Do different definitions modify the gender-specific associations of metabolic syndrome with cardiovascular risk factors?

Abstract

Mikhailidis et al. have commented on our article ‘Metabolic syndrome: different definitions and gender-specific associations with cardiovascular risk factors’1 and provided evidence^2–5 to support the view that associations between the metabolic syndrome (MetS) and cardiovascular (CV) risk factors vary according to the MetS definition employed.

In our article¹, we have used the National Cholesterol Education Program/Adult Treatment Panel III (NCEP/ATP III) definition modified by the American Heart Association/National Heart, Lung and Blood Institute (AHA/NHLBI) criteria to define the MetS, which includes the waist circumference (Men ⩾ 90 cm; Women ⩾ 80 cm). As suggested by Mikhailidis et al., we reanalysed the data using the Joint Interim Societies MetS definition with Chinese waist circumference (Men ⩾ 85 cm; Women ⩾ 80 cm)⁶. The results showed that the prevalence of the MetS changed from 27.9% to 30.4% in men. However, although the associations between MetS and CV risk factors altered slightly, the direction of the associations was no different between these two MetS definitions (see Table 1).

Table 1.

Associations between CV risk factors and prevalence of MetS defined NCEP/ATP III modified by the AHA/NHLBI criteria and the Joint Interim Societies criteria, respectively, in men (N = 8156).

Variables	n	NCEP/ATP III criteria		Joint Interim Societies criteria
Variables	n	Prevalence (%)	OR (95% CI)	Prevalence (%)	OR (95% CI)
Age groups (years) (ref: 18–24)	816	9.1	1.00 (reference)	9.1	1.00 (reference)
25–34	1474	19.4	2.06 (1.56–2.73)	24.7	2.70 (2.05–3.57)
35–44	1882	32.6	4.72 (3.60–6.21)	38.8	6.07 (4.63–7.95)
45–54	2098	37.0	6.36 (4.82–8.40)	41.7	7.75 (5.88–10.21)
55–64	1108	32.3	5.65 (4.21–7.58)	40.6	8.50 (6.36–11.37)
65–74	778	21.3	3.75 (2.71–5.18)	31.6	6.64 (4.86–9.07)
Ethnic group
Han nationality	7670	28.0	1.00 (reference)	33.7	1.00 (reference)
Other	486	26.8	1.06 (0.85–1.33)	32.1	1.06 (0.87–1.31)
Education level (ref: no school)	116	17.2	1.00 (reference)	27.6	1.00 (reference)
Primary school	782	22.5	1.64 (0.95–2.81)	27.1	1.47 (0.92–2.34)
Junior high school	5008	29.1	1.54 (0.91–2.59)	34.5	1.27 (0.82–1.99)
⩾Senior high school	2250	27.6	1.40 (0.82–2.38)	34.1	1.04 (0.66–1.65)
Occupation (ref: Blue-collar worker)	3732	26.6	1.00 (reference)	31.2	1.00 (reference)
White-collar worker	1802	33.4	1.09 (0.93–1.27)	40.5	1.14 (0.99–1.33)
Organization cadre	426	27.2	0.95 (0.74–1.23)	38.0	1.24 (0.98–1.18)
Other	2196	25.6	0.97 (0.85–1.11)	30.1	1.04 (0.92–1.18)
Family income/year (ref: <10,000 RMB)	618	17.5	1.00 (reference)	23.6	1.00 (reference)
10,000–30,000 RMB	846	31.4	1.99 (1.54–2.59)	38.3	1.88 (1.48–2.40)
30,000–50,000 RMB	4198	26.4	1.71 (1.36–2.16)	31.4	1.56 (1.26–1.93)
>50,000 RMB	2494	31.7	2.55 (1.99–3.27)	38.0	2.39 (1.90–3.00)
Family history of hypertension
No	5434	22.3	1.00 (reference)	27.8	1.00 (reference)
Yes	2722	38.9	2.00 (1.80–2.22)	45.1	1.95 (1.76–2.16)
Cigarette smoking (ref: no)	4004	28.7	1.00 (reference)	34.0	1.00 (reference)
Yes	4152	27.1	0.80 (0.72–0.89)	33.2	0.86 (0.77–0.95)
Alcohol consumption (ref: no)	4562	25.5	1.00 (reference)	31.1	1.00 (reference)
Yes	3594	30.9	1.13 (1.02–1.26)	36.7	1.11 (1.01–1.23)
Physical activity (ref: low)	5432	27.9	1.00 (reference)	34.0	1.00 (reference)
High	2724	27.9	0.88 (0.79–0.99)	32.8	0.79 (0.71–0.89)
Control diet with low calorie and fat
Never	6328	28.2	1.00 (reference)	34.2	1.00 (reference)
Yes	1828	26.8	0.92 (0.81–1.04)	31.4	0.83 (0.73–0.94)
Like drinking sugary drinks
Never	6996	28.5	1.00 (reference)	34.5	1.00 (reference)
Yes	1160	24.3	1.19 (1.01–1.39)	28.1	1.12 (0.96–1.31)
Type of the staple food (ref: rice)	4560	26.5	1.00 (reference)	31.7	1.00 (reference)
Cooked wheaten food	478	26.8	0.72 (0.58–0.90)	38.5	1.00 (0.81–1.22)
Both	3118	30.0	0.92 (0.82–1.02)	35.5	0.90 (0.81–1.01)

NCEP/ATP III: National Cholesterol Education Program/Adult Treatment Panel III; AHA/NHLBI: American Heart Association/National Heart, Lung and Blood Institute; CI: confidence interval; OR: odds ratio; RMB: Chinese Yuan; MetS: metabolic syndrome.

OR (95% CI) from multivariable logistic regression model adjusted for all other variables in the table.

Unfortunately, we did not measure serum uric acid (SUA) in our study, but we are grateful for this suggestion which we will consider in future studies.

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