Comparison of Pedometer and Accelerometer Measures of Physical Activity in Preschool Children

2007 ◽  
Vol 19 (2) ◽  
pp. 205-214 ◽  
Author(s):  
Greet Cardon ◽  
Ilse De Bourdeaudhuij
Keyword(s):  
Physical Activity ◽  
Preschool Children ◽  
Vigorous Physical Activity ◽  
Step Count ◽  
Activity Levels ◽  
Accelerometer Data ◽  
Strongly Correlated ◽  
Daily Step ◽  
Step Counts ◽  
Daily Step Count

In this study, daily step counts were recorded for 4 consecutive days in 129 four- and five-year-old children. To compare daily Yamax Digiwalker step counts with minutes of engagement in moderate to vigorous physical activity (MVPA), concurrent accelerometer data were collected in a random subsample (n = 76). The average daily step count was 9,980 (± 2,605). Step counts and MVPA minutes were strongly correlated (r = .73, p < .001). The daily step count of 13,874, equating to 1-hr MVPA engagement, was reached by 8% of the children. Daily step counts in preschool children give valid information on physical activity levels—daily step counts in preschoolers are low.

A Pilot Study Comparing Pedometer Counts with Reported Physical Activity in Elementary Schoolchildren

2004 ◽  
Vol 16 (4) ◽  
pp. 355-367 ◽  
Author(s):  
Greet Cardon ◽  
Ilse De Bourdeaudhuij
Keyword(s):  
Physical Activity ◽  
Pilot Study ◽  
Vigorous Physical Activity ◽  
Step Count ◽  
Regression Equations ◽  
Moderate Correlation ◽  
Daily Step ◽  
Step Counts ◽  
Daily Step Count

In this study pedometer counts were recorded for 6 consecutive days for 92 children (mean age = 9.6 years; range 6.5–12.7) and were compared with the number of minutes per day in which the participants engaged in moderate-to-vigorous physical activity (MVPA). Diaries filled out with the assistance of one of the children’s parents were used to determine minutes of MVPA. The average daily step count was significantly higher in boys than in girls, although the average daily MVPA engagement in minutes did not vary significantly between genders. Based on the regression equations, 60 min of MVPA was equivalent to 15,340 step counts in boys, 11,317 step counts in girls, and 13,130 step counts when results for both genders were combined. A moderate correlation (r = .39, p < .001) was found between pedometer step counts and reported minutes of MVPA. According to the present study findings, however, predictions and promotion of daily MVPA engagement in children based on pedometer counts per day should be made with caution.

scholarly journals AB1320-HPR THE ASSOCIATION BETWEEN PHYSICAL ACTIVITY AND CARDIORESPIRATORY FITNESS IN PATIENTS WITH RHEUMATOID ARTHRITIS AND HIGH CARDIOVASCULAR RISK

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1949.2-1950
Author(s):  
J. Van den Hoek ◽  
M. Van der Leeden ◽  
G. Metsios ◽  
G. Kitas ◽  
H. Jorstad ◽  
...  
Keyword(s):  
Physical Activity ◽  
Cardiovascular Disease ◽  
Cardiorespiratory Fitness ◽  
Vigorous Physical Activity ◽  
Step Count ◽  
Activity Levels ◽  
Daily Step ◽  
Research Support ◽  
Daily Step Count ◽  
The Mean

Background:Rheumatoid arthritis (RA) is associated with increased risk of cardiovascular disease (CVD) disease and CV mortality1. High values of cardiorespiratory fitness (CRF) are protective against CVD and CV mortality2. Physical activity levels in patients with RA are low. Knowledge on whether physical activity is associated with CRF in patients with RA and high CV risk is scarce. This knowledge is important because improving the level of physical activity could improve CRF and lower CV risk in this group of patients with RA and high CV risk. However, it is unclear whether physical activity is associated with CRF in this group of patients. This study presents the preliminary results at baseline of the association of physical activity with CRF from an ongoing pilot study aimed at improving CRF through exercise therapy in patients with RA and high CV risk.Objectives:To determine (i) the level of physical activity in patients with RA and high CV risk and (ii) whether physical activity is associated with CRF in patients with RA and high CV risk.Methods:Patients with RA and high CV risk participated in this pilot study. Increased 10-year risk of CV mortality was determined by using the Dutch SCORE-table. Anthropometrics and disease characteristics were collected. Physical activity was assessed with an Actigraph accelerometer to determine the number of steps and intensity of physical activity expressed in terms of sedentary, light, and moderate-to-vigorous time per day. Participants wore the accelerometer for seven days. A minimum of four measurement days with a wear time of at least 10 hours was required. The VO2max measured with a graded maximal exercise test was used to determine the CRF. Pearson correlation coefficients were calculated for the associations between the different measures of physical activity and VO2max. For the variables that were associated, linear regression analysis was carried out, with pain and disease activity as possible confounders.Results:Thirteen females and five males were included in the study. The mean age was 66.5 (± 15.0) years. Only 22% of the patients met public health physical activity guidelines for the minimal amount of 150 minutes a week. The mean step count was 6237 (± 2297) steps per day and mean moderate-to-vigorous physical activity time was 16.50 (± 23.56) minutes per day. The median VO2max was 16.23 [4.63] ml·kg-1·min-1, which is under the standard. Pearson correlations showed a significant positive association for step count with VO2max. No associations were found for sedentary, light, and moderate-to-vigorous physical activity with VO2max. The significant association between step count and VO2max(p = 0.01) was not confounded by disease severity and pain.Discussion:Since better CRF protects against CVD, increasing daily step count may be a simple way to reduce the risk of CVD in patients with RA and high CV risk. However, these results need to be confirmed in a larger study group. Future research should investigate if improving daily step count will lead to better CRF levels and ultimately will lead to a reduction in CV risk in patients with RA and high CV risk.Conclusion:Physical activity levels of patients with RA and high CV risk do not meet public health requirements for physical activity criteria and the VO2max was under the standard. Step count is positively associated with CRF.References:[1]Agca et al. Atherosclerotic cardiovascular disease in patients with chronic inflammatory joint disorders. Heart. 2016;102(10):790-795.[2]Lemes et al. Cardiorespiratory fitness and risk of all-cause, cardiovascular disease, and cancer mortality in men with musculoskeletal conditions. J Phys Act Health. 2019;16;134-140.Disclosure of Interests:Joëlle van den Hoek: None declared, Marike van der Leeden: None declared, George Metsios: None declared, Georeg Kitas: None declared, Harald Jorstad: None declared, WIllem Lems Grant/research support from: Pfizer, Consultant of: Lilly, Pfizer, Michael Nurmohamed Grant/research support from: Not related to this research, Consultant of: Not related to this research, Speakers bureau: Not related to this research, Martin van der Esch: None declared

scholarly journals Prediction of Optimal Daily Step Count Achievement from Segmented School Physical Activity

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Ryan D. Burns ◽  
Timothy A. Brusseau ◽  
James C. Hannon
Keyword(s):  
Physical Activity ◽  
Activity Patterns ◽  
Step Count ◽  
Activity Levels ◽  
Daily Step ◽  
Step Counts ◽  
School Aged Children ◽  
Daily Step Count ◽  
Generalized Linear Mixed Effects ◽  
Predictive Relationship

Optimizing physical activity in childhood is needed for prevention of disease and for healthy social and psychological development. There is limited research examining how segmented school physical activity patterns relate to a child achieving optimal physical activity levels. The purpose of this study was to examine the predictive relationship between step counts during specific school segments and achieving optimal school (6,000 steps/day) and daily (12,000 steps/day) step counts in children. Participants included 1,714 school-aged children (mean age =9.7±1.0years) recruited across six elementary schools. Physical activity was monitored for one week using pedometers. Generalized linear mixed effects models were used to determine the adjusted odds ratios (ORs) of achieving both school and daily step count standards for every 1,000 steps taken during each school segment. The school segment that related in strongest way to a student achieving 6,000 steps during school hours was afternoon recess (OR = 40.03;P<0.001) and for achieving 12,000 steps for the entire day was lunch recess (OR = 5.03;P<0.001). School segments including lunch and afternoon recess play an important role for optimizing daily physical activity in children.

Abstract P178: Pedometer Feedback Intervention Increases Time Spent in Moderate-to-Vigorous Physical Activity in Cardiac Rehabilitation Patients

Circulation ◽  
2013 ◽  
Vol 127 (suppl_12) ◽  
Author(s):  
Cemal Ozemek ◽  
Wonwoo Byun ◽  
Katrina Riggin ◽  
Scott Strath ◽  
Leonard Kaminsky
Keyword(s):  
Physical Activity ◽  
Cardiac Rehabilitation ◽  
Vigorous Physical Activity ◽  
Activity Level ◽  
Step Count ◽  
Intensity Level ◽  
Activity Levels ◽  
Daily Step ◽  
Light Physical Activity ◽  
Step Counts

Introduction: Pedometer feedback with step goals has previously been demonstrated to be effective in increasing daily steps in cardiac rehabilitation patients. These monitors allow the individual to track steps taken during a day, which may influence the frequency or duration of structured physical activity that is intended to achieve a step goal. However, it is not known whether an increase in step counts by pedometer feedback with step goals also increases time spent in recommended intensity levels for improved health, specifically moderate-to vigorous physical activity (MVPA), in cardiac rehabilitation patients. Hypothesis: Pedometer feedback with weekly step goals will increase time spent in MVPA, mediated by an increase in step counts in cardiac rehabilitation patients. Methods: A total of 31 (22 men and 9 women, age 62 ± 9 years) patients participated in a 12-week maintenance cardiac rehabilitation, pedometer based step goal intervention. Prior to the intervention, each subject’s one week baseline average daily step count was measured and 10% of this value was used to increase step goals during the intervention. Each week the step goal was met, the following week’s goal was appropriately increased. However, if the step goal for the week was not achieved, the step goal would not increase until the goal was fulfilled. Additionally, daily step counts and time spent in MVPA and light physical activity were assessed at baseline (without pedometer feedback) and for each intervention week (with pedometer feedback) using a Kenz Lifecorder PLUS monitor (Nagoya, Japan). Average time spent in light physical activity (activity level of 1-2) and MVPA (activity levels ≥3), were determined according to activity intensity level defined by the manufacturer’s analyses program. Results: The average step count for the baseline week was 5546 ± 2679 steps/day which significantly increased to 8348± 3613 steps/day by week 12 (p<0.01). The average time spent in MVPA also significantly increased (p<0.01) from 19 ± 16 min/day at baseline to 38 ± 23 min/day at week 12. In addition, there was a significant increase (p<0.05) in time spent in light physical activity from baseline (42 ± 18 min/day) to week 12 (51 ± 24 min/day). Conclusion: Findings of this study demonstrate that a 12-week pedometer feedback-based intervention was effective in increasing time spent in MVPA in maintenance cardiac rehabilitation patients. Cardiac rehabilitation facilities can utilize pedometer feedback and goal setting to promote increases in time spent in recommended activity levels previously associated with improved health outcomes.

Using consumer-grade physical activity trackers to measure frailty progression in critical care survivors: An exploratory observational study (Preprint)

2020 ◽  
Author(s):  
Ben Kim ◽  
Miranda Hunt ◽  
John Muscedere ◽  
David M Maslove ◽  
Joon Lee
Keyword(s):  
Physical Activity ◽  
Critical Illness ◽  
Observational Study ◽  
Wearable Devices ◽  
Step Count ◽  
Wearable Device ◽  
Strongly Correlated ◽  
Daily Step ◽  
Daily Step Count

BACKGROUND Critical illness has been suggested as a sentinel event for frailty development for at-risk older adults. Frail critical illness survivors suffer increased adverse health outcomes but monitoring the recovery post-Intensive Care Unit (ICU) is challenging. Clinicians and funders of healthcare system envision an increased role of wearable devices in monitoring clinically relevant measures as the sensor technology is advancing rapidly. Use of wearable devices also generated great interest among older patients and they are the fastest growing group of consumer-grade wearable device users. Recent research studies indicate that consumer-grade wearable devices offer a possibility of measuring frailty. OBJECTIVE To examine the data collected from wearable devices for the progression of frailty among the critical illness survivors. METHODS An observational study was conducted with 12 critical illness survivors from Kingston General Hospital in Canada. Frailty was measured by Clinical Frailty Scale (CFS) at ICU admission (AD), hospital discharge (DC), and 4-week follow-up (FU). Wearable device was worn between DC and FU. The wearable device collected data on steps, physical activity, sleep and heart rate (HR). Patient assessments were reviewed including the severity of illness, cognition level, delirium, activities of daily living, and comorbidity. RESULTS The CFS increased significantly following critical illness compared pre-ICU frailty level (P=.02, d=-0.53). Frail survivors over the 4-week follow-up period had significantly lower daily step counts than non-frail survivors (P=.02, d=1.81). There was no difference in sleep and HR measures. Daily step count was strongly correlated with the CFS at FU (r=-0.72, P=.04). Average HR was strongly correlated with the CFS at DC (r=-0.72, P=.046). HR standard deviation was strongly correlated (r=0.78, P<0.05) with the CFS change from AD to FU. No assocation was found between the CFS and sleep measures. The pattern of increasing step count over the FU period was correlated with the worsening of frailty (r=.62, P=.03). CONCLUSIONS This study demonstrated association between frailty and data generated from a consumer-grade wearable device. Daily step count and HR showed strong association with the frailty progression of the critical illness survivors over time. Understanding this assocation could unlock a new avenue for clinicians to monitor and identify a vulnerable subset of the population that might benefit from an early intervention. CLINICALTRIAL

scholarly journals P0648LEVELS OF PHYSICAL ACTIVITY FOLLOWING AN EPISODE OF STAGE 3 AKI ARE ASSOCIATED WITH RENAL RECOVERY

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Anam Asad ◽  
Maurice Dungey ◽  
Katherine Hull ◽  
James Burton ◽  
Daniel March
Keyword(s):  
Physical Activity ◽  
Renal Function ◽  
Functional Capacity ◽  
Step Count ◽  
Renal Recovery ◽  
Activity Levels ◽  
Daily Step ◽  
Exercise Interventions ◽  
Physical Activity Levels ◽  
Daily Step Count

Abstract Background and Aims Acute kidney injury (AKI) is a known risk factor for the development of chronic kidney disease (CKD). Animal studies have demonstrated the potentially reno-protective effects of physical activity, both against the development of AKI and in promoting renal recovery. However, this has not been investigated in humans. The aim of the study was to investigate the association between physical activity levels and recovery in kidney function, measured by eGFR and creatinine, following an episode of stage 3 AKI. Method Twelve hospitalised participants with non-obstructive stage 3 AKI (as per KDIGO criteria) were asked to complete two questionnaires; the General Practitioner Physical Activity Questionnaire (GPPAQ), a measure of physical activity and; the Duke Activity Status Index, a measure of functional capacity. Baseline questionnaires were completed whilst in hospital (where participants were asked to recall their physical activity and functional capacity levels before hospitalisation) and again at 6-months post discharge. In addition, participants wore a pedometer for 7 consecutive days following discharge to ascertain their daily step count. Baseline renal function was collected using eGFR and creatinine measurements within the 12-months prior to admission; further readings were collected 25 ± 46 days after discharge as a measure of renal recovery (referred to as recovered creatinine). Results Data from the 12 participants who provided step count information were analysed. At diagnosis of stage 3 AKI, participants had a mean creatinine of 547 ± 280 with their mean baseline and recovered creatinine as follows; 95 ± 35 and 172 ± 83. A higher daily step count after discharge was associated with both a higher baseline eGFR (r=0.73, p&lt;0.01) and significant improvements to their renal recovery (r=0.69, p=0.01). There were positive associations between renal recovery and physical activity levels measured using the GPPAQ (r=0.55, p=0.06) and functional capacity (0.17, p=0.6), although not to statistical significance. The participants were divided into two groups based on their recovered creatinine levels. Those who recovered renal function back to within 25% of baseline (n=5) had a higher mean step count compared to those whose renal recovery was less pronounced (n=7); (3712 ±3960 vs 3334 ± 2254, respectively). Conclusion These results show a positive association between physical activity levels and renal recovery following an episode of AKI. This suggests that higher levels of physical activity may be protective and promote recovery of renal function following an episode of AKI. Physical activity and exercise interventions should be tested in the setting of AKI to see whether they are efficacious in promoting renal recovery.

scholarly journals Trajectories of objectively measured physical activity and mood states in older Japanese adults: longitudinal data from the Nakanojo Study

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Shuji Inada ◽  
Kazuhiro Yoshiuchi ◽  
Sungjin Park ◽  
Yukitoshi Aoyagi
Keyword(s):  
Physical Activity ◽  
Depressive Mood ◽  
Mood States ◽  
Step Count ◽  
Accelerometer Data ◽  
Daily Step ◽  
Japanese Adults ◽  
Daily Step Count ◽  
Objectively Measured ◽  
Objectively Measured Physical Activity

Abstract Background Japan, like many developed countries, now faces fiscal problems from the escalating health-care expenditures associated with an aging population. Mental health problems such as depression contribute as much to these growing demands as physical disease, and measures to prevent depression are important to controlling costs. There are few longitudinal studies examining the relation between objectively measured physical activity and depressive symptoms. Therefore, the aims of our study were to explore the patterns of change of physical activity in older Japanese adults for 5 years through the use of trajectory analysis and to examine the relation between physical activity trajectories and depressive mood states. Main body Ninety-two male and 99 female volunteers aged 65–85 years were asked to equip themselves with an electronic accelerometer with a 60-day storage capacity for at least 5 years. The parameters calculated each July for the 5 years were the average daily step count and the average daily duration of activity > 3 METs (moderate to vigorous physical activity: MVPA). Hospital Anxiety and Depression Scale (HADS) assessed corresponding mood states (HADS-A and HADS-D). Trajectories of the accelerometer data were analyzed and fifth-year HADS-D and HADS-A scores were compared among trajectory groups using an analysis of covariance (ANCOVA) that controlled for baseline scores and for baseline scores and age. Six and five distinct trajectories were identified for daily step count and for daily duration of MVPA, respectively. Using ANCOVA controlling for baseline scores, HADS-D scores differed significantly among trajectory groups classed by daily duration of MVPA (p = 0.04), and Tukey’s multiple comparison tests showed significant differences between group 2, whose pattern was stable with the middle duration of MVPA, and group 1, whose pattern was stable with the lowest duration of MVPA (p = 0.02), while the results were not significant controlling for both baseline scores and age. Conclusions Older people with less MVPA continued to do less MVPA over the 5 years of study, which may be related to a future more depressive mood. Further clinical studies will be necessary to clarify these findings.

scholarly journals Physical Activity Behavior Change Driven by Engagement With an Incentive-Based App: Evaluating the Impact of Sweatcoin (Preprint)

2018 ◽  
Author(s):  
Mark Elliott ◽  
Felicia Eck ◽  
Egor Khmelev ◽  
Anton Derlyatka ◽  
Oleg Fomenko
Keyword(s):  
Physical Activity ◽  
Behavior Change ◽  
Physical Activity Behavior ◽  
Step Count ◽  
Activity Levels ◽  
Daily Step ◽  
Activity Change ◽  
Daily Step Count ◽  
Activity Behavior ◽  
Physical Activity Behavior Change

BACKGROUND Physical inactivity, now the fourth leading cause of death, is a primary element of noncommunicable diseases. Despite a great number of attempts, there is still a lack of effective approaches that can motivate sedentary populations to increase their levels of physical activity over a sustained period. Incentives for exercise can provide an immediate reward for increasing activity levels, but because of limited funding to provide rewards, previous programs using this approach have only shown short-term changes in behavior. Sweatcoin (Sweatco Ltd, UK) is an app-based platform that converts physical movement into virtual currency. The currency can be exchanged for goods and services on their marketplace, providing a continuous incentive to be active. This study investigates the physical activity behavior change observed in Sweatcoin users over a 6-month period of app usage. OBJECTIVE The aim of this study was to investigate the change in physical activity (measured using daily step count) of a sample of Sweatcoin users, the longevity of the change, and whether this change can be predicted by demographic and other lifestyle variables. METHODS Activity data from a sample of 5892 Sweatcoin users were used to analyze daily step count. Activity change was measured in terms of the percentage change in average daily step count for each month after registration, relative to that in the 3 months before using the app. Users were grouped according to having no or negative, moderate, or high activity change. A subset of users completed a questionnaire that allowed differences between groups in terms of activity and demographic status to be investigated using regression analyses. RESULTS Daily step count increased by 19% on average over the 6 months following registration (P<.001). Of the questionnaire respondents, 728 were valid responses. A multinomial logistic regression identified the key drivers of moderate and high activity behavior change relative to no or negative change based on the defined groupings. There was a clear impact of seasonality, with those registering for the app in winter (odds ratio [OR] 4.67; P=.001) and spring (OR 5.05; P=.001) being more likely to show high positive activity behavior change than those registering in summer. More striking were the results identifying those classified as overweight (measured through body mass index [BMI]; OR 1.83; P=.02) and less active (based on a self-reported scale of physical activity; OR 0.88; P=.048), being most likely to show high levels of physical activity change following registration with the app. CONCLUSIONS The results highlight that an incentives-based app can induce significant physical activity behavior change, sustained over a 6-month period. Importantly, the results suggest that those typically lacking motivation to exercise (sedentary and high BMI) are most likely to be incentivized to increase their activity levels.

scholarly journals Predictors of Daily Steps at 1-Year Poststroke

Stroke ◽  
2021 ◽  
Author(s):  
Reed Handlery ◽  
Elizabeth W. Regan ◽  
Jill C. Stewart ◽  
Christine Pellegrini ◽  
Courtney Monroe ◽  
...  
Keyword(s):  
Physical Activity ◽  
Characteristic Curve ◽  
Secondary Analysis ◽  
Berg Balance Scale ◽  
Step Count ◽  
Stroke Severity ◽  
Daily Step ◽  
Step Counts ◽  
Daily Step Count ◽  
Walking Speeds

Background and Purpose: Walking has the potential to improve endurance and community participation after stroke. Obtaining ≥6000 daily steps can decrease subsequent stroke risk. Early identification of those prone to low daily steps could facilitate interventions that lead to increased walking and improved health. The purpose of this study was to (1) determine which factors at 2 months poststroke can predict daily step counts at 1 year and (2) determine what step count at 2 months corresponds to obtaining ≥6000 daily steps at 1-year poststroke. Methods: This was a secondary analysis of data from the Locomotor Experience Applied Post Stroke trial, which enrolled participants with walking speeds <0.80 m/second at 2 months poststroke. Daily steps were assessed at 2 months and 1-year poststroke. Linear regression was used to predict daily step counts at 1 year based on factors including age, sex, race and/or ethnicity, stroke severity, walking speed, endurance, fitness, motor function, balance, and balance confidence. A receiver operating characteristic curve determined which step count corresponded to reaching ≥6000 steps at 1 year. Results: Data from 206 participants, mean age=63 (13) years, 43% female, mean baseline daily step count=2922 (2749) steps, were analyzed. The final model to predict daily steps at 1 year poststroke contained daily steps at 2 months and balance (Berg Balance Scale score); these factors explained 38% of the variability in daily steps at 1 year ( P ≤0.001). Participants obtaining ≥1632 daily steps at 2 months were 1.86 (95% CI, 1.52–2.27) times more likely to reach ≥6000 daily steps at 1-year poststroke. Conclusions: Daily steps and balance at 2 months poststroke were the strongest predictors of future daily steps. Improving daily physical activity and targeting balance early after stroke may be necessary to increase physical activity at 1-year poststroke.

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