Understanding the Implications of Birth Weight

The association between exposure to polycyclic aromatic hydrocarbons and birth outcomes: A systematic review and meta-analysis of observational studies

Exposure to polycyclic aromatic hydrocarbons (PAHs) has been linked to adverse birth outcomes; however, to date, the available studies on such relations, with the exception of birth weight, has not been systematically synthesized. We conducted a systematic review and meta-analysis of the available observational studies on the association of maternal exposure to PAHs and their metabolites during pregnancy with indicators of fetal growth and gestational age at delivery. We searched Web of Science, PubMed and Scopus systematically for all relevant published papers in English until 13 January 2023. Random effects meta-analysis was applied to synthesize the association estimates. Publication bias was assessed using Egger's regression. A total of 31 articles were included in our review (n = 703,080 participants). Our quality assessment of reviewed papers showed that 19 research had excellent, nine had good, and three had fair quality. Most of the reviewed studies on exposure to PAHs and their metabolites with gestational age and preterm birth (seven studies) reported no statistically significant association. Eight studies were eligible for our meta-analysis. Results of the meta-analysis indicated that higher levels of maternal urinary 1-OHP was associated with lower birth weight, birth length and head circumference and a higher risk of low birth weight (LBW). However, these associations were not statistically significant. Similarly, the combined association between maternal urinary 1-OHP and newborn's Ponderal index (PI) and Cephalization index were not statistically significant. Overall, our systematic review and meta-analysis suggested a potential adverse impact of exposure to PAHs on LBW, HC, and CC; however, further studies are required to be able to draw concrete conclusions on such associations.

Sex-specific association of high maternal psychological stress during pregnancy on newborn birthweight

Birthweight is an important predictor of newborn health and has been linked to maternal psychological stress during pregnancy. However, it is unclear whether prenatal stress affects birthweight similarly for both male and female infants. We used a well-established pregnancy cohort to investigate the impact of high maternal psychological stress during pregnancy on birthweight as a function of infant sex. Overall, 5702 mother-newborn pairs were analysed. Of these, 198 mothers reported high levels of stress using the Psychological Stress Measure (nine-items version; PSM-9). Maternal psychological stress was assessed between the 24^th and 28^th week of gestation and analyses were performed jointly and independently as a function of neonatal sex (separate analyses for male and female infants). Newborns exposed to high maternal psychological stress during pregnancy (a score above 26 measured using the PSM-9 questionnaire, corresponding to >97.5^th percentile) were compared to newborns of mothers who reported lower stress. ANCOVAs revealed that high levels of maternal stress during pregnancy were linked to infant birthweight as a function of infant sex. Male infants of mothers who reported high levels of stress had a greater birthweight whereas female infants had a lower birthweight under the same conditions, in comparison to mothers who did not report greater levels of stress. Although the effect size is small, these results underline the possibility that male and female fetuses may use different strategies when adapting to maternal adversity and highlight the need to consider infant sex as a moderator of the association between maternal psychological stress during pregnancy and infant birthweight.

Preconception paternal/maternal BMI and risk of small/large for gestational age infant in over 4·7 million Chinese women aged 20-49 years: a population-based cohort study in China

Evidence of couples' BMI and its influence on birth weight is limited and contradictory. Therefore, this study aims to assess the association between couple's preconception BMI and the risk of small for gestational age (SGA)/large for gestational age (LGA) infant, among over 4·7 million couples in a retrospective cohort study based on the National Free Pre-pregnancy Checkups Project between 1 December 2013 and 30 November 2016 in China. Among the live births, 256 718 (5·44 %) SGA events and 506 495 (10·73 %) LGA events were documented, respectively. After adjusting for confounders, underweight men had significantly higher risk (OR 1·17 (95 % CI 1·15, 1·19)) of SGA infants compared with men with normal BMI, while a significant and increased risk of LGA infants was obtained for overweight and obese men (OR 1·08 (95 % CI 1·06, 1·09); OR 1·19 (95 % CI 1·17, 1·20)), respectively. The restricted cubic spline result revealed a non-linear decreasing dose-response relationship of paternal BMI (less than 22·64) with SGA. Meanwhile, a non-linear increasing dose-response relationship of paternal BMI (more than 22·92) with LGA infants was observed. Moreover, similar results about the association between maternal preconception BMI and SGA/LGA infants were obtained. Abnormal preconception BMI in either women or men were associated with increased risk of SGA/LGA infants, respectively. Overall, couple's abnormal weight before pregnancy may be an important preventable risk factor for SGA/LGA infants.

A Mixture of Endocrine Disrupting Chemicals Associated with Lower Birth Weight in Children Induces Adipogenesis and DNA Methylation Changes in Human Mesenchymal Stem Cells

Endocrine Disrupting Chemicals (EDCs) are man-made compounds that alter functions of the endocrine system. Environmental mixtures of EDCs might have adverse effects on human health, even though their individual concentrations are below regulatory levels of concerns. However, studies identifying and experimentally testing adverse effects of real-life mixtures are scarce. In this study, we aimed at evaluating an epidemiologically identified EDC mixture in an experimental setting to delineate its cellular and epigenetic effects. The mixture was established using data from the Swedish Environmental Longitudinal Mother and child Asthma and allergy (SELMA) study where it was associated with lower birth weight, an early marker for prenatal metabolic programming. This mixture was then tested for its ability to change metabolic programming of human mesenchymal stem cells. In these cells, we assessed if the mixture induced adipogenesis and genome-wide DNA methylation changes. The mixture increased lipid droplet accumulation already at concentrations corresponding to levels measured in the pregnant women of the SELMA study. Furthermore, we identified differentially methylated regions in genes important for adipogenesis and thermogenesis. This study shows that a mixture reflecting human real-life exposure can induce molecular and cellular changes during development that could underlie adverse outcomes.

Can Time-Lapse Incubation and Monitoring Be Beneficial to Assisted Reproduction Technology Outcomes? A Randomized Controlled Trial Using Day 3 Double Embryo Transfer

Objective: To determine if the application of time-lapse incubation and monitoring can be beneficial to clinical outcomes in assisted reproductive technology.

Methods: A total of 600 patients were equally randomized to three groups, namely, conventional embryo culture and standard morphological selection (CM group), time-lapse culture and standard morphological selection (TLM group), and time-lapse culture and morphokinetic selection (TLA group). Notably, 424 undergoing fresh autologous in vitro fertilization cycles were analyzed, 132 patients in the CM group, 158 in the TLM group, and 134 in the TLA group. Main outcomes included clinical outcomes, embryo development rates, and perinatal outcomes.

Results: Clinical pregnancy rates in the time-lapse groups were significantly higher than in the CM group (CM 65.2% vs. TLM 77.2% vs. TLA 81.3%). Implantation rates and live birth rates were significantly higher for the TLA group (59.7 and 70.9%) compared with the CM group (47.7 and 56.1%) but not compared with the TLM group (55.4 and 67.1%). There was no statistical difference in miscarriage and ectopic pregnancy rates among the three groups. Overall, birth weight was significantly higher in the time-lapse groups (CM 2,731.7 ± 644.8 g vs. TLM 3,066.5 ± 595.4 g vs. TLA 2,967.4 ± 590.0 g). The birth height of newborns in the TLM group was significantly longer than that of the CM group and TLA group (CM 48.3± 4.4 cm vs. TLM 49.8± 2.3 cm vs. TLA 48.5± 2.7 cm).

Conclusion: Time-lapse incubation and monitoring have a significant benefit on clinical pregnancy rates and on overall birth weights while morphokinetic analysis is not necessary.

Clinical Trial Registration: [www.ClinicalTrials.gov], identifier [NCT02974517].

Association Between Maternal Fasting Plasma Glucose Value and Fetal Weight Among Singletons of Mothers with Gestational Diabetes Mellitus

PURPOSE

Infants with macrosomia are more likely to be born to mothers with gestational diabetes mellitus (GDM). This study aimed to investigate the associations between maternal blood glucose levels and fetal weight, placental weight, and risk of macrosomia in mothers with GDM.

PATIENTS AND METHODS

This retrospective study included 3211 singletons of mothers with GDM at the Shanghai First Maternity and Infant Hospital between January 2017 and December 2019. All women underwent an oral glucose tolerance test (OGTT) during the 24-28 weeks gestation period. Data on fetal and placental parameters were collected at delivery. Multiple linear regression models were used to evaluate the associations of maternal blood glucose levels with fetal weight and placental weight, while multiple logistic regression model was used to estimate the association between maternal blood glucose levels and the risk of macrosomia.

RESULTS

The prevalence of GDM in our study was 7%. Fasting plasma glucose (FPG) was positively correlated with fetal weight (r²=0.0329, P<0.001), and macrosomia risk (odds ratio [OR], 2.42; 95% confidence interval [CI], 1.93-3.04; P<0.001). After adjusting for gestational age, the result remained significant (OR, 2.67; 95% CI, 2.11-3.38; P<0.001). In contrast, there was no significant relationship between 1-h plasma glucose (1hPG) or 2-h plasma glucose (2hPG) and fetal weight (P=0.18, P=0.46). Additionally, 1hPG or 2hPG was not strongly associated with macrosomia risk (OR, 0.95; 95% CI, 0.85-1.05; P=0.32 vs OR, 0.94; 95% CI, 0.85-1.05; P=0.28). Maternal blood glucose levels did not affect placental weight. The associations were similar in women carrying male and female fetuses.

CONCLUSION

Maternal fasting plasma glucose levels were strongly associated with increased birth weight and macrosomia risk. Our findings suggest that fasting plasma glucose may predict birth weight.

Prediction of Birth Weight by Using Neonatal Anthropometric Parameters at Birth in Finote Selam Hospital, Ethiopia

Introduction

Birth weight is an indicator of a newborn’s chances for survival and growth. However, developing countries lack enough weighing scales to identify low birth weight babies. Therefore, finding an alternative to weighing scales is vital.

Objective

To predict birth weight from neonatal anthropometric parameters at birth in Finote Selam Hospital, Ethiopia.

Methods

A hospital-based cross-sectional study was carried out from July 13 to October 27, 2020. A total of 424 live-delivered neonates were enrolled. Based on eligibility, birth weight and neonatal anthropometric parameters like crown–heel length, foot length, hand length, mid-upper arm circumference, umbilical–nipple distance, intermammary distance and head circumference were measured within 24 hours of birth. The association between birth weight and neonatal anthropometric parameters was evaluated using correlation analysis. Birth weight predictive regression models were formulated by using simple and multiple linear regression analysis.

Results

All neonatal anthropometric parameters had positive significant correlation with birth weight at p<0.05. Amongst the neonatal anthropometric parameters, the highest significant correlation with birth weight was observed on mid-upper arm circumference (MUAC) followed by foot length (FL), each being r=0.474 and r=0.461, respectively. The best predictive regression models were formulated as birth weight (kg)=0.117+[0.284×MUAC (cm)] and birth weight (kg)=1.137+[0.254×FL (cm)]. As compared to individual neonatal anthropometric parameters, a combination of MUAC, hand length (HL), FL and crown–heel length (CHL) had the highest significant correlation (r=0.661), and a multiple regression equation used to estimate birth weight was formulated as birth weight (kg)=−2.489+[0.192×MUAC(cm)]+[0.078×HL(cm)]+[0.11×FL (cm)]+[0.036×CHL(cm)].

Conclusion

Using a combination of MUAC, HL, FL and CHL followed by individual MUAC neonatal anthropometric parameters has high significance to identify low birth weight. Prediction of neonatal birth weight from neonatal anthropometric parameters is crucial to minimize the death of neonates due to low birth weight.

A New Model for Birth Weight Prediction Using 2- and 3-Dimensional Ultrasonography by Principal Component Analysis: A Chinese Population Study

OBJECTIVES

To establish a new model for birth weight prediction using 2- and 3-dimensional ultrasonography (US) by principal component analysis (PCA).

METHODS

Two- and 3-dimensional US was prospectively performed in women with normal singleton pregnancies within 7 days before delivery (37-41 weeks' gestation). The participants were divided into a development group (n = 600) and a validation group (n = 597). Principal component analysis and stepwise linear regression analysis were used to develop a new prediction model. The new model's accuracy in predicting fetal birth weight was confirmed by the validation group through comparisons with previously published formulas.

RESULTS

A total of 1197 cases were recruited in this study. All interclass and intraclass correlation coefficients of US measurements were greater than 0.75. Two principal components (PCs) were considered primary in determining estimated fetal birth weight, which were derived from 9 US measurements. Stepwise linear regression analysis showed a positive association between birth weight and PC1 and PC2. In the development group, our model had a small mean percentage error (mean ± SD, 3.661% ± 3.161%). At least a 47.558% decrease in the mean percentage error and a 57.421% decrease in the standard deviation of the new model compared with previously published formulas were noted. The results were similar to those in the validation group, and the new model covered 100% of birth weights within 10% of actual birth weights.

CONCLUSIONS

The birth weight prediction model based on 2- and 3-dimensional US by PCA could help improve the precision of estimated fetal birth weight.