Height, weight, body composition, and waist circumference references for 7- to 17-year-old children from rural Portugal

Chaves, Raquel; Baxter‐Jones, Adam; Souza, Michele; Santos, Daniel; Maia, José

doi:10.1016/j.jchb.2014.03.007

Cited by 19 publications

(42 citation statements)

References 40 publications

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“…WC values increased with age in both sexes, regardless of the anatomical point, which corroborates with the current studies 12,13,46 . Values above the 50 th percentile were chosen as a cutoff point for both WC types assessed to predict cardiovascular risk factors and MetS risk in children.…”

Section: Discussionsupporting

confidence: 92%

“…Different countries developed reference curves for their population and chose different anatomical points for measurements. The adopted measurement for Canadian children and adolescents 11 , rural Portuguese children 12 and Japanese girls 13 on WC reference curves was the narrowest waist point, on the other, in Australian 14 and Japanese 15 children the measurement was performed at the umbilicus level.…”

Section: Introductionmentioning

confidence: 99%

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Waist circumference percentile curves as a screening tool to predict cardiovascular risk factors and metabolic syndrome risk in Brazilian children

et al. 2018

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The goals of this study were to develop reference values for waist circumference (WC) in Brazilian children between 6-10 years old and to evaluate the WC performance in predicting cardiovascular risk factors and metabolic syndrome (MetS) in children. This is a population-based epidemiological cross-sectional study, in which 1,397 children participated, with a 6-10 years old probability sampling and from public and private schools in the city of Uberaba, Minas Gerais State, Brazil. WC was measured at the waist narrowest point (WC1) and at the umbilicus level (WC2). Blood samples and blood pressure were collected to determine the MetS diagnosis. There was a significant effect of age (p = 0.001), anatomical point (WC1 vs. WC2, p = 0.001) and sex-anatomical point interaction (p = 0.016) for WC. Smoothed sex- and age-specific 5th, 10th, 25th, 50th, 75th, 90th and 95th percentile curves of WC1 and WC2 were designed by the LMS method. WC was accurate to predict MetS, for all ages [area under the ROC curve (AUC) > 0.79 and p < 0.05], regardless of sex. This study presented percentile curves for WC at two anatomical points in a representative sample of Brazilian children. Furthermore, WC was shown to be a strong predictor of cardiovascular risk factors and MetS in children.

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Section: Discussionsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Waist circumference percentile curves as a screening tool to predict cardiovascular risk factors and metabolic syndrome risk in Brazilian children

et al. 2018

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“…Concerning WC, the percentile values (p50) are lower than those of CDC-2012 13 reference and relatively similar to the regional study of Chile 16 . These findings confirm that body fat patterns expressed in BMI and WC are normal since they evidenced similar behavior with national and international studies [20][21][22] , especially between the ages of 10 and 16 and in both sexes.…”

Section: Discussionsupporting

confidence: 88%

Relación entre adiposidad corporal y salto horizontal en niños y adolescentes escolares

Caceres

Méndez-Cornejo

Farfán

et al. 2018

Rev. chil. pediatr.

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A high level of physical fitness in childhood and adolescence is associated with more favorable physical and mental health outcomes. Objective: To compare body adiposity and horizontal jump performance with international studies and to analyze the relationship between body adiposity and horizontal jump performance indicators in children and adolescents. Patients and Method: Descriptive study conducted on 812 adolescents from Talca (Chile), with an age range between 10.0 and 16.9 years. Weight, height, waist circumference (WC) and Horizontal jump (HJ) were evaluated after warm-up for 10 to 15 minutes to evaluate the explosive strength of the lower extremities according to the protocol of Castro-Piñero et al. Adiposity and HJ were compared with national and international studies. The data normality was verified by the Kolmogorov-Smirnov test. Smoothed percentile curves (p50) were created for BMI, WC, and HJ for each gender according to the LMS method. Results: Adolescents showed differences in body adiposity and HJ performance with international studies. In both genders, negative and significant correlations were found between the BMI and the HJ (men r =-0.104 and women r =-0.149) and between the WC and the HJ (men r =-0.100 and women r =-0.131). The adolescents who were classified in tertile 1 (good) and tertile 2 (satisfactory) had lower body adiposity (BMI and WC) and better HJ performance than those in tertile 3 (poor). Conclusion: Higher body adiposity and lower HJ performance were observed compared to international studies. In addition, a negative relationship between body adiposity and HJ was found. These findings suggest that the progressive increase of adiposity as age increases negatively affects the strength performance of the lower extremities of the studied children and adolescents.

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“…Within the sample, there were a small number of 16 and 17‐year‐old children. These were combined into the 15‐year‐old group, ie, 15+; for analysis, see Gomes et al Sample 3 consisted of 1745 children (859 boys) aged 7 to 17 years old, recruited as part of the Active Vouzela project in the midlands of Portugal (see Chaves et al). Sample 4 consisted of 2365 children (1197 boys) aged 8 to 17 years old, recruited as part of the Portuguese sibling study on growth, fitness, lifestyle, and health (see Pereira et al).…”

Section: Methodsmentioning

confidence: 99%

Can waist circumference provide a new “third” dimension to BMI when predicting percentage body fat in children? Insights using allometric modelling

et al. 2018

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Summary Introduction Body mass index (BMI) is often criticized for not being able to distinguish between lean and fat tissue. Waist circumference (WC), adjusted for stature, is proposed as an alternative weight status index, as it is more sensitive to changes in central adiposity. Purpose The purpose of the study is to combine the three dimensions of height, mass, and WC to provide a simple, meaningful, and more accurate index associated with percentage body fat (BF%). Methods We employed a four independent sample design. Sample 1 consisted of 551 children (320 boys) (mean ± SD of age = 7.2 ± 2.0 years), recruited from London, UK. Samples 2, 3, and 4 consisted of 5387 children (2649 boys) aged 7 to 17 years recruited from schools in Portugal. Allometric modelling was used to identify the most effective anthropometric index associated with BF%. The data from samples 2, 3, and 4 were used to confirm and cross‐validate the model derived in sample 1. Results The allometric models from all four samples identified a positive mass exponent and a negative height exponent that was approximately twice that of the mass exponent and a waist circumference exponent that was approximately half the mass exponent. Consequently, the body shape index most strongly associated with BF% was BMIWC. The WC component of the new index can simply be interpreted as a WC “weighting” of the traditional BMI. Conclusions Compared with using BMI and WC in isolation, BMIWC0.25emcould provide a more effective and equally noninvasive proxy for BF% in children that can be used in public and community health settings.

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Height, weight, body composition, and waist circumference references for 7- to 17-year-old children from rural Portugal

Cited by 19 publications

References 40 publications

Waist circumference percentile curves as a screening tool to predict cardiovascular risk factors and metabolic syndrome risk in Brazilian children

Waist circumference percentile curves as a screening tool to predict cardiovascular risk factors and metabolic syndrome risk in Brazilian children

Relación entre adiposidad corporal y salto horizontal en niños y adolescentes escolares

Can waist circumference provide a new “third” dimension to BMI when predicting percentage body fat in children? Insights using allometric modelling

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