Growth chart curves do not describe individual growth biology.

Growth reference tables present statistical distributions of size for age of individuals within a sample or population. As summaries of phenotypic variability at the group level, they document that individuals grow by different rates during similar time frames. The data are commonly fitted by mathematical functions to produce the convex curves of percentile distributions useful for infant and childhood growth monitoring. In this form, the growth chart appears to be a frame of reference for judging how well an individual infant/child is progressing through time by comparison with peers across ages. This has led to the assumption that individuals should track in these channels during growth. The interpolated lines between the statistical distributions of size for age at the level of the population do not, however, represent how individuals grow. Growing is an individual process characterized by nonlinear episodic saltatory increments that result in shifting size relationships among similarly aged peers over short time intervals. Data from a prospective, longitudinal study of infants illustrate the poor performance of growth chart curves as representations of individual growth. Clarification of the paradigms supporting perceptions of normal growth patterns is useful both practically and theoretically: growth chart patterns have important clinical sequelae when this informs feeding recommendations. Further characterization of individual growth patterns will contribute to increased understanding of both individual growth biology and the nature of adaptability.