A 24-hour Approach to the Study of Health Behaviors: Temporal Relationships Between Waking Health Behaviors and Sleep
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ORIGINAL ARTICLE
A 24-hour Approach to the Study of Health Behaviors: Temporal Relationships Between Waking Health Behaviors and Sleep Leah A. Irish, Ph.D. & Christopher E. Kline, Ph.D. & Scott D. Rothenberger, B.S. & Robert T. Krafty, Ph.D. & Daniel J. Buysse, M.D. & Howard M. Kravitz, D.O., M.P.H. & Joyce T. Bromberger, Ph.D. & Huiyong Zheng, Ph.D. & Martica H. Hall, Ph.D.
Published online: 17 September 2013 # The Society of Behavioral Medicine 2013
Abstract Background Although sleep is often associated with waking health behaviors (WHB) such as alcohol consumption, caffeine use, smoking, and exercise, the causal direction of these relationships is unclear. Purpose The present study used time series data to examine the temporal dynamics of WHB and sleep characteristics in participants of the Study of Women's Health Across the Nation Sleep Study. Methods Three hundred three women completed daily assessments of WHB and wore wrist actigraphs to measure sleep L. A. Irish : C. E. Kline : D. J. Buysse : J. T. Bromberger : M. H. Hall (*) Department of Psychiatry, University of Pittsburgh School of Medicine, 3811 O’Hara Street, Room E-1131, Pittsburgh, PA 15213, USA e-mail: [email protected] S. D. Rothenberger Department of Statistics, University of Pittsburgh, Pittsburgh, PA, USA R. T. Krafty Department of Statistics, Temple University, Philadelphia, PA, USA H. M. Kravitz Department of Psychiatry, Rush University Medical Center, Chicago, IL, USA H. M. Kravitz Department of Preventive Medicine, Rush University Medical Center, Chicago, IL, USA J. T. Bromberger Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA H. Zheng Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
characteristics for the duration of the study (mean=29.42 days, SD=6.71). Results Vector autoregressive modeling revealed that weekly patterns of sleep and WHB best predicted subsequent sleep and WHB suggesting that the associations between WHB and sleep persist beyond their immediate influence. Some WHB predicted some subsequent sleep characteristics, but sleep did not predict subsequent WHB. Conclusions These novel findings provide insight into the temporal dynamics of 24-h behaviors and encourage consideration of both sleep and WHB in health promotion and behavior change efforts. Keywords Sleep . Actigraphy . Health behaviors . Time series analysis . Vector autoregressive (VAR) modeling . SWAN Sleep Study Chronic illness is a leading cause of morbidity and mortality worldwide [1]. Accordingly, understanding modifiable lifestyle factors that contribute to the development, maintenance, and exacerbation of these diseases, including diet, exercise, and substance use, is of public health and clinical interest [2, 3]. However, an exclusive focus on waking health behaviors (WHB) neglects approximately one third of each day dedicated to sleep. Poor sleep has also been associated with morbidity and mortality [4, 5], and, like WHB, many aspects of sleep are under voluntary behavioral control (e.g., timing, sleep environme
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