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"apellidos" => "Ribeiro" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 4 => array:3 [ "nombre" => "Helen H.M." "apellidos" => "Hermsdorff" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 5 => array:3 [ "nombre" => "Patrícia F." "apellidos" => "Pereira" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 6 => array:3 [ "nombre" => "Silvia E." "apellidos" => "Priore" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 7 => array:3 [ "nombre" => "Sylvia C.C." "apellidos" => "Franceschini" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] ] "afiliaciones" => array:2 [ 0 => array:3 [ "entidad" => "Universidade Federal de Viçosa (UFV), Viçosa, MG, Brazil" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Universidade Federal de Viçosa (UFV), Departamento de Nutrição e Saúde, Viçosa, MG, Brazil" "etiqueta" => "b" "identificador" => "aff0010" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "pt" => array:1 [ "titulo" => "Ponto de corte do índice TyG e sua associação com a adiposidade corporal e estilo de vida em crianças" ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Metabolic syndrome (MS), characterized by the concomitant presence of insulin resistance (IR) and other metabolic alterations, such as obesity, dyslipidemias and arterial hypertension, has been shown to be highly prevalent in children, especially in those with excess body fat.<a class="elsevierStyleCrossRefs" href="#bib0155"><span class="elsevierStyleSup">1,2</span></a> This syndrome is known to be associated with a higher risk of developing cardiovascular diseases and tends to persist into adulthood, but its definition in children remains controversial.<a class="elsevierStyleCrossRefs" href="#bib0160"><span class="elsevierStyleSup">2,3</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">IR, the main indicator used in the diagnosis of MS, is characterized by reduced glucose uptake by the cells for a given insulin concentration. This syndrome has been identified as a public health problem, including in childhood.<a class="elsevierStyleCrossRefs" href="#bib0160"><span class="elsevierStyleSup">2,4</span></a> Studies have shown a strong association between IR and excess body adiposity, mainly in the central region, since the accumulation of intramuscular lipids from the entry of long-chain fatty acid into the cells inhibits the translocation of the glucose transporter (GLUT-4), reducing glucose uptake by the cells, which favors peripheral resistance to insulin action.<a class="elsevierStyleCrossRefs" href="#bib0170"><span class="elsevierStyleSup">4,5</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">There are several methods for the diagnosis of IR, but biomolecular evaluations of insulin receptors and post-receptors and the euglycemic-hyperinsulinemic clamp test, considered the “gold standard,” are expensive and not easily accessible for most of the population.<a class="elsevierStyleCrossRefs" href="#bib0180"><span class="elsevierStyleSup">6,7</span></a> The Homeostasis Model Assessment (HOMA) method has been widely used in studies for the diagnosis of IR and has been validated for children.<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">8</span></a> However, to calculate the HOMA index, it is necessary to measure serum insulin levels, which in most cases is not part of the routine assessment in the health services, especially in the pediatric population, which makes it difficult to use this index for identification of IR in this population.</p><p id="par0020" class="elsevierStylePara elsevierViewall">Recently, the TyG index (the product of the serum triglyceride concentration and fasting glycemia) has been used in studies to evaluate IR in adults<a class="elsevierStyleCrossRefs" href="#bib0185"><span class="elsevierStyleSup">7,9,10</span></a> and adolescents,<a class="elsevierStyleCrossRefs" href="#bib0160"><span class="elsevierStyleSup">2,11</span></a> demonstrating good discriminatory power for the diagnosis of IR.</p><p id="par0025" class="elsevierStylePara elsevierViewall">No studies were identified that tested the TyG index in preschoolers and schoolchildren. Moreover, there was a scarcity of studies evaluating factors other than adiposity that may be associated with IR in children, such as dietary patterns and lifestyle. With the identification of the factors associated with IR in childhood, early intervention can be undertaken, aimed to reduce the risk of cardiovascular diseases throughout life and, consequently, reducing public health expenditures.</p><p id="par0030" class="elsevierStylePara elsevierViewall">Considering these facts, the aim of this study was to investigate the factors associated with IR in children aged 3–7 years and to identify the TyG index cutoff point used for IR prediction in this population.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Design and sample</span><p id="par0035" class="elsevierStylePara elsevierViewall">This was a cross-sectional study, conducted with children from a retrospective birth cohort at the only maternity hospital in the municipality of Viçosa, state of Minas Gerais, Brazil. The children were followed by the Lactation Support Program (Programa de Apoio à Lactação [PROLAC]) during the first year of life and were reassessed at age of 4–7 years. PROLAC is a program of Universidade Federal de Viçosa in partnership with the Human Milk Bank of the municipality. Its main activities are providing guidance to mothers in the postpartum period with the aim to promote breastfeeding, as well as nutritional care for children in their first year of life and for their mothers.</p><p id="par0040" class="elsevierStylePara elsevierViewall">Based on information collected from the PROLAC care records and considering two inclusion criteria (presence of identification data that allowed locating the children and date of birth compatible with age between 4 and 7 years at the time of the study), 669 children were considered eligible for the study. Among those considered eligible to participate, 176 were not located (change of address) after at least three attempts to locate the children through home visits, 75 were not authorized by parents/guardians to participate or did not complete all stages of the study, and eight had problems that prevented their participation. Moreover, eight children were excluded as they had incomplete food consumption data and/or biochemical tests. Thus, the present study sample consisted of 402 children.</p><p id="par0045" class="elsevierStylePara elsevierViewall">The study was approved by the Human Research Ethics Committee of Universidade Federal de Viçosa (Ref. No. 892476/2014) and the norms regulating research involving human beings were adopted, according to the National Health Council (resolution No. 466/2012). The parents or guardians of all children included in the study signed the Informed Consent.</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Body adiposity</span><p id="par0050" class="elsevierStylePara elsevierViewall">The adiposity indicators evaluated were body mass index (BMI) and total body fat, which estimate total adiposity; and the waist-to-height ratio (WHtR) and central fat, which estimate the risk associated with abdominal adiposity.</p><p id="par0055" class="elsevierStylePara elsevierViewall">Weight was measured on an electronic digital scale with a capacity of 150<span class="elsevierStyleHsp" style=""></span>kg and accuracy of 10<span class="elsevierStyleHsp" style=""></span>g, whereas height was measured with a vertical stadiometer fixed to the wall, with a 2-m extension, divided in centimeters and subdivided in millimeters. BMI for age (BMI/A) was calculated as <span class="elsevierStyleItalic">Z</span>-score according to gender, using the World Health Organization reference.<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">12</span></a></p><p id="par0060" class="elsevierStylePara elsevierViewall">Waist circumference was measured at the level of the umbilicus, using a 2-m flexible and inelastic measuring tape, divided into centimeters and subdivided into millimeters. The measurements were performed in triplicate, with the two closest ones being used to calculate the mean. The waist-to-height ratio (WHtR) was calculated based on the ratio of the waist circumference (cm) and the height (cm), considering risk values those >0.5.<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">13</span></a></p><p id="par0065" class="elsevierStylePara elsevierViewall">Body composition assessment was performed using dual energy X-ray absorptiometry (DXA), and the results of the percentage of total and central fat were used for the analyses. All evaluations were performed at the UFV Health Department.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Insulin resistance (IR)</span><p id="par0070" class="elsevierStylePara elsevierViewall">Blood collection was performed at the clinical analysis laboratory of the Health Department of the UFV, after a 12-h fast. Serum triglyceride and fasting blood glucose levels were measured. Additionally, fasting insulin was evaluated in a subsample of study children (35%, <span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>141).</p><p id="par0075" class="elsevierStylePara elsevierViewall">To evaluate insulin resistance (IR), the TyG index was calculated as: ln[fasting triglycerides (mg/dL)<span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>fasting glucose (mg/dL)/2].<a class="elsevierStyleCrossRefs" href="#bib0195"><span class="elsevierStyleSup">9,11</span></a> The IR estimate was also obtained in a subsample of 141 children through the Homeostasis Model Assessment for Insulin Resistance (HOMA-IR), which is the product of fasting insulin (μU/mL) and fasting glycemia (mmol/L), divided by 22.5.<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">14</span></a> Insulin resistance was defined when the HOMA-IR value was higher than the 90th percentile of the sample.<a class="elsevierStyleCrossRefs" href="#bib0155"><span class="elsevierStyleSup">1,4</span></a> This method was adopted as the reference to determine the TyG index cutoff point.</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Dietary patterns</span><p id="par0080" class="elsevierStylePara elsevierViewall">To evaluate study children's food intake, parents or guardians were asked to complete three food records on non-consecutive days, one of which was during the weekend. All records were checked and reviewed by the investigators, along with parents/guardians, to reduce reporting biases. The data were entered and processed using a software (Dietpro<span class="elsevierStyleSup">®</span> software, version 5i, MG, Brazil).</p><p id="par0085" class="elsevierStylePara elsevierViewall">In the identification of food patterns, an <span class="elsevierStyleItalic">a posteriori</span> statistical method was applied through principal component analysis (PCA). Before PCA was performed, sample size adequacy and analysis applicability were evaluated, estimating the Kaiser–Meyer–Olkin coefficient (KMO<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.561) and the Bartlett sphericity test (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001). For a better interpretation of the factors, varimax orthogonal rotation was applied, and the number of factors/components to be retained was determined based on the plot of Cattell's scree test.</p><p id="par0090" class="elsevierStylePara elsevierViewall">Foods/groups with factorial loads<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>≥0.25 were considered strongly associated with the component, providing better information for the identification of a food pattern. For pattern denomination, the characteristics of the foods/groups that contributed the most to each component were considered, as well as the nomenclatures used in other studies.<a class="elsevierStyleCrossRefs" href="#bib0225"><span class="elsevierStyleSup">15,16</span></a></p><p id="par0095" class="elsevierStylePara elsevierViewall">After the identification of the dietary patterns, the factor scores were calculated for each child in the study; thus, each one had a factorial score in all identified patterns.</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Socio-demographic, lifestyle, and breastfeeding variables</span><p id="par0100" class="elsevierStylePara elsevierViewall">A semi-structured questionnaire was applied to the child's parent/guardian to obtain sociodemographic information, such as age and <span class="elsevierStyleItalic">per capita</span> income. The information on life habits was obtained by applying a questionnaire adapted from Andaki.<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">17</span></a> The assessed variables were: daily screen time (television, computer, games) and daily time spent in active activities (running, cycling, playing ball). Data on exclusive breastfeeding time (EBF) were obtained from the PROLAC records.</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Data analysis</span><p id="par0105" class="elsevierStylePara elsevierViewall">Descriptive analysis of the data was performed through measures of frequency distribution, central tendency, and dispersion. The distribution of variables was assessed using the Shapiro–Wilks normality test.</p><p id="par0110" class="elsevierStylePara elsevierViewall">Linear regression was used to investigate the factors associated with IR in the study children, estimating the regression coefficient and the confidence interval. In the bivariate analysis, variables with a value of <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.20 were considered for inclusion in the multiple model. The analyses were performed using a software (Stata Statistical Software: Release 13. College Station, TX, USA) and the statistical significance considered was <span class="elsevierStyleItalic">α</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>5%.</p><p id="par0115" class="elsevierStylePara elsevierViewall">To identify the TyG index cutoff point for IR prediction in the study children, the receiver operating characteristic (ROC) curve was analyzed, considering the cutoff point with the best balance between sensitivity and specificity values. HOMA-IR was the reference method used for identification of the TyG index cutoff point. The analysis of the ROC curve was performed using a software (MedCalc<span class="elsevierStyleSup">®</span> software, Belgium).</p></span></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Results</span><p id="par0120" class="elsevierStylePara elsevierViewall">Most study children were males (55%), with a median age of 73 months. There was no difference in TyG index between genders (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.355). The prevalence of excess weight (overweight or obesity) and alterations in the WHtR index was 25.6% and 26.8%, respectively (data not shown).</p><p id="par0125" class="elsevierStylePara elsevierViewall">As for food consumption, five food patterns were identified among the study children through the PCA, which explained 42.3% of the data variance (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>). The food patterns were called “Traditional” (consisting of foods/preparations typical of Brazilian food, such as: white rice, beans, vegetables, roots, porridge and flour, and meats, fish, and eggs); “Unhealthy” (represented mainly by foods/groups with high sugar and fat content: artificial juice and soft drinks, fried foods, snacks, processed meats, sweets and cream-filled cookies); “Milk and chocolate milk” (mainly represented by milk and dairy products and chocolate powder); “Snacks” (consisting mainly of typical bakery foods: breads, cakes and cookies, butter and margarine, coffee and teas); “Healthy” (natural juice, fruits, vegetables, and broth/soups).</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0130" class="elsevierStylePara elsevierViewall">In the simple linear regression analysis, it was observed that the higher adherence to the “Unhealthy” food pattern was positively associated with the TyG index; as for the daily time spent in active activities, it was negatively associated with the index; that is, the less active the child, the higher the TyG value. Moreover, with each increase of one unit in the four indicators of body adiposity assessed, the higher the TyG values observed in the study children (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>).</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0135" class="elsevierStylePara elsevierViewall">In the multiple model, the variables that remained independently associated with the TyG index were variables of daily time spent in active activities and body adiposity. The lower the daily time spent in active activities, the higher the TyG value; and increase in BMI, WHtR, percentage of total, and central fat was positively associated with TyG (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>).</p><p id="par0140" class="elsevierStylePara elsevierViewall">Of the TyG index cutoff points tested to predict IR in the study children, the best balance between the sensitivity (S) and specificity (Sp) values was 7.88 (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>). Considering this cutoff point, the prevalence of IR in the study children was 42.3% (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>170).</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Discussion</span><p id="par0145" class="elsevierStylePara elsevierViewall">In this study, conducted with children aged 4–7 years from a retrospective cohort, it was observed that the increase in total and central body adiposity and a shorter daily time spent in active activities were positively associated with IR, evaluated by the TyG index. The association between adiposity and IR has been described in other studies with children<a class="elsevierStyleCrossRefs" href="#bib0165"><span class="elsevierStyleSup">3,18,19</span></a>; however, methodological differences, mainly regarding the method used and the cutoff points for the diagnosis of IR, make it difficult to compare the results.</p><p id="par0150" class="elsevierStylePara elsevierViewall">A recent study carried out with Japanese schoolchildren found that increased abdominal adiposity, as assessed by the WHtR, was associated with an increased prevalence of IR, detected by the HOMA index.<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">20</span></a> Nightingale et al.<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">18</span></a> performed a study of children from different regions of the world, and similar to the present study, evaluated body and central adiposity according to different indicators. The authors observed a positive association between all indicators of adiposity and IR, when evaluated by the HOMA index.</p><p id="par0155" class="elsevierStylePara elsevierViewall">In Brazil, Ferreira et al.<a class="elsevierStyleCrossRef" href="#bib0155"><span class="elsevierStyleSup">1</span></a> carried out a cross-sectional study with children and adolescents aged 7–11 years, and found that BMI was positively associated with IR, as assessed by the HOMA index. The present authors did not identify any national studies that evaluated IR only in children (younger than 10 years), without including adolescents; they understand the importance of studying metabolic alterations in prepubertal children, without including those already at puberty, in which the effects of steroid hormones can be already observed. Mainly in relation to IR and MS frequency, there is evidence that they increase with puberty.<a class="elsevierStyleCrossRef" href="#bib0255"><span class="elsevierStyleSup">21</span></a></p><p id="par0160" class="elsevierStylePara elsevierViewall">Peplies et al.,<a class="elsevierStyleCrossRef" href="#bib0260"><span class="elsevierStyleSup">22</span></a> in a longitudinal study carried out with children aged 3–10 years living in eight European countries, found a positive association between body adiposity (assessed by BMI and waist circumference), sedentary behavior, and presence of IR. These findings corroborate those observed in the present study, when, after adjusting for other variables, the longer daily time spent in active activities was associated with lower TyG index values.</p><p id="par0165" class="elsevierStylePara elsevierViewall">Sedentary behavior, which is increasingly observed among children, has been considered an important behavioral risk factor for the development of metabolic alterations, such as IR and dyslipidemia.<a class="elsevierStyleCrossRefs" href="#bib0260"><span class="elsevierStyleSup">22,23</span></a> Thus, it is crucial to encourage in regular physical activity practice and discourage sedentary behavior at this phase.</p><p id="par0170" class="elsevierStylePara elsevierViewall">The prevalence of excess weight (as measured by BMI) and central adiposity (when using the WHtR) were high in the study children, around 25%, similar to that observed in other studies with a similar age group<a class="elsevierStyleCrossRefs" href="#bib0230"><span class="elsevierStyleSup">16,24</span></a> and also according to the Family Budget Survey carried out in Brazil, where the prevalence of excess weight in boys and girls aged 5–9 years was 34.8% and 32.0%, respectively.<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">25</span></a> In children, obesity, especially abdominal obesity, seems to be an important trigger for insulin resistance,<a class="elsevierStyleCrossRef" href="#bib0280"><span class="elsevierStyleSup">26</span></a> which makes obese children a risk group for metabolic alterations, reinforcing the need to define clinical and laboratory indicators for diagnosis in this group.<a class="elsevierStyleCrossRef" href="#bib0285"><span class="elsevierStyleSup">27</span></a> Studies have shown that the combination of BMI and waist circumference improved the prediction of cardiometabolic risk factors in children.<a class="elsevierStyleCrossRefs" href="#bib0260"><span class="elsevierStyleSup">22,28</span></a> Thus, for an early and more reliable diagnosis of adiposity alterations in children, more than one indicator should be used whenever possible.</p><p id="par0175" class="elsevierStylePara elsevierViewall">In the bivariate analysis, the “Unhealthy” dietary pattern was positively associated with the TyG index; that is, children with a higher intake of foods rich in simple sugars and fat had a higher risk of IR. However, after adjusting for lifestyle and adiposity variables, this association was not maintained, due to the strong association between body adiposity and IR. As in the present study, Peplies et al.<a class="elsevierStyleCrossRef" href="#bib0260"><span class="elsevierStyleSup">22</span></a> also found no association between the consumption of sugar-rich foods and IR in children (assessed by the HOMA index) after adjustment for nutritional status. However, it is a consensus that the adoption of a healthy dietary pattern, characterized by the consumption of fruits, vegetables, lean meats, and low intake of sugars and fats, is a determining factor for a lower risk of chronic diseases such as obesity, metabolic syndrome, and cardiovascular diseases. This beneficial effect can be explained, at least in part, by the diet's modulating role on biomarkers of insulin sensitivity and atherogenesis, as well as inflammation and endothelial function.<a class="elsevierStyleCrossRefs" href="#bib0295"><span class="elsevierStyleSup">29,30</span></a></p><p id="par0180" class="elsevierStylePara elsevierViewall">Another relevant result of the study is the cutoff point established for children aged 4–7 years. In the ROC curve analysis, the AUC of 63% indicated a moderate accuracy of the TyG index to identify IR among the study children. However, it is noteworthy that there is no consensus regarding the use of the HOMA index (reference method used) in the assessed age group, especially in relation to the best cutoff point to be used,<a class="elsevierStyleCrossRefs" href="#bib0240"><span class="elsevierStyleSup">18,27</span></a> which may have influenced the accuracy of the index test.</p><p id="par0185" class="elsevierStylePara elsevierViewall">The cutoff point higher than 7.88 was the one that showed the best balance between sensitivity (80.0%) and specificity (53.2%). The cutoff point with a higher sensitivity value in relation to the specificity was chosen to use the TyG index for early identification of IR, so children with a TyG index higher than 7.88 should be considered as having a higher risk for IR development, when compared to those with lower TyG values, and not as already showing IR. If IR risk is identified by TyG, another more precise and more specific method can be used to confirm the diagnosis.</p><p id="par0190" class="elsevierStylePara elsevierViewall">A study carried out with Korean adolescents aged 10–18 identified cutoff points for the TyG index to predict metabolic syndrome, using different diagnostic criteria for the syndrome. The cutoffs ranged from 8.41 to 8.66, with all sensitivity values higher than those of specificity, thus suggesting, as in the present study, the use of the index for the screening of metabolic risk.<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">2</span></a></p><p id="par0195" class="elsevierStylePara elsevierViewall">This study has limitations, especially the fact that the cutoff point of the TyG index is specific for the assessed sample, which impairs the extrapolation of results and its use in other populations. Thus, it is necessary to conduct multicenter studies with children to establish cutoff points for the TyG index, considering different ethnicities. However, this result is still of great scientific relevance, since it is the first aimed at a specific age group, which can be used as a starting point for future studies.</p><p id="par0200" class="elsevierStylePara elsevierViewall">In conclusion, the present study identified that total and central body adiposity and a shorter daily time spent in active activities were positively associated with IR, assessed by the TyG index in children aged 4–7 years, indicating the importance of adopting healthy lifestyle habits, such as regular practice of physical activity and adequate nutrition since childhood, as well as the maintenance of an adequate nutritional status, since body adiposity and lifestyle are associated with cardiovascular risk throughout life. Additionally, the TyG cutoff point of 7.88 was identified, which can be analyzed for future use in screening for IR risk and the associated chronic diseases in this population.</p></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Funding</span><p id="par0205" class="elsevierStylePara elsevierViewall">Fundação de Amparo à Pesquisa do Estado de Minas Gerais – <span class="elsevierStyleGrantSponsor" id="gs1">Fapemig</span>. Process number: Fapemig 02055-13. Conselho Nacional de Desenvolvimento Científico e Tecnológico – <span class="elsevierStyleGrantSponsor" id="gs2">CNPq</span>. Process number: CNPQ 485124/2011-4.</p></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Conflicts of interest</span><p id="par0210" class="elsevierStylePara elsevierViewall">The authors declare no conflicts of interest.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres1170076" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusion" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1094998" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1170075" "titulo" => "Resumo" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusão" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1094999" "titulo" => "Palavras-chave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Methods" "secciones" => array:6 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Design and sample" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Body adiposity" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Insulin resistance (IR)" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Dietary patterns" ] 4 => array:2 [ "identificador" => "sec0035" "titulo" => "Socio-demographic, lifestyle, and breastfeeding variables" ] 5 => array:2 [ "identificador" => "sec0040" "titulo" => "Data analysis" ] ] ] 6 => array:2 [ "identificador" => "sec0045" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "sec0050" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0055" "titulo" => "Funding" ] 9 => array:2 [ "identificador" => "sec0060" "titulo" => "Conflicts of interest" ] 10 => array:2 [ "identificador" => "xack399891" "titulo" => "Acknowledgements" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2017-05-08" "fechaAceptado" => "2017-12-15" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1094998" "palabras" => array:4 [ 0 => "TyG index" 1 => "Adiposity" 2 => "Lifestyle" 3 => "Children" ] ] ] "pt" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palavras-chave" "identificador" => "xpalclavsec1094999" "palabras" => array:4 [ 0 => "Índice TyG" 1 => "Adiposidade" 2 => "Estilo de vida" 3 => "Crianças" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Objective</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">To investigate the factors associated with insulin resistance in children aged 4–7 years, and to identify the cutoff point of the triglyceride-glucose index for the prediction of insulin resistance in this population.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">A cross-sectional study was conducted with 403 children from a retrospective cohort. Insulin resistance was also evaluated in a sub-sample using the HOMA index. Four indicators of body adiposity were assessed: body mass index, waist-to-height ratio, and the percentages of total and central body fat. Food habits were evaluated by the identification of dietary patterns, using principal component analysis. Information was also collected on lifestyle, socioeconomic status, and breastfeeding time.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">The median index observed in the sample was 7.77, which did not differ between the genders. The shorter the time spent in active activities, the higher the triglyceride-glucose value; and increase in the values of body adiposity indicators was positively associated with triglyceride-glucose. The cutoff point with the best balance between sensitivity and specificity values was 7.88 (AUC<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.63, 95% CI: 0.51–0.74).</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusion</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">The present study identified that total and central body adiposity and shorter time spent in lively activities was positively associated with insulin resistance, evaluated through the triglyceride-glucose index. The cutoff point of 7.88 may be used in this population for insulin resistance risk screening, but caution is required when using it in other populations.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusion" ] ] ] "pt" => array:3 [ "titulo" => "Resumo" "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Objetivo</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Investigar os fatores associados à resistência à insulina em crianças de 4 a 7 anos, e identificar o ponto de corte do índice triglicerídeos-glicemia (TyG) para predição da RI nessa população.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Métodos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Estudo transversal, com 403 crianças pertencentes a uma coorte retrospectiva. A resistência à insulina foi avaliada pelo índice triglicerídeos-glicemia e também pelo índice HOMA, este em uma subamostra. Avaliou-se quatro indicadores de adiposidade corporal: o índice de massa corporal, a relação cintura-estatura e os percentuais de gordura corporal total e central. O hábito alimentar foi avaliado pela identificação dos padrões alimentares, utilizando-se a análise de componentes principais. Foram coletadas também informações sobre estilo de vida, condição socioeconômica e tempo de aleitamento materno.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">A mediana observada do índice triglicerídeos-glicemia na amostra foi de 7,77 e não diferiu entre os sexos. Quanto menor o tempo diário em atividades ativas, maior o valor de triglicerídeos-glicemia; e o aumento nos valores dos indicadores de adiposidade corporal associou-se positivamente com o triglicerídeos-glicemia. O ponto de corte com melhor equilíbrio entre os valores de sensibilidade e especificidade foi o de 7,88 (AUC = 0,63; IC 95% 0,51 - 0,74).</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusão</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">O presente estudo identificou que a adiposidade corporal total e central e o menor tempo diário em atividades ativas associou-se positivamente com a resistência à insulina, avaliada pelo índice triglicerídeos-glicemia. O ponto de corte de 7,88 pode ser utilizado nessa população para triagem do risco de resistência à insulina, mas é necessário cautela na sua utilização em outras populações.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusão" ] ] ] ] "NotaPie" => array:2 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0035">Please cite this article as: Vieira-Ribeiro SA, Fonseca PC, Andreoli CS, Ribeiro AQ, Hermsdorff HH, Pereira PF, et al. The TyG index cutoff point and its association with body adiposity and lifestyle in children. J Pediatr (Rio J). 2019;95:217–23.</p>" ] 1 => array:2 [ "etiqueta" => "☆☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0040">Study conducted at Universidade Federal de Viçosa (UFV), Viçosa, MG, Brazil.</p>" ] ] "multimedia" => array:3 [ 0 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Extraction method: principal component analysis. Varimax rotation with Kaiser normalization.</p><p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Values in bold indicate factorial loads<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>≥0.25.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td-with-role" title="table-head ; entry_with_role_rowhead " align="left" valign="top" scope="col">Foods/groups \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " colspan="5" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Dietary patterns</th></tr><tr title="table-row"><th class="td" title="table-head " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Traditional \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Non-healthy \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Milk and chocolate milk \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Snacks \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Healthy \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Milk and dairy products \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.038 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.234 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">0.738</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.164 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.018 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Chocolate milk and sugar \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.026 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.028 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">0.856</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.028 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.050 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Coffee and teas \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.036 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.234 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">−0.502</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">0.252</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.181 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Butter and margarine \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.194 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.182 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.034 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">0.573</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.027 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Breads, cakes and cookies \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.044 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.032 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.012 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">0.703</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.091 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Cream−filled sandwich cookies \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.111 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">0.273</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.105 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">−0.381</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.026 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Beans \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">0.684</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.159 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.102 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.139 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.110 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">White rice \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">0.749</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.004 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.144 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.043 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.161 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Green vegetables \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">0.499</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.051 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.073 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.178 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.256 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Vegetables and legumes \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.371 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.031 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.002 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.055 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">0.433</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Roots, porridge, and flour \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">0.381</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.080 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.017 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.204 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.019 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Fruits \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.125 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.114 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.115 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">−0.273</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">0.532</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Natural juice \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.132 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.034 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.051 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.231 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">0.620</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Artificial juice and soft drinks \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.127 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">0.755</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.020 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.083 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Meats, fish, and eggs \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">0.408</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.329 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.093 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.122 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.142 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Fried food, snacks, and processed meats \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.088 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">0.631</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.106 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.028 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.067 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Sweets and candy \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.010 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">0.477</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.031 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.144 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.443 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Broth and soups \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.090 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">−0.334</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.021 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.049 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">0.306</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Pasta \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.052 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.151 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.072 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><span class="elsevierStyleBold">−0.458</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.027 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Explained variance (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">7.0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Total of explained variance (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">42.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1997347.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Dietary patterns and factorial loads of food groups consumed by children aged 4–7 years.</p>" ] ] 1 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at2" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">TyG, triglyceride-glucose index; BRL, Brazilian reals; BMI, body mass index; WHtR, waist-to-height ratio; EBF, exclusive breastfeeding.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td-with-role" title="table-head ; entry_with_role_rowhead " align="left" valign="top" scope="col">Explanatory variables \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " colspan="4" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">TyG index (response variable)</th></tr><tr title="table-row"><th class="td" title="table-head " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">β</span> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">95% CI \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">β</span><span class="elsevierStyleInf">adj</span><a class="elsevierStyleCrossRef" href="#tblfn0025"><span class="elsevierStyleSup">d</span></a> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">95% CI \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Age (months) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.001 to 0.006 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.002 to 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="table-entry ; entry_with_role_rowhead " align="left" valign="top">Time of EBF (months) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.016 to 0.019 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Per capita</span> income (BRL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.000 to 0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.000 to 0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Screen time (h) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.013 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.007 to 0.034 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Time in active activities (h) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.032<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.060 to −0.005 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.030<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.055 to −0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">“Traditional” pattern \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.007 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.033 to 0.047 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">“Non-healthy” pattern \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.042<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.002 to 0.082 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.028 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.012 to 0.068 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">“Milk and chocolate milk” pattern \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.031<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.008 to 0.071 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.031 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.008 to 0.071 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">“Snack” pattern \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.011 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.029 to 0.051 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">“Healthy” pattern \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.035<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.004 to 0.075 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.027 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.014 to 0.068 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">BMI (<span class="elsevierStyleItalic">Z</span>-score) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.041<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.010 to 0.073 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.031<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.010 to 0.062 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">WHtR \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.336<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.451 to 2.220 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.191<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.279 to 2.104 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Body fat % \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.010<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.005 to 0.015 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.010<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.002 to 0.013 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Central fat % \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.008<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.003 to 0.013 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.014<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.001 to 0.011 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1997346.png" ] ] ] "notaPie" => array:4 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="npar0005"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.20.</p>" ] 1 => array:3 [ "identificador" => "tblfn0010" "etiqueta" => "b" "nota" => "<p class="elsevierStyleNotepara" id="npar0010"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05.</p>" ] 2 => array:3 [ "identificador" => "tblfn0015" "etiqueta" => "c" "nota" => "<p class="elsevierStyleNotepara" id="npar0015"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001.</p>" ] 3 => array:3 [ "identificador" => "tblfn0025" "etiqueta" => "d" "nota" => "<p class="elsevierStyleNotepara" id="npar0020">Adjustment for the variables that showed <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.20 in the bivariate analysis.</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Bivariate and multiple linear regression used to investigate factors associated with variation in the TyG index in children aged 4–7 years (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>402).</p>" ] ] 2 => array:8 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at3" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">TyG index</th></tr><tr title="table-row"><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Cutoff \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Sensitivity (%) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Specificity (%) \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " align="char" valign="top">7.70 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">86.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">37.3 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="char" valign="top">7.73 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">86.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">41.3 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="char" valign="top">7.74 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">42.9 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="char" valign="top">7.88<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">53.2 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="char" valign="top">7.90 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">73.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">55.6 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="char" valign="top">7.93 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">73.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">57.9 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="char" valign="top">7.96 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">66.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">58.7 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1997345.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0020" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="npar0025">Cutoff point with the best balance between sensitivity and specificity values, adopting the – Homeostasis Model Assessment for Insulin Resistance (HOMA-IR; <span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>141) – as the reference method.</p> <p class="elsevierStyleNotepara" id="npar0030">TyG, triglyceride-glucose index.</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Cutoff points, sensitivity, and specificity of the Tyg index for insulin resistance prediction in children aged 4–7 years.</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "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" => "Association of body mass index and insulin resistance with metabolic syndrome in Brazilian children" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:3 [ 0 => "A.P. 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Martínez" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:5 [ "tituloSerie" => "Arq Bras Endocrinol Metab" "fecha" => "2009" "volumen" => "53" "paginaInicial" => "572" "paginaFinal" => "581" ] ] ] ] ] ] 29 => array:3 [ "identificador" => "bib0300" "etiqueta" => "30" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Mediterranean diet, overweight and body composition in children from eight European countries: cross-sectional and prospective results from the IDEFICS study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "G. Tognon" 1 => "A. Hebestreit" 2 => "A. Lanfer" 3 => "L.A. Moreno" 4 => "V. Pala" 5 => "A. Siani" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.numecd.2013.04.013" "Revista" => array:6 [ "tituloSerie" => "Nutr Metab Cardiovasc Dis" "fecha" => "2014" "volumen" => "24" "paginaInicial" => "205" "paginaFinal" => "213" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/23870847" "web" => "Medline" ] ] ] ] ] ] ] ] ] ] ] ] "agradecimientos" => array:1 [ 0 => array:4 [ "identificador" => "xack399891" "titulo" => "Acknowledgements" "texto" => "<p id="par0215" class="elsevierStylePara elsevierViewall">The authors would like to thank the children who participated in the project and their parents/guardians. They also thank Capes for the Doctoral Grant. This project received financial support from FAPEMIG and CNPq.</p>" "vista" => "all" ] ] ] "idiomaDefecto" => "en" "url" => "/00217557/0000009500000002/v1_201903260615/S0021755717304436/v1_201903260615/en/main.assets" "Apartado" => array:4 [ "identificador" => "10179" "tipo" => "SECCION" "en" => array:2 [ "titulo" => "Original articles" "idiomaDefecto" => true ] "idiomaDefecto" => "en" ] "PDF" => "https://static.elsevier.es/multimedia/00217557/0000009500000002/v1_201903260615/S0021755717304436/v1_201903260615/en/main.pdf?idApp=UINPBA000049&text.app=https://jped.elsevier.es/" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0021755717304436?idApp=UINPBA000049" ]
Year/Month | Html | Total | |
---|---|---|---|
2024 November | 5 | 4 | 9 |
2024 October | 34 | 37 | 71 |
2024 September | 31 | 25 | 56 |
2024 August | 46 | 36 | 82 |
2024 July | 73 | 43 | 116 |
2024 June | 38 | 13 | 51 |
2024 May | 26 | 8 | 34 |
2024 April | 38 | 27 | 65 |
2024 March | 61 | 29 | 90 |
2024 February | 26 | 31 | 57 |
2024 January | 28 | 26 | 54 |
2023 December | 22 | 27 | 49 |
2023 November | 56 | 34 | 90 |
2023 October | 46 | 38 | 84 |
2023 September | 40 | 38 | 78 |
2023 August | 29 | 26 | 55 |
2023 July | 22 | 25 | 47 |
2023 June | 23 | 12 | 35 |
2023 May | 27 | 17 | 44 |
2023 April | 33 | 10 | 43 |
2023 March | 65 | 27 | 92 |
2023 February | 35 | 13 | 48 |
2023 January | 23 | 17 | 40 |
2022 December | 40 | 32 | 72 |
2022 November | 33 | 27 | 60 |
2022 October | 53 | 39 | 92 |
2022 September | 23 | 34 | 57 |
2022 August | 32 | 31 | 63 |
2022 July | 32 | 41 | 73 |
2022 June | 22 | 29 | 51 |
2022 May | 29 | 26 | 55 |
2022 April | 38 | 35 | 73 |
2022 March | 44 | 36 | 80 |
2022 February | 25 | 27 | 52 |
2022 January | 41 | 15 | 56 |
2021 December | 42 | 19 | 61 |
2021 November | 27 | 15 | 42 |
2021 October | 30 | 19 | 49 |
2021 September | 25 | 7 | 32 |
2021 August | 14 | 10 | 24 |
2021 July | 16 | 5 | 21 |
2021 June | 14 | 6 | 20 |
2021 May | 26 | 16 | 42 |
2021 April | 45 | 18 | 63 |
2021 March | 31 | 20 | 51 |
2021 February | 22 | 7 | 29 |
2021 January | 23 | 8 | 31 |
2020 December | 15 | 9 | 24 |
2020 November | 23 | 9 | 32 |
2020 October | 19 | 2 | 21 |
2020 September | 20 | 13 | 33 |
2020 August | 26 | 2 | 28 |
2020 July | 20 | 6 | 26 |
2020 June | 24 | 5 | 29 |
2020 May | 13 | 2 | 15 |
2020 April | 17 | 11 | 28 |
2020 March | 20 | 11 | 31 |
2020 February | 32 | 16 | 48 |
2020 January | 26 | 21 | 47 |
2019 December | 18 | 13 | 31 |
2019 November | 13 | 12 | 25 |
2019 October | 27 | 14 | 41 |
2019 September | 14 | 19 | 33 |
2019 August | 17 | 16 | 33 |
2019 July | 14 | 14 | 28 |
2019 June | 29 | 21 | 50 |
2019 May | 24 | 12 | 36 |
2019 April | 51 | 16 | 67 |
2019 March | 35 | 5 | 40 |
2019 February | 25 | 10 | 35 |
2019 January | 20 | 5 | 25 |
2018 December | 25 | 6 | 31 |
2018 November | 22 | 4 | 26 |
2018 October | 27 | 13 | 40 |
2018 September | 11 | 7 | 18 |
2018 August | 6 | 10 | 16 |
2018 July | 9 | 6 | 15 |
2018 June | 6 | 1 | 7 |
2018 May | 3 | 8 | 11 |
2018 April | 0 | 8 | 8 |
2018 March | 0 | 25 | 25 |