Validity of self-reported pregravid weight
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Updated: Oct 5, 2026

Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
1Department of Maternal and Child Health, School of Hygiene and Public Health, Johns Hopkins University, Baltimore, MD.
Self-reported pregravid weight is a commonly used baseline indicator of nutritional status in prenatal weight gain studies. This study assesses the validity of self-reported pregravid weight in 1591 gravidas who entered into prenatal care within the first trimester of pregnancy from 1986 to 1988 at the University of Maryland Medical Systems. A significant difference of 4.3 lb (t = 25.56, P < 0.001) was found between self-reported pregravid weight and estimated pregravid weight. Limits of agreement (interval within which 95% of the differences between the self-reported and measured weights) were constructed by population characteristics. Multiple linear regression models with estimated pregravid weight as the dependent variable were estimated by self-reported pregravid weight, body weight, height, age, race, education, insurance status, and marital status groups. A model with self-reported pregravid weight as the sole independent variable was found to explain 88% of the variance in estimated pregravid weight. Results of this study suggest that the validity of self-report pregravid weight varies with sociodemographic and anthropometric factors. Adjustment by a simple regression equation can minimize error in self-reported pregravid weight.
Self-reported pregravid weight is a commonly used baseline indicator of nutritional status in prenatal weight gain studies. This study assesses the validity of self-reported pregravid weight in 1591 gravidas who entered into prenatal care within the first trimester of pregnancy from 1986 to 1988 at the University of Maryland Medical Systems. A significant difference of 4.3 lb (t = 25.56, P < 0.001) was found between self-reported pregravid weight and estimated pregravid weight. Limits of agreement (interval within which 95% of the differences between the self-reported and measured weights) were constructed by population characteristics. Multiple linear regression models with estimated pregravid weight as the dependent variable were estimated by self-reported pregravid weight, body weight, height, age, race, education, insurance status, and marital status groups. A model with self-reported pregravid weight as the sole independent variable was found to explain 88% of the variance in estimated pregravid weight. Results of this study suggest that the validity of self-report pregravid weight varies with sociodemographic and anthropometric factors. Adjustment by a simple regression equation can minimize error in self-reported pregravid weight.
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