Maternal weight latent trajectories and associations with adverse pregnancy outcomes using a smoothing mixture model

• Published in: Scientific reports Vol. 13; no. 1; p. 9011
• Main Authors: Faraji Azad, Shirin, Biglarian, Akbar, Rostami, Maryam, Bidhendi-Yarandi, Razieh
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 02.06.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 692/308/174; 692/308/3187; 692/308/409; Humanities and Social Sciences; International standards; Mathematical models; multidisciplinary; Neonates; Pregnancy; Risk reduction; Science; Science (multidisciplinary); Statistical analysis; Statistical models; Vitamin D; Vitamin deficiency; Weight
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-023-36312-z

Class membership is a critical issue in health data sciences. Different types of statistical models have been widely applied to identify participants within a population with heterogeneous longitudinal trajectories. This study aims to identify latent longitudinal trajectories of maternal weight associated with adverse pregnancy outcomes using smoothing mixture model (SMM). Data were collected from the Khuzestan Vitamin D Deficiency Screening Program in Pregnancy. We applied the data of 877 pregnant women living in Shooshtar city, whose weights during the nine months of pregnancy were available. In the first step, maternal weight was classified and participants were assigned to only one group for which the estimated trajectory is the most similar to the observed one using SMM; then, we examined the associations of identified trajectories with risk of adverse pregnancy endpoints by applying logistic regression. Three latent trajectories for maternal weight during pregnancy were identified and named as low, medium and high weight trajectories. Crude estimated odds ratio (OR) for icterus, preterm delivery, NICU admission and composite neonatal events shows significantly higher risks in trajectory 1 (low weight) compared to trajectory 2 (medium weight) by 69% (OR = 1.69, 95%CI 1.20, 2.39), 82% (OR = 1.82, 95%CI 1.14, 2.87), 77% (OR = 1.77, 95%CI 1.17, 2.43), and 85% (OR = 1.85, 95%CI 1.38, 2.76), respectively. Latent class trajectories of maternal weights can be accurately estimated using SMM. It is a powerful means for researchers to appropriately assign individuals to their class. The U-shaped curve of association between maternal weight gain and risk of maternal complications reveals that the optimum place for pregnant women could be in the middle of the growth curve to minimize the risks. Low maternal weight trajectory compared to high had even a significantly higher hazard for some neonatal adverse events. Therefore, appropriate weight gain is critical for pregnant women. Trial registration International Standard Randomized Controlled Trial Number (ISRCTN): 2014102519660N1; http://www.irct.ir/searchresult.php?keyword=&id=19660&number=1&prt=7805&total=10&m=1 (Archived by WebCite at http://www.webcitation.org/6p3lkqFdV ).