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BACKGROUND:To examine the associations between objective physical activity measures and subsequent health care utilization. METHODS:We studied 1,283 men (mean age 79.1 years, SD 5.3) participating in the Osteoporotic Fractures in Men Study. Participants wore a SenseWear® Pro Armband monitor for 1 week. Data was summarized as daily (i) step counts, (ii) total energy expenditure, (iii) active energy expenditure, and (iv) activity time (sedentary, ≥ light, ≥ moderate). The outcome measures of 1-year hospitalizations/duration of stay from Medicare data were analyzed with a two-part hurdle model. Covariates included age, clinical center, body mass index, marital status, depressive symptoms, medical conditions, cognitive function, and prior hospitalization. RESULTS:Each 1 SD = 3,092 step increase in daily step count was associated with a 34% (95% confidence interval [CI]: 19%-46%) lower odds of hospitalization in base model (age and center) and 21% (95% CI: 4%-35%) lower odds of hospitalization in fully adjusted models. Similar but smaller associations held for other physical activity measures, but these associations were not significant in fully adjusted models. Among those hospitalized, higher step count was associated with shorter total duration of acute/postacute care stays in the base model only. There was a fourfold significant difference (from model-based estimates) in predicted care days comparing those with 2,000 versus 10,000 daily steps in the base model, but only a twofold difference (not significant) in the full model. CONCLUSION:Daily step count is an easily determined measure of physical activity that may be useful in assessment of future health care burden in older men.

The COVID-19 outbreak resulted in the shutdown of athletic training facilities. Although the effects of these restrictions on daily activity and sleep patterns have been widely analyzed, the employed tools often lacked accuracy, and were based on subjective measures. This study assessed the effects of home confinement on objective physical activity (PA), physiological and sleep parameters in active individuals. Sixteen male elite fitness coaches (age: 29±3 years; height: 183±6 cm; body mass: 82±5 kg, body mass index: 24.7±1.8 kg/m2) participated in this retrospective study. One-way analysis of variance was conducted to analyze selected PA, physiological and sleep parameters collected by smartwatch (Garmin Fenix 6 pro, USA) data during four consecutive months [i.e., pre-confinement, 1st and 2nd months of confinement, and post-confinement, year 2020]. Ramadan intermittent fasting (RIF) month occurred during the 2nd month of confinement. Compared to pre-confinement, significant changes were registered for almost all parameters during the 1st and/or the 2nd month of confinements (p

Objectives: Daily step counts are an easy-to-understand indicator of physical activity; however, there is limited evidence regarding the optimal daily step count to prevent sarcopenia. This study examined the dose-response relationship between daily step count and the prevalence of sarcopenia and explored the optimal dose. Design: Cross-sectional study. Setting and participants: The study included 7949 community-dwelling middle-aged and older adults (aged 45–74 years) from Japan. Measurements: Skeletal muscle mass (SMM) was assessed using bioelectrical impedance spectroscopy, and muscle strength was quantified through handgrip strength (HGS) measurement. Participants who exhibited both low HGS (men:

Background: Commercial activity trackers are increasingly used in research and compared with research-based accelerometers are often less intrusive, cheaper, with improved storage and battery capacity, although typically less validated. The present study aimed to determine the validity of Oura Ring step-count and energy expenditure (EE) in both laboratory and free-living. Methods: Oura Ring EE was compared against indirect calorimetry in the laboratory, followed by a 14-day free-living study with 32 participants wearing an Oura Ring and reference monitors (three accelerometers positioned at hip, thigh, and wrist, and pedometer) to evaluate Oura EE variables and step count. Results: Strong correlations were shown for Oura versus indirect calorimetry in the laboratory (r = 0.93), and versus reference monitors for all variables in free-living (r ≥ 0.76). Significant (p < 0.05) mean differences for Oura versus reference methods were found for laboratory measured sitting (− 0.12 ± 0.28 MET), standing (− 0.27 ± 0.33 MET), fast walk (− 0.82 ± 1.92 MET) and very fast run (− 3.49 ± 3.94 MET), and for free-living step-count (2124 ± 4256 steps) and EE variables (MET: − 0.34-0.26; TEE: 362–494 kcal; AEE: − 487-259 kcal). In the laboratory, Oura tended to underestimate EE with increasing discrepancy as intensity increased. The combined activities and slow running in the laboratory, and all MET placements, TEE hip and wrist, and step count in free-living had acceptable measurement errors (< 10% MAPE), whereas the remaining free-living variables showed close to (≤13.2%) acceptable limits. Conclusion: This is the first study investigating the validity of Oura Ring EE against gold standard methods. Oura successfully identified major changes between activities and/or intensities but was less responsive to detailed deviations within activities. In free-living, Oura step-count and EE variables tightly correlated with reference monitors, though with systemic over- or underestimations indicating somewhat low intra-individual validity of the ring versus the reference monitors. However, the correlations between the devices were high, suggesting that the Oura can detect differences at group-level for active and total energy expenditure, as well as step count. [ABSTRACT FROM AUTHOR]

Research demonstrates that exercise can decrease depressive symptoms, yet it is infrequently prescribed as an intervention. Self‐management techniques offer an effective and cost‐efficient approach to increase engagement in physical activity. The purpose of this study was to evaluate the efficacy of goal setting, self‐monitoring, and feedback for increasing daily step count in university students (N = 4) reporting depressive symptoms. The treatment was efficacious for increasing steps for three participants with varying levels of consistency. All participants showed a decrease in some depression symptoms on the University Student Depression Inventory. Expert ratings on the Clinical Global Impression Scale indicated improvement in global functioning for three participants. Additional research is needed to determine the efficacy of this intervention package for increasing daily steps and the relation to depression symptoms. [ABSTRACT FROM AUTHOR]

Wearable technologies have become powerful tools for health and fitness and are indispensable everyday tools for many individuals; however, significant limitations exist related to the validity of the metrics these monitors purport to measure. Thus, the purpose of the present study was to validate the step count of three wearable monitors (i.e., Yamax 3D Power-Walker, Garmin Vivofit 3 and Medisana Vifit), as well as two Android apps (i.e., Accupedo Pedometer and Pedometer 2.0), in a sample of healthy adults. These monitors and apps were evaluated in a lab-based semi-structured study and a 3-day field study under habitual free-living conditions. A convenience sample of 24 healthy adults (14 males and 10 females; 32.6 ± 2.5 years) participated in both studies. Direct step observation and Actigraph served as the criterion methods and validity was evaluated by comparing each monitor and app with the criterion measure using mean absolute percentage errors (MAPE), Bland–Altman plots, and Intraclass Correlation Coefficients. The results revealed high validity for the three wearable monitors during the semi-structured study, with MAPE values approximately 5% for Yamax and Vifit and well below 5% for Vivofit, while the two apps showed high MAPE values over 20%. In the free-living study all monitors and apps had high MAPE, over 10%. The lowest error was observed for Yamax, Vifit and Pedometer app, while Accupedo app had the highest error, overestimating steps by 32%. The present findings cannot support the value of wearable monitors and apps as acceptable measures of PA and step count in free-living contexts. Wearable monitors and apps that might be valid in one context, might not be valid in different contexts and vice versa, and researchers should be aware of this limitation. [ABSTRACT FROM AUTHOR]

Commercial smartwatches could be useful for step counting and monitoring ambulatory activity. However, in Parkinson's disease (PD) patients, an altered gait, pharmacological condition, and symptoms lateralization may affect their accuracy and potential usefulness in research and clinical routine. Steps were counted during a 6 min walk in 47 patients with PD and 47 healthy subjects (HS) wearing a Garmin Vivosmart 4 (GV4) on each wrist. Manual step counting was used as a reference. An inertial sensor (BTS G-Walk), placed on the lower back, was used to compute spatial-temporal gait parameters. Intraclass correlation coefficient (ICC) and mean absolute percentage error (MAPE) were used for accuracy evaluation and the Spearman test was used to assess the correlations between variables. The GV4 overestimated steps in PD patients with only a poor-to-moderate agreement. The OFF pharmacological state and wearing the device on the most-affected body side led to an unacceptable accuracy. The GV4 showed an excellent agreement and MAPE in HS at a self-selected speed, but an unacceptable performance at a slow speed. In PD patients, MAPE was not associated with gait parameters and clinical variables. The accuracy of commercial smartwatches for monitoring step counting might be reduced in PD patients and further influenced by the pharmacological condition and placement of the device. [ABSTRACT FROM AUTHOR]

Background: Physical inactivity is a known risk factor for atrial fibrillation (AF). Wearable devices, such as smartwatches, present an opportunity to investigate the relation between daily step count and AF risk. Objective: The objective of this study was to investigate the association between daily step count and the predicted 5-year risk of AF. Methods: Participants from the electronic Framingham Heart Study used an Apple smartwatch. Individuals with diagnosed AF were excluded. Daily step count, watch wear time (hours and days), and self-reported physical activity data were collected. Individuals' 5-year risk of AF was estimated, using the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)–AF score. The relation between daily step count and predicted 5-year AF risk was examined via linear regression, adjusting for age, sex, and wear time. Secondary analyses examined effect modification by sex and obesity (BMI≥30 kg/m2), as well as the relation between self-reported physical activity and predicted 5-year AF risk. Results: We examined 923 electronic Framingham Heart Study participants (age: mean 53, SD 9 years; female: n=563, 61%) who had a median daily step count of 7227 (IQR 5699-8970). Most participants (n=823, 89.2%) had a <2.5% CHARGE-AF risk. Every 1000 steps were associated with a 0.08% lower CHARGE-AF risk (P <.001). A stronger association was observed in men and individuals with obesity. In contrast, self-reported physical activity was not associated with CHARGE-AF risk. Conclusions: Higher daily step counts were associated with a lower predicted 5-year risk of AF, and this relation was stronger in men and participants with obesity. The utility of a wearable daily step counter for AF risk reduction merits further investigation. [ABSTRACT FROM AUTHOR]

Abstract Background Physical activity is an important factor in premature mortality reduction, non-communicable disease prevention, and well-being protection. Climate change will alter temperatures globally, with impacts already found on mortality and morbidity. While uncomfortable temperature is often perceived as a barrier to physical activity, the actual impact of temperature on physical activity has been less well studied, particularly in China. This study examined the associations between temperature and objectively measured physical activity among adult populations in five major Chinese cities. Methods Aggregated anonymized step count data was obtained between December 2017-2018 for five major Chinese cities: Beijing, Shanghai, Chongqing, Shenzhen, and Hong Kong. The associations of temperature with daily aggregated mean step count were assessed using Generalized Additive Models (GAMs), adjusted for meteorological, air pollution, and time-related variables. Results Significant decreases in step counts during periods of high temperatures were found for cold or temperate climate cities (Beijing, Shanghai, and Chongqing), with maximum physical activity occurring between 16 and 19.3 °C. High temperatures were associated with decreases of 800-1500 daily steps compared to optimal temperatures. For cities in subtropical climates (Shenzhen and Hong Kong), non-significant declines were found with high temperatures. Overall, females and the elderly demonstrated lower optimal temperatures for physical activity and larger decreases of step count in warmer temperatures. Conclusions As minor reductions in physical activity could consequentially affect health, an increased awareness of temperature’s impact on physical activity is necessary. City-wide adaptations and physical activity interventions should seek ways to sustain physical activity levels in the face of shifting temperatures from climate change.

Daily steps could be a valuable indicator of real-world ambulation in Parkinson’s disease (PD). Nonetheless, no study to date has investigated the minimum number of days required to reliably estimate the average daily steps through commercial smartwatches in people with PD. Fifty-six patients were monitored through a commercial smartwatch for 5 consecutive days. The total daily steps for each day was recorded and the average daily steps was calculated as well as the working and weekend days average steps. The intraclass correlation coefficient (ICC) (3,k), standard error of measurement (SEM), Bland–Altman statistics, and minimum detectable change (MDC) were used to evaluate the reliability of the step count for every combination of 2–5 days. The threshold for acceptability was set at an ICC ≥ 0.8 with a lower bound of CI 95% ≥ 0.75 and a SAM < 10%. ANOVA and Mann–Whitney tests were used to compare steps across the days and between the working and weekend days, respectively. Four days were needed to achieve an acceptable reliability (ICC range: 0.84–0.90; SAM range: 7.8–9.4%). In addition, daily steps did not significantly differ across the days and between the working and weekend days. These findings could support the use of step count as a walking activity index and could be relevant to developing monitoring, preventive, and rehabilitation strategies for people with PD.

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.

Physical activity (PA) is important in Cystic Fibrosis (CF) management. Fitness wearables are becoming increasingly popular as measurement tools of PA; however, the accuracy of these devices should first be evaluated. The purpose of this study was to assess the accuracy of the ActivPAL and Fitbit Charge 2 as a measure of step count in Cystic Fibrosis. Twenty-one participants were recruited from an adult CF Center in Ireland for a single session of testing. Participants walked for 5 min at five pre-determined speeds in a controlled testing environment (2, 2.5, 3, 3.5 and 4 miles per hour on a treadmill) and at three self-selected speeds in a corridor (slow, medium, and fast). They concurrently wore an accelerometer (ActivPAL) and fitness wearable (Fitbit Charge 2), and both were compared to visual observations. Step count is the outcome being assessed. The ActivPAL under-estimated step count by 0.63% across treadmill speeds and 1.1% across self-selected walking speeds. The Fitbit Charge 2 underestimated the step count by 2.97% across treadmill speeds and by 6.3% across self-selected walking speeds. Very strong correlations were found between the ActivPAL and visual observations (r: 0.93 to 0.99), while the Fitbit Charge 2 ranged from weak to very strong correlations when compared to visual observations (r: 0.34 to 0.84). The ActivPAL and Fitbit Charge 2 demonstrated acceptable validity for step count measurement in CF. These devices can be used for tracking PA during interventions in people with CF. [ABSTRACT FROM AUTHOR]

For the various asthma-specific beneficial effects of physical activity, daily physical activity (DPA) and the potential of asthma therapies on DPA require better characterization. Hence, we aimed to determine (a) the DPA of asthma patients, and (b) the effect of add-on mepolizumab on the DPA of severe asthma patients. Methods: Adult outpatients with mild-to-moderate or severe asthma had accelerometer assessment of DPA. Severe asthma patients who were commenced on mepolizumab had their DPA reassessed after 12 months. Results: For the total cohort (n = 36), daily step count, time in moderate-to-vigorous physical activity (MVPA), MVPA volume and Movement Intensity (MI) were 7806 ± 3823 steps, 123 (interquartile range, 63) min, 657 ± 255 MET·min and 1.96 (0.45) m/s2, respectively. All patients met at least one recommendation for DPA but less than half met recommendations for vigorous DPA. Patients on mepolizumab therapy increased daily step count (646 steps; 9%), time in MVPA (20 min; 21%), MVPA volume (87 MET·min; 17%) and MI (0.11 m/s2; 6%) for the same amount of moving time; lung function, asthma control and health-related quality of life also improved. Conclusions: Analysis of the first national data on DPA in asthma and novel comparison against current applicable guidelines and identified beneficial thresholds showed borderline levels of DPA with room for improvement especially for severe asthma patients. In a non-sedentary cohort of severe asthma patients, mepolizumab conferred significant and meaningful improvements in DPA. [ABSTRACT FROM AUTHOR]

Physical activity is decreased in patients with chronic obstructive pulmonary disease, and decreased physical activity leads to a poor prognosis. To determine an individual's target step count from the measured step counts and predicted step counts, simple and detailed prediction equations for step count were developed. To verify the validity of the simple prediction equation, the validity of the simple equation was evaluated in a different cohort and the correlation between the step counts calculated by the simple equation and those by the detailed prediction equation were evaluated. When the step counts calculated by the simple prediction equation for all participants were compared with the measured step counts, a significant correlation was obtained among them, and the calculated values were found to be reproducible with the measured values in patients with a measured step count of <6500 by Bland–Altman plots. Furthermore, the values calculated by the simple prediction equation and those calculated by the detailed prediction equation showed a significant correlation. In conclusion, the simple prediction equation was considered reasonable. [ABSTRACT FROM AUTHOR]

The Verisense Step Count Algorithm facilitates generation of steps from wrist-worn accelerometers. Based on preliminary evidence suggesting a proportional bias with overestimation at low steps/day, but underestimation at high steps/day, the algorithm parameters have been revised. We aimed to establish validity of the original and revised algorithms relative to waist-worn ActiGraph step cadence. We also assessed whether step cadence was similar across accelerometer brand and wrist. Ninety-eight participants (age: 58.6±11.1 y) undertook six walks (~500 m hard path) at different speeds (cadence: 92.9±9.5–127.9±8.7 steps/min) while wearing three accelerometers on each wrist (Axivity, GENEActiv, ActiGraph) and an ActiGraph on the waist. Of these, 24 participants also undertook one run (~1000 m). Mean bias for the original algorithm was −21 to −26.1 steps/min (95% limits of agreement (LoA) ~±65 steps/min) and mean absolute percentage error (MAPE) 17–22%. This was unevenly distributed with increasing error as speed increased. Mean bias and 95%LoA were halved with the revised algorithm parameters (~-10 to −12 steps/min, 95%LoA ~30 steps/min, MAPE ~10-12%). Performance was similar across brand and wrist. The revised step algorithm provides a more valid measure of step cadence than the original, with MAPE similar to recently reported wrist-wear summary MAPE (7–11%). [ABSTRACT FROM AUTHOR]

Introduction: There is conflicting data in the literature regarding the clinical utility of wearable devices. This study examined the association between patient reported outcome measures (PROMs) and step and stair flight counts obtained from wearable devices in postoperative total hip arthroplasty (THA) patients., Methods: Data was collected from a multicenter prospective longitudinal cohort study from October 2018 to February 2022. A smartphone-based platform with smartwatch was utilized for collection of daily step and stair flight counts. Subjects (N = 1644) completed the Hip disability and Osteoarthritis Outcome Score for Joint Replacement (HOOS JR) and numerical rating scale (NRS) pain scores preoperatively and at 1 and 3 months postoperatively. Patients who reported living in a multi-level home (N = 931) were included in analysis of stair flight counts. Pearson correlation coefficients were calculated to determine correlations between step and stair flight counts with NRS pain and HOOS JR scores., Results: Step counts demonstrated a weak negative correlation to NRS pain scores at preoperative (r = - 0.15, p < 0.0001), 1-month (r = - 0.15, p < 0.0001), and 3-months follow-up (r = - 0.06, p = 0.05). Step counts demonstrated a weak positive correlation with HOOS JR scores at preoperative (r = 0.16, p < 0.0001), 1-month (r = 0.15, p < 0.0001), and 3-months (r = 0.13, p < 0.0001). Stair flight counts demonstrated a weak negative correlation with NRS pain preoperatively (r = - 0.19, p < 0.0001) and at 1-month (r = - 0.11, p = 0.003). Stair flight counts positively correlated with HOOS JR scores at preoperative (r = 0.24, p < 0.0001), 1-month (r = 0.15, p < 0.0001), and 3-months (r = 0.09, p = 0.02)., Conclusion: The utilization of wearable technology can enhance the evaluation of patient outcomes after THA, primarily due to the observed correlation between data collected from wearables and PROMs. Our study highlights the importance of the use of objective data, in addition to subjective patient reported data, when analyzing postoperative patient progress, which propels forward the field of postoperative THA patient care., Competing Interests: Declarations. Conflict of interests: Mr. Nickelas Huffman, Dr. Ignacio Pasqualini, Dr Shujaa T. Khan, and Ms. Alison Klika do not have any conflicts of interest to disclose. Ethical approval: The study was approved by the WCG Institutional Review Board and registered in ClinicalTrials.gov prior to enrollment activities (NCT03737149); all subjects provided written informed consent., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Appropriate levels of physical activity (PhA) provide health benefits to patients with chronic diseases, including patients with pulmonary arterial hypertension (PAH). In this study, we examined the effect of physicians' PhA recommendations on PhA, and the benefits and effectiveness of PhA self-monitoring using a pedometer for PAH patients., Methods: A prospective clinical trial was performed from 22 April 2021, with consecutive PAH outpatients in stable condition at least three months prior to the study. Each patient was educated about the benefits of PhA in PAH during the initial visit. Patients wore pedometers (Omron HJ-321-E) for 2 weeks. After PhA assessment, the patients were contacted by a physician by phone. Patients who walked <5,000 steps per day (inactive group) were recommended to increase their PhA, and patients who walked ≥5,000 steps per day (active group) were recommended to maintain this level of PhA. Patients wore pedometers for 3 months. The primary endpoint was the number of steps taken after 12 weeks of the study. The secondary endpoints were the 6-minute walk distance (6MWD), quality of life (QoL) (36-Item Short-Form Health Survey), and anxiety and depression levels., Results: The study included 41 PAH patients aged 45.9±11.9 years, with 32 (78%) of them women. Initially, 18 (44%) patients were in the inactive group (2-week mean: 3,318±1,185 steps/day) while 23 (56%) patients were in the active group (2-week mean: 7,647±1,991 steps/day). The entire study group showed an insignificant decrease in their PhA from 5,203 [interquartile range (IQR), 3,787-7,387] to 4,672 (IQR, 3,821-7,201) steps per day (P=0.57). Patients in the inactive group showed an insignificant increase in their PhA after 12 weeks [increase in the average number of steps per day by 104 (IQR, -244 to 1,007), P=0.52], while patients in the active group showed an insignificant trend towards PhA reduction [change in average daily steps: -815 (IQR, -1,400 to 580), P=0.37]. There were no differences at week 12 in the 6MWD, N-terminal-pro-B-type natriuretic peptide (NT-proBNP) level, QoL, or levels of anxiety and depression, all P values >0.05., Conclusions: Education, a simple recommendation about PhA, and self-monitoring with a pedometer are insufficient to achieve intervention in PAH patients. Additional methods of motivating and supervising these patients are necessary., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://cdt.amegroups.com/article/view/10.21037/cdt-24-249/coif). The authors have no conflicts of interest to declare., (2024 AME Publishing Company. All rights reserved.)

Yoshiaki Minakata, Seigo Sasaki, Yuichiro Azuma, Kazumi Kawabe, Hideya Ono Department of Respiratory Medicine, National Hospital Organization Wakayama Hospital, Wakayama, JapanCorrespondence: Yoshiaki Minakata Tel +81-738-22-3256Fax +81-738-22-2126Email minakata.yoshiaki.qy@mail.hosp.go.jpBackground: To improve physical activity (PA) in patients with chronic obstructive pulmonary disease (COPD), providing a target PA value based on the individual patient’s condition may be a useful interventional strategy. However, to determine the target value, a predictive PA value for each patient is required.Research Question: What is the reference equation consisting of PA-related factors to determine the predictive PA value for each patient with COPD?Material and Methods: In this prospective cross-sectional observational study, we measured the PA with a triaxial accelerometer and several other factors including demographic factors, pulmonary function, dyspnea, exercise capacity, muscle strength, nutrition, and indicators of several comorbidities in stable Japanese outpatients with COPD aged ≥ 40 years old and detected PA-related factors by a multiple regression analysis and stepwise method. We created reference equations for four indices of PA using multiple linear regression equations.Results: Two hundred and twenty-seven patients were registered. The equations of duration at ≥ 2.0 metabolic equivalents (METs) and step count consisted of 4 factors: 6-minute walk distance, modified Medical Research Council dyspnea scale, anxiety score of the Hospital Anxiety and Depression Scale, and the forced expiratory volume in 1 second % of predicted value. Those of duration at ≥ 3.0 METs and total activity at ≥ 3.0 METs consisted of 5 factors: the above 4 factors and age or brain natriuretic peptide. There was no fixed bias or proportional bias between the measured and predictive values in patients with non-high measured PA values.Conclusion: We determined reference equations for four indicators of PA using PA-related factors in Japanese patients with COPD. The predictive values calculated using the equations could be useful for deciding target PA values for each patient.Clinical Trial Registration: UMIN-CTR; No.: UMIN000025459; URL: https://www.umin.ac.jp/ctr/index.htm.Keywords: predictive value, COPD, metabolic equivalents, step count

BackgroundPhysical 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.MethodsFirst, 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.ResultsIn 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.ConclusionsMethodological 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.

Wearable devices represent one of the most popular trends in health and fitness. Rapid advances in wearable technology present a dizzying display of possible functions: from thermometers and barometers, magnetometers and accelerometers, to oximeters and calorimeters. Consumers and practitioners utilize wearable devices to track outcomes, such as energy expenditure, training load, step count, and heart rate. While some rely on these devices in tandem with more established tools, others lean on wearable technology for health-related outcomes, such as heart rhythm analysis, peripheral oxygen saturation, sleep quality, and caloric expenditure. Given the increasing popularity of wearable devices for both recreation and health initiatives, understanding the strengths and limitations of these technologies is increasingly relevant. Need exists for continued evaluation of the efficacy of wearable devices to accurately and reliably measure purported outcomes. The purposes of this review are (1) to assess the current state of wearable devices using recent research on validity and reliability, (2) to describe existing gaps between physiology and technology, and (3) to offer expert interpretation for the lay and professional audience on how best to approach wearable technology and employ it in the pursuit of health and fitness. Current literature demonstrates inconsistent validity and reliability for various metrics, with algorithms not publicly available or lacking high-quality validation studies. Advancements in wearable technology should consider standardizing validation metrics, providing transparency in used algorithms, and improving how technology can be tailored to individuals. Until then, it is prudent to exercise caution when interpreting metrics reported from consumer-wearable devices. [ABSTRACT FROM AUTHOR]

Study Design: This is a method development and validation study.Objectives: The purpose of this study was to develop and test a method for step detection using accelerometer data in patients with lumbar spinal stenosis (LSS). There are 2 objectives: (1) to describe a method for step detection from accelerations measured at the wrist, hip, lower back, thigh and ankle; (2) to assess the accuracy of the method during walking with and without walking aids and during nonwalking activities.Summary Of Background Data: Loss of walking ability is one of the main symptoms of LSS, and there is no validated measure to assess walking activity in daily living in patients with LSS.Materials and Methods: Thirty patients with LSS performed a standardized movement protocol that included walking with and without walking aids and performing nonwalking activities while wearing accelerometers on five different wear-sites. After the walking tests, a method was designed for optimal step detection and compared with a gold standard of observed step count.Results: The method for step detection applied to accelerations from the lower back, hip, thigh, and ankle provided an accurate step counts during continuous walking without walking aids. Accuracy diminished at all wear-sites when walking with walking aids, except the ankle. The wrist provided the most inaccurate step count, and the accelerometers on the thigh and ankle were prone to falsely detecting steps during bicycling.Conclusion: The ankle-worn accelerometer provided the most accurate step count, but wrongly registered steps during nonwalking activities. The developed step detection method shows potential as a measure of walking activity why further development and testing under free-living conditions should be performed. [ABSTRACT FROM AUTHOR]

Abstract Background Walking is a fundamental part of living, and its importance is not limited by age or medical status. Reduced walking speed (WS), or gait velocity, is a sign of advancing age, various disease states, cognitive impairment, mental illness and early mortality. Activity levels, as defined in the literature as “daily step count” (DSC), is also a relevant measure of health status. A deterioration in our walking metrics, such as reduced WS and DSC, is associated with poor health outcomes. These objective measures are of such importance, that walking speed has been dubbed “the 6th vital sign”. We report a new objective measure that scores walking using the relevant metrics of walking speed and daily step count, into an easy-to-understand score from 0 (nil mobility) to 100 (excellent mobility), termed the Simplified Mobility Score (SMoS™). We have provided equal weighting to walking speed and daily step count, using a simple algorithm to score each metric out of 50. Methods Gait data was collected from 182 patients presenting to a tertiary hospital spinal unit with complaints of pain and reduced mobility. Walking speed was measured from a timed walk along an unobstructed pathway. Daily step count information was obtained from patients who had enabled step count tracking on their devices. The SMoS of the sample group were compared to expected population values calculated from the literature using 2-tailed Z tests. Results There were significantly reduced SMoS in patients who presented to the spinal unit than those expected at each age group for both genders, except for the 50–59 age bracket where no statistically significant reduction was observed. Even lower scores were present in those that went on to have surgical management. There was a significant correlation of SMoS scores with subjective disability scores such as the Oswestry Disability Index (ODI) and Visual Analogue Scale (VAS) in this cohort. Conclusions The SMoS is a simple and effective scoring tool which is demonstrably altered in spinal patients across age and gender brackets and correlates well with subjective disability scores. The SMoS has the potential to be used as a screening tool in primary and specialised care settings.

The article presents a study which recommends health referenced standards for step defined physical activity relating to appropriate health indicators in a group of adolescent girls. Topics discussed include participation of adolescent girls aged between 12 to 15 years, and measurement of body mass index (BMI), body fat and blood pressure. The article concludes that adolescent girls may not walk enough to stratify health related outcomes.

Background: Physical Inactivity (PI) and sedentary behaviour are the most important and modifiable risk factors to prevent cardiovascular diseases (CVD). Cardiac rehabilitation (CR) is a multidisciplinary program for patients who have undergone cardiac surgeries. Through CR, monitoring physical activity (PA) is possible and may reduce the rate of rehospitalization. The pedometer is a device that is useful to track the step count of the person day to day. It helps in self-monitoring of PA. The purpose of this review was to summarise the evidence about the effect of pedometer-based exercise program in phase 1 and phase 2 CR. Methods: Databases such as MEDLINE, Cochrane, Scopus, Embase, and Web of Science were searched. This search is limited to randomized controlled trials (RCTs), human trials, a 10-year period, and English language journals. Based on inclusion criteria of pedometer-based exercise programs in phase 1 (inpatient phase) and phase 2 (outpatient phase) of CR and exclusion criteria of studies using pedometer in maintenance phase CR. The primary outcome of the study is step count, while secondary is PA (in terms of time), heart rate, sedentary behaviour, and quality of life. This study quality was assessed by the Downs and Black’s checklist. Results: The study includes 6 RCTs based on the inclusion and exclusion criteria. Most studies show a considerable increase in step count associated with increased patient PA. Few studies have explained a significant increase of PA in the study group and maintained for longer terms. More research is needed to determine the impact of cardiovascular risk factors.

Measures of stepping volume and rate are common outputs from wearable devices, such as accelerometers. It has been proposed that biomedical technologies, including accelerometers and their algorithms, should undergo rigorous verification as well as analytical and clinical validation to demonstrate that they are fit for purpose. The aim of this study was to use the V3 framework to assess the analytical and clinical validity of a wrist-worn measurement system of stepping volume and rate, formed by the GENEActiv accelerometer and GENEAcount step counting algorithm. The analytical validity was assessed by measuring the level of agreement between the wrist-worn system and a thigh-worn system (activPAL), the reference measure. The clinical validity was assessed by establishing the prospective association between the changes in stepping volume and rate with changes in physical function (SPPB score). The agreement of the thigh-worn reference system and the wrist-worn system was excellent for total daily steps (CCC = 0.88, 95% CI 0.83–0.91) and moderate for walking steps and faster-paced walking steps (CCC = 0.61, 95% CI 0.53–0.68 and 0.55, 95% CI 0.46–0.64, respectively). A higher number of total steps and faster paced-walking steps was consistently associated with better physical function. After 24 months, an increase of 1000 daily faster-paced walking steps was associated with a clinically meaningful increase in physical function (0.53 SPPB score, 95% CI 0.32–0.74). We have validated a digital susceptibility/risk biomarker—pfSTEP—that identifies an associated risk of low physical function in community-dwelling older adults using a wrist-worn accelerometer and its accompanying open-source step counting algorithm.

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. 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. 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)). 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. [Display omitted] • This umbrella review is the largest synthesis of daily steps and all-cause mortality in the general population. • Systematic reviews and meta-analyses published to date showed substantial variability in the effect estimates provided. • All-cause mortality risk decreases with more steps: minimum protection at 3143 steps/day, with the lowest risk for >12,500 steps/day. • Future research should categorise daily steps by activity level, analise dose-response, and use 1000 step/day increments. [ABSTRACT FROM AUTHOR]

Maintaining physical activity is an important clinical goal for people with Parkinson’s disease (PwPD). We investigated the validity of two commercial activity trackers (ATs) to measure daily step counts. We compared a wrist- and a hip-worn commercial AT against the research-grade Dynaport Movemonitor (DAM) during 14 days of daily use. Criterion validity was assessed in 28 PwPD and 30 healthy controls (HCs) by a 2 × 3 ANOVA and intraclass correlation coefficients (ICC2,1). The ability to measure daily step fluctuations compared to the DAM was studied by a 2 × 3 ANOVA and Kendall correlations. We also explored compliance and user-friendliness. Both the ATs and the DAM measured significantly fewer steps/day in PwPD compared to HCs (p < 0.01). Step counts derived from the ATs showed good to excellent agreement with the DAM in both groups (ICC2,1 > 0.83). Daily fluctuations were detected adequately by the ATs, showing moderate associations with DAM-rankings. While compliance was high overall, 22% of PwPD were disinclined to use the ATs after the study. Overall, we conclude that the ATs had sufficient agreement with the DAM for the purpose of promoting physical activity in mildly affected PwPD. However, further validation is needed before clinical use can be widely recommended.

Background: Physical activity is an important factor in premature mortality reduction, non-communicable disease prevention, and well-being protection. Climate change will alter temperatures globally, with impacts already found on mortality and morbidity. While uncomfortable temperature is often perceived as a barrier to physical activity, the actual impact of temperature on physical activity has been less well studied, particularly in China. This study examined the associations between temperature and objectively measured physical activity among adult populations in five major Chinese cities. Methods: Aggregated anonymized step count data was obtained between December 2017-2018 for five major Chinese cities: Beijing, Shanghai, Chongqing, Shenzhen, and Hong Kong. The associations of temperature with daily aggregated mean step count were assessed using Generalized Additive Models (GAMs), adjusted for meteorological, air pollution, and time-related variables. Results: Significant decreases in step counts during periods of high temperatures were found for cold or temperate climate cities (Beijing, Shanghai, and Chongqing), with maximum physical activity occurring between 16 and 19.3 °C. High temperatures were associated with decreases of 800-1500 daily steps compared to optimal temperatures. For cities in subtropical climates (Shenzhen and Hong Kong), non-significant declines were found with high temperatures. Overall, females and the elderly demonstrated lower optimal temperatures for physical activity and larger decreases of step count in warmer temperatures. Conclusions: As minor reductions in physical activity could consequentially affect health, an increased awareness of temperature's impact on physical activity is necessary. City-wide adaptations and physical activity interventions should seek ways to sustain physical activity levels in the face of shifting temperatures from climate change. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The growing popularity of wearable physical activity (PA) monitors and fitness applications (apps) in recent years and the vast amounts of data that they generate present attractive possibilities for surveillance. However, measurement accuracy is indispensable when tracking PA variables to provide meaningful measures of PA. The purpose of this study was to examine the criterion validity of wearable PA monitors and a combination of GPS and accelerometer free of charge smartphone apps, during self-paced outdoor walking and running. Thirty-eight healthy adolescents (15.3±2.0 years) participated in this cross-sectional study. They were fitted with Garmin Forerunner 310XT, Garmin Vivofit, Medisana Vifit, and smartphones running the Runkeeper, Runtastic, Sports Tracker (GPS), Pedometer, Accupedo, Pedometer and Pedometer 2.0 (accelerometer) apps. They were asked to walk and run 1.22 km for each trial and two researchers counted every step taken during trials with a digital tally counter. Validity was evaluated by comparing each device with the criterion measure using Repeated measures analysis of variance (ANOVA), Mean Absolute Percentage Errors (MAPE) and Bland-Altman plots. MAPE were low for Forerunner and GPS apps for distance in both conditions (2.27%-9.73%), and significantly higher for the accelerometer monitors and apps (6.92%-39.02%). Vivofit (MAPE=6.51%) and Vifit (MAPE=6.66%) accurately estimated the number of steps during walking, however only Vivofit (MAPE=3.95%) was accurate during running. All accelerometer-based apps had high MAPE for step counting (9.87%-40.26%). The findings suggested that GPS monitors and apps were accurate tools for counting distance during walking and running, while accelerometer-based monitors and apps had higher errors. Vivofit provided accurate estimates of step count in both conditions, and Medisana Vifit was valid during walking. Accupedo was the only app with an acceptable step count error. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to explore the relationship between ambulatory distance with steps/day and increased step length as children age. Methods: This is a prospective cohort study. Forty-five children from the QUALITY cohort were assessed at childhood (baseline) and seven years later during adolescence (follow-up). Daily step count was evaluated by accelerometry, step length by a standardized test, and daily ambulatory distance was calculated based on step count and length. Results: Children grew by an average of 0.33 m from childhood to adolescence (p

ObjectivesThere are concerns regarding the accuracy of step count in Parkinson’s disease (PD) when wearable sensors are used. In this study, it was predicted that providing the normal rhythmicity of walking was maintained, the autocorrelation function used to measure step count would provide relatively low errors in step count.Materials and MethodsA total of 21 normal walkers (10 without PD) and 27 abnormal walkers were videoed while wearing a sensor [Parkinson’s KinetiGraph (PKG)]. Median step count error rates were observed to be

Background: Disturbances of glycemic control and large glycemic variability have been associated with increased risk of type 2 diabetes in the general population as well as complications in people with diabetes. Long-term health benefits of physical activity are well documented but less is known about the timing of potential short-term effects on glycemic control and variability in free-living conditions. Materials and Methods: We analyzed data from 85 participants without diabetes from the Food & You digital cohort. During a 2-week follow-up, device-based daily step count was studied in relationship to glycemic control and variability indices using generalized estimating equations. Glycemic indices, evaluated using flash glucose monitoring devices (FreeStyle Libre), included minimum, maximum, mean, standard deviation, and coefficient of variation of daily glucose values, the glucose management indicator, and the approximate area under the sensor glucose curve. Results: We observed that every 1000 steps/day increase in daily step count was associated with a 0.3588 mg/dL (95% confidence interval [CI]: -0.6931 to -0.0245), a 0.0917 mg/dL (95% CI: -0.1793 to -0.0042), and a 0.0022% (95% CI: -0.0043 to -0.0001) decrease in the maximum glucose values, mean glucose, and in the glucose management indicator of the following day, respectively. We did not find any association between daily step count and glycemic indices from the same day. Conclusions: Increasing physical activity level was linked to blunted glycemic excursions during the next day. Because health-related benefits of physical activity can be long to observe, such short-term physiological benefits could serve as personalized feedback to motivate individuals to engage in healthy behaviors. [ABSTRACT FROM AUTHOR]

Exercise capacity and physical activity are different concepts: the former refers to what an individual is capable of performing, while the latter refers to what the individual does in daily life. Low levels of physical activity (PA), which are very common in individuals with COPD, are associated with poor health outcomes, including increased symptoms, a more rapid decline in lung function, increased health care utilization and increased mortality risk. Because of these pervasive negative outcomes, attempts have been made to increase physical activity in individuals with COPD, hoping that success in this area will mitigate the negative effects of inactivity. Based on its ability to increase exercise capacity and reduce dyspnea in COPD and other chronic respiratory diseases, pulmonary rehabilitation (PR) would be expected also increase physical activity in these patients. However, accessibility to pulmonary rehabilitation programs is problematic in some areas, and studies testing its effectiveness in this outcome area have had inconsistent results. Using telehealth interventions using technology to provide medical care conveniently over a distance would have the benefit of reaching a larger proportion of individuals with COPD. A systematic review of clinical trials testing telehealth to promote physical activity had mixed results and low-certainty evidence, resulting in the inability to recommend any single type of intervention. Thus, using telehealth interventions to promote physical activity for individuals with chronic respiratory diseases, while promising, remains an area where future investigations are needed to identify its optimal modalities and clarify its benefits. [ABSTRACT FROM AUTHOR]

Self-monitoring may represent a mechanism to enhance physical activity among people with multiple sclerosis. To optimise activity monitoring as a behavioural tool to increase physical activity, user experience must be understood. This study evaluated user experience of the Yamax SW-200 Digi-walker pedometer in a group of people with MS. Semi-structured interviews were conducted with 15 adults who participated in a 12-week pedometer-supported behavioural change intervention, the iStep-MS trial. Interviews were audio-recorded and transcribed verbatim. Data were analysed using the Framework Method. An overarching theme Pedometers, the frustrating motivators captures the complex and often contradictory experience of the pedometer. Sub-themes include: Increasing activity awareness, which describes the pedometer's utility in raising activity consciousness; Numeric motivation provides insight into dual motivating and demotivating experiences of using an objective feedback device; (Un) usability focuses on practical concerns encountered in the day-to-day use of the monitor. The Yamax SW-200 Digi-walker raised awareness and enhanced participant motivation to engage in physical activity. Accuracy and usability concerns highlighted warrant consideration in the selection of this pedometer within a population with multiple sclerosis. Changing physical activity behaviour in people with MS: the iStep-MS trial; ISRCTN15343862; Use of self-monitoring tools such as pedometers can enhance physical activity awareness. Objective, numeric step count feedback is an effective motivational tool for physical activity. Accuracy and usability concerns may limit the value of the Yamax SW-200 Digiwalker for people with MS. Identification of individualised, reliable, usable and acceptable tools is important to ensure engagement with self-monitoring. [ABSTRACT FROM AUTHOR]

Background: The purpose of this study was to compare physical activity levels and the proportion of patients who met physical activity recommendations in patients with ankle osteoarthritis and controls.Methods: Ankle osteoarthritis patients (n = 50) and controls (n = 50) were recruited. physical activity was measured using an accelerometer-based monitor. Physical activity parameters, including the step count/day, the proportion of patients who met physical activity recommendations of ≥7000 steps/day, and moderate to vigorous physical activity minutes/day, were compared between the patient groups.Results: The patients with ankle osteoarthritis walked 3998 steps/day, while the controls walked 6531 steps/day (P < .001). Only 7 (14%) ankle osteoarthritis patients and 17 (34%) controls met the physical activity recommendations of ≥7000 steps/day (P =  .01). Time spent performing moderate to vigorous physical activity was 58 and 78 min/day in the ankle osteoarthritis and controls, respectively.Conclusions: The physical activity level of ankle osteoarthritis patients was lower than that of controls. Only a limited proportion of ankle osteoarthritis patients met the physical activity recommendation. [ABSTRACT FROM AUTHOR]

Noncommunicable diseases (NCDs) continue to be a global public health challenge for both developed and low and middle-income countries, with inactivity, overweight and obesity contributing to mortality. The study aimed to determine the body mass index (BMI), objectively measured physical activity (PA) levels, and socio-economic status (SES) of Zimbabwean adolescents and to establish the associations between their BMI and their PA and SES, and between their PA and their SES. Participants (N=126) aged 12-19 years were included in the study. BMI was classified according to the WHO BMI z-scores. Participants' PA levels were measured with a pedometer. SES was determined with the Family Affluence Scale III. The groups' mean BMI was 20.45 kg/m2, with 18.9% of the females and 11.5% of the males being overweight. The groups' mean average number of steps taken per day for seven days was 9 459, and their SES was classified as low. The association between the males, females and groups' BMI with their PA levels was insignificant, negative and weak. There was a significant positive, weak association between BMI and SES for the males (r = 0.289; p < 0.05) and the group (r = 0.227; p < 0.05). The association between the females' PA and their SES was significant, negative and weak (r = - 0.338; p < 0.05) with a significant, negative and moderate association between the males' PA and their SES (r = -0.448; p < 0.05). The higher the participants' BMI, the higher their SES, and the higher their PA levels, the lower their SES. [ABSTRACT FROM AUTHOR]

Abstract Background Physical activity (PA) in adolescence is crucial for lifelong healthy lifestyle, and attention is needed to adolescents at health risk due to insufficient PA. This study investigates the composition of weekly PA in adolescents by PA level and provides a rationale for change in their lifestyles. Methods The research was conducted at 66 schools in Poland between 2009 and 2016, among 949 girls and 650 boys aged 15–18 years. We used pedometers to monitor weekly PA with data assessed using the Indares web app. The participants were split into three groups by mean daily step count (lower, < 9000; middle, 9000–12,999; and higher, ≥ 13,000 steps/day), as a reliable and non-expensive indicator of PA. Results We did not observe statistically significant differences in composition of 7-day PA between participants with varying levels of PA, regardless of their gender (F (12,9558) = 0.60; p = 0.841; η p 2 > 0.000). The smallest differences in daily step counts by PA level were found on Mondays and the biggest on Fridays and Saturdays, in boys and girls; the differences between average school and average weekend days were most pronounced in less active girls (1677 steps/day) and boys (1886 steps/day). During the school week, the highest proportion of less active girls met the 11,000 steps/day recommendation on Fridays (21.9%), statistically significantly less than on other school days (p

Abstract Background Type 1 diabetes (T1D) has been increasing globally over the past three decades. Self-monitoring of blood glucose is a challenge in both developed as well as developing countries. Self-management guidelines include maintaining logbooks for blood glucose, physical activity, and dietary intake that affect glycated hemoglobin (HbA1c) and a multitude of life-threatening acute complications. Innovative, cost-effective interventions along with beneficial lifestyle modifications can improve home-based self-monitoring of blood glucose in T1D patients. The overall objective of this study is to evaluate the relationship between maintaining log books for blood glucose levels, reinforcement by e-messages, and/or daily step count and changes in HbA1c. Methods/design A randomized controlled trial will enroll participants aged 15 years and above in four groups. Each group of 30 participants will be working with a newly designed standard log book for documenting their blood glucose. The first group will be entirely on routine clinical care, the second group will be on routine care and will receive an additional e-device for recording step count (fit bit), the third group will receive routine care and daily motivational e-messages to maintain the log book, and the fourth group along with routine care will receive an e-device for measuring step count (fit bit) and e-messages about maintaining the log book. Patients will be enrolled from pediatric and endocrine clinics of a tertiary care hospital in Karachi. All groups will be followed up for a period of 6 months to evaluate outcomes. Log book data will be obtained every 3 months electronically or during a patient’s clinic visit. HbA1c as a main outcome will be measured at baseline and will be evaluated twice every 3 months. A baseline questionnaire will determine the socio-demographic, nutritional, and physical activity profile of patients. Clinical information for T1D and other co-morbidities for age of onset, duration, complications, hospitalizations, habits for managing T1D, and other lifestyle characteristics will be ascertained. Behavioral modifications for maintaining daily log books as a routine, following e-messages alone, fit bit alone, or e-messages plus using fit bit will be assessed for changes in HbA1c using a generalized estimated equation. Discussion The proposed interventions will help identify whether maintaining log books for blood glucose, motivational e-messages, and/or daily step count will reduce HbA1c levels. Trial registration ClinicalTrials.gov, NCT03864991 . March 6, 2019.

[Purpose] This study aimed to examine the characteristics of preoperative physical activity and its impact on the postoperative period in patients who underwent surgery for esophageal cancer. [Participants and Methods] The participants were 30 patients who were diagnosed with esophageal cancer, underwent surgery, and fulfilled their conditions. Preoperative physical activity was measured using the step count, and metabolic equivalents as the amount of physical activity. We examined the relationships between preoperative step count and METs, patient demographics, treatment-related factors, preoperative physical function, and activities of daily living. Moreover, we examined the relationships of preoperative step count and METs with postoperative mobilization, physical activity, physical function, and activities of daily living. [Results] Preoperative step count was related to age, Glasgow prognostic score, and preoperative functional independence and associated with step count on postoperative days 7-13, METs on postoperative days 7-9, 6-min walking distance, and functional independence measures at discharge. [Conclusion] Improving the nutritional status and increasing preoperative physical activity by walking for esophageal cancer may help improve physical activity after postoperative day 7, exercise tolerance, and activities of daily after discharge., Competing Interests: There are no conflicts of interest to disclose., (2024©by the Society of Physical Therapy Science. Published by IPEC Inc.)

Introduction: Very few studies have examined patterns of physical activity (PA) during a pulmonary rehabilitation (PR) program in people with COPD., Aims: To compare the patterns of PA in: 1) the week before commencing PR (pre-PR) with a week during PR (PR week); 2) PR days and non-PR days during a PR week; 3) pre-PR and the week following PR completion (post-PR)., Methods: This was a multicenter, prospective cohort study. Participants attended twice weekly supervised PR for 8-12 weeks. Daily step count (primary outcome), time in light activities, time in moderate to vigorous PA (MVPA), total sedentary time and sit-to-stand (STS) transitions were measured using a thigh worn accelerometer for seven days, at each assessment time point: pre-PR, PR week and post-PR., Results: 29 participants, mean age (SD) 69years(7), FEV 1 53%pred(16). The PR week compared to pre-PR, showed higher daily: step count (mean difference (95%CI)), 941steps(388-1494); and MVPA, 11mins(6-15), with no difference in: time in light activities, -1min(-6-5); total sedentary time, 7mins(-21-36); or STS transitions, 0(-5-6). PR days compared to non-PR days showed higher: step count, 2810steps(1706-3913); time in light activities 11mins(1-20); time in MVPA, 27mins(17-35) and STS transitions, 8(4-12), with no difference in total sedentary time: -33mins(-80-15). There were no differences in any PA measures post-PR compared to pre-PR (p < 0.05)., Conclusion: Daily step count and time spent in MVPA increased significantly during the PR week, solely due to increased PA on days participants attended PR., Competing Interests: Declaration of competing interest There is no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Older adults living in retirement communities are an understudied population, and the association between their motivation and daily physical activity is unknown. We recruited participants (n = 173) living in a retirement community who completed the Behavioral Regulation in Exercise Questionnaire-2 and wore an activPAL accelerometer to evaluate this relationship. Participants had a median age of 81 years and demonstrated low levels of daily activity with an average step count of 3,637 (±1,965) steps per day and 52 (±25) min of daily stepping time. External motivation was negatively associated with the square root of daily step count (β = -4.57; p < .001) and square root of daily stepping time (β = -0.49; p < .001). Older adults living in retirement communities demonstrated low levels of daily activity, with a negative association between external motivation and daily activity. Strategies are needed to make an active lifestyle supportive and enticing for older adults in these communities.

Background/objectives: Few studies have investigated associations between the motivational outcome based on physical activity (PA) affective experiences (i.e., attraction vs. antipathy toward PA) and behavior. This study investigated cross-sectional and longitudinal associations between attraction (vs. antipathy) toward PA and device-based PA in older adults., Methods: Older adults (n = 139; 71% female, Mage = 70.5) completed assessments of attraction (vs. antipathy) toward PA and 14 days of device-based accelerometry at Times 1 and 2., Results: Greater attraction toward PA at Time 1 was associated with greater steps (β = 5.31, p < .01) and moderate to vigorous intensity PA (β = 3.08, p < .05) at Time 1. Greater attraction toward PA at Time 1 was not significantly associated with steps or moderate to vigorous intensity PA at Time 2., Conclusion: Greater emphasis on resultant motivation from PA affective experiences may be useful in promoting PA in older adults. Significance/Implications: In spite of mixed findings in the present study, there is strong evidence that positive affective responses during a single bout of PA play an important role in predicting future engagement. Yet, affective experiences during PA can be individualistic and often influenced by contextual factors. Interventions designed to increase PA should focus on factors that may create positive affective experiences for participants.