gms | German Medical Science

53. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

15. bis 18.09.2008, Stuttgart

Sixteen possibilities to diagnose the metabolic syndrome – Patterns of distribution of respective combinations by age, gender and comorbidity in a large primary care sample

Meeting Abstract

  • Chakrapani Balijepalli - Institut für Medizinische Informatik, Biometrie und Epidemiologie, Essen, Deutschland
  • Christian Lösch - Institut für Medizinische Informatik, Biometrie und Epidemiologie, Essen, Deutschland
  • Peter Bramlage - Institut für Klinische Pharmakologie, Technische Universität Dresden, Dresden, Deutschland
  • Jürgen Wasem - Lehrstuhl für Medizinmanagement, Universität Duisburg-Essen, Essen, Deutschland
  • Karl-Heinz Jöckel - Institut für Medizinische Informatik, Biometrie und EpidemiologieInstitut für Medizinische Informatik, Biometrie und Epidemiologie, Essen, Deutschland
  • Susanne Moebus - Institut für Medizinische Informatik, Biometrie und Epidemiologie, Essen, Deutschland

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 53. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (gmds). Stuttgart, 15.-19.09.2008. Düsseldorf: German Medical Science GMS Publishing House; 2008. DocEPI5-5

The electronic version of this article is the complete one and can be found online at:

Published: September 10, 2008

© 2008 Balijepalli et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.




The metabolic syndrome (MetS) is defined as a cluster of risk factors for diabetes mellitus type 2 and cardiovascular disease consisting of the presence of three or more of the following criteria: elevated blood glucose (BG), increased waist circumference (WC), increased triglycerides (TG), low high density lipoprotein cholesterol (HDL) and elevated blood pressure (BP). This definition allows 16 possible risk factor combinations that lead to a diagnosis of MetS. Not much is known about the prevalence of each combination, especially with regard to sex, age and comorbidity. Using the dataset of the nation-wide German Metabolic and Cardiovascular Risk Project (GEMCAS) the prevalence of MetS and the 16 different risk factor combinations of MetS in different age and gender subgroups were assessed.

Materials & Methods

GEMCAS included 35,869 subjects (13,942 men and 21,927 women) aged 18-99 years, visiting 1,511 randomly selected general practitioners (GPs) during two weeks in October 2005. A modified definition of the AHA/NHLBI (2004) was used for the diagnosis of MetS: WC >102 cm in men and >88 cm in women, BP ≥130 systolic and/or ≥85 mm Hg diastolic, fasting BG ≥5.6 mmol/L (100 mg/dL) and/or a random BG ≥11.1 mmol/L (200 mg/dL) and/or diabetes mellitus, TG ≥1.7 mmol/L (150 mg/dL), HDL <1.03 mmol/L (40 mg/dL) in men and <1.29 mmol/L (50 mg/dL) in women. Prevalence estimates and their 95%-confidence intervals (95%-CI) were calculated for all combinations. The effects of intake of antihypertensive, antidiabetic, lipid lowering medications and comorbid conditions like cardiovascular disease (CVD), diabetes and cancer were studied, all in relation to age and sex.


The prevalence of MetS was 25% in men (n=3168, mean age 58.8 years, SD ±12.8), 19% in women (n=3954, 61.0 ±13.9 years). In subjects with MetS most men and women (69%, 66% resp.) presented with three criteria of MetS, four criteria were found in about 27% both men and women, whereas 5% of men and 7% of women exhibited five criteria.

Elevated blood pressure, waist circumference and an elevated blood glucose were the single most prevalent criteria among patients with MetS in both men (92%, 84%, 76%, respectively) and women (92%, 93%, 68% resp.). Regarding all triple combination WC-BP-BG was most frequent in both sexes (56%), followed by WC-TG-BG (40%), whereas the combination TG-HDL-BG was the least prevalent combination (men 11.4%, women 12.3%). The triple combination TG-BP-BG was noticeably higher in men than women (36% resp. 25%), whereas all combination including HDL women showed higher prevalences than men (i.e. WC-HDL-BP women 36%, men 21%).

The combinations differed markedly with respect to age (Figure 1 [Fig. 1]). Those combinations including dyslipidemia (HDL, TG), elevated waist circumference and blood pressure are highest in the youngest age-groups attenuating with increasing age (i.e. WC-BP-BG men aged 18-30 years: 57%, 79-99: 33%). Whereas those combinations including elevated blood glucose steeply increased with age (i.e. WC-TG-BP men aged 18-30 years 18-30 year old men: 12%, 79-99 years: 62%).

Intake of medication or a history of CVD gave rise to a higher prevalence for all combinations in both sexes. Prevalences did not differ with regard to a history of cancer.


The results of this nationwide prevalence study show a high prevalence of the metabolic syndrome in the German population attending primary health care. Our analysis revealed differences concerning the possible combinations of a diagnosis of the MetS with respect to age, gender and comorbidity.

Although elevated WC and BP in all age-groups and in both sexes were the main risk factors contributing to the MetS, the third risk factor that is needed to diagnose MetS differed according age and sex, with a higher proportion of those with lipid disorders in the younger age-groups changing to higher blood glucose disorders in the older age-groups. Furthermore about 10% of the patients without abdominal obesity and normal BP had MetS.

Our data contribute to the discussion of the heterogeneity of MetS and the clinical implications of a diagnosis of MetS. When screening for MetS in primary care attendees measurement of waist circumference and blood pressure seem to be a valuable tool to identify subjects at risk in which further laboratory tests are useful, but what is gained by this, is still a matter of debate. Our data show that a unique therapeutic action beyond lifestyle modification is not possible and medical treatment obviously will differ in patients with MetS.


In conclusion the relative importance of different risk factors of the metabolic syndrome may well change with age and between genders putting emphasis on a tailored approach towards very young or very old patients. Further research is needed to answer the question whether MetS is a risk unity in itself or a conglomerate of more or less independent cardiovascular risk factors.