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Diagnostic performance of anthropometric indicators used to assess excess body fat in adolescence

OBJECTIVE: To compare the performance of anthropometric indicators that identify excess body fat (BF) in adolescents. METHODS: This is a methodological study that used probability cluster sampling through school and class draws. Data collection included sociodemographic characteristics and anthropom...

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Detalles Bibliográficos
Autores principales: Antunes, Nelma Maria Neves, Silveira, Marise Fagundes, Silva, Rosângela Ramos Veloso, Rocha, Josiane Santos Brant, de Oliveira, Fernanda Piana Santos Lima, Ruas, Sélen Jaqueline Souza, Borborema, Fabiana Aparecida Maia, Duarte, Jose Henrique Pinto, Rodrigues, Carolina Amaral Oliveira, Brito, Maria Fernanda Santos Figueiredo, Caldeira, Antônio Prates, de Pinho, Lucinéia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Sociedade de Pediatria de São Paulo 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9273120/
https://www.ncbi.nlm.nih.gov/pubmed/35830159
http://dx.doi.org/10.1590/1984-0462/2023/41/2021189
Descripción
Sumario:OBJECTIVE: To compare the performance of anthropometric indicators that identify excess body fat (BF) in adolescents. METHODS: This is a methodological study that used probability cluster sampling through school and class draws. Data collection included sociodemographic characteristics and anthropometric measures. Body mass index (BMI), waist-to-height ratio (WtHR), conicity index (C index), and waist circumference (WC) were calculated. Body fat percentage (BF%) was calculated from skinfold thickness and used as the gold standard. To analyze the data, descriptive statistics, Student’s t-test, Receiver Operating Characteristic (ROC) curve, and Youden’s index were used, in addition to correlation coefficient calculation between the indicators and BF%. RESULTS: A total of 997 adolescents enrolled in municipal secondary schools participated in the study. By calculating the BMI, we found that 10.6% of adolescents were overweight, and 4.7% were obese. BMI, WC, and WtHR had the highest accuracy to predict body fatness. All the anthropometric indicators had higher specificity than sensitivity to diagnose excess BF in males. WC had the highest sensitivity in both genders. C index had the smallest area under the ROC curve and the lowest sensitivity in both genders, but its specificity was equivalent to that of the other indicators. CONCLUSIONS: BMI, WtHR, and WC were the best anthropometric indicators to predict excess BF in adolescents and had the best correlation coefficients. These tools can be considered in the screening to detect excess BF in adolescents.