Neck circumference cutoff points to identify excess android fat

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Viçosa, MG, 2015. 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"apellidos" => "Novaes" ] ] "afiliaciones" => array:1 [ 0 => array:2 [ "entidad" => "Universidade Federal de Viçosa (UFV), Departamento de Nutrição e Saúde, Viçosa, MG, Brasil" "identificador" => "aff0005" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Autor para correspondência." ] ] ] ] "titulosAlternativos" => array:1 [ "pt" => array:1 [ "titulo" => "Pontos de corte do perímetro do pescoço para identificar o excesso de gordura androide" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figura 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1613 "Ancho" => 2918 "Tamanyo" => 316689 ] ] "descripcion" => array:1 [ "pt" => "Áreas abaixo da curva Receiver Operating Characteristic (ROC) e pontos de corte do perímetro do pescoço com melhores valores de sensibilidade, especificidade e valores preditivos para excesso de gordura androide, de acordo com o sexo. Viçosa, MG, 2015. AUC, area under the curve; IC95%, intervalo de confiança de 95%; S, sensibilidade; E, especificidade; VPP, valor preditivo positivo; VPN, valor preditivo negativo." ] ] ] "textoCompleto" => "IntroduçãoA obesidade infantil é considerada um problema de saúde pública mundial, por estar associada a diferentes comorbidades, tais como dislipidemias, diabetes mellitus tipo 2 e hipertensão arterial.<a class="elsevierStyleCrossRef" href="#bib0155">1</a> No Brasil, a Pesquisa de Orçamentos Familiares (POF 2008‐2009) indicou a presença de obesidade em 14,3% das crianças de cinco a nove anos, enquanto que 33,5% apresentam excesso de peso.<a class="elsevierStyleCrossRef" href="#bib0160">2</a> Entretanto, é importante considerar a distribuição de gordura corporal, visto que exerce um papel fundamental no desenvolvimento do risco cardiometabólico.<a class="elsevierStyleCrossRef" href="#bib0165">3</a>Existem diferentes técnicas para avaliar a adiposidade corporal, a absorciometria de raios X de dupla energia (DXA) é considerada um método referência para avaliar a adiposidade central em crianças de todas as idades, pois estima a quantidade de gordura na região androide.<a class="elsevierStyleCrossRef" href="#bib0170">4</a> No entanto, sua aplicação em estudos epidemiológicos e na prática clínica também é limitada por apresentar custo elevado e execução complexa, são necessários métodos simples e menos dispendiosos.Nesse aspecto, o perímetro do pescoço (PP) tem sido proposto como uma ferramenta útil para identificar indivíduos jovens com excesso de peso e risco cardiometabólico por ser um método simples, de baixo custo e ter uma menor variação ao longo do dia comparado ao perímetro da cintura.<a class="elsevierStyleCrossRef" href="#bib0175">5</a> No entanto, até o momento, não foram encontrados estudos na literatura que avaliaram a associação e a capacidade do PP de identificar o excesso de adiposidade central estimada por um método referência, como a gordura na região androide determinada pelo DXA.A ausência da definição de pontos de corte específicos de PP para crianças brasileiras pode ser uma limitação para seu uso rotineiro. Na literatura, segundo o nosso conhecimento, encontra‐se apenas um estudo de delineamento transversal com adolescentes brasileiros matriculados em escolas públicas do município de São Paulo‐SP que propôs pontos de corte de PP para identificar sobrepeso e obesidade.<a class="elsevierStyleCrossRef" href="#bib0180">6</a> Diante disso, são escassos os estudos com essa abordagem em idades mais precoces.Assim, o objetivo deste estudo foi: 1) avaliar a capacidade do PP de identificar o excesso de gordura androide; 2) propor pontos de corte de PP para determinar o excesso de gordura androide em crianças brasileiras.MétodosPopulação e delineamento do estudoEstudo transversal feito com amostra representativa de crianças de oito e nove anos, matriculadas em escolas públicas e privadas da área urbana do município de Viçosa‐MG, de maio a dezembro de 2015. O município de Viçosa fica na Zona da Mata Mineira, a 227km da capital Belo Horizonte. De acordo com o Censo 2010, Viçosa apresenta uma extensão territorial de 299 km2 e 72.244 habitantes, 93,2% residem em área urbana. O Produto Interno Bruto (PIB) per capita é de R$ 19.391,08.<a class="elsevierStyleCrossRef" href="#bib0185">7</a>Os participantes deste estudo foram provenientes da Pesquisa de Avaliação da Saúde do Escolar (PASE), investigação transversal que teve o objetivo de avaliar a saúde cardiovascular desse público infantil no município de Viçosa.<a class="elsevierStyleCrossRef" href="#bib0190">8</a> Em 2015, o município contava com 17 escolas públicas e sete particulares na área urbana que atendiam crianças de oito e nove anos, total de 1.464 crianças matriculadas.Cálculo amostral e processo de amostragemO cálculo amostral foi feito no software Epi Info (versão 7.2; Atlanta, GA), considerando o número total de estudantes de oito e nove anos em 2015 (n=1.464), prevalência de 10,7% de obesidade,<a class="elsevierStyleCrossRef" href="#bib0195">9</a> erro tolerado de 3%, nível de confiança de 95% e acréscimo de 20% para cobertura de perdas, total de 384 crianças a serem estudadas.As crianças foram selecionadas por amostragem aleatória estratificada, a amostra de cada escola atingiu a proporcionalidade dos alunos matriculados por idade e sexo. A seleção de crianças foi feita por sorteio aleatório simples até que o número necessário para cada escola fosse alcançado.Após a seleção, fez‐se contato telefônico com os responsáveis pelas crianças, as quais foram convidadas a participar do estudo. Foram explicados os objetivos e a metodologia do estudo e foi agendado o primeiro encontro, no qual, após explicação de cada etapa aos responsáveis, aqueles que concordaram em participar assinaram o Termo de Consentimento Livre e Esclarecido (TCLE).Não foram incluídas crianças que apresentassem algum problema de saúde que alterasse o estado nutricional ou a composição corporal (deficiências físicas, cognitivas ou múltiplas, distúrbios da tireoide etc.), bem como em uso crônico de medicamentos que interferissem no metabolismo da glicose e/ou lipídios (corticosteroides, estatinas, hipoglicemiantes etc.) e em uso de suplementos vitamínicos ou minerais no decorrer da pesquisa ou nos últimos três meses (suplementação de vitamina D e zinco). E ainda nos casos de impossibilidade de contato com os pais ou responsável após três tentativas.Foi feito em fevereiro de 2015 um estudo‐piloto com 10% da amostra, que incluiu crianças de oito e nove anos matriculadas em uma escola pública, selecionada de forma aleatória, as quais não fizeram parte da amostra final do estudo. Por meio do estudo piloto, foi possível testar a aplicação dos questionários.Dados demográficos, socioeconômicos e de estilo de vidaFoi aplicado um questionário semiestruturado com informações socioeconômicas e demográficas, como idade, sexo, tipo de escola (pública ou privada) e renda per capita (categorizada de acordo com a mediana da amostra total, equivalente a R$ 500,00).Um questionário sobre estilo de vida foi aplicado para estimar o tempo de tela em horas por dia (tempo gasto sentado por longos períodos na frente da televisão, videogame ou computador). O comportamento sedentário foi classificado como tempo de tela maior do que duas horas/dia.<a class="elsevierStyleCrossRef" href="#bib0200">10</a>Antropometria e composição corporalA coleta de dados foi feita em ambiente apropriado por um membro da equipe treinado, com os voluntários sem calçados e com roupas leves. O peso foi aferido em balança digital eletrônica, com capacidade de 150kg e precisão de 0,1kg (Tanita® Modelo Ironman BC 553, Tanita Corporation of America Inc., Artlington Heights, USA) e a estatura foi determinada com um estadiômetro, dividido em centímetros e subdividido em milímetros (Alturexata®, Belo Horizonte, Brasil).Com os dados de peso e estatura obtidos, foi calculado o índice de massa corporal (IMC) e para a classificação do estado nutricional das crianças, foram usados os pontos de corte de IMC por idade (IMC/I) em escore‐z, estabelecidos pela Organização Mundial da Saúde.<a class="elsevierStyleCrossRef" href="#bib0205">11</a> Para avaliação do estado nutricional das mães, foram adotados os critérios para classificação do IMC preconizados pela Organização Mundial de Saúde.<a class="elsevierStyleCrossRef" href="#bib0210">12</a> Crianças e mães com sobrepeso e obesidade foram agrupadas em excesso de peso.O PP foi avaliado com a criança em pé, ereta com a cabeça, no plano horizontal de Frankfurt, com uma fita métrica inextensível (TBW®, São Paulo, Brasil), exatamente abaixo da proeminência laríngea no pescoço, perpendicularmente ao maior eixo do pescoço. Foi exercida pressão mínima, de forma que permitisse o contato completo da fita com a pele. A aferição foi feita em duplicata, foi considerada a média das duas medidas. Para classificação, foram usados os pontos de corte obtidos nas curvas Receiver Operating Characteristic (ROC) com melhores valores de sensibilidade, especificidade e valores preditivos para excesso gordura androide, de acordo com o sexo.O percentual de gordura na região androide foi determinado pela absorciometria de raios X de dupla energia (DXA) (Lunar Prodigy Advance; GE Medical Systems Lunar, Milwaukee, WI, USA), usou‐se o software do próprio equipamento para análise de composição corporal. A gordura androide foi identificada na região entre as costelas e a pelve, a demarcação superior foi feita a 20% da distância da crista ilíaca e do pescoço e a demarcação inferior feita acima da pelve.<a class="elsevierStyleCrossRef" href="#bib0170">4</a> Não foram encontrados na literatura pontos de corte para o diagnóstico de gordura androide elevada em crianças. Por isso, considerou‐se como valores aumentados o percentil 85da amostra de acordo com o sexo, que corresponderam aos valores de 34,0% e 28,9% para meninas e meninos, respectivamente.Avaliação bioquímica e de pressão arterialA coleta de sangue foi feita após jejum de 12 horas no Laboratório de Análises Clínicas da Divisão de Saúde da Universidade Federal de Viçosa (UFV). As amostras foram coletadas por punção venosa em tubo soro, foram centrifugadas por 15 minutos a 3.500rpm e depois separadas em eppendorfs de 1,5mL e armazenadas em ultrafreezer a ‐80°C.O perfil lipídico (colesterol total, lipoproteína de alta densidade ‐ HDL‐c, lipoproteína de baixa densidade ‐ LDL‐c e triglicerídeo) e a glicemia de jejum foram determinados pelo método enzimático colorimétrico, usou‐se kit comercial Bioclin® (Belo Horizonte, MG, Brasil) e foram dosados em equipamento analisador automático (BS‐200 Mindray®, Nanshan, China) no Laboratório de Análises Clínicas (LAC) do Departamento de Nutrição e Saúde da UFV. A classificação dos componentes do perfil lipídico foi feita de acordo com a Atualização da Diretriz Brasileira de Dislipidemias e Prevenção da Aterosclerose.<a class="elsevierStyleCrossRef" href="#bib0215">13</a>A insulina de jejum foi determinada pelo método de imunoensaio por quimioluminescência no laboratório Diagnósticos do Brasil, foi quantificada pelo teste Elecsys Insulin® com limite de detecção de 0,200‐1.000μU/mL. Para a classificação da resistência à insulina, foi usado o valor de HOMA‐IR maior ou igual a 3,16.<a class="elsevierStyleCrossRef" href="#bib0220">14</a>Para aferir a pressão arterial usou‐se um equipamento eletrônico digital no braço com inflação e deflação automática do ar, o tamanho do manguito foi apropriado para o paciente.<a class="elsevierStyleCrossRef" href="#bib0225">15</a> Para avaliar a pressão arterial consideraram‐se sexo, idade e percentil de estatura, também de acordo com a classificação preconizada pela Sociedade Brasileira de Cardiologia.<a class="elsevierStyleCrossRef" href="#bib0225">15</a>Análises estatísticasForam feitas no software Statistical Package for the Social Sciences forWindows, versão 23.0 (SPSS Inc. Chicago, USA). O teste de normalidade de Kolmogorov‐Smirnov foi usado para determinar se as variáveis quantitativas contínuas apresentavam distribuição normal. O nível de significância adotado para todos os testes de hipóteses foi de 5%.Foram feitas análises descritivas dos dados, por meio de frequências relativas, médias (desvio‐padrão) ou medianas (intervalo interquartil). Para comparação de médias ou medianas entre duas amostras independentes foram feitos os testes t de Student ou de Mann‐Whitney, respectivamente.A associação entre o PP (variável independente) e a gordura androide (variável dependente) foi avaliada pela regressão linear múltipla. As variáveis de ajuste que compuseram o modelo final foram: sexo, tipo de escola (pública ou privada), colesterol total, HDL‐c, HOMA‐IR e IMC materno. O modelo final foi avaliado de acordo com os pressupostos da linearidade, homocedasticidade, normalidade, independência, multicolinearidade e resíduos padronizados.As curvas Receiver Operating Characteristic (ROC) determinaram a capacidade do PP de identificar o excesso de gordura androide. Além disso, foram estimados os pontos de corte de PP com melhores valores de sensibilidade (S) e especificidade (E), valores preditivos positivo (VPP) e negativo (VPN).Aspectos éticosEste estudo foi feito de acordo com as diretrizes estabelecidas na Declaração de Helsinque e aprovado pelo Comitê de Ética em Pesquisa com Seres Humanos da Universidade Federal de Viçosa (parecer n° 663.171/2014). O mesmo também foi aprovado pela Secretaria Municipal de Educação, Superintendência Regional de Ensino e direção das escolas.ResultadosA amostra final foi constituída por 376 crianças, houve perda de 2,1% dos participantes por não completarem todas as etapas da pesquisa (não fizeram a coleta de sangue para exames bioquímicos). A partir dos pontos de cortes propostos nas curvas ROC, observou‐se que 20,2% (n=76) das crianças apresentaram PP elevado (<a class="elsevierStyleCrossRef" href="#tbl0005">tabela 1</a>).<elsevierMultimedia ident="tbl0005"></elsevierMultimedia>Na amostra geral, o PP e o percentual de gordura androide apresentaram medianas de 27,0cm e 14,9%, respectivamente. Observaram‐se maiores percentuais de gordura androide em crianças do sexo feminino, de escolas privadas, com excesso de peso, perfil lipídico indesejado, resistência à insulina, pressão arterial elevada e excesso de peso materno. Os mesmos resultados foram encontrados para os maiores valores do PP, com exceção para o tipo de escola, colesterol total e LDL‐c (<a class="elsevierStyleCrossRef" href="#tbl0005">tabela 1</a>).No modelo final de regressão linear múltipla, observou‐se associação positiva entre o PP e o percentual de gordura androide. O aumento em 1cm no PP esteve associado ao aumento de 2,94% na gordura androide, ao ser ajustado por sexo, tipo de escola, colesterol total, HDL‐c, HOMA‐IR e IMC materno (<a class="elsevierStyleCrossRef" href="#tbl0010">tabela 2</a>).<elsevierMultimedia ident="tbl0010"></elsevierMultimedia>A análise na curva ROC demonstrou que o PP foi capaz de identificar o excesso de gordura androide em meninas (AUC: 0,909; IC95%: 0,859; 0,945) e meninos (AUC: 0,938; IC95%: 0,892; 0,968). Os pontos de corte propostos para o sexo feminino (28,3cm) e masculino (28,6cm) tiveram valores de S (feminino: 76,1%; masculino: 85,2%), E (feminino: 92,7%; masculino: 87,6%) e valores preditivos (feminino: VPP 76,1%, VPN 92,7%; masculino: VPP 56,4%, VPN 97,1%) satisfatórios (<a class="elsevierStyleCrossRef" href="#fig0005">fig. 1</a>).<elsevierMultimedia ident="fig0005"></elsevierMultimedia>DiscussãoAté o presente momento, este é o primeiro estudo brasileiro feito com amostra representativa de crianças que demonstrou a capacidade do PP de identificar o excesso de gordura androide. Ademais, o PP apresentou associação direta com a gordura androide, independentemente do sexo, tipo de escola, das concentrações séricas de colesterol total e HDL‐c, HOMA‐IR e IMC materno. Ressalta‐se que os pontos de corte propostos apresentaram valores de S, E e valores preditivos satisfatórios, viabilizaram o uso do PP em estudos epidemiológicos, triagens do risco cardiometabólico e atendimentos ambulatoriais.O uso do PP em adultos é amplamente estudado, observou‐se sua associação direta com o tecido adiposo visceral e o HOMA‐IR em obesos.<a class="elsevierStyleCrossRef" href="#bib0230">16</a> Além disso, um estudo de base populacional com adultos brasileiros demonstrou que o PP pode ser usado para identificar síndrome metabólica e resistência à insulina.<a class="elsevierStyleCrossRef" href="#bib0235">17</a>Nesse sentido, o uso do PP na população pediátrica se torna importante, a maioria dos estudos com esse público o comparou com métodos de estimativa de adiposidade duplamente indiretos, como IMC,<a class="elsevierStyleCrossRef" href="#bib0240">18</a> perímetro da cintura<a class="elsevierStyleCrossRef" href="#bib0245">19</a> e relação cintura‐estatura.<a class="elsevierStyleCrossRef" href="#bib0250">20</a> Em indivíduos de nove a 13 anos da Grécia, o PP esteve associado diretamente às concentrações séricas de triglicerídeo e insulina, HOMA‐IR e pressão arterial; e inversamente à concentração sérica de HDL‐c, quantitative insulin sensitivity check index (QUICKI) e razão glicose‐insulina de jejum (FGIR). O mesmo estudo demonstrou que outras medidas antropométricas usadas em crianças e adolescentes, como escore‐z de IMC, perímetro da cintura e do quadril, relação cintura‐estatura e relação cintura‐quadril, apresentaram associações com os marcadores de risco cardiometabólico semelhantes ao PP.<a class="elsevierStyleCrossRef" href="#bib0255">21</a>O PP é considerado uma opção para identificar adiposidade central por apresentar algumas vantagens em relação ao perímetro da cintura, tais como: boa concordância inter e intraobservador; não é influenciado pelo horário de mensuração (período pré‐prandial e pós‐prandial); maior facilidade para mensurar, pois não requer que o examinado esteja com o mínimo de vestuários, é assim mais aceitável socialmente.<a class="elsevierStyleCrossRef" href="#bib0245">19</a> Entretanto, não há um consenso internacional sobre pontos de corte a serem adotados para o público infantil.Existem pontos de corte do PP propostos a partir de curvas ROC<a class="elsevierStyleCrossRef" href="#bib0240">18</a> e de percentis<a class="elsevierStyleCrossRef" href="#bib0260">22</a> para crianças e adolescentes de acordo com o sexo e a idade em diferentes localidades. No entanto, a grande maioria é de pontos de corte capazes de determinar o excesso de peso/obesidade pelo IMC.<a class="elsevierStyleCrossRefs" href="#bib0240">18,22</a> Por isso, o presente estudo propôs pontos de corte de PP que podem ser usados para identificar o excesso de gordura androide pelo DXA, que é capaz de estimar adiposidade central, é um método considerado referência.<a class="elsevierStyleCrossRef" href="#bib0265">23</a>Em estudo transversal com adolescentes brasileiros de Campinas‐SP, os pontos de corte de PP sugeridos para determinar resistência à insulina foram de 32,0 e 30,3cm para meninas e meninos pré‐púberes, respectivamente.<a class="elsevierStyleCrossRef" href="#bib0245">19</a> Os pontos de corte propostos em estudo transversal feito por Nafiu et al.<a class="elsevierStyleCrossRef" href="#bib0240">18</a> para identificar o excesso de peso em crianças americanas de oito e nove anos foram 29,0 e 30,5cm (meninos), 27,9 e 29,3cm (meninas), respectivamente, próximos dos valores encontrados no nosso estudo. Diante disso, recomenda‐se a validação dos pontos de corte propostos no presente trabalho para outras populações, com o objetivo de identificar o excesso de adiposidade central e também outros fatores de risco cardiometabólico.São de grande relevância estudos que abordam o excesso de adiposidade central no público infantil, visto que as medidas antropométricas que estimam adiposidade central apresentaram maior associação com o risco cardiometabólico, em relação ao IMC em crianças.<a class="elsevierStyleCrossRef" href="#bib0270">24</a> A gordura na região androide compreende o tecido adiposo visceral, o qual é mais lipolítico comparado com o das regiões periféricas. Observa‐se maior liberação hepática de LDL‐c, triglicerídeos e outros ácidos graxos na circulação portal, estímulo da gliconeogênese hepática e inibição da captação hepática de insulina, que causam hiperinsulinemia e resistência à insulina.<a class="elsevierStyleCrossRef" href="#bib0275">25</a>Considerando as elevadas prevalências de excesso de peso, perfil lipídico indesejado e comportamento sedentário nesta amostra e em outras pesquisas semelhantes,<a class="elsevierStyleCrossRefs" href="#bib0280">26,27</a> torna‐se necessário o diagnóstico precoce do excesso de adiposidade central em crianças. Sabe‐se que todas essas alterações podem permanecer na fase adulta, além de estar relacionadas ao processo de aterogênese e a danos cardíacos, que já podem iniciar na infância.<a class="elsevierStyleCrossRefs" href="#bib0290">28,29</a> Ademais, a avaliação do estado nutricional materno é importante para identificar o excesso de adiposidade central em crianças, visto que compartilham fatores genéticos, ambientais (disponibilidade de alimentos na residência) e comportamentais (hábitos alimentares e de estilo de vida).<a class="elsevierStyleCrossRef" href="#bib0300">30</a>Destaca‐se como aspectos positivos deste estudo a avaliação antropométrica ter sido feita por um único pesquisador, o que contribuiu para reduzir os vieses de aferição das medidas; e a amostra ter sido composta exclusivamente por crianças, o que minimiza as possíveis influências hormonais da adolescência na composição corporal. A análise de curva ROC não foi feita estratificada pela idade em função da semelhança fisiológica entre crianças de oito e nove anos. Apesar de o DXA ser incapaz de distinguir os tipos de tecido adiposo, a gordura na região androide obtida nesse exame está fortemente correlacionada ao tecido adiposo visceral em crianças. Como limitações, nota‐se a ausência de valores de referência para classificar a gordura androide em crianças, o que nos permitiu usar o percentil 85da amostra de acordo com o sexo. Diante disso, sugerimos estudos que proponham pontos de corte de gordura na região androide e de PP para todas as faixas etárias infantis, com o propósito de se estabelecer um consenso internacional.Concluímos que o PP é uma medida capaz de identificar o excesso de gordura androide em crianças brasileiras. Os pontos de corte propostos podem ser usados em estudos populacionais, triagens e atendimentos ambulatoriais, desde que sejam validados para o público infantil em que serão aplicados. Dessa maneira, o PP pode fazer parte da rotina de avaliação do estado de saúde de crianças, por ser uma medida simples e de baixo custo, auxilia na identificação precoce do excesso de adiposidade central.FinanciamentoConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (processo: 478910/2013‐4).Conflitos de interesseOs autores declaram não haver conflitos de interesse." "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres1343816" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Method" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1236640" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1343817" "titulo" => "Resumo" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivo" ] 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" => "xpalclavsec1236639" "titulo" => "Palavras‐chave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introdução" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Métodos" "secciones" => array:7 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "População e delineamento do estudo" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Cálculo amostral e processo de amostragem" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Dados demográficos, socioeconômicos e de estilo de vida" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Antropometria e composição corporal" ] 4 => array:2 [ "identificador" => "sec0035" "titulo" => "Avaliação bioquímica e de pressão arterial" ] 5 => array:2 [ "identificador" => "sec0040" "titulo" => "Análises estatísticas" ] 6 => array:2 [ "identificador" => "sec0045" "titulo" => "Aspectos éticos" ] ] ] 6 => array:2 [ "identificador" => "sec0050" "titulo" => "Resultados" ] 7 => array:2 [ "identificador" => "sec0055" "titulo" => "Discussão" ] 8 => array:2 [ "identificador" => "sec0060" "titulo" => "Financiamento" ] 9 => array:2 [ "identificador" => "sec0065" "titulo" => "Conflitos de interesse" ] 10 => array:2 [ "identificador" => "xack465197" "titulo" => "Agradecimentos" ] 11 => array:1 [ "titulo" => "Referências" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2018-04-25" "fechaAceptado" => "2018-11-19" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1236640" "palabras" => array:5 [ 0 => "Adiposity" 1 => "Anthropometry" 2 => "Risk factors" 3 => "Nutritional assessment" 4 => "ROC curve" ] ] ] "pt" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palavras‐chave" "identificador" => "xpalclavsec1236639" "palabras" => array:5 [ 0 => "Adiposidade" 1 => "Antropometria" 2 => "Fatores de risco" 3 => "Avaliação nutricional" 4 => "Curva ROC" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "ObjectiveTo evaluate the ability of neck circumference to identify excess android fat and to propose cutoff points for Brazilian children. MethodThis was a cross‐sectional study with 376 children aged 8 and 9 years enrolled in public and private schools in the urban area of the municipality of Viçosa, Minas Gerais. A semi‐structured questionnaire containing sociodemographic and lifestyle information was applied. The following were collected: neck circumference, weight, and height for the calculation of body mass index. The percentage of fat in the android region was determined by dual energy X‐ray absorptiometry. Linear regression analysis was used to evaluate the association between neck circumference and android fat, adopting a significance level of 5%. Receiver operating characteristic curves were used to evaluate the capacity of neck circumference to determine the excess android fat, as well as to estimate the cutoff points of neck circumference according to gender. ResultsMultiple linear regression showed an association between neck circumference and android fat (β: 2.94, 95% CI: 2.41, 3.47). Neck circumference was able to identify excess android fat in girls (AUC: 0.909, 95% CI: 0.999, 0.945) and boys (AUC: 0.938, 95% CI: 0.892, 0.968). The proposed cutoff points showed satisfactory sensitivity, specificity, and predictive values. ConclusionsNeck circumference is capable of identifying excess android fat in children and can be used in clinical practice and in population studies to determine central adiposity. The proposed cutoff points were satisfactory, but should be validated for other populations." "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Method" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] "pt" => array:3 [ "titulo" => "Resumo" "resumen" => "ObjetivoAvaliar a capacidade do perímetro do pescoço em identificar o excesso de gordura androide e propor pontos de corte para crianças brasileiras. MétodoEstudo transversal com 376 crianças de oito e nove anos, matriculadas em escolas públicas e privadas da área urbana de Viçosa, Minas Gerais. Foi aplicado um questionário semiestruturado com informações sociodemográficas e de estilo de vida. Foram coletados: perímetro do pescoço, peso e estatura para o cálculo do índice de massa corporal. O percentual de gordura na região androide foi determinado pela absorciometria de raios X de dupla energia. A análise de regressão linear foi utilizada para avaliar a associação entre o perímetro do pescoço e a gordura androide, adotando-se o nível de significância de 5%. Por meio das curvas Receiver Operating Characteristic avaliou‐se a capacidade do perímetro do pescoço de determinar o excesso de gordura androide, bem como estimaram‐se os pontos de corte de perímetro do pescoço segundo o sexo. ResultadosA regressão linear múltipla demonstrou associação entre o perímetro do pescoço e a gordura androide (β: 2,94; IC95%: 2,41; 3,47). O perímetro do pescoço foi capaz de identificar o excesso de gordura androide em meninas (AUC: 0,909; IC95%: 0,859; 0,945) e meninos (AUC: 0,938; IC95%: 0,892; 0,968). Os pontos de corte propostos tiveram valores de sensibilidade, especificidade e preditivos satisfatórios. ConclusõesO perímetro do pescoço é uma medida capaz de identificar o excesso de gordura androide em crianças, pode ser usado na prática clínica e em estudos populacionais para determinar a adiposidade central. Os pontos de corte propostos foram satisfatórios, entretanto devem ser validados para outras populações." "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Método" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusões" ] ] ] ] "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "Como citar este artigo: Filgueiras MS, Albuquerque FM, Castro AP, Rocha NP, Milagres LC, Novaes JF. Neck circumference cutoff points to identify excess android fat. J Pediatr (Rio J). 2020;96:356–63." ] ] "multimedia" => array:3 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figura 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1613 "Ancho" => 2918 "Tamanyo" => 316689 ] ] "descripcion" => array:1 [ "pt" => "Áreas abaixo da curva Receiver Operating Characteristic (ROC) e pontos de corte do perímetro do pescoço com melhores valores de sensibilidade, especificidade e valores preditivos para excesso de gordura androide, de acordo com o sexo. Viçosa, MG, 2015. AUC, area under the curve; IC95%, intervalo de confiança de 95%; S, sensibilidade; E, especificidade; VPP, valor preditivo positivo; VPN, valor preditivo negativo." ] ] 1 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Tabela 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Tabela " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "HDL‐c, high density lipoprotein; HOMA‐IR, Homeostatic Model Assessment for Insulin Resistance; LDL‐c, low density lipoprotein.Dados apresentados em média (desvio‐padrão) ou mediana (intervalo interquartil)." "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">Variável \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">Perímetro do pescoço (cm) \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">Gordura androide (%) \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">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">376 (100,0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27,0 (26,0; 28,5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14,9 (7,1; 26,4) \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">Sexo</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">Feminino \t\t\t\t\t\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">196 (52,1) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26,7 (25,5; 28,1) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17,1 (8,6; 20,0) \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">Masculino \t\t\t\t\t\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">180 (47,9) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27,4 (26,4; 28,5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9,7 (5,9; 22,7) \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">p‐valor \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0,001<a class="elsevierStyleCrossRef" href="#tblfn0020">d</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0,001<a class="elsevierStyleCrossRef" href="#tblfn0020">d</a> \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">Idade</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">8 anos \t\t\t\t\t\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">182 (48,4) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26,6 (25,5; 28,0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">13,1 (6,8; 23,9) \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">9 anos \t\t\t\t\t\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">194 (51,6) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27,5 (26,2; 28,5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16.30 (7,8; 27,8) \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">p‐valor \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0,001<a class="elsevierStyleCrossRef" href="#tblfn0020">d</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0,101 \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">Tipo de escola</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">Pública \t\t\t\t\t\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">266 (70,7) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27,2 (2,0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12,5 (6,9; 25,7) \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">Privada \t\t\t\t\t\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">110 (29,3) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27,4 (1,9) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19,3 (8,7; 27,1) \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">p‐valor \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0,448 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0,018<a class="elsevierStyleCrossRef" href="#tblfn0020">d</a> \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">Renda per capita</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">≥ R$500,00 \t\t\t\t\t\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">191 (50,8) \t\t\t\t\t\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">27,4 (1,9) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17,0 (7,3; 27,2) \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"><R$500,00 \t\t\t\t\t\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">185 (49,2) \t\t\t\t\t\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">27,1 (2,0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12,8 (7,1; 24,6) \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">p‐valor \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0,085 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0,115 \t\t\t\t\t\t\n \t\t\t\t</td></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">Tempo de tela/dia</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">> 2 horas \t\t\t\t\t\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">178 (47,3) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27,3 (26,0; 28,5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15,5 (7,3; 27,1) \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">≤ 2 horas \t\t\t\t\t\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">198 (52,7) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27,0 (25,7; 28,1) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">13,2 (7,1; 25,6) \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">p‐valor \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0,119 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0,377 \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">Excesso de peso</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">Sim \t\t\t\t\t\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">123 (32,7) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">29,2 (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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">31,3 (9,7) \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">Não \t\t\t\t\t\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">253 (67,3) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26,3 (1,2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11,1 (6,7) \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">p‐valor \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0,001<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0.001<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \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">Perímetro do pescoço<a class="elsevierStyleCrossRef" href="#tblfn0005">a</a></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">Aumentado \t\t\t\t\t\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">76 (20,2) \t\t\t\t\t\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">29,9 (29,0; 31,0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">32,7 (25,3; 39,3) \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">Adequado \t\t\t\t\t\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">300 (79,8) \t\t\t\t\t\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">26,5 (25,5; 27,5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10,5 (6,2; 19,8) \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">p‐valor \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">‐ \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0,001<a class="elsevierStyleCrossRef" href="#tblfn0020">d</a> \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">Gordura androide<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a></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">≥ p85 \t\t\t\t\t\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">73 (19,4) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">29,5 (28,5; 30,9) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">35,9 (32,2; 43,3) \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"><p85 \t\t\t\t\t\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">303 (80,6) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26,5 (25,5; 27,7) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10,5 (6,3; 18,6) \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">p‐valor \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0,001<a class="elsevierStyleCrossRef" href="#tblfn0020">d</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">‐ \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" 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">Excesso de peso materno</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">Sim \t\t\t\t\t\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">168 (57,3) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27,8 (2,0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">18,3 (8,4; 30,8) \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">Não \t\t\t\t\t\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">125 (42,7) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26,5 (1,8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11,0 (6,2; 19,9) \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">p‐valor \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0,001<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0,001<a class="elsevierStyleCrossRef" href="#tblfn0020">d</a> \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">Colesterol total</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">≥ 170 mg/dL \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">86 (22,9) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27,5 (1,9) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20,5 (7,5; 29,4) \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"><170 mg/dL \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">289 (77,1) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27,2 (1,9) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12,8 (7,1; 24,1) \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">p‐valor \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0,278 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0,011<a class="elsevierStyleCrossRef" href="#tblfn0020">d</a> \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">HDL‐c</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">≤ 45 mg/dL \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">131 (34,9) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27,6 (2,1) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">18,4 (8,0; 32,1) \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">> 45 mg/dL \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">244 (65,1) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27,1 (1,8) \t\t\t\t\t\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">12,9 (6,9; 23,0) \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">p‐valor \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0,006<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0,005<a class="elsevierStyleCrossRef" href="#tblfn0020">d</a> \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">LDL‐c</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">≥ 110 mg/dL \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">58 (15,5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27,7 (1,9) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22,0 (12,8) \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"><110 mg/dL \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">316 (84,5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27,2 (1,9) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16,8 (12,0) \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">p‐valor \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0,064 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0,003<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \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">Triglicerídeo</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">≥ 75 mg/dL \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">176 (46,9) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27,7 (2,1) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19,9 (8,2; 30,7) \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"><75 mg/dL \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">199 (53,1) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26,9 (1,7) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10,6 (6,5; 19,8) \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">p‐valor \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0,001<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0,001<a class="elsevierStyleCrossRef" href="#tblfn0020">d</a> \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">HOMA‐IR</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">≥ 3,16 \t\t\t\t\t\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">9 (2,4) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">30,1 (1.1) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">35,6 (13,2) \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"><3,16 \t\t\t\t\t\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">362 (97,6) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27,2 (1.9) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17,3 (11,9) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\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">p‐valor \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0,001<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0,001<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \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">Pressão arterial</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">Aumentada \t\t\t\t\t\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">25 (6,7) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">29,1 (1,8) \t\t\t\t\t\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">29,0 (13,6) \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">Adequada \t\t\t\t\t\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">350 (93,3) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27,1 (1,9) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16,9 (11,8) \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">p‐valor \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0,001<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0,001<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2305293.png" ] ] ] "notaPie" => array:4 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "a" "nota" => "Classificação de acordo com os pontos de corte obtidos nas curvas Receiver Operating Characteristic." ] 1 => array:3 [ "identificador" => "tblfn0010" "etiqueta" => "b" "nota" => "Meninas (p85=34,0%); Meninos (p85=28,9%)." ] 2 => array:3 [ "identificador" => "tblfn0015" "etiqueta" => "c" "nota" => "Teste t de Student. p<0,05" ] 3 => array:3 [ "identificador" => "tblfn0020" "etiqueta" => "d" "nota" => "Teste de Mann‐Whitney. p<0,05" ] ] ] "descripcion" => array:1 [ "pt" => "Valores do perímetro do pescoço e da gordura androide de acordo com variáveis sociodemográficas, antropométricas, bioquímicas e clínicas. Viçosa, MG, 2015" ] ] 2 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Tabela 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at2" "detalle" => "Tabela " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "Regressão linear múltipla; IC95% ‐ intervalo de confiança de 95%.HDL‐c, high density lipoprotein; HOMA‐IR, Homeostatic Model Assessment for Insulin Resistance; IMC, índice de massa corporal.Ajuste por sexo, tipo de escola, concentrações séricas de colesterol total, HDL‐c, HOMA‐IR e IMC materno." "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">Variável \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">β (IC95%) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p‐valor \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Perímetro do pescoço (cm) \t\t\t\t\t\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">2,94 (2,41; 3,47) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0,001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Sexo feminino \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5,31 (3,33; 7,29) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0,001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Escola privada \t\t\t\t\t\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">2,95 (0,75; 5,15) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0,009 \t\t\t\t\t\t\n \t\t\t\t</td></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">Colesterol total (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0,08 (0,04; 0,11) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0,001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HDL‐c (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">‐0,16 (‐0,27; ‐0,05) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0,004 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HOMA‐IR \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3,05 (1,78; 4,33) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0,001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">IMC materno (kg/m2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0,29 (0,10; 0,47) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0,002 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2305294.png" ] ] ] ] "descripcion" => array:1 [ "pt" => "Associação entre o perímetro do pescoço (variável independente) e o percentual de gordura androide (variável dependente) em crianças. Viçosa, MG, 2015" ] ] ] "bibliografia" => array:2 [ "titulo" => "Referências" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:30 [ 0 => array:3 [ "identificador" => "bib0155" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Worldwide trends in body‐mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population‐based measurement studies in 128. 9 million children, adolescents, and adults" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:1 [ 0 => "NCD Risk Factor Collaboration (NCD-RisC)" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/S0140-6736(17)32129-3" "Revista" => array:6 [ "tituloSerie" => "Lancet" "fecha" => "2017" "volumen" => "390" "paginaInicial" => "2627" "paginaFinal" => "2642" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/29029897" "web" => "Medline" ] ] ] ] ] ] ] ] 1 => array:3 [ "identificador" => "bib0160" "etiqueta" => "2" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Pesquisa de Orçamentos Familiares 2008–2009. 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Estatísticas

Artigo Original

Pontos de corte do perímetro do pescoço para identificar o excesso de gordura androide

Mariana De Santis Filgueiras

Autor para correspondência

mariana.filgueiras@ufv.br

Autor para correspondência.

, Fernanda Martins de Albuquerque, Ana Paula Pereira Castro, Naruna Pereira Rocha, Luana Cupertino Milagres, Juliana Farias de Novaes

Universidade Federal de Viçosa (UFV), Departamento de Nutrição e Saúde, Viçosa, MG, Brasil

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3412

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visto que exerce um papel fundamental no desenvolvimento do risco cardiometab&#243;lico&#46;<a class="elsevierStyleCrossRef" href="#bib0165"><span class="elsevierStyleSup">3</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">Existem diferentes t&#233;cnicas para avaliar a adiposidade corporal&#44; a absorciometria de raios X de dupla energia &#40;DXA&#41; &#233; considerada um m&#233;todo refer&#234;ncia para avaliar a adiposidade central em crian&#231;as de todas as idades&#44; pois estima a quantidade de gordura na regi&#227;o androide&#46;<a class="elsevierStyleCrossRef" href="#bib0170"><span class="elsevierStyleSup">4</span></a> No entanto&#44; sua aplica&#231;&#227;o em estudos epidemiol&#243;gicos e na pr&#225;tica cl&#237;nica tamb&#233;m &#233; limitada por apresentar custo elevado e execu&#231;&#227;o complexa&#44; s&#227;o necess&#225;rios m&#233;todos simples e menos dispendiosos&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">Nesse aspecto&#44; o per&#237;metro do pesco&#231;o &#40;PP&#41; tem sido proposto como uma ferramenta &#250;til para identificar indiv&#237;duos jovens com excesso de peso e risco cardiometab&#243;lico por ser um m&#233;todo simples&#44; de baixo custo e ter uma menor varia&#231;&#227;o ao longo do dia comparado ao per&#237;metro da cintura&#46;<a class="elsevierStyleCrossRef" href="#bib0175"><span class="elsevierStyleSup">5</span></a> No entanto&#44; at&#233; o momento&#44; n&#227;o foram encontrados estudos na literatura que avaliaram a associa&#231;&#227;o e a capacidade do PP de identificar o excesso de adiposidade central estimada por um m&#233;todo refer&#234;ncia&#44; como a gordura na regi&#227;o androide determinada pelo DXA&#46;</p><p id="par0025" class="elsevierStylePara elsevierViewall">A aus&#234;ncia da defini&#231;&#227;o de pontos de corte espec&#237;ficos de PP para crian&#231;as brasileiras pode ser uma limita&#231;&#227;o para seu uso rotineiro&#46; Na literatura&#44; segundo o nosso conhecimento&#44; encontra&#8208;se apenas um estudo de delineamento transversal com adolescentes brasileiros matriculados em escolas p&#250;blicas do munic&#237;pio de S&#227;o Paulo&#8208;SP que prop&#244;s pontos de corte de PP para identificar sobrepeso e obesidade&#46;<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">6</span></a> Diante disso&#44; s&#227;o escassos os estudos com essa abordagem em idades mais precoces&#46;</p><p id="par0030" class="elsevierStylePara elsevierViewall">Assim&#44; o objetivo deste estudo foi&#58; 1&#41; avaliar a capacidade do PP de identificar o excesso de gordura androide&#59; 2&#41; propor pontos de corte de PP para determinar o excesso de gordura androide em crian&#231;as brasileiras&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">M&#233;todos</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Popula&#231;&#227;o e delineamento do estudo</span><p id="par0035" class="elsevierStylePara elsevierViewall">Estudo transversal feito com amostra representativa de crian&#231;as de oito e nove anos&#44; matriculadas em escolas p&#250;blicas e privadas da &#225;rea urbana do munic&#237;pio de Vi&#231;osa&#8208;MG&#44; de maio a dezembro de 2015&#46; O munic&#237;pio de Vi&#231;osa fica na Zona da Mata Mineira&#44; a 227<span class="elsevierStyleHsp" style=""></span>km da capital Belo Horizonte&#46; De acordo com o Censo 2010&#44; Vi&#231;osa apresenta uma extens&#227;o territorial de 299 km<span class="elsevierStyleSup">2</span> e 72&#46;244 habitantes&#44; 93&#44;2&#37; residem em &#225;rea urbana&#46; O Produto Interno Bruto &#40;PIB&#41; <span class="elsevierStyleItalic">per capita</span> &#233; de R&#36; <span class="elsevierStyleItalic">19&#46;391&#44;08</span>&#46;<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">7</span></a></p><p id="par0040" class="elsevierStylePara elsevierViewall">Os participantes deste estudo foram provenientes da Pesquisa de Avalia&#231;&#227;o da Sa&#250;de do Escolar &#40;PASE&#41;&#44; investiga&#231;&#227;o transversal que teve o objetivo de avaliar a sa&#250;de cardiovascular desse p&#250;blico infantil no munic&#237;pio de Vi&#231;osa&#46;<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">8</span></a> Em 2015&#44; o munic&#237;pio contava com 17 escolas p&#250;blicas e sete particulares na &#225;rea urbana que atendiam crian&#231;as de oito e nove anos&#44; total de 1&#46;464 crian&#231;as matriculadas&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">C&#225;lculo amostral e processo de amostragem</span><p id="par0045" class="elsevierStylePara elsevierViewall">O c&#225;lculo amostral foi feito no <span class="elsevierStyleItalic">software</span> Epi Info &#40;vers&#227;o 7&#46;2&#59; Atlanta&#44; GA&#41;&#44; considerando o n&#250;mero total de estudantes de oito e nove anos em 2015 &#40;n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>1&#46;464&#41;&#44; preval&#234;ncia de 10&#44;7&#37; de obesidade&#44;<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">9</span></a> erro tolerado de 3&#37;&#44; n&#237;vel de confian&#231;a de 95&#37; e acr&#233;scimo de 20&#37; para cobertura de perdas&#44; total de 384 crian&#231;as a serem estudadas&#46;</p><p id="par0050" class="elsevierStylePara elsevierViewall">As crian&#231;as foram selecionadas por amostragem aleat&#243;ria estratificada&#44; a amostra de cada escola atingiu a proporcionalidade dos alunos matriculados por idade e sexo&#46; A sele&#231;&#227;o de crian&#231;as foi feita por sorteio aleat&#243;rio simples at&#233; que o n&#250;mero necess&#225;rio para cada escola fosse alcan&#231;ado&#46;</p><p id="par0055" class="elsevierStylePara elsevierViewall">Ap&#243;s a sele&#231;&#227;o&#44; fez&#8208;se contato telef&#244;nico com os respons&#225;veis pelas crian&#231;as&#44; as quais foram convidadas a participar do estudo&#46; Foram explicados os objetivos e a metodologia do estudo e foi agendado o primeiro encontro&#44; no qual&#44; ap&#243;s explica&#231;&#227;o de cada etapa aos respons&#225;veis&#44; aqueles que concordaram em participar assinaram o Termo de Consentimento Livre e Esclarecido &#40;TCLE&#41;&#46;</p><p id="par0060" class="elsevierStylePara elsevierViewall">N&#227;o foram inclu&#237;das crian&#231;as que apresentassem algum problema de sa&#250;de que alterasse o estado nutricional ou a composi&#231;&#227;o corporal &#40;defici&#234;ncias f&#237;sicas&#44; cognitivas ou m&#250;ltiplas&#44; dist&#250;rbios da tireoide etc&#46;&#41;&#44; bem como em uso cr&#244;nico de medicamentos que interferissem no metabolismo da glicose e&#47;ou lip&#237;dios &#40;corticosteroides&#44; estatinas&#44; hipoglicemiantes etc&#46;&#41; e em uso de suplementos vitam&#237;nicos ou minerais no decorrer da pesquisa ou nos &#250;ltimos tr&#234;s meses &#40;suplementa&#231;&#227;o de vitamina D e zinco&#41;&#46; E ainda nos casos de impossibilidade de contato com os pais ou respons&#225;vel ap&#243;s tr&#234;s tentativas&#46;</p><p id="par0065" class="elsevierStylePara elsevierViewall">Foi feito em fevereiro de 2015 um estudo&#8208;piloto com 10&#37; da amostra&#44; que incluiu crian&#231;as de oito e nove anos matriculadas em uma escola p&#250;blica&#44; selecionada de forma aleat&#243;ria&#44; as quais n&#227;o fizeram parte da amostra final do estudo&#46; Por meio do estudo piloto&#44; foi poss&#237;vel testar a aplica&#231;&#227;o dos question&#225;rios&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Dados demogr&#225;ficos&#44; socioecon&#244;micos e de estilo de vida</span><p id="par0070" class="elsevierStylePara elsevierViewall">Foi aplicado um question&#225;rio semiestruturado com informa&#231;&#245;es socioecon&#244;micas e demogr&#225;ficas&#44; como idade&#44; sexo&#44; tipo de escola &#40;p&#250;blica ou privada&#41; e renda <span class="elsevierStyleItalic">per capita</span> &#40;categorizada de acordo com a mediana da amostra total&#44; equivalente a R&#36; 500&#44;00&#41;&#46;</p><p id="par0075" class="elsevierStylePara elsevierViewall">Um question&#225;rio sobre estilo de vida foi aplicado para estimar o tempo de tela em horas por dia &#40;tempo gasto sentado por longos per&#237;odos na frente da televis&#227;o&#44; videogame ou computador&#41;&#46; O comportamento sedent&#225;rio foi classificado como tempo de tela maior do que duas horas&#47;dia&#46;<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">10</span></a></p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Antropometria e composi&#231;&#227;o corporal</span><p id="par0080" class="elsevierStylePara elsevierViewall">A coleta de dados foi feita em ambiente apropriado por um membro da equipe treinado&#44; com os volunt&#225;rios sem cal&#231;ados e com roupas leves&#46; O peso foi aferido em balan&#231;a digital eletr&#244;nica&#44; com capacidade de 150<span class="elsevierStyleHsp" style=""></span>kg e precis&#227;o de 0&#44;1<span class="elsevierStyleHsp" style=""></span>kg &#40;<span class="elsevierStyleItalic">Tanita</span>&#174; Modelo Ironman BC 553&#44; Tanita Corporation of America Inc&#46;&#44; Artlington Heights&#44; USA&#41; e a estatura foi determinada com um estadi&#244;metro&#44; dividido em cent&#237;metros e subdividido em mil&#237;metros &#40;<span class="elsevierStyleItalic">Alturexata</span>&#174;&#44; Belo Horizonte&#44; Brasil&#41;&#46;</p><p id="par0085" class="elsevierStylePara elsevierViewall">Com os dados de peso e estatura obtidos&#44; foi calculado o &#237;ndice de massa corporal &#40;IMC&#41; e para a classifica&#231;&#227;o do estado nutricional das crian&#231;as&#44; foram usados os pontos de corte de IMC por idade &#40;IMC&#47;I&#41; em escore&#8208;z&#44; estabelecidos pela Organiza&#231;&#227;o Mundial da Sa&#250;de&#46;<a class="elsevierStyleCrossRef" href="#bib0205"><span class="elsevierStyleSup">11</span></a> Para avalia&#231;&#227;o do estado nutricional das m&#227;es&#44; foram adotados os crit&#233;rios para classifica&#231;&#227;o do IMC preconizados pela Organiza&#231;&#227;o Mundial de Sa&#250;de&#46;<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">12</span></a> Crian&#231;as e m&#227;es com sobrepeso e obesidade foram agrupadas em excesso de peso&#46;</p><p id="par0090" class="elsevierStylePara elsevierViewall">O PP foi avaliado com a crian&#231;a em p&#233;&#44; ereta com a cabe&#231;a&#44; no plano horizontal de Frankfurt&#44; com uma fita m&#233;trica inextens&#237;vel &#40;<span class="elsevierStyleItalic">TBW</span>&#174;&#44; S&#227;o Paulo&#44; Brasil&#41;&#44; exatamente abaixo da proemin&#234;ncia lar&#237;ngea no pesco&#231;o&#44; perpendicularmente ao maior eixo do pesco&#231;o&#46; Foi exercida press&#227;o m&#237;nima&#44; de forma que permitisse o contato completo da fita com a pele&#46; A aferi&#231;&#227;o foi feita em duplicata&#44; foi considerada a m&#233;dia das duas medidas&#46; Para classifica&#231;&#227;o&#44; foram usados os pontos de corte obtidos nas curvas <span class="elsevierStyleItalic">Receiver Operating Characteristic</span> &#40;ROC&#41; com melhores valores de sensibilidade&#44; especificidade e valores preditivos para excesso gordura androide&#44; de acordo com o sexo&#46;</p><p id="par0095" class="elsevierStylePara elsevierViewall">O percentual de gordura na regi&#227;o androide foi determinado pela absorciometria de raios X de dupla energia &#40;DXA&#41; &#40;Lunar Prodigy Advance&#59; GE Medical Systems Lunar&#44; Milwaukee&#44; WI&#44; USA&#41;&#44; usou&#8208;se o <span class="elsevierStyleItalic">software</span> do pr&#243;prio equipamento para an&#225;lise de composi&#231;&#227;o corporal&#46; A gordura androide foi identificada na regi&#227;o entre as costelas e a pelve&#44; a demarca&#231;&#227;o superior foi feita a 20&#37; da dist&#226;ncia da crista il&#237;aca e do pesco&#231;o e a demarca&#231;&#227;o inferior feita acima da pelve&#46;<a class="elsevierStyleCrossRef" href="#bib0170"><span class="elsevierStyleSup">4</span></a> N&#227;o foram encontrados na literatura pontos de corte para o diagn&#243;stico de gordura androide elevada em crian&#231;as&#46; Por isso&#44; considerou&#8208;se como valores aumentados o percentil 85<span class="elsevierStyleHsp" style=""></span>da amostra de acordo com o sexo&#44; que corresponderam aos valores de 34&#44;0&#37; e 28&#44;9&#37; para meninas e meninos&#44; respectivamente&#46;</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Avalia&#231;&#227;o bioqu&#237;mica e de press&#227;o arterial</span><p id="par0100" class="elsevierStylePara elsevierViewall">A coleta de sangue foi feita ap&#243;s jejum de 12 horas no Laborat&#243;rio de An&#225;lises Cl&#237;nicas da Divis&#227;o de Sa&#250;de da Universidade Federal de Vi&#231;osa &#40;UFV&#41;&#46; As amostras foram coletadas por pun&#231;&#227;o venosa em tubo soro&#44; foram centrifugadas por 15 minutos a 3&#46;500<span class="elsevierStyleHsp" style=""></span>rpm e depois separadas em <span class="elsevierStyleItalic">eppendorfs</span> de 1&#44;5<span class="elsevierStyleHsp" style=""></span>mL e armazenadas em <span class="elsevierStyleItalic">ultrafreezer</span> a &#8208;80<span class="elsevierStyleHsp" style=""></span>&#176;C&#46;</p><p id="par0105" class="elsevierStylePara elsevierViewall">O perfil lip&#237;dico &#40;colesterol total&#44; lipoprote&#237;na de alta densidade &#8208; HDL&#8208;c&#44; lipoprote&#237;na de baixa densidade &#8208; LDL&#8208;c e triglicer&#237;deo&#41; e a glicemia de jejum foram determinados pelo m&#233;todo enzim&#225;tico colorim&#233;trico&#44; usou&#8208;se kit comercial Bioclin&#174; &#40;Belo Horizonte&#44; MG&#44; Brasil&#41; e foram dosados em equipamento analisador autom&#225;tico &#40;BS&#8208;200 Mindray&#174;&#44; Nanshan&#44; China&#41; no Laborat&#243;rio de An&#225;lises Cl&#237;nicas &#40;LAC&#41; do Departamento de Nutri&#231;&#227;o e Sa&#250;de da UFV&#46; A classifica&#231;&#227;o dos componentes do perfil lip&#237;dico foi feita de acordo com a Atualiza&#231;&#227;o da Diretriz Brasileira de Dislipidemias e Preven&#231;&#227;o da Aterosclerose&#46;<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">13</span></a></p><p id="par0110" class="elsevierStylePara elsevierViewall">A insulina de jejum foi determinada pelo m&#233;todo de imunoensaio por quimioluminesc&#234;ncia no laborat&#243;rio Diagn&#243;sticos do Brasil&#44; foi quantificada pelo teste&#160;Elecsys Insulin&#174; com limite de detec&#231;&#227;o de 0&#44;200&#8208;1&#46;000<span class="elsevierStyleHsp" style=""></span>&#956;U&#47;mL&#46; Para a classifica&#231;&#227;o da resist&#234;ncia &#224; insulina&#44; foi usado o valor de HOMA&#8208;IR maior ou igual a 3&#44;16&#46;<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">14</span></a></p><p id="par0115" class="elsevierStylePara elsevierViewall">Para aferir a press&#227;o arterial usou&#8208;se um equipamento eletr&#244;nico digital no bra&#231;o com infla&#231;&#227;o e defla&#231;&#227;o autom&#225;tica do ar&#44; o tamanho do manguito foi apropriado para o paciente&#46;<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">15</span></a> Para avaliar a press&#227;o arterial consideraram&#8208;se sexo&#44; idade e percentil de estatura&#44; tamb&#233;m de acordo com a classifica&#231;&#227;o preconizada pela Sociedade Brasileira de Cardiologia&#46;<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">15</span></a></p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">An&#225;lises estat&#237;sticas</span><p id="par0120" class="elsevierStylePara elsevierViewall">Foram feitas no <span class="elsevierStyleItalic">software Statistical Package for the Social Sciences for</span><span class="elsevierStyleItalic">Windows</span>&#44; vers&#227;o 23&#46;0 &#40;SPSS Inc&#46; Chicago&#44; USA&#41;&#46; O teste de normalidade de Kolmogorov&#8208;Smirnov foi usado para determinar se as vari&#225;veis quantitativas cont&#237;nuas apresentavam distribui&#231;&#227;o normal&#46; O n&#237;vel de signific&#226;ncia adotado para todos os testes de hip&#243;teses foi de 5&#37;&#46;</p><p id="par0125" class="elsevierStylePara elsevierViewall">Foram feitas an&#225;lises descritivas dos dados&#44; por meio de frequ&#234;ncias relativas&#44; m&#233;dias &#40;desvio&#8208;padr&#227;o&#41; ou medianas &#40;intervalo interquartil&#41;&#46; Para compara&#231;&#227;o de m&#233;dias ou medianas entre duas amostras independentes foram feitos os testes <span class="elsevierStyleItalic">t</span> de Student ou de Mann&#8208;Whitney&#44; respectivamente&#46;</p><p id="par0130" class="elsevierStylePara elsevierViewall">A associa&#231;&#227;o entre o PP &#40;vari&#225;vel independente&#41; e a gordura androide &#40;vari&#225;vel dependente&#41; foi avaliada pela regress&#227;o linear m&#250;ltipla&#46; As vari&#225;veis de ajuste que compuseram o modelo final foram&#58; sexo&#44; tipo de escola &#40;p&#250;blica ou privada&#41;&#44; colesterol total&#44; HDL&#8208;c&#44; HOMA&#8208;IR e IMC materno&#46; O modelo final foi avaliado de acordo com os pressupostos da linearidade&#44; homocedasticidade&#44; normalidade&#44; independ&#234;ncia&#44; multicolinearidade e res&#237;duos padronizados&#46;</p><p id="par0135" class="elsevierStylePara elsevierViewall">As curvas <span class="elsevierStyleItalic">Receiver Operating Characteristic</span> &#40;ROC&#41; determinaram a capacidade do PP de identificar o excesso de gordura androide&#46; Al&#233;m disso&#44; foram estimados os pontos de corte de PP com melhores valores de sensibilidade &#40;S&#41; e especificidade &#40;E&#41;&#44; valores preditivos positivo &#40;VPP&#41; e negativo &#40;VPN&#41;&#46;</p></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Aspectos &#233;ticos</span><p id="par0140" class="elsevierStylePara elsevierViewall">Este estudo foi feito de acordo com as diretrizes estabelecidas na Declara&#231;&#227;o de Helsinque e aprovado pelo Comit&#234; de &#201;tica em Pesquisa com Seres Humanos da Universidade Federal de Vi&#231;osa &#40;parecer n&#176; 663&#46;171&#47;2014&#41;&#46; O mesmo tamb&#233;m foi aprovado pela Secretaria Municipal de Educa&#231;&#227;o&#44; Superintend&#234;ncia Regional de Ensino e dire&#231;&#227;o das escolas&#46;</p></span></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Resultados</span><p id="par0145" class="elsevierStylePara elsevierViewall">A amostra final foi constitu&#237;da por 376 crian&#231;as&#44; houve perda de 2&#44;1&#37; dos participantes por n&#227;o completarem todas as etapas da pesquisa &#40;n&#227;o fizeram a coleta de sangue para exames bioqu&#237;micos&#41;&#46; A partir dos pontos de cortes propostos nas curvas ROC&#44; observou&#8208;se que 20&#44;2&#37; &#40;n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>76&#41; das crian&#231;as apresentaram PP elevado &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">tabela 1</a>&#41;&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0150" class="elsevierStylePara elsevierViewall">Na amostra geral&#44; o PP e o percentual de gordura androide apresentaram medianas de 27&#44;0<span class="elsevierStyleHsp" style=""></span>cm e 14&#44;9&#37;&#44; respectivamente&#46; Observaram&#8208;se maiores percentuais de gordura androide em crian&#231;as do sexo feminino&#44; de escolas privadas&#44; com excesso de peso&#44; perfil lip&#237;dico indesejado&#44; resist&#234;ncia &#224; insulina&#44; press&#227;o arterial elevada e excesso de peso materno&#46; Os mesmos resultados foram encontrados para os maiores valores do PP&#44; com exce&#231;&#227;o para o tipo de escola&#44; colesterol total e LDL&#8208;c &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">tabela 1</a>&#41;&#46;</p><p id="par0155" class="elsevierStylePara elsevierViewall">No modelo final de regress&#227;o linear m&#250;ltipla&#44; observou&#8208;se associa&#231;&#227;o positiva entre o PP e o percentual de gordura androide&#46; O aumento em 1<span class="elsevierStyleHsp" style=""></span>cm no PP esteve associado ao aumento de 2&#44;94&#37; na gordura androide&#44; ao ser ajustado por sexo&#44; tipo de escola&#44; colesterol total&#44; HDL&#8208;c&#44; HOMA&#8208;IR e IMC materno &#40;<a class="elsevierStyleCrossRef" href="#tbl0010">tabela 2</a>&#41;&#46;</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0160" class="elsevierStylePara elsevierViewall">A an&#225;lise na curva ROC demonstrou que o PP foi capaz de identificar o excesso de gordura androide em meninas &#40;AUC&#58; 0&#44;909&#59; IC95&#37;&#58; 0&#44;859&#59; 0&#44;945&#41; e meninos &#40;AUC&#58; 0&#44;938&#59; IC95&#37;&#58; 0&#44;892&#59; 0&#44;968&#41;&#46; Os pontos de corte propostos para o sexo feminino &#40;28&#44;3<span class="elsevierStyleHsp" style=""></span>cm&#41; e masculino &#40;28&#44;6<span class="elsevierStyleHsp" style=""></span>cm&#41; tiveram valores de S &#40;feminino&#58; 76&#44;1&#37;&#59; masculino&#58; 85&#44;2&#37;&#41;&#44; E &#40;feminino&#58; 92&#44;7&#37;&#59; masculino&#58; 87&#44;6&#37;&#41; e valores preditivos &#40;feminino&#58; VPP 76&#44;1&#37;&#44; VPN 92&#44;7&#37;&#59; masculino&#58; VPP 56&#44;4&#37;&#44; VPN 97&#44;1&#37;&#41; satisfat&#243;rios &#40;<a class="elsevierStyleCrossRef" href="#fig0005">fig&#46; 1</a>&#41;&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Discuss&#227;o</span><p id="par0165" class="elsevierStylePara elsevierViewall">At&#233; o presente momento&#44; este &#233; o primeiro estudo brasileiro feito com amostra representativa de crian&#231;as que demonstrou a capacidade do PP de identificar o excesso de gordura androide&#46; Ademais&#44; o PP apresentou associa&#231;&#227;o direta com a gordura androide&#44; independentemente do sexo&#44; tipo de escola&#44; das concentra&#231;&#245;es s&#233;ricas de colesterol total e HDL&#8208;c&#44; HOMA&#8208;IR e IMC materno&#46; Ressalta&#8208;se que os pontos de corte propostos apresentaram valores de S&#44; E e valores preditivos satisfat&#243;rios&#44; viabilizaram o uso do PP em estudos epidemiol&#243;gicos&#44; triagens do risco cardiometab&#243;lico e atendimentos ambulatoriais&#46;</p><p id="par0170" class="elsevierStylePara elsevierViewall">O uso do PP em adultos &#233; amplamente estudado&#44; observou&#8208;se sua associa&#231;&#227;o direta com o tecido adiposo visceral e o HOMA&#8208;IR em obesos&#46;<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">16</span></a> Al&#233;m disso&#44; um estudo de base populacional com adultos brasileiros demonstrou que o PP pode ser usado para identificar s&#237;ndrome metab&#243;lica e resist&#234;ncia &#224; insulina&#46;<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">17</span></a></p><p id="par0175" class="elsevierStylePara elsevierViewall">Nesse sentido&#44; o uso do PP na popula&#231;&#227;o pedi&#225;trica se torna importante&#44; a maioria dos estudos com esse p&#250;blico o comparou com m&#233;todos de estimativa de adiposidade duplamente indiretos&#44; como IMC&#44;<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">18</span></a> per&#237;metro da cintura<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">19</span></a> e rela&#231;&#227;o cintura&#8208;estatura&#46;<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">20</span></a> Em indiv&#237;duos de nove a 13 anos da Gr&#233;cia&#44; o PP esteve associado diretamente &#224;s concentra&#231;&#245;es s&#233;ricas de triglicer&#237;deo e insulina&#44; HOMA&#8208;IR e press&#227;o arterial&#59; e inversamente &#224; concentra&#231;&#227;o s&#233;rica de HDL&#8208;c&#44; <span class="elsevierStyleItalic">quantitative insulin sensitivity check index</span> &#40;QUICKI&#41; e raz&#227;o glicose&#8208;insulina de jejum &#40;FGIR&#41;&#46; O mesmo estudo demonstrou que outras medidas antropom&#233;tricas usadas em crian&#231;as e adolescentes&#44; como escore&#8208;z de IMC&#44; per&#237;metro da cintura e do quadril&#44; rela&#231;&#227;o cintura&#8208;estatura e rela&#231;&#227;o cintura&#8208;quadril&#44; apresentaram associa&#231;&#245;es com os marcadores de risco cardiometab&#243;lico semelhantes ao PP&#46;<a class="elsevierStyleCrossRef" href="#bib0255"><span class="elsevierStyleSup">21</span></a></p><p id="par0180" class="elsevierStylePara elsevierViewall">O PP &#233; considerado uma op&#231;&#227;o para identificar adiposidade central por apresentar algumas vantagens em rela&#231;&#227;o ao per&#237;metro da cintura&#44; tais como&#58; boa concord&#226;ncia inter e intraobservador&#59; n&#227;o &#233; influenciado pelo hor&#225;rio de mensura&#231;&#227;o &#40;per&#237;odo pr&#233;&#8208;prandial e p&#243;s&#8208;prandial&#41;&#59; maior facilidade para mensurar&#44; pois n&#227;o requer que o examinado esteja com o m&#237;nimo de vestu&#225;rios&#44; &#233; assim mais aceit&#225;vel socialmente&#46;<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">19</span></a> Entretanto&#44; n&#227;o h&#225; um consenso internacional sobre pontos de corte a serem adotados para o p&#250;blico infantil&#46;</p><p id="par0185" class="elsevierStylePara elsevierViewall">Existem pontos de corte do PP propostos a partir de curvas ROC<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">18</span></a> e de percentis<a class="elsevierStyleCrossRef" href="#bib0260"><span class="elsevierStyleSup">22</span></a> para crian&#231;as e adolescentes de acordo com o sexo e a idade em diferentes localidades&#46; No entanto&#44; a grande maioria &#233; de pontos de corte capazes de determinar o excesso de peso&#47;obesidade pelo IMC&#46;<a class="elsevierStyleCrossRefs" href="#bib0240"><span class="elsevierStyleSup">18&#44;22</span></a> Por isso&#44; o presente estudo prop&#244;s pontos de corte de PP que podem ser usados para identificar o excesso de gordura androide pelo DXA&#44; que &#233; capaz de estimar adiposidade central&#44; &#233; um m&#233;todo considerado refer&#234;ncia&#46;<a class="elsevierStyleCrossRef" href="#bib0265"><span class="elsevierStyleSup">23</span></a></p><p id="par0190" class="elsevierStylePara elsevierViewall">Em estudo transversal com adolescentes brasileiros de Campinas&#8208;SP&#44; os pontos de corte de PP sugeridos para determinar resist&#234;ncia &#224; insulina foram de 32&#44;0 e 30&#44;3<span class="elsevierStyleHsp" style=""></span>cm para meninas e meninos pr&#233;&#8208;p&#250;beres&#44; respectivamente&#46;<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">19</span></a> Os pontos de corte propostos em estudo transversal feito por Nafiu et al&#46;<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">18</span></a> para identificar o excesso de peso em crian&#231;as americanas de oito e nove anos foram 29&#44;0 e 30&#44;5<span class="elsevierStyleHsp" style=""></span>cm &#40;meninos&#41;&#44; 27&#44;9 e 29&#44;3<span class="elsevierStyleHsp" style=""></span>cm &#40;meninas&#41;&#44; respectivamente&#44; pr&#243;ximos dos valores encontrados no nosso estudo&#46; Diante disso&#44; recomenda&#8208;se a valida&#231;&#227;o dos pontos de corte propostos no presente trabalho para outras popula&#231;&#245;es&#44; com o objetivo de identificar o excesso de adiposidade central e tamb&#233;m outros fatores de risco cardiometab&#243;lico&#46;</p><p id="par0195" class="elsevierStylePara elsevierViewall">S&#227;o de grande relev&#226;ncia estudos que abordam o excesso de adiposidade central no p&#250;blico infantil&#44; visto que as medidas antropom&#233;tricas que estimam adiposidade central apresentaram maior associa&#231;&#227;o com o risco cardiometab&#243;lico&#44; em rela&#231;&#227;o ao IMC em crian&#231;as&#46;<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">24</span></a> A gordura na regi&#227;o androide compreende o tecido adiposo visceral&#44; o qual &#233; mais lipol&#237;tico comparado com o das regi&#245;es perif&#233;ricas&#46; Observa&#8208;se maior libera&#231;&#227;o hep&#225;tica de LDL&#8208;c&#44; triglicer&#237;deos e outros &#225;cidos graxos na circula&#231;&#227;o portal&#44; est&#237;mulo da gliconeog&#234;nese hep&#225;tica e inibi&#231;&#227;o da capta&#231;&#227;o hep&#225;tica de insulina&#44; que causam hiperinsulinemia e resist&#234;ncia &#224; insulina&#46;<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">25</span></a></p><p id="par0200" class="elsevierStylePara elsevierViewall">Considerando as elevadas preval&#234;ncias de excesso de peso&#44; perfil lip&#237;dico indesejado e comportamento sedent&#225;rio nesta amostra e em outras pesquisas semelhantes&#44;<a class="elsevierStyleCrossRefs" href="#bib0280"><span class="elsevierStyleSup">26&#44;27</span></a> torna&#8208;se necess&#225;rio o diagn&#243;stico precoce do excesso de adiposidade central em crian&#231;as&#46; Sabe&#8208;se que todas essas altera&#231;&#245;es podem permanecer na fase adulta&#44; al&#233;m de estar relacionadas ao processo de aterog&#234;nese e a danos card&#237;acos&#44; que j&#225; podem iniciar na inf&#226;ncia&#46;<a class="elsevierStyleCrossRefs" href="#bib0290"><span class="elsevierStyleSup">28&#44;29</span></a> Ademais&#44; a avalia&#231;&#227;o do estado nutricional materno &#233; importante para identificar o excesso de adiposidade central em crian&#231;as&#44; visto que compartilham fatores gen&#233;ticos&#44; ambientais &#40;disponibilidade de alimentos na resid&#234;ncia&#41; e comportamentais &#40;h&#225;bitos alimentares e de estilo de vida&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0300"><span class="elsevierStyleSup">30</span></a></p><p id="par0205" class="elsevierStylePara elsevierViewall">Destaca&#8208;se como aspectos positivos deste estudo a avalia&#231;&#227;o antropom&#233;trica ter sido feita por um &#250;nico pesquisador&#44; o que contribuiu para reduzir os vieses de aferi&#231;&#227;o das medidas&#59; e a amostra ter sido composta exclusivamente por crian&#231;as&#44; o que minimiza as poss&#237;veis influ&#234;ncias hormonais da adolesc&#234;ncia na composi&#231;&#227;o corporal&#46; A an&#225;lise de curva ROC n&#227;o foi feita estratificada pela idade em fun&#231;&#227;o da semelhan&#231;a fisiol&#243;gica entre crian&#231;as de oito e nove anos&#46; Apesar de o DXA ser incapaz de distinguir os tipos de tecido adiposo&#44; a gordura na regi&#227;o androide obtida nesse exame est&#225; fortemente correlacionada ao tecido adiposo visceral em crian&#231;as&#46; Como limita&#231;&#245;es&#44; nota&#8208;se a aus&#234;ncia de valores de refer&#234;ncia para classificar a gordura androide em crian&#231;as&#44; o que nos permitiu usar o percentil 85<span class="elsevierStyleHsp" style=""></span>da amostra de acordo com o sexo&#46; Diante disso&#44; sugerimos estudos que proponham pontos de corte de gordura na regi&#227;o androide e de PP para todas as faixas et&#225;rias infantis&#44; com o prop&#243;sito de se estabelecer um consenso internacional&#46;</p><p id="par0210" class="elsevierStylePara elsevierViewall">Conclu&#237;mos que o PP &#233; uma medida capaz de identificar o excesso de gordura androide em crian&#231;as brasileiras&#46; Os pontos de corte propostos podem ser usados em estudos populacionais&#44; triagens e atendimentos ambulatoriais&#44; desde que sejam validados para o p&#250;blico infantil em que ser&#227;o aplicados&#46; Dessa maneira&#44; o PP pode fazer parte da rotina de avalia&#231;&#227;o do estado de sa&#250;de de crian&#231;as&#44; por ser uma medida simples e de baixo custo&#44; auxilia na identifica&#231;&#227;o precoce do excesso de adiposidade central&#46;</p></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Financiamento</span><p id="par0215" class="elsevierStylePara elsevierViewall">Conselho Nacional de Desenvolvimento Cient&#237;fico e Tecnol&#243;gico &#40;CNPq&#41; &#40;processo&#58; 478910&#47;2013&#8208;4&#41;&#46;</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Conflitos de interesse</span><p id="par0220" class="elsevierStylePara elsevierViewall">Os autores declaram n&#227;o haver conflitos de interesse&#46;</p></span></span>"
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            2 => "Risk factors"
            3 => "Nutritional assessment"
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            1 => "Antropometria"
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        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Objective</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">To evaluate the ability of neck circumference to identify excess android fat and to propose cutoff points for Brazilian children&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Method</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">This was a cross&#8208;sectional study with 376 children aged 8 and 9 years enrolled in public and private schools in the urban area of the municipality of Vi&#231;osa&#44; Minas Gerais&#46; A semi&#8208;structured questionnaire containing sociodemographic and lifestyle information was applied&#46; The following were collected&#58; neck circumference&#44; weight&#44; and height for the calculation of body mass index&#46; The percentage of fat in the android region was determined by dual energy X&#8208;ray absorptiometry&#46; Linear regression analysis was used to evaluate the association between neck circumference and android fat&#44; adopting a significance level of 5&#37;&#46; Receiver operating characteristic curves were used to evaluate the capacity of neck circumference to determine the excess android fat&#44; as well as to estimate the cutoff points of neck circumference according to gender&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Multiple linear regression showed an association between neck circumference and android fat &#40;<span class="elsevierStyleItalic">&#946;</span>&#58; 2&#46;94&#44; 95&#37; CI&#58; 2&#46;41&#44; 3&#46;47&#41;&#46; Neck circumference was able to identify excess android fat in girls &#40;AUC&#58; 0&#46;909&#44; 95&#37; CI&#58; 0&#46;999&#44; 0&#46;945&#41; and boys &#40;AUC&#58; 0&#46;938&#44; 95&#37; CI&#58; 0&#46;892&#44; 0&#46;968&#41;&#46; The proposed cutoff points showed satisfactory sensitivity&#44; specificity&#44; and predictive values&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Neck circumference is capable of identifying excess android fat in children and can be used in clinical practice and in population studies to determine central adiposity&#46; The proposed cutoff points were satisfactory&#44; but should be validated for other populations&#46;</p></span>"
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        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Objetivo</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Avaliar a capacidade do per&#237;metro do pesco&#231;o em identificar o excesso de gordura androide e propor pontos de corte para crian&#231;as brasileiras&#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 transversal com 376 crian&#231;as de oito e nove anos&#44; matriculadas em escolas p&#250;blicas e privadas da &#225;rea urbana de Vi&#231;osa&#44; Minas Gerais&#46; Foi aplicado um question&#225;rio semiestruturado com informa&#231;&#245;es sociodemogr&#225;ficas e de estilo de vida&#46; Foram coletados&#58; per&#237;metro do pesco&#231;o&#44; peso e estatura para o c&#225;lculo do &#237;ndice de massa corporal&#46; O percentual de gordura na regi&#227;o androide foi determinado pela absorciometria de raios X de dupla energia&#46; A an&#225;lise de regress&#227;o linear foi utilizada para avaliar a associa&#231;&#227;o entre o per&#237;metro do pesco&#231;o e a gordura androide&#44; adotando-se o n&#237;vel de signific&#226;ncia de 5&#37;&#46; Por meio das curvas <span class="elsevierStyleItalic">Receiver Operating Characteristic</span> avaliou&#8208;se a capacidade do per&#237;metro do pesco&#231;o de determinar o excesso de gordura androide&#44; bem como estimaram&#8208;se os pontos de corte de per&#237;metro do pesco&#231;o segundo o sexo&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">A regress&#227;o linear m&#250;ltipla demonstrou associa&#231;&#227;o entre o per&#237;metro do pesco&#231;o e a gordura androide &#40;&#946;&#58; 2&#44;94&#59; IC95&#37;&#58; 2&#44;41&#59; 3&#44;47&#41;&#46; O per&#237;metro do pesco&#231;o foi capaz de identificar o excesso de gordura androide em meninas &#40;AUC&#58; 0&#44;909&#59; IC95&#37;&#58; 0&#44;859&#59; 0&#44;945&#41; e meninos &#40;AUC&#58; 0&#44;938&#59; IC95&#37;&#58; 0&#44;892&#59; 0&#44;968&#41;&#46; Os pontos de corte propostos tiveram valores de sensibilidade&#44; especificidade e preditivos satisfat&#243;rios&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclus&#245;es</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">O per&#237;metro do pesco&#231;o &#233; uma medida capaz de identificar o excesso de gordura androide em crian&#231;as&#44; pode ser usado na pr&#225;tica cl&#237;nica e em estudos populacionais para determinar a adiposidade central&#46; Os pontos de corte propostos foram satisfat&#243;rios&#44; entretanto devem ser validados para outras popula&#231;&#245;es&#46;</p></span>"
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        "nota" => "<p class="elsevierStyleNotepara" id="npar0025">Como citar este artigo&#58; Filgueiras MS&#44; Albuquerque FM&#44; Castro AP&#44; Rocha NP&#44; Milagres LC&#44; Novaes JF&#46; Neck circumference cutoff points to identify excess android fat&#46; J Pediatr &#40;Rio J&#41;&#46; 2020&#59;96&#58;356&#8211;63&#46;</p>"
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          "pt" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">&#193;reas abaixo da curva <span class="elsevierStyleItalic">Receiver Operating Characteristic</span> &#40;ROC&#41; e pontos de corte do per&#237;metro do pesco&#231;o com melhores valores de sensibilidade&#44; especificidade e valores preditivos para excesso de gordura androide&#44; de acordo com o sexo&#46; Vi&#231;osa&#44; MG&#44; 2015&#46;</p> <p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">AUC&#44; <span class="elsevierStyleItalic">area under the curve</span>&#59; IC95&#37;&#44; intervalo de confian&#231;a de 95&#37;&#59; S&#44; sensibilidade&#59; E&#44; especificidade&#59; VPP&#44; valor preditivo positivo&#59; VPN&#44; valor preditivo negativo&#46;</p>"
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          "leyenda" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">HDL&#8208;c&#44; <span class="elsevierStyleItalic">high density lipoprotein</span>&#59; HOMA&#8208;IR&#44; <span class="elsevierStyleItalic">Homeostatic Model Assessment for Insulin Resistance</span>&#59; LDL&#8208;c&#44; <span class="elsevierStyleItalic">low density lipoprotein</span>&#46;</p><p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Dados apresentados em m&#233;dia &#40;desvio&#8208;padr&#227;o&#41; ou mediana &#40;intervalo interquartil&#41;&#46;</p>"
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                  \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">Vari&#225;vel&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">n &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \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">Per&#237;metro do pesco&#231;o &#40;cm&#41;&nbsp;\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">Gordura androide &#40;&#37;&#41;&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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                  \t\t\t\t">Total&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">14&#44;9 &#40;7&#44;1&#59; 26&#44;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Feminino&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">196 &#40;52&#44;1&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">26&#44;7 &#40;25&#44;5&#59; 28&#44;1&#41;&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">17&#44;1 &#40;8&#44;6&#59; 20&#44;0&#41;&nbsp;\t\t\t\t\t\t\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>Masculino&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">180 &#40;47&#44;9&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">27&#44;4 &#40;26&#44;4&#59; 28&#44;5&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">9&#44;7 &#40;5&#44;9&#59; 22&#44;7&#41;&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>p&#8208;valor&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">0&#44;001<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">d</span></a>&nbsp;\t\t\t\t\t\t\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">&#60;<span class="elsevierStyleHsp" style=""></span>0&#44;001<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">d</span></a>&nbsp;\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"><span class="elsevierStyleVsp" style="height:0.5px"></span></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
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                  \t\t\t\t"><span class="elsevierStyleItalic">Idade</span></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
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>8 anos&nbsp;\t\t\t\t\t\t\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">182 &#40;48&#44;4&#41;&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">26&#44;6 &#40;25&#44;5&#59; 28&#44;0&#41;&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">13&#44;1 &#40;6&#44;8&#59; 23&#44;9&#41;&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>9 anos&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">194 &#40;51&#44;6&#41;&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">27&#44;5 &#40;26&#44;2&#59; 28&#44;5&#41;&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">16&#46;30 &#40;7&#44;8&#59; 27&#44;8&#41;&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>p&#8208;valor&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="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&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  " align="left" valign="\n
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                  \t\t\t\t">&#60;<span class="elsevierStyleHsp" style=""></span>0&#44;001<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">d</span></a>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">0&#44;101&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
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                  \t\t\t\t  " colspan="4" align="left" valign="\n
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                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\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"><span class="elsevierStyleHsp" style=""></span>P&#250;blica&nbsp;\t\t\t\t\t\t\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">266 &#40;70&#44;7&#41;&nbsp;\t\t\t\t\t\t\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">27&#44;2 &#40;2&#44;0&#41;&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">12&#44;5 &#40;6&#44;9&#59; 25&#44;7&#41;&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
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Privada&nbsp;\t\t\t\t\t\t\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">110 &#40;29&#44;3&#41;&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">27&#44;4 &#40;1&#44;9&#41;&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">19&#44;3 &#40;8&#44;7&#59; 27&#44;1&#41;&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>p&#8208;valor&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#44;448&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#44;018<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">d</span></a>&nbsp;\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"><span class="elsevierStyleVsp" style="height:0.5px"></span></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"><span class="elsevierStyleItalic">Renda per capita</span></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>&#8805; R&#36;500&#44;00&nbsp;\t\t\t\t\t\t\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">191 &#40;50&#44;8&#41;&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">27&#44;4 &#40;1&#44;9&#41;&nbsp;\t\t\t\t\t\t\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">17&#44;0 &#40;7&#44;3&#59; 27&#44;2&#41;&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>&#60;<span class="elsevierStyleHsp" style=""></span>R&#36;500&#44;00&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">185 &#40;49&#44;2&#41;&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">27&#44;1 &#40;2&#44;0&#41;&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">12&#44;8 &#40;7&#44;1&#59; 24&#44;6&#41;&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>p&#8208;valor&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="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#44;085&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
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                  \t\t\t\t">0&#44;115&nbsp;\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
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                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></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"><span class="elsevierStyleItalic">Tempo de tela&#47;dia</span></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>&#62; 2 horas&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">178 &#40;47&#44;3&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">27&#44;3 &#40;26&#44;0&#59; 28&#44;5&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">15&#44;5 &#40;7&#44;3&#59; 27&#44;1&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>&#8804; 2 horas&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">198 &#40;52&#44;7&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">27&#44;0 &#40;25&#44;7&#59; 28&#44;1&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">13&#44;2 &#40;7&#44;1&#59; 25&#44;6&#41;&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>p&#8208;valor&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  " align="" valign="\n
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                  \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">0&#44;119&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#44;377&nbsp;\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"><span class="elsevierStyleVsp" style="height:0.5px"></span></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"><span class="elsevierStyleItalic">Excesso de peso</span></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>Sim&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">123 &#40;32&#44;7&#41;&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">29&#44;2 &#40;1&#44;6&#41;&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
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                  \t\t\t\t">31&#44;3 &#40;9&#44;7&#41;&nbsp;\t\t\t\t\t\t\n
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                  \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>N&#227;o&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  " align="left" valign="\n
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                  \t\t\t\t">253 &#40;67&#44;3&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">26&#44;3 &#40;1&#44;2&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">11&#44;1 &#40;6&#44;7&#41;&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">p&#8208;valor&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="" valign="\n
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                  \t\t\t\t">&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;<span class="elsevierStyleHsp" style=""></span>0&#44;001<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\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
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                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></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"><span class="elsevierStyleItalic">Per&#237;metro do pesco&#231;o</span><a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a></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>Aumentado&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">76 &#40;20&#44;2&#41;&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
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                  \t\t\t\t">29&#44;9 &#40;29&#44;0&#59; 31&#44;0&#41;&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
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                  \t\t\t\t">32&#44;7 &#40;25&#44;3&#59; 39&#44;3&#41;&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>Adequado&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">300 &#40;79&#44;8&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">26&#44;5 &#40;25&#44;5&#59; 27&#44;5&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">10&#44;5 &#40;6&#44;2&#59; 19&#44;8&#41;&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
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                  \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>p&#8208;valor&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="" valign="\n
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                  \t\t\t\t">&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8208;&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">&#60;<span class="elsevierStyleHsp" style=""></span>0&#44;001<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">d</span></a>&nbsp;\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
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                  \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"><span class="elsevierStyleItalic">Gordura androide</span><a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a></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>&#8805; p85&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">73 &#40;19&#44;4&#41;&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
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                  \t\t\t\t">29&#44;5 &#40;28&#44;5&#59; 30&#44;9&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">35&#44;9 &#40;32&#44;2&#59; 43&#44;3&#41;&nbsp;\t\t\t\t\t\t\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>&#60;<span class="elsevierStyleHsp" style=""></span>p85&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">303 &#40;80&#44;6&#41;&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
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                  \t\t\t\t">26&#44;5 &#40;25&#44;5&#59; 27&#44;7&#41;&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">10&#44;5 &#40;6&#44;3&#59; 18&#44;6&#41;&nbsp;\t\t\t\t\t\t\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>p&#8208;valor&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="" valign="\n
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                  \t\t\t\t">&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;<span class="elsevierStyleHsp" style=""></span>0&#44;001<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">d</span></a>&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8208;&nbsp;\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"><span class="elsevierStyleVsp" style="height:0.5px"></span></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"><span class="elsevierStyleItalic">Excesso de peso materno</span></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>Sim&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">168 &#40;57&#44;3&#41;&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">27&#44;8 &#40;2&#44;0&#41;&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">18&#44;3 &#40;8&#44;4&#59; 30&#44;8&#41;&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>N&#227;o&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">125 &#40;42&#44;7&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">26&#44;5 &#40;1&#44;8&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">11&#44;0 &#40;6&#44;2&#59; 19&#44;9&#41;&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
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                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>p&#8208;valor&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\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">&#60;<span class="elsevierStyleHsp" style=""></span>0&#44;001<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;<span class="elsevierStyleHsp" style=""></span>0&#44;001<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">d</span></a>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " colspan="4" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></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
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                  \t\t\t\t"><span class="elsevierStyleItalic">Colesterol total</span></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>&#8805; 170 mg&#47;dL&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">86 &#40;22&#44;9&#41;&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">27&#44;5 &#40;1&#44;9&#41;&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  " align="left" valign="\n
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                  \t\t\t\t">20&#44;5 &#40;7&#44;5&#59; 29&#44;4&#41;&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>&#60;<span class="elsevierStyleHsp" style=""></span>170 mg&#47;dL&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">289 &#40;77&#44;1&#41;&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  " align="left" valign="\n
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                  \t\t\t\t">27&#44;2 &#40;1&#44;9&#41;&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">12&#44;8 &#40;7&#44;1&#59; 24&#44;1&#41;&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>p&#8208;valor&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="" valign="\n
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                  \t\t\t\t">&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#44;278&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#44;011<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">d</span></a>&nbsp;\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"><span class="elsevierStyleVsp" style="height:0.5px"></span></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"><span class="elsevierStyleItalic">HDL&#8208;c</span></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>&#8804; 45 mg&#47;dL&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">131 &#40;34&#44;9&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">27&#44;6 &#40;2&#44;1&#41;&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">18&#44;4 &#40;8&#44;0&#59; 32&#44;1&#41;&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>&#62; 45 mg&#47;dL&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">244 &#40;65&#44;1&#41;&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">27&#44;1 &#40;1&#44;8&#41;&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  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">12&#44;9 &#40;6&#44;9&#59; 23&#44;0&#41;&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
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                  \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>p&#8208;valor&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  " align="" valign="\n
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                  \t\t\t\t">&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#44;006<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&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  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#44;005<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">d</span></a>&nbsp;\t\t\t\t\t\t\n
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                  \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"><span class="elsevierStyleVsp" style="height:0.5px"></span></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"><span class="elsevierStyleItalic">LDL&#8208;c</span></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>&#8805; 110 mg&#47;dL&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">58 &#40;15&#44;5&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">27&#44;7 &#40;1&#44;9&#41;&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  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">22&#44;0 &#40;12&#44;8&#41;&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>&#60;<span class="elsevierStyleHsp" style=""></span>110 mg&#47;dL&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">316 &#40;84&#44;5&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">27&#44;2 &#40;1&#44;9&#41;&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">16&#44;8 &#40;12&#44;0&#41;&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>p&#8208;valor&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="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&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">0&#44;064&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#44;003<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
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                  \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"><span class="elsevierStyleVsp" style="height:0.5px"></span></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"><span class="elsevierStyleItalic">Triglicer&#237;deo</span></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>&#8805; 75 mg&#47;dL&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">176 &#40;46&#44;9&#41;&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  " align="left" valign="\n
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                  \t\t\t\t">27&#44;7 &#40;2&#44;1&#41;&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">19&#44;9 &#40;8&#44;2&#59; 30&#44;7&#41;&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>&#60;<span class="elsevierStyleHsp" style=""></span>75 mg&#47;dL&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">199 &#40;53&#44;1&#41;&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  " align="left" valign="\n
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                  \t\t\t\t">26&#44;9 &#40;1&#44;7&#41;&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">10&#44;6 &#40;6&#44;5&#59; 19&#44;8&#41;&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>p&#8208;valor&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="" valign="\n
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                  \t\t\t\t">&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;<span class="elsevierStyleHsp" style=""></span>0&#44;001<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;<span class="elsevierStyleHsp" style=""></span>0&#44;001<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">d</span></a>&nbsp;\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"><span class="elsevierStyleVsp" style="height:0.5px"></span></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
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                    0 => array:2 [
                      "titulo" => "Worldwide trends in body&#8208;mass index&#44; underweight&#44; overweight&#44; and obesity from 1975 to 2016&#58; a pooled analysis of 2416 population&#8208;based measurement studies in 128&#46; 9 million children&#44; adolescents&#44; and adults"
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Informação do artigo

ISSN: 22555536
Idioma original: Português

DOI:10.1016/j.jpedp.2019.02.001

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