Short-term effect of PM2.5 on stroke in susceptible populations: A case-crossover study

Author:

Wang Meng123ORCID,Han Ying1ORCID,Wang Chun-Juan23,Xue Tao4,Gu Hong-Qiu23ORCID,Yang Kai-Xuan23,Liu Heng-Yi4,Cao Man5,Meng Xia12,Jiang Yong2,Yang Xin23,Zhang Jing23,Xiong Yun-Yun2,Zhao Xing-Quan12ORCID,Liu Li-Ping12,Wang Yi-Long1,Guan Tian-Jia5,Li Zi-Xiao12367,Wang Yong-Jun12678ORCID

Affiliation:

1. Vascular Neurology, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China

2. China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China

3. National Center for Healthcare Quality Management in Neurological Diseases, Beijing, China

4. Institute of Reproductive and Child Health, Ministry of Health Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China

5. Department of Health Policy and Management, School of Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

6. Research Unit of Artificial Intelligence in Cerebrovascular Disease, Chinese Academy of Medical Sciences, Beijing, China

7. Chinese Institute for Brain Research, Beijing, China

8. Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China

Abstract

Background: 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/m3 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.

Funder

Beijing Talents Project

National Natural Science Foundation of China

Beijing Municipal Committee of Science and Technology

Ministry of Science and Technology of the People’s Republic of China

CAMS Innovation Fund for Medical Sciences

Natural Science Foundation of Beijing Municipality

Publisher

SAGE Publications

Subject

Neurology

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