Investigation of optimal gestational weight gain based on the occurrence of adverse pregnancy outcomes for Chinese women: a prospective cohort study.

OBJECTIVE: To investigate recommendations for appropriate gestational weight gain (GWG) of Chinese females. METHODS: In total of 3,172 eligible women in the first trimester were recruited into the Chinese Pregnant Women Cohort Study (CPWCS) project. Pregnancy complications and outcomes were collated using the hospital medical records system. The method of occurrence of participants with adverse pregnancy outcomes (Occurrence Method) was conducted to calculate the recommended total GWG for each participant's pre-pregnancy BMI. Occurrence Method data were judged against the Institute of Medicine (IOM) and Japanese recommended criteria in terms of the total occurrence of adverse pregnancy outcomes of pregnant women with appropriate weight gain. RESULTS: The most frequent GWG was ≥ 14 kg and < 16 kg (19.4%), followed by ≥ 10 kg and < 12 kg (15.5%) and ≥ 12 kg and < 14 kg (15.2%). The most frequently occurring adverse pregnancy outcomes were cesarean sections for underweight (30.0%), normal weight (40.4%), overweight (53.6%) and obese (53.7%) women. A large for gestational age (LGA) accounted for 18.0% of the overweight and 20.9% of the obesity group. Gestational diabetes mellitus (GDM) occurred in 16.9% of overweight and 23.1% of obese women. The recommended total GWG in a Chinese women population is ≥ 8 and < 12 kg if underweight, ≥ 12 and < 14 kg for normal weight, ≥ 8.0 and < 10.0 kg if overweight, and < 8 kg for women with obesity. CONCLUSIONS: Current Chinese recommendations provide the optimal ranges of GWG to minimize the occurrence of undesirable pregnancy outcomes for each group of pre-pregnancy BMIs in a Chinese population. TRIAL REGISTRATION: Registered with ClinicalTrials ( NCT03403543 ).

Association among pre-pregnancy body mass index, gestational weight gain and neonatal birth weight: a prospective cohort study in China.

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.

Effects of pre-pregnancy body mass index and gestational weight gain on maternal and infant complications.

BACKGROUND: The potential effects of pre-pregnancy body mass (BMI) and gestational weight gain (GWG) on pregnancy outcomes remain unclear. Thus, we investigated socio-demographic characteristics that affect pre-pregnancy BMIs and GWG and the effects of pre-pregnancy BMI and GWG on Chinese maternal and infant complications. METHODS: 3172 women were enrolled in the Chinese Pregnant Women Cohort Study-Peking Union Medical College from July 25, 2017 to July 24, 2018, whose babies were delivered before December 31, 2018. Regression analysis was employed to evaluate the socio-demographic characteristics affecting pre-pregnancy BMI and GWG values and their effects on adverse maternal and infant complications. RESULTS: Multivariate logistic regression analysis revealed that age groups < 20 years (OR: 1.97), 25-30 years (OR: 1.66), 30-35 years (OR: 2.24), 35-40 years (OR: 3.90) and ≥ 40 years (OR: 3.33) as well as elementary school or education below (OR: 3.53), middle school (OR: 1.53), high school (OR: 1.40), and living in the north (OR: 1.37) were risk factors in maintaining a normal pre-pregnancy BMI. An age range of 30-35 years (OR: 0.76), living in the north (OR: 1.32) and race of ethnic minorities (OR: 1.51) were factors affecting GWG. Overweight (OR: 2.01) and inadequate GWG (OR: 1.60) were risk factors for gestational diabetes mellitus (GDM). Overweight (OR: 2.80) and obesity (OR: 5.42) were risk factors for gestational hypertension (GHp). Overweight (OR: 1.92), obesity (OR: 2.48) and excessive GWG (OR: 1.95) were risk factors for macrosomia. Overweight and excessive GWG were risk factors for a large gestational age (LGA) and inadequate GWG was a risk factor for low birth weights. CONCLUSIONS: Overweight and obesity before pregnancy and an excessive GWG are associated with a greater risk of developing GDM, GHp, macrosomia and LGA. The control of body weight before and during the course of pregnancy is recommended to decrease adverse pregnancy outcomes, especially in pregnant women aged < 20 or > 25 years old educated below university and college levels, for ethnic minorities and those women who live in the north of China. TRIAL REGISTRATION: Registered at Clinical Trials ( NCT03403543 ), September 29, 2017.

Dietary patterns in relation to gestational depression and sleep disturbance in Chinese pregnant women.

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.