Assessing adult physical activity and compliance with 2008 CDC guidelines using a Bayesian two-part measurement error model

by   Daniel Ries, et al.

While there is wide agreement that physical activity is an important component of a healthy lifestyle, it is unclear how many people adhere to public health recommendations on physical activity. The Physical Activity Guidelines (PAG), published by the CDC, provide guidelines to American adults, but it is difficult to assess compliance with these guidelines. The PAG further complicate adherence assessment by recommending activity to occur in at least 10 minute bouts. To better understand the measurement capabilities of various instruments to quantify activity, and to propose an approach to evaluate activity relative to the PAG, researchers at Iowa State University administered the Physical Activity Measurement Survey (PAMS) to over 1,000 participants in four different Iowa counties. In this paper, we develop a two-part Bayesian measurement error model and apply it to the PAMS data in order to assess compliance to the PAG in the Iowa adult population. The model accurately accounts for the 10 minute bout requirement put forth in the PAG. The measurement error model corrects biased estimates and accounts for day to day variation in activity. The model is also applied to the nationally representative National Health and Nutrition Examination Survey.


A Function-Based Approach to Model the Measurement Error in Wearable Devices

Physical activity (PA) is an important risk factor for many health outco...

The Relationship between Moderate to Vigorous Physical Activity and Metabolic Syndrome: A Bayesian Measurement Error Approach

Metabolic Syndrome (MetS) is a serious condition that can be an early wa...

Smoothing spline analysis of variance models: A new tool for the analysis of accelerometer data

Accelerometer data is commonplace in physical activity research, exercis...

A fully Bayesian semi-parametric scalar-on-function regression (SoFR) with measurement error using instrumental variables

Wearable devices such as the ActiGraph are now commonly used in health s...

Posture Recognition in the Critical Care Settings using Wearable Devices

Low physical activity levels in the intensive care units (ICU) patients ...

Modeling complex measurement error in microbiome experiments

The relative abundances of species in a microbiome is a scientifically i...

Does built environment influence physical activity and body postures in homework journeys?

Understanding the effects of built environment on physical activity is i...

Please sign up or login with your details

Forgot password? Click here to reset