Comparison of birth weight, length, and head circumference between the BRISA-RP and Intergrowth-21st cohorts

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Pimenta, Carlos Grandi, Davi C. Aragon, Viviane Cunha Cardoso" "autores" => array:4 [ 0 => array:3 [ "nombre" => "João Roberto R." "apellidos" => "Pimenta" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 1 => array:3 [ "nombre" => "Carlos" "apellidos" => "Grandi" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "b" "identificador" => "aff0010" ] ] ] 2 => array:3 [ "nombre" => "Davi C." 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Other existing terms to describe prenatal malnutrition include: small for gestational age (SGA), intrauterine growth restriction (IUGR), and placental insufficiency. Traditionally, the Battaglia and Lubchenco classification has been used to classify newborns (NB) into small, adequate, and large for gestational age (GA) in relation to the 10th and 90th percentiles regarding the weight variable.<a class="elsevierStyleCrossRef" href="#bib0165">4</a> Information such as being born SGA is important from a clinical and social point of view because it shows a correlation with important outcomes, such as neonatal and infant mortality, low childhood growth, and chronic diseases in adulthood.<a class="elsevierStyleCrossRefs" href="#bib0170">5,6</a>Neonatal reference curves have been published in some countries, but none of them can be used as an international standard for growth.<a class="elsevierStyleCrossRef" href="#bib0180">7</a> Currently, the use of these curves is disputed, because they were created to be used as references for a country, aiming to compare the anthropometric characteristics of NB with those of the overall population, i.e., without the prescriptive nature of a standard applicable to different populations.<a class="elsevierStyleCrossRef" href="#bib0185">8</a>The International Fetal and Newborn Growth Consortium for the 21st Century (INTERGROWTH-21st) is a cross-sectional, multicenter, and transcultural study of NB growth, carried out with the same prescriptive approach and methodological design as that used for the creation of the World Health Organization (WHO) standard currently used for child and adolescent growth evaluation in Brazil.<a class="elsevierStyleCrossRef" href="#bib0190">9</a> The INTERGROWTH-21st (IG-21), which allows the anthropometric analysis of NB, was designed to be a “prescriptive” fetal growth pattern, i.e., to be used as the basis for recommending how healthy fetuses born to healthy mothers in healthy settings “should” grow, rather than a mere reference to how fetuses born in the same countries “actually grow”.<a class="elsevierStyleCrossRef" href="#bib0195">10</a>In this context, the aims of the present study were: (a) to compare the anthropometric data (weight, length, and head circumference) of the birth cohort of Ribeirão Preto 2010 (BRISA-RP) with the IG-21 standard, and (b) to estimate NB phenotypes (SGA, large for gestational age [LGA], stunting, and wasting) according to gender and GA.MethodsThis was a cross-sectional secondary analysis with a descriptive approach of data obtained from a cohort study (Brazilian Ribeirão Preto and São Luís Birth Cohort Studies – BRISA), whose objective was to find new risk factors for preterm birth.<a class="elsevierStyleCrossRef" href="#bib0200">11</a> All newborns who were alive between 01/01/2010 and 12/31/2010 in the city of Ribeirão Preto (PR), São Paulo, Brazil were assessed. During this period, 7702 newborns were evaluated, equivalent to 98% of hospital deliveries in the municipality.Inclusion criteria were children born at hospitals, to mothers living in RP, whereas the exclusion criteria were twin births, stillborn births, those without GA defined by the adopted criteria, those with no defined gender, and NB who had birth weight values incompatible with gestational age<a class="elsevierStyleCrossRef" href="#bib0205">12</a> (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>).<elsevierMultimedia ident="fig0005"></elsevierMultimedia>Data were obtained from an interview with the mothers after delivery and from information contained in the newborns’ medical records.Assessed variablesMaternal age (years), ethnicity (white or non-white), level of schooling (years), marital status (with or without partner), occupation of the head of the family (according to the classification proposed by Olsen and Frische<a class="elsevierStyleCrossRef" href="#bib0210">13</a>), Brazilian economic classification criterion according to the Brazilian Association of Research Companies (CCEB-ABEP),<a class="elsevierStyleCrossRef" href="#bib0215">14</a> number of cigarettes smoked daily during pregnancy, parity, arterial hypertension (prior or gestational), diabetes (previous or gestational), body mass index (BMI, kg/m2) before pregnancy (categorized as low weight [<18.5kg/m2], adequate weight [≥18.5kg/m2 and <25kg/m2], overweight [≥25kg/m2 and <30kg/m2], obesity [≥30kg/m2), and prenatal care (adequate≥4 consultations).The neonatal variables studied were gender, birth weight (BW), birth length, and head circumference (HC). Stunting was defined as length<3rd percentile, wasting as BMI<3rd percentile, SGA as birth weight<3rd percentile, and LGA as birth weight>97th percentile of the IG-21 study.<a class="elsevierStyleCrossRefs" href="#bib0195">10,15</a>GA was estimated based on date of the last menstrual period (LMP) and information from the earliest ultrasonography (USG) examination. A margin of error of ±7 days was calculated for the date found of the first USG.<a class="elsevierStyleCrossRef" href="#bib0225">16</a>Statistical analysesThe descriptive statistics included the mean value, proportion, standard deviation (SD), and 95% confidence interval (95% CI). Fractional polynomials were used to fit the models of the three anthropometric measurements (BW, length, and HC). The generalized additive models for location, scale, and shape (GAMLSS) provide the option of different distributions other than normal (bias distributions and kurtosis), as well as the modeling of other parameters of a distribution that determines scale and shape by using fractional polynomials.<a class="elsevierStyleCrossRef" href="#bib0230">17</a> In all cases, the technique of fractional polynomial smoothing by gender was applied for the 3rd, 50th, and 97th percentiles. For comparison of the curves with the IG-21 standard, the lower limit of 33+0 weeks was adopted, given that the IG-21 has a very questionable curve below 33 weeks considering the small number of newborns included.According to the IG-21 study, the smoothed percentiles of weight, length, and HC for the newborns are shown at exact weeks of gestational age only to avoid the publication of long tables for each day of pregnancy. For instance, the exact GA for the 36th week value is 36 weeks plus 0 days.<a class="elsevierStyleCrossRef" href="#bib0235">18</a> All models and goodness-of-fit evaluations were performed using the statistical software R (R Foundation for Statistical Computing, Vienna, Austria) using GAMLSS support. All graphs were produced using R software.The project was approved by the Research Ethics Committee of the HCFMRP (process no. 11157/2008). All mothers who agreed to participate in the study signed the informed consent.ResultsThe mean maternal age was 27 years (SD=6.2), and the percentage of young and old mothers was similar. Most of the population self-reported as white, approximately half of the mothers had a level of schooling between 9 and 11 years, and the vast majority of the mothers declared having a partner. In most families the occupation of the head of the family was unskilled or semi-skilled manual worker. The upper and intermediate social classes showed a similar representation (Table 1, Supplementary Material).About 1/3 of the mothers were overweight and obese, slightly more than 10% said they were smokers, and about 13% of the mothers were hypertensive and 6% were diabetic.Most of the mothers were primiparous and only 2 % of pregnant women presented inadequate prenatal care (Table 2, Supplementary Material). The distribution by gender was equivalent. Preterm births represented 13% and almost 8% of infants had low birth weight. The SGA rate was 2.9%, while the LGA rate was 4.3%, with an inverse association with GA. Stunting affected 6.5% of the sample and wasting, 1.5% (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>), with a predominance of girls and full-term pregnancies; both conditions were present in 0.4% of the sample.<elsevierMultimedia ident="tbl0005"></elsevierMultimedia>Fig. 1 (Supplementary Material) shows the BRISA-RP histograms of birth weight according to gender. The distributions are very similar, although that of the girls shows greater kurtosis.Distribution curves of BW, length, and HC of the BRISA-RP cohort were constructed, according to GA and gender. <a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a> shows the individual values (observed values) and the smoothed 3rd, 50th, and 97th percentiles (estimated values), using fractional polynomials. Few outliers were observed after 37+0 weeks of GA for BW and almost identical values were observed for length and HC at birth.<elsevierMultimedia ident="fig0010"></elsevierMultimedia>The curves of the 3rd, 50th, and 97th percentiles of the BRISA-RP cohort were compared with IG-21 by GA and gender. For weight in both genders, it was observed that between weeks 33+0 and 39+6, the 50th and 97th percentiles of the BRISA-RP cohort were higher than IG-21; then both percentiles cross the IG-21 pattern and decrease up to week 42+6. For the 3rd percentile, the behavior is similar, but smoother (<a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>). In numerical terms, the divergence between BRISA-RP and IG-21 is more pronounced among preterm (33–36 weeks) NB, in which the mean difference between the two populations is +263g for boys and +270g for girls; in full-term infants (37–40 weeks), the mean difference was +81g for boys and +52g for girls; and for post-term (41 and 42 weeks) NB, the mean difference was −120g for boys and −106g for girls (Table 3, Supplementary Material).<elsevierMultimedia ident="fig0015"></elsevierMultimedia>Regarding length, the growth curve (50th and 97th percentiles) increased steadily from 33 weeks gestation to 37–39 weeks in the BRISA-RP cohort and then crossed the IG-21 curve. The 3rd percentile always remained below the standard (<a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>). Numerically, the mean variation was always<1cm in both boys and girls (Table 4, Supplementary Material).Finally, the HC for both genders showed a large gap between the 50th and 97th percentiles of the BRISA-PR Cohort and the IG-21 curve until reaching the post-term period; however, the 3rd percentile trajectory was parallel with the IG-21 standard until week 39, when it crossed it (<a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>). Regarding the numerical differences, it was observed that preterm NB showed a variation>1cm (1.33cm for boys and 1.39cm for girls), while for full-term and post-term NB, the variation was<1cm (Table 5, Supplementary Material).DiscussionTo the best of the authors’ knowledge, this is the first Brazilian study that compared a cohort at birth with the international standard IG-21 regarding the size of the newborn for gestational age and gender.Of the 7185 single live births, those below the 3rd percentile (SGA) and above the 97th percentile (LGA) of the IG-21 standard for birth weight had detection rates of 2.9% and 4.3%, respectively. For stunting and wasting, the values were 6.5% and 1.5%, respectively.Adjusted percentiles were calculated based on individual data from more than 7000 infants using fractional polynomial regression and data were reported according to full weeks of gestation as smoothed percentiles (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>), which were consistent with the raw data, increasing the confidence in the curves. SGA was defined as birth weight for age and gender<3rd percentile (instead of the more frequently used 10th percentile), indicating a severe insult; this eliminates the chance of erroneous inclusion of a normal newborn into the lowest birth weight distribution.It is evident that the birth weight curves of the BRISA-RP cohort and the IG-21 standard, although similar in the full-term period, are very different at the earliest gestational ages. While at the 40 weeks of GA there was no difference in the medians, at 33 weeks gestation the median BRISA-RP was almost 300g higher. This makes the prevalence of SGA in preterm births higher in the BRISA-PR cohort than in the standard curve. The probable reasons for a higher frequency of LGA in the BRISA-PR cohort were increases in the maternal pre-gestational body mass index, parity, weight gain, and gestational diabetes, as well as the reduction in maternal smoking, which are associated with higher birth weight and preterm birth.<a class="elsevierStyleCrossRef" href="#bib0240">19</a> These frequent factors in the BRISA-PR cohort (Table 2, Supplementary Material) were exclusion criteria in the IG-21 study.<a class="elsevierStyleCrossRef" href="#bib0195">10</a>The scant birth weight divergence found in the curve of full-term pregnancies may suggest that women who reached full-term tend to be healthier and have a lower risk, with a profile similar to those included in the IG-21 study.Other possible explanations for the differences found between the BRISA-RP and IG-21 studies can be attributed to the prescriptive approach of IG-21 (populations with low risk of fetal growth impairment; the population was not selected in the BRISA-RP cohort); gestational age estimate (in the BRISA-RP cohort the GA was defined by a combination of clinical methods and estimated by the earliest USG examination; in the IG-21 study, GA was estimated early through the USG performed before the 14th week of gestation), sample size (the BRISA-RP cohort included 7702 mother-child pairs, whereas the IG-21 evaluated 20,486 NB). Overall, small samples affect the estimate of percentiles in extreme GA<a class="elsevierStyleCrossRef" href="#bib0245">20</a>; this is reflected in <a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>, where the greatest differences between the reference and the standard were observed in the extreme GA. Moreover, there was a difference in the frequency of preterm birth; IG-21 had a very low rate (5.5%), consisting mainly of late preterm deliveries (33–37 weeks gestation) and full-term low birth weight infants (3.2%), probably due to their prescriptive approach. In the BRISA-PR study, preterm birth was 13.2%, more than two-fold the IG-21, although the rate of low birth weight in full-term infants was similar (3.3%).In Latin America, there is no comparable data on the prevalence of nutritional phenotypes in newborns who were evaluated using IG-21, except in a study carried out in Argentina, where the prevalence of the SGA phenotype was 3.6% compared with a local reference and 2.0% with IG-21, quite similar to that of the present study.<a class="elsevierStyleCrossRef" href="#bib0250">21</a> A Peruvian study of newborns 3400m above sea level found no significant differences with the IG-21 standard, but the phenotypes were not evaluated.<a class="elsevierStyleCrossRef" href="#bib0255">22</a> In a study carried out in New Zealand, the proportions of SGA and LGA were 1.06% and 6.2%, respectively.<a class="elsevierStyleCrossRef" href="#bib0260">23</a>The authors of the cross-sectional NB study IG-21 admitted that the use of a single cut-off point to define growth restriction has limitations, and that assessment of the growth velocity or functional assessment of the newborn can provide better means to identify malnourished NB.<a class="elsevierStyleCrossRef" href="#bib0195">10</a>In this sense, stunting constitutes a global indicator of child well-being, reflecting social inequalities and describing specific outcomes of the neonatal period.<a class="elsevierStyleCrossRef" href="#bib0265">24</a> Stunting can be related to organic conditions and is broadly considered a cumulative and long-term process, analogous to chronic malnutrition in children, which requires exposure to one or more risk factors for several months or during pregnancy.<a class="elsevierStyleCrossRef" href="#bib0270">25</a> For this reason, recently the evaluation of this indicator in newborns has gained prominence from the perspective of the first 1000 days of life. This study incorporates, for the first time in neonatal care routine, a method for the early diagnosis of stunting that can be monitored during childhood, using the corresponding WHO Child Growth Standards.<a class="elsevierStyleCrossRef" href="#bib0190">9</a>Alternatively, it is likely that neonatal wasting reflects acute exposures in the weeks prior to delivery, a time when fat deposition is more important. Some authors, however, suggest that differences in severity, rather than the time and duration of insults, result in distinct fetal growth impairment phenotypes, with wasting representing the most severe cases.<a class="elsevierStyleCrossRef" href="#bib0275">26</a> In an earlier study, stunting affected 3.8% and wasting 3.4% of a low-risk population.<a class="elsevierStyleCrossRef" href="#bib0220">15</a>The observed prevalence rates of newborn phenotypes were relatively low, especially for SGA and waisting, as they are also lower than the cut-off points, with clinical significance suggested by the WHO.<a class="elsevierStyleCrossRef" href="#bib0160">3</a> Stunting at birth seems to have a relatively low prevalence, even in low-income countries, but it increases with gestational age (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).<a class="elsevierStyleCrossRef" href="#bib0280">27</a> A possible explanation for the lower waisting value observed in the present study (1.5%) would be elective pregnancy termination due to fetal growth restriction. This is confirmed by the 17% higher cesarean rate at 33–37 weeks than at 38–42 weeks (p<0.001, data not shown).From the point of view of clinical practice, the IG-21 standard could underestimate the frequency of full-term and post-term LGA newborns in the BRISA-RP cohort, with implications for the decline of controls and biochemical tests. On the other hand, using IG-21 would reduce the diagnosis of SGA up to full-term. Although the mean variation in length was always less than 1cm, using IG-21 would increase the diagnosis of stunting throughout pregnancy.Finally, whereas the trajectory of the 3rd percentile of the HC parallel up to week 40, the preterm NB showed a variation>1cm with the BRISA-RP reference, which may influence an overestimation of microcephaly, currently the first step in the diagnosis of Zika virus infection.It is recommended that the reference curves of each country be compared graphically and numerically with a standard (such as the IG-21) to detect adverse perinatal outcomes (such as the phenotypes used in this study) and their long-term effects.<a class="elsevierStyleCrossRefs" href="#bib0285">28,29</a> As with any international standard, local validation is required before implementation.The main strength of the study is its sample size, with relatively recent data collected from a cohort study (BRISA-RP) following stringent and standardized methods, from an unselected population of postpartum women. The study demonstrates the practical application of recommended international growth standards to estimate the prevalence of four phenotypes. However, it is limited to a single municipality, which prevents its generalization.Despite the importance of comparing local populations with standard curves, the use of both reference and standard curves for epidemiological studies still requires their validation through indicators of morbidity and mortality in newborns, as well as the occurrence of chronic non-communicable diseases throughout the life cycle.The NB of the BRISA-RP study, when compared to the IG-21 standard, are heavier, longer, and have a larger HC until they reach full-term.FundingFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP): Process No. 08/53593-0. Fundação de Apoio ao Ensino, Pesquisa e Assistência do Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (FAEPA). Institutional Scientific Initiation Grant from USP.Conflicts of interestThe authors declare no conflicts of interest." "textoCompletoSecciones" => array:1 [ "secciones" => array:11 [ 0 => array:3 [ "identificador" => "xres1378668" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objectives" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1266422" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1378667" "titulo" => "Resumo" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivos" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Método" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusões" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1266423" "titulo" => "Palavras-chave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Methods" "secciones" => array:2 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Assessed variables" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Statistical analyses" ] ] ] 6 => array:2 [ "identificador" => "sec0025" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "sec0030" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0035" "titulo" => "Funding" ] 9 => array:2 [ "identificador" => "sec0040" "titulo" => "Conflicts of interest" ] 10 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2018-10-28" "fechaAceptado" => "2019-03-11" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1266422" "palabras" => array:5 [ 0 => "Newborns" 1 => "Anthropometrics" 2 => "Birth weight" 3 => "Stunting" 4 => "Wasting" ] ] ] "pt" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palavras-chave" "identificador" => "xpalclavsec1266423" "palabras" => array:5 [ 0 => "Recém-nascidos" 1 => "Antropometria" 2 => "Peso ao nascer" 3 => "Stunting" 4 => "Waisting" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "Objectives(a) To determine the 3rd, 50th, and 97th percentiles of weight, length, and head circumference of newborns from the Ribeirão Preto BRISA cohort, according to gender and gestational age, and compare them with the Intergrowth-21st standard; (b) To estimate the small for gestational age (<3rd percentile), large for gestational age (>97th percentile), stunting (length<3rd percentile), and wasting (body mass index<3rd percentile). MethodsObservational study of a cohort of 7702 newborns between 01/01/2010 and 12/31/2010 in the city of Ribeirão Preto, SP, Brazil. The 3rd, 50th, and 97th percentiles were determined for the anthropometric measurements using fractional polynomial regression. ResultsThe weight difference between Ribeirão Preto and Intergrowth-21st was small, being more pronounced in preterm infants (mean difference between the two populations of +266g); for full-term newborns, there was a mean difference of +66g, and for post-term infants, of −113g. For length, the mean variation was always <1cm; whereas for head circumference, preterm newborns showed a variation >1cm, and full-term and post-term newborns showed a variation of <1cm. The small and large for gestational age detection rates were 2.9% and 4.3%, respectively. Stunting affected 6.5% of all newborns and wasting, 1.5%, with a predominance in girls and in full-term pregnancies; both conditions were present in 0.4% of the sample. ConclusionsNewborns from Ribeirão Preto, when compared to the Intergrowth-21 standard, are heavier, longer, and have a larger head circumference until they reach full-term." "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objectives" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] "pt" => array:3 [ "titulo" => "Resumo" "resumen" => "ObjetivosDeterminar os percentis 3, 50 e 97 de peso, comprimento e perímetro cefálico de recém-nascidos da Coorte BRISA Ribeirão Preto, segundo sexo e idade gestacional, e comparar com o padrão Intergrowth-21st; b) Estimar os fenótipos pequeno para idade gestacional ( < percentil 3), grande para idade gestacional ( > percentil 97), stunting (comprimento < percentil 3) e waisting (índice de massa corporal < percentil 3). MétodoEstudo observacional de uma coorte de 7.702 recém-nascidos entre 01/01 e 31/12/2010 na cidade de Ribeirão Preto, SP, Brasil. Os percentis 3, 50 e 97 para as medidas antropométricas foram determinados com regressão polinomial fracionária. ResultadosA diferença de peso entre Ribeirão Preto e Intergrowth-21st foi pequena, mais acentuada nos recém-nascidos pré-termo (diferença média entre as duas populações foi de + 266 gramas); para os recém-nascidos a termo a diferença média foi de + 66 gramas e para os pós-termo de -113 gramas. Para comprimento, a variação média foi sempre < 1cm; enquanto que para perímetro cefálico os recém-nascidos pré-termo apresentaram variação > 1cm e os recém-nascidos a termo e pós-termo tiveram variação < 1cm. As taxas de detecção de pequeno e grande para idade gestacional foram 2,9% e 4,3%, respectivamente. Stunting afetou 6,5% de todos os recém-nascidos e waisting 1,5%, com predomínio em meninas e em gestações a termo; ambas as condições estavam presentes em 0,4% da amostra. ConclusõesOs recém-nascidos de Ribeirão Preto, quando comparados com o padrão Intergrowth-21st, apresentam-se mais pesados, mais longos e com maior circunferência craniana até chegarem a termo." "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivos" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Método" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusões" ] ] ] ] "NotaPie" => array:2 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "Please cite this article as: Pimenta JR, Grandi C, Aragon DC, Cardoso VC. Comparison of birth weight, length, and head circumference between the BRISA-RP and Intergrowth-21st cohorts. J Pediatr (Rio J). 2020;96:511–9." ] 1 => array:2 [ "etiqueta" => "☆☆" "nota" => "Study conducted at Universidade de São Paulo (USP), Faculdade de Medicina de Ribeirão Preto (FMRP), Ribeirão Preto, SP, Brazil." ] ] "apendice" => array:1 [ 0 => array:1 [ "seccion" => array:1 [ 0 => array:4 [ "apendice" => "The following are Supplementary data to this article:<elsevierMultimedia ident="upi0005"></elsevierMultimedia>" "etiqueta" => "Appendix A" "titulo" => "Supplementary data" "identificador" => "sec0065" ] ] ] ] "multimedia" => array:5 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 4087 "Ancho" => 1500 "Tamanyo" => 174211 ] ] "descripcion" => array:1 [ "en" => "Flowchart of the study population (BRISA-RP cohort, 2010). GA, gestational age; NB, newborn." ] ] 1 => array:7 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 3665 "Ancho" => 2935 "Tamanyo" => 771650 ] ] "descripcion" => array:1 [ "en" => "The 3rd, 50th, and 97th smoothed percentiles curves (blue lines) for birth weight, birth length, and head circumference at birth according to gestational age. Empirical values are shown for each gestational week (red circles) and the actual observations (gray circles). BRISA-RP Cohort, 2010." ] ] 2 => array:7 [ "identificador" => "fig0015" "etiqueta" => "Figure 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 3659 "Ancho" => 2917 "Tamanyo" => 689861 ] ] "descripcion" => array:1 [ "en" => "Comparison of the 3rd, 50th, and 97th percentile curves of the BRISA-RP cohort with IG-21 by gestational age and gender." ] ] 3 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "NB, newborns.Stunting, length<3rd percentile of IG-21.Wasting, BMI<3rd percentile of IG-21.SGA (small for gestational age): birth weight<3rd percentile of IG-21.LGA (large for gestational age): birth weight>97th percentile of IG-21." "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Phenotype \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">n \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">% \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">95% CI \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Stunting</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Boys \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">214 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.3–6.9 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Girls \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">246 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.1–7.8 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Total \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">460 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.9–7.1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Per gestational age (weeks)</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">33–37 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">78/1208 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.1–8.0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">38–42 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">382/5887 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.9–7.2 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Wasting</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Boys \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">46 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.0–1.7 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Girls \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">56 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.2–2.0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Total \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">102 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.2–1.8 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Per gestational age (weeks)</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">33–37 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19/1208 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.0–2.4 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">38–42 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">83/5887 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.1–1.7 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">SGA</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Boys \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">93 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.1–3.2 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Girls \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">112 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.6–3.7 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Total \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">205 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.5–3.3 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Per gestational age (weeks)</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">33–37 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">35/1222 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.0–3.9 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">38–42 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">170/5899 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.5–3.3 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">LGA</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Boys \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">153 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.7–5.1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Girls \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">153 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.6–4.9 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Total \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">306 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.8–4.8 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Per gestational age (weeks)</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">33–37 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">131/1222 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9.0–12.6 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">38–42 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">175/5899 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.6–3.4 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2367357.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Newborn phenotypes according to gender and gestational age (33–42 weeks). 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Comparação de peso, comprimento e perímetro cefálico ao nascer entre Coorte BRISA-RP e Intergrowth-21st

João Roberto R. Pimentaa, Carlos Grandib, Davi C. Aragonc, Viviane Cunha Cardosoc,

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vicuca@fmrp.usp.br

Corresponding author.

a Universidade de São Paulo (USP), Faculdade de Medicina de Ribeirão Preto (FMRP), Departamento de Farmacologia, Ribeirão Preto, SP, Brazil

b Sociedade Argentina de Pediatria, Comissão de Pesquisa, Buenos Aires, Argentina

c Universidade de São Paulo (USP), Faculdade de Medicina de Ribeirão Preto (FMRP), Departamento de Puericultura e Pediatria, Ribeirão Preto, SP, Brazil

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    "titulo" => "Comparison of birth weight&#44; length&#44; and head circumference between the BRISA-RP and Intergrowth-21st cohorts"
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        "titulo" => "Compara&#231;&#227;o de peso&#44; comprimento e per&#237;metro cef&#225;lico ao nascer entre Coorte BRISA-RP e Intergrowth-21st"
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          "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Comparison of the 3rd&#44; 50th&#44; and 97th percentile curves of the BRISA-RP cohort with IG-21 by gestational age and gender&#46;</p>"
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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Intrauterine growth is understood as the result of several factors&#44; including the expression of genetic information&#44; maternal nutrition&#44;<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">1</span></a> maternal diseases such as preeclampsia&#44; socioeconomic factors&#44; and environmental factors&#44; such as hypoxia&#46;<a class="elsevierStyleCrossRef" href="#bib0155"><span class="elsevierStyleSup">2</span></a> The universally accepted indicator of fetal malnutrition is low birth weight &#40;&#60;2500<span class="elsevierStyleHsp" style=""></span>g&#41;&#44;<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">3</span></a> but it does not differentiate between stunting &#40;low length for age&#41; and wasting &#40;low body mass index &#91;BMI&#93; for age&#41;&#46; Other existing terms to describe prenatal malnutrition include&#58; small for gestational age &#40;SGA&#41;&#44; intrauterine growth restriction &#40;IUGR&#41;&#44; and placental insufficiency&#46; Traditionally&#44; the Battaglia and Lubchenco classification has been used to classify newborns &#40;NB&#41; into small&#44; adequate&#44; and large for gestational age &#40;GA&#41; in relation to the 10th and 90th percentiles regarding the weight variable&#46;<a class="elsevierStyleCrossRef" href="#bib0165"><span class="elsevierStyleSup">4</span></a> Information such as being born SGA is important from a clinical and social point of view because it shows a correlation with important outcomes&#44; such as neonatal and infant mortality&#44; low childhood growth&#44; and chronic diseases in adulthood&#46;<a class="elsevierStyleCrossRefs" href="#bib0170"><span class="elsevierStyleSup">5&#44;6</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Neonatal reference curves have been published in some countries&#44; but none of them can be used as an international standard for growth&#46;<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">7</span></a> Currently&#44; the use of these curves is disputed&#44; because they were created to be used as references for a country&#44; aiming to compare the anthropometric characteristics of NB with those of the overall population&#44; <span class="elsevierStyleItalic">i&#46;e&#46;</span>&#44; without the prescriptive nature of a standard applicable to different populations&#46;<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">8</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">The International Fetal and Newborn Growth Consortium for the 21st Century &#40;INTERGROWTH-21st&#41; is a cross-sectional&#44; multicenter&#44; and transcultural study of NB growth&#44; carried out with the same prescriptive approach and methodological design as that used for the creation of the World Health Organization &#40;WHO&#41; standard currently used for child and adolescent growth evaluation in Brazil&#46;<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">9</span></a> The INTERGROWTH-21st &#40;IG-21&#41;&#44; which allows the anthropometric analysis of NB&#44; was designed to be a &#8220;prescriptive&#8221; fetal growth pattern&#44; <span class="elsevierStyleItalic">i&#46;e&#46;</span>&#44; to be used as the basis for recommending how healthy fetuses born to healthy mothers in healthy settings &#8220;should&#8221; grow&#44; rather than a mere reference to how fetuses born in the same countries &#8220;actually grow&#8221;&#46;<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">10</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">In this context&#44; the aims of the present study were&#58; &#40;a&#41; to compare the anthropometric data &#40;weight&#44; length&#44; and head circumference&#41; of the birth cohort of Ribeir&#227;o Preto 2010 &#40;BRISA-RP&#41; with the IG-21 standard&#44; and &#40;b&#41; to estimate NB phenotypes &#40;SGA&#44; large for gestational age &#91;LGA&#93;&#44; stunting&#44; and wasting&#41; according to gender and GA&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Methods</span><p id="par0025" class="elsevierStylePara elsevierViewall">This was a cross-sectional secondary analysis with a descriptive approach of data obtained from a cohort study &#40;Brazilian Ribeir&#227;o Preto and S&#227;o Lu&#237;s Birth Cohort Studies &#8211; BRISA&#41;&#44; whose objective was to find new risk factors for preterm birth&#46;<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">11</span></a> All newborns who were alive between 01&#47;01&#47;2010 and 12&#47;31&#47;2010 in the city of Ribeir&#227;o Preto &#40;PR&#41;&#44; S&#227;o Paulo&#44; Brazil were assessed&#46; During this period&#44; 7702 newborns were evaluated&#44; equivalent to 98&#37; of hospital deliveries in the municipality&#46;</p><p id="par0030" class="elsevierStylePara elsevierViewall">Inclusion criteria were children born at hospitals&#44; to mothers living in RP&#44; whereas the exclusion criteria were twin births&#44; stillborn births&#44; those without GA defined by the adopted criteria&#44; those with no defined gender&#44; and NB who had birth weight values incompatible with gestational age<a class="elsevierStyleCrossRef" href="#bib0205"><span class="elsevierStyleSup">12</span></a> &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>&#41;&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0035" class="elsevierStylePara elsevierViewall">Data were obtained from an interview with the mothers after delivery and from information contained in the newborns&#8217; medical records&#46;</p><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Assessed variables</span><p id="par0040" class="elsevierStylePara elsevierViewall">Maternal age &#40;years&#41;&#44; ethnicity &#40;white or non-white&#41;&#44; level of schooling &#40;years&#41;&#44; marital status &#40;with or without partner&#41;&#44; occupation of the head of the family &#40;according to the classification proposed by Olsen and Frische<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">13</span></a>&#41;&#44; Brazilian economic classification criterion according to the Brazilian Association of Research Companies &#40;CCEB-ABEP&#41;&#44;<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">14</span></a> number of cigarettes smoked daily during pregnancy&#44; parity&#44; arterial hypertension &#40;prior or gestational&#41;&#44; diabetes &#40;previous or gestational&#41;&#44; body mass index &#40;BMI&#44; kg&#47;m<span class="elsevierStyleSup">2</span>&#41; before pregnancy &#40;categorized as low weight &#91;&#60;18&#46;5<span class="elsevierStyleHsp" style=""></span>kg&#47;m<span class="elsevierStyleSup">2</span>&#93;&#44; adequate weight &#91;&#8805;18&#46;5<span class="elsevierStyleHsp" style=""></span>kg&#47;m<span class="elsevierStyleSup">2</span> and &#60;25<span class="elsevierStyleHsp" style=""></span>kg&#47;m<span class="elsevierStyleSup">2</span>&#93;&#44; overweight &#91;&#8805;25<span class="elsevierStyleHsp" style=""></span>kg&#47;m<span class="elsevierStyleSup">2</span> and &#60;30<span class="elsevierStyleHsp" style=""></span>kg&#47;m<span class="elsevierStyleSup">2</span>&#93;&#44; obesity &#91;&#8805;30<span class="elsevierStyleHsp" style=""></span>kg&#47;m<span class="elsevierStyleSup">2</span>&#41;&#44; and prenatal care &#40;adequate<span class="elsevierStyleHsp" style=""></span>&#8805;<span class="elsevierStyleHsp" style=""></span>4 consultations&#41;&#46;</p><p id="par0045" class="elsevierStylePara elsevierViewall">The neonatal variables studied were gender&#44; birth weight &#40;BW&#41;&#44; birth length&#44; and head circumference &#40;HC&#41;&#46; Stunting was defined as length<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>3rd percentile&#44; wasting as BMI<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>3rd percentile&#44; SGA as birth weight<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>3rd percentile&#44; and LGA as birth weight<span class="elsevierStyleHsp" style=""></span>&#62;<span class="elsevierStyleHsp" style=""></span>97th percentile of the IG-21 study&#46;<a class="elsevierStyleCrossRefs" href="#bib0195"><span class="elsevierStyleSup">10&#44;15</span></a></p><p id="par0050" class="elsevierStylePara elsevierViewall">GA was estimated based on date of the last menstrual period &#40;LMP&#41; and information from the earliest ultrasonography &#40;USG&#41; examination&#46; A margin of error of &#177;7 days was calculated for the date found of the first USG&#46;<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">16</span></a></p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Statistical analyses</span><p id="par0055" class="elsevierStylePara elsevierViewall">The descriptive statistics included the mean value&#44; proportion&#44; standard deviation &#40;SD&#41;&#44; and 95&#37; confidence interval &#40;95&#37; CI&#41;&#46; Fractional polynomials were used to fit the models of the three anthropometric measurements &#40;BW&#44; length&#44; and HC&#41;&#46; The generalized additive models for location&#44; scale&#44; and shape &#40;GAMLSS&#41; provide the option of different distributions other than normal &#40;bias distributions and kurtosis&#41;&#44; as well as the modeling of other parameters of a distribution that determines scale and shape by using fractional polynomials&#46;<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">17</span></a> In all cases&#44; the technique of fractional polynomial smoothing by gender was applied for the 3rd&#44; 50th&#44; and 97th percentiles&#46; For comparison of the curves with the IG-21 standard&#44; the lower limit of 33<span class="elsevierStyleSup">&#43;0</span> weeks was adopted&#44; given that the IG-21 has a very questionable curve below 33 weeks considering the small number of newborns included&#46;</p><p id="par0060" class="elsevierStylePara elsevierViewall">According to the IG-21 study&#44; the smoothed percentiles of weight&#44; length&#44; and HC for the newborns are shown at <span class="elsevierStyleItalic">exact</span> weeks of gestational age only to avoid the publication of long tables for each day of pregnancy&#46; For instance&#44; the exact GA for the 36th week value is 36 weeks plus 0 days&#46;<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">18</span></a> All models and goodness-of-fit evaluations were performed using the statistical software R &#40;R Foundation for Statistical Computing&#44; Vienna&#44; Austria&#41; using GAMLSS support&#46; All graphs were produced using R software&#46;</p><p id="par0065" class="elsevierStylePara elsevierViewall">The project was approved by the Research Ethics Committee of the HCFMRP &#40;process no&#46; 11157&#47;2008&#41;&#46; All mothers who agreed to participate in the study signed the informed consent&#46;</p></span></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Results</span><p id="par0070" class="elsevierStylePara elsevierViewall">The mean maternal age was 27 years &#40;SD<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>6&#46;2&#41;&#44; and the percentage of young and old mothers was similar&#46; Most of the population self-reported as white&#44; approximately half of the mothers had a level of schooling between 9 and 11 years&#44; and the vast majority of the mothers declared having a partner&#46; In most families the occupation of the head of the family was unskilled or semi-skilled manual worker&#46; The upper and intermediate social classes showed a similar representation &#40;Table 1&#44; Supplementary Material&#41;&#46;</p><p id="par0075" class="elsevierStylePara elsevierViewall">About 1&#47;3 of the mothers were overweight and obese&#44; slightly more than 10&#37; said they were smokers&#44; and about 13&#37; of the mothers were hypertensive and 6&#37; were diabetic&#46;Most of the mothers were primiparous and only 2 &#37; of pregnant women presented inadequate prenatal care &#40;Table 2&#44; Supplementary Material&#41;&#46; The distribution by gender was equivalent&#46; Preterm births represented 13&#37; and almost 8&#37; of infants had low birth weight&#46; The SGA rate was 2&#46;9&#37;&#44; while the LGA rate was 4&#46;3&#37;&#44; with an inverse association with GA&#46; Stunting affected 6&#46;5&#37; of the sample and wasting&#44; 1&#46;5&#37; &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#44; with a predominance of girls and full-term pregnancies&#59; both conditions were present in 0&#46;4&#37; of the sample&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0080" class="elsevierStylePara elsevierViewall">Fig&#46; 1 &#40;Supplementary Material&#41; shows the BRISA-RP histograms of birth weight according to gender&#46; The distributions are very similar&#44; although that of the girls shows greater kurtosis&#46;</p><p id="par0085" class="elsevierStylePara elsevierViewall">Distribution curves of BW&#44; length&#44; and HC of the BRISA-RP cohort were constructed&#44; according to GA and gender&#46; <a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a> shows the individual values &#40;observed values&#41; and the smoothed 3rd&#44; 50th&#44; and 97th percentiles &#40;estimated values&#41;&#44; using fractional polynomials&#46; Few outliers were observed after 37<span class="elsevierStyleSup">&#43;0</span> weeks of GA for BW and almost identical values were observed for length and HC at birth&#46;</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0090" class="elsevierStylePara elsevierViewall">The curves of the 3rd&#44; 50th&#44; and 97th percentiles of the BRISA-RP cohort were compared with IG-21 by GA and gender&#46; For weight in both genders&#44; it was observed that between weeks 33<span class="elsevierStyleSup">&#43;0</span> and 39<span class="elsevierStyleSup">&#43;6</span>&#44; the 50th and 97th percentiles of the BRISA-RP cohort were higher than IG-21&#59; then both percentiles cross the IG-21 pattern and decrease up to week 42<span class="elsevierStyleSup">&#43;6</span>&#46; For the 3rd percentile&#44; the behavior is similar&#44; but smoother &#40;<a class="elsevierStyleCrossRef" href="#fig0015">Fig&#46; 3</a>&#41;&#46; In numerical terms&#44; the divergence between BRISA-RP and IG-21 is more pronounced among preterm &#40;33&#8211;36 weeks&#41; NB&#44; in which the mean difference between the two populations is &#43;263<span class="elsevierStyleHsp" style=""></span>g for boys and &#43;270<span class="elsevierStyleHsp" style=""></span>g for girls&#59; in full-term infants &#40;37&#8211;40 weeks&#41;&#44; the mean difference was &#43;81<span class="elsevierStyleHsp" style=""></span>g for boys and &#43;52<span class="elsevierStyleHsp" style=""></span>g for girls&#59; and for post-term &#40;41 and 42 weeks&#41; NB&#44; the mean difference was &#8722;120<span class="elsevierStyleHsp" style=""></span>g for boys and &#8722;106<span class="elsevierStyleHsp" style=""></span>g for girls &#40;Table 3&#44; Supplementary Material&#41;&#46;</p><elsevierMultimedia ident="fig0015"></elsevierMultimedia><p id="par0095" class="elsevierStylePara elsevierViewall">Regarding length&#44; the growth curve &#40;50th and 97th percentiles&#41; increased steadily from 33 weeks gestation to 37&#8211;39 weeks in the BRISA-RP cohort and then crossed the IG-21 curve&#46; The 3rd percentile always remained below the standard &#40;<a class="elsevierStyleCrossRef" href="#fig0015">Fig&#46; 3</a>&#41;&#46; Numerically&#44; the mean variation was always<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>1<span class="elsevierStyleHsp" style=""></span>cm in both boys and girls &#40;Table 4&#44; Supplementary Material&#41;&#46;</p><p id="par0100" class="elsevierStylePara elsevierViewall">Finally&#44; the HC for both genders showed a large gap between the 50th and 97th percentiles of the BRISA-PR Cohort and the IG-21 curve until reaching the post-term period&#59; however&#44; the 3rd percentile trajectory was parallel with the IG-21 standard until week 39&#44; when it crossed it &#40;<a class="elsevierStyleCrossRef" href="#fig0015">Fig&#46; 3</a>&#41;&#46; Regarding the numerical differences&#44; it was observed that preterm NB showed a variation<span class="elsevierStyleHsp" style=""></span>&#62;<span class="elsevierStyleHsp" style=""></span>1<span class="elsevierStyleHsp" style=""></span>cm &#40;1&#46;33<span class="elsevierStyleHsp" style=""></span>cm for boys and 1&#46;39<span class="elsevierStyleHsp" style=""></span>cm for girls&#41;&#44; while for full-term and post-term NB&#44; the variation was<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>1<span class="elsevierStyleHsp" style=""></span>cm &#40;Table 5&#44; Supplementary Material&#41;&#46;</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0091">Discussion</span><p id="par0105" class="elsevierStylePara elsevierViewall">To the best of the authors&#8217; knowledge&#44; this is the first Brazilian study that compared a cohort at birth with the international standard IG-21 regarding the size of the newborn for gestational age and gender&#46;</p><p id="par0110" class="elsevierStylePara elsevierViewall">Of the 7185 single live births&#44; those below the 3rd percentile &#40;SGA&#41; and above the 97th percentile &#40;LGA&#41; of the IG-21 standard for birth weight had detection rates of 2&#46;9&#37; and 4&#46;3&#37;&#44; respectively&#46; For stunting and wasting&#44; the values were 6&#46;5&#37; and 1&#46;5&#37;&#44; respectively&#46;</p><p id="par0115" class="elsevierStylePara elsevierViewall">Adjusted percentiles were calculated based on individual data from more than 7000 infants using fractional polynomial regression and data were reported according to full weeks of gestation as smoothed percentiles &#40;<a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#41;&#44; which were consistent with the raw data&#44; increasing the confidence in the curves&#46; SGA was defined as birth weight for age and gender<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>3rd percentile &#40;instead of the more frequently used 10th percentile&#41;&#44; indicating a severe insult&#59; this eliminates the chance of erroneous inclusion of a normal newborn into the lowest birth weight distribution&#46;</p><p id="par0120" class="elsevierStylePara elsevierViewall">It is evident that the birth weight curves of the BRISA-RP cohort and the IG-21 standard&#44; although similar in the full-term period&#44; are very different at the earliest gestational ages&#46; While at the 40 weeks of GA there was no difference in the medians&#44; at 33 weeks gestation the median BRISA-RP was almost 300<span class="elsevierStyleHsp" style=""></span>g higher&#46; This makes the prevalence of SGA in preterm births higher in the BRISA-PR cohort than in the standard curve&#46; The probable reasons for a higher frequency of LGA in the BRISA-PR cohort were increases in the maternal pre-gestational body mass index&#44; parity&#44; weight gain&#44; and gestational diabetes&#44; as well as the reduction in maternal smoking&#44; which are associated with higher birth weight and preterm birth&#46;<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">19</span></a> These frequent factors in the BRISA-PR cohort &#40;Table 2&#44; Supplementary Material&#41; were exclusion criteria in the IG-21 study&#46;<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">10</span></a></p><p id="par0125" class="elsevierStylePara elsevierViewall">The scant birth weight divergence found in the curve of full-term pregnancies may suggest that women who reached full-term tend to be healthier and have a lower risk&#44; with a profile similar to those included in the IG-21 study&#46;</p><p id="par0130" class="elsevierStylePara elsevierViewall">Other possible explanations for the differences found between the BRISA-RP and IG-21 studies can be attributed to the prescriptive approach of IG-21 &#40;populations with low risk of fetal growth impairment&#59; the population was not selected in the BRISA-RP cohort&#41;&#59; gestational age estimate &#40;in the BRISA-RP cohort the GA was defined by a combination of clinical methods and estimated by the earliest USG examination&#59; in the IG-21 study&#44; GA was estimated early through the USG performed before the 14th week of gestation&#41;&#44; sample size &#40;the BRISA-RP cohort included 7702 mother-child pairs&#44; whereas the IG-21 evaluated 20&#44;486 NB&#41;&#46; Overall&#44; small samples affect the estimate of percentiles in extreme GA<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">20</span></a>&#59; this is reflected in <a class="elsevierStyleCrossRef" href="#fig0015">Fig&#46; 3</a>&#44; where the greatest differences between the reference and the standard were observed in the extreme GA&#46; Moreover&#44; there was a difference in the frequency of preterm birth&#59; IG-21 had a very low rate &#40;5&#46;5&#37;&#41;&#44; consisting mainly of late preterm deliveries &#40;33&#8211;37 weeks gestation&#41; and full-term low birth weight infants &#40;3&#46;2&#37;&#41;&#44; probably due to their prescriptive approach&#46; In the BRISA-PR study&#44; preterm birth was 13&#46;2&#37;&#44; more than two-fold the IG-21&#44; although the rate of low birth weight in full-term infants was similar &#40;3&#46;3&#37;&#41;&#46;</p><p id="par0135" class="elsevierStylePara elsevierViewall">In Latin America&#44; there is no comparable data on the prevalence of nutritional phenotypes in newborns who were evaluated using IG-21&#44; except in a study carried out in Argentina&#44; where the prevalence of the SGA phenotype was 3&#46;6&#37; compared with a local reference and 2&#46;0&#37; with IG-21&#44; quite similar to that of the present study&#46;<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">21</span></a> A Peruvian study of newborns 3400<span class="elsevierStyleHsp" style=""></span>m above sea level found no significant differences with the IG-21 standard&#44; but the phenotypes were not evaluated&#46;<a class="elsevierStyleCrossRef" href="#bib0255"><span class="elsevierStyleSup">22</span></a> In a study carried out in New Zealand&#44; the proportions of SGA and LGA were 1&#46;06&#37; and 6&#46;2&#37;&#44; respectively&#46;<a class="elsevierStyleCrossRef" href="#bib0260"><span class="elsevierStyleSup">23</span></a></p><p id="par0140" class="elsevierStylePara elsevierViewall">The authors of the cross-sectional NB study IG-21 admitted that the use of a single cut-off point to define growth restriction has limitations&#44; and that assessment of the growth velocity or functional assessment of the newborn can provide better means to identify malnourished NB&#46;<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">10</span></a></p><p id="par0145" class="elsevierStylePara elsevierViewall">In this sense&#44; stunting constitutes a global indicator of child well-being&#44; reflecting social inequalities and describing specific outcomes of the neonatal period&#46;<a class="elsevierStyleCrossRef" href="#bib0265"><span class="elsevierStyleSup">24</span></a> Stunting can be related to organic conditions and is broadly considered a cumulative and long-term process&#44; analogous to chronic malnutrition in children&#44; which requires exposure to one or more risk factors for several months or during pregnancy&#46;<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">25</span></a> For this reason&#44; recently the evaluation of this indicator in newborns has gained prominence from the perspective of the first 1000 days of life&#46; This study incorporates&#44; for the first time in neonatal care routine&#44; a method for the early diagnosis of stunting that can be monitored during childhood&#44; using the corresponding WHO Child Growth Standards&#46;<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">9</span></a></p><p id="par0150" class="elsevierStylePara elsevierViewall">Alternatively&#44; it is likely that neonatal wasting reflects acute exposures in the weeks prior to delivery&#44; a time when fat deposition is more important&#46; Some authors&#44; however&#44; suggest that differences in severity&#44; rather than the time and duration of insults&#44; result in distinct fetal growth impairment phenotypes&#44; with wasting representing the most severe cases&#46;<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">26</span></a> In an earlier study&#44; stunting affected 3&#46;8&#37; and wasting 3&#46;4&#37; of a low-risk population&#46;<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">15</span></a></p><p id="par0155" class="elsevierStylePara elsevierViewall">The observed prevalence rates of newborn phenotypes were relatively low&#44; especially for SGA and waisting&#44; as they are also lower than the cut-off points&#44; with clinical significance suggested by the WHO&#46;<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">3</span></a> Stunting at birth seems to have a relatively low prevalence&#44; even in low-income countries&#44; but it increases with gestational age &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0280"><span class="elsevierStyleSup">27</span></a> A possible explanation for the lower waisting value observed in the present study &#40;1&#46;5&#37;&#41; would be elective pregnancy termination due to fetal growth restriction&#46; This is confirmed by the 17&#37; higher cesarean rate at 33&#8211;37 weeks than at 38&#8211;42 weeks &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#44; data not shown&#41;&#46;</p><p id="par0160" class="elsevierStylePara elsevierViewall">From the point of view of clinical practice&#44; the IG-21 standard could underestimate the frequency of full-term and post-term LGA newborns in the BRISA-RP cohort&#44; with implications for the decline of controls and biochemical tests&#46; On the other hand&#44; using IG-21 would reduce the diagnosis of SGA up to full-term&#46; Although the mean variation in length was always less than 1<span class="elsevierStyleHsp" style=""></span>cm&#44; using IG-21 would increase the diagnosis of stunting throughout pregnancy&#46;</p><p id="par0165" class="elsevierStylePara elsevierViewall">Finally&#44; whereas the trajectory of the 3rd percentile of the HC parallel up to week 40&#44; the preterm NB showed a variation<span class="elsevierStyleHsp" style=""></span>&#62;<span class="elsevierStyleHsp" style=""></span>1<span class="elsevierStyleHsp" style=""></span>cm with the BRISA-RP reference&#44; which may influence an overestimation of microcephaly&#44; currently the first step in the diagnosis of Zika virus infection&#46;</p><p id="par0170" class="elsevierStylePara elsevierViewall">It is recommended that the reference curves of each country be compared graphically and numerically with a standard &#40;such as the IG-21&#41; to detect adverse perinatal outcomes &#40;such as the phenotypes used in this study&#41; and their long-term effects&#46;<a class="elsevierStyleCrossRefs" href="#bib0285"><span class="elsevierStyleSup">28&#44;29</span></a> As with any international standard&#44; local validation is required before implementation&#46;</p><p id="par0175" class="elsevierStylePara elsevierViewall">The main strength of the study is its sample size&#44; with relatively recent data collected from a cohort study &#40;BRISA-RP&#41; following stringent and standardized methods&#44; from an unselected population of postpartum women&#46; The study demonstrates the practical application of recommended international growth standards to estimate the prevalence of four phenotypes&#46; However&#44; it is limited to a single municipality&#44; which prevents its generalization&#46;</p><p id="par0180" class="elsevierStylePara elsevierViewall">Despite the importance of comparing local populations with standard curves&#44; the use of both reference and standard curves for epidemiological studies still requires their validation through indicators of morbidity and mortality in newborns&#44; as well as the occurrence of chronic non-communicable diseases throughout the life cycle&#46;</p><p id="par0185" class="elsevierStylePara elsevierViewall">The NB of the BRISA-RP study&#44; when compared to the IG-21 standard&#44; are heavier&#44; longer&#44; and have a larger HC until they reach full-term&#46;</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0096">Funding</span><p id="par0190" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleGrantSponsor" id="gs1">Funda&#231;&#227;o de Amparo &#224; Pesquisa do Estado de S&#227;o Paulo &#40;FAPESP&#41;</span>&#58; Process No&#46; 08&#47;53593-0&#46; <span class="elsevierStyleGrantSponsor" id="gs2">Funda&#231;&#227;o de Apoio ao Ensino&#44; Pesquisa e Assist&#234;ncia do Hospital das Cl&#237;nicas da Faculdade de Medicina de Ribeir&#227;o Preto da Universidade de S&#227;o Paulo &#40;FAEPA&#41;</span>&#46; Institutional Scientific Initiation Grant from USP&#46;</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Conflicts of interest</span><p id="par0195" class="elsevierStylePara elsevierViewall">The authors declare no conflicts of interest&#46;</p></span></span>"
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    "fechaAceptado" => "2019-03-11"
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          "clase" => "keyword"
          "titulo" => "Keywords"
          "identificador" => "xpalclavsec1266422"
          "palabras" => array:5 [
            0 => "Newborns"
            1 => "Anthropometrics"
            2 => "Birth weight"
            3 => "Stunting"
            4 => "Wasting"
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          "palabras" => array:5 [
            0 => "Rec&#233;m-nascidos"
            1 => "Antropometria"
            2 => "Peso ao nascer"
            3 => "<span class="elsevierStyleItalic">Stunting</span>"
            4 => "<span class="elsevierStyleItalic">Waisting</span>"
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        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Objectives</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">&#40;a&#41; To determine the 3rd&#44; 50th&#44; and 97th percentiles of weight&#44; length&#44; and head circumference of newborns from the Ribeir&#227;o Preto BRISA cohort&#44; according to gender and gestational age&#44; and compare them with the Intergrowth-21st standard&#59; &#40;b&#41; To estimate the small for gestational age &#40;<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>3rd percentile&#41;&#44; large for gestational age &#40;<span class="elsevierStyleHsp" style=""></span>&#62;<span class="elsevierStyleHsp" style=""></span>97th percentile&#41;&#44; stunting &#40;length<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>3rd percentile&#41;&#44; and wasting &#40;body mass index<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>3rd percentile&#41;&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Observational study of a cohort of 7702 newborns between 01&#47;01&#47;2010 and 12&#47;31&#47;2010 in the city of Ribeir&#227;o Preto&#44; SP&#44; Brazil&#46; The 3rd&#44; 50th&#44; and 97th percentiles were determined for the anthropometric measurements using fractional polynomial regression&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">The weight difference between Ribeir&#227;o Preto and Intergrowth-21st was small&#44; being more pronounced in preterm infants &#40;mean difference between the two populations of &#43;266<span class="elsevierStyleHsp" style=""></span>g&#41;&#59; for full-term newborns&#44; there was a mean difference of &#43;66<span class="elsevierStyleHsp" style=""></span>g&#44; and for post-term infants&#44; of &#8722;113<span class="elsevierStyleHsp" style=""></span>g&#46; For length&#44; the mean variation was always &#60;1<span class="elsevierStyleHsp" style=""></span>cm&#59; whereas for head circumference&#44; preterm newborns showed a variation &#62;1<span class="elsevierStyleHsp" style=""></span>cm&#44; and full-term and post-term newborns showed a variation of &#60;1<span class="elsevierStyleHsp" style=""></span>cm&#46; The small and large for gestational age detection rates were 2&#46;9&#37; and 4&#46;3&#37;&#44; respectively&#46; Stunting affected 6&#46;5&#37; of all newborns and wasting&#44; 1&#46;5&#37;&#44; with a predominance in girls and in full-term pregnancies&#59; both conditions were present in 0&#46;4&#37; of the sample&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Newborns from Ribeir&#227;o Preto&#44; when compared to the Intergrowth-21 standard&#44; are heavier&#44; longer&#44; and have a larger head circumference until they reach full-term&#46;</p></span>"
        "secciones" => array:4 [
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        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Objetivos</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Determinar os percentis 3&#44; 50 e 97 de peso&#44; comprimento e per&#237;metro cef&#225;lico de rec&#233;m-nascidos da Coorte BRISA Ribeir&#227;o Preto&#44; segundo sexo e idade gestacional&#44; e comparar com o padr&#227;o Intergrowth-21st&#59; b&#41; Estimar os fen&#243;tipos pequeno para idade gestacional &#40; &#60; percentil 3&#41;&#44; grande para idade gestacional &#40; &#62; percentil 97&#41;&#44; <span class="elsevierStyleItalic">stunting</span> &#40;comprimento &#60; percentil 3&#41; e <span class="elsevierStyleItalic">waisting</span> &#40;&#237;ndice de massa corporal &#60; percentil 3&#41;&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">M&#233;todo</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Estudo observacional de uma coorte de 7&#46;702 rec&#233;m-nascidos entre 01&#47;01 e 31&#47;12&#47;2010 na cidade de Ribeir&#227;o Preto&#44; SP&#44; Brasil&#46; Os percentis 3&#44; 50 e 97 para as medidas antropom&#233;tricas foram determinados com regress&#227;o polinomial fracion&#225;ria&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">A diferen&#231;a de peso entre Ribeir&#227;o Preto e Intergrowth-21st foi pequena&#44; mais acentuada nos rec&#233;m-nascidos pr&#233;-termo &#40;diferen&#231;a m&#233;dia entre as duas popula&#231;&#245;es foi de &#43; 266 gramas&#41;&#59; para os rec&#233;m-nascidos a termo a diferen&#231;a m&#233;dia foi de &#43; 66 gramas e para os p&#243;s-termo de -113 gramas&#46; Para comprimento&#44; a varia&#231;&#227;o m&#233;dia foi sempre &#60; 1<span class="elsevierStyleHsp" style=""></span>cm&#59; enquanto que para per&#237;metro cef&#225;lico os rec&#233;m-nascidos pr&#233;-termo apresentaram varia&#231;&#227;o &#62; 1<span class="elsevierStyleHsp" style=""></span>cm e os rec&#233;m-nascidos a termo e p&#243;s-termo tiveram varia&#231;&#227;o &#60; 1<span class="elsevierStyleHsp" style=""></span>cm&#46; As taxas de detec&#231;&#227;o de pequeno e grande para idade gestacional foram 2&#44;9&#37; e 4&#44;3&#37;&#44; respectivamente&#46; <span class="elsevierStyleItalic">Stunting</span> afetou 6&#44;5&#37; de todos os rec&#233;m-nascidos e <span class="elsevierStyleItalic">waisting</span> 1&#44;5&#37;&#44; com predom&#237;nio em meninas e em gesta&#231;&#245;es a termo&#59; ambas as condi&#231;&#245;es estavam presentes em 0&#44;4&#37; da amostra&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclus&#245;es</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Os rec&#233;m-nascidos de Ribeir&#227;o Preto&#44; quando comparados com o padr&#227;o Intergrowth-21st&#44; apresentam-se mais pesados&#44; mais longos e com maior circunfer&#234;ncia craniana at&#233; chegarem a termo&#46;</p></span>"
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        "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Please cite this article as&#58; Pimenta JR&#44; Grandi C&#44; Aragon DC&#44; Cardoso VC&#46; Comparison of birth weight&#44; length&#44; and head circumference between the BRISA-RP and Intergrowth-21st cohorts&#46; J Pediatr &#40;Rio J&#41;&#46; 2020&#59;96&#58;511&#8211;9&#46;</p>"
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        "nota" => "<p class="elsevierStyleNotepara" id="npar0010">Study conducted at Universidade de S&#227;o Paulo &#40;USP&#41;&#44; Faculdade de Medicina de Ribeir&#227;o Preto &#40;FMRP&#41;&#44; Ribeir&#227;o Preto&#44; SP&#44; Brazil&#46;</p>"
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            "apendice" => "<p id="par0305" class="elsevierStylePara elsevierViewall">The following are Supplementary data to this article&#58;<elsevierMultimedia ident="upi0005"></elsevierMultimedia></p>"
            "etiqueta" => "Appendix A"
            "titulo" => "Supplementary data"
            "identificador" => "sec0065"
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          "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Flowchart of the study population &#40;BRISA-RP cohort&#44; 2010&#41;&#46; GA&#44; gestational age&#59; NB&#44; newborn&#46;</p>"
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          "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">The 3rd&#44; 50th&#44; and 97th smoothed percentiles curves &#40;blue lines&#41; for birth weight&#44; birth length&#44; and head circumference at birth according to gestational age&#46; Empirical values are shown for each gestational week &#40;red circles&#41; and the actual observations &#40;gray circles&#41;&#46; BRISA-RP Cohort&#44; 2010&#46;</p>"
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>Total&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">205&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t  " colspan="4" align="left" valign="\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">33&#8211;37</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">35&#47;1222&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">2&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">2&#46;0&#8211;3&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">38&#8211;42</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">170&#47;5899&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">2&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">2&#46;5&#8211;3&#46;3&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">153&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t">153&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">306&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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Article information

ISSN: 00217557
Original language: English

DOI:10.1016/j.jped.2019.03.003

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Year/Month	Html	Pdf	Total

2024 November	9	6	15
2024 October	38	44	82
2024 September	56	41	97
2024 August	54	66	120
2024 July	63	74	137
2024 June	37	37	74
2024 May	35	27	62
2024 April	44	37	81
2024 March	27	28	55
2024 February	26	29	55
2024 January	18	25	43
2023 December	42	33	75
2023 November	33	36	69
2023 October	36	33	69
2023 September	32	38	70
2023 August	24	15	39
2023 July	29	9	38
2023 June	25	19	44
2023 May	39	21	60
2023 April	37	29	66
2023 March	77	43	120
2023 February	43	27	70
2023 January	61	25	86
2022 December	63	29	92
2022 November	37	26	63
2022 October	65	35	100
2022 September	36	40	76
2022 August	49	36	85
2022 July	40	36	76
2022 June	40	34	74
2022 May	41	28	69
2022 April	62	35	97
2022 March	53	47	100
2022 February	28	34	62
2022 January	51	21	72
2021 December	51	18	69
2021 November	37	21	58
2021 October	54	21	75
2021 September	32	9	41
2021 August	31	10	41
2021 July	25	8	33
2021 June	37	17	54
2021 May	38	15	53
2021 April	86	53	139
2021 March	72	17	89
2021 February	47	28	75
2021 January	39	18	57
2020 December	45	4	49
2020 November	51	15	66
2020 October	61	8	69
2020 September	29	17	46
2020 August	68	16	84
2020 July	13	7	20
2020 June	14	9	23
2020 May	19	13	32
2020 April	19	14	33
2020 March	15	5	20
2020 February	35	10	45
2020 January	22	10	32
2019 December	17	12	29
2019 November	5	6	11
2019 October	15	11	26
2019 September	23	7	30
2019 August	19	8	27
2019 July	11	15	26
2019 June	10	12	22

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