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Many biodemographic studies use biomarkers of inflammation to understand or predict chronic disease and aging. Inflamm-aging, i.e. chronic low-grade inflammation during aging, is commonly characterized by pro-inflammatory biomarkers. However, most studies use just one marker at a time, sometimes leading to conflicting results due to complex interactions(More)
BACKGROUND The concept of metabolic syndrome has been subject to etiological and clinical controversies in recent years. Associations among the five risk factors (obesity, hypertension, hyperglycemia, high triglyceride levels, and low high-density lipoprotein cholesterol) may help establish the validity of the concept, especially in a cohort representative(More)
Many studies of aging examine biomarkers one at a time, but complex systems theory and network theory suggest that interpretations of individual markers may be context-dependent. Here, we attempted to detect underlying processes governing the levels of many biomarkers simultaneously by applying principal components analysis to 43 common clinical biomarkers(More)
BACKGROUND Metabolic syndrome has been shown to predict type 2 diabetes mellitus and cardiovascular events in well-studied cohorts, but lack of appropriate measures in real-life populations has limited its use in clinical settings. We developed and tested an algorithm to identify patients at risk for future diabetes or coronary heart disease (CHD) events(More)
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