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Associations of air pollution and greenness with global burden of breast cancer: an ecological study

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Abstract

Despite the significance of the associations of air pollution and greenness with the risk of breast cancer, this topic has not been investigated on a global scale. We conducted an ecological study using 7 years of data from 162 countries. Disability-adjusted life years (DALYs) and incidence data were used to represent the breast cancer disease burden. Particulate matter with a diameter < 2.5 μm (PM2.5), ozone (O3), nitrogen dioxide (NO2), and the normalized difference vegetation index (NDVI) were adopted as our exposures. We employed generalized linear mixed models to explore the relationship between air pollution and greenness on breast cancer disease burden. The rate ratio (RR) and its 95% confidence interval (CI) indicate the effect size. There is a positive association between air pollution and the burden of breast cancer disease. Contrarily, per interquartile range increment in NDVI was negatively associated with DALYs and incidence. In terms of air pollutants and breast cancer, NDVI seems to have a significant influence on the relationship between these two conditions. A higher amount of greenness helps to alleviate the negative association of air pollution on breast cancer. PM2.5 and O3 play a mediating role in the relationship between greenness and breast cancer disease burden. In areas with higher levels of greenness, there is a possibility that the inverse association between air pollutants and the burden of breast cancer may be influenced.

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Data availability

Data will be made available on request. Publicly available datasets were analyzed in this study. This data can be found here:

[dataset] Global Burden of Disease, 2019. http://ghdx.healthdata.org/gbd-results-tool (Accessed Jan. 18, 2022)

[dataset] Surface PM2.5. Atmospheric Composition Analysis Group, V5.GL.02. https://sites.wustl.edu/acag/datasets (Accessed Jan. 25, 2022)

[dataset] NASA Earth Observations，2022. Vegetation Index. https://neo.gsfc.nasa.gov/ (Accessed Jan. 30, 2022)

[dataset] https://doi.org/10.6084/m9.figshare.12968114 (Accessed Sep. 13, 2022)

[dataset] World Bank, 2022. https://databank.worldbank.org/home.aspx (Accessed Fen. 10, 2022)

Abbreviations

GBD:

Global burden of disease

DALYs:

Disability-adjusted life years

PM2.5 :

Particulate matter with a diameter ≤ 2.5 μm

O3 :

Ozone

NO2 :

Nitrogen dioxide

NDVI:

Normalized difference vegetation index

RR:

Rate ratio

CI:

Confidence interval

IQR:

Interquartile range

VIF:

Variance inflation factor

GLMMs:

Generalized linear mixed models

GDP:

Gross domestic product

GNI:

Gross national income

PAHs:

Polycyclic aromatic hydrocarbons

BaP:

Benzo(a)pyrene

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Acknowledgements

We would like to thank all of our teachers and students for their assistance with this work.

Funding

The work was supported by the Natural Science Key Project of the Anhui Provincial Education Department (no. KJ2021A0710), the Natural Science Key Project of the Anhui Provincial Education Department (no. KJ2018A1012), the Innovation Team Project of Bengbu Medical College (no. BYKC201901), and the 76 self-funded projects of the 2022 Postgraduate Research Innovation Program of Bengbu Medical College (no. Byycxz22036).

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Authors and Affiliations

  1. Department of Epidemiology and Statistics, School of Public Health, Bengbu Medical College, No. 2600 Donghai Avenue, Bengbu, 233000, China

    Peiyao Zhang, Cheng Zhou, Ke Zhao, Chengrong Liu, Chao Liu, Fenfen He, Xianjie Jia & Jing Mi

  2. School of Public Health, Fudan University, Shanghai, China

    Wenjia Peng

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  1. Peiyao Zhang
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  2. Cheng Zhou
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  3. Ke Zhao
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  4. Chengrong Liu
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Contributions

Peiyao Zhang: formal analysis, data curation, writing—original draft, and visualization. Cheng Zhou: investigation and resources. Ke Zhao: software and validation. Chengrong Liu: investigation and software. Chao Liu: investigation and resources. Fenfen He: investigation and resources. Wenjia Peng: methodology, writing—review, and editing. Xianjie Jia: supervision, project administration, writing—review, and editing. Jing Mi: conceptualization, writing—review, editing, supervision, and funding acquisition.

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Correspondence to Jing Mi.

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Zhang, P., Zhou, C., Zhao, K. et al. Associations of air pollution and greenness with global burden of breast cancer: an ecological study. Environ Sci Pollut Res 30, 103921–103931 (2023). https://doi.org/10.1007/s11356-023-29579-2

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