2019/02/20 by Isobel Claire Gormley, Gormley, Isobel Claire, Yuxin Bai +3
Agricultural and Biological Sciences · Medicine · #Applications (stat.AP) #Consumer Attitudes and Food Labeling #FOS: Computer and information sciences #Methodology (stat.ME) #Nutritional Studies and Diet #Sensory Analysis and Statistical Methods
paper · pdf · doi:10.48550/arxiv.1902.07711
openalex publication_date 2019/02/20 · openalex created_date 2022/07/29 · openalex updated_date 2026/07/28
Classical approaches to assessing dietary intake are associated with\nmeasurement error. In an effort to address inherent measurement error in\ndietary self-reported data there is increased interest in the use of dietary\nbiomarkers as objective measures of intake. Furthermore, there is a growing\nconsensus of the need to combine dietary biomarker data with self-reported\ndata.\n A review of state of the art techniques employed when combining biomarker and\nself-reported data is conducted. Two predominant methods, the calibration\nmethod and the method of triads, emerge as relevant techniques used when\ncombining biomarker and self-reported data to account for measurement errors in\ndietary intake assessment. Both methods crucially assume measurement error\nindependence. To expose and understand the performance of these methods in a\nrange of realistic settings, their underpinning statistical concepts are\nunified and delineated, and thorough simulation studies conducted.\n Results show that violation of the methods' assumptions negatively impacts\nresulting inference but that this impact is mitigated when the variation of the\nbiomarker around the true intake is small. Thus there is much scope for the\nfurther development of biomarkers and models in tandem to achieve the ultimate\ngoal of accurately assessing dietary intake.\n