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Accelerometry-Assessed Latent Class Patterns of Physical Activity and Sedentary Behavior With Mortality.

ABSTRACT: Latent class analysis provides a method for understanding patterns of physical activity and sedentary behavior. This study explored the association of accelerometer-assessed patterns of physical activity/sedentary behavior with all-cause mortality.The sample included 4,510 U.S. National Health and Nutrition Examination Survey participants aged ?40 years enrolled in 2003-2006 with mortality follow-up through 2011. Participants used a hip-worn accelerometer for 1 week that provided minute-by-minute information on physical activity/sedentary behavior. Accelerometry patterns were derived using latent class analysis. Cox proportional hazards models provided adjusted hazard ratios with 95% CIs. Analyses were conducted from 2014 to 2016.During an average of 6.6 years of follow-up, 513 deaths occurred. For average counts/minute, the more-active classes had a lower risk of mortality compared with the lowest (Class 1). Findings were generally similar for percentage of the day in minutes and bouts of moderate to vigorous physical activity, defined two ways. For percentage of the day in sedentary behavior, generally no associations were identified. However, the class with the highest percentage of the day in sedentary bouts (Class 1) had a higher risk of mortality (adjusted hazard ratio, 2.10; 95% CI=1.11, 3.97) versus the class with fewer sedentary bouts (Class 7).In this national observational study, time spent in physical activity reduced the risk of all-cause mortality and time spent in sedentary bouts increased the risk of all-cause mortality, regardless of how both were accumulated. The latent class analysis contributed to understanding the impact of patterning of physical activity and sedentary behavior on mortality.

SUBMITTER: Evenson KR

PROVIDER: S-EPMC5260614 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Accelerometry-Assessed Latent Class Patterns of Physical Activity and Sedentary Behavior With Mortality.

Evenson Kelly R KR Herring Amy H AH Wen Fang F

American journal of preventive medicine 20170201 2

<h4>Introduction</h4>Latent class analysis provides a method for understanding patterns of physical activity and sedentary behavior. This study explored the association of accelerometer-assessed patterns of physical activity/sedentary behavior with all-cause mortality.<h4>Methods</h4>The sample included 4,510 U.S. National Health and Nutrition Examination Survey participants aged ≥40 years enrolled in 2003-2006 with mortality follow-up through 2011. Participants used a hip-worn accelerometer for ...[more]

PMID: 28109457

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Project description:BackgroundThe constructs and interdependency of physical behaviors are not well described and the complexity of physical activity (PA) data analysis remains unexplored in COPD. This study examined the interrelationships of 24-hour physical behaviors and investigated their associations with participant characteristics for individuals with mild-moderate airflow obstruction and healthy control subjects.Patients and methodsVigorous PA (VPA), moderate-to-vigorous PA (MVPA), light PA (LPA), stationary time (ST), average movement intensity (vector magnitude counts per minute), and sleep duration for 109 individuals with COPD and 135 healthy controls were obtained by wrist-worn accelerometry. Principal components analysis (PCA) examined interrelationships of physical behaviors to identify distinct behavioral constructs. Using the PCA component loadings, linear regressions examined associations with participant (+, positive correlation; -, negative correlation), and were compared between COPD and healthy control groups.ResultsFor both groups PCA revealed ST, LPA, and average movement intensity as distinct behavioral constructs to MVPA and VPA, labeled "low-intensity movement" and "high-intensity movement," respectively. Sleep was also found to be its own distinct behavioral construct. Results from linear regressions supported the identification of distinct behavioral constructs from PCA. In COPD, low-intensity movement was associated with limitations with mobility (-), daily activities (-), health status (+), and body mass index (BMI) (-) independent of high-intensity movement and sleep. High-intensity movement was associated with age (-) and self-care limitations (-) independent of low-intensity movement and sleep. Sleep was associated with gender (0= female, 1= male; [-]), lung function (-), and percentage body fat (+) independent of low-intensity and high-intensity movement.ConclusionDistinct behavioral constructs comprising the 24-hour day were identified as "low-intensity movement," "high-intensity movement," and "sleep" with each construct independently associated with different participant characteristics. Future research should determine whether modifying these behaviors improves health outcomes in COPD.

Dataset Information

Accelerometry-Assessed Latent Class Patterns of Physical Activity and Sedentary Behavior With Mortality.

Publications

Accelerometry-Assessed Latent Class Patterns of Physical Activity and Sedentary Behavior With Mortality.

Similar Datasets

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