期刊论文详细信息
Data in Brief
Applying latent class assignments for accelerometry data to external populations: Data from the National Health and Nutrition Examination Survey 2003–2006
Annie Green Howard1  Amy H. Herring1  Kelly R. Evenson2  Fang Wen2 
[1] Department of Biostatistics at the Gillings School of Global Public Health, Carolina Population Center, University of North Carolina – Chapel Hill, Chapel Hill, North Carolina, United States;Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina – Chapel Hill, Chapel Hill, North Carolina, United States;
关键词: Epidemiology;    Exercise;    Latent class analysis;    Physical activity;    Mortality;    Prevention;    Sedentary behavior;   
DOI  :  10.1016/j.dib.2016.11.007
来源: DOAJ
【 摘 要 】

Latent class analysis can identify unmeasured mutually exclusive categories (class membership) among participants for either observed categorical or continuous variables. More recently, latent class analysis has been applied to accelerometry to better understand the day-to-day patterns of physical activity and sedentary behavior. Typically, the class assignments are only relevant to the study for which they were derived and not made available for others to use. Using one-week accelerometry (ActiGraph #AM7164) data collected from the National Health and Nutrition Examination Survey during 2003–2006, latent classes of physical activity and sedentary behavior were derived separately for youths 6–17 years and adults >=18 years. The purpose of this article is to provide the latent class assignments developed on this source population (United States) available to others to apply to their studies using similarly collected accelerometry. This method will extend the usefulness of the latent class analysis and allow for comparisons across studies.

【 授权许可】

Unknown   

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