Table 1 shows the baseline characteristics of participants according to new-onset MetS at follow up. The subjects with MetS had higher baseline values of age, blood pressures, weight, BMI, WC, WHR, WHtR, and body fat percentage than those without MetS. No significant differences between the two groups were found in socioeconomic status (residence, marital status, education, occupation, and income level), sedentary time (watching TV and sitting), sleeping time, fasting plasma glucose, and lipid profile.
Table 1
Baseline characteristics of participates according to the development of metabolic symdrome at the end follow up
Variable
|
MetS (n = 280)
|
Non-MetS (n = 870)
|
P-value
|
Age (median, quartile) years
|
51.1 (46.0−56.0)
|
50. (45.6−55.3)
|
< 0.0001a
|
Gender (n, %)
|
0.015c
|
Male
|
84 (30.0)
|
331 (38.0)
|
|
Female
|
196 (70.0)
|
539 (62.0)
|
|
Body mass index (mean ± SD) kg/m2
|
22.1 ± 2.6
|
20.8 ± 2.2
|
< 0.0001b
|
Body fat (mean ± SD) %
|
29.2 ± 5.6
|
21.8 (22.5−30.2)
|
< 0.0001a
|
Wait circumference (mean ± SD) cm
|
76.9 ± 7.3
|
72.0 (67.5−77.0)
|
< 0.0001a
|
Systolic blood pressure (median, quartile) mmHg
|
110.0 (100.0−130.0)
|
110.0 (100.0−120.0)
|
< 0.0001a
|
Diastolic blood pressure (median, quartile) mmHg)
|
70.0 (70.0−80.0)
|
70.0 (60.0−80.0)
|
< 0.0001a
|
Triglycerides (median, quartile) mmol/L
|
1.29 (1.00−2.00)
|
1.29 (0.97−1.91)
|
0.555a
|
HDL-cholesterol (median, quartile) mmol/L
|
1.30 (1.05−1.66)
|
1.27 (1.00−1.66)
|
0.356a
|
Fasting glucose (median, quartile) mmol/L
|
4.60 (4.00−5.09)
|
4.50 (4.00−5.00)
|
0.185a
|
Region (n, %)
|
Rural
|
265 (94.6)
|
844 (97.0)
|
0.063c
|
Urban
|
15 (5.4)
|
26 (3.0)
|
|
Education level (n, %)
|
0.828c
|
Elementary
|
24 (8.6)
|
72 (8.3)
|
|
Intermediate
|
178 (63.6)
|
542 (62.3)
|
|
Secondary
|
31 (11.1)
|
115 (13.2)
|
|
Post–secondary
|
47 (16.8)
|
141 (16.2)
|
|
Income level (n, %)
|
0.506c
|
< 25 percentiles
|
68 (24.3)
|
227 (26.1)
|
|
< 25 percentiles
|
66 (23.6)
|
228 (26.2)
|
|
50– < 75 percentiles
|
67 (23.9)
|
206 (23.7)
|
|
≥ 75 percentiles
|
79 (28.2)
|
209 (24.0)
|
|
Smoking (n, %)
|
< 0.0001c
|
None
|
220 (78.6)
|
609 (70.0)
|
|
Ex-smokers
|
34 (12.1)
|
92 (10.6)
|
|
Current smokers
|
26 (9.3)
|
169 (19.4)
|
|
Leisure time (median, quartile) hour/day
|
5.0 (3.3−7.0)
|
4.8 (3.0−7.0)
|
0.489a
|
Sleeping time (median, quartile) hour/day
|
7.0 (6.0−7.0)
|
7.0 (6.0−7.0)
|
0.260a
|
Family history of diabetes (n, %)
|
|
|
|
Yes
|
17 (6.1)
|
51 (5.9)
|
0.897c
|
No
|
263 (93.9)
|
819 (94.1)
|
|
MetS metabolic syndrome |
a Mann-Whitney U test |
b T-test |
c Chi-Square test |
The comparison of baseline characteristics between participants and non-participants in the follow-up survey is shown in Additional Table. There were no significant differences between two groups in terms of anthropometrics, socioeconomic status, and lifestyles.
During a median follow-up of 5.14 years (quartile: 5.05−5.19 years), 280 (23.4%) subjects developed MetS. As shown in Table 2, the estimated incidences of MetS increased with age in general population. After 55 years of age, about a quarter of men and one third of women suffered from MetS during 5-year period. The MetS incidence was higher in groups: urban, non-heavy occupation, and overweight.
Table 2
Estimated 5-year incidence of metabolic syndrome in a Vietnamese middle-aged population according to baseline characteristics
Baseline characteristics
|
No at risk
|
No new-onset
MetS
|
Person-
year
|
5 years cumulative incidence rate
|
|
Incidence density/1000 person-years
|
|
Total
|
Men
|
Women
|
Total
|
Men
|
Women
|
Total
|
1150
|
280
|
5224.2
|
23.4 (22.2−24.7)
|
20.1 (18.0−22.3)
|
25.3 (23.7−27.0)
|
|
52.9 (46.7−60.1)
|
46.5 (36.9−59.3)
|
56.6 (48.7−65.9)
|
Age group (years)
|
|
|
|
|
|
|
|
|
|
|
40 − 44
|
220
|
42
|
1030.4
|
17.7 (15.3−20.4)
|
18.8 (13.9−24.9)
|
17.4 (14.7−20.4)
|
|
38.2 (28.0−53.1)
|
41.4 (21.9−85.6)
|
37.2 (26.1−54.6)
|
45 − 49
|
294
|
59
|
1368.1
|
18.7 (16.5−21.2)
|
15.4 (12.0−19.5)
|
20.5 (17.6−23.6)
|
|
42.7 (32.7 −56.5)
|
36.0 (21.8−63.2)
|
46.0 (33.6−64.0)
|
50 − 54
|
282
|
63
|
1295.6
|
21.5 (19.1−24.2)
|
16.9 (13.8−20.6)
|
24.6 (21.2−28.3)
|
|
48.4 (37.2−64.0)
|
37.8 (24.5−60.7)
|
55.5 (39.9−79.0)
|
55 − 59
|
214
|
71
|
922.0
|
33.3 (29.8−36.9)
|
26.5 (21.3−32.4)
|
38.6 (34.0−43.4)
|
|
74.1 (57.5−96.4)
|
56.5 (35.4−95.1)
|
89.5 (66.3−122.0)
|
60 − 64
|
140
|
45
|
608.1
|
30.1 (26.3−34.3)
|
24.5 (19.1−30.9)
|
34.2 (29.1−39.7)
|
|
75.2 (55.1−104.5)
|
68.8 (39.4−128.8)
|
80.0 (55.4−118.2)
|
Region
|
|
|
|
|
|
|
|
|
|
|
Rural
|
1109
|
265
|
5051.4
|
22.6 (21.4−23.9)
|
19.1 (17.1−21.3)
|
24.6 (23.0−26.2)
|
|
51.8 (45.6−58.9)
|
43.8 (34.9−55.8)
|
56.3 (48.5−65.7)
|
Urban
|
41
|
15
|
172.8
|
37.2 (29.9−45.0)
|
38.7 (25.9−53.3)
|
36.4 (27.9−46.0)
|
|
68.8 (37.6−133.7)
|
84.9 (30.2−292.0)
|
60.1 (28.2−139.5)
|
Occupation
|
|
|
|
|
|
|
|
|
|
|
Heavy
|
915
|
214
|
4179.5
|
22.7 (21.3−24.2)
|
17.5 (15.1−20.2)
|
25.3 (23.5−27.1)
|
|
50.3 (43.6−58.2)
|
38.6 (28.6−53.2)
|
56.2 (47.9−66.2)
|
None heavy
|
235
|
66
|
1044.7
|
26.2 (23.5−29.2)
|
26.8 (23.0−31.1)
|
25.6 (21.8−29.9)
|
|
63.0 (48.3−83.1)
|
68.0 (47.5−99.9)
|
58.5 (39.7−88.5)
|
Nutrition status
|
|
|
|
|
|
|
|
|
|
|
Underweight
|
160
|
23
|
768.1
|
12.9 (10.5−15.8)
|
9.6 (6.56−13.72)
|
15.3 (11.9−19.5)
|
|
28.9 (18.9−46.1)
|
22.6 (10.4 −57.8)
|
33.3 (19.9−59.0)
|
Normal
|
749
|
154
|
3475.7
|
20.1 (18.7−21.7)
|
14.9 (12.7−17.4)
|
22.7 (20.8−24.7)
|
|
43.2 (36.6−51.4)
|
32.2 (22.8−47.0)
|
48.9 (40.4−59.5)
|
Overweight
|
162
|
64
|
672.7
|
38.7 (34.8−42.6)
|
37.1 (31.0−43.6)
|
39.6 (34.7−44.7)
|
|
97.3 (75.0−128)
|
107 (70.2−169)
|
92.4 (66.5−131)
|
Obesity
|
77
|
37
|
302.6
|
47.6 (41.3−53.8)
|
45.0 (36.1−54.3)
|
50.8 (42.4−59.2)
|
|
123 (88.9−172)
|
109 (67.6−183)
|
140 (90.7−222)
|
Severe obesity
|
2
|
2
|
5.2
|
N/A
|
N/A
|
N/A
|
|
N/A
|
N/A
|
N/A
|
MetS metabolic syndrome |
Data are weighted by the study design, the probability of sampling, finite population correction, and none-response rate. Data are shown as % (95% CI) for cumulative incidence rate and cases (95% CI) for incident density/1000 person-years. N/A, not applicable due to 2 participats with BMI ≥ 30 kg/m2. Nutrition status was classified as underweight (BMI < 18.5 kg/m2), normal (18.5 ≤ BMI < 23 kg/m2), overweight (23 ≤ BMI < 25 kg/m2), obesity (25 ≤ BMI < 30 kg/m2), and severe obesity (BMI ≥ 30 kg/m2). Occupation was categorized as heavy occupation (farmer and manual worker) or none heavy occupation (office clerks, teacher, retired worker, and houseworker). |
The sex- and age- standardized MetS incidences were 24.5% (95% CI: 24.3−24.7) in general population and significantly higher in women [27.3 (95% CI: 27.1−27.5)] than in men [20.4 (95% CI: 20.1−20.6)]. The corresponding new-onset MetS cases per 1000 person-years were 55.6 (95% CI: 54.7−56.5) in general population and much higher in women [62.2 (95% CI: 60.9−63.5)] compared to men [47.5 (95% CI: 46.4−48.7)].
Table 3 presents the development of MetS in participants with single component and pairwise combination of MetS components at the baseline. The more number of MetS component they had at baseline, the more MetS incidence rate they suffered at follow-up. In addition, among participants with one component at baseline, subjects with central obesity had the highest MetS incidence, while people with elevated blood glucose had the lowest incidence. Moreover, among 349 people with 2 MetS components, the highest incidence was seen in those with central obesity and raised blood pressure combination, while the lowest incidence was found in those with low HDL-C and elevated blood glucose combination.
Table 3
Incidence of metabolic syndrome according to the single and combination of baseline metabolic syndrome components
|
At risk
(n)
|
Person- years
|
Case
(n)
|
5 years cumulative incidence rate
(95% CI) (%)
|
Incidence/
1000 person-years
(95% CI)
|
The number of components
|
0
|
243
|
1160.3
|
37
|
15.23 (11.25−20.28)
|
31.89 (23.22−43.64)
|
1
|
558
|
2605.1
|
109
|
19.53 (16.46−23.03)
|
41.84 (34.80−50.23)
|
2
|
349
|
1458.8
|
134
|
38.4 (33.45−43.60)
|
91.86 (78.09−107.8)
|
One of component
|
CO
|
16
|
61.9
|
8
|
50.00 (28.00−72.00)
|
129.24 (66.79−234.8)
|
RBP
|
74
|
311.8
|
27
|
36.49 (26.44−47.87)
|
86.59 (60.19−123.1)
|
HTG
|
183
|
860.7
|
34
|
18.58 (13.61−24.84)
|
39.50 (28.40−54.69)
|
LHC
|
258
|
1237.9
|
37
|
14.34 (10.59−19.14)
|
29.89 (21.76−40.93)
|
EBG
|
27
|
132.7
|
3
|
11.11 (3.58−28.06)
|
22.61 (7.72−64.63)
|
Pairwise combination of components
|
CO-RBP
|
18
|
59.3
|
13
|
72.22 (49.1−87.5)
|
219.2 (132.8−339.8)
|
LHC-CO
|
24
|
85.1
|
15
|
62.50 (42.71−78.84)
|
176.3 (109.8−270.7)
|
LHC-RBP
|
76
|
289.3
|
40
|
52.63 (41.55−63.46)
|
138.3 (103.2−182.8)
|
HTG-RBP
|
60
|
242.7
|
26
|
43.33 (31.57−55.90)
|
107.1 (74.16−152.3)
|
HTG-CO
|
35
|
142.7
|
15
|
42.86 (27.98−59.14)
|
105.1 (64.74−166.2)
|
RBP-EBG
|
11
|
49.3
|
3
|
27.27 (9.75−56.56)
|
60.85 (20.91−164.3)
|
HTG-EBG
|
19
|
85.8
|
5
|
26.32 (11.81−48.79)
|
58.28 (25.15−129.3)
|
LHC-HTG
|
91
|
434.4
|
14
|
15.38 (9.39−24.18)
|
32.23 (19.29−53.63)
|
LHC-EBG
|
14
|
67.6
|
2
|
14.29 (4.01−39.94)
|
29.59 (8.15−101.6)
|
CO-EBG
|
1
|
2.5
|
1
|
100.0 (20.65−100.0)
|
400.0 (74.5−846.6)
|
HR hazard ratio, CI confidence interval, CO central obesity, RBP raised blood pressure, |
HTG high triglycerides, LHC low HDL-Cholesterol, EBG elevated blood glucose |
Table 4 shows HR values of MetS according to candidate risk factors in multivariable analysis. Gender, age, blood pressures, fasting plasma glucose, and obesity-related measurements (WC, HC, WHtR, WHR, BMI, and body fat percentage) were significant risk factors for MetS. The HRs (95% CI) of MetS for gender (females vs males), advanced age, systolic blood pressure, fasting plasma glucose, and WC were 2.04 (1.26−3.29), 1.02 (1.01−1.04), 1.02 (1.01–1.03), 1.12 (1.02–1.40), and 1.08 (1.06−1.10), respectively. There was no significant association between incident MetS with levels of some lifestyle factors, socioeconomic conditions and family history of diabetes.
Table 4
Hazard ratio of metabolic syndrome according to candidate risk factors in multivariate analysis
Risk factors
|
Hazard ratio (95% CI)
|
P-value
|
Gender (female vs male)
|
2.04 (1.26−3.29)
|
0.004
|
Age (years)
|
1.02 (1.01−1.04)
|
0.021
|
Fasting plasma glucose (mmol/L)
|
1.12 (1.02−1.40)
|
0.025
|
Systolic blood pressure (mmol/L)a
|
1.02 (1.01−1.03)
|
< 0.0001
|
Diastolic blood pressure (mmol/L)b
|
1.03 (1.02−1.04)
|
< 0.0001
|
Triglycerides (mmol/L)
|
0.96 (0.85−1.07)
|
0.429
|
High density lipoprotein-cholesterol (mmol/L)
|
0.92 (0.73−1.16)
|
0.481
|
Each of the following obesity-related traits:
|
|
|
Waist circumference (cm)c
|
1.08 (1.06−1.10)
|
< 0.0001
|
Waist height ratio (per 0.03)d
|
1.46 (1.31−1.64)
|
< 0.0001
|
Waist hip ratio (per 0.07)e
|
1.32 (1.19−1.46)
|
< 0.0001
|
Body mass index (kg/m2)f
|
1.22 (1.15−1.27)
|
< 0.0001
|
Body fat (%)g
|
1.11 (1.08−1.15)
|
< 0.0001
|
Hip circumference (cm)h
|
1.10 (1.07−1.13)
|
< 0.0001
|
Family history of diabetes
|
No
|
1.0
|
|
Yes
|
0.88 (0.53−1.44)
|
0.605
|
Residence
|
|
|
Rural
|
1.0
|
|
Urban
|
1.26 (0.73−2.18)
|
0.413
|
Education level
|
|
|
Elementary
|
1.0
|
|
Intermediate
|
1.10 (0.70−1.71)
|
0.687
|
Secondary
|
0.99 (0.55−1.76)
|
0.964
|
Post–secondary
|
0.77 (0.43−1.39)
|
0.385
|
Marital status
|
|
|
Married
|
1.0
|
|
Never
|
0.84 (0.30−2.36)
|
0.739
|
Widowed
|
1.15 (0.72−1.85)
|
0.553
|
Others
|
1.16 (0.47−2.84)
|
0.746
|
Occupation
|
|
|
Heavy
|
1.0
|
|
None heavy
|
1.25 (0.88−1.78)
|
0.210
|
Income level
|
|
|
< 25 percentiles
|
1.0
|
|
25– < 50 percentiles
|
1.06 (0.75−1.51)
|
0.727
|
50– < 75 percentiles
|
1.17 (0.82−1.67)
|
0.374
|
≥ 75 percentiles
|
1.09 (0.76−1.56)
|
0.644
|
Alcohol consumption
|
|
|
None
|
1.0
|
|
< 1 drink/mo
|
0.76 (0.44−1.29)
|
0.308
|
≥ 1 drink/mo to < 1 drink/wk
|
0.94 (0.55−1.60)
|
0.819
|
1 drink/wk to ≤ 1 drink/d
|
0.75 (0.43−1.30)
|
0.303
|
≥ 2 drink/d
|
1.01 (0.57−1.77)
|
0.987
|
Smoking status
|
|
|
None
|
1.0
|
|
Ex-smoker
|
0.72 (0.41−1.27)
|
0.259
|
Current smoker
|
1.12(0.66−1.93)
|
0.672
|
Leisure time/day (hour)
|
0.99 (0.94−1.03)
|
0.549
|
Sleeping time/day (hour)
|
0.96 (0.88−1.05)
|
0.419
|
CI confidence interval |
b replace a in multivariable analysis |
d, e, f, g, h step by step replace c in multivariable analysis |
A multivariable logistic regression analysis with backward stepwise and Bayesian Model Average approach were used to search for the most predictive MetS model with the highest AUC value and parsimonious variables. As a result, gender, age, WC, and SBP were considered in the final model (Table 5). The prediction nomogram for estimating the individual risk of MetS was constructed with above factors in the final model.
Table 5
The final model for prediction of 5-year incident metabolic syndrome in a middle-aged Vietnamese population
Predictor
|
Unit
|
β-coefficient (se)
|
P-value a
|
Gender
|
(female = 1, male = 0)
|
1.132 (0.178)
|
< 0.0001
|
Age
|
year
|
0.060 (0.019)
|
0.002
|
Waist circumference
|
cm
|
0.022 (0.005)
|
< 0.001
|
Systolic blood pressure
|
mmHg
|
|
|
Intercept
|
|
-14.099 (1.191)
|
< 0.0001
|
a Using multivariable logistic regression analysis |
CI Confidence Interval. |
Figure 1 shows the nomogram for predicting new-onset MetS. The C-index before and after bootstrap was 0.742 and 0.7367 respectively, indicating a good discrimination of the nomogram. The calibration curve presented possibility of the nomogram-predicted probabilities versus the actual observation. As shown in Fig. 2a, both these lines were very close with the ideal line and the mean absolute error was 0.009. Thus, the prediction nomogram performed a good calibration. Figure 2b demonstrated that for the predicted probability thresholds between 0.13 and 0.70, the prediction nomogram showed a positive net benefit than strategies for all and none participant to treat.