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OP84 Adapting the online dietary assessment tool ( myfood24 ) for Indigenous communities in the peruvian amazon to research food biodiversity and climate change resilience
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  1. Carol Zavaleta-Cortijo1,
  2. Rosalia Montero1,
  3. Rosa Silvera1,
  4. Andrea Valdivia-Gago1,
  5. Delfina Catip2,
  6. Rocilda Nunta2,
  7. Connie Fernandez3,
  8. Guillermo Lancha4,
  9. Pedro Pizango4,
  10. Juan-Pablo Aparco5
  1. 1Facultad de Salud Publica (FASPA), Universidad Peruana Cayetano Heredia, Lima, Peru
  2. 2Programa Mujer, Asociación Interétnica de Desarrollo de la Selva Peruana (AIDESEP), Lima, Peru
  3. 3Hospital Santa Gema, Direccion Regional de Salud Loreto, Yurimaguas, Peru
  4. 4Pueblo Shawi, Yurimaguas, Peru
  5. 5Centro Nacional de Alimentación y Nutrición (CENAN), INS, Lima, Peru

Abstract

Background Over the past ten years Amazon region has experienced multiple environmental changes including high rates of deforestation, and more frequent ‘once in a century’ extreme weather events. Despite this it is still not clear how these events effect food biodiversity, local diets and nutrition of Amazon Indigenous people. Information on food consumption is urgently needed, especially to identify key Amazonian Indigenous foods which may increase nutritional resilience to extreme climate events. Technological tools represent a potential feasible solution to measure diet for population studies. We have partnered with International researchers, local nutritionist, Indigenous leaders and community members to adapt a digital tool to support dietary measurement in Amazonian Indigenous communities.

Methods The adaptation had three stages. First working with an international multidisciplinary committee, we identified and compiled existing food composition databases to create a database for the Peruvian myfood24 version to use with communities of Shawi ethnicity. Seven food composition tables were identified, and permission was requested for two cases where information was not public. Six food composition tables, one academic publication and one peruvian report about amazon food species, were used for generating a food composition database. Second, using myfood24 guidelines, we completed a data base using Access software. This process involved cleaning and removing duplicate food items, including conversion values (from raw to cooked foods) and calculations for potential nutrient losses on cooking. We used a series of six online focus groups meetings with three peruvian nutritionists, including one nutritionist expert on the Shawi diet, to identify portions, and combinations. Finally, during a workshop with five local community members, a list of Shawi foods were validated, and food preparation was characterised to develop recipes and to take pictures for use in the online tool.

Results The peruvian food composition database to be used with the Shawi communities included a total of 1042 food items, with information for 14 key nutrients. These foods were split into fourteen food categories. Seventy-six possible options on how food is eaten together, and 43 portion measurements were validated in the focus groups. 114 food items were identified in the workshop as commonly consumed by Shawi, with five forest animal foods proving the highest level of iron per 100 g: palm larvae (3.6mg), armadillo (3.5mg), deer (3.5mg), paca (3.4mg) and agouti (3.4mg).

Conclusion A comprehensive Peruvian Food Composition Database with a focus on Shawi diet has been created. This data has been incorporated within the online dietary assessment tool, myfood24. A photo Album and recipes will be completed over the next weeks. The new tool with be useful to understand how food and nutrient intakes in this vulnerable population are affected by climate change events.

  • biodiversity
  • diet quality
  • food composition database

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