Journal of General Internal Medicine, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 11, 2024
Language: Английский
Journal of General Internal Medicine, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 11, 2024
Language: Английский
Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)
Published: Oct. 22, 2024
Classifying individuals based on metabotypes and lifestyle phenotypes using exploratory factor analyses, cluster definition, machine-learning algorithms is promising for precision chronic disease prevention management. This study analyzed data from the NUTRiMDEA online cohort (baseline: n = 17332 62 questions) to develop a clustering tool 32 accessible questions strategies. Participants ranged 18 over 70 years old, with 64.1% female 35.5% male. Five clusters were identified, combining metabolic, lifestyle, personal data: Cluster 1 ("Westernized Millennial", 967) included healthy young fair habits; 2 ("Healthy", 10616) consisted of adults; 3 ("Mediterranean Young Adult", 2013) represented adults showed highest adherence Mediterranean diet; 4 ("Pre-morbid", 600) was characterized by declined mood; 5 ("Pro-morbid", 312) comprised older (47% >55 years) poorer habits, worse health, lower health-related quality life. A computational algorithm elicited, which allowed quick assignment responses ("lifemetabotypes"). approach facilitates personalized interventions recommendations, supporting methods targeted health maintenance prevention.
Language: Английский
Citations
0Published: Jan. 1, 2024
Language: Английский
Citations
0Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 183 - 202
Published: Dec. 4, 2024
Language: Английский
Citations
0Journal of General Internal Medicine, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 11, 2024
Language: Английский
Citations
0