Purpose: The aim of this study was to assess the interaction of kinematic, kinetic, and energetic variables as speed predictors in adolescent swimmers in the front-crawl stroke. Design: Ten boys (mean age [SD] = 16.4 [0.7] y) and 13 girls (mean age [SD] = 14.9 [0.9] y) were assessed. Methods: The swimming performance indicator was a 25-m sprint. A set of kinematic, kinetic (hydrodynamic and propulsion), and energetic variables was established as a key predictor of swimming performance. Multilevel software was used to model the maximum swimming speed. Results: The final model identified time (estimate = −0.008, P = .044), stroke frequency (estimate = 0.718, P < .001), active drag coefficient (estimate = −0.330, P = .004), lactate concentration (estimate = 0.019, P < .001), and critical speed (estimate = −0.150, P = .035) as significant predictors. Therefore, the interaction of kinematic, hydrodynamic, and energetic variables seems to be the main predictor of speed in adolescent swimmers. Conclusions: Coaches and practitioners should be aware that improvements in isolated variables may not translate into faster swimming speed. A multilevel evaluation may be required for a more effective assessment of the prediction of swimming speed based on several key variables rather than a single analysis.
Jorge E. Morais, Tiago M. Barbosa, José A. Bragada, Rodrigo Ramirez-Campillo, and Daniel A. Marinho
Tao Chen, Sanmei Chen, Takanori Honda, Yu Nofuji, Hiro Kishimoto, and Kenji Narazaki
Background: To examine longitudinal changes in accelerometer-measured moderate to vigorous physical activity (MVPA) and associated factors of changes in MVPA among community-dwelling older Japanese men and women over 2 years of follow-up. Methods: In total, 601 participants (72.2 [5.4] y, 40.6% men) were included. MVPA was assessed at baseline (2011) and follow-up (2013) using triaxial accelerometers. Sex-stratified multiple linear regression models were used to identify associated factors of changes in MVPA. Results: On average, a significant decrease in MVPA over 2 years was observed only in women (P < .001). Higher baseline MVPA levels and older age were significantly associated with a decrease in MVPA over 2 years in both men and women. Men who were currently drinking (vs no) and had faster maximum gait speed showed statistically significant increases in MVPA. Women who had very poor/poor economic status (vs fair/good) and were socially isolated (vs no) showed statistically significant increases in MVPA over 2 years, while those who had fear of falling (vs no) and poor/fair self-rated health (vs good/very good) showed statistically significant decreases in MVPA over 2 years. Conclusions: Our findings showed different associated factors of changes in MVPA by sex, suggesting the importance of accounting for sex differences in terms of developing specific intervention strategies for promoting MVPA among older men and women.
Mary Njeri Wanjau, Holger Möller, Fiona Haigh, Andrew Milat, Rema Hayek, Peta Lucas, and J. Lennert Veerman
Objective: The objectives were (1) to establish the strength of the association between incident cases of osteoarthritis (OA) and low back pain (LBP), and physical activity (PA) and to assess the likelihood of the associations being causal; and (2) to quantify the impact of PA on the burden of OA and LBP in Australia. Methods: We conducted a systematic literature review in EMBASE and PubMed databases from January 01, 2000, to April 28, 2020. We used the Bradford Hill viewpoints to assess causality. We used a proportional multistate life table model to estimate the impact of changes in the PA levels on OA and LBP burdens for the 2019 Australian population (aged ≥ 20 y) over their remaining lifetime. Results: We found that both OA and LBP are possibly causally related to physical inactivity. Assuming causality, our model projected that if the 2025 World Health Organization global target for PA was met, the burden in 25 years’ time could be reduced by 70,000 prevalent cases of OA and over 11,000 cases of LBP. Over the lifetime of the current adult population of Australia, the gains could add up to approximately 672,814 health-adjusted life years (HALYs) for OA (ie, 27 HALYs per 1000 persons) and 114,042 HALYs for LBP (ie, 5 HALYs per 1000 persons). The HALY gains would be 1.4 times bigger if the 2030 World Health Organization global target for PA was achieved and 11 times bigger if all Australians adhered to the Australian PA guidelines. Conclusion: This study provides empirical support for the adoption of PA in strategies for the prevention of OA and back pain.
Jingzhi Yu, Kristopher Kapphahn, Hyatt Moore, Farish Haydel, Thomas Robinson, and Manisha Desai
Background: Clustering, a class of unsupervised machine learning methods, has been applied to physical activity data recorded by accelerometers to discover unique patterns of physical activity and health outcomes. The prediction strength metric provides a criterion to determine the optimal number of clusters for clustering methods. The aim of this study is to provide specific guidance for applying prediction strength to time series accelerometer data. Methods: For this purpose, we designed an extensive simulation study. We created a synthetic data set of accelerometer data using data from a childhood obesity management trial. We evaluated the role of a prespecified threshold of the prediction strength metric as a key input parameter. We compared the recommended threshold (between 0.8 and 0.9) with an approach we developed (Local Maxima). Results: The choice of threshold had a large impact on performance. When the noise level increased (greater overlap between true clusters), lower thresholds outperformed the recommended threshold, which tended to underestimate the true number of clusters. In addition, we found that sorting the data by magnitude of intensity in windows within the time series of interest prior to clustering alleviated sensitivity to threshold choice. Furthermore, for accelerometer data, we recommend that the Local Maxima approach be utilized together with a graphical evaluation of the prediction strength metric function over values of k. Finally, we strongly suggest sorting of the data prior to clustering if sorting retains meaning for the research question at hand. Conclusion: Our recommendations can help future researchers discover more robust patterns from accelerometer data.
Alannah K.A. McKay, Megan L.R. Ross, Nicolin Tee, Avish P. Sharma, Jill J. Leckey, and Louise M. Burke
Purpose: To examine the effects of a high-carbohydrate diet (HCHO), periodized-carbohydrate (CHO) diet (PCHO), and ketogenic low-CHO high-fat diet (LCHF) on training capacity. Methods: Elite male racewalkers completed 3 weeks of periodic training while adhering to their dietary intervention. Twenty-nine data sets were collected from 21 athletes. Each week, 6 mandatory training sessions were completed, with additional sessions performed at the athlete’s discretion. Mandatory sessions included an interval session (10 × 1-km efforts on a 6-min cycle), tempo session (14 km with a 450-m elevation gain), 2 long walks (25–40 km), and 2 easy walks (8–12 km) where “sleep-low” and “train-low” dietary strategies were employed for PCHO. Racewalking speed, heart rate, rating of perceived exhaustion, and blood metabolites were collected around key sessions. Results: LCHF covered less total distance than HCHO and PCHO (P < .001); however, no differences in training load between groups were evident (P = .285). During the interval sessions, walking speed was slower in LCHF (P = .001), equating to a 2.8% and 5.6% faster speed in HCHO and PCHO, respectively. LCHF was also 3.2% slower in completing the tempo session than HCHO and PCHO (P = .001). Heart rate was higher (P = .002) and lactate concentrations were lower (P < .001) in LCHF compared to other groups, despite slower walking speeds during the interval session. No between-groups differences in rating of perceived exhaustion were evident (P = .077). Conclusion: Athletes adhering to an LCHF diet showed impaired training capacity relative to their high-CHO-supported counterparts, completing lower training volumes at slower speeds, with higher heart rates.
Sally Paulson, Joshua L. Gills, Anthony Campitelli, Megan D. Jones, Joohee I. Sanders, Jordan M. Glenn, Erica N. Madero, Jennifer L. Vincenzo, Christopher S. Walter, and Michelle Gray
Prior work, primarily focusing on habitual gait velocity, has demonstrated a cost while walking when coupled with a cognitive task. The cost of dual-task walking is exacerbated with age and complexity of the cognitive or motor task. However, few studies have examined the dual-task cost associated with maximal gait velocity. Thus, this cross-sectional study examined age-related changes in dual-task (serial subtraction) walking at two velocities. Participants were classified by age: young-old (45–64 years), middle-old (65–79 years), and oldest-old (≥80 years). They completed single- and dual-task walking trials for each velocity: habitual (N = 217) and maximal (N = 194). While no significant Group × Condition interactions existed for habitual or maximal gait velocities, the main effects for both condition and age groups were significant (p < .01). Maximal dual-task cost (p = .01) was significantly greater in the oldest-old group. With age, both dual-task velocities decreased. Maximal dual-task cost was greatest for the oldest-old group.
Mohsen Shafizadeh, Stuart Bonner, Jonathan Fraser, Shahab Parvinpour, Mohsen Shabani, and Andrew Barnes
The aim of this study was to compare the interlimb coordination, asymmetry, and variability between older adults who participated in sports (n = 25; age = 72.6 ± 6.46 years) and sedentary older adults (n = 20; age = 70.85 ± 3.82 years). The sport participants were selected from tennis and badminton clubs, whereas the sedentary participants were recruited from local community centers. The participants walked at their preferred speed in a 10-m walkway for 2 min. The interlimb coordination was measured by the phase coordination index. Other walking metrics were speed, cadence, swing time, stance time, double-support time, stride time, and swing time asymmetry. The results showed that the sport participants relative to the sedentary group had better interlimb coordination, higher walking speed and cadence, and less swing time variability. Young older adults also had a better interlimb coordination. In conclusion, the findings of this study showed that long-term participation in sports has some antiaging benefits on gait coordination and symmetry in older adults.
Amy Cox and Ryan E. Rhodes
The onset of retirement and children leaving the family home may offer a “window of opportunity” for individuals to influence regular moderate- to vigorous-intensity physical activity; therefore, this study examines the feasibility of a moderate- to vigorous-intensity physical activity intervention among recently retired participants (RET) and parents (P) with children who recently left the family home. A total of 46 inactive RET and nine inactive P were randomized to a 10-week web intervention (n = RET = 25/P = 4) or waitlist control (n = RET = 21/P = 5). Intervention techniques followed the multiprocess action control framework. Enrollment (37.5% for P; 40% for RET), retention (89% for P; 83% for RET), and satisfaction were high. One hundred percent of intervention-sectioned participation increased moderate- to vigorous-intensity physical activity compared with 52% of controls; large effect size differences were observed for key multiprocess action control constructs. Participants were highly satisfied with the intervention; however, recruitment challenges of P support moving to a randomized controlled trial for only the RET group.
Marcos Rescarolli, Francisco Timbó de Paiva Neto, Adalberto Aparecido dos Santos Lopes, Marcelo Dutra Della Justina, Anna Quialheiro Abreu da Silva, Eleonora d’Orsi, and Cassiano Ricardo Rech
This study aimed to examine the relationship between Walk Score index with walking to commuting, moderate-to-vigorous physical activity, and screen time in older adults. Georeferenced addresses were entered into the Walk Score platform. Walking to commute and moderate-to-vigorous physical activity were assessed using the International Physical Activity Questionnaire and categorized according to the World Health Organization recommendations. Screen time was analyzed through self-reported time watching television/being on the computer. We used binary logistic regression to estimate the association between variables. Older adults who lived in places with higher Walk Score had a higher prevalence of walking to commuting (odds ratio = 1.73; 95% confidence interval [1.18, 2.55]) and engaging in moderate-to-vigorous physical activity (odds ratio = 1.76; 95% confidence interval [1.05, 2.98]). A relationship also was observed between higher Walk Score and more time in screen time (odds ratio = 1.67; 95% confidence interval [1.19, 2.34]). The results showed that residing in a more walkable neighborhood increased the chances of the older adults spending 3 hr or more in front of a screen.