Using Momentary Measures to Understand Physical Activity Adoption and Maintenance among Pacific Islanders in the United States

PROJECT SUMMARY/ABSTRACT Pacific Islanders represent one of the fastest growing racial/ethnic groups in the United States. Pacific Islanders suffer from disparities in a variety of health problems such as obesity, cardiovascular diseases, diabetes, and cancer at several sites. Although physical activity is an effective way to reduce the risks of these health problems, Pacific Islander adults are generally less physically activity than non-Hispanic whites. The search for effective policies and interventions to promote PA among Pacific Islanders is severely hampered by the paucity of research on the mechanisms underlying PA behavioral change in this population. This longitudinal study will examine the influence of contextual and environmental factors and acute momentary precipitants on PA adoption and maintenance among 150 sedentary Pacific Islander adults. This study is guided by an overarching conceptual framework derived from models of the social/environmental determinants of health, social cognitive theories of behavioral change, and prior empirical findings. Participants will be assessed using real-time, field-based, state of the art methodologies consisting of MotionSense, ecological momentary assessment, and GPS. MotionSense track behavioral and physiologic data in real-time and can objectively detect PA behaviors and negative affect/stress of participants. GPS permits real-time mapping of an individual’s space-time trajectories and relevant environmental exposures/characteristics (e.g., proximity to PA facilities; neighborhood safety) using geographic information system data. Principal outcomes of interest are PA adoption and PA maintenance. This research would be the first to systematically study PA behaviors of Pacific Islander adults and the first to combine objective and dynamic indices of PA, negative affect/stress, and key environmental influences in PA behavior studies. The comprehensive, multi-method approach is a major advance for the field as it eliminates problems related to an exclusive reliance on self-reports and static residential locations for key outcomes and predictors. In addition, this is one of the first studies to include the framework of dynamic prediction models, a novel statistical approach, to fully examine the huge amount of data yielded by real time assessment approaches. The results will provide critical evidence to guide policies and interventions targeted at reducing PA-related health disparities experienced by Pacific Islanders and potentially other racial/ethnic minorities.