Methods for modeling gestational weight gain: empirical application using electronic health record data from a safety net population

Methods for modeling gestational weight gain: empirical application using electronic health record data from a safety net population

Abstract Background Understanding the risks and effects of gestational weight gain (GWG) is a prominent area of perinatal research but approaches for quantifying GWG are evolving and remain underdeveloped, especially in clinical settings for underserved demographic subgroups. To fill this gap, we de...

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Main Authors: Anna Booman, Kimberly K. Vesco, Rachel Springer, Dang Dinh, Shuling Liu, Kristin Lyon-Scott, Miguel Marino, Jean O’Malley, Amy Palma, Teresa Schmidt, Jonathan M. Snowden, Kalera Stratton, Sarah-Truclinh Tran, Janne Boone-Heinonen
Format: Article
Language:English
Published: BMC 2025-01-01
Series:BMC Pregnancy and Childbirth
Subjects:
Gestational weight gain
Pregnancy
Understudied populations
Bias
Electronic health records
Online Access:https://doi.org/10.1186/s12884-025-07139-5
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