Characterizing Measurement Error in Dietary Sodium in Longitudinal Intervention Studies
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 measurem...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2020-11-01
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| Series: | Frontiers in Nutrition |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnut.2020.581439/full |
| _version_ | 1818648805881413632 |
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| author | Adam Pittman Elizabeth A. Stuart Elizabeth A. Stuart Juned Siddique |
| author_facet | Adam Pittman Elizabeth A. Stuart Elizabeth A. Stuart Juned Siddique |
| author_sort | Adam Pittman |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-17T01:24:16Z |
| format | Article |
| id | doaj.art-92d5b3456b6e41aca3d689173736d56b |
| institution | Directory Open Access Journal |
| issn | 2296-861X |
| language | English |
| last_indexed | 2024-12-17T01:24:16Z |
| publishDate | 2020-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Nutrition |
| spelling | doaj.art-92d5b3456b6e41aca3d689173736d56b2022-12-21T22:08:44ZengFrontiers Media S.A.Frontiers in Nutrition2296-861X2020-11-01710.3389/fnut.2020.581439581439Characterizing Measurement Error in Dietary Sodium in Longitudinal Intervention StudiesAdam Pittman0Elizabeth A. Stuart1Elizabeth A. Stuart2Juned Siddique3Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United StatesDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United StatesDepartment of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United StatesDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United StatesBackground: 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.https://www.frontiersin.org/articles/10.3389/fnut.2020.581439/fulllifestyle interventionmeasurement errornutritionsodium intakebiomarkersself-reporting habits |
| spellingShingle | Adam Pittman Elizabeth A. Stuart Elizabeth A. Stuart Juned Siddique Characterizing Measurement Error in Dietary Sodium in Longitudinal Intervention Studies Frontiers in Nutrition lifestyle intervention measurement error nutrition sodium intake biomarkers self-reporting habits |
| title | Characterizing Measurement Error in Dietary Sodium in Longitudinal Intervention Studies |
| title_full | Characterizing Measurement Error in Dietary Sodium in Longitudinal Intervention Studies |
| title_fullStr | Characterizing Measurement Error in Dietary Sodium in Longitudinal Intervention Studies |
| title_full_unstemmed | Characterizing Measurement Error in Dietary Sodium in Longitudinal Intervention Studies |
| title_short | Characterizing Measurement Error in Dietary Sodium in Longitudinal Intervention Studies |
| title_sort | characterizing measurement error in dietary sodium in longitudinal intervention studies |
| topic | lifestyle intervention measurement error nutrition sodium intake biomarkers self-reporting habits |
| url | https://www.frontiersin.org/articles/10.3389/fnut.2020.581439/full |
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