Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Global food expenditure patterns diverge between low-income and high-income countries

Abstract

Globalization, income growth and changing cultural trends are believed to prompt consumers in low-income countries to adopt the more affluent diet of high-income countries. This study investigates the convergence of food expenditure patterns worldwide, focusing on total food expenditure, raw food categories and ultra-processed foods and beverages across more than 90 countries over the past decades. Contrary to prior belief, we find that food expenditure patterns of lower-income countries do not universally align with those of higher-income nations. This trend is evident across most raw food categories and ultra-processed foods and beverages, as the income level of a country continues to play a crucial role in determining its food expenditure patterns. Importantly, expenditure patterns offer estimates rather than a precise idea of dietary intake, reflecting consumer choices shaped by economic constraints rather than exact dietary consumption.

This is a preview of subscription content, access via your institution

Access options

Buy this article

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Average budget share on total food and stimulants and each category across different income-group countries in 2019.
Fig. 2: Budget share on total food and stimulants and each category across different clubs or groups over the years.
Fig. 3: Geographical distribution of clubs or groups in each food category.

Similar content being viewed by others

Data availability

All food expenditure data and other socio-economic factors used in this study are available on Euromonitor (https://www.euromonitor.com/usa) by subscription. Source data are provided with this paper.

Code availability

The code is available upon reasonable request.

References

  1. Springmann, M. et al. Options for keeping the food system within environmental limits. Nature 562, 519–525 (2018).

    Article  ADS  CAS  PubMed  Google Scholar 

  2. Azzam, A. Is the world converging to a ‘Western diet’? Public Health Nutr. 24, 309–317 (2021).

    Article  PubMed  Google Scholar 

  3. Chepeliev, M. Spillover effects of dietary transitions. Nat. Food 4, 458–459 (2023).

    Article  PubMed  Google Scholar 

  4. Vasileska, A. & Rechkoska, G. Global and regional food consumption patterns and trends. Procedia Social Behav. Sci. 44, 363–369 (2012).

    Article  Google Scholar 

  5. Yi, J. et al. Post-farmgate food value chains make up most of consumer food expenditures globally. Nat. Food 2, 417–425 (2021).

    Article  PubMed  Google Scholar 

  6. Pingali, P. Westernization of Asian diets and the transformation of food systems: implications for research and policy. Food Policy 32, 281–298 (2007).

    Article  Google Scholar 

  7. Bentham, J. et al. Multidimensional characterization of global food supply from 1961 to 2013. Nat. Food 1, 70–75 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Fukase, E. & Martin, W. Economic growth, convergence, and world food demand and supply. World Dev. 132, 104954 (2020).

    Article  Google Scholar 

  9. Chatzimpiros, P. & Harchaoui, S. Sevenfold variation in global feeding capacity depends on diets, land use and nitrogen management. Nat. Food 4, 372–383 (2023).

    Article  CAS  PubMed  Google Scholar 

  10. Tilman, D. & Clark, M. Global diets link environmental sustainability and human health. Nature 515, 518–522 (2014).

    Article  ADS  CAS  PubMed  Google Scholar 

  11. Vaidyanathan, G. What humanity should eat to stay healthy and save the planet. Nature 600, 22–25 (2021).

    Article  ADS  CAS  PubMed  Google Scholar 

  12. Hasegawa, T., Havlík, P., Frank, S., Palazzo, A. & Valin, H. Tackling food consumption inequality to fight hunger without pressuring the environment. Nat. Sustain. 2, 826–833 (2019).

    Article  Google Scholar 

  13. Swinburn, B. A. et al. The global obesity pandemic: shaped by global drivers and local environments. Lancet 378, 804–814 (2011).

    Article  PubMed  Google Scholar 

  14. Popkin, B. M. & Reardon, T. Obesity and the food system transformation in Latin America. Obesity Rev. 19, 1028–1064 (2018).

    Article  CAS  Google Scholar 

  15. Yuan, S. et al. Trends in dietary patterns over the last decade and their association with long-term mortality in general US populations with undiagnosed and diagnosed diabetes. Nutr. Diabetes 13, 5 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  16. O’Hearn, M. et al. Incident type 2 diabetes attributable to suboptimal diet in 184 countries. Nat. Med. 29, 982–995 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Regmi, A., Takeshima, H. & Unnevehr, L. J. Convergence in food demand and delivery: do middle-income countries follow high-income trends? J. Food Distrib. Res. 39, 116–122 (2008).

    Google Scholar 

  18. Popkin, B. M., Adair, L. S. & Ng, S. W. Global nutrition transition and the pandemic of obesity in developing countries. Nutr. Rev. 70, 3–21 (2012).

    Article  PubMed  Google Scholar 

  19. Popkin, B. M. & Hawkes, C. Sweetening of the global diet, particularly beverages: patterns, trends, and policy responses. Lancet Diabetes Endocrinol. 4, 174–186 (2016).

    Article  PubMed  Google Scholar 

  20. Gatto, A., Kuiper, M. & van Meijl, H. Economic, social and environmental spillovers decrease the benefits of a global dietary shift. Nat. Food 4, 496–507 (2023).

    Article  PubMed  Google Scholar 

  21. Michail, N. A. Convergence of consumption patterns in the European Union. Empirical Econ. 58, 979–994 (2020).

    Article  Google Scholar 

  22. Garnett, T., Mathewson, S., Angelides, P. & Borthwick, F. Policies and actions to shift eating patterns: what works. Foresight 515, 518–522 (2015).

    Google Scholar 

  23. Gilbert, P. A. & Khokhar, S. Changing dietary habits of ethnic groups in Europe and implications for health. Nutr. Rev. 66, 203–215 (2008).

    Article  PubMed  Google Scholar 

  24. Singh, G. M. et al. Estimated global, regional, and national disease burdens related to sugar-sweetened beverage consumption in 2010. Circulation 132, 639–666 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Anand, S. S. et al. Food consumption and its impact on cardiovascular disease: importance of solutions focused on the globalized food system: a report from the workshop convened by the World Heart Federation. J. Am. Coll. Cardiol. 66, 1590–1614 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Sun, H. et al. Global disease burden attributed to high sugar-sweetened beverages in 204 countries and territories from 1990 to 2019. Preventive Med. 175, 107690 (2023).

    Article  Google Scholar 

  27. Micha, R. et al. Global, regional, and national consumption levels of dietary fats and oils in 1990 and 2010: a systematic analysis including 266 country-specific nutrition surveys. Brit. Med. J. 348, g2272 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Phillips, P. C. & Sul, D. Transition modeling and econometric convergence tests. Econometrica 75, 1771–1855 (2007).

    Article  MathSciNet  Google Scholar 

  29. Phillips, P. C. & Sul, D. Economic transition and growth. J. Appl. Econom. 24, 1153–1185 (2009).

    Article  MathSciNet  Google Scholar 

  30. De Long, J. B. Productivity growth, convergence, and welfare: comment. Am. Econ. Rev. 78, 1138–1154 (1988).

    Google Scholar 

  31. Quah, D. Galton’s fallacy and tests of the convergence hypothesis. Scand. J. Econ. 95, 427–443 (1993).

    Article  Google Scholar 

  32. Desli, E. & Gkoulgkoutsika, A. World economic convergence: does the estimation methodology matter? Econ. Modell. 91, 138–147 (2020).

    Article  Google Scholar 

  33. Barro, R. J. & Sala-i-Martin, X. Convergence. J. Polit. Econ. 100, 223–251 (1992).

    Article  Google Scholar 

  34. Pesaran, M. H. A pair-wise approach to testing for output and growth convergence. J. Econom. 138, 312–355 (2007).

    Article  MathSciNet  Google Scholar 

  35. Stadnytska, T. Deterministic or stochastic trend: decision on the basis of the augmented Dickey–Fuller test. Methodology 6, 83–92 (2010).

    Article  Google Scholar 

  36. Von Lyncker, K. & Thoennessen, R. Regional club convergence in the EU: evidence from a panel data analysis. Empirical Econ. 52, 525–553 (2017).

    Article  Google Scholar 

  37. Bartkowska, M. & Riedl, A. Regional convergence clubs in Europe: identification and conditioning factors. Econ. Modell. 29, 22–31 (2012).

    Article  Google Scholar 

  38. Lyons, S., Mayor, K. & Tol, R. S. Convergence of consumption patterns during macroeconomic transition: a model of demand in Ireland and the OECD. Econ. Modell. 26, 702–714 (2009).

    Article  Google Scholar 

  39. Reardon, T. et al. The processed food revolution in African food systems and the double burden of malnutrition. Glob. Food Secur. 28, 100466 (2021).

    Article  Google Scholar 

  40. Xia, L. et al. Global food insecurity and famine from reduced crop, marine fishery and livestock production due to climate disruption from nuclear war soot injection. Nat. Food 3, 586–596 (2022).

    Article  PubMed  Google Scholar 

  41. Lucas, E., Guo, M. & Guillén-Gosálbez, G. Low-carbon diets can reduce global ecological and health costs. Nat. Food 4, 394–406 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  42. Spronk, I., Kullen, C., Burdon, C. & O’Connor, H. Relationship between nutrition knowledge and dietary intake. Br. J. Nutr. 111, 1713–1726 (2014).

    Article  CAS  PubMed  Google Scholar 

  43. Baker, P. et al. Ultra‐processed foods and the nutrition transition: global, regional and national trends, food systems transformations and political economy drivers. Obesity Rev. 21, e13126 (2020).

    Article  Google Scholar 

  44. Frazão, E., Meade, B. G. S. & Regmi, A. Converging patterns in global food consumption and food delivery systems. Amber Waves 6, 22–29 (2008).

    Google Scholar 

  45. Popkin, B. M. & Ng, S. W. The nutrition transition to a stage of high obesity and noncommunicable disease prevalence dominated by ultra‐processed foods is not inevitable. Obesity Rev. 23, e13366 (2022).

    Article  Google Scholar 

  46. Baker, P. et al. First‐food systems transformations and the ultra‐processing of infant and young child diets: the determinants, dynamics and consequences of the global rise in commercial milk formula consumption. Maternal Child Nutr. 17, e13097 (2021).

    Article  Google Scholar 

  47. Du, K. Econometric convergence test and club clustering using Stata. Stata J. 17, 882–900 (2017).

    Article  Google Scholar 

  48. Busetti, F., Fabiani, S. & Harvey, A. Convergence of prices and rates of inflation. Oxford Bull. Econ. Stat. 68, 863–877 (2006).

    Article  Google Scholar 

  49. Kearney, J. Food consumption trends and drivers. Philos. Trans. R. Soc. B 365, 2793–2807 (2010).

    Article  Google Scholar 

  50. Djekic, I. et al. Cultural dimensions associated with food choice: a survey based multi-country study. Int. J. Gastron. Food Sci. 26, 100414 (2021).

    Article  Google Scholar 

  51. Wang, J., Yuan, W. & Rogers, C. L. Economic development program spending in the US: is there club convergence? Appl. Econ. 55, 5097–5114 (2023).

    Article  Google Scholar 

  52. McFadden, D. in Frontiers in Econometrics (ed. Zarembka, P.) 105–139 (Academic Press, 1973).

  53. Morales-Lage, R., Bengochea-Morancho, A., Camarero, M. & Martínez-Zarzoso, I. Club convergence of sectoral CO2 emissions in the European Union. Energy Policy 135, 111019 (2019).

    Article  Google Scholar 

  54. World Bank Country and Lending Groups (World Bank, 2024); https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups

Download references

Acknowledgements

This study was supported by the project founded by the US Department of Agriculture, Foreign Agricultural Service (USDA-FX22TA-10960R022, W. Li).

Author information

Authors and Affiliations

Authors

Contributions

W. Li conceptualized and supervised the project. W. Liang analysed the data. W. Liang and P.S. collected the data and drafted the paper. Y.H. created the figures. All authors contributed to revising and editing the manuscript.

Corresponding authors

Correspondence to Wanqi Liang or Wenying Li.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Food thanks Nektarios Michail and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Tables 1–15.

Reporting Summary

Source data

Source Data Fig. 1

Statistical source data for the pie and bar plots.

Source Data Fig. 2

Statistical source data for the line plots.

Source Data Fig. 3

Statistical source data for the maps.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liang, W., Sivashankar, P., Hua, Y. et al. Global food expenditure patterns diverge between low-income and high-income countries. Nat Food 5, 592–602 (2024). https://doi.org/10.1038/s43016-024-01012-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s43016-024-01012-y

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing