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We compared the improvement in components of metabolic syndrome (MS) before and after lifestyle modification, as determined by daily step counts (on a wrist-worn Fitbit®) in participants with and without MS recruited from volunteers attending medical health checkup programs. A linear mixed model was used to analyze the change in MS components between participants with and without MS by group × time interaction. Multiple logistic regression analysis after adjustment for confounders was used to obtain odds ratios (ORs) and 95% confidence intervals (CIs) for improvements in MS components per 1000-steps/day increments. Waist circumference, triglycerides, fasting plasma glucose, and diastolic blood pressure were significantly different between participants with and without MS (group × time: p = 0.010, p < 0.001, p = 0.025, and p = 0.010, respectively). Multivariable-adjusted ORs (95% CI) of improvement in MS components per 1000-steps/day increments were 1.24 (1.01–1.53) in participants with and 1.14 (0.93–1.40) in participants without MS. Walking improved MS components more in individuals with than without MS. From a public health perspective, walking should be encouraged for high-risk MS individuals.

(1) Background: This study examined the cross-sectional association between metabolic syndrome (MetS) status classified into three groups and daily physical activity (PA; step count and active minutes) using a wearable device in Japanese office workers. (2) Methods: This secondary analysis used data from 179 participants in the intervention group of a randomized controlled trial for 3 months. Individuals who had received an annual health check-up and had MetS or were at a high risk of MetS based on Japanese guidelines were asked to use a wearable device and answer questionnaires regarding their daily life for the entire study period. Multilevel mixed-effects logistic regression models adjusted for covariates associated with MetS and PA were used to estimate associations. A sensitivity analysis investigated the associations between MetS status and PA level according to the day of the week. (3) Results: Compared to those with no MetS, those with MetS were not significantly associated with PA, while those with pre-MetS were inversely associated with PA [step count Model 3: OR = 0.60; 95% CI: 0.36, 0.99; active minutes Model 3: OR = 0.62; 95% CI: 0.40, 0.96]. In the sensitivity analysis, day of the week was an effect modifier for both PA (p < 0.001). (4) Conclusions: Compared to those with no MetS, those with pre-MetS, but not MetS, showed significantly lower odds of reaching their daily recommended PA level. Our findings suggest that the day of the week could be a modifier for the association between MetS and PA. Further research with longer study periods and larger sample sizes are needed to confirm our results.

The increasing ubiquity of smartphone data, with greater spatial and temporal coverage than achieved by traditional study designs, have the potential to provide insight into habitual physical activity patterns. This study implements and evaluates the utility of both K-means clustering and agglomerative hierarchical clustering methods in identifying weekly and yearlong physical activity behaviour trends. Characterising the demographics and choice of activity type within the identified clusters of behaviour. Across all seven clusters of seasonal activity behaviour identified, daylight saving was shown to play a key role in influencing behaviour, with increased activity in summer months. Investigation into weekly behaviours identified six clusters with varied roles, of weekday versus weekend, on the likelihood of meeting physical activity guidelines. Preferred type of physical activity likewise varied between clusters, with gender and age strongly associated with cluster membership. Key relationships are identified between weekly clusters and seasonal activity behaviour clusters, demonstrating how short-term behaviours contribute to longer-term activity patterns. Utilising unsupervised machine learning, this study demonstrates how the volume and richness of secondary app data can allow us to move away from aggregate measures of physical activity to better understand temporal variations in habitual physical activity behaviour.

Paths for All’s 8-week online Workplace Step Count Challenge (SCC) is a flagship program of Scotland’s National Walking Strategy. The aim of this study was to examine changes in step counts throughout the duration of the SCC, across four years of delivery. Participants were those who registered for the 2015–2018 SCCs, and reported demographic data at registration. Participants self-reported their device-measured step count for each day of the SCC. Following data screening, mean daily steps for each week were calculated. Linear mixed models (R nlme procedure), controlling for the within subject nature of the step count measure, were used to explore changes in steps over time. Gender and age group (&lt, 45 years, ≥45 years) were entered into a subsequent model. Separate models were created for each year of the SCC and for all years combined. Participants (n = 10,183) were predominantly women (76.8%), aged &lt, 45 (54.6%) and ≥45 years. In general, steps increased each week compared to week 1 (p &lt, 0.001), with a significant increase evident at all but seven of 28 data points. Across the four years of SCC, the increase in steps at week 8 compared to week 1 ranged from 506 to 1223 steps per day, making a substantial contribution to the recommended physical activity levels for health. There was no consistent age or gender effect. The findings provide support for the continued investment in such workplace interventions.

The current social, health, and educational changes in society require an adequate response in school-based physical activity (PA), including physical education (PE) lessons. The objective of this study was to identify the real average step counts of Czech and Polish adolescents during PE lessons, and propose recommendations for improving PE programs. This research was carried out in 143 Czech and 99 Polish schools. In the research, a total of 4911 adolescents aged 12&ndash, 18 years were analyzed as part of teaching practice and 1827 in the context of habitual school practice. Steps were monitored using pedometers. The average step count per PE lesson was 2390 in Czech and Polish boys, while girls achieved 1851 steps. In both countries, boys were subject to greater physical strain in PE lessons compared to girls, both in teaching practice (F(4088,3) = 154.49, p &lt, 0.001, &eta, p2 = 0.102) and school practice (F(1552,3) = 70.66, p &lt, p2 = 0.103). Therefore, the priority in PE lessons is to increase the amount of PA for girls, achieve the objectives of PE during PA, and use wearables to improve awareness of PA and improve physical literacy, as well as to support hybrid and online PE as a complement to traditional PE.

Thailand&rsquo, s first national steps challenge has been implemented in 2020 with the goal to raise the level of physical activity nationwide by monitoring achievements through a smartphone application. This study examined the daily step counts of participants in the first national steps challenge. Six data points from 186,653 valid participants were retrieved and analyzed in five periods using Poisson regression. The mean daily steps peaked at 3196 in Period 1, and steadily dropped to 1205 in Period 5. The daily steps per period were analyzed using the participants&rsquo, characteristics, such as the type of participant, sex, age, body mass index, and area of residence. The overall mean daily steps of the participants meant physical activity was far below the recommended level and tended to drop in later periods. The general population achieved significantly higher mean daily steps than public health officers or village health volunteers (24.0% by multivariate analysis). Participants who were female, younger (&lt, 45 years), obese (body mass index &gt, 30), and living in rural areas had fewer mean daily steps (13.8%, 44.3%, 12.7%, and 14.7% by multivariate analysis, respectively), with statistical significance. In the future, the national steps challenge should be continuously implemented by counting all steps throughout a day, using more strategies to draw attention and raise motivation, advocating for more participants, as well as reporting the whole day step counts instead of distance.

Objectives: This paper describes the development of a physical activity questionnaire (PAQ) designed for Chinese adolescents and their mothers in urban and rural settings, and reports on results of the PAQ, pedometry, and hand grip dynamometry from the Chinese Children and Families Cohort Study pilot investigation (CFCS). Methods: As part of a pilot investigation to evaluate the feasibility to follow-up and obtain detailed nutrition, dietary, physical activity, and ultraviolet radiation (UVR) data from CFCS participants, data were collected in 2013 for 93 adolescent/mother pairs from a rural (n = 41) and an urban site (n = 52) in two provinces. Respondents were asked to wear a pedometer for seven days (Omron HJ-151), use a Takei Digital Grip Strength Dynamometer on (each hand, three trials, two separate days), and complete a 39 item, eight domain PAQ covering the past year. Self-reported physical activity (PA) was linked to metabolic equivalent of task (MET) scores in kcal/kg/hr and used to calculate METs for different domains of PA and intensity categories. Results: Compliance was high (95%) in this measurement protocol administered by health staff during a series of data collection efforts at home and local clinics or health centers. Step counts were highly variable, averaging between 5000 and 10000 per day with somewhat higher step counts in rural adolescent boys. Maximum grip strength (Kgs) was greater in children (Mean = 36.5, SE = 0.8) than mothers (Mean = 28.8, SE = 0.8) and similar in the urban (Mean = 29.6, SE = 0.6) compared to the rural (Mean = 29.6, SE = 0.5) communities overall. Grip strength, step counts, and measures of time spent in different activities or activity intensities were uncorrelated. Conclusion: Device and question-based measurement of PA and strength were readily accepted in these Chinese urban and rural populations. The PAQ on physical activity in the past year produced some plausible population averages, but individual responses suggested recall challenges. If data about specific activities are required, future studies should explore use of standardized survey questions concerning such fewer specific activities or instruments examining shorter time periods such as one, three, or seven day recalls.

Monitoring the real-life mobility of stroke patients could be extremely useful for clinicians. Step counters are a widely accessible, portable, and cheap technology that can be used to monitor patients in different environments. The aim of this study was to validate a low-cost commercial tri-axial accelerometer-based step counter for stroke patients and to determine the best positioning of the step counter (wrists, ankles, and waist). Ten healthy subjects and 43 post-stroke patients were enrolled and performed four validated clinical tests (10 m, 50 m, and 6 min walking tests and timed up and go tests) while wearing five step counters in different positions while a trained operator counted the number of steps executed in each test manually. Data from step counters and those collected manually were compared using the intraclass coefficient correlation and mean average percentage error. The Bland&ndash, Altman plot was also used to describe agreement between the two quantitative measurements (step counter vs. manual counting). During walking tests in healthy subjects, the best reliability was found for lower limbs and waist placement (intraclass coefficient correlations (ICCs) from 0.46 to 0.99), and weak reliability was observed for upper limb placement in every test (ICCs from 0.06 to 0.38). On the contrary, in post-stroke patients, moderate reliability was found only for the lower limbs in the 6 min walking test (healthy ankle ICC: 0.69, pathological ankle ICC: 0.70). Furthermore, the Bland&ndash, Altman plot highlighted large average discrepancies between methods for the pathological group. However, while the step counter was not able to reliably determine steps for slow patients, when applied to the healthy ankle of patients who walked faster than 0.8 m/s, it counted steps with excellent precision, similar to that seen in the healthy subjects (ICCs from 0.36 to 0.99). These findings show that a low-cost accelerometer-based step counter could be useful for measuring mobility in select high-performance patients and could be used in clinical and real-world settings.

Wearable activity trackers can motivate older adults to engage in the recommended daily amount of physical activity (PA). However, individuals may not maintain their use of the trackers over a longer period. To investigate the attitudes of activity tracker adoption and their effects on actual PA performance, we conducted a three-month study. We gave activity trackers to 16 older adults and assessed attitudes on activity tracker adoption through a survey during the study period. We extracted participants&rsquo, PA measures, step counts, and moderate and vigorous physical activity (MVPA) times. We observed significant differences in adoption attitudes during the three different periods (&chi, 2(2, 48) = 6.27, p &lt, 0.05), and PA measures followed similar decreasing patterns (F(83, 1357) = 12.56, 13.94, p &lt, 0.00001). However, the Pearson correlation analysis (r = 0.268, p = 0.284) and a Bland&ndash, Altman plot indicated a bias between two PA measures. Positive attitudes at the initial stage did not persist through the study period, and both step counts and length of MVPA time showed waning patterns in the study period. The longitudinal results from both measures demonstrated the patterns of old adults&rsquo, long-term use and adoption. Considering the accuracy of the activity tracker and older adults&rsquo, athletic ability, MVPA times are more likely to be a reliable measure of older adults&rsquo, long-term use and successful adoption of activity trackers than step counts. The results support the development of better activity tracker design guidelines that would facilitate long-term adoption among older adults.

The purpose of this study was to apply compositional data analysis (CoDA) for the analysis of segmented school step counts and associate the school step count composition to body mass index (BMI) z-scores in a sample of children. Participants were 855 (51.8% female) children recruited from the fourth and fifth grades from four schools following a 7-h school schedule. Using piezoelectric pedometers, step count data were collected during physical education, recess, lunch, and during academic class time. A multi-level mixed effects model associated the step count composition with BMI z-scores. Compositional isotemporal substitution determined changes in BMI z-scores per reallocation of steps between pairs of school segments. A higher percentage of steps accrued during physical education (b = −0.34, 95%CI: −0.65–−0.03, p = 0.036) and recess (b = −0.47, 95%CI: −0.83–−0.11, p = 0.012), relative to other segments, was associated with lower BMI z-scores. Specifically, a 5% to 15% reallocation of steps accrued during lunchtime to either physical education or recess was associated with lower BMI z-scores, ranging from −0.07 to −0.25 standard deviation units. Focusing school-based promotion of physical activity during physical education and recess may have greater relative importance if targeted outcomes are weight-related.

Background: The main aim of this study was to quantify the associations between parents&rsquo, and children&rsquo, s physical activity by age, gender, and the day of the week on the basis of a pedometer-measured step count (SC). Methods: The sample comprised data from 4-to 16-year-old children and their parents from the Czech Republic (1102 mother-child dyads and 693 father-child dyads). The parents and their children wore the Yamax SW200 pedometer during seven days of monitoring. Results: The strongest SC association was found between mothers and daughters aged 4&ndash, 7.9 years on weekdays (rp = 0.402, p &lt, 0.01) and at weekends (rp = 0.577, 0.01). In children aged 8&ndash, 16, the parent-child association is gender-specific, with the father-son relationship being dominant, especially at weekends (weekend SC: fathers-sons8&ndash, 11.9 y rp = 0.416, p &lt, 0.01, fathers-sons12&ndash, 16 y rp = 0.443, p &lt, 0.01). An increase of 1000 steps in the fathers (mothers) is associated with an increase of more than 400 (200) steps in their sons (daughters). Conclusions: This study confirms a strong parent-child SC relationship in children younger than eight years of age. In older children, the parent-child SC association is gender-specific and dominated by the father-son relationship, particularly on weekends. The SC associations that are revealed can be used for the development of physical activity programs for adolescents.

Due to the increasing prevalence of childhood obesity, the association between classroom furniture and energy expenditure as well as physical activity was examined using a standing-desk intervention in three central-Texas elementary schools. Of the 480 students in the 24 classrooms randomly assigned to either a seated or stand-biased desk equipped classroom, 374 agreed to participate in a week-long data collection during the fall and spring semesters. Each participant’s data was collected using Sensewear® armbands and was comprised of measures of energy expenditure (EE) and step count. A hierarchical linear mixed effects model showed that children in seated desk classrooms had significantly lower (EE) and fewer steps during the standardized lecture time than children in stand-biased classrooms after adjusting for grade, race, and gender. The use of a standing desk showed a significant higher mean energy expenditure by 0.16 kcal/min (p < 0.0001) in the fall semester, and a higher EE by 0.08 kcal/min (p = 0.0092) in the spring semester.

Purpose: This study aims to evaluate the physical activity of healthcare personnel and the affecting factors of physical activity (PA) in a hospital using an accelerometer device (Actigraph wGT3X-BT). Method: A total of 63 subjects (22 physicians, 19 nurses, and 23 supporting staff) participated and wore an accelerometer for seven days. Among the outputs, the mean counts for a minute, time spent for light, moderate, and vigorous intensity PA, and step count were extracted. As a secondary study, 16 subjects continued for one more week after feedback on their PA of the previous week and counseling to encourage PA. Result: Most of (62/63) the participants fulfilled the recommended amount of PA, which is more than 300 min of moderate to vigorous physical activity (MVPA). Physicians showed significantly less PA than nurses or supporting staffs: Mean counts per minute (210.4 vs. 476.0 and 441.8 respectively), time in MVPA per week (904.7 min vs. 1471.3 min and 1451.0 min), and step counts per week (69,029 vs. 87,119 and 84,700) (p &lt, 0.001). Nurses and supporting staff were not statistically different. There was no significant difference in the PA of workers in the hospital regarding gender and marital status. However, the average calorie expenditure of the child raising group was significantly higher. There was no statistically significant difference in PA before and after counseling. No participants reported a vigorous degree of exercise intensity over the study period. Conclusion: Most of the healthcare personnel met the recommended PA, however, only 57% (36/63) recalled having engaged in MVPA during the study period. The group of physicians showed less PA compared to nurses or supporting staff. Single check-up and counseling were not found to increase PA.

This study focuses on determining the relationship between parents’ step count (SC) and screen time (ST) and children’s SC and ST on weekdays and at weekends. The participants (278 parents aged 30–45 and their 194 children aged 4–7) were recruited from 10 randomly selected Czech kindergartens. The participants recorded SC and ST duration over a week-long monitoring (≥8 h/day) during September–October 2014 and April–May 2015. The associations between parents’ SC and ST and children’s SC and ST were estimated using general linear regression for weekdays and weekends. Each 2500 SC increase in mothers’/fathers’ daily SC at weekdays (weekends) was associated with an extra 1143/903 (928/753) daily SC in children. Each 60 min of ST increase in mothers’/fathers’ ST at weekdays (weekends) was associated with an extra 7.6/7.6 (16.8/13.0) min of child daily ST. An increase of 2500 mothers’ daily SC was associated with reduction of 2.5 (7.5) min of ST in children at weekdays (weekends). This study reveals a significant relationship between parent-child SC/day, parent-child ST/day, and mothers’ ST and children’s SC at weekends. Weekend days seem to provide a suitable space for the promotion of joint physical activity in parents and their pre-schoolers.

This study assessed and compared the daily step counts recorded by two different motion sensors in order to estimate the free-living physical activity of 135 adolescent girls. Each girl concurrently wore a Yamax pedometer and an ActiGraph accelerometer (criterion measure) every day for seven consecutive days. The convergent validity of the pedometer can be considered intermediate when used to measure the step counts in free-living physical activity; but should be considered with caution when used to classify participants’ step counts into corresponding physical activity categories because of a likelihood of ‘erroneous’ classification in comparison with the accelerometer.

Physical activity (PA) is crucial for maintaining good health of older adults and owning a dog and walking it can enforce it. The purpose of this study was to evaluate the effect of dog ownership on PA in older adults as well as its positive impact on perceived degree of health, and sleep. There were 44 participants of mean age 68 ± 5.4 years (18 males, 26 females) enrolled in this study (dog owners—DO, n = 26; non-dog owners—NDO, n = 18). Xiaomi Mi Band 2 accelerometer, International Physical Activity Questionnaire- Short form (IPAQ-Short Form) and SF-36 questionnaires were used to measure the level of PA, sleep, and subjective health. A statistically significant difference was observed in favor of dog owners in most of the monitored parameters. All accelerometer PA parameters (step count, activity time, distance, calories) showed a significant difference at a p < 0.01. Sleep parameters were significant in total sleep length (p = 0.05) and light sleep length (p < 0.05). DO reported higher total PA time (min/week), MET/min/week spent in walking, and spent calories/week (p < 0.05). In SF-36 they reported higher score (p < 0.05) in general health, physical functioning, social functioning, pain, vitality, and emotional well-being. Body mass index (BMI) was significantly lower in the DO group (p < 0.01). The results suggest that dog ownership may affect the overall PA and health of older adults.