Dissociation between skinfold thickness changes and growth of adipose tissue volume in children and youth

The relationships between skeletal age (SA) and limb composition (arms, legs, and all four limbs) in terms of fat mass (FM), fat‐free mass (FFM), muscle mass (MM) and bone mineral content (BMC) were investigated in 55 males and 53 females aged 9–15 years. The Fels method was used to assess hand‐wrist SAs which were expressed as SA/chronological age (SA/CA). The limb composition data were obtained from a Lunar dual‐energy x‐ray absorptiometer using 3.6z software. The means for the limb composition variables increased gradually with age except in males for whom FM decreased from 12 to 13 years, and FFM and MM increased markedly from 13 to 14 years. There were similar findings when the limb composition data were expressed as percentages of body weight. All of the regressions of SA/CA on limb composition variables had positive slopes. Each of the slopes was significant for males, but nonsignificant for females. © 1996 Wiley‐Liss, Inc.

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Relationship of skeletal age to limb composition during pubescence

Roche

Wellens

Guo

1996

Am. J. Hum. Biol.

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Anthropometric measurement error and the assessment of nutritional status

1999

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Anthropometry involves the external measurement of morphological traits of human beings. It has a widespread and important place in nutritional assessment, and while the literature on anthropometric measurement and its interpretation is enormous, the extent to which measurement error can influence both measurement and interpretation of nutritional status is little considered. In this article, different types of anthropometric measurement error are reviewed, ways of estimating measurement error are critically evaluated, guidelines for acceptable error presented, and ways in which measures of error can be used to improve the interpretation of anthropometric nutritional status discussed. Possible errors are of two sorts; those that are associated with: (1) repeated measures giving the same value (unreliability, imprecision, undependability); and (2) measurements departing from true values (inaccuracy, bias). Imprecision is due largely to observer error, and is the most commonly used measure of anthropometric measurement error. This can be estimated by carrying out repeated anthropometric measures on the same subjects and calculating one or more of the following: technical error of measurement (TEM); percentage TEM, coefficient of reliability (R), and intraclass correlation coefficient. The first three of these measures are mathematically interrelated. Targets for training in anthropometry are at present far from perfect, and further work is needed in developing appropriate protocols for nutritional anthropometry training. Acceptable levels of measurement error are difficult to ascertain because TEM is age dependent, and the value is also related to the anthropometric characteristics of the group or population under investigation. R > 0·95 should be sought where possible, and reference values of maximum acceptable TEM at set levels of R using published data from the combined National Health and Nutrition Examination Surveys I and II (Frisancho, 1990) are given. There is a clear hierarchy in the precision of different nutritional anthropometric measures, with weight and height being most precise. Waist and hip circumference show strong between-observer differences, and should, where possible, be carried out by one observer. Skinfolds can be associated with such large measurement error that interpretation is problematic. Ways are described in which measurement error can be used to assess the probability that differences in anthropometric measures across time within individuals are due to factors other than imprecision. Anthropometry is an important tool for nutritional assessment, and the techniques reported here should allow increased precision of measurement, and improved interpretation of anthropometric data.

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Dissociation between skinfold thickness changes and growth of adipose tissue volume in children and youth

Cited by 2 publications

References 11 publications

Relationship of skeletal age to limb composition during pubescence

Relationship of skeletal age to limb composition during pubescence

Anthropometric measurement error and the assessment of nutritional status

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