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International Diabetes Federation
国际糖尿病联合会

Cognitive function among older adults with diabetes and prediabetes, NHANES 2011-2014
患有糖尿病和糖尿病前期的老年人的认知功能，NHANES，2011-2014 年

Sarah S. Casagrande , Christine Lee , Luke E. Stoeckel , Andy Menke ,
Sarah S. Casagrande , Christine Lee , Luke E. Stoeckel , Andy Menke 、Catherine C. Cowie
凯瑟琳-C-考伊 Social & Scientific Systems, Inc. 8757 Georgia Ave, Silver Spring, MD 20910, United States
社会与科学系统公司8757 Georgia Ave, Silver Spring, MD 20910, United States National Institute of Diabetes and Digestive and Kidney Diseases Division of Diabetes, Endocrinology, and Metabolic Diseases,
美国国家糖尿病、消化和肾脏疾病研究所糖尿病、内分泌和代谢疾病部、6707 Democracy Blud, Bethesda, MD 20892, United States

A R T I C L E I N F O

Article history: 文章历史：

Received 5 May 2020
2020 年 5 月 5 日收到
Received in revised form
收到修订稿
6 April 2021 2021 年 4 月 6 日
Accepted 30 June 2021
2021 年 6 月 30 日接受
Available online 03 July 2021
2021 年 7 月 3 日在线提供

Keywords: 关键词：

Cognitive function 认知功能
Glycemia 血糖
Hemoglobin HbA1c 血红蛋白 HbA1c
NHANES
Older adults 老年人

Abstract 摘要

A B S T R A C T Aims: To determine the association between diabetes status, glycemia, and cognitive function among a national U.S. sample of older adults in the 2011-2014 National Health and Nutrition Examinations Surveys.
A B S T R A C T Aims: To determine between diabetes status, glycemia, and cognitive function among a national U.S. sample of older adults in the 2011-2014 National Health and Nutrition Examinations Surveysys.

Methods: Among 1,552 adults age years, linear and multivariable logistic regressions were used to determine the association between diabetes status (diabetes, prediabetes, normoglycemia) and cognitive function [Consortium to Establish a Registry for Alzheimer's Disease-Word Learning (CERAD W-L), Animal Fluency test, Digit Symbol Substitution Test (DSST)].
方法：在 1552 名 岁的成年人中，使用线性和多变量逻辑回归来确定糖尿病状态（糖尿病、糖尿病前期、正常血糖）与认知功能[阿尔茨海默病登记联盟--单词学习（CERAD W-L）、动物流畅性测试、数字符号替换测试（DSST）]之间的关系。

Results: Overall, diabetes was associated with mild cognitive dysfunction. In age-adjusted models, adults with diabetes had significantly poorer performance on the delayed and total word recalls (CERAD W-L) compared to those with normoglycemia ( 5.8 vs. 6.8 words; and 24.5 vs. 27.6 words; , respectively); the association was nonsignificant after adjusting for cardiovascular disease. Among all adults, cognitive function scores decreased with increasing HbA1c for all assessments, but remained significant in the fully adjusted model for the Animal Fluency and DSST [beta coefficient , , respectively]. As measured by the DSST, the proportion with cognitive impairment was significantly higher for older adults with ( ) vs. (<53 mmol ) vs. ).
结果总体而言，糖尿病与轻度认知功能障碍有关。在年龄调整模型中，与血糖正常的成人相比，糖尿病成人在延迟和总单词回忆（CERAD W-L）方面的表现明显较差（分别为5.8个单词对6.8个单词； ，24.5个单词对27.6个单词； ，）；在调整心血管疾病因素后，这种关联并不显著。在所有成年人中，随着 HbA1c 的增加，所有评估项目的认知功能得分都会下降，但在完全调整模型中，动物流畅度和 DSST 的认知功能得分仍然显著[贝塔系数 , , 分别]。通过 DSST 测定，患有 ( ) 与 (<53 mmol ) 与 ) 的老年人认知功能受损的比例明显更高。

Conclusions: Dysglycemia, as measured by HbA1c, was associated with poorer executive function and processing speed.
结论以 HbA1c 衡量的血糖异常与较差的执行功能和处理速度有关。

©c 2021 Published by Elsevier B.V.
©c 2021 由 Elsevier B.V. 出版。

1. Introduction 1.导言

The prevalence of diagnosed and undiagnosed diabetes among adults in the U.S. has significantly increased over the past several decades from in to in
在过去几十年中，美国成年人中已确诊和未确诊的糖尿病患病率大幅上升，从 到 。
2011-2012 and the burden is substantially higher among older adults ( age years) [1]. In addition, older adults have a higher risk for cognitive impairment, including Alzheimer's Disease, which is estimated at of adults age years [2]. In diabetes, cognitive impairment may largely be due to vascular complications associated with hyperglycemia and diabetes, including cardiovascular disease (CVD) and stroke [3-6]. Severe and repetitive hypoglycemic events have also been associated with initial cognitive impairment and accelerated decline among those with type 2 diabetes [7]; however, no effect was found prospectively among those with type 1 diabetes [8]. Thus, the relationship between glycemic status and cognition is complex [9].
2011-2012年，老年人（ ，年龄为 ）的发病率更高[1]。此外，老年人患认知障碍（包括阿尔茨海默病）的风险更高，据估计，在 岁的成年人中， [2]。糖尿病患者认知障碍的主要原因可能是与高血糖和糖尿病相关的血管并发症，包括心血管疾病（CVD）和中风[3-6]。在 2 型糖尿病患者中，严重和反复的低血糖事件也与最初的认知功能损害和加速衰退有关[7]；但在 1 型糖尿病患者中没有发现前瞻性影响[8]。因此，血糖状况与认知之间的关系是复杂的[9]。
Several epidemiological review studies have shown that cognitive dysfunction is a complication of hyperglycemia in diabetes and even prediabetes [12]. A Framingham Heart Study showed that hyperglycemia was associated with impaired attention and memory among those with undiagnosed diabetes and prediabetes [13]. In the prospective Atherosclerosis Risk in Communities (ARIC) Study, diabetes, higher HbA1c, and prediabetes in midlife was associated with a significantly greater cognitive decline compared to those without diabetes [14].
一些流行病学回顾研究表明，认知功能障碍是糖尿病 甚至糖尿病前期的高血糖并发症之一[12]。弗雷明汉心脏研究显示，在未确诊的糖尿病患者和糖尿病前期患者中，高血糖与注意力和记忆力受损有关[13]。在前瞻性的 "社区动脉粥样硬化风险（ARIC）研究 "中，与没有糖尿病的人相比，中年糖尿病、较高的 HbA1c 和糖尿病前期与认知能力显著下降有关[14]。
However, a specific and detailed assessment of the association of diabetes status, glycemic control, and cognitive function, while also evaluating other factors that may explain this association, has not been carried out in a nationally representative older U.S. sample. While a previous 1999-2002 NHANES study did assess fasting plasma glucose and the association with cognition, the focus was on metabolic syndrome and only one cognitive function assessment was implemented [15]. Another 1999-2002 NHANES study focused on insulin resistance and cognition among older adults but, again, implemented only one cognitive assessment [16]. Finally, a 1988-1994 NHANES study assessed the presence of diabetes and/or hypertension on cognition, but this study was among younger participants age 30-59 years [17]. The more recent 2011-2014 NHANES includes additional measures of cognition as compared to previous NHANES cycles. Thus, to fill this void in the literature, we determined the association between diabetes status, glycemia, and cognitive function among older adults while also accounting for other factors that may explain these associations.
然而，对糖尿病状态、血糖控制和认知功能之间的关系进行具体而详细的评估，同时评估可能解释这种关系的其他因素，还没有在具有全国代表性的美国老年样本中进行过。之前的 1999-2002 年 NHANES 研究确实评估了空腹血浆葡萄糖及其与认知功能的关系，但重点是代谢综合征，只进行了一次认知功能评估[15]。另一项 1999-2002 年 NHANES 研究的重点是老年人的胰岛素抵抗和认知能力，但同样只进行了一次认知能力评估[16]。最后，1988-1994 年的一项 NHANES 研究评估了糖尿病和/或高血压对认知能力的影响，但这项研究的参与者年龄较小，为 30-59 岁[17]。与之前的 NHANES 周期相比，最新的 2011-2014 NHANES 包含了更多的认知测量指标。因此，为了填补这一文献空白，我们确定了老年人糖尿病状态、血糖和认知功能之间的关联，同时还考虑了可能解释这些关联的其他因素。

2. Subjects, Materials, and Methods
2.研究对象、材料和方法

2.1. Study participants 2.1.研究参与者

The National Health and Nutrition Examination Survey (NHANES) is a stratified multistage probability cluster survey conducted in the non-institutionalized civilian U.S. population [18] and includes an in-home interview and a physical examination at a mobile examination center (MEC) [19,20]. Written informed consent approved by the National Center for Health Statistics Institutional Review Board. Our analyses included adults age years who completed cognitive functioning tests and had information on diabetes status in the 2011-2014 survey cycles ( ). Participants selfreported age at interview, sex, race/ethnicity, education, and household income.
美国国家健康与营养检查调查（NHANES）是一项分层多阶段概率群组调查，调查对象为美国非住院平民[18]，调查内容包括家庭访谈和流动检查中心（MEC）的身体检查[19,20]。书面知情同意书由国家卫生统计中心机构审查委员会批准。我们的分析包括在 2011-2014 年调查周期（ ）中完成认知功能测试并提供糖尿病状况信息的 岁成人。参与者自行报告了受访时的年龄、性别、种族/民族、教育程度和家庭收入。

2.2. Diabetes status 2.2.糖尿病状况

Diabetes status groups were defined as follows: diabetes-self-report of a diagnosis by a physician or health care professional, HbA1c ( ), or fasting plasma glucose (FPG) (fasting ) ( ); prediabetes--HbA1c (39-46 mmol ) or FPG 100 ( ); normoglycemia--HbA1c < 5.7% ( ) and FPG ( ). A phlebotomist obtained a blood sample during the MEC visit using a standardized protocol [21]. HOMA-IR, a measure of insulin resistance, was calculated using the following formula: fasting serum insulin ( ) * fasting plasma glucose ( .
糖尿病状态组的定义如下：糖尿病--由医生或医护人员自我报告诊断、HbA1c ( ) 或空腹血浆葡萄糖（FPG） （空腹 ） ( ) ；糖尿病前期--HbA1c (39-46 mmol ) 或 FPG 100 ( ) ；正常血糖--HbA1c < 5.7% ( ) 和 FPG ( ) 。在 MEC 访问期间，一名抽血医师采用标准化方案采集血样[21]。胰岛素抵抗的测量指标 HOMA-IR 用以下公式计算：空腹血清胰岛素 ( ) * 空腹血浆葡萄糖 ( 。

2.3. Cognitive function 2.3.认知功能

The Consortium to Establish a Registry for Alzheimer's Disease (CERAD W-L) assesses immediate and delayed learning ability for new verbal information [22,23]. The CERAD W-L consists of three consecutive learning trials and a delayed recall. For the three learning trials, participants were instructed to read aloud 10 unrelated words. Immediately following the presentation of the words, participants recalled as many words as possible. The delayed recall occurred approximately after the start of the word learning trials. The maximum score on each trial is 10 ; the maximum score for the total word list is 40 (sum of the three trials plus the delayed recall).
建立阿尔茨海默病登记联盟（CERAD W-L）评估对新语言信息的即时和延迟学习能力[22,23]。CERAD W-L 包括三个连续的学习试验和一个延迟回忆。在三次学习试验中，受试者被要求朗读 10 个不相关的单词。单词出现后，受试者立即尽可能多地回忆单词。延迟回忆发生在单词学习试验开始后约 。每次试验的最高分是 10 分；单词表总分的最高分是 40 分（三次试验加延迟回忆的总和）。
The Animal Fluency Test examines verbal category fluency, a component of executive function, as well as other functions such as semantic memory and processing speed [24]. Participants were asked to name as many animals as possible in one minute with a point given for each named animal.
动物流畅性测试主要考察执行功能中的言语类别流畅性，以及语义记忆和处理速度等其他功能[24]。测试要求受试者在一分钟内说出尽可能多的动物名称，每说出一种动物就得一分。
The Digit Symbol Substitution Test (DSST) is a global measure of brain health, relies on processing speed, visual scanning, sustained attention, and short-term memory [25]. The test is conducted using a paper form with a key at the top containing 9 numbers paired with distinct symbols. Participants had two minutes to copy the corresponding symbols in the 133 boxes that adjoin the numbers.
数字符号替换测试（DSST）是对大脑健康状况的全面测量，主要依据处理速度、视觉扫描、持续注意力和短期记忆[25]。测试使用纸质表格进行，表格上方有一个键，键上有 9 个数字和不同的符号。受试者有两分钟的时间在数字旁边的 133 个方框内抄写相应的符号。

2.4. Health behaviors and status
2.4.健康行为和状况

Participants self-reported smoking status (never, former, current), alcohol use ( vs. drinks in past year), and physical inactivity MET (metabolic equivalent) minutes per week of activity]. Height and weight were measured by trained technicians to determine body mass index (BMI, kg/ ). Three blood pressure (BP) readings were taken and averaged after participants were seated for . Hypertension was defined as BP or self-reported use of antihypertensive medication. Hyperlipidemia was defined as total cholesterol or self-reported use of cholesterol
参与者自我报告了吸烟情况（从不吸烟、曾经吸烟、目前吸烟）、饮酒情况（过去一年中饮酒 与 ）以及缺乏运动情况 MET（代谢当量）每周活动分钟数]。身高和体重由经过培训的技术人员测量，以确定体重指数（BMI，公斤/ ）。在 ，参与者坐下后测量三次血压并取平均值。高血压的定义是血压 或自称服用降压药。高脂血症的定义是总胆固醇 或自述服用过胆固醇药物。
lowering medication. History of CVD was self-reported as a previous diagnosis of heart failure, coronary heart disease, angina, or heart attack; history of stroke was also selfreported. The Patient Health Questionnaire (PHQ9) was used to determine depression (PHQ9 score ) [26].
降压药。心血管疾病史为自我报告，即既往诊断为心力衰竭、冠心病、心绞痛或心脏病发作；中风病史也为自我报告。患者健康问卷（PHQ9）用于确定抑郁程度（PHQ9 评分 ）[26]。

2.5. Statistical analysis
2.5.统计分析

The Cohen's d statistic was used to determine the unadjusted standardized effect sizes between those with diabetes or prediabetes and those with normoglycemia for each cognitive test small effect, moderate effect, large effect) [27].
使用 Cohen's d 统计量来确定糖尿病或糖尿病前期患者与血糖正常者在每项认知测试中的未调整标准化效应大小 小效应， 中等效应， 大效应）[27]。
Mean ( confidence interval) cognitive test scores were determined by diabetes status and adjusted for age, race/ethnicity, sex, education, income, smoking status, alcohol consumption, exercise, BMI, hypertension, hyperlipidemia, history of CVD, depression, and history of stroke using linear regression. Each covariate was added individually to the previous model. For succinctness, the regression results are shown with the covariates grouped by the attributes they measure. The continuous association between HbA1c and cognitive test scores was assessed using linear regression (beta coefficients, confidence intervals) and adjusted for the covariates mentioned above; a similar analysis was completed for log-transformed HOMA-IR in place of HbA1c. Finally, the proportion with cognitive impairment by diabetes status and HbA1c level was determined as of the mean cognitive test score for the NHANES population using multivariable logistic regression [28]. All analyses accounted for the cluster design and used sample weights that corrected for non-response, yielding representative estimates of the non-institutionalized U.S. population (SUDAAN User's Manual, Release 9.2, 2008; Research Triangle Institute).
认知测试得分的平均值（ 置信区间）由糖尿病状况决定，并通过线性回归对年龄、种族/民族、性别、教育程度、收入、吸烟状况、饮酒量、运动量、体重指数、高血压、高脂血症、心血管疾病史、抑郁症和中风史进行调整。每个协变量都单独加入到之前的模型中。为简洁起见，回归结果按协变因素所衡量的属性进行分组。HbA1c 与认知测试得分之间的连续关系采用线性回归进行评估（β系数， 置信区间），并根据上述协变量进行调整；对于对数变换后的 HOMA-IR 代替 HbA1c，也完成了类似的分析。最后，使用多变量逻辑回归法[28]，根据NHANES人群认知测试平均得分的 ，按糖尿病状态和HbA1c水平确定认知障碍的比例。所有分析都考虑了分组设计，并使用了校正非响应的样本权重，从而得出了具有代表性的美国非住院人口估计值（《SUDAAN 用户手册》，9.2 版，2008 年；三角研究所）。

3. Results 3.成果

3.1. Characteristics of study population by diabetes status
3.1.按糖尿病状况分列的研究人群特征

The age distribution was similar for those with diabetes, prediabetes, and normoglycemia (Table 1). There was a greater percentage of non-Hispanic black and Hispanic participants, and a lower percentage of women, in those with diabetes compared to those with normoglycemia. There was a higher prevalence of not exercising, obesity, hypertension, and CVD, and stroke among those with diabetes and prediabetes compared to those with normoglycemia.
糖尿病患者、糖尿病前期患者和血糖正常者的年龄分布相似（表 1）。与血糖正常者相比，非西班牙裔黑人和西班牙裔参与者的比例更高，女性比例更低。与血糖正常者相比，糖尿病和糖尿病前期患者不运动、肥胖、高血压、心血管疾病和中风的发病率更高。

3.2. Standardized effect sizes by diabetes status
3.2.按糖尿病状况分列的标准化效应大小

Overall, adults with diabetes had significantly worse cognitive performance compared to those with normoglycemia (Fig. 1). There was a moderate effect size for the total word recall score and DSST (Cohen's for both) and smaller effect sizes for the delayed word recall (Cohen's ) and the Animal Fluency test (Cohen's ) when comparing those with diabetes to those with normoglycemia.
总体而言，与血糖正常者相比，成人糖尿病患者的认知能力明显较差（图 1）。当糖尿病患者与血糖正常者进行比较时，单词回忆总分和DSST（两者均为Cohen's ）的效应大小适中，而延迟单词回忆（Cohen's ）和动物流畅性测试（Cohen's ）的效应大小较小。

3.3. Cognitive function scores by diabetes status
3.3.按糖尿病状况分列的认知功能得分

Adults with diabetes recalled significantly fewer words in the delayed word recall compared to those with normoglycemia in the unadjusted, age-adjusted, and many partially adjusted models, but the association was non-significant in the fully adjusted model ( 6.0 vs. 6.6 words; ) (Table 2). A similar relationship was found with the total word recall test. Those with diabetes performed significantly worse on the DSST compared to those with normoglycemia in the unadjusted model and after further adjustment for age, race/ethnicity, and sex (47.1 vs. 52.3, ), but there was no significant difference after adjusting for education. The percent with cognitive impairment, for any test, was similar by diabetes status in unadjusted and adjusted models (data not shown).
在未调整模型、年龄调整模型和许多部分调整模型中，与血糖正常者相比，糖尿病成人在延迟单词回忆中回忆的单词明显较少，但在完全调整模型中，两者之间的关系并不显著（6.0 个单词对 6.6 个单词； ）（表 2）。总单词回忆测试也发现了类似的关系。在未经调整的模型中，以及在对年龄、种族/民族和性别进行进一步调整后，糖尿病患者在 DSST 中的表现明显差于血糖正常者（47.1 对 52.3， ），但在对教育程度进行调整后，两者没有显著差异。在未经调整的模型和调整后的模型中，在任何测试中出现认知障碍的百分比与糖尿病状况相似（数据未显示）。

3.4. Cognitive function scores by HbA1c and HOMA-IR
3.4.按 HbA1c 和 HOMA-IR 计算的认知功能得分

In the total population, cognitive function scores decreased with increasing HbA1c for all assessments (Table 3). For the DSST, every unit increase in HbA1c resulted in 1.11 fewer matched symbols in the fully adjusted model ( ). The percent with cognitive impairment, as assessed by the DSST, was significantly higher for those with HbA1c ( ) vs. HbA1c ( ) ( vs. ) (Table 4). In a separate analysis replacing HbA1c with log-transformed HOMA-IR, HOMA-IR was not associated with any cognitive function test (data not shown).
在全部人群中，所有评估的认知功能得分都随着 HbA1c 的增加而降低（表 3）。就 DSST 而言，在完全调整模型中，HbA1c 每增加一个单位，匹配符号就会减少 1.11 个 ( )。HbA1c ( ) 与 HbA1c ( ) ( 与 ) 相比，DSST 评估的认知障碍百分比明显更高（表 4）。在用对数转换的 HOMA-IR 替代 HbA1c 的单独分析中，HOMA-IR 与任何认知功能测试都没有关联（数据未显示）。

4. Discussion 4.讨论

In this study of older adults in the United States, we found that those with diabetes, but not prediabetes, had mild cognitive dysfunction compared to those with normoglycemia. These results were found for the CERAD W-L tests after adjusting for demographic characteristics, health behaviors, and BMI, and were marginally significant after adjusting for comorbidities, including CVD. This suggests that immediate and delayed verbal learning ability is compromised among those with diabetes. While dysglycemia was not strongly associated with verbal learning ability, higher HbA1c was associated with worse executive function and processing speed, as measured by the DSST, and was independent of demographic characteristics and other cardiometabolic related indices.
在这项针对美国老年人的研究中，我们发现与血糖正常者相比，糖尿病患者（而非糖尿病前期患者）存在轻度认知功能障碍。在对人口统计学特征、健康行为和体重指数进行调整后，CERAD W-L 测试也发现了这些结果，而在对包括心血管疾病在内的合并症进行调整后，这些结果略有显著性。这表明糖尿病患者的即时和延迟言语学习能力受到了影响。虽然血糖异常与言语学习能力的关系不大，但根据 DSST 测量，较高的 HbA1c 与较差的执行功能和处理速度有关，并且与人口特征和其他心脏代谢相关指数无关。
Older adults with diabetes showed mild cognitive dysfunction as measured by the DSST, which is considered a sensitive measure of global cognitive function, compared to those with normoglycemia. This result aligns with a previous longitudinal study, ARIC, that found significantly greater cognitive decline among adults with diabetes compared to those without diabetes after adjustment for sociodemographics, CVD risk factors, and CVD [14]. Regression analysis in our study showed that the association became non-significant after adjusting for education. Previous research has shown that level of education modifies the relationship between Alzheimer's Disease pathology and cognitive function in older
与血糖正常的老年人相比，被认为是全球认知功能敏感测量指标的 DSST 测量结果显示，患有糖尿病的老年人出现了轻度认知功能障碍。这一结果与之前的一项纵向研究--ARIC--一致，该研究发现，在对社会人口统计学、心血管疾病风险因素和心血管疾病进行调整后，与非糖尿病患者相比，糖尿病患者的认知功能下降幅度明显更大[14]。我们研究中的回归分析表明，在对教育程度进行调整后，这种关联变得不显著。以往的研究表明，教育水平会改变老年痴呆症病理和认知功能之间的关系。
Table 1 - Participant characteristics [percentage (standard error)] by diabetes status among adults age years, NHANES 2011-2014.
表 1 - 2011-2014 年国家健康与人口调查（NHANES）中按 岁成年人糖尿病状况分列的参与者特征 [百分比（标准误差）]。
Diabetes
 糖尿病前期
Prediabetes

正常血糖 (
Normoglycemia
(
Age
60-69 years 60-69 岁 51.8 (3.6) 61.6 (6.0)
years 48.2 (3.6) 38.4 (6.0)
Race/ethnicity 种族/族裔
Non-Hispanic white 非西班牙裔白人 86.3 (3.8)
Non-Hispanic black 非西班牙裔黑人 8.9 (1.3) 6.1 (2.2)
Non-Hispanic Asian 非西班牙裔亚裔 5.1 (1.0) 2.5 (1.2)
Mexican-American 墨西哥裔美国人 4.0 (1.3) 3.1 (1.4)
Other Hispanic 其他西班牙裔 3.7 (1.1)
Female 54.4 (3.1) 58.9 (2.8)
Education
<high school <高中 19.1 (3.0) 13.4 (3.1)
High school 高中 25.3 (2.7)
>high school >高中
Household Income
家庭收入 		12.1 (3.8)
Smoking status 吸烟情况
Never 48.6 (4.2) 50.5 (4.1)
Former 43.6 (1.8) 38.2 (3.1)
Current 10.1 (1.4)
Consume alcohol 饮酒 70.4 (3.8)
Does not exercise 不锻炼 41.4 (2.3)
Body mass index 体重指数
42.8 (3.3)
28.0 (1.9)
Hyperlipidemia 高脂血症 41.1 (3.8) 42.7 (3.5)
Hypertension 高血压 49.2 (3.1)
History of CVD 心血管疾病史
Depression
12.4 (1.8) 7.7 (3.0)
History of Stroke 中风史 7.6 (0.9) 5.1 (1.9)
compared to those with normoglycemia using two-tailed large sample z-tests.
采用双尾大样本 z 检验法，与血糖正常者进行比较。
Includes both diagnosed and undiagnosed diabetes.
包括已诊断和未诊断的糖尿病。
adults [29]. Nevertheless, in the total U.S. population, increasing HbA1c, a measure of average blood glucose levels over an approximate three to four month period, was significantly associated with lower DSST scores even after accounting for multiple covariates, including education. In addition, we found that a significantly higher proportion of older adults with HbA1c ( ) had cognitive impairment, as measured by the DSST, compared to their counterparts with HbA1c ( ). Finally, we found few associations between HbA1c and cognitive impairment when the results were stratified by diabetes status (data not shown). For those with diabetes, current HbA1c control may not have as strong an effect on cognition as the duration of diabetes or the amount of time that diabetes is uncontrolled; in addition, sample size may have been too small to detect a difference. However, there was a significant inverse association between HbA1c and the DSST among the total population and this association remained after full adjustment for all covariates. This may suggest that dysglycemia, as measured by HbA1c, is strongly associated with a measure of global cognitive function regardless of other factors that may affect cognition.
29]。然而，在美国总人口中，HbA1c（衡量大约三到四个月内平均血糖水平的指标）的增加与 DSST 分数的降低显著相关，即使考虑了包括教育在内的多种协变量也是如此。此外，我们还发现，与 HbA1c 为 ( ) 的老年人相比，HbA1c 为 ( ) 的老年人出现认知障碍（以 DSST 为测量指标）的比例明显更高。最后，根据糖尿病状况进行分层后，我们发现 HbA1c 与认知障碍之间几乎没有关联（数据未显示）。对于糖尿病患者来说，目前的 HbA1c 控制情况对认知能力的影响可能不如糖尿病持续时间或糖尿病未得到控制的时间长；此外，样本量可能太小，无法检测出差异。然而，在所有人群中，HbA1c 与 DSST 之间存在明显的反向关系，在对所有协变量进行全面调整后，这种关系依然存在。这可能表明，无论是否存在其他可能影响认知的因素，用 HbA1c 测量的血糖异常与整体认知功能的测量结果都密切相关。
Results from the CERAD W-L measure, a test of word learning and short-term memory, suggest that decreased sensitiv- ity to glucose may affect memory structures in the brain, including the hippocampus [4]. The Longitudinal Health and Retirement Study found that among adults age years, diabetes was associated with a faster rate of memory decline, measured by immediate and delayed word list recalls [30]. In multivariable analysis, adults with diabetes in our study reported significantly fewer words in the total and delayed recall tests compared to those with normoglycemia after adjustment for age, sociodemographic characteristics, lifestyle factors, and obesity, suggesting that verbal learning ability is compromised among those with diabetes, regardless of these factors. The association was attenuated after adjusting for cardiovascular disease; therefore, it appears that cardiovascular disease may moderate the association between diabetes and the CERAD W-L as previously reported [3].
CERAD W-L 测量是对单词学习和短期记忆的测试，其结果表明，对葡萄糖敏感性的降低可能会影响包括海马在内的大脑记忆结构[4]。纵向健康与退休研究》（Longitudinal Health and Retirement Study）发现，在 年龄段的成年人中，糖尿病与记忆力衰退速度加快有关 （通过即时和延迟单词表回忆进行测量）[30]。在多变量分析中，在调整年龄、社会人口学特征、生活方式因素和肥胖等因素后，与血糖正常者相比，我们研究中的糖尿病成人在总回忆和延迟回忆测试中报告的单词数明显较少，这表明无论这些因素如何，糖尿病患者的言语学习能力都会受到影响。在对心血管疾病进行调整后，这种关联有所减弱；因此，正如之前所报道的那样[3]，心血管疾病可能会缓和糖尿病与CERAD W-L之间的关联。
Poor cognition can have detrimental effects on diabetes management and care [31], which may subsequently cause additional comorbidities and complications, including hypoglycemia . In supplemental analysis, we found no association between cognitive impairment and currently implementing these recommended health-related behaviors (ORs range from 0.84 to 1.13 in fully adjusted models, data not shown). In addition, there was no association between cognitive impairment and diabetes self-care behaviors
认知能力差会对糖尿病管理和护理产生不利影响[31]，进而可能导致更多的合并症和并发症，包括低血糖 。在补充分析中，我们发现认知障碍与目前实施这些建议的健康相关行为之间没有关联（在完全调整模型中，ORs 从 0.84 到 1.13 不等，数据未显示）。此外，认知障碍与糖尿病自我护理行为之间也没有关联。
Fig. 1 - Standardized effect sizes (Cohen's and confidence interval) by cognitive assessment tests in those with diabetes or prediabetes compared to those with normoglycemia. Light gray shading indicates a small effect size, medium gray indicates a moderate effect size, and dark gray indicates a large effect size.
图 1 - 与血糖正常者相比，糖尿病或糖尿病前期患者认知评估测试的标准化效应大小（Cohen's 和 置信区间）。浅灰色阴影表示效应大小较小，中灰色表示效应大小适中，深灰色表示效应大小较大。
(checking blood glucose levels and feet for sores) among those with diagnosed diabetes (ORs range from 0.79 to 1.27). Future analyses are needed with more comprehensive measures of self-care behaviors.
(检查血糖水平和脚部是否有溃疡）（OR 值介于 0.79 至 1.27 之间）。今后需要对自我护理行为进行更全面的分析。
We found no difference in cognitive function among those with prediabetes compared to those with normoglycemia. Since prediabetes probably represents a lower magnitude and shorter duration of hyperglycemia relative to diabetes, a significant association may not have been detectable.
我们发现，与血糖正常者相比，糖尿病前期患者的认知功能没有差异。由于与糖尿病相比，糖尿病前期可能代表较低程度和较短持续时间的高血糖，因此可能无法检测到显著的关联。
A major strength of this study is the nationally representative sample of the U.S. non-institutionalized population. In addition, we were able to assess cognitive function by levels of glycemia using laboratory measures for FPG and HbA1c. The NHANES included three different cognitive tests, which provided more depth than previous NHANES surveys; however, there were many domains of cognitive function that we not assessed. The cross-sectional study design limits our ability to make any causal statements about the associ- ation between diabetes and cognitive function. Information on repetitive episodes of hypoglycemia, which has also been associated with cognitive impairment in some studies, was not available in NHANES [7,9]. Finally, we cannot rule out that adjustment is incomplete and that those with higher HbA1c levels may be more frail compared to those with lower HbA1c levels. Those with high HbA1c levels may also be more likely to have episodes of hypoglycemia which makes it difficult to fully elucidate the effect of glycemia .
这项研究的一个主要优势是采用了具有全国代表性的美国非住院人口样本。此外，我们还能通过实验室测量 FPG 和 HbA1c 来评估血糖水平对认知功能的影响。NHANES 包括三种不同的认知测试，比以往的 NHANES 调查更深入；但是，我们没有评估认知功能的许多领域。横断面研究设计限制了我们对糖尿病与认知功能之间的因果关系做出任何陈述的能力。NHANES [7,9]中没有重复低血糖发作的信息，而在一些研究中，低血糖也与认知功能障碍有关。最后，我们不能排除调整不完全，HbA1c 水平较高的人可能比 HbA1c 水平较低的人更虚弱。HbA1c 水平高的人也可能更容易发生低血糖，这就很难完全阐明血糖 的影响。
In a national sample of older adults, we found that persons with diabetes had moderate decrements in cognition compared to those with normoglycemia and that hyperglycemia was associated with poorer executive function and processing speed, regardless of diabetes status. Further research is needed to understand factors leading to impaired cognition among patients with diabetes so that interventions to prevent cognitive decline can be developed.
我们在全国老年人样本中发现，与血糖正常者相比，糖尿病患者的认知能力中度下降，而且无论糖尿病状况如何，高血糖都与较差的执行功能和处理速度有关。要了解导致糖尿病患者认知能力受损的因素，以便制定预防认知能力下降的干预措施，还需要进一步的研究。
Table 2 - Mean (95% confidence interval) cognitive assessment score by diabetes status among adults age years, NHANES 2011-2014.
表 2 - 2011-2014 年 NHANES 中按糖尿病状况分列的成人认知评估得分均值（95% 置信区间）。
Diabetes  糖尿病
Delayed Word Recal 延迟单词记忆
(CERAD W-L)
Normoglycemia 血糖正常
p-value(Diabetes P值（糖尿病
vs. Normoglycemia) 与正常血糖值对比）
p-value (Prediabetes vs. Normoglycemia)
p 值（糖尿病前期与血糖正常值对比）
Unadjusted
Age-adjusted 年龄调整
Model 1 模型 1
Model 2 模型 2
Model 3 模型 3
Model 4 模型 4
Model 5 模型 5
Model 6 模型 6
Model 7 模型 7
Total Word Recall 单词总召回率
(CERAD W-L)
Unadjusted
Age-adjusted 年龄调整
Model 1 模型 1
Model 2 模型 2
Model 3 模型 3
Model 4 模型 4
Model 5 模型 5
Model 6 模型 6
Model 7 模型 7
Animal Fluency 动物流畅性
Unadjusted
Age-adjusted 年龄调整
Model 1 模型 1
Model 2 模型 2
Model 3 模型 3
Model 4 模型 4
Model 5 模型 5
Model 6 模型 6
Model 7 模型 7
Digit Sy 数字 Sy
Sigit Symbol Substitution Test (DSST)
符号替换测验（DSST）
Unadjusted
Age-adjusted 年龄调整
Model 1 模型 1
Model 2 模型 2
Model 3 模型 3
Model 4 模型 4
Model 5 模型 5
Model 6 模型 6
Model 7 模型 7
0.478
0.002 0.687
0.010 0.818
0.015 0.852
0.028 0.986
0.018 0.989
0.006 0.899
0.059 0.929
0.064 0.934
0.240
0.416
0.003 0.541
0.006 0.582
0.012 0.813
0.011 0.769
0.005 0.665
0.052 0.847
0.054 0.845
0.033 0.233
0.056 0.384
0.211 0.595
0.189 0.572
0.443 0.857
0.553 0.787
0.309 0.609
0.225 0.563
0.181 0.556
0.147
0.002 0.314
0.019 0.510
0.024 0.538
0.143 0.970
0.230 0.904
0.080 0.874
0.209 0.856
478
0.687
.818
0.852
0.986
0.989
.899
0.929
Covariates were added individually, but are shown grouped by attribute for succinctness
变量单独添加，但为简洁起见，按属性分组显示
Covariates were added individually, but are shown grouped by attribute for succinctness
变量单独添加，但为简洁起见，按属性分组显示
Table 3 - Beta coefficients for the association between HbA1c and cognitive assessment score among all adults age years, NHANES 2011-2014.
表 3 - 2011-2014 年国家健康与人口调查（NHANES）中 岁所有成年人 HbA1c 与认知评估得分之间关系的 Beta 系数。

延迟单词回忆（CERAD W-L）
Delayed Word Recall
(CERAD W-L)

单词总召回率（CERAD W-L）
Total Word Recall
(CERAD W-L)
Animal Fluency 动物流畅性 Digit Symbol Substitution Test (DSST)
数字符号替换测试（DSST）
-0.19 0.019 -0.51 0.048 -0.64 0.040 -2.55 0.001
Model 2 模型 2 -0.14 0.082 -0.33 0.220 -0.51 0.100 -1.61 0.015
Model 3 模型 3 -0.12 0.153 -0.27 0.302 -0.42 0.146 -1.32 0.021
Model 4 模型 4 -0.10 0.189 -0.21 0.395 -0.38 0.139 -1.17 0.023
Model 5 模型 5 -0.13 0.097 -0.26 0.305 -0.47 0.046 -1.36 0.007
Covariates were added individually, but are shown grouped by attribute for succinctness.
变量是单独添加的，但为了简洁起见，按属性分组显示。
Model 1: Adjusted for age, race/ethnicity
模型 1：根据年龄、种族/族裔进行调整
Model 2: Model sex
模型 2：模型 性别
Model 3: Model 2 + education, income
模型 3：模型 2 + 教育、收入
Model 4: Model smoking status, alcohol consumption, exercise
模型 4：模型 吸烟状况、饮酒量、运动量
Model 5: Model body mass index
模型 5：模型 身体质量指数
Model 6: Model 5 + hypertension, hyperlipidemia, history of CVD
模型 6：模型 5 + 高血压、高脂血症、心血管疾病史
Model 7: Model depression, history of stroke
模型 7：模型 抑郁症、中风病史
Table 4 - The proportion (%, SE) with cognitive impairment in the total population by A1c level among adults age years, NHANES 2011-2014.
表 4 - 2011-2014 年 NHANES 调查中，按 A1c 水平分列的 岁成年人中患有认知障碍的总人口比例（%，SE）。

A1c < 7.0%（<53 毫摩尔/摩尔）
A1c < 7.0%
(<53 mmol/mol)
 A1c 7.0- <8.0
A1c 7.0- <8.0%
A1c
CERAD WL Delayed CERAD WL 延误
Model 1 模型 1
Model 2 模型 2
Model 3 模型 3
Model 4 模型 4
Model 5 模型 5
Model 6 模型 6
Model 7 模型 7
CERAD WL Total CERAD WL 共计
Model 1 模型 1
Model 2 模型 2
Model 3 模型 3
Model 4 型号 4
Model 5 模型 5
Model 6 模型 6
Model 7 模型 7
Animal Fluency 动物流畅性
Model 1 模型 1
Model 2 模型 2
Model 3 模型 3
Model 4 型号 4
Model 5 模型 5
Model 6 模型 6
Model 7 模型 7
DSST
Model 1 模型 1
Model 2 模型 2
Model 3 模型 3
Model 4 型号 4
Model 5 模型 5
Model 6 模型 6
Model 7 模型 7
Cognitive impairment defined as SD of the mean cognitive test score for the NHANES population.
认知障碍的定义是 NHANES 人口认知测试平均得分的 SD 值。
Model 1: Adjusted for age, race/ethnicity
模型 1：根据年龄、种族/族裔进行调整
Model 2: Model sex
模型 2：模型 性别
Model 3: Model 2 + education, income
模型 3：模型 2 + 教育、收入
Model 4: Model 3 + smoking status, alcohol consumption, exercise
模型 4：模型 3 + 吸烟状况、饮酒量、运动量
Model 5: Model body mass index
模型 5：模型 身体质量指数
Model 6: Model 5 + hypertension, hyperlipidemia, history of CVD
模型 6：模型 5 + 高血压、高脂血症、心血管疾病史
Model 7: Model depression, history of stroke
模型 7：模型 抑郁症、中风病史
vs. A1c .
vs. A1c .

Declaration of Competing Interest
竞争利益声明

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
作者声明，他们没有任何可能会影响本文所报告工作的已知经济利益或个人关系。

Acknowledgements 致谢

The authors would like to acknowledge Keith F. Rust, PhD for his statistical support.
作者衷心感谢 Keith F. Rust 博士提供的统计支持。
No potential conflicts of interests relevant to this article were reported.
没有报告与本文相关的潜在利益冲突。
S.S.C. contributed to the research design, analyzed and interpreted the data, and wrote, reviewed, and edited the manuscript. C.L. and L.E.S contributed to the interpretation of the data, the discussion and reviewed and edited the manuscript. A.M. and C.C.C. contributed to the research design, interpretation of the data, and reviewed and edited the manuscript. All authors provided final approval of the manuscript. Dr. Sarah Stark Casagrande is the guarantor of this work and, as such, had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
S.S.C.参与了研究设计，分析和解释了数据，并撰写、审阅和编辑了手稿。C.L.和L.E.S.参与了数据解读、讨论，并对手稿进行了审阅和编辑。A.M.和C.C.C.参与了研究设计、数据解读，并审阅和编辑了手稿。所有作者对手稿进行了最终审批。萨拉-斯塔克-卡萨格兰德博士是这项工作的担保人，因此，她可以完全访问研究中的所有数据，并对数据的完整性和数据分析的准确性负责。
This work was funded by the National Institutes of Diabetes and Digestive and Kidney Diseases (GS-10F-0381L). The sponsor was involved with the study design and data collection only.
这项工作由美国国立糖尿病、消化道和肾脏疾病研究所（GS-10F-0381L）资助。赞助方仅参与了研究设计和数据收集。

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