Abstract

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 ad hoc 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.

Highlights

  • The aim of this study is to illustrate the training system created for standardizing a community of professionals to collect food consumption data for surveillance system.“. . . a healthy diet can contribute to achieving the global targets on NCDs adopted by the Sixty-sixth World Health Assembly, including achieving a 25% relative reduction in premature mortality from NCDs by 2025” [1].Health and nutrition policy requires a thoroughly structured information system in order to provide indicators illustrating the current situation [2,3,4]

  • The CREA Centre for Food and Nutrition (CREA Food and Nutrition) and the National Institute of Health (Istituto Superiore di Sanità—ISS) are here sharing the experience that can help to design supportive training system to build communities of professionals able to carry out dietary data surveillance systems generating data for health managers, food system actors, and policymakers

  • The results showed that between 1990 and 2019, The approach chosen after extensive discussion and comparison between the partners of the training project—CREA-Food and Nutrition, Ministry of Health, National Institute of Health, is an approach defined as “blended” (Figure 3)

Read more

Summary

Introduction

Health and nutrition policy requires a thoroughly structured information system in order to provide indicators illustrating the current situation [2,3,4]. This allows for appraising nutritional requirements at population level (LARN), risks intake exposure (EFSA), and possibility to be prone to have a non-communicable disease [5]. Training systems are aimed at enabling interviewers (recall, diet history), administering survey forms (food diaries, food frequency questionnaires), and/or complementary questionnaires (food propensity questionnaire, background, lifestyle, physical activity, nutrition knowledge), and/or duplicating diets [9]

Objectives
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call