Active Voice: Features of Prolonged Sitting Behavior Correlate with Cardiometabolic Disease Risk Markers
By Kate Lyden, Ph.D. and Sarah Kozey Keadle, Ph.D., M.P.H.
Kate Lyden, Ph.D., is a research scientist at the University of Colorado, Denver. Her research is funded by the NIH and examines the effects of interrupting sedentary time with short and continuous bouts of moderate intensity walking on metabolic outcomes in overweight adults. She has developed methodologies to quantify physical activity, sedentary behavior and sleep using wearable sensors and uses these techniques to understand the dose-response relationship between physical activity, sedentary behavior and chronic disease.
Sarah Kozey Keadle, Ph.D., M.P.H., is a cancer prevention fellow in the Division of Cancer Epidemiology and Genetics at the National Cancer Institute in Bethesda, Maryland. Her research broadly focuses on the relationship between physical activity, sedentary behavior and disease prevention, with a specific interest in improving measures of active and sedentary behaviors and applying novel methods to further our understanding of the associations between these behaviors and health risk.
This commentary presents Drs. Lyden’s and Kozey Keadle’s views on the topic related to a research article they authored with their colleagues and which appears in the May 2015 issue of Medicine & Science in Sports & Exercise® (MSSE).
Based largely on epidemiologic evidence that sedentary behavior increases risk of chronic disease and premature mortality, some have suggested that physical activity guidelines, which currently focus on moderate-to-vigorous physical activity (MVPA), should also include recommendations to reduce sitting. While a basic message of “sit less” may be possible given the current evidence, we believe there are important research questions that need to be answered before specific evidence-based recommendations are warranted. First, what “dose” (or amount) of sedentary behavior is bad for health? Certainly, it is unrealistic to recommend that people never sit, but what is the threshold at which sedentary behaviors begin to negatively influence health? Is this threshold different for specific groups (e.g., young vs. old, exercisers vs. non-exercisers?) Second, does reducing and/or changing patterns of sedentary behavior impact relevant health outcomes? If we recommend to individuals that they reduce their sedentary time, how much should they reduce it, and does it matter what type (e.g., standing vs. walking) and intensity of activity they perform instead?
To answer these questions, experimental trials that manipulate sedentary time are needed. However, previous experimental studies have primarily relied on bed rest or other extreme sedentary conditions (e.g., 24 hours confined to a wheel chair) in part due to the challenge of measuring sedentary behavior. While these studies provide evidence of the possible mechanisms linking sedentary behavior to poor health, they are not representative of “real-world” sedentary behavior. Even the most sedentary, but otherwise healthy individuals, take breaks from sitting to perform activities of daily living. The frequency, type and intensity of these breaks are potentially important factors impacting health. Technological advances that improved the precision of body worn activity monitors now make such studies of habitual patterns of sedentary behavior feasible. These devices enable researchers to link specific behaviors with health-related outcomes, which was the purpose of our article published in the May 2015 issue of MSSE.
Our study was designed to reflect “real-world” sedentary behavior patterns where people are constrained by their job, mode of transportation or other factors that promote sitting. We enrolled 10 participants who were recreationally active and measured their baseline levels of sedentary behavior and physical activity for seven consecutive days using a well-validated activity monitor. During a second seven day period, they were instructed to sit as much as possible, to limit standing and walking, and to refrain from structured exercise. At the end of each week, we conducted an oral glucose tolerance test to assess blood glucose and insulin in response to a glucose load. In the sedentary condition, insulin levels 10 hours post-glucose load, the area under the insulin curve and a composite insulin sensitivity index were all significantly elevated. Because we included data from the activity monitor, we were able to assess whether these changes were linked to specific behaviors. We found that change in the 2-hour insulin was negatively associated with change in light-intensity physical activity (r = -0.62) and positively associated with change in time for sitting bouts that were longer than 30 min (r = 0.82) and 60 min (r = 0.83).
We think our study is an important first step. However, there is much more work needed in this area. We included a small sample of healthy young adults who changed both their exercise and sedentary behaviors. It is plausible that the effect of changing sitting time may differ for people who are not active at baseline or for older adults. Activity monitoring allows researchers to measure relevant behavioral patterns and answer research questions that we believe have important public health implications. We anticipate, and hope, that these tools will be widely used in the future to identify novel behaviors that are important in disease initiation and development.