Objectives: To examine the bidirectional association of sleep duration with proportions of time spent in physical behaviors among Dutch adolescents. Methods: Adolescents (n = 294, 11–15 years) completed sleep diaries and wore an accelerometer (ActiGraph) over 1 week. With linear mixed-effects models, the authors estimated the association of sleep categories (short, optimal, and long) with the following day’s proportion in physical behaviors. With generalized linear mixed models with binomial distribution, the authors estimated the association of physical behavior proportions on sleep categories. Physical behavior proportions were operationalized using percentages of wearing time and by applying a compositional approach. All analyses were stratified by gender accounting for differing developmental stages. Results: For males (number of observed days: 345, n = 83), short as compared with optimal sleep was associated with the following day’s proportion spent in sedentary (−2.57%, p = .03, 95% confidence interval [CI] [−4.95, −0.19]) and light-intensity activities (1.96%, p = .02, 95% CI [0.27, 3.65]), which was not significant in the compositional approach models. Among females (number of observed days: 427, n = 104), long sleep was associated with the proportions spent in moderate- to vigorous-intensity physical activity (1.69%, p < .001, 95% CI [0.75, 2.64]) and in sedentary behavior (−3.02%, p < .01, 95% CI [−5.09, −0.96]), which was replicated by the compositional approach models. None of the associations between daytime activity and sleep were significant (number of obs.: 844, n = 204). Conclusions: Results indicate partial associations between sleep and the following day’s physical behaviors, and no associations between physical behaviors and the following night’s sleep.
Nathalie Berninger, Gregory Knell, Kelley Pettee Gabriel, Guy Plasqui, Rik Crutzen, and Gill Ten Hoor
Gregory Knell, Deborah Salvo, Kerem Shuval, Casey Durand, Harold W. Kohl III, and Kelley P. Gabriel
Recent technological advances allow for field-based data collection of accelerometers in community-based studies. Mail-based administration can markedly reduce the cost and logistic challenges and burden associated with in-person data collection. It necessitates, however, other resources, such as phone calls and mailed reminder prompts, to increase protocol compliance and data recovery. Additionally, lost accelerometers can impact the study’s budget and its internal validity due to missing data. In this article, we present an applied methodological approach used to define thresholds (or cutoff points) at which pursuing unreturned accelerometers is a worthwhile versus futile pursuit. This methodological approach was designed, specifically, to maximize scalability across multiple sectors. We used data from an on-going study that administered accelerometers through the mail to illustrate and encourage investigators to replicate the approach for use in their own studies. In heterogeneous study samples, investigators might consider repeating this approach by study-relevant strata to refine thresholds and improve the return percentages of data collection instruments, minimize the potential missing data, and optimize study staff time and resources.
Gregory Knell, Henry S. Brown, Kelley P. Gabriel, Casey P. Durand, Kerem Shuval, Deborah Salvo, and Harold W. Kohl III
Background: Improving sidewalks may encourage physical activity by providing safe, defined, and connected walking spaces. However, it is unknown if reduced health care expenditures assumed by increased physical activity offset the investment for sidewalk improvements. Methods: This cost-effectiveness analysis of sidewalk improvements in Houston, TX, was among adults enrolled in the Houston Travel-Related Activity in Neighborhoods Study, 2013–2017 . The 1-year change in physical activity was measured using self-report (n = 430) and accelerometry (n = 228) and expressed in metabolic equivalent (MET) hours per year (MET·h·y−1). Cost-effectiveness ratios were calculated by comparing annualized sidewalk improvement costs (per person) with 1-year changes in physical activity. Results: The estimated cost-effectiveness ratio were $0.01 and −$0.46 per MET·h·y−1 for self-reported and accelerometer-derived physical activity, respectively. The cost-effectiveness benchmark was $0.18 (95% confidence interval, $0.06–$0.43) per MET·h·y−1 gained based on the volume of physical activity necessary to avoid health care costs. Conclusions: Improving sidewalks was cost-effective based on self-reported physical activity, but not cost-effective based on accelerometry. Study findings suggest that improving sidewalks may not be a sufficient catalyst for changing total physical activity; however, other benefits of making sidewalks more walkable should be considered when deciding to invest in sidewalk improvements.
Kerem Shuval, Liora Sahar, Kelley Pettee Gabriel, Gregory Knell, Galit Weinstein, Tal Gafni Gal, Felipe Lobelo, and Loretta DiPietro
Background: The Rapid Assessment Disuse Index (RADI) is a brief tool aimed to promptly assess primary care patients’ overall physical inactivity and sedentary behavior. This study examines the relation between physical inactivity and sitting time (RADI) to cardiometabolic risk among primary care patients. Methods: Survey data and electronic medical record information were collated to explore the association between RADI scores (cumulative and sitting) to metabolic syndrome (and components) among women and men, using multivariable logistic regression. Results: Among women, the cumulative RADI score was not significantly associated with metabolic syndrome. However, the RADI sitting score was related to low high-density lipoprotein cholesterol and metabolic syndrome. That is, a transition to a higher RADI sitting score by 1 unit (vs remaining in the score) was related with a 1.4 and 1.3 times higher odds for having low high-density lipoprotein cholesterol (95% confidence interval, 1.05–1.87) and metabolic syndrome (95% confidence interval, 1.02–1.64), respectively. Among men, no significant relations were found. Conclusions: The RADI sitting score is positively and significantly related to high-density lipoprotein and metabolic syndrome among women, yet not men. Due to the RADI’s potential clinical utility, future research should attempt to examine these relations in larger, more robust samples and adjudicated outcomes using a prospective design.
Jacob Szeszulski, Kevin Lanza, Erin E. Dooley, Ashleigh M. Johnson, Gregory Knell, Timothy J. Walker, Derek W. Craig, Michael C. Robertson, Deborah Salvo, and Harold W. Kohl III
Background: Multiple models and frameworks exist for the measurement and classification of physical activity in adults that are applied broadly across populations but have limitations when applied to youth. The authors propose a conceptual framework specifically designed for classifying youth physical activity. Methods: The Youth Physical Activity Timing, How, and Setting (Y-PATHS) framework is a conceptualization of the when (timing), how, and where (setting) of children’s and adolescents’ physical activity patterns. The authors developed Y-PATHS using the design thinking process, which includes 3 stages: inspiration, ideation, and implementation. Results: The Y-PATHS includes 3 major components (timing, how, and setting) and 13 subcomponents. Timing subcomponents include (1) school days: in-school, (2) school days: out-of-school, and (3) nonschool days. How subcomponents include: (1) functional, (2) transportation, (3) organized, and (4) free play. Setting subcomponents include: (1) natural areas, (2) schools, (3) home, (4) recreational facilities, (5) shops and services, and (6) travel infrastructure. Conclusions: The Y-PATHS is a comprehensive classification framework that can help researchers, practitioners, and policymakers to better understand youth physical activity. Specifically, Y-PATHS can help to identify the domains of youth physical activity for surveillance and research and to inform the planning/evaluation of more comprehensive physical activity programming.