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AbstractPurposeMethodResultsConclusionFinding valid and accurate methods to count steps is important after a stroke. To determine the criterion validity and accuracy of the Actigraph and Xiaomi Smart Band to count steps in individuals after stroke. To explore the influence of walking speed on the accuracy of these activity monitors.Individuals after stroke performed the 2-min Walk Test while wearing the ActiGraph and Xiaomi Smart Band. The 2-min Walk Test was recorded, and the observed step count was compared with the estimated step count of both activity monitors.Fifty individuals after stroke were included. The ActiGraph had a low correlation (rho 0.41) between observed and estimated step count and a high percentage absolute error (39%). The Xiaomi Smart Band had a high correlation (rho 0.83) and a moderate percentage absolute error (12%). At high walking speeds, the Xiaomi Smart Band had a low percentage absolute error (3%) and at slow walking speeds had 18% a moderate percentage absolute error.The Xiaomi Smart Band has good criterion validity and moderate-to-high accuracy counting steps after stroke. It is a low-cost activity monitor that is a viable alternative to the more expensive activity monitors used in research.IMPLICATIONS FOR REHABILITATIONThe ActiGraph has low criterion validity and accuracy at counting steps after stroke.The Xiaomi Smart Band has good criterion validity and accuracy at counting steps after a stroke.The Xiaomi Smart Band is a low-cost activity monitor that is a viable alternative to the more expensive activity monitors used in research.The ActiGraph has low criterion validity and accuracy at counting steps after stroke.The Xiaomi Smart Band has good criterion validity and accuracy at counting steps after a stroke.The Xiaomi Smart Band is a low-cost activity monitor that is a viable alternative to the more expensive activity monitors used in research. [ABSTRACT FROM AUTHOR]

OBJECTIVE To compare a commercially available accelerometer, FitBark 2 (FitBark 2nd Generation; FitBark) with a previously validated accelerometer, Actical (Actical; Respironics Inc) during periods of activity and rest. We hypothesized that the FitBark 2 would correlate strongly with the Actical during periods of activity and rest. METHODS 20 dogs between the ages of 1 and 9 years of variable sex, breed, and body weight were enrolled from April through August 2022 in a 1-week pilot trial. Dogs were fitted with a neck collar with both devices mounted on it and wore it continuously for 1 week. Six time points were established to evaluate varying degrees of activity and periods of rest, which included the week, a 1-mile walk, the day of the walk, the hour the walk occurred in, 6 AM to 7 AM on the morning of the walk, and 11 PM to 12 AM on the evening of the walk. Actical and FitBark 2 were compared using linear regression and correlation analysis. RESULTS Correlation analysis revealed a very strong correlation between the Actical and FitBark 2 during the entire week of the study, with a moderate correlation at other time points. Linear regression revealed the strength of the relationship by the r² = 0.85, F1,13 = 76.08. CONCLUSIONS FitBark 2 can be used to evaluate the activity and rest of dogs with varying degrees of correlation when compared to the Actical. CLINICAL RELEVANCE The time period assessed impacts the correlation of the FitBark 2 and Actical. This should be considered when using the FitBark 2 for data collection. [ABSTRACT FROM AUTHOR]

Determine the level of agreement of three activity monitors compared with the gold standard (video review) on the activity level of patients with stroke. A prospective, observational, agreement study was performed on 47 individuals with sub-acute stroke in an inpatient rehabilitation facility. Data was collected during one physical therapy session. Individuals wore three device types; Actigraph (AG), Activpal (AP), and stepwatch activity monitor (SAM). Variables assessed were step counts for each limb (hemiparetic and non-hemiparetic) and percent time standing and other. Results from the activity monitors were compared to the video review and assessed for agreement using the intraclass correlation coefficient (ICC) and accuracy of mean difference from video observation. The step counts with the SAM on the non-hemiparetic limb had the highest ICC for step counts (ICC = 0.98, p < 0.001) and were overestimated with 21% accuracy. The SAM on the hemiparetic limb had 9.7% accuracy (ICC = 0.92, p < 0.001). For percent standing time all devices overestimated with poor reliability. For percent other activity time, the AP had the best accuracy and underestimated for both the hemiparetic limb (9.9% accuracy; ICC = 0.90, p < 0.001) and non-hemiparetic limb (8.3% accuracy; ICC = 0.84, p < 0.001). The use of multiple devices may be warranted to capture an accurate understanding of activity levels in this population of individuals with sub-acute stroke. There are concerns with all monitors and clinicians and researchers should be aware of what measures they are wanting to understand about their population. The stepwatch activity monitor worn on the hemiparetic limb provided the best accuracy and excellent reliability for step counts in this population of subacute stroke. For percent standing time all devices overestimated with poor reliability. For percent other time, the AP had the best accuracy and good reliability on the non-hemiparetic limb. The use of multiple devices may be warranted to capture a more accurate understanding of activity level in this population of individuals with sub-acute stroke. Clinicians and researchers need to be aware of the biases of these devices in this population. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study is to determine the validity of consumer grade step counter devices during the early recovery period after knee replacement surgery. Methods: Twenty-three participants wore a Fitbit Charge or Apple Watch Series 4 smart watch and performed a walking test along a 50-metre hallway. There were 9 males and 14 females included in the study with an average age of 68.5 years and BMI of 32. Each patient wore both the Fitbit Charge and Apple Watch while completing the walking test and an observer counted the ground truth value using a thumb-push tally counter. This test was repeated pre-operatively with no gait aid, immediately post operatively with a walker, at 6 weeks follow up with a cane and at 6 months with no gait aid. Bland-Altman plots were performed for all walking tests to compare the agreement between measurement techniques. Results: Mean overall agreement of step count for pre-operative and at 6 months for subjects walking without gait aids was excellent for both the Apple Watch vs. actual and Fitbit vs. actual with bias values ranging from − 0.87 to 1.36 with limits of agreement (LOA) ranging between − 10.82 and 15.91. While using a walker both devices showed extremely little agreement with the actual step count with bias values between 22.5 and 24.37 with LOA between 11.7 and 33.3. At 6 weeks post-op while using a cane, both the Apple Watch and Fitbit devices had a range of bias values between − 2.8 and 5.73 with LOA between − 13.51 and 24.97. Conclusions: These devices show poor validity in the early post operative setting, especially with the use of gait aids, and therefore results should be interpreted with caution. [ABSTRACT FROM AUTHOR]

We tested whether spontaneous physical activity (SPA) from accelerometers could be used in a whole room calorimeter to estimate thermic effect of food (TEF). Eleven healthy participants (n = 7 females; age: 27 ± 4 yr; body mass index: 22.8 ± 2.6 kg/m2) completed two 23-h visits in randomized order: one "fed" with meals provided and one "fasted" with no food. SPA was measured by ActivPAL and Actigraph accelerometers. Criterion TEF was calculated as the difference in total daily energy expenditure (TDEE) between fed and fasted visits and compared with three methods of estimating TEF: 1) SPA-adjusted TEF (adjTEF)—difference in TDEE without SPA between visits, 2) Wakeful TEF—difference in energy expenditure obtained from linear regression and basal metabolic rate during waking hours, 3) 24-h TEF—increase in TDEE above SPA and sleeping metabolic rate. Criterion TEF was 9.4 ± 4.5% of TDEE. AdjTEF (difference in estimated vs. criterion TEF: activPAL: −0.3 ± 3.3%; Actigraph: −1.8 ± 8.0%) and wakeful TEF (activPAL: −0.9 ± 6.1%; Actigraph: −2.8 ± 7.6%) derived from both accelerometers did not differ from criterion TEF (all P > 0.05). ActivPAL-derived 24-h TEF overestimated TEF (6.8 ± 5.4%, P = 0.002), whereas Actigraph-derived 24-h TEF was not significantly different (4.3 ± 9.4%, P = 0.156). TEF estimations using activPAL tended to show better individual-level agreement (i.e., smaller coefficients of variation). Both accelerometers can be used to estimate TEF in a whole room calorimeter; wakeful TEF using activPAL is the most viable option given strong group-level accuracy and reasonable individual agreement. NEW & NOTEWORTHY: Two research-grade accelerometers can effectively estimate spontaneous physical activity and improve the estimation of thermic effect of food (TEF) in whole room calorimeters. The activPAL demonstrates strong group-level accuracy and reasonable individual-level agreement in estimating wakeful TEF, whereas a hip-worn Actigraph is an acceptable approach for estimating 24-h TEF. These results highlight the promising potential of accelerometers in advancing energy balance research by improving the assessment of TEF within whole room calorimeters. [ABSTRACT FROM AUTHOR]

The intensity gradient is a new cutpoint-free metric that was developed to quantify physical activity (PA) measured using accelerometers. This metric was developed for use with the ENMO (Euclidean norm minus one) metric, derived from raw acceleration data, and has not been validated for use with count-based accelerometer data. In this study, we determined whether the intensity gradient could be reproduced using count-based accelerometer data. Twenty participants (aged 7–22 years) wore a GT1M, an ActiGraph (count-based), and a GT9X, ActiGraph (raw accelerations) accelerometer during both in-lab and at-home protocols. We found strong agreement between GT1M and GT9X counts during the combined in-lab activities (mean bias = 2 counts) and between minutes per day with different intensities of activity (e.g., sedentary, light, moderate, and vigorous) classified using cutpoints (mean bias < 5 min/d at all intensities). We generated bin sizes that could be used to generate IGs from the count data (mean bias = −0.15; 95% LOA [−0.65, 0.34]) compared with the original IG. Therefore, the intensity gradient could be used to analyze count data. The count-based intensity gradient metric will be valuable for re-analyzing historical datasets collected using older accelerometer models, such as the GT1M. [ABSTRACT FROM AUTHOR]

Quantitative measurement of physical activity may complement neurological evaluation and provide valuable information on patients' daily life. We evaluated longitudinal changes of physical activity in patients with Friedreich ataxia (FRDA) using remote monitoring with wearable sensors. We performed an observational study in 26 adult patients with FRDA and 13 age-sex matched healthy controls (CTR). Participants were asked to wear two wearable sensors, at non-dominant wrist and at waist, for 7 days during waking hours. Evaluations were performed at baseline and at 1-year follow-up. We analysed the percentage of time spent in sedentary or physical activities, the Vector Magnitude on the 3 axes (VM3), and average number of steps/min. Study participants were also evaluated with ataxia clinical scales and functional tests for upper limbs dexterity and walking capability. Baseline data showed that patients had an overall reduced level of physical activity as compared to CTR. Accelerometer-based measures were highly correlated with clinical scales and disease duration in FRDA. Significantly changes from baseline to l-year follow-up were observed in patients for the following measures: (i) VM3; (ii) percentage of sedentary and light activity, and (iii) percentage of Moderate-Vigorous Physical Activity (MVPA). Reduction in physical activity corresponded to worsening in gait score of the Scale for Assessment and Rating of Ataxia. Real-life activity monitoring is feasible and well tolerated by patients. Accelerometer-based measures can quantify disease progression in FRDA over 1 year, providing objective information about patient's motor activities and supporting the usefulness of these data as complementary outcome measure in interventional trials. [ABSTRACT FROM AUTHOR]

Gestational diabetes (GDM) is associated with a long-term risk of diabetes. We aimed to determine whether a text-messaging-based lifestyle support program would improve diabetes risk factors following GDM. Women with GDM were randomised following delivery to receive four text messages per week supporting a healthy lifestyle and parenting for 6 months, with feedback from an activity monitor (intervention), or to receive the activity monitor only (control). The primary outcome was a composite of weight, physical activity and dietary goals. There were 177 women randomised, with 88 intervention and 89 control participants. All the participants experienced COVID-19 lockdowns during the study. Six-month primary outcome data were obtained for 57 intervention participants and 56 controls. There were 7/57 (12%) intervention and 6/56 (11%) control participants who met the primary outcome (relative risk, 1.08; 95%CI, 0.63–1.85; p = 0.79). Two intervention participants met the dietary goals compared to none of the control participants (p = NS). The intervention participants were more likely to record >1000 steps/day (on 102 ± 59 vs. 81 ± 59 days, p = 0.03). When analysed monthly, this was not initially different but became significant 3–6 months post-partum. Interviews and surveys indicated that with the Intervention, healthier choices were made, but these were negatively impacted by COVID-19 restrictions. Participants found the messages motivational (74%) and the activity monitor useful (71%). In conclusion, no improvement in the diabetes risk factors occurred among the women receiving the text messaging intervention when affected by COVID-19 restrictions. [ABSTRACT FROM AUTHOR]

Consumer and research activity monitors have become popular because of their ability to quantify energy expenditure (EE) in free-living conditions. However, the accuracy of activity trackers in determining EE in people with Huntington's Disease (HD) is unknown. Research question: Can the ActiGraph wGT3X-B or the Fitbit Charge 4 accurately measure energy expenditure during physical activity, in people with HD compared to Indirect Calorimetry (IC) (Medisoft Ergo Card)? We conducted a cross-sectional, observational study with fourteen participants with mild-moderate HD (mean age 55.7 ± 11.4 years). All participants wore an ActiGraph and Fitbit during an incremental test, running on a treadmill at 3.2 km/h and 5.2 km/h for three minutes at each speed. We analysed and compared the accuracy of EE estimates obtained by Fitbit and ActiGraph against the EE estimates obtained by a metabolic cart, using with Intra-class correlation (ICC), Bland-Altman analysis and correlation tests. A significant correlation and a moderate reliability was found between ActiGraph and IC for the incremental test (r = 0.667)(ICC=0.633). There was a significant correlation between Fitbit and IC during the incremental test (r = 0.701), but the reliability was poor at all tested speeds in the treadmill walk. Fitbit significantly overestimated EE, and ActiGraph underestimated EE compared to IC, but ActiGraph estimates were more accurate than Fitbit in all tests. Significance: Compared to IC, Fitbit Charge 4 and ActiGraph wGT3X-BT have reduced accuracy in estimating EE at slower walking speeds. These findings highlight the need for population-specific algorithms and validation of activity trackers. • First validation of devices to capture energy expenditure in Huntington´s disease • ActiGraph and Fitbit have reduced accuracy in estimating energy expenditure • Hip-worn wearables estimate energy expenditure better than wrist-worn devices [ABSTRACT FROM AUTHOR]

Aims: Physical activity (PA) is an important target for improving clinical outcomes in heart failure (HF) patients. Nonetheless, assessing the daily PA profile in this population is a challenging task, traditionally performed using self‐report questionnaires such as the International PA Questionnaire Short Form (IPAQ‐SF). This study aimed to evaluate the concurrent validity of the IPAQ‐SF and accelerometer‐assessed PA using six published cut‐points in patients with HF and reduced or mildly reduced ejection fraction. Methods and results: The concordance between the IPAQ‐SF and a hip‐worn accelerometer regarding daily time spent performing moderate to vigorous PA in bouts of at least 10 min was assessed in 53 participants for seven consecutive days using six different cut‐points (Barnett, Dibben, Mark, Sanders, Troiano, and Vaha‐Ypya). Spearman's correlation and Bland–Altman plots were used to evaluate concurrent validity between methods. Regressions were used to study the association between patient variables, wear protocol (waking hour or 24 h), and absolute bias. The kappa index was used to evaluate the concordance between IPAQ‐SF and accelerometry for classifying patients as active or non‐active. All analyses were re‐run using non‐bouted metrics to investigate the effect of bouted versus non‐bouted analysis. The IPAQ‐SF and accelerometry showed low to negligible correlation (ρ = 0.12 to 0.37), depending on the cut‐point used. The regression analysis showed that the absolute bias was higher in participants following the waking‐hour protocol at all cut‐points except Dibben's (P ≤ 0.007). The concordance between the two methods to classify patients as active and non‐active was low when using Mark (κ = 0.23) and Barnett (κ = 0.34) cut‐points and poor for the remaining cut‐points (κ = 0.03 to 0.18). The results of the sensitivity analysis showed negligible to low correlation using non‐bouted metrics (ρ = 0.27 to 0.33). Conclusions: Moderate to vigorous PA measures using IPAQ‐SF and accelerometers are not equivalent, and we do not encourage researchers to use IPAQ‐SF alone when assessing PA in HF patients. Moreover, applying personalized collection and processing criteria is important when assessing PA in HF patients. We recommend following the 24 h protocol and selecting cut‐points calibrated in patients with cardiovascular diseases. Finally, it is necessary to develop a new tailored questionnaire that considers walking intensity and is adjusted to the current World Health Organisation recommendations, which use non‐bouted metrics. [ABSTRACT FROM AUTHOR]

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Daily steps could be a valuable indicator of real-world ambulation in Parkinson's disease (PD). Nonetheless, no study to date has investigated the minimum number of days required to reliably estimate the average daily steps through commercial smartwatches in people with PD. Fifty-six patients were monitored through a commercial smartwatch for 5 consecutive days. The total daily steps for each day was recorded and the average daily steps was calculated as well as the working and weekend days average steps. The intraclass correlation coefficient (ICC) (3,k), standard error of measurement (SEM), Bland–Altman statistics, and minimum detectable change (MDC) were used to evaluate the reliability of the step count for every combination of 2–5 days. The threshold for acceptability was set at an ICC ≥ 0.8 with a lower bound of CI 95% ≥ 0.75 and a SAM < 10%. ANOVA and Mann–Whitney tests were used to compare steps across the days and between the working and weekend days, respectively. Four days were needed to achieve an acceptable reliability (ICC range: 0.84–0.90; SAM range: 7.8–9.4%). In addition, daily steps did not significantly differ across the days and between the working and weekend days. These findings could support the use of step count as a walking activity index and could be relevant to developing monitoring, preventive, and rehabilitation strategies for people with PD. [ABSTRACT FROM AUTHOR]

Simple Summary: Automated activity monitors (AAM) represent a useful tool in estrus detection to improve reproductive performance in dairy herds. There are only a few studies, however, investigating the association between the characteristics of an estrus event (i.e., the onset, peak, and end of estrus) determined by an AAM and the timing of artificial insemination (AI) in heifers, depending on the semen type used. Therefore, this observational study was conducted to determine the association between the interval from different characteristics of estrus and the timing of AI on pregnancy per AI (P/AI). Holstein heifers were fitted with a neck-mounted AAM and inseminated either with frozen conventional or sexed semen. Heifers inseminated from 9 to 32 h after the onset of estrus had the greatest P/AI, irrespective of semen type. Investigations on the optimum timing of artificial insemination (AI) following automated activity monitoring (AAM) depending on different types of semen in heifers are limited and in part show controversial results. Therefore, the objective of this observational study was to determine the association between the timing of AI using different characteristics of estrus (i.e., the onset, peak, and end of estrus) and pregnancy per AI (P/AI) in Holstein heifers. Heifers were fitted with a neck-mounted AAM system and inseminated with frozen conventional and sexed semen. The pregnancy per AI (n = 4159) from 2858 heifers from six commercial dairy farms in Germany inseminated upon the alert of an AAM system was evaluated. Estrous intensity was classified based on peak activity into low (35 to 89 index value) and high (90 to 100 index value). We detected a quadratic association between the interval from the onset of estrus to AI and P/AI (p = 0.02). The greatest P/AI was observed for heifers inseminated from 9 to 32 h after the onset of estrus. The intervals from the peak of activity to AI and the end of estrus to AI were not associated with P/AI (p ≥ 0.05). Heifers inseminated with frozen conventional semen (50.1%) had a greater P/AI compared with heifers inseminated with frozen sexed semen (43.3%; p = 0.03). There were no interactions between the intervals from the onset, peak, or end of estrus to AI or the type of semen and the P/AI (p ≥ 0.05). The pregnancy per AI was not associated with estrous intensity (50.5% for low intensity vs. 53.0% for high intensity; p = 0.37). In conclusion, inseminating heifers between 9 and 32 h after the onset of estrus, as detected by the AAM, optimized the P/AI regardless of semen type. [ABSTRACT FROM AUTHOR]

Background: To investigate how changes in sedentary behavior relate to health outcomes, it is important to establish the test–retest reliability of activity monitors in measuring habitual sedentary behavior in people with type 2 diabetes (T2D) as a prerequisite for interpreting this information. Thus, the authors' objective was to examine the test–retest reliability of a common activity monitor (activPAL™) in measuring sedentary behavior and physical activity in people with T2D. Methods: Sedentary-time, standing-time, stepping-time, step-count, and sit-to-stand transitions were obtained from two 7-day assessment periods separated by at least 1 week. Test–retest reliability was determined with the intraclass correlation coefficient (ICC) to compare sedentary and activity measures between the 2 time points. Results: A total of 30 participants with self-reported T2D completed the study (age 65 [6] y, 63% women, body mass index 33.3 [5] kg/m2). High test–retest reliability was found for sedentary-time (ICC =.79; 95% confidence interval [CI],.61–.89) and standing-time (ICC =.74; 95% CI,.53–.87). Very high test–retest reliability was found for stepping-time (ICC =.90; 95% CI,.81–.95), step-count (ICC =.91; 95% CI,.83–.96), and sit-to-stand transitions (ICC =.90; 95% CI,.79–.95). Conclusion: The activPAL™ device showed high to very high test–retest reliability in measuring all tested activity categories in people with T2D. [ABSTRACT FROM AUTHOR]

Purpose: To assess the criterion and construct validity of the Fitbit Zip® to measure physical activity among adults living with HIV. Methods: Participants were video recorded completing 2 walk tests while wearing the Fitbit Zip® and completed 3 selfreported physical activity questionnaires 1 week later. The authors calculated intraclass correlation coefficients (ICCs) to determine agreement between the number of steps taken and distance walked (Fitbit Zip®) with the visual count of number of steps taken and actual distance walked (walk tests). The authors tested 15 a priori hypotheses about predicted associations between questionnaire scores and physical activity measured by the Fitbit Zip®. Results: Among the 34 participants, there was "excellent" agreement between the number of steps taken measured by the Fitbit Zip® and visually counted number of steps taken (ICC = .99) and number of steps taken at slow (ICC = .75), moderate (ICC = .85), and fast (ICC = .78) walking speeds. There was "poor" agreement between the Fitbit Zip® recorded distance and actual determined distance walked (ICC = .20). Three (20%) construct validity hypotheses were confirmed. Conclusions: The Fitbit Zip® demonstrated criterion validity for its ability to measure number of steps taken but not distance walked, and did not demonstrate construct validity for measuring physical activity among adults with HIV. [ABSTRACT FROM AUTHOR]

Currently, there is no way to assess mechanical loading variables such as peak ground reaction forces (pGRF) and peak loading rate (pLR) in clinical settings. The purpose of this study was to develop accelerometry-based equations to predict both pGRF and pLR during walking and running. One hundred and thirty one subjects (79 females; 76.9 ± 19.6 kg) walked and ran at different speeds (2–14 km·h−1) on a force plate–instrumented treadmill while wearing accelerometers at their ankle, lower back and hip. Regression equations were developed to predict pGRF and pLR from accelerometry data. Leave-one-out cross-validation was used to calculate prediction accuracy and Bland–Altman plots. Our pGRF prediction equation was compared with a reference equation previously published. Body mass and peak acceleration were included for pGRF prediction and body mass and peak acceleration rate for pLR prediction. All pGRF equation coefficients of determination were above 0.96, and a good agreement between actual and predicted pGRF was observed, with a mean absolute percent error (MAPE) below 7.3%. Accuracy indices from our equations were better than previously developed equations. All pLR prediction equations presented a lower accuracy compared to those developed to predict pGRF. Walking and running pGRF can be predicted with high accuracy by accelerometry-based equations, representing an easy way to determine mechanical loading in free-living conditions. The pLR prediction equations yielded a somewhat lower prediction accuracy compared with the pGRF equations. Peak ground reaction forces can be accurately predicted through raw accelerometry data. These predictions are valid for a broad range of body masses and for ankle, lower back and hip accelerometer placements. Peak loading rate prediction presented lower accuracy compared with peak ground reaction force prediction. These findings result in a simple method to predict mechanical loading in clinical practice, which is relevant in some areas of sports medicine such as bone health and injury prevention. [ABSTRACT FROM AUTHOR]

A link between inappropriate physical behaviour patterns (low physical activity and high sedentary behaviour) and poor health outcomes has been observed. To provide evidence to quantify this link, it is important to have valid and reliable assessment tools. This study aimed to assess the validity and reliability of the activPAL4TM monitor for distinguishing postures and measuring stepping activity of 6–12-year-old children. Thirteen children (8.5 ± 1.8 years) engaged in pre-determined standardised (12 min) and non-standardised (6 min) activities. Agreement, specificity and positive predictive value were assessed between the activPAL4TM and direct observation (DO) (nearest 0.1 s). Between-activPAL4TM (inter-device) and between-observer (inter-rater) reliability were determined. Detection of sitting and stepping time and forward purposeful step count were all within 5% of DO. Standing time was slightly overestimated (+10%) and fast walking/jogging steps underestimated (−20%). For non-standardised activities, activPAL4TM step count matched most closely to combined backward and forward purposeful steps; however, agreement varied widely. The activPAL4TM demonstrated high levels of reliability (ICC(1, 1) > 0.976), which were higher in some instances than could be achieved through direct observation (ICC(2, 1) > 0.851 for non-standardised activities). Overall, the activPAL4TM recorded standardised activities well. However, further work is required to establish the exact nature of steps counted by the activPAL4TM. [ABSTRACT FROM AUTHOR]

Objectives: Limited research on using smart wearables such as Fitbit devices among people with dementia has shown favourable outcomes. The aim of this study was to explore the acceptability and feasibility of using a Fitbit Charge 3 among people with dementia, living in the community, who took part in the physical exercise component of the Comprehensive REsilience‐building psychoSocial intervenTion pilot study. Methods: A mixed methods study was conducted; Quantitative data relating to wear rates for the Fitbit were recorded and qualitative data were collected by group and individual interviews with the people with dementia and their caregiver about their experience of wearing/using the Fitbit in the study. Results: Nine people with dementia and their caregiver completed the intervention. Only one participant wore the Fitbit consistently. Supporting set‐up and use of the devices was time consuming and caregiver involvement was essential for day‐to‐day support: none of the people with dementia owned a smartphone. Few of them engaged with the Fitbit features, primarily only using it to check the time and only a minority wanted to keep the device beyond the intervention. Discussion: When designing a study using smart wearables such as a Fitbit among people with dementia, consideration should be given to the following: the possible burden on caregivers supporting the use of the device; a lack of familiarity with this technology in the target population; dealing with missing data, and the involvement of the researcher in setting up and supporting use of the device. [ABSTRACT FROM AUTHOR]

Introduction: The COVID-19 lockdown introduced restrictions to free-living activities. Changes to these activities can be accurately quantified using combined measurement. Using activPAL3 and self-reports to collect activity data, the study aimed to quantify changes that occurred in physical activity and sedentary behavior between prelockdown and lockdown. The study also sought to determine changes in indoor and outdoor stepping. Methods: Using activPAL3, four participants recorded physical activity data prelockdown and during lockdown restrictions (February–June 2020). Single events (sitting, standing, stepping, lying) were recorded and analyzed by the CREA algorithm using an event-based approach. The analysis focused on step count, sedentary time, and lying (in bed) time; median and interquartile range were calculated. Daily steps classified as taking place indoors and outdoors were calculated separately. Results: 33 prelockdown and 92 in-lockdown days of valid data were captured. Median daily step count across all participants reduced by 14.8% (from 5,828 prelockdown to 4,963 in-lockdown), while sedentary and lying time increased by 4% and 8%, respectively (sedentary: 9.98–10.30 hr; lying: 9.33–10.05 hr). Individual variations were observed in hours spent sedentary (001: 8.44–8.66, 002: 7.41–8.66, 003: 11.97–10.59, 004: 6.29–7.94, and lying (001: 9.69–9.49, 002: 11.46–11.66, 003: 7.63–9.34, 004: 9.7–11.12) pre- and in-lockdown. Discrepancies in self-report versus algorithm classification of indoor/outdoor stepping were observed for three participants. Conclusion: The study quantitively showed lockdown restrictions negatively impacted physical activity and sedentary behavior; two variables closely linked to health outcomes. This has important implications for public health policies to help develop targeted interventions and mandates that encourage additional physical activity and lower sedentary behavior. [ABSTRACT FROM AUTHOR]

Purpose: This study estimated the long-term individual-level productivity costs of physical inactivity. Methods: The data were drawn from the Northern Finland Birth Cohort 1966, to which the productivity cost variables (sick leaves and disability pensions) from Finnish registries were linked. Individuals (N = 6261) were categorized into physical activity groups based on their level of physical activity, which was measured in three ways: 1) self-reported leisure-time moderate- to vigorous-intensity physical activity (MVPA) at 46 yr old, 2) longitudinal self-reported leisure-time MVPA at 31–46 yr old, and 3) accelerometer-measured overall MVPA at 46 yr old. The human capital approach was applied to calculate the observed costs (years 2012–2020) and the expected costs (years 2012–2031). Results: The results showed that the average individual-level productivity costs were higher among physically inactive compared with the costs among physically active. The results were consistent regardless of the measurement type of physical activity or the period used. On average, the observed long-term productivity costs among physically inactive individuals were €1900 higher based on self-reported MVPA, €1800 higher based on longitudinal MVPA, and €4300 higher based on accelerometer-measured MVPA compared with the corresponding productivity costs among physically active individuals. The corresponding difference in the expected costs was €2800, €1200, and €8700, respectively. Conclusions: The results provide evidence that productivity costs differ according to an individual's level of physical activity. Therefore, investments in physical activity may decrease not only the direct healthcare costs but also the indirect productivity costs paid by the employee, the employer, and the government. [ABSTRACT FROM AUTHOR]

A universal approach to characterizing sport-related physical activity (PA) types in sport settings does not yet exist. Young adults (n = 30), 19–33 years, engaged in a 15-min activity session, performing warm-ups, 3-on-3 soccer, and 3-on-3 basketball. Videos were recorded and manually coded as criterion PA types (walking, running, jumping, rapid lateral movements). Participants wore an accelerometer on their right hip. Multiple machine learning models were developed and compared for predicting PA type. Most models underestimated time spent completing the activities performed least commonly. Point estimates for percent agreement, sensitivity, specificity, F-scores, and kappa were similar across models, with Hidden Markov Models (HMMs) being best at classifying rare events. Models detected activity type during sport-related movements with modest accuracy (kappas ≤.40). Given the better performance of HMMs, incorporating the temporal nature of sport-related activities is important for improving sport-related PA classification. [ABSTRACT FROM AUTHOR]

Background: Like most living organisms, the fruit fly Drosophila melanogaster exhibits strong and diverse behavioural reactions to light. Drosophila is a diurnal animal that displays both short- and long-term responses to light, important for, instance, in avoidance and light wavelength preference, regulation of eclosion, courtship, and activity, and provides an important model organism for understanding the regulation of circadian rhythms both at molecular and circuit levels. However, the assessment and comparison of light-based behaviours is still a challenge, mainly due to the lack of a standardised platform to measure behaviour and different protocols created across studies. Here, we describe the Drosophila Interactive System for Controlled Optical manipulations (DISCO), a low-cost, automated, high-throughput device that records the flies' activity using infrared beams while performing LED light manipulations. Results: To demonstrate the effectiveness of this tool and validate its potential as a standard platform, we developed a number of distinct assays, including measuring the locomotor response of flies exposed to sudden darkness (lights-off) stimuli. Both white-eyed and red-eyed wild-type flies exhibit increased activity after the application of stimuli, while no changes can be observed in Fmr1 null allele flies, a model of fragile X syndrome. Next, to demonstrate the use of DISCO in long-term protocols, we monitored the circadian rhythm of the flies for 48 h while performing an alcohol preference test. We show that increased alcohol consumption happens intermittently throughout the day, especially in the dark phases. Finally, we developed a feedback-loop algorithm to implement a place preference test based on the flies' innate aversion to blue light and preference for green light. We show that both white-eyed and red-eyed wild-type flies were able to learn to avoid the blue-illuminated zones. Conclusions: Our results demonstrate the versatility of DISCO for a range of protocols, indicating that this platform can be used in a variety of ways to study light-dependent behaviours in flies. [ABSTRACT FROM AUTHOR]

Featured Application: Facilitating activity during the evening shift and reducing reliance on sitting as the major means of performing out-of-bed activity are possible avenues to increase overall physical activity among patients post-stroke in acute hospital settings. Early activity post-stroke reduces secondary complications and improves rehabilitation outcomes. This study aimed to describe the physical activities of stroke patients in an acute hospital setting, compare activity patterns between working shifts, and assess associations between activity and clinical status. Twenty-one patients (mean age 69.4 ± 33.4 years,13 men) admitted due to acute ischemic stroke wore activity monitors for two weeks or until discharge. During the morning and evening shifts, the activity monitor collected daily data on walking and body position. The study discovered that patients' overall activity levels were low and that activity was higher during morning shifts than evening shifts (sitting time: 185.31 ± 109.31 min and 91.8 ± 98.46 min, p = 0.002; number of steps: 58.3 ± 32.73 and 30.4 ± 17.6 steps, p < 0.001). Upright and sitting time increased in morning shifts (p = 0.002), while the number of steps increased in both morning and evening shifts (p = 0.002). In the evening shift, there was a fair (r = 0.28, p = 0.02) positive correlation between grip strength and the number of steps, such that patients with higher grip strength took more steps. In addition, there were poor (r = −0.2, p = 0.02) correlations between motor function (Trunk Control Test and Functional Ambulation Category) and time in an upright position, such that patients with lower functional ability sat longer. Clinical characteristics and level of activity did not show any other correlations. To conclude, the main out-of-bed activity of patients was sitting during morning shifts. The findings highlight the temporal differences in activity throughout the day, as well as the disconnect between clinical characteristics and activity levels. [ABSTRACT FROM AUTHOR]

Introduction: Older African Americans have low levels of physical activity, which increases the risk of aging-related health conditions. This study aimed to determine the effectiveness of, and satisfaction with, a community-engaged physical activity intervention targeting older African Americans. Methods: Fifty-six older African Americans were randomized to a successful aging group (SAG) or a physical activity group (PAG) for 12 wk. The PAG consisted of two weekly group exercise sessions and two to three home-based exercise sessions per week. The SAG consisted of weekly group educational sessions related to various aspects of healthy aging. Physical activity was measured by ActiGraph accelerometers and the Community Healthy Activities Model Program for Seniors Activities Questionnaire in both groups, and a Fitbit was continuously worn by PAG participants. Results: Group session attendance was 93% and 86% in the PAG and SAG, respectively. The increase in ActiGraph-derived steps per day (1085.3 ± 265.6 vs 34.7 ± 274.3; P = 0.008) and daily minutes of moderate-to-vigorous physical activity (MVPA; 6.2 ± 1.6 vs 0.3 ± 1.7; d = 0.68; P = 0.01), and self-reported Community Healthy Activities Model Program for Seniors Activities Questionnaire MVPA bouts (3.5 ± 0.77 vs 0.33 ± 0.79; P < 0.001) were significantly greater within the PAG than the SAG. ActiGraph-derived minutes of daily MVPA and steps as well as Fitbit-derived steps per day were significantly greater on days when PAG participants engaged in group sessions compared with days when they self-reported home-based exercise or no exercise (P < 0.016). Participants in both study arms reported high levels of satisfaction (>4- on 5-point Likert scale). Conclusions: The intervention increased physical activity, was well attended, and resulted in high satisfaction. Future studies should assess long-term sustainability in this population. [ABSTRACT FROM AUTHOR]

Purpose: Sleep deficits are a common nonmotor symptom of Parkinson disease (PD). People with mild PD also achieve less physical activity (PA) than healthy older adults (HOA), but the relationship between sleep and PA in PD is unclear. This study examined associations between sleep and PA in participants with PD and HOA. Materials and Methods: Secondary analysis of a prospective observational study. Participants wore a commercially available activity monitor for two weeks. Wilcoxon Rank-Sum tests compared nighttime sleep, wakenings after sleep onset, number of wakenings, naps, step count, and PA intensity between PD and HOA groups. Age-adjusted regression models calculated associations between nighttime sleep and PA. Results: Per day, participants with PD slept 75 fewer minutes (p < 0.01), took 5,792 fewer steps (p < 0.001), achieved less PA at all intensities, and had 32% more sedentary time (p < 0.001) compared to HOA. Thirty minutes more sleep was associated with 26 fewer sedentary minutes for HOA (p = 0.01) and 25 fewer sedentary minutes for the PD group (p < 0.001). Conclusions: Sleep and PA are reduced in mild PD compared to HOA. Both groups demonstrated similar associations between reduced sleep and increased sedentary behavior. Results may encourage providers to screen for sleep deficits when promoting PA. The use of a wrist-worn commercial activity and sleep monitor was well tolerated by both healthy older adults and people with mild Parkinson Disease in this study. People with mild Parkinson Disease slept less and were less active than a group of healthy older adults. Less sleep was associated with more sedentary behavior in both groups. The relationship between poor sleep and sedentary behavior in mild Parkinson Disease suggests that rehabilitation interventions may be optimized by targeting both physical activity and sleep deficits. [ABSTRACT FROM AUTHOR]

Background: Reduced physical activity (PA) was the strongest predictor of all-cause mortality in patients with chronic obstructive pulmonary disease (COPD). This scoping review aimed to map the evidence on the current landscape of physical activity, barriers and facilitators, and assessment tools across COPD patients.Methods: Arksey and O'Malley's scoping review methodology framework guided the conduct of this review. An electronic search was conducted on five English databases (PubMed, Cochrane Library, PsycINFO, CINAHL and Web of Science) and three Chinese databases (CNKI, CQVIP and WAN-FANG) in January 2022. Two authors independently screened the literature, extracted the studies characteristics.Results: The initial search yielded 4389 results, of which 1954 were duplicates. Of the remaining 135 articles, 42 studies met the inclusion criteria. Among the reviewed articles, there were 14 (33.3%) cross-sectional study, 9 (21.4%) cohort study, 4 (9.5%) longitudinal study, 3 qualitative study, 12 (28.7%) randomized control trials. The main barriers identified were older age, women, lung function, comorbidities, COPD symptoms (fear of breathlessness and injury, severe fatigue, anxiety and depression), GOLD stage, frequency of exacerbation, oxygen use, lack of motivation and environment-related (e.g., season and weather). Twelve studies have evaluated the effects of physical exercise (e.g., walking training, pulmonary rehabilitation (PR), pedometer, self-efficacy enhancing intervention and behavioral modification intervention) on PA and showed significant positive effects on the prognosis of patients. However, in real life it is difficult to maintain PA in people with COPD.Conclusions: Changing PA behavior in patients with COPD requires multidisciplinary collaboration. Future studies need to identify the best instruments to measure physical activity in clinical practice. Future studies should focus on the effects of different types, time and intensity of PA in people with COPD and conduct randomized, adequately-powered, controlled trials to evaluate the long-term effectiveness of behavioral change interventions in PA. [ABSTRACT FROM AUTHOR]

Aims Physical activity (PA) is important in patients with heart failure (HF) to improve health outcomes. The adherence to PA is low, and therefore, novel approaches are necessary to increase PA. We aimed to determine the difference in PA in patients with HF who have access to exergaming compared to patients who received motivational support and to explored predictors of a clinically relevant change in non-sedentary time between baseline and 3 months. Methods and results In total, 64 patients (mean age 69 ± 9 years, 27% female) wore an accelerometer 1 week before and 1 week after the intervention. Data were analysed using logistic regression analysis. Patients spent 9 h and 43 min (±1 h 23 min) during waking hours sedentary. There were no significant differences in PA between patients who received an exergame intervention or motivational support. In total, 30 of 64 patients achieved a clinically relevant increase in non-sedentary time. Having grandchildren [odds ratio (OR) 7.43 P = 0.03], recent diagnosis of HF (OR 0.93 P = 0.02), and higher social motivation (OR 2.31 P = 0.03) were independent predictors of a clinically relevant increase of non-sedentary time. Conclusion Clinicians should encourage their patients to engage in alternative approaches to improve PA and reduce sedentary habits. Future exergaming interventions should target individuals with chronic HF who have low social motivation and a low level of light PA that may benefit most from exergaming. Also (non-familial), intergenerational interaction is important to enabling patients in supporting patients in becoming more active. [ABSTRACT FROM AUTHOR]

The aim of the study was to examine changes in objective and self-reported physical activity (PA) among women aged 60 years and older. The study included 200 women aged over 60 years, divided into three groups according to age (60–65 years, 66–70 years, > 70 years). The subjective assessment was provided with the International Physical Activity Questionnaire (IPAQ) – short version with self-reported PA assessment, and objective data was provided by an Actigraph GT3-BT worn for seven days. Significant differences in moderate and high intensity PA, moderate-to-vigorous PA and steps per day were found between the oldest and youngest groups; as well as in low, moderate, moderate-to-vigorous PA and steps per day between groups middle and oldest. In all three age groups, 1) significant differences were observed between subjective and objective measurements of physical activity and 2) no correlation was found between assessment measures. It was found that only direct PA measurement declined with age in women over 60 years old, and that sedentary behavior is underestimated, and moderate and vigorous PA overestimated, with the self-reported IPAQ. [ABSTRACT FROM AUTHOR]

Background and Aims: Activity monitors, such as Fitbits®, are being used increasingly for research purposes and data have been validated in healthy community‐dwelling older adults. Given the lack of research in older adults with neurocognitive disorders, we investigated the consistency of sleep data recorded from a wrist‐worn activity monitor in this population. Methods: Fitbit® activity monitors were worn by hospitalized older adults as part of a parent study investigating sleep and step count in patients recovering from hip fracture surgery in a tertiary care academic hospital in Hamilton, Canada between March 2018 and June 2019. In this secondary analysis, we compared the proportion of missing sleep data between participants with and without a neurocognitive disorder and used a multivariable model to assess the association between neurocognitive disorder and missing sleep data. Results: Of 67 participants included in the analysis, 22 had a neurocognitive disorder (median age: 86.5 years). Sleep data were missing for 47% of the neurocognitive disorder group and 23% of the non‐neurocognitive disorder group. The presence of a neurocognitive disorder was associated with an increased likelihood of missing sleep data using the Fitbit® activity monitors (adjusted odds ratio: 3.41; 95% confidence interval: 1.06–11.73, p = 0.04). Conclusion: The inconsistent nature of sleep data tracking in hospitalized older adults with neurocognitive disorders highlights the challenges of using interventions in patient populations who are often excluded from validation studies. As opportunities expand for activity monitoring in persons with neurocognitive disorders, novel technologies not previously studied in this group should be used with caution. [ABSTRACT FROM AUTHOR]

Background: The rapidly increasing use of wearable technology to monitor free-living ambulatory behavior demands to address to what extent the chosen outcome measures are representative for real-world situations. This scoping review aims to provide an overview of the purpose of use of wearable activity monitors in people with a Lower Limb Amputation (LLA) in the real world, to identify the reported outcome measures, and to evaluate to what extent the reported outcome measures capture essential information from real-world ambulation of people with LLA. Methods: The literature search included a search in three databases (MEDLINE, CINAHL, and EMBASE) for articles published between January 1999 and January 2022, and a hand-search. Results and conclusions: 98 articles met the inclusion criteria. According to the included studies' main objective, the articles were classified into observational (n = 46), interventional (n = 34), algorithm/method development (n = 12), and validity/feasibility studies (n = 6). Reported outcome measures were grouped into eight categories: step count (reported in 73% of the articles), intensity of activity/fitness (31%), type of activity/body posture (27%), commercial scores (15%), prosthetic use and fit (11%), gait quality (7%), GPS (5%), and accuracy (4%). We argue that researchers should be more careful with choosing reliable outcome measures, in particular, regarding the frequently used category step count. However, the contemporary technology is limited in providing a comprehensive picture of real-world ambulation. The novel knowledge from this review should encourage researchers and developers to engage in debating and defining the framework of ecological validity in rehabilitation sciences, and how this framework can be utilized in the development of wearable technologies and future studies of real-world ambulation in people with LLA. [ABSTRACT FROM AUTHOR]

Background: The activPAL accelerometer is used widely for assessment of free-living activity and postural data. Two algorithms, VANE (traditional) and CREA (new), are available to analyze activPAL data, but the comparability of metrics derived from these algorithms is unknown. Purpose: To determine the comparability of physical activity and sedentary behavior metrics from activPAL's VANE and CREA algorithms. Methods: Individuals enrolled in the LIFT trial (n = 354) wore an activPAL accelerometer on the right thigh continuously for 7 days on four occasions, resulting in 5,851 valid days of data for analysis. Daily data were downloaded in the PALbatch software using the VANE and CREA algorithms. Correlations, mean absolute percentage error, effect sizes (ES), and equivalence (within 3%) were calculated to evaluate comparability of the algorithms. Results: Steps, activity score, stepping time, bouts of stepping, and upright time metrics were statistically equivalent, highly correlated (r ≥.98), and had small mean absolute percentage errors (≤2.5%) and trivial ES (ES < 0.07) between algorithms. Stepping bouts also had good comparability. Conversely, sedentary-upright and upright-sedentary transitions and bouts of sitting were not equivalent, with large mean absolute percentage differences (17.4%–141.3%) and small to very large ES (ES = 0.45–3.80) between algorithms. Conclusions: Stepping and upright metrics are highly comparable between activPAL's VANE and CREA algorithms, but sitting metrics had large differences as the VANE algorithm does not capture nonwear or differentiate between sitting and lying down. Researchers using the activPAL should explicitly describe the analytic algorithms used in their work to facilitate data pooling and comparability across studies. [ABSTRACT FROM AUTHOR]

Background: The popularity of consumer-wearable activity trackers has led the scientific community to conduct an increasing number of intervention studies integrating them to promote physical activity (PA) and to reduce sedentary behavior (SB) levels among school-aged children. Therefore, the aim of the present study was to estimate the effects of consumer-wearable activity tracker-based programs on daily objectively measured PA and SB among apparently healthy school-aged children, as well as to compare the influence of participants' and programs' characteristics. Methods: Eligibility criteria were: (1) participants: apparently healthy school-aged children (< 18 years old); (2) intervention: aimed to promote PA and/or to reduce SB incorporating consumer-wearable activity trackers; (3) comparator: baseline measurements and/or a control/traditional group; (4) outcomes: objectively measured daily PA and/or SB levels; (5) study design: pre-experimental, quasi-experimental, and true-experimental trials. Relevant studies were searched from eight databases up to December 2020, as well as from four alternative modes of searching. Based on the Cochrane Risk-of-bias tool 2, the risk of bias was assessed following four domains: (1) randomization process; (2) missing outcome data; (3) measurement of the outcomes; and (4) selection of the reported results. Based on a comprehensive systematic review, meta-analyses of the Cohen's standardized mean difference (d) and 95% confidence interval (CI) with a random-effects model were conducted to estimate the overall effects, as well as the within- and between-study subgroups analyses effects, of the programs on daily total steps, moderate-to-vigorous PA (MVPA), total PA and SB. Results: Forty-four publications (i.e., 45 studies) were included in the systematic review (5,620 unique participants; mean age = 12.85 ± 2.84 years) and 40 publications (i.e., 41 studies) in the meta-analysis. Programs had a mean length of 11.78 ± 13.17 weeks and most used a waist-worn consumer-wearable activity tracker (77.78% waist-worn; 22.22% wrist-worn). Programs characteristics were: goal-setting strategies (64.06%); participants' logbooks (56.25%); counseling sessions (62.50%); reminders (28.13%); motivational strategies (42.19%); and exercise routine (17.19%). Results showed a statistically significant moderate favorable effect on daily total steps (d = 0.612, 95% CI 0.477–0.746), small favorable effect on daily MVPA (d = 0.220, 95% CI 0.134–0.307), trivial favorable effect on daily total PA (d = 0.151, 95% CI 0.038–0.264) and trivial unfavorable effect on daily SB (d = 0.172, 95% CI 0.039–0.305). Subgroups analyses showed a higher effect for daily total steps and daily MVPA levels in females and the physically inactive for daily total steps (p = 0.003–0.044). Programs with educational counseling and/or goal-setting strategies, as well as a greater number of strategies, were more effective for improving children's daily total steps, and wrist-worn activity trackers were more effective than waist-worn trackers for improving their daily MVPA levels (p = 0.001–0.021). Conclusions: Consumer-wearable activity tracker-based programs seem to be effective in promoting school-aged children's daily total steps and MVPA levels, especially for females and those that are physically inactive. These programs should include specific goal-setting, educational counseling, and wrist-worn trackers as especially effective strategies. However, due to the certainty of evidence being from "low" to "moderate", future well-designed primary research studies about the topic are needed. PROSPERO: CRD42020222363. [ABSTRACT FROM AUTHOR]

The objectives of this study were to determine the effects of GnRH at the time of artificial insemination (AI) on ovulation, progesterone 7 d post-AI, and pregnancy in cows detected in estrus using traditional methods (tail chalk removal and mount acceptance visualization) or an automated activity-monitoring (AAM) system. We hypothesized that administration of GnRH at the time of AI would increase ovulation rate, plasma progesterone post-AI, and pregnancy per AI (P/AI) in cows detected in estrus. In experiment 1, Holstein cows (n = 398) were blocked by parity and randomly assigned to receive an injection of GnRH at the time of estrus detection/AI (GnRH, n = 197) or to remain untreated (control, n = 201) on 4 farms. The GnRH was administered as 100 µg of gonadorelin acetate. Ovarian structures and plasma progesterone were assessed in a subset of cows (GnRH, n = 52; control, n = 55) in experiment 1 at the time of AI and 7 d later. In experiment 2, a group of 409 cows in an AAM farm were enrolled as described for experiment 1 (GnRH, n = 207; control, n = 202). Data were categorized for parity (primiparous vs. multiparous), season (cool vs. warm), number of services (first vs. > first), DIM (>150 DIM vs. ≤150 DIM), and for AAM cows in experiment 2 for activity level (high: 90–100 index vs. low: 35–89 index). Pregnancy diagnosis was performed between 32 and 45 d post-AI (P1) and 60 to 115 d post-AI (P2). In experiment 1, there was no difference in plasma progesterone at day of estrus detection (control = 0.09 ng/mL vs. GnRH = 0.16 ng/mL), 7 d later (control = 2.03 ng/mL vs. GnRH = 2.18 ng/mL), and ovulation rate (GnRH = 83.2% vs. control = 77.9%) between treatments. There were no effects of GnRH in experiment 1 for P/AI at P1 (control = 43.3% vs. GnRH = 38.6%), P2 (control = 38.4% vs. GnRH = 34.5%), and for pregnancy loss (control = 9.8% vs. GnRH = 8.2%). In experiment 2, there were no effects of GnRH for P/AI at P1 (control = 39.6% vs. GnRH = 40.1%), P2 (control = 35.0% vs. GnRH = 37.4%), and for pregnancy loss (control = 9.5% vs. GnRH = 6.2%). There was a tendency for a parity effect on P/AI for P1, but not P2 or for pregnancy loss. High-activity cows had greater P/AI in P1 (low activity = 27.9% vs. high activity = 44.1%), P2 (low activity = 21.8% vs. high activity = 41.2%), and lower pregnancy loss (low activity = 20.7% vs. high activity = 5.1%), but there were no interactions between treatment and activity level. The current study did not support the use of GnRH at estrus detection to improve ovulatory response, progesterone 1 wk post-AI, and P/AI. More research is needed to investigate the relationship between GnRH at the time of AI and activity level in herds using AAM systems. [ABSTRACT FROM AUTHOR]

With wearable technology growing in popularity and sophistication, there remains a need to determine the validity of these devices by independent observers. Validation studies of wearable technology can involve large amounts of data, with data preparation techniques that are not always clearly established. This can make attempts to reproduce the results difficult and does not allow researchers to gain guidance in how to perform their own analyses if they wanted to perform a similar study. Therefore, this paper details the process that was utilized to prepare and analyze the accuracy of several heart rate monitors during mountain biking and can be used as a possible guide to researchers looking to perform similar analyses. We also detail the software used and discuss possible alternatives. [ABSTRACT FROM AUTHOR]

Sargent, C, Lastella, M, Schwerdt, S, and Roach, GD. An individualized intervention increases sleep duration in professional athletes. J Strength Cond Res 35(12): 3407-3413, 2021-Athletes typically obtain less sleep than is generally recommended for healthy adults. The aim of this study was to determine whether individualized feedback could increase sleep duration in professional cricket players in the 3 weeks before the start of the domestic season. Players were randomly assigned to a control group (i.e. no individual feedback; n = 8) or an intervention group (i.e. individual feedback about bedtime, wake time, and sleep duration; n = 7). Night-time sleep and daytime naps were monitored using wrist activity monitors in conjunction with self-report sleep diaries for 1 week before, and 1 week after, the feedback intervention. Cumulative sleep duration was calculated as the sum of the sleep duration for a night-time sleep episode and any naps that occurred on the following day. Differences in cumulative sleep duration before and after the intervention were examined using a mixed-effects analysis of variance. There was an interaction between group and week for cumulative sleep duration (p = 0.039; [eta]2 = 0.6; large). The average cumulative sleep duration was longer (+36 minutes) in the intervention group in week 2 compared with week 1. Individualized feedback can be used to increase sleep duration in professional cricket players. In future, it will be important to determine whether improvements in sleep duration can be maintained throughout the season. [ABSTRACT FROM AUTHOR]

Equivalence testing may provide complementary information to more frequently used statistical procedures because it determines whether physical behavior outcomes are statistically equivalent to criterion measures. A caveat of this procedure is the predetermined selection of upper and lower bounds of acceptable error around a specified zone of equivalence. With no clear guidelines available to assist researchers, these equivalence zones are arbitrarily selected. A scoping review of articles implementing equivalence testing was performed to determine the validity of physical behavior outcomes; the aim was to characterize how this procedure has been implemented and to provide recommendations. A literature search from five databases initially identified potentially 1,153 articles which resulted in the acceptance of 19 studies (20 arms) conducted in children/youth and 40 in adults (49 arms). Most studies were conducted in free-living conditions (children/youth = 13 arms; adults = 22 arms) and employed a ±10% equivalence zone. However, equivalence zones ranged from ±3% to ±25% with only a subset using absolute thresholds (e.g., ±1,000 steps/day). If these equivalence zones were increased or decreased by ±5%, 75% (15/20, children/youth) and 71% (35/49, adults), they would have exhibited opposing equivalence test outcomes (i.e., equivalent to nonequivalent or vice versa). This scoping review identifies the heterogeneous usage of equivalence testing in studies examining the accuracy of (in)activity measures. In the absence of evidence-based standardized equivalence criteria, presenting the percentage required to achieve statistical equivalence or using absolute thresholds as a proportion of the SD may be a better practice than arbitrarily selecting zones a priori. [ABSTRACT FROM AUTHOR]

Activity monitors may not accurately detect steps in hospitalized older adults who walk slowly. We compared ActiGraph GT3X+ step counts (hip and ankle locations, default and low frequency extension [LFE] analyses) to the StepWatch monitor (ankle) during a hallway walk in 38 geriatric rehabilitation patients (83.2 ± 7.1 years of age, 0.4 ± 0.2 m/s gait speed). Absolute percent error values were low (<3%) and did not differ for the StepWatch and the GT3X+ (ankle, LFE); however, error values were high (19–97%) when the GT3X+ was worn at the hip and/ or analyzed with the default filter. Although these finding suggest the GT3X+ (ankle, LFE) functions as well as the StepWatch in detecting steps during walking in older adults with slow gait speeds, further research is needed to determine whether the GT3X+ is also able to disregard other body movements (e.g., fidgeting) that occur when full day monitoring is utilized. [ABSTRACT FROM AUTHOR]

Background: Physical activity (PA) has acquired a significant relevance due to the health benefits associated with its practice. Accelerometers are an effective tool to assess PA; however, the diversity of cut-off points used to define different PA intensities through accelerometry could interfere in the interpretation of the findings among studies. Objectives: The present study aimed to examine the sedentary behavior (SB) and physical activity (PA) levels in children using six selected accelerometry protocols based on diverse cut-off points. Methods: Clinical examination, anthropometric measurements, and PA evaluation by accelerometry were assessed in 543 selected children (10 ± 2.4 years old) from the Spanish GENOBOX study. The ActiLife data scoring program was used to determine daily min spent in SB, and light, moderate, vigorous and moderate-vigorous PA using six validated accelerometry protocols differing in their cut-off points. Results: Very different estimations for SB and PA intensity levels were found in children, independently of the non-wear-time algorithm selected, and considering puberty stages, age and body mass index. The time spent in daily SB varied from 471 to 663.7 min, PA ranged from 141 to 301.6 min, and the moderate-vigorous PA was reported between 20.7 and 180.2 min. Conclusion: The choice of a particular accelerometry protocol considering these factors is important to evaluate SB or PA intensities to suit the characteristics of the sample researched. It seems necessary to establish future lines of research that include different analytical approaches to measure SB and PA by accelerometry based on standardized and validated methodology. [ABSTRACT FROM AUTHOR]

Background: For valid accelerometer-assessed physical activity (PA) data, several methodological aspects should be considered. We aimed to 1) visualize the applicability of absolute accelerometer cut-offs to classify PA intensity, 2) verify recommendations to measure PA over 7 days by examining inter-day variability and reactivity, 3) examine seasonal differences in PA, and 4) recommend during which 10 h day period accelerometers should be worn to capture the most PA in patients with heart failure (HEART) and healthy individuals (HEALTH).Methods: Fifty-six HEART (23% female; mean age 66 ± 13 years) and 299 HEALTH (51% female; mean age 54 ± 19 years) of the COmPLETE study wore accelerometers for 14 days. Aim 1 was analyzed descriptively. Key analyses were performed using linear mixed models.Results: The results yielded poor applicability of absolute cut-offs. The day of the week significantly affected PA in both groups. PA-reactivity was not present in either group. A seasonal influence on PA was only found in HEALTH. Large inter-individual variability in PA timing was present.Conclusions: Our data indicated that absolute cut-offs foster inaccuracies in both populations. In HEART, Sunday and four other days included in the analyses seem sufficient to estimate PA and the consideration of seasonal differences and reactivity seems not necessary. For healthy individuals, both weekend days plus four other days should be integrated into the analyses and seasonal differences should be considered. Due to substantial inter-individual variability in PA timing, accelerometers should be worn throughout waking time. These findings may improve future PA assessment.Trial Registration: The COmPLETE study was registered at clinicaltrials.gov ( NCT03986892 ). [ABSTRACT FROM AUTHOR]

Our objective was to determine the effects of a single treatment of human chorionic gonadotropin (hCG) or GnRH from d 5 to 7 of the estrous cycle on cycle length, expression of estrus and fertility in lactating dairy cows. Lactating Holstein cows (n = 354) located in Farm 1 and lactating Jersey cows located in Farm 2 (n = 210) detected in estrus by an Automated Activity Monitor (AAM) system from 27 to 50 days in milk (DIM) were randomly assigned to receive one of three treatments from d 5 to 7 of the estrous cycle: control (untreated; CON; Holstein, n = 111; Jersey, n = 66), GnRH (86 μg gonadorelin acetate im; Holstein, n = 116; Jersey, n = 75), or hCG (3,300 IU im; Holstein, n = 127; Jersey, n = 69). Ovaries were scanned with ultrasound in a random subgroup of cows (Holstein/Farm 1, n = 147; Jersey/Farm 2, n = 94) on the day of treatment and 3 or 4 d later to determine ovulation. Estrus was detected after treatment by an AAM, and peak activity and heat index were recorded. A random subgroup of cows observed in estrus after treatment received first AI from 51 to 80 DIM (Holstein, n = 208; Jersey, n = 138). Pregnancy diagnoses were performed by transrectal ultrasonography at 37 ± 3 d post-AI. Holstein and Jersey cows treated with GnRH and hCG had an increased (P < 0.05) ovulatory response compared with controls. Human chorionic gonadotropin decreased (74%; P = 0.05) and GnRH tended to reduce (75%; P = 0.07) the proportion of multiparous Holstein cows returning to estrus compared with CON (86%). Cows treated with hCG had a longer (P < 0.01) estrous cycle length (24.6 ± 0.3 d, Holstein; 23.0 ± 0.3 d, Jersey) compared with CON cows (22.7 ± 0.3 d, Holstein; 21.3 ± 0.3 d Jersey) and GnRH (22.9 ± 0.3 d, Holstein; 21.1 ± 0.3 d Jersey). The percentage of cows with high (≥80) peak activity and heat index did not differ (P > 0.50) between treatments, and milk production did not affect (P > 0.65) the duration of estrus. Pregnancy per AI (P/AI) was not affected by treatments in Holstein (P = 0.93; CON: 34.3%, GnRH: 35.4%, and hCG: 31.5%) and in multiparous Jersey cows (P = 0.35; CON: 34.3%, GnRH: 35.4%, and hCG: 31.5%), but hCG had greater (P = 0.03; 55%) P/AI than GnRH (30.0%) and a trend (P = 0.06) for greater P/AI than CON (33.3%) in primiparous Jersey cows. In summary, inducing the formation of an accessory corpus luteum from d 5 to 7 of the estrous cycle with hCG reduced expression of estrus in multiparous Holstein cows. Moreover, hCG increased estrous cycle length in Holstein and Jersey cows, and it did not affect first service P/AI at 37 ± 3 d post-AI in Holstein and multiparous Jersey lactating cows. However, hCG increased P/AI in primiparous Jersey cows. Future research with a larger number of cows is needed to confirm these intriguing fertility results. • GnRH and hCG treatments in early luteal phase induced formation of an accessory CL and increased serum P4 in diestrus. • HCG reduced the proportion of non-inseminated Holstein multiparous cows returning to estrus. • Non-inseminated cows treated with hCG in early luteal phase had a longer estrous cycle. • GnRH and hCG did not affect the activity peak and heat index of the post-treatment estrus. • hCG increased P/AI in primiparous Jersey cows but not in Holstein and multiparous Jersey cows. [ABSTRACT FROM AUTHOR]

Aims: Restrictions during the COVID‐19 crisis will have impacted on opportunities to be active. We aimed to (a) quantify the impact of COVID‐19 restrictions on accelerometer‐assessed physical activity and sleep in people with type 2 diabetes and (b) identify predictors of physical activity during COVID‐19 restrictions. Methods: Participants were from the UK Chronotype of Patients with type 2 diabetes and Effect on Glycaemic Control (CODEC) observational study. Participants wore an accelerometer on their wrist for 8 days before and during COVID‐19 restrictions. Accelerometer outcomes included the following: overall physical activity, moderate‐to‐vigorous physical activity (MVPA), time spent inactive, days/week with ≥30‐minute continuous MVPA and sleep. Predictors of change in physical activity taken pre‐COVID included the following: age, sex, ethnicity, body mass index (BMI), socio‐economic status and medical history. Results: In all, 165 participants (age (mean±S.D = 64.2 ± 8.3 years, BMI=31.4 ± 5.4 kg/m2, 45% women) were included. During restrictions, overall physical activity was lower by 1.7 mg (~800 steps/day) and inactive time 21.9 minutes/day higher, but time in MVPA and sleep did not statistically significantly change. In contrast, the percentage of people with ≥1 day/week with ≥30‐minute continuous MVPA was higher (34% cf. 24%). Consistent predictors of lower physical activity and/or higher inactive time were higher BMI and/or being a woman. Being older and/or from ethnic minorities groups was associated with higher inactive time. Conclusions: Overall physical activity, but not MVPA, was lower in adults with type 2 diabetes during COVID‐19 restrictions. Women and individuals who were heavier, older, inactive and/or from ethnic minority groups were most at risk of lower physical activity during restrictions. [ABSTRACT FROM AUTHOR]

Purpose: There is no significant evidence of both biological and motivational effects between virtual reality exercises to traditional/conventional exercise. The aim of this study is to assess the biological and motivational effects of aerobic exercises with virtual reality and traditional exercise methods. Methods: 20 students participated as control and 60 students were divided randomly and equally into two groups, virtual reality exercise group (VRE) and traditional exercise group (TE). Two groups completed the exercise training. Tests were applied to the three groups at the beginning and in the end of the study. An activity monitor and pulse oximeter were used to measure energy expenditure during exercises. Results: After eight weeks, the data from pulse oximeter showed no statistical significance between the exercise groups. The active energy expenditure, PAL and step counts were statistically significant in TE group. There was a statistically significant increase in the sleep quality of the TE group (p = .000). There was no statistical significance among the anxiety scores of all groups. In the spring semester, there was a statistically significant increase in both VRE and TE groups compared to the fall semester (p < .05). Conclusion: The virtual reality exercises produce greater motivational effects, whereas traditional exercises bring greater physical improvements. [ABSTRACT FROM AUTHOR]

Walking is the most common and preferred way for people with multiple sclerosis (MS) to be active. Consumer-grade wearable activity monitors may be used as a tool to assist people with MS to track their walking by counting the number of steps. The authors evaluated the validity of Fitbit One activity tracker in individuals with MS by comparing step counts measured over a 7-day period against ActivPAL3™ (AP). Twenty-five ambulatory adults with MS with an average age 51.7 (10.2) years and gait speed 0.98 (0.47) m/s, median Expanded Disability Status Scale 5.5 (2.5-6.5), and 15 years post-MS diagnosis wore Fitbit One (using both waist and ankle placement) and AP for 7 consecutive days. Validity of Fitbit One for measuring step counts against AP was assessed using intraclass correlation coefficients (ICCs), Bland-Altman plots, and t tests. Regardless of wearing location (waist or ankle), there was good agreement between steps recorded by Fitbit One and AP (ICC: .86 [.82, .90]). The ankle-worn Fitbit measured steps more accurately (ICC: .91 [.81, .95]) than the waist-worn Fitbit (ICC: .81 [.62, .85]) especially in individuals (n = 12) who walked slowly (gait speed = 0.74 m/s). Fitbit One as a user-friendly, inexpensive, consumer-grade activity tracker can accurately record steps in persons with MS in a free-living environment. [ABSTRACT FROM AUTHOR]

Background: The number of days of data and number of subjects necessary to estimate total physical activity (TPA) and moderate-to-vigorous physical activity (M VPA) requires an understanding of within- and between-subject variances, and the influence of sex, body composition, and age. Methods: Seventy-one adults wore accelerometers for 7-day intervals over 6 consecutive months. Results: Body fat and sex influenced TPA and MVPA. The sources of subject-related variation for TPA and MVPA were within-subject (48.4% and 54.3%), between-subject (34.3% and 31.8%), and calendar effects (17.3% and 13.9%). Based on within-subject variances, the error associated with estimating TPA and MVPA by collecting 1 to 7 days of data ranged from 28.2% to 13.3% for TPA and 62.0% to 28.6% for MVPA. Based on between-subject variances, detecting a 10% difference between 2 groups at a power of 90% requires approximately 200 and 725 subjects per group for TPA and MVPA, respectively. Conclusions: Estimates of MVPA are more variable than TPA in overweight adults, therefore more days of data are required to estimate MVPA and larger sample sizes to detect treatment differences for MVPA. Log-transforming data reduces the need for additional days of data collection, thereby improving chances of detecting treatment effects. [ABSTRACT FROM AUTHOR]

Background: Accurate assessments of physical activity and energy expenditure (EE) are needed to advance research on positive and negative graded walking. Purpose: To evaluate the validity of 2 SenseWear Armband monitors (Pro3 and the recently released Mini) during graded walking. Methods: Twenty healthy adults wore both monitors during randomized walking activities on a motorized treadmill at 7 grades (0%, ±5%, ±15%, and ±25%). Estimates of total EE from the monitors were computed using different algorithms and compared with values derived from indirect calorimetry methodology using a 2-way mixed model ANOVA (Device x Condition), correlation analyses and Bland-Altman plots. Results: There was no significant difference in EE between the 2 armbands in any of the conditions examined. Significant main effects for device and condition, as well as a consistent bias, were observed during positive and negative graded walking with a greater over- and under-estimation at higher slope. Conclusions: Both the armbands produced similar EE values and seem to be not accurate in estimation of EE during activities involving uphill and downhill walking. Additional work is needed to understand factors contributing to this discrepancy and to improve the ability of these monitors to accurately measure EE during graded walking. [ABSTRACT FROM AUTHOR]

This study examined the feasibility and effect of sedentary behavior (SB) counseling on total sitting time (TST) and glycemic control in people with type 2 diabetes (T2D). Community-dwelling sedentary adults with T2D (n = 10; 8 women; age 65.6 ± 7.31) completed SB counseling (motivational interviewing-informed education about SB) aided by an activity monitor with a vibrotactile feature (activPAL3TM). The monitor was worn for 7 days, on weeks 1 and 13 (without the vibrotactile feature) and during weeks 5 and 9 (with the vibrotactile feature). Intervention feasibility was determined by study retention rates and activity monitor tolerability, and differences between pre- and post-intervention average daily TST. Paired t -test were performed. The effect size (ES) was calculated using Cohen d. All participants attended all study sessions with only 20% reporting moderate issues tolerating the activity monitor. TST time decreased from 11.8 hours ± 1.76 at baseline to 10.29 hours ± 1.84 at 3 months' assessment (P <.05) with a large ES (Cohen d =.88). HbA1c was decreased by 0.51% (P <.05) at the end of the intervention. This study found that the intervention was feasible for sedentary adults with type 2 diabetes. [ABSTRACT FROM AUTHOR]

Background: Adverse reactions to food are a common dermatological condition in dogs, requiring nutritional intervention using a novel or hydrolysate protein‐based food. Objective: To evaluate a therapeutic food containing egg and phytonutrients in dogs with food allergies using an activity monitor and core outcome set for canine atopic dermatitis (COSCAD'18) guidelines and in a controlled double‐masked, multicenter, prospective clinical trial. Animals: Adult dogs with a history of adverse food reaction as diagnosed by a food elimination trial were recruited from general practices. Methods: After a 21‐day baseline period, dogs were randomized to test or positive control (hydrolyzed protein) food for 21 days. Owner (pruritus visual analog score [PVAS], coat quality, food acceptance, and satisfaction) and veterinarian (canine atopic dermatitis lesion index [CADLI], physical examination) assessments were completed on days 0, 21, and 42. Dogs wore a collar‐mounted activity monitor to record scratching and shaking behavior throughout the study. Statistical analysis included within‐group comparison to baseline and between‐group comparison at study end using a significance threshold of alpha = 0.05. Results: At the end of the treatment period, all results were similar between groups for CADLI, PVAS, owner satisfaction, activity, and questionnaire data. Scores for hair dullness, brittleness, amount of dandruff, feces quality, and food acceptance were positive and not statistically different between groups. Conclusions and Clinical Importance: The therapeutic test food was well‐accepted and efficacious in managing signs of adverse reactions to food compared to baseline as well as compared to the positive control food. [ABSTRACT FROM AUTHOR]

Background: Adverse reactions to food are a common dermatological condition in dogs, requiring nutritional intervention using novel or hydrolysate protein‐based foods. Objective: To evaluate a therapeutic food containing egg and phytonutrients in dogs with food allergies using an activity monitor and core outcome set for canine atopic dermatitis (COSCAD'18) in a controlled double‐masked, multicenter, prospective clinical trial. Animals: Adult dogs with a history of adverse food reaction as diagnosed by a food elimination trial were recruited from general practices. Methods: After a 21‐day baseline period, dogs were randomized to test or positive control (hydrolyzed protein) food for 21 days. Owner (pruritus visual analog score [PVAS], coat quality, food acceptance, and satisfaction) and veterinarian (canine atopic dermatitis lesion index [CADLI], physical examination) assessments were completed on days 0, 21, and 42. Dogs wore a collar‐mounted activity monitor to record sleep, scratching, and shaking behavior throughout the study. Statistical analysis included within‐group comparison to baseline and between‐group comparison at study end using a significance threshold of alpha = 0.05. Results: At the end of the treatment period, all results were similar between groups for CADLI, PVAS, owner satisfaction, activity, and questionnaire data. Scores for hair dullness, brittleness, amount of dandruff, feces quality, and food acceptance were positive and were not statistically different between groups. Conclusions and Clinical Importance: The therapeutic test food was well‐accepted and efficacious in managing signs of adverse reactions to food compared to baseline as well as compared to the positive control food. [ABSTRACT FROM AUTHOR]

Summary: This pilot and feasibility study evaluated wrist‐worn accelerometers to measure recovery from day‐case surgery in comparison with daily quality of recovery‐15 scores. The protocol was designed with extensive patient and public involvement and engagement, and delivered by a research network of anaesthesia trainees. Forty‐eight patients recruited through pre‐operative assessment clinics wore wrist accelerometers for 7 days before (pre‐operative) and immediately after elective surgery (early postoperative), and again at 3 months (late postoperative). Validated activity and quality of recovery questionnaires were administered. Raw accelerometry data were archived and analysed using open source software. The mean (SD) number of valid days of accelerometer wear per participant in the pre‐operative, early and late postoperative periods were 5.4 (1.7), 6.6 (1.1) and 6.6 (1.0) days, respectively. On the day after surgery, Euclidian norm minus one (a summary measure of raw accelerations), step count, light physical activity and moderate/vigorous physical activity decreased to 57%, 47%, 59% and 35% of baseline values, respectively. Activity increased progressively on a daily basis but had not returned to baseline values by 7 days. Patient questionnaires suggested subjective recovery by postoperative day 3 to 4; however, accelerometry data showed that activity levels had not returned to baseline at this point. All activity measures had returned to baseline by 3 months. Wrist‐worn accelerometery is acceptable to patients and feasible as a surrogate measure for monitoring postoperative recovery from day‐case surgery. Our results suggest that patients may overestimate their rate of recovery from day‐case surgery, which has important implications for future research. [ABSTRACT FROM AUTHOR]

Monitoring rumination time (RT) around the time of calving is an effective way of identifying cows at risk of disease in early lactation. However, this only allows for the identification of cows a few days before the onset of clinical signs; thus, effective preventive measures cannot be implemented. Recent research has suggested that biomarkers of immune and metabolic function measured at dry-off (DO) can predict higher disease risk in early lactation. Nevertheless, the extent to which RT around DO is associated with early-lactation disease risk remains unexplored. Thus, the objective of this study was to compare RT in the weeks before and after DO between cows that did and did not experience health disorders in early lactation. For this, we conducted an observational retrospective cohort study utilizing the records available from a large commercial dairy herd in which RT is recorded daily using an automated system. Daily RT from −7 to +14 d relative to DO from 2,258 DO cycles and their respective health records in the first 60 d in milk were used. Differences in RT between animals with and without a disease history were tested with the Student t -test with Bonferroni adjustment. Mixed linear regression analyses were performed to assess differences in RT around DO and the association of RT with the occurrence of mastitis, metritis, retained placenta, hyperketonemia, lameness, hypocalcemia, pneumonia, and displaced abomasum. Rumination time decreased abruptly at DO and remained lower for 3 to 4 d compared with the days before DO. On average, cows affected by hyperketonemia and lameness ruminated 9.83 ± 6.40 and 15.00 ± 6.08 min/d less than unaffected cows, respectively. Cows that developed lameness in the first 60 d in milk showed reduced RT from 1 to 3 d following DO compared with cows that were not diagnosed with lameness in early lactation. However, RT around DO was not associated with the occurrence of the other health disorders studied here. Our results demonstrate that DO is a stressful event for dairy cows resulting in decreased RT for several days. Furthermore, the association between RT around DO and some early-lactation diseases suggests that RT could be a useful tool to identify at-risk cows early enough to allow for preventive interventions. Further studies should investigate the diagnostic utility of incorporating RT data early in the dry period in the disease prediction algorithms of rumination sensors. [ABSTRACT FROM AUTHOR]