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)).
CONCLUSIONS: 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.

OBJECTIVE: This study aimed to quantify the association between step count and multiple health outcomes in a healthy population.
METHODS: PubMed, Embase, Web of Science, and The Cochrane Library were systematically searched for systematic reviews and meta-analyses from inception to April 1, 2022. Literature screening, data extraction, and data analysis were performed in this umbrella review. The intervention factor was daily step counts measured based on devices. Multiple health outcomes included metabolic diseases, cardiovascular diseases, all-cause mortality, and other outcomes in the healthy population.
RESULTS: Twenty studies with 94 outcomes were identified in this umbrella review. The increase in daily step count contributed to a range of human health outcomes. Furthermore, the special population, different age groups, countries, and cohorts should be carefully considered. Negative correlation between step counts and the following outcomes: metabolic outcomes, cardiovascular diseases, all-cause mortality, postural balance, cognitive function, and mental health. However, there was no association between participation in the outdoor walking group and the improvement of systolic blood pressure and diastolic blood pressure. Analysis of the dose-response association between increasing daily step count and the risk of cardiovascular disease events and all-cause mortality showed a substantially linear relationship.
CONCLUSIONS: A wide range of health outcomes can benefit from the right number of steps.

BACKGROUND: eHealth applications can support early mobilization and physical activity (PA) after surgery. This systematic review provides an overview of eHealth services to enhance or record PA after visceral surgery interventions.
METHODS: Two electronic databases (MEDLINE PubMed and Web of Science) were systematically searched (November 2023). Articles were considered eligible if they were controlled trials and described digital devices used to promote PA after visceral surgery. The Cochrane risk of bias (RoB-2) tool was used to determine the methodological quality of studies.
RESULTS: A total of nine randomized controlled studies (RCT) were included in this systematic review. The studies differed with respect to the interventions, surgical indications and evaluation variables. The risk of bias of the individual studies was moderate. The six studies using activity trackers (AT) predominantly showed insignificant improvements in the postoperative step count. The more complex fitness applications could partially reveal significant advantages compared to the control groups and the home-based online training also showed a significant increase in functional capacity.
CONCLUSIONS: Activity tracking alone has so far failed to show clinically relevant effects. In contrast, the more complex eHealth applications revealed advantages compared to usual postoperative care. More high-quality studies are needed for evidence-based recommendations for eHealth services in conjunction with visceral surgery.
UNASSIGNED: HINTERGRUND: eHealth-Anwendungen können die Frühmobilisation und körperliche Aktivität (kA) nach Operationen unterstützen. Dieses systematische Review soll einen Überblick über eHealth-Dienste zur Verbesserung oder Erfassung von kA nach viszeralchirurgischen Eingriffen geben.
METHODS: Zwei elektronische Datenbanken (MEDLINE PubMed und Web of Science) wurden systematisch durchsucht (November 2023). Artikel wurden als geeignet betrachtet, wenn es sich um kontrollierte Studien handelte, die digitale Geräte zur Förderung der kA nach viszeralchirurgischen Eingriffen beschrieben. Zur Bestimmung der methodischen Qualität der Studien wurde das Cochrane Risk of Bias (RoB-2) Tool verwendet.
UNASSIGNED: Neun randomisierte kontrollierte Studien wurden eingeschlossen. Die Studien unterschieden sich hinsichtlich der Interventionen, der chirurgischen Indikationen und der Bewertungsvariablen. Das Biasrisiko der einzelnen Studien war moderat. Die sechs Studien, in denen Aktivitäts-Tracker (AT) verwendet wurden, erzielten überwiegend keine Verbesserungen der Schrittzahl nach der Operation. Die komplexeren Fitnessapplikationen konnten teilweise signifikante Vorteile gegenüber den Kontrollgruppen nachweisen. Ebenso zeigte ein heimbasiertes Onlinetraining eine signifikante Steigerung der funktionellen Kapazität.
UNASSIGNED: Alleiniges AT zeigt bisher keine klinisch relevanten Effekte. Im Gegensatz dazu zeigten die komplexeren eHealth-Anwendungen Vorteile im Vergleich zur üblichen postoperativen Versorgung. Für evidenzbasierte Empfehlungen für eHealth-Dienste in Verbindung mit Viszeralchirurgie sind weitere hochwertige Studien erforderlich.

UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.

UNASSIGNED: There are research-grade devices that have been validated to measure either heart rate (HR) by electrocardiography (ECG) with a Polar chest strap, or step count with ACTiGraph accelerometer. However, wearable activity trackers that measure HR and steps concurrently have been tested against research-grade accelerometers and HR monitors with conflicting results. This review examines validation studies of the Fitbit Charge 2 (FBC2) for accuracy in measuring HR and step count and evaluates the device\'s reliability for use by researchers and clinicians.
UNASSIGNED: This registered review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The robvis (risk-of-bias visualization) tool was used to assess the strength of each considered article.
UNASSIGNED: Eligible articles published between 2018 and 2019 were identified using PubMed, CINHAL, Embase, Cochran, and World of Science databases and hand-searches. All articles were HR and/or step count validation studies for the FBC2 in adult ambulatory populations.
UNASSIGNED: Eight articles were examined in accordance with the eligibility criteria alignment and agreement among the authors and research librarian.
UNASSIGNED: Concordance correlation coefficients (CCC) were used to measure agreement between the tracker and criterion devices. Mean absolute percent error (MAPE) was used to average the individual absolute percent errors.
UNASSIGNED: Studies that measured CCC found agreement between the FBC2 and criterion devices ranged between 26% and 92% for HR monitoring, decreasing in accuracy as exercise intensity increased. Inversely, CCC increased from 38% to 99% for step count when exercise intensity increased. HR error between MAPE was 9.21% to 68% and showed more error as exercise intensity increased. Step measurement error MAPE was 12% for healthy persons aged 24-72 years but was reported at 46% in an older population with heart failure.
UNASSIGNED: Relative agreement with criterion and low-to-moderate MAPE were consistent in most studies reviewed and support validation of the FBC2 to accurately measure HR at low or moderate exercise intensities. However, more investigation controlling testing and measurement congruency is needed to validate step capabilities. The literature supports the validity of the FBC2 to accurately monitor HR, but for step count is inconclusive so the device may not be suitable for recommended use in all populations.

This paper examined whether the criterion validity of step count (SC), energy expenditure (EE), and heart rate (HR) varied across studies depending on the average age, body mass index (BMI), and predominant gender of participants.
Data from 1536 studies examining the validity of various wearable devices were used. Separate multilevel regression models examined the associations among age, gender, and BMI with device criterion validity assessed using mean absolute percent error (MAPE) at the study level.
MAPE values were reported in 970 studies for SC, 328 for EE, and 238 for HR, respectively. There were several significant differences in MAPE between age, gender, and BMI categories for SC, EE, and HR. SC MAPE was significantly different for older adults compared with adults. Compared with studies among normal-weight populations, MAPE was greater among studies with overweight samples for SC, HR, and EE. Comparing studies with more women than men, MAPE was significantly greater for EE and HR.
There are important differences in the criterion validity of commercial wearable devices across studies of varying ages, BMIs, and genders. Few studies have examined differences in error between different age groups, particularly for EE and HR.

UNASSIGNED: Physical activity (PA) is reduced in persons with multiple sclerosis (MS), though it is known to aid in symptom and fatigue management. Methods for measuring PA are diverse and the impact of this heterogeneity on study outcomes is unclear. We aimed to clarify this impact by comparing common methods for deriving PA metrics in MS populations.
UNASSIGNED: First, a rapid review of existing literature identified methods for calculating PA in studies which used the Actigraph GT3X in populations with MS. We then compared methods in a prospective study on 42 persons with MS [EDSS 4.5 (3.5-6)] during a voluntary course of inpatient neurorehabilitation. Mixed-effects linear regression identified methodological factors which influenced PA measurements. Non-parametric hypothesis tests, correlations, and agreement statistics assessed overall and pairwise differences between methods.
UNASSIGNED: In the rapid review, searches identified 421 unique records. Sixty-nine records representing 51 eligible studies exhibited substantial heterogeneity in methodology and reporting practices. In a subsequent comparative study, multiple methods for deriving six PA metrics (step count, activity counts, total time in PA, sedentary time, time in light PA, time in moderate to vigorous PA), were identified and directly compared. All metrics were sensitive to methodological factors such as the selected preprocessing filter, data source (vertical vs. vector magnitude counts), and cutpoint. Additionally, sedentary time was sensitive to wear time definitions. Pairwise correlation and agreement between methods varied from weak (minimum correlation: 0.15, minimum agreement: 0.03) to perfect (maximum correlation: 1.00, maximum agreement: 1.00). Methodological factors biased both point estimates of PA and correlations between PA and clinical assessments.
UNASSIGNED: Methodological heterogeneity of existing literature is high, and this heterogeneity may confound studies which use the Actigraph GT3X. Step counts were highly sensitive to the filter used to process raw accelerometer data. Sedentary time was particularly sensitive to methodology, and we recommend using total time in PA instead. Several, though not all, methods for deriving light PA and moderate to vigorous PA yielded nearly identical results. PA metrics based on vertical axis counts tended to outperform those based on vector magnitude counts. Additional research is needed to establish the relative validity of existing methods.

OBJECTIVE: Although low ambulation among older adults has been linked to a broad range of adverse outcomes during and after acute hospitalisation, a systematic inquiry of the link between step count and these consequences is required. Therefore, the main purpose of this study is to systematically review the relationships between step count and hospitalisation-associated outcomes in acutely hospitalised older adults.
METHODS: The electronic databases MEDLINE, CINAHL, and Embase were searched for studies including older adults (above age 65) hospitalised in acute internal wards. The search included the following key terms: \'accelerometer\', \'step count\', \'hospital\', \'internal ward\', and \'older adults\'. Step count measurement linked to short- and/or long-term outcome(s) during and/or after hospitalisation. All types of articles (except reviews) in English from 1990 to May 2020 were considered. The Newcastle-Ottawa Scale was used to assess the quality of the included observational studies. Randomised controlled trials (RCT) were evaluated using the PEDro scale. The review protocol was registered with PROSPERO International Prospective Register of Systematic Reviews. PRISMA guidelines were followed and a PRISMA checklist for reporting systematic reviews completed.
RESULTS: The search yielded 1340 articles, and of those, the inclusion criteria were met by 12 studies: eight prospective, three interventional (one randomised controlled trial), and one case-control. These studies included three major adverse hospitalisation outcomes associated with step count: functional decline, longer length of stay, and higher re-hospitalisation rate; however, the large heterogeneity in the studies\' methodology makes meta-analysis impossible.
CONCLUSIONS: Daily step count during hospitalisation of older adults is negatively associated with adverse outcomes, but causation cannot be inferred due to inconsistent outcomes and various methodological limitations. More studies are needed to illuminate causal pathways and mechanisms underlying these relationships, especially to differentiate between the relative contribution of personal versus environmental factors.

Consumer-wearable activity trackers are small electronic devices that record fitness and health-related measures.
The purpose of this systematic review was to examine the validity and reliability of commercial wearables in measuring step count, heart rate, and energy expenditure.
We identified devices to be included in the review. Database searches were conducted in PubMed, Embase, and SPORTDiscus, and only articles published in the English language up to May 2019 were considered. Studies were excluded if they did not identify the device used and if they did not examine the validity or reliability of the device. Studies involving the general population and all special populations were included. We operationalized validity as criterion validity (as compared with other measures) and construct validity (degree to which the device is measuring what it claims). Reliability measures focused on intradevice and interdevice reliability.
We included 158 publications examining nine different commercial wearable device brands. Fitbit was by far the most studied brand. In laboratory-based settings, Fitbit, Apple Watch, and Samsung appeared to measure steps accurately. Heart rate measurement was more variable, with Apple Watch and Garmin being the most accurate and Fitbit tending toward underestimation. For energy expenditure, no brand was accurate. We also examined validity between devices within a specific brand.
Commercial wearable devices are accurate for measuring steps and heart rate in laboratory-based settings, but this varies by the manufacturer and device type. Devices are constantly being upgraded and redesigned to new models, suggesting the need for more current reviews and research.

BACKGROUND: The objectives of this review paper were to synthesize the data from randomized controlled trials in the literature to come to a conclusion on the effects of e-health interventions on promoting physical activity in older people.
METHODS: The Medline, CINAHL, Embase, PsycINFO, and SportDiscus databases were searched for articles about studies that 1) recruited subjects with a mean age of > 50 years, 2) tested e-health interventions, 3) employed control groups with no or less advanced e-health strategies, 4) measured physical activity as an outcome, 5) were published between 1st January 2008 and 31st May 2019, and 6) employed randomized controlled trials. The risk of bias in individual studies was assessed using the Physiotherapy Evidence Database scale. To examine the effects of the interventions, variables quantifying the amount of physical activity were extracted. The within-group effects of individual studies were summarized using Hedges g and 95% confidence intervals. Between-group effects were summarized by meta-analyses using RevMan 5.0 with a random effect model.
RESULTS: Of the 2810 identified studies, 38 were eligible, 25 were included in the meta-analyses. The within-group effect sizes (Hedges g) of physical activity in the intervention group at T1 ranged from small to large: physical activity time (0.12 to 0.84), step counts (- 0.01 to 11.19), energy expenditure (- 0.05 to 0.86), walking time (0.13 to 3.33), and sedentary time (- 0.12 to - 0.28). The delayed effects as observed in T2 and T3 also ranged from small to large: physical activity time (0.24 to 1.24) and energy expenditure (0.15 to 1.32). In the meta-analysis, the between-group effect of the e-health intervention on physical activity time measured by questionnaires, physical activity time measured by objective wearable devices, energy expenditure, and step counts were all significant with minimal heterogeneity.
CONCLUSIONS: E-health interventions are effective at increasing the time spent on physical activity, energy expenditure in physical activity, and the number of walking steps. It is recommended that e-health interventions be included in guidelines to enhance physical activity in older people. Further studies should be conducted to determine the most effective e-health strategies.