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"figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1009 "Ancho" => 1667 "Tamanyo" => 85775 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "alt0001" "detalle" => "Fig " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spara001" class="elsevierStyleSimplePara elsevierViewall">TSH measurements in newborns receiving prolonged parenteral nutrition during hospitalization.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Raquel Stocker Pérsico, Rita de Cassia dos Santos Silveira, Claudia Hallal Alves Gazal, Luciana Verçoza Viana" "autores" => array:4 [ 0 => array:2 [ "nombre" => "Raquel Stocker" "apellidos" => "Pérsico" ] 1 => array:2 [ "nombre" => "Rita de Cassia dos Santos" "apellidos" => "Silveira" ] 2 => array:2 [ "nombre" => "Claudia Hallal Alves" "apellidos" => "Gazal" ] 3 => array:2 [ "nombre" => "Luciana Verçoza" "apellidos" => "Viana" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0021755722000924?idApp=UINPBA000049" "url" => "/00217557/0000009900000001/v2_202302081321/S0021755722000924/v2_202302081321/en/main.assets" ] "en" => array:20 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original article</span>" "titulo" => "Growth phenotypes of very low birth weight infants for prediction of neonatal outcomes from a Brazilian cohort: comparison with INTERGROWTH" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "86" "paginaFinal" => "93" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "Viviane Cunha Cardoso, Carlos Grandi, Rita C. 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"identificador" => "aff0001" ] ] ] 21 => array:3 [ "nombre" => "Davi Casale" "apellidos" => "Aragon" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0001" ] ] ] 22 => array:3 [ "nombre" => "Fabio" "apellidos" => "Carmona" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0001" ] ] ] ] "afiliaciones" => array:21 [ 0 => array:3 [ "entidad" => "Universidade de São Paulo, Faculdade de Medicina de Ribeirão Preto, Departamento de Puericultura e Pediatria, São Paulo, SP, Brazil" "etiqueta" => "a" "identificador" => "aff0001" ] 1 => array:3 [ "entidad" => "Sociedad Argentina de Pediatria, Subcomissión de Investigación, Buenos Aires, Argentina" "etiqueta" => "b" "identificador" => "aff0002" ] 2 => array:3 [ "entidad" => "Universidade Federal do Rio Grande do Sul, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil" "etiqueta" => "c" "identificador" => "aff0003" ] 3 => array:3 [ "entidad" => "Universidade do Estado do Rio de Janeiro, Hospital Universitário Pedro Ernesto, Rio de Janeiro, RJ, Brazil" "etiqueta" => "d" "identificador" => "aff0004" ] 4 => array:3 [ "entidad" => "Universidade Federal de Minas Gerais, Hospital das Clínicas, Belo Horizonte, MG, Brazil" "etiqueta" => "e" "identificador" => "aff0005" ] 5 => array:3 [ "entidad" => "Universidade Federal de Uberlândia, Faculdade de Medicina, Departamento de Pediatria, Uberlândia, MG, Brazil" "etiqueta" => "f" "identificador" => "aff0006" ] 6 => array:3 [ "entidad" => "Faculdade de Ciências Médicas de Minas Gerais, Maternidade Escola Hilda Brandão, Belo Horizonte, MG, Brazil" "etiqueta" => "g" "identificador" => "aff0007" ] 7 => array:3 [ "entidad" => "Hospital Estadual Sumaré, Sumaré, SP, Brazil" "etiqueta" => "h" "identificador" => "aff0008" ] 8 => array:3 [ "entidad" => "Hospital Geral de Pirajussara, Taboão da Serra, SP, Brazil" "etiqueta" => "i" "identificador" => "aff0009" ] 9 => array:3 [ "entidad" => "Hospital Estadual de Diadema, Diadema, SP, Brazil" "etiqueta" => "j" "identificador" => "aff0010" ] 10 => array:3 [ "entidad" => "Universidade Estadual de Londrina, Londrina, PR, Brazil" "etiqueta" => "k" "identificador" => "aff0011" ] 11 => array:3 [ "entidad" => "Universidade Federal do Paraná, Departamento de Pediatria, Curitiba, PR, Brazil" "etiqueta" => "l" "identificador" => "aff0012" ] 12 => array:3 [ "entidad" => "Instituto de Medicina Integral Professor Fernando Figueira, Recife, PE, Brazil" "etiqueta" => "m" "identificador" => "aff0013" ] 13 => array:3 [ "entidad" => "Universidade Federal do Maranhão, Hospital Universitário, São Luís, MA, Brazil" "etiqueta" => "n" "identificador" => "aff0014" ] 14 => array:3 [ "entidad" => "Universidade Estadual Paulista, Faculdade de Medicina de Botucatu, Botucatu, SP, Brazil" "etiqueta" => "o" "identificador" => "aff0015" ] 15 => array:3 [ "entidad" => "Universidade Federal de São Paulo, Escola Paulista de Medicina, São Paulo, SP, Brazil" "etiqueta" => "p" "identificador" => "aff0016" ] 16 => array:3 [ "entidad" => "Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, São Paulo, SP, Brazil" "etiqueta" => "q" "identificador" => "aff0017" ] 17 => array:3 [ "entidad" => "Universidade de São Paulo, Hospital Universitário, São Paulo, SP, Brazil" "etiqueta" => "r" "identificador" => "aff0018" ] 18 => array:3 [ "entidad" => "Pontifícia Universidade Católica do Rio Grande do Sul, Hospital São Lucas, Porto Alegre, RS, Brazil" "etiqueta" => "s" "identificador" => "aff0019" ] 19 => array:3 [ "entidad" => "Universidade Estadual de Campinas, Faculdade de Ciências Médicas, Campinas, SP, Brazil" "etiqueta" => "t" "identificador" => "aff0020" ] 20 => array:3 [ "entidad" => "Fundação Oswaldo Cruz, Instituto Nacional de Saúde da Mulher da Criança e do Adolescente Fernandes Figueira, Rio de Janeiro, RJ, Brazil" "etiqueta" => "u" "identificador" => "aff0021" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0001" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0001" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0007">Introduction</span><p id="para0006" class="elsevierStylePara elsevierViewall">Preterm birth is the leading cause of perinatal mortality worldwide and is often a consequence of inadequate intrauterine conditions.<a class="elsevierStyleCrossRef" href="#bib0001"><span class="elsevierStyleSup">1</span></a> For decades, newborns have been categorized as small (SGA) or large (LGA) for gestational age (GA), stunted (short length for GA), or wasted (low weight for length or low body mass index [BMI] for GA).<a class="elsevierStyleCrossRef" href="#bib0002"><span class="elsevierStyleSup">2</span></a></p><p id="para0007" class="elsevierStylePara elsevierViewall">The INTERGROWTH-21st Newborn Size (IG21) standards for infants born at 33 weeks or less of GA were produced with only 408 neonates.<a class="elsevierStyleCrossRef" href="#bib0003"><span class="elsevierStyleSup">3</span></a> This fact limits the reliability and the usefulness of these standards for very low birth weight (VLBW, < 1500 g) preterm infants. In addition, local validation has been recommended by the authors of the IG21 standards and by others.<a class="elsevierStyleCrossRefs" href="#bib0004"><span class="elsevierStyleSup">4–8</span></a></p><p id="para0008" class="elsevierStylePara elsevierViewall">Interestingly, no association has yet been demonstrated between a low weight-to-length (W/L) ratio at birth and major neonatal outcomes. Measures of neonatal morbidity are therefore essential for promoting epidemiological and health service research in order to improve infant health and reduce disparities at birth.<a class="elsevierStyleCrossRef" href="#bib0009"><span class="elsevierStyleSup">9</span></a></p><p id="para0009" class="elsevierStylePara elsevierViewall">The objective of this study was to assess the predictive value of selected growth phenotypes for a composite neonatal morbidity and mortality (CNMM) indicator in preterm infants < 30 weeks and to compare them with IG21.</p></span><span id="sec0002" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0008">Material and methods</span><span id="sec0003" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0009">Study population</span><p id="para0010" class="elsevierStylePara elsevierViewall">This was a retrospective analysis of data collected prospectively as part of the Brazilian Neonatal Research Network (BNRN) database. The study was approved by a local institutional review board (IRB, CAAE #95153318.0.0000.5440, protocol #2.816.983/2018). Signed informed consent was waived because the database is anonymized.</p><p id="para0011" class="elsevierStylePara elsevierViewall">The BNRN includes 20 public tertiary-care university hospitals from three different Brazilian regions: Northeast, Southeast, and South. These hospitals have collected data on VLBW infants since 1999. In 2014, the database migrated to REDCap (Research Electronic Data Capture),<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">10</span></a> with a real-time data quality check, and was then reviewed by supervisors before annual locking. All data are collected prospectively by each center and included in the database. Patients are followed up to the first outcome (death, discharge, transfer, or first birthday).</p><p id="para0012" class="elsevierStylePara elsevierViewall">BNRN inborn or infants admitted to a BNRN center before 28 days of life with a BW of 401 to 1,499 g or GA between 22 weeks and 29 weeks plus 6 days were included in the database. All records from 2014 to 2019 were eligible; infants with GA < 22 or ≥ 30 weeks were not included in the analysis because, according to the original inclusion criteria, BW was truncated at 400 and 1500 g at those GAs, respectively. Outborns, twins, infants with congenital infection or malformations, chromosomal abnormality, delivery room death, and missing data were excluded.</p></span><span id="sec0004" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0010">Database</span><p id="para0013" class="elsevierStylePara elsevierViewall">The dataset contained selected maternal (demographic, clinical, gestational, and related to delivery) and newborn variables (weight and length at birth, GA, gender, Apgar scores, and main clinical outcomes). The duration of mechanical ventilation and neonatal intensive care unit (NICU) stay were adjusted for competing outcomes (death or transfer before extubation and/or discharge) by replacing the censored value with the largest value within each group plus one day.</p></span><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0011">Newborn anthropometric measures</span><p id="para0014" class="elsevierStylePara elsevierViewall">The following ratios were calculated for all infants at birth: W/L ratio (kg/m), BMI (kg/m<span class="elsevierStyleSup">2</span>), and PI (kg/m<span class="elsevierStyleSup">3</span>).</p><span id="sec0006" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0012"><span class="elsevierStyleItalic">Selected growth phenotypes</span> (according to IG21, for GA and sex)</span><p id="para0015" class="elsevierStylePara elsevierViewall">SGA was defined as being below the 3<span class="elsevierStyleSup">rd</span> (SGA3) or 10<span class="elsevierStyleSup">th</span> (SGA10) percentiles of BW, and LGA as being above the 97<span class="elsevierStyleSup">th</span> percentile of BW. Stunting was defined as being below the 3<span class="elsevierStyleSup">rd</span> percentile of the length and wasting as being below the 3<span class="elsevierStyleSup">rd</span> percentile of BMI.</p></span><span id="sec0007" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0013">Composite neonatal morbidity and mortality (CNMM)</span><p id="para0016" class="elsevierStylePara elsevierViewall">A composite of adverse perinatal outcomes commonly associated with preterm birth < 30 weeks (i.e., perinatal morbidity/mortality), was defined as the occurrence of any in-hospital death, oxygen use at 36 weeks corrected postnatal age, intraventricular hemorrhage grade 3 or 4, or Bell stage 2 or 3 necrotizing enterocolitis,<a class="elsevierStyleCrossRef" href="#bib0011"><span class="elsevierStyleSup">11</span></a> based on the recommendations of Webbe et al.<a class="elsevierStyleCrossRef" href="#bib0012"><span class="elsevierStyleSup">12</span></a></p></span></span><span id="sec0008" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0014">Statistical analysis</span><p id="para0017" class="elsevierStylePara elsevierViewall">All variables were summarized as means (standard deviations [SD]), medians (interquartile range [IQR]), or frequencies with percentages, as appropriate.</p><p id="para0018" class="elsevierStylePara elsevierViewall">All infants were randomly allocated to one of two subsets: <span class="elsevierStyleItalic">training set</span> (70% of cases, n = 2,900) and <span class="elsevierStyleItalic">validation set</span> (30% of cases, n = 1,172) using the sample command of the R software. Infants born at less than 24 weeks of GA were assigned to the training set since the IG21 does not contain references for these GAs. The training set was used to calculate the corresponding centiles for weight, length, W/L ratio, BMI, and PI using fractional polynomial models. In all cases, the fractional polynomial smoothing technique by sex was applied. This new reference for preterm infants < 30 weeks that includes the 3<span class="elsevierStyleSup">rd</span>, 10<span class="elsevierStyleSup">th</span>, 50<span class="elsevierStyleSup">th</span>, and 97<span class="elsevierStyleSup">th</span> percentiles for selected growth phenotypes was named BNRN (Brazilian Neonatal Research Network).</p><p id="para0019" class="elsevierStylePara elsevierViewall">The following analysis was calculated using the <span class="elsevierStyleItalic">validation set:</span></p><p id="para0020" class="elsevierStylePara elsevierViewall">Single and multiple <span class="elsevierStyleItalic">log-binomial regression models</span> were fitted to estimate the relative risks (RR) with 95% confidence intervals (95%CI) of CNMM associated with the growth phenotypes, comparing them to IG21. In the multivariate models, the RRs were adjusted for maternal (skin color, education, hypertension, diabetes, smoking, drinking alcohol, and delivery type) and newborn variables (5’ Apgar score < 7).</p><p id="para0021" class="elsevierStylePara elsevierViewall">The <span class="elsevierStyleItalic">agreement</span> between BNRN and IG21 growth phenotypes was estimated using the kappa coefficient. According to this coefficient, the strength of agreement was categorized as poor (< 0), slight (0–0.2), fair (0.21–0.4), moderate (0.41–0.6), substantial (0.61–0.8), or almost perfect (0.81–1.0).<a class="elsevierStyleCrossRef" href="#bib0013"><span class="elsevierStyleSup">13</span></a></p><p id="para0022" class="elsevierStylePara elsevierViewall">The <span class="elsevierStyleItalic">predictive accuracy</span> of the BNRN and IG21 growth phenotypes for CNMM was calculated using sensitivity, specificity, positive (PPV), and negative (NPV) predictive values. <span class="elsevierStyleItalic">Discrimination</span> of the models was assessed by the areas under the ROC curve (AUC), while <span class="elsevierStyleItalic">calibration</span> was assessed by the Hosmer-Lemeshow test (good calibration when p > 0.05). The Brier score was calculated to test de models’ <span class="elsevierStyleItalic">accuracy</span> (where 0 indicates a perfect model and 0.25 is a non-informative model).<a class="elsevierStyleCrossRef" href="#bib0014"><span class="elsevierStyleSup">14</span></a></p><p id="para0023" class="elsevierStylePara elsevierViewall">The Stata 14.1 (StataCorp, College Station, USA), SAS 9.4 (SAS, Cary, USA), and R 3.2.4 with GAMLSS framework (<a href="https://cran.r-project">https://cran.r-project.org/web/packages/gamlss/index.html</a>) statistical packages were used. A significance level of 0.05 was adopted.</p></span></span><span id="sec0009" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0015">Results</span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0016">Study population</span><p id="para0024" class="elsevierStylePara elsevierViewall">A cohort of more than 4,000 preterm infants born from 2014 to 2019 was studied (Supplementary Fig. 1). The main differences in maternal and infants’ characteristics between the training and validation set are depicted in <a class="elsevierStyleCrossRef" href="#sec0024">Supplementary Table 1</a> and <a class="elsevierStyleCrossRef" href="#sec0024">Supplementary Table 2</a>. In short, the training and validation sets were very similar, as expected.</p><p id="para0025" class="elsevierStylePara elsevierViewall">The infants were born to mostly young brown mothers with 8 –11 years of education with a high prevalence of high blood pressure and diabetes and who smoked and consumed alcohol. Most infants were born by cesarean section, at a mean GA of 191 (SD 12) days and with a mean BW of 912 (SD 265) g. The frequencies of abnormal growth phenotypes were very similar, as expected.</p></span><span id="sec0011" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0017">Main outcomes</span><p id="para0026" class="elsevierStylePara elsevierViewall">The newborns exhibited significant morbidity (prolonged NICU stay, bronchopulmonary dysplasia, severe intraventricular hemorrhage, and necrotizing enterocolitis) and a high mortality rate, characterizing a high-risk population (<a class="elsevierStyleCrossRef" href="#sec0024">Supplementary Table 3</a>). The frequency of CNMM was 58.6% for the whole cohort.</p><p id="para0027" class="elsevierStylePara elsevierViewall">Smoothed centiles for BW, length, W/L ratio, BMI, and PI by sex and GA according to the BNRN reference are shown in <a class="elsevierStyleCrossRef" href="#tbl0001">Table 1</a>.</p><elsevierMultimedia ident="tbl0001"></elsevierMultimedia><p id="para0028" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0002">Table 2</a> depicts the comparison and agreement in the frequencies of the selected growth phenotypes between BNRN and IG21. It can be observed that, while the frequencies of all BNRN phenotypes were within the expected limits, those of IG-21 exceeded three to four times the expected values for SGA3, SGA10, and stunting. The opposite was observed for LGA and W/L-for-GA. This agrees with the kappa analysis in which agreement between the two references was substantial only for SGA10 and LGA, while a moderate agreement was found for W/L ratio < 3<span class="elsevierStyleSup">rd</span> percentile and fair agreement for SGA3 and stunting.</p><elsevierMultimedia ident="tbl0002"></elsevierMultimedia></span><span id="sec0012" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0018">Risk of CNMM associated with phenotypes</span><p id="para0029" class="elsevierStylePara elsevierViewall">The adjusted relative risk (aRR) of CNMM associated with BNRN phenotypes (<a class="elsevierStyleCrossRef" href="#tbl0003">Table 3</a>) showed a higher aRR for stunting and wasting, but a lower aRR for SGA 3 and SGA 10 compared to IG21. No differences were observed for SGA10 or LGA.</p><elsevierMultimedia ident="tbl0003"></elsevierMultimedia></span><span id="sec0013" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0019">Predictive ability, discrimination, calibration, and accuracy of the models</span><p id="para0030" class="elsevierStylePara elsevierViewall">All conditions had an excellent specificity (> 95%) and a good PPV (70-90%), except for LGA, but poor sensitivity and NPV. The highest PPV was observed for W/L ratio < 3<span class="elsevierStyleSup">rd</span> percentile according to BNRN (93.1%), followed by stunting according to BNRN (92.6%) (<a class="elsevierStyleCrossRef" href="#tbl0004">Table 4</a>).</p><elsevierMultimedia ident="tbl0004"></elsevierMultimedia><p id="para0031" class="elsevierStylePara elsevierViewall">The analysis of discrimination, calibration, and accuracy (Brier scores) of the model for CNMM is presented in <a class="elsevierStyleCrossRef" href="#sec0024">Supplementary Table 4</a>. Briefly, for both BNRN and IG21, the AUCs were only marginally higher than 0.5 (low discrimination), the Brier scores were very close to 0.25 (not informative), and the Hosmer-Lemeshow test indicated good calibration.</p></span></span><span id="sec0014" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0020">Discussion</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0021">Main findings</span><p id="para0032" class="elsevierStylePara elsevierViewall">This study evaluated several anthropometric measures of preterm infants < 30 weeks at birth and the predictive value of selected growth phenotypes for neonatal morbidity and mortality. In this study, a large cohort of more than 4,000 preterm infants < 30 weeks were randomly allocated to a training or a validation set and percentiles for BW, length, W/L ratio, BMI, and PI by sex and GA were calculated. The results showed that: i) the frequency of all BNRN phenotypes was within the expected limits; ii) the BNRN reference yielded higher aRR than IG21 for length-for-GA and W/L-for-GA, while the opposite was observed for SGA3; iii) both BNRN and IG21 were poor predictors of adverse neonatal outcomes; iv) finally, CNMM showed good calibration but low discrimination.</p></span><span id="sec0016" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0022">Characteristics</span><p id="para0033" class="elsevierStylePara elsevierViewall">The apparent differences between BNRN and IG21 can be explained by the present tertiary site cohort that included mothers with a higher risk profile including a high prevalence of hypertension and diabetes, a population not included in the IG21 Project. Similar percentages were found in a study conducted in São Paulo, Brazil (27.4% with hypertension and 17.3% with diabetes),<a class="elsevierStyleCrossRef" href="#bib0015"><span class="elsevierStyleSup">15</span></a> supporting the idea that preterm birth is associated with early abnormal obstetric conditions. Also, this pattern of high-risk mothers is similar to that of the NEOCOSUR South American Network.<a class="elsevierStyleCrossRef" href="#bib0016"><span class="elsevierStyleSup">16</span></a> This sicker population of mothers suggests that BNRN infants were exposed to a suboptimal intrauterine environment and, possibly, to fetal growth restriction (FGR), one of the most important risk factors associated with preterm birth.<a class="elsevierStyleCrossRef" href="#bib0001"><span class="elsevierStyleSup">1</span></a></p></span><span id="sec0017" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0023">Phenotypes according to BNRM and IG21 criteria</span><p id="para0034" class="elsevierStylePara elsevierViewall">Because the birthweight distribution of the BNRM chart was right-shifted (<a class="elsevierStyleCrossRef" href="#sec0024">Supplementary Fig. 2</a>), whereas the distribution of the INTERGROWTH chart was shifted to systematically lower values<a class="elsevierStyleCrossRef" href="#bib0003"><span class="elsevierStyleSup">3</span></a> the proportion of BNRN live births classified as SGA by the IG21 criteria was greater than that identified by the BNRN, while the proportion classified as LGA was half under IG21 criteria, according to a previous study conducted in Canada.<a class="elsevierStyleCrossRef" href="#bib0007"><span class="elsevierStyleSup">7</span></a> Importantly, some infants with low or high percentile values are healthy infants who are simply genetically smaller or larger.<a class="elsevierStyleCrossRef" href="#bib0017"><span class="elsevierStyleSup">17</span></a> Comparing the normative IG21 standard, this overall picture suggests that BNRN live births have low rates of growth restriction and high rates of excess growth (<a class="elsevierStyleCrossRef" href="#tbl0002">Table 2</a>).</p></span><span id="sec0018" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0024">Reason for the discrepancies between BNRN and IG21</span><p id="para0035" class="elsevierStylePara elsevierViewall">The discrepancy in the W/L ratio between the BNRN and IG21 populations may be explained by the fact that the latter included mothers of widely varying size (particularly height) and few females with BW in the lower 50<span class="elsevierStyleSup">th</span> percentile range, which could have led to the greater W/L ratios in the BNRN reference.<a class="elsevierStyleCrossRef" href="#bib0018"><span class="elsevierStyleSup">18</span></a> The kappa agreement was substantial only for SGA10 and LGA.</p></span><span id="sec0019" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0025">Selected abnormal growth phenotypes and the risks of CNMM</span><p id="para0036" class="elsevierStylePara elsevierViewall">The risks of CNMM were only slightly different when either BNRN or IG21 was used. Overall, having an abnormal growth phenotype was associated with a 1.5- to 1.7-fold increase in the likelihood of CNMM. BNRN yielded statistically significantly higher aRR than IG21 for stunting and wasting, suggesting that they could have suffered fetal growth restriction due to the high frequency of morbidity during pregnancy. The most important difference was that a W/L ratio < 3<span class="elsevierStyleSup">rd</span> percentile was significantly associated with CNMM when BNRN but not when IG21 was used, attributable to the prescriptive design of the INTERGROWTH-21st Project.<a class="elsevierStyleCrossRef" href="#bib0004"><span class="elsevierStyleSup">4</span></a></p><p id="para0037" class="elsevierStylePara elsevierViewall">Differences in neonatal morbidity and mortality rates within centile categories of BNRN and IG21 may be due to differences in the prevalence of phenotypes (<a class="elsevierStyleCrossRef" href="#tbl0002">Table 2</a>). Although SGA-3 live births identified by the IG21 criteria represent more severely growth-restricted infants (9.5%), their CNMM risk was similar to that of SGA-3 infants identified by the BNRN criteria (<a class="elsevierStyleCrossRef" href="#tbl0003">Table 3</a>). This agrees with a recent study in which only prenatal FGR cases with a BW below the 3<span class="elsevierStyleSup">rd</span> percentile employing the IG21 were at higher risk of adverse postnatal outcomes.<a class="elsevierStyleCrossRef" href="#bib0019"><span class="elsevierStyleSup">19</span></a></p><p id="para0038" class="elsevierStylePara elsevierViewall">The prognostic value of the selected abnormal growth phenotypes for CNMM showed poor sensitivity and NPV. As a result, many infants would be categorized as false negatives for CNMM. Infants with any of the phenotypes would be more likely to develop CNMM (<a class="elsevierStyleCrossRef" href="#tbl0003">Table 3</a>), but infants classified as “normal” would still have a 50% risk of developing CNMM.</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0026">Comparison with existing literature</span><p id="para0039" class="elsevierStylePara elsevierViewall">The present results are consistent with previous studies. In the RADIUS trial, the abilities of the INTERGROWTH chart to predict adverse perinatal outcomes were similarly poor (AUCs between 0.50 and 0.59).<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">20</span></a> In a study of 3437 fetuses of African-American women, the INTERGROWTH chart poorly detected composite adverse perinatal outcomes at the 10th centile (e.g., AUC 0.55), with a sensitivity of only 22%.<a class="elsevierStyleCrossRef" href="#bib0021"><span class="elsevierStyleSup">21</span></a> Furthermore, in a cohort of 1054 women from the USA, the 10th centile on a customized standard and the INTERGROWTH standard performed poorly to identify adverse neonatal outcomes (AUC 0.51).<a class="elsevierStyleCrossRef" href="#bib0019"><span class="elsevierStyleSup">19</span></a> Finally, in an Argentinean study the sensitivity, positive predictive values, and Youden Index of phenotypes for adverse perinatal outcomes were very low.<a class="elsevierStyleCrossRef" href="#bib0022"><span class="elsevierStyleSup">22</span></a></p><p id="para0040" class="elsevierStylePara elsevierViewall">In a recent study from Canada the ability of the INTERGROWTH, WHO, and Hadlock charts to predict neonatal risk was poor (AUC = 0.54, for each chart), similar to the present study. At the traditional cut-point of the 10th centile, the sensitivity of the INTERGROWTH chart was 11%, and the positive predictive value was 15%, very low compared with the present study.<a class="elsevierStyleCrossRef" href="#bib0023"><span class="elsevierStyleSup">23</span></a></p></span><span id="sec0021" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0027">Growth phenotypes as screening tools</span><p id="para0041" class="elsevierStylePara elsevierViewall">Although selected growth phenotypes were significantly associated with poor outcomes, they are not useful as screening tools for identifying infants at higher risk using either BNRN or IG21. One possible explanation is that the occurrence of poor outcomes is much more related to postnatal conditions and quality of care than to intrauterine conditions. Another explanation is the choice of the components of the CNMM. Ideally, to be useful as an indicator of neonatal morbidity and mortality, the threshold must have maximum sensitivity but not at the expense of specificity (to minimize unnecessary testing of neonates). A systematic review identified 17 composite neonatal morbidity indicators; however, the heterogeneity of the components and insufficient validation limit their use for benchmarking and meta-analyses.<a class="elsevierStyleCrossRef" href="#bib0024"><span class="elsevierStyleSup">24</span></a></p></span><span id="sec0022" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0028">Strengths and limitations</span><p id="para0042" class="elsevierStylePara elsevierViewall">This study has several <span class="elsevierStyleItalic">strengths</span>. To our knowledge, this is the first study conducted in Brazil that developed a reference chart of several anthropometric measures at birth for preterm infants < 30 weeks and assess the predictive ability of selected growth phenotypes for neonatal morbidity and mortality. Another strength is the high quality of the data, which were prospectively collected and audited. In addition, BRNN is a cohort of preterm (< 30 weeks) and very low birth weight (< 1500 g) infants, larger than any other published cohort examining the association between size at birth and perinatal outcomes with validated data from three Brazilian regions collected during routine prenatal care, representing a huge proportion of the Brazilian territory.</p><p id="para0043" class="elsevierStylePara elsevierViewall">On the other hand, the present findings are <span class="elsevierStyleItalic">limited</span> by the selected cohort of preterm infants < 30 weeks that were admitted to NICUs of tertiary-care university hospitals, a population that is at higher risk. In addition, since the authors’ analysis included 20 public tertiary-care university hospitals from three different Brazilian regions, potential errors concerning gestational age estimates would have affected birth weight-for-gestational age centiles under both the INTERGROWTH and BNRN criteria. Also, there may have been variations in management at each site which could have impacted neonatal morbidity and mortality.</p><p id="para0044" class="elsevierStylePara elsevierViewall">Another limitation is that the W/L ratio quantifies disproportionality between weight and length. As a result, growth restriction or excess resulting in insufficient or excessive weight and length growth may not be correctly identified by the W/L ratio or other weight-for-length ratios.<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">25</span></a> In addition, some important variables such as prenatal steroids, which may be linked to better perinatal outcomes, were not included in this analysis.<a class="elsevierStyleCrossRef" href="#bib0026"><span class="elsevierStyleSup">26</span></a> Finally, there is no gold standard outcome that defines risks associated with preterm birth < 30 weeks;<a class="elsevierStyleCrossRef" href="#bib0023"><span class="elsevierStyleSup">23</span></a> therefore, caution is necessary when generalizing these conclusions to other settings and countries.</p><p id="para0045" class="elsevierStylePara elsevierViewall">The IG21 fetal growth standards might not represent the intrauterine growth of Brazilian fetuses, as does the BNRN cross-sectional growth reference because the latter included a 24 times higher number of preterm infants at less than 30 weeks GA (4,072 infants) and relatively equal numbers of male and female infants.</p></span></span><span id="sec0023" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0029">Conclusions</span><p id="para0046" class="elsevierStylePara elsevierViewall">The BNRN phenotypes at birth differed markedly from the IG21 standards and showed poor accuracy in predicting adverse neonatal outcomes. Taken together, more studies of growth phenotypes in preterm infants < 30 weeks associated with CNMM are still needed before they can be introduced and implemented in clinical practice.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:9 [ 0 => array:3 [ "identificador" => "xres1843951" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abss0001" "titulo" => "Objective" ] 1 => array:2 [ "identificador" => "abss0002" "titulo" => "Method" ] 2 => array:2 [ "identificador" => "abss0003" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abss0004" "titulo" => "Conclusion" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1606574" "titulo" => "Keywords" ] 2 => array:2 [ "identificador" => "sec0001" "titulo" => "Introduction" ] 3 => array:3 [ "identificador" => "sec0002" "titulo" => "Material and methods" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "sec0003" "titulo" => "Study population" ] 1 => array:2 [ "identificador" => "sec0004" "titulo" => "Database" ] 2 => array:3 [ "identificador" => "sec0005" "titulo" => "Newborn anthropometric measures" "secciones" => array:2 [ 0 => array:2 [ "identificador" => "sec0006" "titulo" => "Selected growth phenotypes (according to IG21, for GA and sex)" ] 1 => array:2 [ "identificador" => "sec0007" "titulo" => "Composite neonatal morbidity and mortality (CNMM)" ] ] ] 3 => array:2 [ "identificador" => "sec0008" "titulo" => "Statistical analysis" ] ] ] 4 => array:3 [ "identificador" => "sec0009" "titulo" => "Results" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "sec0010" "titulo" => "Study population" ] 1 => array:2 [ "identificador" => "sec0011" "titulo" => "Main outcomes" ] 2 => array:2 [ "identificador" => "sec0012" "titulo" => "Risk of CNMM associated with phenotypes" ] 3 => array:2 [ "identificador" => "sec0013" "titulo" => "Predictive ability, discrimination, calibration, and accuracy of the models" ] ] ] 5 => array:3 [ "identificador" => "sec0014" "titulo" => "Discussion" "secciones" => array:8 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Main findings" ] 1 => array:2 [ "identificador" => "sec0016" "titulo" => "Characteristics" ] 2 => array:2 [ "identificador" => "sec0017" "titulo" => "Phenotypes according to BNRM and IG21 criteria" ] 3 => array:2 [ "identificador" => "sec0018" "titulo" => "Reason for the discrepancies between BNRN and IG21" ] 4 => array:2 [ "identificador" => "sec0019" "titulo" => "Selected abnormal growth phenotypes and the risks of CNMM" ] 5 => array:2 [ "identificador" => "sec0020" "titulo" => "Comparison with existing literature" ] 6 => array:2 [ "identificador" => "sec0021" "titulo" => "Growth phenotypes as screening tools" ] 7 => array:2 [ "identificador" => "sec0022" "titulo" => "Strengths and limitations" ] ] ] 6 => array:2 [ "identificador" => "sec0023" "titulo" => "Conclusions" ] 7 => array:2 [ "identificador" => "xack651125" "titulo" => "Acknowledgments" ] 8 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2022-01-25" "fechaAceptado" => "2022-07-08" "PalabrasClave" => array:1 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1606574" "palabras" => array:6 [ 0 => "Premature birth" 1 => "Very low birth weight" 2 => "Phenotype" 3 => "Outcome" 4 => "Predictive values" 5 => "Network" ] ] ] ] "tieneResumen" => true "resumen" => array:1 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abss0001" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0002">Objective</span><p id="spara010" class="elsevierStyleSimplePara elsevierViewall">To assess the predictive value of selected growth phenotypes for neonatal morbidity and mortality in preterm infants < 30 weeks and to compare them with INTERGROWTH-21<span class="elsevierStyleSup">st</span> (IG21).</p></span> <span id="abss0002" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0003">Method</span><p id="spara011" class="elsevierStyleSimplePara elsevierViewall">Retrospective analysis of data from the Brazilian Neonatal Research Network (BNRN) database for very low birth weight (VLBW) at 20 public tertiary-care university hospitals. Outcome: the composite neonatal morbidity and mortality (CNMM) consisted of in-hospital death, oxygen use at 36 weeks, intraventricular hemorrhage grade 3 or 4, and Bell stage 2 or 3 necrotizing enterocolitis. Selected growth phenotypes: small-for-gestational-age (SGA) defined as being < 3<span class="elsevierStyleSup">rd</span> (SGA3) or 10<span class="elsevierStyleSup">th</span> (SGA10) percentiles of BW, and large-for-gestational-age (LGA) as being > 97<span class="elsevierStyleSup">th</span> percentile of BW. Stunting as being < 3<span class="elsevierStyleSup">rd</span> percentile of the length and wasting as being < 3<span class="elsevierStyleSup">rd</span> percentile of BMI. Single and multiple log-binomial regression models were fitted to estimate the relative risks of CNMM, comparing them to IG21.</p></span> <span id="abss0003" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0004">Results</span><p id="spara012" class="elsevierStyleSimplePara elsevierViewall">4,072 infants were included. The adjusted relative risks of CNMM associated with selected growth phenotypes were (BNRN/IG21): 1.45 (0.92–2.31)/1.60 (1.27–2.02) for SGA; 0.90 (0.55–1.47)/1.05 (0.55–1.99) for LGA; 1.65 (1.08–2.51)/1.58 (1.28–1.96) for stunting; and 1.48 (1.02–2.17) for wasting. Agreement between the two references was variable. The growth phenotypes had good specificity (>95%) and positive predictive value (70-90%), with poor sensitivity and low negative predictive value.</p></span> <span id="abss0004" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0005">Conclusion</span><p id="spara013" class="elsevierStyleSimplePara elsevierViewall">The BNRN phenotypes at birth differed markedly from the IG21 standard and showed poor accuracy in predicting adverse neonatal outcomes.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abss0001" "titulo" => "Objective" ] 1 => array:2 [ "identificador" => "abss0002" "titulo" => "Method" ] 2 => array:2 [ "identificador" => "abss0003" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abss0004" "titulo" => "Conclusion" ] ] ] ] "NotaPie" => array:1 [ 0 => array:1 [ "nota" => "<p class="elsevierStyleNotepara" id="notep0001">Study conducted at Universidade de São Paulo, Faculdade de Medicina de Ribeirão Preto, Departamento de Pediatria, São Paulo, SP, Brazil.</p>" ] ] "apendice" => array:1 [ 0 => array:1 [ "seccion" => array:1 [ 0 => array:4 [ "apendice" => "<p id="para0047a" class="elsevierStylePara elsevierViewall"><elsevierMultimedia ident="ecom0001"></elsevierMultimedia></p>" "etiqueta" => "Appendix" "titulo" => "Supplementary materials" "identificador" => "sec0025" ] ] ] ] "multimedia" => array:5 [ 0 => array:8 [ "identificador" => "tbl0001" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "alt0001" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:1 [ "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"><a name="en0006"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col">GA \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0001"></a><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="10" align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Weight (kg)</span></th></tr><tr title="table-row"><a name="en000a2"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0003"></a><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="4" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Boys</th><a name="en0004"></a><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top" scope="col"></th><a name="en0005"></a><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="4" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Girls</th></tr><tr title="table-row"><a name="en0002"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0007"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">P3 \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0008"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">P10 \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0009"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">P50 \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0010"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">P97 \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0011"></a><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top" scope="col" style="border-bottom: 2px solid black"></th><a name="en0012"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">P3 \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0013"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">P10 \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0014"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">P50 \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0015"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">P97 \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><a name="en0016"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">22 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0017"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.41 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0018"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.47 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0019"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.58 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0020"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.72 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0021"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top"></td><a name="en0022"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="top">0.40 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0023"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.45 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0024"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.54 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0025"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.66 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0026"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">23 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0027"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.40 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0028"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.47 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0029"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.61 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0030"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.79 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0031"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top"></td><a name="en0032"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="top">0.40 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0033"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.46 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0034"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.58 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0035"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.74 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0036"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">24 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0037"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.41 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0038"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.50 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0039"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.67 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0040"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.88 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0041"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top"></td><a name="en0042"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="top">0.41 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0043"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.48 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0044"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.63 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0045"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.84 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0046"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">25 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0047"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.44 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0048"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.55 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0049"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.75 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0050"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.01 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0051"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top"></td><a name="en0052"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="top">0.42 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0053"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.51 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0054"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.70 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0055"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.95 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0056"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">26 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0057"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.48 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0058"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.61 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0059"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.85 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0060"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.14 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0061"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top"></td><a name="en0062"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="top">0.45 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0063"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.55 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0064"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.78 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0065"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.09 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0066"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">27 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0067"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.53 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0068"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.67 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0069"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.95 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0070"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.29 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0071"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top"></td><a name="en0072"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="top">0.48 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0073"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.61 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0074"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.88 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0075"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.24 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0076"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">28 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0077"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.58 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0078"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.75 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0079"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.06 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0080"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.44 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0081"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top"></td><a name="en0082"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="top">0.53 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0083"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.68 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0084"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.99 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0085"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.41 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0086"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">29 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0087"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">0.64 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0088"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">0.82 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0089"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">1.17 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0090"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">1.60 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0091"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top" style="border-bottom: 2px solid black"></td><a name="en0092"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="top" style="border-bottom: 2px solid black">0.60 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0093"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">0.77 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0094"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">1.13 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0095"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">1.61 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0101"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">GA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0096"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="10" align="center" valign="top" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Length (cm)</span></td></tr><tr title="table-row"><a name="en0097"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0098"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="4" align="center" valign="top" style="border-bottom: 2px solid black">Boys</td><a name="en0099"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0100"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="5" align="center" valign="top" style="border-bottom: 2px solid black">Girls</td></tr><tr title="table-row"><a name="en000a2a"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0102"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P3 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0103"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P10 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0104"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P50 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0105"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P97 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0106"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0107"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top" style="border-bottom: 2px solid black">P3</td><a name="en0108"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P10 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0109"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P50 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0110"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P97 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0111"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">22 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0112"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">24.36 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0113"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">26.21 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0114"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">29.32 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0115"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">32.89 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0116"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0117"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">24.39</td><a name="en0118"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">25.91 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0119"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">28.56 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0120"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">31.70 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0121"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">23 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0122"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">24.95 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0123"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">26.90 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0124"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">30.19 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0125"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">33.95 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0126"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0127"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">24.92</td><a name="en0128"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">26.60 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0129"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">29.53 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0130"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">33.00 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0131"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">24 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0132"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">25.71 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0133"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">27.75 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0134"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">31.19 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0135"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">35.13 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0136"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0137"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">25.52</td><a name="en0138"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">27.34 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0139"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">30.54 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0140"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">34.32 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0141"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">25 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0142"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">26.57 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0143"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">28.69 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0144"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">32.28 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0145"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">36.39 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0146"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0147"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">26.18</td><a name="en0148"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">28.15 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0149"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">31.61 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0150"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">35.69 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0151"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">26 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0152"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">27.50 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0153"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">29.70 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0154"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">33.42 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0155"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">37.69 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0156"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0157"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">26.93</td><a name="en0158"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">29.03 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0159"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">32.73 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0160"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">37.10 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0161"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">27 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0162"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">28.47 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0163"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">30.75 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0164"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">34.59 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0165"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">39.00 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0166"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0167"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">27.76</td><a name="en0168"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">30.00 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0169"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">33.92 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0170"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">38.57 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0171"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">28 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0172"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">29.46 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0173"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">31.81 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0174"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">35.77 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0175"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">40.31 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0176"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0177"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">28.68</td><a name="en0178"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">31.04 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0179"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">35.19 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0180"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">40.09 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0181"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">29 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0182"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">30.46 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0183"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">32.87 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0184"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">36.94 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0185"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">41.60 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0186"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0187"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top" style="border-bottom: 2px solid black">29.70</td><a name="en0188"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">32.18 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0189"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">36.53 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0190"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">41.68 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0196"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">GA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0191"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="10" align="center" valign="top" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Weight-to-length ratio (kg/m)</span></td></tr><tr title="table-row"><a name="en0192"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0193"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="4" align="center" valign="top" style="border-bottom: 2px solid black">Boys</td><a name="en0194"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0195"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="5" align="center" valign="top" style="border-bottom: 2px solid black">Girls</td></tr><tr title="table-row"><a name="en000a3a"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0197"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P3 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0198"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P10 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0199"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P50 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0200"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P97 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0201"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0202"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top" style="border-bottom: 2px solid black">P3</td><a name="en0203"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P10 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0204"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P50 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0205"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P97 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0206"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">22 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0207"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.50 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0208"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.65 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0209"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.89 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0210"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.28 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0211"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0212"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">1.48</td><a name="en0213"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.63 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0214"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.97 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0215"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.40 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0216"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">23 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0217"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.49 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0218"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.67 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0219"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.97 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0220"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.45 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0221"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0222"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">1.48</td><a name="en0223"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.65 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0224"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.05 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0225"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.55 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0226"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">24 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0227"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.51 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0228"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.74 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0229"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.07 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0230"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.65 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0231"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0232"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">1.52</td><a name="en0233"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.69 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0234"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.18 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0235"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.76 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0236"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">25 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0237"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.55 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0238"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.84 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0239"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.21 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0240"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.88 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0241"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0242"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">1.59</td><a name="en0243"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.76 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0244"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.34 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0245"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.98 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0246"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">26 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0247"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.61 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0248"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.97 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0249"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.37 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0250"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">3.14 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0251"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0252"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">1.69</td><a name="en0253"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.86 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0254"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.52 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0255"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">3.24 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0256"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">27 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0257"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.70 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0258"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.11 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0259"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.57 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0260"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">3.44 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0261"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0262"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">1.80</td><a name="en0263"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.98 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0264"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.72 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0265"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">3.52 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0266"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">28 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0267"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.83 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0268"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.27 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0269"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.80 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0270"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">3.77 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0271"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0272"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">1.94</td><a name="en0273"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.14 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0274"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.94 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0275"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">3.80 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0276"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">29 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0277"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">2.00 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0278"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">2.44 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0279"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">3.06 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0280"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">4.15 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0281"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0282"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top" style="border-bottom: 2px solid black">2.08</td><a name="en0283"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">2.34 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0284"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">3.16 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0285"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">4.10 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0291"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">GA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0286"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="10" align="center" valign="top" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Body-mass index (kg/m<span class="elsevierStyleSup">2</span>)</span></td></tr><tr title="table-row"><a name="en0287"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0288"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="4" align="center" valign="top" style="border-bottom: 2px solid black">Boys</td><a name="en0289"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0290"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="5" align="center" valign="top" style="border-bottom: 2px solid black">Girls</td></tr><tr title="table-row"><a name="en050a2a"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0292"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P3 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0293"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P10 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0294"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P50 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0295"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P97 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0296"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0297"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top" style="border-bottom: 2px solid black">P3</td><a name="en0298"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P10 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0299"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P50 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0300"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P97 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0301"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">22 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0302"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">4.93 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0303"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">5.53 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0304"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">6.57 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0305"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">8.50 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0306"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0307"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">5.33</td><a name="en0308"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">5.77 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0309"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">6.66 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0310"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">8.51 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0311"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">23 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0312"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">5.06 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0313"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">5.67 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0314"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">6.76 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0315"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">8.76 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0316"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0317"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">5.18</td><a name="en0318"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">5.67 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0319"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">6.63 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0320"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">8.63 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0321"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">24 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0322"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">5.20 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0323"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">5.84 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0324"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">6.97 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0325"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">9.05 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0326"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0327"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">5.17</td><a name="en0328"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">5.69 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0329"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">6.72 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0330"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">8.88 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0331"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">25 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0332"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">5.37 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0333"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">6.04 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0334"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">7.21 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0335"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">9.38 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0336"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0337"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">5.26</td><a name="en0338"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">5.81 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0339"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">6.91 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0340"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">9.20 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0341"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">26 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0342"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">5.56 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0343"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">6.26 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0344"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">7.48 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0345"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">9.74 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0346"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0347"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">5.43</td><a name="en0348"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">6.01 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0349"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">7.18 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0350"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">9.60 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0351"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">27 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0352"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">5.78 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0353"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">6.51 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0354"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">7.79 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0355"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">10.14 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0356"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0357"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">5.67</td><a name="en0358"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">6.28 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0359"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">7.51 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0360"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">10.05 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0361"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">28 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0362"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">6.03 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0363"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">6.79 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0364"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">8.13 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0365"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">10.59 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0366"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0367"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">5.96</td><a name="en0368"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">6.60 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0369"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">7.89 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0370"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">10.55 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0371"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">29 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0372"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">6.31 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0373"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">7.10 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0374"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">8.50 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0375"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">11.09 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0376"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0377"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top" style="border-bottom: 2px solid black">6.30</td><a name="en0378"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">6.97 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0379"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">8.31 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0380"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">11.08 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0386"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">GA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0381"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="10" align="center" valign="top" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Ponderal index (kg/m<span class="elsevierStyleSup">3</span>)</span></td></tr><tr title="table-row"><a name="en0382"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0383"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="4" align="center" valign="top" style="border-bottom: 2px solid black">Boys</td><a name="en0384"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0385"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="5" align="center" valign="top" style="border-bottom: 2px solid black">Girls</td></tr><tr title="table-row"><a name="en060a2a"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0387"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P3 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0388"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P10 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0389"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P50 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0390"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P97 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0391"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0392"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top" style="border-bottom: 2px solid black">P3</td><a name="en0393"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P10 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0394"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P50 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0395"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top" style="border-bottom: 2px solid black">P97 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0396"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">22 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0397"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">17.97 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0398"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">19.50 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0399"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">24.02 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0400"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">35.11 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0401"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0402"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">20.90</td><a name="en0403"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">21.97 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0404"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">25.94 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0405"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">36.95 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0406"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">23 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0407"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">9.73 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0408"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">11.48 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0409"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">16.66 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0410"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">29.36 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0411"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0412"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">10.77</td><a name="en0413"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">11.99 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0414"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">16.57 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0415"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">29.25 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0416"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">24 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0417"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">5.03 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0418"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">7.06 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0419"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">13.06 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0420"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">27.80 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0421"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0422"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">4.96</td><a name="en0423"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">6.39 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0424"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">11.74 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0425"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">26.53 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0426"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">25 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0427"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">3.29 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0428"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">5.68 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0429"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">12.73 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0430"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">30.04 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0431"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0432"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">2.73</td><a name="en0433"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">4.41 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0434"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">10.74 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0435"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">28.23 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0436"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">26 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0437"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">3.79 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0438"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">6.64 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0439"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">15.03 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0440"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">35.65 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0441"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0442"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">3.13</td><a name="en0443"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">5.16 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0444"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">12.74 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0445"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">33.72 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0446"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">27 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0447"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">5.71 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0448"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">9.14 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0449"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">19.28 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0450"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">44.18 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0451"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0452"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">5.10</td><a name="en0453"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">7.57 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0454"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">16.80 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0455"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">42.33 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0456"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">28 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0457"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">8.04 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0458"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">12.25 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0459"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">24.67 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0460"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">55.17 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0461"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0462"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">7.40</td><a name="en0463"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">10.44 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0464"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">21.84 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0465"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">53.38 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0466"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">29 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0467"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">9.65 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0468"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">14.89 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0469"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">30.34 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0470"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">68.28 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0471"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0472"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="top">8.59</td><a name="en0473"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">12.41 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0474"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">26.71 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0475"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">66.30 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spara001" class="elsevierStyleSimplePara elsevierViewall">Smoothed centiles for birth weight, length, weight-to-length (W/L) ratio, body-mass index (kg/m<span class="elsevierStyleSup">2</span>) and ponderal index (PI), by sex and gestational age (GA), from the Brazilian Neonatal Research Network (2014 – 2019, n = 2900).</p>" ] ] 1 => array:8 [ "identificador" => "tbl0002" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "alt0002" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spara003" class="elsevierStyleSimplePara elsevierViewall">BNRN, Brazilian Neonatal Research Network; IG21, Intergrowth 21<span class="elsevierStyleSup">st</span>; CI, confidence interval; GA, gestational age; SGA, small for gestational age; LGA, large for gestational age; W/L, weight-to-length ratio (kg/m); BMI body-mass index (kg/m<span class="elsevierStyleSup">2</span>); PI, ponderal index (kg/m<span class="elsevierStyleSup">3</span>); N/A, not available.</p><p id="spara004" class="elsevierStyleSimplePara elsevierViewall">Kappa: <span class="elsevierStyleSup">a</span> fair agreement, <span class="elsevierStyleSup">b</span> substantial agreement, <span class="elsevierStyleSup">c</span> moderate agreement.</p><p id="spara005" class="elsevierStyleSimplePara elsevierViewall">Data are expressed as count (percentage).</p>" "tablatextoimagen" => array:1 [ 0 => array:1 [ "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"><a name="en0476"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Growth phenotype</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0477"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">BNRN</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0478"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">IG21</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0479"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Kappa (95%CI)</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><a name="en0480"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"><span class="elsevierStyleBold"><span class="elsevierStyleItalic">Weight-for-GA</span></span> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0481"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0482"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0483"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0484"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>< 3<span class="elsevierStyleSup">rd</span> centile (SGA) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0485"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">23 (2.0) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0486"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">111 (9.5) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0487"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.32 (0.22; 0.42)<span class="elsevierStyleSup">a</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0488"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>< 10<span class="elsevierStyleSup">th</span> centile (SGA) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0489"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">126 (10.8) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0490"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">205 (17.5) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0491"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.72 (0.66; 0.77)<span class="elsevierStyleSup">b</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0492"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>> 97<span class="elsevierStyleSup">th</span> centile (LGA) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0493"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">34 (2.9) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0494"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16 (1.4) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0495"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.63 (0.48; 0.79)<span class="elsevierStyleSup">b</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0496"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"><span class="elsevierStyleBold"><span class="elsevierStyleItalic">Length-for-GA</span></span> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0497"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0498"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0499"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0500"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>< 3<span class="elsevierStyleSup">rd</span> centile (stunted) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0501"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27 (2.4) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0502"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">143 (12.5) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0503"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.28 (0.20; 0.38)<span class="elsevierStyleSup">a</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0504"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"><span class="elsevierStyleBold"><span class="elsevierStyleItalic">W/L-for-GA</span></span> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0505"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0506"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0507"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0508"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>< 3<span class="elsevierStyleSup">rd</span> centile \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0509"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">29 (2.5) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0510"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9 (0.8) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0511"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.47 (0.27; 0.66)<span class="elsevierStyleSup">c</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0512"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"><span class="elsevierStyleBold"><span class="elsevierStyleItalic">BMI-for-GA</span></span> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0513"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0514"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0515"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0516"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>< 3<span class="elsevierStyleSup">rd</span> centile (wasted) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0517"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">36 (3.2) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0518"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">N/A \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0519"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0520"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"><span class="elsevierStyleBold"><span class="elsevierStyleItalic">PI-for-GA</span></span> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0521"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0522"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0523"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0524"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>< 3<span class="elsevierStyleSup">rd</span> centile \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0525"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">28 (2.5) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0526"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">N/A \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0527"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spara002" class="elsevierStyleSimplePara elsevierViewall">Comparison and agreement of selected growth phenotypes by BNRN and IG21 (n = 1172).</p>" ] ] 2 => array:8 [ "identificador" => "tbl0003" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "alt0003" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "<p id="spara007" class="elsevierStyleSimplePara elsevierViewall">BNRN, Brazilian Neonatal Research Network; IG21, Intergrowth 21<span class="elsevierStyleSup">st</span>; RR, crude relative risk; CI, confidence interval; aRR, adjusted relative risk; GA, gestational age; SGA, small for gestational age; LGA, large for gestational age; W/L, weight-to-length ratio (kg/m); BMI, body-mass index (kg/m<span class="elsevierStyleSup">2</span>); PI, ponderal index (kg/m<span class="elsevierStyleSup">3</span>); N/A, not available.</p>" "tablatextoimagen" => array:1 [ 0 => array:1 [ "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"><a name="en0528"></a><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_rowgroup " rowspan="2" align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Growth phenotype</span></th><a name="en0529"></a><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Univariate</span></th><a name="en0530"></a><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Multivariate</span><a class="elsevierStyleCrossRef" href="#tb3fn1"><span class="elsevierStyleBold"><span class="elsevierStyleSup">a</span></span></a></th></tr><tr title="table-row"><a name="en0532"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">RR-BNRN (95%CI)</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0533"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">RR-IG21(95%CI)</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0534"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">aRR-BNRN (95%CI)</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0535"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">aRR-IG21(95%CI)</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><a name="en0536"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Weight-for-GA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0537"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0538"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0539"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0540"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0541"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>< 3<span class="elsevierStyleSup">rd</span> centile (SGA) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0542"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.55 (1.32; 1.83) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0543"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.59 (1.45; 1.76) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0544"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1,45 (0,92; 2,31) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0545"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1,60 (1,27; 2,02) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0546"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>< 10<span class="elsevierStyleSup">th</span> centile (SGA) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0547"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.63 (1.49; 1.79) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0548"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.60 (1.46; 1.75) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0549"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1,62 (1,29; 2,03) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0550"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1,64 (1,34; 1,99) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0551"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>> 97<span class="elsevierStyleSup">th</span> centile (LGA) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0552"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.93 (0.68; 1.29) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0553"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.10 (0.75; 1.62) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0554"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0,90 (0,55; 1,47) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0555"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1,05 (0,55; 1,99) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0556"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Length-for-GA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0557"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0558"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0559"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0560"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0561"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>< 3<span class="elsevierStyleSup">rd</span> centile (stunted) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0562"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.68 (1.50; 1.90) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0563"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.60 (1.45; 176) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0564"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1,65 (1,08; 2,51) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0565"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.58 (1.28; 1.96) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0566"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">W/L-for-GA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0567"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0568"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0569"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0570"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0571"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>< 3<span class="elsevierStyleSup">rd</span> centile \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0572"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.70 (1.52; 1.90) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0573"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.40 (0.98; 1.98) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0574"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1,63 (1,09; 2,43) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0575"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1,32 (0,62; 2,80) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0576"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">BMI-for-GA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0577"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0578"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0579"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0580"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0581"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>< 3<span class="elsevierStyleSup">rd</span> centile (wasted) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0582"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.46 (1.23; 1.73) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0583"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">N/A \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0584"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1,48 (1,02; 2,17) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0585"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">N/A \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0586"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">PI-for-GA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0587"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0588"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0589"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0590"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0591"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>< 3<span class="elsevierStyleSup">rd</span> centile \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0592"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.55 (1.32; 1.83) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0593"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">N/A \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0594"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1,55 (1,02; 2,34) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0595"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">N/A \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tb3fn1" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="notep0006">The aRR was adjusted for maternal variables (skin color, education, hypertension, diabetes, smoking, drinking alcohol, and delivery type) and newborn variables (Apgar 5’ < 7).</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spara006" class="elsevierStyleSimplePara elsevierViewall">Crude and adjusted relative risks of the composite neonatal morbidity and mortality (CNMM) among selected growth phenotypes by BNRN and IG21 (n = 1172).</p>" ] ] 3 => array:8 [ "identificador" => "tbl0004" "etiqueta" => "Table 4" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "alt0004" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spara009" class="elsevierStyleSimplePara elsevierViewall">BNRN, Brazilian Neonatal Research Network; IG21, Intergrowth 21<span class="elsevierStyleSup">st</span>; GA, gestational age; SGA, small for gestational age; LGA, large for gestational age; W/L, weight-to-length ratio (kg/m); BMI, body-mass index (kg/m<span class="elsevierStyleSup">2</span>); PI, ponderal index (kg/m<span class="elsevierStyleSup">3</span>); N/A, not available.</p>" "tablatextoimagen" => array:1 [ 0 => array:1 [ "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"><a name="en0596"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col"><span class="elsevierStyleBold">Growth phenotype</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0597"></a><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="4" align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">BNRN</span></th><a name="en0598"></a><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="4" align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">IG21</span></th></tr><tr title="table-row"><a name="en0599"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0600"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Sensitivity</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0601"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Specificity</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0602"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">PPV</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0603"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">NPV</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0604"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Sensitivity</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0605"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Specificity</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0606"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">PPV</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0607"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">NPV</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><a name="en0608"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Weight-for-GA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0609"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0610"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0611"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0612"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0613"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0614"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0615"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0616"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0617"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span><3<span class="elsevierStyleSup">rd</span> centile (SGA) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0618"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">3,0% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0619"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">99,4% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0620"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">87,0% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0621"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">44,0% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0622"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">14,3% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0623"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">96,9% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0624"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">85,6% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0625"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">46,5% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0626"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span><10<span class="elsevierStyleSup">th</span> centile (SGA) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0627"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">16,4% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0628"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">96,7% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0629"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">86,5% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0630"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">47,0% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0631"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">25,3% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0632"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">92,7% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0633"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">82,0% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0634"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">48,8% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0635"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>>97<span class="elsevierStyleSup">th</span> centile (LGA) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0636"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2,7% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0637"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">96,9% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0638"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">52,9% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0639"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">43,3% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0640"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1,5% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0641"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">98,8% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0642"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">62,5% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0643"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">43,5% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0644"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Length-for-GA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0645"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0646"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0647"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0648"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0649"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0650"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0651"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0652"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0653"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span><3<span class="elsevierStyleSup">rd</span> centile (stunted) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0654"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">3,9% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0655"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">99,6% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0656"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">92,6% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0657"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">45,0% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0658"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">18,7% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0659"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">95,2% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0660"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">83,2% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0661"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">48,0% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0662"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>W/L-for-GA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0663"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0664"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0665"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0666"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0667"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0668"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0669"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0670"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0671"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span><3<span class="elsevierStyleSup">rd</span> centile \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0672"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">4,2% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0673"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">99,6% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0674"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">93,1% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0675"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">45,1% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0676"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1,1% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0677"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">99,6% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0678"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">77,8% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0679"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">44,3% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0680"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">BMI-for-GA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0681"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0682"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0683"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0684"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0685"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0686"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0687"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0688"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0689"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span><3<span class="elsevierStyleSup">rd</span> centile (wasted) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0690"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">4,5% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0691"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">98,6% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0692"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">80,6% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0693"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">44,9% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0694"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">N/A \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0695"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">N/A \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0696"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">N/A \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0697"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">N/A \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0698"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">PI-for-GA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0699"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0700"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0701"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0702"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0703"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0704"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0705"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0706"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0707"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span><3<span class="elsevierStyleSup">rd</span> centile \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0708"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">3,8% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0709"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">99,2% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0710"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">85,7% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0711"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">44,9% \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0712"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">N/A \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0713"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">N/A \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0714"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">N/A \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0715"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">N/A \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spara008" class="elsevierStyleSimplePara elsevierViewall">Prognostic accuracy of selected growth phenotypes by BNRN and IG21 for the composite neonatal morbidity and mortality (CNMM) (n = 1172).</p>" ] ] 4 => array:6 [ "identificador" => "ecom0001" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => false "mostrarDisplay" => true "detalles" => array:1 [ 0 => array:3 [ "identificador" => "alt0005" "detalle" => "Image, application " "rol" => "short" ] ] "Ecomponente" => array:2 [ "fichero" => "mmc1.docx" "ficheroTamanyo" => 212959 ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "cebibsec1" "bibliografiaReferencia" => array:26 [ 0 => array:3 [ "identificador" => "bib0001" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "The distribution of clinical phenotypes of preterm birth syndrome" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "FC Barros" 1 => "AT Papageorghiou" 2 => "CG Victora" 3 => "JA Noble" 4 => "R Pang" 5 => "J Iams" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1001/jamapediatrics.2014.3040" "Revista" => array:6 [ "tituloSerie" => "JAMA Pediatr" "fecha" => "2015" "volumen" => "169" "paginaInicial" => "220" "paginaFinal" => "229" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/25561016" "web" => "Medline" ] ] ] ] ] ] ] ] 1 => array:3 [ "identificador" => "bib0002" "etiqueta" => "2" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Anthropometric characterization of impaired fetal growth" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "CG Victora" 1 => "J Villar" 2 => "FC Barros" 3 => "LC Ismail" 4 => "C Chumlea" 5 => "AT Papageorghiou" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:3 [ "tituloSerie" => "JAMA Pediatr" "fecha" => "2015" "volumen" => "169" ] ] ] ] ] ] 2 => array:3 [ "identificador" => "bib0003" "etiqueta" => "3" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "INTERGROWTH-21st very preterm size at birth reference charts" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:6 [ 0 => "J Villar" 1 => "F Giuliani" 2 => "TR Fenton" 3 => "EO Ohuma" 4 => "LC Ismail" 5 => "SH. 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Permezel" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:5 [ "tituloSerie" => "J Matern Neonatal Med" "fecha" => "2020" "volumen" => "33" "paginaInicial" => "961" "paginaFinal" => "966" ] ] ] ] ] ] 5 => array:3 [ "identificador" => "bib0006" "etiqueta" => "6" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Revised birth centiles for weight, length and head circumference in the UK-WHO growth charts" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:3 [ 0 => "TJ Cole" 1 => "AF Williams" 2 => "CM. Wright" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:5 [ "tituloSerie" => "Ann Hum Biol" "fecha" => "2011" "volumen" => "38" "paginaInicial" => "7" "paginaFinal" => "11" ] ] ] ] ] ] 6 => array:3 [ "identificador" => "bib0007" "etiqueta" => "7" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Evaluation of the INTERGROWTH-21st project newborn standard for use in Canada" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:6 [ 0 => "S Liu" 1 => "A Metcalfe" 2 => "JA León" 3 => "R Sauve" 4 => "MS Kramer" 5 => "KS. 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The authors also thank the BNRN Research Committee for permission to use BNRN data for this study.</p>" "vista" => "all" ] ] ] "idiomaDefecto" => "en" "url" => "/00217557/0000009900000001/v2_202302081321/S002175572200095X/v2_202302081321/en/main.assets" "Apartado" => array:4 [ "identificador" => "10179" "tipo" => "SECCION" "en" => array:2 [ "titulo" => "Original articles" "idiomaDefecto" => true ] "idiomaDefecto" => "en" ] "PDF" => "https://static.elsevier.es/multimedia/00217557/0000009900000001/v2_202302081321/S002175572200095X/v2_202302081321/en/main.pdf?idApp=UINPBA000049&text.app=https://jped.elsevier.es/" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S002175572200095X?idApp=UINPBA000049" ]
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2024 November | 6 | 3 | 9 |
2024 October | 36 | 19 | 55 |
2024 September | 39 | 25 | 64 |
2024 August | 61 | 35 | 96 |
2024 July | 89 | 41 | 130 |
2024 June | 51 | 25 | 76 |
2024 May | 42 | 18 | 60 |
2024 April | 41 | 29 | 70 |
2024 March | 30 | 15 | 45 |
2024 February | 53 | 24 | 77 |
2024 January | 75 | 31 | 106 |
2023 December | 111 | 35 | 146 |
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2023 September | 30 | 45 | 75 |
2023 August | 27 | 18 | 45 |
2023 July | 29 | 17 | 46 |
2023 June | 39 | 25 | 64 |
2023 May | 50 | 22 | 72 |
2023 April | 71 | 27 | 98 |
2023 March | 289 | 71 | 360 |
2023 February | 169 | 59 | 228 |
2023 January | 59 | 31 | 90 |
2022 December | 58 | 34 | 92 |
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2022 September | 22 | 28 | 50 |