Comorbid type 2 diabetes mellitus and hypertension exacerbates cognitive decline: evidence from a longitudinal study

Diabetes, hypertension, and cognitive decline Age and Ageing 2004; 33: 355–361 DOI: 10.1093/ageing/afh100 Age and Ageing Vol. 33 No. 4  British Ger...
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Diabetes, hypertension, and cognitive decline

Age and Ageing 2004; 33: 355–361 DOI: 10.1093/ageing/afh100

Age and Ageing Vol. 33 No. 4  British Geriatrics Society 2004; all rights reserved Published electronically 10 May 2004

Comorbid type 2 diabetes mellitus and hypertension exacerbates cognitive decline: evidence from a longitudinal study LINDA B. HASSING1, SCOTT M. HOFER2, SVEN E. NILSSON4, STIG BERG4, NANCY L. PEDERSEN5,6, GERALD MCCLEARN3, BOO JOHANSSON1 1

Department of Psychology, Göteborg University, Göteborg, Sweden Department of Human Development and Family Studies and 3Center for Developmental and Health Genetics, Pennsylvania State University, University Park, PA, USA 4 Institute of Gerontology, School of Health Sciences, Jönköping, Sweden 5 Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden 6 Department of Psychology, University of Southern California, Los Angeles, CA, USA 2

Address correspondence to: Linda B. Hassing, Department of Psychology, Göteborg University, Box 500, SE-405 30 Göteborg, Sweden. Fax: (+46) 31 773 4628. Email: [email protected]

Abstract Background: diabetes and hypertension are two highly prevalent diseases in the old population. They are highly related such that comorbidity is common. Objectives: to examine (i) the independent impact of the respective diseases on cognitive decline in very old age and (ii) the interactive impact of the two diseases on cognitive decline. Subjects: 258 individuals (mean age = 83 years), all non-demented at baseline. Of these, 128 individuals (non-cases) were free from diabetes and hypertension, 92 individuals had a diagnosis of hypertension, 16 had a type 2 diabetes mellitus diagnosis without hypertension, and 22 had comorbid diabetes and hypertension. Method: a population-based longitudinal study of ageing (The OCTO-Twin Study), including four measurement occasions 2 years apart. The Mini-Mental State Examination was used to measure general cognitive function. Data were analysed using SAS Proc Mixed multilevel modelling. Results: longitudinal trajectories indicated a steeper decline in cognitive function related to diabetes but not related to hypertension. However, the results indicated greatest cognitive decline among persons with comorbid diabetes and hypertension. Conclusions: it is concluded that comorbidity of diabetes and hypertension produce a pronounced cognitive decline. This finding emphasises the importance of prevention and treatment of those highly prevalent diseases in the old population. Keywords: hypertension, type 2 diabetes mellitus, cognitive decline, older age, longitudinal study, vascular disease

Introduction Type 2 diabetes mellitus and hypertension are two highly prevalent diseases among the old that are known to be risk factors for vascular disease. The prevalence of type 2 diabetes is estimated to range between 15% and 25% in the age group of 65 years and older [1]. The corresponding numbers for hypertension range between 50% and 70% [1–3]. Diabetes and hypertension are furthermore highly related such that comorbidity is common [1].

Extensive research on the effects of diabetes on cognitive function in old age has provided mixed findings [4, 5]. Although the majority of the studies have found negative effects on cognitive functioning related to diabetes [6–8], several studies have reported no relationship [9, 10]. The effects of hypertension on cognitive function have also been a subject for extensive research [11]. Most studies indicate that hypertension is negatively related to cognitive test performance [12–14], although some studies report no association [15]. Variation in findings concerning the consequences

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L. B. Hassing et al. of hypertension may be partially explained by age; thus, high blood pressure in young and middle age predicts lower cognitive performance whereas high blood pressure in old age has given mixed findings. A methodological issue that may be a source of these conflicting results is that comorbid diseases are often not considered. The most important condition that has to be screened for or controlled when examining older samples is dementia. The significance of comorbid dementia was demonstrated in a recent study where it was found that initially observed differences between people with diabetes and people without diabetes in cognitive performance were no longer significant when dementia was accounted for [8]. It is also important to control for dementia when examining the impact of hypertension on cognitive function in old age, given that blood pressure decreases following the development of dementia. Thus, given the association between dementia and diabetes, respectively dementia and hypertension, it is possible that one reason for conflicting results as to whether hypertension and diabetes are related to lower cognitive functioning is that some studies control for dementia whereas others do not. Little is known about the comorbid effect of diabetes and hypertension on cognitive function. For example, it is not known if it is more detrimental to have comorbid hypertension and diabetes than having only diabetes. Findings from the Framingham Heart Study indicated that comorbid diabetes and hypertension were associated with lower performance in tasks measuring visual organisation and memory [16]. Furthermore, Kuusisto and colleagues [17] found that people with comorbid hyperinsulinaemia

and hypertension performed worse on several cognitive tasks compared with normoinsulinaemic hypertensive people. The purpose of the present study was to examine the comorbid effects of type 2 diabetes and hypertension on cognitive decline across a 6-year interval in old individuals using the Mini-Mental State Examination [18].

Method Participants

The participants were drawn from the ongoing populationbased longitudinal study ‘Origins of variance in the Old-Old’ [19] which started in 1991. The full sample included 702 individuals at inclusion, in 351 like-sexed pairs, aged 80 years and older. The present study was based on the first four waves of the study and included a sample of individuals that survived the four waves, were not diagnosed with dementia at the first occasion (following DSM-III-R criteria), and had a MMSE score >23 at the first occasion. One hundred and twenty-eight individuals (non-cases) were free from diabetes and hypertension, 92 individuals had a diagnosis of hypertension, 16 had a type 2 diabetes mellitus diagnosis without hypertension, and 22 had comorbid diabetes and hypertension (see Table 1). The total sample size for analyses was 258. Procedure

The participants were investigated in their home. A complete testing session, including rest periods, took about 3.5 to 4.0 hours. The participants were assessed four times at 2-year intervals beginning in 1991.

Table 1. Baseline participant characteristics and diseases across groups Non-cases (n = 128)

Characteristics

Hypertension without diabetes (n = 92)

Diabetes without hypertension (n = 16)

Diabetes and hypertension (n = 22)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Years of age M ± SD

82.5 ± 2.3

82.5 ± 2.2

84.0 ± 3.9

83.1 ± 2.6

M ± SD

7.4 ± 2.3

7.0 ± 2.1

7.6 ± 1.2

7.4 ± 1.5

M ± SD

28.2 ± 1.6 67 59 12 14 13 9 7

28.0 ± 1.7 78 73 11 19 17 12 10

28.0 ± 1.4 50 63 13 25 13 0 6

28.3 ± 1.6 68 55 18 23 18 18 9

M ± SD

24.2 ± 3.4

25.2 ± 3.4

24.0 ± 3.6

25.5 ± 3.7

M ± SD

149.9 ± 20.4

172.5 ± 24.2

155.9 ± 16.0

171.6 ± 18.2

M ± SD

80.2 ± 11.5

87.3 ± 13.6

80.0 ± 9.5

84.8 ± 7.9

5.6 ± 4.6 0–15

7.1 ± 6.3 0–24

Years of education MMSE Sex (women) % Never smoked % Myocardial infarction % Angina pectoris % Congestive heart failure % Stroke % TIA % Body mass index (kg/m2) sBP (mm Hg) dBP (mm Hg) Years with diabetes M ± SD Range

– –

M = mean, SD = standard deviation, MMSE = Mini-Mental State Examination.

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– –

Diabetes, hypertension, and cognitive decline

Medical information During the interview the participants were asked for permission to review their medical records. Medical records for the period 1985–1998 were ordered from hospitals, outpatient clinics, district physicians, and primary health care centers, and multiple requests were made to secure the quality of information and to make sure that the records covered the entire time period and also contained a summary of diseases earlier in life. A physician (co-author Sven E. Nilsson) made a concurrent review of (i) medical records, including reported medical history; (ii) medicine use; and (iii) self-reported information about diseases. An independent 2nd opinion on classification performed by another physician in a 20% subsample produced only marginal amendment. Diagnoses were classified according to the ICD-10 [20]. The conditions of interest for subsequent analyses are hypertension (which was diagnosed in cases where either the records contained information of specific hypertension treatment, or in cases with more than one diastolic value of at least 95 mm Hg or systolic value higher than 160mmHg), type 2 diabetes mellitus (diagnosed using the 1980 WHO criteria when diagnostic level for venous whole blood glucose was 6.7 mmol/l [21]), congestive heart failure, myocardial infarction, angina pectoris, transient cerebral ischemic attack (TIA; that is defined as lasting shorter than 24 hours), stroke, and dementia. Cognitive assessment

The MMSE is a measure of global cognitive functioning. The task reflects orientation, memory, attention, ability to follow verbal and written commands, writing, and copying. The maximum score is 30, indicating normal cognitive functioning. Data analyses

Group differences in demographic and health conditions were analysed with one-way analyses of variance and Chi-square tests. Random coefficients modelling using SAS Proc Mixed was used to estimate individual-level change and predictors of change while accounting for the dependency associated with twin pair status. The multilevel model was characterised by a fixed part which contained average effects for the intercept (initial status) and slope (rate of change) and a random part which contained individual differences (variance) in the intercept, slope, and the within person residual. A three-level linear growth model was composed of a level-1 component of individual outcomes over time, a level-2 component which models individual fixed and random effects of initial status and change over time (person-level covariates can be added at this level), and the level-3 component which models variance associated with twin-pair status. Thus, a three-level structure was characterised by longitudinal measurements nested within individuals which were nested within groups (twin dyad). The syntax for these models is presented in Appendix A. The baseline model specifies a growth model with no level-2 covariates and was used to evaluate the fit of the growth model parameters. In this and subsequent models, zygosity was not modelled as a fixed effect because the

expectation was for no or random differences among MZ and DZ twins in terms of average slope and rate of change. Random effects were, however, estimated separately by zygosity because we expected higher intraclass correlations for MZs than for DZs. Finally, we permitted different estimates of the residual (level-one) variance for the two zygosity groups. Four nested models were estimated for MMSE as the outcome variable. A baseline model, without any covariates, was run to assess initial status and rate of change for the MMSE. Model A introduces the single covariate of hypertension status (0 = no, 1 = yes) adjusted for age, education, gender, smoking habit, angina, myocardial infarction, congestive heart failure, stroke, and TIA. Model B introduces the single covariate of diabetic status (0 = no, 1 = yes), adjusted for the same factors as in Model A. Finally, Model C introduces the interaction term of diabetes and hypertension, also adjusted for same factors as in Model A and B.

Results Participant characteristics at baseline

Participant characteristics are presented in Table 1. No significant differences between groups in participant characteristics were observed except in systolic and diastolic blood pressure (PS < 0.05) which were higher among the two groups with hypertension as compared with the normotensive groups. The two groups with hypertension did not differ in systolic and diastolic blood pressure (PS > 0.05). Further, the two groups with diabetes did not differ with respect to how many years they had had the diagnosis of diabetes (P > 0.05). Change in MMSE Scores across a 6-year Interval

Results from the growth curve modelling are reported in Table 2. The estimates of the average intercept (mean) and rate of change across persons (slope) in the Baseline model were significant. For example, the average person began with a score of 28.36 and declined by 0.33 points per 2-year interval. Model A allows us to explore whether variation in intercepts and slopes is related to hypertension status as a lone covariate of interest after adjusting for age, education, gender, smoking habit, angina, myocardial infarction, congestive heart failure, stroke, and TIA. Neither estimates are significant, indicating that hypertension alone is not a significant factor for change in the MMSE. Model B examines the effect of diabetes. As seen in Table 2, diabetes is significantly associated with rate of change in the MMSE such that those with diabetes decline by an additional 0.29 points per 2-year interval as compared to those without diabetes. However, diabetes was not a significant predictor of initial status in the MMSE. Finally, Model C examines the effect of having co-morbid diabetes and hypertension. This model shows that there is a significant interaction between diabetes and hypertension in rate of change in the MMSE such that those with both diseases decline additionally by 0.42 points per 2-year interval as compared to those free from both

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L. B. Hassing et al. Table 2. Parameter estimates (SE) of the fixed effects for cognitive change Baseline model (No covariate)

Model Aa (Hypertension)

Model Ba (Diabetes)

Model Ca (Diabetes × hypertension)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Level (SE)

Slope (SE)

Level (SE)

Slope (SE)

Level (SE)

Slope (SE)

Level (SE)

Slope (SE)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Mean Hypertension Diabetes Diabetes × hypertension

28.36 (0.11)* – – –

−0.33 (0.05)* – – –

31.52 (3.78)* −0.03 (0.21) – –

−0.25 (0.07)* −0.18 (0.10) – –

32.14 (3.77)* – 0.61 (0.30) –

−0.29 (0.06)* – −0.29 (0.14)* –

31.75 (3.73)* – – 0.92 (0.37)*

−0.30 (0.05)* – – −0.42 (0.18)*

Mean

a Adjusted for age, education, gender, smoking habit, angina, myocardial infarction, congestive heart failure, stroke, and TIA. *P < 0.05.

30

hypertension and diabetes (23%), although the difference between groups was not statistically significant.

28

Discussion

26 24 22 20 T1

T2

Non-cases Diabetes

T3

T4 Hypertension Diabetes + hypertension

Figure 1. Observed mean performance on the MMSE across groups and time.

hypertension and diabetes. The rate of decline in the MMSE related to hypertension and diabetes is portrayed in Figure 1. Survival, prevalent, and incident dementia across groups

As shown in Table 3 the overall survival rate (based on the initial sample of 702 individuals) between T1 and T4 was 52%. The lowest survival rate was observed in the diabetes groups (44% and 46%), however, there was no statistically significant difference between groups (P > 0.05). Prevalence of dementia at baseline across groups is reported in Table 3 (note that demented persons at baseline were excluded from the data analyses on MMSE). The highest prevalence of dementia at baseline was seen among the people with hypertension and diabetes (24%). Further, the highest incidence rate of dementia at T4 was seen among the people with

In the present study, we examined the effects of comorbid hypertension and diabetes on change in MMSE score across a 6-year interval. The participants were drawn from a longitudinal population-based study and were measured on four occasions. Individuals with dementia at baseline were excluded. The main findings showed that all groups had declined after the 6-year follow-up period. Further, differential cognitive change was observed between the groups reflecting the greatest decline among those with comorbid hypertension and diabetes. Our results showed that people with diabetes demonstrated greater cognitive change across the 6-year interval as compared with people without diabetes. This finding is in agreement with other longitudinal studies that report increased cognitive decline related to diabetes [6, 7] and an increased risk of dementia [22, 23]. On the other hand, the impact of hypertension on cognitive function was not statistically significant, although the hypertensives had a somewhat greater decline than the non-cases. A greater decline among the hypertensives would have been expected given the many findings showing this result [12–15, 24–26]. These findings may possibly be a result of the high age of our sample, as several investigations suggest that the negative effects associated with hypertension may vary with age such that greater effects are found among young samples as compared to old samples. For example, Waldstein [27] suggested that nonsignificant association between hypertension and cognitive function in old age might reflect selective attrition. Another possibility would be that early-onset hypertension confers greater risk for cognitive impairment [11]. Although hypertension alone was not related to significantly greater cognitive decline our results suggest that comorbid hypertension and diabetes is combined with

Table 3. Survival, prevalent, and incident dementia across groups Non-cases

Hypertension

Diabetes

Diabetes+hypertension

Total

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Survival until T4 Prevalent dementia at T1a Incident dementia between T1 and T4b a b

171/331 (52%) 51/331 (15%) 10/128 (8%)

135/251 (54%) 30/251 (12%) 12/92 (13%)

These individuals were excluded from this study. Based on the sample that met the criteria for inclusion in the data analyses (see Methods).

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29/52 (44%) 11/52 (21%) 3/16 (19%)

31/68 (46%) 16/68 (24%) 5/22 (23%)

366/702 (52%) 108/702 (15%) 30/258 (12%)

Diabetes, hypertension, and cognitive decline increased risk for cognitive impairment. These results are consistent with prior research [15–17]. When looking into the underlying mechanisms through which diabetes and hypertension interact it should be kept in mind that these conditions may be a part of a larger metabolic syndrome, including hyperglycaemia, hyperinsulinaemia and dyslipidaemia. Thus, several pathways for how these conditions may interact and cause cognitive impairment have been suggested [28]. For example, hyperglycaemia has been shown to be related to loss of cortical neurons as well as a decrease in acetylcholine synthesis and release in the brain of rats [29]. Dyslipidemiea as well as hyperinsulinaemia are related to arteriosclerosis, although it should be noted that hyperinsulinaemia is not always apparent in type 2 diabetes. Furthermore, hypertension is a known risk factor for cerebrovascular disease, lacunar brain infarct, and white matter lesion [30]. In our study we found that there was a higher prevalence of stroke among those with comorbid diabetes and hypertension as compared to people with diabetes without hypertension. This reflects increased vulnerability among those with both diabetes and hypertension. It is also if interest to note that this group had had diabetes for a longer period of time than those with diabetes only. Thus, it may be the case that the longer the period with diabetes, the greater the risk of hypertension and of cognitive impairment. When comparing the incidence rates of dementia across groups in our study we find the highest rate among people with comorbid diabetes and hypertension, followed by people with diabetes without hypertension. However, these figures are based on very small numbers and should therefore be treated cautiously. The main strength of the present study is the longitudinal design, which provides us with the opportunity to simultaneously explore the long-term effects of two risk factors of cognitive impairment. There is also an advantage in using a population-based sample, which minimises selection bias and increases generalisability. However, we need to be cautious when interpreting our results, as there are some limitations to our study. The first limitation is the small sample size. This is, however, a result of the high attrition rate, common for longitudinal studies of very old samples. Furthermore, the attrition rate is especially problematic when studying diseases that are associated with a greater mortality rate, such as diabetes. In our study the survival rate among people with diabetes was somewhat lower as compared to people without diabetes. Another limitation is that cognitive performance was only measured by a global measure that may be too insensitive to detect more subtle and differential change in various cognitive domains. To summarise, this study demonstrates that comorbid diabetes and hypertension further increases the risk of cognitive decline. Thus, it underlines the importance of prevention and treatment of these two common diseases.

Key points

• Hypertension in very old age is not independently related to cognitive decline.

• People with diabetes and hypertension are at a greater risk for cognitive decline than normotensive people with diabetes.

Acknowledgements The OCTO Twin Study is an ongoing longitudinal study conducted at the Institute of Gerontology, School of Health Sciences, Jönköping, Sweden, in collaboration with the Center for Developmental and Health Genetics at the Pennsylvania State University, USA and the Department of Medical Epidemiology and Biostatistics at the Karolinska Institute in Stockholm, Sweden. The authors want to thank RNs Lene Ahlbäck (1991–2001), Agneta Carlholt (1992–2002), Gunilla Hjalmarsson (1991–1993), Eva Georgsson (1993–1995), and Anna-Lena Wetterholm (1993–1994) who travelled throughout the country and examined the participants. There are no conflicts of interest in this study.

Funding This study is supported by a grant from the National Institute on Aging (NIA: AG 08861) of the National Institutes of Health, The Swedish Council for Working Life and Social Research, The Wenner-Gren Foundations, Wilhelm and Martina Lundgrens Foundation, Knut and Alice Wallenberg Foundation, and The Adlerbertska Foundation.

References 1. Fillenbaum G, Pieper C, Cohen H, Cornoni-Huntley J, Guralnik J. Comorbidity of five chronic health conditions in elderly community residents: determinants and impact on mortality. J Gerontol A Biol Sci Med Sci 2000; 55: M84–89. 2. Wolz M, Cutler J, Roccella EJ, Rohde F, Thom T, Burt V. Statement from the National High Blood Pressure Education Program: prevalence of hypertension. Am J Hypertens 2000; 13: 103–4. 3. The sixth report of the Joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure. Arch Intern Med 1997; 157: 2413–46. 4. Ryan CM, Geckle M. Why is learning and memory dysfunction in Type 2 diabetes limited to older adults? Diabetes/Metabolism Res Rev 2000; 16: 308–15. 5. Stewart R, Liolitsa D. Type 2 diabetes mellitus, cognitive impairment and dementia. Diabetic Med 1999; 16: 93–112. 6. Fontbonne A, Berr C, Ducimetiere P, Alperovitch A. Changes in cognitive abilities over a 4-year period are unfavorably affected in elderly diabetic subjects: results of the Epidemiology of Vascular Aging Study. Diabetes Care 2001; 24: 366–70. 7. Gregg EW, Yaffe K, Cauley JA et al. Is diabetes associated with cognitive impairment and cognitive decline among older women? Study of Osteoporotic Fractures Research Group. Arch Intern Med 2000; 160: 174–80. 8. Hassing LB, Johansson B, Pedersen NL, Nilsson SE, Berg S, McClearn G. Type 2 diabetes mellitus and cognitive performance in a population-based sample of the oldest old: Impact of comorbid dementia. Aging Neuropsychol Cognit 2003; 10: 99–107. 9. Bourdel-Marchasson I, Dubroca B, Manciet G, Decamps A, Emeriau JP, Dartigues JF. Prevalence of diabetes and effect on

359

L. B. Hassing et al. quality of life in older French living in the community: the PAQUID Epidemiological Survey. J Am Geriatr Soc 1997; 45: 295–301. 10. Breteler MM, Claus JJ, Grobbee DE, Hofman A. Cardiovascular disease and distribution of cognitive function in elderly people: the Rotterdam Study. Br Med J 1994; 308: 1604–8. 11. Waldstein SR. Health effects on cognitive aging. In Carstensen LL ed. The Aging Mind: Opportunities in Cognitive Research. Washington DC: National Academy Press, 2001. 12. Elias MF, Wolf PA, D’Agostino RB, Cobb J, White LR. Untreated blood pressure level is inversely related to cognitive functioning: the Framingham Study. Am J Epidemiol 1993; 138: 353–64. 13. Cervilla JA, Prince M, Joels S, Lovestone S, Mann A. Longterm predictors of cognitive outcome in a cohort of older people with hypertension. Br J Psychiatry 2000; 177: 66–71. 14. Glynn RJ, Beckett LA, Hebert LE, Morris MC, Scherr PA, Evans DA. Current and remote blood pressure and cognitive decline. JAMA 1999; 281: 438–45. 15. Posner HB, Tang MX, Luchsinger J, Lantigua R, Stern Y, Mayeus R. The relationship of hypertension in the elderly to AD, vascular dementia, and cognitive function. Neurology 2002; 58: 1175–81. 16. Elias PK, Elias MF, D’Agostino RB et al. NIDDM and blood pressure as risk factors for poor cognitive performance. The Framingham Study. Diabetes Care 1997; 20: 1388–95. 17. Kuusisto J, Koivisto K, Mykkanen L et al. Essential hypertension and cognitive function. The role of hyperinsulinemia. Hypertension 1993; 22: 771–9. 18. Folstein MF, Folstein SE, McHugh PR. ‘Mini-mental state’. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975; 12: 189–98. 19. McClearn GE, Johansson B, Berg S et al. Substantial genetic influence on cognitive abilities in twins 80 or more years old. Science 1997; 276: 560–3. 20. Nilsson SE, Johansson B, Berg S, Karlsson D, McClearn GE. A comparison of diagnosis capture from medical records, self-

360

reports, and drug registrations: a study in individuals 80 years and older. Aging Clin Exp Res 2002; 14: 178–84. 21. WHO Expert Committee on Diabetes Mellitus: second report. World Health Organ Tech Rep Ser 1980; 646: 1–80. 22. Ott A, Stolk RP, van Harskamp F, Pols HA, Hofman A, Breteler MM. Diabetes mellitus and the risk of dementia: The Rotterdam Study. Neurology 1999; 53: 1937–42. 23. Hassing LB, Johansson B, Nilsson SE et al. Diabetes mellitus is a risk factor for vascular dementia, but not for Alzheimer’s disease: A population-based study of the oldest old. Int Psychogeriatr 2002; 14: 239–48. 24. Blumenthal JA, Madden DJ, Pierce TW, Siegel WC, Appelbaum M. Hypertension affects neurobehavioral functioning. Psychosom Med 1993; 55: 44–50. 25. Kilander L, Nyman H, Boberg M, Hansson L, Lithell H. Hypertension is related to cognitive impairment: a 20-year follow up of 999 men. Hypertension 1998; 31: 780–6. 26. Wallace RB, Lemke JH, Morris MC, Goodenberger M, Kohout F, Hinrichs JV. Relationship of free-recall memory to hypertension in the elderly. The Iowa 65+ Rural Health Study. J Chronic Dis 1985; 38: 475–81. 27. Waldstein SR. Hypertension and neuropsychological function: a lifespan perspective. Exp Aging Res 1995; 21: 321–52. 28. Kumari M, Brunner E, Fuhrer R. Minireview: Mechanisms by which the matabolic syndrome and diabetes impair memory. J Gerontol A Biol Sci Med Sci 2000; 55: B228–232. 29. Welsh B, Wecker L. Effects of streptozotocin-induced diabetes on acetylcholine metabolism in rat brain. Neurochem Res 1991; 16: 453–60. 30. Breteler MM, van Swieten JC, Bots ML et al. Cerebral white matter lesions, vascular risk factors, and cognitive function in a population based study: the Rotterdam Study. Neurology 1994; 44: 1246–52.

Received 13 June 2003; accepted in revised form 29 December 2003

Diabetes, hypertension, and cognitive decline

Appendix A Baseline Model proc mixed method = ml noitprint covtest noclprint; class id id2; *where zyg = 1; model mmse = year0/s; random intercept/sub = id type = un group = zyg; *Level 3 Variance Component; random intercept year0/sub = id2 (id) type = un gcorr group = zyg; repeated/sub = id2 (id) group = zyg; title ‘MZ Twins: Stacked No covariates’; run;

Model A proc mixed method = ml noitprint covtest noclprint; class id id2; *where zyg = 1; model mmse = year0 age educ sex smok mi ap chf stke tia hyper hyper*year0/s; random intercept/sub = id type = un group = zyg; *Level 3 Variance Component; random intercept year0/sub = id2 (id) type = un gcorr group = zyg; repeated/sub = id2 (id) group = zyg; title ‘MZ Twins: Stacked fixed effects age, education, sex, smoking, miocardial infarction, angina pectoris, congestive heart failure, stroke, TIA, hypertension’; run;

Model B proc mixed method = ml noitprint covtest noclprint; class id id2; *where zyg = 1; model mmse = year0 age educ sex smok mi ap chf stke tia diab diab*year0/s; random intercept/sub = id type = un group = zyg; *Level 3 Variance Component; random intercept year0/sub = id2 (id) type = un gcorr group = zyg; repeated/sub = id2 (id) group = zyg; title ‘MZ Twins: Stacked fixed effects age, education, sex, smoking, miocardial infarction, angina pectoris, congestive heart failure, stroke, TIA, diabetes’; run; Model C proc mixed method = ml noitprint covtest noclprint; class id id2; *where zyg = 1; model mmse = year0 age educ sex smok mi ap chf stke tia diab*hyper diab*hyper*year0/s; random intercept/sub = id type = un group = zyg; *Level 3 Variance Component; random intercept year0/sub = id2 (id) type = un gcorr group = zyg; repeated/sub = id2 (id) group = zyg; title ‘MZ Twins: Stacked fixed effects age, education, sex, smoking, miocardial infarction, angina pectoris, congestive heart failure, stroke, TIA, diabetes and hypertension’; run;

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