» Articles » PMID: 23275359

Measurement of Waist Circumference: Midabdominal or Iliac Crest?

Overview
Journal Diabetes Care
Specialty Endocrinology
Date 2013 Jan 1
PMID 23275359
Citations 102
Authors
Affiliations
Soon will be listed here.
Abstract

Objective: Waist circumference (WC) is used to define central obesity. This study aimed to compare the performance of two recommended locations of WC measurement.

Research Design And Methods: A cohort of 1,898 subjects who were without diabetes from 2006 to 2012 were followed for a median of 31 months (Taiwan Lifestyle Study). The WC-IC, recommended by the National Cholesterol Education Program Third Adult Treatment Panel, was measured at the superior border of the iliac crest, and the WC-mid, recommended by World Health Organization and International Diabetes Federation, was measured midway between the lowest ribs and the iliac crest. The abdominal subcutaneous fat area (SFA) and visceral fat area (VFA) were assessed by computed tomography.

Results: There was greater difference between WC-IC and WC-mid measurements in women than in men (P < 0.001). Both WC-IC and WC-mid correlated significantly with BMI, VFA, and SFA (all P < 0.001). WC-mid was better correlated to VFA than WC-IC, particularly in women, and it correlated more strongly to blood pressure, plasma glucose, hemoglobin A1c, triglyceride levels, HDL cholesterol, and C-reactive protein (all P < 0.05). The association of WC-mid with hypertension, diabetes, and metabolic syndrome was slightly better than that of WC-IC (area under the receiver operator curve 0.7 vs. 0.69, 0.71 vs. 0.68, and 0.75 vs. 0.7, respectively; all age-adjusted P < 0.05). With 90 cm (male)/80 cm (female) as criteria for central obesity, WC-mid, but not WC-IC, predicted the incidence of diabetes development (age-adjusted P = 0.003).

Conclusions: WC-mid is a better measurement to define central obesity than WC-IC, particularly in women.

Citing Articles

Impact of Exercise Manual Program on Biochemical Markers in Sedentary Prediabetic Patients: A Randomized Controlled Trial.

Hafeez S, Rehman S, Riaz S, Hafeez I, Hafeez Z, Mumtaz H Medicina (Kaunas). 2025; 61(2).

PMID: 40005307 PMC: 11857685. DOI: 10.3390/medicina61020190.


Serum uric acid to creatinine ratio as a predictor of insulin resistance, β cell function, and metabolic syndrome in normal Korean adults: a cross-sectional study.

Oh M, Cho S BMC Endocr Disord. 2025; 25(1):31.

PMID: 39910480 PMC: 11796277. DOI: 10.1186/s12902-025-01860-0.


Analysis of Nutrition Knowledge After One Year of Intervention in a National Extracurricular Athletics Program: A Cross-Sectional Study with Pair-Matched Controls of Polish Adolescents.

Skolmowska D, Glabska D, Guzek D, Adamczyk J, Nalecz H, Mellova B Nutrients. 2025; 17(1.

PMID: 39796499 PMC: 11723280. DOI: 10.3390/nu17010064.


Racial-Ethnic Disparities of Obesity Require Community Context-Specific Biomedical Research for Native Hawaiians and Other Pacific Islanders.

Wells R, Torres A, Mau M, Maunakea A Nutrients. 2025; 16(24).

PMID: 39770890 PMC: 11676216. DOI: 10.3390/nu16244268.


Impact of surrogates for insulin resistance on mortality and life expectancy in primary care: a nationwide cross-sectional study with registry linkage (LIPIDOGRAM2015).

Chen Y, Zhong Z, Gue Y, Banach M, McDowell G, Mikhailidis D Lancet Reg Health Eur. 2025; 49:101182.

PMID: 39759579 PMC: 11697418. DOI: 10.1016/j.lanepe.2024.101182.


References
1.
Bao Y, Lu J, Wang C, Yang M, Li H, Zhang X . Optimal waist circumference cutoffs for abdominal obesity in Chinese. Atherosclerosis. 2008; 201(2):378-84. DOI: 10.1016/j.atherosclerosis.2008.03.001. View

2.
Han T, van Leer E, Seidell J, Lean M . Waist circumference action levels in the identification of cardiovascular risk factors: prevalence study in a random sample. BMJ. 1995; 311(7017):1401-5. PMC: 2544423. DOI: 10.1136/bmj.311.7017.1401. View

3.
Mason C, Katzmarzyk P . Variability in waist circumference measurements according to anatomic measurement site. Obesity (Silver Spring). 2009; 17(9):1789-95. DOI: 10.1038/oby.2009.87. View

4.
Ko G, Chan J, Cockram C, Woo J . Prediction of hypertension, diabetes, dyslipidaemia or albuminuria using simple anthropometric indexes in Hong Kong Chinese. Int J Obes Relat Metab Disord. 1999; 23(11):1136-42. DOI: 10.1038/sj.ijo.0801043. View

5.
Kissebah A, Peiris A . Biology of regional body fat distribution: relationship to non-insulin-dependent diabetes mellitus. Diabetes Metab Rev. 1989; 5(2):83-109. DOI: 10.1002/dmr.5610050202. View