PO.PS01.06 · 人群科学
在UK Biobank中运用高斯图模型的网络方法评估膳食模式与结直肠癌风险
A network approach using Gaussian graphical models to evaluate dietary patterns and colorectal cancer risk in the UK Biobank
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
背景：当前关于膳食模式与结直肠癌（CRC）关系的研究依赖于对摄入量进行汇总而未考虑食物组之间结构性依赖关系的方法。高斯图模型（GGMs）通过捕捉各类食物如何相互关联地被摄入来推导膳食模式，为整体饮食行为提供了基于网络的视角。目的：我们旨在使用GGMs识别膳食模式，并考察其与UK Biobank中新发CRC的关联。方法：这项前瞻性队列研究纳入了105,676名具有24小时膳食回顾数据的UK Biobank参与者。使用由43个食物组构建的GGMs识别膳食模式，并将参与者按各模式评分分为三分位。应用Cox比例风险模型估计风险比（HRs）和95%置信区间（CIs），并对人口统计学、生活方式和临床因素进行校正。结果：在中位随访10.1年期间，新诊断1,026例CRC。该网络识别出由不同食物组构成的四种膳食模式。在按性别分层的分析中，加工食品和甜点模式在男性中与较高的CRC风险相关，最高三分位显示风险升高（HR = 1.23；95% CI：1.00-1.50；P-趋势 = 0.048）。在女性中，均衡模式与CRC呈负相关，最高三分位显示风险较低（HR = 0.82；95% CI：0.60-0.93；P-趋势 = 0.041）。在总体或按性别分层的分析中，其他膳食模式（包括以蛋白质为主的模式和饮料模式）均未观察到显著关联。结论：通过GGMs识别的基于网络的膳食模式显示出与CRC风险不同的性别特异性关联。通过处理食物变量之间的成对相关性同时控制其他食物的间接影响，该方法能够比传统模式方法更具特异性地捕捉膳食结构。这些结果有助于在现有流行病学证据框架内更清晰地理解性别特异性膳食模式与CRC风险的关系。
查看英文原文 English abstract
Background : Current research on the link between dietary patterns and colorectal cancer (CRC) has relied on methods that summarize intake without accounting for the structural dependencies among food groups. Gaussian graphical models (GGMs) derive dietary patterns by capturing how foods are consumed in relation to one another, offering a network-based view of overall eating behavior.
Objectives : We aimed to identify dietary patterns using GGMs and to examine their associations with incident CRC in the UK Biobank.
Methods : This prospective cohort study included 105,676 UK Biobank participants with 24-hour recall dietary data. Dietary patterns were identified using GGMs constructed from 43 food groups, and participants were classified into tertiles of each pattern score. Cox proportional hazards models were applied to estimate hazard ratios (HRs) and 95% confidence intervals (CIs), adjusting for demographic, lifestyle, and clinical factors.
Results : Over a median follow-up of 10.1 years, 1,026 cases of CRC were newly diagnosed. The network identified four dietary patterns consisting of different food groups. In sex-stratified analyses, the processed food and dessert pattern was associated with higher CRC risk in male, with the highest tertile showing increased risk (HR = 1.23; 95% CI: 1.00-1.50; P -trend = 0.048). In female, the balanced pattern was inversely associated with CRC, with the highest tertile showing lower risk (HR = 0.82; 95% CI: 0.60-0.93; P -trend = 0.041). No significant associations were observed for the other dietary patterns, including the protein-based and beverage patterns, in the total or sex-stratified analyses.
Conclusions : Network-based dietary patterns identified through GGMs showed different sex-specific associations with CRC risk. By addressing pairwise correlations between food variables while controlling for indirect effects from other foods, this approach captures dietary structures with greater specificity than traditional pattern methods. These results contribute to a clearer understanding of how sex-specific dietary patterns relate to CRC risk within existing epidemiologic evidence.
利益披露 Disclosure
J. Hwang, None..
S. Cho, None..
A. Shin, None.