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Combining Low Price, Low Climate Impact and High Nutritional Value in One Shopping Basket through Diet Optimization by Linear Programming

Author

Listed:
  • Corné Van Dooren

    (Netherlands Nutrition Centre (Voedingscentrum), Eisenhowerlaan 108, 2508 CK The Hague, The Netherlands
    Institute for Environmental Studies, VU University, Boelelaan 1087, 1081 HV Amsterdam, The Netherlands)

  • Marcelo Tyszler

    (Blonk Consultants, Gravin Beatrixstraat 34, 2805 PJ Gouda, The Netherlands)

  • Gerard F. H. Kramer

    (Blonk Consultants, Gravin Beatrixstraat 34, 2805 PJ Gouda, The Netherlands)

  • Harry Aiking

    (Institute for Environmental Studies, VU University, Boelelaan 1087, 1081 HV Amsterdam, The Netherlands)

Abstract
Background: This study aims to find diets with low price and low climate impact, yet fulfilling all nutritional requirements. Methods: Optimization by linear programming. The program constrains 33 nutrients to fulfill Dutch dietary requirements. In a second cycle, the upper boundary for climate impact through greenhouse gas emissions (GHGE) is set to 1.6 kg carbon dioxide equivalents/day (CO 2 eq). In a third cycle, the costs are set on €2.50 as a constraint. The objective function of the optimization maximized the most consumed food products ( n = 206) for male and female adults separately (age 31–50). Results: A diet of 63 popular and low priced basic products was found to deliver all required nutrients at an adequate level for both male and female adults. This plant-based, carbohydrate and fiber-rich diet consists mainly of wholegrain bread, potatoes, muesli, open-field vegetables and fruits. The climate impact of this diet is very low (1.59 kg CO 2 eq/day) compared to the average Dutch diet. By constraining costs, a low carbon diet of €2.59/day is possible. Conclusions: A two-person diet consisting of 63 products and costing €37 per week can simultaneously be healthy and yet have half the average climate impact. Linear programming is a promising tool to combine health and sustainability on both societal and individual levels.

Suggested Citation

  • Corné Van Dooren & Marcelo Tyszler & Gerard F. H. Kramer & Harry Aiking, 2015. "Combining Low Price, Low Climate Impact and High Nutritional Value in One Shopping Basket through Diet Optimization by Linear Programming," Sustainability, MDPI, vol. 7(9), pages 1-19, September.
  • Handle: RePEc:gam:jsusta:v:7:y:2015:i:9:p:12837-12855:d:55999
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    References listed on IDEAS

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    Cited by:

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    3. Xiaoke Yang & Zhihang Zhang & Huangyixin Chen & Rongrong Zhao & Zhongyue Xu & Anguo Xie & Qiuhua Chen, 2019. "Assessing the Carbon Emission Driven by the Consumption of Carbohydrate-Rich Foods: The Case of China," Sustainability, MDPI, vol. 11(7), pages 1-15, March.
    4. Lamis Jomaa & Lara Nasreddine & Farah Naja & Lara Chehade & Nahla Hwalla, 2021. "Sustainable, Healthy and Affordable Diets for Children in Lebanon: A Call for Action in Dire Times," Sustainability, MDPI, vol. 13(23), pages 1-18, November.
    5. Koenen, Melissa & Balvert, Marleen & Fleuren, H.A., 2023. "A Renewed Take on Weighted Sum in Sandwich Algorithms : Modification of the Criterion Space," Other publications TiSEM 795b6c0c-c7bc-4ced-9d6b-a, Tilburg University, School of Economics and Management.
    6. van Dooren, C. & Keuchenius, C. & de Vries, J.H.M. & de Boer, J. & Aiking, H., 2018. "Unsustainable dietary habits of specific subgroups require dedicated transition strategies: Evidence from the Netherlands," Food Policy, Elsevier, vol. 79(C), pages 44-57.
    7. Christine Cleghorn & Nhung Nghiem & Cliona Ni Mhurchu, 2022. "Assessing the Health and Environmental Benefits of a New Zealand Diet Optimised for Health and Climate Protection," Sustainability, MDPI, vol. 14(21), pages 1-13, October.
    8. Koenen, Melissa & Balvert, Marleen & Fleuren, H.A., 2023. "A Renewed Take on Weighted Sum in Sandwich Algorithms : Modification of the Criterion Space," Discussion Paper 2023-012, Tilburg University, Center for Economic Research.
    9. Rahmatollah Beheshti & Jessica C Jones-Smith & Takeru Igusa, 2017. "Taking dietary habits into account: A computational method for modeling food choices that goes beyond price," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-13, May.

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