Accelerated Progression from Mild Cognitive Impairment to Dementia in People with Diabetes

Weili Xu; Barbara Caracciolo; Hui-Xin Wang; Bengt Winblad; Lars Bäckman; Chengxuan Qiu; Laura Fratiglioni


Diabetes. 2010;59(11):2928-2935. 

In This Article

Research Design and Methods

Study Population

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.

Cognitively Intact Cohort

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.

MCI Cohort

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).

Figure 1.

Flowchart of the study population in the Kungsholmen Project.

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.

Data Collection

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]

Assessment of Diabetes and Pre-diabetes

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]

Definition of Mild Cognitive Impairment

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.

Diagnosis of Dementia

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.

Statistical Analysis

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).


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