Increasing burden of poor mental health attributable to high temperature in Australia (2025)

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Subjects Abstract Access options Additional access options: Similar content being viewed by others The trends of disease burden due to high temperature in Mainland China from 1990 to 2019 and its prediction to 2030 Temperature-related death burden of various neurodegenerative diseases under climate warming: a nationwide modelling study The burden of heat-related mortality attributable to recent human-induced climate change Data availability Code availability References Acknowledgements Author information Authors and Affiliations Contributions Corresponding author Ethics declarations Competing interests Peer review Peer review information Additional information Extended data Extended Data Fig. 1 Estimated burden of mental and behavioural disorders (MBDs) attributable to high temperature. Extended Data Fig. 2 Projected mean temperature anomalies. Extended Data Fig. 3 Comparisons of population attributable fractions (PAFs) for mental and behavioural disorders (MBDs) due to high temperature. Extended Data Fig. 4 Projected population attributable fraction (PAFs) for mental and behavioural disorders (MBDs) due to high temperature by State and Territory. Extended Data Fig. 5 Projected burden of mental and behavioural disorders (MBDs) attributable to increasing high temperature. Supplementary information Supplementary Information Rights and permissions About this article Cite this article
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Abstract

High-temperature exposure has important implications for mental and behavioural disorders (MBDs), which could lead to increased risks under climate change. However, knowledge gaps exist in quantifying the attributable burden. Here we assessed the burden of MBDs attributable to temperatures above the location-specific thresholds from 2003 to 2018 using disability-adjusted life years and projected future burdens under the climate scenarios representative concentration pathways RCP 4.5 and 8.5 across Australia, considering various climatic, demographic and adaptation scenarios. We show that high temperatures contributed to an annual loss of 8,458 disability-adjusted life years, representing 1.8% of total MBD burden in Australia. Our findings project a consistent upward trend in the high-temperature-attributable burden of MBDs over time. Specifically, this burden is expected to increase by 11.0–17.2% in the 2030s and by 27.5–48.9% in the 2050s compared to the baseline. Our study underscores the need for both adaptation and mitigation strategies to counteract the adverse effects of warming climate on mental health.

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Increasing burden of poor mental health attributable to high temperature in Australia (1)
Increasing burden of poor mental health attributable to high temperature in Australia (2)
Increasing burden of poor mental health attributable to high temperature in Australia (3)

Similar content being viewed by others

Increasing burden of poor mental health attributable to high temperature in Australia (4)

The trends of disease burden due to high temperature in Mainland China from 1990 to 2019 and its prediction to 2030

Article Open access 14 December 2023

Increasing burden of poor mental health attributable to high temperature in Australia (5)

Temperature-related death burden of various neurodegenerative diseases under climate warming: a nationwide modelling study

Article Open access 12 December 2023

Increasing burden of poor mental health attributable to high temperature in Australia (6)

The burden of heat-related mortality attributable to recent human-induced climate change

Article 31 May 2021

Data availability

This paper uses data collected from the Australian Institute of Health and Welfare, an official health data custodian in Australia. Owing to confidentiality, the original burden-of-disease data cannot be shared. However, the processed climate data are publicly accessible through: (1) SILO (https://www.longpaddock.qld.gov.au/silo/) and (2) CSIRO (https://www.climatechangeinaustralia.gov.au/en/obtain-data/application-ready-data/). Processed population data can be obtained from the Australian Bureau of Statistics at https://www.abs.gov.au/census. Additionally, processed data on the prevalence of mental health issues are available from the Australian Institute of Health and Welfare at https://www.aihw.gov.au/mental-health.

Code availability

The Python code, which includes steps to compute the PAFs for high-temperature exposure, is available via Zenodo at https://doi.org/10.5281/zenodo.14715392 (ref. 46).

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Acknowledgements

J.L. is supported by the Adelaide University China Fee Scholarships (China Scholarship Council). This project is part of an Australian Research Council Discovery Program project (DP200102571 awarded to P.B.).

Author information

Authors and Affiliations

  1. School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia

    Jingwen Liu,Blesson M. Varghese,Alana Hansen,Keith Dear&Peng Bi

  2. Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia

    Geoffrey Morgan,Timothy Driscoll&Ying Zhang

  3. The University Centre for Rural Health, The University of Sydney, Sydney, New South Wales, Australia

    Geoffrey Morgan

  4. Prevention and Environmental Health Unit, Australia Institute of Health and Welfare, Canberra, Australian Capital Territory, Australia

    Vanessa Prescott

  5. Burden of Disease and Mortality Unit, Australian Institute of Health and Welfare, Canberra, Australian Capital Territory, Australia

    Vergil Dolar&Michelle Gourley

  6. Monash Sustainable Development Institute, Monash University, Melbourne, Victoria, Australia

    Anthony Capon

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  1. Jingwen Liu

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Contributions

J.L., B.M.V., A.H. and P.B. conceived of the presented idea. J.L. conducted the analysis and wrote the first draft. J.L., B.M.V., K.D., V.P. and V.D. helped to design the analytical strategy and J.L., B.M.V. and K.D. helped to interpret the findings. All authors critically revised the paper for intellectual content and approved the final version of the paper.

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Correspondence to Peng Bi.

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Extended data

Extended Data Fig. 1 Estimated burden of mental and behavioural disorders (MBDs) attributable to high temperature.

Annual average rate (per 100,000 population) of MBDs attributable to high temperature during the baseline period of 2003–2018 across Australia. Map created with ArcGIS Pro 3.1.0 with shapefiles from the Australian Bureau of Statistics37.

Extended Data Fig. 2 Projected mean temperature anomalies.

Annual mean temperature anomalies (°C) for the periods 2016–2045 (referred to as ‘2030 s’), and 2036–2065 (referred to as ‘2050 s’) compared to the baseline period of 2003–2018, under two representative concentration pathways (RCPs): RCP4.5 and RCP8.5. Maps created with ArcGIS Pro 3.1.0 with shapefiles from the Australian Bureau of Statistics37.

Extended Data Fig. 3 Comparisons of population attributable fractions (PAFs) for mental and behavioural disorders (MBDs) due to high temperature.

The PAFs (as a proportion, %) of the burden of MBDs due to high temperature for the period centred on 2030 s and 2050 s. Data are presented as means with 95% confidence intervals, under two representative concentration pathways (RCPs): RCP4.5 and RCP8.5, and three human adaptation scenarios to climate change (none, partial, full).

Extended Data Fig. 4 Projected population attributable fraction (PAFs) for mental and behavioural disorders (MBDs) due to high temperature by State and Territory.

The PAFs (as a proportion, %) of the burden of MBDs due to high temperature for the period centred on 2030 s and 2050 s. Data are presented as means with 95% confidence intervals, under two representative concentration pathways (RCPs): RCP4.5 and RCP8.5, and three human adaptation scenarios to climate change (none, partial, full).

Extended Data Fig. 5 Projected burden of mental and behavioural disorders (MBDs) attributable to increasing high temperature.

Annual average rate (per 100,000 population) of MBDs attributable to high temperature for future periods centred on the 2030 s and 2050 s, assuming no human adaptation (series B population projection), under two greenhouse gas emission scenarios (RCP4.5 and RCP8.5). Maps created with ArcGIS Pro 3.1.0 with shapefiles from the Australian Bureau of Statistics37.

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Increasing burden of poor mental health attributable to high temperature in Australia (7)

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Liu, J., Varghese, B.M., Hansen, A. et al. Increasing burden of poor mental health attributable to high temperature in Australia. Nat. Clim. Chang. (2025). https://doi.org/10.1038/s41558-025-02309-x

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Increasing burden of poor mental health attributable to high temperature in Australia (2025)
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