Association of habitual physical activity measured by an accelerometer with high-density lipoprotein cholesterol levels in maintenance hemodialysis patients

Data Analytics in Physical Activity Studies With Accelerometers: Scoping Review

BACKGROUND

Monitoring free-living physical activity (PA) through wearable devices enables the real-time assessment of activity features associated with health outcomes and provision of treatment recommendations and adjustments. The conclusions of studies on PA and health depend crucially on reliable statistical analyses of digital data. Data analytics, however, are challenging due to the various metrics adopted for measuring PA, different aims of studies, and complex temporal variations within variables. The application, interpretation, and appropriateness of these analytical tools have yet to be summarized.

OBJECTIVE

This research aimed to review studies that used analytical methods for analyzing PA monitored by accelerometers. Specifically, this review addressed three questions: (1) What metrics are used to describe an individual's free-living daily PA? (2) What are the current analytical tools for analyzing PA data, particularly under the aims of classification, association with health outcomes, and prediction of health events? and (3) What challenges exist in the analyses, and what recommendations for future research are suggested regarding the use of statistical methods in various research tasks?

METHODS

This scoping review was conducted following an existing framework to map research studies by exploring the information about PA. Three databases, PubMed, IEEE Xplore, and the ACM Digital Library, were searched in February 2024 to identify related publications. Eligible articles were classification, association, or prediction studies involving human PA monitored through wearable accelerometers.

RESULTS

After screening 1312 articles, 428 (32.62%) eligible studies were identified and categorized into at least 1 of the following 3 thematic categories: classification (75/428, 17.5%), association (342/428, 79.9%), and prediction (32/428, 7.5%). Most articles (414/428, 96.7%) derived PA variables from 3D acceleration, rather than 1D acceleration. All eligible articles (428/428, 100%) considered PA metrics represented in the time domain, while a small fraction (16/428, 3.7%) also considered PA metrics in the frequency domain. The number of studies evaluating the influence of PA on health conditions has increased greatly. Among the studies in our review, regression-type models were the most prevalent (373/428, 87.1%). The machine learning approach for classification research is also gaining popularity (32/75, 43%). In addition to summary statistics of PA, several recent studies used tools to incorporate PA trajectories and account for temporal patterns, including longitudinal data analysis with repeated PA measurements and functional data analysis with PA as a continuum for time-varying association (68/428, 15.9%).

CONCLUSIONS

Summary metrics can quickly provide descriptions of the strength, frequency, and duration of individuals' overall PA. When the distribution and profile of PA need to be evaluated or detected, considering PA metrics as longitudinal or functional data can provide detailed information and improve the understanding of the role PA plays in health. Depending on the research goal, appropriate analytical tools can ensure the reliability of the scientific findings.

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.

Dietary Intake, Body Composition, and Clinical Parameters: Associations Between the Level and Type of Physical Activity in Hemodialysis Patients

BACKGROUND

Physical inactivity and muscle wasting potentiate each other and are highly prevalent among hemodialysis (HD) patients. The authors evaluated the association between physical activity (PA), clinical, nutritional, and body composition parameters in HD patients.

METHODS

Multicenter cross-sectional study with 581 HD patients. Clinical, body composition, dietary intake, and PA data were recorded. For the analysis, patients were divided into active (follow World Health Organization recommendations) and inactive groups.

RESULTS

A total of 20% of the patients followed World Health Organization recommendations on PA. Differences between physically active and physically inactive patients were observed in age, biochemical parameters and total body water, intracellular water, lean tissue index (LTI), body cell mass, energy, and protein intake. PA was a predictor of higher LTI, body cell mass, and energy intake independently of age, gender, presence of diabetes, dialysis adequacy, and dialysis vintage. Controlling for the effect of age, walking and vigorous PA were positively correlated with energy and protein intake. Vigorous PA was also positively correlated with LTI.

CONCLUSION

The PA is a predictor of higher LTI, body cell mass, and energy intake. Vigorous PA is associated with an improved body composition and dietary pattern, whereas walking seems to be also associated with a favorable nutritional status.

Effect of hemodiafiltration on measured physical activity: primary results of the HDFIT randomized controlled trial

Background

Dialysis patients are typically inactive and their physical activity (PA) decreases over time. Uremic toxicity has been suggested as a potential causal factor of low PA in dialysis patients. Post-dilution high-volume online hemodiafiltration (HDF) provides greater higher molecular weight removal and studies suggest better clinical/patient-reported outcomes compared with hemodialysis (HD).

Methods

HDFIT was a randomized controlled trial at 13 clinics in Brazil that aimed to investigate the effects of HDF on measured PA (step counts) as a primary outcome. Stable HD patients (vintage 3–24 months) were randomized to receive HDF or high-flux HD. Treatment effect of HDF on the primary outcome from baseline to 3 and 6 months was estimated using a linear mixed-effects model.

Results

We randomized 195 patients (HDF 97; HD 98) between August 2016 and October 2017. Despite the achievement of a high convective volume in the majority of sessions and a positive impact on solute removal, the treatment effect HDF on the primary outcome was +538 [95% confidence interval (CI) −330 to 1407] steps/24 h after dialysis compared with HD, and was not statistically significant. Despite a lack of statistical significance, the observed size of the treatment effect was modest and driven by steps taken between 1.5 and 24.0 h after dialysis, in particular between 20 and 24 h (+197 steps; 95% CI −95 to 488).

Conclusions

HDF did not have a statistically significant treatment effect on PA 24 h following dialysis, albeit effect sizes may be clinically meaningful and deserve further investigation.

Higher number of steps and breaks during sedentary behaviour are associated with better lipid profiles

BACKGROUND

Physical activity (PA) is known to be associated with lipid profiles and the risk of both cardiovascular diseases and cancer. The aim of this study was to evaluate the association of objectively measured PA, sedentary behaviour (SB), amount of breaks during SB and number of daily steps with serum lipids in a healthy, Finnish, middle-aged, female population.

METHODS

The participants (571) were recruited at mammography screening, target group was women aged 50-60 years. A measurement of PA was done with accelerometer, blood lipid profile was assessed, and questionnaires of participants characteristics were sent to participants.

RESULTS

The participants with the highest number of daily breaks during SB (≥ 41) had the highest mean concentration of HDL-cholesterol (high density lipoprotein cholesterol, HDL-c) (1.9 mmol/l, standard deviation (SD) 0.4) and the lowest mean concentration of triglycerides (1.0 mmol/l, SD 0.5). HDL-c level was 0.16 mmol/l higher (p < 0.001) in the group with 28-40.9 breaks/day and 0.25 mmol/l higher (p < 0.001) among participants with ≥41 breaks/day than in the group with the fewest breaks during SB (< 28). Those with the most daily steps (≥ 9100) had the highest mean HDL-c level (1.9 mmol/l). HDL-c level was 0.16 mmol/l higher (p < 0.001) among the participants with 5600-9099 steps/day and 0.26 mmol/l higher (p < 0.001) among participants with ≥9100 steps/day than those with the fewest steps (< 5600). The number of daily steps was inversely associated with the triglyceride concentration. From wake-time, participants spent 60% in SB, 18% standing, 14% in light PA, and 9% in moderate-to-vigorous PA (MVPA). PA was associated with serum total cholesterol (TC), HDL-c and triglyceride levels. The mean HDL-c level was the highest in the lowest quartile of SB and in the highest quartile of MVPA.

CONCLUSIONS

To our knowledge, this is the first study showing a high number of objectively measured breaks during SB is associated with a favourable effect on the level of serum lipids, which may later translate into cardiovascular health among middle-aged women.

TRIAL REGISTRATION

This study was registered and approved by the Regional Ethics Committee of Tampere University Hospital in Finland (approval code R15137 ).

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)

Design and methodology of the impact of HemoDiaFIlTration on physical activity and self-reported outcomes: a randomized controlled trial (HDFIT trial) in Brazil

BACKGROUND

End stage renal disease (ESRD) patients require a renal replacement therapy (RRT) to filter accumulated toxins and remove excess water, which are associated with impaired physical function. Hemodialysis (HD) removes middle-molecular weight (MMW) toxins less efficiently compared to hemodiafiltration (HDF); we hypothesized HDF may improve physical function. We detailed the design and methodology of the HDFIT protocol that is testing whether changing from HD to HDF effects physical activity levels and various outcomes.

METHODS

HDFIT is a prospective, multi-center, unblinded, randomized control trial (RCT) investigating the impact of dialysis modality (HDF verses HD) on objectively measured physical activity levels, self-reported quality of life, and clinical/non-clinical outcomes. Clinically stable patients with HD vintage of 3 to 24 months without any severe limitation ambulation were recruited from sites throughout southern Brazil. Eligible patients were randomized in a 1:1 ratio to either: 1) be treated with high volume online HDF for 6 months, or 2) continue being treated with high-flux HD. This study includes run-in and randomization visits (baseline), 3- and 6-month study visits during the interventional period, and a 12-month observational follow up. The primary outcome is the difference in the change in steps per 24 h on dialysis days from baseline to the 6-month follow up in patients treated with HDF versus HD. Physical activity is being measured over one week at study visits with the ActiGraph ( www.actigraphcorp.com ). For assessment of peridialytic differences during the dialysis recovery period, we will analyze granular physical activity levels based on the initiation time of HD on dialysis days, or concurrent times on non-dialysis days and the long interdialytic day.

DISCUSSION

In this manuscript, we provide detailed information about the HDFIT study design and methodology. This trial will provide novel insights into peridialytic profiles of physical activity and various self-reported, clinical and laboratory outcomes in ESRD patients treated by high volume online HDF versus high-flux HD. Ultimately, this investigation will elucidate whether HDF is associated with patients having better vitality and quality of life, and less negative outcomes as compared to HD.

TRIAL REGISTRATION

Registered on ClinicalTrials.gov on 20 April 2016 ( NCT02787161 ).

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

BACKGROUND/AIMS

Neighborhood walkability is associated with indicators of health in the general population. We explored the association between neighborhood walkability and daily steps in hemodialysis (HD) patients.

METHODS

We measured daily steps over 5 weeks using Fitbit Flex (Fitbit, San Francisco, CA, USA) and retrieved Walk Score® (WS) data by patient's home ZIP code (www.walkscore.com; 0 = poorest walkability; 100 = greatest walkability).

RESULTS

HD patients took a mean of 6,393 ± 3,550 steps/day (n = 46). Median WS of the neighborhood where they resided was 28. Patients in an above-median WS (n = 27) neighborhood took significantly more daily steps compared to those (n = 19) in a below-median WS neighborhood (7,514 ± 3,900 vs. 4,800 ± 2,228 steps/day; p < 0.001, t test). Daily steps and WS were directly correlated (R = 0.425; p = 0.0032, parametric test; R = 0.359, p = 0.0143, non-parametric test).

CONCLUSION

This is the first study conducted among HD patients to indicate a direct relationship between neighborhood walkability and the actual steps taken. These results should be considered when designing initiatives to increase and improvise exercise routines in HD populations.

Meeting Recommended Levels of Physical Activity in Relation to Preventive Health Behavior and Health Status Among Adults

Objectives

The purpose of this study was to examine the relationship of meeting the recommended levels of physical activity (PA) with health status and preventive health behavior in adults.

Methods

A total of 5630 adults 18 years of age or older were included in this study. PA was assessed using a series of questions that categorized activities based on their metabolic equivalent values and then categorized individuals based on the reported frequency and duration of such activities. Participants reporting 150 minutes or more of moderate-intensity PA per week were considered to have met the PA guidelines. Multiple logistic regression was used to model the relationships between meeting PA guidelines and health status and preventive health behavior, while controlling for confounding variables.

Results

Overall, 53.9% (95% confidence interval [CI], 51.9 to 55.9%) of adults reported meeting the recommended levels of PA. Among adults with good general health, 56.9% (95% CI, 54.7 to 59.1%) reported meeting the recommended levels of PA versus 43.1% (95% CI, 40.9 to 45.3%) who did not. Adults who met the PA guidelines were significantly more likely not to report high cholesterol, diabetes, chronic obstructive pulmonary disease, arthritis, asthma, depression, or overweight. Furthermore, adults meeting the PA guidelines were significantly more likely to report having health insurance, consuming fruits daily, consuming vegetables daily, and not being a current cigarette smoker.

Conclusions

In this study, we found meeting the current guidelines for PA to have a protective relationship with both health status and health behavior in adults. Health promotion programs should focus on strategies that help individuals meet the current guidelines of at least 150 minutes per week of moderate-intensity PA.

Changes in physical activity and risk of all-cause mortality in patients on maintence hemodialysis: a retrospective cohort study

Background

A previous cohort study indicated a significant association of lower baseline level of physical activity in hemodialysis patients with elevated risks of mortality. However, there have been no reports regarding the association between changes in physical activity over time and mortality in hemodialysis patients. This study was performed to examine the prognostic significance of physical activity changes in hemodialysis patients.

Methods

This retrospective cohort study was performed in 192 hemodialysis patients with a 7-year follow-up. The average number of steps taken per non-dialysis day was used as a measure of physical activity. Forty (20.8%) patients had died during the follow-up period. The percentage change in physical activity between baseline and 12 months was determined, and patients were divided into three categories according to changes in physical activity. A decrease or increase in physical activity > 30% was defined as becoming less or more active, respectively, while decrease or increase in physical activity < 30% were classified as stable.

Results

Forty seven (24.5%), 51 (26.6%), and 94 (49.0%) patients were classified as becoming less active, becoming more active, and stable, respectively. The hazard ratio on multivariate analysis in patients with decreased physical activity was 3.68 (95% confidence interval, 1.55–8.78; P < 0.01) compared to those with increased physical activity.

Conclusions

Reductions in physical activity were significantly associated with poor prognosis independent of not only patient characteristics but also baseline physical activity. Therefore, improved prognosis in hemodialysis patients requires means of preventing a decline in physical activity over time.

Clinical Characteristics of Patients on Hemodialysis With Peripheral Arterial Disease

Patients on hemodialysis (HD; n = 210) were examined for peripheral arterial disease (PAD) using ankle-brachial index (ABI) and toe-brachial index (TBI). The prevalence of PAD was 38.1%. Among patients with PAD, 87.5% were newly diagnosed with PAD, 42.5% were diagnosed with TBI <0.6 despite ABI ≥ 0.9, and 68.7% had no lower limb symptoms. In patients with PAD, the prevalence rate of cerebrovascular disease was 36.3%, coronary artery disease was 42.5%, spinal stenosis was 33.2%, and vertebral fracture 15.0% and was significantly higher than those of the non-PAD patients. Low high-density lipoprotein cholesterol was the most important biomarker among patients with PAD. PAD has been underdiagnosed and untreated in patients on HD because most patients do not have symptoms that could be due to diabetic neuropathy or have insufficient daily activity to experience exertional leg symptoms. Screening for PAD using the ABI and TBI increased diagnostic efficiency in patients on HD and may lead to effective early treatments, including pharmacotherapy, revascularization therapy, and exercise rehabilitation to avoid the worst possible scenario such as lower limb amputation, cardiovascular event, and death.

Relationship between lower extremity muscle strength and all-cause mortality in Japanese patients undergoing dialysis

BACKGROUND

Skeletal muscle wasting is common and insidious in patients who are undergoing hemodialysis. However, the association between lower extremity muscle strength and all-cause mortality remains unclear in this population.

OBJECTIVE

The purpose of this study was to investigate the prognostic significance of lower extremity muscle strength on 7-year survival in a cohort of patients who were clinically stable and undergoing hemodialysis.

DESIGN

A prospective cohort study was conducted.

METHODS

A total of 190 Japanese outpatients who were undergoing maintenance hemodialysis 3 times per week at a hemodialysis center were followed for up to 7 years. Lower extremity muscle strength was evaluated using a handheld dynamometer at the time of patient enrollment in the study. Muscle strength data were divided by dry weight and expressed as a percentage. A Cox proportional hazards regression model was used to assess the contribution of lower extremity muscle strength to all-cause mortality.

RESULTS

The median age (25th and 75th percentiles) of this study population was 64 years (57 and 72 years), 53.2% of the patients were women, and the time on hemodialysis was 39.0 months (15.9 and 110.5 months) at baseline. During a median follow-up of 36.0 months, there were 30 deaths. With a multivariate Cox model, the hazard ratio in the group with a knee extensor strength of <40% was 2.73 (95% confidence interval=1.14-6.52) compared with that in the ≥40% group.

LIMITATIONS

This was a small-scale observational study, and the mechanisms underlying the higher mortality risk in patients with poor muscle strength undergoing hemodialysis than in other patients undergoing hemodialysis remain to be elucidated.

CONCLUSIONS

Decreased lower extremity muscle strength was strongly associated with increased mortality risk in patients undergoing hemodialysis.