Secondary Logo

Journal Logo

Factors related to home discharge in malnourished community-dwelling older adults

A retrospective longitudinal cohort study

Anada, Satoshi OTa,*; Matsumoto, Takuya PT, PhDa; Nakano, Masaru MD, PhDb; Yamada, Satoru MD, PhDc

Section Editor(s): Tarantino., Giovanni

doi: 10.1097/MD.0000000000016290
Research Article: Observational Study
Open

Patients who become malnourished during hospitalization because of illness or treatment often receive intervention from a nutrition support team (NST). The NST intervention not only enhances the nutritional status but also decreases medical expenses and catheter-related complications. However, the impact of the NST intervention on the home discharge of hospitalized community-dwelling older adults remains unclear. Hence, this study aims to investigate factors related to home discharge in malnourished community-dwelling older adults.

In this retrospective longitudinal cohort study, examined 191 community-dwelling older adults aged ≥65 years (108 males; mean age: 80.9 ± 7.8 years) who received the NST intervention. All participants were categorized into two groups based on whether they were home discharged or not (home discharge group and non-home discharge group). We performed intergroup comparisons using serum albumin (Alb) as an index of the nutritional status and functional independence measure (FIM: motor and cognitive items) as an index of activities of daily living (ADL). Furthermore, we constructed a prognostic model of home discharge using the logistic regression analysis.

The home discharge group had 94 participants, with a home discharge rate of 50.8%. Baseline body mass index (BMI), motor-FIM score, and cognitive-FIM score were significantly higher in the home discharge group compared with the non-home discharge group (P = .002, P < .001, P < .001, respectively). In the home discharge group, BMI declined significantly, Alb elevated significantly, and both motor-FIM and cognitive-FIM score enhanced significantly by the completion of the NST intervention (P < .001, P < .001, P < .001, P = .005, respectively). The adjusted logistic regression analysis extracted the baseline BMI (odds ratio [OR], 1.146; 95% confidence interval [CI]: 1.034–1.270), baseline motor-FIM score (OR, 1.070; 95% CI: 1.036–1.105), and extent of change in the motor-FIM score (OR, 1.061; 95% CI: 1.026–1.098) as independent factors that predict home discharge.

This study highlights the significance of higher baseline BMI, higher baseline ADL level, ADL enhancements, and improvements in the nutritional status by the NST intervention in malnourished community-dwelling older adults considering home discharge.

aDepartment of Rehabilitation

bDepartment of Gastroenterology and Hepatology

cDiabetes Center, Kitasato University Kitasato Institute Hospital, Tokyo, Japan.

Correspondence: Satoshi Anada, Department of Rehabilitation, Kitasato University Kitasato Institute Hospital, 5-9-1 Shirokane, Minato-ku, Tokyo 108-8642, Japan (e-mail: anada@insti.kitasato-u.ac.jp).

Abbreviations: ADL = activities of daily living, Alb = serum albumin, BMI = body mass index, CI = confidence interval, cognitive-FIM score = cognitive items of functional independence measure, FIM = functional independence measure, IADL = instrumental activities of daily living, IQR = interquartile range, JSPEN = Japanese Society for Parenteral & Enteral Nutrition, MNA-SF = mini-nutritional assessment short form, motor-FIM score = motor items of functional independence measure, NST = nutrition support team, OR = odds ratio, SD = standard deviation, SGA = subjective global assessment.

The Committee of Ethics of Kitasato University Kitasato Institute Hospital reviewed and approved this study protocol (No. 11018). Informed consent was obtained in the form of opt-out on the website (https://www.kitasato-u.ac.jp/hokken-hp/chiken/REC/optout/11018.pdf).

This study was supported by the Special Research Grant from Kitasato University Kitasato Institute Hospital.

The authors have no funding and conflicts of interest to disclose.

Received April 23, 2019

Received in revised form June 6, 2019

Accepted June 10, 2019

This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0

Back to Top | Article Outline

1 Introduction

Community-dwelling older adults experience multiple aging-related functional impairments and are at high risk of developing health problems, including issues with activities of daily living (ADL), disease onset, and hospitalization.[1,2] A longitudinal study reported that 90.7% of malnourished community-dwelling older adults were frail or in a prefrail state.[3] Malnourished community-dwelling older adults often experience not only declined physical function but also ADL disorders[4–6] and instrumental ADL (IADL) disorders[4,6]; these concerns contribute to hospitalization. Once hospitalized, home discharge often becomes challenging for this population. Another longitudinal study reported that the admission rate of community-dwelling older adults requiring care by the long-term care insurance system of Japan is 57.9%, with more hospitalization or institutionalization expected as the care support level is higher.[7]

Malnutrition is associated with decline in functional status, impaired muscle function, decreased bone mass, immune dysfunction, anemia, reduced cognitive function, poor wound healing, and delayed recovery from surgery.[8] A study reported the prevalence of malnutrition as 3.1% for malnutrition, 26.5% for risk of malnutrition in community-dwelling older adults, as well as 22.0% for malnutrition and 45.6% for risk of malnutrition in hospitalized patients.[9] In developed countries, the primary cause of malnutrition is disease; any chronic or acute disorder could cause or exacerbate malnutrition.[10] Moreover, malnutrition tends to hinder discharge to home because it correlates with falls.[11] Reportedly, malnutrition increases the hospital stays, readmission rate, and mortality among hospitalized elderly patients.[12–15] In addition, malnutrition estimates the future care needs of community-dwelling older adults.[16] Patients who become malnourished during hospitalization because of illness or treatment often receive intervention from a nutrition support team (NST), a multidisciplinary collaborative team that cooperates with doctors and medical professionals to offer safe and effective nutrition management. The NST intervention not only enhances the nutritional status[17,18] but also decreases medical expenses and catheter-related complications.[19] Nevertheless, the impact of the NST intervention on the home discharge of hospitalized community-dwelling older adults remains unclear. If home discharge could be estimated early, it might help decrease the economic burden on society in terms of social resource utilization.

Hence, this study aims to investigate factors related to home discharge among hospitalized community-dwelling older adults who received the NST intervention.

Back to Top | Article Outline

2 Materials and methods

2.1 Study design and participants

In this retrospective longitudinal cohort study, we enrolled community-dwelling older adults aged ≥65 years who were admitted to Kitasato University Kitasato Institute Hospital (Tokyo, Japan) from December 2014 to December 2018 and received the NST intervention. The NST at Kitasato Institute Hospital comprises doctors, pharmacists, nurses, nutritionists, clinical laboratory technicians, a physical therapist, an occupational therapist, a speech-language-hearing therapist, and administrative staff. NST rounds are conducted once a week. Then, targets for intervention by the NST involved those with serum albumin (Alb) at admission ≤3.0 g/dL and who required comprehensive improvement in the nutritional status following nutrition assessment based on the subjective global assessment (SGA)[20] by nutritionists who completed NST professional therapist training (administered by the Japanese Society for Parenteral & Enteral Nutrition; JSPEN)[21] and nurses in each ward. Of note, the SGA is an extensively accepted nutritional assessment tool as an internationally unified standard. Educated medical staff can efficiently perform a nutritional assessment based on interview and physical findings. In the section on history, we evaluated the correlation between weight change, dietary intake change, gastrointestinal symptoms, functional capacity, and disease and its association with nutritional requirements. In the section on physical findings, we evaluated the loss of subcutaneous fat, muscle wasting, ankle edema, sacral edema, and ascites. The Committee of Ethics of Kitasato University Kitasato Institute Hospital reviewed and approved this study protocol (No. 11018).

Back to Top | Article Outline

2.2 Eligibility criteria

In this study, the inclusion criteria were as follows: (1) received NST intervention, Alb at admission ≤3.0 g/dL (Alb 3.0 g/dL is considered high risk for malnutrition with various nutritional screening tools[22]), and required comprehensive improvement of the nutritional status; (2)community-dwelling older adults aged ≥65 years; (3) admitted to our hospital directly from their home; (4)required comprehensive improvement of the nutritional status because of the deterioration of the nutritional status during hospitalization. The exclusion criteria were as follows: (1) aged <65 years, (2) nursing home residents, (3) admitted from other hospitals, and (4) received only one NST intervention.

Back to Top | Article Outline

2.3 Baseline data collection

We collected baseline data including age, gender, duration of the NST intervention, body mass index (BMI), Alb, ADL, and cause of hospitalization. The functional independence measure (FIM)[23] was used as an index of ADL and scores were obtained for motor items (motor-FIM score; 13–91 points) and cognitive items (cognitive-FIM score; 5–35 points). The motor-FIM score is evaluated on the basis of 13 items (each is scored on a 1–7-point scale)—eating, grooming, bathing, dressing upper body, dressing lower body, toileting, bladder management, bowel management, transfer to bed/chair/wheelchair, transfer to toilet, transfer to tub/shower, walk/wheelchair, and stairs. The cognitive-FIM score is evaluated on the basis of 5 items (each is scored on a 1–7-point scale)—comprehension, expression, social interaction, problem solving, and memory. Of note, the FIM score was obtained every week to assess ADL changes. We classified causes of hospitalization using the following nine diagnoses: cancer, gastrointestinal disease, pneumonia, orthopedic disease, respiratory disease (excluding pneumonia), cardiovascular disease, neurological disease, renal disease, and other diseases. Furthermore, BMI, Alb, motor-FIM score, and cognitive-FIM score were evaluated at two timepoints, i.e., at initiation and completion of the NST intervention. Notably, data at the NST intervention initiation were considered baseline values.

Back to Top | Article Outline

2.4 Outcome measures

After completion of the NST intervention during hospitalization, follow-up was performed to investigate patient discharge by medical records. In this study, the primary outcome measure was the attainment of “home discharge” after hospitalization, which was assessed by dividing participants into a home discharge group and a non-home discharge group. As secondary outcome measures, we used ΔBMI, ΔAlb, Δmotor-FIM score, and Δcognitive-FIM score, which were obtained by subtracting the values at the NST initiation from the values at the NST completion. As critical outcomes in NST are nutritional status improvements, we investigated the obtained relationships to assess correlations of ΔBMI, Δmotor-FIM score, and Δcognitive-FIM score with ΔAlb.

Back to Top | Article Outline

2.5 Statistical analysis

All categorical variables are expressed as frequency and percentage, while continuous variables are presented as mean and standard deviation (SD) or median and interquartile range (IQR) based on the normal distribution assumptions were comprehensively evaluated using the Shapiro–Wilk test and quantile-quantile plots.

For the univariate analysis, we used the Student's t-test to compare mean values. In addition, the Mann–Whitney U-test and Wilcoxon signed-rank test were used to compare the median values after validating the presence or absence of independence. Using the Chi-square test, we compared frequencies and ratios (%). Moreover, Pearson's correlation coefficients were obtained to assess correlations. Furthermore, we investigated the obtained relationships to assess correlations of ΔBMI, Δmotor-FIM score, and Δcognitive-FIM score with ΔAlb.

Next, we performed the logistic regression analysis to identify independent predictors of home discharge using variables deemed significant by the univariate analysis. We constructed a prognostic model for home discharge and assessed the effect size of variables by calculating odds ratios (ORs) and 95% confidence intervals (95% CIs). Analyses were crude logistic regression model (model 1) and age, gender, and diagnoses were adjusted to control the confounders or potential confounders (model 2). In this study, we considered two-sided P < .05 as statistically significant. IBM SPSS Statistics version 24.0 (IBM Corp., Armonk, NY), and R version 3.5.2 (R Foundation for Statistical Computing, Vienna, Austria) were used to perform all statistical analyses.

Back to Top | Article Outline

3 Results

3.1 Participants’ baseline characteristics

Of 431 participants who received an NST intervention during the study period, we excluded 240 (118 were admitted from nursing homes; 7 were admitted from other hospitals; 28 were aged <65 years; and 87 received only one NST intervention). The home discharge group consisted of 97 participants, with a home discharge rate of 50.8%. The non-home discharge group consisted of 94 participants; of these, 41 (21.5%) were transferred to other hospitals, 18 (9.4%) were transferred to nursing homes, and 35 (18.3%) died (Figure 1).

Figure 1

Figure 1

Thus, 191 participants (108 males and 83 females; mean age: 80.9 ± 7.8 years) fulfilled the eligibility criteria and thus, they were enrolled. The mean NST intervention duration was 3.0 (IQR 2.0–6.0) weeks. The baseline values were as follows: BMI, 19.4 ± 4.1 kg/m2; Alb, 2.41 ± 0.48 g/dL; motor-FIM score, 21.0 (IQR: 13.0–40.0) points; and cognitive-FIM score, 23.0 (IQR: 12.0–31.0) points. Diagnoses on admission were as follows: cancer (n = 44, 23.0%); gastrointestinal disease (n = 32, 16.8%); pneumonia (n = 29, 15.2%); orthopedic disease (n = 25, 13.1%); respiratory disease other than pneumonia (n = 15, 7.9%); cardiovascular disease (n = 12, 6.3%); neurological disease (n = 7, 3.7%); renal disease (n = 3, 1.6%); and other diseases (n = 24, 12.6%; Table 1).

Table 1

Table 1

Back to Top | Article Outline

3.2 Comparison of participants’ baseline characteristics

The baseline BMI, motor-FIM score, and cognitive-FIM score were significantly higher in the home discharge group compared with the non-home discharge group (P = .002, P < .001, P < .001, respectively). However, age, gender, NST intervention duration, Alb, and diagnosis at admission did not differ markedly between the two groups.

Back to Top | Article Outline

3.3 Correlation between NST intervention initiation and completion

In the home discharge group, the BMI declined significantly, Alb elevated significantly, and both motor-FIM and cognitive-FIM scores enhanced significantly by the NST intervention completion (P < .001, P < .001, P < .001, P = .018, respectively). However, although Alb elevated significantly, the BMI and both motor-FIM and cognitive-FIM scores did not exhibit any significant change from the NST intervention initiation to the NST intervention completion in the non-home discharge group (Table 2).

Table 2

Table 2

Back to Top | Article Outline

3.4 Changes in each parameter between NST intervention initiation and completion

Table 3 presents changes in each parameter between NST intervention initiation and completion. ΔBMI, ΔAlb, and both Δmotor-FIM and Δcognitive-FIM scores were significantly higher in the home discharge group compared with the non-home discharge group (P = .010, P < .001, P < .001, P = .015, respectively).

Table 3

Table 3

Back to Top | Article Outline

3.5 Correlation among ΔAlb and ΔBMI, Δmotor-FIM score, and Δcognitive-FIM score

Figure 2 presents correlations among ΔAlb and ΔBMI, Δmotor-FIM score, and Δcognitive-FIM score. ΔAlb significantly and positively correlated with the Δmotor-FIM score in the home discharge and non-home discharge groups (r = 0.368 and r = 0.204; P < .001 and P = .049, respectively). Contrarily, ΔAlb did not markedly correlate with ΔBMI and Δcognitive-FIM score in the home discharge and non-home discharge groups.

Figure 2

Figure 2

Back to Top | Article Outline

3.6 Prognostic model for home discharge

The logistic regression analysis revealed the baseline BMI (OR, 1.119; 95% CI: 1.019–1.228), baseline motor-FIM score (OR, 1.060; 95% CI: 1.030–1.090), and Δmotor-FIM score (OR, 1.053; 95% CI: 1.020–1.087) to be independent predictors of home discharge (Nagelkerke R2 = 0.401). In addition, considering the impact of disease-related malnutrition,[10] we performed the logistic regression analysis adjusted by age, gender, and diagnoses. The adjusted logistic regression model established the baseline BMI (OR, 1.146; 95% CI: 1.034–1.270), baseline motor-FIM score (OR, 1.070; 95% CI: 1.036–1.105), and Δmotor-FIM score (OR, 1.061; 95% CI: 1.026–1.098) as independent predictors of home discharge (Nagelkerke R2 = 0.468; Table 4).

Table 4

Table 4

Back to Top | Article Outline

4 Discussion

This study established the baseline BMI, baseline motor-FIM score, and Δmotor-FIM score as independent predictors of home discharge of malnourished community-dwelling older adults. The findings highlight the significance of having a high ADL level at the time of initiating an NST intervention and the need of comprehending not only the nutritional status but also the baseline ADL level when considering home discharge in the investigated patient population. If the baseline ADL level is low when initiating the NST intervention, ADL recovery could be insufficient, making it challenging for patients to return home; in such cases, the use of social resources and reviewing the recuperative environment at an early stage should be considered. Boyd et al[24] reported that when ADL at discharge was recovered to the level of that 2 weeks before admission, 67.0% of subjects could maintain that ADL level even 1 year post-discharge; however, those who did not recover experienced further decline in ADL and even death. Thus, early rehabilitation during hospitalization and improving patient ADL level could increase the likelihood of being discharged home.

In this study, the baseline BMI and motor-FIM score were markedly higher in the home discharge group compared with the non-home discharge group, which could indicate the higher ADL level in the former because of their larger skeletal muscle mass.[25] Moreover, in the non-home discharge group, the baseline BMI was near the lower limit for a normal body type (18.5 kg/m2). As the skeletal muscle mass of older adults with declined Alb decreases,[26] it might increase the chances of not being able to return home. Pedersen et al[27] reported that early nutritional follow-up by visiting home discharged patients at the risk of malnutrition effectively maintained ADL level 8 weeks after hospitalization than nutritional counseling by phone. Perhaps, the nutritional status of our participants did not enhance sufficiently at the time of completing the NST intervention. Thus, early nutritional follow-up for those at risk of malnutrition during hospitalization might help maintain ADL levels, thereby facilitating them to continue living at home for as long as possible.

In the home discharge group, the baseline cognitive-FIM score was markedly higher compared with the non-home discharge group, suggesting that community-dwelling older adults maintain cognitive function, and compared with those with cognitive impairments, the rate of ADL recovery in these adults is high.[28] Moreover, those with higher cognitive function are likely to recover ADL more readily. In this study, the cognitive-FIM score was low in the non-home discharge group. Reportedly, the risk of caregiver burden tends to increase when care recipients are cognitively impaired,[29] which is likely an obstacle for home discharge.

At the time of completing the NST intervention, Alb levels had elevated and the motor-FIM score had enhanced markedly in the home discharge group. Conversely, only the motor-FIM score markedly enhanced, and Alb had not substantially increased in the non-home discharge group. We found a significant positive correlation between ΔAlb and Δmotor-FIM score in the home discharge and non-home discharge groups. A prospective cohort study reported that patients determined as malnourished or at risk for malnutrition using the Mini-Nutritional Assessment-Short Form (MNA-SF) during hospitalization exhibited a marked correlation between Alb and ADL at discharge.[30] In addition, a 2-year follow-up study of frail community-dwelling older adults reported a marked correlation between decreases in Alb and decreases in ADL.[31] However, to date, no study has reported any correlation between increased Alb and ADL improvement. Hence, this study suggests a correlation between increased Alb and ADL improvements with home discharge among malnourished community-dwelling older adults, implying that besides improvements in the nutritional status through the NST intervention during hospitalization, ADL improvements are just as crucial for home discharge. In the non-home discharge group, 37% of patients died, indicating the lack of improvement in the nutritional status and ADL, as well as deterioration in their general condition.

This study has some limitations worth acknowledging. First, this was a retrospective study with relatively small sample size, thereby unable to generalize the results to humans until further research. Second, the assessment of the nutritional status was based on Alb and thus, it does not exclude the potential effects of nephrotic syndrome, liver disorder, infectious disease, sepsis, cancer, trauma, and postoperative status. Hence, the nutritional status might not have been reflected precisely.[32] In addition, home discharge might have been affected by other factors, such as the severity of disease leading to hospitalization, swallowing function, nutritional route, and ADL level before hospitalization. Finally, home discharge could have been affected by factors such as the availability of a caregiver, accessibility to nursing care services, and availability of social resources, which were not assessed in this study.

Back to Top | Article Outline

5 Conclusion

This study highlights the significance of higher baseline BMI and higher baseline ADL level when considering home discharge for hospitalized malnourished community-dwelling older adults. Furthermore, besides improving the nutritional status through the NST intervention during hospitalization, enhancement in the ADL level is a critical factor to consider for home discharge.

Back to Top | Article Outline

Acknowledgments

We thank NST members and staff of the Department of Rehabilitation of our hospital.

Back to Top | Article Outline

Author contributions

Conceptualization: Satoshi Anada.

Data curation: Satoshi Anada, Takuya Matsumoto.

Formal analysis: Satoshi Anada, Takuya Matsumoto.

Validation: Satoshi Anada, Takuya Matsumoto, Masaru Nakano, Satoru Yamada.

Writing – original draft: Satoshi Anada.

Writing – review & editing: Satoshi Anada, Takuya Matsumoto, Masaru Nakano, Satoru Yamada.

Back to Top | Article Outline

References

[1]. 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:M146–56.
[2]. Yamada M, Arai H. Predictive value of frailty scores for healthy life expectancy in community-dwelling older Japanese adults. J Am Med Dir Assoc 2015;16:1002e7-e11.
[3]. Wei K, Nyunt MSZ, Gao Q, et al. Frailty and malnutrition: related and distinct syndrome prevalence and association among community-dwelling older adults: Singapore longitudinal ageing studies. J Am Med Dir Assoc 2017;18:1019–28.
[4]. Ferdous T, Cederholm T, Razzaque A, et al. Nutritional status and self-reported and performance-based evaluation of physical function of elderly persons in rural Bangladesh. Scand J Public Health 2009;37:518–24.
[5]. Schrader E, Grosch E, Bertsch T, et al. Nutritional and functional status in geriatric day hospital patients-MNA short form versus full MNA. J Nutr Health Aging 2016;20:918–26.
[6]. Lee LC, Tsai AC. Mini-nutritional assessment predicts functional decline of elderly Taiwanese: result of a population-representative sample. Br J Nutr 2012;107:1707–13.
[7]. Tomita N, Yoshimura K, Ikegami N. Impact of home and community-based services on hospitalisation and institutionalisation among individuals eligible for long-term care insurance in Japan. BMC Health Serv Res 2010;10:345.
[8]. Ahmed T, Haboubi N. Assessment and management of nutrition in older people and its importance to health. Clin Interv Aging 2010;5:207–16.
[9]. Cereda E, Pedrolli C, Klersy C, et al. Nutritional status in older persons according to healthcare setting: a systematic review and meta-analysis of prevalence data using MNA. Clin Nutr 2016;35:1282–90.
[10]. Norman K, Pichard C, Lochs H, et al. Prognostic impact of disease-related malnutrition. Clin Nutr 2008;27:5–15.
[11]. Chien MH, Guo HR. Nutritional status and falls in community-dwelling older people: a longitudinal study of a population-based random sample. PLoS One 2014;9:e91044.
[12]. Slee A, Birch D, Stokoe D. The relationship between malnutrition risk and clinical outcomes in a cohort of frail older hospital patients. Clin Nutr ESPEN 2016;15:57–62.
[13]. Kissova V, Rosenberger J, Goboova M, et al. Ten-year all-cause mortality in hospitalized non-surgical patients based on nutritional status screening. Public Health Nutr 2015;18:2609–14.
[14]. Sullivan DH, Sun S, Walls RC. Protein-energy undernutrition among elderly hospitalized patients: a prospective study. JAMA 1999;281:2013–9.
[15]. Lim SL, Ong KC, Chan YH, et al. Malnutrition and its impact on cost of hospitalization, length of stay, readmission and 3-year mortality. Clin Nutr 2012;31:345–50.
[16]. Tsai AC, Hsu WC, Wang JY. The Mini Nutritional Assessment (MNA) predicts care need in older Taiwanese: results of a national cohort study. Br J Nutr 2014;111:1977–84.
[17]. Traeger SM, Williams GB, Milliren G, et al. Total parenteral nutrition by a nutrition support team: improved quality of care. JPEN J Parenter Enteral Nutr 1986;10:408–12.
[18]. Powers DA, Brown RO, Cowan GS Jr, et al. Nutritional support team vs nonteam management of enteral nutritional support in a Veterans Administration Medical Center teaching hospital. JPEN J Parenter Enteral Nutr 1986;10:635–8.
[19]. Kennedy JF, Nightingale JM. Cost savings of an adult hospital nutrition support team. Nutrition 2005;21:1127–33.
[20]. Detsky AS, McLaughlin JR, Baker JP, et al. What is subjective global assessment of nutritional status? JPEN J Parenter Enteral Nutr 1987;11:8–13.
[21]. Ito A, Higashiguchi T. Recent developments of the Nutritional Support Team (NST) in Japan. Jpn J Nutr Diet 2006;64:213–20.
[22]. Zhang Z, Pereira SL, Luo M, et al. Evaluation of blood biomarkers associated with risk of malnutrition in older adults: a systematic review and meta-analysis. Nutrients 2017;9: pii: E829.
[23]. Dodds TA, Martin DP, Stolov WC, et al. A validation of the functional independence measurement and its performance among rehabilitation inpatients. Arch Phys Med Rehabil 1993;74:531–6.
[24]. Boyd CM, Landefeld CS, Counsell SR, et al. Recovery of activities of daily living in older adults after hospitalization for acute medical illness. J Am Geriatr Soc 2008;56:2171–9.
[25]. Kanehisa H, Fukunaga T. Association between body mass index and muscularity in healthy older Japanese women and men. J Physiol Anthropol 2013;32:4.
[26]. Cabrerizo S, Cuadras D, Gomez-Busto F, et al. Serum albumin and health in older people: review and meta analysis. Maturitas 2015;81:17–27.
[27]. Pedersen JL, Pedersen PU, Damsgaard EM. Early nutritional follow-up after discharge prevents deterioration of ADL functions in malnourished, independent, geriatric patients who live alone - a randomized clinical trial. J Nutr Health Aging 2016;20:845–53.
[28]. Hardy SE, Gill TM. Recovery from disability among community-dwelling older persons. JAMA 2004;291:1596–602.
[29]. Livingston G, Sommerlad A, Orgeta V, et al. Dementia prevention, intervention, and care. Lancet 2017;390:2673–734.
[30]. Wakabayashi H, Sashika H. Malnutrition is associated with poor rehabilitation outcome in elderly inpatients with hospital-associated deconditioning: a prospective cohort study. J Rehabil Med 2014;46:277–82.
[31]. Kitamura K, Nakamura K, Nishiwaki T, et al. Determination of whether the association between serum albumin and activities of daily living in frail elderly people is causal. Environ Health Prev Med 2012;17:164–8.
[32]. Bharadwaj S, Ginoya S, Tandon P, et al. Malnutrition: laboratory markers vs nutritional assessment. Gastroenterol Rep (Oxf) 2016;4:272–80.
Keywords:

activities of daily living; albumin; community-dwelling; functional independence measure; home discharge; malnutrition; nutritional support; patient discharge

Copyright © 2019 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.