Does Examination Table Paper Use Mitigate the Risk of Disease Transmission in a Family Medicine Clinic?

Reducing examination table paper (ETP) use may help curb carbon emissions from health care. Six participants applied Glo Germ (DMA International) to their hands before a common physical examination (abdominal, cardiorespiratory, hip and knee) both with and without ETP. After each exam, UV light was shined on the exam table and photographs were taken. The number of hand touches on ETP-covered areas and uncovered areas were tallied and compared using t tests. Despite covering more surface area, participants touched areas without ETP significantly more than ETP-covered areas (P <.05). Despite its continued use, patients do not have much hand contact with ETP during common clinical examinations.

Trajectories of cardiorespiratory fitness from childhood to adolescence: Findings from the QUALITY cohort.

Estimate the shape and number of cardiorespiratory fitness (CRF) trajectories from childhood to adolescence; and verify whether CRF trajectory membership can be predicted by sex, biological maturation, body weight, body composition and physical activity (PA) in childhood. Data from QUALITY were used. Participants attended baseline (8-10 y old, n = 630) and follow-ups 2 years (n = 564) and 7 years (n = 359) after baseline. Group-based trajectory analysis for relative peak oxygen consumption (VO2peak, ml·kg-1·min-1) was performed. A multinomial logistic regression model was used to estimate the associations between baseline predictors and trajectory membership. Mean age of the 454 participants was 9.7 ± 0.9 years at baseline. Three distinct VO2peak trajectories were identified and all tended to decrease. They were labelled according to the starting point and slope. High-Decreasers were mostly boys, had lower body weight and fat-free mass index and higher PA levels at baseline (p < 0.05). Female sex and higher weight were associated with higher odds of being classified in the Low-Decreaser trajectory (OR = 74.03, 95%CI = 27.06-202.54; OR = 1.48, 95%CI = 1.36-1.60). Those with higher PA were less likely to be Low-Decreasers (OR = 0.96, 95%CI = 0.94-0.97). Sex, body weight and PA in childhood are important influencing factors of VO2peak (ml·kg-1·min-1) trajectories across adolescence.

Longitudinal Physiological and Fitness Evaluations in Elite Ice Hockey: A Systematic Review.

ABSTRACT: Chiarlitti, NA, Crozier, M, Insogna, JA, Reid, RER, and Delisle-Houde, P. Longitudinal physiological and fitness evaluations in elite ice hockey: A systematic review. J Strength Cond Res 35(10): 2963-2979, 2021-Ice hockey has greatly evolved since the last review article was published more than 25 years ago. Although players still combine anaerobic and aerobic conditioning, the pace of the game has greatly increased. Players are faster, stronger, and more agile than their predecessors; however, an important emphasis is now placed on maximizing player performance for the play-offs. For the coaching staff, strength and conditioning coaches, and players, an emphasis on mitigating fitness and physiologic losses throughout the season would be beneficial, given the intimate relationship they share with on-ice performance. This systematic review of the literature outlines the current knowledge concerning longitudinal changes in relation to fitness, body composition, and physiologic parameters across an elite hockey season. The search of 4 large scientific databases (i.e., Embase, PubMed, SPORTDiscus, and Web of Science) yielded 4,049 items, which, after removing duplicates and applying inclusion and exclusion criteria, resulted in 23 published scientific articles to be included in this review. The wide span of literature (1956-2020) made inferences difficult giving the degree to which the game of ice hockey has changed; however, more recent research points to an aerobic deconditioning pattern and increased fatigue throughout the season in a specific group of elite hockey players (i.e., university athletes) while showing that ice hockey can lead to many possible histological adaptations. Ultimately, tracking, identifying, and developing methods to mitigate potential negative longitudinal changes will be imperative to influencing individual and team performance in the later parts of the season.

Seasonal Changes in Physiological Responses and Body Composition During a Competitive Season in Male and Female Elite Collegiate Ice Hockey Players.

Delisle-Houde, P, Reid, RER, Insogna, JA, Chiarlitti, NA, and Andersen, RE. Seasonal changes in physiological responses and body composition during a competitive season in male and female elite collegiate ice hockey players. J Strength Cond Res 33(8): 2162-2169, 2019-Ice hockey continually overloads athletes with limited time for recovery, which may affect several physiological responses and alter body composition. The purpose of this study was to identify changes in physiological parameters and body composition profiles over the competitive season in elite collegiate ice hockey players. Forty-four players, 24 males (age = 22.7 ± 1.3 years, height = 1.82 ± 0.6 m, and body mass = 86.87 ± 6.44 kg) and 20 females (age = 19.9 ± 1.8 years, height = 1.66 ± 0.7 m, and body mass = 68.76 ± 5.91 kg) participated in 4-minute submaximal exercise tests and body composition assessments at pre-season, mid-season, and end-season. Changes in physiological parameters and body composition were analyzed using repeated-measures analysis of covariance controlling for age. Males' postexercise blood lactate concentration decreased (p ≤ 0.05) from pre- to mid-season (9.3 vs. 6.2 mmol·L) and increased (p ≤ 0.05) from mid- to end-season (6.2 vs. 8.0 mmol·L). Heart rate increased (p ≤ 0.05) after the third and fourth minute of the submaximal test in both sexes from pre- to end-season and from mid- to end-season. Males' body fat percentage decreased (p ≤ 0.05) from mid-season (17.4 vs. 16.1%), whereas increases were observed (p ≤ 0.05) in both sexes from mid- to end-season. This study produced evidence that male and female collegiate hockey athletes' physiological responses and body composition profiles change over the season. Sport scientists working with collegiate hockey teams, may need to revise annual training programs to attenuate reductions in fitness and hopefully prevent injuries.

Comparing DXA and Air Displacement Plethysmography to Assess Body Composition of Male Collegiate Hockey Players.

Delisle-Houde, P, Reid, RER, Insogna, JA, Prokop, NW, Buchan, TA, Fontaine, SL, and Andersen, RE. Comparing DXA and air-displacement-plethysmography to assess body composition of male collegiate hockey players. J Strength Cond Res 33(2): 474-478, 2019-Accurate assessment of body composition is an important consideration for athletes because it is a health/performance variable. However, little is known about the variability in values obtained across different assessment methods for specific athlete populations. The purpose of this study was to compare 2 common laboratory methods that assess body composition: air displacement plethysmography (BOD POD) and dual energy x-ray absorptiometry (DXA). Twenty-nine male collegiate hockey players, (Age = 24.07 ± 1.49, BMI = 26.5 ± 2.74) participated in this study. All participants underwent back-to-back BOD POD and DXA evaluations. Paired t-tests and Bland-Altman analyses were performed to compare differences in fat mass, fat percentage, and fat-free mass between methods. Average fat percentage reported by the DXA and BOD POD was 15.34 ± 3.53 and 11.66 ± 4.82 respectively, resulting in a bias score of 3.78 ± 2.33 kg (t(28) = 8.71, p ≤ 0.001). Average fat mass reported by the DXA and BOD POD was 13.42 ± 3.59 and 10.15 ± 4.54 kg respectively, resulting in a bias score of 3.27 ± 1.92 kg (t(28) = 9.18, p ≤ 0.001). Average fat-free mass reported by the DXA and BOD POD was 73.31 ± 5.30 and 76.25 ± 5.74 kg respectively, resulting in a bias score of -2.93 ± 2.06 kg (t(28) = -7.66, p ≤ 0.001). Our findings can help make more insightful comparisons between studies that use different body composition methodologies among athletic populations.

Longitudinal Changes in Body Composition Throughout Successive Seasonal Phases Among Canadian University Football Players.

Kim, J, Delisle-Houde, P, Reid, RER, and Andersen, RE. Longitudinal changes in body composition throughout successive seasonal phases among Canadian university football players. J Strength Cond Res 32(8): 2284-2293, 2018-The purpose of this study was to assess changes in body composition during seasonal phases of the training year among Canadian Inter-University Sport (CIS) football players. Forty university football players were assessed for anthropometry, total body composition, regional body composition, and central adiposity over a 7-month period including the summer off-season and the in-season. Baseline testing occurred in April, before the summer off-season, and follow-ups were completed before training camp, at the beginning of August, and following the in-season, at the beginning of November. Linemen had the greatest tissue percent fat (25.98 ± 6.56%) at baseline, significantly (p < 0.01) greater than big skill (18.69 ± 3.97%) and followed by skill (14.35 ± 3.39%) who were significantly (p < 0.01) leaner than both other groups. Skill players significantly increased fat mass (0.98 ± 0.30 kg, p ≤ 0.05) and waist-to-hip ratio (0.02 ± 0.01, p ≤ 0.05) during the in-season, and linemen increased visceral fat mass from April to November (0.20 ± 0.06 kg, p ≤ 0.01). All players significantly (-1.26 ± 0.30 kg, p = 0.001) decreased lean mass during the in-season. All groups significantly increased bone mineral content during the summer off-season (p ≤ 0.05). There was also a significant time × summer training location interaction (p ≤ 0.05) for fat mass with athletes who remained on campus during summer months gaining the least amount of adiposity. Body composition and central adiposity seem to change differentially among positional groups across the annual training season.

Relationship Between Physiologic Tests, Body Composition Changes, and On-Ice Playing Time in Canadian Collegiate Hockey Players.

Delisle-Houde, P, Chiarlitti, NA, Reid, RER, and Andersen, RE. Relationship between physiologic tests, body composition changes, and on-ice playing time in canadian collegiate hockey players. J Strength Cond Res 32(5): 1297-1302, 2018-Hockey player's body composition and physical fitness are suggested to influence coaching decisions regarding on-ice playing time. The purpose of this study was to explore the relationship between seasonal body composition changes, off-ice preseason testing, and on-ice metrics. Twenty-one Canadian collegiate hockey players (22.70 ± 1.30 years old, 181.0 ± 5.92 cm, 86.52 ± 6.41 kg) underwent off-ice physical testing at the beginning of their season and had one total body dual energy x-ray absorptiometry scan at the beginning and end of the season. The team's statistician tracked all on-ice metrics. Pearson correlations were used to explore relationships between off-ice tests (long jump, vertical jump, beep test, and Wingate test), change in body composition (body fat percentage, visceral adiposity, and total lean tissue mass), and on-ice performance (average time on ice, average shift length, power play time, penalty kill time, and shot differential). Long jump was correlated with shot differential (r = -0.532, p ≤ 0.05) and average shift length (r = -0.491, p ≤ 0.05) while fatigue index was correlated with average ice time (r = -0.476, p ≤ 0.05). Hockey performance is a complex interaction of player's body compositions and skeletal fitness that interact to affect on-ice playing metrics.

Importance of Body Composition in the National Hockey League Combine Physiological Assessments.

Chiarlitti, NA, Delisle-Houde, P, Reid, RER, Kennedy, C, and Andersen, RE. Importance of body composition in the national hockey league combine physiological assessments. J Strength Cond Res 32(11): 3135-3142, 2018-The National Hockey League (NHL) combine was designed to assess draft-eligible players based on body composition, speed, power, and strength. The importance of body composition in the battery of combine physical tests was investigated, and differences in results based on position were explored. Thirty-seven elite male Canadian university hockey players (age = 22.86 ± 1.55 years, mass = 87.21 ± 6.52 kg, and height = 181.69 ± 6.19 cm) participated in the study at the beginning of their hockey season. All participants underwent physical testing (as outlined in the 2016 NHL combine) and 1 total body dual energy x-ray absorptiometry scan to measure body composition. Partial correlations (controlling for body mass) were used to explore the relationship among body composition measures (body fat percentage, visceral fat, body mass index, lower lean tissue mass, upper lean tissue mass, upper fat mass, and lower fat mass) with NHL fitness tests (bench press, pull-ups, grip strength, long jump, proagility, vertical jump, V[Combining Dot Above]O2max, and the Wingate Anaerobic Test). In 4 of the 6 strength/power tests (Wingate Anaerobic Test, long jump, bench press, and both grip strengths), lower and upper lean tissue mass explained significant amounts of variance. Although forwards and defensemen significantly differed in right grip strength and proagility left scores, they did not differ in regard to any body composition variables. Body composition has a significant influence on several combine-specific tests, which may help sport scientists and strength and conditioning coaches to better tailor training programs and to optimize performance in elite hockey players.

Accuracy of two Generic Prediction Equations and One Population-Specific Equation for Resting Energy Expenditure in Individuals with Spinal Cord Injury.

PURPOSE: The primary aim was to assess the accuracy of common prediction equations, the Harris-Benedict (HB) and the Mifflin St. Jeor (MSJ) equations, for estimating resting energy expenditure (REE) among people with spinal cord injury (SCI) against actual REE measurements. The secondary aim was to cross-validate the Buchholz et al. energy prediction equation created for people with SCI. METHODS: A metabolic cart with canopy was used to measure the actual REE. The HB, MSJ, and the Buchholz et al. equations were used for the prediction of REE. RESULTS: Thirty-nine participants (31 males and 8 females) were enrolled in this cross-sectional study. The REEs significantly differed from one another, F(1.52, 57.68) = 52.04, P < 0.001, where both the HB (M = 1703.06, SD = 265.1) and the MSJ (M = 1628.92, SD = 233.8) energy predictions were significantly higher (P < 0.001) than the measured REE (M = 1394.05, SD = 298.7). In contrast, the Buchholz et al. equation did not differ from the measured REE. CONCLUSIONS: Our data show that the HB and MSJ equations do not accurately predict the energy needs of this community. Using a SCI-specific equation would improve estimates of REE, such as the Buchholz et al. equation. More research into energy equations for this population may help health care professionals better tailor dietary requirements for weight management.

Seasonal Changes in Whole Body and Regional Body Composition Profiles of Elite Collegiate Ice-Hockey Players.

The monitoring of a collegiate hockey player's body composition can reflect fitness characteristics and may help players, coaches, or strength and conditioning specialists optimize physiologic gains during an off-season, whereas simultaneously preventing performance decrements in-season. The purpose of the study was to investigate changes in whole-body and regional-body composition of fat and lean tissue. The body composition profiles of 19 elite Canadian collegiate hockey players were assessed using dual energy X-ray absorptiometry. Players completed end-of-season, preseason, and midseason assessments with questionnaires relating to their off-season and in-season training. Statistically significant changes in body composition profiles were observed between the different time points because players showed various tissue gains and losses depending on the region assessed. Overall, players gained (1.38 kg, p ≤ 0.01) and lost (0.79 kg, p ≤ 0.01) fat tissue during the off-season and in-season, respectively. Players also showed a significant gain of leg lean tissue (0.29 kg, p = 0.02) and loss of arm tissue mass (-0.25 kg, p = 0.02) during the first-half of the competitive season. Several correlations emerged that may provide insight into potential trends that could be more pronounced during longer and more demanding schedules. Collegiate hockey players show changes in body composition during the off-season and in-season. The understanding of body composition profiles, body composition fluctuations, and potential variables that may influence the composition of collegiate hockey players can help coaches and athletic programs tailor their team's training, nutrition, lifestyle, and informative resources to further support their athletes.

Energy Intake and Food Habits between Weight Maintainers and Regainers, Five Years after Roux-en-Y Gastric Bypass.

We explored differences in dietary behaviours, energy, and macronutrient intake among individuals who had regained or maintained weight loss 5 or more years after Roux-en-Y gastric bypass (RYGB). This study assessed 27 adults who underwent RYGB an average of 12.1 ± 3.7 years before this study was conducted. Dietary assessment was performed using 3-day food records. Daily energy intake (kcal), protein (g), carbohydrate (g), fat (g), and alcohol intake (g) were computed using the ESHA's Food Processor®. Participants were classified by percent weight loss, maintainers (≥38 %), and regainers (≤30 %). Daily carbohydrate consumption was greater in regainers (222 ± 84.3 g) compared with maintainers (162 ± 67.5 g), (P < 0.05). Thirty-seven percent of participants were not consuming the recommended amount of protein and 26% reported never taking vitamin supplements after surgery. Alcohol consumption was higher among regainers (18.5 ± 30.9 g) compared with maintainers (2.6 ± 6.5 g), (P < 0.05). Finally, 74% of the participants reported no contact with a Registered Dietitian, whereas 78 % were in contact with a health care professional once a year post-surgery. Differences were seen in carbohydrate intake and alcohol consumption between weight maintainers and regainers. These data suggest dietitians need to play a more active role in the long-term care of this medically complex population.

Active time at work following the introduction of a standing and a cycling workstation into worker's office space.

Objectives. Active workstations have been proposed to counteract sedentary behavior at work. This study describes office workers' use of and perceptions toward standing and cycling workstations, and assesses whether the two active workstations were sufficient to break sitting time and replace it with 2-4 h of light activity per workday. Methods. This mixed-method study utilized video recording, semi-structured interviews and a questionnaire. The quantitative data covered time spent sitting, standing and on a cycling workstation. The qualitative data were analyzed based on preferences, barriers and facilitators. Results. Participants (n = 15) used active workstations 125.3 (74.5) min/day and spent 79.0 (63.6) min/day using standing versus 46.3 (47.6) min/day using cycling workstations (p = 0.153, d = 0.58). Following the interviews, the standing workstation was preferred over cycling. The ergonomics of the cycling workstation were not optimal and caused discomfort in use. Seven participants broke their sitting time and accumulated 2+ h of light physical activity per workday. Those participants meeting recommendations were older, had a higher body fat percentage and engaged in less physical activity per week. Conclusion. With a preference for standing workstations, our results showed that 47% of workers used standing and cycling workstations to accumulate 2+ h of active time per day.

Children and chrono-exercise: Timing of physical activity on school and weekend days depends on sex and obesity status.

Recommendations for physical activity (PA) typically focus on frequency, intensity, duration, and type, but timing (chrono-exercise) is also important. The objective of this study is to describe when children are active on school and weekend days and explore PA timing across sex and body mass index (BMI) categories. 359 children (53% male), aged 9.6 (0.9) y, were categorized as normal weight (≥-1 standard deviations (SD) and <1SD; n = 193), overweight (≥1SD and <2SD; n = 80), or obese (≥2SD; n = 86) using WHO BMIz. Moderate-to-vigorous PA (MVPA) was assessed using ActiGraph LS-7164. The results are described as Mean(SD). ANOVA evaluated MVPA across sexes and BMI categories. Normal weight boys were more active than boys with obesity on school (Δ20.33 min; p < 0.001) and weekend days (Δ15.04 min; p < 0.05). On school days, significant differences existed between 9:00 h-11:00 h and 12:00 h-14:00 h (p < 0.017), while on weekends, smaller differences existed throughout the day. Girls' MVPA was similar across BMI categories, on all days (p > 0.05). On school days, 12:00 h-13:00 h represented the most active hour for all participants (~14% total daily MVPA). Peak weekend MVPA was distributed across multiple hours. Differences in MVPA timing emerged on school-days and weekends. Timing may be important when examining the nuances of MVPA in relation to sex and bodyweight in children.

A single-armed proof-of-concept study of Lymfit: A personalized, virtual exercise intervention to improve health outcomes in lymphoma survivors in the pandemic.

BACKGROUND AND OBJECTIVE: Treatments of lymphoma can lead to reduced physical functioning, cancer-related fatigue, depression, anxiety, and insomnia. These side effects can negatively impact the cancer survivor's quality of life. Mounting evidence indicates that physical activities are highly therapeutic in mitigating the short- and long-term side effects of cancer treatments. Yet, lymphoma survivors' participation in physical activities remains suboptimal, which has been further exacerbated by the deleterious effects of isolation during the COVID-19 pandemic. The Lymfit intervention aims to offer motivational support, expert guidance, and a personalized exercise prescription to optimize physical activities among lymphoma survivors. This proof-of-concept study explores implementation feasibility (retention, technical and safety), and the preliminary effects of Lymfit on various health outcomes. METHOD: This was a single-armed trial with a pre-and post-test design. Twenty lymphoma survivors were recruited to participate in the 12-week Lymfit intervention. Wearable activity trackers (Fitbit) were given to participants as a motivational tool and for data collection purposes. Participants received a personalized exercise prescription designed by a kinesiologist. Physiologic metrics were collected by the Fitbit monitors and were stored in the Lymfit database. Self-reported questionnaires measuring health outcomes were collected at baseline and post-intervention. RESULTS: The retention rate of this trial was 70%. Minimal technical issues and no adverse effects were reported. Lymfit led to significant improvements in sleep disturbances and the ability to participate in social activities and decreased fear of cancer recurrence. It also increased daily steps and decreased sedentary time in participants who did not meet the recommended physical activity guidelines. SIGNIFICANCE: With access to resources and fitness centers being limited during the pandemic, the Lymfit intervention filled an immediate need to provide physical activity guidance to lymphoma survivors. Findings provide preliminary support that implementing the Lymfit intervention is feasible and demonstrated promising results.

Dietary intake of micronutrients are predictor of premenstrual syndrome, a machine learning method.

BACKGROUND & AIMS: Premenstrual syndrome (PMS) is a common disorder affecting 30-40% of women of reproductive age. Many modifiable risk factors associated with PMS involve nutrition and poor eating habits. This study aims to explore the correlation between micronutrients and PMS in a group of Iranian women and to build a predictor model showing the PMS using nutritional and anthropometric variables. METHODS: This is a cross-sectional study which was conducted on 223 females in Iran. Anthropometric indices were measured, including Body Mass Index (BMI) and skinfold thickness. Machine learning methods were used to assess participants' dietary intakes, Food Frequency Questionnaire (FFQ) and analyze the data. RESULTS: After applying different variable selection techniques, we have created machine learning models such as KNN. KNN achieved 80.3% accuracy rate and 76.3% F1 score indicating that our model is a curate and valid proof to show a strong relationship between input variables (sodium intake, Skin fold thickness of suprailiac, irregular menstruation, total calorie intake, total fiber intake, trans fatty acids, painful menstruation (dysmenorrhea), total sugar intake, total fat intake, and biotin) and the output variable (PMS). We sorted these effective variables based on their 'Shapley values' and figured out that Na intake, suprailiac skinfold thickness, biotin intake, total fat intake and total sugar intake have a major impact on having PMS. CONCLUSIONS: Dietary intake and anthropometric measurements are highly associated with the occurrence of PMS, and in our model, these variables can predict PMS in women with a high accuracy rate.

Determinants of mechanical efficiency trajectories from childhood to adolescence: Findings from the QUALITY cohort.

PURPOSE: To estimate the shape and number of mechanical efficiency (ME) trajectories from childhood to adolescence; and verify whether ME trajectory membership can be predicted by sex, biological maturation, body weight, body composition and physical activity (PA) in childhood. METHODS: Data from QUALITY, an ongoing cohort study on the natural history of obesity, were used. Participants attended a baseline visit (8-10 years, n = 630) and follow-up visits two years (n = 564), and seven years (n = 377) later. ME was assessed by an incremental cycling test at 50w (ME50w, %) and at VO2peak (MEVO2peak, %). Group-based trajectory analysis for ME and a logistic regression were performed. RESULTS: Mean age of the 454 participants (boys = 54%) was 9.7 ± 0.9 years at baseline. Two distinct ME50w trajectories were identified and all tended to decrease. No distinct trajectories emerged for MEVO2peak; average MEVO2peak increased over time. Thus, the difference between MEVO2peak (∆) at baseline and follow-up was calculated for correlation analysis. Trajectory groups were labeled "Low-Decreaser" and "High-Decreaser" (Reference) for ME50w, describing the starting point and slope. High-Decreasers were mostly prepubertal girls, had lower body weight and fat free mass index, lower PA and lower VO2peak at baseline (χ2or t-test, p < 0.05). Girls were less likely to be Low-Decreasers (OR = 0.56, 95%CI = 0.42-0.74), while having overweight/obesity predicted a greater likelihood of classification in the Low-Decreaser trajectory (OR = 2.38, 95%CI = 1.16-4.88). Those with higher PA were more likely to be Low-Decreasers (OR = 1.02, 95%CI = 1.01-1.04). Finally, concerning MEVO2peak, sex, biological maturation, body weight, zBMI, fat free mass index, PA and VO2peak were positively correlated with ∆ MEVO2peak. CONCLUSIONS: We found evidence that excess weight at baseline predicts low levels of ME in childhood and adolescence. Additionally, higher PA at baseline is not related to higher ME50w levels. More research is needed to identify different approaches to explore this measure in transition to adulthood.

Physical Activity, Screen Time, and Sleep Trajectories From Childhood to Adolescence: The Influence of Sex and Body Weight Status.

BACKGROUND: Behavioral trajectories from childhood to adolescence may differ and are poorly understood. The authors estimated the trajectories of moderate to vigorous physical activity (MVPA), screen time, and sleep duration during this period, by sex and initial weight status. METHODS: Data from Quebec Adiposity and Lifestyle Investigation in Youth, an ongoing cohort study in Canada on the natural history of obesity, were used. Participants predisposed to obesity attended baseline (8-10 y old, n = 630) and follow-up visits 2 years (n = 564) and 7 years (n = 359) after baseline. Participants with completed self-reported and accelerometer-based data were included in the analyses (n = 191, 353, and 240 for MVPA, screen time, and sleep, respectively). The authors performed group-based trajectory analyses and multinomial logistic regression models. RESULTS: Two MVPA, 3 screen time, and 2 sleep trajectories were identified. Girls were more likely than boys to belong to trajectory with lower MVPA means (odds ratio [OR] = 6.45; 95% confidence interval [CI], 3.08 to 13.49), yet less likely to belong to the trajectory with higher screen time (OR = 0.47; 95% CI, 0.23 to 0.97) and lower sleep duration (OR = 0.46; 95% CI, 0.27 to 0.78). Overweight or obesity at baseline was associated with a greater likelihood of belonging to the trajectory with lower MVPA (OR = 10.99; 95% CI, 1.31 to 91.14) and higher screen time (OR = 2.01; 95% CI, 1.04 to 4.06), respectively. CONCLUSIONS: It appears to be gender- and weight-based determinants of behavioral trajectories in this sample. These results may provide guidance for interventions in similar populations.

Adherence to the 24-hour movement guidelines and adiposity in a cohort of at risk youth: A longitudinal analysis.

BACKGROUND: The 24-hour movement guidelines provide recommendations for physical activity, screen time and sleep duration for children. OBJECTIVES: Describe adherence to the guidelines and their cross-sectional and longitudinal associations with adiposity from childhood to adolescence. METHODS: Data are from the QUALITY Cohort. Children were followed at 8 to 10 years (childhood; n = 630), 10 to 12 years (early adolescence; n = 564) and 15 to 17 years (adolescence; n = 377). Physical activity, screen time, and sleep duration were measured by accelerometry and questionnaires. Body mass index z-scores (zBMI), waist circumference, waist-to-height ratio and percent body fat were based on clinical measurements. Multiple linear regressions estimated associations. RESULTS: In childhood, early adolescence and adolescence, 14%, 6%, and 0% of participants met the 24-hour movement guidelines, respectively. Meeting fewer guideline components was cross-sectionally associated with higher adiposity at each visit. Meeting fewer guideline components in childhood was longitudinally associated with higher adiposity at later visits. For example, those meeting none of the guideline components (vs all) in childhood had a 1.66 SD (95% CI: 0.42, 2.89) higher zBMI in early adolescence. CONCLUSION: Few participants met the guidelines. Not meeting the guidelines in childhood is associated with higher adiposity 2 and 7 years later. Interventions are needed to increase adherence to the 24-hour movement guidelines across childhood and adolescence.

Can anthropometry and physical fitness testing explain physical activity levels in children and adolescents with obesity?

OBJECTIVES: As time with patients and resources are increasingly limited, it is important to determine if clinical tests can provide further insight into real-world behaviors linked to clinical outcomes. The purpose of this study was to determine which aspects of anthropometry and physical fitness testing are associated with physical activity (PA) levels among youth with obesity. DESIGN: Cross-sectional study. METHOD: Anthropometry [height, waist circumference, bodyweight, fat percentage], physical fitness [muscular endurance (partial curl-ups), flexibility (sit-and-reach), lower-body power (long-jump), upper-body strength (grip), speed/agility (5×5-m shuttle), cardiorespiratory fitness (VO2-max)], and PA [light (LPA), moderate (MPA), vigorous (VPA), MVPA] was assessed in 203 youth with obesity. RESULTS: The sample was stratified by age <12 yrs (children); 12 yrs (adolescents) and sex. Stepwise regression evaluated associations between PA with anthropometry and physical fitness. Children (57% male) and adolescents (45% male) had a BMI Z-score of 3.5(SD:0.94) and 3.1(SD:0.76) respectively. Long-jump explained 19.5% [(Standardized) Beta=0.44; p=0.001] of variance in VPA for childhood girls and 12.6% (Beta=0.35; p=0.025) of variance in MPA for adolescent boys. 5×5-m shuttle explained 8.4% (Beta=-0.29; p=0.042) of variance in MVPA for childhood girls. Body mass explained 6.3% (Beta=-0.25; p=0.007) of variance in LPA in childhood boys. Fat percentage explained 9.8% (Beta=0.31; p=0.03) of variance in MPA in adolescent girls. CONCLUSIONS: In conclusion, tests of lower body power, body mass and fat percentage provide limited information concerning PA levels in youth with obesity. Activity monitoring should be considered in addition to clinical assessments to more fully understand youth health.

Sleep Duration and Timing in the Medium- to Long-Term Post-Bariatric Surgery.

Sleep duration improves short-term following bariatric surgery; however, little is known about its association with bodyweight medium- to long-term post-surgery. The purpose of this study was to describe sleep duration and its relationship with BMI and body composition. Forty-nine individuals, with a BMI of 36.6 ± 9.8 kg/m2, regained 26.4 ± 17.8% of their lost weight 9.5 ± 3.3 years post-surgery (range 3-16 years). Sleep logs and ActivPAL3 accelerometers were used to assess sleep duration. Participants averaged 7.9 ± 1.6 h/day and 8.5 ± 1.7 h/day of sleep for weekdays and weekends, respectively (P < 0.01). A positive association between delta weekend-weekday sleep timing midpoint with BMI (ß = 0.03, 95% CI = 0.01, 0.06; P = 0.01) was noted in the multivariable-adjusted model. On average, this sample achieved recommended sleep durations medium- to long-term post-surgery. Having an earlier sleep timing midpoint during the weekend may be associated with lower BMI.