Abdominal adiposity as assessed by waist circumference (WC) is a significant predictor of cardiovascular disease and type

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1 WAIST CIRCUMFERENCE IS AN INDEPENDENT PREDICTOR OF INSULIN RESISTANCE IN BLACK AND WHITE YOUTHS SOJUNG LEE, PHD, FIDA BACHA, MD, NESLIHAN GUNGOR, MD, AND SILVA A. ARSLANIAN, MD Objectives We examined how well waist circumference (WC) reflects total and abdominal fat and whether WC predicts insulin resistance independent of body mass index (BMI) percentile in youths. Study design Body composition was measured by dual-energy x-ray absorptiometry and abdominal adiposity by computed tomography. Insulin sensitivity was measured by the hyperinsulinemic-euglycemic clamp. Results Both BMI percentile and WC were significantly associated (P <.01) with total and abdominal fat and insulin sensitivity. WC remained a significant (P <.01) correlate of total and abdominal fat and insulin sensitivity after controlling for BMI percentile. By contrast, BMI percentile did not remain a significant correlate of visceral fat and markers of insulin resistance after controlling for WC. Without exception, WC explained a greater variance in abdominal fat and metabolic profiles than did BMI percentile. Conclusions Our findings suggest that the prediction of health risks associated with obesity in youths is improved by the additional inclusion of WC measure to the BMI percentile. Such observations would reinforce the importance of including WC in the assessment of childhood obesity to identify those at increased metabolic risk due to excess abdominal fat. (J Pediatr 2006;148:188-94) Abdominal adiposity as assessed by waist circumference (WC) is a significant predictor of cardiovascular disease and type 2 diabetes independent of overall adiposity in adults. 1,2 Several epidemiological studies indicate that WC in conjunction with body mass index (BMI) is a better predictor of metabolic risk than either measure alone. 3-5 However, recent evidence 6 suggests that WC and not BMI explains obesity-related health risk in a representative sample of adult population. Although the mechanisms that explain the increased metabolic risk associated with WC are unclear, it is reported that WC is a strong predictor of abdominal fat, 7 a well-known predictor of metabolic dysfunction. The ability of WC to predict abdominal fat and related comorbid conditions in youths is currently unknown. Despite the strong association between BMI and total fat, 8 the use of BMI as an indicator of adiposity in youths has an important limitation due to an individual s variation in growth rates and maturity levels. 9 Indeed, it has been reported that increases in BMI during childhood is largely determined by increases in lean body mass rather than fat mass. 10 Previous studies have examined the utility of WC as an index of health risk in youths. 11,12 Maffeis et al 12 demonstrated that WC is associated with fasting insulin, blood pressure, and insulin resistance index in obese girls. Whether WC is independently related to insulin sensitivity and -cell function in children and adolescents is currently unknown. Waist circumference during the past 10 to 20 years in youths has increased much faster than BMI over the same time period. 13 This is of great concern because abdominal fat conveys substantial health risk for cardiovascular and metabolic disease. 14 Given the escalation in the prevalence of childhood obesity and its related metabolic disorders, 15 identification of youths at high risk is important because these are antecedents of adulthood morbidities. 16,17 Thus, the purpose of this study was twofold: first, to determine how well WC reflects total, abdominal subcutaneous, and visceral fat in youths, and, second, to examine whether WC predicts insulin resistance independent of BMI percentiles. BMI DEXA Body mass index Dual-energy x-ray absorptiometry WC Waist circumference From the Children s Hospital of Pittsburgh, Division of Pediatric Endocrinology, Metabolism, and Diabetes Mellitus, Weight Management and Wellness Center, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania. This research was supported by US Public Health Service Grants RO1-HD-27503, K24-HD-01357, and MO1-RR and the GCRC and Eli Lilly and Company. Submitted for publication May 19, 2005; last revision received Aug 30, 2005; accepted Oct 3, Reprint requests: Silva A. Arslanian, MD, Children s Hospital of Pittsburgh, Division of Pediatric Endocrinology, Metabolism, and Diabetes Mellitus, 3705 Fifth Avenue at DeSoto Street, Pittsburgh, PA E- mail: Silva.Arslanian@chp.edu /$ - see front matter Copyright 2006 Elsevier Inc. All rights reserved /j.jpeds

2 Table I. Subject characteristics Black White 29 M 27 F 47 M 42 F Mean SD Median Range Mean SD Median Range Anthropometric Age (y) Tanner stage I II V Weight (kg) BMI (kg/m 2 ) BMI percentile Waist circumference (cm) Body composition Total body AT (kg)* Total abdominal AT (cm 2 ) Visceral AT (cm 2 ) ASAT (cm 2 ) Metabolic variables Fasting glucose (mg/dl) Fasting insulin ( U/mL) Proinsulin (pmol/l) Insulin sensitivity (mg/min per kg FFM per U/mL) Data are shown as mean SD. AT, Adipose tissue; ASAT, abdominal subcutaneous adipose tissue. *n 53 and n 83 in black and white, respectively. n 54 and n 88 in black and white, respectively. n 52 and n 83 in black and white, respectively. Figure 1. Association of WC (upper panel, A through C) and BMI (lower panel, D through F) with total, abdominal subcutaneous, and visceral fat. Black squares indicate blaack; white squares, white. Waist Circumference Is An Predictor of Insulin Resistance In Black And White Youths 189

3 Table II. Relations (r) between BMI percentiles, WC, total and abdominal fat, and metabolic variables BMI percentile WC Unadj Adj* Unadj Adj Total body AT Total abdominal AT Visceral AT 0.53 NS ASAT Fasting glucose 0.26 NS Fasting insulin 0.38 NS Proinsulin 0.34 NS Insulin sensitivity 0.34 NS All variables were log-transformed to normalize their distribution. NS, not significant. All other listed correlations are significant, P.01. *After controlling for WC; after controlling for BMI percentile. P.05. METHODS Subjects Subjects consisted of healthy black (n 56) and white (n 89) youths who participated in various body composition and metabolic studies, some of whom have been reported previously. 18,19 The subjects varied in age (8 to 17 years) and BMI (14 to 50 kg/m 2 ). Study participants were recruited through newspaper advertisements in the greater Pittsburgh area, flyers posted in the city public transportation, and posters placed on campus. The investigation was approved by the Institutional Review Board and performed in the General Clinical Research Center. Parental informed consent and child assent were obtained from all participants before participation, in accordance with the ethical guidelines of Children s Hospital of Pittsburgh. All participants were in good health, on the basis of clinical history, physical examination, and routine hematological and biochemical tests. None of the subjects were taking medications known to affect the primary outcome variables. Pubertal development was assessed by physical examination according to Tanner criteria and was confirmed by measurement of plasma testosterone in male subjects, estradiol in female subjects, and dehydroepiandrosterone sulfate in both. Anthropometric Measurements Body weight and height were measured to the nearest 0.1 kg and 0.1 cm, respectively, by using standardized equipment. WC was obtained at the midpoint between the lowest rib and the iliac crest. BMI was calculated as weight (kg) divided by the square of height (m 2 ). The Centers for Disease Control and Prevention Growth Charts were used to calculate sex-and age-specific BMI percentiles. 20 Body Composition Total fat was assessed by dual-energy x-ray absorptiometry (DEXA). DEXA was not performed on 9 subjects whose body weight exceeded the DEXA weight limit. A single axial image of the abdomen (L4-L5) was obtained by means of computed tomography to measure abdominal subcutaneous and visceral fat. Both measures are described in detail elsewhere. 21 Insulin Sensitivity All participants, except for one black boy, underwent a 3-hour hyperinsulinemic-euglycemic clamp after 10 to 12 hours of overnight fasting. Briefly, intravenous crystalline insulin (Humulin; Lilly, Indianapolis, IN) was infused at a constant rate of 40 mu/m 2 per minute in normal-weight subjects and 80 mu/m 2 per minute in obese subjects, as previously described by us. 22,23 Plasma glucose was clamped at 5.6 mmol/l, with a variable-rate infusion of 20% dextrose, based on arterialized plasma glucose determinations every 5 minutes. The insulin-stimulated glucose disposal rate was calculated by using the average exogenous glucose infusion rate during the final 30 minutes of the clamp. Insulin sensitivity was calculated by dividing insulin-stimulated glucose disposal rate by the steady-state insulin levels during the last 30 minutes of the clamp, as described previously. 18 Insulin sensitivity is expressed per metabolically active fat-free mass (mg/min per kg fat-free mass per U/mL). Biochemical Measurements Plasma glucose was measured by the glucose oxidase method, with a glucose analyzer (YSI, Inc, Yellow Springs, OH), and the insulin concentration was determined by radioimmunoassay. 18 Proinsulin was measured at the Esoterix Endocrinology Laboratory (Calabasas Hills, CA) by immunochemiluminescent assays. Proinsulin was not measured in three subjects because of insufficient serum sample. Statistical Analysis Statistical procedures were performed with the use of SPSS (Version 13.0; SPSS, Inc, Chicago, IL). Mann- Whitney U tests were used to evaluate racial differences in subject characteristics. Log transformations were performed to normalize the distribution for all analyses. Pearson and partial correlation coefficients were used to determine the associations among BMI percentiles, WC, total and abdominal fat, and metabolic profiles. Multiple regression analyses were used to quantify the independent contribution of BMI percentiles and WC to total and abdominal fat and metabolic profiles. Although BMI percentile and WC were significantly correlated (r 0.72), the colinearity diagnostics indicated that BMI percentile and WC could be used in the same regression model. To further investigate the contributions of WC and BMI percentile to the markers of insulin resistance, subjects were divided into low ( 75 th ), moderate (75 th to 90 th ), and high WC ( 90 th ) groups 24 and normal weight ( 85 th ), at risk for overweight (85 th to 95 th ) and overweight ( 95 th ) groups. 25 General linear models were used to determine 190 Lee et al The Journal of Pediatrics February 2006

4 Table III. Multiple regression analyses examining independent contributions of BMI percentile and WC to the variance of total and abdominal adiposity Dependent variables Step contribution of BMI percentile variables SE P R 2 Step contribution of WC variables SE P R 2 Total body AT 1 Age Age Gender Gender Race Race Pubertal status Pubertal status BMI percentile WC BMI percentile WC and BMI and WC percentile Total abdominal AT 1 Age Age Gender Gender Race Race Pubertal status Pubertal status BMI percentile WC BMI percentile WC and BMI and WC percentile Visceral AT 1 Age Age Gender Gender Race Race Pubertal status Pubertal status BMI percentile WC BMI percentile WC and BMI and WC percentile ASAT 1 Age Age Gender Gender Race Race Pubertal status Pubertal status BMI percentile WC BMI percentile WC and BMI and WC percentile BMI percentile, WC, total body AT, and all abdominal AT measures were log-transformed to normalize their distribution. Step 1 Age, gender, race, and pubertal status entered together. Step 2 BMI percentile (left side of table) or WC (right side of table) added to step 1. Step 3 BMI percentile and WC together added to step 1. the influence of WC or BMI group on the markers of insulin resistance. RESULTS Subject Characteristics Black and white youths did not differ with respect to age, BMI, and all measures of body composition (Table I). Figure 1 indicates that both BMI and WC are significantly associated with total fat, abdominal subcutaneous, and visceral fat. Although both BMI percentile and WC were significant (P.01) correlates of total body fat, abdominal fat, and metabolic profiles (Table II), WC remained a significant (P.01) correlate of these variables after controlling for BMI percentile. In contrast, BMI percentile did not remain a significant correlate of visceral fat and markers of insulin resistance after controlling for WC. Multiple regression analyses revealed that the variance explained (R 2 ) for total and abdominal fat and metabolic variables were significantly increased when WC was added to BMI percentile in the multiple regression models (Table III and Table IV). By contrast, BMI percentile did not add (P.10) to the variance in visceral fat and markers of insulin resistance (eg, fasting insulin, proinsulin, and insulin sensitivity) explained by WC and only marginally (1% 3%) contributed to the variance in total body fat, abdominal subcutaneous fat, and fasting glucose. These findings suggest that the influence of BMI percentile on total and abdominal adiposity and metabolic profiles are mediated through central obesity, measured by WC, and that WC alone is an independent predictor of total and abdominal adiposity and metabolic profiles. As shown in Figure 2, increasing WC and BMI percentile was associated with lower insulin sensitivity and higher fasting insulin and proinsulin (P for trend.01). Waist Circumference Is An Predictor of Insulin Resistance In Black And White Youths 191

5 Table IV. Multiple regression analyses examining independent contributions of BMI percentile and WC to the variance of metabolic profiles Dependent variables Step contribution of BMI percentile variables SE P R 2 Step contribution of WC variables SE P R 2 Fasting glucose 1 Age Age Gender Gender Race Race Pubertal status Pubertal status BMI percentile WC BMI percentile WC and BMI and WC percentile Fasting insulin 1 Age Age Gender Gender Race Race Pubertal status Pubertal status BMI percentile WC BMI percentile WC and BMI and WC percentile Proinsulin 1 Age Age Gender Gender Race Race Pubertal status Pubertal status BMI percentile WC BMI percentile WC and BMI and WC percentile Insulin sensitivity 1 Age Age Gender Gender Race Race Pubertal status Pubertal status BMI percentile WC BMI percentile WC and BMI and WC percentile BMI percentile, WC, and all metabolic variables were log-transformed to normalize their distribution. Step 1 Age, gender, race, and pubertal status entered together. Step 2 BMI percentile (left side of table) or WC (right side of table) added to step 1. Step 3 BMI percentile and WC together added to step 1. DISCUSSION We examined whether WC independently contributes to the prediction of total and abdominal fat and insulin resistance in black and white youths. Our primary finding is that although both BMI percentile and WC were significantly associated with measures of abdominal fat and insulin resistance, WC remained a significant correlate of abdominal adiposity and insulin sensitivity even after controlling for BMI percentile, independent of race. Further, we observed that WC explained a greater variance in abdominal adiposity and insulin sensitivity than did BMI percentile. These observations underscore the notion that WC should be incorporated into the assessment of childhood obesity, both in the clinical and the research setting, to identify those at increased health risks caused by excess total and abdominal fat. In adults, it is well established that WC is a predictor of morbidity 5,6 and mortality 26 independent of BMI. It has been suggested that the added health risk predicted by WC is explained by its ability to act as a surrogate for abdominal fat. 27 Janssen et al 7 reported that for a given BMI category, WC is an independent contributor of abdominal fat, and the use of WC in combination with BMI explained a greater variance in abdominal fat than BMI alone in adult men and women. Consistent with this, our findings in children and adolescents suggest that both BMI and WC are associated with total and abdominal subcutaneous fat. However, results from the present study indicate that in the pediatric population, WC alone is a strong predictor of visceral fat. Although it has been suggested that only small amounts of visceral fat are physiologically present before adulthood, 28 visceral fat is now recognized as a depot that predisposes children and adolescents to development of insulin resistance and type 2 diabetes. 19,29 A growing body of evidence suggests that WC is associated with risk factors for cardiovascular disease and insulin resistance in children and adolescents. 11,12,30 Savva et al 30 reported that WC is a better predictor of blood pressure and dyslipidemia than BMI in 10- to 14-year-old boys and girls. 192 Lee et al The Journal of Pediatrics February 2006

6 and proinsulin levels. Combined with the observation that WC has increased much faster than BMI during the past 10 to 20 years in youths, 13 our findings support the recommendation that WC should be included in the routine clinical assessment of childhood obesity to identify those at increased health risk for metabolic consequences caused by increased abdominal fat. The authors express their gratitude to the study participants and their parents and to the General Clinical Research Center staff for their assistance. Figure 2. Insulin sensitivity, fasting insulin, and proinsulin across the WC (left panel, A through C) and BMI percentile (right panel, D through F) groups. Data are shown as mean SEM. Further, Moreno et al 11 have shown that WC is the best anthropometric tool for the screening of the metabolic syndrome in children. Our observation that in a large sample of children and adolescents, WC is an independent predictor of insulin sensitivity measured by the euglycemic clamp expands previous observations 12,15,30,31 and indicates the usefulness of WC as an indicator of abdominal obesity-related metabolic dysfunction. Together, these observations suggest the need to include this simple measure in clinical practice to evaluate childhood obesity and related metabolic profiles. Accordingly, WC percentiles have been developed for children and adolescents in several countries. 24,32,33 Fernandez et al 24 reported sex-, race-, and age-specific WC percentiles in a large representative sample of US youths. In that study, the WC cutoff at the 90 th percentile of the WC distribution for 13-year-old black girls exceeds the WC value of 88 cm, identified as the cutoff for increased metabolic dysfunction in adult women. 24,27 Further studies are needed to examine whether the proposed cutoffs 24 are related to elevated health risks in a large sample of children and adolescents. Our findings provide compelling evidence that WC is a significant marker of total and abdominal fat independent of BMI percentiles in youths. Further, WC is a strong independent predictor of insulin resistance, elevated fasting insulin, REFERENCES 1. Rexrode KM, Carey VJ, Hennekens CH, Walters EE, Colditz GA, Stampfer MJ, et al. Abdominal adiposity and coronary heart disease in women. JAMA 1998;280: Ohlson LO, Larsson B, Svardsudd K, Welin L, Eriksson H, Wilhelmsen L, et al. The influence of body fat distribution on the incidence of diabetes mellitus: 13.5 years of follow-up of the participants in the study of men born in Diabetes 1985;34: Zhu S, Heshka S, Wang Z, Shen W, Allison DB, Ross R, et al. Combination of BMI and waist circumference for identifying cardiovascular risk factors in whites. Obes Res 2004;12: Ardern CI, Katzmarzyk PT, Janssen I, Ross R. Discrimination of health risk by combined body mass index and waist circumference. Obes Res 2003;11: Janssen I, Katzmarzyk PT, Ross R. Body mass index, waist circumference, and health risk: evidence in support of current National Institutes of Health guidelines. Arch Intern Med 2002;162: Janssen I, Katzmarzyk PT, Ross R. Waist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr 2004;79: Janssen I, Heymsfield SB, Allison DB, Kotler DP, Ross R. Body mass index and waist circumference independently contribute to the prediction of nonabdominal, abdominal subcutaneous, and visceral fat. Am J Clin Nutr 2002;75: Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 2000;320: Daniels SR, Khoury PR, Morrison JA. The utility of body mass index as a measure of body fatness in children and adolescents: differences by race and gender. Pediatrics 1997;99: Maynard LM, Wisemandle W, Roche AF, Chumlea WC, Guo SS, Siervogel RM. Childhood body composition in relation to body mass index. Pediatrics 2001;107: Moreno LA, Pineda I, Rodriguez G, Fleta J, Sarria A, Bueno M. Waist circumference for the screening of the metabolic syndrome in children. Acta Paediatr 2002;91: Maffeis C, Corciulo N, Livieri C, Rabbone I, Trifiro G, Falorni A, et al. Waist circumference as a predictor of cardiovascular and metabolic risk factors in obese girls. Eur J Clin Nutr 2003;57: McCarthy HD, Ellis SM, Cole TJ. Central overweight and obesity in British youth aged years: cross sectional surveys of waist circumference. BMJ 2003;326: Bjorntorp P. Portal adipose tissue as a generator of risk factors for cardiovascular disease and diabetes. Arteriosclerosis 1990;10: Katzmarzyk PT, Srinivasan SR, Chen W, Malina RM, Bouchard C, Berenson GS. Body mass index, waist circumference, and clustering of cardiovascular disease risk factors in a biracial sample of children and adolescents. Pediatrics 2004;114:e Freedman DS, Khan LK, Dietz WH, Srinivasan SR, Berenson GS. Relationship of childhood obesity to coronary heart disease risk factors in adulthood: the Bogalusa Heart Study. Pediatrics 2001;108: Freedman DS, Khan LK, Serdula MK, Dietz WH, Srinivasan SR, Berenson GS. The relation of childhood BMI to adult adiposity: the Bogalusa Heart Study. Pediatrics 2005;115:22-7. Waist Circumference Is An Predictor of Insulin Resistance In Black And White Youths 193

7 18. Arslanian SA, Saad R, Lewy V, Danadian K, Janosky J. Hyperinsulinemia in black children: decreased insulin clearance and increased insulin secretion and its relationship to insulin sensitivity. Diabetes 2002;51: Bacha F, Saad R, Gungor N, Janosky J, Arslanian SA. Obesity, regional fat distribution, and syndrome X in obese black versus white adolescents: race differential in diabetogenic and atherogenic risk factors. J Clin Endocrinol Metab 2003;88: Kuczmarski RJ, Ogden CL, Guo SS, Grummer-Strawn LM, Flegal KM, Mei Z, et al CDC Growth Charts for the United States: methods and development. Vital Health Stat : Danadian K, Balasekaran G, Lewy V, Meza MP, Robertson R, Arslanian SA. Insulin sensitivity in black children with and without family history of type 2 diabetes. Diabetes Care 1999;22: Arslanian SA, Lewy VD, Danadian K. Glucose intolerance in obese adolescents with polycystic ovary syndrome: roles of insulin resistance and beta-cell dysfunction and risk of cardiovascular disease. J Clin Endocrinol Metab 2001;86: Lewy VD, Danadian K, Witchel SF, Arslanian S. Early metabolic abnormalities in adolescent girls with polycystic ovarian syndrome. J Pediatr 2001;138: Fernandez JR, Redden DT, Pietrobelli A, Allison DB. Waist circumference percentiles in nationally representative samples of black, European- American, and Mexican-American children and adolescents. J Pediatr 2004;145: Barlow SE, Dietz WH. Obesity evaluation and treatment: Expert Committee recommendations: the Maternal and Child Health Bureau, Health Resources and Services Administration and the Department of Health and Human Services. Pediatrics 1998;102:E Bigaard J, Tjonneland A, Thomsen BL, Overvad K, Heitmann BL, Sorensen TI. Waist circumference, BMI, smoking, and mortality in middleaged men and women. Obes Res 2003;11: Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults: The Evidence Report: National Institutes of Health. Obes Res 1998;6(Suppl 2):51S-209S. 28. Goran MI, Kaskoun M, Shuman WP. Intra-abdominal adipose tissue in young children. Int J Obes Relat Metab Disord 1995;19: Weiss R, Dufour S, Taksali SE, Tamborlane WV, Petersen KF, Bonadonna RC, et al. Prediabetes in obese youth: a syndrome of impaired glucose tolerance, severe insulin resistance, and altered myocellular and abdominal fat partitioning. Lancet 2003;362: Savva SC, Tornaritis M, Savva ME, Kourides Y, Panagi A, Silikiotou N, et al. Waist circumference and waist-to-height ratio are better predictors of cardiovascular disease risk factors in children than body mass index. Int J Obes Relat Metab Disord 2000;24: Freedman DS, Serdula MK, Srinivasan SR, Berenson GS. Relation of circumferences and skinfold thicknesses to lipid and insulin concentrations in children and adolescents: the Bogalusa Heart Study. Am J Clin Nutr 1999;69: Katzmarzyk PT. Waist circumference percentiles for Canadian youth y of age. Eur J Clin Nutr 2004;58: McCarthy HD, Jarrett KV, Crawley HF. The development of waist circumference percentiles in British children aged y. Eur J Clin Nutr 2001;55: Years Ago in The Journal of Pediatrics ANTIBIOTICS AND CHEMOTHERAPEUTIC AGENTS IN THE TREATMENT OF UNCOMPLICATED RESPIRATORY INFECTIONS IN CHILDREN: ACONTROLLED STUDY. Hardy LM, Traisman HS. J Pediatr 1956; 48: It is a personal privilege to comment on this article written by two pediatricians who, between them, contributed over 100 years of outstanding service to the medical school of Northwestern University and to Children s Memorial Hospital. Drs Hardy and Traisman tested whether any of three antimicrobial regimens, given at the time of diagnosis, would reduce the duration of symptoms or incidence of complications in children with upper respiratory infections. Although today, we expect that hypotheses will be tested in controlled, double-blinded studies, this study stood in stark contrast to many of the anecdotal and uncontrolled reports filling the literature at the time. The results contributed importantly to the growing weight of evidence that favored supportive therapy alone for uncomplicated viral illnesses. The paper is replete with incidental observations that provide intriguing insight into medical care and society at the time. For example, the authors observed that only 23% of the clinic population at Children s Memorial had hemoglobin levels of 12, compared with 90% of the private patients of these pediatricians. Secondly, although the controlled study was conducted among hospital clinic patients, a similar non-randomized data collection was performed with private patients. The comparison between control and treatment groups was similar in the two parallel studies. Thomas P. Green, MD Department of Pediatrics Children s Memorial Hospital and Northwestern University Feinberg School of Medicine Chicago, Illinois YMPD /j.jpeds Lee et al The Journal of Pediatrics February 2006