Publications by authors named "Ethan T Hunt"

7 Publications

  • Page 1 of 1

Children's moderate-to-vigorous physical activity on weekdays versus weekend days: a multi-country analysis.

Int J Behav Nutr Phys Act 2021 Feb 10;18(1):28. Epub 2021 Feb 10.

MRC Epidemiology Unit & Centre for Diet and Activity Research, University of Cambridge, Cambridge, UK.

Purpose: The Structured Days Hypothesis (SDH) posits that children's behaviors associated with obesity - such as physical activity - are more favorable on days that contain more 'structure' (i.e., a pre-planned, segmented, and adult-supervised environment) such as school weekdays, compared to days with less structure, such as weekend days. The purpose of this study was to compare children's moderate-to-vigorous physical activity (MVPA) levels on weekdays versus weekend days using a large, multi-country, accelerometer-measured physical activity dataset.

Methods: Data were received from the International Children's Accelerometer Database (ICAD) July 2019. The ICAD inclusion criteria for a valid day of wear, only non-intervention data (e.g., baseline intervention data), children with at least 1 weekday and 1 weekend day, and ICAD studies with data collected exclusively during school months, were included for analyses. Mixed effects models accounting for the nested nature of the data (i.e., days within children) assessed MVPA minutes per day (min/day MVPA) differences between weekdays and weekend days by region/country, adjusted for age, sex, and total wear time. Separate meta-analytical models explored differences by age and country/region for sex and child weight-status.

Results/findings: Valid data from 15 studies representing 5794 children (61% female, 10.7 ± 2.1 yrs., 24% with overweight/obesity) and 35,263 days of valid accelerometer data from 5 distinct countries/regions were used. Boys and girls accumulated 12.6 min/day (95% CI: 9.0, 16.2) and 9.4 min/day (95% CI: 7.2, 11.6) more MVPA on weekdays versus weekend days, respectively. Children from mainland Europe had the largest differences (17.1 min/day more MVPA on weekdays versus weekend days, 95% CI: 15.3, 19.0) compared to the other countries/regions. Children who were classified as overweight/obese or normal weight/underweight accumulated 9.5 min/day (95% CI: 6.9, 12.2) and 10.9 min/day (95% CI: 8.3, 13.5) of additional MVPA on weekdays versus weekend days, respectively.

Conclusions: Children from multiple countries/regions accumulated significantly more MVPA on weekdays versus weekend days during school months. This finding aligns with the SDH and warrants future intervention studies to prioritize less-structured days, such as weekend days, and to consider providing opportunities for all children to access additional opportunities to be active.
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http://dx.doi.org/10.1186/s12966-021-01095-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7877033PMC
February 2021

Comparison of multichannel and single channel wrist-based devices with polysomnography to measure sleep in youth.

J Clin Sleep Med 2020 Nov 11. Epub 2020 Nov 11.

Department of Exercise Science, University of South Carolina, Columbia, South Carolina.

Study Objectives: To compare sleep parameters produced by the Fitbit Charge 3 (Fitbit) and Actigraph GT9X accelerometer (Actigraph) to polysomnography (PSG) in youth.

Methods: Youth (n=56, age=9.2±3.3 years) wore a Fitbit and Actigraph on their non-dominant wrist concurrently with PSG during an overnight observation at a children's sleep lab. Total sleep time (TST), sleep efficiency (SE), wake after sleep onset (WASO), sleep onset, and sleep offset were extracted from Fitabase and Actilife with the Sadeh algorithm, respectively. Bland-Altman plots were used to assess the agreement between wearable devices and PSG.

Results: Seventy-nine percent of participants were diagnosed with obstructive sleep apnea. Compared to PSG, Fitbit and Actigraph underestimated TST by 6.1 min (absolute mean bias [AMB] = 27.7 min) and 31.5 min (AMB = 38.2 min), respectively. Fitbit overestimated SE by 3.0% (AMB=6.3%) and Actigraph underestimated SE by 12.9% (AMB=13.2%). Fitbit overestimated WASO by 18.8 min (AMB=23.9 min) and Actigraph overestimated by 56.1 min (AMB=54.7 min). Fitbit and Actigraph underestimated sleep onset by 1.2 min (AMB=13.9 min) and 10.2 min (AMB=18.1 min), respectively. Fitbit and Actigraph overestimated sleep offset by 6.0 min (AMB=12.0 min) and 10.5 min (AMB=12.6 min). Linear regression indicated significant trends with Fitbit underestimating WASO and SE at higher values.

Conclusions: Fitbit provided comparable, and in some cases better sleep estimates with PSG, compared to Actigraph. Findings support the use of multichannel devices to measure sleep in youth. Additional studies are needed in healthy samples, over several nights, and in free-living settings.
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http://dx.doi.org/10.5664/jcsm.8980DOI Listing
November 2020

Comparing measures of free-living sleep in school-aged children.

Sleep Med 2019 08 18;60:197-201. Epub 2019 Apr 18.

Healthy Active Living and Obesity Research Group, Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, K1H 8L1, Canada.

Objective/background: Recent technological advances and emerging commercially-available consumer-friendly sleep assessment products affords researchers with a host of tools to consider for capturing free-living sleep in children. The purpose of this study was to compare free-living sleep characteristics (duration and bed/wake times) across different measures in children.

Methods: Elementary school-aged children (N = 30, mean age 7.2 years, 63% boys, 87% non-Hispanic white) wore an ActiGraph GT9X Link and Fitbit Charge HR on the non-dominant wrist, with a Beddit 3 Sleep Monitor affixed to their mattress for two consecutive weekend nights of free-living sleep. Parents completed a sleep log of bed and wake times. Absolute differences in bed and wake times were examined and Bland Altman plots assessed the level of agreement across sleep measures.

Results: Across the four sleep measures, total sleep time (TST) ranged from 458 min/night (ActiGraph GT9X Link) to 613 min/night (Parent report). Mean bed and wake times ranged from 8:46 to 9:03, and 6:52 to 7:16, respectively. Pearson correlation coefficients were moderate between all four sleep measures (range r = 0.30-0.71). Bland-Altman plots indicated the highest level of agreement for TST was between Beddit 3 Sleep Monitor and Fitbit Charge HR (mean difference -11.7, limits of agreement: 119.0, -142.4 min).

Conclusions: The findings from this study show a high level of agreement of when a child goes to sleep and wakes up across a variety of sleep measures; however, more work is needed to classify TST once the sleep period has commenced.
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http://dx.doi.org/10.1016/j.sleep.2019.04.006DOI Listing
August 2019

Examining the impact of a summer learning program on children's weight status and cardiorespiratory fitness: A natural experiment.

Eval Program Plann 2019 06 18;74:84-90. Epub 2019 Feb 18.

University of South Carolina, 921 Assembly St, Columbia, SC, 29208, United States.

This study examined the impact of an existing 7-week summer learning program on children's weight status and cardiorespiratory fitness (CRF).

Methods: Using an observational repeated measures within-subjects design, children's (N = 20 mean age = 6.35; 45% female; 80% African American) height, weight, and CRF (i.e., Fitnessgram PACER), were measured during the first and final week of the seven week program. Descriptive statistics were calculated for all variables. Median regression analysis examined estimated the differences in BMI zscore, overweight and obesity prevalence, and CRF during the first week (baseline) compared to the final week (outcome).

Results: Of those enrolled initially in the program, 77% attended for more than 4 weeks. When controlling for attendance and sex, no statistically significant changes were observed for, median zBMI (pre: 0.12, post: 0.11) or CRF (pre: 10, post: 13.5 PACER laps). All children except for one maintained the same weight status (e.g. normal weight, overweight) from baseline to outcome. A total of 12 participants increased or maintained the number of PACER laps completed, while 8 participants' PACER laps decreased.

Conclusion: The results of this natural experiment provides preliminary evidence that participation in a structured summer program can potentially mitigate unhealthy weight gains and fitness loss over the summer for some children. Future studies with larger more representative samples are needed to establish the impact of structured summer programming on children's CRF and weight status.
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http://dx.doi.org/10.1016/j.evalprogplan.2019.02.009DOI Listing
June 2019

Validity and Wearability of Consumer-based Fitness Trackers in Free-living Children.

Int J Exerc Sci 2019 1;12(5):471-482. Epub 2019 Mar 1.

Department of Exercise Science, Arnold School of Public Heath, University of South Carolina, Columbia, South Carolina, USA.

Over the past decade wearable fitness trackers (WFTs) have grown in popularity with more recent versions able to capture the pulse rate noninvasively on the wrist of the wearer. Most of evidence on the validity of WFTs have explored adults in clinical settings. Thus, the purpose of this study is to 1) evaluate the validity of a wrist-placed WFT in determining heart rate, and 2) examine the wear compliance of a wrist-placed WFT, in children in free-living settings. In study 1, 19 children (5-12 yrs) wore a Fitbit Charge HR and a Polar chest strap heart rate (HR) monitor for 2 hours while performing sedentary-to-vigorous activities at a holiday camp in December 2016. In study 2, 20 children with mild developmental disabilities (8-13 yrs) were asked to wear a Fitbit Alta HR during summer 2017. In study 1, mean absolute percent difference between the WFT HR and criterion was 6.9%. Overall, >75% of WFT HRs were within 5-10% of the criterion. Bland Altman plots indicated a moderate-to-high level of agreement between the WFT and criterion (mean difference 4.1%; Limits of Agreement 26.8, -18.5%). In study 2, participants had the device in their possession for 43 days (SD±14, range 14 - 56 days) and wore it on 67% of those days (range: 20 - 96%) for at least 10 hours/day. Preliminary evidence suggests that WFTs can provide comparable HR estimates to a criterion field-based measure and children can wear WFTs for extended monitoring periods in free-living settings.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6413843PMC
March 2019

Income, Race and its Association with Obesogenic Behaviors of U.S. Children and Adolescents, NHANES 2003-2006.

J Community Health 2019 06;44(3):507-518

Department of Exercise Science Arnold School of Public Health, University of South Carolina, Public Health Research Center, 921 Assembly St, 29201, Columbia, SC, USA.

Objectives: To describe the associations of income and race with obesogenic behaviors and % body fat among a large sample of U.S. children and adolescents.

Design: Data were obtained from the 2003-2004 and 2005-2006 National Health and Nutritional Examination Survey. Multiple linear regression models and interactions were used to examine the associations of moderate-to-vigorous physical activity (MVPA), sedentary time, diet quality, and screen-time with income-to-poverty ratio and race. Separate stratified analyses explored associations among individual obesogenic behaviors within race and income groups.

Results: This study included children and adolescents (n = 3551, mean = 13.1 years, SD = 3.9 years) who were 37% Hispanic, 27% White, and 35% Black. Overall, Hispanic children/adolescents had significantly higher levels of adiposity (3.6, 95 CI = 0.9, 6.3) than white children and adolescents. Medium-income children and adolescents engaged in less MVPA (- 3.3 min, 95 CI = - 5.1, - 1.5), had poorer diet quality (- 1.1, 95 CI = - 1.9, - 0.2), and used screens less (- 33.9 min, 95 CI = - 45.4, - 22.4) than children and adolescents from low-income households. High-income children and adolescents also engaged in less MVPA (- 3.1 min, 95 CI = - 5.5, - 0.7) and used screens less (- 62.9 min, 95 CI = - 78.3, - 47.4) than children and adolescents from low-income households. However, there were significant race/ethnicity-by-income interactions for high-income Hispanic children and adolescents with diet quality (- 3.5 HEI-2010 score, 95 CI = - 6.6, - 0.4) and screen time (66.9 min, 95 CI = 24.7, 109.0). There was also a significant race/ethnicity-by-income interaction for the screen-time of Black children and adolescents from medium (33.8 min, 95% CI 0.2, 67.3) and high (75.8 min, 95% CI 34.7, 117.0) income households.

Conclusions: There appears to be a complex relationship that varies by race/ethnicity between income, obesogenic behaviors, and adiposity levels among children and adolescents. More work is needed to identify the behavioral mechanisms that are driving disparate rates of overweight and obesity among minority children and those from low-income households.
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http://dx.doi.org/10.1007/s10900-018-00613-6DOI Listing
June 2019