Penrose O'Connell C, Gross Phillip J, Singh Hardeep, Rynarzewska Ania Izabela, Ayazo Crystal, Jones Louise
Northeast Georgia Medical Center, Gainesville, GA 30501, USA.
Nutrients. 2025 Jul 28;17(15):2459. doi: 10.3390/nu17152459.
Traditional dietary screeners face significant limitations: they rely on subjective self-reporting, average intake estimates, and are influenced by a participant's awareness of being observed-each of which can distort results. These factors reduce both accuracy and reproducibility. The Guide Against Age-Related Disease (GARD) addresses these issues by applying Assembly Theory to objectively quantify food and food behavior (FFB) complexity. This study aims to validate the GARD as a structured, bias-resistant tool for dietary assessment in clinical and research settings. The GARD survey was administered in an internal medicine clinic within a suburban hospital system in the southeastern U.S. The tool assessed six daily eating windows, scoring high-complexity FFBs (e.g., fresh plants, social eating, fasting) as +1 and low-complexity FFBs (e.g., ultra-processed foods, refined ingredients, distracted eating) as -1. To minimize bias, patients were unaware of scoring criteria and reported only what they ate the previous day, avoiding broad averages. A computer algorithm then scored responses based on complexity, independent of dietary guidelines. Internal (face, convergent, and discriminant) validity was assessed using Spearman rho correlations. Face validation showed high inter-rater agreement using predefined Assembly Index (A) and Copy Number (N) thresholds. Positive correlations were found between high-complexity diets and behaviors (rho = 0.533-0.565, < 0.001), while opposing constructs showed moderate negative correlations (rho = -0.363 to -0.425, < 0.05). GARD scores aligned with established diet patterns: Mediterranean diets averaged +22; Standard American Diet averaged -10.
它们依赖主观的自我报告、平均摄入量估计，并且会受到参与者对被观察的意识的影响——这些因素中的每一个都可能扭曲结果。这些因素降低了准确性和可重复性。抗年龄相关性疾病指南（GARD）通过应用组装理论来客观量化食物和食物行为（FFB）的复杂性，从而解决了这些问题。本研究旨在验证GARD作为临床和研究环境中饮食评估的一种结构化、抗偏差工具。GARD调查是在美国东南部郊区医院系统的内科诊所进行的。该工具评估了六个每日饮食时段，将高复杂性的FFB（例如，新鲜植物、社交性饮食、禁食）评分为+1，将低复杂性的FFB（例如，超加工食品、精制成分、分心饮食）评分为 -1。为了尽量减少偏差，患者不知道评分标准，只报告前一天吃了什么，避免宽泛的平均值。然后，一个计算机算法根据复杂性对回答进行评分，与饮食指南无关。使用斯皮尔曼等级相关系数评估内部（表面、收敛和区分）效度。表面效度显示，使用预定义的组装指数（A）和拷贝数（N）阈值，评分者间的一致性很高。高复杂性饮食与行为之间存在正相关（rho = 0.533 - 0.565，< 0.001），而相反的结构显示出中等程度的负相关（rho = -0.363至 -0.425，< 0.05）。GARD评分与既定的饮食模式一致：地中海饮食平均为 +22；标准美国饮食平均为 -10。
