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The accuracy of parent-reported height and weight for 6-12 year old U.S. children
Davene R Wright1,2, Karen Glanz3,4, Trina Colburn5
1Department of Pediatrics, University of Washington School of Medicine, M/S CW8-6, PO Box 5371, Seattle, WA, 98145-5005, USA. Davene.Wright@seattlechildrens.org.
Insights
Correction factors improved height and weight concordance in parent-reported child measurements but did not enhance accuracy for identifying overweight or obese children. Further research with larger samples is recommended.
Area of Science:
- Pediatrics
- Public Health
- Biostatistics
Background:
- Parent-reported child measurements are often used in research but may differ from directly measured values.
- Previous studies have explored correlations between parent-reported and measured child BMI, height, and weight.
- Validating correction factors for parent-reported data is crucial for accurate epidemiological studies.
Purpose of the Study:
- To validate correction factors for parent-reported child height, weight, and BMI.
- To assess the accuracy of corrected parent-reported measures in classifying children's weight status.
Main Methods:
- Examined concordance using the Lin coefficient for parent-reported versus measured child height, weight, and BMI in 616 participants.
- Developed a correction model using 75% of the sample and applied it to the remaining 25% test sample.
- Assessed the accuracy of corrected measures for identifying overweight/obesity using sensitivity and specificity.
Main Results:
- Initial concordance between parent-reported and measured values was low for height (0.007), weight (-0.039), and BMI (-0.005).
- Correction factors improved concordance in the test sample to 0.752 for height, 0.616 for weight, and 0.227 for BMI.
- Sensitivity for detecting overweight/obesity decreased from 42.8% to 25.6%, while specificity improved from 79.5% to 88.6% with corrected measures.
Conclusions:
- Correction factors enhanced height and weight concordance but did not improve the sensitivity of parent-reported data for identifying child overweight and obesity.
- The study highlights limitations in using corrected parent-reported data for obesity classification.
- Future research requires larger, nationally representative samples to explore demographic variations in correction coefficients.
Background:
Previous studies have examined correlations between BMI calculated using parent-reported and directly-measured child height and weight. The objective of this study was to validate correction factors for parent-reported child measurements.
Methods:
Concordance between parent-reported and investigator measured child height, weight, and BMI (kg/m2) among participants in the Neighborhood Impact on Kids Study (n = 616) was examined using the Lin coefficient, where a value of ±1.0 indicates perfect concordance and a value of zero denotes non-concordance. A correction model for parent-reported height, weight, and BMI based on commonly collected demographic information was developed using 75% of the sample. This model was used to estimate corrected measures for the remaining 25% of the sample and measured concordance between correct parent-reported and investigator-measured values. Accuracy of corrected values in classifying children as overweight/obese was assessed by sensitivity and specificity.
Results:
Concordance between parent-reported and measured height, weight and BMI was low (0.007, - 0.039, and - 0.005 respectively). Concordance in the corrected test samples improved to 0.752 for height, 0.616 for weight, and 0.227 for BMI. Sensitivity of corrected parent-reported measures for predicting overweight and obesity among children in the test sample decreased from 42.8 to 25.6% while specificity improved from 79.5 to 88.6%.
Conclusions:
Correction factors improved concordance for height and weight but did not improve the sensitivity of parent-reported measures for measuring child overweight and obesity. Future research should be conducted using larger and more nationally-representative samples that allow researchers to fully explore demographic variance in correction coefficients.
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