Abstract
Background
Sarcopenia, characterized by the progressive loss of skeletal muscle mass and strength in older adults, is a key determinant of frailty and functional decline. Affecting up to 15% of individuals aged 65–80 years and more than 50% of those over 80, sarcopenia not only compromises physical autonomy but also increases the risk of metabolic dysfunction and cognitive decline. Emerging evidence suggests that age-related gut microbiota dysbiosis contributes to these impairments by reducing microbial diversity and altering host metabolic signaling, leading to chronic inflammation and mitochondrial dysfunction. The present study aims to evaluate the safety, tolerability, and preliminary efficacy of oral fecal microbiota transplantation derived from young, physically active donors administered to older adults, focusing on outcomes related to functional autonomy, muscle performance, metabolism and cognition.
Methods
This is a double-blind, randomized, placebo-controlled clinical trial involving community-dwelling adults aged 65–84 years. Participants will be randomized 1:1 to receive either FMT capsules or placebo following a short course of oral rifaximin (or placebo). Assessments will be performed at baseline and at 4, 8, and 20 weeks post-intervention. The primary outcomes are safety and tolerability, as well as changes in the Global Index of Functional Autonomy (GDLAM battery) and muscle strength. Secondary outcomes include gait speed, body composition (DXA), metabolic biomarkers, gut microbiota composition (shotgun metagenomics), cognitive performance, and psychological well-being.
Expected impact
By restoring microbial diversity and function, FMT from young, active donors may enhance muscle quality, cognitive resilience, and metabolic health in older adults. This study introduces a novel, non-invasive therapeutic approach based on lyophilized and encapsulated microbiota, offering a feasible and scalable strategy to promote healthy aging.
Trial registration
ClinicalTrials.gov NCT06649981. Date of registration October 21, 2024.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12877-025-06920-7.
Keywords: Gut microbiome, Aging, Fecal microbiota transplantation, Frailty, Functional autonomy
Background
Sarcopenia is a progressive skeletal muscle disorder characterized by the loss of muscle mass and strength, leading to disability, frailty, and increased mortality [1]. Its prevalence reaches approximately 15% among adults aged 65–80 years and exceeds 50% in those over 80 [2], making it a critical determinant of health decline in older age [3]. Beyond mobility impairment and fracture risk [4, 5], sarcopenia is linked to cardiometabolic diseases [6, 7], cognitive decline [8], and increased hospital admissions and healthcare costs [9, 10]. Preserving muscle health is therefore essential to sustain autonomy, resilience, and well-being in older adults.
Aging is characterized not only by progressive biological deterioration but also by a reduction in physiological resilience, the capacity to recover from stressors and maintain homeostasis. Declines in neuromuscular, metabolic, and immunological systems diminish the ability of older adults to withstand acute challenges such as illness, inactivity, or nutritional deficits. Reduced resilience contributes to the transition from robustness to frailty, amplifying vulnerability to sarcopenia, falls, hospitalization, and mortality. Within this framework, interventions that strengthen physiological resilience may hold particular promise for delaying or mitigating age-related functional decline.
Aging is also associated with profound alterations in gut microbiota composition. Older adults typically exhibit reduced microbial diversity, loss of beneficial taxa, expansion of opportunistic pathogens, and decreased stability or resilience of the microbial ecosystem [11–14]. These age-related shifts disrupt immunometabolic homeostasis and have been linked to frailty, impaired physical function, chronic inflammation, and increased risk of infectio [15–20]. Such findings support the concept of a gut–muscle axis, whereby microbial metabolites, immune signaling, and gut barrier integrity influence muscle metabolism and systemic inflammation.
Fecal microbiota transplantation (FMT) has proven highly effective in recurrent Clostridioides difficile infection [21–24] and is increasingly recognized as a promising strategy to restore gut microbial balance in age-related conditions. Given the multifactorial nature of sarcopenia, recent research has explored the gut microbiota as a potential modulator of muscle metabolism and systemic inflammation. Alterations in gut microbial composition can influence host energy balance, nutrient absorption, and immune regulation through the production of metabolites such as short-chain fatty acids (SCFAs), which enhance insulin sensitivity, mitochondrial biogenesis, and anti-inflammatory pathways [25–30]. Conversely, the chronic low-grade inflammation of aging (“inflammaging”) contributes to muscle atrophy [31–35], cognitive decline [36–39], and metabolic dysfunction [40, 41]. These findings have led to the conceptualization of the gut–muscle axis as a critical pathway in the pathophysiology of sarcopenia and a potential target for therapeutic intervention. Importantly, sarcopenia is increasingly recognized as a systemic condition, affecting not only mobility but also cognition [37] and metabolic health [42], including metabolic dysfunction-associated steatotic liver disease (MASLD) [43, 44], through shared mechanisms such as inflammation [39, 40], insulin resistance [42, 45], and altered muscle-derived endocrine signaling [46, 47].
Donors in this study will be young, physically active individuals. The rationale for selecting trained donors is based on growing evidence that physical exercise significantly shapes gut microbiota composition, forming a healthy microbiota profile. Animal studies have demonstrated that chronic exercise not only increases microbial diversity but also reduces both systemic and intestinal inflammation [48]. Importantly, the microbiota profile induced by exercise differs from that driven by diet alone, suggesting that physical activity promotes the development of a distinct microbial community with unique functional characteristics [49]. Exercise-induced microbial changes have been linked to improved intestinal barrier integrity and enhanced host metabolic function [14, 15, 50]. In humans, higher gut microbial diversity has consistently been observed in athletes compared with sedentary individuals, even after adjusting for age, sex, and body weight [14, 51]. Moreover, regular physical activity has been reported to restore a healthier microbiota composition in individuals with dysbiosis [52].
Together, this evidence suggests that the microbiota of physically active young donors may represent an optimal source for FMT, offering anti-inflammatory and metabolic benefits that could be particularly relevant for counteracting sarcopenia and age-related functional decline. Building on this rationale, the ARMOR (Aging Resilience Through Microbiota Optimization and Regulation) study aims to determinate whether FMT from young, trained donors can improve skeletal muscle function in older adults, thereby enhancing resilience and reducing cognitive and metabolic impairments associated with aging.
Methods and design
Study design
This study will be a single-center, randomized, double-blind, placebo-controlled, parallel-group trial (RCT) designed to evaluate the safety, feasibility, and preliminary efficacy of FMT from young physically trained donors to older adults. The trial has been registered at ClinicalTrials.gov (Identifier: NCT06649981|| https://clinicaltrials.gov/study/NCT06649981 || official title: Aging Resilience Through Microbiota Optimization and Regulation [ARMOR]) with the registration posted on October 21, 2024.
All evaluations will take place at the Institute of Nutrition and Food Technology (INTA), Universidad de Chile. However, administration of capsules will be carried out at The Clinical Trial Unit of Clínica Universidad de Los Andes. The study includes a total of seven visits, with evaluations conducted at four key time points: baseline, and at 4, 8, and 20 weeks after the FMT (Fig. 1). Each visit is described in detail below.
Fig. 1.
Schedule of visits and assessments for clinical trial participants
V0 (Screening and Informed Consent): participants are briefed on study procedures, provide written informed consent, and eligibility is confirmed based on inclusion and exclusion criteria.
V1 (Baseline, Pre-FMT): Participants undergo comprehensive assessments, including clinical blood tests, bone densitometry, body composition analysis, abdominal, muscle, and carotid ultrasound, and indirect calorimetry. Cognitive and psychological evaluations, assessment of autonomy and functional capacity, and dietary intake using a food frequency questionnaire are also conducted. Serum and stool samples are collected. Physical activity and sleep quality are monitored via accelerometer for 1 week.
V2 (Capsule Administration): Prior to capsule administration, participants will take the antibiotic rifaximin for three consecutive days (1.2 g per day) to transiently reduce intestinal bacterial load. Participants assigned to the placebo group will receive a matching placebo for the antibiotic. After completing this pre-treatment phase, FMT or placebo capsules are administered under supervision at The Clinical Trial Unit in Clínica Universidad de los Andes.
V3 (Week 1 Post-FMT): A telephone follow-up is conducted to monitor potential adverse events following capsule administration.
V4 (Week 4 Post-FMT): Follow-up assessments include blood tests, muscle and carotid ultrasound, cognitive and psychosocial evaluations, and assessment of autonomy and functional capacity. Serum and stool samples are collected.
V5 (Week 8 Post-FMT): The same procedures as in V1 are repeated to monitor mid-term effects. In addition, a 24-hour dietary recall is conducted to assess recent dietary intake. Only serum samples are collected.
V6 (Week 20 Post-FMT – Final Evaluation): repeats the full battery of baseline evaluations to monitor long-term outcomes and ensure participant safety.
Recruitment and participants
Participants will include community-dwelling older adults aged 65–84 years. Recruitment will be conducted through public dissemination using posters, telephone invitations, and communication with primary care centers (CESFAM), targeting individuals from different municipalities within the Santiago Metropolitan Area in Chile. All inclusion and exclusion criteria are detailed in Table 1.
Table 1.
Eligibility criteria
| Inclusion Criteria | Exclusion Criteria |
|---|---|
| Community-dwelling adults aged 65–84 years | Systolic blood pressure ≥ 180 mmHg or diastolic blood pressure ≥ 110 mmHg at screening |
| Unintentional body weight change < 10% within the last 6 months | Allergy to rifaximin |
| Self-sufficient (Barthel Index score > 60) | Acute infection or inflammatory condition within the past 4 weeks |
| Fasting plasma glucose ≤ 7.2 mmol/L or HbA1c ≤ 8% within the last 6 months | Use of antibiotics or probiotics within the past 12 weeks |
| Ability to swallow capsules safely | Hospitalization within the past 12 weeks |
| Current or recent (within 6 months) insulin use | |
| Difficulty swallowing (dysphagia) | |
| Diagnosis of inflammatory bowel disease, Crohn’s disease, ulcerative colitis, Clostridioides difficile infection, or colon cancer | |
| Treatment with immunosuppressive therapy for organ transplantationDiagnosis of leukemia, lymphoma, or mesenchymal diseases (except osteoarthritis) | |
| Current corticosteroid or biological therapy use | |
| History of autoimmune or chronic inflammatory conditions (e.g., rheumatoid arthritis, chronic or active hepatitis B/C, HIV, pancreatitis, or liver cirrhosis) | |
| Active malignancy | |
| Current drug or alcohol abuse (more than three drinks per day or seven per week) | |
| Diagnosis of dementia |
Sample size
Assuming an expected 15% difference in handgrip strength (measured by dynamometry) between the FMT and placebo groups, with a 1:1 randomization ratio (FMT vs. placebo), we estimated that a total of 80 participants (40 per study arm) would provide 80% power to detect the primary outcome at a two-sided alpha level of 0.05. Sample size was calculated using the mean and standard deviation of handgrip strength reported by [53].
Randomization and allocation concealment
Participants will be randomly assigned in a 1:1 ratio to the FMT or placebo group using a centralized, computer-generated allocation sequence created by an independent statistician. Randomization will use permuted blocks of variable size to maintain balance between groups while preserving allocation concealment. The sequence will be implemented through the REDCap Randomization Module, which ensures secure, real-time allocation and prevents prediction of upcoming assignments. Access to the randomization module will be restricted to the unblinded allocation manager, who will have no involvement in participant recruitment, clinical assessments, or data analysis. Randomization will occur only after verification of eligibility at the baseline visit. All study personnel, including investigators, participants, outcome assessors, and data analysts, will remain blinded to treatment allocation until database lock.
Intervention
Donor selection and screening
FMT donors will be healthy adults aged 20–35 years with a body mass index (BMI) of 20–25 kg/m², an ECOG (Eastern Cooperative Oncology Group) performance status of 0, and a metabolic equivalent (MET) ≥ 600 min per week, reflecting a physically active and metabolically healthy profile. Donors must engage in at least 150 min of high-intensity aerobic exercise weekly.
Candidates will undergo comprehensive medical, lifestyle, and laboratory screening. Exclusion criteria include chronic gastrointestinal, autoimmune, metabolic, neurological, psychiatric, or malignant diseases; recent gastrointestinal surgery (except appendectomy); use of antibiotics or proton-pump inhibitors within the previous 3 months; recreational drug use; excessive alcohol intake; recent hospitalization or surgery; pregnancy; BMI > 30 kg/m²; metabolic syndrome; and severe allergies.
All donors will be screened for transmissible pathogens. Blood tests will include complete blood count, biochemistry, liver and thyroid function, lipid and glucose profiles, and serology for HIV, HBV, HCV, HAV, HEV, HTLV I/II, Treponema pallidum, and Mycobacterium tuberculosis. Stool tests will detect bacterial, viral, and parasitic pathogens, including Clostridioides difficile, Helicobacter pylori, Salmonella spp., Shigella spp., Campylobacter spp., Giardia lamblia, Norovirus, and Rotavirus, as well as multidrug-resistant organisms. Only donors with negative results and no epidemiological risk factors will be accepted. Written informed consent will be obtained from all donors.
Capsule preparation and quality control
All FMT preparations will be processed under sterile conditions within a biosafety cabinet (Class II). To ensure traceability and process control, aliquots of the fecal material will be collected at three stages: (1) raw fecal sample (2), post-processing suspension (pre–freeze-drying), and (3) final freeze-dried product.
Sample Processing
On the day of donation, the donor questionnaire will be reviewed for completeness and accuracy. If any exclusion criteria are met, the donation will be discarded. Each sample will be verified for correct donor identification, collection date, and macroscopic characteristics (appearance and consistency). Diarrheic or excessively hard stools, or those containing visible foreign material, will be discarded.
Each stool sample will be homogenized in sterile 0.9% saline and glycerol (final concentration: saline in a 1:5 ratio relative to feces; glycerol corresponding to 30% of the saline volume). The mixture will be prepared in sterile glassware and inverted several times to ensure uniform blending.
Approximately 400 mL of this saline–glycerol solution will be added to the stool sample placed in a Stomacher bag, allowing hydration for 30 min. The mixture will then be homogenized using a Stomacher device at 230 rpm for 1 min, repeated as needed until a uniform suspension is obtained. The homogenate will be filtered through a sterile sieve to remove large particles (seeds and fibers), and the remaining saline–glycerol solution will be used to rinse the sieve to maximize yield.
The filtrate will be distributed into 50 mL centrifuge tubes (≤ 40 mL per tube) and centrifuged at 4 °C for 20 min at 1600 rpm. The supernatant will be carefully collected and re-centrifuged at 8300 rpm for 20 min at 4 °C. The final pellet will be recovered using sterile spatulas, transferred to sterile Petri dishes, and frozen at − 80 °C for at least 30 min prior to freeze-drying.
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2.
Freeze-Drying and Encapsulation.
Freeze-drying will be performed using a Labconco lyophilizer set to − 50 °C under automatic mode and run overnight. Once complete, the chamber will be vented gradually to prevent product dispersal, and the dried material will be collected into sterile ziplock bags for storage until encapsulation.
An aliquot of the freeze-dried material will be stored for microbiological and quality control analyses. For encapsulation, the lyophilized product will be gently loosened using a sterile spatula and manually filled into acid-resistant, opaque capsules (size 00). Capsules will be tightly packed to ensure consistent dosing.
Finished capsules will be stored in sealed, properly labeled containers at 4 °C, with a desiccant to prevent moisture absorption.
Intervention administration
Prior to FMT, all participants will receive a short course of the non-absorbable antibiotic rifaximin to reduce resident intestinal bacterial load and facilitate engraftment of donor microbiota. Participants will take rifaximin 200 mg, two tablets three times daily for three consecutive days before FMT administration. Participants in the placebo group will receive placebo tablets identical in appearance and dosage schedule to maintain blinding.
On the day of intervention, participants assigned to the FMT group will receive four capsules containing lyophilized fecal microbiota. Each capsule contains 600 mg of freeze-dried product, for a total dose of 2.4 g administered orally in a single session under supervision by trained study personnel. Capsules are acid-resistant and opaque to preserve bacterial viability and ensure blinding. Participants assigned to the placebo group will receive an equivalent number of capsules identical in appearance, size, and weight, containing the inert excipient matrix without microbiota. Both FMT and placebo capsules will be stored at 4 °C and transported in temperature-controlled conditions to the clinical site for administration.
Vital signs (blood pressure, heart rate, respiratory rate, and temperature) will be measured immediately before and 30 min after capsule administration to monitor acute physiological responses. Following ingestion, all participants will be observed for at least 30 min to detect potential immediate adverse effects such as nausea, vomiting, or abdominal discomfort. Participants will also be instructed to report any delayed gastrointestinal or systemic symptoms within 48 h and at subsequent follow-up visits.
Outcomes measures
Primary outcomes
Handgrip Strength Assessment
Handgrip strength will be assessed as a primary outcome measure of muscle function and overall physical performance. Measurements will be obtained using a calibrated Jamar hydraulic hand dynamometer (Model J00105) following standardized protocols. Participants will perform the test in a seated position with the elbow flexed at 90°, wrist in a neutral position, and the arm unsupported. The dynamometer offers five adjustable handle positions to accommodate different hand sizes; therefore, the handle will be individually set for each participant to ensure optimal finger flexion and a secure grip [54]. Two trials will be conducted for each hand, alternating sides, with a brief rest between attempts. The highest value (kg) from the dominant hand will be recorded for analysis.
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2.
Functional autonomy
Functional autonomy will be evaluated using the Global Index (GI) of the GDLAM (Latin American Group for Maturity) battery, according to the instructions published in 2024 for the Chilean population [55].
The GDLAM battery evaluates the ability to perform activities of daily living independently through five physical performance tests:
10-meter walk test (W10 m): Time to walk 10 meters from a standing start.
Sit-to-stand test (SSP): Time to stand up five times consecutively from a chair.
Supine-to-stand test (SPP): Time required to stand up from a prone position.
Agility test with cone circuit (SCMA): Time to complete a 4-meter diagonal circuit around cones from a seated start position.
Shirt test (PTS): Time required to put on and remove a T-shirt while standing.
Each subtest records time in seconds, with 5-minute rest intervals between tests. The Global Index (GI) of functional autonomy is then computed using the following formula:
![]() |
Lower GI values indicate better functional autonomy and greater independence in daily activities. The GI provides a composite measure integrating mobility, strength, balance, and coordination, and will be evaluated at baseline 4-, 8- and 20-weeks post-intervention.
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3.
Safety and tolerability of oral FMT
The primary safety outcome will be the incidence of adverse events (AEs) and serious adverse events (SAEs) over 20 weeks following intervention. Safety monitoring will include assessment of vital signs (blood pressure, heart rate, respiratory rate, and temperature) immediately before and after capsule administration, and at each subsequent study visit (weeks 4, 8, and 20). Tolerability will be evaluated based on the occurrence, duration, and severity of gastrointestinal symptoms or other related adverse effects, recorded through clinical interviews.
Secondary outcomes
Clinical examinations
Blood samples will be collected in the early morning after an overnight fast of 8 to 12 hours to conduct the biochemical and hormonal analyses outlined in Table 2. Participants will also be asked to provide a stool sample for microbiome and metabolite analysis. During the same visit, two ultrasound assessments will be performed: a) a carotid ultrasound will be conducted to determine carotid intima–media thickness, and b) an abdominal ultrasound will evaluate hepatic steatosis using the Hamaguchi Score, which assesses hepatorenal echo contrast to assess liver brightness, deep attenuation assessing diaphragm blurring, and intrahepatic vessel colapse .Liver brightness and hepatorenal contrast are evaluated together. If both bright liver and hepatorenal contrast are negative, the final score is 0. Deep attenuation is scored from 0 to 2, while vessel blurring can either be positive (score of 1) or negative (score of 0). Therefore, the total Hamaguchi score ranges from 0 to 6 [56].
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Frailty
Table 2.
Biological Materials, collection Procedures, and clinical and laboratory outcomes
| Type of Material | Collection | Procedure | Outcomes / Analytes |
|---|---|---|---|
| Blood | Venipuncture (fasting) | Hemogram and blood count | Red blood cells, white blood cells, hemoglobin, hematocrit, platelets, MCV, MCH, MCHC, RDW, differential count (neutrophils, lymphocytes, monocytes, eosinophils, basophils) |
| Biochemical profile | Uric acid, albumin, total bilirubin, calcium, total cholesterol, lactate dehydrogenase (LDH), alkaline phosphatase, glucose, phosphorus, total proteins, AST (GOT) | ||
| Renal function | Serum creatinine, estimated glomerular filtration rate (eGFR), urea | ||
| Muscle enzymes | Creatine kinase (CK), lactate | ||
| Inflammatory markers | C-reactive protein (CRP) | ||
| Endocrine and metabolic hormones | Insulin, HOMA-IR, thyroid-stimulating hormone (TSH), insulin-like growth factor-1 (IGF-1) | ||
| Lipid profile | HDL, LDL, VLDL cholesterol, triglycerides, total cholesterol, cholesterol/HDL ratio, cholesterol/triglyceride ratio | ||
| Liver function tests | Direct bilirubin, indirect bilirubin, alkaline phosphatase, ALT (GPT), GGT | ||
| Electrolytes | Sodium, potassium, chloride | ||
| Micronutrients and metabolites | Vitamin B12, 25-OH vitamin D, homocysteine | ||
| Sample storage | Serum aliquots stored at − 80 °C in cryovials for future analyses | ||
| PBMC isolation | Peripheral blood mononuclear cells (PBMCs) isolated by Ficoll density gradient centrifugation and stored at − 80 °C | ||
| PBMC analyses | Evaluation of autophagy (LC3-II, p62) and inflammation markers (IL-6, TNF-α, IL-1β); high-resolution respirometry (oxigraphy) to assess mitochondrial function | ||
| Stool | Fresh stool collection | Microbiome analysis | Shotgun metagenomic sequencing for comprehensive taxonomic and functional profiling, including assessment of microbial diversity (alpha and beta), gene content and metabolic pathways |
| Storage | Stool aliquots stored at − 80 °C for DNA extraction and microbial metabolite analysis |
Frailty will be evaluated using two complementary approaches: a combined Frailty Index (FI-combined) [57] and a phenotypic frailty model [58]. The combined FI integrates both self-reported clinical deficits and laboratory parameters. The self-reported FI will include 30 variables assessing health status across multiple domains: chronic diseases, symptoms, disabilities in daily living, psychological problems, balance (Romberg test), physical performance, depressive symptoms (Geriatric Depression Scale, GDS), and cognitive function (Mini-Mental State Examination, MMSE). Binary variables will be coded as 0 (absent) or 1 (present), while ordinal variables will be assigned intermediate scores (0.5). The MMSE will be coded as 0 if >23, 0.5 if 15–23, and 1 if ≤14; the GDS will be coded as 0 if <11 and 1 if ≥11. The laboratory-based FI (FI-lab) will include 15 parameters derived from nine biochemical tests, together with vital signs (heart rate, systolic and diastolic blood pressure, pulse pressure) and anthropometric measures (BMI and waist circumference). Each variable will be coded as 0 when within the normal reference range and 1 when outside the range. The combined FI will then be computed as the sum of deficits divided by the total number of variables (n = 45), yielding a continuous score from 0 (no deficits) to 1.0 (all deficits present).Additionally, frailty will be assessed using the Fried Phenotype (FP) model, which includes five criteria: unintentional weight loss, self-reported exhaustion, weakness (handgrip strength), slowness (gait speed), and low physical activity. Participants will be categorized as robust (0 criteria), prefrail (1–2 criteria), or frail (3–5 criteria) [58]. The determination of muscle weakness will be based on validated cut-off points established for the Chilean older adult population, in alignment with both regional and international guidelines for sarcopenia screening. Specifically, muscle weakness will be defined as a handgrip strength measurement below 27 kg for men and below 15 kg for women [59].
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3.
Cognitive and Psychological Assessments
Cognitive performance will be evaluated before and after the FMT intervention to assess higher-order cognitive abilities, including attention, executive function, working memory, language, memory, and processing speed. All assessments will be administered by trained psychologists in a quiet environment following standardized neuropsychological testing procedures.
The Mini-Mental State Examination (MMSE) [60] will be used as a general screening tool to evaluate global cognitive function, covering orientation, immediate and delayed recall, attention and calculation, language, and visuoconstructional skills.
The Trail Making Test (TMT) Parts A and B [61] will assess processing speed, visual attention, and cognitive flexibility. Part A measures psychomotor speed and visual scanning, while Part B evaluates executive control and task-switching ability.
The Verbal Fluency Test (FAS) [62] will assess lexical access, language production, and executive retrieval strategies, by requiring participants to generate as many words as possible beginning with a given letter within one minute
The Digit Span Test (forward and backward) [63], from the Wechsler Adult Intelligence Scale, will assess attention span and working memory capacity. The forward condition primarily evaluates short-term auditory memory, while the backward condition requires manipulation and sequencing of information, reflecting executive functioning.
The Frontal Assessment Battery (FAB) [64] will evaluate executive functions related to frontal lobe activity, including conceptualization, mental flexibility, motor programming, inhibitory control, and autonomy of action.
Mental health and mood status will be evaluated using validated self-report instruments administered by trained psychologists. The Perceived Stress Scale (PSS-14) [65, 66] will be used to assess the degree to which participants perceive situations in their lives as stressful, capturing cognitive and emotional responses to daily stressors. Depressive symptoms will be evaluated using the 15-item Geriatric Depression Scale (GDS-15) [67, 68], a tool specifically designed to detect mood disturbances and depressive symptoms commonly experienced in older adults. Anxiety symptoms will be assessed using the Beck Anxiety Inventory (BAI) [69], which provides a measure of physiological and cognitive manifestations of anxiety that is relatively independent from depressive symptoms.
In addition, psychological well-being will be assessed through the Ryff Psychological Well-Being Scale [70], focusing on the Purpose in Life subscale, as well as the Satisfaction with Life Scale (SWLS) [71] and the Subjective Happiness Scale (Lyubomirsky & Lepper) [72], to evaluate positive psychological functioning, life satisfaction, and perceived happiness.
Finally, participants will complete a Psychosocial Determinants of Health Questionnaire, designed to explore their life history, social context, and psychological factors that may influence health status and resilience in aging.
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4.
Anthropometry, body composition, and nutritional assessment
Body mass and height will be measured to the nearest 0.1 kg and 0.01 m, respectively, using a calibrated scale and stadiometer. Body mass index (BMI) will be calculated as body mass divided by height squared (kg•m⁻²). In addition, waist, hip, and calf circumferences will be measured with an inelastic anthropometric tape a 201 SECA ergonomic circumference measuring tape to evaluate adiposity. All anthropometric measurements will be obtained following standardized procedures by the same nutritionist throughout the study to minimize inter-observer variability.
Body composition will be assessed by dual-energy X-ray absorptiometry (DXA) using a Lunar IDXA (GE Medical Systems, Madison, Wi, USA). Participants will lie in the supine position, centered on the scanning table, with arms slightly abducted from the trunk. DXA provides quantitative measures of fat mass and fat-free mass (g) for the whole body and specific regions (arms, legs, and trunk). DXA will also be used to assess bone mineral density (BMD) at the lumbar spine and femoral neck. All scans will be performed using the same DXA device and software version General Electric software version 13.6 to ensure comparability. An adequate hydration status will be confirmed clinically prior to the examination.
Finally, dietary intake will be assessed using a Quantified Food Consumption Tendency Questionnaire (Q-FCTQ) with a 7-day recall period. This instrument was designed to evaluate the habitual consumption of standard food items, while also including a specific focus on probiotic-rich food sources. These sources encompassed a range of commercially available products and traditional fermented foods, such as probiotic-added dairy drinks, kefir, and kombucha. To facilitate the precise quantification of food portions consumed, the Food Portion Photographic Atlas validated and used in the Chilean National Food Consumption Survey (ENCA) will be utilized [73]. This atlas, which contains visual representations of standardized portion sizes, will be employed by the interviewer to guide the participant's estimation of their habitual intake amount. Subsequently, the reported portions will be converted into grams or milliliters using the standardized equivalence table accompanying the atlas, thus ensuring the objectivity and comparability of the consumption data. These data will be used to explore potential associations between nutritional patterns, body composition, and bone and metabolic outcomes.
Statistical analysis
Within the framework of this clinical trial, statistical analyses will be conducted according to the pre-specified Statistical Analysis Plan (SAP) and will follow an intention-to-treat (ITT) principle, with additional per-protocol (PP) analyses performed as sensitivity assessments. Continuous variables will be summarized using means and standard deviations or medians with interquartile ranges (25th–75th percentile), depending on distributional assumptions evaluated through standard diagnostics. Categorical variables will be described using absolute and relative frequencies. For the primary and secondary continuous outcomes, changes from baseline across follow-up visits (weeks 4, 8, and 20) will be analyzed using mixed-effects models for repeated measures (MMRM), including fixed effects for treatment, visit, and treatment-by-visit interaction, and adjusting for baseline values and key covariates (age, sex, BMI). This approach accounts for within-participant correlation and allows for valid inference under missing-at-random assumptions without explicit imputation. For categorical endpoints, generalized linear mixed models will be used, whereas χ² or Fisher’s exact tests will describe simple comparisons of proportions. Estimates of treatment effect will be reported as adjusted mean differences, odds ratios, relative risks, or risk differences with corresponding 95% confidence intervals.
Microbiome analyses will be performed according to dedicated procedures described in the SAP, including diversity metrics (Shannon index, beta-diversity PERMANOVA), and differential abundance analyses using ANCOM-BC with false discovery rate control at q = 0.05. High-dimensional exploratory models (e.g., MaAsLin2) will be used to investigate associations between microbial features and changes in muscle, cognitive, and metabolic outcomes. Sensitivity analyses will incorporate PP populations, alternative covariance structures, and multiple imputation to evaluate the robustness of results to assumptions about missing data. All analyses will be performed by the study biostatistics team at INTA to ensure methodological rigor, reproducibility, and adherence to ICH E9(R1) standards.
Expected impact
This clinical trial is expected to provide novel insights into the role of the gut microbiota in promoting healthy aging and functional independence among older adults. By transferring intestinal microbiota from young, physically active donors, this study introduces a pioneering, non-invasive therapeutic strategy aimed at restoring microbial diversity and metabolic functionality through the administration of lyophilized, encapsulated microbiota. The integration of multi-domain outcomes—including muscle performance, cognitive function, metabolic biomarkers, and microbiome composition—will allow a comprehensive evaluation of the systemic effects of microbiota modulation.
If proven safe and effective, this approach could represent a transformative intervention to counteract sarcopenia, cognitive decline, and metabolic derangements while promoting resilience and healthy aging in older adults. Moreover, the development of a standardized, stable, and scalable capsule-based FMT formulation could facilitate clinical translation and implementation in diverse healthcare settings. In the long term, this work aims to contribute to the development of microbiota-based therapies that enhance functional autonomy, resilience, and quality of life in older adults, addressing a major global public health challenge associated with population aging.
Supplementary Information
Acknowledgements
Not applicable.
Data sharing
De-identified individual participant data (including codebooks and statistical code) will be made available upon reasonable request to the corresponding author after publication of the main results. Data will be shared with qualified researchers for purposes of replicating analyses or conducting methodologically sound secondary analyses. All requests will require a data-sharing agreement to ensure protection of participant confidentiality.
Dissemination policy
In accordance with SPIRIT guidelines, our dissemination plan includes communicating trial results to participants, healthcare professionals, the public, and other relevant stakeholders through multiple channels, including posting results in the trial registry, providing a plain-language summary for participants, and disseminating findings through peer-reviewed publications and scientific presentations.
Authors’ contributions
CAG coordinated the clinical study, contributed to the overall study design, and prepared the protocol manuscript. AG designed the nutritional intake assessments, and DM developed the nutritional evaluations and frailty phenotype. CS designed the physical and functional assessments. LO designed the cognitive testing battery and DTD designed the psychological and affective components. RdC contributed to the study design and trained the team in capsule preparation. RBS performed PBMC respirometry analyses design. FJC and PJU contributed to the study design. FS contributed to geriatric and safety aspects. RQ and DB contributed to gastroenterology components and study design. RE served as the lead clinical researcher, providing major input into study design and clinical oversight. GJ, as principal investigator, led the scientific conceptualization, methodological supervision, and final approval of the protocol. All authors reviewed, provided critical feedback on the protocol design, and approved the final version of the manuscript.
Funding
This work is funded by The Wellcome Leap Dynamic Resilience program (co-funded by Temasek Trust). This study underwent external peer review prior to the award of funding.
The funder had no role in the design, data collection, analysis, interpretation, or decision to submit the protocol for publication.
Data availability
No datasets were generated or analysed during the current study.
Declarations
Ethics approval and consent to participate
The study protocol was approved by the Clinical Research Ethics Committee of Universidad de Los Andes (CEC2024000), Santiago, Chile. Participants enrolled to date have been fully informed of the potential risks and benefits and have provided written informed consent prior to participation. Recruitment is ongoing, and all additional participants will also provide written informed consent before enrollment.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyere O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48(1):16–31. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Marty E, Liu Y, Samuel A, Or O, Lane J. A review of sarcopenia: enhancing awareness of an increasingly prevalent disease. Bone. 2017;105:276–86. [DOI] [PubMed] [Google Scholar]
- 3.Mijnarends DM, Luiking YC, Halfens RJG, Evers S, Lenaerts ELA, Verlaan S, et al. Muscle, health and costs: A glance at their relationship. J Nutr Health Aging. 2018;22(7):766–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Miyakoshi N, Hongo M, Mizutani Y, Shimada Y. Prevalence of sarcopenia in Japanese women with osteopenia and osteoporosis. J Bone Min Metab. 2013;31(5):556–61. [DOI] [PubMed] [Google Scholar]
- 5.Go SW, Cha YH, Lee JA, Park HS. Association between Sarcopenia, bone Density, and Health-Related quality of life in Korean men. Korean J Fam Med. 2013;34(4):281–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Cleasby ME, Jamieson PM, Atherton PJ. Insulin resistance and sarcopenia: mechanistic links between common co-morbidities. J Endocrinol. 2016;229(2):R67–81. [DOI] [PubMed] [Google Scholar]
- 7.Alqahtani SA, Schattenberg JM. NAFLD in the elderly. Clin Interv Aging. 2021;16:1633–49. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Chang KV, Hsu TH, Wu WT, Huang KC, Han DS. Association between sarcopenia and cognitive impairment: A systematic review and Meta-Analysis. J Am Med Dir Assoc. 2016;17(12):1164. e7- e15. [DOI] [PubMed] [Google Scholar]
- 9.Cawthon PM, Lui LY, Taylor BC, McCulloch CE, Cauley JA, Lapidus J, et al. Clinical definitions of sarcopenia and risk of hospitalization in Community-Dwelling older men: the osteoporotic fractures in men study. J Gerontol Biol Sci Med Sci. 2017;72(10):1383–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Antunes AC, Araujo DA, Verissimo MT, Amaral TF. Sarcopenia and hospitalisation costs in older adults: a cross-sectional study. Nutr Diet. 2017;74(1):46–50. [DOI] [PubMed] [Google Scholar]
- 11.Nagpal R, Mainali R, Ahmadi S, Wang S, Singh R, Kavanagh K, et al. Gut Microbiome and aging: physiological and mechanistic insights. Nutr Healthy Aging. 2018;4(4):267–85. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Hou K, Wu ZX, Chen XY, Wang JQ, Zhang D, Xiao C, et al. Microbiota in health and diseases. Signal Transduct Target Ther. 2022;7(1):135. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Rajilic-Stojanovic M, de Vos WM. The first 1000 cultured species of the human Gastrointestinal microbiota. FEMS Microbiol Rev. 2014;38(5):996–1047. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Ticinesi A, Lauretani F, Milani C, Nouvenne A, Tana C, Del Rio D et al. Aging gut microbiota at the Cross-Road between Nutrition, physical Frailty, and sarcopenia: is there a gut-Muscle. Axis? Nutrients. 2017;9(12):1303. [DOI] [PMC free article] [PubMed]
- 15.Claesson MJ, Jeffery IB, Conde S, Power SE, O’Connor EM, Cusack S, et al. Gut microbiota composition correlates with diet and health in the elderly. Nature. 2012;488(7410):178–84. [DOI] [PubMed] [Google Scholar]
- 16.Mariat D, Firmesse O, Levenez F, Guimaraes V, Sokol H, Dore J, et al. The Firmicutes/Bacteroidetes ratio of the human microbiota changes with age. BMC Microbiol. 2009;9:123. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Odamaki T, Kato K, Sugahara H, Hashikura N, Takahashi S, Xiao JZ, et al. Age-related changes in gut microbiota composition from newborn to centenarian: a cross-sectional study. BMC Microbiol. 2016;16:90. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.O’Sullivan O, Coakley M, Lakshminarayanan B, Conde S, Claesson MJ, Cusack S, et al. Alterations in intestinal microbiota of elderly Irish subjects post-antibiotic therapy. J Antimicrob Chemother. 2013;68(1):214–21. [DOI] [PubMed] [Google Scholar]
- 19.Woodmansey EJ, McMurdo ME, Macfarlane GT, Macfarlane S. Comparison of compositions and metabolic activities of fecal microbiotas in young adults and in antibiotic-treated and non-antibiotic-treated elderly subjects. Appl Environ Microbiol. 2004;70(10):6113–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Saraswati S, Sitaraman R. Aging and the human gut microbiota-from correlation to causality. Front Microbiol. 2014;5:764. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.van Nood E, Vrieze A, Nieuwdorp M, Fuentes S, Zoetendal EG, de Vos WM, et al. Duodenal infusion of donor feces for recurrent clostridium difficile. N Engl J Med. 2013;368(5):407–15. [DOI] [PubMed] [Google Scholar]
- 22.Bakker GJ, Nieuwdorp M. Fecal microbiota transplantation: therapeutic potential for a multitude of diseases beyond clostridium difficile. Microbiol Spectr. 2017;5(4):291–308. [DOI] [PMC free article] [PubMed]
- 23.Jiang ZD, Jenq RR, Ajami NJ, Petrosino JF, Alexander AA, Ke S, et al. Safety and preliminary efficacy of orally administered lyophilized fecal microbiota product compared with frozen product given by enema for recurrent clostridium difficile infection: A randomized clinical trial. PLoS ONE. 2018;13(11):e0205064. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Youngster I, Mahabamunuge J, Systrom HK, Sauk J, Khalili H, Levin J, et al. Oral, frozen fecal microbiota transplant (FMT) capsules for recurrent clostridium difficile infection. BMC Med. 2016;14(1):134. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.den Besten G, van Eunen K, Groen AK, Venema K, Reijngoud DJ, Bakker BM. The role of short-chain fatty acids in the interplay between diet, gut microbiota, and host energy metabolism. J Lipid Res. 2013;54(9):2325–40. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.den Besten G, Gerding A, van Dijk TH, Ciapaite J, Bleeker A, van Eunen K, et al. Protection against the metabolic syndrome by Guar Gum-Derived Short-Chain fatty acids depends on peroxisome Proliferator-Activated receptor gamma and Glucagon-Like Peptide-1. PLoS ONE. 2015;10(8):e0136364. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Walsh ME, Bhattacharya A, Sataranatarajan K, Qaisar R, Sloane L, Rahman MM, et al. The histone deacetylase inhibitor butyrate improves metabolism and reduces muscle atrophy during aging. Aging Cell. 2015;14(6):957–70. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Biagi E, Nylund L, Candela M, Ostan R, Bucci L, Pini E, et al. Through ageing, and beyond: gut microbiota and inflammatory status in seniors and centenarians. PLoS ONE. 2010;5(5):e10667. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Shapiro H, Thaiss CA, Levy M, Elinav E. The cross talk between microbiota and the immune system: metabolites take center stage. Curr Opin Immunol. 2014;30:54–62. [DOI] [PubMed] [Google Scholar]
- 30.Kang L, Li P, Wang D, Wang T, Hao D, Qu X. Alterations in intestinal microbiota diversity, composition, and function in patients with sarcopenia. Sci Rep. 2021;11(1):4628. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Can B, Kara O, Kizilarslanoglu MC, Arik G, Aycicek GS, Sumer F, et al. Serum markers of inflammation and oxidative stress in sarcopenia. Aging Clin Exp Res. 2017;29(4):745–52. [DOI] [PubMed] [Google Scholar]
- 32.Picca A, Fanelli F, Calvani R, Mule G, Pesce V, Sisto A, et al. Gut dysbiosis and muscle aging: searching for novel targets against sarcopenia. Mediators Inflamm. 2018;2018:7026198. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Ko F, Abadir P, Marx R, Westbrook R, Cooke C, Yang H, et al. Impaired mitochondrial degradation by autophagy in the skeletal muscle of the aged female Interleukin 10 null mouse. Exp Gerontol. 2016;73:23–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Sayed RKA, Fernandez-Ortiz M, Diaz-Casado ME, Aranda-Martinez P, Fernandez-Martinez J, Guerra-Librero A, et al. Lack of NLRP3 inflammasome activation reduces Age-Dependent sarcopenia and mitochondrial Dysfunction, favoring the prophylactic effect of melatonin. J Gerontol Biol Sci Med Sci. 2019;74(11):1699–708. [DOI] [PubMed] [Google Scholar]
- 35.McBride MJ, Foley KP, D’Souza DM, Li YE, Lau TC, Hawke TJ, et al. The NLRP3 inflammasome contributes to sarcopenia and lower muscle glycolytic potential in old mice. Am J Physiol Endocrinol Metab. 2017;313(2):E222–32. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Burtscher J, Millet GP, Place N, Kayser B, Zanou N. The Muscle-Brain axis and neurodegenerative diseases: the key role of mitochondria in Exercise-Induced neuroprotection. Int J Mol Sci. 2021;22(12):6479. [DOI] [PMC free article] [PubMed]
- 37.Oudbier SJ, Goh J, Looijaard S, Reijnierse EM, Meskers CGM, Maier AB. Pathophysiological mechanisms explaining the association between low skeletal muscle mass and cognitive function. J Gerontol Biol Sci Med Sci. 2022;77(10):1959–68. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Koyama A, O’Brien J, Weuve J, Blacker D, Metti AL, Yaffe K. The role of peripheral inflammatory markers in dementia and alzheimer’s disease: a meta-analysis. J Gerontol Biol Sci Med Sci. 2013;68(4):433–40. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Singh-Manoux A, Dugravot A, Brunner E, Kumari M, Shipley M, Elbaz A, et al. Interleukin-6 and C-reactive protein as predictors of cognitive decline in late midlife. Neurology. 2014;83(6):486–93. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Luo Y, Lin H. Inflammation initiates a vicious cycle between obesity and nonalcoholic fatty liver disease. Immun Inflamm Dis. 2021;9(1):59–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Franceschi C, Garagnani P, Parini P, Giuliani C, Santoro A. Inflammaging: a new immune-metabolic viewpoint for age-related diseases. Nat Rev Endocrinol. 2018;14(10):576–90. [DOI] [PubMed] [Google Scholar]
- 42.Kim K, Park SM. Association of muscle mass and fat mass with insulin resistance and the prevalence of metabolic syndrome in Korean adults: a cross-sectional study. Sci Rep. 2018;8(1):2703. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Li AA, Kim D, Ahmed A. Association of sarcopenia and NAFLD: an overview. Clin Liver Dis (Hoboken). 2020;16(2):73–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Kim G, Lee SE, Lee YB, Jun JE, Ahn J, Bae JC, et al. Relationship between relative skeletal muscle mass and nonalcoholic fatty liver disease: A 7-Year longitudinal study. Hepatology. 2018;68(5):1755–68. [DOI] [PubMed] [Google Scholar]
- 45.Ekblad LL, Rinne JO, Puukka P, Laine H, Ahtiluoto S, Sulkava R, et al. Insulin resistance predicts cognitive decline: an 11-Year Follow-up of a nationally representative adult population sample. Diabetes Care. 2017;40(6):751–8. [DOI] [PubMed] [Google Scholar]
- 46.Delezie J, Handschin C. Endocrine crosstalk between skeletal muscle and the brain. Front Neurol. 2018;9:698. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Lourenco MV, Frozza RL, de Freitas GB, Zhang H, Kincheski GC, Ribeiro FC, et al. Exercise-linked FNDC5/irisin rescues synaptic plasticity and memory defects in alzheimer’s models. Nat Med. 2019;25(1):165–75. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Yoon EJ, Lee SR, Ortutu BF, Kim JO, Jaiswal V, Baek S, et al. Effect of endurance exercise training on gut microbiota and ER stress. Int J Mol Sci. 2024;25:19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Campbell SC, Wisniewski PJ, Noji M, McGuinness LR, Haggblom MM, Lightfoot SA, et al. The effect of diet and exercise on intestinal integrity and microbial diversity in mice. PLoS ONE. 2016;11(3):e0150502. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Hintikka JE, Ahtiainen JP, Permi P, Jalkanen S, Lehtonen M, Pekkala S. Aerobic exercise training and gut microbiome-associated metabolic shifts in women with overweight: a multi-omic study. Sci Rep. 2023;13(1):11228. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Clarke SF, Murphy EF, O’Sullivan O, Lucey AJ, Humphreys M, Hogan A, et al. Exercise and associated dietary extremes impact on gut microbial diversity. Gut. 2014;63(12):1913–20. [DOI] [PubMed] [Google Scholar]
- 52.Shukla SK, Cook D, Meyer J, Vernon SD, Le T, Clevidence D, et al. Changes in gut and plasma Microbiome following exercise challenge in myalgic Encephalomyelitis/Chronic fatigue syndrome (ME/CFS). PLoS ONE. 2015;10(12):e0145453. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Lera L, Albala C, Leyton B, Marquez C, Angel B, Saguez R, et al. Reference values of hand-grip dynamometry and the relationship between low strength and mortality in older Chileans. Clin Interv Aging. 2018;13:317–24. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Roberts HC, Denison HJ, Martin HJ, Patel HP, Syddall H, Cooper C, et al. A review of the measurement of grip strength in clinical and epidemiological studies: towards a standardised approach. Age Ageing. 2011;40(4):423–9. [DOI] [PubMed] [Google Scholar]
- 55.Huerta Ojeda A, Jofre-Saldia E, Arriagada Molina J, Rojas Quinchavil P, Parada Toledo MP, Galdames Maliqueo S, et al. Test-retest reliability of Latin American group for maturity (GDLAM) protocol in older women. PLoS ONE. 2024;19(4):e0302134. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Hamaguchi M, Kojima T, Itoh Y, Harano Y, Fujii K, Nakajima T, et al. The severity of ultrasonographic findings in nonalcoholic fatty liver disease reflects the metabolic syndrome and visceral fat accumulation. Am J Gastroenterol. 2007;102(12):2708–15. [DOI] [PubMed] [Google Scholar]
- 57.Wang C, Fang X, Tang Z, Hua Y, Zhang Z, Gu X, et al. A frailty index based on routine laboratory data predicts increased risk of mortality in Chinese community-dwelling adults aged over 55 years: a five-year prospective study. BMC Geriatr. 2022;22(1):679. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol Biol Sci Med Sci. 2001;56(3):M146–56. [DOI] [PubMed] [Google Scholar]
- 59.Lera L, Angel B, Sanchez H, Picrin Y, Hormazabal MJ, Quiero A, et al. [Validation of cut points of skeletal muscle mass index for identifying sarcopenia in Chilean older people]. Nutr Hosp. 2014;31(3):1187–97. [DOI] [PubMed] [Google Scholar]
- 60.Folstein MF, Folstein SE, McHugh PR. Mini-mental state. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189–98. [DOI] [PubMed] [Google Scholar]
- 61.Tombaugh TN. Trail making test A and B: normative data stratified by age and education. Arch Clin Neuropsychol. 2004;19(2):203–14. [DOI] [PubMed] [Google Scholar]
- 62.Olabarrieta-Landa L, Rivera D, Galarza-Del-Angel J, Garza MT, Saracho CP, Rodriguez W, et al. Verbal fluency tests: normative data for the Latin American Spanish speaking adult population. NeuroRehabilitation. 2015;37(4):515–61. [DOI] [PubMed] [Google Scholar]
- 63.Thomas Valentine CB, Eversole K, Boxley L. Erica Dawson. Wechsler adult intelligence scale-IV. In: Ltd JWaS, editor. The Wiley Encyclopedia of Personality and Individual Differences, Measurement and Assessment2020. pp. 457 – 63.
- 64.Dubois B, Slachevsky A, Litvan I, Pillon B. The FAB: a frontal assessment battery at bedside. Neurology. 2000;55(11):1621–6. [DOI] [PubMed] [Google Scholar]
- 65.Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24(4):385–96. [PubMed] [Google Scholar]
- 66.Remor E. Psychometric properties of a European Spanish version of the perceived stress scale (PSS). Span J Psychol. 2006;9(1):86–93. [DOI] [PubMed] [Google Scholar]
- 67.Baker FM, Espino DV. A Spanish version of the geriatric depression scale in Mexican-American elders. Int J Geriatr Psychiatry. 1997;12(1):21–5. [DOI] [PubMed] [Google Scholar]
- 68.Marc LG, Raue PJ, Bruce ML. Screening performance of the 15-item geriatric depression scale in a diverse elderly home care population. Am J Geriatr Psychiatry. 2008;16(11):914–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 69.Beck AT, Epstein N, Brown G, Steer RA. An inventory for measuring clinical anxiety: psychometric properties. J Consult Clin Psychol. 1988;56(6):893–7. [DOI] [PubMed] [Google Scholar]
- 70.Keyes CL, Shmotkin D, Ryff CD. Optimizing well-being: the empirical encounter of two traditions. J Pers Soc Psychol. 2002;82(6):1007–22. [PubMed] [Google Scholar]
- 71.Vera PUA, Celis K, Silva J. Evaluation of subjective Well-being: analysis of the satisfaction with life scale in Chilean population. Universitas Physiol. 2012;11:719–27. [Google Scholar]
- 72.Vera P, Celis K, Córdova N. Evaluación de La Felicidad: análisis psicométrico de La Escala de Felicidad subjetiva En población Chilena. Terapia psicológica. 2011;29:127–33. [Google Scholar]
- 73.Encuesta de Consumo Alimentario en Chile. 2016 Available from: https://www.minsal.cl/enca/
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This section collects any data citations, data availability statements, or supplementary materials included in this article.
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Data Availability Statement
No datasets were generated or analysed during the current study.


