24 h Accelerometry: impact of sleep-screening methods on estimates of sedentary behaviour and physical activity while awake

Losing sleep influences dietary intake in children: a longitudinal compositional analysis of a randomised crossover trial

BACKGROUND

Although inadequate sleep increases the risk of obesity in children, the mechanisms remain unclear. The aims of this study were to assess how sleep loss influenced dietary intake in children while accounting for corresponding changes in sedentary time and physical activity; and to investigate how changes in time use related to dietary intake.

METHODS

A randomized crossover trial in 105 healthy children (8-12 years) with normal sleep (~ 8-11 h/night) compared sleep extension (asked to turn lights off one hour earlier than usual for one week) and sleep restriction (turn lights off one hour later) conditions, separated by a washout week. 24-h time-use behaviors (sleep, wake after sleep onset, physical activity, sedentary time) were assessed using waist-worn actigraphy and dietary intake using two multiple-pass diet recalls during each intervention week. Longitudinal compositional analysis was undertaken with mixed effects regression models using isometric log ratios of time use variables as exposures and dietary variables as outcomes, and participant as a random effect.

RESULTS

Eighty three children (10.2 years, 53% female, 62% healthy weight) had 47.9 (SD 30.1) minutes less sleep during the restriction week but were also awake for 8.5 (21.4) minutes less at night. They spent this extra time awake in the day being more sedentary (+ 31 min) and more active (+ 21 min light physical activity, + 4 min MVPA). After adjusting for all changes in 24-h time use, losing 48 min of sleep was associated with consuming significantly more energy (262 kJ, 95% CI:55,470), all of which was from non-core foods (314 kJ; 43, 638). Increases in sedentary time were related to increased energy intake from non-core foods (177 kJ; 25, 329) whereas increases in MVPA were associated with higher intake from core foods (72 kJ; 7,136). Changes in diet were greater in female participants.

CONCLUSION

Loss of sleep was associated with increased energy intake, especially of non-core foods, independent of changes in sedentary time and physical activity. Interventions focusing on improving sleep may be beneficial for improving dietary intake and weight status in children.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ANZCTR ACTRN12618001671257, Registered 10th Oct 2018, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=367587&isReview=true.

Predictors for achieving optimal sleep in healthy children: Exploring sleep patterns in a sleep extension trial

STUDY OBJECTIVES

Earlier bedtimes can help some children get more sleep, but we don't know which children, or what features of their usual sleep patterns could predict success with this approach. Using data from a randomized crossover trial of sleep manipulation, we sought to determine this.

METHODS

Participants were 99 children aged 8-12years (49.5% female) with no sleep disturbances. Sleep was measured by actigraphy at baseline and over a restriction or extension week (1 hour later or earlier bedtime respectively), randomly allocated and separated by a washout week. Data were compared between baseline (week 1) and extension weeks only (week 3 or 5), using linear or logistic regression analyses as appropriate, controlling for randomization order.

RESULTS

One hour less total sleep time than average at baseline predicted 29.7 minutes (95% CI: 19.4, 40.1) of sleep gained and 3.45 (95% CI: 1.74, 6.81) times higher odds of successfully extending sleep by >30 minutes. Per standardized variable, less total sleep time and a shorter sleep period time were the strongest predictors (significant odds ratios (ORs) of 2.51 and 2.28, respectively). Later sleep offset, more variability in sleep timing and lower sleep efficiency also predicted sleep gains. The sleep period time cut-point that optimized prediction of successful sleep gains was <8 hours 28 minutes with 75% of children's baseline sleep in that range.

CONCLUSIONS

Children with a baseline sleep period time <8½ hours a night obtained the most sleep from earlier bedtimes maintained over a week, demonstrating experimentally the value of earlier bedtimes to improve sleep.

CLINICAL TRIALS REGISTRY

Australian New Zealand Clinical Trial Registry, ACTRN12618001671257, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=367587&isReview=true.

Does Wrist-Worn Accelerometer Wear Compliance Wane over a Free-Living Assessment Period? An NHANES Analysis

PURPOSE

Accelerometers are used to objectively measure physical behaviors in free-living environments, typically for seven consecutive days or more. We examined whether participants experience "wear fatigue," a decline in wear time day over day, during typical assessment period acquired in a nationally representative sample of 6- to 80-yr-olds in the United States.

METHODS

Participants were instructed to wear an ActiGraph GT3X+ on their nondominant wrist continuously for seven consecutive days. Participants with seven complete days of recorded data, regardless of wear status, were included in the analyses ( N = 13,649). Wear was scored with the sleep, wake, and nonwear algorithm.

RESULTS

Participants averaged 1248 ± 3.6 min·d -1 (mean ± SE) of wear over the assessment, but wear time linearly decreased from day 1 (1295 ± 3.2 min) to day 7 (1170 ± 5.3 min), resulting in a wear fatigue of -18.1 ± 0.7 min·d -1 ( β ± SE). Wear fatigue did not differ by sex but varied by age-group-highest in adolescents (-26.8 ± 2.4 min·d -1 ) and lowest in older adults (-9.3 ± 0.9 min·d -1 ). Wear was lower in evening (1800-2359 h) and early morning (0000-0559 h) compared with the middle of the day and on weekend days compared with weekdays. We verified similar wear fatigue (-23.5 ± 0.7 min·d -1 ) in a separate sample ( N = 14,631) with hip-worn devices and different wear scoring. Applying minimum wear criteria of ≥10 h·d -1 for ≥4 d reduced wear fatigue to -5.3 and -18.7 min·d -1 for the wrist and hip, respectively.

CONCLUSIONS

Patterns of wear suggest noncompliance may disproportionately affect estimates of sleep and sedentary behavior, particularly for adolescents. Further study is needed to determine the effect of wear fatigue on longer assessments.

A comparative study of different sleep assessment methods for preschool children

PURPOSE

This study aimed to examine the differences between different sleep assessment methods for preschool children.

METHODS

Preschool children (n = 54, mean age: 4.6 years) were recruited from kindergarten. Data were collected using an accelerometer, a sleep log, and sleep questionnaire. Furthermore, correlation analysis, Bland-Altman analysis, and repeated measures ANOVA were performed.

RESULTS

(1) The sleep duration evaluated by different sleep assessment methods were all significantly correlated, among which the sleep log and Sadeh algorithm showed the highest correlation (r = 0.972, p < .001), while the Tudor-Locke algorithm and the sleep questionnaire demonstrated the lowest correlation (r = 0.383, p < .01); (2) The points between different sleep assessment methods were all within 95% LoA, except for the sleep log and Tudor-Locke algorithm; (3) In various methods of sleep assessment, significant differences were observed in sleep onset (F2 (1.6,85.0)  = 32.8, p < .001, η2 : 0.38), while no significant differences were observed in sleep offset (F2 (1.5,80.1)  = 32.8, p = .05, η2 : 0.05); (4) In addition, no significant difference in sleep onset was observed between the sleep questionnaire and sleep log (p > .05), and there was also no significant difference in sleep onset between the Sadeh algorithm and the Tudor-Locke algorithm (p > .05).

CONCLUSIONS

Both the Sadeh algorithm and the Tudor-Locke algorithm can be used as effective algorithms for sleep duration assessment of Chinese preschool children, with the latter having obvious advantages in large sample surveys. Future research should pay attention to the differences between different sleep assessment methods when using these algorithms.

Where does the time go when children don't sleep? A randomized crossover study

OBJECTIVE

This study aimed to describe how mild sleep deprivation in children changes time spent physically active and sedentary.

METHODS

In 2018 through 2020, children (n = 105) with normal sleep were randomized to go to bed 1 hour earlier (extension) or 1 hour later (restriction) than their usual bedtime for 1 week, each separated by a 1-week washout. Twenty-four-hour movement behaviors were measured with waist-worn actigraphy and expressed in minutes and proportions (percentages). Mixed-effects regression models determined mean differences in time use (95% CI) between conditions. Time gained from sleep lost that was reallocated to other movement behaviors in the 24-hour day was modeled using regression.

RESULTS

Children (n = 96) gained ~49 minutes of awake time when sleep was restricted compared with extended. This time was mostly reallocated to sedentary behavior (28 minutes; 95% CI: 19-37), followed by physical activity (22 minutes; 95% CI: 14-30). When time was expressed as a percentage, the overall composition of movement behavior remained similar across both sleep conditions.

CONCLUSIONS

Children were not less physically active when mildly sleep deprived. Time gained from sleeping less was proportionally, rather than preferentially, reallocated to sedentary time and physical activity. These findings suggest that decreased physical activity seems unlikely to explain the association between short sleep and obesity in children.

Effect of Sleep Changes on Health-Related Quality of Life in Healthy Children: A Secondary Analysis of the DREAM Crossover Trial

IMPORTANCE

Little is known regarding the effect of poor sleep on health-related quality of life (HRQOL) in healthy children.

OBJECTIVE

To determine the effect of induced mild sleep deprivation on HRQOL in children without major sleep issues.

DESIGN, SETTING, AND PARTICIPANTS

This prespecified secondary analysis focused on HRQOL, a secondary outcome of the Daily Rest, Eating, and Activity Monitoring (DREAM) randomized crossover trial of children who underwent alternating weeks of sleep restriction and sleep extension and a 1-week washout in between. The DREAM trial intervention was administered at participants' homes between October 2018 and March 2020. Participants were 100 children aged 8 to 12 years who lived in Dunedin, New Zealand; had no underlying medical conditions; and had parent- or guardian-reported normal sleep (8-11 hours/night). Data were analyzed between July 4 and September 1, 2022.

INTERVENTIONS

Bedtimes were manipulated to be 1 hour later (sleep restriction) and 1 hour earlier (sleep extension) than usual for 1 week each. Wake times were unchanged.

MAIN OUTCOMES AND MEASURES

All outcome measures were assessed during both intervention weeks. Sleep timing and duration were assessed using 7-night actigraphy. Children and parents rated the child's sleep disturbances (night) and impairment (day) using the 8-item Pediatric Sleep Disturbance and 8-item Sleep-Related Impairment scales of the Patient-Reported Outcomes Measurement Information System questionnaire. Child-reported HRQOL was assessed using the 27-item KIDSCREEN questionnaire with 5 subscale scores and a total score. Both questionnaires assessed the past 7 days at the end of each intervention week. Data were presented as mean differences and 95% CIs between the sleep restriction and extension weeks and were analyzed using intention to treat and an a priori difference in sleep of at least 30 minutes per night.

RESULTS

The final sample comprised 100 children (52 girls [52%]; mean [SD] age, 10.3 [1.4] years). During the sleep restriction week, children went to sleep 64 (95% CI, 58-70) minutes later, and sleep offset (wake time) was 18 (95% CI, 13-24) minutes later, meaning that children received 39 (95% CI, 32-46) minutes less of total sleep per night compared with the sleep extension week in which the total sleep time was 71 (95% CI, 64-78) minutes less in the per-protocol sample analysis. Both parents and children reported significantly less sleep disturbance at night but greater sleep impairment during the day with sleep restriction. Significant standardized reductions in physical well-being (standardized mean difference [SMD], -0.28; 95% CI, -0.49 to -0.08), coping in a school environment (SMD, -0.26; 95% CI, -0.42 to -0.09), and total HRQOL score (SMD, -0.21; 95% CI, -0.34 to -0.08) were reported by children during sleep restriction, with an additional reduction in social and peer support (SMD, -0.24; 95% CI, -0.47 to -0.01) in the per-protocol sample analysis.

CONCLUSIONS AND RELEVANCE

Results of this secondary analysis of the DREAM trial indicated that even 39 minutes less of sleep per night for 1 week significantly reduced several facets of HRQOL in children. This finding shows that ensuring children receive sufficient good-quality sleep is an important child health issue.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry: ACTRN12618001671257.

Investigating the moderators and mediators of an effective sleep intervention in the Prevention of Overweight in Infancy (POI) randomized controlled trial: Exploratory analyses

The Prevention of Overweight in Infancy (POI) sleep intervention halved obesity risk at 2 years of age. However, the intervention mechanisms are unclear. Consequently, the objective of the current work was to use exploratory analyses to investigate potential moderators and mediators of the sleep intervention on obesity outcomes at age 2 years. Data were collected between 2009 and 2012. The effect of demographic and study design variables on body mass index z-score (BMI z-score) and obesity was compared in moderator subgroups at 2 years of age (n = 683, 85%). Mediating effects of child and parent-household variables assessed whether the sleep intervention resulted in meaningful changes in the mediating variable (defined as changes which were statistically significant [p < .05] or where the effect size was ≥0.15 SD), followed by assessing relationships with obesity outcomes. The sleep intervention appeared most effective in children in higher deprivation areas (effect on BMI z-score -0.25 [-0.53, 0.04], effect on obesity odds ratio [OR] 0.43 [0.16, 1.13]), and with mothers of non-European, non-Māori ethnicity (effect on BMI z-score -0.27 [-0.73, 0.20], effect on obesity OR 0.13 [95% confidence interval 0.01, 1.11]). This suggested moderation by deprivation and ethnicity. Aspects of sleep improved meaningfully in children after intervention but did not significantly relate to obesity outcomes, and other outcomes were not meaningfully affected by the sleep intervention. Thus, mediation was not indicated. Overall, the POI sleep intervention improved obesity outcomes at 2 years, and the current work identified some potential moderators, but no mediators.

Importance of characterising sleep breaks within the 24-h movement behaviour framework

Accelerometers measure the acceleration of the body part they are attached and allow to estimate time spent in activity levels (sedentary behaviour, light, and moderate-to-vigorous physical activity) and sleep over a 24-h period for several consecutive days. These advantages come with the challenges to analyse the large amount of data while integrating dimensions of both physical activity/sedentary behaviour and sleep domains. This commentary raises the questions of 1) how to classify sleep breaks (i.e. wake after sleep onset) during the night within the 24-h movement behaviour framework and 2) how to assess their impact on health while also accounting for night time sleep duration and time in sedentary behaviour and physical activity during the day. The authors advocate for future collaborations between researchers from the physical activity/sedentary behaviour and sleep research fields to ensure appropriate analysis and interpretation of the tremendous amount of data recorded by the newer generation accelerometers. This is the only way forward to provide meaningfully accurate evidence to inform future 24-h movement behaviour guidelines.

Adherence to 24-h movement behavior guidelines and psychosocial functioning in young children: a longitudinal analysis

BACKGROUND

A recent paradigm shift has highlighted the importance of considering how sleep, physical activity and sedentary behaviour work together to influence health, rather than examining each behaviour individually. We aimed to determine how adherence to 24-h movement behavior guidelines from infancy to the preschool years influences mental health and self-regulation at 5 years of age.

METHODS

Twenty-four hour movement behaviors were measured by 7-day actigraphy (physical activity, sleep) or questionnaires (screen time) in 528 children at 1, 2, 3.5, and 5 years of age and compared to mental health (anxiety, depression), adaptive skills (resilience), self-regulation (attentional problems, hyperactivity, emotional self-control, executive functioning), and inhibitory control (Statue, Head-Toes-Knees-Shoulders task) outcomes at 5 years of age. Adjusted standardised mean differences (95% CI) were determined between those who did and did not achieve guidelines at each age.

RESULTS

Children who met physical activity guidelines at 1 year of age (38.7%) had lower depression (mean difference [MD]: -0.28; 95% CI: -0.51, -0.06) and anxiety (MD: -0.23; 95% CI: -0.47, 0.00) scores than those who did not. At the same age, sleeping for 11-14 h or having consistent wake and sleep times was associated with lower anxiety (MD: -0.34; 95% CI: -0.66, -0.02) and higher resilience (MD: 0.35; 95% CI: 0.03, 0.68) scores respectively. No significant relationships were observed at any other age or for any measure of self-regulation. Children who consistently met screen time guidelines had lower anxiety (MD: -0.43; 95% CI: -0.68, -0.18) and depression (MD: -0.36; 95% CI: -0.62, -0.09) scores at 5. However, few significant relationships were observed for adherence to all three guidelines; anxiety scores were lower (MD: -0.42; 95% CI: -0.72, -0.12) in the 20.2% who adhered at 1 year of age, and depression scores were lower (MD: -0.25; 95% CI: -0.48, -0.02) in the 36.7% who adhered at 5 years of age compared with children who did not meet all three guidelines.

CONCLUSIONS

Although adherence to some individual movement guidelines at certain ages throughout early childhood was associated with improved mental health and wellbeing at 5 years of age, particularly reduced anxiety and depression scores, there was little consistency in these relationships. Future work should consider a compositional approach to 24-h time use and how it may influence mental wellbeing.

TRIAL REGISTRATION

ClinicalTrials.gov number NCT00892983.

Is achieving 7,000 steps/day cross-sectionally and prospectively associated with older adults' lower-extremity performance?

Background

Evidence regarding the association between daily steps recommendation and older adults’ lower limb strength is lacking; thus, this study investigated whether taking at least 7,000 steps/day is cross-sectionally and prospectively related to lower-extremity performance in older Taiwanese adults.

Methods

There were 89 community-dwelling adults aged over 60 years (mean age: 69.5 years) attending both baseline and follow-up surveys. This study used adjusted logistic regression analysis to explore cross-sectional and prospective relationships between their accelerometer-assessed daily steps and lower-extremity performance (five-times-sit-to-stand test).

Results

This study found the older adults who took 7,000 steps/day were more likely to have better lower-extremity performance cross-sectionally (odds ratio [OR] = 3.82; 95 % confidence interval [CI]: 1.04, 13.95; p = 0.04), as well as to maintain or increase their lower-extremity performance prospectively (OR = 3.53; 95 % CI: 1.05, 11.84; p = 0.04).

Conclusions

Our findings support a minimum recommended level of step-based physical activity for older adults, namely, 7,000 steps/day, as beneficial for maintaining or increasing older adults’ lower-extremity performance.

The MiaoMiao study: can do-it-yourself continuous glucose monitoring technology improve fear of hypoglycaemia in parents of children affected by type 1 diabetes?

Purpose

Type 1 diabetes (T1D) is one of the most common chronic diseases of childhood and comes with considerable management and psychological burden for children and their families. Fear of hypoglycaemia (FOH), particularly nocturnal hypoglycaemia, is a common worry. Continuous glucose monitoring (CGM) is a tool that may help reduce FOH, as well as reduce overall diabetes burden. However, CGM systems are expensive and often not publicly funded or subsidised. MiaoMiao (MM) is a novel relatively affordable third-party add-on technology to intermittently scanned CGM (isCGM). MM allows users to convert their isCGM to a form of "Do-it-yourself" (DIY)-CGM. Our hypothesis is that MM-CGM will result in significant reduction in parental fear from hypoglycaemia. The primary objective is to determine the impact of real-time DIY-CGM on parental fear of hypoglycaemia using Hypoglycaemia Fear Survey (HFS).

Methods

This is a multisite randomised cross-over study of 55 New Zealand children (ages 2-13 years) with established T1D and current users of isCGM (Abbott FreeStyle Libre). DIY-CGM will be compared to usual care with isCGM. Participants will be randomised to either arm of the study for 6 weeks followed by a 4-week wash-out period before crossing over to the other study arm for a further 6 weeks.

Discussion

The results of this study will provide much needed clinical trial data regarding DIY-CGM effectiveness in reducing parental FOH, as measured by HFS, as well as various other secondary outcomes including traditional glycaemic metrics, and child and caregiver sleep. The trial was registered with the Australian New Zealand Clinical Trials Registry (ACTRN 12619001551189) on 18 November 2019, and the World Health Organisation International Clinical Trial Registry Platform (Universal Trial Number U1111-1236-9189).

Identifying bedrest using waist-worn triaxial accelerometers in preschool children

Purpose

To adapt and validate a previously developed decision tree for youth to identify bedrest for use in preschool children.

Methods

Parents of healthy preschool (3-6-year-old) children (n = 610; 294 males) were asked to help them to wear an accelerometer for 7 to 10 days and 24 hours/day on their waist. Children with ≥3 nights of valid recordings were randomly allocated to the development (n = 200) and validation (n = 200) groups. Wear periods from accelerometer recordings were identified minute-by-minute as bedrest or wake using visual identification by two independent raters. To automate visual identification, chosen decision tree (DT) parameters (block length, threshold, bedrest-start trigger, and bedrest-end trigger) were optimized in the development group using a Nelder-Mead simplex optimization method, which maximized the accuracy of DT-identified bedrest in 1-min epochs against synchronized visually identified bedrest (n = 4,730,734). DT's performance with optimized parameters was compared with the visual identification, commonly used Sadeh’s sleep detection algorithm, DT for youth (10-18-years-old), and parental survey of sleep duration in the validation group.

Results

On average, children wore an accelerometer for 8.3 days and 20.8 hours/day. Comparing the DT-identified bedrest with visual identification in the validation group yielded sensitivity = 0.941, specificity = 0.974, and accuracy = 0.956. The optimal block length was 36 min, the threshold 230 counts/min, the bedrest-start trigger 305 counts/min, and the bedrest-end trigger 1,129 counts/min. In the validation group, DT identified bedrest with greater accuracy than Sadeh’s algorithm (0.956 and 0.902) and DT for youth (0.956 and 0.861) (both P<0.001). Both DT (564±77 min/day) and Sadeh’s algorithm (604±80 min/day) identified significantly less bedrest/sleep than parental survey (650±81 min/day) (both P<0.001).

Conclusions

The DT-based algorithm initially developed for youth was adapted for preschool children to identify time spent in bedrest with high accuracy. The DT is available as a package for the R open-source software environment (“PhysActBedRest”).

Comparing the activPAL software's Primary Time in Bed Algorithm against Self-Report and van der Berg's Algorithm

The purpose of this study was to compare activPAL algorithm-estimated values for time in bed (TIB), wake time (WT) and bedtime (BT) against self-report and an algorithm developed by van der Berg and colleagues. Secondary analyses of baseline data from the Community Activity for Prevention Study (CAPS) were used in which adults ≥ 18 years wore the activPAL for seven days. Mixed-effects models compared differences between TIB, WT, and BT for all three methods. Bland-Altman plots examined agreement and the two-one-sided test examined equivalence. activPAL was not equivalent to self-report or van der Berg in estimating TIB, but was equivalent to self-report for estimating BT, and was equivalent to van der Berg for estimating WT. The activPAL algorithm requires adjustments before researchers can use it to estimate TIB. However, researchers can use activPAL's option to manually enter self-reported BT and WT to estimate TIB and better understand 24-hour movement patterns.

Comparison of Sedentary Time Between Thigh-Worn and Wrist-Worn Accelerometers

Background: The accuracy of wrist-worn accelerometers in identifying sedentary time has been scarcely studied in free-living conditions. The aim of this study was to compare daily sedentary time estimates between a thigh-worn accelerometer, which measured sitting and lying postures, and a wrist-worn accelerometer, which measured low levels of movement. Methods: The study population consisted of 259 participants (Mage = 62.8 years, SD = 0.9) from the Finnish Retirement and Aging Study (FIREA). Participants wore an Axivity AX3 accelerometer on their mid-thigh and an Actigraph wActiSleep-BT accelerometer on their non-dominant wrist simultaneously for a minimum of 4 days in free-living conditions. Two definitions to estimate daily sedentary time were used for data from the wrist-worn accelerometer: 1) the count cutpoint, ≤1853 counts per minute; and 2) the Euclidean Norm Minus One (ENMO) cutpoint, <30 mg. Results: Compared to the thigh-worn accelerometer, daily sedentary time estimate was 63 min (95% confidence interval [CI] = −53 to −73) lower by the count cutpoint and 50 min (95% CI = 34 to 67) lower by the ENMO cutpoint. The limits of agreement in daily sedentary time estimates between the thigh- and cutpoint methods for wrist-worn accelerometers were wide (the count cutpoint: −117 to 243, the ENMO cutpoint: −212 to 313 min). Conclusions: Currently established cutpoint-based methods to estimate sedentary time from wrist-worn accelerometers result in underestimation of daily sedentary time compared to posture-based estimates of thigh-worn accelerometers. Thus, sedentary time estimates obtained from wrist-worn accelerometers using currently available cutpoint-based methods should be interpreted with caution and future work is needed to improve their accuracy.

Objectively assessed physical activity patterns and physical function in community-dwelling older adults: a cross-sectional study in Taiwan

OBJECTIVES

To objectively assess light physical activity (PA), moderate-to-vigorous PA (MVPA), step counts and number of 10 min MVPA bouts and their association with physical function among older adults.

DESIGN

Cross-sectional design.

SETTING

Urban community setting in Taiwan.

PARTICIPANTS

127 Taiwanese older adults aged over 65 years (mean age=70.8±5.3 years; 72% women).

PRIMARY AND SECONDARY OUTCOME MEASURES

Triaxial accelerometers were used to measure PA variables for 10 hours/day for seven consecutive days. Then, five physical function components (handgrip strength, single-leg stance, 5-metre walk speed, timed up and go and sit-to-stand test) were measured. Multiple linear regressions were used to perform separate analyses for older men and women.

RESULTS

For older women, daily MVPA time (β: 0.39, 95% CI: 0.12, 0.64; p=0.004), daily step counts (β: 0.46, 95% CI: 0.12, 0.78; p=0.009) and number of 10 min MVPA bouts (β: 0.27, 95% CI: 0.001, 0.53; p=0.049) were positively associated with handgrip strength after adjusting for accelerometer wear time, sedentary time and other confounders. Furthermore, daily MVPA time was positively associated with a single-leg stance (β: 0.25, 95% CI: 0.02, 0.49; p=0.036) and higher daily step counts were associated with shorter walking speed performance (β: -0.31, 95% CI: -0.57, -0.001; p=0.049). None of the variables of the objectively assessed PA patterns was associated with physical function outcomes among older men due to their small sample size.

CONCLUSIONS

Daily MVPA, MVPA bouts of at least 10 min and accumulated daily steps are important for improving physical function among older women. Future prospective research should establish causal associations between PA patterns and functional ability among older adults.

Prevalence and socio-demographic correlates of accelerometer measured physical activity levels of school-going children in Kampala city, Uganda

Background

The current international physical activity guidelines for health recommend children to engage in at least 60 minutes of moderate-to-vigorous physical activity (MVPA) daily. Yet, accurate prevalence estimates of physical activity levels of children are unavailable in many African countries due to the dearth of accelerometer-measured physical activity data. The aim of this study was to describe the prevalence and examine the socio-demographic correlates of accelerometer-measured physical activity among school-going children in Kampala city, Uganda.

Methods

A cross-sectional study design was used to recruit a sample of 10–12 years old school-going children (n = 256) from 7 primary schools (3 public schools and 4 private schools) in Kampala city, Uganda. Sedentary time, light-intensity physical activity (LPA), moderate-intensity physical activity (MPA) and vigorous-intensity physical activity (VPA) were measured by accelerometers (ActiGraph GT3X+ [Pensacola, Florida, USA]) over a seven-day period. Socio-demographic factors were assessed by a parent/guardian questionnaire. Weight status was generated from objectively measured height and weight and computed as body mass index (BMI). Multi-level logistic regressions identified socio-demographic factors that were associated with meeting physical activity guidelines.

Results

Children’s sedentary time was 9.8±2.1 hours/day and MVPA was 56±25.7 minutes/day. Only 36.3% of the children (38.9% boys, 34.3% girls) met the physical activity guidelines. Boys, thin/normal weight and public school children had significantly higher mean daily MVPA levels. Socio-demographic factors associated with odds of meeting physical activity guidelines were younger age (OR = 0.68; 95% CI = 0.55–0.84), thin/normal weight status (OR = 4.08; 95% CI = 1.42–11.76), and socioeconomic status (SES) indicators such as lower maternal level of education (OR = 2.43; 95% CI = 1.84–3.21) and no family car (OR = 0.31; 95% CI = 0.17–0.55).

Conclusion

Children spent a substantial amount of time sedentary and in LPA and less time in MVPA. Few children met the physical activity guidelines. Lower weight status, lower maternal education level and no family car were associated with meeting physical activity guidelines. Effective interventions and policies to increase physical activity among school-going children in Kampala, are urgently needed.

Semisupervised Physical Exercise and Lifestyle Counseling in Cardiometabolic Risk Management in Sedentary Adults: Controlled Randomized Trial (BELLUGAT)

BACKGROUND

The purpose of this study was to evaluate the feasibility and effectiveness of a high-intensity semisupervised exercise program alongside lifestyle counseling as an intervention for managing cardiometabolic risk in sedentary adults.

METHODS

A 40-week 3-arm randomized controlled clinical trial (16-wk intervention and 24-wk follow-up) was used. Seventy-five sedentary adults (34-55 y) with at least 1 cardiometabolic risk factor were randomized into one of the following arms: (1) aerobic interval training (AIT) plus lifestyle counseling (n = 25), (2) low- to moderate-intensity continuous training plus lifestyle counseling (traditional continuous training, TCT) (n = 27), or (3) lifestyle counseling alone (COU) (n = 23). Metabolic syndrome severity scores, accelerometer-based physical activity, and self-reported dietary habits were assessed at baseline, after the intervention, and at follow-up.

RESULTS

AIT was well accepted with high enjoyment scores. All groups showed similar improvements in metabolic syndrome severity scores (standardized effect size = 0.46) and dietary habits (standardized effect size = 0.30). Moderate to vigorous physical activity increased in all study groups, with the number of responders higher in AIT and TCT groups (50%) than in COU group (21%). Both AIT and TCT had a greater impact on sedentary behavior than COU (63.5% vs 30.4% responders).

CONCLUSIONS

AIT appears to be a feasible and effective strategy in sedentary individuals with cardiometabolic risk factors. AIT could be included in intervention programs tackling unhealthy lifestyles.

Intermittent fasting, Paleolithic, or Mediterranean diets in the real world: exploratory secondary analyses of a weight-loss trial that included choice of diet and exercise

BACKGROUND

Intermittent fasting (IF) and Paleolithic (Paleo) diets produce weight loss in controlled trials, but minimal evidence exists regarding long-term efficacy under free-living conditions without intense dietetic support.

OBJECTIVES

This exploratory, observational analysis examined adherence, dietary intake, weight loss, and metabolic outcomes in overweight adults who could choose to follow Mediterranean, IF, or Paleo diets, and standard exercise or high-intensity interval training (HIIT) programs, as part of a 12-mo randomized controlled trial investigating how different monitoring strategies influenced weight loss (control, daily self-weighing, hunger training, diet/exercise app, brief support).

METHODS

A total of 250 overweight [BMI (in kg/m2) ≥27] healthy adults attended an individualized dietary education session (30 min) relevant to their self-selected diet. Dietary intake (3-d weighed diet records), weight, body composition, blood pressure, physical activity (0, 6, and 12 mo), and blood indexes (0 and 12 mo) were assessed. Mean (95% CI) changes from baseline were estimated using regression models. No correction was made for multiple tests.

RESULTS

Although 54.4% chose IF, 27.2% Mediterranean, and 18.4% Paleo diets originally, only 54% (IF), 57% (Mediterranean), and 35% (Paleo) participants were still following their chosen diet at 12 mo (self-reported). At 12 mo, weight loss was -4.0 kg (95% CI: -5.1, -2.8 kg) in IF, -2.8 kg (-4.4, -1.2 kg) in Mediterranean, and -1.8 kg (-4.0, 0.5 kg) in Paleo participants. Sensitivity analyses showed that, due to substantial dropout, these may be overestimated by ≤1.2 kg, whereas diet adherence increased mean weight loss by 1.1, 1.8, and 0.3 kg, respectively. Reduced systolic blood pressure was observed with IF (-4.9 mm Hg;  -7.2, -2.6 mm Hg) and Mediterranean (-5.9 mm Hg; -9.0, -2.7 mm Hg) diets, and reduced glycated hemoglobin with the Mediterranean diet (-0.8 mmol/mol; -1.2, -0.4 mmol/mol). However, the between-group differences in most outcomes were not significant and these comparisons may be confounded due to the nonrandomized design.

CONCLUSIONS

Small differences in metabolic outcomes were apparent in participants following self-selected diets without intensive ongoing dietary support, even though dietary adherence declined rapidly. However, results should be interpreted with caution given the exploratory nature of analyses. This trial was registered with the Australian New Zealand Clinical Trials Registry as ACTRN12615000010594 at https://www.anzctr.org.au.

Quantity versus quality of objectively measured sleep in relation to body mass index in children: cross-sectional and longitudinal analyses

BACKGROUND/OBJECTIVES

Although sleep duration is well established as a risk factor for child obesity, how measures of sleep quality relate to body size is less certain. The aim of this study was to determine how objectively measured sleep duration, sleep timing, and sleep quality were related to body mass index (BMI) cross-sectionally and longitudinally in school-aged children.

SUBJECTS/METHODS

All measures were obtained at baseline, 12 and 24 months in 823 children (51% female, 53% European, 18% Māori, 12% Pacific, 9% Asian) aged 6-10 years at baseline. Sleep duration, timing, and quality were measured using actigraphy over 7 days, height and weight were measured using standard techniques, and parents completed questionnaires on demographics (baseline only), dietary intake, and television usage. Data were analysed using imputation; mixed models, with random effects for person and age, estimated both a cross-sectional effect and a longitudinal effect on BMI z-score, adjusted for multiple confounders.

RESULTS

The estimate of the effect on BMI z-score for each additional hour of sleep was -0.22 (95% CI: -0.33, -0.11) in cross-sectional analyses and -0.05 (-0.10, -0.004) in longitudinal analyses. A greater effect was observed for weekday sleep duration than weekend sleep duration but variability in duration was not related to BMI z-score. While sleep timing (onset or midpoint of sleep) was not related to BMI, children who were awake in the night more frequently (0.19; 0.06, 0.32) or for longer periods (0.18; 0.06, 0.36) had significantly higher BMI z-scores cross-sectionally, but only the estimates for total time awake (minutes) were significant longitudinally (increase in BMI z-score of 0.04 for each additional hour awake).

CONCLUSION

The beneficial effect of a longer sleep duration on BMI was consistent in children, whereas evidence for markers of sleep quality and timing were more variable.

Physical activity, sedentary time and cardiometabolic health indicators among Mexican children

We examined the independent associations of moderate to vigorous physical activity (MVPA) and sedentary time (ST) with cardiometabolic indicators in Mexican children (4-6 years of age). We conducted a cross-sectional study (n = 400) using the measures of MVPA and ST (7-day accelerometry) and the following indicators: % body fat, waist circumference, body mass index (BMI) z-score, glycated haemoglobin, blood glucose, triglycerides, total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, leptin, adiponectin and resting blood pressure. We examined the independent associations of MVPA and ST with cardiometabolic indicators through confounder-adjusted and mutually adjusted (including both MVPA and ST) linear regression models. Confounder-adjusted models showed that MVPA was associated with higher BMI z-scores and lower adiponectin levels in girls and lower body fat among boys. ST was associated with higher body fat, in the full sample, and lower LDL cholesterol among boys. After mutually adjusting for MVPA and ST, MVPA (10-minute increase) remained significantly associated with BMI z-score in girls (β = 0.187, 95% CI: 0.019, 0.356) and ST (60-minute increase) remained significantly associated with higher body fat (β = 1.11%, 95% CI: 0.019, 2.203) among boys and higher glycated haemoglobin (β = 0.047% points, 95% CI: 0.000, 0.094) in the full sample. In preschool-aged children, the objective measures of ST and MVPA were associated with small differences in cardiometabolic health indicators. ST was unfavourably associated with some cardiometabolic indicators even after adjusting for MVPA, and thus appeared to have a more significant role than MVPA, especially in boys. Future longitudinal studies should confirm these results.

Association of physical activity with adiposity in preschoolers using different clinical adiposity measures: a cross-sectional study

BACKGROUND

More research is needed about the association between physical activity (PA), sedentary behaviour (SB), and adiposity in preschoolers, particularly using more direct clinical measures of adiposity. Therefore, the main objective of this study was to investigate the association between objectively measured PA and different clinical adiposity measures in a large sample of preschoolers.

METHODS

Four hundred sixty-three predominantly normal-weight (77%) 2-6-year-old preschool children participated in the Swiss Preschoolers' Health Study (SPLASHY). Physical activity was measured using accelerometers and was analyzed using 15-s (uni-axial) epoch length using validated cut-offs. Adiposity measures included body mass index (BMI), the sum of four skinfolds, and waist circumference (WC). Multilevel linear regression modeling, adjusted for age, sex and wear time, was used to assess the association between PA and SB with BMI, WC, and skinfold thickness.

RESULTS

Total PA and different PA intensities were positively and SB was inversely associated with BMI in the total sample and in the normal-weight children (p < 0.05). Total PA was inversely associated with skinfold thickness in overweight and obese children (p < 0.05), while there was only a weak association for vigorous PA (p > 0.05). Moderate and moderate-to-vigorous PA were positively, and SB was negatively associated with WC in the total sample and in the normal-weight children (p < 0.05). Additional adjustment for potential sociocultural and biological confounding variables attenuated some of the results.

CONCLUSIONS

In this very young and predominantly normal-weight population, PA is positively related to BMI and WC, but this relationship is not observed in overweight and obese children. In this latter population, PA is inversely, and SB is positively related to skinfold thickness. Skinfold thickness could represent a useful and simple clinical measure of body fat in preschoolers. The role of vigorous PA in the prevention of early childhood obesity should be further investigated in future studies.

TRIAL REGISTRATION

ISRCTN ISRCTN41045021 . Retrospectively registered 06 May 2014.

The effect of mild sleep deprivation on diet and eating behaviour in children: protocol for the Daily Rest, Eating, and Activity Monitoring (DREAM) randomized cross-over trial

BACKGROUND

Although insufficient sleep has emerged as a strong, independent risk factor for obesity in children, the mechanisms by which insufficient sleep leads to weight gain are uncertain. Observational research suggests that being tired influences what children eat more than how active they are, but only experimental research can determine causality. Few experimental studies have been undertaken to determine how reductions in sleep duration might affect indices of energy balance in children including food choice, appetite regulation, and sedentary time. The primary aim of this study is to objectively determine whether mild sleep deprivation increases energy intake in the absence of hunger.

METHODS

The Daily, Rest, Eating, and Activity Monitoring (DREAM) study is a randomized controlled trial investigating how mild sleep deprivation influences eating behaviour and activity patterns in children using a counterbalanced, cross-over design. One hundred and ten children aged 8-12 years, with normal reported sleep duration of 8-11 h per night will undergo 2 weeks of sleep manipulation; seven nights of sleep restriction by going to bed 1 hr later than usual, and seven nights of sleep extension going to bed 1 hr earlier than usual, separated by a washout week. During each experimental week, 24-h movement behaviours (sleep, physical activity, sedentary behaviour) will be measured via actigraphy; dietary intake and context of eating by multiple 24-h recalls and wearable camera images; and eating behaviours via objective and subjective methods. At the end of each experimental week a feeding experiment will determine energy intake from eating in the absence of hunger. Differences between sleep conditions will be determined to estimate the effects of reducing sleep duration by 1-2 h per night.

DISCUSSION

Determining how insufficient sleep predisposes children to weight gain should provide much-needed information for improving interventions for the effective prevention of obesity, thereby decreasing long-term morbidity and healthcare burden.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12618001671257 . Registered 10 October 2018.

Sedentary Behaviors in Today's Youth: Approaches to the Prevention and Management of Childhood Obesity: A Scientific Statement From the American Heart Association

This scientific statement is about sedentary behavior and its relationship to obesity and other cardiometabolic outcomes in youth. A deleterious effect of sedentary behavior on cardiometabolic health is most notable for screen-based behaviors and adiposity; however, this relation is less apparent for other cardiometabolic outcomes or when sedentary time is measured with objective movement counters or position monitors. Increasing trends of screen time are concerning; the portability of screen-based devices and abundant access to unlimited programming and online content may be leading to new patterns of consumption that are exposing youth to multiple pathways harmful to cardiometabolic health. This American Heart Association scientific statement provides an updated perspective on sedentary behaviors specific to modern youth and their impact on cardiometabolic health and obesity. As we reflect on implications for practice, research, and policy, what emerges is the importance of understanding the context in which sedentary behaviors occur. There is also a need to capture the nature of sedentary behavior more accurately, both quantitatively and qualitatively, especially with respect to recreational screen-based devices. Further evidence is required to better inform public health interventions and to establish detailed quantitative guidelines on specific sedentary behaviors in youth. In the meantime, we suggest that televisions and other recreational screen-based devices be removed from bedrooms and absent during meal times. Daily device-free social interactions and outdoor play should be encouraged. In addition, parents/guardians should be supported to devise and enforce appropriate screen time regulations and to model healthy screen-based behaviors.

CHAMP: A cluster randomized-control trial to prevent obesity in child care centers

Foundational elements of lifelong health are formed during the preschool years. Child care attendance has nearly doubled in the past 5 years making child care centers an ideal setting to establish healthy habits that prevent pediatric obesity. Despite the promising evidence of efficacy of child care-based obesity prevention interventions, limited attention has been directed to criteria needed for implementation at scale. There is potential to improve children's dietary and physical activity behaviors in diverse communities through theory-based, culturally appropriate, manualized interventions, delivered by child care staff. CHAMP (Creating Healthy Habits Among Maryland Preschoolers) is a 3-arm cluster randomized controlled childhood obesity prevention trial, aiming to improve motor skills, physical activity and willingness to try new foods among 864 preschoolers (age 3-5 years) enrolled in 54 child care centers in 10 Maryland counties. CHAMP is informed by social-cognitive and bioecological theories and based on an evidence-based program, The Food Friends®. The two intervention arms include: 1) child care-center based lessons (18-week gross motor and 12-week nutrition) administered by trained child care staff, and 2) a web-based intervention for caregivers in addition to center-based lessons. Evaluations are conducted among children, caregivers, and child care staff at fall enrollment, midline, and spring, following intervention completion. Analyses include linear mixed-models, accounting for clustering and repeated measures, incorporating center-arms as moderators. CHAMP will provide evidence-based information to inform wellness guidelines and policies that can be disseminated broadly, to ensure that child care centers provide opportunities for children to develop healthy eating, and physical activity habits. Trial Registration: NCT03111264; https://clinicaltrials.gov/ct2/show/NCT03111264.

The associations between neighborhood walkability attributes and objectively measured physical activity in older adults

A limited number of studies have used objective measures to examine the associations between the built environment and physical activity (PA) among older adults. This study aimed to examine geographic information systems-derived neighborhood walkability attributes and accelerometer measured PA in older adults. Data were collected from 124 older Taiwanese adults aged over 60 years (mean age: 69.9). Adjusted multiple linear regression was performed to explore the associations between five neighborhood walkability factors (population density, street connectivity, sidewalk availability, access to destinations, and public transportation) and five metrics of accelerometer-measured physical activity (total PA, moderate-to-vigorous PA, light PA, long moderate-to-vigorous PA bouts, and daily step counts). After adjusting for potential confounders, we found that greater sidewalk availability was positively associated with daily step counts in older adults (β = 0.165; 95% confidence interval: 0.006, 0.412; P = 0.043). No associations between other neighborhood environment attributes and PA metrics were observed. In conclusion, high sidewalk availability in the neighborhood may be supportive for older adults’ daily step counts. Further longitudinal research is needed to establish the causality between the built environment and objectively measured PA in older adults.

Factors associated with accelerometer measured movement behaviours among White British and South Asian children aged 6-8 years during school terms and school holidays

OBJECTIVES

To investigate factors associated with movement behaviours among White British (WB) and South Asian (SA) children aged 6-8 years during school terms and holidays.

DESIGN

Cross-sectional.

SETTING

Three primary schools from the Bradford area, UK.

PARTICIPANTS

One hundred and sixty WB and SA children aged 6-8 years.

PRIMARY AND SECONDARY OUTCOMES

Sedentary behaviour (SB), light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA) measured by accelerometry during summer, winter and spring and during school terms and school holidays. Data were analysed using multivariate mixed-effects multilevel modelling with robust SEs. Factors of interest were ethnicity, holiday/term, sex, socioeconomic status (SES), weight status, weekend/weekday and season.

RESULTS

One hundred and eight children (67.5%) provided 1157 valid days of data. Fifty-nine per cent of children were WB (n=64) and 41% (n=44) were SA. Boys spent more time in MVPA (11 min/day, p=0.013) compared with girls and SA children spent more time in SB (39 min, p=0.017) compared with WB children in adjusted models. Children living in higher SES areas were more sedentary (43 min, p=0.006) than children living in low SES areas. Children were more active during summer (15 min MVPA, p<0.001; 27 LPA, p<0.001) and spring (15 min MVPA, p=0.005; 38 min LPA, p<0.001) and less sedentary (-42 min and -53 min, p<0.001) compared with winter. Less time (8 min, p=0.012) was spent in LPA during school terms compared with school holidays. Children spent more time in MVPA (5 min, p=0.036) during weekend compared with weekdays. Overweight and obese children spent more time in LPA (21 min, p=0.021) than normal-weight children.

CONCLUSION

The results of our study suggest that significant child level factors associated with movement behaviours are ethnicity, sex, weight-status and area SES. Significant temporal factors are weekends, school holidays and seasonality. Interventions to support health enhancing movement behaviours may need to be tailored around these factors.

Objective sleep and physical activity using 24-hour ankle-worn accelerometry among toddlers from low-income families

OBJECTIVES

Poverty is a risk for short sleep duration and limited physical activity. This study describes sleep, physical activity, and sedentary behavior of Women, Infants, and Children-eligible toddlers and the proportion of toddlers meeting recommendations for sleep and physical activity, and examines associations with body mass index z scores and poverty.

PARTICIPANTS/MEASUREMENTS

A total of 101 toddlers (12-32 months) from low-income families (62% African American) wore 24-hour ankle accelerometers over 3-7 consecutive days. Concurrent validity for daytime napping was assessed using parent-reported toddler wake/sleep between 08:00 and 20:00 collected using Ecological Momentary Assessment. Logistic regressions predicted odds of meeting guidelines.

RESULTS

Toddlers averaged 10.56 hours of sleep in 24 hours. All toddlers averaged ≥180 minutes of total activity per day, 38% had ≥60 minutes of moderate/vigorous physical activity per day, 32% of toddlers slept between 11 and 14 hours over 24 hours, and 26% had a bedtime before 9:00 pm. Body mass index z score was not associated with meeting guidelines. Poverty was associated with less than 60 minutes of moderate/vigorous physical activity.

CONCLUSIONS

Most toddlers were not meeting sleep guidelines. This study provides objective data on sleep and activity among a diverse sample of low-income toddlers. Objective measures of sleep and physical activity facilitate surveillance of children meeting guidelines for sleep and physical activity. Such norms are needed to examine disparities among children from varying racial and economic backgrounds. Future research should examine if meeting guidelines is related to other health indicators.

Effect of 6 months' flash glucose monitoring in adolescents and young adults with type 1 diabetes and suboptimal glycaemic control: managing diabetes in a 'flash' randomised controlled trial protocol

BACKGROUND

Teenagers and young adults with type 1 diabetes (T1D) experience significant burden managing this serious chronic condition and glycaemic control is at its unhealthiest during this life stage. Flash glucose monitoring (FGM) is a new technology that reduces the burden of glucose monitoring by easily and discreetly displaying glucose information when an interstitial glucose sensor worn on the upper arm is scanned with a handheld reader, as opposed to traditional capillary glucose sampling by finger prick (otherwise known as self-monitored blood glucose, SMBG). The effectiveness of this technology and impacts of its long-term use in youth with pre-existing suboptimal glycaemic control are unknown. This study therefore aims to investigate the effectiveness of FGM in addition to standard care in young people with T1D.

METHODS

This is a two phase study programme including a multi-centre randomised, parallel-group study consisting of a 6-month comparison between SMBG and FGM, with an additional 6-month continuation phase. We will enrol adolescents with T1D aged 13-20 years (inclusive), with suboptimal glycaemic control (mean glycated haemoglobin (HbA1c) in past 6 months ≥75 mmol/mol [≥9%]). Participants will be randomly allocated (1:1) to FGM (FreeStyle Libre; intervention group) or to continue SMBG with capillary blood glucose testing (usual care group). All participants will continue other aspects of standard care with the study only providing the FreeStyle Libre. At 6 months, the control group will cross over to the intervention. The primary outcome is the between group difference in changes in HbA1c at 6 months. Additional outcomes include a range of psychosocial and health economic measures as well as FGM acceptability.

DISCUSSION

>If improvements are found, this will further encourage steps towards integrating FGM into regular diabetes care for youth with unhealthy glycaemic control, with the expectation it will reduce daily diabetes management burden and improve short- and long-term health outcomes in this high-risk group.

TRIAL REGISTRATION

This trial was registered with the Australian New Zealand Clinical Trials Registry on 5 March 2018 ( ACTRN12618000320257p ) and the World Health Organization International Clinical Trials Registry Platform (Universal Trial Number U1111-1205-5784).

High-Intensity Interval Training in the Real World: Outcomes from a 12-Month Intervention in Overweight Adults

PURPOSE

Although high-intensity interval training (HIIT) and moderate-intensity continuous exercise have comparable health outcomes in the laboratory setting, effectiveness studies in real-world environments are lacking. The aim of this study was to determine the effectiveness of an unsupervised HIIT program in overweight/obese adults over 12 months.

METHODS

Two hundred and fifty overweight/obese adults could choose HIIT or current exercise guidelines of 30 min·d moderate-intensity exercise. HIIT participants received a single training session and were advised to independently perform HIIT three times per week using a variety of protocols. Mixed models, with a random effect for participant, compared differences in weight, body composition, blood pressure, aerobic fitness, physical activity, and blood indices at 12 months, adjusting for relevant baseline variables.

RESULTS

Forty-two percent (n = 104) of eligible participants chose HIIT in preference to current guidelines. At 12 months, there were no differences between exercise groups in weight (adjusted difference HIIT vs conventional = -0.44 kg; 95% confidence interval [CI] = -2.5 to 1.6) or visceral fat (-103 cm; -256 to 49), although HIIT participants reported greater enjoyment of physical activity (P = 0.01). Evidence of adherence to ≥2 sessions per week of unsupervised HIIT (from HR monitoring) declined from 60.8% at baseline to 19.6% by 12 months. Participants remaining adherent to HIIT over 12 months (23%) were more likely to be male (67% vs 36%, P = 0.03), with greater reductions in weight (-2.7 kg; -5.2 to 0.2) and visceral fat (-292 cm; -483 to -101) than nonadherent participants.

CONCLUSIONS

HIIT was well accepted by overweight adults, and opting for HIIT as an alternative to standard exercise recommendations led to no difference in health outcomes after 12 months. Although regular participation in unsupervised HIIT declined rapidly, those apparently adherent to regular HIIT demonstrated beneficial weight loss and visceral fat reduction.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry (ACTRN12615000010594), retrospectively registered.

ActiGraph GT3X+ and Actical Wrist and Hip Worn Accelerometers for Sleep and Wake Indices in Young Children Using an Automated Algorithm: Validation With Polysomnography

Objectives: Our count-scaled algorithm automatically scores sleep across 24 hours to process sleep timing, quantity, and quality. The aim of this study was to validate the algorithm against overnight PSG in children to determine the best site placement for sleep. Methods: 28 children (5-8 years) with no history of sleep disturbance wore two types of accelerometers (ActiGraph GT3X+ and Actical) at two sites (left hip, non-dominant wrist) for 24-h. Data were processed using the count-scaled algorithm. PSG data were collected using an in-home Type 2 device. PSG-actigraphy epoch sensitivity (sleep agreement) and specificity (wake agreement) were determined and sleep outcomes compared for timing (onset and offset), quantity [sleep period time (SPT) and total sleep time (TST)], and quality metrics [sleep efficiency and waking after sleep onset (WASO)]. Results: Overall, sensitivities were high (89.1% to 99.5%) and specificities low (21.1% to 45.7%). Sleep offset was accurately measured by actigraphy, regardless of brand or placement site. By contrast, sleep onset agreed with PSG using hip-positioned but not wrist-positioned devices (difference ActiGraph : PSG 21 min, P < .001; Actical : PSG 14 min, P < .001). The ActiGraph at the wrist accurately detected WASO and sleep efficiency, but under (-34 min, P < .001) and overestimated (5.8%, P < .001) these at the hip. The Actical under- and over-estimated these variables respectively at both sites. Results for TST varied ranging from significant differences to PSG of -26 to 21 min (ActiGraph wrist and hip respectively) and 9 min (ns) to 59 min for Actical (wrist and hip respectively). Conclusion: Overall the count-scaled algorithm produced high sensitivity at the expense of low specificity in comparison with PSG. A best site placement for estimates of all sleep variables could not be determined, but overall the results suggested ActiGraph GT3X+ at the hip may be superior for sleep timing and quantity metrics, whereas the wrist may be superior for sleep quality metrics. Both devices placed at the hip performed well for sleep timing but not for sleep quality. Differences are likely linked to freedom of movement of the wrist vs the trunk (hip) during overnight sleep.

24-h movement behaviors from infancy to preschool: cross-sectional and longitudinal relationships with body composition and bone health

Background

New physical activity guidelines for children address all movement behaviors across the 24-h day (physical activity, sedentary behavior, sleep), but how each component relates to body composition when adjusted for the compositional nature of 24-h data is uncertain.

Aims

To i) describe 24-h movement behaviors from 1 to 5 years of age, ii) determine cross-sectional relationships with body mass index (BMI) z-score, iii) determine whether movement behaviors from 1 to 5 years of age predict body composition and bone health at 5 years.

Methods

24-h accelerometry data were collected in 380 children over 5–7 days at 1, 2, 3.5 and 5 years of age to determine the proportion of the day spent: sedentary (including wake after sleep onset), in light (LPA) and moderate-to-vigorous physical activity (MVPA), and asleep (including naps). BMI was determined at each age and a dual-energy x-ray absorptiometry (DXA) scan measured fat mass, bone mineral content (BMC) and bone mineral density (BMD) at 5 years of age. 24-h movement data were transformed into isometric log-ratio co-ordinates for multivariable regression analysis and effect sizes back-transformed.

Results

At age 1, children spent 49.6% of the 24-h day asleep, 38.2% sedentary, 12.1% in LPA, and 0.1% in MVPA, with corresponding figures of 44.4, 33.8, 19.8 and 1.9% at 5 years of age. Compositional time use was only related significantly to BMI z-score at 3.5 years in cross-sectional analyses. A 10% increase in mean sleep time (65 min) was associated with a lower BMI z-score (estimated difference, − 0.25; 95% CI, − 0.42 to − 0.08), whereas greater time spent sedentary (10%, 47 min) or in LPA (10%, 29 min) were associated with higher BMI z-scores (0.12 and 0.08 respectively, both p < 0.05). Compositional time use from 1 to 3.5 years was not related to future BMI z-score or percent fat. Although MVPA at 2 and 3.5 years was consistently associated with higher BMD and BMC at 5 years, actual differences were small.

Conclusions

Considerable changes in compositional time use occur from 1 to 5 years of age, but there is little association with adiposity. Although early MVPA predicted better bone health, the differences observed had little clinical relevance.

Trial registration

ClinicalTrials.gov number NCT00892983.

Electronic supplementary material

The online version of this article (10.1186/s12966-018-0753-6) contains supplementary material, which is available to authorized users.

Accelerometer Data Collection and Processing Criteria to Assess Physical Activity and Other Outcomes: A Systematic Review and Practical Considerations

BACKGROUND

Accelerometers are widely used to measure sedentary time, physical activity, physical activity energy expenditure (PAEE), and sleep-related behaviors, with the ActiGraph being the most frequently used brand by researchers. However, data collection and processing criteria have evolved in a myriad of ways out of the need to answer unique research questions; as a result there is no consensus.

OBJECTIVES

The purpose of this review was to: (1) compile and classify existing studies assessing sedentary time, physical activity, energy expenditure, or sleep using the ActiGraph GT3X/+ through data collection and processing criteria to improve data comparability and (2) review data collection and processing criteria when using GT3X/+ and provide age-specific practical considerations based on the validation/calibration studies identified.

METHODS

Two independent researchers conducted the search in PubMed and Web of Science. We included all original studies in which the GT3X/+ was used in laboratory, controlled, or free-living conditions published from 1 January 2010 to the 31 December 2015.

RESULTS

The present systematic review provides key information about the following data collection and processing criteria: placement, sampling frequency, filter, epoch length, non-wear-time, what constitutes a valid day and a valid week, cut-points for sedentary time and physical activity intensity classification, and algorithms to estimate PAEE and sleep-related behaviors. The information is organized by age group, since criteria are usually age-specific.

CONCLUSION

This review will help researchers and practitioners to make better decisions before (i.e., device placement and sampling frequency) and after (i.e., data processing criteria) data collection using the GT3X/+ accelerometer, in order to obtain more valid and comparable data.

PROSPERO REGISTRATION NUMBER

CRD42016039991.

Sleep, nutrition, and physical activity interventions to prevent obesity in infancy: follow-up of the Prevention of Overweight in Infancy (POI) randomized controlled trial at ages 3.5 and 5 y

Background

Our Prevention of Overweight in Infancy (POI) study suggested that a brief sleep intervention in infancy reduced the risk of obesity at age 2 y. In contrast, we observed no benefit from the nutrition and activity intervention.

Objective

The objective of the study was to determine how these interventions influenced growth at ages 3.5 and 5 y compared with usual care (Control).

Design

A follow-up of a parallel, 4-arm, single-blind, 2-y, randomized controlled trial in 802 women (86% European, 48% primiparous) recruited in pregnancy (58% response rate) was undertaken. All groups received standard Well-Child care with additional support for 3 intervention groups: FAB (promotion of breastfeeding, healthy eating, physical activity: 8 contacts, antenatal, 18 mo); Sleep (prevention of sleep problems: antenatal, 3 wk); Combination (both interventions). Follow-up measures were collected by staff blinded to group allocation. The primary outcome was child body mass index (BMI) z score, and secondary outcomes were prevalence of obesity (BMI ≥95th percentile), self-regulation (psychological measures), sleep, physical activity (accelerometry, questionnaires), and dietary intake (food-frequency questionnaire). Analyses were conducted through the use of multiple imputation.

Results

Retention was 77% at age 3.5 y and 69% at age 5 y. Children in the FAB group had significantly higher BMI z scores than did Controls at age 5 y (adjusted difference: 0.25; 95% CI: 0.04, 0.47) but not at age 3.5 y (0.15; 95% CI: -0.04, 0.34). Children who received the Sleep intervention (Sleep and Combination groups) had significantly lower BMI z scores at age 3.5 y (-0.24; 95% CI: -0.38, -0.10) and at age 5 y (-0.23; 95% CI: -0.38, -0.07) than children who did not (Control and FAB groups).

Conclusions

A conventional intervention had unexpected adverse long-term weight outcomes, whereas positive outcomes from a less conventional sleep intervention remained promising at age 5 y. More intensive or extended sleep intervention might have larger or longer-lasting effects and should be investigated. This trial was registered at clinicaltrials.gov as NCT00892983.

Wear-Time Compliance with a Dual-Accelerometer System for Capturing 24-h Behavioural Profiles in Children and Adults

To advance the field of time-use epidemiology, a tool capable of monitoring 24 h movement behaviours including sleep, physical activity, and sedentary behaviour is needed. This study explores compliance with a novel dual-accelerometer system for capturing 24 h movement patterns in two free-living samples of children and adults. A total of 103 children aged 8 years and 83 adults aged 20-60 years were recruited. Using a combination of medical dressing and purpose-built foam pouches, participants were fitted with two Axivity AX3 accelerometers—one to the thigh and the other to the lower back—for seven 24 h periods. AX3 accelerometers contain an inbuilt skin temperature sensor that facilitates wear time estimation. The median (IQR) wear time in children was 160 (67) h and 165 (79) h (out of a maximum of 168 h) for back and thigh placement, respectively. Wear time was significantly higher and less variable in adults, with a median (IQR) for back and thigh placement of 168 (1) and 168 (0) h. A greater proportion of adults (71.6%) achieved the maximum number of complete days when compared to children (41.7%). We conclude that a dual-accelerometer protocol using skin attachment methods holds considerable promise for monitoring 24-h movement behaviours in both children and adults.

Classification and Processing of 24-Hour Wrist Accelerometer Data

Background: An important step in accelerometer data analysis is the classification of continuous, 24-hour data into sleep, wake, and non-wear time. We compared classification times and physical activity metrics across different data processing and classification methods.Methods: Participants (n = 576) from the Finnish Retirement and Aging Study (FIREA) wore an accelerometer on their non-dominant wrist for seven days and nights and filled in daily logs with sleep and waking times. Accelerometer data were first classified as sleep or wake time by log, and Tudor-Locke, Tracy, and ActiGraph algorithms. Then, wake periods were classified as wear or non-wear by log, Choi algorithm, and wear sensor. We compared time classification (sleep, wake, and wake wear time) as well as physical activity measures (total activity volume and sedentary time) across these classification methods.Results:M(SD) nightly sleep time was 467 (49) minutes by log and 419 (88), 522 (86), and 453 (74) minutes by Tudor-Locke, Tracy, and ActiGraph algorithms, respectively. Wake wear time did not differ substantially when comparing Choi algorithm and the log. The wear sensor did not work properly in about 29% of the participants. Daily sedentary time varied by 8–81 minutes after excluding sleep by different methods and by 1–18 minutes after excluding non-wear time by different methods. Total activity volume did not substantially differ across the methods.Conclusion: The differences in wear and sedentary time were larger than differences in total activity volume. Methods for defining sleep periods had larger impact on outcomes than methods for defining wear time.

24 h-accelerometry in epidemiological studies: automated detection of non-wear time in comparison to diary information

Estimation of physical activity using 24 h-accelerometry requires detection of accelerometer non-wear time (NWT). It is common practice to define NWT as periods >60 minutes of consecutive zero-accelerations, but this algorithm was originally developed for waking hours only and its applicability to 24 h-accelerometry is unclear. We investigated sensitivity and specificity of different algorithms to detect NWT in 24 h-accelerometry compared to diary in 47 ActivE and 559 KORA participants. NWT was determined with algorithms >60, >90, >120, >150, or >180 minutes of consecutive zero-counts. Overall, 9.1% (ActivE) and 15.4% (KORA) of reported NWT was >60 minutes. Sensitivity and specificity were lowest for the 60-min algorithm in ActivE (0.72 and 0.00) and KORA (0.64 and 0.08), and highest for the 180-min algorithm in ActivE (0.88 and 0.92) and for the 120-min algorithm in KORA (0.76 and 0.74). Nevertheless, when applying these last two algorithms, the overlap of accelerometry with any diary based NWT minutes was around 20% only. In conclusion, only a small proportion of NWT is >60 minutes. The 60-min algorithm is less suitable for NWT detection in 24 h-accelerometry because of low sensitivity, specificity, and small overlap with reported NWT minutes. Longer algorithms perform better but detect lower proportions of reported NWT.

The effect of increasing risk and challenge in the school playground on physical activity and weight in children: a cluster randomised controlled trial (PLAY)

BACKGROUND

To investigate whether changing the play environment in primary schools to one that includes greater risk and challenge increases physical activity and reduces body mass index (BMI).

SUBJECTS/METHODS

A 2-year cluster randomised controlled trial was undertaken in 16 New Zealand schools (years 1-8). Intervention schools (n=8) redesigned their play environments to encourage imaginative and independent free play by increasing opportunities for risk and challenge (for example, rough-and-tumble play), reducing rules and adding new playground components (for example, loose parts). Control schools (n=8) were asked to not change their play environment. A qualified playworker rated all school play environments at baseline and 1 year. Primary outcomes were moderate-to-vigorous physical activity (7-day accelerometry) and BMI z-score, collected in 840 children at baseline, 1 and 2 years. Data were analysed using generalised estimating equations.

RESULTS

Multiple changes were made to the school play environments resulting in a significant difference in overall play evaluation score between intervention and control schools of 4.50 (95% confidence interval: 1.82 to 7.18, P=0.005), which represents a substantial improvement from baseline values of 19.0 (s.d. 3.2). Overall, schools liked the intervention and reported many benefits, including increased physical activity. However, these beliefs did not translate into significant differences in objectively measured physical activity, either as counts per minute (for example, 35 (-51 to 120) during lunch break) or as minutes of moderate-to-vigorous physical activity (0.4, -1.1 to 2.0). Similarly, no significant differences were observed for BMI, BMI z-score or waist circumference at 1 or 2 years (all P>0.321).

CONCLUSIONS

Altering the school play environment to one that promoted greater risk and challenge for children did not increase physical activity, nor subsequently alter body weight. Although schools embraced the concept of adding risk and challenge in the playground, our findings suggest that children may have been involved in different, rather than additional activities.

How consumer physical activity monitors could transform human physiology research

A sedentary lifestyle and lack of physical activity are well-established risk factors for chronic disease and adverse health outcomes. Thus, there is enormous interest in measuring physical activity in biomedical research. Many consumer physical activity monitors, including Basis Health Tracker, BodyMedia Fit, DirectLife, Fitbit Flex, Fitbit One, Fitbit Zip, Garmin Vivofit, Jawbone UP, MisFit Shine, Nike FuelBand, Polar Loop, Withings Pulse O₂, and others have accuracies similar to that of research-grade physical activity monitors for measuring steps. This review focuses on the unprecedented opportunities that consumer physical activity monitors offer for human physiology and pathophysiology research because of their ability to measure activity continuously under real-life conditions and because they are already widely used by consumers. We examine current and potential uses of consumer physical activity monitors as a measuring or monitoring device, or as an intervention in strategies to change behavior and predict health outcomes. The accuracy, reliability, reproducibility, and validity of consumer physical activity monitors are reviewed, as are limitations and challenges associated with using these devices in research. Other topics covered include how smartphone apps and platforms, such as the Apple ResearchKit, can be used in conjunction with consumer physical activity monitors for research. Lastly, the future of consumer physical activity monitors and related technology is considered: pattern recognition, integration of sleep monitors, and other biosensors in combination with new forms of information processing.

Validity of an automated algorithm to identify waking and in-bed wear time in hip-worn accelerometer data collected with a 24 h wear protocol in young adults

Researchers are increasingly using 24 h accelerometer wear protocols. No automated method has been published that accurately distinguishes 'waking' wear time from other data ('in-bed', non-wear, invalid days) in young adults. This study examined the validity of an automated algorithm developed to achieve this for hip-worn Actigraph GT3X  +  60 s epoch data. We compared the algorithm against a referent method ('into-bed' and 'out-of-bed' times visually identified by two independent raters) and benchmarked against two published algorithms. All methods used the same non-wear rules. The development sample (n  =  11) and validation sample (n  =  95) were Australian young adults from the Raine pregnancy cohort (54% female), all aged approximately 22 years. The agreement with Rater 1 in each minute's classification (yes/no) of waking wear time was examined as kappa (κ), limited to valid days (⩾10 h waking wear time per day) according to the algorithm and Rater 1. Bland-Altman methods assessed agreement in daily totals of waking wear and in-bed wear time. Excellent agreement (κ  >  0.75) was obtained between the raters for 80% of participants (median κ  =  0.94). The algorithm showed excellent agreement with Rater 1 (κ  >  0.75) for 89% of participants and poor agreement (κ  <  0.40) for 1%. In this sample, the algorithm (median κ  =  0.86) performed better than algorithms validated in children (median κ  =  0.77) and adolescents (median κ  =  0.66). The mean difference (95% limits of agreement) between Rater 1 and the algorithm was 7 (-220, 234) min d^-1 for waking wear time on valid days and  -41 (-309, 228) min d^-1 for in-bed wear time. In this population, the automated algorithm's validity for identifying waking wear time was mostly good, not worse than inter-rater agreement, and better than the evaluated published alternatives. However, the algorithm requires improvement to better identify in-bed wear time.

Three-year follow-up of a randomised controlled trial to reduce excessive weight gain in the first two years of life: protocol for the POI follow-up study

BACKGROUND

The Prevention of Overweight in Infancy (POI) study was a four-arm randomised controlled trial (RCT) in 802 families which assessed whether additional education and support on sleep (Sleep group); food, physical activity and breastfeeding (FAB group); or both (Combination group), reduced excessive weight gain from birth to 2 years of age, compared to usual care (Control group). The study had high uptake at recruitment (58 %) and retention at 2 years (86 %). Although the FAB intervention produced no significant effect on BMI or weight status at 2 years, the odds of obesity were halved in those who received the sleep intervention, despite no apparent effect on sleep duration. We speculate that enhanced self-regulatory behaviours may exist in the Sleep group. Self-regulation was not measured in our initial intervention, but extensive measures have been included in this follow-up study. Thus, the overall aim of the POI follow-up is to determine the extent to which augmented parental support and education on infant sleep, feeding, diet, and physical activity in the first 2 years of life reduces BMI at 3.5 and 5 years of age, and to determine the role of self-regulation in any such relationship.

METHODS/DESIGN

We will contact all 802 families and seek renewed consent to participate in the follow-up study. The families have received no POI intervention since the RCT finished at 2 years of age. Follow-up data collection will occur when the children are aged 3.5 and 5 years (i.e. up to 3 years post-intervention). Outcomes of interest include child anthropometry, body composition (DXA scan), diet (validated food frequency questionnaire), physical activity (accelerometry), sleep (questionnaire and accelerometry), and self-regulation (questionnaires and neuropsychological assessment).

DISCUSSION

Our follow-up study has been designed primarily to enable us to determine whether the intriguing benefit of the sleep intervention suggested at 2 years of age remains as children approach school age. However, cohort analyses will also investigate how BMI, self-regulation, and sleep consolidation develop during the early years. This information will be valuable to researchers and policy makers progressing the field of early childhood obesity prevention.

TRIAL REGISTRATION

ClinicalTrials.gov number NCT00892983 .

Identifying waking time in 24-h accelerometry data in adults using an automated algorithm

As accelerometers are commonly used for 24-h measurements of daily activity, methods for separating waking from sleeping time are necessary for correct estimations of total daily activity levels accumulated during the waking period. Therefore, an algorithm to determine wake and bed times in 24-h accelerometry data was developed and the agreement of this algorithm with self-report was examined. One hundred seventy-seven participants (aged 40-75 years) of The Maastricht Study who completed a diary and who wore the activPAL3™ 24 h/day, on average 6 consecutive days were included. Intraclass correlation coefficient (ICC) was calculated and the Bland-Altman method was used to examine associations between the self-reported and algorithm-calculated waking hours. Mean self-reported waking hours was 15.8 h/day, which was significantly correlated with the algorithm-calculated waking hours (15.8 h/day, ICC = 0.79, P = < 0.001). The Bland-Altman plot indicated good agreement in waking hours as the mean difference was 0.02 h (95% limits of agreement (LoA) = -1.1 to 1.2 h). The median of the absolute difference was 15.6 min (Q1-Q3 = 7.6-33.2 min), and 71% of absolute differences was less than 30 min. The newly developed automated algorithm to determine wake and bed times was highly associated with self-reported times, and can therefore be used to identify waking time in 24-h accelerometry data in large-scale epidemiological studies.

Gut microbiota manipulation with prebiotics in patients with non-alcoholic fatty liver disease: a randomized controlled trial protocol

Background

Evidence for the role of the gut microbiome in the pathogenesis of non-alcoholic fatty liver disease (NAFLD) is emerging. Strategies to manipulate the gut microbiota towards a healthier community structure are actively being investigated. Based on their ability to favorably modulate the gut microbiota, prebiotics may provide an inexpensive yet effective dietary treatment for NAFLD. Additionally, prebiotics have established benefits for glucose control and potentially weight control, both advantageous in managing fatty liver disease. Our objective is to evaluate the effects of prebiotic supplementation, adjunct to those achieved with diet-induced weight loss, on heptic injury and liver fat, the gut microbiota, inflammation, glucose tolerance, and satiety in patients with NAFLD.

Methods/design

In a double blind, placebo controlled, parallel group study, adults (BMI ≥25) with confirmed NAFLD will be randomized to either a 16 g/d prebiotic supplemented group or isocaloric placebo group for 24 weeks (n = 30/group). All participants will receive individualized dietary counseling sessions with a registered dietitian to achieve 10 % weight loss. Primary outcome measures include change in hepatic injury (fibrosis and inflammation) and liver fat. Secondary outcomes include change in body composition, appetite and dietary adherence, glycemic and insulinemic responses and inflammatory cytokines. Mechanisms related to prebiotic-induced changes in gut microbiota (shot-gun sequencing) and their metabolic by-products (volatile organic compounds) and de novo lipogenesis (using deuterium incorporation) will also be investigated.

Discussion

There are currently no medications or surgical procedures approved for the treatment of NAFLD and weight loss via lifestyle modification remains the cornerstone of current care recommendations. Given that prebiotics target multiple metabolic impairments associated with NAFLD, investigating their ability to modulate the gut microbiota and hepatic health in patients with NAFLD is warranted.

Trial registration

ClinicalTrials.gov (NCT02568605) Registered 30 September 2015