In this 11-year study of 260 patients with SAH, 533 patients with ICH, and 3,245 patients with IS, we found that some patterns of RH and CC and daily changes in AP and RH were associated with the risk of some types of stroke. In addition, we used the NAO, AO, EA/WR, SCA, and ENSO indices as predictors for the evaluation the risk of stroke. For the first time, we detected a protective effect of warmer ENSO (a stronger El Niño) on the risk of SAH, a positive association between the risk of HS and the EA/WR, a negative association between the rate ratio of IS and the AOI, and a negative impact of a strong positive SCA on the risk of IS. Apart from these results, during November-March, a higher risk of HS was related to a positive NAO, and a negative correlation between the risk of IS and the NAOI was found. In the analysis, an impact of teleconnection indices was detected, adjusting for seasonal variation, T, and other weather variables.
In our study, the risk of HS was associated with daily changes in AP above the threshold of 3.9 hPa for SAH and 9.55 hPa for ICH. These results are in line with those obtained by other authors who found a significant association between SAH and ICH and changing AP. The daily change in AP with a lag of 1 day was positively correlated with the daily number of SAHs in the English Midlands [19], and the daily change in AP >10 hPa was associated with the risk of SAH in the UK [38] and in Germany [20].
To our knowledge, the risk of SAH was associated with a higher RH and CC level, and the risk of ICH was associated with a higher CC level on the previous day and with a lower daily RH change. Some authors found a significant association between stroke and RH and daily hours of sunshine, which is the opposite variable to cloud cover. A decrease in daily sunlight hours was positively associated with the risk of SAH [17,39]. A positive association between SAH and RH was found in the humid subtropical zone [16] and in the Rhein Main area [20], while in the southern regions of France and in the areas with various climatic conditions (41 states of USA), a negative association between SAH and RH was observed [17, 39]. ICH is negatively correlated with sunshine hours [40] and positively correlated with the amount of precipitation [6], which coincides with our results.
We found a positive effect of a strong warm ENSO on human health. In our study, most of these events (NINO3.4>1.14) fell into colder months. Therefore, the protective effect of a warmer ENSO on SAH may be explained by the effect of ENSO on the weather pattern during autumn and winter. Studies have shown that the warm and cold phases of ENSO have different impacts on the pattern of weather regimes during the colder season in Europe [33]. Strong El Niño events were related to a higher sea level pressure, a lower T, and dry air in the Baltic countries [41,33,42]. According to our data, during the second half of autumn, the NINO3.4>1.14 period was characterised by a lower mean AP, more precipitation and RH, and a very significantly lower diurnal temperature range (DTR) (by 1.3 °C, p<0.001). In winter, the NINO3.4>1.14 period was characterised by a lower T, WS, and CC and a higher AP and DTR. These weather patterns may be associated with a lower risk of SAH. Some studies have shown that a higher DTR is significantly associated with higher mortality, and this effect was stronger during autumn [43,44]. Therefore, a lower DTR during autumn may have a positive effect on human health.
We found a positive association between the EA/WRI and HS and an increase in the risk of IS during a strong negative EA/WR phase. These effects were similar during both the colder and the warmer periods, and the additional inclusion of the NAOI in the model did not reduce the significance of the EA/WRI. In the studied region, in winter, the positive EA/WR produced cold advection from the north and was characterised by a lower air temperature, a lower precipitation level, and stronger atmospheric circulation [45]. In the southeastern region of the Baltic Sea, the EA/WRI is negatively correlated with air temperature in spring [46], lake water temperature in spring-autumn [47], and precipitation amount in summer [45]. According to our data, during the positive EA/WR phase, a higher mean WS and AP in winter and a lower mean T and a higher mean AP both in spring and summer were observed. Apart from this, a higher variation was found in the daily change in AP both in winter and spring. Thus, a higher EA/WRI was related to a stronger variation in AP, colder air flow in winter, and colder air in other seasons. The complexity of these weather patterns may be associated with a higher risk of HS.
For the first time, negative correlations between IS and AO and between IS and NAO only during November-March were found. According to the results of studies by other authors, AO was associated not only with tropospheric variability but also with stratospheric variability and changes in weather patterns in Lithuania and nearby regions [48,49]. During January-March, a positive AO brings a higher surface T and a lower precipitation in middle-latitude regions [50]. In the region of the Baltic Sea, a positive correlation between T and AO was observed during January-March [51], March-May [52], July and October [46], and September-March [53]. According to our data, the AOI was positively correlated with T in all seasons, excluding summer, and negatively correlated with RH, excluding winter. It is possible that this complex of weather patterns (a higher T and a lower RH during the equinox, a lower RH in summer, and warmer winters) related to days of a higher AOI had a protective effect against the risk of IS.
The SCAI was positively correlated with T in summer and negatively correlated with T and positively correlated with AP over the region of the Baltic Sea in winter [26,31,46]; the same associations were found in our study. The positive phase of SCA indicates more likely anticyclonic conditions and a lower level of atmospheric circulation over the Baltic Sea region during autumn-spring [26], and the anticyclonic conditions over Scandinavia substantially suppress westerly zonal airflow in summer [54]. It is possible that cold outbreaks during the colder period and the atmospheric variations related to a stronger positive SCA are associated with the risk of IS.
During the colder period, a positive NAO had a protective effect against IS, but a negative NAO had a protective effect against HS. During wintertime, in the Baltic Sea region, a positive NAOI was associated with a higher T and with altered weather: a higher WS, a lower AP, and a northeastward shift in the Atlantic storm activity with enhanced activity from Newfoundland into Northern Europe [25]. As a positive NAO during the winter was associated with more changing weather, a positive NAO was risky for HS, whereas a change in T was more relevant for IS. Studies in Northern and Middle Europe have shown a higher risk of HS associated with changing weather but not with T [19,20,22,38]. A study conducted in the UK showed a significant impact of changes in T only on IS, whereas changes in AP had a significant impact only on the risk of HS [55].
According to the literature, both positive and negative NAO phases are associated with worse health outcomes. [56] found a positive association between the daily AOI with a lag of 3 days and the incidence of and mortality from acute myocardial infarction in Northern Sweden. An inverse association between the climate index (which represents winters with a strong negative phase of the NAO) and the level of mortality from ischaemic heart disease was found in England [57]. In addition, a negative association between the NAO index and systolic and diastolic blood pressure during spring-autumn was found [58].
The pathophysiological mechanisms underlying the correlation between stroke and weather conditions have been discussed. Factors that increase the risk of stroke include high blood pressure, some diseases, and the lack of regular exercise. Blood pressure is influenced by cold, stress and physical activity [58]. Donkelaar et al. [22] hypothesised that AP changes trigger the inflammation process in the aneurysm wall. Variations in AP may influence vessel walls and endothelial function by endogenous inflammatory mechanisms [21]. Studies on thrombosis in air travel suggest that prothrombin fragments and the thrombin-antithrombin complex are activated in hypobaric conditions [59,60], which could be another clue to the underlying mechanism.
Studies on the associations between physical activity in the elderly and weather conditions in Europe showed that physical activity decreased with increasing WS, precipitation, humidity, and a shorter duration of sunshine [61,62]. These weather conditions are associated with a negative AO and NAO excluding winter months; therefore, it can be assumed that negative AOs are associated with fewer physical activity opportunities for the elderly, who are likely to be stressed. Thisal activity can explain why a negative AO increased the risk of IS.
The present study has several strengths the inclusion of a large number of patients with various types and subtypes of stroke, the long study period, and standardised methods and criteria used for stroke registration. In addition, the present study analyses daily stroke incidence data by stroke subtypes, daily meteorological data, and the variation of these data with respect to the previous day and uses teleconnections such as NAO, AO, EA/WR, SCA, and ENSO. Moreover, the patients that were included coming from a small geographical area (Kaunas) contributes to the homogeneity of weather conditions. In our study, associations between atmospheric circulation patterns such as NAO, AO EA/WR, SCA, and ENSO and the risk of stroke were found for the first time.
The limitation is that other potential confounders such as air pollution, influenza epidemics or other respiratory infections were not directly considered in this study. In our region, infections are strongly related to the season with the highest prevalence during winter [63]. In our study, the analyses were controlled for the month and T. Residual confounding by short-term respiratory epidemics remains a possibility. Moreover, we did not consider weather-related physical activity that may have had an impact on individual exposure to outdoor T and humidity.
In our study, the influence of air pollution, which is a known trigger for cardiovascular diseases, was not examined. We did not have air pollution data for the entire study period, but the additional inclusion of the daily concentrations of PM10, NO2, or O3 did not change the association between the risk of strokes and teleconnection indices. Based on the results published by other authors [64], we can assume that the short-term effect of PM10, NO2, or O3 on the risk of stroke was not significant enough to affect the results of our study. First, the level of air pollution in Kaunas is not high. Second, our stroke patients were relatively young (<65 years of age), whereas in other studies presenting a positive association between air pollution and stroke (except for those performed in subtropics or in regions with high levels of pollutants), the mean age of the patients was over 70 years [68]. Third, we did not evaluate other comorbidities such as acute myocardial infarction, ischaemic heart disease, arterial hypertension, heart failure or other risk factors such as atrial fibrillation, diabetes, dyslipidaemia, or renal or malignant diseases, which may also be associated with a higher risk of ischaemic and haemorrhagic stroke. Fourth, harmful lifestyle factors such as alcohol consumption or smoking, which increase the risk of haemorrhagic stroke, cannot be ruled out, either.