In a recent study published in the journal eClinicalMedicine, researchers assess the detrimental effects of long-term air pollution exposure on the dynamic transitions of stroke and dementia, especially the influence of air pollution during different time intervals, using the United Kingdom (UK) Biobank data.
Study: Ambient air pollution and the dynamic transitions of stroke and dementia: a population-based cohort study. Image Credit: okanozdemir/Shutterstock.com
Specifically, they evaluated the health effects of multiple air pollutants in ambient air. This comprised a mixture of both particulate matter (PM) and gaseous pollutants.
Background
The outcome of stroke can be fatal, especially among aged people. Stroke accounts for 11.6% of all global deaths and is a leading cause of neurological death and disability worldwide.
In 2019, more than 50 million people had dementia. This is projected to increase to 152 million by 2050.
Given the non-availability of interventions to prevent dementia onset and fatal stroke outcomes, investigation of the alterable risk factors of both conditions remains a priority.
Notably, both stroke and dementia create reciprocal risks, which necessitates investigation of the risk factors involved in the “transition” from stroke to comorbid dementia and dementia to comorbid stroke.
Furthermore, emerging evidence suggests that the risk from stroke or dementia to comorbidity varies with the duration of the disease. Thus, studying its impacts (that changes over time) could be critical to optimizing prevention and management strategies for stroke or dementia.
Study methodology
In the present study, researchers first calculated the air pollution score using levels of pollutants: PM2.5, PM2.5-10, PMcoarse, and nitrogen dioxide (NO2), measured in the study area using passive samplers.
Next, they combined these measurements with residential addresses (of participants) to develop LUR models to elucidate any significant spatial variance in air pollutants.
Finally, they created an air pollution score using principal components analysis (PCA) based on the measured pollutants. The team followed up with all participants until lost to follow-up, death, or February 2020.
The researchers then identified stroke and dementia cases using the UK Biobank data from death registries and hospitals.
They used Cox proportional hazard models to assess the associations of air pollution with stroke, dementia, comorbidity, and all-cause mortality. Multi-state models were used to determine the association of air pollution with the dynamic transitions of stroke and dementia.
The results, i.e., each interquartile range (IQR) increase in air pollution score and individual air pollutants, were presented as hazard ratios (HRs) with 95% confidence intervals (CIs).
The study models further stratified the observed associations between air pollution and transitions according to age (