CARDIOVASCULAR DISEASE

Rapid weather changes are associated with increased ischemic

stroke risk: a case-crossover study

Florian Rakers1,3 • Rene Schiffner1 • Sven Rupprecht1 • Antje Brandstadt2 •

Otto W. Witte1 • Mario Walther2 • Peter Schlattmann2 • Matthias Schwab1

Received: 26 March 2014 / Accepted: 12 June 2015

� Springer Science+Business Media Dordrecht 2015

Abstract Observational studies focusing on absolute

meteorological values suggest an association between

meteorological parameters and stroke risk but these results

are inconsistent and conflicting. Since changes in weather

can provoke atrial fibrillation, we examined the association

between rapid weather changes and stroke risk in 1694

patients with determinable onset of stroke symptoms in a

case-crossover study in central Germany. Days one to three

before stroke onset were classified as hazard periods and

day seven as the respective control period. Risk of

ischemic stroke in relation to 24 h differences in mean

ambient temperature, relative humidity and atmospheric

pressure was determined. The association between tem-

perature and stroke risk appears to be close to linear with

an increase in stroke risk of 11 % (odds ratio 1.11, 95 %

confidence interval 1.01–1.22) for each 2.9 �C temperature

decrease over 24 h. In individuals with a higher cardio-

vascular risk, stroke risk increased by 30 % (1.30,

1.06–1.61). Risk for cardioembolic strokes increased by

26 % (1.26, 1.06–1.50). Rapid positive or negative changes

in relative humidity ([5 %) and atmospheric pressure

([10 hPa) increased stroke risk by a maximum of 30 %

(1.30, 1.02–1.66) and 63 % (1.63, 1.10–2.42). In

individuals with a higher cardiovascular risk, rapid changes

in atmospheric pressure were associated with a four-times

higher stroke risk (4.56, 1.26–16.43). Our results suggest

that rapid decreases in ambient temperature and rapid

changes in relative humidity and atmospheric pressure

increase stroke risk under temperate climate conditions.

Individuals with a high cardiovascular risk profile seem to

be at greater risk.

Keywords Cerebrovascular disease � Stroke � Infarction �

Stroke prevention � Weather

Introduction

An increase in several significant risk factors for stroke can

be attributed to long term or acute changes in weather. For

example, onset of atrial fibrillation—the primary cause of

cardioembolic strokes—can be provoked by cold weather

[1, 2]. In addition, a low relative humidity is known to

increase human blood viscosity [3] which is an established

predictor for ischemic strokes [4]. Although a few obser-

vational studies suggest that ambient temperature [5–8] and

atmospheric pressure [9, 10] influence stroke risk, results

are inconsistent and conflicting [11]. A humidity-related

stroke risk could not be demonstrated so far [7, 9]. More-

over, most of these studies focused on absolute meteoro-

logical values and did not take rapid weather changes into

account [5–7]. Lastly, study samples in the studies were

often relatively small [8, 9, 12, 13]. Weather-related stroke

risk is physiologically plausible and knowledge of an

association between weather and stroke risk could help

develop stroke prevention strategies and facilitate a shift in

the awareness of health professionals regarding early signs

of stroke in adverse weather conditions.

& Florian Rakers

florian.rakers@med.uni-jena.de

1 Hans Berger Department of Neurology, Jena University

Hospital, Bachstrasse 18, 07743 Jena, Thuringia, Germany

2 Institute of Medical Statistics, Computer Sciences and

Documentation, Jena University Hospital, Bachstrasse 18,

07743 Jena, Thuringia, Germany

3 Department of Neurology, Helios Hospital Berlin-Buch,

Schwanebecker Chaussee 50, 13125 Berlin, Germany

123

Eur J Epidemiol

DOI 10.1007/s10654-015-0060-3

In the current case-crossover study performed under

temperate climate conditions that prevail in large parts of

Europe and North America, we hypothesized firstly, that

rapid weather changes have an influence on ischemic

stroke risk; and secondly, that this risk applies specifically

to cardioembolic stroke because sympathetic autonomic

activity which promotes atrial fibrillation, increases with

lower temperature [1, 2].

Methods

Study design

Admission data were retrieved from the Jena University

Hospital’s patient data management system. Using the

International Classification of Diseases—10th Revision

(ICD-10) codes, we searched for transient cerebral

ischemic attack lasting between 1 and 24 h (G45.92) and

cerebral infarction (I63.X). Study period was the 1st of

January 2003 until 31st of December 2010 and the

catchment area involved a radius of\10 km around Jena

(filtered by postal codes). Accordingly, patient health

records and all medical reports (including self-reports or

accounts from accompanying caregivers) plus emergency

records together with CT/MRI results were individually

screened to verify the diagnosis and the date and time of

stroke onset. In wake-up strokes, stroke onset was defined

as the mean time between bedtime and wake-up time.

Additional data collected comprises age, sex and risk

factors to calculate the individual Framingham stroke risk

score [14]. Baseline systolic blood pressure needed for

this calculation was estimated from average systolic blood

pressure during the first 3 days of hospitalization. Stroke

subtypes were classified in accordance with the Trial of

ORG 10172 in Acute Stroke Treatment (TOAST) criteria

[15]. Severity of stroke symptoms was determined

according to the National Institutes of Health Stroke Scale

(NIHSS) [16]. Regular meetings were held during the

study period to ensure consistent stroke classification

procedures.

Exclusion criteria included: (1) inaccessible patient file,

(2) stroke occurring outside the 10 km zone around Jena

University Hospital, (3) diagnosis other than stroke due to

errors in hospital admission data, and, (4) inability to

determine the acute onset of stroke symptoms.

Temperature, relative humidity and atmospheric pres-

sure data were provided as hourly values for the entire

study period by the meteorological monitoring station of

the Jena University of Applied Sciences (longitude

11�340E/latitude 50�550N/altitude 215 m). The city of Jena

has a temperate climate with mild summers and moderately

cool winters [17].

Statistical analysis

A case-crossover analysis was used to determine weather-

related stroke risk. This design was previously developed

to study the association between a transient exposure and a

risk factor for the development of an acute and rare event

[18]. The approach is a variation of the case–control

method, the difference being that every patient serves as

his or her own control. This allows controlling by design

for individual risks such as age, sex, socioeconomic status

or seasonal influences that do not change over a short

period of time. Interference is based on comparing the

potentially health-affecting conditions directly before the

event (hazard interval: 24 h weather changes between day-

2 and -1, -3 and -2 and between day-4 and -3 before onset

of stroke symptoms) with the same conditions in the

patient’s recent past (control interval: 24 h weather chan-

ges on respective days in previous week). The number of

days between weather change and stroke onset is referred

to as lag time. Three different lag times were used to

consider a potential delay before impact of the specific

meteorological variable. Conditional logistic regression

was used to take the self-matching structure of the case-

crossover design into account. The stratifying variable in

this case is the individual patient. The association between

mean daily changes in temperature, relative humidity and

atmospheric pressure and ischemic stroke risk is quantified

as the odds ratio that describes the change in odds for an

event according to alterations in the examined weather

characteristics. The hourly values of meteorological vari-

ables obtained from the meteorological station described

above were averaged over 24 h for day one, two and three

(hazard period) and day seven (control period) before

stroke occurrence. Averaged meteorological variables were

analyzed in two different models of conditional logistic

regression: (model one) as a continuous variable and

(model two) as a categorized variable with six categories.

For ambient temperature, cut off values were -5, -3, -1,

1, 3, 5 �C. Temperature changes between -1 and 1 �C

were taken as the reference category. For relative humidity,

cutoff values were the same as for temperature. For

atmospheric pressure, cutoff values were -10, -5, -2, 2,

5, 10 hPa with the changes in atmospheric pressure

between -2 and 2 hPa serving as the reference category.

These cutoff values were chosen according to values used

in previous studies to ensure comparability [12] or after

visual inspection of the appropriate distribution curve.

Confounding in a case-crossover study is only possible

among correlated transient exposures. In this study—given

the nature of weather—patients were exposed to all three

meteorological variables at the same time. To control for

this within-individual confounding, we used multivariable

conditional logistic regression. In addition, we regarded the

F. Rakers et al.

123

day of the week as a potential confounder as stroke risk

also depends on the day of the week [19]. By choosing a

7-day control period, both stroke occurrence and control

period shared the same day of the week and we adjusted for

this potential confounder. All analyses were performed for

the whole study population as well as for age (stratified by

older or younger than 60 years), sex and other risk factor

subgroups. The Framingham stroke risk score [14] was

grouped into three categories (mild risk: B12 points,

moderate risk: 13–17 points, high risk: C18) after visual

inspection of the distribution curve. The NIHSS was

grouped into two categories (less severe:\8 points, more

severe: C8 points) which is consistent with other stroke

studies [20]. Odds ratios in model one (weather as a con-

tinuous variable) refer to a 24 h change in the respective

meteorological variable that equals the 10th percentile of

all observed 24 h changes in this variable during the study

period (Table 2), i.e. we present odds ratios associated with

weather changes that are not uncommon and thus clinically

relevant.

Results

Study cohort

Of the 2066 patients admitted to Jena University Hospital

with a diagnosis of stroke, 177 (9 %) could not be pro-

cessed as patient files were not available during the

screening period. In 81 cases (4 %), we were unable to

retrospectively determine the date of acute onset of stroke

symptoms and a further 114 cases (5 %) did not meet the

ischemic stroke criteria. The remaining 1694 cases formed

the basis of this case-crossover study (Fig. 1). Character-

istics of the study population are described in Table 1. The

Framingham Stroke Risk could be calculated retrospec-

tively in 1645 cases and the NIHSS could be retrieved

electronically in 782 cases.

Meteorological variables

Table 2 summarizes the 24 h changes in mean daily values

of meteorological variables. During the study period, the

average daily temperature ranged from -14.0 to 28.6 �C.

Average daily atmospheric pressure and relative humidity

values ranged from 955.1 to 1017.1 hPa and 40.0–99.1 %,

respectively.

Stroke risk in relation to temperature

Figure 2 shows the association between stroke risk and the

change in ambient temperature analyzed as a continuous

variable. For each 2.9 �C decrease in mean daily ambient

temperature, the stroke risk in the overall population

increased by a maximum of 11 % [OR 1.10, 95 % confi-

dence interval (CI) 1.01–1.21, lag time: 1 day; 1.11,

1.01–1.22, lag time: 2 days]. Further, the risk for car-

dioembolic strokes increased by 26 % (1.26, 1.06–1.50, lag

1 day). The general risk of stroke in older patients

increased by a maximum of 13 % (1.13, 1.02–1.25, lag

1 day; 1.11, 1.01–1.23, lag 2 days). In women, the general

stroke risk increased by 14 % (1.14, 1.01–1.30, lag 2 days).

Those with increased risk for vascular disease showed a

30 % (1.30, 1.06–1.61, lag 1 day) higher general stroke

risk for a medium Framingham score and a 16 % (1.16,

1.01–1.32, lag 2 days) higher risk for a high Framingham

score. The magnitude of all associations decreased over

time and associations were non-significant following a lag

time of[2 days.

In the categorized model, positive odds ratios indicate

an increased stroke risk in the overall population following

a decrease in mean daily ambient temperature between 3

and 5 �C (1.15, 0.87–1.51, lag 2 days) and more so for a

decrease of greater than 5 �C (1.47, 0.85–2.52, lag 2 days;

Fig. 5). However, the CI included 1.00. Increases in tem-

perature of more than 5 �C were associated with an up to

47 % (0.53, 0.28–1.00, lag 1 day; 0.57, 0.29–1.05, lag

2 days) decrease in stroke risk (Fig. 5). In subgroups,

stroke risk in women increased by 30 % (1.30, 1.01–1.68,

lag 2 days) after a temperature decrease of 1–3 �C. Stroke

risk more than tripled (3.25, 1.03–10.25, lag 2 days) in

those with a medium Framingham risk score following a

decrease in temperature of more than 5 �C. Risk for less

severe strokes increased by 74 % (1.74, 1.06–2.87, lag

2 days) after a temperature decrease of 3–5 �C. The risk for

cardioembolic strokes tended to be more than two times

higher (2.77, 0.97–7.89, lag 1 day) after a temperature

decrease of more than 5 �C. For cardioembolic strokes,

stroke risk decreased by 22 % (0.78, 0.47–1.29, lag 3 days)

following a temperature increase of 1–3 �C. In males,

stroke risk decreased by 67 % (0.33, 0.12–0.93, lag 1 day)

after a temperature increase of more than 5 �C.

Stroke risk in relation to relative humidity

Figure 3 depicts the association between stroke risk and the

mean daily relative humidity analyzed as a continuous

variable. For each mean daily decrease in relative humidity

of 4.1 %, the general stroke risk in the overall population

increased by 4 % (1.04, 1.01–1.07, lag 1 day) and the risk

for cardioembolic strokes by 6 % (1.06, 1.00–1.12, lag

1 day). The general stroke risk in women increased by 6 %

(1.06, 1.01–1.11, lag 1 day), and in younger individuals by

9 % (1.09, 1.00–1.18, lag 1 day). In patients with a low

Framingham score, the general risk of stroke was raised by

7 % (1.07, 1.01–1.14, lag 1 day).

Rapid weather changes are associated with increased ischemic stroke risk: a case-crossover…

123

Analysis of the mean daily relative humidity as a cate-

gorized variable demonstrated a increase in stroke risk of

maximal 30 % (1.26, 1.01–1.59, lag 1 day; 1.30,

1.02–1.66, lag 2 days, Fig. 5) in the overall population

following a more than 5 % decrease in relative humidity. A

comparable increase in stroke risk was observed after an

increase in relative humidity of 3–5 % (1.34, 0.98–1.84,

lag 1 day; 1.39, 1.01–1.90, lag 2 days; Fig. 5). In sub-

groups, the stroke risk generally increased in males by a

maximum of 48 % (1.48, 1.07–2.05, lag 1 day; 1.38,

0.98–1.93, lag 2 days; 1.45, 1.03–2.05, lag 3 days) after

exposure to a decrease in relative humidity of more than

5 % and by a maximum of 72 % (1.45, 0.90–2.32, lag

1 day; 1.48, 0.93–2.35, lag 2 days; 1.72, 1.07–2.75, lag

3 days) after exposure to an increase in relative humidity

between 3 and 5 %. In patients with a low Framingham

score, stroke risk increased by 71 % (1.71, 1.02–2.88, lag

1 day) after a decrease in relative humidity of more than

5 %. Risk for strokes due to large artery atherosclerosis

was about three times higher (2.72, 1.11–6.7, lag 1 day;

3.11, 1.28–7.53, lag 2 days) after an increase in relative

humidity between 3 and 5 %.

Stroke risk in relation to atmospheric pressure

Figure 4 shows the association between stroke risk and

mean daily atmospheric pressure analyzed as a continuous

variable. We found no association between a change in

atmospheric pressure over 24 h and the general stroke risk

in the overall population at all lag times. However, for each

Fig. 1 Flowchart of the patient

data selection process for the

case-crossover study

Table 1 Characteristics of patients admitted to the Jena University

Hospital with a verified diagnosis of ischemic stroke or transient

ischemic attack (TIA) between 1st January 2003 and 31st December

2010

No. %

Overall population 1694 100

Median age (years) 75

Young (\60) 246 15

Old (C60) 1448 85

Men 824 49

Previous stroke/TIA 526 31

Pathogenesis

Small artery occlusion 696 41

Cardioembolism 541 32

Large artery atherosclerosis 272 16

Undetermined 185 11

Median Framingham stroke risk score 18

Low (B12) 381 23

Middle (13–17) 401 24

High (C17) 863 53

Median NIHSS score 4

Less severe (\8) 504 64

More severe (C8) 278 36

F. Rakers et al.

123

Table 2 Percentiles of 24 h

changes of mean daily

meteorological parameters over

the study period 1st January

2003–31st December 2010

Percentiles

5th 10th 25th 50th 75th 90th 95th

Temperature (�C) -3.8 -2.9 -1.4 0.1 1.5 2.8 3.6

Atmospheric pressure (hPa) -4.1 -3.2 -1.9 -0.2 1.6 3.7 5.1

Relative humidity (%) -5.9 -4.1 -1.8 0.2 2.1 3.8 4.9

Fig. 2 Odds ratios for the

association of stroke risk with a

decrease of 2.9 �C in mean

daily ambient temperature over

24 h for lag times of 1, 2 and

3 days before onset of stroke

symptoms in the overall

population and subgroups.

Square size is proportional to

the number of cases, bars

indicate 95 % CI, adjusted for

relative humidity and

atmospheric pressure, filled

squares mark odds ratios with

confidence intervals not

including 1.00

Fig. 3 Odds ratios for the

association of stroke risk with a

decrease of 4.1 % in mean daily

relative humidity over 24 h for

lag times of 1–3 days before

onset of stroke symptoms in the

overall population and

subgroups. Square size is

proportional to the number of

cases, bars indicate 95 % CI,

adjusted for temperature and

atmospheric pressure, filled

squares mark odds ratios with

confidence intervals not

including 1.00

Rapid weather changes are associated with increased ischemic stroke risk: a case-crossover…

123

3.2 hPa increase in atmospheric pressure over 24 h, the risk

for clinically severe strokes decreased by 11 % (0.89,

0.80–0.99, lag 1 day). In younger individuals, the general

stroke risk also decreased by 14 % (0.86, 0.76–0.96, lag

2 days).

Analyzed as a categorized variable, a decrease of mean

daily atmospheric pressure of more than 10 hPa over 24 h

was associated with an increase in stroke risk by up to

46 % (1.32, 0.86–2.04, lag 1 day; 1.46, 0.96–2.11, lag

3 days; Fig. 5) in the overall population. Comparably, after

an increase in atmospheric pressure of more than 10 hPa,

stroke risk increased in the overall population by a maxi-

mum of 63 % (1.56, 1.06–2.29, lag 1 day; 1.63, 1.10–2.42,

lag 3 days; Fig. 5). Increases in stroke risk were observed

after a decrease in atmospheric pressure between 2 and

5 hPa (1.38, 1.14–1.69, lag 3 days; Fig. 5) and after an

increase in atmospheric pressure between 2 and 5 hPa

(1.29, 1.03–1.63, lag 3 days; Fig. 5). Within subgroups,

stroke risk increased in older patients by 79 % (1.79,

1.10–2.91, lag 1 day) after a decrease in atmospheric

pressure of more than 10 hPa, by 37 % (1.37, 1.11–1.69,

lag 3 days) after a decrease in atmospheric pressure

between 2 and 5 hPa and by a maximum of 58 % (1.55,

1.03–2.36, lag 1 day; 1.58, 1.06–2.43, lag 2 days) after an

increase in atmospheric pressure of more than 10 hPa. In

males, stroke risk increased by a maximum of 67 % (1.35,

1.01–1.81, lag 1 day; 1.67, 1.26–2.21, lag 3 days) follow-

ing a decrease in atmospheric pressure between 2 and 5 and

by 84 % (1.84, 1.03–3.27, lag 1 day) after an increase in

atmospheric pressure of more than 10 hPa. Those with a

medium Framingham score showed a more than four-times

higher stroke risk after a decrease in atmospheric pressure

of more than 10 hPa (4.56, 1.26–16.43, lag 1 day). In

patients with a high Framingham score, stroke risk

increased by 46 % (1.46, 1.11–1.92, lag 3 days) after a

decrease in atmospheric pressure between 2 and 5 hPa and

by 71 % (1.71, 1.02–2.94, lag 3 days) after an increase in

atmospheric pressure of more than 10 hPa. Risk for strokes

due to large artery atherosclerosis approximately doubled

following a decrease in atmospheric pressure between 5

and 10 hPa (2.30, 1.29–4.10, lag 3 days) and after an

increase in atmospheric pressure between 5 and 10 hPa

(1.88, 1.01–3.50, lag 3 days). Risk for strokes due to small

artery occlusion was more than doubled (2.22, 1.16–4.22,

lag 3 days) after an increase in atmospheric pressure of

more than 10 hPa.

Discussion

The present study identifies a rapid decrease of ambient

temperature as well as rapid changes in relative humidity

and atmospheric pressure as risk factors for ischemic stroke

in a large study population from a primary care hospital in

central Germany using two different models of conditional

logistic regression analysis.

In the firstmodel, meteorological variables were analyzed

as continuous variables and thus a linear association between

weather and stroke risk was assumed (Figs. 2, 3, 4). This

assumption was then further explored by analyzing the

Fig. 4 Odds ratios for the

association of stroke risk with a

decrease of 3.2 hPa in mean

daily atmospheric pressure over

24 h for lag times of 1, 2 and

3 days before onset of stroke

symptoms in the overall

population and subgroups.

Square size is proportional to

the number of cases, bars

indicate 95 % CI, adjusted for

temperature and relative

humidity, filled squares mark

odds ratios with confidence

intervals not including 1.00

F. Rakers et al.

123

appropriate variable in a categorized model. Here, a rapid

drop in temperature was generally associated with an

increased stroke risk, whereas large increases in temperature

were associatedwith a decreased stroke risk both in the entire

study population (Fig. 5) and in the subgroups. Even though

the protective effects of a temperature increase are more

distinct than the increased risk of a temperature drop, the

association between ambient temperature and stroke risk

appears to be close to linear. For changes in relative humidity

and atmospheric pressure, the assumption of linearity could

generally not be met. Larger increases as well as larger

decreases of these variableswithin 24 hwere associatedwith

an increased stroke risk resulting in an almost U-shaped

association curve (Fig. 5).

Fig. 5 Odds ratios for the association of stroke risk with categorized

24 h changes of ambient temperature, relative humidity and atmo-

spheric pressure for different cut off points and lag times in the

overall study population. Overlaid with 2nd order polynomial

trendline to illustrate the observed associations. Bars indicate 95 %

confidence inverval. Asterisks marks odds ratios with confidence

intervals not including 1.00. Each odds ratio is adjusted for the two

respective other meteorological variables. Non-filled boxes represent

the reference category

Rapid weather changes are associated with increased ischemic stroke risk: a case-crossover…

123

A rapid decrease in temperature over 24 h was associ-

ated with an increased risk for cardioembolic strokes in

both logistic regression analysis models. This is compatible

with the mechanistic explanation of a temperature-related

onset of atrial fibrillation—the primary cause of car-

dioembolic strokes—which is also provoked by cold

weather [1, 2]. Other possible mechanisms for the raised

incidence of cardioembolic strokes include increased sys-

tolic blood pressure at low temperatures and a consecu-

tively increased left atrial dilatation promoting atrial

fibrillation [1, 2]. In line with this, the odds ratios from

both models indicate that in those with an increased vas-

cular risk profile for vascular disease—in whom the inci-

dence of atrial fibrillation is greatest [21]—the association

between acute temperature changes and stroke risk is most

pronounced. In women and elderly patients, stroke risk

seems to increase following decreasing temperatures.

However, these associations were significant only when

temperature was analyzed as a continuous variable and the

odds ratios were close to those in the overall population.

Thus, our results do not allow a final conclusion about

whether stroke risk associated with temperature is gender

or age dependent. While gender effects have previously

been reported in Asia [5, 8], two previous European reports

failed to show a significant gender effect for temperature-

related ischemic stroke risk [12, 13].

In contrast to our results, two recent studies undertaken

in Italy [10] and Scotland [22] reported a positive corre-

lation between an increase in temperature and ischemic

stroke risk. A further study from Israel has shown an

increased stroke risk in the Negev Desert on hot days [23].

However, the Mediterranean climate found in Italy, the

maritime climate of western Scotland and the desert cli-

mate in Israel are not comparable to central Europe’s cli-

mate [17], and accordingly these findings do not

necessarily contradict our results. Moreover, the Italian and

Scottish studies differed significantly in design, as both

analyses specified the first day of hospitalization as the

onset of stroke and not the time of actual onset of stroke

symptoms. This approach might have introduced a bias in

the two European studies, since it is estimated that

10–30 % of all stroke patients present to the emergency

department with a delay of more than 24 h [24]. In

agreement with our findings, a small case-crossover study

from South Korea [8] also showed an association between

a drop in temperature and increased risk for stroke.

To date, the impact of humidity on ischemic stroke risk

has received little attention. In a Spanish study and in one

large intercontinental analysis [7, 9], relative humidity

and/or rainfall were not associated with stroke risk,

although a Japanese study reported a positive association

between rainfall and stroke risk in women [5]. However,

this association was not sustained after adjusting for other

meteorological factors. While these studies focused on

mid- and long-term changes of meteorological variables,

our results suggest that especially rapid changes in relative

humidity increase stroke risk, regardless of whether these

changes are positive or negative. In the categorized model,

a consistently higher odds ratio was observed in males after

large changes in relative humidity at all lag times. Our

findings might be partly explained by a physiological

response to a drop in relative humidity leading to increased

blood viscosity [3] that may promote ischemic strokes via

increased thrombogenesis [4].

We observed a considerably higher stroke risk after

sudden positive or negative changes in atmospheric pres-

sure in the categorized model. Our results may appear to be

in conflict with other studies in which no significant

association between atmospheric pressure and ischemic

stroke risk was ascertained [13, 22, 25]. However, these

studies assumed a linear association between atmospheric

pressure and stroke risk and as such are comparable to our

first model that did not show a relationship between

atmospheric pressure and stroke risk. Further, it has been

suggested that changes in atmospheric pressure may lead to

a plaque rupture in the carotid arteries [29]. Even though

this speculation would support our finding of an association

between changes in atmospheric pressure and stroke risk

related to large artery pathogenesis, to date, there are no

data in the literature that provide a validated mechanism

for this association [11].

Our study includes several important features. This is

the first analysis to show a weather-related stroke risk in

the prevailing temperate climate of large parts of Europe

and North America. Secondly, the large study population

allows the determination of a weather-related cardioem-

bolic stroke risk and identification of an increased stroke

risk in the subgroup of individuals with an increased risk

profile for vascular disease. Thirdly, by using the onset of

stroke symptoms instead of the date of hospital admission

or mortality data for our analysis, we avoided a potential

bias that might have affected the outcome in previous

studies [5–8].

It is important to note a few limitations of our hospital-

based study. Firstly, since we had no way of determining

the number of stroke patients not admitted to the hospital, a

selection bias might have altered the results. However,

since the Jena University Hospital is the only hospital with

a stroke unit within the defined study radius and all

emergencies are referred to the emergency department, this

minimizes a potential selection bias. Secondly, we were

unable to control for air-pollution. Air-pollution can result

in respiratory infections which are not only potential

stroke-risk factors but also linked to changes in meteoro-

logical parameters [26, 27]. However, average air-pollution

in the rural Jena region is low [28] compared to

F. Rakers et al.

123

metropolitan areas like Seoul [26]. In addition, our data did

not include microclimate information, such as room tem-

perature and room humidity. However, extensive heating

and air conditioning is relatively uncommon in the climate

examined. Moreover, we did not consider weather-related

physical activity that may have an impact on individual

exposure to outdoor temperatures and humidity.

Conclusions

Our findings show a marked association between stroke

risk and rapid weather changes. Sudden decreases in

ambient temperature as well as rapid changes in relative

humidity and atmospheric pressure over 24 h increase

stroke risk under temperate climate conditions. Analyzing a

large cohort, we identified that individuals with a higher

risk profile for vascular disease are at particular risk. In the

general population, this risk applies mainly but not exclu-

sively to cardioembolic strokes. The knowledge of the

association between weather and stroke risk may encour-

age healthcare authorities to implement stroke prevention

strategies by means of shifting the attention of health

professionals to early signs of stroke under adverse weather

conditions, by raising public awareness and educating

subgroups at risk.

Acknowledgments We thank Nasim Kroegel (Jena University

Hospital) for critical reading of the manuscript and her helpful

suggestions.

Conflict of interest None.

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