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Relationship Between Parent and Child Physical Activity Using Novel Acceleration Metrics.

Samantha DonnellyDuncan S BuchanGillian McLellanRosemary Arthur
Published in: Research quarterly for exercise and sport (2020)
Background: Raw acceleration data lend themselves to innovative metrics in which comparisons can be made across populations. This study examined whether the intensity gradient (IG) or average acceleration (AvAcc) was associated with body mass index (BMI) in children and adults and explored parent-child associations between time spent in physical activity intensities and BMI. Methods: Parent-child dyads (n = 90) wore a wrist-mounted ActiGraph GT3X+ monitor for ≥ 3 valid days (i.e., ≥ 16 hrs each day). Participants' BMI was calculated. Results: Girls' BMI-z scores were positively associated with parent BMI and inactive time. Parent BMI was negatively associated with boys' inactive time. Parental inactive time predicted girls' BMI-z scores. The metrics were not associated with parent BMI, and no independent effects were observed between the metrics. Associations between boys' IG and BMI z-score were observed. No independent effects were observed between the metrics and no significant associations were observed between boys' BMI z-score and AvAcc. Girls' AvAcc and IG were not associated with BMI z-score and no independent effects were observed between the metrics. Conclusion: Findings support previous research which suggests that parent's activity does not influence their child's activity.
Keyphrases
  • body mass index
  • weight gain
  • physical activity
  • mental health
  • young adults
  • machine learning
  • depressive symptoms
  • deep learning
  • artificial intelligence
  • high intensity