activity involvement, and psychological distress through a latent class analysis (LCA) with a sample of Canadian high school student-athletes. In consideration of the mixed findings in the literature as it relates to the overscheduling hypothesis, we hypothesized that participants with a wider breadth of
Sport Participation, Extracurricular Activity Involvement, and Psychological Distress: A Latent Class Analysis of Canadian High School Student-Athletes
Camille Sabourin, Stéphanie Turgeon, Laura Martin, Scott Rathwell, Mark Bruner, John Cairney, and Martin Camiré
Physical Activity and Sedentary Activity Patterns Among Children and Adolescents: A Latent Class Analysis Approach
Carrie D. Patnode, Leslie A. Lytle, Darin J. Erickson, John R. Sirard, Daheia J. Barr-Anderson, and Mary Story
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.
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.
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.
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.
Co-varying Patterns of Physical Activity and Sedentary Behaviors and Their Long-Term Maintenance Among Adolescents
Jihong Liu, Jinseok Kim, Natalie Colabianchi, Andrew Ortaglia, and Russell R. Pate
We examined the covarying patterns of physical activity and sedentary behaviors among adolescents and their long-term maintenance.
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.
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).
Findings are useful to aid the development of multifactorial interventions that promote physical activity and reduce screen time among adolescents transitioning to adulthood.
Associations Between Timing of Meals, Physical Activity, Light Exposure, and Sleep With Body Mass Index in Free-Living Adults
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
Associations Between Latent Classes of Perceived Neighborhood Destination Accessibility and Walking Behaviors in Older Adults of a Low-Density and a High-Density City
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
Assessing Natural Groupings of Common Leisure-Time Physical Activities and Its Correlates Among US Adolescents
Jihong Liu, Han Sun, Michael William Beets, and Janice C. Probst
We examined the natural groupings of leisure-time physical activities (LTPA) among US adolescents and their correlates.
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.
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.
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.
Not All Play Equipment Is Created Equal: Associations Between Equipment at Home and Children’s Physical Activity
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
Periodic Change in Sufficient Physical Activity: A 2-Year Study of a Multi-Ethnic Cohort
Rod K. Dishman and Claudio Nigg
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.
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.
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.
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.
Healthier Energy Balance Behaviors Most Important for Health-Related Quality of Life in Rural Cancer Survivors in Central Pennsylvania
Jenny L. Olson, Michael Robertson, Minxing Chen, David E. Conroy, Kathryn H. Schmitz, and Scherezade K. Mama
number of categories may exist. Model-based techniques, such as latent class analysis (LCA), provide a method for identifying the optimal number of behavioral clusters in a sample that may not have all possible combinations of behaviors. 18 This approach can be especially valuable for examining
How to Classify Who Experienced Flow from Who Did Not Based on the Flow State Scale-2 Scores: A Pilot Study of Latent Class Factor Analysis
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.