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Rising socio-economic costs of PM2.5 pollution and medical service mismatching

Nature Sustainability volume 8, pages 265–275 (2025)Cite this article

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Abstract

The harmful impact of fine particulate matter (PM2.5) air pollution on public health remains a pressing concern. Detrimental effects of such pollution on elderly populations can be exacerbated by the ageing process, making it necessary to identify vulnerable groups or regions, especially in the context of shifting demographics and healthcare disparities. Focusing on Japan, with its extreme ageing demographic, our study assesses the health impacts of PM2.5 across different age segments from a spatial–temporal perspective while considering the uneven distribution of medical resources across different regions. We find that the Baby Boomer generation, born in the 1950s, faces a statistical value of life that is approximately 52% higher than that of other generations, signifying that individuals of this generation are more likely to bear increased costs for health issues caused by long-term exposure to PM2.5. On the basis of 170,000 medical-clinic records across Japan, our research reveals that the disease burden exacerbated by mismatches in medical resources has become increasingly evident, affecting over 86% of the areas we studied, with remote regions in West Japan being particularly vulnerable. These findings highlight the amplified challenges posed by demographic shifts, the need for targeted health and environmental policies, and serve as a critical warning for regions facing similar issues.

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Fig. 1: Age-stratified AVSL and PM2.5-related health impacts in Japan.
Fig. 2: Monetized health impacts attributable to PM2.5 exposure and the contribution from different prefectures and age segments.
Fig. 3: Map of disease burden considering the spatial mismatch between PM2.5 exposure and healthcare resources.

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Data availability

PM2.5 concentration data are publicly available on the website of the Atmospheric Composition Analysis Group of Washington University in St Louis51 (https://sites.wustl.edu/acag/). Population data are maintained by Li and Managi52. We obtained the age structure data and household asset data from the Statistics Bureau of Japan (https://www.stat.go.jp/english/). GDP data are available from the Japan Cabinet Office (https://www.cao.go.jp/index-e.html). Baseline mortality, life expectancy and survival probability data are also open access and can be obtained from the Global Burden of Disease Study 201953 (https://ghdx.healthdata.org/gbd-2019). Medical-clinic records data are developed by the Geospatial Information Authority of Japan, Ministry of Land, Infrastructure, Transport and Tourism, and are available from https://nlftp.mlit.go.jp/. Source data are provided with this paper.

Code availability

The code used to process and analyse the data is developed in Python 3.7, and is available from the corresponding authors upon reasonable request.

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Acknowledgements

We thank for Z. Chen (University of Tokyo, Tokyo, Japan) for his help and insightful comments regarding the figures of the paper. This research is also funded by Japan Society for the Promotion of Science KAKENHI B (grant number JP24K03146, Y.Y.) and KAKENHI C (grant number JP23K11542, L.Y.).

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Authors and Affiliations

  1. Graduate School of Engineering, University of Tokyo, Tokyo, Japan

    Xiaoyan Xu, Liqiao Huang, Yoshikuni Yoshida & Yin Long

  2. Business School, Sichuan University, Chengdu, China

    Liming Yao

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  1. Xiaoyan Xu
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Contributions

X.X. and Y.L. conceptualized the research question and designed the analytical framework. X.X. and L.H. conducted the data collection, preprocessing, modelling and statistical analyses. Visualizations were created by X.X. and Y.L. The paper was draughted by X.X. and L.H., and it was critically reviewed and revised by Y.L., Y.Y. and L.Y. All authors discussed the results and edited the final paper.

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Correspondence to Liming Yao or Yin Long.

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Nature Sustainability thanks Pin Wang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Xu, X., Huang, L., Yao, L. et al. Rising socio-economic costs of PM2.5 pollution and medical service mismatching. Nat Sustain 8, 265–275 (2025). https://doi.org/10.1038/s41893-025-01509-9

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