Abstract
[Purpose] To determine sex-based differences in body composition, based on discharge destination of patients admitted to a convalescent rehabilitation unit. [Participants and Methods] A total of 135 patients admitted to a convalescent rehabilitation unit were included. Body composition, motor function subscale of the Functional Independence Measure (mFIM) score, length of stay, and mean number of rehabilitation sessions per day were measured and compared between home and non-home discharge groups. [Results] The home and non-home discharge groups comprised 112 (45 males and 67 females) and 23 (nine males and 14 females) participants, respectively. Differences were observed in phase angle (PhA), skeletal muscle mass index (SMI), extracellular water to total body water ratio, and mFIM score for both sexes, based on discharge destination. Binomial logistic regression analysis with discharge destination as the dependent variable showed that the mFIM score and length of stay were influencing factors for males and females, respectively. [Conclusion] PhA and SMI are promising new tools for assessing common discharge destinations in both sexes, suggesting an impact of recovery in the mFIM score and on length of stay in male and female patients, respectively.
Keywords: Body composition, Convalescent rehabilitation units, Functional Independence Measure
INTRODUCTION
The Japanese healthcare system includes convalescent rehabilitation units, where patients who have completed acute treatment recover their functional abilities through intensive rehabilitation. These units are intended to facilitate patient recovery and return to daily life and the community. However, owing to the severity of conditions and factors related to aging, an increasing number of patients require ongoing care and face challenges regarding discharge home1). To address this issue, it is essential to assess patients’ physical characteristics and functional independence, set appropriate discharge goals, and develop effective care plans. Previous studies have shown that body composition, including muscle mass, fat mass, and water content, has a significant impact on rehabilitation outcomes and patients’ lives after discharge2, 3). Furthermore, the Functional Independence Measure (FIM) is widely used to assess motor and activities of daily living (ADL) abilities in rehabilitation. The motor function subscale of the FIM (mFIM) plays an important role in determining discharge destination and planning individualized care strategies4, 5).
Prior studies have suggested that patients discharged home tend to have greater muscle mass and motor capacity than those transitioning to institutional care6). Furthermore, patients initially identified as being at risk of institutionalization have been shown to have improved outcomes with targeted rehabilitation interventions7). Although some knowledge of differences in body composition and mFIM scores according to the discharge site has been obtained, comprehensive analyses and studies involving sex differentiation are scarce.
Therefore, the purpose of this study was to examine sex differences in body composition, mFIM score at discharge, length of stay, and average number of rehabilitation sessions per day by discharge destination among patients admitted to a convalescent rehabilitation unit. By identifying these differences, we aim to contribute to the development of effective care approaches tailored to individual needs and to strengthen support systems to facilitate discharge home and return to the community.
PARTICIPANTS AND METHODS
This study included 135 patients (54 males, age 78.6 ± 7.2 years; 81 females, age 84.8 ± 6.4 years; mean ± standard deviation) aged 65 years or older admitted to the International University of Health and Welfare, Shioya Hospital Convalescent Rehabilitation Unit between August 2021 and September 2022. The medical categories included neurosurgery (40 patients), neurology (20 patients), and orthopedics (75 patients).
Height, weight, and body composition were measured within 2 weeks of discharge. Height was measured with participants in the supine position using a measuring tape in those unable stand, and weight was measured using a wheelchair scale for patients unable stand. Body mass index (BMI) was calculated as weight (kg) divided by height squared (m2). Body composition was measured using a multifrequency bioimpedance device (InBody S10; InBody, Tokyo, Japan) to assess body fat percentage, phase angle (PhA), skeletal muscle mass index (SMI), and extracellular water/total body water (ECW/TBW) ratio. This measurement device can be used in a supine or seated position when they are unable to stand or sit due to severe functional disability or bed-ridden condition8, 9).
Participants without permission from their attending physician to undergo the measurement, with an implanted electronic medical device such as a pacemaker, and wearing a life support device such as a biometric monitor were excluded from the analysis. Data regarding the mFIM score at discharge, length of stay, and average number of rehabilitation sessions per day were collected from the hospital’s electronic medical records.
This study was conducted in compliance with the Declaration of Helsinki, with approval from the Research Ethics Review Committee of the International University of Health and Welfare (Approval number: 23-Io-10). Informed consent was obtained from the participants or their families after a thorough explanation of the study.
Patients were classified into home discharge and non-home discharge groups. The home discharge group included those returning home or to serviced senior housing, while the non-home discharge group consisted of patients admitted to a geriatric health care facility, a short-stay facility, or transferred to a hospital. To compare independent variables between the two groups, unpaired t-tests were conducted. Furthermore, a binomial logistic regression analysis was performed to predict discharge destination, using discharge destination as the dependent variable and factors that showed significant differences in the unpaired t-test as independent variables. All statistical analyses were conducted using SPSS Statistics (version 29; IBM Corp., Armonk, NY, USA), with a significance level of 5%.
RESULTS
The home discharge group comprised 112 patients (45 males and 67 females), while the non-home discharge group included 23 patients (9 males and 14 females). Among male patients, those in the home discharge group had significantly higher weight, BMI, PhA, SMI, and mFIM scores compared to those in the non-home discharge group. Similarly, female patients in the home discharge group had significantly higher age, height, weight, PhA, SMI, ECW/TBW, mFIM scores, length of stay, and average number of rehabilitation sessions per day than those in the non-home discharge group (Table 1). For both sexes, none of the confounders showed more than a moderate correlation coefficient (Tables 2, 3). Additionally, binomial logistic regression analysis identified the mFIM score at discharge as a significant factor for male patients, while length of stay was significant for female patients (Table 4).
Table 1. Comparison of basic attributes between home and non-home discharge groups.
| Males, n=54 | Females, n=81 | |||||
| Home discharge group | Non-home discharge group | p-value | Home discharge group | Non-home discharge group | p-value | |
| n=45 | n=9 | n=67 | n=14 | |||
| Age (years) | 77.0 ± 8.6 | 80.1 ± 5.7 | 80.7 ± 7.6 | 88.8 ± 5.1 | * | |
| Height (cm) | 162.1 ± 7.4 | 162.1 ± 3.7 | 148.7 ± 6.6 | 141.3 ± 6.8 | * | |
| Weight (kg) | 56.7 ± 7.2 | 51.0 ± 5.0 | * | 48.6 ± 9.2 | 41.7 ± 6.2 | * |
| BMI (kg/m2) | 21.6 ± 2.4 | 19.4 ± 2.0 | * | 22.0 ± 4.1 | 20.9 ± 3.2 | |
| Percent body fat (%) | 27.2 ± 7.7 | 27.1 ± 7.5 | 33.6 ± 9.3 | 30.6 ± 12.0 | ||
| PhA (°) | 4.4 ± 0.8 | 3.6 ± 0.9 | * | 3.8 ± 0.8 | 3.1 ± 0.7 | * |
| SMI (kg/m2) | 6.5 ± 0.9 | 5.8 ± 0.6 | * | 5.4 ± 1.1 | 4.7 ± 0.5 | * |
| ECW/TBW (%) | 0.402 ± 0.010 | 0.407 ± 0.013 | 0.406 ± 0.016 | 0.419 ± 0.009 | * | |
| mFIM at discharge (points) | 75.5 ± 16.8 | 56.2 ± 21.5 | * | 73.7 ± 17.5 | 50.9 ± 18.7 | * |
| Length of stay (days) | 72.1 ± 34.9 | 72.2 ± 46.0 | 62.7 ± 29.0 | 89.9 ± 31.5 | * | |
| Average number of rehabilitation sessions per day (points) | 8.0 ± 0.8 | 7.7 ± 0.5 | 7.9 ± 0.8 | 6.9 ± 1.2 | * | |
Data are presented as the mean ± standard deviation.
Unpaired t-test was used to study the differences between the group. *p<0.05.
BMI: body mass index; PhA: phase angle; SMI: skeletal muscle mass index; ECW/TBW: extracellular water/total body water; mFIM: motor function subscale of the Functional Independence Measure.
Table 2. Correlation coefficients among confounding factors (male patients).
| Age | Height | Weight | BMI | PBF | PhA | SMI | ECW/TBW | mFIM | Length of stay | Rehabilitation | |
| Age | 1 | ||||||||||
| Height | −0.43* | 1 | |||||||||
| Weight | −0.37* | 0.45* | 1 | ||||||||
| BMI | −0.08 | −0.24 | 0.76* | 1 | |||||||
| Percent Body Fat | 0.19 | −0.22 | 0.30* | 0.50* | 1 | ||||||
| PhA | −0.32* | 0.22 | 0.56* | 0.44* | −0.02 | 1 | |||||
| SMI | −0.32* | 0.30* | 0.63* | 0.47* | −0.39* | 0.53* | 1 | ||||
| ECW/TBW | 0.33* | −0.31* | −0.44* | −0.25 | 0.05 | −0.73* | −0.22 | 1 | |||
| mFIM at discharge | −0.24 | 0.14 | 0.33* | 0.25 | −0.02 | 0.52* | 0.35* | −0.42* | 1 | ||
| Length of stay | 0.11 | 0.10 | 0.05 | −0.03 | 0.04 | −0.06 | −0.05 | 0.04 | −0.25 | 1 | |
| Average number of rehabilitationsessions per day | −0.41* | 0.03 | 0.19 | 0.18 | −0.14 | 0.23 | 0.24 | −0.26 | 0.30* | 0.23 | 1 |
Pearson’s rank correlation coefficient. *p<0.05.
BMI: body mass index; PhA: phase angle; SMI: skeletal muscle mass index; ECW/TBW: extracellular water/total body water; mFIM: motor function subscale of the Functional Independence Measure.
Table 3. Correlation coefficients among confounding factors (female patients).
| Age | Height | Weight | BMI | PBF | PhA | SMI | ECW/TBW | mFIM | Length of stay | Rehabilitation | |
| Age | 1 | ||||||||||
| Height | −0.48* | 1 | |||||||||
| Weight | −0.24* | 0.37* | 1 | ||||||||
| BMI | 0.01 | −0.14 | 0.87* | 1 | |||||||
| Percent body fat | −0.01 | −0.15 | 0.61* | 0.74* | 1 | ||||||
| PhA | −0.45* | 0.21 | 0.39* | 0.31* | 0.15 | 1 | |||||
| SMI | −0.22* | 0.32* | 0.77* | 0.65* | 0.10 | 0.51* | 1 | ||||
| ECW/TBW | 0.31* | −0.27* | −0.16 | −0.01 | 0.05 | −0.67* | −0.33* | 1 | |||
| mFIM at discharge | −0.45* | 0.51* | 0.34* | 0.10 | 0.05 | 0.57* | 0.35* | −0.35* | 1 | ||
| Length of stay | 0.20 | −0.10 | −0.11 | −0.07 | −0.18 | −0.17 | 0.04 | 0.04 | −0.36* | 1 | |
| Average number of rehabilitationsessions per day | −0.47* | 0.46* | 0.32* | 0.10 | 0.15 | 0.31* | 0.25* | −0.33* | 0.37* | −0.07 | 1 |
Pearson’s rank correlation coefficient. *p<0.05.
BMI: body mass index; PhA: phase angle; SMI: skeletal muscle mass index; ECW/TBW: extracellular water/total body water; mFIM: motor function subscale of the Functional Independence Measure.
Table 4. Binomial logistic regression analysis for home discharge according to independent variables.
| β | p-value | Exp (β) | 95% CI for Exp (β) | ||
| Lower | Upper | ||||
| Male patients | |||||
| BMI | 0.365 | 1.441 | 0.995 | 2.087 | |
| mFIM at discharge | 0.045 | * | 1.046 | 1.005 | 1.090 |
| Female patients | |||||
| mFIM at discharge | 0.032 | 1.032 | 0.996 | 1.070 | |
| Length of stay | −0.023 | * | 0.978 | 0.955 | 1.000 |
Place of discharge (home discharge=1, non-home discharge=0). *p<0.05.
BMI: body mass index; mFIM: motor function subscale of the Functional Independence Measure; CI: confidence interval.
DISCUSSION
We examined sex-based differences in body composition, functional assessment, and rehabilitation status between home and non-home discharge groups of older patients admitted to a convalescent rehabilitation unit. Our analysis revealed that the mFIM score at discharge and length of stay were strong independent predictors of home discharge for male and female patients, respectively.
The significant predictive value of the mFIM score at discharge as a determinant of discharge destination in male patients supports a previous finding that recovery of motor function after rehabilitation intervention is directly related to return home10). The mFIM score is a quantitative measure of a patient’s independence in ADL, and its improvement is an important indicator that increases the likelihood of returning home11, 12). Since the timing of rehabilitation intervention may be influenced by the patient’s chief complaint, such as subjective fatigue or lowered fatigue threshold due to low nutrition or heart failure symptoms, so it is recommended that female heart failure patients receive rehabilitation services in a timely manner. Furthermore, parameters such as body weight, BMI, PhA, and SMI, which are objective indicators of nutritional status and muscle mass, may have significantly influenced the choice of discharge destination because they reflect the quality of general condition and functional recovery. For men, in addition to these biological indices, interventions that comprehensively support improvement in ADL, such as improvement of living environment and appropriate adjustment of welfare equipment, may play a decisive role in facilitating patients’ return home.
However, for female patients, length of stay was a significant predictor, as long duration of stay may make it more difficult to return home. In addition, significant differences were observed in the average number of rehabilitation sessions per day, suggesting that the timing and duration of rehabilitation intervention, as well as the number of interventions, may be important factors in determining discharge destination. Women tend to undergo more pronounced physiological changes than men do, such as age-related changes in body composition, reduction in skeletal muscle mass, and appearance of edema, and fluctuations in ECW/TBW ratio reflect changes specific to women as an indicator of fluid balance and edema status13, 14). These factors, coupled with the timing of rehabilitation intervention and optimization of the number of interventions, may influence decisions regarding discharge destination. In other words, for women, a rapid response to the start of rehabilitation and an appropriate number of interventions may be key to a more effective return home.
It is important to note that discharge-related decisions are also influenced by social and environmental factors, such as family support, living environment, and availability of long-team care insurance services15). These factors, along with physical function, play an important role in post-discharge life. We plan to conduct further research based on the impact of social hospitalization due to care insurance service procedures and neglect. For future perspectives, an integrated analysis of physical and social factors is required.
We found that physical composition and functional assessment of older patients in a recovery unit have a sex-specific effect on discharge destination decisions. This underscores the importance of individualized care and rehabilitation interventions that consider sex differences and provide a pathway for future intervention program development and long-term outcome evaluation.
Funding
This study was funded by JSPS KAKENHI (grant numbers 21K10581 and 24K23756).
Conflicts of interest
The authors have no conflicts of interest relevant to this article.
REFERENCES
- 1.Kakehi A: About the 2020 National Fact-Finding Survey. http://www.rehabili.jp/publications/book/b2021_04/2021_04_2.pdf (Accessed Jan. 23, 2025)
- 2.Rinaldo N, Pasini A, Straudi S, et al. : Effects of exercise, rehabilitation, and nutritional approaches on body composition and bone density in people with multiple sclerosis: a systematic review and meta-analysis. J Funct Morphol Kinesiol, 2023, 8: 132. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Patrick AE, Umaru MB, Muhammad AA, et al. : The impact of body composition on functional recovery, mortality, and survival: a systematic review of research conducted in a cohort of stroke survivors. Egypt J Neurol Psychiatr Neurosurg, 2024, 60: 111. [Google Scholar]
- 4.Wolfram W, Katja JV, Stefan G: FIM-score predictors of discharge destination in older patients admitted for inpatient rehabilitation. Tasman Med J, 2020, 2: 68–73. [Google Scholar]
- 5.Onishi Y, Kimura S, Ishikawa KB, et al. : Clarification of factors determining discharge destination among elderly patients after stroke with low levels of independence in activities of daily living: a retrospective study. Arch Rehabil Res Clin Transl, 2022, 4: 100226. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Moriwaki M, Hayashida K, Ogata Y: Factors associated with non-home discharge of patients hospitalized for hip fracture: a nationwide retrospective study using the Japanese diagnostic procedure combination database. Medicine (Baltimore), 2023, 102: e33138. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Kikuo O: The role of rehabilitation in the elderly to get better functionings: activities change activities of functionings. J Int Univ Health Welfare, 2015, 20: 1–8. [Google Scholar]
- 8.Kubo A, Sato M, Yakabi A, et al. : Association between regional phase angle and level of locomotion among older females requiring long-term care in a health facility. J Phys Ther Sci, 2024, 36: 392–395. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Takayama A, Ishizaka M, Kubo A, et al. : Association between phase angle and level of independence in daily living among institutionalized super older females requiring nursing care. J Phys Ther Sci, 2024, 36: 526–529. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Yutaro M, Masanori W, Itaru H: Factors influencing return to home in a recovery unit. J Nagoya Gakuin Univ, 2013, 2: 1–8. [Google Scholar]
- 11.Ouellette DS, Timple C, Kaplan SE, et al. : Predicting discharge destination with admission outcome scores in stroke patients. NeuroRehabilitation, 2015, 37: 173–179. [DOI] [PubMed] [Google Scholar]
- 12.Nakaizumi D, Uchiyama K, Washida K, et al. : Combinations of independent motor functional independence measure items associated with home discharge in stroke patients in post-acute rehabilitation wards: an UpSet plot analysis. Cureus, 2024, 16: e73982. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Enderle J, Reljic D, Jensen B, et al. : Normal values for body composition in adults are better represented by continuous reference ranges dependent on age and BMI. Clin Nutr, 2023, 42: 644–652. [DOI] [PubMed] [Google Scholar]
- 14.Sato M, Ishizaka M, Endo Y, et al. : Comparison of body composition between patients admitted to convalescent rehabilitation and long-term care wards. J Phys Ther Sci, 2025, 37: 141–144. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Mormer ER, Berkeley SB, Johnson AM, et al. : Social determinants of health and the use of community-based rehabilitation following stroke: methodologic considerations. Arch Rehabil Res Clin Transl, 2024, 6: 100358. [DOI] [PMC free article] [PubMed] [Google Scholar]