Relationships between Neighborhood Walkability and Objectively Measured Physical Activity Levels in Hemodialysis Patients

Narrative Review: Clinical Implications and Assessment of Frailty in Patients With Advanced CKD

Frailty is a multidimensional clinical syndrome characterized by low physical activity, reduced strength, accumulation of multiorgan deficits, decreased physiological reserve, and vulnerability to stressors. Frailty has key social, psychological, and cognitive implications. Frailty is accelerated by uremia, leading to a high prevalence of frailty in patients with advanced chronic kidney disease (CKD) and end-stage kidney disease (ESKD) as well as contributing to adverse outcomes in this patient population. Frailty assessment is not routine in patients with CKD; however, a number of validated clinical assessment tools can assist in prognostication. Frailty assessment in nephrology populations supports shared decision-making and advanced communication and should inform key medical transitions. Frailty screening and interventions in CKD or ESKD are a developing research priority with a rapidly expanding literature base.

Correlates of Rates and Treatment Readiness for Depressive Symptoms, Pain, and Fatigue in Hemodialysis Patients: Results from the TĀCcare Study

Key Points

Lower neighborhood walkability was associated with higher depressive symptoms and fatigue and younger age with depressive symptoms. Depressive symptoms, pain, and fatigue were frequently reported, often occurred together, and were often not all already treated. Patients with a higher symptom burden and men may be more likely to be ready to seek treatment for depressive symptoms, pain, or fatigue.

Background

Patients on hemodialysis (HD) often experience clinically significant levels of pain, fatigue, and depressive symptoms. We explored potential sociodemographic differences in symptom burden, current treatment, and readiness to seek treatment for these symptoms in patients screened for the TĀCcare trial.

Methods

In-center HD patients from Pennsylvania and New Mexico were screened for fatigue (≥5 on 0–10-point Likert scale), pain (Likert scale ≥4), depressive symptoms (≥10 Patient Health Questionnaire-9), and readiness to seek treatment (5–item Stages of Behavior Change questionnaire). Symptom burden and treatment status by sociodemographic factors were evaluated using chi square, Fisher exact tests, and logistic regression models.

Results

From March 2018 to December 2021, 506 of 896 (57%) patients screened met eligibility criteria and completed the symptom screening (mean age 60±13.9 years, 44% female, 17% Black, 25% American Indian, and 25% Hispanics). Of them, 77% screened positive for ≥1 symptom and 35% of those were receiving treatment for ≥1 of these symptoms. Pain, fatigue, and depressive symptom rates were 52%, 64%, and 24%, respectively. Age younger than 65 years was associated with a higher burden of depressive symptoms, pain, and reporting ≥1 symptom (P <0.05). The percentage of patients ready to seek treatment increased with symptom burden. More men reported readiness to seek treatment (85% versus 68% of women, P <0.001). Among those with symptoms and treatment readiness, income was inversely associated with pain (>$60,000/yr: odds ratio [OR]=0.16, confidence interval [CI]=0.03 to 0.76) and living in less walkable neighborhoods with more depressive symptoms (OR= 5.34, CI=1.19 to 24.05) and fatigue (OR= 5.29, CI=1.38 to 20.33).

Conclusions

Pain, fatigue, and depressive symptoms often occurred together, and younger age, less neighborhood walkability, and lower income were associated with a higher burden of symptoms in HD patients. Male patients were less likely to be receiving treatment for symptoms. These findings could inform priority HD patient symptom identification and treatment targets.

The Impact of a Wearable Activity Tracker and Structured Feedback Program on Physical Activity in Hemodialysis Patients: The Step4Life Pilot Randomized Controlled Trial

RATIONALE & OBJECTIVE

People with end-stage kidney disease (ESKD) have very low physical activity, and the degree of inactivity is strongly associated with morbidity and mortality. We assessed the feasibility and effectiveness of a 12-week intervention coupling a wearable activity tracker (FitBit) and structured feedback coaching versus wearable activity tracker alone on changes in physical activity in hemodialysis patients.

STUDY DESIGN

Randomized controlled trial.

SETTING & PARTICIPANTS

55 participants with ESKD receiving hemodialysis who were able to walk with or without assistive devices recruited from a single academic hemodialysis unit between January 2019 and April 2020.

INTERVENTIONS

All participants wore a Fitbit Charge 2 tracker for a minimum of 12 weeks. Participants were randomly assigned 1:1 to a wearable activity tracker plus a structured feedback intervention versus the wearable activity tracker alone. The structured feedback group was counseled weekly on steps achieved after randomization.

OUTCOME

The outcome was step count, and the main parameter of interest was the absolute change in daily step count, averaged per week, from baseline to completion of 12 weeks intervention. In the intention-to-treat analysis, mixed-effect linear regression analysis was used to evaluate change in daily step count from baseline to 12-weeks in both arms.

RESULTS

Out of 55 participants, 46 participants completed the 12-week intervention (23 per arm). The mean age was 62 (± 14 SD) years; 44% were Black, and 36% were Hispanic. At baseline, step count (structured feedback intervention: 3,704 [1,594] vs wearable activity tracker alone: 3,808 [1,890]) and other participant characteristics were balanced between the arms. We observed a larger change in daily step count in the structured feedback arm at 12 weeks relative to use of the wearable activity tracker alone arm (Δ 920 [±580 SD] versus Δ 281 [±186 SD] steps; between-group difference Δ 639 [±538 SD] steps; P<0.05).

LIMITATIONS

Single-center study and small sample size.

CONCLUSION

This pilot randomized controlled trial demonstrated that structured feedback coupled with a wearable activity tracker led to a greater daily step count that was sustained over 12 weeks relative to a wearable activity tracker alone. Future studies are required to determine longer-term sustainability of the intervention and potential health benefits in hemodialysis patients.

FUNDING

Grants from industry (Satellite Healthcare) and government (National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK).

TRIAL REGISTRATION

Registered at ClinicalTrials.gov with study number NCT05241171.

Continuous Long-Term Physical Activity Monitoring in Hemodialysis Patients

Background

Physical inactivity is common in patients receiving hemodialysis, but activity patterns throughout the day and in relation to dialysis are largely unknown. This knowledge gap can be addressed by long-term continuous activity monitoring, but this has not been attempted and may not be acceptable to patients receiving dialysis.

Methods

Ambulatory patients with end-stage kidney disease receiving thrice-weekly hemodialysis wore commercially available wrist-worn activity monitors for 6 months. Step counts were collected every 15 minutes and were linked to dialysis treatments. Physical function was assessed using the Short Physical Performance Battery (SPPB). Fast time to recovery from dialysis was defined as ≤2 hours. Mixed effects models were created to estimate step counts over time.

Results

Of 52 patients enrolled, 48 were included in the final cohort. The mean age was 60 years, and 75% were Black or Hispanic. Comorbidity burden was high, 38% were transported to and from dialysis by paratransit, and 79% had SPPB <10. Median accelerometer use (199 days) and adherence (95%) were high. Forty-two patients (of 43 responders) reported wearing the accelerometer every day, and few barriers to adherence were noted. Step counts were lower on dialysis days (3991 [95% CI, 3187 to 4796] versus 4561 [95% CI, 3757 to 5365]), but step-count intensity was significantly higher during the hour immediately after dialysis than during the corresponding time on nondialysis days (188 steps per hour increase [95% CI, 171 to 205]); these levels were the highest noted at any time. Postdialysis increases were more pronounced among patients with fast recovery time (225 [95% CI, 203 to 248] versus 134 [95% CI, 107 to 161] steps per hour) or those with SPPB ≥7. Estimates were unchanged after adjustment for demographics, diabetes status, and ultrafiltration rate.

Conclusions

Long-term continuous monitoring of physical activity is feasible in patients receiving hemodialysis. Highly granular data collection and analysis yielded new insights into patterns of activity after dialysis treatments.

How different are objective operationalizations of walkability for older adults compared to the general population? A systematic review

Background

Walking is an essential activity for everyone and for older adults in particular, given that it is the most accessible form of physical activity and one of the healthiest transportation modes. Understanding how walkability (the potential of the environment to enable and/or encourage walking) has been objectively measured and analyzed for older adults is critical to create more inclusive, healthy, and sustainable environments and to promote healthy aging. Despite the numerous reviews on physical activity among older adults and its relationship with the built environment, the literature still lacks comparison reviews focusing specifically on objective operationalizations of walkability for older adults vs. the general population.

Methods

We conducted a systematic review of 146 empirical studies that measured walkability objectively in relation to walking-related outcomes. We compared studies focused on older adults (n = 24) and the general population (n = 122). Content analysis included the characteristics of the study design, walkability measures, spatial extent, and associations found between walkability and walking-related outcomes.

Results

In both groups of publications, the majority of studies were conducted in the US, Canada, and Europe, and largely in high-income countries. They were mostly published in health-related journals and used cross-sectional designs, operationalized walkability by using indexes, employed self-reported measures for walking-related outcomes, and found positive associations between walkability and walking outcomes. However, we observed some differences among studies focusing on older adults. Compared to studies focusing on the general population, a larger proportion of studies on older adults was conducted in the Middle East and Asia, and they used longitudinal designs, mixed methods to measure walking-related outcomes, variables related with land-use characteristics, safety from traffic and crime, and greenery, and a larger proportion found positive, as well as no associations between walkability and walking-related outcomes.

Conclusion

Although there is a promising increase in interest in older adults-focused walkability studies in the last decade, there is still a need for more studies focusing on different settings, using wider spatial extents, longitudinal designs, objective or mixed methods to collect outcome data, and specific variables and/or specially created indexes for older adults and for settings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-03233-x.

Daily Step Counts in Patients With Chronic Kidney Disease: A Systematic Review and Meta-Analysis of Observational Studies

Background

Physical inactivity is an essential factor in the prognosis of patients with chronic kidney disease (CKD). Daily step count is a straightforward measure to assess physical activity levels. Understanding the step counts among different CKD stages is essential to change sedentary behavior.

Objectives

This systematic review and meta-analysis aimed to investigate the daily step counts in patients with CKD at a different stage.

Design

A systematic review and meta-analysis.

Data Sources

The literature search was performed in PubMed, Embase, and Web of Science from inception to November 3rd, 2021.

Review Methods

Observational studies (cross-sectional, case-control, or cohort studies) reported specific values of step counts in CKD patients by the wearable device were included. A random-effects model was used to pool the data. Subgroup analysis explored differences in outcomes by stage of CKD. Heterogeneity between studies was assessed using the χ2 test of Cochrane's Q statistic. A contour-enhanced funnel plot was conducted to investigate publication bias. Univariate and multivariate meta-regression was conducted to examine possible sources of heterogeneity.

Results

Twenty-eight articles were identified and used for quantitative analysis. The result showed that the daily step count in patients with CKD was 4642.47 (95% CI: 4274.18–5010.76), and significantly lower than the healthy population. Subgroup analysis revealed that the step counts decreased before dialysis, dropped to a freezing point at the hemodialysis phase, and increased after kidney transplantation. Meta-regression analysis showed that daily step counts were relatively higher in the Americas or younger than 60 or kidney transplant recipients.

Conclusion

The status of daily step counts in patients with CKD decreases with CKD severity and increases after kidney transplantation. Although studies have begun to focus on strategies to improve step counts in patients with CKD, future studies should focus more on step counts in pre-dialysis patients and changing their physically inactive lifestyle early to alleviate deteriorating renal function.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=291551, identifier: CRD42021291551.

The Impact of Wearable Technologies in Health Research: Scoping Review

Background

Wearable devices hold great promise, particularly for data generation for cutting-edge health research, and their demand has risen substantially in recent years. However, there is a shortage of aggregated insights into how wearables have been used in health research.

Objective

In this review, we aim to broadly overview and categorize the current research conducted with affordable wearable devices for health research.

Methods

We performed a scoping review to understand the use of affordable, consumer-grade wearables for health research from a population health perspective using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework. A total of 7499 articles were found in 4 medical databases (PubMed, Ovid, Web of Science, and CINAHL). Studies were eligible if they used noninvasive wearables: worn on the wrist, arm, hip, and chest; measured vital signs; and analyzed the collected data quantitatively. We excluded studies that did not use wearables for outcome assessment and prototype studies, devices that cost >€500 (US $570), or obtrusive smart clothing.

Results

We included 179 studies using 189 wearable devices covering 10,835,733 participants. Most studies were observational (128/179, 71.5%), conducted in 2020 (56/179, 31.3%) and in North America (94/179, 52.5%), and 93% (10,104,217/10,835,733) of the participants were part of global health studies. The most popular wearables were fitness trackers (86/189, 45.5%) and accelerometer wearables, which primarily measure movement (49/189, 25.9%). Typical measurements included steps (95/179, 53.1%), heart rate (HR; 55/179, 30.7%), and sleep duration (51/179, 28.5%). Other devices measured blood pressure (3/179, 1.7%), skin temperature (3/179, 1.7%), oximetry (3/179, 1.7%), or respiratory rate (2/179, 1.1%). The wearables were mostly worn on the wrist (138/189, 73%) and cost <€200 (US $228; 120/189, 63.5%). The aims and approaches of all 179 studies revealed six prominent uses for wearables, comprising correlations—wearable and other physiological data (40/179, 22.3%), method evaluations (with subgroups; 40/179, 22.3%), population-based research (31/179, 17.3%), experimental outcome assessment (30/179, 16.8%), prognostic forecasting (28/179, 15.6%), and explorative analysis of big data sets (10/179, 5.6%). The most frequent strengths of affordable wearables were validation, accuracy, and clinical certification (104/179, 58.1%).

Conclusions

Wearables showed an increasingly diverse field of application such as COVID-19 prediction, fertility tracking, heat-related illness, drug effects, and psychological interventions; they also included underrepresented populations, such as individuals with rare diseases. There is a lack of research on wearable devices in low-resource contexts. Fueled by the COVID-19 pandemic, we see a shift toward more large-sized, web-based studies where wearables increased insights into the developing pandemic, including forecasting models and the effects of the pandemic. Some studies have indicated that big data extracted from wearables may potentially transform the understanding of population health dynamics and the ability to forecast health trends.

Wearable Fitness Trackers to Predict Clinical Deterioration in Maintenance Hemodialysis: A Prospective Cohort Feasibility Study

Rationale & Objective

People receiving hemodialysis often require urgent care or hospitalizations. It is possible that reductions in a patient’s level of physical activity may serve as an “early warning” of clinical deterioration, allowing timely clinical intervention. We explored whether step count could serve as a trigger for deterioration.

Study Design

Prospective observational cohort feasibility study.

Setting & Participants

We recruited consenting adult participants from outpatient dialysis clinics in Calgary, AB, between June 28, 2019, and October 10, 2019.

Exposure and Outcomes

Participants wore a wristband fitness tracker for 4 weeks. Activity data from the trackers were imported weekly into the study database. Demographic, clinical management, functional impairment, and frailty were assessed at baseline. Clinical events (urgent care and emergency department visits and hospitalizations) were monitored during the observation period.

Analytical Approach

Box and whisker plots and line plots were used to describe each participant’s daily steps. Adjusted rate ratios (and 95 % confidence intervals) were calculated to assess the associations between the number of steps taken each day and potential predictors.

Results

Data from 46 patients were included; their median age was 64 years (range, 22 to 85), and 63 % were men. The median number of steps taken per day was 3,133 (range, 248-13,753). Fourteen events among 11 patients were reported. Within patients, step count varied considerably; it was not possible to identify a patient-specific normal range for daily step count. There was no association between step count and the occurrence of clinical events, although the number of events was very small.

Limitations

The number of participants was relatively small, and there were too few events to model to examine whether step count could predict clinical deterioration.

Conclusions

Within-patient variation in daily step count was too high to generate a normal range for patients. However, patient-specific norms over a longer period (3- or 7-day periods) appear potentially worthy of future study in a larger sample and/or over a longer follow-up.

Exercise training in chronic kidney disease-effects, expectations and adherence

There is increasing evidence showing the health benefits of physical activity, such as better survival and possibly even a slower decline in kidney function, in people with chronic kidney disease (CKD). There is convincing evidence that exercise training improves physical function measured as aerobic capacity, muscle endurance strength and balance at all ages and all stages of CKD. In fact, long-term adherence to well-designed and adequately monitored exercise training programmes is high. In general, patients express interest in exercise training and are motivated to improve their physical function and health. A growing number of nephrologists regard physical activity and exercise training as beneficial to patients with CKD. However, many feel that they do not have the knowledge to prescribe exercise training and suppose that patients are not interested. Patients state that support from healthcare professionals is crucial to motivate them to participate in exercise training programmes and overcome medical, physical and psychological barriers such as frailty, fatigue, anxiety and fear. Equally important is the provision of funding by healthcare providers to ensure adequate prescription and follow-up by trained exercise physiologists for this important non-pharmacological treatment.

Physical activity in hemodialysis patients on nondialysis and dialysis days: Prospective observational study

INTRODUCTION

The physical decline in patients with end-stage kidney disease (ESKD) is associated with morbidity and mortality. Prior studies have attempted to promote physical activity at the time of dialysis; however, physical activity patterns on the nondialysis days are unknown. This study aimed to quantify physical activity on dialysis and nondialysis days in hemodialysis patients using a wearable actigraph.

METHODS

In this prospective study, subjects receiving hemodialysis were recruited from two outpatient dialysis units in urban San Diego and rural Imperial County, CA, between March 2018 and April 2019. Key inclusion criteria included: (1) receiving thrice weekly hemodialysis for ≥3 months, (2) age ≥ 18 years, and (3) able to walk with or without assistive devices. All participants wore a Fitbit Charge 2 tracker for a minimum of 4 weeks. The primary outcome was the number of steps per day. Each participant completed the Physical Activity Questionnaire, the Patient Health Questionnaire (PHQ)-9, the PROMIS Short form Fatigue Questionnaire at baseline, and the Participant Technology Experience Questionnaire at day 7 after study enrolment.

FINDINGS

Of the 52 recruited, 45 participants (urban = 25; rural = 20) completed the study. The mean age was 61 ± 15 years, 42% were women, 64% were Hispanic, and the mean dialysis vintage was 4.4 ± 3.0 years. For those with valid Fitbit data (defined as ≥10 hours of wear per day) for 28 days (n = 45), participants walked an average of 3688 steps per day, and 73% of participants were sedentary (<5000 steps/day). Participants aged >80 years were less active than younger (age < 65 years) participants (1232 vs. 4529 steps, P = 0.01). There were no statistical differences between the groups when stratified by gender (women vs. men [2817 vs. 4324 steps, respectively]), urbanicity (rural vs. urban dialysis unit [3141 vs. 4123 steps, respectively]), and dialysis/nondialysis day (3177 vs. 4133 steps, respectively). Due to the small sample size, we also calculated effect sizes. The effect size was medium for the gender differences (cohen's d = 0.57) and small to medium for urbanicity and dialysis/nondialysis day (d = 0.37 and d = 0.33, respectively). We found no association between physical activity and self-reported depression and fatigue scale. The majority of participants (62%, 28/45) found the Fitbit tracker easy to wear and comfortable.

DISCUSSION

ESKD participants receiving hemodialysis are frequently sedentary, and differences appear more pronounced in older patients. These findings may assist in designing patient-centered interventions to increase physical activity among hemodialysis patients.

Impact of hemodialysis and post-dialysis period on granular activity levels

Background

Physical activity (PA) is typically lower on hemodialysis (HD) days. Albeit intradialytic inactivity is expected, it is unknown whether recovery after HD contributes to low PA. We investigated the impact of HD and post-HD period on granular PA relative to HD timing.

Methods

We used baseline data from the HDFIT trial conducted from August 2016 to October 2017. Accelerometry measured PA over 1 week in patients who received thrice-weekly high-flux HD (vintage 3 to 24 months), were clinically stable, and had no ambulatory limitations. PA was assessed on HD days (0 to ≤24 h after start HD), first non-HD days (> 24 to ≤48 h after start HD) and second non-HD day (> 48 to ≤72 h after start HD). PA was recorded in blocks/slices: 4 h during HD, 0 to ≤2 h post-HD (30 min slices), and > 2 to ≤20 h post-HD (4.5 h slices). Blocks/slices of PA were captured at concurrent/parallel times on first/second non-HD days compared to HD days.

Results

Among 195 patients (mean age 53 ± 15 years, 71% male), step counts per 24-h were 3919 ± 2899 on HD days, 5308 ± 3131 on first non-HD days (p < 0.001), and 4926 ± 3413 on second non-HD days (p = 0.032). During concurrent/parallel times to HD on first and second non-HD days, patients took 1308 and 1128 more steps (both p < 0.001). Patients took 276 more steps and had highest rates of steps/hour 2-h post-HD versus same times on first non-HD days (all p < 0.05). Consistent findings were observed on second non-HD days.

Conclusions

PA was higher within 2-h of HD versus same times on non-HD days. Lower PA on HD days was attributable to intradialytic inactivity. The established PA profiles are of importance to the design and development of exercise programs that aim to increase activity during and between HD treatments.

Trial registration

HDFIT was prospectively registered 20 April 2016 on ClinicalTrials.gov (NCT02787161)

Standardising the measurement of physical activity in people receiving haemodialysis: considerations for research and practice

BACKGROUND

Physical activity (PA) is exceptionally low amongst the haemodialysis (HD) population, and physical inactivity is a powerful predictor of mortality, making it a prime focus for intervention. Objective measurement of PA using accelerometers is increasing, but standard reporting guidelines essential to effectively evaluate, compare and synthesise the effects of PA interventions are lacking. This study aims to (i) determine the measurement and processing guidance required to ensure representative PA data amongst a diverse HD population, and; (ii) to assess adherence to PA monitor wear amongst HD patients.

METHODS

Clinically stable HD patients from the UK and China wore a SenseWear Armband accelerometer for 7 days. Step count between days (HD, Weekday, Weekend) were compared using repeated measures ANCOVA. Intraclass correlation coefficients (ICCs) determined reliability (≥0.80 acceptable). Spearman-Brown prophecy formula, in conjunction with a priori ≥  80% sample size retention, identified the minimum number of days required for representative PA data.

RESULTS

Seventy-seven patients (64% men, mean ± SD age 56 ± 14 years, median (interquartile range) time on HD 40 (19-72) months, 40% Chinese, 60% British) participated. Participants took fewer steps on HD days compared with non-HD weekdays and weekend days (3402 [95% CI 2665-4140], 4914 [95% CI 3940-5887], 4633 [95% CI 3558-5707] steps/day, respectively, p < 0.001). PA on HD days were less variable than non-HD days, (ICC 0.723-0.839 versus 0.559-0.611) with ≥ 1 HD day and ≥  3 non-HD days required to provide representative data. Using these criteria, the most stringent wear-time retaining ≥ 80% of the sample was ≥7 h.

CONCLUSIONS

At group level, a wear-time of ≥7 h on ≥1HD day and ≥ 3 non-HD days is required to provide reliable PA data whilst retaining an acceptable sample size. PA is low across both HD and non- HD days and future research should focus on interventions designed to increase physical activity in both the intra and interdialytic period.