Abstract
[Purpose] To examine short-term changes in frailty status over 3 months in older adults attending a hospital-based frailty outpatient clinic and to identify factors associated with frailty improvement. [Participants and Methods] This retrospective observational study included 100 community-dwelling adults aged ≥60 years who attended a hospital-based frailty outpatient clinic and were classified as frail or pre-frail at baseline. The outpatient care program included medical evaluation, nutritional counseling, and individualized home exercise instruction. Frailty was assessed using the Japanese Cardiovascular Health Study criteria at baseline and after 3 months. [Results] Frailty status improved in 51% of participants after 3 months. Among the frailty components, slow walking speed and exhaustion showed the greatest improvements. In multivariable logistic regression analysis, daily home exercise adherence was independently associated with frailty improvement, whereas exercising several days per week or not exercising was associated with significantly lower odds of improvement. [Conclusion] Frailty status improved in approximately half of the participants during 3 months of multidisciplinary outpatient care. Daily home exercise frequency was independently associated with frailty improvement in this real-world clinical setting.
Key words: Frailty, Aged, Multidisciplinary care team
INTRODUCTION
Frailty is a multidimensional geriatric syndrome characterized by decreased physiological reserves and increased vulnerability to external stressors, leading to adverse outcomes, such as disability, hospitalization, and mortality1,2,3). Given Japan’s rapidly aging population, prevention and management of frailty are critical public health priorities. The Japanese version of the Cardiovascular Health Study (J-CHS) criteria, which assesses five physical domains—grip strength, walking speed, exhaustion, physical activity, and unintentional weight loss—is widely used for frailty screening in both research and clinical practice4).
Frailty is a dynamic condition and potentially reversible condition, and previous studies have reported that multidomain approaches combining physical exercise, nutritional support, and comprehensive medical care may be associated with favorable frailty-related outcomes5,6,7). Among these components, regular physical activity, including daily walking and resistance training, is a crucial factor in preventing frailty and promoting recovery8,9,10,11). In addition, some previous studies have examined short-term frailty-related outcomes, particularly in exercise-based interventions and community-based programs12, 13). However, less is known about short-term changes in frailty status in real-world, hospital-based outpatient settings, where routine frailty care is delivered by a multidisciplinary team and may include medical assessment, nutritional counseling, individualized exercise instruction, and lifestyle or social support according to patient needs. From a clinical perspective, understanding such short-term changes is important because outpatient care often requires early evaluation to adjust management goals and sustain patient motivation.
The Frailty Outpatient Clinic at Matsumoto City Hospital (Matsumoto, Japan) provides an integrated program that combines medical evaluation, nutritional counseling by registered dietitians, and individualized home exercise instruction (resistance and balance training) by rehabilitation professionals. Follow-up assessments are conducted to monitor changes in physical, cognitive, and body composition parameters 3 months after the baseline evaluation. Unlike many community studies that focus on long-term prevention, this hospital-based setting enables direct medical management, including the evaluation of frailty-related diseases. Therefore, in the present study, we aimed to examine short-term changes in frailty status over 3 months and to identify factors associated with frailty improvement among older adults who attended this clinic.
PARTICIPANTS AND METHODS
In this retrospective observational study, consecutive outpatients who attended the Frailty Outpatient Clinic at Matsumoto City Hospital between January 2022 and December 2024 were considered for inclusion. The clinic evaluates approximately 10 new patients per month and provides frailty care through a multidisciplinary outpatient team. Assessments include physical and cognitive testing, medical evaluation, nutritional counseling, and individualized exercise instruction. Nurses also provided lifestyle guidance, and medical social workers were involved in social support and care coordination when needed. Participants were referred to the clinic through multiple pathways, including referrals from other hospital departments, recommendations from the city’s community-based frailty prevention programs, and self-referral by individuals concerned about functional decline.
Participants were community-dwelling adults aged ≥60 years who completed the clinic’s standardized frailty assessment protocol at both baseline and the 3-month follow-up. Individuals classified as robust at baseline, according to the Japanese version of the Fried frailty phenotype, were excluded.
The study protocol was approved by the ethics committee of Matsumoto City Hospital (approval no.: 05-3) on February 27, 2024, and conducted in accordance with the Declaration of Helsinki. As the study was observational, an opt-out approach was employed to obtain consent. Study information was disclosed on the hospital website, and participants were provided with the opportunity to decline participation.
All participants were assessed at baseline and at 3 months using a standardized protocol. Assessments included frailty components, physical performance, cognitive function, and body composition. The frailty clinic was operated by a multidisciplinary team consisting of physicians, registered dietitians, rehabilitation staff (physical and occupational therapists), and nurses.
At the initial visit, participants underwent the following comprehensive assessments and received routine outpatient care:
• Medical evaluation (physicians, approximately 30 minutes):
Physicians conducted clinical assessments to identify conditions related to frailty, reviewed medications, and ordered additional tests (e.g., brain CT or MRI) when neurological causes were suspected.
• Nutritional counseling (registered dietitians, approximately 30 minutes):
Each participant received individualized nutritional counseling focusing on protein intake, meal balance, and strategies to prevent weight loss or malnutrition.
• Exercise instruction (rehabilitation staff, approximately 60 minutes):
Physical and occupational therapists provided one-on-one home exercise instruction (~60 minutes), including resistance, balance, and gait training. Resistance exercises focused on the lower limbs and were performed at a Borg scale of approximately 13 for 10–15 repetitions in two or more sets. Participants were encouraged to walk at least 4,000 steps per day14). Balance training included tandem standing and single-leg stance. All participants received standardized home exercise instruction at baseline. Participants were provided with weekly home exercise log sheets including resistance training, balance exercises, and aerobic activity. Based on these prospective records, overall home exercise frequency during the 3-month period was categorized as “daily”, “several days per week”, or “none”. The “none” category represented non-adherence rather than absence of exercise prescription. Frail or pre-frail participants were additionally offered weekly outpatient rehabilitation sessions (20–40 minutes), as needed.
• Nursing support
Nurses assisted with body composition measurements (bioelectrical impedance analysis, InBody 770; InBody Co., Seoul, Korea)15), vital sign monitoring, and physician examinations. They also provided lifestyle guidance related to daily self-management when needed.
• Social support
Medical social workers provided social support and care coordination when needed, including consultation regarding community resources and welfare services.
At baseline, all assessment results were jointly reviewed by the team to determine the optimal individualized plan. Follow-up evaluations at 3 months used the same protocol to assess changes in frailty, cognition, and physical function.
Daily physical activity was objectively measured using a Life Corder accelerometer (Suzuken Co. Ltd., Nagoya, Japan)16). The participants were instructed to wear the device on their waist during waking hours for 7 consecutive days and remove it only during bathing or sleeping. The mean daily step count (steps/day) was calculated from valid monitoring days.
Data on demographic variables (age, sex, and body mass index [BMI]) and comorbidities (neurological, orthopedic, cardiac, and respiratory diseases; diabetes mellitus; and cancer) were obtained from medical records or structured interviews. Physical performance was assessed using grip strength, 10-m walking speed (comfortable and maximum), timed up-and-go test, single-leg standing time, and the weight-bearing index (WBI) of knee extension strength. Grip strength and walking speed, which were also used for J-CHS classification, were measured by trained rehabilitation staff according to the clinic’s standardized protocol. Grip strength was measured with the participant in a standing position using a handheld dynamometer, and the better value from two trials on each side was adopted. Comfortable walking speed was calculated from the time required to walk 10 m at a comfortable pace. The knee extension strength was measured using a handheld dynamometer (μTas F-1; Anima Corp., Tokyo, Japan)17). Each leg was measured twice, and the average of the highest values from both sides was divided by the body weight to calculate the WBI. Cognitive function was evaluated using the Japanese version of the Montreal Cognitive Assessment (MoCA-J)18), and depressive symptoms were assessed using the Geriatric Depression Scale19). Body composition, including the skeletal muscle mass index, phase angle, and body fat percentage, was measured using bioelectrical impedance analysis (InBody 770).
Definition of frailty and outcome classification: Frailty was assessed according to the J-CHS criteria4), which consists of the following five components:
(1) weakness (low grip strength: <28 kg in male and <18 kg in female individuals),
(2) slowness (usual walking speed <1.0 m/s),
(3) exhaustion (self-reported fatigue),
(4) low activity (no engagement in light exercise or physical activity), and
(5) weight loss (unintentional loss ≥2 kg in the past 6 months).
Participants meeting three or more criteria were classified as frail, those meeting one or two criteria were classified as pre-frail, and those meeting none were classified as robust.
Frailty status was reevaluated using the same criteria at the 3-month follow-up. Participants whose frailty category improved (e.g., from frail to pre-frail or robust, or from pre-frail to robust) were assigned to the “improved group”. Those who remained in the same category or whose frailty category worsened were assigned to the “maintained/worsened group”.
Missing baseline and background covariates, including demographic and medical factors, were imputed using the missForest algorithm20) with 100 trees (ntree=100) and a fixed random seed (1234) to ensure reproducibility. This nonparametric random forest-based method is suitable for mixed-type data and has been applied in clinical datasets with mixed continuous and categorical variables21). Continuous variables were presented as median (interquartile range), and categorical variables, as frequency (%).
Univariate logistic regression analyses were conducted to examine the associations between frailty improvement and each independent variable, including demographic and clinical characteristics (age, sex, BMI, and comorbidities), baseline physical and cognitive measures, and behavioral indicators related to rehabilitation participation and home exercise frequency. Participation in supervised outpatient rehabilitation was recorded as a binary variable (yes/no).
Variables considered clinically important a priori based on previous literature and clinical relevance, together with variables showing a univariate association with frailty improvement (p<0.10), were entered into the multivariable logistic regression model using a forced-entry approach22). Age and cognitive status were retained as adjustment variables because of their clinical relevance to frailty outcomes11), and respiratory disease and baseline daily step count were also included based on the univariate results. In the primary multivariable model, “daily” home exercise frequency was used as the reference category. To examine the ordinal nature of home exercise frequency, we additionally performed a trend analysis using multivariable binary logistic regression. Home exercise frequency was coded as 0=none, 1=several days per week, and 2=daily, and was entered into the model as an ordinal predictor. The same covariates as those in the primary multivariable model were included. Results of the logistic regression analyses are presented as odds ratios (ORs) with 95% confidence intervals (CIs) and p-values. All statistical analyses were performed using R version 4.3.2 (R Foundation for Statistical Computing, Vienna, Austria). Statistical significance was defined as p<0.05.
RESULTS
Overall, 100 participants were included in the analysis (Fig. 1). Of these, 31 (31%) were classified as frail and 69 (69%) as pre-frail at baseline according to the J-CHS criteria. The median age was 80.5 (range: 76.0–85.0) years, and 65% were female. At baseline, the median grip strength was 22.0 (range: 18.0–26.0) kg, and the comfortable walking speed was 0.96 (range: 0.74–1.15) m/s. The median daily step count was 2,594 (range: 1,292–4,245) steps/day (Table 1).
Fig. 1.
Flow chart of participant inclusion and exclusion.
Table 1. Baseline characteristics in clinical, functional, and frailty-related parameters of the study participants (N=100).
| N=100 | Missing | ||
| Age (years) | 80.50 [76.00, 85.00] | 0 | |
| BMI (kg/m2) | 22.45 [20.00, 24.88] | 19 | |
| Sex: female (%) | 65 (65.0) | 0 | |
| Neurological disease (%) | 13 (13.0) | 14 | |
| Orthopedic disease (%) | 30 (30.0) | 17 | |
| Cardiac disease (%) | 22 (22.0) | 12 | |
| Respiratory disease (%) | 8 (8.0) | 12 | |
| Diabetes mellitus (%) | 11 (11.0) | 12 | |
| Cancer (%) | 7 (7.0) | 12 | |
| Baseline grip strength (kg) | 22.00 [18.00, 26.00] | 9 | |
| Baseline comfortable walking speed (m/s) | 0.96 [0.74, 1.15] | 10 | |
| Baseline maximum walking speed (m/s) | 1.24 [0.93, 1.49] | 14 | |
| Baseline WBI (points) | 0.40 [0.29, 0.44] | 25 | |
| Baseline TUG (s) | 11.20 [8.91, 14.24] | 10 | |
| Baseline single-leg standing time (s) | 12.86 [5.04, 30.98] | 12 | |
| Baseline MoCA-J (points) | 23.00 [20.00, 26.00] | 10 | |
| Baseline SMI (kg/m2) | 6.20 [5.30, 7.00] | 20 | |
| Baseline phase angle (°) | 4.10 [3.70, 4.40] | 21 | |
| Baseline average step count (steps/d) | 2,593.50 [1291.50, 4245.25] | 18 | |
| Baseline GDS (points) | 4.00 [2.75, 8.00] | 46 | |
| Baseline low grip strength (%) | 33 (33.0) | 5 | |
| Baseline slow walking speed (%) | 54 (54.0) | 7 | |
| Baseline low activity (%) | 40 (40.0) | 0 | |
| Baseline weight loss (%) | 27 (27.0) | 0 | |
| Baseline exhaustion (%) | 41 (41.0) | 0 | |
| Home exercise frequency: | 34 | ||
| Daily (%) | 37 (37.0) | ||
| Several days/week (%) | 36 (36.0) | ||
| None | 17 (17.0) | ||
| Individual rehabilitation provided (%) | 39 (39.0) | ||
| Nutritional counseling provided (%) | 79 (79.0) | ||
| Baseline frailty status: pre-frail (%) | 69 (69.0) | ||
| Baseline frailty status: frail (%) | 31 (31.0) | ||
Data are presented as median (interquartile range) or number (%). Missing values indicate the number of participants with unavailable data for each variable. Frailty categories were defined according to the Japanese Cardiovascular Health Study criteria. BMI: body mass index; eGFR: estimated glomerular filtration rate; WBI: Walking Balance Index; TUG: Timed Up and Go; MoCA-J: Montreal Cognitive Assessment-Japanese version; SMI: skeletal muscle mass index; GDS: Geriatric Depression Scale.
Overall, 51 participants (51%) showed improvement in frailty status, whereas 49 (49%) maintained the same category or worsened. The proportion of participants categorized as frail decreased from 31% at baseline to 11% at 3 months, while the proportion categorized as robust increased to 35%. At baseline, the most common frailty components were slow walking speed (54%), exhaustion (41%), and low activity (40%). At 3 months, the prevalence of all J-CHS components decreased in the overall sample. McNemar’s test showed significant reductions in each component. In the improved group, decreases in slow walking speed and exhaustion were particularly prominent, whereas these changes were less evident in the maintained/worsened group (Fig. 2). Detailed absolute numbers, percentages, and paired comparisons are presented in Supplementary Table 1.
Fig. 2.
Changes in components of the Japanese Cardiovascular Health Study (J-CHS) frailty criteria from baseline to 3 months in the improved and maintained/worsened groups.
Values are presented as percentages within each group. Corresponding absolute numbers and overall paired comparisons are provided in Supplementary Table 1. The improved group included participants whose frailty category improved over 3 months (n=51), and the maintained/worsened group included those whose frailty category remained unchanged or worsened (n=49).
The univariate logistic regression analysis (Table 2) showed that home exercise frequency was significantly associated with frailty improvement. Compared with participants who exercised daily, the odds of improvement were lower in those who exercised several days per week (OR: 0.27, 95% CI: 0.10–0.67, p=0.005) and in those who did not exercise (OR: 0.11, 95% CI: 0.03–0.38, p=0.001). No significant associations were observed for baseline step count (per 1,000 steps/day), age, grip strength, BMI, or phase angle.
Table 2. Univariate logistic regression analysis of the factors associated with improvement in frailty after 3 months.
| Variable | OR | 95% CI (lower) | 95% CI (upper) |
| Age (years) | 0.94 | 0.87 | 1.01 |
| Baseline grip strength (kg) | 1.04 | 0.98 | 1.11 |
| Baseline comfortable walking speed (m/s) | 3.98 | 0.95 | 18.36 |
| Baseline maximum walking speed (m/s) | 2.34 | 0.82 | 7.11 |
| Baseline WBI | 21.23 | 0.64 | 877.42 |
| BMI (kg/m2) | 0.97 | 0.87 | 1.08 |
| Baseline TUG (s) | 0.97 | 0.90 | 1.02 |
| Baseline single-leg standing time (s) | 1.00 | 0.98 | 1.02 |
| Baseline MoCA-J (points) | 1.00 | 0.90 | 1.12 |
| Baseline SMI (kg/m2) | 0.99 | 0.66 | 1.49 |
| Baseline phase angle (°) | 1.46 | 0.68 | 3.19 |
| Baseline average step count (per 1,000 steps/day) | 1.19 | 1.00 | 1.42 |
| Baseline GDS (points) | 0.92 | 0.82 | 1.03 |
| Sex: male (%) | 0.86 | 0.38 | 1.96 |
| Neurological disease (%) | 0.80 | 0.24 | 2.60 |
| Orthopedic disease (%) | 1.51 | 0.65 | 3.61 |
| Cardiac disease (%) | 1.52 | 0.59 | 4.08 |
| Respiratory disease (%) | 0.12 | 0.01 | 0.71 |
| Diabetes mellitus (%) | 0.32 | 0.07 | 1.19 |
| Cancer (%) | 0.70 | 0.13 | 3.36 |
| Home exercise frequency: several days/week (%) (ref: daily) | 0.27** | 0.10 | 0.67 |
| Home exercise frequency: none (%) | 0.11*** | 0.03 | 0.38 |
| Individual rehabilitation provided (yes/no) | 0.79 | 0.36 | 1.75 |
| Nutritional counseling provided (%) | 1.75 | 0.59 | 5.55 |
*p<0.05, **p<0.01, ***p<0.001. ORs and 95% CIs were calculated using univariate logistic regression analysis to identify factors associated with improvement in frailty at 3 months. Improvement was defined as a shift to a lower frailty category based on the Japanese Cardiovascular Health Study criteria. OR: odds ratio; CI: confidence interval; BMI: body mass index; eGFR: estimated glomerular filtration rate; WBI: Walking Balance Index; TUG: Timed Up and Go; MoCA-J: Montreal Cognitive Assessment–Japanese version; SMI: skeletal muscle mass index; GDS: Geriatric Depression Scale; KCL: Kihon Checklist; ref: reference.
Table 3 presents the results of the multivariable logistic regression analysis. After adjusting for age, MoCA-J score, home exercise frequency, respiratory disease, and baseline step count, home exercise frequency remained independently associated with frailty improvement. Compared with those who exercised daily, the odds of improvement were lower in participants who exercised several days per week (OR: 0.29, 95% CI: 0.11–0.77, p=0.014) and in those who did not exercise (OR: 0.11, 95% CI: 0.02–0.40, p=0.002). Baseline step count, expressed per 1,000 steps/day, was not significantly associated with frailty improvement in the multivariable model.
Table 3. Multivariate logistic regression analysis of factors independently associated with improvement in frailty after 3 months.
| Variable | OR | 95% CI (lower) | 95% CI (upper) |
| Age (years) | 0.948 | 0.869 | 1.028 |
| Baseline MoCA-J score (points) | 0.957 | 0.839 | 1.087 |
| Presence of respiratory disease (yes/no) | 0.129 | 0.006 | 0.878 |
| Baseline average step count per day (per 1,000 steps/day) | 1.000 | 0.999 | 1.000 |
| Home exercise frequency: several days/week (ref: daily) | 0.292* | 0.105 | 0.773 |
| Home exercise frequency: None (ref: daily) | 0.107** | 0.023 | 0.404 |
*p<0.05, **p<0.01. Multivariate logistic regression analysis was performed to identify independent factors associated with improvement in frailty at 3 months. Improvement was defined as a shift to a lower frailty category based on the Japanese Cardiovascular Health Study criteria. MoCA-J: Montreal Cognitive Assessment-Japanese version; OR: odds ratio; CI: confidence interval; ref: reference.
In the additional trend analysis treating home exercise frequency as an ordinal predictor, higher home exercise frequency was significantly associated with greater odds of frailty improvement after adjustment for age, MoCA-J score, respiratory disease, and baseline step count (OR per one-category increase: 3.14, 95% CI: 1.61–6.10, p for trend <0.001; Supplementary Table 2).
The proportion of participants who received supervised outpatient rehabilitation was similar between the improved and maintained/worsened groups (20/51 [39.2%] vs. 19/44 [43.2%], p=0.835; Supplementary Table 3).
As a sensitivity analysis, we performed a complete-case multivariable logistic regression analysis using the same model as in the primary analysis (n=78). The overall direction of the associations was similar to that of the imputed analysis, with home exercise frequency remaining significantly associated with frailty improvement (Supplementary Table 4).
DISCUSSION
In this study, we examined short-term changes in frailty status over 3 months in older adults attending a multidisciplinary frailty outpatient clinic and explored factors associated with frailty improvement. Frailty status improved in approximately half of the participants, and daily home exercise frequency was independently associated with improvement. Among the J-CHS frailty components, walking speed and exhaustion showed the largest changes over time in the improved group.
Previous studies have shown that frailty status can change over time and that multidomain care or exercise-based programs may be associated with favorable outcomes5,6,7). In the present study, improvement in frailty status was observed within 3 months in a substantial proportion of participants attending a hospital-based frailty clinic. Because this was a retrospective observational study without a control group, our findings should be interpreted as temporal changes observed during routine outpatient care rather than as evidence of treatment effectiveness. Nevertheless, the findings suggest that short-term changes in frailty status can be captured in a real-world clinical setting.
Among the examined factors, home exercise frequency was most consistently associated with frailty improvement. Participants who reported daily home exercise were more likely to show improvement than those who exercised several days per week or not at all. This finding is consistent with previous studies reporting that regular exercise and exercise adherence are related to better functional outcomes and favorable frailty transitions9).
Studies have shown that increased physical activity and regular exercise are beneficial in improving frailty9). In particular, a combination of supervised exercise sessions performed two to three times per week and additional home-based training has been shown to effectively enhance frailty status, as supported by systematic reviews5). Similarly, home-based exercise programs have been reported to improve the average number of frailty criteria met, which is comparable to the effects of supervised interventions12, 13). These studies typically recommended performing aerobic exercise or a combination of resistance and aerobic exercises at least three times per week; however, they did not specifically examine the differences in exercise frequency within home-based programs.
In this real-world analysis, daily home exercise frequency showed a significant association with frailty improvement. Although home exercise frequency was recorded prospectively using weekly log sheets, it was based on self-reported records and may have been subject to reporting bias. In addition, reverse causality cannot be excluded; participants who were physically and functionally able to exercise regularly may have been more likely to show improvement in frailty status. Therefore, the present findings should be interpreted as an association rather than a causal effect of exercise frequency. The home exercise program used in this clinic focused on lower-limb strengthening and balance exercises that can be performed without special equipment, which may make it feasible for community-dwelling older adults.
Among the components of the J-CHS frailty criteria, walking speed and exhaustion showed the greatest improvement. A decline in walking speed has been reported to be a strong predictor of future functional decline and need for long-term care23). Moreover, walking speed is closely associated with survival and is widely recognized as an important indicator of overall health and functional status24). In the present study, these changes were observed during follow-up in a multidisciplinary outpatient clinic; however, the contribution of each care component, such as medical evaluation, nutritional counseling, and exercise instruction, could not be separated. Thus, the observed changes in walking speed and exhaustion should be interpreted descriptively.
Our findings suggest that multidisciplinary frailty clinics may provide a useful framework for monitoring short-term changes in frailty status and supporting individualized outpatient management. Because physicians, dietitians, rehabilitation professionals, and nurses evaluate patients in the same setting, potentially modifiable problems can be identified and followed over time. At the same time, the present study did not allow us to determine which specific component of care was most strongly related to the observed changes.
This study has several limitations. First, as a retrospective observational study without a control group, causal inferences cannot be made. Second, the 3-month follow-up period was relatively short, and the durability of the observed changes remains unclear. Third, although missing data were statistically imputed, residual confounding and potential bias related to missingness could not be excluded. Fourth, although home exercise frequency was recorded prospectively using weekly self-reported logs, the accuracy of these records could not be independently verified. In addition, the content and intensity of home exercises were not objectively monitored, limiting a precise evaluation of dose–response relationships. Furthermore, reverse causality cannot be excluded because participants with better physical and functional status may have been more able to perform home exercises regularly, whereas those with underlying physical or psychological limitations may have been less likely to adhere to exercise recommendations. Finally, because participants were outpatients from a single hospital clinic, the generalizability of these findings to other settings may be limited. However, the findings may be applicable to similar community-dwelling older outpatients with pre-frailty or frailty who receive hospital-based frailty assessment and care.
Frailty status improved in approximately half of the participants during 3 months of multidisciplinary outpatient care. Daily home exercise frequency was independently associated with frailty improvement. Walking speed and exhaustion showed the largest changes over time. These findings support the clinical relevance of short-term frailty monitoring in hospital-based outpatient settings.
Funding
This work was supported by the Japan Society for the Promotion of Science KAKENHI (grant number: 24K20496).
Conflict of interest
The authors declare no potential conflicts of interest concerning the authorship and publication of this article.
Supplementary
Funding Statement
This work was supported by the Japan Society for the Promotion of Science KAKENHI (grant number: 24K20496).
REFERENCES
- 1.Clegg A, Young J, Iliffe S, et al. : Frailty in elderly people. Lancet, 2013, 381: 752–762. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Fried LP, Tangen CM, Walston J, et al. Cardiovascular Health Study Collaborative Research Group: Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci, 2001, 56: M146–M156. [DOI] [PubMed] [Google Scholar]
- 3.Kojima G, Iliffe S, Walters K: Frailty index as a predictor of mortality: a systematic review and meta-analysis. Age Ageing, 2018, 47: 193–200. [DOI] [PubMed] [Google Scholar]
- 4.Satake S, Arai H: The revised Japanese version of the Cardiovascular Health Study criteria (revised J-CHS criteria). Geriatr Gerontol Int, 2020, 20: 992–993. [DOI] [PubMed] [Google Scholar]
- 5.Apóstolo J, Cooke R, Bobrowicz-Campos E, et al. : Effectiveness of interventions to prevent pre-frailty and frailty progression in older adults: a systematic review. JBI Database Syst Rev Implement Reports, 2018, 16: 140–232. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Dedeyne L, Deschodt M, Verschueren S, et al. : Effects of multi-domain interventions in (pre)frail elderly on frailty, functional, and cognitive status: a systematic review. Clin Interv Aging, 2017, 12: 873–896. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Theou O, Stathokostas L, Roland KP, et al. : The effectiveness of exercise interventions for the management of frailty: a systematic review. J Aging Res, 2011, 2011: 569194. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Kim H, Kim M, Kojima N, et al. : Exercise and nutritional supplementation on community-dwelling elderly Japanese women with sarcopenic obesity: a randomized controlled trial. J Am Med Dir Assoc, 2016, 17: 1011–1019. [DOI] [PubMed] [Google Scholar]
- 9.Zeng Z, Hsu CL, Sit CH, et al. : The role of physical activity and physical function in predicting physical frailty transitions in Chinese older adults: longitudinal observational study from CHARLS. JMIR Aging, 2025, 8: e75887. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Zhu LY, Chan R, Kwok T, et al. : Effects of exercise and nutrition supplementation in community-dwelling older Chinese people with sarcopenia: a randomized controlled trial. Age Ageing, 2019, 48: 220–228. [DOI] [PubMed] [Google Scholar]
- 11.Liu J, Zhu Y, Tan JK, et al. : Factors associated with frailty in older adults in community and nursing home settings: a systematic review with a meta-analysis. J Clin Med, 2024, 13: 2382. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Meng NH, Li CI, Liu CS, et al. : Effects of concurrent aerobic and resistance exercise in frail and pre-frail older adults: a randomized trial of supervised versus home-based programs. Medicine (Baltimore), 2020, 99: e21187. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Karmakar P, Wong MC, AlMarzooqi MA, et al. : Enhancing physical and psychosocial health of older adults in Saudi Arabia through walking: comparison between supervised group-based and non-supervised individual-based walking. Eur J Investig Health Psychol Educ, 2023, 13: 2342–2357. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Watanabe D, Yoshida T, Watanabe Y, et al. : Objectively measured daily step counts and prevalence of frailty in 3,616 older adults. J Am Geriatr Soc, 2020, 68: 2310–2318. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.McLester CN, Nickerson BS, Kliszczewicz BM, et al. : Reliability and agreement of various InBody body composition analyzers as compared to dual-energy x-ray absorptiometry in healthy men and women. J Clin Densitom, 2020, 23: 443–450. [DOI] [PubMed] [Google Scholar]
- 16.Kumahara H, Schutz Y, Ayabe M, et al. : The use of uniaxial accelerometry for the assessment of physical-activity-related energy expenditure: a validation study against whole-body indirect calorimetry. Br J Nutr, 2004, 91: 235–243. [DOI] [PubMed] [Google Scholar]
- 17.Katoh M, Yamasaki H: Comparison of reliability of isometric leg muscle strength measurements made using a hand-held dynamometer with and without a restraining belt. J Phys Ther Sci, 2009, 21: 37–42. [Google Scholar]
- 18.Fujiwara Y, Suzuki H, Yasunaga M, et al. : Brief screening tool for mild cognitive impairment in older Japanese: validation of the Japanese version of the Montreal Cognitive Assessment. Geriatr Gerontol Int, 2010, 10: 225–232. [DOI] [PubMed] [Google Scholar]
- 19.Friedman B, Heisel MJ, Delavan RL: Psychometric properties of the 15-item geriatric depression scale in functionally impaired, cognitively intact, community-dwelling elderly primary care patients. J Am Geriatr Soc, 2005, 53: 1570–1576. [DOI] [PubMed] [Google Scholar]
- 20.Stekhoven DJ, Bühlmann P: MissForest—non-parametric missing value imputation for mixed-type data. Bioinformatics, 2012, 28: 112–118. [DOI] [PubMed] [Google Scholar]
- 21.Nakamura K, Sasaki T, Yokokawa Y, et al. : Health literacy and frailty: the mediating role of instrumental activities of daily living. Psychogeriatrics, 2025, 25: e70010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Bursac Z, Gauss CH, Williams DK, et al. : Purposeful selection of variables in logistic regression. Source Code Biol Med, 2008, 3: 17. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Makizako H, Shimada H, Doi T, et al. : Impact of physical frailty on disability in community-dwelling older adults: a prospective cohort study. BMJ Open, 2015, 5: e008462. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Studenski S, Perera S, Patel K, et al. : Gait speed and survival in older adults. JAMA, 2011, 305: 50–58. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.