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      Correlations among adiposity measures in school-aged children


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          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.


          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.


          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).


          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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          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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            Body mass index as a measure of adiposity among children and adolescents: a validation study.

            To test the hypothesis that in a healthy pediatric population body mass index (BMI) (kilograms per meter square) is a valid measure of fatness that is independent of age for both sexes. Total body fat (TBF) (in kilograms) and percent of body weight as fat (PBF) were estimated by dual energy x-ray absorptiometry (DXA) in 198 healthy Italian children and adolescents between 5 and 19 years of age. We developed multiple regression analysis models with TBF and percent body fat as dependent variables and BMI, age, and interaction terms as independent variables. Separate analyses were conducted for boys and girls. BMI was strongly associated with TBF (R2 = 0.85 and 0.89 for boys and girls, respectively) and PBF (R2 =0.63 and 0.69 for boys and girls, respectively). Confidence limits on BMI-fatness association were wide, with individuals of similar BMI showing large differences in TBF and in PBF. Age was a significant covariate in all regression models. Addition of nonlinear terms for BMI did not substantially increase the R2 for TBF and PBF models in boys and girls. Our results support the use of BMI as a fatness measure in groups of children and adolescents, although interpretation should be cautious when comparing BMI across groups that differ in age or when predicting a specific individual's TBF or PBF.
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              Comparison of dual-energy x-ray absorptiometric and anthropometric measures of adiposity in relation to adiposity-related biologic factors.

              Dual-energy x-ray absorptiometry (DXA) can provide accurate measurements of body composition. Few studies have compared the relative validity of DXA measures with anthropometric measures such as body mass index (BMI) and waist circumference (WC). The authors compared correlations of DXA measurements of total fat mass and fat mass percent in the whole body and trunk, BMI, and WC with obesity-related biologic factors, including blood pressure and levels of plasma lipids, C-reactive protein, and fasting insulin and glucose, among 8,773 adults in the National Health and Nutrition Examination Survey (1999-2004). Overall, the magnitudes of correlations of BMI and WC with the obesity-related biologic factors were similar to those of fat mass or fat mass percent in the whole body and trunk, respectively. These observations were largely consistent across different age, gender, and ethnic groups. In addition, in both men and women, BMI and WC demonstrated similar abilities to distinguish between participants with and without the metabolic syndrome in comparison with corresponding DXA measurements. These data indicate that the validity of simple anthropometric measures such as BMI and WC is comparable to that of DXA measurements of fat mass and fat mass percent, as evaluated by their associations with obesity-related biomarkers and prevalence of metabolic syndrome.

                Author and article information

                BMC Pediatr
                BMC Pediatr
                BMC Pediatrics
                BioMed Central
                24 June 2013
                : 13
                : 99
                [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
                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.

                : 27 March 2013
                : 17 June 2013
                Research Article

                adiposity, obesity, dxa, bmi


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