Background Applying latent class analysis (LCA) to accelerometry can help elucidated
underlying patterns. This study described the patterns of accelerometer-determined …

Latent class analysis can identify unmeasured mutually exclusive categories (class
membership) among participants for either observed categorical or continuous variables …

Background This study described the patterns of accelerometer-determined physical activity
and sedentary behavior among adults using a nationally representative sample from the …

Background Latent class analysis (LCA) identifies distinct groups within a heterogeneous
population, but its application to accelerometry-assessed physical activity and sedentary …

Background: While much is known about the overall levels of physical activity and sedentary
activity among youth, few studies have attempted to define clusters of such behaviors. The …

Background To gain more understanding of the potential health effects of sedentary time,
knowledge is required about the accumulation and longitudinal development of young …

Purpose We used latent class analysis (LCA) to assess patterns of physical activity among
adults, using the 7 d of accelerometer data from the 2003-2004 NHANES. Methods For each …

Purpose: The objective of this study was to quantify age-related changes in accelerometer-
derived day-level physical activity and sedentary behavior pattern metrics (ie, number …

Purpose To identify “activity phenotypes” from accelerometer-derived activity characteristics
among young adults. Methods Participants were young adults (n= 628, mean age, 22.1, SD …

Background Large, heterogeneous datasets are required to enhance understanding of the
multi-level influences on children's physical activity and sedentary behaviour. One route to …