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Valeria Vega López, Norma Ramos-Ibáñez, L. Joana Cázares Lara, R. Joab Medina Gómez, Diana Pérez-Salgado" "autores" => array:6 [ 0 => array:4 [ "nombre" => "Luis" "apellidos" => "Ortiz-Hernández" "email" => array:1 [ 0 => "lortiz@correo.xoc.uam.mx" ] "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] 1 => array:2 [ "nombre" => "A. Valeria" "apellidos" => "Vega López" ] 2 => array:2 [ "nombre" => "Norma" "apellidos" => "Ramos-Ibáñez" ] 3 => array:2 [ "nombre" => "L. Joana" "apellidos" => "Cázares Lara" ] 4 => array:2 [ "nombre" => "R. Joab" "apellidos" => "Medina Gómez" ] 5 => array:2 [ "nombre" => "Diana" "apellidos" => "Pérez-Salgado" ] ] "afiliaciones" => array:1 [ 0 => array:2 [ "entidad" => "Universidad Autónoma Metropolitana (UAM), Departamento de Salud, Mexico City, Mexico" "identificador" => "aff0005" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "pt" => array:1 [ "titulo" => "Equações com base na antropometria para prever a gordura corporal medida por absorciometria em crianças em idade escolar e adolescentes" ] ] "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" => 2539 "Ancho" => 3005 "Tamanyo" => 465962 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Bland–Altman graphs for the difference in %BF measured by DXA and estimated %BF by new prediction equations based on anthropometry in the validation sample of Mexican children and adolescents. %BF by DXA, percentage of body fat estimated by dual-energy X-ray absorptiometry.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Overweight and obesity are important public health problems because of their magnitude and impact on health. In 2012, prevalence of overweight and obesity in Mexican schoolchildren 5–11 years old was 34.4% (19.8% and 14.6%, respectively) and, in adolescents 12–19 years old, it was 34.9%.<a class="elsevierStyleCrossRef" href="#bib0155"><span class="elsevierStyleSup">1</span></a> In schoolchildren, this value was slightly higher (34.8%) in 2006, whereas in adolescents, it was lower (33.2%).</p><p id="par0010" class="elsevierStylePara elsevierViewall">Children with obesity tend to become adults with obesity, which increases their risk for the development of chronic diseases.<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">2</span></a> Obesity represents an economic problem because the treatment of its co-morbidities carries high costs.<a class="elsevierStyleCrossRef" href="#bib0165"><span class="elsevierStyleSup">3</span></a> Hence, it is necessary that obesity is accurately diagnosed.</p><p id="par0015" class="elsevierStylePara elsevierViewall">Different methods for assessing body fat include hydrodensitometry, dual energy X-ray absorptiometry (DXA), and deuterium dilution. These measures are used mainly in research settings because the required equipment is costly and must be operated by specialized technicians. For these reasons, these methods are unsuitable for population studies, clinical practice, and screening activities. On the contrary, anthropometric measurements – although indirect indicators of adiposity – are economical, non-intrusive, and highly reproducible.<a class="elsevierStyleCrossRef" href="#bib0170"><span class="elsevierStyleSup">4</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">Various equations based on anthropometry have been used to estimate body fat in children, and these methods have been developed in Euro- and Afro-descendent subjects. Slaughter equations<a class="elsevierStyleCrossRef" href="#bib0175"><span class="elsevierStyleSup">5</span></a> are the most frequently used in the evaluation of body composition in children and adolescents.<a class="elsevierStyleCrossRefs" href="#bib0180"><span class="elsevierStyleSup">6–9</span></a> These equations were developed in 310 Afro-American and Euro-American people from 8 to 29 years of age.<a class="elsevierStyleCrossRef" href="#bib0175"><span class="elsevierStyleSup">5</span></a> However, these equations tend to overestimate body fat.<a class="elsevierStyleCrossRefs" href="#bib0190"><span class="elsevierStyleSup">8,9</span></a> In recent years, Dezenberg equations have been used,<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">7</span></a> which were developed in a sample of 202 Afro- and Euro-American children aged 4–10 years of age. In Latino children from the USA, these equations inaccurately estimate body fat.<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">10</span></a> These results show that equations developed in an ethnic group can be used in other populations, but the obtained estimation could be inaccurate. In the case of the Latino population, it has been recognized that the present-day Mexican population is an admixture among Amerindian, European, and African ancestries.<a class="elsevierStyleCrossRef" href="#bib0205"><span class="elsevierStyleSup">11</span></a></p><p id="par0025" class="elsevierStylePara elsevierViewall">Few studies in Latin America have explored the validity of prediction equations to estimate body fat in children using anthropometric measurements.<a class="elsevierStyleCrossRefs" href="#bib0210"><span class="elsevierStyleSup">12,13</span></a> It is possible that equations developed in populations of European or African ancestry could not be applied to the Latin American population due to ethnic differences in amount and distribution of body fat. For example, in comparison with European- or African-descended children, those with Latino ancestry have higher waist circumference.<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">14</span></a> In addition, pediatric Latin American populations have a high weight in relation to their height (an indirect indicator of adiposity), which is not always is due to excess body fat.<a class="elsevierStyleCrossRefs" href="#bib0225"><span class="elsevierStyleSup">15,16</span></a> Other reasons for high weight without excess adiposity could be that in comparison with the reference population, Latino populations have lower heights<a class="elsevierStyleCrossRefs" href="#bib0225"><span class="elsevierStyleSup">15,16</span></a> but higher values of muscle mass,<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">16</span></a> fat-free mass hydration,<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">17</span></a> trunk length,<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">15</span></a> body frame (<span class="elsevierStyleItalic">i.e.</span>, bone thickness),<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">15</span></a> and thorax circumference.<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">18</span></a> Therefore, the objectives of this study were (1) to evaluate the validity of previously published equations to estimate %BF in Latino children, and (2) to develop and validate new equations in Latino children to predict body fat using DXA as the gold standard.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Methods</span><p id="par0030" class="elsevierStylePara elsevierViewall">A cross-sectional study was carried out with a convenience sample of schoolchildren and adolescents aged 5–19 years from Mexico City. The participants were recruited from elementary (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>7), junior high (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>8), and high schools (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>4) in Mexico City and a community center in the State of Mexico. The research team presented the project to the principal of each school, and all students were invited to participate. Additionally, children of employees from the Metropolitan Autonomous University at Xochimilco (UAM-X) participated in the study. Children with a plaster cast or motor disabilities were excluded from the study. The study was approved by the Division of Biological and Health Sciences from UAM-X. The participants and their parents or guardians were informed about the research procedures, and the latter provided informed consent.</p><p id="par0035" class="elsevierStylePara elsevierViewall">Following the procedures used in other studies,<a class="elsevierStyleCrossRefs" href="#bib0185"><span class="elsevierStyleSup">7,10,19</span></a> the total sample (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>601) was randomly divided into two groups. Data from two-thirds of the participants were used to develop equations (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>398), and data from the remaining one-third of the children were used to validate new and previously published equations (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>203). The SPSS software package (IBM Corp. 2010. IBM SPSS Statistics for Windows, version 20.0. NY, USA) was used to generate these samples (option “Random sample of cases” in the command “Select cases”).</p><p id="par0040" class="elsevierStylePara elsevierViewall">Most anthropometric measurements were performed following the techniques described by Lohman et al.<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">20</span></a> Waist circumference was measured according to the technique described by Fernández et al.<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">14</span></a> Observers were standardized following the Habicht protocol.<a class="elsevierStyleCrossRef" href="#bib0255"><span class="elsevierStyleSup">21</span></a> Participants were measured with light clothes and without shoes. Stature was measured with a portable stadiometer, model 214 (SECA<span class="elsevierStyleSup">®</span>, SP, Brazil) and body weight with a digital scale, model 813 (SECA<span class="elsevierStyleSup">®</span>, SP, Brazil). Waist and arm circumferences were obtained with a metallic tape (Lufkin<span class="elsevierStyleSup">®</span>, MD, USA). Skinfolds (triceps, bicipital, subscapular, suprailiac, and calf) were measured with a compass (Harpenden<span class="elsevierStyleSup">®</span>, Mediflex Produtos Cirúrgicos, NY, USA). Each skinfold was measured three times, and the average value was analyzed. Bitrochanteric breadth and sitting stature were measured with an anthropometer (Harpenden<span class="elsevierStyleSup">®</span>, Mediflex Produtos Cirúrgicos, NY, USA). Elbow breadth was measured with an anthropometer (Futrex<span class="elsevierStyleSup">®</span>, MD, USA).</p><p id="par0045" class="elsevierStylePara elsevierViewall">Body mass index (BMI: body weight/height<span class="elsevierStyleSup">2</span>) was calculated as a <span class="elsevierStyleItalic">Z</span>-score for age and sex using the World Health Organization reference.<a class="elsevierStyleCrossRef" href="#bib0260"><span class="elsevierStyleSup">22</span></a> Maturity was estimated using the equations of Mirwald et al.<a class="elsevierStyleCrossRef" href="#bib0265"><span class="elsevierStyleSup">23</span></a></p><p id="par0050" class="elsevierStylePara elsevierViewall">The percentage of body fat (%BF) was evaluated with DXA using equipment Model Discovery Wi (Hologic<span class="elsevierStyleSup">®</span>, MA, USA) Calibration, scanning, and image analysis were completed following the manufacturer procedures and those described by the International Society for Clinical Densitometry (ISCD).<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">24</span></a> The images were analyzed using the whole body option for Hispanic populations, model APEX version 3.3.0.1 (Hologic<span class="elsevierStyleSup">®</span>, MA, USA). The coefficients of variation for the technician were 1.27% for total body fat (TBF) in kilograms, 0.66% for lean body mass, and 1.04% for %TBF, which are acceptable according to the ISCD.<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">24</span></a></p><p id="par0055" class="elsevierStylePara elsevierViewall">The distribution of anthropometric variables was assessed using the Kolmogorov–Smirnov test (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>). When the variable had a biased distribution, it was transformed using the base-10 logarithm to achieve a closer symmetric distribution. Linear regression models were estimated using DXA derived %BF as a dependent variable and anthropometric measurement as independent variables. Separate models were estimated for each sex. The equations were developed using the following two procedures:<ul class="elsevierStyleList" id="lis0005"><li class="elsevierStyleListItem" id="lsti0005"><span class="elsevierStyleLabel">(a)</span><p id="par0060" class="elsevierStylePara elsevierViewall">Different combinations of independent variables were manually tested. First, the capacity of each anthropometric variable to estimate %BF was evaluated (Supplementary Table S1). In addition, scatter plots were graphed to verify the linear relationship among the variables. A curvilinear relationship of %BF with age was evident in boys; meanwhile, among girls, this relationship was linear. For this reason, in models for boys, the quadratic term of age was incorporated. Because age and maturity are related, separate models with each variable were estimated, and no differences were observed. For simplicity, only models with age were reported. The coefficient of determination (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span>) and standard error (SE) were used as criteria to identify the variables that better predicted %BF. A variable was considered an adequate predictor when the <span class="elsevierStyleItalic">p</span>-value was <0.050.</p></li><li class="elsevierStyleListItem" id="lsti0010"><span class="elsevierStyleLabel">(b)</span><p id="par0065" class="elsevierStylePara elsevierViewall">The automatic backward and forward procedures of the linear regression command of SPSS software were used (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>). In the backward option, all variables were introduced in the models, and then those that had a low partial correlation with the dependent variable were excluded (elimination criteria: <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>0.100). In the forward option, the variables were introduced one-by-one according to greater correlation with the dependent variable. These variables were introduced and kept if they significantly predicted the dependent variable (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.050).</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia></li></ul></p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0070" class="elsevierStylePara elsevierViewall">The assessment of the validity of the previously published equations was carried out using age-matched subjects from the population that was used to develop them (<span class="elsevierStyleItalic">e.g.</span>, for the Slaughter equations,<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">25</span></a> participants data from 8 to 18 years old were used and for the Deurenberg equations<a class="elsevierStyleCrossRef" href="#bib0280"><span class="elsevierStyleSup">26</span></a> the range was 7–19 years). The validity of Stevens equations for girls could not be assessed because there was no data for children of menarche age. In these regression models, the dependent variable was DXA derived %BF, and the independent variable was %BF obtained by equations previously developed and those developed in this study (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>). One criterion for validity was whether there was a significant difference between the intercept and the origin (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>0.050) because, if there is difference, the equations would systematically over- or under-estimate %BF. Finally, the Bland Altman plots were graphed (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a> and Supplementary Fig. S1) to verify whether bias existed in the estimations according to adiposity levels. Differences between the measured and estimated %BF were plotted against the average of measured and estimated %BF. Only equations whose intercept was not different from the origin were plotted. The statistical analyses were performed using SPSS software (IBM Corp. 2010. IBM SPSS Statistics for Windows, version 20.0. NY, USA)</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0075" class="elsevierStylePara elsevierViewall">Statistical power analysis for different scenarios was completed using the G*Power software.<a class="elsevierStyleCrossRef" href="#bib0285"><span class="elsevierStyleSup">27</span></a> For the development of equations (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>) given a significance level (<span class="elsevierStyleItalic">α</span>) of 0.050, a sample size of 207, an effect of 85.8% (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span>), and seven predictors (scenario for the girls’ equation), the statistical power was 1.00. The same result was obtained with the scenario for the three equations for boys. For the validation analysis (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>), the power obtained under the different scenarios with respect to the sample size (<span class="elsevierStyleItalic">n</span> from 29 to 93), the effect (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span> from 51.0 to 91.6%) and the number of predictors (1–7) was always satisfactory (<span class="elsevierStyleItalic">i.e.</span>, ≥0.80).</p></span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Results</span><p id="par0080" class="elsevierStylePara elsevierViewall">A descriptive analysis of the anthropometric variables in the development and validation samples is shown in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>. The mean age of the development sample was 11.88 years, which is higher than that of the validation sample (11.32 years, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.019). In both samples, half of the participants were girls (development sample: 52%, validation sample: 50.7%). Although most participants were pre-pubescent, the proportion was higher in the validation sample than in the development sample (58.6% <span class="elsevierStyleItalic">vs.</span> 47.7%, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.050).</p><p id="par0085" class="elsevierStylePara elsevierViewall">For each sex group, different anthropometric characteristics were related to %BF (Supplementary Table S1). In boys, the variables that better predicted %BF were age, stature, BMI, circumferences of arm and waist, bitrochanteric and elbow breadth, sitting stature, weight, sitting stature index, and five skinfolds. Among girls, the best predictors were age, stature, weight, sitting stature, sitting stature index, BMI, circumference of arm and waist, five skinfolds, and bitrochanteric and elbow breadth.</p><p id="par0090" class="elsevierStylePara elsevierViewall">Using automated procedures, the two models satisfactorily predicted %BF in boys (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>). With the backward option, the following variables were included in the model (called Equation (1)): stature, BMI, arm and waist circumferences, body weight, and triceps, subscapular, suprailiac, and calf skinfolds (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>93%, SE<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>2.5%). With the forward option, the model (called Equation (2)) included the following variables: stature, arm and waist circumferences, and triceps, subscapular, and suprailiac skinfolds (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>92%, SE<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>2.5%). In boys, manual selection produced a model (Equation (3)) that included age, stature, waist circumference, and triceps, subscapular, and suprailiac skinfolds (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>92%, SE<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>2.0%). In girls, both of the automated procedures produced the same solution (called Equation (1)) with the following variables: sitting stature, BMI, waist circumference, triceps, elbow breadth, and subscapular and calf skinfolds (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>85%, SE<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>2.5%). Among girls, the manual selection model did not adequately predict %BF (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>80.0%).</p><p id="par0095" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a> shows the different estimations of %BF obtained by equations in the validation sample. In all of the age groups, the newly developed equations in Mexican schoolchildren and adolescents had high coefficients of determination (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>85% in boys and ≥78% in girls) and the lowest SE (≤3.05% in boys and ≤3.52% in girls); in addition, their intercepts did not differ from the origin (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>0.050). Although with the Dezenberg equations the intercept did not differ from the origin (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>0.050), their predictive capacity (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>77.7 in boys and <79.8 in girls) was lower than that of the equations developed here (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>88 and 82%, respectively). The Stevens equations in boys explained a significant proportion of variance (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>85%), but the intercept differed from the origin. In both sexes, the Slaughter equations overestimated %BF (positive intercept, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.050). The Deurenberg equations underestimated %BF in boys (negative intercept, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.050) and overestimated in girls. The Huang equations overestimated %BF in both sexes.</p><p id="par0100" class="elsevierStylePara elsevierViewall">The Bland–Altman plots (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>A, B and D) revealed that developed equations through automatic procedures produce biased estimations of %BF. These equations overestimated values in children with low adiposity, while in those with high adiposity, values were underestimated. The equation developed by manual selection in boys yielded estimations without systematic bias (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>C).</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Discussion</span><p id="par0105" class="elsevierStylePara elsevierViewall">The main aim of this study was to develop equations based on anthropometric measurements to predict %BF for Mexican schoolchildren and adolescents. The four developed equations require measures related to adiposity, linear growth, and body frame. For boys, three equations explained a high proportion of the %BF variance (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>92%). Although the equation for girls explained a high proportion of variance (85%), this was lower than that for boys. Another aim of the study was to analyze the validity of previously developed equations. With the exception of Dezenberg's equations, none of previously published equations were valid in the sample of Mexican schoolchildren and adolescents.</p><p id="par0110" class="elsevierStylePara elsevierViewall">In its original population,<a class="elsevierStyleCrossRef" href="#bib0175"><span class="elsevierStyleSup">5</span></a> the Slaughter equations had acceptable predictive capacity (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span> from 75% to 78% in the total sample). However, in the Mexican schoolchildren and adolescents, these equations overestimated the %BF. The same trend was observed Indian children,<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">9</span></a> Chinese children with obesity,<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">8</span></a> and British children.<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">6</span></a> The Deurenberg equations<a class="elsevierStyleCrossRef" href="#bib0280"><span class="elsevierStyleSup">26</span></a> were developed in 379 Dutch children and adolescents from 7 to 20 years of age and had low to moderate predictive capacity (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>41% to 69% in the total sample). In the Mexican pediatric population, these equations underestimated %BF in boys and overestimated it in girls. However, the opposite effect occurred in British children.<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">6</span></a> Physical differences of Mexican children and adolescents in comparison with those who participated in the Slaughter<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">25</span></a> and Deurenberg<a class="elsevierStyleCrossRef" href="#bib0280"><span class="elsevierStyleSup">26</span></a> studies could explain the results found in the present study. Participants in the Slaughter<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">25</span></a> and Deurenberg<a class="elsevierStyleCrossRef" href="#bib0280"><span class="elsevierStyleSup">26</span></a> samples were taller (155.2<span class="elsevierStyleHsp" style=""></span>cm and 164.3<span class="elsevierStyleHsp" style=""></span>cm <span class="elsevierStyleItalic">vs.</span> 144.2<span class="elsevierStyleHsp" style=""></span>cm, respectively) and heavier (47.4<span class="elsevierStyleHsp" style=""></span>kg and 53.9<span class="elsevierStyleHsp" style=""></span>kg <span class="elsevierStyleItalic">vs.</span> 42<span class="elsevierStyleHsp" style=""></span>kg, respectively) than children in the Mexican sample but had lower %BF (16.7% and 15.1% <span class="elsevierStyleItalic">vs.</span> 25.8%, respectively).</p><p id="par0115" class="elsevierStylePara elsevierViewall">In Mexican schoolchildren and adolescents, the estimations obtained with the Dezenberg equations did not tend to systematically over- or underestimate %BF (<span class="elsevierStyleItalic">i.e</span>., the intercept did not differ from the origin). However, the predictive capacity of the Dezenberg equations (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>68.1% to 77.4% in boys and 62.9% to 79.8% in girls) was lower than those of the equations developed in this study (88.5%–90.2% and 82.1%, respectively). Similar findings were obtained in Cuban schoolchildren.<a class="elsevierStyleCrossRef" href="#bib0290"><span class="elsevierStyleSup">28</span></a> Nevertheless, in Latino<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">10</span></a> and Indian schoolchildren,<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">9</span></a> the Dezenberg equations underestimated %BF; whereas in British schoolchildren theses equations had a bias of 13% in the estimation of %BF measured by deuterium dilution.<a class="elsevierStyleCrossRef" href="#bib0295"><span class="elsevierStyleSup">29</span></a></p><p id="par0120" class="elsevierStylePara elsevierViewall">The Huang equations<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">10</span></a> were developed in 96 Latino schoolchildren from 7 to 13 years of age from the USA and had an acceptable predictive capacity (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>86%–97% in the total sample). In the Mexican sample these equations overestimated %BF. Although participants of the Huang study were Latino, they were heavier than the Mexican schoolchildren in the current sample. These differences could reflect the different environments where children from the USA and Mexico live.</p><p id="par0125" class="elsevierStylePara elsevierViewall">The Stevens equations<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">19</span></a> were developed with a multi-ethnic sample of 5374 subjects 8–17 years of age and had a predictive capacity up to 85% in boys using DXA as the gold standard. This equation tended to underestimate the %BF in Mexican schoolchildren and adolescents.</p><p id="par0130" class="elsevierStylePara elsevierViewall">The Latin American population has certain physical characteristics such as lower height, short lower extremities, higher levels of body fat in the trunk and abdominal regions, and larger body frame.<a class="elsevierStyleCrossRefs" href="#bib0220"><span class="elsevierStyleSup">14–16</span></a> For this reason, in the present study, body characteristics related to linear growth (<span class="elsevierStyleItalic">i.e.</span>, stature or sitting stature) and body frame (<span class="elsevierStyleItalic">i.e</span>., elbow or bitrochanteric breadth) were measured in addition to those related to adiposity (<span class="elsevierStyleItalic">i.e.</span>, skinfolds and waist circumference). In the equations developed for boys, stature had a negative regression coefficient; whereas in girls, the coefficients for elbow breadth and sitting stature index were also negative. This shows that children or adolescents with higher stature or larger body frames tend to have less adiposity. In addition, in the new equation measurements of abdominal and trunk fat were predictors of %BF, including waist circumference and subscapular and suprailiac skinfolds.</p><p id="par0135" class="elsevierStylePara elsevierViewall">One limitation of the study is that a convenient sample was used. Therefore, generalization of these findings should be done with caution. Another limitation is that although DXA is considered an adequate method to measure adiposity,<a class="elsevierStyleCrossRef" href="#bib0300"><span class="elsevierStyleSup">30</span></a> its validity in a Mexican population has not been established. In the development of the equations for Mexican children and adolescents, less predictive capacity was observed in girls than boys. This difference by sex has been observed in other samples.<a class="elsevierStyleCrossRefs" href="#bib0245"><span class="elsevierStyleSup">19,26</span></a> In the future, measurements should be identified that increase the predictive capacity of equations in girls. A main limitation of this research is that a convenience sample of children and adolescents from Mexico City was used, and, therefore, the sample had a specific ethnic composition. In this way, although the developed equations provide an improved estimation of %BF in the sample under study, their use in other populations should be extended with caution. In other words, the validity of these equations should be evaluated in other samples of children from other regions of Mexico and other Latin American countries. This is necessary because the Latin American population is diverse in terms of ethnic ancestry. For example, in the southeast region of Mexico, there is a predominance of Amerindian ancestry over European, whereas in the Northern region the opposite trend is observed.<a class="elsevierStyleCrossRef" href="#bib0205"><span class="elsevierStyleSup">11</span></a> Finally, the predictive capacity of the estimated %BF (with the equations published here) to identify clinically relevant outcomes (<span class="elsevierStyleItalic">i.e.</span>, cardiovascular risk) should be determined.</p><p id="par0140" class="elsevierStylePara elsevierViewall">In conclusion, the findings indicate that the equations developed based on anthropometric measurements appropriately predict %BF in a heterogeneous group of Mexican schoolchildren and adolescents. In contrast, equations developed in other populations (even with similar ethnic characteristics) have reduced predictive capacity to estimate %BF. Therefore, the equations developed in this study can be used to assess the %BF in Mexican schoolchildren and adolescents, as they demonstrate greater validity and lower error compared with the previously published equations.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Conflicts of interest</span><p id="par0145" class="elsevierStylePara elsevierViewall">The authors declare no conflicts of interest.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:10 [ 0 => array:3 [ "identificador" => "xres872801" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec861530" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres872802" "titulo" => "Resumo" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusões" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec861531" "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" => "Conflicts of interest" ] 9 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2016-04-17" "fechaAceptado" => "2016-08-24" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec861530" "palabras" => array:6 [ 0 => "Body fat" 1 => "Children" 2 => "Adolescents" 3 => "Mexico" 4 => "Dual X-ray absorptiometry" 5 => "Anthropometry" ] ] ] "pt" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palavras-chave" "identificador" => "xpalclavsec861531" "palabras" => array:6 [ 0 => "Gordura corporal" 1 => "Crianças" 2 => "Adolescentes" 3 => "México" 4 => "Absorciometria de dupla energia de raios-X" 5 => "Antropometria" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Objective</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">To develop and validate equations to estimate the percentage of body fat of children and adolescents from Mexico using anthropometric measurements.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">A cross-sectional study was carried out with 601 children and adolescents from Mexico aged 5–19 years. The participants were randomly divided into the following two groups: the development sample (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>398) and the validation sample (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>203). The validity of previously published equations (<span class="elsevierStyleItalic">e.g</span>., Slaughter) was also assessed. The percentage of body fat was estimated by dual-energy X-ray absorptiometry. The anthropometric measurements included height, sitting height, weight, waist and arm circumferences, skinfolds (triceps, biceps, subscapular, supra-iliac, and calf), and elbow and bitrochanteric breadth. Linear regression models were estimated with the percentage of body fat as the dependent variable and the anthropometric measurements as the independent variables.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Equations were created based on combinations of six to nine anthropometric variables and had coefficients of determination (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span>) equal to or higher than 92.4% for boys and 85.8% for girls. In the validation sample, the developed equations had high <span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span> values (≥85.6% in boys and ≥78.1% in girls) in all age groups, low standard errors (SE<span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>3.05% in boys and ≤3.52% in girls), and the intercepts were not different from the origin (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>0.050). Using the previously published equations, the coefficients of determination were lower, and/or the intercepts were different from the origin.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">The equations developed in this study can be used to assess the percentage of body fat of Mexican schoolchildren and adolescents, as they demonstrate greater validity and lower error compared with previously published equations.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] "pt" => array:3 [ "titulo" => "Resumo" "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Objetivo</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Desenvolver e validar equações para estimar o percentual de gordura corporal (%GC) de crianças e adolescentes do México utilizando medidas antropométricas.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Métodos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Foi realizado um estudo transversal com 601 crianças e adolescentes do México com idades entre 5 e 19 anos. Os participantes foram divididos aleatoriamente nos seguintes dois grupos: a amostra de desenvolvimento (n<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>398) e a amostra de validação (n<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>203). A validade das equações publicadas anteriormente (por exemplo, Slaughter) também foi avaliada. O %GC foi estimado por absorciometria de dupla energia de raios-X (raio-X de dupla energia (DXA)). As medidas antropométricas incluíram estatura, altura sentado, peso, circunferências da cintura e do braço, dobras cutâneas (tríceps, bíceps, subescapular, suprailíaca e panturrilha) e larguras do cotovelo e bitrocantérica. Os modelos de regressão linear foram estimados com o %GC sendo a variável dependente e as medidas antropométricas como as variáveis independentes.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">As equações foram criadas com base nas combinações de seus a nove variáveis antropométricas e apresentaram coeficientes de determinação (r<span class="elsevierStyleSup">2</span>) iguais ou superiores a 92,4% para meninos e 85,8% para meninas. Na amostra de validação, as equações desenvolvidas apresentaram altos valores de r<span class="elsevierStyleSup">2</span> (≥ 85,6% em meninos e<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>78,1% em meninas) em todos os grupos, baixo nível de erros padrão (EP<span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>3,05% em meninos e<span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>3,52% em meninas) e os interceptos não foram diferentes da origem (p<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>0,050). Utilizando as equações publicadas anteriormente, os coeficientes de determinação foram menores e/ou os interceptos foram diferentes da origem.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusões</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">As equações desenvolvidas neste estudo podem ser utilizadas para avaliar o %GC das crianças em idade escolar e adolescentes mexicanos, pois elas possuem uma maior validade e menor erro em comparação às equações publicadas anteriormente.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusões" ] ] ] ] "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0100">Please cite this article as: Ortiz-Hernández L, Vega López AV, Ramos-Ibáñez N, Cázares Lara LJ, Medina Gómez RJ, Pérez-Salgado D. Equations based on anthropometry to predict body fat measured by absorptiometry in schoolchildren and adolescents. J Pediatr (Rio J). 2017;93:365–73.</p>" ] ] "apendice" => array:1 [ 0 => array:1 [ "seccion" => array:1 [ 0 => array:4 [ "apendice" => "<p id="par0160" class="elsevierStylePara elsevierViewall">The following are the supplementary data to this article:<elsevierMultimedia ident="upi0005"></elsevierMultimedia></p>" "etiqueta" => "Appendix A" "titulo" => "Supplementary data" "identificador" => "sec0035" ] ] ] ] "multimedia" => array:5 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 2539 "Ancho" => 3005 "Tamanyo" => 465962 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Bland–Altman graphs for the difference in %BF measured by DXA and estimated %BF by new prediction equations based on anthropometry in the validation sample of Mexican children and adolescents. %BF by DXA, percentage of body fat estimated by dual-energy X-ray absorptiometry.</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:3 [ "leyenda" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Significance by the Kolmogorov–Smirnov test.</p>" "tablatextoimagen" => array:2 [ 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="" valign="top" scope="col"> \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">Development sample</th><th class="td" title="table-head " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Validation sample</th></tr><tr title="table-row"><th class="td" title="table-head " align="" valign="top" scope="col"> \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">Boys (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>191) \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">Girls (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>207) \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">Boys (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>100) \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">Girls (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>103) \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">% (<span class="elsevierStyleItalic">n</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">% (<span class="elsevierStyleItalic">n</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">% (<span class="elsevierStyleItalic">n</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">% (<span class="elsevierStyleItalic">n</span>) \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 " colspan="5" align="left" valign="top"><span class="elsevierStyleItalic">Sexual maturity</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Prepubescent \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">66.0 (126) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">30.9 (64) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">75.0 (75) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">42.7 (44) \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"><span class="elsevierStyleHsp" style=""></span>Pubescent \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">27.2 (52) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">38.6 (80) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">22.0 (22) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">34.0 (35) \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"><span class="elsevierStyleHsp" style=""></span>Post-pubescent \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">6.8 (13) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">30.4 (63) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.0 (3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">23.3 (24) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1472874.png" ] ] 1 => 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="" 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<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>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">Mean<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>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">Mean<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>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">Mean<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>SD \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"><span class="elsevierStyleItalic">Body fat (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">27.1<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>9.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">32.6<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.8<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>9.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">32.8<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7.4 \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"><span class="elsevierStyleItalic">Age (years)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.3<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>2.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.5<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>2.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.9<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>2.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.9<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>2.9 \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"><span class="elsevierStyleItalic">Age</span><span class="elsevierStyleSup"><span class="elsevierStyleItalic">2</span></span><span class="elsevierStyleItalic">(years</span><span class="elsevierStyleSup"><span class="elsevierStyleItalic">2</span></span><span class="elsevierStyleItalic">)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">136.0<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>59.2<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">141.1<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>67.5<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">133.3<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>56.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">127.9<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>62.6 \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"><span class="elsevierStyleItalic">Height (cm)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">149.2<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>16.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">146.2<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>13.1<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">144.2<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>15.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">145.2<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>13.7 \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"><span class="elsevierStyleItalic">Sitting height (cm)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">76.9<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">76.5<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7.2<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">74.3<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">75.5<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7.9 \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"><span class="elsevierStyleItalic">Sitting height ratio (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">51.7<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.8<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">52.3<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">51.6<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>2.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">52.0<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>2.7<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \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"><span class="elsevierStyleItalic">Weight (kg)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">47.4<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>15.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">45.0<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>14.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">42.0<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>14.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">43.7<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>14.0 \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"><span class="elsevierStyleItalic">Body mass index (kg/m</span><span class="elsevierStyleSup"><span class="elsevierStyleItalic">2</span></span><span class="elsevierStyleItalic">)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">20.7<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">20.5<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">19.7<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>3.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">20.3<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.3 \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"><span class="elsevierStyleItalic">Arm circumference (cm)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">24.2<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">23.9<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>3.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">23.2<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>3.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">23.9<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>3.7 \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"><span class="elsevierStyleItalic">Waist circumference (cm)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">73.8<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>12.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">72.0<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>11.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">70.1<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>11.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">72.5<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>10.8 \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"><span class="elsevierStyleItalic">Triceps skinfold (mm)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.9<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>6.6<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">16.7<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>5.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.2<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>6.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.2<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>5.8 \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"><span class="elsevierStyleItalic">Biceps skinfold (mm)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.3<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.5<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.0<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>3.9<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">7.7<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>3.8<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.8<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.8<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \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"><span class="elsevierStyleItalic">Subscapular skinfold (mm)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.2<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7.8<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">15.7<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.0<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7.6<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">16.0<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>9.2 \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"><span class="elsevierStyleItalic">Suprailiac skinfold (mm)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">18.9<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>12.7<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">22.0<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>12.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">16.0<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>11.3<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">21.9<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>11.9 \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"><span class="elsevierStyleItalic">Calf skinfold (mm)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.1<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>6.7<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">15.8<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>6.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.4<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>5.9<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">16.0<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>6.6 \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"><span class="elsevierStyleItalic">Bitrochanteric breadth (cm)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">29.7<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">29.5<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">27.9<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">29.3<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.5 \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"><span class="elsevierStyleItalic">Elbow breadth (cm)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.6<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.1<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.4<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.1<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.4 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1472876.png" ] ] ] "notaPie" => array:3 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="npar0005"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>0.050.</p>" ] 1 => array:3 [ "identificador" => "tblfn0010" "etiqueta" => "b" "nota" => "<p class="elsevierStyleNotepara" id="npar0010"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>0.010.</p>" ] 2 => array:3 [ "identificador" => "tblfn0015" "etiqueta" => "c" "nota" => "<p class="elsevierStyleNotepara" id="npar0015"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>0.001.</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Descriptive statistics of the anthropometric measures in the development and validation samples of Mexican children and adolescents.</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:3 [ "leyenda" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">%BF by DXA, percentage of body fat estimated by dual-energy X-ray absorptiometry; BMI, body mass index; SE, standard error.</p><p id="spar0070" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleItalic">p</span>-Values of regression coefficients were:</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">Equations \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">Multiple linear regression models \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">r</span><span class="elsevierStyleSup">2</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">SE (%) \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 " colspan="4" align="left" valign="top"><span class="elsevierStyleItalic">For boys</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−8.739<span class="elsevierStyleHsp" style=""></span>−<span class="elsevierStyleHsp" style=""></span>0.384<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">c</span></a> (height, cm)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>35.371<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">a</span></a> (log weight, kg)<span class="elsevierStyleHsp" style=""></span>−<span class="elsevierStyleHsp" style=""></span>0.892<a class="elsevierStyleCrossRef" href="#tblfn0025"><span class="elsevierStyleSup">b</span></a> (BMI, kg/m<span class="elsevierStyleSup">2</span>)<span class="elsevierStyleHsp" style=""></span>−<span class="elsevierStyleHsp" style=""></span>0.299<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">a</span></a> (arm circumference, cm)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>0.258<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">c</span></a> (waist circumference, cm)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>17.732<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">c</span></a> (log triceps skinfold)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>6.698<a class="elsevierStyleCrossRef" href="#tblfn0025"><span class="elsevierStyleSup">b</span></a> (log subscapular skinfold)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>3.545<a class="elsevierStyleCrossRef" href="#tblfn0035"><span class="elsevierStyleSup">d</span></a> (log suprailiac skinfold)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>4.019<a class="elsevierStyleCrossRef" href="#tblfn0035"><span class="elsevierStyleSup">d</span></a> (log calf skinfold) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">93.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.5 \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"><span class="elsevierStyleHsp" style=""></span>2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.511<span class="elsevierStyleHsp" style=""></span>−<span class="elsevierStyleHsp" style=""></span>0.152<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">c</span></a> (height, cm)<span class="elsevierStyleHsp" style=""></span>−<span class="elsevierStyleHsp" style=""></span>0.431<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">c</span></a> (arm circumference, cm)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>0.213<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">c</span></a> (waist circumference, cm)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>21.271<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">c</span></a> (log triceps skinfold)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>7.386<a class="elsevierStyleCrossRef" href="#tblfn0025"><span class="elsevierStyleSup">b</span></a> (log subscapular skinfold)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>4.981<a class="elsevierStyleCrossRef" href="#tblfn0025"><span class="elsevierStyleSup">b</span></a> (log suprailiac skinfold) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">92.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.56 \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"><span class="elsevierStyleHsp" style=""></span>3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−1.791<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>0.329 (age, years)<span class="elsevierStyleHsp" style=""></span>−<span class="elsevierStyleHsp" style=""></span>0.033<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">a</span></a> (age<span class="elsevierStyleSup">2</span>, years<span class="elsevierStyleSup">2</span>)<span class="elsevierStyleHsp" style=""></span>−<span class="elsevierStyleHsp" style=""></span>0.141<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">c</span></a> (height, cm)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>0.162<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">c</span></a> (waist circumference, cm)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>18.516<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">c</span></a> (log triceps skinfold)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>6.013<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">a</span></a> (log subscapular skinfold)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>5.633<a class="elsevierStyleCrossRef" href="#tblfn0025"><span class="elsevierStyleSup">b</span></a> (log suprailiac skinfold) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">92.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.61 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="4" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="4" align="left" valign="top"><span class="elsevierStyleItalic">For girls</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−7.299<span class="elsevierStyleHsp" style=""></span>−<span class="elsevierStyleHsp" style=""></span>21.436<a class="elsevierStyleCrossRef" href="#tblfn0025"><span class="elsevierStyleSup">b</span></a> (log sitting height)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>17.739<a class="elsevierStyleCrossRef" href="#tblfn0025"><span class="elsevierStyleSup">b</span></a> (log BMI)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>20.143<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">a</span></a> (log waist circumference)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>7.813<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">c</span></a> (log triceps skinfold)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>6.379<a class="elsevierStyleCrossRef" href="#tblfn0025"><span class="elsevierStyleSup">b</span></a> (log subscapular skinfold)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>6.051<a class="elsevierStyleCrossRef" href="#tblfn0025"><span class="elsevierStyleSup">b</span></a> (log calf skinfold)<span class="elsevierStyleHsp" style=""></span>−<span class="elsevierStyleHsp" style=""></span>16.364<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">a</span></a> (log elbow breadth) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">85.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.65 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1472877.png" ] ] ] "notaPie" => array:4 [ 0 => array:3 [ "identificador" => "tblfn0020" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="npar0020"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.050.</p>" ] 1 => array:3 [ "identificador" => "tblfn0025" "etiqueta" => "b" "nota" => "<p class="elsevierStyleNotepara" id="npar0025"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.010.</p>" ] 2 => array:3 [ "identificador" => "tblfn0030" "etiqueta" => "c" "nota" => "<p class="elsevierStyleNotepara" id="npar0030"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001.</p>" ] 3 => array:3 [ "identificador" => "tblfn0035" "etiqueta" => "d" "nota" => "<p class="elsevierStyleNotepara" id="npar0035"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>0.072.</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Multiple linear regression models having %BF by DXA as outcome and anthropometric characteristics as predictors in the development sample of Mexican children and adolescents.</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:3 [ "leyenda" => "<p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">%BF DXA, percentage of body fat estimated by dual-energy X-ray absorptiometry; Min, minimum; Max, maximum; SE, standard error; <span class="elsevierStyleItalic">r</span><span class="elsevierStyleSup">2</span>, coefficient of determination; <span class="elsevierStyleItalic">α</span>, intercept; T-SF, triceps skinfold; B-SF, biceps skinfold; SS-SF, subscapular skinfold; SI-SF, supra-iliac skinfold; C-SF, calf skinfold.</p><p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">The estimations were made based on:</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="" valign="top" scope="col"> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " colspan="7" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Boys</th><th class="td" title="table-head " colspan="7" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Girls</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">Min \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">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 \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">r</span><span class="elsevierStyleSup">2</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">SE (%) \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">α</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"><span class="elsevierStyleItalic">p</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">Min \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">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 \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">r</span><span class="elsevierStyleSup">2</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">SE (%) \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">α</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"><span class="elsevierStyleItalic">p</span> \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"><span class="elsevierStyleItalic">8–18 years</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " colspan="7" align="center" valign="top"><span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>85</td><td class="td" title="table-entry " colspan="7" align="center" valign="top"><span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>84</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>%BF DXA \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">47.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">52.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">32.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \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"><span class="elsevierStyleHsp" style=""></span>Equation 1 \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">44.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">91.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.59 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.64 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.478 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">45.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">33.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">78.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.52 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.39 \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></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Equation 2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">44.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">90.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.72 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.49 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.603 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \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"><span class="elsevierStyleHsp" style=""></span>Equation 3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">43.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.2 \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><td class="td" title="table-entry " align="char" valign="top">2.60 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.25 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.776 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \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"><span class="elsevierStyleHsp" style=""></span>Slaughter<a class="elsevierStyleCrossRef" href="#tblfn0040"><span class="elsevierStyleSup">a</span></a> \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">44.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">20.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">78.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.17 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">6.75 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">47.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">62.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.60 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.79 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.000 \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"><span class="elsevierStyleHsp" style=""></span>Slaughter<a class="elsevierStyleCrossRef" href="#tblfn0045"><span class="elsevierStyleSup">b</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">54.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">23.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.92 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">6.73 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">60.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">27.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">51.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.27 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.96 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.000 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="15" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">7–19 years</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " colspan="7" align="center" valign="top"><span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>93</td><td class="td" title="table-entry " colspan="7" align="center" valign="top"><span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>92</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>%BF DXA \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">47.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">52.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">33.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \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"><span class="elsevierStyleHsp" style=""></span>Equation 1 \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">44.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">26.0 \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><td class="td" title="table-entry " align="char" valign="top">2.66 \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">0.370 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">45.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">33.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">79.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.42 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.45 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.806 \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"><span class="elsevierStyleHsp" style=""></span>Equation 2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">44.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">26.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">90.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.78 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.75 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.423 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \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"><span class="elsevierStyleHsp" style=""></span>Equation 3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">43.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.6 \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><td class="td" title="table-entry " align="char" valign="top">2.65 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.03 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.972 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \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"><span class="elsevierStyleHsp" style=""></span>Deurenberg<a class="elsevierStyleCrossRef" href="#tblfn0050"><span class="elsevierStyleSup">c</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">31.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">19.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.05 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−6.85 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">35.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">23.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">67.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.25 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.70 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.097 \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"><span class="elsevierStyleHsp" style=""></span>Deurenberg<a class="elsevierStyleCrossRef" href="#tblfn0055"><span class="elsevierStyleSup">d</span></a> \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">34.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">20.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">84.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.55 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−6.54 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">40.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">26.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">67.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.29 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.97 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.023 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="15" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">4–10 years</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " colspan="7" align="center" valign="top"><span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>29</td><td class="td" title="table-entry " colspan="7" align="center" valign="top"><span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>33</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>%BF DXA \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">44.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">28.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">45.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">33.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \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"><span class="elsevierStyleHsp" style=""></span>Equation 1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">39.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">29.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">88.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.82 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−2.14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.335 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">44.9 \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">82.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.25 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.11 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.430 \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"><span class="elsevierStyleHsp" style=""></span>Equation 2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">40.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">29.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">88.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.86 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−3.65 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.128 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \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"><span class="elsevierStyleHsp" style=""></span>Equation 3 \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">40.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">29.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">90.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.64 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−2.59 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.219 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \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"><span class="elsevierStyleHsp" style=""></span>Dezenberg<a class="elsevierStyleCrossRef" href="#tblfn0060"><span class="elsevierStyleSup">e</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">36.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">68.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.77 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.57 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.888 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">36.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">62.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.65 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.48 \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></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Dezenberg<a class="elsevierStyleCrossRef" href="#tblfn0065"><span class="elsevierStyleSup">f</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">15.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">36.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">77.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.02 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.42 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.892 \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">38.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">26.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">79.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.43 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">7.67 \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></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Dezenberg<a class="elsevierStyleCrossRef" href="#tblfn0070"><span class="elsevierStyleSup">g</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">34.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">23.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">77.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.99 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.50 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.385 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">38.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">27.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">79.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.43 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.95 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.147 \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"><span class="elsevierStyleHsp" style=""></span>Dezenberg<a class="elsevierStyleCrossRef" href="#tblfn0075"><span class="elsevierStyleSup">h</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">33.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">23.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">77.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.32 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.237 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">37.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">26.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">79.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.43 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.28 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.046 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="15" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">7–13 years</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " colspan="7" align="center" valign="top"><span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>66</td><td class="td" title="table-entry " colspan="7" align="center" valign="top"><span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>53</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>%BF DXA \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">44.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">27.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">52.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">33.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \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"><span class="elsevierStyleHsp" style=""></span>Equation 1 \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">41.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">27.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">87.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.89 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.17 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.900 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">45.3 \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">83.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.36 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.48 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.822 \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"><span class="elsevierStyleHsp" style=""></span>Equation 2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">42.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">27.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">85.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.05 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.03 \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="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \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"><span class="elsevierStyleHsp" style=""></span>Equation 3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">43.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">27.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">87.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.81 \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">0.522 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \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"><span class="elsevierStyleHsp" style=""></span>Huang<a class="elsevierStyleCrossRef" href="#tblfn0080"><span class="elsevierStyleSup">i</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">42.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">24.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">61.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.97 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.51 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">46.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">28.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">63.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.96 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.25 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.000 \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"><span class="elsevierStyleHsp" style=""></span>Huang<a class="elsevierStyleCrossRef" href="#tblfn0085"><span class="elsevierStyleSup">j</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−1.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">40.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">21.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">64.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.81 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.85 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">47.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">31.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">63.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.96 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.000 \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"><span class="elsevierStyleHsp" style=""></span>Huang<a class="elsevierStyleCrossRef" href="#tblfn0090"><span class="elsevierStyleSup">k</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">40.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">23.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">58.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.98 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−6.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">44.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">22.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">67.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.70 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">19.47 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.000 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="15" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">8–17 years</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " colspan="7" align="center" valign="top"><span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>85</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \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"><span class="elsevierStyleHsp" style=""></span>%BF DXA \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">47.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \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"><span class="elsevierStyleHsp" style=""></span>Equation 1 \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">44.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">91.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.59 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.64 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.478 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \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"><span class="elsevierStyleHsp" style=""></span>Equation 2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">44.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">90.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.72 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.49 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.603 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \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"><span class="elsevierStyleHsp" style=""></span>Equation 3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">43.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.2 \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><td class="td" title="table-entry " align="char" valign="top">2.59 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.25 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.776 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \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"><span class="elsevierStyleHsp" style=""></span>Stevens<a class="elsevierStyleCrossRef" href="#tblfn0095"><span class="elsevierStyleSup">l</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">20.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">49.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">31.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">83.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.63 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−10.89 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1472875.png" ] ] ] "notaPie" => array:12 [ 0 => array:3 [ "identificador" => "tblfn0040" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="npar0040">T-SF and C-SF.</p>" ] 1 => array:3 [ "identificador" => "tblfn0045" "etiqueta" => "b" "nota" => "<p class="elsevierStyleNotepara" id="npar0045">T-SF and SS-SF.</p>" ] 2 => array:3 [ "identificador" => "tblfn0050" "etiqueta" => "c" "nota" => "<p class="elsevierStyleNotepara" id="npar0050">T-SF and B-SF.</p>" ] 3 => array:3 [ "identificador" => "tblfn0055" "etiqueta" => "d" "nota" => "<p class="elsevierStyleNotepara" id="npar0055">T-SF, B-SF SI-SF, and SS-SF.</p>" ] 4 => array:3 [ "identificador" => "tblfn0060" "etiqueta" => "e" "nota" => "<p class="elsevierStyleNotepara" id="npar0060">Weight.</p>" ] 5 => array:3 [ "identificador" => "tblfn0065" "etiqueta" => "f" "nota" => "<p class="elsevierStyleNotepara" id="npar0065">Weight and T-SF.</p>" ] 6 => array:3 [ "identificador" => "tblfn0070" "etiqueta" => "g" "nota" => "<p class="elsevierStyleNotepara" id="npar0070">Weight, T-SF, and gender.</p>" ] 7 => array:3 [ "identificador" => "tblfn0075" "etiqueta" => "h" "nota" => "<p class="elsevierStyleNotepara" id="npar0075">Weight, T-SF, gender, and ethnicity.</p>" ] 8 => array:3 [ "identificador" => "tblfn0080" "etiqueta" => "i" "nota" => "<p class="elsevierStyleNotepara" id="npar0080">Age.</p>" ] 9 => array:3 [ "identificador" => "tblfn0085" "etiqueta" => "j" "nota" => "<p class="elsevierStyleNotepara" id="npar0085">Age and gender.</p>" ] 10 => array:3 [ "identificador" => "tblfn0090" "etiqueta" => "k" "nota" => "<p class="elsevierStyleNotepara" id="npar0090">Age, gender, and height.</p>" ] 11 => array:3 [ "identificador" => "tblfn0095" "etiqueta" => "l" "nota" => "<p class="elsevierStyleNotepara" id="npar0095">Age, race, weight, height, waist, and T-SF.</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Cross-validation of new and previously published prediction equations in validation sample of Mexican children and adolescents.</p>" ] ] 4 => array:5 [ "identificador" => "upi0005" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => false "mostrarDisplay" => true "Ecomponente" => array:2 [ "fichero" => "mmc1.docx" "ficheroTamanyo" => 537305 ] ] ] "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" => "Encuesta nacional de salud y nutrición 2012, Resultados nacionales. 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2024 July | 36 | 381 | 417 |
2024 June | 21 | 14 | 35 |
2024 May | 17 | 14 | 31 |
2024 April | 24 | 26 | 50 |
2024 March | 30 | 15 | 45 |
2024 February | 32 | 23 | 55 |
2024 January | 17 | 22 | 39 |
2023 December | 11 | 21 | 32 |
2023 November | 22 | 35 | 57 |
2023 October | 27 | 32 | 59 |
2023 September | 27 | 34 | 61 |
2023 August | 20 | 14 | 34 |
2023 July | 15 | 11 | 26 |
2023 June | 13 | 9 | 22 |
2023 May | 20 | 17 | 37 |
2023 April | 16 | 7 | 23 |
2023 March | 40 | 19 | 59 |
2023 February | 27 | 13 | 40 |
2023 January | 16 | 22 | 38 |
2022 December | 49 | 29 | 78 |
2022 November | 18 | 25 | 43 |
2022 October | 35 | 29 | 64 |
2022 September | 20 | 30 | 50 |
2022 August | 23 | 25 | 48 |
2022 July | 25 | 29 | 54 |
2022 June | 33 | 29 | 62 |
2022 May | 34 | 32 | 66 |
2022 April | 44 | 28 | 72 |
2022 March | 37 | 38 | 75 |
2022 February | 20 | 24 | 44 |
2022 January | 15 | 19 | 34 |
2021 December | 13 | 13 | 26 |
2021 November | 11 | 18 | 29 |
2021 October | 16 | 19 | 35 |
2021 September | 11 | 8 | 19 |
2021 August | 6 | 8 | 14 |
2021 July | 6 | 10 | 16 |
2021 June | 16 | 41 | 57 |
2021 May | 17 | 15 | 32 |
2021 April | 18 | 21 | 39 |
2021 March | 14 | 12 | 26 |
2021 February | 12 | 10 | 22 |
2021 January | 14 | 8 | 22 |
2020 December | 14 | 8 | 22 |
2020 November | 8 | 8 | 16 |
2020 October | 10 | 7 | 17 |
2020 September | 17 | 13 | 30 |
2020 August | 6 | 5 | 11 |
2020 July | 8 | 6 | 14 |
2020 June | 8 | 6 | 14 |
2020 May | 15 | 4 | 19 |
2020 April | 14 | 10 | 24 |
2020 March | 7 | 2 | 9 |
2020 February | 11 | 13 | 24 |
2020 January | 20 | 17 | 37 |
2019 December | 10 | 7 | 17 |
2019 November | 3 | 4 | 7 |
2019 October | 9 | 10 | 19 |
2019 September | 21 | 10 | 31 |
2019 August | 6 | 8 | 14 |
2019 July | 10 | 8 | 18 |
2019 June | 10 | 4 | 14 |
2019 May | 14 | 5 | 19 |
2019 April | 14 | 13 | 27 |
2019 March | 11 | 6 | 17 |
2019 February | 8 | 5 | 13 |
2019 January | 10 | 6 | 16 |
2018 December | 13 | 7 | 20 |
2018 November | 53 | 1 | 54 |
2018 October | 338 | 11 | 349 |
2018 September | 153 | 6 | 159 |
2018 August | 51 | 5 | 56 |
2018 July | 38 | 4 | 42 |
2018 June | 63 | 5 | 68 |
2018 May | 166 | 6 | 172 |
2018 April | 54 | 2 | 56 |
2018 March | 22 | 3 | 25 |
2018 February | 15 | 3 | 18 |
2018 January | 16 | 2 | 18 |
2017 December | 10 | 3 | 13 |
2017 November | 22 | 6 | 28 |
2017 October | 33 | 10 | 43 |
2017 September | 18 | 12 | 30 |
2017 August | 24 | 13 | 37 |
2017 July | 7 | 6 | 13 |
2017 June | 2 | 5 | 7 |
2017 May | 0 | 4 | 4 |
2017 April | 3 | 5 | 8 |
2017 March | 0 | 6 | 6 |
2017 February | 0 | 11 | 11 |