Sex differences in the risk profile and male
predominance in silent brain infarction in community-
dwelling elderly subjects: the Sefuri brain MRI study
Yuki Takashima1, Yoshikazu Miwa2, Takahiro Mori1, Manabu Hashimoto1, Akira Uchino3, Takefumi Yuzuriha1,
Toshiyuki Sasaguri2and Hiroshi Yao1
Although brain infarction is more common in men, the male predominance of silent brain infarction (SBI) was inconsistent in
the earlier studies. This study was to examine the relationship between sex differences in the risk profile and SBI. We conducted
a population-based, cross-sectional analysis of cardiovascular risk factors and SBI on MRI. We asked all the female participants
about the age at natural menopause and parity. SBI was detected in 77 (11.3%) of 680 participants (266 men and 414
women) with a mean age of 64.5 (range 40–93) years. In the logistic analysis, age (odds ratio (OR)¼2.760/10 years, 95%
confidence interval (CI)¼2.037–3.738), hypertension (OR¼3.465, 95% CI¼1.991–6.031), alcohol intake (OR¼2.494, 95%
CI¼1.392–4.466) and smoking (OR¼2.302, 95% CI¼1.161–4.565) were significant factors concerning SBI. Although SBI was
more prevalent among men, this sex difference disappeared on the multivariate model after adjustment for other confounders.
In 215 women aged 60 years or older, age at natural menopause, early menopause, duration of menopause, number of children
and age at the last parity were not significantly associated with SBI after adjustment for age. Hypertension and age were
considered to be the major risk factors for SBI in community-dwelling people. Male predominance in SBI was largely due
to higher prevalence of alcohol habit and smoking in men than in women in our population.
Hypertension Research (2010) 33, 748–752; doi:10.1038/hr.2010.69; published online 30 April 2010
Keywords: asymptomatic stroke; lacunar infarction; menopause; MRI; risk factors
Brain infarction is more common in men.1Male sex may be a risk
factor for symptomatic stroke, whereas premenopausal women
appeared to be protected from cardiovascular events or stroke.
Exceptions were groups of 35–44 years and over 85 years, in which
women had slightly greater stroke incidence than men.2Estrogen may
have beneficial effects on endothelial function and atherosclerosis in
addition to the hormone’s effects on serum lipid concentrations,
raising the possibility of sex differences in arterial remodeling.3The
ability to have children at older age may be a marker for slow aging
and extreme longevity.4On the contrary, Zhang et al.5have found that
high gravity and high parity were associated with a higher risk of
ischemic stroke. In the Framingham Heart Study, early menopause
was associated with an increased incidence of ischemic stroke.6Taken
together, female sex may be a non-modifiable protective factor against
symptomatic ischemic stroke. However, the male predominance of
silent brain infarction (SBI) was inconsistent in the earlier studies.7–11
With regard to SBI, the North Manhattan Study found that male
sex was independently associated with SBI on a multivariable logistic
regression model.7Although the Rotterdam Scan Study reported a
higher prevalence of SBI among women than men, the sex difference
was no longer statistically significant when adjusted for other risk
factors.8In a population-based consecutive autopsy series of residents
(the Hisayama Study), SBI tended to be more frequent (non-signifi-
cant on multivariate analysis) in female among 713 subjects without
clinical stroke: 16.2% of 390 men and 19.2% of 323 women with a
mean age at death of 78.3 years.9In contrast, sex was not indepen-
dently associated with an increased risk of SBI in the Cardiovascular
Health Study and Framingham Offspring Study.10,11In this study, we
conducted a population-based, cross-sectional analysis of brain MRI
findings to examine the relationship between sex differences in the risk
profile and SBI.
Between 1997 and 2007, we randomly contacted approximately 1200 inhabi-
tants aged 40 years or older, living in the rural community of Sefuri village,
Saga, Japan, through the village office, and 720 subjects (60%) visited for their
first MRI examination. These subjects were living independently at home
Received 25 January 2010; revised 3 March 2010; accepted 17 March 2010; published online 30 April 2010
1Center for Emotional and Behavioral Disorders, National Hospital Organization Hizen Psychiatric Center, Saga, Japan;2Department of Clinical Pharmacology, Graduate School of
Medical Sciences, Kyushu University, Fukuoka, Japan and3Department of Radiology, Saitama Medical University International Medical Center, Saitama, Japan
Correspondence: Dr H Yao, Center for Emotional and Behavioral Disorders, National Hospital Organization Hizen Psychiatric Center, Mitsu 160, Yoshinogari, Kanzaki,
Saga 842-0192, Japan.
Hypertension Research (2010) 33, 748–752
& 2010 The Japanese Society of Hypertension All rights reserved 0916-9636/10 $32.00
without apparent dementia. Eight subjects did not undergo MRI examination
because of claustrophobia (n¼5) and contraindications for MRI (n¼3).
Subjects with a history of stroke (n¼18), brain tumor (n¼5), malignant
neoplasm (n¼2), psychiatric disorders including depression (n¼3) or a history
of head trauma (n¼4) were also excluded. Two cases of transient ischemic
attack were included in subjects with a history of stroke: one had progressed to
overt stroke 2 days later and the other proved to be a small putamenal
hemorrhage on MRI. The National Hospital Organization Hizen Psychiatric
Center Institutional Review Board approved the study (No. 15-1), and written
informed consent was obtained from all subjects.
Participants underwent a structured clinical interview, a neurological exami-
nation, general hematology tests, biochemistry tests and ECGs. Blood pressure
was measured in the sitting position by the standard cuff method after a 5-min
rest. Vascular risk factors were defined as described earlier.12,13Briefly, arterial
hypertension was considered present if a subject had a history of repeated
blood pressure recordings above 140/90mmHg or the subject was being treated
for hypertension. Diabetes mellitus was defined as fasting plasma glucose
47.77mmoll–1and/or HbA1c 46.0%, or an earlier diagnosis of diabetes
mellitus. Hyperlipidemia was defined as total serum cholesterol concentration
45.69mmoll–1or if the subject was being treated for hyperlipidemia. We
obtained information about usual alcohol intake and type of alcohol consumed
from a detailed questionnaire as described earlier.13We defined one drink as
10g of ethanol, calculated as follows: 350ml beers as 1.4 drinks, 180ml sake
(rice wine) as 2.2 drinks, 180ml shochu (white spirits) as 3.6 drinks, 60ml
whisky as 2.0 drinks and 120ml wine as 1.2 drinks. In this study, we defined
alcohol intake as one drink or more per week, because the earlier study from
the same population revealed that even light drinkers had the similar risk
for SBI (odds ratio (OR)¼4.1, 95% confidence interval (CI)¼1.7–10.0) as
moderate drinkers (OR¼3.1, 95% CI¼1.3–7.0). Former drinkers were con-
sidered non-drinker in this study. Smoking was defined as present if the
subject smoked at least an average of 10 cigarettes per day.
We asked all the female participants about items discussed below using a
questionnaire, and analyzed potential risk factors for SBI in 215 women aged
60 years or older in relation to age at natural menopause and parity. Natural
menopause was considered to occur if a woman had ceased menstruating
naturally for at least 1 year. Age at natural menopause was the self-reported age
at last menstrual period. Early menopause was defined as natural menopause
before age 40. Women were also queried as to the cause of menopause (natural,
surgical, other), whether a hysterectomy was performed, number of ovaries
removed, the use of hormone replacement therapy, the total number of
children and the age at giving birth to her last child. Subjects with non-natural
menopause were excluded from the analysis.
The combination of T1WI, T2WI and FLAIR images is required to
accurately detect both SBI and white matter lesions (WMLs).14Therefore, T1
weighted (TR/TE¼510/12ms), T2 weighted (TR/TE¼4300/110ms) and FLAIR
(TR/TI/TE¼6750/1600/22ms) images were obtained with a slice thickness of
6mm with a 1mm interslice gap with an MRI (1.0T, Shimadzu Magnex XP,
Kyoto, Japan). SBI was shown as low signal intensities on T1-weighted images,
and their size was 5mm or larger as described earlier (Figure 1).12,13
We differentiated enlarged perivascular spaces from SBI on the basis of their
location, shape and size.15,16The WMLs were defined as isointense with normal
brain parenchyma on T1-weighted images, high signal intensity areas on
T2-weighted images and were classified into deep white matter lesions
(DWMLs) and periventricular hyperintensities (PVHs). We used the validated
rating scale of DWMLs by Fazekas et al.17: Grade 0, absent; Grade 1, punctate
foci; Grade 2, beginning confluence of foci; Grade 3, large confluent areas.
Figure 1 (a–c) An 80-year-old man with silent brain infarction (SBI) in the right thalamus (arrow) and the left basal ganglia (arrow head). The SBI is shown
as low signal intensity on the T1 weighted (A), high signal intensity on the T2 weighted and iso or high signal intensity with or without low intensity at the
center on the fluid-attenuated inversion recovery (FLAIR) images. (d) A 70-year-old man with dilated periventricular spaces in the bilateral lower one-third of
basal ganglia (circles). Bar indicates 10mm. L, left.
Sex differences in silent brain infarction
Y Takashima et al
For PVHs, we determined the presence and severity (Grade 0, absent; Grade 1,
pencil thin; Grade 2, smooth halo lining) using FLAIR images. All scans were
reviewed independently by two authors (HYand AU) who were blinded to all
clinical data. In the case of disagreement between the raters, a consensus
reading was held.
All values were given as mean±s.d. The data were analyzed with the
Predictive Analysis Software (PASW Statistics 18.0, formerly called SPSS
Statistics, SPSS Inc., Chicago, IL, USA). A significance level of 0.05 was used
in all analyses. For the univariate analysis, the t-test for continuous variables,
the w2test for categorical variables and the non-parametric Mann–Whitney
U-test for variables with skewed distribution were used as appropriate. We
chose the variables for entry into the multivariate analysis based on the clinical
and neuroradiological findings after univariate testing. Multivariate analysis
was performed using the forward stepwise method of logistic analysis.
The subjects comprised 266 men and 414 women with a mean age
of 64.5 (range 40–93) years (Table 1). SBI, DWMLs and PVHs
were detected in 77 (11.3%), 204 (30.0%) and 121 (17.8%) of 680
participants, respectively. The prevalence of all these MRI findings
increased steeply with age, whereas SBI alone were more frequent in
men than in women (Figure 2). Of 77 subjects with SBI, 73 (95%) had
only lacune(s) and 51 of 73 subjects (70%) had a single lacune.
The mean age at natural menopause was 48.7±4.4 years (a median
of 50 years), and the mean number of children was 3.5±1.4 (a median
of 3). Age at natural menopause, early menopause (10 of 215 women)
and age at the last parity were not significantly associated with SBI
(Table 2). Although duration of menopause (P¼0.010) and number of
children (P¼0.052) tended to be associated with SBI on univariate
analysis, these associations did not persist after adjustment for age. In
this group of female subjects aged 60 years or older, alcohol habit was
independently associated with SBI. Even if hypertension, diabetes
mellitus and hyperlipidemia were forced into the multivariate model
regardless of statistical significance, they did not affect the results
of Table 2.
In the logistic analysis, age (OR¼2.760/10 years, 95% CI¼2.037–
3.738), hypertension (OR¼3.465, 95% CI¼1.991–6.031), alcohol
intake (OR¼2.494, 95% CI¼1.392–4.466) and smoking (OR¼2.302,
95% CI¼1.161–4.565) were significant factors concerning SBI
(Table 3). Male sex was not significantly associated with WMLs.
Hypertension and age, but neither alcohol nor smoking, were the
major factors associated with both DWMLs and PVHs (Table 3).
Although SBI was more prevalent among men on univariate analysis
(P¼0.015), this sex difference disappeared on the multivariate model
after adjustment for other confounders. Age, body mass index,
hypertension and blood pressure were well balanced between men
and women (Table 1). Hypertension was present in 260 (38.2%)
of 680 subjects. Blood pressure levels were 126±16/76±9, 153±20/
81±11 and 166±17/89±10mmHg in normotensive subjects
(n¼420), treated hypertensive subjects (n¼169) and non-treated
hypertensive subjects (n¼91), respectively. Common vascular risk
factors such as diabetes mellitus, alcohol and smoking were more
frequent in men, and more frequent hyperlipidemia in women.
This is the first study, which showed that higher prevalence of lifestyle
risk factors rather than sex explains the male predominance of SBI. We
found a prevalence of SBI of 11.3% in community-dwelling subjects
with a mean age of 64.5 years. This is comparable with two prior
studies, the Atherosclerosis Risk in Community (ARIC) Study18and
the Framingham Heart Study11(prevalence and mean age: 11%, 63
years and 10.7%, 61 years, respectively). A Japanese brain check-up
study, among participants who received MRI at their own expense,
reported a similar prevalence of 10.6%.19This study showed that age,
hypertension, alcohol habit and smoking were independently asso-
ciated with SBI. We found a male predominance of SBI (15.0% in men
vs. 8.9% in women), which was similar to the North Manhattan Study
(21.3% in men vs. 15.2% in women).7However, male sex was not
significantly associated with SBI after adjustment for other vascular
risk factors. In other words, higher prevalence of risk factors such as
alcohol and smoking in men produced male predominance of SBI
in this study.
Table 1 Sex differences in demographic measures
Body mass index (kgm–2)
Systolic blood pressure (mmHg)
Diastolic blood pressure (mmHg)
Mean blood pressure (mmHg)
Diabetes mellitus (%)
Values are mean±s.d.
*P¼0.002, **Po0.001 vs. men.
50-59 60-6970-7980-93 (years)
40-49 50-59 60-6970-79 80-93 (years)
40-4950-59 60-6970-7980-93 (years)
Figure 2 Prevalence of silent brain infarction (SBI), deep white matter
lesions (DWMLs) and periventricular hyperintensities (PVHs) with increasing
age in male and female participants.
Sex differences in silent brain infarction
Y Takashima et al
In this study, assumed risk factors unique to women such as early
menopause did not associate with SBI, and older age at the last parity,
as a potential marker for longevity, seemed negative in terms of
preventing SBI inwomen. Age at natural menopause, early menopause
and age at the last parity were not significantly associated with SBI.
Duration of menopause and number of children, which tended to be
associated with SBI on univariate analysis, were not significant after
adjustment for age. As the majority of silent infarcts are related to
small vessel disease, menopause and parity might not be detected as
factors relevant to SBI. Alternatively, the age at menopause and parity
might be an important risk for atherosclerosis (for example large-
artery occlusive infarction, carotid atherosclerosis and coronary heart
disease).20–22Strengths of this study include that it is population based
and includes a relatively large number of residents. The limitation of
this study would be that we could not provide the sex differences in
incidence of SBI because of the cross-sectional nature. The Rotterdam
Scan Study, which reported higher prevalence of SBI among women
than men,8showed similar SBI incidence for both sexes.23Sex
differences in SBI incidence need to be further investigated in future
studies. Another limitation of this study would be that women
before age 60 were excluded from the analysis for the effects of
natural menopause and parity on SBI, because SBI was rare before
60 years (2 of 139 women). Therefore, we cannot exclude the
possibility that early menopause or high parity could be the basis
for SBI at younger ages.
Age and hypertension are the most widely accepted risk factors for
SBI, and other cardiovascular risk factors for symptomatic stroke were
also found to raise the risk of SBI.24In the longitudinal Rotterdam
Study, age, blood pressure, diabetes mellitus, cholesterol, homocys-
teine levels and smoking were associated with new SBI in participants
without prevalent infarcts.23Similarly, the Framingham Offspring
Study showed that atrial fibrillation, hypertension, systolic blood
pressure and an elevated plasma homocysteine, but neither age nor
gender were independently associated with an increased risk of SBI.11
As most of silent infarcts are subcortical lacunar infarction, risk factors
for SBI are similar to those of lacunar infarction or the small vessel
disease. Recently, the community-based PATH Through Life Study
showed that hypertension was the major treatable risk factor for
lacunar infarcts.25Therefore, the present results are compatible with
those reported earlier in terms of risk factor profiles of SBI.
Two earlier studies, the Cardiovascular Health Study and the ARIC
Study, have investigated the effects of alcohol intake on subclinical
MRI findings.26,27The Cardiovascular Health Study found that
moderate alcohol consumption in older adults, aged 65 years or
older was associated with a lower prevalence of SBI, whereas the
ARIC Study showed that alcohol intake in middle-aged adults was not
associated with MRI infarction. Our earlier study as well as this study
revealed that even a low amount of regular drinking may be a risk
factor for SBI in community-dwelling Japanese people.13Effects of
alcohol on SBI were evident also in the selected group of female
subjects with natural menopause aged 60 years or older (Table 3).
Discrepancies between the results of our study and those of the earlier
studies may be partly explained by racial differences such as obviously
lower body mass index of Japanese compared with those of western
populations, and the frequent genetic deficiency in alcohol detoxifica-
tion in Japanese and Orientals.28Furthermore, among a Japanese
population, lacunar infarction was the most common subtype of
cerebral infarction,29whereas stroke registries of western countries
have reported lower frequencies of lacunar infarction than of ather-
othrombotic and cardioembolic infarction. Alcohol may be partly
protective against proximal segment of the cerebrovascular tree, but
not for small vessels or SBI.
The relationship between smoking and SBI has been unclear. With
regard to symptomatic stroke, an early meta-analysis revealed that the
Table 2 Menopause, parity and silent brain infarction among women
aged 60 years or older
P Odds ratio 95% CIP
Age (per 10 years)
Age at natural menopause
Duration of menopause
(per 10 years)
No. of children
Age at the last parity
Abbreviation: CI, confidence interval.
Table 3 Potential risk factors for silent brain infarction and white matter lesions
Silent brain infarction Deep white matter lesionsPeriventricular hyperintensities
P Odds ratio95% CIPP Odds ratio95% CIPP Odds ratio 95% CIP
Age (per 10 years)
Uric acid (per mg
2.760 2.037–3.738 0.0000.000
2.0841.737–2.502 0.000 0.000
3.4651.991–6.031 0.000 1.611
Abbreviations: CI, confidence interval; NS, non-significant.
Sex differences in silent brain infarction
Y Takashima et al
relative risk of stroke associated with smoking was 1.5 (95% CI¼
1.4–1.6).30Subarachnoid hemorrhage was most clearly associated
with smoking, and cerebral infarction was almost twice as likely in
smokers compared with non-smokers. Although smoking may be
more strongly related to atherogenic strokes rather than small vessel
disease,31the smoking-associated increased risk was found for lacunar
infarction.32,33Mannami et al.33summarized several plausible
mechanisms for smoking-related risk of stroke such as hypercoagul-
able states, reduced blood flow, reduced HDL cholesterol and direct
injury to endothelial cells. The ARIC Study showed that current
smoking and hypertension both almost doubled the odds of SBI
(1.88 for current smoking, 2.00 for hypertension).15In a high-risk
Japanese community-dwelling population, smoking status and systolic
blood pressure were independent determinant of the number of
SBI.34This study also found an independent association of smoking
with SBI. Of note, the higher prevalence of SBI in men was partly
due to the fact that smoking habit in women was extremely low in
In conclusion, age, hypertension, alcohol and smoking were
considered to be the risk factors for SBI in community-dwelling
people. We showed that higher prevalence of alcohol habit and
smoking in men than in women rather than biological effects of sex
resulted in apparent male predominance in SBI in our population.
Therefore, modification of the lifestyle risk factors would prevent SBI
particularly in men and even in women with personal habits such
as alcohol consumption and cigarette smoking.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
We express special thanks to T Muto and K Yamamoto for their technical
assistance with the laboratory examinations and the MRI scanning, K Fukuda
for valuable advice on the relationship between alcohol and SBI and
N Kawahara-Ideno for registration of participants.
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