Cohort Profile: Mapping Antenatal Maternal Stress (MAMS)

Cohort Profile: Mapping Antenatal Maternal Stress (MAMS) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Cohort Profile: Mapping Antenatal Maternal Stress (MAMS) Jenell Ong, Nurshuhadah Binte Abdulla, Valerie Ng, Benjamin Chow, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9206507/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract The Mapping Antenatal Maternal Stress (MAMS) study is a prospective, longitudinal birth cohort designed to investigate factors influencing maternal antenatal emotional well-being and develop a predictive model for this state. The study also aims to explore genetic and environmental contributions of maternal antenatal emotional well-being and how maternal mental health impacts child outcomes, including executive functions, socio-emotional, and neurocognitive development. The MAMS study recruited 1419 women aged 21–40 years in early to mid-pregnancy between September 2019 and November 2022 from the National University Hospital of Singapore, resulting in 1258 children born to the cohort. The participants were followed up for 4-6 visits during pregnancy and 7 visits postnatally until the child reached three years old. Data collection involved standardized questionnaires and the collection of biological samples (blood, buccal swabs, saliva) at multiple time points. A subset of 227 MAMS children underwent intensive laboratory-based assessments of executive functions and brain development, including electroencephalography (EEG), magnetic resonance imaging (MRI), and eye-tracking during the first three years of life. Paternal assessments and reports on child behavioral outcomes were also incorporated into this sub-study. Pregnancy Maternal Stress Mental Health Cohort Studies Child Development Figures Figure 1 Figure 2 INTRODUCTION Depression, anxiety, and persistently elevated psychological distress during pregnancy are associated with detrimental outcomes in both mothers and their offspring. Mothers with poor prenatal mental health experience impairments in parenting and psychosocial functions [1, 2]. Notably, a comprehensive economic research revealed that 72% of healthcare costs related to poor maternal mental health are incurred by the affected children [3]. These children are at heightened risk for cognitive, emotional, and social development difficulties compared to their peers [4-9]. Neuroimaging studies have further shown that elevated prenatal maternal mental health problems are linked to variations in neural circuits and brain structures in neonates [10-12], similar to those observed in adults with depression [13] and anxiety [14]. Importantly, maternal symptoms of depression and anxiety predict a significantly increased risk of psychopathology in the offspring [15-17]. Despite compelling evidence for the importance of maternal emotional well-being during pregnancy, there remains a critical gap in the availability of clinical predictive models to identify women at risk for poor perinatal mental health. This gap limits opportunities for early detection and intervention during pregnancy. While a prior episode of major depression is a well-established predictor [18], it accounts for only a small percentage of women who subsequently develop clinical or high levels of perinatal depression. Similarly, early life adversity (e.g., childhood maltreatment or poor parental care) [19], low socio-economic status [20], and poor social support [21], have been associated with an increased risk for perinatal mood and anxiety disorders. There is also evidence of familial transmission, as women with a family history of depression are more likely to experience poor perinatal mental health, suggesting a genetic component to this risk [18, 22]. Preliminary research suggests that genetic influences interact with developmental history and psychosocial factors to determine the risk for antenatal depression [23]. Far less is known about the etiology of maternal antenatal anxiety, which in turn increases the risk for postpartum depression. Emerging findings indicate that maternal genetic variation may contribute to marked individual differences in the onset and trajectory of anxiety and depression in pregnancy [24-26]. Although recent genome-wide studies have identified shared genetic loci for depression and anxiety [27], much of this work has focused on the serotonergic systems [28] and post-partum symptoms [29, 30], despite growing recognition that risk pathways often begin during pregnancy [31], or even before conception [32]. More importantly, mental health is not merely the absence of psychopathology [33]. Mental health lies on a continuum, with positive maternal mental health on the opposite end of the spectrum. Positive maternal mental health has been shown to benefit child development, especially in domains of language acquisition and social communications, independent of maternal depressive or anxiety symptoms [34]. Yet, there is a paucity of research on factors that predict positive maternal mental health, despite its implications for intergenerational well-being and public health. Understanding these protective factors may be critical to promoting resilience in both mothers and children, and advancing targeted preventive strategies at the population level. The Mapping Antenatal Maternal Stress (MAMS) study is a prospective, longitudinal birth cohort study that aims to comprehensively investigate the determinants and consequences of prenatal maternal mental health among women in Singapore. First, we aim to identify the key psychosocial and biological factors that underlie individual differences in maternal mental health during pregnancy, employing predictive algorithms to model risk and resilience profiles. Second, we seek to differentiate the predictors of maternal depressive and anxiety symptoms from those associated with positive mental health, to provide a multidimensional understanding of the full spectrum of maternal emotional well-being. Third, we will examine perinatal maternal mental health in relation to child developmental outcomes, using standardized clinical measures with predictive validity for children's cognitive, emotional, and social outcomes. Finally, we will investigate the contribution of genotypic variation associated with perinatal maternal mental health using a genome-wide analysis of single-nucleotide polymorphisms (SNPs). Specifically, we will compute polygenic risk scores (PRS) for psychiatric and behavioural traits to examine how genetic susceptibility may moderate the association between key psychosocial factors and maternal mental health trajectories, and in turn, how these combined influences affect child outcomes such as executive functions and emotion regulation. Just as important is how psychosocial factors could moderate the genetic risk of poor mental health. We hypothesize that positive maternal mental health will be independently predicted by protective factors such as high emotional support, resilience, and adaptive coping strategies, beyond the absence of psychopathology. We also hypothesize that the PRS for psychiatric vulnerability (e.g., depression, anxiety) will moderate the associations between psychosocial risk factors and maternal mental health, such that individuals with higher genetic susceptibility will exhibit greater emotional reactivity to psychosocial stressors. Lastly, we hypothesize that both maternal mental health and genetic susceptibility will jointly influence child developmental outcomes, with poor maternal mood and higher PRS predicting poorer child developmental outcomes, such as cognitive, and executive functions. STUDY DESIGN AND METHODOLOGY Study population and recruitment The MAMS study recruited 1419 pregnant women aged 21 to 40 years from the National University Hospital, Singapore, between September 2019 and November 2022. Eligible participants needed to be below 24 gestational weeks based on dating by first-trimester ultrasonography, proficient in English, able to respond to questionnaires, intend to stay in Singapore for the next 5 years, have access to a smartphone or digital device, and be willing to participate and provide written consent. Women carrying multiple gestations, those pregnant via assisted reproduction, with pre-existing or a history of psychotic depression, schizophrenia, and bipolar disorders, currently on oral or intravenous steroids and/or thyroid medication, with a history of thyroid disease, or currently enrolled in any interventional randomized controlled trials, were excluded from the study. We approached 8303 women, of whom 6794 were either not suitable or unwilling to participate. 1509 were interested and potentially eligible, of which 90 were subsequently no longer interested in participating in the study. A total of 1419 pregnant women were ultimately recruited into the study. Figure 1 shows the flowchart of participants' progress through the study. Of these 1419 pregnant women, 88.2% (n = 1251) delivered their babies, while 11.8% (n = 168) were lost during pregnancy due to multiple reasons (Figure 1). To date, 1055 mothers and index children have been followed through 24 months, with 36-month follow-up underway (Figure 1). From 13 September 2021, participants in the MAMS study were also asked whether they were interested in a more comprehensive set of assessments to characterize children's early neurodevelopment and parent-child interactions. Their spouses were also invited to participate in the MAMS-Child Outcomes (MAMS-CO) sub-study. 227 (16.0%) mother-child pairs and 133 (9.4%) fathers enrolled into MAMS-CO. Child assessments include brain MRI scans, electroencephalography and eye-tracking tasks, developmental and cognitive assessments, language evaluations, as well as anthropometric and skin-fold thickness measurements. Biological samples, including buccal swabs and saliva, are collected from both parents and the child. Mothers participate in cognitive, socio-emotional, and parenting tasks, while both parents complete self-administered questionnaires across this sub-study period. All participants provided written informed consent. Ethical approval was obtained from the National Healthcare Group Domain Specific Review Board (reference 2018/00967 and 2021/00189). This study has been retrospectively registered at ClinicalTrials.gov (MAMS: NCT07432217; MAMS-CO: NCT07432243) on 25 February 2026. Overview Data were collected at multiple time points across the prenatal and postnatal periods. During pregnancy, mothers completed questionnaires across 4-6 gestational windows depending on gestation at enrolment (refer to Table 1). In the postnatal period, participants provided self-reported data at 7 time points, specifically when the child was 1, 3, 6, 12, 18, 24, and 36 months old, which were also aligned with scheduled laboratory assessments where applicable. Data collected during pregnancy The 4-6 time points during pregnancy consisted of an initial visit for obtaining informed consent and eligibility screening. Table 1 specifies the data collected during pregnancy. Upon enrolment, mothers provided information on their demographic background and general health status. Mothers were asked to wear an Oura ring for a one-week period during 9-14 weeks’ gestation and again during16-29 weeks’ gestation to monitor sleep patterns while completing a sleep diary. A single blood sample was obtained from pregnant mothers, with clear documentation of gestational age at sampling. Blood samples were used to assess allostatic load and associated biomarkers, including inflammatory chemokines. Maternal psychological well-being was assessed using validated questionnaires, including the Edinburgh Postnatal Depression Scale, State-Trait Anxiety Inventory, Perceived Stress Scale, Loneliness Scale, Reconstructed Depressive Experiences Questionnaire, and Pregnancy-related Anxiety Scale. Family psychiatric history was assessed via the Family Interview for Genetic Studies. Maternal childhood experiences were evaluated using the Childhood Trauma Questionnaire, a retrospective version of the McMaster Family Assessment Device, the Parental Bonding Instrument, and the PTSD Checklist for DSM-5 (PCL-5). Social and interpersonal factors were assessed using the Multidimensional Scale of Perceived Social Support, the Experience in Close Relationship, as well as items on marital quality from the Quality of Marriage Index, Marital Strain Scale, and McGill Assessment of Relationship Commitment. Maternal personality traits were assessed using the Big Five Inventory, the Rosenberg Self-Esteem Scale, and the Standardized Assessment of Personality – Abbreviated Scale. Executive functioning was assessed via the Behaviour Rating Inventory of Executive Function – Adult Version. Additionally, mothers completed questionnaires related to sleep beliefs and behaviours, including the Dysfunctional Beliefs and Attitudes about Sleep, Morning-Eveningness Questionnaire, and the Pittsburgh Sleep Quality Index. Pregnancy-related experiences, lifestyle habits, and quality of life were also assessed, including the Quality of Life Enjoyment and Satisfaction, and the Pain Catastrophizing Scale to capture perceptions of pain. Data collected at delivery After delivery, detailed information on antenatal, peripartum, and postpartum events was obtained from antenatal, obstetric, and neonatal hospital medical records. These included routine antenatal clinical and laboratory data, such as maternal weight, blood pressure, urine dipstick, and results from the 3-timepoint 75g oral glucose tolerance test (OGTT). Details on antenatal conditions, and complications such as gestational diabetes mellitus (GDM), hypertensive disorders of pregnancy, and antepartum haemorrhage, were captured. Peripartum events, e.g., mode of delivery and maternity complications, and routinely recorded fetal and neonatal data, including fetal ultrasound parameters, infant sex, birth weight, head circumference, and neonatal complications, were also extracted from medical records. Data collected during postnatal period Table 2 lists the data collected during the postnatal period for mothers and children. Child executive functional and behavioural traits were reported by parents using a suite of internationally validated instruments, including the Behavioural Rating Inventory of Executive Function – Preschool version, Early Childhood Behavioural Questionnaire – Short Form, Infant Behaviour Questionnaire – Revised, and the Strengths and Difficulties Questionnaire. Cognitive, motor, language, socio-emotional, and adaptive behavioural development were assessed using the Bayley Scales of Infant and Toddler Development (4 th Edition; Bayley-4). Sleep patterns and quality were assessed using maternal reports using the Brief Infant Sleep Questionnaire – Revised Short Form. Child sleep quality was also objectively measured using the Philips Respironics Actiwatch 2, worn on the ankle at ages 6, 12, and 24 months. Mothers also reported additional data, including infant feeding practices, particularly breastfeeding, and the child’s physical health status, such as respiratory symptoms, skin conditions, and gastrointestinal issues. Concurrently, mothers continued to provide self-reported data across the postnatal period. Their psychological well-being was monitored using the same validated questionnaires administered during pregnancy, excluding the Pregnancy-related Anxiety Scale. Postnatal sleep quality and chronotype were also assessed using the Pittsburgh Sleep Quality Index and the Morning-Eveningness Questionnaire respectively. Parenting experiences, specifically perceived parenting stress, self-efficacy, and satisfaction, were captured using the Parenting Stress Index – Short Form, and the Parental Sense of Competence. Mothers also continued to complete questionnaires related to their general health, lifestyle behaviors, marital quality, social support, and quality of life, as previously described. For mothers who consented to their child’s participation in the sub-study, MAMS-CO, with more intensive assessments during the child’s first three years of life, assessments were conducted at the same timepoints as those for the broader participant group. In addition to standard questionnaires, these mothers completed supplementary surveys regarding their child’s screen time and childcare arrangements. Language exposure and development were assessed using an in-house questionnaire, as well as the Stim-Q (Infant and Toddler versions), and the Preschool Language Scale – Fifth Edition. Digital audio recordings of the child’s natural environment to capture language input and interaction patterns were collected using the Language Environment Analysis (LENA) recorder at ages 1 and 3 years. Infant development was evaluated using the Ages and Stages Questionnaire and the cognitive module of Bayley-4. Additionally, child anthropometry and neurophysiological assessments were performed during laboratory-based visits at 1, 3, 6, 12, 18, 24, and 36 months. Structural MRI, diffusion-weighted imaging, and resting-state functional MRI scans were performed at 1 and 6 months of age. During 1-36 months, children also participated in a series of age-appropriate eye-tracking tasks, resting-state and task-based electroencephalography (EEG), and event-related potentials (ERPs) to examine auditory recognition, attention, and executive functioning. Dual mother-child EEG recordings were obtained at 6 and 18 months. EEG was collected using the Electrical Geodesics, Inc. (EGI) systems with 128-electrode nets. Maternal sensitivity was assessed through a video recording of the mother-child interaction at 6 months. Additionally, skin assessments were performed to evaluate the extent and severity of atopic dermatitis using the SCORing Atopic Dermatitis (SCORAD) index, and to determine food sensitization or allergy through skin prick tests. Table 3 presents data collected from fathers during pregnancy and the postnatal period. Fathers who consented to participate completed the same questionnaires as mothers to examine their mental health, experiences of childhood adversity, psychosocial factors, and perceptions of their child’s socioemotional, cognitive, and behavioral development. Biosamples collected Buccal samples were collected from mothers, fathers, and children enrolled in the study, either through a home collection kit or during on-site visits. Additionally, buccal samples were obtained from children at 2 years of age for telomere length analysis. Saliva samples were also collected from both mothers and children during the postnatal 3-month visit to facilitate biochemical markers analysis. KEY FINDINGS AND PUBLICATIONS The baseline demographic characteristics are listed in Table 4. Out of the 1419 women recruited into MAMS, 602 (42.4%) were Chinese, 588 (41.4%) were Malays, 155 (10.9%) were Indians, while the remaining 74 (5.2%) were of different ethnicities (see Table 4 for more details). A majority (66.8%, n = 948) were born in Singapore, of whom 79 (5.6%) had foreign-born partners. Conversely, 116 (8.2%) foreign-born women had Singapore-born partners. The mean age of women at recruitment was 30.8 years (range 21.5 – 40.0 years; SD 3.6), and 812 (57.2%) participants had attained at least a tertiary level of education. During pregnancy, 263 (18.5%) women were diagnosed with gestational diabetes mellitus (GDM). Baseline characteristics of participants enrolled in MAMS-CO were compared with the remainder of the MAMS cohort (represented as “Not in MAMS-CO” in Table 4). Standardized mean differences (SMDs) were calculated to assess the magnitude of group differences independent of sample size and accounting for unequal group sizes [35, 36]. SMDs of less than 0.1 were interpreted as negligible differences, whilst 0.25 represented the threshold for potentially meaningful differences [37-39]. SMDs between 0.1 and 0.25 were considered indicative of small differences. There were modest differences between mothers who enrolled in MAMS-CO (n = 227) and those who did not (see Table 4 for details). The most notable difference was in ethnicity, with MAMS-CO comprising a higher proportion of Chinese women (55.5%, n = 126) and fewer Malay women (31.3%, n = 71) compared with those not enrolled in MAMS-CO (Chinese: 39.9%, n = 476; Malay: 43.4%, n = 517). Smaller differences were observed in age at recruitment, birthplace, and educational attainment. Mothers enrolled in MAMS-CO were slightly older (mean = 31.3 years; SD 3.3) than those in MAMS only (30.7 years; SD 3.6). Additionally, a higher proportion of Singapore-born women had foreign-born partners in MAMS-CO (9.3%, n = 21) than in MAMS only (4.9%, n = 58). More women in MAMS-CO attained at least a tertiary level of education (69.6%, n = 158) compared to women who were only in MAMS (54.9%, n = 654). In all other aspects examined, MAMS-CO mothers were comparable to their MAMS-only counterparts. We examined whether maternal depressive symptom levels differed, given that cohort recruitment occurred during the COVID-19 pandemic, with various lockdown protocols implemented between mid-2020 and 2022. The tightest restrictions occurred from 7 April 2020 to 1 June 2020, with brief recurrences from 16 May 2021 to 13 June 2021 and from 22 July 2021 to 9 August 2021. The time trends of mothers’ Edinburgh Postnatal Depression Scale (EPDS) scores across pregnancy were analysed using local polynomial regression (LOESS). LOESS smoothing showed that maternal depressive symptoms remained relatively stable throughout these lockdown periods (Figure 2). Similarly stable trajectories in levels of depressive symptoms across the perinatal period were also reported in MAMS mothers in Kee et al., as well as in six other international cohorts across three decades [31]. Strengths and limitations The MAMS study was explicitly designed to investigate the determinants and consequences of maternal perinatal mental health, particularly in relation to child developmental outcomes. As such, it undertakes more intensive assessments of executive function during the first 3 years of the child’s life, including EEG and eye-tracking tasks to supplement laboratory-based behavioural measures. The MAMS study provides a rare longitudinal perspective on an understudied period of executive function development [40], particularly in Asian populations. Recruiting fathers into the MAMS-CO sub-study allows MAMS to examine the role of fathers in direct and indirect pathways to maternal well-being and child outcomes. As MAMS-CO commenced recruitment partway through the primary study, some fathers were already in the postnatal phase at enrolment. Consequently, paternal data from the pregnancy phase are comparatively limited. Nevertheless, the inclusion of fathers enables longitudinal investigation of paternal influences beginning around the perinatal period. Dyadic analyses will provide insights into the similarity and accuracy of actual and perceived factors, reciprocal effects between parents, and their relationships with child socioemotional outcomes. Several characteristics of the MAMS cohort make it particularly relevant to population trends in Singapore. Firstly, Malays were oversampled, comprising 41.4% of the MAMS cohort; at recruitment in 2019, Malays accounted for 13.4% of the resident population [41]. Among Singapore's ethnic groups, Malays are the largest ethnic minority and have the highest fertility rate [42]. As the proportion of Malays in Singapore is projected to increase despite an overall decline in the national total fertility rate, their overrepresentation in MAMS is especially salient for understanding future population trends. In addition, a proportion of women and/or their partners were foreign-born, reflecting broader demographic patterns in Singapore. In recent decades, both the total number of new Singapore Citizenship and Permanent Residences granted annually has increased by 24.0% from 46,791 in 2010 to 58,030 in 2024 [43]. Concomitantly, the proportion of transnational marriages has increased from 15.1% of citizen marriages in 1984 to 36.6% in 2024 [44]. Consistent with this, the Singapore Longitudinal Early Development Study (SG-LEADS) indicated that 43.1% of families had at least one foreign-born parent [45]. The same study highlighted vulnerabilities particular to families with foreign-born mothers, who may face distinct social and family dynamics [45]. The inclusion of foreign-born women and their partners in MAMS therefore enhances the cohort’s representativeness of contemporary family structures in Singapore. A limitation of the MAMS study is its relatively modest sample size, particularly for those who opted to continue in the comprehensive sub-study. This may be partially attributed to hesitancy around physical contact during the COVID-19 pandemic. Declarations Collaborations The research team welcomes potential collaborations. Investigators interested in collaborations are encouraged to reach out to the lead principal investigators, Dr. Michelle Z.L Kee ( [email protected] ) or Associate Professor Shiao-Yng Chan ( [email protected] ), principal investigators A/Profs Ai Peng Tan ( [email protected] ) and Evelyn C. Law ( [email protected] ). Funding: This work is supported by the Agency for Science, Technology and Research (A*STAR) Prenatal / Early Childhood Grant Call (H22P0M0001) under MJM. Competing Interests: The authors have no relevant financial or non-financial interests to disclose. Author Contributions: Author contributions in alphabetical order: Conceptualization and Methodology: Ai Peng Tan, Evelyn C. Law, Michael J. Meaney, Michelle Z.L Kee, Shiao-Yng Chan Project administration: Benjamin Chow, Nurshuhadah Binte Abdullah, Valerie Ng Formal analysis and investigation: Jenell Ong, Michelle Z.L Kee, Santhi Ponmudi Writing – original draft preparation: Jenell Ong, Michelle Z.L Kee, Santhi Ponmudi Writing – reviewing and editing: Ai Peng Tan, Cornelia Chee, Evelyn C. Law, Helen Chen, Michael J. Meaney, Michelle Z.L Kee, Shiao-Yng Chan All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Ethics Approval: Ethical approval was obtained from the National Healthcare Group Domain Specific Review Board (reference 2018/00967 and 2021/00189). Consent to Participate: Written informed consent was provided by all participants. References Weinberg MK, Tronick EZ, Beeghly M, Olson KL, Kernan H, Riley JM. Subsyndromal depressive symptoms and major depression in postpartum women. 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J Clin Epidemiol. 2013; https://doi.org/10.1016/j.jclinepi.2013.01.013 Hripcsak G, Zhang L, Chen Y, et al. Assessing Covariate Balance With Small Sample Sizes. Stat Med. 2025; https://doi.org/10.1002/sim.70212 Rubin DB. Using Propensity Scores to Help Design Observational Studies: Application to the Tobacco Litigation. Health Services and Outcomes Research Methodology. 2001; https://doi.org/10.1023/a:1020363010465 Hendry A, Jones EJH, Charman T. Executive function in the first three years of life: Precursors, predictors and patterns. Dev Rev. 2016; https://doi.org/10.1016/j.dr.2016.06.005 Singapore Department of Statistics. Singapore Residents By Age Group, Ethnic Group And Sex, At End June [Data Table]. 2024. https://tablebuilder.singstat.gov.sg/table/TS/M810011. Accessed 2 Sep 2025. Singapore Department of Statistics. Population Trends 2024 [Report]. Ministry of Trade and Industry. 2024. https://www.singstat.gov.sg/-/media/files/publications/population/population2024.ashx. Accessed 2 Sep 2025. Singapore Department of Statistics. Number And Profile Of Singapore Citizenships And Permanent Residencies Granted [Data Table]. 2025. https://tablebuilder.singstat.gov.sg/table/TS/M810781. Accessed 30 Sep 2025. Singapore Department of Statistics. Number And Proportion Of Inter-Ethnic And Transnational Marriages Among Citizen Marriages [Data Table]. 2025. https://tablebuilder.singstat.gov.sg/table/TS/M830184. Accessed 2 Sep 2025. Yeung W-JJ, Lu S. Family Dynamics in Cross-National Families With Young Children in Singapore. Journal of Family Issues. 2023; https://doi.org/10.1177/0192513x231156675 Tables Table 1. Data collected during the pregnancy period of the MAMS study Visits (coincide with routine antenatal care) 1 2 3 4 5 6 Gestation (weeks) Week 9-14 Week 12-18 Week 16-24 Week 23-29 Week 28-33 Week 32-38 MOTHER Self-Administered Questionnaires a ✓ ✓ ✓ ✓ ✓ ✓ Actigraphy ✓ ✓ Buccal sample b ✓ Blood sample c ✓ a Self-administered questionnaires include Behavior Rating Inventory of Executive Function - Adult Version BRIEF-A, Big Five Inventory (BFI), Breastfeeding Questionnaire (Pregnancy), Childhood Trauma Questionnaire (CTQ), Demographic & Health Questionnaire (Pregnancy), Dysfunctional Beliefs and Attitudes about Sleep (DBAS), Edinburgh Postnatal Depression Scale (EPDS), Experience in Close Relationships (ECR), Family Interview for Genetic Studies (FIGS), General Health Questionnaire, items from the Quality of Marriage Index, Marital Strain Scale, and McGill Assessment of Relationship Commitment, Lifestyle & Health Questionnaire, Locus Of Control, Loneliness Scale, McMaster Family Assessment Device (FAD) – Retrospective, Morning Eveningness Questionnaire (MEQ), Multidimensional Scale Of Perceived Social Support, Pain Catastrophizing Scale (PCS), Parental Bonding Instrument (PBI), PCL-5, Perceived Socioeconomic Status, Perceived Stress Scale, Pittsburgh Sleep Quality Index (PSQI), Pregnancy Experience, Pregnancy-related Anxiety Scale (PrAS), Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q-SF), Reconstructed Depressive Experiences Questionnaire, Rosenberg Self-Esteem Scale, Standardised Assessment of Personality – Abbreviated Scale, State-Trait Anxiety Inventory (STAI), Subjective Well-being Questionnaire. b Buccal collection may take place in the postnatal phase if it was not collected during pregnancy. c Blood samples consist of both fasting and non-fasting blood collected during routine obstetrics visit. Gestation at collection will be accounted for during analysis. Table 2. Data collected from mothers and children in the postnatal period of the MAMS and MAMS-CO study Visits 1 2 3 4 5 6 7 Age of child Month Month Month Month Month Month Month 1 3 6 12 18 24 36 MOTHER Self-administered questionnaires a ✓ ✓ ✓ ✓ ✓ ✓ ✓ Saliva collection ✓ Parent-child Interaction P CHILD Actigraphy P ✓ ✓ P Buccal sample collection P MRI: Head Scan ✓ P EEG (Resting, Synchrony, Auditory Oddball, Visual Expectation, Attention-Shifting b , Flanker b , Hide & Seek b ) ✓ ✓ ✓ ✓ ✓ ✓ Eye-tracking (Attention-Shifting) ✓ ✓ ✓ Other lab-based tasks (Elephant Task, Spin-the-Pots, Head-Toes-Knees-Shoulders, 8 Boxes Fruits, Glitter Box) ✓ ✓ Preschool Language Scales (PLS-5) ✓ ✓ Bayley Scales of Infant and Toddler Development, Fourth Edition (Bayley-4) ✓ ✓ Language Environment Analysis (LENA) ✓ ✓ SCORing Atopic Dermatitis (SCORAD) ✓ ✓ ✓ Skin Prick Test ✓ ✓ Anthropometry c ✓ ✓ P ✓ ✓ ✓ ✓ Saliva collection ✓ a Self-administered questionnaires include Ages & Stages Questionnaire, Beck Depression Inventory II (BDI-II), Behavior Rating Inventory of Executive Function - Adult Version BRIEF-A, Behavior Rating Inventory of Executive Function - Preschool Version BRIEF-P, Big Five Inventory (BFI), Breastfeeding Questionnaire (Postnatal), Brief Infant Sleep Questionnaire (BISQ), Childhood Trauma Questionnaire (CTQ), COVID19-related Questionnaire, Demographic & Health Questionnaire, Dysfunctional Beliefs about Sleep (DBAS), Early Childhood Behavior Questionnaire – Short Form (ECBQ-Short), Edinburgh Postnatal Depression Scale (EPDS), Experience in Close Relationships (ECR), Family Interview for Genetic Studies (FIGS), General Paediatric Health Questionnaire, General Health Questionnaire, Gut Microbiome Sampling Questionnaire, items from the Quality of Marriage Index, Marital Strain Scale, and McGill Assessment of Relationship Commitment, Home & Caregiver Questionnaire (HCQ), Infant Behavior Questionnaire - Revised (IBQ-R) Short Form, Infant Care Questionnaire, Infant Discipline, Locus Of Control, Loneliness Scale, McMaster Family Assessment Device (FAD) – Retrospective, Morning Eveningness Questionnaire (MEQ), Multidimensional Scale Of Perceived Social Support, Pain Questionnaire, Parental Bonding Instrument (PBI), Parenting Sense of Competence Scale, Parenting Stress Index - Short Form, Perceived Socioeconomic Status, PCL-5, Perceived Stress Scale, Pittsburgh Sleep Quality Index, Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q-SF), Reconstructed Depressive Experiences Questionnaire, Rosenberg Self-Esteem Scale, Standardised Assessment of Personality – Abbreviated Scale, State-Trait Anxiety Inventory (STAI), Stim-Q, Strengths and Difficulties Questionnaire, Subjective Well-being Questionnaire. b Conducted with eye-tracking. In the event where child refuses to wear the EEG electrodes hat, task will be conducted without EEG. c Measurement of length, weight, and head circumference. Table 3. Data collected from fathers in the MAMS-CO study Visits 0 1 2 3 4 5 6 7 Age of child Enrol a Month Month Month Month Month Month Month 1 3 6 12 18 24 36 FATHER Self-administered questionnaires b ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ Buccal sample collection ✓ a Fathers were welcome to join the sub-study at any time from pregnancy to postnatal phase. b Self-administered questionnaires include Ages & Stages Questionnaire, Beck Depression Inventory II (BDI-II), Behavior Rating Inventory of Executive Function - Adult Version BRIEF-A, Behavior Rating Inventory of Executive Function - Preschool Version BRIEF-P, Big Five Inventory (BFI), Breastfeeding Questionnaire (Postnatal), Brief Infant Sleep Questionnaire (BISQ), Childhood Trauma Questionnaire (CTQ), COVID19-related Questionnaire, Demographic & Health Questionnaire, Dysfunctional Beliefs about Sleep (DBAS), Early Childhood Behavior Questionnaire – Short Form (ECBQ-Short), Edinburgh Postnatal Depression Scale (EPDS), Experience in Close Relationships (ECR), Family Interview for Genetic Studies (FIGS), General Paediatric Health Questionnaire, General Health Questionnaire, Gut Microbiome Sampling Questionnaire, items from the Quality of Marriage Index, Marital Strain Scale, and McGill Assessment of Relationship Commitment, Home & Caregiver Questionnaire (HCQ), Infant Behavior Questionnaire - Revised (IBQ-R) Short Form, Infant Care Questionnaire, Infant Discipline, Locus Of Control, Loneliness Scale, McMaster Family Assessment Device (FAD) – Retrospective, Morning Eveningness Questionnaire (MEQ), Multidimensional Scale Of Perceived Social Support, Pain Questionnaire, Parental Bonding Instrument (PBI), Parenting Sense of Competence Scale, Parenting Stress Index - Short Form, Perceived Socioeconomic Status, PCL-5, Perceived Stress Scale, Pittsburgh Sleep Quality Index, Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q-SF), Reconstructed Depressive Experiences Questionnaire, Rosenberg Self-Esteem Scale, Standardised Assessment of Personality – Abbreviated Scale, State-Trait Anxiety Inventory (STAI), Stim-Q, Strengths and Difficulties Questionnaire, Subjective Well-being Questionnaire. Table 4. Demographic characteristics of MAMS mothers All MAMS ( N = 1419) MAMS-CO ( n = 227) Not in MAMS-CO ( n = 1192) Standardized Mean Differences (SMDs) Age at recruitment [Mean (SD)] 30.8 (3.6) 31.3 (3.3) 30.7 (3.6) 0.17 Ethnicity 0.32 Chinese 602 (42.4%) 126 (55.5%) 476 (39.9%) Malay 588 (41.4%) 71 (31.3%) 517 (43.4%) Indian 155 (10.9%) 21 (9.3%) 134 (11.2%) Other a 74 (5.2%) 9 (4.0%) 65 (5.5%) Born in Singapore 0.20 Singapore-born with Singapore-born partner 869 (61.2%) 136 (59.9%) 733 (61.5%) Singapore-born with foreign-born partner 79 (5.6%) 21 (9.3%) 58 (4.9%) Foreign-born with Singapore-born partner 116 (8.2%) 24 (10.6%) 92 (7.7%) Foreign-born with foreign-born partner 223 (15.7%) 44 (19.4%) 179 (15.0%) Missing 132 (9.3%) 2 (0.9%) 130 (10.9%) Education 0.21 University and above 812 (57.2%) 158 (69.6%) 654 (54.9%) Pre-tertiary 386 (27.2%) 50 (22.0%) 336 (28.2%) Secondary and below 98 (6.9%) 17 (7.5%) 81 (6.8%) Missing 123 (8.7%) 2 (0.9%) 121 (10.2%) Gestational diabetes mellitus (GDM) b 0.02 Yes 263 (18.5%) 45 (19.8%) 218 (18.3%) No 977 (68.9%) 174 (76.7%) 803 (67.4%) Pregnancy loss before time for routine OGTT 30 (2.1%) 0 (0.0%) 30 (2.5%) Records unavailable due to change in healthcare provider 18 (1.3%) 4 (1.8%) 14 (1.2%) Pre-existing diabetes/ newly diagnosed in pregnancy 14 (1.0%) 2 (0.9%) 12 (1.0%) Lost to follow-up before time for routine OGTT 12 (0.9%) 0 (0.0%) 12 (1.0%) Missing c 105 (7.4%) 2 (0.9%) 103 (8.6%) Sex of child N = 1251 n = 227 n = 1024 0.01 Male 665 (53.2%) 122 (53.7%) 543 (53.0%) Female 555 (44.4%) 104 (45.8%) 451 (44.0%) Missing c 31 (2.5%) 1 (0.4%) 30 (2.9%) Note. SMDs were calculated using the tableone package in R, excluding missing data categories. a Includes Filipino, Caucasian, Hispanic and other ethnicities. b SMD calculated with GDM categories (yes or no) only. c Missing as participants dropped out and did not consent to continued access of data after dropping out. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 25 Apr, 2026 Reviewers invited by journal 01 Apr, 2026 Editor invited by journal 30 Mar, 2026 Editor assigned by journal 25 Mar, 2026 First submitted to journal 23 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Numbers are accurate as of 1 July 2025. There are 1055 active subjects still in the study as of 1 July 2025. Asterisks (*) indicate timepoints for which data collection is still ongoing. MAMS-CO refers to the sub-study with more comprehensive assessments of the children and inclusion of paternal data. O\u0026amp;G = Obstetrics and Gynaecology. SAQ = Self-Administered Questionnaire.\u003c/p\u003e","description":"","filename":"Eur.J.EpidemiolMAMSProfileFig1Mar2026.png","url":"https://assets-eu.researchsquare.com/files/rs-9206507/v1/1960fba2ec04fb8c4fc1e68b.png"},{"id":106403929,"identity":"12aea18c-8954-43e7-a725-bf9849d38e96","added_by":"auto","created_at":"2026-04-08 09:15:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2571750,"visible":true,"origin":"","legend":"\u003cp\u003eEdinburgh Postnatal Depression Scale (EPDS) scores across pregnancy visits. Each point represents a single observation. Points are jittered horizontally to avoid overplotting. Dotted lines represent the EPDS cut-off score of 10 indicating high, subclinical depression. Time periods highlighted in red indicate periods of tight COVID-19 restrictions. Solid lines indicate smoothed time trends for EPDS scores at each pregnancy timepoint. Shaded grey area indicates 95% confidence intervals. The LOESS span, which controls the degree of smoothing, was selected using the loess.as() function from the fANCOVA package in R. Both bias-corrected Akaike Information Criteria (AICC) and generalized cross-validation (GCV) suggested an optimal span of 0.90.\u003c/p\u003e","description":"","filename":"Eur.J.EpidemiolMAMSProfileFig2smallMar2026.png","url":"https://assets-eu.researchsquare.com/files/rs-9206507/v1/eed806a99c9fbaa6653db991.png"},{"id":106405868,"identity":"b8eaa6b5-4f98-491a-a6c9-cb6abc7c2dd8","added_by":"auto","created_at":"2026-04-08 09:28:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3438801,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9206507/v1/5344102b-8006-4625-9108-463525848144.pdf"}],"financialInterests":"","formattedTitle":"Cohort Profile: Mapping Antenatal Maternal Stress (MAMS)","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eDepression, anxiety, and persistently elevated psychological distress during pregnancy are associated with detrimental outcomes in both mothers and their offspring. Mothers with poor prenatal mental health experience impairments in parenting and psychosocial functions [1, 2]. Notably, a comprehensive economic research revealed that 72% of healthcare costs related to poor maternal mental health are incurred by the affected children [3]. These children are at heightened risk for cognitive, emotional, and social development difficulties compared to their peers [4-9]. Neuroimaging studies have further shown that elevated prenatal maternal mental health problems are linked to variations in neural circuits and brain structures in neonates [10-12], similar to those observed in adults with depression [13] and anxiety [14]. Importantly, maternal symptoms of depression and anxiety predict a significantly increased risk of psychopathology in the offspring [15-17].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDespite compelling evidence for the importance of maternal emotional well-being during pregnancy, there remains a critical gap in the availability of clinical predictive models to identify women at risk for poor perinatal mental health. This gap limits opportunities for early detection and intervention during pregnancy. While a prior episode of major depression is a well-established predictor [18], it accounts for only a small percentage of women who subsequently develop clinical or high levels of perinatal depression. Similarly, early life adversity (e.g., childhood maltreatment or poor parental care) [19], low socio-economic status [20], and poor social support [21], have been associated with an increased risk for perinatal mood and anxiety disorders. There is also evidence of familial transmission, as women with a family history of depression are more likely to experience poor perinatal mental health, suggesting a genetic component to this risk [18, 22]. Preliminary research suggests that genetic influences interact with developmental history and psychosocial factors to determine the risk for antenatal depression [23]. Far less is known about the etiology of maternal antenatal anxiety, which in turn increases the risk for postpartum depression. Emerging findings indicate that maternal genetic variation may contribute to marked individual differences in the onset and trajectory of anxiety and depression in pregnancy [24-26]. Although recent genome-wide studies have identified shared genetic loci for depression and anxiety [27], much of this work has focused on the serotonergic systems [28] and post-partum symptoms [29, 30], despite growing recognition that risk pathways often begin during pregnancy [31], or even before conception [32].\u003c/p\u003e\n\u003cp\u003eMore importantly, mental health is not merely the absence of psychopathology [33]. Mental health lies on a continuum, with positive maternal mental health on the opposite end of the spectrum. Positive maternal mental health has been shown to benefit child development, especially in domains of language acquisition and social communications, independent of maternal depressive or anxiety symptoms [34]. Yet, there is a paucity of research on factors that predict positive maternal mental health, despite its implications for intergenerational well-being and public health. Understanding these protective factors may be critical to promoting resilience in both mothers and children, and advancing targeted preventive strategies at the population level.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Mapping Antenatal Maternal Stress (MAMS) study is a prospective, longitudinal birth cohort study that aims to comprehensively investigate the determinants and consequences of prenatal maternal mental health among women in Singapore. First, we aim to identify the key psychosocial and biological factors that underlie individual differences in maternal mental health during pregnancy, employing predictive algorithms to model risk and resilience profiles. Second, we seek to differentiate the predictors of maternal depressive and anxiety symptoms from those associated with positive mental health, to provide a multidimensional understanding of the full spectrum of maternal emotional well-being. Third, we will examine perinatal maternal mental health in relation to child developmental outcomes, using standardized clinical measures with predictive validity for children's cognitive, emotional, and social outcomes. Finally, we will investigate the contribution of genotypic variation associated with perinatal maternal mental health using a genome-wide analysis of single-nucleotide polymorphisms (SNPs). Specifically, we will compute polygenic risk scores (PRS) for psychiatric and behavioural traits to examine how genetic susceptibility may moderate the association between key psychosocial factors and maternal mental health trajectories, and in turn, how these combined influences affect child outcomes such as executive functions and emotion regulation. Just as important is how psychosocial factors could moderate the genetic risk of poor mental health. We hypothesize that positive maternal mental health will be independently predicted by protective factors such as high emotional support, resilience, and adaptive coping strategies, beyond the absence of psychopathology. We also hypothesize that the PRS for psychiatric vulnerability (e.g., depression, anxiety) will moderate the associations between psychosocial risk factors and maternal mental health, such that individuals with higher genetic susceptibility will exhibit greater emotional reactivity to psychosocial stressors. Lastly, we hypothesize that both maternal mental health and genetic susceptibility will jointly influence child developmental outcomes, with poor maternal mood and higher PRS predicting poorer child developmental outcomes, such as cognitive, and executive functions.\u0026nbsp;\u003c/p\u003e"},{"header":"STUDY DESIGN AND METHODOLOGY","content":"\u003cp\u003e\u003cstrong\u003eStudy population and recruitment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe MAMS study recruited 1419 pregnant women aged 21 to 40 years from the National University Hospital, Singapore, between September 2019 and November 2022. Eligible participants needed to be below 24 gestational weeks based on dating by first-trimester ultrasonography, proficient in English, able to respond to questionnaires, intend to stay in Singapore for the next 5 years, have access to a smartphone or digital device, and be willing to participate and provide written consent. Women carrying multiple gestations, those pregnant via assisted reproduction, with pre-existing or a history of psychotic depression, schizophrenia, and bipolar disorders, currently on oral or intravenous steroids and/or thyroid medication, with a history of thyroid disease, or currently enrolled in any interventional randomized controlled trials, were excluded from the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe approached 8303 women, of whom 6794 were either not suitable or unwilling to participate. 1509 were interested and potentially eligible, of which 90 were subsequently no longer interested in participating in the study. A total of 1419 pregnant women were ultimately recruited into the study. Figure 1 shows the flowchart of participants' progress through the study. Of these 1419 pregnant women, 88.2% (n = 1251) delivered their babies, while 11.8% (n = 168) were lost during pregnancy due to multiple reasons (Figure 1). To date, 1055 mothers and index children have been followed through 24 months, with 36-month follow-up underway (Figure 1). From 13 September 2021, participants in the MAMS study were also asked whether they were interested in a more comprehensive set of assessments to characterize children's early neurodevelopment and parent-child interactions. Their spouses were also invited to participate in the MAMS-Child Outcomes (MAMS-CO) sub-study. 227 (16.0%) mother-child pairs and 133 (9.4%) fathers enrolled into MAMS-CO. Child assessments include brain MRI scans, electroencephalography and eye-tracking tasks, developmental and cognitive assessments, language evaluations, as well as anthropometric and skin-fold thickness measurements. Biological samples, including buccal swabs and saliva, are collected from both parents and the child. Mothers participate in cognitive, socio-emotional, and parenting tasks, while both parents complete self-administered questionnaires across this sub-study period. All participants provided written informed consent. Ethical approval was obtained from the National Healthcare Group Domain Specific Review Board (reference 2018/00967 and 2021/00189). This study has been retrospectively registered at ClinicalTrials.gov (MAMS: NCT07432217; MAMS-CO: NCT07432243) on 25 February 2026.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOverview\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were collected at multiple time points across the prenatal and postnatal periods. During pregnancy, mothers completed questionnaires across 4-6 gestational windows depending on gestation at enrolment (refer to Table 1). In the postnatal period, participants provided self-reported data at 7 time points, specifically when the child was 1, 3, 6, 12, 18, 24, and 36 months old, which were also aligned with scheduled laboratory assessments where applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collected during pregnancy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 4-6 time points during pregnancy consisted of an initial visit for obtaining informed consent and eligibility screening. Table 1 specifies the data collected during pregnancy. Upon enrolment, mothers provided information on their demographic background and general health status. Mothers were asked to wear an Oura ring for a one-week period during 9-14 weeks’ gestation and again during16-29 weeks’ gestation to monitor sleep patterns while completing a sleep diary. A single blood sample was obtained from pregnant mothers, with clear documentation of gestational age at sampling. Blood samples were used to assess allostatic load and associated biomarkers, including inflammatory chemokines.\u003c/p\u003e\n\u003cp\u003eMaternal psychological well-being was assessed using validated questionnaires, including the Edinburgh Postnatal Depression Scale, State-Trait Anxiety Inventory, Perceived Stress Scale, Loneliness Scale, Reconstructed Depressive Experiences Questionnaire, and Pregnancy-related Anxiety Scale. Family psychiatric history was assessed via the Family Interview for Genetic Studies. Maternal childhood experiences were evaluated using the Childhood Trauma Questionnaire, a retrospective version of the McMaster Family Assessment Device, the Parental Bonding Instrument, and the PTSD Checklist for DSM-5 (PCL-5).\u003c/p\u003e\n\u003cp\u003eSocial and interpersonal factors were assessed using the Multidimensional Scale of Perceived Social Support, the Experience in Close Relationship, as well as items on marital quality from the Quality of Marriage Index, Marital Strain Scale, and McGill Assessment of Relationship Commitment. Maternal personality traits were assessed using the Big Five Inventory, the Rosenberg Self-Esteem Scale, and the Standardized Assessment of Personality – Abbreviated Scale. Executive functioning was assessed via the Behaviour Rating Inventory of Executive Function – Adult Version.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAdditionally, mothers completed questionnaires related to sleep beliefs and behaviours, including the Dysfunctional Beliefs and Attitudes about Sleep, Morning-Eveningness Questionnaire, and the Pittsburgh Sleep Quality Index. Pregnancy-related experiences, lifestyle habits, and quality of life were also assessed, including the Quality of Life Enjoyment and Satisfaction, and the Pain Catastrophizing Scale to capture perceptions of pain.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collected at delivery\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter delivery, detailed information on antenatal, peripartum, and postpartum events was obtained from antenatal, obstetric, and neonatal hospital medical records. These included routine antenatal clinical and laboratory data, such as maternal weight, blood pressure, urine dipstick, and results from the 3-timepoint 75g oral glucose tolerance test (OGTT). Details on antenatal conditions, and complications such as gestational diabetes mellitus (GDM), hypertensive disorders of pregnancy, and antepartum haemorrhage, were captured. Peripartum events, e.g., mode of delivery and maternity complications, and routinely recorded fetal and neonatal data, including fetal ultrasound parameters, infant sex, birth weight, head circumference, and neonatal complications, were also extracted from medical records.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collected during postnatal period\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 lists the data collected during the postnatal period for mothers and children. Child executive functional and behavioural traits were reported by parents using a suite of internationally validated instruments, including the Behavioural Rating Inventory of Executive Function – Preschool version, Early Childhood Behavioural Questionnaire – Short Form, Infant Behaviour Questionnaire – Revised, and the Strengths and Difficulties Questionnaire. Cognitive, motor, language, socio-emotional, and adaptive behavioural development were assessed using the Bayley Scales of Infant and Toddler Development (4\u003csup\u003eth\u003c/sup\u003e Edition; Bayley-4). Sleep patterns and quality were assessed using maternal reports using the Brief Infant Sleep Questionnaire – Revised Short Form. Child sleep quality was also objectively measured using the Philips Respironics Actiwatch 2, worn on the ankle at ages 6, 12, and 24 months. Mothers also reported additional data, including infant feeding practices, particularly breastfeeding, and the child’s physical health status, such as respiratory symptoms, skin conditions, and gastrointestinal issues.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConcurrently, mothers continued to provide self-reported data across the postnatal period. Their psychological well-being was monitored using the same validated questionnaires administered during pregnancy, excluding the Pregnancy-related Anxiety Scale. Postnatal sleep quality and chronotype were also assessed using the Pittsburgh Sleep Quality Index and the Morning-Eveningness Questionnaire respectively. Parenting experiences, specifically perceived parenting stress, self-efficacy, and satisfaction, were captured using the Parenting Stress Index – Short Form, and the Parental Sense of Competence. Mothers also continued to complete questionnaires related to their general health, lifestyle behaviors, marital quality, social support, and quality of life, as previously described.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor mothers who consented to their child’s participation in the sub-study, MAMS-CO, with more intensive assessments during the child’s first three years of life, assessments were conducted at the same timepoints as those for the broader participant group. In addition to standard questionnaires, these mothers completed supplementary surveys regarding their child’s screen time and childcare arrangements. Language exposure and development were assessed using an in-house questionnaire, as well as the Stim-Q (Infant and Toddler versions), and the Preschool Language Scale – Fifth Edition. Digital audio recordings of the child’s natural environment to capture language input and interaction patterns were collected using the Language Environment Analysis (LENA) recorder at ages 1 and 3 years. Infant development was evaluated using the Ages and Stages Questionnaire and the cognitive module of Bayley-4.\u003c/p\u003e\n\u003cp\u003eAdditionally, child anthropometry and neurophysiological assessments were performed during laboratory-based visits at 1, 3, 6, 12, 18, 24, and 36 months. Structural MRI, diffusion-weighted imaging, and resting-state functional MRI scans were performed at 1 and 6 months of age. During 1-36 months, children also participated in a series of age-appropriate eye-tracking tasks, resting-state and task-based electroencephalography (EEG), and event-related potentials (ERPs) to examine auditory recognition, attention, and executive functioning. Dual mother-child EEG recordings were obtained at 6 and 18 months. EEG was collected using the Electrical Geodesics, Inc. (EGI) systems with 128-electrode nets. Maternal sensitivity was assessed through a video recording of the mother-child interaction at 6 months. Additionally, skin assessments were performed to evaluate the extent and severity of atopic dermatitis using the SCORing Atopic Dermatitis (SCORAD) index, and to determine food sensitization or allergy through skin prick tests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Table 3 presents data collected from fathers during pregnancy and the postnatal period. Fathers who consented to participate completed the same questionnaires as mothers to examine their mental health, experiences of childhood adversity, psychosocial factors, and perceptions of their child’s socioemotional, cognitive, and behavioral development.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiosamples collected\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBuccal samples were collected from mothers, fathers, and children enrolled in the study, either through a home collection kit or during on-site visits. Additionally, buccal samples were obtained from children at 2 years of age for telomere length analysis. Saliva samples were also collected from both mothers and children during the postnatal 3-month visit to facilitate biochemical markers analysis.\u0026nbsp;\u003c/p\u003e"},{"header":"KEY FINDINGS AND PUBLICATIONS ","content":"\u003cp\u003eThe baseline demographic characteristics are listed in Table 4. Out of the 1419 women recruited into MAMS, 602 (42.4%) were Chinese, 588 (41.4%) were Malays, 155 (10.9%) were Indians, while the remaining 74 (5.2%) were of different ethnicities (see Table 4 for more details). A majority (66.8%, n = 948) were born in Singapore, of whom 79 (5.6%) had foreign-born partners. Conversely, 116 (8.2%) foreign-born women had Singapore-born partners. The mean age of women at recruitment was 30.8 years (range 21.5 – 40.0 years; SD 3.6), and 812 (57.2%) participants had attained at least a tertiary level of education.\u0026nbsp;During pregnancy, 263 (18.5%) women were diagnosed with gestational diabetes mellitus (GDM).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBaseline characteristics of participants enrolled in MAMS-CO were compared with the remainder of the MAMS cohort (represented as “Not in MAMS-CO” in Table 4). Standardized mean differences (SMDs) were calculated to assess the magnitude of group differences independent of sample size and accounting for unequal group sizes [35, 36]. SMDs of less than 0.1 were interpreted as negligible differences, whilst 0.25 represented the threshold for potentially meaningful differences [37-39]. SMDs between 0.1 and 0.25 were considered indicative of small differences. There were modest differences between mothers who enrolled in MAMS-CO (n = 227) and those who did not (see Table 4 for details). The most notable difference was in ethnicity, with MAMS-CO comprising a higher proportion of Chinese women (55.5%, n = 126) and fewer Malay women (31.3%, n = 71) compared with those not enrolled in MAMS-CO (Chinese: 39.9%, n = 476; Malay: 43.4%, n = 517). Smaller differences were observed in age at recruitment, birthplace, and educational attainment. Mothers enrolled in MAMS-CO were slightly older (mean = 31.3 years; SD 3.3) than those in MAMS only (30.7 years; SD 3.6). Additionally, a higher proportion of Singapore-born women had foreign-born partners in MAMS-CO (9.3%, n = 21) than in MAMS only (4.9%, n = 58). More women in MAMS-CO attained at least a tertiary level of education (69.6%, n = 158) compared to women who were only in MAMS (54.9%, n = 654). In all other aspects examined, MAMS-CO mothers were comparable to their MAMS-only counterparts.\u003c/p\u003e\n\u003cp\u003eWe examined whether maternal depressive symptom levels differed, given that cohort recruitment occurred during the COVID-19 pandemic, with various lockdown protocols implemented between mid-2020 and 2022. The tightest restrictions occurred from 7 April 2020 to 1 June 2020, with brief recurrences from 16 May 2021 to 13 June 2021 and from 22 July 2021 to 9 August 2021. The time trends of mothers’ Edinburgh Postnatal Depression Scale (EPDS) scores across pregnancy were analysed using local polynomial regression (LOESS).\u0026nbsp;LOESS smoothing showed that maternal depressive symptoms remained relatively stable throughout these lockdown periods (Figure 2). Similarly stable trajectories in levels of depressive symptoms across the perinatal period were also reported in MAMS mothers in Kee et al., as well as in six other international cohorts across three decades [31].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengths and limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe MAMS study was explicitly designed to investigate the determinants and consequences of maternal perinatal mental health, particularly in relation to child developmental outcomes. As such, it undertakes more intensive assessments of executive function during the first 3 years of the child’s life, including EEG and eye-tracking tasks to supplement laboratory-based behavioural measures. The MAMS study provides a rare longitudinal perspective on an understudied period of executive function development [40], particularly in Asian populations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRecruiting fathers into the MAMS-CO sub-study allows MAMS to examine the role of fathers in direct and indirect pathways to maternal well-being and child outcomes. As MAMS-CO commenced recruitment partway through the primary study, some fathers were already in the postnatal phase at enrolment. Consequently, paternal data from the pregnancy phase are comparatively limited. Nevertheless, the inclusion of fathers enables longitudinal investigation of paternal influences beginning around the perinatal period. Dyadic analyses will provide insights into the similarity and accuracy of actual and perceived factors, reciprocal effects between parents, and their relationships with child socioemotional outcomes.\u003c/p\u003e\n\u003cp\u003eSeveral characteristics of the MAMS cohort make it particularly relevant to population trends in Singapore. Firstly, Malays were oversampled, comprising 41.4% of the MAMS cohort; at recruitment in 2019, Malays accounted for 13.4% of the resident population [41]. Among Singapore's ethnic groups, Malays are the largest ethnic minority and have the highest fertility rate [42]. As the proportion of Malays in Singapore is projected to increase despite an overall decline in the national total fertility rate, their overrepresentation in MAMS is especially salient for understanding future population trends.\u003c/p\u003e\n\u003cp\u003eIn addition, a proportion of women and/or their partners were foreign-born, reflecting broader demographic patterns in Singapore. In recent decades, both the total number of new Singapore Citizenship and Permanent Residences granted annually has increased by 24.0% from 46,791 in 2010 to 58,030 in 2024 [43]. Concomitantly, the proportion of transnational marriages has increased from 15.1% of citizen marriages in 1984 to 36.6% in 2024 [44]. Consistent with this, the Singapore Longitudinal Early Development Study (SG-LEADS) indicated that 43.1% of families had at least one foreign-born parent [45]. The same study highlighted vulnerabilities particular to families with foreign-born mothers, who may face distinct social and family dynamics [45]. The inclusion of foreign-born women and their partners in MAMS therefore enhances the cohort’s representativeness of contemporary family structures in Singapore.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA limitation of the MAMS study is its relatively modest sample size, particularly for those who opted to continue in the comprehensive sub-study. This may be partially attributed to hesitancy around physical contact during the COVID-19 pandemic.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCollaborations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research team welcomes potential collaborations. Investigators interested in collaborations are encouraged to reach out to the lead principal investigators, Dr. Michelle Z.L Kee ([email protected]) or Associate Professor Shiao-Yng Chan ([email protected]), principal investigators A/Profs Ai Peng Tan ([email protected]) and Evelyn C. Law ([email protected]).\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis work is supported by the Agency for Science, Technology and Research (A*STAR)\u003c/p\u003e\n\u003cp\u003ePrenatal / Early Childhood Grant Call (H22P0M0001) under MJM.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u0026nbsp;\u003c/strong\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eAuthor contributions in alphabetical order:\u003c/p\u003e\n\u003cp\u003eConceptualization and Methodology: Ai Peng Tan, Evelyn C. Law, Michael J. Meaney, Michelle Z.L Kee, Shiao-Yng Chan\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eProject administration: Benjamin Chow, Nurshuhadah Binte Abdullah, Valerie Ng\u003c/p\u003e\n\u003cp\u003eFormal analysis and investigation: Jenell Ong, Michelle Z.L Kee, Santhi Ponmudi\u003c/p\u003e\n\u003cp\u003eWriting – original draft preparation: Jenell Ong, Michelle Z.L Kee, Santhi Ponmudi\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWriting – reviewing and editing: Ai Peng Tan, Cornelia Chee, Evelyn C. Law, Helen Chen, Michael J. Meaney, Michelle Z.L Kee, Shiao-Yng Chan\u003c/p\u003e\n\u003cp\u003eAll authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval:\u0026nbsp;\u003c/strong\u003eEthical approval was obtained from the National Healthcare Group Domain Specific Review Board (reference 2018/00967 and 2021/00189).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate:\u0026nbsp;\u003c/strong\u003eWritten informed consent was provided by all participants.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWeinberg MK, Tronick EZ, Beeghly M, Olson KL, Kernan H, Riley JM. Subsyndromal depressive symptoms and major depression in postpartum women. Am J Orthopsychiatry. 2001; https://doi.org/10.1037/0002-9432.71.1.87\u003c/li\u003e\n\u003cli\u003eDubber S, Reck C, Muller M, Gawlik S. Postpartum bonding: the role of perinatal depression, anxiety and maternal-fetal bonding during pregnancy. 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Positive maternal mental health during pregnancy associated with specific forms of adaptive development in early childhood: Evidence from a longitudinal study. Dev Psychopathol. 2017; https://doi.org/10.1017/S0954579417001249\u003c/li\u003e\n\u003cli\u003eYang D, Dalton JE. A unified approach to measuring the effect size between two groups using SAS. SAS Global Forum 2012. p. 1-6.\u003c/li\u003e\n\u003cli\u003eLaczo RM, Sackett PR, Bobko P, Cortina JM. A comment on sampling error in the standardized mean difference with unequal sample sizes: avoiding potential errors in meta-analytic and primary research. J Appl Psychol. 2005; https://doi.org/10.1037/0021-9010.90.4.758\u003c/li\u003e\n\u003cli\u003eStuart EA, Lee BK, Leacy FP. Prognostic score-based balance measures can be a useful diagnostic for propensity score methods in comparative effectiveness research. J Clin Epidemiol. 2013; https://doi.org/10.1016/j.jclinepi.2013.01.013\u003c/li\u003e\n\u003cli\u003eHripcsak G, Zhang L, Chen Y, et al. Assessing Covariate Balance With Small Sample Sizes. Stat Med. 2025; https://doi.org/10.1002/sim.70212\u003c/li\u003e\n\u003cli\u003eRubin DB. Using Propensity Scores to Help Design Observational Studies: Application to the Tobacco Litigation. Health Services and Outcomes Research Methodology. 2001; https://doi.org/10.1023/a:1020363010465\u003c/li\u003e\n\u003cli\u003eHendry A, Jones EJH, Charman T. Executive function in the first three years of life: Precursors, predictors and patterns. Dev Rev. 2016; https://doi.org/10.1016/j.dr.2016.06.005\u003c/li\u003e\n\u003cli\u003eSingapore Department of Statistics. Singapore Residents By Age Group, Ethnic Group And Sex, At End June [Data Table]. 2024. https://tablebuilder.singstat.gov.sg/table/TS/M810011. Accessed 2 Sep 2025.\u003c/li\u003e\n\u003cli\u003eSingapore Department of Statistics. Population Trends 2024 [Report]. Ministry of Trade and Industry. 2024. https://www.singstat.gov.sg/-/media/files/publications/population/population2024.ashx. Accessed 2 Sep 2025.\u003c/li\u003e\n\u003cli\u003eSingapore Department of Statistics. Number And Profile Of Singapore Citizenships And Permanent Residencies Granted [Data Table]. 2025. https://tablebuilder.singstat.gov.sg/table/TS/M810781. Accessed 30 Sep 2025.\u003c/li\u003e\n\u003cli\u003eSingapore Department of Statistics. Number And Proportion Of Inter-Ethnic And Transnational Marriages Among Citizen Marriages [Data Table]. 2025. https://tablebuilder.singstat.gov.sg/table/TS/M830184. Accessed 2 Sep 2025.\u003c/li\u003e\n\u003cli\u003eYeung W-JJ, Lu S. Family Dynamics in Cross-National Families With Young Children in Singapore. Journal of Family Issues. 2023; https://doi.org/10.1177/0192513x231156675\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Data collected during the pregnancy period of the MAMS study\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVisits\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(coincide with routine antenatal care)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGestation\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(weeks)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeek\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e9-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeek\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e12-18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeek\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e16-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeek\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e23-29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeek\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e28-33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeek\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e32-38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMOTHER\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eSelf-Administered Questionnaires \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eActigraphy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 26px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eBuccal sample \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" style=\"width: 78px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eBlood sample \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" style=\"width: 78px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Self-administered questionnaires include Behavior Rating Inventory of Executive Function - Adult Version BRIEF-A, Big Five Inventory (BFI), Breastfeeding Questionnaire (Pregnancy), Childhood Trauma Questionnaire (CTQ), Demographic \u0026amp; Health Questionnaire (Pregnancy), Dysfunctional Beliefs and Attitudes about Sleep (DBAS), Edinburgh Postnatal Depression Scale (EPDS), Experience in Close Relationships (ECR), Family Interview for Genetic Studies (FIGS), General Health Questionnaire, items from the Quality of Marriage Index, Marital Strain Scale, and McGill Assessment of Relationship Commitment, Lifestyle \u0026amp; Health Questionnaire, Locus Of Control, Loneliness Scale, McMaster Family Assessment Device (FAD) \u0026ndash; Retrospective, Morning Eveningness Questionnaire (MEQ), Multidimensional Scale Of Perceived Social Support, Pain Catastrophizing Scale (PCS), Parental Bonding Instrument (PBI), PCL-5, Perceived Socioeconomic Status, Perceived Stress Scale, Pittsburgh Sleep Quality Index (PSQI), Pregnancy Experience, Pregnancy-related Anxiety Scale (PrAS), Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q-SF), Reconstructed Depressive Experiences Questionnaire, Rosenberg Self-Esteem Scale, Standardised Assessment of Personality \u0026ndash; Abbreviated Scale, State-Trait Anxiety Inventory (STAI), Subjective Well-being Questionnaire.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Buccal collection may take place in the postnatal phase if it was not collected during pregnancy.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec\u003c/sup\u003e Blood samples consist of both fasting and non-fasting blood collected during routine obstetrics visit. Gestation at collection will be accounted for during analysis.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Data collected from mothers and children in the postnatal period of the MAMS and MAMS-CO study\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVisits\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 33px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge of child\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e24\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e36\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMOTHER\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003eSelf-administered questionnaires \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 33px;\"\u003e\n \u003cp\u003eSaliva collection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 33px;\"\u003e\n \u003cp\u003eParent-child Interaction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCHILD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003eActigraphy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003eBuccal sample collection\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"7\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003eMRI: Head Scan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003eEEG (Resting, Synchrony, Auditory Oddball, Visual Expectation, Attention-Shifting \u003csup\u003eb\u003c/sup\u003e, Flanker \u003csup\u003eb\u003c/sup\u003e, Hide \u0026amp; Seek \u003csup\u003eb\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003eEye-tracking (Attention-Shifting)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003eOther lab-based tasks (Elephant Task, Spin-the-Pots, Head-Toes-Knees-Shoulders, 8 Boxes Fruits, Glitter Box)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003ePreschool Language Scales (PLS-5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003eBayley Scales of Infant and Toddler Development, Fourth Edition (Bayley-4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003eLanguage Environment Analysis (LENA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003eSCORing Atopic Dermatitis (SCORAD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003eSkin Prick Test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003eAnthropometry \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003eSaliva collection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Self-administered questionnaires include Ages \u0026amp; Stages Questionnaire, Beck Depression Inventory II (BDI-II), Behavior Rating Inventory of Executive Function - Adult Version BRIEF-A, Behavior Rating Inventory of Executive Function - Preschool Version BRIEF-P, Big Five Inventory (BFI), Breastfeeding Questionnaire (Postnatal), Brief Infant Sleep Questionnaire (BISQ), Childhood Trauma Questionnaire (CTQ), COVID19-related Questionnaire, Demographic \u0026amp; Health Questionnaire, Dysfunctional Beliefs about Sleep (DBAS), Early Childhood Behavior Questionnaire \u0026ndash; Short Form (ECBQ-Short), Edinburgh Postnatal Depression Scale (EPDS), Experience in Close Relationships (ECR), Family Interview for Genetic Studies (FIGS), General Paediatric Health Questionnaire, General Health Questionnaire, Gut Microbiome Sampling Questionnaire, items from the Quality of Marriage Index, Marital Strain Scale, and McGill Assessment of Relationship Commitment, Home \u0026amp; Caregiver Questionnaire (HCQ), Infant Behavior Questionnaire - Revised (IBQ-R) Short Form, Infant Care Questionnaire, Infant Discipline, Locus Of Control, Loneliness Scale, McMaster Family Assessment Device (FAD) \u0026ndash; Retrospective, Morning Eveningness Questionnaire (MEQ), Multidimensional Scale Of Perceived Social Support, Pain Questionnaire, Parental Bonding Instrument (PBI), Parenting Sense of Competence Scale, Parenting Stress Index - Short Form, Perceived Socioeconomic Status, PCL-5, Perceived Stress Scale, Pittsburgh Sleep Quality Index, Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q-SF), Reconstructed Depressive Experiences Questionnaire, Rosenberg Self-Esteem Scale, Standardised Assessment of Personality \u0026ndash; Abbreviated Scale, State-Trait Anxiety Inventory (STAI), Stim-Q, Strengths and Difficulties Questionnaire, Subjective Well-being Questionnaire.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Conducted with eye-tracking. In the event where child refuses to wear the EEG electrodes hat, task will be conducted without EEG.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec\u003c/sup\u003e Measurement of length, weight, and head circumference.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Data collected from fathers in the MAMS-CO study\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVisits\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge of child\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnrol \u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e24\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e36\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFATHER\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eSelf-administered questionnaires \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eBuccal sample collection\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"8\" style=\"width: 79px;\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u0026nbsp;\u003c/sup\u003eFathers were welcome to join the sub-study at any time from pregnancy to postnatal phase.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Self-administered questionnaires include Ages \u0026amp; Stages Questionnaire, Beck Depression Inventory II (BDI-II), Behavior Rating Inventory of Executive Function - Adult Version BRIEF-A, Behavior Rating Inventory of Executive Function - Preschool Version BRIEF-P, Big Five Inventory (BFI), Breastfeeding Questionnaire (Postnatal), Brief Infant Sleep Questionnaire (BISQ), Childhood Trauma Questionnaire (CTQ), COVID19-related Questionnaire, Demographic \u0026amp; Health Questionnaire, Dysfunctional Beliefs about Sleep (DBAS), Early Childhood Behavior Questionnaire \u0026ndash; Short Form (ECBQ-Short), Edinburgh Postnatal Depression Scale (EPDS), Experience in Close Relationships (ECR), Family Interview for Genetic Studies (FIGS), General Paediatric Health Questionnaire, General Health Questionnaire, Gut Microbiome Sampling Questionnaire, items from the Quality of Marriage Index, Marital Strain Scale, and McGill Assessment of Relationship Commitment, Home \u0026amp; Caregiver Questionnaire (HCQ), Infant Behavior Questionnaire - Revised (IBQ-R) Short Form, Infant Care Questionnaire, Infant Discipline, Locus Of Control, Loneliness Scale, McMaster Family Assessment Device (FAD) \u0026ndash; Retrospective, Morning Eveningness Questionnaire (MEQ), Multidimensional Scale Of Perceived Social Support, Pain Questionnaire, Parental Bonding Instrument (PBI), Parenting Sense of Competence Scale, Parenting Stress Index - Short Form, Perceived Socioeconomic Status, PCL-5, Perceived Stress Scale, Pittsburgh Sleep Quality Index, Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q-SF), Reconstructed Depressive Experiences Questionnaire, Rosenberg Self-Esteem Scale, Standardised Assessment of Personality \u0026ndash; Abbreviated Scale, State-Trait Anxiety Inventory (STAI), Stim-Q, Strengths and Difficulties Questionnaire, Subjective Well-being Questionnaire.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u003c/strong\u003e Demographic characteristics of MAMS mothers\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll MAMS\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003cem\u003eN\u0026nbsp;\u003c/em\u003e= 1419)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMAMS-CO\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003cem\u003en\u003c/em\u003e = 227)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNot in MAMS-CO\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003cem\u003en\u003c/em\u003e = 1192)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandardized Mean Differences (SMDs)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003eAge at recruitment [Mean (SD)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e30.8 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e31.3 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e30.7 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003eEthnicity\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Chinese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e602 (42.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e126 (55.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e476 (39.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Malay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e588 (41.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e71 (31.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e517 (43.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Indian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e155 (10.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e21 (9.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e134 (11.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Other \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e74 (5.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e9 (4.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e65 (5.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003eBorn in Singapore\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Singapore-born with Singapore-born partner\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e869 (61.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e136 (59.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e733 (61.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Singapore-born with foreign-born partner\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e79 (5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e21 (9.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e58 (4.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Foreign-born with Singapore-born partner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e116 (8.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e24 (10.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e92 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Foreign-born with foreign-born partner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e223 (15.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e44 (19.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e179 (15.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Missing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e132 (9.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e2 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e130 (10.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003eEducation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;University and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e812 (57.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e158 (69.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e654 (54.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Pre-tertiary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e386 (27.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e50 (22.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e336 (28.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Secondary and below\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e98 (6.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e17 (7.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e81 (6.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Missing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e123 (8.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e2 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e121 (10.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003eGestational diabetes mellitus (GDM) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e263 (18.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e45 (19.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e218 (18.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e977 (68.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e174 (76.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e803 (67.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Pregnancy loss before time for routine \u0026nbsp;OGTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e30 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e30 (2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Records unavailable due to change in healthcare provider\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e18 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e4 (1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e14 (1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Pre-existing diabetes/ newly diagnosed in pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e14 (1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e2 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e12 (1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Lost to follow-up before time for routine OGTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e12 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e12 (1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Missing \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e105 (7.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e2 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e103 (8.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003eSex of child\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cem\u003eN\u003c/em\u003e = 1251\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cem\u003en\u003c/em\u003e = 227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cem\u003en\u0026nbsp;\u003c/em\u003e= 1024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e665 (53.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e122 (53.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e543 (53.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e555 (44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e104 (45.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e451 (44.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Missing \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e31 (2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e1 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e30 (2.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote.\u003c/em\u003e SMDs were calculated using the \u003cem\u003etableone\u003c/em\u003e package in R, excluding missing data categories.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u0026nbsp;\u003c/sup\u003eIncludes Filipino, Caucasian, Hispanic and other ethnicities.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e SMD calculated with GDM categories (yes or no) only.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec\u003c/sup\u003e Missing as participants dropped out and did not consent to continued access of data after dropping out.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-epidemiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejep","sideBox":"Learn more about [European Journal of Epidemiology](https://www.springer.com/journal/10654)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ejep/default.aspx","title":"European Journal of Epidemiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Pregnancy, Maternal Stress, Mental Health, Cohort Studies, Child Development","lastPublishedDoi":"10.21203/rs.3.rs-9206507/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9206507/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The Mapping Antenatal Maternal Stress (MAMS) study is a prospective, longitudinal birth cohort designed to investigate factors influencing maternal antenatal emotional well-being and develop a predictive model for this state. The study also aims to explore genetic and environmental contributions of maternal antenatal emotional well-being and how maternal mental health impacts child outcomes, including executive functions, socio-emotional, and neurocognitive development. The MAMS study recruited 1419 women aged 21–40 years in early to mid-pregnancy between September 2019 and November 2022 from the National University Hospital of Singapore, resulting in 1258 children born to the cohort. The participants were followed up for 4-6 visits during pregnancy and 7 visits postnatally until the child reached three years old. Data collection involved standardized questionnaires and the collection of biological samples (blood, buccal swabs, saliva) at multiple time points. A subset of 227 MAMS children underwent intensive laboratory-based assessments of executive functions and brain development, including electroencephalography (EEG), magnetic resonance imaging (MRI), and eye-tracking during the first three years of life. Paternal assessments and reports on child behavioral outcomes were also incorporated into this sub-study.","manuscriptTitle":"Cohort Profile: Mapping Antenatal Maternal Stress (MAMS)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-07 16:43:27","doi":"10.21203/rs.3.rs-9206507/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2026-04-25T12:06:37+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-02T01:22:59+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"European Journal of Epidemiology","date":"2026-03-30T07:16:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-25T08:27:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Epidemiology","date":"2026-03-24T00:13:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-epidemiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejep","sideBox":"Learn more about [European Journal of Epidemiology](https://www.springer.com/journal/10654)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ejep/default.aspx","title":"European Journal of Epidemiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"3c8002e3-7406-4cfd-a91c-5fb78c8b2a65","owner":[],"postedDate":"April 7th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-07T16:43:27+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-07 16:43:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9206507","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9206507","identity":"rs-9206507","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}