一个方法框架来推导德国基于食物的饮食指南2024:食品组,营养目标和目标功能
Anne Carolin Schäfer1,2, Heiner Boeing3, Rozenn Gazan4
1German Nutrition Society, Bonn, Germany.
PloS one
|March 12, 2025
概括
饮食优化模型对于基于食物的饮食指南 (FBDGs) 至关重要. 这项研究为这些模型制定了一个框架,展示了不同的目标功能如何影响饮食建议和营养目标的实现.
科学领域:
- 营养科学与公共卫生
- 饮食学中的计算建模.
- 粮食政策和指导方针的制定
背景情况:
- 饮食优化越来越多地用于制定基于食物的饮食指南 (FBDGs),以平衡健康和可持续性.
- 对优化模型参数缺乏系统的研究和报告,这阻碍了一致的应用.
研究的目的:
- 在FBDG开发中建立饮食优化模型的框架.
- 使用等级食品分类来定义决策变量.
- 探索对象函数和营养目标结合的数学形式.
主要方法:
- 作为德国成年人饮食数据 (n=10,419) 的决策变量,利用了FoodEx2食物组 (3-7级).
- 开发了12个模型,不同的目标函数类型 (线性/正方形,相对/绝对偏差) 和营养目标列表 (allNUT-DRV,modNUT-DRV,modNUT-AR).
- 整合了可接受性约束和最小化了与平均观察摄入量的偏差.
主要成果:
- 食品Ex2食物组是优化饮食的合适决策变量.
- 目标函数类型显著影响了改性食品组的数量,平方绝对显示了最大的变化 (248组).
- 所有模型都达到营养目标,但线性相对模型具有最多的结合营养约束.
结论:
- 该研究提供了一个基本框架,用于在FBDGs的优化模型中运行饮食方面.
- 展示了方法选择对饮食优化结果的影响.
- 为改进公共卫生营养中的饮食优化方法提供了见解.
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