Validity and reliability of portable A-mode ultrasound in measuring body fat percentage: A systematic review with meta-analysis

Luiz Fernando Ferreira; Elirez Bezerra da Silva; Alexander Barreiros Cardoso Bomfim

doi:10.1371/journal.pone.0292872

. 2024 Feb 8;19(2):e0292872. doi: 10.1371/journal.pone.0292872

Validity and reliability of portable A-mode ultrasound in measuring body fat percentage: A systematic review with meta-analysis

Luiz Fernando Ferreira ¹, Elirez Bezerra da Silva ², Alexander Barreiros Cardoso Bomfim ^1,^*

Editor: Emiliano Cè³

PMCID: PMC10852247 PMID: 38330039

Abstract

The present Systematic Review with Meta-analysis study aimed to evaluate the validity and reliability of the Portable A-mode Ultrasound (P-US) for measuring body fat percentage (BF%). Only studies with participants of both genders which had assessed BF% using P-US compared to the reference standard were selected. Publications up until May 31, 2022 were searched in the MEDLINE, COCHRANE, Science Direct, Web of Science, LILACS, SciELO, PEDro, SPORT Discus, CINAHL and SCOPUS databases. QUADAS-2 was used to assess the risk of bias in the validity studies and QAREL was used for the methodological quality of reliability studies. The JAMOVI software program synthesized the results, from which the Pearson Correlation Coefficient (r) or the square root of the Multiple Linear Regression Determination Coefficient (R²) were extracted for the validity studies, and the Mean of Errors of the Bland-Altman Test (ME) and the Confidence Interval (95%CI) with Upper and Lower Limits for the reliability studies. A total of 13 studies were included, generating 26 results for the quantitative synthesis, 14 for validity and 12 for reliability. Regarding the validity results, a strong correlation was identified between the equipment (r = 0.870 [0.845–0.895], P<0.001), with moderate and true heterogeneity (I² = 53.47%, P = 0.003), presenting publication bias. A small effect size was identified regarding the reliability results, overestimating the results due to chance between the devices (ME = 0.207 [-0.798–1.212], P = 0.686), with low heterogeneity also due to chance (I² = 19.44%, P = 0.253), with no publication bias. All of the evaluated studies showed some violation of the instruments, confirming the high risk of bias and the low methodological quality. There is concern with heterogeneity for the validity results explained by the subgroups’ analysis. The P-US associated with anthropometric perimeters satisfactorily measures the BF% with samples greater than 100 participants, and males. The results in the reliability assessment show high agreement and high variability, greatly expanding the confidence interval, which should be viewed with reservations. This review received financial support from the Brazilian Air Force. The study was registered with PROSPERO under the number CRD42020166617.

Introduction

Studies prove that physical fitness is extremely important in the success of military operations. Physically active soldiers can fight regardless of the time of day and can withstand stress in the most varied conditions, in addition to recovering more quickly from injuries when compared to those who are not physically fit [1].

Overweight/obesity was the occurrence with the greatest effect in the US Air Force (USAF) and one of the predictors associated with low physical fitness among men [2], while studies in the US Army (US-ARMY) report that obese individuals are not fit for military service [3].

Accurately determining body composition is of extreme interest to the Armed Forces. Excess adipose tissue and a high fat percentage are related to increased risk of morbidity and mortality, and the same is true among military personnel [4].

Assessment methods such as Dual-energy X-ray Absorptiometry (DXA), Air Displacement Plethysmography (ADP) and Hydrostatic Weighing (HW) can provide accurate results, but such methods are expensive and are only available in controlled environments, which makes access and operability difficult [5]. The challenge is to adopt methods with easy measurement, low cost, and which are valid and reliable, in addition to logistic feasibility for large populations and in different scenarios.

The ultrasonic evaluation method has been used for decades, showing high reliability for measuring subcutaneous fat [6] and is indicated as a practical and low-cost tool for analyzing body composition [7, 8]. Portable A-mode Ultrasound (P-US) from the Bodymetrix^® brand (IntelaMetrix, Inc.–model: BX 2000) has shown promising results in terms of validity and reliability, depending on the group selected to perform the validation procedure [9].

The validity and reliability of the P-US were confirmed in studies by Johnson et al. [10], Bielemann et al. [11], Wagner; Cain; Clark [12], Schoenfeld et al. [8], Ripka et al. [7, 13] and Totosy de Zepetnek et al. [14]. Validity was only confirmed in the studies by Johnson et al. [15] and Baranauskas et al. [16], and reliability was only confirmed in the studies by Smith-Ryan et al. [9] and Hendrickson et al. [17].

The present Systematic Review with Meta-analysis is justified by the possibility of adopting an instrument for measuring body composition which is easy to use, low cost, valid, reliable, and capable of carrying out measurements in uncontrolled environments and large populations, such as in a military group.

It also aims to establish a true and temporary result from studies that presented conflicting results, such as Smith-Ryan et al. [9] or Loenneke et al. [18], which did not confirm the validity for the sample of people with overweight/obesity and with normal weight, respectively, in addition to not existing in previous reviews determining the validity and reliability of the P-US to measure body fat percentage (BF%).

Objective

The objective of this study is to evaluate the validity and reliability of the Portable A-mode Ultrasound (P-US) for measuring body fat percentage (BF%).

Method

This Systematic Review with Meta-analysis was written according to the PRISMA 2020 Statement [19, 20], (S1 Checklist), which suggests essential items that should be described in systematic reviews with or without meta-analysis.

Eligibility criteria

Studies were selected considering the PIRO [21] strategy with participants of both genders, of any age (Participant), who had their body composition assessed by the P-US of the Bodymetrix^® brand (Index Test) in comparison with the DXA, or the ADP or even the HW (Reference Standard) and which presented results for the BF% (Outcome).

Equipment such as DXA, ADP and HW are established as valid and reliable instruments for assessing body composition, and in particular BF%. We recognize that there is still no consensus in the literature regarding the reliability between the methods, in particular, DXA and ADP [22–25]. In the present review, we considered the results of the outcome valid and reliable among themselves.

Sources of information and search strategy

The following databases were consulted: MEDLINE (US National Library of Medicine), COCHRANE, Science Direct, Web of Science, LILACS (Latin American and Caribbean Literature in Health Sciences), SciELO, PEDro (Physiotherapy Evidence Database), SPORT Discus, CINAHL (Cumulative Index to Nursing and Allied Health Literature) and SCOPUS from June 13 to August 13, 2019, and updated from May 22 to 31, 2022, by two researchers (LF, AB) independently. They defined the best search phrase in each database by consensus as the one with the highest number of records based on the eligibility criteria, without time or language filter. The results are shown in Fig 1.

Fig 1 — * Studies present at least one result for validity or reliability.

The following search terms and their synonyms were adopted, present in the Descriptors in Health Sciences (DeCS) and the Medical Subject Headings (MeSH): “Body Composition” OR “Composition, Body” AND “US portable” OR “Ultrasound portable” OR Bodymetrix. The search phrase was obtained using the Boolean operators “AND” between the descriptors and “OR” between the synonyms. Reference lists and other sources were explored (S1 File).

The study selection process, data collection and collected items

Two reviewers independently (LF, AB) selected the studies and disagreements were resolved by consensus. All studies found in the identification stage went through the selection phase when duplicates were manually removed using the EndNote Web software program. After reading the titles and abstracts, those that did not meet the eligibility criteria were discarded. In the impossibility of deciding on eligibility for titles and abstracts, readings of the full text were performed for selecting studies included in this review.

Data extraction was performed by two researchers (LF, AB) independently, and discrepancies were resolved by consensus. The information collected was as follows: Author(s); Kind of study; Sample characteristic; Reference standard; Protocol used / Sites measured by P-US; Result (BF%); Statistical test; Outcome result: Pearson’s Correlation Test (r) or Multiple/Simple Linear Regression Determination Coefficient (R²) and Bland-Altman Test values.

When results were not available by gender (M and F), the total result (M/F) was extracted. No restrictions were placed regarding when the authors declared the number of sites evaluated, the use of the P-US own analysis software or the Multiple/Simple Linear Regression Equation, but they had to be validity and/or reliability studies.

The study by Smith-Ryan et al. [9], Baranauskas et al. [16] and the study by Bielemann et al. [11] received funding from funding agencies in their countries. In addition to the available information listed above, data were collected as part of the sample’s professional activity, when available.

Assessment of methodological quality and risk of bias of studies

QUADAS-2 [26] was used to assess the risk of bias in the validity studies, which is structured so that the key domains (Patient Selection; Index Test(s); Reference Standard; Flow and Time) are classified in terms of risk of bias and research applicability concerns. Each key domain presents a series of guiding questions that help in the judgment of biases and applicability, as shown in Fig 2.

First, two researchers (LF, AB) performed an independent judgment through the question “What is the validity of portable ultrasound in measuring body fat percentage?” after the process of adapting QUADAS-2 to the Systematic Review. Then they recorded the information used to conclude the trial and disagreements were resolved by consensus.

In assessing the risk of bias for each of the four key domains, the guiding questions were answered as “YES”, “NO” or “UNCERTAIN”. All “YES” answers mean low risk of bias, while if any question is answered “NO”, it changes the risk of bias. At the end of the responses, the risk of bias was judged as “LOW”, “HIGH” or “UNCERTAIN”, without assigning scores. Applicability was also judged as “LOW”, “HIGH” or “UNCERTAIN”.

The QAREL tool [27] was used to independently assess the methodological quality of reliability studies by the researchers (LF, AB) and differences were resolved by consensus. There was an adaptation of the QAREL because only reproducibility studies between equipment were evaluated. Thus, questions 3 to 8 were not applied to the study and were suppressed because they are restricted to inter-rater analysis, which is not the subject of this review.

The QAREL tool consists of an 11-item checklist that considers sampling bias and representativeness of subjects and evaluators, evaluator blinding, examination order effects (order in which evaluators or subjects were examined), adequacy of the time between repeated measurements, application and appropriate test interpretation, and whether statistical analysis of reliability was appropriate, as shown in Table 1.

Table 1. Methodological quality and risk of bias for reliability studies according to the QAREL scale.

Author(s) (year) / Item	1	2	3	4	5	6	7	8	9	10	11
BIELEMANN et al., (2016)	N	U	X	X	X	X	X	X	U	Y	Y
HENDRICKSON et al., (2019)	N	Y	X	X	X	X	X	X	Y	N	Y
JOHNSON et al., (2014)	N	U	X	X	X	X	X	X	Y	Y	Y
KANG et al., (2020) [45]	N	U	X	X	X	X	X	X	U	Y	Y
RIPKA et al., (2016a)	N	U	X	X	X	X	X	X	U	N	Y
RIPKA et al., (2016b)	N	U	X	X	X	X	X	X	U	Y	Y
SCHOENFELD et al., (2017)	N	Y	X	X	X	X	X	X	U	N	Y
SMITH-RYAN et al., (2014)	N	Y	X	X	X	X	X	X	Y	N	Y
TOTOSY DE ZEPETNEK et al., (2021)	N	U	X	X	X	X	X	X	Y	N	Y
WAGNER; CAIN; CLARK, (2016)	N	Y	X	X	X	X	X	X	Y	N	Y

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Y–Yes; N–No; U–Uncertain; N/A ‐ Not Applicable; X–Questions excluded; 1 –Sampling Bias; 2 –Experience of the Evaluators; 3 to 7 –Blinding of the Evaluators; 8 –Reliability between Evaluators; 9 –Interval and Time; 10 –Test Application and Interpretation; 11 –Statistical Test.

Each item can be answered as “YES”, “NO” or “UNCERTAIN” in its evaluation, and some items include the option “NOT APPLICABLE”. The questions were formulated in such a way that a “YES” answer indicates good quality for the study, while a “NO” answer indicates low quality. Those items classified as ‘‘NO” may invalidate and compromise the study results, regardless of the number of items that were classified as ‘‘YES”.

Effect measures

The results of Pearson’s Correlation Coefficient (r) or the Multiple/Simple Linear Regression Determination Coefficient (R²) were extracted for validity studies, and the square root was extracted, interpreted according to Mukaka [28].

Next, the results of the Bland-Altman Test [29], mean of errors (ME), the standard deviation of errors (SDe), upper (UL) and lower (LL) limits with a 95% confidence interval (95%CI) were extracted from the reliability studies to assess the agreement between the measurements measured by the Standard Reference equipment and the P-US; however, when no information was provided in the text, data were imputed from the graph through the Meazure version 2.0.1 software program.

The Bland-Altman Test is widely used in the medical sciences to verify the agreement between two measurements, a new measurement and the reference standard measurement, which is generally more expensive or invasive [30].

The analysis performed by the Bland-Altman presents a graphical variation of dispersion which enables evaluating the agreement between the methods, with the mean value between the measures being on the X axis [(P-US + REFERENCE STANDARD)/2], and the error obtained from the difference between the fat percentage measurements being on the Y axis (P-US–REFERENCE STANDARD), resulting in the ME and the 95%CI (ME ± 1.96SDe), as indicated in the graph [31].

Reliability results in repeatability (intra-evaluator) and reproducibility (inter-evaluator) were discarded. There is consensus in the literature that the P-US is capable of producing reliable results when the evaluators are experienced and have undergone training, as according to the studies by Smith-Ryan et al. [9], Wagner; Cain, Clark [12], Hendrickson et al. [17], Totosy de Zepetnek et al. [14], Ferreira and Bomfim [32], and Carvalho et al. [33].

Synthesis of collected data methods

A summary table was constructed (Table 2) with the identification of the studies, the type of study, the sample characteristics, as well as the outcomes for validity and reliability. Data analysis was performed by an independent researcher (LF) using the JAMOVI software program.

Table 2. Data extracted from the studies included in the meta-analysis.

Author(s) (year)	Study type	Sample characteristics	Reference standard	Protocol used / Sites measured	Result (BF%)	Statistical test	Outcome
Author(s) (year)	Study type	Sample characteristics	Reference standard	Protocol used / Sites measured	Result (BF%)	Statistical test	r	Bland-Altman ME±SDe (UL–LL)
BARANAUSKAS et al., (2015)	Validity	n = 76 (33M and 43F) Age: 22.8 ± 2.5 years Mass: 70.35 ± 16.12 kg Height: 1.71 ± 0.12 m	DXA	BodyView / JP7	DXA 25.19 ± 8.62 P-US 21.31 ± 6.29	Pearson’s Correlation	0.816	#
BIELEMANN et al., (2016)	Validity and Reliability	n = 104 (F) Age: 31.9 ± 9.9 years BMI: 24.8 ± 4.3 Kg/m²	ADP	Sites (SK): Abdominal, Calf Circunference: Calf	ADP 34.1 ± 8.0 P-US 34.2 ± 7.3	Multiple Linear Regression Bland-Altman	0.901*	0.1±3.37 (-6.5–6.7)
BIELEMANN et al., (2016)	Validity and Reliability	n = 102 (M) Age: 30.0 ± 8.1 years BMI: 25.7 ± 3.7 Kg/m²	ADP	Sites (SK): Triceps, Thigh Circumference: Thigh Diameter: Biceps muscle	ADP 21.2 ± 7.3 P-US 21.7 ± 6.4	Multiple Linear Regression Bland-Altman	0.854*	0.5±3.67 (-6.8–7.7)
HENDRICKSON et al., (2019)	Reliability	n = 31 (21M and 10F) Age: 26.7.8 ± 3.9 years Mass: 75.0 ± 13.8 kg Height: 1.77 ± 0.9 m BMI: 23.9 ± 3.0 Kg/m²	ADP	BodyView / JP3	ADP # P-US 17.6 ± 6.9	Bland-Altman	#	0±3.57 (-9–7)
JOHNSON et al., (2012)	Validity	n = 26 (18M and 8F) Age: 22.9 ± 1.35 years	ADP	BodyView / JP3	ADP 15.5 ± 5.83 P-US 15.7 ± 5.14	Pearson’s Correlation	0.879	#
JOHNSON et al., (2014)	Reliability	n = 84 (35M and 49F) Age: 23.0 ± 4.7 years Mass: 70.35 ± 15.97 kg Height: 1.71 ± 0.12 m BMI: 23.6 ± 3.6 Kg/m²	DXA	BodyView / JP7	DXA 25.6 ± 0.9 P-US 21.6 ± 0.76	Bland-Altman	#	4.4±4.8 (-5.1–13.8)
	Validity	n = 49 (F) Age: 23.0 ± 4.7 years Mass: 60.55 ± 10.30 kg Height: 1.64 ± 0.09 m BMI: 22.0 ± 3.1 Kg/m²	DXA	BodyView / JP7	DXA 29.7 ± 1.0 P-US 26.0 ± 0.5	Pearson’s Correlation	0.65	#
	Validity	n = 35 (M) Age: 23.0 ± 3.3 years Mass: 83.73 ± 11.97 kg Height: 1.80 ± 0.08 m BMI: 23.6 ± 3.2 Kg/m²	DXA	BodyView / JP7	DXA 20.1 ± 1.3 P-US 15.7 ± 0.6	Pearson’s Correlation	0.84	#
KANG et al., (2020)	Validity and Reliability	n = 105 (M) Age: 20.01 ± 2.11 years Mass: 73.26 ± 13.6 kg Height: 1.72 ± 0.10 m BMI: 23.91 ± 3.77 Kg/m²	DXA	BodyView / 9 Parllo	DXA 18.22 ± 8.4 P-US 17.77 ± 3.80	Pearson’s Correlation Bland-Altman	0.790	0.4 ± 5.56 (-10.4–11.3)
LOENNEKE et al., (2014)	Validity	n = 13 (F) Age: 20 ± 1 years Mass: 62.9 ± 7.6 kg Height: 1.60 ± 0.1 m	DXA	BodyView / JP3	DXA 21.6 ± 5.7 P-US 25.0 ± 4.4	Pearson’s Correlation	0.753	#
RIPKA et al., (2016a)	Validity and Reliability	n = 143 (M) Age: 14.77 ± 1.49 years Mass: 60.45 ± 11.05 kg Height: 1.69 ± 0.09 m	DXA	Sites (SK): Triceps, Thigh, Suprailiac	DXA 19.94 ± 5.36 P-US 10.57 ± 4.45	Multiple Linear Regression Bland-Altman	0.905*	0.15±1.19 (-4.72–2.49)
RIPKA et al., (2016b)	Validity and Reliability	n = 34 (F) Age: 13.0 ± 2.3 years Mass: 52.8 ± 9.3 kg BMI: 20.82 ± 4.31 Kg/m²	DXA	Sites (SK): Triceps, Subscapularis, Thigh, Chest	DXA 30.3 ± 4.9 P-US 22.5 ± 5.7	Multiple Linear Regression Bland-Altman	0.844*	0±3.57 (-7.0–7.0)
RIPKA et al., (2016b)	Validity and Reliability	n = 71 (M) Age: 14.0 ± 2.0 years Mass: 57.8 ± 12.2 kg BMI: 20.79 ± 3.11 Kg/m²	DXA	Sites (SK): Triceps, Subscapularis, Thigh, Chest	DXA 20.0 ± 7.2 P-US 9.6 ± 6.6	Multiple Linear Regression Bland-Altman	0.921*	0±2.96 (-5.4–5.8)
SCHOENFELD et al., (2017)	Validity and Reliability	n = 20 (F) Age: 22.4 ± 2.8 years Mass: 62.2 ± 6.5 kg Height: 1.63 ± 0.05 m	ADP	BodyView / JP4	ADP 25.59 ± 7.94 P-US 26.51 ± 6.32	Pearson’s Correlation Bland-Altman	0.86	-0.92±4.09 (-9.0–7.09)
SMITH-RYAN et al., (2014)	Reliability	n = 47 (20M and 27F) Age: 37.6 ± 11.6 years Mass: 94.1 ± 16.1 kg Height: 1.73 ± 0.10 m BMI: 31.5 ± 5.2 Kg/m²	ADP	BodyView / JP7	ADP 33.7 ± 7.6 P-US 29.0 ± 6.5	Bland-Altman	#	-4.72**±3.73 (-12.0–2.59)
TOTOSY DE ZEPETNEK et al., (2021)	Validity and Reliability	n = 49 (16M and 33F) Age: 31.4 ± 10.7 years Mass: 68.0 ± 12.9 kg Height: 1.69 ± 0.8 m BMI: 23.5 ± 3.0 Kg/m²	ADP	Sites (SK): (M/F) Chest, Abdominal, Thigh, Triceps, Subscapularis, Suprailiac, Mid Axillary	ADP 24.7 ± 7.2 P-US 24.3 ± 6.6	Multiple Linear Regression Bland-Altman	0.848*	- 0.32±3.85 (-7.87–7.22)
WAGNER; CAIN; CLARK, (2016)	Validity and Reliability	n = 45 (22M and 23F) Age: 20.1 ± 1.6 years Mass: 71.8 ± 12.4 kg Height: 1.72 ± 0.10 m BMI: 24.1 ± 2.4 Kg/m²	ADP	Sites (SK): (M) Chest, Abdominal, Thigh (F) Triceps, Thigh, Suprailiac	ADP 14.9 ± 6.7 P-US 18.2 ± 7.6	Simple Linear Regression Bland-Altman	0.921*	3.2**±2.96 (-2.8–9.0)

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n–Number of evaluated subjects; (M)–Male; (F)–Female; BF%–Body Fat Percentage; P-US–Portable Ultrasound; BodyView–P-US analysis software; DXA–Dual-energy X-ray Absorptiometry; JP7 –Jackson–Pollock Protocol, Seven Sites; JP4 ‐ Jackson–Pollock Protocol, Four Sites; JP3 ‐ Jackson–Pollock Protocol, Three Sites; L3 –Lohman Protocol, Three Sites; 9 Parllo–Parllo Protocol, 9 sites; r–Pearson’s Correlation Coefficient; LL–Lower Limit; UL–Upper Limit; ME–Mean of Errors of the Bland-Altman Test; SDe–Standard Deviation of Errors of Bland-Altman Test [(Bland-Altman UL-ME)/1.96]; BMI–Body Mass Index; ADP–Air Displacement Plethysmography; Sites (SK): skinfolds measured by P-US; (*) extracted the square root of the results of the Multiple/Simple Linear Regression Determination Coefficient; (**) Imputed data.

The analysis in validity studies was performed using Pearson’s Correlation Coefficient (r), crude correlation as a continuous outcome measure. The Q Test [34] and the I² statistic were used to assess heterogeneity (tau²), and the Z Test to estimate the 95% confidence interval. A statistical significance level of P≤0.05 was adopted (Fig 3).

Fig 3 — **Result:** Random Effect–Hunter-Schmidt (k = 14): Intercept 0.870 [0.845–0.895]; P<0.001. Heterogeneity: Tau² 0.001 (SE = 7e-04); I² = 53.47%; Q = 31.502; P = 0.003.

The analysis in reliability studies was performed using the effect size from the ME and SDe values of the Bland-Altman Test as a continuous outcome measure. The Q Test [34] and the I² statistic were also used to assess heterogeneity (tau²), and the Z Test to estimate the confidence interval (CI) at 95%. A statistical significance level of P≤0.05 was adopted (Fig 5).

Fig 5 — **Result:** Fixed Effect (k = 12): Intercept 0.207 [-0.796–1.212]; P = 0.686. Heterogeneity: Tau² 0 (SE = NA); I² = 19.44%; Q = 13.655; P = 0.253.

A funnel plot and the Egger test were used to assess publication bias, adopting a statistical significance level of P≤0.05. P-values of the Egger’s Test lower than 0.05 and the absence of the isosceles triangle in the funnel plot characterize publication bias (Figs 4 and 6).

Fig 4 — **Result:** The Egger Test quantitatively evaluated the risk of publication bias, and the following results were found: Egger’s Test = -4.393 P <0.001.

Fig 6 — **Result:** The Egger test quantitatively evaluated the risk of publication bias, with the following results: Egger’s Test = 0.083; P = 0.934.

Men and women have different body composition characteristics [35], affecting the results of the outcomes, especially for those methods that use subcutaneous adipose tissue to measure BF%, such as P-US.

Validity studies with P-US can be performed by associating the BF% value measured through its analysis software program (BodyView) with the reference standard, characterized as simple regression studies. Other studies can be performed through the value expressed in millimeters measured by P-US at different anthropometric sites, combined with perimeters, diameters, among other predictive body variables, to predict the BF% result of the reference standard, characterized as multiple regression studies.

Thus, the analysis of subgroups was adopted in the following extracts to detect the cause of heterogeneity: Male, Female, Total (Male and Female), Simple Regression and Multiple Regression, as shown in Table 3.

Table 3. Results of subgroup analysis to detect the cause of heterogeneity.

Type of analysis (n)	Results included “Total” (year) [n]	Type of effect	Heterogeneity	Meta-analysis
Subgroup [M/F] (196)	“4” Baranauskas et al., (2015) [76]; Johnson et al., (2012) [26]; Totosy de Zepetnek et al., (2021) [49]; Wagner; Cain; Clark (2016) [45]	Fixed	Tau² = 0 (SE = NA) I² = 54% Q = 6.522; P = 0.089	0.884 [0.852–0.917] P < 0.001
Subgroup [F] (220)	“5” Bielemann et al., (2016) [104]; Johnson et al., (2014) [49]; Loenneke et al., (2014b) [13]; Ripka et al., (2016b) [34]; Schoenfeld et al., (2017) [20]	Random (Hunter-Smith)	Tau² = 0.0015 (SE = 0.0012) I² = 35.41% Q = 10.557 P = 0.032	0.849 [0.792–0.906] P < 0.001
Subgroup [M] (456)	“5” Bielemann et al., (2016) [102]; Johnson et al., (2014) [35]; Kang et al., (2020) [105]; Ripka et al., (2016a) [143]; Ripka et al., (2016b) [71]	Random (Hunter-Smith)	Tau² = 9e-04 (SE = 8e-04); I² = 60.87% Q = 14.076 P = 0.007	0.876 [0.840–0.912] P < 0.001
Subgroup [Simple Regression] (324)	"9” Baranauskas, et al., (2015) [76]; Johnson et al., (2012) [26]; Johnson et al., (2014) [49]; Johnson et al., (2014) [35]; Kang et al., (2020) [105]; Loenneke et al., (2014) [13]; Schoenfeld et al., (2016) [20]	Fixed	Tau² = 0 (SE = NA); I² = 18.87% Q = 7.396 P = 0.286	0.818 [0.781–0.855] P < 0.001
Subgroup [Multiple Regression] (548)	“5” Bielemann et al., (2016) [104]; Bielemann et al., (2016) [102]; Ripka et al., (2016a) [143]; Ripka et al., (2016b) [34]; Ripka et al., (2016b) [71]; Totosy de Zepetnek et al., (2021) [49]; Wagner et al., (2016) [45]	Fixed	Tau² = 0 (SE = NA); I² = 25.91% Q = 8.0098 P = 0.231	0.901 [0.885–0.917] P < 0.001

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Studies that did not present adequate statistical tests for the selected outcomes were excluded. The retrieved studies invariably presented more than one result for both validity and reliability. The extracted and selected results obeyed the following criteria in this order: the Multiple Linear Regression Determination Coefficient with the highest number of sites evaluated by P-US, the highest value of associations (r) and the lowest ME value of the Bland-Altman Test.

Results

The studies by Ulbricht et al. [36], Neves et al. [37], Loenneke et al. [38], Chiriţă-Emandi et al. [39], Krkeljas et al. [40] and Elsey et al. [41] were excluded because they did not compare the P-US with the DXA, the ADP or the WH; Utter and Hager [42], Johnson, et al. [43] and Jones [44] were excluded because the outcome was not BF%, according to the PIRO [21] strategy proposed in this Systematic Review.

Validity studies

See Figs 3 and 4.

Reliability studies

See Figs 5 and 6.

Discussion

The main findings of this Systematic Review with Meta-analysis are: (1) the Validity of the P-US was confirmed through a strong correlation with the reference standard; and (2) the Reliability was confirmed due to the low bias found between the values achieved by the P-US and the reference standard.

Validity studies

All studies showed at least one violation of the instrument regarding the key domain “Patient Selection”, characterizing it as at high risk of bias (Fig 2). Violations of the instrument were restricted to the sample, such as the lack of criteria declared by the authors for selection, size and composition and the lack of reporting on the interval time between one test and another.

The outcome result (BF%) for validity presented by the 11 studies included with 14 results meta-analyzed by the JAMOVI software program (Version 2.2.5) was reported by Pearson’s correlation coefficient (Fig 3). The result of the meta-analysis was 0.870 with a 95% CI between [0.845–0.895], with P <0.001, which indicates a strong correlation between the P-US and the reference standard [28].

The present meta-analysis also shows moderate heterogeneity of 53.47% and true (P = 0.003), which justifies the random effect analysis model with the Hunter-Schmidt protocol [46, 47], with heterogeneity being incorporated in the result of the meta-analysis.

The analysis to explain the heterogeneity was performed by subgroups: male/female, male only, female only, simple regression studies and multiple regression studies (Table 3). The results by subgroups point to a low to moderate heterogeneity, indicating the fixed effect analysis model when P>0.05.

From the data presented (see Table 3), the Male Subgroup (Subgroup [M]) has similar inconsistency to the other groups, despite having twice the sample size than the other extracts (Subgroup [M/F] and Subgroup [F]), which can be explained by the difficulty in measuring subcutaneous fat in women.

The difficulty in measuring BF% in women or obese individuals of both genders occurs in instruments that assess subcutaneous fat (skinfold caliper and P-US), crediting this difficulty to the fact that subcutaneous fat is not easily separated from the muscle [10, 48, 49].

When performing the analysis by the simple regression and multiple regression study types, the inconsistency that was at 53.47% true changed to 18.87% and 25.91%, respectively, due to probability, which confirms that the different ways of achieving the validity of the instrument influenced the results of the present meta-analysis.

The results that contributed the most and the least to the meta-analysis result relative to the weight of each study (graphically available through the forest plot) had different characteristics. Two of the four best results present samples greater than 100 participants, three of them with male components and up to three P-US measurements associated with anthropometric perimeters developed in multiple linear regression equations. Moreover, the four worst results all contain less than 50 participants, female, with three or more P-US measurements without the association with anthropometric perimeters and with the use of Pearson’s Correlation Coefficient.

Despite the excellent results achieved, studies developed with anthropometric measurements associated with P-US measurements in multiple linear regression equations did not show the cross-validation results characterized by a new evaluation of the equation achieved with a smaller sample, on average 20% of the initial sample, which we consider a serious methodological error.

Due to the lack of cross-validation, the results only have internal validity and cannot be adopted for similar groups or other groups. There is concern with heterogeneity explained by the subgroups’ analysis; however, the P-US measuring up to three sites, associated with anthropometric perimeters in Multiple/Simple Linear Regression Equations, with sample sizes greater than 100 participants and males seems to satisfactorily evaluate the body fat percentage.

Publication bias was confirmed in both the qualitative analysis (see Fig 4) with the absence of the funnel plot, and in the quantitative analysis with the Egger test (P<0.001). The problems reported were in the development of each study, mainly related to the size, stratification and composition of the sample, as well as the different ways of measuring the outcome, which may have influenced the publication bias.

Despite the high association found between the instruments to measure the BF%, the body fat percentage result must be evaluated together with the agreement between them, constituting the reliability analysis.

Reliability studies

Six questions related to procedures between evaluators were excluded in assessing the methodological quality of reliability studies, as they did not fit the purpose of this meta-analysis (Table 1).

All studies showed some violation of the instrument’s items, confirming the low methodological quality of the evaluated studies, which characterizes them as having a high risk of bias. The main violations were the lack of information about the evaluators’ experience in evaluating the interval outcome between measuring the measures and the lack of adequate interpretation in the Bland-Altman Test.

The 12 results present in 10 meta-analysis studies (Fig 5) for the Bias outcome was 0.207 [-0.798–1.212], with P = 0.686, which indicates high agreement between the P-US and the reference standard, and low heterogeneity (I² = 19.44%) with P = 0.253. Even admitting the possibility of inaccuracy between the DXA and ADP instruments (admitted as the reference standard), it seems that the meta-analysis was able to mitigate the incompatibility between them.

Although the results achieved by the P-US for reliability demonstrated by the forest plot (Fig 5) are promising, they should be viewed with caution.

The individual results in each study show variations which may compromise the precision of the P-US measurement. We highlight the study by Bielemann et al. [11] (see Table 2) for males, included in this meta-analysis, which presents mean errors of 0.5 [-6.8 to 7.7]. From this result, a eutrophic man (similar to the sample of the referenced study) may present a fat percentage of 22% in the reference standard equipment, while this result by P-US may be between 15.2 and 29.7%, within the confidence interval of 95%, which we believe presents a high variation when it comes to the outcome (BF%), although the authors reported that there was no systematic bias.

Publication bias (Fig 6) was not confirmed in either the qualitative analysis (with the appearance of the isosceles triangle), nor in the quantitative analysis, with the Egger Test showing P = 0.934.

The results of publication bias confirm a pattern for reliability studies involving the P-US that still falls short of reliability studies of the same nature, which can be proven by the high risk of bias and low methodological quality of the studies, as evaluated by the QAREL.

The results of the bias presented by the studies in the reliability assessment reveal high agreement, despite the variability of the results, which increases the confidence interval and the necessary clinical precision.

The P-US and the use of anthropometric measurements in Multiple Linear Regression Equations seem to present better results when compared with the reference standard.

The results confirm the accuracy of the equipment, similar to others which measure BF% through subcutaneous fat, such as the skinfold caliper. The ease in measuring the BF%, low cost and logistical feasibility for large populations are advantages which should be considered, proving to be effective for physical training centers, for monitoring changes in body composition, in epidemiological approaches and in evaluations that do not require clinical precision.

Conclusion

Based on the results of this Systematic Review with Meta-analysis, the P-US is a valid and reliable device for measuring body fat percentage. Studies with representative samples of the population, selected at random in adequate amounts, preferably using a software program for this purpose or with 20 individuals for each variable evaluated are recommended, as well as studies that assess the agreement between the P-US and the reference standard method, the analysis of the results using the Bland-Altman Test and the dispersion graph between the methods, with the objective of verifying the bias behavior.

Finally, samples with different characteristics are suggested to verify the potential of P-US in measuring body fat percentage, especially samples with high deposits of subcutaneous fat. There must be a report about the interval time between one test and another, preferably less than 48 hours; in addition, the anthropometric measurements should be associated with the measurements measured by the P-US in multiple linear regression equations and with the adoption of a group for the cross-validation in order to assess the ability of the P-US to measure the body fat percentage for external validity.

Registration and protocol

This Systematic Review with Meta-analysis was registered on the PROSPERO platform (International Prospective Register of Systematic Review), on 02/27/2020 and received the provisional ID number 166617 and the definitive registration on 04/28/2020 number CRD42020166617, updated on 07/07/2021, available at: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020166617.

Supporting information

S1 Checklist. PRISMA 2020.

(PDF)

Click here for additional data file.^{(355.2KB, pdf)}

S1 File. Search phrases.

(PDF)

Click here for additional data file.^{(269.3KB, pdf)}

S2 File. QAREL supplement.

(PDF)

Click here for additional data file.^{(245.2KB, pdf)}

S3 File. QUADAS-2 supplement.

(PDF)

Click here for additional data file.^{(490.4KB, pdf)}

S4 File. Statistical analysis supplement.

(ZIP)

Click here for additional data file.^{(704.6KB, zip)}

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

AB and LF received financial support from the Brazilian Air Force. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0292872.r001

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29 Jun 2023

PONE-D-23-06958Validity and reliability of portable ultrasound in measuring body fat percentage: A systematic review with meta-analysisPLOS ONE

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Reviewer #1: The authors made some progress in the meta-analysis and systematic review of Bodymetrix® branded portable ultrasound (P-US) measurement of body fat percentage, supplementing our previous understanding of how to use P-US to measure body fat percentage and suggesting that we have important implications for better, faster and more accurate measurement of body fat percentage.

Reviewer #2: This paper adresses an interesting problem- whether Portable Ultrasound (P-US) is a valid and reliable method to measure body fat percentage (BF%). The authors propose systematic review with Meta-analysis study to review and

synthesize the existing literatures. The results show high validity and reliability of the P-US as a device for measuring body fat percentage. Publication bias and subgroups analysis are also performed. Overall, the article is well organized and the statistical analysis is rigorous and sound.

**********

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Reviewer #1: Yes

Reviewer #2: No

**********

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PLoS One. 2024 Feb 8;19(2):e0292872. doi: 10.1371/journal.pone.0292872.r002

Author response to Decision Letter 0

2 Aug 2023

In order to respond to the editor’s and reviewers’ suggestions, the changes and arguments regarding the comments are presented below:

Comment from the Academic Editor:

Change in the purpose of the study, “Evaluate the validity and reliability of the P-US for measuring body fat percentage (BF%)”.

Response to Academic Publisher's: In view of the comment, we decided to change the study objective, as suggested.

Reviewers' comments.

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

Response to Reviewers: no comment.

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Response to Reviewers: no comments, thanks!

3. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: No

Reviewer #2: Yes

Response to Reviewers: In response to Reviewer 1's comment, we decided to insert the data sheets provided by the JAMOVI software for the validity and reliability results, the analysis of the QUADAS-2 instrument, as well as that of the QAREL (Supplement 2).

4. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: No, review, please.

Reviewer #2: Yes

Response to Reviewers: In response to Reviewer 1's comment, we decided to forward the manuscript to a professional native English (Canadian) reviewer for further review.

5. Review Comments to the Author

Reviewer #2: This paper addresses an interesting problem- whether Portable Ultrasound (P-US) is a valid and reliable method to measure body fat percentage (BF%). The authors propose systematic review with Meta-analysis study to review and synthesize the existing literatures. The results show high validity and reliability of the P-US as a device for measuring body fat percentage. Publication bias and subgroups analysis are also performed. Overall, the article is well organized and the statistical analysis is rigorous and sound.

Response to Reviewers: no comments, thanks!

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes

Reviewer #2: No

In response to questions raised by Reviewer 1 through the file “Peer review.docx”.

The authors made some progress in the meta-analysis and systematic review of Bodymetrix® branded portable ultrasound (P-US) measurement of body fat percentage, supplementing our previous understanding of how to use P-US to measure body fat percentage and suggesting that we have important implications for better, faster and more accurate measurement of body fat percentage. However, there are still some issues that need further improvement, as described below.

Major Issues

1. Lines 105-108, in the data standard, what is the specific method of P-UB compared with DXA, ADP, HW methods? Are the resulting BF% values true and comparable? On what basis?

Lines 105-108: “Considering the PIRO(21) strategy, studies were selected with participants of both genders, of any age (Participant), who assessed body composition with the P-US of the Bodymetrix® brand (Index Test) in comparison with the DXA, or the ADP or even the HW (Reference Standard) and that presented results for the BF% (Outcome)”.

Reply to Reviewer 1:

In response to the question raised, we decided to characterize the way of decoding the signals emitted by the ultrasound, inserting the term “A-mode” (amplitude), characteristic of the Portable Ultrasound A-mode (US-P) of the brand Bodymetrix® (IntelaMetrix, Inc – model: BX 2000). We inserted the term “A-mode” in lines 4, 23, 75, and 95.

Although DXA, ADP, and HW are established as valid methods for assessing body composition, and in particular fat percentage, we recognize that there is still no consensus in the literature regarding the reliability between the DXA and ADP methods.

Thus, in lines 111-113, we inserted following wording: “In the present review, we consider the results of DXA and ADP as valid and reliable for determining body composition in the presented outcome (inserting 4 references)”.

Note: in the Discussion item, in the reliability studies, it was verified that the meta-analysis was able to mitigate the possible lack of agreement between the DXA and ADP instruments. We have inserted the following wording (lines 385-388): “Even admitting the possibility of inaccuracy between the DXA and PDA instruments, admitted as the reference standard, it seems that the meta-analysis was able to mitigate the incompatibility between them”.

2. Lines 44-47, read whether the observer used BodyMetrix™ to compare Three-Site and Seven-Site measurements, suggesting further refinement of the Seven-Site statistical analysis data.

Lines 44-47: “However, the P-US measures satisfactorily when it measures up to three sites associated with anthropometric perimeters in Multiple Linear Regression Equations with samples greater than 100 participants, and males”.

Reply to Reviewer 1:

The reports in lines 44-47 reinforce that the best results presented by the meta-analysis are those that used prediction equations involving the P-US measuring up to three sites associated with anthropometric measurements with samples greater than 100 male participants.

It is possible that we didn’t word it properly, so we apologize. Thus, in consideration of the Reviewer, we decided to change the wording: “The P-US associated with anthropometric perimeters satisfactorily measures the BF% with samples greater than 100 participants, and males”.

3. Line 154, The QUADAS-2 in the design method is proposed to be modified to QUADAS-C (Quality Assessment of Diagnostic Accuracy Studies-Comparative). The QUADAS-C tool was developed as an extension of QUADAS-2 to assess the risk of bias in comparative diagnostic test accuracy studies.

Line 154-158: QUADAS-2(24) was used to assess the risk of bias in the validity studies, which is structured so that the key domains (Patient Selection; Index Test(s); Reference Standard; Flow and Time) are classified in terms of risk of bias and research applicability concerns. Each key domain presents a series of guiding questions that help in judging biases and applicability, as shown in Figure 2.

Reply to Reviewer 1:

To respond to the Reviewer's request, we turned to Yang et al. (2020) and some published reviews (YOON et al., 2023; CHOW et al., 2023; TSIKOPOULOS et al., 2022; ZYFODIA et al., 2021) to support our position.

The QUADAS-C tool (Quality Assessment of Diagnostic Accuracy Studies-Comparative) was developed as an extension of QUADAS-2 to assess the risk of bias in comparative studies of diagnostic accuracy when evaluating the accuracy of 2 or more Index Tests compared to each other and to the Reference Standard. The “C” stands for comparison when assessing the risk of bias in studies included in a systematic review. Table 1, below, presents the characteristics of the aforementioned studies compared with our manuscript.

Table 1: Comparison between different publications

Author (year) Index Tests Reference Standard

(ITa vs ITb)

Yoon et al. (2023) ITa: AI Tomography

ITb: Evaluation by Radiologists

Chow et al. (2023) ITa: PSMA-PET Histopathology

ITb: CIM

Tsikopoulos et al. (2022) ITa: DTT Musculoskeletal Infection Society Criteria

ITb: Sonification

Zyfodia et al. (2021) ITa: Xpert Ultra Rifacipin resistance

ITb: Xpert MTB

Our manuscript ITa: P-US DXA or ADP or HW

ITb:

ITa: Index Test a; ITb: Index Test b; AI: Artificial intelligence; PSMA-PET: positron emission tomography of prostate-specific membrane antigen; CIM: Conventional Imaging Modalities; DTT: dithiothreitol; Xpert Ultra: rapid test to detect tuberculosis; Xpert MTB: rapid test to detect tuberculosis; P-US: Portable Ultrasound; DXA: Dual-energy X-ray Absorptiometry; ADP: Air Displacement Plethysmography; HW: Hydrostatic Weighing.

Our manuscript uses only one IT (P-US), there are no comparisons with other index tests, we evaluate its results with the Reference Standard (DXA or ADP, or HW). By associating anthropometric perimeters with the P-US results in prediction equations, we do not consider this procedure as another instrument for evaluating BF%. We understand that QUADAS-C would be necessary if studies were located that evaluated the performance between P-US (ITa) and bioimpedance (ITb), having DXA as the Reference Standard, a hypothetical study that has not been located so far.

These being the arguments and with the necessary respect, we disagree with Reviewer 1's suggestion.

Minor Issues

4. Lines 100-101, 123-125, 218, refer to the website address as deleted or abbreviated as possible

Reply to Reviewer 1:

Because of the suggestions, we decided to remove the electronic addresses.

100-101 www.prisma-statment.org

123 www.decs.bvsalud.org/en/

125 https://www.ncbi.nlm.nih.gov/mesh/

5. In the flow diagram in Figure 1, the changes are corrected in the order of Identification、Screening、Eligibility、Included.

Reply to Reviewer 1:

Because of the suggestions, we have corrected the flowchart.

6. In Figure 3 and Figure 5, it is recommended to modify the setting position of Result in the figure, and do not overlap with other contents

Reply to Reviewer 1:

Taking into account the suggestions, we have improved the image.

REFERENCES

Yang B, Mallett S, Takwoingi Y, Davenport CF, Hyde CJ, Whiting PF, Deeks JJ, Leeflang MMG; QUADAS-C Group†; Bossuyt PMM, Brazzelli MG, Dinnes J, Gurusamy KS, Jones HE, Lange S, Langendam MW, Macaskill P, McInnes MDF, Reitsma JB, Rutjes AWS, Sinclair A, de Vet HCW, Virgili G, Wade R, Westwood ME. QUADAS-C: A Tool for Assessing Risk of Bias in Comparative Diagnostic Accuracy Studies. Ann Intern Med. 2021 Nov;174(11):1592-1599. doi: 10.7326/M21-2234. Epub 2021 Oct 26. PMID: 34698503.

Yoon JH, Strand F, Baltzer PAT, Conant EF, Gilbert FJ, Lehman CD, Morris EA, Mullen LA, Nishikawa RM, Sharma N, Vejborg I, Moy L, Mann RM. Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis. Radiology. 2023 Jun;307(5):e222639. doi: 10.1148/radiol.222639. Epub 2023 May 23. PMID: 37219445; PMCID: PMC10315526.

Chow KM, So WZ, Lee HJ, Lee A, Yap DWT, Takwoingi Y, Tay KJ, Tuan J, Thang SP, Lam W, Yuen J, Lawrentschuk N, Hofman MS, Murphy DG, Chen K. Head-to-head Comparison of the Diagnostic Accuracy of Prostate-specific Membrane Antigen Positron Emission Tomography and Conventional Imaging Modalities for Initial Staging of Intermediate- to High-risk Prostate Cancer: A Systematic Review and Meta-analysis. Eur Urol. 2023 Jul;84(1):36-48. doi: 10.1016/j.eururo.2023.03.001. Epub 2023 Apr 7. PMID: 37032189.

Tsikopoulos K, Christofilos SI, Kitridis D, Sidiropoulos K, Stoikos PN, Gravalidis C, Givissis P, Papaioannidou P. Is sonication superior to dithiothreitol in diagnosis of periprosthetic joint infections? A meta-analysis. Int Orthop. 2022 Jun;46(6):1215-1224. doi: 10.1007/s00264-022-05350-z. Epub 2022 Feb 24. Erratum in: Int Orthop. 2022 Mar 24;: PMID: 35199219.

Zifodya JS, Kreniske JS, Schiller I, Kohli M, Dendukuri N, Schumacher SG, Ochodo EA, Haraka F, Zwerling AA, Pai M, Steingart KR, Horne DJ. Xpert Ultra versus Xpert MTB/RIF for pulmonary tuberculosis and rifampicin resistance in adults with presumptive pulmonary tuberculosis. Cochrane Database Syst Rev. 2021 Feb 22;2:CD009593. doi: 10.1002/14651858.CD009593.pub5. PMID: 33616229.

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PLoS One. doi: 10.1371/journal.pone.0292872.r003

Decision Letter 1

Emiliano Cè

12 Sep 2023

PONE-D-23-06958R1Validity and reliability of portable A-mode ultrasound in measuring body fat percentage: A systematic review with meta-analysisPLOS ONE

Dear Dr. Bomfim,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

ACADEMIC EDITOR:Dear Authors,your R1 manuscript version has been revised by one expert in the field that still retrieved some minor point you should consider during the revision process. Please submit your revised manuscript by Oct 27 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
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An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Emiliano Cè

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

**********

6. Review Comments to the Author

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Hai Cui

**********

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PLoS One. 2024 Feb 8;19(2):e0292872. doi: 10.1371/journal.pone.0292872.r004

Author response to Decision Letter 1

15 Sep 2023

In order to respond to the reviewer’s suggestions, the changes and arguments regarding the comments are presented below:

Comment from Reviewer #1:

Reviewer #1: All comments have been addressed.

Reply to Reviewer #1: thanks!

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reply to Reviewer #1: no comment

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

Reply to Reviewer #1: We inform you that the statistical analysis used was appropriate for the following reasons:

3.1. The JAMOVI program has already been used in other studies(1–5) and is capable of analyzing mean effect measures and correlations;

3.2. The selection of effect measures was appropriate: for validity, Pearson’s correlation coefficient; for reliability, the result of the Bland-Altman Test, which is the mean of the errors;

3.3. Heterogeneity was assessed for both outcomes, and according to its results, the analysis model (fixed effect or random effects) was used to incorporate it or not into the meta-analysis and explain it;

3.4. In the case of high and true heterogeneity, subgroup analyzes were performed in an attempt to explain it;

3.5. All of this information is clearly described in the Effect measures and Synthesis of collected data methods (lines 184-246) in the Method section.

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reply to Reviewer #1: no comment.

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reply to Reviewer #1: no comment, thanks!

6. Review Comments to the Author

Reply to Reviewer #1: no comment.

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Hai Cui

Minor Issue

1. Lines 214-215, It is recommended to delete the connection to the JAMOVI 2.2.5 software program download site, as any update or change may lead to misunderstanding by readers or researchers.

Reply to Reviewer #1: in response to the suggestion, we decided to remove the JAMOVI software version and web address.

Please check "Response to Reviewer.docx"

2. Figure 2, Modify the color distinction in Figure 2 to be consistent with that in Table 1. Different risk levels are suggested to be expressed in numbers (e.g: low risk 1, high risk 2, unknown risk 3).

Reply to Reviewer #1: in response to the suggestion, we standardized the colors based on Table 1 and inserted the numbers 1, 2 and 3 for “low risk”, “high risk” and “uncertain risk”, respectively.

Please check "Response to Reviewer.docx"

3. Table 3, Change the data format of the Heterogeneity and Meta-analysis items in Table 3 to left-justified.

Reply to Reviewer #1: We changed the formatting of the table, as suggested.

Please check "Response to Reviewer.docx"

References:

1. Leporace G, Metsavaht L, Gonzalez FF, Arcanjo de Jesus F, Machado M, Celina Guadagnin E, et al. Validity and reliability of two-dimensional video-based assessment to measure joint angles during running: A systematic review and meta-analysis. J Biomech [Internet]. 2023;157(July):111747. Available at: https://doi.org/10.1016/j.jbiomech.2023.111747.

2. Dokponou YCH, Badirou OBA, Agada KN, Dossou MW, Lawson LD, Ossaga MAD, et al. Transcranial doppler in the non-invasive estimation of intracranial pressure in traumatic brain injury compared to other non-invasive methods in lower-middle income countries: Systematic review and meta-analysis. J Clin Neurosci. 2023;113(May):70–6.

3. Pentapati KC, Yeturu SK, Siddiq H. A reliability generalization meta-analysis of Child Oral Impacts on Daily Performances (C – OIDP) questionnaire. J Oral Biol Craniofacial Res [Internet]. 2020;10(4):776–81. Available at: https://doi.org/10.1016/j.jobcr.2020.10.017

4. Farzan R, Hosseini SJ, Firooz M, Tabarian MS, Jamshidbeigi A, Samidoust P, et al. Perceived stigmatisation and reliability of questionnaire in the survivors with burns wound: A systematic review and meta-analysis. Int Wound J. 2023;(March):1–13.

5. Olumade TJ, Uzairue LI. Clinical characteristics of 4499 COVID-19 patients in Africa: A meta-analysis. J Med Virol. 2021;93(5):3055–61.

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PLoS One. doi: 10.1371/journal.pone.0292872.r005

Decision Letter 2

Emiliano Cè

2 Oct 2023

Validity and reliability of portable A-mode ultrasound in measuring body fat percentage: A systematic review with meta-analysis

PONE-D-23-06958R2

Dear Dr. Bomfim,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Emiliano Cè

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

**********

6. Review Comments to the Author

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: HAI CUI

**********

PLoS One. doi: 10.1371/journal.pone.0292872.r006

Acceptance letter

Emiliano Cè

5 Oct 2023

PONE-D-23-06958R2

Validity and reliability of portable A-mode ultrasound in measuring body fat percentage: A systematic review with meta-analysis

Dear Dr. Bomfim:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Prof. Emiliano Cè

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Checklist. PRISMA 2020.

(PDF)

Click here for additional data file.^{(355.2KB, pdf)}

S1 File. Search phrases.

(PDF)

Click here for additional data file.^{(269.3KB, pdf)}

S2 File. QAREL supplement.

(PDF)

Click here for additional data file.^{(245.2KB, pdf)}

S3 File. QUADAS-2 supplement.

(PDF)

Click here for additional data file.^{(490.4KB, pdf)}

S4 File. Statistical analysis supplement.

(ZIP)

Click here for additional data file.^{(704.6KB, zip)}

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Data Availability Statement

All relevant data are within the paper and its Supporting Information files.

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PERMALINK

Validity and reliability of portable A-mode ultrasound in measuring body fat percentage: A systematic review with meta-analysis

Luiz Fernando Ferreira

Elirez Bezerra da Silva

Alexander Barreiros Cardoso Bomfim

Roles

Abstract

Introduction

Objective

Method

Eligibility criteria

Sources of information and search strategy

Fig 1. Flowchart of the 13 studies included in the meta-analysis with a total of 26 results, with 14 results for validity and 12 results for reliability.

The study selection process, data collection and collected items

Assessment of methodological quality and risk of bias of studies

Fig 2. Methodological quality and risk of bias for validity studies according to the QUADAS-2 scale.

Table 1. Methodological quality and risk of bias for reliability studies according to the QAREL scale.

Effect measures

Synthesis of collected data methods

Table 2. Data extracted from the studies included in the meta-analysis.

Fig 3. Forest plot of the 11 included studies, with 14 meta-analyzed results.

Fig 5. Forest plot of the 10 included studies, with 12 meta-analyzed results.

Fig 4. Funnel plot, qualitative analysis of publication bias.

Fig 6. Funnel plot, qualitative analysis of publication bias.

Table 3. Results of subgroup analysis to detect the cause of heterogeneity.

Results

Validity studies

Reliability studies

Discussion

Validity studies

Reliability studies

Conclusion

Registration and protocol

Supporting information

Data Availability

Funding Statement

References

Decision Letter 0

Patricia Rezende do Prado

Roles

Author response to Decision Letter 0

Decision Letter 1

Emiliano Cè

Roles

Author response to Decision Letter 1

Decision Letter 2

Emiliano Cè

Roles

Acceptance letter

Emiliano Cè

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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