Seasonal variation of stroke incidence in Wujin, a city in southeast China

Seasonal variation in the incidence of primary intracerebral hemorrhage: a 16-year nationwide analysis

Introduction

Data on nationwide trends and seasonal variations in the incidence of Intracerebral Hemorrhage (ICH) in the United States (US) are lacking.

Methods

We used the Nationwide Inpatient Sample (2004-2019) and Census Bureau data to calculate the quarterly (Q1:January-March; Q2:April-June; Q3:July-September; Q4:October-December) incidence rates (IR) of adult (≥18 years) ICH hospitalizations, aggregated across Q1-Q4 and Q2-Q3. We report adjusted incidence rate ratios (aIRR) and 95% confidence intervals (CI) for differences in the quarterly incidence of ICH, as compared to acute ischemic stroke (AIS), between Q1Q4 and Q2Q3 using a multivariable Poisson regression model. We additionally performed stratified analyses across the four US regions.

Results

Among 822,143 (49.0% female) ICH and 6,266,234 (51.9% female) AIS hospitalizations, the average quarterly crude IR of ICH was consistently higher in Q1Q4 compared to Q2Q3 (5.6 vs. 5.2 per 100,000) (aIRR, CI: 1.09, 1.08-1.11)-this pattern was similar across all four US regions. However, a similar variation pattern was not observed for AIS incidence. The incidence (aIRR, CI) of both ICH (1.01, 1.00-1.02) and AIS (1.03, 1.02-1.03) is rising.

Conclusion

Unlike AIS, ICH incidence is consistently higher in colder quarters, underscoring the need for evaluation and prevention of factors driving seasonal variations in ICH incidence.

Seasonal patterns and associations in the incidence of acute ischemic stroke requiring mechanical thrombectomy

Background

In order to identify risk periods with an increased demand in technical and human resources, we tried to determine patterns and associations in the incidence of acute ischemic stroke due to embolic large vessel occlusions (eLVO) requiring mechanical thrombectomy (MT).

Methods

We conducted a time series analysis over a 9‐year period (2010–2018) based on observational data in order to detect seasonal patterns in the incidence of MT due to eLVO (n = 2628 patients). In a series of sequential negative binominal regression models, we aimed to detect further associations (e.g., temperature, atmospheric pressure, air pollution).

Results

There was a 6‐month seasonal pattern in the incidence of MT due to eLVO (p = 0.024) peaking in March and September. Colder overall temperature was associated with an increase in MT due to eLVO (average marginal effect [AME], [95% CI]: −0.15 [−0.30–0.0001]; p = 0.05; per °C). A current increase in the average monthly temperature was associated with a higher incidence of MT due to eLVO (0.34 [0.11–0.56]; p = 0.003). Atmospheric pressure was positively correlated with MT due to eLVO (0.38 [0.13–0.64]; p = 0.003; per hectopascal [hPa]). We could detect no causal correlation between air pollutants and MT due to eLVO.

Conclusions

Our data suggest a 6‐month seasonal pattern in the incidence of MT due to eLVO peaking in spring and early autumn. This might be attributed to two different factors: (1) a current temperature rise (comparing the average monthly temperature in consecutive months) and (2) colder overall temperature. These results could help to identify risk periods requiring an adaptation in local infrastructure.