Cui-Yue Hu

Maternal dietary patterns and gestational diabetes mellitus: a large prospective cohort study in China

Few studies have explored the relationship between dietary patterns and the risk of gestational diabetes mellitus (GDM). Evidence from non-Western areas is particularly lacking. In the present study, we aimed to examine the associations between dietary patterns and the risk of GDM in a Chinese population. A total of 3063 pregnant Chinese women from an ongoing prospective cohort study were included. Data on dietary intake were collected using a FFQ at 24-27 weeks of gestation. GDM was diagnosed using a 75 g, 2 h oral glucose tolerance test. Dietary patterns were determined by principal components factor analysis. A log-binomial regression model was used to examine the associations between dietary pattern and the risk of GDM. The analysis identified four dietary patterns: vegetable pattern; protein-rich pattern; prudent pattern; sweets and seafood pattern. Multivariate analysis showed that the highest tertile of the vegetable pattern was associated with a decreased risk of GDM (relative risk (RR) 0·79, 95% CI 0·64, 0·97), compared with the lowest tertile, whereas the highest tertile of the sweets and seafood pattern was associated with an increased risk of GDM (RR 1·23, 95% CI 1·02, 1·49). No significant association was found for either the protein-rich or the prudent pattern. The protective effect of a high vegetable pattern score was more evident among women who had a family history of diabetes (P for interaction=0·022). These findings suggest that the vegetable pattern was associated with a decreased risk of GDM, while the sweets and seafood pattern was associated with an increased risk of GDM. These findings may be useful in dietary counselling during pregnancy.

Connections between the human gut microbiome and gestational diabetes mellitus

Abstract The human gut microbiome can modulate metabolic health and affect insulin resistance, and it may play an important role in the etiology of gestational diabetes mellitus (GDM). Here, we compared the gut microbial composition of 43 GDM patients and 81 healthy pregnant women via whole-metagenome shotgun sequencing of their fecal samples, collected at 21–29 weeks, to explore associations between GDM and the composition of microbial taxonomic units and functional genes. A metagenome-wide association study identified 154 837 genes, which clustered into 129 metagenome linkage groups (MLGs) for species description, with significant relative abundance differences between the 2 cohorts. Parabacteroides distasonis, Klebsiella variicola, etc., were enriched in GDM patients, whereas Methanobrevibacter smithii, Alistipes spp., Bifidobacterium spp., and Eubacterium spp. were enriched in controls. The ratios of the gross abundances of GDM-enriched MLGs to control-enriched MLGs were positively correlated with blood glucose levels. A random forest model shows that fecal MLGs have excellent discriminatory power to predict GDM status. Our study discovered novel relationships between the gut microbiome and GDM status and suggests that changes in microbial composition may potentially be used to identify individuals at risk for GDM.

Maternal Dietary Patterns and Fetal Growth: A Large Prospective Cohort Study in China

There was limited evidence revealing the association of Chinese maternal dietary patterns with fetal growth. We aimed to examine the relationship of maternal dietary patterns during pregnancy to neonatal birth weight and birth weight for gestational age in a Chinese population. A total of 6954 mother-child pairs were included from the Born in Guangzhou Cohort Study. Maternal diet during pregnancy was assessed using a self-administered food frequency questionnaire. Cluster analysis was used to identify dietary patterns. The following six dietary patterns were identified: “Cereals, eggs, and Cantonese soups” (n 1026, 14.8%), “Dairy” (n 1020, 14.7%), “Fruits, nuts, and Cantonese desserts” (n 799, 11.5%), “Meats” (n 1066, 15.3%), “Vegetables” (n 1383, 19.9%), and “Varied” (n 1224, 17.6%). The mean neonatal birth weight Z scores of women in the above patterns were 0.02, 0.07, 0.20, 0.01, 0.06, and 0.14, respectively. Women in the “Fruits, nuts, and Cantonese desserts” and “Varied” groups had significantly heavier infants compared with those in the “Cereals, eggs, and Cantonese soups” group. Compared with women in the “Cereals, eggs, and Cantonese soups” group, those in the “Varied” group had marginally significantly lower odds of having a small-for-gestational age (SGA) infant after adjustment for other confounders (OR 0.77, 95% CI 0.57, 1.04, p = 0.08). These findings suggest that compared to a traditional Cantonese diet high in cereals, eggs, and Cantonese soups, a diet high in fruits, nuts, and Cantonese desserts might be associated with a higher birth weight, while a varied diet might be associated with a greater birth weight and also a decreased risk of having a SGA baby.

Validity and Reproducibility of a Dietary Questionnaire for Consumption Frequencies of Foods during Pregnancy in the Born in Guangzhou Cohort Study (BIGCS)

This study aimed to examine the reproducibility and validity of a new food frequency questionnaire (FFQ) used in a birth cohort study to estimate the usual consumption frequencies of foods during pregnancy. The reference measure was the average of three inconsecutive 24 h diet recalls (24 HR) administrated between two FFQs, and the reproducibility was measured by repeating the first FFQ (FFQ1) approximately eight weeks later (FFQ2). A total of 210 pregnant women from the Born in Guangzhou Cohort Study (BIGCS) with full data were included in the analysis. The Spearman’s correlation coefficients of FFQ1 and FFQ2 ranged from 0.33 to 0.71. The intraclass correlation coefficients of the two FFQs ranged from 0.22 to 0.71. The Spearman’s correlation coefficients of the 24 HR and FFQ2 ranged from 0.23 to 0.62. Cross-classification analysis showed 65.1% of participants were classified into same and contiguous quintiles, while only 3.2% were misclassified into the distant quintiles. Bland-Altman methods showed good agreement for most food groups across the range of frequencies between FFQ1 and FFQ2. Our findings indicated that the reproducibility and validity of the FFQ used in BIGCS for assessing the usual consumption frequencies of foods during pregnancy were acceptable.

Does tea consumption during early pregnancy have an adverse effect on birth outcomes

BACKGROUND Tea, a common beverage, has been suggested to exhibit a number of health benefits. However, one of its active ingredients, caffeine, has been associated with preterm birth and low birthweight. We investigated whether tea consumption during early pregnancy is associated with an increased risk of preterm birth and abnormal fetal growth. METHODS A total of 8775 pregnant women were included from the Born in Guangzhou Cohort Study. Tea consumption (type, frequency, and strength) during their first trimester and social and demographic factors were obtained by way of questionnaires administered during pregnancy. Information on birth outcomes and complications during pregnancy was obtained from hospital medical records. RESULTS Overall habitual tea drinking (≥1 serving/week) prevalence among pregnant women was low, at 16%. After adjustment for potential confounding factors (eg, maternal age, educational level, monthly income) tea drinking during early pregnancy was not associated with an increased risk of preterm birth or abnormal fetal growth (small or large for gestational age) (P>.05). CONCLUSIONS We did not identify a consistent association between frequency of tea consumption or tea strength and adverse birth outcomes among Chinese pregnant women with low tea consumption. Our findings suggest that occasional tea drinking during pregnancy is not associated with increased risk of preterm birth or abnormal fetal growth. Given the high overall number of annual births in China, our findings have important public health significance.

Progesterone use in early pregnancy: a prospective birth cohort study in China

Abstract Background The US Food and Drug Administration recommended that the use of progesterone to reduce the risk of preterm births in women with a previous preterm birth should begin after the 16th week of gestation. In the USA, even a 4·5% reported rate of progesterone use in the first trimester is regarded as a high prescription for unknown fetal risk. Unfortunately, we identified a 10 times higher prevalence of progesterone prescription in early pregnancy in an ongoing study, the Born in Guangzhou Cohort Study (BIGCS) in China. We aimed to investigate the potential effects of progesterone use in early pregnancy on maternal and birth outcomes. Methods 6617 pregnant women were included from the BIGCS between January, 2013, and January, 2015. Progesterone use during early pregnancy ( Findings 2787 (42%) women reported progesterone use in early pregnancy. After adjusting for potential confounders, women who used progesterone had significantly higher risks of caesarean section (odds ratio 1·31 [95% CI 1·05–1·63]; p=0·0146) and post-partum depression (1·22 [1·00–1·49]; p=0·0497). No effect of progesterone use was reported for preterm-birth prevention, fetal growth, and gestational diabetes. Interpretation Progesterone use in early pregnancy gives no benefit and even results in harm for specific pregnancy outcomes. In view of the high use rate in China, progesterone prescription in early pregnancy should be regarded as an urgent public health concern. Monitoring of clinic practice, study of long-term effects on health, and evidence-based policy are needed. Funding Guangzhou Science and Technology Bureau, Guangzhou, China (2011Y2-00025, 2012J5100038, and 201508030037).

Predictions of Preterm Birth from Early Pregnancy Characteristics: Born in Guangzhou Cohort Study

Preterm birth (PTB, <37 weeks) is the leading cause of death in children <5 years of age. Early risk prediction for PTB would enable early monitoring and intervention. However, such prediction models have been rarely reported, especially in low- and middle-income areas. We used data on a number of easily accessible predictors during early pregnancy from 9044 women in Born in Guangzhou Cohort Study, China to generate prediction models for overall PTB and spontaneous, iatrogenic, late (34–36 weeks), and early (<34 weeks) PTB. Models were constructed using the Cox proportional hazard model, and their performance was evaluated by Harrell’s c and D statistics and calibration plot. We further performed a systematic review to identify published models and validated them in our population. Our new prediction models had moderate discrimination, with Harrell’s c statistics ranging from 0.60–0.66 for overall and subtypes of PTB. Significant predictors included maternal age, height, history of preterm delivery, amount of vaginal bleeding, folic acid intake before pregnancy, and passive smoking during pregnancy. Calibration plots showed good fit for all models except for early PTB. We validated three published models, all of which were from studies conducted in high-income countries; the area under receiver operating characteristic for these models ranged from 0.50 to 0.56. Based on early pregnancy characteristics, our models have moderate predictive ability for PTB. Future studies should consider inclusion of laboratory markers for the prediction of PTB.