RT Journal Article
T1 An Approach to Early Detection of Metabolic Syndrome through Non-Invasive Methods in Obese Children.
A1 Molina-Luque, Rafael
A1 Ulloa, Natalia
A1 Gleisner, Andrea
A1 Zilic, Martin
A1 Romero-Saldaña, Manuel
A1 Molina-Recio, Guillermo
K1 anthropometry
K1 child
K1 early diagnosis
K1 metabolic syndrome
K1 obesity
AB Metabolic Syndrome (MetS) has a high prevalence in children, and its presence increases in those with a high BMI. This fact confirms the need for early detection to avoid the development of other comorbidities. Non-invasive variables are presented as a cost-effective and easy to apply alternative in any clinical setting. To propose a non-invasive method for the early diagnosis of MetS in overweight and obese Chilean children. We conducted a cross-sectional study on 221 children aged 6 to 11 years. We carried out multivariate logistic regressions, receiver operating characteristic curves, and discriminant analysis to determine the predictive capacity of non-invasive variables. The proposed new method for early detection of MetS is based on clinical decision trees. The prevalence of MetS was 26.7%. The area under the curve for the BMI and waist circumference was 0.827 and 0.808, respectively. Two decision trees were calculated: the first included blood pressure (≥104.5/69 mmHg), BMI (≥23.5 Kg/m2) and WHtR (≥0.55); the second used BMI (≥23.5 Kg/m2) and WHtR (≥0.55), with validity index of 74.7% and 80.5%, respectively. Early detection of MetS is possible through non-invasive methods in overweight and obese children. Two models (Clinical decision trees) based on anthropometric (non-invasive) variables with acceptable validity indexes have been presented. Clinical decision trees can be applied in different clinical and non-clinical settings, adapting to the tools available, being an economical and easy to measurement option. These methods reduce the use of blood tests to those patients who require confirmation.
SN 2227-9067
YR 2020
FD 2020-12-17
LK https://hdl.handle.net/10668/24348
UL https://hdl.handle.net/10668/24348
LA en
DS RISalud
RD Apr 17, 2025