Citation:
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Abstract:
In the context of clinical and epidemiologic research, dietary intake is a particularly complex exposure to measure given the vast diversity of foods consumed globally, with variation in consumption patterns across eating occasions, days, seasons, and the life cycle. Assessing intake is challenged by measurement error arising from various sources, including imperfect recall of foods consumed in retrospective assessments, such as 24-hour diet recalls and food-frequency questionnaires, and reactivity associated with real-time recording in the case of food records. In analysis and interpretation, further complexity is introduced by the diversity of dietary components often of interest in a given study, related to the growing recognition of the need to account for the multidimensionality of intake to holistically characterize and translate the effects of dietary patterns on health and disease risk. These challenges, resulting gaps in the quantity and quality of dietary intake data available for populations globally, and resulting deficits in time-relevant and evidence-based strategies for improving dietary patterns continue to inspire innovative approaches that attempt to surmount challenges faced by conventional dietary assessment methods. As of October 2022, this methods collection includes seven video articles describing the development, evaluation, and/or application of innovative dietary assessment and analysis methods and tools that researchers may consider applying in their own work. Three of the articles describe the protocol for developing the method to assist interested researchers in creating similar methods tailored to specific settings or populations. The methods incorporate aspects of nutritional, behavioral, and computer science and mechanical, electrical, and software engineering, highlighting the importance of broad interdisciplinary and integrative perspectives to innovation in this field.