Might the Timing of Physical Activity Have an Impact on Overall Health or Disease Recovery?
Dr. Loki Natarajan, UC San Diego Department of Family Medicine and Public Health, presenting her research at the Institute for Public Health’s “Public Health Research Day,” April 5, 2017.
Loki Natarajan, PhD
Physical inactivity and sedentary behavior are recognized risk factors for many chronic diseases. Therefore, there is a keen interest in determining how much physical activity is necessary, to maintain a healthy lifestyle and prevent disease. Physical activity researchers often employ accelerometers, wrist- or hip-worn sensors that provide objective measurements of movement, in their studies. Accelerometers can yield minute-level acceleration counts, thus providing a rich framework for assessing physical activity patterns. However, the resulting data sets are large and complex, and therefore can be difficult to analyze and interpret. Potentially valuable minute-level information is lost, when accelerometer research data is only examined collectively, for time periods of days or weeks.
Dr. Loki Natarajan, a Professor of Family Medicine and Public Health in the UC San Diego Division of Biostatistics and Bioinformatics, and her colleagues received a Pilot Grant Award from the Institute for Public Health, to address this problem. Using a method called Functional Principal Component Analysis (FPCA), they implemented new statistical approaches and computational tools, to analyze these large and complex data series. Their focus was on detecting and better understanding time-based patterns of physical activity. They were especially interested in examining whether different patterns of activity throughout the course of the day, were associated with better health. Dr. Natarajan presented her summary findings as one of three keynote addresses, at the April 5, 2017 Public Health Research Day, sponsored by the UC San Diego Institute for Public Health.
The study included 578 overweight women with and without cancer at a variety of stages. This allowed the research team to test whether activity patterns differ by cancer status. For example, are patterns different for women with more aggressive cancer, or women with no cancer history? Dr. Natarajan and team then tested a model to determine whether these various physical activity patterns were associated with key health outcomes, such as insulin levels, and quality of life.
Applying FPCA, Dr. Natarajan and colleagues identified four physical activity patterns that described more than 50% of the variation in the data: (i) high physical activity throughout the day (ii) low activity in the morning (iii) high activity mid-morning onwards (iv) low mid-morning activity and high evening activity. Cancer survivors, compared to women without cancer, subscribed to patterns exhibiting lower activity at the beginning and end of the day with higher activity in the mid-morning period. When considering other health outcomes, higher total physical activity was associated with better insulin regulation and quality of life, after accounting for age, BMI and cancer status. Of more interest, in these adjusted models, increasing and maintaining higher activity in the mid-morning through evening was associated with better insulin regulation. Thus, these preliminary results suggest that health outcomes are impacted not only by the total volume of physical activity, but also by temporal patterns of activity accumulation.
These findings are preliminary and exploratory, and should not be interpreted as causal. However, they support the possible utility of additional research on the activity patterns which are most beneficial to health. This kind of research might eventually lead to specific recommendations not only about amount of activity, but also about the timing of activity that appears most beneficial to overall health.
If you would like a copy of the Research Presentation slides, which include greater technical detail, click here.