Physical activity and sedentary behavior patterns using accelerometry from a national sample of United States adults
- PMID: 25889192
- PMCID: PMC4336769
- DOI: 10.1186/s12966-015-0183-7
Physical activity and sedentary behavior patterns using accelerometry from a national sample of United States adults
Abstract
Background: This study described the patterns of accelerometer-determined physical activity and sedentary behavior among adults using a nationally representative sample from the United States.
Methods: Using 2003-2006 National Health and Nutrition Examination Survey (NHANES) data, 7931 adults at least 18 years old wore an ActiGraph accelerometer for one week, providing at least 3 days of wear for >=8 hours/day. Cutpoints defined moderate to vigorous physical activity (MVPA; >= 2020 and >=760 counts/minute), vigorous physical activity (> = 5999 counts/minute), and sedentary behavior (<100 counts/minute). Latent class analysis (LCA) was used to estimate patterns of physical activity and sedentary behavior. All estimates were weighted to reflect the United States population.
Results: For weighted percent of MVPA out of total wearing time, 5 classes were identified from least to most active: 65.3% of population (weighted mean 9.3 minutes/day), 24.9% (32.1 minutes/day), 3.2% that was low on the weekdays but much higher on the weekends (52.0 minutes/day), 5.9% (59.9 minutes/day), and 0.7% in the highest class (113.6 minutes/day). Using the lower MVPA threshold, 6 classes emerged with each class ranging in population from 1.2% to 43.6%. A vigorous activity class could not be derived due to low prevalence. For weighted percent of sedentary behavior out of total wearing time, 5 classes were identified from most to least sedentary: 6.3% of population (weighted mean 660.2 minutes/day), 25.1% (546.8 minutes/day), 37.7% (453.9 minutes/day), 24.0% (354.8 minutes/day), and 7.0% (256.3 minutes/day). Four of the classes showed generally similar results across every day of the week, with the absolute percents differing across classes. In contrast, the least sedentary class showing a marked rise in percent of time spent in sedentary behavior on the weekend (weighted mean 336.7-346.5 minutes/day) compared to weekdays (weighted mean 255.2-292.4 minutes/day).
Conclusion: The LCA models provided a data reduction process to identify patterns using minute-by-minute accelerometry data in order to explore meaningful contrasts. The models supported 5 or 6 distinct patterns for MVPA and sedentary behavior. These physical activity and sedentary behavior patterns can be used as intervention targets and as independent or dependent variables in future studies of correlates, determinants, or outcomes.
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References
-
- U.S. Department of Health and Human Services: 2008 Physical Activity Guidelines for Americans. ODPHP Publication No. U0036. Washington, D.C.; 2008: 1-61. Accessed September 4, 2014 at http://www.health.gov/paguidelines/.
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