Independent and joint associations of aerobic and muscle-strengthening exercise with mental health in adolescents: A cross-sectional analysis before and during COVID-19 using the 2015-2021 National Youth Risk Behavior Survey

PURPOSE

COVID-19 led to social isolation that may have compromised adolescent mental health. This study examined the independent and joint associations of aerobic physical activity (PA) and muscle-strengthening exercise (MSE) with mental health problems in adolescents.

METHODS

Participants were US adolescents who completed the 2015-2021 National Youth Risk Behavior Survey (N = 61,298; 45.7% female). Data were collected between 2015 and 2021 and analyzed in 2023. Outcomes were binary response items asking about feeling sad/hopeless, having difficulty concentrating, remembering, or making decisions, and having a suicidal ideation. Preventive exposure variables were items asking about frequencies of aerobic PA and MSE with responses dichotomized to align with recommendations. Independent and joint associations were examined using robust Poisson regression with covariates selected using double selection lasso. Structural equation models examined the associations treating PA and MSE as continuous predictors and poor mental health as a latent dependent variable.

RESULTS

Meeting either recommendation alone associated with a 4-10% lower prevalence of mental health problems (APR = 0.90-0.96, p < 0.05), and meeting both recommendations associated with a 15%-20% lower prevalence of mental health problems (APR = 0.80-0.85, p < 0.001). Although categorical joint associations were stronger in males (p < 0.05), multiplicative interactions were observed in females using continuous variables for PA and MSE (β = -0.09, p < 0.001).

CONCLUSION

Meeting aerobic PA and MSE recommendations associated with lower prevalence of mental health problems. Participation in MSE below recommended levels may be beneficial for females when combined with aerobic PA. Future research should examine these associations by acquiring contextual information and device-based assessments.

Dose-response associations of Monitor-Independent Movement Summary with health-related fitness in youth

The purpose of this study was to determine the dose-response associations between Monitor-Independent Movement Summary (MIMS) units and health-related fitness in youth. The sample comprised US children and adolescents who participated in the 2012 National Youth Fitness Survey (NNYFS; N = 1158, 48.9% female). Health-related fitness domains were assessed using tests of cardiorespiratory endurance (timed maximal and graded treadmill tests), muscular strength (modified pull-up and grip tests), and muscular endurance (plank test). Movement data were collected using wrist-worn ActiGraph accelerometers with raw data processed using MIMS and the calculated metrics of average MIMS/day, Peak 60-min MIMS, and Peak 30-min MIMS. Weighted regression models examined linear associations between MIMS metrics and fitness test scores. Nonlinear associations were examined using weighted spline models with knots placed at the 10th, 50th, and 90th percentiles. Models were adjusted for covariates and fit was examined using the coefficient of determination (R2 ). The strongest adjusted linear relationships included a positive association between MIMS/day (per every 1000 units) and maximal endurance times (b = 5.5 s, p < 0.001) and between Peak 60-min MIMS (per every 10 units) and estimated aerobic capacity (b = 1.7 mL/kg/min, p < 0.001), modified pull-ups (b = 0.7 reps, p < 0.001), and plank test scores (b = 5.0 s, p < 0.001). Linear spline models had slightly higher R2 values (R2 range = 16.9%-74.8%) compared to linear models (R2 range = 15.0%-74.5%). The relationship between MIMS metrics and fitness test scores was best modeled as piecewise linear functions. Although all MIMS metrics associated with cardiorespiratory endurance, Peak 60-min MIMS showed stronger associations with tests of muscular strength and endurance.

Moderate to vigorous physical activity, leucine, and protein intake contributions to muscle health in middle age

Objective:

Identify contributors to differences in the muscle size and strength of sedentary and active young and middle-aged adults.

Methods:

This cross-sectional study included 98 participants aged 20-65 years. Participants were categorized based on age and self-reported physical activity (PA) habits. Participants completed a strength assessment of knee extensors (KEPT), knee flexors (KFPT), plantar flexors (PFPT), and dorsiflexors (DFPT), a 3-day dietary intake log, 7-day accelerometry, and a magnetic resonance imaging (MRI) scan for muscle cross-sectional area analysis of the right quadriceps (CSAq).

Results:

There were significant age and activity-related group effects for relative protein intake (p<0.001), relative energy intake (p=0.04), KEPT (p=0.01), CSAq (p=0.002), PFPT (p=0.004) and DFPT (p=0.003). Moderate, moderate-to-vigorous, and vigorous PA were positively associated with CSAq (R²=0.69- 0.71; p<0.05), KEPT (R²=0.61-0.63; p<0.05), and PFPT (R²=0.31-0.36; p<0.05). Relative protein intake and daily leucine intake were significantly and positively associated with CSAq (R²=0.70 and 0.67 respectively; p<0.05), KEPT (R²=0.62 and 0.65 respectively; p<0.05), and PFPT (R²=0.29 and 0.28 respectively; p<0.05).

Conclusion:

Muscle size and strength were lower in middle age relative to younger age, but increased PA, protein intake, and leucine intake was associated with the preservation of muscle size and strength in larger muscle groups of the lower body.

A randomized trial to promote physical activity in adult pre-hypertensive and hypertensive patients

The purpose of the pilot study was to determine the effectiveness of wearable activity trackers alone or in combination with behaviour change strategies for promoting physical activity (PA) among individuals with pre-hypertension or hypertension. A sample of 44 adults (68% female and mean age 55) were randomized to receive either a Fitbit Charge HR 3 alone (FB) or the Fitbit in combination with behaviour change strategies (i.e., goal setting, behaviour goal review, adaptive feedback) delivered by a trained health coach (FB+) for 12 weeks. Moderate and vigorous PA (MVPA), steps, and sedentary time (ST) were assessed using ActiGraph wGT3X-BT. The FB+ group significantly increased PA [+1854 (2518) steps/day, p < .01] and MVPA [+26 (34) mins/day, p < .05], and decreased their ST [-63 (73) mins/day, p < .01]. The FB group significantly increased  MVPA [+11 (16) mins/day, p < .05], and decreased their ST [-87 (117) mins/day, p < .01]. Participants in FB+ had a significantly greater increase in MVPA/day compared to FB only with a between-group effect size of 0.6 (p < .05). Using Fitbit for self-monitoring is effective in increasing PA and reducing ST among pre-hypertensive and hypertensive participants. Additional behaviour change support amplified the intervention effectiveness for promoting MVPA.

Animal-Based Dietary Protein Intake Is Not A Risk Factor For Metabolic Syndrome Among Young Or Middle-Aged Females

Background:

Metabolic syndrome (MetS) increases risk for morbidity and premature mortality. Blood pressure, waist circumference, and fasting triglycerides (TG), blood glucose (BG), and high-density lipoprotein cholesterol (HDL) are factors for determining MetS. The Simple Method for Quantifying Metabolic Syndrome (siMS) score and risk score estimate risk of MetS. The purpose for this study was to exam the relationship of animal-based (ABP) and plant-based protein (PLP) with MetS as estimated by siMS score and risk score. Physical activty is another important consideration in MetS as it can reduce blood pressure, waist circumference and blood glucose, and affect blood lipid and lipoprotein concentrations.

Methods:

A cross-sectional study examined whether physical activity (PA) level and dietary protein source (i.e., animal- or plant-based) among young (18-24 years) and middle-aged (45-60 years) females were associated with siMS score and siMS risk score. Average time spent in sedentary, light, and moderate-to-vigorous PA (MVPA; min/wk), steps (steps/day), energy intake (kcal/day), percent dietary protein to total energy intake, ABP and PLP dietary intake, and ABP:PLP ratio (g/day) were included in the analysis. Volunteers were recruited from North Dakota and Minnesota from 2017 to 2019.

Results:

Eighty-one female participants (mean ± SD; young, n = 38, 20.4 ± 1.7 years, middle-aged, 52.5 ± 4.8 years) were included in the independent t-tests used to examine group differences in age, body mass index, HDL, BG, TG, systolic blood pressure, waist circumference, energy intake, energy intake percentage of total carbohydrates, fat, protein, ABP, and PLP, ABP:PLP, siMS score, and siMS risk score. Stepwise linear regressions were used to evaluate whether PA level and dietary protein source were predictors of siMS score and siMS risk score among young and middle-aged adult females. There was an inverse relationship between PLP intake and siMS score. The model explained 6.9% of the variance in siMS risk score (F_{1, 80} = 5.93). Plant-based protein intake was inversely related to siMS risk score while light PA was positively associated with siMS risk score. The model explained 16% of the variance in siMS risk score (F_{1, 80} = 7.53). Animal-based dietary protein intake did not impact siMS score (p = 0.180) and siMS risk score (p = 0.283).

Conclusions:

Plant-based protein intake was associated with a lower risk of MetS via siMS scores, while ABP was not associated. Given the nature of the cross-sectional design of this study, no causal relationship can be determined, but longitudinal studies or randomized control trials to confirm the results from this study are needed in the future.

Evenness of Dietary Protein Intake Is Positively Associated with Lean Mass and Strength in Healthy Women

Background:

Evenness of protein intake is associated with increased lean mass, but its relationship with muscle strength and performance is uncertain.

Objectives:

We determined the association of evenness of protein intake with lean mass, muscle strength and endurance, and functional ability.

Design:

This was a cross-sectional study.

Setting:

Data were collected at a research university in the upper midwestern United States.

Participants:

One hundred ninety-two healthy women, aged 18 to 79 years, mean ± SEM 41.9 ± 1.3, completed the study.

Measurements:

Dietary intake was assessed using 3-day food diaries verified with food frequency questionnaires. To assess evenness of protein intake, the day was divided into 3 periods: waking to 11:30, 11:31 to 16:30, and after 16:30. Lean mass was measured with dual energy X-ray absorptiometry. Lower-body muscle strength and endurance were determined using isokinetic dynamometry. Upper-body muscle strength was maximal handgrip strength. Functional ability was assessed using 6-m gait speed and 30-second chair stand tests. Accelerometry measured physical activity.

Results:

Intakes of 25 g or more of protein at 1 or more of the 3 periods was positively associated with lean mass (β ± S.E.; 1.067 ± 0.273 kg, P < .001) and upper-body (3.274 ± 0.737 kg, P < .001) and lower-body strength (22.858 ± 7.918 Nm, P = .004) when controlling for age, body mass index, physical activity, and energy and protein intakes. Consuming at least 0.24 g/kg/period for those under 60 years and 0.4 g/kg/period for those 60 years and older was related to lean mass (0.754 ± 0.244 kg, P = .002), upper-body strength (2.451 ± 0.658 kg, P < .001), and lower-body endurance (184.852 ± 77.185 J, P = .018), controlling for the same variables.

Conclusions:

Evenness of protein intake is related to lean mass, muscle strength, and muscular endurance in women. Spreading protein intake throughout the day maximizes the anabolic response to dietary protein, benefiting muscle mass and performance.

Bidirectional relationships of physical activity and gross motor skills before and after summer break: Application of a cross-lagged panel model

BACKGROUND

Gross motor skills are postulated to have a bidirectional relationship with physical activity (PA); however, no study has tested this relationship before and after a summer break. The purpose of this study was to examine the bidirectional relationships between school PA and gross motor skills in children before and after a summer break.

METHODS

Participants were a sample of 440 children recruited from 3 low-income schools (age = 8.9 ± 1.2 years, mean ± SD). PA was assessed as average school-day step counts using Yamax DigiWalker pedometers (Yamasa Tokei Keiki, Tokyo, Japan) worn for 5 consecutive school days. Gross motor skills were assessed using the Test for Gross Motor Development, 3rd edition. Data were collected at 2 timepoints: at the end of spring semester (T1) and at the beginning of the subsequent fall semester (T2). An age- and body mass index-adjusted cross-lagged model was employed to relate T1 school step counts with T2 gross motor skills and T1 gross motor skills with T2 school step counts.

RESULTS

T1 gross motor skills significantly predicted T2 school step counts (β = 0.24, 95 % confidence interval (95%CI): 0.08-0.40, p = 0.003); however, T1 school step counts did not predict T2 gross motor skills (β = 0.04, 95%CI: -0.06 to 0.14, p = 0.445). The model explained 35.4% and 15.9% of the variances of T2 gross motor skills and T2 school step counts, respectively. Additional analyses indicated that these relationships were driven primarily by ball skills.

CONCLUSION

The relationship between gross motor skills and school PA was not bidirectional; however, higher gross motor skills, specifically ball skills, predicted higher school PA after a 3-month summer break.

Parent and Child Perceptions of Barriers to Active School Commuting

BACKGROUND

Active commuting (AC) to and from school can contribute to physical activity, although it has recently seen a global decline. The purpose of this study was to examine the agreement between parent and child perceptions of barriers to school AC.

METHODS

Participants were parents (N = 152, M_age  = 40.6 ± 6.3 years) and elementary school children (N = 98, M_age  = 10.0 ± 1.2 years). School commute type/frequency and barriers to AC were collected via surveys. Intraclass correlation coefficients (ICCs) were used to assess relative agreement between parent and child perceptions (N = 98 dyads). Paired t tests and equivalence testing were employed to assess group-level agreement. Bland-Altman analysis was used to assess individual-level agreement. Partial correlations of AC with perceptions were also assessed.

RESULTS

All parent and child perceptions of barriers to AC to school had low agreement. Bland-Altman Plots indicated negative bias for all but 3 barrier perceptions. Paired t tests indicated significant differences between parent and child perceptions for 8 out of 15 barriers while equivalence testing deemed no parent-child perception equivalent. Partial correlations with AC frequency were significant for 7 parent perceptions and 2 child perceptions.

CONCLUSIONS

Parent and child perceptions have low agreement. Programs aimed at promoting AC to and from school should account for these discrepancies.

Physical activity in the early postpartum period in primiparous women

Little is known about early postpartum physical activity (PA).

OBJECTIVES

We aimed to describe PA amount and types and compare moderate-vigorous PA (MVPA) at 12-25 (T1) and 33-46 days (T2) postpartum.

DESIGN

Cross-sectional study.

METHODS

Participants, primiparas delivered vaginally, wore wrist accelerometers and completed questionnaires. Median and interquartile range (IQR) describe minutes/day of PA intensities in total minutes, 5- and 10-minute bouts. Wilcoxon Signed Rank test compared MVPA.

RESULTS

577 (age: 28.3 (SD: 5.1)) had accelerometry or questionnaire at either time-point. 405 had accelerometry at both time-points. Median (IQR) total minutes/day for light, moderate, vigorous and MVPA were 295.8 (256.1-331.7), 54.6 (40-72.7), 0.4 (0.2-0.8), and 55.5 (40.4-74.3), respectively, at T1 and 329 (289.4-367.1), 63.6 (46.9-82.2), 0.6 (0.3-1.3), and 64.5 (47-84.8), respectively, at T2. Median (IQR) minutes/day for MVPA in 5- and 10-minute bouts were 1.6 (0-5.5) and 0 (0-3.8) at T1, and 3 (0-9.2) and 0 (0-5.5) at T2. At T1, 75% (406/541) and at T2, 72.4% (397/548) reported non-impact activities. At T1, 4% and at T2, 13% reported impact/straining activities. MVPA was greater at T2 than T1 (p < 0.0001) with medians (IQR) of: total: 64.7 (47-84.6) vs 56.5 (41-74.9) minutes; 5-minute bouts: 3 (0-9.8) vs 1.7 (0-5.6) minutes; and 10-minute bouts: 1.3(0-6) vs 0(0-3.8) minutes.

CONCLUSIONS

Women had high daily MVPA, though MVPA in bouts remained low. Significant increases in MVPA from T1 to T2 were small, few women reported impact/straining activities. Realistic return to pre-pregnancy PA levels should recognize the relative lack of sustained/strenuous activity in early postpartum.

Parent Preferences for Physical Activity in Before and After School Programs in Rural and Suburban Communities: A Discrete Choice Experiment

BACKGROUND

The purpose of this study was to examine and compare parent preferences of before and after school physical activity program components in rural and suburban elementary schools.

METHODS

A discrete choice experiment was conducted to measure parent preferences for components of before/after school programs. A total of 183 parents (age = 37.2 [8.2] y, 155 females) sampled from 15 elementary schools (K-6 grades) in the Western United States took part in the study, half of which were from a rural community (n = 93, 50.8%). Results from the discrete choice experiment were analyzed using hierarchic Bayesian methodology, which estimated utility scores and was used to calculate important scores for program components.

RESULTS

The specific goal of the before/after school program was the strongest determinant of parents' stated choice overall, followed by leaders, time of day, length, and main focus. Learning sports as the physical activity goal was the top-rated attribute. Subgroup analyses revealed discrepancies between suburban and rural parents and parents of boys and girls.

CONCLUSION

This study extends the application of discrete choice experiments to school-based programming, providing a unique way to design empirically based, stakeholder informed school programs, specifically within before and after school settings.

Validation of the Apple Watch for Estimating Moderate-to-Vigorous Physical Activity and Activity Energy Expenditure in School-Aged Children

The Apple Watch is one of the most popular wearable devices designed to monitor physical activity (PA). However, it is currently unknown whether the Apple Watch accurately estimates children’s free-living PA. Therefore, this study assessed the concurrent validity of the Apple Watch 3 in estimating moderate-to-vigorous physical activity (MVPA) time and active energy expenditure (AEE) for school-aged children under a simulated and a free-living condition. Twenty elementary school students (Girls: 45%, age: 9.7 ± 2.0 years) wore an Apple Watch 3 device on their wrist and performed prescribed free-living activities in a lab setting. A subgroup of participants (N = 5) wore the Apple Watch for seven consecutive days in order to assess the validity in free-living condition. The K5 indirect calorimetry (K5) and GT3X+ were used as the criterion measure under simulated free-living and free-living conditions, respectively. Mean absolute percent errors (MAPE) and Bland-Altman (BA) plots were conducted to assess the validity of the Apple Watch 3 compared to those from the criterion measures. Equivalence testing determined the statistical equivalence between the Apple Watch and K5 for MVPA time and AEE. The Apple Watch provided comparable estimates for MVPA time (mean bias: 0.3 min, p = 0.91, MAPE: 1%) and for AEE (mean bias: 3.8 kcal min, p = 0.75, MAPE: 4%) during the simulated free-living condition. The BA plots indicated no systematic bias for the agreement in MVPA and AEE estimates between the K5 and Apple Watch 3. However, the Apple Watch had a relatively large variability in estimating AEE in children. The Apple Watch was statistically equivalent to the K5 within ±17.7% and ±20.8% for MVPA time and AEE estimates, respectively. Our findings suggest that the Apple Watch 3 has the potential to be used as a PA assessment tool to estimate MVPA in school-aged children.

Relationship of heart rate, perceived exertion, and intra-abdominal pressure in women

Background

Exercise increases intra-abdominal pressure (IAP) acutely, which may impact the pelvic floor of women. IAP during exercise demonstrates high variability among women but is not routinely assessed. Assessing less invasive measures related to IAP during exercise may facilitate study of how IAP impacts the pelvic floor.

Methods

The objective of this study was to investigate the relationship of heart rate and rating of perceived exertion (RPE) with IAP during a standard treadmill test. We describe the trend of IAP by predicted aerobic fitness during incremental exercise. IAP was measured using a validated transducer placed in the upper vagina. Heart rate and RPE were collected during the first 3 stages of the standard Bruce treadmill protocol. Relationships of heart rate and RPE with IAP were determined by Pearson correlation coefficients. Predicted aerobic fitness values for each participant were ranked in tertiles with IAP by treadmill stage.

Results

Twenty-four women participated in this study (mean age: 24.7 (5.4) years; body mass index: 22.5 (2.2) kg/m²). There were significant relationships between heart rate and IAP (r= 0.67, p < 0.001) and RPE and IAP (r= 0.60, p < 0.001) across treadmill stages. Tertiles of predicted aerobic fitness and IAP displayed similar trends as other exercise measures during incremental exercise, such as, heart rate and ventilation.

Conclusion

Heart rate and RPE could be used as proxy measures of IAP during incremental exercise. Aerobic fitness may help explain IAP variability in women and provide context for future research on IAP and pelvic floor health.

School-based physical activity interventions in rural and urban/suburban communities: A systematic review and meta-analysis

Disparities in physical activity and health outcomes exist between urban and rural youth. School settings can be utilized to promote physical activity in youth regardless of urban-rural status. This systematic review and meta-analysis aimed to assess and compare the effect of rural and urban/suburban school-based physical activity programs on total physical activity in youth. A search of five databases was conducted. A total of 33 studies remained after the exclusion process, 28 of which took place in urban/suburban schools and five of which took place in rural schools. The DerSimonian and Laird random effects model was employed with the estimates of heterogeneity taken from the inverse-variance fixed-effect model. For rural studies, the Hartung-Knapp-Sidak-Jonkman method was used to obtain error estimates. Results from the total sample indicated a significant but small pooled increase in daily physical activity (Hedge's g = 0.12, 95% confidence interval [CI]: 0.06-0.18), which held for interventions conducted in urban/suburban schools (Hedge's g = 0.12, 95% CI: 0.06-0.19). For rural school-based interventions, there was no significant pooled effect (Hedge's g = 0.06, 95% CI: -0.50 to 0.61). This meta-analysis provides evidence that school-based interventions can be marginally effective for increasing daily physical activity in children and adolescents; however, no effect was observed for interventions implemented in rural settings.

Comprehensive comparison of Apple Watch and Fitbit monitors in a free-living setting

Objectives

The aim of this study was to evaluate the accuracy of three consumer-based activity monitors, Fitbit Charge 2, Fitbit Alta, and the Apple Watch 2, all worn on the wrist, in estimating step counts, moderate-to-vigorous minutes (MVPA), and heart rate in a free-living setting.

Methods

Forty-eight participants (31 females, 17 males; ages 18–59) were asked to wear the three consumer-based monitors mentioned above on the wrist, concurrently with a Yamax pedometer as the criterion for step count, an ActiGraph GT3X+ (ActiGraph) for MVPA, and a Polar H7 chest strap for heart rate. Participants wore the monitors for a 24-hour free-living condition without changing their usual active routine. MVPA was calculated in bouts of ≥10 minutes. Pearson correlation, mean absolute percent error (MAPE), and equivalence testing were used to evaluate the measurement agreement.

Results

The average step counts recorded for each device were as follows: 11,734 (Charge2), 11,922 (Alta), 11,550 (Apple2), and 10,906 (Yamax). The correlations in steps for the above monitors ranged from 0.84 to 0.95 and MAPE ranged from 17.1% to 35.5%. For MVPA minutes, the average were 76.3 (Charge2), 63.3 (Alta), 49.5 (Apple2), and 47.8 (ActiGraph) minutes accumulated in bouts of 10 or greater minutes. The correlation from MVPA estimation for above monitors were 0.77, 0.91, and 0.66. MAPE from MVPA estimation ranged from 44.7% to 55.4% compared to ActiGraph. For heart rate, correlation for Charge2 and Apple2 was higher for sedentary behavior and lower for MVPA. The MAPE ranged from 4% to 16%.

Conclusion

All three consumer monitors estimated step counts fairly accurately, and both the Charge2 and Apple2 reported reasonable heart rate estimation. However, all monitors substantially underestimated MVPA in free-living settings.

Segmented School Physical Activity and Weight Status in Children: Application of Compositional Data Analysis

The purpose of this study was to apply compositional data analysis (CoDA) for the analysis of segmented school step counts and associate the school step count composition to body mass index (BMI) z-scores in a sample of children. Participants were 855 (51.8% female) children recruited from the fourth and fifth grades from four schools following a 7-h school schedule. Using piezoelectric pedometers, step count data were collected during physical education, recess, lunch, and during academic class time. A multi-level mixed effects model associated the step count composition with BMI z-scores. Compositional isotemporal substitution determined changes in BMI z-scores per reallocation of steps between pairs of school segments. A higher percentage of steps accrued during physical education (b = −0.34, 95%CI: −0.65–−0.03, p = 0.036) and recess (b = −0.47, 95%CI: −0.83–−0.11, p = 0.012), relative to other segments, was associated with lower BMI z-scores. Specifically, a 5% to 15% reallocation of steps accrued during lunchtime to either physical education or recess was associated with lower BMI z-scores, ranging from −0.07 to −0.25 standard deviation units. Focusing school-based promotion of physical activity during physical education and recess may have greater relative importance if targeted outcomes are weight-related.

Measures Derived from Panoramic Ultrasonography and Animal-Based Protein Intake Are Related to Muscular Performance in Middle-Aged Adults

Ultrasonography advantageously measures skeletal muscle size and quality, but some muscles may be too large to capture with standardized brightness mode (B-mode) imaging. Panoramic ultrasonography can capture more complete images and may more accurately measure muscle size. We investigated measurements made using panoramic compared to B-mode ultrasonography images of the rectus femoris with muscular performance. Concurrently, protein intake plays an important role in preventing sarcopenia; therefore, we also sought to investigate the association between animal-based protein intake (ABPI) and muscular performance. Ninety-one middle-aged adults were recruited. Muscle cross-sectional area (CSA) and thickness were obtained using B-mode and panoramic ultrasound and analyzed with Image J software. Muscular performance was assessed using isokinetic dynamometry, a 30-s chair test, and handgrip strength. Three-day food diaries estimated dietary intakes. Linear regression models determined relationships between measures from ultrasonography and muscular performance. Mixed linear models were used to evaluate the association between ABPI and muscular performance. Muscle CSA from panoramic ultrasonography and ABPI were positively associated with lower-body strength (β ± S.E.; CSA, 42.622 ± 20.024, p = 0.005; ABPI, 65.874 ± 19.855, p = 0.001), lower-body endurance (β ± S.E.; CSA, 595 ± 200.221, p = 0.001; ABPI, 549.944 ± 232.478, p = 0.020), and handgrip strength (β ± S.E.; CSA, 6.966 ± 3.328, p = 0.004; ABPI, 0.349 ± 0.171, p = 0.045). Panoramic ultrasound shows promise as a method for assessing sarcopenia. ABPI is related to better muscular performance.

The Validity of MotionSense HRV in Estimating Sedentary Behavior and Physical Activity under Free-Living and Simulated Activity Settings

MotionSense HRV is a wrist-worn accelerometery-based sensor that is paired with a smartphone and is thus capable of measuring the intensity, duration, and frequency of physical activity (PA). However, little information is available on the validity of the MotionSense HRV. Therefore, the purpose of this study was to assess the concurrent validity of the MotionSense HRV in estimating sedentary behavior (SED) and PA. A total of 20 healthy adults (age: 32.5 ± 15.1 years) wore the MotionSense HRV and ActiGraph GT9X accelerometer (GT9X) on their non-dominant wrist for seven consecutive days during free-living conditions. Raw acceleration data from the devices were summarized into average time (min/day) spent in SED and moderate-to-vigorous PA (MVPA). Additionally, using the Cosemed K5 indirect calorimetry system (K5) as a criterion measure, the validity of the MotionSense HRV was examined in simulated free-living conditions. Pearson correlations, mean absolute percent errors (MAPE), Bland–Altman (BA) plots, and equivalence tests were used to examine the validity of the MotionSense HRV against criterion measures. The correlations between the MotionSense HRV and GT9X were high and the MAPE were low for both the SED (r = 0.99, MAPE = 2.4%) and MVPA (r = 0.97, MAPE = 9.1%) estimates under free-living conditions. BA plots illustrated that there was no systematic bias between the MotionSense HRV and criterion measures. The estimates of SED and MVPA from the MotionSense HRV were significantly equivalent to those from the GT9X; the equivalence zones were set at 16.5% for SED and 29% for MVPA. The estimates of SED and PA from the MotionSense HRV were less comparable when compared with those from the K5. The MotionSense HRV yielded comparable estimates for SED and PA when compared with the GT9X accelerometer under free-living conditions. We confirmed the promising application of the MotionSense HRV for monitoring PA patterns for practical and research purposes.

Movement Behaviors and Perceived Loneliness and Sadness within Alaskan Adolescents

Physical activity, screen use, and sleep are behaviors that integrate across the whole day. However, the accumulative influence of meeting recommendations for these 24-h movement behaviors on the mental health of Alaskan adolescents has not been examined. The purpose of this study was to examine the associations between movement behaviors, loneliness, and sadness within Alaskan adolescents. Data were obtained from the 2019 Alaska Youth Risk Behavior Survey (YRBS). The number of adolescents participating in the 2019 Alaska YRBS was 1897. Associations between meeting recommendations for movement behaviors with loneliness and sadness were examined using weighted logistic regression models, adjusted for age, sex, race/ethnicity, and body mass index (BMI). Approximately 5.0% of the sample met recommendations for all three movement behaviors. Meeting 2 or 3 movement behavior recommendations was associated with lower odds of loneliness (odds ratio (OR) range = 0.23 to 0.44, p < 0.01). Additionally, meeting 1 to 3 movement behavior recommendations was associated with lower odds of sadness (OR range = 0.29 to 0.52, p < 0.05). Joint association analyses determined that these relationships were primarily driven by meeting the sleep recommendation for loneliness and meeting the screen use recommendation for sadness. The results support use of multiple movement-based behavior programming to attenuate feelings of loneliness and sadness within Alaskan adolescents.

Contribution of Protein Intake and Concurrent Exercise to Skeletal Muscle Quality with Aging

BACKGROUND

The use of magnetic resonance imaging (MRI) derived functional cross-sectional area (FCSA) and intramuscular adipose tissue (IMAT) to define skeletal muscle quality is of fundamental importance in order to understand aging and inactivity-related loss of muscle mass.

OBJECTIVES

This study examined factors associated with lower-extremity skeletal muscle quality in healthy, younger, and middle-aged adults.

DESIGN

Cross-sectional study.

SETTING AND PARTICIPANTS

Ninety-eight participants (53% female) were classified as younger (20-35 years, n=50) or middle-aged (50-65 years, n=48) as well as sedentary (≤1 day per week) or active (≥3 days per week) on self-reported concurrent exercise (aerobic and resistance).

MEASUREMENTS

All participants wore an accelerometer for seven days, recorded a three-day food diary, and participated in magnetic resonance imaging (MRI) of the lower limbs. Muscle cross-sectional area (CSA) was determined by tracing the knee extensors (KE) and plantar flexors, while muscle quality was established through the determination of FCSA and IMAT via color thresholding.

RESULTS

One-way analysis of variance and stepwise regression models were performed to predict FCSA and IMAT. KE-IMAT (cm2) was significantly higher among sedentary (3.74 ± 1.93) vs. active (1.85 ± 0.56) and middle-aged (3.14 ± 2.05) vs. younger (2.74 ± 1.25) (p < 0.05). Protein intake (g•kg•day-1) was significantly higher in active (1.63 ± 0.55) vs. sedentary (1.19 ± 0.40) (p < 0.05). Sex, age, concurrent exercise training status, and protein intake were significant predictors of KE FCSA (R2 = 0.71, p < 0.01), while concurrent exercise training status and light physical activity predicted 33% of the variance in KE IMAT (p < 0.01).

CONCLUSION

Concurrent exercise training, dietary protein intake, and light physical activity are significant determinants of skeletal muscle health and require further investigation to mitigate aging and inactivity-related loss of muscle quality.

Agreement between the Apple Series 1, LifeTrak Core C200, and Fitbit Charge HR with Indirect Calorimetry for Assessing Treadmill Energy Expenditure

The purpose of this study was to examine agreement in energy expenditure between the Apple Series 1 Watch, LifeTrak Core C200, and Fitbit Charge HR with indirect calorimetry during various treadmill speeds in young adults. Participants were a sample of college-aged students (mean age = 20.1 (1.7) years; 13 females, 17 males). Participants completed six structured 10-minute exercise sessions on a treadmill with speeds ranging from 53.6 m·min^-1 to 187.7 m·min^-1. Indirect calorimetry was used as the criterion. Participants wore the Apple Watch, LifeTrak, and Fitbit activity monitors on their wrists. Group-level agreement was examined using equivalence testing, relative agreement was examined using Spearman's rho, and individual-level agreement was examined using Mean Absolute Percent Error (MAPE) and Bland-Altman Plots. Activity monitor agreement with indirect calorimetry was supported using the Apple Watch at 160.9 m·min^-1 (Mean difference = -2.7 kcals, 90% C.I.: -8.3 kcals, 2.8 kcals; MAPE = 11.9%; r_s = 0.64) and 187.7 m·min^-1 (Mean difference = 3.7 kcals, 90% C.I.: -2.2 kcals, 9.7 kcals; MAPE = 10.7%; r_s = 0.72) and the Fitbit at 187.7 m·min^-1 (Mean difference = -0.2 kcals, 90% C.I.: -8.8 kcals, 8.5 kcals; MAPE = 20.1%; r_s = 0.44). No evidence for statistical equivalence was seen for the LifeTrak at any speed. Bland-Altman Plot Limits of Agreement were narrower for the Apple Series 1 Watch compared to other monitors, especially at slower treadmill speeds. The results support the utility of the Apple Series 1 Watch and Fitbit Charge HR for assessing energy expenditure during specific treadmill running speeds in young adults.

Gross Motor Skills Predict Classroom Behavior in Lower-Income Children

Children from lower income families tend to have low levels of on-task behavior in the academic classroom. The purpose of this study was to examine the associations of gross motor skills and classroom behavior in a sample of lower-income children. Participants were a sample of 1,135 school-aged children (mean age = 8.3 ± 1.8 years) recruited from three low-income US schools. A reduced version of the Test for Gross Motor Development 2nd Edition (TGMD-2) was used to assess gross motor skills. Total TGMD-2 scores, locomotor subtest scores, and object control subtest scores were stratified into quintiles for analysis. Students' classroom behavior was recorded 1 year later using a Planned Activity Check (PLACHECK) 5-s momentary time sampling procedure. Classrooms were dichotomized into those that had students at least 80% on-task and those that did not. Multilevel generalized mixed models were employed to examine the relationship between gross motor skills and meeting at least 80% classroom behavior, adjusting for age, sex, and change in BMI, and aerobic fitness. Children in the highest TGMD-2 quintile had 4.17 higher odds of being in an on-task classroom 1 year later (95%CI [2.25-7.76], p < 0.001). This relationship was primarily driven by the relationship between object control quintile scores and classroom behavior, as children within the higher quintile for object control had 3.81 higher odds of being in an on-task classroom 1 year later (95%CI [2.67-5.46], p < 0.001). There was a significant relationship between individual gross motor skills, specifically object control skills, and group level on-task classroom behavior in lower-income children.

Concurrent validity of the Fitbit for assessing sedentary behavior and moderate-to-vigorous physical activity

Background

Recent advances in sensor technologies have promoted the use of consumer-based accelerometers such as Fitbit Flex in epidemiological and clinical research; however, the validity of the Fitbit Flex in measuring sedentary behavior (SED) and physical activity (PA) has not been fully determined against previously validated research-grade accelerometers such as ActiGraph GT3X+. Therefore, the purpose of this study was to examine the concurrent validity of the Fitbit Flex against ActiGraph GT3X+ in a free-living condition.

Methods

A total of 65 participants (age: M = 42, SD = 14 years, female: 72%) each wore a Fitbit Flex and GT3X+ for seven consecutive days. After excluding sleep and non-wear time, time spent (min/day) in SED and moderate-to-vigorous PA (MVPA) were estimated using various cut-points for GT3X+ and brand-specific algorithms for Fitbit, respectively. Repeated measures one-way ANOVA and mean absolute percent errors (MAPE) served to examine differences and measurement errors in SED and MVPA estimates between Fitbit Flex and GT3X+, respectively. Pearson and Spearman correlations and Bland-Altman (BA) plots were used to evaluate the association and potential systematic bias between Fitbit Flex and GT3X+. PROC MIXED procedure in SAS was used to examine the equivalence (i.e., the 90% confidence interval with ±10% equivalence zone) between the devices.

Results

Fitbit Flex produced similar SED and low MAPE (mean difference [MD] = 37 min/day, P = .21, MAPE = 6.8%), but significantly higher MVPA and relatively large MAPE (MD = 59–77 min/day, P < .0001, MAPE = 56.6–74.3%) compared with the estimates from GT3X+ using three different cut-points. The correlations between Fitbit Flex and GT3X+ were consistently higher for SED (r = 0.90, ρ = 0.86, P < .01), but weaker for MVPA (r = 0.65–0.76, ρ = 0.69–0.79, P < .01). BA plots revealed that there is no apparent bias in estimating SED.

Conclusion

In comparison with the GT3X+ accelerometer, the Fitbit Flex provided comparatively accurate estimates of SED, but the Fitbit Flex overestimated MVPA under free-living conditions. Future investigations using the Fitbit Flex should be aware of present findings.

Feasibility and Effectiveness of a Wearable Technology-Based Physical Activity Intervention in Preschoolers: A Pilot Study

The purpose of this pilot study was to evaluate the feasibility and the effectiveness of an intervention that employed a technology-based physical activity (PA) monitoring system and teacher-regulated strategies to promote PA in preschoolers. A total of 93 preschoolers (53% girls, 4.7 years) from 5 child care centers were recruited for a one-week intervention and randomly assigned into control (2 centers, n = 45) or intervention (3 centers, n = 48) group. Key intervention components included: (1) wearable device-based, real-time monitoring of children’s PA by classroom teachers and (2) teacher-regulated strategies for providing more opportunities for PA. Sedentary behavior (SED) and PA were measured using accelerometers. Overall, children in the intervention group showed significantly lower level of SED (31.6 vs. 33.6 min/h) and higher level of total PA (28.4 vs. 26.4 min/h) than children in the control group, after adjusting for age, sex, race, parent education level, parent perception of their child’s PA, BMI, and childcare centers. Teachers in the intervention group reported that the intervention was highly feasible to be implemented in their current classroom settings. In conclusion, we observed high acceptability and initial effectiveness of the current intervention. Subsequent research at larger-scale is warranted to fully evaluate the effectiveness of the intervention strategies tested in this study.

The Use of a Fitbit Device for Assessing Physical Activity and Sedentary Behavior in Preschoolers

OBJECTIVE

To determine the accuracy of the Fitbit Flex (FF) activity monitor for assessing preschoolers' physical activity (PA) and sedentary behavior (SED) in free-living conditions.

STUDY DESIGN

This is a cross-sectional study of 27 preschoolers (41% girls; age, 4.9 years) who each wore the FF and ActiGraph GT3X+ (AG) simultaneously for 24 hours. Raw data from each device were temporally matched and summarized into estimates of SED, moderate-to-vigorous PA, and total PA after removing sleep and nonwear time periods. Equivalence testing was performed to compare the 90% CIs of the estimates from the FF with the respective equivalence zone (±15% of the mean estimates) from the AG.

RESULTS

The FF yielded equivalent estimates of SED (mean difference, 42-71 minutes/day) and total PA (mean difference, 42-70 minutes/day), but lower moderate-to-vigorous PA (mean difference, 29-67 minutes/day) than the AG, on average. The FF showed strong correlations and relatively low mean absolute percent errors (MAPEs) in relation to the AG for SED (r = 0.87; MAPE = 9.1%) and total PA (r = 0.71; MAPE = 14.3%), but a moderate correlation and high MAPE for moderate-to-vigorous PA (r = 0.59; MAPE = 70.1%).

CONCLUSIONS

The FF activity monitor accurately estimated the amount of time spent in SED and overall PA in preschool-aged children, but with an underestimation of moderate-to-vigorous PA. Our findings support the use of the FF as a feasible and a relatively accurate PA monitoring tool in clinical and research settings.

Comparison of Wearable Trackers' Ability to Estimate Sleep

Tracking physical activity and sleep patterns using wearable trackers has become a current trend. However, little information exists about the comparability of wearable trackers measuring sleep. This study examined the comparability of wearable trackers for estimating sleep measurement with a sleep diary (SD) for three full nights. A convenience sample of 78 adults were recruited in this research with a mean age of 27.6 ± 11.0 years. Comparisons between wearable trackers and sleep outcomes were analyzed using the mean absolute percentage errors, Pearson correlations, Bland⁻Altman Plots, and equivalent testing. Trackers that showed the greatest equivalence with the SD for total sleep time were the Jawbone UP3 and Fitbit Charge Heart Rate (effect size = 0.09 and 0.23, respectively). The greatest equivalence with the SD for time in bed was seen with the SenseWear Armband, Garmin Vivosmart, and Jawbone UP3 (effect size = 0.09, 0.16, and 0.07, respectively). Some of the wearable trackers resulted in closer approximations to self-reported sleep outcomes than a previously sleep research-grade device, these trackers offer a lower-cost alternative to tracking sleep in healthy populations.

Classification Accuracy of a Wearable Activity Tracker for Assessing Sedentary Behavior and Physical Activity in 3-5-Year-Old Children

This study examined the accuracy of the Fitbit activity tracker (FF) for quantifying sedentary behavior (SB) and varying intensities of physical activity (PA) in 3-5-year-old children. Twenty-eight healthy preschool-aged children (Girls: 46%, Mean age: 4.8 ± 1.0 years) wore the FF and were directly observed while performing a set of various unstructured and structured free-living activities from sedentary to vigorous intensity. The classification accuracy of the FF for measuring SB, light PA (LPA), moderate-to-vigorous PA (MVPA), and total PA (TPA) was examined calculating Pearson correlation coefficients (r), mean absolute percent error (MAPE), Cohen's kappa (k), sensitivity (Se), specificity (Sp), and area under the receiver operating curve (ROC-AUC). The classification accuracies of the FF (ROC-AUC) were 0.92, 0.63, 0.77 and 0.92 for SB, LPA, MVPA and TPA, respectively. Similarly, values of kappa, Se, Sp and percentage of correct classification were consistently high for SB and TPA, but low for LPA and MVPA. The FF demonstrated excellent classification accuracy for assessing SB and TPA, but lower accuracy for classifying LPA and MVPA. Our findings suggest that the FF should be considered as a valid instrument for assessing time spent sedentary and overall physical activity in preschool-aged children.

Sedentary Behavior in Preschoolers: How Many Days of Accelerometer Monitoring Is Needed?

The reliability of accelerometry for measuring sedentary behavior in preschoolers has not been determined, thus we determined how many days of accelerometry monitoring are necessary to reliably estimate daily time spent in sedentary behavior in preschoolers. In total, 191 and 150 preschoolers (three to five years) wore ActiGraph accelerometers (15-s epoch) during the in-school (≥4 days) and the total-day (≥6 days) period respectively. Accelerometry data were summarized as time spent in sedentary behavior (min/h) using three different cutpoints developed for preschool-age children (<37.5, <200, and <373 counts/15 s). The intraclass correlations (ICCs) and Spearman-Brown prophecy formula were used to estimate the reliability of accelerometer for measuring sedentary behavior. Across different cutpoints, the ICCs ranged from 0.81 to 0.92 for in-school sedentary behavior, and from 0.75 to 0.81 for total-day sedentary behavior, respectively. To achieve an ICC of ≥0.8, two to four days or six to nine days of monitoring were needed for in-school sedentary behavior and total-day sedentary behavior, respectively. These findings provide important guidance for future research on sedentary behavior in preschool children using accelerometry. Understanding the reliability of accelerometry will facilitate the conduct of research designed to inform policies and practices aimed at reducing sedentary behavior in preschool children.

Correlates of objectively measured physical activity in cardiac patients

Cardiac patients would benefit from increasing their physical activity (PA) levels. Understanding of factors that influence cardiac patients' PA participation would benefit the development of effective interventions. Therefore, the purpose of this study was to determine correlates of objectively-measured PA in cardiac patients. Participants were 65 cardiac patients (74% male, 95% white), age 58.6±10.6 years. The amount of time spent in PA was measured by ActiGraph GT3X accelerometers for 7 days prior to joining cardiac rehabilitation programs (CRP). A total of 25 potential determinants of PA across multiple domains (demographic, clinical, psychosocial, and behavioral) were measured via self-reported questionnaire and clinical examinations. Backward elimination model selection procedures were performed to examine associations of potential determinants with total PA (min/day) and moderate-to-vigorous PA (MVPA) (min/day). Patients spent 153.8±62.8 and 8.4±8.1 min/day in total PA and MVPA, respectively. Across four domains, ten and five potential correlates were found to be significant in univariate analyses for MVPA and total PA, respectively. In the final model, functional capacity, PA readiness, and participation in regular exercise were positively associated with MVPA (R(2) =26.6%). Functional capacity and PA readiness were also positively associated with total PA (R(2) =15.9%). Future initiatives to increase PA levels in cardiac patients could be improved by considering patients' functional capacity, PA readiness, and exercise history in designing interventions.

Physical activity in preschool children: comparison between Montessori and traditional preschools

BACKGROUND

Little is known about the influence of Montessori methods on children's physical activity (PA). This cross-sectional study compared PA of children attending Montessori and traditional preschools.

METHODS

We enrolled 301 children in 9 Montessori and 8 traditional preschools in Columbia, South Carolina. PA was measured by accelerometry on weekdays during preschool (In-School), non-school (Non-School), and all day (All Day). Minutes/hour of light, moderate-to-vigorous (MVPA), and total PA (light + MVPA) were calculated.

RESULTS

Children attending Montessori preschools accumulated more In-School light (7.7 vs. 6.5 minute/hour), MVPA (7.7 versus 6.5 minute/hour), and total PA (15.4 versus 13.0 minute/hour) than children attending traditional preschools, after adjusting for sex, race/ethnicity, body mass index, parent education and neighborhood poverty index. For Non-School (8.5 versus 6.2 minute/hour) and All Day (8.5 versus 7.6 minute/hour), children in Montessori preschools accumulated more MVPA than children in traditional preschools. In-School PA was higher for children in private Montessori than public Montessori preschools (8.1 versus 7.0 minute/hour; 8.1 versus 6.7 minute/hour; 16.1 versus 13.6 minute/hour, for light, MVPA, and total PA, respectively).

CONCLUSIONS

Children attending Montessori preschools were more active than children attending traditional preschools. Adopting the Montessori system may be an important strategy for promoting PA in children.

Intermonitor reliability of the GT3X+ accelerometer at hip, wrist and ankle sites during activities of daily living

The triaxial GT3X+ accelerometer can measure activity counts in the vertical, horizontal right to left, horizontal front to back planes, and can generate a summative score of the three axes represented by vector magnitude (VM). Information on the reliability of the GT3X+ at the hip, wrist and ankle sites, over all axes and VM during activities of daily living (ADL) is lacking in the literature. Forty healthy adults (14 men and 26 women) were randomly assigned to perform 10 of 20 ADL (consisting of sedentary, housework, yard work, locomotive and recreational activities) while wearing two monitors on the hip, wrist and ankle. Subjects performed each ADL over 7 min and the mean activity counts during the last 4 min were used for analyses. Average intraclass correlations between monitors were high for the three sites for each axis and VM (hip: 0.943, 0.857, 0.864 and 0.966, respectively; wrist: 0.994, 0.963, 0.961 and 0.989, respectively; ankle: 0.977, 0.979, 0.927 and 0.986, respectively). These data suggest that GT3X+ accelerometers measurements made from the hip, wrist and ankle sites are reliable during ADL across all axes and VM.

Precision of total and regional body fat estimates from dual-energy X-ray absorptiometer measurements

OBJECTIVES

To evaluate the precision of both total %fat and all the regional %fat measures acquired from both the Lunar Prodigy and Lunar iDXA software.

DESIGN

Cross-sectional study.

SETTING

University-based research laboratory.

PARTICIPANTS

The sample consisted of 300 individual test records from men and women who had volunteered to participate in dual-energy x-ray absorptiometer (DXA) technician precision training studies. Subjects ranged in age from 20-84 years and in body mass index from 15.7-52.0 kg.m-2.

MEASUREMENTS

A total of 27 different technicians performed three total body scan measurements on 10-15 different subjects. The Lunar Prodigy and Lunar iDXA were used for 253 and 47 precision training evaluations, respectively. The regions of interest (ROI) were automatically determined by the enCORE software (autoROI) for total body, android, gynoid, trunk, legs, and arms regions and the region %fat data were used for analyses.

RESULTS

The CV for total body %fat was 1.9% and 0.9% for the Prodigy and iDXA, respectively. CV's for %fat measures at regional sites ranged from 1.2-4.4% for the Prodigy measures and 0.9-2.4% for the iDXA measures. The ICC for both devices ranged from 0.990 to 0.999.

CONCLUSION

Monitoring the status of body composition changes with age is gaining more clinical acceptance. Thus, it is important that practitioners use measures that are both precise and accurate. The findings from the current study add support that DXA measurements can be used with a high level of confidence for serial testing of patients.