ORIGINAL ARTICLE

Age-dependent association between cigarette smoking on whitematter hyperintensities

Sung Hun Kim • Chang-Ho Yun • Seo-Young Lee •

Kyung-ho Choi • Min Bom Kim • Hee-Kwon Park

Received: 30 August 2010 / Accepted: 28 April 2011 / Published online: 12 May 2011

� Springer-Verlag 2011

Abstract Previous reports have shown that cigarette

smoking is associated with white matter hyperintensities

(WMHs). However, it remains unclear whether this is true

for all ages. We investigated the association between cig-

arette smoking, WMHs, and age. We retrospectively

reviewed charts from 595 patients, who presented as out-

patients from January 2007 to March 2010. Grading of

periventricular WMHs (PVWMHs) and the scores of deep

WMHs (DWMHs) was determined based on criteria

established by the Rotterdam Scan Study. We compared

the degree of WMHs between smokers and non-smokers,

and those younger than the age of 65 years versus those

above. In younger age group, smokers had higher grades of

PVWMHs and more microbleeds than non-smokers. In the

older age group, total burden of DWMHs was much greater

in smokers than nonsmokers. Multivariate regression

analysis showed that cigarette smoking was an independent

risk factor for PVWMHs in the younger age group and for

DWMHs in the older age group. The location of WMHs in

association with smoking seems to differ among age

groups. Age should be considered when interpreting the

effects of smoking on the brain.

Keywords Age � Periventricular � Smoking �White matter hyperintensities

Introduction

Cigarette smoking is a well-known risk factor for stroke

and myocardial infarction [1, 2]. Many studies show that

cigarette smoking is also associated with neurodegenera-

tive diseases such as Alzheimer’s and Parkinson’s disease

[3–5]. In elderly individuals, smoking was associated with

decrease in cerebral perfusion and reduced cerebral gray

matter volume [6, 7]. Some of the effects of smoking on the

cardiovascular or central nervous system are age-depen-

dent [8, 9]. However, the age-dependent effects of smoking

on the brain have not been fully elucidated.

White matter hyperintensities (WMHs) on brain mag-

netic resonance images (MRI) are reportedly related to

stroke, dementia [10], and hypertension [11]. WMHs and

microbleeds in the elderly individuals have been known to

reflect the severity of cerebral small vessel ischemia [12–

15]. Some population-based studies, with middle-aged and

older adults, report that chronic smoking is associated with

increased incidence of WMHs [11, 16–21], but other

investigators have observed an inverse correlation between

WMHs and smoking [16, 22, 23].

In this study, we investigated the possibility of cigarette

smoking affecting the brain in an age-dependent manner by

assessing the degree of WMHs and number of microbleeds

in smokers versus non-smokers.

Patients and methods

Participants and demographic findings

Between January 2007 and March 2010, we retrospectively

reviewed charts from a total of 701 patients who presented

as an outpatient and had a brain MRI. Exclusion criteria

S. H. Kim � S.-Y. Lee � K. Choi � M. B. Kim

Department of Neurology, Kangwon National University

Hospital, Chuncheon, South Korea

C.-H. Yun � H.-K. Park (&)

Department of Neurology, Inha University Hospital,

7-206, 3-Ga, Sinheung-Dong, Jung-gu,

Incheon 400-711, South Korea

e-mail: parkhkwon@gmail.com

123

Neurol Sci (2012) 33:45–51

DOI 10.1007/s10072-011-0617-1

were as follows: (1) incomplete or poor-quality MR ima-

ges; (2) insufficient evaluation of cardiovascular risk fac-

tors; (3) the history or brain images of medical disease

affecting WMHs, such as migraine, intracranial hemor-

rhage or territorial infarction and (4) insufficient history of

cigarette smoking. One hundred and six patients were

excluded due to lack of data or other criteria. Routine

laboratory work-up and brain MRIs (including gradient

echo images) for the remaining 595 subjects were

reviewed. A current smoker was defined as an individual

who smoked currently on a regular basis or during the last

5 years. A non-smoker was defined as an individual who

did not smoke for the last 5 years. We also interviewed the

patients to acquire information such as the age at which

they started smoking. Pack-years were calculated as:

[(number of cigarettes per day/20) 9 (duration of smoking

until present time in years)]. Additional cerebrovascular risk

factors were clarified through routine laboratory findings and

medical history [24]. The following risk factors were

assessed: hypertension, which was defined as a previous

history of blood pressure repeatedly above 140/90 mmHg at

intervals of C1 week or being on antihypertensives; hyper-

lipidemia, which was defined as repeated elevation of total

cholesterol (C221 mg/dl) or being on lipid-lowering medi-

cation and diabetes, which was defined as a fasting serum

glucose over 126 mg/dl or being on anti-diabetic medica-

tion. The amount and type of alcohol consumed over the

past year were also documented.

Radiological findings

All patients underwent MRI scans performed on a 1.5 T

superconducting magnet system (GE, Milwaukee, USA).

Whole images were obtained with 27 contiguous, 5 mm

axial slices per scan without an interslice gap, in accor-

dance with the previously described imaging protocol [25].

Two blinded neurologists (H-K. Park and S. H. Kim) rated

the WMHs on a consensus basis and evaluated the number

of microbleeds on gradient echo sequences. WMHs were

defined as hyperintense focal lesions on FLAIR sequences

and iso- or hypointense focal lesions on T1-weighted

sequences and scored according to the method described in

the previous article [26]. The periventricular white matter

hyperintensities (PVWMHs) were assessed and rated in the

three regions—frontal, band, and posterior horns. The sum

of these regional grades was used to calculate the peri-

ventricular (PV) grades, which ranged from 0 to 9. Deep

white matter hyperintensities (DWMHs) were rated by the

number and size on FLAIR images. The DWMH scores

were calculated by multiplying each lesion by a size-

dependent constant, as a quantitative measure of DWMHs

(Fig. 1) [26]. Microbleeds were defined as homogenous

round signal loss (B5 mm) on gradient echo scans [25].

Data analysis

Data were expressed as the number (%) or mean ± SD.

Fisher’s exact tests were used to analyze discontinuous

variables, and unpaired Student’s t tests were used to

analyze continuous variables. To analyze the association

between smoking and WMHs in the younger and older age

groups, the subjects were categorized into two groups by

median value of the age (65 years). To identify whether

smoking was an independent risk factor for DWMHs or

PVWMHs, variables with p values\0.05 were entered into

a multivariate binary regression model. All statistical

analyses were performed using SPSS 14.0 for Windows

(SPSS Inc., Chicago, IL).

Results

Out of a total 595 patients (347 men; mean age

63.5 ± 10.7 years), 336 suffered a lacunar infarct in the

past (Table 1). A total of 144 patients (24.2%) were

smokers. The mean pack-year (PY) of the smokers was

66.2 ± 52.1 PY, and the mean age at onset of smoking was

24.8 ± 9.6 years. Three hundred and eighty-three partici-

pants had a history of hypertension, and 139 had a history

of diabetes mellitus. The mean values of HbA1c and total

cholesterol were 6.08% and 178.3 mg/dl, respectively. The

mean values of total DWMHs scores, PVWMH grades, and

the number of microbleeds were 1.56 ml, 1.50 and 1.11,

respectively. The male:female ratio was higher in smokers

than in non-smokers. Smokers were younger, and more

frequently had a history of diabetes, atrial fibrillation,

alcohol consumption, and lacunar infarction than non-

smokers (Table 1). The PVWMH grades, the total scores of

DWMHs and the number of microbleeds on MRI tended to

be greater in smokers than in non-smokers. Among

smokers, pack-years correlated with the PVWMH grades

(Pearson’s correlation r = 0.206, p = 0.01), even though

there was no association between this and DWMHs scores,

or the number of microbleeds. We were unable to find any

correlation between the first age of smoking and the total

burden of PVWMHs, DWMHs or number of microbleeds

(Pearson correlation: PVWMH grades, p = 0.95; DWMH

scores, p = 0.13; numbers of microbleeds, p = 0.83).

To determine the age-specific effects of cigarette

smoking on cerebral microvessels, we investigated the total

burden of PVWMHs, DWMHs and microbleeds, according

to the smoking status in younger (B64 years, n = 295) and

older (C65 years, n = 300) age groups. We found that

there was an age-dependent association between smoking

and either PVWMHs or DWMHs. In the younger group,

the PVWMH grades was much higher in smokers than in

non-smokers (p = 0.002), but there was no difference in

46 Neurol Sci (2012) 33:45–51

123

DWMH load between the two (p = 0.39, Table 2). In

the older age group, smokers had a larger burden of

DWMHs than non-smokers (p = 0.049), even though there

was no difference in PVWMH grades between smokers

and non-smokers (p = 0.58). Smokers tended to have more

microbleeds than non-smokers in either age group

(Table 2).

To identify whether there were any additional cardio-

vascular risk factors affecting WMHs, we compared the

prevalence of risk factors according to the burden of

PVWMs or DWMHs in both age groups (Table 3). We

found differences in the risk factors, related to PVWMHs

or DWMHs between the younger and older age groups. In

the younger age group, hypertension, hyperlipidemia, and

current smoking were more frequent in patients with

PVWMHs than those without, even though there was no

association of PVWMHs with the frequency of old age

(C57 years) men, diabetes mellitus, or lacunar infarction.

Larger scores of DWMHs (C0.27 ml) were more strongly

associated with advanced age (C57 years), and lacunae

than those with smaller scores. In the older age group, there

was no association between smoking and PVWMHs. The

subjects with higher grade of PVWMHs had the more

frequent history of advanced age (C71 years) and lacunae.

Hypertension and current smoking were also associated

with larger scores of DWMHs (C0.5 ml).

Fig. 1 Typical appearance of PVWMH (a) and DWMH (b) on

FLAIR scans. WMHs were defined as hyperintense focal lesions on

FLAIR sequences and iso- or hypointense focal lesions on T1-

weighted sequences. PVWMHs were assessed and rated in three

regions. The sum of these regional grades was used for the PVWMH

grades and ranged from 0 to 9. DWMH were rated by number and size

and the DWMH scores were added as a quantitative measure of

DWMH by multiplying each lesion by a size-dependent constant

Table 1 Baseline patient characteristics

Characteristics Total (n = 595) Smoker (n = 144) Non-smoker (n = 451) p value

Age*, years ± SD 63.5 ± 10.7 61.1 ± 10.5 64.3 ± 10.7 0.002

Male gender, n (%) 347 (58.3) 133 (92.4) 214 (47.5) \0.001

Medical history

Hypertension, n (%) 383 (64.4) 101 (70.1) 282 (62.5) 0.110

Diabetes mellitus, n (%) 139 (23.4) 45 (31.3) 94 (20.8) 0.013

Hyperlipidemia, n (%) 160 (26.9) 41 (28.5) 119 (26.4) 0.666

Atrial fibrillation, n (%) 95 (16.0) 61 (42.4) 34 (7.5) \0.001

Alcohol consumption, n (%) 130 (21.8) 59 (41.0) 71 (15.7) \0.001

Lacunar infarction, n (%) 336 (56.5) 102 (70.8) 234 (51.9) \0.001

Laboratory findings*

WBC count, /mm3 5,324 ± 1,850 5,575 ± 2,043 5,244 ± 1,780 0.082

HbA1c, % 6.08 ± 0.86 6.21 ± 0.98 6.03 ± 0.81 0.045

T. cholesterol, mg/dl 178.3 ± 35.6 180.6 ± 35.7 177.5 ± 35.6 0.373

Neuroradiologic findings*

Grade of PVWMH, grade ± SD 1.50 ± 1.71 1.85 ± 1.94 1.39 ± 1.61 0.011

Total scores of DWMH, ml ± SD 1.56 ± 2.85 1.94 ± 2.81 1.43 ± 2.85 0.062

Total number of microbleeds, n ± SD 1.11 ± 3.27 1.86 ± 4.64 0.87 ± 2.66 0.015

DWMH deep white matter hyperintensities, PVWMH periventricular white matter hyperintensities

Statistical significant differences were determined by Fisher’s exact test (categorical values) or Student’s t test (continuous values, marked as *)

Neurol Sci (2012) 33:45–51 47

123

We investigated whether smoking was an independent

risk factor for PVWMHs in the younger and DWMHs in

the older age groups. After adjusting for advanced age,

hypertension, hyperlipidemia and lacunar infarction,

current smoking was an independent risk factor for

PVWMHs in the younger age group (OR = 2.13; 95%

CI 1.21–3.72; p = 0.008). In the older age group,

smoking was not associated with PVWMHs indepen-

dently. However, multivariate analysis showed that a

history of smoking was independently associated with a

larger burden of DWMHs (OR = 2.43; 95% CI 1.30–

4.54; p = 0.005) (Table 4).

Discussion

In this study, we found an overall association between

cigarette smoking and PVWMHs. Age-based stratification

showed that smoking was associated with PVWMHs, but

not with DVWMHs, in the younger age group. In the older

Table 2 Clinical characteristics and radiological findings according to age

Younger group (B64 years), (n = 295) Older group (C65 years), (n = 300)

Smoker

(n = 87)

Non-smoker

(n = 208)

p value Smoker

(n = 57)

Non-smoker

(n = 243)

p value

Grades of PVWMH, grade ± SD 1.92 ± 2.06 1.14 ± 1.60 0.002 1.74 ± 1.76 1.60 ± 1.59 0.582

Total scores of DWMH, cc ± SD 1.78 ± 2.95 1.47 ± 2.82 0.390 2.18 ± 2.61 1.40 ± 2.88 0.049

Number of microbleeds, n ± SD 1.80 ± 4.69 0.66 ± 2.53 0.034 1.95 ± 4.61 1.04 ± 2.75 0.054

DWMH deep white matter hyperintensities, PVWMH periventricular white matter hyperintensities

Statistical significances of differences were analyzed by Student’s t tests

Table 3 Clinical characteristics and WMHS according to age groups

Characteristics Total

(n = 295)

Lower grades

of PVWMH (=0)

(n = 139)

Higher grades

of PVWMH (C1)

(n = 156)

p value Smaller scores

of DWMH

(\0.27 cc)

(n = 148)

Larger scores

of DWMH

(C0.27 cc)

(n = 147)

p value

Younger group (B64 years)

Age*, years ± SD 55.3 ± 8.3 54.9 ± 8.4 55.7 ± 8.2 0.39 54.2 ± 8.6 56.4 ± 7.9 0.02

Male gender, n (%) 165 (55.9) 70 (50.4) 95 (60.9) 0.08 79 (53.4) 86 (58.5) 0.41

Hypertension, n (%) 160 (54.2) 63 (45.3) 97 (62.2) 0.005 69 (46.6) 91 (61.9) 0.10

Diabetes mellitus, n (%) 69 (23.4) 35 (25.2) 34 (21.8) 0.50 35 (23.6) 34 (23.1) 1.00

Hyperlipidemia, n (%) 70 (23.7) 25 (18.0) 45 (28.8) 0.04 38 (25.7) 32 (21.8) 0.49

Lacunar infarction, n (%) 165 (55.9) 70 (50.4) 95 (60.9) 0.08 72 (48.6) 93 (63.3) 0.01

Current smoking, n (%) 87 (29.5) 28 (20.1) 59 (37.8) 0.001 36 (24.3) 51 (34.7) 0.06

Characteristics Total

(n = 300)

Lower grades

of PVWMH (B1)

(n = 163)

Higher grades

of PVWMH (C2)

(n = 137)

p value Smaller scores

of DWMH

(\0.5 cc)

(n = 147)

Larger scores

of DWMH

(C0.5 cc)

(n = 153)

p value

Older group (C65 years)

Age*, years ± SD 71.6 ± 5.2 70.8 ± 4.8 72.6 ± 5.5 0.003 71.1 ± 4.8 72.2 ± 5.4 0.07

Male gender, n (%) 182 (60.7) 99 (60.7) 83 (60.6) 1.00 86 (58.5) 96 (62.7) 0.48

Hypertension, n (%) 223 (74.3) 115 (70.6) 108 (78.8) 0.11 98 (66.7) 125 (81.7) 0.004

Diabetes mellitus, n (%) 70 (23.3) 32 (19.6) 38 (27.7) 0.10 31 (21.1) 39 (25.5) 0.41

Hyperlipidemia, n (%) 90 (30.0) 44 (27.0) 46 (33.6) 0.26 43 (29.3) 47 (30.7) 0.80

Lacunar infarction, n (%) 171 (57.0) 82 (50.3) 89 (65.0) 0.01 80 (54.4) 91 (59.5) 0.42

Current smoking, n (%) 57 (19.0) 26 (16.0) 31 (22.6) 0.18 18 (12.2) 39 (25.5) 0.005

DWMH deep white matter hyperintensities, PVWMH periventricular white matter hyperintensities

Statistical significant differences were determined by Fisher’s exact test (categorical values) or Student’s t test (continuous values, marked as *)

48 Neurol Sci (2012) 33:45–51

123

group, smokers had a greater burden of DWMHs than non-

smokers.

Previous studies revealed that cigarettes contain various

compounds, such as nicotine, and the effects of smoking on

the central nervous system are various and complex [27].

Cigarette smoking has been shown to be associated with

cardiovascular diseases, stroke and neurodegenerative

diseases, although the relationship between smoking and

neurodegeneration was controversial [8, 9]. It is interesting

to note that the effects of smoking in humans were affected

by age. For example, smoking causes marked tachycardia

and suppression of central sympathetic outflow in young

individuals, whereas in middle-aged subjects sympathetic

vasoconstrictor activity is not suppressed even though

tachycardia occurs to a lesser degree [8]. Cigarette smoking

is protective in younger individuals with Parkinson’s dis-

ease but not in the elderly individuals [9].

Smoking is also a well-known risk factor for WMHs

[11, 17–23]. Cytotoxic cell edema secondary to nicotine-

induced osmotic imbalance and vasogenic edema has been

suggested as a possible mechanism of increased WMHs in

smokers [28]. In elderly individuals, chronic exposure to

smoking is related to low cerebral blood flow [6], which

may be a potential mechanism underlying the association

between smoking and WMH burden. Nicotine has been

shown to evoke age-dependent changes in gene expression

in white matter microstructures of rat brains [29, 30].

However, some previous authors showed an inverse asso-

ciation between smoking and the presence of WMHs [22,

23]. Previous clinical studies did not consider the location

and quantity of WMHs or age-based stratification for

smoking effect. Here, we compared the effects of cigarette

smoking on PVWMHs and DWMHS in younger and older

age groups and found that effects of smoking on WMHs

differed among the young and the elderly individuals. We

thought that the age-dependent effects of smoking on brain

and the different age distribution of study population might

cause the discrepancy in the results among the previous

clinical studies [18, 20, 22, 23].

DWMHs are known to be mainly associated with cere-

brovascular disease [11]. We discovered that there was a

clear association between DWMHs and smoking individuals

over the age of 65 years, which implies that smoking might

increase the risk of stroke in the elderly individuals. Previous

studies have shown that PVWMHs are more frequently

observed in patients with neurodegenerative disorders, such

as Parkinson’s disease, and associated with memory and gait

disturbance [31], even though the pathology and mecha-

nisms underlying PVWMHs and DWMHs still remain

unclear [32, 33]. Recent studies reported that small vessel

changes could be due to abnormal venous drainage, hence

lead to WMHs [34, 35]. The periventricular and subcortical

areas differ in venous drainage systems [35], which might

explain the differences in mechanisms of the two. Our results

showed that smoking was also associated with an increase in

PVWMHs in the younger age group. This fact indicated that

the smoking may accelerate aging of the brain in our younger

age population.

The association between cholesterol and WMHs has

also been controversial. Some reports have indicated that

subjects with WMH had lower levels of cholesterol than

those without WMHs, even though others showed that

increased cholesterol levels were associated with WMHs

[36–38]. Our study revealed that hyperlipidemia tended to

Table 4 Multivariate analysis

DWMH deep white matter

hyperintensities, PVWMHperiventricular white matter

hyperintensities

Statistical significant

differences were determined by

multiple binary regression tests

Characteristics PVWMH grades (C1) DWMH (C0.27 cc)

OR (95% CI) p value OR (95% CI) p value

Younger group (B64 years)

Age (C57 years) 1.14 (0.70–1.85) 0.61 2.18 (1.33–3.55) 0.002

Hypertension 1.83 (1.13–2.97) 0.01 1.57 (0.97–2.55) 0.07

Hyperlipidemia 1.69 (0.95–3.01) 0.08 0.65 (0.37–1.15) 0.14

Lacunar infarction 1.14 (0.69–1.89) 0.60 1.64 (0.99–2.73) 0.05

Current smoking 2.13 (1.21–3.72) 0.008 1.50 (0.86–2.61) 0.15

Characteristics PVWMH grades (C2) DWMH (C0.50 cc)

OR (95% CI) p value OR (95% CI) p value

Older group (C65 years)

Age (C71 years) 1.74 (1.08–2.79) 0.02 1.52 (0.95–2.43) 0.08

Hypertension 1.34 (0.77–2.31) 0.30 2.07 (1.19–3.58) 0.01

Hyperlipidemia 1.30 (0.78–2.18) 0.31 1.04 (0.62–1.74) 0.88

Lacunar infarction 1.79 (1.11–2.89) 0.02 1.12 (0.69–1.80) 0.66

Current smoking 1.61 (0.89–2.93) 0.12 2.43 (1.30–4.54) 0.005

Neurol Sci (2012) 33:45–51 49

123

be associated with PVWMHs in the younger age group and

had an age-dependent effect on white matter, which might

have made it difficult to delineate any association between

cholesterol and WMHs in the previous studies [36–38].

This result suggests that an age-dependent effect of

hyperlipidemia on human white matter is also plausible. It

does not seem to happen unfrequently that the white matter

changes evoked by some factors might differ according to

age and the location of white matter.

Previous studies have shown that microbleeds located in

the deep white matter or infratentorial areas were associ-

ated with smoking and WMHs [39]. We found that

smoking was associated with microbleeds only in the

younger group. The association between microbleeds and

smoking was stronger in younger than in older individuals,

and the age-dependent pattern of microbleeds was quite

similar to that of PVWMHs, but not of DWMHs. This

suggested that smoking might have a similar effect on

PVWMHs and microbleeds, but different on DWMHs.

Individuals may exhibit an age-dependent susceptibility to

smoking, which could lead to periventricular white matter

lesions or microbleeds in young smokers and deep white

matter changes in older individuals.

There was also a correlation between PVWMHs and

pack-years of smoking, but not between DWMHs and

pack-years of smoking. Age at the onset of smoking was

not associated with DWMHs or PVWMHs. This implied

that smoking, regardless of the amount, plays an important

role in the development of DWMHs, even though both the

amount and history of smoking contributed to the devel-

opment of PVWMHs.

This study has some limitations. First, this was the ret-

rospective study and we could not exclude the possibility that

selection bias due to the overall premature death of smokers

might cause an age-dependent difference in WMH distri-

bution in smokers, which was believed to result in the inverse

association between smoking and Alzheimer’s disease [5].

The large number of recruited stroke patients also might lead

to a selection bias. To avoid this bias, the history of stroke

was adjusted in the multivariate analysis. Second, the fre-

quency and severity of PVWMH and DWMH increase pro-

gressively with the age [40], and therefore the decision to

categorize the patients into two groups based on median age

(65 years) might be controversial. Age of 65 years is sig-

nificant in cerebrovascular disease, because nearly three

quarters of all strokes occur over the age of 65 years and the

stroke of the patients younger than 65 years was considered

as young age stroke [41]. However, to confirm such age-

related effects of smoking on the cerebral white matter and

the true discrimination threshold age, a large prospective

study including patients recruited from the general popula-

tion should be performed.

Conclusion

To our knowledge, our study was the first to investigate the

age-dependent effects of smoking on WMHs. We maintain

that the cigarette smoking affects the brain in an age-

dependent manner. Such findings can assist the interpre-

tation of WMHs and cardiovascular risk factors in a

clinical setting.

Acknowledgments This work was supported by INHA UNIVER-

SITY Research Grant (INHA-42157-01).

Conflict of interest The authors report no conflicts of interest.

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