U.S. Adolescent Rest-Activity patterns: insights from functional principal component analysis (NHANES 2011-2014).

Autor: Yeung CHC; Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, 1200 Pressler St., Houston, TX, USA., Lu J; Department of Biostatistics and Data Science, School of Public Health, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA.; Center for Spatial‑Temporal Modeling for Applications in Population Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA., Soltero EG; United States Department of Agriculture/Agricultural Research Services Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX, 77030, USA., Bauer C; Department of Biostatistics and Data Science, School of Public Health, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA. cici.x.bauer@uth.tmc.edu.; Center for Spatial‑Temporal Modeling for Applications in Population Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA. cici.x.bauer@uth.tmc.edu., Xiao Q; Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, 1200 Pressler St., Houston, TX, USA. qian.xiao@uth.tmc.edu.; Center for Spatial‑Temporal Modeling for Applications in Population Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA. qian.xiao@uth.tmc.edu.
Jazyk: angličtina
Zdroj: The international journal of behavioral nutrition and physical activity [Int J Behav Nutr Phys Act] 2023 Oct 13; Vol. 20 (1), pp. 125. Date of Electronic Publication: 2023 Oct 13.
DOI: 10.1186/s12966-023-01520-3
Abstrakt: Background: Suboptimal rest-activity patterns in adolescence are associated with worse health outcomes in adulthood. Understanding sociodemographic factors associated with rest-activity rhythms may help identify subgroups who may benefit from interventions. This study aimed to investigate the association of rest-activity rhythm with demographic and socioeconomic characteristics in adolescents.
Methods: Using cross-sectional data from the nationally representative National Health and Nutrition Examination Survey (NHANES) 2011-2014 adolescents (N = 1814), this study derived rest-activity profiles from 7-day 24-hour accelerometer data using functional principal component analysis. Multiple linear regression was used to assess the association between participant characteristics and rest-activity profiles. Weekday and weekend specific analyses were performed in addition to the overall analysis.
Results: Four rest-activity rhythm profiles were identified, which explained a total of 82.7% of variance in the study sample, including (1) High amplitude profile; (2) Early activity window profile; (3) Early activity peak profile; and (4) Prolonged activity/reduced rest window profile. The rest-activity profiles were associated with subgroups of age, sex, race/ethnicity, and household income. On average, older age was associated with a lower value for the high amplitude and early activity window profiles, but a higher value for the early activity peak and prolonged activity/reduced rest window profiles. Compared to boys, girls had a higher value for the prolonged activity/reduced rest window profiles. When compared to Non-Hispanic White adolescents, Asian showed a lower value for the high amplitude profile, Mexican American group showed a higher value for the early activity window profile, and the Non-Hispanic Black group showed a higher value for the prolonged activity/reduced rest window profiles. Adolescents reported the lowest household income had the lowest average value for the early activity window profile.
Conclusions: This study characterized main rest-activity profiles among the US adolescents, and demonstrated that demographic and socioeconomic status factors may shape rest-activity behaviors in this population.
(© 2023. BioMed Central Ltd., part of Springer Nature.)
Databáze: MEDLINE
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