实用老年医学 ›› 2023, Vol. 37 ›› Issue (2): 178-182.doi: 10.3969/j.issn.1003-9198.2023.02.017

• 临床研究 • 上一篇    下一篇

肥胖与老年人脑体积及认知功能的关系

岑颜, 窦苗苗, 隗倩, 陆小伟   

  1. 210029 江苏省南京市,南京医科大学第一附属医院老年神经内科
  • 收稿日期:2022-03-13 出版日期:2023-02-20 发布日期:2023-02-27
  • 通讯作者: 陆小伟,Email:njluxiaowei@163.com
  • 基金资助:
    国家自然科学基金资助项目(81771286)

Associations of obesity with brain volume and cognition in elderly

CEN Yan, DOU Miao-miao, WEI Qian, LU Xiao-wei   

  1. Department of Gerontology and Neurology, the First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
  • Received:2022-03-13 Online:2023-02-20 Published:2023-02-27
  • Contact: LU Xiao-wei, Email: njluxiaowei@163.com

摘要: 目的 观察老年人群肥胖与大脑体积、认知功能之间的关系。方法 回顾性分析2015~2018年就诊于南京医科大学第一附属医院老年科且行三维磁共振结构成像的病人177例,根据BMI及腰臀比(WHR)来评估病人的肥胖情况。采用MMSE评估病人的认知功能,并将病人分为认知障碍组(76例)和无认知障碍组(101例)。使用基于体素的CAT12软件自动分割大脑总体积、脑白质体积、脑灰质体积、脑白质病变体积。比较2组临床特征资料及脑体积相关指标。采用Pearson相关系数描述BMI、WHR与脑体积的相关性。采用Logistic回归模型分析BMI、腹型肥胖与认知障碍的关系。利用广义线性回归模型分析BMI与MMSE之间的关系。结果 2组在性别、文化程度、MMSE评分、BMI、WHR、腹型肥胖、大脑总体积、脑灰质体积、脑白质体积方面差异均有统计学意义(P<0.05)。Pearson相关分析提示,BMI及WHR均与脑白质体积呈正相关(r=0.152、0.235,均P<0.05)。Logistic回归分析显示,超重(OR=0.384,95%CI:0.189~0.778,P =0.008)和肥胖(OR=0.316,95%CI:0.134~0.747,P =0.009)的病人认知障碍风险降低。广义线性模型分析提示,BMI独立于年龄、文化、吸烟史、脑体积变化,与MMSE评分相关(B=0.044,95%CI:0.007~0.080,P=0.019)。结论 BMI独立于脑体积变化改善认知,对老年人认知功能可能具有保护作用。

关键词: 肥胖, 体质量指数, 脑白质, 认知障碍

Abstract: Objective To observe the relationship of obesity with brain volume and cognition in the elderly population. Methods A total of 177 patients performed with complete 3-dimensional magnetic resonance imaging in the Department of Geriatrics, the First Affiliated Hospital of Nanjing Medical University from January 2015 to December 2018 were retrospectively analyzed. Body mass index (BMI) and waist-to-hip ratio (WHR) were used to evaluate obesity. All patients were evaluated by Mini-Mental State Scale (MMSE) and divided into two groups, cognitively impaired group (n=76) and non-cognitive impaired group (n=101). Brain volume was automatically segmented into total volume, white matter volume, grey matter volume, and white matter hyperintensities (WMH )volume with CAT12 software. Clinical feature data and brain volume were compared between the two groups. The correlations of BMI and WHR with brain volume were assessed by the Pearson correlation coefficients. Logistic regression was applied to analyze the relationship of BMI and abdominal obesity with cognitive impairment. Moreover, univariate and multivariate generalized linear models were used to analyze the correlation between BMI and MMSE. Results There were significant differences in gender, education, MMSE, BMI, WHR, total brain volume, grey matter volume, and white matter volume between the two groups (P<0.05). Pearson correlation analysis showed that BMI and WHR were positively correlated with white matter volume(r=0.152, 0.235, P<0.05). Logistic regression analysis showed that overweight patients(OR=0.384,95%CI:0.189-0.778, P=0.008)and obese patients (OR=0.316,95%CI:0.134-0.747, P=0.009)had a reduced risk of cognitive impairment. The generalized linear model showed that the MMSE score of patients was significantly positively related to BMI (B=0.044, 95%CI: 0.007-0.080, P=0.019) independent of age, education, smoking and brain volume. Conclusions BMI, independent of brain volume, may have a protective effect on cognitive function in the elderly.

Key words: obesity, body mass idex, brain volume, cognitive impairment

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