Generating a representative anthropometric dataset for U.S. children and youth.

Area of Science:

• Pediatric anthropometry
• Biometric data analysis
• Human factors engineering

Background:

• Publicly available anthropometric data for U.S. children is limited and difficult to use for design.
• Existing data, like the National Health and Nutrition Examination Survey (NHANES), requires complex weighting and lacks detail for specific age groups.
• Critical percentile data for design, especially at the extremes, is often missing from current datasets.

Purpose of the Study:

• To develop and validate a method for synthesizing an unweighted anthropometric dataset for U.S. children and youth (ages 2-19).
• To address the scarcity of detailed anthropometric data needed for product and environmental design.
• To provide a foundation for creating updated and more accessible design-relevant datasets.

Main Methods:

• Generated continuous models for stature, body weight, and body mass index (BMI) distributions based on age and sex.
• Validated the synthesized data against published non-parametric quantiles from 2015-2018 NHANES data.
• Focused on creating an unweighted dataset for broader usability in design applications.

Main Results:

• The synthesized dataset demonstrated excellent agreement with published NHANES quantiles for stature, weight, and BMI.
• The method successfully models anthropometric distributions across a wide age range of children and youth.
• The generated data fills gaps in critical lower and upper percentile estimates.

Conclusions:

• The validated method provides a robust, synthesized anthropometric dataset for U.S. children and youth.
• This synthesized data serves as a valuable resource for design practitioners needing detailed anthropometric information.
• The approach allows for continuous updates as new NHANES data becomes available, ensuring relevance.