Estimating the Cost and Ratio of the Optimal Food Basket by Iranians to the Minimum Wage

Document Type : Research Paper

Authors

1 Department of Community Nutrition, Faculty of Nutrition, Tabriz University of Medical Sciences, Tabriz, Iran.

2 Department of Health Economics, Faculty of Management and Medical Informatics, Tabriz Health Services Management Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.

Abstract

Introduction: Estimating the food supply cost is one of the essential applications of optimal food baskets. This study aimed to calculate the cost of an optimal food basket for Iranians and the ratio of the cost of an optimal food basket to the minimum wage in 2020 and 2021.  Methods: This cross-sectional study estimated the costs and ratio of the optimal food basket to the workers' minimum wage from the perspective of economically vulnerable groups. The cost approach was based on the research data, using forms and checklists prepared by the researcher and referring to information published by the Statistics Center, the Central Bank, and the Ministry of Welfare. Excel software was used to calculate and draw graphs. Results: This study showed the high cost of red meat, fruits, and dairy products. The lowest cost was for pasta, sugar, and potatoes. The per capita cost of an optimal food basket for one day in 2020 and 2021 was 223576 and 306833 Rials, respectively. The ratio of the cost of an optimal food basket of the minimum wage in 2020 and 2021 was 57% and 50%, respectively. Conclusion: The study's most crucial finding was the importance of purchasing power adequacy in providing the optimal food basket. This finding underscored the urgency of addressing wage issues, particularly in the lower-income and working classes, as a significant basis for determining wages and planning for sustainable development.

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References

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Journal of Nutrition,Fasting and Health
Volume 12, Issue 3
September 2024
Pages 189-195

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History

  • Receive Date: 11 February 2024
  • Revise Date: 27 March 2024
  • Accept Date: 03 April 2024

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