Cross-sectional data accurately model longitudinal growth in the craniofacial skeleton.

ABSTRACT: Dense, longitudinal sampling represents the ideal for studying biological growth. However, longitudinal samples are not typically possible, due to limits of time, prohibitive cost, or health concerns of repeat radiologic imaging. In contrast, cross-sectional samples have few such drawbacks, but it is not known how well estimates of growth milestones can be obtained from cross-sectional samples. The Craniofacial Growth Consortium Study (CGCS) contains longitudinal growth data for approximately 2000 individuals. Single samples from the CGCS for individuals representing cross-sectional data were used to test the ability to predict growth parameters in linear trait measurements separately by sex. Testing across a range of cross-sectional sample sizes from 5 to the full sample, we found that me

SUBMITTER: Middleton KM 

PROVIDER: S-EPMC10630296 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature