Leptin as a predictor of metabolic syndrome in prepubertal children.
OBJECTIVE
Leptin has been suggested as a potential biomarker of cardiovascular risk. This paper aims to ascertain, based on a sample of prepubertal children, which serum leptin value best suited to identify metabolic syndrome (MS).


METHODS
This observational, cross-sectional study recruited children from the outpatient pediatrics clinic, with the purpose of validating serum leptin level cutoffs to identify MS. All obese and overweight children who met eligibility criteria were included in the study, as was a sample of normal-weight children. The sample underwent clinical assessment and blood fasting glucose, lipid profile, insulin, and leptin were measured. Sensitivity and specificity were estimated for each leptin measurement, using MS as the outcome. These values were used to construct a receiver operating characteristic (ROC) curve. The association between MS and leptin was assessed using logistic models to predict MS.


RESULTS
A total of 65 normal weight, 46 overweight, and 164 obese children were analyzed (160 boys, 115 girls; age: 93.7 ± 17.8 months). The most appropriate leptin cutoff was 13.4 ng/mL (sensitivity 67.6%; specificity 68.9%; accuracy 72.1%). The logistic model indicated that leptin levels above 13.4 ng/dL were significantly associated with MS and that, for every 1 ng/dL increase in leptin levels, the odds of MS increase by 3% (p = 0.002; OR 1.03; 95% CI 1.01-1.05).


CONCLUSIONS
Leptin may be a useful biomarker of cardiovascular risk in prepubertal children, with an optimal cutoff of 13.4 ng/mL. Identification of potential new risk markers for cardiovascular disease in children could contribute to the development of preventive strategies.
Faculdade de Ciências Médicas, Departamento de Pediatria, Universidade do Estado do Rio de Janeiro (UERJ), Rio de Janeiro, RJ, Brasil.
Isabel
I
Madeira
Faculdade de Ciências Médicas, Departamento de Medicina Interna, UERJ, Rio de Janeiro, RJ, Brasil.
Maria Alice
MA
Bordallo
Faculdade de Ciências Médicas, Departamento de Tecnologias da Informação e Educação em Saúde, UERJ, Rio de Janeiro, RJ, Brasil.
Nádia Cristina
NC
Rodrigues
Instituto de Nutrição, Departamento de Nutrição Aplicada, UERJ, Rio de Janeiro, RJ, Brasil.
Cecilia
C
Carvalho
Hospital Universitário Pedro Ernesto, Unidade Docente Assistencial de Endocrinologia e Metabologia, UERJ, Rio de Janeiro, RJ, Brasil.
Fernanda
F
Gazolla
Faculdade de Ciências Médicas, Departamento de Medicina Interna, UERJ, Rio de Janeiro, RJ, Brasil.
Paulo
P
Collett-Solberg
Hospital Universitário Pedro Ernesto, Unidade Docente Assistencial de Endocrinologia e Metabologia, UERJ, Rio de Janeiro, RJ, Brasil.
Clarice
C
Medeiros
Hospital Universitário Pedro Ernesto, Unidade Docente Assistencial de Endocrinologia e Metabologia, UERJ, Rio de Janeiro, RJ, Brasil.
Ana Paula
AP
Bordallo
Hospital Universitário Pedro Ernesto, Unidade Docente Assistencial de Endocrinologia e Metabologia, UERJ, Rio de Janeiro, RJ, Brasil.
Marcos
M
Borges
Hospital Universitário Pedro Ernesto, Unidade Docente Assistencial de Endocrinologia e Metabologia, UERJ, Rio de Janeiro, RJ, Brasil.
Claudia
C
Monteiro
Faculdade de Ciências Médicas, UERJ, Rio de Janeiro, RJ, Brasil.
Rebeca
R
Ribeiro
D015415:Biomarkers / Q000097:blood; D002648:Child; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D020738:Leptin / Q000097:blood*; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood*; D011237:Predictive Value of Tests; D012372:ROC Curve; D012680:Sensitivity and Specificity
D015415:Biomarkers; D020738:Leptin