用随机森林回归算法辨析长寿人群饮食特征与健康指标间量化关系  

Analysis of Quantitative Relationship between Dietary Characteristics and Health Indicators of Long-lived Population by Random Forest Regression Algorithm

作　　者：马金克 宋瑶 韩坤宸 朱雯君 于晓涵 张钦任 张曦予 李全阳[1] MA Jinke;SONG Yao;HAN Kunchen;ZHU Wenjun;YU Xiaohan;ZHANG Qinren;ZHANG Xiyu;LI Quanyang(College of Light Industry and Food Engineering of Guangxi University,Nanning 530000,China)

机构地区：[1]广西大学轻工与食品工程学院,广西南宁530000

出　　处：《食品工业科技》2022年第8期389-398,共10页Science and Technology of Food Industry

基　　金：国家自然科学基金面上项目(31871802);广西重点研发计划项目(桂科AB18221065)。

摘　　要：为探索广西长寿人群饮食特征与其身体健康指标之间潜在的量化关系,于2016~2018年征集广西长寿地区(凤山县、东兰县、上林县、大化县、岑溪市)的长寿人群及其部分后代为对象,采用半定量膳食频率调查问卷法(Food frequency questionnaire,FFQ)量化调查其饮食情况,收集长寿人群的常规体检指标及血液样本分析数据,用熵权法对所得结果相应指标的权重进行计算,进一步引入健康综合指数(Health composite index,HCI)对健康指标进行综合评估,再采用随机森林回归算法对志愿者食物及营养素摄入量与HCI间进行建模,据此探究各个参数之间存在的量化关系,模型的结果采用准确度(Accuracy)评估。结果表明,不同年龄组的BMI、血红蛋白、甘油三脂、C-反应蛋白具有显著性差异;食物组分摄入量及营养素摄入量在不同年龄组间差异性极显著(P<0.001)。百岁组的能量摄入量最低,均值为1451.43 kcal。百岁组的HCI中位数最大(值为0.676)且分布相对集中。经随机森林回归算法建立的8个模型中,百岁组的食物和营养素摄入量对其HCI的回归准确度最高,分别为93.37%和93.40%。其中,高鱼虾类食物摄入量对百岁组HCI影响烈度较大,为0.41;低红肉类食物摄入量对90s组HCI影响烈度较高,为0.20,这也量化反映了水产品和红肉类产品对老人健康状况的影响作用。在本研究涉及的样本间,能量与蛋白质摄入量对HCI影响烈度较低(影响烈度<0.12);维生素A摄入量对HCI影响烈度较高(影响烈度≥0.17)。本研究构建了长寿人群饮食特征与健康指标间的随机森林回归模型,发现高鱼虾类、低红肉类食物摄入量及较高维生素A、高膳食纤维摄入量是百岁组、90s组所特有的饮食特征,对其HCI具有积极影响,这为通过饮食改善人体健康状况提供了参考。同时,该模型阐明的饮食与健康指标间的量化关系,也使得依据饮食特征预测志愿者�To explore the potential quantitative relationship between dietary characteristics and physical health indicators of the long-lived population in Guangxi,the longevous in Guangxi(Fengshan County,Donglan County,Shanglin County,Dahua County,and Cenxi City)and some of their descendants were recruited from 2016 to 2018.A semi-quantitative food frequency questionnaire(FFQ)was used to investigate their diet,routine physical examination indicators and blood sample analysis data of the long-lived population were collected,and the weight of the corresponding indicators obtained was calculated by the entropy weight method.Health composite index(HCI)was further introduced to conduct a comprehensive evaluation of health indicators,and stochastic forest regression algorithm was used to model the relationship between volunteers’food and nutrient intake and HCI,to explore the quantitative relationship between each parameter.The results of the model were evaluated by‘Accuracy’.The results showed that BMI,hemoglobin,triglyceride and C-reactive protein were significantly different in different age groups.There were significant differences in food component intake and nutrient intake among different age groups(P<0.001).The centenarian group had the lowest energy intake,with a mean of1451.43 kcal.The centenarian group had the largest median HCI(0.676)and distribution were relatively concentrated.Among the 8 models established by random forest regression algorithm,the regression accuracy of food and nutrient intake to HCI of the centenarian group was the highest(93.37%and 93.40%,respectively).Among them,high fish and shrimp food intake had a greater impact on HCI in the centenarian group(0.41).Low red meat food intake had a higher impact intensity of 0.20 on HCI in the 90s group,which also quantitatively reflected the impact of aquatic products and red meat products on the health status of the elderly.Among the samples involved in this study,the effect intensity of energy and protein intake on HCI was low(effect intensity<0.12)

关 键 词：长寿人群 饮食特征 健康指标量化 随机森林回归 准确度 

分 类 号：TS201[轻工技术与工程—食品科学]