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晚年体重指数的动态特征预测认知轨迹和阿尔茨海默病:一项纵向研究。

Dynamic Features of Body Mass Index in Late Life Predict Cognitive Trajectories and Alzheimer's Disease: A Longitudinal Study.

机构信息

Department of Neurology, Qingdao Municipal Hospital, Dalian Medical University, Dalian, China.

Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China.

出版信息

J Alzheimers Dis. 2024;100(4):1365-1378. doi: 10.3233/JAD-240292.

Abstract

BACKGROUND

The causal relationships of late-life body mass index (BMI) with Alzheimer's disease (AD) remains debated.

OBJECTIVE

We aimed to assess the associations of dynamic BMI features (ΔBMIs) with cognitive trajectories, AD biomarkers, and incident AD risk.

METHODS

We analyzed an 8-year cohort of 542 non-demented individuals who were aged ≥65 years at baseline and had BMI measurements over the first 4 years. ΔBMIs were defined as changing extent (change ≤ or >5%), variability (standard deviation), and trajectories over the first 4 years measured using latent class trajectory modeling. Linear mixed-effect models were utilized to examine the influence of ΔBMIs on changing rates of AD pathology biomarkers, hippocampus volume, and cognitive functions. Cox proportional hazards models were used to test the associations with AD risk. Stratified analyzes were conducted by the baseline BMI group and age.

RESULTS

Over the 4-year period, compared to those with stable BMI, individuals who experienced BMI decreases demonstrated accelerated declined memory function (p = 0.006) and amyloid-β deposition (p = 0.034) while BMI increases were associated with accelerated hippocampal atrophy (p = 0.036). Three BMI dynamic features, including stable BMI, low BMI variability, and persistently high BMI, were associated with lower risk of incident AD (p < 0.005). The associations were validated over the 8-year period after excluding incident AD over the first 4 years. No stratified effects were revealed by the BMI group and age.

CONCLUSIONS

High and stable BMI in late life could predict better cognitive trajectory and lower risk of AD.

摘要

背景

老年人的体重指数(BMI)与阿尔茨海默病(AD)之间的因果关系仍存在争议。

目的

本研究旨在评估动态 BMI 特征(ΔBMI)与认知轨迹、AD 生物标志物和 AD 发病风险之间的关系。

方法

我们分析了一个 8 年的队列,包括 542 名年龄≥65 岁的非痴呆个体,他们在基线时有 BMI 测量值,并在最初的 4 年内进行了 BMI 测量。ΔBMI 定义为变化幅度(变化≤或>5%)、变异性(标准差)以及使用潜在类别轨迹建模在最初 4 年内的轨迹。线性混合效应模型用于研究 ΔBMI 对 AD 病理生物标志物、海马体积和认知功能变化率的影响。Cox 比例风险模型用于测试与 AD 风险的相关性。分层分析按基线 BMI 组和年龄进行。

结果

在 4 年期间,与稳定 BMI 的个体相比,BMI 下降的个体表现出记忆功能(p=0.006)和淀粉样蛋白-β沉积(p=0.034)的加速下降,而 BMI 增加与海马萎缩(p=0.036)的加速有关。三种 BMI 动态特征,包括稳定的 BMI、低 BMI 变异性和持续高 BMI,与较低的 AD 发病风险相关(p<0.005)。在排除前 4 年内的新发 AD 后,这些关联在 8 年期间得到了验证。BMI 组和年龄没有显示分层效应。

结论

晚年高且稳定的 BMI 可以预测更好的认知轨迹和 AD 风险较低。

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