This study represents one of few longitudinal panel studies of adolescent physical activity examining change in youth physical activity. Personal, family, peer, and demographic covariates of initial status and change in physical activity were included, and the model was tested across boys and girls. As hypothesized, the results of the study provide evidence of a significant decline in physical activity from ages 12-17 years. Significant variation around the group means also was evident.
In line with previous research, boys were significantly more physically active at age 12 than girls, but both boys and girls became significantly less physically active from ages 12-17 years. Significant covariates included physical maturation, barriers efficacy, friend physical activity, and friend social support.
Barriers efficacy was found to be a significant influence on the intercept (age 12) and slope (ages 12-17) of physical activity for both boys and girls, supporting prior research indicating the importance of self-efficacy beliefs (4
), and in particular, barriers efficacy beliefs on youth physical activity (17
). Boys and girls with higher efficacy to overcome barriers were initially more active and those with a more positive change in barriers efficacy from Times 1-4 declined less in physical activity from ages 12-17 years, suggesting that efficacy to overcome barriers may not only promote current physical activity but also might protect against future activity declines.
Physical maturation emerged as a significant predictor of physical activity for boys only. Armstrong and Welsman (15
) suggested that boys who are successful in youth sports tend to be more mature. In this study, early maturing boys had higher levels of physical activity at age 12, but experienced a greater decrease in physical activity during adolescence than later-maturing boys. Thus, early maturing boys may have higher levels of physical activity early on may be at greater risk for physical activity declines during adolescence and may require special attention. More research is needed to determine how physical maturation affects physical activity in boys and girls.
Results also highlight the importance of friends. Boys and girls with physically active friends were more physically active at age 12. For girls, having physically active friends also played a protective role in that those with increases in physically active friends over time also had less of a decline in physical activity from ages 12-17. While there was also an effect of Time 1 friend physical activity on the slope (girls who had more physically active friends had a greater decline in physical activity over time), this result is most likely attributed to a change score effect, as explained earlier. For boys, social support of friends also was a significant covariate of physical activity at age 12.
In pre-adolescence and adolescence, youth increasingly value and spend time with peers, including such contexts as organized sport, physical education, and neighborhood games (28
). Friends who presumably are similar to each other in many respects might act as powerful models with regard to physical activity participation (30
). Findings on the importance of friends' activity and support imply that health promotion programs aimed at increasing youth physical activity might be most effective if they included efforts targeting friends or significant others.
This study has limitations and strengths. The research was conducted in one metropolitan area with a predominantly White sample, restricting the ability to make comparisons by race. The physical activity measures have limitations. Measurement of youth physical activity is difficult, with no measure being perfect for every situation. The physical activity measures selected for this study were based on many factors, including the epidemiological nature of the study, the availability of measures at the time the study started, prior findings, study aims, and practicality and simplicity. Since results of the study are affected by the physical activity measures, it must be noted that other studies with different measures may yield different results.
The covariates included in the study represent only a small number of possible potential influences on adolescent physical activity. Other contextual influences (e.g., school, neighborhood, the media) may be important in explaining adolescent physical activity. In particular, neighborhood factors have been found to play a significant role in physical activity and other health behaviors (40
); thus, future studies should include analyses of data nested within neighborhoods. The current study demonstrated the importance of physical maturation in explaining physical activity trends, and the authors encourage researchers to pursue studies that include potential physiological and biological as well as social and contextual variables.
Only a handful of covariates were found to be significantly related to youth physical activity when included in this model along with the other covariates. These results could be due to the combination of covariates used or to the measures or calculation of measures. For example, there are numerous ways to calculate parent physical activity—a mean as in this study, a maximum, or sum—and all represent slightly different approaches. Future studies could examine how children are influenced differently by combinations of parent activity patterns.
Another limitation of this study is the lack of variance in physical activity at age 10 and 11, which necessitated the omission of these data from the LGM model. The cause may be related to the measures, to the specific cohort, or to the age of the participants. Because no other cohort contributed data for these two ages, cohort and age effects can not be disentangled and, as a result, neither can be ruled out. Future studies with different samples are needed to determine whether trajectories of physical activity can be modeled for younger age groups.
Major strengths of the study are the longitudinal nature of the data and design, the use of LGM and cohort-sequential modeling to test the trajectory of physical activity from ages 12-17 with only four annual assessments, and a multiple-group model specification to determine gender effects. The inclusion of individual, family, peer, and demographic covariates also is a strength of the study. The longitudinal nature of the study addresses a critical need for data on patterns of youth physical activity and how it changes over time. By following participants through pre-adolescence and adolescence, it is possible to document changes in physical activity during crucial times when participation declines and to examine influential factors of such change. Other strengths of the study include the randomly recruited sample, self- and parent-report data, and the use of different data methods (survey items and pedometer data) to document physical activity.
The latent variable approach is a powerful technique for the operationalization of physical activity, as it offers an efficient and appropriate way to combine several physical activity variables into one factor for analysis. This approach can be used successfully not only with cross-sectional data but also in longitudinal analyses, as demonstrated in the current study with the use of the cohort-sequential curve-of-factors LGM. There are many advantages of LGM, including its flexibility, practicality, and value for modeling developmental processes, and its ability to identify important predictors and outcomes of change. Unfortunately, to date LGM has been vastly underutilized in the study of physical activity. Future studies are encouraged to use procedures such as LGM to examine the etiology and development of youth physical activity from childhood through adolescence so that we can better understand the risk and protective factors associated with physical activity decline, and thus devise effective interventions for maintaining physical activity throughout childhood, adolescence, and the life span.