Analysis of longitudinal data in craniofacial research: some strategies

Growth of the anterior dental arch in black American children: a longitudinal study from 3 to 18 years of age

Dental arch size and form change systematically because of tooth emergence and because teeth migrate into shorter and broader arch forms in the deciduous dentition and again in the permanent dentition. The present longitudinal analysis describes changes in arch form in a cohort of 52 black American children (Nashville, Tenn) between the ages of 3 and 18 years. The anterior (incisor-canine) arch dimensions were analyzed. Incisor-to-canine depth remained static in both arches between 3 and 5 years but shortened significantly between 12 and 18 years. Intercanine width broadened significantly in both arches, first during the deciduous dentition, then again as the primary teeth were supplanted by the permanent incisors and canines. But there was no change in intercanine width once the permanent canines were in functional occlusion (approximately 11-18 years). These changes alter anterior arch form (the ratio depth/width). This index decreased significantly during the deciduous phase as the arches broadened; the index increased from 6 to 10 years as teeth were replaced, then again decreased during the duration of the study (approximately 10-18 years). Dimensions of these black American children all exceed comparable values for white American children, although the anterior shapes are indistinguishable. The present data focus attention on the dynamics of arch form in which considerable, protracted change occurs by physiologic migration, not just during the short phase of tooth replacement.

Multiple linear regression as an analytical tool in cephalometric studies

When the effect is studied of a factor like 'orthodontic therapy' on linear craniofacial growth, the concomitant consequence of age and gender on size cannot be ignored. The methodologically correct solution is division of the study group into smaller units, each of which is homogeneous with respect to age, gender, and therapy, and to compare these with matched controls. Yet, apart from matched controls being hard to find, this method of subdivision has the serious drawback that smaller groups decrease statistical power. A solution without the need to create sub-groups lies in the application of multiple linear regression analysis. It has been applied to biological data in other studies, but verification of the outcome has not been reported so far. Indeed, testing the mathematical assumptions underlying the regression model created unresolvable obstacles and, therefore, it was decided to perform verification by means of practical examples. Two separate tests for the applicability of the multiple linear regression method, on different data, with differing predictor sets, and with different control samples have been performed.