Studying the circadian rhythms of sleep, physical activity, and dietary intake in relation to obesity
Although the growing research in these areas has provided new insights into the health effects of the circadian patterns of human behaviors, several gaps remain: 1) most previous studies only examined one or few aspects of the circadian patterns noted above, and there is a need of examining a more comprehensive set of circadian parameters to better characterize the circadian variation of these behaviors and understand their role in obesity; 2) little is known about the interrelationships among the circadian patterns of these behaviors, and how they may interact with each other to impact body weight. We propose to address these gaps using the unique data available in the Interactive Diet and Activity Tracking in AARP (IDATA) study by evaluating multiple circadian parameters of physical activity and dietary intake. Our circadian parameters will include distribution of physical activity as well as caloric and macronutrient intakes across the 24 hours, and the stability of these circadian parameters across the study period. We will examine these circadian parameters in relation to measurements of body size and composition. We will also explore the interrelationship among these parameters and assess their combined effects on obesity.
Aim 1 To study circadian patterns of sleep, physical activity, and dietary intake in relation to adiposity
Aim 2 To examine the interrelationship of circadian patterns of sleep, physical activity and dietary intake and explore the interaction among these circadian behavioral cycles in relation to adiposity
Methods
Circadian parameters
We propose to generate the following circadian parameters using data from ActivPal, ActiGraph, ACT24 and ASA 24.
Physical activity (from 24-hour ActivPal and non-24 hour ActiGraph)
1. Physical activity distribution across 24 hours (ActivPal), measured by activity level in the morning, afternoon and evenings, or by time at which 25%, 50%, and 75% of total daily activity was accumulated
2. Physical activity distribution during wake time (ActiGraph)
3. Interday stability (ActivPal): this is a measure of how stable the rhythm is over multiple days. It is calculated as the ratio of the variance of the average 24-hour patterns around the mean and the overall variance
4. Intraday variability (ActivPal): a variable that reflects the fragmentation of the rhythm, that is, the rate of shifting between resting and activity.
5. We will also explore using ACT24 to evaluate the full 24-hour pattern using activity log
Food intake (from ASA 24)
1. Total caloric intake distribution across 24 hours: measured by caloric intake in the morning, afternoon and evenings, or by time at which 25%, 50%, and 75% of total daily caloric intake was accumulated
2. Macronutrient intake: we will use the same method to evaluate the timing of intakes of carbohydrate, protein and fat
3. We will calculate interday stability and intraday variability using the same method mentioned above in the Physical Activity Section
Body measurements
Weight, height, waist circumference, hip circumference, and body fat percentage
Statistical analysis
For aim 1, we will examine circadian parameters in relation to body composition and body size using multiple linear regression (continuous measure of body composition and body size) and multiple logistic regression (obesity and overweight). For aim 2, we will examine the interrelationship of the aforementioned variables by looking at the correlations and using factor analysis to characterize the study population based on their circadian patterns of physical activity and eating behaviors. We will then examine the relationship between circadian patterns and obesity.
1) Kathleen Janz, Department of Health and Human Physiology, University of Iowa
2) Charles Matthews, Division of Cancer Epidemiology and Genetics, NCI