Validity of Body Mass Index Compared with Other Body-Composition Screening Indexes for the Assessment of Body Fatness in Children and Adolescents

University of Verona, Verona, Veneto, Italy
American Journal of Clinical Nutrition (Impact Factor: 6.77). 07/2002; 75(6):978-85.
Source: PubMed


Validation studies of height- and weight-based indexes of body fatness in children and adolescents have examined only small samples of school-age children.
The objective was to validate the performance of age- and sex-specific body mass index (BMI) compared with the Rohrer index (RI) and weight-for-height in screening for both underweight and overweight in children aged 2-19 y.
Data from the third National Health and Nutrition Examination Survey (n = 11096) and a pooled data set from 3 studies that used dual-energy X-ray absorptiometry (n = 920) were examined. The receiver operating characteristic curve was used to characterize the sensitivity and specificity of these 3 indexes in classifying both underweight and overweight. Percentage body fat and total fat mass were determined by dual-energy X-ray absorptiometry. Subcutaneous fat was assessed on the basis of the average of triceps and subscapular skinfold thicknesses.
For children aged 2-19 y, BMI-for-age was significantly better than were weight-for-height and RI-for-age in detecting overweight when average skinfold thicknesses were used as the standard, but no differences were found in detecting underweight. When percentage body fat or total fat mass was used as the standard, BMI-for-age was significantly better than was RI-for-age in detecting overweight in children aged 3-19 y. No differences were found between BMI-for-age and weight-for-height in detecting overweight or underweight.
For children and adolescents aged 2-19 y, the performance of BMI-for-age is better than that of RI-for-age in predicting underweight and overweight but is similar to that of weight-for-height.

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    • "The Centers for Disease Control suggest Body Mass Indexes as reliable indicators of body fatness for most children and teens. Research has shown that BMI scores correlate to direct measures of body fat (Mei et al., 2002) and is used as an alternative for direct measures of body fat (CDC, 2011a, b). See Table I for a breakdown of weight status (e.g., underweight, average weight, overweight, and obese) for the current sample across all time points. "

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    • "Hunger was included as a covariate using the 1 ( " very hungry " ) to 5 ( " very full " ) rating made before the scan. Because BMI percentile (i.e., BMI relative to same-age, same-sex peers) more accurately represents body composition during childhood and adolescence than raw BMI scores (Mei et al., 2002), we calculated BMI percentile for the 46 individuals under 20 years of age using the Center for Disease Control's BMI-forage growth chart as implemented at Calculator.aspx. "
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    ABSTRACT: The ability to regulate temptation and manage appetitive cravings is an important aspect of healthy adolescent development, but the neural systems underlying this process are understudied. In the present study, 60 healthy females evenly distributed from 10 to 23years of age used reappraisal to regulate the desire to consume personally-craved and not craved unhealthy foods. Reappraisal elicited activity in common self-regulation regions including dorsal and ventral lateral prefrontal cortex (specifically superior and inferior frontal gyri), dorsal anterior cingulate cortex, and inferior parietal lobule. Viewing personally-craved foods (versus not craved foods) elicited activity in regions including the ventral striatum, as well as more rostral and ventral anterior cingulate cortex extending into orbitofrontal cortex. Age positively correlated with regulation-related activity in the right inferior frontal gyrus, and negatively correlated with reactivity-related activity in the right superior and dorsolateral prefrontal cortices. Age-adjusted BMI negatively correlated with regulation-related activity in predominantly left lateralized frontal and parietal regions. These results suggest that the age-related changes seen in the reappraisal of negative emotion may not be as pronounced in the reappraisal of food craving. Therefore, reappraisal of food craving in particular may be an effective way to teach teenagers to manage cravings for other temptations encountered in adolescence, including alcohol, drugs, and unhealthy food. Copyright © 2014. Published by Elsevier Inc.
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    • "In Study 2, BMI was assessed at baseline , and at 3-month, 6-month, 1-year, and 2-year follow-ups. Although BMI does not distinguish between increased mass in the form of fat, lean tissue or bone and hence can lead to significant misclassification (McCarthy, Cole, Fry, Jebb, & Prentice, 2006; Prentice & Jebb, 2001), BMI correlates with direct measures of total body fat such as dual energy X-ray absorptiometry (r = 0.80 to 0.90) and with health measures including blood pressure, adverse lipoprotein profiles , atherosclerotic lesions, serum insulin levels, and diabetes mellitus in adolescent samples (Dietz & Robinson, 1998; Mei et al., 2002; Steinberger et al., 2005). Further, raw BMI scores are superior to age-and sex-adjusted percentiles or BMIz scores for modeling change over time in longitudinal data analyses (Berkey & Colditz, 2007). "
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    ABSTRACT: Because food intake exerts its rewarding effect by increasing dopamine (DA) signaling in reward circuitry, it theoretically follows that individuals with a greater number of genotypes putatively associated with high DA signaling capacity are at increased risk for overeating and subsequent weight gain. We tested the association between the multilocus genetic composite risk score, defined by the total number of genotypes putatively associated with greater DA signaling capacity (i.e. TaqIA A2 allele, DRD2-141C Ins/Del and Del/Del genotypes, DRD4-S allele, DAT1-S allele, and COMT Val/Val genotype), and future increases in Body Mass Index (BMI) in three prospective studies. Participants in Study 1 (N = 30; M age = 15.2; M baseline BMI = 26.9), Study 2 (N = 34; M age = 20.9; M baseline BMI = 28.2), and Study 3 (N = 162; M age = 15.3, M baseline BMI = 20.8) provided saliva samples from which epithelial cells were collected, permitting DNA extraction. The multilocus genetic composite risk score was associated with future increases in BMI in all three studies (Study 1, r = 0.37; Study 2, r = 0.22; Study 3, r = 0.14) and the overall sample (r = 0.19). DRD4-S was associated with increases in BMI in Study 1 (r = 0.42), Study 2 (r = 0.27), and in the overall sample (r = 0.17). DAT1-S was associated with increases in BMI in Study 3 (r = 0.17) and in the overall sample (r = 0.12). There were no associations between the other genotypes (TaqIA, COMT, and DRD2-141C) and change in BMI over 2-year follow-up. Data suggest that individuals with a genetic propensity for greater DA signaling capacity are at risk for future weight gain and that combining alleles that theoretically have a similar function may provide a more reliable method of modeling genetic risk associated with future weight gain than individual genotypes. Copyright © 2014. Published by Elsevier Ltd.
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