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Performance of neck circumference to predict obesity and metabolic syndrome among adult Saudis: a cross-sectional study

BACKGROUND: Neck circumference (NC) is a novel simple and stable body measurement, a growing body of evidence indicates its validity to diagnose obesity and metabolic syndrome (MetS). Because the cutoff value of NC is gender and ethnic-specific; we conducted the current study to explore the performa...

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Detalles Bibliográficos
Autores principales: Alzeidan, Rasmieh, Fayed, Amel, Hersi, Ahmed S., Elmorshedy, Hala
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6442431/
https://www.ncbi.nlm.nih.gov/pubmed/30984406
http://dx.doi.org/10.1186/s40608-019-0235-7
Descripción
Sumario:BACKGROUND: Neck circumference (NC) is a novel simple and stable body measurement, a growing body of evidence indicates its validity to diagnose obesity and metabolic syndrome (MetS). Because the cutoff value of NC is gender and ethnic-specific; we conducted the current study to explore the performance of NC to predict general obesity, central obesity, and MetS among adult Saudis of both genders. METHODS: This is a cross-sectional study which included 3063 adult Saudis (1156 males and 1907 females) with a mean age of 38.6 ± 14.1 years. Anthropometric measurements and blood pressure were assessed by a standardized methodology. Blood tests including fasting lipid panel, blood glucose, fasting blood glucose and hemoglobin A1c (HBA1c) were measured for all participants. We identified the MetS based on Adult Treatment Panel III (ATPIII definition). Data were analyzed using SPSS®19 (PASW statistics data document 19); NC was compared to relevant anthropometric measures to predict obesity and MetS using Receiver Operator Characteristic (ROC) analyses. The cutoff value of NC which possessed good discriminating power between obese and non-obese patients was estimated by Youden index, and we estimated the adjusted Odds Ratio (OR) to delineate the association between NC and the outcome variables by multiple logistic regression analysis. RESULTS: ROC analyses demonstrated good performance of NC for general obesity, central obesity and MetS; as a predictor of obesity in non-diabetics, Area Under the Curve (AUC) ranged from 0.77–0.86. In MetS, AUC was 0.77 and 0.82 for males and females respectively. The best cutoff values of the NC to predict obesity were ≥ 37.5 cm for males versus ≥32.5 cm for females. The results of adjusted logistic regression analysis adjusted for age and waist height ratio, revealed a consistent positive association between NC, general obesity, MetS, and central obesity: ORs were 4.26, 3.03, 1.45 for males versus 4.65, 3.66, and1.47 for females respectively. CONCLUSION: NC stands out as an independent predictor of obesity and the MetS. Its stability, easiness of application, low cost and the cultural acceptance, justify its use as a screening tool for general and central obesity as well as MetS among Saudis under community settings, and as an additional routine measurement for health professionals.