| 摘要: |
| ［摘要］ 目的 基于老年人群饮食结构构建预测认知功能障碍的列线图模型。方法 选取中国老年健康影响因素跟踪调查（CLHLS）2018年数据，研究对象为65岁及以上老年人。饮食结构基于面对面访谈收集的食物消费频率计算，认知功能采用简易精神状态检查量表（MMSE）进行评估。应用R 4.6.1软件的caret包，将符合标准的6 681名研究对象按7∶3比例随机划分为训练集与验证集，其中训练集4 677名，验证集2 004名。基于训练集数据，通过logistic回归分析筛选独立预测因子，并构建列线图模型。采用受试者工作特征（ROC）曲线、校准曲线及决策曲线分析评价列线图模型的预测效能及临床适用性。结果 多因素logistic回归模型筛选出包括年龄、性别、主食类型、蔬菜、鱼类、蛋类、奶制品、坚果、海藻、维生素补剂、饮酒、体质量指数共12个老年人认知障碍的独立影响因素，并构建列线图模型。模型区分度良好，训练集和验证集的曲线下面积（AUC）分别为0.782和0.736；校准曲线显示预测概率与实际观测值拟合良好；决策曲线分析表明，在5%～80%阈值概率范围内模型净获益优于“全部干预”、“不干预”策略，证实该列线图具有良好的临床应用价值。结论 该列线图模型在预测老年人认知功能障碍方面具有一定的临床价值，所包含的临床预测因子均可从日常生活评估中便捷获取。 |
| 关键词: 饮食结构 认知障碍 列线图 中国老年健康影响因素跟踪调查数据库 |
| DOI：10.3969/j.issn.1674-3806.2026.07.14 |
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| Construction of a nomogram model for predicting cognitive impairment in older adults based on dietary patterns |
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Zhang Jian1, Li Hui2, Sun Yongfu1, Fan Ruijun3
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1.Department of Laboratory Medicine, the Second Clinical Medical School of Ningxia Medical University, the First People′s Hospital of Yinchuan, Yinchuan 750004, China; 2.Department of Laboratory Medicine, the Second People′s Hospital of Yinchuan, Yinchuan 750001, China; 3. Clinical Laboratory Diagnostics Center, People′s Hospital of Ningxia Hui Autonomous Region, Yinchuan 750001, China
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| Abstract: |
| ［Abstract］ Objective To construct a nomogram model for predicting cognitive impairment in older adults based on their dietary patterns. Methods The data were selected from the 2018 Chinese Longitudinal Healthy Longevity Survey(CLHLS), and the participants were adults aged 65 years and older. Dietary patterns were calculated based on the consumption frequency of food items collected through face-to-face interviews. Cognitive function was assessed by using the Mini-Mental State Examination(MMSE) scale. A total of 6 681 participants who met the criteria were randomly divided into a training set and a validation set at a ratio of 7∶3 using the statistical software R package “caret”(4.6.1), with 4 677 participants in the training set and 2 004 participants in the validation set. Based on the training set data, logistic regression analysis were conducted to screen independent predictors and construct a nomogram model. Receiver operating characteristic(ROC) curve, calibration curve and decision curve analysis(DCA) were used to assess the predictive efficacy and clinical applicability of the nomogram model. Results Twelve independent influencing factors of cognitive impairment in the older adults were screened out by a multivariate logistic regression model, including age, gender, staple food type, vegetables, fish, eggs, dairy products, nuts, seaweed, vitamin supplements, alcohol consumption and body mass index(BMI). Based on these influencing factors, a nomogram model was constructed. The nomogram showed good discriminative ability, and the area under the curve(AUC) in the training set and the validation set was 0.782 and 0.736, respectively. The calibration curve showed a good agreement between the predicted probabilities and the actual observed values. The DCA showed that within the threshold probabilities ranging from 5% to 80%, the net benefit of the model was better than that of “all the interventions” and that of “no interventions” strategies, proving that the nomogram model had good clinical practical value. Conclusion The nomogram model has certain clinical application value in predicting cognitive impairment in older adults, and its included clinical predictors can be conveniently obtained from routine assessments. |
| Key words: dietary patterns cognitive impairment nomogram Chinese Longitudinal Healthy Longevity Survey(CLHLS) database |
