The subjects were participants of the Kuopio Ischemic Heart Disease Risk Factor Study (KIHD), which is an ongoing prospective population-based study designed to investigate risk factors for chronic diseases, including Type 2 diabetes and cardiovascular diseases, among middle-aged men (31). The study population was a random age-stratified sample of men living in Eastern Finland who were 42, 48, 54, or 60 yr old at baseline examinations in 1984–1989. The Research Ethics Committee of the University of Kuopio approved the study. All study subjects gave their written informed consent. The recruitment of the subjects has been described previously in detail (31). The present study included 1069 men who did not have diabetes, cardiovascular disease, or cancer and who had complete data on physical activity, V̇O2max, and the main characteristics of the metabolic syndrome at baseline.
Assessment of leisure-time physical activity.
The validated KIHD 12-month Leisure-Time Physical Activity Questionnaire was used as described previously (17,19). This is a detailed quantitative questionnaire of the most common conditioning and lifestyle leisure-time physical activities of middle-aged Finnish men. The questionnaire enables the assessment of the duration, frequency, and mean intensity of leisure-time physical activity as recalled over the previous 12 months. Low-intensity physical activity was defined as <4.5 metabolic equivalents (METs; 1 MET is defined as the energy expenditure at rest, corresponding to an oxygen uptake of 3.5 mL O2·kg−1). At least moderate-intensity physical activity was defined as ≥ 4.5 METs (34). Occupational physical activity, as assessed by the KIHD Occupational Physical Activity Interview (17,18), was not associated with the main components of the metabolic syndrome, except serum triglycerides (data not shown), and is not addressed in this paper.
Assessment of cardiorespiratory fitness.
A graded symptom-limited maximal exercise test was carried out between 8:00 a.m. and 10:00 a.m. on an electrically braked cycle ergometer. Workload was increased linearly by 20 W·min−1. V̇O2max was measured directly with breath-by-breath respiratory gas exchange analysis, as previously described (16,19). V̇O2max was defined as the peak or plateau in oxygen uptake. The tests were supervised by an experienced physician.
Assessment of obesity.
Body mass index (BMI) was computed as the ratio of weight to the square of height (kg·m−2). Waist circumference was taken as the average of two measurements taken after inspiration and expiration (mean difference between the two measurements ≈1.5 cm) at the midpoint between the lowest rib and the iliac crest. Waist-hip ratio (WHR) was defined as the ratio of waist girth to the circumference of the hips measured at the trochanter major.
Measurement of blood pressure.
Blood pressure was measured with a random-zero mercury sphygmomanometer (Hawksley, UK). The measurement protocol included, after supine rest of 5 min, three measurements in supine, one in standing, and two in sitting position with 5-min intervals. The mean of all six measurements was used as systolic and diastolic blood pressure.
Subjects were asked to fast for 12 h before blood sampling. They were also asked to refrain from smoking for 12 h and from consuming alcohol for 3 d before blood draws. Blood glucose was measured using a glucose dehydrogenase method after precipitation of proteins by trichloroacetic acid. The serum samples for insulin determination were stored frozen at −80°C. Serum insulin was determined with a Novo Biolabs radioimmunoassay kit (Novo Nordisk, Bagsvaerd, Denmark). The coefficient of variation (CV) was 8.9% at 9.4 pmol·L−1. Low-density lipoprotein (low-density lipoprotein (LDL)) and HDL fractions were separated from fresh serum by combined ultracentrifugation and precipitation. The cholesterol contents of lipoprotein fractions and serum triglycerides were measured enzymatically. The CV was 5.2% for LDL, 9.2% for HDL, 10.8% for HDL2 (N = 210) and 1.9% for triglycerides (N = 7). Apolipoprotein B was determined with an immunoturbidimetric method using an antiserum. The CV was 2.7% (N = 117). Fibrinogen was measured based on the clotting of diluted plasma with excess thrombin. The CV was 2.4%. Serum uric acid was measured enzymatically (Kone Instruments, Espoo, Finland).
Definition of the metabolic syndrome.
The metabolic syndrome was defined as the presence of hyperinsulinemia (fasting serum insulin concentration in the top 25% of these nondiabetic men), impaired fasting glucose, or diabetes and the presence of at least two of the following: obesity (WHR >0.90 or BMI ≥ 30 kg·m−2), dyslipidemia (serum triglycerides ≥ 1.70 mmol·L−1 or serum HDL cholesterol < 0.9 mmol·L−1), or hypertension (blood pressure ≥ 140/90 mm Hg or blood pressure medication) (1). Impaired fasting glucose was defined as fasting blood glucose 5.6–6.0 mmol·L−1 (equivalent to a fasting plasma glucose 6.1–6.9 mmol·L−1) (1). Diabetes was defined as fasting blood glucose ≥ 6.1 mmol·L−1 (equivalent to fasting plasma glucose ≥ 7.0 mmol·L−1) or a clinical diagnosis of diabetes with either dietary, oral, or insulin treatment (1). In the present study, men with diabetes were excluded.
The WHO definition of the metabolic syndrome proposed insulin resistance to be measured by the euglycemic hyperinsulinemic clamp and impaired glucose tolerance to be used in the definition (1). In the present study, fasting serum insulin was used to estimate insulin resistance and impaired fasting glucose was used as a substitute for impaired glucose tolerance, as has been proposed for epidemiological studies (3). Microalbuminuria as a core component in the metabolic syndrome is controversial (3) and uncommon in nondiabetic persons (12). Microalbuminuria was therefore not included in the present definition (3). These modifications of the WHO definition of the metabolic syndrome have been validated (13).
Assessments of medical history and medications, smoking, alcohol consumption, and adult socioeconomic status have been described previously (16,19,32).
Differences in clinical and biochemical characteristics between men who had the metabolic syndrome and those who did not were tested for statistical significance with Student’s t-test and, where indicated, the chi-squared test. The cross-sectional associations of leisure-time physical activity and V̇O2max with components of or variables related to the metabolic syndrome were assessed using partial correlation analysis. The associations of leisure-time physical activity and V̇O2max with the risk of having the metabolic syndrome was estimated using logistic regression models adjusting first for age, and second for age, smoking, alcohol consumption, and adulthood socioeconomic status. Leisure-time physical activity and V̇O2max were categorized into thirds for the logistic regression analyses except for at least moderate-intensity physical activity, which was categorized based on minutes per week according to the CDC/ACSM recommendations (26,28,34). Categorization of at least moderate-intensity physical activity into thirds gave similar results, however. The covariates for the logistic regression models were forced into the model. Ninety-five percent confidence intervals were estimated based on the assumption of normality.
As a complementary approach for assessing the associations of leisure-time physical activity and cardiorespiratory fitness with the metabolic syndrome, factor analysis was carried out using core components of or variables related to the metabolic syndrome, V̇O2max, and leisure-time physical activity. Potentially confounding factors (variables related to smoking and alcohol consumption) were also included. Principal component analysis was used for the extraction of the initial factors. Only factors with eigenvalues > 1.0 were retained in the analysis. The initial factors were then subjected to promax rotation to generate correlated factors. The factors were then interpreted as such but also subjected to a second-order factor analysis with a varimax rotation to assess possible underlying pathophysiological relationships (11). Cutoffs for loading varying from 0.20 to 0.40 have been recommended for the interpretation of factors (24,33). For interpretation in this study, we considered variables with loadings ≥ 0.40 to be heavily loaded on the factor and variables having a correlation coefficient of 0.30–0.39 to be moderately loaded. The durations of leisure-time physical activity are presented as medians (interquartile ranges); other data are presented as means and standard deviations or simple percentages. Serum triglycerides and insulin and the durations of leisure-time physical activity were corrected for skewing using log transformation but are presented using untransformed values. Statistical significance was considered to be P < 0.05. All statistical analyses were performed with SPSS 10.0 for Windows (Chicago, IL).
Characteristics according to the presence of the metabolic syndrome.
Men with the metabolic syndrome had a lower V̇O2max, and they were less physically active during their leisure time than men without the syndrome (Table 1). As would be expected, men with the metabolic syndrome had a larger waist girth and a higher BMI and WHR; higher fasting blood glucose and serum insulin; higher serum triglycerides and apolipoprotein B and lower serum HDL and HDL2 cholesterol; and higher blood pressure. Men with the metabolic syndrome also had higher levels of blood leukocytes, plasma fibrinogen, and serum uric acid than men without the syndrome. Moreover, men with the metabolic syndrome consumed more alcohol.
Physical activity, maximal oxygen uptake and the components of the metabolic syndrome.
Total, at least moderate-intensity, and low-intensity leisure-time physical activity were inversely associated with BMI, waist girth, WHR, and fasting serum insulin (Table 2). Total physical activity was also negatively correlated with fasting blood glucose, serum uric, blood leukocyte count, and diastolic blood pressure, and positively correlated with serum HDL and HDL2 cholesterol. At least moderate-intensity physical activity showed somewhat stronger inverse associations with measures of abdominal obesity, fasting serum insulin, serum lipids, and blood leukocytes than low-intensity physical activity. V̇O2max was inversely associated with BMI, waist girth, WHR, fasting blood glucose and serum insulin, serum triglycerides and apolipoprotein B, systolic and diastolic blood pressure, blood leukocytes, plasma fibrinogen, and serum uric acid and directly associated with serum HDL and HDL2 cholesterol (Table 2). V̇O2max was also correlated with total leisure-time physical activity (r = 0.20, P < 0.001) and at least moderate-intensity physical activity (r = 0.25, P < 0.001) but more weakly with low-intensity physical activity (r = 0.07, P = 0.031).
Physical activity and the metabolic syndrome.
Men who engaged in <3.6 h·wk−1 of any leisure-time physical activity (lowest third) were 64% more likely to have the metabolic syndrome than those participating in ≥ 6.8 h·wk−1 of physical activity (highest third) after adjustment for age (Table 3). Low-intensity physical activity was not associated with the metabolic syndrome (Table 3). Men with <1 h·wk−1 of at least moderate-intensity physical activity (≥4.5 METs) were 63% more likely to have the metabolic syndrome than those with ≥ 3.0 h·wk−1 of such physical activity (Table 3). Further adjustment for age, smoking, alcohol consumption, and adulthood socioeconomic status did not affect the associations (Table 3), but the relationships disappeared after adjustment for BMI (data not shown).
Cardiorespiratory fitness and the metabolic syndrome.
V̇O2max had a strong, inverse, and graded association with the risk of having the metabolic syndrome. Men with the V̇O2max < 29.1 mL·kg−1·min−1 (lowest third) had a 6.4-fold and men with the V̇O2max 29.1–35.4 mL·kg−1·min−1 (middle third) had a 2.8-fold greater likelihood of having the metabolic syndrome than men with a V̇O2max ≥35.5 mL·kg−1·min−1 (highest third) after adjustment for age (Table 4). After further adjustment for other confounders, the least fit men were almost seven times more likely to have the metabolic syndrome. Adjustment for BMI weakened the association, but men with the V̇O2max < 29.1 mL·kg−1·min−1 and 29.1–35.4 mL·kg−1·min−1 still had a 3.6-fold (95% confidence interval 1.5–4.7, P = 0.001) and a 1.9-fold (95% confidence interval 1.05–3.3, P = 0.03) increased likelihood of having the metabolic syndrome, respectively.
Factor analysis and the metabolic syndrome.
In the factor analysis containing variables related to the metabolic syndrome, leisure-time physical activity, and cardiorespiratory fitness as well as smoking and alcohol intake, six factors that explained 58% of the total variance were extracted and rotated using the promax method. The factor explaining the greatest portion of the total variance (20%) had moderate and heavy loadings of the core components of the metabolic syndrome (Table 5) and was termed the metabolic syndrome factor. This factor also had heavy loadings for V̇O2max (−0.57) and at least moderate-intensity physical activity (−0.44). Low-intensity physical activity loaded weakly on the metabolic syndrome factor (−0.23). V̇O2max also loaded moderately on the smoking and inflammation (−0.31), dyslipidemia (−0.31), and blood pressure (−0.33) factors. Use of total leisure-time physical activity instead of its subcategories resulted in similar findings, with total physical activity also loading onto the metabolic syndrome factor (−0.37).
The promax rotation produces correlated factors. The principal factor of the first-order factor analysis had the strongest loadings for most of the main components of the metabolic syndrome and was therefore termed the metabolic syndrome factor. Nonetheless, the dyslipidemia factor, the blood pressure factor, and to a lesser extent the alcohol factor all had features of the metabolic syndrome (Table 5) and correlated with each other and the metabolic syndrome factor (r = 0.28–0.36). Factor analysis of the first-order factors with extraction and varimax rotation generated three second-order factors explaining 66% of the variance. The main second-order factor explaining 33% of the variance could clearly be termed the metabolic syndrome factor, with loading by the metabolic syndrome factor from the first-order analysis as well as the factors characterized by dyslipidemia, blood pressure, and alcohol (loadings >0.60). Measures of adiposity, insulin, lipids, blood pressure, and uric acid all loaded moderately to heavily on this factor variance. V̇O2max also loaded heavily on the second-order metabolic syndrome factor (−0.50), but interestingly, loadings for leisure-time physical activity were weak (<0.20). The smoking and inflammation factor and the hypercholesterolemia factor that were generated in the first-order analyses loaded onto respective second-order factors (0.95 and 0.94). The authors will provide additional data on the factor analyses upon request.
This is one of the few studies in a population-based cohort showing that individuals with low levels of leisure-time physical activity and cardiorespiratory fitness are more likely to have the metabolic syndrome, and to our knowledge, the first to demonstrate an association using a standard definition. Findings from the factor analyses furthermore suggest that a sedentary lifestyle and even more so cardiorespiratory fitness are not only associated with the metabolic syndrome but could also be considered features of the metabolic syndrome.
The CDC-ACSM guidelines recommend that all adults should engage in at least 30 min of moderate-intensity physical activity per day to prevent chronic diseases, including Type 2 diabetes and cardiovascular diseases (34). These guidelines also emphasize participation in not only conditioning but also lifestyle physical activity, and the accumulation of physical activity either continuously or in bouts throughout the day. The present findings suggest that sedentary men are more likely to have the metabolic syndrome than men complying with the CDC-ACSM recommendations, i.e., those who engage in at least 3 h·wk−1 of at least moderate-intensity conditioning or lifestyle physical activity. In a study in 711 working men who presented for preventive assessment at a private hospital previously (6), the age-adjusted association between physical activity and the likelihood of the clustering of metabolic factors decreased with increasing intensity of physical activity. In our study, low-intensity physical activity was not associated with the presence of the metabolic syndrome. Low-intensity physical activity has usually been less strongly associated with the risk of most chronic diseases than moderate or vigorous physical activity (22,34). The associations of total and at least moderate-intensity physical activity with the metabolic syndrome disappeared when BMI was controlled for, perhaps to be expected because of the crucial role of overweight and obesity in the metabolic syndrome, and because BMI is included in the definition of the metabolic syndrome.
An important finding of the present study is that directly measured V̇O2max had a strong, inverse, and graded association with the risk of having the metabolic syndrome independently of confounders. The least fit men (V̇O2max < 29.1 mL·kg−1·min−1, lowest third) were almost seven times more likely to have the metabolic syndrome than the most fit men (V̇O2max ≥35.5 mL·kg−1·min−1, highest third) when major confounders were allowed for. Even after controlling for BMI, the least fit men had a nearly fourfold likelihood of having the metabolic syndrome. Our findings agree with the results of two U.S. studies suggesting that low cardiorespiratory fitness is a major determinant of the metabolic syndrome (6,37). Whaley and coworkers (37) found a strong inverse dose-response relationship between total time on a maximal treadmill exercise test and the number of metabolic abnormalities in a large cohort of men and women attending the Cooper Clinic. Carroll and coworkers (6) observed an inverse dose-response relationship between V̇O2max (mL·kg−1·min−1), predicted indirectly with the strand-Rhyming method, and the likelihood of the clustering of metabolic factors.
The present data agree with previous findings that low levels of moderate and vigorous leisure-time physical activity and cardiorespiratory fitness are associated not only with core components of the metabolic syndrome but also with other factors known to be related to the metabolic syndrome, including serum uric acid and markers of inflammation and hemostasis such as blood leukocytes and plasma fibrinogen (6,9,18,35–37).
Factor analysis has been used to reduce intercorrelated variables into a smaller set of underlying factors that can be used to explain complex underlying physiological phenomena (7,24,29). Previous studies on the metabolic syndrome (7,24,29) have generated factors with differences at least in part related to the variables entered into the analyses, but the factor explaining the greatest variance has consistently had heavy loadings by measures of adiposity and fat distribution, insulin, and glucose (7,25,29). These studies have used the varimax rotation, which has been criticized, because it generates uncorrelated factors that may not reflect the underlying pathophysiological processes that link them (11). Accordingly, we used a promax rotation to generate correlated factors (11). The principle factor explaining 20% of the total variance most strongly characterized the metabolic syndrome. The dyslipidemia factor, blood pressure factor, and to a lesser extent the alcohol factor also had features of the metabolic syndrome. The second-order factor analysis generated a metabolic syndrome factor that was loaded onto heavily by the principle factor from the first analysis that best characterized the metabolic syndrome as well as the three other factors with features of the metabolic syndrome. This principal second-order factor was strongly loaded onto by the main components of the metabolic syndrome. Overall, the factor analyses suggest that the metabolic syndrome has variable manifestations but that there is nonetheless an underlying pathophysiological commonality. We have previously shown in a simpler factor analysis that the metabolic syndrome factor predicted cardiovascular mortality (15). The metabolic syndrome factor in this study, using perhaps a biologically more relevant approach (11), also strongly predicts cardiovascular mortality and incident diabetes (data not shown).
In the first-order factor analysis, both V̇O2max (−0.57) and at least moderate-intensity leisure-time physical activity (−0.44) loaded heavily on the principle factor explaining 20% of the total variance that most strongly characterized the metabolic syndrome. V̇O2max also loaded onto the dyslipidemia factor and the blood pressure factor. In the second-order factor analysis, V̇O2max (−0.50), but not low-intensity or at least moderate-intensity physical activity (<0.20), loaded onto the metabolic syndrome factor. Previously, a study in 970 Helsinki policemen found a physical activity to be weakly loaded (−0.25) and V̇O2max to be heavily loaded (−0.66) onto the metabolic syndrome factor generated after varimax rotation (29). In that study, however, a crude dichotomized measure of physical activity was used, and V̇O2max was measured indirectly with a submaximal exercise test. Physical activity also weakly loaded onto the insulin resistance factor (−0.25) in a study of 522 senior company employees using factor analysis restricted to factors with eigenvalues ≥ 2.0 (9). Physical activity was even more crudely assessed, however (based on only the recall of regular, occasional, or no walking).
Accurate assessment of habitual leisure-time physical activity and cardiorespiratory fitness in epidemiological studies is difficult. Physical activity was measured using the KIHD 12-month Leisure-time Physical Activity Questionnaire, which provides detailed and quantitative information on the frequency, duration, and intensity of habitual leisure-time physical activity as recalled for the preceding 12 months. When readministered 12 months later, leisure-time physical activity in the questionnaire was quite repeatable (17). Even so, the associations between leisure-time physical activity and the metabolic syndrome in both logistic regression and factor analyses are underestimated because of the inherent imprecision of physical activity questionnaires. It is likely that the association between physical activity and the metabolic syndrome would have been stronger if an objective and more accurate measure of physical activity had been used. Of the main components of the metabolic syndrome, occupational physical activity correlated only with serum triglycerides, and we therefore focused on leisure-time physical activity. A strength of the present study is that V̇O2max was measured directly using a respiratory gas exchange analysis during a maximal symptom-limited cycle ergometer exercise test under standardized conditions, which is an accurate and highly reproducible measure of cardiorespiratory fitness (2). This likely explains at least in part the fact that the associations of V̇O2max with the components of the metabolic syndrome were stronger than the relationships of physical activity. Because cardiorespiratory fitness also has a strong genetic component, caution should nonetheless be used when extrapolating the associations of cardiorespiratory fitness with the metabolic syndrome to physical activity.
Our findings, based on a detailed and validated physical activity questionnaire and a directly measured V̇O2max from a maximal exercise test, suggest that a sedentary lifestyle and even more so poor cardiorespiratory fitness could be considered features of the metabolic syndrome. These data may partly explain our previous observations that low levels of leisure-time physical activity and cardiorespiratory fitness are associated with increased risk for Type 2 diabetes (22), coronary heart disease (19), and cardiovascular and overall mortality (20), as well as accelerated progression of carotid atherosclerosis (16). The present data together with previous findings support the CDC-ACSM recommendations for regular physical activity and good cardiorespiratory fitness in the prevention of the metabolic syndrome and ultimately Type 2 diabetes and cardiovascular diseases. Measurement of V̇O2max in sedentary men with risk factors may provide an efficient means for targeting individuals who would benefit from interventions to prevent the metabolic syndrome and its consequences.
We are indebted to Juha M. Venäläinen, M.D., Esko Taskinen, M.D., Riitta Salonen, M.D., and Hannu Litmanen, M.D., for supervising the exercise stress tests and to Kristiina Nyyssönen, Ph.D., and Kari Seppänen, M.Sc., for supervising the chemical analyses.
The KIHD study was supported by grants from the Academy of Finland (grants for projects 41471, 1041086 and 2041022), the Ministry of Education of Finland (grants for projects 167/722/96, 152/722/97, 156/722/98, 134/722/99 and 157/722/2000), and the City of Kuopio. Timo Lakka was supported by grants from the Academy of Finland, the Yrjo Jahnsson Foundation, the Paavo Nurmi Foundation, and the University of Kuopio.
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