IDEAS home Printed from https://ideas.repec.org/a/gam/jworld/v6y2025i2p48-d1631242.html
   My bibliography  Save this article

A Machine Learning Perspective on the Climatic and Socioeconomic Determinants of Mental Health in Southeast Asia

Author

Listed:
  • Teerachai Amnuaylojaroen

    (School of Energy and Environment, University of Phayao, Phayao 56000, Thailand
    Atmospheric Pollution and Climate Research Unit, School of Energy and Environment, University of Phayao, Phayao 56000, Thailand)

  • Nichapa Parasin

    (School of Allied Health Science, University of Phayao, Phayao 56000, Thailand)

Abstract

The growing burden of mental health disorders necessitates a comprehensive understanding of their environmental and socioeconomic determinants. This study employs machine learning to analyze the relationship between mental health mortality and key socioeconomic and climatic factors across Southeast Asia. Using a Random Forest model (R 2 = 0.95), we identify the population size and the Physical Quality of Life Index (PQLI) as the strongest predictors of mental health mortality, while climate indices—the proportion of warm nights (TN90p) and hot days (TX90p)—exhibit weaker direct effects (importance < 0.1), but significant indirect effects through socioeconomic pathways. The regional disparities highlight Indonesia as the most climate-sensitive country, whereas the Philippines shows weaker climate–mortality correlations, suggesting that its socioeconomic resilience and healthcare infrastructure can mitigate climate impacts. These findings underscore the need for integrated climate–mental health strategies, particularly for vulnerable regions experiencing extreme temperatures and socioeconomic stressors.

Suggested Citation

  • Teerachai Amnuaylojaroen & Nichapa Parasin, 2025. "A Machine Learning Perspective on the Climatic and Socioeconomic Determinants of Mental Health in Southeast Asia," World, MDPI, vol. 6(2), pages 1-27, April.
  • Handle: RePEc:gam:jworld:v:6:y:2025:i:2:p:48-:d:1631242
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2673-4060/6/2/48/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2673-4060/6/2/48/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Joshua Graff Zivin & Matthew Neidell, 2014. "Temperature and the Allocation of Time: Implications for Climate Change," Journal of Labor Economics, University of Chicago Press, vol. 32(1), pages 1-26.
    2. Katie Hayes & Peter Berry & Kristie L. Ebi, 2019. "Factors Influencing the Mental Health Consequences of Climate Change in Canada," IJERPH, MDPI, vol. 16(9), pages 1-13, May.
    3. Teerachai Amnuaylojaroen & Jirarat Inkom & Radshadaporn Janta & Vanisa Surapipith, 2020. "Long Range Transport of Southeast Asian PM2.5 Pollution to Northern Thailand during High Biomass Burning Episodes," Sustainability, MDPI, vol. 12(23), pages 1-14, December.
    4. Helen Berry & Kathryn Bowen & Tord Kjellstrom, 2010. "Climate change and mental health: a causal pathways framework," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 55(2), pages 123-132, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jingbin He & Xinru Ma, 2021. "Extreme Temperatures and Firm-Level Stock Returns," IJERPH, MDPI, vol. 18(4), pages 1-22, February.
    2. Mullins, Jamie T. & White, Corey, 2019. "Temperature and mental health: Evidence from the spectrum of mental health outcomes," Journal of Health Economics, Elsevier, vol. 68(C).
    3. Melissa Dell & Benjamin F. Jones & Benjamin A. Olken, 2014. "What Do We Learn from the Weather? The New Climate-Economy Literature," Journal of Economic Literature, American Economic Association, vol. 52(3), pages 740-798, September.
    4. Xi Chen & Chih Ming Tan & Xiaobo Zhang & Xin Zhang, 2020. "The effects of prenatal exposure to temperature extremes on birth outcomes: the case of China," Journal of Population Economics, Springer;European Society for Population Economics, vol. 33(4), pages 1263-1302, October.
    5. Raissa Sorgho & Isabel Mank & Moubassira Kagoné & Aurélia Souares & Ina Danquah & Rainer Sauerborn, 2020. "“We Will Always Ask Ourselves the Question of How to Feed the Family”: Subsistence Farmers’ Perceptions on Adaptation to Climate Change in Burkina Faso," IJERPH, MDPI, vol. 17(19), pages 1-25, October.
    6. Nicholas Apergis & Alexandros Gabrielsen & Lee Smales, 2016. "(Unusual) weather and stock returns—I am not in the mood for mood: further evidence from international markets," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 30(1), pages 63-94, February.
    7. Zhang, Shaohui & Guo, Qinxin & Smyth, Russell & Yao, Yao, 2022. "Extreme temperatures and residential electricity consumption: Evidence from Chinese households," Energy Economics, Elsevier, vol. 107(C).
    8. Wang, Meng & Zhang, Shiying, 2024. "High temperatures and traffic accident crimes: Evidence from more than 470,000 offenses in China," Economics & Human Biology, Elsevier, vol. 55(C).
    9. Chadi, Adrian & Hetschko, Clemens, 2025. "Income or leisure? On the hidden benefits of (un)employment," European Economic Review, Elsevier, vol. 171(C).
    10. Joshua Graff Zivin & Solomon M. Hsiang & Matthew Neidell, 2018. "Temperature and Human Capital in the Short and Long Run," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 5(1), pages 77-105.
    11. Nkabinde, B & Lekhanya, L.M & Dorasamy, N., 2024. "Rural-Urban Migration Challenges in South Africa: Case of Kwazulu-Natal (SA)," Journal of Economic and Social Development, Clinical Journals Press, vol. 11(02), pages 01-17, September.
    12. Brian C. Thiede & Abbie Robinson & Clark Gray, 2024. "Climatic Variability and Internal Migration in Asia: Evidence from Big Microdata," Population and Development Review, The Population Council, Inc., vol. 50(2), pages 513-540, June.
    13. Frijters, Paul & Johnston, David W. & Knott, Rachel & Torgler, Benno, 2021. "Resilience to Disaster: Evidence from Daily Wellbeing Data," IZA Discussion Papers 14220, Institute of Labor Economics (IZA).
    14. Mariano J. Rabassa & Mariana Conte Grand & Christian M. García-Witulski, 2021. "Heat warnings and avoidance behavior: evidence from a bike-sharing system," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 23(1), pages 1-28, January.
    15. Sahoo, Dukhabandhu & Mohanty, Pritisudha & Mishra, Surbhi & Behera, Manash & Mohapatra, Souryabrata, 2024. "Does climate-smart agriculture technology improve the subjective well-being of farmers? Evidence from micro-level data," MPRA Paper 123955, University Library of Munich, Germany.
    16. Grover,Arti Goswami & Kahn,Matthew Edwin, 2024. "Firm Adaptation to Climate Risk in the Developing World," Policy Research Working Paper Series 10797, The World Bank.
    17. Joshua Graff Zivin & Matthew Neidell, 2012. "The Impact of Pollution on Worker Productivity," American Economic Review, American Economic Association, vol. 102(7), pages 3652-3673, December.
    18. Gordon H. Hanson, 2010. "Why Isn't Mexico Rich?," Journal of Economic Literature, American Economic Association, vol. 48(4), pages 987-1004, December.
    19. Dai, Zhifeng & Zhu, Haoyang, 2024. "Climate policy uncertainty and urban green total factor productivity: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 96(PA).
    20. Stefano Bosi & David Desmarchelier & Lionel Ragot, 2015. "Pollution effects on labor supply and growth," International Journal of Economic Theory, The International Society for Economic Theory, vol. 11(4), pages 371-388, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jworld:v:6:y:2025:i:2:p:48-:d:1631242. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.