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Physical Activity Measurement in Children Accepting Table Tennis Training

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Published on: July 27, 2022

Defining accelerometer thresholds for physical activity in girls using ROC analysis.

Sofiya Alhassan¹, Thomas N Robinson

¹Department of Kinesiology, University of Massachusetts, Amherst, MA, USA.

Journal of Physical Activity & Health

|March 17, 2010

Summary

This summary is machine-generated.

Optimal accelerometer-measured physical activity (PA) thresholds for predicting cardiovascular disease (CVD) risk factors in girls were identified using ROC analysis. These thresholds were lower than generally recommended, suggesting a need for re-evaluation in diverse populations.

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Area of Science:

Pediatric Health
Cardiovascular Disease Research
Physical Activity Measurement

Background:

Receiver operating characteristic (ROC) analysis is a standard method for determining optimal thresholds in diagnostic and screening tests.
Identifying accurate physical activity (PA) thresholds is crucial for predicting cardiovascular disease (CVD) risk factors in pediatric populations.

Purpose of the Study:

To apply ROC analysis to establish optimal accelerometer-derived PA thresholds for predicting specific CVD risk factors in girls.
To compare these empirically derived PA thresholds with existing general recommendations.

Main Methods:

Utilized data from the Stanford Girls Health Enrichment Multisite Studies trial.
Assessed PA using accelerometers over multiple days.
Applied ROC analysis to identify thresholds for overweight, hyperinsulinemia, and multiple CVD risk factor clustering.

Main Results:

Optimal thresholds for discriminating overweight girls were >= 11.1 min/day at >= 2,600 counts/min.
Thresholds for hyperinsulinemia or >= 2 CVD risk factors were >= 16.6 min/day at >= 2,000 counts/min.
Area Under the Curve (AUC) values ranged from 0.58 to 0.66, with associated sensitivities and specificities reported.

Conclusions:

Empirically derived PA thresholds for CVD risk prediction in this cohort were lower than current general guidelines.
The study highlights the utility of ROC analysis for defining clinically relevant PA thresholds.
Further validation in diverse populations is recommended for research, surveillance, and program evaluation.