Accumulating evidence suggests an association between coronary heart disease and risk for cognitive impairment or dementia, but no study has systematically reviewed this association. Therefore, we summarized the available evidence on the association between coronary heart disease and risk for cognitive impairment or dementia.
Medline, Embase, PsycINFO, and CINAHL were searched for all publications until 8th January 2016. Articles were included if they fulfilled the inclusion criteria: (1) myocardial infarction, angina pectoris or coronary heart disease (combination of both) as predictor variable; (2) cognition, cognitive impairment or dementia as outcome; (3) population-based study; (4) prospective (≥1 year follow-up), cross-sectional or case-control study design; (5) ≥100 participants; and (6) aged ≥45 years. Reference lists of publications and secondary literature were hand-searched for possible missing articles. Two reviewers independently screened all abstracts and extracted information from potential relevant full-text articles using a standardized data collection form. Study quality was assessed with the Newcastle-Ottawa Scale. We pooled estimates from the most fully adjusted model using random-effects meta-analysis.
We identified 6,132 abstracts, of which 24 studies were included. A meta-analysis of 10 prospective cohort studies showed that coronary heart disease was associated with increased risk of cognitive impairment or dementia (OR = 1.45, 95%CI = 1.21–1.74, p<0.001). Between-study heterogeneity was low (I2 = 25.7%, 95%CI = 0–64, p = 0.207). Similar significant associations were found in separate meta-analyses of prospective cohort studies for the individual predictors (myocardial infarction, angina pectoris). In contrast, meta-analyses of cross-sectional and case-control studies were inconclusive.
This meta-analysis suggests that coronary heart disease is prospectively associated with increased odds of developing cognitive impairment or dementia. Given the projected worldwide increase in the number of people affected by coronary heart disease and dementia, insight into causal mechanisms or common pathways underlying the heart-brain connection is needed.
Citation: Deckers K, Schievink SHJ, Rodriquez MMF, van Oostenbrugge RJ, van Boxtel MPJ, Verhey FRJ, et al. (2017) Coronary heart disease and risk for cognitive impairment or dementia: Systematic review and meta-analysis. PLoS ONE 12(9): e0184244. https://doi.org/10.1371/journal.pone.0184244
Editor: Stephen D. Ginsberg, Nathan S Kline Institute, UNITED STATES
Received: February 14, 2017; Accepted: August 21, 2017; Published: September 8, 2017
Copyright: © 2017 Deckers et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: Data are available from DataverseNL: http://hdl.handle.net/10411/EC8JX9.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Coronary heart disease (CHD) is the leading cause of death worldwide . An estimated 7.4 million people died from CHD in 2012 . CHD is a broad disease category and consists of several conditions with myocardial infarction (MI) and angina pectoris (AP) being the most prevalent ones. CHD affects the vascular system supplying the heart muscle due to build-up of atheromatous plaques that cover the lining of the coronary arteries .
At the same time, dementia is an important health problem due to increasing incidence rates and its impact on health and daily life . Major modifiable risk factors for cognitive impairment and dementia relate to or impact the vascular system including hypertension, smoking, obesity, diabetes, hypercholesterolemia and lack of physical exercise [5, 6]. Notably, these factors are also risk factors for CHD . While CHD is a candidate risk factor for dementia or cognitive impairment, the evidence base has not been established to a similar extent, yet . In a recent systematic review of the literature on modifiable risk factors, several studies on heart disease were identified, of which the majority reported a higher risk for cognitive impairment or dementia . Some other types of heart disease have been related to cognitive decline or dementia risk, too, with most substantial evidence for atrial fibrillation [9–11]. A meta-analysis of 7 prospective studies found that individuals with atrial fibrillation had a 36 percent increased risk of developing cognitive impairment or dementia . To date, no meta-analysis exists for major heart diseases such as MI and AP.
Therefore, the aim of the present study is to summarize the outcome of all available population-based studies investigating the relation between CHD, notably MI, and AP, and risk for cognitive impairment or dementia in a systematic review and meta-analysis.
Materials and methods
Data sources and searches
The literature search was conducted in Medline, Embase, PsycINFO, and CINAHL. The search string consisted of predictor-related terms (e.g. myocardial infarction, angina pectoris), outcome-related terms (e.g. dementia, Alzheimer, cognition), as well as some specific limitations (e.g. only studies in human, language restrictions). The complete search strategy is provided in S1 Appendix.
All publications until 8th January 2016 were included if they fulfilled the following eligibility criteria: 1) MI, AP, or a CHD variable that is a combination of MI and AP (e.g. ischemic heart disease (IHD)) as predictor variable; 2) cognition, cognitive impairment or dementia as outcome; 3) population-based study; 4) prospective (≥1 year follow-up), cross-sectional or case-control study design; 5) ≥100 participants; and 6) aged ≥45 years. Reference lists of publications and secondary literature (review articles, editorials, book chapters, etc.) were hand-searched for possible missing articles.
Data extraction and quality assessment
The selection process followed the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) and MOOSE (Meta-analysis Of Observational Studies in Epidemiology) guidelines (S2 and S3 Appendices) [12, 13]. Titles and abstracts were screened by two independent assessors (KD, MMFR) based on the abovementioned eligibility criteria. Next, full text articles of potentially relevant citations were scrutinized by two independent investigators (KD, MMFR). A standardized data collection form was used to extract information such as study design, study cohort, demographics, predictor variable, outcome, and effect estimate. In case of discrepancy, discussion with a third reviewer (SK) took place. Corresponding authors were contacted by e-mail if full-text articles were not available or information was missing (e.g. effect estimates, sample sizes, definition of CHD) or ambiguous (with maximum three reminders in case of non-response). The Newcastle-Ottawa Scale (NOS) was used to asses study quality . For cross-sectional studies, an adapted version of the NOS was applied (S4 Appendix).
Data synthesis and analysis
Studies qualifying for pooling in meta-analyses were analyzed with random effects models to estimate the pooled odds ratios (OR) and their 95% confidence intervals (CI). Estimates from the most fully adjusted model were used. Meta-analyses were conducted for each exposure separately, i.e. for MI, AP, and CHD. The latter included all studies that reported a risk estimate for MI, AP or a combination of MI and AP. In case a study reported risk estimates for multiple exposures the combination estimate (first choice) or the effect estimate with the smallest standard error (i.e. largest sample size; second choice) was chosen. Studies with overlapping study populations were only included if they used other study designs (e.g. cross-sectional and prospective). Heterogeneity among studies was assessed using the I2 statistic and the 95% CI for I2 was calculated using the non-central χ2 approach. Potential sources of heterogeneity (including mean age at baseline, mean follow-up duration, percentage of women, outcome measurement and study quality) were explored by meta-regression. The 95% prediction interval was estimated for each meta-analysis including at least 3 observational studies. This measure takes into account the between-study heterogeneity and provides an interval for the expected estimate of a future observational study and has been recommended to be standardly included in meta-analysis . Potential publication bias (i.e. small study effects) was assessed by visual inspection of funnel plots and Egger’s test. All tests were two-sided at an alpha-level of 0.05 and all analyses were done with Stata 13.1 (StataCorp, TX).
The search yielded 6,132 abstracts, of which 142 (2.3%) were included for full-text review. Of these, 119 were excluded due to different reasons based on the exclusion criteria (Fig 1). Six authors were contacted to obtain full-text articles that were not available to us, of which 5 responded to our request. Additionally, 10 authors were contacted for missing or ambiguous information, of whom 7 responded. Two additional studies were found from cross-references [16, 17], of which one could be included . This resulted in 8 cross-sectional studies, 5 case-control studies, 10 prospective cohort studies and 1 study with both cross-sectional and prospective analyses (designated as cross-sectional regarding study quality). Quality assessment of all 24 included studies was sufficient (overall mean NOS score = 6.8, SD = 1.29, range = 3–9). Separate analyses for each study design showed similar results for prospective (mean NOS score = 6.91, SD = 1.04, range = 5–8) and cross-sectional studies (mean NOS score = 7.22, SD = 0.97, range = 6–9), but the quality of case-control studies was somewhat lower (mean NOS score = 5.8, SD = 1.92, range = 3–8), mainly due to the effects of one particular study with a score of 3. All 24 studies and their details and results are summarized in detail in Tables 1–3 and Table A in S5 Appendix.
Prospective cohort studies
From the eleven prospective cohort studies, seven focused on MI [16, 18–23], four on AP [19, 22–24], and four studies on the CHD compound [22, 25–27]. Of those focusing on MI, four studies did not find an association with dementia, Alzheimer’s disease, vascular dementia or decline to mild cognitive impairment or dementia [20–23]. Three studies did find a significant association between MI and dementia , Alzheimer’s disease and Alzheimer’s disease/vascular dementia (but only for MI ascertained at the late-life visit), and possible dementia/mild cognitive impairment . Two out of the four AP studies did find that AP increased the risk of dementia or possible dementia/mild cognitive impairment [19, 24], whereas the other two studies did not find an association [22, 23]. For the CHD compound, three studies did not find a relation with cognitive decline or decline to dementia/mild cognitive impairment [22, 25, 27], whereas one study found that CHD was a significant predictor of vascular dementia .
In the meta-analysis, a total of ten studies representing 24,801 persons could be included [16, 18–26]. CHD was associated with a 45% increased risk of dementia, cognitive impairment or cognitive decline (OR = 1.45, 95%CI = 1.21–1.74, p<0.001; Fig 2). Heterogeneity was low (I2 = 25.7%, 95%CI = 0–64, p = 0.207), without suggestion of small-study effects (Egger’s test, p = 0.739; Figure A in S5 Appendix). No statistically significant source of heterogeneity was identified in a meta-regression analysis. Associations were slightly stronger in studies (n = 7) focusing on dementia (OR = 1.55, 95%CI = 1.20–2.00, p = 0.001; I2 = 40.6%, 95%CI = 0–74, p = 0.121) [16, 18, 20, 21, 23, 24, 26]. There were too few studies to conduct separate meta-analyses for the different subtypes of dementia. Similar significant results were found for MI (OR = 1.46, 95%CI = 1.16–1.84, p = 0.001, Figure B in S5 Appendix) and AP (OR = 1.36, 95%CI = 1.12–1.65, p = 0.002, Figure C in S5 Appendix) separately.
Four out of five case-control studies reported on MI. Three of these found no association between MI and dementia or Alzheimer’s disease [28–30], whereas one nested case-control study did find a significant association between MI and dementia risk . Two case-control studies investigated the relation between AP and risk for dementia, Alzheimer’s disease or vascular dementia. Both studies showed no significant associations [30, 32].
Four studies representing 6,397 individuals could be included in the meta-analysis [28, 30–32]. CHD was not significantly associated with risk of total or vascular dementia (OR = 1.14, 95%CI = 0.79–1.64, p = 0.482; Figure D in S5 Appendix). There were signs of moderate heterogeneity (I2 = 60.3%, 95%CI = 0–85, p = 0.056). There was no strong evidence for small-study effects based on the Egger’s test (p = 0.062) and visual inspection of the funnel plot (Figure E in S5 Appendix). No statistically significant source of heterogeneity was identified in a meta-regression analysis. Separate meta-analyses for MI and AP showed comparable non-significant results (MI: OR = 1.32, 95%CI = 0.78–2.21, p = 0.302, Figure F in S5 Appendix; AP: OR = 0.98, 95%CI = 0.71–1.36, p = 0.911, Figure G in S5 Appendix).
Out of nine cross-sectional studies, six studies reported on MI [27, 33–37], three on AP [34, 36, 37], and five on the CHD compound (MI+AP) [27, 37–40]. Of the six studies investigating MI, four found a significant relation with poor cognitive functioning [27, 33, 34, 37], and two studies found no association with prevalent cognitive impairment [35, 36]. For AP, two studies found a significant association with poor cognitive functioning [34, 37], whereas one study found no association with mild cognitive impairment . For the CHD compound studies, three studies found a significant association with poor cognitive functioning [27, 37, 40], one study found no relation with cognitive function or cognitive impairment , and one study found a significant association with dementia risk .
In the meta-analysis, four studies representing 623,588 persons could be included [35, 36, 38, 39]. CHD was not significantly associated with an increased risk of cognitive impairment or dementia (OR = 1.23, 95%CI = 0.76–1.97, p = 0.398; Figure H in S5 Appendix). In the CHD meta-analysis, substantial heterogeneity was observed (I2 = 81.2%, 95%CI = 26–91, p = 0.001). No statistically significant source of heterogeneity was identified in a meta-regression analysis, although inclusion of some study characteristics (e.g. mean age at baseline, outcome measurement and study quality) led to a reduction in I2 (e.g. mean age at baseline: 81.2% to 53.1%). There was no evidence for small-study effects based on the Egger’s test (p = 0.407) and visual inspection of the funnel plot (Figure I in S5 Appendix). Similar non-significant results were found for MI (OR = 1.11, 95%CI = 0.79–1.57, p = 0.548; Figure J in S5 Appendix). It was not possible to perform a meta-analysis for AP since there was only one study .
The results of the meta-analysis of prospective cohort studies indicate that individuals with CHD have, on average, a 45% increased risk of cognitive impairment or dementia. Separate meta-analyses of prospective cohort studies for the individual predictors (MI, AP) showed similar significant results. In contrast, meta-analyses of cross-sectional and case-control studies yielded no significant results, possibly due to the low number of studies included within these analyses and the moderate to substantial heterogeneity among studies. It has to be noted that, for cross-sectional studies, those studies that could not be included in the meta-analysis (those using different continuous outcome measures of cognitive functioning), majorly found lower cognitive abilities in CHD. The literature on CHD is mixed in general, with the majority of prospective and cross-sectional studies demonstrating a significant association with cognition or dementia, and most of the case-control studies showed no association.
The exact biological mechanism by which CHD is related to risk of cognitive impairment or dementia is still unknown, but several candidate pathways exist. CHD and dementia share common risk factors such as obesity, type-2 diabetes, smoking, hypertension, physical inactivity, and hypercholesterolemia [7, 8]. Post-hoc meta-regression analyses showed that there were no differences between studies (n = 3) that corrected for cardiovascular risk factors (diabetes, hypertension, high cholesterol) and studies that did not correct for these factors. In other words, the association between CHD and dementia risk cannot be solely explained by shared cardiovascular risk factors. Additionally, CHD can be associated with cardiac complications (atrial fibrillation, heart failure), whose association with cognitive impairment or dementia is well-established [7, 9]. Additionally, CHD and accompanying vascular insufficiency can lead to cerebrovascular changes such as reduced cerebral blood flow (which can lead to hypoperfusion) , white matter lesions and brain infarctions , which in turn are associated with reduced cognitive functioning and risk of dementia [42, 43]. CHD might however not itself be causally related to cognition, but brain-effects (e.g. cognitive impairment with vascular origin) might be due to underlying atherosclerosis, which increases both the risk of CHD and dementia [44, 45].
Policy makers and health workers must become more aware that identification of individuals at high risk for CHD or dementia is essential to intervene at an early stage by targeting shared modifiable risk factors (e.g. obesity, hypercholesterolemia, physical inactivity, hypertension, smoking).
Studies have shown that targeting these modifiable risk factors can be effective in reducing incidence rates and disease burden [5, 46]. Concerted actions focusing on the heart-brain connection might be key to fostering healthy aging. Future public health campaigns focusing on preventing CHD are dementia should join forces and consider placing a greater emphasis on targeting shared risk factors.
The strengths of this study include the use of large population-based studies with different study designs and the use of risk estimates that were pre-adjusted for confounding variables. Nevertheless, a number of limitations have to be mentioned. First, some studies based the ascertainment of the predictors on self-report or proxy-report, which can be prone to recall bias and underreporting, particularly given the relative older age of the included cohorts. This is particularly problematic in case-control studies, in which differential reporting bias may lead to exposure misclassification and diluted or even biased estimates. Fortunately, the majority of the included studies used validated or combined (e.g. self-report verified by validated) measurements to establish the exposure status. Related to this, is the underreporting of CHD events whereby stronger association might be distorted. This particularly applies to AP since AP is often missed, especially in comorbidity with atrial fibrillation. However, as shown by the separate meta-analyses of prospective cohort studies for MI and AP, there were no large differences between the different exposures. Second, substantial heterogeneity was observed in both cross-sectional and case-control studies. This can be related to differences in methodology across studies (e.g. assessment of dementia or cognitive functioning, ascertainment of exposure, variation between cohorts (e.g. gender specific) selection of study participants, follow-up duration and adjustment for important covariates). While meta-regression analyses did not identify any statistically significant source of heterogeneity (e.g. mean age at baseline, outcome measurement, follow-up duration), other methodological differences not included in the analyses might explain the between-study difference in effect estimates. By using a random-effects meta-analysis we have tried to account for variability within and between studies. The abovementioned issues related to cross-sectional and case-control studies might have led to the inconsistent findings between study designs. As prospective cohort studies are generally considered superior study designs to test the association between CHD exposure and dementia risk, we based our conclusion mainly on the results prospective cohort studies, but thereby not ignoring the findings of the other study designs. Third, the observed effects could probably be attributed to residual confounding in the original studies, although we used the most fully adjusted models. Fourth, studies were excluded if their CHD exposure was not a combination of purely MI and AP. For instance, studies reporting on IHD based on the the International Classification of Diseases and Related Health Problems (ICD-10) codes for IHD (I20-I25) were excluded because some of the codes also include coronary atherosclerosis and coronary artery aneurysm which are more causes of IHD . While this has led to the exclusion of studies affirming the association between CHD and cognitive impairment or dementia, our focus was on MI and AP as the most prevalent conditions. Using a broader search strategy that includes all causes of IHD led to more than 12,000 search hits (now 6,132), which was considered unfeasible. Fifth, there were unfortunately too few studies to conduct separate meta-analyses for the different subtypes of dementia. Sixth, it would have been interesting to conduct stratified meta-analyses for gender, but unfortunately gender-specific risk estimates are scarce.
In conclusion, CHD was associated with an increased risk of cognitive impairment or dementia in prospective cohort studies. More mechanistic studies are needed that focus on the underlying biological pathways (e.g. left ventricular dysfunction, cerebral small vessel disease,hypoperfusion) and shared risks (e.g. hypertension, arterial stiffness, common genetic variants) that link CHD and risk of cognitive impairment or dementia.
S4 Appendix. Newcastle-Ottawa quality assessment scale adapted for cross-sectional studies.
The authors are grateful to Ms Kira Akimova and Ms Maria Shcheglova for conducting preliminary work for the purpose of this study.
- 1. Collaborators GMaCoD. Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388(10053): 1459–544. pmid:27733281
- 2. World Health Organization. Cardiovascular diseases—Fact sheet N°317 [updated 2015 January]. http://www.who.int/mediacentre/factsheets/fs317/en/.
- 3. Mendis S, Puska P, Norrving B. Global Atlas on Cardiovascular Disease Prevention and Control. Geneva: World Health Organization, 2011.
- 4. Ferri CP, Prince M, Brayne C, Brodaty H, Fratiglioni L, Ganguli M, et al. Global prevalence of dementia: a Delphi consensus study. Lancet. 2005;366(9503): 2112–7. pmid:16360788
- 5. Norton S, Matthews FE, Barnes DE, Yaffe K, Brayne C. Potential for primary prevention of Alzheimer's disease: an analysis of population-based data. Lancet Neurol. 2014;13(8): 788–94. pmid:25030513
- 6. Plassman BL, Williams JW Jr., Burke JR, Holsinger T, Benjamin S. Systematic review: factors associated with risk for and possible prevention of cognitive decline in later life. Ann Intern Med. 2010;153(3): 182–93. pmid:20547887
- 7. Justin BN, Turek M, Hakim AM. Heart disease as a risk factor for dementia. Clin Epidemiol. 2013;5: 135–45. pmid:23658499
- 8. Deckers K, van Boxtel MP, Schiepers OJ, de Vugt M, Munoz Sanchez JL, Anstey KJ, et al. Target risk factors for dementia prevention: a systematic review and Delphi consensus study on the evidence from observational studies. Int J Geriatr Psychiatry. 2015;30(3): 234–46. pmid:25504093
- 9. Kalantarian S, Stern TA, Mansour M, Ruskin JN. Cognitive impairment associated with atrial fibrillation: a meta-analysis. Ann Intern Med. 2013;158(5 Pt 1): 338–46. pmid:23460057
- 10. Kwok CS, Loke YK, Hale R, Potter JF, Myint PK. Atrial fibrillation and incidence of dementia: a systematic review and meta-analysis. Neurology. 2011;76(10): 914–22. pmid:21383328
- 11. Santangeli P, Di Biase L, Bai R, Mohanty S, Pump A, Cereceda Brantes M, et al. Atrial fibrillation and the risk of incident dementia: a meta-analysis. Heart Rhythm. 2012;9(11): 1761–8. pmid:22863685
- 12. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009;339: b2535. pmid:19622551
- 13. Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA. 2000;283(15): 2008–12. pmid:10789670
- 14. Wells G, Shea B, O’connell D, Peterson J, Welch V, Losos M, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. 2000.
- 15. IntHout J, Ioannidis JP, Rovers MM, Goeman JJ. Plea for routinely presenting prediction intervals in meta-analysis. BMJ Open. 2016;6(7): e010247. pmid:27406637
- 16. Kivipelto M, Helkala EL, Laakso MP, Hanninen T, Hallikainen M, Alhainen K, et al. Apolipoprotein E epsilon4 allele, elevated midlife total cholesterol level, and high midlife systolic blood pressure are independent risk factors for late-life Alzheimer disease. Ann Intern Med. 2002;137(3): 149–55. pmid:12160362
- 17. Sparks DL, Hunsaker JC 3rd, Scheff SW, Kryscio RJ, Henson JL, Markesbery WR. Cortical senile plaques in coronary artery disease, aging and Alzheimer's disease. Neurobiol Aging. 1990;11(6): 601–7. pmid:1704106
- 18. Aronson MK, Ooi WL, Morgenstern H, Hafner A, Masur D, Crystal H, et al. Women, myocardial infarction, and dementia in the very old. Neurology. 1990;40(7): 1102–6. pmid:2356012
- 19. Haring B, Leng X, Robinson J, Johnson KC, Jackson RD, Beyth R, et al. Cardiovascular disease and cognitive decline in postmenopausal women: results from the Women's Health Initiative Memory Study. J Am Heart Assoc. 2013;2(6): e000369. pmid:24351701
- 20. Hayden KM, Zandi PP, Lyketsos CG, Khachaturian AS, Bastian LA, Charoonruk G, et al. Vascular risk factors for incident Alzheimer disease and vascular dementia: the Cache County study. Alzheimer Dis Assoc Disord. 2006;20(2): 93–100. pmid:16772744
- 21. Ikram MA, van Oijen M, de Jong FJ, Kors JA, Koudstaal PJ, Hofman A, et al. Unrecognized myocardial infarction in relation to risk of dementia and cerebral small vessel disease. Stroke. 2008;39(5): 1421–6. pmid:18323497
- 22. Lipnicki DM, Sachdev PS, Crawford J, Reppermund S, Kochan NA, Trollor JN, et al. Risk factors for late-life cognitive decline and variation with age and sex in the Sydney Memory and Ageing Study. PLoS One. 2013;8(6): e65841. pmid:23799051
- 23. Newman AB, Fitzpatrick AL, Lopez O, Jackson S, Lyketsos C, Jagust W, et al. Dementia and Alzheimer's disease incidence in relationship to cardiovascular disease in the Cardiovascular Health Study cohort. J Am Geriatr Soc. 2005;53(7): 1101–7. pmid:16108925
- 24. Chen R, Hu Z, Wei L, Ma Y, Liu Z, Copeland JR. Incident dementia in a defined older Chinese population. PLoS One. 2011;6(9): e24817. pmid:21966372
- 25. Kalmijn S, Feskens EJ, Launer LJ, Kromhout D. Cerebrovascular disease, the apolipoprotein e4 allele, and cognitive decline in a community-based study of elderly men. Stroke. 1996;27(12): 2230–5. pmid:8969786
- 26. Ross GW, Petrovitch H, White LR, Masaki KH, Li CY, Curb JD, et al. Characterization of risk factors for vascular dementia: the Honolulu-Asia Aging Study. Neurology. 1999;53(2): 337–43. pmid:10430423
- 27. Verhaeghen P, Borchelt M, Smith J. Relation between cardiovascular and metabolic disease and cognition in very old age: cross-sectional and longitudinal findings from the berlin aging study. Health Psychol. 2003;22(6): 559–69. pmid:14640852
- 28. Bursi F, Rocca WA, Killian JM, Weston SA, Knopman DS, Jacobsen SJ, et al. Heart disease and dementia: a population-based study. Am J Epidemiol. 2006;163(2): 135–41. pmid:16293716
- 29. Massaia M, Pallavicino Di Ceva A, Bo M, Cappa G, Zannella P, Persico D, et al. Risk factors for dementia of Alzheimer's type: a case-control, retrospective evaluation. Arch Gerontol Geriatr Suppl. 2001;7: 253–9. pmid:11431071
- 30. Takahashi PY, Caldwell CR, Targonski PV. Effect of vascular burden as measured by vascular indexes upon vascular dementia: a matched case-control study. Clin Interv Aging. 2012;7: 27–33. pmid:22291470
- 31. Brayne C, Gill C, Huppert FA, Barkley C, Gehlhaar E, Girling DM, et al. Vascular risks and incident dementia: results from a cohort study of the very old. Dement Geriatr Cogn Disord. 1998;9(3): 175–80. pmid:9622006
- 32. Hughes TF, Andel R, Small BJ, Borenstein AR, Mortimer JA, Wolk A, et al. Midlife fruit and vegetable consumption and risk of dementia in later life in Swedish twins. Am J Geriatr Psychiatry. 2010;18(5): 413–20. pmid:19910881
- 33. Breteler MM, Claus JJ, Grobbee DE, Hofman A. Cardiovascular disease and distribution of cognitive function in elderly people: the Rotterdam Study. BMJ. 1994;308(6944): 1604–8. pmid:8025427
- 34. Elwood PC, Pickering J, Bayer A, Gallacher JE. Vascular disease and cognitive function in older men in the Caerphilly cohort. Age Ageing. 2002;31(1): 43–8. pmid:11850307
- 35. Petrovitch H, White L, Masaki KH, Ross GW, Abbott RD, Rodriguez BL, et al. Influence of myocardial infarction, coronary artery bypass surgery, and stroke on cognitive impairment in late life. Am J Cardiol. 1998;81(8): 1017–21. pmid:9576163
- 36. Roberts RO, Knopman DS, Geda YE, Cha RH, Roger VL, Petersen RC. Coronary heart disease is associated with non-amnestic mild cognitive impairment. Neurobiol Aging. 2010;31(11): 1894–902. pmid:19091445
- 37. Singh-Manoux A, Britton AR, Marmot M. Vascular disease and cognitive function: evidence from the Whitehall II Study. J Am Geriatr Soc. 2003;51(10): 1445–50. pmid:14511166
- 38. Arntzen KA, Schirmer H, Wilsgaard T, Mathiesen EB. Impact of cardiovascular risk factors on cognitive function: the Tromso study. Eur J Neurol. 2011;18(5): 737–43. pmid:21143340
- 39. Heath CA, Mercer SW, Guthrie B. Vascular comorbidities in younger people with dementia: a cross-sectional population-based study of 616 245 middle-aged people in Scotland. J Neurol Neurosurg Psychiatry. 2015;86(9): 959–64. pmid:25406350
- 40. Singh-Manoux A, Sabia S, Lajnef M, Ferrie JE, Nabi H, Britton AR, et al. History of coronary heart disease and cognitive performance in midlife: the Whitehall II study. Eur Heart J. 2008;29(17): 2100–7. pmid:18648106
- 41. Gruhn N, Larsen FS, Boesgaard S, Knudsen GM, Mortensen SA, Thomsen G, et al. Cerebral Blood Flow in Patients With Chronic Heart Failure Before and After Heart Transplantation. Stroke. 2001;32(11): 2530–3. pmid:11692012
- 42. de la Torre JC. Cardiovascular risk factors promote brain hypoperfusion leading to cognitive decline and dementia. Cardiovasc Psychiatry Neurol. 2012;2012: 367516. pmid:23243502
- 43. Debette S, Markus HS. The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ. 2010;341: c3666. pmid:20660506
- 44. Roeters van Lennep JE, Westerveld HT, Erkelens DW, van der Wall EE. Risk factors for coronary heart disease: implications of gender. Cardiovascular Research. 2002;53(3): 538–49. pmid:11861024
- 45. van Oijen M, de Jong FJ, Witteman JC, Hofman A, Koudstaal PJ, Breteler MM. Atherosclerosis and risk for dementia. Ann Neurol. 2007;61(5): 403–10. pmid:17328068
- 46. Manuel DG, Lim J, Tanuseputro P, Anderson GM, Alter DA, Laupacis A, et al. Revisiting Rose: strategies for reducing coronary heart disease. BMJ. 2006;332(7542): 659–62. pmid:16543339
- 47. World Health Organization. International Statistical Classification of Diseases and Related Health Problems, 10th Revision. Geneva: World Health Organization, 1992.