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American Journal of Clinical Nutrition, Vol. 76, No. 3, 653-658, September 2002
© 2002 American Society for Clinical Nutrition


Original Research Communication

Predicting overweight and obesity in adulthood from body mass index values in childhood and adolescence1,2,3

Shumei Sun Guo, Wei Wu, William Cameron Chumlea and Alex F Roche

1 From the Departments of Community Health (SSG, WW, WCC, and AFR), Mathematics and Statistics (SSG), and Pediatrics (WW, WCC, and AFR), Wright State University, Dayton, OH.

See corresponding editorial on page 497.

2 Supported by grants HD 27063 and HD 12252 from the National Institutes of Health, Bethesda, MD.

3 Address reprint requests to SS Guo, Department of Community Health, Wright State University School of Medicine, 3171 Research Boulevard, Kettering, OH 45420. E-mail: shumei.guo{at}wright.edu.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background: The Centers for Disease Control and Prevention (CDC) introduced the clinical use of the body mass index (BMI; in kg/m2) in growth charts for young males and females.

Objective: This study updates our previous report with the use of new CDC BMI charts and definitions of adult overweight and obesity to predict adult overweight or obesity.

Design: Logistic models were fitted to relate adult overweight and obesity to childhood and adolescent BMI values at each age for 166 males and 181 females in the Fels Longitudinal Study and were applied to predict adult overweight and obesity at the 75th, 85th, and 95th percentiles on the CDC charts of childhood and adolescent BMI.

Results: A child or adolescent with a high BMI percentile on the CDC BMI-for-age growth charts has a high risk of being overweight or obese at 35 y of age, and this risk increases with age. For example, the probability of adult obesity at the 85th percentile for young males was <=20% to 17 y of age and 20–59.9% afterward; the corresponding probability for young females was 20–39.9% to 18 y of age and 40–59.9% afterward.

Conclusion: Our clinically applicable method assigns a child’s or adolescent’s BMI value to a group with a known probability of overweight or obesity in adulthood.

Key Words: Overweight • obesity • body mass index • children • adolescents • adults • risk analysis


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Recently, the Centers for Disease Control and Prevention (CDC) published revised growth charts for US children and adolescents (1). In this new set of growth charts, the CDC introduced the clinical use of the body mass index (BMI; in kg/m2) in BMI-for-age charts for young males and females aged 2–20 y. These new BMI charts were developed by using data from the National Health Examination Survey (NHES) Cycles II and III, data from the National Health and Nutrition Examination Surveys (NHANES) I and II, and data for children from 2 to 6 y of age from NHANES III (1). The introduction of these BMI-for-age charts is in response to continued concern for the high prevalence of overweight and obesity among US children (2, 3).

Previously, we analyzed serial data from the Fels Longitudinal Study to evaluate the ability of childhood and adolescent BMI values to predict adult overweight, defined as a BMI >= 26 and >=28 for women and men, respectively (4). In that report, a percentile value was assigned to each childhood or adolescent BMI value by using sex- and age-specific NHANES II reference data for white children (5). The assigned BMI percentile values in childhood and adolescence were related to subsequent adult overweight status by using logistic regression. The fitted logistic models estimated the probability of adult overweight at 35 y of age for children and adolescents with BMI values at the 50th, 75th, 85th, and 95th percentiles. We determined that Fels children and adolescents with high BMI values on the basis of NHANES II percentiles had a known probability of high BMI values in adulthood (4). The higher the childhood or adolescent BMI percentile and the older the child or adolescent, the greater was the risk of being overweight at 35 y of age (4). The development of overweight or obesity in childhood and adolescence is related to subsequent overweight or obesity in adulthood and an increased risk of adult morbidity and mortality (6, 7).

In light of the availability of the recently published CDC BMI-for-age growth charts in pediatric clinics and the health importance of identifying and characterizing the long-term effects of childhood and adolescent obesity (8), we revised our previous work (4) with 3 major changes. First, the definition of overweight was updated and a definition of obesity was added to reflect current knowledge and recommendations. For persons aged 35 y, adult overweight is defined as a BMI >= 25 and adult obesity is defined as a BMI >= 30. These new definitions follow the recommendations of the World Health Organization; the National Heart, Lung, and Blood Institute; the National Institutes of Health; and the US Department of Health and Human Services (911). Second, childhood and adolescent BMI values are now related separately to these adult definitions of overweight and obesity by using logistic regression. Third, the probabilities of adult overweight and obesity were derived from childhood and adolescent BMI values at the 75th, 85th, and 95th percentiles by using the new CDC BMI-for-age growth charts (1). This new analysis and report allow one to use these BMI-for-age charts to determine a child’s or adolescent’s risk of being overweight or obese as an adult. High BMI percentile values in childhood or adolescence can assist us in identifying and selecting children and adolescents at risk and in assigning to them probabilities of adult overweight or obesity. This health information can help those children and adolescents who are at risk and in need of close monitoring or intervention.


    SUBJECTS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Sample
The data were obtained from 166 male and 181 female white participants in the Fels Longitudinal Study. Data for those who were pregnant or had known diseases were excluded. Fels participants were enrolled at or soon after birth and were not selected with regard to factors known to be associated with obesity (12). BMI values were computed from serial, annual Fels data for weight and stature from 3 to 20 y of age and from 30 to 39 y of age. Because of missed measurements at various ages, data are missing for some participants at some ages; thus, at any age or for any age group, the number of participants varies and therefore differs slightly from the total number of participants. The study protocol was approved by the Institutional Review Board of Wright State University, and participants signed an informed consent statement.

Statistical methods
In the Fels Longitudinal Study, data are collected at 3-mo intervals for the first year, at 6-mo intervals thereafter to 18 y of age, and every 2 y thereafter (12). There are few BMI values for Fels children aged <3 y because recumbent length is measured instead of stature. Therefore, the analysis in the present study was conducted for each annual age from 3 to 18 y and at 20 y. An annual age is defined as the age plus or minus 6 mo (eg, the annual age for 3 y is 2.5–3.5 y). Within each annual age, the BMI values of all participants were averaged. A BMI value for each participant at 35 y of age was obtained by averaging all available BMI values from 30 to 39 y of age. Logistic regression was applied to separately relate overweight and obesity in adulthood to childhood and adolescent BMI values at each annual age with the use of PROC LOGISTIC in SAS (13). From these Fels fitted logistic models, the probabilities at 35 y of age of having a BMI >= 25 (overweight) or >=30 (obesity) were estimated by using average BMI values at the 75th, 85th, and 95th percentiles within each defined annual age of the CDC BMI-for-age growth charts.

Receiver operating characteristic curves, which are plots of sensitivity (percentage of true-positive results) along the vertical axis against the 1-specificity (percent false-positive rate) along the horizontal axis, for BMI values at 3, 8, 13, and 18 y of age for prediction of BMI >= 25 and >=30 at 35 y of age were plotted separately for young males and females. Each age-specific curve represents the relation between sensitivity and 1-specificity at 3, 8, 13, or 18 y of age. The height of each curve increased with age, indicating that the false-positive rate decreased or the specificity increased for a particular level of sensitivity, eg, 80%. If a curve is steep, it is an indication of a high sensitivity and specificity and an accurate prediction. These receiver operating characteristic curves were used to select cutoffs for the separate prediction of overweight and obesity. In the present study, we selected the BMI cutoffs at 18 y of age for a sensitivity level of 80%. Relative risks and their SEs were calculated for the selected childhood and adolescent cutoffs in relation to risks in adulthood (14).


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Sample sizes and mean (±SD) BMI values at 3, 8, 13, 18, and 35 y of age are shown in Table 1Go by sex and by the absence or presence of overweight or obesity at 35 y of age. The selected ages represent early and late childhood, pubescence, and postpubescence. For both sexes, overweight or obese adults at 35 y of age had significantly higher BMI values in childhood and adolescence (P < 0.05) than did nonoverweight or nonobese adults.


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TABLE 1 . BMI values at 3, 8, 13, 18, and 35 y of age by sex and by the absence or presence in adulthood of overweight or obesity or of obesity1
 
For young males and females with childhood and adolescent BMI values at the 75th, 85th, and 95th percentiles, the probabilities of overweight or obesity at 35 y of age are shown in Tables 2 and 3GoGo, respectively. Overall, these probabilities increased with age. The probabilities of adult overweight (Table 2Go) at the 75th, 85th, and 95th childhood and adolescent BMI percentiles were significantly greater for young males than for young females (P < 0.05), but there was no sex difference after 13 y of age at the 95th percentile. However, the probabilities for adult obesity (Table 3Go) were significantly greater for young females than for young males at the 75th, 85th, and 95th percentiles at all ages. Except for those in the 95th percentile at 20 y of age, the young males and females had a greater risk of overweight than of obesity in adulthood at all of the ages from 3 to 20 y.


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TABLE 2 . Probabilities of adult overweight (BMI >= 25) at 35 y of age for young males and females with BMI values at the 75th, 85th, and 95th percentiles on the Centers for Disease Control and Prevention BMI-for-age growth charts
 

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TABLE 3 . Probabilities of adult obesity (BMI >= 30) at 35 y of age for young males and females with BMI values at the 75th, 85th, and 95th percentiles on the Centers for Disease Control and Prevention BMI-for-age growth charts
 
Receiver operating characteristic curves for BMI values at 3, 8, 13, and 18 y of age for prediction of BMI >= 25 and >=30 at 35 y of age were calculated separately for the males and the females. The height of each curve increased with age, indicating that the false-positive rate decreased for a particular level of sensitivity, eg, 80%. At 18 y of age, the BMI values for predicting the risk of obesity with 80% sensitivity had specificity rates (1-percent false-positive rates) of 84% for the males and 76% for the females; the corresponding BMI value was approximately at the 72nd percentile. At 80% sensitivity, the accuracy of prediction for overweight and obesity in adulthood improved as a function of age, especially in the males, but at ages <14;18 y, the accuracy of prediction for overweight and obesity in adulthood was better for the females than for the males.

The BMI values at 18 y of age at the 50th and 72nd percentiles were chosen as cutoffs for identifying overweight and obesity in adulthood at 35 y of age. The BMI values at these percentiles had greater sensitivity and specificity than did those at other percentiles (Table 4Go). The probability of overweight at 35 y of age predicted from BMI values at or above the 50th percentile at 18 y of age (Table 4Go) was 0.69 for the males (53 of 77) and 0.56 for the females (35 of 63). The sensitivities were 0.83 for the males and 0.74 for the females, and the specificity rates were 0.72 for the males and 0.73 for the females. Using the BMI cutoff of the 50th percentile at 18 y of age, the relative risks of adult overweight were 12.1 (95% CI: 5.49, 27.3) for the males and 7.92 (95% CI: 3.61, 17.4) for the females. Likewise, the probability of adult obesity predicted from BMI values at or above the 72nd percentile at 18 y of age was 0.36 for both the males (15 of 42) and the females (13 of 36). The sensitivities of the prediction of adult obesity were 0.83 for the males and 0.76 for the females, and the specificities were 0.79 for the males and 0.83 for the females. Using the BMI cutoff of the 72nd percentile at 18 y of age, the relative risks of adult obesity were 19.3 (95% CI: 5.20, 71.4) for the males and 15.7 (95% CI: 4.69, 52.5) for the females.


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TABLE 4 . Sensitivity (Se), specificity (Sp), and odds ratio (OR) of the selected BMI cutoffs at 18 y of age of the 50th or 72nd percentile for predicting overweight or obesity, respectively, in adulthood at 35 y of age
 
Probability of overweight at 35 y of age
The 75th, 85th, and 95th reference percentiles from the CDC national reference data for BMI values for young males and females aged 3–20 y are shown in Figures 1–4GoGoGoGo. The probabilities of adult overweight based on childhood and adolescent BMI percentiles are shown in Figures 1 and 2GoGo. The lines for the 3 percentiles in Figures 1 and 2GoGo are shaded differentially to indicate the age ranges during which the probability of overweight at 35 y of age was <40%, 40–59.9%, 60–79.9%, or >=80%. For example, as shown in Figure 2Go, a girl aged 12 y with a BMI of 25 was at the 95th percentile and had a >=80% probability of adult overweight. The probability of having a BMI >= 25 at 35 y of age increased with childhood and adolescent BMI percentile and with age. Young males with a childhood or adolescent BMI at the 75th percentile had a probability of adult overweight of 40–59.9% from 3 to 14 y of age, after which the probability was 60–79.9% until 20 y of age. Young females with a BMI in childhood or adolescence at the 75th percentile had a probability of adult overweight of <40% from 3 to 6 y of age, of 40–59.9% from 6 to 18 y of age, and of 60–79.9% from 18 to 20 y of age. At the 85th percentile, the probability for young males was 60–79.9%, except at ages younger than 6 y (40–59.9%) and at ages older than 16 y (>=80%). For young females, the probability at the 85th percentile was 40–59.9% to 10 y of age, 60–79.9% from 10 to 18 y of age, and >=80% after 18 y of age. The probability of adult overweight for those with a childhood or adolescent BMI at the 95th percentile was 40–59% for girls from 3 to 4 y of age and 60–79.9% for boys from 3 to 8 y of age and girls from 4 to 10 y of age; at older ages the probability was >=80% for each sex.



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FIGURE 1. . The probabilities of adult overweight for young males based on the 75th, 85th, and 95th BMI percentiles in childhood and adolescence from the CDC BMI-for-age growth charts.

 


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FIGURE 2. . The probabilities of adult overweight for young females based on the 75th, 85th, and 95th BMI percentiles in childhood and adolescence from the CDC BMI-for-age growth charts.

 


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FIGURE 3. . The probabilities of adult obesity for young males based on the 75th, 85th, and 95th BMI percentiles in childhood and adolescence from the CDC BMI-for-age growth charts.

 


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FIGURE 4. . The probabilities of adult obesity for young females based on the 75th, 85th, and 95th BMI percentiles in childhood and adolescence from the CDC BMI-for-age growth charts.

 
Probability of obesity at 35 y of age
The probabilities of adult obesity based on childhood and adolescent BMI percentiles are shown in Figures 3 and 4GoGo. For a childhood or adolescent BMI at the 75th percentile, the probability of adult obesity was <20% at all ages for young males and from 3 to 18 y of age for young females. At the 85th percentile, the probability for young males was also <20% to 17 y of age and 40–59% after 18 y of age. For young females, the probability at the 85th percentile was 20–39.9% from 4 to 18 y of age, after which the probability was 40–59.9%. For young males, the probability of adult obesity for those with a childhood or adolescent BMI at the 95th percentile was <20% from 3 to 4 y of age, 20–39.9% from 4 to 12 y of age, 40–59.9% from 12 to 17 y of age, and >=60% afterward. For young females, the probability at the 95th percentile was 20–39.9% from 3 to 5 y of age, 40–59.9% from 5 to 12 y of age, and >=60% from 12 to 20 y of age.


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The present findings support our earlier work (4, 6) showing that BMI values during childhood and adolescence are important risk factors for the presence of adult overweight or obesity and the attendant risks of increased morbidity and mortality (15, 16). In the earlier article (4), we showed the value of childhood and adolescent BMI percentiles for predicting overweight at 35 y of age. In the present study, we further show the clinically predictive value of the CDC BMI-for-age growth charts for adult overweight and obesity. BMI has a high correlation with total body fat and percentage of body fat in children and adults (17), but it is not a precise indicator of overweight or obesity (18). A high BMI value for an individual child or adult can be due to high fat-free mass (19). Nevertheless, BMI is the most commonly used index of overweight and obesity for which cutoffs are established (10).

In the present study, adult overweight was categorized as a BMI >= 25 and adult obesity as a BMI >= 30. The present findings, like our previous ones, show that the probability of adult overweight and obesity based on childhood and adolescent BMI values increases with age during childhood and adolescence (4). This result shows that high childhood or adolescent BMI values, ie, overweight or obesity in childhood or adolescence, are important risk factors for adult overweight and obesity. These findings, along with those of other researchers, emphasize the continued importance of adolescence as one of the significant "critical periods" in the development of adult obesity (6, 8, 20). The extent of the increase in probabilities of adult overweight and obesity with age was also greater for children with BMI values at the 95th percentile than for those with BMI values at the 75th percentile regardless of their age.

In the present study, more than one-half of the children and adolescents with BMI values at the 75th percentile on the new CDC BMI-for-age growth charts had a risk of being overweight as adults. Children and adolescents with BMI values at the 95th percentile had a 62–98% likelihood of being overweight at 35 y of age. More than 10% of the children and adolescents with BMI values at all ages at the 75th percentile on the CDC BMI-for-age growth charts had a risk of being obese as adults. Among the children and adolescents with BMI values at the 95th percentile, approximately one-fifth of the boys aged <=8 y became obese adults, as did one-third of the young males aged between 8 and 13 y and more than one-half of those aged >=13 y. Among the young females with BMI values at the 95th percentile, one-third of those aged <=8 y, more than one-half of those aged between 8 and 13 y, and two-thirds of those aged >=13 y were at risk of being obese at 35 y of age.

The sensitivity and specificity of selected childhood and adolescent BMI cutoffs in relation to adult BMI >= 25 and >=30 were analyzed for ages 3, 8, 13, and 18 y. The age-specific cutoffs may be used to evaluate an individual child’s or adolescent’s BMI values. For example, an 18-y-old male whose BMI value exceeds the 72nd percentile on the CDC BMI-for-age growth charts will have an {approx}40% probability of becoming an obese man at 35 y of age. The sensitivity and specificity at 3, 8, and 13 y of age were lower than those at 18 y of age for the chosen cutoff, and they were lower in the males than in the females. The sensitivity and specificity of the chosen cutoff (50th percentile for overweight and 72nd percentile for obesity) were excellent for predicting overweight and obesity at 35 y of age from BMI values at 18 y of age. This cutoff could facilitate public health screening programs by detecting children and adolescents with a high probability of being overweight or obese at 35 y of age.

When the plots of the probabilities in the present study are compared with those in our previous study (4), it is apparent that the risk of adult overweight for these children at any age has increased for those with high BMI percentiles on the 2000 CDC BMI growth-for-age charts. In our previous study, young males at the 75th BMI NHANES II percentile after the age of 14 y only had a 20–30% risk of adult overweight, but young males at these ages now have a 60–80% risk of being overweight as adults (Figure 1Go). Previously, boys as young as 5 or 6 y of age at the 75th percentile had a risk of adult overweight of <20%, but boys at these ages at the 75th percentile now have a risk of 40–60% (Figure 1Go). Similar associations between the findings of the previous study and those of the present study occur at the 85th and 95th BMI percentiles for males and females from 3 to 20 y of age. Clearly, the increased prevalence of overweight and obesity reported among US children and adolescents (2) has contributed to a corresponding increase in those who will predictably become overweight or obese as adults. These increases in the predicted probability of adult overweight or obesity are also affected by a change in the definition of adult overweight from a BMI >= 26 for women and >=28 for men to a BMI >= 25 for both sexes.

The prevalence of overweight and obesity among children, adolescents, and adults is a health problem in the United States and around the world (2, 2123). The probabilities reported here should be useful in clinical and public health assessments of children and adolescents with high BMI values on the new CDC charts. BMI values should be calculated for all children and adolescents, and a child or adolescent with a BMI at the 85th percentile or higher should be evaluated closely at all ages to confirm or rule out excess adiposity. Efforts should be made during childhood and adolescence to reduce high BMI values. This is preferable to waiting until adulthood when the pathophysiologic changes associated with overweight and obesity are likely to be established and when it is difficult to change lifestyles. Because children with high BMI values will be seen at repeated visits, one should also pay close attention to the patterns of change in the BMI values. We have also reported that the pattern of change in BMI with age, such as its velocity, is also a significant predictor of adult values for BMI and body fatness (6). Thus, the utility of BMI to predict overweight and obesity from childhood to adulthood is considerable. This is a very useful index for characterizing and monitoring the onset, development, and degree of overweight and obesity from childhood to adulthood.

Although the data used in this study were from white children and adolescents, the CDC BMI-for-age growth charts were developed from data on white, black, and Mexican American children and adolescents in the United States (6). White and black children and adolescents are represented at all ages, whereas Mexican American children are represented only from 2 to 6 y of age (6). When the probabilities and risk relations in the present study are applied to nonwhite ethnic or racial groups of children and adolescents, the results may be different from those presented. However, ethnic or racial differences in overweight and obesity are affected by nonbiological causes, and there is an increased degree of genetic admixture among children in the United States. Therefore, it is reasonable to assume that similar probabilities and risk relations for BMI between childhood, adolescence, and adulthood could exist in other ethnic or racial groups.


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. Kuczmarski RJ, Ogden CL, Grummer-Strawn LM, et al. CDC growth charts: United States.Adv Data 2000;314:1–28.[Medline]
  2. Troiano RP, Flegal KM, Kuczmarski RJ, Campbell SM, Johnson CL. Overweight prevalence and trends for children and adolescents: the National Health and Nutrition Examination Surveys, 1963 to 1991.Arch Pediatr Adolesc Med 1995;149:1085–91.[Abstract]
  3. Ogden CL, Troiano RP, Briefel RR, Kuczmarski RJ, Flegal KM, Johnson CL. Prevalence of overweight among preschool children in the United States, 1971 through 1994. Pediatrics [serial online] 1997;99:e1. Internet: http://www.pediatrics.org/cgi/content/full/99/4/e1 (accessed 24 June 2002).
  4. Guo S, Chumlea WC, Roche AF, Gardner JD, Siervogel RM. The predictive value of childhood body mass index values for overweight at age 35 years.Am J Clin Nutr 1994;59:810–9.[Abstract/Free Full Text]
  5. Najjar MF, Rowland M. Anthropometric reference data and prevalence of overweight, United States, 1976–80. Vital Health Stat 11 1987;1–73.
  6. Guo SS, Huang C, Maynard LM, et al. BMI during childhood, adolescence, and young adulthood in relation to adult overweight and adiposity: the Fels Longitudinal Study.Int J Obes Relat Metab Disord 2000;24:1628–35.[Medline]
  7. Must A, Jacques P, Dallal G, Bajema C, Dietz W. Long-term morbidity and mortality of overweight adolescents. A follow-up of the Harvard Growth Study of 1922 to 1935.N Engl J Med 1992;327:1350–5.[Abstract]
  8. Dietz WH, Gortmaker SL. Preventing obesity in children and adolescents. In: Fielding J, Brownson R, Starfield B, eds. Annual review of public health. Atlanta: Division of Nutrition and Physical Activity, Centers for Disease Control and Prevention, 2001:337–53.
  9. US Department of Health and Human Services, ed. Healthy people 2010: understanding and improving health. 2nd ed. Washington, DC: US Government, 2000.
  10. World Health Organization. Obesity: preventing and managing the global epidemic. Geneva: World Health Organization Programme of Nutrition, 1998.
  11. National Heart Lung and Blood Institute. The sixth report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. Bethesda, MD: National Institutes of Health, 1997:1–70.
  12. Roche AF. Growth, maturation, and body composition: the Fels Longitudinal Study 1929–1991. Cambridge, United Kingdom: Cambridge University Press, 1992.
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  18. Forbes GB. Lean body mass-body fat interrelationships in humans.Nutr Rev 1987;45:225–31.[Medline]
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  20. Dietz W. Critical periods in childhood for the development of obesity.Am J Clin Nutr 1994;59:955–9.[Abstract/Free Full Text]
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Received for publication August 27, 2001. Accepted for publication March 26, 2002.


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M. Garipagaoglu, N. Oner, U. Vatansever, M. Inan, Y. Kucukugurluoglu, and C. Turan
Dietary Intakes of Adolescents Living in Edirne, Turkey
J. Am. Coll. Nutr., June 1, 2008; 27(3): 394 - 400.
[Abstract] [Full Text] [PDF]


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The Journal of School NursingHome page
S. A. Stoddard, M. Y. Kubik, and C. Skay
Is School-Based Height and Weight Screening of Elementary Students Private and Reliable?
The Journal of School Nursing, February 1, 2008; 24(1): 43 - 48.
[Abstract] [Full Text] [PDF]


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PediatricsHome page
A. C. Skinner, M. L. Mayer, K. Flower, and M. Weinberger
Health Status and Health Care Expenditures in a Nationally Representative Sample: How Do Overweight and Healthy-Weight Children Compare?
Pediatrics, February 1, 2008; 121(2): e269 - e277.
[Abstract] [Full Text] [PDF]


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PediatricsHome page
N. F. Krebs, J. H. Himes, D. Jacobson, T. A. Nicklas, P. Guilday, and D. Styne
Assessment of Child and Adolescent Overweight and Obesity
Pediatrics, December 1, 2007; 120(Supplement_4): S193 - S228.
[Abstract] [Full Text] [PDF]


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Ther Adv Cardiovasc DisHome page
P. Velasquez-Mieyer, C. P. Neira, R. Nieto, and P. A. Cowan
Review: Obesity and cardiometabolic syndrome in children
Therapeutic Advances in Cardiovascular Disease, October 1, 2007; 1(1): 61 - 81.
[Abstract] [PDF]


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Am. J. Physiol. Regul. Integr. Comp. Physiol.Home page
S. J. Spencer, A. Mouihate, M. A. Galic, S. L. Ellis, and Q. J. Pittman
Neonatal immune challenge does not affect body weight regulation in rats
Am J Physiol Regulatory Integrative Comp Physiol, August 1, 2007; 293(2): R581 - R589.
[Abstract] [Full Text] [PDF]


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JAMAHome page
M. Savoye, M. Shaw, J. Dziura, W. V. Tamborlane, P. Rose, C. Guandalini, R. Goldberg-Gell, T. S. Burgert, A. M. G. Cali, R. Weiss, et al.
Effects of a Weight Management Program on Body Composition and Metabolic Parameters in Overweight Children: A Randomized Controlled Trial
JAMA, June 27, 2007; 297(24): 2697 - 2704.
[Abstract] [Full Text] [PDF]


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Am. J. Clin. Nutr.Home page
A. C. Nooyens, L. L. Koppes, T. L. Visscher, J. W. Twisk, H. C. Kemper, A J. Schuit, W. van Mechelen, and J. C Seidell
Adolescent skinfold thickness is a better predictor of high body fatness in adults than is body mass index: the Amsterdam Growth and Health Longitudinal Study
Am. J. Clinical Nutrition, June 1, 2007; 85(6): 1533 - 1539.
[Abstract] [Full Text] [PDF]


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Health Educ ResHome page
G.-J. de Bruijn, S. P. J. Kremers, H. de Vries, W. van Mechelen, and J. Brug
Associations of social-environmental and individual-level factors with adolescent soft drink consumption: results from the SMILE study
Health Educ. Res., April 1, 2007; 22(2): 227 - 237.
[Abstract] [Full Text] [PDF]


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RadiologyHome page
G. Taylor
Good Fat, Bad Fat-Does Location Matter?
Radiology, March 1, 2007; 242(3): 645 - 646.
[Full Text] [PDF]


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Scand J Public HealthHome page
N. Karnehed, F. Rasmussen, and M. Kark
Obesity in young adulthood and later disability pension: A population-based cohort study of 366,929 Swedish men
Scand J Public Health, January 1, 2007; 35(1): 48 - 54.
[Abstract] [PDF]


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Diabetes CareHome page
K. Asao, W.H. L. Kao, K. Baptiste-Roberts, K. Bandeen-Roche, T. P. Erlinger, and F. L. Brancati
Short Stature and the Risk of Adiposity, Insulin Resistance, and Type 2 Diabetes in Middle Age: The Third National Health and Nutrition Examination Survey (NHANES III), 1988-1994
Diabetes Care, July 1, 2006; 29(7): 1632 - 1637.
[Abstract] [Full Text] [PDF]


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J Am Coll CardiolHome page
M. Chinali, G. de Simone, M. J. Roman, E. T. Lee, L. G. Best, B. V. Howard, and R. B. Devereux
Impact of Obesity on Cardiac Geometry and Function in a Population of Adolescents: The Strong Heart Study
J. Am. Coll. Cardiol., June 6, 2006; 47(11): 2267 - 2273.
[Abstract] [Full Text] [PDF]


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Arch Pediatr Adolesc MedHome page
S. E. Anderson, P. Cohen, E. N. Naumova, and A. Must
Association of Depression and Anxiety Disorders With Weight Change in a Prospective Community-Based Study of Children Followed Up Into Adulthood
Arch Pediatr Adolesc Med, March 1, 2006; 160(3): 285 - 291.
[Abstract] [Full Text] [PDF]


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PediatricsHome page
K. C. Eckstein, L. M. Mikhail, A. J. Ariza, J. S. Thomson, S. C. Millard, H. J. Binns, and for the Pediatric Practice Research Group
Parents' Perceptions of Their Child's Weight and Health
Pediatrics, March 1, 2006; 117(3): 681 - 690.
[Abstract] [Full Text] [PDF]


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PediatricsHome page
E. W. Demerath, C. M. Schubert, L. M. Maynard, S. S. Sun, W. C. Chumlea, A. Pickoff, S. A. Czerwinski, B. Towne, and R. M. Siervogel
Do Changes in Body Mass Index Percentile Reflect Changes in Body Composition in Children? Data From the Fels Longitudinal Study
Pediatrics, March 1, 2006; 117(3): e487 - e495.
[Abstract] [Full Text] [PDF]


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Am. J. Clin. Nutr.Home page
J. Dwyer
Starting down the right path: nutrition connections with chronic diseases of later life
Am. J. Clinical Nutrition, February 1, 2006; 83(2): 415S - 420S.
[Abstract] [Full Text] [PDF]


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Scand J Public HealthHome page
M. Kark and F. Rasmussen
Growing social inequalities in the occurrence of overweight and obesity among young men in Sweden
Scand J Public Health, December 1, 2005; 33(6): 472 - 477.
[Abstract] [PDF]


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Diabetes Spectr.Home page
P. Velasquez-Mieyer, S. Perez-Faustinelli, and P. A. Cowan
Identifying Children at Risk for Obesity, Type 2 Diabetes, and Cardiovascular Disease
Diabetes Spectr, October 1, 2005; 18(4): 213 - 220.
[Abstract] [Full Text] [PDF]


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PediatricsHome page
E. P. Whitlock, S. B. Williams, R. Gold, P. R. Smith, and S. A. Shipman
Screening and Interventions for Childhood Overweight: A Summary of Evidence for the US Preventive Services Task Force
Pediatrics, July 1, 2005; 116(1): e125 - e144.
[Abstract] [Full Text] [PDF]


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J. Clin. Endocrinol. Metab.Home page
K. E. Remsberg, E. W. Demerath, C. M. Schubert, Wm. C. Chumlea, S. S. Sun, and R. M. Siervogel
Early Menarche and the Development of Cardiovascular Disease Risk Factors in Adolescent Girls: The Fels Longitudinal Study
J. Clin. Endocrinol. Metab., May 1, 2005; 90(5): 2718 - 2724.
[Abstract] [Full Text] [PDF]