Weaver Connie, Armah Seth, Bruno Richard S, Fletcher Andrew, Glahn Raymond, Herter-Aeberli Isabelle, Karosas Tasija, Loechl Cornelia U, Lopez-Teros Veronica, McBurney Michael I, Melse-Boonstra Alida, Novotny Rachel, Reddy Manju B, Rigutto-Farebrother Jessica, Tanumihardjo Sherry, Udomkesmalee Emorn, Van Den Heuvel Ellen, Wallace Taylor, Winichagoon Pattanee
School of Exercise and Nutritional Sciences, San Diego State University, San Diego, CA, United States.
Department of Nutrition, University of North Carolina at Greensboro, Greensboro, NC, United States.
Adv Nutr. 2025 Jul 17;16(9):100481. doi: 10.1016/j.advnut.2025.100481.
Current nutrient intake recommendations, nutritional assessments, and food labeling rely on estimated total nutrient content in foods and dietary supplements. However, the adequacy of nutrient intake depends not only on the total amount consumed but also on the fraction absorbed and utilized by the body. Accurate assessments of nutrient bioavailability require predictive equations or algorithms. This paper outlines a 4-step framework designed to guide researchers in developing such equations. The framework includes: 1) identifying key factors that influence nutrient or bioactive compound bioavailability; 2) conducting a comprehensive literature review of high-quality human studies to inform the development of predictive equations; 3) constructing predictive equations based on these insights; and 4) validate the equation, when feasible, to potentiate translation. This structured approach aims to enhance the accuracy and precision of nutrient bioavailability estimates, address data limitations, and highlight evidence gaps to inform future research and policy on nutrients and bioactive compounds.
当前的营养素摄入建议、营养评估和食品标签都依赖于对食品和膳食补充剂中营养素总含量的估计。然而,营养素摄入是否充足不仅取决于摄入的总量,还取决于身体吸收和利用的部分。准确评估营养素的生物利用度需要预测方程或算法。本文概述了一个4步框架,旨在指导研究人员开发此类方程。该框架包括:1)确定影响营养素或生物活性化合物生物利用度的关键因素;2)对高质量的人体研究进行全面的文献综述,以为预测方程的开发提供信息;3)基于这些见解构建预测方程;4)在可行的情况下验证方程,以促进转化。这种结构化方法旨在提高营养素生物利用度估计的准确性和精确性,解决数据限制问题,并突出证据差距,为未来关于营养素和生物活性化合物的研究及政策提供信息。