Johns Hopkins Bloomberg School of Public Health
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ActiGraph Digital Data Summit 2021November 4 - 5 | Learn more
Statistical modeling of circadian rhythms of physical activity
- Published on Jun 21, 2017
Purpose: The proposed symposium will introduce novel and intuitive statistical methods for modeling the human circadian rhythm based on data collected using body-worn physical activity monitors. All methods are motivated by and applied to large observational studies.
Rationale: Biological rhythms have been under intense methodological development across all disciplines of health research. Data obtained from body-worn physical activity monitors provide a much more complete view of human activity than was previously available. The intensity of human activity combined with its within- and between-day chronotype provide new possibilities for scientific research and raise a host of new challenges for statistical analysis.
Objectives: The main objective is to present the potential of physical activity data for studying biological rhythms. We will introduce the methodology for the analysis of daily patterns of activity for large epidemiological studies. Next, we will present exploratory analysis techniques and introduce novel statistical methods for modeling circadian patterns with their application to health research.
Summary: We will introduce a new perspective on diurnal patterns of physical activity and their relation to health and demographic outcomes.
- Jacek Urbanek 1
- Vadim Zipunnikov 1
- Jiawei Bai 1
- Kathleen Merikangas 2
National Institute of Mental Health
ICAMPAM 2017 Abstract Booklet