In:
International Journal of Stroke, SAGE Publications, Vol. 18, No. 3 ( 2023-03), p. 312-321
Abstract:
Fine particulate matter (PM2.5) is a risk factor for stroke, and patients with pre-existing diseases appear to be particularly susceptible. We conducted a case-crossover study to examine the association between short-term exposure to fine particulate matter (PM2.5) and hospital admission for stroke in individuals with atrial fibrillation (AF), hypertension, diabetes, or hyperlipidemia. Methods: Patients diagnosed with acute ischemic stroke (AIS) were recruited from 2015 to 2017 in Chinese Stroke Center Alliances. We estimated daily PM2.5 average exposures with a spatial resolution of 0.1° using a data assimilation approach combining satellite measurements, air model simulations, and monitoring values. Conditional logistic regression was used to assess PM2.5-related stroke risk in patients with pre-existing medical co-morbidities. Results: A total of 155,616 patients diagnosed with AIS were admitted. Patients with a history of AF ( n = 15,430), hypertension ( n = 138,220), diabetes ( n = 43,737), or hyperlipidemia ( n = 16,855) were assessed separately. A 10 µg/m 3 increase in daily PM2.5 was associated with a significant increase in AIS for individuals with AF at lag 4 (odds ratio (OR), 1.008; 95% confidence interval (CI), 1.002–1.014), and with hypertension (OR, 1.008; 95% CI, 1.006–1.010), diabetes (OR, 1.006; 95% CI, 1.003–1.010), and hyperlipidemia (OR, 1.007; 95% CI, 1.001–1.012) at lags 0–7. Elderly (⩾ 65 years old) and female patients with AF had significantly higher associations at lag 5 (OR, 1.009; 95% CI, 1.002–1.015) and lag 5 (OR, 1.010; 95% CI, 1.002–1.018), respectively. Conclusion: Short-term exposure to PM2.5 is significantly associated with hospital admission for stroke in individuals with pre-existing medical histories, especially in older or female patients with AF. Preventive measures to reduce PM2.5 concentrations are particularly important in individuals with other medical co-morbidities.
Type of Medium:
Online Resource
ISSN:
1747-4930
,
1747-4949
DOI:
10.1177/17474930221110024
Language:
English
Publisher:
SAGE Publications
Publication Date:
2023
detail.hit.zdb_id:
2211666-7
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