Accelerated Progression From Mild Cognitive Impairment to Dementia in People With Diabetes

Data were derived from the Kungsholmen Project, which was a population-based prospective cohort study on aging and dementia, including all registered inhabitants who were age ≥75 years and living in the Kungsholmen district of central Stockholm, Sweden, in 1987 (21,22). By means of a two-phase survey, among the 1,700 participants at baseline (1987–1989), two cohorts (a cognitively intact cohort and an MCI cohort) were identified. The two cohorts were followed for 9 years (until 1997–1998) to detect incident dementia and MCI cases.

The cognitively intact cohort consisted of 1,098 individuals after excluding 225 persons who were clinically diagnosed with prevalent dementia (using Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition [DSM-III-R] criteria) (23), 31 subjects with very low global cognitive status in the absence of a dementia diagnosis, and 9 with unknown educational level. An additional 337 subjects who were identified as having prevalent MCI (14,24) constituted the MCI cohort. Of the 1,098 cognitively intact individuals, 135 dropped out at the first follow-up examination resulting in 963 participants.

Of the 337 subjects with MCI, 35 refused to participate in the first follow-up examination or had moved, leaving 302 persons for the MCI cohort. This cohort included 120 aMCI subjects who had memory complaints and objective episodic memory impairment (14,24) and 182 oCIND subjects who had significant impairment in global cognitive performance, as defined in a previous report (15).

During the 9-year follow-up, three clinical examinations were carried out at an average interval of 3 years. Throughout the follow-up period, in the cognitively intact cohort, 357 people died and 52 dropped out. In the MCI cohort, 101 individuals died, and 13 were dropouts. Figure 1 shows the details of a flowchart of the study population from baseline to the third follow-up examination (1987–1989 to 1997–1998).

Medical records and death certificates were available for all participants who died during the follow-up. Informed consent was received from participants or from informants when the person was cognitively impaired. The Ethics Committee at Karolinska Institutet approved all phases of the Kungsholmen Project.

Global cognitive functioning was assessed with the Mini-Mental State Examination (MMSE), and subjective memory problems were evaluated by questioning the subjects and close informants. Data on age, sex, and education were collected from subjects at baseline following standardized protocols (22,25). Education was measured as the maximum years of formal schooling, and was dichotomized (≥8 vs. <8 years) based on results from a previous study (26). Weight and height were measured with a standard scale in light clothing and with no shoes. BMI was calculated as weight (kg) divided by height (m) squared. Arterial blood pressure (i.e., systolic Korotkoff phase I and diastolic phase V) was measured on the right arm by nurses, with the subject placed in a sitting position after a 5-min rest. Information on medical history was taken for all participants from the inpatient registry system, which encompasses all hospitals in Stockholm from 1969 onward. The International Classification of Disease, 8th revision (ICD-8) and the ICD-9th revisions (ICD-9) were used in the registry system until 1997. Medical conditions derived from the inpatient register database included ischemic heart disease (ICD-8, ICD-9, codes 410–414), heart failure or left ventricular failure or other myocardial insufficiency (ICD-8. codes 427 and 428; ICD-9, code 428.x), atrial fibrillation (ICD-8 code 427.9; ICD-9 code 427), stroke (ICD-8, ICD-9, codes 430–438), hypertension (ICD-8 codes 400–404; ICD-9 codes 401–405), and diabetes (ICD-8, ICD-9. code 250). Information on medical drug use for the 2 weeks prior to the baseline interview was collected from the subjects. Drugs were coded according to the Anatomical Therapeutic Chemical (ATC) Classification System (27). Hypoglycemic drugs included hypoglycemic medications or insulin injection (ATC code A10). Blood pressure lowering drugs were defined as all medicines potentially used for lowering blood pressure (ATC codes C02, C03, and C07). Genomic DNA was prepared from peripheral blood samples that were taken at baseline, and APOE allelic status was determined following a standard procedure (28).

Blood samples were taken at baseline survey and at each follow-up examination. Random (nonfasting) blood glucose was measured using a glucose oxidase procedure at baseline and follow-ups. Diabetes was identified by clinical examination and through the inpatient register system, use of hypoglycemic drugs, and random blood glucose level ≥11.0 mmol/l (19,29). Pre-diabetes was considered to be present if random blood glucose level was 7.8–11.0 mmol/l in diabetes-free participants (5,29).

People with MCI included all nondemented participants who fulfilled aMCI or oCIND criteria. Amnestic MCI is characterized by memory deficits, and was defined according to standard criteria (24,30) and operationalized as follows (15): 1) absence of dementia; 2) normal general cognitive function: absence of oCIND; 3) memory complaints: self- or informant-reported memory problems; 4) objective memory impairment: scoring 1.5 SD below age- and education-adjusted mean in a verbal episodic memory test (free recall of rapidly presented random words) (31); and 5) normal activities of daily living (ADL): no impairment in the Katz ADL scale. A diagnosis of oCIND represents global cognitive impairment, and was defined as having no dementia and scoring 1 SD or more below age- and education-adjusted means on the MMSE derived from the dementia-free sample at baseline (15,32). A diagnosis of oCIND was applied to subjects who were considered neither as normal nor as aMCI nor as demented. In the present study, aMCI and oCIND were mutually exclusive.

At baseline and follow-up, all participants underwent a comprehensive medical and cognitive assessment. Cognitive functions were tested by asking for facts of general knowledge and past personal information (semantic and episodic memory); by object naming and comprehension of commands and sentences (language); by problem solving and interpretation of proverbs (abstract thinking); by coping figures (visuospatial ability); and by calculation and solving mathematical problems (calculation). Dementia was diagnosed on the basis of clinical judgment following DSM-III-R criteria, in which a validated 3-step diagnostic procedure was used (22). Two examining physicians independently made a preliminary diagnosis, and in the case of disagreement, a third opinion was sought to reach a concordant diagnosis. The diagnosis of Alzheimer's disease (AD) required gradual onset, progressive deterioration, and lack of any other specific causes of dementia. The diagnosis of vascular dementia (VaD) required abrupt onset, stepwise deterioration, history of stroke, or focal deficits. The Hachinski scale was also used to support the differential diagnosis between AD and VaD (33). The diagnostic criteria for AD and VaD were equivalent to probable AD according to the National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) criteria (34), and to the National Institute of Neurological Disorders and Stroke Association Internationale pour la Recherche et l'Enseignement en Neurosciences (NINDS-AIREN) criteria (35). For deceased participants, the diagnosis of dementia and its subtypes was made by two physicians by reviewing the medical records and death certificates.

The baseline characteristics of people with diabetes and pre-diabetes and participants free from these conditions were compared using χ² tests for categorical variables and one-way ANOVAs for continuous variables. For the cross-sectional data at baseline, logistic regression analyses were used to estimate the odds ratio (OR) and 95% confidence intervals (CIs) of MCI, aMCI, and oCIND separately in relation to diabetes and pre-diabetes in the dementia-free participants.

The incidence rates were calculated as the number of events occurring during the entire follow-up period divided by person-years of follow-up standardized by age, sex, and education. Cox proportional hazards models were used to estimate the hazard ratios (HRs) and 95% CIs of dementia, AD, and MCI in relation to diabetes and pre-diabetes. Diabetes and pre-diabetes were modeled as separate and combined groups in the analyses. For nondemented subjects in the MCI cohort and non-MCI participants in the cognitively intact cohort, the follow-up time was calculated from the date of baseline interview to the date of the last follow-up examination or death. For the demented and MCI cases, the follow-up time was estimated as the full time during which the subjects were free of dementia or MCI plus half of the follow-up time during which dementia or MCI developed.

The proportional hazards assumption was confirmed by graphs and tests based on Schoenfeld residuals. Age, sex, education, baseline MMSE score, BMI, APOE genotype, and vascular disorders (i.e., heart disease, stroke, antihypertensive drug use, and blood pressure) were considered as potential confounders. As diabetes and pre-diabetes are related to elevated mortality, we also adjusted for survival status at follow-up (20). All dementia, AD, MCI, aMCI, oCIND, and death were used as separate outcomes in the Cox regression analyses. The Kaplan-Meier survival analysis was used to compare the cumulative probability of events among subjects in different groups. In secondary analyses, we modeled diabetes and pre-diabetes as time-dependent covariates. The statistical analyses were performed using Stata SE 10 for Windows (StataCorp, College Station, TX).

Among the 1,435 dementia-free participants at baseline, 337 were detected as MCI cases, including 131 aMCI and 206 oCIND. Compared with non-MCI subjects, people with MCI were older (OR 0.94, [95% CI 0.89–0.99, P = 0.015]), and had a lower level of education (<8 vs. ≥8 years, OR 2.13 [95% CI 1.35–3.38]) and MMSE score (OR 0.36 [95% CI 0.29–0.46]), and higher proportion of APOE ε4 carriers (OR 1.91 [95% CI 1.15–3.15]). The two groups showed no significant differences in terms of sex, stroke, heart disease, and blood pressure. Logistic regression analyses were performed to assess the cross-sectional relationship between diabetes and MCI based on the dementia-free subjects (n = 1,435). The multi-adjusted ORs related to diabetes or pre-diabetes were 1.32 (95% CI 0.82–1.31) for overall MCI, 1.12 (95% CI 0.67–1.20) for aMCI, and 1.03 (95% CI 0.57–1.23) for oCIND.

Of the 1,435 individuals who were initially identified as free of dementia at baseline, 170 subjects were lost to the first follow-up (Fig. 1). Compared with participants, dropouts were younger, but the two groups had no significant differences in other features. Multiple logistic regression analysis showed that being a dropout had ORs of 0.94 (95% CI 0.91–0.98) for old age, 1.26 (95% CI 0.84–1.87) for female sex, 1.24 (95% CI 0.89–1.73) for low education, 1.02 (95% CI 0.94–1.09) for a lower score on MMSE (<24 vs. ≥24), 0.35 (95% CI 0.28–1.06) for diabetes, 0.69 (95% CI 0.47–1.09) for heart disease, and 0.66 (95% CI 0.45–1.08) for stroke.

Of the 1,265 nondemented participants, 963 were cognitively intact and 302 had MCI, which constituted the two cohorts for longitudinal analyses. In the cognitively intact cohort, 56 subjects (5.8%) had diabetes, and 30 (3.1%) had pre-diabetes (Table 1). In the MCI cohort, 18 (6.0%) subjects had diabetes, and 16 (5.3%) were ascertained as having pre-diabetes. Among the 34 MCI subjects with diabetes or pre-diabetes, 27 (79.4%) were classified as oCIND, and 7 (20.6%) had aMCI (Table 2).

In the cognitively intact cohort, during the 9-year follow-up (4,656 person-years; mean per person = 4.8 years; maximum = 10.5 years), 182 participants developed MCI, including 42 aMCI and 140 oCIND. In addition, 212 were diagnosed with dementia, including 150 AD and 26 VaD. Table 3 shows the incidence rate standardized by age, sex, and education, and multi-adjusted HRs of MCI related to diabetes and pre-diabetes. We found no statistically significant association of either diabetes or pre-diabetes with incident MCI and its subgroups, whereas diabetes and pre-diabetes were significantly related to an increased risk of incident dementia. This association was present even when adjusting for several potential confounders, including APOE and vascular disorders. No interaction with APOE genotype or other variables was obtained.

In the MCI cohort, during the same period (1,092 person-years; mean per person = 3.6 years; maximum = 10.3 years), 155 subjects developed dementia, including 125 AD and 4 VaD. Using either standard or time-dependent Cox models, we found that diabetes and pre-diabetes were associated with an increased risk of developing dementia and AD in people with MCI after controlling for possible confounders, including APOE and vascular disorders (Table 4). Of the 125 AD subjects, 57 had aMCI and 68 had oCIND at baseline. We further performed stratified analysis according to MCI subgroups. Diabetes and pre-diabetes substantially increased the risk of progression from oCIND to dementia (HR 4.31 [95% CI 1.97–9.42]), but not from aMCI (HR 2.24 [95% CI 0.75–6.71]). However, the statistical power was limited for these stratified analyses because of the small number of people in each subgroup of MCI.

Kaplan-Meier survival analysis in people with MCI showed that the median time from baseline to dementia occurrence was 1.83 years (95% CI 2.44–4.24) in people with diabetes or pre-diabetes, and 5.01 years (95% CI 5.15–6.19) in people without such conditions. Thus, diabetes or pre-diabetes accelerated the progression from MCI to dementia by an average of 3.18 years (Fig. 2).

Similar results were obtained when we used only the incident MCI cohort that was identified at the first follow-up examination (n = 94, of whom 36 developed dementia during the next 6-year follow-up), and when we repeated the analyses among participants who survived until the time when dementia status was determined (n = 170, 136 dementia and 115 AD). Further, we performed the analyses by leaving out the participants with missing values of APOE genotype or BMI, which produced results that were the same as those from the initial analysis. Finally, in the MCI cohort, among the 34 people with either diabetes or pre-diabetes, 18 (52.9%) developed dementia and 16 (47.1%) died during the 9-year follow-up period. Diabetes and pre-diabetes were significantly associated with elevated mortality (HR 1.75 [95% CI 1.17–2.60]) after adjustment for age, sex, education, baseline MMSE score, BMI, APOE genotype, and vascular disorders.

The incidence of dementia is increased in patients with diabetes by 50–100% compared with people without diabetes, as shown by several reports, including those from our group (2). We are now able to extend these findings by showing that diabetes and pre-diabetes increase the risk of conversion from MCI to dementia. In this large longitudinal study of elderly adults, we found that 1) diabetes and pre-diabetes substantially accelerate the progression from MCI to dementia; 2) the risk effect of pre-diabetes on the progression from MCI to dementia appears stronger than diabetes; 3) diabetes and pre-diabetes anticipate dementia occurrence by more than 3 years; and 4) we confirm an increased risk of dementia, but not of MCI, in subjects with diabetes or pre-diabetes.

To date, Italian (10) and French (17) population-based longitudinal studies have examined the role of vascular risk factors, including diabetes, in the progression of MCI to dementia, and failed to find an association. There are several reasons for the discrepant findings. First, as pre-diabetes was not assessed in these two studies, subjects with this condition were included in the nondiabetes group, which might have diluted the effect of diabetes on dementia risk due to the strong influence of pre-diabetes on the progression from MCI to dementia, as shown in our report. Second, in the two studies, diabetes was identified based on fasting blood glucose ≥7.2 and ≥7.8 mmol/l, respectively, which are higher than the WHO criteria of 7.0 mmol/l (29). Finally, in both studies, the follow-up time was only 3.5 to 4 years, and the populations were younger than our cohort. As a result, the statistical power of the two studies may be limited because of the small number of incident dementia cases.

Findings from brain imaging and neuropathologic studies support the notion that the increased risk of cognitive decline and dementia in elderly people with diabetes reflects a dual pathologic process involving both cerebrovascular damage and neurodegenerative changes (36,–38). In addition to vascular pathways, several possible pathophysiologic mechanisms, including hyperglyceamia, insulin resistance, oxidative stress, advanced glycation end products, and inflammatory cytokines, may explain the effect of glucose deregulation on dementia risk. Recent genetic studies have found that chromosome 10 contains the genes for both late-onset AD and type 2 diabetes (39). Interestingly, a clinicopathologic study suggested that there may be a shared predisposition for developing amyloid in both the pancreas and the brain (40). All these mechanisms may explain the accelerated progression from MCI to dementia observed in this study. In addition, in subjects with MCI, cognitive deficits may affect the ability to manage complex behaviors such as those required for diabetes self-care (41), which may lead to a vicious circle. Therefore, an additional increased risk of developing dementia resulting from diabetes can be expected in people with MCI.

The stronger effect of pre-diabetes than diabetes on the conversion from MCI to dementia may be caused by the high glycemic level in pre-diabetes that is a commonly ignored condition. In our study, about 30% of patients with diabetes had normal random blood glucose level by hypoglycemic treatment and dietary control; effective glycemic control may reduce the risk of dementia in people with diabetes (20). Further, insulin resistance (hyperinsulinemia without hyperglycemia) is stronger in people with pre-diabetes than those with frank diabetes (42).

A number of studies that evaluated the cognitive function in patients with diabetes or pre-diabetes have shown that poor glucose regulation is associated with global cognitive decline, with impaired verbal memory in particular, but the evidence for deficits in other cognitive domains is weak (43). However, a recent prospective study suggested that diabetes-related cognitive deficits and MCI may represent different entities that do not necessarily affect the same domains (44). Another longitudinal study reported that diabetes may be related to psychomotor slowing, but not to deficits in other cognitive domains typically involved in MCI (45). Results from our study showed that diabetes and pre-diabetes were associated with MCI and its subgroups, neither cross sectionally nor longitudinally. This is in agreement with an Italian longitudinal study (10) and a case-control study from the Mayo Clinic (8). However, the latter study found an association of MCI with a longer duration and greater severity of diabetes, and Luchsinger et al. (9) reported a higher risk of both aMCI and oCIND in diabetic patients in a population with very high prevalence of diabetes. These findings suggest that only severe and longstanding diabetes may be related to MCI. Unfortunately, our study sample was too small to verify this hypothesis. An alternative explanation suggested by van den Berg (46) is the old age of the study population involved, where the lower cognitive level at baseline may have masked any additional impact of diabetes. In other words, the standard MCI criteria may not be sensitive enough to identify those people with global cognitive deficits due to diabetes (16). Finally, another possibility is that in very old people, diabetes and pre-diabetes may accelerate the process of dementia so rapidly that a possible association between diabetes and MCI cannot be detected when follow-up examinations are carried out with intervals longer than 1 year.

The main strengths of our study are the population-based cohort study, the long-term prospective study design, and the assessment of diabetes at baseline and each follow-up examination. However, some limitations should be noted. First, we used random blood glucose to define diabetes and pre-diabetes, which might result in an attenuation of the associations. However, the prevalence of diabetes in our study population (8.9%) is comparable with those reported from an elderly Swedish population (47). Second, as there are no specific recommended tools to diagnose MCI, the operationalization of the criteria may differ slightly from those in other studies. In addition, prevalent MCI cases were included in the MCI cohort, which might contain persons with long-term cognitive impairment that remains stable over time. However, similar results were obtained when the incident MCI cohort identified at first follow-up examination was used. Third, as the Kungsholmen Project is based on an elderly population (the mean age was 82 years at baseline), the dropouts from the screening phase to the third follow-up were mainly because of death (48). Diabetes, MCI, and dementia are all associated with elevated mortality (20,49), which may lead to an underestimation of the strength of the diabetes-dementia or diabetes-MCI association due to selective survival. Thus, caution is needed when generalizing our findings to younger populations. Finally, the diagnoses of dementia were made on a clinical basis. However, the clinical assessment for dementia was comprehensive and validated in a previous study (22). Although neuroimaging data may help detect vascular lesions in the brain, it is difficult to determine the significance of these lesions, as coexistence of AD-related pathologic changes and vascular lesions in the brain is very common in late life (50).

In summary, our results provide further support for the important role of diabetes and pre-diabetes in dementia, and highlight the need to control diabetes and detect pre-diabetes to prevent or postpone dementia in people with MCI. Our findings underline the importance of regularly monitoring cognitive function in people with diabetes and pre-diabetes. The lack of association between diabetes and the risk of MCI in our study suggests that diabetes may lead to dementia bypassing MCI or shortening the MCI phase in elderly people.

Research grants were received from the Swedish Council for Working Life and Social Research, the Swedish Research Council in Medicine, and Swedish Brain Power. This study was also supported in part by funds from the Loo and Hans Ostermans Foundation, the Foundation for Geriatric Diseases at Karolinska Institutet, the Gamla Tjänarinnor Foundation, the Bertil Stohnes Foundation, and Demensförbundet (Sweden).

No potential conflicts of interest relevant to this article were reported.

W.X. initiated and designed the study, performed the analysis, and wrote the first draft. L.F. supervised the study, and contributed to the results interpretation and revision of the text. B.W. and L.B. contributed to the acquirement of the initial data and revised the text. B.C., H.-X.W., and C.Q. helped with the data interpretation and revised the report.

The authors thank all the staff of the Kungsholmen Project for their collaboration in data collection and management.