Fetal growth trajectories of babies born large-for-gestational age in the LIFECODES Fetal Growth Study

Background Babies born large-for-gestational age have an increased risk of adverse health outcomes, including birth injuries, childhood obesity, and cardiometabolic disorders. However, little work has been done to characterize patterns of fetal growth among large-for-gestational age births, which may further elucidate high- and low-risk subgroups. Objective This study aimed to identify subgroups of large-for-gestational age births based on trajectories of fetal growth derived from prenatal ultrasound measurements and explore differences in sociodemographic, pregnancy, and birth outcome characteristics across subgroups. Study Design This study identified and described trajectories of fetal growth among large-for-gestational age births (n=235) in the LIFECODES Fetal Growth Study. Ultrasound measurements of fetal growth in middle to late pregnancy were abstracted from health records. Group-based multi-trajectory modeling was applied to measurements of head circumference, abdominal circumference, and femur length z-scores to identify multivariate trajectories of fetal growth. Moreover, sociodemographic variables, pregnancy characteristics, and birth outcomes based on trajectory membership were summarized. Results This study identified 4 multivariate trajectories of fetal growth among large-for-gestational age births: catch-up growth (n=28), proportional abdominal circumference–to–femur length growth (n=67), disproportional abdominal circumference–to–femur length growth (n=96), and consistently large (n=44). Fetuses in the “catch-up growth” group exhibited small relative sizes in midpregnancy (ie, below average head circumference, abdominal circumference, and femur length z-scores) and large relative sizes in late pregnancy. Growth among these births was driven by increases in relative abdominal circumference and head circumference sizes. Participants who delivered births assigned to this group were less likely to have normal glucose control (40% vs 65%–75%) and more likely to have pregestational diabetes mellitus (36% vs 10%–17%) than other large-for-gestational age subgroups. In addition, the babies in this trajectory group were more likely to have macrosomia (86% vs 67%–73%) and to be admitted to the neonatal intensive care unit (32% vs 14%–21%) than other large-for-gestational age subgroups. In contrast, babies in the “consistently large” group had the largest relative size for all growth parameters throughout gestation and experienced a lower risk of adverse birth outcomes than other large-for-gestational age subgroups. Conclusion This study characterized several trajectories of fetal growth among large-for-gestational age births, which were related to different pregnancy characteristics and the distribution of adverse birth outcomes. Although the number of individuals within some trajectories was small, a subgroup that exhibited a catch-up growth phenotype during gestation was identified, which may be uniquely associated with exposure to pregestational diabetes mellitus and a higher risk of admission to the neonatal intensive care unit. These results have highlighted that the risk of adverse outcomes may not be evenly distributed across all large-for-gestational age births. Babies born large-for-gestational age have an increased risk of adverse health outcomes, including birth injuries, childhood obesity, and cardiometabolic disorders. However, little work has been done to characterize patterns of fetal growth among large-for-gestational age births, which may further elucidate high- and low-risk subgroups. This study aimed to identify subgroups of large-for-gestational age births based on trajectories of fetal growth derived from prenatal ultrasound measurements and explore differences in sociodemographic, pregnancy, and birth outcome characteristics across subgroups. This study identified and described trajectories of fetal growth among large-for-gestational age births (n=235) in the LIFECODES Fetal Growth Study. Ultrasound measurements of fetal growth in middle to late pregnancy were abstracted from health records. Group-based multi-trajectory modeling was applied to measurements of head circumference, abdominal circumference, and femur length z-scores to identify multivariate trajectories of fetal growth. Moreover, sociodemographic variables, pregnancy characteristics, and birth outcomes based on trajectory membership were summarized. This study identified 4 multivariate trajectories of fetal growth among large-for-gestational age births: catch-up growth (n=28), proportional abdominal circumference–to–femur length growth (n=67), disproportional abdominal circumference–to–femur length growth (n=96), and consistently large (n=44). Fetuses in the “catch-up growth” group exhibited small relative sizes in midpregnancy (ie, below average head circumference, abdominal circumference, and femur length z-scores) and large relative sizes in late pregnancy. Growth among these births was driven by increases in relative abdominal circumference and head circumference sizes. Participants who delivered births assigned to this group were less likely to have normal glucose control (40% vs 65%–75%) and more likely to have pregestational diabetes mellitus (36% vs 10%–17%) than other large-for-gestational age subgroups. In addition, the babies in this trajectory group were more likely to have macrosomia (86% vs 67%–73%) and to be admitted to the neonatal intensive care unit (32% vs 14%–21%) than other large-for-gestational age subgroups. In contrast, babies in the “consistently large” group had the largest relative size for all growth parameters throughout gestation and experienced a lower risk of adverse birth outcomes than other large-for-gestational age subgroups. This study characterized several trajectories of fetal growth among large-for-gestational age births, which were related to different pregnancy characteristics and the distribution of adverse birth outcomes. Although the number of individuals within some trajectories was small, a subgroup that exhibited a catch-up growth phenotype during gestation was identified, which may be uniquely associated with exposure to pregestational diabetes mellitus and a higher risk of admission to the neonatal intensive care unit. These results have highlighted that the risk of adverse outcomes may not be evenly distributed across all large-for-gestational age births.