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Background: Among elementary-aged children (5-12yrs), summer vacation is associated with accelerated gains in Body Mass Index (BMI). A key behavioral driver of BMI gain is a lack of physical activity (PA). Previous studies indicate PA decreases during summer, compared to the school year but whether this difference is consistent among boys and girls, across age, and by income status remains unclear. This study examined differences in school and summer movement behaviors in a diverse cohort of children across three years. Methods: Children (N = 1,203, age range 5–14 years, 48% girls) wore wrist-placed accelerometers for a 14-day wear-period during school (April/May) and summer (July) in 2021 to 2023, for a total of 6 timepoints. Mixed-effects models examined changes in school vs. summer movement behaviors (moderate-to-vigorous physical activity [MVPA], sedentary) for boys and girls, separately, and by age and household income groups (low, middle, and upper based on income-to-poverty ratio). Results: Children provided a total of 35,435 valid days of accelerometry. Overall, boys (+ 9.1 min/day, 95CI 8.1 to 10.2) and girls (+ 6.2 min/day, 95CI 5.4 to 7.0) accumulated more MVPA during school compared to summer. Boys accumulated less time sedentary (-9.9 min/day, 95CI -13.0 to -6.9) during school, while there was no difference in sedentary time (-2.7 min/day, 95CI -5.7 to 0.4) for girls. Different patterns emerged across ages and income groups. Accumulation of MVPA was consistently greater during school compared to summer across ages and income groups. Generally, the difference between school and summer widened with increasing age, except for girls from middle-income households. Accumulation of sedentary time was higher during school for younger children (5-9yrs), whereas for older children (10-14yrs), sedentary time was greater during summer for the middle- and upper-income groups. For boys from low-income households and girls from middle-income households, sedentary time was consistently greater during summer compared to school across ages. Conclusions: Children are less active and more sedentary during summer compared to school, which may contribute to accelerated BMI gain. However, this differs by biological sex, age, and income. These findings highlight the complex factors influencing movement behaviors between school and summer. [ABSTRACT FROM AUTHOR]

Objectives: To examine the association between acculturation and leisure-time physical activity among Asian Americans. Design: Data came from the 2011–2016 National Health and Nutrition Examination Survey, restricting to non-Hispanic Asian adults aged 20 years and older (n = 1989). Acculturation was assessed by language preference at home, birth locations, and length of residency in the United States (US). Self-reported physical activity was used to estimate leisure-time moderate-to-vigorous physical activity (MVPA) in MET-minutes/week and meeting the World Health Organization's physical activity guidelines. Multiple linear and logistic regression models were used to model MVPA as continuous and categorical variables, respectively. Results: A quarter of Asian Americans spoke only English and 47.8% spoke only non-English at home; 13.0% were born in the US. Asians who spoke only English (adjusted prevalence ratio [aPR]:1.5) and Asians who spoke both English and non-English at home (aPR: 1.4) had greater proportions of meeting physical activity guidelines compared to those who spoke only non-English at home. The US-born Asians had higher a proportion of meeting the physical activity guidelines (aPR:1.4) and performed 547.6 more MET-minutes of MVPA each week than foreign-born Asians; they also had a higher proportion of meeting the physical activity guidelines than foreign-born Asians who stayed in US for ≤ 10 years (aPR:1.5). Length of time staying in the US was associated with a higher proportion of meeting physical activity guidelines. Among foreign-born Asian Americans, higher acculturation measures were also positively associated with meeting physical activity guidelines. Conclusions: Acculturation was positively associated with physical activity levels among Asian Americans. More acculturated Asian Americans such as those who spoke more English at home and US-born Asians, performed more MVPA than less acculturated Asian Americans. Interventions are needed to promote physical activity among non-English speaking Asian immigrants and recent immigrants. [ABSTRACT FROM AUTHOR]

Introduction: This study examined the potential of a device agnostic approach for predicting physical activity from consumer wearable accelerometry compared with a research-grade accelerometry. Methods: Seventy-five 5- to 12-year-olds (58% male, 63% White) participated in a 60-min protocol. Children wore wrist-placed consumer wearables (Apple Watch Series 7 and Garmin Vivoactive 4) and a research-grade device (ActiGraph GT9X) concurrently with an indirect calorimeter (COSMED K5). Activity intensities (i.e., inactive, light, moderate-to-vigorous physical activity) were estimated via indirect calorimetry (criterion), and the Hildebrand thresholds were applied to the raw accelerometer data from the consumer wearables and research-grade device. Epoch-by-epoch (e.g., weighted sensitivity, specificity) and discrepancy (e.g., mean bias, absolute error) analyses evaluated agreement between accelerometry-derived and criterion estimates. Equivalence testing evaluated the equivalence of estimates produced by the consumer wearables and ActiGraph. Results: Estimates produced by the raw accelerometry data from ActiGraph, Apple, and Garmin produced similar criterion agreement with weighted sensitivity = 68.2% (95% confidence interval (CI), 67.1%–69.3%), 73.0% (95% CI, 71.8%–74.3%), and 66.6% (95% CI, 65.7%–67.5%), respectively, and weighted specificity = 84.4% (95% CI, 83.6%–85.2%), 82.0% (95% CI, 80.6%–83.4%), and 75.3% (95% CI, 74.7%–75.9%), respectively. Apple Watch produced the lowest mean bias (inactive, −4.0 ± 4.5; light activity, 2.1 ± 4.0) and absolute error (inactive, 4.9 ± 3.4; light activity, 3.6 ± 2.7) for inactive and light physical activity minutes. For moderate-to-vigorous physical activity, ActiGraph produced the lowest mean bias (1.0 ± 2.9) and absolute error (2.8 ± 2.4). No ActiGraph and consumer wearable device estimates were statistically significantly equivalent. Conclusions: Raw accelerometry estimated inactive and light activity from wrist-placed consumer wearables performed similarly to, if not better than, a research-grade device, when compared with indirect calorimetry. This proof-of-concept study highlights the potential of device-agnostic methods for quantifying physical activity intensity via consumer wearables. [ABSTRACT FROM AUTHOR]