Association between PM_2.5 and hypertension among the floating population in China: a cross-sectional study

ABSTRACT

Few studies have investigated the association between PM_2.5 and hypertension among floating populations. We therefore examined the relationship using binary logistic regression. Each grade of increment in the annual average PM_2.5 (grade one: ≤15 µg/m³; grade two: 15–25 µg/m³; grade three: 25–35 µg/m³ [Excluding 25]; grade four: ≥35 µg/m³) was associated with an increased risk of hypertension (odds ratio [OR] = 1.081, 95% confidence interval (CI): 1.034–1.129). Among the female floating population (OR = 1.114, 95% CI: 1.030–1.204), those with education level of primary school and below (OR = 1.140, 95% CI: 1.058–1.229), construction workers (OR = 1.228, 95% CI: 1.058–1.426), and those living in the eastern region of China (OR = 1.241, 95% CI: 1.145–1.346) were more vulnerable to PM_2.5. These results indicate that PM_2.5 is positively associated with hypertension in floating populations. Floating populations who are female, less educated, construction workers, and living in the eastern region of China are more vulnerable to the adverse impacts of PM_2.5.

KEYWORDS:

• PM_2.5
• hypertension
• association
• floating population
• cross-sectional study

Acknowledgements

The authors would like to thank China Migration Population Service Center and the China Air Quality Monitoring Platform. Thanks to Dr. Xu Rongbin of Monash University for his valuable suggestions on the revision of this paper.

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Hongyu Li and Yang Zhao are co-first authors for the paper.

Authors contributions

Hongyu Li, Yang Zhao, Luyang Wang: Data curation, Formal analysis, Methodology, Writing – original draft. Haiyun Liu, Yukun Shi: Methodology, Writing – review & editing. Junyan Liu, Haotian Chen: Methodology, Writing – review & editing. Baoshun Yang, Haifeng Shan: Data curation, Software. Shijia Yuan, Wenhui Gao: Data curation, Writing – review & editing. Guangcheng Wang: Data curation, Writing – review & editing. Chunlei Han: Conceptualization, Methodology, Writing – review & editing.

Availability of data and materials

The data that support the findings of this study are available upon request from the authors.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/09603123.2023.2190959.

Additional information

Funding

Chunlei Han was supported by Shandong Province social science planning research project (22CRKJ01)