The Impact of Excluding Adverse Neonatal Outcomes on the Creation of Gestational Weight Gain Charts Among Women from Low- and Middle-income Countries with Normal and Overweight BMI

Rangel Bousquet Carrilho T 1 , Wang D 2 , Hutcheon JA 3 , Wang M 4 , Fawzi WW 5 , Kac G 6 Show all authors , members of the GWG Pooling Project Consortium

Affiliations 

  • 1 Nutritional Epidemiology Observatory, Josué de Castro Nutrition Institute, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil; Department of Obstetrics and Gynaecology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
  • 2 Department of Global and Community Health, College of Public Health, George Mason University, Fairfax, VA, United States
  • 3 Department of Obstetrics and Gynaecology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
  • 4 Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, United States; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, United States
  • 5 Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, United States; Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, United States; Department of Nutrition, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, United States
  • 6 Nutritional Epidemiology Observatory, Josué de Castro Nutrition Institute, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil. Electronic address: gilberto.kac@gmail.com
Am J Clin Nutr, 2024 Mar 22.
PMID: 38522618 DOI: 10.1016/j.ajcnut.2024.03.016

Abstract

BACKGROUND: Existing gestational weight gain (GWG) charts vary considerably in their choice of exclusion/inclusion criteria, and it is unclear to what extent these criteria create differences in the charts' percentile values.

OBJECTIVES: We aimed to establish the impact of including/excluding pregnancies with adverse neonatal outcomes when constructing GWG charts.

METHODS: This is an individual participant data analysis from 31 studies from low- and middle-income countries. We created a dataset that included all participants and a dataset restricted to those with no adverse neonatal outcomes: preterm < 37 wk, small or large for gestational age, low birth weight < 2500 g, or macrosomia > 4000 g. Quantile regression models were used to create GWG curves from 9 to 40 wk, stratified by prepregnancy BMI, in each dataset.

RESULTS: The dataset without the exclusion criteria applied included 14,685 individuals with normal weight and 4831 with overweight. After removing adverse neonatal outcomes, 10,479 individuals with normal weight and 3466 individuals with overweight remained. GWG distributions at 13, 27, and 40 wk were virtually identical between the datasets with and without the exclusion criteria, except at 40 wk for normal weight and 27 wk for overweight. For the 10th and 90th percentiles, the differences between the estimated GWG were larger for overweight (∼1.5 kg) compared with normal weight (<1 kg). Removal of adverse neonatal outcomes had minimal impact on GWG trajectories of normal weight. For overweight, the percentiles estimated in the dataset without the criteria were slightly higher than those in the dataset with the criteria applied. Nevertheless, differences were <1 kg and virtually nonexistent at the end of pregnancy.

CONCLUSIONS: Removing pregnancies with adverse neonatal outcomes has little or no influence on the GWG trajectories of individuals with normal and overweight.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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