Related Experiment Video
Updated: Jul 6, 2026

Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts
Published on: January 29, 2018
The missing data problem in birth weight percentiles and thresholds for "small-for-gestational-age"
Jennifer A Hutcheon1, Robert W Platt
1Department of Epidemiology and Biostatistics, McGill University Faculty of Medicine, Montreal, Quebec, Canada. jennifer.hutcheon@mail.mcgill.ca
Conventional weight-for-gestational-age charts for identifying small-for-gestational-age infants are biased due to missing fetal weight data. New methods are needed for unbiased assessment of fetal growth and restriction risks.
Area of Science:
- Perinatal epidemiology
- Fetal growth research
Background:
- Weight-for-gestational-age charts traditionally define small-for-gestational-age infants using livebirth data.
- These charts have significant limitations for preterm infants due to missing in-utero fetal weight data.
Purpose of the Study:
- To address the bias in current small-for-gestational-age definitions.
- To propose methods for unbiased perinatal weight percentile calculation.
Main Methods:
- Critically evaluate existing weight-for-gestational-age chart methodologies.
- Discuss the impact of missing fetal weight data on etiologic studies.
- Recommend standard epidemiologic approaches for handling missing data.
Main Results:
- Livebirth-based references introduce considerable bias in etiologic studies of fetal growth restriction.
- Missing data on in-utero fetal weights are a major limitation, especially for preterm infants.
Conclusions:
- Standard epidemiologic methods for missing data are crucial.
- Unbiased perinatal weight percentiles are necessary for accurate fetal growth assessment.
- Improved methods will enhance understanding of fetal growth restriction risks.
Related Concept Videos
z Scores and Area Under the Curve
Regression Toward the Mean
One-Way ANOVA: Unequal Sample Sizes
Pathophysiology of Diabetes
Type 1 diabetes is characterized by autoimmune-mediated destruction of pancreatic β cells, with environmental factors potentially triggering this process in genetically susceptible individuals. Despite many not having a family history, certain genes increase susceptibility, suggesting a...
Wald-Wolfowitz Runs Test II
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and 0s. In...
Normal Distribution
