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Erschienen in: BMC Geriatrics 1/2020

Open Access 01.12.2020 | Research article

Non-exercise based estimation of cardiorespiratory fitness is inversely associated with metabolic syndrome in a representative sample of Korean adults

verfasst von: Inhwan Lee, Shinuk Kim, Hyunsik Kang

Erschienen in: BMC Geriatrics | Ausgabe 1/2020

Abstract

Background

This study investigated the association between non-exercise based estimation of cardiorespiratory fitness (eCRF) and metabolic syndrome (Mets) in Korean adults aged 18 years and older (13,400 women and 9885 men).

Methods

Data from the 2008 and 2011 Korea National Health and Nutrition Examination Surveys IV and V in South Korea were analyzed. eCRF was assessed with a previously validated procedure. Participants were classified into 5 categories from the lowest quantile to the highest quantile based on individual eCRF distributions.

Results

The findings showed an independent and inverse association between eCRF and Mets in women and men separately. Individuals in the highest eCRF category (quantile 5) had a significantly lower prevalence of Mets (14.5 and 14.8% for women and men, respectively) compared with their counterparts (40.4 and 46.4% for women and men, respectively) in the lowest eCRF category (quantile 1), and the association showed a graded response, with the quantiles 2, 3, and 4 also significantly associated with a lower prevalence of Mets compared with the quantile 1. Furthermore, the prevalence of Mets in the highest quantile compared with the lowest quantile remained statistically significant in both men (p < 0.05) and women (p < 0.05) even after adjustments for age, body mass index, skeletal muscle index, smoking, heavy drinking, vitamin D, caloric intake, and dietary intakes of carbohydrates, fats, and proteins.

Conclusion

The findings support a preventive role for eCRF against Mets in Korean adults.
Hinweise

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Abkürzungen
eCRF
non-exercise based estimation of cardiorespiratory fitness
Mets
metabolic syndrome
CVDs
Cardiovascular diseases
KNHANES
Korea National Health and Nutrition Examination Surveys
Peak VO2
Peak volume of oxygen consumption
HOMA-IR
Homeostasis model assessment of insulin resistance
ASM
Appendicular skeletal muscle mass
DXA
Dual energy X-ray absorptiometry
SMI
Skeletal muscle index

Background

Metabolic syndrome (Mets) represents a clustering of risk factors such as central obesity, hyperglycemia, hypertension, hypertriglyceridemia, and decreased high-density lipoprotein cholesterol [1]. Left untreated, Mets leads to the development of non-communicable diseases, such as type 2 diabetes and cardiovascular diseases (CVDs) in residents of both developed and developing countries [2, 3]. Western lifestyles characterized by obesity and physical inactivity have been blamed for the etiology of the global epidemic [1]. Along with unhealthy lifestyles, low level of cardiorespiratory fitness (CRF), which reflects the maximal capacity of the respiratory and cardiovascular systems to supply oxygen to working skeletal muscles during exercise, is another well-established risk factor of Mets [4, 5]. Low CRF is also associated with an increased risk of all- and specific-cause mortality [68].
In Korea, a third of adults suffer from Mets. The prevalence of Mets is on the rise, particular in men, and in those of advancing age, with the greatest prevalence seen in elderly persons [9]. Considering continuing rise in prevalence and adverse consequences in conjunction with a rapidly aging society, Mets will continue to represent a key public health issue in Korea. Obesity and physical inactivity have been suggested as two of the primary lifestyle risk factors responsible for Mets in Korea [10]. However, less attention has been paid to investigating the impact of CRF for Mets in Korean populations. A literature review uncovered only 2 studies that examined physical fitness in relation to Mets in Korean adults. In a cross-sectional study involving 227 older adults aged 60 years and older, Hwang and Kim [11] examined the association between physical performances of a sit-up test and the Tecumseh step test as indices of muscular fitness and cardiopulmonary fitness, respectively, and they reported an inverse relationship between muscular and/or cardiopulmonary fitness and Mets. In another study involving 1007 Korean adults who underwent routine health checkups, Hong et al. [12] examined the association between a step test-based CRF and Mets, and they found that low CRF and obesity were significantly associated with an increased risk of Mets. Those previous studies recognized a prognostic role of CRF but failed to prove it in a representative sample of Korean adults. Consequently, the relationship of CRF with Mets in Korean populations remains to be confirmed.
Objectively measuring CRF is often limited by the need for specialized equipment, trained personnel, sufficient time, and other factors [8], especially in a population-based study involving a large sample size. To circumvent those limitations, Jurca et al. [13] showed that CRF can be estimated from routinely obtained health indicators with an acceptable accuracy. We previously showed that this non-exercise based estimation of CRF (eCRF) could be used an alternative tool to estimate the risk of morbidity and mortality from all and specific causes in Korean adults [14]. This study examined the association between eCRF and Mets in a representative sample of Korean adults aged 18 years and older.

Methods

Data source and study population

The data used for this study were drawn from the Korea National Health and Nutrition Examination Surveys (KNHANES) IV and V, which were conducted nationwide in South Korea from 2008 until 2011. A detailed description of the KNHANES, including the sampling method, is available elsewhere [15, 16]. For the current study, we selected a total of 28,071 adults aged 18 years and older from those who participated in the 2008–2011 KNHANES IV and V. Of them, 1899 individuals were excluded because parameters (46 missing in height and weight, 1571 missing resting heart rate, and 282 missing in physical activity) used to estimate CRF were not available. An additional 2887 were excluded because the components of Mets (1601 missing in waist circumference, 1267 missing in fasting blood glucose, 17 missing in resting blood pressure, and 2 missing in blood lipids) were not available. Ultimately, 23,285 adults (13,400 women and 9885 men) were included in the final data analyses (Fig. 1). The Korean National Institute for Bioethics Policy reviewed and approved the study design (P01–201504–21-005) in accordance with the Declaration of Helsinki. Informed consent was obtained from all of the study. Written informed consent was obtained from all participants included in the study.

Estimation of cardiorespiratory fitness

Non-exercise-based estimation of CRF (eCRF) was determined as peak volume of oxygen consumption (peak VO2) using a formula described by Jurca et al. [13]: eCRF (ml·kg− 1·min− 1) = 2.77 (men = 0 and women = 1) - 0.10 (age) - 0.17 (body mass index) - 0.03 (resting heart rate) + 1.00 (physical activity score) + 18.07.
Participants were then classified into five categories (from the lowest to the highest quantile) on the basis of age- and sex-specific quantiles of their estimated peak VO2 distributions.

Clinical and laboratory measurements

Participants were required to complete self-administered questionnaires regarding smoking and alcohol habits, physical activity, and past medical history. Smoking status was classified as current smokers or non-smokers. Heavy drinking was defined as > 14 drinks/week for men and > 7 drinks/week for women on the basis of drinking frequency (days per week) and quantify (drinks per week) in the past year [17]. The Korean version of International Physical Activity Questionnaire (IPAQ) short form was used to assess frequency (times/week) and duration (minutes) of physical activity lasting for at least 10 min according to intensity (light, moderate, and vigorous, which were expressed in METs-minutes/week. The validity and reliability of the IPAQ was reported in a previous study involving Korean adults [18].
Height, weight, waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), and dietary intakes of carbohydrates, fats, and proteins were assessed by trained persons. Height and weight were measured with a portable stadiometer (seca 225 stadiometer, SECA, CA, USA) and a portable scale (GL-6000-20, G-technology, Seoul, Korea), respectively, and body mass index (BMI) was calculated as weight divided by height (kg/m2).
Resting blood pressures were measured with a sphygmomanometer (Baumanometer® wall unit 33, Baum Co. Inc., NY, USA) with the subjects in seated position, with the arm at heart level and resting on the armrest of a chair. For resting heart rate (RHR) measurement, pulse rates at the wrist were counted in 15 s and multiplied by 4: RHR (betas/min) = the number of pulse rates in 15 s × 4. Pulse rates were counted in three separate times, and average values of the second and third counts were used. The Korean version of food frequency questionnaire with an acceptable accuracy [19] was used to assess dietary intakes of carbohydrates (g/day), fats (g/day), and proteins (g/day) in conjunction with caloric intake (kcal/day).
Appendicular skeletal muscle mass (ASM) was measured with a dual energy X-ray absorptiometry (DXA). Skeletal muscle index (SMI) was calculated by dividing the sum of ASM in the bilateral upper and lower four limbs (kg) by body weight (kg) as expressed as percentage as a modified formula from the study of Janssen et al. [20]: SMI (%) = ASM (kg) / body weight (kg) × 100. The ASM/body weight method was used previous studies involving Korean populations [21].
Fasting venous blood sampling was performed after overnight fasting to determine concentrations of glucose, total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), insulin, hemoglobin A1c (HbA1c), and vitamin D. Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated using a formula described by Mattew et al. [22]: fasting insulin (uU/L) x fasting glucose (nmol/L)/22.5. A detailed description of the clinical and laboratory measurements is available elsewhere [15, 16].

Definition of metabolic syndrome

Mets was defined according to the revised National Cholesterol Education Program definition [23] with adoption of a Korean-specific WC threshold [24]. Individuals with three or more of the following criteria were defined as having Mets: 1) abdominal obesity; WC > 90 cm in men or > 85 cm in women; 2) hypertriglyceridemia; TG > 150 mg/dL or medication use; 3) low HDL-C; HDL-C < 40 mg/dL in men and < 50 mg/dL in women; 4) high resting blood pressure; SBP > 130 mmHg and/or DBP > 85 mmHg or use of antihypertensive agents; and 5) hyperglycemia; glucose > 100 mg/dL or use of anti-diabetic medication.

Statistics

All variables were checked for normality, both visually and through the Kolmogorov-Smirnov test, and subjected to log10 transformation (i.e., TG, fasting glucose, fasting insulin, HOMA-IR, and HbA1c, physical activity), if necessary, prior to statistical analyses. Descriptive statistics were presented as means and standard deviations for continuous variables and as percentages for categorical variables. Analysis of variance (ANOVA) was used to test any significant differences in the measured variables between men and women or between those with and without Mets. Odd ratio (OR) and 95% confidence interval (95% CI) for Mets were calculated according to eCRF quantiles using multiple logistic regression before and after adjustments for all measured covariates. Alpha was set at 0.05. All statistical analyses were performed using the SPSS-PC statistical software (version 23.0, SPSS, Inc.).

Results

Table 1 represents characteristics of study participants. Men had higher BMI (p < 0.001), waist circumference (p < 0.001), SMI (p < 0.001), physical activity (p < 0.001), eCRF (p < 0.001), resting blood pressures (p < 0.001), triglycerides (p < 0.001), fasting glucose (p < 0.001) and insulin (p < 0.001), HbA1c (p < 0.001), serum vitamin D (p < 0.001), caloric intake (p < 0.001), intakes of protein (p < 0.001), fat (p < 0.001), and carbohydrates (p < 0.001), smoking (p < 0.001), and heavy drinking (p < 0.001) but lower resting heart rate (p < 0.001) and HDL-C (p < 0.001) compared with women. No significant differences in age and HOMA-IR were observed between men and women.
Table 1
Descriptive statistics of study participants
Characteristic
Women
(N = 13,400)
Men
(N = 9885)
Total
(N = 23,285)
Age (years)
49.1 ± 16.1
49.0 ± 15.8
49.0 ± 16.0
Body mass index (kg/m2)a
23.4 ± 3.5
24.0 ± 3.1
23.7 ± 3.3
Waist circumference (cm)a
78.8 ± 10.0
84.6 ± 8.9
81.2 ± 9.9
Skeletal muscle index (%)a
27.0 ± 2.7
34.1 ± 3.0
30.0 ± 4.5
Physical activity (METs-minutes/week)a
2399.8 ± 3931.1
3299.4 ± 4885.4
2781.7 ± 4384.3
Resting heart rate (beats/min)a
71.4 ± 9.1
70.1 ± 9.6
70.8 ± 9.3
eCRF (ml/kg/min)a
29.0 ± 7.8
39.6 ± 7.6
33.5 ± 9.3
Systolic BP (mmHg)a
116.7 ± 18.1
121.8 ± 15.9
118.8 ± 17.4
Diastolic BP (mmHg)a
74.3 ± 10.3
79.7 ± 10.6
76.6 ± 10.7
Total cholesterol (mg/dL)a
189.4 ± 36.6
187.5 ± 35.7
188.6 ± 36.3
HDL-C (mg/dL)a
50.8 ± 11.6
45.8 ± 10.8
48.7 ± 11.5
Triglycerides (mg/dL)a
115.8 ± 81.6
159.7 ± 136.7
134.5 ± 110.6
Glucose (mg/dL)a
96.1 ± 21.7
100.3 ± 25.3
97.9 ± 23.4
Insulin (μU/mL)a
10.1 ± 5.9
9.9 ± 5.6
10.0 ± 5.8
HbA1c (%)a
6.1 ± 1.2
6.2 ± 1.3
6.2 ± 1.3
HOMA-IR
2.5 ± 2.3
2.5 ± 1.8
2.5 ± 2.1
Vitamin D (ng/mL)a
17.2 ± 6.4
19.8 ± 6.9
18.3 ± 6.7
Caloric intake (kcal/day)a
1648 ± 641
2297 ± 922
1907 ± 829
Protein (g/day)a
57.9 ± 29.3
82.5 ± 43.7
67.7 ± 37.7
Fat (g/day)a
30.9 ± 24.1
45.3 ± 35.6
36.6 ± 30.1
Carbohydrate (g/day)a
285.6 ± 111.5
354.9 ± 127.1
313.2 ± 122.7
Current/past smokers, n (%)a
1297 (9.7)
7808 (79.0)
9105 (39.1)
Heavy drinking, n (%)a
619 (4.6)
2389 (24.2)
3008 (13.0)
BP blood pressure, HDL-C high-density lipoprotein cholesterol, eCRF non-exercise-based estimation of cardiorespiratory fitness, HOMA homeostatic model assessment of insulin resistance
aSignificant difference between men and women (p < 0.001)
Table 2 represents the prevalence of each risk factor defining Mets. Decreased HDL-C was the most frequent risk factor, followed by hypertension, hypertriglyceridemia, hyperglycemia, and central obesity. Table 3 represents the proportion of clustering of one or more risk factors for Mets. The presence of Mets was 25.7% in the total group. Men had a higher prevalence of Mets than women (28.7% vs. 23.5%) (p < 0.001). Table 4 compares physical characteristics and risk factors of those with and without Mets. As expected, individuals with Mets were older, heavier, and physically less fit and had more severe profiles of risk factors compared with individuals without Mets.
Table 2
Prevalence of metabolic syndrome risk factors
Risk factor
Women
Men
Combined
Waist circumferencea
26.6% (3563)
26.8% (2650)
26.7% (6213)
Fasting blood glucoseb
23.1% (3102)
33.6% (3321)
27.6% (6423)
Blood pressurec
26.9% (3603)
40.3% (3988)
32.6% (7591)
HDL-Cd
51.3% (6880)
33.3% (3292)
43.7% (10,172)
Triglyceridese
22.1% (2968)
38.1% (3771)
28.9% (6739)
HDL-C high-density lipoprotein cholesterol
a > 90 for men and > 85 cm for women
b > 100 mg/dL or drug treatment for impaired fasting glucose
c > 130 systolic or > 85 diastolic blood pressure or drug treatment for hypertension
d < 40 mg/dL for men; < 50 mg/dL for women
e > 150 mg/dL or drug treatment for high serum triglycerides
Table 3
Clustering of metabolic syndrome risk factors
No. of risk factors meeting threshold
Women
Men
Combined
0
27.8% (3725)
22.4% (2218)
25.5% (5943)
1
29.5% (3955)
25.2% (2489)
27.7% (6444)
2
19.2% (2577)
23.7% (2344)
21.1% (4921)
3
13.8% (1845)
17.3% (1714)
15.3% (3559)
4
7.6% (1018)
9.1% (897)
8.2% (1915)
5
2.1% (280)
2.3% (223)
2.2% (503)
Individuals with three or more of the risk factors were coded for analyses as having the metabolic syndrome
Table 4
Individuals with metabolic syndrome (Mets) compared with apparently healthy individuals
Parameters
Individuals with Mets (N = 5977)
Individuals without Mets (N = 17,308)
Women, n (%)a
3143 (52.6)
10,257 (59.3)
Age (years)a
56.6 ± 14.0
46.4 ± 15.8
Body mass index (kg/m2)a
26.1 ± 3.2
22.8 ± 3.0
Waist circumference (cm)a
89.6 ± 8.1
78.4 ± 8.8
Skeletal muscle index (%)a
28.9 ± 4.2
30.4 ± 4.5
Physical activity (METs-minutes/week)
2716.3 ± 4354.5
2804.2 ± 4394.4
Resting heart rate (beats/min)a
71.6 ± 9.5
70.6 ± 9.3
eCRF (ml/kg/min)a
29.6 ± 9.5
34.8 ± 8.9
Systolic BP (mmHg)a
131.1 ± 16.6
114.6 ± 15.6
Diastolic BP (mmHg)a
82.6 ± 10.6
74.5 ± 10.0
Total cholesterol (mg/dL)a
199.1 ± 38.9
185.0 ± 34.6
HDL-C (mg/dL)a
41.2 ± 8.7
51.2 ± 11.3
Triglycerides (mg/dL)a
217.2 ± 150.0
105.9 ± 74.2
Glucose (mg/dL)a
112.3 ± 31.3
92.9 ± 17.3
Insulin (μU/mL)a
12.5 ± 8.4
9.1 ± 4.2
HbA1c (%)a
6.8 ± 1.4
5.8 ± 1.0
HOMA-IRa
3.5 ± 3.3
2.1 ± 1.2
Vitamin D (ng/mL)a
18.8 ± 6.7
18.1 ± 6.7
Caloric intake (kcal/day)a
1877.9 ± 844.4
1917.2 ± 823.2
Protein (g/day)a
64.7 ± 36.9
68.8 ± 37.9
Fat (g/day)a
32.1 ± 28.5
38.2 ± 30.4
Carbohydrate (g/day)
314.6 ± 120.9
312.8 ± 123.4
Current/past smokers, n (%)a
2639 (44.2)
6466 (37.4)
Heavy drinking, n (%)a
921 (15.5)
2087 (12.1)
Individuals with three or more of metabolic syndrome risk factors (i.e.., central obesity, hypertension, hyperglyceridemia, hypertriglyceridemia, and low HDL-C) were coded for analyses as having the metabolic syndrome (Mets)
BP blood pressure, HDL-C high-density lipoprotein cholesterol, eCRF non-exercise-based estimation of cardiorespiratory fitness, HOMA homeostatic model assessment of insulin resistance
aSignificant difference between individuals with and without metabolic syndrome (p < 0.001)
Table 5 represents the results of logistic regression analyses for Mets. An inverse and graded association between eCRF and Mets was found in women (p < 0.001) and men (p < 0.001) separately. In women, the prevalence of Mets ranged from 40.0% in the lowest quantile of eCRF (quantile 1) to 14.5% in the highest quantile of eCRF (quantile 5), and the association showed a graded response, with the quantiles 2, 3, and 4 also significantly associated with a lower prevalence of the Mets compared with the quantile 1. In men, similarly, the prevalence of Mets ranged from 46.4% in the lowest quantile to 14.8% in the highest quantile, and the association showed a graded response, with the quantiles 2, 3, and 4 also significantly associated with a lower prevalence of Mets compared with the quantile 1. The lower prevalence of Mets for the highest quantile compared with the lowest quantile remained significant in both men and women even after adjustments for age (p < 0.001 and p < 0.001 in men and women, respectively) and additionally adjustments for BMI, SMI, physical activity, smoking, heavy drinking, vitamin D, caloric intakes, and intakes of macronutrients (p < 0.05 and p < 0.05 in men and women, respectively).
Table 5
Prevalence and logistic regression models for metabolic syndrome according to non-exercise-based estimation of cardiorespiratory fitness (eCRF) categories
Model
Quantile 1 (lowest)
Quantile 2
Quantile 3
Quantile 4
Quantile 5 (highest)
Women, No. of case
1070 (40.0)
619 (23.1)
476 (15.1)
589 (22.0)
389 (14.5)
OR
1.0
0.451** (0.401–0.508)
0.325** (0.286–0.368)
0.423** (0.375–0.477)
0.255** (0.224–0.291)
ORa
1.0
0.414** (0.363–0.472)
0.303** (0.264–0.348)
0.397** (0.348–0.453)
0.231** (0.200–0.267)
ORb
1.0
0.915 (0.761–1.100)
0.955 (0.793–1.149)
0.862 (0.714–1.041)
0.715* (0.570–0.897)
ORc
1.0
0.952 (0.790–1.147)
0.860 (0.704–1.051)
0.862 (0.710–1.046)
0.738* (0.587–0.928)
Men, No. of case
916 (46.4)
503 (25.4)
525 (26.6)
597 (30.2)
293 (14.8)
OR
1.0
0.394** (0.344–0.450)
0.418** (0.365–0.477)
0.499** (0.438–0.569)
0.201** (0.173–0.234)
ORa
1.0
0.397** (0.346–0.454)
0.425** (0.372–0.487)
0.504** (0.442–0.576)
0.206** (0.176–0.240)
ORb
1.0
0.940 (0.785–1.125)
0.863 (0.712–1.047)
0.852 (0.708–1.026)
0.730* (0.585–0.911)
ORc
1.0
0.864 (0.707–1.056)
0.941 (0.767–1.153)
0.872 (0.710–1.072)
0.664* (0.517–0.852)
OR odds ratio. Data are presented as OR (95% confidence interval)
Adjusted for age
Adjusted for age, body mass index, skeletal muscle index, physical activity, smoking, and heavy drinking
Adjusted for age, body mass index, skeletal muscle index, physical activity, smoking, heavy drinking, vitamin D, caloric intake, and intakes of protein, fat, and carbohydrate
**Significantly different compared with individuals in the lowest eCRF category (Quantile 1) at p < 0.001
*Significantly different compared with individuals in the lowest eCRF category (Quantile 1) at p < 0.05

Discussion

In this population-based study, we examined the association between eCRF and Mets in Korean adults and found that eCRF was inversely associated with Mets, with men more likely to have a higher prevalence of Mets compared with women. This was the first study to show that the inverse association between eCRF and Mets remained statistically significant even after adjustments for all the covariates, implying a preventive role of CRF against the development of Mets in Korean adults.
The current findings of the study are in accordance with previous studies reporting an inverse association between CRF and Mets in Western populations. By analyzing the data obtained from two clinical trials involving 170 African-American postmenopausal women aged 40–65 years, for example, Adams-Campbel et al. [25] showed that individuals with very low CRF (< 18 mL·kg− 1 ·min− 1) had a higher prevalence of Mets, abdominal obesity, hypertriglyceridemia, and low HDL compared with individuals with moderate CRF (> 22 mL·kg− 1 ·min− 1), and the inverse association between CRF and Mets remained significant after adjustments for age, marital status, income, education, body composition, and other risk factors. By conducting a cohort of 3636 adults (1629 women) who participated in the Ball State Adult Fitness Program Longitudinal Lifestyle Study, Kelly et al. [26] also found an inverse and graded association between quartiles of CRF and Mets for both women and men, and the inverse association remained statistically significant even after adjustments for age at test date, physical activity, and cigarette smoking status. In addition, Ingle et al. [27] showed that fit British men had an approximately 50% lower prevalence of Mets compared with unfit British men, particularly in those aged 50 years or younger.
Similarly, an inverse association between CRF and Mets has been reported from previous studies involving Asian populations, such as Chinese women [28], Japanese women [29], and Chinese children [30]. In Korea, previous studies reported a significant association between physical fitness and Mets in older adults [11]. Similarly, parameters of muscular fitness and cardiopulmonary fitness were inversely and independently associated with the prevalence of Mets in older Korean adults [11]. Both high BMI and poor CRF were significantly associated with a higher prevalence of Mets in Korean adults [12], implying a synergistic effect of obesity and poor physical fitness on the etiology of Mets. In agreement with, Kim et al. [31] examined the relationship of visceral adiposity and CRF with Mets in a sample of 232 Korean overweight and obese adults, and found that high visceral adiposity and low CRF were additively associated with Mets. In that study, they also showed that high CRF alleviated the deleterious impact of visceral adiposity on Mets, implying CRF as a modifier in determining the relationship between visceral adiposity and Mets. Together, the findings of the current study agree with and extend the previous studies reporting eCRF as an independent predictor of Mets in Korean populations.
The preventive effects of higher eCRF quantiles against the prevalence of Mets observed in the present study represent levels that are attainable by most individuals. eCRF levels of approximately 29.9 mL/kg/min (or 8.5 METs) and 19.5 mL/kg/min (or 5.6 Mets) for men and women, respectively, represent the thresholds between the lowest quantile of eCRF and the second quantile of eCRF and are reasonably achievable through aerobic exercise. A lower prevalence of Mets was seen in those who were in the upper 4 quantiles in a dose-response manner, suggesting that further prevention against Mets can be achieved as one moves up the eCRF continuum with exercise training. In addition, the current findings show that logistic results for women and men were independent of all measured confounders, including age, markers of obesity and sarcopenia, physical activity, smoking, heavy drinking, vitamin D, caloric intake and intakes of macronutrients.
Several explanations can be given for the sex difference in the prevalence of Mets observed in the current study. First, we found that Korean men were more centrally obese than women. Central obesity is closely associated with whole body insulin resistance [9]. Consequently, central obesity-related insulin resistance, as shown by elevated levels of plasma insulin and HbA1c, is likely to have contributed to the sex difference. Second, an analysis by Oh et al. [32] of the 1988 KNHANES data showed that smoking was significantly associated with elevated TG and decreased HDL-C in conjunction with abdominal obesity in a dose-response manner. A higher rate of smoking might therefore have played a role in the sex difference we found. Lastly, other lifestyle risk factors such as heavy alcohol consumption, excessive caloric intakes, sarcopenic obesity, and physical inactivity may have played additional roles in determining the sex difference in the prevalence of Mets between Korean men and women [12, 21]. In particular, several mechanisms can be involved in the independent and inverse association between eCRF and Mets. First, CRF is positively associated with insulin sensitivity and/or insulin action in both overweight/obese [33] and normal subjects [34], implying its protective effect against Mets by enhancing insulin sensitivity. Second, high CRF provides a protective effect against Mets by suppressing pro-inflammation while enhancing anti-inflammation [35]. Third, high CRF alleviates the deleterious effects of central obesity and Mets [36]. Lastly, high CRF-induced promotion of mitochondrial biogenesis may lead to protection from Mets [37].
This study has several strengths and limitations. Strengths include a large sample size that is representative of Korean women and men over a wide range of age. To the best of our knowledge, this study represents the largest and Korean population-based study reporting an inverse association between eCRF and Mets after adjustment for a number of relevant confounders. In addition, the current findings support the use of eCRF as an alternative tool used to predict the risk of Mets. One study limitation is the inclusion of non-exercise-based estimates for CRF rather than objective measurements. The accuracy of eCRF used in the current study remains to be confirmed in a representative sample of Korean adults. The cross-sectional nature of the current study is another limitation in drawing conclusions about causation.

Conclusion

The current findings confirm a protective role of eCRF against the development of Mets in Korean women and men, implying that adopting a more physically active lifestyle and promoting fitness can be clinically important in upper quantiles, especially for the lowest quantile of eCRF.

Acknowledgements

We gratefully thank the Korea Centers for Disease Control and Prevention (KCDC) for allowing use of their data for this study.
The Sungkunwan University institutional review board of human study reviewed and approved the study protocol (SKKU 2017–06-009). Written informed consent was obtained from all participants.
No applicable.

Competing interests

The corresponding author (HK) declares that he currently serves as an associate editor of this journal.
Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creativecommons.​org/​licenses/​by/​4.​0/​. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Literatur
1.
Zurück zum Zitat Grundy SM, Brewer HB Jr, Cleeman JI, Smith SC Jr, Lenfant C, National Heart L, Blood I, American HA. Definition of metabolic syndrome: report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Arterioscler Thromb Vasc Biol. 2004;24:e13–8.PubMed Grundy SM, Brewer HB Jr, Cleeman JI, Smith SC Jr, Lenfant C, National Heart L, Blood I, American HA. Definition of metabolic syndrome: report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Arterioscler Thromb Vasc Biol. 2004;24:e13–8.PubMed
2.
Zurück zum Zitat Hanson RL, Imperatore G, Bennett PH, Knowler WC. Components of the "metabolic syndrome" and incidence of type 2 diabetes. Diabetes. 2002;51:3120–7.CrossRef Hanson RL, Imperatore G, Bennett PH, Knowler WC. Components of the "metabolic syndrome" and incidence of type 2 diabetes. Diabetes. 2002;51:3120–7.CrossRef
3.
Zurück zum Zitat Mottillo S, Filion KB, Genest J, Joseph L, Pilote L, Poirier P, Rinfret S, Schiffrin EL, Eisenberg MJ. The metabolic syndrome and cardiovascular risk a systematic review and meta-analysis. J Am Coll Cardiol. 2010;56:1113–32.CrossRef Mottillo S, Filion KB, Genest J, Joseph L, Pilote L, Poirier P, Rinfret S, Schiffrin EL, Eisenberg MJ. The metabolic syndrome and cardiovascular risk a systematic review and meta-analysis. J Am Coll Cardiol. 2010;56:1113–32.CrossRef
4.
Zurück zum Zitat Myers J, McAuley P, Lavie CJ, Despres J-P, Arena R, Kokkinos P. Physical activity and cardiorespiratory fitness as major markers of cardiovascular risk: their independent and interwoven importance to health status. Prog Cardiovasc Dis. 2015;57:306–14.CrossRef Myers J, McAuley P, Lavie CJ, Despres J-P, Arena R, Kokkinos P. Physical activity and cardiorespiratory fitness as major markers of cardiovascular risk: their independent and interwoven importance to health status. Prog Cardiovasc Dis. 2015;57:306–14.CrossRef
5.
Zurück zum Zitat Swift DL, Lavie CJ, Johannsen NM, Arena R, Earnest CP, O’keefe JH, Milani RV, Blair SN, Church TS. Physical activity, cardiorespiratory fitness, and exercise training in primary and secondary coronary prevention. Circ. J. 2013;77:281–92.CrossRef Swift DL, Lavie CJ, Johannsen NM, Arena R, Earnest CP, O’keefe JH, Milani RV, Blair SN, Church TS. Physical activity, cardiorespiratory fitness, and exercise training in primary and secondary coronary prevention. Circ. J. 2013;77:281–92.CrossRef
6.
Zurück zum Zitat Kodama S, Saito K, Tanaka S, Maki M, Yachi Y, Asumi M, Sugawara A, Totsuka K, Shimano H, Ohashi Y, Yamada N, Sone H. Cardiorespiratory fitness as a quantitative predictor of all-cause mortality and cardiovascular events in healthy men and women: a meta-analysis. JAMA. 2009;301:2024–35.CrossRef Kodama S, Saito K, Tanaka S, Maki M, Yachi Y, Asumi M, Sugawara A, Totsuka K, Shimano H, Ohashi Y, Yamada N, Sone H. Cardiorespiratory fitness as a quantitative predictor of all-cause mortality and cardiovascular events in healthy men and women: a meta-analysis. JAMA. 2009;301:2024–35.CrossRef
7.
Zurück zum Zitat Schmid D, Leitzmann M. Cardiorespiratory fitness as predictor of cancer mortality: a systematic review and meta-analysis. Ann Oncol. 2014;26:272–8.CrossRef Schmid D, Leitzmann M. Cardiorespiratory fitness as predictor of cancer mortality: a systematic review and meta-analysis. Ann Oncol. 2014;26:272–8.CrossRef
8.
Zurück zum Zitat Wang Y, Chen S, Zhang J, Zhang Y, Ernstsen L, Lavie CJ, Hooker SP, Chen Y, Sui X. Nonexercise estimated cardiorespiratory fitness and all-cancer mortality: the NHANES III study. Mayo Clin Proc. 2018;93:848–56.CrossRef Wang Y, Chen S, Zhang J, Zhang Y, Ernstsen L, Lavie CJ, Hooker SP, Chen Y, Sui X. Nonexercise estimated cardiorespiratory fitness and all-cancer mortality: the NHANES III study. Mayo Clin Proc. 2018;93:848–56.CrossRef
10.
Zurück zum Zitat Oh SW. Obesity and metabolic syndrome in Korea. Diabetes Metab J. 2011;35:561–6.CrossRef Oh SW. Obesity and metabolic syndrome in Korea. Diabetes Metab J. 2011;35:561–6.CrossRef
13.
Zurück zum Zitat Jurca R, Jackson AS, LaMonte MJ, Morrow JR Jr, Blair SN, Wareham NJ, Haskell WL, van Mechelen W, Church TS, Jakicic JM, Laukkanen R. Assessing cardiorespiratory fitness without performing exercise testing. Am J Prev Med. 2005;29:185–93.CrossRef Jurca R, Jackson AS, LaMonte MJ, Morrow JR Jr, Blair SN, Wareham NJ, Haskell WL, van Mechelen W, Church TS, Jakicic JM, Laukkanen R. Assessing cardiorespiratory fitness without performing exercise testing. Am J Prev Med. 2005;29:185–93.CrossRef
15.
Zurück zum Zitat Yoon YS, Oh SW, Baik HW, Park HS, Kim WY. Alcohol consumption and the metabolic syndrome in Korean adults: the 1998 Korean National Health and nutrition examination survey. Am J Clin Nutr. 2004;80:217–24.CrossRef Yoon YS, Oh SW, Baik HW, Park HS, Kim WY. Alcohol consumption and the metabolic syndrome in Korean adults: the 1998 Korean National Health and nutrition examination survey. Am J Clin Nutr. 2004;80:217–24.CrossRef
16.
Zurück zum Zitat Kweon SH, Kim YN, Jang MJ, Kim YJ, Kim KR, Choi SH, Chun SM, Khang YH, Oh KW. Data resource profile: the Korea National Health and nutrition examination survey (KNHANES). Int J Epidemiol. 2014;43:69–77.CrossRef Kweon SH, Kim YN, Jang MJ, Kim YJ, Kim KR, Choi SH, Chun SM, Khang YH, Oh KW. Data resource profile: the Korea National Health and nutrition examination survey (KNHANES). Int J Epidemiol. 2014;43:69–77.CrossRef
17.
Zurück zum Zitat Xi B, Veeranki SP, Zhao M, Ma C, Yan Y, Mi J. Relationship of alcohol consumption to all-cause, cardiovascular, and cancer-related mortality in U.S. adults. J. Am. Coll. Cardiol. 2017;70:913–22.CrossRef Xi B, Veeranki SP, Zhao M, Ma C, Yan Y, Mi J. Relationship of alcohol consumption to all-cause, cardiovascular, and cancer-related mortality in U.S. adults. J. Am. Coll. Cardiol. 2017;70:913–22.CrossRef
18.
Zurück zum Zitat Oh JY, Yang YJ, Kim BS, Kang JH. Validity and reliability of Korean version of international physical activity questionnaire (IPAQ) short form. J Korean Acad Fam Med. 2007;28:532–41. Oh JY, Yang YJ, Kim BS, Kang JH. Validity and reliability of Korean version of international physical activity questionnaire (IPAQ) short form. J Korean Acad Fam Med. 2007;28:532–41.
19.
Zurück zum Zitat Kim J, Kim Y, Ahn YO, Paik HY, Ahn Y, Tokudome Y, Hamajima N, Inoue M, Tajima K. Development of a food frequency questionnaire in Koreans. Asia Pac J Clin Nutr. 2003;12:243–50.PubMed Kim J, Kim Y, Ahn YO, Paik HY, Ahn Y, Tokudome Y, Hamajima N, Inoue M, Tajima K. Development of a food frequency questionnaire in Koreans. Asia Pac J Clin Nutr. 2003;12:243–50.PubMed
20.
Zurück zum Zitat Janssen I, Heymsfield SB, Ross R. Low relative skeletal muscle mass (sarcopenia) in older persons is associated with functional impairment and physical disability. J Am Geriatr Soc. 2002;50:889–96.CrossRef Janssen I, Heymsfield SB, Ross R. Low relative skeletal muscle mass (sarcopenia) in older persons is associated with functional impairment and physical disability. J Am Geriatr Soc. 2002;50:889–96.CrossRef
21.
Zurück zum Zitat Lim S, Kim JH, Yoon JW, Kang SM, Choi SH, Park YJ, Kim KW, Lim JY, Park KS, Jang HC. Sarcopenic obesity: prevalence and association with metabolic syndrome in the Korean longitudinal study on health and aging (KLoSHA). Diabetes Care. 2010;33:1652–4.CrossRef Lim S, Kim JH, Yoon JW, Kang SM, Choi SH, Park YJ, Kim KW, Lim JY, Park KS, Jang HC. Sarcopenic obesity: prevalence and association with metabolic syndrome in the Korean longitudinal study on health and aging (KLoSHA). Diabetes Care. 2010;33:1652–4.CrossRef
22.
Zurück zum Zitat Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28:412–9.CrossRef Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28:412–9.CrossRef
23.
Zurück zum Zitat Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, Gordon DJ, Krauss RM, Savage PJ, Smith SC Jr, Spertus JA, Costa F, American Heart Association; National Heart, Lung, and Blood Institute. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 2005;112:2735–52.CrossRef Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, Gordon DJ, Krauss RM, Savage PJ, Smith SC Jr, Spertus JA, Costa F, American Heart Association; National Heart, Lung, and Blood Institute. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 2005;112:2735–52.CrossRef
24.
Zurück zum Zitat Lee SY, Park HS, Kim DJ, Han JH, Kim SM, Cho GJ, Kim DY, Kwon HS, Kim SR, Lee CB, Oh SJ, Park CY, Yoo HJ. Appropriate waist circumference cutoff points for central obesity in Korean adults. Diabetes Res. Clin. Pract. 2007;75:72–80.CrossRef Lee SY, Park HS, Kim DJ, Han JH, Kim SM, Cho GJ, Kim DY, Kwon HS, Kim SR, Lee CB, Oh SJ, Park CY, Yoo HJ. Appropriate waist circumference cutoff points for central obesity in Korean adults. Diabetes Res. Clin. Pract. 2007;75:72–80.CrossRef
25.
Zurück zum Zitat Adams-Campbell LL, Dash C, Kim BH, Hicks JC, Makambi K, Hagberg JM. Cardiorespiratory fitness and metabolic syndrome in postmenopausal African-American women. Int J Sports Med. 2016;37:261–6.CrossRef Adams-Campbell LL, Dash C, Kim BH, Hicks JC, Makambi K, Hagberg JM. Cardiorespiratory fitness and metabolic syndrome in postmenopausal African-American women. Int J Sports Med. 2016;37:261–6.CrossRef
26.
Zurück zum Zitat Kelley E, Imboden MT, Harber MP, Finch H, Kaminsky LA, Whaley MH. Cardiorespiratory fitness is inversely associated with clustering of metabolic syndrome risk factors: the Ball State adult fitness program longitudinal lifestyle study. Mayo Clin Proc Innov Qual Outcomes. 2018;2:155–64.CrossRef Kelley E, Imboden MT, Harber MP, Finch H, Kaminsky LA, Whaley MH. Cardiorespiratory fitness is inversely associated with clustering of metabolic syndrome risk factors: the Ball State adult fitness program longitudinal lifestyle study. Mayo Clin Proc Innov Qual Outcomes. 2018;2:155–64.CrossRef
27.
Zurück zum Zitat Ingle L, Mellis M, Brodie D, Sandercock GR. Associations between cardiorespiratory fitness and the metabolic syndrome in British men. Heart. 2017;103:524–8.CrossRef Ingle L, Mellis M, Brodie D, Sandercock GR. Associations between cardiorespiratory fitness and the metabolic syndrome in British men. Heart. 2017;103:524–8.CrossRef
30.
Zurück zum Zitat Liao W, Xiao DM, Huang Y, Yu HJ, Yuan S, Chen T, Phongsavan P, Mao ZF, He QQ. Combined association of diet and cardiorespiratory fitness with metabolic syndrome in Chinese schoolchildren. Matern. Child Health J. 2016;20:1904–10.CrossRef Liao W, Xiao DM, Huang Y, Yu HJ, Yuan S, Chen T, Phongsavan P, Mao ZF, He QQ. Combined association of diet and cardiorespiratory fitness with metabolic syndrome in Chinese schoolchildren. Matern. Child Health J. 2016;20:1904–10.CrossRef
32.
Zurück zum Zitat Oh SW, Yoon YS, Lee ES, Kim WK, Park C, Lee S, Jeong EK, Yoo T. Korea National Health and nutrition examination survey. Association between cigarette smoking and metabolic syndrome: the Korea National Health and nutrition examination survey. Diabetes Care. 2005;28:2064–6.CrossRef Oh SW, Yoon YS, Lee ES, Kim WK, Park C, Lee S, Jeong EK, Yoo T. Korea National Health and nutrition examination survey. Association between cigarette smoking and metabolic syndrome: the Korea National Health and nutrition examination survey. Diabetes Care. 2005;28:2064–6.CrossRef
33.
Zurück zum Zitat Haufe S, Engeli S, Budziarek P, Utz W, Schulz-Menger J, Hermsdorf M, Wiesner S, Otto C, Haas V, de Greiff A, Luft FC, Boschmann M, Jordan J. Cardiorespiratory fitness and insulin sensitivity in overweight or obese subjects may be linked through intrahepatic lipid content. Diabetes. 2010;59:1640–7.CrossRef Haufe S, Engeli S, Budziarek P, Utz W, Schulz-Menger J, Hermsdorf M, Wiesner S, Otto C, Haas V, de Greiff A, Luft FC, Boschmann M, Jordan J. Cardiorespiratory fitness and insulin sensitivity in overweight or obese subjects may be linked through intrahepatic lipid content. Diabetes. 2010;59:1640–7.CrossRef
34.
Zurück zum Zitat Vella CA, Van Guilder GP, Dalleck LC. Low cardiorespiratory fitness is associated with markers of insulin resistance in young, normal weight, Hispanic women. Metab Syndr Relat Disord. 2016;14:272–8.CrossRef Vella CA, Van Guilder GP, Dalleck LC. Low cardiorespiratory fitness is associated with markers of insulin resistance in young, normal weight, Hispanic women. Metab Syndr Relat Disord. 2016;14:272–8.CrossRef
36.
Zurück zum Zitat Barry VW, Baruth M, Beets MW, Durstine JL, Liu J, Blair SN. Fitness vs. fatness on all-cause mortality: a meta-analysis. Prog. Cardiovasc Dis. 2014;56:382–90.CrossRef Barry VW, Baruth M, Beets MW, Durstine JL, Liu J, Blair SN. Fitness vs. fatness on all-cause mortality: a meta-analysis. Prog. Cardiovasc Dis. 2014;56:382–90.CrossRef
37.
Zurück zum Zitat Cuthbertson DJ, Davies KB. Higher levels of cardiorespiratory fitness keep liver mitochondria happy! J Physiol. 2017;595:5719–20.CrossRef Cuthbertson DJ, Davies KB. Higher levels of cardiorespiratory fitness keep liver mitochondria happy! J Physiol. 2017;595:5719–20.CrossRef
Metadaten
Titel
Non-exercise based estimation of cardiorespiratory fitness is inversely associated with metabolic syndrome in a representative sample of Korean adults
verfasst von
Inhwan Lee
Shinuk Kim
Hyunsik Kang
Publikationsdatum
01.12.2020
Verlag
BioMed Central
Erschienen in
BMC Geriatrics / Ausgabe 1/2020
Elektronische ISSN: 1471-2318
DOI
https://doi.org/10.1186/s12877-020-01558-z

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