Jennifer I. Flynn

Estimating Physical Activity in Youth Using a Wrist Accelerometer.

PURPOSE The purpose of this study was to develop and validate methods for analyzing wrist accelerometer data in youth. METHODS A total of 181 youth (mean ± SD; age, 12.0 ± 1.5 yr) completed 30 min of supine rest and 8 min each of 2 to 7 structured activities, selected from a list of 25. Receiver operating characteristic (ROC) curves and regression analyses were used to develop prediction equations for energy expenditure (child-METs; measured activity V˙O2 divided by measured resting V˙O2) and cut points for computing time spent in sedentary behaviors (SB), light (LPA), moderate (MPA), and vigorous (VPA) physical activity. Both vertical axis (VA) and vector magnitude (VM) counts per 5 s were used for this purpose. The validation study included 42 youth (age, 12.6 ± 0.8 yr) who completed approximately 2 h of unstructured PA. During all measurements, activity data were collected using an ActiGraph GT3X or GT3X+, positioned on the dominant wrist. Oxygen consumption was measured using a Cosmed K4b. Repeated-measures ANOVA were used to compare measured versus predicted child-METs (regression only) and time spent in SB, LPA, MPA, and VPA. RESULTS All ROC cut points were similar for area under the curve (≥0.825), sensitivity (≥0.756), and specificity (≥0.634), and they significantly underestimated LPA and overestimated VPA (P < 0.05). The VA and VM regression models were within ±0.21 child-METs of mean measured child-METs and ±2.5 min of measured time spent in SB, LPA, MPA, and VPA, respectively (P > 0.05). CONCLUSIONS Compared to measured values, the VA and VM regression models developed on wrist accelerometer data had insignificant mean bias for child-METs and time spent in SB, LPA, MPA, and VPA; however, they had large individual errors.

Detecting indoor and outdoor environments using the ActiGraph GT3X+ light sensor in children.

INTRODUCTION Experts recommend children spend more time playing outdoors. The ambient light sensor of the ActiGraph GT3X+ provides lux measurements. A lux is the International Systems unit of illumination, equivalent to 1 lm·m. Few studies have established a lux threshold for determining whether a child is indoors or outdoors. PURPOSE This study aimed 1) to assess the reliability of the ActiGraph GT3X+ ambient light sensor, 2) to identify a lux threshold to accurately discriminate between indoor and outdoor activities in children, and 3) to test the accuracy of the lux threshold in a free-living environment. METHODS In part 1, a series of reliability tests were performed using 20 ActiGraph GT3X+ monitors under different environmental conditions. Cronbachs alpha was used to determine interinstrument reliability. In part 2, 18 children performed 11 different activities (five indoors and six outdoors) for 6 min each. The optimal threshold for detecting indoor/outdoor activity was determined using a receiver operator characteristic curve analysis. In part 3, 18 children at a preschool wore the monitor during a school day. Percent accuracy was determined for all conditions. RESULTS In part 1, the devices had Cronbachs alpha values of 0.992 and 1.000 for indoor and outdoor conditions, respectively, indicating high interinstrument reliability. In part 2, the optimal lux threshold was determined to be 240 lux (sensitivity = 0.92, specificity = 0.88, area under the curve = 0.96, 95% CI = 0.951-0.970). In part 3, results of the school-day validation demonstrated the monitor was 97.0% accurate for overall detection of indoor and outdoor conditions (outdoor = 88.9%, indoor = 99.1%). CONCLUSIONS The results demonstrate that an ActiGraph GT3X+ lux threshold of 240 can accurately assess indoor and outdoor conditions of preschool children in a free-living environment.

The Modifying Effects of Race/Ethnicity and Socioeconomic Status on the Change in Physical Activity From Elementary to Middle School

PURPOSE Youth physical activity (PA) levels differ by race/ethnicity and socioeconomic status (SES). It is well established that various multilevel factors may influence changes in PA. The present study examined whether the association between the change in individual, interpersonal, and environmental factors and the change in PA is modified by race/ethnicity or SES. METHODS This study followed 643 youths and their parents from suburban and rural South Carolina participating in the Transitions and Activity Changes in Kids (TRACK) Study in 2008-2009 and 2010-2011. We assessed total PA in youth using accelerometry and categorized youth and parent survey data into blocks based on the socioecological model. Multivariate regression growth curve models evaluated whether the association between change in independent variables and change in PA was modified by race/ethnicity or SES. RESULTS PA declined from fifth to seventh grade among all racial/ethnic and SES groups. Associations between the range of variables and change in PA were modified by race/ethnicity but not SES. Blacks did not share any common predictors of change in PA with whites or Hispanics. However, child-reported number of active friends was associated with total PA, and enjoyment of PA was associated with change in PA among both whites and Hispanics. Significant interactions by time varied by racial/ethnic group. CONCLUSIONS The factors that influence changes in youth PA vary by race/ethnicity but not SES. These findings reinforce the complex nature of addressing PA behavior in diverse samples and further support the need for culturally appropriate interventions to promote PA in youth.

Physiologic Responses to Running with a Jogging Stroller

The purpose of this study was to assess the effect of running with a jogging stroller (JS) on oxygen consumption (VO2), heart rate (HR), and rating of perceived exertion (RPE). This study included 2 parts: Part 1 involved participants (N=15) running on an indoor track and Part 2 involved participants (N=12) running on a paved greenway. All participants completed 6, one-mile trials randomized over 2 visits: 3 were completed at a predetermined pace (160.8 m·min (- 1)) without a JS (NoJS), with 11.36 kg in the JS (JS1), and 22.72 kg in the JS (JS2) and 3 were self-paced and included NoJS, JS1, and JS2. VO2 and HR were measured using a portable metabolic system and telemetry. Repeated measures ANOVAs were used to determine differences among conditions. Part 1, there were no differences in VO2 across conditions, but HR and RPE were significantly higher (P<0.05) during the JS trials compared to the NoJS trials. Part 2, VO2 and RPE during JS trials were higher than NoJS trials (P<0.05). No significant differences were found in HR. The results indicate that it is feasible to run while pushing a JS with minimal increases in exertion compared to running without a JS.

The Physical Activity Patterns of Greenway Users Playing Pokémon Go: A Natural Experiment

OBJECTIVE The aim of the study was to compare objectively measured physical activity (PA) between greenway users playing and not playing Pokémon Go. MATERIALS AND METHODS A sample of 100 participants walking on a greenway wore an Omron pedometer and ActiGraph accelerometer and provided demographic data through an intercept survey during a natural experiment. Mann-Whitney U tests and multiple regression compared greenway PA variables between Pokémon Go (n = 13) and non-Pokémon Go (n = 87). RESULTS Pokémon Go users were significantly younger (P < 0.01) than non-Pokémon Go users. Despite no differences in greenway walking time (42 ± 18 minutes), Pokémon Go users took fewer aerobic steps (2361 ± 1663 steps vs. 4144 ± 2591 steps; P = 0.03), walked shorter distances (1.38 ± 0.68 miles vs. 1.98 ± 1.05 miles; P = 0.049), burned fewer calories (119 ± 79 kcal vs. 202 ± 158 kcal; P = 0.04), spent more time in sedentary (16% ± 12% vs. 2% ± 7%; P < 0.01) and light (29% ± 24% vs. 15% ± 21%; P < 0.01) intensity activity, less time in moderate (52% ± 30% vs. 71 ± 29%; P = 0.02) and moderate-to-vigorous PA (MVPA) (55% ± 29% vs. 82% ± 23%; P < 0.01), and took fewer steps/min (67 ± 24 steps/min vs. 103 ± 23 steps/min; P < 0.01) than non-Pokémon Go users. Pokémon Go step rate rarely exceeded 100 steps/min for >5 minutes at a time. Multiple regression confirmed differences in sedentary, light, vigorous, MVPA, and steps/min between Pokémon Go and non-Pokémon Go users after controlling for covariates (P < 0.05). Age was significantly positively associated with aerobic steps, steps, walking distance and time, more light, but less vigorous, and MVPA (P < 0.05). CONCLUSION While playing Pokémon Go greenway users are likely stopping more and walking at a slower pace than walkers not playing Pokémon Go.

Active Families in the Great Outdoors: a program to promote family outdoor physical activity

ABSTRACT This study evaluated a 4-week program to increase the time families spent engaging in outdoor activity. Parents were provided strategies to increase family outdoor activity and locations to be active. Sixteen families completed the program. Duration and number of family outdoor activity bouts per week, type of activities, locations, and family member attendance were measured using logs. Pre/post surveys were conducted to determine the usefulness of providing educational resources and maps. Compared to baseline (216.1±127.3 min/week), family outdoor activity for weeks 1 (316.1±180.2 min/week), 2 (351.1±209.1 min/week), and 4 (317.5±186.8 min/week) were significantly greater at follow-up. At follow-up, parents reported increased regular exercise and encouragement for their child to be active. Children reported adults engaged in physical activity with them and increased transportation to places to be active. This novel program increased family outdoor activity levels and contributes to limited research on strategies to increase outdoor activity in youth.