Body Fat Distribution and Long-Term Risk of
Stroke Mortality
David Tanne, MD; Jack H. Medalie, MD; Uri Goldbourt, PhD
Downloaded from http://stroke.ahajournals.org/ by guest on June 16, 2017
Background and Purpose—Excess weight is an important determinant of cardiovascular disease, but the relationship
between excess weight, its distribution, and stroke is yet unclear. We examined in a large prospective cohort study the
association between body fat distribution and stroke mortality among middle-aged men.
Methods—A cohort of male civil servants and municipal employees free of cardiovascular disease in Israel (n⫽9151) were
followed up for mortality over 23 years. The subscapular skinfold (SSF) was used as a measure of trunk and overall
obesity and the ratio of subscapular to triceps skinfold thickness (SFR) as an indicator of trunk versus peripheral
distribution of body fat.
Results—During the follow-up period, 316 died of stroke, and 865 died of coronary heart disease. The estimated
age-adjusted hazard ratios (HRs) for stroke mortality, associated with 1 SD increment of SSF, was 1.12 (95% CI, 1.01
to 1.25) and for body mass index, 1.17 (1.06 to 1.30), but these associations were markedly weakened when adjusting
for blood pressure. SFR was associated with an age-adjusted HR for stroke mortality of 1.14 (1.03 to 1.26). Further
adjusting for systolic blood pressure, diabetes mellitus, cigarette smoking, and socioeconomic status (HR, 1.11; 1.01 to
1.23) as well as body mass index (HR, 1.11; 1.00 to 1.23) only mildly attenuated this association. Subjects with SFR
in the upper quartile exhibited a ⬇1.5-fold higher adjusted HR (1.53; 1.10 to 2.12) compared with the lowest quartile.
Conclusion—Indices of body fat and body fat distribution predict long-term stroke and coronary heart disease mortality
among middle-aged men. SFR, an indicator of trunk versus peripheral distribution of body fat, is associated with stroke
mortality, independent of main mediators of the effect of obesity on health and of body mass index. (Stroke. 2005;36:
1021-1025.)
Key Words: body composition 䡲 coronary heart disease 䡲 obesity 䡲 stroke
E
xcess weight is an important determinant of cardiovascular disease.1,2 Several investigators have found that
overweight men, defined on the basis of high body mass
index (BMI), have a greater risk of developing stroke than
subjects with normal levels of total body fatness,3,4 but other
investigators did not find such an association.5,6 Indeed, some
persons with increased BMI may have a normal amount of
body fat and a large muscle mass, whereas others may have
excess adiposity and reduced muscle mass. Therefore, it has
become apparent that the relationship between obesity and
cardiovascular disease depends not only on the amount of
body fat but also on its distribution. Individuals with increased fat accumulation in the abdominal region, indicated
by high waist-to-hip ratio, often have atherogenic lipid
profiles and were found to be at an increased stroke risk.6,7
The Israeli Ischemic Heart Disease (IIHD) project was a
longitudinal investigation of cardiovascular disease among
⬇10 000 male civil servants and municipal employees in
Israel.8,9 This cohort provided a wide range of occupations
and socioeconomic levels in the male working population of
Israel at the time of inclusion. Subjects underwent extensive
appraisal of health and were followed for mortality over a
long period of time. Skinfold thickness was measured at
baseline and enabled estimation of body fat distribution.
Thus, the subscapular skinfold (SSF) was used as a measure
of trunk and overall obesity, whereas the ratio of subscapular
to triceps skinfold thickness (SFR) as an indicator of trunk
versus peripheral distribution of body fat. The present investigation deals with the prediction of stroke mortality over a
long-term follow-up by body fat distribution among subjects
free of known cardiovascular disease at baseline.
Subjects and Methods
Study Participants
Participants of the IIHD project were chosen by stratified sampling
of male civil servants and municipal employees based on an age ⱖ40
years on inclusion, place of work confined to the 3 largest urban
areas in Israel (Tel-Aviv, Jerusalem, and Haifa), and sampling
Received September 10, 2004; final revision received December 24, 2004; accepted February 14, 2005.
From the Department of Epidemiology and Preventive Medicine (D.T., U.G.), Sackler School of Medicine, Tel-Aviv University, Israel; Stroke Center
(D.T.), Department of Neurology, Chaim Sheba Medical Center, Tel Hashomer, Israel; Department of Family Medicine (J.H.M.), Case Western Reserve
University, Cleveland, Ohio; and Neufeld Cardiac Research Institute (U.G.), Chaim Sheba Medical Center, Tel Hashomer, Israel.
Correspondence to David Tanne, MD, Department of Neurology, Chaim Sheba Medical Center, Tel-Hashomer 52621, Israel. E-mail
[email protected]
© 2005 American Heart Association, Inc.
Stroke is available at http://www.strokeaha.org
DOI: 10.1161/01.STR.0000162584.39366.1c
1021
1022
Stroke
May 2005
TABLE 1. BMI, Body Fat Distribution, and Age-Adjusted Mortality by Area of Birth*
Age-Adjusted
Stroke Mortality,
%
Age-Adjusted
CHD Mortality,
%
BMI,
kg/m2
SSF,
mm
SFR
Middle East
24.9 (3.6)
18.9 (8.9)
1.66 (0.74)
3.95
8.09
North Africa
25.9 (3.8)
19.6 (9.1)
1.63 (0.73)
4.40
8.71
Eastern Europe
25.8 (2.9)
18.5 (7.7)
1.70 (0.80)
3.24
9.90
Central Europe
25.5 (2.9)
18.2 (7.6)
1.54 (0.72)
2.71
10.11
Southern Europe
25.9 (3.1)
18.3 (7.8)
1.53 (0.71)
2.98
10.76
Israel
26.1 (3.5)
20.9 (8.4)
1.64 (0.67)
3.80
10.35
*Data are given as mean (SD) unless otherwise specified.
Downloaded from http://stroke.ahajournals.org/ by guest on June 16, 2017
fractions aimed at obtaining numbers of study subjects from 6 areas
of birth (central Europe, eastern Europe, the Balkan countries, the
Middle East, northern Africa, and Israel), approximately proportional to the Israeli male population of this age. The percentage
consenting to participate among eligible subjects and undergoing the
baseline examination was 86%. Participants underwent clinical and
blood biochemical evaluations in 1963, 1965, and 1968, as detailed
previously.8,9 Subjects with either a history of myocardial infarction
or those whose chest pain status was summarized as “definite” or
“possible” angina pectoris according to the IIHD study protocol were
excluded from this analysis.
Body Fat Assessments
For calculating BMI, height was measured (without shoes) to the
nearest centimeter and weight to the nearest kilogram with subjects
wearing trousers only. Skinfold thickness was measured in millimeter using a Lange skinfold caliper. SSF was measured at the inferior
angle of the scapula, and the triceps skinfold was measured posteriorly at the halfway point between the outer edge of the acromion
process and the olecranon process of the ulna. SSF was used as a
measure of trunk and overall obesity and SFR as an indicator of trunk
versus peripheral distribution of body fat.
Cause of Death Determination
The underlying cause of death was documented on the basis of
case-by-case determination by a review panel through mid-1970 and
by the use of the International Classification of Diseases (ICD) codes
7, 8, and 9 thereafter. Deaths from cerebrovascular disease were
based on ICD-9 codes 430 to 438 and those from coronary heart
disease (CHD) by codes 410 to 414 and 798. For the earlier
(pre-1971) deaths, comparison of death certificates with the analyses
of hospital records by the panel yielded a 90% agreement. Information on mortality after 1970 was derived from the Israeli Mortality
Registry.
Statistical Analysis
Analyses of the association between BMI and body fat distribution
and the end points of stroke and CHD mortality were performed
adjusted for traditional risk factors and potential confounders.
Adjusted hazards were estimated using the proportional hazard
model by Cox.10 The appropriateness of the proportional hazards
assumption was examined by observing Schoenfeld’s residuals.
Adjusted hazard ratios (HRs) and 95% CIs are presented. Stata 7.0
software was used for the multivariate analysis of fatal stroke
incidence over 23 years.11
Results
Skinfold thickness was measured in 8638 of the 9151
participants free of cardiovascular disease at baseline (94%),
of whom 316 died of stroke and 865 died of CHD during the
23-year follow-up. The mean BMI, SSF, and SFR in our
cohort were 25.6⫾3.3 kg/m 2 , 19.0⫾8.3 mm, and
1.62⫾0.74 mm, respectively. The distribution of these indi-
ces by area of birth are shown in Table 1. Main risk factors
for stroke by quartiles of BMI, SSF, and SFR are presented in
Table 2. With increasing quartiles of BMI and central fat
distribution, subjects tended to be somewhat older, to have
higher blood pressure, more diabetes mellitus, and lower
proportions of HDL out of total cholesterol, and fewer of
them smoked.
Mortality by BMI and Body Fat Distribution
The crude rates of death from stroke and CHD by BMI are
summarized in Table 3. Rates of stroke mortality per 10 000
person years of follow-up rose by increasing quartiles of BMI
from 15.7 to 17.5, 17.3, and 21.9. Four percent of our cohort
was very lean (BMI ⬍20 kg/m2), 37% had a BMI of 20 to
24.9 kg/m2, 49% a BMI of 25 to 29.9 kg/m2, and 9% were
obese (BMI ⬎30 kg/m2). Rates of stroke mortality by these
categories ranged between 9.3 and 22.8 per 10 000 person
years of follow-up.
The crude rates of death from stroke and CHD by indices
of body fat distribution are summarized in Table 4. Rates of
stroke mortality per 10 000 person years of follow-up range
across quartiles of SSF between 15.1 to 15.4, 16.2 up to 20.6,
and across quartiles of SFR from 13.4 to 15.8, 14.7, and up to
22.3, respectively.
Multivariate Analysis
Adjusted HRs for dying from stroke and for dying from CHD
(per 1 SD change) are shown in Table 5. Results of hazards
adjusted for age (model A), for age and systolic blood
pressure (model B) and for age, systolic blood pressure,
diabetes mellitus, smoking, and socioeconomic status (model
C) are provided. The analysis of the association of SFR with
incident fatal stroke is also shown incorporating adjustment
for BMI (model D). Using proportional hazards, the ageadjusted HR associated with 1 SD increment of BMI was 1.17
(95% CI, 1.06 to 1.30) and for SSF, 1.12 (95% CI, 1.01 to
1.25). These associations were weakened when systolic or
diastolic blood pressure, mediators of the effect of obesity on
health, were also included in the model. A 1 SD increment of
SFR was associated with an age-adjusted HR for stroke
mortality of 1.14 (95% CI, 1.03 to 1.26). Further adjustment
for systolic blood pressure, diabetes, cigarette smoking, and
socioeconomic status (HR, 1.11; 95% CI, 1.01 to 1.23) only
mildly attenuated this association. Further adjustment for
baseline BMI did not change this association. Subjects with
SFR in the upper quartile exhibited a ⬇1.5-fold higher HR
Tanne et al
TABLE 2.
Body Fat Distribution and Stroke Mortality
1023
Risk Factors for Stroke by Quartiles of Indices of BMI and Body Fat Distribution*
Age, y
SBP, mm Hg
DBP, mm Hg
%HDL
Smokers
(%)
Diabetes Mellitus
(%)
BMI, kg/m2
I
⬍23.37
48.5 (6.8)
129.1 (18.8)
79.6 (9.9)
21.0 (6.3)
1374 (61.1)
72 (3.2)
II
23.37–25.59
49.2 (6.8)
133.7 (19.6)
83.0 (10.2)
18.3 (5.5)
1142 (49.8)
98 (4.3)
III
25.60–27.74
49.1 (6.8)
135.8 (19.5)
84.5 (10.7)
17.3 (5.5)
1055 (45.8)
92 (4.0)
IV
⬎27.74
49.3 (6.6)
139.8 (21.3)
87.4 (11.6)
16.5 (5.0)
1110 (48.3)
150 (6.5)
I
⬍13
48.5 (6.8)
129.9 (18.7)
80.3 (9.9)
20.7 (6.3)
1308 (60.0)
57 (2.6)
II
13–18
49.0 (6.7)
134.4 (19.8)
83.5 (10.5)
18.3 (5.8)
1259 (50.0)
105 (4.2)
III
19–24
49.1 (6.8)
135.9 (20.3)
84.7 (11.2)
17.3 (5.2)
945 (45.9)
89 (4.3)
IV
⬎24
49.2 (6.7)
138.6 (20.8)
86.1 (11.4)
16.7 (4.9)
1023 (47.8)
150 (7.0)
I
⬍1.12
48.4 (6.7)
133.0 (18.8)
82.6 (10.1)
19.0 (6.1)
1097 (52.2)
55 (2.6)
II
1.12–1.46
48.8 (6.7)
134.4 (20.5)
83.3 (11.0)
18.2 (5.8)
1131 (51.3)
89 (4.0)
III
1.47–1.95
48.9 (6.8)
134.2 (19.8)
83.8 (11.1)
17.9 (5.6)
1116 (51.8)
101 (4.7)
IV
⬎1.95
49.6 (6.8)
137.2 (21.0)
84.8 (11.4)
17.6 (5.4)
1029 (47.7)
147 (6.8)
SSF, mm
SFR
Downloaded from http://stroke.ahajournals.org/ by guest on June 16, 2017
SBP indicates systolic blood pressure; DBP, diastolic blood pressure; %HDL, percentage of total serum cholesterol contained in
high-density lipoprotein.
*Data for continuous variables are given as mean (SD) and for categorical variables as No. (%).
compared with the lowest quartile (1.53; 95% CI, 1.10 to
2.12), adjusting for age, smoking, and socioeconomic status
(Figure). Evidently, this ratio declines as weight-determined
factors such as blood pressure and diabetes are also adjusted
for (to 1.31).
Discussion
This article reports 1 of the few long-term longitudinal studies of
central obesity and the subsequent development of stroke mortality, controlling for baseline BMI. In this cohort of middleaged men free of cardiovascular disease at baseline, SFR, an
indicator of trunk versus peripheral distribution of body fat, is an
independent predictor of long-term stroke mortality.
Several studies have shown an association of obesity, as
defined by BMI, with the risk of stroke. In the Physicians’
Health Study, increasing BMI was associated with a steady
increase in the risks of total, ischemic, and hemorrhagic stroke.
Although accounted for mostly by concomitant hypertension
TABLE 3.
and diabetes, a significant increase remained after adjustment for
these potential biological mediators.3 The Honolulu Heart Program reported that BMI was associated with increased risk of
thromboembolic stroke among nonsmoking men in older middle
age.4 In contrast, other studies have failed to find an independent
relationship between obesity measured by BMI and increased
risk of stroke in men.5,6
Over the last 4 decades, the prevalence of obesity (BMI
ⱖ30 kg/m2) has increased in the United States from 13% to
31%, and the prevalence of overweight (a BMI of 25 to 29.9
kg/m2) has increased from 31% to 34%.12 Increase in the
prevalence of obesity was also observed over the years
among middle-aged men in Israel.13 The working middleaged men in our cohort, recruited in Israel in the mid-1960s,
indeed included a low proportion of obese men.
The effects of obesity on cardiovascular health and disease
are numerous, hypertension being one of the most profound.
A weakening of associations between BMI with stroke
BMI and 23-Year Fatal CHD and Stroke Rates*
No. of Deaths
Crude Rates (95% CI)
Person Years
of Follow-Up
CHD
Stroke
45 986
47 096
46 807
45 656
156
214
227
268
65
81
75
95
33.9
45.4
48.5
58.7
(29.0–39.7)
(39.7–52.0)
(42.6–55.2)
(52.1–66.2)
15.7
17.5
17.3
21.9
(12.5–19.6)
(14.2–21.6)
(14.0–21.3)
(18.2–26.4)
24
286
203
240
112
8
116
67
87
38
27.8
40.3
45.7
54.1
67.2
(18.6–41.5)
(35.9–45.2)
(38.4–51.8)
(47.7–61.3)
(55.8–80.9)
9.3
16.4
14.9
19.0
22.8
(4.6–18.5)
(13.6–19.6)
(11.7–19.0)
(18.9–24.2)
(16.6–31.3)
CHD
Stroke
Quartiles of BMI
I
II
III
IV
Categories of BMI, kg/m2
⬍20
20–24.9
25–26.9
27–29.9
⬎30
8637
70 933
44 950
44 359
10 666
*Rates per 10 000 person years of follow-up.
1024
Stroke
May 2005
TABLE 4.
Indices of Body Fat and 23-Year Fatal CHD and Stroke Rates*
No. of Deaths
Person Years
of Follow-Up
Crude Rates (95% CI)
CHD
Stroke
CHD
Stroke
44 369
51 225
41 859
43 170
159
238
209
232
67
79
68
89
35.8
46.5
49.9
53.7
(30.7–41.9)
(40.9–52.8)
(43.6–57.2)
(47.3–61.1)
15.1
15.4
16.2
20.6
(11.9–19.2)
(12.4–19.2)
(12.8–20.6)
(16.7–25.4)
43 147
44 880
44 085
43 136
168
205
209
234
58
71
65
96
38.9
45.6
47.4
54.2
(33.4–45.3)
(39.8–52.4)
(41.4–54.3)
(47.7–61.7)
13.4
15.8
14.7
22.3
(10.4–17.4)
(12.5–20.0)
(11.6–18.8)
(18.2–27.2)
Quartiles of SSF
I
II
III
IV
Quartiles of SFR
I
II
III
IV
*Rates per 10 000 person years of follow-up.
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mortality and between SSF, an indicator of trunk obesity, and
stroke mortality when blood pressure was adjusted for may
indicate the role of the latter in mediating long-term health
hazards among overweight men. If we regard blood pressure
as well as diabetes as mediators rather than confounders of
the association between obesity and clinical outcome, we
consider adjustment to these weight-determined factors as
potential overadjustment, and therefore present the HRs
without these mediators as the findings of main significance.
Individuals with increased fat accumulation in the abdominal region often have atherogenic lipid profiles and are at
increased cardiovascular risk. The Health Professionals
Follow-Up Study showed that the highest quintile of waistto-hip ratio was associated with an increased risk of stroke
among men but did not ascertain the mediating effect of
hypertension, diabetes, and hyperlipidemia.6 In a case-control
study from the Northern Manhattan Stroke Study, abdominal
obesity was an independent, potent risk factor for ischemic
stroke and a stronger risk factor than BMI.7 In the National
Health and Nutrition Examination Survey (NHANES) I
Epidemiological Follow-up Study, higher SFR was associated with a mildly but significantly increased incidence of
stroke but only in white male former smokers, with a 1.4-fold
increased risk in those with SFR in the upper compared with
the lower quartile.14 In middle-aged Finnish men, SSF was
positively associated with stroke incidence (odds ratio, 1.6;
95% CI, 1.3 to 2.0, per 1 SD difference), independent of BMI
and other variables, including plasma insulin.15
TABLE 5.
There is a strong link between obesity and a generalized
metabolic disorder of which insulin resistance is an indicator.
Gavrila et al found that in addition to overall obesity, central fat
distribution is an independent negative predictor of serum
adiponectin and suggest that adiponectin may represent a link
between central obesity and insulin resistance.16 Abdominal
adipose tissue accumulations are the critical correlates of elevated plasma C-reactive protein levels found in men with
atherogenic dyslipidemia of the insulin resistance syndrome.17
There are different methods to assess body fat distribution.
SFR likely measures a somewhat different aspect of relative
body fat distribution than other measures such as waist
circumference or waist-to-hip ratio.18 SSF measures subcutaneous trunk fat, a somewhat different aspect of absolute trunk
body fat than indicators such as waist girth, which measures
subcutaneous and intra-abdominal fat, or intra-abdominal fat
on computerized tomographic scanning for visceral fat. Unlike the girth or radiographic measures, skinfolds do not
directly reflect visceral fat. However, reported associations
with incidence of hypertension have been similar.19 Skinfolds
should not be affected by changes in lean body mass with
aging. Although not an optimal measure for clinical settings,
the advantages of skinfold thickness are long-established
standardized methods with wide availability in data sets from
large population surveys, thus offering a useful opportunity to
researchers and interested clinicians. Elevated SFR might be
a marker for a state characterized by increased trunk and
visceral fat, leading to insulin resistance and increased plasma
insulin levels with resulting dyslipidemia, glucose intoler-
Adjusted HRs for Dying From CHD and Stroke by BMI, Trunk Obesity, and Body Fat Distribution*
BMI
SSF
SFR
CHD
Stroke
CHD
Stroke
CHD
Stroke
HR (95% CI)
HR (95% CI)
HR (95% CI)
HR (95% CI)
HR (95% CI)
HR (95% CI)
Model A
1.20 (1.13–1.27)
1.17 (1.06–1.30)
1.13 (1.06–1.20)
1.12 (1.01–1.25)
1.08 (1.02–1.16)
1.14 (1.03–1.26)
Model B
1.12 (1.05–1.20)
1.07 (0.96–1.20)
1.06 (1.00–1.13)
1.04 (0.93–1.16)
1.05 (0.99–1.12)
1.09 (0.99–1.22)
Model C
1.11 (1.04–1.17)
1.05 (0.94–1.17)
1.06 (0.99–1.13)
1.04 (0.93–1.16)
1.05 (0.98–1.12)
1.11 (1.01–1.23)
Model D
...
...
...
...
...
1.11 (1.00–1.23)
*Per 1 SD of change.
Model A adjusted for age; model B adjusted in addition for systolic blood pressure; model C adjusted in addition for diabetes
mellitus, smoking, and socioeconomic status; model D adjusted in addition for BMI.
Tanne et al
Body Fat Distribution and Stroke Mortality
1025
of SFR and incident fatal stroke that is little affected by
confounders or mediators, support or disagreement of such a
hypothesis would require examination of the association of
SFR with long-term outcome in other prospective cohort
studies.
References
Downloaded from http://stroke.ahajournals.org/ by guest on June 16, 2017
Bar graph of HRs and SE for stroke mortality by quartiles of
SSF to SFR adjusted for age, smoking, socioeconomic status,
and area of birth. Information is based on 8576 subjects and
286 stroke deaths. HR for the lower quartile is defined as 1.
ance, and hypertension that may contribute to development of
arteriosclerosis and stroke.
Study limitations included the fact that only middle-aged
male participants were recruited in this cohort, precluding
examination of these relationships in women. However, the
included subjects resemble the nationwide distribution of
working middle-aged men in Israel at the time of inclusion.
Second, long-term mortality data were obtained from death
certificates, known for their potential inaccuracies, and the
autopsy rate in Israel is extremely low. However, mortality
data are available derived from the Israeli Mortality Registry,
for which nationwide information is virtually complete.
Third, no information was collected on stroke incidence, type,
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on a single assessment of skinfold thickness, known to be
prone to interobserver and intraobserver variability, and other
indices of abdominal obesity were not measured. Finally, as
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of follow up, we have no information concerning how the
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distribution of body fat, was found to be a predictor of
long-term stroke mortality among middle-aged men free of
cardiovascular disease at baseline, independent of baseline
BMI. Although our results are consistent with an association
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Body Fat Distribution and Long-Term Risk of Stroke Mortality
David Tanne, Jack H. Medalie and Uri Goldbourt
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Stroke. 2005;36:1021-1025; originally published online March 31, 2005;
doi: 10.1161/01.STR.0000162584.39366.1c
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