The Relationship Between Moderate to Vigorous Physical Activity and Metabolic Syndrome: a Bayesian Measurement Error Approach

• Activity Number: 349 - Longitudinal, Spatial, and Bayesian Methods
• Type: Contributed
• Date/Time: Tuesday, July 31, 2018 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Daniel Ries* and Alicia Carriquiry
• Companies: Sandia National Laboratories and Iowa State University
• Keywords: measurement error; metabolic syndrome; physical activity; Bayesian; seemingly unrelated regressions

Abstract

Metabolic Syndrome (MetS) is a serious condition that can be an early warning sign of heart disease and type 2 diabetes. MetS is characterized by having elevated levels of blood pressure, cholesterol, waist circumference, and fasting glucose. In order to design interventions, health professionals are interested in the relationship between a MetS diagnosis and physical activity. Most articles in the literature do not consider the measurement error in the physical activity measurements nor the correlations among the MetS risk factors. Using data from the National Health and Nutrition Examination Survey (NHANES), we explore the relationship between minutes in moderate to vigorous physical activity (MVPA) and MetS risk factors. A measurement error model is constructed for the accelerometry data that incorporates the dependence in the data collection design. Nonlinear seemingly unrelated regressions (SUR) incorporate dependence among MetS risk factors. Mixtures of multivariate normal allow for flexibility in the regression errors. We quantify the relationship between the levels of each risk factor and minutes in MVPA.