Cutoff points for continuous metabolic risk score in adolescents from southern Brazil

Cézane Priscila Reuter; Lars Bo Andersen; Andréia Rosane de Moura Valim; Éboni Marília Reuter; Leticia Borfe; Jane Dagmar Pollo Renner; Elza Daniel de Mello

doi:10.1002/ajhb.23211

Cutoff points for continuous metabolic risk score in adolescents from southern Brazil

Am J Hum Biol. 2019 Mar;31(2):e23211. doi: 10.1002/ajhb.23211. Epub 2019 Jan 11.

Authors

Cézane Priscila Reuter^{1

2

3}, Lars Bo Andersen⁴, Andréia Rosane de Moura Valim³, Éboni Marília Reuter^{1

2}, Leticia Borfe³, Jane Dagmar Pollo Renner³, Elza Daniel de Mello¹

Affiliations

¹ Programa de Pós-graduação em Saúde da Criança e do Adolescente, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil.
² Departamento de Educação Física e Saúde, Universidade de Santa Cruz do Sul (UNISC), Santa Cruz do Sul, RS, Brazil.
³ Programa de Pós-graduação em Promoção da Saúde, Universidade de Santa Cruz do Sul (UNISC), Santa Cruz do Sul, RS, Brazil.
⁴ Department of Sport, Food and Natural Sciences, Western Norway University of Applied Sciences, Bergen, Norway.

PMID: 30635949
DOI: 10.1002/ajhb.23211

Abstract

Objective: There is no consensus on the best diagnostic criteria for metabolic syndrome (MetS) in the child and adolescent population. Thus, the present study aimed to establish cutoff points for a continuous metabolic risk score (cMetS) in adolescents from southern Brazil.

Methods: This was a cross-sectional study conducted between 2014 and 2015. The sample consisted of 1739 schoolchildren (985 girls), aged 10-17 years. cMetS was calculated by sum of the Z-score of the following parameters: waist circumference, systolic blood pressure, glucose, high-density lipoprotein cholesterol, triglycerides, and cardiorespiratory fitness. Three diagnostic criteria of MetS were used to create cut points for cMetS.

Results: The best cutoff point for cMetS was set at 3.40 for boys (sensitivity: 100.0%, specificity: 92.9%, AUC: 0.978) and 3.61 for girls (sensitivity: 100, 0%, specificity: 93.1%, AUC: 0.991). For these cutoff points, metabolic risk was found in 8.9% of adolescents (9.4% for boys and 8.5% for girls). A linear relationship was found between the mean values of cMetS and the number of components of MetS (mean cMetS -1.09 for no component present and 6.66 for 3 or more components).

Conclusions: The use of cMetS is valid for adolescents and can detect a greater proportion of students with metabolic risk, compared to the current criteria for diagnosis of MetS.