Active Style Pro Research Articles

Comparison of step-count outcomes across seven different activity trackers: a free-living experiment with young and older adults

BackgroundThere are now many different types of activity trackers, including pedometers and accelerometers, to estimate step counts per day. Previous research has extensively examined step-count measurements using activity trackers across various settings while simultaneously wearing different devices.; however, older adults frequently display distinct walking patterns and gait speeds compared to younger adults. This study aimed to compare the step-count between older and younger adults by having them simultaneously wear seven different activity trackers in free-living experiments.MethodsThis study included 35 younger adults (21–43 yrs) and 57 physically independent older adults (65–91 yrs). All participants simultaneously wore one pedometer and six activity trackers: ActiGraph GT3X + Wrist and Hip, Omron Active Style Pro HJA-350IT, Panasonic Actimarker, TANITA EZ-064, Yamasa TH-300, and Yamasa AS-200 for seven days. A regression equation was also used to assess inter-device compatibility.ResultsWhen comparing wrist-worn ActiGraph to the six hip-worn activity trackers, the wrist-worn ActiGraph consistently recorded step counts over 4,000 steps higher than hip-worn activity trackers in both groups (range, 3000–5000 steps). Moreover, when comparing the ActiGraph worn on the wrist to that worn on the hip, the proportion was higher among older adults compared to younger ones (younger: 131%, older: 180%). The Actimarker recorded the highest average step counts among six hip-worn devices, with 8,569 ± 4,881 overall, 9,624 ± 5,177 for younger adults, and 7,890 ± 4,562 for older adults. The difference between the hip-worn ActiGraph and Active Style Pro was just about 70 steps/day overall. The correlation among all devices demonstrated a very high consistency, except for the wrist-worn ActiGraph (r = 0.874–0.978).ConclusionsStep counts recorded from seven selected consumer-based and research-grade activity trackers and one pedometer, except for the wrist-worn ActiGraph. showed a variation of approximately 1700 steps (range, 1265–2275 steps) steps for both groups, yet maintained a high correlation with each other. These findings will be valuable for researchers and clinicians as they compare step counts across different studies or representative surveys conducted globally.

Evaluation of Energy Balance Estimated From Total Energy Expenditure and Body Composition Changes in Junior Sumo Wrestlers: An Observational Study Over Six Months.

Background Sumo is a sport that requires wrestlers to develop their physique from childhood for athletic advantage. However, the energy expenditure and energy balance required for the growth of junior Sumo wrestlers remain unclear. This study aimed to determine the energy balance of junior Sumo wrestlers over six months usingdoubly labeled water (DLW) and bioelectrical impedance analysis (BIA). Methodology A total of 12 male Sumo wrestlers were affiliated with a local Sumo club (average age = 15 ± 1 years). The total energy expenditure (TEE) was measured using DLW, whereas body composition was evaluated using BIA. Daily physical activity was quantified using a tri-accelerometer (Active style Pro HJA-750C). Results The TEE was 4,194 ± 734 kcal/day, while daily physical activity without training was 786 ± 50 minutes. Within six months, the body weight increased by 2.0 ± 3.2 kg, fat-free mass (FFM) was augmented by 2.1 kg, while fat mass did not change significantly. The surplus energy accumulated was 5.6 ± 213 kcal/day. Conclusions The excess energy of junior Sumo wrestlers predominantly increases their FFM. To increase their physical prowess, wrestlers adhere to a lifestyle characterized by high-intensity training and attenuated daily physical activity.

Prediction of the Physical Activity Level of Community-Dwelling Older Japanese Adults with a Triaxial Accelerometer Containing a Classification Algorithm for Ambulatory and Non-Ambulatory Activities

Accurate methods for the prediction of the total energy expenditure and physical activity level (PAL) in community-dwelling older adults have not been established. Therefore, we examined the validity of estimating the PAL using an activity monitor (Active style Pro HJA-350IT, [ASP]) and proposed correction formulae for such populations in Japan. Data for 69 Japanese community-dwelling adults aged 65 to 85 years were used. The total energy expenditure in free-living conditions was measured with the doubly labeled water method and the measured basal metabolic rate. The PAL was also estimated from metabolic equivalent (MET) values obtained with the activity monitor. Adjusted MET values were also calculated with the regression equation of Nagayoshi et al. (2019). The observed PAL was underestimated, but significantly correlated, with the PAL from the ASP. When adjusted using the Nagayoshi et al. regression equation, the PAL was overestimated. Therefore, we developed regression equations to estimate the actual PAL (Y) from the PAL obtained with the ASP for young adults (X) as follows: women: Y = 0.949 × X + 0.205, mean ± standard deviation of the prediction error = 0.00 ± 0.20; men: Y = 0.899 × X + 0.371, mean ± standard deviation of the prediction error = 0.00 ± 0.17.

Step-count outcomes of 13 different activity trackers: Results from laboratory and free-living experiments

BackgroundMany activity trackers have been developed, but steps can still be inconsistent from one monitor to another. Research questionWhat are the differences and associations between the steps of 13 selected consumer-based and research-grade wearable devices during 1 standardized day in a metabolic chamber and 15-day free-living trials? MethodsIn total, 19 healthy adults between 21 and 50 years-old participated in this study. Participants were equipped with 12 accelerometer-based active trackers and one pedometer (Yamasa) in order to monitor the number of steps per day. The devices were worn on the waist (ActiGraph, Omron, Actimarker, Lifedorder, Withings, and Yamasa) or non-dominant wrist (Fitbit, Garmin, Misfit, EPSON, and Jawbone), or placed in a pocket (Omron CaloriScan, and TANITA). Participants performed structured activities over a 24 h period in a chamber (Standardized day), and steps were monitored in the same participants in free-living trials for 15 successive days using the same monitors (free-living days). ResultsWhen the 13 monitors were ranked by their steps, waist-worn ActiGraph was located at the center (7th) of the monitors both in the Standardized (12,252 ± 598 steps/day, mean ± SD) and free-living days (9295 ± 4027 steps/day). The correlation between the accelerometer-based devices was very high (r = 0.87–0.99). However, the steps of Yamasa was significantly lower in both trials than ActiGraph. The wrist-worn accelerometers had significantly higher steps than other devices both trials (P < 0.05). The differences between ActiGraph and Actimarker or Lifecorder was less than 100 steps/day in the Standardized day, and the differences between ActiGraph and Active Style Pro was less than 100 steps/day in the free-living days. Regression equation was also performed for inter-device compatibility. SignificanceStep obtained from the wrist-worn, waist-worn, and pocket-type activity trackers were significantly different from each other but still highly correlated in free-living conditions.

Differences in Accelerometer-Measured Physical Activity and Sedentary Behavior Between Middle-Aged Men and Women in Japan: A Compositional Data Analysis.

Differences in accelerometer-measured sedentary behavior and different physical activity (PA) intensities between men and women have been poorly described. The authors examined gender differences in time-use activity composition and total volume of PA. A cross-sectional mail survey was conducted from 2013 to 2015 with a randomized sample of 6000 middle-aged (40-64y) community-dwelling Japanese adults living in urban and regional cities. Participants wore Active style Pro HJA-350IT on their waist for 7 consecutive days. Gender differences in activity time use was examined using compositional data analysis to control for time spent in all activity measures. In total, 757 participants (303 men, 52.3 [7.1]y) with valid data were included in the analysis. Women spent on average 12.6% less time in sedentary behavior and 23.4% more time in light-intensity PA than men, whereas no significant difference was found for moderate to vigorous PA. Women accumulated a significantly greater volume of PA than men (17.8 vs 15.0 metabolic equivalent of task h/d). Japanese middle-aged women showed higher levels of PA than men because they spent more time in light-intensity PA. Given the health benefits of light-intensity PA, evaluating only moderate to vigorous PA may lead to an underestimation of women's participation in PA.

Changes in rural older adults\u2019 sedentary and physically-active behaviors between a non-snowfall and a snowfall season: compositional analysis from the NEIGE study

BackgroundLevels of physical activity change throughout the year. However, little is known to what extent activity levels can vary, based on accelerometer determined sedentary and physically-active time. The aim of this longitudinal study was to examine older adults’ activity changes from a non-snowfall season to a subsequent snowfall season, with consideration of the co-dependence of domains of time use.MethodsParticipants were 355 older Japanese adults (53.1% women, aged 65–84 years) living in a rural area of heavy snowfall who had valid accelerometer (Active style Pro HJA-750C) data during non-snowfall and snowfall seasons. Activity was classified as sedentary behavior (SB), light-intensity PA (LPA), and moderate-to-vigorous PA (MVPA). Compositional changes from the non-snowfall to the snowfall season were analyzed using Aitchison’s perturbation method. The ratios of each component in the composition, such as [SBsnow/SBnon-snow, LPAsnow/LPAnon-snow, MVPAsnow/MVPAnon-snow] for seasonal changes, were calculated and were then divided by the sum of these ratios.ResultsIn men, the percentages of time spent in each activity during the non-snowfall/snowfall seasons were 53.9/64.6 for SB; 40.8/31.6 for LPA; and 5.3/3.8 for MVPA; these corresponded to mean seasonal compositional changes (∆SB, ∆LPA, ∆MVPA) of 0.445, 0.287, and 0.268 respectively. In women, the percentages of time spent in each activity during the non-snowfall/snowfall seasons were 47.9/55.5 for SB; 47.9/41.0 for LPA; and 4.2/3.5 for MVPA; these corresponded to mean seasonal compositional changes (∆SB, ∆LPA, ∆MVPA) of 0.409, 0.302, and 0.289 respectively. The degree of seasonal change was greatest in men.ConclusionsIn older adults, activity behaviors were changed unfavorably during snowfall season, particularly so for men. The degree of seasonal change was greatest for SB. Development of strategies to keep rural older adults active during the snowfall season may be needed for maintaining a consistently-active lifestyle for their health.

Accelerometer-determined Physical Activity And Functional Fitness In Community-dwelling Older Japanese Women

PURPOSE: The proportion of elderly people in Japan’s population now exceeds 28%, identifying the country as a “super-aging society.” It is important for people to maintain health and independence as they age. Therefore, it is important for them to maintain functional fitness. The purpose of this study was to analyze the associations between accelerometer-determined physical activity and clinical measures of functional fitness. METHODS: One hundred ninety-nine community-dwelling Japanese women (age: 68.9 ± 4.8 years, BMI: 22.4 ± 2.8) wore an Active Style Pro HJA-350IT accelerometer for five weeks (Omron Healthcare Co., Ltd, Japan) on their waistline for the entire day, except when bathing, showering, swimming, or sleeping. The instrument measured the daily number of steps and accumulated time (minutes) spent in sedentary behavior (SB: < 1.5 metabolic equivalents or METs; 1 MET=3.5 ml/kg/min), light-intensity physical activity (LPA: 1.5 to 2.9 METs), and moderate- and vigorous-intensity physical activity (MVPA: ≥ 3.0 METs). Common functional fitness measures included hand grip, sit-up, sit and reach, functional reach, chair stands, 10-m walk, 10-m obstacle walk, and timed up and go. Functional fitness of participants was compared according to quartiles of steps/day and time spent in SB, LPA, and MVPA. These quartiles are denoted as Q1 (lowest activity quartile), Q2, Q3, and Q4 (highest activity quartile). RESULTS: Participants accumulated (median, [IQR]) 6,939 [5,000-8,896] steps/day, 286.1 [228.0-349.7] SB min/day, 451.1 [398.1-509.3] LPA min/day, and 68.9 [45.7-93.0] MVPA min/day. The 10-m walk, 10-m obstacle walk, and timed up and go measures differed significantly across the steps/day quartiles (Q1<Q2, p<0.05) and MVPA quartiles (Q1<Q2, Q3, Q4, p<0.05). The 10-m walk (Q1<Q2, p<0.05), timed up and go (Q1<Q2, p<0.05), and functional reach (Q2, Q3> Q4, p<0.05) measures differed significantly across SB quartiles. There were no differences observed across LPA quartiles. CONCLUSIONS: Accelerometer-determined physical activity, especially time in MVPA, was associated with a number of different functional fitness measures.

Validity of the Use of a Triaxial Accelerometer and a Physical Activity Questionnaire for Estimating Total Energy Expenditure and Physical Activity Level among Elderly Patients with Type 2 Diabetes Mellitus: CLEVER-DM Study

Introduction: Evaluation of total energy expenditure (TEE) and physical activity level (PAL) is important for treatment of patients with type 2 diabetes mellitus (T2DM). However, the validity of accelerometers (ACC) and physical activity questionnaires (PAQ) for estimating TEE and PAL remains unknown in elderly populations with T2DM. We evaluated the accuracy of TEE and PAL results estimated by an ACC (TEE_ACC and PAL_ACC) and a PAQ (TEE_PAQ and PAL_PAQ) in elderly patients with T2DM. Methods: Fifty-one elderly patients with T2DM (aged 61–79 years) participated in this study. TEE_ACC was calculated with PAL_ACC using a triaxial ACC (Active style Pro HJA-750c) over 2 weeks and predicted basal metabolic rate (BMR) by Ganpule’s equation. TEE_PAQ was estimated using predicted BMR and the PAL_PAQ from the ­Japan Public Health Center Study-Long questionnaire. We compared the results to TEE_DLW measured with the doubly labeled water (DLW) method and PAL_DLW calculated with BMR using indirect calorimetry. Results: TEE_DLW was 2,165 ± 365 kcal/day, and TEE_ACC was 2,014 ± 339 kcal/day; TEE_ACC was strongly correlated with TEE_DLW (r = 0.87, p < 0.01) but significantly underestimated (–150 ± 183 kcal/day, p < 0.05). There was no significant difference in TEE_PAQ and TEE_DLW (–49 ± 284 kcal/day), while the range of difference seemed to be larger than TEE_ACC. PAL_DLW, PAL_ACC, and PAL_PAQ were calculated to be 1.71 ± 0.17, 1.69 ± 0.16, and 1.78 ± 0.24, respectively. ­PAL_ACC was strongly correlated with PAL_DLW (r = 0.71, p < 0.01), and there was no significant difference between the 2 values. PAL_PAQ was moderately correlated with PAL_DLW (r = 0.43, p < 0.01) but significantly overestimated. Predicted BMR was significantly lower than the BMR ­measured by indirect calorimetry (1,193 ± 186 vs. 1,262 ± 155 kcal/day, p < 0.01). Conclusions: The present ACC and questionnaire showed acceptable correlation of TEE and PAL compared with DLW method in elderly patients with T2DM. Systematic errors in estimating TEE may be improved by the better equation for predicting BMR.

The effects of a brain-friendly diet on metabolic and physiological parameters and cognitive performance (Brave study)

AbstractCognitive performance is related to lipid and glucose metabolism and metabolic activation that are regulated by diet. Further, there is good evidence to support that change in lifestyle, for instance in diet, may promote cognitive health. However, vast majority of the existing studies have focused on children or older adults. We studied the effects of a brain-friendly diet (Brainfood) on metabolic and physiological parameters and cognitive performance in office workers at assumed metabolic risk. We conducted a diet-switch, 4-week intervention study on 84 volunteers with elevated plasma LDL levels in pre-screening. The brainfood diet was planned to be optimal for metabolism and cognitive function; special attention was paid for regular meal frequency, a well-balanced light lunch at work and optimised recipes ensuring quality of carbohydrates and fat, and sufficient protein amount. The control diet was a typical western diet. Breakfast supplies, lunch and afternoon snacks were provided to participants, and they received nutritional counselling. Participants' sociodemographic characteristics, such as age and sex, were queried in the beginning of the intervention. Plasma samples were collected at the end of the 2-week lead-in period, and control and intervention periods. The samples were analysed using high-throughput nuclear magnetic resonance (NMR) spectrometry for quantification of lipoprotein subclasses and particle sizes, cholesterol, glycerides, phospholipids, apolipoproteins, fatty acids, amino acids, ketone bodies, fluid balance, glycolysis and inflammation markers. Participants completed a 3-day food diary at the end of the 2-week lead-in period, and control and intervention periods. Anthropometric measurements (height and weight) were measured at the same timepoints by a study nurse. Physical activity was instructed to be maintained at the pre-study level during the whole study period and it was monitored by using a 3-axial accelerometer (Active style Pro HJA, Omron, Japan). Cognition was measured with standardized neuropsychological tests (Bourdon-Wiersma, FAT, N-Back, NASA-TLX, KSS, RAVLT, Stroop, WMS-III, task-switching) under a psychologist's supervision and as tablet, PC or online tests. Brainfood reduced saturated fat and salt intakes and increased polyunsaturated fat, fibre, vitamin C and D, iron and magnesium intakes. Favourable effects were seen in the atherogenic lipid measurements, such as fatty acids, LDL, IDL and small VLDL, as well as fatty acids, phospholipids and glutamine. Intervention did not affect the physiological or cognitive parameters except for a decrease in inaccuracy of visual attention (p = 0.027). In conclusion, the Brainfood diet could be recommended for office workers as a healthy diet following Nordic nutrition recommendations.

The Choice of Pedometer Impacts on Daily Step Counts in Primary School Children under Free-Living Conditions.

Background: We examined whether daily step counts under free-living conditions differed among four types of pedometers used by primary school children. Methods: In Study one, we compared the Yamax SW-200 (widely used in research) and the Kenz Lifecorder (accelerometer-based pedometer) in 30 children (6–12 years). In Study two, after confirming good correlation between these devices, we used Kenz Lifecorder as the criterion device and compared it with the Yamasa EX-200 (pants pocket-type pedometer) and the Omron Active style Pro (accelerometer-based pedometer) among 48 (7–12 years) or 108 children (7–12 years). Results: In Study one, comparable mean step counts between pedometers were observed. The correlation was strong (r = 0.91); the average difference between these two pedometers was +4.5%. In Study two, the average differences between Kenz Lifecorder and Yamasa EX-200 and Kenz Lifecorder and Omron Active style Pro were −7.9% and −18.2%, respectively, and those were not significantly equivalent according to the two one-sided-tests method. The correlations between Yamasa or Omron Active style Pro and Lifecorder were moderate and strong, respectively. Conclusions: The choice of pedometer had a substantial impact on step counts. A consensus on the appropriate pedometer for quantifying daily step counts is needed for evidence-based recommendations for health promotion.

Validity of estimating physical activity intensity using a triaxial accelerometer in healthy adults and older adults

BackgroundA triaxial accelerometer with an algorithm that could discriminate locomotive and non-locomotive activities in adults has been developed. However, in the elderly, this accelerometer has not yet been validated. The...

Physical Activity and Sedentary Behavior Assessment: A Laboratory-Based Evaluation of Agreement between Commonly Used ActiGraph and Omron Accelerometers.

Different models of accelerometer have the potential to provide a different estimate of the same physical activity or sedentary behavior. Our study compared the outputs of the Active Style Pro (ASP) and ActiGraph (AG) devices in assessing predicted metabolic equivalents (METs) for specific activities under laboratory conditions. Thirty healthy young adults wore two hip accelerometers (ASP and AG), simultaneously while performing twenty-two activities (eight sedentary, eight household, and six ambulatory activities) in a controlled laboratory setting. For the AG, predicted METs for each activity was calculated using four equations based on vertical-axis and vector magnitude data. Separate paired t-tests and Bland–Altman analysis examined the difference and agreement in METs between AG using four commonly used equations and ASP measurements for each activity. AG devices using different equations calculated significantly different outcomes for most activities compared with ASP devices. The smallest differences in predicted METs estimates between ASP and AG were observed for ambulatory activities. Ambulatory activities demonstrated the best agreement between ASP and AG regardless of which AG equation was used. Our findings can be used to assist researchers in their selection of accelerometer and output estimation equations for measuring physical activity and sedentary behavior in adults.

Accuracy of 12 Wearable Devices for Estimating Physical Activity Energy Expenditure Using a Metabolic Chamber and the Doubly Labeled Water Method: Validation Study.

BackgroundSelf-monitoring using certain types of pedometers and accelerometers has been reported to be effective for promoting and maintaining physical activity (PA). However, the validity of estimating the level of PA or PA energy expenditure (PAEE) for general consumers using wearable devices has not been sufficiently established.ObjectiveWe examined the validity of 12 wearable devices for determining PAEE during 1 standardized day in a metabolic chamber and 15 free-living days using the doubly labeled water (DLW) method.MethodsA total of 19 healthy adults aged 21 to 50 years (9 men and 10 women) participated in this study. They followed a standardized PA protocol in a metabolic chamber for an entire day while simultaneously wearing 12 wearable devices: 5 devices on the waist, 5 on the wrist, and 2 placed in the pocket. In addition, they spent their daily lives wearing 12 wearable devices under free-living conditions while being subjected to the DLW method for 15 days. The PAEE criterion was calculated by subtracting the basal metabolic rate measured by the metabolic chamber and 0.1×total energy expenditure (TEE) from TEE. The TEE was obtained by the metabolic chamber and DLW methods. The PAEE values of wearable devices were also extracted or calculated from each mobile phone app or website. The Dunnett test and Pearson and Spearman correlation coefficients were used to examine the variables estimated by wearable devices.ResultsOn the standardized day, the PAEE estimated using the metabolic chamber (PAEEcha) was 528.8±149.4 kcal/day. The PAEEs of all devices except the TANITA AM-160 (513.8±135.0 kcal/day; P>.05), SUZUKEN Lifecorder EX (519.3±89.3 kcal/day; P>.05), and Panasonic Actimarker (545.9±141.7 kcal/day; P>.05) were significantly different from the PAEEcha. None of the devices was correlated with PAEEcha according to both Pearson (r=−.13 to .37) and Spearman (ρ=−.25 to .46) correlation tests. During the 15 free-living days, the PAEE estimated by DLW (PAEEdlw) was 728.0±162.7 kcal/day. PAEE values of all devices except the Omron Active style Pro (716.2±159.0 kcal/day; P>.05) and Omron CaloriScan (707.5±172.7 kcal/day; P>.05) were significantly underestimated. Only 2 devices, the Omron Active style Pro (r=.46; P=.045) and Panasonic Actimarker (r=.48; P=.04), had significant positive correlations with PAEEdlw according to Pearson tests. In addition, 3 devices, the TANITA AM-160 (ρ=.50; P=.03), Omron CaloriScan (ρ=.48; P=.04), and Omron Active style Pro (ρ=.48; P=.04), could be ranked in PAEEdlw.ConclusionsMost wearable devices do not provide comparable PAEE estimates when using gold standard methods during 1 standardized day or 15 free-living days. Continuous development and evaluations of these wearable devices are needed for better estimations of PAEE.

Associations of neighborhood walkability with intensity- and bout-specific physical activity and sedentary behavior of older adults in Japan.

We examined the relationships of objectively-measured walkability with accelerometer-measured activity patterns including bout-specific moderate-to-vigorous physical activity (MVPA), light-intensity physical activity (LPA) and sedentary behavior in older Japanese adults. This cross-sectional study included 450 men and women (mean age 74 years) who were randomly selected from a resident registry of each municipality (Bunkyo, Fuchu and Oyama city). Neighborhood walkability was assessed using geographic information system data and activity patterns by a validated accelerometer (Active style Pro HJA-350IT). MVPA was assessed as overall (all minutes), short-bout (<10 min) and long-bout (≥10 min). We used analysis of covariance to examine environmental relationships with the three MVPA measures, LPA and sedentary behavior by quartiles of walkability, adjusting for accelerometer wear time and sociodemographic, behavioral and health-related factors. In total, 27% of participants achieved ≥150 min/week of long-bout MVPA. Walkability was not associated with overall MVPA (Q1 = 35.0, Q2 = 31.9, Q3 = 31.4, Q4 = 34.2 min/day) Older adults living in low-walkability areas significantly accumulated more short-bout MVPA (Q1 = 27.2, Q2 = 22.1, Q3 = 20.1, Q4 = 20.5 min/day) and LPA (Q1 = 346, Q2 = 311, Q3 = 289, Q4 = 284 min/day), but less sedentary behavior (Q1 = 479, Q2 = 520, Q3 = 544, Q4 = 544 min/day) than those living in high-walkability areas. Those living in low-walkability areas accumulated more LPA and short-bout MVPA. These activities might be helpful targets for initiatives to promote physical activity among older adult residents of low-walkability areas. Geriatr Gerontol Int 2019; 19: 861-867.

Association between age at onset of independent walking and objectively measured sedentary behavior is mediated by moderate-to-vigorous physical activity in primary school children

ObjectiveAge at onset of walking has been shown as an early predictor of physical activity in infants and children. However, little is known about whether age at onset of walking may predict sedentary behavior (SB). The aim of the present study was to examine the association between the timing of onset of walking and objectively measured SB, and whether this association is mediated by moderate-to-vigorous physical activity (MVPA) in children.MethodsThe subjects were 388 elementary school children aged 6–12 years. Current weight and height data were collected. Birth weight and the age in months the child first walked independently were reported based on the parents’ recall. Children’s SB and physical activity were objectively measured using a triaxial accelerometer (Active style Pro HJA-350IT, OMRON). The following summary outcome variables were derived from accelerometer data: Time (min/day) spent in SB (≤1.5 metabolic equivalents [METs]) and MVPA (≥3.0 METs).ResultsThe mean ± SD time (min/day) spent in sedentary was 376 ± 62 and MVPA was 67.6 ± 20.8. Multiple linear regression analyses revealed that a later age at independent walking was associated with increased time spent in SB (β = 0.15, P < 0.001) and decreased time spent in MVPA (β = -0. 18, P < 0.001) after adjusting for gender, birth weight, current age, body weight, schools, and time spent wearing the accelerometer. When MVPA was introduced as a covariate in the model predicting SB, the association between the age at independent walking and time spent in SB was completely attenuated (β = 0.04, P = 0.215), while MVPA was significantly associated with SB (β = -0.61, P < 0.001).ConclusionsOur results indicate that infants who walked at a later age spent more time in SB in childhood, and this association is mediated by MVPA. Appropriate interventions which focus on increasing MVPA and thereby reducing SB may be beneficial in infants who demonstrate a later age at onset of independent walking.

Objectively evaluated physical activity and sedentary time in primary school children by gender, grade and types of physical education lessons

BackgroundDuring the typical school day, physical education (PE) gives children an opportunity for physical activity (PA) and reduces their sedentary time, but little is known about objectively evaluated PA and sedentary time during PE lessons and the differences across genders and grades. There is also a lack of research comparing PA and sedentary time among the different types of PE lessons. The primary aim of this study was to examine primary school students’ moderate-to-vigorous PA (MVPA) levels and sedentary time during PE and whether there are gender or grade differences in a cross-sectional study. The secondary aim was to determine which types of PE lessons are best for increasing PA and reducing sedentary time.MethodsObjectively evaluated MVPA and sedentary time during PE lessons in Japan with a triaxial accelerometer (Active style Pro HJA-350IT, Omron Healthcare) in girls (n = 221) and boys (n = 181). Minutes of sedentary time were categorized into metabolic equivalents (METs): categories ranged from sedentary time (METs ≤1.5) to MVPA (METs ≥3.0). Time tables and PE lesson types were evaluated using logs maintained by the class teachers.ResultsTime spent in MVPA and sedentary time were 27.3 and 24.3%, respectively. After adjustments for grade, relative body weight and school, boys spent significantly more time in MVPA compared with girls, but with an estimated mean difference of approximately 1 min. After adjustment for gender, relative body weight and school, the younger grades (1st and 2nd) spent significantly more time in MVPA and significantly less time in sedentary time compared with other grades. Moreover, after adjustments for gender, grade, relative body weight and school, the time spent in MVPA during gymnastic and track and field lessons was significantly lower than that during ball game lessons. Sedentary time during gymnastic lessons was significantly longer than in track and field and ball game lessons.ConclusionsChildren did not engage in much MVPA and also spent time in sedentary time during PE, but there are no gender differences. The children were most active during ball game lessons. Therefore, it is important to increase MVPA and reduce sedentary time during PE in both genders.

Verification of a Motion Sensor for Evaluating Physical Activity in COPD Patients.

Background Objective evaluation of the physical activity (PA) in patients with chronic obstructive pulmonary disease (COPD) is important. We validated a triaxial accelerometer, Active Style Pro HJA-750C® (HJA), and evaluated the necessary conditions for obtaining reproducible data. Methods The PA measured by HJA was compared with that measured by two already validated accelerometers in 11 patients with COPD (age: 76.6 ± 6.9, FEV1% predicted: 57.6 ± 18.6). Then, the influence of weather and holidays on the PA and the required number of days to obtain repeatability were examined in 21 patients with COPD (age: 73.0 ± 8.0, FEV1% predicted: 58.7 ± 19.0). Results The PA values measured by HJA and those by DynaPort Move Monitor® (DMM) or Actimarker® (AM) were significantly correlated at all intensities (p=0.024 at ≥4.0 METs by DMM and p < 0.0001 at the rest) except at ≥4.0 METs by AM, though the values measured by HJA were higher than those by AM which was reported to underestimate PA. The durations of PA on rainy days were significantly shorter than those on nonrainy days, but those on holidays were not different from those on weekdays. The values of ICC for 3, 4, or 5 days were higher than 0.8 at all intensities. The PA measured by HJA was correlated with the dyspnea scale FVC and age and tended to correlate with FEV1. Conclusions The HJA was validated for evaluating the PA in patients with COPD. This trial is registered with UMIN000016363.

The known-groups validity of intensity-based physical activity measurement using an accelerometer in people with subacute stroke.

[Purpose] This study aimed to assess the known-groups validity of the estimated metabolic equivalents during physical activities using accelerometer, Active Style Pro HJA 350-IT, in people with subacute stroke. [Subjects and Methods] Ten participants with subacute stroke and ten healthy people performed six activities (lying, sitting, standing, sitting with reaching task, standing with reaching task, and walking) and metabolic equivalents were estimated using the accelerometer during each activity. These estimated metabolic equivalents were compared with reported metabolic equivalents through compendiums or previous studies. Additionally, the estimated metabolic equivalents were compared between subacute stroke and healthy control participants. [Results] The estimated metabolic equivalents of both groups during maintaining posture showed significantly lower values in comparison with previous studies. There were no significant differences between the estimated metabolic equivalents during sitting with reaching tasks or standing with reaching tasks when compared with compendium metabolic equivalents across both groups. The estimated metabolic equivalents during walking were inevitable values significantly differed from previous study which conducted with stroke patients with lower gait abilities in both groups. [Conclusion] The estimated metabolic equivalents using accelerometer may be suitable to assess movement activity rather than motionless activity, and accelerometer demonstrated acceptable validity in people with subacute stroke.

Comparability of activity monitors used in Asian and Western-country studies for assessing free-living sedentary behaviour

This study aims to compare the outputs of the waist-worn Active style Pro HJA-350IT (ASP; used in studies with Asian populations), the waist-worn ActiGragh™GT3X+ using the normal filter (GT3X+) and the thigh-worn activPAL3 (AP) in assessing adults’ sedentary behaviour (total sedentary time, number of breaks) under free-living conditions. Fifty healthy workers wore the three monitors simultaneously during their waking hours on two days, including a work day and a non-work day. Valid data were at least 10 hours of wearing time, and the differences between monitors on the sedentary outputs using the AP as criterion measurement were analyzed by ANOVA. The number of participants who had complete valid data for work day and non-work day was 47 and 44, respectively. Total sedentary time and breaks estimated by the AP were respectively 466.5 ± 146.8 min and 64.3 ± 24.9 times on the work day and 497.7 ± 138.3 min and 44.6 ± 15.4 times on the non-work day. In total sedentary time, the ASP estimated 29.7 min (95%CI = 7.9 to 51.5) significantly shorter than the AP on the work day but showed no significant difference against the AP on the non-work day. The GT3X+ estimated 80.1 min (54.6 to 105.6) and 52.3 (26.4 to 78.2) significantly longer than the AP on the work day and the non-work day, respectively. For the number of breaks from sedentary time, on both days, the ASP and the GT3X+ estimated significantly more than the AP: 14.1 to 15.8 times (6.3 to 22.5) for the ASP and 27.7 to 28.8 times (21.8 to 34.8) for the GT3X+. Compared to the AP as the criterion, the ASP can underestimate total sedentary time and the GT3X+ can overestimate it, and more so at the lower levels of sedentary time. For breaks from sedentary time, compared to the AP, both the GT3X+ the ASP can overestimate.

Association between objectively evaluated physical activity and sedentary behavior and screen time in primary school children

BackgroundEven when meeting guidelines for physical activity (PA), considerable sedentary time may be included. This study in primary school children investigated the relationships between objectively evaluated sedentary and PA times at different intensities using triaxial accelerometry that discriminated between ambulatory and non-ambulatory PA. The relationships between subjectively evaluated screen time (i.e. time spent viewing television and videos, playing electronic games, and using personal computers) and objectively evaluated sedentary and PA times were examined.MethodsObjectively evaluated sedentary and PA times were assessed for 7 consecutive days using a triaxial accelerometer (Active style Pro: HJA-350IT) in 426 first to sixth grade girls and boys. Metabolic equivalents [METs] were used to categorize the minutes of sedentary time (≤1.5 METs), light PA (LPA, 1.6–2.9 METs), moderate-to-vigorous PA (MVPA, ≥3.0 METs) and vigorous PA (VPA, ≥6.0 METs). The physical activity level (PAL) was calculated using the mean MET value. Subjectively evaluated screen time behaviors were self-reported by participants and parents acting together. The associations between PA and sedentary and screen time variables were examined using partial correlation analyses.ResultsAfter adjustment for age, body weight and wearing time, objectively evaluated sedentary time correlated strongly with non-ambulatory and total LPA and PAL, moderately with ambulatory LPA, non-ambulatory or total MVPA, and weakly with ambulatory MVPA, ambulatory, non-ambulatory or total VPA. Subjectively evaluated screen time was not associated significantly with objectively evaluated sedentary and PA times or PAL. On average, each reduction of 30 min in daily sedentary time was associated with 6 or 23 min more of MVPA or LPA, respectively.ConclusionsThese findings show that higher daily sedentary time may be compensated mainly by lower LPA, while the association between sedentary time and MVPA was moderate. Therefore, improving MVPA and reducing sedentary time are important in primary school children.