ArticleFrontiers in neurology2022
Potential modifiable factors associated with late-life cognitive trajectories.
Article in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 10 citations in OpenAlex.
- Prevalence of cancer-related cognitive impairment among patients with nasopharyngeal carcinoma: a cross-sectional study.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Article
- Sociodemographic features associated with the MoCA, SPPB, and GDS scores in a community-dwelling elderly population.BMC geriatrics · 2023Article
- Subjective Cognitive Decline and Frailty Trajectories and Influencing Factors in Japanese Community-Dwelling Older Adults: A Longitudinal Study.Journal of clinical medicine · 2023Article
- Health Conditions Associated with Alzheimer's Disease and Vascular Dementia.Annals of neurology · 2023Article
- Grip strength, gait speed, and trajectories of cognitive function in community-dwelling older adults: A prospective study.Alzheimer's & dementia (Amsterdam, Netherlands)Article
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Authors and funding
10 authors at 3 institutions in 2 countries.
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Abstract
Objective: There is variability across individuals in cognitive aging. To investigate the associations of several modifiable factors with high and low cognitive performance. Methods: Data came from 17,724 community-dwelling individuals aged 65-98 years. Global cognition, verbal fluency, episodic memory, and psychomotor speed were assessed over up to seven years. Group-based multi-trajectory modeling identified distinct cognitive trajectories. Structural equation modeling examined the direct/indirect associations of social/behavioral factors and several chronic conditions with cognitive trajectories. Results: Seven trajectory subgroups were identified. In the structural equation modeling we compared two subgroups-participants with the highest (14.2%) and lowest (4.1%) cognitive performance with the average subgroup. Lower education, never alcohol intake, and frailty directly predicted increased risk of low performance, and decreased likelihood of high performance. Hypertension (RR: 0.69, 95%CI: 0.60-0.80), obesity (RR: 0.84, 95%CI: 0.73-0.97), diabetes (RR: 0.69, 95%CI: 0.56-0.86) and depression (RR: 0.68, 95%CI: 0.54-0.85) only predicted lower likelihood of high cognitive performance, while dyslipidemia was only associated with low performance (RR: 1.30, 95%CI: 1.07-1.57). Living alone predicted increased risk of low cognitive performance and several comorbidities. Smoking did not predict cognitive trajectories but was associated with increased risk of diabetes, obesity and frailty. Findings were similar when examining the direct associations between modifiable risk factors and all seven cognitive subgroups. Conclusions: Although several modifiable factors were associated with high performance, and reversely with low performance, this was not observed for obesity, hypertension and dyslipidemia. Further, health behaviors may affect cognitive function indirectly,
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