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Correlations among adiposity measures in school-aged children

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      Abstract

      Background

      Given that it is not feasible to use dual x-ray absorptiometry (DXA) or other reference methods to measure adiposity in all pediatric clinical and research settings, it is important to identify reasonable alternatives. Therefore, we sought to determine the extent to which other adiposity measures were correlated with DXA fat mass in school-aged children.

      Methods

      In 1110 children aged 6.5-10.9 years in the pre-birth cohort Project Viva, we calculated Spearman correlation coefficients between DXA (n=875) and other adiposity measures including body mass index (BMI), skinfold thickness, circumferences, and bioimpedance. We also computed correlations between lean body mass measures.

      Results

      50.0% of the children were female and 36.5% were non-white. Mean (SD) BMI was 17.2 (3.1) and total fat mass by DXA was 7.5 (3.9) kg. DXA total fat mass was highly correlated with BMI (r s=0.83), bioimpedance total fat (r s=0.87), and sum of skinfolds (r s=0.90), and DXA trunk fat was highly correlated with waist circumference (r s=0.79). Correlations of BMI with other adiposity indices were high, e.g., with waist circumference (r s=0.86) and sum of subscapular plus triceps skinfolds (r s=0.79). DXA fat-free mass and bioimpedance fat-free mass were highly correlated (r s=0.94).

      Conclusions

      In school-aged children, BMI, sum of skinfolds, and other adiposity measures were strongly correlated with DXA fat mass. Although these measurement methods have limitations, BMI and skinfolds are adequate surrogate measures of relative adiposity in children when DXA is not practical.

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      Most cited references 30

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      Anthropometric measurement error and the assessment of nutritional status.

      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 of 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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        Measuring body composition.

        Several aspects of body composition, in particular the amount and distribution of body fat and the amount and composition of lean mass, are now understood to be important health outcomes in infants and children. Their measurement is increasingly considered in clinical practice; however, paediatricians are often unsure as to which techniques are appropriate and suitable for application in specific contexts. This article summarises the pros and cons of measurement technologies currently available for paediatric application. Simple techniques are adequate for many purposes, and simple regional data may often be of greater value than "whole body" values obtained by more sophisticated approaches.
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          Waist circumference and waist-to-height ratio are better predictors of cardiovascular disease risk factors in children than body mass index

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            Author and article information

            Affiliations
            [1 ]Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
            [2 ]Department of Nutrition, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
            [3 ]Channing Division of Network Medicine, Brigham and Women’s Hospital, 181 Longwood Avenue, Boston, MA 02115, USA
            [4 ]Department of Population Medicine, Obesity Prevention Program, Harvard Medical School and Harvard Pilgrim Health Care Institute, 133 Brookline Avenue, 3rd Floor, Boston, MA 02215, USA
            Contributors
            Journal
            BMC Pediatr
            BMC Pediatr
            BMC Pediatrics
            BioMed Central
            1471-2431
            2013
            24 June 2013
            : 13
            : 99
            23799991
            3693882
            1471-2431-13-99
            10.1186/1471-2431-13-99
            Copyright ©2013 Boeke et al.; licensee BioMed Central Ltd.

            This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

            Categories
            Research Article

            Pediatrics

            adiposity, obesity, dxa, bmi

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