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Prenatal Maternal Stress and Child IQ

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Title: Prenatal Maternal Stress and Child IQ
Language: English
Authors: Cortes Hidalgo, Andrea P., Neumann, Alexander, Bakermans-Kranenburg, Marian J., Jaddoe, Vincent W. V., Rijlaarsdam, Jolien, Verhulst, Frank C., White, Tonya, van IJzendoorn, Marinus H., Tiemeier, Henning
Source: Child Development. Mar-Apr 2020 91(2):347-365.
Availability: Wiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA
Peer Reviewed: Y
Page Count: 19
Publication Date: 2020
Document Type: Journal Articles
Reports - Research
Descriptors: Prenatal Influences, Mothers, Stress Variables, Pregnancy, Cognitive Development, Intelligence Quotient, Ethnicity, Correlation, Acculturation, Minority Groups, Immigrants, Foreign Countries
Geographic Terms: Netherlands
DOI: 10.1111/cdev.13177
ISSN: 0009-3920
Abstract: The evidence for negative influences of maternal stress during pregnancy on child cognition remains inconclusive. This study tested the association between maternal prenatal stress and child intelligence in 4,251 mother-child dyads from a multiethnic population-based cohort in the Netherlands. A latent factor of prenatal stress was constructed, and child IQ was tested at age 6 years. In Dutch and Caribbean participants, prenatal stress was not associated with child IQ after adjustment for maternal IQ and socioeconomic status. In other ethnicities no association was found; only in the Moroccan/Turkish group a small negative association between prenatal stress and child IQ was observed. These results suggest that prenatal stress does not predict child IQ, except in children from less acculturated minority groups.
Abstractor: As Provided
Entry Date: 2020
Accession Number: EJ1246006
Database: ERIC
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  Value: <anid>AN0142101339;cdv01mar.20;2020Mar09.02:20;v2.2.500</anid> <title id="AN0142101339-1">Prenatal Maternal Stress and Child IQ </title> <p>The evidence for negative influences of maternal stress during pregnancy on child cognition remains inconclusive. This study tested the association between maternal prenatal stress and child intelligence in 4,251 mother–child dyads from a multiethnic population‐based cohort in the Netherlands. A latent factor of prenatal stress was constructed, and child IQ was tested at age 6 years. In Dutch and Caribbean participants, prenatal stress was not associated with child IQ after adjustment for maternal IQ and socioeconomic status. In other ethnicities no association was found; only in the Moroccan/Turkish group a small negative association between prenatal stress and child IQ was observed. These results suggest that prenatal stress does not predict child IQ, except in children from less acculturated minority groups.</p> <p>Fetal neurodevelopment represents a vulnerable period in which maternal exposure to stress is suggested to have a long‐term impact on the development in offspring (Wadhwa, Sandman, & Garite, [<reflink idref="bib73" id="ref1">73</reflink>]). However, its impact on child cognitive outcomes remains unclear. One of the reasons for inconsistent study results may be that the concept of maternal stress during pregnancy is imprecisely and differently defined; most previous research encompassed only one dimension as the measure of stress, such as psychopathology or stress reactions to <emph>specific</emph> events, and key confounders such as maternal IQ were often not taken into account. In this study, we assessed maternal prenatal stress as a latent construct based on several manifestations of stress in different life domains. Our population‐based prospective cohort study gave us the opportunity to examine the association between stress during pregnancy and child intelligence in the offspring of mothers with various ethnic backgrounds and lifestyle characteristics.</p> <hd id="AN0142101339-2">Maternal Stress During Pregnancy and Offspring Cognition</hd> <p>Barker and Osmond ([<reflink idref="bib2" id="ref2">2</reflink>]) hypothesized that maternal undernutrition during pregnancy causes fetal changes with long‐term consequences in the offspring. While this theory was initially developed in relation to maternal undernutrition, it was later broadened to include other in utero exposures. This comprehensive model, termed as the "Developmental Origins of Health and Disease" (DOHaD), proposes that the environment can have a long‐lasting influence during the phase of developmental plasticity, and in interaction with genetic factors determine health and risk of disease in later life (Gluckman & Hanson, [<reflink idref="bib22" id="ref3">22</reflink>]; Wadhwa, Buss, Entringer, & Swanson, [<reflink idref="bib72" id="ref4">72</reflink>]). As part of the DOHaD model the effects of prenatal psychological stress on offspring developmental outcomes have also been evaluated, with the purpose of understanding the relation between maternal stress and fetal development as well as later psychobiological outcomes (Wadhwa et al., [<reflink idref="bib72" id="ref5">72</reflink>]).</p> <p>Studies that assessed maternal stress during pregnancy in relation to offspring outcomes have used different definitions of stress. Stress is thought to occur when individuals perceive the environmental demands as exceeding their capacity of adaptation (Cohen, Kessler, & Gordon, [<reflink idref="bib12" id="ref6">12</reflink>]). This broad definition of stress has led to studies of a wide variety of stressors in pregnant women, such as interpersonal problems, financial difficulties, physical complaints, depression, or worries about their pregnancy (O'Donnell, O'Connor, & Glover, [<reflink idref="bib48" id="ref7">48</reflink>]). Also, while many scholars consider depression and stress to be different concepts, studies on the association of prenatal stress and child outcomes often include depression in the stress definition. For example, a systematic review of the association between maternal prenatal stress and young children's cognitive development operationalized maternal psychological distress as the occurrence of depression, anxiety, perceived stress or stressful experiences during pregnancy (Kingston, McDonald, Austin, & Tough, [<reflink idref="bib36" id="ref8">36</reflink>]). Very similar inclusion criteria were used by Kinsella and Monk ([<reflink idref="bib37" id="ref9">37</reflink>]) in their narrative review of maternal stress studies, which summarized the associations of maternal depression, stress, and anxiety with neurobehavioral outcomes. Pregnancy‐specific anxiety has also been included as part of the maternal prenatal stress concept in studies on the association with child mental development (DiPietro, Novak, Costigan, Atella, & Reusing, [<reflink idref="bib15" id="ref10">15</reflink>]). The variation in the definition and measures of maternal prenatal stress reflects that stress during pregnancy can manifest differently in different domains of life. In the following section, we briefly summarize studies focusing on specific stress measures. Studies are organized according to their measure of stress to facilitate a review of the literature.</p> <hd id="AN0142101339-3">Maternal Anxiety During Pregnancy</hd> <p>Studies of prenatal maternal anxiety and child cognition show inconsistent results. Brouwers, Van Baar, and Pop ([<reflink idref="bib7" id="ref11">7</reflink>]) observed an association between prenatal anxiety, as measured with the State‐Trait Inventory, and less optimal offspring mental development assessed with the Bayley scales of Infant Development in a group of 105 two‐year‐old Dutch children. Likewise, higher maternal prenatal anxiety was associated with lower IQ scores in a sample of 57 adolescents aged 14‐ to 15‐year old (Van den Bergh et al., [<reflink idref="bib71" id="ref12">71</reflink>]) and with lower academic performance in 5,801 16‐year‐old adolescents in the ALSPAC cohort (Pearson et al., [<reflink idref="bib52" id="ref13">52</reflink>]). In contrast, Grant et al. found no difference between infants of mothers with prenatal anxiety and controls in their scores for the mental development index of the Bayley scales in a sample of 77 seven‐month‐old children (Grant, McMahon, Reilly, & Austin, [<reflink idref="bib23" id="ref14">23</reflink>]). Similarly, Koutra et al. found that maternal anxiety during pregnancy did not predict less optimal cognitive development in offspring using a sample of 223 eighteen‐month‐old children from a population‐based cohort in Greece (Koutra et al., [<reflink idref="bib39" id="ref15">39</reflink>]). DiPietro et al. ([<reflink idref="bib14" id="ref16">14</reflink>]) reported that higher levels of maternal prenatal stress were related to accelerated fetal and infant neurological maturation in a sample of 112 healthy pregnancies. Also higher levels of maternal prenatal anxiety were associated with <emph>better</emph> offspring mental development measured with the Bayley Scales of Infant Development in 82 two‐year‐old children who belonged to a well‐nourished, financially stable population (DiPietro et al., [<reflink idref="bib15" id="ref17">15</reflink>]).</p> <hd id="AN0142101339-4">Maternal Depression During Pregnancy</hd> <p>Studies of prenatal maternal depression and child cognitive outcomes also showed discrepant results. Self‐reported depressive symptoms were assessed in a sample of 6,979 pregnant mothers from the ALSPAC cohort and children of mothers with higher levels of depressive symptoms during pregnancy had slightly worse cognitive functioning as measured by the Wechsler Intelligence Scale for Children (Evans et al., [<reflink idref="bib20" id="ref18">20</reflink>]). In contrast, Tse, Rich‐Edwards, Rifas‐Shiman, Gillman, and Oken ([<reflink idref="bib67" id="ref19">67</reflink>]) observed that children who were exposed to maternal depression during pregnancy did not perform differently, compared to nonexposed children, on the Peabody Picture Vocabulary Test at 3 years of age in a study of 1,030 mother–child pairs.</p> <hd id="AN0142101339-5">Other Measures of Prenatal Stress</hd> <p>A few studies assessed maternal perceived stress during pregnancy, that is, the degree to which life events were considered stressful. Perceived maternal prenatal stress was related to lower offspring intelligence as measured with the Stanford Binet Scale in 550 three‐year‐old children (Slykerman et al., [<reflink idref="bib59" id="ref20">59</reflink>]). Other studies related pregnancy‐specific anxiety to child cognitive outcomes. Huizink et al. studied pregnancy‐specific anxiety in a sample of 170 mothers, and found that higher self‐reported pregnancy‐specific anxiety predicted lower mental developmental scores as measured with the Bayley Scales of Infant Development in 8‐month‐old children (Huizink, de Medina, Mulder, Visser, & Buitelaar, [<reflink idref="bib29" id="ref21">29</reflink>]). Similar results were observed by Davis and Sandman ([<reflink idref="bib13" id="ref22">13</reflink>]) who studied the presence of pregnancy‐specific anxiety in a sample of 125 pregnant mothers and found an association with lower mental scores on the Bayley scales in 1‐year‐old children. Laplante et al. studied a group of 89 mothers, who were exposed during pregnancy to an ice storm in the Canadian province of Québec. They observed that maternal prenatal stress, retrospectively reported, was associated with lower children's IQ scores at age 5 years (Laplante, Brunet, Schmitz, Ciampi, & King, [<reflink idref="bib40" id="ref23">40</reflink>]).</p> <hd id="AN0142101339-6">A Broad Definition of Stress</hd> <p>The previous studies aimed to investigate how specific aspects of maternal stress are related to child cognitive development. However, stressful events rarely happen in isolation but rather tend to co‐occur, increasing the risk for a deleterious offspring effect (Appleyard, Egeland, van Dulmen, & Sroufe, [<reflink idref="bib1" id="ref24">1</reflink>]). Moreover, psychological or perceived stress cannot be directly observed (Milfont & Fischer, [<reflink idref="bib46" id="ref25">46</reflink>]) and can only be assessed by self‐reported indicators that represent related aspects of stress (e.g., daily hassles, severe life events; O'Donnell et al., [<reflink idref="bib48" id="ref26">48</reflink>]). The substantial conceptual and phenotypic overlap of these stress measures are arguments supporting a broad concept of perceived stress. Furthermore, no specific mechanistic pathways toward offspring cognition have been established for any of the different perceived stress measures. Therefore, to examine the broad concept of perceived prenatal maternal stress, we constructed a latent variable. The latent variable model captures the structure underlying the covariance among the observed variables (the self‐reported stress measures; Bartholomew, Knott, & Moustaki, [<reflink idref="bib3" id="ref27">3</reflink>]), while simultaneously reducing the dimensionality. This approach has an additional advantage. Members of different groups (e.g., females and males, old and young age groups, ethnic groups) are often compared with the assumption that pertinent variables represent similar constructs across groups. This assumption, known as measurement invariance, is often not tested (Milfont & Fischer, [<reflink idref="bib46" id="ref28">46</reflink>]). However, when there is lack of measurement invariance (when the concept is not equivalent in all groups), the interpretation and comparison of the construct (prenatal maternal stress) across groups is not meaningful. Latent variable models can be specified without this assumption if the different groups are accounted for and give insight into the extent of variability of the construct between the groups.</p> <p>We modeled a broad concept of stress to account for the high co‐occurrence of stress factors. This broad stress definition, that encompasses different domains, allowed us to better examine the long‐term effects of prenatal stress on child cognition than an individual stressor approach. We tested the measurement invariance of the stress concept in our multiethnic population‐based sample. Due to lack of invariance across ethnicities, we performed our analyses in separate ethnic groups.</p> <hd id="AN0142101339-7">Methodological Considerations</hd> <p>The studies on maternal stress and child cognition are not only characterized by a diversity of exposure measures but also vary in the degree to which they account for methodological challenges inherent to studies of prenatal exposure and child cognition. First, some researchers assessed maternal prenatal stress retrospectively (Laplante et al., [<reflink idref="bib40" id="ref29">40</reflink>]). Studies with retrospective stress assessment yielded larger effect sizes, which could reflect a problem of recall bias (Tarabulsy et al., [<reflink idref="bib63" id="ref30">63</reflink>]). Second, the existing literature of maternal prenatal stress and offspring cognitive outcomes includes a broad array of outcome measures in infants, children and adolescents, hampering a direct comparison of results. A meta‐analysis of studies that assessed child cognitive development between 0 and 60 months of age (typically with the Bayley Scales of Infant Development) reported a small negative effect of prenatal stress (Tarabulsy et al., [<reflink idref="bib63" id="ref31">63</reflink>]). The literature in children between 5 and 12 years is less extensive and also shows less consistent results. Most studies examined the effect of specific stress measures and while some found a negative effect of prenatal stress (assessed as depressive symptoms, anxiety, or stress), others reported no association with child IQ. In contrast, research in adolescents shows a consistently negative effect of prenatal stress on child cognition. However, this evidence should be interpreted with caution as it is based on few, small studies and different specific cognitive measures, whereas IQ was rarely examined. Third, some studies lack adjustment for key confounders like parental intelligence. Cognitive ability is one of the most heritable traits (Polderman et al., [<reflink idref="bib53" id="ref32">53</reflink>]) and shared genetic effects could underlie any observed association between maternal stress and child cognition. Yet, parental intelligence is often not controlled for when examining the association between prenatal stress and child IQ. Fourth, parental education as a measure of genetic transmission and environment quality (i.e., socioeconomic status [SES] and intellectual stimulation; Rowe, Jacobson, & Van den Oord, [<reflink idref="bib58" id="ref33">58</reflink>]) is strongly related to maternal stress and to child cognitive development. The lack of adjustment for parental education may make it difficult to distinguish between the specific effects of prenatal stress and contextual influences on child cognitive outcomes. Most studies adjusted for parental education level; in these studies results are mixed. In contrast, studies that did not account for parental education show a consistent negative association between prenatal stress and child cognition. Fifth, stressed pregnant women tend to be stressed mothers. Postnatal stress influences caregiving and this could inappropriately augment the association between prenatal stress and child IQ. Lastly, the studies on the association of prenatal stress and child cognitive development do not usually take into account vulnerable groups, such as ethnic minorities. Modern societies are characterized by large groups of ethnic minorities, which are more likely to have financial difficulties and are vulnerable to experience stress related to acculturation due to stigma, prejudice and discrimination. This particular kind of stress has been described as "minority stress" (Marshal et al., [<reflink idref="bib42" id="ref34">42</reflink>]; Meyer, [<reflink idref="bib44" id="ref35">44</reflink>]), and it is suggested that the social stressful environment experienced by these individuals generates a higher risk of mental health problems (Meyer, [<reflink idref="bib44" id="ref36">44</reflink>]). Also, although ethnicity and SES are often strongly intertwined, there are unique risks related to ethnic minority status that are not accounted for by SES, such as the social community networks, the degree of acculturation, and discrimination (Dyal & Dyal, [<reflink idref="bib16" id="ref37">16</reflink>]; Williams, [<reflink idref="bib74" id="ref38">74</reflink>]).</p> <p>This study fills several gaps in the literature. We present evidence on the joint effect of different stress domains on the IQ of school‐aged children. In our sample, stress was examined prospectively at different time points during pregnancy, child IQ was assessed with a nonverbal test when children were 5–7 years old, and we controlled our analyses for maternal education and IQ. Furthermore, we provide evidence on the role of ethnicity in the association between prenatal stress and offspring IQ.</p> <hd id="AN0142101339-8">Aim of This Study</hd> <p>The aim of this study was to examine the association between global maternal prenatal stress and offspring IQ at age 6 years. We hypothesized that maternal stress during pregnancy is related to offspring intelligence, even after accounting for key confounders like maternal intelligence. We tested this hypothesis using structural equation modeling, assessing global maternal prenatal stress with a latent construct and child cognition with a nonverbal IQ test. Data were collected within the prospective multiethnic cohort of the Generation R Study.</p> <hd id="AN0142101339-9">Method</hd> <p></p> <hd id="AN0142101339-10">Setting and Population</hd> <p>This research was conducted within the framework of the Generation R Study, a population‐based cohort in Rotterdam, the Netherlands (Kooijman et al., [<reflink idref="bib38" id="ref39">38</reflink>]). This city has a larger proportion of ethnic minorities (44% of inhabitants are of foreign background) than the Netherlands (19%). The largest ethnic minority groups in Rotterdam are the Surinamese (9%), Turkish (7%), and Moroccan (6%; Statistics Netherlands, [<reflink idref="bib61" id="ref40">61</reflink>]). Mothers with a delivery date from April 2002 until January 2006 were enrolled to study determinants of early development and health. Among all eligible children, the response rate was 61%. The proportion of ethnic minority groups in our cohort was higher than nationally reflecting the urban setting of the study, but differed only marginally from that in Rotterdam. The largest minority groups were the Surinamese (9%), Turkish (9%), and Moroccan (6%; Jaddoe et al., [<reflink idref="bib30" id="ref41">30</reflink>]). The education level and household income were higher in the study cohort than in the study area, suggesting a slight selection toward higher SES (Jaddoe et al., [<reflink idref="bib31" id="ref42">31</reflink>]). However, the educational distribution in Generation R was similar to that in the Netherlands; in our sample 55.4% of mothers had a high level of education, this was 53.5% in the women in the Netherlands (reference year: 2002; Statistics Netherlands, [<reflink idref="bib61" id="ref43">61</reflink>]).</p> <p>The study was approved by the Medical Ethics Committee of the Erasmus Medical Center, Rotterdam, and written informed consent was obtained from all adult participants.</p> <p>In total, there were 8,976 children whose mothers were enrolled in the Generation R Study during pregnancy. Stress information was obtained by postal questionnaires at different time points during pregnancy. Most of the information on stress was collected when the mothers were 20–25 weeks pregnant. Mothers who did not reply to this questionnaire were excluded, as were those with information available on only one of the four stress indicators (see Statistical Analysis). This left 6,812 mothers with available information on prenatal stress exposure at baseline. As our study was conducted in a multiethnic sample we examined measurement invariance of the stress construct across ethnicities. Due to lack of measurement invariance (see Statistical Analysis), mothers without information on their national origin could not be included in our study (<emph>n</emph> = 138), as ethnicity‐specific analyses could not be performed. In total, 6,674 participants had information available at baseline for stress exposure and ethnic origin. Nonverbal intelligence was assessed when children were 6 years old. Children who did not participate in this follow‐up data collection wave (<emph>n</emph> = 2,168, 32.5% lost to follow‐up) were excluded. Of the 4,506 participants with available information at follow‐up, children who had no complete IQ score and were, thus, set to 50, were not included as this typically represents invalid IQ scores (<emph>n</emph> = 14). Children who had an IQ score ≤ 70 (<emph>n</emph> = 92) were included only in sensitivity analyses because these scores often indicate poor compliance during the IQ test. Children whose mothers were from Non‐Western American countries (<emph>n</emph> = 50) or Asian other than Indonesian (<emph>n</emph> = 99) were not included as the sample size of these groups was smaller than the number of parameters in our models. This left 4,251 mother–child pairs for analyses (see Figure ).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/CDV/01mar20/cdev13177-fig-0001.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="cdev13177-fig-0001.jpg" title="Flowchart of sample selection. [Color figure can be viewed at wileyonlinelibrary.com]" /> </p> <p></p> <hd id="AN0142101339-12">Sample Characteristics</hd> <p>Characteristics of the study sample are presented in Table  for the six main ethnic groups: Dutch (<emph>n</emph> = 2,567), Non‐Dutch Western (<emph>n</emph> = 380), Caribbean (<emph>n</emph> = 426), Moroccan/Turkish (<emph>n</emph> = 532), African (<emph>n</emph> = 197), and Indonesian (<emph>n</emph> = 149; for more details see Covariates). The majority of the mothers were of Dutch origin (60.0%) and the mean ages at enrollment ranged from 27.9 to 32.7 years. Most of the Dutch mothers had college or higher education (67.0%), whereas in the Caribbean, Moroccan and Turkish, and African mothers this percentage was below 30%. The average maternal IQ was 100.9 (<emph>SD</emph> = 12.6) in the Dutch group, 101.6 (<emph>SD</emph> = 13.5) in the Indonesian, 98.5 (<emph>SD</emph> = 13.9) in the Non‐Dutch Western, 90.2 (<emph>SD</emph> = 14) in the Caribbean, 86.0 (<emph>SD</emph> = 14.4) in the Moroccan/Turkish, and 85.4 (<emph>SD</emph> = 15.3) in the African group.</p> <p>Parental and Child Characteristics</p> <p> <ephtml> <table><thead valign="top"><tr><th align="left">Characteristics</th><th align="center">Dutch (<italic>n</italic> = 2,567)</th><th align="center">Non‐Dutch Western (<italic>n</italic> = 380)</th><th align="center">Caribbean (<italic>n</italic> = 426)</th><th align="center">Moroccan/Turkish (<italic>n</italic> = 532)</th><th align="center">African (<italic>n</italic> = 197)</th><th align="center">Indonesian (<italic>n</italic> = 149)</th></tr><tr><th align="center"><italic>M</italic> (<italic>SD</italic>) or %</th><th align="center"><italic>M</italic> (<italic>SD</italic>) or %</th><th align="center"><italic>M</italic> (<italic>SD</italic>) or %</th><th align="center"><italic>M</italic> (<italic>SD</italic>) or %</th><th align="center"><italic>M</italic> (<italic>SD</italic>) or %</th><th align="center"><italic>M</italic> (<italic>SD</italic>) or %</th></tr></thead><tbody><tr><td align="left">Maternal</td></tr><tr><td align="left">Age, years</td><td align="center">31.7 (4.2)</td><td align="center">31.2 (4.5)</td><td align="center">28.5 (5.8)</td><td align="center">27.9 (5.1)</td><td align="center">28.4 (5.8)</td><td align="center">32.7 (4.9)</td></tr><tr><td align="left">Education, %</td></tr><tr><td align="left">Primary</td><td align="center">0.9</td><td align="center">3.5</td><td align="center">5.9</td><td align="center">20.4</td><td align="center">14.3</td><td align="center">0.7</td></tr><tr><td align="left">Secondary</td><td align="center">32.1</td><td align="center">31.9</td><td align="center">65.1</td><td align="center">58.4</td><td align="center">63.8</td><td align="center">28.2</td></tr><tr><td align="left">Higher</td><td align="center">67.0</td><td align="center">64.6</td><td align="center">29.0</td><td align="center">21.2</td><td align="center">21.9</td><td align="center">71.1</td></tr><tr><td align="left">Smoking in pregnancy, %</td><td align="center">13.9</td><td align="center">14.7</td><td align="center">17.1</td><td align="center">21.2</td><td align="center">15.7</td><td align="center">14.1</td></tr><tr><td align="left">Alcohol frequently in pregnancy, %</td><td align="center">12.5</td><td align="center">11.9</td><td align="center">2.0</td><td align="center">0.0</td><td align="center">4.8</td><td align="center">13.1</td></tr><tr><td align="left">Maternal IQ score</td><td align="center">100.9 (12.6)</td><td align="center">98.5 (13.9)</td><td align="center">90.2 (14.0)</td><td align="center">86.0 (14.4)</td><td align="center">85.4 (15.3)</td><td align="center">101.6 (13.5)</td></tr><tr><td align="left">Family income, %</td></tr><tr><td align="left">< 1,200 €</td><td align="center">4.6</td><td align="center">8.7</td><td align="center">38.7</td><td align="center">43.8</td><td align="center">56.0</td><td align="center">9.1</td></tr><tr><td align="left">1,200–2,000 €</td><td align="center">13.8</td><td align="center">22.2</td><td align="center">22.3</td><td align="center">37.8</td><td align="center">22.2</td><td align="center">8.8</td></tr><tr><td align="left">>2,000 €</td><td align="center">81.6</td><td align="center">69.1</td><td align="center">39.0</td><td align="center">18.4</td><td align="center">21.8</td><td align="center">82.1</td></tr><tr><td align="left">Paternal</td></tr><tr><td align="left">Education, %</td></tr><tr><td align="left">Primary</td><td align="center">2.3</td><td align="center">5.3</td><td align="center">9.9</td><td align="center">24.0</td><td align="center">26.0</td><td align="center">0.0</td></tr><tr><td align="left">Secondary</td><td align="center">32.1</td><td align="center">37.6</td><td align="center">66.1</td><td align="center">50.2</td><td align="center">51.7</td><td align="center">28.0</td></tr><tr><td align="left">Higher</td><td align="center">65.6</td><td align="center">57.1</td><td align="center">24.0</td><td align="center">25.8</td><td align="center">22.3</td><td align="center">72.0</td></tr><tr><td align="left">Child</td></tr><tr><td align="left">Age, years</td><td align="center">6.1 (0.4)</td><td align="center">6.1 (0.4)</td><td align="center">6.3 (0.7)</td><td align="center">6.3 (0.6)</td><td align="center">6.3 (0.6)</td><td align="center">6.1 (0.5)</td></tr><tr><td align="left">Child IQ score</td><td align="center">105.3 (13.7)</td><td align="center">101.6 (13.7)</td><td align="center">96.7 (12.4)</td><td align="center">96.2 (11.9)</td><td align="center">97.4 (13.1)</td><td align="center">105.2 (12.3)</td></tr><tr><td align="left">Gender, % girls</td><td align="center">51.4</td><td align="center">55.5</td><td align="center">50.0</td><td align="center">49.2</td><td align="center">51.8</td><td align="center">51.7</td></tr><tr><td align="left">Birthweight, grams</td><td align="center">3,472.5 (565.7)</td><td align="center">3,420.4 (565.8)</td><td align="center">3,203.5 (558.5)</td><td align="center">3,440.9 (502.0)</td><td align="center">3,268.3 (563.0)</td><td align="center">3,468.5 (594.1)</td></tr></tbody></table> </ephtml> </p> <p>1 Note</p> <p>3 The characteristics were measured in the imputed data set (<emph>n</emph> = 4,251).</p> <p>In our study 51.4% of the children were girls, and the average child nonverbal IQ score was 105.3 (<emph>SD</emph> = 13.7) in the Dutch children, 105.2 (<emph>SD</emph> = 12.3) in the Indonesian, 101.6 (<emph>SD</emph> = 13.7) in the Non‐Dutch Western, 96.7 (<emph>SD</emph> = 12.4) in the Caribbean, 96.2 (<emph>SD</emph> = 11.9) in the Moroccan/Turkish, and 97.4 (<emph>SD</emph> = 13.1) in the African children (Table ).</p> <hd id="AN0142101339-13">Measures</hd> <p></p> <hd id="AN0142101339-14">Prenatal Maternal Stress Exposure</hd> <p>To examine the association between a broadly operationalized prenatal stress measure and offspring IQ at age 6 years, we used a prenatal maternal stress exposure construct developed by Cecil et al. ([<reflink idref="bib8" id="ref44">8</reflink>]) that has previously been implemented with good model fit using Generation R data (Rijlaarsdam et al., [<reflink idref="bib56" id="ref45">56</reflink>]). This stress construct is based on maternal reports during pregnancy in relation to four stress domains, accounting for different manifestations of stress: <emph>life stress</emph> (stressful life events such as illness, work‐related problems, pregnancy‐related anxiety), <emph>contextual stress</emph> (e.g., major financial difficulties, housing conditions), <emph>personal stress</emph> (e.g., psychiatric symptoms, criminal involvement), and <emph>interpersonal stress</emph> (e.g., family functioning, difficulties with others). For each stress domain, item scores were summed and divided by the number of completed items. Thus, higher scores represent greater stress exposure. For this study, we adapted the stress construct by excluding maternal education and substance use from the stress domain variables. Although related to stress experience, maternal education and substance use have been shown to affect offspring neurobehavioral development mostly by pathways independent of maternal prenatal stress (Hanscombe et al., [<reflink idref="bib25" id="ref46">25</reflink>]; Olds, Henderson, & Tatelbaum, [<reflink idref="bib49" id="ref47">49</reflink>]; Olney et al., [<reflink idref="bib50" id="ref48">50</reflink>]). All stress domains were positively correlated (all <emph>p</emph> < .001; Table ; see Supporting Information for full item and instruments descriptions, Table S1).</p> <p>Correlations Between the Prenatal Stress Domains</p> <p> <ephtml> <table><thead valign="top"><tr><th align="left" /><th align="center"><italic>M</italic> (<italic>SD</italic>)</th><th align="center">Correlation matrix</th></tr><tr><th align="center">Life stress</th><th align="center">Contextual stress</th><th align="center">Personal stress</th><th align="center">Interpersonal stress</th></tr></thead><tbody><tr><td align="left">Stress domains</td></tr><tr><td align="left">Life stress</td><td align="center">1.85 (1.5)</td><td align="center">—</td><td align="center" /><td align="center" /><td align="center" /></tr><tr><td align="left">Contextual stress</td><td align="center">1.06 (1.4)</td><td align="center">.36</td><td align="center">—</td><td align="center" /><td align="center" /></tr><tr><td align="left">Personal stress</td><td align="center">0.13 (0.4)</td><td align="center">.33</td><td align="center">.37</td><td align="center">—</td><td align="center" /></tr><tr><td align="left">Interpersonal stress</td><td align="center">1.90 (2.6)</td><td align="center">.33</td><td align="center">.42</td><td align="center">.42</td><td align="center">—</td></tr></tbody></table> </ephtml> </p> <ulist> <item>2 Note</item> <item>4 Correlation significant at the.01 level (two‐tailed). All <emph>p</emph> < .001. <emph>n</emph> = 4,251.</item> </ulist> <hd id="AN0142101339-15">Child Cognition</hd> <p>Child intelligence was measured in the research center by trained research assistants with a nonverbal IQ test when children were 5–7 years old. A nonverbal test was selected that minimized the potential bias related to the Dutch language abilities among children of Non‐Dutch ethnicities. We administered two subtests of a validated Dutch nonverbal intelligence test: Snijders‐Oomen Niet‐verbale intelligentie test, 2.5‐7‐ revisie (SON‐R 2.5‐7; Tellegen, Winkel, Wijnberg‐Williams, & Laros, [<reflink idref="bib65" id="ref49">65</reflink>]). The subtests were "Mosaics," that evaluates spatial insight, and "Categories," that examines abstract reasoning abilities. The average alpha reliability of the total score of the SON‐R 2.5‐7 was of.90 (Tellegen et al., [<reflink idref="bib65" id="ref50">65</reflink>]) and the reliabilities for the subtest scores that we used were.73 and.71 for Mosaics and Categories, respectively. The correlation between scores derived from the two applied subsets and the scores form the complete test was.86 (P. J. Tellegen, personal communication, March 7, 2011). The raw scores were transformed into nonverbal IQ scores, using age‐specific normal values based on the exact child age (Tellegen, Winkel, Wijnberg‐Williams, & Laros, [<reflink idref="bib64" id="ref51">64</reflink>]).</p> <p>The nonverbal IQ scores were normally distributed, ranging from 71 to 147 with a mean of 102.6 and a standard deviation of 13.8 in our study sample (Figure S1). During the assessment, research assistants rated the child's motivation, collaboration and understanding of instructions (Basten et al., [<reflink idref="bib4" id="ref52">4</reflink>]).</p> <hd id="AN0142101339-16">Covariates</hd> <p>The variables selected as covariates were maternal IQ score, maternal and paternal educational level, family income, maternal alcohol consumption, and smoking during pregnancy. We selected the confounders based on determinants of child cognitive development, the existing literature on the association between maternal prenatal stress and child intelligence (Eriksen et al., [<reflink idref="bib18" id="ref53">18</reflink>]; Henrichs et al., [<reflink idref="bib27" id="ref54">27</reflink>]; Tse et al., [<reflink idref="bib67" id="ref55">67</reflink>]), and by change‐in‐estimate criteria (cut‐off of 5%). Maternal educational level, maternal alcohol consumption and smoking during pregnancy, family income, and paternal education level were assessed with questionnaires during pregnancy. Educational level was indicated by the highest completed education, and was classified in primary, secondary, and higher education. Smoking during pregnancy was collected at enrollment and during mid and late pregnancy and was categorized as nonsmoking during pregnancy, smoking until pregnancy was known and continued smoking throughout pregnancy. Family income, defined by the total net monthly income of the household, was classified as below social security level (< 1,200 €), low income (1,200–2,000 €), and modal to high income (more than 2,000 €). Maternal intelligence was measured at the same time when child IQ data were collected, when the mother accompanied the 6‐year‐old child to the research center, with the set I of the Raven's Advanced Progressive Matrices Test (Raven, [<reflink idref="bib55" id="ref56">55</reflink>]). This test has been shown to be a valid and reliable short form of the Raven's Progressive Matrices test to assess nonverbal cognition (Chiesi, Ciancaleoni, Galli, & Primi, [<reflink idref="bib10" id="ref57">10</reflink>]; Pearson, [<reflink idref="bib51" id="ref58">51</reflink>]) and the nonverbal aspect of the test minimizes the impact of the language abilities in the Non‐Dutch mothers in our study.</p> <hd id="AN0142101339-17">Maternal Ethnicity</hd> <p>Information on maternal ethnicity was collected by questionnaires during pregnancy and was defined according to Statistics Netherlands ([<reflink idref="bib61" id="ref59">61</reflink>]). The ethnic classification was based on the country of birth of the parents of the participant. If one of the parents was born abroad, the participant was considered to be of Non‐Dutch ethnic origin. If both parents were born abroad, the country of birth of the participant's mother defined the participant's ethnic origin. Maternal ethnicity was initially categorized as Dutch, Non‐Dutch Western, and Non‐Western. The Non‐Dutch Western mothers came from European, Oceanian, and Western American countries. The Non‐Western group included four subgroups: Caribbean (Dutch Antillean and Surinamese), Moroccan/Turkish (Moroccan and Turkish), African (Cape Verdian and other African), and Indonesian mothers. In the ethnic minority groups, a questionnaire on self‐reported Dutch language ability was administered during pregnancy. Dutch language ability was defined as a composite of three questions that referred to reading, writing, and speaking abilities. The sense of belonging to the Dutch culture was assessed during pregnancy based on the extent to which the participant agreed with the following statement: "I feel part of the Dutch culture." Following recent evidence that supports the predictive validity of single‐items measures (Bowling, [<reflink idref="bib5" id="ref60">5</reflink>]), these items (i.e., language abilities and feeling part of the Dutch culture) were used as proxy measures for maternal acculturation. Higher scores indicated higher levels of acculturation. The distribution of these variables in the various ethnic groups is described in Table S2.</p> <hd id="AN0142101339-18">Statistical Analysis</hd> <p></p> <hd id="AN0142101339-19">Measurement Model</hd> <p>A reflective, standardized latent construct of maternal prenatal stress was estimated in R (Lavaan Package developmental version 0.6‐1.1141 (Rosseel, [<reflink idref="bib57" id="ref61">57</reflink>])) using the previously described four stress domains (life stress, contextual stress, personal stress, and interpersonal stress) as indicators. Internal reliability of the stress domains and of the latent construct of maternal prenatal stress was assessed with confirmatory factor analyses (see Rijlaarsdam et al., [<reflink idref="bib56" id="ref62">56</reflink>]). The latent construct showed good model fit as judged with the comparative fit index (CFI, acceptable fit ≥ .90, McDonald & Ho, [<reflink idref="bib43" id="ref63">43</reflink>]).</p> <p>An important requirement for a meaningful interpretation of the analysis with a latent construct is the measurement invariance of the construct across relevant subgroups in the population (i.e., the meaning of the concept of stress is the same across members of relevant subgroups; Milfont & Fischer, [<reflink idref="bib46" id="ref64">46</reflink>]). We performed measurement invariance tests to examine whether the maternal stress construct was similar across child sex and maternal national origin subgroups as our cohort is a multiethnic sample. The invariance of the latent construct was evaluated with a series of hierarchically nested multigroup models in which constraints of the loadings, intercepts and variances of the latent variable were progressively implemented. To decide whether a more restricted model fitted as well as a less restricted model, we used the delta CFI cutoff of < .01 (Hirschfeld & von Brachel, [<reflink idref="bib28" id="ref65">28</reflink>]), which is robust for testing the between‐group invariance of latent variable models (Cheung & Rensvold, [<reflink idref="bib9" id="ref66">9</reflink>]). Measurement invariance was tested across the groups of maternal ethnicity. We aimed to define broad ethnic groups in whom the stress construct was invariant. First, measurement invariance tests were performed across the three main maternal ethnic groups (i.e., Dutch, Non‐Dutch Western, and Non‐Western). Due to lack of invariance across these ethnic groups (i.e., lack of equivalent psychometric properties; see Results), we could not validly examine global prenatal stress in an unstratified sample. Therefore, the subsequent analyses were performed in more narrowly defined ethnic groups, organized by the national origins of the participants and socioeconomic characteristics shared by specific ethnic groups (Odé, [<reflink idref="bib47" id="ref67">47</reflink>]). The main analyses were performed in six ethnic subgroups: Dutch, Non‐Dutch Western, Caribbean, Moroccan/Turkish, African, and Indonesian (see factor loadings for the measurement model of global prenatal maternal stress for the different ethnic groups in Table ).</p> <p>Standardized Factor Loading Estimates (and Standard Errors) for the Global Prenatal Maternal Stress in the Measurement Model for the Different Ethnic Groups</p> <p> <ephtml> <table><thead valign="top"><tr><th align="left">Indicators</th><th align="center">Factor loadings</th></tr><tr><th align="center">Dutch <italic>n</italic> = 2,567</th><th align="center">Non‐Dutch Western <italic>n</italic> = 380</th><th align="center">Caribbean <italic>n</italic> = 426</th><th align="center">Moroccan/Turkish <italic>n</italic> = 532</th><th align="center">African <italic>n</italic> = 197</th><th align="center">Indonesian <italic>n</italic> = 149</th></tr><tr><th align="center">Estimate (<italic>SE</italic>)</th><th align="center">Estimate (<italic>SE</italic>)</th><th align="center">Estimate (<italic>SE</italic>)</th><th align="center">Estimate (<italic>SE</italic>)</th><th align="center">Estimate (<italic>SE</italic>)</th><th align="center">Estimate (<italic>SE</italic>)</th></tr></thead><tbody><tr><td align="left">Life stress</td><td align="center">.44 (0.03)</td><td align="center">.54 (0.08)</td><td align="center">.52 (0.07)</td><td align="center">.57 (0.06)</td><td align="center">.56 (0.08)</td><td align="center">.67 (0.20)</td></tr><tr><td align="left">Contextual stress</td><td align="center">.55 (0.04)</td><td align="center">.57 (0.07)</td><td align="center">.61 (0.06)</td><td align="center">.48 (0.05)</td><td align="center">.79 (0.07)</td><td align="center">.40 (0.15)</td></tr><tr><td align="left">Personal stress</td><td align="center">.48 (0.06)</td><td align="center">.57 (0.12)</td><td align="center">.59 (0.07)</td><td align="center">.70 (0.05)</td><td align="center">.60 (0.08)</td><td align="center">.27 (0.18)</td></tr><tr><td align="left">Interpersonal stress</td><td align="center">.59 (0.04)</td><td align="center">.62 (0.08)</td><td align="center">.62 (0.07)</td><td align="center">.56 (0.05)</td><td align="center">.60 (0.08)</td><td align="center">.49 (0.18)</td></tr></tbody></table> </ephtml> </p> <hd id="AN0142101339-20">Structural Path Analysis</hd> <p>The construction of the measurement model and the analyses of the association between the latent construct of maternal prenatal stress and child cognition were simultaneously performed using structural equation modeling in R (Lavaan Package). Analyses (Path model: Figure ) were conducted in the following ethnic subgroups: Dutch, Non‐Dutch Western, Caribbean, Moroccan/Turkish, African, and Indonesian. The models were estimated with the robust maximum likelihood estimator (Huber‐White standard errors) and the latent variable was scaled by standardization of the latent variable variance to 1. The path coefficients represent the change in the predicted child IQ score per standard deviation increase in maternal prenatal stress.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/CDV/01mar20/cdev13177-fig-0002.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="cdev13177-fig-0002.jpg" title="Path model of the structural equation model for the association between global prenatal maternal stress and child IQ scores. [Color figure can be viewed at wileyonlinelibrary.com]" /> </p> <p></p> <p>Confounders were initially selected based on existing literature and then by change‐in‐estimate criteria (cut‐off of 5%; Mickey & Greenland, [<reflink idref="bib45" id="ref68">45</reflink>]), that is, evaluating the change in the estimate of the association between maternal stress and child intelligence when adding each confounder to the univariate regression. The confounders selected were maternal IQ, maternal education, paternal education, family income, maternal smoking during pregnancy, and alcohol consumption during pregnancy. Four models of the association between maternal stress during pregnancy and child intelligence were constructed with a progressive inclusion of covariates to show the impact of the adjustment for groups of key confounders. Adjustment for confounders was applied to the latent construct and to the prenatal stress—child IQ path. The goodness of fit of these progressively adjusted models was compared with the Bayesian information criterion (BIC) and Akaike's information criterion (AIC). A lower value for AIC and BIC indicates a better fit (Jouni, [<reflink idref="bib34" id="ref69">34</reflink>]).</p> <hd id="AN0142101339-22">Sensitivity Analyses</hd> <p>In additional analyses, we explored the association between the prenatal stress domains included in the latent construct and child IQ using multiple linear regression analyses. As in the overall model, the analyses were performed in each ethnic group and with similar adjustment for confounders. The regression estimates are presented for the standardized stress indicators.</p> <p>We further examined the associations between the different prenatal stress measures and child IQ by linear regression analyses; every stress measure included in our stress latent construct was studied (for more information see Table S1). These analyses were performed in the complete unstratified sample and also separately for each ethnic group, controlling for maternal IQ, SES‐related factors and substance use. We further adjusted the associations in the complete sample for ethnic groups in a second model. Analyses were not performed in a subgroup of stress variables with < 10 exposed participants.</p> <p>As SES has been shown to moderate the amount of variance in IQ explained by the shared environment (Turkheimer, Haley, Waldron, D'Onofrio, & Gottesman, [<reflink idref="bib68" id="ref70">68</reflink>]), we explored the role of SES as a moderator in the association of prenatal stress and child IQ. To this aim, we calculated the principal component of the different SES measures (i.e., maternal and paternal education and household income). Following our main analyses, we ran an additional model adding the SES‐principal component as predictor and its interaction with the stress latent construct. The stress latent construct and the interaction term were orthogonalized (i.e., their covariance was fixed to 0).</p> <p>To better represent the variation of low IQ scores in the general population, we also tested if the association between prenatal stress and child IQ changed if children with IQ scores below 70 (<emph>n</emph> = 92), which are considered less valid (Mackenzie & Wonders, [<reflink idref="bib41" id="ref71">41</reflink>]), were included. We also used a more conservative approach in a subsequent sensitivity analysis and included only children (<emph>n</emph> = 3,702) who had good motivation, collaboration, and understanding of instructions during the IQ test.</p> <hd id="AN0142101339-23">Missing Data</hd> <p>The sample (<emph>n</emph> = 4,251) had complete information for child IQ scores, maternal ethnicity and for at least two of the four stress indicators. All missing value frequencies per variable were below 15% (maximum: contextual stress = 11.3%). Multiple imputation was performed for the missing values of the stress indicators and the confounders in the statistical software of R (MICE package version 2.46 (van Buuren & Groothuis‐Oudshoorn, [<reflink idref="bib70" id="ref72">70</reflink>])), using 40 imputations. The semTools package (semTools version 0.4‐15.910 (Jorgensen et al., [<reflink idref="bib33" id="ref73">33</reflink>])) was used to pool the estimates.</p> <p>The acculturation variables were included in a post hoc analysis. These variables were only available for ethnic minorities. The maximum percentage of missing values was 21.2% for the variable "Feeling part of the Dutch culture" and 14.5% for Language abilities in the Moroccan/Turkish mothers.</p> <hd id="AN0142101339-24">Nonresponse Analysis</hd> <p>Differences in baseline characteristics between children included in our study sample and those who were not included were evaluated using chi‐square tests for the categorical and independent t‐tests for the continuous variables (See also the baseline characteristics of children lost to follow‐up in Table S3). The nonresponse analyses showed that mothers of children who were not included were younger (mean maternal age = 28.7) and less educated (13.4% of these mothers had only primary education) than mothers of children in the study (<emph>M</emph><subs>age</subs> = 30.7, primary education = 4.6%). Also, excluded mothers were more likely to smoke throughout pregnancy (19.0%) than mothers of children in our study sample (15.3%).</p> <hd id="AN0142101339-25">Results</hd> <p></p> <hd id="AN0142101339-26">Measurement Model</hd> <p>Analyses of measurement invariance of the stress latent construct showed strict invariance when grouping participants by child sex (delta CFI < .01), but lack of invariance across the broad maternal ethnic groups (i.e., Dutch, Non‐Dutch Western, and Non‐Western; Table S4) and across the ethnic subgroups of the Non‐Western mothers (Caribbean, Moroccan/Turkish, African, and Indonesian; <emph>n</emph> = 1,304; Table S5). However, there was strong measurement invariance within the Moroccan/Turkish, the Caribbean (Surinam and Dutch Antilles), and the African (African other than Moroccan, and Cape Verdean) subgroups (Tables S6–S8). As there was lack of invariance across the broad ethnic groupings but strong measurement invariance in more narrowly defined ethnic groups, the association of maternal prenatal stress and child IQ was evaluated in six ethnic groups separately: Dutch, Non‐Dutch Western, Caribbean, Moroccan/Turkish, African, and Indonesian.</p> <p>The measurement model and the structural equation model are depicted in Figure . The loadings of the latent stress construct on each stress indicator variable ranged from.27 (personal stress in the Indonesian mothers) to.79 (contextual stress in the African mothers) in the six ethnic groups (Table ).</p> <hd id="AN0142101339-27">Maternal Prenatal Stress and Child IQ</hd> <p>Table  shows the association between the latent construct of maternal prenatal stress and child IQ in the six ethnic groups (Dutch, Non‐Dutch Western, Caribbean, Moroccan/Turkish, African, and Indonesian). Results are shown with the stepwise confounder adjustment and presented as Model 1 (unadjusted model) to Model 4 (fully adjusted model; Table ).</p> <p>Association of Global Maternal Prenatal Stress (Latent Variable) With Child IQ</p> <p> <ephtml> <table><thead valign="top"><tr><th align="left">Ethnic group</th><th align="center"><italic>n</italic></th><th align="center">Child IQ</th></tr><tr><th align="center">Model 1</th><th align="center">Model 2</th><th align="center">Model 3</th><th align="center">Model 4</th></tr><tr><th align="center"><italic>b</italic> (<italic>SE</italic>)</th><th align="center"><italic>p</italic></th><th align="center"><italic>b</italic> (<italic>SE</italic>)</th><th align="center"><italic>p</italic></th><th align="center"><italic>b</italic> (<italic>SE</italic>)</th><th align="center"><italic>p</italic></th><th align="center"><italic>b</italic> (<italic>SE</italic>)</th><th align="center"><italic>p</italic></th></tr></thead><tbody><tr><td align="left">Dutch</td><td align="center">2,567</td><td align="center">−1.57 (0.36)</td><td align="center">< .001</td><td align="center">−1.13 (0.35)</td><td align="center">.001</td><td align="center">−.30 (0.38)</td><td align="center">.431</td><td align="center">−.19 (0.39)</td><td align="center">.631</td></tr><tr><td align="left">Non‐Dutch Western</td><td align="center">380</td><td align="center">−.25 (1.01)</td><td align="center">.805</td><td align="center">.09 (0.97)</td><td align="center">.929</td><td align="center">.62 (1.01)</td><td align="center">.539</td><td align="center">.51 (1.01)</td><td align="center">.613</td></tr><tr><td align="left">Non‐Western</td></tr><tr><td align="left">Caribbean</td><td align="center">426</td><td align="center">−1.58 (0.67)</td><td align="center">.019</td><td align="center">−1.45 (0.66)</td><td align="center">.028</td><td align="center">−.61 (0.72)</td><td align="center">.398</td><td align="center">−.43 (0.74)</td><td align="center">.561</td></tr><tr><td align="left">Moroccan/Turkish</td><td align="center">532</td><td align="center">−1.83 (0.65)</td><td align="center">.005</td><td align="center">−1.73 (0.63)</td><td align="center">.006</td><td align="center">−1.44 (0.64)</td><td align="center">.024</td><td align="center">−1.53 (0.63)</td><td align="center">.015</td></tr><tr><td align="left">African</td><td align="center">197</td><td align="center">.24 (1.07)</td><td align="center">.820</td><td align="center">.25 (1.08)</td><td align="center">.820</td><td align="center">.48 (1.14)</td><td align="center">.674</td><td align="center">.06 (1.22)</td><td align="center">.960</td></tr><tr><td align="left">Indonesian</td><td align="center">149</td><td align="center">−.22 (1.74)</td><td align="center">.899</td><td align="center">−.49 (2.01)</td><td align="center">.809</td><td align="center">−2.01 (1.83)</td><td align="center">.271</td><td align="center">−1.97 (3.54)</td><td align="center">.577</td></tr></tbody></table> </ephtml> </p> <ulist> <item>5 Note</item> <item>8 Models were constructed using structural equation modeling (Lavaan package). Values are regression coefficients, standard errors, and <emph>p</emph> values. The estimates are based on the standardized latent factor (global stress). A progressive adjustment was applied to the latent factor and to the structural path as listed below. All models converged in at least 38 data sets. In the Indonesian group, Model 2 and 4 had pooled negative variance for the indicator of contextual stress which probably reflects a relatively low sample size given the numbers of parameters. <emph>n</emph> = 4,251. Model 1. Without adjustment; Model 2. Model 1 + Maternal IQ; Model 3. Model 2 + Maternal education + Paternal education + Family income; Model 4. Model 3 + Maternal smoking during pregnancy + Maternal alcohol consumption during pregnancy.</item> </ulist> <p>In the Dutch population, a one‐standard‐deviation increase in the levels of maternal stress was associated with 1.57 (<emph>SE</emph> = 0.36) points lower child IQ score in the initial analyses. After adjusting for maternal intelligence, the association was attenuated (β = −1.13 points, <emph>SE</emph> = 0.35) and finally disappeared in Model 3, after additional adjustment for the socioeconomic indicators, that is, maternal and paternal education and family income (β = −.30 points, <emph>SE</emph> = 0.38, <emph>p</emph>‐value = .43). A similar stepwise reduction of the association of prenatal maternal stress and child intelligence was observed in the Caribbean group, in whom the association disappeared in the third model, after adjustment for SES (β = −.61 points, <emph>SE</emph> = 0.72, <emph>p</emph>‐value = .40).</p> <p>No association between maternal stress during pregnancy and child intelligence was observed in the unadjusted model in the Non‐Dutch Western, the African, and the Indonesian groups. In contrast, a one‐standard‐deviation increase in the levels of prenatal stress in the Moroccan and Turkish mothers was related to 1.83 point lower child IQ in the initial model, and this association was only slightly attenuated after complete adjustment for potential confounders (Model 4: β = −1.53 points, <emph>SE</emph> = 0.63).</p> <p>The goodness of fit of these progressively adjusted models was evaluated with the AIC and BIC for each ethnic group (Table S9). Both criteria indicated in general a better fit of the models with additional adjustment for SES‐related factors and substance use (i.e., Models 3 and 4).</p> <p>We performed exploratory regression analyses between each of the maternal stress indicators and child IQ in the different ethnic groups. In the Dutch population, no association was found between any of the stress indicators (i.e., life stress, contextual stress, personal stress, and interpersonal stress) and child IQ after controlling for confounders (Table ). Likewise, in the Moroccan/Turkish group, only suggestive associations between the maternal stress indicators and child IQ were observed after adjustment (Table ). The stress domains were not related to child IQ in the other ethnicities, except for one of four domain measures in the Indonesians, in whom one‐standard‐deviation higher contextual stress in the mother was related to a 3‐point lower offspring IQ (<emph>SE</emph> = 1.36, <emph>p</emph>‐value = .02; Table S10).</p> <p>Association Between Indicators of Maternal Prenatal Stress and Child IQ Score in the Dutch Group</p> <p> <ephtml> <table><thead valign="top"><tr><th align="left" /><th align="center">Child IQ</th></tr><tr><th align="center">Model 1</th><th align="center">Model 2</th><th align="center">Model 3</th><th align="center">Model 4</th></tr><tr><th align="center"><italic>b</italic> (<italic>SE</italic>)</th><th align="center"><italic>p</italic></th><th align="center"><italic>b</italic> (<italic>SE</italic>)</th><th align="center"><italic>p</italic></th><th align="center"><italic>b</italic> (<italic>SE</italic>)</th><th align="center"><italic>p</italic></th><th align="center"><italic>b</italic> (<italic>SE</italic>)</th><th align="center"><italic>p</italic></th></tr></thead><tbody><tr><td align="left">Stress variables</td></tr><tr><td align="left">Life stress</td><td align="center">−.39 (0.32)</td><td align="center">.22</td><td align="center">−.19 (0.31)</td><td align="center">.54</td><td align="center">.09 (0.32)</td><td align="center">0.79</td><td align="center">.16 (0.33)</td><td align="center">.61</td></tr><tr><td align="left">Contextual stress</td><td align="center">−1.10 (0.36)</td><td align="center">.002</td><td align="center">−.72 (0.34)</td><td align="center">.03</td><td align="center">.01 (0.39)</td><td align="center">0.98</td><td align="center">.10 (0.39)</td><td align="center">.81</td></tr><tr><td align="left">Personal stress</td><td align="center">−1.19 (0.39)</td><td align="center">.002</td><td align="center">−.82 (0.39)</td><td align="center">.04</td><td align="center">−.30 (0.40)</td><td align="center">0.46</td><td align="center">−.19 (0.41)</td><td align="center">.64</td></tr><tr><td align="left">Interpersonal stress</td><td align="center">−1.46 (0.36)</td><td align="center">< .001</td><td align="center">−1.19 (0.35)</td><td align="center">.001</td><td align="center">−.57 (0.37)</td><td align="center">0.13</td><td align="center">−.53 (0.37)</td><td align="center">.15</td></tr></tbody></table> </ephtml> </p> <ulist> <item>6 Note</item> <item>9 Models were constructed using multiple linear regression (SEM function, MLR estimator (maximum likelihood estimation with robust (Huber‐White) standard errors)). Values are regression coefficients, standard errors, and <emph>p</emph> values. The stress variables were standardized. <emph>n</emph> = 2,567. Model 1. Without adjustment; Model 2. Model 1 + Maternal IQ; Model 3. Model 2 + Maternal education + Paternal education + Family income; Model 4. Model 3 + Maternal smoking during pregnancy + Maternal alcohol consumption during pregnancy.</item> </ulist> <p>Association Between Indicators of Maternal Prenatal Stress and Child IQ Score in the Moroccan/Turkish Group</p> <p> <ephtml> <table><thead valign="top"><tr><th align="left" /><th align="center">Child IQ</th></tr><tr><th align="center">Model 1</th><th align="center">Model 2</th><th align="center">Model 3</th><th align="center">Model 4</th></tr><tr><th align="center"><italic>b</italic> (<italic>SE</italic>)</th><th align="center"><italic>p</italic></th><th align="center"><italic>b</italic> (<italic>SE</italic>)</th><th align="center"><italic>p</italic></th><th align="center"><italic>b</italic> (<italic>SE</italic>)</th><th align="center"><italic>p</italic></th><th align="center"><italic>b</italic> (<italic>SE</italic>)</th><th align="center"><italic>p</italic></th></tr></thead><tbody><tr><td align="left">Stress variables</td></tr><tr><td align="left">Life stress</td><td align="center">−.86 (0.44)</td><td align="center">.05</td><td align="center">−.91 (0.43)</td><td align="center">.04</td><td align="center">−.77 (0.45)</td><td align="center">.09</td><td align="center">−.82 (0.44)</td><td align="center">.06</td></tr><tr><td align="left">Contextual stress</td><td align="center">−.93 (0.46)</td><td align="center">.04</td><td align="center">−.97 (0.46)</td><td align="center">.03</td><td align="center">−.64 (0.49)</td><td align="center">.19</td><td align="center">−.65 (0.49)</td><td align="center">.19</td></tr><tr><td align="left">Personal stress</td><td align="center">−.69 (0.42)</td><td align="center">.10</td><td align="center">−.67 (0.42)</td><td align="center">.11</td><td align="center">−.59 (0.44)</td><td align="center">.18</td><td align="center">−.62 (0.41)</td><td align="center">.13</td></tr><tr><td align="left">Interpersonal stress</td><td align="center">−1.43 (0.51)</td><td align="center">.01</td><td align="center">−1.16 (0.51)</td><td align="center">.02</td><td align="center">−.92 (0.53)</td><td align="center">.09</td><td align="center">−.96 (0.51)</td><td align="center">.06</td></tr></tbody></table> </ephtml> </p> <ulist> <item>7 Note</item> <item>10 Models were constructed using multiple linear regression (SEM function, MLR estimator). Values are regression coefficients, standard errors and <emph>p</emph> values. The stress variables were standardized. All models converged in at least 25 imputed data sets. <emph>n</emph> = 532. Model 1. Without adjustment; Model 2. Model 1 + Maternal IQ; Model 3. Model 2 + Maternal education + Paternal education + Family income; Model 4. Model 3 + Maternal smoking during pregnancy + Maternal alcohol consumption during pregnancy.</item> </ulist> <p>In order to test if the association between maternal prenatal stress and child intelligence in the Moroccan/Turkish group was explained by minority stress, we performed a post hoc sensitivity analysis in this ethnic group. We adjusted the association of maternal prenatal stress and child IQ in Model 2 (i.e., model adjusted only for maternal IQ) for maternal acculturation variables (feeling part of the Dutch culture and language abilities). The association between maternal stress and child IQ in the Moroccan/Turkish participants remained essentially unchanged after this adjustment (β = −1.73 points, <emph>SE</emph> = 0.63, <emph>p</emph>‐value = .01). Additionally, in separate linear regression models, we observed that acculturation was not associated with child IQ in the Moroccan/Turkish ethnic group. Better maternal language abilities were, however, related to less prenatal stress in the Moroccan/Turkish group. Also, this ethnic minority had the lowest level of self‐reported acculturation in our sample (Table S2). The sensitivity analyses of the associations between the individual stress measures and child IQ are presented in Table S11. The analyses in the complete study sample demonstrate the independent contribution of ethnic origin to the association of prenatal stress and child IQ. After additional adjustment for ethnicity (Model 2), the associations between most stress variables and child IQ (already adjusted for maternal IQ, SES and substance use) were substantially reduced. Only family conflict and lack of satisfaction with obstetric care were related to lower child IQ after full adjustment for potential confounders. However, these results should be interpreted cautiously given the number of tests. We also explored the role of SES as a moderator in the association of the latent prenatal stress construct and child IQ; no significant interaction with SES on the association with IQ was observed (Table S12).</p> <p>The analyses of the association between prenatal stress and IQ including children with an IQ below 70 are presented in Table S13. The associations did not change substantially, with one exception, in the Moroccan/Turkish group the association was attenuated in Model 3 and was only borderline significant. When we included only children who showed good compliance during the IQ test the associations after full adjustment for confounders were essentially unchanged if compared with the primary analysis. In this latter sensitivity analysis the association between stress and child IQ in the Moroccan/Turkish group remained after adjustment for confounders (β = −1.64 points, <emph>SE</emph> = 0.79, <emph>p</emph>‐value = .038), indicating possible information bias in the sensitivity analysis that included children with very low IQ.</p> <hd id="AN0142101339-28">Discussion</hd> <p>In the ethnic Dutch group and in the Caribbean minority, no association between maternal self‐reported prenatal stress and child IQ was observed after adjustment for maternal IQ and socioeconomic‐related factors, contrary to our main hypothesis. No association was found, even before adjustment, between prenatal stress and child IQ in the Non‐Dutch Western, the African and the Indonesian groups. Only in the Moroccan and Turkish mother–child dyads, maternal prenatal stress predicted a lower child IQ score after adjustment for confounders.</p> <p>Most of the previous prenatal stress research focused on psychiatric problems such as depressive symptoms (Tse et al., [<reflink idref="bib67" id="ref74">67</reflink>]), anxiety (Van den Bergh et al., [<reflink idref="bib71" id="ref75">71</reflink>]) or in generally perceived stress (Slykerman et al., [<reflink idref="bib59" id="ref76">59</reflink>]), and the studies that assessed more than one manifestation of stress usually investigated the association with child cognition in separate models (e.g., DiPietro et al., [<reflink idref="bib15" id="ref77">15</reflink>]). In contrast, we assessed maternal prenatal stress with a latent construct based on different life domains, capturing more indices of maternal stress during pregnancy. As stressful events tend to co‐occur, the simultaneous assessment of various indices of prenatal stress is more relevant to public health than the single stress measurements (Felitti et al., [<reflink idref="bib21" id="ref78">21</reflink>]). Additionally, the latent construct allowed us to systematically examine the shared variance of the different stress manifestations (Tinsley & Tinsley, [<reflink idref="bib66" id="ref79">66</reflink>]) and to test whether the stress experience was similar across different groups in society (Milfont & Fischer, [<reflink idref="bib46" id="ref80">46</reflink>]). Previous studies on the relation between maternal stress and offspring cognition in school‐age children reported mixed findings. Some observed a negative effect of stress, whereas others did not find any association. These studies typically focused on specific stress measures, such as depressive symptoms, anxiety, or stressful events. We do not intend to reconcile this conflicting evidence with this study, but to extend the scientific knowledge with a complementary approach: testing the association between a broad, cumulative stress construct and cognitive functioning of school‐age children.</p> <p>The adjustment of the association between maternal prenatal stress and child IQ for family income, maternal and paternal education and maternal alcohol consumption and smoking during pregnancy could be seen by some scholars as over‐adjustment since these variables are life‐style factors generally related to the concept of stress (Cohen, Doyle, & Baum, [<reflink idref="bib11" id="ref81">11</reflink>]; Hassanbeigi, Askari, Hassanbeigi, & Pourmovahed, [<reflink idref="bib26" id="ref82">26</reflink>]), thus the adjustment for these variables was performed in a late step and in separate models. These factors affect offspring mental development through multiple pathways other than maternal stress during pregnancy (Eriksen et al., [<reflink idref="bib18" id="ref83">18</reflink>]; Hanscombe et al., [<reflink idref="bib25" id="ref84">25</reflink>]; Olds et al., [<reflink idref="bib49" id="ref85">49</reflink>]; Olney et al., [<reflink idref="bib50" id="ref86">50</reflink>]). Parental education influences child IQ mainly by three pathways: first, education is highly correlated with IQ and thus the association of parental education and child IQ is strongly genetically determined. Second, parental education affects child cognitive development through parenting and upbringing. Third, low parental education can also be seen as a cause of stress, for example, financial stress during pregnancy. Importantly, financial stress and other education‐related stress indicators were accounted for by the indicator of contextual stress. Likewise, the consumption of alcohol and tobacco during pregnancy can be seen as a marker of stress. However, pregnant women in the Netherlands are not consistently advised to be totally abstinent. Consequently, alcohol consumption in our and other study samples is associated with indicators of well‐being (Kelly et al., [<reflink idref="bib35" id="ref87">35</reflink>]). The inclusion of these SES indicators and substance use in the stress construct would inappropriately broaden the stress definition, with implications for the etiological understanding and public health interventions.</p> <p>In the offspring of the Dutch and Caribbean mothers, the association between maternal prenatal stress and child IQ was explained by maternal IQ and socioeconomic indicators (i.e., parental education and family income). Differences in the association between prenatal stress and child IQ across ethnic groups may represent a difference in the understanding of stress and the influence of the transactive nature of the genetic cognitive potential and the postnatal environment in the prediction of offspring cognition. In the Moroccan/Turkish group, mothers had, on average, a lower IQ score than the mean in our sample (average maternal IQ score = 97.1) and the percentage of mothers with only primary education was the highest among all ethnicities. In contrast, the lack of association between prenatal stress and child IQ, even in the unadjusted model, in the Non‐Dutch Western, the African, and the Indonesian groups can best be explained by the lack of variance in child IQ accounted for by SES‐related factors due to the homogeneity in social background.</p> <p>Parental education level, as a proxy for "environmental quality" (i.e., financial resources and intellectual stimulation), is suggested to be a moderator for the heritability of IQ; typically, the IQ heritability is higher when the level of parental education is higher. Also, Rowe et al. ([<reflink idref="bib58" id="ref88">58</reflink>]) demonstrated that the proportion of variance in IQ explained by the shared environmental effects, such as SES and family structure, is higher when the level of parental education was lower. Thus, in those ethnicities with high parental education the absence of an association between prenatal stress and IQ could be related to the low variance explained by the shared environment (such as a maternal stress). In contrast, the low education in the Moroccan and Turkish parents would imply that the IQ phenotype would be highly responsive to environmental variation. Additionally, the Moroccan and Turkish mothers may be sharing a sustained stressor, that would prolong maternal stress into the postnatal period and therefore influence cognitive development, through lower cognitive stimulation, parenting style, and the home environment (Guo & Harris, [<reflink idref="bib24" id="ref89">24</reflink>]; Jensen, Dumontheil, & Barker, [<reflink idref="bib32" id="ref90">32</reflink>]).</p> <p>We examined the role of minority stress in the negative association between prenatal maternal stress and child IQ in the Moroccan and Turkish. More than 25% of the population of Rotterdam are immigrants, and most of them come from Surinam, Turkey, or Morocco (Entzinger & Engbersen, [<reflink idref="bib17" id="ref91">17</reflink>]). The native majority in the Netherlands corresponds to a relatively affluent and financially equal population with a good quality of life (Eurostat Statistical Book, [<reflink idref="bib19" id="ref92">19</reflink>]), whereas the ethnic minorities encounter high levels of stress related to the pressure of integration and acculturation (Smith, [<reflink idref="bib60" id="ref93">60</reflink>]; Statistics Netherlands [<reflink idref="bib62" id="ref94">62</reflink>]). The integration of ethnic minorities in the Netherlands remains particularly difficult for the immigrants coming from Morocco or Turkey (Statistics Netherlands [<reflink idref="bib62" id="ref95">62</reflink>]) as they display low levels of upward social mobility (Uitermark, [<reflink idref="bib69" id="ref96">69</reflink>]). We explored the influence of minority stress, as measured by the acculturation variables, on the association between maternal stress and child IQ. Among all ethnic minorities, the Moroccan and Turkish mothers had the lowest levels of self‐reported acculturation. However, acculturation did not confound the association between maternal stress and child IQ in the Moroccan/Turkish sample. We cannot rule out that the low acculturation in the Moroccan and Turkish mothers, compared to other ethnicities, may indicate a vulnerability to stress, as postulated by Dyal and Dyal ([<reflink idref="bib16" id="ref97">16</reflink>]). We were not able to test the interaction between maternal stress and acculturation as maternal prenatal stress was not invariant across ethnicities. Several other limitations must be also considered. First, the latent construct lacks direct measure and does not have inherent units (Ramlall, [<reflink idref="bib54" id="ref98">54</reflink>]). Therefore, the direct translation of our results to public health may be limited. However, it is difficult to imagine how a broad concept of stress could be directly measured. Second, it is possible that the latent, broad, stress construct approach obscures associations of specific stress measures, such as the association observed between the contextual stress domain and child IQ in the Indonesian ethnic group. However, an association found while examining various stress measures in different groups could be the result of multiple testing and thus reflect chance. Third, we observed a higher average IQ in the children compared to maternal IQ in all ethnicities. This may reflect the difference in the IQ measures used in children and mothers, and thus absolute IQ mother–child differences cannot be evaluated. Additionally, although a valid assessment of performance, maternal IQ is an imperfect measure of child genetic potential, as the offspring IQ is also determined by postnatal factors such as schooling (Brinch & Galloway, [<reflink idref="bib6" id="ref99">6</reflink>]) and by paternal IQ. In order to account for the child genetic potential we could only adjust our analyses for maternal and not for paternal IQ. Fourth, the mothers who did not respond were younger and less educated, characteristics that may suggest a higher risk of experiencing higher levels of stress. The absence of these participants in our study may affect the generalizability of our results. Fifth, we grouped participants in ethnic groups according to the presence of stress‐related environmental factors, such as their socioeconomic background (Odé, [<reflink idref="bib47" id="ref100">47</reflink>]). Yet, genetic and cultural differences across and even within countries remain. However, the observed measurement invariance of the stress construct in our sample supported our grouping, suggesting that these ethnic groups share a similar understanding of the concept of stress (Milfont & Fischer, [<reflink idref="bib46" id="ref101">46</reflink>]). Sixth, the Indonesian group had a small sample size relative to the number of parameters in the model, limiting the precision of results in this group.</p> <p>This study contributes to a better understanding of the association between maternal stress during pregnancy and child intelligence in the general population. We did not find support for the model predicting prenatal stress effects on later cognitive development in the majority of our study sample. We showed that any observed association was mostly explained by maternal IQ and SES indicators, except in the least acculturated ethnic minority. Most likely, postnatal factors, such as social disadvantage, sustained maternal stress, and ethnic‐related stressors, may play a role in the offspring cognitive development of less acculturated minorities.</p> <p>GRAPH: Figure S1. Distribution of Child IQ scores (including all IQ scores)Table S1. Stress Domains and Instruments UsedTable S2. Descriptive Information of Acculturation Among Ethnic GroupsTable S3. Nonresponse AnalysisTable S4. Measurement Invariance Across Groups of Maternal Ethnicity (Dutch, Non‐Dutch Western, Non‐Western)Table S5. Measurement Invariance Across Subgroups of Maternal Non‐Western Ethnicity (Caribbean, Moroccan/Turkish, African, Indonesian)Table S6. Measurement Invariance Across Moroccan and Turkish GroupsTable S7. Measurement Invariance Across the Subgroups Within the Caribbean Ethnic Group (Dutch Antilles, Surinam)Table S8. Measurement Invariance Across the Subgroups Within the African Ethnic Group (Cape Verde, Other African)Table S9. Fit Indices of Models for the Association of Global Maternal Prenatal Stress (Latent Variable) and Child IQTable S10. Association Between the Stress Domains and Child IQ in Each Ethnic Group (Analyses in the Dutch and Moroccan/Turkish Groups are in Tables 5 and 6)Table S11. Association of Maternal Prenatal Stress Measures and Child IQTable S12. Moderation Effect of Socioeconomic Status on the Association of Prenatal Stress and Child IQTable S13. Association of Global Maternal Prenatal Stress (Latent Variable) With Child IQ Including Child IQ Scores Below 70</p> <ref id="AN0142101339-29"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref24" type="bt">1</bibl> <bibtext> We gratefully acknowledge the contribution of the children and parents, general practitioners, hospitals, midwives, and pharmacies in Rotterdam, the Netherlands. The Generation R Study was conducted by the Erasmus Medical Center in close collaboration with the School of Law and Faculty of Social Sciences of the Erasmus University Rotterdam, the Municipal Health Service Rotterdam area, the Rotterdam Homecare Foundation, and the Stichting Trombosedienst & Artsenlaboratorium Rijnmond in Rotterdam. The work of Henning Tiemeier is supported by grants from the European Union Seventh Framework Program (FP7/2007‐2013): ACTION: Aggression in Children (grant number 602768) and from the Netherlands Organization for Scientific Research (NWO‐grant 016.VICI.170.200). Alexander Neumann is supported by a grant of the Dutch Ministry of Education, Culture, and Science and the Netherlands Organization for Scientific Research (NWO grant No. 024.001.003, Consortium on Individual Development). Andrea P. Cortes Hidalgo and Marinus H. van IJzendoorn are supported by the award from the Netherlands Organization for Scientific Research (Spinoza prize to Marinus H. van IJzendoorn). Marian J. Bakermans‐Kranenburg is supported by the European Research Council (ERC AdG). Marinus H. van IJzendoorn and Marian J. Bakermans‐Kranenburg are additionally supported by the Gravitation program of the Dutch Ministry of Education, Culture, and Science and the Netherlands Organization for Scientific Research (NWO grant number 024.001.003). Jolien Rijlaarsdam is supported by a research award from the Netherlands Organization for Scientific Research (NWO ZonMw VENI, grant no. 91618147). Vincent W.V. Jaddoe received a grant from the Netherlands Organization for Health Research and Development (VIDI 016.136.361), and a Consolidator Grant from the European Research Council (ERC‐2014‐CoG‐648916). 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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Prenatal Maternal Stress and Child IQ
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Cortes+Hidalgo%2C+Andrea+P%2E%22">Cortes Hidalgo, Andrea P.</searchLink><br /><searchLink fieldCode="AR" term="%22Neumann%2C+Alexander%22">Neumann, Alexander</searchLink><br /><searchLink fieldCode="AR" term="%22Bakermans-Kranenburg%2C+Marian+J%2E%22">Bakermans-Kranenburg, Marian J.</searchLink><br /><searchLink fieldCode="AR" term="%22Jaddoe%2C+Vincent+W%2E+V%2E%22">Jaddoe, Vincent W. V.</searchLink><br /><searchLink fieldCode="AR" term="%22Rijlaarsdam%2C+Jolien%22">Rijlaarsdam, Jolien</searchLink><br /><searchLink fieldCode="AR" term="%22Verhulst%2C+Frank+C%2E%22">Verhulst, Frank C.</searchLink><br /><searchLink fieldCode="AR" term="%22White%2C+Tonya%22">White, Tonya</searchLink><br /><searchLink fieldCode="AR" term="%22van+IJzendoorn%2C+Marinus+H%2E%22">van IJzendoorn, Marinus H.</searchLink><br /><searchLink fieldCode="AR" term="%22Tiemeier%2C+Henning%22">Tiemeier, Henning</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Child+Development%22"><i>Child Development</i></searchLink>. Mar-Apr 2020 91(2):347-365.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Wiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 19
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2020
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Prenatal+Influences%22">Prenatal Influences</searchLink><br /><searchLink fieldCode="DE" term="%22Mothers%22">Mothers</searchLink><br /><searchLink fieldCode="DE" term="%22Stress+Variables%22">Stress Variables</searchLink><br /><searchLink fieldCode="DE" term="%22Pregnancy%22">Pregnancy</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+Development%22">Cognitive Development</searchLink><br /><searchLink fieldCode="DE" term="%22Intelligence+Quotient%22">Intelligence Quotient</searchLink><br /><searchLink fieldCode="DE" term="%22Ethnicity%22">Ethnicity</searchLink><br /><searchLink fieldCode="DE" term="%22Correlation%22">Correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Acculturation%22">Acculturation</searchLink><br /><searchLink fieldCode="DE" term="%22Minority+Groups%22">Minority Groups</searchLink><br /><searchLink fieldCode="DE" term="%22Immigrants%22">Immigrants</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Netherlands%22">Netherlands</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1111/cdev.13177
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0009-3920
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The evidence for negative influences of maternal stress during pregnancy on child cognition remains inconclusive. This study tested the association between maternal prenatal stress and child intelligence in 4,251 mother-child dyads from a multiethnic population-based cohort in the Netherlands. A latent factor of prenatal stress was constructed, and child IQ was tested at age 6 years. In Dutch and Caribbean participants, prenatal stress was not associated with child IQ after adjustment for maternal IQ and socioeconomic status. In other ethnicities no association was found; only in the Moroccan/Turkish group a small negative association between prenatal stress and child IQ was observed. These results suggest that prenatal stress does not predict child IQ, except in children from less acculturated minority groups.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2020
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1246006
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1246006
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1111/cdev.13177
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 19
        StartPage: 347
    Subjects:
      – SubjectFull: Prenatal Influences
        Type: general
      – SubjectFull: Mothers
        Type: general
      – SubjectFull: Stress Variables
        Type: general
      – SubjectFull: Pregnancy
        Type: general
      – SubjectFull: Cognitive Development
        Type: general
      – SubjectFull: Intelligence Quotient
        Type: general
      – SubjectFull: Ethnicity
        Type: general
      – SubjectFull: Correlation
        Type: general
      – SubjectFull: Acculturation
        Type: general
      – SubjectFull: Minority Groups
        Type: general
      – SubjectFull: Immigrants
        Type: general
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Netherlands
        Type: general
    Titles:
      – TitleFull: Prenatal Maternal Stress and Child IQ
        Type: main
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      – PersonEntity:
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            NameFull: Cortes Hidalgo, Andrea P.
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            NameFull: Neumann, Alexander
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            NameFull: Bakermans-Kranenburg, Marian J.
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            NameFull: Jaddoe, Vincent W. V.
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            NameFull: White, Tonya
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            NameFull: van IJzendoorn, Marinus H.
      – PersonEntity:
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            NameFull: Tiemeier, Henning
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      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2020
          Identifiers:
            – Type: issn-print
              Value: 0009-3920
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              Value: 91
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: Child Development
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