TY - JOUR
T1 - Characterizing Measurement Error in Dietary Sodium in Longitudinal Intervention Studies
AU - Pittman, Adam
AU - Stuart, Elizabeth A.
AU - Siddique, Juned
N1 - Publisher Copyright:
© Copyright © 2020 Pittman, Stuart and Siddique.
PY - 2020/11/27
Y1 - 2020/11/27
N2 - Background: Previous measurement error work that investigates the relationship between a nutritional biomarker and self-reported intake levels has typically been at a single time point, in a single treatment group, or with respect to basic patient demographics. Few studies have examined the measurement error structure in longitudinal randomized trials, and whether the error varies across time or group. This structure is crucial to understand, however, in order to correct for measurement error in self-reported outcomes and properly interpret the longitudinal effects of dietary interventions. Methods: Using two longitudinal randomized controlled trials with internal longitudinal validation data (urinary biomarkers and self-reported values), we examine the relationship between urinary sodium and self-reported sodium and whether this relationship changes as a function of time and/or treatment condition. We do this by building a mixed effects regression model, allowing for a flexible error variance-covariance structure, and testing all possible interactions between time, treatment condition, and self-reported intake. Results: Using a backward selection approach, we arrived at the same final model for both validation data sets. We found no evidence that measurement error changes as a function of self-reported sodium. However, we did find evidence that urinary sodium can differ by time or treatment condition even when conditioning on self-reported values. Conclusion: In longitudinal nutritional intervention trials it is possible that measurement error differs across time and treatment groups. It is important for researchers to consider this possibility and not just assume non-differential measurement error. Future studies should consider data collection strategies to account for the potential dynamic nature of measurement error, such as collecting internal validation data across time and treatment groups when possible.
AB - Background: Previous measurement error work that investigates the relationship between a nutritional biomarker and self-reported intake levels has typically been at a single time point, in a single treatment group, or with respect to basic patient demographics. Few studies have examined the measurement error structure in longitudinal randomized trials, and whether the error varies across time or group. This structure is crucial to understand, however, in order to correct for measurement error in self-reported outcomes and properly interpret the longitudinal effects of dietary interventions. Methods: Using two longitudinal randomized controlled trials with internal longitudinal validation data (urinary biomarkers and self-reported values), we examine the relationship between urinary sodium and self-reported sodium and whether this relationship changes as a function of time and/or treatment condition. We do this by building a mixed effects regression model, allowing for a flexible error variance-covariance structure, and testing all possible interactions between time, treatment condition, and self-reported intake. Results: Using a backward selection approach, we arrived at the same final model for both validation data sets. We found no evidence that measurement error changes as a function of self-reported sodium. However, we did find evidence that urinary sodium can differ by time or treatment condition even when conditioning on self-reported values. Conclusion: In longitudinal nutritional intervention trials it is possible that measurement error differs across time and treatment groups. It is important for researchers to consider this possibility and not just assume non-differential measurement error. Future studies should consider data collection strategies to account for the potential dynamic nature of measurement error, such as collecting internal validation data across time and treatment groups when possible.
KW - biomarkers
KW - lifestyle intervention
KW - measurement error
KW - nutrition
KW - self-reporting habits
KW - sodium intake
UR - http://www.scopus.com/inward/record.url?scp=85106818097&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85106818097&partnerID=8YFLogxK
U2 - 10.3389/fnut.2020.581439
DO - 10.3389/fnut.2020.581439
M3 - Article
C2 - 33330581
AN - SCOPUS:85106818097
SN - 2296-861X
VL - 7
JO - Frontiers in Nutrition
JF - Frontiers in Nutrition
M1 - 581439
ER -