type 2 diabetes and cognition

TYPE 2 DIABETES AND COGNITION Neuropsychological sequelae of vascular risk factors in the ageing brain

Esther van den Berg

Cover design Joost van den Berg & Robin Band Layout Renate Siebes, Proefschrift.nu Printed by Ipskamp Drukkers B.V., Enschede ISBN 978-90-393-5106-2 © 2009 E. van den Berg All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage or retrieval system, without permission in writing from the author.

TYPE 2 DIABETES AND COGNITION Neuropsychological sequelae of vascular risk factors in the ageing brain TYPE 2 DIABETES EN COGNITIE Neuropsychologische gevolgen van vasculaire risicofactoren voor het verouderende brein (met een samenvatting in het Nederlands)

Proefschrift ter verkrijging van de graad van doctor aan de Universiteit Utrecht op gezag van de rector magnificus, prof.dr. J.C. Stoof, ingevolge het besluit van het college voor promoties in het openbaar te verdedigen op dinsdag 15 september 2009 des middags te 2.30 uur

door

Esther van den Berg geboren op 20 november 1978 te Rotterdam

Promotoren:

Prof.dr. L.J. Kappelle Prof.dr. R.P.C. Kessels

Co-promotor:

Dr. G.J. Biessels

De studies beschreven in dit proefschrift werden mede mogelijk gemaakt door de financiële steun van het Diabetes Fonds (subsidies 2001.00.023 en 2003.01.004). De totstandkoming van dit proefschrift werd mede mogelijk gemaakt door financiële steun van het Diabetes Fonds, het Remmert Adriaan Laan Fonds, de Internationale Stichting Alzheimer Onderzoek, Alzheimer Nederland, AstraZeneca, Novo Nordisk, Eli Lilly, Janssen-Cilag, Lundbeck en Bristol-Myers Squibb.

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Contents

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9

1.1

Introduction ognitive fu

11

1.2

Outline of the thesis

25

a list of u Type 2 diabetes mellitus, cognitive function and dementia: delay a per Vascular and determinants themmetabolic visu

Vascular risk factors and cognition: Systematic reviews Chapter 2

Type 2 diabetes mellitus, hypertension, dyslipidemia and obesity: A systematic comparison of their impact on cognition

29

Chapter 3

Diabetes and other vascular risk factors for dementia: Which factor matters most? A systematic review

55

THE HOORN STUDY Cognition and vascular disease in pre-diabetic stages and recent onset diabetes Chapter 4

Cognitive functioning in elderly persons with type 2 diabetes and metabolic syndrome: The Hoorn study

71

Chapter 5

10-year time course of risk factors for increased carotid intimamedia thickness: The Hoorn study

85

Chapter 6

Blood pressure levels in pre-diabetic stages are associated with worse cognitive functioning in patients with type 2 diabetes

97

Chapter 7

Albuminuria is unrelated to cognitive functioning in wellcontrolled patients with type 2 diabetes mellitus

107

THE UTRECHT DIABETIC ENCEPHALOPATHY STUDY Cognition in type 2 diabetes: Neuropsychological profile and progression over time Chapter 8

A detailed profile of cognitive dysfunction and its relation to psychological distress in patients with type 2 diabetes mellitus

113

Chapter 9

Mild impairments in cognition in patients with type 2 diabetes mellitus: The use of the concepts MCI and CIND

127

Chapter 10

A 4-year follow-up study of cognitive functioning in patients with type 2 diabetes mellitus

131

THE LEIDEN 85-PLUS STUDY Cognition, type 2 diabetes and the metabolic syndrome in the oldest of the old Chapter 11

The impact of diabetes mellitus on cognitive decline in the oldest of the old: A prospective population-based study

141

Chapter 12

The metabolic syndrome is associated with decelerated cognitive decline in the oldest old

153

Chapter 13

General discussion

163

13.1

Main findings and implications for future research

165

13.2

Implications for clinical care

171

References

177

Summary

201

Samenvatting

207

List of publications

213

Acknowledgements

217

Dankwoord

219

Curriculum vitae

223

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General introduction

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Type 2 diabetes mellitus, cognitive function and dementia: Vascular and metabolic determinants E van den Berg, RPC Kessels, LJ Kappelle, EHF de Haan, GJ Biessels

Drugs of Today, 42: 741-754, 2006

Chapter 1.1

T2DM, cognitive functioning and dementia

Abstract Type 2 diabetes mellitus (T2DM) is a common metabolic disease, with a rising global prevalence. It is associated with slowly progressive end-organ damage in the eyes and kidneys, but also in the brain. The latter complication is often referred to as ‘diabetic encephalopathy’ and is characterized by mild to moderate impairments in cognitive functioning. T2DM is also associated with an increased risk of dementia. To date, the pathogenetic mechanisms are largely unclear. Cognitive impairments in patients with T2DM have been associated both with vascular risk factors, such as hypertension and dyslipidemia, and with diabetes-related factors such as glycemic control, duration of the disease and treatment modality. Studies that address these associations generally focus on statistical (in)dependence of certain risk factors in the association between T2DM and cognitive decline rather than the causality of the association, which, from a mechanistic point of view, is more relevant. In this review we describe the association between T2DM and cognitive dysfunction and dementia. Furthermore, potential determinants of impaired cognition in T2DM are addressed both from the perspective of statistical associations and from a mechanistic point of view.

12

Chapter 1.1

Type 2 diabetes mellitus (T2DM) is a common metabolic disease, especially in older people, with global prevalence estimates ranging from 2.8% in 2000 to a projected 4.4% in 2030 [1]. Worldwide, the number of patients is expected to increase from 171 million in 2000 to 366 million in 2030. T2DM is characterized by hyperglycemia, caused by insulin resistance and an inadequate compensation in the secretion of insulin [2]. It may result in complications such as kidney failure, foot ulcers, peripheral neuropathy and blindness. Furthermore, T2DM is associated with a high risk of cardiovascular disease and premature death [3,4]. In the last decade it has become increasingly evident that diabetes may also affect the central nervous system, a complication referred to as ‘diabetic encephalopathy’ [5]. This complication is reflected in impaired cognitive functioning [6] and is also associated with an increased risk of dementia [7]. The aim of this review is to describe the effects of T2DM on cognitive function and dementia and to address possible determinants of cognitive decline.


Introduction

T2DM and cognitive dysfunction In 1922, Miles and Root were the first to describe a possible relation between diabetes and cognitive dysfunction. Compared to non-diabetic persons, they observed worse performance of patients with diabetes on measures of memory, arithmetic and psychomotor speed [8]. Since then, numerous studies have examined the relation between T2DM and cognitive functioning [6,9,10]. Cognitive functioning is comprised of multiple cognitive domains, such as memory, information-processing speed, language, visuoconstruction, perception, attention and executive functions, which can be impaired selectively [11]. In the next section the relation between T2DM and these cognitive domains will be addressed in detail. Where possible, the extent to which a cognitive domain is impaired will be expressed in effect sizes (Cohen’s d [12]). In neuropsychological studies, effect sizes below 0.2 are considered small, between 0.2 and 0.8 medium and above 0.8 large [12]. Many studies on the effect of T2DM on cognitive functioning assessed memory function. Generally, in verbal memory tests patients have to repeat a short paragraph or recall a list of unrelated words that is presented to them repeatedly. Patients are asked to recall the text or the words immediately (immediate recall) and/or after a delay period of 20 to 30 minutes (delayed recall). In visuospatial memory tests patients are asked to recall spatial information that is presented to them visually. The majority of the studies that examined memory function were cross-sectional. Most of these studies observed diminished verbal memory in patients with T2DM, with effect sizes ranging from 0.2 to 0.6 [13,14]. The effects appear to be larger for non-contextual information (recall of unrelated words) compared to contextual information (paragraph recall). Diminished visuospatial memory is observed in about half of the studies addressing this domain, with effect sizes comparable to those of verbal memory [14,15]. In longitudinal studies memory function has been assessed less often. These studies report cognitive decline in verbal memory for patients with T2DM [16,17]. The single longitudinal study that examined visuospatial memory observed no effects of T2DM [16].

13

Chapter 1.1


Attention has also been examined in many studies, with a wide range of test procedures. Basic attention span (currently more recognized as ‘working memory’) is often assessed by asking patients to verbally repeat series of digits of increasing length (Digit Span, Wechsler Adult Intelligence Scale III [WAIS-III]) [18] or tap series of blocks of increasing length in the same fixed order as the experimenter [19,20]. More complex attention processes are related to, for example sustained, selective or divided attention. A widely used test for selective attention is the Stroop Color Word Test [21] in which patients are asked to name the ink colour of incongruously printed colour names. In general, cross-sectional and longitudinal studies show worse performance of T2DM patients on complex attention tasks (effect sizes range from 0.3-0.6 [22]) but not basic attention tasks (effect sizes range from 0 to 0.2 [23]) compared to non-diabetic persons. Closely related to attention is the domain of executive functioning, which has only recently gained attention in the literature and which has been studied less extensively in T2DM until now. Executive functioning involves the planning and monitoring of behaviour, and mental flexibility. Examples of tests that are often used to measure this domain are the Trail Making Test Part B [24], where patients are asked to alternatively connect letters and digits, and Verbal Fluency [25], where patients are asked to reproduce as many words as possible that begin with a specified letter of the alphabet over one minute. The majority of cross-sectional studies that measured executive functioning showed diminished performance of the patients with T2DM [22,26]. Effect sizes range from 0.3 to 0.6. Longitudinal studies also observed a greater decline over time for patients with patients [16,27]. Information-processing speed involves tests in which the ability to process information within a limited amount of time is essential. For example, in the Digit Symbol Test (WAIS-III [18]) patients are asked to copy as many symbols according to a code key in 90 or 120 seconds. This test is known to be sensitive to cognitive decline and is thus used in many studies. Other tests in this domain rely on reaction times, i.e. the ability to respond as quickly as possible to stimuli that are presented on a computer screen or a response panel. The majority of cross-sectional studies that assess this domain show diminished performance in patients with T2DM [23,26]. Effects sizes range from 0.2 to 0.8. The Digit Symbol Test has been used frequently in longitudinal studies. The decline in performance on this task was larger in patients with T2DM than in nondiabetic participants [17]. The domains of perception, visuoconstruction and language have been examined by a minority of studies, which usually showed no differences between patients with T2DM and non-diabetic persons [14,23]. However, based on the present limited literature, no clear conclusion can be drawn on these domains. Summarizing these results, patients with T2DM have moderate impairments across all cognitive domains. These impairments are most consistently found in verbal memory and information processing speed. This neuropsychological profile does not reflect a problem of competence as such, but rather of performance. Patients with T2DM seem to have a diminished ability to efficiently process unstructured information, particularly when the cognitive task at hand requires speed of response [28]. This results in a slower performance on neuropsychological tasks and difficulties in more

14

Pre-DM

B

T2DM

Pre-DM

C

T2DM

Pre-DM

T2DM

Figure 1.1.1 Putative course of development of cognitive dysfunction in T2DM. In option A cognitive impairments develop after the onset of T2DM and progress gradually thereafter. This course of development would fit the hypothesis that hyperglycemia itself plays the major role in the development of cognitive impairments. In option B the onset of cognitive impairment is in the early pre-diabetic phase, with a continuous decline thereafter. This time course would fit the hypothesis that risk factors associated with the pre-diabetic condition (e.g. hypertension, obesity and dyslipidemia) rather than hyperglycemia itself are the prime determinants of cognitive decline. Option C is a combination of the two previous options; early cognitive impairments develop from pre-diabetic stages onwards, due to exposure to vascular risk factors (dotted line). After development of diabetes, hyperglycemia accelerates cognitive decline (solid line).


Cognitive impairment

Chapter 1.1

A

demanding situations such as memory tasks. Some researchers have addressed cognitive functioning in non-demented patients with T2DM in more global terms, by classifying persons as either being cognitively ‘intact’ or ‘impaired’. Concepts such as ‘mild cognitive impairment’ (MCI) [29] and ‘cognitive impairment, no dementia’ (CIND) [30] are used in this context. The criteria for CIND include impairment in one or more cognitive domains, functional independence and no dementia. The criteria for MCI include the presence of an isolated memory deficit in the absence of dementia. Although the exact diagnostic criteria for both of these concepts are under debate, persons who meet the criteria for either MCI or CIND have a substantially increased risk of developing dementia [31,32]. Studies concerning the prevalence and incidence of MCI and CIND in patients with T2DM generally showed that T2DM was associated with CIND [33], but not specifically with amnesic MCI [3337]. This is in line with the aforementioned neuropsychological results showing that the cognitive impairments as encountered in patients with T2DM are not limited to the memory domain, but rather can be observed across multiple cognitive domains. Several methodological issues should be taken into account when addressing the association between T2DM and cognitive functioning. Over 90% of the studies described previously are cross-sectional, with a case-control design, and have usually applied multiple cognitive tests in relatively small samples. This may have lead to type I and type II statistical errors. In addition, many different testing procedures were used, ranging from single estimates of cognitive function, such as the Mini Mental State Examination (MMSE or 3MS) [38] or similar instruments, to extensive neuropsychological test batteries covering all cognitive domains in detail. This limits both comparison between different studies and extrapolation to the general population of patients with T2DM. Given the reported patterns of cognitive impairment in

15

Chapter 1.1


patients with T2DM, future studies should include a test battery that at least covers the domains of memory, information-processing speed and executive functions. In addition, domains that have not been examined extensively so far, such as perception, visuoconstruction and language, should receive more attention. To date, it is unclear at which ‘stage’ of T2DM cognitive impairments start to develop. The progression from normal glucose tolerance to T2DM is a gradual process in which insulin resistance plays a crucial role [39]. In conditions such as the ‘metabolic syndrome’ insulin resistance is clustered with other metabolic and vascular abnormalities (e.g. obesity, dyslipidemia, raised blood pressure, as well as prothrombotic and proinflammatory states) [39,40]. This syndrome predisposes to both atherosclerotic cardiovascular disease and T2DM, and may be considered a prediabetic condition [40,41]. The few studies that have addressed cognitive functioning in pre-diabetic conditions mostly used relatively crude outcome measures, such as the MMSE or a clinical diagnosis of dementia [42-45]. With this approach, more subtle forms of cognitive decline may have been missed. Despite these limitations, impaired glucose metabolism that did not fulfil the criteria for T2DM was found to be associated with impaired cognitive functioning in cross-sectional population based surveys in non-diabetic elderly individuals [42,43], though not invariably [44]. Other studies have provided evidence that clustering of cardiovascular risk factors in the metabolic syndrome increases the risk of dementia [45]. Based on these results, a picture emerges in which the development of cognitive impairments in patients with T2DM represents a continuum, with an onset in the pre-clinical stages of diabetes, and a gradual progression thereafter (Figure 1.1.1). This hypothesis needs to be confirmed, however, in studies using standardized neuropsychological tests in well-defined populations with different stages of impaired glucose metabolism.

Risk of dementia Prospective population-based studies show a twofold increased risk of incident dementia in patients with T2DM [7]. In the Rotterdam Study, for example, in which 6,370 elderly participants were studied prospectively, the relative risk of incident dementia in patients with T2DM was 1.9 (95% confidence interval [CI] 1.3-2.8) [46]. Similar results were observed in the Honolulu-Asia Aging Study (relative risk of dementia in T2DM 1.5 [95% CI 1.01-2.2]) [47]. Several studies have also assessed the relation between T2DM and dementia subtypes. A recent systematic review indicated that both the risk of Alzheimer’s disease (AD) and of vascular dementia (VaD) were increased in patients with diabetes (8 of 13 studies, 6 of 9 studies respectively) [7]. One might conclude from these observations that T2DM is associated with both Alzheimer type and vascular pathology in the brain. This issue is, however, still debated. The reliability of the clinical diagnostic criteria for AD and VaD is a key issue in this debate. Lack of sensitivity and specificity of diagnostic criteria may have considerable impact on the results of large population-based surveys, particularly in those that did not include neuroimaging data from all participants. Because T2DM is a well known risk factor for cerebrovascular disease, the risk of misclassifying dementia

16

Chapter 1.1

Brain imaging Ageing is associated with several changes on brain imaging, including loss of total brain volume (atrophy) [48], white-matter lesions [49] and (silent) brain infarcts [50]. These changes may form the structural basis of age-related cognitive decline and, ultimately, dementia.


may be even larger in patients with T2DM than in those without. Mixed dementia pathology may thus be an even more complex issue in patients with T2DM than in the population at large. Nevertheless, the association between T2DM and dementia is evident. Because diabetes-associated dementia may be at least partially preventable, it might be more pragmatic to try and identify potentially modifiable risk factors and underlying mechanisms than to focus primarily on dementia subtype issues.

Studies that assessed the association between T2DM and these age-related brain imaging abnormalities can roughly be divided in three categories. The first category includes studies with ‘non-selected’ samples from the general population, or casecontrol studies in which patients with T2DM, unselected for any particular pathology, have been compared with control participants. The second category includes cohorts of patients with established vascular disease. The third category includes patients that are recruited through neurological outpatient clinics (e.g. memory clinics). We focus on studies from the first category as these are most likely to provide information that is relevant to the general population of patients with T2DM. Although the number of such studies is small, modest cortical and subcortical atrophy and symptomatic or asymptomatic infarcts appear to be more common in patients with T2DM than in controls [51-55]. The relation between T2DM and white-matter lesions is less clear, but a modest increase in lesion load has been reported [55]. To date, there are only two studies that specifically addressed the relation between brain abnormalities and cognitive functioning in patients with T2DM [55,56]. Cognitive functioning within the T2DM group was related to white-matter lesions, atrophy and the presence of infarctions (analysis adjusted for age, sex, and estimated IQ) [55,56].

Determinants and mechanisms of impaired cognition and dementia T2DM is closely related to other risk factors for accelerated cognitive decline and dementia, such as hypertension and atherosclerotic vascular disease. These risk factors, in concert with socio-economic factors, T2DM-specific conditions and medication, and other co-morbidities (e.g. depression), could be important determinants of accelerated cognitive decline and the increased risk of dementia in patients with T2DM (Table 1.1.1). In the next section these determinants are discussed. Text box 1.1.1 and Figures 1.1.2 and 1.1.3 offer a theoretical framework in which the relation of these determinants to T2DM and cognitive decline can be viewed.

17

Chapter 1.1

T2DM, cognitive functioning and dementia Table 1.1.1 Possible determinants of cognitive dysfunction in T2DM Demographic factors

Vascular risk factors

T2DM-related factors

Genetic

Other

Socio-economic status

Hypertension

APOE genotype

Depression

Educational level

Dyslipidemia

Glycemic control (HbA1c)

Age

Obesity

Sex

Atherosclerosis

Ethnic background

Stroke

Hypoglycemia Duration of the disease

Lifestyle (e.g. smoking, diet)

Microvascular complications Insulin resistance Glucose-lowering treatment

Text box 1.1.1 Statistical associations and causality: concepts and definitions The association between a risk factor (being a variable with a significant association with a clinical outcome) and an outcome measure can be regarded from a purely statistical or a mechanistic perspective. From a statistical perspective, a risk factor can be classified as an independent or a dependent risk factor [74]. An independent risk factor is defined as a risk factor that remains its significant statistical association with the outcome measure when other established risk factors for the outcome are included in the statistical model. A dependent risk factor loses its statistical association with the outcome when other established risk factors for the outcome are included in the statistical model. As such, independence is determined by a specific statistical model and as such highly reliant on the set of established risk factors included in that model [74]. From a mechanistic perspective, a risk factor can be classified as causal or noncausal. This classification is based on insights in underlying pathophysiological mechanisms. Causality is therefore not defined statistically, but needs to be discerned from experimental studies [74]. A causal risk factor directly impacts the outcome measure. A noncausal risk factor is associated with a causal factor but does not have a causal relation with the outcome measure. However, by its association with a causal factor, a noncausal factor is indirectly associated with the outcome. Figure 1.1.2 shows three models through which the causality of the association between T2DM and cognitive decline can be viewed. The studies that have been reviewed in the first half of this paper provide little support for reverse causality (Model B): the prospective studies that show accelerated cognitive decline or an increased risk of dementia in patients with established T2DM refute this option. The issue whether the association between T2DM and cognitive decline is causal (Model C) or not (Model A) is, however, still debated. If one assumes T2DM to be causally related to cognitive decline, a particular factor ‘X’ that is associated with T2DM and/or cognitive decline, may play different roles in this causal relation (Figure 1.1.3) [75]. Factor X can be associated with T2DM and have an indirect, noncausal association with cognitive decline (Model A). Factor X can also have a causal relation with cognitive decline, independent of T2DM (Model B). In this case, X and T2DM have cumulative effects. Factor X can also be a modulating factor in the association between T2DM and cognitive decline (Model C). In this model, the impact of T2DM on cognition varies across levels of factor X, but factor X has no direct impact on cognition. Factor X and T2DM may also interact, in which case factor X has a direct causal relation with cognitive decline, but also modulates the association between T2DM and cognition (Model D). Finally, factor X may be a mediator in the association between T2DM and cognitive decline (Model E). In this model T2DM leads to factor X, which in turn leads to cognitive decline.

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Chapter 1.1

Y

Cognitive decline

T2DM B

T2DM

Cognitive decline

T2DM

Cognitive decline

C

A

X

Figure 1.1.2 Models of causality for the association between T2DM and cognitive decline. Model A shows a noncausal association between T2DM and cognitive decline, where both T2DM and cognitive decline are the consequence of a third factor ‘Y’. In this model T2DM is a noncausal factor for cognitive decline, that is indirectly associated with cognitive decline through its association with factor Y. Model B shows reverse causality, where T2DM is the consequence of cognitive decline. Model C shows T2DM as a causal factor for cognitive decline.

C

T2DM

B

X

X

Cognitive decline

+

/-

Cognitive decline

+

/-

Cognitive decline


A

T2DM D

X

Cognitive decline T2DM

T2DM E

T2DM

X

Cognitive decline

Figure 1.1.3 The role of risk factor ‘X’ in the causal relation between T2DM and cognitive decline. In model A risk factor X is an indirect causal factor by causing cognitive decline through T2DM. Model B shows that risk factor X has a cumulative effect on top of the effect of T2DM. In model C risk factor X is a modulating factor: the effect of T2DM on cognitive decline varies across levels of factor X. Model D shows interaction between the effects of risk factor X and T2DM on cognitive decline. Finally, in model E risk factor X mediates the association between T2DM and dementia.

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Chapter 1.1


Demographic factors Several demographic factors, such as socio-economic status, age and sex, are associated with both T2DM and cognitive dysfunction. For example, women with a lower socioeconomic status or a lower educational level have 20 to 60% increased odds of having T2DM [57]. In addition, the risk of cognitive decline and dementia is increased for persons with lower socio-economic status or educational level [58,59]. Factors such as gender and ethnic background also affect the incidence of vascular disease and vascular risk factors [60-62]. These demographic factors may therefore be important confounders in the association between T2DM and cognitive decline. Indeed, the majority of studies that were reviewed in the first section of this paper take these confounders into account. It is still unclear if demographic factors can modulate the impact of T2DM on cognition. Studies that specifically examined cognitive function in women [63] or men [64] with diabetes show essentially the same cognitive impairments. Also the relative risk of dementia does not appear to differ across study populations of patients with T2DM with different ethnic backgrounds [7]. In this respect, the effects of age deserve special attention, as T2DM is particularly common among older individuals. Also, age is an important risk factor for both cognitive decline and T2DM. The pattern of neuropsychological deficits in younger patients with T2DM, with mild impairments across the cognitive domains and the largest effects in the domains of verbal memory and information processing speed, resembles the pattern of cognitive decline seen in older persons without T2DM [65,66]. Age and T2DM may thus have cumulative effects on cognition, but age may also be a modulating factor. Both studies in patients with T2DM and in experimentally diabetic rodents [67] suggest that the effects of age and diabetes on cognition may indeed interact. Such an interaction would also be plausible from a mechanistic point of view; several of the mechanisms that are assumed to mediate the toxic effects of hyperglycemia on the brain, such as oxidative stress, the accumulation of advanced glycation end-products and microangiopathy are also implicated in brain ageing [68].

Vascular risk factors T2DM is associated with vascular risk factors (hypertension, obesity, dyslipidemia) and vascular disease (atherosclerosis, stroke). These factors are, in turn, associated with cognitive decline. Vascular disease and vascular risk factors may thus be considered as a ‘confounder’ in the association between T2DM and cognitive decline. In this view, T2DM as such would be a noncausal factor that is indirectly associated with cognitive decline through its association with vascular disease. An alternative view would be that the effects of T2DM on cognition are exclusively mediated through vascular disease. It is indeed likely that vascular disease can serve as both an independent risk factor and as a mediator in the association between T2DM and cognition. Thus far, studies on the role of vascular risk factors in the association between diabetes and impaired cognition have mainly focussed on hypertension. Detailed studies on potential confounding, mediating or modulating effects of dyslipidemia and obesity are lacking. In the Framingham study, both T2DM and hypertension were clear risk factors for poor cognitive performance [69], and the effects of T2DM and hypertension appeared

20

Chapter 1.1

T2DM-related factors T2DM-related factors, such as glycemic control, duration of the disease, microvascular complications and treatment modality may play a mediating role in the etiology of cognitive impairments. To date, however, the relation between these factors and cognitive functioning in patients with T2DM has not been examined in sufficient detail.


to interact. Some studies report cumulative effects of hypertension and T2DM [70], or suggest that the association between T2DM and impaired cognition is primarily due to confounding by vascular risk factors [71]. Other studies, however, do not confirm that hypertension is involved in the relation between T2DM and impaired cognition [16,27,72], or even report a decreased risk of dementia in persons with both T2DM and hypertension, relative to those with T2DM alone [73]. Thus, the role of hypertension in the relation between T2DM and cognitive decline needs to be further examined.

In general, longer duration of diabetes and worse glycemic control are associated with more and more severe microvascular end-organ complications both in type 1 diabetes mellitus (T1DM) and T2DM [76,77]. Studies in patients with T1DM indeed suggest that chronic exposure to hyperglycemia may have a negative impact on cognitive function [78]. Several studies in patients with T2DM report similar findings. Longer duration of T2DM was associated with a greater risk of cognitive impairment [27,69] and patients with screen-detected T2DM, who presumably have shorter exposure to hyperglycemia, had a slightly lower risk of developing dementia than people with a known history of T2DM [46,47]. In agreement, elevated HbA1c levels, which reflect chronic hyperglycemia, were found to be associated with impaired cognition in T2DM [55,72,79,80], but not invariably [81,82]. A number of studies suggest that cognitive dysfunction is partially reversible with improvement of glycemic control [83-86]. However, a randomized clinical trial on the effects of intensified glucoselowering therapy versus standard treatment is still lacking [87]. From a mechanistic point of view, there are several ways in which increased glucose levels may affect the brain. In general, toxic effects of high glucose levels at tissue level may be mediated through an enhanced flux of glucose through the so-called polyol and hexosamine pathways, disturbances of intracellular second messenger pathways, an imbalance in the generation and scavenging of reactive oxygen species, and by advanced glycation of important functional and structural proteins [88]. These processes may directly affect brain tissue but might also lead to microvascular changes in the brain [5]. Insulin resistance is another potential determinant of cognitive decline in T2DM. Hyperinsulinemia has been associated with an increased risk of AD in the general population [89]. The association between insulin resistance and hyperinsulinemia and cognitive decline in patients with T2DM is yet to be examined in detail. From a mechanistic point of view, disturbances of insulin metabolism may be linked to cognitive decline and dementia through disturbances of synaptic plasticity and cerebral amyloid and tau metabolism [90]. The treatment of diabetes is focused on maintaining normal glucose levels. Patients are initially treated with dietary restrictions and exercise to control hyperglycemia. In

21

Chapter 1.1


a later stage oral hypoglycemic drugs or insulin injections are added to this regimen. Hypoglycemia is a well-known complication of glucose-lowering therapy. Although severe hypoglycemic episodes are much less common in T2DM than in T1DM, such episodes may have detrimental effects on the brain. However, data on the impact of hypoglycemic episodes on cognition in T2DM are still lacking. In T1DM a recent meta-analysis provided no evidence for an association between the occurrence of hypoglycemic episodes and impaired cognition [78], despite the fact that small case series suggested that such an association might exist [91]. Glucose-lowering compounds, including insulin, might also have direct effects on the brain [5]. It is, however, difficult to disentangle the interplay between patient factors, which demand a particular therapy, potential direct effects of treatment on the brain, and indirect effects of treatment on the brain, though modulation of glucose levels. This complex interplay is clearly reflected in observations from the Rotterdam study, where patients receiving insulin treatment had the highest risk of developing dementia (OR 4.3 [95% CI 1.7-10.5]), oral glucose-lowering medication was associated with an intermediate risk (OR 2.4 [95% CI 1.4-4.1]) and the lowest risk was found in patients who received no drug treatment (OR 1.3 [95% CI 0.7-2.3]) [46].

Genetic factors Genetic predisposition also plays an important role in the association between T2DM, cognitive impairment and dementia, but thus far only the role of Apolipoprotein (APOE) has been examined. The presence of the APOE ε4 allele is a risk factor for the development of AD [92]. Patients with T2DM who carry the APOE ε4 allele appear to have a twofold increased risk of dementia compared to non-diabetic persons with either of these risk factors in isolation [47,93]. It is still unclear whether this increased risk represents cumulative effects or an interaction between the APOE genotype and T2DM.

Other factors A recent meta-analysis reported that patients with T2DM have a twofold increased risk of depression compared to non-diabetic persons [94]. The prevalence of major depressive disorder in patients with T2DM was estimated at 11% and depressive symptoms were observed in 31% of the patients. The relation between T2DM and depression is not well understood. Depressive symptoms may result from difficulty in coping with chronic disease. Alternatively, metabolic changes as a consequence of diabetes (disturbances in noradrenergic and serotonergic neurotransmitter systems in the brain, in the hypothalamic-pituitary axis, changes in cortisol levels) might also underlie depression [95-98]. Depression may even predispose to the development of T2DM [99]. Depression in itself is associated with memory dysfunction and slowing of mental speed [11]. The nature of the relation between depression, cognitive function, and T2DM has not been thoroughly examined. Co-morbid depression may be considered as a confounder in the association between T2DM and cognitive function, but the effects of depression and T2DM on cognition could also be cumulative, or interact. Alternatively, both depression and cognitive dysfunction might be the result of the same diabetes-related process.

22

Chapter 1.1

Conclusions and directions for further research It is now well-established that T2DM is associated with moderate impairments in cognitive functioning and an increased risk of dementia. Brain-imaging studies show increased age-related brain abnormalities in patients with T2DM compared to nondiabetic persons, which may form the structural basis for cognitive decline. Detailed epidemiological studies on risk factors for cognitive decline in patients with T2DM are scarce. These studies usually address the statistical (in)dependence of risk factors in the association between T2DM and cognitive decline rather than causality, which, from a mechanistic point of view, is more relevant.


Lifestyle factors, such as smoking and diet, are associated with both T2DM [100,101] and with cognitive decline and dementia [102,103]. Similar to demographic factors, such as sex and socio-economic status, these factors are potentially non-causal and confounding risk factors in the association between T2DM and cognitive decline. These factors are, however, modifiable, which may result in a decrease in T2DM prevalence and dementia.

The relative mild nature of the global cognitive impairments in patients with T2DM may not primarily call for large clinical intervention trials. However, as a group patients with T2DM perform worse than age-matched persons without T2DM, which increases the risk of more severe cognitive impairments and dementia. This increased risk of dementia clearly demands our attention. We need to be able to identify patients that have an increased risk of developing dementia, identify underlying mechanisms and potentially modifiable determinants, and assess the effects of treatments that are specifically aimed at these determinants. Further research on the association between T2DM and cognitive decline should focus on these goals.

23

Chapter 1.1

24


of digits of

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1.2


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Chapter 1.2


Outline of the thesis The studies that are reviewed in chapter 1.1 show that type 2 diabetes mellitus (T2DM) is associated with mild to moderate decrements in cognitive functioning. The general focus of this thesis is to further elucidate the course of development of cognitive dysfunctioning associated with T2DM and to examine the role of the exposure to vascular risk factors. T2DM develops in association with vascular risk factors, such as hypertension and obesity, each of which may affect cognitive functioning independently of diabetes. The first part of the thesis provides a systematic review of the impact of T2DM, hypertension, obesity and dyslipidemia on cognitive functioning (chapter 2) and on the risk of dementia (chapter 3). The second part of the thesis addresses the question in which stage of the T2DM cognitive decrements start to develop. The progression from normal glucose tolerance to T2DM is a gradual process in which insulin resistance plays a crucial role. In prediabetic stages, insulin resistance often co-occurs with the vascular risk factors that are examined in chapters 2 and 3. This cluster of risk factors is usually referred to as the ‘metabolic syndrome’. One may hypothesize that at least part of the cognitive decrements associated with T2DM also start to develop in these early stages. In chapter 4 this hypothesis is investigated by comparing the cognitive profiles of patients with T2DM with persons with the metabolic syndrome, who had a similar vascular risk factor profile but no diabetes, and control participants. Prolonged exposure to vascular risk factors is likely to play a role in the etiology of diabetes-related cognitive decrements, but traditional statistical models are inapt to analyze the effect of exposure to changing risk factor levels over time. In chapter 5 we tested the applicability of linear mixed models to examine the 10year time course of risk factors for increased intima-media thickness, as a measure of (pre)clinical atherosclerosis. In chapter 6 these models were then applied to neuropsychological data, to examine the effect of exposure to vascular risk factors in the preceding 16 years on present cognitive functioning in patients with T2DM. Vascular disease is one of the potential mechanisms in the relation between T2DM and cognitive dysfunctioning. In chapter 7 the association between albuminuria, which may be considered as a marker of microvascular disease in both T2DM as well as in the general population, and cognitive functioning is examined in patients with T2DM. The third part of this thesis is aimed at the further characterization of the neuropsy chological profile that is associated with T2DM by comparing cognitive functioning in older persons with T2DM with non-diabetic control participants by means of a detailed neuropsychological examination (chapter 8). In chapter 9 the use of the concepts ‘mild cognitive impairment’ (MCI) and ‘cognitive impairment, no dementia’ (CIND) in relation to cognition in T2DM is investigated. The rate of cognitive decline over time was examined by a 4-year follow-up study (chapter 10) of the patients and controls that were described in chapters 8 and 9.

26

Chapter 1.2 Outline of the thesis

The final part of the thesis is focused at the effect of age in the association between T2DM and cognition by addressing the impact of T2DM (chapter 11) and the metabolic syndrome (chapter 12) on cognitive functioning in persons over 85 years old. In chapter 13 the results presented in this thesis are discussed as well as directions for future research and implications for clinical care.

27

Chapter 1.2

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Type 2 diabetes mellitus, hypertension, dyslipidemia and obesity: A systematic comparison of their impact on cognition E van den Berg, RP Kloppenborg, RPC Kessels, LJ Kappelle, GJ Biessels

Biochimica et Biophysica Acta, 1792: 470-481, 2009

Chapter 2

Vascular risk factors and cognitive dysfunction

Abstract Vascular risk factors, such as type 2 diabetes mellitus, hypertension, dyslipidemia and obesity, have been associated with an increased risk of cognitive dysfunction, particularly in the elderly. The aim of this systematic review was to compare these risk factors with regard to the nature and magnitude of the associated cognitive decrements. Cross-sectional and longitudinal studies that assessed cognitive functioning in nondemented persons in relation to diabetes/impaired glucose metabolism (k=36), hypertension (k=24), dyslipidemia (k=7) and obesity (k=6) and that adjusted or matched for age, gender and education were included. When possible, effect sizes (Cohen’s d) were computed per cognitive domain. Diabetes and hypertension were clearly associated with cognitive decrements; the results for obesity and dyslipidemia were less consistent. Effect sizes were moderate (median ~ –0.3) for all risk factors. Decline was found in all cognitive domains, although the effects on cognitive speed, mental flexibility and memory were most consistent. Methodological aspects of included studies and implications of these findings are discussed.

30

Chapter 2

As the world’s population gets older, cognitive dysfunction will be an increasing burden for society and health care resources. Although age remains the main risk factor for cognitive decline and dementia, it is increasingly recognized that a substantial number of cases with dementia may be attributable to vascular risk factors (i.e. type 2 diabetes mellitus, hypertension, dyslipidemia, obesity [7,104-106]), and consequently these risk factors emerge as major targets for therapeutic intervention. Although vascular risk factors often co-occur and have shared consequences, such as atherosclerosis, there are also differences in their impact on different organ systems. Type 2 diabetes and hypertension, for example, are strongly associated with end-organ damage in the retina and kidney, through pathophysiological mechanisms that are at least in part specific to these conditions [107-110]. For obesity and dyslipidemia the association with retinal and kidney damage is less evident [111,112]. This raises the question whether the impact on the brain, in particular on cognitive functioning, is similar across these vascular risk factors. Longitudinal population-based studies that assess the risk of dementia in association with diabetes, hypertension, dyslipidemia and obesity show that each of these factors is associated with a relative risk of dementia of approximately 1.5 (systematic review: [113]). There are, however, also some differences between these risk factors, particularly with regard to the modulating effect of age at the time of exposure (e.g. [114,115]). Although dementia is obviously a highly relevant clinical end-point it should be regarded as a final stage of cerebral damage. Based on the observation that different risk factors convey a similar risk of dementia, one may not conclude that the initial damage associated with each factor is identical. This initial damage, which may be reflected in decrements in cognitive functioning short of dementia, is of particular interest from the viewpoints of pathophysiology and prevention. The aim of the present study is therefore to quantify and compare the profile and size of cognitive decrements associated with type 2 diabetes, hypertension, dyslipidemia, and obesity in non-demented persons.


Introduction

Materials and methods Identification of studies This systematic review aimed to include all published studies that examined cognitive functioning associated with type 2 diabetes mellitus or impaired glucose metabolism, hypertension, dyslipidemia or obesity and that met the following inclusion criteria: the study (1) was published after 1990, (2) had a population-based or case-control design, (3) matched or adjusted the exposed and the non-exposed groups for the basic confounders age, sex and educational level, (4) addressed at least two cognitive domains with validated neuropsychological tests or, if only one domain was examined, used at least two different tests on that domain. Studies that assessed cognitive functioning only with a global screening instrument, such as the Mini-Mental State Examination, or reported only a composite measure of cognition were not included. Studies that specifically involved patients with type 1 diabetes were also not included. Medline (1990 to March 2008) and bibliographies from included papers were used to

31

Chapter 2


identify relevant papers. The search was limited to papers that were written in English and concerned human participants. We used the search terms (‘diabetes’, ‘hyperglycemia’ or ‘glucose tolerance’), (‘hypertension’ or ‘blood pressure’), (‘dyslipidemia’, ‘hypercholesterolemia’, ‘cholesterol’, ‘high-density lipoprotein’, ‘low-density lipoprotein’ or ‘triglycerides’), (‘waist circumference’, ‘obesity’, ‘overweight’, ‘abdominal fat’ or ‘body-mass index’) in combination with (‘cognitive’ or ‘neuropsychological’) in full or truncated versions. Titles and abstracts were scanned and potentially eligible papers were collected in full-text versions. RPK and EvdB independently judged eligible papers according to the inclusion criteria. In case of disagreement a consensus judgment was made, together with GJB. This review focuses on cognitive dysfunction in the absence of dementia. However, only a subset of the papers that met our inclusion criteria specifically mentioned exclusion of demented subjects in their methods section. More often exclusion of subjects with dementia or other neurological or mental conditions was mentioned in more global terms. Tables 2.1a to 2.1d list the exclusion criteria for individual studies.

Included studies For diabetes/impaired glucose metabolism the search yielded 1,702 hits, 27 of which met our inclusion criteria for diabetes and 9 for impaired glucose metabolism. The search yielded 2,406 hits for hypertension (24 studies were included), 653 hits for dyslipidemia (7 studies were included) and 1,113 hits for obesity (6 studies were included). Papers that addressed more than one vascular risk factor were included in multiple risk factor sections in this review (e.g. [116-120]). When more than one paper reported on the same population, the paper with the largest sample size and/ or the most detailed information on that risk factor and/or cognitive functioning was included (e.g. [69,121], [117,122] or [17,116]).

Data extraction and analysis Data on study design, sample size, sex and baseline age were extracted from the studies and details were included in Tables 2.1a through 2.1d. When available, the proportion of participants with the risk factor (e.g. diabetes or hypertension), risk factors definitions, and the exclusion criteria of the different studies were extracted. Only studies with age-, sex-, and education-matched or -adjusted results were included. Additional adjustments are listed in the final column of Tables 2.1a through 2.1d. The included studies used variable domain classifications, which hampers comparison of the effects between studies. All test scores were therefore regrouped into the domains general intelligence, memory, processing speed, attention, cognitive flexibility, perception/ visuoconstruction and language [11] according to a predefined classification of tests per domain, as listed in Appendix 2.1. When available, means and SDs were extracted from the included studies and converted into Cohen’s d as an estimate for effect size [12]. Negative effect sizes indicate worse cognition in the group with the risk factor. Median effect sizes per cognitive domain are presented in Tables 2.2a through 2.2d. In neuropsychological studies, effect sizes 0.8 large [12].

32

Chapter 2

Risk factors in the included studies were mostly dichotomized (e.g., diabetes yes/no). In a minority of studies the risk factors were analyzed as continuous variables in statistical analyses. The majority of studies included both participants who were either treated or untreated for a particular risk factor. If data on untreated patients were available, these were included in the Tables.


The results of studies that did not present data that could be converted into effect sizes are presented in Table 2.2 by means of direction of effect (‘–’ meaning ‘elevated levels of risk factor are associated with worse cognition’, ‘+’ meaning ‘elevated levels of risk factor are associated with better cognition or decreased levels of risk factor are associated with worse cognition (inverse effects)’, ‘+/–’ meaning ‘both elevated and decreased levels of risk factor are associated with worse cognition (U- or J-shaped associations)’, ‘=’ meaning ‘no statistically significant association between risk factor and cognition’). Results from cross-sectional and longitudinal studies are presented separately. To obtain insight into the potential modifying role of age at the time of exposure the studies are listed according to age at baseline.

We did not perform a formal meta-analysis because of the heterogeneity of risk factor assessment and the variety of assessment procedures of cognitive functioning, study design (e.g. cross-sectional/longitudinal or case-control/population-based), and presentation of the analyses and results (e.g. risk factor presented dichotomously or as continuous variable, differences in adjustment for confounding variables).

Results Methodological aspects Despite the strict inclusion criteria, the studies included in this review differed substantially in design and outcome measures. Case-control studies generally provided limited information about participant selection and specific in- and exclusion criteria. Several studies specifically selected participants who were treated in outpatient clinics of hospitals, whereas other studies were population-based. There was also considerable variation in the extent to which co-morbid conditions (e.g. depression, stroke) and vascular risk factors other than the studied factor were dealt with. Large populationbased studies generally used less detailed measures of cognitive functioning, but often assessed possible confounding or interaction effects across different risk factors more rigorously. Ten studies on diabetes specifically excluded participants who had a stroke. For obesity, dyslipidemia and hypertension these numbers were 2, 3 and 13, respectively. Eight diabetes-studies specifically mentioned exclusion of persons who were demented (at baseline). For obesity, dyslipidemia and hypertension these numbers were 4, 2 and 6, respectively.

Cognitive functioning The methods of neuropsychological assessment differed markedly among the included studies, ranging from an evaluation limited to one or two cognitive domains to a comprehensive examination across all major cognitive domains. The three domains

33

34 174 1811 59 40

C-C C-C P C-C

Vanhanen et al. [43]

Brands et al. [128]

Elias et al. [69]

Reaven et al. [26]

13913

P P P P

Scott et al. [133]

Grodstein et al. [134]

Lindeman et al. [44]

Wahlin et al. [135]

915

P C-C


van Harten et al. [132]

504

P P

Desmond et al. [120]

Kilander et al. [130]

338

664

2374

1131

136

249

38

C-C C-C

Atiea et al. [15]

U’ren et al. [129]

83

76

P C-C

Cerhan et al. [116]

Cosway et al. [14]

1360

100

C-C P

Ryan et al. [22]

Van Boxtel et al. [127]

284

C-C C-C

Dey et al. [125]

56

n

Fuh et al. [126]

Cross-sectional

Diabetes

Design

9

28

3

16

68

20

15

12

50

50

49

10

68

42

50

11

3

50

25

50

% with risk factor

84

74

74

74

73

73

72

71

71

69

69

68

66

65

57

45-64

24-81

51

48

47

Age

20

ND

0

42

44

35

100

34

16

68

59

ND

48

43

41

45

51

27

0

63

% male

History, GT

GT

History

GT

History

History, GT

GT

History

History

History

History

History, GT

History

GT

History

History, GT

History

History

History, GT

History

Risk factor definition

Dementia, N/P comorbidity, MD

None

VD

Not specified

Stroke, dementia, N/P comorbidity

Dementia

Not specified

Stroke

Stroke, N/P comorbidity


Dementia, stroke, N/P comorbidity

Stroke, T1DM

Dementia, N/P comorbidity

Dementia

Stroke, N/P comorbidity, blindness

Stroke, N/P comorbidity, old age

Dementia, N/P comorbidity

N/P comorbidity

Stroke


Exclusion criteria

Table 2.1a Description of included studies for type 2 diabetes mellitus and impaired glucose metabolism

VD

DEP, ethnicity

BP, BMI, DEP, vitamin E, hormone therapy, quality of life

BP, BMI, DEP, estrogen use

BP

BP, VD, smoking, alcohol

ethnicity

Additional adjustment/ matchinga

Chapter 2 Vascular risk factors and cognitive dysfunction

P P P P

P P

Knopman et al. [17]

Fontbonne et al. [16]

Kanaya et al. [72]

Gregg et al. [27]

Hassing et al. [137]

van den Berg et al. [138]

C-C P P


Scott et al. [133]


P P P

Fontbonne et al. [16]

Kanaya et al. [72]


586

999

926

5647

664

1131

83

248

596

274

9679

999

926

10963

5647

14

25

11

12

26

16

27

27

16

13

7

12

6

12

5

73

70

65

~45

74

74

65

48

85

83

72

70

65

47-70

~45

37

40

40

72

ND

42

43

0

34

29

0

40

40

44

72

GT

GT

GT

GT

GT

GT

GT

GT

History, GT

History

History

History, GT

History, GT

History, GT

History, GT

Dementia

Not specified

MMSE88 cm for women

BMI ≥ 30 kg/m2

BMI ≥ 25 kg/m2


Stroke, dementia, VD

Stroke, dementia

Dementia

>65 years old

Dementia, N/P comorbidity, vision or hearing disability

N/P comorbidity, MD

Exclusion criteria

BP, T2DM, MD, alcohol, smoking

BP, T2DM, alcohol, perceived health

Smoking, alcohol

BP, VD, T2DM, MD, ethnicity, smoking, study site

DEP


a

All studies were age-, sex- and education-adjusted or -matched, additional adjustments are listed. P, population-based design; T2DM, type 2 diabetes; MMSE, MiniMental State Examination; BMI, Body-mass Index; BP, blood pressure (including systolic blood pressure, history of hypertension, use of antihypertensive medication); VD, vascular disease (including cerebrovascular disease, stroke, tia, cardiac disease); DEP, depression (including scores on the Beck Depression Inventory, use of antidepressive medication, measures of anxiety and stress); N/P comorbidity, neurological or psychiatric comorbidity (including epilepsy, Parkinson’s disease, malignancies in central nervous system, sensory of motor neuron disease, depression, psychoactive medication such as sedatives, anticonvulsants, substance abuse, mental retardation, head trauma); MD, metabolic disturbances (including hyperlipidemia, thyroid disease, renal failure, systemic disease).

P

Cournot et al. [142]

Longitudinal

P

Gunstad et al. [140]

Cross-sectional

Design

Table 2.1b Description of included studies for obesity


P

Dik et al. [118]

P P P P

Teunissen et al. [122]

Komulainen et al. [146]

de Frias et al. [147]

Reitz et al. [148]

1147

524

101

144

438

1183

4110

n

50

ND

ND

ND

ND

ND

ND

% with risk factor

76

67

64

57

49

75

37

Age

32

49

0

60

0

49

100

% male

Total cholesterol, HDL cholesterol, LDL cholesterol and triglycerides as continuous variables

Total cholesterol and triglycerides as continuous variables

HDL cholesterol 160/95 mmHg


Dementia, MD, antihypertensive medication

>65 years old

Sroke, T2DM

Stroke

Not specified

Not specified

None

Stroke, N/P comorbidity, old age


VD, N/P comorbidity, antihypertensive medication

Stroke, N/P comorbidity, MD, DM

Exclusion criteria

Smoking, alcohol

Fasting glucose

Ethnicity

VD, DEP, medication use, smoking, alcohol, perceived health

Ethnicity



P

P

Hebert et al. [163]

Paran et al. [164]

495

4284

847

186

1811

1702

10963

1814

502

392

529

717

3270

71

ND

ND

51

32

ND

32

ND

ND

15

64

5

19

77

74

71

68

68

55-88

47-70

53

50

47

46

39-59

30-59

28

38

59

100

ND

40

44

53

100

100

49

100

50

SBP ≥140 mmHg

Duplicate measurement, continuous variables

Duplicate measurement, continuous variables

≥160/90 mmHg or medication + tertiles of DBP

>160/95 mmHg

≥160/95 mmHg

≥140/90 mmHg or medication


DBP ≤70 mmHg

SBP ≥140 mmHg

≥140/90 mmHg + as continuous variables

SBP ≥140 mmHg throughout adult life



Not specified

Stroke, dementia, MD

None

Stroke, T1DM

Stroke

Stroke

Stroke, dementia

Not specified

VD


Not specified


‘Chronic conditions’ (unspecified)

Ethnicity

Antihypertensive medication, DEP, alcohol, smoking

MD, smoking, alcohol

DBP, antihypertensive medication, VD, smoking, alcohol

Alcohol, smoking

Ethnicity, psychoactive medication

Stroke

BMI, DEP, alcohol, smoking

DEP, VD, antihypertensive medication

Ethnicity

a


All sstudies were age-, sex- and education-adjusted or -matched, additional adjustments are listed. C-C, case-control design; P, population-based design; DM, diabetes mellitus; SBP, systolic blood pressure; DBP, diastolic blood pressure; VD, vascular disease (including cerebrovascular disease, stroke, tia, cardiac disease); DEP, depression (including scores on the Beck Depression Inventory, use of antidepressive medication); N/P comorbidity, neurological or psychiatric comorbidity (including epilepsy, Parkinson’s disease, malignancies in central nervous system, sensory of motor neuron disease, depression, psychoactive medication such as sedatives, anticonvulsants, substance abuse, mental retardation, head trauma); MD, metabolic disturbances (including hyperlipidemia, thyroid disease, renal failure, systemic disease).

P

Waldstein et al. [162]

P

Knopman et al. [17]

P

P

Wolf et al. [119]

Reinprecht et al. [161]

P


P

P

Swan et al. [159]

P

P

Elias et al. [158]

Elias et al. [121]

P

Swan et al. [157]

Elias et al. [69]

P

Pavlik et al. [156]

Longitudinal

Chapter 2

39

Chapter 2


that were assessed in most studies were memory, processing speed and cognitive flexibility. Memory function was usually assessed by means of a verbal memory test where participants had to recall a list of unrelated words that was presented to them repeatedly (Rey Auditory Verbal Learning Test [123]) or had to recall a short paragraph (Wechsler Memory Scale – Logical Memory [124]). Generally, participants were asked to recall the words or the text immediately (immediate recall) and/or after a delay period of 20 to 30 minutes. Visuospatial memory was assessed in only a minority (65) showed somewhat larger effect sizes than studies with younger populations. Six studies adjusted their results for the effects of other vascular risk factors [27,69,132-135]. Analyses with or without these adjustments generally showed similar results. Eight included studies [16,43,44,72,126,133,136,139] reported on the association between impaired glucose metabolism (IGM) short of diabetes and cognitive functioning (Table

40

Chapter 2

IGM was associated with statistically significant worsening of cognitive performance in 1 out of 4 cross-sectional and none out of 4 longitudinal studies. Effect sizes across the different domains ranged from –1.4 to 0.2, with a median effect size of –0.1. Interestingly, two studies showed opposing effects. One cross-sectional study [126] showed that IGT participants tended to perform better than control participants and another [133] showed that IGT participants performed worse than both the control group and the T2DM patients. Only one study adjusted the result for other vascular risk factors [133]. The results from this study did not differ from the results of other studies.


2.1a). Two out of 4 cross-sectional studies had a case-control design. All populationbased studies used an oral glucose tolerance test (OGTT) or fasting blood glucose to define impaired glucose metabolism (impaired fasting glucose (IFG): >6.1 but ≤7.0 mmol/l or impaired glucose tolerance (IGT): 2h glucose >7.8 but 65 years). One late life study actually reported an inverted U-shaped association showing that both low and high BMI was associated with worse cognition [141]. Three studies adjusted their results for the effects of other vascular risk factors [141-143]. Analyses with or without these adjustments generally showed similar results.

Dyslipidemia Seven studies [118,122,144-148] that assessed the association between dyslipidemia and cognitive functioning were included (Table 2.1c), all were population-based. Studies on dyslipidemia mostly assessed serum cholesterol levels (6 studies). Several studies also measured triglycerides, HDL-cholesterol and LDL-cholesterol. Results were either

41

42

..

..

..


Wahlin et al. [135]

–


Grodstein et al. [134]

–0.8*

Desmond et al. [120]

..

–2.3*

U’ren et al. [129]

Scott et al. [133]

–0.4

Atiea et al. [15]

..

–0.1

Reaven et al. [26]

..

–

Elias et al. [69]

van Harten et al. [132]

–0.2

Brands et al. [128]


–0.1

..

..

Cerhan et al. [116]


..

Cosway et al. [14]

–0.3

–0.4

Ryan et al. [22]

Van Boxtel et al. [127]

–0.2*

–0.1

–0.2

=

–0.4

0

–

–0.3

–1.2*

–0.4

–0.7*

–*

–0.3*

–0.7*

–0.1

–*

–*

–0.2

–

..

Fuh et al. [126]

–*

Memory

Dey et al. [125]

Cross-sectional

Diabetes

General intelligence

..

0

..

..

–0.4*

–0.4*

–

..

–0.6

–0.2

–0.7*

..

–0.4*

–1.4*

–0.4

–*

–*

–0.4*

–0.2

..

Processing speed

..

..

..

..

..

..

..

–0.1

–1.9*

–0.5

..

..

–0.4*

–1.4*

..

..

–*

–0.6

..

–*

Attention

–0.3*

–0.1

–0.2

=

–0.4*

–0.2

–

..

–0.3

–0.7

–0.9*

–

–0.3*

–0.6*

–0.3

–*

–*

–0.3

–0.2

–

Cognitive flexibility

..

–0.1

..

..

..

..

–

–0.5*

..

..

..

–

–0.2

–0.7

..

..

..

–0.4

..

..

Perception/ construction

..

..

..

..

..

..

..

–0.4

..

..

..

..

..

..

..

..

..

..

..

–

Language

Table 2.2a Results of included studies for diabetes and impaired glucose metabolism

Largest between-group difference on least structured tests

T2DM was associated with a significantly lower composit z-score

No association between T2DM and cognitive functioning

T2DM was associated with a significantly lower composit z-score

Hypertensive T2DM patients were at greatest risk of cognitive impairment (