Publication: Neck circumference as a predictor of metabolic syndrome: A cross-sectional study
Issued Date
2019-01-01
Resource Type
ISSN
18780210
17519918
17519918
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2-s2.0-85072182453
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Mahidol University
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SCOPUS
Bibliographic Citation
Primary Care Diabetes. (2019)
Suggested Citation
Issarayus Laohabut, Kamol Udol, Pochamana Phisalprapa, Weerachai Srivanichakorn, Thanet Chaisathaphol, Chaiwat Washirasaksiri, Tullaya Sitasuwan, Charoen Chouriyagune, Chonticha Auesomwang Neck circumference as a predictor of metabolic syndrome: A cross-sectional study. Primary Care Diabetes. (2019). doi:10.1016/j.pcd.2019.08.007 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/52173
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Title
Neck circumference as a predictor of metabolic syndrome: A cross-sectional study
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Abstract
© 2019 Primary Care Diabetes Europe Background: Data relating to the association between neck circumference (NC) and metabolic syndrome (MetS) in Southeast Asian population are scarce. Aims: We aimed to investigate association between NC and MetS in Thai adults, and to determine gender-specific NC cutoff values for predicting MetS. Methods: This cross-sectional study enrolled patients aged ≥18 years that attended the health examination center at Siriraj Hospital (Bangkok, Thailand) during February 2016 to January 2017. Demographic, clinical, anthropometric data, and biochemical investigations for diagnosing MetS were collected. Results: 390 patients (age 35.5 ± 9.7 years with range 20–73 years; 81.3% women) were included. Mean NC was significantly higher in MetS than in non-MetS (p < 0.001). Receiver operating characteristic curve analysis revealed NC ≥38 cm and ≥33 cm to be the optimal cutoff points for MetS in men and women, respectively. Body mass index and anthropometric indices were positively correlated with NC in both men and women. Among women, all components of MetS were significantly associated with NC. Conclusions: Using the identified gender-specific cutoff values, NC is a useful tool for predicting MetS in Thais. NC was found to be well-correlated with almost all of the metabolic risk factors, anthropometric indices, and MetS components evaluated in this study.