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      Tri-Ponderal Mass Index vs. Fat Mass/Height 3 as a Screening Tool for Metabolic Syndrome Prediction in Colombian Children and Young People

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          Abstract

          Tri-ponderal mass index (TMI) and fat mass index (FMI) have been proposed as alternative approaches for assessing body fat since BMI does not ensure an accurate screening for obesity and overweight status in children and adolescents. This study proposes thresholds of the TMI and FMI for the prediction of metabolic syndrome (MetS) in children and young people. For this purpose, a cross-sectional study was conducted on 4673 participants (57.1% females), who were 9–25 years of age. As part of the study, measurements of the subjects’ weight, waist circumference, serum lipid indices, blood pressure and fasting plasma glucose were taken. Body composition was measured by bioelectrical impedance analysis (BIA). The TMI and FMI were calculated as weight (kg)/height (m 3) and fat mass (kg)/height (m 3), respectively. Following the International Diabetes Federation (IDF) definition, MetS is defined as including three or more metabolic abnormalities. Cohort-specific thresholds were established to identify Colombian children and young people at high risk of MetS. The thresholds were applied to the following groups: (i) a cohort of children where the girls’ TMI ≥ 12.13 kg/m 3 and the boys’ TMI ≥ 12.10 kg/m 3; (ii) a cohort of adolescents where the girls’ TMI ≥ 12.48 kg/m 3 and the boys’ TMI ≥ 11.19 kg/m 3; (iii) a cohort of young adults where the women’s TMI ≥ 13.21 kg/m 3 and the men’s TMI ≥ 12.19 kg/m 3. The FMI reference cut-off values used for the different groups were as follows: (i) a cohort of children where the girls’ FMI ≥ 2.59 fat mass/m 3 and the boys’ FMI ≥ 1.98 fat mass/m 3; (ii) a cohort of adolescents where the girls’ FMI ≥ 3.12 fat mass/m 3 and the boys’ FMI ≥ 1.46 fat mass/m 3; (iii) a cohort of adults where the women’s FMI ≥ 3.27 kg/m 3 and the men’s FMI ≥ 1.65 kg/m 3. Our results showed that the FMI and TMI had a moderate discriminatory power to detect MetS in Colombian children, adolescents, and young adults.

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          Estimation of the Youden Index and its associated cutoff point.

          The Youden Index is a frequently used summary measure of the ROC (Receiver Operating Characteristic) curve. It both, measures the effectiveness of a diagnostic marker and enables the selection of an optimal threshold value (cutoff point) for the marker. In this paper we compare several estimation procedures for the Youden Index and its associated cutoff point. These are based on (1) normal assumptions; (2) transformations to normality; (3) the empirical distribution function; (4) kernel smoothing. These are compared in terms of bias and root mean square error in a large variety of scenarios by means of an extensive simulation study. We find that the empirical method which is the most commonly used has the overall worst performance. In the estimation of the Youden Index the kernel is generally the best unless the data can be well transformed to achieve normality whereas in estimation of the optimal threshold value results are more variable.
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            Prevalence of the metabolic syndrome in American adolescents: findings from the Third National Health and Nutrition Examination Survey.

            Metabolic syndrome (MetS) is defined by the Third Report of the Adult Treatment Panel (ATP III) using criteria easily applied by clinicians and researchers. There is no standard pediatric definition. We defined pediatric MetS using criteria analogous to ATP III as > or =3 of the following: (1) fasting triglycerides > or =1.1 mmol/L (100 mg/dL); (2) HDL or =6.1 mmol/L (110 mg/dL); (4) waist circumference >75th percentile for age and gender; and (5) systolic blood pressure >90th percentile for gender, age, and height. MetS prevalence in US adolescents was estimated with the Third National Health and Nutritional Survey 1988 to 1994. Among 1960 children aged > or =12 years who fasted > or =8 hours, two thirds had at least 1 metabolic abnormality, and nearly 1 in 10 had MetS. The racial/ethnic distribution was similar to adults: Mexican-Americans, followed by non-Hispanic whites, had a greater prevalence of MetS compared with non-Hispanic blacks (12.9%, [95% CI 10.4% to 15.4%]; 10.9%, [95% CI 8.4% to 13.4%]; and 2.5%, [95% CI 1.3% to 3.7%], respectively). Nearly one third (31.2% [95% CI 28.3% to 34.1%]) of overweight/obese adolescents had MetS. Our definition of pediatric MetS, designed to be closely analogous to ATP III, found MetS is common in adolescents and has a similar racial/ethnic distribution to adults in this representative national sample. Because childhood MetS likely tracks into adulthood, early identification may help target interventions to improve future cardiovascular health.
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              Statistics review 13: Receiver operating characteristic curves

              This review introduces some commonly used methods for assessing the performance of a diagnostic test. The sensitivity, specificity and likelihood ratio of a test are discussed. The uses of the receiver operating characteristic curve and the area under the curve are explained.
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                Author and article information

                Journal
                Nutrients
                Nutrients
                nutrients
                Nutrients
                MDPI
                2072-6643
                27 March 2018
                April 2018
                : 10
                : 4
                : 412
                Affiliations
                [1 ]Centro de Estudios Para la Medición de la Actividad Física CEMA, Escuela de Medicina y Ciencias de la Salud, Universidad del Rosario, Bogotá 111221, Colombia; jorge.correa@ 123456urosario.edu.co
                [2 ]Grupo GRINDER, Programa de Educación Física y Deportes, Universidad del Valle, Santiago de Cali 76001, Colombia; hugo.carrillo@ 123456correounivalle.edu.co
                [3 ]Grupo Interdisciplinario de Estudios en Salud y Sociedad (GIESS), Institución Universitaria Escuela Nacional del Deporte, Santiago de Cali 76001, Colombia
                [4 ]Departamento de Enfermería, Facultad de Ciencias de la Salud, Avda. De la Ilustración, 60, University of Granada, 18016 Granada, Spain; emigoji@ 123456ugr.es (E.G.-J.); jschmidt@ 123456ugr.es (J.S.-R.); macoro@ 123456ugr.es (M.C.-R.)
                [5 ]Grupo CTS-436, Adscrito al Centro de Investigación Mente, Cerebro y Comportamiento (CIMCYC), University of Granada, 18071 Granada, Spain
                [6 ]Laboratorio de Ciencias de la Actividad Física, el Deporte y la Salud, Facultad de Ciencias Médicas, Universidad de Santiago de Chile, USACH, Santiago 7500618, Chile; antonio.garcia.h@ 123456usach.cl
                [7 ]Grupo de Ejercicio Físico y Deportes, Vicerrectoría de Investigaciones, Universidad Manuela Beltrán, Bogotá 110231, Colombia; katherine.gonzalez@ 123456docentes.umb.edu.co
                Author notes
                [* ]Correspondence: robin640@ 123456hotmail.com or robinson.ramirez@ 123456urosario.edu.co ; Tel.: +57-1-297-0200 (ext. 3428)
                Author information
                https://orcid.org/0000-0003-3075-6960
                https://orcid.org/0000-0001-5103-6028
                https://orcid.org/0000-0001-9165-4349
                https://orcid.org/0000-0002-1397-7182
                Article
                nutrients-10-00412
                10.3390/nu10040412
                5946197
                29584641
                944655c7-2369-4355-94b0-44c830f570ce
                © 2018 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 06 February 2018
                : 21 March 2018
                Categories
                Article

                Nutrition & Dietetics
                adiposity,fat mass,tri-ponderal mass index,fat mass index,metabolic syndrome,children

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