60-s Epochs Research Articles

Stimulus type and duration affect magnitude and evolution of flicker-induced hyperemia measured by laser speckle flowgraphy at the optic disc and peripapillary vessels

Neurovascular coupling is a vital mechanism employed by the cerebrovascular system, including the eye, to regulate blood flow in periods of neuronal activation. This study aims to investigate if laser speckle flowgraphy (LSFG) can detect coupling response elicited by flickering light stimuli and how variations in stimulus type and duration can affect the magnitude and evolution of blood flow in the optic nerve head (ONH) and peripapillary vessels. Healthy adults were exposed to two types of 10-Hz flicker stimuli: a photopic negative response-like stimulus (PhNR-S) or a visual evoked potential-like stimulus (VEP-S)—each presented in separate 10- and 60-s epochs. Both PhNR-S and VEP-S significantly increased ONH blood flow (p < 0.001) immediately after flicker cessation, with a trend of 60-s stimuli (PhNR-S = 11.6%; VEP-S = 10.4%) producing a larger response than 10-s stimuli (PhNR-S = 7.5%; VEP-S = 6.2%). Moreover, exposure to 60-s stimuli elicited a significantly prolonged ONH hyperemic response, especially with PhNR-S. Lastly, stimulation with either 60-s stimuli elicited a robust increase in blood flow within the peripapillary arterioles (p < 0.01) and venules (p < 0.01) as well. Flicker stimulation with common visual electrophysiology stimuli (PhNR-S and VEP-S) induced a demonstrable increase in ONH and peripapillary vessel blood flow, which varied with flicker duration. Our results validate that LSFG is a robust method to quantify flicker-induced hyperemic responses and to study neurovascular coupling in humans.

Research-Grade Accelerometers to Assess Intervention Effectiveness and Commercial Wearables as a Self-Monitoring Tool: Are the Two Aligned on Moderate to Vigorous Physical Activity?

There is limited evidence about how comparable commercial monitors and moderate to vigorous physical activity (MVPA) cut-points frequently used with research-grade accelerometers are in estimating time spent in MVPA when both are worn on the wrist. We used data from 14 adults (57.3 years) who concurrently wore Fitbit (Versa 2) and Axivity (AX3) monitors to assess comparability between the Fitbit and Axivity data, aggregated to 5-s and 60-s epochs, for time spent in daily MVPA and MVPA in bouts of ≥1 – &lt;2 min, ≥2 – &lt;5 min, and ≥5 min. The Fitbit provided higher estimates of total daily MVPA (93.8 ± 66.3 min/day) compared with Axivity-assessed MVPA derived from either 5-s (59.2 ± 37.3 min/day) or 60-s (47.4 ± 36.2 min/day) epochs. The number and duration of MVPA bouts were also higher from Fitbit compared with Axivity (5-s and 60-s epochs). Intraclass correlation coefficients showed moderate to good reliability between MVPA assessed by the Fitbit and Axivity devices (5 s and 60 s). Bland–Altman analysis suggested proportional bias between the Fitbit and Axivity outcomes with wide limits of agreement. No MVPA outcomes were within the 10% equivalency zone. Researchers utilizing the Fitbit as a self-monitoring tool within an intervention should be aware of the potential misalignment with the research-grade accelerometer used to evaluate intervention effectiveness. Feedback from a Fitbit may inform participants they have achieved the required MVPA, while outcomes from the research-grade device may classify them as not meeting their target.

Effect of Data Reduction Techniques on Daily Moderate to Vigorous Physical Activity Collected with ActiGraph® in People with COPD.

ActiGraph® is a valid, frequently used, accelerometer to quantify moderate to vigorous physical activities (MVPA) in people with COPD. The impact of ActiGraph processing techniques on this population is unknown. This study aimed to explore the effect of data reduction techniques on MVPA in people with COPD. MVPA/day, through ActiGraph GT3X+, was estimated using: Troiano, Freedson 98 and FreedsonVM3 cutoffs, 15-s and 60-s epochs, and normal and low-frequency extension (LFE) filters. Cutoff, epoch, and filter effects were explored with Aligned Rank Transform-ANOVA. Lin's concordance correlation coefficients and Bland-Altman plots were used to evaluate agreement and bias between different techniques. The analysis included 136 people with COPD (79% male; 68 ± 8 years; FEV1 51 ± 17% predicted). MVPA/day differed according to cutoff, filter, and epoch selection (p-value < 0.001). FreedsonVM3 cutoff, 15-s epochs, and LFE yielded the highest MVPA (45 min/day, 68% of physically active participants). Troiano cutoff, 60-s epochs, and normal filter yielded the lowest MVPA (8 min/day, 20% of physically active participants). Only comparisons between Troiano and Freedson98 cutoffs presented an almost perfect agreement. ActiGraph data reduction techniques affected MVPA/day estimates and their interpretation at the individual and group level. Studies using different processing criteria should not be compared in people with COPD. Future studies with a gold standard are required to ascertain which processing technique produces the most accurate MVPA estimates in COPD. Meanwhile, future trials employing the ActiGraph GT3X+ may consider estimating MVPA based on Freedson VM3 cutofffs, 60-s epochs, and normal filter.

Convergent Validity Between Epoch-Based activPAL and ActiGraph Methods for Measuring Moderate to Vigorous Physical Activity in Youth and Adults

Purpose: We investigated convergent validity of commonly used ActiGraph scoring methods with various activPAL scoring methods in youth and adults. Methods: Youth and adults wore an ActiGraph and activPAL simultaneously for 1–3 days. We compared moderate to vigorous physical activity (MVPA) estimates from the ActiGraph Evenson 15-s (youth) and Freedson 60-s (adult) cut-point scoring methods and four activPAL scoring methods based on metabolic equivalents (METs), step counts, vertical axis counts, and vector magnitude counts. All activPAL methods were applied to 15-s epochs for youth and 60-s epochs for adults, and the METs method was also applied to 1-s epochs. Epoch-level agreement was examined with classification tests (sensitivity, positive predictive value, and F1) using the ActiGraph methods as the referent. Day-level agreement was examined using tests of mean error, mean absolute error, and Spearman correlations. Results: Relative to ActiGraph methods, which indicated a mean MVPA of 41 min/day for youth and 24 min/day for adults, the activPAL METs method applied to 15-s epochs in youth and 60-s epochs in adults yielded the most comparable estimates of MVPA. Daily MVPA estimated from all other activPAL scoring methods generally had poor agreement with ActiGraph methods in youth and adults. Conclusion: When using the same epoch lengths between monitors, MVPA estimation via the activPAL METs scoring method appears to have good comparability to ActiGraph cut points at the group-level and moderate comparability at the individual-level in youth and adults. When using this scoring method, the activPAL appears to be appropriate for measuring daily minutes of MVPA in youth and adults.

The Influence of Accelerometer Epoch Length on Associations of Physical Activity Intensity and Volume with Bone Outcomes.

Two accelerometer metrics (intensity-gradient and average-acceleration) can be used to determine the relative contributions of physical activity (PA) volume and intensity for health, but it is unknown whether epoch length influences the associations detected. This is important when considering bone health, as bone is particularly responsive to high intensity PA, which may be underestimated by longer epochs. This study aimed to assess the associations between average-acceleration, a proxy measure of PA volume, and intensity-gradient, reflective of PA intensity distribution, from PA data from 1-s to 60-s epochs at age 17 to 23 years with bone outcomes at age 23 years. This is a secondary analysis of 220 participants (124 females) from the Iowa Bone Development Study, a longitudinal study of bone health from childhood to early adulthood. Accelerometer-assessed PA data, captured at age 17 to 23 years, were summarised over 1-s, 5-s, 15-s, 30-s, and 60-s epochs, to generate average-acceleration and intensity-gradient from each epoch length, averaged across ages. Regression analysed associations between mutually adjusted average-acceleration and intensity-gradient with dual-energy X-ray absorptiometry assessed total-body-less-head (TBLH) bone mineral content (BMC), spine areal bone mineral density (aBMD), hip aBMD, and femoral neck cross-sectional area and section modulus at age 23 years. Intensity-gradient was positively associated with TBLH BMC in females, with spine aBMD in males, and with hip aBMD and geometry in both sexes, when a 1 to 5-s epoch was used. Average-acceleration was positively associated with TBLH BMC, spine aBMD and hip aBMD in males, generally when the adjustment for intensity-gradient was from > 1-s epochs. Intensity and volume were important for bone outcomes in both sexes and males, respectively. A 1 to 5-s epoch length was most appropriate to assess the mutually adjusted associations of intensity-gradient and average-acceleration with bone outcomes in young adults.

Comparing the most demanding scenarios of official matches across five different professional team sports in the same club

The purpose of this study was to compare the most demanding scenarios (MDS) of match-play across five different team sports of the same club (basketball, futsal, handball, rink hockey and soccer) during five different time epochs (30, 60, 120, 180 and 300 s). Sixty-five professional male players were monitored across 14 to 17 official matches via a local positioning system. Peak physical demands included total distance, distance, and actions >18 km·h −1 and distance and number of accelerations and decelerations >2 m·s −2 . One-way analysis of variance and Tukey post-hoc tests were used to test statistical significance (p <.05), whereas standardized Cohen's effect size and the respective 95% confidence intervals were calculated to detect differences between team sports. While soccer and rink hockey achieved the greatest MDS in total distance, and distance and number of actions >18 km·h −1 during all the time epochs examined, basketball presented the highest peak values in number of accelerations and decelerations >2 m·s −2 during 30-s and 60-s time epochs. In conclusion, the MDS during competition are significantly different across team sports, which can be useful in determining the upper limit threshold for sport-specific training optimisation and return to play purposes.

Assessment of neonatal respiratory rate variability

Accurate measurement of respiratory rate (RR) in neonates is challenging due to high neonatal RR variability (RRV). There is growing evidence that RRV measurement could inform and guide neonatal care. We sought to quantify neonatal RRV during a clinical study in which we compared multiparameter continuous physiological monitoring (MCPM) devices. Measurements of capnography-recorded exhaled carbon dioxide across 60-s epochs were collected from neonates admitted to the neonatal unit at Aga Khan University-Nairobi hospital. Breaths were manually counted from capnograms and using an automated signal detection algorithm which also calculated mean and median RR for each epoch. Outcome measures were between- and within-neonate RRV, between- and within-epoch RRV, and 95% limits of agreement, bias, and root-mean-square deviation. Twenty-seven neonates were included, with 130 epochs analysed. Mean manual breath count (MBC) was 48 breaths per minute. Median RRV ranged from 11.5% (interquartile range (IQR) 6.8–18.9%) to 28.1% (IQR 23.5–36.7%). Bias and limits of agreement for MBC vs algorithm-derived breath count, MBC vs algorithm-derived median breath rate, MBC vs algorithm-derived mean breath rate were − 0.5 (− 2.7, 1.66), − 3.16 (− 12.12, 5.8), and − 3.99 (− 11.3, 3.32), respectively. The marked RRV highlights the challenge of performing accurate RR measurements in neonates. More research is required to optimize the use of RRV to improve care. When evaluating MCPM devices, accuracy thresholds should be less stringent in newborns due to increased RRV. Lastly, median RR, which discounts the impact of extreme outliers, may be more reflective of the underlying physiological control of breathing.

Comparison of Self-Reported and Device-Based Measured Physical Activity Using Measures of Stability, Reliability, and Validity in Adults and Children.

Quantification of physical activity (PA) depends on the type of measurement and analysis method making it difficult to compare adherence to PA guidelines. Therefore, test-retest reliability, validity, and stability for self-reported (i.e., questionnaire and diary) and device-based measured (i.e., accelerometry with 10/60 s epochs) PA was compared in 32 adults and 32 children from the SMARTFAMILY study to examine if differences in these measurement tools are systematic. PA was collected during two separate measurement weeks and the relationship for each quality criteria was analyzed using Spearman correlation. Results showed the highest PA values for questionnaires followed by 10-s and 60-s epochs measured by accelerometers. Levels of PA were lowest when measured by diary. Only accelerometry demonstrated reliable, valid, and stable results for the two measurement weeks, the questionnaire yielded mixed results and the diary showed only a few significant correlations. Overall, higher correlations for the quality criteria were found for moderate than for vigorous PA and the results differed between children and adults. Since the differences were not found to be systematic, the choice of measurement tools should be carefully considered by anyone working with PA outcomes, especially if vigorous PA is the parameter of interest.

Pediatric cardiopulmonary resuscitation quality during intra-hospital transport

AimTo evaluate pediatric cardiopulmonary resuscitation (CPR) quality during intra-hospital transport to facilitate extracorporeal membrane oxygenation (ECMO)-CPR (ECPR). We compared chest compression (CC) rate, depth, and fraction (CCF) between the pre-transport and intra-transport periods. MethodsObservational study of children <18 years with either in-hospital cardiac arrest (IHCA) or out-of-hospital cardiac arrest (OHCA) who underwent transport between two care locations within the hospital for ECPR and who had CPR mechanics data available. Descriptive patient and arrest characteristics were summarized. The primary analysis compared pre- to intra-transport CC rate, depth, and fraction. A secondary analysis compared the proportion of pre- versus intra-transport 60-s epochs meeting guideline recommendations for rate (100–120/min), depth (≥4 cm for infants; ≥5 cm for children ≥1 year), and CCF (≥0.80). ResultsSeven patients (four IHCA; three witnessed OHCA) met eligibility criteria. Six (86%) patients survived the event and two (28%) survived to hospital discharge. Median transport CPR duration was 7 [IQR 5.5, 8.5] minutes. There were no differences in pre- vs. intra-transport CC rate (115 [113, 118] vs. 118 [114, 127] CCs/minute; p = 0.18), depth (3.2 [2.7, 4.4] vs. 3.6 [2.5, 4.6] cm; p = 0.50), or CCF (0.89 [0.82, 0.90] vs. 0.92 [0.79, 0.97]; p = 0.31). Equivalent proportions of 60-s CPR epochs met guideline recommendations between pre- and intra-transport (rate: 66% vs. 57% [p = 0.22]; depth: 14% vs. 19% [p = 0.39]; CCF: 80% vs. 75% [p = 0.43]). ConclusionsPediatric CPR quality was maintained during intra-hospital patient transport, suggesting that it is reasonable for ECPR systems to incorporate patient transport to facilitate ECMO cannulation.

Modifying Accelerometer Cut-Points Affects Criterion Validity in Simulated Free-Living for Adolescents and Adults

ABSTRACT Purpose: To assess changes in criterion validity when modifying cut-points for use in different epoch lengths. Method: Simulated free-living data came from 42 adolescents (2-hr each) and 29 adults (6-hr each) wearing a hip-worn accelerometer and portable indirect calorimeter (Cosmed K4b2). K4b2 data were classified as sedentary behavior (SB), light physical activity (LPA), or moderate-to-vigorous physical activity (MVPA), and compared to estimates from accelerometer data processed with three youth and three adult cut-points in six epoch lengths (1, 5, 10, 15, 30, and 60-s). A cut-point of 100 counts per minute was used for all SB estimates. Results: For both adolescents and adults, SB estimates in all but 60-s epochs were significantly higher than the criterion, by 18.4%–78.4% (all p < .02). CPS had varied effects on youth LPA, ranging from favorable effects for one cut-point (1.9% underestimation in 1-s epochs, versus 40.2% overestimation in the originally-calibrated epoch length; p < .01 and p = .91, respectively) to unfavorable effects for another (41.8% underestimation in 1-s epochs, versus 9.8% underestimation in the originally-calibrated epoch length; p < .01 and p = .39, respectively). Adult LPA estimates in 30-s or 60-s epochs were closest to the criterion (within 5.2%–37.3%, p = .0001–0.49). Youth MVPA estimates in 60-s epochs were closest to the criterion (within 9.5%–53.2%, all p < .05), whereas adult MVPA estimates in 1-s epochs were closest to the criterion (within 6.6%–34.2%, p = .02–0.59). Conclusion: Cut-point modification is not universally beneficial, and thus it is not recommended.

ActivPAL and ActiGraph Assessed Sedentary Behavior and Cardiometabolic Health Markers.

To establish whether associations between sedentary behavior and cardiometabolic health differ when assessed by thigh-worn and waist-worn accelerometry. Participants were recruited from several areas in the United Kingdom. Sedentary behavior was assessed using the activPAL worn on the thigh and ActiGraph worn on the waist. Average total (TST), prolonged (bouts ≥30 min; PST) and breaks (BST) in sedentary time were calculated. Cardiometabolic health markers included: adiposity (body fat) and surrogate markers of adiposity ((waist circumference, body mass index [BMI]), lipids (total, low density lipoprotein, and high-density lipoprotein [HDL] cholesterol, triglycerides), blood pressure, and glucose (fasting, 2 h and glycated hemoglobin A1c). A clustered cardiometabolic risk score was calculated. Linear regression analysis examined the associations with cardiometabolic health. There were 1457 participants (mean age [± standard deviation], 59.38 ± 11.85 yr; 51.7% male; mean BMI, 30.19 ± 5.59 kg·m) included in the analyses. ActivPAL and ActiGraph sedentary variables were moderately correlated (0.416-0.511, P < 0.01); however, all variables were significantly different from each other (P < 0.05). Consistency was observed across devices in the direction and magnitude of associations of TST and PST with adiposity, surrogate markers of adiposity, HDL, triglycerides, and cardiometabolic risk score and for BST with adiposity, surrogate markers of adiposity, and cardiometabolic risk. Differences across devices were observed in associations of TST and PST with diastolic blood pressure, for TST with 2-h glucose and for BST with HDL. No other associations were observed for any other health marker for either device. Results suggest that associations with cardiometabolic health are largely comparable across the two common assessments of sedentary behavior but some small differences may exist for certain health markers.

Validity of objective methods for measuring sedentary behaviour in older adults: a systematic review

BackgroundThe evidence showing the ill health effects of prolonged sedentary behaviour (SB) is growing. Most studies of SB in older adults have relied on self-report measures of SB. However, SB is difficult for older adults to recall and objective measures that combine accelerometry with inclinometry are now available for more accurately assessing SB. The aim of this systematic review was to assess the validity and reliability of these accelerometers for the assessment of SB in older adults.MethodsEMBASE, PubMed and EBSCOhost databases were searched for articles published up to December 13, 2017. Articles were eligible if they: a) described reliability, calibration or validation studies of SB measurement in healthy, community-dwelling individuals, b) were published in English, Portuguese or Spanish, and c) were published or in press as journal articles in peer-reviewed journals.ResultsThe review identified 15 studies in 17 papers. Of the included studies, 11 assessed the ActiGraph accelerometer. Of these, three examined reliability only, seven (in eight papers) examined validity only and one (in two papers) examined both. The strongest evidence from the studies reviewed is from studies that assessed the validity of the ActiGraph. These studies indicate that analysis of the data using 60-s epochs and a vertical magnitude cut-point < 200 cpm or using 30- or 60-s epochs with a machine learning algorithm provides the most valid estimates of SB. Non-wear algorithms of 90+ consecutive zeros is also suggested for the ActiGraph.ConclusionsFew studies have examined the reliability and validity of accelerometers for measuring SB in older adults. Studies to date suggest that the criteria researchers use for classifying an epoch as sedentary instead of as non-wear time (e.g., the non-wear algorithm used) may need to be different for older adults than for younger adults. The required number of hours and days of wear for valid estimates of SB in older adults was not clear from studies to date. More older-adult-specific validation studies of accelerometers are needed, to inform future guidelines on the appropriate criteria to use for analysis of data from different accelerometer brands.Trial registrationPROSPERO ID# CRD42017080754 registered December 12, 2017.

Number of days required for reliably estimating physical activity and sedentary behaviour from accelerometer data in older adults

ABSTRACT The purpose of the study was to examine the minimum number of monitoring days for reliably estimating physical activity (PA) and sedentary behaviour (SB) from accelerometer data in older adults. Forty-two older adults from a local senior centre participated in this study. Participants wore an ActiGraph wGT3X-BT on the right hip for 7 consecutive days. Accelerometer data were downloaded to a computer and converted to activity count data in 60s epochs. Time spent in SB and different PA intensity categories were estimated with commonly used activity count cut-points. Participants with at least 7 valid days of monitoring (≥10 h.day−1) were included in the analysis. Intraclass correlation coefficients (ICC) were calculated for determining single-day monitoring reliability. The Spearman-Brown prophecy formula was used to estimate the minimum number of monitoring days required for achieving an ICC of 0.80. Single-day ICC values for time spent in SB and PA intensity categories ranged from 0.45 to 0.61. Minimum number of monitoring days required for achieving an ICC of 0.80 ranged from 2.5 to 4.9 days. In this study, a minimum of 5 consecutive days of monitoring was required for reliably estimating SB and PA from accelerometer data in older adults.

Relationships of depressive behavior and sertraline treatment with walking speed and activity in older female nonhuman primates.

Depression is the most common mental health problem in aging persons and is a leading risk factor for physical disability, especially in women. Though antidepressant drugs such as serotonin reuptake inhibitors (SSRI) are commonly prescribed, epidemiological evidence reveals mixed effects of long-term antidepressant use on physical function and activity, possibly depending on depressive status. The purpose of this preclinical trial was to determine the relationships of depressive behavior and the potential for an SSRI treatment to modulate walking speed and activity patterns in older adult female cynomolgus monkeys (Macaca fascicularis). We evaluated the effects of depression and a commonly prescribed SSRI, sertraline HCl (20mg/kg/day p.o.), on (a) walking speed, (b) accelerometry-derived activity (counts) and sedentariness (daytime 60-s sedentary epochs), and (c) observed locomotor and sedentary behaviors (% time) in adult female depressed and nondepressed monkeys (n=42; 17.2±1.8years) during an 18month pre-treatment phase and an 18month treatment phase using a longitudinal, stratified placebo-control study design. Monkeys that were depressed prior to treatment (19/42) subsequently had slower walking speeds (F D [1, 38] =4.14; p≤0.05) and tended to be more sedentary during the daytime (F D [1, 38] =3.63; p≤0.06). Sertraline did not affect depressive behaviors, walking speed, accelerometry-derived physical activity or sedentariness, or time observed in total locomotor or sedentary behavior (all p>0.10). This study provides the first experimental demonstration of relationships between nonhuman primate behavioral depression and walking speed, activity, and sedentariness and provides evidence for a lack of an effect of SSRI treatment on these phenotypes.

Moving Forward with Backward Compatibility: Translating Wrist Accelerometer Data.

This study aimed to provide a means for calibrating raw acceleration data from wrist-worn accelerometers in relation to past estimates of children's moderate-to-vigorous physical activity (MVPA) from a range of cut points applied to hip-worn ActiGraph data. This is a secondary analysis of three studies with concurrent 7-d accelerometer wear at the wrist (GENEActiv) and hip (ActiGraph) in 238 children age 9-12 yr. The time spent above acceleration (ENMO) thresholds of 100, 150, 200, 250, 300, 350, and 400 mg from wrist acceleration data (≤5-s epoch) was calculated for comparison with MVPA estimated from widely used children's hip-worn ActiGraph MVPA cut points (Freedson/Trost, 1100 counts per minute; Pate, 1680 counts per minute; Evenson, 2296 counts per minute; Puyau, 3200 counts per minute) with epochs of ≤5, 15, and 60 s. The optimal ENMO thresholds for alignment with MVPA estimates from ActiGraph cut points determined from 70% of the sample and cross validated with the remaining 30% were as follows: Freedson/Trost = ENMO 150+ mg, irrespective of ActiGraph epoch (intraclass correlation [ICC] ≥ 0.65); Pate = ENMO 200+ mg, irrespective of ActiGraph epoch (ICC ≥ 0.67); Evenson = ENMO 250+ mg for ≤5- and 15-s epochs (ICC ≥ 0.69) and ENMO 300+ mg for 60-s epochs (ICC = 0.73); Puyau = ENMO 300+ mg for ≤5-s epochs (ICC = 0.73), ENMO 350+ mg for 15-s epochs (ICC = 0.73), and ENMO 400+ mg for 60-s epochs (ICC = 0.65). Agreement was robust with cross-validation ICC = 0.62-0.71 and means within ∣7.8∣% ± 4.9% of MVPA estimates from ActiGraph cut points, except Puyau 60-s epochs (ICC = 0.42). Incremental ENMO thresholds enable children's acceleration data measured at the wrist to be simply and directly compared, at a group level, with past estimates of MVPA from hip-worn ActiGraphs across a range of cut points.

Number of Days Required to Estimate Habitual Activity Using Wrist-Worn GENEActiv Accelerometer: A Cross-Sectional Study.

IntroductionObjective methods like accelerometers are feasible for large studies and may quantify variability in day-to-day physical activity better than self-report. The variability between days suggests that day of the week cannot be ignored in the design and analysis of physical activity studies. The purpose of this paper is to investigate the optimal number of days needed to obtain reliable estimates of weekly habitual physical activity using the wrist-worn GENEActiv accelerometer.MethodsData are from a subsample of the Mitchelstown cohort; 475 (44.6% males; mean aged 59.6±5.5 years) middle-aged Irish adults. Participants wore the wrist GENEActiv accelerometer for 7-consecutive days. Data were collected at 100Hz and summarised into a signal magnitude vector using 60s epochs. Each time interval was categorised according to intensity based on validated cut-offs. Spearman pairwise correlations determined the association between days of the week. Repeated measures ANOVA examined differences in average minutes across days. Intraclass correlations examined the proportion of variability between days, and Spearman-Brown formula estimated intra-class reliability coefficient associated with combinations of 1–7 days.ResultsThree hundred and ninety-seven adults (59.7±5.5yrs) had valid accelerometer data. Overall, men were most sedentary on weekends while women spent more time in sedentary behaviour on Sunday through Tuesday. Post hoc analysis found sedentary behaviour and light activity levels on Sunday to differ to all other days in the week. Analysis revealed greater than 1 day monitoring is necessary to achieve acceptable reliability. Monitoring frame duration for reliable estimates varied across intensity categories, (sedentary (3 days), light (2 days), moderate (2 days) and vigorous activity (6 days) and MVPA (2 days)).ConclusionThese findings provide knowledge into the behavioural variability in weekly activity patterns of middle-aged adults. Since Sunday differed from all other days in the week this suggests that day of the week cannot be overlooked in the design and analysis of physical activity studies and thus should be included in the study monitoring frames. Collectively our data suggest that six days monitoring, inclusive of Saturday and Sunday, are needed to reliably capture weekly habitual activity in all activity intensities using the wrist-worn GENEActiv accelerometer.

Are Physical Activity Patterns Interdependent Between 24-35 Month-olds And Their Parents?

PURPOSE: To evaluate physical activity (PA) interdependence and patterns among under-resourced, urban dwelling 24-35 month-old children and their parents. METHODS: Hip worn accelerometers were used to collect PA data from N = 60 dyads for 7 days at 30Hz. Child and parent data were analyzed in 5s and 60s epochs using Costa (2014) and Freedson (1998) cut points, respectively, with a custom algorithm. Descriptive statistics, correlations, tests for temporal and dyadic interdependence, two-phase linear regression, unbalanced panel data analysis, and a cross-lagged path analysis model were run. Significance level was set a priori at p < 0.05. RESULTS: PA data for 44 dyads (girls: n = 24; women: n = 43) achieved sufficient wear time reliability of r = 0.7 to 0.8. Most children (89%) were insufficiently active, while most parents (82%) met recommended volumes of PA. Vector magnitude (VM) patterns, reflecting PA intensity, were time dependent for children, but were independent from their parent’s VM patterns. Girls and boys participated in activities of similar VM. Child and parent time spent in PA were interdependent for light (LPA) [r(44) = 0.56] and moderate-vigorous (MVPA) [r(44) = 0.40], but not for sedentary (SED) behavior. There were no differences in SED nor LPA time between girls and boys. On average, girls spent fewer minutes per day in MVPA [35.4(19.3)] than did boys [44.1(23.8)], and parents of boys spent fewer minutes in MVPA per day [51.8(28.4)] than did parents of girls [66.5(32.2)] (β1*β2 = 11.797, t = 2.73). Children also spent fewer minutes in MVPA [39.5(21.7)] than their parents [59.6(31.1)] (β = -19.34, t = -4.47). Total time spent in PA (TPA) during a given hour had a significant effect on TPA time in the following hour for children [γ11 = 0.49(0.02), Z = 21.7] and for parents [γ22= 0.73(0.02), Z = 37.6]. After adjusting for respective time spent in TPA during the prior hour, parents showed a stronger effect on children’s minutes in TPA [γ21 = 0.13(0.01), Z = 10.3] than children did on the amount of time their parents spent in TPA [γ12 = 0.12(0.03), Z = 3.4]. CONCLUSION: Time spent in PA is temporally interdependent for very young children and their parents. However, the intensity of PA was independent within dyads. These data suggest that the temporal patterns of children’s PA should be considered when designing PA interventions.

The Influence of Epoch Length on Physical Activity Patterns Varies by Child's Activity Level

Purpose: Patterns of physical activity (PA) and sedentary time, including volume of bouted activity, are important health indicators. However, the effect of accelerometer epoch length on measurement of these patterns and associations with health outcomes in children remain unknown. Method: We measured activity patterns in 308 children (52% girls, age range = 8–11 years) using ActiGraph GT1M accelerometers with 15-s epochs and reintegrated to 60-s epochs. We calculated the volume (minutes per day) of moderate-to-vigorous PA (MVPA), sedentary time, light, moderate, and vigorous PA, as well as bouted MVPA and sedentary time (0–5 min, 5–10 min, 10–20 min, and > 20 min). Results: The difference between 15-s and 60-s epochs was statistically significant for all outcomes; however, effect sizes were small or negligible in 30% of comparisons. Bias ranged from 1.9 min/day (total MVPA) to 102.7 min/day (0–5 min sedentary bouts). Regression-based estimates of bias and 95% limits of agreement illustrated that the magnitude, and in some cases, the direction, of between-epoch differences varied with activity level. Correlations with body mass index and cardiovascular fitness were similar for 15-s (r = − .19 to .20) and 60-s (r = − .16 to .29) epochs. Estimated 15-s data (predicted from 60-s) were similar to measured data and had similar relationships with health outcomes. Conclusion: Epoch length influences measurement of PA and sedentary patterns and the effect is modified by activity level. However, associations with health outcomes were similar and epoch differences can be adjusted. Future research should clarify the accuracy of different epoch lengths for measuring bouted activity and evaluate whether epoch length alters relationships with additional health outcomes.

Comparing the Actical and ActiGraph Approach to Measuring Young Children’s Physical Activity Levels and Sedentary Time

Young children's activity and sedentary time were simultaneously measured via the Actical method (i.e., Actical accelerometer and specific cut-points) and the ActiGraph method (i.e., ActiGraph accelerometer and specific cut-points) at both 15-s and 60-s epochs to explore possible differences between these 2 measurement approaches. For 7 consecutive days, participants (n = 23) wore both the Actical and ActiGraph side-by-side on an elastic neoprene belt. Device-specific cut-points were applied. Paired sample t tests were conducted to determine the differences in participants' daily average activity levels and sedentary time (min/h) measured by the 2 devices at 15-s and 60-s time sampling intervals. Bland-Altman plots were used to examine agreement between Actical and ActiGraph accelerometers. Regardless of epoch length, Actical accelerometers reported significantly higher rates of sedentary time (15 s: 42.7 min/h vs 33.5 min/h; 60 s: 39.4 min/h vs 27.1 min/h). ActiGraph accelerometers captured significantly higher rates of moderate-to-vigorous physical activity (15 s: 9.2 min/h vs 2.6 min/h; 60 s: 8.0 min/h vs 1.27 min/h) and total physical activity (15 s: 31.7 min/h vs 22.3 min/h; 60 s: = 39.4 min/h vs 25.2 min/h) in comparison with Actical accelerometers. These results highlight the present accelerometry-related issues with interpretation of datasets derived from different monitors.

Physical Activity Behaviors of Daily Living in 2-3 Year-Olds Attending an Early Head Start Program

PURPOSE: To describe Physical Activity (PA) in 2-3 year-old low-income children attending an Early Head Start program (EHS) in a major urban center. METHODS: Child-parent dyads were given triaxial accelerometers (ActiGraph GT3X+) to wear at the waist during waking hours for 5 days. Child and parent PA ActiGraph data were analyzed in 5s and 60s epochs, respectively, using macro-based data reduction algorithms. The following wear time criteria were applied for child and parent, respectively, Non-Wear: 0cpm x 20min, < 3 hours/day, < 3 days observed; Non-Wear: 0cpm x 60mins, < 6 hours/day, < 3 days observed. Respective child and parent PA thresholds for sedentary (SED), light (LPA), and moderate to vigorous (MVPA) were defined using Costa (2014) and Freedson (1998) cut points. Descriptive statistics, Pearson’s correlations, and a one-way ANOVA were run, and the significance level was set at p < .05. RESULTS: Child-parent dyad data sets meeting wear time criteria (n=17) were analyzed. Children wore the ActiGraph for (5.6 ± 1.4) days and (8.73 ± 1.55) hours/day. Parents wore the ActiGraph for (5.6 ± 1.3) days and (10.18 ± 1.91) hours/day. There was a significant difference in the percentage of time spent in all intensities of PA between children (34 ± 5%) and parents (42 ± 8%). Children spent a greater portion of time in SED (66 ± 5%) than parents (58 ± 8%), while children also spent more time in MVPA (7 ± 3%) than their parents (3 ± 1%). Daily minutes spent in MVPA for children (35 ± 47mins) and parents (18 ± 11mins) were below the national MVPA recommendations of 60mins/day and 30mins x 5 days/week for children and adults, respectively. There was a significant correlation (r= .715) between the number LPA bouts per day for children (755 ± 193 bouts/day) and parents (80 ± 20 bouts/day). There was also a significant correlation (r= .548) between child and parent time spent in SED. CONCLUSION: Children and parents attending an EHS program were insufficiently active and spent a majority of their time being sedentary and in light physical activity. These results support the need to target interventions to increase PA for young children and their adult caregivers. Sponsored by the Teachers College, Columbia University Vice President’s Student Research in Diversity Grant and the Teachers College, Columbia University Arthur Zankel Urban Fellowship.