Intrarater Reliability and the Value of Real Change for Waist and Hip Circumference Measures by a Novice Rater

Wang, Ching‐Yi; Liu, Mei-Hui; Chen, Yueh-Chi

doi:10.2466/pms.110.c.1053-1058

Cited by 6 publications

(4 citation statements)

References 10 publications

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“…Moreover, the variation in measurement error may be caused by a number of other factors not mentioned in Table 1 such as muscle mass, bone structure, lean tissues, looseness of abdominal muscles, posture, phase of respiration and time since the last meal (26,27) . Additionally, measurement error may be larger among overweight and obese subjects compared with normal-weight subjects due to difficulty in locating anatomical landmarks (14,15,27,28) .…”

Section: Measurement Error Of Waist Circumferencementioning

confidence: 99%

Measurement error of waist circumference: gaps in knowledge

Verweij

Terwee

Proper

et al. 2012

Public Health Nutr.

116

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Objective: 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. Design: 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. Results: 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. Conclusions: 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.

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Section: Measurement Error Of Waist Circumferencementioning

confidence: 99%

Measurement error of waist circumference: gaps in knowledge

Verweij

Terwee

Proper

et al. 2012

Public Health Nutr.

116

View full text Add to dashboard Cite

show abstract

“…28,29 This may be because measurement error for each site may vary by body type and obesity status, thereby magnifying the error when both measurements are used. 30 The present study used the same trained study staff at each data collection site to conduct the circumference measurements. Consistency was apparent in the results between the 1-site and 2-site equations.…”

Section: Discussionmentioning

confidence: 99%

“…The reproducibility of waist and hip circumference measurements has a higher level of intra‐ and inter‐rater reliability than measurements that incorporate both hips and waist (e.g., hip‐to‐waist ratio) 28,29 . This may be because measurement error for each site may vary by body type and obesity status, thereby magnifying the error when both measurements are used 30 . The present study used the same trained study staff at each data collection site to conduct the circumference measurements.…”

Section: Discussionmentioning

confidence: 99%

Development and cross‐validation of a circumference‐based predictive equation to estimate body fat in an active population

Taylor,

Castellani,

Bartlett

et al. 2024

Obesity Science & Practice

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ObjectiveThe U.S. Army uses sex‐specific circumference‐based prediction equations to estimate percent body fat (%BF) to evaluate adherence to body composition standards. The equations are periodically evaluated to ensure that they continue to accurately assess %BF in a diverse population. The objective of this study was to develop and validate alternative field expedient equations that may improve upon the current Army Regulation (AR) body fat (%BF) equations.MethodsBody size and composition were evaluated in a representatively sampled cohort of 1904 active‐duty Soldiers (1261 Males, 643 Females), using dual‐energy X‐ray absorptiometry (%BFDXA), and circumferences obtained with 3D imaging and manual measurements. Sex stratified linear prediction equations for %BF were constructed using internal cross validation with %BFDXA as the criterion measure. Prediction equations were evaluated for accuracy and precision using root mean squared error, bias, and intraclass correlations. Equations were externally validated in a convenient sample of 1073 Soldiers.ResultsThree new equations were developed using one to three circumference sites. The predictive values of waist, abdomen, hip circumference, weight and height were evaluated. Changing from a 3‐site model to a 1‐site model had minimal impact on measurements of model accuracy and performance. Male‐specific equations demonstrated larger gains in accuracy, whereas female‐specific equations resulted in minor improvements in accuracy compared to existing AR equations. Equations performed similarly in the second external validation cohort.ConclusionsThe equations developed improved upon the current AR equation while demonstrating robust and consistent results within an external population. The 1‐site waist circumference‐based equation utilized the abdominal measurement, which aligns with associated obesity related health outcomes. This could be used to identify individuals at risk for negative health outcomes for earlier intervention.

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“…A trained investigator measured WC and HC. WC was measured following exhalation at the midpoint between the lowest rib and iliac cres [ 23 ]. HC was measured at the point of maximum prominence.…”

Section: Methodsmentioning

confidence: 99%

Characteristics and correlation of body fat distribution and brachial-ankle pulse wave velocity in adults aged 20–59 years: a cross-sectional study

Wang,

Shi,

Luo

et al. 2024

BMC Cardiovasc Disord

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Background Fat distribution is closely related to vascular stiffness. This study aimed to investigate age and sex differences in fat distribution and brachial-ankle pulse wave velocity (baPWV), and the association between fat parameters and baPWV. Methods A total of 10,811 participants aged 20–59 years were recruited. Measures included waist and hip circumference, waist-to-hip ratio (WHR), body mass index (BMI), percentage body fat (PBF), subcutaneous fat area (SFA), visceral fat area (VFA), and baPWV. Results The results confirm that fat accumulates with age and that men tend to carry more abdominal fat than women in the same age group. The findings also indicate that baPWV increases with age and is significantly higher in men than in women in the same age group. In addition, WHR, VFA, and baPWV were more strongly correlated than baPWV and BMI, SFA, and PBF. Finally, the effects of age, PBF, WHR, and VFA on baPWV were greater for the higher quantiles. Conclusions There are age and sex differences in fat distribution and baPWV. Abdominal obesity is more closely linked to arterial stiffness than overall obesity, and people with higher baPWV are more affected by obesity parameters.

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Intrarater Reliability and the Value of Real Change for Waist and Hip Circumference Measures by a Novice Rater

Cited by 6 publications

References 10 publications

Measurement error of waist circumference: gaps in knowledge

Measurement error of waist circumference: gaps in knowledge

Development and cross‐validation of a circumference‐based predictive equation to estimate body fat in an active population

Characteristics and correlation of body fat distribution and brachial-ankle pulse wave velocity in adults aged 20–59 years: a cross-sectional study

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