Facilitating ambulatory heart rate variability analysis using accelerometry-based classifications of body position and self-reported sleep.

Objective.This study aimed to examine differences in heart rate variability (HRV) across accelerometer-derived position, self-reported sleep, and different summary measures (sleep, 24 h HRV) in free-living settings using open-source methodology.Approach.HRV is a biomarker of autonomic activity. As it is strongly affected by factors such as physical behaviour, stress, and sleep, ambulatory HRV analysis is challenging. Beat-to-beat heart rate (HR) and accelerometry data were collected using single-lead electrocardiography and trunk- and thigh-worn accelerometers among 160 adults participating in the SCREENS trial. HR files were processed and analysed in the RHRV R package. Start time and duration spent in physical behaviours were extracted, and time and frequency analysis for each episode was performed. Differences in HRV estimates across activities were compared using linear mixed models adjusted for age and sex with subject ID as random effect. Next, repeated-measures Bland-Altman analysis was used to compare 24 h RMSSD estimates to HRV during self-reported sleep. Sensitivity analyses evaluated the accuracy of the methodology, and the approach of employing accelerometer-determined episodes to examine activity-independent HRV was described.Main results.HRV was estimated for 31 289 episodes in 160 individuals (53.1% female) at a mean age of 41.4 years. Significant differences in HR and most markers of HRV were found across positions [Mean differences RMSSD: Sitting (Reference) - Standing (-2.63 ms) or Lying (4.53 ms)]. Moreover, ambulatory HRV differed significantly across sleep status, and poor agreement between 24 h estimates compared to sleep HRV was detected. Sensitivity analyses confirmed that removing the first and last 30 s of accelerometry-determined HR episodes was an accurate strategy to account for orthostatic effects.Significance.Ambulatory HRV differed significantly across accelerometry-assigned positions and sleep. The proposed approach for free-living HRV analysis may be an effective strategy to remove confounding by physical activity when the aim is to monitor general autonomic stress.

Who Reaches the NHL? A 20-Year Retrospective Analysis of Junior and Adult Ice Hockey Success in Relation to Biological Maturation in Male Swedish Players.

OBJECTIVES: This study investigated the relationship between biological maturation and success in adolescence and adulthood in male Swedish ice hockey players. METHODS: Anthropometric records of players in certified ice hockey high schools between 1998 and 2017 were retrieved (n = 4787). The database was complemented with records of Swedish junior national teams (U16, U18, U20) and National Hockey League (NHL) appearances. Biological maturation was recorded as a percentage of adult height (%AH), and selection probabilities were estimated using a generalised linear mixed effects model. Biological age was determined by comparing players with age-matched growth reference values. Categories of %AH, standard deviation z-scores and biological age offset describing early, on-time and late maturation were created. RESULTS: A total of 217 players had played on the U16 national team (junior success), and 96 reached the NHL (adult success). The difference [95% confidence interval (CI)] in baseline %AH between players with junior versus adult success was - 0.75 (- 0.39, - 1.11). Looking at age-offset categories in junior success, 30% of players were early maturing and 19% of players were late maturing, showing a bias towards early maturation (p < 0.01). In contrast, more late-maturing players (40%) achieved adult success than early-maturing players (25%), and NHL players had significantly later maturation [%AH: - 0.48 (- 0.80, - 0.16)] than non-NHL players. CONCLUSION: This unique 20-year analysis shows that junior success in male ice hockey is positively related to early maturation, while adult success is inversely related to advanced maturation. Ice hockey organisations should implement maturation assessments to optimise the development of both late- and early-matured players.

Recreational screen time trajectories during early childhood and imaging-measured body composition at age 7 in the Odense child cohort.

BACKGROUND: Children spend increasing amounts of time on recreational screen media, which may lead to an obesogenic environment. OBJECTIVES: We investigated the association of trajectories of screen time across ages 3, 5 and 7 years with body composition at age 7 in the Odense Child Cohort. METHODS: Data were collected in the Municipality of Odense, Denmark, between 2010 and 2019. Group-based trajectory modelling was applied to group participants into four trajectories of prospective parent-reported screen time. Body composition was assessed using dual-energy x-ray absorptiometry with calculated fat-mass index (FMI) as the primary outcome. Primary models were linear multivariable regression models adjusted for participants' sex, age, birthweight, maternal origin, maternal education, maternal body-mass-index, and maternal age. Further models were adjusted for additional possible confounders. Selection bias was addressed by inverse probability weighting. RESULTS: In total, 803 children (48.2% female) were included in the primary analysis. Participants with screen time at all time points were assigned to four trajectory groups [constant low screen time (12.7%), low increase (36.3%), high increase between ages 3 and 5 (33.5%) and high increase in screen time (17.5%)]. Sample characteristics differed across missing data status and trajectories. Mean FMI (kg/m2 ) and standard deviation (SD) were 3.7 (SD 1.3) and 3.9 (SD 1.6) for the constant low versus high screen time, respectively. No differences in FMI were found between screen time trajectory groups at age 7 (adjusted mean difference 0.1 kg/m2 , 95% confidence interval -0.3, 0.5 for constant low versus high screen time). No consistent associations between screen time groups and secondary body composition outcomes were found. CONCLUSIONS: Results from this study do not suggest that recreational screen time from age 3 to 7 years is associated with adiposity or other measures of body composition.

Physical Activity and Risk of Major Diabetes-Related Complications in Individuals With Diabetes: A Systematic Review and Meta-Analysis of Observational Studies.

BACKGROUND: Physical activity is a cornerstone in diabetes management; however, evidence synthesis on the association between physical activity and long-term diabetes-related complications is scarce. PURPOSE: To summarize and evaluate findings on physical activity and diabetes-related complications, we conducted a systematic review and meta-analysis. DATA SOURCES: We searched PubMed, Web of Science, and the Cochrane Library for articles published up to 6 July 2021. STUDY SELECTION: We included prospective studies investigating the association between physical activity and incidence of and mortality from diabetes-related complications, i.e., cardiovascular disease (CVD), coronary heart disease, cerebrovascular events, heart failure, major adverse cardiovascular events, and microvascular complications such as retinopathy and nephropathy, in individuals with diabetes. DATA EXTRACTION: Study characteristics and risk ratios with 95% CIs were extracted. Random-effects meta-analyses were performed, and the certainty of evidence and risk of bias were evaluated with use of the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) and Risk Of Bias In Non-randomised Studies - of Interventions (ROBINS-I) tools. DATA SYNTHESIS: Overall, 31 studies were included. There was moderate certainty of evidence that high versus low levels of physical activity were inversely associated with CVD incidence, CVD mortality (summary risk ratio 0.84 [95% CI 0.77, 0.92], n = 7, and 0.62 [0.55, 0.69], n = 11), and microvascular complications (0.76 [0.67, 0.86], n = 8). Dose-response meta-analyses showed that physical activity was associated with lower risk of diabetes-related complications even at lower levels. For other outcomes, similar associations were observed but certainty of evidence was low or very low. LIMITATIONS: Limitations include residual confounding and misclassification of exposure. CONCLUSIONS: Physical activity, even below recommended amounts, was associated with reduced incidence of diabetes-related complications.