A Hattori chart analysis of body mass index in infants and children

Wells, Jck

doi:10.1038/sj.ijo.0801132

Cited by 212 publications

(198 citation statements)

References 29 publications

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“…Whereas several studies have reported strong correlations between BMI and %fat, 24,25 other studies have highlighted the wide variability in %fat present for a given BMI value. 26 Equally, %fat provides a problematic ranking of fatness as discussed previously. 22 Garrow and Webster 27 argued that when assessing the validity of BMI as a proxy for fatness, the optimum index of fatness to use as the reference is FMI, as both indices are adjusted for height.…”

Section: C Modelmentioning

confidence: 92%

A simplified approach to analysing bio-electrical impedance data in epidemiological surveys

et al. 2006

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Background: Bio-electrical impedance analysis (BIA) is widely used to estimate body composition. It is simple, quick and cheap, but less accurate than other methods. It has potential epidemiological value, but has conventionally required validation before application. Aims: To develop a simple method of expressing weight, height and impedance data that avoids the need for populationspecific validation equations in order to facilitate epidemiological application. Methods: Body composition was measured using the four-component model in young adults (43 males, 90 females). Impedance (R) was measured hand-foot and foot-foot. Lean mass and fat mass were adjusted for height to give lean mass index (LMI) and fat mass index (FMI). Based on theoretical principles, we generated the index 1/R, which provides an index of body water adjusted for height. Sex-specific regression models were used to investigate the relationships between (a) 1/R and LMI, and (b) body mass index (BMI) adjusted for 1/R and FMI. The success of this approach was evaluated in relation to the conventional BIA approach, using correlation analysis. Results: 1/R was a highly significant predictor of LMI. BMI adjusted for 1/R was a significant predictor of FMI. Our approach performed as well as the conventional approach for LMI, but not for FMI. Discussion: Direct use of BIA data, rather than their combination with population-specific equations for the prediction of total body water, proved successful at ranking individuals of both sexes in terms of LMI and FMI. The index 1/R may prove particularly valuable in epidemiological studies where ranking of LMI is required.

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Section: C Modelmentioning

confidence: 92%

A simplified approach to analysing bio-electrical impedance data in epidemiological surveys

et al. 2006

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“…In children, for example, individuals of the same age and gender have a twofold range of body fat mass for a given BMI value (Wells 2000), as shown in Fig. 1(a), a scenario also present in those who are obese .…”

Section: Indices Of Body Composition In Epidemiological Researchmentioning

confidence: 94%

“…Initial studies suggested that 'adiposity rebound', the age at which childhood BMI reaches a natural nadir before increasing again, was a significant predictor of later obesity (Rolland-Cachera et al 1987). More recent studies have suggested that such rebound is both a misnomer, in that it refers to BMI rather than adiposity per se (Wells, 2000), and also a statistical artefact since the time of rebound is inherently a function of initial BMI (Cole, 2004). A more appropriate interpretation of these data is simply that those gaining weight rapidly in childhood have a significantly increased risk of obesity subsequently.…”

Section: Postnatal Growth and Subsequent Body Compositionmentioning

confidence: 99%

Programming of body composition by early growth and nutrition

Wells¹,

Chomtho²,

Fewtrell³

2007

Proc. Nutr. Soc.

395

301

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There is now compelling evidence that growth patterns in early life are associated with risk of the metabolic syndrome in adulthood, although the relative importance of prenatal v. postnatal growth for such associations remains controversial. Body composition may play a key role in the ‘programming’ of such diseases, through itself being programmed by early growth, and perhaps also by being a mediator of the programming process. Early studies reporting positive associations between birth weight and adult BMI suggested a tendency for large babies to become obese adults. Such findings appeared contradictory to the many studies linking low birth weight with increased risk of the metabolic syndrome. Recent studies now indicate that birth weight is strongly predictive of later lean mass, and has a much weaker association with later fatness. Studies that link low birth weight with a more central adipose distribution in later life remain controversial, and require confirmation using more sophisticated methodologies. Findings for infant growth rate appear population-specific, with infant weight gain predicting subsequent lean mass in developing countries, but predicting subsequent fat mass and obesity in industrialised populations. Further studies are required on this issue, to ensure that appropriate public health policies are recommended for countries across the range of economic development. Although the links between early growth and later disease risk implicate early-life nutrition, either in utero or during infancy, few prospective studies have explored the influence of early diet on later body composition. Many studies have associated breast-feeding with a reduced prevalence of obesity categorised by BMI; however, the few studies directly evaluating childhood fatness provide little support for this hypothesis. Recent advances in the ability to measure body composition during the infant period offer a major opportunity to improve the understanding of the nutritional programming of body composition and its contribution, or lack thereof, to subsequent disease risk.

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“…body size during youth mainly reflect increases in lean mass rather than BF 36,37 . In this line, Brion et al 6 found a positive association between blood pressure (a single CVD risk factor) and lean mass after accounting for BF.…”

mentioning

confidence: 99%