1. health and fitness
2. disease
3. diabetes

Sports Med 2004; 34 (6): 371-418
0112-1642/04/0006-0371/$31.00/0
REVIEW ARTICLE
 2004 Adis Data Information BV. All rights reserved.
What is the Relationship Between
Exercise and
Metabolic Abnormalities?
A Review of the Metabolic Syndrome
Sean Carroll1 and Mike Dudfield2
1
2
School of Leisure and Sports Studies, Beckett Park Campus, Leeds Metropolitan University,
Leeds, UK
Leeds Sports Development Unit, Leeds Leisure Services, Leeds, UK
Contents
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371
1. The Metabolic Syndrome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373
2. Epidemiology of the Metabolic Syndrome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373
3. Metabolic Syndrome Phenotypes: Expert Panel Guidelines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376
4. Pathophysiology and Subclinical Metabolic Abnormalities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379
5. Physical Activity, Exercise and Metabolic Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379
6. Overview: Exercise in the Treatment of the Metabolic Syndrome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381
7. The Effects of Exercise Training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 387
7.1 The Metabolic Syndrome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 387
7.2 Insulin Resistance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 388
7.3 Abdominal Adipose Tissue Accumulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389
7.4 Impaired Glucose Regulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389
7.5 Atherogenic Dyslipidaemia: Systematic Review and Meta-Analysis . . . . . . . . . . . . . . . . . . . . . . . 390
7.6 Hypertension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 406
8. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 409
Abstract
Prevention of the metabolic syndrome and treatment of its main characteristics
are now considered of utmost importance in order to combat the epidemic of type
2 diabetes mellitus and to reduce the increased risk of cardiovascular disease and
all-cause mortality. Insulin resistance/hyperinsulinaemia are consistently linked
with a clustering of multiple clinical and subclinical metabolic risk factors. It is
now widely recognised that obesity (especially abdominal fat accumulation),
hyperglycaemia, dyslipidaemia and hypertension are common metabolic traits
that, concurrently, constitute the distinctive insulin resistance or metabolic syndrome. Cross-sectional and prospective data provide an emerging picture of
associations of both physical activity habits and cardiorespiratory fitness with the
metabolic syndrome. The metabolic syndrome, is a disorder that requires aggressive multi-factorial intervention. Recent treatment guidelines have emphasised the
clinical utility of diagnosis and an important treatment role for ‘therapeutic
lifestyle change’, incorporating moderate physical activity. Several previous
372
Carroll & Dudfield
narrative reviews have considered exercise training as an effective treatment for
insulin resistance and other components of the syndrome. However, the evidence
cited has been less consistent for exercise training effects on several metabolic
syndrome variables, unless combined with appropriate dietary modifications to
achieve weight loss.
Recently published randomised controlled trial data concerning the effects of
exercise training on separate metabolic syndrome traits are evaluated within this
review. Novel systematic review and meta-analysis evidence is presented indicating that supervised, long-term, moderate to moderately vigorous intensity exercise
training, in the absence of therapeutic weight loss, improves the dyslipidaemic
profile by raising high density lipoprotein-cholesterol and lowering triglycerides
in overweight and obese adults with characteristics of the metabolic syndrome.
Lifestyle interventions, including exercise and dietary-induced weight loss may
improve insulin resistance and glucose tolerance in obesity states and are highly
effective in preventing or delaying the onset of type 2 diabetes in individuals with
impaired glucose regulation. Randomised controlled trial evidence also indicates
that exercise training decreases blood pressure in overweight/obese individuals
with high normal blood pressure and hypertension. These evidence-based findings
continue to support recommendations that supervised or partially supervised
exercise training is an important initial adjunctive step in the treatment of
individuals with the metabolic syndrome. Exercise training should be considered
an essential part of ‘therapeutic lifestyle change’ and may concurrently improve
insulin resistance and the entire cluster of metabolic risk factors.
The purpose of this paper is to review the recently published literature concerning the effects of increased physical activity and exercise on metabolic
abnormalities. Over the last decade, investigators
have given increased attention to the complex role
of multiple metabolic abnormalities in the development of related chronic diseases such as type 2
diabetes mellitus and cardiovascular disease
(CVD).[1-6] Insulin resistance is now recognised as
an early metabolic abnormality that precedes the
development of type 2 diabetes.[7,8] Epidemiological
evidence that insulin resistance and compensatory
hyperinsulinaemia are also risk factors for multiple
risk factor clustering, atherosclerosis and coronary
heart disease (CHD)[9-11] have added to the evolving
concept of a distinct insulin-resistance syndrome.
This syndrome may represent the common soil for
the development of both diabetes and CHD.[5,12] The
first aim of this review is to summarise the recent
literature on the clustering of lipid and non-lipid risk
factors of metabolic origin, closely linked to insulin
 2004 Adis Data Information BV. All rights reserved.
resistance,[13,14] now designated the metabolic syndrome.[15-18] Epidemiological studies are evaluated
that provide an emerging picture of the prevalence
and outcomes of metabolic risk factor clustering.
Cross-sectional and prospective associations of both
physical activity habits and cardiorespiratory fitness
with the metabolic syndrome will be considered.
Recent working definitions of the metabolic or insulin resistance syndrome provided by several expert
groups[18-20] and therapeutic lifestyle implications
will be outlined. The second aim is to review the
effects of exercise training on the major components
of the metabolic syndrome, namely insulin resistance, abdominal fat accumulation, hyperglycaemia,
dyslipidaemia and hypertension. Within contemporary reviews,[21-25] exercise training has been considered effective in the treatment of insulin resistance
and related components of the syndrome. However,
the evidence for exercise effects has been considered less consistent for dyslipidaemia, impaired glucose regulation and hypertension, unless exercise
Sports Med 2004; 34 (6)
Exercise and Metabolic Abnormalities
training is combined with appropriate dietary modifications to achieve weight loss.[24-28] Within this
review, interpretative emphasis will be given to the
accumulated evidence from randomised controlled
trials (RCTs) of exercise training on the major characteristics of the syndrome. This evidence-based
approach is consistent with recent scientific convention.[29-31] Moreover, clinical trials that have examined exercise training alone rather than those specifically combined with hypocalorific dietary changes
will be highlighted.
1. The Metabolic Syndrome
Evidence for the clustering of CVD risk factors is
longstanding.[15,17] As early as 1923, Kylin described the constellation of hyperglycaemia,
hyperuricaemia and hypertension (cited by
Groop[32]). Thereafter, the history of metabolic clustering, including the contributions of Camus (1966),
Albrink et al. (1980), Hanefeld, Leonhardt (1981),
Modan et al. (1985) and Wingard et al. (1983), have
been variably described within several recent reviews.[13,17,32-35] The work of Pyorala et al. (1979),
and Welborn and Wearne (1979) are acknowledged[17] as early publications relating hyperinsulinaemia and glucose intolerance to CVD risk. The
entity of a metabolic syndrome, however, did not
receive much consideration until Reaven (1988) introduced ‘Syndrome X’ in his Banting Lecture to the
American Diabetes Association.[13] Syndrome X referred to a group of connected disorders characterised by impaired glucose tolerance (IGT), dyslipidaemia, hypertension, associated with increased
risk of both type 2 diabetes and CVD.[13] Insulin
resistance, located primarily in skeletal muscle and
limited to non-oxidative glucose disposal was cited
as the primary underlying mechanism for the syndrome. The combination of insulin resistance and
compensatory hyperinsulinaemia were considered
necessary for the development of other lipid and
non-lipid abnormalities.[13,36,37] Insulin resistance
was also acknowledged as the central feature of this
syndrome by De Fronzo and Ferrannini et al.[14,38,39]
Concurrently, other researchers[40,41] (following the
seminal publications of Vague[42]), recognised body
 2004 Adis Data Information BV. All rights reserved.
373
fat distribution as important in mediating metabolic
risk. Notably, Kaplan[43] described the clustering of
metabolic abnormalities associated with hyperinsulinaemia as the ‘deadly quartet’, with reference to
the combination of upper body fat accumulation,
hyperglycaemia, hypertriglyceridaemia and hypertension. Over the years, metabolic clustering has
also been given numerous labels, the most recent
designations including the multiple metabolic syndrome,[44] metabolic syndrome X,[17,34] cardiovascular metabolic or cardiometabolic syndrome[45,46] and the dysmetabolic syndrome.[47]
However, the terms, ‘insulin resistance’[20] or ‘metabolic syndrome’[18,19] are now most widely accepted
for this clinical entity. For the purposes of this
review, the latter terminology will be adopted.
2. Epidemiology of the
Metabolic Syndrome
Since the mid-1980s, there had been considerable
interest in the epidemiology of the metabolic risk
factor clustering. Liese et al.[44] have comprehensively reviewed the analytical epidemiological studies within this area. Several early population-based
studies provided evidence for the existence of an
identifiable pathological syndrome, including those
showing associations of separate CVD risk factors
with incident development of type 2 diabetes.[48,49]
Other investigations demonstrated that hyperinsulinaemia and central adiposity preceded the development of hypertension, dyslipidaemia and metabolic clusters.[50-53] Numerous analyses have been
subsequently published using statistical approaches
(notably factor or principal component analysis) to
defining distinct metabolic clusters within diverse
populations.[15,44,54-60] This multivariate correlation
approach has provided a method for empirically
describing the clustering characteristics of related
metabolic variables and potentially underlying features of the syndrome. As reviewed by Meigs[61] and
Liese et al.,[44] these investigations have indicated
that the separate components of the syndrome may
result from multiple underlying physiological processes, with a prominent role for insulin resistance.[15,61,62] The clustering of metabolic disorders
Sports Med 2004; 34 (6)
374
has been increasingly evaluated within the framework of genetic epidemiology, including both family and twin studies.[63-68]
Epidemiological investigations have documented
that the metabolic syndrome occurs commonly
among middle-aged and elderly individuals, with a
higher prevalence in men and among older individuals.[18,19] Table I and table II show the prevalence of
multiple risk factors within numerous recent epidemiological studies among middle-aged and elderly
adults.[69-90] Although comparisons between studies
are problematic due to differences in definitions and
diagnostic criteria,[72] the tables clearly show the
frequent and widespread nature of metabolic risk
factor clustering. The investigators of the European
Group for the Study of Insulin Resistance[20] have
cited the frequency of a defined insulin resistance
syndrome to be between 7–36% for middle-aged
males and between 5–22% for females of the same
age across eight population studies. Ferrannini et
al.[11] have estimated that only 30% of adults are free
from at least one of the major defining risk characteristics of the metabolic syndrome. Moreover,
within one random population survey, over 90% of
all hypertensive patients had at least one metabolic
risk factor in addition to hypertension itself.[76] Multiple metabolic clustering has been documented
across a wide variety of ethnic groups with a high
prevalence among Native and Mexican Americans
and Asian Indians, among other minority
groups.[18,80,90]
It is now widely accepted that the metabolic
syndrome has an important mediating role in the
increased risk of CVD and type 2 diabetes.[15,18,19]
Recently, several investigations have shown that
clusters of metabolic variables (including those
identified by factor analysis) are associated with
incident development of diabetes,[55,91] CVD[92-97]
and all-cause mortality.[71] Individuals exhibiting
metabolic clustering related to insulin resistance
have been shown to have a 4- to 11-fold increased
relative risk for type 2 diabetes and a 2- to 4-fold
increased risk of both CHD and CVD compared
with individuals without this phenotype.[15]
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Carroll & Dudfield
Publication of evidence from lipid-lowering clinical trial settings (West of Scotland Coronary Prevention Study[83] [WOSCOPS]) and preliminary
data from the Scandinavian Simvastatin Survival
Study (4S study)[98] and the Air Force/Texas Coronary Atherosclerosis Prevention Study (AFCAPS/
TexCAPS)[98] also indicate that patients with metabolic syndrome are 1.5 and 2 times more likely to
have an acute CHD or CVD event than those without the metabolic syndrome, respectively. Within
the WOSCOPS study,[83] the metabolic syndrome
continued to predict CHD events significantly (hazard ratio 1.30) in a multivariate model incorporating
conventional risk factors. Analysis of participants in
the control arms of the two other large clinical
trials[98] showed that patients categorised with the
metabolic syndrome had increased risk of CVD
events regardless of Framingham risk category
(Framingham CVD risk score >20 versus ≤20%
10-year risk). These findings confirm that the metabolic syndrome is an important risk factor in the
development of CHD/CVD events in both hypercholesterolaemic patients with CHD (4S study),
among males with moderately raised cholesterol
levels (WOSCOPS study), and adults with average
cholesterol levels (AFCAPS/TexCAPS study) both
without evidence of CHD. These data support previous observations suggesting that metabolic syndrome confers additional risk not entirely accounted
for by widely recommended traditional CHD scoring paradigms.
The clinical importance of the metabolic syndrome is due mainly to the increased risk imparted
by the concurrent clustering of several ‘independent’ CVD risk factors within the same individual.[24] Some prospective studies[79,83] have reported
an increased risk of CHD associated with the metabolic syndrome after adjusting for conventional risk
factors, but not above that explained by the individual effects of the defining variables.[79,83] Others have
indicated that there may be substantial additional
CVD risk above and beyond the individual risk
factors[88] (see section 4).
Sports Med 2004; 34 (6)
Population
n
Age (y)
Metabolic risk factors evaluated
Participants with metabolic
clustering (%)
Reference
>2
≥3
Whitehall II Study, London, UK
4 978
39–63
IGT, SBP, HDL-C, TG, WHR
NR
15.8
69
Kuppio Ischaemic Heart Disease Risk Factor Study,
Finland
2 272
42–60
IGT, FI, HTN, HDL-C, TG
28.6
7.4
53
Naples, Italy
Risk factors & Life Expectancy Project, 9 studies, Italy
Framingham Offspring Study, Framingham, USA
1 252
35–64
IFG, HTN, DBP
28.6
7.0
70
25 561
20–69
IFG, HTN, HDL-C, TG
42.1
15.1
71
2 406
18–74
IFG, SBP, TC, HDL-C, TG, BMI
37.0
18.0
54
35–70
WHO definition:[18] inc. HOMA IR
NR
15.0
73
58
WHO definition:[18] inc. IFG, FI
65.0
15.8
74
42–55
T2D, IFG/IGT, HTN, TC, HDL-C, TG
40.6
17.9
75
13.5
14.7
28.7
Botnia, Sweden/Finland
Gothenberg, Sweden
NHANES III 1988–1994, multicentre, USA
391
1 398
WHO definition:[18] inc. FI (without obesity)
Oulu, Finland
259
50.9 ± 6.1
Control
76
50.5 ± 5.9
Hypertensive on medication
26.8
15 534
20–88
IFG, SBP, WC, TG
14.9
5.6
77
British Regional Heart Study. 18 selected British towns
5 222
40–59
IFG, HTN, TC, HDL-C, TG
46.8
10.2
78
Caerphilly and Speedwell studies, UK
4 197
45–63
FI, FG, TG, BMI, DBP
NR
20.0 > 4
metabolic risk
factors
79
EGIR multicentre, 8 participating European studies
1 384
<40
EGIR definition[20]
13.0
20
3 250
40–55
261
Dallas, Texas, USA
Exercise and Metabolic Abnormalities
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Table I. Prevalence of metabolic clustering within middle-aged and older males within several recent population investigations
Hypertensive
20.0
2 996
>55
NHANES III 1988–1994, multicentre, USA
8 814
>20
NCEP ATP III definition[19]
Kuppio Ischaemic Heart Disease Risk Factor Study,
Finland
1 209
42–60
NCEP ATP III definition:[19]
2 857
adults
40–74
24.0
80
81
with WC >102.0cm
8.8
with WC >94.0cm
14.0
WHO definition/EGIR[19] inc. FI and IFG
14.2
with WC >94.0cm
13.4
Age-adjusted WHO definition:[18] inc.
OGTT and fasting HOMA
27.6
Age-adjusted NCEP ATP III definition[19]
25.1
82
Continued next page
375
Sports Med 2004; 34 (6)
NHANES III 1988–1994, multicentre, USA
33.0
44.9
24.7
32.9
WHO definition:[18] inc. FI
definition:[18]
inc. HOMA IR
NCEP ATP III definition[19]
WHO
40–79
WHO
470
450
San Antonio Heart Study, Texas, USA
Bruneck, Italy
30–79
1 503
Framingham Offspring Study, Massachusetts, USA
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BMI = body mass index; DBP = diastolic blood pressure; EGIR = European Group for the study of Insulin Resistance; FG = fasting glucose; FI = fasting hyperinsulinaemia; HDL-C
= high density lipoprotein-cholesterol; HOMA IR = Homeostasis Model Assessment, Fasting Insulin Resistance Index; HTN = hypertension; IFG = impaired fasting glucose; IGT =
impaired glucose tolerance; inc. = incorporating; NR = not reported; NCEP ATP III = National Cholesterol Education Programme, Adult Treatment Panel III; NHANES III = Third US
National Health & Nutrition Examination Survey; OGTT = oral glucose tolerance test; SBP = systolic blood pressure; TC = total cholesterol; TG = triglycerides; T2D = type 2
diabetes mellitus; WC = waist circumference; WHO = World Health Organization; WHR = waist-to-hip circumference ratio.
24.7
NCEP ATP III definition[19]
85
30.3
inc. FI
definition:[18]
16.5
26.9
NCEP ATP III definition[19]
83
26.2
≥3
>2
57.0
Adapted NCEP ATP III definition:[19] inc.
BMI
6 447
West of Scotland Prevention Study, Scotland, UK
(moderately hypercholesterolaemic men)
55.2 ± 5.5
Participants with metabolic
clustering (%)
Metabolic risk factors evaluated
Age (y)
n
Population
Table I. Contd
84
Carroll & Dudfield
Reference
376
3. Metabolic Syndrome Phenotypes:
Expert Panel Guidelines
Within the accumulating epidemiological evidence (tables I and II), the metabolic syndrome has
been by case definition, phenotypically heterogeneous. Several expert panels[17-20] have recently provided some uniformity by proposing similar metabolic components within the syndrome (table III).
These guidelines are consistent in that there is a
focus on insulin resistance/hyperinsulinaemia,
hyperglycaemia, obesity (especially central/upper
body distribution), dyslipidaemia and hypertension
as constituent traits. Nevertheless, considerable disparity exists within the expert panel criteria for the
individual metabolic traits, as well as the syndrome
itself, likely due to the different emphasis within
each consultation.
Within population-based studies of non-diabetic
Caucasian adults,[84,85] only 66–82% diagnosed with
the metabolic syndrome according to the World
Health Organization (WHO) definition concurrently
met the National Cholesterol Education Programme
(NCEP), Adult Treatment Panel (ATP) III criteria.
This would indicate that the different criteria show
only moderate agreement in identifying a group with
similar characteristics, leading to significant differences in predicted insulin resistance and CHD risk.
Studies have also documented significant racial/
ethnic heterogeneity in the classification of the syndrome itself.[84] Hanley et al.[89] have nevertheless
shown that both the WHO and NCEP ATP III metabolic syndrome criteria identify nondiabetic individuals with low insulin sensitivity using frequently
sampled intravenous glucose tolerance tests. The
associations were notably stronger using the WHO
definition. WHO and NCEP definitions were also
significantly associated with risk of being in the
lowest quartile of insulin sensitivity-adjusted acute
insulin response and disposition index, but these
associations were generally weaker than those for
insulin sensitivity. Thus, individuals characterised
with the metabolic syndrome (by several different
criteria), are more insulin resistant and at increased
CHD risk versus those without the metabolic syndrome.[84]
Sports Med 2004; 34 (6)
Population
n
Age (y)
Metabolic risk factors evaluated
Participants with metabolic
clustering (%)
53.3 ± 5.6
IFG, HTN, HDL-C, TG
11.9
303
50–84
IFG/IGT, T2D, HTN, HDL-C, TG
18 495
20–69
IFG, HTN, HDL-C, TG
Framingham Offspring Study, Framingham, USA
2 569
18–74
NHANES III, multicentre, USA
1 611
Dallas, Texas, USA
3 898
Botnia, Sweden/Finland
1 133
>2
Atherosclerosis Risk in Communities Study,
multicentre, USA
Rancho Bernado, South California, USA
Risk Factors and Life Expectancy Project, multicentre,
Italy
5 237
52
7.9
86
37.2
15.3
71
IFG, SBP, TC, HDL-C, TG, BMI
38.0
19.0
54
54.1 ± 19.8
IFG/IGT, T2D, HTN, TC, HDL-C, TG, FI
36.4
15.8
76
20–88
IFG, SBP, WC, TG
3.5
0.6
56
35–70
WHO definition:[18] inc. HOMA IR
10.0
74
WHO definition:[18] inc. FI (without obesity)
267
51.8 ± 6.0
Control
258
51.8 ± 5.9
Hypertensive on medication
1 412
<40
3 773
40–55
3 772
>55
NHANES III 1988–1994, multicentre, USA
1 887
NHANES III 1988–1994, multicentre, USA
2 857
adults
Framingham Offspring Study, Massachusetts, USA
San Antonio Heart Study, Texas, USA
1 721
EGIR
14 719
16.7
26.4
definition[20]
3.0
20
17.0
definition[19]
>20
NCEP ATP III
22.8
80
Age-adjusted WHO definition:[18] inc.
OGTT and fasting HOMA
32.1
82
Age-adjusted NCEP ATP III definition[19]
32.9
30–79
40–79
40.7
NCEP ATP III definition[19]
21.4
WHO definition:[18] inc. FI
19.7
NCEP ATP III definition[19]
21.3
definition:[18]
inc. FI
17.2
WHO definition:[18] inc. HOMA IR
35.9
NCEP ATP III definition[19]
19.1
NCEP ATP III definition[19]
84
45.7
24.4
85
87
BMI = body mass index; EGIR = European Group for the study of Insulin Resistance; FI = fasting hyperinsulinaemia; HDL-C = high density lipoprotein-cholesterol; HOMA IR =
Homeostasis Model Assessment, Fasting Insulin Resistance Index; HTN = hypertension; IFG = impaired fasting glucose; IGT = impaired glucose tolerance; inc. = incorporating;
NCEP ATP III = National Cholesterol Education Programme, Adult Treatment Panel III; NHANES III = Third US National Health & Nutrition Examination Survey; OGTT = oral
glucose tolerance test; SBP = systolic blood pressure; TC = total cholesterol; TG = triglycerides; T2D = type 2 diabetes mellitus; WC = waist circumference; WHO = World Health
Organization.
377
Sports Med 2004; 34 (6)
Women’s Health Study
5.2
40–74
611
450
77
5.6
7.0
WHO
Bruneck, Italy
≥3
1.6
Oulu, Finland
EGIR, multicentre, 8 participating European studies
Reference
Exercise and Metabolic Abnormalities
 2004 Adis Data Information BV. All rights reserved.
Table II. Prevalence of metabolic clustering within middle-aged and older females within several recent population investigations
378
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Table III. Comparison of recent expert panel[18-20] guideline criteria for the diagnosis of the metabolic or insulin resistance syndromea
Metabolic risk factor
WHO (1998) diagnostic level[18]b
NCEP ATP III (2000) diagnostic level[19]c
EGIR (2002) diagnostic level[20]d
Obesity (abdominal obesity)
BMI ≥30.0 kg/m2 and/or waist to hip
Waist circumference: >102.0cm (M),
Waist circumference: >94.0cm (M);
circumference ratio >0.9 (M), >0.85 (F)
>88.0cm (F)
>80.0cm (F)
Type 2 diabetes, impaired glucose
Impaired fasting glucose ≥6.1 mmol/L
Insulin resistance/glucose intolerance
tolerance or insulin resistance
Hyperinsulinaemia – fasting insulin
above the upper quartile for non-
(Lowest 25% percentile for insulin
diabetic individuals
sensitivity by euglycaemic clamp or
Impaired fasting plasma glucose ≥6.1
highest quartile fasting insulin or
mmol/L (≥5.6 mmol/L venous or
HOMA)
capillary whole blood)
Dyslipidaemia
HDL-C
triglycerides
Blood pressure
Microalbuminuria
<0.9 mmol/L (M)
<1.04 mmol/L (M)
<1.00 mmol/L (M and F) and/or
<1.0 mmol/L (F)
<1.30 mmol/L (F)
treatment for dyslipidaemia
≥1.69 mmol/L
≥ 1.69 mmol/L
≥2.0 mmol/L
≥140/90mm Hg
≥ 130/85mm Hg and/or treatment for
≥140/90mm Hg and/or treatment for
hypertension
hypertension
Not utilised for diagnosis
Not utilised for diagnosis
Overnight urinary albumin excretion
rate ≥20.0 µg/min
a
The American Association of Clinical Endocrinologists (AACE) have proposed an additional set of clinical criteria for the ‘insulin resistance syndrome’.[3] These criteria
have been likened to a hybrid of those of the ATP III and WHO metabolic syndrome.[2] The term ‘insulin resistance syndrome’ does not include categorical diabetes. The
precise diagnostic criteria are not well specified and left to clinical judgement. In patients without impaired FG, a 2-hour postglucose challenge is recommended.
b
To meet WHO (1998) criteria, an individual with impaired glucose tolerance must meet two or more other metabolic criteria to be diagnosed with the metabolic syndrome.
An individual with normal glucose tolerance must meet two metabolic criteria in addition to being diagnosed insulin resistant.
c
Under the NCEP ATP III (2000) criteria, an individual must meet at least three of the metabolic risk factor criteria to be diagnosed with the metabolic syndrome. Some
males can develop risk factors when the waist circumference is only marginally increased (94–102cm).
EGIR (2002) provide an alternative definition of the metabolic syndrome for non-diabetic individuals, the insulin-resistance syndrome. An individual with fasting
hyperinsulinaemia must meet two or more of the other components to be diagnosed with the insulin-resistance syndrome.
BMI = body mass index; EGIR = European Group for the study of Insulin Resistance; F = females; HDL-C = high density lipoprotein-cholesterol; HOMA = Homeostasis Model
Assessment; M = males; NCEP ATP III = National Cholesterol Education Programme, Adult Treatment Panel III; WHO = World Health Organization.
Carroll & Dudfield
Sports Med 2004; 34 (6)
d
Exercise and Metabolic Abnormalities
4. Pathophysiology and Subclinical
Metabolic Abnormalities
Elucidation of the complex pathophysiological
mechanisms underlying metabolic syndrome remains a ‘work-in-progress’[17] and is beyond the
scope of this review. Insulin resistance, upper body
fat accumulation (particularly intra-abdominally),
impaired postprandial lipid metabolism and increased intracellular lipid content of skeletal muscle
appear relevant to this heterogeneous condition
which probably develops through a generalised imbalance in the metabolism of both carbohydrates and
lipids.[13,16,33,43,62,88,99-103]
It is considered that the clustering of the main
characteristics of the metabolic syndrome allows the
clinician to assume that other sub-clinical risk factors, not routinely measured, are also present.[16,18]
Indeed, several authors[104] have emphasised that the
syndrome often constitutes an interplay of multiple
subtle biochemical abnormalities, often none sufficiently aberrant to be considered a risk factor by
itself. Since the original description of Syndrome
X,[13] numerous other subsidiary features have been
added.[19,105-108] Table IV includes many of the miscellaneous sub-clinical abnormalities that have been
associated with the metabolic syndrome. The features of the syndrome appear highly related and
involve several physiological systems.[19,38,61,104,109]
Clinicians should recognise that the co-occurrences
of these metabolic abnormalities are almost certainly related to insulin resistance/hyperinsulinaemia.[16,18,110] Furthermore, there is substantial
evidence that they are all CVD risks warranting
aggressive therapeutic intervention.[16,111]
Heritability has been shown to be important in
the development of insulin resistance[32,145] and the
mutual clustering of metabolic variables.[32,101,145]
Genetic predisposition (related to several candidate
genes[32]) in combination with the effect of environmental factors is likely to influence the development
of insulin resistance and/or the clinical expression of
the metabolic syndrome. Table V outlines several
commonly cited environmental risk factors for insulin resistance and/or the metabolic syndrome. The
role of an unfavourable fetal environment (intrauter 2004 Adis Data Information BV. All rights reserved.
379
ine malnutrition) leading to a ‘thrifty phenotype’
which manifests itself under adverse circumstances
in adult life remains an intriguing hypothesis.[146]
Low birth weight and early life events, adult socioeconomic and lifestyle influences may independently and in combination contribute to insulin resistance and increased metabolic syndrome risk.[147] In
462 nondiabetic middle-aged Caucasian men,[148]
those with low birth size were at least 2-fold more
likely to have the metabolic syndrome (WHO definition) following adjustment for childhood or adult
socioeconomic status or adult body mass index
(BMI). Thinness at birth was even more clearly
associated with the metabolic syndrome in men engaging in <25 min/wk of vigorous leisure time physical activity and in men with a maximum oxygen
˙ 2max) of <28.6 mL/kg/min. In conconsumption (VO
trast, among active and fit men, the association was
absent. Thus it was considered that regular strenuous physical activity and maintenance of cardiorespiratory fitness may lessen the lifelong metabolic
abnormalities associated with thinness at birth.
5. Physical Activity, Exercise and
Metabolic Risk
In prospective cohort studies, higher levels of
physical activity and cardiorespiratory fitness have
quite consistently protected against the development
of diabetes and CVD[148,171-176] and combined endpoints.[177] Physical activity has been inversely associated with the risk of these conditions, specifically
CVD, in a dose-response fashion.[178,179] Physical
activity may protect against these conditions in part
through components of the metabolic syndrome.[180-183] Byberg et al.[182] have shown that
adjustment for insulin, proinsulin and split proinsulin conferred the largest attenuation of the increased
risk of CVD mortality associated with sedentary
behaviour among middle-aged males. These metabolic variables were also those that over time showed the largest improvement associated with increased physical activity.[175,182]
Numerous epidemiological studies have now reported significant associations between physical activity and cardiorespiratory fitness measures with
Sports Med 2004; 34 (6)
380
Carroll & Dudfield
Table IV. Potential subclinical metabolic abnormalities associated with the metabolic syndrome[16,17,108,109]
Insulin resistance
Cardiovascular system disorders[112-117]
↓ Insulin-mediated glucose disposal in tissues (muscle, liver, fat)
↑ Sympathetic adrenergic activity (increased heart rate and cardiac
output, decreased heart rate variability)
Fasting and post-challenge hyperinsulinaemia
Left ventricular hypertrophy or ↑ wall thickness and concentric
remodelling
↓ Insulin receptor number and proteins of the insulin signalling
cascade
Vascular smooth muscle hypertrophy
Altered GLUT-4 expression (major insulin-stimulated glucose
transporter)
Inelastic blood vessels
Impaired glycogen synthesis
Absent nocturnal decreases in heart rate and blood pressure
Dyslipidaemia
Salt sensitive hypertension
↑ Non-esterified free fatty acids (resistance to insulin suppression
of postprandial adipose tissue lipolysis)
Pro-thrombotic disorders[118-121]
↑ Postprandial lipaemia (including chylomicrons and remnants)
↑ Plasminogen activator inhibitor-1
↑ VLDL synthesis and secretion, and apolipoprotein B secretion
Hyperfibrinogenaemia
↑ Small dense LDL-C (↓ LDL particle size)
↑ Plasma/blood viscosity
Altered pituitary-adrenal function[99,122]
↑ Factor VII:C
Hypercortisolaemia, ↑ glucocortocoids
Endothelial dysfunction/low-grade inflammation[123-131]
↑ Glucocortocoid receptor function
Impaired skeletal muscle vasodilation (impaired endothelial derived
nitric oxide production)
↓ Growth hormone
↑ Plasma concentration of vascular adhesion molecules
Sex hormone interactions[132]
↑ Highly sensitive C-reactive protein and interleukin 6
↑ Androgens (F)
Alterations in the tumour necrosis factor-α system
↓ Androgens (M)
Altered liver function[103,133]
↓ DHEA
↑ Glucose production
Polycystic ovary syndrome
↓ Insulin removal
Altered renal function[134]
↑ γ-Glutamyl transpeptidase
Sodium retention
↑ Hepatic lipase activity
↑ Renin-angiotensin-aldosterone
Altered skeletal muscle[100-102,135-140]
↓ Uric acid clearance
↑ Intramuscular triglycerides
Microalbuminuria
Altered plasma membrane phospholipids
Altered adipose tissue physiology[141-144]
↑ Type II a fibres
↑ Visceral fat accumulation
↓ Muscle capillary density
Disordered fat storage and mobilisation
Altered glycolytic and oxidative enzyme capacities
Hyperleptinaemia (leptin resistance)
↓ Adiponectin
DHEA = dehydroepiandrosterone; F = females; GLUT-4 = glucose transporter; LDL-C = low density lipoprotein-cholesterol; M = males;
VLDL = very low density lipoprotein; ↓ indicates decrease; ↑ indicates increase.
insulin resistance and most other separate components of the metabolic syndrome among both young,
middle-aged and older adults.[24,69,147,184-188] However, the potential importance of physical activity
and cardiorespiratory fitness in the development of
multiple metabolic abnormalities has been less extensively investigated compared with other lifestyle
factors.[44] Only recently can epidemiological data
be evaluated for associations between physical activity and cardiovascular fitness and the clustering
 2004 Adis Data Information BV. All rights reserved.
of metabolic risk factors within both cross-sectional
and prospective settings[77,180,189-193] (table VI).
Strong inverse associations between physical activity, cardiorespiratory fitness and the clustering of
metabolic variables have been shown in several
cross-sectional investigations across different ethnic
and socioeconomic groups, mainly representing
middle-aged Caucasian men and women. Within the
population-based Kuoppio study,[180] men who engaged in at least moderate-intensity (≥4.5 metabolic
Sports Med 2004; 34 (6)
Exercise and Metabolic Abnormalities
381
Table V. Environmental risk factors associated with the metabolic
syndrome
Risk factor
References
Early life experiences (fetal development and
infant growth)
146,149-152
Low social status as a child
152
Progressive weight gain during childhood and 153,154
preadolescence
Progressive weight gain during early to middle 17,50,147,155,156
adulthood
Western diet (high in refined carbohydrates,
low in fibre, high in saturated fat)
157-161
Cigarette smoking
162-164
Psychosocial factors: social/occupational
status, social isolation and education
69,165,166
Psychological distress, which may include
165-170
depression, anxiety, vital exhaustion,
temperament-related behaviour and attributes
such as hostility and anger expression
equivalents [METs]) leisure time physical activity
of <1.0 h/wk were 60% more likely to have a
modified WHO definition of the metabolic syndrome than those engaging in ≥3.0 h/wk even after
adjustment for confounding variables (age, socioeconomic status, smoking and alcohol consumption). However, low-intensity (<4.5 METs) physical
activity was not associated with the metabolic syn˙ 2max <29.1 mL/kg/min were
drome. Men with a VO
almost 3–4 times more likely to have the metabolic
˙ 2max ≥35.5 mL/kg/
syndrome than those with a VO
min even after adjusting for BMI and the above cited
confounders.
As outlined in section 2, the statistical method of
factor analysis has been widely adopted in order to
define a basic phenotype underlying the clustering
of metabolic risk variables.[61] An early study of 970
middle-aged Caucasian males[93] showed that pre˙ 2max, derived from a submaximal exercise
dicted VO
test, to be heavily loaded (–0.66) on a so-called
insulin-resistance factor. A complimentary factor
analysis has subsequently been undertaken within
1069 middle-aged Kuoppio males.[193] A first-order
factor analysis including 19 variables, showed a
principal factor (explaining 20% of total data variance) with heavy loadings for both directly-deter˙ 2max (–0.57) and moderate or heavy loadmined VO
ings for other proposed components of the metabolic
 2004 Adis Data Information BV. All rights reserved.
syndrome (including BMI, waist circumference,
fasting triglycerides [TGs], insulin and glucose).
This factor also had moderate loadings for total or
moderate and higher intensity leisure-time physical
activity (factor loadings –0.37 and –0.44, respec˙ 2max also loaded moderately on separate
tively). VO
but interrelated dyslipidaemia, blood pressure and
inflammatory factors (together contributing a further 20% of the total data variance). Hedman et
al.[100] have shown that both fibre-type distribution
and muscle capillary density contribute to the beneficial effects of self-reported physical activity on the
insulin resistance syndrome within a populationbased sample of 475 middle-aged men.
6. Overview: Exercise in the Treatment
of the Metabolic Syndrome
NCEP ATP III[19] recognised the metabolic syndrome as a major contributor to CVD risk beyond
raised levels of low density lipoprotein-cholesterol
(LDL-C).[19] Increased emphasis was placed on the
appropriate management of the metabolic syndrome
among patients undergoing lipid management. According to these evidence-based guidelines,[19] management of the metabolic syndrome has a 2-fold
objective: firstly, to reduce potential underlying
causes; and secondly, to treat associated non-lipid
and lipid risk factors. Clinical trials have shown that
modifying three major components of the syndrome
(atherogenic dyslipidaemia, hypertension and the
prothrombotic state) will reduce risk for CVD.[19]
Modification of impaired glucose regulation will
reduce the risk of type 2 diabetes.[27] As each independent risk factor can amplify the patient’s risk of
CVD, an integrated, multi-faceted approach is indicated for patients with the metabolic syndrome.[19]
According to the NCEP ATP III guidelines, firstline therapies for all the lipid and non-lipid risk
factors associated with the metabolic syndrome are
weight reduction and increased physical activity.
Specific emphasis on weight reduction is delayed (3
months) following an adequate trial of other dietary
measures for LDL-C lowering. The role of regular
physical activity is reinforced within the NCEP ATP
III treatment algorithm with particular attention to
Sports Med 2004; 34 (6)
382
 2004 Adis Data Information BV. All rights reserved.
Table VI. Epidemiological studies of leisure-time physical activity (LTPA)/cardiorespiratory fitness (CRF) and the metabolic syndrome (MS)
Study
Study design,
population,
demographic
characteristics
Study association(s)
MS discrete
components
Results
Ely Young Cohort
Feasibility Study
Wareham et al.[189]
Cross-sectional,
random populationbased sample
73 M, 89 F, 30–49y
Physical activity level
(total energy
expenditure) and
cardiorespiratory
fitness (submaximal
cycle ergometry), MS
components
One or more
abnormalities from:
Unadjusted odds ratio of
physical activity level:
1. quartile: 1.0
2. quartile: 0.49 (95% CI
3. quartile: 0.25 (95% CI
4. quartile: 0.33 (95% CI
Aerobics Center,
Longitudinal Study,
Dallas,Texas, USA
Whaley et al.[77]
Cross-sectional
15 534 M, 3898 F,
predominantly
Caucasian, middle/
upper SE status
Cardiorespiratory
fitness (maximal
treadmill exercise test
time), MS components
Comments
MS by
Association independent of
gender and obesity
0.14, 1.60)
0.05, 0.94)
0.08, 1.18)
IGT ≥7.8 mmol/L
TG ≥ 2.82 mmol/L
HDL-C (M) <0.91
mmol/L, (F) <1.17
mmol/L
DBP ≥95mm Hg
Unadjusted odds ratio for MS by
cardiorespiratory fitness level:
1. quartile: 1.0
2. quartile: 0.65 (95% CI 0.21, 2.00)
3. quartile: 0.36 (95% CI 0.10, 1.19)
4. quartile: 0.06 (95% CI 0.01, 0.46)
Following adjustment for sex,
obesity and measurement
error, PAL has stronger
association with MS
Three or more
abnormalities from:
WC >100cm
Age-adjusted cumulative odds ratio
for accumulated number of metabolic
abnormalities in least-fit category:
M
Low CRF (lowest 20%)
inversely associated with MS
Association with accumulated
number of metabolic
abnormalities graded across
CRF categories
TG ≥1.69 mmol/L
3.0 (95% CI 2.7, 3.4) vs moderately
fit
FG ≥6.1 mmol/L
10.1 (95% CI 9.1, 11.2) vs high fit
SBP ≥140mm Hg
F
2.7 (95% CI 2.1, 3.5) vs moderately
fit
4.9 (95% CI 3.8, 6.3) vs high fit
Cross-sectional
740 M, employed,
middle/upper SE
status
LTPA classification
and cardiorespiratory
fitness (submaximal
cycle ergometry), MS
components
Three or more
abnormalities from:
Age-adjusted odds ratio for MS by
LTPA level:
Strong association shown with
MS based on highest risk
quintiles of MS components
Continued next page
Carroll & Dudfield
Sports Med 2004; 34 (6)
Leeds Metropolitan Area,
W. Yorkshire, UK
Carroll et al.[190]
Study
Cross-Cultural Activity
Participation Study,
multicentre, USA
Irwin et al.[191]
Study design,
population,
demographic
characteristics
Cross-sectional triethnic sample
146 African
American, Native
American and
Caucasian F,
40–83y
Study association(s)
LTPA and
cardiorespiratory
fitness (maximal
treadmill exercise test
time), MS components
MS discrete
components
Results
Comments
FG ≥6.1 mmol/L
Sedentary 1.0
Strong associations evident
excluding obesity from MS
definition.
TG ≥1.7 mmol/L
Occasional/light 0.68 (95% CI 0.28,
1.59)
HDL-C <0.9 mmol/L
≥ Moderate 0.23 (95% CI 0.07, 0.93)
BP ≥140/90mm Hg
Age-adjusted odds ratio for MS by
cardiorespiratory fitness level:
BMI ≥30.0 kg/m2
1. low 1.0
2. moderate 0.31 (95% CI 0.13,
0.74)
3. high 0.16 (95% CI 0.05, 0.51)
Three or more
abnormalities from:
FI ≥173 pmol/L
FG ≥7 mmol/L
TG ≥2.26 mmol/L
HDL-C <1.16 mmol/L
BP ≥140/90mm Hg or
antihypertensive
BMI ≥30.0 kg/m2 or
WC ≥88.0cm
Adjusted (age, ethnicity, study site)
odds ratio for MS according to
moderate to vigorous intensity
(>3 METs) LTPA category (MET-min/
day):
1. 18–257; 1.0
2. 263–376; 0.76 (0.29–2.05)
3. 378–598; 0.38 (0.12–1.15)
4. 611–1351; 0.16 (0.05–0.58)
1.
2.
3.
4.
Cross-sectional
360 middle-aged M
executives, 47 ± 7y
Cardiorespiratory
fitness (maximal
treadmill time), MS
components
Three or more
abnormalities from:
Inverse associations
demonstrated for energy
expenditure in moderate
intensity (3–6 METs) physical
activity
Similar odds ratios were
observed for approximately the
same MET-min/day in
moderate to vigorous and
moderate intensity physical
activity
4.4–10.0; 1.0
10.2–13.0; 0.31 (0.07–0.63)
13.1–15.9; 0.13 (0.04–0.45)
16.1–26.0; 0.03 (0.01–0.15)
Prevalence of MS according to
maximal treadmill duration (quartiles):
Significant inverse gradient
observed for the prevalence of
MS across quartiles of
cadiorespiratory fitness
Continued next page
383
Sports Med 2004; 34 (6)
Executive Health
Programme, Mayo Clinic,
Minnesota, USA
Kullo et al.[192]
Exercise and Metabolic Abnormalities
 2004 Adis Data Information BV. All rights reserved.
Table VI. Contd
384
 2004 Adis Data Information BV. All rights reserved.
Table VI. Contd
Study
Study design,
population,
demographic
characteristics
Study association(s)
MS discrete
components
Results
Comments
FG ≥6.1 mmol/L
TG ≥1.70 mmol/L
HDL-C <1.03 mmol/L
BP ≥130/85mm Hg
WHR >0.95
1.
2.
3.
4.
Odds ratio for the prevalence
of the MS was 5.67 for
subjects in the lowest
compared with the highest
fitness quartile, after
adjustment for age and BMI
39.0%
24.0%
13.0%
4.0%
Components of MS according to
maximal treadmill duration (quartiles):
1. 2.1 ± 1.3
2. 1.6 ± 1.3
3. 1.2 ± 1.2
4. 0.9 ± 0.9
Kuopio Ischaemic Heart
Disease Risk Factor
Study, Kuopio, Eastern
Finland
Laaksonen et al.[180]
Prospective, random
age stratified sample
612 M, 42–60y
LTPA and
cardiorespiratory
˙ 2max), MS
fitness (VO
components
Adjusted odds ratio for MS according
to LTPA category:
Odds ratios for MS were not
attenuated adjusting for age,
BMI, adult SE status, smoking,
alcohol, pre-existing CVD
FG 5.6–6.0 mmol/L,
Plus two from:
TG ≥1.70 mmol/L
HDL-C <0.9 mmol/L
BP ≥140/90mm Hg or
antihypertensive
WHR >0.9 or
BMI >30.0 kg/m2
Tertiles of moderate and vigorous
LTPA (>4.5 METs, min/wk)
1. <60; 1.0
2. 61–180; 0.82 (0.48–1.38)
3. ≥180; 0.52 (0.30–0.90)
Moderate and vigorous LTPA
particularly effective in
reducing odds for MS in highrisk men
Tertiles of vigorous LTPA (>7.5
METs, min/wk)
1. <10; 1.0
2. 10–59; 0.65 (0.30–1.08)
3. ≥60; 0.37 (0.21–0.66)
Associations of LTPA but not
CRF with MS attenuated by
mediating metabolic risk
factors
Continued next page
Carroll & Dudfield
Sports Med 2004; 34 (6)
Modified WHO
definition FI (upper
25%) or
Study
Study design,
population,
demographic
characteristics
Study association(s)
MS discrete
components
Results
Comments
˙ 2max(mL/kg/min)
Tertiles of VO
1. <28.9; 1.0
2. 29.0–35.6; 0.53 (0.31–0.89)
3. ≥35.7; 0.25 (0.13–0.49)
Kuopio Ischaemic Heart
Disease Risk Factor
Study, Kuopio, Eastern
Finland
Lakka et al.[193]
Cross-sectional,
random age
stratified sample
1069 M, 42–60y
LTPA and
cardiorespiratory
˙ 2max), MS
fitness (VO
components
Modified WHO
definition:
Adjusted odds ratio for MS according
to LTPA category:
Odds ratios for MS were not
attenuated adjusting for age,
adult SE status, smoking,
alcohol
FI (upper 25%) or
FG 5.6–6.0 mmol/L,
plus two from:
TG ≥1.70 mmol/L
HDL-C <0.9 mmol/L
BP ≥140/90mm Hg or
antihypertensive
WHR >0.9 or
BMI >30.0 kg/m2
Category of total LTPA (min/wk)
1. ≥409; 1.0
2. 213–408; 1.04 (0.66–1.63)
3. <213; 1.64 (1.08–2.49)
Associations between
categories of LTPA and MS
not significant after adjustment
for BMI
Exercise and Metabolic Abnormalities
 2004 Adis Data Information BV. All rights reserved.
Table VI. Contd
Low-intensity LTPA was not
associated with the MS
Category of moderate and vigorous
LTPA (>4.5 METs, min/wk)
1. ≥180; 1.0
2. 60–179; 1.14 (0.73–1.76)
3. <60; 1.63 (1.07–2.48)
Associations of CRF with MS
attenuated by BMI, but lowest
tertiles had a significant 1.9and 3.6-fold increased
likelihood of MS compared
with highest
BMI = body mass index; BP = blood pressure; CVD = cardiovascular disease; DBP = diastolic blood pressure; F = female; FG = fasting glucose; FI = fasting hyperinsulinaemia;
HDL-C = high density lipoprotein-cholesterol; IGT = impaired glucose tolerance; M = male; MET = metabolic equivalent; PAL = physical ability level; SBP = systolic blood pressure;
˙ 2max = maximal oxygen consumption; WC = waist circumference; WHO = World Health Organization; WHR = waist-to-hip
SE = socioeconomic status; TG = triglycerides; VO
circumference ratio.
385
Sports Med 2004; 34 (6)
˙ 2max(mL/kg/min)
Tertiles of VO
1. ≥35.5; 1.0
2. 29.1–35.4; 2.79 (1.62–4.80)
3. <29.1; 6.35 (3.74–10.8)
 2004 Adis Data Information BV. All rights reserved.
Fig. 1. An evidence-based approach to medical monitoring and implementation of therapeutic lifestyle change for the metabolic syndrome.[19,194] BMI = body mass index; BP =
blood pressure; CVD = cardiovascular disease; HDL-C = high density lipoprotein-cholesterol; LDL-C = low density lipoprotein-cholesterol; PA = physical activity; TG = triglycerides;
↑ indicates increase.
• Create dietary and moderate
PA plans
• Begin dietary and PA logs
• Consider referral to dietician
• Provide metabolic
syndrome handouts
LDL-C or non-HDL-C above treatment target
• Consider LDL-C lowering medications
• Consider low-dose aspirin therapy
• Vigorous reduction in saturated fat and
cholesterol intake
• Add plant stanols/sterols
• ↑ Viscous fibre
• Avoid low total fat intake
LDL-C or non-HDL-C above treatment
target
• Consider adding LDL-C lowering
medications (esp. LDL-C >4.1 mmol/L)
• Consider low-dose aspirin therapy
BP above treatment target
• Consider anti-hypertensive
therapy
LDL-C or non-HDL-C
above treatment target
• Increase lipid-lowering
medications
No change in waist and weight, but
reduced LDL-C or non-HDL-C
• Referral to exercise specialist for
supervision and specific advice
• Exercise ECG and fitness
assessment
• Referral to dietician
No change in waist and weight, but
reduced LDL-C or non-HDL-C
• Reinforce dietary therapy and PA
• Consider referral to dietician
Medical monitoring
VISIT 4: 18 weeks
Evaluate:
• LDL-C <3.4 mmol/L
• Waist circumference
• Weight, BMI
• BP >140/90mm Hg
• Diet and exercise logs
Medical monitoring
VISIT 3: 12 weeks
Evaluate:
• LDL-C <3.4 mmol/L
• Waist circumference
• Weight, BMI
• BP <130/85mm Hg
• Diet and exercise logs
Several recent reviews[194-196] have outlined the
primacy of weight loss in the treatment of the metabolic syndrome. Indeed the impact of managing the
syndrome with diet and physical activity are often
defined in terms of the immediate effects of modest
(2.0–4.5kg) or clinically significant weight-loss as
documented in a recent primer article[197] summarised from the National Heart, Lung and Blood
Institute evidence-based report on obesity.[29] Several systematic reviewers[198] and expert panels[29]
have comprehensively examined the research evidence on the efficacy of physical activity and exercise, with and without dietary restriction, in the
treatment of adult overweight and obesity. Randomised studies of exercise intervention for the treatment of overweight show very modest weight losses
(approximately 1–2kg) independent of the effects of
dietary restriction.[198] Furthermore, evidence indicates that in most investigations, exercise does not
significantly increase initial weight losses over and
above that obtained with dietary intervention alone.
Reaven[199] has emphasised not all patients with the
metabolic syndrome are classified as overweight or
obese. Moreover, overweight/obese patients often
do not achieve therapeutic weight loss goals. Recent
consensus statements[30] and a systematic review[200]
Medical monitoring
VISIT 2: 6 weeks
Evaluate:
• LDL-C <3.4 mmol/L
• Waist circumference
• Weight, BMI
• BP <130/85mm Hg
• Diet and exercise adherence
It is now widely acknowledged[22,24,195] that for
metabolic benefits, regular exercise should be performed more frequently (3–5 days per week) and for
a longer duration (up to 60 minutes) at a lower
˙ 2max) than typintensity (approximately 40–60% VO
ically prescribed for cardiorespiratory fitness improvement. It has been suggested[22,195] that the
chronic effect of exercise on metabolic comorbidities may be largely (but not entirely) a consequence
of concomitant loss of body fat, especially of abdominal adipose tissue.
VISIT 1
• Assess overall short-term
(10y) CVD risk
• Establish LDL-C or non-HDL-C
therapy target
(TG <2.26 mmol/L)
• BP
• Diet and physical activity
assessment
• Psychological profile
its benefits for management of the metabolic syndrome. The recommendation for increased moderate
physical activity is introduced when therapeutic lifestyle change is initiated and is reinforced (with
consideration for referral to an exercise specialist for
prescription and guidance in exercise training),
when emphasis shifts to specific management of the
metabolic syndrome (figure 1).
Carroll & Dudfield
Medical monitoring
VISIT N
Continue evaluation
every 4−6mo
during 1st year;
every 6−12mo
long term
386
Sports Med 2004; 34 (6)
Exercise and Metabolic Abnormalities
substantiate the important role of exercise in the
‘mediation of a healthier bodyweight’[200] among
overweight and obese adults without excessive energy deprivation. This review will now consider the
effects of exercise training on the metabolic syndrome and its major components, namely insulin
resistance, abdominal fat accumulation, hyperglycaemia, dyslipidaemia and hypertension.
7. The Effects of Exercise Training
7.1 The Metabolic Syndrome
To date, few controlled studies have reported
concurrently the effectiveness of exercise training
alone for multiple metabolic risk factors. An early
controlled trial by Smutok and colleagues[201] compared the effects of 20 weeks of strength training to
those of aerobic training on lipoprotein-lipids, blood
pressure and insulin/glucose responses to an oral
glucose tolerance test (OGTT) in overweight sedentary males. Whilst both interventions improved glucose tolerance and reduced insulin responses to oral
glucose, there were no significant changes in lipoprotein-lipids or blood pressure. Katzel et al.[202]
examined the effects of the sequential interventions
of 9 months of aerobic exercise training followed by
weight loss (with continued training) on metabolic
risk factors in obese middle-aged and older men.
Exercise training increased maximal aerobic capacity by 14% with no significant change in
bodyweight. However, exercise training alone did
not improve oral glucose tolerance responses and
blood pressure, and there were no significant lipid
changes. In contrast, additional weight-loss intervention (without further fitness improvement) was
associated with decreased glucose and insulin responses during the OGTT (8% and 30%, respectively) and improved lipoprotein-lipids. Other studies
(reported within separate publications[203,204]) have
demonstrated that longer-term (12-month) exercise
training alone and combined with dietary intervention simultaneously markedly affected glucose-insulin, lipoprotein-lipids and blood pressure responses
in sedentary, overweight middle-aged men and
women with increased metabolic risk-factor levels.
 2004 Adis Data Information BV. All rights reserved.
387
Waist circumference reduction was a significant
predictor for beneficial changes in indexes of
haemostatic, carbohydrate and lipid metabolism,
mostly independent of physical fitness.
Dengel et al.[205] reported that 6-month aerobic
exercise and dietary restriction intervention substantially lowers blood pressure and significantly improved glucose metabolism in obese, sedentary, insulin-resistant men. The intervention reduced
bodyweight by 9%, (percentage body fat by 21%)
˙ 2max by 16%. Favourable lipoand increased VO
protein-lipid responses were also reported. Watkins
et al.[206] recently evaluated the effects of a 6-month
intervention involving aerobic exercise training
alone or exercise combined with calorie restriction
on 53 adults with metabolic syndrome characteristics (selected from within a larger randomised controlled trial). Hyperinsulinaemic responses to an
OGTT, were significantly improved with aerobic
exercise training, but not blood pressure or lipoprotein-lipid responses. In contrast, weight loss (in
the context of exercise training) appeared to be
important in improving blood pressure and dyslipidaemia.
Among 621 African American and Caucasian
sedentary participants recruited to the Health Risk
Factors Exercise Training and Genetics (HERITAGE) Family Study,[207] the prevalence of the
NCEP ATP III defined metabolic syndrome was
16.9%. The overall prevalence of the syndrome decreased to 11.8% after exercise training. Of the 105
participants with the metabolic syndrome at baseline, 30.5% (32 participants) were no longer classified as having the metabolic syndrome after the
exercise training. Among these 32 participants; 43%
decreased TGs, 16% improved high density lipoprotein-cholesterol (HDL-C), 38% decreased blood
pressure, 9% improved fasting plasma glucose, and
28% decreased their waist circumference in accordance with NCEP ATP III threshold values. There
were no sex or race differences in the efficacy of
exercise in treating the metabolic syndrome. Further
preliminary evidence of the effectiveness of intensive lifestyle intervention on the incidence of metabolic syndrome has also been shown among multiSports Med 2004; 34 (6)
388
Carroll & Dudfield
ethnic individuals (55% Caucasians, 45% minority)
with IGT participating in the US Diabetes Prevention Program (DPP) study.[208] The baseline prevalence of the metabolic syndrome (according to
NCEP ATP III criteria) was 53% among all the DPP
participants (57% among Caucasian participants).
Among the 1523 participants without metabolic
syndrome at baseline, the incidence of the syndrome
was significantly reduced by 41% in a 3-year follow-up in the intensive lifestyle intervention group
compared with placebo. In comparison, metabolic
syndrome incidence was less effectively reduced
(17%) in the participants randomised to treatment
with metformin.
7.2 Insulin Resistance
To achieve maximum benefit from modification
of multiple metabolic abnormalities, the underlying
insulin-resistant state must become a therapy target.[209] The effects of diet and exercise on insulin
resistance have been comprehensively examined
within several recent narrative[210-213] and systematic
reviews.[28] It is now well established[28,214,215] that
hypocaloric diets and bodyweight reduction improves insulin resistance. Insulin sensitivity may
improve by up to 60% with equivalent diet- or
exercise-induced weight loss (8% bodyweight)
among obese middle-aged men.[215] The improvements in insulin sensitivity after bodyweight loss
and exercise training may be partially attributable to
changes in body fat distribution, in a particularly
significant reduction in the ratio of visceral fat.[215]
Several[214-219] but not all[220] longitudinal studies
of exercise training also indicate significant improvements in measures of insulin sensitivity among
middle-aged and older adults. Increased regular exercise has also been shown to improve insulin action
in obesity without concomitant changes in weight
and/or body composition. The RCTs of Ross et
al.,[215] Dengel et al.[216] and Katzel et al.[214] have
examined the effects of exercise training on insulin
action in overweight/obese males. Within these investigations, previously overweight/obese sedentary
treated participants typically performed moderate
aerobic exercise (approximately 50–80% heart rate
 2004 Adis Data Information BV. All rights reserved.
reserve) over periods of 3–10 months. Supervised
exercise was performed for a minimum of three
sessions per week up to daily, with session durations
ranging from 15–60 minutes. Ross et al.[215] showed
that 3 months of exercise training without weight
loss in obese males was associated with a 30%
improvement in insulin sensitivity compared with
no treatment control. Dengel et al.[216] reported significant increases in insulin-mediated glucose disposal rates as measured by the hyperinsulinaemic euglycaemic clamp with exercise training that was significantly greater than control. Within this and other
investigations,[214,216] insulin areas under the OGTT
curve were significantly reduced among overweight
and obese males (from –8 to –19%) with no significant changes in glucose responses. Among 53 men
and women with a clustering of metabolic syndrome
characteristics,
hyperinsulinaemic
responses
(2-hour insulin concentrations) to glucose challenge
were significantly reduced (27%) in an exerciseonly treatment group compared with controls.[206]
Davey et al.[217] reported the effects of 3 months
supervised exercise training (three half-hour ses˙ 2max)
sions of interval walking/jogging (65–75% VO
plus one supervised aerobic circuit training session
on insulin resistance among sedentary overweight
European and South Asian males and females with a
high insulin-resistance index. Exercise without
weight change significantly improved insulin sensitivity (by 40%) among participants in whom it was
determined within 24 hours of the last exercise
session, but not at 5 days. A 3-month trial of intensive lifestyle intervention[218] (including 5 weekly,
20-minute exercise sessions at 80–90% age-predicted maximum heart rate) attaining below clinically
recommended weight-loss (3–4% bodyweight), also
showed significantly greater improvement in insulin
sensitivity than modest lifestyle changes among
overweight
insulin-resistant
normoglycaemic
adults. It is unclear from this report[218] how long
after the last exercise session the euglycaemic insulin clamps were performed. Among sedentary, overweight/obese individuals participating within the
Studies of a Targeted Risk Reduction Intervention
Through Defined Exercise (STRRIDE) study[219] all
Sports Med 2004; 34 (6)
Exercise and Metabolic Abnormalities
the exercise groups (low volume/moderate intensity
˙ 2peak});
[40–55% peak oxygen consumption {VO
˙ 2peak) and
low volume/high intensity (65–80% VO
˙ 2peak)] sighigh volume/high intensity (65–80% VO
nificantly increased insulin sensitivity compared
with controls. The relative improvement the insulin
sensitivity index (derived from the intravenous glucose tolerance test) in the low volume/moderate
intensity and high volume/high intensity groups
(~85%) were greater than in the low volume/high
intensity group (~40%). Thus, it appears that a wide
range of exercise intensity and volume reverses the
insulin resistance that develops within middle-aged
overweight inactive adults.
Several comprehensive reviews[181,203-209] have
considered the potential mechanisms responsible for
the improvement in insulin sensitivity with exercise
independent of weight loss, some that are illustrated
in table V.
7.3 Abdominal Adipose Tissue Accumulation
Excess fat deposition in the abdominal region is a
stronger predictor of CVD and type 2 diabetes than
overall adiposity.[29,112,141,221] As reviewed by
Despres and Marette[221] this may be explained by
the associated increase in visceral adipose tissue,
which is known to be independently associated with
insulin resistance, glucose intolerance and dyslipidaemia. Other studies highlight the metabolic
effects of other upper-body fat (truncal) deposits
including the contributions of deep subcutaneous
abdominal fat.[122,221] In clinical practice, most individuals with insulin resistance have high abdominal
fat accumulation as evaluated by waist circumference.[221] As previously outlined[222] these observations suggest that intervention strategies designed to
reduce obesity would be enhanced if abdominal fat,
in particular visceral fat accumulation, were substantially reduced.
Dietary energy restriction has been the principal
intervention strategy in attempts to reduce intraabdominal fat and most current knowledge is based
on energy-restriction studies within obese
adults.[215,222,223] It is apparent that for every kilogram of diet-induced weight-loss there is an approx 2004 Adis Data Information BV. All rights reserved.
389
imate 2–5% reduction in visceral fat. The findings of
some studies suggest that visceral fat may be preferentially depleted by weight loss, although this is less
evident among obese females.[215,222,223] Changes in
anthropometric surrogates such as waist circumference have been cited as reasonably well correlated
with corresponding changes in both abdominal and
visceral fat accumulation.[223]
Current knowledge from RCTs[29] and other nonrandomised studies among overweight/obese middle-aged and older adults[224,225] suggest that increased exercise (in the absence of weight loss) is
not associated with substantial reductions in abdominal adiposity, as determined by anthropometric
measures. However, there is evidence from RCT for
independent effects of exercise on visceral and abdominal subcutaneous adipose tissue (derived by
imaging techniques) among overweight/obese middle-aged and older individuals. As reviewed by Ross
et al.,[215,223] a limited number of RCTs have reported on exercise-induced reductions in visceral fat
among groups consuming isocaloric diets or instructed not to change dietary habits. Within one
study, an exercise-induced reduction of 8%
bodyweight (without caloric restriction) was shown
to reduce visceral fat mass by approximately
28%.[215] Reductions in total abdominal and visceral
fat accumulation among overweight post-menopausal females, have also been shown following
longer-term exercise training with modest weight
loss (0.4kg) compared with controls.[226] Several
other non-randomised studies[223] have shown that
exercise with or without weight loss in overweight/
obese individuals is associated with reductions in
both visceral and abdominal subcutaneous fat. A
long-term, moderate exercise intervention combined
with an isocaloric, low saturated fat diet and moderate exercise has been shown to substantially reduce
total abdominal adiposity among overweight adults
with IGT.[227]
7.4 Impaired Glucose Regulation
Impaired glucose regulation refers to the condition in which blood glucose levels are higher than
normal but do not meet the diagnostic criteria for
Sports Med 2004; 34 (6)
390
type 2 diabetes.[228] The condition includes the separate categories of impaired fasting glucose (IFG)
and IGT.[228,229] In the majority of cohorts investigated, IGT is more prevalent than IFG.[229] Concordance between the impaired fasting and post-prandial glucose levels appears limited. Prevalence studies
indicate that not more than 50% of individuals with
IFG exhibit IGT and a lower proportion (20–30%)
of individuals with IGT also have IFG.[229-231] Peripheral insulin resistance is most characteristic of
IGT, whilst impaired insulin secretion and suppression of hepatic glucose output are more prominent
features of IFG.[229] Both disorders are associated
with a significantly increased risk of developing
type 2 diabetes, with the highest risk among individuals exhibiting the combined condition.[229] Available evidence indicates that although both these
conditions are associated with metabolic syndrome
characteristics,[229,232,233] IGT is more strongly associated with CVD outcomes and with all-cause mortality.[234]
Five RCTs reviewed by the 1999 Obesity Education Initiative expert panel,[29] showed that weight
loss produced by lifestyle intervention improved
fasting glucose and glucose responses to oral glucose tolerance compared with controls.[29] The review of Ivy[27] suggested that exercise training has
little effect on glucose tolerance unless there is some
impaired glucose regulation at baseline. Several
RCTs[215,216,225,235-239] have shown inconsistent effects of exercise training on glucose homeostasis
among normoglycaemic overweight and obese
adults. Some[225,235,237] have shown exercise interventions, with or without weight loss, to have no
significant changes in total or incremental glucose
responses during a 2- or 3-hour OGTT compared
with controls. In contrast, weight loss induced by
dietary restriction and exercise has been associated
with a significant reduction in total glucose responses during the OGTT among obese normal glucose tolerant males.[215] Furthermore, among older
overweight individuals,[236] aerobic exercise training
(both with and without calorie restriction-induced
weight loss) resulted in significant reductions in the
incremental glucose area during the 2-hour OGTT
 2004 Adis Data Information BV. All rights reserved.
Carroll & Dudfield
compared with controls. Among sedentary, overweight, mildly hypertensive subjects[238] (some exhibiting IGT), combined exercise and weight loss
showed significant reductions in both fasting and
incremental glucose responses to OGTT compared
with an exercise only intervention. Similarly, aerobic exercise training combined with dietary-induced
weight loss[225] has also been associated with a significant reduction in fasting glucose compared with
exercise-only and control conditions.
Three major RCTs (summarised in table VII)
conducted in diverse countries, settings and incorporating various ethnic groups have confirmed that
lifestyle intervention, including regular structured
exercise can prevent or delay progression to type 2
diabetes among high-risk groups with impaired glucose regulation.[240-243] Relative reductions in the
incidence of type 2 diabetes in the intervention
groups including regular exercise ranged from 41%
to 58% compared with controls. Of note are the
changes observed within the Finnish Diabetes Prevention Study,[242] which included middle-aged
(mean age 55 years) obese individuals (mean BMI
31 kg/m2) with IGT. At 12 and 24 months, both
fasting plasma glucose and 2-hour OGTT glucose
levels decreased significantly more among the intervention subjects compared with controls. Within
this study, only 43% of intervention subjects attained the treatment goal for bodyweight reduction
(5% bodyweight loss). Among the remaining intervention-group subjects, the odds ratio for type 2
diabetes in those achieving the treatment goal with
respect to exercise was 0.2 (95% CI 0.1, 0.6) compared with those in the intervention group who
remained sedentary. The corresponding odds ratio
within the control group was 0.6 (95% CI 0.7, 1.1).
7.5 Atherogenic Dyslipidaemia: Systematic
Review and Meta-Analysis
The combination of hypertriglyceridaemia, low
levels of HDL-C and a preponderance of small,
dense LDL-C particles have been named the ‘atherogenic lipoprotein phenotype’, ‘atherogenic dyslipidaemia’ or ‘lipid triad’.[244] This dyslipidaemic
phenotype has been associated with the central comSports Med 2004; 34 (6)
Study
Study characteristics
Study design and intervention
Effectiveness of lifestyle
intervention
Study main outcomes
Da Qing IGT and
577 M and F, 45 ±
Clinics (with 5–33 IGT patients)
At 6y follow-up, estimated calorie
31%, 46% and 42% reduction in
Diabetes Study,
9.1y
randomised to diet, exercise, diet and
intake was non-significantly lower
diabetes incidence (adjusted for
China[240,241]
IGT based on single
exercise interventions or general advice
in diet and diet plus exercise
baseline characteristics) within the
OGTT (WHO 1985
(control)
groups
diet, exercise and combined groups,
criteria)
Follow up = 6y
Physical activity was significantly
respectively
Participants recruited
Analysis on 530 participants
higher than baseline in the
Lifestyle interventions were more
from 33 health clinics
Exercise treatment goals
exercise and diet plus exercise
effective in those with lower insulin
284 had baseline
Physical activity counselling to attain:
groups
resistance and higher insulin
fasting and 2h post-
30 min (mild)/20 min (moderate) or 5–10
OGTT insulin
min vigorous physical activity per day
secretion at baseline
Exercise and Metabolic Abnormalities
 2004 Adis Data Information BV. All rights reserved.
Table VII. Recent randomised controlled intervention studies in adults with impaired glucose regulation
determinations
Finnish Diabetes
522 adults (350 F),
Randomised (stratified by 2h glucose,
43% of intervention participants
Prevention Study[242]
40–64y
sex and centre) to intensive diet and
achieved weight loss >5% (at
Overall 58% reduction in risk of T2D
in the intervention group
Overweight (BMI >25)
exercise intervention or general advice
12mo) vs 13% within the control
Cumulative incidence 11% vs 23% at
and IGT (WHO 1985
(control)
group (p = 0.001)
4y
criteria from mean of 2
Treatment goals:
86% achieved >4 h/wk moderate
Incidence inversely related with
OGTTs)
5% weight loss
exercise (at 12mo) vs 71% within
degree of compliance with
Recruited from 5
total fat <30% (saturated, 10%)
the control group (p = 0.001)
intervention
moderate exercise >4 h/wk (inc.
47% achieved <30% total fat
centres in Finland
supervised circuit training)
intake (at 12mo) vs 26% within
Mean follow-up = 3.2y
the control group (p = 0.001)
Intention to treat analysis
Diabetes Prevention
3234 adults (68% F)
Randomisation stratified by centre to
50% of participants achieved
Program, USA[243]
45% non-Caucasian
placebo or metformin – both with
weight loss (at 24 wks), 38% at
reduction in incidence of T2D with
Overweight (variable
general advice or intensive lifestyle
most recent visit
intensive lifestyle intervention
BMI criteria for different
intervention
74% achieved physical activity
No significant difference between sex
ethnic groups)
Treatment goals:
goals (at 24 wks), 58% at most
or minority groups
7% weight loss
recent visit
IGT (2h post-OGTT
total fat <30% (saturated 10%)
Lifestyle more effective than
level 7.8–11.0)
moderate exercise >150 min/wk
metformin in restoring normal
Mean follow-up = 2.8y
post-OGTT glucose levels
Intention to treat analysis
BMI = body mass index; F = female; IFG = impaired fasting glucose; IGT = impaired glucose tolerance; M = male; OGTT = oral glucose tolerance test; T2D = type 2 diabetes
mellitus; WHO = World Health Organization.
391
Sports Med 2004; 34 (6)
IFG 5.3–6.9
Compared with placebo: 58%
392
ponents of the metabolic syndrome, namely, impaired insulin-mediated glucose disposal[245,246] and
abdominal fat accumulation.[10,244,247]
It has been proposed that an impaired systemic
antilipolytic action of insulin and increased systemic
free fatty acid flux underlie the association between
intra-abdominal
fat
and
insulin
resistance.[29,195,200,248,249] Intra-abdominal fat is relatively insensitive to insulin and has a high lipolytic
activity, partly due to its complement of adrenergic
receptors.[29,109,249] The often-coexistent features of
hyperinsulinaemia and increased non-esterified free
fatty acid levels affect several interconnected steps
in lipoprotein-lipid metabolism.[250] Both features
appear to contribute to increased TG-enriched lipoproteins in the circulation, particularly post-prandially.[250,251] Laws[250] and others[33,251] have reviewed
recent advances in the understanding of these complex associations, which may include:
• Relative deficiency of post-prandial lipoprotein
lipase activity and higher hepatic lipase activities
resulting in a reduced clearance of fasting and
post-prandial TG-rich lipoprotein particles.
• A prominent role for increased cholesteryl-ester
transfer protein activity (with increased neutral
lipid transfer between very low density lipoprotein [VLDL] and other lipoprotein particles)
leading to low HDL-C concentrations (especially
the cardioprotective HDL2 subfraction) and increased atherogenic small, dense LDL particles.
• Increased fractional catabolic rate of apolipoprotein A-I contributing to lower HDL-C.
Whilst narrative reviews have been supportive of
favourable effects of exercise training on TGs within the context of the metabolic syndrome,[22,23]
others,[21,24,25] especially those confined to RCTs,[26]
have provided only limited evidence to support a
specific role for exercise training in improving undesirable lipoprotein levels in overweight adults.
Eriksson et al.[24] indicated that there was some
uncertainty regarding the independent associations
between exercise training and dyslipidaemia. The
addition of exercise training to a hypocalorific, reduced-fat diet in overweight/obese adults (weightloss >4.5kg) generally improves HDL-C and TG
 2004 Adis Data Information BV. All rights reserved.
Carroll & Dudfield
levels, although evidence remains limited in individuals with dyslipidaemias, especially females.[26] An
earlier comprehensive narrative review of Buemann
and Tremblay[22] suggested that although exercise
training studies resulted in smaller weight loss than
energy restriction programmes of similar length,
they may be equally potent in reducing TGs and
increasing HDL-C among overweight individuals.
Clearly, further evidence-based data for exercise
benefits on dyslipidaemia are required, given the
early treatment recommendations for moderate exercise among individuals with the metabolic syndrome.
Limited data are available concerning the effects
of exercise training on lipoprotein-lipids among individuals with the metabolic syndrome, probably
due to its lack of precise definition.[24] For the purposes of this review, we have evaluated the RCT
data on the effects of physical activity/exercise
training alone on overweight/obesity related dyslipoproteinaemias (specifically low HDL-C and high
TGs) characteristic of the metabolic syndrome in
adult men and women. An English language literature search from 1987 to the end of 2002 was
conducted via MEDLINE (National Library of
Medicine, Bethesda, Maryland, USA). The following key words were used alone or in various combinations for computer searches: physical activity,
exercise, lipids and lipoproteins. The reference lists
from original and review articles were also reviewed
to identify other relevant studies. This search
method included an expert panel obesity treatment
evidence report,[29] previous systematic reviews[252,253] and meta-analysis[254] of responses of
blood lipids and lipoproteins to exercise training
alone or combined with dietary intervention.
The inclusion criteria for this review were as
follows:
• Published randomised trials that included a comparative non-exercise control group.
•
Overweight/obese participants (BMI ≥24.9 kg/
m2 or above average/at-risk body fat content[255,256]), sedentary or relatively inactive
adults, with no evidence of CVD or type 2 diabetes.
Sports Med 2004; 34 (6)
Exercise and Metabolic Abnormalities
65 potentially relevant RCTs
identified and screened for retrieval
23 RCTs retrieved for
more detailed examination
393
42 RCTs excluded
n = 26 normolipidaemic
n = 5 isolated low HDL phenotype
n = 5 missing HDL or TG data
n = 2 resistance training only
n = 1 duplicate study
n = 1 non-eligible study duration
n = 1 included CHD/T2D
n = 1 type IV hypertriglyceridaemic
7 RCTs excluded
n = 7 studies combining exercise
training with caloric restriction
and/or dietary modification
16 potentially appropriate RCTs
to be included in the meta-analysis
1 RCT excluded
41−46% individuals regularly engaged
in sport activities at baseline
15 RCTs included in the meta-analysis
Fig. 2. Systematic review and meta-analysis profile summarising trial flow. CHD = coronary heart disease; HDL = high density lipoprotein;
RCT = randomised controlled trial; T2D = type 2 diabetes mellitus; TG = triglycerides.
•
Physical activity interventions and exercise training studies reporting follow-up data between 12
and 52 weeks.
• Evidence of dyslipidaemia on baseline examination, with mean levels of TG and HDL-C approaching or consistent with recent NCEP ATP
III guidelines[19] for the diagnosis of the metabolic syndrome.
The systematic review trial flow chart is illustrated in figure 2. A total of 65 RCTs investigating
exercise training on blood lipoprotein-lipids were
identified within this literature search. All 65 RCTs
were examined against the study selection criteria.
Forty-two RCTs were excluded at this stage of the
review. The main reasons for exclusion of studies
were normal mean baseline lipoprotein-lipids, an
isolated low HDL-C phenotype and incomplete data
reported to ascertain a combined dyslipidaemic phenotype (HDL-C and TG). A total of 23 randomised,
controlled, parallel-design trials met the study selection criteria in that they assessed the effect of physical activity/exercise intervention on lipoproteinlipids in sedentary, overweight/obese individuals
 2004 Adis Data Information BV. All rights reserved.
with dyslipidaemia. Seven studies examined the
combined effects of exercise training with energy
restriction and/or dietary modifications. For the purposes of this review, detailed consideration will only
be given to 15 clinical trials[214,237,257-269] (incorporating 20 study groups) evaluating the effects of
physical activity/exercise intervention alone on lipoprotein-lipids. One RCT[270] was excluded as a large
proportion of the participants were classified as
physically active at baseline. The characteristics of
the included studies are presented in table VIII.
One author (Carroll) extracted information on
sample size, participant characteristics, intervention
characteristics and treatment results. As recommended for continuous data,[271,272] the weighted mean
difference (WMD) method was used for primary
analyses. Five RCTs[237,259,260,262,265] reported mean
change data (± standard deviation or standard error)
for lipoprotein-lipids and one recent investigation[269] provided unpublished mean change data. To
avoid the potential bias from using only six trials,
change scores were calculated for eight studies[257,258,261,263,264,266-268] by subtracting the mean end
Sports Med 2004; 34 (6)
394
 2004 Adis Data Information BV. All rights reserved.
Table VIII. Characteristics of included randomised controlled exercise intervention trials
Study
Kiens et
n
al.[257]
Juneau et al.[258]
48
57
Characteristics of
participants
M, aged 30–44y,
12 wks
sedentary, 62%
Supervised exercise, including swimming, running and
non-smokers
other indoor/outdoor activities
˙ 2max, 45 min, 4 × per wk
80% VO
M, aged 40–60y,
6mo study
sedentary, 81%
Home-based walking and slow jogging programme,
˙ 2max, 40–50 min, 5 × per wk
50–66% VO
non-smokers
Wood et al.[259]
88
Description of reported exercise programme (type,
intensity, duration and frequency)
M, aged 39–59y,
12mo study
overweight, non-
Supervised walking and jogging programme, 60–80%
smokers
MHR, 40–50 min, 3 × per wk
Estimated exercise volume (MET min)
estimated (METs)
session (MET min)
wk (MET min/wk)
8.6
389
1010
5.1
230
1150
5.6
251
1255
Unsupervised exercise 2 × per wk
King et al.[260]
168
M, aged 50–65y,
12mo study
5.7a
226
678
sedentary, 81%
Supervised and home-based exercise groups (mainly
4.4b
132
661
non-smokers
walking and/or jogging programmes), 2 intensities (high
3.3
116
578
5.8
347
1040
73–88% PHR/low 60–73% PHR); 30–40 min, 3–5 × per
wk
Nieman et al.[261]
Anderssen et
al.[262]
30
92
F, aged 67–85y,
3mo study
sedentary, non-
Supervised brisk walking programme, 60% HRR, 30–40
smokers
min, 5 × per wk
M and F (n = 21),
12mo study
aged 40y,
Supervised aerobic exercise (aerobics, circuit-training,
sedentary,
brisk walking and jogging programme, 60–80% PHR,
overweight,
60 min, 3 × per wk
normal or diastolic
hypertension
Continued next page
Carroll & Dudfield
Sports Med 2004; 34 (6)
dyslipidaemic, high
Study
Katzel et
n
al.[214]
Ready et al.[263]
67
25
Characteristics of
participants
Description of reported exercise programme (type,
intensity, duration and frequency)
Estimated exercise volume (MET min)
estimated (METs)
session (MET min)
6.0
212
635
4.4
264
1320
2.5
152
456
12mo study
6.9
411
1234
F, post-
Supervised aerobic exercise (brisk walking jogging)
4.7
284
853
menopausal, aged
programme, 60–80 MHR, 60 min, 3 × per wk
45–64y
(supplemented with home-based activities as required)
M and F (approx.
24mo study – 12mo data utilised
3.3c
181
903c
80% F), aged
Brisk walking, 50–60 min, 1–2 × per wk (wks 1–10)
M, aged 46–80y,
9mo study
obese, sedentary,
Supervised stationary cycling programme, 70–80%
non-smokers
HRR, 45 min, 3 × per wk
F, mean age 62y,
6mo study
post-menopausal,
Walking, 54% HRR, 60 min, 5 × per wk (1–2
sedentary, non-
supervised sessions)
wk (MET min/wk)
smokers, mildly
Exercise and Metabolic Abnormalities
 2004 Adis Data Information BV. All rights reserved.
Table VIII. Contd
hyperlipidaemic
Erikkson et al.[264]
14
M and F (n = 7),
6mo study
mean age 60y,
Supervised aerobic endurance, 60% MHR, 60 min, 1 ×
impaired glucose
per wk
tolerance with
Home-based exercise (walking, jogging, swimming,
family history of
cycling), 60–90 min, 2 × per wk
T2D
Stefanick et al.[237]
93
M, aged 30–64y,
high LDL-C, low
HDL-C
88
Wing et al.[265]
57
Home-based walking, 4.8km (3 miles), 5 × per wk
overweight with
Unspecified periodic participation in other aerobic
family history of
activities
T2D
Continued next page
395
Sports Med 2004; 34 (6)
40–55y,
396
 2004 Adis Data Information BV. All rights reserved.
Table VIII. Contd
Study
Kokkinos et
n
al.[266]
34
Characteristics of
participants
Description of reported exercise programme (type,
intensity, duration and frequency)
M African-
4mo study
Americans,
Stationary cycling, 60–80% MHR, 20–50 (mean 44)
35–76y, sedentary,
min, 3 × per wk
Estimated exercise volume (MET min)
estimated (METs)
session (MET min)
wk (MET min/wk)
4.0
174
522
4.3
194
970
5.86
268
1020
non-smokers,
history of essential
hypertension with
anti-hypertensive
medication
Lavrencic et al.[267]
29
M, aged 40–60y,
3mo study
non-smokers,
Supervised cycle ergometry programme, up to 80%
diagnosed with
MHR, 30 min, 3 × per wk
metabolic
syndrome
Nieman et al.[268]
43
F, overweight and
3mo study
obese, aged
Four supervised aerobic exercise sessions (walking/
25–75y, limited
running) per wk. One unsupervised walking session per
moderate to
wk
vigorous exercise
Progressive exercise up to: 70–85% MHR, 45.0 min per
habits, non-
session
smokers
Kraus et al.[269]
84
M and F, aged
6mo study
40–65y, sedentary,
Supervised aerobic exercise (treadmill walking/running,
overweight or
stationary cycling, elliptical training)
mildly obese,
dyslipidaemic
× per wk, 174 ± 35 min/wk (45.8 min per session)
Continued next page
Carroll & Dudfield
Sports Med 2004; 34 (6)
˙ 2max, 3.8 ± 0.7
High amount, high intensity: 65–80% VO
High-intensity group.
Low-intensity group.
Estimated from brisk walking pace.
a
b
c
n
Study
Table VIII. Contd
743
218
 2004 Adis Data Information BV. All rights reserved.
F = females; HDL-C = high density lipoprotein-cholesterol; HRR = heart rate reserve; LDL-C = low density lipoprotein-cholesterol; M = males; MET = metabolic equivalent; MHR =
˙ 2max = maximum oxygen consumption.
maximum heart rate; PHR = peak heart rate; T2D = type 2 diabetes mellitus; VO
0.6 × per wk, 176 ± 36 min/wk (52 min per session)
˙ 2max, 3.4 ±
Low amount, moderate intensity: 40–55% VO
4.2
714
238
session (MET min)
estimated (METs)
6.1
× per wk, 117 ± 26 min/wk (39 min per session)
˙ 2max, 3.0 ± 0.5
Low amount, high intensity: 65–80% VO
397
Characteristics of
participants
Description of reported exercise programme (type,
intensity, duration and frequency)
Estimated exercise volume (MET min)
wk (MET min/wk)
Exercise and Metabolic Abnormalities
study score from that at baseline. Estimated variances for each study group (exercise and control
study groups) were calculated from variances reported at baseline and end study values using previously developed methods.[273] A correlation coefficient of 0.5 was assumed between the baseline
and end study lipoprotein lipid values and equal
variances during the trial between intervention and
control groups. In one study,[214] change scores had
to be calculated from a graphical presentation of
relative changes (post-intervention to pre-intervention values.
The assessment of the methodological quality of
controlled trials is considered a routine procedure in
a meta-analysis.[274] The quality of the RCTs included in this review were not assessed by assigning a
quality scoring system as this has been regarded as
problematic.[275] Rather, the influence of key components of methodological quality,[275] such as generation of treatment allocation and handling of attrition in the analysis, are shown individually for each
of the studies (table IX).
Pooled effect sizes were calculated by assigning
weights equal to the inverse of the total variance for
net changes in lipoprotein-lipids. For studies that
included multiple outcomes because of more than
one exercise study group,[260,269] net changes versus
the control group were treated as independent data
points. Meta-analysis was facilitated by Stats Direct,
using the following methods. The pooled mean effect size estimate (d+) is calculated using direct
weights defined as the inverse of the variance of d
for each study. An approximate confidence interval
for d+ is given with a Chi-square statistic and
probability of this pooled effect size being equal to
zero.[276] Standardised mean differences were also
evaluated. For estimating the standardised mean difference, Stats Direct uses g (modified Glass statistic
with pooled sample standard deviation) and the unbiased estimator d.[276] For each study, Stats Direct
gives g with an exact confidence interval and d with
an approximate confidence interval. An iterative
method based on the non-central t distribution is
used to construct the confidence interval for g.[275]
Sports Med 2004; 34 (6)
398
Carroll & Dudfield
Table IX. Mean baseline anthropometric and metabolic characteristics in the male-only, combined male/female and female-only study
groups within selected randomised controlled trials of exercise training
Anthropometric and metabolic variables
Male only
(max. n = 9)
Male/female
(max. n = 5)
Female only
(max. n = 4)
mean
SD
mean
SD
mean
SD
BMI (kg/m2)
29.12
1.78
30.06
3.28
28.90
3.11
Total cholesterol (mmol/L)
5.60
0.40
5.99
0.55
5.42
0.58
LDL-C (mmol/L)
3.74
0.31
3.55
0.55
4.00
0.52
HDL-C (mmol/L)
1.087
0.14
1.128
0.01
1.233
0.10
Non HDL-C (mmol/L)
4.52
0.37
4.58
0.71
4.94
0.46
Triglyceride (mmol/L)
˙ 2max (mL/kg/min)
VO
1.60
0.25
2.04
0.80
1.79
0.15
31.41
4.87
27.28
5.88
23.33
3.51
Total number of participants
574
247
186
BMI = body mass index; HDL-C = high density lipoprotein-cholesterol; LDL-C = low density lipoprotein-cholesterol; max. = maximum;
˙ 2max = maximum oxygen consumption.
VO
Heterogeneity of net study group changes in lipoprotein-lipids was examined using the formal Q
statistic and a p-value of <0.10, since the Q statistic
tends to have low power as a strict test of homogeneity.[277] A test for heterogeneity examines the null
hypothesis that all studies are evaluating the same
effect. The formal Q statistic was used in conjunction with other proposed methods (I2) for assessing
heterogeneity.[278] Fixed-effects models were used
exclusively in the absence of significant heterogeneity.
The semiquantitative funnel plot approach was
utilised to examine potential publication bias (the
tendency for studies that yield statistically significant results to be submitted and published). A funnel plot normally relates each study groups sample
characteristics to their point estimates.[279,280] Publication bias was also examined using a recently developed test for asymmetry of the funnel plot.[281]
This is a test for the Y intercept = 0 from a linear
regression of normalised effect estimate (estimate
divided by its standard error) against precision (reciprocal of the standard error of the estimate)
weighted by the reciprocal of the variance of the
estimate. Stats Direct provides this bias indicator
method (in conjunction with Kendall’s method)
with all meta-analyses. Begg and Mazumdar[282]
proposed testing the interdependence of variance
and effect size using Kendall’s rank correlation
method.
 2004 Adis Data Information BV. All rights reserved.
The general characteristics of the included studies are shown in table VIII. Ten study
groups[214,237,257-260,266,267] comprised of only male
participants, six study groups[262,264,265,269] included
mixed sexes and there were four female-only study
groups.[237,261,263,268]
Overweight/obesity[214,259,261,262,265,268,269] and/or
sedentary status[214,257-263] were primary recruitment
criteria in most trials. Other primary recruitment
criteria in several studies related to concomitant
metabolic abnormalities, including mild to moderate
dyslipidaemia,[269] IGT,[264] high normal blood pressure or hypertension,[266] hyperlipidaemia,[237,262]
multiple metabolic abnormalities[262,267] and family
history of type 2 diabetes.[264,265] The mean age of
the participants, from studies that provided such
information, was 51.8 (±8.1) years. Older participants (>60 years) were represented in one study,[261]
with post-menopausal females specifically recruited
in two other investigations.[237,263]
The trials included a total of 1007 participants.
Female-only study groups included 186 participants. Mixed sex study groups included 247 participants, with the male/female breakdown unspecified
in several investigations. Only two studies reported
recruiting non-Caucasian adults.[266,269] Within the
trials, 587 participants were randomised to exercise
interventions and 420 to control groups. The mean
number of participants within the exercise intervention and the control groups were 29.4 (±14.3) and
26.3 (±13.4), respectively. Table IX summarises the
Sports Med 2004; 34 (6)
399
baseline anthropometric and metabolic characteristics of the participants. Baseline mean data appear
concordant with the designation of a sedentary, unfit, overweight/obese cohort with mild to moderate
dyslipidaemia. One trial[267] included 20 participants
on antihypertensive agents and eight participants on
hypolipidaemic agents. A further trial[266] involved
all participants (n = 34) concurrently taking antihypertensive medication. Both these studies reported no medication changes during the intervention
period. Of the studies that provided relevant information, seven specifically recruited non-smokers[258,261-263,266-268] and two others[258,260] reported
predominantly non-smoking cohorts (77–81% participants).
In general, an effect size of 0.20 is considered small using the standardised difference method.
Heterogeneity of effect size changes in lipoprotein-lipids was examined using the Q statistic. Fixed-effects models are utilised given the absence of significant
heterogeneity.
a
b
 2004 Adis Data Information BV. All rights reserved.
HDL-C = high density lipoprotein-cholesterol; LDL-C = low density lipoprotein-cholesterol.
17
0.25
–0.286 to –0.14 <0.0001 21.7
–0.21
18
0.23
–0.46, –0.21
Triglyceride
–0.326
<0.0001 22.0
0
0.55
0.027 to 0.065 <0.0001 17.6
0.046
0
0.50
0.14, 0.37
0.254
HDL-C
<0.0001 18.4
0
0.94
0.89
0.98
0.001
LDL-C
–0.118, 0.12
8.4
0.96
0
0.005
–0.07 to 0.06
9.0
0
0.91
0.29
–0.14 to 0.04
0.50
–0.178, 0.08
Total cholesterol
–0.05
8.4
0.94
0
–0.05
9.0
p-value I2
p-value Qb
95% CI
effect
size
Weighted mean difference method
I2
p-value
Qb
p-value
95% CI
effect sizea
Standardised mean difference method
Lipoprotein-lipid
Table X. Pooled estimates of effect size (approximate 95% confidence intervals) using both standardised and weighted mean difference approaches for the effects of exercise on
lipoprotein-lipids in overweight/obese adults with dyslipidaemic changes characteristic of the metabolic syndrome
Exercise and Metabolic Abnormalities
The duration of the exercise intervention ranged
from 12 to 52 weeks (median 39 weeks). The majority of the studies incorporated supervised structured
aerobic exercise programmes, including walking,
stationary cycling, swimming, jogging and/or running. Several studies[259,260,263,264,268] incorporated
1–4 weekly supervised exercise sessions supplemented by home-based activities. One trial[265] included up to two supervised exercise sessions for 10
weeks and home-based walking thereafter and a
further trial[258] had participants randomised to study
groups of home-based higher-intensity stationary
cycling and walking/jogging programmes. The exercise intensity (physiological intensity relative to
maximum) was reported for all 15 study groups.
Mean exercise intensity varied between 40% and
˙ 2max (median 64%). The estimated exer80% of VO
cise intensity as multiples of resting metabolic rate
ranged from 2.5 to 8.6 METs (median 5.1 METs).
Exercise frequency was typically 3–5 weekly sessions (median 3 sessions) with a duration of 30–60
minutes (median 45.0 minutes). The range between
single treatment groups for total exercise volume
was considerable at 450–1320 METs/min/wk. Ten
study groups reported sufficient data to further characterise the exercise dose: mean weekly energy expenditure ranged from 650 to 2095 kcal/wk (median
1600 kcal/wk).
˙ 2max in the exercise
The mean increase in VO
treatment groups with available data (n = 18) was
Sports Med 2004; 34 (6)
400
3.2 ± 1.59 mL/kg/min, with a reduction of 0.18 ±
1.27 mL/kg/min observed in the 13 control groups
(p < 0.0001). The mean percentage increase in
˙ 2max in the exercise treatment groups, adjusting
VO
for control was approximately 11.0%. The relative
˙ 2max across exercise study
improvement in VO
groups (ranging from 1 to 25%) appears entirely
consistent with other observations of changes in
cardiorespiratory fitness within eleven randomised
experimental studies of middle-aged and elderly
relatively inactive individuals.[283] Body mass
changes were reported in 12 treatment groups included in the present analysis, and three
others[258,264,267] reported BMI changes. The mean
changes in body mass consequent to exercise training were modest compared with the no treatment
control groups (–0.62 ± 1.32 versus 0.30 ± 0.69kg,
respectively; p = 0.032). Mean changes in body
mass in the exercise study groups ranged from –1.5
to 1.9kg, with the exception of the moderate weightloss (–4.0kg) induced by the long-term (12-month)
exercise training study of Wood et al.[259] These
findings are consistent with an earlier review of
RCTs showing modest benefits of exercise
(1.0–2.0kg) for weight loss.[284]
Carroll & Dudfield
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
−0.30
−0.05 0
0.20
0.45
Pooled weighted mean difference = 0.046387
(95% CI = 0.027543, 0.065231)
Table X summarises the overall results for
changes in lipoprotein-lipids for the exercise training study groups. Formal statistical tests of heterogeneity of effect size changes among study groups
(Q statistic[272]) were non-significant within all lipoprotein-lipid analyses performed. Accordingly, primary outcome results are reported using fixed-effect
models for the estimation of an overall effect size.
The summary statistics within table X are reported
using both WMD and standardised mean difference
methods.
Fig. 3. Forest plot showing a meta-analysis of pooled weighted
mean difference changes (95% CI) in high density lipoprotein-cholesterol within 20 randomised controlled exercise training study
groups. Each exercise training study group is represented by the
shaded square that corresponds to the point estimate. The horizontal line joins the lower and upper limits of the 95% CI for the
treatment effect. The area of the shaded square reflects the weight
of the study in the meta-analysis. The open diamond at the bottom
of the graph represents the pooled weighted mean difference and
95% CI for the 20 study groups, calculated using a fixed effects
model. The solid vertical line through the figure corresponds to no
effect of treatment. 1 = Keins et al.;[257] 2 = Juneau et al.;[258] 3 =
Wood et al.;[259] 4 = Nieman et al.;[261] 5 = King et al. (supervised
high-intensity group-based exercise);[260] 6 = King et al. (high-intensity home-based exercise);[260] 7 = King et al. (lower intensity homebased exercise);[260] 8 = Ready et al.;[263] 9 = Katzel et al.;[214] 10 =
Stefanick et al. (males);[237] 11 = Stefanick et al. (females);[237] 12 =
Lavrencic et al.;[267] 13 = Anderssen et al.;[262] 14 = Eriksson et
al.;[264] 15 = Kokkinos et al.;[266] 16 = Wing et al.;[265] 17 = Nieman et
al.;[268] 18 = Kraus et al. (high amount, high intensity);[269] 19 =
Kraus et al. (low amount, high intensity);[269] 20 = Kraus et al. (low
amount, moderate intensity);[269]
In the 20 study groups examining HDL-C responses to exercise training alone compared with a
no-treatment control, the pooled estimate of the
effect size (standardised difference between the
means) was small (0.255; 95% CI 0.137, 0.37) but
statistically significant (p < 0.0001). The same analyses of HDL-C change using a WMD method showed a HDL-C increase of 0.046 mmol/L (95% CI
0.27, 0.65 mmol/L; p < 0.0001). Figure 3 shows the
results from each study group for HDL-C change
(WMD point estimate and 95% CI) in response to
exercise training graphically displayed in a Forest
plot. Sensitivity analyses were performed for
changes in HDL-C, whereby the influence of each
study on the overall treatment effect was estimated
by excluding each study group in turn from the
analysis. Sensitivity analyses for HDL-C change
 2004 Adis Data Information BV. All rights reserved.
Sports Med 2004; 34 (6)
Exercise and Metabolic Abnormalities
401
using the WMD model showed homogeneity and
consistent results with statistically significant treatment effects ranging from 0.035 to 0.065 mmol/L
(all p-values < 0.001). The estimate of effect size
changes also remained robust to other sensitivity
analyses, including the removal of the female-only
study groups (effect size estimate 0.046 mmol/L
95% CI 0.066, 0.071; p < 0.0001). The effect size
estimate for the four female-only study groups was
0.052 (95% CI 0.005, 0.11; p = 0.07).
1
2
In the 19 study groups examining TG responses
to exercise training, the standardised difference between the means was also relatively small but statistically significant at –0.33 (95% CI –0.45, –0.21; p <
0.0001). The WMD method resulted in a corresponding mean TG reduction of –0.21 mmol/L
(95% CI –0.29, –0.14; p < 0.0001). Figure 4 shows
the Forest plot for TG change (WMD: point estimate
and 95% CI) in response to exercise training Sensitivity analyses for TG change using the WMD
method showed homogeneity with consistent statistically significant fixed effects ranging from –0.20
to –0.23 mmol/L (all p < 0.0001). Exclusion of the
King et al. (subgroup 2)[260] male-only study group
increased the pooled effect size by 0.02 mmol/L.
Whereas exclusion of the Kraus et al.[269] combined
male/female study group 3 (the largest point estimate) decreased the pooled effect size by only 0.01
mmol/L. The effect size also remained significant
excluding all three combined male/female study
groups of Kraus et al.[269] (WMD: –0.17 mmol/L;
95% CI –0.25, –0.09 mmol/L; p < 0.001; Q statistic,
p = 0.89). Excluding the female-only study
groups[237,261,263,268] did not effect the significance of
the pooled estimate of the treatment effect for TG
(–0.24 mmol/L; 95% CI –0.32, –0.16; p < 0.0001).
The WMD effect size for TG was not significant for
the four female-only study groups (–0.10, 95% CI
–0.27, 0.07; p = 0.26).
13
No statistically significant differences were evident for changes in total cholesterol or LDL-C concentrations in the exercise intervention compared
with control groups using both pooled estimates by
standardised mean difference or WMD methods.
WMDs between the exercise intervention and con 2004 Adis Data Information BV. All rights reserved.
3
4
5
6
7
8
9
10
11
12
14
15
16
17
18
19
−2
−1
0
1
Pooled weighted mean difference = −0.213399
(95% CI = −0.286254, −0.140545)
Fig. 4. Forest plot showing a meta-analysis of pooled weighted
mean difference changes (95% CI) in triglyceride within 19 randomised controlled exercise training study groups. Each exercise training study group is represented by the shaded square, which corresponds to the point estimate. The horizontal line joins the lower and
upper limits of the 95% CI for the treatment effect. The area of the
shaded square reflects the weight of the study in the meta-analysis.
The open diamond at the bottom of the graph represents the pooled
weighted mean difference and 95% CI for the 19 study groups,
calculated using a fixed effects model. The solid vertical line
through the figure corresponds to no effect of treatment. 1 = Keins
et al.;[257] 2 = Juneau et al.;[258] 3 = Wood et al.;[259] 4 = Nieman et
al.;[261] 5 = King et al. (supervised high-intensity group-based exercise);[260] 6 = King et al. (high-intensity home-based exercise);[260] 7
= King et al. (lower intensity home-based exercise);[260] 8 = Ready
et al.;[263] 5 = King et al. (supervised high-intensity group-based
exercise);[260] 6 = King et al. (high-intensity home-based exercise);[260] 7 = King et al. (lower intensity home-based exercise);[260]
12 = Anderssen et al.;[262] 13 = Eriksson et al.;[264] 14 = Kokkinos et
al.;[266] 15 = Wing et al.;[265] 16 = Nieman et al.;[268] 17 = Kraus et al.
(high amount, high intensity);[269] 18 = Kraus et al. (low amount,
high intensity);[269] 19 = Kraus et al. (low amount, moderate intensity);[269]
trol groups for total cholesterol and LDL-C were
–0.04 (95% CI –0.15, 0.06 mmol/L; p = 0.42 ) and
-0.005 (–0.09, 0.08 mmol/L; p = 0.90), respectively.
Empirical studies show that inadequate quality of
RCTs may distort the results from meta-analyses
and systematic reviews.[275] Table XI presents severSports Med 2004; 34 (6)
402
 2004 Adis Data Information BV. All rights reserved.
Table XI. Characteristics of methodological quality reported within selected randomised controlled trials of exercise training
Study
Randomisation
Overall subject drop-out/
exclusions
23%: 27% of subjects in
the exercise group, 13%
in the control group
Accuracy of analytical
methods
12–14h fasted blood
samples
Repeat sample 12–24h
after last exercise session
Methodological error
reported for HDL-C
Exercise frequency
compliance
NR
Keins et al.[257]
Juneau et al.[258]
NR
NR
5%: 3 subjects (2 control)
had missing lipid data
12h fasted blood samples
No QC data reported
NR
Wood et al.[259]
Sealed envelope
NR
16%: 24 subjects in total
withdrew or had
incomplete lipid data (inc.
5 subjects [10%]
randomised to exercise
intervention)
12–16h fasted blood
samples
CDC lipid standardisation
programme
No QC data reported
NR
King et al.[260]
NR
NR
15%: summary data
presented only for nonparticipation
15–18% of subjects
randomised to exercise
intervention
12–16h fasted blood
samples
CDC lipid standardisation
programme
Measures blinded to
subject assignment
Group exercise 53%
Home-based 75–79%
Adherence to exercise
intensity also reported
Nieman et al.[261]
NR
NR
6%: 2 (13%) subjects
randomised to exercise
intervention withdrew
Fasting state of subjects
not reported
CV reported for control
sera
NR
Anderssen et al.[262]
NR
NR
Intention to treat analysis
5%: 10 (5%) subjects
randomised to intervention
withdrew or were
excluded on medical
grounds
Overnight fasted blood
samples Laboratory
procedures described in
detail within earlier
publication
57–63% within
supervised/unsupervised
exercise
Katzel et al.[214]
NR
NR
31%: 52 (31%) withdrew
or had incomplete lipid
data (27% randomised to
intervention)
12h fasted blood samples
Internal standard controls
CV reported
NR
Ready et al.[263]
NR
NR
38%: 9 subjects (38%)
randomised to intervention
either withdrew or were
dropped as non-compliers
12h fasted blood samples
Mean of two separate day
samples for baseline
lipids
No QC data reported
17.5 (73%) of supervised
sessions completed
Good compliance with
overall walking
programme
Continued next page
Carroll & Dudfield
Sports Med 2004; 34 (6)
NR
Study
blinding
NR
Study
Randomisation
NR
Study
blinding
NR
Overall subject drop-out/
exclusions
0%: all subjects
completed study
Accuracy of analytical
methods
12h fasted blood samples,
repeat sample 5d after
last exercise session
No QC data reported
Exercise frequency
compliance
90% supervised sessions
Eriksson et al.[264]
Stefanick et al.[237]
Efron procedure
NR
3%: not more than 3
subjects randomised to
intervention or control
group (4% males, 2%
females)
Lipoprotein-lipids: mean of
two 12h fasted samples
No QC data reported
QC data within CDC Lipid
Standardisation
Programme limits
NR
Wing et al.[265]
NR
NR
22%: 34 (22%) subjects
withdrew (inc. 20% of
subjects randomised to
intervention groups)
Fasting state of subjects
not reported CDC
approved lipid laboratory
No QC data reported
16% in the exercise
condition at 12mo
(56% at 6mo)
Kokkinos et al.[266]
NR
NR
6%: 2 subjects excluded
(both randomised to
exercise intervention
group)
3 non-completers (1
randomised to exercise
intervention)
12h fasted blood samples
24h after last exercise
session
Intra- and inter-assay CV
reported
NR
Lavrencic et al.[267]
NR
NR
3%: 1 subject withdrew
(randomised to exercise
intervention)
12h fasted blood samples,
3–7d after last exercise
session
86% supervised exercise
sessions
Nieman et al.[268]
NR
NR
0%: all subjects
randomised appeared to
complete study
(11 of 102 subjects did
not comply with research
design)
Fasting state of subjects
not reported National
clinical laboratory attaining
standardisation guidelines
for precision and accuracy
83% supervised exercise
sessions
Overall 95% for all
sessions
Kraus et al.[269]
Computer generated blocked
randomisationa
Yes
Intention to treat analysis
30.2% subjects withdrew
from the study
33–46% subjects
randomised to exercise
intervention
15 subjects (9.4%) had an
excessively low rate of
adherence to exercisea
Fasted blood samples
No QC data reported
Lipid profiling by NMR
spectroscopy verified by
differential
ultracentrifugation
86.8–92.1% supervised
exercise sessions
Exercise and Metabolic Abnormalities
 2004 Adis Data Information BV. All rights reserved.
Table XI. Contd
No QC data reported
Provided by investigators.
CDC = Centre for Disease Control; CV = coefficient of variation; HDL-C = high density lipoprotein-cholesterol; NMR = nuclear magnetic resonance; NR = not reported; QC = quality
control.
403
Sports Med 2004; 34 (6)
a
404
 2004 Adis Data Information BV. All rights reserved.
a
0.00
0.04
Standard error
Trials frequently omitted important information
on the influence of other aspects of methodological
quality. Six trials[214,237,258,259,261,266] failed to provide
any information relating to exercise compliance.
Within the trials that provided such information,
reported adherence rates within the exercise intervention study groups (defined as percentage of exercise sessions attended) varied considerably from 16
to 92%. Five studies reported exercise compliance
rates >75%[260,264,267-269] but only one had a duration
of >6 months.[260] Several reviews[253,254] have commented on the difficulty in separating the effects of
exercise training from changes in body composition
and dietary habits. Only six trials within this analysis[214,258,260,263,268] measured body composition
changes using criterion methods (hydrostatic weighing, dual energy x-ray absorptiometry [DEXA], total body potassium) or reported assessment of dietary intake.[237,261,262,265,268,269] Few investigations reported other aspects of good methodology such as
the mean of separate day lipid samples,[237,263] or
reporting sampling time after last exercise session.[257,264,266,267] Quality control data for biochemical methods was specifically reported within
five studies[214,261,266,269] with four others referring to
participation with lipid standardisation programmes[237,260,265] or published methods within an earlier
report.[262] The above methodological disparities resulted in RCTs of variable quality.
The present meta-analysis is notable in that there
is statistical homogeneity of lipid responses between
the exercise intervention study groups. This may be
attributable to the relative similarity in subject characteristics and that only interventions of exercise
training were included. The homogeneity of lipid
responses may be viewed as an asset in deriving
conclusions about the effect of exercise-only interventions in obesity-related dyslipidaemia. Critical
examination for the presence of publication and
related biases has been cited as an essential part of
meta-analytical studies.[272] Of the 20 study groups
0.08
0.12
0.16
−0.3
−0.1
0.1
0.3
0.5
b
50
40
Precision
al characteristics of methodological quality for the
studies included within the meta-analysis. Three
studies reported or provided information on the
method of random assignment of study participants[237,259,269] and two performed an intention-totreat analysis.[262,269] All studies provided sufficient
information to evaluate loss to follow-up of randomised participants (comprising participant drop-out,
removal for non-compliance or incomplete participant data). Only one small trial[264] (n = 14) included
all randomised participants within the final analysis.
Overall loss to follow-up ranged from 3 to 38%
within
the
study
groups,
with
seven
trials[214,257,259,260,263,265,269] showing a patient attrition ≥15% in the exercise intervention group.
Carroll & Dudfield
30
20
10
0
−1.0
−0.6
−0.2
0.2
0.6
1.0
1.4
Effect size
Fig. 5. Funnel (bias detection) plots showing 20 individual (a) study
standard errors (scale reversed) and (b) study precision, against
the weighted mean difference effect estimate with 95% CI for high
density lipoprotein-cholesterol (HDL-C). HDL-C statistical bias indicators: from regression of normalised effect vs precision (Egger et
al.[274]): intercept (0 if unbiased) = –0.092917 (approximate 95% CI
= –1.090422, 0.904587), p = 0.847. From Kendall’s test on standardised effect vs variance (Begg and Mazumdar[282]): tau = 0.231579,
p = 0.165.
Sports Med 2004; 34 (6)
Exercise and Metabolic Abnormalities
These findings provide further evidence for a
specific role of regular moderate to moderatelyvigorous exercise training in improving the dyslipoproteinaemia (high TG, low HDL-C) most commonly associated with the metabolic syndrome. In
their quantitative analysis, Durstine et al.[252] indicated that exercise training studies are often effective in raising mean HDL-C levels by 0.05–0.21
mmol/L (4–22%), and lowering TG levels by
0.01–0.43 mmol/L (4–37%). The above review[252]
indicated that the effect of exercise training on
HDL-C is likely to be relatively small in obese
individuals with low baseline HDL-C levels. In contrast, the review indicated that raised baseline TG
levels did not appear to adversely impact on TG
responses to exercise training; although inverse relationships were reported for overall adiposity and
central fat distribution.[252] In agreement with these
findings, our estimated mean increase in HDL-C of
0.046 mmol/L (or 4.1%) among overweight/obese
dyslipidaemic subjects is modest and at the lower
end of the expected range. A similar mean HDL-C
 2004 Adis Data Information BV. All rights reserved.
a
Standard error
0.0
0.2
0.4
0.6
−2
−1
1
0
b
13
10
Precision
included within this review, only five trials reported
a significant decrease in fasting TG[257,259,262,263,269]
and three trials[257,259,269] reported a significant increase in HDL-C compared with controls. The publication of several studies with non-significant lipoprotein-lipid changes in response to exercise training does not suggest that publication bias is likely to
be problematic. Skewed and asymmetrical inverted
funnel plots (scatterplots of treatment effect estimates against measures of sample size) may indicate
publication bias or exaggerated responses due to
methodological issues.[272] The funnel plots with
respect to effect size changes for HDL-C and TG
responses to exercise training do not show marked
asymmetry (figure 5 and figure 6) and complimentary statistical bias indicators were not significant.
Examination of the plot for HDL displays some
asymmetry, notably the higher quality trial of Wood
et al.[259] displays a relatively large treatment effect
(figure 5). However, interpretative caution is urged
in that the above analyses are based in the context of
a limited number of homogeneous small study
groups.
405
7
4
1
−3
−2
−1
0
1
2
Effect size
Fig. 6. Funnel (bias detection) plots showing 19 individual (a) study
standard errors (scale reversed) and (b) study precision, against
the weighted mean difference effect estimate with 95% confidence
intervals for triglyceride. Triglyceride bias indicators: from regression of normalised effect vs precision (Egger et al. [274]): intercept (0
if unbiased) = –0.342292 (approximate 95% CI = –1.724899,
1.040316), p = 0.6082. From Kendall’s test on standardised effect
vs variance (Begg and Mazumdar[282]): tau = –0.005848, p = 0.945.
increase of 4.6% was reported within a recent
systematic review of diverse exercise training studies in which dietary habits were not simultaneously
treated.[253] In the present analysis, the reduction in
TG responses to exercise training were estimated to
be somewhat higher (12%). Our estimates of HDLC and TG change with exercise training are similar
to those reported within an earlier meta-analysis of
randomised controlled exercise trials incorporating
heterogeneous study groups.[254] Subgroup analysis
within 476 hyperlipidaemic subjects showed a
weighted mean reduction in TGs of 0.15 mmol/
L.[254] Moreover, our findings are in general agreeSports Med 2004; 34 (6)
406
ment with responses to exercise training noted
among overweight, sedentary Caucasian men exhibiting the hyperinsulinaemic, high TG/low HDL-C
phenotype.[285] These participants showed a significant increase in HDL-C (4.9%) and concomitant
reduction in fasting TG (–15%) with exercise training.
The present meta-analysis also provides further
evidence showing that weight loss is not necessary
for exercise training to have favourable effects on
HDL-C and TG levels. Wood et al.[259] illustrated
within their investigation that changes in body fat
mass were responsible for the observed effects on
HDL-C. Thus, exercise training studies that achieve
a sizeable weight loss, even without restricted energy intake, are likely to have an increased effect on
HDL-C. Durstine et al.[252] reported that for most
individuals, the positive effects of regular exercise
are exerted on blood lipids at low training volumes,
with frequent increases in HDL-C in both sexes and
reductions in TG in males commonly associated
with training volumes eliciting energy expenditures
of 1200 kcal/wk. With the exception of two study
groups of middle-aged African-American hypertensive males[266] and elderly females[261] most trials
included in the present analysis accrued a weekly
energy expenditure approximating or exceeding the
above threshold. As previously indicated,[252] the
exercise training study groups with weekly energy
expenditures at the upper end of the observed range
tended to have the most favourable treatment effect
sizes for HDL-C and TG. The STRRIDE study[269]
also showed significant beneficial effects of exercise volume on HDL-C and TG (within the moderate- to high-intensity range, approximately 4–6
METs), with minimal weight change, in overweight
subjects with mild-to-moderate dyslipidaemia.
Our findings are consistent with other systematic
reviews[26,253] showing that exercise training, more
often than not, does not alter total cholesterol and
LDL-C concentrations. (table X displays mean
changes in total cholesterol and LDL-C). The present analysis is notable in that it contains studies in
which there is no concomitant reduction in fat intake
or substantial changes in body composition. The
 2004 Adis Data Information BV. All rights reserved.
Carroll & Dudfield
systematic review of Leon and Sanchez[253] showed
that exercise training (in the absence of simultaneous dietary intervention) resulted in mean reductions of total cholesterol and LDL-C of 1% and 3%,
respectively. Exercise-induced and diet-induced
weight loss produce comparable mean changes in
the mass of small LDL and in LDL peak particle
diameter.[286] It had previously been reported that
changes in LDL subfraction distribution may be
dependent on weight loss.[287] Alternatively, the STRRIDE study[269] has demonstrated that both moderate- and high-intensity exercise, even in the absence
of clinically significant weight reduction, can reduce
the concentration of small LDL and LDL particles
and increase the mean LDL particle size, without
changing LDL-C concentration.
Stefanick[26] has reported that RCT data strongly
suggest that the addition of exercise to a weightreducing and/or fat-reduced diet improves HDL-C
and TG in normolipidaemic adults. The reduction in
elevated LDL-C, a primary treatment goal for the
metabolic syndrome,[18] was reported as less consistent within overweight and obese adults. However,
within a separate meta-analysis of combined exercise and dietary studies, we have recently demonstrated significant improvements in all aspects of the
lipoprotein-lipid profile among overweight/obese
dyslipidaemic adults treated with supervised exercise and a hypocalorific and/or fat reduced diet
(Carroll and Dudfield, unpublished data).
In summary, longer term regular supervised exercise training of a moderate to moderately vigorous
intensity, even in the absence of clinically significant weight loss (<5% bodyweight), is associated
with modest improvements in the dyslipidaemic
profile, by raising HDL-C and lowering TG among
middle-aged and older overweight/obese adults.
However, as highlighted in previous reviews,[22] exercise alone may not always be sufficient to normalise the atherogenic dyslipidaemia associated with
the metabolic syndrome.
7.6 Hypertension
Hypertension has been well established as a metabolic disorder.[114] Approximately one-quarter to
Sports Med 2004; 34 (6)
Exercise and Metabolic Abnormalities
407
one-third of normal weight hypertensive patients
have comorbid insulin resistance determined by
euglycaemic clamp or insulin suppression test.[114]
Among normotensive adults, blood pressure values
are inversely independently associated with insulin
sensitivity,[114] particularly among the relatively lean. The insulin resistance of hypertension is often
associated with a high rate of sodium/lithium
countertransport activity, salt sensitivity and microalbuminuria.[114,288,289]
Lifestyle modifications have been recommended
as the initial treatment strategy for lowering high
blood pressure within current treatment guidelines.[290,291] Several meta-analyses of RCTs have
confirmed that weight reduction through dietary restriction appears an effective method in the treatment of hypertension,[292] including overweight hypertensive participants. A meta-analysis published
in 2000, showed modest weight loss (3–9%) was
associated with a significant reduction in mean reduction systolic and diastolic blood pressure of approximately 3.0mm Hg compared with non-intervention controls.[293,294]
The narrative review of Eriksson et al.[24] indicated that regular exercise training produces a modest
antihypertensive effect, with females and relatively
lean participants deriving most benefit. There also
now appears consistently good evidence from
systematic reviews of longitudinal studies that regular exercise training reduces blood pressure.[295,296]
The most recent systematic review of 74 hyperten-
sive exercise training groups, Hagberg et al.[295]
indicated that exercise training significantly reduced
blood pressure in approximately 75–80% of groups
with hypertension, with a weighted mean reduction
of 10.6/8.2mm Hg. The overall data, within the
above review also generally supported the inference
that hypertensive women reduced their blood pressure somewhat more and somewhat more consistently with exercise training than males.
In 1998, the Obesity Expert Panel[29] reported
that three meta-analyses of 68 controlled studies of
physical activity intervention among both hypertensive and normotensive participants showed significant blood pressure reductions independent or in
the absence of weight loss. A 1999 meta-analysis[297]
confined to RCTs of aerobic exercise training
among overweight/obese participants, the blood
pressure lowering effect was small but remained
statistically significant among normotensive study
groups (baseline blood pressure: 128/84mm Hg).
The mean reduction observed in blood pressure
among these overweight subjects (3.3/2.5mm Hg),
is not disparate to that observed in normal weight
participants. The above analyses included 12 RCTs
of exercise training among overweight/obese hypertensive participants.[297] As shown in table XII
(Fagard RH, unpublished data) within these study
groups, a more pronounced reduction in blood pressure was demonstrated (mean reduction 7.0/ 6.0mm
Hg). Subsequent RCTs[236,238] among overweight
middle-aged and older subjects have also demon-
Table XII. Baseline data and net changes in response to exercise training in overweighta individuals with hypertensionb[264]
Baseline data
Age (y)
Net change
n
mean ± SEMc
14
43.27 ± 2.19
n
mean ± SEMd
p-value
–0.357 ± 0.106
–5.88 ± 1.25
<0.005
<0.001
<0.001
BMI (kg/m2)
14
27.32 ± 0.59
14
HR (beats/min)
˙ 2peak (mL/kg/min)
VO
12
75.1 ± 0.84
11
12
33.60 ± 1.60
11
SBP (mm Hg)
14
145.8 ± 1.77
14
4.77 ± 0.37
–6.68 ± 1.54
DBP (mm Hg)
14
96.5 ± 0.80
14
–5.46 ± 1.24
a
BMI ≥25 kg/m2.
b
SBP ≥140mm Hg and/or DBP ≥90mm Hg based on baseline blood pressure, irrespective of treatment.
c
Weighted means ± SEM.
d
Net weighted mean ± SEM.
<0.001
<0.001
BMI = body mass index; DBP = diastolic blood pressure; HR = heart rate; n = number of study groups; SBP = systolic blood pressure; SEM
˙ 2peak = peak oxygen consumption.
= standard error of the mean; VO
 2004 Adis Data Information BV. All rights reserved.
Sports Med 2004; 34 (6)
408
strated the effectiveness of exercise (with and without weight loss) to lower blood pressure. Behavioural weight loss, with and without exercise were associated with 7–10/6–7mm Hg reductions in systolic
and diastolic blood pressure, respectively. In these
trials,[236,238] mean blood pressures were typically
reduced by 4–6mm Hg within the exercise-only
study groups. A subgroup analysis of metabolic
syndrome patients within one RCT,[206] showed a
mean blood pressure reduction of 7/5mm Hg in
those randomised to exercise training compared
with a reduction of 3/0mm Hg observed among
controls.
The overall results of the published studies recently reviewed[295] indicate that blood pressure reductions are soon apparent (with 10 weeks) following commencement of exercise training in hypertensive patients. Blood pressure continues to decline
somewhat more with prolonged exercise training
programmes. There is no convincing evidence that
the blood pressure response differs in relation to
exercise intensity between 40–70% of individual
maximal capacity.[165,297] Furthermore, other typical
exercise programme characteristics (3–5 times
weekly frequency, 30–60 minutes per session) appear unrelated to blood pressure responses.[297] As
highlighted by Eriksson et al.[24] the decrement in
blood pressure with exercise training is often not
sufficient to produce normal blood pressure in many
investigations. The sixth report of the Joint National
Committee (JNC VI) on Prevention, Detection,
Evaluation and Treatment of High Blood Pressure
guidelines, indicate that patients with the metabolic
syndrome should be managed differently than patients who do not have the disorder.[290] Both behavioural therapy and pharmacological treatment may
be indicated for the initial treatment of hypertensive
adults with the metabolic syndrome.[290] Indeed, the
blood pressure level (after initiating drug therapy)
that represents a relative contraindication for exercise training among hypertensive metabolic syndrome patients may require further consideration.[298,299] Comprehensive lifestyle intervention,
including moderate-intensity aerobic exercise training, has been shown to substantially lower blood
 2004 Adis Data Information BV. All rights reserved.
Carroll & Dudfield
pressure and improve blood pressure control among
overweight adults already on antihypertensive medication.[300]
Heterogeneity in the insulin resistance/hyperinsulinaemia and blood pressure association has been
cited[23,24] as a possible explanation for the inconsistent blood pressure responses observed across exercise training studies. Shahid and Schneider[23] indicated within their review that significant exerciseinduced blood pressure reductions in hypertensive
patients are limited to those with insulin resistance/
hyperinsulinaemia. It has been proposed that all
obese individuals with hypertension are likely to be
insulin resistant. However, several RCTs[236,238] incorporating exercise only intervention groups have
not been coherent in demonstrating corresponding
or directly associated improvements in blood pressure and postprandial insulin responses. Other potential mechanisms of action for exercise training
and weight loss effects on blood pressure have been
summarised extensively elsewhere.[294,295] Metabolic effectors may include structural and/or functional
changes in the vasculature, modulation of the reninangiotensin system, stimulation of the sympathetic
nervous system, intracellular ion changes and genetic interactions.[114] The mechanisms underlying lifestyle-induced blood pressure reductions are probably not mutually exclusive and may be especially
relevant given the apparent refractoriness to antihypertensive therapy among obese, insulin-resistant
individuals with hypertension.[114]
Hypertrophy and concentric remodelling of the
left ventricle appear relatively common (10–20%
and 30–50% of younger/middle-aged and older individuals, respectively) manifestations of both insulin
resistance, obesity and hypertension.[113,116,117,301-304]
Left ventricular hypertrophy and concentric
remodelling are strongly associated with cardiovascular events.[305-307] Intervention trials in overweight hypertensive patients have indicated that
weight loss alone decreases left ventricular wall
thickness but has limited effect on chamber
size.[308-310] Among overweight sedentary subjects
with high normal or mildly elevated blood pressure
exercise training both with and without weight loss
Sports Med 2004; 34 (6)
Exercise and Metabolic Abnormalities
has been associated with comparable ventricular
remodelling and reductions in left ventricular
mass.[311] In view of the more substantial reductions
in blood pressure associated with weight loss, exercise training may have a more beneficial effect on
left ventricular architecture.[236,311]
8. Conclusion
Several previous narrative and systematic reviews have provided relatively limited high-quality
scientific evidence for exercise effects on several
common metabolic traits, unless combined with appropriate dietary modifications to achieve weight
loss. The conclusion of this review is that there is
now a more consistent pattern of findings from
RCTs that long-term exercise training, without
weight reduction, modestly decreases abdominal adipose tissue and improves insulin action among
overweight/obese adults. Exercise effects on glucose tolerance may also be evident within normoglycaemic overweight/obese individuals, although
improvements are more probable with concurrent
weight loss. Most RCT studies have been performed
within middle-aged and older males and evidence
for improvements in abdominal fat, insulin action
and glucose tolerance within overweight or obese
women is more limited. Exercise alone and combined with dietary intervention is effective in improving impaired glucose regulation and delaying or
preventing type 2 diabetes among both sexes. Longer-term exercise training in middle-aged and older
overweight/obese adults, even in the absence of
clinically significant weight loss, is associated with
modest, but clinically relevant improvements in the
dyslipidaemic profile, by raising HDL-C and lowering TG. Exercise training also modestly reduces
blood pressure, with most positive changes evident
among overweight/obese individuals with hypertension.
Consistent with some earlier recommendations,[21,22] the majority of RCTs reviewed for exercise effects on metabolic abnormalities have prescribed frequent aerobic endurance activity (3–5
days/wk), typically of a longer duration (30–60 minutes per session) and at a relatively moderate to
 2004 Adis Data Information BV. All rights reserved.
409
moderately vigorous intensity (typically 60% of
maximal aerobic potential). However, absolute energy expenditure does not often exceed 7 METs.
Well designed RCTs are now required to establish
the lower threshold for exercise intensity and
amount for metabolic outcomes. Furthermore, the
majority of trials included within this review (and
specifically our meta-analysis of exercise effects on
lipoproteins) involved regimes that could be described as ‘physiological fitness training’.[90] Conventional to most trials were group-based supervised exercise sessions within a specialised facilities
affording frequent professional contact. Concerns
remain that despite substantial benefits, these regimes may be difficult to sustain in overweight/
obese patients.[90] The findings of this review need
to be considered in the context of recent recommendations to incorporate necessary daily physical activity into ‘active lifestyles’ in patients with the
metabolic syndrome.[19] At present, there is limited
evidence that such ‘standard lifestyle interventions’
including specific advice and recommendations for
informal, moderate, daily life physical activities
(which are more widely applicable) improve separate or multiple metabolic abnormalities.[312-314]
Moreover, there are insufficient data from nonrandomised and randomised exercise trials to establish dose-response relationships between intensity
and volume of exercise and multiple metabolic abnormalities.
In summary, this review provides evidence of the
benefits of long-term regular exercise training for
management of the metabolic syndrome. As indicated in the NCEP ATP III guidelines,[19] if resources
are available, referral to an exercise specialist for
supervised or partially supervised exercise training
may complement professional nutritional advice in
the implementation of therapeutic lifestyle changes.
A model for the introduction of exercise therapy in a
stepwise manner (as currently proposed for nutrition
therapy), beginning with an emphasis on daily life
activities and followed by consideration for referral
to supervised exercise could be envisaged. Largescale, multicentre RCTs incorporating both supervised exercise and home-based lifestyle activity
Sports Med 2004; 34 (6)
410
Carroll & Dudfield
among patients with the metabolic syndrome are
now required to better define the dose-response relationships of progressively higher volumes of exercise and metabolic clustering. Studies are also required to establish exercise interactions with various
dietary modifications[16,19,144,199,315-317] that have
been recommended to achieve optimal metabolic
improvements in this condition. There is currently
limited clinical exercise data from ethnic minority
populations at high-risk of the metabolic syndrome.
Acknowledgements
The authors are grateful to the following investigators
who supplied unpublished information for the purposes of
this review: Dr R. Fagard, Hypertension and Cardiovascular
Rehabilitation Unit, Faculty of Medicine, Katholieke Universiteit Leuven, Leuven, Belgium; Drs W.E. Kraus and C.A.
Slentz, Division of Cardiology Department of Medicine,
Duke University Medical Center, Durham, NC, USA; Drs
L.L. Watkins and J.A. Blumenthal, Departments of Psychiatry and Behavioral Sciences, Duke University Medical
Center, Durham, NC, USA; Drs K.R. Short and K.S. Nair,
Department of Internal Medicine, Division of Endocrinology,
Mayo Clinic, Rochester, MN, USA; Dr M.L. Irwin, Division
of Chronic Disease Epidemiology, Yale School of Public
Health, New Haven, CT, USA; Dr J. Oldroyd, Department of
Epidemiology and Public Health, University of Newcastle,
UK.
No sources of funding were used to assist in the preparation of this review. The authors have no conflicts of interest
that are directly relevant to the content of this review.
References
1. Grundy SM, Bazzarre T, Cleeman J, et al. Prevention Conference V: beyond secondary prevention. Identifying the highrisk patient for primary prevention: medical office assessment:
Writing Group 1. American Heart Association Medical/ Scientific Statement. Circulation 2000; 101: 111-6
2. Grundy SM, Brewer Jr HB, Cleeman JI, et al. Definition of
metabolic syndrome: report of the National Heart, Lung, and
Blood Institute/American Heart Association Conference on
Scientific Issues Related to Definition. Circulation 2004; 109:
433-8
3. Einhorn D, Reaven GM, Cobin RH, et al. American College of
Endocrinology position statement on the insulin resistance
syndrome. Endocr Pract 2003; 9: 237-52
4. Wilson PWF, Kannel WB, Silbershatz H, et al. Clustering of
metabolic factors and coronary heart disease. Arch Intern Med
1999; 159: 1104-9
5. Garvey WT, Hermayer KL. Clinical implications of the insulin
resistance syndrome. Clin Cornerstone 1998; 1: 13-8
6. Lamarche B, Lewis GF. Atherosclerosis prevention for the next
decade: risk assessment beyond low density lipoprotein cholesterol. Can J Cardiol 1998; 14: 841-51
 2004 Adis Data Information BV. All rights reserved.
7. Yki-Jarvinen H. Pathogenesis of non-insulin dependent diabetes
mellitus. Lancet 1994; 343: 91-5
8. De Fronzo RA. The triumvirate: β-cell, muscle and liver: a
collusion responsible for NIDDM. Diabetes 1988; 37: 667-87
9. Smiley T, Oh P, Shane LG. The relationship of insulin resistance measured with reliable indexes to coronary artery disease
risk factors and outcomes: a systematic review. Can J Cardiol
2001; 17: 797-805
10. Ruige JB, Assenfelt WJJ, Dekker JM, et al. Insulin and risk of
cardiovascular disease: a meta-analysis. Circulation 1998; 97:
996-1001
11. Ferrannini E, Haffner SM, Mitchell BD, et al. Hyperinsulinemia: the key feature of a cardiovascular and metabolic
syndrome. Diabetologia 1991; 34: 416-22
12. Stern MP. Diabetes and cardiovascular disease: the common
soil hypothesis. Diabetes 1995; 44: 369-74
13. Reaven GM. Role of insulin resistance in human disease. Diabetes 1988; 37: 1595-607
14. De Fronzo RA. Insulin resistance, hyperinsulinemia, and coronary artery disease: a complex metabolic web. J Cardiovasc
Pharm 1992; 20 Suppl. 11: S1-16
15. Meigs JB. Epidemiology of the metabolic syndrome. Am J
Manag Care 2002; 8 Suppl. 11: S283-92
16. Reaven G. Metabolic syndrome: pathophysiology and implications for management of cardiovascular disease. Circulation
2002; 106: 286-8
17. Hansen BC. The metabolic syndrome X. Ann N Y Acad Sci
1999; 18: 1-24
18. World Health Organisation Consultation. Definition, diagnosis
and classification of diabetes mellitus and its complications:
report of the World Health Organisation Consultation. Geneva:
World Health Organisation, 1999
19. Expert Panel on Detection, Evaluation and Treatment of High
Blood Cholesterol in Adults. Executive summary on the third
report on the The National Cholesterol Education Program
(NCEP) Expert Panel on Detection, Evaluation and Treatment
of High Blood Cholesterol in Adults (Adult Treatment Panel
III). JAMA 2001; 285: 2486-97
20. The European Group for the Study of Insulin Resistance
(EGIR). Frequency of the WHO metabolic syndrome in
European cohorts, and an alternative definition of an insulin
resistance syndrome. Diabetes Metab 2002; 28: 364-76
21. Westheim A, Os I. Physical activity and the metabolic cardiovascular syndrome. J Cardiovasc Pharmacol 1992; 20 Suppl. 8:
S49-53
22. Buemann B, Tremblay A. Effects of exercise training on abdominal obesity and related metabolic complications. Sports Med
1996; 21: 191-212
23. Shahid SK, Schneider SH. Effects of exercise on insulin resistance syndrome. Coron Artery Dis 2000; 11: 103-9
24. Eriksson J, Taimela S, Koivisto VA. Exercise and the metabolic
syndrome. Diabetologia 1997; 40: 125-35
25. Dela F. Physical training in the treatment of metabolic syndrome. Ugeskr Laeger 2002; 164: 2147-52
26. Stefanick ML. Physical activity for preventing and treating
obesity-related dyslipoproteinemias. Med Sci Sports Exerc
1999; 31: S609-18
27. Ivy JL. Role of exercise training in the prevention and treatment
of insulin resistance and non-insulin dependent diabetes mellitus. Sports Med 1997; 24: 321-36
28. Kelley DE, Goodpaster BH. Effects of physical activity on
insulin action and glucose tolerance in obesity. Med Sci Sports
Exerc 1999; 31: S619-23
Sports Med 2004; 34 (6)
Exercise and Metabolic Abnormalities
29. National Heart, Lung and Blood Institute. Obesity Education
Initiative Expert Panel: clinical guidelines on the identification, evaluation and treatment of overweight and obesity in
adults: the evidence report. Bethesda (MD): National Institutes
of Health, 1998 Sep. NIH publication no.98-4083: 1-228
30. Grundy SM, Blackburn G, Higgins M, et al. Consensus statement physical activity in the prevention and treatment of
obesity and its comorbidities. Med Sci Sports Exerc 1999; 31:
S502-8
31. Bouchard C. Physical activity and health: introduction to the
dose-response symposium. Med Sci Sports Exerc 2001; 33:
S347-50
32. Groop L. Genetics of the metabolic syndrome. Br J Nutr 2000;
83 Suppl. 1: S39-48
33. Ginsberg HN. Insulin resistance and cardiovascular disease. J
Clin Invest 2000; 106: 453-8
34. Timar O, Sestier F, Levy E. Metabolic syndrome X: a review.
Can J Cardiol 2000; 16: 779-89
35. Hayden MR, Tyagi SC. Intimal redox stress: accelerated atherosclerosis in metabolic syndrome and type 2 diabetes. Atheroscleropathy. Cardiovascular Diabetology 2002 [online]. Available from URL: http: //www.Cardiab.com/content/1/1/3 [Accessed 2003 Jan]
36. Reaven GM. Syndrome X: past, present, and future. In: Draznin
B, Rizza R, editors. Clinical research in diabetes and obesity.
Vol 2. Totowa (NJ): Humana Press Inc., 1997: 357-82
37. Reaven GM. Role of insulin resistance in human disease (syndrome X): an expanded definition. Annu Rev Med 1993; 44:
121-31
38. De Fronzo RA, Ferrannini E. Insulin resistance: a multifaceted
syndrome responsible for non-insulin dependent diabetes,
obesity, hypertension, dyslipidemia and atherosclerotic cardiovascular disease. Diabetes Care 1991; 14: 173-94
39. Ferrannini E. The insulin resistance syndrome. Curr Opin Nephrol Hypertens 1992; 1: 291-8
40. Kissebah AH, Vydelingum N, Murray R, et al. Relation of body
fat distribution to metabolic complications of obesity. J Clin
Endocrinol Metab 1982; 54: 254-60
41. Krotkiewski M, Bjorntorp P, Sjostrom L, et al. Impact of
obesity on metabolism in men and women: importance of
regional adipose tissue distribution. J Clin Invest 1983; 72:
1150-62
42. Vague J. The degree of masculine differentiation of obesities: a
factor determining predisposition to diabetes, atherosclerosis,
gout and uric calculous disease. Am J Clin Nutr 1956; 4: 20-34
43. Kaplan NM. The deadly quartet. Upper-body obesity, glucose
intolerance, hypertriglyceridemia, and hypertension. Arch
Intern Med 1989; 149: 1514-20
44. Liese AD, Mayer-Davis EJ, Haffner SM. Development of the
multiple metabolic syndrome: an epidemiological perspective.
Epidemiol Rev 1998; 20: 157-72
45. Fagan TC, Deedwania PC. The cardiovascular dysmetabolic
syndrome. Am J Med 1998; 105: 77S-82S
46. Sowers JR. Update on the cardiometabolic syndrome. Clin
Cornerstone 2002; 4: 17-22
47. Groop L, Orho-Melander M. The dysmetabolic syndrome. J
Intern Med 2001; 250: 105-20
48. Haffner SM, Ferrannini E, Hazuda HP, et al. Clustering of
cardiovascular risk factors in confirmed prehypertensive individuals: does the clock for coronary heart disease start ticking
before the onset of clinical diabetes? Hypertension 1992; 20:
38-45
 2004 Adis Data Information BV. All rights reserved.
411
49. Haffner SM, Valdez RA, Hazuda HP, et al. Prospective analysis
of the insulin resistance syndrome (syndrome X). Diabetes
1992; 41: 715-22
50. Everson SA, Goldberg DE, Helmrich SP, et al. Weight gain and
the risk of developing insulin resistance syndrome. Diabetes
Care 1998; 21: 1637-43
51. Mykkanen L, Kuusisto J, Haffner SM, et al. Hyperinsulinemia
predicts multiple atherogenic changes in lipoproteins in elderly
subjects. Arterioscler Thromb 1994; 14: 518-26
52. Liese AD, Mayer-Davis EJ, Tyroler HA, et al. Development of
the multiple metabolic syndrome in the ARIC cohort: joint
contribution of insulin, BMI, and WHR. Ann Epidemiol 1997;
7: 407-16
53. Salonen JT, Lakka TM, Lakka HM, et al. Hyperinsulinemia is
associated with the incidence of hypertension and dyslipidemia in middle-aged men. Diabetes 1998; 47: 270-5
54. Meigs JB, D’Agostino RB, Wilson PWF, et al. Risk variable
clustering in the insulin-resistance syndrome. The
Framingham Offspring Study. Diabetes 1997; 46: 1594-600
55. Hanson RL, Imperatore G, Bennett PH, et al. Components of
the ‘metabolic syndrome’ and incidence of type 2 diabetes.
Diabetes 2002; 51: 3120-7
56. Arya R, Blangero J, Williams K, et al. Factors of insulin
resistance syndrome-related phenotypes are linked to genetic
locations on chromosomes 6 and 7 in nondiabetic MexicanAmericans. Diabetes 2002; 51: 841-7
57. Gray RS, Fabsitz RR, Cowan LD, et al. Risk factor clustering in
the insulin resistance syndrome: the Strong Heart Study. Am J
Epidemiol 1998; 148: 869-78
58. Donahue RP, Bean JA, Donahue RD, et al. Does insulin
resistance unite the separate components of the insulin resistance syndrome?: evidence from the Miami Community
Health Study. Arterioscler Thromb Vasc Biol 1997; 17:
2413-7
59. Anderson PJ, Critchley JAJH, Chan JCN, et al. Factor analysis
of the metabolic syndrome: obesity vs insulin resistance as the
central abnormality. Int J Obes Relat Metab Disord 2001; 25:
1782-8
60. Hanley AJG, Karter AJ, Festa A, et al. Factor analysis of the
metabolic syndrome using directly measured insulin sensitivity: the Insulin Resistance Atherosclerosis Study. Diabetes
2002; 51: 2642-7
61. Meigs JB. Invited commentary: insulin resistance syndrome?.
Syndrome X? Multiple metabolic syndrome? A syndrome at
all?: factor analysis reveals patterns in the fabric of correlated
metabolic risk factors. Am J Epidemiol 2000; 152: 908-11
62. Zimmet P, Boyko EJ, Collier GR, et al. Etiology of the
metabolic syndrome: potential role of insulin resistance, leptin
resistance, and other players. Ann N Y Acad Sci 1999; 13:
25-44
63. Liese AD, Mayer-Davis EJ, Tyroler HA, et al. Familial components of the multiple metabolic syndrome: the ARIC study.
Diabetologia 1997; 40: 963-70
64. Hong Y, Rice T, Gagnon J, et al. Familial clustering of insulin
and abdominal visceral fat: the Heritage Family Study. J Clin
Endocrinol Metab 1998; 83: 4239-45
65. Samaras K, Nguyen TV, Jenkins AB, et al. Clustering of insulin
resistance, total and central fat: same genes or same environment. Twin Res 1999; 2: 218-25
66. Mitchell BD, Kammerer CM, Mahaney MC, et al. Genetic
analysis of the IRS: pleiotropic effects of genes influencing
insulin levels on lipoprotein and obesity measures. Arterioscler
Thromb Vasc Biol 1996; 16: 281-8
Sports Med 2004; 34 (6)
412
67. Nelson TL, Vogler GP, Pedersen NL, et al. Genetic and
environmental influences on body fat distribution, fasting insulin levels and CVD: are the influences shared. Twin Res 2000;
3: 43-50
68. Hong Y, Pedersen NL, Brismar K, et al. Genetic and environmental architecture of the features of the insulin-resistance
syndrome. Am J Hum Genet 1997; 60: 143-52
69. Brunner EJ, Marmot MG, Nanchahal K, et al. Social inequality
in coronary disease risk: central obesity and the metabolic
syndrome: evidence from the Whitehall II Study. Diabetologia
1997; 40: 1341-9
70. Imperatore G, Riccardi G, Iovine C, et al. Plasma fibrinogen: a
new factor of the metabolic syndrome: a population-based
study. Diabetes Care 1998; 21: 649-54
71. Trevisan M, Liu J, Bahsas FB, et al. Syndrome X and mortality:
a population-based study: For the Risk Factor and Life Expectancy Research Group. Am J Epidemiol 1998; 148: 958-66
72. Valdez R. Epidemiology. Nutr Rev 2000; 58 (3 Pt 2): S4-6
73. Isomaa B, Almgren P, Tuomi T, et al. Cardiovascular morbidity
and mortality associated with the metabolic syndrome. Diabetes Care 2001; 24: 683-9
74. Hulthe J, Bokemark L, Wikstrand J, et al. The metabolic
syndrome, LDL particle size, and atherosclerosis. Arterioscler
Thromb Vasc Biol 2000; 20: 2140-7
75. Okosun IE, Liao Y, Rotimi CN, et al. Abdominal adiposity and
clustering of multiple metabolic syndrome components in
White, Black and Hispanic Americans. Ann Epidemiol 2000;
10: 263-70
76. Rantala AO, Kauma H, Lilja M, et al. Prevalence of the
metabolic syndrome in drug treated hypertensive patients and
control subjects. J Intern Med 1999; 245: 163-74
77. Whaley MH, Kampert JB, Kohl HW, et al. Physical fitness and
clustering of risk factors associated with the metabolic syndrome. Med Sci Sports Exerc 1999; 31: 287-93
78. Wannamethee SG, Shaper AG, Durrington PN, et al. Hypertension, serum insulin, obesity, and the metabolic syndrome. J
Hum Hypertens 1998; 12: 735-41
79. Yarnell JWG, Patterson CC, Bainton D, et al. Is metabolic
syndrome a discrete entity in the general population?: evidence
from the Caerphilly and Speedwell population studies. Heart
1998; 79: 248-52
80. Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic
syndrome among US adults. JAMA 2002; 287: 356-9
81. Lakka H-M, Laaksonen DE, Lakka TA, et al. The metabolic
syndrome and total and cardiovascular disease mortality in
middle-aged men. JAMA 2002; 288: 2709-16
82. Ford ES, Giles WH. A comparison of the prevalence of the
metabolic syndrome using two proposed definitions. Diabetes
Care 2003; 26: 575-81
83. Sattar N, Gaw A, Scherbakova O, et al. Metabolic syndrome
with and without C-Reactive Protein as a predictor of coronary
heart disease and diabetes in the West of Scotland Prevention
Study. Circulation 2003; 108: 414-9
84. Meigs JB, Wilson PWF, Nathan DM, et al. Prevalence and
characteristics of the metabolic syndrome in the San Antonio
Heart and Framingham Offspring Studies. Diabetes 2003; 52:
2160-7
85. Bonora E, Kiechl S, Willeit J, et al. Metabolic syndrome:
epidemiology and more extensive phenotypic description:
cross-sectional data from the Bruneck Study. Int J Obes 2003;
27: 1283-9
86. Yarborough DE, Barrett-Connor E, Kritz-Silverstein D, et al.
Birth weight, adult weight and girth as predictors of the meta-
 2004 Adis Data Information BV. All rights reserved.
Carroll & Dudfield
87.
88.
89.
90.
91.
92.
93.
94.
95.
96.
97.
98.
99.
100.
101.
102.
103.
bolic syndrome in postmenopausal women. Diabetes Care
1998; 21: 1652-8
Ridker PM, Buring JE, Cook NR, et al. C-reactive protein, the
metabolic syndrome, and risk of incident cardiovascular
events: an 8-year follow-up of 14 719 initially healthy American women. Circulation 2003; 107: 391-7
Reilly MP, Rader DJ. The metabolic syndrome: more than the
sum of its parts? Circulation 2003; 108: 1546-51
Hanley AJ, Wagenknecht LE, D’Agostino Jr RB, et al. Identification of subjects with insulin resistance and beta-cell dysfunction using alternative definitions of the metabolic syndrome.
Diabetes 2003; 52: 2740-7
World Health Organisation (1998) Obesity. Preventing and
managing the global epidemic. Report of the WHO consultation on obesity [WHO/NUT/NCD/981]. Geneva: WHO, 1997
Jun 3-5
Laaksonen DE, Lakka HM, Niskanen LK, et al. Metabolic
syndrome and development of diabetes mellitus: application
and validation of recently suggested definitions of the metabolic syndrome in a prospective cohort study. Am J Epidemiol
2002; 156: 1070-7
Kekalainen P, Sarlund H, Pyorala K, et al. Hyperinsulinemia
cluster predicts development of type 2 diabetes independently
of family history of diabetes. Diabetes Care 1999; 22: 86-92
Pyorala M, Miettinen H, Halonen P, et al. Insulin resistance
syndrome predicts the risk of coronary heart disease and stroke
in healthy middle-aged men: the 22 year follow-up results of
the Helsinki Policemen Study. Arterioscler Thromb Vasc Biol
2000; 20: 538-44
Howard BV, Criqui MH, Curb JD, et al. Risk factor clustering
in the insulin resistance syndrome and its relationship to
cardiovascular disease in postmenopausal White, Black, Hispanic, and Asian/Pacific Islander women. Metabolism 2003;
52: 362-71
Lempiainen P, Mykkanen L, Pyorala K, et al. Insulin resistance
syndrome predicts coronary heart disease events in elderly
nondiabetic men. Circulation 1999; 100: 123-8
Lehto S, Ronnemaa T, Pyorala K, et al. Cardiovascular risk
factor clustering with endogenous hyperinsulinemia predict
death from coronary heart disease in patients with type II
diabetes. Diabetologia 2000; 43: 148-55
Kuusisto J, Lempiainen P, Mykkanen L, et al. Insulin resistance
syndrome predicts coronary heart disease events in elderly
type 2 diabetic men. Diabetes Care 2001; 24: 1629-33
Girman CJ, Rhodes T, Mercuri M, et al. The metabolic syndrome and risk of major coronary events in the Scandinavian
Simvastatin Survival Study (4S) and the Air Force/Texas
Coronary Atherosclerosis Prevention Study (AFCAPS/TexCAPS). Am J Cardiol 2004 93(2): 136-41
Bjorntorp P, Rosmond R. The metabolic syndrome: a neuroendocrine disorder? Br J Nutr 2000; 83 Suppl. 1: S49-57
Hedman A, Byberg L, Reneland R, et al. Muscle morphology,
self-reported physical activity and insulin resistance syndrome. Acta Physiol Scand 2002; 175: 325-32
Goodpaster BH, Kelley DE. Role of muscle in triglyceride
metabolism. Curr Opin Lipidol 1998; 9: 231-6
Simoneau J-A, Veerkamp JH, Turcotte LP, et al. Markers of
capacity to utilise fatty acids in human skeletal muscle: relation to insulin resistance and obesity and effects of weight loss.
FASEB J 1999; 13: 2051-60
Radzuik J, Pye S. The role of the liver in insulin action and
resistance. In: Reaven G, Laws A, editors. Contemporary
Sports Med 2004; 34 (6)
Exercise and Metabolic Abnormalities
104.
105.
106.
107.
108.
109.
110.
111.
112.
113.
114.
115.
116.
117.
118.
119.
120.
121.
122.
123.
endocrinology. Insulin resistance: the metabolic syndrome X.
Totowa (NJ): Humana Press Inc., 1999: 197-231
Ansell BJ. The metabolic syndrome: an interplay of multiple
subtle cardiovascular risk factors: case study and commentary.
JCOM 2002 [online]. Available from URL: http://www.turnerwhite.com [Accessed 2003 Oct 1]
Despres J-P. Abdominal obesity as important component of
insulin resistance syndrome. Nutrition 1993; 9: 452-9
Juhan-Vague I, Alessi MC, Vague P. Increased plasminogen
activator inhibitor 1 levels: a possible link between insulin
resistance and atherothrombosis. Diabetologia 1991; 34:
457-62
McFarlane SI, Banerji M, Sowers JR. Insulin resistance and
cardiovascular disease. J Clin Endocrinol Metab 2001; 86:
713-8
Corry DB, Tuck ML. Selective aspects of the insulin resistance
syndrome. Curr Opin Nephrol Hypertens 2001; 10: 507-14
Bjorntorp P. Visceral obesity: a ‘civilisation syndrome’. Obes
Res 1993; 1: 216-22
Bonara E, Kiechl S, Willeit J, et al. Prevalence of insulin
resistance in metabolic disorders. Diabetes 1998; 47: 1643-9
Despres J-P, Lemieux I, Prud’homme D. Treatment of obesity:
need to focus on high risk abdominally obese patients. BMJ
2001; 322: 716-20
Abate N. Obesity and cardiovascular disease: pathogenetic role
of the metabolic syndrome and therapeutic implications. J
Diabet Complications 2000; 14: 154-74
Verdecchia P, Reboldi G, Schillaci G, et al. Circulating insulin
and insulin growth factor-1 are independent determinants of
left ventricular mass and geometry in essential hypertension.
Circulation 1999; 100: 1802-7
Ferrannini E. Insulin resistance and blood pressure. In: Reaven
G, Laws A, editors. Contemporary endocrinology. Insulin
resistance: the metabolic syndrome X. Totowa (NJ): Humana
Press Inc., 1999
Landsberg L. Insulin-mediated sympathetic stimulation: role in
the pathogenesis of obesity-related hypertension (or how insulin affects blood pressure, and why). ) J Hypertens 2001; 19:
523-8
Sundstrom J, Lind L, Nystrom N, et al. Left ventricular concentric remodelling rather than left ventricular hypertrophy is
related to the insulin resistance syndrome in elderly men.
Circulation 2000; 101: 2595-600
Reaven GM, Lithell H, Landsberg L. Hypertension and associated metabolic abnormalities-the role of insulin resistance
and the sympathoadrenal system. N Engl J Med 1996; 334:
374-81
Juhan-Vague I, Alessi MC. PAI-1, obesity, insulin resistance
and risk of cardiovascular events. Thromb Haemost 1997; 78:
656-60
Kohler HP, Grant PJ. Plasminogen-activator inhibitor type 1 and
coronary artery disease. N Engl J Med 2000; 342: 1792-801
Meigs JB, Mittleman MA, Nathan DM, et al. Hyperinsulinemia, hyperglycaemia, and impaired hemostasis. JAMA
2000; 283: 221-8
Miller GJ. Hyperlipidemia and hypercoagulability. Prog Lipid
Res 1993; 32: 61-9
Chrousos GP. The role of stress and the hypothalamic-pituitaryadrenal axis in the pathogenesis of the metabolic syndrome:
neuroendocrine and target tissue related causes. Int J Obes
Relat Metab Disord 1999; 24 Suppl. 2: S50-5
Das UN. Is metabolic syndrome x an inflammatory condition.
Exp Biol Med (Maywood) 2002; 227: 989-7
 2004 Adis Data Information BV. All rights reserved.
413
124. Festa A, D’Agostino R, Howard G, et al. Inflammation and
microalbuminuria in nondiabetic subjects: the Insulin Resistance Atherosclerosis Study. Kidney Int 2000; 58: 1703-10
125. Frolich M, Imhof A, Berg G, et al. Association between Creactive protein and features of the metabolic syndrome: a
population-based study. Diabetes Care 2000; 23: 1835-9
126. Hak AE, Stehouwer CD, Bots ML, et al. Associations of Creactive protein with measures of obesity, insulin resistance
and atherosclerosis in healthy middle-aged women. Arterioscler Thromb Vasc Biol 2000; 19: 1986-91
127. Hotamisligil GS, Spiegelman BM. Tumor necrosis factor alpha:
a key component of the obesity-diabetes link. Diabetes 1994;
43: 1271-8
128. McLaughlin T, Abbasi F, Lamendola C, et al. Differentiation
between obesity and insulin resistance in the association with
C-reactive protein. Circulation 2002; 106: 2908-12
129. Pinkney JH, Stehouwer CDA, Coppack SW, et al. Endothelial
dysfunction: cause of the insulin resistance syndrome. Diabetes 1997; 46 Suppl. 2: S9-S13
130. Tooke JE, Hanneman MM. Adverse endothelial function in the
insulin resistance syndrome. J Intern Med 2000; 247: 425-31
131. Baron AD, Quon MJ. Insulin action and endothelial function.
In: Reaven G, Laws A, editors. Contemporary endocrinology.
Insulin resistance: the metabolic syndrome X. Totowa (NJ):
Humana Press Inc., 1999: 247-63
132. Bjorntorp P. Androgens, the metabolic syndrome and noninsulin dependent diabetes. Ann N Y Acad Sci 1993; 676:
242-52
133. Rantala AO, Kauma H, Lilja M, et al. Gamma-glutamyl transpeptidase and the metabolic syndrome. J Intern Med 2000;
248: 230-8
134. Reaven GM. The kidney: an unwilling accomplice in syndrome
X. Am J Kidney Dis 1997; 30: 928-31
135. Simoneau J-A, Colberg SR, Thaete FL, et al. Skeletal muscle
glycolytic and oxidative enzyme capacities and determinants
of insulin sensitivity and muscle composition in obese women.
FASEB J 1995; 9: 273-8
136. Kelley DE, Mandriano LJ. Fuel selection in human skeletal
muscle in insulin resistance. Diabetes 2000; 49: 677-83
137. Pan DA, Lillioja S, Kritetos AD, et al. Skeletal muscle triglyceride levels are inversely related to insulin action in man.
Diabetes 1997; 46: 983-8
138. Lillioja S, Young AA, Cutler CL, et al. Skeletal muscle capillary density and fibre type are possible determinants of in vivo
insulin resistance in man. J Clin Invest 1987; 80: 415-24
139. Vessby B, Tengblad S, Lithell H. The insulin sensitivity is
related to the fatty acid composition of the serum lipids and
skeletal muscle phospholipids in 70 year old men. Diabetologia 1994; 37: 1044-50
140. Frayn KN. Insulin resistance, impaired postprandial lipid metabolism and abdominal obesity: a deadly triad. Med Princ Pract
2002; 11 Suppl. 2: 31-40
141. Bonora E. Relationship between regional fat distribution and
insulin resistance. Int J Obes Relat Metab Disord 2000; 24
Suppl. 2: S32-5
142. Lewis GF, Carpentier A, Khosrow A, et al. Disordered fat
storage and mobilisation in the pathogenesis of insulin resistance and type 2 diabetes. Endocrine Rev 2002; 23: 201-29
143. de Courten M, Zimmet P, Hodge A, et al. Hyperleptinaemia: the
missing link in the metabolic syndrome? Diabetes Med 1997;
14: 200-8
144. Poppitt SD, Keogh GF, Prentice AM, et al. Long-term effects of
ad libitum low fat, high carbohydrate diets on body weight and
Sports Med 2004; 34 (6)
414
145.
146.
147.
148.
149.
150.
151.
152.
153.
154.
155.
156.
157.
158.
159.
160.
161.
162.
163.
164.
Carroll & Dudfield
serum lipids in overweight subjects with metabolic syndrome.
Am J Clin Nutr 2002; 75: 11-20
Lehtovirta M, Kaprio J, Forsblom C, et al. Insulin secretion and
insulin sensitivity in monozygotic and dizygotic twins.
Diabetologia 2000; 43: 285-93
McKeigue PM. Fetal effects on insulin resistance and glucose
tolerance. In: Reaven G, Laws A, editors. Contemporary endocrinology. Insulin resistance: the metabolic syndrome X. Totowa (NJ): Humana Press Inc., 1999
Ruderman N, Chisholm D, Pi-Sunyer X, et al. The metabolically obese, normal weight individual revisited. Diabetes 1998;
47: 699-713
Laaksonen DE, Lakka HM, Lynch J, et al. Cardiorespiratory
fitness and vigorous leisure-time physical activity modify the
association of small size at birth with the metabolic syndrome.
Diabetes Care 2003; 26: 2156-64
Martyn CN, Hales CN, Barker DJ, et al. Fetal growth and
hyperinsulinemia in adult life. Diabet Med 1998; 15: 688-94
Phillips DI, Barker DJ, Hales CN, et al. Thinness at birth and
insulin resistance in adult life. Diabetologia 1994; 37: 150-4
Phipps K, Barker DJ, Hales CN, et al. Fetal growth and
impaired glucose tolerance in men and women. Diabetologia
1993; 36: 225-8
Davey Smith G, Hart C. Insulin resistance syndrome and childhood social conditions. Lancet 1997; 349: 284-5
Vanhala MJ, Vanhala PT, Keinanen-Kiukaanniemi SM, et al.
Relative weight gain and obesity as a child predict metabolic
syndrome as an adult. Int J Obes Relat Metab Disord 1999; 23:
656-9
Chen W, Bao W, Begum S, et al. Age-related patterns of the
clustering of cardiovascular risk variables of syndrome X from
childhood to young adulthood in a population made up of
Black and White subjects: the Bolalusa Heart Study. Diabetes
2000; 49: 1042-8
Chan JM, Rimm EB, Colditz GA, et al. Obesity, fat distribution,
and weight gain as risk factors for clinical diabetes in men.
Diabetes Care 1994; 17: 961-7
Colditz GA, Willett WC, Rotnitzky A, et al. Weight gain as a
risk factor for clinical diabetes in women. Ann Intern Med
1995; 122: 481-6
Mayer-Davis J, Monaco JH, Hoen HM, et al. Dietary fat and
insulin sensitivity in a triethnic population: the role of obesitas.
The Insulin Resistance Atherosclerosis Study (IRAS). Am J
Clin Nutr 1997; 65: 79-87
Tremblay A. Nutritional determinants of the insulin resistance
syndrome. Int J Obes Relat Metab Disord 1995; 19 Suppl. 1:
S60-8
Wirfalt E, Hedblad B, Gullberg B, et al. Food patterns and
components of the metabolic syndrome in men and women: a
cross-sectional study within the Malmo Diet and Cancer Cohort. Am J Epidemiol 2001; 154: 1150-9
Vessby B. Dietary fat and insulin action in humans. Br J Nutr
2000; 83 Suppl. 1: S91-6
Wolever TMS. Dietary carbohydrates and insulin action in
humans. Br J Nutr 2000; 83 Suppl. 1: S97-102
Zavaroni I, Bonini L, Gasparini P, et al. Cigarette smokers are
relatively glucose intolerant, hyperinsulinemic and dyslipidemic. Am J Cardiol 1994; 73: 904-5
Facchini F, Hollenbeck CB, Jeppesen J, et al. Insulin resistance
and cigarette smoking. Lancet 1992; 339: 1128-30
Eliasson B, Attvall S, Taskinen MR, et al. The insulin resistance
syndrome in smokers is related to smoking habits. Arterioscler
Thromb 1994; 14: 1946-50
 2004 Adis Data Information BV. All rights reserved.
165. Rosmond R, Bjorntorp P. Occupational status, cortisol secretory
pattern, and visceral obesity in middle-aged men. Obes Res
2000; 8: 445-50
166. Horsten M, Mittleman MA, Wamala SP, et al. Social relations
and the metabolic syndrome in middle-aged Swedish women. J
Cardiovasc Risk 1999; 6: 391-7
167. Raikkonen K, Matthews KA, Kuller LH. The relationship between psychological risk attributes and the metabolic syndrome in healthy women: antecedent or consequence? Metabolism 2002; 51: 1573-7
168. Raikkonen K, Matthews KA, Kuller LH, et al. Anger, hostility,
and visceral adipose tissue in healthy postmenopausal women.
Metabolism 1999; 48: 1146-51
169. Keltikangas-Jarvinen L, Raikkonen K, Hautanen A, et al. Vital
exhaustion, anger expression, and pituitary and adrenocortical
hormones: implications for the insulin resistance syndrome.
Arterioscler Thromb Vasc Biol 1996; 16: 275-80
170. Keltikangas-Jarvinen L, Ravaja N, Viikari J. Identifying Cloninger’s temperament profiles as related to the early development of the metabolic cardiovascular syndrome in young men.
Arterioscler Thromb Vasc Biol 1996; 19: 1998-2006
171. Lakka TA, Venalainen JM, Rauramaa R, et al. Relation of
leisure time physical activity and cardiorespiratory fitness to
risk of acute myocardial infarction. N Engl J Med 1994; 330:
1549-54
172. Folsom AR, Arnett DK, Hutchinson RG, et al. Physical activity
and incidence of coronary heart disease in middle-aged women
and men. Med Sci Sports Exerc 1997; 29: 901-9
173. James SA, Jamjoum L, Raghunathan TE, et al. Physical activity
and NIDDM in African-Americans: the Pitt County Study.
Diabetes Care 1998; 21: 555-62
174. Hu FB, Sigal RJ, Rich-Edwards JW, et al. Walking compared
with vigorous activity and risk of type 2 diabetes in women: a
prospective study. JAMA 1999; 282: 1433-49
175. Lynch J, Helmrich SP, Lakka TA, et al. Moderately intense
physical activities and high levels of cardiorespiratory fitness
reduce the risk of non-insulin-dependent diabetes mellitus in
middle-aged men. Arch Intern Med 1996; 156: 1307-14
176. Wei M, Gibbons LW, Mitchell TL, et al. The association
between cardiorespiratory fitness and impaired fasting glucose
and type 2 diabetes mellitus in men. Ann Intern Med 1998;
130: 89-96
177. Wannamethee SG, Shaper AG, Walker M, et al. Lifestyle and
15-year survival free of heart attack, stroke, and diabetes in
British middle-aged men. Arch Intern Med 1998; 158: 2433-40
178. Kohl HW. Physical activity and cardiovascular disease: evidence for a dose response. Med Sci Sports Exerc 2001; 33:
S472-83
179. Kelley DE, Goodpaster BH. The effects of exercise on glucose
homeostasis in type 2 diabetes mellitus. Med Sci Sports Exerc
2001; 33: S495-501
180. Laaksonen DE, Lakka H-M, Salonen JT, et al. Low levels of
leisure-time physical activity and cardiorespiratory fitness predict development of the metabolic syndrome. Diabetes Care
2002; 25: 1612-8
181. Zimmet PZ, Collins VR, Dowse GK, et al. The relation of
physical activity to cardiovascular disease risk factors in
Mauritians. Am J Epidemiol 1991; 134: 862-75
182. Byberg L, Zethelius B, McKeigue PM, et al. Changes in
physical activity are associated with changes in metabolic
cardiovascular risk factors. Diabetologia 2001; 44: 2134-9
183. Wannamethee SG, Shaper AG, Alberti KGMM. Physical activity, metabolic factors, and the incidence of coronary heart
Sports Med 2004; 34 (6)
Exercise and Metabolic Abnormalities
184.
185.
186.
187.
188.
189.
190.
191.
192.
193.
194.
195.
196.
197.
198.
199.
200.
201.
disease and type 2 diabetes. Arch Intern Med 2000; 160:
2108-16
Clausen JO, Borch-Johnsen K, Ibsen H, et al. Insulin sensitivity
index, acute insulin response, and glucose effectiveness in a
population-based sample of 380 young healthy Caucasians:
analysis of the impact of gender, body fat, physical fitness, and
lifestyle factors. J Clin Invest 1996; 98: 1195-209
Mayer-Davis EJ, D’Agostino Jr R, Karter AJ, et al. For the
IRAS Investigators. Intensity and amount of physical activity
in relation to insulin sensitivity: the Insulin Resistance Atherosclerosis Study. JAMA 1998; 279: 669-74
Siscovick DS, Fried L, Mittlemark M, et al. Exercise intensity
and subclinical cardiovascular disease in the elderly: the
Cardiovascular Health Study. Am J Epidemiol 1997; 145:
977-86
Mensink GBM, Heerstrass DW, Neppelenbroek SE, et al. Intensity, duration and frequency of physical activity and coronary risk factors. Med Sci Sports Exerc 1997; 29: 1192-8
Thune I, Njolstad I, Lochen M-L, et al. Physical activity
improves the metabolic risk profiles in men and women: the
Tromso Study. Arch Intern Med 1998; 158: 1633-40
Wareham NJ, Hennings SJ, Byrne CD, et al. A quantitative
analysis of the relationship between habitual energy expenditure, fitness and the metabolic cardiovascular syndrome. Br J
Nutr 1998; 80: 235-41
Carroll S, Cooke CB, Butterly RJ. Metabolic risk factor clustering, associations of both physical activity and cardiorespiratory fitness in middle-aged men. Med Sci Sports Exerc 2000; 32:
2079-86
Irwin ML, Ainsworth BE, Mayer-Davis EJ, et al. Physical
activity and the multiple metabolic syndrome in a tri-ethnic
sample of women. Obes Res 2002; 10: 1030-7
Kullo IJ, Hensrud DD, Allison TG. Relation of low cardiorespiratory fitness to the metabolic syndrome in middle-aged men.
Am J Cardiol 2002; 90: 795-7
Lakka TA, Laaksonen DE, Lakka H-M, et al. Sedentary lifestyle, poor cardiorespiratory fitness and the metabolic syndrome. Med Sci Sports Exerc 2003; 35: 1279-86
Bevis LC, Blackburn G. The obesity epidemic: prevention and
treatment of the metabolic syndrome. Medscape 2002 [online].
Available from URL: http://www.medscape.com [Accessed
2003 Oct 1]
Despres J-P. Visceral obesity, insulin resistance, and dyslipidemia: contribution of endurance exercise training to the
treatment of the plurimetabolic syndrome. Exerc Sport Sci Rev
1997; 25: 271-300
Giles T. Reducing the risk of cardiovascular events through
weight loss. Medscape 2002 [online]. Available from URL:
http://www.medscape.com [Accessed 2003 Jan]
Denke MA, Pasternack RC. Defining and treating the metabolic
syndrome: a primer from the Adult Treatment Panel III. Curr
Treat Options Cardiovasc Med 2001; 3: 251-3
Miller WC, Koceja DM, Hamilton EJ. A meta-analysis of the
past 25 years of weight loss research using diet, exercise or diet
plus exercise intervention. Int J Obes Relat Metab Disord
1997; 21: 941-7
Reaven G. Syndrome X. Curr Treat Options Cardiovasc Med
2001; 3: 323-32
Pescatello LS, Van Heest JL. Physical activity mediates a
healthier body weight in the presence of obesity. Br J Sports
Med 2000; 34: 86-93
Smutock MA, Reece PF, Kokkinos PF, et al. Aerobic versus
strength training for risk factor intervention in middle-aged
 2004 Adis Data Information BV. All rights reserved.
415
202.
203.
204.
205.
206.
207.
208.
209.
210.
211.
212.
213.
214.
215.
216.
217.
men at high risk for coronary heart disease. Metabolism 1993;
42: 177-84
Katzel LI, Bleecker ER, Rogus EM, et al. Sequential effects of
aerobic exercise training and weight loss on risk factors for
coronary disease in healthy, obese middle-aged and older men.
Metabolism 1997; 46: 1441-7
Torjesen PA, Birkeland KI, Anderssen SA, et al. Lifestyle
changes may reverse development of the insulin resistance
syndrome. The Oslo Diet and Exercise Study: a randomized
trial. Diabetes Care 1997; 20: 26-31
Anderssen SA, Holme I, Urdal P, et al. Associations between
central obesity and indexes of hemostatic, carbohydrate and
lipid metabolism: results of a 1-year intervention from the Oslo
Diet and Exercise Study. Scand J Med Sci Sports 1998; 8:
109-15
Dengel DR, Hagberg JM, Pratley RE, et al. Improvements in
blood pressure, glucose metabolism, and lipoprotein lipids
after aerobic exercise plus weight loss in obese, hypertensive
middle-aged men. Metabolism 1998; 47: 1075-82
Watkins LL, Sherwood A, Feinglos M, et al. Effects of exercise
and weight loss on cardiac risk factors associated with syndrome X. Arch Intern Med 2003; 163: 1889-95
Katzmarzyk PT, Leon AS, Wilmore JH, et al. Targeting the
metabolic syndrome with Exercise: evidence from the HERITAGE Family Study. Med Sci Sports Exerc 2003; 35 (10):
1703-9
Diabetes Prevention Program Research Group. The effect of
intensive lifestyle Intervention (ILS) and metformin (MET) on
the incidence of metabolic syndrome among the participants in
the Diabetes Prevention Program. American Diabetes Association 63rd Scientific Session. Epidemiology: Predictors of Diabetes; 2003 Jun 16; New Orleans, abstract no. 250-OR
Minehira K, Tappy L. Dietary and lifestyle interventions in the
management of the metabolic syndrome: present status and
future perspective. Eur J Clin Nutr 2002; 56: 1262-9
Ryan DH, Diabetes Prevention Program Research Group. Diet
and exercise in the prevention of diabetes. Int J Clin Pract
Suppl 2003; 134: 28-35
Goodpaster BH, Kelley DE, Wing RR, et al. Effects of weight
loss on regional fat distribution and insulin sensitivity in
obesity. Diabetes 1999; 48: 839-47
Borghouts LB, Keizer HA. Exercise and insulin sensitivity: a
review. Int J Sports Med 1999; 20: 1-12
Henriksen EJ. Exercise effects of muscle insulin signalling and
action. Invited review: effects of acute exercise and exercise
training on insulin resistance. J Appl Physiol 2002; 93: 788-96
Katzel LI, Bleeker ER, Colman EG, et al. Effects of weight loss
vs aerobic exercise training on risk factors for coronary artery
disease in healthy, obese, middle-aged and older men. JAMA
1995; 274: 1915-21
Ross R, Dagone D, Jones PJ, et al. Reduction in obesity and
related comorbid conditions after diet-induced weight-loss or
exercise induced weight loss. Ann Intern Med 2000; 133:
92-103
Dengel DR, Pratley RE, Hagberg JM, et al. Distinct effects of
aerobic exercise training and weight loss on glucose homeostasis in obese sedentary men. J Appl Physiol 1996; 8: 318-25
Davey GJG, Roberts JD, Patel S, et al. Effects of exercise on
insulin resistance in South Asians and Europeans. J Exerc
Physiol [online] 2000; 3 (2). Available from URL: http://
www.asep.org/JEPDavey.html [Accessed 2004 Mar 23]
Sports Med 2004; 34 (6)
416
218. McAuley KA, Williams SM, Mann JI, et al. Intensive lifestyle
changes are necessary to improve insulin sensitivity: a randomised controlled trial. Diabetes Care 2002; 25: 445-52
219. Houmard JA, Tanner CJ, Slentz CA, et al. The effect of the
volume and intensity of exercise training on insulin sensitivity.
J Appl Physiol 2004; 96 (1): 101-6
220. Short KR, Vittone JL, Bigelow ML, et al. Impact of aerobic
exercise training on age-related changes in insulin sensitivity
and muscle oxidative capacity. Diabetes 2003; 52: 1888-96
221. Despres J-P, Marette A. Obesity and insulin resistance: epidemiological, metabolic and molecular aspects. In: Reaven G, Laws
A, editors. Contemporary endocrinology. Insulin resistance:
the metabolic syndrome X. Totowa (NJ): Humana Press Inc.,
1999
222. Smith SR, Zachwieja JJ. Visceral adipose tissue: a critical
review of intervention strategies. Int J Obes Relat Metab
Disord 1999; 23: 329-35
223. Ross R, Freeman JA, Janssen I. Exercise alone is an effective
strategy for reducing obesity and related comorbidities. Exerc
Sport Sci Rev 2000; 28: 165-70
224. Di Pietro L, Seeman TE, Stachenfield NS, et al. Moderateintensity aerobic exercise training improves glucose tolerance
in aging independent of abdominal adiposity. J Am Geriatr Soc
1998; 46: 875-9
225. Torjesen PA, Birkeland KI, Anderssen SA, et al. The Oslo Diet
and Exercise Study: a randomised trial: lifestyle changes may
reverse development of the insulin resistance syndrome. Diabetes Care 1997; 20: 26-31
226. Irwin ML, Yasui Y, Ulrich CM, et al. Effect of exercise on total
and intra-abdominal body fat in postmenopausal women: a
randomised controlled trial. JAMA 2003; 289: 323-30
227. Liao D, Asberry PJ, Shofer JB, et al. Improvement of BMI,
body composition, and body fat distribution with lifestyle
modification in Japanese Americans with impaired glucose
tolerance. Diabetes Care 2002; 25: 1504-10
228. Borch-Johnsen K. The new classification of diabetes mellitus
and IGT: a critical approach. Exp Clin Endocrinol Diabetes
2001; 109 Suppl. 2: S86-93
229. Unwin N, Shaw J, Zimmet P, et al. International Diabetes
Federation IGT/IFG Consensus Statement. Impaired glucose
tolerance and impaired fasting glycaemia: the current status on
definition and intervention. Diabet Med 2002; 19: 708-23
230. Davies MJ, Raymond NT, Day JL, et al. Impaired glucose
tolerance and fasting hyperglycaemia have different characteristics. Diabet Med 2000; 17: 433-40
231. Larsson H, Berglund G, Lindgarde F, et al. Comparison of
WHO and ADA criteria for diagnosis of diabetes and glucose
intolerance. Diabetologia 1998; 41: 1124-5
232. Rathman W, Giani G, Mielck A. Cardiovascular risk factors in
newly diagnosed abnormal glucose tolerance: comparison of
1997 ADA and 1985 WHO criteria. Diabetologia 1999; 42:
1268-9
233. Hanefeld M, Temelkova-Kurktschiev T, Schaper F, et al. Impaired fasting glucose is not a risk factor for atherosclerosis.
Diabet Med 1999; 16: 212-8
234. DECODE Study Group. Glucose tolerance and mortality: comparison of the WHO and ADA diagnostic criteria. Lancet
1999; 354: 617-21
235. Potteiger JA, Jacobsen DJ, Donnelly JE. A comparison of
methods for analysing glucose and insulin areas under the
curve following nine months of exercise in overweight adults.
Int J Obes Relat Metab Disord 2002; 26: 87-9
 2004 Adis Data Information BV. All rights reserved.
Carroll & Dudfield
236. Dengel DR, Galecki AT, Hagberg JM, et al. The independent
and combined effects of weight loss and aerobic exercise on
blood pressure and oral glucose tolerance in older men. Am J
Hypertens 1998; 11: 1405-12
237. Stefanick ML, Mackey S, Sheehan M, et al. Effects of diet and
exercise in men and postmenopausal women with low levels of
HDL cholesterol and high levels of LDL cholesterol. N Engl J
Med 1998; 339: 12-20
238. Blumenthal JA, Sherwood A, Gullette ECD, et al. Exercise and
weight loss reduce blood pressure in men and women with
mild hypertension. Arch Intern Med 2000; 160: 1947-58
239. Hellenius ML, Brismar KE, Berglund BH, et al. Effects on
glucose tolerance, insulin secretion, insulin-like growth factor
1 and its binding protein, IGFBP-1, in a randomised controlled
diet and exercise study in healthy middle-aged men. J Intern
Med 1995; 238: 121-30
240. Pan X, Li G, Hu Y-H, et al. Effects of diet and exercise in
preventing NIDDM in people with impaired glucose tolerance.
The Da Qing IGT Diabetes Study. Diabetes Care 1997; 20:
537-44
241. Li G, Hu Y, Yang W, et al. Effects of insulin resistance and
insulin secretion on the efficacy of interventions to retard
development of type 2 diabetes mellitus: the Da Qing IGT and
Diabetes Study. Diabetes Res Clin Pract 2002; 58: 193-200
242. Toumilehto J, Lindstrom J, Eriksson JG, et al. Prevention of
type 2 diabetes mellitus by changes in lifestyle among subjects
with impaired glucose tolerance. N Engl J Med 2001; 344:
1343-50
243. Knowler WC, Barrett-Connor E, Fowler SE, et al. Reduction in
the incidence of type 2 diabetes with lifestyle intervention or
metformin. N Engl J Med 2002; 346: 393-403
244. Grundy SM. Hypertriglyceridemia, atherogenic dyslipidemia,
and the metabolic syndrome. Am J Cardiol 1998; 81: 18B-25B
245. Howard BV, Mayer-Davis EJ, Goff D, et al. Relationships
between insulin resistance and lipoproteins in nondiabetic
African Americans, Hispanics, and non-Hispanic Whites: the
Insulin Resistance Atherosclerosis Study. Metabolism 1998;
47: 1174-9
246. Reaven GM, Chen Y-DI, Jeppesen J, et al. Insulin resistance
and hyperinsulinemia in individuals with small, dense, low
density lipoprotein particles. J Clin Invest 1993; 92: 141-6
247. Sattar N, Tan CE, Han TS, et al. Associations of indicies of
adiposity with atherogenic lipoprotein subfractions. Int J Obes
Relat Metab Disord 1998; 22: 432-9
248. Abbassi F, McLaughlin T, Lamendola C, et al. Insulin regulation of plasma free fatty acid concentrations is abnormal in
healthy subjects with muscle insulin resistance. Metabolism
2000; 49: 151-4
249. Bjorntorp P. ‘Portal’ adipose tissue as a generator of risk factors
for cardiovascular disease and diabetes. Arterioscler Thromb
1990; 10: 493-6
250. Laws A. Insulin resistance and dyslipidemia: implications for
coronary heart disease risk. In: Reaven G, Laws A, editors.
Contemporary endocrinology. Insulin resistance: the metabolic syndrome X. Totowa (NJ): Humana Press Inc., 1999
251. Taskinen MR. Insulin resistance and lipoprotein metabolism.
Curr Opin Lipidol 1995; 6: 153-60l
252. Durstine JL, Grandjean PW, Davis PG, et al. Blood lipid and
lipoprotein adaptations to exercise: a quantitative analysis.
Sports Med 2001; 31: 1033-62
253. Leon AS, Sanchez OA. Response of blood lipids to exercise
training alone or combined with dietary intervention. Med Sci
Sports Exerc 2001; 33: S502-15
Sports Med 2004; 34 (6)
Exercise and Metabolic Abnormalities
254. Halbert JA, Silagy CA, Finucane P, et al. Exercise training and
blood lipids in hyperlipidemia and normolipidemic adults: a
meta-analysis of randomised, controlled trials. Euro J Clin
Nutr 1999; 53: 514-22
255. Gallagher D, Heymsfield SB, Heo M, et al. Healthy percentage
body fat ranges: an approach for developing guidelines based
on body mass index. Am J Clin Nutr 2000 Sep; 72 (3): 694-701
256. Zhu S, Wang Z, Shen WS, et al. Percentage body fat ranges
associated with metabolic syndrome risk: results based on the
third National Health and Nutrition Examination Survey
(1988-1994). Am J Clin Nutr 2003; 78: 228-35
257. Kiens B, Jorgensen I, Lewis S, et al. Increased plasma HDLcholesterol and aop A-1 in sedentary middle-aged men after
physical conditioning. Euro J Clin Invest 1980; 10: 203-9
258. Juneau M, Rogers F, De Santos V, et al. Effectiveness of selfmonitored, home-based, moderate-intensity exercise training
in middle-aged men and women. Am J Cardiol 1987; 60: 66-70
259. Wood PD, Stefanick ML, Dreon DM, et al. Changes in plasma
lipids and lipoproteins in overweight men during weight loss
through dieting as compared with exercise. N Engl J Med
1988; 319: 1173-9
260. King AC, Haskell WL, Taylor B, et al. Group- vs home-based
exercise training in healthy older men and women: a community-based clinical trial. JAMA 1991; 266: 1535-42
261. Nieman DC, Warren BJ, O’Donnell KA, et al. Physical activity
and serum lipids in elderly women. J Am Geriatr Soc 1993; 41:
1339-44
262. Anderssen SA, Haaland A, Hjermann I, et al. Oslo Diet and
Exercise Study: a one-year randomised intervention trial: effect on hemostatic and other coronary risk factors. Nutr Metab
Cardiovasc Dis 1995; 5: 189-200
263. Ready EA, Drinkwater D, Ducas J, et al. Walking program
reduces elevated cholesterol in women postmenopause. Can J
Cardiol 1995; 11: 905-12
264. Eriksson J, Tuominen J, Valle T, et al. Aerobic endurance
exercise or circuit-type resistance training for individuals with
impaired glucose tolerance. Horm Metab Res 1998; 30: 37-41
265. Wing RR, Venditti EV, Jakicic JM, et al. Lifestyle intervention
in overweight individuals with a family history of diabetes.
Diabetes Care 1998; 21: 350-9
266. Kokkinos PF, Narayan P, Colleran J, et al. Effects of moderate
intensity exercise on serum lipids in African-American men
with severe systemic hypertension. Am J Cardiol 1998; 81:
732-5
267. Lavrencic A, Salobir BG, Keber I. Physical training improves
flow-mediated dilation in patients with the polymetabolic syndrome. Arterioscler Thromb Vasc Biol 2000; 20: 551-60
268. Nieman DC, Brock DW, Butterworth D, et al. Reducing diet
and/or exercise training decreases the lipid and lipoprotein risk
factors of moderately obese women. J Am Coll Nutr 2002; 21:
344-50
269. Kraus WE, Houmard JA, Duscha BD, et al. Effects of the
amount and intensity of exercise on plasma lipoproteins. N
Engl J Med 2002; 347: 1483-92
270. Schuit AJ, Schouten EG, Miles TP, et al. The effect of six
months training on weight, body fatness and serum lipids in
apparently healthy elderly Dutch men and women. Int J Obes
Relat Metab Disord 1998; 22: 847-53
271. Clarke M, Oxman AD, editors. Cochrane Reviewers’ Handbook
4.2.0 [updated 2003 Mar]. Available from URL: http://
www.cochrane.dk/cochrane/handbook/handbook.htm. [Accessed 2003 Oct 10]
 2004 Adis Data Information BV. All rights reserved.
417
272. Sutton AJ, Abrams KR, Jones DR, et al. Methods for metaanalysis in medical research. Chichester: John Wiley & Sons,
2001
273. Follmann D, Elliott P, Suh I, et al. Variance imputation for
overviews of clinical trials with continuous response. J Clin
Epidemiol 1992; 45: 769-73
274. Egger M, Davey Smith G. Meta-analysis: potentials and promise. BMJ 1997; 315: 1371-4
275. J¨uni P, Altman DG, Egger M. Assessing the quality of controlled clinical trials. In: Egger M, Davey Smith G, Altman DG,
editors. Systematic reviews in health care: meta-analysis in
context. 2nd ed. London: BMJ Books, 2001
276. Hedges LV, Olkin I. Statistical methods for meta-analysis.
Orlando (FL): Academic Press, 1985
277. Deeks JJ, Altman DG, Bradburn MJ. Statistical methods for
examining heterogeneity and combining results from several
studies in meta-analysis. In: Egger M, Davey Smith G, Altman
DG, editors. Systematic reviews in healthcare: meta-analysis
in context. 2nd ed. London: BMJ Books, 2001: 285-312
278. Higgins JPT, Thompson SG, Deeks JJ, et al. Measuring inconsistency in meta-analyses. BMJ 2003; 327: 557-60
279. Sterne JAC, Egger M, Davey Smith G. Meta-analysis: investigating and dealing with publication and other bias. In: Egger
M, Davey Smith G, Altman DG, editors: Systematic reviews in
health care: meta-analysis in context. 2nd ed. London: BMJ
Books, 2001: 189-210
280. Sterne JAC, Egger M. Funnel plots for detecting bias in metaanalysis: guidelines on choice of axis. J Clin Epidemiol 2001;
54: 1046-55
281. Egger M, Davey Smith G, Schneider M, et al. Bias in metaanalysis detected by a simple, graphical test. BMJ 1997; 315:
629-34
282. Begg CB, Mazumdar M. Operating characteristics of a rank
correlation test for publication bias. Biometrics 1994; 50:
1088-99
283. Oja P. Dose response between total volume of physical activity
and health and fitness. Med Sci Sports Exerc 2001; 33:
S428-34
284. Wing RR. Physical activity in the treatment of adulthood overweight and obesity: current evidence and research issues. Med
Sci Sports Exerc 1999; 31 (11 Suppl.): S547-52
285. Couillard C, Despres J-P, Lamarche B, et al. Effects of endurance exercise training on plasma HDL cholesterol levels depend on levels of triglycerides: evidence from men of the
Health Risk Factors Exercise Training and Genetics (HERITAGE) Family Study. Arterioscler Thromb Vasc Biol 2001;
21: 1226-32
286. Williams PT, Krauss RM, Vranizan KM, et al. Changes in
lipoprotein subfractions during diet-induced and exercise-induced weight loss in moderately overweight men. Circulation
1990; 81: 1293-304
287. Williams PT, Krauss KM, Vranizan KM, et al. Effects of
exercise-induced weight loss on LDL subfractions in healthy
men. Arteriosclerosis 1989; 9: 623-32
288. Doria A, Fioretto P, Avogaro A, et al. Insulin resistance is
associated with high sodium-lithium countertransport activity
in essential hypertension. Am J Physiol 1991; 261: E691-4
289. Sowers JR, Epstein M, Frolich ED. Diabetes, hypertension and
cardiovascular disease: an update. Hypertension 2001; 37:
1053-9
290. The sixth report of the Joint National Committee on prevention,
detection, evaluation and treatment of high blood pressure.
Arch Intern Med 1997; 157: 2413-46
Sports Med 2004; 34 (6)
418
291. World Health Organisation. International Society of Hypertension Guidelines for the Management of Hypertension: Guidelines Subcommittee. J Hypertens 1999; 17: 151-83
292. Staessen J, Fagard R, Amery A. The relationship between body
weight and blood pressure. J Hypertens 1988; 2: 207-17
293. Brand MB, Mulrow CD, Chiquette E, et al. Dieting to reduce
body weight for controlling hypertension in adults. Available
in The Cochrane Library [database on disk and CD ROM].
Updated quarterly. The Cochrane Collaboration; issue 1. Oxford: Update Software, 2000
294. Hermansen K. Diet, blood pressure and hypertension. Br J Nutr
2000; 83 Suppl. 1: S113-9
295. Hagberg JM, Park JJ, Brown MD. The role of exercise training
in the treatment of hypertension: an update. Sports Med 2000;
30: 193-206
296. Fagard RH. Exercise characteristics and blood pressure response to dynamic physical training. Med Sci Sports Exerc
2001; 33: S484-92
297. Fagard RH. Physical activity in the prevention and treatment of
hypertension in the obese. Med Sci Sports Exerc 1999; 31 (11
Suppl.): S624-30
298. Niedfeldt MW. Managing hypertension in athletes and physically active patients. Am Fam Physician 2002; 66: 445-52
299. Gordon N. Hypertension. In: Durstine JL, Moore GE, editors.
ACSM’s exercise management for persons with chronic diseases and disabilities. 2nd ed. American College of Sports
Medicine. Champaign (IL): Human Kinetics, 2003: 76-80
300. Miller ED, Erlinger TP, Young DR, et al. Results of the diet,
exercise, and weight loss intervention trial. Hypertension
2002; 40: 612-8
301. Devereux RB, Roman MJ. Hypertensive cardiac hypertrophy:
pathophysiologic and clinical characteristics. In: Laragh JH,
Brenner BM, editors. Hypertension: pathophysiology, diagnosis and management. 2nd ed. New York (NY): Reaven Press
Ltd, 1995: 409-24
Carroll & Dudfield
306. Vakili BA, Okin PM, Devereux RB. Prognostic implications of
left ventricular hypertrophy. Am Heart J 2001; 141: 334-41
307. Weber MA, Smith DH, Neutel JM, et al. The therapeutic
implications of left ventricular hypertrophy in the hypertensive
patient. Am J Ther 1995; 2: 972-7
308. MacMahon SW, Wilcken DEL, Macdonald GJ. The effect of
weight reduction on left ventricular mass: a randomised controlled trial in young overweight hypertensive patients. N Engl
J Med 1986; 314: 334-9
309. Farerberg B, Berglund A, Anderssen OK, et al. Cardiovascular
effects of weight reduction versus antihypertensive drug treatment: a comparative, randomised, 1-year study of obese men
with mild hypertension. J Hypertens 1991; 9: 431-9
310. Hiemeno E, Nishino K, Okazaki T, et al. A weight reduction
and weight maintenance program with long-lasting improvement in ventricular mass and blood pressure. Am J Hypertens
1999; 12: 682-90
311. Hinderlitter A, Sherwood A, Gullette ECD, et al. Reduction of
left ventricular hypertrophy after exercise and weight loss in
overweight patients with mild hypertension. Arch Intern Med
2002; 162: 1333-9
312. Lalonde L, Gray-Donald K, Lowensteyn I, et al. Comparing the
benefits of diet and exercise in the treatment of dyslipidemia.
Prev Med 2002; 35: 16-24
313. Andersen RE, Wadden TA, Bartlett SJ, et al. Effects of lifestyle
activity vs structured aerobic exercise in obese women: a
randomised trial. JAMA 1999; 281: 335-40
314. Snyder KA, Donnelly JE, Jabobsen DJ, et al. The effects of
long-term, moderate intensity, intermittent exercise on aerobic
capacity, body composition, blood lipids, insulin and glucose
in overweight females. Int J Obes Relat Metab Disord 1997;
21: 1180-9
315. Purnell JQ, Brunzell JD. The central role of dietary fat, not
carbohydrate, in the insulin resistance syndrome. Curr Opin
Lipidol 1997; 8: 17-22
302. Rutter MK, Parise H, Benjamin EJ, et al. Impact of glucose
intolerance and insulin resistance on cardiac structure and
function: sex-related differences in the Framingham Heart
Study. Circulation 2003; 107: 448-54
316. Wolever TM, Mehling C. High carbohydrate-low-glycaemic
index dietary advice improves glucose disposition index in
subjects with impaired glucose tolerance. Br J Nutr 2002; 87:
477-87
303. Lind L, Anderssen PE, Andren B, et al. Left ventricular
hypertrophy in hypertension is associated with the insulin
resistance syndrome. J Hypertens 1995; 13: 433-8
317. Dumesnil JG, Turgeon J, Tremblay A, et al. Effect of a lowglycaemic index-low-fat-high protein diet on the atherogenic
metabolic risk profile of abdominally obese men. Br J Nutr
2001; 86: 557-68
304. Morricone L, Malavazos AE, Coman C, et al. Echocardiographic abnormalities in normotensive obese patients: relationship with visceral fat. Obes Res 2002, 98
305. Kannel WB. Risk stratification in hypertension: new insights
from the Framingham study. Am J Hypertens 2000; 13:
3S-10S
 2004 Adis Data Information BV. All rights reserved.
Correspondence and offprints: Dr Sean Carroll, School of
Leisure and Sports Studies, Beckett Park Campus, Leeds
Metropolitan University, Leeds LS6 3QS, UK.
Sports Med 2004; 34 (6)