Ambient air pollution and the dynamic transitions of stroke and dementia: a population-based cohort study

EClinicalMedicine. 2023 Dec 12:67:102368. doi: 10.1016/j.eclinm.2023.102368. eCollection 2024 Jan.

Abstract

Background: Stroke and dementia are the leading causes of neurological disease burden. Detrimental effects of air pollution on both conditions are increasingly recognised, while the impacts on the dynamic transitions have not yet been explored, and whether critical time intervals exist is unknown.

Methods: This prospective study was conducted based on the UK Biobank. Annual average air pollution concentrations at baseline year 2010 estimated by land-use regression models were used as a proxy for long-term air pollution exposure. Associations between multiple air pollutants (PM2.5, PM2.5-10, and NO2) indicated by air pollution score and the dynamic transitions of stroke and dementia were estimated, and the impacts during critical time intervals were explored. The date cutoff of this study was February 29, 2020.

Findings: During a median follow-up of 10.9 years in 413,372 participants, 6484, 3813, and 376 participants developed incident stroke, dementia, and comorbidity of stroke and dementia. For the overall transition from stroke to comorbid dementia, the hazard ratio (HR) for each interquartile range (IQR) increase in air pollution score was 1.38 (95% CI, 1.15, 1.65), and the risks were limited to two time intervals (within 1 year and over 5 years after stroke). As for the transition from dementia to comorbid stroke, increased risk was only observed during 2-3 years after dementia.

Interpretation: Our findings suggested that air pollution played an important role in the dynamic transition of stroke and dementia even at concentrations below the current criteria. The findings provided new evidence for alleviating the disease burden of neurological disorders related to air pollution during critical time intervals.

Funding: The State Scholarship Fund of China Scholarship Council.

Keywords: Air pollution; Critical time intervals; Dementia; Dynamic transitions; Stroke.