Intrauterine Exposures and Maternal Health Status during Pregnancy in Relation to Later Child Health: A Review of Pregnancy Cohort Studies in Europe

Six decades of longitudinal health knowledge production: a systematic review on Nordic birth cohort studies

This systematic review (a) identifies birth cohort studies (BCSs) established in the Nordic countries, (b) describes their basic characteristics, and (c) explores how these characteristics have evolved over time, discussing their implications to knowledge production. To identify Nordic BCSs, cohort databases and relevant scientific articles were systematically searched and screened.The review shows that since 1959, more than 600,000 index children have participated in the 79 Nordic BCSs (22 Danish, 20 Finnish, 12 Norwegian, 24 Swedish, one Icelandic), over half of them still ongoing. The Nordic BCSs cover a wide geographical area including the Nordic Arctic. The topics of BCSs have varied over time but most have focused on examining the developmental origins of diseases. A quarter of them had a general scope, while the rest started with a specific focus, commonly atopic diseases. All BCSs collected questionnaire and/or interview data and over 60% of the BCSs announced exclusion criteria for participants, typically insufficient language proficiency.NBCSs have produced crucial scientific knowledge for over six decades, but there are underutilised opportunities including systematic interdisciplinary collaboration, inclusion of children's own views of their health and well-being, intergenerational data collection, and specific knowledge of Arctic indigenous peoples and other minorities.

Identifying optimal ranges of weight gain at the end of the second trimester result from a population-based cohort study

OBJECTIVE

To identify the optimal weight gain at the end of the second trimester.

DESIGN

This was a population-based cohort study from the antenatal care system in Tianjin, China. We calculated gestational weight gain (GWG) based on the weight measured in the first trimester and the end of the second trimester. Restricted cubic spline analysis was performed to model the possible non-linear relationships between GWG and adverse outcomes. The optimal GWG was defined as the value of the lowest risk. Non-inferiority margins and the shape of the spline curves identified the recommended ranges in Chinese-specific BMI categories.

SETTING

Tianjin Maternal and Child Health Cohort.

PARTICIPANTS

Singleton pregnant women aged 18-45 years.

RESULTS

In total, 69 859 pregnant women were included. Adverse outcome (including stillbirth, preterm birth, hypertensive disorders of pregnancy, gestational diabetes mellitus, small and large for gestational age) was significantly associated with GWG at the end of the second trimester. The risk score was non-linearly correlated with GWG in the underweight, normal weight and overweight groups. GWG at the end of the second trimester should not be < 7 kg in underweight group. For most normal-weight women, a GWG of about 8 kg is optimal. Pregnant women who are overweight should not have a GWG of more than 9 kg. We advised women with overweight and obesity to keep positive growth of GWG (> 0 kg) in the first and second trimesters.

CONCLUSIONS

According to the comprehensive adverse maternal and infant outcomes, we recommend the optimal GWG at the end of the second trimester. This study may provide a considerable reference for weight management.

Associations between Maternal Dietary Patterns, Biomarkers and Delivery Outcomes in Healthy Singleton Pregnancies: Multicenter Italian GIFt Study

Background: Maternal nutrition represents a critical risk factor for adverse health outcomes in both mother and offspring. We aimed to investigate associations between maternal nutritional habits, biomarker status, and pregnancy outcome among Italian healthy normal-weight pregnancies. Methods: Multicenter prospective cohort study recruiting Italian healthy normal-weight women with singleton spontaneous pregnancies at 20 ± 2 weeks (T1) in Milan and Naples. All patients underwent nutritional evaluations by our collecting a 7-day weighed dietary record at 25 ± 1 weeks (T2) and a Food Frequency Questionnaire at 29 ± 2 weeks (T3). Maternal venous blood samples were collected at T3 to assess nutritional, inflammatory and oxidative biomarker concentrations (RBCs folate, vitamin D, hepcidin, total antioxidant capacity). Pregnancy outcomes were collected at delivery (T4). General linear models adjusted for confounding factors were estimated to investigate associations between maternal dietary pattern adherence, nutrient intakes, biomarker concentrations and delivery outcomes. Results: 219 healthy normal-weight pregnant women were enrolled. Vitamin D and RBCs folate concentrations, as well as micronutrient intakes, were consistently below the recommended range. In a multi-adjusted model, maternal adherence to the most prevalent ‘high meat, animal fats, grains’ dietary pattern was positively associated with hepcidin concentrations and negatively associated with gestational age at delivery in pregnancies carrying female fetuses. Hepcidin plasma levels were further negatively associated to placental weight, whereas vitamin D concentrations were positively associated to neonatal weight. Conclusions: A high adherence to an unbalanced ‘high meat, animal fats, grains’ pattern was detected among Italian normal-weight low-risk pregnancies, further associated with maternal pro-inflammatory status and gestational age at delivery. This evidence underlines the need for a dedicated nutritional counseling even among low-risk pregnancies.

A Role for Data Science in Precision Nutrition and Early Brain Development

Multimodal brain magnetic resonance imaging (MRI) can provide biomarkers of early influences on neurodevelopment such as nutrition, environmental and genetic factors. As the exposure to early influences can be separated from neurodevelopmental outcomes by many months or years, MRI markers can serve as an important intermediate outcome in multivariate analyses of neurodevelopmental determinants. Key to the success of such work are recent advances in data science as well as the growth of relevant data resources. Multimodal MRI assessment of neurodevelopment can be supplemented with other biomarkers of neurodevelopment such as electroencephalograms, magnetoencephalogram, and non-imaging biomarkers. This review focuses on how maternal nutrition impacts infant brain development, with three purposes: (1) to summarize the current knowledge about how nutrition in stages of pregnancy and breastfeeding impact infant brain development; (2) to discuss multimodal MRI and other measures of early neurodevelopment; and (3) to discuss potential opportunities for data science and artificial intelligence to advance precision nutrition. We hope this review can facilitate the collaborative march toward precision nutrition during pregnancy and the first year of life.