Biological and psychological predictors of heart rate patterns during physical activity. (March 2023)

• Record Type: Journal Article
• Authors: Kaplan, Deanna M.; Palitsky, Roman; Dunsiger, Shira I.; Wu, Wen-Chih; Parker, Amira G.; Troubh, Jessica K.; Whitworth, James.W.; Bock, Beth C.
• Is Part Of: Psychology of sport and exercise. Volume 65(2023)
• Publication Date: 2023-03
• Subjects: Physical activity -- Latent class modeling -- Heart rate -- Exercise; PA Physical Activity -- LCM Latent Class Modeling -- HR Heart Rate; Sports -- Psychological aspects -- Periodicals; Exercise -- Psychological aspects -- Periodicals; Psychology -- Periodicals; Sports -- Periodicals; Exercise -- Periodicals; Societies, Medical -- Periodicals; Psychology; Sports; Exercise; Societies, Medical; Sports -- Aspect psychologique -- Périodiques; Exercice -- Aspect psychologique -- Périodiques; 613.71019
• DOI: 10.1016/j.psychsport.2022.102346
• Languages: English
• ISSNs: 1469-0292

Abstract

Abstract: Objective: Latent class modeling (LCM) offers a promising approach for examining correlates of heart rate (HR) patterns over multiple exercise sessions. This research examined biological and psychological variables associated with different patterns of HR response to physical activity (PA). Methods: In a three-arm randomized controlled trial (exercise video games vs. standard exercise vs. non-exercise control), HR was recorded during PA sessions over a 12-week period. LCM identified three patterns of HR during PA across 189 participants in active arms: 1) high HR across sessions with low variability within sessions, 2) linear increase in HR across sessions with low variability within sessions, and 3) high variability in HR across all sessions. Associations with biological (resting heart rate, blood pressure, BMI, age, cholesterol, triglycerides, HbA1c) and psychological (depression, motivations for PA, PA-induced feelings) predictors of latent class membership were iteratively tested. Results: Psychological variables played as important a role in the final model as biological variables for predicting latent class membership. Few differences were found between LC1 and LC2, but LC3 differed from the other two groups in that participants were likelier to report that they feel revitalized after PA (vs. LC1 and LC2), to be less motivated for PA (vs. LC1), reported greater depression (vs. LC1 and LC2), and were younger (vs. LC1). Conclusions: These findings demonstrate the potential of LCM to identify biological and psychological factors associated with chronotropic responses to PA, and advance understanding of the role of psychological factors in chronotropic PA outcomes. Highlights: Latent class modeling found three patterns in heart rate during an exercise trial. Baseline psychological variables were key predictors of these patterns. Psychological covariates may be important to patterns of heart rate during exercise. Results have implications for wearable fitness trackers.