Maternal and Child Health Journal

, Volume 16, Issue 1, pp 197–202

Misreport of Gestational Weight Gain (GWG) in Birth Certificate Data

  • Charmaine Smith Wright
  • Mark Weiner
  • Russ Localio
  • Lihai Song
  • Peter Chen
  • David Rubin
Article

DOI: 10.1007/s10995-010-0724-2

Cite this article as:
Wright, C.S., Weiner, M., Localio, R. et al. Matern Child Health J (2012) 16: 197. doi:10.1007/s10995-010-0724-2

Abstract

Birth certificates are potentially a valuable source of information for studying gestational weight gain (GWG) during pregnancy, particularly important given new Institute of Medicine (IOM) guidelines. We examined factors associated with the accuracy of maternal GWG self-report by linking the gold standard obstetric electronic medical record (EMR) of women from a large urban practice to state birth certificates. Primary outcomes included maternal under-reporting of GWG (>10 lbs below the EMR), accurate reporting (within 10 lbs), and over-reporting (>10 lbs above EMR). Data were stratified across categories of pre-pregnancy body mass index (BMI) and the actual GWG IOM categories (inadequate, adequate, and excessive) acquired in the clinical setting and recorded in the EMR. Among 1,223 women, mean (SD) age was 27.4 (6.2) years, mean (SD) BMI was 28.2 (8.1) kg/m2, and mean GWG was 26.0 (20.2) pounds. The majority of women with normal BMI (<25 kg/m2) and adequate GWG reported GWG accurately (78.8%), more so than any other group. After adjusting for age, race, insurance status, and number of prenatal visits, among women with actual adequate GWG, women with high BMI (≥25 kg/m2) were more likely to over-report GWG than women with normal BMI (RR 4.7, 95% CI 2.6–8.4). In patients with normal BMI, women with excessive GWG were more likely to under-report than women with adequate GWG (RR 6.0, 95% CI 3.0–12.1). Such findings raise concern for systematic bias that would limit the use of birth certificate data for studying population trends in GWG.

Keywords

Maternal obesity Gestational weight gain Vital statistics 

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Charmaine Smith Wright
    • 1
    • 2
    • 3
  • Mark Weiner
    • 2
  • Russ Localio
    • 2
  • Lihai Song
    • 3
  • Peter Chen
    • 4
  • David Rubin
    • 3
  1. 1.Robert Wood Johnson Clinical Scholar ProgramUniversity of PennsylvaniaPhiladelphiaUSA
  2. 2.Division of General Internal MedicineUniversity of PennsylvaniaPhiladelphiaUSA
  3. 3.Division of General PediatricsChildren’s Hospital of PhiladelphiaPhiladelphiaUSA
  4. 4.Department of Obstetrics and GynecologyUniversity of PennsylvaniaPhiladelphiaUSA

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