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Carrie D. Patnode, Leslie A. Lytle, Darin J. Erickson, John R. Sirard, Daheia J. Barr-Anderson and Mary Story

Background:

While much is known about the overall levels of physical activity and sedentary activity among youth, few studies have attempted to define clusters of such behaviors. The purpose of this study was to identify and describe unique classes of youth based on their participation in a variety of physical activity and sedentary behaviors.

Methods:

Latent class analysis was used to characterize segments of youth based on patterns of self-reported and accelerometer-measured participation in 12 behaviors. Children and adolescents (N = 720) from 6th-11th grade were included in the analysis. Differences in class membership were examined using multinomial logistic regression.

Results:

Three distinct classes emerged for boys and girls. Among boys, the 3 classes were characterized as “Active” (42.1%), “Sedentary” (24.9%), and “Low Media/Moderate Activity” (33.0%). For girls, classes were “Active” (18.7%), “Sedentary” (47.6%), and “Low Media/Functional Activity” (33.7%). Significant differences were found between the classes for a number of demographic indicators including the proportion in each class who were classified as overweight or obese.

Conclusions:

The behavioral profiles of the classes identified in this study can be used to suggest possible audience segments for intervention and to tailor strategies appropriately.

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Jihong Liu, Jinseok Kim, Natalie Colabianchi, Andrew Ortaglia and Russell R. Pate

Background:

We examined the covarying patterns of physical activity and sedentary behaviors among adolescents and their long-term maintenance.

Methods:

Data came from the National Longitudinal Study of Adolescent Health (1995–2002). We used latent class analysis to identify distinct covarying patterns in adolescence. Logistic regression models were used to predict odds of meeting moderate-to-vigorous physical activity (MVPA) recommendations (≥5 bouts/week) and exceeding screen time guidelines (>2 hours/day) 6 years later based on their adolescent class profile.

Results:

Five classes for each gender were identified and labeled as low physical activity (PA)/low sedentary behaviors (SED), moderate (Mod) PA/high (HI) SED, Mod PA/low SED, HI PA/low SED, and HI PA (except skating/biking)/low SED. Compared with low PA/low SED, males and females in Mod PA/low SED, HI PA/low SED, and HI PA (except skating/biking)/low SED classes had increased odds of meeting MVPA recommendations in young adulthood. Mod PA/HI SED had higher odds of exceeding screen time guidelines in young adulthood (adjusted odds ratio [AOR] for females: 1.67, 95% CI: 1.00−2.81; AOR for males: 3.31, 95% CI: 1.80−6.09).

Conclusions:

Findings are useful to aid the development of multifactorial interventions that promote physical activity and reduce screen time among adolescents transitioning to adulthood.

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Catherine R. Marinac, Mirja Quante, Sara Mariani, Jia Weng, Susan Redline, Elizabeth M. Cespedes Feliciano, J. Aaron Hipp, Daniel Wang, Emily R. Kaplan, Peter James and Jonathan A. Mitchell

-related behaviors may occur simultaneously within an individual, making inferences about associations challenging when only one behavior is examined without accounting for others. Person-centered modeling approaches, such as a latent class analysis (LCA), may be a useful analytic approach to address this issue of

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Jihong Liu, Han Sun, Michael William Beets and Janice C. Probst

Objectives:

We examined the natural groupings of leisure-time physical activities (LTPA) among US adolescents and their correlates.

Methods:

Data came from the 1999−2006 NHANES, restricted to 3865 boys and 3641 girls 12−19 years old. Respondents were asked to report > 40 types of moderate-to-vigorous LTPA in the past month. Latent class analyses were used to identify natural groupings of the top 10 LTPA using the proportion of each activity’s metabolic equivalents (METs) to total energy expenditure from all physical activities.

Results:

For each gender, 5 natural groupings of LTPA were identified. Among boys, they were basketball players and runners (72.8%), football players (9.0%), bicycle riders (7.5%), soccer players (5.8%), and walkers (4.7%). For girls, the 5 natural groupings in descending order were dancers/walkers/joggers (79.0%), aerobic exercisers (6.1%), swimmers (5.6%), volleyball players (4.9%), and soccer players (4.2%). The natural groupings of physical activities were also impacted by age, race, weight status, region, and season of interview.

Conclusions:

The natural groupings of LTPA reflect adolescent’s preference and these activity patterns are likely shaped by their social and physical environments. Better understanding of common LTPAs and their natural groupings is useful in the design of effective PA interventions.

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Ernest Boakye-Dankwa, Anthony Barnett, Nancy A. Pachana, Gavin Turrell and Ester Cerin

, can overcome these problems ( Cerin et al., 2017 ; Clarke & Nieuwenhuijsen, 2009 ). Latent class analysis, a probabilistic model-based person-centered approach ( Bergman & Magnusson, 1997 ; Collins & Lanza, 2010 ), has been applied to classify respondents into subgroups based on a range of

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Rod K. Dishman and Claudio Nigg

Background:

Measuring the way people vary across time in meeting recommended levels of physical activity is a prerequisite to quantifying exposure in outcome studies or identifying determinants of sufficient physical activity. The study determined whether distinct patterns of change in sufficient physical activity could be identified in a population.

Methods:

A cohort (N = 497) from a random, multiethnic sample of adults living in Hawaii was assessed every 6 months for 2 years beginning spring 2004. Latent transition analysis classified people as sufficiently or insufficiently active each time.

Results:

In the total cohort, odds that people would move from insufficient to sufficient activity (45% to 59%) at each 6-month transition were higher than odds they would move from sufficient to insufficient activity (8% to 13%). However, those odds, as well as types and amounts of physical activity, differed widely among and within 3 of 4 transition classes that represented 21% of the cohort.

Conclusions:

Point-prevalence of sufficient physical activity in the total cohort was similar to contemporary U.S. estimates. However, physical activity varied between and within subgroups of the cohort. Further research is needed using self-report and objective measures to determine patterns of change in sufficient physical activity in other representative cohorts.

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Katrina M. Moss, Annette J. Dobson, Kimberley L. Edwards, Kylie D. Hesketh, Yung-Ting Chang and Gita D. Mishra

combinations of equipment available to children, we conducted a latent class analysis (LCA; proc LCA 39 ) to identify mutually exclusive groups based on the combination of equipment. Excluding balls, bikes, and books due to very high frequencies (and thus low variability), all remaining types of equipment were

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Masato Kawabata and Rachel Evans

The present study examined the extent to which scores on the Flow State Scale-2 (FSS-2) could differentiate individuals who experienced flow characteristics in physical activity from those who did not. A total of 1,048 participants completed the Japanese version of the FSS-2. Latent class factor analysis (LCFA), which combines the strengths of both latent class analysis and factor analysis, was conducted on the FSS-2 responses. Four classes were identified through a series of LCFAs and the patterns of the item-average scores for the nine flow attributes were found parallel among these classes. The top two classes (15.1% and 38.9% of the whole sample) were considered the groups who experienced flow characteristics during their physical activities. These results indicated that individuals who experienced flow attributes in physical activity could be differentiated from those who did not based on their FSS-2 scores. Criteria for classifying individuals into the two groups were proposed.

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Natalie Colabianchi, Jamie L. Griffin, Kerry L. McIver, Marsha Dowda and Russell R. Pate

Background:

Numerous studies have focused on the role of environments in promoting physical activity, but few studies have examined the specific locations where children are active and whether being active in these locations is associated with physical activity levels over time.

Methods:

Self-reported locations of where physical activity occurred and physical activity measured via accelerometry were obtained for a cohort of 520 children in 5th and 6th grades. Latent class analysis was used to generate classes of children defined by the variety of locations where they were active (ie, home, school grounds, gyms, recreational centers, parks or playgrounds, neighborhood, and church). Latent transition analyses were used to characterize how these latent classes change over time and to determine whether the latent transitions were associated with changes in physical activity levels.

Results:

Two latent classes were identified at baseline with the majority of children in the class labeled as ‘limited variety.’ Most children maintained their latent status over time. Physical activity levels declined for all groups, but significantly less so for children who maintained their membership in the ‘greater variety’ latent status.

Conclusions:

Supporting and encouraging physical activity in a variety of locations may improve physical activity levels in children.

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Danilo R. Silva, Cláudia S. Minderico, Pedro B. Júdice, André O. Werneck, David Ohara, Edilson S. Cyrino and Luís B. Sardinha

patterns using latent class analysis applied to accelerometry . Int J Behav Nutr Phys Act . 2016 ; 13 : 55 . PubMed ID: 27142304 doi:10.1186/s12966-016-0382-x 27142304 10.1186/s12966-016-0382-x