Background: Based on the AHA/NHLBI-definition three out of five cardiometabolic traits must be present for the diagnosis of the metabolic syndrome (MetS), resulting in 16 different combination types. The associated cardiovascular risk may however be different and specific combination may be indicative of an increased risk, furthermore little is known to which extent these 16 combinations contribute to the overall prevalence of MetS. Here we assessed the prevalence of all 16 combination types of MetS, analyzed the impact of age and gender on prevalence rates, and estimated the 10-year risk of fatal and non-fatal myocardial infarction (MI) of each MetS combination type.
Methods: We used data of the German Metabolic and Cardiovascular Risk Project (GEMCAS), a cross-sectional study, performed during October 2005, including 35,869 participants (aged 18-99 years, 61% women). Age-standardized prevalence and 10-year PROCAM and ESC risk scores for MI were calculated.
Results: In both men and women the combination with elevated waist-circumference, blood pressure and glucose (WC-BP-GL) was the most frequent combination (28%), however a distinct unequal distribution was observed regarding age and sex. Any combination with GL was common in the elderly, whereas any combination with dyslipidemia and without GL was frequent in the younger. Men without MetS had an estimated mean 10-year risk of 4.7% (95%-CI: 4.5%-4.8%) for MI (PROCAM), whereas the mean 10-year risk of men with MetS was clearly higher (age-standardized 7.9%; 7.8-8.0%). In women without MetS the mean 10-year risk for MI was 1.1%, in those with MetS 2.3%. The highest impact on an estimated 10-year risk for MI (PROCAM) was observed with TG-HDL-GL-BP in both sexes (men 14.7%, women 3.9%). However, we could identify combinations with equal risks of non-fatal and fatal MI compared to participants without MetS.
Conclusions: We observed large variations in the prevalence of all 16 combination types and their association to cardiovascular risk. The importance of different combinations of MetS changes with age and between genders putting emphasis on a tailored approach towards very young or very old subjects. This knowledge may guide clinicians to effectively screen individuals and prioritize diagnostic procedures depending on age and gender.