Paper
Thursday, July 22, 2004
This presentation is part of : Disease Prevention in Women
A Finite Mixture Model of Growth Trajectories of Physical Activity and Mood Outcomes for Sedentary Women
Mary A. Nies, RN, PhD, FAAN, FAAHB, Ty Partridge, PhD, and Hesham Gadelrab, MA. College of Nursing, Wayne State University, Detroit, MI, USA
Learning Objective #1: Discuss behaviors important for increasing physical activity in women
Learning Objective #2: Discuss strategies for translation to practice
Objective: Physical activity is one of the most recognized behaviors for preventing chronic illnesses such as cardiovascular disease and diabetes; yet women, especially minority women, are at risk because of inactivity. The current study sought to identify latent classes of growth trajectories for physical activity and mood in a sample of initially sedentary women.

Design/Methods: Latent growth mixture modeling was used. POMS (mood), time to walk 1 mile, and minutes walked per week were assessed at three times: baseline, six-months, and 12-months. Several behavioral, psychological, physiological, environmental, and demographic variables were used as predictors of classes identified using latent growth mixture modeling

Sample: The sample consisted of 313 physically sedentary women from metropolitan communities between the ages of 30 and 60 years with a mean age of 44.5.

Findings: Two classes (responders and non-responders) were identified separately for POMS, time to walk 1 mile, and minutes walked per week. The two-class model yielded a good model fit with the data with entropy ranging from .93 to .98. This indicates that the model identified class membership with very little ambiguity. Additionally, logistic regression analyses revealed a set of behavioral, psychological, psychological, and environmental variables that were predictive of class membership.

Conclusions: Latent growth mixture modeling is a viable technique for identifying heterogeneous classes of growth trajectories. The current findings suggest that the likelihood of sedentary women to engage in physical activity and benefit from intervention may be associated with relapse prevention, restructuring plans, percent body fat, physical activity status, community walk, perceived benefits of walking, and number of children in household.

Implications: These variables may be used as screening factors when selecting women for interventions that will fit into their daily life style and be most successful for increasing physical activity.

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