Effects of the Protein Supplementation Associated With Exercise Training in Elderly With Sarcopenic Obesity Undergoing Caloric Restriction
Phase: NA
Conditions: Sarcopenic Obesity, Aging
Sponsor: University of Sao Paulo General Hospital

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Protein Supplementation in Older Adults with Sarcopenic Obesity Undergoing 
Caloric Restriction and Exercise. 
 
 
Clinical trial registration number: NCT04981366 
Unique Protocol ID: 04234918.1.0000.0065 
 
Principal Investigator 
Professor, Hamilton Roschel,  
Center of Lifestyle Medicine; Laboratory of Assessment and Conditioning in 
Rheumatology, Hospital das Clínicas, Faculdade de Medicina, Universidade de Sao 
Paulo, Av Dr Arnaldo, 455, Third Floor, 01246-903, São Paulo, São Paulo, Brazil. 
Applied Physiology and Nutrition Research Group-School of Physical Education and 
Sport and Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, SP, 
Brazil. 
 
Sub-investigators 
PhD student, Gersiel Oliveira Junior, Center of Lifestyle Medicine; Faculdade de 
Medicina, Universidade de Sao Paulo, São Paulo, São Paulo, Brazil. 
PhD student, Rafael Genario, Center of Lifestyle Medicine; Faculdade de Medicina, 
Universidade de Sao Paulo, São Paulo, São Paulo, Brazil. 
PhD student, Alice Erwig Leitão, Center of Lifestyle Medicine; Faculdade de Medicina, 
Universidade de Sao Paulo, São Paulo, São Paulo, Brazil. 
MSc student, Tathiane Franco, Center of Lifestyle Medicine; Faculdade de Medicina, 
Universidade de Sao Paulo, São Paulo, São Paulo, Brazil. 
PhD, Saulo Gil, Center of Lifestyle Medicine; Faculdade de Medicina, Universidade de 
Sao Paulo, São Paulo, São Paulo, Brazil 
Professor Bruno Gualano, Center of Lifestyle Medicine; Faculdade de Medicina, 
Universidade de Sao Paulo, São Paulo, São Paulo, Brazil 
 
Trial center: 
 
Center of Lifestyle Medicine; Laboratory of Assessment and Conditioning in 

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Rheumatology, Hospital das Clínicas, Faculdade de Medicina, Universidade de Sao 
Paulo, Av Dr Arnaldo, 455, Third Floor, 01246-903, São Paulo, São Paulo, Brazil 
 
 

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SUMMARY 
PROTOCOL ....................................................................................................................5 
SUMMARY OF STUDY .................................................................................................5 
BACKGROUND AND SIGNIFICANCE ......................................................................6 
STUDY HYPOTHESIS ...................................................................................................8 
AIM ...................................................................................................................................8 
RESEARCH DESIGN AND METHODS ......................................................................8 
STUDY POPULATION ............................................................................................................ 9 
Inclusion criteria ................................................................................................................. 9 
Exclusion criteria................................................................................................................. 9 
Follow-up procedure: .......................................................................................................... 9 
STUDY DESIGN .................................................................................................................... 10 
RANDOMIZATION ............................................................................................................... 10 
EXAMINATIONS ................................................................................................................... 10 
Anthropometry .................................................................................................................. 11 
Body composition .............................................................................................................. 11 
Skeletal muscle size ........................................................................................................... 11 
Quadriceps muscular cross-sectional area ....................................................................... 12 
Rectus femoris and vastus lateralis muscular cross-sectional area ................................. 12 
Visceral and subcutaneous fat areas ................................................................................ 13 
Muscle biopsies .................................................................................................................. 13 
Bone health ........................................................................................................................ 15 
Bone microarchitecture ................................................................................................... 15 
Bone mineral content and areal bone mineral density..................................................... 16 
Strength and functionality ................................................................................................ 16 
Isometric strength ............................................................................................................ 16 
Isoinertial strength ........................................................................................................... 17 
Functional capacity ......................................................................................................... 17 
Cardiopulmonary assessments ......................................................................................... 18 
Pulmonary function ......................................................................................................... 18 
Cardiorespiratory fitness ................................................................................................. 19 
Dietary assessments ........................................................................................................... 19 
Biochemical analyses ......................................................................................................... 20 
Lipid profile .................................................................................................................... 20 

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Glycated hemoglobin ...................................................................................................... 20 
Oxidative Stress markers ................................................................................................. 20 
Gut hormones and inflammatory markers ....................................................................... 21 
Bon-related parameters ................................................................................................... 21 
Oral glucose tolerance test (OGTT)................................................................................. 21 
Telomere length ................................................................................................................. 22 
Health-related quality of life ............................................................................................ 23 
Sleep quality ....................................................................................................................... 23 
Depression and anxiety ..................................................................................................... 24 
Ccognitive processing speed ............................................................................................. 24 
Cognitive executive function ............................................................................................ 25 
EXPERIMENTAL INTERVENTIONS .................................................................................. 25 
Caloric restriction and dietary supplementation............................................................ 25 
Exercise training intervention .......................................................................................... 26 
SAMPLE SIZE CALCULATION ........................................................................................... 27 
DATA ANALYSIS................................................................................................................... 28 
STATISTICAL ANAYSIS PLAN .................................................................................28 
STUDY TIME LINE .....................................................................................................30 
REFERENCES ..............................................................................................................31 
 
 
 

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PROTOCOL 
 
Protein Supplementation in Older Adults with Sarcopenic Obesity Undergoing 
Caloric Restriction and Exercise. 
 
SUMMARY OF STUDY 
 
Sarcopenic obesity increases the risks of mortality, comorbidities, and the development 
of various geriatric syndromes, making it a growing concern for the older adults. 
However, treatment options are controversial and lack sufficient data. Combining 
exercise training, caloric restriction, and increased dietary protein is a potential strategy, 
but the long-term effects on muscle, bone health, cardiovascular function, and aging are 
still unclear. Therefore, this study aimed to investigate the impact of combining protein 
supplementation with exercise training and caloric restriction in older adults with 
sarcopenic obesity. 
 This will be a single-center, double-blinded, parallel-group, randomized, placebo-
controlled trial. Older adults with sarcopenic obesity (n= 105) will be allocated to one of 
three groups: protein supplementation (PTN, n=35), placebo supplementation (PLA, 
n=35), or control (CON, n=35). The PTN and PLA groups will receive dietary 
supplements in addition to an exercise training and calorie restriction intervention, while 
the CON group will receive no intervention. Body composition, bone health, 
cardiorespiratory fitness, pulmonary function, functional capacity, muscle cross-sectional 
area, upper and lower-limb maximal dynamic strength, endothelial function, biochemical 
parameters, health-related quality of life, cognitive function, sleep quality, symptoms of 
anxiety and depression, and nutritional status will be assessed before and after a 16-week 
intervention period. A linear mixed model with repeated measures analysis will be 
conducted to assess within- and between-group effects of the intervention, using baseline 
values of the outcome as covariates. Whenever significant group-by-time interactions will 
be found, post-hoc tests on the adjusted predictions with Sidak’s adjustment will be 
performed for multiple comparisons. Significance will be set at p<0.05. Data will be 
reported as the mean and standard deviation, along with the estimated mean difference 
(EMD) between groups and its 95% confidence interval (95% CI) when a main effect or 
interaction is observed. 
 

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BACKGROUND AND SIGNIFICANCE 
 
The prevalence of obesity among older adults is growing worldwide (1-3). 
Excessive adipose tissue is linked to insulin resistance, high blood pressure, endothelial 
dysfunction, and dyslipidemia, obesity offers a heightened risk for developing 
cardiovascular and metabolic diseases, particularly among older individuals (4-6). 
Concurrently, aging is associated with declines in skeletal muscle mass and function (i.e., 
sarcopenia) (7), which can be further exacerbated by obesity (8-10). The interplay of these 
conditions poses an emergent public health issue termed sarcopenic obesity (11-13), a 
condition associated with greater risk of morbimortality and worse health-related quality 
of life (14, 15). 
The optimal treatment approach for sarcopenic obesity in older adults is still a 
subject of debate. Numerous studies have highlighted the potential benefits of caloric 
restriction for managing obesity and mitigating its associated negative effects (16-21). 
However, weight loss resulting from caloric restriction may further worsen age-related 
declines in skeletal muscle and bone mass in older adults (20). For this reason, exercise 
training has been frequently recommended as a countermeasure to offset skeletal muscle 
and bone mass losses while potentiating weight loss (22, 23). Although previous studies 
partly support this idea, exercise training alone has been shown unable to fully preserve 
skeletal muscle and bone tissue (17, 24, 25), warranting additional strategies to counteract 
the adverse effects of caloric restriction on these tissues. 
For instance, acute protein intake can activate anabolic pathways in skeletal 
muscle and stimulate the release of growth factors essential for maintaining bone structure 
(26, 27). Over the long term, high-protein diets may help support muscle and bone 
turnover, potentially reducing caloric restriction-associated adverse effects on body 
composition, even in older populations (28-34). Importantly, increased dietary protein 
intake have been demonstrated to positively impact functional capacity in older adults 
when combined with exercise training interventions, possibly preserving/enhancing their 
autonomy (35, 36).  
Protein supplementation may also confer metabolic benefits on lipid metabolism, 
insulin resistance, endothelial function, and immune function (37-40). Indeed, protein 
supplementation, especially whey protein, modulates incretin hormones and is highly 
insulinotropic (38, 39), which may improve insulin sensitivity, glycemic variability (41, 
42) and lipid profile (43). Furthermore, immunoglobins present in whey protein are 

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thought to possess anti-inflammatory properties (37-39), which may help reduce 
inflammatory status in these patients (44-46). Also, the use of whey protein has been 
recommended to improve endothelial function. Significant improvements in flow-
mediated dilation (FMD) response, a prognostic marker of cardiovascular events (47), 
have been demonstrated following whey protein supplementation in different populations 
(40, 48, 49).  
Cardiorespiratory fitness, a clinical prognostic marker that is highly responsive to 
exercise training, is also likely to respond positively to dietary interventions when 
combined with exercise training (50). Previous small-scale studies have demonstrated the 
benefits of protein supplementation during endurance training on cardiorespiratory fitness 
in both healthy individuals and clinical populations (51-53). It can be speculated that the 
positive effects of protein supplementation on skeletal muscle mass and mitochondrial 
adaptations (54) may enhance mechanical efficiency and bioenergetic metabolism, 
further contributing to improvements in cardiorespiratory fitness. Moreover, ventilatory 
inefficiency and exertional dyspnea, which are often associated with obesity, may also 
improve with changes in body composition and weight loss, particularly through 
reductions in fat mass (55, 56).  
Finally, recent studies have also shown a positive association between skeletal 
muscle mass and leukocyte telomere length, a marker of biological aging (57, 58). A 
similar negative association is observed between obesity-related parameters (e.g., body 
mass index, fat mass, waist-to-hip ratio, etc.) and leukocyte telomere length (59-62). It is 
plausible to speculate that improvements in body composition (e.g., maintaining muscle 
mass while reducing fat mass) through interventions combining both protein 
supplementation and exercise training may influence the rate of telomere shortening, 
potentially impacting overall health. 
Collectively, these positive effects of protein may be of significant clinical 
relevance, considering that these conditions are highly prevalent in older adults, 
especially among those with sarcopenic obesity (63-67). Therefore, this study aimed at 
investigating the impact of protein supplementation in addition to exercise training and 
caloric restriction on fat-free mass (as primary outcome) in older adults with sarcopenic 
obesity. Secondary outcomes include skeletal muscle fiber area, muscle strength and 
functionality, fat mass (total, visceral and subcutaneous), bone health parameters (bone 
mineral density, microarchitecture and bone metabolism markers). Other outcomes 
included cardiopulmonary capacity (cardiorespiratory fitness and pulmonary function), 

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glycemic control and insulin sensitivity, endothelial function, inflammation, and related 
cellular and molecular mechanisms (telomere length, oxidative stress, and lipid profile). 
We hypothesized that this integrated approach could provide substantial benefits for body 
composition, and various health-related outcomes crucial to managing sarcopenic obesity 
in this population. 
 
STUDY HYPOTHESIS 
 
We hypothesized that protein supplementation can provide additional benefits on 
body composition and bone health more than only caloric restriction and exercise training 
in this population. Additionally, we hypothesized that these improvements would enhance 
muscle function. Furthermore, we also expected that protein supplementation would 
enhance the effects of caloric restriction and exercise training on glycemic control, insulin 
sensitivity, endothelial function, inflammatory markers, lipid profile, telomere length and 
oxidative stress markers. 
 
AIM 
 
This study aimed at investigating the impact of protein supplementation in 
addition to exercise training and caloric restriction on fat-free mass (as primary outcome) 
in older adults with sarcopenic obesity. Secondary outcomes include skeletal muscle fiber 
area, muscle strength and functionality, fat mass (total, visceral and subcutaneous), bone 
health parameters (bone mineral density, microarchitecture and bone metabolism 
markers). In addition, this study will aim the effects of protein supplementation in other 
outcomes including cardiopulmonary capacity (cardiorespiratory fitness and pulmonary 
function), glycemic control and insulin sensitivity, endothelial function, inflammation, 
and related cellular and molecular mechanisms (telomere length, oxidative stress, and 
lipid profile). 
 
RESEARCH DESIGN AND METHODS 
 
This 16-week study will be a single-center, double-blinded, parallel-group, 
randomized, placebo-controlled trial.  
 

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STUDY POPULATION 
 
Older adults will be recruited from the Division of Geriatrics at the School of 
Medicine of the University of São Paulo, as well as through advertisements on social 
media and in community-based centers for older adults. All participants will provide 
written informed consent before enrollment in the study. 
 
Inclusion criteria 
 
Men and women aged 65 years or older, with central obesity (waist circumference 
>102 cm for men and >88 cm for women), body mass index (BMI) of ≥30 kg/m², 
sarcopenia (according to the criteria set by the Foundation for the National Institutes of 
Health (FNIH) (68)), not engaged in an exercise training program, and with stable weight 
within the past 6 months will be considered eligible to participate. Reference cut-off 
values for sarcopenia will include a handgrip strength-to-BMI ratio of less than 1.0 
kg/BMI and an appendicular fat-free mass-to-BMI ratio of less than 0.789 kg/BMI for 
men, and a handgrip strength-to-BMI ratio of less than 0.56 kg/BMI and an appendicular 
fat-free mass-to-BMI ratio of less than 0.512 kg/BMI for women (68). 
 
Exclusion criteria 
 
Exclusion criteria will include a history of recent malignancies (within the past 5 
years); cognitive deficits or dementia that prevent the participant from reading and 
signing the informed consent form; and medical conditions in which physical testing or 
engaging in exercise training would be contraindicated (e.g., locomotor disabilities or 
cardiopulmonary diseases, including unstable angina, heart failure, myocardial infarction, 
or chronic obstructive pulmonary disease). 
 
Follow-up procedure: 
 
In case of drop-out, the participant will be asked to complete a full set of 
examinations at the time of drop out. 
 

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STUDY DESIGN 
 
The present study will be a single-center, double-blinded, parallel-group, 
randomized, placebo-controlled trial. Figure 1 illustrates the study design. Initially, 
participants will be pre-screened through phone calls or personal interviews. Those who 
meet the preliminary criteria will then be further assessed for their medical condition and 
eligibility criteria. Eligible participants will be matched based on sex and then randomly 
allocated in a 1:1:1 ratio into one of the following experimental groups: (a) protein 
supplementation (PTN), (b) placebo supplementation (PLA), or (c) control (CON).  
Both the PTN and PLA groups will receive dietary supplementation, will be caloric-
restricted, and will engage in an exercise training program. Participants in the CON group 
will receive no intervention other than general guidance on healthy eating and physical 
activity. All outcomes of interest will be assessed immediately before participants’ 
randomization at baseline (PRE) and after 16 weeks of intervention (POST). 
Anthropometric and dietary parameters will be reassessed at weeks 4, 8, and 12. 
Participants will also meet with a registered dietitian from the research team every two 
weeks in order to ensure compliance with the dietary intervention. 
 
RANDOMIZATION 
 
Eligible participants will be sex-matched and then randomly allocated using a 
computer-generated block design in a 1:1:1 ratio into one of the following experimental 
groups through a specific software (https://randomizer.org): (a) protein supplementation 
(PTN), (b) placebo supplementation (PLA), or (c) control (CON). The allocation 
sequence will be concealed from the research staff. 
 
EXAMINATIONS 
 
The primary outcome will be the change from baseline in fat-free mass (total, 
appendicular, appendicular relative to BMI and leg). Secondary outcomes will include 
other measures of body composition (i.e. fat and bone density), bone microarchitecture, 
bone metabolism, and specific muscle functions. Other outcomes, including 
cardiopulmonary capacity (cardiorespiratory fitness and pulmonary function), glycemic 
control, insulin sensitivity, endothelial function, inflammation, cognitive function and 

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related cellular and molecular mechanisms (telomere length, oxidative stress, and lipid 
profile) will also be assessed. 
 
Anthropometry 
 
Body weight and height will be measured on a calibrated digital scale with a 
stadiometer, respectively. Also, a trained researcher will carefully measure 
anthropometric data, including waist (WC) and hip circumferences (HC). WC will be 
determined at the midpoint between the lowest rib and top of the iliac crest on the axial 
plane, while the HC will be measured at the widest part of the hips. All assessments will 
be performed with the participant standing; a plastic tape will be used for these 
measurements. 
 
Body composition 
 
Total and segmental fat-free, and fat mass parameters, and areal bone mineral 
density (aBMD) of the whole body, lumbar spine, femoral neck, and total hip parameters 
will be assessed by a whole-body dual-energy X-ray absorptiometry (DXA) using 
Hologic QDR 4500A densitometry equipment (Discovery Densitometer, Hologic Inc., 
Bedford, MA, USA). The DXA will be calibrated with phantoms as per the manufacturer's 
guidelines each day before measurements are taken. Assessments will be carried out in 
the morning, using a consistent positioning of participants on the scanning bed of the 
DXA equipment (36). All exams will be conducted by an experienced technologist 
blinded to the study protocol. 
The precision errors for aBMD assessments will be determined following 
recommendations from the International Society for Clinical Densitometry (69). 
 
Skeletal muscle size  
 
Skeletal muscle size will be assessed using computed tomography (CT) and B-
mode ultrasound. For both CT and ultrasound imaging exams, participants will first be 
positioned supine with their shoulders extended, hands placed above their heads, and 
knees fully extended. All muscular cross-sectional area (mCSA) images will be acquired 
in the right leg. Before assessments, participants will lay down for 20 minutes to allow 

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fluid distribution (70). During assessments, the legs will be restrained with Velcro straps 
to prevent internal or external hip rotation and participants will be instructed to relax as 
much as possible their lower limb muscles. 
 
Quadriceps muscular cross-sectional area 
 
Quadriceps mCSA will be evaluated through computed tomography (CT) scans 
(Discovery CT 750HD, GE Healthcare, Chicago, IL). PRE and POST images will be 
acquired by the same blinded specialized radiology technician, under medical 
supervision, and processed using GE Healthcare workstation. To avoid bias, both will be 
blinded to the participants' group assignment. Initially, an image will be captured to 
determine the thigh length, which will be defined as the perpendicular distance from the 
greater trochanter to the inferior border of the lateral epicondyle of the femur. Quadriceps 
mCSA images will be acquired at 50% of the segment and processed using GE Healthcare 
workstation. Image acquisition parameters will be as follows: slice thickness = 10 mm; 
table increment = 10 mm, 0.70 rev/s, 120 kV, 68 mAs per slice, and field of view = 500. 
Density values used will range from 30–100 HU. Quadriceps mCSA will be determined 
using computerized planimetry through the 'freehand region of interest (ROI)' tool of the 
image analysis software Isite PACS 4.1 (Philips Healthcare Informatics, 4100 East Third 
Ave., Suite 101 Foster City, CA, USA).  
 
Rectus femoris and vastus lateralis muscular cross-sectional area 
 
Rectus femoris and vastus lateralis mCSA will be assessed by a B-mode 
ultrasound with a 7.5-MHz linear-array probe (LOGIQ e PRO – GE Healthcare, Chicago, 
IL, US) as previously described (71). Similarly to CT scans, images will be obtained at 
50% of the segment. This anatomical point will be transversally marked every 2 cm with 
semipermanent ink and used as a reference for the probe displacement. Sequential images 
will be acquired, aligning the superior edge of the probe with each mark on the skin 
following a middle-to-lateral direction. To avoid pressure on the muscle tissue, which 
could result in image distortion, a generous amount of conductive gel will be used. After 
the data collection, the muscle images will be reconstructed in PowerPoint (Microsoft, 
Redmond, WA, USA). mCSA will then be measured using computerized planimetry (i.e., 
by contouring following the muscle fascia using an 800-dpi mouse) (Madena 3.2.5; Eye-

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Physics, Los Alamitos, CA, USA). The planimetry software (ImageJ, NIH, USA) will be 
calibrated with fixed distance scales displayed in the US images. A single investigator, 
blinded to the participants' group assignment, will perform the analyses.  
 
Visceral and subcutaneous fat areas 
 
Visceral (VAT) and subcutaneous adipose tissue (SAT) areas will be measured by 
CT scans (Discovery CT 750HD, GE Healthcare, Chicago, IL). Similarly, the same 
blinded specialized radiology technician will acquire the images at PRE and POST under 
medical supervision and process them using the GE Healthcare workstation. First, an 
image will be initially obtained to determine the umbilical scar, which will allow the 
delineation of total and visceral adipose tissue areas (72). 
VAT will be assessed using the following procedures: (i) the technician will 
manually draw a line below the skin to obtain the total adipose tissue, which will be 
defined as the sum of adipose tissue hounsfield units (HU) inside this line, and (ii) VAT 
will be segmented by drawing a line, which begins at the abdominal linea alba, bisects 
the rectus abdominis, the internal oblique, the iliacus, and laterally around the peritoneum 
surrounding the vertebral body to join at the midline anterior to the vertebral body. All 
HU inside this line that meet the criteria for adipose tissue X-ray density will be counted 
as visceral adipose tissue (73). 
Abdominal SAT area will be determined by the difference between VAT and total 
abdominal fat, by using computerized planimetry through the 'freehand ROI' tool of the 
image analysis software Isite PACS 4.1 (Philips Healthcare Informatics, 4100 East Third 
Ave., Suite 101 Foster City, CA, USA). Image acquisition parameters will be as follows: 
slice thickness = 10 mm; table increment = 10 mm, 0.70 rev/s, 120 kV, 68 mAs per slice 
and field of view = 500. Density values used will range from −30 to −190 HU. 
 
Muscle biopsies  
Prior to tissue extraction, the area will be cleansed with an antiseptic solution. 
Subsequently, the selected site will be anesthetized with a subcutaneous injection of 3 mL 
of 2% lidocaine. Following local anesthesia, a small incision (~5 cm) will be made down 
to the muscle fascia using a surgical scalpel. A Bergström biopsy needle will then be 
inserted into the lateral portion of the vastus lateralis at a depth of approximately 4 cm, 
adjusted based on the thickness of subcutaneous fat (74). Suction will be applied to the 

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outer end of the needle using a 120 mL syringe, allowing a small muscle tissue sample to 
be excised by the needle’s internal blade (75). After the needle is withdrawn, pressure will 
be applied to the incision site to prevent bleeding, and the incision will be closed and 
covered with sterile bandages (76). 
Immediately after extraction (~150 mg), visible adipose or connective tissue 
fragments will be carefully removed under a standard dissection microscope (Quimis 
Q7740SZ, Quimis, Brazil). Aliquots will then be separated for subsequent analyses. 
Following separation, the samples will be rapidly frozen in liquid nitrogen and stored at 
−80 °C until further examination. For immunofluorescence assays, a small fragment (~20 
mg) will be embedded in optimal cutting temperature (OCT) medium (Tissue-Tek, Sakura 
Finetek Europe B.V., Zoeterwoude, Netherlands) with muscle fibers oriented 
transversely. These fragments will be rapidly frozen, initially in isopentane cooled with 
liquid nitrogen, and subsequently immersed in liquid nitrogen. 
 
Assessment of cross-sectional area, myonuclei count, myonuclear domain, 
capillarization, and satellite cell content 
 
Immunofluorescence techniques will be employed to assess the muscle fiber 
cross-sectional area (CSA), the number of myonuclei, satellite cells, capillaries, and 
myonuclear domain. Seven-micrometer transverse sections will be prepared from OCT-
embedded samples, brought to room temperature, and fixed in chilled methanol for 10 
minutes. The sections will then be washed and blocked for 60 minutes in phosphate-
buffered saline containing 5% goat serum and 0.3% Triton X-100. 
For quantification, the sections will be incubated with primary antibodies against 
MHCI, Laminin, Pax7, and CD31, followed by appropriate secondary antibodies. Nuclei 
will be visualized using a fluorescent mounting medium containing 4′,6-diamidino-2-
phenylindole (DAPI; Abcam, Mounting Medium With DAPI - Aqueous, Fluoroshield, 
ab104139), and coverslips will be applied to the slides. 
Images will be captured with an Olympus BX51 Fluorescence microscope with a 
magnification of ×200. A minimum of 120 fibers will be analyzed for CSA, myonuclei 
count, myonuclear domain, and satellite cells, as recommended by Mackey et al. (2009) 
(77). For capillarization assessment, a minimum of 50 fibers will be evaluated following 
Hepple et al. (1997) (78). Parameters analyzed will include the capillary count (CC, the 
number of capillaries surrounding a fiber), the capillary-to-fiber ratio (C/Fi), and the 

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capillary index per fiber perimeter. All images will be analyzed by a single researcher in 
a blinded manner. 
 
Bone health  
 
Bone microarchitecture 
 
Bone microarchitecture [volumetric bone mineral density (vBMD) and structural 
parameters of trabecular and cortical bones] will be assessed at the distal region of the 
radius of the non-dominant limb using High-Resolution Peripheral Quantitative 
Computed Tomography (HR-pQCT), in accordance with previously established 
guidelines (79). Specifically, the following parameters will be obtained: total vBMD; 
trabecular vBMD, cortical vBMD, trabecular bone volume fraction, trabecular number, 
trabecular thickness, trabecular separation, cortical thickness (Ct.Th), diameter and 
relative cortical porosity (Ct. Po), and stiffness and failure load of the finite element (FE). 
During the scan, the participant’s limb will be immobilized in a carbon fiber shell. 
The procedure allows the simultaneous acquisition of approximately 110 parallel slices 
with a resolution of 82 μm, corresponding to a 9.02 mm section along the axial direction, 
starting 9.5 mm proximal to the reference line, which will be defined as the region of 
interest (ROI) for data evaluation. All HR-pQCT measurements and analysis will be 
performed by the same experienced evaluator, blinded to the participants’ experimental 
group. All images will be acquired using the following settings: effective energy of 60 
kVp, X-ray, tube current of 95 mAs, and matrix of 1536 x 1536. Quality control will be 
monitored through daily examinations of a Phantom standard, which contains 
hydroxyapatite sticks (HA) embedded in a resin fabric (QRM, Moehrendorf, Germany). 
Test-retest coefficient of variation (CV) in our laboratory is 0.93%-1.41% for volumetric 
bone mineral density measurements, and 1.49-7.59% for structural parameters (80). 
For morphological analyses, except for cortical parameters, the standard analysis 
method will be used. The technician will perform a semi-automatic contouring process 
slice by slice to identify the periosteal limit of the bone, thus extracting the bone region 
of the surrounding soft tissue. The bone region will be extracted using a Laplace-
Hamming filter (ε 0.5, cut-off 0.4, respectively) and a global cut-off threshold of 400 
permille (‰) to generate the segmented bone volume. This method will be used to 
perform the morphological analysis [81]. Due to limitations in the standard method (e.g., 

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insufficient extraction of the cortex, which may be thin and/or highly porous, or when the 
trabecular structure is rich and well connected to the cortex), the advanced analysis 
method, also known as the extended analysis, will be used for the determination of 
cortical parameters (cortical vBMD, Ct.Th, and Ct. Po) (79). 
For the analyses of volumetric density and structural parameters, the analysis of 
FE models of the distal radius will be carried out based on images obtained directly from 
HR-pQCT, with the aim of evaluating the biomechanical parameters of the bone and, 
therefore, estimate tissue susceptibility to fractures. For FE analysis, the software 
provided by the equipment manufacturer will be used (Finite Element Software, v.1.13, 
Scanco Medica AG, Switzerland, January 2009, Manufacturer’s Guide). The vector 
information obtained from the models will be converted into blocks called voxels, which 
comprise the smallest unit that makes up the image of the analyzed material and have a 
cubic format. In FE analysis, the software will estimate and analyze the behavior of bone 
tissue when it is subjected to a force along its axis. 
 
Bone mineral content and areal bone mineral density 
 
Bone mineral content (BMC) and areal bone mineral density (aBMD) will be 
assessed by whole-body DXA using a Hologic QDR 4500A densitometry equipment 
(Discovery Densitometer, Hologic Inc., Bedford, MA, USA). The aBMD will be 
measured at the following sites: lumbar spine (L1 to L4), femoral neck, total hip, and 
whole body in accordance with the recommendations from the International Society for 
Clinical Densitometry (81). 
 
Strength and functionality 
 
Isometric strength  
 
Isometric handgrip strength will be obtained using a handgrip dynamometer 
(Jamar®, Sammons Preston Rolyan, USA). The test will be conducted with the 
participant seated, shoulders adducted, and in a neutral rotation with their elbow bent at 
a 90° angle (82). They will perform three maximum effort attempts, each lasting 5 
seconds, with a 1-minute rest interval between each attempt. The best result will be 
recorded for analysis. 

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Isoinertial strength  
 
The maximal amount of weight that can be lifted in a single repetition will be 
measured using the one-repetition maximum (1RM) strength test, following widely used 
and well-established recommendations (83). The test will be performed in the inclined 
leg-press 45º (Nakagym, São Paulo, Brazil) and bench-press machines (Nakagym, São 
Paulo, Brazil) for lower body and upper body strength assessments, respectively. The 
same testing protocol will be followed for both machines. Briefly, participants will 
complete a 5-minute general warm-up on a treadmill at 3 km·h-1, followed by a specific 
warm-up consisting of one set of eight repetitions at 50% of their estimated 1RM and one 
set of three repetitions at 70% of their estimated 1RM, with a 1-minute rest between sets. 
After that, participants will have up to five attempts to achieve their 1RM, with a 3-minute 
rest between each attempt. The 1RM will be considered the higher load at which the 
participant can perform a full eccentric-concentric movement through a 90° range of 
motion. Importantly, before the baseline assessments, participants will perform two 
familiarization sessions spaced at least 72 hours apart. If the variation between 
familiarization and testing sessions is higher than 5%, which is acknowledged as the 
normal interday variation in strength assessments (84, 85), an additional testing session 
will be performed respecting the same time interval between sessions. 
 
Functional capacity  
 
Functional capacity will be measured through the 30-s sit-to-stand test, the timed-
up-and-go test, and the short physical performance battery (SPPB) (86-88). These tests 
are widely used to evaluate functional status across various clinical (89-91), including 
older adults and frail participants (86, 92), due to its ease of application. They are 
considered valid instruments and present excellent reliability (93). 
The 30-s sit-to-stand test will evaluate the maximum number of stands that an 
individual can perform from a standard-height armless-chair (i.e., 45 cm) in 30 seconds, 
whereas the timed-up-and-go test will register the minimal time (in seconds) required to 
rise from a standard chair, walk to a line on the floor 3 meters away, turn around, and sit 
back down again. Before the test, the investigator will verbally explain and demonstrate 
how to perform each test correctly. Participants will then practice each test once to 

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familiarize themselves. A 1-minute rest will be provided between familiarization and 
testing. Then, two new attempts will be allowed for each test. All tests will be conducted 
by the same investigator to avoid bias. 
The SPPB consists of a static standing balance test, habitual gait speed, and lower 
limb muscle strength (assessed through an adapted timed-stands test) (92). For the 
balance test, the participant must be able to maintain each position (i.e., side-by-side, 
semi-tandem stand, tandem stand) for 10 s. The score is zero for participant who are 
unable to maintain balance in the first position for 10 s. If the participant can stay in the 
first position for 10 s but cannot maintain the second position for 10 s, the score is 1 point. 
A score of 2 is assigned to participants who can remain in the second position for 10 s but 
cannot sustain the third position for more than 3 s. A score of 3 is assigned to participants 
who can remain in the third position for 3 to 9 s, and the maximum score (4 points) is 
given if they can stay in the third position for 10 s. For the gait speed test over a distance 
of 4 m, a score of zero is assigned to participants unable to complete the test. A score of 
1 is given to participants who complete the course in more than 8.70 s (i.e., 0.46 m/s); a 
score of 2 for a time between 6.21 to 8.70 s (i.e., 0.47 to 0.64 m/s); a score of 3 for a time 
between 4.82 to 6.20 s (i.e., 0.65 to 0.82 m/s); and the maximum score, 4 points, for a 
time less than 4.82 s (i.e., 0.83 m/s). In the timed-stands test, the participant must sit and 
stand from a chair 5 times consecutively as quickly as possible. A score of zero is given 
when the participant cannot perform 5 repetitions. A score of 1 is given for a time greater 
than 16.7 s; a score of 2 for a time between 13.7 to 16.6 s; a score of 3 for a time between 
11.2 to 13.6 s; and the maximum score, 4 points, for a time less than 11.1 s (92). The total 
SPPB score is calculated by adding the scores from each test, with individual test scores 
ranging from zero (worst performance) to four points (best performance); the highest 
possible SPPB total score is 12 points.  
 
Cardiopulmonary assessments 
 
Pulmonary function  
 
Forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), 
FEV1/FVC ratio, forced mid-expiratory flow, and both peak inspiratory and expiratory 
flow will be evaluated through a pulmonary function test (PFT). The PFT will be 
conducted in the upright position, without the use of bronchodilators, following 

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established recommendations (94, 95). The system (Cortex, Germany) will be calibrated 
immediately before each test following the manufacturer's specifications. 
 
Cardiorespiratory fitness 
 
Classical cardiorespiratory fitness-related variables, including measured and 
percent-predicted values for oxygen uptake at peak (V̇ O2peak) and at ventilatory 
threshold (V̇ O2VT), oxygen pulse (V̇ O2/HR), respiratory exchange ratio (RER), and HR 
responses will be assessed during a maximal graded cardiopulmonary exercise test (CPX) 
and recovery. Pulmonary ventilation (V̇ E), breathing reserve [V̇ E-to-maximum voluntary 
ventilation ratio (V̇ E/MVV)], ventilatory equivalent for carbon dioxide (V̇ E/VCO2), and 
the end-tidal carbon dioxide pressure (PETCO2) will also be evaluated. 
CPX will be performed on a treadmill (Centurion C200, Micromed, Brazil) using 
an individualized modified Balke protocol to the limit of tolerance (95). All tests will be 
conducted in the same intrahospital laboratory under controlled room temperature (20-
23°C). The system will be calibrated immediately before each test using standard 
calibration gases (12% O2, 5% CO2, and balanced in N2) and a 3-L calibration gas 
syringe (Cortex, Germany) following the manufacturer's specifications. Gas exchange 
will be assessed breath-by-breath by continuous sampling using a facemask coupled to a 
gas analyzer (Metalyzer 3B, Cortex, Germany). Ventilatory parameters will be measured 
by a turbine (Cortex, Germany) with a volume transducer (flow sensor). Outlying values 
(greater than ±2 SD from the mean rolling averages) will be automatically identified and 
excluded by the analytic software (MetaSoft Studio, Cortex, Germany). Background 
noise will be smoothed from the breath-by-breath data by using a 30-second rolling 
average. HR will be continuously recorded beat-by-beat from the R-R interval using a 12-
lead electrocardiograph. (ErgoPC Elite, Micromed, Brazil). 
 
Dietary assessments  
 
Dietary parameters, including caloric intake and macronutrient and micronutrient 
content, will be determined using a specific software based on the USDA (United States 
Department of Agriculture) food database (Nutritionist Pro® v.7.3, Axxya Systems, 
Woodinville, WO, USA). Initially, a trained dietitian will provide oral and written 

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instructions on how to complete 3-day food records (two from non-consecutive weekdays 
and one from a weekend day), including guidance on timing and estimation of portion 
sizes using household measures. All 3-day food records will be individually reviewed in-
person through structured interviews with the same trained dietitian using the USDA 
Automated Multiple-Pass Method, which is a standardized validated method that includes 
five memory cues (1: quick list; 2: forgotten foods list; 3: time and occasion; 4: detail and 
review; and 5: final probe) to avoid recording errors and ensure comprehensive recall of 
all possible foods consumed. (96). This double-checking strategy will be implemented in 
order to reduce recall bias and enhance data collection accuracy. During interviews, 
portion size aids will be further clarified using food booklets with household measures 
(97, 98) and real-size food pictures (99). 
 
Biochemical analyses 
 
All blood-related biochemical analyses will be carried out in an accredited 
laboratory at our Clinical Hospital. Initially, blood samples (15 mL) will be collected 
between 08:00 and 10:00 hours, after a 12-hour overnight fast from the median or cephalic 
basilic vein. Samples will be processed and stored at −80°C until analysis. 
 
Lipid profile 
 
Lipid profile, including triglycerides, total cholesterol and its subfractions (i.e., 
VLDL-C, LDL-C, HDL-C, non-HDL-C), will be evaluated via colorimetric enzymatic 
methods.  
Glycated hemoglobin 
 
Glycated 
hemoglobin 
will 
be 
assessed 
via 
high-performance 
liquid 
chromatography performance by ion exchange as a surrogate marker of long-term blood 
glucose levels.  
 
Oxidative Stress markers 
 

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Enzymatic antioxidant assays for catalase (CAT), superoxide dismutase (SOD), 
glutathione peroxidase (GPx), glutathione reductase (GR), and glutathione S-transferase 
(GST) will be performed on plasma samples centrifuged at 10,000 g for 10min at 4°C. 
CAT activity will be measured using Fossati et al.’s modified method, where H2O2 is 
dismutated into water and oxygen, followed by a peroxidase-catalyzed reaction with o-
dianisidine. SOD activity will be evaluated using a colorimetric assay kit (Sigma Aldrich). 
GPx and GR activities will be determined by tracking NADPH oxidation at 340nm, as 
previously described (100). GST activity was measured by GSH catalysis and CDNB 
complex formation. Lipid peroxidation was assessed through malondialdehyde levels, 
following the TBARS method described by Conti et al. (101)..  
Gut hormones and inflammatory markers 
 
Gut hormones [ghrelin, gastric inhibitory peptide (GIP), pancreatic polypeptide 
(PP) and peptide YY (PYY)], inflammatory markers, including pro- and anti-
inflammatory cytokines (TNF-α, IL-6, IL-10, IL-1ra, IL-1B, and IL-4) will be assessed 
using Luminex xMAP technology, except for C-reactive protein  which will be assessed 
via an immunoturbidimetric assay.  
Bon-related parameters 
 
Bone turnover markers, including Collagen type I C-telopeptide (CTX) and 
procollagen type I N-propeptide (P1NP), will be measured by automated 
electrochemiluminescence methods following recommendations of the International 
Osteoporosis Foundation and International Federation of Clinical Chemistry (102). 
Serum levels of 25-hydroxyvitamin D, intact PTH, total and ionized calcium, will be 
determined 
using 
chemiluminescent 
immunoassay, 
electrochemiluminescence, 
enzymatic colorimetric assay, and ion-selective electrodes methods, respectively. 
 
Oral glucose tolerance test (OGTT) 
 
To assess insulin sensitivity and glucose metabolism, a 2-h oral glucose tolerance 
test will be conducted. Blood samples will be collected at 0 (i.e., after a 12-h overnight 
fast), 30, 60, 90, and 120 minutes following the ingestion of a 75 g glucose bolus.Serum 

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glucose levels will be measured using a colorimetric enzymatic assay, insulin levels will 
be quantified using a human-specific radioimmunoassay, and C-peptide levels will be 
determined through a chemiluminescent immunometric assay. Area under the curve 
(AUC), along with the Matsuda index (103), homeostatic model assessment-insulin 
resistance (HOMA-IR) and homeostatic model assessment of β-cell function cell function 
(HOMA-B) (104) will be calculated. 
 
Telomere length 
 
Particularly for telomere length (TL) analysis, blood samples will be collected 
using ethylenediaminetetraacetic acid (EDTA) tubes and stored at -80ºC until analysis. 
DNA will be extracted using the PureLink™ Genomic DNA Mini Kit (Thermo Fisher 
Scientific) following the manufacturer's instructions. DNA will be quantified using the 
NanoVue Plus spectrophotometer (General Electric), and its integrity will be evaluated 
via gel electrophoresis technique (105, 106). TL analysis will be measured in accordance 
with the modified protocol described by Cawthon and colleagues (107). The relative 
average of telomeres will be quantified via Real-Time Polymerase Chain Reaction (RT-
qPCR) technique. RT-qPCR reactions will be conducted in 96-well plates using the 
StepOnePlus™ Real-Time PCR System (Applied Biosystems®). All samples and 
reference DNA will be analyzed in duplicates using 25 ng of DNA. Three wells for 
internal control will be included in each run. For the reaction, the SYBR® Green PCR 
Mastermix kit (PureLink™) will be used with a final volume of 25 µL. The specific 
primer sequences used for telomeres are presented in Table 2. The 36B4 reaction will 
include 12.5 µL of SYBR Green (PureLink™), 0.03 µL of forward primer, 0.05 µL of 
reverse primer, and 11.42 µL of ultrapure water. For the telomere reaction, 12.5 µL of 
SYBR Green, 0.03 µL of forward primer, 0.03 µL of reverse primer, and 11.44 µL of 
ultrapure water will be used. The RT-qPCR run will consist of four distinct steps: first, an 
initial step at 50°C for 2 minutes. Second, 40 amplification cycles at 95°C for 2 minutes 
each. Third, a step at 55°C for 15 seconds. Finally, a step at 60°C for 1 minute. 
 
Table 2. Primer sequences and concentrations for telomere and 36B4 gene amplification 
in RT-qPCR Assay 

23 
 
Version 4 – 23, August 2021 
 
Primer 
Sequence (5' -> 3') 
Concentration 
 (nM) 
Tel 1 Forward 
GGT TTT TGA GGG TGA GGG TGA GGG TGA 
GGG TGA GGG T 
300 
Tel 2 Reverse 
TCC CGA CTA TCC CTA TCC CTA TCC CTA 
TCC CTA TCC CTA 
300 
36B4u 
Forward 
CAG CAA GTG GGA AGG TGT AAT CC  
300 
36B4d Reverse CCC ATT CTA TCA TCA ACG GGT ACA A 
500 
 
The relative quantification of TL will be determined using the telomere to single-
copy gene ratio (T/S) by calculating the delta values (Δ) of cycle threshold (Ct) [Ct 
(telomeres) - Ct (reference gene)]. Following the parameters previously described (108), 
the ratio of T/S for each sample will be calculated using the equation: 
2 −𝛥𝛥𝐶𝑇 =  2 −𝛥𝐶𝑇(𝑎 𝑡𝑎𝑟𝑔𝑒𝑡 𝑠𝑎𝑚𝑝𝑙𝑒) −𝛥𝐶𝑇(𝑎 𝑟𝑒𝑓𝑒𝑟𝑒𝑛𝑐𝑒 𝑠𝑎𝑚𝑝𝑙𝑒) 
 
Health-related quality of life 
 
Health-related quality of life (HRQoL) will be evaluated through the Medical 
Outcomes Study 36 – Item Short-Form Health Survey (SF-36) (109). The SF-36 provides 
scores across eight domains: physical functioning, role-physical, bodily pain, general 
health, vitality, social functioning, role-emotional, and mental health. Additionally, 
physical and mental component summary scores will be calculated. Scores will range 
from 0 to 100, with lower scores indicating worse HRQoL. 
 
Sleep quality 
 
Sleep quality will be assessed using the Portuguese version of the Pittsburgh Sleep 
Quality Index (PSQI) (110). In brief, the PSQI assesses sleep quality over a 1-month 
period by means of a questionnaire involving 19 self-rated questions and 5 questions 
answered by bedmates/roommates. The latter questions are used only for clinical 
information, and thus, will not be used in the current study. The 19 questions are 
categorized into 7 components, graded on a score that ranges from 0 to 3. The PSQI 

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components are as follows: subjective sleep quality (C1), sleep latency (C2), sleep 
duration (C3), habitual sleep efficiency (C4), sleep disturbances (C5), use of sleeping 
medication (C6) and daytime dysfunction (C7). The sum of scores for these 7 components 
will yield one global score, which will range from 0 to 21, in which the highest score 
indicates worst sleep quality. Participants will be classified as good sleepers in case of 
PSQI ≤ 5 and poor sleepers for PSQI > 5. 
 
Depression and anxiety  
 
Depression will be assessed using the short form of the Geriatric Depression Scale 
(GDS) with 15 items (GDS-15), which is specifically designed for screening depression 
in older adults (111). This shortened version offers very similar sensitivity and specificity 
compared to the original 30-item scale (112). Each item on the abbreviated scale will be 
scored as either 0 or 1, resulting in a total score range from 0 to 15. A cutoff score between 
5 and 6 will be used to differentiate between non-cases and cases of depression. 
Anxiety will be assessed using the Geriatric Anxiety Inventory (GAI), a self-
administered tool comprising 20 questions with dichotomous responses (agree/disagree) 
(113). This brief questionnaire will be easy to use even in cases of fatigue, lower education 
levels, or mild cognitive impairment. The GAI will employ a cutoff score system where 
scores between 0 and 10 will indicate absence of anxiety, scores between 11 to 15 will 
denote mild to moderate anxiety, and scores between 16 to 20 will be suggestive of severe 
anxiety. 
 
Ccognitive processing speed 
 
Cognitive processing speed will be assessed utilizing the Trail Making Test 
(TMT). The most widely employed version of the TMT comprises parts A and B. In part 
A, the subject utilizes a pencil to connect a series of 25 encircled numbers in numerical 
order. In part B, the subject connects 25 encircled numbers and letters in numerical and 
alphabetical order, alternating between the numbers and letters. For instance, the first 
number "1" is followed by the first letter "A," followed by the second number "2" then 
second letter "B" and so forth. The numbers and letters are positioned in a semi-random 
fixed order, in such a manner as to prevent overlapping lines being drawn by the 

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examinee. The primary variables of interest are the total time to completion for parts A 
and B. A cutoff time of 300 s is generally employed to discontinue test administration and 
is therefore the typical maximum score (114). 
 
Cognitive executive function 
 
Cognitive executive function will be assessed by Stroop Test (ST) (Victoria 
version). The ST will follow the guideline specifications suggested by Duncan 2006 
(115). Three cards, each containing 24 stimuli against a white background, will be used. 
Card A will consist of rectangles printed randomly in green, pink, blue, and brown. Card 
B will be organized similarly to Card A but will have rectangles replaced by unrelated 
words to concepts of color (each, never, today, and all) printed in uppercase in the four 
colors mentioned. Card C will also be organized similarly to Card A, representing the 
interference card where the written stimuli will be the names of the colors (brown, blue, 
pink, and green) printed in the same colors, ensuring that the ink color and the color name 
never match (e.g., the word "brown" printed in pink, green, or blue). For the first card, 
participants will state the colors of the rectangles as quickly as possible. For cards B and 
C, subjects will state the color of the printed words instead of reading the words 
themselves. The criterion score will be the time taken to perform the task for each card, 
and all errors will be corrected promptly without stopping the chronometer (116). 
 
EXPERIMENTAL INTERVENTIONS 
 
Caloric restriction and dietary supplementation  
 
Participants allocated to the intervention groups (PTN and PLA) received 
individual meal plans to induce a caloric deficit of 300-500 kcal/day from their habitual 
energy intake assessed at baseline. Habitual intake values were contrasted with total 
energy requirements individually estimated by FAO/WHO equation for older adults, 
applying a sedentary activity factor at baseline and an active factor for later time points 
(differences between calculation methods were <1% throughout the study). The caloric 
deficit was maintained based on regular reassessment of dietary parameters every four 
weeks. In addition, participants met biweekly with registered dietitians for individual 

26 
 
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behavioral therapy involving nutritional education in order to enhance adherence to the 
caloric restriction protocol. 
Participants from PTN and PLA will be provided, on a weekly basis, with 
unlabeled dietary supplement bottles to be consumed daily at breakfast. The PTN group 
will receive 40g of whey protein (Nutrata®, São Paulo, Brazil), while the PLA group will 
receive an isocaloric non-nitrogenous placebo (Nutrata®, São Paulo, Brazil), consisting 
of a carbohydrate blend (isomaltulose, waxy maize, maltodextrin), with the same flavor 
(natural chocolate) and texture. They will be asked to record their supplement intake (time 
and day) and return the bottles (empty or not) weekly to monitor adherence. To ensure a 
daily intake of 1500mg of calcium and 1000IU of vitamin D, calcium and vitamin D 
supplements will also be provided to prevent deficiencies associated with caloric 
restriction, as previously recommended (117).  
The research team will be available to answer any questions about the 
supplementation protocol throughout the trial. 
 
Exercise training intervention 
 
Participants from both PTN and PLA groups will engage in a three-times-a-week 
exercise training program for 16 weeks. The program will include resistance and 
endurance exercises. Resistance training will consist of six exercises targeting major 
muscle groups: incline leg press 45°, leg extension, leg curl, calf raise, horizontal bench 
press, and lat pull-down. Endurance training will involve walking and/or running. The 
exercise training protocol's periodization will follow recommendations from widely 
accepted position stands for older adults (118, 119) (Table 3). For each exercise, resistance 
training will progress from 1 set of 15-20 repetition maximum (RM) in the first week to 
3 sets of 10-12 RM in the final four weeks of training. Whenever a participant exceeds 
the upper limit of the repetition range for two consecutive sets, the intensity will be 
adjusted by increasing the exercise load. Similarly, endurance exercise will progress from 
30 minutes at 55–65% of heart rate maximum (HRmax) during the first four weeks to 40 
minutes at 70–80% HRmax during the last four weeks of training. Borg’s Rating of 
Perceived Exertion (RPE) scale (120) will be used as an auxiliary tool for monitoring 
exercise intensity and training progression. In these cases, the targeted intensity will range 
from ‘very light’/‘fairly light’ (Borg’s RPE score 9–11 a.u.) to ‘somewhat hard’/‘hard’ 

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(Borg’s RPE score 13–15 a.u.). All training sessions will be supervised by an experienced 
exercise physiologist blinded to the participants’ group assignment. A training log will be 
maintained for each session to monitor adherence and control the training load. 
 
Table 3. Exercise training prescription. 
Type of exercise 
Weeks 
Volume 
Intensity 
Borg’s RPE 
Resistance training 
1 
1 set 
15-20 RM 
NA 
2-4 
2 sets 
15-20 RM 
NA 
5-8 
3 sets 
15-20 RM 
NA 
9-12 
3 sets 
12-15 RM 
NA 
13-16 
3 sets 
10-12 RM 
NA 
Endurance training 
1-4 
30 min 
55-65% HRmax 
9-11 a.u. 
5-8 
35 min 
55-65% HRmax 
9-11 a.u. 
9-12 
40 min 
60-70% HRmax 
11-13 a.u. 
13-16 
40 min 
70-80% HRmax 
13-15 a.u. 
Abbreviations: RM: repetition maximum, HRmax: maximum heart rate, RPE: rating of 
perceived exertion, a.u.: arbitrary units, NA: Not applicable. 
 
To address the higher prevalence of comorbidities in this population, additional 
precautions will be implemented. All participants will have their resting blood pressure 
measured by an automatic monitor (SPACELABS, São Paulo, Brazil) immediately before 
each training session, and sessions will be suspended if systolic or diastolic blood pressure 
readings are ≥160 mmHg or ≥105 mmHg, respectively (121, 122). Likewise, blood 
glucose levels will be measured before training sessions for participants with type-2 
diabetes, with acceptable values considered to be between 90 and 250 mg/dL (123). 
Additionally, heart rate (HR) and peripheral oxygen saturation (SpO2) will be 
continuously monitored during endurance exercise. Whenever necessary, participants will 
receive outpatient care and consultation with our medical staff.  
The CON group will receive one-on-one guidance and behavioral orientations 
focusing on a healthy lifestyle, including nutritional education and physical activity at 
PRE, and every four weeks throughout the trial. 
 
SAMPLE SIZE CALCULATION 
 

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Sample size was determined a priori using the G-Power software (Version 3.1.9.2, 
University of Kiel, Germany). The analysis was conducted by inputting α error (0.05), 
power (1 - β error = 0.95), and effect size (Hedges’ g = 0.61), considering previous data 
indicating a lower loss of fat-free mass in individuals undergoing caloric restriction who 
had an increase in protein intake compared to their counterparts who maintained their 
usual protein intake (31). Calculations were based on an ANOVA with repeated measures 
(within-between interactions) and the total sample size was determined to be 81 
individuals. To account for midtrial withdrawals, the sample will be increased by ~30% 
(i.e. 105 participants). 
 
DATA ANALYSIS 
 
Data will be presented as mean ± standard deviation (SD), estimated mean difference 
between groups (EMD) at POST (only in the presence of group x time interaction), 95% 
confidence interval (95%CI), unless otherwise indicated. Baseline characteristics will be 
compared between groups using either Fisher exact test or generalized linear model with 
Sidak post hoc adjustment whenever necessary. Data will be analyzed using an intention-
to-treat (ITT) approach to preserve the integrity of randomization. Before inferential 
analysis, outliers will be identified, and the data will be tested for homogeneity of 
variance and sphericity. Dependent variables will be analyzed by a linear mixed model 
analysis for repeated measures (assuming time [PRE and POST] and group [PTN, and 
PLA] with baseline values as covariate. The restricted maximum likelihood method, 
compound symmetry covariance structure, and Kenward-Roger degrees of freedom 
approximation will be applied for all models. In order to maintain the overall significance 
level at 0.05, the primary endpoints will be assessed using Hochberg’s procedure (124). 
For all secondary outcomes the significance level will be set at p≤0.05. Whenever 
significant group-by-time interactions are identified, post‐hoc tests on the adjusted 
predictions with Sidak’s adjustment will be performed for multiple comparisons. 
 All analyses will be performed in the statistical environment R (version 3.5.3; R 
Core Team 2020). 
 
STATISTICAL ANAYSIS PLAN 
 

29 
 
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All analyses will be performed in the statistical environment R (version 3.5.3; R 
Core Team 2020). We will perform all the comparisons using two-sided significance tests. 
Intention-to-treat analyses will be performed by analyzing data from all participants 
originally randomized to preserve the integrity of randomization. The longitudinal 
analysis of all outcomes will be performed using a linear mixed model for repeated 
measures, assuming ‘group’ (PTN, and PLA) and ‘time’ (pre-intervention and post-
intervention) as fixed factors, and ‘subjects’ as a random factor, with an interaction 
between ‘group’ and ‘time’ added to the model; baseline values of the outcome will be 
used as covariates. For all models, maximum restricted likelihood and Kenward-Roger 
degrees of freedom will be used for model fit and estimation. We will adjust for testing 
of the four primary outcomes, total fat-free mass, appendicular fat-free mass, 
appendicular fat-free mass relative to body mass index, and leg fat-free mass, using 
Hochberg’s procedure in order to maintain the overall significance level at 0.05. Since the 
other hypothesis tests (for the secondary outcomes) will be more exploratory in nature, 
the Hochberg’s correction will not be used, and two-sided p-values less than 0.05 will be 
considered to indicate statistical significance. For both primary and secondary outcomes, 
whenever significant group-by-time interactions are identified, post‐hoc tests on the 
adjusted predictions with Sidak’s adjustment will be performed for multiple comparisons. 
Mixed model analyses will be used instead of standard repeated measures analysis 
of variance because of the likelihood that there will be dropouts and missed visits that 
preclude the use of the classical approach (125, 126). The mixed model approach we will 
employ fits a linear regression model to each subject and assumes that both error terms 
and regression coefficients are normally distributed in these lines. It then uses the EM 
algorithm to combine the individual lines and to generate empirical Bayes, maximum 
likelihood, and restricted maximum likelihood estimates of model parameters. Because 
lines are generated for individuals, the model is more general than standard repeated 
measures analysis of variance in that it has no requirements about common measurement 
times between subjects and can deal easily with missing data. In all analyses, careful 
attention will be given to ensuring that the conditions that are required of a particular 
statistical method are satisfied. We will assess the normality of regression residuals and 
ensure the homogeneity of variances when analyzes of variance and covariance are 
performed. When required assumptions are not satisfied, data transformations will be 
explored and utilized as appropriate. 
 

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STUDY TIME LINE 
 
July 2021 – August 2023 
 
 

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REFERENCES 
 
1. 
Roh E, Choi KMJFie. Health consequences of sarcopenic obesity: a narrative 
review. 2020;11:530178. 
2. 
Wannamethee SG, Atkins JLJCDR. Sarcopenic obesity and cardiometabolic 
health and mortality in older adults: a growing health concern in an ageing population. 
2023;23(11):307-14. 
3. 
Lopez-Otin C, Blasco MA, Partridge L, Serrano M, Kroemer G. The hallmarks of 
aging. Cell. 2013;153(6):1194-217. 
4. 
Powell-Wiley TM, Poirier P, Burke LE, Despres JP, Gordon-Larsen P, Lavie CJ, 
et al. Obesity and Cardiovascular Disease: A Scientific Statement From the American 
Heart Association. Circulation. 2021;143(21):e984-e1010. 
5. 
Piche ME, Tchernof A, Despres JP. Obesity Phenotypes, Diabetes, and 
Cardiovascular Diseases. Circulation research. 2020;126(11):1477-500. 
6. 
Conway B, Rene A. Obesity as a disease: no lightweight matter. Obesity reviews 
: an official journal of the International Association for the Study of Obesity. 
2004;5(3):145-51. 
7. 
Morgan PT, Smeuninx B, Breen L. Exploring the Impact of Obesity on Skeletal 
Muscle Function in Older Age. Frontiers in nutrition. 2020;7:569904. 
8. 
Lang IA, Llewellyn DJ, Alexander K, Melzer D. Obesity, physical function, and 
mortality in older adults. Journal of the American Geriatrics Society. 2008;56(8):1474-8. 
9. 
Vincent HK, Vincent KR, Lamb KM. Obesity and mobility disability in the older 
adult. Obesity reviews : an official journal of the International Association for the Study 
of Obesity. 2010;11(8):568-79. 
10. 
Rolland Y, Lauwers-Cances V, Cristini C, Abellan van Kan G, Janssen I, Morley 
JE, et al. Difficulties with physical function associated with obesity, sarcopenia, and 
sarcopenic-obesity in community-dwelling elderly women: the EPIDOS (EPIDemiologie 
de l'OSteoporose) Study. The American journal of clinical nutrition. 2009;89(6):1895-
900. 
11. 
Zhang X, Xie X, Dou Q, Liu C, Zhang W, Yang Y, et al. Association of sarcopenic 
obesity with the risk of all-cause mortality among adults over a broad range of different 
settings: a updated meta-analysis. BMC geriatrics. 2019;19(1):183. 
12. 
Wannamethee SG, Atkins JL. Sarcopenic Obesity and Cardiometabolic Health 
and Mortality in Older Adults: a Growing Health Concern in an Ageing Population. 
Current diabetes reports. 2023;23(11):307-14. 
13. 
Batsis JA, Villareal DT. Sarcopenic obesity in older adults: aetiology, 
epidemiology and treatment strategies. Nat Rev Endocrinol. 2018;14(9):513-37. 
14. 
Prado CM, Batsis JA, Donini LM, Gonzalez MC, Siervo M. Sarcopenic obesity 
in older adults: a clinical overview. Nat Rev Endocrinol. 2024;20(5):261-77. 
15. 
Benz E, Pinel A, Guillet C, Capel F, Pereira B, De Antonio M, et al. Sarcopenia 
and Sarcopenic Obesity and Mortality Among Older People. JAMA Netw Open. 
2024;7(3):e243604. 
16. 
Weinheimer EM, Sands LP, Campbell WW. A systematic review of the separate 
and combined effects of energy restriction and exercise on fat-free mass in middle-aged 
and older adults: implications for sarcopenic obesity. Nutrition reviews. 2010;68(7):375-
88. 
17. 
Villareal DT, Chode S, Parimi N, Sinacore DR, Hilton T, Armamento-Villareal R, 
et al. Weight loss, exercise, or both and physical function in obese older adults. N Engl J 
Med. 2011;364(13):1218-29. 

32 
 
Version 4 – 23, August 2021 
 
18. 
Miller GD, Nicklas BJ, Davis C, Loeser RF, Lenchik L, Messier SP. Intensive 
weight loss program improves physical function in older obese adults with knee 
osteoarthritis. Obesity (Silver Spring). 2006;14(7):1219-30. 
19. 
Messier SP, Gutekunst DJ, Davis C, DeVita P. Weight loss reduces knee-joint 
loads in overweight and obese older adults with knee osteoarthritis. Arthritis and 
rheumatism. 2005;52(7):2026-32. 
20. 
Papageorgiou M, Kerschan-Schindl K, Sathyapalan T, Pietschmann P. Is Weight 
Loss Harmful for Skeletal Health in Obese Older Adults? Gerontology. 2019:1-13. 
21. 
Waters DL, Ward AL, Villareal DT. Weight loss in obese adults 65years and older: 
a review of the controversy. Experimental gerontology. 2013;48(10):1054-61. 
22. 
Armamento-Villareal R, Aguirre L, Waters DL, Napoli N, Qualls C, Villareal DT. 
Effect of Aerobic or Resistance Exercise, or Both, on Bone Mineral Density and Bone 
Metabolism in Obese Older Adults While Dieting: A Randomized Controlled Trial. 
Journal of bone and mineral research : the official journal of the American Society for 
Bone and Mineral Research. 2019. 
23. 
Shah K, Armamento-Villareal R, Parimi N, Chode S, Sinacore DR, Hilton TN, et 
al. Exercise training in obese older adults prevents increase in bone turnover and 
attenuates decrease in hip bone mineral density induced by weight loss despite decline in 
bone-active hormones. Journal of bone and mineral research : the official journal of the 
American Society for Bone and Mineral Research. 2011;26(12):2851-9. 
24. 
Mesinovic J, Jansons P, Zengin A, de Courten B, Rodriguez AJ, Daly RM, et al. 
Exercise attenuates bone mineral density loss during diet-induced weight loss in adults 
with overweight and obesity: A systematic review and meta-analysis. Journal of sport and 
health science. 2021;10(5):550-9. 
25. 
Frimel TN, Sinacore DR, Villareal DT. Exercise attenuates the weight-loss-
induced reduction in muscle mass in frail obese older adults. Med Sci Sports Exerc. 
2008;40(7):1213-9. 
26. 
Bikle DD, Tahimic C, Chang W, Wang Y, Philippou A, Barton ER. Role of IGF-I 
signaling in muscle bone interactions. Bone. 2015;80:79-88. 
27. 
Dolan E, Sale C. Protein and bone health across the lifespan. The Proceedings of 
the Nutrition Society. 2019;78(1):45-55. 
28. 
Sukumar D, Ambia-Sobhan H, Zurfluh R, Schlussel Y, Stahl TJ, Gordon CL, et 
al. Areal and volumetric bone mineral density and geometry at two levels of protein intake 
during caloric restriction: a randomized, controlled trial. Journal of bone and mineral 
research : the official journal of the American Society for Bone and Mineral Research. 
2011;26(6):1339-48. 
29. 
Josse AR, Atkinson SA, Tarnopolsky MA, Phillips SM. Diets higher in dairy foods 
and dietary protein support bone health during diet- and exercise-induced weight loss in 
overweight and obese premenopausal women. The Journal of clinical endocrinology and 
metabolism. 2012;97(1):251-60. 
30. 
Skov AR, Toubro S, Ronn B, Holm L, Astrup A. Randomized trial on protein vs 
carbohydrate in ad libitum fat reduced diet for the treatment of obesity. International 
journal of obesity and related metabolic disorders : journal of the International 
Association for the Study of Obesity. 1999;23(5):528-36. 
31. 
Wycherley TP, Moran LJ, Clifton PM, Noakes M, Brinkworth GD. Effects of 
energy-restricted high-protein, low-fat compared with standard-protein, low-fat diets: a 
meta-analysis of randomized controlled trials. The American journal of clinical nutrition. 
2012;96(6):1281-98. 
32. 
Verreijen AM, Verlaan S, Engberink MF, Swinkels S, de Vogel-van den Bosch J, 
Weijs PJ. A high whey protein-, leucine-, and vitamin D-enriched supplement preserves 

33 
 
Version 4 – 23, August 2021 
 
muscle mass during intentional weight loss in obese older adults: a double-blind 
randomized controlled trial. The American journal of clinical nutrition. 2015;101(2):279-
86. 
33. 
Kim JE, O'Connor LE, Sands LP, Slebodnik MB, Campbell WW. Effects of 
dietary protein intake on body composition changes after weight loss in older adults: a 
systematic review and meta-analysis. Nutrition reviews. 2016;74(3):210-24. 
34. 
Houston DK, Nicklas BJ, Ding J, Harris TB, Tylavsky FA, Newman AB, et al. 
Dietary protein intake is associated with lean mass change in older, community-dwelling 
adults: the Health, Aging, and Body Composition (Health ABC) Study. The American 
journal of clinical nutrition. 2008;87(1):150-5. 
35. 
Liao CD, Wu YT, Tsauo JY, Chen PR, Tu YK, Chen HC, et al. Effects of Protein 
Supplementation Combined with Exercise Training on Muscle Mass and Function in 
Older Adults with Lower-Extremity Osteoarthritis: A Systematic Review and Meta-
Analysis of Randomized Trials. Nutrients. 2020;12(8). 
36. 
Liao CD, Lee PH, Hsiao DJ, Huang SW, Tsauo JY, Chen HC, et al. Effects of 
Protein Supplementation Combined with Exercise Intervention on Frailty Indices, Body 
Composition, and Physical Function in Frail Older Adults. Nutrients. 2018;10(12). 
37. 
Stevenson EJ, Allerton DM. The role of whey protein in postprandial glycaemic 
control. The Proceedings of the Nutrition Society. 2018;77(1):42-51. 
38. 
Sousa GT, Lira FS, Rosa JC, de Oliveira EP, Oyama LM, Santos RV, et al. Dietary 
whey protein lessens several risk factors for metabolic diseases: a review. Lipids in health 
and disease. 2012;11:67. 
39. 
Adams RL, Broughton KS. Insulinotropic Effects of Whey: Mechanisms of 
Action, Recent Clinical Trials, and Clinical Applications. Ann Nutr Metab. 
2016;69(1):56-63. 
40. 
Fekete AA, Giromini C, Chatzidiakou Y, Givens DI, Lovegrove JA. Whey protein 
lowers blood pressure and improves endothelial function and lipid biomarkers in adults 
with prehypertension and mild hypertension: results from the chronic Whey2Go 
randomized 
controlled 
trial. 
The American 
journal 
of 
clinical 
nutrition. 
2016;104(6):1534-44. 
41. 
Tettamanzi F, Bagnardi V, Louca P, Nogal A, Monti GS, Mambrini SP, et al. A 
High Protein Diet Is More Effective in Improving Insulin Resistance and Glycemic 
Variability Compared to a Mediterranean Diet-A Cross-Over Controlled Inpatient Dietary 
Study. Nutrients. 2021;13(12). 
42. 
Sun Y, Ling C, Liu L, Zhang J, Wang J, Tong X, et al. Effects of Whey Protein or 
Its Hydrolysate Supplements Combined with an Energy-Restricted Diet on Weight Loss: 
A Randomized Controlled Trial in Older Women. Nutrients. 2022;14(21). 
43. 
Pal S, Ellis V, Dhaliwal S. Effects of whey protein isolate on body composition, 
lipids, insulin and glucose in overweight and obese individuals. The British journal of 
nutrition. 2010;104(5):716-23. 
44. 
Rondanelli M, Klersy C, Terracol G, Talluri J, Maugeri R, Guido D, et al. Whey 
protein, amino acids, and vitamin D supplementation with physical activity increases fat-
free mass and strength, functionality, and quality of life and decreases inflammation in 
sarcopenic elderly. The American journal of clinical nutrition. 2016;103(3):830-40. 
45. 
Nabuco HCG, Tomeleri CM, Fernandes RR, Sugihara Junior P, Cavalcante EF, 
Cunha PM, et al. Effect of whey protein supplementation combined with resistance 
training on body composition, muscular strength, functional capacity, and plasma-
metabolism biomarkers in older women with sarcopenic obesity: A randomized, double-
blind, placebo-controlled trial. Clinical nutrition ESPEN. 2019;32:88-95. 

34 
 
Version 4 – 23, August 2021 
 
46. 
Liberman K, Njemini R, Luiking Y, Forti LN, Verlaan S, Bauer JM, et al. Thirteen 
weeks of supplementation of vitamin D and leucine-enriched whey protein nutritional 
supplement attenuates chronic low-grade inflammation in sarcopenic older adults: the 
PROVIDE study. Aging clinical and experimental research. 2019;31(6):845-54. 
47. 
Thijssen DHJ, Bruno RM, van Mil A, Holder SM, Faita F, Greyling A, et al. Expert 
consensus and evidence-based recommendations for the assessment of flow-mediated 
dilation in humans. European heart journal. 2019;40(30):2534-47. 
48. 
Hajizadeh-Sharafabad F, Sharifi Zahabi E, Tarighat-Esfanjani A. Role of whey 
protein in vascular function: a systematic review and meta-analysis of human intervention 
studies. The British journal of nutrition. 2022;128(4):659-72. 
49. 
Ballard KD, Bruno RS, Seip RL, Quann EE, Volk BM, Freidenreich DJ, et al. 
Acute ingestion of a novel whey-derived peptide improves vascular endothelial responses 
in healthy individuals: a randomized, placebo controlled trial. Nutrition journal. 
2009;8:34. 
50. 
Lin YN, Tseng TT, Knuiman P, Chan WP, Wu SH, Tsai CL, et al. Protein 
supplementation increases adaptations to endurance training: A systematic review and 
meta-analysis. Clinical nutrition. 2021;40(5):3123-32. 
51. 
Robinson MM, Turner SM, Hellerstein MK, Hamilton KL, Miller BF. Long-term 
synthesis rates of skeletal muscle DNA and protein are higher during aerobic training in 
older humans than in sedentary young subjects but are not altered by protein 
supplementation. FASEB J. 2011;25(9):3240-9. 
52. 
Ferguson-Stegall L, McCleave E, Ding Z, Doerner Iii PG, Liu Y, Wang B, et al. 
Aerobic exercise training adaptations are increased by postexercise carbohydrate-protein 
supplementation. Journal of nutrition and metabolism. 2011;2011:623182. 
53. 
Cheng YH, Wei L, Chan WP, Hsu CY, Huang SW, Wang H, et al. Effects of protein 
supplementation on aerobic training-induced gains in cardiopulmonary fitness, muscle 
mass, and functional performance in chronic stroke: A randomized controlled pilot study. 
Clinical nutrition. 2020;39(9):2743-50. 
54. 
Margolis LM, Pasiakos SM. Optimizing intramuscular adaptations to aerobic 
exercise: effects of carbohydrate restriction and protein supplementation on 
mitochondrial biogenesis. Adv Nutr. 2013;4(6):657-64. 
55. 
Brock JM, Billeter A, Muller-Stich BP, Herth F. Obesity and the Lung: What We 
Know Today. Respiration; international review of thoracic diseases. 2020;99(10):856-66. 
56. 
Bernhardt V, Babb TG. Exertional dyspnoea in obesity. Eur Respir Rev. 
2016;25(142):487-95. 
57. 
Meyer A, Salewsky B, Spira D, Steinhagen-Thiessen E, Norman K, Demuth I. 
Leukocyte telomere length is related to appendicular lean mass: cross-sectional data from 
the Berlin Aging Study II (BASE-II). The American journal of clinical nutrition. 
2016;103(1):178-83. 
58. 
Chen L, Shivappa N, Dong X, Ming J, Zhao Q, Xu H, et al. Association between 
appendicular skeletal muscle index and leukocyte telomere length in adults: A study from 
National Health and Nutrition Examination Survey (NHANES) 1999-2002. Clinical 
nutrition. 2021;40(5):3470-8. 
59. 
Njajou OT, Cawthon RM, Blackburn EH, Harris TB, Li R, Sanders JL, et al. 
Shorter telomeres are associated with obesity and weight gain in the elderly. Int J Obes 
(Lond). 2012;36(9):1176-9. 
60. 
Rode L, Nordestgaard BG, Weischer M, Bojesen SE. Increased body mass index, 
elevated C-reactive protein, and short telomere length. The Journal of clinical 
endocrinology and metabolism. 2014;99(9):E1671-5. 

35 
 
Version 4 – 23, August 2021 
 
61. 
Mundstock E, Sarria EE, Zatti H, Mattos Louzada F, Kich Grun L, Herbert Jones 
M, et al. Effect of obesity on telomere length: Systematic review and meta-analysis. 
Obesity (Silver Spring). 2015;23(11):2165-74. 
62. 
Aguiar SS, Rosa TS, Sousa CV, Santos PA, Barbosa LP, Deus LA, et al. Influence 
of Body Fat on Oxidative Stress and Telomere Length of Master Athletes. J Strength Cond 
Res. 2021;35(6):1693-9. 
63. 
Kim TN, Park MS, Lim KI, Choi HY, Yang SJ, Yoo HJ, et al. Relationships 
between sarcopenic obesity and insulin resistance, inflammation, and vitamin D status: 
the Korean Sarcopenic Obesity Study. Clinical endocrinology. 2013;78(4):525-32. 
64. 
Batsis JA, Mackenzie TA, Jones JD, Lopez-Jimenez F, Bartels SJ. Sarcopenia, 
sarcopenic obesity and inflammation: Results from the 1999-2004 National Health and 
Nutrition Examination Survey. Clinical nutrition. 2016;35(6):1472-83. 
65. 
Liu C, Wong PY, Chung YL, Chow SK, Cheung WH, Law SW, et al. Deciphering 
the "obesity paradox" in the elderly: A systematic review and meta-analysis of sarcopenic 
obesity. Obesity reviews : an official journal of the International Association for the Study 
of Obesity. 2023;24(2):e13534. 
66. 
Dutra MT, Avelar BP, Souza VC, Bottaro M, Oliveira RJ, Nobrega OT, et al. 
Relationship between sarcopenic obesity-related phenotypes and inflammatory markers 
in postmenopausal women. Clinical physiology and functional imaging. 2017;37(2):205-
10. 
67. 
Pinel A, Guillet C, Capel F, Pouget M, De Antonio M, Pereira B, et al. 
Identification of factors associated with sarcopenic obesity development: Literature 
review and expert panel voting. Clinical nutrition. 2024;43(6):1414-24. 
68. 
Studenski SA, Peters KW, Alley DE, Cawthon PM, McLean RR, Harris TB, et al. 
The FNIH sarcopenia project: rationale, study description, conference recommendations, 
and final estimates. 2014;69(5):547-58. 
69. 
Shepherd JA, Lu Y, Wilson K, Fuerst T, Genant H, Hangartner TN, et al. Cross-
calibration and minimum precision standards for dual-energy X-ray absorptiometry: the 
2005 ISCD Official Positions. Journal of clinical densitometry : the official journal of the 
International Society for Clinical Densitometry. 2006;9(1):31-6. 
70. 
Berg HE, Tedner B, Tesch PA. Changes in lower limb muscle cross-sectional area 
and tissue fluid volume after transition from standing to supine. Acta physiologica 
Scandinavica. 1993;148(4):379-85. 
71. 
Lixandrao ME, Ugrinowitsch C, Bottaro M, Chacon-Mikahil MP, Cavaglieri CR, 
Min LL, et al. Vastus lateralis muscle cross-sectional area ultrasonography validity for 
image fitting in humans. J Strength Cond Res. 2014;28(11):3293-7. 
72. 
Benatti F, Solis M, Artioli G, Montag E, Painelli V, Saito F, et al. Liposuction 
induces a compensatory increase of visceral fat which is effectively counteracted by 
physical activity: a randomized trial. The Journal of clinical endocrinology and 
metabolism. 2012;97(7):2388-95. 
73. 
Smith SR, Lovejoy JC, Greenway F, Ryan D, deJonge L, de la Bretonne J, et al. 
Contributions of total body fat, abdominal subcutaneous adipose tissue compartments, 
and visceral adipose tissue to the metabolic complications of obesity. Metabolism. 
2001;50(4):425-35. 
74. 
Bergstrom J. Percutaneous needle biopsy of skeletal muscle in physiological and 
clinical research. Scandinavian journal of clinical and laboratory investigation. 
1975;35(7):609-16. 
75. 
Neves M, Jr., Barreto G, Boobis L, Harris R, Roschel H, Tricoli V, et al. Incidence 
of adverse events associated with percutaneous muscular biopsy among healthy and 

36 
 
Version 4 – 23, August 2021 
 
diseased subjects. Scandinavian journal of medicine & science in sports. 2012;22(2):175-
8. 
76. 
Tarnopolsky MA, Pearce E, Smith K, Lach B. Suction-modified Bergstrom 
muscle biopsy technique: experience with 13,500 procedures. Muscle & nerve. 
2011;43(5):717-25. 
77. 
Mackey AL, Kjaer M, Charifi N, Henriksson J, Bojsen-Moller J, Holm L, et al. 
Assessment of satellite cell number and activity status in human skeletal muscle biopsies. 
Muscle & nerve. 2009;40(3):455-65. 
78. 
Hepple RT. A new measurement of tissue capillarity: the capillary-to-fibre 
perimeter exchange index. Canadian journal of applied physiology = Revue canadienne 
de physiologie appliquee. 1997;22(1):11-22. 
79. 
Whittier DE, Boyd SK, Burghardt AJ, Paccou J, Ghasem-Zadeh A, Chapurlat R, 
et al. Guidelines for the assessment of bone density and microarchitecture in vivo using 
high-resolution peripheral quantitative computed tomography. Osteoporosis international 
: a journal established as result of cooperation between the European Foundation for 
Osteoporosis and the National Osteoporosis Foundation of the USA. 2020;31(9):1607-
27. 
80. 
Murai IH, Roschel H, Dantas WS, Gil S, Merege-Filho C, de Cleva R, et al. 
Exercise Mitigates Bone Loss in Women With Severe Obesity After Roux-en-Y Gastric 
Bypass: A Randomized Controlled Trial. The Journal of clinical endocrinology and 
metabolism. 2019;104(10):4639-50. 
81. 
Shuhart CR, Yeap SS, Anderson PA, Jankowski LG, Lewiecki EM, Morse LR, et 
al. Executive Summary of the 2019 ISCD Position Development Conference on 
Monitoring Treatment, DXA Cross-calibration and Least Significant Change, Spinal Cord 
Injury, Peri-prosthetic and Orthopedic Bone Health, Transgender Medicine, and 
Pediatrics. Journal of clinical densitometry : the official journal of the International 
Society for Clinical Densitometry. 2019;22(4):453-71. 
82. 
MacDermid J, Solomon G, Valdes K. Clinical Assessment Recommendations: 
American Society of Hand Therapists; 2015. 
83. 
Brown LE, Weir JP. Asep procedures recommendation I: accurate assessment of 
muscular strength and power. Journal of Exercise Physiology Online. 2001;4(3). 
84. 
Schroeder ET, Wang Y, Castaneda-Sceppa C, Cloutier G, Vallejo AF, Kawakubo 
M, et al. Reliability of maximal voluntary muscle strength and power testing in older men. 
J Gerontol A Biol Sci Med Sci. 2007;62(5):543-9. 
85. 
Salem GJ, Wang M-Y, Sigward S. Measuring Lower Extremity Strength in Older 
Adults: The Stability of Isokinetic versus 1RM Measures. Journal of Aging and Physical 
Activity. 2002;10(4):489-503. 
86. 
Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, et 
al. A short physical performance battery assessing lower extremity function: association 
with self-reported disability and prediction of mortality and nursing home admission. 
Journal of gerontology. 1994;49(2):M85-94. 
87. 
Podsiadlo D, Richardson S. The timed "Up & Go": a test of basic functional 
mobility for frail elderly persons. Journal of the American Geriatrics Society. 
1991;39(2):142-8. 
88. 
Jones CJ, Rikli RE, Beam WC. A 30-s chair-stand test as a measure of lower body 
strength in community-residing older adults. Research quarterly for exercise and sport. 
1999;70(2):113-9. 
89. 
Martinez-Velilla N, Casas-Herrero A, Zambom-Ferraresi F, Saez de Asteasu ML, 
Lucia A, Galbete A, et al. Effect of Exercise Intervention on Functional Decline in Very 

37 
 
Version 4 – 23, August 2021 
 
Elderly Patients During Acute Hospitalization: A Randomized Clinical Trial. JAMA 
Intern Med. 2019;179(1):28-36. 
90. 
Kortebein P, Symons TB, Ferrando A, Paddon-Jones D, Ronsen O, Protas E, et al. 
Functional impact of 10 days of bed rest in healthy older adults. J Gerontol A Biol Sci 
Med Sci. 2008;63(10):1076-81. 
91. 
Onder G, Penninx BW, Ferrucci L, Fried LP, Guralnik JM, Pahor M. Measures of 
physical performance and risk for progressive and catastrophic disability: results from the 
Women's Health and Aging Study. J Gerontol A Biol Sci Med Sci. 2005;60(1):74-9. 
92. 
Guralnik JM, Winograd CH. Physical performance measures in the assessment of 
older persons. Aging. 1994;6(5):303-5. 
93. 
Ostir GV, Volpato S, Fried LP, Chaves P, Guralnik JM, Women's H, et al. 
Reliability and sensitivity to change assessed for a summary measure of lower body 
function: results from the Women's Health and Aging Study. Journal of clinical 
epidemiology. 2002;55(9):916-21. 
94. 
Graham BL, Steenbruggen I, Miller MR, Barjaktarevic IZ, Cooper BG, Hall GL, 
et al. Standardization of Spirometry 2019 Update. An Official American Thoracic Society 
and European Respiratory Society Technical Statement. Am J Respir Crit Care Med. 
2019;200(8):e70-e88. 
95. 
American Thoracic S, American College of Chest P. ATS/ACCP Statement on 
cardiopulmonary exercise testing. Am J Respir Crit Care Med. 2003;167(2):211-77. 
96. 
Moshfegh AJ, Rhodes DG, Baer DJ, Murayi T, Clemens JC, Rumpler WV, et al. 
The US Department of Agriculture Automated Multiple-Pass Method reduces bias in the 
collection of energy intakes. The American journal of clinical nutrition. 2008;88(2):324-
32. 
97. 
Polacow VO, Scagliusi FB, Lancha Junior AH. Validation of a portion-size 
measurement aid in a brazilian sample.  International Conference on Dietary Assessment 
Methods - Expanding the Horizon: Dietary Assessment in a Multi-Cultural World: 
Institute of Nutrition; 2003. 
98. 
Scagliusi FB, Polacow VO, Artioli GG, Benatti FB, Lancha AH, Jr. Selective 
underreporting of energy intake in women: magnitude, determinants, and effect of 
training. Journal of the American Dietetic Association. 2003;103(10):1306-13. 
99. 
Hess MA. Portion photos of popular foods: American Dietetic Association; 1997. 
100. 
Paglia DE, Valentine WN. Studies on the quantitative and qualitative 
characterization of erythrocyte glutathione peroxidase. J Lab Clin Med. 1967;70(1):158-
69. 
101. 
Conti M, Morand P, Levillain P, Lemonnier AJCc. Improved fluorometric 
determination of malonaldehyde. 1991;37(7):1273-5. 
102. 
Vasikaran S, Cooper C, Eastell R, Griesmacher A, Morris HA, Trenti T, et al. 
International Osteoporosis Foundation and International Federation of Clinical Chemistry 
and Laboratory Medicine position on bone marker standards in osteoporosis. Clinical 
chemistry and laboratory medicine. 2011;49(8):1271-4. 
103. 
Matsuda M, DeFronzo RA. Insulin sensitivity indices obtained from oral glucose 
tolerance testing: comparison with the euglycemic insulin clamp. Diabetes care. 
1999;22(9):1462-70. 
104. 
Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. 
Homeostasis model assessment: insulin resistance and beta-cell function from fasting 
plasma glucose and insulin concentrations in man. Diabetologia. 1985;28(7):412-9. 
105. 
Voytas D. Agarose gel electrophoresis. Current protocols in neuroscience. 
2001;Appendix 1:Appendix 1N. 

38 
 
Version 4 – 23, August 2021 
 
106. 
Lee PY, Costumbrado J, Hsu CY, Kim YH. Agarose gel electrophoresis for the 
separation of DNA fragments. Journal of visualized experiments : JoVE. 2012(62). 
107. 
Cawthon RM. Telomere measurement by quantitative PCR. Nucleic acids 
research. 2002;30(10):e47. 
108. 
Scheinberg P, Cooper JN, Sloand EM, Wu CO, Calado RT, Young NS. Association 
of telomere length of peripheral blood leukocytes with hematopoietic relapse, malignant 
transformation, and survival in severe aplastic anemia. JAMA. 2010;304(12):1358-64. 
109. 
Ware JEJHI. SF-36 health survey: manual and interpretation guide. 1993. 
110. 
Bertolazi AN, Fagondes SC, Hoff LS, Dartora EG, Miozzo IC, de Barba ME, et 
al. Validation of the Brazilian Portuguese version of the Pittsburgh Sleep Quality Index. 
Sleep medicine. 2011;12(1):70-5. 
111. 
Yesavage JA, Brink TL, Rose TL, Lum O, Huang V, Adey M, et al. Development 
and validation of a geriatric depression screening scale: a preliminary report. Journal of 
psychiatric research. 1982;17(1):37-49. 
112. 
Burke WJ, Roccaforte WH, Wengel SP. The short form of the Geriatric Depression 
Scale: a comparison with the 30-item form. Journal of geriatric psychiatry and neurology. 
1991;4(3):173-8. 
113. 
Pachana NA, Byrne GJ, Siddle H, Koloski N, Harley E, Arnold E. Development 
and validation of the Geriatric Anxiety Inventory. International psychogeriatrics. 
2007;19(1):103-14. 
114. 
Bowie CR, Harvey PD. Administration and interpretation of the Trail Making 
Test. Nature protocols. 2006;1(5):2277-81. 
115. 
Duncan MT. Obtenção de dados normativos para desempenho no teste de Stroop 
num grupo de estudantes do ensino fundamental em Niterói. [Assessment of normative 
data of Stroop test performance in a group of elementary school students in Niterói.]. 
Jornal Brasileiro de Psiquiatria. 2006;55(1):42-8. 
116. 
Campanholo KR, Romao MA, Machado MAR, Serrao VT, Coutinho DGC, 
Benute GRG, et al. Performance of an adult Brazilian sample on the Trail Making Test 
and Stroop Test. Dementia & neuropsychologia. 2014;8(1):26-31. 
117. 
Villareal DT, Apovian CM, Kushner RF, Klein S, American Society for N, Naaso 
TOS. Obesity in older adults: technical review and position statement of the American 
Society for Nutrition and NAASO, The Obesity Society. The American journal of clinical 
nutrition. 2005;82(5):923-34. 
118. 
American College of Sports M, Chodzko-Zajko WJ, Proctor DN, Fiatarone Singh 
MA, Minson CT, Nigg CR, et al. American College of Sports Medicine position stand. 
Exercise and physical activity for older adults. Med Sci Sports Exerc. 2009;41(7):1510-
30. 
119. 
Fragala MS, Cadore EL, Dorgo S, Izquierdo M, Kraemer WJ, Peterson MD, et al. 
Resistance Training for Older Adults: Position Statement From the National Strength and 
Conditioning Association. J Strength Cond Res. 2019;33(8):2019-52. 
120. 
Borg GA. Psychophysical bases of perceived exertion. Med Sci Sports Exerc. 
1982;14(5):377-81. 
121. 
Barroso WKS, Rodrigues CIS, Bortolotto LA, Mota-Gomes MA, Brandao AA, 
Feitosa ADM, et al. Brazilian Guidelines of Hypertension - 2020. Arquivos brasileiros de 
cardiologia. 2021;116(3):516-658. 
122. 
Pelliccia A, Sharma S, Gati S, Back M, Borjesson M, Caselli S, et al. 2020 ESC 
Guidelines on sports cardiology and exercise in patients with cardiovascular disease. 
European heart journal. 2021;42(1):17-96. 

39 
 
Version 4 – 23, August 2021 
 
123. 
Colberg SR, Sigal RJ, Yardley JE, Riddell MC, Dunstan DW, Dempsey PC, et al. 
Physical Activity/Exercise and Diabetes: A Position Statement of the American Diabetes 
Association. Diabetes care. 2016;39(11):2065-79. 
124. 
Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and 
Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society: Series B 
(Methodological). 1995;57(1):289-300. 
125. 
Ugrinowitsch C, Fellingham GW, Ricard MD. Limitations of ordinary least 
squares models in analyzing repeated measures data. Med Sci Sports Exerc. 
2004;36(12):2144-8. 
126. 
Gadbury GL, Coffey CS, Allison DB. Modern statistical methods for handling 
missing repeated measurements in obesity trial data: beyond LOCF. Obesity reviews : an 
official journal of the International Association for the Study of Obesity. 2003;4(3):175-
84.