Measurement error of waist circumference: gaps in knowledge

• Published in: Public health nutrition Vol. 16; no. 2; pp. 281 - 288
• Main Authors: Verweij, Lisanne M, Terwee, Caroline B, Proper, Karin I, Hulshof, Carel TJ, van Mechelen, Willem
• Format: Journal Article
• Language: English
• Published: Cambridge, UK Cambridge University Press 01.02.2013
• Subjects: Abdomen; Anthropometry - methods; Assessment and methodology; Biological and medical sciences; clinical examination; Clinical medicine; Diagnostic Errors; Humans; Medical sciences; Metabolic diseases; Obesity; Obesity, Abdominal - diagnosis; Overweight; repeatability; Waist Circumference; Waist circumference; Measurement error; Short term; Human; State of the art; Literature; Measurement result; Definition; Corporal biometry; Change; Knowledge; Recommendation; Objective; Need; Goal; Individual; Professional practice; Scientific research; Repeated measurement
• ISSN: 1368-9800; 1475-2727; 1475-2727
• DOI: 10.1017/S1368980012002741

It is not clear whether measuring waist circumference in clinical practice is problematic because the measurement error is unclear, as well as what constitutes a clinically relevant change. The present study aimed to summarize what is known from state-of-the-art research. To identify the magnitude of the measurement error of waist circumference measurements from the literature, a search was conducted in PubMed from 1975 to February 2011. The measurement error may vary between 0·7 cm and 15 cm. Taking a realistic range of measurable waist circumference into account (60-135 cm), we argue that a short-term clinically relevant change in waist circumference of 5 % may lie between 3·0 and 6·8 cm and a maintained clinically relevant change of 3 % between 1·8 and 4·1 cm. Based on these results, we conclude it may be difficult to distinguish clinically relevant change from measurement error in individual subjects, due to the large measurement error and unclear definition of clinically relevant change. More research is needed to address these gaps in knowledge. To minimize measurement error, we recommend using a uniform measurement protocol, training and repeated measurements.