RESUMO Objetivo Avaliar a associação entre a composição corporal de crianças e adolescentes com a renda familiar. Métodos Estudo transversal, foram incluídos participantes entre 5 e 19 anos. As variáveis socioeconômicas foram avaliadas por meio de questionário padronizado. As variáveis de desfecho foram escore Z do índice de massa corporal e parâmetros de bioimpedância (massa muscular esquelética, massa livre de gordura e percentual de gordura) e variáveis preditoras (idade, sexo, raça, local de residência, escolaridade do pai, peso ao nascer e aleitamento materno) foram analisados pelo modelo de regressão quantílica e são apresentados os dados do percentil 50. Os testes foram bidirecionais, e as diferenças foram consideradas significativas com p<0,05. Resultados Entre os 529 participantes incluídos, 284 (53,6%) eram do sexo feminino e a média de idade foi de 11,41±3,9 anos. O escore Z do índice de massa corporal foi o único desfecho que não apresentou diferenças entre os sexos (p=0,158). No modelo bruto, uma menor renda familiar foi associada a menor massa muscular esquelética (Diferença= -7,70; IC 95% -9,32 a -5,89), p<0,001), menor massa livre de gordura (Diferença= -13,40; IC 95% -16,40 a -10,39, p<0,001) e o menor percentual de gordura associou-se à menor renda familiar (Diferença= -5,01, IC 95% -9,91 a -0,11, p=0,027). O escore Z do IMC não foi associado à renda familiar. Conclusão A renda familiar está diretamente associada à menor massa magra, ao percentual de gordura e à massa muscular esquelética em crianças e adolescentes.

ABSTRACT Objective To evaluate the association between children and adolescents’ body composition with family income. Methods Cross-sectional study, participants between 5 and 19 years were included. A standardized questionnaire assessed socioeconomic variables. The outcome variables were z-score of Body Mass Index and bioimpedance parameters (skeletal muscle mass, fat-free mass, and fat percentage) and predictor variables (age, sex, race, place of residence, father’s education, birth weight and breastfeeding) were analyzed using the quantile regression model and data from the 50th percentile are presented. The tests were bidirectional and the differences were considered significant with p<0.05. Results Among the 529 participants included, 284 (53.6%) were female and the mean age was 11.41±3.9 years. The Body Mass Index z-score was the only outcome that did not show differences between sexes (p=0.158). In the crude model, lower family income was associated with lower skeletal muscle mass (Difference=-7.70; 95% CI -9.32 to -5.89), p<0.001), lower fat-free mass (Difference= -13.40; 95% CI -16.40 to -10.39, p<0.001) and the lowest percentage of fat was associated with lower family income (Difference= -5.01, 95% CI -9.91 to -0.11, p=0.027). The z-score of BMI was not associated with family income. Conclusion Family income is directly associated with lower fat-free mass, fat percentage, and skeletal muscle mass in children and adolescents.

Abstract Objectives: The aim of this study was to estimate the percentage distribution of body composition parameters for healthy people at different ages from the assessment of electrical bioimpedance. Methods: A cross-sectional study of healthy Brazilian aged 5 years and older. Were evaluated: total body fat; percent body fat; fat-free mass; percent lean mass; fat mass index; and fat-free mass index. Results: Of 1240 participants, with a median age of 27.0 years, 52.5% were female, and 73.7% were Caucasian. Most of the body composition variables were associated with age. The fat-free mass increased from youth to adult and decreased in the elderly in both sexes, with higher values in males than in females. In males, the percentage of lean mass has higher values in adolescence compared to childhood, and in adults compared to the elderly, when analyzed from the 50th percentile. In women, fat-free mass compared to adulthood, values were higher in childhood and lower in older ages. Conclusions: The study is the first to describe the Brazilian reference values for most clinical parameters of bioimpedance in percentiles stratified by different life cycles and sex. These findings can be very useful in clinical practice for health promotion and monitoring the nutritional status of the individual.

Abstract Objective: The aim of the present study was to evaluate the agreement between the most used skinfold thickness equations with multi-frequency bioimpedance analysis in the prediction of body fat levels in children. Method: A cross-sectional study of healthy Brazilian community-dwelling individuals. The anthropometric assessment included height, body mass, arm circumference, and waist circumference. The percentage of body fat was obtained by measuring skinfold thickness equations and using bioimpedance analysis, and skinfold thickness was measured using a scientific skinfold caliper. Bland-Altman plot analysis was used to verify the agreement between the methods. Results: There were 439 children and adolescents evaluated, with a mean age of 11.6 ± 3.7 years. The mean body fat by bioimpedance analysis was 22.8% ± 10.4%, compared to 22.4% ± 8.8% by Slaughter (1), 20.4% ± 9.2% by Slaughter (2), 19.6% ± 4.4% by Goran, and 24.7% ± 10.0% by Huang equations. Bland-Altman plot analysis revealed limits of agreement greater than 8% between the bioimpedance analysis approach and equations, exceeding the clinically acceptable limit predefined a priori. None of the equations had good agreement with bioimpedance analysis. Conclusion: It was concluded that skinfold thickness and bioimpedance analysis should not be used interchangeably in children and adolescents.