Active Voice: Taking Measure of Physical Activity, Sedentary Behavior and Metabolic Health in Youth
By Donna Spruijt-Metz, Ph.D., and Ya-Wen Hsu, Ph.D.
Viewpoints presented in SMB commentaries reflect opinions of the authors and do not necessarily reflect positions or policies of ACSM.
Donna Spruijt-Metz, Ph.D., is Associate Professor in the Department of Preventive Medicine at the University of Southern California. Her research focuses on mobile health, games for health and pediatric obesity and is particularly concerned with understanding how behavioral, psychosocial, metabolic, built environmental and social environmental forces interact to influence behavior and health. Ya-Wen Hsu, Ph.D., is Assistant Professor in the Department of Hospital and Health Care Administration at the Chia Nan University of Pharmacy & Science in Taiwan. Her research has focused on mixed methods to measure activity and metabolic health in minority populations and on determinants of obesity in East Asian populations. This commentary presents Drs. Spruijt-Metz’s and Hsu’s views associated with the research article they and their colleagues published in the Dec. 2011 issue of Medicine & Science in Sports & Exercise® (MSSE).
The relationship between physical activity (PA) and adiposity in children is well-documented. However, interventions to promote and maintain meaningful increases in PA outside the clinic have not been broadly effective. Even when modest increases in PA are achieved, limited impacts on obesity have been noted. In the battle to increase activity and reduce adiposity in youth, we are up against major challenges, including diminishing dollars to support opportunities for PA and safe places to play. Here, we put forth three thoughts that might promote more robust intervention effects on adiposity and better understanding of the complex influences of activity on health.
First, time spent in sedentary behavior (SB) is a crucial modifiable risk factor for obesity, and SB should be studied as a distinct construct from PA. Learn more. The protective effects of PA on health could be attenuated by prolonged SB, as demonstrated by Ekelund et al. in 2006. To better understand the independent, cumulative and interactive effects of SB and PA on health outcomes, simultaneous focus on PA and SB is advised. We have found it more feasible to convince youth to decrease time spent in SB than to persuade them to increase their PA levels meaningfully. Perhaps barriers to decreasing SB are lower than barriers to increasing PA. For instance, reducing SB by simply standing up or taking a short walk around the premises at home, school or work requires minimal resources (e.g., time, cost and equipment) and may be easier to achieve than meaningful increases in PA. Finally, it might be possible that reductions in SB could serve as a first step toward subsequent increases in PA.
A second issue is the lack of a universal definition of sedentary activities. Relying on single narrow indicators of SB, such as TV viewing, may not be sufficient to understand the influence of SB on obesity. Among other considerations, the increasing availability of affordable, attractive, low-intensity, media-related activities cannot be ignored. Conversely, there are disadvantages of a sweeping definition of SB (such as a cut-point) because this includes time spent in homework and other activities that might be low in energy expenditure, but are not desirable targets for behavioral change. Crafting a research definition of SB that takes these limitations into account may increase the clinical impact of interventions on SB.
Third, informative assessments of activity levels are central to evaluating their influences on health outcomes. While objective measurement has become increasingly popular, self-report remains the most utilized activity measure. In the study reported in our MSSE article, we utilized objective (accelerometers) and subjective (3-Day Physical Activity Recall) PA/SB measures simultaneously to assess the associations between PA, SB and metabolic syndrome. We found that PA and SB measured by accelerometry vs. 3DPAR showed different associations with metabolic outcomes. Because subjective and objective activity measures have diverse strengths and weaknesses, future research might benefit by simultaneously using both types of measures. On a cautionary note, not all self-reports are created equal; the key is to choose a valid self-report tool that provides rich contextual data.
We suggest that a combined focus on SB and PA along with simultaneous objective and subjective measurement could help to a) define the roles that PA and SB play in health, and b) delineate the best paths towards successful interventions to improve activity levels and impact metabolic health.