Dataset Information

Enhancing the value of accelerometer-assessed physical activity: meaningful visual comparisons of data-driven translational accelerometer metrics.

ABSTRACT: The lack of consensus on meaningful and interpretable physical activity outcomes from accelerometer data hampers comparison across studies. Cut-point analyses are simple to apply and easy to interpret but can lead to results that are not comparable. We propose that the optimal accelerometer metrics for data analysis are not the same as the optimal metrics for translation. Ideally, analytical metrics are precise continuous variables that cover the intensity spectrum, while translational metrics facilitate meaningful, public-health messages and can be described in terms of activities (e.g. brisk walking) or intensity (e.g. moderate-to-vigorous physical activity). Two analytical metrics that capture the volume and intensity of the 24-h activity profile are average acceleration (volume) and intensity gradient (intensity distribution). These allow investigation of independent, additive and interactive associations of volume and intensity of activity with health; however, they are not immediately interpretable. The MX metrics, the acceleration above which the most active X minutes are accumulated, are translational metrics that can be interpreted in terms of indicative activities. Using a range of MX metrics illustrates the intensity gradient and average acceleration (i.e. 24-h activity profile). The M120, M60, M30, M15 and M5 illustrate the most active accumulated minutes of the day, the M1/3DAY the most active accumulated 8?h of the day. We demonstrate how radar plots of MX metrics can be used to interpret and translate results from between- and within-group comparisons, provide information on meeting guidelines, assess individual activity profiles relative to percentiles and compare activity profiles between domains and/or time periods.

SUBMITTER: Rowlands AV

PROVIDER: S-EPMC6895365 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Enhancing the value of accelerometer-assessed physical activity: meaningful visual comparisons of data-driven translational accelerometer metrics.

Rowlands Alex V AV Dawkins Nathan P NP Maylor Ben B Edwardson Charlotte L CL Fairclough Stuart J SJ Davies Melanie J MJ Harrington Deirdre M DM Khunti Kamlesh K Yates Tom T

Sports medicine - open 20191205 1

The lack of consensus on meaningful and interpretable physical activity outcomes from accelerometer data hampers comparison across studies. Cut-point analyses are simple to apply and easy to interpret but can lead to results that are not comparable. We propose that the optimal accelerometer metrics for data analysis are not the same as the optimal metrics for translation. Ideally, analytical metrics are precise continuous variables that cover the intensity spectrum, while translational metrics f ...[more]

PMID: 31808014

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Project description:IntroductionThe aim of this study was to assess the impact of baseline characteristics on visual outcome of patients with diabetic macular edema and compare the results of clinical trials with different patient populations.MethodsA model was created with patient-level data from the RESPOND/RESTORE trials to estimate the impact of baseline characteristics on increases in best-corrected visual acuity (BCVA) with anti-vascular endothelial growth factor therapies, measured by letters gained on the Early Treatment Diabetic Retinopathy Study scale from baseline to month 12. Mean BCVA gains with ranibizumab 0.5 mg pro re nata or laser photocoagulation monotherapy were predicted, assuming baseline characteristics equivalent to those in the VIVID-DME/VISTA-DME trials. These results were compared with the gain with aflibercept 2.0 mg every 8 weeks in VIVID-DME/VISTA-DME. Sensitivity analyses assessed outcome robustness.ResultsBaseline BCVA and central retinal thickness differed significantly between trials. In unadjusted data, patients in RESPOND/RESTORE receiving ranibizumab gained an additional 6.6 letters [95% confidence interval (CI): 4.5-8.7] compared with patients receiving laser monotherapy. After adjusting data to assume baseline characteristics equivalent to VIVID-DME/VISTA-DME, patients receiving ranibizumab were predicted to gain an additional 9.9 letters (95% CI: 7.3-12.4) compared with those receiving laser monotherapy. These results were similar (0.1-letter difference in favor of aflibercept; 95% CI: -2.9 to 3.2; P = 0.94) to the gain in BCVA in patients receiving aflibercept in VIVID-DME/VISTA-DME compared with those receiving laser monotherapy (10.0 letters, 95% CI: 8.3-11.7).ConclusionAfter adjusting for baseline characteristics, the difference in letters gained between patients receiving ranibizumab versus aflibercept was non-significant across trials, highlighting the importance of adjusting for baseline characteristics in future comparisons.FundingNovartis Pharma AG.

Project description:INTRODUCTION:The way physical activity (PA) and sedentary behavior (SB) are accumulated throughout the day (i.e., patterns) may be important for health, but identifying measurable and meaningful metrics of behavioral patterns is challenging. This study evaluated accelerometer-derived metrics to determine whether they predicted PA and SB patterns and were reliably measured. METHODS:We defined and measured 55 metrics that describe daily PA and SB using data collected by using the activPAL monitor in four studies. The first two studies were randomized crossover designs that included recreationally active participants. Study 1 experimentally manipulated time spent in moderate-to-vigorous-intensity PA and sedentary time, and study 2 held time in exercise constant and manipulated SB. Study 3 included inactive participants who increased exercise, decreased sedentary time, or both. The study conditions induced distinct behavioral patterns; thus, we tested whether the new metrics could improve the prediction of an individual's study condition after adjusting for the overall volume of PA or SB using conditional logistic regression. In study 4, we measured the 3-month reliability for the pattern metrics by calculating intraclass correlation coefficients in a community-dwelling sample who wore the activPAL monitor twice for 7 d. RESULTS:In each of the experimental studies, we identified new metrics that could improve the accuracy for predicting condition beyond SB and moderate-to-vigorous-intensity PA volume. In study 1, 23 metrics were predictive of a highly active condition, and in study 2, 24 metrics were predictive of a highly sedentary condition. In study 4, the median intraclass correlation coefficients (25-75th percentiles) of the metrics were 0.59 (0.46-0.65). CONCLUSIONS:Several new metrics were predictive of patterns of SB, exercise, and nonexercise behavior and are moderately reliable for a 3-month period. Applying these metrics to determine whether daily behavioral patterns are associated with health-outcomes is an important area of future research.

Dataset Information

Enhancing the value of accelerometer-assessed physical activity: meaningful visual comparisons of data-driven translational accelerometer metrics.

Publications

Enhancing the value of accelerometer-assessed physical activity: meaningful visual comparisons of data-driven translational accelerometer metrics.

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