Aim: To investigate the association of dietary patterns with gestational depression and sleep disturbance. Methods: Women in early pregnancy were recruited from the Chinese Pregnant Women Cohort Study (CPWCS) through July 25th, 2017 to November 26th, 2018, and eventually 7615 participants were included in this study. The qualitative food frequency questionnaire (Q-FFQ), Edinburgh Postnatal Depression Scale (EPDS), and the Pittsburgh Sleep Quality Index (PSQI) were used to assess dietary, depression and sleep quality during pregnancy, respectively. Dietary patterns were derived by factor analysis. Logistic regression was used to estimate the odds ratio (OR) and 95% confidence interval (95% CI) of each outcome according to quartiles of each dietary pattern. Results: Five dietary patterns were identified. Participants with the highest quartile in plant-based pattern had a significantly lower likelihood of mental problems (OR: 95% CI for depression: 0.66, 0.55-0.79; sleep disturbance: 0.80, 0.68-0.93); Similar results were observed in vitamin-rich pattern (OR: 95% CI for depression: 0.46, 0.38-0.55; sleep disturbance: 0.76, 0.65-0.89); However, contrary results were found in high-fat pattern (OR: 95% CI for depression: 2.15, 1.25-1.85; sleep disturbance: 1.43, 1.22-1.67); In animal protein-rich pattern, participants with the highest quartile had a decreased likelihood of depression (OR: 0.80, 95% CI: 0.67-0.96). As for bean products pattern, participants with the highest quartile had an increased risk of depression (OR: 1.28, 95% CI:1.06-1.53). Interactions of dietary patterns and lifestyles on mental disorders were observed. Conclusion: Dietary patterns were associated with gestational depression and sleep disturbance. Relevant departments and maternal and child health personnel should conduct health education for pregnant women and guide them to eat properly.

Background This study aims to explore the relationships between pre-pregnancy body mass index (BMI), gestational weight gain (GWG), rate of GWG during the second and third trimesters (GWGrate) and birth weight among Chinese women. Methods Women were enrolled by 24 hospitals in 15 different provinces in mainland China from July 25th, 2017 to 26 November 2018. Pre-pregnancy BMI, GWG and GWGrate were calculated and divided in to different groups. The multinomial logistic regression model and restrictive cubic spline model were used to explore the relationships. Results Of the 3585 participants, women who were underweight, had insufficient GWG or GWGrate had 1.853-, 1850- or 1.524-fold higher risks for delivering small-for-gestational-age (SGA) infant compared with women who had normal BMI, sufficient GWG or GWGrate. Women who were overweight/obese, had excessive GWG or GWGrate had 1.996-, 1676- or 1.673-fold higher risks for delivering large-for-gestational-age (LGA) infant. The effects of GWG and GWGrate on birth weight varied by pre-pregnancy BMI statuses. Dose-response analysis demonstrated L-shaped and S-shaped relationships between pre-pregnancy BMI, GWG, GWGrate and neonatal birth weight. Conclusions Pre-pregnancy BMI, GWG or GWGrate were associated with neonatal birth weight among Chinese women. Both body weight before and during pregnancy should be maintained within the recommendations to prevent abnormal birth weight.

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PurposeA multicentre prospective cohort study, known as the Chinese Pregnant Women Cohort Study (CPWCS), was established in 2017 to collect exposure data during pregnancy (except environmental exposure) and analyse the relationship between lifestyle during pregnancy and obstetric outcomes. Data about mothers and their children’s life and health as well as children’s laboratory testing will be collected during the offspring follow-up of CPWCS, which will enable us to further investigate the longitudinal relationship between exposure in different periods (during pregnancy and childhood) and children’s development.Participants9193 pregnant women in 24 hospitals in China who were in their first trimester (5–13 weeks gestational age) from 25 July 2017 to 26 November 2018 were included in CPWCS by convenience sampling. Five hospitals in China which participated in CPWCS with good cooperation will be selected as the sample source for the Chinese Pregnant Women Cohort Study (Offspring Follow-up) (CPWCS-OF).Findings to dateSome factors affecting pregnancy outcomes and health problems during pregnancy have been discovered through data analysis. The details are discussed in the ‘Findings to date’ section.Future plansInfants and children and their mothers who meet the criteria will be enrolled in the study and will be followed up every 2 years. The longitudinal relationship between exposure (questionnaire data, physical examination and biospecimens, medical records, and objective environmental data collected through geographical information system and remote sensing technology) in different periods (during pregnancy and childhood) and children’s health (such as sleeping problem, oral health, bowel health and allergy-related health problems) will be analysed.Trail registration numberCPWCS was registered with ClinicalTrials.gov on 18 January 2018: NCT03403543. CPWCS-OF was registered with ClinicalTrials.gov on 24 June 2020: NCT04444791.

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