Cohort profile: the Taicang and Wuqiang mother-child cohort study (TAWS) in China

Trajectory of gestational weight gain is related to birthweight: The TAWS cohort study in China

Few studies have reported the timing and amount of gestational weight gain (GWG) to prevent large-for-gestational-age (LGA) or small-for-gestational-age (SGA). This study aimed to evaluate the association of GWG velocity in each trimester with LGA or SGA based on data from the Taicang and Wuqiang cohort study (TAWS, n = 2008). We used a linear mixed model to evaluate the association of trimester-specific GWG velocity with birthweight categories and stratified by prepregnancy body mass index category and parity. For normal-weight pregnant women, mothers with LGA births had higher GWG velocities than mothers with appropriate-for-gestational-age (AGA) births in the first trimester (0.108 vs. 0.031 kg/week, p < 0.01), second trimester (0.755 vs. 0.631 kg/week, p < 0.01) and third trimester (0.664 vs. 0.594 kg/week, p < 0.01); in contrast, mothers with SGA births had lower GWG velocities than mothers with AGA births in the second trimester (0.528 vs. 0.631 kg/week, p < 0.01) and third trimester (0.541 vs. 0.594 kg/week, p < 0.01). For normal-weight pregnant women with AGA births, multiparous women had lower GWG velocities than primiparous women in the second (0.602 vs. 0.643 kg/week, p < 0.01) and third trimesters (0.553 vs. 0.606 kg/week, p < 0.01). Therefore, for normal-weight women, LGA prevention would begin in early pregnancy and continue until delivery and the second and third trimesters may be critical periods for preventing SGA; in addition, among normal-weight pregnant women with AGA births, multiparous women tend to have lower weight gain velocities than primiparous women.

Maximising the potential of Chinese birth cohort studies: a systematic review of mother-baby cohorts in mainland China

OBJECTIVES

There is now a growing interest in early-life influences on adult diseases in China. A number of birth cohorts have been established. This systematic review provided a better understanding of the development of mother-baby cohorts in China.

STUDY DESIGN

Systematic review.

METHODS

We conducted a systematic review for research or profile papers in English/Chinese that reported data from mother-baby cohorts in mainland China, with ≥1y follow-up after birth. We identified 315 papers, corresponding to 31 cohorts from 19 provinces/megacities.

RESULTS

All cohorts started in 1999-2017 (21 after 2010) and were set up with broad objectives or specific scientific focus. The baseline sample size varied, from <500 to >300,000 mothers. A majority of cohorts were initiated during pregnancy and followed children to <10y, only six to adolescence and none into adulthood. These cohorts mostly collected samples from mothers and babies, in addition to using interviews/questionnaires to collect information about pregnancy, birth and child health. Most cohorts were recruited from a single province/city. The large western region was understudied.

CONCLUSIONS

Mother-baby cohorts have developed rapidly in China, but usually with a short follow-up duration. Extending the follow-up of children and developing cross-cohort collaboration will increase the diversity, size and coverage of the sample, allow studying early influences on life-course health and identify targets for early intervention in the Chinese population.

Effects of prepregnancy dietary patterns on infant birth weight: a prospective cohort study

BACKGROUND

Maternal nutrition can have a profound effect on fetal growth, development, and subsequent infant birth weight. However, little is known regarding the influence of prepregnancy dietary patterns.

OBJECTIVES

This study aimed to explore the effects between prepregnancy dietary patterns on birth weight.

METHODS

This study included 911 singleton live-born infants from the Taicang and Wuqiang Mother-Child Cohort Study (TAWS). Baseline information and prepregnancy diet data were collected during early pregnancy. Newborn birth information was obtained from the Wuqiang County Hospital. Macrosomia, defined as a birth weight of ≥4000 g, and large for gestational age (LGA), defined as a birth weight higher than the 90th percentile for the same sex and gestational age, were the outcomes of interest. The dietary patterns were extracted using principal component analysis. Logistic regression models were used to investigate the association between prepregnancy dietary patterns (in tertiles) and macrosomia and LGA, and subgroup analysis was further explored by pre-pregnancy body mass index (BMI).

RESULTS

Four dietary patterns were identified based on 15 food groups. These patterns were named as "cereals-vegetables-fruits," "vegetables-poultry-aquatic products," "milk-meat-eggs," and "nuts-aquatic products-snacks." After adjusting for sociodemographic characteristics, pregnancy complications, and other dietary patterns, greater adherence to the "cereals-vegetables-fruits" pattern before pregnancy was associated with a higher risk of macrosomia (adjusted OR = 2.220, 95% CI: 1.018, 4.843), while greater adherence to the "nuts-aquatic products-snacks" pattern was associated with a lower risk of macrosomia (adjusted OR = 0.357, 95% CI: 0.175, 0.725) compared to the lowest tertile. No significant association was observed between prepregnancy dietary patterns and LGA. However, after subgroup analysis of pre-pregnancy BMI, "cereals-vegetables-fruits" pattern was associated with an increased risk of LGA in overweight and obese mothers (adjusted OR = 2.353, 95% CI: 1.010, 5.480).

CONCLUSIONS

An unbalanced pre-pregnancy diet increases the risk of macrosomia and LGA, especially in overweight or obese women before pre-pregnancy.

The Association between Macrosomia and Amino Acids' Levels in Maternal and Cord Sera: A Case-Control Study

This study aims to explore the relationship between macrosomia and amino acids in maternal and cord sera.

METHODS

In the case-control study, 78 pairs of mothers and newborns were recruited from December 2016 to November 2019. Participants were divided into the macrosomia group (BW ≥ 4000 g, n = 39) and the control group (BW between 2500 g and 3999 g, n = 39) according to the birth weight (BW) of newborns. Maternal vein blood samples were collected before delivery and cord vein blood samples were collected after birth. The levels of amino acids in maternal and cord sera were measured by liquid chromatography and mass spectrometry (LC-MS/MS) in the year 2021. The difference in amino acid levels in maternal and cord sera between the two groups was compared, and the contribution of each amino acid to the difference between the two groups was analyzed. Unconditional logistic regression analysis was used to test the relationship between macrosomia and amino acids.

RESULTS

In maternal serum during the antepartum, the levels of asparagine, glutamine, methionine, alanine, and threonine in the macrosomia group were higher but arginine was lower than that in the control group (p < 0.05). In cord serum, the levels of lysine, histidine, phenylalanine, arginine, tryptophan, valine, isoleucine, glutamate, tyrosine, and total essential amino acid (EAA) in the macrosomia group were lower while glutamine was higher than that in the control group (p < 0.05). The ratios of EAA, valine, threonine, methionine, tryptophan, and alanine in maternal serum to those in cord serum were higher, while the ratio of glutamine was lower in the macrosomia group (p < 0.05). Arginine and threonine in maternal serum and glutamate, glutamine, and histidine in cord serum were associated with macrosomia (p < 0.05).

CONCLUSION

Most of the amino acid levels in the maternal sera of the macrosomia group are higher than those in the control group, while most of the amino acids' levels in the cord sera of the macrosomia group are lower than those in the control group. The ratios of some amino acids in maternal serum to those in cord serum were different between the two groups. Arginine and threonine in maternal serum and glutamate, glutamine, and histidine in cord serum are closely related to macrosomia.