Measuring Children’s Activity Levels: The Association Between Step-Counts and Activity Time

2006 ◽  
Vol 3 (2) ◽  
pp. 221-229 ◽  
Author(s):  
Aaron Beighle ◽  
Robert P. Pangrazi
Keyword(s):  
Physical Activity ◽  
Strong Association ◽  
Activity Levels ◽  
Activity Time ◽  
Free Living ◽  
Step Counts ◽  
Steps Per Day

Background:The primary purpose of this study was to describe the association between activity time and step counts in children.Methods:Subjects were 590 students (334 girls, 256 boys) with each gender having a mean age of 9.2 ± 1.8 y. All subjects wore the Walk4Life 2505 pedometer for four consecutive weekdays. This pedometer simultaneously measures both step counts and activity time.Results:Boys accumulated significantly more minutes of activity time/day (140.9 ± 39.6 vs. 126.3 ± 38.1), steps/day (13,348 ± 4131 vs. 11,702 ± 3923), and steps per min (93.99 ± 5.8 vs. 91.85 ± 5.8) than girls (P < 0.001) Steps/day was a significant predictor of activity time/day (P < 0.0001).Conclusions:Boys accumulate more steps per day and more activity time per day than girls. There is a strong association between steps per day and activity time in children. Daily steps per minute as a measure of free living physical activity in children is explored

An Examination of the Activity Patterns of Elementary School Children

2002 ◽  
Vol 14 (4) ◽  
pp. 432-441 ◽  
Author(s):  
Susan D. Vincent ◽  
Robert P. Pangrazi
Keyword(s):  
Physical Activity ◽  
Activity Patterns ◽  
Individual Variability ◽  
Activity Levels ◽  
Same Sex ◽  
Factorial Anova ◽  
Step Counts ◽  
Meaningful Activity ◽  
Significant Difference ◽  
Steps Per Day

Research has suggested a trend of decreasing activity with age necessitating a renewed emphasis on promoting physical activity for children. The purpose of this study was to assess current physical activity levels of children and to establish initial standards for comparison in determining appropriate activity levels of children based on pedometer counts. Children, 6–12 years old (N = 711), wore sealed pedometers for 4 consecutive days. Mean step counts ranged from 10,479–11,274 and 12300–13989 for girls and boys respectively. Factorial ANOVA found a significant difference between sex (F = 90.16, p < .01) but not among age (F = 0.78, p = .587). Great individual variability existed among children of the same sex. Further analysis found significant differences among children of the same sex above the 80th percentile and below the 20th percentile. A reasonable activity standard might be approximately 11,000 and 13,000 steps per day for girls and boys respectively, although further discussion of this is warranted. The descriptive nature of this study provides insights into the activity patterns of children and the mean step counts for boys and girls at each age can serve as a preliminary guide for determining meaningful activity levels for children based on pedometer counts.

Free-Living Pedometer Step Counts of High School Students

2004 ◽  
Vol 16 (1) ◽  
pp. 44-53 ◽  
Author(s):  
Bridgette E. Wilde ◽  
Charles B. Corbin ◽  
Guy C. Le Masurier
Keyword(s):  
Physical Activity ◽  
High School ◽  
High School Students ◽  
Physical Education ◽  
Moderate Activity ◽  
Activity Levels ◽  
School Students ◽  
Free Living ◽  
Steps Per Day ◽  
Activity Recommendations

The purpose of this study was to examine the pedometer-measured physical activity levels of high school students (Grades 9–12). Comparisons were made between sexes, among grades, among groups based on level of participation in sport and physical education, and among groups based on levels of self-reported physical activity (based on questions from the National Youth Risk Behavior Surveillance System). Participants wore sealed pedometers for 4 consecutive school days. Results indicated no differences among days of monitoring but did show significant differences in mean steps per day between sexes, among grades, and among activity levels. Males took more steps per day than females did, and 10th graders took more steps than 12th graders did. Teens involved in sport and physical education took more steps than did those not involved. Teens who reported meeting both moderate and vigorous activity recommendations were most active, followed by teens meeting recommendations for moderate activity.

Step Count Validation of a Tri-Axial Accelerometer During Walking and Jogging

2012 ◽  
Author(s):  
Emma Fortune ◽  
Vipul Lugade ◽  
Melissa Morrow ◽  
Kenton Kaufman
Keyword(s):  
Physical Activity ◽  
Wearable Sensors ◽  
Living Environment ◽  
Activity Levels ◽  
Light Weight ◽  
Free Living ◽  
Step Counts ◽  
Step Counting ◽  
High Level ◽  
Very High

Gait analysis is an important tool in assessing the health and activity levels of patients and regular physical activity has been associated with health improvements in a number of populations. Step counting is one of the most commonly used measures of physical activity [1] and many studies have investigated the use of wearable sensors for step counts [2–4]. Their small size and light weight mean that they may be used in a free living environment and are suitable for home deployment. One of the main issues associated with step counts as a measure of physical activity is that a very high level of accuracy in step detection is needed.

Daily Physical Activity by Occupational Classification in US Adults: NHANES 2005–2006

2018 ◽  
Vol 15 (12) ◽  
pp. 900-911 ◽  
Author(s):  
Jeremy A. Steeves ◽  
Catrine Tudor-Locke ◽  
Rachel A. Murphy ◽  
George A. King ◽  
Eugene C. Fitzhugh ◽  
...  
Keyword(s):  
Physical Activity ◽  
Social Services ◽  
Strong Association ◽  
Total Activity ◽  
Daily Physical Activity ◽  
Activity Levels ◽  
Occupational Classification ◽  
Occupational Category ◽  
Steps Per Day ◽  
Objectively Measured

Background: Little is known about the daily physical activity (PA) levels of people employed in different occupational categories. Methods: Nine ActiGraph accelerometer-derived daily PA variables are presented and ranked for adults (N = 1465, 20–60 y) working in the 22 occupational categories assessed by NHANES 2005–2006. A composite score was generated for each occupational category by summing the rankings of 3 accelerometer-derived daily PA variables known to have strong associations with health outcomes (total activity counts [TAC], moderate to vigorous PA minutes per week in modified 10-minute bouts [MVPA 10], and percentage of time spent in sedentary activity [SB%]). Results: Classified as high-activity occupational categories, “farming, fishing, forestry,” and “building & grounds cleaning, maintenance” occupations had the greatest TAC (461 996 and 449 452), most MVPA 10 (149.6 and 97.8), most steps per day (10 464 and 11 602), and near the lowest SB% (45.2% and 45.4%). “Community, social services” occupations, classified as low-activity occupational categories, had the second lowest TAC (242 085), least MVPA 10 (12.1), fewest steps per day (5684), and near the highest SB% (64.2%). Conclusions: There is a strong association between occupational category and daily activity levels. Objectively measured daily PA permitted the classification of the 22 different occupational categories into 3 activity groupings.

scholarly journals How Well iPhones Measure Steps in Free-Living Conditions: Cross-Sectional Validation Study (Preprint)

2018 ◽  
Author(s):  
Shiho Amagasa ◽  
Masamitsu Kamada ◽  
Hiroyuki Sasai ◽  
Noritoshi Fukushima ◽  
Hiroyuki Kikuchi ◽  
...  
Keyword(s):  
Physical Activity ◽  
Linear Trend ◽  
Living Conditions ◽  
Step Count ◽  
Spearman Correlation ◽  
Free Living ◽  
Convenience Sample ◽  
Step Counts ◽  
Steps Per Day ◽  
Free Living Conditions

BACKGROUND Smartphones have great potential for monitoring physical activity. Although a previous laboratory-based study reported that smartphone apps were accurate for tracking step counts, little evidence on their accuracy in free-living conditions currently exists. OBJECTIVE We aimed to investigate the accuracy of step counts measured using iPhone in the real world. METHODS We recruited a convenience sample of 54 adults (mean age 31 [SD 10] years) who owned an iPhone and analyzed data collected in 2016 and 2017. Step count was simultaneously measured using a validated pedometer (Kenz Lifecorder) and the iPhone. Participants were asked to carry and use their own iPhones as they typically would while wearing a pedometer on the waist for 7 consecutive days during waking hours. To assess the agreement between the two measurements, we calculated Spearman correlation coefficients and prepared a Bland-Altman plot. RESULTS The mean step count measured using the iPhone was 9253 (3787) steps per day, significantly lower by 12% (1277/10,530) than that measured using the pedometer, 10,530 (3490) steps per day (P<.001). The Spearman correlation coefficient between devices was 0.78 (P<.001). The largest underestimation of steps by the iPhone was observed among those who reported to have seldom carried their iPhones (seldom carry: mean −3036, SD 2990, steps/day; sometimes carry: mean −1424, SD 2619, steps/day; and almost always carry: mean −929, SD 1443, steps/day; P for linear trend=.08). CONCLUSIONS Smartphones may be of practical use to individuals, clinicians, and researchers for monitoring physical activity. However, their data on step counts should be interpreted cautiously because of the possibility of underestimation due to noncarrying time.

scholarly journals Objective measurement of physical activity in Macaca fascicularis

1982 ◽  
Vol 16 (3) ◽  
pp. 240-243
Author(s):  
Wayne T. Corbett ◽  
Harry M. Schey ◽  
A. W. Green
Keyword(s):  
Physical Activity ◽  
Standard Deviation ◽  
Macaca Fascicularis ◽  
Living Environment ◽  
Activity Levels ◽  
Free Living ◽  
Activity Measurements ◽  
Active Intermediate ◽  
The Mean ◽  
The Relationship

The mean and standard deviation over 24 h for 3 groups of animals - active, intermediate and inactive - in physical activity units were 10948 ± 3360, 2611 ± 1973 and 484 ± 316 respectively. The differences were significant ( P = 0·004), demonstrating the ability of the method to distinguish between groups that can be visibly differentiated. The small within-animal physical activity standard deviation (18·85 PAU) obtained in another group, suggests that it also yields reliable physical activity measurements for non-human primates. The monitoring device used can discriminate between individual nonhuman primate physical activity levels in a free-living environment and does not alter daily behaviour. This makes possible the study of the relationship between physical activity and atherosclerosis in nonhuman primates.

scholarly journals Dynamic Target Setting increases workplace physical activity: evidence from a randomised trial

2021 ◽  
Author(s):  
Susannah Hume ◽  
Pieter Cornel ◽  
Michael Sanders ◽  
Karen Tindall ◽  
Paul Vilanti ◽  
...  
Keyword(s):  
Physical Activity ◽  
Field Experiment ◽  
Randomised Trial ◽  
Activity Levels ◽  
Target Setting ◽  
High Physical Activity ◽  
Physical Activity Levels ◽  
Steps Per Day ◽  
Dynamic Target

We conduct a field experiment in a large workplace, testing two forms of target to increase physical activity - standard targets (10,000 steps per day) or dynamic targets (10% more than last week). We find that effects overall are modest, but that dynamic targets are more impactful for people with high physical activity levels.

scholarly journals The association between psychological characteristics and physical activity levels in people with knee osteoarthritis: a cross-sectional analysis

2020 ◽  
Author(s):  
Daisuke Uritani ◽  
Jessica Kasza ◽  
Penny K. Campbell ◽  
Ben Metcalf ◽  
Thorlene Egerton
Keyword(s):  
Physical Activity ◽  
Self Efficacy ◽  
Pain Catastrophizing ◽  
Psychological Characteristics ◽  
Activity Levels ◽  
Cross Sectional ◽  
Fear Of Movement ◽  
Physical Activity Levels ◽  
Steps Per Day ◽  
The Relationship

Abstract Background:The aim of this study was to examine the relationship between psychological characteristics and physical activity levels, measured as the average number of steps per day, in people with knee osteoarthritis (OA).Methods: This study analysed baseline data from a randomized controlled trial (Australian New Zealand Clinical Trials Registry reference: ACTRN12612000308897). A total of 167 adults aged over 50 years, with knee pain rated as four or more on an 11-point numeric rating scale, and knee OA diagnosed using American College of Rheumatology clinical criteria, were recruited from the community (62 men and 105 women; mean age, 62.2 ± 7.5 years). The average number of steps per day over seven consecutive days was measured using an accelerometer-based device. Psychological characteristics evaluated were: depressive symptoms (Depression Anxiety Stress Scale), self-efficacy (Arthritis Self-Efficacy Scale for pain and other symptoms), fear of movement (Brief Fear of Movement Scale for Osteoarthritis), and pain catastrophizing (Pain Catastrophizing Scale). The association between the average number of steps per day and psychological characteristics was analyzed using a multiple linear regression analysis, with the average number of steps per day as the dependent variable, adjusting for each psychological characteristic separately, and age, sex, body mass index, and pain entered as covariates.Results: There was evidence that the amount of physical activity was associated with fear of movement (coefficient [B]: -117, 95% confidence interval [95%CI]: -227 to -8) and with pain catastrophizing (B: -44, 95%CI: -86 to -1). The association with self-efficacy was similar (B:117, 95%CI: -12 to 246). However, the direction of the association with depressive symptoms was less clear (B: -59, 95%CI: -138 to 19).Conclusions: The results of this study revealed that the relationship was such that lower fear of movement and lower pain catastrophizing may be associated with more steps per day. It may be hypothesized that fear of moving and pain catastrophizing lead to activity avoidance and that strategies to improve these disease-related psychological aspects may be useful in enhancing physical activity participation, although this hypothesis is highly speculative and needs further testing given the cross-sectional design of this study.

scholarly journals A Move-A-Thon Event: A Workplace Demonstration of a Proposed Alternative Strategy to Incentivize Workers to Engage in Physical Activity

2019 ◽  
Vol 67 (4) ◽  
pp. 153-158
Author(s):  
Susan Reutman ◽  
Renee Lewis
Keyword(s):  
Physical Activity ◽  
Health Promotion ◽  
Small Group ◽  
Worksite Health Promotion ◽  
Activity Levels ◽  
Charitable Donation ◽  
Physical Activity Levels ◽  
Steps Per Day ◽  
Worksite Health ◽  
Incentive Strategy

Motivating employees to increase their physical activity is a health promotion challenge. A Move-A-Thon (MAT) event approach was implemented as an alternative incentive to help workers to optimize their physical activity levels. We implemented a demonstration project in which workers were incentivized for their participation through monetized donations to charity. Their steps were monitored over the 2-week demonstration period. The MAT goal was for participants to achieve a minimum of 3,000 daily steps for 2 weeks, for which they could earn a total donation of up to US$20. Participants walking at least once with up to five different “exercise buddies” could earn up to US$2 more per buddy for donation. Of 10 workers invited, nine enrolled and eight completed participation by logging their monitored steps across an average of 13.75 full MAT participation days. Participants averaged 9,330.8 steps per day—more than triple the lower threshold required for a maximum US$20 charitable donation. The eight participants walked with a total of 21 “exercise buddies.” They were receptive to future MAT events of longer duration. In total, the monetized donation to charity made by those eight participants was US$202. The MAT event participants were successful at promoting physical activity among a small group of workers for 2 weeks. Future worksite health promotion projects with this type of incentive strategy are indicated.

scholarly journals Pedometer-determined physical activity among primary schoolchildren in Kuala Lumpur

2019 ◽  
Vol 28 (2) ◽  
pp. 115-123
Author(s):  
Bee Suan Wee ◽  
Awang Bulgiba ◽  
Abd. Talib Ruzita ◽  
Mohd. Noor Ismail ◽  
Bee Koon Poh
Keyword(s):  
Physical Activity ◽  
Primary School ◽  
Sociodemographic Factors ◽  
Activity Level ◽  
Activity Levels ◽  
Kuala Lumpur ◽  
Daily Step ◽  
Step Counts ◽  
Primary Schoolchildren ◽  
Physical Activity Levels

Objective: The aim of this study was to objectively measure physical activity and its association with sociodemographic factors among Malaysian primary school-age children. Methods: A total of 111 primary school children in Kuala Lumpur were selected through random sampling. Activity pattern was determined using pedometers and differences by sex, ethnicity and body mass index categories were analysed. The relationship between pedometer-determined physical activity and sociodemographic factors were also studied. Results: Overall, boys attained significantly higher daily step counts than girls (9573 ± 4145 vs 7313 ± 2697). Significant difference in daily step counts between boys and girls were observed during weekdays ( p<0.01), weekends ( p<0.05) and total mean step counts ( p<0.01). Malay ethnicity showed higher daily step counts during weekdays than weekends ( p<0.05). Compared with boys, girls had higher odds (OR=5.58; 95% CI 1.12, 27.77) of not meeting the recommended daily step counts. Those who had low physical activity levels had higher odds (OR=15.75; 95% CI 1.78, 139.33) of not meeting recommended daily step counts than children who had moderate physical activity level. Conclusion: Boys were significantly more active than girls and physical activity was greater during weekdays than on weekends. The primary schoolchildren in Kuala Lumpur were sedentary, with minimum physical activity being observed. Differences in sexes and physical activity levels influenced pedometer step counts in children.

Sign in / Sign up

Export Citation Format

Share Document