Council for Agricultural Research and Economics, Research Centre for Food and Nutrition, Rome, Italy.
Servizio Formazione - Presidenza, National Institute of Health, Rome, Italy.
Front Public Health. 2021 Mar 12;9:590315. doi: 10.3389/fpubh.2021.590315. eCollection 2021.
The eating patterns in a population can be estimated through dietary surveys in which open-ended assessment methods, such as diaries and interviews, or semi-quantitative food frequency questionnaires are administered. A harmonized dietary survey methodology, together with a standardized operational procedure, in conducting the study is crucial to ensure the comparability of the results and the accuracy of information, thus reducing uncertainty and increasing the reliability of the results. Dietary patterns (i) include several target variables (foods, energy and nutrients, other food components), (ii) require several explanatory variables (age, gender, anthropometric measurements, socio-cultural and economic characteristics, lifestyle, preferences, attitudes, beliefs, organization of food-related activities, etc.), and (iii) have impacts in several domains: imbalance diets; acute and chronic exposures affect health, specifically non-communicable diseases; and then sanitary expenditure. On the other hand, food demand has impacts on the food system: production, distribution, and food services system; food wastes and other wastes generated by food-related activities of the households (e.g., packaging disposal) have consequences on the "health of the planet" which in turn can have effects on human health. Harmonization and standardization of measurement methods and procedures in such a complex context require an structured information system made by databases (food nomenclatures, portion sizes, food atlas, recipes) and methodological tools (quantification methods, food coding systems, assessment of nutritional status, data processing to extrapolate what we consider validated dietary data). Establishing a community of professionals specialized in dietary data management could lead to build a surveillance system for monitoring eating habits in the short term, thus reducing costs, and to arrange a training re-training system. Creating and maintaining the dietary data managers community is challenging but possible. In this context, the cooperation between the CREA Research Centre for Food and Nutrition and the Italian National Health Institute (ISS) promoted and supported by the Italian Ministry of Health may represent a model of best practice that can ensure a continuous training for the professional community carrying out a nutritional study.
人群的饮食习惯可以通过膳食调查来估计，其中采用开放式评估方法，如日记和访谈，或半定量食物频率问卷进行调查。采用协调一致的膳食调查方法和标准化操作程序进行研究对于确保结果的可比性和信息的准确性至关重要，从而降低不确定性并提高结果的可靠性。饮食习惯 (i) 包括几个目标变量（食物、能量和营养素、其他食物成分），(ii) 需要几个解释变量（年龄、性别、人体测量测量、社会文化和经济特征、生活方式、偏好、态度、信念、与食物相关的活动组织等），以及 (iii) 在几个领域产生影响：饮食不平衡；急性和慢性暴露会影响健康，特别是非传染性疾病；然后是卫生支出。另一方面，食物需求对食物系统有影响：生产、分配和食物服务系统；家庭与食物相关的活动产生的食物浪费和其他废物（例如，包装处理）对“地球健康”产生影响，进而对人类健康产生影响。在这种复杂的情况下，需要一个结构化的信息系统，由数据库（食物命名法、份量、食物图谱、食谱）和方法工具（量化方法、食物编码系统、营养状况评估、数据处理以推断我们认为有效的饮食数据）组成，来协调和标准化测量方法和程序。建立一个专门从事饮食数据管理的专业人员社区，可以建立一个监测短期饮食习惯的监测系统，从而降低成本，并安排培训和再培训系统。创建和维护饮食数据管理员社区具有挑战性，但也是可行的。在这种情况下，CREA 食品与营养研究中心与意大利国家卫生研究所（ISS）之间的合作得到了意大利卫生部的支持和推动，可能代表了一种最佳实践模式，可以确保从事营养研究的专业人员进行持续培训。
