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Updated: May 11, 2026
09:36
Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Underestimation of adolescent obesity
Alison M Buttenheim1, Noreen Goldman, Anne R Pebley
1School of Nursing, University of Pennsylvania, Philadelphia, PA 19104, USA. abutt@nursing.upenn.edu
Nursing Research
|May 3, 2013
Summary
Adolescent obesity estimates are skewed by nonresponse bias in self-reported height and weight. Accounting for nonresponse reveals higher obesity prevalence, especially in younger teens.
Area of Science:
- Public Health
- Epidemiology
- Child Health
Background:
- Adolescent obesity prevalence estimates rely on self-reported height and weight.
- Previous studies overlooked potential bias from nonresponse in self-reported data.
- Selective nonresponse can significantly impact obesity prevalence calculations.
Purpose of the Study:
- To evaluate the impact of selective nonresponse in self-reported height and weight on adolescent obesity estimates.
- To determine if nonresponse bias affects obesity prevalence calculations differently across age groups.
Main Methods:
- Analysis of 613 adolescents (ages 12-17) from the Los Angeles Family and Neighborhood Survey (2006-2008).
- Comparison of obesity prevalence using self-reported data versus measured height and weight.
- Assessment of obesity estimates with and without accounting for nonresponse bias.
Main Results:
- Younger adolescents who did not self-report height and weight had higher measured obesity prevalence (40%) than those who did (30%).
- Self-reported data underestimated measured obesity prevalence by 12 percentage points when nonresponse was considered, versus 9 percentage points when not.
- Findings remained consistent across different child growth references.
Conclusions:
- Selective nonresponse in self-reported height and weight significantly affects adolescent obesity surveillance.
- Public health strategies for adolescent obesity prevention must incorporate adjustments for nonresponse bias.
- Further research with nationally representative samples is recommended to validate these findings.
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