Phase angle assessment: Frailty/sarcopenia and walking in hospitalised patients receiving haemodialysis

Abstract

Background

As concerns about ageing among patients receiving dialysis increase, exercise becomes an essential early intervention to prevent frailty and sarcopenia. A swift and easy physical assessment function is required, with phase angle (PhA), the angle at which microscopic electricity passes through the cell membrane, emerging as a potential alternative.

Objectives

This study aimed to determine the relationship between PhA measurements and the identification of sarcopenia, frailty, ambulatory capacity, and primary dialysis disease in hospitalised patients undergoing dialysis. Additionally, whether PhA could help assess these factors was investigated.

Methods

This cross-sectional study was conducted including 49 Japanese inpatients (25 male and 24 females) aged 76.3 ± 9.2 years (range: 53–96 years) undergoing dialysis. Body composition data, including PhAs, were measured. Frailty was assessed using the Japanese version of the Cardiovascular Health Study (J-CHS) criteria, while sarcopenia was diagnosed per the Asian Sarcopenia Working Group’s guidelines. Patients were categorised and compared according to the presence or absence of frailty and sarcopenia, ambulatory status, and underlying dialysis condition (diabetic nephropathy).

Results

Frailty and sarcopenia prevalences were 61.2% and 83.7%, respectively. Non-ambulatory patients exhibited significantly higher age and lower PhA than their ambulatory counterparts. PhA and grip strength were significant factors influencing ambulation.

Conclusions

While PhA decreased, its association with frailty or sarcopenia was not statistically significant. However, PhA was significantly lower among non-ambulatory patients. These results indicate that although PhA assessment is promising, caution is warranted when considering it as a substitute for other assessments in patients receiving haemodialysis with compromised physical function.

Keywords

ambulatory frailty haemodialysis phase angle sarcopenia

Introduction

The number of patients receiving haemodialysis is increasing annually owing to the rising incidence of primary diseases such as diabetes, which are associated with lifestyle factors. Diabetic nephropathy has been the leading cause of dialysis initiation in Japan since 1998, with approximately 340,000 patients receiving chronic dialysis in 2020.¹ This represents a 1.5-fold increase over approximately 20 years, considering the number was about 200,000 in 2000. Concurrently, ageing presents a significant challenge in this population. The Japan Society for Dialysis Therapy reports that the average age of patients on chronic dialysis has increased over the years, from around 54 in 1985 to over 70 in 2020.¹ Since 2017, the age distribution of dialysis patients has shifted from under 64 to over 65 years. As these patients age, several issues emerge, including sarcopenia, decline in muscle strength and mass, frailty, as well as reduced physical function. Sarcopenia is highly prevalent among patients receiving dialysis and is associated with a high mortality rate.² In the United States, the prevalence of frailty among patients receiving dialysis was 67.7%, particularly among older individuals, reaching 44.4% for those in their 40s and 78.8% for those over 80 years old.³ Frailty in patients undergoing dialysis has been linked to poor short-term prognosis and a heightened risk of adverse events.⁴ Therefore, preventing and managing sarcopenia and frailty are crucial for improving the life expectancy of patients undergoing dialysis.

Exercise therapy is recommended to prevent sarcopenia and frailty in patients receiving haemodialysis.^5,6 However, a simple method to assess physical decline is needed for early detection. A screening test that identifies patients with reduced physical function who are at risk of frailty and sarcopenia at an early stage would enable immediate and effective intervention in patients in need of exercise therapy. Phase angle (PhA), measured using bioelectrical impedance analysis (BIA), is an easy-to-measure indicator of physical function decline. PhA is defined as reactance, expressed as the angle at which microscopic electricity passes through the cell membrane.⁷ The higher the PhA, the higher the integrity of the cell membrane, indicating better cell function and health; it is, thus, considered an indicator of cell health.⁸ Additionally, the ratio of extracellular water to total water (ECW/TBW), as measured using BIA, is a factor indicating the degradation of cell membranes. A comparison of survivors and deceased intensive care unit (ICU) patients showed that the PhA of deceased patients was significantly lower and their ECW/TBW levels were significantly higher than those in survivors, indicating that PhA can be used as a prognostic factor in ICU patients.⁹ PhA has also been reported to be a useful marker of sarcopenia, cachexia, and malnutrition in hospitalised patients with cardiovascular diseases.¹⁰ In a study examining the relationship between muscle quality and PhA in community-dwelling older adults, PhA demonstrated good accuracy in detecting sarcopenia.¹¹ Another study investigating the association between PhA, protein-energy wasting (PEW), and frailty in patients receiving haemodialysis has shown an increased risk of PEW and frailty in the low PhA group.¹² From these previous studies, it can be concluded that although PhA is a useful prognostic marker for the severity of illness, malnutrition, and survival, there are still few studies on the PhA in Japanese patients receiving haemodialysis, and its use remains uncertain. Many patients receiving haemodialysis in Japan are older and have advanced frailty and sarcopenia. If simple assessment data, such as the PhA, could be made available, it could contribute to the health of patients receiving dialysis by identifying those who require appropriate intervention at an earlier stage.

Therefore, in this study, we sought to clarify the relationship between PhA data obtained from BIA and the diagnosis of sarcopenia, frailty, ambulation, and primary dialysis disease, as well as to examine whether the PhA could serve as an alternative means of these assessments.

Materials and methods

Participants

This study was conducted at a hospital specialising in dialysis in Japan. We included a total of 49 individuals (25 males and 24 females) with an average age of 76.3 ± 9.2 years (range: 53–96 years), who had a rehabilitation prescription and agreed to participate in the study out of approximately 250 inpatients admitted between August 2019 and February 2024. These participants received a written and verbal explanation of the study from the researchers, and those who volunteered to participate confirmed their participation with a written informed consent form. This study was conducted following the principles of the Declaration of Helsinki and ethical considerations. Approval was obtained from the Research Ethics Committee of Mizuhokai Medical Corporation prior to commencement (approval no. 18).

Study design

This cross-sectional study aimed to investigate the relationship between PhA data obtained from BIA and baseline data on other physical functions and diseases.

Data collection

Body composition data were measured using the InBody S10 body composition analyser (InBody Japan Co. Ltd., Tokyo, Japan). The body composition data included height, weight, body mass index (BMI), percentage body fat (%BF), skeletal muscle mass (SMM), skeletal muscle index (SMI), and PhA scores. Body composition was measured in the supine position after dialysis. In addition, the date of dialysis, primary dialysis disease, serum albumin level, and date of dialysis initiation were collected from medical records. Patients with diabetic nephropathy as the primary disease requiring dialysis were included in the diabetes mellitus (DM) group, and those with other diseases were included in the non-DM group. Dialysis history (days) was calculated as the number of days between the start of dialysis and the date of data collection. The Japanese version of the Cardiovascular Health Study (J-CHS)¹³ was used to diagnose frailty. Weight information, as required by the J-CHS criteria, was obtained from medical records, while information on fatigue and physical activity was obtained directly from the participants. The J-CHS determines frailty when three or more of the five items (weight loss, muscle weakness, fatigue, walking speed, and physical activity) are applied and pre-frailty when one or two items are applied. Those who had at least three items were classified into the frailty group, and those who had none or 1–2 items were classified into the non-frailty group. All participants in this study met one or more of the J-CHS criteria and were classified as having frailty or pre-frailty. Sarcopenia was assessed following the 2019 Diagnostic Criteria of the Asian Working Group for Sarcopenia (AWGS).¹⁴ Those who met the AWGS criteria for sarcopenia or severe sarcopenia were included in the sarcopenia group, whereas others were included in the non-sarcopenia group. Grip strength and walking speed, necessary for the diagnosis of frailty and sarcopenia, were measured by a physiotherapist. Grip strength was measured twice with the grip width adjusted to ensure that the second joint of the index finger was almost perpendicular to the non-shunt limb, with both legs naturally open to the left and right in an upright position and the arms hanging, and the better result was recorded as the representative value. Walking speed was measured with a 10-m walking test; 10 m plus 1 m forward and backwards, for a total of two 12-m comfortable walking speeds, with the faster one recorded as the representative value. Physiotherapists assessed the participants’ ability to walk, based on which participants were divided into two groups: ambulatory and non-ambulatory.

Statistical analysis

All scale data are presented as mean ± standard deviation. Measures of frailty, sarcopenia, DM, and gait were compared between the two groups using a two-sample t-test. A multiple logistic regression analysis was performed with walkability as the dependent variable. The independent variables were age, history of dialysis, serum albumin level, body weight, BMI, SMM, %BF, SMI, PhA, and grip strength. To investigate the cut-off value of PhA to determine whether patients could walk, receiver operating characteristic (ROC) curves were constructed with walking ability as the state variable and PhA as the test variable, and the cut-off values were verified by sensitivity and specificity.

Results

The findings of this study revealed that among the 49 participants, 30 (61.2 %) exhibited frailty, while 41 (83.7%) were diagnosed with sarcopenia. Among them, 37 were ambulatory and 12 were non-ambulatory patients. Additionally, 23 patients had diabetic nephropathy, whereas 26 had other diseases, including nephrosclerosis, chronic glomerulonephritis, and polycystic kidney disease. The two-sample t-test results indicated no significant differences in the measurement parameters between individuals with and without frailty or sarcopenia (Table 1). A comparison of gait ability between the two groups showed significantly higher age (77.78 ± 8.96 vs 71.75 ± 8.99, p < 0.05) and significantly lower PhA (3.38 ± 0.82 vs 2.78 ± 0.61, p < 0.05) in the non-ambulatory group than in the ambulatory group (Table 2). In a comparison of primary dialysis diseases, the DM group exhibited significantly lower age (p < 0.01) and significantly higher height (p < 0.01), weight (p < 0.01), and skeletal muscle mass (p < 0.01) than the non-DM group (Table 2). In the multiple logistic regression analysis, PhA (p < 0.05) and grip strength (p < 0.05) were used as independent variables, whereas ambulatory and non-ambulatory binary data were the dependent variables (Table 3). The ROC curve identified a cut-off value of 3.15° for PhA, with a sensitivity of 0.629, specificity of 0.600, AUC of 0.717, and p < 0.05.

Table 1.

Comparison of groups with and without frailty and sarcopenia.

	Non-frailty (n = 18)	Frailty (n = 23)	Non-sarcopenia (n = 8)	Sarcopenia (n = 33)
Age (years)	75.21 ± 11.65	77.00 ± 7.49	76.13 ± 11.91	76.34 ± 8.82
Dialysis history (days)	2912.68 ± 2935.95	1957.00 ± 2164.03	2931.63 ± 3137.78	2209.71 ± 2393.64
Serum albumin (g/dL)	3.20 ± 0.22	3.09 ± 0.69	3.03 ± 0.35	3.16 ± 0.58
Height (cm)	157.48 ± 9.74	155.40 ± 7.25	153.51 ± 8.01	156.88 ± 8.41
Body weight (kg)	48.65 ± 10.61	45.75 ± 7.29	50.25 ± 13.26	46.27 ± 7.66
BMI (kg/m²)	19.53 ± 4.03	19.04 ± 3.41	21.35 ± 5.57	18.79 ± 3.01
%BF (%)	30.05 ± 11.72	25.18 ± 11.87	24.50 ± 15.50	27.83 ± 11.18
SMM (kg)	17.30 ± 3.83	17.12 ± 2.90	18.93 ± 2.91	16.82 ± 3.28
PhA (°)	3.33 ± 0.91	3.19 ± 0.74	3.49 ± 0.85	3.19 ± 0.80
SMI (kg/m²)	5.32 ± 1.08	5.10 ± 1.14	6.59 ± 0.76	4.91 ± 0.95**
GS (kg)	20.11 ± 7.68	17.18 ± 6.89	20.64 ± 9.16	17.86 ± 6.89

Non-sarcopenia versus sarcopenia: **p<0.01.

BMI: body mass index; %BF: percent of body fat; SMM: skeletal muscle mass; PhA: phase angle; SMI: skeletal muscle index; GS: grip strength.

Table 2.

Comparison of groups with and without diabetes mellitus and with and without walkable ability.

	Non-DM (n = 17)	DM (n = 24)	Walkable (n = 29)	Not-walkable (n = 12)
Age (years)	80.92 ± 8.04	71.09 ± 7.72**	77.78 ± 8.96	71.75 ± 8.99+
Dialysis history (days)	2035.65 ± 2479.00	2657.57 ± 2551.57	2190.19 ± 2472.46	2751.17 ± 2674.22
Serum albumin (g/dL)	3.23 ± 0.65	3.03 ± 0.40	3.16 ± 0.60	3.06 ± 0.41
Height (cm)	153.11 ± 7.25	159.60 ± 8.28**	155.05 ± 8.71	160.58 ± 5.28
Body weight (kg)	42.97 ± 4.88	51.17 ± 10.16**	46.01 ± 7.59	50.35 ± 12.22
BMI (kg/m²)	18.30 ± 1.92	20.22 ± 4.70	19.14 ± 3.04	19.61 ± 5.48
%BF (%)	26.79 ± 9.70	27.70 ± 14.10	27.45 ± 11.20	26.50 ± 14.83
SMM (kg)	15.97 ± 2.86	18.48 ± 3.27**	16.83 ± 3.30	18.47 ± 3.04
PhA (°)	3.32 ± 0.87	3.17 ± 0.76	3.38 ± 0.82	2.78 ± 0.61+
SMI (kg/m²)	4.96 ± 1.04	5.44 ± 1.14	5.14 ± 1.34	5.33 ± 1.04
GS (kg)	16.45 ± 6.35	20.43 ± 7.79	17.37 ± 7.01	21.25 ± 7.57

Non-DM versus DM: *p<0.05, **p<0.01; Walkable versus not-walkable: ⁺p<0.05.

DM: diabetes mellitus; BMI: body mass index; %BF: percent of body fat; SMM: skeletal muscle mass; PhA: phase angle; SMI: skeletal muscle index; GS: grip strength.

Table 3.

Results of the multiple logistic regression analysis.

Adopted independent variable	Partial regression coefficient	p-Value	Odds ratio	95% CI
PhA	−1.318	0.048	0.268	0.073–0.986
GS	0.148	0.038	0.059	1.008–1.332

Model chi-square test: p < 0.01, Hosmer–Lemeshow test: p = 0.367.

Dependent variable: walkable = 0 and not-walkable = 1

Independent variables not in equation: age, dialysis history, serum albumin, BMI, %BF, SMM, SMI, and GS.

PhA: phase angle; GS: grip strength; CI: confidence interval; BMI: body mass index; %BF: percent of body fat; SMM: skeletal muscle mass; SMI: skeletal muscle index.

Discussion

In the present study, the prevalence of frailty and sarcopenia was found to be high. Previous studies have reported a high prevalence of frailty and sarcopenia in patients receiving haemodialysis. This is strongly associated with an increased risk of adverse outcomes such as hospitalisation and death^15–17; however, there are few reports specifically focussing on hospitalised patients. The present novel findings suggest that the prevalence of frailty and sarcopenia is higher in patients receiving haemodialysis than that previously reported.

In this study, we examined these associations to determine whether PhA assessment could be used as an alternative method for evaluating frailty and sarcopenia. Our hypothesis posited that obtaining PhA data from body composition measurements would adequately help in the early diagnosis of patients with frailty and sarcopenia, thereby facilitating the identification of candidates for renal rehabilitation at an earlier stage. However, our findings did not reveal a significant association between frailty or sarcopenia and the PhA. Saitoh et al. investigated the relationship between frailty and PhA, reporting that patients undergoing dialysis with a PhA of less than 3.7° were significantly associated with frailty, even after adjusting for age, diabetes, and years of dialysis.¹² Unlike previous studies, our research solely included inpatients, an older age cohort, and individuals with notably low PhA measurements. In a study involving older Japanese individuals, a correlation between age and PhA was observed, with individuals over 90 years old, including non-dialysis patients and nursing home residents, exhibiting a very low PhA of 2.6°.¹⁸ Patients receiving dialysis typically exhibit lower physical activity levels and diminished fitness than the healthy sedentary individuals.¹⁹ Of the 49 participants in our study, only 13 had a PhA of 3.7° or higher, suggesting that our participants had substantially low fitness levels and poor PhA data initially. Consequently, evaluating the PhA in Japanese inpatients undergoing dialysis may necessitate using the criteria distinct from those employed in previous studies.

Furthermore, no association was found between frailty or sarcopenia and PhA; however, an association was found between walking ability, age, and PhA. Since PhA is affected by age,¹⁸ the older age in the non-ambulatory group was considered the primary factor. Besides age, PhA and grip strength were associated with walking ability in the multiple logistic regression analysis. Gunn et al. performed PhA assessments in walkable rehabilitation patients and suggested that PhA may serve as a useful indicator of a patient’s functional status.²⁰ To our knowledge, there have been no reports on PhA assessment in patients with ambulatory difficulties upon dialysis. Our study found an association between PhA and ambulation in inpatients with ambulatory impairment, suggesting that PhA could be an early predictor of ambulation in patients undergoing dialysis. The results suggest that in care settings where rehabilitation specialists are not available, a simple assessment of body composition may predict physical function even when gait assessment is not immediately available. In addition, a PhA of 3.15° was utilised as a cut-off for ambulation in this study; however, the sensitivity and specificity were inadequate, and the predictive accuracy was low. Further validation of a more precise cut-off is warranted in future studies.

Additionally, we compared two groups based on the presence or absence of diabetic nephropathy as the primary dialysis disease. The results showed that diabetic nephropathy was associated with younger age and higher body weight and skeletal muscle mass, although no significant association with the PhA was observed. Hence, predicting physical function decline in DM patients using PhA, which correlates strongly with age, may pose certain challenges. It may be necessary to modify the physical function index used in older patients receiving haemodialysis based on the underlying dialysis disease.

This study had some limitations. First, the study had a small number of participants, skewing the number of participants in the two-group comparison and resulting in a low predictive accuracy of the cut-off values for PhA. In clinical research, minority groups often fail to attract a large number of participants. Further validation is required to increase the number of participants in these groups. Second, this was a cross-sectional study, and while we identified individual associations, we were unable to verify causal relationships. Although we found an association between PhA and walking ability at present, it remains to be seen whether the PhA can predict the state of true walking disability in advance. Further longitudinal observational studies are warranted to address these questions. Third, this study included individuals aged from their 50s to over 90 years, encompassing a wide age range. In a study on PhA, it may have been necessary to limit the age group to some extent due to a strong correlation with age. However, the inclusion of older adults may have yielded different results from those of previous studies. The populations of Japan and other countries worldwide will continue to age. By 2025, it is projected that 30% of Japan’s total population will be in the older age group, and by 2040, those aged 75 years and older will account for more than 20% of the total population.²¹ Further studies on older patients receiving dialysis in Japan may benefit patients worldwide. The new association of PhA in patients receiving haemodialysis was informative, but future studies could increase the number of participants through multi-centre studies and include older participants to validate the cut-off value of PhA for patients who need dialysis. Based on these studies, establishing the PhA as a simple alternative method to assess physical function and implementing immediate rehabilitation interventions are crucial.

The relationships between PhA assessment and frailty, sarcopenia assessment, ambulatory ability, and primary dialysis disease were investigated in hospitalised patients undergoing haemodialysis. The results showed that the PhA decreased in the participants; however, there was no significant association with frailty or sarcopenia. Compared with the ambulatory group, the non-ambulatory group had a significantly decreased PhA. PhA and grip strength were significantly associated with ambulation. These results suggest that using PhA as a substitute for other assessments in hospitalised patients receiving haemodialysis with impaired physical function may be challenging. Further research is required to make PhA assessment a simple alternative to physical function assessment.

Footnotes

Acknowledgements

We express our sincere gratitude to the patients and staff of Mizuho Hospital in Japan for their cooperation in this study. We would like to thank Editage () for the English language editing.

ORCID iD

Masahiro Noguchi

Ethical approval

This study was conducted following the principles of the Declaration of Helsinki and ethical considerations. Approval was obtained from the Research Ethics Committee of Mizuhokai Medical Corporation prior to commencement (approval no. 18).

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

References

Hanafusa

Abe

Joki

, et al. Annual dialysis data report 2020, JSDT renal data registry. Ren Replace Ther 2024; 10: 14. DOI: 10.1186/s41100-024-00531-5.

Mori

Nishide

Okuno

, et al. Impact of diabetes on sarcopenia and mortality in patients undergoing haemodialysis. BMC Nephrol 2019; 20: 105. DOI: 10.1186/s12882-019-1271-8.

Johansen

Chertow

Jin

, et al. Significance of frailty among dialysis patients. J Am Soc Nephrol 2007; 18: 2960–2967. DOI: 10.1681/asn.2007020221.

Garcia-Canton

Rodenas

Lopez-Aperador

, et al. Frailty in hemodialysis and prediction of poor short-term outcome: mortality, hospitalization and visits to hospital emergency services. Ren Fail 2019; 41: 567–575. DOI: 10.1080/0886022x.2019.1628061.

Yamagata

Hoshino

Sugiyama

, et al. Clinical practice guideline for renal rehabilitation: systematic reviews and recommendations of exercise therapies in patients with kidney diseases. Ren Replace Ther 2019; 5: 28. DOI: 10.1186/s41100-019-0209-8.

American College of Sports Medicine . ACSM’s guidelines for exercise testing and prescription. Liguori

Feito

Fountaine

, et al. (eds) 11th ed. Philadelphia, PA: Wolters Kluwer/Lippincott Williams & Wilkins Health, 2020.

Foster

Lukaski

. Whole-body impedance--what does it measure? Am J Clin Nutr 1996; 64(3 Suppl): 388S–396S. DOI: 10.1093/ajcn/64.3.388s.

Lukaski

Kyle

Kondrup

. Assessment of adult malnutrition and prognosis with bioelectrical impedance analysis: phase angle and impedance ratio. Curr Opin Clin Nutr Metab Care 2017; 20: 330–339. DOI: 10.1097/mco.0000000000000387.

Lee

Kwon

Shin

, et al. Use of bioelectrical impedance analysis for the assessment of nutritional status in critically ill patients. Clin Nutr Res 2015; 4: 32–40. DOI: 10.7762/cnr.2015.4.1.32.

10.

Hirose

Nakajima

Nozawa

, et al. Phase angle as an indicator of sarcopenia, malnutrition, and cachexia in inpatients with cardiovascular diseases. J Clin Med 2020; 9: 2554. DOI: 10.3390/jcm9082554.

11.

Akamatsu

Kusakabe

Arai

, et al. Phase angle from bioelectrical impedance analysis is a useful indicator of muscle quality. J Cachexia Sarcopenia Muscle 2022; 13: 180–189. DOI: 10.1002/jcsm.12860.

12.

Saitoh

Ogawa

Kondo

, et al. Bioelectrical impedance analysis-derived phase angle as a determinant of protein-energy wasting and frailty in maintenance hemodialysis patients: retrospective cohort study. BMC Nephrol 2020; 21: 438. DOI: 10.1186/s12882-020-02102-2.

13.

Satake

Arai

. The revised Japanese version of the Cardiovascular Health Study criteria (revised J-CHS criteria). Geriatr Gerontol Int 2020; 20: 992–993. DOI: 10.1111/ggi.14005.

14.

Chen

Woo

Assantachai

, et al. Asian Working Group for Sarcopenia: 2019 consensus update on sarcopenia diagnosis and treatment. J Am Med Dir Assoc 2020; 21: 300.e2–307.e2. DOI: 10.1016/j.jamda.2019.12.012.

15.

Takeuchi

Uchida

Kakio

, et al. The prevalence of frailty and its associated factors in Japanese hemodialysis patients. Aging Dis 2018; 9: 192–207. DOI: 10.14336/ad.2017.0429.

16.

Zhao

Liu

. The prevalence of frailty in patients on hemodialysis: a systematic review and meta-analysis. Int Urol Nephrol 2020; 52: 115–120.

17.

Lee

Son

. Prevalence and associated factors of frailty and mortality in patients with end-stage renal disease undergoing hemodialysis: a systematic review and meta-analysis. Int J Environ Res Publ Health 2021; 18: 3471. DOI: 10.3390/ijerph18073471.

18.

Kubo

Ishizaka

Tsukahara

, et al. Association between age and phase angle in “old” and “super-old” nursing home residents. J Phys Ther Sci 2022; 34: 642–645. DOI: 10.1589/jpts.34.642.

19.

Johansen

Chertow

, et al. Physical activity levels in patients on hemodialysis and healthy sedentary controls. Kidney Int 2000; 57: 2564–2570. DOI: 10.1046/j.1523-1755.2000.00116.x.

20.

Gunn

Halbert

Giles

, et al. Bioelectrical phase angle values in a clinical sample of ambulatory rehabilitation patients. Dyn Med 2008; 7: 14. DOI: 10.1186/1476-5918-7-14.

21.

Ministry of Internal Affairs and Communications . Population of older people in Japan (Japanese). Japan: Ministry of Internal Affairs and Communications, 2022. https://www.stat.go.jp/data/topics/topi1321.html. (Accessed 28 February 2024).