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


Journal

American journal of obstetrics and gynecology
ISSN: 1097-6868
Titre abrégé: Am J Obstet Gynecol
Pays: United States
ID NLM: 0370476

Informations de publication

Date de publication:
03 2023
Historique:
received: 22 07 2022
revised: 07 10 2022
accepted: 07 10 2022
pmc-release: 01 03 2024
pubmed: 15 10 2022
medline: 25 2 2023
entrez: 14 10 2022
Statut: ppublish

Résumé

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.

Sections du résumé

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.

Identifiants

pubmed: 36241081
pii: S0002-9378(22)00811-0
doi: 10.1016/j.ajog.2022.10.006
pmc: PMC9974610
mid: NIHMS1847688
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Intramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

340.e1-340.e20

Subventions

Organisme : Intramural NIH HHS
ID : ZIA ES103321
Pays : United States

Commentaires et corrections

Type : CommentIn

Informations de copyright

Published by Elsevier Inc.

Références

Pediatr Endocrinol Rev. 2005 Mar;2(3):372-7
pubmed: 16429113
Diabetes Care. 2016 Jun;39(6):982-7
pubmed: 27208333
PLoS One. 2016 Jan 05;11(1):e0146532
pubmed: 26731406
Obstet Gynecol. 2020 Jan;135(1):e18-e35
pubmed: 31856124
Ann Intern Med. 2007 Oct 16;147(8):W163-94
pubmed: 17938389
Obstet Gynecol. 2013 Aug;122(2 Pt 1):248-254
pubmed: 23969791
Pediatr Res. 2017 Aug;82(2):305-316
pubmed: 28445454
Lancet Diabetes Endocrinol. 2020 Apr;8(4):292-300
pubmed: 32135135
Diabetes Care. 2018 Jul;41(7):1362-1369
pubmed: 29934479
Epidemiology. 2021 Nov 1;32(6):860-867
pubmed: 34270495
Australas J Ultrasound Med. 2014 Feb;17(1):38-44
pubmed: 28191205
Am J Obstet Gynecol. 1985 Feb 1;151(3):333-7
pubmed: 3881966
Early Hum Dev. 2009 Oct;85(10):653-8
pubmed: 19786331
BMC Med. 2018 Nov 6;16(1):203
pubmed: 30396349
Stat Methods Med Res. 2018 Jul;27(7):2015-2023
pubmed: 29846144
Front Psychol. 2018 Feb 22;9:130
pubmed: 29520242
Ultrasound Obstet Gynecol. 2010 Dec;36(6):735-42
pubmed: 20521236
Am J Obstet Gynecol. 2023 Mar;228(3):334.e1-334.e21
pubmed: 36027952
Epidemiology. 2021 Sep 1;32(5):664-671
pubmed: 34086648
Diabetologia. 2016 Jun;59(6):1089-94
pubmed: 26995651
Best Pract Res Clin Endocrinol Metab. 2008 Feb;22(1):173-90
pubmed: 18279787
Biometrics. 2009 Dec;65(4):1233-42
pubmed: 19432784
Sci Rep. 2020 Feb 7;10(1):2157
pubmed: 32034195
Hypertens Res. 2013 Aug;36(8):725-35
pubmed: 23595042
Am J Obstet Gynecol. 2018 Feb;218(2S):S630-S640
pubmed: 29422205
Int J Epidemiol. 2001 Dec;30(6):1233-41
pubmed: 11821313
Ultrasound Obstet Gynecol. 2005 Jan;25(1):80-9
pubmed: 15505877
Stat Methods Med Res. 2017 Oct;26(5):2424-2436
pubmed: 26265768
Eur J Epidemiol. 2021 Oct;36(10):985-991
pubmed: 34661814
JAMA. 2020 Aug 18;324(7):700-701
pubmed: 32808993
Ultrasound Obstet Gynecol. 2013 Apr;41(4):390-7
pubmed: 22744817
Am J Obstet Gynecol. 2012 Nov;207(5):407.e1-7
pubmed: 22981320
Am J Epidemiol. 2008 Apr 1;167(7):786-92
pubmed: 18343882

Auteurs

Paige A Bommarito (PA)

Epidemiology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, Research Triangle Park, NC.

David E Cantonwine (DE)

Division of Maternal-Fetal Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.

Danielle R Stevens (DR)

Epidemiology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, Research Triangle Park, NC.

Barrett M Welch (BM)

School of Public Health, University of Nevada, Reno, Reno, NV.

Angel D Davalos (AD)

Biostatistics and Computational Biology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, Research Triangle Park, NC.

Shanshan Zhao (S)

Biostatistics and Computational Biology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, Research Triangle Park, NC.

Thomas F McElrath (TF)

Division of Maternal-Fetal Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.

Kelly K Ferguson (KK)

Epidemiology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, Research Triangle Park, NC. Electronic address: kelly.ferguson2@nih.gov.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH