Daily step count and all-cause mortality in a sample of Japanese elderly people: a cohort study

Daily steps and all-cause mortality: An umbrella review and meta-analysis

OBJECTIVE

This study aimed to describe the variability in estimates of the association of daily steps and all-cause mortality in systematic reviews with meta-analyses, to identify the factors potentially responsible for it, and to provide an updated estimate.

METHODS

Five databases were systematically searched up to May 2024 to identify systematic reviews with meta-analyses and prospective cohort studies. A qualitative synthesis of previous reviews and an updated meta-analysis of cohort studies were performed. Pooled hazard ratios (HRs) with their 95% confidence intervals (CIs) were calculated using a random-effects model.

RESULTS

Eleven systematic reviews with meta-analyses and 14 cohort studies were included, revealing considerable variability in result presentation. Our updated meta-analysis showed a nonlinear association, indicating a lower risk of all-cause mortality with increased daily steps, with a protective threshold at 3143 steps/day, and a pooled HR of 0.91 (95% CI: 0.87, 0.95) per 1000 steps/day increment. Physical activity categories consistently indicated progressively reduced mortality risk, with the highly active category (>12,500 steps/day) exhibiting the lowest risk (0.35 (95% CI: 0.29, 0.42)).

CONCLUSION

Systematic reviews and meta-analyses showed considerable variability in effect estimates due to different methods of quantifying exposure. Despite it, our study underscores the importance of increased daily steps in reducing all-cause mortality, with a minimum protective dose of 3000 steps/day, although the optimal dose differed according to age and sex. It is recommended that future studies categorise daily steps by physical activity category, perform dose-response analyses, and use increments of 1000 steps/day.

Daily Step Count and its Association with Arterial Stiffness Parameters in Older Adults

BACKGROUND

Daily step count is a simple parameter for assessing physical activity. However, the potential advantages of setting daily step goals below the traditional 10,000-step threshold remain unclear. The cross-sectional study aimed to determine the relationship between daily step counts and arterial stiffness outcomes in older individuals.

METHODS

Forty-eight older adults recorded their daily step counts over a 7-day period using a pedometer. The participants were classified into two groups based on their daily step count: Group 1 (n = 28) consisted of individuals taking fewer than 5000 steps per day, while Group 2 (n = 20) included those who recorded 5,000 to 9,999 steps per day. To evaluate arterial stiffness parameters, we measured pulse wave velocity (PWV), cardio-ankle vascular index (CAVI), and ankle-brachial index (ABI). Hemodynamic and biochemical parameters were also determined.

RESULTS

Participants who accumulated fewer daily steps exhibited higher PWV compared to each group. An inverse association was observed between average steps per day and PWV. However, no significant differences were found between daily step counts and CAVI or ABI.

CONCLUSION

Conclusions: As individuals increase their daily step count, they may experience a reduction in arterial stiffness. Consequently, the assessment of daily steps has benefits for enhancing vascular health and overall well-being among older individuals.

The association between daily step count and all-cause and cardiovascular mortality: a meta-analysis

AIMS

There is good evidence showing that inactivity and walking minimal steps/day increase the risk of cardiovascular (CV) disease and general ill-health. The optimal number of steps and their role in health is, however, still unclear. Therefore, in this meta-analysis, we aimed to evaluate the relationship between step count and all-cause mortality and CV mortality.

METHODS AND RESULTS

We systematically searched relevant electronic databases from inception until 12 June 2022. The main endpoints were all-cause mortality and CV mortality. An inverse-variance weighted random-effects model was used to calculate the number of steps/day and mortality. Seventeen cohort studies with a total of 226 889 participants (generally healthy or patients at CV risk) with a median follow-up 7.1 years were included in the meta-analysis. A 1000-step increment was associated with a 15% decreased risk of all-cause mortality [hazard ratio (HR) 0.85; 95% confidence interval (CI) 0.81-0.91; P < 0.001], while a 500-step increment was associated with a 7% decrease in CV mortality (HR 0.93; 95% CI 0.91-0.95; P < 0.001). Compared with the reference quartile with median steps/day 3867 (2500-6675), the Quartile 1 (Q1, median steps: 5537), Quartile 2 (Q2, median steps 7370), and Quartile 3 (Q3, median steps 11 529) were associated with lower risk for all-cause mortality (48, 55, and 67%, respectively; P < 0.05, for all). Similarly, compared with the lowest quartile of steps/day used as reference [median steps 2337, interquartile range 1596-4000), higher quartiles of steps/day (Q1 = 3982, Q2 = 6661, and Q3 = 10 413) were linearly associated with a reduced risk of CV mortality (16, 49, and 77%; P < 0.05, for all). Using a restricted cubic splines model, we observed a nonlinear dose-response association between step count and all-cause and CV mortality (Pnonlineraly < 0.001, for both) with a progressively lower risk of mortality with an increased step count.

CONCLUSION

This meta-analysis demonstrates a significant inverse association between daily step count and all-cause mortality and CV mortality with more the better over the cut-off point of 3867 steps/day for all-cause mortality and only 2337 steps for CV mortality.

A metabolomic signature of decelerated physiological aging in human plasma

The degenerative processes that occur during aging increase the risk of disease and impaired health. Meanwhile, interventions that target aging to promote healthy longevity are gaining interest, both academically and in the public. While nutritional and physical interventions exist, efficacy is often difficult to determine. It is therefore imperative that an aging score measuring the biological aging process is available to the wider public. However, simple, interpret, and accessible biological aging scores are lacking. Here, we developed PhysiAge, a physiological aging score based on five accessible parameters that have influence on or reflect the aging process: (1) average daily step count, (2) blood glucose, (3) systolic blood pressure, (4) sex, and (5) age. Here, we found that compared to calendar age alone, PhysiAge better predicts mortality, as well as established muscle aging markers such as decrease in NAD+ levels, increase in oxidative stress, and decline in physical functioning. In order to demonstrate the usefulness of PhysiAge in identifying relevant factors associated with decelerated aging, we calculated PhysiAges for a cohort of aged individuals and obtained mass spectrometry-based blood plasma metabolomic profiles for each individual. Here, we identified a metabolic signature of decelerated aging, which included components of the TCA cycle, including malate, citrate, and isocitrate. Higher abundance of these metabolites was associated with decelerated aging, in line with supplementation studies in model organisms. PhysiAge represents an accessible way for people to track and intervene in their aging trajectories, and identifies a metabolic signature of decelerated aging in human blood plasma, which can be further studied for its causal involvement in human aging.

Relationship of Daily Step Counts to All-Cause Mortality and Cardiovascular Events

BACKGROUND

The minimal and optimal daily step counts for health improvements remain unclear.

OBJECTIVES

A meta-analysis was performed to quantify dose-response associations of objectively measured step count metrics in the general population.

METHODS

Electronic databases were searched from inception to October 2022. Primary outcomes included all-cause mortality and incident cardiovascular disease (CVD). Study results were analyzed using generalized least squares and random-effects models.

RESULTS

In total, 111,309 individuals from 12 studies were included. Significant risk reductions were observed at 2,517 steps/d for all-cause mortality (adjusted HR [aHR]: 0.92; 95% CI: 0.84-0.999) and 2,735 steps/d for incident CVD (aHR: 0.89; 95% CI: 0.79-0.999) compared with 2,000 steps/d (reference). Additional steps resulted in nonlinear risk reductions of all-cause mortality and incident CVD with an optimal dose at 8,763 (aHR: 0.40; 95% CI: 0.38-0.43) and 7,126 steps/d (aHR: 0.49; 95% CI: 0.45-0.55), respectively. Increments from a low to an intermediate or a high cadence were independently associated with risk reductions of all-cause mortality. Sex did not influence the dose-response associations, but after stratification for assessment device and wear location, pronounced risk reductions were observed for hip-worn accelerometers compared with pedometers and wrist-worn accelerometers.

CONCLUSIONS

As few as about 2,600 and about 2,800 steps/d yield significant mortality and CVD benefits, with progressive risk reductions up to about 8,800 and about 7,200 steps/d, respectively. Additional mortality benefits were found at a moderate to high vs a low step cadence. These findings can extend contemporary physical activity prescriptions given the easy-to-understand concept of step count. (Dose-Response Relationship Between Daily Step Count and Health Outcomes: A Systematic Review and Meta-Analyses; CRD42021244747).

The relationship between mortality and daily number of steps in type 2 diabetes

BACKGROUND

Physical activity (PA) is an established modifiable factor for the prevention of cardiovascular disease. Our objective was to assess the association of PA with mortality rates in a national sample of patients with diabetes.

METHODS

We analyzed a nationally representative sample from The National Health and Nutrition Examination Survey (NHANES, periods 2003-2004 and 2005-2006) that used PA Monitors. Individuals were matched for BMI, number of steps/per day and age. Three groups were created: subjects with less than 5000/steps per day (low), 5000-7500/steps per day (moderate) and more than 7500/steps per day (high levels of physical activity). All-cause mortality was ascertained through December 2015.

RESULTS

A sample of 3072 individuals (1018 with diabetes) was analyzed. Patients with diabetes had 30% increased risk of mortality of all causes (RR: 1.298, 95% CI [1.162-1.451], P<0.001), higher levels of PA (>7500 steps/day) provided similar relative risk for subjects with diabetes compared to their controls (RR:1.256 [95% CI 0.910-1.732]). In a Poisson model adjusted for sex, history of previous cardiovascular event or cancer, ethnicity, Hb1ac, SBP, and total cholesterol to HDL ratio, patients with diabetes and moderate or high PA had an associated 44% to 80% lower risk of all-cause mortality compared to those with low PA.

CONCLUSIONS

The subgroup of patients with diabetes and high PA had no excess of mortality compared to the general population. PA can reduce the gap for all-cause mortality, used as an index of cardiovascular fitness and a clinical tool for the assessment of mortality risk.

How to Keep the Balance between Red and Processed Meat Intake and Physical Activity Regarding Mortality: A Dose-Response Meta-Analysis

BACKGROUND

Non-communicable diseases have become a major threat to public health, with cardiovascular diseases (CVDs) and cancer being the top two causes of death each year.

OBJECTIVE

Our objective is to evaluate the balanced association between the effect of red and processed meat intake on the risk of death and the effect of physical activity on the risk of mortality, where the risk of death includes all causes, CVDs, and cancers.

METHODS

We searched electronic databases, including PubMed, ISI Web of Science, Embase, and the Cochrane Library, for prospective studies reporting risk estimates for the association between the intake of red and processed meat, walking, and muscle-strengthening activity (MSA) and the risk of mortality from all causes, CVDs, and cancer. We extracted fully adjusted effect estimates from original studies and performed a summary analysis using the fixed and random-effect models.

RESULTS

A conventional meta-analysis showed that red meat and processed meat were positively associated with the risk of mortality, and daily steps and MSA were negatively associated with the risk of death. Further analysis of the dose-response relationship showed that a risk reduction (20%) from 39.5 min/week of MSA or 4100 steps/d was equivalent to an increased risk of all-cause mortality from a daily intake of 103.4 g/d of red meat or 50 g/d of processed meat. The risk was further decreased as the number of steps per day increased, but the risk reversed when the MSA exceeded the threshold (39.5 min/week).

CONCLUSIONS

Adherence to physical activity is an effective way to reduce the risk of mortality due to meat intake. However, the total intake of red meat and processed meat should be controlled, especially the latter. Walking is recommended as the main daily physical activity of choice, while MSAs are preferred when time is limited, but it should be noted that longer MSAs do not provide additional benefits.

Ambulatory Activity and Risk of Premature Mortality Among Young and Middle-aged American Indian Individuals

Importance

To our knowledge, no published studies have investigated the association of ambulatory activity with risk of death among young and middle-aged American Indian individuals. The burden of chronic disease and risk of premature death is higher among American Indian individuals than among the general US population, so better understanding of the association of ambulatory activity with risk of death is needed to inform public health messaging in tribal communities.

Objective

To examine the association of objectively measured ambulatory activity (ie, steps per day) with risk of death among young and middle-aged American Indian individuals.

Design, Setting, and Participants

The ongoing longitudinal Strong Heart Family Study (SHFS) is being conducted with participants aged 14 to 65 years in 12 rural American Indian communities in Arizona, North Dakota, South Dakota, and Oklahoma and includes up to 20 years of follow-up (February 26, 2001, to December 31, 2020). This cohort study included SHFS participants who had available pedometer data at baseline. Data analysis was performed on June 9, 2022.

Exposures

Objectively measured ambulatory activity at baseline.

Main Outcomes and Measures

Outcomes of interest were total and cardiovascular-related mortality. Mixed-effects Cox proportional hazards regression was used to estimate hazard ratios for risk of death, with entry at the time of the pedometer assessment and time at risk until death or the latest adjudicated date of follow-up.

Results

A total of 2204 participants were included in this study. Their mean (SD) age was 41.0 (16.8) years; 1321 (59.9%) were female and 883 (40.1%) were male. During a mean follow-up of 17.0 years (range, 0-19.9 years), 449 deaths occurred. Compared with participants in the lowest quartile of steps per day (<3126 steps), individuals in the upper 3 quartiles of steps per day had lower risk of mortality, with hazard ratios of0.72 (95% CI, 0.54-0.95) for the first quartile, 0.66 (95% CI, 0.47-0.93) for the second quartile, and 0.65 (95% CI, 0.44-0.95) for the third quartile after adjustment for age, sex, study site, education, smoking status, alcohol use, diet quality, body mass index, systolic blood pressure, prevalent diabetes, prevalent cardiovascular disease, biomarker levels (fibrinogen, low-density lipoprotein cholesterol, and triglycerides), medication use (hypertensive or lipid-lowering agents), and self-reported health status. The magnitude of the hazard ratios was similar for cardiovascular mortality.

Conclusions and Relevance

In this cohort study, American Indian individuals who took at least 3126 steps/d had a lower risk of death compared with participants who accumulated fewer steps per day. These findings suggest that step counters are an inexpensive tool that offers an opportunity to encourage activity and improve long-term health outcomes.

COVID-19 Containment Measures-a Step Back for Walking Mobility? A 2-Year, 60-Country Analysis of the Apple Mobility Data

BACKGROUND

COVID-19 containment measures curb viral spread but may hamper walking mobility. As a low daily step count is associated with increased noncommunicable diseases and mortality, assessing the relationship between pandemic responses and walking mobility can help trade-off public health measures. We investigated the association between containment stringency and walking mobility across 60 countries in the period between January 21, 2020 and January 21, 2022 and modeled how this could impact mortality hazard.

METHODS

Walking mobility was measured through the Apple Mobility Trends, containment measures stringency index through the Oxford COVID-19 response tracker (which considers local policies on closures, healthcare, and economy), and meteorological data by National Oceanic and Atmospheric Administration weather stations. Walking mobility was regressed over stringency in a mixed-effect model with weather variables as covariates. The impact of stringency on all-cause mortality due to reduced mobility was modeled based on regression results, prepandemic walking mobility, and the association between step count and all-cause mortality hazard.

RESULTS

Across the 60 countries, the average stringency was 55 (9) (mean [SD]) out of 100. Stringency was negatively associated with walking mobility; a log-linear model fitted data better than a linear one, with a regression coefficient for stringency on ln (walking mobility) (95% confidence interval) of  -1.201 × 10-2 (-1.221 × 10-2 to -1.183 × 10-2). Increasing stringency, thus decreasing walking mobility, nonlinearly incremented the modeled all-cause mortality hazard by up to ∼40%.

CONCLUSIONS

In this study, walking mobility was negatively associated with containment measures stringency; the relationship between stringency, mobility, and the subsequent impact on health outcomes may be nonlinear. These findings can help in balancing pandemic containment policies.

Device-Measured Physical Activity and Sedentary Behavior in Relation to Cardiovascular Diseases and All-Cause Mortality: Systematic Review and Meta-Analysis of Prospective Cohort Studies

Introduction

This review synthesized evidence from prospective cohort studies on the association of device-measured physical activity and sedentary behavior with cardiovascular disease and all-cause mortality among adults.

Methods

Five databases were searched from 2000 through April 29, 2020. Study quality was appraised using the NIH Quality Assessment Tool. Pooled hazard ratio and 95% CI were obtained from random-effects meta-analyses. Subgroup analyses by age and sex were conducted for studies on all-cause mortality.

Results

Of 29 articles included in the systematic review, 5 studies on cardiovascular disease mortality and 15 studies on all-cause mortality were included in meta-analyses. Comparing the highest with the lowest exposure categories, the pooled hazard ratios (95% CIs) for cardiovascular disease mortality were 0.29 (CI=0.18, 0.47) for total physical activity, 0.37 (CI=0.25, 0.55) for moderate-to-vigorous physical activity, 0.62 (0.41-0.93) for light physical activity, and 1.89 (CI=1.09, 3.29) for sedentary behavior. The pooled hazard ratios (95% CIs) for all-cause mortality were 0.42 (CI=0.34, 0.53) for total physical activity, 0.43 (CI=0.35, 0.53) for moderate-to-vigorous physical activity, 0.58 (CI=0.43, 0.80) for light physical activity, and 1.58 (CI=1.19, 2.09) for sedentary behavior. The pooled hazard ratio (95% CI) for all-cause mortality was 0.35 (CI=0.29, 0.42) for steps per day, but the studies available for analysis were conducted in older adults. The results of subgroup analyses were consistent with the main results.

Discussion

Rapidly accumulating evidence suggests that more physical activity and less sedentary behavior are associated with a lower risk of cardiovascular disease and all-cause mortality. Similar beneficial relationships were found for step counts and all-cause mortality among older adults. Future studies employing standardized research methodologies and up-to-date data processing approaches are warranted to recommend specific amounts of physical activity and limits to sedentary behavior.

The evolution of human step counts and its association with the risk of chronic disease

Walking - humans' most fundamental form of moderate intensity physical activity - is associated with reduced risks of morbidity and mortality. Evolutionary perspectives have contributed much to understanding the effects of walking and other physical activities on health; however, we know comparatively little about how step counts (steps taken per day) changed over the course of human evolution, potentially affecting how selection operated on physiological responses to moderate intensity physical activity that influence morbidity and mortality. Here, we compare step counts across humans and our closest living relatives, the great apes. Compiling data from epidemiology and comparative physiology, we show how step counts more than tripled during human evolution, potentially linking higher levels of moderate intensity physical activity with reduced morbidity and mortality, and we highlight how recent decreases in step counts are an evolutionary mismatch. We raise the hypothesis that the dose-response relationship between moderate intensity physical activity and health was shifted in humans to require more steps per day to promote extended healthspan and lifespan.

Association of accelerometer-derived step volume and intensity with hospitalizations and mortality in older adults: A prospective cohort study

PURPOSE

This study aimed to examine the associations of accelerometer-derived steps volume and intensity with hospitalizations and all-cause mortality in older adults.

METHODS

This prospective cohort study involved 768 community-dwelling Spanish older adults (78.8 ± 4.9 years, mean ± SD; 53.9% females) from the Toledo Study for Healthy Aging (2012-2017). The number of steps per day and step cadence (steps/min) were derived from a hip-mounted accelerometer worn for at least 4 days at baseline. Participants were followed-up over a mean period of 3.1 years for hospitalization and 5.7 years for all-cause mortality. Cox proportional hazards regression models were used to estimate the individual and joint associations between daily steps and stepping intensity with hospitalizations and all-cause mortality.

RESULTS

Included participants walked 5835 ± 3445 steps/day with an intensity of 7.3 ± 4.1 steps/min. After adjusting for age, sex, body mass index (BMI), education, income, marital status and comorbidities, higher step count (hazard ratio (HR) = 0.95, 95% confidence interval (95%CI: 0.90-1.00, and HR = 0.87, 95%CI: 0.81-0.95 per additional 1000 steps) and higher step intensity (HR = 0.95, 95%CI: 0.91-0.99, and HR = 0.89, 95%CI: 0.84-0.95 per each additional step/min) were associated with fewer hospitalizations and all-cause mortality risk, respectively. Compared to the group having low step volume and intensity, individuals in the group having high step volume and intensity had a lower risk of hospitalization (HR = 0.72, 95%CI: 0.52-0.98) and all-cause mortality (HR = 0.60, 95%CI: 0.37-0.98).

CONCLUSION

Among older adults, both high step volume and step intensity were significantly associated with lower hospitalization and all-cause mortality risk. Increasing step volume and intensity may benefit older people.

Dose-response association between the daily step count and all-cause mortality: A systematic review and meta-analysis

This review aims to investigate the dose-response relationship between the daily step count and all-cause mortality. PubMed, the Cochrane Library, Embase, and Web of Science were searched for all articles of cohort studies investigating the association between the daily step count and all-cause mortality. Cohort research articles were included if they reported mortality with no less than 3 categories of the daily step count, and hazard ratio (HR) with a 95% Confidence Interval (CI) was reported. Dose-response association meta-analysis and subsequent sex subgroup analysis were performed. The final analysis included a total of nine studies. Compared with the low-step count population, the high-step count population had a 62% lower risk of all-cause death (HR = 0.38, 95% CI 0.27-0.49). There was a non-linear dose-response relationship between the daily step count and all-cause mortality. Compared with the least (1895 steps), the first quartile (4000 steps/day) had a 37% lower risk for all causes of death (HR = 0.63, 0.57-0.71), the second quartile (6388 steps/day) had a 60% lower risk for all causes of death (HR = 0.40, 0.32-0.49), the third quartile (9994.3 steps/day) had a 75% lower risk of all-cause death than the first quartile (HR = 0.25, 0.19-0.33).

Accurate Step Count with Generalized and Personalized Deep Learning on Accelerometer Data

Physical activity (PA) is globally recognized as a pillar of general health. Step count, as one measure of PA, is a well known predictor of long-term morbidity and mortality. Despite its popularity in consumer devices, a lack of methodological standards and clinical validation remains a major impediment to step count being accepted as a valid clinical endpoint. Previous works have mainly focused on device-specific step-count algorithms and often employ sensor modalities that may not be widely available. This may limit step-count suitability in clinical scenarios. In this paper, we trained neural network models on publicly available data and tested on an independent cohort using two approaches: generalization and personalization. Specifically, we trained neural networks on accelerometer signals from one device and either directly applied them or adapted them individually to accelerometer data obtained from a separate subject cohort wearing multiple distinct devices. The best models exhibited highly accurate step-count estimates for both the generalization (96-99%) and personalization (98-99%) approaches. The results demonstrate that it is possible to develop device-agnostic, accelerometer-only algorithms that provide highly accurate step counts, positioning step count as a reliable mobility endpoint and a strong candidate for clinical validation.

Association Between Step Count Measured With a Smartphone App (Pain-Note) and Pain Level in Patients With Chronic Pain: Observational Study

Background

Chronic pain is the leading cause of disability, affecting between 20% and 50% of the global population. The key recommended treatment is physical activity, which can be measured in daily life using a pedometer. However, poor adherence to pedometer use can result in incorrect measurements. Furthermore, only a few studies have investigated a possible curvilinear association between physical activity and chronic pain.

Objective

In this study, we developed the Pain-Note smartphone app to collect real-world data on step count, using the smartphone’s built-in pedometer. The aims of our research are (1) to evaluate the association between daily step count and pain level among patients with chronic pain and (2) determine if the association between daily step count and pain level was curvilinear.

Methods

We conducted a cross-sectional study based on step count data collected with the app and on the results of questionnaires, which measured the duration and intensity of pain, the widespread pain index, the symptom severity score, and the insomnia severity scale, including 7 questions for symptoms of depression. We analyzed the association between step count and pain level as a nonlinear relationship using a restricted cubic spline model. A prespecified subgroup analysis was also conducted based on fibromyalgia criteria.

Results

Between June 1, 2018, and June 11, 2020, a total of 6138 records were identified, of which 1273 were analyzed. The mean age of the participants was 38.7 years, 81.9% (1043/1273) were female, and chronic pain was present for more than 5 years in 43.2% (550/1273) of participants. Participants in the third and fourth quartiles for step count (more than 3045 and 5668 steps a day, respectively) showed a significant positive association between higher step count and lower numerical pain rating scale (mean difference –0.43, 95% CI –0.78 to –0.08, P=.02; –0.45; 95% CI –0.8 to –0.1, P=.01, respectively) than those in the first quartile (less than or equal to 1199 steps a day). The restricted cubic spline model for the association between step count and pain scale displayed a steep decline followed by a moderate decrease as the step count increased; the inflection point was 5000 steps. However, this association was not observed among participants who met the fibromyalgia criteria (491/1273), who showed a steep positive increase below 2000 steps. Data were collected between June 1, 2018, and June 11, 2020, and were analyzed on November 18, 2021.

Conclusions

Step count measured with the Pain-Note app showed a nonlinear association with pain level. Although participants with and without fibromyalgia showed a negative correlation between step count and pain level, participants who meet the criteria for fibromyalgia may present a different relationship between walking and pain perception compared to those in the general chronic pain population.

Daily steps and all-cause mortality: a meta-analysis of 15 international cohorts

Background

Although 10 000 steps per day is widely promoted to have health benefits, there is little evidence to support this recommendation. We aimed to determine the association between number of steps per day and stepping rate with all-cause mortality.

Methods

In this meta-analysis, we identified studies investigating the effect of daily step count on all-cause mortality in adults (aged ≥18 years), via a previously published systematic review and expert knowledge of the field. We asked participating study investigators to process their participant-level data following a standardised protocol. The primary outcome was all-cause mortality collected from death certificates and country registries. We analysed the dose–response association of steps per day and stepping rate with all-cause mortality. We did Cox proportional hazards regression analyses using study-specific quartiles of steps per day and calculated hazard ratios (HRs) with inverse-variance weighted random effects models.

Findings

We identified 15 studies, of which seven were published and eight were unpublished, with study start dates between 1999 and 2018. The total sample included 47 471 adults, among whom there were 3013 deaths (10.1 per 1000 participant-years) over a median follow-up of 7.1 years ([IQR 4.3–9.9]; total sum of follow-up across studies was 297 837 person-years). Quartile median steps per day were 3553 for quartile 1, 5801 for quartile 2, 7842 for quartile 3, and 10 901 for quartile 4. Compared with the lowest quartile, the adjusted HR for all-cause mortality was 0.60 (95% CI 0.51–0.71) for quartile 2, 0.55 (0.49–0.62) for quartile 3, and 0.47 (0.39–0.57) for quartile 4. Restricted cubic splines showed progressively decreasing risk of mortality among adults aged 60 years and older with increasing number of steps per day until 6000–8000 steps per day and among adults younger than 60 years until 8000–10 000 steps per day. Adjusting for number of steps per day, comparing quartile 1 with quartile 4, the association between higher stepping rates and mortality was attenuated but remained significant for a peak of 30 min (HR 0.67 [95% CI 0.56–0.83]) and a peak of 60 min (0.67 [0.50–0.90]), but not significant for time (min per day) spent walking at 40 steps per min or faster (1.12 [0.96–1.32]) and 100 steps per min or faster (0.86 [0.58–1.28]).

Interpretation

Taking more steps per day was associated with a progressively lower risk of all-cause mortality, up to a level that varied by age. The findings from this meta-analysis can be used to inform step guidelines for public health promotion of physical activity.

The relationships between step count and all-cause mortality and cardiovascular events: A dose-response meta-analysis

BACKGROUND

A goal of 10,000 steps per day is widely advocated, but there is little evidence to support that goal. Our purpose was to examine the dose-response relationships between step count and all-cause mortality and cardiovascular disease risk.

METHODS

Cochrane Central Register of Controlled Trials, EMBASE, OVID, PubMed, Scopus, and Web of Science databases were systematically searched for studies published before July 9, 2021, that evaluated the association between daily steps and at least 1 outcome.

RESULTS

Sixteen publications (12 related to all-cause mortality, 5 related to cardiovascular disease; and 1 article contained 2 outcomes: both all-cause death and cardiovascular events) were eligible for inclusion in the meta-analysis. There was evidence of a nonlinear dose-response relationship between step count and risk of all-cause mortality or cardiovascular disease (p = 0.002 and p = 0.014 for nonlinearity, respectively). When we restricted the analyses to accelerometer-based studies, the third quartile had a 40.36% lower risk of all-cause mortality and a 35.05% lower risk of cardiovascular event than the first quartile (all-cause mortality: Q1 = 4183 steps/day, Q3 = 8959 steps/day; cardiovascular event: Q1 = 3500 steps/day, Q3 = 9500 steps/day; respectively).

CONCLUSION

Our meta-analysis suggests inverse associations between higher step count and risk of premature death and cardiovascular events in middle-aged and older adults, with nonlinear dose-response patterns.

Daily Step Count and All-Cause Mortality: A Dose-Response Meta-analysis of Prospective Cohort Studies

BACKGROUND

Uncertainty remains about the optimum step count per day for health promotion.

OBJECTIVE

We aimed to investigate the association between step count per day and all-cause mortality risk.

METHODS

PubMed, Scopus, and ISI Web of Science were searched to January 2021 to find prospective cohort studies of the association between device-based step count per day and all-cause mortality risk in the general population. Two reviewers extracted data in duplicate and rated the certainty of evidence using the GRADE approach. Study-specific hazard ratios (HRs) were pooled using a random-effects model.

RESULTS

Seven prospective cohort studies with 175,370 person-years and 2310 cases of all-cause mortality were included. The HR for each 1000 steps per day was 0.88 (95% CI 0.83-0.93; I² = 79%, n = 7) in the overall analysis, 0.87 (95% CI 0.78-0.97; I² = 59%, n = 3) in adults older than 70 years, and 0.92 (95% CI 0.89-0.95; I² = 37%, n = 2) in studies controlled for step intensity. Dose-response meta-analysis indicated a strong inverse association, wherein the risk decreased linearly from 2700 to17,000 steps per day. The HR for 10,000 steps per day was 0.44 (95% CI 0.31-0.63). The certainty of evidence was rated strong due to upgrades for large effect size and dose-response gradient.

CONCLUSIONS

Even a modest increase in steps per day may be associated with a lower risk of death. These results can be used to develop simple, efficient and easy-to-understand public health messages.

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.

Accelerometer-Measured Daily Step Counts and Adiposity Indicators among Latin American Adults: A Multi-Country Study

The aim of the present study was to examine the sex-related associations between accelerometer-measured daily step counts and adiposity indicators in adults from eight Latin American countries. We analyzed data from 2524 adults (aged 18–65 years) from the Latin American Study of Nutrition and Health. Device-measured daily step counts were measured by accelerometers (ActiGraph GT3X). The outcomes were body mass index (BMI; (kg/m2), waist and neck circumference (in cm). Overall, the mean of daily steps counts, BMI, waist and neck circumference were 10699.8, 27.3, 89.6, and 35.8. Weak and negative associations were observed between daily steps counts and BMI (r = −0.17; p < 0.05) and waist circumference (r = −0.16; p < 0.05); however, step counts was not associated with neck circumference. Daily steps counts were negatively associated with BMI (β: −0.054; 95%CI: −0.077; −0.012) and waist circumference (−0.098; −0.165; −0.030) independently of age and socioeconomic level. In men, there were significant negative associations between daily steps counts with BMI (−0.075; −0.119; −0.031) and waist circumference (−0.140; −0.233; −0.048), and in women, there was no significant association with either of the body composition indicators. The findings from this study need to be examined in prospective settings that use device-measured from Latin America.

Objectively measured physical activity and all cause mortality: A systematic review and meta-analysis

Current physical activity recommendations have been based on evidence from systematic reviews of questionnaire-based data. Questionnaire-based physical activity data are subject to both random and non-random error. If the estimated association between physical activity and health outcomes was different when a more accurate, objective measure was used, this would have important health policy implications for physical activity. We conducted a systematic review and meta-analysis of published cohort studies that investigated the association between an objective measure of physical activity and all cause mortality. We searched PubMed, Scopus, Embase, Cochrane library, and SPORTDiscus for prospective cohort studies that examined the association between objectively measured (accelerometer, pedometer, or doubly labeled water method) physical activity and mortality in adults aged≥18 years, of either sex. Summary hazard ratios and 95% confidence interval [CI]s were computed using random-effects models. Thirty-three articles from 15 cohort studies were identified that together ascertained 3903 deaths. The mean years of follow-up ranged from 2.3-14.2 years. Individuals in the highest category of light, moderate-to-vigorous, and total physical activity had 40% (95%CI 20% to 55%), 56% (95%CI 41% to 67%), and 67% (95%CI 57% to 75%), respectively, lower risk for mortality compared to individuals in the lowest category of light, moderate-to-vigorous, and total physical activity. The summary hazard ratio for objectively measured physical activity and all cause mortality is lower than previously estimated from questionnaire based studies. Current recommendations for physical activity that are based on subjective measurement may underestimate the true reduction in mortality risk associated with physical activity.

Can a multi-level intervention approach, combining behavioural disciplines, novel technology and incentives increase physical activity at population-level?

BACKGROUND

Despite a global call for action and growing burden of non-communicable diseases (NCD) associated with physical inactivity, effective interventions to increase community-wide physical activity (PA) remain few. NCDs accounted for 80% of Singapore's disease burden (2015) and yet 40% of Singaporeans did not meet minimum recommended weekly PA despite evidence of the benefits to cardiorespiratory health, diabetes and cancer prevention.

METHODS

A large-scale public health intervention was initiated in 2015 to increase population-level PA through incidental daily walking. Intervention components included fitness trackers, redeemable rewards and gamification, implemented in a mutually-reinforcing manner within an eco-system supportive of PA and informed by real-time data analytics. Mean daily step count at baseline and post-intervention were compared across periods, and the influence of participant sub-groups characteristics on overall results, using significance tests. Standards for Reporting on Implementation Studies (StaRI) were adhered to.

RESULTS

Intervention reach increased fourfold from 129,677 participants in wave 1 (2015-16) to 690,233 in wave 3 (2017-18) amounting to a total of 1,184,410 Step Challenge participations. Mean days of fitness tracker use increased from 2.4 to 5.0 days/week among participants completing the Challenge in wave 1 and from 5.3 to 6.0 days/week in wave 3. The mean number of daily steps between pre-Challenge and Challenge periods increased by 4163 (sd=1360; p< 0.001) in wave 1, by 2242 (sd=334; p< 0.001) in wave 2 and by 1645 steps/day (sd=54; p< 0.001) in wave 3. Mean daily step increases between wave 1 and 3 also suggest that incidental PA was maintained, a finding supported by a 2017 national population survey showing that incidental PA among adults increased from 5% in 2010 to 14% in 2017 while moderate-intensity PA increased from 5 to 10% over the same period.

CONCLUSION

Population-level PA was effectively increased through multi-level interventions integrating technology, behavioural economics, gamification, marketing, communications and community linkages within a supportive context- and climate-appropriate environment. Responsive data analytics were instrumental to strengthen implementation by tailoring modalities that maximise effectiveness at population-level. Further analyses are needed to explore potential barriers, challenges or unmet needs in sub-groups with lower uptake to tailor future interventions for greater reach and impact.

Older Adults' Daily Step Counts and Time in Sedentary Behavior and Different Intensities of Physical Activity

Background

Daily step count is the simplest measure of physical activity. However, little is known about how daily step count related to time spent in different intensities of physical activity (PA) and sedentary behavior (SB).

Methods

These cross-sectional data were derived from 450 older Japanese adults (56.7% men; mean age, 74.3 years) who were randomly selected from three communities and responded a survey. Daily step count and time spent in moderate-to-vigorous PA (MVPA), light-intensity PA (LPA), and SB were measured using a validated wearable technology (HJA-350IT). Associations of daily step count with time spent in measured behaviors were examined using linear regression models with isometric log-ratio transformations of time-use composition, adjusting for gender, age, and residential area.

Results

Participants averaged 5,412 (standard deviation, 2,878) steps/d and accumulated MVPA, LPA, and SB corresponding to 4.0%, 34.8%, and 61.2% of daily waking time, respectively. Daily step count significantly increased with increase in time spent in MVPA relative to other behaviors (ie, LPA and SB) and in the ratio of LPA to SB after allowing for MVPA. After stratification, daily step count was significantly related to the ratio of LPA to SB in those taking <5,000 steps/d, but not in those taking 5,000–7,499 and ≥7,500 steps/d.

Conclusions

Higher daily step count can be an indicator of not only larger relative contribution of time spent in MVPA, but also higher ratio between LPA and SB, particularly among those who are the least physically active.

mHealth app using machine learning to increase physical activity in diabetes and depression: clinical trial protocol for the DIAMANTE Study

INTRODUCTION

Depression and diabetes are highly disabling diseases with a high prevalence and high rate of comorbidity, particularly in low-income ethnic minority patients. Though comorbidity increases the risk of adverse outcomes and mortality, most clinical interventions target these diseases separately. Increasing physical activity might be effective to simultaneously lower depressive symptoms and improve glycaemic control. Self-management apps are a cost-effective, scalable and easy access treatment to increase physical activity. However, cutting-edge technological applications often do not reach vulnerable populations and are not tailored to an individual's behaviour and characteristics. Tailoring of interventions using machine learning methods likely increases the effectiveness of the intervention.

METHODS AND ANALYSIS

In a three-arm randomised controlled trial, we will examine the effect of a text-messaging smartphone application to encourage physical activity in low-income ethnic minority patients with comorbid diabetes and depression. The adaptive intervention group receives messages chosen from different messaging banks by a reinforcement learning algorithm. The uniform random intervention group receives the same messages, but chosen from the messaging banks with equal probabilities. The control group receives a weekly mood message. We aim to recruit 276 adults from primary care clinics aged 18-75 years who have been diagnosed with current diabetes and show elevated depressive symptoms (Patient Health Questionnaire depression scale-8 (PHQ-8) >5). We will compare passively collected daily step counts, self-report PHQ-8 and most recent haemoglobin A1c from medical records at baseline and at intervention completion at 6-month follow-up.

ETHICS AND DISSEMINATION

The Institutional Review Board at the University of California San Francisco approved this study (IRB: 17-22608). We plan to submit manuscripts describing our user-designed methods and testing of the adaptive learning algorithm and will submit the results of the trial for publication in peer-reviewed journals and presentations at (inter)-national scientific meetings.

TRIAL REGISTRATION NUMBER

NCT03490253; pre-results.

Instrumented measures of sedentary behaviour and physical activity are associated with mortality in community-dwelling older adults: A systematic review, meta-analysis and meta-regression analysis

BACKGROUND

Sedentary behaviour (SB) and physical activity (PA) can be objectively assessed with inertial sensors to describe bodily movement. Higher SB and lower PA is associated with higher chronological age and negative health outcomes. This study aimed to quantify the association between instrumented measures of SB (i-SB) and PA (i-PA) and mortality in community-dwelling older adults, to subsequently compare the quantitative effect sizes and to determine the dose-response relationships.

METHODS

An electronic search in six databases from inception to 27th of June 2019 was conducted. All articles reporting on i-SB or i-PA and mortality in community-dwelling older adults aged 60 years or older were considered eligible. A meta-analysis was conducted for the association between i-SB and i-PA and mortality expressed in Hazard Ratios (HR) and 95% Confidence Intervals (95% CI). A meta-regression analysis was performed to determine the dose-response relationship between i-SB and steps per day and mortality.

RESULTS

Twelve prospective articles representing eleven cohorts, reporting data of 38,141 participants were included. In total 2502 (6.4%) participants died during follow-up (2.0 to 9.8 years). Comparing the most sedentary with the least sedentary groups of participants resulted in a pooled HR of 2.44 (95% CI 1.82-3.25). Comparing the least active with the most active groups of participants resulted in a pooled HR of 1.93 (95% CI 1.39-2.69); 2.66 (95% CI 2.11-3.35); 3.43 (95% CI 2.61-4.52), and 3.09 (95% CI 2.33-4.11) for light, moderate-to-vigorous-, total PA and steps per day, respectively. Meta-regression analyses showed clear dose-response relationships between i-SB and steps per day and mortality risk.

CONCLUSION

Both i-SB and i-PA are significantly associated with mortality in community-dwelling older adults, showing the largest effect size for total physical activity. Dose-response relationships could be observed for i-SB and steps per day.

Diurnal Profiles of Locomotive and Household Activities Using an Accelerometer in Community-Dwelling Older Adults with Musculoskeletal Disorders: A Cross-Sectional Survey

The present study investigates the diurnal profiles of locomotive and household activities in older adults with musculoskeletal disorders (MSDs) using an accelerometer. Furthermore, we examined the effect of chronic pain on their diurnal profiles in both activities. Seventy-one older adults with MSDs (73-89 years) were included in this cross-sectional survey, and 25 age-matched older adults (75-86 years) were selected as healthy older adults. The daily physical activities, including steps walked and locomotive and household activity intensities, were recorded using a triaxial accelerometer in terms of metabolic equivalent task-hours per week (MET-h/week). The diurnal profiles of steps and locomotive activities in older adults with MSDs were considerably lower than those of healthy older adults. In contrast, there was no significant decline in household activity. However, the locomotive and household activities were reduced by severe chronic pain. This survey demonstrated that the diurnal profiles of household activity in older people with MSDs as well as those in age-matched healthy older adults were maintained. Furthermore, severe chronic pain influenced both activities. Therefore, the maintenance of household activity throughout the day, as well as the management of chronic pain, may be important strategies for the promotion of physical activity in older people with MSDs.

Objectively Measured Daily Step Counts and Prevalence of Frailty in 3,616 Older Adults

OBJECTIVES

Although previous studies have reported lower mortality and morbidity in people with higher daily step counts, the association between frailty and objectively measured step counts has not been evaluated well. We investigated the association between step counts and prevalence of frailty in community‐dwelling older adults.

DESIGN

A cross‐sectional study.

SETTING

The Kyoto‐Kameoka study in Japan.

PARTICIPANTS

We used data of 3,616 Japanese older adults, aged 65 years or older, with valid daily step count data, obtained by an accelerometer‐based pedometer.

MEASUREMENTS

The step count during 4 or more days was objectively obtained by a validated triaxial accelerometer. Participants were classified by quartiles (Qs) based on their step counts. Frailty was defined using the Fried phenotype (FP) model and the Kihon Checklist (KCL). We evaluated the association between prevalence of frailty and step counts using multivariate logistic regression and the restricted cubic spline model.

RESULTS

Mean step counts across low‐to‐high Qs of distribution were 1,759, 2,988, 4,377, and 7,200 steps/day, respectively. The prevalence of frailty, as defined by the FP model and KCL, was 11.3% and 26.8%, respectively. After adjusting for confounders, there was a negative association between the odds ratio (OR) and prevalence of frailty, as defined by the FP model among people with higher step counts (Q1: reference; Q2: OR = 0.73; 95% confidence interval (CI) = 0.56–0.96; Q3: OR = 0.56; 95% CI = 0.42–0.76; and Q4: OR = 0.41; 95% CI = 0.30–0.57; P for trend <.001). The mean step count of the population was 4,081. The OR of frailty for a 1,000‐steps/day increment was 0.74 (95% CI = 0.58–0.91) and 0.85 (95% CI = 0.72–0.97) below 4,000 steps and above 4,000 steps, respectively. In the spline model, this relationship was similar between the FP model and KCL.

CONCLUSION

These findings suggest that slightly increasing the current step count, as by 1,000 steps/day (about 10 minutes of activity), may potentially prevent frailty. J Am Geriatr Soc 68:2310–2318, 2020.

Systematic review of the prospective association of daily step counts with risk of mortality, cardiovascular disease, and dysglycemia

BACKGROUND

Daily step counts is an intuitive metric that has demonstrated success in motivating physical activity in adults and may hold potential for future public health physical activity recommendations. This review seeks to clarify the pattern of the associations between daily steps and subsequent all-cause mortality, cardiovascular disease (CVD) morbidity and mortality, and dysglycemia, as well as the number of daily steps needed for health outcomes.

METHODS

A systematic review was conducted to identify prospective studies assessing daily step count measured by pedometer or accelerometer and their associations with all-cause mortality, CVD morbidity or mortality, and dysglycemia (dysglycemia or diabetes incidence, insulin sensitivity, fasting glucose, HbA1c). The search was performed across the Medline, Embase, CINAHL, and the Cochrane Library databases from inception to August 1, 2019. Eligibility criteria included longitudinal design with health outcomes assessed at baseline and subsequent timepoints; defining steps per day as the exposure; reporting all-cause mortality, CVD morbidity or mortality, and/or dysglycemia outcomes; adults ≥18 years old; and non-patient populations.

RESULTS

Seventeen prospective studies involving over 30,000 adults were identified. Five studies reported on all-cause mortality (follow-up time 4-10 years), four on cardiovascular risk or events (6 months to 6 years), and eight on dysglycemia outcomes (3 months to 5 years). For each 1000 daily step count increase at baseline, risk reductions in all-cause mortality (6-36%) and CVD (5-21%) at follow-up were estimated across a subsample of included studies. There was no evidence of significant interaction by age, sex, health conditions or behaviors (e.g., alcohol use, smoking status, diet) among studies that tested for interactions. Studies examining dysglycemia outcomes report inconsistent findings, partially due to heterogeneity across studies of glycemia-related biomarker outcomes, analytic approaches, and sample characteristics.

CONCLUSIONS

Evidence from longitudinal data consistently demonstrated that walking an additional 1000 steps per day can help lower the risk of all-cause mortality, and CVD morbidity and mortality in adults, and that health benefits are present below 10,000 steps per day. However, the shape of the dose-response relation is not yet clear. Data are currently lacking to identify a specific minimum threshold of daily step counts needed to obtain overall health benefit.

Step by step: Association of device-measured daily steps with all-cause mortality-A prospective cohort Study

Introduction

Walking is free, does not require special training, and can be done almost everywhere. Therefore, walking is a feasible behavior on which to tailor public health messages. This study assesses the prospective association and dose‐response relationship between daily steps and all‐cause mortality.

Materials and Methods

Daily steps were measured by waist‐mounted accelerometers in 2183 individuals (53% women) for seven consecutive days at baseline (2008‐09). Participants were followed for a median period of 9.1 years and associations between steps and all‐cause mortality determined by registry linkage were assessed using Cox proportional hazard regression with adjustment for relevant covariates.

Results

Mean age was 57.0 (SD 10.9) years at baseline. Median (IQR) daily steps across ascending quartiles were 4651 (3495‐5325), 6862 (6388‐7350), 8670 (8215‐9186), and 11 467 (10 556‐13 110), respectively. During follow‐up, 119 individuals died (68% men). Higher number of daily steps was associated with a lower risk of all‐cause mortality with hazard ratios of 1.00 (referent), 0.52 (0.29‐0.93), 0.50 (0.27‐0.94), and 0.43 (0.21‐0.88) across ascending quartiles of daily steps in the multivariable‐adjusted model with follow‐up commencing 2 years after baseline. Risk differences per 1000 individuals for ascending quartiles were 6.8 (2.9‐9.3), 7.1 (0.8‐11.1), and 8.0 (1.7‐12.1), respectively.

Conclusions

Daily steps were associated with lower mortality risk in a non‐linear dose‐response pattern. The risk is almost halved when comparing the least active referent against the second quartile equivalent to a difference of about 2200 daily steps. Encouraging those least active to increase their daily steps may have substantial public health implications.

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)

How Are Wearable Activity Trackers Adopted in Older Adults? Comparison between Subjective Adoption Attitudes and Physical Activity Performance

Wearable activity trackers can motivate older adults to engage in the recommended daily amount of physical activity (PA). However, individuals may not maintain their use of the trackers over a longer period. To investigate the attitudes of activity tracker adoption and their effects on actual PA performance, we conducted a three-month study. We gave activity trackers to 16 older adults and assessed attitudes on activity tracker adoption through a survey during the study period. We extracted participants’ PA measures, step counts, and moderate and vigorous physical activity (MVPA) times. We observed significant differences in adoption attitudes during the three different periods (χ²(2, 48) = 6.27, p < 0.05), and PA measures followed similar decreasing patterns (F(83, 1357) = 12.56, 13.94, p < 0.00001). However, the Pearson correlation analysis (r = 0.268, p = 0.284) and a Bland–Altman plot indicated a bias between two PA measures. Positive attitudes at the initial stage did not persist through the study period, and both step counts and length of MVPA time showed waning patterns in the study period. The longitudinal results from both measures demonstrated the patterns of old adults’ long-term use and adoption. Considering the accuracy of the activity tracker and older adults’ athletic ability, MVPA times are more likely to be a reliable measure of older adults’ long-term use and successful adoption of activity trackers than step counts. The results support the development of better activity tracker design guidelines that would facilitate long-term adoption among older adults.

Momentary Physical Activity Co-Occurs with Healthy and Unhealthy Dietary Intake in African American College Freshmen

Background: Research investigating interrelations between physical activity and dietary intake has primarily used retrospective, summary-based measures of behavior subject to increased recall bias. This study used ecological momentary assessment (EMA) methods with accelerometry to determine within-day, momentary associations between physical activity and dietary intake behaviors in African American college freshmen. Methods: Participants (N = 50) completed a dietary EMA protocol that assessed food/fluids consumed over the past 2 h at five random times per day and wore an activPAL accelerometer for 7 days to measure physical activity. Physical activity was operationalized as step counts in the 2 h prior to the EMA prompt (matching the EMA recall window). Results: On occasions when participants took more steps than was typical for them in the 2 h prior to the EMA prompt, they were more likely to consume sugar-sweetened beverages (OR = 1.37, p < 0.001), water (OR = 1.28, p < 0.001), fruit (OR = 1.44, p < 0.001), vegetables (OR = 1.19, p = 0.02), and fried fast food (OR = 1.21, p = 0.04) over that same time. Conclusion: Momentary physical activity co-occurred with momentary consumption of both healthy and unhealthy dietary intake. These behavioral interrelations suggest potential implications for obesity risk and multiple health behavior change interventions in young adult African Americans.

Resistin concentration is inversely associated with objectively measured physical activity in healthy older women

Regular physical activity (PA) has been associated with decreased risk of many chronic diseases and increased longevity among older adults. In addition, ageing has been associated with higher levels of different inflammatory biomarkers while the association between inflammatory biomarkers and PA has remained controversial. The aim of the current investigation was to examine the association between blood biomarkers and objectively assessed PA among a sample of healthy older women with different levels of PA engagement. A total of 81 healthy women were recruited. Study participants were allocated to three groups according to accelerometer-obtained PA data. Body composition was assessed with dual-energy X-ray absorptiometry. Fasting blood samples were collected for the measurement of resistin, leptin, tumour necrosis factor alpha (TNFα) and C-reactive protein (CRP) concentrations. There were no significant differences between groups for resistin, leptin, TNFα and for CRP concentrations; however, higher moderate-to-vigorous physical activity (MVPA) groups tended to have lower level of blood biomarker concentrations. There was a significant negative relationship between resistin and steps per day. Inverse association between leptin and MVPA was significant after controlling for age. In multivariate stepwise linear regression analysis, steps per day were the strongest independent predictor for resistin, whereas for leptin, TNFα and CRP the strongest independent predictor was whole body fat mass. In conclusion, this study demonstrated negative association between resistin concentration and steps per day. Sedentary time and light PA had no relationship with resistin, leptin, TNFα or CRP concentrations.

Effect of walking on depression prevalence for diabetes using information communication technology: Prospective study

AIM

This study aimed to evaluate the prevention of diabetic depression and its impact on medical costs through the implementation of a step count monitoring system using information and communication technology.

METHODS

This study carried out a longitudinal analysis of a prospective cohort. A total of 296 participants were enrolled in the intervention group and 882 participants in the control group. The participants in the intervention group were provided with pedometers, which each participant was asked to scan using devices stationed throughout the city. Activity data were stored in real time by a cloud system. The experiment lasted 30 months.

RESULTS

None of the diabetes patients in the intervention group was diagnosed with depression during the study period, compared with 4.09% in the control group. Thus, the intervention suppressed the increase in medical costs for the people who did not develop depression in the diabetic group.

CONCLUSIONS

The prevalence rate of depression among the participants with diabetes was lowered significantly. The medical costs of the participants who did not have diabetes were also reduced by implementing the step count monitoring system with information and communication technology. This shows that the use of an information and communication technology pedometer system can have favorable effects in terms of preventing depression in diabetes patients and further benefits for non-diabetic people. Geriatr Gerontol Int 2019; 19: 1147-1152.

Daily steps and diet, but not sleep, are related to mortality in older Australians

OBJECTIVES

Supporting healthy ageing is a key priority worldwide. Physical activity, diet quality and sleep are all associated with health outcomes, but few studies have explored their independent associations with all-cause mortality in an older population in the same model. The study aim was to examine associations between step-count, self-reported diet quality, restless sleep, and all-cause mortality in adults aged 55-85 years.

DESIGN

A prospective cohort study of adults in Newcastle, New South Wales, Australia.

METHOD

Data were from 1697 participants (49.3% women; baseline mean age 65.4 ± 7.1 years). Daily steps (measured by pedometer), diet quality (from a modified Australian Recommended Food Score), and frequency of restless sleep (by self-report) were assessed in relation to all-cause mortality using Cox proportional hazard regression with adjustment for sex, age, household income and smoking. Baseline data were collected between January 2005 and April 2008, and last follow-up was in March 2017 (median follow-up 9.6 years).

RESULTS

Higher step count (HR: 0.93, 95%CI: 0.88-0.98 per 1000-step increment) and higher diet quality (HR: 0.86, 95%CI: 0.74-0.99 per 8-point increment in diet quality score) were associated with reduced mortality risk. Restless sleep for ≥3 nights/week was not associated with mortality risk (HR: 1.03, 95%CI: 0.78-1.39). Sensitivity analyses, adjusting for chronic disease and excluding deaths <1 year after baseline, did not change these estimates.

CONCLUSIONS

Increased daily steps and consumption of a greater variety of nutrient-dense foods every week would result in substantial health benefits for older people. Future research should include a greater variety of sleep measures.

Association of Step Volume and Intensity With All-Cause Mortality in Older Women

IMPORTANCE

A goal of 10 000 steps/d is commonly believed by the public to be necessary for health, but this number has limited scientific basis. Additionally, it is unknown whether greater stepping intensity is associated with health benefits, independent of steps taken per day.

OBJECTIVE

To examine associations of number of steps per day and stepping intensity with all-cause mortality.

DESIGN, SETTING, AND PARTICIPANTS

This prospective cohort study included 18 289 US women from the Women's Health Study who agreed to participate by wearing an accelerometer during waking hours for 7 days between 2011 and 2015. A total of 17 708 women wore and returned their devices; data were downloaded successfully from 17 466 devices. Of these women, 16 741 were compliant wearers (≥10 h/d of wear on ≥4 days) and included in the analyses, which took place between 2018 and 2019.

EXPOSURES

Steps per day and several measures of stepping intensity (ie, peak 1-minute cadence; peak 30-minute cadence; maximum 5-minute cadence; time spent at a stepping rate of ≥40 steps/min, reflecting purposeful steps).

MAIN OUTCOMES AND MEASURES

All-cause mortality.

RESULTS

Of the 16 741 women who met inclusion criteria, the mean (SD) age was 72.0 (5.7) years. Mean step count was 5499 per day, with 51.4%, 45.5%, and 3.1% of time spent at 0, 1 to 39 (incidental steps), and 40 steps/min or greater (purposeful steps), respectively. During a mean follow-up of 4.3 years, 504 women died. Median steps per day across low-to-high quartiles of distribution were 2718, 4363, 5905, and 8442, respectively. The corresponding quartile hazard ratios (HRs) associated with mortality and adjusted for potential confounders were 1.00 (reference), 0.59 (95% CI, 0.47-0.75), 0.54 (95% CI, 0.41-0.72), and 0.42 (95% CI, 0.30-0.60), respectively (P < .01). In spline analysis, HRs were observed to decline progressively with higher mean steps per day until approximately 7500 steps/d, after which they leveled. For measures of stepping intensity, higher intensities were associated with significantly lower mortality rates; however, after adjusting for steps per day, all associations were attenuated, and most were no longer significant (highest vs lowest quartile for peak 1-minute cadence, HR = 0.87 [95% CI, 0.68-1.11]; peak 30-minute cadence, HR = 0.86 [95% CI, 0.65-1.13]; maximum 5-minute cadence, HR = 0.80 [95% CI, 0.62-1.05]; and time spent at a stepping rate of ≥40 steps/min, HR = 1.27 [95% CI, 0.96-1.68]; P > .05).

CONCLUSIONS AND RELEVANCE

Among older women, as few as approximately 4400 steps/d was significantly related to lower mortality rates compared with approximately 2700 steps/d. With more steps per day, mortality rates progressively decreased before leveling at approximately 7500 steps/d. Stepping intensity was not clearly related to lower mortality rates after accounting for total steps per day.

Daily Step Counts for Measuring Physical Activity Exposure and Its Relation to Health

PURPOSE

A systematic primary literature review was conducted to evaluate the relationship of physical activity-as measured by daily step counts-with all-cause mortality, cardiovascular disease mortality, incident cardiovascular disease, and type 2 diabetes mellitus; to evaluate the shape of dose-response relationships; and to interpret findings in the context of development of the Physical Activity Guidelines for Americans, Second Edition.

METHODS

A primary literature search encompassing 2011 to March 2018 for existing literature reporting on these relationships was conducted.

RESULTS

Eleven pertinent articles were identified. Seven longitudinal studies examined the relationship between daily step counts and mortality, disease incidence, or risk. Two studies examined objectively measured steps per day and all-cause mortality; one was restricted to a relatively small elderly population. One study examined cardiovascular events, defined as cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke. The other four longitudinal studies addressed incident type 2 diabetes. All longitudinal studies reported an inverse relationship between steps per day and outcome risk. In one study, 531 cardiovascular events occurred during more than 45,000 person-years of follow-up. Before intervention, each increment of 2000 steps per day up to 10,000 steps was associated with a 10% lower cardiovascular event rate. Also, for every increase of 2000 steps per day over baseline, there was an 8% yearly reduction in cardiovascular event rate in individuals with impaired glucose tolerance.

CONCLUSIONS

Daily step count is a readily accessible means by which to monitor and set physical activity goals. Recent evidence supports previously limited evidence of an inverse dose-response relationship of daily steps with important health outcomes, including all-cause mortality, cardiovascular events, and type 2 diabetes. However, more independent studies will be required before these observations can be translated into public health guidelines.

Walking cadence required to elicit criterion moderate-intensity physical activity is moderated by fitness status

The aims of this study were to estimate the walking cadence required to elicit a VO₂reserve (VO₂R) of 40% and determine if fitness status moderates the relationship between walking cadence and %VO₂R. Twenty participants (10 male, mean(s) age 32(10) years; VO₂max 45(10) mL·kg^-1·min^-1) completed resting and maximal oxygen consumption tests prior to 7 x 5-min bouts of treadmill walking at increasing speed while wearing an Apple Watch and measuring oxygen consumption continuously. The 7 x 5-min exercise bouts were performed at speeds between 3 and 6 km·h^-1 with 5-min seated rest following each bout. Walking cadence measured at each treadmill speed was recorded using the Apple Watch "Activity" app. Using Bayesian regression, we predict that participants need a walking cadence of 138 to 140 steps·min^-1 to achieve a VO₂R of 40%. However, these values are moderated by fitness status such that those with lower fitness can achieve 40% VO₂R at a slower walking cadence. The results suggest that those with moderate fitness need to walk at ~40% higher than the currently recommended walking cadence (100 steps·min^-1) to elicit moderate-intensity physical activity. However, walking cadence required to achieve moderate-intensity physical activity is moderated by fitness status.