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Figure 1.
Distribution of Sleep Duration per Night for the Total Sample
Distribution of Sleep Duration per Night for the Total Sample
Figure 2.
Box and Whisker Plot Comparison of the Distribution of the Insulin Sensitivity Index (ISI) Obtained by the Hyperglycemic Clamp Technique in Adolescents With Adequate Sleep vs Sleep Deprivation
Box and Whisker Plot Comparison of the Distribution of the Insulin Sensitivity Index (ISI) Obtained by the Hyperglycemic Clamp Technique in Adolescents With Adequate Sleep vs Sleep Deprivation

Adequate sleep was considered to be 8 hours/night or longer; sleep deprivation, less than 8 hours/night. Analysis was by Mann-Whitney U test. FFM indicates fat-free mass; horizontal line in center of each box, median; upper and lower borders of each box, 75th and 25th percentiles, respectively; and whiskers above and below each box, 90th and 10th percentiles, respectively.

Table 1.  
Clinical, Anthropometric, and Biochemical Characteristics of the Adolescent Study Participants
Clinical, Anthropometric, and Biochemical Characteristics of the Adolescent Study Participants
Table 2.  
Multivariable-Adjusted Associations Between Sleep Adequacy and Markers of Insulin Resistance in Adolescents
Multivariable-Adjusted Associations Between Sleep Adequacy and Markers of Insulin Resistance in Adolescents
Table 3.  
Comparison of the Markers of Insulin Resistance According to Sleep Adequacy, Stratified by BMI Categories in Adolescents
Comparison of the Markers of Insulin Resistance According to Sleep Adequacy, Stratified by BMI Categories in Adolescents
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Original Investigation
Adolescent and Young Adult Health
May 2016

Association of Sleep Deprivation With Reduction in Insulin Sensitivity as Assessed by the Hyperglycemic Clamp Technique in Adolescents

Author Affiliations
  • 1Faculty of Health and Life Sciences, University Center Nossa Senhora do Patrocinio, Itu, Brazil
  • 2Laboratory of Investigation on Metabolism and Diabetes, Gastrocentro, University of Campinas, Campinas, Brazil
  • 3Post-Graduate Program in Child and Adolescent Health, Faculty of Medical Science, University of Campinas, Campinas, Brazil
  • 4School of Applied Sciences, University of Campinas, Limeira, Brazil
  • 5Department of Pediatrics, University of Campinas, Campinas, Brazil
  • 6National Institute of Science and Technology of Obesity and Diabetes, Campinas, Brazil
 

Copyright 2016 American Medical Association. All Rights Reserved. Applicable FARS/DFARS Restrictions Apply to Government Use.

JAMA Pediatr. 2016;170(5):487-494. doi:10.1001/jamapediatrics.2015.4365
Abstract

Importance  The association between short sleep duration and decreased insulin sensitivity in adolescents has been described. However, to our knowledge, no studies have investigated this association measuring insulin sensitivity by the hyperglycemic clamp technique.

Objectives  To compare the distributions of parameters of insulin resistance in adolescents with sleep deprivation vs adequate sleep, and to investigate the association between sleep deprivation and insulin sensitivity.

Design, Setting, and Participants  Cross-sectional multicenter study using data from the Brazilian Metabolic Syndrome Study conducted from June 29, 2011, to December 3, 2014, at an obesity outpatient clinic at the University of Campinas and public schools, with a convenience sample of 615 adolescents aged 10 to 19.9 years with a body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) for age and sex at the fifth percentile or higher. A subsample of 81 adolescents underwent the hyperglycemic clamp technique.

Main Outcomes and Measures  The self-reported sleep duration was used to classify the population into 2 groups: adolescents with sleep deprivation (<8 hours/night) and adolescents with adequate sleep (≥8 hours/night). Insulin sensitivity was assessed using the hyperglycemic clamp technique.

Results  Among the 615 adolescents (56.3% female; median age, 15.9 years [interquartile range, 12.9-17.8 years]) included in the sample, the mean (SD) sleep duration was 7.9 (1.7) hours/night. The adolescents with sleep deprivation (n = 257) compared with those with adequate sleep (n = 358) had a higher median (interquartile range) age (17.0 [15.4-18.3] vs 14.1 [11.8-16.9] years), BMI (25.0 [21.2-29.3] vs 23.1 [19.5-27.6]), waist circumference (83.0 [73.5-95.4] vs 79.0 [68.5-91.0] cm), sagittal abdominal diameter (17.9 [15.8-20.8] vs 17.0 [15.0-19.8] cm), neck circumference (35.2 [33.0-38.0] vs 33.0 [30.0-35.5] cm), uric acid level (4.9 [4.0-5.8] vs 4.5 [3.7-5.5] mg/dL), and white blood cell count (7000 [5900-8200] vs 6600 [5600-7800] cells/μL) (all P < .05). Moreover, the adolescents with sleep deprivation had a lower median (interquartile range) insulin sensitivity index compared with those with adequate sleep (0.10 [0.05-0.21] vs 0.21 [0.09-0.33] mg · kgfat-free mass−1 · min−1 · mU/L × 100, respectively; difference, −0.01; 95% CI, −0.01 to −0.00; P = .02). After controlling for age and sex in the multivariate regression model, sleep deprivation remained an independent predictor for those variables. In the sleep deprivation group, BMI and central distribution of fat were higher in all categories of adiposity.

Conclusions and Relevance  Sleep deprivation (<8 hours of sleep per night) is associated with centripetal distribution of fat and decreased insulin sensitivity in adolescents. Therefore, investigations of sleep duration and sleep quality in adolescents should be included in clinical practice to promote, through health education, the eradication of the health risks associated with sleep restriction.

Introduction

Sleep is a vital biological process for health and is influenced by circadian rhythms, which play an important role in controlling the sleep-wake cycle, hormone release, core body temperature, subjective alertness, and performance level.1 The sleep-wake cycle is controlled by 2 independent homeostatic and circadian processes, the interaction of which determines the timing and structure of sleep. The homeostatic process is responsible for the increase in sleep propensity during wakefulness and its dissipation during sleep, whereas the circadian process is responsible for the alternation between periods of sleep and wakefulness (high and low sleep propensities). Another process underlying sleep regulation is the ultradian process, which is responsible for the architecture of the sleep period. This process occurs during the sleep episode and represents an alternation between the 2 basic sleep states, non–rapid eye movement sleep and rapid eye movement sleep.2-4 Thus, the synchronization between these processes is essential for health.

Although the specific functions of sleep are not completely understood, there is evidence that sleep exerts a modulatory effect on the metabolic,5-8 endocrine,5,8 cardiovascular,9 and immune systems.5,10 Therefore, it provides essential benefits to health and is necessary for healthy body functions. However, there is no consensus in the literature on the cutoff values for the optimal and insufficient numbers of sleep hours for adolescents. Recommendations range from 8 to 11 hours/night.11,12

Despite the absence of a consensus on the optimal number of sleep hours for adolescents, studies have shown a decline in the nocturnal sleep duration among adolescents. A retrospective study conducted in the United States from 1991 to 2012 (N = 272 077), in which the adolescents were asked how often they obtained 7 or more hours of sleep and how often they obtained less than 7 hours of sleep, revealed a decline in the sleep duration in the last 20 years.13 Similar trends have been reported in children and adolescents from various parts of the world.14-16 These changes in the sleep patterns influence the circadian rhythm, and circadian disruption contributes to physiological alterations and has harmful effects on health. Several epidemiological and clinical studies of adults have shown that disruptions in the timing of the sleep-wake cycle and the circadian rhythm as well as sleep deprivation can lead to disordered physiological rhythms, predisposing individuals to several disorders, including alterations in glucose metabolism,7,8 diabetes,6,17 hypertension,6 cardiovascular disease,9,18 alterations in the circulating levels of hormones,18 and increased daytime levels of inflammatory mediators.19 Thus, it is essential to investigate the detrimental effects of sleep deprivation on the health of adolescents.

Laboratory studies of young and middle-aged healthy adults that have investigated the effects of total and partial sleep deprivation on health have demonstrated alterations in the metabolic and endocrine systems, including decreases in glucose tolerance and insulin sensitivity.7,8,20 However, we found only 1 laboratory study that investigated the effects of partial sleep deprivation on markers of glucose metabolism in healthy and normal-weight adolescents.21 This study had a randomized crossover design and revealed that the homeostasis model assessment (HOMA) value was significantly higher for the short sleep duration (4 hours/night) compared with that for the long sleep duration (9 hours/night), whereas the Matsuda index was lower for the short sleep duration. Insulin levels were higher in these individuals in the fasted state, whereas C-peptide levels were higher both in the fasting state and according to the area under the curve for the short sleep duration compared with the long sleep duration.

Epidemiological studies have suggested an association between short sleep duration and decreased insulin sensitivity in adolescents.22,23 However, to our knowledge, no studies to date have investigated the association between sleep deprivation and insulin sensitivity as determined by the hyperglycemic clamp technique in adolescents. Therefore, the aims of this study were as follows: (1) to compare the distribution of clinical, anthropometric, and laboratory markers of insulin resistance (IR) in adolescents with sleep deprivation (<8 hours/night) and adequate sleep (≥8 hours/night); and (2) to investigate the association between sleep deprivation and insulin sensitivity as assessed by the hyperglycemic clamp technique.

Box Section Ref ID

Key Points

  • Question Is sleep deprivation associated with insulin resistance in adolescents?

  • Findings Adolescents with sleep deprivation had higher plasma uric acid levels and adiposity markers, particularly those related to centripetal distribution of body fat, in addition to higher insulin resistance compared with adolescents with adequate sleep.

  • Meaning Sleep duration and sleep quality in adolescents should be asked in clinical practice to decrease the risks of insulin resistance in high-risk adolescents.

Methods
Study Design and Study Sample

This sample comprised adolescents participating in the Brazilian Metabolic Syndrome Study, a cross-sectional multicenter study conducted from June 29, 2011, to December 3, 2014, in Campinas and Itu, Brazil. The adolescents were recruited by convenience sampling from the child and adolescent obesity outpatient clinic at the University of Campinas and public schools. Data from 615 adolescents (346 girls) aged 10 to 19.9 years were analyzed. Eligible adolescents for the study were aged 10 to 19 years and had a body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) for age and sex at or above the fifth percentile. The exclusion criteria were presence of a genetic syndrome, delayed neuropsychomotor development, hepatopathy, nephropathy, malnutrition, metabolic disorders (eg, hypothyroidism, hyperthyroidism, and type 1 and type 2 diabetes), cervical lymph nodes or deformities, goiter, and use of systemic corticosteroids and drugs with hypoglycemic and hypolipidemic properties. A subsample consisting of 81 adolescents (40 girls) underwent the hyperglycemic clamp technique.

The protocol was approved by the Research Ethics Committee of the University of Campinas. Written informed consent was obtained from the participants’ parents or legal guardians. The participants did not receive a stipend for their participation.

Clinical Evaluation

Blood pressure was measured by the auscultatory technique. A mercury-column sphygmomanometer with appropriate-sized cuffs was used.24

Anthropometric and Body Composition Evaluations

Weight and height were measured, and the values were used to calculate BMI-for-age z scores using Epi Info version 3.5.2 software (Centers for Disease Control and Prevention). Waist circumference was measured midway between the lowest rib and the superior border of the iliac crest.25 The sagittal abdominal diameter was measured with the participant in the supine position on a firm examination table with the knees slightly bent, using a Holtain-Kahn abdominal caliper. The sagittal abdominal diameter was defined as the distance between the table and the top of the body at the umbilicus level.26 Neck circumference was measured at the midpoint of the neck.27 The neck circumference to height ratio was calculated as the neck circumference in centimeters divided by height in centimeters.28 Body composition was estimated by tetrapolar bioimpedance.

Laboratory Assessment

Blood samples were obtained after a 12-hour overnight fast. The plasma glucose level, lipid profile (enzymatic colorimetric methods), plasma uric acid level (uricase method), white blood cell (WBC) count (automated WBC count or microscopic differential WBC count), and plasma insulin level (human insulin enzyme-linked immunosorbent assay kit EZHI-14K; Millipore; sensitivity, 2 μU/mL; intra-assay coefficient of variation, 4.6%-7.0%; interassay coefficient of variation, 9.1%-11.4%) were measured.

Insulin Sensitivity Assessment

The 2-hour hyperglycemic clamp technique (with plasma glucose concentration raised to 225 mg/dL; to convert to millimoles per liter, multiply by 0.0555) was the reference method used to assess insulin sensitivity.29 Insulin sensitivity was measured according to the average rate of glucose infusion during the last 60 minutes of the clamp test minus urinary glucose excretion, with an adjustment for fat-free mass, and divided by the mean insulin concentration of 5 dosages during the same period.

The HOMA was calculated by the HOMA2 Calculator at http://www.dtu.ox.ac.uk/homacalculator/.30,31

Determination of Sleep Hours

Sleep duration was estimated by asking the following question: “How many hours do you usually sleep per night?” The self-reported sleep duration was used to classify the population into the following 2 groups: adolescents with sleep deprivation (<8 hours/night) and adolescents with adequate sleep (≥8 hours/night).

Statistical Analysis

Data were analyzed using SPSS for Windows version 20 statistical software (SPSS, Inc). P < .05 was considered statistically significant. Differences between the sleep deprivation and adequate sleep groups were analyzed by the Mann-Whitney U test. The data are presented as median (interquartile range [IQR]). The independent relationships between sleep deprivation and the variables related to IR were examined by multiple linear regression analysis controlled by age and sex.

Results

The main clinical, anthropometric, and biochemical characteristics of the total sample and hyperglycemic clamp technique subsample are presented in Table 1. Among the 615 adolescents (56.3% female; median age, 15.9 years [IQR, 12.9-17.8 years]) included in the sample, the mean (SD) sleep duration was 7.9 (1.7) hours/night; for the 81 participants included in the hyperglycemic clamp subsample (49.4% female; median age, 14.3 years [IQR, 12.9-16.4 years]), the mean (SD) sleep duration was 7.9 (1.5) hours/night. The most frequent sleep duration was 8 hours (27.3%) (Figure 1). The prevalence of sleep deprivation was 41.8% in the total sample and 48.1% in the hyperglycemic clamp subsample.

The adolescents with sleep deprivation (n = 257) compared with those with adequate sleep (n = 358) had a higher median (IQR) age (17.0 [15.4-18.3] vs 14.1 [11.8-16.9] years), BMI (25.0 [21.2-29.3] vs 23.1 [19.5-27.6]), waist circumference (83.0 [73.5-95.4] vs 79.0 [68.5-91.0] cm), sagittal abdominal diameter (17.9 [15.8-20.8] vs 17.0 [15.0-19.8] cm), neck circumference (35.2 [33.0-38.0] vs 33.0 [30.0-35.5] cm), uric acid level (4.9 [4.0-5.8] vs 4.5 [3.7-5.5] mg/dL; to convert to micromoles per liter, multiply by 59.485), and WBC count (7000 [5900-8200] vs 6600 [5600-7800] cells/μL; to convert to ×109 per liter, multiply by 0.001) (all P < .05) (Table 2). Moreover, the adolescents with sleep deprivation had a lower median (IQR) insulin sensitivity index compared with those with adequate sleep (0.10 [0.05-0.21] vs 0.21 [0.09-0.33] mg · kgfat-free mass−1 · min−1 · mU/L × 100, respectively; difference, −0.01; 95% CI, −0.01 to −0.00; P = .02) (Figure 2). In the multivariable regression model, after controlling for age and sex, sleep deprivation remained an independent predictor for these variables (P < .05). No significant differences were observed for BMI z score, body fat, lipid profile, glucose, insulin, and HOMA-IR index in the adolescents with adequate sleep compared with those with sleep deprivation (all P > .05).

Table 3 presents the analysis separated by each of the 3 categories of BMI. In the adolescents with normal weight, it is interesting to observe that the sleep deprivation group showed higher medians of blood pressure (P = .04 for both systolic and diastolic), BMI (P < .001), waist circumference (P < .001), sagittal abdominal diameter (P < .001), neck circumference (P < .001), neck circumference to height ratio (P < .001), uric acid level (P = .03), and WBC count (P = .005) compared with the group of adolescents with adequate sleep. In addition, the sleep deprivation group had diminished levels of high-density lipoprotein cholesterol in comparison with the group of adolescents with adequate sleep (P = .03). In the categories of overweight and obesity, the main differences observed were in the general adiposity and central adiposity parameters, with the sleep deprivation group showing the higher values (P < .05).

Discussion

Changes in sleep patterns have become widespread in modern society, including a decline in the nocturnal sleep duration, principally among adolescents.13-16 Studies of adults have shown that a short sleep duration is an important risk factor for metabolic and endocrine changes.6-9,11,17-19 Thus, research on the consequences of sleep deprivation on the health of adolescents is needed. This study compared the distribution of clinical, anthropometric, and laboratory markers of IR in Brazilian adolescents with sleep deprivation (<8 hours/night) and adequate sleep (≥8 hours/night) and investigated whether sleep deprivation reduces insulin sensitivity as assessed by the hyperglycemic clamp technique. The main findings were that the adolescents with sleep deprivation had higher plasma uric acid levels and adiposity markers, particularly those related to centripetal distribution of body fat, in addition to higher IR compared with those with adequate sleep.

There is no consensus in the literature on the cutoff value for the optimal number of sleep hours per night for adolescents. Considering that the recommendations range between 8 and 11 hours/night, we chose to divide the adolescents into those with sleep durations of less than 8 vs 8 or more hours/night.11,12 Based on these criteria, 41.8% of the adolescents in this study reported sleep deprivation. The high prevalence of sleep deprivation found in this study is consistent with that found in a study by Kuciene and Dulskiene32 in which 29.7% of the participants reported an insufficient sleep duration (<8 hours/day). Consistent with other findings, our study demonstrated that adolescents were not getting enough sleep and that the sleep duration decreased with increasing age. Studies conducted in India,33 Germany,34 and Taiwan35 have shown that the average sleep duration has decreased to less than 8 hours for high school–aged students.

In this study, adolescents with sleep deprivation had higher blood pressure compared with those with adequate sleep considering nonadjusted analysis. After adjustments for sex and age, these findings were no longer observed. In a previous study of Lithuanian adolescents aged 12 to 15 years,32 adolescents with a short sleep duration (<8 hours/day) had higher mean blood pressure compared with those who slept 8 hours/day or longer. Additionally, a significant association was observed between short sleep duration and prehypertension and hypertension in this population. In a cross-sectional study of 4902 Chinese children and adolescents (aged 5-18 years),36 short sleep duration (<9 hours) was found to be associated with a higher risk of hypertension compared with a longer sleep duration (9-10 hours) among boys aged 11 to 14 years. One hypothesis for this increase in blood pressure related to sleep deprivation is the increased synthesis of catecholamines via modulation of the hypothalamic regulatory neural network.6,37

Our results showed that the adolescents with sleep deprivation had higher levels of adiposity markers, particularly those related to the centripetal distribution of body fat, compared with the adolescents with adequate sleep. These findings are in agreement with those of a study of 3311 European adolescents (aged 12.5-17.49 years).38 The European adolescents with short sleep duration showed a higher body fat level and waist circumference. In contrast to our findings, studies of European adolescents38 and Lithuanian children and adolescents32 have reported higher BMIs in individuals who sleep for a short duration compared with those who sleep 8 hours/day or longer. These discrepant results may be owing to methodological differences, such as differences among sample sizes (smaller in this study) or the methods used to assess adiposity (BMI-for-age z scores in this study vs BMIs in the previous studies).

In this study, the plasma uric acid level was higher in the adolescents with sleep deprivation. We did not find any studies evaluating the association between sleep duration and hyperuricemia in adolescents. A study of sleep variables (sleep duration, snoring, snorting, and daytime sleepiness) and high serum uric acid levels (serum levels of >6.8 mg/dL in men and >6.0 mg/dL in women) in 6491 adults (aged ≥20 years) from the National Health and Nutrition Examination Survey conducted in 2005 to 2008 found that snoring for more than 5 nights per week, daytime sleepiness, and an additive composite score of sleep variables were associated with a high serum uric acid level in the age- and sex-adjusted model and in a multivariable model with adjustments for demographic and lifestyle or behavioral risk factors.39 This association was attenuated with the addition of variables related to clinical outcome, such as depression, diabetes, hypertension, and high cholesterol levels. These results indicate that there is a positive relationship between sleep variables, including snoring, snorting, and daytime sleepiness, and a high serum uric acid level.

To our knowledge, this is the first report investigating whether sleep deprivation reduces insulin sensitivity, assessed with the hyperglycemic clamp technique, in Brazilian adolescents. The adolescents with a short sleep duration (<8 hours/night) had the lowest hyperglycemic clamp–derived insulin sensitivity index, suggesting that they had a higher level of IR than the adolescents with adequate sleep (≥8 hours/night). Comparisons of the results of this study with those from previous studies are hindered by differences in sample sizes, the ages of the included participants, the characteristics of the adolescents, the methods used for measuring sleep duration, the cutoff values for defining sleep deprivation, the methods used to assess insulin sensitivity, and the methods used for data analysis. The adolescents with sleep deprivation had a higher numerical value of the HOMA-IR index compared with those with adequate sleep. The lack of statistical significance in the HOMA-IR index can be explained by the limitations of the method. In fact, HOMA-IR is a surrogate method for the measurement of IR. The clamp technique is more accurate and precise and can detect more subtle differences than those observed by HOMA-IR. Our findings differ from those obtained in previous studies by Flint et al22 and Klingenberg et al,21 but they are in agreement with those of Javaheri et al,23 who did not detect significant differences in the distribution of HOMA-IR levels among various categories of sleep duration. In the cohort of the study by Flint et al,22 HOMA-IR levels were compared among groups of 40 obese children and adolescents (aged 3.5-18.5 years) categorized according to polysomnogram results. They found that the group with a sleep duration of less than 6 hours had a higher HOMA-IR value.22 Klingenberg et al21 conducted a study with a randomized crossover design with 2 experimental conditions and 3 consecutive nights of short sleep duration (4 hours/night) and long sleep duration (9 hours/night) to assess 21 healthy, normal-weight adolescent boys (mean [SD] age, 16.8 [1.3] years), finding that the HOMA-IR value was significantly higher for the short sleep duration compared with the long sleep duration.21 A cross-sectional study conducted by Javaheri et al23 to evaluate 471 children and adolescents (mean [SD] age, 15.7 [2.1] years) revealed similar HOMA-IR values for 3 categories of sleep duration (≤6.59, 6.60-8.74, and ≥8.75 hours), as measured by actigraphy. These differences may be attributed to differences in the characteristics of the adolescents, in the methods used to assess sleep duration, and in the cutoff values used to define sleep deprivation.

Our study has some limitations. First, sleep duration was determined by a self-reported questionnaire. Polysomnography is considered the gold standard for determining sleep duration.40 However, this method is not suitable for large-scale epidemiological studies owing to its high cost. Second, we conducted a cross-sectional analysis, which does not enable the inference of causality and the self-reported sleep duration. Third, the hyperglycemic clamp technique is not considered the gold-standard method to assess IR. However, previous studies have shown strong correlation between IR assessed by the hyperglycemic clamp technique and that assessed by the euglycemic hyperinsulinemic clamp technique. Correlations were in the range of r = 0.82, P = .005 and r = 0.90, P = .001 in adolescents with different levels of adiposity and glucose tolerance.29,41 Furthermore, for ethical reasons, our scientific committee had approved our study in healthy volunteers only with a dynamic test not infusing insulin. Thus, the hyperglycemic clamp technique was the best choice.

Conclusions

The results of this study indicate that sleep deprivation (<8 hours/night) is associated with centripetal distribution of fat and decreased insulin sensitivity in adolescents. Therefore, investigations of sleep duration and sleep quality in adolescents should be included in clinical practice to promote, through health education, the eradication of the health risks associated with sleep restriction. Experimental and longitudinal studies are needed to establish causal inference; to investigate the mechanisms underlying the relationships between sleep deprivation and changes in clinical, anthropometric, and laboratory markers of IR as well as alterations in insulin sensitivity; and to identify the optimal sleep patterns and the cutoff values for the optimal number of hours of sleep per night for adolescents.

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Article Information

Corresponding Author: Bruno Geloneze, MD, PhD, Laboratory of Investigation on Metabolism and Diabetes, Gastrocentro, University of Campinas, Rua Carlos Chagas 420, University City “Zeferino Vaz,” 13081-970 Campinas, São Paulo, Brazil (bgeloneze@terra.com.br).

Accepted for Publication: November 19, 2015.

Published Online: March 21, 2016. doi:10.1001/jamapediatrics.2015.4365.

Author Contributions: Dr Geloneze had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Geloneze.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: De Bernardi Rodrigues, da Silva, Vasques, Geloneze.

Critical revision of the manuscript for important intellectual content: Vasques, Camilo, Barreiro, Cassani, Zambon, Antonio, Geloneze.

Statistical analysis: da Silva, Vasques, Geloneze.

Obtained funding: Vasques, Geloneze.

Administrative, technical, or material support: De Bernardi Rodrigues, Vasques, Cassani, Geloneze.

Study supervision: Vasques, Barreiro, Zambon, Antonio, Geloneze.

Conflict of Interest Disclosures: None reported.

Funding/Support: This work was supported by grant 563664/2010-0 from the National Council for Scientific and Technological Development.

Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Group Information: The Brazilian Metabolic Syndrome Study (BRAMS) Investigators were Ana Carolina Junqueira Vasques, RD, PhD, Ana Maria De Bernardi Rodrigues, RN, MSc, Arnandra Nichaela Biill Alves, RN, Bruna Dyane Sitta, RN, Bruno Geloneze, MD, PhD, Camila Inajara Caturani de Araujo, RN, Cleliani de Cassia da Silva, RD, MSc, Daniella Fernandes Camilo, RD, MSc, Fabiana Lopes Nogueira, RD, Francieli Barreiro, RD, MSc, José Carlos Pareja, MD, PhD, Leandra Giorgetti dos Santos, RD, Maria Ângela Reis de Góes Monteiro Antonio, MD, PhD, Mariana da Silva Oliveira, RN, Mariana Pontes Ferrari, RD, Mariana Porto Zambon, MD, PhD, Mayra Mello, RD, Patrícia Brito Rodrigues, RD, Roberta Soares Lara Cassani, RD, PhD, Stela Caroline Rodrigues de Meira, RN, and Vanessa Cristine Rugolo, RN.

Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the University of Campinas.

Additional Contributions: Fabiana Lopes Nogueira, RD, Leandra Giorgetti dos Santos, RD, Mariana Pontes Ferrari, RD, Mayra Mello, RD, and Patrícia Brito Rodrigues, RD, Laboratory of Investigation in Metabolism and Diabetes, Gastrocentro, University of Campinas, Campinas, Brazil, assisted with recruitment of the participants and with data collection, and José Carlos Pareja, MD, PhD, Laboratory of Investigation in Metabolism and Diabetes, Gastrocentro, University of Campinas, Campinas, Brazil, contributed to the interpretation of analyses; they received no compensation.

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