Determinants of body composition measured by dual-energy X-ray absorptiometry in Dutch children and adolescents

Boot, Annemieke M.; Bouquet, J; Ridder, Maria A. J. de; Krenning, Eric P.; Keizer‐Schrama, Sabine M.P.F. de Muinck

doi:10.1093/ajcn/66.2.232

Cited by 209 publications

(159 citation statements)

References 26 publications

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“…23 The correlation of BMI to PBF has been described differently in other studies. 24 In this study in obese young subjects the overall correlation of BMI and PBF was signi®cant (for all, r 0.65; girls, r 0.68, boys, r 0.63), which is almost identical to the results presented by Pietrobelli et al in normalweight children and adolescents. 25 In our study the degree of obesity was far beyond the 95th percentile of BMI.…”

Section: Bmi and Fatness In Children K Widhalm Et Alsupporting

confidence: 90%

Does the BMI reflect body fat in obese children and adolescents? A study using the TOBEC method

et al. 2001

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OBJECTIVE: Due to the fact that obesity is de®ned as excess of body fat mass, we tested the hypothesis whether the body mass index (BMI) can be used as a valid measure for the detection of the degree of obesity in individual obese children and adolescents. METHODS: A total of 204 obese children and adolescents (105 boys, 99 girls) aged 6 ± 17 y, using total body electrical conductivity (TOBEC) for fat measurement, were included into this study.A multiple regression analysis was performed with percentage body fat (PBF) as dependent variable and BMI, age and sex as independent variables. First-and second-order interaction terms were also included. Since all interaction terms showed a signi®cant in¯uence on PBF, regression analysis was performed separately for boys and girls, dividing each group into two age subgroups (subjects younger than 10 y, and subjects 10 y or older). RESULTS: BMI and PBF were observed to be positively correlated (overall: r 0,65; P 0.0001; boys r 0.63 and girls: r 0.68). Through a multiple regression analysis 57% of the variance of PBF could be explained by the independent variables. In boys younger than 10 y 73% and in girls younger than 10 y 63% of the variance of PBF was explained by the BMI. In subjects 10 y or older the association was poor (boys: 27%; girls: 38%). It should be emphasized that there is a wide range in the relationship between PBF and BMI in the obese subjects. CONCLUSION: From these results we conclude that BMI might be a useful parameter for epidemiological studies: however in the individual pediatric patient, especially from 10 y onwards, it gives only a limited insight to the degree of obesity based on the de®nition.

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Section: Bmi and Fatness In Children K Widhalm Et Alsupporting

confidence: 90%

Does the BMI reflect body fat in obese children and adolescents? A study using the TOBEC method

et al. 2001

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“…In a cross-sectional study, %BF increased with age in girls only. 40 As %BF is increased in older girls, associations between macronutrients and adiposity might be stronger in girls aged 9 ± 10 y, 10 like in our study, than in younger girls.…”

Section: Discussionsupporting

confidence: 60%

Macronutrient energy intake and adiposity in non obese prepubertal children aged 5–11 y (the Fleurbaix Laventie Ville Santé Study)

et al. 2000

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OBJECTIVE: To investigate associations between adiposity indices and food intake in nonobese prepubertal freeliving children. SUBJECTS: Five-hundred and one children, 280 boys and 221 girls aged 5 ± 11 y in two little towns in northern France. DESIGN: Cross-sectional survey. MAIN OUTCOME MEASURES: Height and weight, four skinfolds (biceps, triceps, subscapular, suprailiac), waist and hip girths, were measured. Sum of skinfolds (SSF), body mass index (BMI), and relative weight (RW) were calculated. Energy intake (EI), percentage of energy intake ascribed to carbohydrates (%EIC), complex carbohydrates (%EICC), fats (%EIF), saturated fats (%EISF) and proteins (%EIP) were assessed by a single 24 h record. Basal metabolic rate (BMR) was estimated according to Scho®eld's equations. Obese (RW 120%), and underreporting children according to Goldberg's and Black's equations were excluded. RESULTS: In multiple linear regressions analyses performed with hierarchical mixed models, adiposity indices were signi®cantly and inversely associated in girls with %EIC (all P-values`0.02), and positively with %EIF (all P-values 0.05, waist girth and BMI excepted). Similar but non-signi®cant trends were observed in boys. The relationships were not linear, and thresholds close to current dietary recommendations were highlighted. When %EIF was low, a lower percentage of energy intake ascribed to %EISF was associated with thinness. These associations remained after the exclusion of children who had an EIaBMR 1.50. CONCLUSIONS: In nonobese prepubertal children aged 5 ± 11 y, a high %EIC, close to dietary recommendations ( 55%), was associated with thinness. A high %EIF, over the upper dietary recommendation ( 35%), was associated with a greater adiposity thickness. There was no further increase in adiposity beyond this threshold. Reasons for the absence of a linear relationship pattern between adiposity and macronutrient intake remain to be determined.

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“…The 95th centiles for our population are higher than those previously reported. 19 We found that the reference 95th centile for BMI corresponded to a PBF value of 37.7% for females and 32.2% for males. In this study we used BIA to determine PBF and have previously shown that BIA is more accurate than anthropometry at predicting PBF.…”

Section: Discussionmentioning

confidence: 61%

Obesity in Auckland school children: a comparison of the body mass index and percentage body fat as the diagnostic criterion

et al. 2001

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OBJECTIVES: First, to determine obesity rates in Auckland school children according to their ethnic group using two different criteria: the body mass index (BMI) and percentage body fat (PBF) derived from bioelectrical impedance analysis (BIA). Second to examine the relationship between BMI and body composition across ethnic groups to determine if BMI references from European children accurately re¯ect obesity in other ethnic groups. DESIGN: A total of 2273 Auckland school children, aged 5 ± 10.9 y had their height, weight and bioelectrical impedance measured. Using these measurements, each child's BMI, fat free mass, fat mass and PBF were derived. RESULTS: In all 14.3% of children were obese using the recommended de®nition of obesity (BMI) greater than the 95th percentile). There was no clinically signi®cant difference in the relationship between BMI and body composition in different ethnic groups. Obesity rates varied with ethnicity (P`0.0001) and were higher in Paci®c Island (24.1%) and Maori (15.8%) than in European children (8.6%). Obesity rates also varied with age (P`0.03), with the highest rates in older children. PBF levels were higher in females than males (P`0.0001). Using a de®nition of obesity based on percentage body fat (PBF b 30%), obesity rates were higher in all ethnic groups. CONCLUSIONS: Obesity rates are high in Auckland school children and there are clear differences in obesity rates in different ethnic groups. If BMI criteria are used to de®ne obesity in our population, we recommend the same standards be used for children of all ethnicities.

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Determinants of body composition measured by dual-energy X-ray absorptiometry in Dutch children and adolescents

Cited by 209 publications

References 26 publications

Does the BMI reflect body fat in obese children and adolescents? A study using the TOBEC method

Does the BMI reflect body fat in obese children and adolescents? A study using the TOBEC method

Macronutrient energy intake and adiposity in non obese prepubertal children aged 5–11 y (the Fleurbaix Laventie Ville Santé Study)

Obesity in Auckland school children: a comparison of the body mass index and percentage body fat as the diagnostic criterion

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