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Maternal and Child Health Journal

, Volume 18, Issue 7, pp 1667–1674 | Cite as

Validity of Prepregnancy Weight Status Estimated from Self-reported Height and Weight

  • Dayeon Shin
  • Hwan Chung
  • Lorraine Weatherspoon
  • Won O. SongEmail author
Article

Abstract

The Institute of Medicine’s gestational weight gain guidelines are intended to reduce pregnancy complications, poor birth outcomes and excessive postpartum weight retention. The specific weight gain guidelines vary by prepregnancy weight status. We evaluated the validity of prepregnancy weight status (underweight, normal weight, overweight and obesity) classified from self-reported prepregnancy height and weight in reference to those from measured data during the first trimester of pregnancy and imputed data for both pregnant and age-matched non-pregnant women included in the National Health and Nutrition Examination Survey 2003–2006. Self-reported prepregnancy weight status was validated by two ideal references: imputed data with the number of imputations as 10 (n = 5,040) using the data of age-matched non-pregnant women who had both self-reported and measured data, and weight status based on height and weight measured during the first trimester (n = 95). Mean differences, Pearson’s correlations (r), and Kappa statistics (κ) were used to examine the strength of agreement between self-reported data and the two reference measures. Mean (standard error of the mean) differences between self-reported versus imputed prepregnancy weight was −1.7 (0.1) kg with an r = 0.98 (p < 0.001), and κ = 0.78 which indicate substantial agreement for the 504 pregnant women. Mean (SEM) differences between self-reported prepregnancy weight versus measured weight in the first trimester was −2.3 (0.7) kg with r = 0.98 (p < 0.001), and κ = 0.76, which also showed substantial agreements in 95 pregnant women. Prepregnancy weight status classified based on self-reported prepregnancy height and weight was valid.

Keywords

Validity Self-reports Prepregnancy weight status 

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Dayeon Shin
    • 1
  • Hwan Chung
    • 2
  • Lorraine Weatherspoon
    • 1
  • Won O. Song
    • 1
    Email author
  1. 1.Department of Food Science and Human NutritionMichigan State UniversityEast LansingUSA
  2. 2.Department of StatisticsKorea UniversitySeoulKorea

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