Utility of ultrasound for body fat assessment: validity and reliability compared to a multi-compartment criterion (2024)

Abstract

Measurement of body composition to assess health risk and prevention is expanding. Accurate portable techniques are needed to facilitate use in clinical settings. This study evaluated the accuracy and repeatability of a portable ultrasound (US) in comparison to a four-compartment criterion for percent body fat (%Fat) in overweight/obese adults. Fifty-one participants (mean ± SD; Age: 37.2 ± 11.3 yrs; BMI: 31.6 ± 5.2 kg·m⁻²) were measured for %Fat using US (GE Logiq-e) and skinfolds. A subset of 36 participants completed a second day of the same measurements, to determine reliability. US and skinfolds %Fat was calculated using the seven-site Jackson & Pollock equation. The Wang-4C model was used as the criterion method for %Fat. Compared to a gold standard criterion, US %Fat (36.4 ± 11.8%; p=0.001; standard error of estimate [SEE]=3.5%) was significantly higher than the criterion (33.0 ± 8.0%), but not different than skinfolds (35.3 ± 5.9%; p=0.836; SEE=4.5%). US resulted in good reliability, with no significant differences from Day 1 (39.95 ± 15.37%) to Day 2 (40.01 ± 15.42%). Relative consistency was 0.96 and standard error of measure was 0.94%. Although US over-predicted %Fat compared to the criterion, a moderate SEE for US is suggestive of a practical assessment tool in overweight individuals. %Fat differences reported from these field-based techniques are less than reported by other single-measurement laboratory methods and therefore may have utility in a clinical setting. This technique may also accurately track changes.

Keywords: body composition, fat mass, four-compartment model, lean mass, obese, sex, ultrasound biometry

Introduction

The importance of body composition for long term health and risk of chronic disease is expanding (Padwal, et al. 2016). It is widely recognized that high body fat is linked with a number of health disturbances, such as cardiovascular disease (Rosito, et al. 2008), metabolic abnormalities (Smith, et al. 2001; Snijder, et al. 2004), hypertension (Cassano, et al. 1990; Seidell, et al. 1991), and sleep apnea (Schafer, et al. 2002), among others. Body composition assessment is an important aspect to be integrated within clinical practice as a preventative health approach. Specifically, patient care is shifting toward a more individualized preventative model with the establishment of patient-centered medical homes (Hoff, et al. 2012). Measurement of body composition can allow for treatment to be individualized to the patient, is predictive of disease risk, and allows for establishment of optimal nutrition and weight loss goals (Thibault, et al. 2012). The obesity epidemic is highlighting the need for accurate assessments of composition as a means for clinical use and has the potential to be integrated into the patient-centered medical home (Jensen 2008). The evaluation of body composition in overweight/obese individuals provides additional challenges when trying to accurately quantify compartments. Despite the obvious increase in body fat in overweight/obese (OW/OB) individuals, excess body fat can also influence the composition of water, mineral, and protein content resulting in inaccurate assessments (Heyward, et al. 2004). Previous data suggests that hydration levels are higher in OW/OB men and women (Albu, et al. 1989), and relative mineral and protein content in obese are greater than assumed values (Fogelholm, et al. 1997). There is also large variability of these compartments among OW/OB individuals (Fuller, et al. 1994). Therefore finding accurate field methods to assess body composition in OW/OB individuals is warranted.

Measurement of body composition in a clinical setting is often limited by time, equipment, and expertise. Various techniques to assess body composition are available such as air displacement plethysmography, bioelectrical impedance analysis, and skinfolds, with the majority based upon two-compartment models which divide the body into fat mass and fat-free mass. With advancing technology, accuracy of body composition methods are improving. Multi-compartment models, which assess >3 compartments of the body, reduce the number of assumptions utilized in composition estimation, yielding a more accurate estimate of body composition (Wang, et al. 2002). Multi-compartment models are now considered the gold standard for body composition measurement (Heymsfield, et al. 2015; Wang, et al. 2002). Although multi-compartment models are the most accurate, they require an array of specialized equipment including air displacement plethysmography (ADP), bioelectrical impedance analysis to measure total body water (TBW), and dual energy x-ray absorptiometry (DEXA) to estimate bone mineral to determine a four compartment (4C) model of body composition (Wang, et al. 2002).

Due to the potential use of body composition measurement in clinical settings, accurate and portable ‘field-based’ methods are needed. Traditionally, skinfolds have been widely used as a common field-based method. There are a number of limitations with the skinfold technique, which are compounded in an overfat population (Wagner, et al. 1999). Notably, most clinics lack the personnel and time required to complete a skinfold evaluation. Ultrasonography (US), which has been around for decades, has contrasting support for its use as an accurate measurement technique for body composition. It may also potentially address the time limitation with skinfolds, as new software is being developed by a few companies where images can be analyzed in real time and results computed instantaneously. To date, this software is not fully developed or widely available; therefore there is still a time commitment to analyze the images and compute results. With regards to accuracy, initial investigations by Fanelli and Kuczmarski (1987) suggested that US and skinfolds produced similar measurements. More recently, Leahy et al. (2012) demonstrated that US measures of subcutaneous fat thickness were highly correlated with percent body fat in young healthy adults, when compared to a DEXA criterion. In contrast, our laboratory previously reported a less sophisticated A-mode ultrasound to over-predict body fat in obese subjects, when compared to a multi-compartment criterion (Smith-Ryan, et al. 2014). However, to date, we are aware of no previous investigations that have assessed the accuracy of US for percent body fat, in comparison to a multi-compartment criterion body composition method.

Technological advancements have transformed US to a portable, clear-resolution imaging package that is used in a variety of clinics for standard of care practice. Due to the equipment availability and widespread use of US in clinical environments, the ability to accurately assess body composition using US would be a potentially feasible option. Therefore, the purpose of this study was to evaluate the accuracy and repeatability of a portable B-mode ultrasound in comparison to a 4-compartment criterion for percent body fat (%Fat) in overweight and obese adults, as well as evaluate values in men and women, respectively. A secondary purpose was to compare the US to another common field-based method, skinfolds, in overweight and obese adults.

Methods

Subjects

Fifty-one overweight/obese men and women (mean ± SD; Age: 37.2 ± 11.3 yrs; Height: 173.0 ± 10.1 cm; Weight: 94.7 ± 16.8 kg; body mass index (BMI): 31.6 ± 5.2 kg·m⁻²) volunteered to participate in this study. Descriptive statistics are presented in Table 1. A subset of 36 participants (Age: 38.6 ± 11.2 yrs; Height: 174.2 ± 10.3 cm; Weight: 93.6 ± 16.3 kg; BMI: 31.2 ± 5.1 kg·m⁻²; n=18 men and women, respectively) completed a second day of testing to obtain reliability data. All participants signed an approved informed consent form, in accordance with the Declaration of Helsinki: ethical principles for medical research involving human subjects (Crigger 2000). Eligibility criteria included men and women aged 18–55 years, a body mass index of 25–45 kg·m⁻², and not taking medication that would influence hydration or skeletal muscle mass.

Table 1.

Demographic data for the entire group and for men and women, respectively. (Mean ± SD).

	Age (yrs)		Height (cm)		Weight (kg)		BMI

	Range	Mean ± SD	Range	Mean ± SD	Range	Mean ± SD	Range	Mean ± SD

N=51	20.0–54.0	37.2 ± 11.3	156.8–194.1	173.0 ± 10.1	63.4–132.0	94.7± 16.8	25.9–45.6	31.6 ± 5.2
Men (n=22)	21.0–53.0	40.4 ± 10.6	167.7–194.1	182.1 ± 7.2	76.0–132.0	102.8 ± 14.2	26.6–40.1	31.0 ± 4.1
Women (n=29)	20.0–54.0	34.8 ± 11.5	156.8–178.2	166.1 ± 5.4	63.4 – 121.3	88.5 ± 16.1	25.9–45.6	32.1 ± 6.0

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Experimental Design

All participants completed measurements following an 8-hour fast (ad libitum water intake was encouraged up to 1h before testing), and abstaining from exercise for a minimum of 24 hours. All body composition tests were performed in the same environment with a consistent ambient temperature, and 24–48 hours apart. For validity comparisons, a 4C model was used as the criterion method, using the equation from Wang et al.(2002). Reproducibility data was obtained on two separate days, at the same time of the morning for both testing periods (± 2 hours). All measurements were performed by the same investigator. For both field based measurement techniques body density was calculated; body density is a value of total mass expressed relative to total body volume, based on the assumption that body fat has a density of 0.90 and fat free body has a density of 1.10 (Heyward, et al. 2004).

Skinfolds

Skinfold thickness was measured to the nearest millimeter on the subject’s right side using a Lange caliper (Beta Technology, Inc., Cambridge, MD). All measurements were taken on the right side of the body while the subject was standing; seven sites were measured in accordance with the International Society for Advances in Kinanthropmetry (Kinanthropometry 2001), including the chest, triceps, subscapula, midaxilla, suprailiac, abdomen, and thigh. Thickness measures were taken in duplicate, and completed by the same technician, and used in the seven-site Jackson-Pollock equation to calculate body density for males [Eq. 1] and females [Eq. 2], respectively

Males : Body Density = 1.11200000 - (0.00043499 \times Sum o f Seven Skinfolds) + {(0.00000055 \times Sum o f Seven Skinfolds)}^{2} - (0.00028826 \times Age)

(Jackson, et al. 1978);

[Eq. 1]

Females : Body Density = 1.0970 - (0.00046971 \times Sum o f Seven Skinfolds) + {(0.00000055 \times Sum o f Seven Skinfolds)}^{2} - (0.00012828 \times Age)

(Jackson, et al. 1980).

[Eq. 2]

Subsequently, %Fat was calculated according to Siri (1993).

Ultrasound Measurements

Measurements were conducted using a portable ultrasound system; NextGen Logiq-e^® (GE Healthcare, Wisconsin, USA), using a wide-band linear array probe (12L-RS, 5–13 MHz). All measurements were taken on the right side of the body at the same location of the skinfold measurements and as previously described by Heyward et al. (2004). Specifically, the chest measurement was taken with the probe oriented diagonally at a distance of one-half (for men) and one-third (for women) between the armpit and the nipple. The triceps measurement was taken with the probe placed vertically at the midpoint between the lateral projection of the acromial process and the inferior margin of the olecranon process. For the subscapular thickness, with a diagonal orientation, the measurement was taken just inferior to the scapula. In a vertical position, the midaxillary site was measured below the armpit horizontally from the xiphoid process. The suprailiac measurement was taken just above the iliac crest along the natural cleavage of the skin in a diagonal probe position. The abdomen thickness measurement was taken 3 cm lateral to the belly button with the probe in a horizontal position. Lastly, the thigh measurement, half-way between the inguinal crease and top of the patella, was taken with the probe in a vertical position. Measurements were made by applying a liberal amount of transmission gel to the probe and placing the probe flush against the skin at the specified point. Equal pressure was applied to all sites in order to minimize tissue deformation, with the image captured when the probe became flush with the skin and no layer of gel was visible on the image. Measurements were taken in duplicate by the same technician; a third measurement was taken if two values were not within 10%. In order to compute subcutaneous fat thickness, manual measurement, using the ‘measure’ function within the system, was used to capture fat thickness in cm (Figure 1) just below the skin-facial border. These values were then entered into a custom spreadsheet (Microsoft excel, Microsoft, Redmond, WA); values were first converted to mm and then doubled to mimic a skinfold measurement, and then used in the seven-site Jackson-Pollock equation to calculate body density for males [Eq. 1] and females [Eq. 2], respectively. After calculating body density, %Fat was calculated using the equation by Siri et al. as described above in equations 3–5 (Siri 1993).

Multi-Compartment Criterion

The 4C model requires measurement of separate compartments of the body that are typically estimated from standard assumptions in other 2 and 3C models. With the 4C model, body volume (BV), TBW, and total body bone mineral content (Mo) were measured and then used to estimate FM using the model described by Wang et al.(2002):

FM (kg) = 2.748 (BV) - 0.699 (TBW) + 1.129 (Mo) - 2.051 (BM) .

[Eq. 6]

%Fat and FFM were then calculated using equations 2 and 3, respectively.

Body volume and BM were determined from air displacement plethysmography using the BodPod (Cosmed, USA Software V 4.2+), which was calibrated prior to each use according to the manufacturer’s guidelines. The subject’s weight (kg) was measured, while wearing a tight-fitting bathing suit or compression shorts and sports bra, to the nearest 0.01 kg using the device’s corresponding scale (Tanita Corp, Tokyo Japan). Two trials were performed for each subject to obtain two BV measurements within 150 mL. Thoracic lung volume was estimated; previous reports have shown that predicted lung volumes are not significantly different than measured volumes, even in obese subjects (Demerath, et al. 2002; McCrory, et al. 1998).

Total body water was determined from bioelectrical impedance spectroscopy (SFB7, ImpediMed, Queensland, Australia). TBW estimates were taken while the participant laid supine on a table with no contact between the arms, trunk, and legs separated by ≥ 30°. Electrodes were placed at the distal ends of the participant’s right hand and foot. Prior to analysis, each subject rested for a minimum of five minutes to allow for fluid to settle. The average of two trials within ± 0.05 liters was used to represent each participant’s TBW.

Dual energy x-ray absorptiometry (Hologic, Discovery W, Bedford, MA) was used to estimate total bone mineral content (BMC) using the device’s default software (Apex V 3.3). BMC was converted to Mo, to be used in the 4C model, using the following equation:

Mo = total body BMC \times 1.0436

(Wang, et al. 1998).

[Eq. 7]

Statistical Analyses

The accuracy of %Fat estimates (US, skinfolds) were based upon the evaluation of predicted values versus the criterion or actual value from the 4C model by calculating the total error (TE):

TE = \sqrt{\sum} \frac{{(predicted - actual)}^{2}}{n}

[Eq. 8]

and

Results

Validity

In comparison to the 4C criterion, the US produced significantly (p<0.001) higher %Fat values (36.4 ± 11.8%); skinfolds were not significantly different (35.3 ± 5.9%; p=0.836) (Table 2). For both methods, about 70% of the variance could be explained. The US and skinfolds resulted in ‘fairly good’ estimates (SEE=4.5%Fat) according to Heyward et al.(2004).

Table 2.

Validity of the ultrasound and skinfolds compared to the four-compartment criterion.

Sample	Method	Mean	r²	SEE (%)	TE (%)
All	4C	33.0 ± 8.0
	Ultrasound	36.4 ± 11.8*	0.7	3.5	6.9
	Skinfolds	35.3 ± 5.9	0.7	4.5	9.0
Men	4C	26.1 ± 5.8
	Ultrasound	26.8 ± 4.1	0.6	2.4	3.7
	Skinfolds	29.8 ± 6.0	0.3	4.1	4.3
Women	4C	38.2 ± 5.3
	Ultrasound	47.4± 6.9*	0.4	4.7	8.9
	Skinfolds	39.0 ± 4.4	0.5	2.6	2.9

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indicates significant difference compared to 4C (p<0.001)

When evaluated by sex, US %Fat values were significantly different for females (p=0.001), but not for males (p=0.380), in comparison to the 4C model (Table 2). Skinfolds were not significantly different for men (p=0.547) or women (p=0.176). For men, error values were more acceptable for US (SEE=2.4%), compared to skinfolds (SEE=4.1%). For females, the US resulted in fair (SEE=3.5%) to poor estimates (SEE=8.2%) of %Fat, with skinfolds producing the most acceptable error rate (SEE=2.6%).

Reliability

There were no significant differences (p=0.734) between Day 1 (39.95 ± 15.37%) and Day 2 (40.01 ± 15.42%) %Fat values for the US. There were also no significant between day differences for men or women (Table 3). Skinfold values were the only method to produce significantly different results from Day 1 (34.99 ± 6.04%) to Day 2 (35.62 ± 5.98%). Test-retest values are presented in Table 3. Consistency values were acceptable for both methods with absolute consistency (ICC) values greater than 0.966.

Table 3.

Test-retest reliability statistics for B-mode ultrasound total group, ultrasound men only, ultrasound women only, and skinfolds for percent body fat (%Fat) values.

	B-Mode	US-Men	US-Women	Skinfold
p-value	0.734	0.684	0.478	0.013
ICC	0.966	0.939	0.994	0.973
SEM (%Fat)	0.944	0.990	0.905	0.994
MD (%)	2.6	2.7	2.5	2.8

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Discussion

Ultrasound is one of few field based tools that can assess total and regional body composition. A number of new ultrasound devices are portable and compact, readily available, and widely used in clinical medicine. In the present study, US produced similar error values as the commonly used skinfold method, but resulted in significantly higher %Fat values than the 4C gold standard. Based on the current results, US may over-predict %Fat in overweight/obese adults, but may still be a useful field-based measurement technique. The skill and time required for US measurement may be less than that required for skinfolds, and US may be more accurate than other commonly used field-based assessments, such as bioelectrical impedance analysis (Heyward, et al. 2004; Moon, et al. 2009). Values in the present study were more accurate for men, compared to women, which may be a function of the overall lower adiposity in this sample of men. One previous evaluation contrasts the current results, reporting that US may be superior to skinfolds for measurement of body density in obese individuals (Kuczmarski, et al. 1987). However, this previous report utilized an extinct ‘advanced diagnostic research’ (ADR) US model reducing its generalizability. This previous study also only measured six skinfold sites, excluding the chest and abdominal sites. The addition of those two sites, especially the abdominal fold in the current obese population, may have contributed to the discrepant findings. Additionally, a few recent papers have reported similar validity to the present study when using less sophisticated amplitude (A)-mode ultrasound units (Ripka, et al. 2016; Smith-Ryan, et al. 2014). These investigations have demonstrated US to underestimate %Fat in young normal weight adults (Ripka, et al. 2016), and overestimate in overweight and obese adults (Schoenfeld, et al. 2016; Smith-Ryan, et al. 2014). Similarly, the B-mode US in the current study provided an overestimation of %Fat in an OW/OB sample.

Despite the variability of precision of B-mode US, it appears to be a reliable method for %Fat measurement, which may provide utility for measurement of body composition in clinical and field-based settings. To date, this is the first investigation that we are aware of that has reported reliability of B-mode US. Previous data from our laboratory have demonstrated good reliability for A-mode US with a standard error of measure of 2.2%Fat in a similar population (Smith-Ryan, et al. 2014). The present results demonstrate better reliability with a standard measurement error of 0.94%, which suggests high sensitivity for the potential to detect changes in %Fat in an overfat population. Thus, this portable US may be used to evaluate the effects of a clinical intervention, such as medication, exercise, or diet on %Fat.

Body mass index is still the primary element used to determine health and body ‘composition’ in the clinic, despite its limitations (Janssen, et al. 2004). The lack of time for measurement is understood, but with increasing focus on patient experience and disease prevention in the patient-centered medical home (Hoff, et al. 2012), measurement of body composition could play an important role. Dual-energy x-ray absorptiometry has been used in clinical settings, but is costly and often inaccessible for routine care; DEXA may also be less accurate for an overfat population (Williams, et al. 2006). In contrast, US is commonly found in a variety of clinics, is portable, non-invasive, and eliminates the concern for radiation found with DEXA. US also allows for segmental and regional evaluation of fat and muscle thickness in regions that may be linked with greater health disparities such as the abdomen and hips, as well as the thigh for detection of sarcopenia (Loenneke, et al. 2014). Additionally, although not measured in the present study, US can also be used to accurately measure visceral fat, which is a primary risk factor for cardiovascular disease (Matsuzawa, et al. 1995; Ribeiro-Filho, et al. 2003).

Males/Females

Due to the varied composition and regional deposition of fat between men and women, sex-specific evaluations are important. Specifically, women have higher body fat levels, the majority of which remains subcutaneous. In contrast, while lower in overall total body fat, men have a preferential storage of visceral/central fat, which inherently increases risk of metabolic disease (Karastergiou, et al. 2012; Karpe, et al. 2015). The present study demonstrated that the US may be more valid in men, while over-predicting %Fat in women. Establishing these baseline characteristics of patients, with the ability to track changes over time, may be beneficial for tracking disease risk.

Limitations

In the present study, the same technician completed all of the scans and measurements, thereby potentially masking inter-technician variability which may occur in real world testing. However, unlike the A-mode US, the B-mode US image is clear and likely reduces user error, but due to tissue compression there may be some inter-tester variability, which is not addressed in the present study. Also, to date, there is not a standardized method for measurement of %Fat using US. Additionally, overweight and obese individuals, as measured in the current study, have been suggested to have greater intramuscular fat which may have contributed to the over-prediction of %Fat by interfering with the brightness of the reflection from the US (Nijboer-Oosterveld, et al. 2011). Utility of this US in a normal weight population for %Fat measurement has not yet been evaluated against a criterion method, and may provide better estimates. However, O’Neill et al. (2016) recently reported similar %Fat values from predicted multiple regression values in athletes compared to DEXA, which may suggest the error in the present study was a result of higher subcutaneous fat of the participants. Comparison to a multiple compartment criterion, versus DEXA, may also have influenced the error discrepancy.

Summary and Conclusions

When compared to a multi-compartment criterion, the B-mode US resulted in an over-prediction of %Fat in a group of overweight and obese individuals. When stratified by sex, the US proved to be accurate in men, but remained inaccurate in women. When comparing the overestimation of about 3.5%Fat, this is comparable to a number of other more widely accepted body composition techniques, including DEXA and BodPod, neither of which are portable (Heyward, et al. 2004; Moon, et al. 2009). The repeatability of the US was high, providing potential use as a portable clinical tool. Using %Fat as a clinical outcome and/or tracking in the clinic, rather than body weight or BMI may be a better indicator of disease risk and progression. Future research should evaluate the feasibility of implementing such a tool within a clinic and as a component of a patient centered medical home.

Acknowledgments

Funding: This study was funded by the Nutrition Obesity Research Center (P30DK056350). The project described was also supported by the National Center for Advancing Translational Sciences, National Institutes of Health (NIH), through Grant 1KL2TR001109. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Footnotes

Conflict of Interest: The authors declare that they have no conflicts to declare.

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Utility of ultrasound for body fat assessment: validity and reliability compared to a multi-compartment criterion (2024)

Abstract

Introduction

Methods

Subjects

Table 1.

Experimental Design

Skinfolds

Ultrasound Measurements

Figure 1.

Multi-Compartment Criterion

Statistical Analyses

Results

Validity

Table 2.

Reliability

Table 3.

Discussion

Males/Females

Limitations

Summary and Conclusions

Acknowledgments

Footnotes

References

References