Elsevier

Nutrition

Volume 57, January 2019, Pages 225-230
Nutrition

Applied nutritional investigation
Development of a bedside-applicable ultrasound protocol to estimate fat mass index derived from whole body dual-energy x-ray absorptiometry scans,✯✯

https://doi.org/10.1016/j.nut.2018.04.012Get rights and content

Highlights

  • Adipose tissue ultrasound.

  • Bedside body composition analysis.

  • Fat mass index prediction

Abstract

Objectives

Precise measures of adiposity are difficult to obtain in clinical settings due to a lack of access to accurate and reliable techniques. The aim of this study was to develop and internally validate a bedside-applicable ultrasound protocol to estimate fat mass index.

Methods

We conducted an observational cross-sectional study of 94 university and community dwelling adults who attended a single data-collection session. Adipose tissue thickness was quantified in a supine or prone position using the four-site protocol (images two anterior sites on each thigh) and the nine-site protocol (images nine anterior and posterior sites). Adipose tissue thicknesses from the four-site protocol were compared against the fat mass index that was derived from dual-energy x-ray absorptiometry scans. Subsequently, we optimized the accuracy of the four-site protocol with the addition of bedside-accessible adipose tissue thicknesses from the nine-site protocol and easily obtained covariates.

Results

The four-site protocol was strongly associated (R2 = 0.65) with fat mass index but wide limits of agreement (–3.53 kg/m2 and 3.50 kg/m2) were observed using the Bland-Altman analysis. With the addition of the anterior upper arm and abdomen adipose tissue thicknesses as well as the covariates age, sex, and body mass index, the model accuracy improved (R2 = 0.93) and the Bland-Altman analysis displayed narrower limits of agreement (–1.57 kg/m2 and 1.60 kg/m2).

Conclusions

This optimized protocol developed can be applied bedside and provide accurate assessments of fat mass index.

Introduction

The prevalence of obesity is increasing world-wide and requires urgent intervention to mitigate the substantial health risks that are associated with this condition [1], [2]. Not only does obesity increase the risk of developing noncommunicable diseases such as hypertension, type 2 diabetes, coronary heart disease, stroke, and many cancers [1], obesity also negatively affects quality of life [3] and increases the risk of premature death [4].

Obtaining non-invasive, accurate, and reliable measures of adiposity in clinical or community facilities is challenging. Currently, body mass index (BMI) is the most common tool to indirectly measure adiposity due to its simplicity of assessment and interpretation. However, BMI cannot distinguish specific tissues, and changes in body composition can be highly variable among individuals and have a significant influence on a patient's response to treatment, quality of life, and health-oriented outcomes [5]. Applying accurate and precise body composition modalities such as computed tomography (CT), magnetic resonance imaging (MRI), and dual-energy x-ray absorptiometry (DXA) may be useful to quantify adiposity and track changes over time, but these approaches are impractical due to costs, radiation exposure (in the case of CT scans), and limited accessibility [6]. These challenges in obtaining accurate measures of adiposity have been recognized in the strategic plan for obesity research that was released by the National Institutes of Health, with an emphasis on developing clinically applicable approaches [7].

Ultrasonography, which is a non-invasive and readily available tool, has been utilized to quantify adipose tissue thickness and has demonstrated strong associations with whole body adiposity measured using DXA [8], [9], [10], [11], bio-electrical impedance analysis [12], hydrostatic weighing [13], [14], air displacement plethysmography [12], [15], [16], and multicompartment models [17], [18]. However, the majority of these protocols are applied in a non-supine posture and include posterior adipose tissue thicknesses, which limits the clinical application in individuals with reduced mobility or patients who are confined to a hospital bed.

Here, we sought to develop and internally validate a bedside-viable ultrasound protocol to predict whole body adiposity. Specifically, we assessed the agreement between a four-site protocol (images in four locations on the anterior thigh compartment) and DXA-based fat mass index, and subsequently. optimized the accuracy of the four-site protocol by incorporating additional bedside-accessible adipose tissue thicknesses and easily obtained covariates.

Section snippets

Study design and participants

This observational study recruited 94 participants to attend a single data collection session at the University of Waterloo between August 2015 and May 2016. Participants underwent anthropometric measures, a whole body DXA scan, and ultrasound assessments in a supine or prone position using the previously established nine-site [19] and four-site [20] protocols. This study was reviewed and cleared by a University of Waterloo Clinical Research ethics committee. Written informed consent was

Results

Of the 94 participants who were recruited, 56% were female and when compared with male participants, female participants displayed a significantly lower median BMI (23.7 vs. 25.6 kg/m2; P = 0.016) but higher median body fat percentage (34.7 vs. 24.2 %; P < 0.001) and body fat index (7.8 vs. 6.4 kg/m2; P = 0.001; Table 1). Fifty-five of 94 participants were ages <60 y and 39 participants were ages ≥60 y.

When compared with male participants, female participants displayed significantly greater

Discussion

The objective of this study was to develop and internally validate a bedside-viable ultrasound protocol to estimate the DXA-derived fat mass index. We demonstrated that a four-site protocol that images the anterior thigh compartment (often utilized for muscle thickness quantifications [20], [28]) is strongly associated (R2 = 0.65) with fat mass index; however, wide limits of agreement were observed for the Bland-Altman analysis. The addition of adipose tissue thicknesses of the anterior upper

Conclusions

We demonstrated that the four-site protocol adipose tissue thicknesses may be strongly associated with a whole body measure of adiposity, but wide limits of agreement that were observed on Bland-Altman plots suggest that this protocol alone does not accurately predict fat mass index. However, the addition of the anterior upper arm and abdomen adipose tissue thickness alongside age, sex, and BMI significantly improves the associations with fat mass index and reduces the limits of agreement,

Acknowledgments

The authors thank Janice Skafel and Stephanie Auer for conducting all DXA scans, Mamiko Noguchi and Kathryn Zuj for assisting with ultrasound training, and Benoit Lafleur and Alyssa Tondat for assisting with data collection.

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  • Cited by (0)

    Sources of support: This work was supported by Canada Graduate Scholarship (Master)–Canadian Institute of Health Research, Province of Ontario Ministry of Research and Innovation Early Researcher Award, Canada Foundation for Innovation, Natural Sciences and Engineering Research Council, and Canadian Institute of Health Research.

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    Conflicts of interest: The authors declare that they have no conflicts of interest.

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