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M. Serra-Prat1,2, M. Terradellas1, I. Lorenzo1, M. Arús3, E. Burdoy4, A. Salietti4, S. Ramírez5, E. Palomera1, M. Papiol6, E. Pleguezuelos7


1. Research Unit. Consorci Sanitari del Maresme, Mataró, Barcelona, Spain; 2. Centro de Investiación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), ISCIII, Madrid, Spain; 3. Dietetics and Nutrition Unit, Hospital of Mataró, Consorci Sanitari del Maresme, Mataró, Barcelona, Spain; 4. ABS Mataró Centre, Consorci Sanitari del Maresme, Mataró, Barcelona, Spain; 5. ABS Cirera-Molins, Consorci Sanitari del Maresme, Mataró, Barcelona, Spain; 6. ABS Argentona, Consorci Sanitari del Maresme, Mataró, Barcelona, Spain; 7. Rehabilitation Department, Hospital of Mataró, Consorci Sanitari del Maresme, Mataró, Barcelona, Spain

Corresponding Author: Mateu Serra-Prat, Research Unit, Hospital de Mataró, Carretera de Cierera s/n, 08304 Mataró, Barcelona, Spain, Tel. + 34 93 741 77 30, mserra@csdm.cat

J Frailty Aging 2021;in press
Published online September 24, 2021, http://dx.doi.org/10.14283/jfa.2021.38



Background: Obesity is a risk factor for frailty and muscle weakness, so weight loss in obese older adults may prevent frailty and functional decline.
Objective: To assess the safety and efficacy of a multimodal weight-loss intervention in improving functional performance and reducing frailty risk in obese older adults.
Design: Randomized controlled trial with 2 parallel arms.
Setting and participants: Community-dwelling obese adults aged 65-75 years with body mass index (BMI) 30-39 kg/m2.
Intervention: 6-month multimodal intervention based on diet and a physical activity program. Control group: Usual care.
Main and secondary outcome measures: Frailty (Fried criteria) rate and functional performance at 6, 12, and 24 months of follow-up, respectively.
Intermediate outcome measures: Weight loss, body composition changes, and metabolic and inflammatory biomarker changes.
Results: N=305. The study intervention increased gait speed at 12 and 24 months of follow-up, but had no significant effect on frailty prevention. It was effective in reducing weight, BMI, fat mass, interleukin 6, and insulin resistance and improving self-reported quality of life.
Conclusions: The study intervention was not demonstrated to be effective in preventing frailty in obese people aged 65-75 years at 24 months of follow-up. However, it allowed weight loss and a reduction in inflammatory and insulin resistance markers, which could have a long-term effect on frailty that requires further research.

Key words: Randomized controlled trial, obese, multimodal intervention, frailty, insulin resistance.



Frailty is a clinical condition in which the individual is in a vulnerable state at increased risk of disease, adverse health outcomes, disability, and death when exposed to a stressor (1). It is considered a geriatric syndrome characterized by a decline in the functioning of different organs and systems. Frailty has a great impact on quality of life (QoL) and increases the risk of falls, functional decline, dependency, and institutionalization (2). Frailty prevalence in the community-dwelling population aged over 65 years has been estimated at 11%, rising to as high as 50% in the population aged over 80 years (3). Frailty causes and pathophysiology are not well understood. Some authors consider frailty to be the result of an accumulation of different unrelated diseases, dysfunctions, and disabilities (4). Other authors consider frailty to be the result of a pathophysiological process involving the breakdown of homeostatic mechanisms mainly expressed as impaired muscle function (5). As risk factors for frailty, several studies have pointed to comorbidities such as diabetes, stroke, dementia, and depression (6, 7), and also to pain and certain physiological changes that appear with age, such as low-intensity inflammatory processes (8), changes in body composition, hormonal imbalances (9), loss of appetite, nutritional disturbances, insulin resistance, and dehydration (10).
Obesity, which is also prevalent in the population of older adults (11), has been related with frailty in both cross-sectional (12-16) and prospective population-based studies (17), with the relationship between obesity and muscle mass and strength described as negative (18). Mechanisms through which obesity can promote frailty and muscle wasting may include: (a) fatty infiltration of the muscle so that it loses quality and strength, (b) pro-inflammatory cytokine release with catabolic and anorectic effects (19), (c) low physical activity levels favouring muscular atrophy, (d) increased cardiovascular risk and increased stroke and heart failure incidence, (e) increased risk of osteoarthritis and pain, limiting physical activity, (f) hormonal changes including reduced oestrogen, testosterone, sex hormone binding globulin, dehydroepiandrosterone, growth hormone, and insulin-like growth factor (IGF-I) levels, and increased prolactin and cortisol levels (20), and (g) insulin resistance and a risk of type 2 diabetes mellitus, associated with a loss of muscle mass and strength (21). Sarcopenic obesity is a clinical condition of reduced muscle mass in the context of excess adiposity, most often reported in older people as both conditions increase with age (22). Sarcopenia has a negative prognostic impact in obese individuals and may lead to frailty, disability, and increased morbimortality (23).
Based on the evidence, it would seem reasonable to think that an intervention based on a healthy diet and physical exercise aimed at reducing body mass index (BMI) below 30 kg/m2 without loss of muscle mass could effectively and safely prevent frailty and disability in obese older adults over the mid-/long-term. While the health benefits of diet and exercise in older people have been widely demonstrated, leaving no doubt as to the validity of the corresponding recommendations (24-27), weight loss to prevent frailty, disability, dependency, and institutionalization in obese older adults has been little studied. The lack of evidence may be due in part to poor adherence to diet and exercise recommendations, the difficulty to change habits and lifestyles (28), and the fear of weight loss accentuating muscle mass loss and muscle wasting in older adults (20). We evaluated the safety and efficacy of a multimodal weight-loss intervention in community-dwelling obese older adults. Primary objectives were to assess improvements in functional performance and reductions in frailty risk, while secondary objectives were to assess changes in anthropometric, body composition, metabolic, and inflammatory parameters.


Materials and Methods

Study design and population

Our open-label randomized controlled trial (RCT) with 2 parallel arms (intervention and control) and 2 years of follow-up recruited adults aged 65-75 years, with a BMI of
30-39 kg/m2 (inclusive), who had at least one of the following obesity-related clinical conditions for which weight loss is advisable: dyslipidaemia, hypertension, diabetes or insulin resistance, obesity-related physical limitations, or sleep apnoea/hypopnoea. Exclusion criteria were dementia, neurodegenerative diseases, severe psychiatric disorders, cancer diagnoses, lower limb amputation, institutionalization, and life expectancy <6 months. Candidate participants were pre-selected from the database corresponding to three Maresme region primary care centres in the province of Barcelona (Catalonia, Spain) according to age, BMI criteria, and inclusion/exclusion criteria. These candidates were invited by telephone to a visit in which selection criteria were verified and individuals received information about the study and granted their written consent. Sample size was calculated usig the GRANMO calculator (https://www.imim.cat/ofertadeserveis/software-public/granmo/) according to the proportion of frail individuals at 24 months of follow-up. For an alpha risk of 0.05 and a beta risk of less than 0.1 in a bilateral comparison, 162 subjects needed to be included in each group to detect a statistically significant difference in frailty prevalence, expected to be 21% for the control group and 7% for the intervention group (6, 17). For an anticipated loss to follow-up of 25%, recruitment of a total of 360 individuals was required. Participants were recruited at the 3 primary care centres from February to June 2017. Individuals were randomized to either the intervention or control group according to identification codes and the sequentially numbered opaque sealed envelope (SNOSE) technique. Randomization was stratified by primary care centre, with each centre receiving 120 envelopes (60 for each study group). Envelopes were opened only once the patient had consented and had been recruited. The study protocol was approved by the local ethics committee (reference number CEIC CSdM 60/16) and the study was registered in the ClinicalTrials.gov database (https://clinicaltrials.gov) under identifier NCT03000907.


The intervention consisted of a 6-month multimodal personalized program combining individual and group sessions. The intervention was as follows:
1. Diet. A dietician assessed nutritional status and nutrition requirements and developed a personalized eating plan for each intervention group individual aimed at achieving BMI<30 or weight loss>10%. The assessment considered how obesity had evolved, possible triggers, current dietary habits, the dietary environment, daily physical activity, and exercise regime, and included a physical examination covering weight, height, waist and hip circumferences, and bioimpedance analysis (BIA). These data were used to estimate the basal metabolic rate (BMR), daily energy expenditure (DEE) based on activity level, and recommended daily intake (RDI) necessary to achieve BMI<30 or weight loss>10% within 6 months. During this period individuals attended monthly individualized follow-up visits to evaluate weight evolution, to assess and reinforce adherence and to make necessary changes to established recommendations. Personalized eating plans were based on a diet as follows: (a) hypocaloric, with a caloric deficit of 300-400 kcal/day with respect to the DEE, (b) balanced in macronutrients, with around 20%, 50% 27% of total energy delivered in the form of proteins (1.2 g/kg/day), carbohydrates, and fat, respectively, and (c) balanced in micronutrients (vitamins and minerals) according to current recommendations, with supplementation of vitamins (D, B6, B12) and minerals (calcium, magnesium, selenium) if deficient.
2. Exercise. A multicomponent physical exercise program included the following: (a) 45 minutes of unsupervised daily aerobic exercise (e.g., walking outdoors) on at least 5 days/week, (b) unsupervised strength, balance, and flexibility exercises for 15-20 minutes/day on 3 days a week (adapted to different ailments and with personalized follow-up to avoid injuries) to be done at home, and (c) health education by a physiotherapist, consisting of 20 theoretical-practical group sessions of 1 hour/week in the primary care centre, aimed at improving adherence and emphasizing the importance of physical exercise and also including Nordic walking in groups twice a month. Unsupervised daily walks and home exercises were not monitored. Participants received a leaflet explaining the exercises they had to do at home with illustrated instructions.

Individuals assigned to the control group received their usual care, which involved no specific weight-loss intervention other than the usual dietary and hygienic recommendations of the primary care team.

Outcome measures and data collection

The main outcome measure was prevalence of frailty at 6, 12 and 24 months according to Fried criteria (5), with participants classified as robust, pre-frail, or frail if they fulfilled none, 1-2, or 3 or more of the following 5 criteria: (a) unintentional weight loss, (b) exhaustion, (c) low physical activity, (d) slow walking speed, and (e) poor grip strength, measured using a handheld Jamar dynamometer (Lafayette Instrument Co). Secondary outcome measures were the following indicators of functional performance: Barthel score, 2-minute walking test (2MWT), timed up-and-go test (TUG), gait speed, unipodal stance test (UST), number of falls in the previous 3 months, and daily hours walking outdoors.
Intermediate outcome measures were as follows: weight loss, change in BMI, change in body composition (BIA-evaluated fat mass, lean mass, and muscle mass), body fat distribution according to waist circumference, hip circumference, and waist/hip ratio (WHR), glycaemic control according to haemoglobin subunit alpha (HbA1) levels, insulin resistance according to the homeostatic model assessment of insulin resistance (HOMA-IR), and serum levels of inflammatory markers – interleukin 6 (IL-6) and C-reactive protein (CRP) – and anabolic hormones – IGF-1 and testosterone – as determined by commercialized kits. Outcome measures were evaluated in follow-up checks at 6, 12, and 24 months. Other data collected were as follows: sociodemographic characteristics, toxic habits (tobacco and alcohol consumption), comorbidities, number of medications, chronic pain as assessed by a visual analogue scale (VAS), and self-reported QoL as assessed by a 0-10 point horizontal VAS using identical question to those for the 5-dimension EuroQoL (EQ5D) VAS. Outcome evaluators, participants, and usual healthcare providers were not blinded to the intervention group.

Data analysis

Data analysis was by intention-to-treat (ITT). The intervention and control groups were compared at baseline and at 6, 12, and 24 months of follow-up using the X2 test or Fisher’s exact test for categorical variables, and the t-test or Mann-Whitney U test for numerical variables. Normality of continuous variables was assessed by the Kolmogorov-Smirnov test. Baseline to follow-up differences in the outcome measures were calculated and compared between the two study groups using the X2 test or Fisher’s exact test for categorical variables, and the t-test or Mann-Whitney U test for numerical ones. Moreover, regarding main numerical outcome measures, a general linear model analysis (GLM; ANOVA of repeated measures) was used to test both; a) if their evolution over time (repeated measures) differ between study groups (interaction between evolution and study group) and b) the group effect (independently of evolution). Statistical significance was established in all cases for a 2-sided p-value of <.05.



A total of 1,014 subjects were pre-selected, 319 of whom fulfilled the selection criteria and granted their informed consent. Of the 305 who attended the baseline visit, 150 were randomly allocated to the intervention group and 155 to the control group. Loss to follow-up was 21.6% at 6 months, 28.2% at 12 months, and 43.6% at 24 months, with no significant differences observed between groups. Figure 1 shows the study flow chart. Two deaths occurred during the study, neither attributed to the intervention (a case of cancer and the other non-specified). No other side effects were reported. The study sample (n = 305) had a mean age of 69.7 years, 65.9% were women, 15% lived alone, 27% had no education, and showed a mean BMI of 34 and a mean Barthel score of 99. Most frequent co-morbidities were arterial hypertension (76.1%), dyslipidaemia (66.9%), arthrosis (66.5%), diabetes (26.2%), gastroesophageal reflux (24.6%), peripheral vascular disease (23.9%) and depression (22.6%). Table 1 summarizes the main baseline characteristics for the sample and the 2 groups. Except for asthma prevalence and gait speed (significantly higher – p=0.025- and lower –p=0.035-, respectively, in the intervention group), no differences were observed in baseline sociodemographic characteristics, toxic habits, comorbidities, medications, functional capacity, physical examination parameters, or inflammatory, metabolic, or anabolic biomarkers between the groups. Baseline frailty prevalence was 2.7% in the intervention group and 1.3% in the control group (p=0.442). Overall, those data indicate that intervention and control groups were homogeneous and comparable.

Figure 1. Study flow Chart


No between-group differences in frailty prevalence were observed at 6, 12, and 24 months. At 6 months, frailty status had worsened (changed from robust to pre-frail or from pre-frail to frail) in 8.3% of intervention group individuals compared to 16.2% of control group individuals (p=0.069). No significant frailty status worsening differences were observed at 12 and 24 months of follow-up. At 12 months, 8 and 9 intervention and control group individuals, respectively, had become frail, for an incidence rate of 7.38 and 7.37 new cases/100 person-years, respectively. Table 2 compares frailty and functional outcome measures for the 2 groups at 6, 12, and 24 months of follow-up. It points to a significant effect of the study intervention in terms of increased daily outdoors walking by 6 months, and increased gait speed by 12 and 24 months of follow-up, with an improvement of 0.07 m/sec maintained at both 12 (p=0.035) and 24 (p=0.036) months.

Table 1. Main baseline characteristics for the sample and intervention (I) and control (C) groups

Data expressed as mean (standard deviation) except where otherwise indicated. 2MWT: 2-minute walking test. BMI: body mass index. HbA1: haemoglobin subunit alpha. HOMA-IR: homeostatic model assessment of insulin resistance. MNA-sf: Short-Form Mini-Nutritional Assessment. QoL: quality of life. TUG: Timed up-and-go test. UST: unipodal stance test. VAS: 0-10 visual analogue scale. WHR: waist-hip ratio; Items in bold are statistically significant at p<.05.


Table 2. Frailty and functional outcome measures for the intervention (I) and control (C) groups at 6, 12, and 24 months of follow-up

Data expressed as mean (standard deviation) except where otherwise indicated. 2MWT: 2-minute walking test. TUG: Timed up-and-go test. UST: unipodal stance test. Items in bold are statistically significant at p<.05.


Table 3 compares intermediate outcome measures between groups at 6, 12, and 24 months of follow-up. It shows a significant effect of the study intervention on weight loss (-4.2 vs -1.1 kg, p<0.001) and BMI reduction (-1.7 vs -0.5 points, p<0.001) at 6 months of follow-up that, however, tended to attenuate over time. It also points to a slight reduction in fat mass, especially in women at 12 months (-1.3 vs +0.6 kg, p=0.013), but no effect on lean mass. The intervention group compared to the control group achieved lower IL-6 levels at 12 months of follow-up (4.1 vs 5.7 mg/dL, p=0.030), lower insulin levels at 12 and 24 months of follow-up (12.7 vs 16.4 µU/mL; p=0.027 and 12.4 vs 15.1 µU/mL; p=0.025, respectively), and lower insulin resistance (HOMA-IR) at 12 and 24 months of follow-up (3.6 vs 4.8; p=0.016 and 3.4 vs 4.3; p=0.021, respectively). Self-reported QoL was better among intervention group individuals, especially in the first 6 months of the intervention (73.3 vs 68.1; p=0.024).

Table 3. Intermediate outcome measures for the intervention (I) and control (C) groups at 6, 12, and 24 months of follow-up

Data expressed as mean (standard deviation) except where otherwise indicated. BMI: body mass index. CRP: C-reactive protein. HbA1: haemoglobin subunit alpha. HOMA-IR: homeostatic model assessment of insulin resistance. IGF-1: insulin-like growth factor 1. IL-6: interleukin-6. QoL: quality of life. TSF: tricipital skinfold. VAS: 0-10 visual analogue scale. WHR: waist-hip ratio; Items in bold are statistically significant at p<.05.


The GLM analysis showed that the evolution over time of 2MWT, weight, BMI, waist circumference, fat mass, lean mass and cholesterol significantly differ between both study groups (p valeues: 0.001, <0.001, <0.001, 0.008, 0.013, 0.006, 0.037, respetively). It also showed a significant group effect on insulin (p=0.011) and HOMA IR (p=0.039).



Our RCT shows that, for obese 65-75 year old individuals, a multimodal weight-loss intervention based on diet and exercise is safe and effective in reducing weight and normalizing BMI. It may also reduce fat mass, improve certain metabolic and inflammatory parameters, and enhance self-reported QoL. However, not only was it not possible to demonstrate an effect in preventing frailty and functional decline, benefits progressively disappeared within a few months of the intervention ending.
There is abundant evidence on the positive effects of physical exercise and healthy diet in improving muscle strength and physical performance in older populations (27). The LIFE study showed that a structured, moderate-intensity physical activity program consisting of aerobic, resistance, and flexibility training activities reduced major disability over 2.6 years among older adults at risk for disability (29). Several RCTs that have assessed the effect of interventions on frailty prevention or reversion as the main outcome measure (30-33) indicate that physical, nutritional, and cognitive interventions are effective in improving frailty scores in pre-frail and frail older people. However, as far as we are aware, no RCTs have assessed the effects of weight loss on mid- and long-term prevention of frailty in obese older people. While not reaching any definitive conclusion, our RCT brings new evidence to bear. During the 6 months of the intervention, the worsening in frailty status in the intervention group (8%) was half that in the control group (16%), for a difference that was very nearly statistically significant (p=0.069). After 24 months of follow-up, however, no clearly significant effect of the study intervention in preventing frailty was observed. On the other hand, at 12 and 24 months, intervention group individuals experienced a higher 0.07 m/s improvement in gait speed in comparison to control group individuals. Although this improvement in functional capacity may seem poor, it is worth remembering the clinical relevance of gait speed as an indicator of functional performance, frailty and health, and noting that gait speed is strongly associated with survival in older adults (34). A pooled analysis of 9 cohort studies shows that survival increases across the full range of gait speeds, with significant increments (hazard ratio 0.88) per 0.1 m/s (34). Our rather modest results regarding the prevention of frailty and functional decline may be explained in several ways. Firstly, the study sample was relatively young (mean age 69 years) and had good baseline functional capacity. Secondly, the intervention was specifically designed to lose weight, not to improve muscle strength; a more intensive physical activity program that included sensorimotor aspects, as well as training in activities of daily living, would likely have improved results. A program to eliminate obesity alone, if not accompanied by a physical strengthening program, would not appear to be enough to enhance strength and functional capacity over the short-to-medium term. Thirdly, follow-up to 24 months was insufficient as this was too short a period for frailty to develop in our relatively young and functional population: obesity’s impact on frailty is a long-term effect, and likewise the effect of reducing obesity on frailty prevention. Fourthly, losses to follow-up were higher than expected and, especially during the second year, occurred mostly among frailer people, consequently limiting the statistical power of the study to identify differences between the intervention and control groups. Finally, intervention effects were evident during it but progressively fell off after its conclusion. The fact that the positive effect on weight, BMI improvement, and waist circumference was lost once the intervention concluded highlights the need to maintain such interventions over more prolonged periods of time and to incorporate the intervention guidelines as lifestyle changes in order to observe long-term effects. A higher duration of the diet and physical exercise intervention could provide a longer effect duration, but maintaining the intervention for prolonged periods in aged population is a recognised difficult challenge (35). While our results do not support the main hypothesis of study, they do not rule it out. Thus, further studies with large enough samples, more prolonged interventions, and longer follow-up periods are required to confirm the hypothesis that weight loss in obese older adults may contribute to the prevention of frailty and functional decline. Furthermore, the additional inclusion of intensive interventions designed to improve muscle strength would contribute to the prevention of frailty and functional decline in this population.
An interesting result of the study intervention is the observed effect in reducing fat mass, especially in women, and correlating with improved insulin resistance (HOMA-IR) and inflammation (IL-6) indicators. Reducing excess weight and fat mass could have a long-term effect in reducing frailty, as both insulin resistance and inflammation have been related with frailty incidence (36). Clinical relevance of weight loss is reflected in the improvement of inflammatory and insulin resistance parameters. In our study, weight loss had a high impact on reducing, and even eliminating, treatment with oral anti-diabetics or insulin in some patients. No improvement was observed in lean mass or in muscle mass, however, which would reaffirm the risk of muscle mass loss deriving from weight loss diets in older people. Such diets should be restricted only to older adults who are obese (BMI≥30 kg/m2) and who have comorbidities, functional limitations, or metabolic complications related to excess weight, should be accompanied by a muscle strengthening program (20), and should be strictly supervised. Moreover, weight loss can carry a special risk in older people with sarcopenic obesity as it can accentuate loss of muscle mass and bone mass and increase the risk of falls and fractures (22). This is why in people with sarcopenic obesity, interventions should prioritize the increase in muscle mass and function over weight loss. Although loss of strength is a more consistent risk for disability and death than is loss of muscle mass (37), both must be targets of interventions to prevent frailty. Finally, it is also worth mentioning that intervention group individuals had better self-reported QoL during the intervention than control group individuals; however, this effect also disappeared within 6 months after the intervention ended. Although it may be difficult for the subjects themselves to perceive the short-term positive effects of physical activity on health (some physiological parameters may improve, but may only be perceptible if analysed), regular exercise has clear psychological benefits for perceptions of health and wellbeing and even for improved socialization and self-esteem (38). These results agree with those reported by the published RCT on the effect of weight loss interventions in older adults with obesity (39). These trails provided evidence of low to moderate quality and suggest that weight reduction, especially fat mass reduction with preserved lean mass, can lead to improvements in physical function and quality of life (39). However, further well-designed RCTs are needed in aged obese population to provide definitive guidance in clinical practice. Adherence of older adults to physical exercise programs tends to be poor. Barriers to exercising include age, being female, fatigue, health problems, pain, and lack of motivation and willpower; in contrast, the desire to spend time outdoors and in nature are protective factors for exercising (28). Poor adherence – defined as attendance at less than 50% of the sessions with the dietician or physiotherapist – was observed in almost half the individuals in our study, a similar percentage to that observed in other studies (32). Compliance with visits with the dietician (individual sessions) was better (67%) than with the physiotherapist (practical group sessions with a less flexible schedule) (40%). Better compliance was associated with a higher effect of the study intervention in terms of weight loss, reduced BMI, fat mass, and insulin levels, and was also related to improved gait speed. Future lines of research in the field of frailty prevention in obese seniors should include; a) the design of new therapeutic strategies with more effective combinations of diet and exercise, b) the establishment of the type of exercise with the greatest impact on functional improvement and its optimal duration, c) the assessment of the interactions with other types of interventions that may potentiate the expected effect, and interactions with other clinical conditions (chronic inflammation, dehydration, etc.), or d) studies on how to improve compliance, adherence, or motivation for a change in healthier habits in aged population.
While the RCT design is a key strength, our study also has some weaknesses. A first limitation is the lack of sufficient statistical power, mainly due to greater losses to follow-up than expected. Follow-up losses were slightly higher in the intervention group and were associated with female gender, sarcopenia, number of medications, no outdoors life, poor physical activity, and depression. While the losses occurred homogeneously in both study groups (reducing possible bias), they mainly reflected people with greater frailty or poorer functional capacity (thereby diluting the possible effects). Another limitation was that it was impossible to keep participants blind to the study intervention and, thus, the difficulty to mask the evaluators. Although not a double-blind study, we think that the main outcome measures followed clear, explicit, and precise criteria, and standardized and validated procedures. However, it must be noted that while frailty is a clinical condition that is well accepted by geriatricians and the scientific community, there is no consensus regarding diagnostic criteria. In this study, we used the very widely used and validated criteria of Linda Fried (5), which, however, have limitations related to their exclusively physical orientation and reliability when applied by non-expert evaluators. Moreover, the study intervention consisted of a combination of exercise and diet at the same time and, therefore, it was impossible distinguishing the effects of these two components. The observed effect must be considered due to the multimodal intervention as a whole. Finally, as mentioned earlier, our relatively young and robust study sample, the non-extension of the intervention beyond 6 months, and an overly short follow-up period (24 months) restricted possibilities of proving the hypothesis regarding the prevention of frailty and functional decline.
In conclusion, this study has not conclusively demonstrated that weight loss and BMI normalization in obese people aged 65-75 years reduces frailty risk at 24 months of follow-up. Even so, weight loss and fat mass reduction were accompanied by an improvement in certain inflammatory and insulin resistance parameters, and this may, in turn, have long-term effects in preventing frailty and functional decline. The working hypothesis remain reasonable and plausible, therefore, and should be tested with larger sample sizes and longer interventions and follow-up periods.


Author Contributions: Conceptualization MS-P; methodology MS-P, EP, MP and EB; formal analysis EP; investigation MT, IL, MA, AS, SR and MP; data curation MS-P, EP; writing—original draft preparation MS-P; funding acquisition, MS-P. All authors have read and agreed to the published version of the manuscript.

Funding: This study was funded by grants from the Spanish Ministry of Health (Instituto de Salud Carlos III, Fondo de Investigación Sanitaria (FIS) program PI16/00750).

Institutional Review Board Statement: The study protocol was approved by the local ethics committee (reference number CEIC CSdM 60/16). The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Ethics Committee of Consorci Sanitari del Maresme (CSdM)(protocol code CEIC CSdM-60/16, 26th October 2016).

Informed Consent Statement: Written informed consent was obtained from all subjects involved in the study.

Conflicts of Interest: The authors have no conflicts of interest to disclose.

Ethical standards: All participants gave their informed consent. The study protocol was approved by the local ethics committee (reference number CEIC CSdM 60/16)



1. Morley J, Vellas B, van Kan GA, Anker SD, Bauer JM, Bernabei R, et al. Frailty consensus: a call to action. JAMDA 2013; 14: 392-7.
2. Brown NA, Zenilman ME. The impact of frailty in the elderly on the outcome of surgery in the aged. Advances in Surgery 2010; 44: 229-49.
3. Collard R M, Boter H, Schoevers RA, Oude Voshaar RC. Prevalence of frailty in community-dwelling older persons: a systematic review. J Am Geriatr Soc 2012; 60: 1487-92.
4. Rockwood K, Mitnitski A. Frailty Defined by Deficit Accumulation and Geriatric Medicine Defined by Frailty. Clin Geriatr Med 2011; 27: 17–26.
5. Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. Journals of Gerontology Series A: Biological Sciences and Medical Sciences 2001; 56 (3): M146-M156.
6. Serra-Prat M, Papiol M, Vico J, Palomera E, Arús M, cabré M. Incidence and risk factors for frailty in the community-dwelling elderly population. A two-year follow-up cohort study. J Gerontol Geriatr Res 2017; 6:6. DOI: 10.4172/2167-7182.1000452.
7. Tze Pin Ng, Liang Feng, Ma Shwe Zin Nyunt, AnisLarbi, Keng Bee Yap. Frailty in older persons: multisystem risk factors and the frailty risk index (FRI) (2014). JAMDA 15: 635-42.
8. Soysal P, Stubbs B, Lucato P, Luchini C, MarcoSolmiM.D., Roberto Peluso M.D., Ahme TuranIsikM.D., Enzo Manzato M.D., Stefania Maggi M.D., Marcello Maggio M.D.nA. Matthew PrinaPh.D.oTheodore D.CoscoPh.D.pYu-TzuWuPh.D.qNicolaVerones. Inflammation and frailty in the elderly: A systematic review and meta-analysis. Ageing Research Reviews 2016; 31: 1-8.
9. Joshua I. Barzilay, MD; Caroline Blaum, MD, MS; Tisha Moore, BA; et al Qian Li Xue, PhD; Calvin H. Hirsch, MD; Jeremy D. Walston, MD; Linda P. Fried, MD, MPH. Insulin Resistance and Inflammation as Precursors of Frailty. The Cardiovascular Health Study. Arch Intern Med. 2007;167(7):635-641. doi:10.1001/archinte.167.7.635
10. Serra-Prat M, Lorenzo I, Palomera E, Yébenes JC, Campins L, Cabré M. Intracellular water content in lean mass is associated with muscle strength, functional capacity and frailty in community-dwelling elderly individuals. A cross-sectional study. Nutrients 2019, 11, 661; doi:10.390/nu11030661.
11. Gutiérrez-Fisac JL, Guallar-Castillón P, León-Muñoz LM, Graciani A, Banegas JR, Rodríguez-Artalejo F. Prevalence of general and abdominal obesity in the adult population of Spain, 2008-2010: the ENRICA study. Obes Rev 2012;13(4):388-92.
12. Blaum CS, Xue QL, Michelon E, Semba RD, Fried LP. The association between obesity and the frailty syndrome in older women: the Women’s Health and Aging Studies. J Am Geriatr Soc. 2005;53(6):927-34.
13. Woods NF, LaCroix AZ, Gray SL, Aragaki A, Cochrane BB, Brunner RL, Masaki K, Murray A, Newman AB, Women’s Health Initiative. Frailty: emergence and consequences in women aged 65 and older in the Women’s Health Initiative Observational Study. J Am Geriatr Soc 2005; 53:1321-30.
14. Stenholm S, Strandberg TE, Pitkälä K, Sainio P, Heliövaara M, Koskinen S. Midlife obesity and risk of frailty in old age during a 22-year follow-up in men and women: the Mini-Finland Follow-up Survey. J Gerontol A Biol Sci Med Sci 2014; 69:73-8.
15. Hubbard RE, Lang IA, Llewellyn DJ, Rockwood K. Frailty, body mass index, and abdominal obesity in older people. J Gerontol A Biol Sci Med Sci 2010 Apr;65(4):377-81.
16. Barzilay JI, Cotsonis GA, Walston J, Schwartz AV, Satterfield S, Miljkovic I, Harris TB, Health ABC Study. Insulin resistance is associated with decreased quadriceps muscle strength in nondiabetic adults aged >or=70 years. Diabetes Care 2009;32(4):736-8. LM
17. García-Esquinas E, García-García FJ, León-Muñoz LM, Carnicero JA, Guallar-Castillón P, Gonzalez-Colaço M, López-García E, Alonso-Bouzón C, Rodríguez-Mañas L, Rodríguez-Artalejo F. Obesity, fat distribution, and risk of frailty in two population-based cohorts of older adults in Spain. Obesity (Silver Spring) 2015 Apr;23(4):847-55.
18. Stenholm S, Tiainen K, Rantanen T, Sainio P, Heliövaara M, Impivaara O, Koskinen S. Long-term determinants of muscle strength decline: prospective evidence from the 22-year mini-Finland follow-up survey. J Am Geriatr Soc. 2012 Jan;60(1):77-85. doi: 10.1111/j.1532-5415.2011.03779.x. Epub 2011 Dec 28. PMID: 22211568.
19. Schrager MA, Metter EJ, Simonsick E, Ble A, Bandinelli S, Lauretani F, Ferrucci L. Sarcopenic obesity and inflammation in the InCHIANTI study. J Appl Physiol (1985). 2007 Mar;102(3):919-25. doi: 10.1152/japplphysiol.00627.2006. Epub 2006 Nov 9. PMID: 17095641; PMCID: PMC2645665.
20. Kennedy RL, Chokkalingham K, Srinivasan R. Obesity in the elderly: who should we be treating, and why, and how? Curr Opin Clin Nutr Metab Care. 2004 Jan;7(1):3-9. doi: 10.1097/00075197-200401000-00002. PMID: 15090896.
21. Kalyani RR, Saudek CD, Brancati FL, Selvin E. Association of diabetes, comorbidities, and A1C with functional disability in older adults: results from the National Health and Nutrition Examination Survey (NHANES), 1999-2006. Diabetes Care. 2010 May;33(5):1055-60. doi: 10.2337/dc09-1597. Epub 2010 Feb 25. PMID: 20185736; PMCID: PMC2858174.
22. Prado CM, Wells JC, Smith SR et al. Sarcopenic obesity: a critical appraisal of the current evidence. Clin Nutr 2012; 31: 583–601.
23. Tian S, Xu Y. Association of sarcopenic obesity with the risk of all-cause mortality: A meta-analysis of prospective cohort studies. Geriatr Gerontol Int 2016; 16: 155–66.
24. Limongi F, Siviero P, Bozanic A, Noale M, Veronese N, Maggi S. The Effect of Adherence to the Mediterranean Diet on Late-Life Cognitive Disorders: A Systematic Review. J Am Med Dir Assoc. 2020 Oct;21(10):1402-1409. doi: 10.1016/j.jamda.2020.08.020. PMID: 32981667.
25. Tsai MC, Lee CC, Liu SC, Tseng PJ, Chien KL. Combined healthy lifestyle factors are more beneficial in reducing cardiovascular disease in younger adults: a meta-analysis of prospective cohort studies. Sci Rep. 2020 Oct 23;10(1):18165. doi: 10.1038/s41598-020-75314-z. PMID: 33097813; PMCID: PMC7584648.
26. Rossi PG, Carnavale BF, Farche ACS, Ansai JH, de Andrade LP, Takahashi ACM. Effects of physical exercise on the cognition of older adults with frailty syndrome: A systematic review and meta-analysis of randomized trials. Arch Gerontol Geriatr. 2020 Dec 10;93:104322. doi: 10.1016/j.archger.2020.104322. Epub ahead of print. PMID: 33360014.
27. Sherrington C, Fairhall N, Kwok W, Wallbank G, Tiedemann A, Michaleff ZA, Ng CACM, Bauman A. Evidence on physical activity and falls prevention for people aged 65+ years: systematic review to inform the WHO guidelines on physical activity and sedentary behaviour. Int J Behav Nutr Phys Act. 2020 Nov 26;17(1):144. doi: 10.1186/s12966-020-01041-3. PMID: 33239019; PMCID: PMC7689963.
28. Sebio R, Serra-Prat M. Opinion of community-dwelling elderly obese about the barriers and facilitators to engage physical exercise. Sport Sci Health 2020; 16: 411–418. https://doi.org/10.1007/s11332-019-00616-3
29. Pahor M, Guralnik JM, Ambrosius WT, et al. Effect of structured physical activity on prevention of major mobility disability in older adults: the LIFE study randomized clinical trial. JAMA. 2014;311 (23):2387-2396.
30. Cesari M, Vellas B, Hsu FC, Newman AB, Doss H, King AC, et al. A physical activity intervention to treat the frailty syndrome in older persons-results from the LIFE-P study. J Gerontol A Biol Sci Med Sci. 2015 Feb;70(2):216-22.
31. Ng TP, Feng L, Nyunt MS, Feng L, Niti M, Tan BY, et al. Nutritional, Physical, Cognitive, and Combination Interventions and Frailty Reversal Among Older Adults: A Randomized Controlled Trial.Am J Med 2015;128(11):1225-1236.
32. Serra-Prat M, Sist X, Domenich R, Jurado L, Saiz A, Roces A, Palomera E, Terradelles M, Papiol M. Effectiveness of an intervention to prevent frailty in community-dwelling older people consulting in primary care. A randomized controlled trial. Age Ageing 2017; 46(3):401-7.
33. Puts MTE, Toubasi S, Andrew MK, Ashe MC, Ploeg J, Atkinson E, Ayala AP, Roy A, Rodríguez Monforte M, Bergman H, McGilton K. Interventions to prevent or reduce the level of frailty in community-dwelling older adults: a scoping review of the literature and international policies. Age Ageing. 2017 May 1;46(3):383-392.
34. Studenski S, Perera S, Patel K, et al. Gait speed and survival in older adults. JAMA. 2011;305(1):50-58.
35. Billot M, Calvani R, Urtamo A, et al. Preserving Mobility in Older Adults with Physical Frailty and Sarcopenia: Opportunities, Challenges, and Recommendations for Physical Activity Interventions. Clin Interv Aging. 2020 Sep 16;15:1675-1690.
36. Barzilay JI, Blaum C, Moore T, Xue QL, Hirsch CH, Walston JD, Fried LP. Insulin resistance and inflammation as precursors of frailty: the Cardiovascular Health Study. Arch Intern Med. 2007 Apr 9;167(7):635-41.
37. Mitchell WK, Williams J, Atherton P, Larvin M, Lund J, Narici M. Sarcopenia, dynapenia, and the impact of advancing age on human skeletal muscle size and strength; a quantitative review. Front Physiol. 2012;3:260.
38. Kazeminia M, Salari N, Vaisi-Raygani A, Jalali R, Abdi A, Mohammadi M, Daneshkhah A, Hosseinian-Far M, Shohaimi S. The effect of exercise on anxiety in the elderly worldwide: a systematic review and meta-analysis. Health Qual Life Outcomes. 2020 Nov 11;18(1):363.
39. Batsis JA, Gill LE, Masutani R, et al. Weight Loss Interventions in Older Adults with Obesity: A Systematic Review of Randomized Controlled Trials Since 2005. J Am Geriatr Soc. 2017; 65(2): 257–268.