摘要: 大數(shù)據(jù)是一種新興的信息技術(shù)，廣泛應(yīng)用于各行各業(yè)。大數(shù)據(jù)技術(shù)在膳食營養(yǎng)健康中的應(yīng)用主要是結(jié)合營養(yǎng)學(xué)、醫(yī)學(xué)等相關(guān)學(xué)科，利用大數(shù)據(jù)技術(shù)挖掘、分析數(shù)據(jù)，再根據(jù)個(gè)人生理指標(biāo)提供個(gè)性化的信息服務(wù)。本文以Web of Science核心合集和中國知網(wǎng)中文數(shù)據(jù)庫為數(shù)據(jù)來源，利用VOSviewer，對(duì)近10年大數(shù)據(jù)與膳食營養(yǎng)健康領(lǐng)域的相關(guān)文獻(xiàn)進(jìn)行年度發(fā)文量和關(guān)鍵詞分析?？偨Y(jié)分析了大數(shù)據(jù)技術(shù)在膳食營養(yǎng)健康領(lǐng)域中的應(yīng)用以及其所面臨的挑戰(zhàn)。最后，對(duì)大數(shù)據(jù)在膳食營養(yǎng)健康領(lǐng)域的未來研究趨勢(shì)做出了展望，以期為大數(shù)據(jù)技術(shù)在該領(lǐng)域的深入研究及應(yīng)用提供幫助。

Abstract: As an emerging information technology, big data has been widely used in all aspects of life. As for the application of big data technology in dietary nutrition and health, it revolves mainly around the combination of nutrition, medicine and other relevant disciplines, during which big data technology is adopted to mine and analyze data for the provision of personalized information services tailored to personal physiological indicators. With the core collection of Web of Science and CNKI Chinese database as data sources, and VOSviewer is applied in this paper to analyze the annual volume of publication and the keywords of relevant literature on big data as well as dietary nutrition and health published over the past 10 years. Then, the application of big data technology in the field of dietary nutrition and health and the challenges arising from this field are summarized and analyzed. Finally, the future trend of big data research in the field of dietary nutrition and health is indicated, which would provide guidance for the in-depth research and application of big data technology in this field.

圖  1   2011~2021年大數(shù)據(jù)在膳食營養(yǎng)健康領(lǐng)域研究的文獻(xiàn)數(shù)量圖

Figure  1.   Distribution of the number of literatures on big data in the field of dietary nutrition and health from 2011 to 2021

圖  2   CNKI關(guān)鍵詞共現(xiàn)網(wǎng)絡(luò)圖

Figure  2.   CNKI keyword co-occurrence network diagram

圖  3   WOS關(guān)鍵詞共現(xiàn)網(wǎng)絡(luò)圖

Figure  3.   WOS keyword co-occurrence network diagram

表  1   2011~2021年間大數(shù)據(jù)在膳食營養(yǎng)健康相關(guān)研究關(guān)鍵詞共現(xiàn)聚類簇

Table  1   Co-occurrence clusters of big data in dietary nutrition and health related research from 2011 to 2021

聚類編號(hào) CNKI關(guān)鍵詞聚類簇
聚類標(biāo)簽WOS關(guān)鍵詞聚類簇
聚類標(biāo)簽 1hadoop、應(yīng)用研究、數(shù)據(jù)挖掘、
智慧醫(yī)療、糖尿病、飲食管理genetic testing, high-fat diet, metabotying, nutrition,
personalized nutrition, precision nutrition, vitamins
2亞健康、健康管理、大數(shù)據(jù)技術(shù)、
大數(shù)據(jù)時(shí)代、慢性病3 d food printing, 3 d printing, customized fabrication,
muti-material, platform design, printing precision
3個(gè)性化營養(yǎng)、慢性病預(yù)防和管理、
精準(zhǔn)營養(yǎng)、營養(yǎng)基因competitive sports, dietary nutrition, nutrition supplement,
nutrition status, reasonable diet4個(gè)性化推薦、推薦系統(tǒng)、
機(jī)器學(xué)習(xí)、深度學(xué)習(xí)allergic diseases,
metabolic intervention,
pregnancy5云計(jì)算、慢性病管理、物聯(lián)網(wǎng)body mass index, enterotype,
gut microbiota, short-chain fatty acids6云平臺(tái)、互聯(lián)網(wǎng)+、營養(yǎng)健康diet, metabolomics,
obesity, proteomics7信息化平臺(tái)、大數(shù)據(jù)、慢病管理fatty acids, nutrigenomics8體質(zhì)健康、大數(shù)據(jù)平臺(tái)、學(xué)生9營養(yǎng)、營養(yǎng)管理、食品安全10健康領(lǐng)域、大數(shù)據(jù)背景、食品營養(yǎng) 11隱私保護(hù)12管理系統(tǒng)

表  2   國外食物成分?jǐn)?shù)據(jù)庫相關(guān)信息

Table  2   Relevant information of foreign food composition databases

數(shù)據(jù)庫名稱數(shù)據(jù)庫內(nèi)容用途 阿拉伯食物成分?jǐn)?shù)據(jù)庫[35]數(shù)據(jù)庫開發(fā)為在線膳食評(píng)估工具myfood24；包含2016種食物及其大量營養(yǎng)素、微量營養(yǎng)素?cái)?shù)據(jù)
旨在促進(jìn)營養(yǎng)流行病學(xué)研究，幫助測(cè)量阿拉伯人口的
飲食攝入
愛爾蘭食物成分?jǐn)?shù)據(jù)庫[36]共編入938種食品，包括459種復(fù)合菜肴、92種營養(yǎng)補(bǔ)充劑促進(jìn)數(shù)據(jù)共享；為研究人員和決策者提供愛爾蘭特定
食品成分?jǐn)?shù)據(jù)
DietSys[37]包含9851種食品，其中5901種被分配為1至27份或者部分大小的選擇，41% 的食品被歸類為超加工食品用于高效、準(zhǔn)確的飲食分析；用于評(píng)估巴西、阿根廷和
北美居民的飲食攝入量myfood24 FCDB[38]
開發(fā)為在線膳食評(píng)估工myfood24；包含40274常用食品和品牌食品，包含120個(gè)大量營養(yǎng)素、微量營養(yǎng)素?cái)?shù)據(jù)，5669個(gè)食物部分圖像
反映英國消費(fèi)者可獲得的各種食品，并潛在地
提高飲食評(píng)估的準(zhǔn)確性喀里多尼亞食物成分
數(shù)據(jù)庫[39]數(shù)據(jù)庫集成到基于移動(dòng)應(yīng)用程序的24 h召回工具iRecall中，共有972種食品，涵蓋40個(gè)食品類別和25種營養(yǎng)價(jià)值，包括飽和脂肪和總糖對(duì)食物和營養(yǎng)數(shù)據(jù)進(jìn)行更改提供了靈活性；為新喀里多尼亞的居民制定有針對(duì)性的公共衛(wèi)生政策和個(gè)人及社區(qū)一級(jí)的營養(yǎng)干預(yù)，以改善飲食，減少與飲食有關(guān)的健康風(fēng)險(xiǎn)

表  3   營養(yǎng)健康服務(wù)平臺(tái)信息

Table  3   Information on nutrition and health service platform

平臺(tái)名稱結(jié)構(gòu)框架服務(wù)對(duì)象目的 食品安全與營養(yǎng)云服務(wù)平臺(tái)架構(gòu)方案[41]數(shù)據(jù)匯聚層、數(shù)據(jù)處理層、信息分析層、用戶應(yīng)用層
服務(wù)于政府、企業(yè)、
消費(fèi)者、社會(huì)媒體實(shí)現(xiàn)數(shù)據(jù)收集、數(shù)據(jù)處理以及信息服務(wù)膳食營養(yǎng)云服務(wù)
平臺(tái)[42]基礎(chǔ)架構(gòu)即服務(wù)、平臺(tái)即服務(wù)和軟件即服務(wù)，不同云層
提供不同的服務(wù)
一般人群、餐飲企業(yè)、專業(yè)營養(yǎng)師以及公共衛(wèi)生政府部門傳播營養(yǎng)學(xué)及慢性病預(yù)防知識(shí)；獲取人群膳食信息將相關(guān)統(tǒng)計(jì)數(shù)據(jù)快速傳遞給政府后指導(dǎo)民眾營養(yǎng)均衡、科學(xué)膳食；為政府制定
相關(guān)營養(yǎng)政策提供參考依據(jù)
營養(yǎng)健康知識(shí)服務(wù)
系統(tǒng)平臺(tái)[43]知識(shí)資源倉儲(chǔ)層、知識(shí)服務(wù)支撐層、知識(shí)服務(wù)用戶層專家、一般人群打造符合國家營養(yǎng)健康產(chǎn)業(yè)發(fā)展需要的營養(yǎng)健康知識(shí)資源匯聚中心和綜合性知識(shí)服務(wù)平臺(tái)；探索和構(gòu)建營養(yǎng)健康領(lǐng)域知識(shí)服務(wù)模式

表  4   三種疾病監(jiān)測(cè)系統(tǒng)信息

Table  4   Information of three disease surveillance systems

名稱框架用途 高血壓早期預(yù)警和
健康管理平臺(tái)[64]數(shù)據(jù)采集和存儲(chǔ)模塊、健康風(fēng)險(xiǎn)分析模塊、健康指導(dǎo)模塊、健康管理
效果評(píng)價(jià)模塊
利用機(jī)器學(xué)習(xí)的數(shù)學(xué)模型進(jìn)行健康風(fēng)險(xiǎn)評(píng)估，采用大數(shù)據(jù)的Hadoop平臺(tái)。對(duì)與影響
高血壓的有關(guān)因素（攝鹽量、攝油量等）進(jìn)行監(jiān)測(cè)后，由專家給出健康指導(dǎo)意見，
提高患者的知曉率、治療率智能體重管控系統(tǒng)[65]攝入量模塊、輸出量模塊、個(gè)人體重?cái)?shù)據(jù)、群體體重?cái)?shù)據(jù)、預(yù)警模塊依托大數(shù)據(jù)提供專業(yè)、實(shí)時(shí)、高效的智能系統(tǒng)。對(duì)個(gè)人數(shù)據(jù)進(jìn)行長期收集，將個(gè)人數(shù)據(jù)與群體數(shù)據(jù)進(jìn)行比對(duì)，對(duì)用戶在使用過程中的營養(yǎng)素?cái)z入量、熱量、運(yùn)動(dòng)量等直接與
健康情況相關(guān)的各項(xiàng)指標(biāo)進(jìn)行監(jiān)測(cè)，實(shí)時(shí)發(fā)出預(yù)警
糖尿病患者膳食
管理系統(tǒng)[66]用戶層、應(yīng)用層、數(shù)據(jù)層和支持層4層能有效輔助和優(yōu)化糖尿病患者臨床飲食治療工作；利用食物互換法編制飲食方案，
能科學(xué)有效地滿足患者膳食的個(gè)性化需求；為患者、醫(yī)護(hù)人員及管理者之間交流互動(dòng)
提供良好的環(huán)境；為糖尿病的智能預(yù)防、控制和治療提供一個(gè)有效的方法 [1] 張一迪. 大數(shù)據(jù): 進(jìn)入深度應(yīng)用新階段[N]. 中國電子報(bào), 2021-12-21 （ 6 ） .

ZHANG Y D, Big data: Entering a new stage of deep application [N]. China Electronics News, 2021-12-21 （ 6 ） .

[2] 林子雨. 大數(shù)據(jù)技術(shù)原理與應(yīng)用[M]. 北京: 人民郵電出版社: 大數(shù)據(jù)創(chuàng)新人才培養(yǎng)系列, 2017, 1: 301. LIN Z Y. The principle and application of big data technology [M]. Beijing: People's Posts and Telecommunications Press: Big Data Innovative Talent Training Series, 2017, 1: 301. [3] 語沐. 助推數(shù)字中國建設(shè)大數(shù)據(jù)未來可期[N]. 人民郵電, 2021-12-16 （ 6 ） .

YU M. Boosting the construction of digital China with a promising future of big data [N]. People's Posts and Telecommunications, 2021-12-16 （ 6 ） .

[4] 趙碧. “十四五”大數(shù)據(jù)產(chǎn)業(yè)發(fā)展規(guī)劃發(fā)布[N]. 中國產(chǎn)經(jīng)新聞, 2021-12-02 （ 2 ） .

ZHAO B. ''14th Five-Year'' big data industry development plan released [N]. China Sankei News, 2021-12-02 （ 2 ） .

[5] 劉艷, 張肖會(huì), 吳麗. 大數(shù)據(jù)與產(chǎn)業(yè)融合發(fā)展[J]. 天津科技,2021,48(12):4?6. [LIU Y, ZHANG X H, WU L. Integrated development of big data and industry[J]. Tianjin Science and Technology,2021,48(12):4?6. doi: 10.3969/j.issn.1006-8945.2021.12.002 [6]

WANG B, WANG Y J. Big data in safety management: An overview[J]. Safety Science,2021:143. doi: 10.1016/J.SSCI.2021.105414

[7]

KONUR S, LAN Y, THAKKER D, et al. Towards design and implementation of Industry 4.0 for food manufacturing[J]. Neural Comput and Applic, 2021.

[8] 劉愛玲, 馬冠生. 大數(shù)據(jù)在營養(yǎng)領(lǐng)域中的應(yīng)用[J]. 中國食物與營養(yǎng),2015,21(11):5?7. [LIU A L, MA G S. Application of big data in the field of nutrition[J]. China Food and Nutrition,2015,21(11):5?7. doi: 10.3969/j.issn.1006-9577.2015.11.001 [9]

MCDONALD D, GLUSMAN G, PRICE N. Personalized nutrition through big data[J]. Nat Biotechnol,2016,34(5):152?154. doi: 10.1038/nbt.3476

[10]

O'SULLIVAN A, HENRICK B, DIXON B, et al. 21st century toolkit for optimizing population health through precision nutrition[J]. Critical Reviews in Food Science and Nutrition,2018(58):17, 3004?3015.

[11] 駱靖陽, 陸柏益. 基于文獻(xiàn)計(jì)量學(xué)的食品大數(shù)據(jù)技術(shù)研究分析[J]. 食品科學(xué),2021,42(5):278?287. [LUO J Y, LU B Y. Research and analysis of food big data technology based on bibliometrics[J]. Food Science,2021,42(5):278?287. doi: 10.7506/spkx1002-6630-20200408-095 [12] 國民營養(yǎng)計(jì)劃 （ 2017-2030年 ） [J]. 營養(yǎng)學(xué)報(bào), 2017, 39 （ 4 ） : 315?320.

National Nutrition Plan （ 2017-2030 ） [J]. Journal of Nutrition, 2017, 39 （ 4 ） : 315?320.

[13] 《“健康中國2030”規(guī)劃綱要》[J]. 中國預(yù)防醫(yī)學(xué)雜志, 2019, 20（8）: 770.

"Healthy China 2030" Planning Outline[J]. Chinese Journal of Preventive Medicine, 2019, 20（8）: 770.

[14] 《中國居民膳食指南科學(xué)研究報(bào)告 （ 2021 ） 》簡(jiǎn)本[J]. 營養(yǎng)學(xué)報(bào), 2021, 43 （ 2 ） : 102.

A brief version of "Scientific Research Report on Dietary Guidelines for Chinese Residents （ 2021 ） "[J]. Journal of Nutrition, 2021, 43 （ 2 ） : 102.

[15] 陶啟, 李偉, 丁紅衛(wèi), 等. 食品大數(shù)據(jù)應(yīng)用綜述[J]. 食品與生物技術(shù)學(xué)報(bào),2020,39(12):1?5. [TAO Q, LI W, DING H W, et al. A review of the application of food big data[J]. Journal of Food and Biotechnology,2020,39(12):1?5. doi: 10.3969/j.issn.1673-1689.2020.12.001 [16] 王融. 大數(shù)據(jù)時(shí)代[M]. 北京: 人民郵電出版社, 2017, 3: 305.

WANG R. The era of big data [M]. Beijing: People's Posts and Telecommunications Publishing House, 2017, 3: 305.

[17] 于博, 余海忠, 湯尚文, 等. 服務(wù)于食品產(chǎn)業(yè)轉(zhuǎn)型升級(jí)的高新技術(shù)平臺(tái)構(gòu)建研究[J]. 南方農(nóng)業(yè),2017,11(7):56?58. [YU B, YU H Z, TANG S W, et al. Research on the construction of a high-tech platform serving the transformation and upgrading of the food industry[J]. Nanfang Agriculture,2017,11(7):56?58. [18] 李杰, 陳超美. CiteSpace: 科技文本挖掘及可視化[M]. 北京: 首都經(jīng)濟(jì)貿(mào)易大學(xué)出版社, 2016: 194

LI J, CHEN C M. CiteSpace: Science and technology text mining and visualization [M]. Beijing: Capital University of Economics and Business Press, 2016: 194.

[19] 褚宇鹍. 大數(shù)據(jù)背景下青少年體質(zhì)健康監(jiān)測(cè)管理體系構(gòu)建研究[J]. 青少年體育,2020(11):39?40,46. [CHU Y K. Research on the construction of adolescent physical health monitoring and management system under the background of big data[J]. Youth Sports,2020(11):39?40,46. doi: 10.3969/j.issn.2095-4581.2020.11.007 [20] 茹欣. AK養(yǎng)老機(jī)構(gòu)基于“互聯(lián)網(wǎng)+”的老年人健康管理模式研究[D]. 哈爾濱: 哈爾濱工業(yè)大學(xué), 2021.

RU X. Research on the health management model of the elderly based on "Internet+" in AK pension institutions [D]. Harbin: Harbin Institute of Technology, 2021.

[21]

KIM MINJI, JANG WON, JANG SOJEONG. Association of dietary patterns and frailty in elderly: Data from the korea national health and nutrition examination survey 2014~2018[J]. Current Developments in Nutrition,2021,5(Supplement2):1051.

[22] 王楨, 何葉青, 周先利, 等. 醫(yī)學(xué)人工智能輔助開展糖尿病患者遠(yuǎn)程管理探析[J]. 四川醫(yī)學(xué),2021,42(5):488?493. [WANG Z, HE Y Q, ZHOU X L, et al. Research on remote management of diabetic patients assisted by medical artificial intelligence[J]. Sichuan Medicine,2021,42(5):488?493. doi: 10.16252/j.cnki.issn1004-0501-2021.05.012 [23] 尹恒, 秦棋. 數(shù)字健康個(gè)性化營養(yǎng)管理對(duì)妊娠期糖尿病孕婦妊娠結(jié)局的影響[J]. 川北醫(yī)學(xué)院學(xué)報(bào),2021,36(8):982?985. [YIN H, QIN Q. Effects of digital health personalized nutrition management on pregnancy outcomes of pregnant women with gestational diabetes mellitus[J]. Journal of North Sichuan Medical College,2021,36(8):982?985. doi: 10.3969/j.issn.1005-3697.2021.08.008 [24] 朱宵彤. 心血管疾病預(yù)測(cè)模型的研究[D]. 長春: 長春理工大學(xué), 2021.

ZHU X T. Research on the prediction model of cardiovascular disease [D]. Changchun: Changchun University of Science and Technology, 2021.

[25]

DENISE K, DANPING ZHENG, ERAN E. Gut microbiome and its potential link to personalized nutrition [J]. Current Opinion in Physiology, 2021, 22(5).

[26]

YANG J. Genetic testing and personalized nutrition system for men's health care[J]. Computational Science and Its Applications,2021,12957(10):195?204.

[27] 師平, 白亞瓊. 3D打印技術(shù)在食品加工領(lǐng)域中的應(yīng)用[J]. 食品工業(yè),2021,42(10):231?235. [SHI P, BAI Y Q. Application of 3D printing technology in the field of food processing[J]. Food Industry,2021,42(10):231?235. [28] 劉珊慧, 楊樂, 唐建軍. 數(shù)據(jù)庫技術(shù)應(yīng)用基礎(chǔ)[M]. 南京大學(xué)出版社: 普通高等院校“十三五”規(guī)劃教材, 2017, 12: 297.

LIU S H, YANG L, TANG J J. The application basis of database technology [M]. Nanjing University Press: "Thirteenth Five-Year Plan" textbook for ordinary colleges and universities, 2017, 12: 297.

[29]

KAPSOKEFALOU M, ROE M, TURRINI A, et al. Food composition at present: New challenges[J]. Nutrients,2019,11(8):1714. doi: 10.3390/nu11081714

[30]

BALASUBRAMANIAM V, MUSTAR S, ABD RASHED A, et al. Recent techniques in nutrient analysis for food composition database[J]. Molecules,2020,25(19):4567. doi: 10.3390/molecules25194567

[31] 食品數(shù)據(jù)庫[DB/OL]. http://db.foodmate.net/

Food Database[DB/OL]. http://db.foodmate.net/

[32] 馬秀麟, 姚自明, 鄔彤, 等. 數(shù)據(jù)分析方法及應(yīng)用[M]. 北京: 人民郵電出版社, 2015, 5: 302.

MA X L, YAO Z M, WU T, et al. Data analysis methods and applications [M]. Beijing: People's Posts and Telecommunications Press, 2015, 5: 302.

[33] 陸穎. 我國主流消費(fèi)食物營養(yǎng)成分的監(jiān)測(cè)[C]//南京: 營養(yǎng)研究與臨床實(shí)踐——第十四屆全國營養(yǎng)科學(xué)大會(huì)暨第十一屆亞太臨床營養(yǎng)大會(huì)、第二屆全球華人營養(yǎng)科學(xué)家大會(huì)論文摘要匯編[A]. 2019: 441?442.

LU Y. Monitoring of Nutritional Compositions of Mainstream Consumed Foods in my country[C]// Nanjing: Nutrition Research and Clinical Practice—Abstracts of the 14th National Nutrition Science Conference, the 11th Asia-Pacific Clinical Nutrition Conference, and the 2nd Global Chinese Nutrition Scientists Conference[A]. 2019: 441?442.

[34] 王竹. 加強(qiáng)食物成分監(jiān)測(cè), 綜合利用地方特色資源, 為健康中國服務(wù)[J]. 衛(wèi)生研究,2020,49(6):961. [WANG Z. Strengthen the monitoring of food components, comprehensively utilize local characteristic resources, and serve a healthy China[J]. Health Research,2020,49(6):961. [35]

BAWAJEEH AREEJ, KALENDAR SONDOS, SCARPA GIULIA. Development of an Arabic food composition database for use in an Arabic online dietary assessment tool (myfood24)[J]. Journal of Food Composition and Analysis,2021, 80(4):104047.

[36]

BLACK L J, IRELAND J, ROE M, et al. Development of an on-line Irish food composition database for nutrients[J]. Journal of Food Composition and Analysis,2011,24(7):1017?1023. doi: 10.1016/j.jfca.2011.01.015

[37]

RODRIGUES P, LAURA S, NEHA K, et al. Development of DietSys: A comprehensive food and nutrient database for dietary surveys[J]. Journal of Food Composition and Analysis,2021:102.

[38]

CARTER M C, HANCOCK N, BROWN H, et al. Development of a new branded UK food composition database for an online dietary assessment tool[J]. Nutrients,2016,8(8):480. doi: 10.3390/nu8080480

[39]

CHEN J, BERTRAND S, GALY O, et al. The design and development of a food composition database for an electronic tool to assess food intake in new caledonian families[J]. Nutrients,2021,13(5):1668. doi: 10.3390/nu13051668

[40]

OCKé MARGA C, CAROLINE T M. The essential role of food composition databases for public health nutrition -Experiences from the Netherlands[J]. Journal of Food Composition and Analysis,2021:101.

[41] 劉彤, 譚紅, 張經(jīng)華. 基于大數(shù)據(jù)的食品安全與營養(yǎng)云平臺(tái)服務(wù)模式研究[J]. 食品安全質(zhì)量檢測(cè)學(xué)報(bào),2015,6(1):366?371. [LIU T, TAN H, ZHANG J H. Research on the service model of food safety and nutrition cloud platform based on big data[J]. Journal of Food Safety and Quality Inspection,2015,6(1):366?371. doi: 10.19812/j.cnki.jfsq11-5956/ts.2015.01.067 [42] 劉洋, 張桂蕓, 石玉弟. 基于大數(shù)據(jù)的膳食營養(yǎng)云平臺(tái)關(guān)鍵問題思考[J]. 營養(yǎng)學(xué)報(bào),2018,40(4):313?316. [LIU Y, ZHANG G Y, SHI Y D. Thoughts on key issues of the cloud platform for dietary nutrition based on big data[J]. Journal of Nutrition,2018,40(4):313?316. doi: 10.3969/j.issn.0512-7955.2018.04.001 [43] 楊曉燕, 何洪優(yōu), 張波. 基于大數(shù)據(jù)的營養(yǎng)健康知識(shí)服務(wù)系統(tǒng)設(shè)計(jì)研究[J]. 信息技術(shù)與信息化,2018(12):216?218. [YANG X Y, HE H Y, ZHANG B. Research on the design of nutrition and health knowledge service system based on big data[J]. Information Technology and Informatization,2018(12):216?218. doi: 10.3969/j.issn.1672-9528.2018.12.071 [44] 盛實(shí)旺. 個(gè)性化的智能飲食推薦系統(tǒng)開發(fā)[D]. 杭州: 浙江理工大學(xué), 2016: 35?37

SHENG S W. Development of personalized intelligent diet recommendation system [D]. Hangzhou: Zhejiang Sci-Tech University, 2016: 35?37.

[45] 郭廣頌, 席俊杰, 文振華. 個(gè)性化食譜智能優(yōu)化系統(tǒng)[J]. 計(jì)算機(jī)工程與設(shè)計(jì),2021,42(4):1143?1150. [GUO G S, XI J J, WEN Z H. Intelligent optimization system for personalized recipes[J]. Computer Engineering and Design,2021,42(4):1143?1150. doi: 10.16208/j.issn1000-7024.2021.04.035 [46]

YANG L Q, YANG H J, NICOLA D, et al. Yum-Me: A personalized nutrient-based meal recommender system[J]. Association for Computing Machinery,2018,36(1):31.

[47]

DANIEL KIRK, CAGATAY CATAL, BEDIR TEKINERDOGAN. Precision nutrition: A systematic literature review[J]. Computers in Biology and Medicine,2021:133.

[48] 郭英男, 柳鵬, 陳勇言, 等. 精準(zhǔn)營養(yǎng)的實(shí)踐與挑戰(zhàn)[J]. 中國慢性病預(yù)防與控制,2021,29(11):874?878. [GUO Y N, LIU P, CHEN Y Y, et al. Practice and challenges of precision nutrition[J]. Chronic Disease Prevention and Control in China,2021,29(11):874?878. doi: 10.16386/j.cjpccd.issn.1004-6194.2021.11.017 [49]

XU X W, WANG J, LI J. Developing a Chinese food nutr ient data analysis system for precise dietary intake management[J]. Lecture Notes in Computer Science,2018:360?366.

[50] 趙麗云, 郭齊雅, 趙文華. 加強(qiáng)營養(yǎng)調(diào)查與監(jiān)測(cè), 改善中國居民營養(yǎng)與健康狀況[J]. 衛(wèi)生研究,2019,48(4):517?522. [ZHAO L Y, GUO Q Y, ZHAO W H, et al. Strengthening nutrition survey and monitoring to improve the nutrition and health status of Chinese residents[J]. Health Research,2019,48(4):517?522. [51] 國家衛(wèi)生計(jì)生委疾病預(yù)防控制局. 中國居民營養(yǎng)與慢性病狀況報(bào)告[M]. 北京: 人民衛(wèi)生出版社, 2015.

National Health and Family Planning Commission Bureau of Disease Control and Prevention. Report on nutrition and chronic disease status of Chinese residents [M]. Beijing: People's Health Publishing House, 2015.

[52]

PATEL C, PHO N, MCDUFFIE M, et al. A database of human exposomes and phenomes from the US National Health and Nutrition Examination Survey[J]. Sci Data 3,2016:160096. doi: 10.1038/sdata.2016.96

[53]

IKEDA N, TAKIMOTO H, IMAI S, et al. Data resource profile: The Japan national health and nutrition survey (NHNS).[J]. International Journal of Epidemiology,2015,44(6):1842?1849. doi: 10.1093/ije/dyv152

[54] 賴建強(qiáng). “互聯(lián)網(wǎng)+”膳食評(píng)估成為營養(yǎng)工作創(chuàng)新技術(shù)[J]. 中華預(yù)防醫(yī)學(xué)雜志,2017,51(10):878?880. [LAI J Q. "Internet+" dietary assessment has become an innovative technology for nutrition work[J]. Chinese Journal of Preventive Medicine,2017,51(10):878?880. doi: 10.3760/cma.j.issn.0253-9624.2017.10.002 [55] 趙瑩瑩, 楊振宇, 何宇納, 等. 膳食評(píng)估技術(shù)創(chuàng)新與發(fā)展[C]//中國營養(yǎng)學(xué)會(huì)第十三屆全國營養(yǎng)科學(xué)大會(huì)暨全球華人營養(yǎng)科學(xué)家大會(huì)論文匯編[A]. 2017: 217.

ZHAO Y Y, YANG Z Y, HE Y N, et al. Innovation and development of dietary assessment technology [C]//Proceedings of the 13th National Nutrition Science Conference and Global Chinese Nutrition Scientists Conference of the Chinese Nutrition Society[A]. 2017: 217.

[56] 李海通. 基于圖像分析技術(shù)的嬰幼兒膳食智能評(píng)估系統(tǒng)的設(shè)計(jì)與實(shí)現(xiàn)[D]. 北京: 北京郵電大學(xué), 2020.

LI H T. Design and implementation of an intelligent food assessment system for infants and young children based on image analysis technology [D]. Beijing: Beijing University of Posts and Telecommunications, 2020.

[57] 王燁, 于欣平, 賴建強(qiáng). 我國營養(yǎng)調(diào)查未來發(fā)展模式探索[J]. 營養(yǎng)學(xué)報(bào),2017,39(5):431?435. [WANG Y, YU X P, LAI J Q. Exploration on the future development model of nutrition survey in my country[J]. Journal of Nutrition,2017,39(5):431?435. doi: 10.3969/j.issn.0512-7955.2017.05.006 [58] 任向楠, 丁鋼強(qiáng), 彭茂祥, 等. 大數(shù)據(jù)與營養(yǎng)健康研究[J]. 營養(yǎng)學(xué)報(bào),2017,39(1):5?9. [REN X N, DING G Q, PENG M X, et al. Research on big data and nutritional health[J]. Journal of Nutrition,2017,39(1):5?9. doi: 10.3969/j.issn.0512-7955.2017.01.002 [59] 李鵬, 湯志杰. 大數(shù)據(jù)下慢性病患者健康檔案管理系統(tǒng)的實(shí)現(xiàn)[J]. 微型電腦應(yīng)用,2021,37(10):57?59. [LI P, TANG Z J. Realization of chronic disease patient health record management system under big data[J]. Microcomputer Application,2021,37(10):57?59. doi: 10.3969/j.issn.1007-757X.2021.10.016 [60] 馬逸杰, 陳大方. 大數(shù)據(jù)與疾病監(jiān)測(cè)[J]. 傷害醫(yī)學(xué)(電子版),2019,8(1):1?5. [MA Y J, CHEN D F. Big data and disease monitoring[J]. Injury Medicine (Electronic Edition),2019,8(1):1?5. [61] 曾航齊, 黃桂新. 基于Hadoop的醫(yī)療健康檔案大數(shù)據(jù)平臺(tái)構(gòu)建[J]. 中國數(shù)字醫(yī)學(xué),2017,12(7):64?66. [ZENG H Q, HUANG G X. Construction of a big data platform for medical and health records based on Hadoop[J]. China Digital Medicine,2017,12(7):64?66. doi: 10.3969/j.issn.1673-7571.2017.07.019 [62] 賈寧, 李瑛達(dá). 基于智能可穿戴設(shè)備的個(gè)性化健康監(jiān)管平臺(tái)的構(gòu)建[J]. 計(jì)算機(jī)科學(xué),2019,46(S1):566?570. [JIA N, LI Y D. Construction of a personalized health supervision platform based on smart wearable devices[J]. Computer Science,2019,46(S1):566?570. [63] 王勇, 尹鵬飛, 李娟. 基于HBase的健康大數(shù)據(jù)平臺(tái)性能優(yōu)化及應(yīng)用[J]. 軟件導(dǎo)刊,2017,16(10):146?149,158. [WANG Y, YIN P F, LI J. Performance optimization and application of health big data platform based on HBase[J]. Software Guide,2017,16(10):146?149,158. [64] 桂小柯, 張麗杰, 陳禹保, 等. 高血壓早期預(yù)警和健康管理平臺(tái)的構(gòu)建[J]. 中國衛(wèi)生標(biāo)準(zhǔn)管理,2014,5(21):1?3. [GUI X K, ZHANG L J, CHEN Y B, et al. Construction of an early warning and health management platform for hypertension[J]. China Health Standard Management,2014,5(21):1?3. [65] 徐穎穎, 莊彥, 未培. 智能體重管控系統(tǒng)的設(shè)計(jì)[J]. 通化師范學(xué)院學(xué)報(bào),2018,39(12):133?136. [XU Y Y, ZHUANG Y, WEI P. Design of intelligent weight control system[J]. Journal of Tonghua Normal University,2018,39(12):133?136. doi: 10.13877/j.cnki.cn22-1284.2018.12.031 [66] 章琦, 章瑋, 白正玉. 基于大數(shù)據(jù)糖尿病患者膳食管理系統(tǒng)的設(shè)計(jì)[J]. 中國全科醫(yī)學(xué),2021,24(13):1697?1702. [ZHANG Q, ZHANG W, BAI Z Y. Design of dietary management system for diabetic patients based on big data[J]. Chinese General Medicine,2021,24(13):1697?1702. [67] 史鈺斐. 健康醫(yī)療大數(shù)據(jù)發(fā)展應(yīng)用的思考[J]. 無線互聯(lián)科技,2021,18(19):94?95. [SHI Y F. Thinking about the development and application of health and medical big data[J]. Wireless Internet Technology,2021,18(19):94?95. doi: 10.3969/j.issn.1672-6944.2021.19.043 [68] 王燁, 牛然, 于欣平, 賴等. 基于網(wǎng)絡(luò)爬蟲和膳食評(píng)估輔助技術(shù)對(duì)方艙醫(yī)院新冠肺炎患者膳食結(jié)構(gòu)與營養(yǎng)供應(yīng)的分析[J]. 營養(yǎng)學(xué)報(bào),2020,42(3):291?295,300. [WANG Y, NIU R, YU X P, et al. Analysis of dietary structure and nutritional supply of patients with COVID-19 in Fangcang Hospital based on web crawler and dietary assessment assistant technology[J]. Journal of Nutrition,2020,42(3):291?295,300. doi: 10.3969/j.issn.0512-7955.2020.03.017 [69]

MORGENSTERN JASON D, ROSELLA LAURA C, COSTA ANDREW P, et al. Perspective: Big data and machine learning could help advance nutritional epidemiology[J]. Advances in Nutrition,2021,12(3):621?631. doi: 10.1093/advances/nmaa183

[70] 莫祖英, 賀雅文. 大數(shù)據(jù)質(zhì)量管理與數(shù)據(jù)安全性、數(shù)據(jù)成本效益的關(guān)系分析[J]. 管理工程師,2021,26(6):19?25. [MO Z Y, HE Y W. Analysis of the relationship between big data quality management, data security, and data cost-effectiveness[J]. Management Engineer,2021,26(6):19?25. [71] 袁楊. 健康醫(yī)療大數(shù)據(jù)應(yīng)用發(fā)展的SWOT分析[J]. 醫(yī)學(xué)信息學(xué)雜志,2018,39(7):22?26,45. [YUAN Y. SWOT analysis of the application and development of health and medical big data[J]. Journal of Medical Informatics,2018,39(7):22?26,45. doi: 10.3969/j.issn.1673-6036.2018.07.004 [72] 李聯(lián)寧. 大數(shù)據(jù)技術(shù)及應(yīng)用教程[M]. 北京: 清華大學(xué)出版社, 2016.

LI L N. Big data technology and application tutorial [M]: Beijing: Tsinghua University Press, 2016.

[73] 田海平, 劉程. 大數(shù)據(jù)時(shí)代隱私倫理的論域拓展及基本問題——以大數(shù)據(jù)健康革命為例進(jìn)行的探究[J]. 倫理學(xué)研究,2018(3):67?72. [TIAN H P, LIU C. The domain expansion and basic problems of privacy ethics in the era of big data: An exploration of the health revolution of big data[J]. Ethics Research,2018(3):67?72. doi: 10.3969/j.issn.1671-9115.2018.03.014 [74] 李旭, 楊曉燕, 趙宇曦. 營養(yǎng)健康領(lǐng)域的大數(shù)據(jù)應(yīng)用和數(shù)據(jù)安全策略研究[J]. 電子世界,2019(13):92?93. [LI X, YANG X Y, ZHAO Y X. Research on big data application and data security strategy in the field of nutrition and health[J]. Electronic World,2019(13):92?93. doi: 10.19353/j.cnki.dzsj.2019.13.047 [75] 崔曉暉, 李偉, 顧誠淳. 食品科學(xué)大數(shù)據(jù)與人工智能技術(shù)[J]. 中國食品學(xué)報(bào),2021,21(2):1?8. [CUI X H, LI W, GU C C. Food science big data and artificial intelligence technology[J]. Chinese Journal of Food Science,2021,21(2):1?8. doi: 10.16429/j.1009-7848.2021.02.001 [76] 景應(yīng)忠. 貴州銅仁為學(xué)生營養(yǎng)餐撐起“安全云”[J]. 貴州教育,2019(24):23?26. [JING Y Z. Tongren, Guizhou builds up a "safety cloud" for nutritious meals for students[J]. Guizhou Education,2019(24):23?26.

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