Adolescent Feet Are Not Small Adult Feet

Many arch structure classification methods exist, but arch structure may be influenced by factors such as age and physical activity. It is unknown if previous arch structure classifications from adult populations are appropriate for adolescents. The purpose of our study was to compare arch structure classifications between adolescent-specific and previously published classification systems.

We enrolled 141 uninjured adolescents who participated in long-distance running activities. We measured arch height index (AHI) for both feet in seated and standing positions and classified arch structure as cavus, rectus, or planus. We calculated kappa and percent agreement to compare arch structure classification for our participants with previously published classifications. We performed one-sample t tests to compare mean AHI values from our participants with previously published values. We performed Pearson correlation and percent agreement for arch structure classification for AHI measured in seated and standing for our participants.

We observed no to weak and unacceptable agreement (κ = -0.008 to 0.702; P < .001 to .77; 29-72%) for seated and standing AHI between our classification and most prior classifications. Our seated and standing mean AHI values differed from most prior studies (P < .001 to .99; d = 0.00-1.52). We observed a very large positive correlation (r = 0.90; P < .001) with moderate and acceptable classification agreement (κ = 0.641; P < .001; 83%) between mean AHI values measured in seated and standing positions.

Arch structure classification varied based on classification system and showed poor agreement between most previously reported classification systems. Mean AHI values were significantly different for adolescent runners in our study compared with most previously reported mean values. Researchers and clinicians may classify arch structure in a seated or standing position if position-specific criteria are applied. Special care should be taken before extrapolating classification systems originating from populations with different characteristics, such as age, sport participation, and health status.