<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.2" xml:lang="en">
    <front>
        <journal-meta>
            <journal-id journal-id-type="pmc">F1000Research</journal-id>
            <journal-title-group>
                <journal-title>F1000Research</journal-title>
            </journal-title-group>
            <issn pub-type="epub">2046-1402</issn>
            <publisher>
                <publisher-name>F1000 Research Limited</publisher-name>
                <publisher-loc>London, UK</publisher-loc>
            </publisher>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.12688/f1000research.109195.1</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Research Article</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>Cut-off points for low skeletal muscle mass in older adults: Colombia 
                    <italic>versus</italic> other populations</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: 1 approved, 1 approved with reservations]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Pineda-Zuluaga</surname>
                        <given-names>Maria Camila</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Gonz&#x00e1;lez-Correa</surname>
                        <given-names>Clara Helena</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0001-5621-2166</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Sepulveda-Gallego</surname>
                        <given-names>Luz Elena</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Department of Basic Sciences, Universidad de Caldas, Manizales, Research Group of Nutrition, Metabolism and Food Safety, Colombia</aff>
                <aff id="a2">
                    <label>2</label>Department of Public Health, Universidad de Caldas, Manizales, Research Group for Health Promotion and Disease Prevention, Colombia</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:clara.gonzalez@ucaldas.edu.co">clara.gonzalez@ucaldas.edu.co</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>11</day>
                <month>3</month>
                <year>2022</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2022</year>
            </pub-date>
            <volume>11</volume>
            <elocation-id>304</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>2</day>
                    <month>3</month>
                    <year>2022</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2022 Pineda-Zuluaga MC et al.</copyright-statement>
                <copyright-year>2022</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/11-304/pdf"/>
            <abstract>
                <p>
                    <bold>Background:</bold> The European Working Group on Sarcopenia in the Elderly defined sarcopenia as a geriatric syndrome with a diagnostic criteria of low skeletal muscle mass (LMM). Various sarcopenia consensuses recommend as cut-offs for LMM, the use of below 2 SDs from the mean skeletal muscle mass index (SMI) of a young reference group. Given the contrast between reported cut-offs, the objective of this study was to establish cut-offs for LMM from older adults in Manizales and compare them with those published in the literature.</p>
                <p>
                    <bold>Methods:</bold> This was a prospective, cross-sectional analytical study in 237 healthy elderly patients from the city of Manizales, Colombia. Anthropometric measurements of weight, height and body mass index were estimated. The SMI was estimated with the Xitron Technologies bioimpedance meter using the Janssen formula. For the comparison of SMI cut-offs, studies that evaluated this parameter with bioelectrical impedance analysis (BIA) were taken into account, in addition to being obtained from the &#x2212;2 SD from the sex-specific mean of a young reference group.</p>
                <p>
                    <bold>Results</bold>: The cut-off points for SMI were 8.0 kg/m
                    <sup>2</sup> for men and 6.1 kg/m
                    <sup>2</sup> for women. There was a statistically significant difference when evaluating LMM from the cut-offs of the present study and those reported in Spain, Turkey, and Finland. The cut-off points of SMI derived from this sample of Colombian men and women may be adequate for the diagnosis in the Colombian geriatric population. However, we did not find significant differences when comparing the cut-offs for SMI from a population of older adults and young adults from the same city.</p>
                <p>
                    <bold>Conclusions:</bold>The cut-off points of SMI by BIA derived from a sample of Colombian men and women may be adequate for the diagnosis of LMM in the Colombian geriatric population or populations with similar characteristics to those of the sample evaluated here.</p>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>Cut-off points</kwd>
                <kwd>skeletal muscle mass index</kwd>
                <kwd>older adults</kwd>
                <kwd>Colombia.</kwd>
            </kwd-group>
            <funding-group>
                <funding-statement>The author(s) declared that no grants were involved in supporting this work.</funding-statement>
            </funding-group>
        </article-meta>
    </front>
    <body>
        <sec id="sec1" sec-type="intro">
            <title>1. Introduction</title>
            <p>Human aging is related to a set of modifications that produce irreversible alterations in body systems.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup> At the level of the musculoskeletal system, there is a reduction in muscle mass and a decrease in strength, which leads to the loss of functional capacity, which is known as sarcopenia.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> The prevalence of this disease ranges between 15% and 50% and increases progressively with age depending on sociodemographic and gender variables.
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> Sarcopenia is one of the main causes of age-related disability
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup> and is associated with frailty, muscle weakness, functional impairment, falls, fractures, dependency, institutionalization, and even premature death
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup> it also imposes a significant economic burden on health services.
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> The European Working Group on Sarcopenia in Older People (EWGSOP)
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> defined this as a geriatric syndrome that requires the presence of low skeletal muscle mass (LMM) as one of its main diagnostic criteria.
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup>
            </p>
            <p>Among the etiological mechanisms of LMM in older adults are the decrease in sex hormones, increased apoptosis, mitochondrial dysfunction, loss of motor neurons, decreased physical activity, endocrine alterations, among others.
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> That is how, LMM is a common problem for older adults around the world, with a prevalence ranging from 7% to 50%,
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> likewise, an annual decrease of 3% is reported after the sixth decade of life.
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup>
            </p>
            <p>Estimation of skeletal muscle mass (SMM) can be done from various methods. In terms of precision and reproducibility, magnetic resonance imaging (MRI) and dual-X-ray absorptiometry (DXA) are ideal.
                <sup>
                    <xref ref-type="bibr" rid="ref13">13</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup> However, these methods are often expensive, complex, less available in clinical practice and commonly not used in studies with large sample sizes.
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup> Bioelectrical impedance analysis (BIA) is not only the most widely available technique in low- and middle-income countries,
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> but also a reliable, portable, simple, inexpensive, and non-invasive method that estimates body composition and is taken as a valid substitute for total muscle mass with high correlation with MRI results.
                <sup>
                    <xref ref-type="bibr" rid="ref16">16</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref17">17</xref>
                </sup>
            </p>
            <p>To establish an LMM for older adults by BIA, the literature establishes some variables that must be considered, such as device, measurement methodology, BIA equation, and characteristics of the population studied, such as geographic location, age, race, sex, lifestyle, weight, height, among others.
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup>
            </p>
            <p>Most researchers evaluate the total or appendicular SMM in young adults since in this age range the plateau of muscle growth is reached and subsequently remains relatively constant.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> Similarly, the EWGSOP and the Asian Sarcopenia Group (AWGS) recommend as cut-off points for LMM, the use of minus two standard deviations (&lt;&#x2212;2 SD) from the sex-specific mean of a young reference group.
                <sup>
                    <xref ref-type="bibr" rid="ref18">18</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref19">19</xref>
                </sup> In contrast to the above, the cut-off points used can alter the interpretation of the results to a great extent. As an example, Baumgartner 
                <italic toggle="yes">et al</italic>.,
                <sup>
                    <xref ref-type="bibr" rid="ref20">20</xref>
                </sup> defined cut-off points for low muscle mass at 7.26 kg/m
                <sup>2</sup> and 5.45 kg/m
                <sup>2</sup>, for men and women, respectively; while a previous study in our city, defined it as 8.39 kg/m
                <sup>2</sup> and 6.42 kg/m
                <sup>2</sup>, for men and women.
                <sup>
                    <xref ref-type="bibr" rid="ref21">21</xref>
                </sup> These variations in the young population demonstrate the need to establish ethnic cut-off points and even those derived from older adults who live in the community to achieve real diagnoses that promote preventive and therapeutic strategies to impact sarcopenia.</p>
            <p>Given the contrast between the data reported in the different geographic areas, the objective of this study was to compare cut-off points for LMM from older adults in Manizales with those found in the literature.</p>
        </sec>
        <sec id="sec2" sec-type="methods">
            <title>2. Methods</title>
            <sec id="sec3">
                <title>2.1 Study design and subjects</title>
                <p>This was a prospective, cross-sectional analytical study. The calculation of the sample size was 195 people, as described by the Manizales City Council, which reported 40000 adults over 60 years of age in a city having approximately 400000 habitants&#x00a0;and a sarcopenia prevalence of 15.5%, with 95% confidence and precision 5%. Finally,&#x00a0;237 elderly patients from the city of Manizales who live in the community were included in the study. The patients were evaluated between March 2019 and March 2020, in the University of Caldas&#x00a0;health service provider. The inclusion criteria considered being over 60 years of age, being a resident of Manizales, not having a sarcopenia diagnosis, and being independent in carrying out activities of daily living. Once they attended the assessment site, it was confirmed that they could perform activities such as dressing, undressing, going up and downstairs, using the bathroom, control sphincters, and move from chair to stretcher. Exclusion criteria were considered when there were&#x00a0;advanced or exacerbated chronic diseases, decompensated mental illnesses, partial or total amputation, pacemakers, wearing of non-removable metal parts or prostheses, moderate or severe disability, edema, and current use of diuretics were defined. This project was evaluated by the ethics committee of the Faculty of Health of the University of Caldas and was considered low risk (ethic&#x2019;s board number CBCS-094), likewise, the participants signed the informed consent, before to being included in the study.</p>
            </sec>
            <sec id="sec4">
                <title>2.2 Anthropometric measurements</title>
                <p>The measurements were performed in the morning, and it was confirmed that the patients met the standardization requirements for their evaluation.
                    <sup>
                        <xref ref-type="bibr" rid="ref22">22</xref>
                    </sup> Height without shoes was assessed with a Seca Heightronic-235 stadiometer
                    <sup>&#x00ae;</sup>, and the weight with light clothing with a PP2000 from Icob-Dectecto
                    <sup>&#x00ae;</sup>, with a scale of &#x00b1;0.01 cm and &#x00b1;0.1 kg, respectively. When there was a difference greater than 0.5 cm or 0.01 kg, a third measurement was taken, to have an average and record the final result. In addition, the body mass index (BMI) was established as weight over height squared, BMI = (weight/height
                    <sup>2</sup>).</p>
            </sec>
            <sec id="sec5">
                <title>2.3 Estimation of the SMI using BIA and cut-off points</title>
                <p>For the BIA estimates, humidity and temperature were controlled using a dehumidifier (BFH416 from Bionaire TM), heater, and thermo-hygrometer (13307 from Delta Trak
                    <sup>&#x00ae;</sup>, &#x00b1;0.1&#x00b0;C). BIA was performed three times on the dominant hemi-body on a non-conductive table with the Hydra 4200 Xitron Technologies bioimpedancemeter
                    <sup>&#x00ae;</sup>. The SMM was calculated from data at the resistance of 50 kHz and the predictive equation of Janssen 
                    <italic toggle="yes">et al</italic>., validated for the Hispanic population (
                    <xref ref-type="disp-formula" rid="e1">equation 1</xref>)
                    <sup>
                        <xref ref-type="bibr" rid="ref23">23</xref>
                    </sup>:
                    <disp-formula id="e1">
                        <mml:math display="block">
                            <mml:mi>SMM</mml:mi>
                            <mml:mspace width="0.25em"/>
                            <mml:mfenced close=")" open="(" separators="|">
                                <mml:mi>kg</mml:mi>
                            </mml:mfenced>
                            <mml:mo>=</mml:mo>
                            <mml:mfenced close="]" open="[" separators="|">
                                <mml:mrow>
                                    <mml:msup>
                                        <mml:mtext>(height</mml:mtext>
                                        <mml:mn>2</mml:mn>
                                    </mml:msup>
                                    <mml:mo>/</mml:mo>
                                    <mml:msub>
                                        <mml:mi>R</mml:mi>
                                        <mml:mtext>50</mml:mtext>
                                    </mml:msub>
                                    <mml:mspace width="0.25em"/>
                                    <mml:mi>x</mml:mi>
                                    <mml:mspace width="0.25em"/>
                                    <mml:mn>0.401</mml:mn>
                                    <mml:mo>+</mml:mo>
                                    <mml:mfenced close=")" open="(" separators="|">
                                        <mml:mrow>
                                            <mml:mtext>gender</mml:mtext>
                                            <mml:mspace width="0.25em"/>
                                            <mml:mi>x</mml:mi>
                                            <mml:mspace width="0.25em"/>
                                            <mml:mn>3.825</mml:mn>
                                        </mml:mrow>
                                    </mml:mfenced>
                                    <mml:mo>+</mml:mo>
                                    <mml:mfenced close=")" open="(" separators="|">
                                        <mml:mrow>
                                            <mml:mi>age</mml:mi>
                                            <mml:mspace width="0.25em"/>
                                            <mml:mi>x</mml:mi>
                                            <mml:mo>&#x2212;</mml:mo>
                                            <mml:mn>0.071</mml:mn>
                                        </mml:mrow>
                                    </mml:mfenced>
                                </mml:mrow>
                            </mml:mfenced>
                            <mml:mo>+</mml:mo>
                            <mml:mn>5.102</mml:mn>
                            <mml:mo>.</mml:mo>
                        </mml:math>
                        <label>(1)</label>
                    </disp-formula>
                </p>
                <p>In this, the height is expressed in cm and&#x00a0;the BIA&#x00a0;resistance (R
                    <sub>50</sub>) in ohms. For gender, 1 is for men and 0 to women, and age in years. Subsequently, to determine the SMI the SMM is normalized for height, SMI = (SMM/height
                    <sup>2</sup>). Finally, to establish the cut-off point of SMI, the specific mean by sex was taken into account &lt;&#x2212;2 SD to define LMM.</p>
            </sec>
            <sec id="sec6">
                <title>2.4 Comparison of cut-off points</title>
                <p>A bibliographic search of descriptive studies, cut-off points&#x00a0;studies, clinical trials, meta-analysis, and consensus was carried out in electronic databases, including Aminar, Mendeley, Nature, PubMed, Web of Science, Taylor &amp; Francis, Springer, Scopus, and Science Direct. Due to LMM is commonly confused with sarcopenia in the literature, we use both terms for the search. For the search strategy the following MeSH terms and boolean operators were used: (&#x201c;cut-off points&#x201d; AND &#x201c;skeletal muscle mass&#x201d;) (&#x201c;cut-off points&#x201d; AND &#x201c;sarcopenia&#x201d;), (&#x201c;cut-off points&#x201d; AND &#x201c;Low skeletal muscle mass&#x201d;), (&#x201c;Skeletal muscle mass&#x201d; AND &#x201c;bioelectrical impedance analysis&#x201d;), (&#x201c;low skeletal muscle mass&#x201d; AND &#x201c;elderly&#x201d;), (&#x201c;sarcopenia&#x201d; AND &#x201c;bioelectrical impedance analysis&#x201d;),</p>
                <p>Studies in English and Spanish with full- text availability recording&#x00a0;SMM values estimated by BIA that reported normalized&#x00a0;cut-off points of SMI for&#x00a0;LMM diagnosis&#x00a0;in older adults were included. These cut-off points had to be obtained from the mean value &lt;&#x2212;2 SD of a young or older reference population differentiated by sex. On the other hand, those studies written in languages other than Spanish and English, were duplicated, defined cut-off points of SMI from appendicular BIA or&#x00a0;had measurements with methods other than BIA were excluded.</p>
                <p>The data of the studies found were exported to an Excel spreadsheet (Microsoft Excel 2010; RRID:SCR_016137) to eliminate duplicate references and extract of the purpose of the research, methodological design, population characteristics, description of the BIA device, and recording of the cut-off points for the SMI for each sex (
                    <xref ref-type="fig" rid="f1">Figure 1</xref>).</p>
                <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                    <label>Figure 1. </label>
                    <caption>
                        <title>Flowchart on the selection of studies that report cut-off points for SMI for diagnosis of LMM.</title>
                    </caption>
                    <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/120671/e0531291-a116-4f3b-8215-4c33b746d900_figure1.gif"/>
                </fig>
            </sec>
            <sec id="sec7">
                <title>2.5 Statistical analysis</title>
                <p>The Kolmogorov&#x2013;Smirnov test was used to determine the distribution of the data since more than 50 people were evaluated. For the descriptive analysis of the qualitative variables, absolute values and relative frequencies were used. The quantitative variables were analyzed according to their distribution using means and standard error of the mean. SMI values were classified by sex and were shown as mean and SD of the mean with 95% confidence intervals for comparison with other studies. Subsequently, the different cut-off points for SMI found in the literature were applied to the 237 older adults in the present study to establish the proportion of people with LMM and identify whether there were significant differences between them. Then the confidence intervals of the difference of these proportions were established. All analyses were carried out with the statistical software SPSS (SPSS version 25; RRID: SCR_002865), licensed by the University of Caldas.</p>
            </sec>
        </sec>
        <sec id="sec8" sec-type="results">
            <title>3. Results</title>
            <p>This study included 237 people older than 60 years. 59.5% were men and in the range of&#x00a0; 65 to 69.9 years and constituted 54.4% of the sample. Urban origin was predominated, the right hand was dominant in 225 of the participants and the BMI was higher in women. The SMM for this sample was 27.8 kg for men and 17.3 kg for women. The mean and SD for the SMI were estimated at 9.6&#x00b1;0.8 kg/m
                <sup>2</sup> and 7.5&#x00b1;0.7 kg/m
                <sup>2</sup> for men and women, respectively. In the present study, the cut-off points for SMI were established as &#x2212;2 SD of the mean of the elderly, then&#x00a0;8.0 kg/m
                <sup>2</sup> for men and 6.1 kg/m
                <sup>2</sup> for women&#x00a0;were the final results.</p>
            <p>Six articles reported&#x00a0; cut-off points for SMI by BIA. Five of them used tetrapolar technique and measurements at 50 kHz, the remaining four studies do not report this type of data. Most of the studies used the formula of Janssen et al., to estimate the SMI.
                <sup>
                    <xref ref-type="bibr" rid="ref24">24</xref>
                </sup> One study reported&#x00a0; SMM &#x00a0;calculation as a multiplication of FFM estimated by BIA with a constant (0.566) and then normalizing it by the height of the subjects. From these six&#x00a0;studies, similar to the one reported here, only one established the cut-off points for SMI for a population of healthy adults over 60 years, while the others established it from &#x2212;2 SD of a young reference group of the same population.</p>
            <p>The study by Villada 
                <italic toggle="yes">et al.</italic>, although it was not carried out in the elderly population, did have as its objective the assessment of young adults to determine the cut-off points for LMM in older adults, and that is why it will be included in this comparison, since, additionally, it was carried out in the same geographic region of the present study and we were interested to know whether or not there was a significant difference when applying its cut-off points to our sample.</p>
            <p>The range of published cut-off points for SMI for the diagnosis of LMM was 8.25 kg/m
                <sup>2</sup> to 9.31 kg/m
                <sup>2</sup> in men and 5.14 kg/m
                <sup>2</sup> to 7.40 kg/m
                <sup>2</sup> in women. The cut-off points of the SMI of this study and those reported in the literature are presented in 
                <xref ref-type="table" rid="T1">Table 1</xref>.</p>
            <table-wrap id="T1" orientation="portrait" position="float">
                <label>Table 1. </label>
                <caption>
                    <title>Articles that report SMI cut-off points through BIA.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Author</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Population</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Team of BIA</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Criteria for cut-off point</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Cut-off point (kg/m
                                <sup>2</sup>)</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Masanes et al. 2012
                                <sup>
                                    <xref ref-type="bibr" rid="ref12">12</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">230 healthy people, 70-80 years old, Spain.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">RJL Systems BIA 101</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-2SD of Spanish young adults (20-42 years old).</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2642;8.25; &#x2640;6.68</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Han et al. 2016
                                <sup>
                                    <xref ref-type="bibr" rid="ref6">6</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Older adults 878 healthy people,&gt; 65 years, China</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">MFBIA InBody 720</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-2SD of Chinese young adults (20-40 years).</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2642;7.40; &#x2640;5.14</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Bahat et al. 2016
                                <sup>
                                    <xref ref-type="bibr" rid="ref8">8</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">406 outpatients,&gt; 60 years, Turkey</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Tanita BC-532</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-2SD of Turkish young adults (18-39 years old).</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2642;9.20; &#x2640;7.40</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Villada et al. 2018
                                <sup>
                                    <xref ref-type="bibr" rid="ref21">21</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">255 healthy young people, 10,835 years old, Colombia</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Hydra 4200 Xitron Technologies</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-2SD of young Colombian adults (18-35 years old).</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2642;8.39; &#x2640;6.42</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Bj&#x00f6;rkman et al. 2019
                                <sup>
                                    <xref ref-type="bibr" rid="ref14">14</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">428 healthy people,&gt; 75 years old, Finland</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">ImpediMed SFB7</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Average value of older adults</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2642;9.31; &#x2640;6.90</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Bulut et al. 2020
                                <sup>
                                    <xref ref-type="bibr" rid="ref19">19</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1150 healthy people,&gt; 60 years, Turkey</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Tanita MC-780U</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-2DE of Turkish young adults.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2642;8.33; &#x2640;5.70</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Pineda et al. 2022
                                <xref ref-type="table-fn" rid="tfn1">*</xref>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">237 healthy people,&gt; 60 years old, Colombia</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Hydra 4200 Xitron Technologies</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-2SD of the mean value for older adults</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2642;8.0; &#x2640;6.1</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>Abbreviations: BIA: Bioelectrical impedance analysis; -2DE: below two standard deviations; &#x2642;: Man; &#x2640;: Woman.</p>
                    <fn-group content-type="footnotes">
                        <fn id="tfn1">
                            <label>*</label>
                            <p>Present study.</p>
                        </fn>
                    </fn-group>
                </table-wrap-foot>
            </table-wrap>
            <p>Finally, the cut-off points for the diagnosis of LMM reported in the literature were applied to our sample of 237 healthy older adults from the city of Manizales. It was found that the portion the proportion of people with LMM when applying the different cut-off points ranged from 0.0084 to 0.3544. With the cut-off points of the present study, three persons with LMM were identified, while with the study by Masanes 
                <italic toggle="yes">et al</italic>., 23 cases; Han 
                <italic toggle="yes">et al</italic>., zero cases; Bahat 
                <italic toggle="yes">et al</italic>., 84 cases; Villada 
                <italic toggle="yes">et al</italic>., four cases; Bj&#x00f6;rkman 
                <italic toggle="yes">et al</italic>., 59 cases and Bulut 
                <italic toggle="yes">et al</italic>., two cases.</p>
            <p>Once the confidence intervals of the difference in the proportions were established, a statistically significant difference was found between the LMM results of the cut-off points of the present study and those reported in three of the articles.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref19">19</xref>
                </sup> On the other hand, the study by Villada 
                <italic toggle="yes">et al</italic>., did not show a significant difference in the LMM from &#x2212;2 SD of the mean of older adults or those obtained from &#x2212;2 SD of the mean in a young population reference from the same region.</p>
        </sec>
        <sec id="sec9" sec-type="discussion|conclusion">
            <title>4. Discussion and conclusion</title>
            <p>This is the first Latin American study using a sample of healthy older adults living in the community to establish SMI cut-off points for LMM by BIA. In the present study, the cut-off points for this purpose, were &lt;8.0 kg/m
                <sup>2</sup> for men and &lt;6.1 kg/m
                <sup>2</sup> for women. These data are lower than those reported by Bahat 
                <italic toggle="yes">et al</italic>.,
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> who described 9.20 kg/m
                <sup>2</sup> and 7.40 kg/m
                <sup>2</sup> in men and women, respectively. Perhaps, this difference is due to the fact that the Caucasian population has a different anthropometry than the Latin American ones, as suggested by Gallagher 
                <italic toggle="yes">et al</italic>.,
                <sup>
                    <xref ref-type="bibr" rid="ref25">25</xref>
                </sup> when they establish that the SMI depends on 80% of the variables height, age, weight, and sex.</p>
            <p>SMM is considered an important parameter of body composition, associated with chronic diseases and risk to the health of older adults.
                <sup>
                    <xref ref-type="bibr" rid="ref26">26</xref>
                </sup> The BIA technique allows the calculation of the SMI and is valid substitute for total muscle mass since it has a good correlation with the results from the MRI.
                <sup>
                    <xref ref-type="bibr" rid="ref16">16</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref17">17</xref>
                </sup> However, the validity and precision of this method depend on the formula and methodology used, so it is important to have an adequate protocol and reference values applicable to the study population.
                <sup>
                    <xref ref-type="bibr" rid="ref27">27</xref>
                </sup>
            </p>
            <p>When doing the bibliographic review, it was realized that the measurement of the cut-off points of SMI to define LMM has been carried out in few populations around the world,
                <sup>
                    <xref ref-type="bibr" rid="ref28">28</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref29">29</xref>
                </sup> so it was not possible to find articles that met the inclusion criteria in Latin American countries. For this reason, and due to the high prevalence LMM, more research is required to obtain baseline data and establish cut-off points for SMI that can be used in clinical practice in order to carry out timely medical interventions.
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup> Several studies have shown significant differences in the prevalence of LMM when applying cut- off points to populations other than the original population group.
                <sup>
                    <xref ref-type="bibr" rid="ref30">30</xref>
                </sup> For this reason, it is suggested that these data obtained for populations of specific ethnic groups.
                <sup>
                    <xref ref-type="bibr" rid="ref31">31</xref>
                </sup> Thus, this study represents one of the few that records specific data for a country.</p>
            <p>It should be noted that our results showed statistically significant differences when evaluating LMM applying the data obtained in this study and those reported in three studies published in samples from Spain, Turkey and, Finland.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref19">19</xref>
                </sup> Thereby, it could be said that cut-off points cannot be used in the populations indistinctly because the genetic characteristics of the populations, anthropometric and occupational differences, type of methodology, equipment, statistical analysis, and cut-off point used.
                <sup>
                    <xref ref-type="bibr" rid="ref32">32</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref33">33</xref>
                </sup>
            </p>
            <p>This is how that, when applying the cut-off points established in this study, the cases of LMM were significantly lower and differ from those described in other geographical areas. The differences found may be due, not only to the reasons already stated, but also to the fact that most of these studies obtained their data from young reference population and not directly from healthy older adults as in the present study. The cut-off points for SMI were the lowest, perhaps because they were derived from &#x2212;2 SD from the mean value obtained in a group of healthy older adults and, therefore, the mean value of this population is smaller than the of young adults.
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup> This is why no universal cut-off points are defined for diagnosing LMM.</p>
            <p>It should also be said that in a country with ethnic diversity like Colombia, which also has a different aging index for each region, it is necessary to define regional limits for the application of these cut-off points.</p>
            <p>There was no significant difference in the identification of LMM cases applying to our sample the cut-off points found from older or younger adults from the same city (Manizales). The implication in the clinical practice is that the use of our cut-off points from a young population in closer to real data form elders and prevents underestimation or overestimation of the prevalence of LLM or sarcopenia in older adults as if it could happen if, for example, the cut-off points reported by Bahat 
                <italic toggle="yes">et al.</italic>
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> (male: 9.20; female: 7.40) were used for our population, or, even more serious, if the references by a Masanes 
                <italic toggle="yes">et al.</italic>
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup> (male: 8.25; female: 6.68), or Bj&#x00f6;rkman 
                <italic toggle="yes">et al.</italic>
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup> (male: 9.31; female: 6.90) were applied.</p>
            <p>The study is not without limitations. The BIA values were not validated by a reference technique such as DXA or MRI and previous studies have reported that the estimation of SMM in older adults using BIA can lead to inaccuracies due to the hydration of their lean mass and the shape of the appendicular muscles.
                <sup>
                    <xref ref-type="bibr" rid="ref34">34</xref>
                </sup> However, the technique has been recommended by the EWGSOP.
                <sup>
                    <xref ref-type="bibr" rid="ref31">31</xref>
                </sup> Another limitation is that were few patients older than 70 years, and it is recommended to expand the sample from this age in future studies. On the other said, the strength of this study has to do with the extensive review of the literature to find studies that reported their cut-off points for LMM by BIA. Furthermore, BIA evaluation was carried out under standardized protocols that allowed the results. In addition, the SMI was calculated from the formula of Janssen 
                <italic toggle="yes">et al.</italic>,
                <sup>
                    <xref ref-type="bibr" rid="ref35">35</xref>
                </sup> which was a cross-validated with whole-body MRI a BIA equation, in a sample of 269 Caucasian men and women between 18 and 86 years old. Here it is important to mention that the authors reported this equation as a tool useful for Caucasian, African American and Hispanic populations. In this way, the findings of the present work should be considered under the limitations and strengths expressed.</p>
            <p>In conclusion, no significant differences were found when comparing the cut-off points for SMI of population of older and younger adults from the same city, so evaluating LMM from the latter would not cause an overestimation of this pathology. The cut-off points of SMI by BIA derived from a sample of Colombian men and women may be adequate for the diagnosis of LMM in the Colombian geriatric population or populations with similar characteristics to those of the sample evaluated here.</p>
        </sec>
        <sec id="sec10">
            <title>Data availability</title>
            <p>Data are restricted as part of the written informed consent. Data may be obtained for the purposes of research or review from Clara Helena Gonz&#x00e1;lez-Correa (
                <email xlink:href="mailto:clara.gonzalez@ucalas.edu.co">clara.gonzalez@ucalas.edu.co</email>) on the condition that permission is granted by the participants and for research or review purposes only.</p>
        </sec>
    </body>
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                    <article-title>Skeletal Muscle Cutpoints Associated with Elevated Physical Disability Risk in Older.</article-title>
                    <year>2004</year>;<volume>159</volume>(<issue>4</issue>):<fpage>413</fpage>&#x2013;<lpage>21</lpage>.</mixed-citation>
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    </back>
    <sub-article article-type="reviewer-report" id="report164396">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.120671.r164396</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>L&#x00f3;pez-Teros</surname>
                        <given-names>Miriam T.</given-names>
                    </name>
                    <xref ref-type="aff" rid="r164396a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0001-9486-005X</uri>
                </contrib>
                <aff id="r164396a1">
                    <label>1</label>Medical, Dental and Health Sciences Program, National Autonomous University of Mexico, Mexico City, Mexico</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>11</day>
                <month>5</month>
                <year>2023</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2023 L&#x00f3;pez-Teros MT</copyright-statement>
                <copyright-year>2023</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport164396" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.109195.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>The objective of this article is to define cut-off points for LMM (low muscle mass) using SMI (skeletal muscle mass index) evaluated by BIA (bioimpedance) for Colombian older adults, which can be used for the diagnosis of sarcopenia. It is pertinent since the importance of having specific cut-off points for each region is recognized, in addition to the fact that there are few published studies on SMM (Whole-body skeletal muscle mass) or ASMM (appendicular skeletal muscle mass) cut-off points. The importance of having specific cut-off points for each region to define LMM is recognized.</p>
            <p> </p>
            <p> 
                <underline>
                    <bold>Observations:</bold>
                </underline>
            </p>
            <p> </p>
            <p> 
                <underline>Introduction:</underline> 
                <list list-type="bullet">
                    <list-item>
                        <p>It is suggested to mention the difference between obtaining Whole-body skeletal muscle mass (SMM) and not ASMM to define LMM, as mentioned in EWGSOP2.</p>
                    </list-item>
                    <list-item>
                        <p>I don't know if in this analysis the ASMM could have been better calculated, this formula could have been used for its estimation that is mentioned in the EWGSOP2 (Yamada 
                            <italic>et al.</italic>, 2017
                            <sup>
                                <xref ref-type="bibr" rid="rep-ref-164396-1">1</xref>
                            </sup>).</p>
                    </list-item>
                </list> </p>
            <p> 
                <underline>Methodology:</underline> 
                <list list-type="bullet">
                    <list-item>
                        <p>In relation to the previous comment, the MesH term "appendicular skeletal muscle mass" could have been added to the systematic review.</p>
                    </list-item>
                </list> </p>
            <p> 
                <underline>Statistic analysis:</underline> 
                <list list-type="bullet">
                    <list-item>
                        <p>It is mentioned that the proportion of subjects with LMM in the present study was compared with the results reported in the studies included in the review, but it is not mentioned what statistical tests were used for this comparison.</p>
                    </list-item>
                </list> </p>
            <p> 
                <underline>Results:</underline> 
                <list list-type="bullet">
                    <list-item>
                        <p>It is recommended to add a table of the general characteristics of the study population, such as means and frequencies of variables such as age, sex, comorbidity, anthropometric measurements (weight, height, BMI), SMI, among others.</p>
                    </list-item>
                    <list-item>
                        <p>It is mentioned that there were significant differences between the proportion of subjects with LMM in the present study versus studies reported in the review, it is suggested to add the p value or the 95% CI found in the statistical tests.</p>
                    </list-item>
                </list> </p>
            <p> 
                <underline>Discussion:</underline> 
                <list list-type="bullet">
                    <list-item>
                        <p>To go deeper into using SMM and not ASMM to define LMM, as well as about the model used Hydra 4200 Xitron Technologies bioimpedancemeter&#x00ae;, which has previously been reported on the accuracy of this equipment.</p>
                    </list-item>
                </list>
            </p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Partly</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>No source data required</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>Nutrition and geriatric, with researc topics: sarcopenia, frailty, physical performance,&#x00a0; functional dependence, dietary patterns and food security in older adults.</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.</p>
        </body>
        <back>
            <ref-list>
                <title>References</title>
                <ref id="rep-ref-164396-1">
                    <label>1</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>Developing and Validating an Age-Independent Equation Using Multi-Frequency Bioelectrical Impedance Analysis for Estimation of Appendicular Skeletal Muscle Mass and Establishing a Cutoff for Sarcopenia.</article-title>
                        <source>
                            <italic>Int J Environ Res Public Health</italic>
                        </source>.<year>2017</year>;<volume>14</volume>(<issue>7</issue>) :
                        <elocation-id>10.3390/ijerph14070809</elocation-id>
                        <pub-id pub-id-type="pmid">28753945</pub-id>
                        <pub-id pub-id-type="doi">10.3390/ijerph14070809</pub-id>
                    </mixed-citation>
                </ref>
            </ref-list>
        </back>
        <sub-article article-type="response" id="comment9768-164396">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>Gonz&#x00e1;lez-Correa</surname>
                            <given-names>Clara Helena </given-names>
                        </name>
                        <aff>Universidad de Caldas, Colombia</aff>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>No se revelaron intereses contrapuestos.</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>14</day>
                    <month>6</month>
                    <year>2023</year>
                </pub-date>
            </front-stub>
            <body>
                <p>
                    <bold>Dear reviewer,</bold>
                </p>
                <p> </p>
                <p> We welcome your comments and suggestions about our work. We will take into account what you suggest to improve the academic merit of our research.</p>
                <p> </p>
                <p> 
                    <bold>1. It is suggested to mention the difference between obtaining Whole-body skeletal muscle mass (SMM) and not ASMM to define LMM, as mentioned in EWGSOP2.</bold>
                </p>
                <p> </p>
                <p> The reason why we use total and not appendicular SMI, is because in the investigations carried out in our research laboratory a protocol has been used since 2013 to standardize the measurement of patients (Bioelectrical impedance analysis (BIA): A proposal for standardization of the classical method in adults. 2012 J. Phys.: Conf. Ser. 407 012018).&#x00a0;</p>
                <p> Nevertheless, we are very grateful for your suggestion, as this is an aspect that we would like to take into account from now on in our research, taking into account the importance of evaluating LMM from the formula for ASMM as mentioned in EWGSOP2.&#x00a0;</p>
                <p> </p>
                <p> 
                    <bold>2. It is mentioned that the proportion of subjects with LMM in the present study was compared with the results reported in the studies included in the review, but it is not mentioned what statistical tests were used for this comparison.</bold>
                </p>
                <p> </p>
                <p> In the statistical analysis section, it was described: "SMI values were classified by sex and were shown as mean and SD of the mean with 95% confidence intervals for comparison with other studies. Subsequently, the different cut-off points for SMI found in the literature were applied to the 237 older adults in the present study to establish the proportion of people with LMM and identify whether there were significant differences between them. Then the confidence intervals of the difference of these proportions were established".&#x00a0;</p>
                <p> </p>
                <p> 
                    <bold>3. It is recommended to add a table of the general characteristics of the study population, such as means and frequencies of variables such as age, sex, comorbidity, anthropometric measurements (weight, height, BMI), and SMI, among others.</bold>
                </p>
                <p> </p>
                <p> In this case, as the general characteristics of the participants were few, we described them in text form in the initial part of the results. Thus, we describe the mean and standard deviation of age, gender, origin, and predominant dominance. We also mentioned that the BMI was higher in the women included in the study. We also described the mean and standard deviation of SMM and SMI by gender. Thank you very much for this recommendation, it will be taken into account for future research.&#x00a0;</p>
                <p> </p>
                <p> 
                    <bold>4. It is mentioned that there were significant differences between the proportion of subjects with LMM in the present study versus studies reported in the review, it is suggested to add the p-value or the 95% CI found in the statistical tests.</bold>
                </p>
                <p> </p>
                <p> ICs were added to the results session: "Finally, the cut-off points for the diagnosis of LMM reported in the literature were applied to our sample of 237 healthy older adults from the city of Manizales. It was found that the portion the proportion of people with LMM when applying the different cut-off points ranged from 0.0084 to 0.3544. With the cut-off points of the present study, three persons with LMM were identified, while with the study by Masanes et al., 23 cases (CI: 0,0778- 0,1162); Han et al., zero cases; Bahat et al., 84 cases (CI: 0,3233-0,3855); Villada et al., four cases (CI: 0,0078-0,0242); Bj&#x00f6;rkman et al., 59 cases (CI: 0,2208-0,277) and Bulut et al., two cases (CI: 0,0025-0,0143)".&#x00a0;</p>
                <p> </p>
                <p> 
                    <bold>5. To go deeper into using SMM and not ASMM to define LMM, as well as about the model used Hydra 4200 Xitron Technologies bioimpedancemeter&#x00ae;, which has previously been reported on the accuracy of this equipment.</bold>
                </p>
                <p> </p>
                <p> It was included in the discussion:&#x00a0;</p>
                <p> </p>
                <p> "In addition, the XiTRON Hydra 4200 was used to estimate muscle mass. This is a 3rd generation single-channel tetrapolar BIA device that scans 50 frequencies between 5kHz and 1MHz, its accuracy compared to the tedious laboratory dilution methods has been reported numerous times in scientific journals. Scientific studies have also shown the technology to be repeatable and sensitive to small changes, able to detect the volume distribution differences between subjects".</p>
            </body>
        </sub-article>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report147195">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.120671.r147195</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Bahat</surname>
                        <given-names>G&#x00fc;listan</given-names>
                    </name>
                    <xref ref-type="aff" rid="r147195a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <contrib contrib-type="author">
                    <name>
                        <surname>Tufan</surname>
                        <given-names>Asli</given-names>
                    </name>
                    <xref ref-type="aff" rid="r147195a2">2</xref>
                    <role>Co-referee</role>
                </contrib>
                <aff id="r147195a1">
                    <label>1</label>Division of Geriatrics, Department of Internal Medicine, Istanbul Medical School, Istanbul University, Istanbul, Turkey</aff>
                <aff id="r147195a2">
                    <label>2</label>Medical Faculty, Marmara University, Istanbul, Turkey</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>30</day>
                <month>8</month>
                <year>2022</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2022 Bahat G and Tufan A</copyright-statement>
                <copyright-year>2022</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport147195" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.109195.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>This is a prospective study aiming to define local cut-off points for low muscle mass and to compare them with the existing cut-off points in the literature. A &#x201c;one size fits all&#x201d; approach can be misleading in the diagnosis of sarcopenia. EWGSOP has therefore recommended that national cut-off points be used for sarcopenia diagnosis. This study fills a gap in the definition of sarcopenia and is of interest to the readership of the journal. However, some major and minor points need to be clarified.</p>
            <p> </p>
            <p> </p>
            <p> 
                <bold>Major point:</bold>
            </p>
            <p> For sarcopenia diagnosis, EWGSOP recommends using the normative data of healthy young adults. Why have the authors used the normative data of older adults for LMM diagnosis?</p>
            <p> </p>
            <p> </p>
            <p> 
                <bold>Minor points:</bold>
            </p>
            <p> &#x201c;237 elderly patients from the city of Manizales who live in the community were included in the study. The patients were evaluated in the University of Caldas health service provider.&#x201d; It is not quite clear how the patients were recruited. Were they hospital outpatients? If so, they are expected to be relatively more disabled compared to the older population in general, which may be considered as a limitation of the study.</p>
            <p> </p>
            <p> </p>
            <p> The abbreviations under table 1 reads:&#x00a0;</p>
            <p> -2
                <bold>DE</bold>: below two standard deviations, which should have been &#x201c;-2
                <bold>SD</bold>&#x201d;&#x00a0;(also in the table: &#x201c;-2DE of Turkish young adults&#x201d;).</p>
            <p> </p>
            <p> </p>
            <p> It would be better if the discussion started with &#x201c;To the authors&#x2019; best knowledge&#x2026;&#x201d;</p>
            <p> </p>
            <p> </p>
            <p> There are minor grammatical and semantic errors throughout the text.</p>
            <p> </p>
            <p> &#x201c;The implication in the clinical practice is that the use of our cut-off points from a young population in closer to real data form elders and prevents underestimation or overestimation of the prevalence of LLM or sarcopenia in older adults as if it could happen if, for example, the cut-off points reported by Bahat 
                <italic>et al</italic>.
                <sup>8</sup> (male: 9.20; female: 7.40) were used for our population, or, even more serious, if the references by a Masanes et al.12 (male: 8.25; female: 6.68), or Bj&#x00f6;rkman
                <italic> et al</italic>.
                <sup>14</sup> (male: 9.31; female: 6.90) were applied.&#x201d; This sentence in the discussion section is too long and confusing.</p>
            <p> </p>
            <p> </p>
            <p> In order to avoid ageism, the term &#x201c;elderly&#x201d; should be replaced with &#x201c;older adults&#x201d;.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>sarcopenia</p>
            <p>We confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however we have significant reservations, as outlined above.</p>
        </body>
        <sub-article article-type="response" id="comment8700-147195">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>Gonz&#x00e1;lez-Correa</surname>
                            <given-names>Clara Helena </given-names>
                        </name>
                        <aff>Universidad de Caldas, Colombia</aff>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>30</day>
                    <month>8</month>
                    <year>2022</year>
                </pub-date>
            </front-stub>
            <body>
                <p>
                    <italic>Dear reviewer,</italic>
                </p>
                <p> </p>
                <p> We welcome your comments and suggestions about our work. We will take into account what you suggest to improve the academic merit of our research.</p>
                <p> </p>
                <p> We will now respond to the first two comments. The other observations regarding terminology and grammatical errors will be taken into account and modified in the paper once the F1000 editorial authorizes it.</p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>For sarcopenia diagnosis, EWGSOP recommends using the normative data of healthy young adults. Why have the authors used the normative data of older adults for LMM diagnosis?</italic>
                    </bold>
                </p>
                <p> </p>
                <p> Although EWGSOP recommends using the normative data of healthy young adults, we used the</p>
                <p> normative data directly from older adults for LMM diagnosis because we consider that the rapidly</p>
                <p> changing dynamics of lifestyles and morbidities can create huge differences between a young</p>
                <p> generation from which reference values are taken and an older adult generation that may have a</p>
                <p> difference of 50 or more years. We wanted to see whether or not the cut-off points for low muscle</p>
                <p> mass resulting from the young were similar to those obtained from a population of older adults, all</p>
                <p> at ages corresponding to the same generation.</p>
                <p> </p>
                <p> 
                    <italic>
                        <bold>&#x00a0;If so, they are expected to be relatively more disabled compared to the older population in general, which may be considered as a limitation of the study.</bold>
                    </italic>
                </p>
                <p> </p>
                <p> The inclusion criteria considered being over 60 years of age, being a resident of Manizales, not having a sarcopenia diagnosis, and being independent in carrying out activities of daily living.</p>
                <p> </p>
                <p> The University of Caldas health service provider serves people not only from the University but is</p>
                <p> open to the entire community of the city. The volunteers were tested there but were recruited</p>
                <p> among independent people living in the community, who did not have pathologies that would</p>
                <p> affect the measurements of muscle mass and were considered healthy. Wide dissemination was</p>
                <p> carried out through social networks, word of mouth, pamphlets, the University's website, and</p>
                <p> other radio news media in the city.</p>
            </body>
        </sub-article>
    </sub-article>
</article>
