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Best Practice Model for Pediatric Research.

Cross-sectional relationships reported by Haapala et al. (1) provide welcome confirmation of previous studies of insulin resistance in young children, including the UK Early Bird (2) and the Australian LOOK studies (3), which among others have continued on with interventions (4) and longitudinal investigations (5). Haapala and colleagues supported revisiting cross-sectional relationships by asserting that previous studies measuring cardiorespiratory fitness may have elicited spurious relationships. Their rationale was that scaling fitness by body weight is not justified from a statistical or physiological perspective in children because it does not remove the effect of body size and composition (1). Debate continues as to the best way of converting an absolute measure such as physical performance into a measure of physical fitness suitable for comparing children of different heights, weights, and body composition. The process is complicated in that allometric relationships change during growth, but also by the nature of the test. For example, in contrast to seated cycle ergometry, a running test involves both vertical and horizontal vectors of whole-body momentum, requiring different scaling approaches. Researchers might consider statistical modeling as a means to overcome such problems. For example, general linear mixed modeling provides a powerful and flexible framework for explaining the variation of a response variable (e.g., insulin resistance) by a series of appropriately adjusted explanatory variables (e.g., physical performance, physical activity, body composition, height, weight, and socioeconomic status) within the same model, along with analyses of longitudinal relationships and intervention effects (4). The use of many pairwise comparisons by Haapala and coworkers is a statistical practice best avoided, as are statements such as “children with higher BF% and higher Wmax/LM and those with higher BF% and lower Wmax/LM had higher HOMA IR than children with lower BF% and higher Wmax/LM and those with lower BF% and lower Wmax/ LM” (1) (BF% is percent body fat; W, power; LM, lean mass; HOMA-IR, insulin resistance). Had a general modeling approach been used, this might have been written as “HOMA-IR in children is positively related to BF% irrespective of their CRF,” or even more informatively as “in two children of