001     304430
005     20250906114839.0
024 7 _ |a 10.1016/j.inpsyc.2025.100141
|2 doi
024 7 _ |a pmid:40908200
|2 pmid
024 7 _ |a 1041-6102
|2 ISSN
024 7 _ |a 1741-203X
|2 ISSN
037 _ _ |a DKFZ-2025-01843
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Paul, Cinara
|b 0
245 _ _ |a Predictors of health-related quality of life in older adults over a course of twelve years - Results from a large population-based study using a machine learning approach.
260 _ _ |a Cambridge
|c 2025
|b Cambridge Univ. Press
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1757078237_963
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
500 _ _ |a epub
520 _ _ |a The proportion of older people is growing dramatically, implying that predictors of health-related quality of life (HRQoL) in older adults are of major interest within public health research.Analyses were based on the ESTHER study, a German population-based cohort study conducted in the federal state of Saarland, Germany. The study was initiated in 2000-2002 and included 9940 community-dwelling older adults recruited via general practioners. At the 8-year follow-up (2008-2010), 6071 active participants were offered additional home visits, of whom 3124 agreed to participate. These 3124 participants (mean age (SD) 69.6 (6.3) years; 52.6 % female) served as baseline sample for our analysis. Predictions were made at 3-year intervals up to 12 years (20-year follow-up; 2020-2021, n = 1438). Physical and mental HRQoL was assessed using the Short Form Health Survey (SF-12). 47 features were investigated. Random forest regression was used to identify the most important predictors.Physical HRQoL was predictable up to 6 years, with top 5 predictors being: somatic symptom burden, bio-psycho-social (BPS) health care needs, frailty, age, and BMI class. For mental HRQoL, predictors consistently ranging among the top 5 across all time intervals were: somatic symptom burden, BPS health care needs, symptoms of depression, and symptoms of anxiety. There appeared to be a time-dependent shift in key predictors of mental HRQoL, with symptoms of depression and anxiety being most important in short-term, while somatic symtom burden and BPS health care needs were most important in long-term.Somatic symptom burden and bio-psycho-social health care needs emerged as key predictors of both, physical and mental HRQoL in older adults. These variables may be important to consider when developing future interventions aimed to improve HRQoL in older adults, and could also be relevant for policies concerned with successful aging.
536 _ _ |a 313 - Krebsrisikofaktoren und Prävention (POF4-313)
|0 G:(DE-HGF)POF4-313
|c POF4-313
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
650 _ 7 |a Bio-psycho-social health care needs
|2 Other
650 _ 7 |a Health-related quality of life
|2 Other
650 _ 7 |a Longitudinal study
|2 Other
650 _ 7 |a Machine learning
|2 Other
650 _ 7 |a Older Adults
|2 Other
650 _ 7 |a Random forest
|2 Other
700 1 _ |a Schöttker, Ben
|0 P:(DE-He78)c67a12496b8aac150c0eef888d808d46
|b 1
|u dkfz
700 1 _ |a Brenner, Herrmann
|0 P:(DE-HGF)0
|b 2
700 1 _ |a Holleczek, Bernd
|b 3
700 1 _ |a Friederich, Hans-Christoph
|b 4
700 1 _ |a Wild, Beate
|b 5
773 _ _ |a 10.1016/j.inpsyc.2025.100141
|g p. 100141 -
|0 PERI:(DE-600)2147136-8
|p nn
|t International psychogeriatrics
|v nn
|y 2025
|x 1041-6102
909 C O |o oai:inrepo02.dkfz.de:304430
|p VDB
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 1
|6 P:(DE-He78)c67a12496b8aac150c0eef888d808d46
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 2
|6 P:(DE-HGF)0
913 1 _ |a DE-HGF
|b Gesundheit
|l Krebsforschung
|1 G:(DE-HGF)POF4-310
|0 G:(DE-HGF)POF4-313
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-300
|4 G:(DE-HGF)POF
|v Krebsrisikofaktoren und Prävention
|x 0
914 1 _ |y 2025
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
|d 2024-12-17
|w ger
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2024-12-17
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2024-12-17
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2024-12-17
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2024-12-17
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1180
|2 StatID
|b Current Contents - Social and Behavioral Sciences
|d 2024-12-17
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0130
|2 StatID
|b Social Sciences Citation Index
|d 2024-12-17
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1110
|2 StatID
|b Current Contents - Clinical Medicine
|d 2024-12-17
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2024-12-17
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2024-12-17
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b INT PSYCHOGERIATR : 2022
|d 2024-12-17
915 _ _ |a IF >= 5
|0 StatID:(DE-HGF)9905
|2 StatID
|b INT PSYCHOGERIATR : 2022
|d 2024-12-17
920 1 _ |0 I:(DE-He78)C070-20160331
|k C070
|l C070 Klinische Epidemiologie der Krebsfrüherkennung
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-He78)C070-20160331
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21