Myles W. O’Brien, William R. Wojcik, and Jonathon R. Fowles
Wearable physical activity monitors are associated with an increase in user’s habitual physical activity levels. Most of the older adult population do not meet the national moderate- to vigorous-intensity physical activity (MVPA) recommendations and may benefit from being prescribed a physical activity monitor. The PiezoRx is a class one medical grade device that uses step rate thresholds to measure MVPA. The validity and reliability of the PiezoRx in measuring MVPA has yet to be determined in older persons. We assessed the validity and interinstrument reliability of the PiezoRx to measure steps and MVPA in older adults. Participants (n = 19; 68.8 ± 2.3 years) wore an Omron HJ-320 pedometer, ActiGraph GT3X accelerometer, and four PiezoRx monitors during a five-stage treadmill walking protocol. The PiezoRx devices were set at moderate physical activity and vigorous physical activity step rate thresholds (steps per minute) of 100/120, 110/130, adjusted for height and adjusted for height + fitness. The PiezoRx exhibited a stronger correlation (intraclass correlation coefficient = .82) with manually counted steps than the ActiGraph (intraclass correlation coefficient = .53) and Omron (intraclass correlation coefficient = .54) and had a low absolute percentage error (3 ± 6%). The PiezoRx with moderate physical activity/vigorous physical activity step thresholds adjusted to 110/130 was strongly correlated to indirect calorimetry (0.84, p < .001) and best distinguished each walking stage as MVPA or not (sensitivity: 88%; specificity: 95%). The PiezoRx monitor is a valid and reliable measure of step count and MVPA among older adults. The device’s ability to measure MVPA in absolute terms was improved when step rate thresholds for moderate physical activity/vigorous physical activity were increased to 110/130 steps per minute in this population.
Andrea Ramírez Varela and Michael Pratt
In 2012, the Global Observatory for Physical Activity (GoPA!) was established to provide information that would enable countries to initiate or improve research capacity, surveillance systems, program development, and policymaking to increase physical activity levels. Findings from the first GoPA! Country Cards showed an unequal distribution of physical activity surveillance, research productivity, and policy development and implementation around the world. Regular global monitoring of these factors, especially in countries with the largest data gaps, was recommended to combat the global pandemic of physical inactivity. After 6 years and using standardized methods, GoPA! is launching the second set of Country Cards based on data up to 2019 from 217 countries. Overall results showed that periodic national surveillance of physical activity was less common in low-income countries, compared with middle- and high-income countries. Large inequities were seen with more than a 50-fold difference in publications between high- and low-income countries and 32% of the countries worldwide had no physical activity policy. GoPA! has a critical role in facilitating evidence-based physical activity promotion building on international guidelines and the World Health Organization Global Action Plan. GoPA! will continue to monitor progress as we battle the global pandemic of physical inactivity.
Ja’mese V. Booth, Sarah E. Messiah, Eric Hansen, Maria I. Nardi, Emily Hawver, Hersila H. Patel, Hannah Kling, Deidre Okeke, and Emily M. D’Agostino
Background: Only 24% of US youth meet physical activity recommendations set by the Centers for Disease Control and Prevention. Research demonstrates that community-based programs provide underresourced minority youth with opportunities for routine physical activity, although limited work draws from accelerometry data. This study objectively assessed youth physical activity attributable to participation (vs nonparticipation) days in a park-based afterschool program in Miami-Dade County, Miami, FL. Methods: Participants’ (n = 66; 60% male; 57% white Hispanic, 25% non-Hispanic black, 14% Black Hispanic, mean age = 10.2 y) physical activity was assessed April to May 2019 over 10 days across 7 park sites using Fitbit (Charge 2) devices. Separate repeated-measures multilevel models were developed to assess the relationship between program daily attendance and total (1) moderate to vigorous physical activity minutes and (2) step counts per day. Results: Models adjusted for individual-level age, sex, race/ethnicity, poverty, and clustering by park showed significantly higher moderate to vigorous physical activity minutes (β = 25.33 more minutes per day; 95% confidence interval, 7.0 to 43.7, P < .01) and step counts (β = 4067.8 more steps per day; 95% confidence interval, 3171.8 to 4963.8, P < .001) on days when youth did versus did not attend the program. Conclusions: Study findings suggest that park-based programs may support underserved youth in achieving daily physical activity recommendations.
Bethany Barone Gibbs, Melissa A. Jones, John M. Jakicic, Arun Jeyabalan, Kara M. Whitaker, and Janet M. Catov
Background: Though moderate- to vigorous-intensity physical activity is recommended, limited research exists on sedentary behavior (SED) during pregnancy. Methods: The authors conducted a prospective cohort study to describe objectively measured patterns of SED and activity during each trimester of pregnancy. Women wore thigh- (activPAL3) and waist-mounted (ActiGraph GT3X) activity monitors. SED and activity were compared across trimesters using likelihood ratio tests and described using group-based trajectories. Exploratory analyses associated SED and activity trajectories with adverse pregnancy outcomes and excessive gestational weight gain. Results: Pregnant women (n = 105; mean [SD] age = 31  y; prepregnancy body mass index = 26.2 [6.6] kg/m2) had mean SED of 9.7, 9.5, and 9.5 hours per day (P = .062) across trimesters, respectively. Some activities differed across trimesters: standing (increased, P = .01), stepping (highest in second trimester, P = .04), steps per day (highest in second trimester, P = .008), and moderate- to vigorous-intensity physical activity (decreased, P < .001). Prolonged SED (bouts ≥ 30 min) and bouted moderate- to vigorous-intensity physical activity (≥10 min) were stable (P > .05). In exploratory analyses, higher SED and lower standing, stepping, and steps per day trajectories were associated with increased odds of adverse pregnancy outcomes (P < .05). No trajectories were associated with excessive gestational weight gain. Conclusions: Pregnant women exhibited stable SED of nearly 10 hours per day across pregnancy. Future research evaluating SED across pregnancy and adverse pregnancy outcome risk is warranted.
Shikha Prashad, Yue Du, and Jane E. Clark
Current methods to understand implicit motor sequence learning inadequately assess motor skill acquisition in daily life. Using fixed sequences in the serial reaction time task is not ideal as participants may become aware of the sequence, thereby changing the learning from implicit to explicit. Probabilistic sequences, in which stimuli are linked by statistical, rather than deterministic, associations can ensure that learning remains implicit. Additionally, the processes underlying the learning of motor sequences may differ based on sequence structure. Here, the authors compared the learning of fixed and probabilistic sequences to randomly ordered stimuli using a modified serial reaction time task. Both the fixed and probabilistic sequence groups exhibited learning as indicated by decreased response time and variability. In the initial stage of learning, fixed sequences exhibited both online and offline gains in response time; however, only the offline gain was observed during the learning of probabilistic sequences. These results indicated that probabilistic structures may be learned differently from fixed structures and have important implications for our current understanding of motor learning. Probabilistic sequences more accurately reflect motor skill acquisition in daily life, offer ecological validity to the serial reaction time framework, and advance our understanding of motor learning.