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dc.contributor.authorRietman, M Liset
dc.contributor.authorHulsegge, Gerben
dc.contributor.authorNooyens, Astrid C J
dc.contributor.authorDollé, Martijn E T
dc.contributor.authorPicavet, H Susan J
dc.contributor.authorBakker, Stephan J L
dc.contributor.authorGansevoort, Ron T
dc.contributor.authorSpijkerman, Annemieke M W
dc.contributor.authorVerschuren, W M Monique
dc.date.accessioned2019-10-11T12:10:36Z
dc.date.available2019-10-11T12:10:36Z
dc.date.issued2019-01-01
dc.identifier.issn1664-2295
dc.identifier.pmid31214102
dc.identifier.doi10.3389/fneur.2019.00497
dc.identifier.urihttp://hdl.handle.net/10029/623321
dc.description.abstractBackground: Long-term changes in (bio)markers for cognitive frailty are not well characterized. Therefore, our aim is to explore (bio)marker trajectories in adults who became cognitively frail compared to age- and sex-matched controls who did not become cognitively frail over a 15 year follow-up. We hypothesize that those who become cognitively frail have more unfavorable trajectories of (bio)markers compared to controls. Methods: The Doetinchem Cohort Study is a longitudinal population-based study that started in 1987-1991 in men and women aged 20-59 years, with follow-up examinations every 5 years. For the current analyses, we used data of 17 potentially relevant (bio)markers (e.g., body mass index (BMI), urea) from rounds 2 to 5 (1993-2012). A global cognitive functioning score (based on memory, speed, and flexibility) was calculated for each round and transformed into education and examination round-adjusted z-scores. The z-score that corresponded to the 10th percentile in round 5 (z-score = -0.77) was applied as cut-off point for incident cognitive frailty in rounds 2-5. In total, 455 incident cognitively frail cases were identified retrospectively and were compared with 910 age- and sex-matched controls. Trajectories up to 15 years before and 10 years after incident cognitive frailty were analyzed using generalized estimating equations with stratification for sex and adjustment for age and, if appropriate, medication use. Results were further adjusted for level of education, depressive symptoms, BMI, and lifestyle factors. Results: In men, (bio)marker trajectories did not differ as they ran parallel and the difference in levels was not statistically significant between those who became cognitively frail compared to controls. In women, total cholesterol trajectories first increased and thereafter decreased in cognitively frail women and steadily increased in controls, gamma-glutamyltransferase trajectories were more or less stable in cognitively frail women and increased in controls, and urea trajectories increased in cognitively frail women and remained more or less stable in controls. Results were similar after additional adjustment for potential confounders. Conclusions: Out of the 17 (bio)markers included in this explorative study, differential trajectories for three biomarkers were observed in women. We do not yet consider any of the studied (bio)markers as promising biomarkers for cognitive frailty.en_US
dc.language.isoenen_US
dc.subjectDoetinchem Cohort Studyen_US
dc.subjectbiomarkersen_US
dc.subjectcognitive frailtyen_US
dc.subjectmarkersen_US
dc.subjecttrajectoriesen_US
dc.titleTrajectories of (Bio)markers During the Development of Cognitive Frailty in the Doetinchem Cohort Study.en_US
dc.typeArticleen_US
dc.identifier.journalFront Neurol 2019; 10:497en_US
dc.source.journaltitleFrontiers in neurology


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