array:24 [ "pii" => "S2387020623001407" "issn" => "23870206" "doi" => "10.1016/j.medcle.2022.09.025" "estado" => "S300" "fechaPublicacion" => "2023-05-12" "aid" => "6133" "copyright" => "Elsevier España, S.L.U.. All rights reserved" "copyrightAnyo" => "2022" "documento" => "article" "crossmark" => 1 "subdocumento" => "fla" "cita" => "Med Clin. 2023;160:379-84" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "Traduccion" => array:1 [ "es" => array:19 [ "pii" => "S0025775322006224" "issn" => "00257753" "doi" => "10.1016/j.medcli.2022.09.024" "estado" => "S300" "fechaPublicacion" => "2023-05-12" "aid" => "6133" "copyright" => "Elsevier España, S.L.U." "documento" => "article" "crossmark" => 1 "subdocumento" => "fla" "cita" => "Med Clin. 2023;160:379-84" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "es" => array:13 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original</span>" "titulo" => "Índice de masa triponderal y marcadores de riesgo metabólico en niños y adolescentes con obesidad" "tienePdf" => "es" "tieneTextoCompleto" => "es" "tieneResumen" => array:2 [ 0 => "es" 1 => "en" ] "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "379" "paginaFinal" => "384" ] ] "titulosAlternativos" => array:1 [ "en" => array:1 [ "titulo" => "Triponderal mass index and markers of metabolic risk in children and adolescents with obesity" ] ] "contieneResumen" => array:2 [ "es" => true "en" => true ] "contieneTextoCompleto" => array:1 [ "es" => true ] "contienePdf" => array:1 [ "es" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figura 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1027 "Ancho" => 1675 "Tamanyo" => 93935 ] ] "descripcion" => array:1 [ "es" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Evolución a lo largo de la edad del valor medio absoluto del índice de masa corporal (IMC) y del índice de masa triponderal (IMT).</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Enrique Palomo Atance, Francisco Javier Caballero Mora, David Espadas Maciá, Mercedes Marbán Calzón, Pilar Sevilla Ramos, Lourdes García Villaescusa, María Jesús Dabad Moreno, José Ramón Muñoz-Rodríguez, Rafael Ruiz Cano" "autores" => array:9 [ 0 => array:2 [ "nombre" => "Enrique" "apellidos" => "Palomo Atance" ] 1 => array:2 [ "nombre" => "Francisco Javier" "apellidos" => "Caballero Mora" ] 2 => array:2 [ "nombre" => "David" "apellidos" => "Espadas Maciá" ] 3 => array:2 [ "nombre" => "Mercedes" "apellidos" => "Marbán Calzón" ] 4 => array:2 [ "nombre" => "Pilar" "apellidos" => "Sevilla Ramos" ] 5 => array:2 [ "nombre" => "Lourdes" "apellidos" => "García Villaescusa" ] 6 => array:2 [ "nombre" => "María Jesús" "apellidos" => "Dabad Moreno" ] 7 => array:2 [ "nombre" => "José Ramón" "apellidos" => "Muñoz-Rodríguez" ] 8 => array:2 [ "nombre" => "Rafael" "apellidos" => "Ruiz Cano" ] ] ] ] ] "idiomaDefecto" => "es" "Traduccion" => array:1 [ "en" => array:9 [ "pii" => "S2387020623001407" "doi" => "10.1016/j.medcle.2022.09.025" "estado" => "S300" "subdocumento" => "" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2387020623001407?idApp=UINPBA00004N" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0025775322006224?idApp=UINPBA00004N" "url" => "/00257753/0000016000000009/v1_202304210930/S0025775322006224/v1_202304210930/es/main.assets" ] ] "itemSiguiente" => array:18 [ "pii" => "S238702062300147X" "issn" => "23870206" "doi" => "10.1016/j.medcle.2022.09.026" "estado" => "S300" "fechaPublicacion" => "2023-05-12" "aid" => "6134" "copyright" => "Elsevier España, S.L.U." "documento" => "article" "crossmark" => 1 "subdocumento" => "fla" "cita" => "Med Clin. 2023;160:385-91" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "en" => array:13 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original article</span>" "titulo" => "The correlation of lipid profile and waist circumference with phenylalanine levels in adult patients with classical phenylketonuria" "tienePdf" => "en" "tieneTextoCompleto" => "en" "tieneResumen" => array:2 [ 0 => "en" 1 => "es" ] "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "385" "paginaFinal" => "391" ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Correlación del perfil lipídico y el perímetro de cintura con los niveles de fenilalanina en pacientes adultos con fenilcetonuria clásica" ] ] "contieneResumen" => array:2 [ "en" => true "es" => true ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1864 "Ancho" => 2508 "Tamanyo" => 214134 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Correlation matrix between some cardiovascular risk factors and phenylalanine levels. Linear correlations of some parameters related to Phe levels with demographic variables (age), anthropometric measurements and indices (BMI, WC), and laboratory parameters of cardiovascular risk (uric acid and lipid profile). WC – waist circumference. BMI – body mass index. TC – total cholesterol. HDL-c – high-density lipoprotein cholesterol. LDL-c – low-density lipoprotein cholesterol. TG – triglycerides. Phe – phenylalanine. Median_Phe – median levels of Phe. Min_Phe – minimum levels of Phe. Max_Phe – maximum levels of Phe. Range_Phe – range of Phe levels.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Nestor Vazquez-Agra, Silvia Fernandez-Crespo, Ana-Teresa Marques-Afonso, Anton Cruces-Sande, Sofia Barbosa-Gouveia, Miguel-Angel Martinez-Olmos, Alvaro Hermida-Ameijeiras" "autores" => array:7 [ 0 => array:2 [ "nombre" => "Nestor" "apellidos" => "Vazquez-Agra" ] 1 => array:2 [ "nombre" => "Silvia" "apellidos" => "Fernandez-Crespo" ] 2 => array:2 [ "nombre" => "Ana-Teresa" "apellidos" => "Marques-Afonso" ] 3 => array:2 [ "nombre" => "Anton" "apellidos" => "Cruces-Sande" ] 4 => array:2 [ "nombre" => "Sofia" "apellidos" => "Barbosa-Gouveia" ] 5 => array:2 [ "nombre" => "Miguel-Angel" "apellidos" => "Martinez-Olmos" ] 6 => array:2 [ "nombre" => "Alvaro" "apellidos" => "Hermida-Ameijeiras" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S238702062300147X?idApp=UINPBA00004N" "url" => "/23870206/0000016000000009/v1_202305121215/S238702062300147X/v1_202305121215/en/main.assets" ] "itemAnterior" => array:17 [ "pii" => "S2387020623001481" "issn" => "23870206" "doi" => "10.1016/j.medcle.2022.10.020" "estado" => "S300" "fechaPublicacion" => "2023-05-12" "aid" => "6135" "documento" => "article" "crossmark" => 1 "subdocumento" => "fla" "cita" => "Med Clin. 2023;160:373-8" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "en" => array:13 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original article</span>" "titulo" => "The risk of osteoporosis in patients with ankylosing spondylitis—A large retrospective matched cohort study" "tienePdf" => "en" "tieneTextoCompleto" => "en" "tieneResumen" => array:2 [ 0 => "en" 1 => "es" ] "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "373" "paginaFinal" => "378" ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "El riesgo de osteoporosis en pacientes con espondilitis anquilosante: un estudio retrospectivo de cohortes emparejadas" ] ] "contieneResumen" => array:2 [ "en" => true "es" => true ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0010" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1866 "Ancho" => 2508 "Tamanyo" => 233645 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Competing risk analysis for osteoporosis in patients with ankylosing spondylitis versus controls in the total cohort, and stratified by sex.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Kassem Sharif, Avishai M. Tsur, Niv Ben-Shabat, Abdulla Watad, Arnon D. Cohen, Howard Amital" "autores" => array:6 [ 0 => array:2 [ "nombre" => "Kassem" "apellidos" => "Sharif" ] 1 => array:2 [ "nombre" => "Avishai M." "apellidos" => "Tsur" ] 2 => array:2 [ "nombre" => "Niv" "apellidos" => "Ben-Shabat" ] 3 => array:2 [ "nombre" => "Abdulla" "apellidos" => "Watad" ] 4 => array:2 [ "nombre" => "Arnon D." "apellidos" => "Cohen" ] 5 => array:2 [ "nombre" => "Howard" "apellidos" => "Amital" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2387020623001481?idApp=UINPBA00004N" "url" => "/23870206/0000016000000009/v1_202305121215/S2387020623001481/v1_202305121215/en/main.assets" ] "en" => array:19 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original article</span>" "titulo" => "Triponderal mass index and markers of metabolic risk in children and adolescents with obesity" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "379" "paginaFinal" => "384" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "Enrique Palomo Atance, Francisco Javier Caballero Mora, David Espadas Maciá, Mercedes Marbán Calzón, Pilar Sevilla Ramos, Lourdes García Villaescusa, María Jesús Dabad Moreno, José Ramón Muñoz-Rodríguez, Rafael Ruiz Cano" "autores" => array:9 [ 0 => array:4 [ "nombre" => "Enrique" "apellidos" => "Palomo Atance" "email" => array:1 [ 0 => "palomo.enrique@gmail.com" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] 1 => array:3 [ "nombre" => "Francisco Javier" "apellidos" => "Caballero Mora" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 2 => array:3 [ "nombre" => "David" "apellidos" => "Espadas Maciá" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] ] ] 3 => array:3 [ "nombre" => "Mercedes" "apellidos" => "Marbán Calzón" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">d</span>" "identificador" => "aff0020" ] ] ] 4 => array:3 [ "nombre" => "Pilar" "apellidos" => "Sevilla Ramos" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">e</span>" "identificador" => "aff0025" ] ] ] 5 => array:3 [ "nombre" => "Lourdes" "apellidos" => "García Villaescusa" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">f</span>" "identificador" => "aff0030" ] ] ] 6 => array:3 [ "nombre" => "María Jesús" "apellidos" => "Dabad Moreno" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">g</span>" "identificador" => "aff0035" ] ] ] 7 => array:3 [ "nombre" => "José Ramón" "apellidos" => "Muñoz-Rodríguez" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">h</span>" "identificador" => "aff0040" ] ] ] 8 => array:3 [ "nombre" => "Rafael" "apellidos" => "Ruiz Cano" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">g</span>" "identificador" => "aff0035" ] ] ] ] "afiliaciones" => array:8 [ 0 => array:3 [ "entidad" => "Endocrinología Pediátrica, Servicio de Pediatría, Hospital General Universitario de Ciudad Real, Grupo de Endocrinología Pediátrica de Castilla-La Mancha (GEPCAM), Ciudad Real, Spain" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Endocrinología Pediátrica, Servicio de Pediatría, Hospital Santa Bárbara, Grupo de Endocrinología Pediátrica de Castilla – La Mancha (GEPCAM), Puertollano, Ciudad Real, Spain" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Endocrinología Pediátrica, Servicio de Pediatría, Hospital Virgen de la Luz, Grupo de Endocrinología Pediátrica de Castilla – La Mancha (GEPCAM), Cuenca, Spain" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Endocrinología Pediátrica. Servicio de Pediatría, Hospital General La Mancha Centro, Grupo de Endocrinología Pediátrica de Castilla – La Mancha (GEPCAM), Alcázar de San Juan, Ciudad Real, Spain" "etiqueta" => "d" "identificador" => "aff0020" ] 4 => array:3 [ "entidad" => "Endocrinología Pediátrica, Servicio de Pediatría, Hospital Universitario de Guadalajara, Grupo de Endocrinología Pediátrica de Castilla – La Mancha (GEPCAM), Guadalajara, Spain" "etiqueta" => "e" "identificador" => "aff0025" ] 5 => array:3 [ "entidad" => "Endocrinología Pediátrica, Servicio de Pediatría, Hospital General de Almansa, Grupo de Endocrinología Pediátrica de Castilla – La Mancha (GEPCAM), Almansa, Albacete, Spain" "etiqueta" => "f" "identificador" => "aff0030" ] 6 => array:3 [ "entidad" => "Endocrinología Pediátrica, Servicio de Pediatría, Hospital General Universitario de Albacete, Grupo de Endocrinología Pediátrica de Castilla – La Mancha (GEPCAM), Albacete, Spain" "etiqueta" => "g" "identificador" => "aff0035" ] 7 => array:3 [ "entidad" => "Unidad de Investigación Traslacional, Hospital General Universitario de Ciudad Real, Ciudad Real, Spain" "etiqueta" => "h" "identificador" => "aff0040" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Índice de masa triponderal y marcadores de riesgo metabólico en niños y adolescentes con obesidad" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:8 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1027 "Ancho" => 1675 "Tamanyo" => 95237 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0005" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Change in mean absolute body mass index (BMI) and triponderal mass index (TMI) values over age.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Obesity in childhood tends to be perpetuated through adolescence and adulthood and constitutes a risk factor for the development of multiple complications that can lead to a shorter life expectancy.<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1–3</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">For the clinical assessment of patients with obesity, it has become necessary to make an indirect estimate of the amount and distribution of body fat, using different anthropometric indices that relate weight to height. Of these, the body mass index (BMI) has been the most widely used, so that reference values have been obtained to establish the diagnoses of overweight and obesity.<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">4</span></a> The usefulness of BMI to define them is based on the fact that, in the adult body, weight is proportional to height squared. However, during the period of growth that characterizes childhood and adolescence and that is associated with changes in the distribution of adiposity, it has been observed that this proportionality is not always fulfilled, which has called into question the ability of BMI to establish the diagnosis of overweight and obesity.<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">In recent years it has been published that another anthropometric index, the triponderal mass index (TMI), which is obtained by the ratio between weight and height cubed, would estimate the percentage of body fat and visceral fat more accurately than BMI, so its use has been proposed for the assessment of obesity during childhood and adolescence.<a class="elsevierStyleCrossRefs" href="#bib0025"><span class="elsevierStyleSup">5–7</span></a> Likewise, and unlike BMI, it has been observed that the absolute values of TMI drop sharply from birth to 6 years of age, remaining uniform thereafter,<a class="elsevierStyleCrossRefs" href="#bib0040"><span class="elsevierStyleSup">8,9</span></a> so it would not be necessary to correct its values for age by calculating the Z-<span class="elsevierStyleItalic">score</span>, which would considerably simplify the evaluation of these patients.</p><p id="par0020" class="elsevierStylePara elsevierViewall">Although it has been reported that the ability of TMI to identify patients with obesity-associated metabolic complications may be similar to that of BMI, its relationship with the presence of metabolic syndrome and with various cardiovascular risk factors in both paediatric and adult age has not yet been well established.<a class="elsevierStyleCrossRefs" href="#bib0050"><span class="elsevierStyleSup">10,11</span></a></p><p id="par0025" class="elsevierStylePara elsevierViewall">Therefore, the objectives of the present study would be: first, to determine the association between TMI and different cardiovascular and metabolic risk markers, as well as to establish cut-off points for TMI that are related to increased cardiovascular risk values in these markers.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Material and methods</span><p id="par0030" class="elsevierStylePara elsevierViewall">A multicenter, observational, cross-sectional and prospective study was designed to include patients under 14 years of age diagnosed with obesity in the paediatric endocrinology units of the 7 participating centres, all of which belonged to public hospitals in the same autonomous community. Patients with monogenic obesity or obesity associated with malformation syndromes, as well as those associated with endocrinopathies or iatrogenic causes were excluded.</p><p id="par0035" class="elsevierStylePara elsevierViewall">The data were collected during the period 1 July 2019 to 30 June 2021. The selection of the study population was made by consecutive non-randomized sampling, so that a random sample of 207 individuals was considered sufficient to estimate a population percentage of about 15% with a replacement rate of 5%, a confidence of 95% and a precision of<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>5 percentage units.</p><p id="par0040" class="elsevierStylePara elsevierViewall">The variables analysed were: sex, age, pubertal stage, weight, height, waist circumference, BMI, TMI, basal glucose and insulin, <span class="elsevierStyleItalic">Homeostasis Model Assessment</span> (HOMA) index, systolic and diastolic blood pressure, total cholesterol, triglycerides, HDL-c, LDL-c, glutamic oxaloacetic transaminase (GOT), glutamic pyruvic transaminase (GPT) and uric acid.</p><p id="par0045" class="elsevierStylePara elsevierViewall">Weight was determined on an electronic scale with a range of 0–120<span class="elsevierStyleHsp" style=""></span>kg and accuracy of 100<span class="elsevierStyleHsp" style=""></span>g, with the patient being assessed in underwear. The height was measured in a rigid wall-mounted inextensible measuring rod with a range of 60–200<span class="elsevierStyleHsp" style=""></span>cm and an accuracy of 0.1<span class="elsevierStyleHsp" style=""></span>cm, and the measurement was made with the patient barefoot.</p><p id="par0050" class="elsevierStylePara elsevierViewall">BMI was calculated using the formula weight (kg)/height<span class="elsevierStyleSup">2</span> (m) and TMI was calculated using the formula weight (kg)/height<span class="elsevierStyleSup">3</span> (m). In both cases the results were expressed in Z-<span class="elsevierStyleItalic">score</span> with respect to the reference values of the <span class="elsevierStyleItalic">Barcelona Longitudinal Growth Study 1995–2017</span> for age and sex.<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a> The diagnosis of obesity was made in those cases in which BMI value was equal to or greater than 2 deviations from the Z-<span class="elsevierStyleItalic">score</span> of the reference population for age and sex.</p><p id="par0055" class="elsevierStylePara elsevierViewall">The waist circumference was measured with the patient in a standing position, taking at the end of expiration the midpoint between the lower costal margin and the iliac crest. The graphs of Fernández et al.<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">12</span></a> were used as reference values, and the results were expressed in Z-<span class="elsevierStyleItalic">score</span>.</p><p id="par0060" class="elsevierStylePara elsevierViewall">The stage of pubertal development was determined by Tanner's stages<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a> (I, II, III, IV and V), where stage <span class="elsevierStyleSmallCaps">i</span> corresponds to the prepubertal stage and stages <span class="elsevierStyleSmallCaps">ii</span> to <span class="elsevierStyleSmallCaps">v</span> correspond to the different degrees of pubertal development until reaching adult maturity.</p><p id="par0065" class="elsevierStylePara elsevierViewall">Blood pressure measurement was performed with the patient seated and the left arm at heart level using an oscillometric electronic device after 5<span class="elsevierStyleHsp" style=""></span>min of rest. Three determinations were made, with the lowest being recorded.</p><p id="par0070" class="elsevierStylePara elsevierViewall">For the determination of baseline blood glucose and insulin, total cholesterol, LDL-c, HDL-c, triglycerides, GOT, GPT and uric acid, blood was drawn while the patient was fasting. The HOMA index was calculated according to the formula: glucose (mmol/l)<span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>insulin (μIU/mL)/22.5. For basal insulin and HOMA index, and according to the published reference values for our population,<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a> hyperinsulinism was defined if basal insulin was ≥15<span class="elsevierStyleHsp" style=""></span>mUI/mL and a high HOMA index if its value was<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>3.5. For the lipoprotein profile, and according to the reference values of the <span class="elsevierStyleItalic">National Cholesterol Education Program Expert Panel,</span><a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> high total cholesterol was defined if ≥200<span class="elsevierStyleHsp" style=""></span>mg/dl, high LDL-c if ≥130<span class="elsevierStyleHsp" style=""></span>mg/dl, low HDL-c if <40<span class="elsevierStyleHsp" style=""></span>mg/dl and high triglycerides if ≥130<span class="elsevierStyleHsp" style=""></span>mg/dl. For uric acid, hyperuricemia was considered if value ≥7<span class="elsevierStyleHsp" style=""></span>mg/dl. For patients aged 10 years or older, metabolic syndrome was defined according to the criteria of the <span class="elsevierStyleItalic">International Diabetes Federation</span> (IDF),<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">16</span></a> which included the assessment of waist circumference, blood pressure and HDL-c, triglycerides and baseline glucose levels.</p><p id="par0075" class="elsevierStylePara elsevierViewall">SPSS® v 28.0 (IBM, USA) software was used for the statistical study. A descriptive analysis was performed for qualitative variables, which were represented by frequency distribution tables, and for quantitative variables, which were expressed by statistics of central tendency (mean) and dispersion (standard deviations [SD]). Regarding the inferential statistical analysis, Spearman's correlation test (between quantitative variables) and the Mann–Whitney U test for the difference in means (between qualitative and quantitative variables) were used for independent samples, after verifying the normal distribution of the quantitative variables by means of the Kolmogorov–Smirnov test. In all cases, a statistical significance level equal to p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05 was established.</p><p id="par0080" class="elsevierStylePara elsevierViewall">The data were stratified according to sex, pubertal development and severity of obesity, establishing in this case 2 groups: one that included those obese patients with greater body adiposity (Z-<span class="elsevierStyleItalic">score</span> of BMI<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>3) and another with the rest of the patients in the sample (Z-<span class="elsevierStyleItalic">score</span> of BMI<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>2 SD and <3).</p><p id="par0085" class="elsevierStylePara elsevierViewall">This study was conducted in accordance with the principles of the Declaration of Helsinki and amendments relating to research in humans, and an informed consent form was requested from the parents or legal representatives of each patient included. The research protocol was approved by the Clinical Research Ethics Committee of each participating hospital.</p></span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Results</span><p id="par0090" class="elsevierStylePara elsevierViewall">We included 199 patients (50.3% male) diagnosed with obesity with a mean age of 11.08 (0.17) years and ages ranging from 3.2 to 13.9 years, of whom 41% were prepubertal. BMI had a mean Z-<span class="elsevierStyleItalic">score</span> of 3.31 (0.07) and TMI a mean Z-<span class="elsevierStyleItalic">score</span> of 4.7 (0.11). As for the absolute value of TMI, its mean was 19.68 (0.16) kg/m<span class="elsevierStyleSup">3</span>. In turn, 16.7% of patients aged 10 years or more met the IDF criteria for metabolic syndrome. The results of the descriptive study of the rest of the anthropometric, laboratory and blood pressure parameters are shown in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>.</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0095" class="elsevierStylePara elsevierViewall">Once the absolute TMI value has been calculated throughout the different ages of the patients in the sample, it can be observed that their mean values remain stable from 4 to 14 years of age, with a range between 18.77 and 21.23<span class="elsevierStyleHsp" style=""></span>kg/m<span class="elsevierStyleSup">3</span> (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>). When comparing the evolution of absolute TMI values with those of BMI, it can be seen that the latter increase with age, so that the mean absolute value of BMI in younger patients is significantly lower than that of 14-year-old patients (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>).</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0100" class="elsevierStylePara elsevierViewall">Statistically significant correlations were obtained between the Z-<span class="elsevierStyleItalic">score</span> TMI value and waist circumference (r<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.571; p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05), basal insulin (r<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.198; p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05), the HOMA index (r<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.189; p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05) and HDL-c (r<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.188; p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05) (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>). Likewise, significant correlations were observed between the Z-<span class="elsevierStyleItalic">score</span> BMI value with the same parameters (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>). When stratifying by sex, a correlation of TMI with basal insulin (r<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.253; p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05) and HOMA index (r<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.240; p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05) was observed; an association that was not detected in males (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>). Regarding stratification according to the presence or absence of pubertal development, it was appreciated that TMI correlates in prepubertal patients with different cardiovascular and metabolic risk markers, such as waist circumference (r<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.658; p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05), HDL-c (r<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.306; p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05) and LDL-c (r<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.233; p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05) (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>). On the other hand, when stratifying according to the severity of obesity, it was observed that those with a Z-<span class="elsevierStyleItalic">score</span> of BMI<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>3 showed a correlation of TMI with waist circumference (r<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.331; p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05), basal insulin (r<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.273; p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05), the HOMA index (r<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.271; p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05) and triglycerides (r<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.220; p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05) (<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>).</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><elsevierMultimedia ident="tbl0020"></elsevierMultimedia><p id="par0105" class="elsevierStylePara elsevierViewall">Finally, we looked for differences in TMI absolute values for several metabolic risk parameters. These were: meet IDF metabolic syndrome criteria (only applicable to patients ≥10 years), have basal insulin ≥15<span class="elsevierStyleHsp" style=""></span>μUI/mL, HOMA ≥3.5, basal cholesterol ≥200<span class="elsevierStyleHsp" style=""></span>mg/dl, triglycerides ≥130<span class="elsevierStyleHsp" style=""></span>mg/dl, HDL-c<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>40<span class="elsevierStyleHsp" style=""></span>mg/dl, LDL-c<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>130<span class="elsevierStyleHsp" style=""></span>mg/dl and uric acid ≥7<span class="elsevierStyleHsp" style=""></span>mg/dl. Thus, the aim was to establish cut-off points in TMI in order to estimate the risk of complications associated with obesity in each patient. In this analysis, we found TMI values of 20.15 (2.18) vs. 19.51 (2.41) kg/m<span class="elsevierStyleSup">3</span> (p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0,05) among those with basal insulin levels ≥15<span class="elsevierStyleHsp" style=""></span>μIU/mL relative to the rest, and TMI values of 20.36 (2.46) vs. 19.46 (2.29) kg/m<span class="elsevierStyleSup">3</span> (p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05) in patients with HDL-c<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>40<span class="elsevierStyleHsp" style=""></span>mg/dl with respect to the rest (<a class="elsevierStyleCrossRef" href="#tbl0025">Table 5</a>).</p><elsevierMultimedia ident="tbl0025"></elsevierMultimedia></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Discussion</span><p id="par0110" class="elsevierStylePara elsevierViewall">TMI aims to be a tool for the assessment of patients with obesity, overcoming the limitations of BMI in the first years of life, such as the underestimation of body adiposity in periods of intense growth such as adolescence and the ability to predict complications associated with weight gain.<a class="elsevierStyleCrossRefs" href="#bib0025"><span class="elsevierStyleSup">5,10</span></a> Thus, reports have shown that TMI correlates better than BMI with body adiposity as measured by dual-energy X-ray absorptiometry (DEXA),<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">7</span></a> and in mostly pubertal patient populations has revealed a higher incidence of both overweight and obesity.<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> Moreover, it seems to discriminate better than BMI the central body fat distribution,<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> even in preschool patients,<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> which may be associated with a large part of the metabolic and cardiovascular complications associated with obesity and would allow the identification of patients at risk. In this regard, a correlation between TMI and serum leptin levels,<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a> which is a recognized biomarker of body adiposity, has also been found in a population of healthy adolescents. Our study has demonstrated a correlation between TMI values and waist circumference as an indirect indicator of visceral fat accumulation, an association observed in both sexes, both in pubertal and prepubertal children and in all cases of obesity included, regardless of the severity of obesity.</p><p id="par0115" class="elsevierStylePara elsevierViewall">On the other hand, in our study population it can be observed that the mean values of TMI remain stable throughout age, which contrasts with the evolution of BMI, whose values are progressively increasing. For this reason, BMI should be adjusted according to age, which makes it necessary to have population reference values for its correct interpretation. This uniform distribution of TMI in the paediatric age has been published in studies conducted in healthy population,<a class="elsevierStyleCrossRefs" href="#bib0040"><span class="elsevierStyleSup">8,9</span></a> but it had not been observed in a group in which all patients had obesity. This would simplify the clinical assessment of obesity and would be an additional advantage of TMI over BMI.<a class="elsevierStyleCrossRefs" href="#bib0050"><span class="elsevierStyleSup">10,11</span></a></p><p id="par0120" class="elsevierStylePara elsevierViewall">Regarding the relationship between TMI and the obesity-associated comorbidities, it has been observed in patients aged 10 years and older that practically all the risk factors related to the metabolic syndrome are more severe in cases with high values of TMI than in those in which it is within the normal range,<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">21</span></a> so TMI has been recognized as having a moderate capacity to discriminate patients with different complications related to excess adiposity.<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">22</span></a> Even so, there is controversy on this point, since some studies have published that the determination of TMI would be superior to BMI in predicting cardiovascular risk in young adults,<a class="elsevierStyleCrossRefs" href="#bib0115"><span class="elsevierStyleSup">23,24</span></a> while others give it a capacity similar to BMI.<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">25</span></a> Regarding the association with specific risk factors, we found a correlation between TMI and basal insulin levels similar to that of BMI,<a class="elsevierStyleCrossRefs" href="#bib0040"><span class="elsevierStyleSup">8,25,26</span></a> as well as positive correlations with waist circumference, blood pressure (both systolic and diastolic), basal glucose, total cholesterol, triglycerides and LDL-c, and a negative correlation with HDL-c.<a class="elsevierStyleCrossRefs" href="#bib0125"><span class="elsevierStyleSup">25,27</span></a> These findings coincide to a large extent with those obtained in our study, where a positive correlation of TMI with waist circumference and a negative correlation with HDL-c values were observed. Likewise, when stratifying the results, an association between TMI and insulin levels was observed in the groups of females, patients with pubertal development and in those with a Z-<span class="elsevierStyleItalic">score</span> of BMI<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>3. This fact could be of clinical interest, since it is well known that insulin resistance is one of the pathophysiological bases for obesity-associated comorbidities, including the metabolic syndrome. For all these reasons and taking into account the consistent values of TMI throughout age, a cut-off point has been calculated for the absolute value of TMI to identify obese patients at metabolic risk,<a class="elsevierStyleCrossRef" href="#bib0055"><span class="elsevierStyleSup">11</span></a> which has been set at 18.7<span class="elsevierStyleHsp" style=""></span>kg/m<span class="elsevierStyleSup">3</span>. Along the same lines, one of the objectives of our study focused on finding TMI values that would allow differentiation between patients who met different cardiovascular and metabolic risk markers. The results showed that those with insulin ≥15<span class="elsevierStyleHsp" style=""></span>μIU/mL and with HDL-c<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>40<span class="elsevierStyleHsp" style=""></span>mg/dl showed significantly higher TMI values with respect to the rest who did not meet these criteria. For both cases, TMI result was slightly higher than 20<span class="elsevierStyleHsp" style=""></span>kg/m<span class="elsevierStyleSup">3</span> (<a class="elsevierStyleCrossRef" href="#tbl0025">Table 5</a>).</p><p id="par0125" class="elsevierStylePara elsevierViewall">At the present time no evidence has been demonstrated on the ability of TMI to predict increased markers of inflammation associated with obesity,<a class="elsevierStyleCrossRefs" href="#bib0050"><span class="elsevierStyleSup">10,28</span></a> such as high transaminases (GOT and GPT), free fatty acids, interleukin 6, tumour necrosis factor alpha, or levels of fetuin A and monocyte chemotactic protein 1. For this reason, it has been published that TMI would be associated with the metabolic abnormalities of obesity, but it does not seem to reflect the inflammatory changes that obesity entails.<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">28</span></a> In our study, GOT and GPT levels were analysed, and no association was found in any case.</p><p id="par0130" class="elsevierStylePara elsevierViewall">The limitations of this study include the lack of a control population of healthy children to compare the results obtained in our group, as well as the need for prospective follow-up studies with larger samples in order to determine the progression of patients according to their TMI levels. Similarly, it would be interesting to correlate objective parameters of body adiposity (such as DEXA determination) with TMI and the different metabolic risk factors and markers of inflammation. Finally, it would be necessary to establish cut-off points for TMI that relate to the presence of metabolic risk factors according to different ethnic groups.</p><p id="par0135" class="elsevierStylePara elsevierViewall">Therefore, it could be concluded that TMI is a useful parameter in the assessment of children and adolescents with obesity, since it is related to well-known metabolic risk factors, such as increased waist circumference, basal insulin and HOMA index, and decreased HDL-c. In our group of patients, absolute TMI values higher than 20<span class="elsevierStyleHsp" style=""></span>mg/kg<span class="elsevierStyleSup">3</span> would be associated with basal insulin levels ≥15<span class="elsevierStyleHsp" style=""></span>μIU/mL and with HDL-c levels <40<span class="elsevierStyleHsp" style=""></span>mg/dl. Also, since its values remain consistent throughout development, age-dependent corrections of TMI would not be necessary, which would greatly simplify the evaluation of these patients.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Ethical considerations</span><p id="par0140" class="elsevierStylePara elsevierViewall">We, the authors, declare that we have obtained informed consent from the study participants, as well as approval from the relevant clinical research ethics committees of each participating hospital.</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Funding</span><p id="par0145" class="elsevierStylePara elsevierViewall">We, the authors, declare that we did not receive any funding for this study.</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Conflict of interest</span><p id="par0150" class="elsevierStylePara elsevierViewall">We, the authors, declare that we have no conflict of interest in relation to this article.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres1896945" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background and objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Material and methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1641257" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1896946" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Antecedentes y objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Material y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1641256" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:2 [ "identificador" => "sec0010" "titulo" => "Material and methods" ] 6 => array:2 [ "identificador" => "sec0015" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "sec0020" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0025" "titulo" => "Ethical considerations" ] 9 => array:2 [ "identificador" => "sec0030" "titulo" => "Funding" ] 10 => array:2 [ "identificador" => "sec0035" "titulo" => "Conflict of interest" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2022-06-28" "fechaAceptado" => "2022-09-22" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1641257" "palabras" => array:4 [ 0 => "Pediatric obesity" 1 => "Body mass index" 2 => "Metabolic syndrome" 3 => "Insulin" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1641256" "palabras" => array:4 [ 0 => "Obesidad pediátrica" 1 => "Índice de masa corporal" 2 => "Síndrome metabólico" 3 => "Insulina" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Background and objective</span><p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Triponderal mass index (TMI) would estimate excess adiposity better than body mass index (BMI), maintaining stable values during childhood. This work aims to determine the correlation between TMI and markers of metabolic risk as well as set values of TMI that are related to an increase of metabolic risk.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Material and methods</span><p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">Multicenter, observational, cross-sectional and prospective study in children under 14 years of age with obesity. Variables: age, sex, pubertal stage, weight, height, abdominal circumference, BMI, TMI, basal glucose and insulin, HOMA index, blood pressure, lipoprotein profile, transaminases and uric acid. BMI and TMI were expressed according to the values of the Barcelona Longitudinal Study. Statistical analysis was performed with the SPSS® program.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">199 patients (50.3% male), age 11.08 (2.48) years, TMI 19.68 (2.36) kg/m<span class="elsevierStyleSup">3</span>. Correlation between TMI and abdominal circumference (r 0.571; p 0), insulin (r 0.198; p 0.005), HOMA index (r 0.189; p 0.008) and HDL-c (r −0.188; p 0.008) was observed. IMT<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>20.15<span class="elsevierStyleHsp" style=""></span>kg/m<span class="elsevierStyleSup">3</span> was associated with insulin ≥15 mIU/mL (p 0.029) and IMT<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>20.36<span class="elsevierStyleHsp" style=""></span>kg/m<span class="elsevierStyleSup">3</span> with HDL-c <40<span class="elsevierStyleHsp" style=""></span>mg/dl (p 0.023).</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">TMI was correlated with increase of abdominal circumference, insulin and HOMA index and decrease of HDL-c. IMT<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>20<span class="elsevierStyleHsp" style=""></span>kg/m<span class="elsevierStyleSup">3</span> can be associated with increased insulin and decreased HDL-c. Therefore, the IMT seems to be a useful parameter in the assessment of pediatric patients with obesity.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background and objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Material and methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Antecedentes y objetivo</span><p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">El índice de masa triponderal (IMT) estimaría mejor que el índice de masa corporal (IMC) el exceso de adiposidad manteniendo valores estables durante la infancia. Este trabajo pretende determinar la correlación del IMT con marcadores de riesgo metabólico y establecer valores del IMT que se relacionen con un aumento del riesgo metabólico.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Material y métodos</span><p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">Estudio multicéntrico, observacional, transversal y prospectivo en menores de 14 años con obesidad. Variables: edad, sexo, estadio puberal, peso, talla, perímetro abdominal, IMC, IMT, glucosa e insulina basales, índice HOMA, presión arterial, perfil lipoproteico, transaminasas y ácido úrico. El IMC y del IMT se expresaron según los valores del Estudio longitudinal de Barcelona. Se realizó análisis estadístico con el programa SPSS®.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0095" class="elsevierStyleSimplePara elsevierViewall">199 pacientes (50,3% varones), edad 11,08 (2,48) años, IMT 19,68 (2,36) kg/m<span class="elsevierStyleSup">3</span>. Se observó correlación del IMT con perímetro abdominal (r 0,571; p 0), insulina (r 0,198; p 0,005), índice HOMA (r 0,189; p 0,008) y HDL-c (r −0,188; p 0,008). El IMT<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>20,15<span class="elsevierStyleHsp" style=""></span>kg/m<span class="elsevierStyleSup">3</span> se asoció a insulina ≥15 mUI/mL (p 0,029) y el IMT<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>20,36<span class="elsevierStyleHsp" style=""></span>kg/m<span class="elsevierStyleSup">3</span> a HDL-c <40<span class="elsevierStyleHsp" style=""></span>mg/dl (p 0,023).</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusiones</span><p id="spar0100" class="elsevierStyleSimplePara elsevierViewall">El IMT se correlacionó con el incremento del perímetro abdominal, la insulina y el índice HOMA y la disminución del c-HDL. El IMT<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>20<span class="elsevierStyleHsp" style=""></span>kg/m<span class="elsevierStyleSup">3</span> puede asociarse a elevación de la insulina y a descenso del c-HDL. Por ello, el IMT parece ser un parámetro útil en la valoración de los pacientes pediátricos con obesidad.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Antecedentes y objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Material y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] ] "multimedia" => array:6 [ 0 => array:8 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1027 "Ancho" => 1675 "Tamanyo" => 95237 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0005" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Change in mean absolute body mass index (BMI) and triponderal mass index (TMI) values over age.</p>" ] ] 1 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0010" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">HDL-c: high density lipoproteins cholesterol; LDL-c: low density lipoproteins cholesterol; SD: standard deviations; GOT: glutamic oxaloacetic transaminase; GPT: glutamic pyruvic transaminase; HOMA: Homeostasis Model Assessment; IDF: International Diabetes Federation; BMI: body mass index; TMI: triponderal mass index; BP: blood pressure.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Age (years), mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11.08 (0.17) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Sex, % \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">50.3 males; 49.7 females \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Tanner stages (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (41); 2 (10); 3 (16); 4 (18); 5 (15) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Waist circumference (Z-<span class="elsevierStyleItalic">score</span>), mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.76 (0.11) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">BMI (Z-<span class="elsevierStyleItalic">score</span>), mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.31 (0.07) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">TMI (absolute value; kg/m<span class="elsevierStyleSup">3</span>), mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19.68 (0.16) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">TMI (Z-<span class="elsevierStyleItalic">score</span>), mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.7 (0.11) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Systolic BP (mmHg), mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">114 (0.94) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Diastolic BP (mmHg), mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">68.55 (0.68) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Basal Insulin (μIU/mL), mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20.61 (0.9) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HOMA Index, mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.55 (0.21) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Total cholesterol (mg/dl), mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">157.01 (1.92) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Triglycerides (mg/dL), mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">99.89 (0.14) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HDL-c (mg/dl), mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">47.51 (0.77) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">LDL-c (mg/dl), mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">90.11 (1.72) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">GOT (IU/l), mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22.08 (0.55) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">GPT (IU/l), mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">21.66 (0.8) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Uric acid (mg/dl), mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.17 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Metabolic syndrome in<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>10 years (IDF criteria; %). \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Yes (16.7); no (83.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3170460.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Description of the sample.</p>" ] ] 2 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0015" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">HDL-c: high density lipoproteins cholesterol; LDL-c: low density lipoproteins cholesterol; GOT: glutamic oxaloacetic transaminase; GPT: glutamic pyruvic transaminase; HOMA: Homeostasis Model Assessment; BMI: body mass index; TMI: triponderal mass index; NS: statistically non-significant p value.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">Variables \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">BMI (Z-<span class="elsevierStyleItalic">score</span>)</th><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">TMI (Z-<span class="elsevierStyleItalic">score</span>)</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">r \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">r \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Waist circumference (Z-<span class="elsevierStyleItalic">score</span>) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.624 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.571 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Basal Insulin (μUI/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.175 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.013 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.198 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.005 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HOMA Index \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.161 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.023 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.189 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.008 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Total cholesterol (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.074 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.05 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Triglycerides (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.017 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.05 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HDL-c (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.171 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.016 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.188 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.008 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">LDL-c (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.025 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.021 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">GOT (IU/l) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.053 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.016 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">GPT (IU/l) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.059 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.042 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Uric acid (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.122 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.139 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3170461.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Correlation of body mass index and triponderal mass index with various cardiovascular and metabolic risk markers.</p>" ] ] 3 => array:8 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0020" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">HDL-c: high density lipoproteins cholesterol; LDL-c: low density lipoproteins cholesterol; GOT: glutamic oxaloacetic transaminase; GPT: glutamic pyruvic transaminase; HOMA: Homeostasis Model Assessment; TMI: triponderal mass index; NS: statistically non-significant p value.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Female</th><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Male</th><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Prepubertal</th><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Pubertal</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">Variables \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="8" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">TMI (Z-<span class="elsevierStyleItalic">score</span>)</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">r \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">r \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">r \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">r \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Waist circumference (Z-<span class="elsevierStyleItalic">score</span>) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.568 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.581 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.658 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.525 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Basal Insulin (μIU/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.253 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.012 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.158 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.188 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.201 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.03 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HOMA Index \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.240 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.017 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.145 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.199 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.173 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Total cholesterol (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.073 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.058 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.142 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.186 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.04 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Triglycerides (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.112 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.013 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.143 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.016 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HDL-c (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.192 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.189 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.306 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.005 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.103 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">LDL-c (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.028 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.027 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.233 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.035 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.159 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">GOT (IU/l) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.09 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.118 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.066 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.009 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">GPT (IU/l) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.08 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.118 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.109 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.004 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Uric acid (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.137 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.148 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.158 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.115 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3170463.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Stratification by sex and pubertal development of correlations between triponderal mass index and different cardiovascular and metabolic risk markers.</p>" ] ] 4 => array:8 [ "identificador" => "tbl0020" "etiqueta" => "Table 4" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0025" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Obesity defined in 2 groups: Z-score del IMC<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>3 y Z-score del IMC<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>2 y <<span class="elsevierStyleHsp" style=""></span>3).</p><p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">HDL-c: high density lipoproteins cholesterol; LDL-c: low density lipoproteins cholesterol; GOT: glutamic oxaloacetic transaminase; GPT: glutamic pyruvic transaminase; HOMA: Homeostasis Model Assessment; BMI: body mass index; TMI: triponderal mass index; NS: statistically non-significant p value.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Z-<span class="elsevierStyleItalic">score</span> IMC<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>3</th><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Z-<span class="elsevierStyleItalic">score</span> IMC<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>2 y <<span class="elsevierStyleHsp" style=""></span>3</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">Variables \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">TMI (Z-<span class="elsevierStyleItalic">score</span>)</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">r \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">r \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Waist circumference (Z-score) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.331 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.315 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Basal Insulin (μIU/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.273 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.007 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.027 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HOMA Index \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.271 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.008 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.013 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Total cholesterol (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.041 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.074 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Triglycerides (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.22 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.032 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.002 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HDL-c (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.191 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.076 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">LDL-c (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.127 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">GOT (IU/l) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.01 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.084 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">GPT (IU/l) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.153 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.058 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Uric acid (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.102 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.139 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3170464.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Stratification according to severity of obesity between triponderal mass index and different cardiovascular and metabolic risk markers.</p>" ] ] 5 => array:8 [ "identificador" => "tbl0025" "etiqueta" => "Table 5" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0030" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">HDL-c: high density lipoproteins cholesterol; LDL-c: low density lipoproteins cholesterol; SD: standard deviations; HOMA: Homeostasis Model Assessment; IDF: International Diabetes Federation; TMI: triponderal mass index; NS: statistically non-significant p value.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">TMI (kg/m<span class="elsevierStyleSup">3</span>)mean (SD) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Metabolic syndrome (IDF criteria) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20.25 (2.39) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">No metabolic syndrome (IDF criteria) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19.51 (2.36) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Insulin<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>15<span class="elsevierStyleHsp" style=""></span>μUI/mL \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20.15 (2.18) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.029 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Insulin<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>15<span class="elsevierStyleHsp" style=""></span>μUI/mL \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19.51 (2.41) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HOMA index<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>3,5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19.95 (2.42) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HOMA index<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>3,5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19.36 (2.26) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Uric acid<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>7<span class="elsevierStyleHsp" style=""></span>mg/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20.08 (2.12) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Uric acid<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>7<span class="elsevierStyleHsp" style=""></span>mg/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19.65 (2.38) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Total Cholesterol<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>200<span class="elsevierStyleHsp" style=""></span>mg/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20.01 (2.74) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Total Cholesterol<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>200<span class="elsevierStyleHsp" style=""></span>mg/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19.65 (2.33) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Triglycerides<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>130<span class="elsevierStyleHsp" style=""></span>mg/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19.46 (1.96) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Triglycerides<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>130<span class="elsevierStyleHsp" style=""></span>mg/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19.72 (2.44) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HDL-c<span class="elsevierStyleHsp" style=""></span>≥ <span class="elsevierStyleHsp" style=""></span>40<span class="elsevierStyleHsp" style=""></span>mg/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19.46 (2.29) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.023 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HDL-c<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>40<span class="elsevierStyleHsp" style=""></span>mg/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20.36 (2.46) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">LDL-c≥<span class="elsevierStyleHsp" style=""></span>130<span class="elsevierStyleHsp" style=""></span>mg/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19.96 (3.21) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">LDL-c<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>130<span class="elsevierStyleHsp" style=""></span>mg/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19.66 (2.32) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3170462.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Differences in the absolute value of triponderal mass index between patients with different cardiovascular and metabolic risk markers.</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:28 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Childhood obesity, other cardiovascular risk factors, and premature death" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:6 [ 0 => "P.W. Franks" 1 => "R.L. Hanson" 2 => "W.C. Knowler" 3 => "M.L. Sievers" 4 => "P.H. Bennett" 5 => "H.C. Looker" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1056/NEJMoa0904130" "Revista" => array:6 [ "tituloSerie" => "N Engl J Med." "fecha" => "2010" "volumen" => "362" "paginaInicial" => "485" "paginaFinal" => "493" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/20147714" "web" => "Medline" ] ] ] ] ] ] ] ] 1 => array:3 [ "identificador" => "bib0010" "etiqueta" => "2" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Body-mass index in 2.3 million adolescents and cardiovascular death in adulthood" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "G. Twig" 1 => "G. Yaniv" 2 => "H. Levine" 3 => "A. Leiba" 4 => "N. Goldberger" 5 => "E. Derazne" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:3 [ "tituloSerie" => "N Engl J Med" "fecha" => "2016" "volumen" => "374" ] ] ] ] ] ] 2 => array:3 [ "identificador" => "bib0015" "etiqueta" => "3" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Complicaciones metabólicas de la obesidad infantil" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:2 [ 0 => "D. Yeste" 1 => "A. Carrascosa" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:5 [ "tituloSerie" => "An Pediatr (Barc)." "fecha" => "2011" "volumen" => "75" "paginaInicial" => "e1" "paginaFinal" => "9" ] ] ] ] ] ] 3 => array:3 [ "identificador" => "bib0020" "etiqueta" => "4" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Weight-stature indices to measure underweight, overweight, and obesity" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:1 [ 0 => "T.J. Cole" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "LibroEditado" => array:5 [ "editores" => "J.H.Himes" "titulo" => "Anthropometric Assessment of Nutritional Status" "paginaInicial" => "83" "paginaFinal" => "111" "serieFecha" => "1991" ] ] ] ] ] ] 4 => array:3 [ "identificador" => "bib0025" "etiqueta" => "5" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Tri-ponderal mass index vs body mass index in estimating body fat during adolescence" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "C.M. Peterson" 1 => "H. Su" 2 => "D.M. Thomas" 3 => "M. Heo" 4 => "A.H. Golnabi" 5 => "A. Pietrobelli" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1001/jamapediatrics.2017.0460" "Revista" => array:7 [ "tituloSerie" => "JAMA Pediatr." "fecha" => "2017" "volumen" => "171" "numero" => "7" "paginaInicial" => "629" "paginaFinal" => "636" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/28505241" "web" => "Medline" ] ] ] ] ] ] ] ] 5 => array:3 [ "identificador" => "bib0030" "etiqueta" => "6" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Association of youth triponderal mass index vs body mass index with obesity-related outcomes in adulthood" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "F. Wu" 1 => "M.J. Buscot" 2 => "M. Juonala" 3 => "N. Hutri-Kähönen" 4 => "J.S.A. Viikari" 5 => "O.T. Raitakari" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1001/jamapediatrics.2018.3034" "Revista" => array:6 [ "tituloSerie" => "JAMA Pediatr." "fecha" => "2018" "volumen" => "172" "paginaInicial" => "1192" "paginaFinal" => "1195" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/30326018" "web" => "Medline" ] ] ] ] ] ] ] ] 6 => array:3 [ "identificador" => "bib0035" "etiqueta" => "7" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Triponderal mass index rather than body mass index: an indicator of high adiposity in Italian children and adolescents" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "A. De Lorenzo" 1 => "L. Romano" 2 => "L. Di Renzo" 3 => "P. Gualtieri" 4 => "C. Salimei" 5 => "E. Carrano" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.nut.2018.09.007" "Revista" => array:6 [ "tituloSerie" => "Nutrition." "fecha" => "2019" "volumen" => "60" "paginaInicial" => "41" "paginaFinal" => "47" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/30529185" "web" => "Medline" ] ] ] ] ] ] ] ] 7 => array:3 [ "identificador" => "bib0040" "etiqueta" => "8" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Triponderal mass index is useful for screening children and adolescentes with insulin-resistance" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "F.S. Neves" 1 => "R.O. Alvim" 2 => "D. Zaniqueli" 3 => "V.O. Pani" 4 => "C.R. Martins" 5 => "M.A.S. Peçanha" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1590/1984-0462/2020/38/2019066" "Revista" => array:3 [ "tituloSerie" => "Rev Paul Pediatr." "fecha" => "2020" "volumen" => "38" ] ] ] ] ] ] 8 => array:3 [ "identificador" => "bib0045" "etiqueta" => "9" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Índice de massa corporal e índice de massa triponderal de 1453 niños no obesos ni malnutridos de la generación del milenio. Estudio longitudinal de Barcelona" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "A. Carrascosa" 1 => "D. Yeste" 2 => "A. Moreno-Galdó" 3 => "M. Gussinyé" 4 => "Á Ferrández" 5 => "M. Clemente" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:6 [ "tituloSerie" => "An Pediatr (Barc)." "fecha" => "2018" "volumen" => "89" "numero" => "3" "paginaInicial" => "137" "paginaFinal" => "143" ] ] ] ] ] ] 9 => array:3 [ "identificador" => "bib0050" "etiqueta" => "10" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Tri-ponderal mass index as a screening tool for identifying body fat and cardiovascular risk factors in children and adolescents: a systematic review" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:5 [ 0 => "J. Sun" 1 => "R. Yang" 2 => "M. Zhao" 3 => "P. Bovet" 4 => "B. Xi" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.3389/fendo.2021.694681" "Revista" => array:3 [ "tituloSerie" => "Front Endocrinol (Lausanne)." "fecha" => "2021" "volumen" => "12" ] ] ] ] ] ] 10 => array:3 [ "identificador" => "bib0055" "etiqueta" => "11" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Precisión diagnóstica del índice de masa triponderal para identificar el fenótipo de riesgo metabólico em pacientes obesos" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "D. Yeste" 1 => "M. Clemente" 2 => "A. Campos" 3 => "A. Fábregas" 4 => "E. Mogas" 5 => "L. Soler" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:6 [ "tituloSerie" => "An Pediatr (Barc)." "fecha" => "2021" "volumen" => "94" "numero" => "2" "paginaInicial" => "68" "paginaFinal" => "74" ] ] ] ] ] ] 11 => array:3 [ "identificador" => "bib0060" "etiqueta" => "12" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Waist cincumference percentiles in nationally representative samples of African-American, European-American, and Mexican-American children and adolescentes" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "J.R. Fernández" 1 => "D.T. Redden" 2 => "A. Pietrobelli" 3 => "D.B. Allison" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.jpeds.2004.06.044" "Revista" => array:6 [ "tituloSerie" => "J Pediatr." "fecha" => "2004" "volumen" => "145" "paginaInicial" => "439" "paginaFinal" => "444" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/15480363" "web" => "Medline" ] ] ] ] ] ] ] ] 12 => array:3 [ "identificador" => "bib0065" "etiqueta" => "13" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Clinical longitudinal standards for height, weight, height velocity, weight velocity, and stages of puberty" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:2 [ 0 => "J.M. Tanner" 1 => "R.H. Whitehouse" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:5 [ "tituloSerie" => "Arch Dis Child." "fecha" => "1976" "volumen" => "51" "paginaInicial" => "170" "paginaFinal" => "179" ] ] ] ] ] ] 13 => array:3 [ "identificador" => "bib0070" "etiqueta" => "14" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Indice HOMA y QUICKI, insulina y péptido C en niños sanos. Puntos de corte de riesgo cardiovascular" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "B. García Cuartero" 1 => "C. García Lacalle" 2 => "C. Jiménez Lobo" 3 => "A. González Vergaz" 4 => "C. Calvo Rey" 5 => "M.J. Alcázar Villar" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1157/13102513" "Revista" => array:7 [ "tituloSerie" => "An Pediatr (Barc)." "fecha" => "2007" "volumen" => "66" "numero" => "5" "paginaInicial" => "481" "paginaFinal" => "490" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/17517203" "web" => "Medline" ] ] ] ] ] ] ] ] 14 => array:3 [ "identificador" => "bib0075" "etiqueta" => "15" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:1 [ "titulo" => "Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents; National Heart, Lung, and Blood Institute. Expert panel on integrated guidelines for cardiovascular health and risk reduction in children and adolescents: summary report" ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1542/peds.2009-2107C" "Revista" => array:7 [ "tituloSerie" => "Pediatrics." "fecha" => "2011" "volumen" => "128" "numero" => "Suppl 5" "paginaInicial" => "S213" "paginaFinal" => "56" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/22084329" "web" => "Medline" ] ] ] ] ] ] ] ] 15 => array:3 [ "identificador" => "bib0080" "etiqueta" => "16" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "The metabolic syndrome in children and adolescents – an IDF consensus report" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "P. Zimmet" 1 => "K.G. Alberti" 2 => "F. Kaufman" 3 => "N. Tajima" 4 => "M. Silink" 5 => "S. Arslanian" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:5 [ "tituloSerie" => "Ped Diabetes." "fecha" => "2007" "volumen" => "8" "paginaInicial" => "299" "paginaFinal" => "306" ] ] ] ] ] ] 16 => array:3 [ "identificador" => "bib0085" "etiqueta" => "17" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Diagnostic accuracy of tri-ponderal mass index and body mass index in estimating overweight and obesity in South African children" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:2 [ 0 => "V.K. Moselakgomo" 1 => "M. Van Staden" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.4102/phcfm.v11i1.2136" "Revista" => array:7 [ "tituloSerie" => "Afr J Prim Health Care Fam Med." "fecha" => "2019" "volumen" => "11" "numero" => "1" "paginaInicial" => "e1" "paginaFinal" => "e7" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/31793317" "web" => "Medline" ] ] ] ] ] ] ] ] 17 => array:3 [ "identificador" => "bib0090" "etiqueta" => "18" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Tri-ponderal mass index vs body mass index in discriminating central obesity and hypertension in adolescents with overweight" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "A.E. Malavazos" 1 => "G. Capitanio" 2 => "V. Milani" 3 => "F. Ambrogi" 4 => "I.A. Matelloni" 5 => "S. Basilico" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.numecd.2021.02.013" "Revista" => array:7 [ "tituloSerie" => "Nutr Metab Cardiovasc Dis." "fecha" => "2021" "volumen" => "31" "numero" => "5" "paginaInicial" => "1613" "paginaFinal" => "1621" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/33741212" "web" => "Medline" ] ] ] ] ] ] ] ] 18 => array:3 [ "identificador" => "bib0095" "etiqueta" => "19" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Tri-ponderal mass index: a screening tool for risk of central fat accumulation in Brazilian preschool children" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:5 [ 0 => "V.G. Nascimento" 1 => "C.J. Bertoli" 2 => "P.R. Gallo" 3 => "L.C. Abreu" 4 => "C. Leone" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.3390/medicina55090577" "Revista" => array:6 [ "tituloSerie" => "Medicina (Kaunas)." "fecha" => "2019" "volumen" => "55" "numero" => "9" "paginaInicial" => "577" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/31500381" "web" => "Medline" ] ] ] ] ] ] ] ] 19 => array:3 [ "identificador" => "bib0100" "etiqueta" => "20" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Leptin is associated with the tri-ponderal mass index in children: a cross-sectional study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "B. Empringham" 1 => "W.J. Jennings" 2 => "R. Rajan" 3 => "A.J. Fleming" 4 => "C. Portwine" 5 => "D.L. Johnston" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.2147/AHMT.S289973" "Revista" => array:6 [ "tituloSerie" => "Adolesc Health Med Ther." "fecha" => "2021" "volumen" => "12" "paginaInicial" => "9" "paginaFinal" => "15" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/33727877" "web" => "Medline" ] ] ] ] ] ] ] ] 20 => array:3 [ "identificador" => "bib0105" "etiqueta" => "21" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Distribution of tri-ponderal mass index and its relation to body mass index in children and adolescents aged 10 to 20 years" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:2 [ 0 => "H.K. Park" 1 => "Y.S. Shim" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1210/clinem/dgaa030" "Revista" => array:7 [ "tituloSerie" => "J Clin Endocrinol Metab" "fecha" => "2020" "volumen" => "105" "numero" => "3" "paginaInicial" => "e826" "paginaFinal" => "34" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/31995184" "web" => "Medline" ] ] ] ] ] ] ] ] 21 => array:3 [ "identificador" => "bib0110" "etiqueta" => "22" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Tri-Ponderal Mass Index vs. Fat Mass/Height³ as a screening tool for metabolic syndrome prediction in Colombian children and young people" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "R. Ramírez-Vélez" 1 => "J.E. Correa-Bautista" 2 => "H.A. Carrillo" 3 => "E. González-Jiménez" 4 => "J. Schmidt-RioValle" 5 => "M. Correa-Rodríguez" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.3390/nu10040412" "Revista" => array:6 [ "tituloSerie" => "Nutrients." "fecha" => "2018" "volumen" => "10" "numero" => "4" "paginaInicial" => "412" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/29584641" "web" => "Medline" ] ] ] ] ] ] ] ] 22 => array:3 [ "identificador" => "bib0115" "etiqueta" => "23" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Role of tri-ponderal mass index in cardio-metabolic risk assessment in children and adolescents: compared with body mass index" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:6 [ 0 => "X. Wang" 1 => "B. Dong" 2 => "J. Ma" 3 => "Y. Song" 4 => "Z. Zou" 5 => "L. Arnold" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1038/s41366-019-0416-y" "Revista" => array:7 [ "tituloSerie" => "Int J Obes (Lond)." "fecha" => "2020" "volumen" => "44" "numero" => "4" "paginaInicial" => "886" "paginaFinal" => "894" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/31332274" "web" => "Medline" ] ] ] ] ] ] ] ] 23 => array:3 [ "identificador" => "bib0120" "etiqueta" => "24" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Tri-ponderal mass index and body mass index in prediction of pediatric metabolic syndrome: the CASPIAN-V study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "M. Khoshhali" 1 => "M. Heidari-Beni" 2 => "M. Qorbani" 3 => "M.E. Motlagh" 4 => "H. Ziaodini" 5 => "R. Heshmat" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.20945/2359-3997000000206" "Revista" => array:7 [ "tituloSerie" => "Arch Endocrinol Metab." "fecha" => "2020" "volumen" => "64" "numero" => "2" "paginaInicial" => "171" "paginaFinal" => "178" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/32236304" "web" => "Medline" ] ] ] ] ] ] ] ] 24 => array:3 [ "identificador" => "bib0125" "etiqueta" => "25" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Age-specific estimates and comparisons of youth tri-ponderal mass index and body mass index in predicting adult obesity-related outcomes" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "F. Wu" 1 => "M.J. Buscot" 2 => "H. Niinikoski" 3 => "S.P. Rovio" 4 => "M. Juonala" 5 => "M.A. Sabin" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.jpeds.2019.10.062" "Revista" => array:6 [ "tituloSerie" => "J Pediatr." "fecha" => "2020" "volumen" => "218" "paginaInicial" => "198" "paginaFinal" => "203" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/31757470" "web" => "Medline" ] ] ] ] ] ] ] ] 25 => array:3 [ "identificador" => "bib0130" "etiqueta" => "26" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Tri-ponderal mass index as a tool for insulin resistance prediction in overweight adolescents: a cross-sectional study" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:6 [ 0 => "A.R. Matsuo" 1 => "W.A. Lopes" 2 => "J.C. Locatelli" 3 => "C.F. Simões" 4 => "G.H. de Oliveira" 5 => "N. Nardo Jr" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.nut.2020.110744" "Revista" => array:3 [ "tituloSerie" => "Nutrition." "fecha" => "2020" "volumen" => "74" ] ] ] ] ] ] 26 => array:3 [ "identificador" => "bib0135" "etiqueta" => "27" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "The relationship between tri-ponderal mass index and metabolic syndrome and its components in youth aged 10-20 years" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:1 [ 0 => "Y.S. Shim" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1038/s41598-019-50987-3" "Revista" => array:6 [ "tituloSerie" => "Sci Rep." "fecha" => "2019" "volumen" => "9" "numero" => "1" "paginaInicial" => "14462" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/31594996" "web" => "Medline" ] ] ] ] ] ] ] ] 27 => array:3 [ "identificador" => "bib0140" "etiqueta" => "28" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Evidence in obese children: contribution of tri-ponderal mass index or body mass index to dyslipidemia, obesity-inflammation, and insulin sensitivity" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "N. Akcan" 1 => "M. Obaid" 2 => "J. Salem" 3 => "R. Bundak" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1515/jpem-2019-0106" "Revista" => array:7 [ "tituloSerie" => "J Pediatr Endocrinol Metab." "fecha" => "2020" "volumen" => "33" "numero" => "2" "paginaInicial" => "223" "paginaFinal" => "231" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/31809264" "web" => "Medline" ] ] ] ] ] ] ] ] ] ] ] ] ] "idiomaDefecto" => "en" "url" => "/23870206/0000016000000009/v1_202305121215/S2387020623001407/v1_202305121215/en/main.assets" "Apartado" => array:4 [ "identificador" => "43310" "tipo" => "SECCION" "en" => array:2 [ "titulo" => "Original articles" "idiomaDefecto" => true ] "idiomaDefecto" => "en" ] "PDF" => "https://static.elsevier.es/multimedia/23870206/0000016000000009/v1_202305121215/S2387020623001407/v1_202305121215/en/main.pdf?idApp=UINPBA00004N&text.app=https://www.elsevier.es/" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2387020623001407?idApp=UINPBA00004N" ]
Información de la revista
Compartir
Descargar PDF
Más opciones de artículo
Original article
Triponderal mass index and markers of metabolic risk in children and adolescents with obesity
Índice de masa triponderal y marcadores de riesgo metabólico en niños y adolescentes con obesidad
Enrique Palomo Atancea,
, Francisco Javier Caballero Morab, David Espadas Maciác, Mercedes Marbán Calzónd, Pilar Sevilla Ramose, Lourdes García Villaescusaf, María Jesús Dabad Morenog, José Ramón Muñoz-Rodríguezh, Rafael Ruiz Canog
Autor para correspondencia
a Endocrinología Pediátrica, Servicio de Pediatría, Hospital General Universitario de Ciudad Real, Grupo de Endocrinología Pediátrica de Castilla-La Mancha (GEPCAM), Ciudad Real, Spain
b Endocrinología Pediátrica, Servicio de Pediatría, Hospital Santa Bárbara, Grupo de Endocrinología Pediátrica de Castilla – La Mancha (GEPCAM), Puertollano, Ciudad Real, Spain
c Endocrinología Pediátrica, Servicio de Pediatría, Hospital Virgen de la Luz, Grupo de Endocrinología Pediátrica de Castilla – La Mancha (GEPCAM), Cuenca, Spain
d Endocrinología Pediátrica. Servicio de Pediatría, Hospital General La Mancha Centro, Grupo de Endocrinología Pediátrica de Castilla – La Mancha (GEPCAM), Alcázar de San Juan, Ciudad Real, Spain
e Endocrinología Pediátrica, Servicio de Pediatría, Hospital Universitario de Guadalajara, Grupo de Endocrinología Pediátrica de Castilla – La Mancha (GEPCAM), Guadalajara, Spain
f Endocrinología Pediátrica, Servicio de Pediatría, Hospital General de Almansa, Grupo de Endocrinología Pediátrica de Castilla – La Mancha (GEPCAM), Almansa, Albacete, Spain
g Endocrinología Pediátrica, Servicio de Pediatría, Hospital General Universitario de Albacete, Grupo de Endocrinología Pediátrica de Castilla – La Mancha (GEPCAM), Albacete, Spain
h Unidad de Investigación Traslacional, Hospital General Universitario de Ciudad Real, Ciudad Real, Spain