Original article
Skinfold reference curves and their use in predicting metabolic syndrome risk in children
Curvas de referência de dobras cutâneas e sua utilização na predição do risco de síndrome metabólica em crianças
Alynne C.R. Andakia,
, Teresa M.B. de Quadrosb, Alex P. Gordiab, Jorge Motac, Adelson L.A. Tinôcod, Edmar L. Mendesa
Corresponding author
a Universidade Federal do Triângulo Mineiro (UFTM), Departamento de Ciências do Esporte, Uberaba, MG, Brazil
b Universidade Federal do Recôncavo da Bahia (UFRB), Centro de Formação de Professores, Cruz das Almas, BA, Brazil
c Universidade do Porto, Faculdade do Desporto, Porto, Portugal
d Universidade Federal de Viçosa (UFV), Departamento de Nutrição e Saúde, Viçosa, MG, Brazil
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FISH, fluorescence in situ hybridization; MLPA, multiplex ligation probe amplification; CMA, chromosomal microarray; CNVs, copy number variations; ChAS, chromosome analysis suite; DGV, database of genomic variants; DECIPHER, database of chromosomal imbalance and phenotype in humans using ensemble resources; OMIM, Online Mendelian Inheritance In Man.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Miriam Coelho Molck, Milena Simioni, Társis Paiva Vieira, Ilária Cristina Sgardioli, Fabíola Paoli Monteiro, Josiane Souza, Agnes Cristina Fett-Conte, Têmis Maria Félix, Isabella Lopes Monlléo, Vera Lúcia Gil-da-Silva-Lopes" "autores" => array:10 [ 0 => array:2 [ "nombre" => "Miriam Coelho" "apellidos" => "Molck" ] 1 => array:2 [ "nombre" => "Milena" "apellidos" => "Simioni" ] 2 => array:2 [ "nombre" => "Társis" "apellidos" => "Paiva Vieira" ] 3 => array:2 [ "nombre" => "Ilária Cristina" "apellidos" => "Sgardioli" ] 4 => array:2 [ "nombre" => "Fabíola" "apellidos" => "Paoli Monteiro" ] 5 => array:2 [ "nombre" => "Josiane" "apellidos" => "Souza" ] 6 => array:2 [ "nombre" => "Agnes Cristina" "apellidos" => "Fett-Conte" ] 7 => array:2 [ "nombre" => "Têmis Maria" "apellidos" => "Félix" ] 8 => array:2 [ "nombre" => "Isabella" "apellidos" => "Lopes Monlléo" ] 9 => array:2 [ "nombre" => "Vera Lúcia" "apellidos" => "Gil-da-Silva-Lopes" ] ] ] ] ] "idiomaDefecto" => "en" "Traduccion" => array:1 [ "pt" => array:9 [ "pii" => "S2255553617300332" "doi" => "10.1016/j.jpedp.2017.03.004" "estado" => "S300" "subdocumento" => "" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "pt" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2255553617300332?idApp=UINPBA000049" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0021755717302188?idApp=UINPBA000049" "url" => "/00217557/0000009300000005/v1_201709220054/S0021755717302188/v1_201709220054/en/main.assets" ] "itemAnterior" => array:20 [ "pii" => "S0021755717304552" "issn" => "00217557" "doi" => "10.1016/j.jped.2016.11.012" "estado" => "S300" "fechaPublicacion" => "2017-09-01" "aid" => "501" "copyright" => "Sociedade Brasileira de Pediatria" "documento" => "article" "crossmark" => 1 "licencia" => "http://creativecommons.org/licenses/by-nc-nd/4.0/" "subdocumento" => "fla" "cita" => "J Pediatr (Rio J). 2017;93:482-9" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:2 [ "total" => 1344 "formatos" => array:3 [ "EPUB" => 81 "HTML" => 1048 "PDF" => 215 ] ] "en" => array:13 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original article</span>" "titulo" => "Association between weather seasonality and blood parameters in riverine populations of the Brazilian Amazon" "tienePdf" => "en" "tieneTextoCompleto" => "en" "tieneResumen" => array:2 [ 0 => "en" 1 => "pt" ] "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "482" "paginaFinal" => "489" ] ] "titulosAlternativos" => array:1 [ "pt" => array:1 [ "titulo" => "Relação da sazonalidade climática com parâmetros sanguíneos de ribeirinhos residentes na Amazônia brasileira" ] ] "contieneResumen" => array:2 [ "en" => true "pt" => true ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1435 "Ancho" => 3020 "Tamanyo" => 146292 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Distribution of values and confidence intervals (CI) for serum iron and ferritin, according to community and period. *Statistically significant result for comparison of means between the periods (dry and rainy seasons) through paired Student's <span class="elsevierStyleItalic">t</span>-test and <span class="elsevierStyleItalic">p</span>-value <0.05. <span class="elsevierStyleSup">#</span>Statistically significant result for comparison of means between the communities (in each period) through Student's <span class="elsevierStyleItalic">t</span>-test for independent samples and <span class="elsevierStyleItalic">p</span>-value <0.05.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Poliany C.O. 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Andaki, Teresa M.B. de Quadros, Alex P. Gordia, Jorge Mota, Adelson L.A. Tinôco, Edmar L. Mendes" "autores" => array:6 [ 0 => array:4 [ "nombre" => "Alynne C.R." "apellidos" => "Andaki" "email" => array:1 [ 0 => "alynneandaki@yahoo.com.br" ] "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" => "Teresa M.B. de" "apellidos" => "Quadros" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 2 => array:3 [ "nombre" => "Alex P." "apellidos" => "Gordia" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 3 => array:3 [ "nombre" => "Jorge" "apellidos" => "Mota" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] ] ] 4 => array:3 [ "nombre" => "Adelson L.A." "apellidos" => "Tinôco" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">d</span>" "identificador" => "aff0020" ] ] ] 5 => array:3 [ "nombre" => "Edmar L." "apellidos" => "Mendes" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] ] "afiliaciones" => array:4 [ 0 => array:3 [ "entidad" => "Universidade Federal do Triângulo Mineiro (UFTM), Departamento de Ciências do Esporte, Uberaba, MG, Brazil" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Universidade Federal do Recôncavo da Bahia (UFRB), Centro de Formação de Professores, Cruz das Almas, BA, Brazil" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Universidade do Porto, Faculdade do Desporto, Porto, Portugal" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Universidade Federal de Viçosa (UFV), Departamento de Nutrição e Saúde, Viçosa, MG, Brazil" "etiqueta" => "d" "identificador" => "aff0020" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "pt" => array:1 [ "titulo" => "Curvas de referência de dobras cutâneas e sua utilização na predição do risco de síndrome metabólica em crianças" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 4107 "Ancho" => 2097 "Tamanyo" => 367297 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Percentile curves (p5, p10, p25, p50, p75, p90, and p95) of the triceps, biceps, subscapular, and suprailiac skinfolds, as well as for their sum, of girls and boys aged 6–10 years, Uberaba, MG, Brazil.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Cardiovascular diseases are the main cause of death in Brazil<a class="elsevierStyleCrossRef" href="#bib0155"><span class="elsevierStyleSup">1</span></a> and worldwide.<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">2</span></a> Cardiovascular risk factors, such as total and visceral obesity, dyslipidemias, arterial hypertension, hyperglycemia, and hyperinsulinemia have been considered determinants for the development of cardiovascular diseases. Metabolic syndrome (MetS), characterized by the presence of three or more of these risk factors,<a class="elsevierStyleCrossRef" href="#bib0165"><span class="elsevierStyleSup">3</span></a> has gained importance due to its consistent association with cardiovascular morbimortality.<a class="elsevierStyleCrossRef" href="#bib0170"><span class="elsevierStyleSup">4</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">The presence of cardiovascular risk factors and MetS has been observed in adults<a class="elsevierStyleCrossRef" href="#bib0175"><span class="elsevierStyleSup">5</span></a> as well as in children and adolescents.<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">6</span></a> In recent years, concerns about the diagnosis of and early intervention on these metabolic disorders has increased due to evidence that risk factors observed in childhood and adolescence tend to persist and worsen in adulthood.<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">7</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">In addition to blood pressure (BP) and waist circumference measurements, biochemical analyses of blood fractions of HDL-c, triglycerides, and glucose should be performed for the diagnosis of MetS. Blood collection is an invasive, expensive and difficult to perform technique, especially in children and adolescents. In turn, the use of practical and low-cost methods may be an important alternative for the screening of MetS at the population level. In this sense, skinfolds (SFs) were shown to be a promising tool for MetS screening in the pediatric population, due to its strong correlation with subcutaneous adiposity.<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">8</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">According to Ali et al.,<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">9</span></a> the accumulation of subcutaneous adiposity is a strong predictor of insulin resistance and hypertriglyceridemia in children and adolescents, and was a stronger predictor of cardiometabolic risk factors than visceral fat. Furthermore, the influence of subcutaneous adiposity on MetS risk is present in children and adolescents, but not in adults.<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">9</span></a></p><p id="par0025" class="elsevierStylePara elsevierViewall">Percentile curves for SFs have been developed with samples of young North-American,<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">10</span></a> Polish,<a class="elsevierStyleCrossRef" href="#bib0205"><span class="elsevierStyleSup">11</span></a> and Indian populations.<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">12</span></a> It is noteworthy that the World Health Organization<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">13</span></a> presented an important publication in 2007, in which reference curves for anthropometric measurements, including triceps and subscapular SFs were created as an international reference for multi-country populations (Brazil, United States, Ghana, India, Norway, and Oman). However, to the best of the authors’ knowledge, SF percentile curves have not been proposed for Brazilian children, nor are there any SF percentile curves that can be used to predict MetS in the pediatric population. Reference curves from other populations may not be applicable to Brazilian children due to ethnic, cultural, and socioeconomic differences.</p><p id="par0030" class="elsevierStylePara elsevierViewall">Therefore, the present study aimed to design reference curves of four SFs (subscapular, suprailiac, biceps, and triceps) and to determine cutoffs to predict the risk of MetS in children aged 6–10 years.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Methods</span><p id="par0035" class="elsevierStylePara elsevierViewall">A cross-sectional, population-based epidemiological study was carried out with a probabilistic sample of children aged 6–10 years from public and private schools located in the urban and rural areas of the city of Uberaba, MG, Brazil.</p><p id="par0040" class="elsevierStylePara elsevierViewall">The sample calculation considered the number of children enrolled in Elementary School (1st to 9th year of schooling), a prevalence of MetS of 50% (unknown prevalence in the municipality), tolerable error of 3.5% and confidence level of 95%. The minimum sample size was 768 children; after adding 10% to compensate for losses and refusals and 20% to minimize confounding factors, the sample totaled 1014 children.</p><p id="par0045" class="elsevierStylePara elsevierViewall">For sample selection, the schools were stratified according to the type of school as municipal, state, or private.</p><p id="par0050" class="elsevierStylePara elsevierViewall">The World Health Organization<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">14</span></a> recommends that 10–15 sample collection points (schools) be used for epidemiological surveys, and that the number of subjects in each age group should vary between 25 and 50 for each site. Therefore, 15 of the 90 eligible schools of the municipality of Uberaba were randomly selected using the random number table. For the adequacy and representativeness of the local population, the number of children in each stratum was determined proportionally to the number of enrollments, according to data provided by the State Education Secretariat. Municipal schools accounted for 43.6% of enrollments, 41.9% of students were enrolled from state schools and 14.5% from private schools.</p><p id="par0055" class="elsevierStylePara elsevierViewall">After approval by the Ethics Committee in Research with Human Beings of Universidade Federal do Triângulo Mineiro (Protocol CEP/UFTM: 1710), the school principals were contacted to obtain authorization and to schedule the collections. Students who met the inclusion criteria and were interested in participating in the research received the informed consent form for the information and signature of their parents and/or guardians. Anthropometry and blood collections were performed at the school itself, following specific protocols.</p><p id="par0060" class="elsevierStylePara elsevierViewall">The biceps (BSF), triceps (TSF), subscapular (SSSF), and suprailiac (SISF) SFs were obtained using an adipometer (Lange Skinfold Caliper, England, UK) exerting constant pressure of 10<span class="elsevierStyleHsp" style=""></span>g/mm<span class="elsevierStyleSup">2</span>. Measurements were performed on the right side of the body, with three non-consecutive repetitions for each measurement. The final measure constituted the mean of the three values. All measurements were performed by two qualified evaluators submitted to previous training and calibration. The results were interpreted alone, as well as by the sum of the four SFs assessed, and were expressed in millimeters (mm).</p><p id="par0065" class="elsevierStylePara elsevierViewall">BP was measured using a mercury column sphygmomanometer (Unitec, São Paulo, Brazil), with cuffs of appropriate sizes for the circumference of the children's arms, in accordance with the VI Brazilian Guidelines for Hypertension.<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">15</span></a> Three BP measurements were performed at the first visit, after which the first was discarded and the mean of the last two were considered. When the child had an alteration in systolic or diastolic BP above the 90th percentile, two further measurements were performed on two different days following the same procedure adopted on the first day.<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">15</span></a></p><p id="par0070" class="elsevierStylePara elsevierViewall">The volunteers were invited to go to school, following a 12-h fast, on certain days and at certain times, accompanied by their parents. Nursing professionals collected blood samples (8<span class="elsevierStyleHsp" style=""></span>mL) in BD Vacutainer™ tubes (Becton, Dickinson and Company, New Jersey, USA). Serum samples were analyzed for the measurement of HDL-c and triglycerides and plasma for glycemia. The semi-automated Bio 200F analyzer (Bioplus, São Paulo, Brazil) was used. Standardized methods quantitatively determined blood variables, following the standards and technical specifications of the reagents used.</p><p id="par0075" class="elsevierStylePara elsevierViewall">The diagnosis of MetS<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">16</span></a> was determined by the presence of at least three of the following alterations: triglycerides ≥100<span class="elsevierStyleHsp" style=""></span>mg/dL; HDL-c <50<span class="elsevierStyleHsp" style=""></span>mg/dL; glycemia ≥110<span class="elsevierStyleHsp" style=""></span>mg/dL; waist circumference ≥75th percentile for age and gender; and alteration in BP (diastolic or systolic) >90th percentile adjusted for age, height and gender.</p><p id="par0080" class="elsevierStylePara elsevierViewall">Variables were tested for their normality using the Kolmogorov–Smirnov test. Outliers were identified and withdrawn using the interval between quartiles. The Mann–Whitney <span class="elsevierStyleItalic">U</span>-test was used to compare independent groups with non-parametric distribution.</p><p id="par0085" class="elsevierStylePara elsevierViewall">For comparison with other studies, the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles were chosen as reference values. Reference curves were created using the Cole LMS method.<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">17</span></a> The LMS method assumes that, for independent data with positive values, the age-specific Box–Cox transformation can be employed to make them have a normal distribution; the <span class="elsevierStyleItalic">L</span>, <span class="elsevierStyleItalic">M</span>, and <span class="elsevierStyleItalic">S</span> values are natural cubic splines with knot sequence without each age range. The sample, in each gender, was separated into age groups with 100 or more individuals, the lowest number considered to be adequate for the LMS method.<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">17</span></a></p><p id="par0090" class="elsevierStylePara elsevierViewall">The receiver operating characteristic (ROC) curve was used to evaluate the predictive capacity of diagnostic tests. The areas below the ROC curves (AUC) were calculated to assess the discriminatory power of the SFs in the indication of metabolic alterations constituting the MetS. The sensitivity and specificity values of the anthropometric indicators were calculated for each cutoff present in the sample. The cutoff that showed the best equilibrium between sensitivity and specificity was chosen to optimize the association between these two parameters, showing higher accuracy (lower number of false negative and false positive values). The statistical significance of each analysis was verified by the AUC and by the lower limit of the 95% confidence interval >0.5.<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">18</span></a></p></span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Results</span><p id="par0095" class="elsevierStylePara elsevierViewall">A total of 1480 elementary school students from the urban and rural areas of Uberaba, MG, Brazil, with a mean age of 8.55 years (SD<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1.53 years), of whom 52.2% were females, participated in the study.</p><p id="par0100" class="elsevierStylePara elsevierViewall">Girls had a higher prevalence of MetS (12.6% <span class="elsevierStyleItalic">vs</span>. 8.5%, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05) and higher SF values in all assessed anatomical points (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05) when compared with boys (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0105" class="elsevierStylePara elsevierViewall">Percentile curves (p5, p10, p25, p50, p75, p90, and p95) were created for the four assessed SFs, as well as for their sum, for both genders (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>). Overall, all SFs showed a linear increase according to age and gender, with higher values being observed in girls.</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0110" class="elsevierStylePara elsevierViewall">The four assessed SFs and their sum were accurate in predicting MetS for girls (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>) and boys (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>). Most of the suggested values are above the 75th percentile for age and gender.</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><elsevierMultimedia ident="tbl0015"></elsevierMultimedia></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Discussion</span><p id="par0115" class="elsevierStylePara elsevierViewall">The present study showed percentile SF curves of the central and peripheral regions of the body, as well as the sum of the four SFs to predict the risk of MetS according to age and gender in Brazilian children. The curves outlined here may be a useful strategy to prevent the risk of MetS in childhood, with the possibility of being used in schools, family health units, clinics, and hospitals. According to the present findings, both the central adiposity, as well as the peripheral adiposity SFs and the sum of four SFs showed cutoffs with high sensitivity and specificity values to predict the risk of MetS in children. Approximately 75% of the children in the present study with SF values above the 75th percentile, regardless of the assessed SF, had MetS.</p><p id="par0120" class="elsevierStylePara elsevierViewall">The prevalence of MetS in Brazilian children and adolescents varied from 0% to 42.4%, according to data from a systematic review.<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">19</span></a> In the present study, MetS was prevalent in 12.6% of the girls and 8.5% of the boys, with a significant difference between the genders. The heterogeneity of definitions and cutoffs for the MetS components may explain, at least partly, the different prevalence rates reported in the literature.<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">19</span></a> However, it is true that the prevalence of MetS has been increasing among children and adolescents, with a significantly higher proportion among those who are obese.<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">20</span></a></p><p id="par0125" class="elsevierStylePara elsevierViewall">The percentile distribution of the triceps and subscapular SFs were performed in 8568 Chinese schoolchildren aged 7–18 years of age<a class="elsevierStyleCrossRef" href="#bib0255"><span class="elsevierStyleSup">21</span></a> and 32,783 North-American children and adolescents.<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">10</span></a> The percentile values for TSF and SSSF of Chinese and American children were lower than the percentiles of boys and girls in the present study. This result is of concern, due to the association between SFs and central obesity, unfavorable lipid profile, increased levels of insulin and BP, and left ventricular mass.<a class="elsevierStyleCrossRef" href="#bib0260"><span class="elsevierStyleSup">22</span></a> The accumulation of subcutaneous fat, translated into high SF values, increase the chances of children having metabolic alterations.</p><p id="par0130" class="elsevierStylePara elsevierViewall">Pre-pubertal Mexican children aged 6–10 years had a three-fold higher chance of having alterations in MetS components when the distribution of SSSF was in the fourth quartile of the sample (low HDL-c levels [OR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>3.16; 95% CI: 1.41–7.10; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.01]) and high triglyceride levels (OR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>3.27; 95% CI: 2.02–5.29; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001).<a class="elsevierStyleCrossRef" href="#bib0265"><span class="elsevierStyleSup">23</span></a> However, high values of Σ3SF (TSF<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>BSF<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>SSSF; >90th percentile) in German children aged 3–11 years increased the chance of having three or more cardiovascular risk factors by 1.6-fold (95% CI: 1.1–2.2; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05) and the chance of having arterial hypertension by 1.7-fold (95% CI: 1.1–2.7; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05)].<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">24</span></a></p><p id="par0135" class="elsevierStylePara elsevierViewall">The results of the present study demonstrated that all isolated SF measures predict the risk of MetS in both genders. In the scientific investigations related to the subject, studies with TSF and SSSF are predominant.<a class="elsevierStyleCrossRefs" href="#bib0200"><span class="elsevierStyleSup">10,13,21,25</span></a> Many studies have used SF values alone as a predictor of the amount of body fat<a class="elsevierStyleCrossRefs" href="#bib0275"><span class="elsevierStyleSup">25–29</span></a> and isolated cardiometabolic risk factors.<a class="elsevierStyleCrossRefs" href="#bib0210"><span class="elsevierStyleSup">12,30</span></a> Conversely, studies investigating the power of SF in predicting MetS in the pediatric population remain scarce.</p><p id="par0140" class="elsevierStylePara elsevierViewall">The use of the sum of SF absolute values may become an interesting predictor of MetS, as it minimizes biases in predictive body composition equations, as well as suggesting values that show equilibrium/disequilibrium of body fat distribution (TSF<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>BSF<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>SSSF<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>SISF). Among the different anthropometric measures tested, ∑4SF was the most accurate predictor of MetS in Brazilian girls and boys, with AUC<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.908 and AUC<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.897, respectively.<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">6</span></a></p><p id="par0145" class="elsevierStylePara elsevierViewall">In the present study, the ∑4SF showed an AUC of 0.859 for girls and 0.879 for boys, and the suggested cutoffs showed high sensitivity values (>80%).</p><p id="par0150" class="elsevierStylePara elsevierViewall">To the best of the authors’ knowledge, this is the first study with percentile curves of the central and peripheral region SFs, as well as the sum of four SFs, used to predict MetS in a representative sample of Brazilian schools. However, this study had a cross-sectional design, which did not allow the determination of whether alterations in subcutaneous adiposity reflect changes in the MetS components. Thus, longitudinal studies are necessary to define the causal association between MetS and subcutaneous adiposity. It is worth mentioning that, although the study population was delimited among students from the 1st to the 5th year of Elementary School, the State Education Secretariat provided updated data on all Elementary School years, which may have overestimated the sample calculation.</p><p id="par0155" class="elsevierStylePara elsevierViewall">Reference curves from other countries can either underestimate or overestimate the disease due to ethnic, socioeconomic, and cultural differences. The development of percentile curves with populations of different geographic areas is a relevant challenge to allow a more accurate screening of MetS in young individuals through the evaluation of SFs.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Funding</span><p id="par0160" class="elsevierStylePara elsevierViewall">Fundação de Amparo à Pesquisa do Estado de Minas Gerais (<span class="elsevierStyleGrantSponsor" id="gs1">Fapemig</span>).</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Conflicts of interest</span><p id="par0165" class="elsevierStylePara elsevierViewall">The authors declare no conflicts of interest.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:11 [ 0 => array:3 [ "identificador" => "xres904128" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objectives" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusion" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec884745" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres904129" "titulo" => "Resumo" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivos" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusão" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec884744" "titulo" => "Palavras-chave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:2 [ "identificador" => "sec0010" "titulo" => "Methods" ] 6 => array:2 [ "identificador" => "sec0015" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "sec0020" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0025" "titulo" => "Funding" ] 9 => array:2 [ "identificador" => "sec0030" "titulo" => "Conflicts of interest" ] 10 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2016-07-28" "fechaAceptado" => "2016-11-16" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec884745" "palabras" => array:4 [ 0 => "Anthropometry" 1 => "Metabolic syndrome X" 2 => "Cross-sectional studies" 3 => "Child" ] ] ] "pt" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palavras-chave" "identificador" => "xpalclavsec884744" "palabras" => array:4 [ 0 => "Antropometria" 1 => "Síndrome X" 2 => "Estudos de corte transversal" 3 => "Crianças" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Objectives</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">To draw skinfold (SF) reference curves (subscapular, suprailiac, biceps, triceps) and to determine SF cutoff points for predicting the risk of metabolic syndrome (MetS) in children aged 6–10 years old.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">This was a cross-sectional study with a random sample of 1480 children aged 6–10 years old, 52.2% females, from public and private schools located in the urban and rural areas of the municipality of Uberaba (MG). Anthropometry, blood pressure, and fasting blood samples were taken at school, following specific protocols. The LMS method was used to draw the reference curves and ROC curve analysis to determine the accuracy and cutoff points for the evaluated skinfolds.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">The four SF evaluated (subscapular, suprailiac, biceps, and triceps) and their sum (∑4SF) were accurate in predicting MetS for both girls and boys. Additionally, cutoffs have been proposed and percentile curves (p5, p10, p25, p50, p75, p90, and p95) were outlined for the four SF and ∑4SF, for both genders.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusion</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">SF measurements were accurate in predicting metabolic syndrome in children aged 6–10 years old. Age- and gender-specific smoothed percentiles curves of SF provide a reference for the detection of risk for MetS in children.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objectives" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusion" ] ] ] "pt" => array:3 [ "titulo" => "Resumo" "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Objetivos</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Desenhar curvas de referência de quatro dobras cutâneas (subescapular, suprailíaca, bíceps, tríceps) e determinar pontos de corte para predizer o risco de SM em crianças de seis a 10 anos de idade.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Métodos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Estudo epidemiológico de base populacional, corte transversal, com amostra probabilística, estratificada por segmento de ensino, com 1.480 crianças de 6 a 10 anos de idade, 52,2% do sexo feminino, oriundas de escolas públicas e privadas, localizadas na zona urbana e rural do município de Uberaba (MG). Antropometria (dobras cutâneas), pressão arterial e as coletas de sangue em jejum foram realizadas em espaço reservado na escola, seguindo protocolos específicos. O métodolo LMS foi utilizado para desenhar as curvas de referência e análise de curva ROC para determinar a acurácia e pontos de corte para as dobras cutâneas avaliadas.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">As quatro DC avaliadas (subescapular, suprailíaca, bíceps e tríceps) e o seu somatório (∑4DC) foram acurados na predição da SM para meninas e meninos. Adicionalmente, pontos de corte foram propostos e curvas percentílicas (p5, p10, p25, p50, p75, p90 e p95) foram delineadas para as quatro DC e o ∑4DC, para ambos os sexos.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusão</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Medidas de DC foram acuradas em predizer SM em escolares de seis a 10 anos de idade. As curvas percentílicas de DC desenhadas por idade e sexo fornecem referência na detecção do risco de SM em crianças.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivos" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusão" ] ] ] ] "NotaPie" => array:2 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Please cite this article as: Andaki AC, Quadros TM, Gordia AP, Mota J, Tinôco AL, Mendes EL. Skinfold reference curves and their use in predicting metabolic syndrome risk in children. J Pediatr (Rio J). 2017;93:490–6.</p>" ] 1 => array:2 [ "etiqueta" => "☆☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0010">Study carried out at Universidade Federal do Triângulo Mineiro, Uberaba, MG, Brazil.</p>" ] ] "multimedia" => array:4 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 4107 "Ancho" => 2097 "Tamanyo" => 367297 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Percentile curves (p5, p10, p25, p50, p75, p90, and p95) of the triceps, biceps, subscapular, and suprailiac skinfolds, as well as for their sum, of girls and boys aged 6–10 years, Uberaba, MG, Brazil.</p>" ] ] 1 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleItalic">n</span>, sample number; SD, standard deviation; Min, minimum value; Max, maximum value; TSF, triceps skinfold; BSF, biceps skinfold; SSSF, subscapular skinfold; SISF, suprailiac skinfold; ∑4SFs, sum of the four skinfolds evaluated.</p><p id="spar0060" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleItalic">Note</span>: Significant difference between genders <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>0.05, Mann–Whitney test.</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-with-role" title="table-head ; entry_with_role_rowhead " align="left" valign="top" scope="col">Variables \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Girls (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>773)</th><th class="td" title="table-head " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Boys (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>707)</th><th class="td" title="table-head " align="left" valign="top" scope="col"><span class="elsevierStyleItalic">p</span>-Value \t\t\t\t\t\t\n \t\t\t\t</th></tr><tr title="table-row"><th class="td" title="table-head " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Mean (SD) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Median (min–max) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Mean (SD) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Median (min–max) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">BSF (mm) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.14 (5.15) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.00 (3.00–29.00) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.57 (5.29) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">6.67 (3.00–28.00) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">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="table-entry ; entry_with_role_rowhead " align="left" valign="top">TSF (mm) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.45 (5.66) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.33 (5.00–35.00) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.71 (6.67) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.67 (5.00–35.00) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">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="table-entry ; entry_with_role_rowhead " align="left" valign="top">SSSF (mm) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.77 (7.63) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.00 (4.00–44.00) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.85 (7.50) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">7.00 (4.00–44.00) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">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="table-entry ; entry_with_role_rowhead " align="left" valign="top">SISF (mm) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.40 (10.56) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.67 (3.00–51.00) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.12 (10.23) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">6.67 (3.00–50.00) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">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="table-entry ; entry_with_role_rowhead " align="left" valign="top">∑4SFs (mm) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">50.93 (28.31) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">42.0 (10.00–163.00) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">42.37 (29.79) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">31.00 (11.00–202.67) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1520142.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Descriptive skinfold characteristics of schoolchildren aged 6–10 years of age, from the municipality of Uberaba, MG, Brazil, by gender.</p>" ] ] 2 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at2" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">AUC, area under the receiver operating characteristic curve; 95% CI, 95% confidence interval; <span class="elsevierStyleItalic">S</span>, sensitivity; Sp, specificity; TSF, triceps skinfold; BSF, biceps skinfold; SSSF, subscapular skinfold; SISF, suprailiac skinfold; ∑4SFs, sum of the four assessed skinfolds.</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="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Age (years) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Predictors \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">AUC \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span>-Value \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">95% CI</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Cutoff (mm) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">S</span> (%) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Sp (%) \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " rowspan="5" align="char" valign="top">6</td><td class="td" title="table-entry " align="left" valign="top">BSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.832 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.014 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.709 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.955 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">79 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">TSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.771 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.044 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.566 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.977 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">15.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">82 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SSSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.864 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.007 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.760 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.967 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">74 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SISF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.805 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.024 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.666 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.943 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">75 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">∑4SFs \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.833 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.013 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.708 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.959 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">40.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">68 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="9" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="5" align="char" valign="top">7</td><td class="td" title="table-entry " align="left" valign="top">BSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.894 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.81 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.977 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">88 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">85 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">TSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.927 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.874 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.98 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">83 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SSSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.924 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.871 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.978 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">86 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SISF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.909 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.841 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.977 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">76 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">∑4SFs \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.927 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.872 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.982 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">57.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">83 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="9" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="5" align="char" valign="top">8</td><td class="td" title="table-entry " align="left" valign="top">BSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.803 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.705 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.902 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">87 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">65 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">TSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.838 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.751 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.924 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">73 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">84 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SSSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.874 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.775 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.974 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">84 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SISF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.828 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.727 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.929 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">87 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">65 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">∑4SFs \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.858 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.770 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.945 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">57.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">78 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="9" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="5" align="char" valign="top">9</td><td class="td" title="table-entry " align="left" valign="top">BSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.862 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.773 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.951 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">86 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">79 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">TSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.844 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.731 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.956 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">85 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">71 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SSSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.88 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.802 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.959 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">86 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SISF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.84 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.752 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.927 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">60 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">∑4SFs \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.871 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.788 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.954 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">66 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">86 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">78 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="9" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="5" align="char" valign="top">10</td><td class="td" title="table-entry " align="left" valign="top">BSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.764 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.627 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.902 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">68 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">TSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.756 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.629 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.884 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">19 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">75 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">81 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SSSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.823 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.701 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.945 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">15.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">79 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">78 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SISF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.78 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.648 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.911 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">18.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">71 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">∑4SFs \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.791 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.659 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.923 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">71.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1520143.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Skinfold cutoffs for predicting metabolic syndrome in girls, by age, municipality of Uberaba, MG, Brazil.</p>" ] ] 3 => array:8 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at3" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">AUC, area under the receiver operating characteristic curve; 95% CI, 95% confidence interval; <span class="elsevierStyleItalic">S</span>, sensitivity; Sp, specificity; TSF, triceps skinfold; BSF, biceps skinfold; SSSF, subscapular skinfold; SISF, suprailiac skinfold; ∑4SFs, sum of the four assessed skinfolds.</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="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Age (years) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Predictors \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">AUC \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span>-Value \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">95% CI</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Cutoff (mm) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">S</span> (%) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Sp (%) \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " rowspan="5" align="char" valign="top">6</td><td class="td" title="table-entry " align="left" valign="top">BSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.95 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.002 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.902 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">91.5 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">TSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.95 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.002 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.893 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">16.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">88.7 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SSSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.93 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.004 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.854 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">82.6 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SISF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.90 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.007 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.807 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.997 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">81.6 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">∑4SFs \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.003 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.87 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">51.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">86.1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="9" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="5" align="char" valign="top">7</td><td class="td" title="table-entry " align="left" valign="top">BSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.86 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.007 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.726 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.994 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">72.2 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">TSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.83 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.015 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.681 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.969 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">72.6 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SSSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.90 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.003 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.789 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">7.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">71.6 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SISF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.82 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.016 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.635 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">7.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">60 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">60.7 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">∑4SFs \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.86 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.007 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.71 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">32.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">66.2 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="9" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="5" align="char" valign="top">8</td><td class="td" title="table-entry " align="left" valign="top">BSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.84 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.044 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.641 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">66.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">63.1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">TSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.84 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.048 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.626 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">66.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">61.1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SSSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.88 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.025 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.756 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">73.9 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SISF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.91 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.016 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.821 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">82.5 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">∑4SFs \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.89 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.024 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.761 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">42.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">75.5 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="9" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="5" align="char" valign="top">9</td><td class="td" title="table-entry " align="left" valign="top">BSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.86 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.767 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.955 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">87.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">68.2 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">TSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.86 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.769 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.954 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">88.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">72.0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SSSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.92 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.868 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.980 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">83.7 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SISF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.92 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.852 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.982 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">88.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">81.4 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">∑4SFs \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.90 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.832 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.974 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">55.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">88.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">81.4 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="9" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="5" align="char" valign="top">10</td><td class="td" title="table-entry " align="left" valign="top">BSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.678 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.930 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">86.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">70.9 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">TSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.78 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.645 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.917 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">79.6 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SSSF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.77 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.002 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.638 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.905 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">72.3 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SISF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.79 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.653 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.920 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">22.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">73.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">86.3 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">∑4SFs \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.79 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.661 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.920 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">61.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80.3 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1520144.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Skinfold cutoffs for predicting metabolic syndrome in girls, by age, municipality of Uberaba, MG, Brazil.</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:30 [ 0 => array:3 [ "identificador" => "bib0155" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Mortality due to cardiovascular diseases in Brazil and in the metropolitan region of Sao Paulo: a 2011 update" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:2 [ 0 => "A.P. 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| Year/Month | Html | Total | |
|---|---|---|---|
| 2024 November | 5 | 3 | 8 |
| 2024 October | 18 | 30 | 48 |
| 2024 September | 25 | 23 | 48 |
| 2024 August | 40 | 21 | 61 |
| 2024 July | 66 | 38 | 104 |
| 2024 June | 27 | 14 | 41 |
| 2024 May | 18 | 12 | 30 |
| 2024 April | 30 | 22 | 52 |
| 2024 March | 35 | 16 | 51 |
| 2024 February | 50 | 24 | 74 |
| 2024 January | 44 | 25 | 69 |
| 2023 December | 17 | 25 | 42 |
| 2023 November | 14 | 23 | 37 |
| 2023 October | 19 | 34 | 53 |
| 2023 September | 18 | 33 | 51 |
| 2023 August | 11 | 9 | 20 |
| 2023 July | 18 | 14 | 32 |
| 2023 June | 19 | 8 | 27 |
| 2023 May | 21 | 15 | 36 |
| 2023 April | 21 | 3 | 24 |
| 2023 March | 42 | 22 | 64 |
| 2023 February | 33 | 12 | 45 |
| 2023 January | 19 | 15 | 34 |
| 2022 December | 34 | 26 | 60 |
| 2022 November | 28 | 21 | 49 |
| 2022 October | 25 | 38 | 63 |
| 2022 September | 19 | 25 | 44 |
| 2022 August | 24 | 41 | 65 |
| 2022 July | 33 | 46 | 79 |
| 2022 June | 19 | 21 | 40 |
| 2022 May | 20 | 28 | 48 |
| 2022 April | 26 | 37 | 63 |
| 2022 March | 26 | 33 | 59 |
| 2022 February | 11 | 19 | 30 |
| 2022 January | 10 | 16 | 26 |
| 2021 December | 11 | 21 | 32 |
| 2021 November | 8 | 11 | 19 |
| 2021 October | 10 | 20 | 30 |
| 2021 September | 5 | 11 | 16 |
| 2021 August | 9 | 10 | 19 |
| 2021 July | 3 | 12 | 15 |
| 2021 June | 5 | 6 | 11 |
| 2021 May | 11 | 12 | 23 |
| 2021 April | 12 | 13 | 25 |
| 2021 March | 11 | 4 | 15 |
| 2021 February | 2 | 7 | 9 |
| 2021 January | 10 | 7 | 17 |
| 2020 December | 10 | 8 | 18 |
| 2020 November | 7 | 14 | 21 |
| 2020 October | 12 | 8 | 20 |
| 2020 September | 12 | 12 | 24 |
| 2020 August | 2 | 3 | 5 |
| 2020 July | 8 | 7 | 15 |
| 2020 June | 6 | 3 | 9 |
| 2020 May | 2 | 4 | 6 |
| 2020 April | 6 | 12 | 18 |
| 2020 March | 3 | 3 | 6 |
| 2020 February | 14 | 13 | 27 |
| 2020 January | 10 | 17 | 27 |
| 2019 December | 10 | 5 | 15 |
| 2019 November | 3 | 3 | 6 |
| 2019 October | 4 | 11 | 15 |
| 2019 September | 6 | 5 | 11 |
| 2019 August | 12 | 9 | 21 |
| 2019 July | 14 | 6 | 20 |
| 2019 June | 11 | 8 | 19 |
| 2019 May | 3 | 5 | 8 |
| 2019 April | 13 | 8 | 21 |
| 2019 March | 5 | 5 | 10 |
| 2019 February | 4 | 7 | 11 |
| 2019 January | 6 | 4 | 10 |
| 2018 December | 7 | 8 | 15 |
| 2018 November | 33 | 4 | 37 |
| 2018 October | 229 | 13 | 242 |
| 2018 September | 80 | 5 | 85 |
| 2018 August | 27 | 5 | 32 |
| 2018 July | 19 | 2 | 21 |
| 2018 June | 33 | 4 | 37 |
| 2018 May | 45 | 10 | 55 |
| 2018 April | 55 | 2 | 57 |
| 2018 March | 78 | 7 | 85 |
| 2018 February | 126 | 5 | 131 |
| 2018 January | 42 | 6 | 48 |
| 2017 December | 113 | 2 | 115 |
| 2017 November | 23 | 11 | 34 |
| 2017 October | 34 | 17 | 51 |
| 2017 September | 7 | 8 | 15 |
| 2017 August | 1 | 7 | 8 |
| 2017 July | 0 | 7 | 7 |
| 2017 June | 0 | 13 | 13 |
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