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 Table of Contents  
Year : 2021  |  Volume : 5  |  Issue : 4  |  Page : 247-256

Associations of prepregnancy body mass index, gestational weight gain, and intelligence in offspring: A systematic review and meta-analysis

1 Department of Obstetrics and Gynecology, International Peace Maternity and Child Health Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai 200030, China
2 Institute of Reproduction and Development, Obstetrics and Gynecology Hospital, Fudan University, Shanghai 200011, China
3 Department of Obstetrics and Gynecology, International Peace Maternity and Child Health Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai 200030; Institute of Reproduction and Development, Obstetrics and Gynecology Hospital, Fudan University, Shanghai 200011, China

Date of Submission17-Mar-2021
Date of Decision23-Aug-2021
Date of Acceptance30-Sep-2021
Date of Web Publication30-Dec-2021

Correspondence Address:
He-Feng Huang
Obstetrics and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai 200011
Yan-Ting Wu
Obstetrics and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai 200011
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/2096-2924.334380

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Objective: Increasing evidences have shown that prepregnancy maternal weight and gestational weight gain (GWG) may associate with offspring's neurodevelopment. However, the effects of prepregnancy maternal overweight, obesity, and excessive GWG on offspring's intelligence remain controversial. This meta-analysis aimed to re-assess the association between prepregnancy body mass index (BMI), GWG, and children's intelligence.
Methods: We systematically searched multiple databases, including PubMed, EMBASE, Cochrane Library, and Ovid Medline, from their inception through February 2021. Studies assessing the association between prepregnancy BMI or GWG and children's intelligence were further screened manually before final inclusion. Cohorts that analyzed the association between prepregnancy BMI or GWG and intelligence of offspring were included, and we used the Mantel–Haenszel fixed-effects method to compute the weighted mean difference (WMD) and 95% confidence interval (CI) of each study.
Results:A total of 12 articles were included in this systematic review, while six of them in the meta-analysis. There was a significant full-scale IQ reduction in children born from overweight and obese mothers, with WMDs of −3.08 (95% CI: −4.02, −2.14) and −4.91 (95% CI: −6.40, −3.42), respectively. Compared with control group, the WMDs for performance and verbal intelligence quotient (IQ) were decreased in overweight and obesity groups. However, we observed no association between children's full-scale IQ and excessive GWG with WMD of −0.14 (95% CI: −0.92, 0.65).
Conclusions: Women's prepregnancy overweight and obesity adversely associate with children's intelligence but no association with excessive GWG. Our study suggests that further researches focusing on the effect of prepregnancy maternal health on offspring's intelligence development are needed.

Keywords: Gestational Weight Gain; Intelligence; Maternal Obesity; Offspring; Prepregancy Overweight and Obesity

How to cite this article:
Zhu SM, He YC, Zhang C, Wu YT, Huang HF. Associations of prepregnancy body mass index, gestational weight gain, and intelligence in offspring: A systematic review and meta-analysis. Reprod Dev Med 2021;5:247-56

How to cite this URL:
Zhu SM, He YC, Zhang C, Wu YT, Huang HF. Associations of prepregnancy body mass index, gestational weight gain, and intelligence in offspring: A systematic review and meta-analysis. Reprod Dev Med [serial online] 2021 [cited 2022 Jun 30];5:247-56. Available from: https://www.repdevmed.org/text.asp?2021/5/4/247/334380

  Introduction Top

Overweight and obesity are increasingly considered as public health concerns and critical factors globally for diverse disorders, such as cardiovascular diseases, diabetes, cancers, and even COVID-19 infection.[1] According to a report from the World Health Organization (WHO), approximately 40% of the world's population are overweight and 13% aobese.[2] In China, the prevalence of overweight increased from 25.1% in 1997 to 39.6% in 2009, and the prevalence of obesity in adolescents alone more than doubled from 1991 to 2015.[3]

Maternal overweight and obesity is another major concern as 17.82%–27.8% of women are obesity before conception in different countries.[4],[5],[6] Preconception obesity usually predisposes the offspring to an array of developmental disorders, physically and mentally. Prepregnancy obesity has been shown to be involved in a variety of severe pregnancy complications, such as gestational diabetes, preeclampsia, postpartum hemorrhage, and thromboembolism. More strikingly, prepregnancy obesity results in adverse neonatal outcomes, such as preterm birth, congenital abnormalities, and macrosomia.[7] In addition, the intrauterine environment may have a programming effect on children, namely fetal programming proposed by Baker in the 1980s.[8] Moreover, some studies have suggested that maternal obesity may have long-term effects on offspring's development during childhood and their health in adulthood. For example, maternal obesity has been shown to adversely affect fetal programming, predisposing offspring to cardiovascular diseases, metabolic disorders, and allergic diseases.[9],[10],[11]

Bodyweight management during pregnancy is a common problem for gravidae. Although evidence has suggested that weight control during pregnancy may be the most effective way to diminish perinatal complications, nearly half of the pregnant women, especially those who were overweight or obese, still exceeded their gestational weight gain (GWG) goal in 2017.[12] Independent of prepregnancy obesity, excessive GWG leads to an increased incidence of adverse outcomes among offspring, such as obesity, asthma, and cardiovascular diseases in adolescence and adulthood.[13],[14],[15]

Prepregnancy maternal bodyweight and excessive GWG have also been adversely related with offspring's intelligence development and susceptibility to psychological disorders. Fetal brain development begins during the first trimester of pregnancy. Intrauterine exposure to adipose tissue, hyperglycemia, and other adverse environmental factors may have a critical influence on children's nervous system. There is growing evidence that both prepregnancy overweight, obesity, and excessive GWG are negatively associated with offspring's neurodevelopment and increase the risks of attention-deficit hyperactivity disorder (ADHD),[16] autism,[17] intellectual disability as well.[18] All these neurodeveloping disorders have been hypothesized to be induced by decreased production of neurotrophic factors through epigenetic regulation and disturbed hippocampal progenitor cell division and neurogenesis.[19]

Several systematic reviews have examined the association between maternal prepregnancy body mass index (BMI) and offspring's neurodevelopment and found that prepregnancy overweight and obesity had an adverse impact on children's neurodevelopment[20] and predisposed children to emotional/behavioral problems,[21] eating disorders, ADHD, and psychotic diseases.[22] However, none of them has systematically studied the association between prepregnancy overweight, obesity, excessive GWG, and children's intelligence. Thus, in this systematic review and meta-analysis, we aimed to investigate the association between prepregnancy BMI, GWG, and the intelligence of offspring, providing valuable instructions for obese and overweight women before conception.

  Methods Top

This systematic review and meta-analysis is registered in PROSPERO (Number: CRD42020199215) and is reported according to Meta-analysis Of Observational Studies in Epidemiology Guidelines [Additional File 6].[23]

Search strategy and selection criteria

We performed a systemic search covering the PubMed, EMBASE, Cochrane Library, and Ovid Medline databases without language restrictions from their inception through February 2021. We used combined key terms that are summarized as follows: “prepregnancy,” “maternal,” “gestational weight gain,” “obesity,” “BMI,” “intelligence,” “mental,” and “cognition” [Additional File 1]. A manual search was performed by using the reference lists of key articles. Two authors (SZ and YH) independently reviewed the study titles and abstracts, and candidate full texts were retrieved and perused by the same authors to determine whether they met the inclusion criteria.

Selection criteria

Prospective and retrospective cohorts that analyzed the association between prepregnancy BMI/GWG and intelligence in offspring were considered for inclusion in this systematic review and meta-analysis. The inclusion criteria were as follows: (1) participants: mother–child pairs; (2) exposure: prepregnancy overweight, obesity, and excessive GWG; (3) control: normal prepregnancy weight for prepregnancy overweight and obesity, and GWG as recommended for excessive GWG; (4) primary outcome: children's full-scale intelligence quotient (FIQ) assessed by standardized tests; and (5) secondary outcome: children's performance and verbal intelligence quotient (PIQ and VIQ) assessed by standardized tests. Studies were excluded if (1) children had any pathological status that might affect the results of intelligence assessment, such as ADHD, impaired hearing, or vision[20] and (2) the sample size of the cohort study was less than 100. When two articles extracted data from the same cohort, we selected the one that was published earlier, and when the intelligence of children in the same cohort was evaluated at different ages, their data were analyzed as two independent samples.

Data extraction and quality assessment

Two authors (SZ and YH) independently extracted the following data from all eligible studies: maternal age at birth, age of the child at evaluation, total number of mother–child pairs, and tool for the intelligence assessment and dimensions covered. Disagreements were resolved by discussion with an additional author (CZ). BMI was categorized according to the WHO[24] guidelines, and we classified GWG as below, within, and above the age-standardized Z scores (below: <−1 SD, within: −1 to +1 SD, and above: >+1 SD)[25] or 2009 Institute of Medicine recommendations with a normal range of 12.5–18.0 kg for women with a BMI of <18.5 kg/m2, 11.5–16 kg for women with a BMI of 18.5–24.9 kg/m2; 7.0–11.5 kg for women with a BMI of 25.0–29.9 kg/m2; and 5.0–9.0 kg for women with a BMI of ≥30.0 kg/m2.[26] Two authors evaluated the quality of eligible studies independently using the Newcastle–Ottawa Scale (NOS).[27] We evaluated the selection, ascertainment of exposure, adjustment of covariates, assessment, and follow-up for outcomes for each study. A study was classified as high quality if it received more than 7 stars.[28]

Data synthesis and statistical analysis

Two authors (SZ and YH) extracted IQ test scores from eligible studies. The data were checked and typed in STATA 14 (Stata Corporation, College Station, TX, USA) by another researcher (CZ). We used the Mantel–Haenszel fixed-effects method to compute the weighted mean difference (WMD) and 95% confidence interval (CI) of each study, as effect measures.[29] The I2 statistical parameter was used to assess heterogeneity, and it was considered moderate to high heterogeneity if I2 value was >50%.[30] In this meta-analysis, I2 values were less than 50%, so it was appropriate to use a fixed-effect model. If the two-sided P < 0.05, it was considered statistically significant.

To assess the influence of a single study on the summary WMD and to examine whether it contributed to a large portion of the heterogeneity, sensitivity analysis was carried out by removing studies one by one. Publication bias was assessed using Egger's linear regression test, Begg's rank correlation, and visual inspection of funnel plots.[31],[32] These analyses were carried out with STATA 14.

  Results Top

In total, 5,199 articles were retrieved after the initial search; among them, 1,830 were removed as duplicates, and 53 were left after screening the title and abstract. Finally, 12 studies[33],[34],[35],[36],[37],[38],[39],[40],[41],[42],[43],[44] were eligible for systematic review [Figure 1]. Six of 12 articles offered sufficient data for statistical analysis.[33],[34],[35],[38],[41],[44] Among these six studies, five analyzed the association between maternal prepregnancy obesity, overweight, and children's intelligence,[33],[34],[35],[38],[41] and three analyzed the impact of excessive GWG and children's intelligence.[35],[41],[44] In one cohort, the intelligence of children was evaluated at different ages, and their data were only used in the subgroup analysis based on age.[41]
Figure 1: Flowchart of study selection process.

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Study characteristics

The main characteristics of the included studies for systematic review are summarized in [Table 1]. All these 12 articles are prospective cohort studies performed between 2003 and 2019. Of the six cohorts for meta-analysis, the sample size ranged from 355 to 30,212. The average maternal age at childbirth ranged from 21 to 35 years, and children's intelligence was evaluated between 3 and 10 years. Five studies[33],[34],[37],[39],[44] used the Wechsler scale to measure IQ, two[38],[41] based on Differential Intelligence Scales, and two[35],[43] based on the Stanford–Binet test. Stanford–Binet test produces only a single, general intelligence score, while Wechsler scale provides a number of different scores including nVIQ, VIQ, and PIQ. However, Differential Intelligence Scales mainly focus on measuring diverse abilities including verbal, nonverbal, and special reasoning ability in children. We included studies providing data for overweight and obesity separately or studies that showed total GWG.
Table 1: Characteristics of the included studies

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Quality assessment

The mean value of the included six studies was 7.5 stars, ranging from 6 to 8, andfive studies were considered high quality, according to the NOS scale [Additional File 2]. Among them, only one study had a secure record of prepregnancy weight,[34] and three other studies described subjects lost to follow-up or had a small number of subjects lost to follow-up (<20%).[33],[35],[44] However, participants of three studies were selective and did not represent the general population in their region.[34],[38],[41]


A pooled analysis of five studies that assessed the association between prepregnancy BMI and FIQ in offspring was performed by using a fixed-effects model [Figure 2] and [Additional File 3]. There was a significant FIQ reduction in children of overweight and obese women, with WMDs of −3.08 (95% CI: −4.02, −2.14) and −4.91 (95% CI: −6.40, −3.42), respectively. Heterogeneity estimates were I2 = 33.4% (P = 0.212) and I2 = 0.0% (P = 0.679) for prepregnancy overweight and obesity, respectively. Two studies also evaluated the association between overweight, obesity, and PIQ, and four studies explored the association between overweight, obesity, and VIQ. We noticed that both the PIQ and VIQ of the overweight and obesity group were significantly lower than those of the controls, with WMDs of −2.40 (95% CI: −3.45, −1.34) and −5.28 (95% CI: −7.22, −3.34), respectively, for PIQ, and −3.47 (95% CI: −4.38, −2.56) and −5.71 (95% CI: −7.13, −4.29), respectively, for VIQ, suggesting a potential negative association between maternal prepregnancy weight status and offspring's intellectual function in many dimensions [Figure 3] and [Figure 4]. Heterogeneity estimates were I2 = 39.8% (P = 0.197) and I2 = 16.2% (P = 0.275) in the PIQ group and I2 = 19.0% (P = 0.295) and I2 = 34.5% (P = 0.205) in the VIQ group for prepregnancy overweight and obesity, respectively. To reduce variability, two groups of FIQ were meta-analyzed according to the child age at evaluation (whether or not the child was younger than 5 years). In both overweight and obesity groups, we did not find any significant heterogeneity between the two groups based on age [Additional File 4]a and [Additional File 4]b.
Figure 2: Forest plots comparing the difference of full-scale intelligence quotient scores between children of prepregnancy overweight and normal weight mother, pre-pregnancy obese and normal weight mother and children of mother who gained excessive weight and adequate weight during pregnancy.

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Figure 3: Forest plots comparing performance intelligence quotient level in children of prepregnancy overweight and obesity mother between normal weight.

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Figure 4: Forest plots comparing verbal intelligence quotient level in children of prepregnancy overweight and obesity mother between controls.

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Two studies reported the association between GWG and intelligence in offspring. However, compared with adequate weight gain, excessive GWG shows no significant reduction in children's full-scale intelligence scores, with a WMD of 0.44 (95% CI: −0.45,1.33), suggesting a weak association between GWG and children's intelligence [Figure 2 and Additional File 3]. The heterogeneity I2 was 0.0% (P = 0.692), which suggests low heterogeneity. In the subgroup analysis, we did not find any significant difference in full-scale intelligence level between children <5 years and ≥5 years [Additional File 4c].

Sensitivity analysis

The performance of this analysis was not significantly impacted when any single cohort was excluded from the aggregated dataset comprised of all selected cohorts.

Publication bias

Publication bias was not found with either the Egger's or Begg's test for small-study effects [Additional Files 3]. A review of the funnel plots showed no evidence of publication bias [Additional File 5a-c and Additional Files 6].

  Discussion Top

In this meta-analysis, we found a significantly lower general IQ score in children from both overweight and obese women, which are consistent with previous related studies, such as the prediction model proposed by Eriksen et al., supporting the idea that parity, maternal breastfeeding, and birth weight may affect children's intelligence, while maternal prepregnancy obesity is a minor predictor.[37] Coo et al. analyzed paternal weight status and found that paternal obesity had less to do with children's intelligence than maternal obesity.[33] In addition, Zhu et al. studied children born from infertile women undergoing assisted reproductive technology and found that prepregnancy obesity increased the risk of preeclampsia, gestational diabetes, and preterm delivery, which may contribute to impaired cognitive function, highlighting the complicated network involved in intelligence development.[34] Our meta-analysis covers more studies, and it provides more robust evidence in revealing the association between prepregnancy overweight, obesity, and offspring intelligence.

Surprisingly, our data showed no association between GWG and children's intelligence. Neither inadequate GWG nor excessive GWG showed significant association with children's intelligence according to all the included cohorts, even if inadequate and excessive GWG may possibly because of lack of nutrients or overnutrition for fetal nervous system development.[45] So far, the association between GWG and offspring's intelligence remains controversial, due to the utilization of covariates and participants difference in these studies. Pugh et al. found that excessive GWG was associated with executive function but not IQ scores.[35] Kominarek et al. studied women with thyroid dysfunction, and they found no association between excessive GWG and neurodevelopment outcomes in children.[41] In addition, Gage et al. found a slight positive association between GWG and intelligence level in offspring.[44] We found little variation in intelligence level between children from mothers who gained excessive and those had inadequate GWG, which seems contradictory to common knowledge. Several studies have shown that suboptimal GWG is associated with an increased risk for gestational and perinatal complications, including gestational hypertension disorders, gestational diabetes, and fetal macrosomia,[46],[47],[48],[49] which may have an adverse impact on children's nervous system development. Furthermore, we should consider the potential adverse long-term effects of intrauterine adiposity exposure.[50] In a word, our results suggest that weight control during pregnancy may not rescue the cognitive impairment caused by prepregnancy obesity.

Many factors may affect children's intelligence and included studies considered a variety of covariates. Maternal IQ is one of the most important mediators for the studies focusing on the association between mother's and children's intelligence.[51] In our meta-analysis, two studies included this point in their adjusted model.[35],[38] Furthermore, pregnancy complications, such as preeclampsia and gestational diabetes, may have an adverse effect on children's intelligence, potentially owing to the pathologic changes during fetal nervous system development.[52],[53] In addition, gestational complications may increase the risk of preterm birth, which is believed to impact neurocognitive development. Four studies considered pregnancy complications and adjusted for these covariates.[33],[34],[35] In addition, family environment has raised more attention because of its considerable role in children development.[54] Two studies suggested that it may affect children's long-term intellectual functioning and took it as a covariate.[35],[38] Paternal factors could in greater or less extend to affect children's intelligence level.[55] However, only one of the included studies proposed a model adjusted for paternal BMI.[33] Further studies covered more covariates are needed to come to a more reliable conclusion.

In terms of the mechanism underlying the association between maternal preconception obesity and offspring intelligence, epigenetic modification may play a role. Previous studies have shown that preconception obesity may affect ovary function and oocyte quality.[56] Oocytes from obese mice showed a significantly decreased DNA methylation of PPAR-α promoter, which may further impair nervous system development in offspring.[57] In the brains of offspring from mothers fed a high-fat-diet prepregnancy, DNA methylation in the promotor regions of opioid receptors and dopamine transporters decreased, while global hypermethylation was observed in the brain regions associated with reward responses, such as the ventral tegmental area and prefrontal cortex.[58] These dysregulations of DNA methylation induced by obesity may have been fixed in oocyte before conception. Most importantly, for prepregnancy obese women, weight control during pregnancy could not rescue the altered epigenetic markers. Edlow et al. found that maternal prepregnancy obesity contributed to gene dysregulations, and normal diet during pregnancy led to more epigenetic alterations in fetal brains rather than rescue. However, the mechanism of how GWG impact nervous system development in offspring has rarely been studied.

Strengths and limitations

The fetal origins of adult disease have attracted increasing attention due to their long-term effects on public health, and studies in this field are burgeoning. Recently, several studies have evaluated the impact of maternal prepregnancy obesity on children's cognitive development, the prevalence of ADHD, autism, behavioral problems, and intellectual disability. Using the aggregate data extracted from reported cohort studies, we performed a statistical analysis to ascertain the association of children's intelligence with the GWG and prepregnancy BMI. Our meta-analysis confirms that prepregnancy obesity and overweight, rather than excessive GWG, have a stronger relationship with lower IQ levels in children, thus providing valuable information for weight management for childbearing-aged women. Our study shows that weight control before pregnancy is probably more important than GWG control in terms of the child's long-term health status. Although there are many more immediate and important health concerns related to increase BMI, a small change of IQ could also be an important concern.

However, this study has shortcomings: (i) in addition to having possible publication bias, this study is not comprehensive due to the limited accessibility of data in the studies; (ii) only six articles were available for quantitative analysis, and certainly more studies are needed to better analyze the association between maternal obesity and children's intelligence; (iii) the offspring's IQ measuring tools in each study was different; (iv) although the included studies considered many covariates, more important confounders are needed in further studies; (v) two studies did not use the WHO criteria for overweight and obesity, and the included studies evaluating the effect of GWG did not use the same criteria, leading to potential bias in this meta-analysis; (vi) since the intelligence assessment covered many dimensions, such as verbal and nonverbal intelligence, a subgroup analysis was recommended. Due to the limited sample size in each subgroup, the analysis could not be performed in the GWG group; (vii) our meta-analysis was based largely on studies from developed countries, and more studies from developing countries are needed; (viii) the participants of some studies may not well represent the whole population due to ethnicity stratification and presence of pregnancy-related disease, which may lead to bias; (ix) most of the studies evaluated children's intelligence at the ages of 3–10 years. However, the intelligence level is still developing at these ages, and a longer follow-up time is needed; and (x) we could not prove that weight management during pregnancy cannot rescue intelligence impairment in offspring from prepregnancy obesity women because of lack of studies in this issue.

In conclusion, our meta-analysis shows that prepregnancy overweight and maternal obesity may inversely correlate with the children's intelligence and there is no significant difference in children's intelligence scores between excessive and adequate GWG. For women with childbearing plans, an early weight management before pregnancy may profit their children's intelligence.

Supplementary information is linked to the online version of the paper on the Reprod Dev Med website.

Financial support and sponsorship

The work presented in this paper was supported by the Program of Shanghai Academic Research Leader (20XD1424100), Shanghai Hospital Development Center (SHDC12018X17), Shanghai Municipal Health Commission (201840210), and Science and Technology Commission of Shanghai Municipality (18410711800).

Conflicts of interest

There are no conflicts of interest.

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  [Figure 1], [Figure 2], [Figure 3], [Figure 4]

  [Table 1]


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