Potential Impacts of Meteorological Variables on Acute Ischemic Stroke Onset

Abstract

Purpose

The effects of meteorological parameters on stroke occurrence remain debated. The aim of the study was to assess the association between meteorological parameters and ischemic stroke onset in cold seasons in Tianjin.

Patients and Methods

Patients with acute ischemic stroke (946) were identified by standard sampling from one stroke unit in the Second Hospital of Tianjin Medical University, Tianjin, China, from 10/1/2014 to 4/30/2019. Generalized linear Poisson regression models were used to explore the effect of meteorological parameters (air temperature, barometric pressure, and relative humidity) on daily ischemic stroke onset after adjusting for air pollutants, day of week, and public holiday.

Results

The results showed that ischemic stroke onset was positively associated with the diurnal variation of temperature (β coefficient: 0.020, 95% CI [0.001, 0.038] p<0.05). Significant positive correlation between ischemic stroke onset and barometric pressure (mean, minimum) was found (β coefficient: 0.010, 95% CI [0.001,0.019] p<0.05; 0.010, 95% CI [0.001,0.019] p<0.05). The subgroup analysis considering age and gender difference showed that the older and the female were more vulnerable to weather conditions.

Conclusion

Our study demonstrated that there was a measurable effect of weather parameters on daily ischemic stroke onset in colder seasons, suggesting that meteorological variables may, at least in part, play as risk factors for ischemic stroke onset, especially for the aging and female population.

Keywords:

• cold temperature
• air pressure
• ischemic stroke

Acknowledgments

This work was supported by Major Social Science Program of Tianjin Municipal Education Commission (2017JWZD36) and Key Technology Research and Development Program of Science & Technology of Tianjin (18ZXDBSY00210).

Data Sharing Statement

The data used to support the findings of this study are available from the corresponding author upon request.

Author Contributions

Sean X. Leng and Xin Li are the co-corresponding authors. All authors contributed to data analysis, drafting or revising the article, gave final approval of the version to be published, and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.