Melissa Chambers, DO,​a Stephanie K. Tanamas, PhD,​b Elena J. Clark, BS,b​ Diana L. Dunnigan, MD,c​ Chirag R. Kapadia, MD,​a RobertGrowth L. Hanson, MD, MPH, Tracking​b Robert G. Nelson, MD, PhD, in​b William Severely C. Knowler, MD, DrPH,b​ Madhumita Sinha, MD, MHSMb Obese or Underweight Children OBJECTIVES: abstract

To illustrate the difficulties in optimal growth monitoring of children with severe obesity or underweight by usingz the Centers for Disease Control and Prevention (CDC) 2000 age- and sex-specific BMI percentile growth charts. We also aimed to examine the utility of a new modified CDC BMI score chart to monitor growth in children with normal and METHODS: z extreme BMI percentiles by using real-life clinical scenarios.

Modified BMI score charts were created by using the 2000 CDCz algorithm. Three cases of children with extreme BMI values and abnormal growth patterns were plotted by using the standard CDC 2000 clinical growth chart, the modified BMI score chart, and the CDC BMI percentile chart, modified to include the percentage of the 95th percentile RESULTS: (%BMIp95) curves. Children with severe obesity could not be plotted on the standard CDC BMI percentile chart because their BMI points lay above the chart cutoff. Children with a low BMI (<3%) were also difficult to track on the standard BMI percentile chart. The addition of the %BMIp95 scale to the standard BMI percentile chart allowed tracking of severely obese zchildren; however, it did not address severely underweight children and required a change of units within the chart when transitioning from normal to obese BMIs. The modified BMI CONCLUSIONS: z score chart allowed uniform tracking. The modified CDC score chart is suitable for growth tracking of children with normal and extreme growth patterns; the measures correlate well with the %BMIp95,​ and the chart can be incorporated easily into existing electronic health record systems for NIH clinical use.

aDivision of Endocrinology and Diabetes, Phoenix Children’s Hospital, Phoenix, Arizona; bDiabetes Epidemiology What’sw Kno n on This Subject: With the and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, National increasing prevalence of childhood obesity, optimal Institutes of Health, Phoenix, Arizona; and cPhoenix Indian Medical Center, Phoenix, Arizona methods for growth tracking are needed. The Dr Chambers conceptualized the study, collected patient data, assisted in study design, and Centers for Disease Control (CDC) 2000 age- and assisted in drafting the manuscript; Dr Tanamas and Ms Clark assisted is study design, assisted sex-specific BMI percentile growth charts currently with creation of the growth charts, and critically reviewed the manuscript; Drs Dunnigan, Nelson, in use are inadequate for growth monitoring at and Hanson assisted with the study design and critically reviewed the manuscript; Dr Kapadia extremes of BMI percentiles. obtained study data and critically reviewed the manuscript; Dr Knowler assisted in study design, including the creation of the growth charts, and critically reviewed the manuscript; Dr Sinha What This Study Adds: Growth in children with conceptualized the study, assisted in study design, and drafted the initial manuscript; and all normal and problematic growth was tracked by authors approved the final manuscript as submitted. using CDC 2000 BMI growth charts, charts with additional curves depicting percent of the 95th DOI: https://​doi.​org/​10.​1542/​peds.​2017-​2248 percentile, and our proposed modified CDC BMI z Accepted for publication Sep 12, 2017 score charts. Address correspondence to Madhumita Sinha, MD, MHSM, Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, 1550 E. Indian School Rd, Phoenix, AZ 85014. E-mail: [email protected] PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online, 1098-4275). To cite: Chambers M, Tanamas SK, Clark EJ, et al. Growth Tracking in Severely Obese or Underweight Children. Pedi­ atrics. 2017;140(6):e20172248

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Chambers et al https://doi.org/10.1542/peds.2017-2248 December 2017 Growth Tracking in Severely Obese or Underweight Children 6 140 Pediatrics 2017 ROUGH GALLEY PROOF z The global epidemic of childhood whereinz overweight is defined as a score software program provided by obesity is worsening. An estimated score >2 SD and obesity is defined the CDC, which allows for quantifying − 10 41 million children worldwide under as a score >3 SD above the mean. extreme BMI values; (2) to describe − – the age of1 5 are either overweight Conversely, BMIs-for-age < 2 SD methods to construct 2000 CDC or obese. In the United States, the and < 3 SD below the mean on the BMI-for-age based percentile charts

prevalence of obesity among children WHO charts are considered wasted10, 11​ by inclusion of additional curves and adolescents 2 to 19 years of age and severely wasted, respectively. ‍ depicting %BMIp95; and (3) to ∼ z has stabilized over the past2 decade Currently, the CDC has not published present actual clinical case scenarios but remains high at 17%. More score charts for clinical growth of children with growth problems concerning is the increasing trend trackingz in children in the United and plot BMI-for-age by using in severe obesity,3 especially among States. However, age- and sex-specific 2000 CDC BMI-for-age percentile older children. This epidemic, BMI scores can be calculated from charts that are currently in clinical combined with the existing challenge the skewness, median, and coefficient use, the 2000 CDC charts with the of tracking growth progress in of variation values provided by the addition of %BMIp95 growth lines for underweight children, has presented CDC, which are derived from the characterizing growth in children a new predicament for clinicians smoothed percentile curves12 of the with zBMI percentiles in the upper as they struggle to identify an easy 2000 CDC growth charts. z extremes, and our proposed modified and meaningful method to monitor z BMI score charts. The age-z and sex-specific BMI growth and interventions. score, or CDC BMI unmodified score Methods In 2000, the Centers for Disease (BMI ), which is frequently used in Control and Prevention (CDC) research and current clinical practice, is inadequate for longitudinal growth published age- and sex-specific The growth5 charts proposed by growth charts that are currently tracking, especially13 among severely Gulati et al that allow for tracking obese children. To address this used by pediatric care providers in “ z ” of severe obesity (BMI >36) were the United States for assessment problem, the CDC now provides created by using the 2000 CDC of growth and nutritional status in modified scores that are based growth chart as the base, with the on a fixed SD and are not bounded by children and4 adolescents 2 to 19 14 addition of new percentile curves years of age. A serious limitation of upper or lower15 limits. Freedman above the 95th percentile. These new these growth charts, however, is the and Berenson recently compared percentile curves were calculated by inability to assess and track growth longitudinal tracking of multiple multiplying the age- and sex-specific BMI metrics by using data from the in children with very high BMI 5,as6​ wellz BMI at the 95th percentile by values as children with very low BMI. ‍ The zBogalusa Heart Study cohort; the from 1.1 through 2.0 to derive the basic problem is that the standard authors found the tracking of BMI 110% to 200% BMIp95. scores and percentiles based on age scores to be weakerz compared z p95 We created the age- and sex-specific and sex are severely compressed at with that of %BMI and adjusted modified BMI score charts by using high BMI levels, so that very high (modified) BMI scores especially z the statistical program provided or very low values are not well among children with high BMI values. 16,17​ by CDC. ‍ The modified BMI quantified, causing a relatively large z Considering thesez latest research scores are based on extrapolating change in BMI results from only a z – findings, we propose a uniform one-half of the distance between small change in BMI percentile or 14 6 8 modified BMI score chart that could 0 and +2 scores. To further score. ‍ Alternative charts have been z be used to track BMI in all categories illustrate the difference in how BMI proposed recently, including those z of growth, from severe underweight is represented on a plot using BMI using a percentage of the smoothed to severe obesity, withoutz changing and modified BMI score methods, 95th BMI percentile (%BMIp95) for 5 units or adding clinical complexity. we plotted different BMI values less obeseZ children. These modified BMI score charts than and greater than the median scores identify the distance and could be easily integrated into in a hypothetical girl and boy of 5.5 z existing electronic health record direction of deviation from the mean, and 12.5 yearsz of age, respectively and scores are a standardized systems and would be ideal for (Fig 1). It is evident from this figure quantity reflecting the reference both primary care and pediatric that the BMI curve plateaus at the subspecialty use. population that can be compared upper extremez and is exaggerated across age,9 sex, and anthropometric The objectives of this study arez as at the lower extreme, whereas the measuresz . The World Health follows: (1) to describe methods z modified BMI curve shows a linear Organization (WHO) has BMI-for- used to construct BMI-for-age score distribution at both extremes. In the age score charts for clinical use, growth charts by using the modified middle range of BMI representing Downloaded from www.aappublications.org/news by guest on September 29, 2021 2 Chambers et al

Chambers et al https://doi.org/10.1542/peds.2017-2248 December 2017 Growth Tracking in Severely Obese or Underweight Children 6 140 Pediatrics 2017 ROUGH GALLEY PROOF FIGURE 1 BMI tracking of children by using BMIz and modified BMIz score methods for (A) a 5.5-year-old boy, (B) a 5.5-year-old old girl, (C) a 12.5-year-old boy, and (D) a 12.5-year-old girl.

Results z z z most normal weight children, the Case 1 provides more continuous tracking. By BMI and modified BMI are nearly using the modified BMI score chart (Fig 4), it is possible to see that the identical. z − Clinical Scenarios Plotted by Using A 13-year-old girl was referred to the patient started in the normal weight Different Growth Charts pediatric endocrine specialty clinic category at a score slightly > 1 for evaluation and management of at age 10 years. Her BMI increased excessive weight gain. She developed dramatically within 4 years, zand rapid weight gain after starting peaked at > +3 SD by age 14, before To illustrate the differences in anticonvulsant medications at age beginning a downtrend to a score of growth trends among children +3 SD. This change is also illustrated in 11 years. At age 13.5 years, intensive ∼ with problematic growth patterns p95 lifestyle interventions were initiated, the %BMI chart, which reveals that involving both severe underweight which resulted in a downward tracking her BMI peaked at 130% of the 95th and severe obesity, we selected ’ of her weight. In Fig 2, her BMI at percentile (Fig 3) before she began a 3 clinical cases from a pediatric yearly visits from ages 10 to 14 years downtrend, remaining >120% of the endocrinology clinic at a children s and at 2 additional visits between ages 95th percentile for her age and sex. hospital and plotted changes in BMI 14 to 15 years was plotted by using the When she transitioned from normal using all 3 growth charts. Two of 2000 CDC BMI-for-age percentile chart weight into the obesity category, the the 3 children had excessive weight, for girls. In Figs 3 and 4, the plot was quantitative measure changed from and the third was an underweight percentile to percent of the 95th illustrated by using an age- andz sex- child. specific 2000 CDC percentile chart with Cpercentile.ase 2 p95 ’ %BMI and the modified BM score The institutional review board at chart. With either zof these charts, more Phoenix Children s Hospital granted extreme BMIs can be tracked, although A 12-year-old girl with a history a waiver of informed consent for this the modified BMI score chart uses of attention deficit hyperactivity study. a uniform unit of measurement and disorder was on stimulant therapy Downloaded from www.aappublications.org/news by guest on September 29, 2021 PEDIATRICS Volume 140, number 6, December 2017 3

Chambers et al https://doi.org/10.1542/peds.2017-2248 December 2017 Growth Tracking in Severely Obese or Underweight Children 6 140 Pediatrics 2017 ROUGH GALLEY PROOF FIGURE 2 Two to 20 years: female patients. BMI-for-age percentiles. The BMI of a female patient (Case 1) who transitioned from having normal weight to having severe obesity between the ages of 10 to 14 years was plotted by using the CDC 2000 BMI-for-age-sex growth chart, and the BMI of a female patient (Case 2) with underweight problems was plotted by using the CDC 2000 BMI-for-age-sex growth chart. Source: developed by the National Center for Health Statistics in collaboration with the National Center for Chronic Disease Prevention and Health Promotion (http://www​ .​cdc.​gov/growthchar​ ts).

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Chambers et al https://doi.org/10.1542/peds.2017-2248 December 2017 Growth Tracking in Severely Obese or Underweight Children 6 140 Pediatrics 2017 ROUGH GALLEY PROOF FIGURE 3 Two to 20 years: female patients, continued. BMI-for-age %BMIp95. The BMI of a female patient (Case 1) who transitioned from having normal weight to having severe obesity between the ages of 10 to 14 years was plotted by using a modified 2000 CDC percentile chart with %BMIp95, and the BMI of a female patient (Case 2) with underweight problems was plotted by using a modified 2000 CDC percentile chart with %BMIp95.

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Chambers et al https://doi.org/10.1542/peds.2017-2248 December 2017 Growth Tracking in Severely Obese or Underweight Children 6 140 Pediatrics 2017 ROUGH GALLEY PROOF FIGURE 4 Two to 20 years: female patients, continued. BMI-for-age z scores calculated by using the modified BMI z score. The BMI of a female patient (Case 1) who transitioned from having normal weight to having severe obesity between the ages of 10 to 14 years was plotted by using a modified BMI-for-age z score chart, and the BMI of a female patient (Case 2) with underweight problems was plotted by using a modified BMI-for-age z score chart.

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Chambers et al https://doi.org/10.1542/peds.2017-2248 December 2017 Growth Tracking in Severely Obese or Underweight Children 6 140 Pediatrics 2017 ROUGH GALLEY PROOF Discussion Z

until 12 years of age, when she was lower extremes. score charts do znot referred to the specialty clinic for have this limitation. However, in the The reference population data for the evaluation of growth failure. The current commonly used CDC BMI 2000 CDC growth charts currently patient had a severe loss of appetite scores, the power transformation to used for assessment of growth and and poor caloric intake, resulting in achieve normality results in a severe nutritional status of children in the z low body weight for age and poor compression of the distribution United States were obtained from weight gain. After weaning her of scores, primarily at the upper nationally representative surveys from stimulants and implementing 18 end. To address the extreme values conducted between 1963 and 1994. an optimized diet plan, her growth of growth indicators considered Since then, we have witnessed an improved. Figure 2 illustrates the biologically implausible before obesity epidemic, with one-third of z corresponding BMI changes in the obesity epidemic, the CDC has children now considered overweight this patient plotted by using the ≥ since introduced a modified score or obese. The prevalence rates of 14 conventional 2000 CDC percentile ≥ program. By using this method, class 2 (BMI 120% of the 95th growth chart. Her growth was also ≥ the BMI of an individual is expressed percentile or BMI 35) and class 3 plotted on the %BMIp95 chart (Fig 3); ≥ relative to the median BMI in units (BMI 140% of the 95th percentile z the plot is identical to the 2000 CDC of 1/2 the distance between 0 and or BMI 40) obesity have risen 14 BMI-for-age chart and tracks mostly +2 scores. The advantage of significantly and are estimated to be below the third percentile, so it 3 this method is that assumptions 5.9% and 2.1%, respectively. The cannot be well quantified, creating are not made beyond the limits of inadequacies in optimal tracking a challenge for optimal tracking in observed values in the reference z of severely obese and underweight − these low percentiles. By using the sample, and values can be tracked children by using current growth modified BMI score method in Fig outside of the 3 to +3 SD range. charts are problematic, especially z 4, we note that the growth line has The CDC documentation includes a − − in clinical settings where periodic “ ” an upward trend toward the median description of the modified score as z growth monitoring is essential from just < 3 SD to just > 2 SD, a tool for identifying implausible for assessing the effectiveness of crossing 2 lines over a 14-month values, that is, probable data 11 therapeutic interventions. period. By the WHO interpretation,​ errors. It is becoming increasingly “ ” the child has improved from a To address the more pervasive 7 clear, however, that many, if not severely wasted category11 to being issue of severe obesity, Flegal et al nearly all, of these high values are within normal limits. suggested that a practical approach real, representing20 severely obese Case 3 would be to express high BMI values children. p95 as a %BMI , rather than imputing z high percentiles that are unreliable We previously used the modified A 15-year-old boy with no known at the tails of the distribution. On the score method to characterize underlying chronic medical problems basis of this method, the American secular trends in childhood obesity ≥ 21 was referred to the endocrine Heart Association defined severe in an American Indian population. ≥ specialty clinic for excessive obesity in children aged 2 years Although the CDCz has developed a weight gain. He indulged in high as having a BMI 120% BMIp95 software program that calculates ≥ z consumption of calorie-dense foods, for age and sex, or as having a modified BMI scores, it has not compounded by a sedentary lifestyle. BMI 35 (the definition of class developed score growthz charts. To Intensive lifestyle modifications were 2 obesity19 in adults), whichever5 is demonstrate the clinical utility of implemented that resulted in a slight lower. In 2012, Gulati et al built using a modified BMI score chart, in reduction in BMI. His BMI could not on this concept and proposed new the current study, we used illustrative be plotted by using the 2000 CDC growth charts that are convenient cases from a pediatric endocrinology clinical BMI-for-age percentile chart for clinical tracking of severely clinic to plot BMI changes in childrenz because all the BMI values exceeded obese children and adolescents. with severe obesity and found that 35 and were beyond the limit of the Although the %BMIp95 method both %BMIp95 and modified CDC chart (Fig 5). Figure 6 shows how of characterizing severe obesity score charts track growthz changes in his BMI was tracked by usingz the has been gaining favor, there is an severely obese children satisfactorily. p95 %BMI chart, and Fig 7 shows zthe obvious discontinuity in the units of The modified BMI score chart can plot using the modified BMI score measurement between the nonobese also be used to track children who fall chart. In both the modified BMI and obese groups. It also addresses below the third percentilez on standard score chart and the %BMIp95 chart, a only children in the upper extremes, charts. Among underweight children, similar change in growth pattern and and does not create a unified chart the modified BMI score chart was points of change are shown. to track growth in children in the more informative than the 2000 CDC Downloaded from www.aappublications.org/news by guest on September 29, 2021 PEDIATRICS Volume 140, number 6, December 2017 7

Chambers et al https://doi.org/10.1542/peds.2017-2248 December 2017 Growth Tracking in Severely Obese or Underweight Children 6 140 Pediatrics 2017 ROUGH GALLEY PROOF FIGURE 5 Two to 20 years: male patient. BMI-for-age percentiles. Shown here are the BMI plots of a male patient (Case 3) with severe obesity who demonstrated an improvement in BMI that could not be tracked by using the CDC 2000 BMI-for-age-sex growth chart. Source: developed by the National Center for Health Statistics in collaboration with the National Center for Chronic Disease Prevention and Health Promotion (http://www​ .​cdc.​gov/​growthcharts).

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Chambers et al https://doi.org/10.1542/peds.2017-2248 December 2017 Growth Tracking in Severely Obese or Underweight Children 6 140 Pediatrics 2017 ROUGH GALLEY PROOF FIGURE 6 Two to 20 years: male patient, continued. BMI-for-age %BMIp95. Shown here are the BMI plots of a male patient (Case 3) with severe obesity who demonstrated improvement in BMI that could be tracked by using a modified 2000 CDC percentile chart with %BMIp95.

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Chambers et al https://doi.org/10.1542/peds.2017-2248 December 2017 Growth Tracking in Severely Obese or Underweight Children 6 140 Pediatrics 2017 ROUGH GALLEY PROOF FIGURE 7 Two to 20 years: male patient, continued. BMI-for-age z scores calculated by using the modified BMI z score. Shown here are the BMI plots of a male patient (Case 3) with severe obesity who showed improvement in BMI that was adequately tracked by using a modified BMI-for-age z score chart.

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Chambers et al https://doi.org/10.1542/peds.2017-2248 December 2017 Growth Tracking in Severely Obese or Underweight Children 6 140 Pediatrics 2017 ROUGH GALLEY PROOF Conclusions 23 standard BMI% chart in this study.15 estimates. Childhoodz BMI also24 Recently, Freedman and Berenson predicted early adult mortality. The As the search continues for an compared different BMI metrices modified BMI score and %BMIp95 z optimal method of characterizing for longitudinal growth tracking are also highly correlated in this z children with normal growth as well in children. Modified BMI values population of American Indian − r P as growth problems who fall at the were substituted for BMI values children and adolescents aged 5 to 17 extremes of the spectrum of BMIs, beyond < 1.88 (third percentile) or years (Spearman = 0.99, < .0001; 15 we demonstrate, using clinical cases, >1.88 (97th percentile). We have S.K.T. et al, unpublished observations). z ± z the utility of plotting BMI using the shown in Fig 1, however, that even modified score method compared within the 1.88 SD range, the curves Modified BMI scores are useful in with methods using the %BMIp95 and derived by using both methods are quantifying values that lie beyond z standard BMI percentile 2000 CDC nearly identical. Hence, using a single the percentile ranges and provide growth charts. The %BMIp95 statistic modified BMI score chart would be a uniformity in characterizing growth has the disadvantage of complexity simple and preferred replacement to trends in severe obesity without the because of its discontinuity at the the standard percentile and %BMIp95 discontinuity in units of measurement 95th percentile, and the standard charts. In addition, we recommend between obese and nonobese groups z growth charts based on percentiles redefining weight categories based that occurs with the recently-proposed z 5 suffer from compression at the on scores, as has been described in %BMIp95 charts. Children who are 10,11​ − z extremes because percentiles are WHO score growth charts. ‍ growing normally are expected to bounded by 0 and 100, regardless remain between 2 SD and +2 SD z Although the authors of previous of how low or high the BMI is. z scores of a specific anthropometric studies questioned the validity of BMI z z The modified score charts, on measure and consistently track along scores in severe obesity and their the other hand, are conceptually the same score without crossing weak association with other adiposity 10 and computationally simpler, score lines over time. A deviation measures, these inferences were accommodate high and low BMIs, z may indicate risk on the basis of the based largely on the compressed BMI and may be more useful in clinical 6,13​ z direction of change toward or away z scores. ‍ By using data from the z 10 settings as well as in epidemiologic z from the median. Another benefit of NHANES to compare BMI scores, studies. The modified BMI chart modified scores is the ability to track modified BMI scores, %BMIp95, and should therefore be strongly children on the opposite end of the the change in the smoothed 95th BMI considered as a replacement for the weight spectrum. These children may percentile with indirect measures of current CDC 2000 BMI percentile be well below the third percentile on adiposity that included circumferences, charts as well as the recently z the standard BMI chart, and tracking skinfolds, and fat mass, we found that z proposed %BMIp95 growth charts. their progress on standard charts is BMI had a weaker correlation with challenging. By using modified scores, Acknowledgments adiposity measures than %BMIp95 and it is easier to determine if they are the change in the smoothed 95th BMI moving closer to, or farther from, the percentile among the severely obese z − 13 median. For ease of reading, we drafted We acknowledge Ms Sayuko Kobes, children This observation was made ’ z our modified score charts from 5 SD Ms Dorota Wasak, Ms Mary Hoskin, primarily because of the attenuation to +6 SD. However, these values can be and Mr Sanil Reddy for their of the CDC s estimated scores from altered infinitely to fit a specific clinical assistance with the study. skewness, median, and coefficient of z case. Lastly, an additional potential variation parameters, as explained advantage of scores is that they previously. can be easily adapted and integrated Abbreviations Severe obesity is associated with into existing electronic health record z − substantial health risks, including systems. We have also color-coded z a greater risk of diabetes and the score lines from 3 to +3 to help 22 BMI : Centers for Disease cardiovascular disease. In 1 pediatric health providers in explaining z Control and Prevention study of American Indian youth, growth patterns to parents. The only z BMI unmodified score BMI was strongly associated with limitation we see to adopting the CDC: Centers for Disease Control adiposity estimated from dual- modified score is that users will not and Prevention energy radiograph absorptiometry, be used to it and may confuse it with z WHO: World Health Organization and BMI was as strongly associated the traditional growth charts based on %BMIp95: percentage of the with cardiovascular and metabolic percentiles or with the unmodified smoothed 95th BMI risk factors as were dual-energy score that results in a compression of percentile radiograph absorptiometry high values of BMI. Downloaded from www.aappublications.org/news by guest on September 29, 2021 PEDIATRICS Volume 140, number 6, December 2017 11

Chambers et al https://doi.org/10.1542/peds.2017-2248 December 2017 Growth Tracking in Severely Obese or Underweight Children 6 140 Pediatrics 2017 ROUGH GALLEY PROOF Copyright © 2017 by the American Academy of Pediatrics FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose. FUNDING: Supported by the Intramural Research Program of the National Institute of Diabetes and Digestive and Kidney Diseases. Funded by the National Institutes of Health (NIH). POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

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Chambers et al https://doi.org/10.1542/peds.2017-2248 December 2017 Growth Tracking in Severely Obese or Underweight Children 6 140 Pediatrics 2017 ROUGH GALLEY PROOF Growth Tracking in Severely Obese or Underweight Children Melissa Chambers, Stephanie K. Tanamas, Elena J. Clark, Diana L. Dunnigan, Chirag R. Kapadia, Robert L. Hanson, Robert G. Nelson, William C. Knowler and Madhumita Sinha Pediatrics 2017;140; DOI: 10.1542/peds.2017-2248 originally published online November 7, 2017;

Updated Information & including high resolution figures, can be found at: Services http://pediatrics.aappublications.org/content/140/6/e20172248 References This article cites 13 articles, 4 of which you can access for free at: http://pediatrics.aappublications.org/content/140/6/e20172248#BIBL Subspecialty Collections This article, along with others on similar topics, appears in the following collection(s): Developmental/Behavioral Pediatrics http://www.aappublications.org/cgi/collection/development:behavior al_issues_sub Growth/Development Milestones http://www.aappublications.org/cgi/collection/growth:development_ milestones_sub Obesity http://www.aappublications.org/cgi/collection/obesity_new_sub Permissions & Licensing Information about reproducing this article in parts (figures, tables) or in its entirety can be found online at: http://www.aappublications.org/site/misc/Permissions.xhtml Reprints Information about ordering reprints can be found online: http://www.aappublications.org/site/misc/reprints.xhtml

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