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BackgroundThe relationship between intention and behavior has been well researched, but most studies fail to capture dynamic, time-varying contextual factors. Ecological momentary assessment through mobile phone technology is an innovative method for collecting data in real time, including time-use data. However, only a limited number of studies have examined day-level plans to be physically active and subsequent physical activity behavior using real-time time-use data to better understand this relationship. ObjectiveThis study aims to examine whether plans to be physically active (recorded in advance on an electronic calendar) were associated with objectively assessed physical activity (accelerometry), to identify activities that replaced planned periods of physical activity by using the mobile app Life in a Day (LIAD), and to test the feasibility and acceptability of LIAD for collecting real-time time-use data. MethodsThe study included 48 university students who were randomly assigned to 1 of 3 protocols, which were defined by 1, 3, or 5 days of data collection. Participants were asked to record their planned activities on a Google Calendar and were provided with mobile phones with LIAD to complete time-use entries in real time for a set of categories (eg, exercise or sports, eating or cooking, school, or personal care). Participants were instructed to wear an accelerometer on their nondominant wrist during the protocol period. A total of 144 days of protocol data were collected from the 48 participants. ResultsProtocol data for 123 days were eligible for analysis. A Fisher exact test showed a statistically significant association between plans and physical activity behavior (P=.02). The congruence between plans and behavior was fair (Cohen κ=0.220; 95% CI 0.028-0.411). Most participants did not plan to be active, which occurred on 75.6% (93/123) of days. Of these 93 days, no physical activity occurred on 76 (81.7%) days, whereas some physical activity occurred on 17 (18.3%) days. On the remaining 24.4% (30/123) of days, some physical activity was planned. Of these 30 days, no physical activity occurred on 18 (60%) days, whereas some physical activity occurred on 12 (40%) days. LIAD data indicated that activities related to screen time most often replaced planned physical activity, whereas unplanned physical activity was often related to active transport. Feasibility analyses indicated little difficulty in using LIAD, and there were no significant differences in feasibility by protocol length. ConclusionsConsistent with previous literature, physical activity plans and physical activity behaviors were linked, but not strongly linked. LIAD offers insight into the relationship between plans and behavior, highlighting the importance of active transport for physical activity and the influence of screen-related behaviors on insufficient physical activity. LIAD is a feasible and practical method for collecting time-use data in real time.

Little is known about how the neighborhood social environment (e.g., safety, crime, traffic) impacts child physical activity. We examine the mechanism by which the neighborhood social environment is associated with child physical activity, moderated by individual-level cultural factors (e.g., language at home, immigrant generation) and mediated by neighborhood physical activity-related social norms (e.g., seeing walkers in the neighborhood). Data included 2749 non-Hispanic White and Hispanic children from the Healthy Communities Study. Multilevel regression was performed. The neighborhood social environment was not associated with physical activity in the full sample. However, Hispanic children speaking both English and Spanish and first- or second-generation Hispanic children engaged in more physical activity when the quality of the neighborhood social environment was higher (b = 1.60, p < 0.001 for Hispanic children speaking English and Spanish; b = 2.03, p < 0.01 for first-generation Hispanic children; b = 1.29, p < 0.01 for second-generation Hispanic children). Neighborhood physical activity-related social norms mediated the association between the neighborhood social environment and physical activity among Hispanic children speaking English and Spanish (b = 0.33, p < 0.001) and second-generation Hispanic children (b = 0.40, p < 0.001). Findings suggest heterogeneity in how neighborhood social environments impact physical activity by cultural factors. Health promotion programs may need to enhance neighborhood social environments to increase Hispanic children's physical activity.

Background: There is currently a nationwide effort to bring parks and green spaces within a 10-minute walk of the home. We examined the association between park area within 1 km of a child's residence and self-reported park-specific physical activity (PA) along with accelerometer-derived moderate to vigorous physical activity (MVPA). Methods: A subsample of K through eighth-grade youth (n = 493) from the Healthy Communities Study reported whether they engaged in park-specific PA during the last 24 hours and wore an accelerometer for up to 7 days. Park area was defined as the percentage of park land in a 1 km Euclidean buffer around the participant's residence, categorized into quintiles. Analysis consisted of logistic and linear regression modeling with interaction effects that controlled for clustering within communities. Results: Regression models estimated greater park-specific PA for participants in the fourth and fifth quintiles of park land. Age, sex, race ethnicity, and family income were unrelated to park-specific PA. Accelerometer analysis indicated that total MVPA was unrelated to park area. Older children (β = −8.73, P <.001) and girls (β = −13.44, P <.001) engaged in less MVPA. Seasonality significantly predicted both park-specific PA and total MVPA. Conclusion: Increasing park area is likely to improve youth PA patterns, lending support for the 10-minute walk initiative. [ABSTRACT FROM AUTHOR]

Background: Understanding how and where children accumulate their physical activity (PA) and sedentary minutes throughout the day has important implications for behavioral interventions. Purpose: The purpose of this study was to examine the duration and intensity of habitual PA and sedentary time (SED) at and away from school among preadolescent children. Methods: Data from twenty-one children ages 7-11 (57% girls; 57% nonwhite; 24% overweight/obese) were included in this analysis. Proportion of time spent in PA, SED, and SED bouts were examined on school days (in-school and out-of-school) and non-school days via accelerometry. Results: When comparing school time with non-school time on school days, children accumulated a higher proportion of light PA while in-school [49.3% (i.e. 5 min 18 s) vs. 39.6% (i.e. 3 h 53 min), p = 0.01]. While at school, the proportion of time spent in SED was less [46.3% (i.e. 3 h 7 min) vs. 56.3% (i.e. 5 h 32 min), p = 0.01] and fewer children spent time engaged in prolonged sitting compared to out-of-school [uninterrupted SED for 30 min 52.4% (i.e. 11 children) vs. 85.7% (i.e. 18 children), p = 0.02]. Discussion: These findings suggest children are proportionately most active and least sedentary when at school, yet children only accumulated approximately 18 min of moderate-to-vigorous PA in this environment. Translation to Health Education Practice: These preliminary findings can help to inform physical activity programming designed to promote life-long physical activity behaviors in children.

Objectives Adiposity may have a role in the risk of dementia. Fewer studies have focused on the relationship between change in adiposity and cognitive decline. Our study aimed to explore the association between the change in adiposity and cognitive function in Black and White older adults. Methods The participants were 12,204 older adults without cognitive impairment (62.8 ± 8.0 years) in the United States. The percent body mass index change (%BMI change) and percent waist circumference change (%WC change) were measured at 2 in-home visits (first: 2003–2007, second: 2013–2016). Cognitive status was assessed by the Six-Item Screener annually. Memory and executive function were measured by word list learning, MOCA recall and orientation, and letter and animal fluency every 2 years. Logistic regression or linear regression models were used to estimate the relationship between percent change in adiposity and cognitive function. Results After 12.7 ± 1.7 years, a greater decrease in %BMI change or %WC change was significantly associated with a higher risk of cognitive impairment. Compared to older adults with −5% ≤ change ≤ 5% from baseline, a significantly higher risk of cognitive impairment and greater loss in memory and executive function were found among those who experienced more than a 10% decline in %BMI change or %WC change. Older adults who experienced a 5%–10% decrease in %BMI change had a higher risk of cognitive impairment and greater loss of memory compared to those with −5% ≤ change ≤ 5%. Discussion A greater decrease in %BMI (>5%) and %WC (>10%) change was associated with greater cognitive loss observed over time. [ABSTRACT FROM AUTHOR]

Background: Research on physical activity breaks and facilities (indoor and outdoor) in secondary schools is relatively limited. Methods: School administrators and students in nationally representative samples of 8th (middle school) and 10th/12th grade (high school) students were surveyed annually from 2008-2009 to 2011-2012. School administrators reported information about physical activity breaks and facilities. Students self-reported height, weight, and physical activity. Results: The prevalence of physical activity breaks and indoor and outdoor facilities (dichotomized by median split) differed significantly by region of the country, school size, student race/ethnicity, and school socioeconomic status (SES). Breaks were associated with lower odds of overweight (adjusted odds ratio [AOR]?=?0.91, 95% confidence interval [CI]: 0.83-1.00) and obesity (AOR?=?0.86, 95% CI: 0.75-0.99) among middle school students. Among low-SES middle school students and schools, higher indoor facilities were associated with lower rates of overweight and obesity. Among high school students, higher indoor and outdoor facilities were associated with 19-42% higher odds of moderate-to-vigorous physical activity. Conclusions: Physical activity breaks and school facilities may help to address high rates of overweight/obesity and low physical activity levels among secondary students, especially lower-SES students. Students in all schools should have equal access to these resources.

Background: The prevalence of childhood obesity is higher in economically and socially deprived areas. Higher levels of physical activity reduce the risk of excessive weight gain in youth, and research has focused on environmental factors associated with children's physical activity, though the term "physical activity desert" has not come into wide use. Methods: This exploratory study operationalized the term "physical activity desert" and tested the hypothesis that children living in physical activity deserts would be less physically active than children who do not. A cross-sectional study design was applied with 992 fifth-grade students who had provided objectively measured physical activity data. Five of 12 possible elements of the built environment were selected as descriptors of physical activity deserts, including no commercial facilities, no parks, low play spaces, no cohesion, and the presence of incivilities. Results: Univariate and multivariate analyses showed that only the absence of parks was associated with less physical activity in children. Conclusion: Children living in a "no park" zone were less active than their counterparts who lived near a park. This study contributes preliminary conceptual and operational definitions of "physical activity desert." Future studies of physical activity deserts should be undertaken in larger and more diverse samples. [ABSTRACT FROM AUTHOR]

Features of the physical environment may affect post-stroke recovery, but empirical evidence is limited. This study examines associations between features of the physical environment and post-stroke physical quality of life (PH-QOL). The study sample included stroke survivors enrolled in the Caring for Adults Recovering from the Effects of Stroke project, a prospective cohort. Features of the physical environment surrounding participants' home addresses were audited using Google Earth. Audits captured information about crossings (e.g. curb-cuts; range 0-4), street segments (e.g. sidewalks; range 0-17.5), and a route (e.g. parks; range 0-27) near participants' home. Summary scores were categorized into tertials representing "few," "some," and "many" pedestrian-friendly features. Post-stroke PH-QOL was measured by the SF-12 (range 0-100) around 6 to 12-, 18-, 27-, and 36-months post-stroke. Linear mixed models were used to estimate PH-QOL over time. Chained multiple imputation was used to account for missing data. Two hundred and seventy-five participants were eligible, among whom 210 had complete data. Most participants lived in areas with "few" features to promote outdoor mobility. Participants living in environments with "some" crossing features had a 4.90 (95% CI: 2.32, 7.48) higher PH-QOL score across the observation period in comparison to participants living in environments with "few" crossing features. Features of the physical environment along street segments and routes were not associated with post-stroke PH-QOL. Crossing features are associated with post-stroke PH-QOL. Modifying features of the physical environment at nearby crossings, such as curb-cuts, may be a promising strategy for increasing PH-QOL. [ABSTRACT FROM AUTHOR]

Background Literature has focused on neighborhood environments and their possible impacts on obesity and obesity-related behaviors. However, few longitudinal studies have examined the effect of neighborhood socioeconomic status (nSES) on childhood obesity. Purpose Investigate the longitudinal association between nSES and obesity and obesity-related unhealthy behaviors. Methods We obtained data from the Fragile Families and Child Wellbeing Study (N = 2,072). The main exposure was nSES (measured using an index of five variables representing wealth, income, education, and occupation from the Decennial Census 2000) at ages 3, 5, and 9. The outcome was children's body mass index z -score (BMIz) at ages 5, 9, and 15. Three measures of obesity-related behaviors (i.e. child- or caregiver-reported soda/snack food intake, fast-food intake, and sedentary behaviors) at ages 5, 9, and 15 were included as mediators and outcomes. Cross-lagged path analyses were conducted. Results Higher nSES at a previous wave was associated with consuming less soda/snack foods (β s = −0.15 to −0.11 [varying by ages], p <.05) and fast-food intake (β s = −0.21 to −0.14 [varying by ages], p <.01), and less frequent sedentary behaviors (β s = −0.14 to −0.06 [varying by ages], p <.01), but not with BMIz (β s = −0.08 to 0.05 [varying by ages], p >.05). Unhealthy behaviors did not mediate the nSES–BMIz association at alpha.05. Conclusion Health policies need to target low-socioeconomic neighborhoods to shape healthy lifestyles in children. To develop effective interventions, future research needs to examine comprehensive potential mediators like obesity-related parenting skills, home environments, and built and social environments on the risk of childhood obesity and obesity-related behaviors. [ABSTRACT FROM AUTHOR]

Background: The 2013-2014 school year involved preparation for implementing the new US Department of Agriculture (USDA) competitive foods nutrition standards. An awareness of associations between commercial supplier involvement, food vending practices, and food vending item availability may assist schools in preparing for the new standards. Methods: Analyses used 2007-2012 questionnaire data from administrators of 814 middle and 801 high schools in the nationally representative Youth, Education, and Society study to examine prevalence of profit from and commercial involvement with vending machine food sales, and associations between such measures and food availability. Results: Profits for the "school district" were associated with decreased low-nutrient, energy-dense (LNED) food availability and increased fruit/vegetable availability. Profits for the "school" and use of company suppliers were associated with increased LNED availability; company suppliers also were associated with decreased fruit/vegetable availability. Supplier "say" in vending food selection was associated with increased LNED availability and decreased fruit/vegetable availability. Conclusions: Results support (1) increased district involvement with school vending policies and practices, and (2) limited supplier "say" as to what items are made available in student-accessed vending machines. Schools and districts should pay close attention to which food items replace vending machine LNED foods following implementation of the new nutrition standards.