BackgroundObservational epidemiological studies indicate that maternal height is associated with gestational age at birth and fetal growth measures (i.e., shorter mothers deliver infants at earlier gestational ages with lower birth weight and birth length). Different mechanisms have been postulated to explain these associations. This study aimed to investigate the casual relationships behind the strong association of maternal height with fetal growth measures (i.e., birth length and birth weight) and gestational age by a Mendelian randomization approach.Methods and FindingsWe conducted a Mendelian randomization analysis using phenotype and genome-wide single nucleotide polymorphism (SNP) data of 3,485 mother/infant pairs from birth cohorts collected from three Nordic countries (Finland, Denmark, and Norway). We constructed a genetic score based on 697 SNPs known to be associated with adult height to index maternal height. To avoid confounding due to genetic sharing between mother and infant, we inferred parental transmission of the height-associated SNPs and utilized the haplotype genetic score derived from nontransmitted alleles as a valid genetic instrument for maternal height. In observational analysis, maternal height was significantly associated with birth length (p = 6.31 × 10−9), birth weight (p = 2.19 × 10−15), and gestational age (p = 1.51 × 10−7). Our parental-specific haplotype score association analysis revealed that birth length and birth weight were significantly associated with the maternal transmitted haplotype score as well as the paternal transmitted haplotype score. Their association with the maternal nontransmitted haplotype score was far less significant, indicating a major fetal genetic influence on these fetal growth measures. In contrast, gestational age was significantly associated with the nontransmitted haplotype score (p = 0.0424) and demonstrated a significant (p = 0.0234) causal effect of every 1 cm increase in maternal height resulting in ~0.4 more gestational d. Limitations of this study include potential influences in causal inference by biological pleiotropy, assortative mating, and the nonrandom sampling of study subjects.ConclusionsOur results demonstrate that the observed association between maternal height and fetal growth measures (i.e., birth length and birth weight) is mainly defined by fetal genetics. In contrast, the association between maternal height and gestational age is more likely to be causal. In addition, our approach that utilizes the genetic score derived from the nontransmitted maternal haplotype as a genetic instrument is a novel extension to the Mendelian randomization methodology in casual inference between parental phenotype (or exposure) and outcomes in offspring.

Objectives The purpose of this study is to evaluate the prevalence, impact, and interaction of short interpregnancy interval (IPI), pre-pregnancy body mass index (BMI) category, and pregnancy weight gain (PWG) on the rate of preterm birth. Methods This is a population-based retrospective cohort study using vital statistics birth records from 2006 to 2011 in OH, US, analyzing singleton live births to multiparous mothers with recorded IPI (n = 393,441). Preterm birth rate at <37 weeks gestational age was compared between the referent pregnancy (defined as normal pre-pregnancy maternal BMI, IPI of 12-24 months, and Institute of Medicine (IOM) recommended PWG) and those with short or long IPI, abnormal BMI (underweight, overweight, and obese), and high or low PWG (under or exceeding IOM recommendations). Results Only 6 % of the women in this study had a referent pregnancy, with a preterm birth rate of 7.6 % for this group. Short IPIs of <6 and 6-12 months were associated with increased rates of preterm birth rate to 12.9 and 10.4 %, respectively. Low PWG compared to IOM recommendations for pre-pregnancy BMI class was also associated with increased preterm birth rate of 13.2 % for all BMI classes combined. However, the highest rate of preterm birth of 25.2 % occurred in underweight women with short IPI and inadequate weight gain with OR 3.44 (95 % CI 2.80, 4.23). The fraction of preterm births observed in this cohort that can be attributed to short IPIs is 5.9 %, long IPIs is 8.3 %, inadequate PWG is 7.5 %, and low pre-pregnancy BMI is 2.2 %. Conclusions Our analysis indicates that a significant proportion of preterm births in Ohio are associated with potentially modifiable risk factors. These data suggest public health initiatives focused on preterm birth prevention could include counseling and interventions to optimize preconception health and prenatal nutrition.

There is significant variability in the threshold to report specific medication errors in the hospital setting. More work needs to be done to further improve the education surrounding error reporting in hospitals for all noted subgroups.

The control of normal birth timing in mammals and the fundamental signals that initiate preterm birth in humans are critical areas of scientific investigation. Preterm birth is the leading cause of infant mortality throughout the world, and the single greatest challenge in women's and children's health today. Despite the recognised importance of this area of investigation, relatively limited advances have been made. In part, this limited success in revealing mechanisms results from divergence in the endocrine physiology of pregnancy between species. To have an effect on these biological and medical gaps in knowledge, new genetic studies in humans and comparative genomic investigations across species have been undertaken. In this article, the authors summarise the current status of genetic and genomic approaches to elucidate the control of birth timing. Key Concepts: Genetic factors, primarily in the maternal genome, contribute to preterm birth risk. The physiology of human pregnancy differs from other species except for other higher primates. Humans have unique constraints for birth timing related to foetal size and/or metabolism. Candidate gene association studies have not been generally informative. New data emerging from non‐biased genome‐wide approaches have suggested new pathways for birth timing and preterm birth risk.