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[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.

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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 (ß = 5.31, p < .01) and moderate to vigorous intensity PA (ß = 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.

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Background: Kaempferol (KMP), a flavonoid in edible plants, exhibits diverse pharmacological effects. Growing body of evidence associates extended lifespan with physical activity (PA) and sleep, but KMP's impact on these behaviors is unclear. This double-blind, placebo-controlled, crossover trial assessed KMP's effects on PA and sleep. Methods: A total of 33 city workers (17 males and 16 females) participated in this study. They were randomly assigned to take either 10 mg of KMP or placebo for 2 weeks in the order allocated, with a 7-day washout period in between. All participants wore an accelerometer-based wearable device (Fitbit Charge 4), which monitored daily PA, heart rate (HR), and HR variability during sleep. Results: The duration of wearing the device was 23.73 ± 0.04 h/day. HR decreased in each PA level, and the mean daily step count and distance covered increased significantly during KMP intake compared to placebo. The outing rate, number of trips, number of recreational activities, and time spent in recreation on weekends increased. Sleep quality improved following KMP intake. The decrease in HR and increase in RMSSD may be important in mediating the effects of these KMPs. Conclusion: KMP leads to behavioral changes that subsequently improve sleep quality and potentially improve long-term quality of life. Clinical Trial Registration: https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000048447, UMIN000042438.

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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 (ß = -4.57; p < .001) and square root of daily stepping time (ß = -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.

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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), FEV1 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.

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PURPOSE: The aim of this study is to determine the validity of consumer grade step counter devices during the early recovery period after knee replacement surgery. METHODS: Twenty-three participants wore a Fitbit Charge or Apple Watch Series 4 smart watch and performed a walking test along a 50-metre hallway. There were 9 males and 14 females included in the study with an average age of 68.5 years and BMI of 32. Each patient wore both the Fitbit Charge and Apple Watch while completing the walking test and an observer counted the ground truth value using a thumb-push tally counter. This test was repeated pre-operatively with no gait aid, immediately post operatively with a walker, at 6 weeks follow up with a cane and at 6 months with no gait aid. Bland-Altman plots were performed for all walking tests to compare the agreement between measurement techniques. RESULTS: Mean overall agreement of step count for pre-operative and at 6 months for subjects walking without gait aids was excellent for both the Apple Watch vs. actual and Fitbit vs. actual with bias values ranging from - 0.87 to 1.36 with limits of agreement (LOA) ranging between - 10.82 and 15.91. While using a walker both devices showed extremely little agreement with the actual step count with bias values between 22.5 and 24.37 with LOA between 11.7 and 33.3. At 6 weeks post-op while using a cane, both the Apple Watch and Fitbit devices had a range of bias values between - 2.8 and 5.73 with LOA between - 13.51 and 24.97. CONCLUSIONS: These devices show poor validity in the early post operative setting, especially with the use of gait aids, and therefore results should be interpreted with caution.

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OBJECTIVE: This study aimed to describe the variability in estimates of the association of daily steps and all-cause mortality in systematic reviews with meta-analyses, to identify the factors potentially responsible for it, and to provide an updated estimate. METHODS: Five databases were systematically searched up to May 2024 to identify systematic reviews with meta-analyses and prospective cohort studies. A qualitative synthesis of previous reviews and an updated meta-analysis of cohort studies were performed. Pooled hazard ratios (HRs) with their 95% confidence intervals (CIs) were calculated using a random-effects model. RESULTS: Eleven systematic reviews with meta-analyses and 14 cohort studies were included, revealing considerable variability in result presentation. Our updated meta-analysis showed a nonlinear association, indicating a lower risk of all-cause mortality with increased daily steps, with a protective threshold at 3143 steps/day, and a pooled HR of 0.91 (95% CI: 0.87, 0.95) per 1000 steps/day increment. Physical activity categories consistently indicated progressively reduced mortality risk, with the highly active category (>12,500 steps/day) exhibiting the lowest risk (0.35 (95% CI: 0.29, 0.42)). CONCLUSION: Systematic reviews and meta-analyses showed considerable variability in effect estimates due to different methods of quantifying exposure. Despite it, our study underscores the importance of increased daily steps in reducing all-cause mortality, with a minimum protective dose of 3000 steps/day, although the optimal dose differed according to age and sex. It is recommended that future studies categorise daily steps by physical activity category, perform dose-response analyses, and use increments of 1000 steps/day.

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With the increased push for personalized medicine, researchers and clinicians have begun exploring the use of wearable sensors to track patient activity. These sensors typically prioritize device life over robust onboard analysis, which results in lower accuracies in step count, particularly at lower cadences. To optimize the accuracy of activity-monitoring devices, particularly at slower walking speeds, proven methods must be established to identify suitable settings in a controlled and repeatable manner prior to human validation trials. Currently, there are no methods for optimizing these low-power wearable sensor settings prior to human validation, which requires manual counting for in-laboratory participants and is limited by time and the cadences that can be tested. This article proposes a novel method for determining sensor step counting accuracy prior to human validation trials by using a mechanical camshaft actuator that produces continuous steps. Sensor error was identified across a representative subspace of possible sensor setting combinations at cadences ranging from 30 steps/min to 110 steps/min. These true errors were then used to train a multivariate polynomial regression to model errors across all possible setting combinations and cadences. The resulting model predicted errors with an R2 of 0.8 and root-mean-square error (RMSE) of 0.044 across all setting combinations. An optimization algorithm was then used to determine the combinations of settings that produced the lowest RMSE and median error for three ranges of cadence that represent disabled low-mobility ambulators, disabled high-mobility ambulators, and healthy ambulators (30-60, 20-90, and 30-110 steps/min, respectively). The model identified six setting combinations for each range of interest that achieved a ±10% error in cadence prior to human validation. The anticipated range of errors from the optimized settings at lower walking speeds are lower than the reported errors of wearable sensors (±30%), suggesting that pre-human-validation optimization of sensors may decrease errors at lower cadences. This method provides a novel and efficient approach to optimizing the accuracy of wearable activity monitors prior to human validation trials.

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OBJECTIVE: Individuals with chronic pain due to knee osteoarthritis (OA) are insufficiently physically active, and alterations of facilitatory and inhibitory nociceptive signaling are common in this population. Our objective was to examine the association of these alterations in nociceptive signaling with objective accelerometer-based measures of physical activity in a large observational cohort. DESIGN: We used data from the Multicenter Osteoarthritis Study. Measures of peripheral and central pain sensitivity included pressure pain threshold at the knee and mechanical temporal summation at the wrist, respectively. The presence of descending pain inhibition was assessed by conditioned pain modulation (CPM). Physical activity was quantitatively assessed over 7 days using a lower back-worn activity monitor. Summary metrics included steps/day, activity intensity, and sedentary time. Linear regression analyses were used to evaluate the association of pain sensitivity and the presence of descending pain inhibition with physical activity measures. RESULTS: Data from 1873 participants was analyzed (55.9% female, age = 62.8 ± 10.0 years). People having greater peripheral and central sensitivity showed lower step counts. CPM was not significantly related to any of the physical activity measures, and none of the exposures were significantly related to sedentary time. CONCLUSIONS: In this cohort, greater peripheral and central sensitivity were associated with reduced levels of objectively-assessed daily step counts. Further research may investigate ways to modify or treat heightened pain sensitivity as a means to increase physical activity in older adults with knee OA.

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While physical activity (PA) is understood to promote vascular health, little is known about whether the daily and weekly patterns of PA accumulation associate with vascular health. Accelerometer-derived (activPAL3) 6- or 7-day stepping was analyzed for 6430 participants in The Maastricht Study (50.4% women; 22.4% Type 2 diabetes mellitus (T2DM)). Multivariable regression models examined associations between stepping metrics (average step count, and time spent slower and faster paced stepping) with arterial stiffness (measured as carotid-femoral pulse wave velocity (cfPWV)), and several indices of microvascular health (heat-induced skin hyperemia, retinal vessel reactivity and diameter), adjusting for confounders and moderators. PA pattern metrics were added to the regression models to identify associations with vascular health beyond that of stepping metrics. Analyses were stratified by T2DM status if an interaction effect was present. Average step count and time spent faster paced stepping was associated with better vascular health, and the association was stronger in those with compared to those without T2DM. In fully adjusted models a higher step count inter-daily stability was associated with a higher (worse) cfPWV in those without T2DM (std ß = 0.04, p = 0.007) and retinal venular diameter in the whole cohort (std ß = 0.07, p = 0.002). A higher within-day variability in faster paced stepping was associated with a lower (worse) heat-induced skin hyperemia in those with T2DM (std ß = -0.31, p = 0.008). Above and beyond PA volume, the daily and weekly patterns in which PA was accumulated were additionally associated with improved macro- and microvascular health, which may have implications for the prevention of vascular disease.

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Shoe-based wearable sensor systems are a growing research area in health monitoring, disease diagnosis, rehabilitation, and sports training. These systems-equipped with one or more sensors, either of the same or different types-capture information related to foot movement or pressure maps beneath the foot. This captured information offers an overview of the subject's overall movement, known as the human gait. Beyond sensing, these systems also provide a platform for hosting ambient energy harvesters. They hold the potential to harvest energy from foot movements and operate related low-power devices sustainably. This article proposes two types of strategies (Strategy 1 and Strategy 2) for an energy-autonomous shoe-based system. Strategy 1 uses an accelerometer as a sensor for gait acquisition, which reflects the classical choice. Strategy 2 uses a piezoelectric element for the same, which opens up a new perspective in its implementation. In both strategies, the piezoelectric elements are used to harvest energy from foot activities and operate the system. The article presents a fair comparison between both strategies in terms of power consumption, accuracy, and the extent to which piezoelectric energy harvesters can contribute to overall power management. Moreover, Strategy 2, which uses piezoelectric elements for simultaneous sensing and energy harvesting, is a power-optimized method for an energy-autonomous shoe system.

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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. CONCLUSION: A wide range of health outcomes can benefit from the right number of steps.

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[This corrects the article DOI: 10.3389/fpubh.2023.1190464.].

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Although sleep quality and physical activity (PA) may influence on arterial stiffness, the combined effects of these two factors on arterial stiffness remain unknown. A total of 103 healthy middle-aged and older men and women (aged 50-83 years) with no history of cardiovascular disease and depression were included in this study. Arterial stiffness was measured using carotid-femoral pulse wave velocity (cfPWV), brachial-ankle PWV (baPWV), and femoral-ankle PWV (faPWV). Poor sleepers were defined as those with a Pittsburgh Sleep Quality Index score of >5.5. Using an accelerometer for seven consecutive days, low levels of PA were defined as low moderate-to-vigorous-intensity PA (MVPA) <19.0 min/day and low step counts <7100 steps/day, respectively. Poor sleepers with low PA levels, as determined by MVPA and daily steps, showed higher cfPWV, but not faPWV or baPWV, in middle-aged and older adults. Furthermore, in the analysis of covariance (ANCOVA) analyses adjusted for age, obesity, dyslipidemia, and sedentary behavior, the cfPWV result remained significant. Our study revealed that the coexistence of poor sleep quality and decreased PA (low MVPA or daily steps) might increase central arterial stiffness in middle-aged and older adults. Therefore, adequate sleep (good and sufficient sleep quality) and regular PA, especially at appropriate levels of MVPA (i.e., at least of 7100 steps/day), should be encouraged to decrease central arterial stiffness in middle-aged and older adults.

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AIMS/HYPOTHESIS: Adults with type 1 diabetes should perform daily physical activity to help maintain health and fitness, but the influence of daily step counts on continuous glucose monitoring (CGM) metrics are unclear. This analysis used the Type 1 Diabetes Exercise Initiative (T1DEXI) dataset to investigate the effect of daily step count on CGM-based metrics. METHODS: In a 4 week free-living observational study of adults with type 1 diabetes, with available CGM and step count data, we categorised participants into three groups-below (<7000), meeting (7000-10,000) or exceeding (>10,000) the daily step count goal-to determine if step count category influenced CGM metrics, including per cent time in range (TIR: 3.9-10.0 mmol/l), time below range (TBR: <3.9 mmol/l) and time above range (TAR: >10.0 mmol/l). RESULTS: A total of 464 adults with type 1 diabetes (mean±SD age 37±14 years; HbA1c 48.8±8.1 mmol/mol [6.6±0.7%]; 73% female; 45% hybrid closed-loop system, 38% standard insulin pump, 17% multiple daily insulin injections) were included in the study. Between-participant analyses showed that individuals who exceeded the mean daily step count goal over the 4 week period had a similar TIR (75±14%) to those meeting (74±14%) or below (75±16%) the step count goal (p>0.05). In the within-participant comparisons, TIR was higher on days when the step count goal was exceeded or met (both 75±15%) than on days below the step count goal (73±16%; both p<0.001). The TBR was also higher when individuals exceeded the step count goals (3.1%±3.2%) than on days when they met or were below step count goals (difference in means -0.3% [p=0.006] and -0.4% [p=0.001], respectively). The total daily insulin dose was lower on days when step count goals were exceeded (0.52±0.18 U/kg; p<0.001) or were met (0.53±0.18 U/kg; p<0.001) than on days when step counts were below the current recommendation (0.55±0.18 U/kg). Step count had a larger effect on CGM-based metrics in participants with a baseline HbA1c ≥53 mmol/mol (≥7.0%). CONCLUSIONS/INTERPRETATION: Our results suggest that, compared with days with low step counts, days with higher step counts are associated with slight increases in both TIR and TBR, along with small reductions in total daily insulin requirements, in adults living with type 1 diabetes. DATA AVAILABILITY: The data that support the findings reported here are available on the Vivli Platform (ID: T1-DEXI; https://doi.org/10.25934/PR00008428 ).

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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. CONCLUSION: 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.

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OBJECTIVES: Commercially available wearable activity monitors can promote physical activity behaviour. Clinical trials typically quantify physical activity with research grade activity monitors prior to testing interventions utilising commercially available wearable activity monitors aimed at increasing step count. Therefore, it is important to test the agreement of these two types of activity monitors. OBJECTIVES: Observational. METHODS: Thirty adults (20-65 years, n = 19 females) were provided a Fitbit Charge 4©. To determine reliability using an intraclass correlation coefficient, two, one-minute bouts of treadmill walking were performed at a self-selected pace. Subsequently, participants wore both an ActiGraph wGT3X-BT and the Fitbit for seven days. To determine agreement, statistical equivalence and the mean absolute percentage error were calculated and represented graphically with a Bland-Altman plot. Ordinary least products regression was performed to identify fixed or proportional bias. RESULTS: The Fitbit showed 'good' step count reliability on the treadmill (intraclass correlation coefficient = 0.75, 95 % CI = 0.53-0.87, p < 0.001). In free-living however, it overestimated step count when compared to the ActiGraph wGT3X-BT (mean absolute percentage error = 26.02 % ±â€¯14.63). Measurements did not fall within the ± 10 % equivalence region and proportional bias was apparent (slope 95 % CI = 1.09-1.35). CONCLUSIONS: The Fitbit Charge 4© is reliable when measuring step count on a treadmill. However, there is an overestimation of daily steps in free-living environments which may falsely indicate compliance with physical activity recommendations.

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Background and Objectives: Mild cognitive impairment (MCI) is an early stage of dementia in which everyday tasks can be maintained; however, notable challenges may occur in memory, focus, and problem-solving skills. Therefore, motor-cognitive dual-task training is warranted to prevent cognitive decline and improve cognition in aging populations. This study aimed to determine the influence of such dual-task activities during straight and curved walking on the activities of the prefrontal cortex and associated gait variables in older adults with MCI. Materials and Methods: Twenty-seven older adults aged ≥65 years and identified as having MCI based on their scores (18-23) on the Korean Mini-Mental State Examination were enrolled. The participants performed four task scenarios in random order: walking straight, walking straight with a cognitive task, walking curved, and walking curved with a cognitive task. The activation of the prefrontal cortex, which is manifested by a change in the level of oxyhemoglobin, was measured using functional near-infrared spectroscopy. The gait speed and step count were recorded during the task performance. Results: Significant differences were observed in prefrontal cortex activation and gait variables (p < 0.05). Specifically, a substantial increase was observed in prefrontal cortex activation during a dual task compared with that during a resting-state (p < 0.013). Additionally, significant variations were noted in the gait speed and step count (p < 0.05). Conclusions: This study directly demonstrates the impact of motor-cognitive dual-task training on prefrontal cortex activation in older adults with MCI, suggesting the importance of including such interventions in enhancing cognitive function.

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BACKGROUND: Established health-related quality of life scores do not consider both subjective and objective indices of health. We propose the subjective and objective quality of life score (SOQOL) for the comprehensive assessment of health-related quality of life and aim to provide normative population data. The SOQOL is compatible with smartphone applications, allowing widespread use on a global scale. METHODS: Normative SOQOL population data was sourced from pre-existing datasets on the EQ-5D-5L, daily step count, and walking speed. Normative values were calculated using weighted grand means. We trialled the SOQOL in a group of five patients presenting to a spinal neurosurgery clinic. RESULTS: SOQOL scores decreased with age, and women had lower scores in every age group. In our case series, the spine patients with the biggest SOQOL deficit compared to age- and sex-matched population averages were found to be surgical while the rest were non-surgical. CONCLUSIONS: The SOQOL shows promise as a simple and effective scoring tool that is compatible with smartphones, potentially useful for screening in primary and specialized care settings, and for assessment following healthcare interventions. This study, however, is preliminary, and the findings are primarily suggestive. They underline the necessity for future, more comprehensive studies to validate and expand upon these initial observations. The conclusion of both this abstract and the full paper will clearly state these limitations and the preliminary nature of the study.

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Although walking has proven efficacy for glycemic control, patients struggle to meet daily step goals. This secondary analysis investigated the effect of step count measurement rate on glycemic control. Patients with type 2 diabetes from eight hospitals in Japan participated in a 12-month randomized controlled trial. The intervention group received DialBetesPlus, a self-management support system that allowed patients to monitor step count using a pedometer. We divided the intervention group into two groups based on whether daily step count measurement rate (the percentage of days with pedometer use) increased or decreased during the last three months of the intervention (month 10-12), relative to the first three months of the intervention (month 1-3). Patients with a reduced measurement rate experienced a worsening in glycemic control, with between-group difference of 0.516% in the amount of change in HbA1c (p=0.012). We conclude that step count measurement may lead to a better glycemic profile.

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