Volume 14, Issue 2 (volume 14, number 2 2022)                   IJDO 2022, 14(2): 69-76 | Back to browse issues page


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Bidmeshki F, Hazar N, Mirzaei M, Rahmanian M. Finding an Appropriate Cut-off Point for Neck Circumference to Determine Overweight and Obesity in a Large Sample of Iranian Adults. IJDO. 2022; 14 (2) :69-76
URL: http://ijdo.ssu.ac.ir/article-1-703-en.html
MD Specialist of Endocrinology and Metabolism, Diabetes Research Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Abstract:   (261 Views)
Objective: Obesity is a major public health concern and there are different ways to detect it in population. The aim of the present study is to evaluate the neck circumference (NC) in a simple and practical way.
Materials and Methods: This cross-sectional survey utilized data from the Yazd Health Study (YaHS) which is a population-based cohort study. In brief, 9962 individuals aged 20-70 years with measurement of body weight, height, waist circumference (WC) and NC were available for analysis. To determine the relationship between NC and other anthropometric measurement, we utilized of Pearson's correlation coefficient. Receiver operator characteristic (ROC) curve analysis was used to find out an optimal cut off value for detecting general and central obesity as well as to determine the sensitivity and specificity of NC in predicting general and central obesity. The whole analysis was performed using SPSS version 22.
Results: NC correlated positively with body mass index (BMI) (r= 0.608, P< 0.001 in men and r= 0.541, P< 0.001 in women) and WC (r= 0.662, P< 0.001 in men and r= 0.542, P< 0.001 in women). The best cut-off point for NC to determine people with general obesity was 40.25 cm for men and 35.75 cm for women.
Conclusion: The NC has an acceptable correlation with BMI and WC. In addition, NC is a simple free measurement which may be utilized in various health-care settings. These properties make the NC as the best anthropometrics to determine overweight and obesity and it can be used as an appropriate predictor for overweight and obesity in population-based screening programs.
 
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Type of Study: Research | Subject: Special
Received: 2021/12/12 | Accepted: 2022/03/9 | Published: 2022/05/20

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