Prediction of abnormal body fat percentage by anthropometrics parameters using receiver operating characteristic curve

Erika Severeyn, Sara Wong, Hector Herrera, Alexandra La Cruz, Jesus Velasquez, Monica Huerta

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

The World Health Organization has defined obesity as the abnormal or excessive fat accumulation that represents a risk to health". Although obesity is characterized by an excessive amount of body fat, it is commonly measured using body mass index which is unable to differentiate between elevated body fat content and increased lean mass. The indicator that best predicts obesity is the one that quantify adipose tissue and, therefore, the estimation of body fat percentage (BFP). Skinfolds have been used to measure the BFP, based on the Siri and Brozec formula. There are no official cut-off points for BFP, as the associated data is relatively insufficient worldwide. Studies agreed that fewer than 25% in men and 30% in women are commonly used as normal BFP. The aim of this study is to evaluate the capability of the anthropometrics variables to discriminate subjects with abnormal BFP. A database of 1053 subjects with 28 anthropometrics measures was used. Area under the receiver operating characteristic curves (AUCROC), sensibility (SEN), specificity (SPE) and negative predictive value (NPV) was calculated to evaluate the predictive ability of anthropometric variables measured. Three circumferences (Arm, waist and hip) and four skinfolds (calf, suprailiac, abdominal and thigh) were the variables with the best abnormal BFP detection capability, with an AUCROC>0.800 (SEN>0.760 and SPE>0.673). Having a high probability of detecting subjects with normal BFP (NPV>0.970). Easier variables to acquire, such as waist, arm, and hip circumferences, could be used in low-income countries where it is not easy to have a plicometer.

Idioma originalInglés
Título de la publicación alojada2020 IEEE ANDESCON, ANDESCON 2020
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781728193656
DOI
EstadoPublicada - 13 oct 2020
Evento2020 IEEE ANDESCON, ANDESCON 2020 - Quito, Ecuador
Duración: 13 oct 202016 oct 2020

Serie de la publicación

Nombre2020 IEEE ANDESCON, ANDESCON 2020

Conferencia

Conferencia2020 IEEE ANDESCON, ANDESCON 2020
País/TerritorioEcuador
CiudadQuito
Período13/10/2016/10/20

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