Latent profile analysis of young adolescents' physical activity across locations on schooldays. (September 2018)

• Record Type: Journal Article
• Authors: Borner, Kelsey B.; Mitchell, Tarrah B.; Carlson, Jordan A.; Kerr, Jacqueline; Saelens, Brian E.; Schipperijn, Jasper; Frank, Lawrence D.; Conway, Terry L.; Glanz, Karen; Chapman, Jim E.; Cain, Kelli L.; Sallis, James F.
• Is Part Of: Journal of transport & health. Volume 10(2018)
• Page Start: 304
• Page End: 314
• Publication Date: 2018-09
• Subjects: Accelerometry -- Built environment -- Global positioning systems; Transportation -- Health aspects -- Periodicals; Transportation -- Periodicals; Public Health -- Periodicals; Noise, Transportation -- Periodicals; Air Pollutants -- Periodicals; 388
• DOI: 10.1016/j.jth.2018.05.010
• Languages: English
• ISSNs: 2214-1405

Abstract

Abstract: Purpose: To investigate whether adolescents cluster into profiles based on where they accumulate moderate-to-vigorous physical activity (MVPA), if overall MVPA differs across profiles, and if walking to school and participant and neighborhood characteristics explain profile membership. Methods: Adolescents (N=528; mean age=14.12±1.44; 50% girls) wore accelerometers and Global Positioning Systems (GPS) trackers for 3.9±1.5 days to assess MVPA minutes in five locations: at home, at school, in home neighborhood, in school neighborhood, and other. Walking to school and participant characteristics were assessed by questionnaire, and neighborhood environment by Geographic Information Systems (GIS). Latent profile analysis (LPA) was used to identify profiles/groups of participants based on accumulation of physical activity across the five locations. Mixed-effects regression tested differences in overall MVPA, walking to school, and other characteristics across profiles. Results: Four initial profiles emerged: one Insufficiently Active profile and three Active profiles (Active Around School, Active Home Neighborhood, and Active Other Locations). The Insufficiently Active profile emerging from the first LPA (90% of participants) was further separated into four profiles in a second LPA: Insufficiently Active, and three additional Active profiles (Moderately-Active Around School, Moderately-Active Home Neighborhood, and Active At Home). Those in the six Active profiles had more overall MVPA (41.1–92.7 min/day) than those in the two Insufficiently Active profiles (34.5–38.3 min/day). Variables that differed across profiles included walking to school, sports/athletic ability, and neighborhood walkability. Conclusions: Although most participants did not meet the MVPA guideline, the six Active profiles showed the places in which many adolescents were able to achieve the 60-min/day guideline. The home and school neighborhood (partly through walking to school), other locations, and to a lesser extent the home, appeared to be key sources for physical activity that distinguished active from insufficiently active adolescents. Finding the right match between the individual and physical activity source/location may be a promising strategy for increasing active travel and MVPA in adolescents. Highlights: Patterns of physical activity across locations were related to overall activity. Main locations for physical activity varied across adolescent clusters. Neighborhood activity and active travel were key distinguishers of active adolescents. Identifying the best location-person match could support targeted interventions.