261 research outputs found
COVID-19 highlights the potential for a more dynamic approach to physical activity surveillance
Get PDFWrist-worn Accelerometry for Runners: Objective Quantification of Training Load.
Get PDFPURPOSE: This study aimed to apply open-source analysis code to raw habitual physical activity data from wrist-worn monitors to: 1) objectively, unobtrusively, and accurately discriminate between "running" and "nonrunning" days; and 2) develop and compare simple accelerometer-derived metrics of external training load with existing self-report measures. METHODS: Seven-day wrist-worn accelerometer (GENEActiv; Activinsights Ltd, Kimbolton, UK) data obtained from 35 experienced runners (age, 41.9 ± 11.4 yr; height, 1.72 ± 0.08 m; mass, 68.5 ± 9.7 kg; body mass index, 23.2 ± 2.2 kg·m; 19 [54%] women) every other week over 9 to 18 wk were date-matched with self-reported training log data. Receiver operating characteristic analyses were applied to accelerometer metrics ("Average Acceleration," "Most Active-30mins," "Mins≥400 mg") to discriminate between "running" and "nonrunning" days and cross-validated (leave one out cross-validation). Variance explained in training log criterion metrics (miles, duration, training load) by accelerometer metrics (Mins≥400 mg, "workload (WL) 400-4000 mg") was examined using linear regression with leave one out cross-validation. RESULTS: Most Active-30mins and Mins≥400 mg had >94% accuracy for correctly classifying "running" and "nonrunning" days, with validation indicating robustness. Variance explained in miles, duration, and training load by Mins≥400 mg (67%-76%) and WL400-4000 mg (55%-69%) was high, with validation indicating robustness. CONCLUSIONS: Wrist-worn accelerometer metrics can be used to objectively, unobtrusively, and accurately identify running training days in runners, reducing the need for training logs or user input in future prospective research or commercial activity tracking. The high percentage of variance explained in existing self-reported measures of training load by simple, accelerometer-derived metrics of external training load supports the future use of accelerometry for prospective, preventative, and prescriptive monitoring purposes in runners
A comparison of analytical approaches to investigate associations for accelerometry-derived physical activity spectra with health and developmental outcomes in children
Get PDFUnder embargo until: 2021-09-20The use of high-resolution physical activity intensity spectra obtained from accelerometry can improve knowledge of associations with health and development beyond the use of traditional summary measures of intensity. The aim of the present study was to compare three different approaches for determining associations for spectrum descriptors of physical activity (the intensity gradient, principal component analysis, and multivariate pattern analysis) with relevant outcomes in children. We used two datasets including physical activity spectrum data (ActiGraph GT3X+) and 1) a cardiometabolic health outcome in 841 schoolchildren and 2) a motor skill outcome in 1081 preschool children. We compared variance explained (R2) and associations with the outcomes for the intensity gradient (slope) across the physical activity spectra, a two-component principal component model describing the physical activity variables, and multivariate pattern analysis using the intensity spectra as the explanatory data matrices. Results were broadly similar for all analytical approaches. Multivariate pattern analysis explained the most variance in both datasets, likely resulting from use of more of the information available from the intensity spectra. Yet, volume and intensity dimensions of physical activity are not easily disentangled and their relative importance may be interpreted differently using different methodology.acceptedVersio
Introducing novel approaches for examining the variability of individuals' physical activity
Get PDFTudor-Locke and colleagues previously assessed steps/day for 1 year. The aim of this study was to use this data set to introduce a novel approach for the investigation of whether individual's physical activity exhibits periodicity fluctuating round a mean and, if so, the degree of fluctuation and whether the mean changes over time. Twenty-three participants wore a pedometer for 365 days, recorded steps/day and whether the day was a workday. Fourier transform of each participant's daily steps data showed the physical activity had a periodicity of 7 days in half of the participants, matching the periodicity of the workday pattern. Activity level remained stable in half of the participants, decreased in ten participants and increased in two. In conclusion, the 7-day periodicity of activity in half of the participants and correspondence with the workday pattern suggest a social or environmental influence. The novel analytical approach introduced herein allows the determination of the periodicity of activity, the degree of variability in activity that is tolerated during day-to-day life and whether the activity level is stable. Results from the use of these methodologies in larger data sets may enable a more focused approach to the design of interventions that aim to increase activity
Absolute intensity thresholds for tri-axial wrist and waist accelerometer-measured movement behaviors in adults
Get PDFAim: This study was aimed to: (1) compare raw triaxial acceleration data from GENEActiv (GA) and ActiGraph GT3X+ (AG) placed on the non-dominant wrist; (2) compare AG placed on the non-dominant and dominant wrist, and waist; (3) derive brand- and placement-specific absolute intensity thresholds for inactive and sedentary time, and physical activity intensity in adults. Methods: Eighty-six adults (44 men; 34.6 ± 10.8 years) performed nine activities while simultaneously wearing GA and AG on wrist and waist. Acceleration (in gravitational equivalent units; mg) was compared with oxygen uptake (measured with indirect calorimetry). Results: Increases in acceleration mirrored increases in intensity of activities, regardless of device brand and placement. Differences in acceleration between GA and AG worn at the non-dominant wrist were small but tended to be high at lower intensity activities. Thresholds for differentiating inactivity (<1.5 MET) from activity (≥1.5 MET) ranged from 25 mg (AG non-dominant wrist; sensitivity 93%, specificity 95%) to 40 mg (AG waist; sensitivity 78%, specificity 100%). For moderate intensity (≥3 METs), thresholds ranged from 65 mg (AG waist; sensitivity 96%, specificity 94%) to 92 mg (GA non-dominant; sensitivity 93%, specificity 98%); vigorous intensity (≥6 METs) thresholds ranged from 190 mg (AG waist; sensitivity 82%, specificity 92%) to 283 mg (GA non-dominant; sensitivity 93%, specificity 98%). Conclusion: Raw triaxial acceleration outputs from two widely used accelerometer brands may have limited comparability in low intensity activities. Thresholds derived in this study can be utilized in adults to reasonably classify movement behaviors into categories of intensity.publishedVersio
Wear Compliance and Activity in Children Wearing Wrist and Hip-Mounted Accelerometers.
Get PDFPURPOSE: This study aimed to (i) explore children's compliance to wearing wrist and hip-mounted accelerometers, (ii) compare children's physical activity (PA) derived from wrist and hip raw accelerations, and (iii) examine differences in raw and counts PA measured by hip-worn accelerometry. METHODS: One hundred and twenty nine 9-10 y old children wore a wrist-mounted GENEActiv accelerometer (GAwrist) and a hip-mounted ActiGraph GT3X+ accelerometer (AGhip) for 7 d. Both devices measured raw accelerations and the AGhip also provided counts-based data. RESULTS: More children wore the GAwrist than the AGhip regardless of wear time criteria applied (p<.001 - .035). Raw data signal vector magnitude (SVM; r = .68), moderate PA (MPA; r = .81), vigorous PA (VPA; r = .85), and moderate-to-vigorous PA (MVPA; r = .83) were strongly associated between devices (p<.001). GAwrist SVM (p = .001), MPA (p = .037), VPA (p = .002), and MVPA (p = .016) were significantly greater than AGhip. According to GAwrist raw data, 86.9% of children engaged in at least 60 min MVPA[BULLET OPERATOR]d, compared to 19% for AGhip. ActiGraph MPA (raw) was 42.00 ± 1.61 min[BULLET OPERATOR]d compared to 35.05 ± 0.99 min[BULLET OPERATOR]d (counts) (p=.02). Actigraph VPA was 7.59 ± 0.46 min[BULLET OPERATOR]d (raw) and 37.06 ± 1.85 min[BULLET OPERATOR]d (counts; p=.19). CONCLUSION: In children accelerometer wrist placement promotes superior compliance than the hip. Raw accelerations were significantly higher for GAwrist compared to AGhip, possibly due to placement location and technical differences between devices. AGhip PA calculated from raw accelerations and counts differed substantially, demonstrating that PA outcomes derived from cutpoints for raw output and counts cannot be directly compared
Maturational timing, physical self-perceptions and physical activity in UK adolescent females: Investigation of a mediated effects model
Get PDFBackground: Advanced
(early) biological maturation may be a risk factor for inactivity among adolescent
girls. The aim of the present paper was to test the mediational effects of body
attractiveness and physical self-worth on the relationship between biological
maturity and accelerometer assessed moderate-to-vigorous physical activity (MVPA)
in a large multi-ethnic sample of girls from the Midlands area in the UK (11-14
years).
Methods: Biological
maturity (predicting age at peak height velocity (APHV)); self-perceptions of
body attractiveness, physical self-worth, and minutes spent in MVPA were assessed
in 1062 females aged 11 to 14 years.
Results: Structural
equation modeling using maximum likelihood estimation and boot- strapping
procedures supported the hypothesized model. Later maturation predicted higher
perceptions of body attractiveness (β=.25, p<.001) which, in turn, predicted
higher perceptions of physical self-worth (β=.91, p<.001) and, significantly
higher MVPA (β=.22, p<.001). Examination
of the bootstrap-generated bias-corrected confidence intervals suggested that perceptions
of body attractiveness and physical self-worth partially mediated a positive association
between predicted APHV and MVPA (β=.05, p
Conclusions: Greater biological maturity (i.e. early maturity)
in adolescent girls is associated with less involvement in MVPA and appears to
be partly explained by lower perceptions of body attractiveness and physical
self-worth. Physical activity interventions should consider girls perceptions of their pubertal related physiological changes
during adolescence, particularly among early maturing girls. </p
A data-driven, meaningful, easy to interpret, standardised accelerometer outcome variable for global surveillance
Get PDFThis is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Objectives: Our aim is to demonstrate how a data-driven accelerometer metric, the acceleration above which
a person’s most active minutes are accumulated, can a) quantify the prevalence of meeting current physical
activity guidelines for global surveillance and b) moving forward, could inform accelerometer-driven physical
activity guidelines. Unlike cut-point methods, the metric is population-independent (e.g. age) and potentially
comparable across datasets. Design: Cross-sectional, secondary data analysis. Methods: Analyses were
carried out on five datasets using wrist-worn accelerometers: children (N=145), adolescent girls (N=1669),
office workers (N=114), pre- (N=1218) and post- (N=1316) menopausal women, and adults with type 2
diabetes (N=475). Open-source software (GGIR) was used to generate the magnitude of acceleration above
which a person’s most active 60, 30 and 2 minutes are accumulated: M60ACC; M30ACC and M2ACC,
respectively. Results: The proportion of participants with M60ACC (children) and M30ACC (adults) values
higher than accelerations representative of brisk walking (i.e., moderate-to-vigorous physical activity) ranged
from 17-68% in children and 15%-81% in adults, tending to decline with age. The proportion of pre-and postmenopausal women with M2ACC values meeting thresholds for bone health ranged from 6-13%. Conclusions:
These metrics can be used for global surveillance of physical activity, including assessing prevalence of
meeting current physical activity guidelines. As accelerometer and corresponding health data accumulate it
will be possible to interpret the metrics relative to age- and sex- specific norms and derive evidence-based
physical activity guidelines directly from accelerometer data for use in future global surveillance. This is
where the potential advantages of these metrics lie
Modelling the Reallocation of Time Spent Sitting into Physical Activity: Isotemporal Substitution vs. Compositional Isotemporal Substitution.
Get PDFIsotemporal substitution modelling (ISM) and compositional isotemporal modelling (CISM) are statistical approaches used in epidemiology to model the associations of replacing time in one physical behaviour with time in another. This study's aim was to use both ISM and CISM to examine and compare associations of reallocating 60 min of sitting into standing or stepping with markers of cardiometabolic health. Cross-sectional data collected during three randomised control trials (RCTs) were utilised. All participants (n = 1554) were identified as being at high risk of developing type 2 diabetes. Reallocating 60 min from sitting to standing and to stepping was associated with a lower BMI, waist circumference, and triglycerides and higher high-density lipoprotein cholesterol using both ISM and CISM (p < 0.05). The direction and magnitude of significant associations were consistent across methods. No associations were observed for hemoglobin A1c, total cholesterol, or low-density lipoprotein cholesterol for either method. Results of both ISM and CISM were broadly similar, allowing for the interpretation of previous research, and should enable future research in order to make informed methodological, data-driven decisions
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