On correlations between adjacent velocities and accelerations in longitudinal growth data

Abstract

Correlations are examined between adjacent velocity and acceleration growth in stature, weight and skinfold thickness in a group of adolescent boys measured approximately quarterly. It is concluded that some substantial component of the variability behaves rather like measurement error, and this is likely to represent negative feedback homeostasis.

Pulsatile growth pattern during catch‐up growth in childhood coeliac disease

“…The plot of sequential increments in randomly generated series of numbers does not describe any pattern, although it may generate significant correlations between successive accelerations (9). Our peaks do hold the filter of the worst estimate of the velocity error.…”

“…This finding does not support the hypothesis that pulsatility is only present during catch-up growth. Several lines of evidence have been presented on the presence of a pulsatile velocity pattern during normal growth of children for height (9,11,12) leg length (13) and weight (14). Recently, the pulsatile pattern of normal growth was suggested by a study which appeared in Science, describing "saltation and stasis" in the growth increments of 10 healthy infants measured weekly and 21 measured more frequently (1 5).…”

New analytic approaches in auxology

“…Using their novel method, the authors are able to establish community-level "target" effects, differences in maturational timing, and previous growth tempo as significant determinants of the growth process (see also ref. 24). The ability of the method they propose to deal with this more complex structure of growth determinants while simultaneously testing more specific ecological hypotheses has the potential to underpin significant advances in growth research.…”

“…In summary, they propose a regression-based framework that permits direct testing of hypotheses about the dynamics of growth. Hypothesis testing may not be accomplished using simple descriptive methods such as curve fitting (27), and more complex probabilistic frameworks such as those used in multilevel modeling or models based on nonlinear dynamics suffer challenges related to interpretability (24)(25)(26). The approach of Aßmann and Hermanussen permits the analysis of individual differences in growth tempo and maturity status while facilitating hypothesis testing about ecologic effects.…”

“…Although other methods for analyzing ecological complexity and examining causation in auxology have been presented in the forms of multilevel modeling (24,25) and applications of nonlinear dynamics (26), this article presents a compelling and straightforward framework for analyzing longitudinal growth data subject to serial autocorrelation and missing data (both important challenges in longitudinal growth studies). In summary, they propose a regression-based framework that permits direct testing of hypotheses about the dynamics of growth.…”