o:26632 Laboratory data clustering in defining population cohorts: case study on metabolic indicators Klaster analiza laboratorijskih podataka u cilju definisanja populacionih grupa: Test model sa metaboličkim indikatorima en ABSTRACT The knowledge on the general population health is important for creating public policies and organization of medical services. However, per­sonal data are often limited, and mathematical models are employed to achieve a general overview. Cluster analysis was used in this study to assess general trends in po­pulation health based on laboratory data. Metabolic indicators were chosen to test the model and define population cohorts. Data on blood analysis of 33,049 persons, namely the concentrations of glucose, total cholesterol and triglycerides, were col­lected in a public health laboratory and used to define metabolic cohorts employing computational data clustering (CLARA method). The population was shown to be distributed in 3 clusters: persons with hyper­cholesterolemia with or without changes in the concentration of triglycerides or glucose, persons with reference or close to reference concentrations of all three analytes and persons with predo­mi­nantly elevated all three parameters. Clus­tering of biochemical data, thus, is a use­ful statistical tool in defining popul­ation groups in respect to certain health aspect. computational model, blood analytes, dependent variables, community health groups 1552099 10.2298/JSC220106037P 2022-10-12T06:11:31.411Z 44 yes 46 Ivan Pavićević Institute of Public Health of Belgrade, Serbia 0000-0001-8743-7368 Goran Miljuš University of Belgrade, Institute for the Application of Nuclear Energy INEP, Serbia doktor biohemijskih nauka person 0000-0001-6417-8711 Olgica Nedić University of Belgrade, Institute for the Application of Nuclear Energy INEP, Serbia doktor biohemijskih nauka person 0000-0003-2042-0056 application/pdf 2391853 https://phaidrabg.bg.ac.rs/o:26632 no yes 18 70 92000001 11A29 11A2905 Journal of the Serbian Chemical Society 87 9 1025 1033 Serbian Chemical Society 2022-07-22