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Effect of climate-driven childhood sleep erosion on potential regional economic inequality

Nature Sustainability (2026)Cite this article

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Abstract

Climate change is likely to increase human exposure to high temperatures, leading to sleep loss. Reduced sleep duration may impair intellectual and cognitive performance, including in childhood, with potential socioeconomic impacts. Here we explore the potential global and regional economic costs of diminished childhood cognitive performance related to future climate-driven sleep erosion. Relative to the 2001–2010 baseline, excess sleep loss worldwide is projected to reach 16.37 h per year per person by the 2100s under a high-emissions scenario. Correspondingly, the associated economic costs linked to sleep erosion and potential intellectual decline are estimated to reach trillions of dollars. Less-developed regions are projected to experience greater per-capita potential intelligence quotient losses and are likely to bear several times the relative economic burden faced by the wealthiest regions, thereby probably exacerbating global environmental and economic inequalities. Our findings advance understanding of the health and economic effects of climate change and can inform fair climate policies.

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Fig. 1: Country projections of excess population-weighted sleep loss related to temperature warming under three SSP scenarios compared with the baseline values.
Fig. 2: Projections of children’s IQ point loss per capita related to temperature-driven sleep loss in different countries and regions at the end of the century.
Fig. 3: The potential economic costs of IQ loss related to temperature-driven sleep loss at the end of century under three SSP scenarios.

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Data availability

The data that support the findings of this study are all available from publicly available sources. Atmospheric and climate variables can be collected from ISIMIP3b at https://data.isimip.org/. Population projections are based on the work of ref. 52 and available at https://data.nasa.gov/dataset/global-one-eighth-degree-population-base-year-and-projection-grids-based-on-the-shared-soc. Age structure projections we used are from United Nations Department of Economic and Social Affairs at https://population.un.org/wpp/. Historical GDP and future projections of GDP were collected from the World Bank at https://data.worldbank.org/ and IIASA at https://tntcat.iiasa.ac.at/SspDb/, respectively. IQ distributions among regions we referred to are presented from National IQ dataset 1.3.2 at https://viewoniq.org/?p=124.

Code availability

We used MATLAB2021b and R software (version 4.1.1, R Project) to perform the main analysis. The main codes in this study are publicly available on GitHub at https://github.com/Bowen-NJU/Climate_sleep_IQ.

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Acknowledgements

This study is supported by the National Natural Science Foundation of China (grants 42588101 and 42475191 to H.W.; 725B2019 to L.L.); the Fundamental Research Funds for the Central Universities - Cemac ‘GeoX’ Interdisciplinary Program (20250306 to H.W.); Central University Basic Scientific Research Business Expenses Special Funds (2025300124 to Y.P.); Jiangsu Provincial Decision-making Consultation Research Base Project (24SSL040 to Y.P.); Lab of Global Climate Change Disaster Effects and Technology-enabled Emergency Management of Nanjing University; and the Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, China. We thank the Nanjing University Supercomputer Center and Institute of Social Science Survey, Peking University, for their assistance.

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Authors and Affiliations

  1. Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, China

    Bowen Chu, Yijing Zhu, Jianfeng Luo, Jiuyi Chen & Haikun Wang

  2. Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA

    Xiang Liu

  3. Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, China

    Yijing Zhu

  4. School of Government, Nanjing University, Nanjing, China

    Lan Luo & Yi Peng

  5. Department of the Geophysical Sciences, University of Chicago, Chicago, IL, USA

    Duzitian Li

  6. Nanjing-Helsinki Institute in Atmospheric and Earth System Sciences, Nanjing University, Suzhou, China

    Haotian Zheng & Haikun Wang

  7. Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia

    Yuming Guo

  8. Collaborative Innovation Center of Climate Change, Nanjing, China

    Haikun Wang

  9. Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, Nanjing, China

    Haikun Wang

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Contributions

H.W. and B.C designed this study. B.C., X.L., Y.Z. and J.L. led the data analysis. B.C., X.L., L.L. and J.L. provided data. B.C., X.L., Y.Z., J.L., L.L, J.C., D.L., H.Z., Y.P., Y.G. and H.W. contributed to the discussion and interpretation of the results. B.C., X.L., Y.Z. and H.W. wrote the paper with inputs from all co-authors.

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Correspondence to Haikun Wang.

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Chu, B., Liu, X., Zhu, Y. et al. Effect of climate-driven childhood sleep erosion on potential regional economic inequality. Nat Sustain (2026). https://doi.org/10.1038/s41893-026-01779-x

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