ArticleJournal of physical activity & health2010
Defining accelerometer thresholds for physical activity in girls using ROC analysis.
Article in Journal of physical activity & health, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Trial
- Calibrating Wrist-Worn Accelerometers for Physical Activity Assessment in Preschoolers: Machine Learning Approaches.JMIR formative research · 2020Article
- Sleep duration, timing, variability and measures of adiposity among 8- to 12-year-old children with obesity.Obesity science & practice · 2018Article
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Authors and funding
2 authors.
Funding
Abstract
backgroundReceiver operating characteristic (ROC) analysis is a common method used in diagnostic and screening tests to define thresholds levels of a factor that discriminates between 2 levels of another factor. The purpose of this analysis was to use ROC analysis to determine the optimal accelerometer-measured physical activity (PA) thresholds for predicting selective cardiovascular disease (CVD) risk factors.
methodsROC was performed using data from Stanford Girls Health Enrichment Multisite Studies trial. PA was assessed for multiple days using accelerometers. CVD variables were overweight, elevated triglyceride, reduced HDL-C, hypertension, impaired fasting glucose, fasting insulin, and clustering of multiple CVD risk factors.
resultsA sample of 261 girls participated, of which 208 had complete CVD risk measures (mean +/- SD age = 9.4 +/- 0.9yrs, BMI = 20.7 +/- 4.8kg/m2). An average of > or =11.1 minutes/day at > or =2,600 counts/min was the maximally sensitive and specific threshold for discriminating girls who were overweight, > or =16.6 minutes/day at > or =2,000 counts/min for hyperinsulinemia or with > or =2 CVD risk factors. The Area Under the Curve for overweight, hyperinsulinemia, and > or =2 CVD risk factors was of 0.66, 0.58, and 0.60, respectively. The sensitivity and specificity associated with overweight, hyperinsulinemia, and > or =2 CVD risk factors were 60.3% and 72.9%, 53.3% and 83.9%, 44.0% and 84.7%, respectively.
conclusionEmpirically-derived thresholds of PA to optimally discriminate between girls with and without CVD risk were lower in this sample than generally recommended. This ROC approach should be repeated in other populations to determine optimal PA thresholds with clinical validity for research, surveillance and program evaluation.
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