Latent profile analysis of young adolescents’ physical activity across locations on schooldays

Kelsey B. Borner, Tarrah B. Mitchell, Jordan A. Carlson, Jacqueline Kerr, Brian E. Saelens, Jasper Schipperijn, Lawrence D. Frank, Terry L. Conway, Karen Glanz, Jim E. Chapman, Kelli L. Cain, James F. Sallis

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Resumé

AbstractPurpose 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.
OriginalsprogEngelsk
TidsskriftJournal of Transport & Health
Vol/bind10
Sider (fra-til)304-314
ISSN2214-1405
DOI
StatusUdgivet - 1. sep. 2018

Fingeraftryk

adolescent
school
school sports
information system
travel
regression
questionnaire
ability
Group

Citer dette

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. / Latent profile analysis of young adolescents’ physical activity across locations on schooldays. I: Journal of Transport & Health. 2018 ; Bind 10. s. 304-314.
@article{ce9c589838f6468c9a896bf4bd24478c,
title = "Latent profile analysis of young adolescents’ physical activity across locations on schooldays",
abstract = "AbstractPurpose 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.",
keywords = "Accelerometry, Built environment, Global positioning systems",
author = "Borner, {Kelsey B.} and Mitchell, {Tarrah B.} and Carlson, {Jordan A.} and Jacqueline Kerr and Saelens, {Brian E.} and Jasper Schipperijn and Frank, {Lawrence D.} and Conway, {Terry L.} and Karen Glanz and Chapman, {Jim E.} and Cain, {Kelli L.} and Sallis, {James F.}",
year = "2018",
month = "9",
day = "1",
doi = "10.1016/j.jth.2018.05.010",
language = "English",
volume = "10",
pages = "304--314",
journal = "Journal of Transport & Health",
issn = "2214-1405",
publisher = "Elsevier",

}

Borner, KB, Mitchell, TB, Carlson, JA, Kerr, J, Saelens, BE, Schipperijn, J, Frank, LD, Conway, TL, Glanz, K, Chapman, JE, Cain, KL & Sallis, JF 2018, 'Latent profile analysis of young adolescents’ physical activity across locations on schooldays', Journal of Transport & Health, bind 10, s. 304-314. https://doi.org/10.1016/j.jth.2018.05.010

Latent profile analysis of young adolescents’ physical activity across locations on schooldays. / 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.

I: Journal of Transport & Health, Bind 10, 01.09.2018, s. 304-314.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

T1 - Latent profile analysis of young adolescents’ physical activity across locations on schooldays

AU - Borner, Kelsey B.

AU - Mitchell, Tarrah B.

AU - Carlson, Jordan A.

AU - Kerr, Jacqueline

AU - Saelens, Brian E.

AU - Schipperijn, Jasper

AU - Frank, Lawrence D.

AU - Conway, Terry L.

AU - Glanz, Karen

AU - Chapman, Jim E.

AU - Cain, Kelli L.

AU - Sallis, James F.

PY - 2018/9/1

Y1 - 2018/9/1

N2 - AbstractPurpose 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.

AB - AbstractPurpose 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.

KW - Accelerometry

KW - Built environment

KW - Global positioning systems

U2 - 10.1016/j.jth.2018.05.010

DO - 10.1016/j.jth.2018.05.010

M3 - Journal article

VL - 10

SP - 304

EP - 314

JO - Journal of Transport & Health

JF - Journal of Transport & Health

SN - 2214-1405

ER -