Journal of Gerontology: MEDICAL SCIENCES
Cite journal as: J Gerontol A Biol Sci Med Sci. 2011 September;66A(9):1022–1029
doi:10.1093/gerona/glr093
Published by Oxford University Press on behalf of The Gerontological Society of America.
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Advance Access published on June 8, 2011
Weight Loss and Low-Intensity Exercise for the Treatment
of Metabolic Syndrome in Obese Postmenopausal Women
Lyndon J. Joseph,1,2,* Ronald L. Prigeon,1,2,* Jacob B. Blumenthal,1,2 Alice S. Ryan,1,2 and
Andrew P. Goldberg1,2
1Division
of Gerontology and Geriatric Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore.
2Geriatric Research, Education, and Clinical Center, Baltimore Veterans Affairs Medical Center, Maryland.
*These two authors contributed equally to this work.
Address correspondence to Andrew P. Goldberg, MD, Baltimore Veterans Affairs Medical Center, Geriatric Research, Education, and Clinical Center,
BT/18/GR, 10 North Greene Street, Baltimore, MD 21201. Email: [email protected]
Background. The prevalence of the metabolic syndrome (MetSyn) approaches 50% in postmenopausal women. This
study examines the efficacy of lifestyle modification for the treatment of MetSyn and its associated risk for cardiovascular
disease and diabetes in this population.
Methods. This prospective controlled study examines the effects of a 6-month weight loss and low-intensity exercise
program (WL+LEX) on body composition (dual-energy X-ray absorptiometry and abdominal computed tomography
scans), fasting glucose and lipid levels, cytokines, and blood pressure in postmenopausal women with and without MetSyn.
Results. WL+LEX reduced body weight (MetSyn: −5% vs non-MetSyn: −7%) and fat mass (−11% vs −15%) and increased
VO2max (+2% vs +3%) in both MetSyn (N = 35) and non-MetSyn (N = 41) groups. Constituents of MetSyn decreased comparably in both groups. Fifteen (45%) MetSyn participants responded (R) by converting to non-MetSyn, 18 remained MetSyn
(NR), and 2 had missing data. Reduction in fat mass (−15% vs −8%, p = .02) was greater in R than NR, but there were
no between-group differences in changes in VO2max, cytokines, or other variables. The decrease in the number of MetSyn
criteria was greater in R than in NR (−27 vs −13, p < .0001) due to decreases in blood pressure (p < .01), glucose
(p = .02), and with a trend for triglyceride (p = .07). Reductions in fat mass best predicted resolution of MetSyn (p = .04).
Conclusions. Women who lose more fat are more likely to lower blood pressure, glucose, and triglyceride levels to
resolve MetSyn. Thus, a WL+LEX program effectively treats postmenopausal women with MetSyn.
Key Words: Exercise—Dieting—Metabolic syndrome—Inflammation.
Received July 1, 2010; Accepted April 16, 2011
Decision Editor: Luigi Ferrucci, MD, PhD
T
HE increased proportion of overweight and obese
older individuals in Western societies over the past
several decades is largely due to a sedentary lifestyle and
dietary excess. These individuals have a high prevalence
of the metabolic syndrome (MetSyn), a constellation of
metabolic abnormalities including abdominal obesity,
dyslipidemia, hypertension, and glucose intolerance (1).
The prevalence of MetSyn increases with age, affecting
~40% of the U.S. population older than 50 years with 56%
of women compared with 46% of men aged 60 years or
older having MetSyn (2,3). A recent analysis of the Third
National Health and Nutrition Examination Survey shows
that the MetSyn is associated with a significantly higher
all-cause, cardiovascular, and even noncardiac mortality
in postmenopausal women that is not apparent in men over
an observation period as long as 12 years (4). The high
prevalence of MetSyn in older women and its strong association with diabetes, cardiovascular disease (CVD) (5–9),
and decreased mobility (10–12), risk factors for disability
1022
and mortality in older people, makes its treatment a public
health priority.
Pharmacological interventions are effective in treating
dyslipidemia, hypertension, and elevated glucose levels, but
they fail to adequately address the risk factors of the 21st
century sedentary obesogenic lifestyle. In contrast, lifestyle
changes that directly address inactivity and overeating show
encouraging results in the treatment of MetSyn. The Diabetes Prevention Program (13) and other studies (14,15)
showed that diet-induced weight loss and exercise were
more effective than placebo in resolution of MetSyn across
the age span, but our study focuses on obese postmenopausal women where diabetes, CVD risk (3), and morbidity/
mortality are high (16). The purpose of this study was to
evaluate the effectiveness of a diet-induced weight loss and
low-intensity exercise program (WL+LEX) to reduce individual constituents and prevalence of MetSyn in obese postmenopausal women, as well as reduce CVD risk in obese
postmenopausal women without MetSyn. We hypothesized
LIFESTYLE CHANGE RESOLVES METABOLIC SYNDROME
that this lifestyle program would reduce multiple indices of
CVD risk and the prevalence of the MetSyn in obese postmenopausal women primarily through reductions in body
fat and that the metabolic improvements would be greater in
women with worse atherogenic metabolic profiles.
Methods
Overweight and obese postmenopausal women were
recruited from the Baltimore, MD, to Washington, DC, area
who met the following inclusion criteria: (a) no menstruation for more than 1 year, follicle stimulating hormone more
than 30 IU/L, and no hormone replacement therapy; (b)
body mass index 27–40 kg/m2; (c) weight-stable (<2.0 kg
weight change during the previous year); and (d) sedentary
(<20-minute exercise three times per week) but able to walk
2 mph on a treadmill for 5 minutes. Participants were
healthy, with a normal physical examination; 12-lead resting electrocardiogram; graded exercise test; and normal
liver, renal, and hematological blood assays. Exclusion
criteria included diabetes (fasting glucose > 7 mmol/L or
2 hours after 75 g oral glucose >11 mmol/L), poorly controlled blood pressure (>160/90) or high triglyceride ([TG] >
400 mg/dL), orthopedic limitations that would limit physical
activity, or significant metabolic disorders such as untreated
hypothyroidism. Participants using medications that affect
glucose metabolism were excluded; however, participants
were permitted to take antihypertensive (N = 6) and lipidlowering medications (N = 2). No tobacco product use was
permitted for the previous 5 years. This manuscript presents
a new hypothesis and adds cytokine data to a previous report (17). Participants provided informed consent according
to the University of Maryland Institutional Review Board
for Human Research.
Study Design
To minimize the effect of dietary composition as a
confounder of metabolic changes with WL+LEX, women
underwent a 6- to 8-week American Heart Association Step 1
diet (18) stabilization period during which they met weekly
with a registered dietician. Women then underwent baseline
testing including measurement of body composition, aerobic
fitness (VO2max), sitting blood pressure on three occasions,
and overnight 12-hour fasted plasma lipids, glucose and
2-hour postprandial glucose, and insulin levels before
beginning a 6-month WL+LEX intervention. There were
weekly dietitian-led WL classes in the principles of 250–
350 kcal/d caloric restriction that focused on eating behavior,
stress management, modification of binge eating, and
control of portion sizes. The participants participated in a
low-intensity aerobic exercise program that involved walking 1 d/wk on a treadmill at 50%–60% heart rate reserve for
45 minutes under the supervision of an exercise physiologist and instruction to walk a minimum of 2 d/wk at the
same intensity on their own. At the end of the 6-month
1023
program, women were weight-stabilized on an isocaloric diet
(<0.5 kg change) for 2 weeks prior to retesting while continuing the exercise program. The same series of tests performed
at baseline were repeated 36–48 hours after the last exercise
session. Participants were classified as having MetSyn
according to the Adult Treatment Panel III guidelines (1).
Procedures
Participants were weighed in kilograms and height measured in meters using a stadiometer; body mass index was
computed as kilograms per square meter. Waist circumference was measured at the narrowest point superior to the
hip. Body composition was determined using dual-energy x-ray absorptiometry (DPX-L; Lunar Radiation Corp.,
Madison, WI), and fat and lean tissue mass were determined with the LUNAR version 1.3z DPX-L extended analysis program. Visceral abdominal (VAT) and subcutaneous
adipose tissue (SAT) areas were measured using a singleslice computed tomography scan taken between L4 and L5
(17). Maximum aerobic capacity (VO2max) was measured using a modified Balke treadmill test as previously described
(19). A valid measurement required that at least two criteria
were met: (a) maximum heart rate greater than 90% of agepredicted maximum computed as 220 − age; (b) respiratory
exchange ratio of 1.10 or greater; and (c) plateau in oxygen
consumption (<200 mL/min change) with increasing work
rate. Blood for fasting glucose, insulin, and lipid profiles were
obtained after a 12-hour overnight fast three times, and results
averaged. Two-hour glucose and insulin levels were measured
after ingestion of 75 g glucose. Other blood chemistries were
obtained from a single fasting blood sample. Attendance was
taken at all classes, and compliance to diet was judged monthly
on a 1–5 scale (5 is best) based on quality of weekly food
records, class participation, knowledge of nutrition principles
for WL, and WL and averaged. During metabolic testing, compliance and weight were monitored twice weekly for weight
stability (<0.5 kg weight change) and weekly by review of
7-day food records and 24-hour dietary recalls.
Laboratory Methods
Glucose concentrations were measured by a glucose
oxidase method (YSI Instruments, Yellow Springs, OH)
and insulin concentrations by radioimmunoassay (Linco, St
Louis, MO). Tumor necrosis factor (TNF), TNF receptor
superfamily 1A and 1B, and interleukin-6 (IL-6) concentrations were determined by enzyme-linked immunosorbent assays using Quantikine immunoassay kits from R&D Systems
(Minneapolis, MN). The inter- and intra-assay Coefficient of
Variation were less than 6% for IL-6 and the soluble receptors
and less than 12% for TNF. High-sensitive C-reactive protein
was measured by automated immunoanalyzer (Immulite;
Diagnostics Products, Los Angeles, CA) with inter- and
intra-assays CVs of 7.5% and 4.4%, respectively. Plasma
TG and cholesterol were analyzed by enzymatic methods
1024
JOSEPH ET AL.
(Hitachi model 917 analyzer), and high-density lipoprotein
cholesterol was measured in the supernatant after precipitation with dextran sulfate (20). Low-density lipoprotein was
calculated using the Friedewald equation: LDL-C = total
cholesterol − (TG/5 + HDL-C).
Statistical Analyses
Homeostasis model assessment—insulin resistance was
computed as (glucose × insulin)/22.5 with glucose expressed
in millimolar and insulin in microunits per milliliter.
Comparisons between groups were performed using linear
least-squares regression with groups identified by dummy
variables and race included as a covariable. These equations
were solved using a modified Applied Statistics Algorithm
274 (21). Change data are expressed as a percentage of the
initial value. Outlying and influential data were identified
according to Belsley and colleagues (22). The categorical
analysis for baseline criteria count between groups compares the proportion of participants satisfying criteria with
those who do not. The categorical analysis for response to
WL+LEX compares the proportion of participants who no
longer satisfy a criterion with those who continue to satisfy
a criterion using Fisher’s exact test. Stepwise logistic
regression was performed using the R statistical program.
Data are mean ± SD with significance at p ≤ .05.
Results
Participants
The 115 participants included 83 (72%) Caucasians(C)
and 32 (28%) African Americans (AA) who were 11 ± 8
years postmenopausal. The 39 participants (34%) who
dropped out due to time constraints or personal reasons included 25 of the 83 C and 14 of the 32 AA (p = .19 between
races). Participants were divided into two groups at baseline
based on MetSyn status. Dropouts did not differ by MetSyn
status (MetSyn = 21/56 vs non-MetSyn = 14/55, p = .22; data
missing in four participants). The dropouts were heavier (91
+ 14 vs 86 + 13 kg, p = .05), had higher VAT (176 + 59 vs 152
+ 50 cm2, p = .03), and were more insulin resistant (homeostasis model assessment: 4.2 + 1.9 vs 3.1 + 1.5, p = .003) than
the 76 participants who completed the intervention. Overall
attendance to intervention was 76% with mean compliance
score of 3.33; there was no difference by MetSyn status, with
non-MetSyn participants attending 76% and the MetSyn
76% of classes with average compliance scores of 3.5 and
3.2 (p = Not Significant [NS]), respectively. Participants reported that they walked at home two to three times per week
for 30–45 minutes at the prescribed heart rate.
Baseline Differences Between MetSyn and Non-MetSyn
When compared as continuous variables (Table 1), most
of the metabolic indices and MetSyn constituents differed
between the MetSyn and non-MetSyn groups. There were
significant between-group differences in all MetSyn criteria
when compared as categorical variables (p ≤ .001), except
for blood pressure (p = .07).
Response to WL+LEX in MetSyn and non-MetSyn
groups.—We compared the responses of non-MetSyn with
MetSyn groups to test whether participants with the worse
metabolic profile at baseline would show the greatest improvement. The response in both groups was robust, with
most variables showing a highly significant change (Table 1).
The non-MetSyn group showed significantly greater
improvements in VAT, total cholesterol, low-density lipoprotein cholesterol, and IL-6 responses, but there were no
differences in the responses of the MetSyn variables. We
then determined whether the two groups differed in the
number of MetSyn criteria that changed with intervention
(ie, a categorical analysis). This showed that there were
significant reductions in the waist, TG, and glucose constituents in the MetSyn group (Table 3) but no difference
between MetSyn and non-MetSyn in the relative number of
criteria that changed (non-MetSyn: 22 of 61 vs MetSyn: 40
of 118, p = Not Significant).
Baseline differences between responder (R) and nonresponder (NR) groups.—Of the 33 MetSyn participants, 15
responded to WL+LEX by converting to non-MetSyn status
and were classified as responders (R) and the 18 who
remained MetSyn were classified as nonresponders (NR).
There were no significant differences between R and NR
participants at baseline in any of the MetSyn components,
either when expressed as continuous (Table 2) or categorical variables. The only variable that differed between the
R and NR groups at baseline was VO2max expressed per
kilogram body weight (p = .001), with NR being more
deconditioned prior to intervention.
Response to WL+LEX in responder (R) and nonresponder
(NR) groups.—There was no difference between the NR and
R groups in attendance (NR: 77% ± 13%, R: 78% ± 12%,
p = .67) or compliance (NR: 3.1 ± 1.0, R: 3.4 ± 1.1, p = .47).
At baseline, the NR consumed slightly less carbohydrate
than the R (57% vs 61%, p < .04), but there were no differences in total calories or other dietary variables. There were
no differences between NR and R in the changes in total
calories; carbohydrate; protein; fat; saturated, monounsaturated, or polyunsaturated fat; fiber; or sodium with WL+LEX;
but dietary cholesterol intake decreased less in the NR than
in the R (26% vs 37%, p = .004).
The WL+LEX intervention did not change VO2max (liters
per minute) significantly in either group; however, all
anthropometric and many of the metabolic constituents in
both the NR and R groups decreased (Table 2; Figure 1).
Reductions in fat mass (−8% vs −15%, p = .02) and percent
fat (2.4% vs −4.0%, p = .05) were greater in R, and the
1025
LIFESTYLE CHANGE RESOLVES METABOLIC SYNDROME
Table 1. Baseline Values and Response to WL+LEX in Women With and Without MetSyn
Baseline Values
Age, y
Weight, kg
BMI, kg/m2
% Body fat
Fat mass, kg
Lean mass, kg
Waist, cm
VAT, cm2
SAT, cm2
VO2max, mL/kg/m
VO2max, L/min
SBP, mmHg
DBP, mmHg
Total cholesterol,
mg/dL
TG, mg/dL
HDL-C, mg/dL
LDL-C, mg/dL
Glu0, mg/dL
Glu120, mg/dL
Ins0, pmol/L
HOMA-IR
hsCRP, mg/mL
IL-6, pg/mL
TNF-a, pg/mL
sTNFR1A, pg/mL
sTNFR1B, pg/mL
Percent Change After WL+LEX
Non-MetSyn (n = 41)
MetSyn (n = 35)
Difference (95% CL)
p Value
Non-MetSyn
MetSyn
Difference (95% CL)
p Value†
60 ± 6
83 ± 12
31 ± 4
47 ± 5
38 ± 8
40 ± 5
93 ± 9
135 ± 41
457 ± 111
20.2 ± 3
1.66 ± 0.3
121 ± 17
78 ± 11
207 ± 39
59 ± 6
90 ± 13
34 ± 5
48 ± 5
42 ± 9
43 ± 6
101 ± 9
172 ± 54
472 ± 120
19.6 ± 3
1.76 ± 0.2
130 ± 12
81 ± 6
198 ± 35
−1 (−4 to 1)
7 (2–13)
3 (1–5)
1 (−1 to 3)
4 (0–8)
3 (1–6)
8 (4–12)
37 (16–58)
15 (−39 to 69)
−0.7 (−2.0 to 0.7)
0.1 (−0.02 to 0.23)
8 (2–15)
3 (−1 to 7)
−9 (−26 to 8)
.38
.008
.003
.52
.03
.003
<.001
.001
.58
.33
.09
.01
.16
.29
−7 ± 4*
−7 ± 4*
−4.1 ± 3*
−15 ± 10*
1±4
−5 ± 6*
−17 ± 14*
−12 ± 13*
11 ± 9*
3 ± 7*
0 ± 12
−3 ± 16*
−4 ± 9*
−5 ± 5*
−5 ± 5*
−3.1 ± 2*
−11 ± 8*
0±4
−3 ± 4*
−9 ± 19*
−12 ± 11*
9 ± 13*
2 ± 10
−1 ± 12
0 ± 11
1±9
2 (0–4)
2 (0–4)
0.9 (−0.4 to 2.2)
3 (−1 to 8)
−1 (−3 to 1)
1 (−1 to 4)
9 (1–17)
−1(−6 to 4)
−2 (−8 to 4)
0 (−4 to 3)
−1 (−7 to 6)
5 (−1 to 11)
5 (1–9)
.06
.09
.15
.12
.28
.30
.03
.77
.52
.80
.85
.09
.02
110 ± 37
54 ± 14
131 ± 33
94 ± 7
124 ± 34
63 ± 21
2.5 ± 0.9
0.5 ± 0.4
2.5 ± 1.3
0.9 ± 0.4
1028 ± 235
2143 ± 405
149 ± 50
45 ± 10
123 ± 31
100 ± 17
145 ± 30
98 ± 37
4.0 ± 1.6
0.6 ± 0.3
2.4 ± 1.1
1.0 ± 0.4
1177 ± 307
2336 ± 493
38 (20–56)
−9 (−14 to −3)
−8 (−23 to 7)
4 (1–8)
20 (6–35)
34 (21–47)
1.5 (0.9–2.1)
0.1 (−0.1 to 0.3)
−0.1 (−0.9 to 0.6)
0.1 (−0.1 to 0.3)
148 (2–295)
193 (−54 to 440)
<.001
.002
.27
.02
.008
<.001
<.001
.51
.70
.33
.05
.12
−10 ± 19*
6 ± 14*
−6 ± 12*
−4 ± 9*
−3 ± 25
−9 ± 22*
−13 ± 26
−14 ± 58
−14 ± 36*
8 ± 71
−3 ± 15
−2 ± 10
−13 ± 16*
10 ± 10*
3 ± 12
−3 ± 8
−11 ± 16*
−4 ± 20
−6 ± 24
−25 ± 40*
28 ± 52*
−14 ± 25*
−4 ± 12
−4 ± 10
−3 (−11 to 6)
4 (−2 to 9)
9 (3–15)
2 (−2 to 6)
−8 (−18 to 2)
5 (−5 to 15)
7 (−5 to 18)
−11 (−44 to 22)
35 (14–56)
−12 (−33 to 8)
−2 (−11 to 7)
−2 (−8 to 4)
.52
.21
.002
.36
.13
.30
.28
.49
.002
.23
.71
.43
Notes: Values are mean ± SD. BMI = body mass index; CL = confidence limits; Glu0 = glucose at Time 0; Glu120 = glucose at time 120 minutes; HDL-C = highdensity lipoprotein cholesterol; HOMA-IR = homeostasis model assessment—insulin resistance; hsCRP = high-sensitive C-reactive protein; IL-6 = interleukin-6;
Ins0 = insulin concentration at Time 0; LDL-C = low-density lipoprotein cholesterol; SAT = subcutaneous abdominal fat, S/DBP = systolic/diastolic blood pressure;
sTNFR = soluble tumor necrosis factor receptor; TG = triglyceride; TNF-a = tumor necrosis factor alpha; VAT = visceral adipose tissue.
*Indicates significant change (p < .05) in response to WL+LEX. †p Value of non-MetSyn versus MetSyn.
reduction in visceral fat was more than twofold greater in R
(−6% vs −14%, p = Not Significant). There were no betweengroup differences in changes in VO2max, cytokines, or other
variables. Of the MetSyn variables, waist, TG, and highdensity lipoprotein cholesterol showed significant improvements in both NR and R participants, fasting glucose decreased
only in R, and blood pressure did not change significantly in
either group (Table 2). As expected, the change in the total
number of MetSyn criteria was significantly greater in the R
group (−27 vs −13, p < .0001), and when the individual criteria
were examined (Table 3), there were differences in the
changes in blood pressure (p < .01) and glucose (p = .03)
criteria, with a trend toward significance for TG (p = .07).
Stepwise logistic regression using candidate variables
of body composition and fitness showed that the change
in fat mass was the best predictor of resolution of MetSyn
(p = .04).
Discussion
The metabolic syndrome is a cluster of abnormalities that
are associated with increased risk of developing CVD and
type 2 diabetes (5–7). Results of this study show that a
6-month lifestyle intervention of moderate weight loss and
low-intensity exercise effectively reduces both CVD risk
factors and the prevalence of the MetSyn by 45%. A novel
outcome of our study is that the reductions in TG, glucose,
and blood pressure are the MetSyn criteria primarily associated with conversion from MetSyn to non-MetSyn
status. This is similar to National Health and Nutrition
Examination Survey study data which suggests that hypertriglyceridemia and hypertension are the cardiometabolic
abnormalities responsible for the heightened prevalence of
MetSyn among older women (3) and supports the possibility that the high prevalence of MetSyn is related to weight
gain in midlife (23) leading to abdominal obesity, high TGs,
and low high-density lipoprotein (24). Our results also show
that WL+LEX reduces the constituents of the MetSyn in
obese postmenopausal women both with and without
MetSyn to an equivalent degree, which suggests that this
intervention may be effective in preventing as well as reversing the MetSyn. Although most of the MetSyn variables
decreased in response to the intervention, there were greater
reductions in the non-MetSyn criteria of total cholesterol
and low-density lipoprotein cholesterol, IL-6, and VAT in
the non-MetSyn than in the MetSyn participants, suggesting
an overall health benefit of this lifestyle intervention for
obese postmenopausal women.
1026
JOSEPH ET AL.
Table 2. Physiological and Metabolic Responses to WL+LEX in Responders (R) and Nonresponders (NR)
Baseline Values
Age, y
Weight, kg
BMI, kg/m2
% Body fat
Fat mass, kg
Lean mass, kg
Waist, cm
VAT, cm2
SAF, cm2
VO2max mL/kg/m
VO2max, L/m
SBP, mmHg
DBP, mmHg
Total cholesterol, mg/dL
TG, mg/dL
HDL-C, mg/dL
LDL-C, mg/dL
Glu0, mg/dL
Glu120, mg/dL
Ins0, pmol/L
HOMA-IR
hsCRP, mg/mL
IL-6, pg/mL
TNF-a, pg/mL
sTNFR1A, pg/mL
sTNFR1B, pg/mL
Percent Change After WL+LEX
NR (n = 18)
R (n = 15)
Change
p Value
NR
R
Change
p Value†
58 ± 6
93 ± 15
35 ± 5
49 ± 6
45 ± 10
44 ± 7
103 ± 10
166 ± 59
489 ± 114
18 ± 3
1.69 ± 0.3
133 ± 13
82 ± 6
196 ± 34
154 ± 51
43 ± 8
121 ± 27
98 ± 10
147 ± 24
102 ± 35
4.2 ± 1.6
0.5 ± 0.3
2.2 ± 1.0
1.0 ± 0.5
1196 ± 342
2420 ± 561
59 ± 5
86 ± 11
32 ± 4
47 ± 4
40 ± 8
42 ± 4
98 ± 8
180 ± 50
467 ± 131
21 ± 2
1.81 ± 0.2
126 ± 12
79 ± 6
208 ± 32
147 ± 48
45 ± 7
133 ± 28
97 ± 8
140 ± 36
90 ± 40
3.6 ± 1.7
0.6 ± 0.4
2.5 ± 1.2
1.1 ± 0.3
1159 ± 287
2252 ± 429
1 (−4 to 6)
−6 (−17 to 4)
−3 (−6 to 1)
−2 (−6 to 1)
−5 (−12 to 1)
−1 (−7 to 5)
−5 (−12 to 2)
14 (−32 to 60)
−22 (−140 to 96)
3 (1–5)
0.12 (−0.1 to 0.3)
−7 (−16 to 2)
−2 (−7 to 3)
12 (−14 to 39)
−8 (−26 to 11)
2 (−3 to 6)
12 (−8 to 32)
−1 (−8 to 5)
−7 (−31 to 16)
−12 (−43 to 18)
−0.5 (−1.8 to 0.8)
0.1 (−0.2 to 0.4)
0.4 (−0.4 to 1.1)
0.1 (−0.4 to 0.7)
−37 (−285 to 212)
−168 (−589 to 252)
.71
.21
.15
.19
.13
.65
.15
.54
.71
.001
.16
.15
.35
.35
.42
.45
.25
.76
.55
.43
.43
.57
.32
.67
.77
.43
−4 ± 4*
−4 ± 4*
−2.4 ± 1.6*
−8 ± 4*
0±4
−2 ± 4*
−6 ± 18
−14 ± 10*
9 ± 14*
2 ± 10
1 ± 13
4 ± 13
1±8
−12 ± 12*
7 ± 11*
3 ± 11
−1 ± 9
−11 ± 14*
−4 ± 19
−5 ± 24
−25 ± 38
42 ± 57*
−15 ± 27
−5 ± 11
−7 ± 5*
−7 ± 5*
−7 ± 5*
−4.1 ± 2.9*
−15 ± 10*
−1 ± 4
−4 ± 4*
−14 ± 21*
−12 ± 12*
12 ± 12*
4 ± 10
−3 ± 11
−3 ± 8
−1 ± 10
−15 ± 18*
13 ± 9*
0 ± 12
−5 ± 7*
−11 ± 18*
−8 ± 17
−13 ± 16*
−25 ± 44
11 ± 43
−13 ± 23
−4 ± 13
−1 ± 13
−2 (−6 to 1)
−2 (−6 to 1)
−1.6 (−3.2 to −0.1)
−7 (−12 to −1)
−1 (−4 to 2)
−2 (−5 to 1)
−9 (−23 to 6)
2 (−7 to 11)
4 (−7 to 14)
2 (−6 to 9)
−4 (−13 to 4)
−6 (−14 to 1)
−2 (−8 to 4)
−2 (−12 to 7)
6 (−2 to 13)
−3 (−10 to 4)
−4 (−10 to 2)
0 (−17 to 17)
−3 (−16 to 10)
−8 (−23 to 7)
0 (−7 to 6)
−31(−75 to 13)
1 (−34 to 37)
2 (−5 to 8)
7 (−1 to 14)
.14
.14
.05
.02
.37
.14
.24
.71
.50
.67
.29
.11
.52
.63
.14
.46
.20
.98
.61
.30
.89
.18
.94
.65
.09
Notes: Values are mean ± SD. BMI = body mass index; Glu0 = glucose at Time 0; Glu120 = glucose at time 120 minutes; HDL-C = high-density lipoprotein
cholesterol; HOMA-IR = homeostasis model assessment—insulin resistance; hsCRP = high-sensitive C-reactive protein; IL-6 = interleukin-6; Ins0 = insulin concentration at Time 0; LDL-C = low-density lipoprotein cholesterol; SAT = subcutaneous abdominal fat, S/DBP = systolic/diastolic blood pressure; sTNFR = soluble
tumor necrosis factor receptor; TG = triglyceride; TNF-a = tumor necrosis factor alpha; VAT = visceral adipose tissue.
*Indicates significant change (p < .05) in response to WL+LEX. †p Value of nonresponders versus responders.
Interestingly, none of the changes in MetSyn variables
after WL+LEX differed between R and NR when analyzed
as continuous variables. Although MetSyn is predictive of
the development of diabetes and CVD, both the American
20
*
*
Change after WL+LEX (Percent)
10
0
*
*
*
-10
-20
*
*
-30
-40
Waist
TG
NR
R
HDL-C
BP-Syst
BP-Diast
Glucose
Figure 1. Response of metabolic syndrome variables to weight loss and
low-intensity exercise (WL+LEX) in responders (R) and nonresponders (NR).
Data are mean ± SD. BP = blood pressure; HDL-C = high-density lipoprotein
cholesterol; TG = triglyceride.
and the European Diabetes Associations and others express
concern over the arbitrary and dichotomous nature of the
cut points for its constituents (25–28), which is supported
by the discordance between the categorical and continuous
variable analysis in this study.
The participants who achieved larger reductions in percent body fat and fat mass with WL+LEX were more likely
to reverse MetSyn status. The small change in VO2max,
when calculated as absolute O2 consumption (liters per
minute) to minimize the inflated increase in VO2max if
expressed per kilogram body weight, supports the primary
role of WL in resolution of MetSyn. However, the exercise
may have prevented significant loss of lean mass seen with
WL alone in older people, which may predispose to sarcopenia (29). Thus, both WL and meeting the physical activity
guidelines for Americans seem to reduce the incidence and
development of MetSyn components in older adults (30,31).
The moderate dropout rate and resultant small sample size
probably precluded determination whether the resolution of
the MetSyn in these women is related primarily to the
decrease in visceral body fat. Although there was no difference in the attendance to the WL+LEX classes between the
responders and the nonresponders, the responders did
lose more body fat and may have complied better with
1027
LIFESTYLE CHANGE RESOLVES METABOLIC SYNDROME
Table 3. Responses of MetSyn Constituents by Category to WL-LEX in Responders (R) and Nonresponders (NR)
MetSyn at Baseline
MetSyn waist
MetSyn TG
MetSyn HDL-C
MetSyn BP
MetSyn glucose
MetSyn total
Nonresponders
Responders
Baseline (N = 33)
Change Due to
WL+LEX
Baseline (N = 18)
Change Due to
WL+LEX
Baseline (N = 15)
Change Due to
WL+LEX
p Value†
33
20
28
21
16
118
−5*
−12*
−6
−6
−11*
−40*
18
12
17
13
9
69
−1
−5
−2
−1
−4
−13
15
8
11
8
7
49
−4*
−7*
−4
−5
−7*
−27*
NS
NS (.07)
NS
.007
.02
<.0001
Notes: Values represent number of participants. Two participants with baseline data were missing postintervention data and MetSyn status could not be determined after WL+LEX. BP = blood pressure; HDL-C = high-density lipoprotein cholesterol; TG = triglyceride; NS = Not Significant.
*Indicates that the difference (pre- and post-WL+LEX) in the number of MetSyn participants with each MetSyn constituent is significant (p < .05). †p Value of
the response in NR versus R.
the intervention suggesting that behavioral factors may be
important. Other possible contributing factors to these responses include genetic susceptibility, as the effects of the
fat mass and obesity associated (FTO) gene variants on
obesity can be blunted through physical activity (32).
The post hoc analysis is a weakness in the design, but our
results are congruent with the findings that a 6-month moderate intensity exercise regimen consisting of flexibility,
balance, aerobic and strength training, and 8% weight loss
is associated with a 59% reduction in the prevalence of the
MetSyn in older men and women (14). Interestingly, the
41% reduction in the prevalence of MetSyn in the Diabetes
Prevention Program population of glucose intolerant men
and women (13) was observed after 3 years of a WL and
exercise intervention in contrast to the 6-month intervention
in the current study and that of Villareal and colleagues
(14). In another study examining the effects of a Mediterranean diet with instructions to increase daily physical activity
by 30 minutes, there was a 60% reduction in the MetSyn in
middle-aged men and women after 2 years (33). In a recent
study (34), there were even greater reductions in MetSyn
variables after a more intensive walking program in which
energy intake is kept constant or when exercise is combined
with caloric restriction to increase VO2max by ~15% in a
smaller group of 24 older men and women with MetSyn.
Furthermore, in an observational study in older Japanese
men and women, the risk of MetSyn was 4.3 times greater
in the least active quartile compared with the most active
(35). This suggests that the intensity, duration, and likelihood of compliance to the lifestyle intervention should be
considered when designing treatment program for MetSyn.
Several investigators postulate that a chronic low-grade
inflammation is a key component of MetSyn in older people
(36), especially given the relationship between elevated cytokine concentrations, obesity, and insulin resistance (37).
However, inflammation is not included in the definition of
the MetSyn in the United States (1) or Europe (38,39). Similar to our previous work, there are no differences in the
majority of the cytokine concentrations at baseline other
than soluble tumor necrosis factor receptor (sTNFR1A)
between the MetSyn and the non-MetSyn groups (40).
There were significant reductions in both high-sensitive Creactive protein and TNF-a levels in the MetSyn and IL-6 in
the non-MetSyn participants, confirming our earlier reports
(36,40). Contrary to the reductions found in response to a
12-month Mediterranean diet and physical activity intervention (33), IL-6 increased significantly in the MetSyn and
NR groups. Although we anticipated a decrease in sTNFR1A, but not in sTNFR1B receptors based on our prior
work (41,42), there were only small decreases in TNF receptors with intervention. It is possible that the low-intensity
walking exercise chosen in the current study did not
improve fitness to the same extent as in our previous interventions, given the inverse relationship of the changes in
sTNFR1A with VO2max (41). Further research in a larger
sample is necessary to assess the independent and combined
effects of weight loss and aerobic exercise of different
intensities and duration on cytokines, and their role in the
CVD risk and complications associated with MetSyn in
older adults.
Thus, a lifestyle intervention that employs a weightreducing diet coupled with low-intensity exercise reduces
the constituents of the MetSyn in overweight and obese
middle-aged to older Caucasian and African American postmenopausal women. This intervention is effective in women
with and without MetSyn, suggesting a beneficial role for
WL+LEX in preventing the development of MetSyn as well
as treating MetSyn in these high CVD risk individuals.
Future studies are necessary to elucidate the mechanisms
underlying these metabolic changes, the most effective
exercise and weight loss programs and the predictors of the
most desirable metabolic and health-related outcomes in
older women with MetSyn.
Funding
Supported by the National Institutes of Health (K01 AG021457 to L.J.J.,
R01 AG20116 to A.P.G., AG019310 to A.S.R., P30 AG028747 to A.P.G.,
P60 DK078637, and DK072488) and the Department of Veterans Affairs
(Baltimore VA Medical Center, Geriatric Research, Education and Clinical
Center, VA Research Career Scientist Award to A.S.R., Advanced Career
Development Award to J.B.B., and the Department of Veteran Affairs
Medical Research Service, Baltimore, Maryland).
1028
JOSEPH ET AL.
Acknowledgments
L.J.J. contributed to this article as an employee of the University of
Maryland. L.J.J. is currently employed at the National Institute on Aging,
National Institutes of Health. The views expressed are his own and do not
necessarily represent the views of the National Institutes of Health or the
U.S. Government.
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