IIEP   24411
INSTITUTO INTERDISCIPLINARIO DE ECONOMIA POLITICA DE BUENOS AIRES
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
Calculating nutrient consumption statistics from household national surveys: pitfalls and opportunities
Autor/es:
ESTEFANIA CUSTODIO; SOFÍA JIMENEZ-CALVO; MARIA PRISCILA RAMOS
Reunión:
Seminario; Seminar D4 JRC Seville; 2020
Resumen:
Accurate data on dietary habits is essential to assess the impact and to inform the priorities of food related policies, and individual dietary intake surveys are considered the most precise method for estimating energy and nutrient intakes. However, although many developed countries carry out periodic individual dietary intake surveys only seldom low-income countries do so, due to the high costs, the time burden and the technical capacities they require. For those countries, the FAO food balance sheets (FBS) have been widely used for the estimation of caloric and nutrient intakes. However, FBS are not meant to assess the dietary diversity of a population and their level of concordance with results derived from national individual dietary intakes have been shown to be very low. In recent years, the focus has been on national household surveys (e.g. Household Budget Surveys, Household Consumption and Expenditure Surveys, etc) as alternative vehicles to collect this type of information. These surveys gather data on food consumption as an integral part of their multipurpose questionnaires, are conducted in a regular basis in many countries and are less costly than individual dietary intake surveys. However, they are not specifically designed for diet or food security analysis and that is why the methods to treat and analyse the data and to interpret the results becomes specially relevant. In this seminar we will present different methodological approaches and the ADePT-Food Security Module (ADePT-FSM) software developed by the World Bank and the Statistics Division of FAO to facilitate food security and nutrient analysis based on household survey data.