gms | German Medical Science

Gesundheit – gemeinsam. Kooperationstagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS), Deutschen Gesellschaft für Sozialmedizin und Prävention (DGSMP), Deutschen Gesellschaft für Epidemiologie (DGEpi), Deutschen Gesellschaft für Medizinische Soziologie (DGMS) und der Deutschen Gesellschaft für Public Health (DGPH)

08.09. - 13.09.2024, Dresden

Optimization modelling to identify sustainable diets for adults in Ouagadougou, Burkina Faso

Meeting Abstract

  • Dorothee Liu - Heidelberg Institute of Global Health (HIGH), Medical Faculty and University Hospital Heidelberg, Heidelberg University, Heidelberg, Germany
  • Anais Gonnet - Heidelberg Institute of Global Health (HIGH), Medical Faculty and University Hospital Heidelberg, Heidelberg University, Heidelberg, Germany
  • Gabriel Kallah-Dagadu - Heidelberg Institute of Global Health (HIGH), Medical Faculty and University Hospital Heidelberg, Heidelberg University, Heidelberg, Germany; University of KwaZulu-Natal (UKZN), Durban, South Africa
  • Roch Modeste Millogo - Institut Supérieur des Sciences de la Population (ISSP), Université Joseph Ki-Zerbo, Ouagadougou, Burkina Faso
  • Issa Coulibaly - Institut Supérieur des Sciences de la Population (ISSP), Université Joseph Ki-Zerbo, Ouagadougou, Burkina Faso
  • Idrissa Ouili - Institut Supérieur des Sciences de la Population (ISSP), Université Joseph Ki-Zerbo, Oagadougou, Burkina Faso
  • Abdramane Soura - Institut Supérieur des Sciences de la Population (ISSP), Université Joseph Ki-Zerbo, Oagadougou, Burkina Faso
  • Ina Danquah - Heidelberg Institute of Global Health (HIGH), Medical Faculty and University Hospital Heidelberg, Heidelberg University, Heidelberg, Germany; Hertz-Chair Innovation for Planetary Health and Center for Development Research (ZEF), University of Bonn, Bonn, Germany

Gesundheit – gemeinsam. Kooperationstagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS), Deutschen Gesellschaft für Sozialmedizin und Prävention (DGSMP), Deutschen Gesellschaft für Epidemiologie (DGEpi), Deutschen Gesellschaft für Medizinische Soziologie (DGMS) und der Deutschen Gesellschaft für Public Health (DGPH). Dresden, 08.-13.09.2024. Düsseldorf: German Medical Science GMS Publishing House; 2024. DocAbstr. 125

doi: 10.3205/24gmds531, urn:nbn:de:0183-24gmds5319

Published: September 6, 2024

© 2024 Liu et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. See license information at http://creativecommons.org/licenses/by/4.0/.


Outline

Text

Background: Optimization modelling constitutes a promising method for prototyping sustainable diets that are nutritionally adequate, climate-friendly, affordable, and socio-culturally acceptable [1]. In sub-Saharan Africa, rapid urbanization and economic growth confer an ongoing nutrition transition, characterized by shifts towards unsustainable diets rich in animal products and processed foods [2]. This study aimed to develop sustainable diets by optimization modelling for adults living in formal and informal settlements in Ouagadougou, Burkina Faso.

Methods: We used cross-sectional data collected within the Ouagadougou Health and Demographic Surveillance System (HDSS) between February and April 2021, involving 1000 adults (≥ 25 years) living in formal and informal settlements [3]. Dietary intake was assessed using a semi-quantitative food frequency questionnaire, the African Food Propensity Questionnaire (APFQ), that captures the intake of 134 food items over the past 12 months. Greenhouse gas emissions were calculated using the International Standard Organization (ISO) standards (14040 and 14044) on product life cycle assessment (LCA), and ISO 14067 on the carbon footprint of products, and prices of the food items were collected in local supermarkets in Ouagadougou. Per settlement type and sex, quadratic programming was performed to obtain optimal combinations of food intake in three cycles to achieve i) nutritional adequacy and cultural acceptability; ii) plus 50% reduction in greenhouse gas emissions (GHGE); and iii) plus maintaining the observed food costs.

Results: In this study population (median age: 42 years (IQR: 21); female: 64.3%), the most common food groups were coffee and tea (median intake: 282.6 g/d (IQR: 546.4)), rice, pasta and corn (median intake: 233.7 g/d (IQR: 148.2)), and maize-based foods (median intake: 220.0 g/d (IQR: 700.0)), and median energy intake was 1834.1 kcal/d (IQR: 908.1). Median GHGE were 3256.4 g CO2-e/d (IQR: 3755.4) and median costs were 3.2 €/d (IQR: 2.2). After three cycles, optimization modelling yielded shifts from animal-based protein sources (meat, dairy) to plant-based sources (legumes, nuts), as well as increased intakes of vegetables, starchy foods, eggs, and partly, fish. However, in none of the settlement types, the recommended intake for calcium (1000 g/d) was met. In informal settlements, critical nutrients were folate (for both sexes) and dietary fiber (for males).

Conclusion: The optimized diets for this study population emphasize a shift from animal- to plant-based proteins as a feasible option within the constraints of nutrient requirements, socio-cultural acceptability, GHGEs and food costs. The identified critical nutrients should be considered in future public health measures and supplementation programs. The optimized diets form a prototype of sustainable diets in the target population.

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.


References

1.
Van Dooren C. A Review of the Use of Linear Programming to Optimize Diets, Nutritiously, Economically and Environmentally. Front Nutr. 2018;5:48.
2.
Popkin BM. Nutrition Transition and the Global Diabetes Epidemic. Curr Diab Rep. 2015;15(9):64.
3.
Weil K, Coulibaly I, Fuelbert H, Herrmann A, Millogo RM, Danquah I. Dietary patterns and their socioeconomic factors of adherence among adults in urban Burkina Faso: a cross-sectional study. J Health Popul Nutr. 2023;42(1):107.