AGREEMENT OF STEP-BASED METRICS FROM ACTIGRAPH AND ACTIVPAL ACCELEROMETERS WORN CONCURRENTLY AMONG ADULTS 18-65

BACKGROUND: Counting steps is a simple way to assess physical activity (PA) that is easily understood by the public at large. Current technology allows steps to be assessed via smartphones, various fitness trackers and wearables. The previous Physical Activity Guidelines Advisory Council recommended a move towards a steps-based PA recommendation. An improved understanding of the agreement for steps-based metrics across multiple devices is an important step towards facilitating such a recommendation. Therefore, the purpose of this study is to compare the steps measured from two research-grade accelerometers: The Actigraph (AG) and Activpal (AP), in a sample of adults. METHODS: Thirteen men (n = 4) and women (n = 9) aged 18 - 65 years (30 ± 15.7 years; BMI = 23.4 ± 5.1) underwent 7 days of PA assessment while wearing an AG and AP. The AG was worn on the right hip and the AP was worn on the right thigh. Paired sample t-tests were conducted to evaluate mean differences in steps per day, sedentary time, as well as peak 1-minute and 30-minute cadence. RESULTS: Mean moderate-to-vigorous intensity PA minutes per day achieved in all subjects measured via AG subjects was 53.0 ± 24.9. Sedentary minutes per day was greater with the AG (923.7 ± 121.8) compared to the AP (499.0 ± 106.4; P \u3c0.001). Total steps per day were less with the AG (9077.0 ± 3171.3) than the AP (10139.2 ± 3068.0, P = 0.007). Peak 1-minute cadence was greater in the AG vs the AP (143.6 ± 23.0 and 136.0 ± 18.0, P = 0.036). Peak 30-minute cadence did not differ between devices (131.2 ± 22.4 and 127.0 ± 15.0 for AG and AP, respectively; P = 0.25). CONCLUSION: Compared to the AG, the AP underestimated sedentary time and overestimated steps per day, suggesting poor agreement between two research-validated devices. More research is needed across a wide range of populations to further improve the understanding of the agreement between PA assessment devices

COMPARISON OF A.I. DERIVED HEART RATE VARIABILITY TO A PREVIOUSLY VALIDATED HEART RATE VARIABILITY ASSESSMENT

BACKGROUND: Heart rate variability (HRV) has become a useful measure to assess autonomic function and is becoming a common measure provided by devices available to the consumer. One such device utilizes artificial intelligence (A.I.) to analyze and provide HRV data to the owner. Whether this device provides accurate measures of HRV is not clear. Therefore, the purpose of this study is to assess whether the HRV metrics made with the Wellue 24-hour electrocardiography device with A.I. analysis is similar to those from a well-validated method of HRV assessment. METHODS: Eleven individuals [age = 37.2 ± 20.7 yr.; height = 170.3 ± 9.5 cm; weight = 69.7 ± 11.3 kg; BMI = 24.1 ± 4.3] completed a 20-minute, supine resting HRV assessment while wearing both the Wellue and a Polar H10 heart rate monitor around their torso. R-R data measured by the Polar monitor was captured using the Elite HRV application and HRV analysis was performed using Kubios Standard (version 3.5.0) software. To minimize the impact of respiration on HRV, subjects breathed at a standard rate of 12 breaths per minute, utilizing a metronome. RESULTS: The Wellue reported a higher minimum heart rate compared to Kubios (59.3 ± 8.6 vs. 57.2 ± 8.4 for Wellue and Kubios, respectively; P = 0.006), a higher resting standard deviation of N-N intervals (SDNN) (70.2 ± 32.2 vs. 57.6 ± 32.4, P = 0.006), a higher natural log transformed very low-frequency power (VLFLog) (7.03 ± 1.86 vs. 3.78 ± 0.86, P \u3c0.001), and a lower baseline width of the R-R interval histogram (TINN) (32.1 ± 121 vs. 338.1 ± 141.6, P \u3c0.001). There was no difference in the other reported HRV variables between methods. CONCLUSIONS: Results suggest that A.I. derived HRV via the Wellue device showed good agreement to a well-validated method of HRV assessment with some metrics, and divergent findings in other. More research with a greater sample size and across a broad range of individuals is needed to further elucidate the validity of the Wellue device

IMPACT OF PHYSICAL ACTIVITY AND SLEEP QUALITY ON HEART RATE VARIABILITY IN COLLEGE STUDENTS

BACKGROUND: Poor sleep quality links to health issues like obesity and insulin resistance. Heart rate variability (HRV) measures autonomic nervous system imbalance, possibly connecting poor sleep to these problems. Emerging evidence suggests a negative link between physical activity (PA) and HRV. However, past studies mainly used subjective questionnaires, neglecting college students (CS) who often have suboptimal sleep habits. Our study explores sleep quality, PA, and HRV in CS. METHODS: Fifteen highly active CS (7 male, 8 female; age = 20.6 ± 2.0 yr; BMI = 23.9 ± 3.8 kg/m2; body fat = 18.9 ± 7.4%) underwent 7 days of PA and sleep assessment using accelerometry (ActiGraph GT3X). Subjects wore the device on their hip during waking hours and on their non-dominant wrist during sleep. HRV was assessed over 24 hours using a continuous measurement device worn on the chest (Wellue 24-hour ECG recorder). RESULTS: A negative association was found between daily moderate-to-vigorous PA (MVPA) minutes and the low frequency to high frequency ratio (LF:HF Ratio) (r = -0.63, P = 0.015). Those with a higher LF:HF Ratio spent less time in MVPA (4.6% ± 0.7) compared to those with a lower LF:HF Ratio (7.5% ± 3.0, P = 0.03), and accumulated fewer average MVPA minutes per hour (2.6 ± 0.4 vs. 4.1 ± 1.7, p = 0.04). Unexpectedly, sleep efficiency (r = -0.68, P = 0.008) and average awakenings per night (r = 0.81, P = 0.001) were associated with a higher root mean square of successive RR intervals (RMSSD). CONCLUSIONS: The LF:HF ratio reflects autonomic nervous system balance, with a higher ratio indicating greater imbalance. Results suggest that less daily MVPA is associated with more significant autonomic imbalance. The connection between sleep and RMSSD remains unclear, but low sleep efficiency and frequent awakenings may hinder achieving rapid-eye-movement sleep, increasing sympathetic activity and reducing HRV

OBJECTIVELY MEASURED PHYSICAL ACTIVITY DIFFERENCES IN YOUNGER VS OLDER COLLEGE STUDENTS

BACKGROUND: Surprisingly little research exists examining the objective physical activity (PA) of college students. Previous research from our laboratory found daily step averages of approximately 8800 steps per day while averaging 60 minutes of moderate-to-vigorous intensity physical activity (MVPA) per day in a sample that consisted of all levels of college students. Yet to be examined is whether there is a difference in these values depending on time spent on campus of a residential university. Therefore, the purpose of this study was to examine the difference in PA between newer college students and those who are older and have more experience at a residential university setting. METHODS: Male (n = 46) and female (n = 91) college students (age = 20.3 ± 1.7; BMI = 24.5 ± 4.5) underwent 7-day objective PA assessment via ActiGraph accelerometer. Independent sample t-tests were used to assess mean differences in PA between students less than 20 years of age and those 20 years and older. RESULTS: Students 20+ years (n = 90) took fewer steps per day (8648.1 ± 2739.1 vs. 10897.0 ± 3764.8, P \u3c0.001), and accumulated fewer minutes of MVPA per day (56.1 ± 22.5 vs. 80.2 ± 33.3, P\u3c0.001) than students less than 20 years (n = 47). There was no difference in the number of sedentary minutes accumulated per day (773.8 ± 165.1 and 782.6 ± 156.1 for older and younger respectively; P = 0.7) or light intensity PA minutes (237.3 ± 66.7 and 248.5 ± 66.6; P = 0.35). Body weight or BMI did not differ between groups. CONCLUSION: Our findings indicate a substantial divergence in daily step count and MVPA between older and younger college students. Although the precise determinants of this gap remain elusive, our findings suggest that housing arrangements may play a pivotal role. Older college students tend to reside off-campus and depend more on motor vehicles for commuting to campus, while their younger counterparts predominantly live on-campus, resulting in increased PA through active commuting between dormitories, classes, dining facilities and other campus activities