Difference In Step Count Research Articles

Step Counts of Middle-Aged and Elderly Adults for 10 Months Before and After the Release of Pokémon GO in Yokohama, Japan.

BackgroundSmartphones have been integrated into our society and are expected to serve as tools to improve health outcomes. In the summer of 2016, Pokémon GO, a location-based augmented reality game for smartphones was released; it attracted attention from the perspective of health, especially with its potential to increase physical activity (PA). A few studies have compared objectively measured step counts before and after the release of the game; however, they were conducted over a short study period and evaluated only young people.ObjectiveThe objective of this study was to confirm whether there was a difference in step counts between middle-aged and elderly players and nonplayers before and after the release of Pokémon GO.MethodsA total of 46 players and 184 nonplayers aged ≥40 years were matched for sex, age group, and PA level; they were respondents to a questionnaire randomly sent to citizens who were given free pedometers by Yokohama city. Their play status was identified through the questionnaire. To investigate the change in step counts before and after the release of Pokémon GO according to play status, a 2-way repeated-measures analysis of variance was performed. Step counts 1 month before the release of the game were compared with those 8 months after the release. In addition, subgroup analyses according to sex, age group, PA level, and subjective health status were performed.ResultsThe mean ages of players and nonplayers were 56.5 (SD 9.9) years and 57.3 (SD 9.6) years, respectively, and the mean baseline step counts of players and nonplayers were 7641.8 (SD 2754.5) and 7903.3 (SD 2674.7), respectively. There was no significant difference in the age and baseline step counts according to a t test (2-tailed). In the analysis of all samples, the interaction between play status and time effect was significant for 3 of 8 months after release. In the subgroup analyses, the interaction was significant for 3 months in men, 7 months in the 55-64-year-old group, 2 months in workers, 4 months in the active group in PA level, and 2 months in participants with subjectively good health. The interaction was significant for only 1 month, at most, in other subgroups.ConclusionsThe present study confirmed a difference in step counts between players and nonplayers before and after the release of Pokémon GO. According to our analysis, step counts were higher until 7 months after the release. The player group maintained their step counts in winter, despite the decrease in step counts of nonplayers. In subgroup analyses, players were more likely to be men, aged <55 years, workers, active, and subjectively in good health.

Differences in Step Counts, Motor Competence, and Enjoyment Between an Exergaming Group and a Non-Exergaming Group.

The purpose of this study was to examine the effect of an exergaming program on physical activity, motor competence, and enjoyment in preschool children. A sample of 65 preschool children was recruited from an urban preschool located in the Western United States. Children were randomly assigned to either an exergaming (n = 36) or a free-play group (n = 29). The intervention was 30 min/day, 5 days/week for 12 weeks for both groups, and all outcome variables were measured once during the final week of the intervention. The exergaming program included three active videogames: GoNoodles, Adventure to Fitness, and Cosmic Kids Yoga. Children in the free-play group were offered a variety of sport activities. School-day step counts were recorded using pedometers, motor competence was assessed by the Test for Gross Motor Development-Edition 3 (TGMD-3), and enjoyment was accessed using one subscale of the Intrinsic Motivational Inventory. A 2 × 2 multivariate analysis of variance (MANOVA) test was employed to examine the differences between sexes and groups on the outcome variables. The omnibus MANOVA yielded a statistically significant multivariate group main effect (F = 3.71, P = 0.016). Follow-up tests revealed statistically significant differences between groups on average school step counts (mean difference = 785 steps, P = 0.003, d = 0.68) and total TGMD-3 scores (mean difference = 8.7, P = 0.019, d = 0.51), with the exergaming group displaying higher mean scores compared with the free-play group. Young children who were randomly assigned to the exergaming group demonstrated higher school-day step counts and higher motor competence levels compared with the free-play group. These results support the use of this modality in childcare settings.

Accuracy And Reliability Of A Consumer-grade Activity Tracker Among Older People

Activity trackers are popular devices used to track and encourage physical activity; although the accuracy of activity trackers among older people is unknown. PURPOSE: The purpose of this pilot study was to evaluate the accuracy and reliability of step counts from a consumer-grade activity tracker by comparing step counts to a research-grade accelerometer and video recording. METHODS: Ten volunteers (mean age = 71.20±6.00 years) agreed to participate. Two participants did not complete the second round of testing. Researchers collected height, weight, and age. The activity tracker and accelerometer were set-up using manufacturer’s procedures. Participants wore the activity tracker and accelerometer as they walked 96 meters around an indoor gym floor at their normal walking pace. The walk was also video recorded to determine observational step count confirmed by two researchers. The same procedures were repeated on a second, non-consecutive day. Data collected from the activity tracker were compared to the accelerometer and observed step count. In addition, step counts from the first walk were compared to step counts from the second walk. RESULTS: At the first walk, the activity tracker was found to significantly underestimate step counts by 16.00 steps when compared to the observed step count, t (7) = -2.69, p = .031. The activity tracker step count was not different than the accelerometer step count. At the second walk, no differences in step counts were observed between the activity tracker and the accelerometer or the observed step count (p > .05). In addition, no differences in step counts were observed between walk 1 and walk 2 using the activity tracker, accelerometer, and observed step count. CONCLUSION: Although preliminary, these data indicate fair accuracy and good reliability of a consumer-grade activity tracker when compared to the research- grade accelerometer and observed step count. We suggest this pilot study be extended to include additional participants and comparisons of other activity trackers. Activity trackers are widely used to measures physical activity, but their accuracy and reliability remains questionable especially among older people. Additionally, products and upgrades are made available so quickly that research on the accuracy and reliability of these devices is difficult to obtain.

The Influence of Activity Trackers on Physical Activity, Cardiorespiratory Endurance, Body Composition, and Exercise Motivation

PURPOSE: The purpose of this research was to examine the influence of activity trackers on physical activity (PA), cardiorespiratory endurance (CRE), body fat percentage (BF%), and exercise motivation. METHODS: Forty-eight healthy volunteer participants ages 18-72 who did not achieve more than 3000 metabolic equivalent of task minutes (METmin) per week of physical activity (PA) were recruited to participate in a 12-week walking intervention. Participants were given the International Physical Activity Questionnaire (IPAQ), exercise motivation inventory (EMI-2) survey, tested for anthropometric measures, and tested for CRE at baseline and final testing. Participants were divided into an activity tracker group and a control group. RESULTS: Thirty-four participants (female = 29, male = 5) completed the full 12-week study. Analyses revealed no significant differences between the treatment and control groups for PA, CRE, BF%, or motivation from baseline to final testing. There were significant improvements in PA measured by the IPAQ for both groups from baseline (M = 1042.71 METmin, SD = 882.57) to final testing (M = 3499.35 METmin, SD = 2931.34), F(2, 64) = 17.374, p = .000; however, step counts did not improve for either group from baseline to final testing. Mean difference in step counts were 1,897 steps and 1,614 steps for the testing and control groups respectively. There were significant improvements in CRE for both groups from baseline to final testing (Mean difference = 2.24 ml 0 /kg·min-1), F(1, 29) = 13.016, p = .001. CONCLUSIONS: Analyses revealed that the walking program may have been effective for improving PA and CRE, but that activity trackers did not provide any additional benefits. The conclusion is that activity trackers alone may not be an effective tool for the improvement of PA, CRE, BF%, or motivation.

Comparing Physical Activity Measurements of Wrist‐worn Accelerometer‐Based NeoFit Devices among Different Locations

Increasing physical activity has been strongly recommended to reduce mortality and healthcare costs. Various wrist‐worn accelerometer‐based devices have been developed to measure level of physical activity, yet little is known about the ability of the devices to precisely estimate physical activity measurements among different locations (i.e., left vs. right; distal vs. proximal).PURPOSEWe, therefore, investigated whether there are differences in heart rates, step counts, and calories estimated from newly developed wearable device (NeoFit) worn at different locations.METHODSThirty‐two healthy subjects (26 ± 6.6 years) participated in both laboratory and free living activities while wearing Neofit at four different locations: right proximal (RP), right distal (RD), left proximal (LP), or left distal (LD). Laboratory activities consisted resting, slow walking (53.6 m/min), brisk walking (107.3 m/min), running (160.9 m/min) on a treadmill, and recovery. Free living activities included lying down, shopping, climbing stairs, laundry, cleaning, working on the computer, stretching, walking, jogging, and sports activity. Repeated measures ANOVAs were performed with a Neofit monitor placement as a within‐subjects factor on a total of 15 laboratory and free‐living activities for each outcome measurement. Bonferroni technique was used to adjust the alpha level of .003 (.05/15). The Greenhouse‐Geisser (G‐G) adjusted F and degrees of freedom were reported.RESULTSThere were no significant differences in heart rates among four different locations in both laboratory and free living activities. However, step counts and calories were significantly different among devices during running: F(2.00, 62.04) = 12.58, G‐G p &lt; .001 and F(1.96, 58.86) = 10.22, G‐G p &lt; .001, respectively. Step counts and calories estimation in NeoFit monitors worn at left arm were markedly higher than those recorded from right arm (steps: LP &amp; LD &gt; RD, LD &gt; RP; calories: LP &amp; LD &gt; RP &amp; RD). In free‐living activities, significant differences in step counts and calories were observed during shopping, F(1.67, 51.54) = 15.90, G‐G p &lt; .001 and F(1.94, 60.01) = 9.07, G‐G p &lt; .001, respectively); laundry, F(1.50, 46.63) = 10.25, G‐G p = .001 and F(2.58, 79.85) = 7.08, G‐G p = .001, respectively); and sports, F(1.31, 39.21) = 10.70, G‐G p = .001 and F(2.28, 70.53) = 15.79, G‐G p &lt; .001, respectively). NeoFit monitors worn at left arm also displayed higher step counts and calories than those from right arm during sports (steps: LP &amp; LD &gt; RP, LP &gt; RD; calories: LP &amp; LD &gt; RD, LP &gt; RP). In contrast to the results of laboratory activities, step counts and calories estimated from right arm were considerably higher than those from left arm during shopping (steps: RP &amp; RD &gt; LP &amp; LD; calories: RP &amp; RD &gt; LP; RP &gt; LD) and laundry (steps: RP &amp; RD &gt; LP &amp; LD; calories: RP &gt; LP &amp; LD; RD &gt; LD). No significant difference between proximal and distal placements was found during all activities.CONCLUSIONWe found that NeoFit placement sites does not markedly affect the estimation of heart rates. The estimation of step counts, and calories during the laboratory‐based and free‐living activities were somewhat different between left and right arms. Further investigation is warranted to examine the accuracy of NeoFit monitors against criterion measures of physical activity.Support or Funding InformationSupported by MEDIPLUS SOLUTION.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Evaluating the effects of active morning commutes on students' overall daily walking activity in Singapore: Do walkers walk more?

Abstract Walking has multiple health benefits. One way to increase students’ walking activity is by encouraging active morning commutes. However, students may compensate for active commutes by walking less throughout the day, rendering such initiatives ineffective in increasing overall walking activity. This study aims to assess how morning commuting modes affect students’ walking levels, hypothesizing that gains in walking from active morning commutes may not be sustained throughout the day due to compensatory behavior. Our study analyzed objectively measured, sensor-collected data of 5600 children (ages 7 to 18) in Singapore for up to four consecutive weekdays between September and November 2015. Potential confounders of age, socioeconomic status, and built environment characteristics, as well as home-school distance as an effect modifier, were examined. We used linear mixed effects models to analyze differences in step count between students with different morning modes, as well as to analyze ‘within students’ variations when students switched between different modes over different days. Students who walked or took public transport walked more than their driven peers during morning commuting hours, by 96.1 steps per hour (95% CI = 71.5, 120.8) and 54.1 steps per hour (95% CI = 32.2, 75.9) respectively. Students who switched morning commute modes from car to public transport took 47.6 more morning steps per hour (95% CI = 10.3, 84.9) when using public transport, compared to when driven. However, the relationship between morning travel modes and step count per hour across the full day was less clear-cut. Both our ‘between students’ and ‘within students’ analyses suggest that taking more active morning modes, after controlling for all possible confounders and modifers, was not associated with higher step counts over the entire day. Encouraging students to walk more through more active morning commutes alone may have limited effectiveness in increasing overall daily walking activity.

Savouring our mistakes: Learning from the FitQuest project

Abstract Although serious games for children can potentially have important social, educational and health benefits, the research process from initial game design to a robust evaluation is lengthy and complex. This paper describes the design and evaluation process of an exergame for children. It reports on the inconclusive results of a cluster randomised controlled trial (RCT) conducted among children aged 10–11 years attending 10 state-funded primary schools in Scotland. One class in each school was randomly allocated to intervention ( n = 5 , 111 children) or control ( n = 5 , 104 children). Intervention schools were given FitQuest, a smartphone game for the Android platform, and were requested to play the game during at least one hour of mandated Physical Education (PE) lessons per week for 5 weeks. Participants in the control arm took part in standard mandated PE lessons. Primary outcome measures were step count, minutes spent in moderate to vigorous physical activity (MVPA) and exercise self-efficacy. None of the children spent the recommended time per week playing FitQuest. There were no significant differences in step count, MVPA or self-efficacy by intervention group. The paper reflects on possible flaws during the design and evaluation process which could have led to the disappointing results, and presents some proposals for improving the research process for developing serious games for children. These include: deepening the ways in which we interact with domain expert colleagues, developing a shared understanding of the expectations for different phases of evaluation, closing the gap between game design knowledge and domain theories, raising the standards of evidence for design guidelines, encouraging synthesis across studies by evaluating mid-range theories rather than individual games, and developing guidelines for monitoring intervention fidelity in this domain.

Effectiveness of physical activity intervention among government employees with metabolic syndrome

Background/ObjectiveOur study aimed to assess the effects of physical activity interventions via standing banners (point-of-decision prompt) and aerobics classes to promote physical activity among individuals with metabolic syndrome. MethodsWe conducted a cluster randomized controlled intervention trial (16-week intervention and 8-week follow-up). Malaysian government employees in Putrajaya, Malaysia, with metabolic syndrome were randomly assigned by cluster to a point-of-decision prompt group (n = 44), an aerobics group (n = 42) or a control group (n = 103) based on sample size calculation formula. Step counts were evaluated by Lifecorder e-STEP accelerometers for all participants. Metabolic syndrome was defined according to the ‘harmonizing’ definition, in which individuals who have at least three of the five metabolic risk factors (waist circumference, high-density lipoprotein cholesterol, triglycerides, fasting glucose levels, systolic and diastolic blood pressure) will be classified as having metabolic syndrome. A total of 80% of the enrolled government employees with metabolic syndrome completed the programme. Data were analyzed using SPSS for Windows (version 20, SPSS, Chicago, IL). ResultsThere were significantly higher step counts on average in the aerobics group compared to the control group over assessments. Assessments at baseline, post-intervention and follow-up showed a significant difference in step counts between the intervention and control groups. The greatest reductions in the proportions of individuals with metabolic syndrome were observed in the aerobics group with a reduction of 79.4% in the post-intervention assessment compared to the assessment at baseline. ConclusionThe findings of this study suggest that physical activity intervention via aerobics classes is an effective strategy for improving step counts and reducing the prevalence of metabolic syndrome.

Physiological responses, hitting accuracy and step count of a tennis drill in function of court surface: a randomised cross-over design

The present study examined physiological responses, hitting accuracy and step count during a tennis drill on both clay and hard courts. Twenty elite tennis players performed two identical ball machine led drills. Maximum and mean heart rate, energy expenditure, playing intensity (MET values) and step count were measured using the Polar RCX-5 device and the SenseWear Pro3 Armband. Hitting accuracy was calculated as the percentage of balls that were hit within marked zones. There was no significant difference and a trivial effect size between clay and hard court for maximal and mean heart rate, MET values and hitting accuracy. There was a small effect size and a trend towards a significantly higher energy expenditure on clay court. Step count showed a large effect size and was significantly lower on clay court. The correlations between step count, hitting accuracy and the physiological responses indicated little difference between clay and hard court. There was a significant moderate positive correlation between step count and hitting accuracy on hard court only. Despite a significant difference in step count, this study did not find a significant difference in physiological responses and hitting accuracy between clay and hard court during a ball machine led drill.

Use of activity tracking in major visceral surgery\u2014the Enhanced Perioperative Mobilization (EPM) trial: study protocol for a randomized controlled trial

BackgroundEnhanced recovery after surgery (ERAS) programs are aimed at minimizing postoperative stress and accelerating postoperative recovery by implementing multiple perioperative principles. “Early mobilization” is one such principle, but the quality of assessment and monitoring is poor, and evidence of improved outcome is lacking. Activity trackers allow precise monitoring and automatic feedback to the patients to enhance their motivation for early mobilization. The aim of the study is to monitor and increase the postoperative mobilization of patients by giving them continuous automatic feedback in the form of a step count using activity-tracking wristbands.Methods/designPatients undergoing elective open and laparoscopic surgery of the colon, rectum, stomach, pancreas, and liver for any indication will be included. Further inclusion criteria are age between 18 and 75 years, American Society of Anesthesiologists Physical Status class less than IV, and a signed informed consent form. Patients will be stratified into two subgroups, laparoscopic and open surgery, and will be randomized 1:1 for automatic feedback of their step count using an activity tracker wristband. The control group will have no automatic feedback. The sample size (n = 30 patients in each of the four groups, overall n = 120) is calculated on the basis of an assumed difference in step count of 250 steps daily (intervention group versus control group). The primary study endpoint is the average step count during the first 5 postoperative days; secondary endpoints are the percentage of patients in the two groups who master the predefined mobilization (step count) targets, assessment of additional activity data obtained from the devices, assessment of preoperative mobility, length of hospital and intensive care unit stays, number of patients who receive physiotherapy, 30-day mortality, and overall 30-day morbidity.DiscussionEarly mobilization is a key element of ERAS. However, enhanced early mobilization is difficult to define, to assess objectively, and to implement in clinical practice. Consequently, there is a discrepancy between ERAS targets and actual practice, especially in patients undergoing major visceral surgery. This study is the first randomized controlled trial investigating the use and feasibility of activity tracking to monitor and enhance postoperative early mobilization.Trial registrationClinicalTrials.gov identifier: NCT02834338. Registered on 15 June 2016.

Increasing Physical Activity and Enjoyment Through Goal-Setting at Summer Camp

Children’s physical activity levels decrease in the summer months, which explains the interest in out-of-school programs that maintain and increase physical activity (Carrel, Clark, Peterson, Eickhoff, & Allen, 2007). Park and recreation professionals have long understood their contributions to physical activity efforts (Mowen, Trauntvein, Graefe, & Son, 2012). Physical activity is inherent in many recreation programs and commonly embedded in program and facility designs, though efforts to leverage these inherent strengths are often less intentional. In school and work contexts, programs that use goal-setting with pedometers have been linked to increasing physical activity levels (Kang, Marshall, Barreira, & Lee, 2009). However, for such a program to work in a recreation context, it would need to be effective at boosting physical activity and remain enjoyable for participants (Trew, Kremer, Gallagher, Scully, & Ogle, 1997). The purpose of this study was to assess the impact of three different goal-setting programs with pedometers on children’s physical activity and enjoyment in a day camp setting. The goal-setting programs differed each week; campers set individual goals, small group goals, and then a camp-wide goal. A secondary aim was to assess if differences in step counts and enjoyment of physical activity existed for male/female and older/younger campers. Participants included 88 children between the ages of 5 and 11 (mean age was 7.8 ± 1.6 years). Physical activity and enjoyment measures were collected at baseline and three subsequent weeks during the goal-setting programs. There were significant increases in step counts when comparing the baseline to individual goal-setting (Δ = 776 steps, p = 0.003, d = 0.38) and for camp-wide goal-setting (Δ = 1547 steps, p < 0.001, d = 0.78), and significant increases in enjoyment compared to baseline for group goal-setting (Δ = .91 enjoyment, p = 0.001, d = 0.52) and for camp-wide goal-setting (Δ = .66 enjoyment, p = 0.003, d = 0.40). Boys were more physically active than girls ( p = .006, d = 0.50) and on average took 796 more steps. Also, older campers enjoyed physical activity less; the correlation between age and enjoyment was r = -.317 (p = .003). These data illustrate that a goal-setting pedometer-based program functioning at a broader level was most effective at increasing both physical activity and participants’ enjoyment of physical activity. Concerted efforts by recreation programmers may be necessary to encourage physical activity that is enjoyable among girls and older children. Subscribe to JPRA

Does School-Based Health Promotion Affect Physical Activity on Weekends? And, Does It Reach Those Students Most in Need of Health Promotion?

ObjectiveTo determine whether a school-based health promotion program affects children’s weekend physical activity and whether this effect varies according to socioeconomic-status.MethodsThis was a quasi-experimental trial of school-based programs on physical activity levels implemented in disadvantaged neighborhoods in Alberta, Canada. In 2009 and 2011, 7 full days of pedometer data were collected from cross-sectional samples of grade 5 students (age 10–11 years) from 10 intervention schools in low-socioeconomic neighbourhoods and 20 comparison schools in middle-socioeconomic neighbourhoods. Multilevel models assessed differences in step-counts between intervention and comparison groups over-time by weight (objectively measured) and socioeconomic status subgroups.ResultsIn 2009, children from intervention schools were less active on weekends relative to comparison schools (9212 vs. 11186 steps/day p<0.01). Two years later, daily step-counts on weekend days among children in low socioeconomic intervention schools increased such that they approximated those of children from middle socioeconomic comparison schools (12148 vs. 12121 steps/day p = 0.96). The relative difference in steps between intervention and comparison schools on weekends reduced from -21.4% to 0.2% following the intervention. The normalization of weekend step counts was similar for normal weight (–21.4% to +2.0%) and overweight (-19.1 to +3.9%) children, and was balanced across socioeconomic subgroups.ConclusionsThese data suggest that school-based health promotion is effective for reducing inequities in physical activity levels outside school hours. Investments in school-based health promotion lead to behavior modification beyond the school environment.Trial RegistrationClinicalTrials.gov NCT01914185

Validation of a pouch-mounted activPAL3 accelerometer

The activPAL accelerometer is a commonly used device for the assessment of physical activity in cross-sectional and intervention research. These devices are usually attached directly to the skin; however, recent studies report problems such as skin irritation associated with this attachment method and therefore adequate alternate methods are needed. The aim of this study was to validate the use of an elasticised pouch to secure an activPAL3c (PAL Technologies, Glasgow, UK) accelerometer for the assessment of sedentary and physical activity behaviours during laboratory and free-living conditions. Twenty-eight healthy adults wore two activPAL3c accelerometers, one secured in an elasticised pouch, and one directly attached to the skin, on the anterior surface of the right thigh during laboratory-based walking at a self-selected pace, treadmill walking at 0.89ms−1, 1.56ms−1 and running at 2.2ms−1, and during free-living conditions. Paired samples t-tests and intraclass correlation coefficients were used to investigate the difference and agreement between accelerometer outputs. No statistically significant difference in step count between pouch-mounted and skin-mounted activPAL3c accelerometers was evident during walking at any speed under laboratory conditions. No statistically significant difference in step count, upright time, sitting time or postural transitions was found between pouch-mounted and skin-mounted activPAL3c accelerometers during free-living conditions. Intraclass correlation coefficients showed a high to very high level of agreement between pouch-mounted and skin-mounted activPAL3c accelerometers for each outcome variable. The use of an elasticised pouch to secure the activPAL3c accelerometer appears to be a valid method of attachment and may offer advantages over direct skin mounting.

Editorial: Learning from failures in game design for children

Although serious games for children can potentially have important social, educational and health benefits, the research process from initial game design to a robust evaluation is lengthy and complex. This paper describes the design and evaluation process of an exergame for children. It reports on the inconclusive results of a cluster randomised controlled trial (RCT) conducted among children aged 10–11 years attending 10 state-funded primary schools in Scotland. One class in each school was randomly allocated to intervention (n=5, 111 children) or control (n=5, 104 children). Intervention schools were given FitQuest, a smartphone game for the Android platform, and were requested to play the game during at least one hour of mandated Physical Education (PE) lessons per week for 5 weeks. Participants in the control arm took part in standard mandated PE lessons. Primary outcome measures were step count, minutes spent in moderate to vigorous physical activity (MVPA) and exercise self-efficacy. None of the children spent the recommended time per week playing FitQuest. There were no significant differences in step count, MVPA or self-efficacy by intervention group.The paper reflects on possible flaws during the design and evaluation process which could have led to the disappointing results, and presents some proposals for improving the research process for developing serious games for children. These include: deepening the ways in which we interact with domain expert colleagues, developing a shared understanding of the expectations for different phases of evaluation, closing the gap between game design knowledge and domain theories, raising the standards of evidence for design guidelines, encouraging synthesis across studies by evaluating mid-range theories rather than individual games, and developing guidelines for monitoring intervention fidelity in this domain.

Do school-based physical activity interventions increase or reduce inequalities in health?

Little is known about the effectiveness of school-based health promotion on physical activity inequalities among children from low-income areas. This study compared the two-year change in physical activity among 10–11 year-old children attending schools with and without health promotion programs by activity level, body weight status, and socioeconomic backgrounds to assess whether health promotion programs reduce or exacerbate health inequalities. This was a quasi-experimental trial of a Comprehensive School Health (CSH) program implemented in schools located in socioeconomically disadvantaged neighbourhoods in Edmonton, Alberta, Canada. In the spring of 2009 and 2011, pedometer (7 full days) and demographic data were collected from cross-sectional samples of grade five children from 10 intervention and 20 comparison schools. Socioeconomic status was determined from parent self-report. Low-active, active, and high-active children were defined according to step-count tertiles. Multilevel linear regression methods adjusted for potential confounders were used to assess the relative inequity in physical activity and were compared between groups and over-time. In 2009, a greater proportion of students in the intervention schools were overweight (38% vs. 31% p = 0.03) and were less active (10,827 vs. 12,265 steps/day p < 0.001). Two years later, the relative difference in step-counts between intervention and comparison schools reduced from −15.5% to 0% among low-active students, from −13.4% to 0% among active students, and from −15.1% to −2.7% among high-active students. The relative difference between intervention and comparison schools reduced from −11.1% to −1.6% among normal weight students, from −16.8% to −1.4% among overweight students, and was balanced across socioeconomic subgroups. These findings demonstrate that CSH programs implemented in socioeconomically disadvantaged neighbourhoods reduced inequalities in physical activity. Investments in school-based health promotion are a viable, promising, and important approach to improve physical activity and prevent childhood obesity, and may also reduce inequalities in health.

Children and Pedometers: A Study in Reactivity and Knowledge

Pedometers are simple inexpensive tools that are widely used for the measurement of physical activity. Reactivity is always a concern when using pedometers. An issue not yet addressed is the role previous knowledge has on the impact of reactivity. The primary purpose of this study was to examine if reactivity exists in 4th-6th grade students and if prior knowledge about pedometers had an effect on reactivity. Participants included 109 (54 females) 4th- 6th grade students from a suburban charter school. Prior to data collection, students completed a questionnaire to measure their knowledge of pedometers. Pedometers were worn from after-school until before school each day for two weeks with half of the students wearing sealed devices the first week, then switching to unsealed. Steps were counted and pedometers were redistributed each afternoon. Repeated measures ANOVA results showed no significant differences in step counts between unsealed and sealed conditions, or when knowledge and experience regarding pedometers was included as a covariate. Pedometers are inexpensive and reliable tools that researchers and educators can use to measure physical activity. In this study reactivity did not occur with older elementary students and a student’s knowledge of pedometers did not affect reactivity.

Impact of accelerometer wear time on physical activity data: a NHANES semisimulation data approach

BackgroundCurrent research practice employs wide-ranging accelerometer wear time criteria to identify a valid day of physical activity (PA) measurement.ObjectiveTo evaluate the effects of varying amounts of daily accelerometer wear time...

Prevalence of New Zealand Children and Adolescents Achieving Current Physical Activity and Television Watching Recommendations

Aims were to investigate sex, ethnicity, and age differences in achieving daily step count and television (TV) watching recommendations in schoolchildren. Participants were 615 children (n = 325) and adolescents (n = 290) aged 5 to 16 years. Activity was assessed over 5 days using pedometers; TV time was collected via parental proxy-report and self-report. Ethnic, sex, and age differences in step counts, TV time, and odds of meeting TV and step count recommendations were examined for weekdays, weekend days, and overall using generalized estimation equation modeling. Overall, girls were more active than boys (P < .001). Adolescents were more active than children (P = .044), watched more TV (P = .005), and were less likely to meet TV watching recommendations (P = .004). Non-European children watched significantly more TV (P = .008), and were significantly less likely to meet TV recommendations than non-European children (P = .001). Participants watched more TV and accumulated less steps on weekend days than weekdays. Multifaceted interventions focusing on both increasing activity and decreasing TV time are needed, especially on weekends. Children and girls may benefit more from activity interventions, while ethnic-specific interventions focusing on TV habits may be most efficacious for adolescents.

Preliminary Evidence for School-Based Physical Activity Policy Needs in Washington, DC

The school setting could be a primary venue for promoting physical activity among inner-city children due to the structured natured of the school day. We examined differences in step counts between structured school days (SSD) and weekend days (WED) among a sample of public school children in Washington, DC. Subjects (N = 29) were third- to sixth-grade students enrolled in government-funded, extended-day enrichment programs. Step counts were measured using a pedometer (Bodytronics) over 2 SSD and 2 WED. Differences in mean step counts between SSD and WED were determined using multivariable linear regression, with adjustments for age, sex, and reported distance between house and school (miles). Recorded step counts were low on both SSD and WED (7735 ± 3540 and 8339 ± 5314 steps/day). Boys tended to record more steps on SSD compared with girls (8080 ± 3141 vs. 7491 ± 3872 steps/day, respectively), whereas girls recorded more steps on the WED compared with boys (9292 ± 6381 vs. 7194 ± 3669 steps/day). Parameter estimates from the regression modeling suggest distance from school (P < .01) to be the strongest predictor of daily step counts, independent of day (SSD/WED), sex, and age. Among inner-city school children, a safe walking route to and from school may provide an important opportunity for daily physical activity.

Between-Monitor Differences in Step Counts Are Related to Body Size: Implications for Objective Physical Activity Measurement

BackgroundThe quantification of the relationships between walking and health requires that walking is measured accurately. We correlated different measures of step accumulation to body size, overall physical activity level, and glucose regulation.MethodsParticipants were 25 men and 25 women American Indians without diabetes (Age: 20-34 years) in Phoenix, Arizona, USA. We assessed steps/day during 7 days of free living, simultaneously with three different monitors (Accusplit-AX120, MTI-ActiGraph, and Dynastream-AMP). We assessed total physical activity during free-living with doubly labeled water combined with resting metabolic rate measured by expired gas indirect calorimetry. Glucose tolerance was determined during an oral glucose tolerance test.FindingsBased on observed counts in the laboratory, the AMP was the most accurate device, followed by the MTI and the AX120, respectively. The estimated energy cost of 1000 steps per day was lower in the AX120 than the MTI or AMP. The correlation between AX120-assessed steps/day and waist circumference was significantly higher than the correlation between AMP steps and waist circumference. The difference in steps per day between the AX120 and both the AMP and the MTI were significantly related to waist circumference.InterpretationBetween-monitor differences in step counts influence the observed relationship between walking and obesity-related traits.