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Updated: Feb 3, 2026

Using Retinal Imaging to Study Dementia
Published on: November 6, 2017
Variability in metabolic parameters and risk of dementia: a nationwide population-based study
Seung-Hwan Lee1, Kyungdo Han2, Hanna Cho3
1Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, 06591, Korea.
Background:
Variability in biological parameters has been reported to be associated with adverse health outcomes. We aimed to investigate the composite effect of the visit-to-visit variability in blood pressure, glucose, cholesterol, and body mass index on the risk of dementia.
Methods:
A population-based cohort study including 2,930,816 subjects without a history of dementia, hypertension, diabetes mellitus, and dyslipidemia who underwent ≥ 3 health examinations was performed. The coefficient of variation (CV), standard deviation, and variability independent of the mean were calculated as variability indices. High variability was defined as having values in the highest quartile for each parameter.
Results:
A total of 32,901 (1.12%) participants developed dementia, of which 74.4% and 11.0% were attributable to Alzheimer's disease and vascular dementia, respectively, during the median follow-up of 5.5 years. Individuals with higher variability of each parameter were at higher risk of future dementia. In the multivariable adjusted model, the hazard ratios and 95% confidence intervals of all-cause dementia were 1.22 (1.19-1.26) for one parameter, 1.39 (1.35-1.43) for two parameters, 1.54 (1.48-1.60) for three parameters, and 1.73 (1.60-1.88) for four parameters compared with subjects having no parameters of high variability measured as the CV. Consistent results were noted for Alzheimer's disease and vascular dementia, using other indices of variability and in various sensitivity and subgroup analyses.
Conclusions:
There was a linear association between the number of high variability parameters and risk of dementia. Reducing variability of metabolic parameters would be a target to preserve cognitive reserve in the general population.
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