Cardiovascular Risk Factors and Excess Adiposity Among Overweight Children and Adolescents: The Bogalusa Heart Study

ORIGINAL ARTICLES

Cardiovascular Risk Factors and Excess Adiposity Among Overweight Children and Adolescents: The Bogalusa Heart Study DAVID S. FREEDMAN, PHD, ZUGUO MEI, MD, PHD, SATHANUR R. SRINIVASAN, PHD, GERALD S. BERENSON, MD, WILLIAM H. DIETZ, MD

AND

Objective To explore the accuracy of various body mass index (BMI) cutpoints in identifying children who have excess adiposity (based on skinfold thicknesses), adverse levels of lipids, insulin, and blood pressures, and a high risk for severe adult obesity. Study design Cross-sectional (n ⴝ 10,099) and longitudinal (n ⴝ 2392) analyses were performed among subjects who participated in the Bogalusa Heart Study. Results Of children with a BMI >95th percentile (P) of the Centers for Disease Control (CDC) growth charts, 39% had at least two risk factors, 65% had excess adiposity, and 65% had an adult BMI of >35 kg/m2. Of those with a BMI >99th P, 59% had at least two risk factors, 94% had excess adiposity, and 88% had an adult BMI of >35 kg/m2. About 4% of children in the US now have a BMI >99th P. Conclusions The 99th P of BMI-for-age may be appropriate for identifying children who are at very high risk for biochemical abnormalities and severe adult obesity. More aggressive weight control strategies may be warranted for this subgroup. (J Pediatr 2007;150:12-7) here have been marked secular trends in childhood obesity, and about 18% of 6- to 19-year-olds in the US are now overweight.1 Many studies have shown that high levels of body mass index (BMI, kg/m2) among children and adolescents are associated with adverse levels of lipids, insulin, and blood pressure.2-4 Furthermore, longitudinal studies indicate that childhood BMI is associated with vascular fatty streaks and with raised lesions,5 obesity,2,4,6 left ventricular mass,7 and premature mortality in adulthood.8 Although steps to treat overweight children and adolescents have been recommended,9 the lack of reimbursement is a disincentive for health-care professionals to care for overweight pediatric patients.10,11 This may, in part, be because children with a BMIfor-age ⱖ95th percentile (P) of the Centers for Disease Control (CDC) growth charts are considered to be “overweight,”12,13 whereas the International Classification of Diseases, See editorial, p 3 9th edition (ICD-9) includes codes for obesity (278.0) and morbid obesity (278.01) but not for overweight. From the Division of Nutrition and Physical Synchronizing the language and ICD-9 codes is not difficult for obesity. A BMI Activity, Centers for Disease Control and 2 th ⱖ30 kg/m is used to identify adult obesity, and this cutpoint is about the 95 P of BMI Prevention, Atlanta, Georgia; and Tulane 14 Center for Cardiovascular Health, Tulane in the CDC growth charts for 19-year-old boys and 17-year-old girls. This corresponUniversity School of Public Health and dence may have influenced the Institute of Medicine to use the term obesity throughout Tropical Medicine, New Orleans, Louisiana. 15 its report on the prevention of childhood obesity. The findings and conclusions in this report are those of the authors and do not necAmong adults, more severe forms of obesity have been categorized as class 2 2 2 13 essarily represent those of the CDC. (35-39.9 kg/m ) or class 3 (ⱖ40 kg/m ) obesity. Although the anthropometric criterion Supported by National Institutes of Aging that can identify children and adolescents who are likely to have these more extreme forms Grant AG-16592. of adult obesity is unclear, several characteristics seem appropriate. We suggest that a child Submitted for publication Apr 11, 2006; last revision received Jun 23, 2006; accepted identified as very overweight, on the basis of BMI-for-age, should have a high probability Aug 23, 2006. of having excess body fat, adverse levels of several risk factors, and class 2 or 3 obesity in

T

BMI CDC DBP DXA HDL

12

Body mass index Centers for Disease Control Diastolic blood pressure Dual energy x-ray absorptiometry High-density lipoprotein

LDL NHANES P SBP

Low-density lipoprotein National Health and Nutrition Examination Survey Percentile Systolic blood pressure

Reprint requests: David S Freedman, CDC K-26, 4770 Buford Highway, Atlanta GA 30341. E-mail: [email protected]. 0022-3476/$ - see front matter Copyright © 2007 Mosby Inc. All rights reserved. 10.1016/j.jpeds.2006.08.042

adulthood. In addition, this classification should identify a reasonable number of very overweight children and adolescents for whom additional therapies are warranted. We explore the extent to which several different BMI-for-age cutpoints meet these criteria.

METHODS Study Population The Bogalusa (Louisiana) Heart Study is a communitybased study of cardiovascular disease risk factors in early life.16 Seven cross-sectional examinations of schoolchildren in Bogalusa were conducted between 1973 and 1994. Adults (18 to 37 years of age) who had been previously examined as children were examined in four studies from 1982 to 1996. Our cross-sectional analyses are restricted to 5- to 17year-olds who were fasting, and who had recorded values for weight, height, and levels of six cardiovascular disease risk factors: triglycerides, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, fasting insulin, systolic blood pressure (SBP), and diastolic blood pressure (DBP). These criteria resulted in 10,099 observations from 6731 children. Longitudinal analyses examined the relation of childhood BMI to adult obesity, and they were based on a cohort of 2392 children (5 to 14 years of age) who were re-examined in adulthood. As previously described,17 this cohort comprises about 37% of all age-eligible subjects. We used the 1999-2004 National Health and Nutrition Examination Survey (NHANES)18 to estimate the proportion of 5- to 17-year-olds in the US who have a BMI above various cutpoints. Pregnant girls were excluded from the analyses, as were persons with missing information on weight or height. Measurements In Bogalusa, height was measured with an Iowa Height Board (Specialized Center of Research-A, University of Iowa, Iowa City, Iowa), and weight with a balance beam metric scale (Detecto Scales Inc, Brooklyn, NY); BMI (kg/m2) was calculated as an index of relative weight. The sum of the triceps and subscapular skinfolds, which were measured using Lange Skinfold Calipers (Cambridge Scientific Industries, Cambridge, MD), is used as an index of adiposity. Sex-specific BMI-for-age percentiles and Z scores were calculated from the 2000 CDC Growth Charts.14 Childhood overweight is defined as a BMI-for-age ⱖCDC 95th P.13 We also examined the utility of the 96th through 99th percentiles, as calculated from parameters for the skewness (L), central tendency (M), and dispersion (S) of the CDC growth charts, to establish the category of “very overweight.” It should be realized that these more extreme BMI percentiles are estimated less accurately. Height and weight were measured in NHANES 1999 to 2004 during a physical examination using standardized protocols and calibrated equipment.19

Serum concentrations of triglycerides were determined using enzymatic procedures in a standardized laboratory, and concentrations of LDL and HDL cholesterol were determined using heparin-calcium precipitation and agar-agarose gel electrophoresis.20 Plasma insulin determinations were performed using a radioimmunoassay procedure (Phadebas Insulin Kit, Pharmacia Diagnostic AB, Uppsala, Sweden). Although differences in examination year complicate the comparison of risk factor levels across studies, mean lipid levels in the Bogalusa Heart Study are fairly similar to those seen in the 1970s in the Lipid Research Clinics Prevalence Study21 and in NHANES III (1988-1994).22 As previously described,16,23 right arm, sitting SBP and DBP were measured six times by trained observers with a mercury sphygmomanometer (Baumanometer, W.A. Baum Co Inc, Copiague, NJ). Because of differences in the methods used to obtain blood pressure, levels in the Bogalusa Heart Study are typically 5 to 10 mm Hg lower than those in other studies.23 Because risk factor levels and skinfold thicknesses vary by sex and age, we defined “adverse” levels relative to a child’s peers. Within each sex, risk factors were regressed on age, age2, and age3; the residuals would represent levels relative to children of the same sex and age. (Height and height2 were also included in the prediction of SBP and DBP.) To reduce heteroscedasticity, we regressed the absolute values of these residuals on age.24 Dividing each residual (from the first regression model) by its predicted absolute value (from the second model) yielded age-adjusted levels of each risk factor. An age-adjusted level of the skinfold sum, triglycerides, LDL cholesterol, and insulin ⱖ90th P was considered adverse, as was an HDL cholesterol level ⬍10th P. Because of the correlation between SBP and DBP, an adverse blood pressure level was defined as either a SBP or DBP ⱖ90th P. Although these cutpoints were based on the distribution of risk factors in Bogalusa, the lipid cutpoints are comparable to those reported by others. For example, of the 145 10- to 14-year-old Caucasian boys we classified as having an adverse LDL cholesterol level, 144 were also above the 90th P of LDL cholesterol (126 mg/dL) in the Lipids Research Clinics Prevalence Study.21 In addition, only 31 (2%) of the 1347 Caucasian boys who did not have an adverse LDL cholesterol level in Bogalusa had a level ⱖ126 mg/dL. However, because of differences in blood pressure methods,23 very few children in Bogalusa had a SBP or DBP above the 90th P of the National High Blood Pressure Education Program.25,26

Statistical Analyses The analyses, which were performed using Statistical Analysis Systems (SAS Institute, Cary, NC) and R,27 focus on the sensitivity and positive predictive value of a high BMI-for-age for excess adiposity, adverse risk factor levels, and adult obesity. In analyses of excess adiposity, for example, the sensitivity is the proportion of children with excess adiposity who have a high BMI, whereas the positive predictive

Cardiovascular Risk Factors and Excess Adiposity Among Overweight Children and Adolescents: The Bogalusa Heart Study

13

Table II. Prevalence of multiple risk factors and high skinfold thickness according to BMI percentile Number of Risk Factors BMI-for-Age Categories ⬍25 P 25 P - 49 P 50 P - 84 P 85 P - 94 P ⱖ95 P (overweight)‡ ⱖ96 P ⱖ97 P ⱖ98 P ⱖ99 P Percentiles 90 - 90.9 91 - 91.9 92 - 92.9 93 - 93.9 94 - 94.9 95 - 95.9 96 - 96.9 97 - 97.9 98 - 98.8 99 - 99.4 ⱖ99.5

Excess Adiposity*

>1

>2

>3

>4

(1801) (2215) (3458) (1400) (1225) (1011) (777) (523) (226)

25%† 29% 36% 51% 70% 73% 76% 80% 84%

5% 5% 9% 19% 39% 42% 46% 52% 59%

1% 1% 2% 5% 18% 20% 23% 27% 33%

0 0 0 1% 5% 5% 7% 8% 11%

0 0 1% 13% 65% 71% 78% 86% 94%

(122) (137) (169) (187) (168) (214) (234) (254) (297) (173) (53)

49% 50% 57% 56% 55% 52% 64% 69% 77% 83% 87%

16% 21% 25% 22% 21% 21% 29% 34% 46% 55% 72%

6% 4% 8% 7% 5% 7% 10% 16% 23% 33% 34%

1% 1% 2% 1% 2% 3% 1% 3% 6% 11% 11%

14% 12% 18% 20% 24% 38% 47% 60% 81% 92% 98%

(N)

*Defined as a skinfold sum ⱖ90th P relative to children of the same sex and age. †Values represent the percentage of children within each BMI category who have the specified number of risk factors or excess adiposity. ‡Percentages for the BMI ⱖ95th (and higher) categories represent the positive predictive value of the specified cutpoint.

RESULTS The mean age of the examined children in the crosssectional sample was 11.4 years (range, 5 to 17 years), and mean levels of various characteristics are shown in Table I (available at www.jpeds.com). About 12% of the children were overweight, and 2% had a BMI ⱖCDC 99th P. Several of the sex differences in risk factor levels varied by age, but girls had higher levels of triglycerides, LDL cholesterol, insulin, and DBP, whereas among 5- to 10-year-olds, boys had higher levels of HDL cholesterol than did girls. Overall, 26% 14

Freedman et al

100

100 80

80

< 12 years

60

≥12 years

60

40

Prevalence (%)

value is the proportion of children with a high BMI who truly have excess adiposity. The prevalences of adverse risk factors and excess adiposity were examined within various BMI categories, and associations are displayed graphically using locally weighted scatterplot smoothing (lowess).28 To illustrate the relation of BMI to excess adiposity, we plotted values of the skinfold sum versus age for the overweight children. We also show the 90th and 75th Ps of the skinfold sum by age in Figure 2 (available at www.jpeds.com); these values were calculated using quantile regression, a technique that allows one to estimate percentiles of a variable as a function of other variables.29 Analyses of data from NHANES 1999 to 2004 used sample weights to account for differential probabilities of selection, nonresponse, and noncoverage. Estimates of standard errors accounted for the complex sampling design.30

40

≥1 risk factor

20

20

≥2

≥3

0 0

20

40

60

80

≥4 0 100

0

20

40

60

80

100

40

60

80

100

100

100

Boys

80

Girls

80

60

60

40

40

20

20

0

0 0

20

40

60

80

100

0

20

BMI-for-Age Percentile Figure 1. The relation of BMI-for-age to the proportion of children with ⱖ1, ⱖ2, ⱖ3, and ⱖ4 risk factors. Proportions were smoothed using lowess, with a neighborhood width of 15%. Analyses are stratified by age (top panels) and sex (bottom panels).

of the children had at least one risk factor, and 4% had three or more risk factors. Table II and Figure 1 show the relation of BMI-for-age The Journal of Pediatrics • January 2007

Table III. Relation of childhood BMI to adult obesity Adulthood Childhood N

BMI P

Age

BMI

BMI >30 (%)

1161 832 130 121 122 26

0-49 50-84 85-89 90-94 95-98 >99

13 ⫾ 2* 12 ⫾ 2 13 ⫾ 2 12 ⫾ 2 13 ⫾ 2 12 ⫾ 3

22.7 ⫾ 4 27.1 ⫾ 5 30.3 ⫾ 5 32.4 ⫾ 6 37.1 ⫾ 7 43.6 ⫾ 9

5% 23% 47% 64% 84% 100%

BMI >35 (%)

BMI >40 (%)

1% 8% 16% 33% 60% 88%

0 2% 5% 13% 34% 65%

*Values are mean ⫾ SD.

to the number of adverse risk factors. As BMI-for-age increased, the proportion of children with at least two risk factor increased from 5% (BMI ⬍25 P) to 59% (BMI ⱖ99 P), and marked increases were also seen in the proportion of children with three or more risk factors. As seen in the bottom of Table I, these prevalences did not increase substantially between the 90th P and 95th P of BMI, but there were marked increases at higher BMI levels. The prevalence of ⱖ3 risk factors, for example, was 6% at the 90th P, 7% at the 95th P, and 33% at the 99th P. As indicated in Figure 1, these associations were markedly nonlinear, with substantial increases in the prevalence of multiple risk factors occurring only at very high BMIs. In addition, the associations did not vary substantially by age (top panels) or sex (lower panels). The prevalence of ⱖ3 risk factors among children with a BMI ⱖ 99th P, for example, was 32% among boys, 34% among girls, 34% among 5- to 10-year-olds, and 32% among 11- to 17-year-olds. The final column of Table II shows that the proportion of children with excess adiposity increased from 0% (BMI ⬍50 P) to 98% (BMI ⱖ99.5 P) across the BMI-for-age categories. Overall, excess adiposity was seen among 65% of the overweight children, and among 94% of those who had a BMI ⱖ99th P. These cutpoints also yielded sensitivities of 79% (BMI ⱖ95 P) and 21% (BMI ⱖ99 P), along with specificities of 95% and 99.8% in identifying excess adiposity (data not shown). Figure 2 (available at www.jpeds.com) shows levels of the skinfold sum by age for the 1225 overweight children. Although 35% of the overweight children did not have excess adiposity, only 5% (56/1225) had a skinfold sum ⬍75th P. Similarly, 6% of the 226 children with a BMI ⱖ99th P did not have excess adiposity, but only one child (a 6-year-old boy) had a skinfold sum ⬍75th P. The longitudinal relation of childhood BMI-for-age to adult (mean age, 27 years) levels was then examined (Table III). Whereas only 5% of the 1161 children with a BMI ⬍50 P became obese adults, 84% of the children with a BMI between the 95th and 98th Ps, and all of the children with a BMI ⱖ99th P, were obese in adulthood. In addition, 88% of children with a BMI ⱖ99th P had an adult BMI ⱖ35 kg/m2. We then used data from NHANES 1999 to 2004 to estimate the proportion of children in the US who have a

BMI ⱖ95th or ⱖ99th P. Overall, 17% of these 5- to 17-yearolds were overweight and 4% had a BMI ⱖ99th P, but the prevalences varied by sex and age (Table IV). The highest prevalences of overweight were seen among 8-year-old boys (25%), whereas the proportion of children who had a BMI ⱖ99th P reached 9% among 5-year-old boys.

DISCUSSION Children and adolescents who have high levels of BMI relative to their sex and age peers are likely to have multiple risk factors, excess adiposity, and a high risk for adult obesity. Because levels of BMI and metabolic risk factors are continuous, the classification of “very overweight” children will always be somewhat arbitrary, but we have shown that the 99th P of BMI-for-age (1) is associated with a greatly increased frequency of biochemical abnormalities, (2) has a high predictive value for adult BMI levels of ⱖ35 kg/m2, and (3) identifies a reasonable number (about 4%) of children and adolescents. The use of the 99th P of BMI-for-age to identify children and adolescents with more severe types of obesity is also reasonably consistent with the adult classifications. For example, the 99th Ps of the CDC growth charts among 17-year-olds are close to the adult cutpoint for class 2 obesity among boys (34.4 kg/m2) and close to the cutpoint for class 3 (extreme) obesity among girls (40.8 kg/m2).13 In addition, because of recent secular trends, the current (NHANES 1999-2004) 99th P of BMI at 16 years of age is about 40 kg/m2 among both boys and girls. The presence of multiple risk factors among children is associated with more extensive fatty streaks and fibrous plaques in later life,5 and the associations that we observed agree well with previous reports.31,32 Although the dichotomization of BMI and risk factor levels among children varies substantially across studies, a BMI ⱖCDC 95th P has a sensitivity of 49% and a specificity of 90% in identifying children with three or more risk factors.32 Furthermore, national data indicate that overweight adolescents are about 10 times as likely to have at least two risk factors as are those with a BMI ⬍85th P.31 Previous analyses have also examined the tracking of BMI, and fatter children have consistently been found to be more likely to become obese adults than are thinner chil-

Cardiovascular Risk Factors and Excess Adiposity Among Overweight Children and Adolescents: The Bogalusa Heart Study

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Table IV. Proportion of children who have BMI levels >95th P (overweight) or >99th P in NHANES 19992004 Boys

Girls CDC 99th P of BMI

Overweight

CDC 99th P of BMI

Overweight

Age (y)

N

Cutpoint (kg/m2)*

%

Cutpoint (kg/m2)

%†

N

Cutpoint (kg/m2)

%

Cutpoint (kg/m2)

%†

5 6 7 8 9 10 11 12 13 14 15 16 17

240 254 274 282 259 265 253 437 444 406 421 459 464

18.1 18.8 19.6 20.6 21.6 22.7 23.7 24.7 25.6 26.4 27.2 27.9 28.6

18 13 13 25 17 18 19 18 16 17 16 22 16

20.1 21.6 23.6 25.6 27.6 29.3 30.7 31.8 32.6 33.2 33.6 33.9 34.4

9 5 4 6 4 4 4 2 3 5 4 6 6

286 255 279 276 264 256 278 438 474 467 376 381 387

18.5 19.2 20.2 21.2 22.4 23.6 24.7 25.8 26.8 27.7 28.5 29.3 30.0

16 10 10 19 17 18 21 13 20 16 16 15 12

21.5 23.0 24.6 26.4 28.2 29.9 31.5 33.1 34.6 36.0 37.5 39.1 40.8

6 4 2 6 2 3 4 3 2 2 1 2 3

*Cutpoints are for the percentile (95th or 99th) at the midpoint of the year (e.g., 5.5 y). †The relative error for the estimated prevalences is the estimated prevalence divided by its standard error. The mean relative error in estimating the proportion of children with a BMI >99th P was 32%, and it ranged from 24% to 60% across sex and age groups.

dren.2,4,6 Of the 26 children with a BMI ⱖ99th P in our longitudinal analyses, 88% had an adult BMI ⱖ35 kg/m2 and 65% had an adult BMI ⱖ40 kg/m2. In addition, because BMI levels increase with age in adulthood, it would be expected that some of the very overweight children who had a BMI ⬍40 kg/m2 in early adulthood (mean age, 27 years) would be morbidly obese in later life. We may have therefore underestimated the probability that a very overweight child would have a BMI of 40 kg/m2 or more in adulthood. The limitations of BMI, which does not distinguish between fat mass and fat-free mass, as an indicator of obesity are well known.33 Furthermore, several studies of childhood BMI have found only moderate (r ⬍0.5) correlations with more accurate estimates of body fatness.34,35 It appears, however, that although the association between BMI and body fatness can be weak among non-overweight children, it is much stronger at higher BMI levels.36,37 Therefore, a BMI level ⱖCDC 95th P (and particularly ⱖ99th P) is a good indicator of excess adiposity.38 It is frequently stated that many children with excess adiposity do not have a high BMI.39 This low sensitivity, however, may largely be due to the cutpoints used for BMI and body fatness, and it has been found40 that decreasing the cutpoint for percentage of body fat from 37.5% to 30% greatly reduces (from 66% to 24%) the sensitivity of overweight in identifying obese girls. However, even if BMI-for-age and adiposity were perfectly correlated, if the prevalence of excess adiposity was 10% (for example) and the prevalence of overweight was 5%, the sensitivity could not exceed 50%. In the current study, the prevalences of overweight and excess adiposity were fairly similar (10% to 12%), and the resulting sensitivity was 79%. 16

Freedman et al

If a BMI-for-age ⱖ99th P is used to identify children for more aggressive treatment, it would be important to know the proportions (positive predictive values) of these children who have excess adiposity or at least one risk factor. Although 6% of the 226 children with a BMI ⱖ99th P did not have excess adiposity and 16% did not have adverse risk factors, additional analyses indicated that 98% (222/226) of these very overweight children had either excess adiposity or at least one risk factor. Therefore, it is likely that very few children with a BMI-for-age ⱖ99th P would have neither excess adiposity nor adverse risk factors. A clinical examination should exclude the very overweight child whose high BMI is because of increased lean body mass. Although it could be argued that other BMI cutpoints could be used to define “very overweight,” additional analyses indicated that the 98th BMI P would classify 8% of children as very overweight, and would substantially increase the number of false positives. In contrast, only 1% of children in NHANES 1999 to 2004 have a BMI ⱖ99.5 P. Some of the misclassification that we observed is likely because of measurement errors, and although these errors may be largest for skinfold thicknesses, all characteristics are subject to these errors. For example, one very overweight child (a 6-year-old boy with a BMI of 29.3 kg/m2) had a skinfold sum ⬍75th P. Although this child’s weight was 39.8 kg (using a balance beam scale), the recorded weight on an automatic scale was 19.8 kg, and the higher weight may have been a transcription error. In addition, it should be realized that adverse risk factor levels are also seen among non-overweight children. We found, for example, that about one-third of the children with a BMI between the 50th and 84th percentiles had at least one risk factor. The Journal of Pediatrics • January 2007

Population-based approaches for preventing and treating childhood overweight, which has now reached 18%,1 are important. However, more intensive weight control strategies, such as aggressive hypocaloric dietary therapy, pharmacotherapy, and bariatric surgery, may be warranted for very overweight children. Additional research is needed, however, to clarify the potential benefits and adverse effects of aggressive therapy for this group.10

REFERENCES 1. Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM. Prevalence of overweight and obesity in the United States, 1999-2004. JAMA 2006; 295:1549-55. 2. Must A, Strauss RS. Risks and consequences of childhood and adolescent obesity. Int J Obes Relat Metab Disord 1999;23(suppl 2):S2-S11. 3. Freedman DS, Dietz W, Srinivasan SR, Berenson GS. The relation of overweight to cardiovascular risk factors among children and adolescents: the Bogalusa Heart Study. Pediatrics 1999;103:1175-82. 4. Reilly JJ, Methven E, McDowell ZC, Hacking B, Alexander D, Stewart L, et al. Health consequences of obesity. Arch Dis Child 2003;88:748-52. 5. Berenson GS, Srinivasan SR, Bao W, Newman WP III, Tracy RE, Wattigney WA. Association between multiple cardiovascular risk factors and atherosclerosis in children and young adults. New Engl J Med 1998;338:1650-6. 6. Power C, Lake JK, Cole TJ. Measurement and long-term health risks of child and adolescent fatness. Int J Obes Relat Metab Disord 1997;21:507-26. 7. Li X, Li S, Ulusoy E, Chen W, Srinivasan SR, Berenson GS. Childhood adiposity as a predictor of cardiac mass in adulthood: the Bogalusa Heart Study. Circulation 2004;110:3488-92. 8. Engeland A, Bjorge T, Tverdal A, Sogaard AJ. Obesity in adolescence and adulthood and the risk of adult mortality. Epidemiology 2004;15:79-85. 9. Dietz WH, Robinson TN. Clinical practice. Overweight children and adolescents. N Engl J Med 2005;352:2100-9. 10. Tershakovec AM, Watson MH, Wenner WJ Jr, Marx AL. Insurance reimbursement for the treatment of obesity in children. J Pediatr 1999;134:573-8. 11. Story MT, Neumark-Stzainer DR, Sherwood NE, Holt K, Sofka D, Trowbridge FL, et al. Management of child and adolescent obesity: attitudes, barriers, skills, and training needs among health care professionals. Pediatrics 2002;110:210-14. 12. Himes JH, Dietz WH. Guidelines for overweight in adolescent preventive services: recommendations from an expert committee. Am J Clin Nutr 1994;59:307-16. 13. Kuczmarski RJ, Flegal KM. Criteria for definition of overweight in transition: background and recommendations for the United States. Am J Clin Nutr 2000;72:1074-81. 14. CDC National Center for Health Statistics. 2000 CDC Growth Charts: United States. Percentile Data Files with LMS Values. Available online at: http://www.cdc.gov/ nchs/data/nhanes/growthcharts/bmiage.txt. Accessed June 12, 2006. 15. Committee on Prevention of Obesity in Children and Youth, Institute of Medicine. Preventing Childhood Obesity: Health in the Balance. Washington, DC: The National Academies Press; 2004. 16. Berenson GS. Cardiovascular Risk Factors in Children. New York: Oxford University Press; 1980. 17. 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. 18. Centers for Disease Control and Prevention (CDC). National Center for Health Statistics (NCHS). National Health and Nutrition Examination Survey Data. Hyattsville, Md: US Department of Health and Human Services, Centers for Disease Control and Prevention. Available online at: http://www.cdc.gov/nchs/about/major/nhanes/ datalink.htm. Accessed November 28, 2006. 19. Lohman TG, Roche AF, Martorell R, eds. Anthropometric Standardization Reference Manual. Champaign, Ill: Human Kinetics Books, 1988.

20. Srinivasan SR, Frerichs RR, Webber LS, Berenson GS. Serum lipoprotein profile in children from a biracial community. The Bogalusa Heart Study. Circulation 1976;54:309-18. 21. National Cholesterol Education Program. Report of the expert panel on blood cholesterol levels in children and adolescents. Washington, DC: US Department of Health and Human Services; National Institutes of Health publication 91-2732. September 1991. 22. Hickman TB, Briefel RR, Carroll MD, Rifkind BM, Cleeman JI, Maurer KR, et al. Distributions and trends of serum lipid levels among United States children and adolescents ages 4-19 years: data from the Third National Health and Nutrition Examination Survey. Prev Med 1998;27:879-90. 23. Berenson GS, Cresanta JL, Webber LS. High blood pressure in the young. Ann Rev Med 1984;35:535-60. 24. Griffiths JK, Iles TC, Koduah M, Nix AB. Centile charts II: alternative nonparametric approach for establishing time-specific reference centiles and assessment of the sample size required. Clin Chem 2004;50:907-14. 25. Report of the Second Task Force on Blood Pressure Control in Children—1987. Task Force on Blood Pressure Control in Children. National Heart, Lung, and Blood Institute, Bethesda, Md. Pediatrics 1987;379:1-25. 26. Update on the 1987 Task Force Report on High Blood Pressure in Children and Adolescents: a working group report from the National High Blood Pressure Education Program. National High Blood Pressure Education Program Working Group on Hypertension Control in Children and Adolescents. Pediatrics 1996;98:649-58. 27. R Development Core Team (2005). R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. ISBN 3-90005107-0. Available online at: http://www.R-project.org. Accessed November 28, 2006. 28. Cleveland WS. The elements of graphing data. Monterey, Calif: Wadsworth Advanced Books and Software; 1985:170-8. 29. Koenker R (2005). Quantreg: quantile regression. R package version 3.82. Available online at: http://www.econ.uiuc.edu/⬃roger/research/rq/rq.html. Accessed November 28, 2006. 30. Lumley T (2005). Survey: analysis of complex survey samples. R package version 3.4-1. Available online at: http://cran.r-project.org/src/contrib/Descriptions/survey.html. Accessed November 28, 2006. 31. Cook S, Weitzman M, Auinger P, Nguyen M, Dietz WH. Prevalence of a metabolic syndrome phenotype in adolescents: findings from the third National Health and Nutrition Examination Survey, 1988-1994. Arch Pediatr Adolesc Med 2003;157:821-7. 32. 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:e198-e205. 33. Prentice AM, Jebb SA. Beyond body mass index. Obes Rev 2001;2:141-7. 34. 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;99:804-7. 35. Kerruish KP, O’Connor J, Humphries IR, Kohn MR, Clarke SD, Briody JN, et al. Body composition in adolescents with anorexia nervosa. Am J Clin Nutr 2002;75: 31-7. 36. Bray GA, Delaney JP, Harsha DW, Volaufova J, Champagne CC. Evaluation of body fat in fatter and leaner 10-y-old African American and white children: the Baton Rouge Children’s Study. Am J Clin Nutr 2001;73:687-702. 37. Mast M, Langnase K, Labitzke K, Bruse U, Preuss U, Muller MJ. Use of BMI as a measure of overweight and obesity in a field study on 5–7 year old children. Eur J Nutr 2002;41:61-7. 38. Freedman DS, Ogden CL, Berenson GS, Horlick M. Body mass index and body fatness in childhood. Curr Opin Clin Nutr Metab Care 2005;8:618-23. 39. Zimmermann MB, Gubeli C, Puntener C, Molinari L. Detection of overweight and obesity in a national sample of 6 –12-y-old Swiss children: accuracy and validity of reference values for body mass index from the US Centers for Disease Control and Prevention and the International Obesity Task Force. Am J Clin Nutr 2004;79:838-43. 40. Neovius MG, Linne YM, Barkeling BS, Rossner SO. Sensitivity and specificity of classification systems for fatness in adolescents. Am J Clin Nutr 2004;80:597-603.

Cardiovascular Risk Factors and Excess Adiposity Among Overweight Children and Adolescents: The Bogalusa Heart Study

17

Boys

Skinfold Sum (mm)

60

Girls 60

BMI ≥ 99 P

50

95 - 98 P 50

40

40

30

30

90 P

20

20

75 P

10

10

0

0 6

8

10

14

18

6

8

10

14

18

Age (y) Figure 2. Levels of the skinfold sum (subscapular plus triceps) by age among overweight boys (left) and girls (right) with a BMI ⱖCDC 95th P. Each point represents a child, and the dark triangles represent children with a BMI ⱖCDC 99th P. The lines represent the 90th and 75th Ps of the skinfold sum, at each age, as calculated by quantile regression.

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Freedman et al

The Journal of Pediatrics • January 2007

Table I. Various characteristics of the cross-sectional sample Boys

N % African-American BMI (kg/m2) BMI Z score BMI >CDC 95 P (overweight) BMI >CDC 99 P Skinfold sum (mm) Risk factors Triglycerides (mg/dL) LDL cholesterol (mg/dL) HDL cholesterol (mg/dL) Insulin (␮U/mL) SBP (mm Hg) DBP (mm Hg) Number of risk factors† 1 2 3 >4

Girls

5 - 10 y

11 - 17 y

5 - 10 y

11 - 17 y

2276 37% 17.3 ⫾ 3* 0.3 ⫾ 1.0 12% 3% 10 ⫾ 6

2704 37% 21.1 ⫾ 4 0.3 ⫾ 1.1 13% 2% 13 ⫾ 8

2408 38% 17.4 ⫾ 3 0.3 ⫾ 1.1 11% 2% 13 ⫾ 7

2711 39% 21.5 ⫾ 5 0.3 ⫾ 1.1 13% 2% 17 ⫾ 8

61 ⫾ 29 100 ⫾ 25 61 ⫾ 16 7⫾5 97 ⫾ 8 57 ⫾ 8

72 ⫾ 35 95 ⫾ 25 56 ⫾ 17 11 ⫾ 6 108 ⫾ 10 64 ⫾ 8

69 ⫾ 32 105 ⫾ 26 58 ⫾ 16 9⫾6 97 ⫾ 9 58 ⫾ 9

76 ⫾ 35 97 ⫾ 25 56 ⫾ 16 13 ⫾ 7 107 ⫾ 9 67 ⫾ 8

26% 9% 3% 1%

26% 8% 3% 1%

27% 8% 3% 3%

27% 10% 3% 1%

*Values are mean ⫾ SD. †Other than blood pressure, adverse risk factor levels are defined as a level >90th P or ⬍10th P (for HDL cholesterol). Elevated blood pressure is defined as SBP or DBP >90th P. The maximum number of possible risk factors was five.

Cardiovascular Risk Factors and Excess Adiposity Among Overweight Children and Adolescents: The Bogalusa Heart Study

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