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This study investigated park access and park quality in the context of childhood obesity. Participants were 20,638 children ages 6-17y from a large primary care health system. Analyses tested associations of park access and park characteristics with children's weight status, and sociodemographic interactions. Both park access and the quality of nearest park were associated with a lower odds of having obesity. Park quality interacted with age, sex, and income. Findings suggest park access is important for supporting a healthy weight in children. Park quality may be most important among 12-14-year-olds, girls, and higher income groups.
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Obesidad Infantil , Niño , Femenino , Humanos , Adolescente , Obesidad Infantil/epidemiología , Estado de Salud , RentaRESUMEN
BACKGROUND: Most neighborhood food and activity related environment research in children has been cross-sectional. A better understanding of prospective associations between these neighborhood environment factors and children's weight status can provide stronger evidence for informing interventions and policy. This study examined associations of baseline and changes in neighborhood healthy food access and walkability with changes in children's weight status over 5 years. METHODS: Height, weight, and home address were obtained for 4,493 children (> 75% were Black or Latinx) from primary care visits within a large pediatric health system. Eligible participants were those who had measures collected during two time periods (2012-2014 [Time 1] and 2017-2019 [Time 2]). Data were integrated with census tract-level healthy food access and walkability data. Children who moved residences between the time periods were considered 'movers' (N = 1052; 23.4%). Mixed-effects models, accounting for nesting of children within census tracts, were conducted to model associations of baseline and changes in the neighborhood environment variables with Time 2 weight status (BMIz and overweight or obese vs. healthy weight). Models adjusted for weight status and child and neighborhood sociodemographics at baseline. RESULTS: Children living in a neighborhood with [ample] healthy food access at Time 1 had a lower BMIz at Time 2, regardless of mover status. A decrease in healthy food access was not significantly associated with children's weight status at Time 2. Baseline walkability and improvements in walkability were associated with a lower BMIz at Time 2, regardless of mover status. CONCLUSIONS: Findings provide evidence that residing in a neighborhood with healthy food access and walkability may support a healthy weight trajectory in children. Findings on changes in the neighborhood environment suggested that improved walkability in the neighborhood may support children's healthy weight. The greater and more consistent findings among movers may be due to movers experiencing greater changes in neighborhood features than the changes that typically occur within a neighborhood over a short period of time. Future research is needed to investigate more robust environmental changes to neighborhoods.
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Salud Infantil , Alimentos , Humanos , Niño , Estudios Transversales , Programas de Gobierno , Estado de SaludRESUMEN
BACKGROUND/OBJECTIVES: Sedentary behavior (SB) has both movement and postural components, but most SB research has only assessed low movement, especially in children. The purpose of this study was to compare estimates and health associations of SB when derived from a standard accelerometer cut-point, a novel sitting detection technique (CNN Hip Accelerometer Posture for Children; CHAP-Child), and both combined. METHODS: Data were from the International Study of Childhood Obesity, Lifestyle, and the Environment (ISCOLE). Participants were 6103 children (mean ± SD age 10.4 ± 0.56 years) from 12 countries who wore an ActiGraph GT3X+ accelerometer on the right hip for approximately one week. We calculated SB time, mean SB bout duration, and SB breaks using a cut-point (SBmovement), CHAP-Child (SBposture), and both methods combined (SBcombined). Mixed effects regression was used to test associations of SB variables with pediatric obesity variables (waist circumference, body fat percentage, and body mass index z-score). RESULTS: After adjusting for MVPA, SBposture showed several significant obesity associations favoring lower mean SB bout duration (b = 0.251-0.449; all p < 0.001) and higher SB breaks (b = -0.005--0.052; all p < 0.001). Lower total SB was unexpectedly related to greater obesity (b = -0.077--0.649; p from <0.001-0.02). For mean SB bout duration and SB breaks, more associations were observed for SBposture (n = 5) than for SBmovement (n = 3) or SBcombined (n = 1), and tended to have larger magnitude as well. CONCLUSIONS: Using traditional measures of low movement as a surrogate for SB may lead to underestimated or undetected adverse associations between SB and obesity. CHAP-Child allows assessment of sitting posture using hip-worn accelerometers. Ongoing work is needed to understand how low movement and posture are related to one another, as well as their potential health implications.
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Obesidad Infantil , Niño , Humanos , Obesidad Infantil/epidemiología , Conducta Sedentaria , Ejercicio Físico , Estilo de Vida , Índice de Masa Corporal , Acelerometría/métodosRESUMEN
BACKGROUND: A better understanding of the extent to which psychosocial and environmental correlates of physical activity are specific to locations would inform intervention optimization. PURPOSE: To investigate cross-sectional associations of location-general and location-specific variables with physical activity and sedentary time in three common locations adolescents spend time. METHODS: Adolescents (N = 472,Mage = 14.1,SD = 1.5) wore an accelerometer and global positioning systems (GPS) tracker and self-reported on psychosocial (e.g., self-efficacy) and environmental (e.g., equipment) factors relevant to physical activity and sedentary time. We categorized each survey item based on whether it was specific to a location to generate psychosocial and environmental indices that were location-general or specific to either school, non-school, or home location. Physical activity (MVPA) and sedentary time were based on time/location match to home, school, or all "other" locations. Mixed-effects models investigated the relation of each index with location-specific activity. RESULTS: The location-general and non-school physical activity psychosocial indices were related to greater MVPA at school and "other" locations. The school physical activity environment index was related to greater MVPA and less sedentary time at school. The home activity environment index was related to greater MVPA at home. The non-school sedentary psychosocial index was related to less sedentary time at home. Interactions among indices revealed adolescents with low support on one index benefited (i.e., exhibited more optimal behavior) from high support on another index (e.g., higher scores on the location-general PA psychosocial index moderated lower scores on the home PA environment index). Concurrent high support on two indices did not provide additional benefit. CONCLUSIONS: No psychosocial or environment indices, including location-general indices, were related to activity in all locations. Most of the location-specific indices were associated with activity in the matching location(s). These findings provide preliminary evidence that psychosocial and environmental correlates of activity are location specific. Future studies should further develop location-specific measures and evaluate these constructs and whether interventions may be optimized by targeting location-specific psychosocial and environmental variables across multiple locations.
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Características de la Residencia , Conducta Sedentaria , Adolescente , Estudios Transversales , Ejercicio Físico , Humanos , Instituciones AcadémicasRESUMEN
BACKGROUND: Hip-worn accelerometer cut-points have poor validity for assessing children's sedentary time, which may partly explain the equivocal health associations shown in prior research. Improved processing/classification methods for these monitors would enrich the evidence base and inform the development of more effective public health guidelines. The present study aimed to develop and evaluate a novel computational method (CHAP-child) for classifying sedentary time from hip-worn accelerometer data. METHODS: Participants were 278, 8-11-year-olds recruited from nine primary schools in Melbourne, Australia with differing socioeconomic status. Participants concurrently wore a thigh-worn activPAL (ground truth) and hip-worn ActiGraph (test measure) during up to 4 seasonal assessment periods, each lasting up to 8 days. activPAL data were used to train and evaluate the CHAP-child deep learning model to classify each 10-s epoch of raw ActiGraph acceleration data as sitting or non-sitting, creating comparable information from the two monitors. CHAP-child was evaluated alongside the current practice 100 counts per minute (cpm) method for hip-worn ActiGraph monitors. Performance was tested for each 10-s epoch and for participant-season level sedentary time and bout variables (e.g., mean bout duration). RESULTS: Across participant-seasons, CHAP-child correctly classified each epoch as sitting or non-sitting relative to activPAL, with mean balanced accuracy of 87.6% (SD = 5.3%). Sit-to-stand transitions were correctly classified with mean sensitivity of 76.3% (SD = 8.3). For most participant-season level variables, CHAP-child estimates were within ± 11% (mean absolute percent error [MAPE]) of activPAL, and correlations between CHAP-child and activPAL were generally very large (> 0.80). For the current practice 100 cpm method, most MAPEs were greater than ± 30% and most correlations were small or moderate (≤ 0.60) relative to activPAL. CONCLUSIONS: There was strong support for the concurrent validity of the CHAP-child classification method, which allows researchers to derive activPAL-equivalent measures of sedentary time, sit-to-stand transitions, and sedentary bout patterns from hip-worn triaxial ActiGraph data. Applying CHAP-child to existing datasets may provide greater insights into the potential impacts and influences of sedentary time in children.
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Conducta Sedentaria , Muslo , Acelerometría , Servicios de Salud , Humanos , Proyectos de InvestigaciónRESUMEN
Despite experiencing health inequities, less is known about neighborhood environments and physical activity among Hispanic/Latino adults compared to other populations. We investigated this topic in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Hispanic/Latino adults in the San Diego, California area of the U.S. completed measures of overall moderate-to-vigorous physical activity (MVPA) via accelerometry and domain-specific MVPA via questionnaire at Visits 1 (2008-2011; n = 4086) and 2 (2014-2017; n = 1776), ~6 years apart. 800-m home neighborhood buffers were used to create objective measures of residential, intersection, and retail density, bus/trolley stops, greenness, parks, and recreation area at Visit 1. Regression models tested the association of each neighborhood feature with MVPA at Visit 1 and over 6 years, adjusting for individual characteristics and neighborhood socioeconomic deprivation. At Visit 1, those in neighborhoods with higher vs. lower retail density or recreation area (+1 vs. -1 standard deviation from the mean) engaged in 10% more overall MVPA and 12-22% more active transportation. Those in neighborhoods with higher vs. lower residential density engaged in 22% more active transportation. Those in neighborhoods with higher vs. lower greenness and park count engaged in 14-16% more recreational MVPA. Neighborhood features were unassociated with changes in MVPA over 6 years. Although changes in MVPA over time were similar across neighborhoods, Hispanic/Latino adults living in neighborhoods with design features supportive of walking and recreational activity (e.g., greater residential and retail density, more parks and recreation facilities) were consistently more active. Improving neighborhood environments appears important for supporting physical activity among Hispanic/Latino adults.
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Planificación Ambiental , Salud Pública , Entorno Construido , Ejercicio Físico , Hispánicos o Latinos , Humanos , Características de la Residencia , CaminataRESUMEN
BACKGROUND: The COVID-19 pandemic has resulted in the closure of schools and may have inadvertently resulted in decreased physical activity for youth. Emerging evidence suggests that school closures due to the COVID-19 pandemic could have hastened the inactivity of youth, possibly due to a lack of structure outside of school and increased access to sedentary activities. OBJECTIVE: The purpose of this study was to assess changes in physical activity from pre-school closure (before the pandemic) to post-school closure (during the pandemic) among youth in spring 2020. METHODS: This study used a natural experimental design; youth were enrolled in a physical activity study prior to the lockdown, which was enforced due to the pandemic. The number of device-assessed steps per day and moderate-to-vigorous physical activity minutes per week were measured by using a Garmin Vivofit 4 (Garmin Ltd) accelerometer over 8 weeks. Mixed effects models were used to compare physical activity variables, which were measured before and during the COVID-19 pandemic. RESULTS: Youth were primarily Hispanic or Latinx (8/17, 47%) and female (10/17, 59%). The number of daily steps decreased by 45.4% during the school closure, from a pre-school closure mean of 8003 steps per day to a post-school closure mean of 4366 steps per day. Daily moderate-to-vigorous physical activity decreased by 42.5%, from a pre-school closure mean of 80.18 minutes per week to a post-school closure mean of 46.13 minutes per week. CONCLUSIONS: Youth are engaging in roughly half as much physical activity during the school closure as they were prior to the school closure. If additional evidence supports these claims, interventions are needed to support youths' engagement in physical activity in the Midwest.
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BACKGROUND: Remote drop-off programs allow children living "unwalkable" distances from school to walk partway by being dropped off by personal vehicle or bus closer to the school, supporting physical activity and health. However, little evidence exists to guide implementation of such programs. METHODS: Semi-structured interviews were conducted with key informants from 7 remote drop-off programs to capture descriptive information and qualitative content (e.g., barriers, facilitators, outcomes). Qualitative content was analyzed using inductive thematic analysis and identified themes were organized within implementation science frameworks. RESULTS: Programs were from low and high socioeconomic areas (free/reduced price lunch range=4%-92%) and initiated by various champions (school staff=29%, parents=29%, external=42%). 29% of programs incorporated the yellow school bus, 43% involved >100 students, and 71% involved route distances ≥0.5 miles. Twenty themes were identified across 5 implementation science domains (Intervention Characteristics, Inner Setting, Outer Setting, Implementation Process, and Outcomes). Positive outcomes included physical activity, socialization, and improved focus for students; decreased traffic; and positive perceptions of the program by students, parents, and school staff/administrators. Barriers included traffic, weather, and student engagement. Facilitators included having a champion and support from school leaders and the community, conducting process improvements, and incentivizing participation. CONCLUSIONS: Remote drop-offs are feasible for supporting active school commuting but underutilized. Promising strategies for supporting uptake and implementation of such programs include communicating benefits, developing champions, engaging school and community leaders, and improving the neighborhood built environment.
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BACKGROUND: Active travel to school contributes to multiple physical and psychosocial benefits for youth, yet population rates of active travel to school are alarmingly low in the USA and many other countries. Though walking school bus interventions are effective for increasing rates of active travel to school and children's overall physical activity, uptake of such interventions has been low. The objective of this study was to conduct a mixed methods implementation evaluation to identify contextual factors that serve as barriers and facilitators among existing walking school bus programs. METHODS: Semi-structured interviews guided by the Consolidated Framework for Implementation Research (CFIR) were conducted with leaders of low-sustainability (n = 9) and high-sustainability (n = 11) programs across the USA. A combination of quantitative (CFIR-based) coding and inductive thematic analysis was used. The CFIR-based ratings were compared between the low- and high-sustainability programs and themes, subthemes, and exemplary quotes were provided to summarize the thematic analysis. RESULTS: In both the low- and high-sustainability programs, three of the 15 constructs assessed were commonly rated as positive (i.e., favorable for supporting implementation): student/family needs and resources, implementation climate, and planning. Three constructs were more often rated as positive in the high-sustainability programs: organizational incentives and rewards, engaging students and parents, and reflecting and evaluating. Three constructs were more often rated as positive in the low-sustainability programs: student/family needs and resources - built environment, available resources, and access to knowledge and information. Four themes emerged from the thematic analysis: planning considerations, ongoing coordination considerations, resources and supports, and benefits. CONCLUSIONS: Engagement of students, parents, and community members were among the factors that emerged across the quantitative and qualitative analyses as most critical for supporting walking school bus program implementation. The information provided by program leaders can help in the selection of implementation strategies that overcome known barriers for increasing the long-term success of community-based physical activity interventions such as the walking school bus.
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BACKGROUND: The authors assessed agreement between participant diaries and two automated algorithms applied to activPAL (PAL Technologies Ltd, Glasgow, United Kingdom) data for classifying awake wear time in three age groups. METHODS: Study 1 involved 20 youth and 23 adults who, by protocol, removed the activPAL occasionally to create nonwear periods. Study 2 involved 744 older adults who wore the activPAL continuously. Both studies involved multiple assessment days. In-bed, out-of-bed, and nonwear times were recorded in the participant diaries. The CREA (in PAL processing suite) and ProcessingPAL (secondary application) algorithms estimated out-of-bed wear time. Second- and day-level agreement between the algorithms and diary was investigated, as were associations of sedentary variables with self-rated health. RESULTS: The overall accuracy for classifying out-of-bed wear time as compared with the diary was 89.7% (Study 1) to 95% (Study 2) for CREA and 89.4% (Study 1) to 93% (Study 2) for ProcessingPAL. Over 90% of the nonwear time occurring in nonwear periods >165 min was detected by both algorithms, while <11% occurring in periods ≤165 min was detected. For the daily variables, the mean absolute errors for each algorithm were generally within 0-15% of the diary mean. Most Spearman correlations were very large (≥.81). The mean absolute errors and correlations were less favorable for days on which any nonwear time had occurred. The associations between sedentary variables and self-rated health were similar across processing methods. CONCLUSION: The automated awake wear-time classification algorithms performed similarly to the diary information on days without short (≤2.5-2.75 hr) nonwear periods. Because both diary and algorithm data can have inaccuracies, best practices likely involve integrating diary and algorithm output.
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Despite evidence of the importance of neighborhood built environment features in relation to physical activity and obesity, research has been limited in informing localized practice due to small sample sizes and limited geographic coverage. This demonstration study integrated data from a local pediatric health system with nationally available neighborhood built environment data to inform local decision making around neighborhood environments and childhood obesity. Height/weight from clinic visits and home neighborhood measures from the U.S. Environmental Protections Agency and WalkScore were obtained for 15,989 6-17 year olds. Multilevel models accounted for the nested data structure and were adjusted for neighborhood income and child sociodemographics. In 9-17 year olds, greater street connectivity and walkability were associated with a 0.01-0.04 lower BMIz (Ps = .009-.017) and greater residential density, street connectivity, and walkability were associated 5-7% lower odds of being overweight/obese (Ps = .004-.044) per standard deviation increase in environment variable. 45.9% of children in the lowest walkability tertile were overweight or obese, whereas 43.1% of children in the highest walkability tertile were overweight or obese. Maps revealed areas with low walkability and a high income-adjusted percent of children overweight/obese. In the Kansas City area, data showed that fewer children were overweight/obese in more walkable neighborhoods. Integrating electronic health records with neighborhood environment data is a replicable process that can inform local practice by highlighting the importance of neighborhood environment features locally and pointing to areas most in need of interventions.
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Entorno Construido , Planificación Ambiental , Niño , Ciudades , Ejercicio Físico , Humanos , Características de la Residencia , CaminataRESUMEN
Remotely delivered interventions are promising for reaching large numbers of people, though few have targeted multiple levels of influence such as schools and families. This study evaluated two versions (arms) of a remotely delivered classroom-based physical activity (CBPA) intervention. One arm solely included remote CBPA; the other included remote CBPA and mobile health (mHealth) family supports. Six schools were randomized to CBPA or CBPA+Family. Both arms were remotely delivered for seven weeks. CBPA+Family added behavior change tools delivered via text messages and newsletters to caregiver/child dyads. Garmin devices measured moderate-to-vigorous activity (MVPA) in both arms and were used for goal setting/monitoring in the CBPA+Family arm (integrated with the text messages). Caregivers completed surveys evaluating intervention acceptability. 53 participants (CBPA n=35; CBPA+Family n=18; 9.7±0.7 years) were included. Increases in MVPA were similar between arms, showing a pre-post effect of the CBPA but no additional effect of family supports. MVPA was low at baseline and during the first 3 weeks (CBPA 7.5±3.1 minutes/day; CBPA+Family 7.9±2.7 minutes/day) and increased by Weeks 6-8 (CBPA 56.8±34.2 minutes/day; CBPA+Family 49.2±18.7 minutes/day). Approximately 90% of caregivers reported high satisfaction with the added family support content. CBPA+Family participants wore the Garmin later into the study period. Remote delivery of CBPA appears feasible and effective for supporting increases in children's MVPA. Adding family supports to school-based interventions appears acceptable and may support engagement, demonstrating promise for more multilevel/multi-setting interventions, though the multilevel intervention was not more effective than the single-level intervention in increasing children's MVPA.
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Objective: To investigate the convergent validity of a global positioning system (GPS)-based and two consumer-based measures with trip logs for classifying pedestrian, cycling, and vehicle trips in children and adults. Methods: Participants (N = 34) wore a Qstarz GPS tracker, Fitbit Alta, and Garmin vivosmart 3 on multiple days and logged their outdoor pedestrian, cycling, and vehicle trips. Logged trips were compared with device-measured trips using the Personal Activity Location Measurement System (PALMS) GPS-based algorithms, Fitbit's SmartTrack, and Garmin's Move IQ. Trip- and day-level agreement were tested. Results: The PALMS identified and correctly classified the mode of 75.6%, 94.5%, and 96.9% of pedestrian, cycling, and vehicle trips (84.5% of active trips, F1 = 0.84 and 0.87) as compared with the log. Fitbit and Garmin identified and correctly classified the mode of 26.8% and 17.8% (22.6% of active trips, F1 = 0.40 and 0.30) and 46.3% and 43.8% (45.2% of active trips, F1 = 0.58 and 0.59) of pedestrian and cycling trips. Garmin was more prone to false positives (false trips not logged). Day-level agreement for PALMS and Garmin versus logs was favorable across trip modes, though PALMS performed best. Fitbit significantly underestimated daily cycling. Results were similar but slightly less favorable for children than adults. Conclusions: The PALMS showed good convergent validity in children and adults and were about 50% and 27% more accurate than Fitbit and Garmin (based on F1). Empirically-based recommendations for improving PALMS' pedestrian classification are provided. Since the consumer devices capture both indoor and outdoor walking/running and cycling, they are less appropriate for trip-based research.
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PURPOSE AND OBJECTIVES: Walking school bus programs increase children's physical activity through active travel to school; however, research to inform large-scale implementation of such programs is limited. We investigated contextual factors, implementation outcomes, and student outcomes in existing walking school bus programs in the United States and internationally. INTERVENTION APPROACH: Walking school bus programs involve a group of children walking to school together with an adult leader. On the trip to school, these adults provide social support, address potential traffic and interpersonal safety, and serve as role models to the children while children increase their physical activity levels. EVALUATION METHODS: We conducted surveys with existing walking school bus programs identified through internet searches, referrals, and relevant email listservs. Leaders from 184 programs that operated at least 1 trip per week completed the survey. We used regression analyses to compare differences in contextual factors by area income and location, associations between contextual factors and implementation outcomes, and associations between implementation outcomes and student outcomes. RESULTS: Walking school bus programs in low-income communities had more route leaders and engaged in more active travel to school-related activities of being sustained than those in higher income. Programs that had no external funding, multiple route leaders, and coordination by a school or district staff member (as opposed to a parent) had greater student participation than other programs. Providing more trips than other programs per week was associated with reduced tardiness, reduced bullying, and improved neighborhood walkability. The greatest barriers to implementation were recruiting and maintaining students and identifying and maintaining route leaders. IMPLICATIONS FOR PUBLIC HEALTH: Walking school bus programs can be implemented successfully in many contexts using various models. The involvement of several people in leadership roles is critical for sustainability. Evidence-based implementation strategies that overcome barriers can improve reach, implementation, and sustainability of walking school bus programs and can increase children's physical activity.
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Ejercicio Físico , Desarrollo de Programa/métodos , Estudiantes/estadística & datos numéricos , Caminata/estadística & datos numéricos , Niño , Femenino , Humanos , Masculino , Evaluación de Programas y Proyectos de Salud , Instituciones Académicas/estadística & datos numéricos , Encuestas y CuestionariosRESUMEN
BACKGROUND: Investigation of physical activity and dietary behaviors across locations can inform "setting-specific" health behavior interventions and improve understanding of contextual vulnerabilities to poor health. This study examined how physical activity, sedentary time, and dietary behaviors differed across home, school, and other locations in young adolescents. METHODS: Participants were adolescents aged 12-16 years from the Baltimore-Washington, DC and the Seattle areas from a larger cross-sectional study. Participants (n = 472) wore an accelerometer and Global Positioning Systems (GPS) tracker (Mean days = 5.12, SD = 1.62) to collect location-based physical activity and sedentary data. Participants (n = 789) completed 24-h dietary recalls to assess dietary behaviors and eating locations. Spatial analyses were performed to classify daily physical activity, sedentary time patterns, and dietary behaviors by location, categorized as home, school, and "other" locations. RESULTS: Adolescents were least physically active at home (2.5 min/hour of wear time) and school (2.9 min/hour of wear time) compared to "other" locations (5.9 min/hour of wear time). Participants spent a slightly greater proportion of wear time in sedentary time when at school (41 min/hour of wear time) than at home (39 min/hour of wear time), and time in bouts lasting ≥30 min (10 min/hour of wear time) and mean sedentary bout duration (5 min) were highest at school. About 61% of daily energy intake occurred at home, 25% at school, and 14% at "other" locations. Proportionately to energy intake, daily added sugar intake (5 g/100 kcal), fruits and vegetables (0.16 servings/100 kcal), high calorie beverages (0.09 beverages/100 kcal), whole grains (0.04 servings/100 kcal), grams of fiber (0.65 g/100 kcal), and calories of fat (33 kcal/100 kcal) and saturated fat (12 kcal/100 kcal) consumed were nutritionally least favorable at "other" locations. Daily sweet and savory snacks consumed was highest at school (0.14 snacks/100 kcal). CONCLUSIONS: Adolescents' health behaviors differed based on the location/environment they were in. Although dietary behaviors were generally more favorable in the home and school locations, physical activity was generally low and sedentary time was higher in these locations. Health behavior interventions that address the multiple locations in which adolescents spend time and use location-specific behavior change strategies should be explored to optimize health behaviors in each location.