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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.

Health equity remains one of the most pressing challenges in public health, with significant inequities in health outcomes across various social, economic, and demographic lines. Factors such as socioeconomic status, race, ethnicity, gender, and geographic location often determine access to health care, healthy environments, and opportunities to engage in sport and physical activity. These inequities contribute to an increased risk of chronic diseases, poorer mental health, and reduced quality of life in marginalized populations. This paper explores the potential of sport and physical activity as powerful tools to address these persistent health inequities and support broader social change through an interdisciplinary approach. By leveraging insights from various disciplines including public health, sociology, psychology, education, epigenetics, and sport sciences (kinesiology) to form an interdisciplinary lens, this paper aims to highlight how sport and physical activity can not only reduce health inequities but also serve as catalysts for broader societal transformations. [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.

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]

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]