Lina Bergman, Ulrica Nilsson, Karuna Dahlberg, Maria Jaensson, Josefin Wångdahl
Validity and reliability of the arabic version of the HLS-EU-Q16 and HLS-EU-Q6 questionnaires
BMC public health
number biomarkers denoting various pathophysiological pathways implicated aetiology risk agerelated diseases hence combined impact multiple biomarkers relation ageing free major chronic diseases cancer cardiovascular disease type 2 diabetes sufficiently explored measured concentrations 13 biomarkers random subcohort 2500 participants european prospective investigation cancer nutrition potsdam study chronic diseasefree ageing defined reaching age 70 years within study followup without major chronic diseases including cardiovascular disease type 2 diabetes cancer using novel machinelearning technique aimed identify biomarker clusters explore association chronic diseasefree ageing multivariableadjusted logistic regression analysis taking sociodemographic lifestyle anthropometric factors account participants reached age 70 years 321 met criteria chronicdisease free ageing machine learning analysis identified three distinct biomarker clusters among signature characterised high concentrations highdensity lipoprotein cholesterol adiponectin insulinlike growth factorbinding protein 2 low concentrations triglycerides associated highest odds ageing free major chronic diseases multivariable adjustment association attenuated sociodemographic lifestyle adiposity indicators pointing relative importance factors determinants healthy ageing data underline importance exploring combinations biomarkers rather single molecules understanding complex biological pathways underpinning healthy ageing