Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, 06591, Korea.
Department of Medical Statistics, College of Medicine, The Catholic University of Korea, Seoul, 06591, Korea.
Alzheimers Res Ther. 2018 Oct 27;10(1):110. doi: 10.1186/s13195-018-0442-3.
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.
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.
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.
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.
已有研究报道，生物学参数的变异性与不良健康结局相关。我们旨在研究血压、血糖、胆固醇和体重指数的随访间变异性对痴呆风险的综合影响。
进行了一项基于人群的队列研究，纳入了 2930816 名无痴呆、高血压、糖尿病和血脂异常病史且至少接受过 3 次健康检查的受试者。变异系数（CV）、标准差和均值独立变异被计算为变异指数。高变异被定义为每个参数的最高四分位数值。
共有 32901 名（1.12%）参与者发生痴呆，其中 74.4%和 11.0%归因于阿尔茨海默病和血管性痴呆，中位随访时间为 5.5 年。每个参数的变异程度较高的个体发生未来痴呆的风险更高。在多变量调整模型中，与无高变异参数的个体相比，各参数的全因痴呆风险比（HR）和 95%置信区间（CI）分别为 1.22（1.19-1.26）、1.39（1.35-1.43）、1.54（1.48-1.60）和 1.73（1.60-1.88）。对于阿尔茨海默病和血管性痴呆，使用其他变异指标和各种敏感性及亚组分析，也得到了一致的结果。
高变异参数的数量与痴呆风险之间存在线性关联。降低代谢参数的变异性可能是保护普通人群认知储备的目标。
