桥梁流行病学证据和饮食健康影响模型:选择风险-结果对的结构化方法
Anna E Jacob1, Claire Dénos2,3,4, Lieselot Boone3
1National Food Institute, Technical University of Denmark, Kgs Lyngby, Denmark.
Critical reviews in food science and nutrition
|January 23, 2026
概括
这项研究通过系统地选择证据并提取剂量反应数据来增强饮食对健康的影响建模. 它创建了一个开放访问的数据库,用于透明的公共卫生营养评估.
科学领域:
- 营养科学 营养科学
- 流行病学 流行病学
- 公共卫生 公共卫生
背景情况:
- 饮食对健康的影响模型对于公共卫生营养至关重要,但在系统的证据选择和剂量反应数据提取方面面临挑战.
- 现有的方法缺乏标准化的风险-结果对选择方法和从文献中协调的数据检索.
研究的目的:
- 更新北欧营养建议2023 (NNR2023) 的流行病学证据库.
- 提出一种比较证据分级系统的方法.
- 开发一种简化方法,从元分析中提取非线性剂量反应曲线.
- 建立一个开放访问的综合饮食证据数据库.
主要方法:
- 复制NNR2023搜索方法用于证据选择.
- 使用修改后的NNR2023标准来选择风险-结果对.
- 采用开源图表阅读器来提取数据点以进行非线性关系估计.
- 适合零碎常数函数来建模剂量反应曲线.
主要成果:
- 包括来自更新和原始NNR2023证据的159个风险结果关联.
- 确定了51种非线性剂量反应关系.
- 大约40%的证据获得了中等范围的确定性.
结论:
- 开发的方法和开放访问数据库提高了饮食对健康影响建模的透明度.
- 提供了一种标准化的方法,用于在公共卫生营养中选择和利用证据.
- 促进更强大,更可靠的健康影响评估.
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