placebo) Daily supplementation from 12 weeks of gestation up to immediate postpartum period assessed during allocation Cognitive and psychomotor development through Bayley Scales of Infant Development, 2nd Edition (BSID-II) at the age of 6, 12 and 18 months Maternal age, test administrator, prematurity, maternal CD4 at baseline and BMI, and child’s HIV-1 status and gender. Hanieh et al, 2013 [25]/RCT 1,258 sample in Viet Nam One capsule of MMNs taken twice a week (60 mg elemental iron plus 1.5 mg folic acid plus a variation of the dose of micronutrients in the UNIMMAP) One capsule of IFA taken twice a week (60 mg elemental iron plus 1.5 mg folic acid per capsule; administered as 2 capsules/week) Twice per week from less than 16 weeks of gestation up to 3 months postpartum assed during allocation Cognitive, communication, motor, and personal social development assessed by BSID III at the age of 6 months Maternal age, parity, randomization, birth weight, infant gender and gestational age. Prado et al. 2012 [21]/RCT 487 sample in Indonesia Iron 30 mg, Folic acid 400 μg, Retinol (retinyl acetate) 800 μg Vitamin D (ergocalciferol) 200 IU Vitamin E (a-tocopherol acetate) 10 mg Ascorbic acid 70 mg Vitamin B1 (thiamine mononitrate) 1.4 mg Vitamin B2 (riboflavin) 1.4 mg Niacin (niacinanide) 18 mg Vitamin B6 (pyridoxine) 1.9 mg Vitamin B12 (cyanocobalamin) 2.6 μg Zinc (zinc gluconate) 15 mg Copper 2 mg Selenium 65 μg Iodine 150 μg Iron 30 mg and Folic acid 400 μg Women received a daily supplement throughout the duration of pregnancy and until 3 months postpartum assessed during allocation Cognitive, communication, motor and personal social development assessed by Bayley Scale of Motor Development and the Ages and Stages Questionnaire; Picture Vocabulary Test; Block Design Test; Socioemotional Development Scale at the age of 42 months Home Observation for the Measurement of the Environment (HOME) inventory score, child’s Hb concentration, mother’s MUAC, birth weight, and compliance (mean percentage of supplements consumed). D’Souza et al 2019 [65]/Cohort 6246 samples in New Zealand Mothers took multivitamins during pregnancy Mothers who did not take multivitamins during pregnancy During pregnancy assessed by interview of mothers using questionnaire Behavioral problems/personal social by Strengths and Difficulties Questionnaire (SDQ) at the age of 2 years Mother’s ethnicity, mother’s education, mother’s age when pregnant, child’s gestational age, child’s birth weight, child’s gender, parity, planned pregnancy, mother in paid employment, area-level deprivation, and rurality D’Souza et al, 2019 [66]/Cohort 5768 samples in New Zealand Mothers took multivitamins during pregnancy Mothers did not take multivitamins during pregnancy During pregnancy assessed through interview of mothers using questionnaire Behavioral problems and communication problems by SDQ and MacArthur-Bates Communicative Development inventories (CDIs) at the age of 2 years Maternal depression, maternal lifestyle factors such as smoking, alcohol intake , mother’s ethnicity, mother’s education, mother’s age, parity, whether or not the pregnancy was planned, socioeconomic deprivation, Child’s gender, gestational age at birth, and birthweight. Tan et al, 2020 [67]/Case control 617 (416 case and 201 control in China Mothers took multi micronutrients during pregnancy Mothers who did not took any supplements during pregnancy During pregnancy (from LMP to birth for at least 4 days per week) assessed through structured interviews of mothers Language problem, motor development, personal social development and autistic like behaviors assessed by revised Gesell Developmental Scale (GDS) and Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria at the mean age of 4.68 years for cases; mean age of 4.47 years for controls Age of the child at assessment, gender, residence, household income, age of mothers at child’s birth, age of the fathers at child’s birth, birth mode and gestational weeks at birth, and birth weight. Liew et al, 2018 [68]/Cohort 20247 samples in Denmark Mothers took multivitamins during pregnancy Women who indicated no supplement use for the same entire period were used as the unexposed group Multivitamin use beginning 4-weeks prior to their LMP through 8-weeks after their LMP (−4 to 8 weeks) assessed through interview of mothers using questionnaire Behavioral problems/personal social assessed by SDQ by the age of 7 years Maternal age; household socio-economic status; maternal smoking; and alcohol consumption during pregnancy, maternal pre-pregnancy body mass index, birth year, offspring sex. Surén et al, 2013 [69]/Cohort 85,176 in Norway Mothers who took folic acid plus other vitamins and minerals No any supplements 4 weeks before to 8 weeks after the start of pregnancy assessed through food frequency questionnaire report of mothers Autistic disorder assessed by Autism Diagnostic Interview – Revised (ADI-R) and Autism Diagnostic Observation Schedule (ADOS) by the mean age of 6.4 years Parental education, parental age, whether the pregnancy was planned, maternal smoking during pregnancy, maternal body mass index, parity, and year of birth. Schmidt et al, 2011 [70]/Case control 566 (288 case & 278 control) in USA Daily multivitamin intake during the stated period No any supplements Periconceptional period (three months before pregnancy through the first month of pregnancy) assessed through telephone interviews of mothers Autism risk assessed by Autism Diagnostic Interview–Revised and Autism Diagnostic Observation Schedule at the age of 24–60 months Maternal education and child’s birth year Schmidt et al, 2012 [71]/Case control 707 (429 case & 278 control) sample in USA Daily multivitamin intake during the stated period No any supplements Periconceptional period (three months before pregnancy through the first month of pregnancy) assessed by telephone interviews of mothers Autism spectrum disorder assessed using the Autism Diagnostic Interview–Revised and Autism Diagnostic Observation Schedule by the age of 24-60 months Child sex and birth year, maternal and child race-ethnicity, maternal age, maternal education, pre pregnancy BMI, maternal birthplace, cigarette smoking, alcohol consumption and paternal age. Schmidt et al, 2019 [72]/Cohort 332 sample in USA daily multivitamin intake during 1st months of gestation no any supplements Multivitamins use in the 1st months of gestation assessed through telephone-assisted interviews and mailed questionnaire Autism spectrum disorder assessed using the Autism Diagnostic Interview–Revised and Autism Diagnostic Observation Schedule at 36 months of age Maternal age and education, mode of delivery, and maternal intention to become pregnant Virk et al, 2016 [73]/Cohort 35,059 sample in Denmark Women who took multivitamins for at least 4 days per week on the stated period Women who did not took any supplement for the same entire period were used as the unexposed group 4 weeks prior from the last menstrual period through to 8 weeks after the last menstrual period (−4 to 8 weeks) assessed by structured interviews of mothers Autistic disorder assessed based on International Classification of Diseases, 10 th edition (ICD-10) at the mean age of 9.6 years Smoking and alcohol consumption during pregnancy, maternal pre-pregnancy BMI, maternal mental health status, and socioeconomic status DeSoto & Hitlan, 2012 [74]/Case control 256 case children & 752 controls samples in USA Women who took multivitamins during pregnancy Women who did not took any supplement during pregnancy During pregnancy intake was assessed by interview of mothers using questionnaire Autistic like disorder assessed by Discriminant Function Analysis (DFA) by the age of 6-12 years Maternal age, birth weight, poverty ratio, birth order, breast feeding duration, maternal prenatal health care/seeking behavior, and child medical conditions Braun et al, 2014 [75]/Cohort 209 sample in USA Women who took multivitamins in 2nd trimester of gestation daily Women who did not took any supplement during pregnancy During 2nd trimester of pregnancy assessed by interview of mothers using questionnaire Autistic behavior assessed by Social Responsiveness Scale (SRS) by the age of 4-5 years Maternal age, race, education, household income, marital status, health insurance, employment, frequency of fresh fruit/vegetable intake, and food security DeVilbiss et al, 2017 [76]/Cohort 273, 107 sample in Sweden Women who took multivitamins during pregnancy daily Women who did not took any supplement during pregnancy During the entire pregnancy period assessed by interview of mothers using questionnaire ASD assessed based on international classification of diseases, 10 th revision (ICD-10) & Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV) by the age of 4 to 15 years Child characteristics (sex, birth year, and years resided in Stockholm County), socioeconomic indicators (education, family income, and maternal birth country), maternal characteristics (age, body mass index, parity, smoking status), medication use during pregnancy (antidepressants or antiepileptics), and maternal neuropsychiatric conditions (anxiety disorders, autism, bipolar disorder, depression, epilepsy, intellectual disability, non-affective psychotic disorders, and stress disorders) Levine et al, 2018 [77]/Cohort 45,300 samples in Israel Women took multivitamins during pregnancy on daily bases Women with no any supplement intake During the entire gestation up to birth confirmed by interview of mothers using questionnaire ASD based on International Classification of Diseases, Ninth Revision by the age of 8 to 12 years Sex, birth year, socioeconomic status, maternal and paternal psychiatric diagnosis by childbirth, maternal and paternal age at childbirth, and parity Raghavan et al, 2018 [52]/Cohort 1257 samples in USA Multivitamin supplement intake for ≤2 times/week and >5 times/week Multivitamin supplement intake for 3-5 times/week Supplementation during, preconception, 1 st , 2 nd and 3 rd trimesters assessed though mothers self-report Autism risk based on ICD-9 aged up to 12 years Child sex, maternal age at delivery, smoking during pregnancy, parity, maternal education, year of the baby's birth and Methylene tetrahydrofolate reductase (MTHFR) C677T genotypes. Li et al, 2018 [51]/Case control 374 cases; 354controls taken in China Folic acid and calcium intake during pregnancy preparation, during pregnancy or during lactation Folic acid intake during pregnancy preparation, during pregnancy or during lactation or no intake on the stated period Folic acid and calcium intake during pregnancy preparation, during pregnancy or during lactation were assessed by interview of mothers using structured questionnaire Autistic disorder according to the Diagnostic and Statistical Manual of Mental Disorders. Fourth Edition, Text Revision (DSM-IV-TR) among children aged 3 to 6 years Child’s age and gender, parental age, maternal BMI before conception and delivery, and premature delivery RCT: Randomized Controlled Trial; BSID: Bayley Scales of Infant Development; BSID-II: Bayley Scales of Infant Development, 2nd Edition; BSID-III: Bayley Scales of Infant Development–third edition; ASQ-3: Ages and Stages Questionnaires, Third Edition; FA: Folic Acid; IFA: iron and folic acid; WISC-IV: Wechsler Intelligence Scale for Children- Fourth Edition; SDQ: Strengths and Difficulties Questionnaire; CDIs: MacArthur-Bates Communicative Development inventories; UNIMMAP: United Nations International Multiple Micronutrient Antenatal Preparation; DSM: Diagnostic and Statistical Manual of Mental Disorders; BMI: Body Mass Index; ICD: International Classification of Diseases; LMP: Last Menstrual Period; ASD: Autism Spectrum of Diseases; ADI-R: Autism Diagnostic Interview Revised; ADOS: Autism Diagnostic Observation Schedule; DFA: Discriminant Function Analysis; SRS: Social Responsiveness Scale. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7713425","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":520596647,"identity":"0cc946f9-1ad5-4f38-8e63-3fa8791ff8b0","order_by":0,"name":"Amsalu Taye 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13:24:00","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":true,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7713425/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7713425/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":92495820,"identity":"244d1050-ae8a-4793-a30a-2c58398016d7","added_by":"auto","created_at":"2025-09-30 10:24:02","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":557525,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of study selection for systematic review and meta-analysis of prenatal multiple micronutrient supplementation effects on child neurodevelopment.\u003c/p\u003e","description":"","filename":"Figure1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7713425/v1/932efb0bbdde48bc25e259d5.jpeg"},{"id":92495823,"identity":"628039b4-8970-41c2-9090-6144d91d009b","added_by":"auto","created_at":"2025-09-30 10:24:03","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":436763,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of prenatal multiple micronutrients supplementation effect on autistic-like behavior in children.\u003c/p\u003e","description":"","filename":"Figure2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7713425/v1/610886acd28c9c358dfc2fe1.jpeg"},{"id":92495822,"identity":"f4be2760-9510-45de-8c27-637e44c654be","added_by":"auto","created_at":"2025-09-30 10:24:03","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":474186,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of prenatal multiple micronutrients supplementation and risk of autistic-like behavior in children based on study design.\u003c/p\u003e","description":"","filename":"Figure3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7713425/v1/37a11236d093fe675644ef72.jpeg"},{"id":92495821,"identity":"f7f68fc8-2009-43ce-9791-c2d6fed8bd11","added_by":"auto","created_at":"2025-09-30 10:24:03","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":289918,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of the association between prenatal multiple micronutrients supplementation and cognitive development of children.\u003c/p\u003e","description":"","filename":"Figure4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7713425/v1/2618e2a0194a27f57d197fc6.jpeg"},{"id":92495828,"identity":"6a8bf5bd-9933-4f22-80f6-32a22429b3d8","added_by":"auto","created_at":"2025-09-30 10:24:03","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":164410,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of the association between prenatal multiple micronutrients supplementation and language and communication developments of children.\u003c/p\u003e","description":"","filename":"Figure5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7713425/v1/bbc24e20b70f4a209b82c774.jpeg"},{"id":92495826,"identity":"12ee0df6-db2c-4984-a7cc-9f9e593d7bab","added_by":"auto","created_at":"2025-09-30 10:24:03","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":199482,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of the association between prenatal multiple micronutrients supplementation and psychomotor skills development of children.\u003c/p\u003e","description":"","filename":"Figure6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7713425/v1/42d8dd9ce4e147262d3e084f.jpeg"},{"id":92495824,"identity":"40492f7f-5969-4cd6-a3f7-2e2a1a11fd1a","added_by":"auto","created_at":"2025-09-30 10:24:03","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":144646,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of the association between prenatal multiple micronutrients supplementation and children’s socioemotional and behavioral development.\u003c/p\u003e","description":"","filename":"Figure7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7713425/v1/92eb9ba847652a5ece99790d.jpeg"},{"id":92496713,"identity":"365cedc1-2980-4450-962e-594befce6b9a","added_by":"auto","created_at":"2025-09-30 10:32:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6388120,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7713425/v1/b57cc7a8-ab1f-4a58-9394-36ba5a845846.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003ePrenatal Multiple Micronutrient Supplementation and Child Neurodevelopment: A Systematic Review and Meta-analysis.\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOptimizing outcomes across pregnancy, neonatal, and early childhood stages requires the provision of comprehensive care and support throughout the prenatal, intrapartum, and postpartum periods. Additionally, enhancing women\u0026rsquo;s health during the preconception phase is essential. Evidence indicates that poor maternal nutritional status during both the preconception and prenatal periods adversely affects fetal and neonatal outcomes, including neurodevelopment, physical growth, cardiometabolic health, and immune function [1].\u003c/p\u003e\n\u003cp\u003eExisting scientific evidence demonstrates that good nutritional status of women both before and during pregnancy is vital for promoting normal fetal physical growth and brain development [2]. It also plays a critical role in preventing the occurrence of adverse pregnancy outcomes, congenital anomalies [3], and non-communicable diseases throughout the lifespan of the newborn [4-8]. More importantly, inadequate and/or excessive nutrient intake has been associated with adverse long-term outcomes and noncommunicable diseases in offspring [5]. Fetal development within the intrauterine environmentcan irreversibly change individual genetic and metabolic pathways, leading to adaptive pathophysiological changes in offspring and an increased risk of non-communicable diseases later in life [9]. For example, one adverse pregnancy outcome, low birth weight (LBW), has been associated with an increased risk of cardiovascular disease[10], respiratory problems [11], and polycystic ovary syndrome[12] later in life.\u003c/p\u003e\n\u003cp\u003ePregnancy is a period of significant changes in a woman\u0026rsquo;s physiological status and involves increased nutritional demands to support the growth of the fetus and placenta. As a result, metabolic requirements increase substantially. Therefore, the physiological demands of pregnancy can exacerbate existing nutrient deficiencies, leading to serious health consequences for both the fetus and the newborn [1]. Moreover, studies have consistently reported a frequent co-occurrence of multiple nutrient deficiencies among women of reproductive age, particularly those living in poor socioeconomic settings [13], where diets often lack diversity and fortified foods are less available and consumed [14]. Hence, Hence, ensuring adequate intake of vitamins and minerals (micronutrients)[15], along with other essential nutrients during pregnancy, may require supplementation. This is especially important for women who are undernourished or have inadequate dietary intake due to poverty, disease, lifestyle-related factors, or other conditions. In addition, evidence suggests that supplementation with multiple micronutrients (MMN) during pregnancy reduces the risk of deficiencies and contributes to improved fetal outcomes[16].\u003c/p\u003e\n\u003cp\u003eAvailable scientific evidence indicates that certain nutrients play a critical role in regulating brain development, particularly during the fetal and early postnatal periods. Accordingly, studies have identified that the developing brain is especially susceptible to nutritional deprivation due to its impact on the rapid progression of several neurodevelopmental processes, including synapse formation, neuronal myelination, and the synthesis of neurometabolic and neurotransmitter systems [17-19]. It has been reported that the most important micronutrients for brain development include omega-3 fatty acids, folic acid, iron, zinc, copper, iodine, selenium, vitamin A, and choline [20]. \u003c/p\u003e\n\u003cp\u003eVarious individual studies have demonstrated an association between child neurodevelopment and selected micronutrients such as iron, folic acid, zinc, and multiple micronutrient (MMN) supplementation during pregnancy. However, findings from these studies regarding the impact of micronutrient supplementation on child health outcomes, including neurodevelopment, remain inconsistent. Some studies have reported that supplementation during pregnancy is associated with improved child neurodevelopment, while others have found no association and a few have even reported potential risks. For example, a study conducted in Indonesia [21] found that MMN supplementation during pregnancy significantly improved children\u0026rsquo;s motor and cognitive abilities at 42 months of age compared to iron and folic acid (IFA) supplementation, but showed no significant difference in communication and personal-social skills. A study conducted in China [22] reported significant improvements in communication, gross motor, fine motor, problem-solving, and personal-social skills among the MMN-supplemented group compared to the folic acid plus iron group at 3 years of age. On the other hand, another study in China [23] revealed prenatal MMN supplementation had significantly improved communication skill among children aged 6 to 24 months compared to non-supplemented groups but no significant difference in cognitive, motor, and social-emotional skills between supplemented and non-supplemented groups. In contrary, a study in rural Nepal [24] found that iron and folic acid supplementation, compared to MMN supplementation, led to greater improvements in intellectual, motor, and executive functioning in children aged 7\u0026ndash;9 years. Similarly, a study in Viet Nam [25] reported prenatal IFA supplementation significantly improved cognitive development at 6 months of age compared to MMN supplementation. On the other hand, a study conducted in Bangladesh [26] revealed MMN supplementation as compared to iron and folic acid supplementation significantly improved problem-solving skill, motor development and behavior in infants at the age of 7 months. In contrary, a study in China [27] did not find a significant difference on intellectual development between prenatal MMN and IFA or folic acid alone supplementation in early school aged children (aged 7-10 years).\u003c/p\u003e\n\u003cp\u003eSeveral studies revealed that iodine supplementation during pregnancy improved motor and cognitive development in children[28-30]. A study reported no significant differences in children\u0026rsquo;s cognitive development born from mothers of supplemented and non-supplemented groups with iodine in the preconception period living in the same locality [31]. According to Iannotti et al [32], zinc supplementation during pregnancy improved motor development. On the other hand, other studies done in Bangladeshi and England indicated that zinc supplementation during pregnancy did not improve motor development in children [33, 34]. Similarly, another study revealed that zinc plasma concentration level during pregnancy had a slight long-lasting effect on child\u0026rsquo;s cognitive development [35]. A study also revealed that MMN supplementation as compared to folic acid alone or folic acid plus iron supplementation did not significantly improve psychomotor and cognitive development of infants at 6 months of age and did not significantly improve psychomotor development at 1 year of age [36], but revealed a significant improvement in cognitive development at 1 year of age. In contrary, a study done in Tanzania [37] showed a significant improvement in psychomotor development but not cognitive development among multivitamin supplemented groups compared with none supplemented groups of infants at the age of both 6 and 12 months of age. On the other hand, a trial study in Bangladesh [38] showed prenatal MMN supplementation had no significant effect on cognitive, language and motor development and function at 2 years of age as compared to folic acid plus iron supplementations.\u003c/p\u003e\n\u003cp\u003eMore importantly, individual articles may not have enough statistical power to assess the effects on child health outcomes. An all-inclusive review scoping all aspects of effects of prenatal MMN supplementations on children\u0026rsquo;s neurodevelopment has not been well established so far. Previous reviews have mainly focused on the impacts of prenatal nutrition supplementation, including both single vitamins and multivitamin combinations, on autism spectrum disorders[39-41]. However, a comprehensive review that specifically examines the effects of multiple micronutrient supplementation alone is still urgently needed. Furthermore, most of existed findings regarding the effects of MMN supplementation on communication skill, cognitive skill, motor development and personal social interaction skill has not been yet synthesized and meta-analyzed. Hence, the aim of the current study is to systematically synthesize existing evidence on the association between prenatal multiple micronutrient supplementation during pregnancy and child neurodevelopment. This review uniquely applies updated methodological frameworks, namely the Risk of Bias 2.0 tool and the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach, which to our knowledge have not been previously employed in this context. In addition, the study quantitatively analyzes pooled effect sizes to assess the impact of prenatal multiple micronutrient intake on neurodevelopmental outcomes in children.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe current systematic review and meta-analysis is prepared and presented based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline[42]. The protocol of this review was not registered in PROSPERO.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSearch strategies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA comprehensive search with no date limit of all relevant studies were carried out in the following electronic databases: PubMed/MEDLINE, Web of Science, Scopus, Cochrane Library, CINAHL, Science Direct, and Google Scholar (\u003cstrong\u003eTable 1\u003c/strong\u003e). The search was limited to studies that were conducted in humans and were reported in the English language. In addition, relevant grey literatures such as dissertations, thesis, conference abstracts and others were searched and checked through the access of various subject-specific databases and websites. The search of literatures was used the following keywords individually and in combination through \u0026ldquo;AND\u0026rdquo; or \u0026ldquo;OR\u0026rdquo; Boolean operators as follows: \u0026ldquo;effect\u0026rdquo;, \u0026ldquo;prenatal\u0026rdquo;, \u0026ldquo;antenatal\u0026rdquo;, \u0026ldquo;micronutrients\u0026rdquo;, \u0026ldquo;trace elements\u0026rdquo;, \u0026ldquo;supplement\u0026rdquo;, \u0026ldquo;supplementation\u0026rdquo;, \u0026ldquo;status\u0026rdquo;, \u0026ldquo;children\u0026rdquo; and \u0026ldquo;neurodevelopment\u0026rdquo;. The search of the study findings was conducted between March 1 to April 1, 2022. All articles published until April 1, 2022 were included in the current study. At last, reference lists of accessed studies and related review reports were also examined to identify more eligible articles. The primary authors of few articles were contacted for missing data or to clarify vague methods or results reported, and accordingly most responded to the request and given raw data from which necessary analysis was performed, and those studies with no reply were excluded. Identified researches by our search strategy were collected and managed by using EndNote library.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eEligibility criteria and study selection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion criteria: \u003c/strong\u003eStudies included in this systematic review and meta-analysis were conducted on human children under 18 years of age. Eligible designs included observational studies (cross-sectional, case-control, and cohort) and interventional studies (randomized controlled trials) that evaluated the association between prenatal multiple micronutrient supplementation and neurodevelopmental outcomes in children. Only studies published in English were considered. Importantly, studies were included if they assessed the effects of prenatal supplementation with at least three micronutrients, including formulations such as the United Nations International Multiple Micronutrient Preparation (UNIMMAP)[43], compared to supplementation with two or fewer micronutrients, no supplementation, or placebo. Included studies had no limits on time of initiation of supplement and duration of supplementations for micronutrients during pregnancy. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExclusion criteria: \u003c/strong\u003estudies were excluded if they were animal studies, reviews, editorials, clinical\u003c/p\u003e\n\u003cp\u003eanswers, case reports or case series, commentaries, or letters to the editor. A small number of studies were excluded due to incomplete data, despite at least three attempts to contact the corresponding authors. These exclusions were necessary because the lack of complete data prevented proper quality assessment. Studies in which the intervention included fewer than three micronutrients were excluded.\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOutcome measures \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe outcomes measured in this study are various types of child neurodevelopmental outcomes, including autistic-like behaviors, cognitive development, language and communication development, psychomotor development, and social-emotional and behavioral development. These outcomes were assessed among children under 18 years of age. Child neurodevelopmental status was evaluated using the Ages and Stages Questionnaire \u0026ndash; Third Edition (ASQ-3) [44], Bayley Scale of Infant Development (BSID) [45], International Classification of Diseases (ICD) criteria, Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria, and other tools (\u003cstrong\u003eTable 2\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData abstraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were extracted using a standardized template developed in Microsoft Excel, adapted from the Cochrane Review Group (CRG). Two authors of this review (ATW and SAG) independently extracted the following information from each study: first author\u0026rsquo;s name, year of publication, study country, study design, sample size, assessment methods for prenatal micronutrient intake, duration of intake, intake levels/dose, offspring\u0026rsquo;s age at assessment, outcome assessment method, types of neurodevelopmental outcomes, adjusted and crude risk estimates with corresponding 95% confidence intervals (CIs), and adjusted confounders. Any discrepancies between the two authors during data extraction were resolved through discussion until consensus was reached. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRisk of bias assessment in included studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo review authors (ATW and SAG) independently assessed the risk of bias for each study included in this systematic review and meta-analysis using a predetermined assessment form. Any disagreements were resolved through discussion, and in a few cases, study authors were contacted for clarification. Quality indicators were adapted from the Cochrane Handbook for Systematic Reviews of Interventions [46] and used to determine the risk of bias level for each included study.\u003c/p\u003e\n\u003cp\u003eFor randomized controlled trials (RCTs), the following criteria were used: 1. Method of sequence generation; 2. Allocation concealment; 3. Blinding of participants; 4. Method of outcome assessment; 5. Incomplete outcome data; 6. Selective outcome reporting; 7. Other potential sources of bias. Based on the reviewers\u0026rsquo; judgments, studies were categorized as having high, low, or unclear risk of bias. Moreover, the quality of observational studies was assessed through Newcastle-Ottawa Quality Assessment parameters [47]. Accordingly, selection procedures, comparability issues and outcome measures were considered, to assess the quality of included cross-sectional and cohort studies. Selection procedures, comparability and exposure parameters were also considered for quality assessment of case-control studies. Based on the parameters\u0026rsquo; studies are classified as low, medium and high-quality studies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCertainty of Evidence Assessment:\u003c/strong\u003e The certainty of evidence for each outcome was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework. This approach evaluates the quality of evidence across five domains: risk of bias, inconsistency, indirectness, imprecision, and publication bias. For randomized controlled trials, the initial rating was high, while observational studies began as low certainty. Downgrading or upgrading decisions were made based on predefined criteria.\u003c/p\u003e\n\u003cp\u003eSummary of Findings tables were generated using GRADEpro GDT software, presenting pooled effect estimates, number of studies and participants, and the final certainty rating for each outcome. The GRADE assessments were conducted independently by two reviewers, with discrepancies resolved through discussion or consultation with a third reviewer.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData processing and analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExtracted data in Microsoft Excel spreadsheet software were imported into R (version 4.1.3) software and STATA version 14 software. Using R (version 4.1.3) software, we have demonstrated the association between prenatal multiple micronutrients supplementation of women and children\u0026rsquo;s neurodevelopment consequences which include cognitive development skills, socioemotional and behavioral skills, language and communication development skills, and psychomotor development skills. STATA version 14 software was used to reveal the association between multiple micronutrients supplementation during pregnancy and autistic-like behavior in children. In the current analysis, the reference category was the lowest category of micronutrients supplementation or no supplementations. Statistical heterogeneity among included studies were assessed using Cochran\u0026rsquo;s Q-test and I\u003csup\u003e2\u003c/sup\u003estatistics. I\u003csup\u003e2\u003c/sup\u003e value ranges from 0% to 100%[48], where 0% indicates no observed heterogeneity and large values indicate increasing heterogeneity. An I\u003csup\u003e2\u003c/sup\u003e value of less than 25%, 25-50%, 50-75% and greater than 75% is considered as very low, low, moderate and high heterogeneity respectively[48]. Since the test statistic showed statistically significant heterogeneity among the studies on cognitive, language, psychomotor and behavioral development (I\u003csup\u003e2\u003c/sup\u003e = 42.2%, p\u0026lt;0.05; 53.98%, p\u0026lt;0.05; 95%, p\u0026lt;0.01; 87%, p\u0026lt;0.01 respectively), a random-effects meta-analysis model was used to estimate the DerSimonian and Laird\u0026apos;s pooled size effects. To decrease random variations of primary studies, we conducted subgroup analyses based on study design, study settings, sample size, and year of publication. Meta-regression analysis was also performed to investigate the possible sources of heterogeneity among subgroups. At last, we performed sensitivity analyses to explore whether individual study strongly affected the results of the meta-analysis, by deleting one study at a time. Publication bias was assessed via visual inspection of traditional and Begg\u0026rsquo;s funnel plots for asymmetry. In addition, publication bias was also assessed using both Egger\u0026rsquo;s[49] and Begg\u0026rsquo;s test [50], and for both tests statistically significant publication bias was declared at a p-value \u0026lt; 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eStudy selection processes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWith electronic and manual searches, a total of 9,150 study titles were identified, including 667 duplicates, leaving 8,483 articles for screening (Figure 1). Of these, 8,401 were excluded based on title and abstract review, resulting in 82 articles for full-text assessment. These full-text articles were evaluated using predetermined eligibility criteria. Of the 82 articles, 56 were excluded due to irrelevant exposures and/or outcomes. Specifically, some studies examined micronutrient supplementation combined with macronutrients but did not analyze the effects of micronutrients separately. Others focused solely on iron and folic acid supplementation, which did not meet the criteria for multiple micronutrient exposure. Several studies described the exposure as \u0026ldquo;dietary supplements\u0026rdquo; without clarifying whether these were micronutrient-based. Additionally, a number of studies reported outcomes related to child growth such as weight, height, length, and other anthropometric indices, rather than neurodevelopmental outcomes. After full-text review, 26 articles remained. Of these, 24 met the inclusion criteria for both the systematic review and meta-analysis. The remaining two were included only in the systematic synthesis but excluded from meta-analysis: one study [51] had a somewhat vague definition of micronutrient exposure, and the other [52] used a reference category that was neither low nor no supplement use.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eBrief description of included studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe characteristics of the included studies are presented in detail in Table 2. Of the 26 studies included in this systematic review and meta-analysis, 9 were randomized controlled trials (RCTs), 11 cohort studies, 5 case-control studies, and 1 cross-sectional study, published between 2006 and 2020. The sample sizes of the included studies ranged from 209 to 273,107 participants. Approximately 46% of the studies were conducted in the USA (6 studies) and China (6 studies). The remaining studies were conducted in Denmark (2), New Zealand (2), Bangladesh (2), Indonesia (2), Norway (1), Vietnam (1), Sweden (1), Nepal (1), Israel (1), and Tanzania (1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults of neurodevelopmental outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeta-analysis results of autistic-like behavior\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThirteen studies met the inclusion criteria for the meta-analysis of autistic-like behavior (Figure 2), including nine cohort studies and four case-control studies. The overall meta-analysis result showed a statistically significant association between prenatal multiple micronutrients supplementation and the risk of autistic-like behavior in children during the postnatal period, the pooled OR 0.44 with 95%CI:0.3, 0.63. Statistically significant heterogeneity is not observed (I\u003csup\u003e2\u003c/sup\u003e=0%, p-value=0.883). We performed sensitivity analysis and found significant pooled OR for all of the omitted studies. Similarly, meta-analysis of both cohort and case-control studies showed a significant association between prenatal multiple micronutrients supplementation and risk of autistic-like behavior in children (\u003cstrong\u003eFigure 3\u003c/strong\u003e). Meta-analysis of cohort studies found pooled OR with 95%CI, 0.49: 0.3, 0.78 and found no significant heterogeneity (I\u003csup\u003e2\u003c/sup\u003e=0%, p-value=0.912). Sensitivity analysis was performed and found significant pooled OR except Levine et al, 2018 study. Pooled OR with 95%CI after omitting Levine et al, 2018 study is 0.64: 0.32, 1.17. The traditional funnel plot showed a little bit asymmetric distribution of included studies and hence there may be of publication bias due to few studies. Meta-analysis of case-control studies found pooled OR with 95%CI, 0.38: 0.21, 0.67 and found no significant heterogeneity (I\u003csup\u003e2\u003c/sup\u003e=0%, p-value=0.421). Sensitivity analysis was performed and for all of the omitted studies, we found significant pooled OR. The traditional funnel plot showed a little bit asymmetric distribution of included studies and hence there may be publication bias due to few studies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGRADE Assessment\u003c/strong\u003e: The certainty of evidence for the outcome of autistic-like behavior was rated as moderate. Although the pooled effect was statistically significant and consistent across study designs, the rating was downgraded by one level due to suspected publication bias and reliance on observational studies, which inherently begin at a lower certainty level. No downgrades were made for inconsistency, indirectness, or imprecision, given the narrow confidence intervals and low heterogeneity. The moderate certainty suggests that prenatal multiple micronutrient supplementation is likely associated with reduced risk of autistic-like behavior, but further high-quality randomized trials are needed to strengthen confidence in this finding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeta-analysis results of cognitive development\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEleven studies were included in the meta-analysis to evaluate the association between prenatal multiple micronutrients supplementation and the cognitive development of children. The overall analysis showed a statistically significant association between multiple micronutrients supplementation during pregnancy and the cognitive development of children in the postnatal period, pooled mean difference estimates of 0.18 with 95%CI: 0.02, 0.34 (\u003cstrong\u003eFigure 4\u003c/strong\u003e). We perform analysis using a random-effects model since heterogeneity between included studies were noticed (I\u003csup\u003e2\u003c/sup\u003e=42.2%, p-value=0.05). Sensitivity analysis was performed and most significant and some insignificant pooled mean differences were obtained following omitting of studies. Except omitting of Cheng et al, 2019; Prado et al, 2017; Tofail et al, 2008 and Prado et al, 2012, omitting of other included studies yield significant pooled mean differences. Pooled mean difference after omitting Cheng et al, 2019; Prado et al, 2017; Tofail et al, 2008 and Prado et al, 2012 respectively were 0.14, -0.05, 0.34; 0.18, -0.05, 0.42;0.16, -0.07, 0.39 and 0.14, -0.04, 0.31. In our meta-analysis, the traditional funnel plot did not reveal noticeable publication bias.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGRADE Assessment:\u003c/strong\u003e The certainty of evidence for the cognitive development outcome was rated as moderate. Although the pooled effect was statistically significant and supported by multiple studies, the rating was downgraded by one level due to inconsistency (moderate heterogeneity) and imprecision in sensitivity analyses, where exclusion of certain studies led to loss of statistical significance. No downgrades were made for risk of bias or publication bias, as most studies were well-conducted and the funnel plot showed symmetry. The moderate certainty indicates that prenatal multiple micronutrient supplementation is likely beneficial for cognitive development, but further high-quality randomized trials are needed to confirm the magnitude and consistency of the effect.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeta-analysis results of language and communication development\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeven studies were included in this meta-analysis to evaluate the association between multiple micronutrients supplementation during pregnancy on children\u0026rsquo;s language and communication development. The current meta-analysis did not show a significant association between prenatal multiple micronutrients supplementation and children\u0026rsquo;s language and communication skills development, pooled mean difference estimates of 0.18 with 95%CI: -0.03, 0.4 (\u003cstrong\u003eFigure 5\u003c/strong\u003e). A random-effects model analysis was performed due to the moderate heterogeneity distinguished between included studies (I\u003csup\u003e2\u003c/sup\u003e=53.98%, p-value\u0026lt;0.05). Sensitivity analysis was performed and insignificant pooled mean differences were observed in omitting of all included studies. Publication bias was observed in the traditional funnel plot, which may be attributed to a few studies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGRADE Assessment:\u003c/strong\u003e The certainty of evidence for the outcome of language and communication development was rated as low. The rating was downgraded due to inconsistency (moderate heterogeneity) and imprecision, as the confidence interval crossed the line of no effect and sensitivity analyses yielded non-significant results throughout. Additionally, publication bias was suspected based on funnel plot asymmetry. No upgrades were applied, as the included studies were observational and the effect size was small and uncertain. The low certainty suggests that current evidence is insufficient to determine whether prenatal multiple micronutrient supplementation has a meaningful impact on language and communication development in children.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeta-analysis results of psychomotor development\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEleven studies were evaluated to reveal the association between multiple micronutrients supplementation during gestation and children\u0026rsquo;s gross and fine motor skills. Our meta-analysis result shown that prenatal multiple micronutrients supplementation during gestation were significantly associated with psychomotor skill development of children, pooled mean difference of 0.73 with 95%CI:0.19, 1.27 (\u003cstrong\u003eFigure 6\u003c/strong\u003e). A random-effects model analysis was performed due to the sizeable heterogeneity distinguished between included studies (I\u003csup\u003e2\u003c/sup\u003e=95.08%, p-value\u0026lt;0.01). We performed sensitivity analysis and found statistically significant pooled mean differences by omitting of all included studies sequentially. There was no observable publication bias seen in the traditional funnel plot.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGRADE Assessment:\u003c/strong\u003e The certainty of evidence for the outcome of gross and fine motor skills development was rated as low. Although the pooled effect was statistically significant and sensitivity analyses supported the robustness of the findings, the rating was downgraded due to serious inconsistency (very high heterogeneity) and the observational nature of most included studies. No downgrades were made for publication bias, as the funnel plot appeared symmetrical. The low certainty indicates that while prenatal multiple micronutrient supplementation may improve motor development, the magnitude and consistency of the effect remain uncertain, and further high-quality randomized trials are needed to strengthen the evidence base.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeta-analysis results of socioemotional and behavioral development\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNine studies were evaluated in the current meta-analysis to see the association between multiple micronutrients supplementation during pregnancy and children socioemotional and behavioral development in the postnatal period. Our meta-analysis result showed no significant association between prenatal multiple micronutrients supplementation and socioemotional and behavioral developments of children, pooled mean difference of 0.23 with 95%CI: -0.02, 0.48 (\u003cstrong\u003eFigure 7\u003c/strong\u003e). A random-effects model analysis was performed due to the high heterogeneity distinguished between included studies (I\u003csup\u003e2\u003c/sup\u003e=87.23%, p-value\u0026lt;0.01). Sensitivity analysis was performed and observed non-significant pooled mean differences in omitting one at a time of all included studies. Noticeable publication bias was not found in the traditional funnel plot. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGRADE Assessment:\u003c/strong\u003e The certainty of evidence for the outcome of socioemotional and behavioral development was rated as low. The rating was downgraded due to serious inconsistency (high heterogeneity) and imprecision, as the confidence interval crossed the line of no effect and sensitivity analyses consistently yielded non-significant results. Although no publication bias was detected, the evidence base consisted primarily of observational studies, which begin at a lower certainty level. The low certainty indicates that current evidence is insufficient to determine whether prenatal multiple micronutrient supplementation has a meaningful impact on socioemotional and behavioral development in children.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWomen\u0026rsquo;s well-being, nutrition, and health from preconception through pregnancy are critical for supporting successful pregnancy and long-term outcomes for both mother and child. Convincing epidemiological studies have documented that poor nutrition during pregnancy, particularly in the form of insufficient or deficient micronutrient intake, is associated with adverse neurodevelopmental outcomes in children, including lower cognitive functioning, deficits in social communication, and disruptive behavioral problems [53].\u003c/p\u003e\n\u003cp\u003eThe present systematic review and meta-analysis is comprehensive, up-to-date, and field advancing in nature, presenting systematically synthesized and meta-analyzed evidence on the association between prenatal multiple micronutrients supplementation and neurodevelopmental outcomes such as autistic-like behaviors, cognitive development, language and communication development, psychomotor development and socioemotional and behavioral development in children in comparison to no supplementation or low supplementation.\u003c/p\u003e\n\u003cp\u003eOur meta-analysis result showed prenatal micronutrients supplementations had an effect in neurodevelopment of children in later life. Our finding is in agreement with the previous study findings conducted elsewhere [17, 54, 55].\u003c/p\u003e\n\u003cp\u003eAccordingly, our meta-analysis result revealed that prenatal multiple micronutrients supplementation has a statistically significant association with autistic-like behavior in children as compared to no supplementation or supplementation with only IFA. Children born from mothers with multiple micronutrients supplementation during pregnancy will have a 56% chance of reduction in autistic-like behavior as compared to those children born from mothers with no supplementation or supplementation with only IFA. Our meta-analysis also found multiple micronutrients supplementation significantly associated with cognitive and psychomotor development of children as compared to those with no supplementation or IFA supplementation only. This may be due to the fact that brain development will be affected by inadequate nutrient intake. It is assumed that all nutrients are important for neuronal and supporting cell growth and development, but some have more well-defined impacts during the prenatal period, explicitly on brain circuitry involved in basic neurocognitive processes [56]. Across brain areas, deficits in relevant specific maternal nutrient intake in early gestation have an immense effect on cell proliferation, and thus, cell number. While deficits later in gestation impact cell differentiation, including size and complexity, which, in the case of neurons, will also affect synaptogenesis and dendritic arborization [56]. Micronutrients, such as FA, iron, zinc, and other vitamins, contribute to genome changes in the growing embryo during the critical period of embryogenesis [57], which in turn influences cognitive function [58]. In case of no supplementation of micronutrients during pregnancy, there may be a deficiency in iron or folic acid, which are very important for brain development and methylation. Whereas, in case of only IFA supplementations during gestation there may be deficient in zinc and vitamin B12 which are more important for brain DNA and RNA synthesis, which begins early in gestation [59] as well as more important for cognition, memory and motor development [60]. \u003c/p\u003e\n\n\u003cp\u003eOur meta-analysis showed no significant differences in language and communication skills, as well as socioemotional and behavioral development, among children born to mothers who received multiple micronutrient (MMN) supplementation during pregnancy compared to those born to non-supplemented or iron and folic acid (IFA) supplemented mothers. Researchers in nearly all included studies attempted to control for potential confounding factors using various methods to better clarify the association between maternal micronutrient supplementation during gestation and neurodevelopmental outcomes in children. However, since most studies relied on self-reported intake, which is subject to recall and reporting bias, there may still be unaccounted maternal and paternal characteristics that confound the observed associations. Additionally, there may be no significant differences in body concentrations of micronutrients between supplemented and non-supplemented groups due to contextual variations in baseline nutrient status across study populations. In some cases, the non-supplemented group may have compensated through dietary intake or food fortification [61]. More importantly, the timing, duration, and dose of supplementation of micronutrient may contribute to the lack of observed differences. For example, supplementation after the first trimester of pregnancy may result in lack of certain micronutrients which may be required in the periconceptional period so as to promote normal embryogenesis, hence the full effect of nutrients may not be realized. It has been revealed that periconceptional supplementation of micronutrients significantly influenced neurodevelopment in children as compared to other period of supplementations[62]. It has been also reported that, the impact of prenatal micronutrients supplementation on offspring\u0026rsquo;s neurodevelopment differs for different time of embryo development [40]. Specific areas of the human brain develop quickly with neurogenesis and migration of neural cells starting early in the first months of pregnancy[63]. The brain and spinal cord are particularly susceptible to environmental stimuli, such as nutrition, during this critical period of growth, proliferation, and differentiation [17]. \u003c/p\u003e\n\u003cp\u003eSimilar to other systematic reviews, this systematic review and meta-analysis has its own limitation. Therefore, these limitations should be considered before the interpretation of the findings. The major limitation of this study is only those studies reported in English language were considered to conduct this review; hence, the finding of the current review may be affected by those reports published in other languages. In addition, in this study moderate to high heterogeneity were observed among included studies in most of analyzed neurodevelopmental outcomes. Hence, a random-effects model and sensitivity analysis were performed to adjust the issue of heterogeneity. The major factor for heterogeneity across included studies may be differences in contextual nutrients status [61]. The other possible justifications of the observed heterogeneity may be variability in the study area, sample size, design, exposure initiation time, exposure duration, outcome measurement approaches and others. But the current systematic review and meta-analysis has strengths. The first strength is that this review and meta-analysis is primary in terms of systematically synthesizing and meta analyzing of existed individual studies in a comprehensive manner which revealed the association between multiple micronutrients supplementation and neurodevelopmental outcomes like autistic-like behavior, cognitive, language and communication, psychomotor, socioemotional and behavioral development in children in comparison to no prenatal supplementation or low prenatal supplementation. In addition, the strength of the present systematic review and meta-analysis is the use of the largest sample size which has high statistical power to reveal the association between prenatal multiple micronutrients supplementation on child health outcomes in the postnatal period; because individual articles may not have enough statistical power to assess the effects of supplementation on child health outcomes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe present systematic review and meta-analysis found that multiple micronutrients supplementation during pregnancy significantly reduced the risk of autistic-like behavior in children. By multiple micronutrients supplementation during gestation, it is possible to reduce the risk of autistic-like behavior in children by 56% as compared to no supplementation or supplementations with IFA. The present meta-analysis also indicated a significant association between multiple micronutrients supplementation and cognitive development in children and revealed a significant association between multiple micronutrients supplementation and psychomotor development in children. On the other hand, our meta-analysis showed no significant association between multiple micronutrients supplementation and language and communication development and socioemotional and behavioral skills development in children. Micronutrients supplementation needs to be strengthened particularly in low-income countries where maternal undernutrition is high. The association between prenatal multiple micronutrients supplementation and language and behavioral development in children needs further investigation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eASQ-3: Ages and Stages\u0026nbsp;Questionnaire \u0026ndash; Third Edition\u003c/p\u003e\n\u003cp\u003eBMI: Body Mass Index\u003c/p\u003e\n\u003cp\u003eBSID: Bayley Scale of Infant Development\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCI: Confidence Interval\u003c/p\u003e\n\u003cp\u003eDSM:\u0026nbsp;Diagnostic and Statistical Manual of Mental Disorders\u003c/p\u003e\n\u003cp\u003eICD: International Classification of Diseases\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIFA: Iron and Folic Acid\u003c/p\u003e\n\u003cp\u003eMMN: Multiple Micronutrients\u003c/p\u003e\n\u003cp\u003eOR: Odds Ratio\u003c/p\u003e\n\u003cp\u003eRCT: Randomized Controlled Trial\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUNIMMAP: United Nations International Multiple Micronutrient Antenatal Preparation\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA.T.W.: Conception of review protocol, study design, literature review, data extraction, data analysis, interpretation and drafting the manuscript. S.A.G.: Literature review, data analysis, data extraction, quality assessment and reviewing the manuscript. All authors contributed equally and have read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be available upon request of the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of conflicting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) declared no potential conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) received no financial support for this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGernand AD, Schulze KJ, Stewart CP, West KP, Jr., Christian P: \u003cstrong\u003eMicronutrient deficiencies in pregnancy worldwide: health effects and prevention\u003c/strong\u003e. \u003cem\u003eNature reviews Endocrinology \u003c/em\u003e2016, \u003cstrong\u003e12\u003c/strong\u003e(5):274-289.\u003c/li\u003e\n\u003cli\u003eBourre JM: \u003cstrong\u003eDietary omega-3 fatty acids for women\u003c/strong\u003e. \u003cem\u003eBiomedicine \u0026amp; pharmacotherapy = Biomedecine \u0026amp; pharmacotherapie \u003c/em\u003e2007, \u003cstrong\u003e61\u003c/strong\u003e(2-3):105-112.\u003c/li\u003e\n\u003cli\u003eFowles ER: \u003cstrong\u003eWhat\u0026apos;s a Pregnant Woman to Eat? 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Underwood L, Morton SMB: \u003cstrong\u003eAntenatal and Postnatal Determinants of Behavioural Difficulties in Early Childhood: Evidence from Growing Up in New Zealand\u003c/strong\u003e. \u003cem\u003eChild psychiatry and human development \u003c/em\u003e2019, \u003cstrong\u003e50\u003c/strong\u003e(1):45-60.\u003c/li\u003e\n\u003cli\u003eD\u0026apos;Souza S, Crawford CN, Buckley J, Underwood L, Peterson ER, Bird A, Morton SMB, Waldie KE: \u003cstrong\u003eAntenatal determinants of early childhood talking delay and behavioural difficulties\u003c/strong\u003e. \u003cem\u003eInfant behavior \u0026amp; development \u003c/em\u003e2019, \u003cstrong\u003e57\u003c/strong\u003e:101388.\u003c/li\u003e\n\u003cli\u003eTan M, Yang T, Zhu J, Li Q, Lai X, Li Y, Tang T, Chen J, Li T: \u003cstrong\u003eMaternal folic acid and micronutrient supplementation is associated with vitamin levels and symptoms in children with autism spectrum disorders\u003c/strong\u003e. \u003cem\u003eReproductive toxicology (Elmsford, NY) \u003c/em\u003e2020, \u003cstrong\u003e91\u003c/strong\u003e:109-115.\u003c/li\u003e\n\u003cli\u003eVirk J, Liew Z, Olsen J, Nohr EA, Catov JM, Ritz B: \u003cstrong\u003ePre-conceptual and prenatal supplementary folic acid and multivitamin intake, behavioral problems, and hyperkinetic disorders: A study based on the Danish National Birth Cohort (DNBC)\u003c/strong\u003e. \u003cem\u003eNutritional neuroscience \u003c/em\u003e2018, \u003cstrong\u003e21\u003c/strong\u003e(5):352-360.\u003c/li\u003e\n\u003cli\u003eSur\u0026eacute;n P, Roth C, Bresnahan M, Haugen M, Hornig M, Hirtz D, Lie KK, Lipkin WI, Magnus P, Reichborn-Kjennerud T\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eAssociation between maternal use of folic acid supplements and risk of autism spectrum disorders in children\u003c/strong\u003e. \u003cem\u003eJAMA \u003c/em\u003e2013, \u003cstrong\u003e309\u003c/strong\u003e(6):570-577.\u003c/li\u003e\n\u003cli\u003eSchmidt RJ, Hansen RL, Hartiala J, Allayee H, Schmidt LC, Tancredi DJ, Tassone F, Hertz-Picciotto I: \u003cstrong\u003ePrenatal vitamins, one-carbon metabolism gene variants, and risk for autism\u003c/strong\u003e. \u003cem\u003eEpidemiology (Cambridge, Mass) \u003c/em\u003e2011, \u003cstrong\u003e22\u003c/strong\u003e(4):476-485.\u003c/li\u003e\n\u003cli\u003eSchmidt RJ, Tancredi DJ, Ozonoff S, Hansen RL, Hartiala J, Allayee H, Schmidt LC, Tassone F, Hertz-Picciotto I: \u003cstrong\u003eMaternal periconceptional folic acid intake and risk of autism spectrum disorders and developmental delay in the CHARGE (CHildhood Autism Risks from Genetics and Environment) case-control study\u003c/strong\u003e. \u003cem\u003eAm J Clin Nutr \u003c/em\u003e2012, \u003cstrong\u003e96\u003c/strong\u003e(1):80-89.\u003c/li\u003e\n\u003cli\u003eSchmidt RJ, Iosif A-M, Guerrero Angel E, Ozonoff S: \u003cstrong\u003eAssociation of Maternal Prenatal Vitamin Use With Risk for Autism Spectrum Disorder Recurrence in Young Siblings\u003c/strong\u003e. \u003cem\u003eJAMA Psychiatry \u003c/em\u003e2019, \u003cstrong\u003e76\u003c/strong\u003e(4):391-398.\u003c/li\u003e\n\u003cli\u003eVirk J, Liew Z, Olsen J, Nohr EA, Catov JM, Ritz B: \u003cstrong\u003ePreconceptional and prenatal supplementary folic acid and multivitamin intake and autism spectrum disorders\u003c/strong\u003e. \u003cem\u003eAutism : the international journal of research and practice \u003c/em\u003e2016, \u003cstrong\u003e20\u003c/strong\u003e(6):710-718.\u003c/li\u003e\n\u003cli\u003eDeSoto MC, Hitlan RT: \u003cstrong\u003eSynthetic folic acid supplementation during pregnancy may increase the risk of developing autism\u003c/strong\u003e. \u003cem\u003eJournal of Pediatric Biochemistry \u003c/em\u003e2012, \u003cstrong\u003e2\u003c/strong\u003e(4):251-261.\u003c/li\u003e\n\u003cli\u003eBraun JM, Froehlich T, Kalkbrenner A, Pfeiffer CM, Fazili Z, Yolton K, Lanphear BP: \u003cstrong\u003eBrief report: are autistic-behaviors in children related to prenatal vitamin use and maternal whole blood folate concentrations?\u003c/strong\u003e \u003cem\u003eJ Autism Dev Disord \u003c/em\u003e2014, \u003cstrong\u003e44\u003c/strong\u003e(10):2602-2607.\u003c/li\u003e\n\u003cli\u003eDeVilbiss EA, Magnusson C, Gardner RM, Rai D, Newschaffer CJ, Lyall K, Dalman C, Lee BK: \u003cstrong\u003eAntenatal nutritional supplementation and autism spectrum disorders in the Stockholm youth cohort: population based cohort study\u003c/strong\u003e. \u003cem\u003eBMJ (Clinical research ed) \u003c/em\u003e2017, \u003cstrong\u003e359\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eLevine SZ, Kodesh A, Viktorin A, Smith L, Uher R, Reichenberg A, Sandin S: \u003cstrong\u003eAssociation of Maternal Use of Folic Acid and Multivitamin Supplements in the Periods Before and During Pregnancy With the Risk of Autism Spectrum Disorder in Offspring\u003c/strong\u003e. \u003cem\u003eJAMA Psychiatry \u003c/em\u003e2018, \u003cstrong\u003e75\u003c/strong\u003e(2):176-184.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003eSearches performed in PubMed, Web of Science, and other databases to examine the effect of prenatal multiple micronutrients supplementation on child neurodevelopment.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eDatabases searched\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 462px;\"\u003e\n \u003cp\u003eSearching terms\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eNumber of identified studies\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003ePubMed /MEDLINE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 462px;\"\u003e\n \u003cp\u003eEffect[All Fields] AND prenatal[All Fields] AND (\u0026quot;trace elements\u0026quot;[All Fields] OR \u0026quot;micronutrients\u0026quot;[All Fields] OR \u0026quot;trace elements\u0026quot;[MeSH Terms] OR (\u0026quot;trace\u0026quot;[All Fields] AND \u0026quot;elements\u0026quot;[All Fields]) OR \u0026quot;trace elements\u0026quot;[All Fields] OR \u0026quot;micronutrient\u0026quot;[All Fields] OR \u0026quot;micronutrients\u0026quot;[MeSH Terms] OR \u0026quot;micronutrients\u0026quot;[All Fields]) AND supplementation[All Fields] AND status[All Fields] AND children\u0026apos;s[All Fields] AND neurodevelopment[All Fields]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e618\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eWeb of Science Core Collection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 462px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSearch Query\u003c/strong\u003e: TS=(\u0026quot;prenatal micronutrient supplementation\u0026quot; AND \u0026quot;child neurodevelopment\u0026quot;) AND TS=(\u0026quot;systematic review\u0026quot; OR \u0026quot;meta-analysis\u0026quot;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eGoogle Scholar\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 462px;\"\u003e\n \u003cp\u003e\u0026ldquo;Effect\u0026rdquo; and \u0026ldquo;prenatal\u0026rdquo; and \u0026ldquo;micronutrient\u0026rdquo; and \u0026ldquo;supplementation\u0026rdquo; and \u0026ldquo;status\u0026rdquo; and \u0026ldquo;children\u0026rdquo; and \u0026ldquo;neurodevelopment\u0026rdquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e8450\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eFrom other sources\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 462px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eTotal accessed articles\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 462px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e9150\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eFinal full-text articles relevant to current study\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 462px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003eBackground characteristics of included studies in the current systematic review and meta-analysis.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"972\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eStudies\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003eSamples and study Country\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eIntake and dose intervention/MMN group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eIntake and dose control group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eInitiation and duration of exposure and methods of exposure assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eTypes of neuro development assessed and assessment methods\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eAdjusted confounders\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eLi et al, 2009 [36]/RCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e5828 sample in China\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eUNIMMAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eReceived 400 \u0026micro;g of folic acid and 60mg of iron per day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eFrom 14 weeks of gestation until delivery assessed through allocation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eCognitive development and psychomotor development assessed through BSID at the age of 6 and 12 months\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eInfant\u0026rsquo;s age, gender, gestational age at birth, Apgar scores at 1 and 5 minutes after birth, birth weight, history of pathological jaundice, history of pneumonia, mother\u0026rsquo;s age at delivery, BMI at enrollment, educational level, occupational class, number of supplement tablets consumed, father\u0026rsquo;s educational level and occupational class, and family socioeconomic status.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eHe et al, 2020 [23]/cross sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e446 samples taken in China\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;Vitamins and minerals taken for at least three times a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eNone taken\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eIn the first three months of pregnancy assessed by interview using structured questionnaire\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eCommunication skill, motor, problem solving and personal social development through BSID-III by the age of 6-24 months\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eGender, age, birth weight, and height-for age of child, age and education of mother, whether mother is primary caregiver, family income, home\u003c/p\u003e\n \u003cp\u003eparenting environment, duration of breastfeeding in month, complementary feeding when child aged above 6 months, and village fixed effect.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eCheng et al, 2019 [22]/Cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e939 samples in China\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eMothers who took iron, FA, multivitamin, and zinc supplements\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eMothers who used both iron and FA supplements\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eDuring pregnancy known by face-to-face intervein using questionnaire\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eCommunication, gross motor, fine motor, problem solving and personal social assessed by ASQ-3 at 3 years of age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eMaternal age, maternal education, average monthly household income, maternal postpartum BMI, maternal height, maternal calcium supplementation, gestational dietary intake, passive smoking during pregnancy, alcohol use during pregnancy, maternal parity, infant gender, infant birthweight, length at birth, gestational age, infant feeding practices, infant supplement use, and infant dietary intake.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eChristian et al, 2016 [38]/RCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e8529 samples in Bangladesh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003e13 micronutrients in addition to the IFA at the same amount in the control supplement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eIron (27 mg) and folic acid (600 mg) supplement daily\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eFrom 10.9 week through 3 months postpartum during allocation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eCognitive, communication and psychomotor development by BSID-III at the age of 2 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eHousehold demographic and socioeconomic statuses, maternal husband\u0026rsquo;s and their own education and occupation, pregnancy history, breastfeeding and complementary feeding practices, morbidity histories, treatments sought, and vaccinations status.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003ePrado et al, 2017 [64]/RCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;19 274 sample in Indonesia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;UNIMMAP\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eMothers who used IFA capsule contained 30 mg iron and 400 \u0026mu;g folic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eMMN or IFA capsules taken daily throughout the duration of pregnancy and until 3 months postpartum known during allocation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eCognitive development, motor (fine \u0026amp; gross), and personal social assessed using set of specific tests adapted to local context by the age of 9-12 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eMaternall and paternal education, maternal MUAC, maternal haemoglobin, height, wealth index, preterm birth, small for gestational age, postnatal growth, child haemoglobin, child age and sex, HOME inventory score, and maternal depression score.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eTofail et al, 2008 [26]/RCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e2853 sample in Bangladesh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eMM group took UNIMMAP package\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eIFA group received 30 mg Fe and 400 \u0026mu;g folate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eDaily supplementation from week 14 of gestation until delivery assessed during allocation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eProblem-solving, motor development and behavior/ personal social assessed by problem-solving support and cover tests, Psychomotor Developmental Index (PDI) of the Bayley Scales of Infant Development-II and Wolke\u0026rsquo;s behavior ratings at the age of 7 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eMaternal age, mothers\u0026rsquo; BMI, hemoglobin, parity, parents\u0026rsquo; education and employment, housing quality, family wealth, food groups, and sex and birth weight of infants.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eLi et al, 2015 [27]/RCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e1744 sample in China\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eUNIMMAP package\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e400 \u0026mu;g/d folic acid and 30mg/d Fe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eDaily supplementation from week 14 of gestation until delivery assessed during allocation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eCognitive development assessed by Wechsler Intelligence Scale for Children Fourth Edition (WISC-IV) at the age of 7-10 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eAge of children, household wealth index, fathers\u0026rsquo; educational level, maternal occupation, child school level, number of supplement tablets consumed, birth weight, history of anemia, gestational weeks, and respiratory tract infection.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eChristian et al, 2010 [24]/RCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e676 sample in Nepal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eUNIMMAP package\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eFolic acid (400 \u0026mu;g) plus iron (60 mg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eDaily supplementation from 11 weeks of pregnancy through 3 months postpartum assessed during allocation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eCognitive development and motor development assessed by Universal Nonverbal Intelligence Test (UNIT); Movement Assessment Battery for Children (MABC) by the age of 7 to 9 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eDesign effect, age, sex, schooling status, asset score, diary product intake, meat/chicken/fish intake, lower respiratory tract infection, and diarrhea/dysentery.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eMcGrath et al, 2006 [37]/RCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e681 sample in Tanzania\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eMultivitamins which include vitamin A (30 mg of beta-carotene plus 5000 IU preformed vitamin A);20 mg of B1, 20 mg of B2, 25 mg of B6, 100mg of niacin, 50 \u0026mu;g of B12, 500 mg of C, 30 mg of E, and 0.8 mg of folic acid.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eNone taken (placebo)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eDaily supplementation from 12 weeks of gestation up to immediate postpartum period assessed during allocation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eCognitive and psychomotor development through Bayley Scales of Infant Development, 2nd Edition (BSID-II) at the age of 6, 12 and 18 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eMaternal age, test administrator, prematurity, maternal CD4 at baseline and BMI, and child\u0026rsquo;s HIV-1 status and gender.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eHanieh et al, 2013 [25]/RCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e1,258 sample in Viet Nam\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eOne capsule of MMNs taken twice a week (60 mg elemental iron plus 1.5 mg\u003cbr\u003e\u0026nbsp;folic acid plus a variation of the dose of micronutrients in the\u003cbr\u003e\u0026nbsp;UNIMMAP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eOne capsule of IFA taken twice a week (60 mg elemental iron plus 1.5 mg folic acid per capsule; administered as 2 capsules/week)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eTwice per week from less than 16 weeks of gestation up to 3 months postpartum assed during allocation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eCognitive, communication, motor, and personal social development assessed by BSID III at the age of 6 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eMaternal age, parity, randomization, birth weight, infant gender and gestational age.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003ePrado et al. 2012 [21]/RCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e487 sample in Indonesia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eIron 30 mg, Folic acid 400 \u0026mu;g, Retinol (retinyl acetate) 800 \u0026mu;g\u003cbr\u003e\u0026nbsp;Vitamin D (ergocalciferol) 200 IU\u003cbr\u003e\u0026nbsp;Vitamin E (a-tocopherol acetate) 10 mg\u003cbr\u003e\u0026nbsp;Ascorbic acid 70 mg\u003cbr\u003e\u0026nbsp;Vitamin B1 (thiamine mononitrate) 1.4 mg\u003cbr\u003e\u0026nbsp;Vitamin B2 (riboflavin) 1.4 mg\u003cbr\u003e\u0026nbsp;Niacin (niacinanide) 18 mg\u003cbr\u003e\u0026nbsp;Vitamin B6 (pyridoxine) 1.9 mg\u003cbr\u003e\u0026nbsp;Vitamin B12 (cyanocobalamin) 2.6 \u0026mu;g\u003cbr\u003e\u0026nbsp;Zinc (zinc gluconate) 15 mg\u003cbr\u003e\u0026nbsp;Copper 2 mg\u003cbr\u003e\u0026nbsp;Selenium 65 \u0026mu;g\u003cbr\u003e\u0026nbsp;Iodine 150 \u0026mu;g\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eIron 30 mg and Folic acid 400 \u0026mu;g\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eWomen received a daily supplement throughout the duration of pregnancy and until 3 months postpartum assessed during allocation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eCognitive, communication, motor and personal social development assessed by Bayley Scale of Motor Development and the Ages and Stages Questionnaire; Picture Vocabulary Test; Block Design Test; Socioemotional Development Scale at the age of 42 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eHome Observation for the Measurement of the Environment (HOME) inventory score, child\u0026rsquo;s Hb concentration, mother\u0026rsquo;s MUAC, birth weight, and compliance (mean percentage of supplements consumed).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eD\u0026rsquo;Souza et al 2019 [65]/Cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e6246 samples in New Zealand\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eMothers took multivitamins during pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eMothers who did not take multivitamins during pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eDuring pregnancy assessed by interview of mothers using questionnaire\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eBehavioral problems/personal social by\u0026nbsp;Strengths and Difficulties Questionnaire\u0026nbsp;(SDQ) at the age of 2 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eMother\u0026rsquo;s ethnicity, mother\u0026rsquo;s education, mother\u0026rsquo;s age when pregnant, child\u0026rsquo;s gestational age, child\u0026rsquo;s birth weight, child\u0026rsquo;s gender, parity, planned pregnancy, mother in paid employment, area-level deprivation, and rurality\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eD\u0026rsquo;Souza et al, 2019 [66]/Cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e5768 samples in New Zealand\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eMothers took multivitamins during pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eMothers did not take multivitamins during pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eDuring pregnancy assessed through interview of mothers using questionnaire\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eBehavioral problems and communication problems by SDQ and MacArthur-Bates Communicative Development inventories (CDIs) at the age of 2 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eMaternal depression, maternal lifestyle factors such as smoking, alcohol intake\u003cem\u003e,\u0026nbsp;\u003c/em\u003emother\u0026rsquo;s ethnicity, mother\u0026rsquo;s education, mother\u0026rsquo;s age, parity, whether or not the pregnancy was planned, socioeconomic deprivation, Child\u0026rsquo;s gender, gestational age at birth, and birthweight.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eTan et al, 2020 [67]/Case control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e617 (416 case and 201 control in China\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eMothers took multi micronutrients during pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eMothers who did not took any supplements during pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eDuring pregnancy (from LMP to birth for at least 4 days per week) assessed through structured interviews of mothers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eLanguage problem, motor development, personal social development and autistic like behaviors assessed by revised Gesell Developmental Scale (GDS) and Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria at the mean age of 4.68 years for cases; mean age of 4.47 years for controls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eAge of the child at assessment, gender, residence, household income, age of mothers at child\u0026rsquo;s birth, age of the fathers at child\u0026rsquo;s birth, birth mode and gestational weeks at birth, and birth weight.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eLiew et al, 2018 [68]/Cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e20247 samples in Denmark\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eMothers took multivitamins during pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eWomen who indicated no supplement use for the same entire period were used as the unexposed group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eMultivitamin use beginning 4-weeks prior to their LMP through 8-weeks after their LMP (\u0026minus;4 to 8 weeks) assessed through interview of mothers using questionnaire\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eBehavioral problems/personal social assessed by SDQ by the age of 7 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eMaternal age; household socio-economic status; maternal smoking; and alcohol consumption during pregnancy, maternal pre-pregnancy body mass index, birth year, offspring sex.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eSur\u0026eacute;n et al, 2013 [69]/Cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e85,176 in Norway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eMothers who took folic acid plus other vitamins and minerals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eNo any supplements\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003e4 weeks before to 8 weeks after the start of pregnancy assessed through food frequency questionnaire report of mothers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eAutistic disorder assessed by Autism Diagnostic Interview \u0026ndash;\u003cbr\u003e\u0026nbsp;Revised (ADI-R) and Autism Diagnostic Observation Schedule (ADOS) by the mean age of 6.4 years\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eParental education, parental age, whether the pregnancy was planned, maternal smoking during pregnancy, maternal body mass index, parity, and year of birth.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eSchmidt et al, 2011 [70]/Case control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e566 (288 case \u0026amp; 278 control) in USA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eDaily multivitamin intake during the stated period\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eNo any supplements\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003ePericonceptional period (three months before pregnancy through the first month of pregnancy) assessed through telephone interviews of mothers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eAutism risk assessed by Autism Diagnostic Interview\u0026ndash;Revised and Autism\u003cbr\u003e\u0026nbsp;Diagnostic Observation Schedule at the age of 24\u0026ndash;60 months \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eMaternal education and child\u0026rsquo;s birth year\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eSchmidt et al, 2012 [71]/Case control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e707 (429 case \u0026amp; 278 control) sample in USA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eDaily multivitamin intake during the stated period\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eNo any supplements\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003ePericonceptional period (three months before pregnancy through the first month of pregnancy) assessed by telephone interviews of mothers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eAutism spectrum disorder assessed using the Autism Diagnostic Interview\u0026ndash;Revised and Autism Diagnostic Observation Schedule by the age of 24-60 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eChild sex and birth year, maternal and child race-ethnicity, maternal age, maternal education, pre pregnancy BMI, maternal birthplace, cigarette smoking, alcohol consumption and paternal age.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eSchmidt et al, 2019 [72]/Cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e332 sample in USA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003edaily multivitamin intake during 1st months of gestation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eno any supplements\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eMultivitamins use in the 1st months of gestation assessed through telephone-assisted interviews and mailed questionnaire\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eAutism spectrum disorder assessed using the Autism Diagnostic Interview\u0026ndash;Revised and Autism Diagnostic Observation Schedule at 36 months of age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eMaternal age and education, mode of delivery, and maternal intention to become pregnant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eVirk et al, 2016 [73]/Cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e35,059 sample in Denmark\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eWomen who took multivitamins for at least 4 days per week on the stated period\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eWomen who did not took any supplement for the same entire period were used as the unexposed group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003e4 weeks prior from the last menstrual period through to 8 weeks after the last menstrual period (\u0026minus;4 to 8 weeks) assessed by structured interviews of mothers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eAutistic disorder assessed based on International Classification\u003cbr\u003eof Diseases, 10\u003csup\u003eth\u0026nbsp;\u003c/sup\u003eedition (ICD-10) at the mean age of 9.6 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eSmoking and alcohol consumption during pregnancy, maternal pre-pregnancy BMI, maternal mental health status, and socioeconomic status\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eDeSoto \u0026amp; Hitlan, 2012 [74]/Case control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e256 case children \u0026amp; 752 controls samples in USA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eWomen who took multivitamins during pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eWomen who did not took any supplement during pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eDuring pregnancy intake was assessed by interview of mothers using questionnaire\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eAutistic like disorder assessed by Discriminant Function Analysis (DFA) by the age of 6-12 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eMaternal age, birth weight, poverty ratio, birth order, breast feeding duration, maternal prenatal health care/seeking behavior, and child medical conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eBraun et al, 2014 [75]/Cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e209 sample in USA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eWomen who took multivitamins in 2nd trimester of gestation daily\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eWomen who did not took any supplement during pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eDuring 2nd trimester of pregnancy assessed by interview of mothers using questionnaire\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eAutistic behavior assessed by Social Responsiveness Scale (SRS) by the age of 4-5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eMaternal age, race, education, household income, marital status, health insurance, employment, frequency of fresh fruit/vegetable intake, and food security\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eDeVilbiss et al, 2017 [76]/Cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e273, 107 sample in Sweden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eWomen who took multivitamins during pregnancy daily\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eWomen who did not took any supplement during pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eDuring the entire pregnancy period assessed by interview of mothers using questionnaire\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eASD assessed based on international classification of diseases, 10\u003csup\u003eth\u003c/sup\u003e revision (ICD-10) \u0026amp; Diagnostic and Statistical Manual of\u003cbr\u003e\u0026nbsp;Mental Disorders, fourth edition (DSM-IV) by the age of 4 to 15 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eChild characteristics (sex, birth year, and years resided in Stockholm County), socioeconomic indicators (education, family income, and maternal birth country), maternal characteristics (age, body mass\u003cbr\u003e\u0026nbsp;index, parity, smoking status), medication use during pregnancy (antidepressants or antiepileptics), and maternal neuropsychiatric conditions (anxiety disorders, autism, bipolar disorder, depression, epilepsy, intellectual disability, non-affective psychotic disorders, and stress disorders)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eLevine et al, 2018 [77]/Cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e45,300 samples in Israel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eWomen took multivitamins during pregnancy on daily bases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eWomen with no any supplement intake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eDuring the entire gestation up to birth confirmed by interview of mothers using questionnaire\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eASD based on International Classification of Diseases, Ninth Revision by the age of 8 to 12 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eSex, birth year, socioeconomic status, maternal and paternal psychiatric diagnosis by childbirth, maternal and paternal age at childbirth, and parity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eRaghavan et al, 2018 [52]/Cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e1257 samples in USA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eMultivitamin supplement intake for\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026le;2 times/week and \u0026gt;5 times/week\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eMultivitamin supplement intake for\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3-5 times/week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eSupplementation during, preconception, 1\u003csup\u003est\u003c/sup\u003e, 2\u003csup\u003end\u0026nbsp;\u003c/sup\u003eand 3\u003csup\u003erd\u003c/sup\u003e trimesters assessed though mothers self-report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eAutism risk based on ICD-9 aged up to 12 years\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eChild sex, maternal age at delivery, smoking during pregnancy, parity, maternal education, year of the baby\u0026apos;s birth and Methylene tetrahydrofolate reductase (MTHFR) C677T genotypes.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eLi et al, 2018 [51]/Case control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e374 cases; 354controls taken in China\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003eFolic acid and calcium intake during pregnancy preparation, during\u003c/p\u003e\n \u003cp\u003epregnancy or during lactation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003eFolic acid intake during pregnancy preparation, during\u003c/p\u003e\n \u003cp\u003epregnancy or during lactation or no intake on the stated period\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eFolic acid and calcium intake during pregnancy preparation, during\u003c/p\u003e\n \u003cp\u003epregnancy or during lactation were assessed by interview of mothers using structured questionnaire\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eAutistic disorder according to the Diagnostic and Statistical Manual of Mental\u003c/p\u003e\n \u003cp\u003eDisorders.\u003c/p\u003e\n \u003cp\u003eFourth Edition, Text Revision (DSM-IV-TR) among children aged 3 to 6 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 241px;\"\u003e\n \u003cp\u003eChild\u0026rsquo;s age and gender, parental\u003c/p\u003e\n \u003cp\u003eage, maternal BMI before conception and delivery, and premature delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eRCT: Randomized Controlled Trial; BSID: Bayley Scales of Infant Development; BSID-II: Bayley Scales of Infant Development, 2nd Edition; BSID-III: Bayley Scales of Infant Development\u0026ndash;third edition; ASQ-3: Ages and Stages Questionnaires, Third Edition; FA: Folic Acid; IFA: iron and folic acid; WISC-IV: Wechsler Intelligence Scale for Children- Fourth Edition; SDQ: Strengths and Difficulties Questionnaire; CDIs: MacArthur-Bates Communicative Development inventories; UNIMMAP:\u0026nbsp;United Nations International Multiple Micronutrient Antenatal Preparation; DSM: Diagnostic and Statistical Manual of Mental Disorders; BMI: Body Mass Index; ICD:\u0026nbsp;International Classification of Diseases; LMP: Last Menstrual Period; ASD: Autism Spectrum of Diseases; ADI-R: Autism Diagnostic Interview Revised; ADOS: Autism Diagnostic Observation Schedule; DFA: Discriminant Function Analysis; SRS: Social Responsiveness Scale.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Debre Markos University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Micronutrients, macronutrients, supplementation, pregnancy, neurodevelopment, birth outcomes, children, systematic review, meta-analysis","lastPublishedDoi":"10.21203/rs.3.rs-7713425/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7713425/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThere are various inconclusive individual studies that have reported the association between child neurodevelopment and prenatal multiple micronutrient supplementation during pregnancy. Hence, the main aim of the current systematic review and meta-analysis is to determine the pooled effect size of prenatal multiple micronutrients supplementation on different neurodevelopmental outcomes in children.\u003c/p\u003e\n\u003cp\u003eSystematic electronic search of PubMed/MEDLINE, Web of Science, Cochrane Library, CINAHL, Science Direct, and Google Scholar was conducted to access relevant articles to the current systematic review and meta-analysis. Eligible articles were selected based on predefined eligibility criteria, and data from the selected articles were extracted using Excel templates. Data analysis was performed using R and STATA software. Statistically significant heterogeneity among included studies was assessed using Cochran’s Q-test and I\u003csup\u003e2\u003c/sup\u003e statistics. Potential publication bias was evaluated by examining asymmetry in the funnel plots. Pooled Odds Ratios and Pooled Mean Differences, along with the corresponding 95% confidence intervals for prenatal micronutrient supplementation on neurodevelopmental outcomes in children, were calculated using a random-effects meta-analysis model. Statistical significance was defined as a p-value of \u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003eThe present systematic review and meta-analysis revealed that prenatal multiple micronutrients supplementation is significantly associated with autistic-like behavior (pooled Odds Ratio: 0.44, 95%CI: 0.30, 0.63), cognitive development (pooled mean difference: 0.18, 95%CI; 0.02, 0.34), and psychomotor development (pooled mean difference: 0.73, 95%CI: 0.19, 1.27) in children during postnatal life.\u003c/p\u003e\n\u003cp\u003eThe present systematic review and meta-analysis revealed that multiple micronutrients supplementation during pregnancy significantly reduces the risk of autistic-like behavior in children by 56% as compared to no supplementation or supplementations with iron and folic acid. The present meta-analysis also demonstrates a significant association between multiple micronutrient supplementation and improvements in cognitive and psychomotor development.\u003c/p\u003e","manuscriptTitle":"Prenatal Multiple Micronutrient Supplementation and Child Neurodevelopment: A Systematic Review and Meta-analysis.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-30 10:23:39","doi":"10.21203/rs.3.rs-7713425/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f17b5911-5265-4af7-9190-ebdbe8d34476","owner":[],"postedDate":"September 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-30T10:23:39+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-30 10:23:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7713425","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7713425","identity":"rs-7713425","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}