Potential Usefulness of Nutritional Ultrasound for Morphofunctional Assessment in Patients With Obesity

Potential Usefulness of Nutritional Ultrasound for Morphofunctional Assessment in Patients With Obesity | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Potential Usefulness of Nutritional Ultrasound for Morphofunctional Assessment in Patients With Obesity GARCIA OLIVARES MARIA, DALLA ROVERE LARA, FERNANDEZ JIMENEZ ROCIO, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3999407/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Assessing the nutritional status of patients with obesity (PwO) is mandatory to secure optimal management. Easy, affordable procedures to accomplish this purpose would be appreciated. Nutritional ultrasound (NU) is a simple, non-invasive method for morphofunctional analysis. Methods We evaluated the ability of NU to determine body composition in a cohort of 178 PwO. Bioelectrical impedance analysis (BIA) and handgrip strength dynamometry (HGS), which are accepted methods to monitor body composition and muscle functionality, respectively, in PwO, were used for comparative purposes. Results There was a highly significant correlation between NU-measured quadriceps rectus femoris (RF) cross-sectional area (CSA) and BIA-measured fat-free markers such as body cell mass (r = 0.638, P <0.001), fat free mass (r = 0.597, P <0.001) or appendicular skeletal muscle mass (r = 0.591, P <0.001). The correlation between RF-CSA and HGS was also significant (r = 0.536, P < 0.001). NU-measured leg subcutaneous adipose tissue (L-SAT) was highly correlated with BIA-measured fat mass (%) (r = 0.656, P <0.001). There was a significant inverse correlation between L-SAT and HGS (r = -0.416, P <0.001). Conclusions These results suggest that NU can be a useful, cheap, portable tool to assess nutritional status. Health sciences/Endocrinology/Endocrine system and metabolic diseases/Obesity Biological sciences/Physiology/Metabolism/Metabolic diseases/Metabolic syndrome Obesity nutritional status morphofunctional assessment nutritional ultrasound bioelectrical impedance analysis handgrip strength dynamometry Figures Figure 1 Figure 2 Figure 3 Introduction Obesity is a pathological condition. When not managed correctly, it may predispose patients to an increased risk of cardiorenal, metabolic and other complications, thus compromising their life expectancy and quality of life (QoL). Morphofunctional assessment of nutritional status and body composition is required to determine the appropriate treatment for patients with obesity (PwO) [1]. Body mass index (BMI), although enlightening, does not provide information regarding either body composition or visceral adiposity, thus increasing the risk of misleading diagnoses and favoring the so-called obesity or BMI paradox [2]. Dual-energy X-ray absorptiometry (DXA) is considered to be the reference method for evaluating body composition indicators such as fat mass (FM), fat free mass (FFM) or bone mineral content (BMC) [3, 4]. However, it has important limitations, namely expense, specific training requirement and radiation exposure, which preclude widespread use [5]. For this reason, other procedures have been applied and validated to assess body composition and muscle function, namely bioelectrical impedance analysis (BIA) and hand grip strength dynamometry (HGS). BIA is based on the different impedance for an electric current presented by the body’s water and cell mass, which allows the calculation of fat mass (FM) and fat free mass (FFM) [6]. BIA is not as expensive as DXA, and does not require specific training. BIA has shown good consistency for FM and FFM assessment in healthy subjects and PwO [7-9], although the results are influenced by the hydration level of the patient and measurements of body composition are indirect, which requires the use of prediction equations [10]. Handgrip strength dynamometry (HGS) is a reliable indicator of muscle condition and muscle functionality. HGS has been found to be associated with body composition parameters [11], and the procedure has been used to assess the risk of disease-related malnutrition [12], metabolic syndrome [13], abdominal obesity [14], and sarcopenic obesity (SO) [15]. Nutritional ultrasound (NU) evaluates body compartments such as muscle, adipose, connective, vascular and bone tissue, to assess ultrasound-based body composition. This procedure is emerging as a cheap, portable, non-invasive, widely available and easy-to-use procedure for morphofunctional assessment [16]. NU consists of two dimensions to assess FFM (muscle) and FM (adipose tissue). Many NU procedures involve the anterior rectum area of the quadriceps, the so called rectus femoris (RF). Its composition changes in malnutrition states are well defined [15, 16]. Thus, RF-cross-sectional-area (RF-CSA) and RF-Y-axis values have been shown to be reliable indicators of strength and functional performance [17-19]. NU also yields valuable information regarding subcutaneous fat in the leg (L-SAT), as well as abdominal fat, either subcutaneous or visceral (VAT) [20]. We have previously demonstrated the potential usefulness of NU to predict malnutrition-related mortality in cancer patients [21], and sarcopenia in post-critical COVID-19 and colorectal cancer patients [20, 22]. Our present aim was to test the suitability of NU in the morphofunctional assessment of PwO and metabolic diseases. For this purpose, the morphofunctional analysis of RF as a surrogate for body composition was performed by NU in a cohort of PwO. For validation purposes, NU diagnoses were compared with those obtained by BIA and HGS. Methods Study design Consecutive patients attending the Obesity Unit at Quirónsalud Hospital of Málaga, Spain, between November 2021 and November 2022, either for the first time or for routine review, who had a diagnosis of obesity, with or without DM2, were recruited for a cross sectional study. This consisted of assessing the morphofunctional status of patients by using functional procedures to measure muscle quality (HGS), as well as by applying BIA and NU-based procedures to determine body composition. The ultimate aim was to explore the suitability of NU to analyze the nutritional status of PwO. Patients also underwent extensive clinical examination and laboratory testing, and their obesity status was determined according to the American Association of Clinical Endocrinologists (AACE) guidelines [23]. Inclusion criteria were age ≥18 years old (y.o.) and either BMI ≥30 kg/m 2 or BMI ≥27 kg/m 2 and at least one comorbidity associated with body weight (prediabetes or type 2 diabetes, hypertension, dyslipidemia, obstructive sleep apnea, cardiovascular disease). Data anonymization was guaranteed. All patients gave informed consent. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki and started once the Provincial Research Ethic Committee (CEI) of Málaga had approved the study protocol. Study code was 1168-N-23. Morphofunctional assessment Nutritional Status and body composition BIA The bioimpedance measurements were performed using a phase-sensitive single-frequency analyzer (Nutrilab, Akern ® Srl, Pontassieve, Italy), as previously described [21]. In brief, the device applies an alternating sinusoidal electric current of 400 µA at 50 kHz [±0.1%; resolution Rz: ±1%, Xc: ±1%, coefficients of variation <2%]. Standard whole-body tetrapolar measurements were performed, with the patient in a supine position with a leg opening of 45° compared to the median line of the body, and the upper limbs 30° away from the trunk. One Ag/AgCl very low-impedance electrode was placed on the back of the right hand and another electrode on the corresponding foot, each one of them including a sensor and injector area separated by 5 cm (BIVAtrodes, Akern ® Srl). The patient was advised to abstain from food and drink for >2 h before the test to warrant proper fluid distribution. Resistance (R, Ω), reactance (Xc, Ω), phase angle (PhA, °), standardized phase angle (SPA, °) were determined, and bioelectric parameters to estimate the body composition, such as FM (kg and %), FFM (kg), body cell mass (BCM, kg), SMM (kg) and appendicular SMM (ASMM, kg), were assessed. NU A comprehensive NU study was performed, as previously described [22], to take advantage of the two dimensions of the procedure which allow the assessment of FFM and FM in RF, as well as of abdominal FM [16, 20-22]. A Mindray Ò Z60 ultrasound analyzer was used with frequency range of 10 to 12 MHz (Mindray, Madrid, Spain). The patient was relaxed in a supine position, lying with the knee fully extended. RF muscle ultrasound scans were taken in its lower third. RF-CSA, circumference of the quadriceps RF (RF-CIR), RF-X-axis and RF-Y-axis, i.e., the linear measurement of the distance between the muscular limits of the RF (lateral and anteroposterior), as well as L-SAT [24], were determined. Scans corresponding to abdominal adipose tissue ultrasound were also taken at the midpoint between the xiphoid appendix and the navel on the midline [total subcutaneous abdominal fat (T-SAT), superficial subcutaneous abdominal fat (S-SAT), preperitoneal or visceral fat (VAT)]. In order to minimize intraobserver variability, a trained healthcare technician performed three repeats for each measurement. The average value was subsequently calculated. Furthermore, a second trained examiner always monitored the procedures performed by the examiner. Fig. 1 shows two NU images corresponding to RF and abdominal adipose tissue. The aforementioned variables are properly identified and indicated. Functional outcome HGS was determined by using the JAMAR-Dynamometer (J. A. Preston Corporation, New York, NY, USA). Patients were sitting with the shoulder adducted and the elbow flexed at 90º with the forearm and wrist of the dominant arm in a neutral position. Three measurements were obtained, and the average value was considered as the final result. Statistical analyses For descriptive purposes, the mean [standard deviation (SD)] was used for quantitative, normally distributed variables. The two-tailed unpaired t test, with Welch’s correction in the event that variances were significantly different, was used to compare quantitative variables between female and male patients. The Fisher´s exact test was used to compare qualitative variables. In order to compare the suitability of the different procedures to assess the morphofunctional status of PwO, the one-tailed Pearson test was used to analyze correlations between functional/body composition variables determined by BIA, NU or HGS. Statistical significance was set at P <0.05. All calculations were performed using JAMOVI, version 2.3.22 (Sydney, Australia). Results Baseline features Two hundred patients attended the Obesity Unit during the scheduled study period. Fifteen of them had not the complete assessment with BIA, HGS and NU. Seven additional patients whose data were outliers not representing natural variations in the population but measurement, processing or data entry errors, were also excluded. Thus, 178 patients, 69.7% of whom were female, were finally recruited for morphofunctional assessment (Table 1). Male weight, BMI and waist circumference were significantly higher in male patients (average weight was 24 kg higher, and BMI and waist circumference were 2.6 kg/m 2 and 15 cm higher, respectively). HbA1c values were close to the lower limit of the range of prediabetes. Accordingly, fasting circulating glucose levels were also close to the upper range of normality, and the HOMA insulin resistance index (HOMA-IR) was elevated, being higher in males. More than 80% of patients presented with at least one obesity-related complication. Total cholesterol and trigycerides were within normal range, which was partly explained by the widespread use of statins (not shown). Male patients had a significantly higher BMI and waist circumference than female ones. Morphofunctional assessment Morphofunctional assessment measurements using BIA, NU and HGS are shown in Table 2. Significant differences between female and male patients were observed independently of the methods used to assess body composition and muscle strength. Higher values in muscle composition and muscle functionality variables were observed in men and, conversely, the proportion of abdominal and limb adipose tissue was higher in women. Accordingly, there were significant differences in BCM between men and women. More interestingly, there was a fair correlation between the different methods used to analyze body composition, as well as between these and functional assessment by HGS (Figs. 2 and 3). A highly significant correlation was observed between BIA functional and muscle markers such as BCM, FFM or ASMM, and the NU parameter that best represents strength and functional performance, namely RF-CSA. The association between the rest of the BIA and NU functional and muscle measurements was always significant or highly significant. A low, still significant correlation was observed between BIA PhA and NU muscle markers (Fig. 2A). A correlation was also observed between BIA and NU when body composition estimates reflecting fat status were analyzed, especially between NU-measured leg fat mass, estimated by L-SAT, and BIA-measured body FM. An association between abdominal FM as estimated by NU and BIA-measured FM was also detected (Fig. 2B). Interestingly, there was a highly significant direct correlation between the reference procedure to assess functional status and NU-measured muscle markers, as well as a highly significant inverse correlation between the former and NU-measured leg fat (Fig. 3A). Finally, a medium or high correlation was assessed between HGS and body composition parameters estimated by BIA (Fig. 3B). Discussion To the best of our knowledge this is the first study that has compared the potential validity of NU in the morphofunctional assessment of nutritional status of PwO, against two methods, BIA and HGS, that are well-established for this purpose [25, 26]. Close follow-up of the evolution of body composition of PwO is mandatory for their proper management. Available, easy-to-use tools are required for this purpose. NU-based procedures to assess muscle mass and adipose tissue have been previously used to diagnose nutritional status and metabolic disorders in a variety of clinical conditions such as cancer, infection, hospitalization, non-alcoholic fatty liver disease, chronic obstructive pulmonary disease or hemodyalisis [20-22, 27-31, reviewed in 16]. Our analysis was performed in a real-world cohort of PwO. The results suggest that NU can be a valid technique for assessing the nutritional status of patients with this clinical condition. The size and location of quadriceps RF allows for an easy, time-saving way to perform NU procedures in routine clinical practice. Among NU-measured variables, RF-CSA is essential for clinical application and it has been associated with muscle strength [32]. We observed a relevant, significant association between RF-CSA and BIA estimates of non-fat variables such as BCM, FFM, SMI and ASMM. The noteworthy correlation found between RF-CSA and BCM is of interest since the latter provides information about the number of metabolically active cells in the body, and has been suggested to be a reliable marker of malnutrition [33]. An association between RF-CSA and other BIA-measured variables such as FFM or ASMM in the presence of other clinical conditions has also been reported [20, 22]. On the other hand, according to the previous findings, RF-CSA also showed a high correlation with HGS dynamometry, thus suggesting that the former can also reflect the muscle functionality of PwO. Muscle circumference as well as transverse and longitudinal axis are also highly informative NU-measured variables [16]. In our cohort, they were also directly correlated with muscle-related BIA and HGS parameters. Finally, the close association found between muscle-related BIA variables and HGS dynamometry results, which has been previously reported [34, 35], further validates the methods used to assess body composition in our cohort of PwO. When focusing on the assessment of fat mass body composition markers, we also found a fair correlation between NU-measured L-SAT and FM as estimated by BIA, in accordance with our previous observations in a cohort of patients with colorectal cancer [20]. Therefore, subcutaneous fat of RF also provides reliable information regarding the fat status of PwO. Furthermore, NU is able to provide a more complete picture, since it can distinguish between limb and visceral fat, which has a great impact on health risks [36], while BIA provides an overall, indirect estimation of body fat obtained by applying mathematical modeling [25]. NU measured visceral fat has been previously associated with metabolic syndrome features in PwO [37]. On the other hand, remarkably, L-SAT showed an inverse correlation with HGS measurements. Dynamometry is a powerful predictor of disability, frailty, morbidity and mortality [38]. Thus, the close alignment between HGS and both muscle and fat RF markers reinforces the potential usefulness of NU to assess the nutritional status of PwO. Our study has some limitations. The proportion of male and female patients is not balanced, and the sample size of the cohort precludes a reliable analysis after stratifying by sex. We have not performed repeated measurements to estimate variability. The cross-sectional nature of the study does not allow us to test the validity of the method to monitor changes in body composition subsequent to treatment initiation/change, lifestyle changes, and so on, an issue that will be addressed in ongoing studies. In patients with obesity class III or higher, muscle steatosis may challenge a clear differentiation between lean mass and FM. Finally, although BIA and HGS are accepted methods for assessing nutritional status, DXA is the gold-standard, and a direct comparison between NU and DXA was not performed. In summary, our results suggest that NU may be a valid tool to assess body composition of PwO. Anthropometry and BIA are the most widely used procedures in clinical practice in the obesity setting, and NU contributes a morphologic view of muscle component and fat distribution. Since NU only requires equipment that is easy to handle, affordable and non-space-consuming, it may be available not only in hospitals but also in primary care centers or dietitian offices, thus allowing close follow-up of body composition and metabolic changes in PwO, which will contribute to secure optimal management. Declarations Acknowledgments This work received funding from Novo Nordisk. The funder was not involved in the study design, analysis, interpretation of data, the writing of this article or the decision to submit it for publication. Author Contributions MGO designed research, performed measurements and wrote the paper; LDR, RFJ and CHA performed measurements, performed literature search and reviewed critically the manuscript; JAF and VMJ contributed patients and reviewed critically the mansucript; JMGA designed research and wrote the paper. Disclosure of Conflicts of Interest JMGA, JAF, participation in advisory boards and speaker sessions for Novo Nordisk, Abbott Nutrition, Fresenius Kabi, Persan Farma, Danone, Adventia, Eli Lilly... MGO, LDR, RFJ, CHA, VMJ declare no conflict of interest. Data Availability statement The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. References Andreoli A, Garaci F, Cafarelli FP, Guglielmi G. Body composition in clinical practice. 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Baseline characteristics of the recruited population Variables Patient cohort Overall ( n = 178) Male ( n = 54) Female ( n = 124) P Demographic Age (years) 46.6 (12.5) 45.7 (12.3) 47.0 (12.3) 0.517 Sex (female), n (%) 124 (69.7) n.a. n.a. n.a. Weight (kg) 102.0 (21.1) 119.0 (21.3) 94.7 (16.3) <0.001 Height (cm) 166.2 (9.2) 175.9 (6.6) 162.0 (6.7) <0.001 BMI (kg/m 2 ) 36.7 (6.2) 38.5 (7.5) 35.9 (5.4) 0.028 Waist circumference (cm) 115.7 (14.4) 126.0 (13.0) 111.0 (12.3) <0.001 Hip circumference (cm) 123.0 (11.3) 123.0 (13.0) 123.0 (12.3) 0.879 Obesity stage according to AACE a , n (%) 0.046 b Stage 0 28 (15.7) 4 (7.4) 24 (19.3) 0.046 Stage 1 78 (43.8) 26 (48.1) 52 (41.9) 0.512 Stage 2 72 (40.4) 24 (44.4) 48 (38.7) 0.509 Biochemical Glucose (mg/dL) 97.4 (25.5) 105.1 (36.2) 93.8 (17.8) 0.058 HbA1c (%) 5.61 (0.79) 5.76 (1.15) 5.53 (0.53) 0.223 HOMA-IR, median (IQR) 2.90 (1.88, 4.38) 3.72 (1.87, 6.14) 2.73 (1.86, 4.06) 0.037 Total cholesterol (mg/dL) 186.6 (39.0) 179.7 (38.8) 189.7 (38.8) 0.181 Triglycerides (mg/dL) 111.8 (60.5) 139.3 (81.9) 99.8 (44.0) 0.007 25-hydroxyvitamin D (ng/mL) 22.7 (9.2) 21.4 (7.0) 23.3 (10.1) 0.211 Data are mean ± standard deviation, except where otherwise indicated. The two-tailed unpaired t test was used to compare quantitative variables between male and female patients, with Welch’s correction in the event that variances were significantly different, except in the case of HOMA-IR, for which the two-tailed Mann-Whitney U test was used. The two-tailed Fisher´s exact test was used to compare qualitative variables between male and female patients. a Stage 0: BMI ≥30 kg/m 2 , no obesity-related complications; Stage 1: BMI ≥25 kg/m 2 , presence of one or more mild to moderate obesity-related complications; Stage 2: BMI ≥25 kg/m 2 , presence of one or more severe obesity-related complications [23]. b For this analysis, male and female patients were grouped according to whether they were at Stage 0 vs. at either Stage 1 or Stage 2. AACE, American Association of Clinical Endocrinologists; BMI, body mass index; HbA1c, glycosylated hemoglobin; HOMA-IR, HOMA insulin resistance index; IQR, interquartile range; n.a., not applicable. Table 2. Skeletal muscle function and body composition assessment Variables Cohort Overall ( n = 178) Male ( n = 54) Female ( n = 124) P BC assessment (BIA) PhA ( o ) 6.17 (0.79) 6.40 (0.96) 6.08 (0.70) 0.019 SPA ( o ) 0.33 (0.69) 0.12 (0.68) 0.41 (0.68) 0.016 BCM (kg) 31.9 (8.5) 42.4 (7.8) 27.6 (3.6) <0.001 FFM (kg) 58.6 (13.6) 76.4 (10.3) 51.2 (5.6) <0.001 FFMI (%) 22.1 (14.9) 24.6 (3.5) 21.0 (16.8) 0.153 FM (kg) 43.7 (13.3) 44.2 (15.3) 43.5 (12.4) 0.760 FM (%) 42.5 (7.2) 35.9 (6.5) 45.2 (5.5) <0.001 FMI (%) 16.3 (7.3) 14.3 (5.3) 17.2 (7.9) 0.022 SMI (cm 2 /m 2 ) 9.26 (2.03) 11.50 (1.78) 8.32 (1.21) <0.001 ASMM (kg) 23.8 (6.1) 31.3 (5.0) 20.6 (3.1) <0.001 SMM/kg 25.4 (4.9) 30.2 (4.8) 23.3 (3.3) <0.001 BC assessment (NU) RF-CSA (cm 2 ) 4.94 (1.52) 6.11 (1.70) 4.42 (1.10) <0.001 RF-CIR (cm) 9.10 (1.38) 10.0 (1.41) 8.68 (1.15) <0.001 RF-X axis (cm) 3.68 (0.74) 4.10 (0.91) 3.50 (0.57) <0.001 RF-Y axis (cm) 1.69 (0.36) 1.93 (0.39) 1.59 (0.30) <0.001 L-SAT (cm) 1.81 (0.72) 1.34 (0.79) 2.02 (0.56) <0.001 RF-CSA/kg 4.96 (1.43) 5.31 (1.51) 4.80 (1.36) 0.036 RF-Y axis/kg 1.70 (0.37) 1.66 (0.33) 1.72 (0.39) 0.361 T-SAT (cm) 3.09 (0.96) 2.83 (1.15) 3.20 (0.84) 0.019 S-SAT (cm) 1.59 (0.58) 1.41 (0.58) 1.67 (0.56) 0.007 VAT (cm) 1.12 (0.54) 1.20 (0.65) 1.08 (0.48) 0.188 Functional assessment HGS (kg) 27.1 (11.0) 39.9 (9.3) 20.9 (5.2) <0.001 Body composition was assessed by both BIA and NU, and skeletal muscle function was assessed by HGS. Results are expressed as mean (SD). The two-tailed unpaired t test was used to compare quantitative variables between male and female patients, with Welch’s correction in the event that variances were significantly different. ASMM, appendicular skeletal muscle mass; BC, body composition; BCM, body cell mass; BIA, bioelectrical impedance analysis; CE, creatine excretion; FFM, fat-free mass; FFMI, fat-free mass index; FM, fat mass; FMI, fat mass index; h, hours; HGS, handgrip strength; IQR, interquartile range; L-SAT, leg subcutaneous adipose fat; SD, standard deviation; NU, nutritional ultrasound; PhA, phase angle; RF-CIR, rectus femoris quadriceps circumference; RF-CSA, rectus femoris cross-sectional area; Rz, resistance; SMI, skeletal muscle index; SMM, skeletal muscle mass; SPA, standardized phase angle; S-SAT, superficial abdominal subcutaneous adipose fat; T-SAT, total abdominal subcutaneous adipose fat; Xc, reactance; VAT, visceral adipose tissue. Additional Declarations Competing interest reported. JMGA, JAF, participation in advisory boards and speaker sessions for Novo Nordisk, Abbott Nutrition, Fresenius Kabi, Persan Farma, Danone, Adventia, Eli Lilly... MGO, LDR, RFJ, CHA, VMJ declare no conflict of interest. Supplementary Files graphicalabstractoriginal.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3999407","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":280451253,"identity":"e06a79e7-1f4f-4cf9-94d1-5a2ed6a7f6c7","order_by":0,"name":"GARCIA OLIVARES MARIA","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCElEQVRIiWNgGAWjYFADZiD+UGEDJBkbDxCthXHGmTSQlgYitYB08bYcBjPwatFt730mwfDLLp+/nfkBM2/Debu17YeBttTYROPSYnbmuJkEY1+y5YzDbAaMc3fcTt52JhGo5VhabgMuLTfS2CQYe5gNDJgZDBjenrmdbHYAqIWx4TBuLfefgbTUA7Wwf2DgbTuXbHb+IQEtN9jYJBh+HAZq4TFg5G07YGd2g5AtZ9KYLRIbjhtIHOYpODjjTHKC2Q2gLQn4/HL8GOOND3+qDfj7j2988KHCzt7sfPrDBx9qbHBqAQIWicQ2COsAECeCVSbgVg4CzB8Y/iB49vgVj4JRMApGwUgEAEWMYmk/3lu3AAAAAElFTkSuQmCC","orcid":"","institution":"Hospital QuironSalud Malaga / Hospital Regional Universitario Malaga","correspondingAuthor":true,"prefix":"","firstName":"GARCIA","middleName":"OLIVARES","lastName":"MARIA","suffix":""},{"id":280451255,"identity":"41de39a1-4cd7-43b0-a4ad-d2ee4d2b03dd","order_by":1,"name":"DALLA ROVERE LARA","email":"","orcid":"","institution":"Hospital Quironsalud Malaga","correspondingAuthor":false,"prefix":"","firstName":"DALLA","middleName":"ROVERE","lastName":"LARA","suffix":""},{"id":280451259,"identity":"4fc23e59-6ca8-4c8f-8281-695111e8d755","order_by":2,"name":"FERNANDEZ JIMENEZ ROCIO","email":"","orcid":"","institution":"Hospital Quironsalud Malaga / Hospital Virgen de la Victoria","correspondingAuthor":false,"prefix":"","firstName":"FERNANDEZ","middleName":"JIMENEZ","lastName":"ROCIO","suffix":""},{"id":280451260,"identity":"92612644-5aca-490f-a592-895a87fd695a","order_by":3,"name":"HARDY AÑON CARMEN","email":"","orcid":"","institution":"Hospital Quironsalud Malaga","correspondingAuthor":false,"prefix":"","firstName":"HARDY","middleName":"AÑON","lastName":"CARMEN","suffix":""},{"id":280451265,"identity":"20802246-030c-45dd-8184-d34e6677dd72","order_by":4,"name":"ABUIN FERNANDEZ JOSE","email":"","orcid":"","institution":"Hospital Quironsalud Malaga","correspondingAuthor":false,"prefix":"","firstName":"ABUIN","middleName":"FERNANDEZ","lastName":"JOSE","suffix":""},{"id":280451269,"identity":"7dffaa21-4e73-4a31-bf92-fea93dc6b49a","order_by":5,"name":"MORILLAS JIMENEZ VIRGINIA","email":"","orcid":"","institution":"Hospital QuironSalud Malaga / Hospital Regional Universitario Malaga","correspondingAuthor":false,"prefix":"","firstName":"MORILLAS","middleName":"JIMENEZ","lastName":"VIRGINIA","suffix":""},{"id":280451272,"identity":"0daa197e-e2fe-4483-9d5e-1208eb604c8c","order_by":6,"name":"GARCIA ALMEIDA JOSE MANUEL","email":"","orcid":"","institution":"Hospital Quironsalud Malaga / Hospital Virgen de la Victoria","correspondingAuthor":false,"prefix":"","firstName":"GARCIA","middleName":"ALMEIDA JOSE","lastName":"MANUEL","suffix":""}],"badges":[],"createdAt":"2024-02-29 10:48:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3999407/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3999407/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53015718,"identity":"2ea94e39-d699-4c53-b34a-931e50c0eb55","added_by":"auto","created_at":"2024-03-19 15:59:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":238394,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIdentification of nutritional status variables by nutritional ultrasound\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNutritional ultrasound of RF muscle and abdominal adipose tissue. \u003cstrong\u003ePanel A\u003c/strong\u003e (RF muscle): A, L-SAT; B, RF-X-axis; C, RF-Y-axis; D, RF-CSA and RF-CIR. \u003cstrong\u003ePanel B\u003c/strong\u003e (abdominal adipose tissue): 1, T-SAT; 2, S-SAT; 3, VAT or preperitoneal adipose tissue.\u003c/p\u003e\n\u003cp\u003eCIR, circumference; CSA, cross-sectional-area; L-SAT, leg subcutaneous fat; RF, rectus femoris; S-SAT, superficial subcutaneous adipose fat; T-SAT, total subcutaneous adipose fat; VAT, visceral adipose tissue or preperitoneal tissue.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3999407/v1/1f715f396db05751a9045374.png"},{"id":53014047,"identity":"18c19533-ec42-4fed-877c-fd2d9a51d8a1","added_by":"auto","created_at":"2024-03-19 15:51:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":78315,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation matrix of the morphofunctional parameters in the PwO cohort: NU \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003evs.\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e BIA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e*\u003cem\u003eP\u003c/em\u003e \u0026lt;0.05; **\u003cem\u003eP\u003c/em\u003e \u0026lt;0.01; ***\u003cem\u003eP\u003c/em\u003e \u0026lt;0.001.\u003c/p\u003e\n\u003cp\u003eThe one-tailed Pearson correlation test was used.\u003c/p\u003e\n\u003cp\u003eASMM, appendicular skeletal muscle mass; BCM, body cell mass; BIA, bioelectrical impedance analysis; CE, creatine excretion; FFM, fat-free mass; FM, fat mass; h, hours; L-SAT, leg subcutaneous adipose fat; NU, nutritional ultrasound; PhA, phase angle; PwO, patients with obesity; RF-CIR, rectus femoris quadriceps circumference; RF-CSA, rectus femoris cross-sectional area; SMM, skeletal muscle mass; S-SAT, superficial abdominal subcutaneous adipose fat; T-SAT, total abdominal subcutaneous adipose fat; VAT, visceral adipose tissue.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3999407/v1/2b0b37cb63af2a2b0d076786.png"},{"id":53014046,"identity":"88d83783-1947-4e1b-bc96-d4c2662ec421","added_by":"auto","created_at":"2024-03-19 15:51:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":68768,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation matrix of the morphofunctional parameters in the PwO cohort: NU and BIA \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003evs.\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e HGS.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e*\u003cem\u003eP\u003c/em\u003e \u0026lt;0.05; **\u003cem\u003eP\u003c/em\u003e \u0026lt;0.01; ***\u003cem\u003eP\u003c/em\u003e \u0026lt;0.001.\u003c/p\u003e\n\u003cp\u003eThe one-tailed Pearson correlation test was used.\u003c/p\u003e\n\u003cp\u003eASMM, appendicular skeletal muscle mass; BCM, body cell mass; BIA, bioelectrical impedance analysis; CE, creatine excretion; FFM, fat-free mass; FM, fat mass; h, hours; HGS, handgrip strength; L-SAT, leg subcutaneous adipose fat; NU, nutritional ultrasound; PhA, phase angle; PwO, patients with obesity; RF-CIR, rectus femoris quadriceps circumference; RF-CSA, rectus femoris cross-sectional area; SMM, skeletal muscle mass; S-SAT, superficial abdominal subcutaneous adipose fat; T-SAT, total abdominal subcutaneous adipose fat; VAT, visceral adipose tissue.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3999407/v1/2d5356a98e1960c5989c3f67.png"},{"id":65235529,"identity":"3bb25f28-d868-4b5e-bb63-fea8aa1206d5","added_by":"auto","created_at":"2024-09-25 05:33:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":954199,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3999407/v1/d851a20b-a4cd-4bf4-96ee-01c36589781f.pdf"},{"id":53014049,"identity":"3ada8c48-25c1-43e3-af9e-3c2ff5f2a8d0","added_by":"auto","created_at":"2024-03-19 15:51:07","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":489682,"visible":true,"origin":"","legend":"","description":"","filename":"graphicalabstractoriginal.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3999407/v1/793ad280b9f16c16c66067b0.pdf"}],"financialInterests":"Competing interest reported. JMGA, JAF, participation in advisory boards and speaker sessions for Novo Nordisk, Abbott Nutrition, Fresenius Kabi, Persan Farma, Danone, Adventia, Eli Lilly... MGO, LDR, RFJ, CHA, VMJ declare no conflict of interest.","formattedTitle":"\u003cp\u003ePotential Usefulness of Nutritional Ultrasound for Morphofunctional Assessment in Patients With Obesity\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eObesity is a pathological condition. When not managed correctly, it may predispose patients to an increased risk of cardiorenal, metabolic and other complications, thus compromising their life expectancy and quality of life (QoL). Morphofunctional assessment of nutritional status and body composition is required to determine the appropriate treatment for patients with obesity (PwO) [1].\u0026nbsp;Body mass index (BMI), although enlightening, does not provide information regarding either body composition or visceral adiposity, thus increasing the risk of misleading diagnoses and favoring the so-called obesity or BMI paradox\u0026nbsp;[2]. Dual-energy X-ray absorptiometry (DXA) is considered to be the reference method for evaluating body composition indicators such as fat mass (FM), fat free mass (FFM) or bone mineral content (BMC) [3,\u0026nbsp;4]. However, it has important limitations, namely expense, specific training requirement and radiation exposure, which preclude widespread use [5]. For this reason, other procedures have been applied and validated to assess body composition and muscle function, namely bioelectrical impedance analysis (BIA) and hand grip strength dynamometry (HGS). BIA is based on the different impedance for an electric current presented by the body\u0026rsquo;s water and cell mass, which allows the calculation of fat mass (FM) and fat free mass (FFM) [6]. BIA is not as expensive as DXA, and does not require specific training. BIA has shown good consistency for FM and FFM assessment in healthy subjects and PwO [7-9], although the results are\u0026nbsp;influenced by the hydration level of the patient and measurements of body composition are indirect, which requires the use of prediction equations\u0026nbsp;[10]. Handgrip strength dynamometry (HGS) is a reliable indicator of muscle condition and muscle functionality. HGS has been found to be associated with body composition parameters [11], and the procedure has been used to assess the risk of disease-related malnutrition [12], metabolic syndrome [13], abdominal obesity [14], and sarcopenic obesity (SO) [15].\u003c/p\u003e\n\u003cp\u003eNutritional ultrasound (NU) evaluates body compartments such as muscle, adipose, connective, vascular and bone tissue, to assess ultrasound-based body composition. This procedure is emerging as a cheap, portable, non-invasive, widely available and easy-to-use procedure for morphofunctional assessment [16]. NU consists of two dimensions to assess FFM (muscle) and FM (adipose tissue). Many NU procedures involve the anterior rectum area of the quadriceps, the so called rectus femoris (RF). Its composition changes in malnutrition states are well defined [15,\u0026nbsp;16]. Thus, RF-cross-sectional-area (RF-CSA) and RF-Y-axis values have been shown to be reliable indicators of strength and functional performance [17-19].\u0026nbsp;NU also yields valuable information regarding subcutaneous fat in the leg (L-SAT), as well as abdominal fat, either subcutaneous or visceral (VAT) [20]. We have previously demonstrated the potential usefulness of NU\u003csup\u003e\u0026nbsp;\u003c/sup\u003eto predict malnutrition-related mortality in cancer patients [21], and sarcopenia in post-critical COVID-19 and colorectal cancer patients [20, 22]. Our present aim was to test the suitability of NU in the morphofunctional assessment of PwO and metabolic diseases. For this purpose, the morphofunctional analysis of RF as a surrogate for body composition was performed by NU in a cohort of PwO. For validation purposes, NU diagnoses were compared with those obtained by BIA and HGS.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy design\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConsecutive patients attending the Obesity Unit at Quir\u0026oacute;nsalud Hospital of M\u0026aacute;laga, Spain, between November 2021 and November 2022, either for the first time or for routine review, who had a diagnosis of obesity, with or without DM2, were recruited for a cross sectional study. This consisted of assessing the morphofunctional status of patients by using functional procedures to measure muscle quality (HGS), as well as by applying BIA and NU-based procedures to determine body composition. The ultimate aim was to explore the suitability of NU to analyze the nutritional status of PwO. Patients also underwent extensive clinical examination and laboratory testing, and their obesity status was determined according to the American Association of Clinical Endocrinologists (AACE) guidelines [23].\u003c/p\u003e\n\u003cp\u003eInclusion criteria were age \u0026ge;18 years old (y.o.) and either BMI \u0026ge;30 kg/m\u003csup\u003e2\u003c/sup\u003e or BMI \u0026ge;27 kg/m\u003csup\u003e2\u003c/sup\u003e and at least one comorbidity associated with body weight (prediabetes or type 2 diabetes, hypertension, dyslipidemia, obstructive sleep apnea, cardiovascular disease).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData anonymization was guaranteed. All patients gave informed consent. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki and started once the Provincial Research Ethic Committee (CEI) of M\u0026aacute;laga had approved the study protocol. Study code was 1168-N-23.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMorphofunctional assessment\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNutritional Status and body composition\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBIA\u003c/p\u003e\n\u003cp\u003eThe bioimpedance measurements were performed using a phase-sensitive single-frequency analyzer (Nutrilab, Akern\u003csup\u003e\u0026reg;\u003c/sup\u003e Srl, Pontassieve, Italy), as previously described [21]. In brief, the device applies an alternating sinusoidal electric current of 400 \u0026micro;A at 50 kHz [\u0026plusmn;0.1%; resolution Rz: \u0026plusmn;1%, Xc: \u0026plusmn;1%, coefficients of variation \u0026lt;2%]. Standard whole-body tetrapolar measurements were performed, with the patient in a supine position with a leg opening of 45\u0026deg; compared to the median line of the body, and the upper limbs 30\u0026deg; away from the trunk. One Ag/AgCl very low-impedance electrode was placed on the back of the right hand and another electrode on the corresponding foot, each one of them including a sensor and injector area separated by 5 cm (BIVAtrodes, Akern\u003csup\u003e\u0026reg;\u003c/sup\u003e Srl). The patient was advised to abstain from food and drink for \u0026gt;2 h before the test to warrant proper fluid distribution. Resistance (R, Ω), reactance (Xc, Ω), phase angle (PhA, \u0026deg;), standardized phase angle (SPA, \u0026deg;) were determined, and bioelectric parameters to estimate the body composition, such as FM (kg and %), FFM (kg), body cell mass (BCM, kg), SMM (kg) and appendicular SMM (ASMM, kg), were assessed.\u003c/p\u003e\n\u003cp\u003eNU\u003c/p\u003e\n\u003cp\u003eA comprehensive NU study was performed, as previously described [22],\u0026nbsp;to take advantage of the two dimensions of the procedure which allow the assessment of FFM and FM in RF, as well as of abdominal FM [16,\u0026nbsp;20-22].\u0026nbsp;A Mindray\u003csup\u003e\u0026Ograve;\u003c/sup\u003e Z60 ultrasound analyzer was used with frequency range of 10 to 12 MHz (Mindray, Madrid, Spain). The patient was relaxed in a supine position, lying with the knee fully extended. RF muscle ultrasound scans were taken in its lower third. RF-CSA, circumference of the quadriceps RF (RF-CIR), RF-X-axis and RF-Y-axis, i.e., the linear measurement of the distance between the muscular limits of the RF (lateral and anteroposterior), as well as L-SAT [24],\u0026nbsp;were determined. Scans corresponding to abdominal adipose tissue ultrasound were also taken at the midpoint between the xiphoid appendix and the navel on the midline [total subcutaneous abdominal fat (T-SAT), superficial subcutaneous abdominal fat (S-SAT), preperitoneal or visceral fat (VAT)]. In order to minimize intraobserver variability, a trained healthcare technician performed three repeats for each measurement. The average value was subsequently calculated. Furthermore, a second trained examiner always monitored the procedures performed by the examiner. \u0026nbsp; \u0026nbsp;Fig.\u0026nbsp;1 shows two NU images corresponding to RF and abdominal adipose tissue. The aforementioned variables are properly identified and indicated. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunctional outcome\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eHGS was determined by using the JAMAR-Dynamometer (J. A. Preston Corporation, New York, NY, USA). Patients were sitting with the shoulder adducted and the elbow flexed at 90\u0026ordm; with the forearm and wrist of the dominant arm in a neutral position. Three measurements were obtained, and the average value was considered as the final result.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStatistical analyses\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor descriptive purposes, the mean [standard deviation (SD)] was used for quantitative, normally distributed variables. The two-tailed unpaired t test, with Welch\u0026rsquo;s correction in the event that variances were significantly different, was used to compare quantitative variables between female and male patients. The Fisher\u0026acute;s exact test was used to compare qualitative variables. In order to compare the suitability of the different procedures to assess the morphofunctional status of PwO, the one-tailed Pearson test was used to analyze correlations between functional/body composition variables determined by BIA, NU or HGS. Statistical significance was set at \u003cem\u003eP\u003c/em\u003e \u0026lt;0.05. All calculations were performed using JAMOVI, version 2.3.22 (Sydney, Australia).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBaseline features\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo hundred patients attended the Obesity Unit during the scheduled study period. Fifteen of them had not the complete assessment with BIA, HGS and NU. Seven additional patients whose data were outliers not representing natural variations in the population but measurement, processing or data entry errors, were also excluded. Thus, 178 patients, 69.7% of whom were female, were finally recruited for morphofunctional assessment\u0026nbsp;(Table 1).\u0026nbsp;Male weight, BMI and waist circumference were significantly higher in male patients (average weight was 24 kg higher, and BMI and waist circumference were 2.6 kg/m\u003csup\u003e2\u003c/sup\u003e and 15 cm higher, respectively). HbA1c values were close to the lower limit of the range of prediabetes. Accordingly, fasting circulating glucose levels were also close to the upper range of normality, and the HOMA insulin resistance index (HOMA-IR) was elevated, being higher in males.\u0026nbsp;More than 80% of patients presented with at least one obesity-related complication. Total cholesterol and trigycerides were within normal range, which was partly explained by the widespread use of statins (not shown). Male patients had a significantly higher BMI and waist circumference than female ones.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMorphofunctional assessment\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMorphofunctional assessment measurements using BIA, NU and HGS are shown in Table\u0026nbsp;2.\u0026nbsp;Significant differences between female and male patients were observed independently of the methods used to assess body composition and muscle strength. Higher values in muscle composition and muscle functionality variables were observed in men and, conversely, the proportion of abdominal and limb \u0026nbsp;adipose tissue was higher in women. Accordingly, there were significant differences in BCM between men and women.\u003c/p\u003e\n\u003cp\u003eMore interestingly, there was a fair correlation between the different methods used to analyze body composition, as well as between these and functional assessment by HGS (Figs. 2 and 3). A highly significant correlation was observed between BIA functional and muscle markers such as BCM, FFM or ASMM, and the NU parameter that best represents strength and functional performance, namely RF-CSA. The association between the rest of the BIA and NU functional and muscle measurements was always significant or highly significant. A low, still significant correlation was observed between BIA PhA and NU muscle markers (Fig. 2A). A correlation was also observed between BIA and NU when body composition estimates reflecting fat status were analyzed, especially between NU-measured leg fat mass, estimated by L-SAT, and BIA-measured body FM. An association between abdominal FM as estimated by NU and BIA-measured FM was also detected (Fig. 2B). Interestingly, there was a highly significant direct correlation between the reference procedure to assess functional status and NU-measured muscle markers, as well as a highly significant inverse correlation between the former and NU-measured leg fat (Fig. 3A). Finally, a medium or high correlation was assessed between HGS and body composition parameters estimated by BIA (Fig. 3B).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo the best of our knowledge this is the first study that has compared the potential\u0026nbsp;validity of NU in the morphofunctional assessment of nutritional status of PwO, against two methods, BIA and HGS, that are well-established for this purpose\u0026nbsp;[25,\u0026nbsp;26]. Close follow-up of the evolution of body composition of PwO is mandatory for their proper management. Available, easy-to-use tools are required for this purpose. NU-based procedures to assess muscle mass and adipose tissue have been previously used to diagnose nutritional status and metabolic disorders in a variety of clinical conditions such as cancer, infection, hospitalization, non-alcoholic fatty liver disease, chronic obstructive pulmonary disease or hemodyalisis\u0026nbsp;[20-22,\u0026nbsp;27-31,\u0026nbsp;reviewed in 16]. Our analysis was performed in a real-world cohort of PwO. The results suggest that NU\u003csup\u003e\u0026nbsp;\u003c/sup\u003ecan be a valid technique for assessing the nutritional status of patients with this clinical condition.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe size and location of quadriceps RF allows for an easy, time-saving way to perform NU procedures in routine clinical practice. Among NU-measured variables, RF-CSA is essential for clinical application and it has been associated with muscle strength\u0026nbsp;[32].\u0026nbsp;We observed a relevant, significant association between RF-CSA and BIA estimates of non-fat variables such as BCM, FFM, SMI and ASMM. The noteworthy correlation found between RF-CSA and BCM is of interest since the latter provides information about the number of metabolically active cells in the body, and has been suggested to be a reliable marker of malnutrition\u0026nbsp;[33]. An association between RF-CSA and other BIA-measured variables such as FFM or ASMM in the presence of other clinical conditions has also been reported\u0026nbsp;[20,\u0026nbsp;22].\u0026nbsp;On the other hand, according to the previous findings, RF-CSA also showed a high correlation with HGS dynamometry, thus suggesting that the former can also reflect the muscle functionality of PwO. Muscle circumference as well as transverse and longitudinal axis are also highly informative NU-measured variables\u0026nbsp;[16]. In our cohort, they were also directly correlated with muscle-related BIA and HGS parameters. Finally, the close association found between muscle-related BIA variables and HGS dynamometry results, which has been previously reported\u0026nbsp;[34,\u0026nbsp;35], further validates the methods used to assess body composition in our cohort of PwO. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhen focusing on the assessment of fat mass body composition markers, we also found a fair correlation between NU-measured L-SAT and FM as estimated by BIA, in accordance with our previous observations in a cohort of patients with colorectal cancer\u0026nbsp;[20]. Therefore, subcutaneous fat of RF also provides reliable information regarding the fat status of PwO. Furthermore, NU is able to provide a more complete picture, since it can distinguish between limb and visceral fat, which has a great impact on health risks\u0026nbsp;[36], while BIA provides an overall, indirect estimation of body fat obtained by applying mathematical modeling\u0026nbsp;[25]. NU measured visceral fat has been previously associated with metabolic syndrome features in PwO\u0026nbsp;[37]. On the other hand, remarkably, L-SAT showed an inverse correlation with HGS measurements. Dynamometry is a powerful predictor of disability, frailty, morbidity and mortality\u0026nbsp;[38]. Thus, the close alignment between HGS and both muscle and fat RF markers reinforces the potential\u0026nbsp;usefulness of NU to assess the nutritional status of PwO.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur study has some limitations. The proportion of male and female patients is not balanced, and the sample size of the cohort precludes a reliable analysis after stratifying by sex. We have not performed repeated measurements to estimate variability. The cross-sectional nature of the study does not allow us to test the validity of the method to monitor changes in body composition subsequent to treatment initiation/change, lifestyle changes, and so on, an issue that will be addressed in ongoing studies. In patients with obesity class III or higher, muscle steatosis may challenge a clear differentiation between lean mass and FM.\u0026nbsp;Finally, although BIA and HGS are accepted methods for assessing nutritional status, DXA is the gold-standard, and a direct comparison between NU and DXA was not performed. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn summary, our results suggest that NU may be a valid tool to assess body composition of PwO. Anthropometry and BIA are the most widely used procedures in clinical practice in the obesity setting, and NU contributes a morphologic view of muscle component and fat distribution. Since NU only requires equipment that is easy to handle, affordable and non-space-consuming, it may be available not only in hospitals but also in primary care centers or dietitian offices, thus allowing close follow-up of body composition and metabolic changes in PwO, which will contribute to secure optimal management.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work received funding from Novo Nordisk. The funder was not involved in the study design, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMGO designed research, performed measurements and wrote the paper; LDR, RFJ and CHA performed measurements, performed literature search and reviewed critically the manuscript; JAF and VMJ contributed patients and reviewed critically the mansucript; JMGA designed research and wrote the paper.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure of Conflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJMGA, JAF, participation in advisory boards and speaker sessions for Novo Nordisk, Abbott Nutrition, Fresenius Kabi, Persan Farma, Danone, Adventia, Eli Lilly... MGO, LDR, RFJ, CHA, VMJ declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAndreoli A, Garaci F, Cafarelli FP, Guglielmi G. Body composition in clinical practice. Eur J Radiol. 2016;85:1461-8. \u003c/li\u003e\n\u003cli\u003eDram\u0026eacute; M, Godaert L. The Obesity Paradox and Mortality in Older Adults: A Systematic Review. Nutrients. 2023;15:1780. \u003c/li\u003e\n\u003cli\u003eBuckinx F, Landi F, Cesari M, Fielding RA, Visser M, Engelke K, et al. Pitfalls in the measurement of muscle mass: a need for a reference standard. 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Endocrinol Diabetes Nutr (Engl Ed). 2023;70 Suppl 1:74-84. \u003c/li\u003e\n\u003cli\u003eBerger J, Bunout D, Barrera G, de la Maza MP, Henriquez S, Leiva L, et al. Rectus Femoris (RF) Ultrasound for the Assessment of Muscle Mass in Older People. Arch Gerontol Geriatr. 2015;61:33-8. \u003c/li\u003e\n\u003cli\u003eRustani K, Kundisova L, Leopoldo P, Nante N, Bicchi M. Ultrasound Measurement of Rectus Femoris Muscle Thickness as a Quick Screening Test for Sarcopenia Assessment. Arch Gerontol Geriatr. 2019;83:151-4. \u003c/li\u003e\n\u003cli\u003eMueller N, Murthy S, Tainter CR, Lee J, Riddell K, Fintelmann FJ, et al. Can Sarcopenia Quantified by Ultrasound of the Rectus Femoris Muscle Predict Adverse Outcome of Surgical Intensive Care Unit Patients and Frailty? A Prospective, Observational Cohort Study. Ann Surg. 2017;264:1116-24.\u003c/li\u003e\n\u003cli\u003eVegas-Aguilar IM, Guirado-Pel\u0026aacute;ez P, Fern\u0026aacute;ndez-Jim\u0026eacute;nez R, Boughanem H, Tinahones FJ, Garcia-Almeida JM. Exploratory Assessment of Nutritional Evaluation Tools as Predictors of Complications and Sarcopenia in Patients with Colorectal Cancer. Cancers (Basel). 2023;15:847.\u003c/li\u003e\n\u003cli\u003eGarc\u0026iacute;a-Garc\u0026iacute;a C, Vegas-Aguilar IM, Rioja-V\u0026aacute;zquez R, Cornejo-Pareja I, Tinahones FJ, Garc\u0026iacute;a-Almeida JM. Rectus Femoris Muscle and Phase Angle as Prognostic Factor for 12-Month Mortality in a Longitudinal Cohort of Patients with Cancer (AnyVida Trial). Nutrients. 2023;15:522.\u003c/li\u003e\n\u003cli\u003eCornejo-Pareja I, Soler-Beunza AG, Vegas-Aguilar IM, Fern\u0026aacute;ndez-Jim\u0026eacute;nez R, Tinahones FJ, Garc\u0026iacute;a-Almeida JM. Predictors of Sarcopenia in Outpatients with Post-Critical SARS-CoV2 Disease. Nutritional Ultrasound of Rectus Femoris Muscle, a Potential Tool. Nutrients. 2022;14:4988. \u003c/li\u003e\n\u003cli\u003eGarvey WT, Garber AJ, Mechanick JI, Bray GA, Dagogo-Jack S, Einhorn D, et al; The Aace Obesity Scientific Committee. American Association of Clinical Endocrinologists and American College of Endocrinology position statement on the 2014 advanced framework for a new diagnosis of obesity as a chronic disease. Endocr Pract. 2014;20:977-89.\u003c/li\u003e\n\u003cli\u003eHern\u0026aacute;ndez-Socorro CR, Saavedra P, L\u0026oacute;pez-Fern\u0026aacute;ndez JC, Ruiz-Santana S. Assessment of Muscle Wasting in Long-Stay ICU Patients Using a New Ultrasound Protocol. Nutrients. 2018;10:1849.\u003c/li\u003e\n\u003cli\u003eLukaski HC. Requirements for clinical use of bioelectrical impedance analysis (BIA). Ann N Y Acad Sci. 1999;873:72-6.\u003c/li\u003e\n\u003cli\u003eNorman K, Stob\u0026auml;us N, Gonzalez MC, Schulzke JD, Pirlich M. Hand grip strength: outcome predictor and marker of nutritional status. Clin Nutr. 2011;30:135-42. \u003c/li\u003e\n\u003cli\u003eVitturi N, Soattin M, De Stefano F, Vianello D, Zambon A, Plebani M, et al. Ultrasound, anthropometry and bioimpedance: a comparison in predicting fat deposition in non-alcoholic fatty liver disease. Eat Weight Disord. 2015;20:241-7.\u003c/li\u003e\n\u003cli\u003eNijholt W, Beek LT, Hobbelen JSM, van der Vaart H, Wempe JB, van der Schans CP, et al. The added value of ultrasound muscle measurements in patients with COPD: An exploratory study. Clin Nutr ESPEN. 2019;30:152-8.\u003c/li\u003e\n\u003cli\u003eOzturk Y, Deniz O, Coteli S, Unsal P, Dikmeer A, Burkuk S, et al. Global Leadership Initiative on Malnutrition criteria with different muscle assessments including muscle ultrasound with hospitalized internal medicine patients. JPEN J Parenter Enteral Nutr. 2022;46:936-45.\u003c/li\u003e\n\u003cli\u003eSanz-Paris A, Gonz\u0026aacute;lez-Fernandez M, Hueso-Del R\u0026iacute;o LE, Ferrer-Lahuerta E, Monge-Vazquez A, Losfablos-Callau F, et al. Muscle Thickness and Echogenicity Measured by Ultrasound Could Detect Local Sarcopenia and Malnutrition in Older Patients Hospitalized for Hip Fracture. Nutrients. 2021;13:2401.\u003c/li\u003e\n\u003cli\u003eSahathevan S, Khor BH, Singh BKS, Sabatino A, Fiaccadori E, Daud ZAM, et al. Association of Ultrasound-Derived Metrics of the Quadriceps Muscle with Protein Energy Wasting in Hemodialysis Patients: A Multicenter Cross-Sectional Study. Nutrients. 2020;12:3597. \u003c/li\u003e\n\u003cli\u003eSeymour JM, Ward K, Sidhu PS, Puthucheary Z, Steier J, Jolley CJ, et al. Ultrasound measurement of rectus femoris cross-sectional area and the relationship with quadriceps strength in COPD. Thorax. 2009;64:418-23.\u003c/li\u003e\n\u003cli\u003eMoonen HPFX, Van Zanten ARH. Bioelectric impedance analysis for body composition measurement and other potential clinical applications in critical illness. Curr Opin Crit Care. 2021;27:344-53.\u003c/li\u003e\n\u003cli\u003eSacco AM, Valerio G, Alicante P, Di Gregorio A, Spera R, Ballarin G, et al. Raw bioelectrical impedance analysis variables (phase angle and impedance ratio) are significant predictors of hand grip strength in adolescents and young adults. Nutrition. 2021;91-92:111445.\u003c/li\u003e\n\u003cli\u003eMartins PC, de Lima LRA, Berria J, Petroski EL, da Silva AM, Silva DAS. Association between phase angle and isolated and grouped physical fitness indicators in adolescents. Physiol Behav. 2020;217:112825.\u003c/li\u003e\n\u003cli\u003eDespres JP, Lemieux I. Abdominal obesity and metabolic syndrome. Nature. 2006;444(7121):881-7. \u003c/li\u003e\n\u003cli\u003eCuatrecasas G, de Cabo F, Coves MJ, Patrascioiu I, Aguilar G, March S, et al. Ultrasound measures of abdominal fat layers correlate with metabolic syndrome features in patients with obesity. Obes Sci Pract. 2020;6:660-7.\u003c/li\u003e\n\u003cli\u003eS\u0026aacute;nchez-Torralvo FJ, Gonz\u0026aacute;lez-Poveda I, Garc\u0026iacute;a-Olivares M, Porras N, Gonzalo-Mar\u0026iacute;n M, Tapia MJ, et al. Poor Physical Performance Is Associated with Postoperative Complications and Mortality in Preoperative Patients with Colorectal Cancer. Nutrients. 2022;14:1484. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e\u003cstrong\u003e. Baseline characteristics of the recruited population\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"656\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.457317073170735%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatient cohort\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003cem\u003en\u003c/em\u003e = 178)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003cem\u003en\u003c/em\u003e = 54)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003cem\u003en\u003c/em\u003e = 124)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003eDemographic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Age (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e46.6 (12.5)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003e45.7 (12.3)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003e47.0 (12.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e0.517 \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Sex (female), n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e124 (69.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003en.a.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003en.a.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003en.a.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Weight (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e102.0 (21.1)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003e119.0 (21.3)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003e94.7 (16.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Height (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e166.2 (9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003e175.9 (6.6)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003e162.0 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;BMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e36.7 (6.2)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003e38.5 (7.5)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003e35.9 (5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Waist circumference (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e115.7 (14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003e126.0 (13.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003e111.0 (12.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Hip circumference (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e123.0 (11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003e123.0 (13.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003e123.0 (12.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e0.879\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Obesity stage according to AACE\u003csup\u003ea\u003c/sup\u003e, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e0.046\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Stage 0 \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e28 (15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003e4 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003e24 (19.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Stage 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e78 (43.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003e26 (48.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003e52 (41.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e0.512\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Stage 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e72 (40.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003e24 (44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003e48 (38.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e0.509\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003eBiochemical\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Glucose (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e97.4 (25.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003e105.1 (36.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003e93.8 (17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;HbA1c (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e5.61 (0.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003e5.76 (1.15)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003e5.53 (0.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e0.223\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;HOMA-IR, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e2.90 (1.88, 4.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003e3.72 (1.87, 6.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003e2.73 (1.86, 4.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Total cholesterol (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e186.6 (39.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003e179.7 (38.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003e189.7 (38.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e0.181\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Triglycerides (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e111.8 (60.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003e139.3 (81.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003e99.8 (44.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.78658536585366%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;25-hydroxyvitamin D (ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.00609756097561%\"\u003e\n \u003cp\u003e22.7 (9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597560975609756%\"\u003e\n \u003cp\u003e21.4 (7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\"\u003e\n \u003cp\u003e23.3 (10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.75609756097561%\"\u003e\n \u003cp\u003e0.211\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eData are mean \u0026plusmn; standard deviation, except where otherwise indicated. The two-tailed unpaired t test was used to compare quantitative variables between male and female patients, with Welch\u0026rsquo;s correction in the event that variances were significantly different, except in the case of HOMA-IR, for which the two-tailed Mann-Whitney U test was used. The two-tailed Fisher\u0026acute;s exact test was used to compare qualitative variables between male and female patients. \u003csup\u003ea\u003c/sup\u003eStage 0: BMI \u0026ge;30 kg/m\u003csup\u003e2\u003c/sup\u003e, no obesity-related complications; Stage 1: BMI \u0026ge;25 kg/m\u003csup\u003e2\u003c/sup\u003e, presence of one or more mild to moderate obesity-related complications; Stage 2: BMI \u0026ge;25 kg/m\u003csup\u003e2\u003c/sup\u003e, presence of one or more severe obesity-related complications [23]. \u003csup\u003eb\u003c/sup\u003eFor this analysis, male and female patients were grouped according to whether they were at Stage 0 \u003cem\u003evs.\u003c/em\u003e at either Stage 1 or Stage 2.\u003c/p\u003e\n\u003cp\u003eAACE, American Association of Clinical Endocrinologists; BMI, body mass index; HbA1c, glycosylated hemoglobin; HOMA-IR, HOMA insulin resistance index; IQR, interquartile range; n.a., not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Skeletal muscle function and body composition assessment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"548\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCohort\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003cem\u003en\u003c/em\u003e = 178)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003cem\u003en\u003c/em\u003e = 54)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003cem\u003en\u003c/em\u003e = 124)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003eBC assessment (BIA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;PhA (\u003csup\u003eo\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e6.17 (0.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e6.40 (0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e6.08 (0.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;SPA (\u003csup\u003eo\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e0.33 (0.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e0.12 (0.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e0.41 (0.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;BCM (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e31.9 (8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e42.4 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e27.6 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;FFM (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e58.6 (13.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e76.4 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e51.2 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;FFMI (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e22.1 (14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e24.6 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e21.0 (16.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e0.153\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;FM (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e43.7 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e44.2 (15.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e43.5 (12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e0.760\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;FM (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e42.5 (7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e35.9 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e45.2 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;FMI (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e16.3 (7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e14.3 (5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e17.2 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;SMI (cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e9.26 (2.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e11.50 (1.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e8.32 (1.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;ASMM (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e23.8 (6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e31.3 (5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e20.6 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;SMM/kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e25.4 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e30.2 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e23.3 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003eBC assessment (NU)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;RF-CSA (cm\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e4.94 (1.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e6.11 (1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e4.42 (1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;RF-CIR (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e9.10 (1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e10.0 (1.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e8.68 (1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;RF-X axis (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e3.68 (0.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e4.10 (0.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e3.50 (0.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;RF-Y axis (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e1.69 (0.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e1.93 (0.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e1.59 (0.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;L-SAT (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e1.81 (0.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e1.34 (0.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e2.02 (0.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; RF-CSA/kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e4.96 (1.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e5.31 (1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e4.80 (1.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; RF-Y axis/kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e1.70 (0.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e1.66 (0.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e1.72 (0.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e0.361\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;T-SAT (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e3.09 (0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e2.83 (1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e3.20 (0.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;S-SAT (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e1.59 (0.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e1.41 (0.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e1.67 (0.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;VAT (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e1.12 (0.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e1.20 (0.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e1.08 (0.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e0.188\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003eFunctional assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;HGS (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e27.1 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e39.9 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.6581352833638%\"\u003e\n \u003cp\u003e20.9 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.420475319926874%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eBody composition was assessed by both BIA and NU, and skeletal muscle function was assessed by HGS. Results are expressed as mean (SD). The two-tailed unpaired t test was used to compare quantitative variables between male and female patients, with Welch\u0026rsquo;s correction in the event that variances were significantly different.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eASMM, appendicular skeletal muscle mass; BC, body composition; BCM, body cell mass; BIA, bioelectrical impedance analysis; CE, creatine excretion; FFM, fat-free mass; FFMI, fat-free mass index; FM, fat mass; FMI, fat mass index; h, hours; HGS, handgrip strength; IQR, interquartile range; L-SAT, leg subcutaneous adipose fat; SD, standard deviation; NU, nutritional ultrasound; PhA, phase angle; RF-CIR, rectus femoris quadriceps circumference; RF-CSA, rectus femoris cross-sectional area; Rz, resistance; SMI, skeletal muscle index; SMM, skeletal muscle mass; SPA, standardized phase angle; S-SAT, superficial abdominal subcutaneous adipose fat; T-SAT, total abdominal subcutaneous adipose fat; Xc, reactance; VAT, visceral adipose tissue.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Obesity, nutritional status, morphofunctional assessment, nutritional ultrasound, bioelectrical impedance analysis, handgrip strength dynamometry ","lastPublishedDoi":"10.21203/rs.3.rs-3999407/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3999407/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground\u003c/p\u003e\n\u003cp\u003eAssessing the nutritional status of patients with obesity (PwO) is mandatory to secure optimal management. Easy, affordable procedures to accomplish this purpose would be appreciated. Nutritional ultrasound (NU) is a simple, non-invasive method for morphofunctional analysis.\u003c/p\u003e\n\u003cp\u003eMethods\u003c/p\u003e\n\u003cp\u003eWe evaluated the ability of NU to determine body composition in a cohort of 178 PwO. Bioelectrical impedance analysis (BIA) and handgrip strength dynamometry (HGS), which are accepted methods to monitor body composition and muscle functionality, respectively, in PwO, were used for comparative purposes.\u003c/p\u003e\n\u003cp\u003eResults\u003c/p\u003e\n\u003cp\u003eThere was a highly significant correlation between NU-measured quadriceps rectus femoris (RF) cross-sectional area (CSA) and BIA-measured fat-free markers such as body cell mass (r = 0.638, \u003cem\u003eP \u003c/em\u003e\u0026lt;0.001), fat free mass (r = 0.597, \u003cem\u003eP \u003c/em\u003e\u0026lt;0.001) or appendicular skeletal muscle mass (r = 0.591, \u003cem\u003eP \u003c/em\u003e\u0026lt;0.001). The correlation between RF-CSA and HGS was also significant (r = 0.536, \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.001). NU-measured leg subcutaneous adipose tissue (L-SAT) was highly correlated with BIA-measured fat mass (%) (r = 0.656, \u003cem\u003eP \u003c/em\u003e\u0026lt;0.001). There was a significant inverse correlation between L-SAT and HGS (r = -0.416, \u003cem\u003eP \u003c/em\u003e\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003eConclusions\u003c/p\u003e\n\u003cp\u003eThese results suggest that NU can be a useful, cheap, portable tool to assess nutritional status.\u003c/p\u003e","manuscriptTitle":"Potential Usefulness of Nutritional Ultrasound for Morphofunctional Assessment in Patients With Obesity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-19 15:51:02","doi":"10.21203/rs.3.rs-3999407/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"616d95f7-3803-4c9a-8cf7-eddc23397d47","owner":[],"postedDate":"March 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":29555316,"name":"Health sciences/Endocrinology/Endocrine system and metabolic diseases/Obesity"},{"id":29555317,"name":"Biological sciences/Physiology/Metabolism/Metabolic diseases/Metabolic syndrome"}],"tags":[],"updatedAt":"2024-09-25T05:09:01+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-19 15:51:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3999407","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3999407","identity":"rs-3999407","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}