Background
Metabolic syndrome (MS), a clustering of three or more obesity-related risk factors namely high waist circumference, high triglycerides, high blood pressure, high blood glucose and low high-density lipoprotein (HDL) cholesterol [
1], has emerged as an important risk factor for cardiovascular disease [
2] and is associated with morbidity and all-cause mortality [
3,
4]. The prevalence of MS increases with age [
5], and is highly prevalent among midlife women, with the rates varying from 23.2 to 35.1% [
6‐
9]. The exact origin of this condition is less certain, but hormonal changes have been implicated as a causal factor for the increasing risk of MS at the menopausal transition [
10,
11]. Besides menopausal hormonal changes, interactions of genetic and behavioral factors also contribute to clustering of metabolic risk factors [
12]. Therefore, clinical guidelines and strategies indicate that healthy eating and active lifestyle are the frontline approaches to preventing MS [
1].
Substantial evidence demonstrates an inverse association of physical activity (PA) and cardiorespiratory fitness (CRF) with risk of MS in middle-aged and older populations [
13‐
27]. The protective effects of higher levels of PA or CRF on MS are evident regardless of age, sex, body composition, smoking, alcohol intake and other clinical factors. PA is a behavior, defined as any bodily movement that increases energy expenditure, including both leisure time and non-leisure time activities, whereas CRF is a physiologic attribute, usually measured by a maximal or submaximal exercise test, and expressed as maximal oxygen uptake (VO
2max). Compared with self-reported PA, CRF is a more accurate [
28] and is thought to be stronger as a predictor of health outcomes because it is less prone to misclassification. Although CRF is partly determined by levels of PA, PA and CRF may be differentially influenced by body composition, environmental factors as well as genetic components [
29]. Therefore the influence of PA and CRF on MS may occur through separate pathways.
Although several studies have simultaneously examined PA and CRF with MS [
14,
15,
17,
18,
23,
25], the independent roles of both PA and CRF with MS are less firmly established. The combined contributions of PA and CRF with MS are less studied. Although in a previous population-based study, middle-aged men with both sedentary lifestyle and poor CRF were associated with increased risk of MS [
15], this study has been carried out among Caucasians, who may differ significantly from Chinese in terms of lifestyle, diet, and body physiology. For example, the age-defined VO
2max was noted to differ between Chinese adult men and women and their age-matched Caucasians adults [
30]. Previously we have examined the normative values of CRF in Chinese midlife and elderly women. Although similar VO
2max values were observed as those of same sex and comparable age in Western populations, the VO
2max values being in the 5-15
th percentile values from the norms of the Cooper Institute [
31,
32].
There is evidence suggesting that higher CRF levels are associated with fewer metabolic complications and lower risk of heart disease or cancer across different weight status groups. Ortega et al. [
33] have recently reported that metabolically healthy but obese middle-age individuals had better fitness than their metabolically abnormal obese peers, and for a given fitness level, the metabolically healthy but obese phenotype had a lower risk of all-cause mortality, non-fatal and fatal cardiovascular disease, and cancer mortality. The authors suggested that fitness assessment can contribute to properly define a subset of obese individuals who do not have an elevated risk of cardiovascular disease or cancer. However, the authors used the cut-off point of a BMI ≥ 30 kg/m
2 for obesity which may not be suitable for Asian adults, who have different body build and body composition [
34]. Moreover, the prevalence of MS in Chinese women is high [
35]. Further research is needed to examine the relative and combined associations of PA and CRF with the risk of MS, and to understand whether higher CRF is a common feature in metabolically healthy but obese individuals, particularly among Chinese population.
The aim of the present study was to examine the cross-sectional relative and combined associations of PA and CRF with the risk of MS in a population-based sample of Hong Kong Chinese midlife women, taking into account for the potential confounding factors including age, BMI, and dietary total calories intake. We also aimed to test whether CRF is more highly associated with MS than PA, whether the associations between PA/CRF and MS are different across BMI categories, and whether metabolically healthy but obese individuals have higher CRF level.
Results
A total of 184 Chinese midlife women were examined (mean age, 61.1 ± 3.1 years; range, 54.9–69.4 years) The majority of the subjects were married (75.7%), worked as a housewife (71.7%), and had primary level of education (97.8%). The prevalence of MS was 21.7%. The mean PA score was 9.1 ± 1.4 (range 5.9 to 13.1) and the mean VO
2max was 22.8 ± 3.8 ml/kg/min (range 13.8 to 35.7 ml/kg/min). Subjects with MS had a significantly lower VO
2max that those without it (P < 0.0001) (Table
1).
Table 1
Characteristics of the study population according to the presence of metabolic syndrome
Age, year | 61.1 ± 3.1 | 61.2 ± 3.1 | 60.9 ± 3.1 | 0.680 | — |
Marital status, now married | 139 (75.5) | 108 (75.0) | 31 (77.5) | 0.745 | — |
Education attainment, primary or above | 180 (97.8) | 141 (97.9) | 39 (97.5) | 0.873 | — |
Occupation, housewife | 132 (71.7) | 102 (70.8) | 30 (75.0) | 0.605 | — |
Medical history | | | | | |
Hypertension | 37 (20.1) | 18 (12.5) | 19 (47.5) | 0.000 | — |
Hypercholesterolemia | 54 (30.5) | 42 (30.2) | 12 (31.6) | 0.872 | — |
Diabetes | 14 (7.7) | 4 (2.8) | 10 (25.0) | 0.000 | — |
Use of medication | | | | | |
Anti-hypertensive | 34 (18.5) | 16 (11.1) | 18 (45.0) | 0.000 | — |
Lipid-lowering | 17 (9.2) | 12 (8.3) | 5 (12.5) | 0.421 | — |
Anti-diabetic | 13 (7.1) | 3 (2.1) | 10 (25.0) | 0.000 | — |
Anthropometric and metabolic factor | | | | |
Systolic blood pressure, mmHg | 120.6 ± 17.5 | 118.2 ± 15.7 | 128.3 ± 20.5 | 0.001 | 0.001 |
Diastolic blood pressure, mmHg | 71.9 ± 8.1 | 71.5 ± 7.9 | 73.0 ± 8.1 | 0.296 | 0.316 |
BMI, kg/m2
| 23.4 ± 3.0 | 22.7 ± 2.6 | 26.1 ± 2.9 | 0.000 | 0.000 |
Waist circumference, cm | 78.5 ± 7.9 | 76.4 ± 7.0 | 86.0 ± 6.7 | 0.000 | 0.000 |
Waist-hip-ratio | 0.85 ± 0.05 | 0.84 ± 0.05 | 0.88 ± 0.04 | 0.000 | 0.000 |
Total cholesterol, mmol/L | 5.3 ± 0.9 | 5.4 ± 0.9 | 5.0 ± 0.7 | 0.018 | 0.020 |
HDL cholesterol, mmol/L | 1.6 ± 0.5 | 1.8 ± 0.4 | 1.2 ± 0.2 | 0.000 | 0.000 |
LDL cholesterol, mmol/L | 3.1 ± 0.8 | 3.2 ± 0.9 | 2.9 ± 0.6 | 0.034 | 0.098 |
Triglycerides, mmol/L | 1.3 ± 0.8 | 1.1 ± 0.4 | 2.2 ± 1.3 | 0.000 | 0.000 |
Fasting blood glucose, mmol/L | 5.2 ± 0.9 | 5.0 ± 0.7 | 5.8 ± 1.1 | 0.000 | 0.000 |
Lifestyle factor | | | | | |
Current smoker | 2 (1.1) | 1 (0.7) | 1 (2.5) | 0.330 | — |
Regular drinking* | 9 (4.9) | 6 (4.2) | 3 (7.5) | 0.387 | — |
Dietary total calories intake, kcal/day | 1341.7 ± 400.9 | 1354.8 ± 380.8 | 1294.6 ± 468.7 | 0.403 | 0.377 |
PA, total index | 9.1 ± 1.5 | 9.2 ± 1.5 | 8.9 ± 1.2 | 0.394 | 0.364 |
CRF, VO2max, ml/kg/min | 22.8 ± 3.8 | 23.5 ± 3.4 | 20.1 ± 3.9 | 0.000 | 0.000 |
After adjustment for age, BMI, and dietary total calories intake, PA was inversely associated with the prevalence of MS (P = 0.04); however, the association was eliminated after further adjustment for CRF (P = 0.09). CRF was inversely associated with the prevalence of MS independent of age, BMI, and dietary total calories intake, and the association remained significant after further adjustment for PA (P = 0.01). The percentage contribution (R
2) of PA with MS ranged from 0.043 to 0.403 while that of CRF ranged from 0.192 to 0.367 (Table
2).
Table 2
Prevalence and odds ratio within 95% confidence interval for metabolic syndrome across physical activity and cardiorespiratory fitness categories
PA | | | | | | | | | | |
Inactive | 19 (31.7) | 0.023 | 1.0 (reference) | | 1.0 (reference) | | 1.0 (reference) | | 1.0 (reference) | |
Active | 21 (16.9) | | 0.44 (0.21–0.90) | 0.024 | 0.42 (0.18–0.97) | 0.041 | 0.42 (0.18–0.98) | 0.044 | 0.47 (0.20–1.13) | 0.090 |
Nagelkerke R2
| | | 0.043 | | 0.348 | | 0.348 | | 0.403 | |
CRF | | | | | | | | | | |
Unfit | 26 (43.3) | 0.000 | 1.0 (reference) | | 1.0 (reference) | | 1.0 (reference) | | 1.0 (reference) | |
Fit | 14 (11.3) | | 0.16 (0.07–0.34) | 0.000 | 0.31 (0.13–0.73) | 0.008 | 0.31 (0.13–0.74) | 0.008 | 0.31 (0.13–0.76) | 0.010 |
Nagelkerke R2
| | | 0.192 | | 0.367 | | 0.367 | | 0.367 | |
In the CRF stratified analyses, PA was not associated with the prevalence of MS within both unfit and fit categories. On the other hand, in the PA stratified analyses, CRF was associated inversely with the prevalence of MS within subjects who were inactive (OR 0.18, 95%CI 1.05 to 0.66, P = 0.01). However, OR of having MS was not significant within subjects who were active (P = 0.38) (Table
3).
Table 3
Relative risk of having metabolic syndrome by physical activity in cardiorespiratory fitness stratified analysis and by cardiorespiratory fitness in physical activity stratified analysis
PA | | | | | | |
Inactive | 14 (56.0) | 1 (reference) | | 5 (14.3) | 1 (reference) | |
Active | 12 (34.3) | 0.68 (0.20–2.32) | 0.543 | 9 (10.1) | 0.28 (0.07–1.07) | 0.062 |
| Inactive | | | Active | | |
| No. (%) of MS | OR (95% CI) | P | No. (%) of MS | OR (95% CI) | P |
CRF | | | | | | |
Unfit | 14 (56.0) | 1 (reference) | | 12 (34.3) | 1 (reference) | |
Fit | 5 (14.3) | 0.18 (0.05–0.66) | 0.010 | 9 (10.1) | 0.55 (0.15–2.09) | 0.381 |
To further examine whether adiposity confounds the associations of PA and CRF with MS, subsequent analyses were performed stratified by BMI whereas PA was associated inversely with the prevalence of MS within subjects who were normal weight (OR 0.12, 95%CI 0.04 to 0.39, P < 0.0001). However, OR of having MS was not significant within subjects who were obese (P = 0.17). High CRF had a beneficial effect on MS for those in the normal weight category (OR 0.26, 95%CI 0.09 to 0.77, P = 0.02). The corresponding OR was 0.16 (95%CI 0.04 to 0.59, P = 0.01) within those who were obese (Table
4).
Table 4
Relative risk of having metabolic syndrome by physical activity and cardiorespiratory fitness in BMI stratified analysis
PA | | | | | | |
Inactive | 12 (29.3) | 1 (reference) | | 7 (36.8) | 1 (reference) | |
Active | 5 (5.5) | 0.12 (0.04–0.39) | <0.0001 | 16 (48.5) | 2.5 (0.67–9.64) | 0.173 |
CRF | | | | | | |
Unfit | 8 (25.0) | 1 (reference) | | 18 (64.3) | 1 (reference) | |
Fit | 9 (9.0) | 0.26 (0.09–0.77) | 0.015 | 5 (20.8) | 0.16 (0.04–0.59) | 0.006 |
In the combined associations of PA and CRF with MS, subjects who were fit had significantly lower risk of having MS whether or not they were active (OR 0.14, 95%CI 0.04 to 0.45, P = 0.001) or inactive (OR 0.23, 95%CI 0.06 to 0.88, P = 0.03); however, if subjects were active but unfit, risk of having MS was not lower compared with the referent group that were classified as inactive and unfit (Table
5).
Table 5
Combined associations of physical activity and cardiorespiratory fitness with metabolic syndrome
PA | | | | | | |
Inactive | 14 (56.0) | 1 (reference) | | 5 (14.3) | 0.23 (0.06–0.88) | 0.031 |
Active | 12 (34.3) | 0.31 (0.09–1.06) | 0.061 | 9 (10.1) | 0.14 (0.04–0.45) | 0.001 |
Table
6 shows BMI and CRF levels across the four MS/BMI categories. After adjustment for age, dietary total calories intake, and PA, metabolically healthy but overweight/obese subjects had higher CRF than their metabolically abnormal and overweight/obese peers, but the difference did not reach statistically significance. A decreasing trend in the level of CRF was observed across the categories (P for trend <0.0001).
Table 6
Body mass index and cardiorespiratory fitness levels in metabolically healthy but overweight/obese subjects compared with metabolically healthy and normal weight, metabolically abnormal but normal weight, and metabolically abnormal and overweight/obese subjects
Metabolically healthy and normal weight | 83 | 20.8 ± 1.4 | 24.0 ± 3.6 | 0.000 | 0.000 |
Metabolically healthy but overweight/obese | 84 | 25.4 ± 1.8 | 22.2 ± 3.4*
| | |
Metabolically abnormal and normal weight | 3 | 21.4 ± 1.1 | 20.1 ± 5.6 | | |
Metabolically abnormal and overweight/obese | 14 | 27.4 ± 2.4 | 19.6 ± 4.0*
| | |
Discussion
Results of the present study showed that PA was not associated as strongly as CRF with the prevalence of MS and the risk reduction was larger in subjects who were fit than those who were active after adjusting for age, BMI, and dietary total calories intake. Subjects who were active had 58% lower risk of having MS, but the association was no longer significant after adjustment for CRF. Subjects who were fit had 69% lower risk, and the association remained significant after further adjustment for PA. In stratified analyses, CRF was significantly associated with the risk of MS within inactive subjects. In combined analysis, subjects who were inactive but fit had lower risks of having MS. However, if subjects were active and unfit, the OR of having MS was not significantly lower than the referent group that was inactive and unfit.
Our findings are generally consistent with extensive research that has documented the inverse associations between PA and MS [
14,
15,
17,
18,
23,
25]. However, after adjustment for CRF, the association between PA and MS observed in our study became attenuated. In stratified analyses, no significant association between PA and the prevalence of MS was observed within unfit or fit categories. These findings must be interpreted with caution given the imprecise measurement associated with self-reported PA since self-reported data are more prone to recall bias and misclassification. Furthermore, the lack of statistical significance is likely explained by the small number of MS in fit subjects (n = 5). However, Laaksonen et al. [
14] reported that middle-aged men without MS who complied with the PA recommendations had reduced risk of developing MS by about one-half compared with those engaging in no more than 60 minutes of moderate exercise per week, independent of CRF. The Medical Research Council (MRC) Ely Study showed that PA remained associated with MS and its progression after adjustment for CRF [
17,
18]. It has also been shown that increasing levels of PA may protect against MS even in the absence of improved CRF [
23]. The disparate findings may be due to the use of different PA measurements, in that PA was measured objectively with individually calibrated heart rate against energy expenditure in the MRC Ely Study, which is more precise compared with self-report data; and this may partially explain the relatively stronger associations found between PA and MS than with CRF. However, in contrast to this notion, several studies have stated that leisure-time PA not resulting in an increase in CRF may not provide any protective effect on cardiovascular disease or its risk factors [
45,
46]. Results from the Aerobics center longitudinal study also demonstrated that the association of PA with all-cause mortality was eliminated after controlling for CRF [
47]. Therefore, the independent role of PA on risk of MS is not confirmed. It is reasonable to suggest that the lower levels of CRF that are normally associated with PA are at least partially responsible for our findings.
Our results also agree with previous cross-sectional [
24] and longitudinal studies [
26] suggesting that low CRF is an independent risk factor of MS. Based on the baseline data of the Dose-Responses to Exercise Training Study (DR’s EXTRA), older men and women aged 57-79 years who were in the lowest tertile of VO
2max had a 10-fold higher risk of MS compared with those in the highest tertile [
24]. Based on the baseline and 2-year follow-up data of the same study, those who were in the highest tertile of baseline VO
2max were 68% less likely to develop MS than those in the lowest tertile [
26]. To check whether CRF contributes to the risk of MS independently of PA, PA was further adjusted and the association between CRF and MS remained significant, with subjects who were fit had 69% lower risk of MS. However, the MRC Ely Study showed contradictory results, with the association between CRF and MS attenuated after adjustment for objectively measured PA [
17]. Therefore, whether the CRF effects on risk reduction for MS risk differ between PA levels is not firmly established.
The mechanisms by which moderate-to-high CRF provides a beneficial effect on the metabolic risk still needs to be determined but it is reasonable to believe that the benefit may be largely mediated by components of MS. A previous study in 297 apparently healthy men showed that the high CRF group had lower triglyceride levels and higher HDL cholesterol levels than the low-or moderate-CRF groups, independent of abdominal subcutaneous and visceral fat [
20]. The finding of this study showing the independent association between CRF and MS for a given level of BMI lends further support to this observation.
Few studies have simultaneously examined PA and CRF on the risk of MS using combined stratification analysis, although one previous study in middle-aged men found that low levels of PA and CRF were associated with MS [
15]. Since CRF is a strong correlate of PA, and the influence of PA and CRF on MS may occur through separate pathways, we examined the combined association of PA and CRF with the prevalence of MS, and similar associations were observed. Our results also showed that the combined effects of PA and CRF with MS were stronger than the single relative risks of having MS in fit subjects. However, although PA is an important determinant of CRF, genetic variation has a significant effect on response to exercise and thus CRF [
29,
48]. Recently, Timmons et al. [
49] pointed out different individuals may respond differently to exercise and some individuals respond well to aerobic exercise with increased CRF while others did not. Therefore, incorporation of CRF into individual risk assessment may provide an efficient method for identifying individuals who would benefit from interventions to preventing MS.
In contrast with previous studies showing a higher CRF level among metabolically healthy but obese subjects than their metabolically abnormal and obese peers [
33,
50], we did not observe significant differences in level of CRF between the two groups in this study. Perhaps the small sample size of metabolically abnormal and overweight/obese subjects (n = 14) attenuated the statistical power. Differences in characteristics and the methods to identify obesity are also likely to contribute in part to the discrepancies between the studies. In the study of Ortega et al. [
33] a mean BMI of 25.8 ± 4.0 kg/m
2 was reported and the author defined obese as a BMI of ≥ 30 kg/m
2 and compared the metabolically healthy and normal weight phenotype with the metabolically healthy but obese / metabolically abnormal and obese groups, leaving out those with overweight in the analyses. In a second study, Messier et al. [
50] used dual-energy X-ray absorptiometry and computed tomography scan as methods to identify metabolically healthy but obese subjects. In contrast with these studies, the mean BMI was lower in our study (23.4 ± 3.0 kg/m
2). Moreover, we defined overweight as a BMI of ≥ 23 kg/m
2 and obese as a BMI of ≥ 25 kg/m
2 and divided subjects into two groups, one group representing normal weight, and the other representing overweight/obese. Previous evidence suggested that findings from studies of Caucasians should not be extrapolated to other ethnic groups such as Asians from whom other cut-off points have been defined for obesity [
51]. The Cooperative Meta-analysis group of the working group in obesity in China who suggest defining overweight as BMI ≥ 24 to 27.9 kg/m
2 and obesity as BMI ≥ 28 kg/m
2[
52]. Nevertheless, there appears to be trend of a decreasing CRF levels across the MS/BMI categories, regardless of age, dietary total calories intake, and PA. Therefore, the findings of this study lend some support to the previous literature on the role of CRF on the risk of MS, and suggest that public health guidelines may need to be modified by placing more emphasis on the CRF level, especially for the midlife women.
Several studies have reported the prevalence of MS among midlife women, from 23.2 to 35.1% across different populations [
6‐
9]. The prevalence in Chinese women is also high [
35], in that people of Asian origin tend to accumulate more body fat and develop cardiovascular risk factors at lower BMI levels or smaller waist circumference than Caucasians [
34]. However, the prevalence of MS in our study (21.7%) was lower than that reported from an earlier study in China. In the study of 181 postmenopausal women conducted in 2006-2008, the prevalence of MS was 33.7% [
9]. Variation in the prevalence of MS could be due to heterogeneity of population characteristics such as age distribution, socioeconomic status or nutritional status, or due to different genetic background.
This study has several strengths, in that we were able to assess VO
2max directly by respiratory gas analysis during a maximum exercise test, and such analyses have been less studied in Chinese, particularly among midlife women. It is recognized that VO
2max is an accurate measure of CRF and an objective measure of recent patterns of PA, which is less prone to misclassification than self-reported PA, and this may partially explain the relatively weaker associations found between MS and PA than with CRF in this study. Other strengths of this study include the adjustment for multiple potential confounders, including dietary intake, which is known to influence the components of MS [
27]. In a public health perspective, our findings have important implications, in highlighting that moderate-to-high CRF may reduce metabolic risk in midlife women, who represent a group of individuals at higher risk of future cardiovascular disease. Although PA may be less predictive of health outcomes compared with CRF, it is a primary modifiable factor to improve CRF despite some individuals may not respond well to aerobic exercise [
48,
49]. Therefore, health care providers should encourage their patients to become more fit by participating in regular PA to reduce MS risk.
There are some limitations in this study. The subjects were not representative of the Hong Kong population, in that their education level was higher. PA was self-reported such that the measurement accuracy is inferior to that of physical fitness in quality; therefore the difference in result between PA and CRF may be partly a reflection of this measurement accuracy. The sample size was small and the cross-sectional design also does not allow us to infer a causal relationship of PA and CRF with MS.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
RY contributed to the writing of manuscript, data collection and analysis. FY contributed to data collection and analyses. SCH developed the concept, planned data analyses and designed the study. JW developed the concept, planned data analyses, designed the study and writing of manuscript. We express our gratitude to our study subjects for their excellent collaboration. All authors read and approved the final manuscript.