Details

Autor(en) / Beteiligte

• Ittermann, Till
• Dörr, Marcus
• Markus, Marcello R.P.
• Nauck, Matthias
• Jürgens, Clemens
• Schipf, Sabine
• Schmidt, Carsten O.
• Völzke, Henry
• Richter, Adrian

Titel

Variability of biomarkers used for the classification of metabolic syndrome: A repeated measurements study

Ist Teil von

• Nutrition, metabolism, and cardiovascular diseases, 2022-07, Vol.32 (7), p.1693-1702

Ort / Verlag

Netherlands: Elsevier B.V

Erscheinungsjahr

2022

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• The definition of the metabolic syndrome consists of five components. The underlying measurements are subject to intra-individual variability. This repeated measurements study investigated the impact of intra-individual measurement variability on the stability of the diagnosis of metabolic syndrome over 12 months. Twenty-five employees of the University Medicine Greifswald aged 22–70 years were examined once a month over one year. Examinations included blood sampling and anthropometric and blood pressure measurements. Laboratory measurements included glucose, cholesterol (high-density lipoprotein [HDL], and low-density lipoprotein [LDL]), and triglycerides. The metabolic syndrome was defined according to the International Diabetes Federation modified for non-fasting blood samples. Variations in continuous metabolic markers were assessed using coefficients of variation (CV) and intra-class correlation coefficients (ICC). Overall eight participants (32%) were categorized at least once within 12 months as having a metabolic syndrome; in none of those metabolic syndrome was found consistently over the study follow-ups. The Cohen's Kappa for metabolic syndrome was 0.57. CV was highest for triglycerides (27.5%) followed by glucose (10.1%), LDL- (9.5%), and HDL-cholesterol (8.6%). ICC's were lowest for glucose (0.51), triglycerides (0.65), systolic (0.68), and diastolic blood pressure (0.69). We showed that the measurement of biomarkers defining the metabolic syndrome is a time-varying condition with implications for the concept of the metabolic syndrome. To account for this uncertainty in prevalence studies we propose to identify uncertain cases according to the current definition of the metabolic syndrome. For analysing associations we recommend to apply probabilistic sensitivity analyses. •Measurement of the biomarkers for defining the metabolic syndrome is a time-varying condition with implications for the concept of the metabolic syndrome.•Serum glucose and triglycerides are the most varying components of the metabolic syndrome.•To account for variations in components of the metabolic syndrome we propose to identify uncertain cases according to the current definition of the metabolic syndrome.