Physical Activity Across the Clinical Trajectory of Chronic Kidney Disease and in Patients Undergoing Peritoneal Dialysis: A Cross‐Sectional Study Using Accelerometry

ABSTRACT

Aim

Physical activity is associated with prognosis in older adults with chronic kidney disease (CKD). However, previous studies have relied mainly on self‐report questionnaires, and objective evidence remains limited, particularly among patients undergoing peritoneal dialysis (PD). We assessed physical activity using a triaxial accelerometer across CKD stages and PD and examined its association with exercise self‐efficacy.

Methods

This cross‐sectional study included 114 outpatients recruited between June 2023 and June 2024. Physical activity was measured with a triaxial accelerometer over four consecutive days. Exercise self‐efficacy was assessed using the Exercise Self‐Efficacy Scale. Group differences and associations between physical activity and clinical variables were examined.

Results

In total, 114 participants (early: n = 37; advanced: n = 47; PD: n = 30) were analyzed. Physical activity declined with disease progression and was lowest in the PD group. Median daily step counts were 4729, 3831, and 3086 in the early, advanced, and PD stages, respectively, with a significant difference between early‐stage CKD and PD (p = 0.04). Median moderate‐to‐vigorous physical activity (min/week) was 75, 40, and 32.5, respectively, remaining below recommended levels in all groups. In the PD group, higher exercise self‐efficacy was independently associated with greater moderate‐to‐vigorous physical activity and step counts.

Conclusions

Physical activity declined with CKD progression, reaching low levels among patients undergoing PD. In this group, exercise self‐efficacy was associated with physical activity, suggesting its relevance when developing strategies to support activity. Further research should identify appropriate ways to encourage physical activity in aging CKD populations.

As chronic kidney disease progressed, physical activity decreased, with the lowest levels observed among patients undergoing peritoneal dialysis (PD). Among patients undergoing PD, exercise self‐efficacy was independently associated with both moderate‐to‐vigorous physical activity and daily step counts.

1. Introduction

The number of people with chronic kidney disease (CKD) is increasing worldwide. The growing number of patients requiring dialysis or kidney transplantation puts a substantial strain on healthcare systems as well as society [1]. In Japan, the number of older adults with CKD is increasing rapidly, making the prevention of disease progression and complications an important clinical issue throughout all clinical stages [2]. Traditionally, exercise therapy for patients with CKD has been developed within the context of renal rehabilitation, primarily targeting patients undergoing hemodialysis (HD) [3]. However, in recent years, the importance of exercise therapy for patients with non‐dialysis CKD has also been recognized [4]. In Japan, this has been further reinforced by healthcare policy, including the introduction of comprehensive management programs for non‐dialysis CKD in the 2024 reimbursement revision [5]. However, patients undergoing peritoneal dialysis (PD) are excluded from exercise therapy reimbursement. There are concerns that patients undergoing PD, who tend to be physically inactive and are considered to be at high risk, may be overlooked by the support system. Physical activity (PA) encompasses not only planned exercise, such as exercise therapy, but also activities carried out in daily life. The World Health Organization Guidelines on PA and sedentary behavior state that PA encompasses all forms of physical movement in daily life, not only exercise. Reducing sedentary behavior and increasing daily PA are particularly important for older adults and those with chronic conditions [6]. PA is reportedly associated with suppressed renal function decline, reduced cardiovascular events, and lower mortality in patients with CKD, attracting attention as a prognostic factor [7]. PD is a home‐based treatment that offers a relatively high degree of freedom in daily life. However, self‐reported PA levels are low and have been reported to be associated with reduced quality of life [8]. Regarding the objective assessment of PA in patients with CKD, physical function assessments such as the Timed Up and Go test are prevalent in both the pre‐dialysis and dialysis phases. However, objective assessments of PA in free‐living settings using accelerometers are limited [9, 10]. Conversely, self‐efficacy is recognized as a significant determinant of PA, promoting behavioral change in patients with chronic diseases [11] and influencing health behaviors related to PD [12]. While previous studies have examined the relationship between PA and self‐efficacy across all stages of CKD, PA has primarily been assessed through self‐report and has not been sufficiently validated [13].

Therefore, this study focused on the progression of CKD and treatment modalities and aimed to objectively assess PA in patients undergoing conservative management and PD while examining its association with exercise self‐efficacy.

2. Methods

2.1. Study Design, Setting, and Participants

This cross‐sectional study was conducted among outpatients at Kyushu University Hospital between June 2023 and June 2024. The inclusion criteria were: (a) age ≥ 18 years; (b) attendance at the diabetes or nephrology outpatient clinic; and (c) ability to complete self‐administered questionnaires in Japanese. The exclusion criteria were: (a) undergoing HD, (b) limitations in PA due to severe diabetic complications (e.g., lower limb amputation, severe visual impairment), (c) respiratory or cardiovascular diseases that limit PA, and (d) cognitive impairment. Patients undergoing HD require three treatment sessions per week, each lasting 4–5 h, which may affect daily PA levels. By contrast, patients undergoing PD generally have lifestyles comparable to those of patients with CKD receiving conservative management. Therefore, this study examined actual PA levels in patients with progressive CKD and those undergoing PD. Patients undergoing HD were excluded.

The required sample size to detect a statistically significant association between accelerometer‐measured PA and the Exercise Self‐Efficacy Scale (ESES) was calculated, assuming an effect size of 0.5, α = 0.05, and power = 0.80. The target sample size was 102 participants.

Patients were approached during outpatient visits. The investigator explained the purpose, methods, and ethical considerations of the study, and written informed consent was obtained. The study protocol was approved by the Ethics Review Committee of Kyushu University (Approval no. 23028‐00, approved on April 26, 2023), and the study protocol was subsequently amended and reapproved (Approval no. 23028‐01, approved on December 28, 2023). Body composition was measured using a multifrequency bioelectrical impedance analyzer (InBody770; InBody Co. Ltd., Seoul, Korea). Participants then wore an ActiGraph GT3X accelerometer (ActiGraph LLC, Pensacola, FL, USA) for 4 days to measure their PA and sedentary behavior time, and mailed it back together with the completed self‐administered questionnaires. Data were anonymized using study‐specific identification numbers.

2.2. PA Assessment

The ActiGraph GT3X (4.6 × 3.3 × 1.5 cm) is a triaxial accelerometer used worldwide for the assessment of PA. Participants were instructed to wear the accelerometer at waist level during four consecutive days, as recommended to minimize errors in assessing ambulatory PA. Because previous studies found no significant weekday–weekend difference in objectively measured total steps, participants wore the device on consecutive days regardless of day type [14]. They wore the device at all times except during sleep and activities involving water exposure, such as bathing or swimming. Non‐wear time was defined as ≥ 90 consecutive min of zero activity counts [15]. Patients undergoing PD positioned the device to avoid interfering with their catheter. Data were valid if the device was worn for at least 10 h (600 min) on 2 days. Previous studies have shown that moderate‐to‐vigorous physical activity (MVPA) and daily step count can be reliably estimated from 1 to 2 days of accelerometer monitoring when dialysis is not performed [16]. Data were imported and analyzed using ActiLife (ActiGraph), a device‐specific software tool, and recorded in 60‐s epochs, consistent with previous accelerometer‐based studies in patients with CKD and older adults [17, 18]. Activity intensity was categorized using the following commonly applied cut‐points: sedentary (0–99 counts/min), light (100–1951 counts/min), and moderate‐to‐vigorous (≥ 1952 counts/min) [19]. In line with international guidelines, the recommended MVPA level was defined as 150 min/week. A daily step count of 4000 steps was used as a reference value based on previous research [6, 20]. As no clear recommendation exists for light physical activity (LPA), LPA was not assessed against a recommended level.

2.3. ESES

Self‐efficacy is the belief in one's ability to perform the actions necessary to achieve a goal or produce an outcome. It indicates the strength of self‐belief in the capacity to execute required activities. For example, individuals with higher self‐efficacy exert greater effort toward activities [11]. This study assessed self‐efficacy related to PA using the ESES. The ESES measures self‐efficacy in older adults with low PA levels and patients with chronic diseases [21]. A Japanese version of the ESES has been developed, and its reliability and validity have been verified [22]. The Japanese version of the ESES consists of 10 items on a 4‐point Likert scale ranging from “Not at all confident” to “Always confident,” yielding a total score that ranges from 10 to 40 points. Higher scores indicate greater self‐efficacy.

2.4. Clinical Data

Demographic data (e.g., age, sex, and smoking status), comorbidities, and clinical parameters (e.g., hemoglobin [Hb] and albumin [Alb] levels) were collected from medical records and self‐administered questionnaires. For patients receiving PD, dialysis‐related variables, including modality (continuous ambulatory peritoneal dialysis [CAPD] or automated peritoneal dialysis [APD]) and Kt/V, an indicator of dialysis adequacy, were collected. CKD stage was classified according to the estimated glomerular filtration rate (eGFR), based on the Kidney Disease: Improving Global Outcomes guidelines [23]. For the purposes of this study, patients not receiving dialysis were categorized as early stage (G1–G3a: eGFR ≥ 45 mL/min/1.73 m²) or advanced stage (G3b–G5: eGFR < 45 mL/min/1.73 m²). Patients undergoing PD were classified as G5D, and analyses included three groups. Because CKD stage G3b and above is associated with a higher risk of cardiovascular events and mortality, an eGFR threshold of 45 mL/min/1.73 m² defined the groups [5]. Comorbidities were assessed using the Charlson Comorbidity Index (CCI). Because all participants had CKD, renal disease was excluded from the CCI calculation. Body composition parameters (body mass index [BMI] and skeletal muscle mass index [SMI]) were measured using bioelectrical impedance analysis.

2.5. Statistical Analysis

Participants were classified into three groups according to their renal function and treatment modality: early‐stage CKD (G1–G3a), advanced‐stage CKD (G3b–G5, non‐dialysis), and PD. Patient characteristics were presented using descriptive statistics and frequency distributions. The normality of continuous variables was assessed using the Shapiro–Wilk test. One‐way analysis of variance (ANOVA) was used when normality and homogeneity of variance assumptions were met. Welch's ANOVA was applied when homogeneity of variance was violated, and the Kruskal–Wallis test was used when normality was not assumed. For multiple comparisons, the Bonferroni method was applied when homogeneity of variance was confirmed; otherwise, the Games–Howell method was used with adjusted p values. Chi‐square tests compared categorical variables. Within each group, associations between PA levels (MVPA and step count) and age, sex, CCI, Hb, BMI, and ESES scores were examined using Spearman's rank correlation coefficient. Because disease severity, treatment modality, and PA‐related clinical characteristics were considered to differ among the early‐stage CKD, advanced‐stage CKD, and PD groups, multivariable regression analyses were conducted separately for each group. Variables that were statistically significant or showed suggestive associations in univariate analyses were entered into the multivariable regression models. The CCI was classified into three groups: 0 points (low risk), 1–2 points (moderate risk), and ≥ 3 points (high risk) [24]. Because the sample size in each group was small, interaction terms between group and ESES score were not examined. The ESES score was treated as a continuous variable. Statistical analysis was performed using IBM SPSS Statistics version 29 (IBM, Armonk, NY, USA), with a significance level of 5%.

3. Results

3.1. Patient Characteristics

Of the 118 participants who gave their consent, those with missing data were excluded, leaving 114 for analysis: 84 with non‐dialysis CKD and 30 undergoing PD (see Table 1). The mean age was 65 ± 12.2 years, with 57 participants (50%) being male. Hb and Alb levels were significantly lower in the PD group. No significant differences were observed in BMI or SMI. Furthermore, no significant differences were observed in smoking or alcohol consumption.

TABLE 1.

Baseline characteristics of the early CKD, advanced CKD, and PD groups.

	CKD Stage 1–3a (n = 37)	CKD Stage 3b–5 (n = 47)	PD (n = 30)	p
				Stage 1–3a vs. 3b–5	Stage 1–3a vs. PD	Stage 3b–5 vs. PD
Age (years)	63.0 ± 13.1	69.1 ± 12.0	61.8 ± 9.6	0.009 a	0.699 a	0.004 a
Sex (male), n (%)	17 (45.9)	28 (59.6)	12 (40)	0.205 b
CKD stage, n (%)
G1	3 (8.1)			< 0.001 b
G2	20 (54.1)
G3a	14 (37.8)
G3b		19 (40.4)
G4		19 (40.4)
G5		9 (19.1)	30 (100)
CCI score, n (%)
< 1	3 (8.1)	6 (12.8)		0.065 b
1–2	17 (45.9)	21 (44.7)	22 (73.3)
≥ 3	17 (45.9)	20 (42.6)	8 (26.7)
Hb (g/dL)	13.9 ± 1.6	12.3 ± 1.6	10.9 ± 1.0	< 0.001 c	< 0.001 c	< 0.001 c
Alb (g/dL)	4.2 ± 0.3	4.0 ± 0.4	3.3 ± 0.5	0.206 a	< 0.001 a	< 0.001 a
BMI (kg/m2)	23.3 ± 3.6	23.9 ± 3.9	23.1 ± 4.1	0.757 c	0.975 c	0.682 c
SMI (kg/m2)	6.8 ± 1.0	7.2 ± 1.3	7.2 ± 1.5	0.222 c	0.284 c	0.983 c
Smoking, n (%)	5 (13.5)	4 (8.5)	4 (13.3)	0.718 b
Alcohol consumption, n (%)	13 (35.1)	14 (29.8)	10 (33.3)	0.970 b
ESES score	25.4 ± 4.8	23.6 ± 5.8	23.6 ± 6.5	0.226 a	0.133 a	0.660 a

Note: Continuous variables were compared using ANOVA/Welch's ANOVA with Bonferroni or Games–Howell post hoc tests as appropriate. Non‐normally distributed variables were analyzed using the Kruskal–Wallis test. Continuous variables are presented as mean ± SD or median (interquartile range), as appropriate. Categorical variables are presented as number (%).

Abbreviations: Alb, albumin; ANOVA, analysis of variance; BMI, body mass index; CCI, Charlson Comorbidity Index; CKD, chronic kidney disease; ESES, Exercise Self‐Efficacy Scale; Hb, hemoglobin; PD, peritoneal dialysis; SD, standard deviation; SMI, skeletal muscle mass index.

^a Adjusted p values were calculated using the Kruskal–Wallis test.

^b Adjusted p values were calculated using the chi‐square test.

^c Adjusted p values were calculated using the Games–Howell post hoc test.

3.2. PA

The average ActiGraph wear time was 885.1 min/day. The valid wear period was 2 days for eight participants (7%) and 3 or more days for 106 (93%). No significant differences were observed in MVPA or daily step counts between participants with two valid wear days and those with three or more valid wear days (p = 0.07 and p = 0.45, respectively). Figure 1 shows the PA values for each group. The daily LPA was 281 min in the early CKD group, 215 min in the advanced CKD group, and 195 min in the PD group. A significant difference was observed between the early CKD and PD groups (p < 0.001). MVPA was 75 min/week in the early CKD group, 40 min/week in the advanced CKD group, and 32.5 min/week in the PD group. While no significant differences were observed between groups, all groups fell below recommended levels, with the advanced CKD and PD groups showing lower levels. The median daily step count was 4729, 3831, and 3086 steps, respectively, for the early CKD, advanced CKD, and PD groups. There was a significant difference between the early CKD and PD groups (p = 0.04). The early CKD group met the recommended level, whereas the advanced CKD and PD groups did not, with the PD group falling far short.

FIGURE 1.

Comparison of light physical activity (LPA) (a), moderate‐to‐vigorous physical activity (MVPA) (b), and daily steps (c) among the groups. The dashed lines indicate the reference thresholds for MVPA (≥ 150 min/week) and daily steps (≥ 4000 steps/day). CKD, chronic kidney disease; LPA, light physical activity; MVPA, moderate‐to‐vigorous physical activity; PD, peritoneal dialysis.

3.3. Exercise Self‐Efficacy and PA

Table 2 shows the univariate correlations between each PA level and clinical data/ESES scores. In the advanced CKD group, age was negatively correlated with MVPA. By contrast, positive correlations were observed between the ESES score and both MVPA and step count in the PD group. Further analyses examined associations between PA and Hb, Alb, dialysis modality, and dialysis adequacy in the PD group. Neither Hb (MVPA: ρ = 0.039, p = 0.840; step count: ρ = 0.099, p = 0.603) nor Alb (MVPA: ρ = 0.045, p = 0.812; step count: ρ = −0.040, p = 0.833) was significantly associated with MVPA or step count. MVPA and step count did not differ significantly between patients receiving CAPD and APD (p = 0.632 and p = 0.545, respectively). Kt/V was not significantly associated with MVPA (ρ = 0.150, p = 0.430) or step count (ρ = 0.172, p = 0.363). Based on these results, multivariable regression analysis was performed with MVPA and step count as the dependent variables (Table 3). In the advanced CKD group, age showed a negative correlation with MVPA. Conversely, the ESES score showed significant positive associations with MVPA and step count in the PD group. After adjustment for age, Hb, and Alb, the ESES score remained independently associated with MVPA (β = 0.546, p = 0.007) and step count (β = 0.454, p = 0.030) (Table S1).

TABLE 2.

Correlation analysis between physical activity and related factors, stratified by group.

	CKD Stage 1–3a (n = 37)			CKD Stage 3b–5 (n = 47)			PD (n = 30)
	LPA (min/day)	MVPA (min/week)	Steps (steps/day)	LPA (min/day)	MVPA (min/week)	Steps (steps/day)	LPA (min/day)	MVPA (min/week)	Steps (steps/day)
Age	0.00	−0.28	−0.26	−0.07	−0.38**	−0.18	0.05	0.00	0.04
Hb	−0.08	0.06	0.11	0.06	−0.03	0.06	0.07	0.04	0.10
Alb	−0.10	0.20	0.14	0.03	−0.03	−0.01	−0.20	0.05	−0.04
BMI	−0.17	−0.05	−0.03	0.01	−0.21	−0.08	0.00	−0.02	0.01
SMI	−0.03	0.17	0.10	−0.06	0.13	0.04	0.15	0.20	0.28
ESES	−0.13	0.00	−0.19	0.26	0.24	0.27	0.08	0.38*	0.42*

Note: Spearman's rank correlation coefficients (ρ) were calculated to examine associations between physical activity variables and baseline demographic and clinical factors in each group.

Abbreviations: Alb, albumin; BMI, body mass index; CKD, chronic kidney disease; ESES, Exercise Self‐Efficacy Scale; Hb, hemoglobin; LPA, light physical activity; MVPA, moderate‐to‐vigorous physical activity; PD, peritoneal dialysis; SMI, skeletal muscle mass index.

^** p < 0.01.

^* p < 0.05.

TABLE 3.

Multivariable regression analyses of the association between ESES score and physical activity, stratified by group.

	CKD Stage 1–3a (n = 37)				CKD Stage 3b–5 (n = 47)				PD (n = 30)
	MVPA (min/week)		Steps (steps/day)		MVPA (min/week)		Steps (steps/day)		MVPA (min/week)		Steps (steps/day)
	β	p	β	p	β	p	β	p	β	p	β	p
Age	−0.238	0.270	−0.327	0.117	−0.311	0.036	−0.156	0.309	−0.146	0.455	−0.140	0.490
Sex	−0.232	0.259	−0.121	0.535	−0.310	0.059	−0.111	0.513	−0.071	0.718	−0.006	0.975
CCI	−0.125	0.555	0.316	0.125	−0.137	0.386	−0.172	0.305	−0.204	0.286	−0.331	0.101
Hb	−0.009	0.964	−0.088	0.660	−0.242	0.152	−0.063	0.720	0.107	0.563	0.022	0.908
BMI	−0.065	0.724	−0.040	0.822	−0.104	0.487	−0.067	0.671	−0.213	0.272	−0.121	0.545
ESES	0.074	0.700	−0.246	0.185	0.145	0.357	0.230	0.170	0.503	0.019	0.433	0.047

Note: Sex was coded as male = 0, female = 1. CCI was categorized as 0 points (low risk), 1–2 points (moderate risk), and ≥ 3 points (high risk).

Abbreviations: BMI, body mass index; CCI, Charlson Comorbidity Index; CKD, chronic kidney disease; ESES, Exercise Self‐Efficacy Scale; Hb, hemoglobin; MVPA, moderate‐to‐vigorous physical activity; PD, peritoneal dialysis.

4. Discussion

This study objectively demonstrated that PA declines with CKD progression, particularly among patients undergoing PD, in the context of an aging population of patients with CKD. Furthermore, exercise self‐efficacy was associated with PA in this population. MVPA levels fell below recommended thresholds across all groups, suggesting insufficient PA among patients with CKD.

Although PD is a home‐based therapy that offers a high degree of flexibility in daily life, PA levels were lowest among patients undergoing PD in this study. This may be due to physical factors such as renal anemia, malnutrition, and abdominal distension, as well as time constraints associated with dialysis exchanges and reduced opportunities for activity [25, 26, 27]. In this study, PA was not significantly associated with Hb, Alb, Kt/V, or dialysis modality (CAPD/APD). These findings suggest that nonclinical and non‐dialysis‐related factors may contribute to reduced PA among patients undergoing PD. As patients with CKD age, they are more likely to develop comorbidities such as diabetes and cardiovascular disease. PA plays a crucial role not only in relation to renal function but also in the management of these conditions and maintenance of physical function [4, 5]. Consequently, a decline in PA may lead to an increased risk of multifaceted health issues.

Conversely, a key finding of this study was that exercise self‐efficacy was associated with PA only among patients undergoing PD. These findings suggest that self‐efficacy may be associated with PA despite physical limitations. Although Hb, Alb, Kt/V, and dialysis modality (CAPD/APD) were not significantly associated with PA, exercise self‐efficacy remained independently associated with MVPA and step count after adjustment for age, Hb, and Alb. Together, these findings suggest that exercise‐related psychological factors, alongside physical factors, may influence PA among patients undergoing PD. Self‐efficacy refers to an individual's belief in their ability to accomplish specific tasks or goals and is an important psychosocial factor associated with health behaviors [11]. Higher self‐efficacy has been associated with PA levels and long‐term activity maintenance among older adults and patients with chronic diseases [28]. Previous studies have shown that self‐efficacy‐enhancing interventions, including patient involvement in goal setting and nursing feedback, are associated with improved PA and self‐management behaviors among patients with chronic diseases [29, 30]. These findings suggest that self‐efficacy‐focused support strategies may also be important for patients undergoing PD. Previous studies have primarily used self‐reported questionnaires and pedometers to assess PA in patients with CKD, particularly those undergoing PD [31, 32]. While these studies consistently indicate low PA levels among patients undergoing PD, many rely on subjective assessments that do not fully capture activity intensity [33]. A key feature of this study was that accelerometers were used to objectively and quantitatively assess PA in patients ranging from those with early‐ and advanced‐stage CKD to those undergoing PD. While the findings are broadly consistent with previous observational studies and systematic reviews reporting low PA levels among patients undergoing PD [7], the present study is notable in that it objectively quantified activity intensity using accelerometry. Furthermore, by examining the association between activity intensity and exercise self‐efficacy in patients undergoing PD, this study provides objective evidence that could inform future intervention strategies. These findings suggest that supporting daily PA in this population requires more than exercise recommendations and should address exercise self‐efficacy. Multidisciplinary approaches incorporating goal setting, feedback, and ongoing nurse support may strengthen self‐efficacy and encourage PA. Longitudinal and interventional studies are needed to clarify these relationships.

The intergroup comparisons in this study are not intended to provide a straightforward comparison of different patient populations; rather, they were aimed at capturing changes in PA within clinical pathways in relation to CKD progression and differences in treatment modalities. Furthermore, as the population of patients with CKD continues to age, reduced PA is likely to become an increasingly important clinical issue. While this study did not strictly focus on older adults, the combination of aging and disease progression may lead to a more pronounced decline in PA.

This study has some limitations. First, participants were recruited from a single facility, so caution is required when interpreting the results and generalizing the conclusions given the small sample size. Second, as participants were interested in PA, there is a potential for self‐selection bias. Third, although 60‐s epochs are widely used in accelerometer research, they may average brief activity bouts in older adults and underestimate MVPA. Furthermore, as this was a cross‐sectional study, it was not possible to establish a causal relationship between self‐efficacy and PA. Further research is required, including intervention and longitudinal studies, to verify the impact of changes in self‐efficacy on PA levels.

In conclusion, PA declined as CKD progressed, with the lowest levels observed among patients undergoing PD. Exercise self‐efficacy was associated with PA, particularly in this group. These findings suggest that exercise self‐efficacy may be important when encouraging daily PA among patients receiving PD. Further research should investigate factors associated with PA in aging populations with CKD and those receiving dialysis. Longitudinal and interventional studies should also evaluate appropriate nursing support.

Author Contributions

Megumi Yoshida: acquired research funding and participated in study conception, design, patient recruitment, data analysis, and writing. Ryuichi Sakamoto: participated in designing, recruiting, and writing the study. Toshiaki Nakano: participated in designing, recruiting, and writing the study. Toshiaki Ohkuma: helped design, recruit, and write the study. Kimie Fujita: participated in study design, formal analysis, data interpretation, writing – review and editing, critical review of intellectual content, and final approval of the manuscript.

Funding

This work was supported by Japan Society for the Promotion of Science (JP22K21148).

Ethics Statement

This study was conducted in accordance with the Declaration of Helsinki. The Ethics Review Committee of Kyushu University approved this study (ID: 23028‐01). All participants provided written informed consent to participate in this study.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Table S1: Multivariable regression analysis of factors associated with physical activity in patients receiving peritoneal dialysis.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.