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Canadian Journal of Public Health = Revue Canadienne de Santé Publique logoLink to Canadian Journal of Public Health = Revue Canadienne de Santé Publique
. 2022 Jan 13;113(3):455–464. doi: 10.17269/s41997-021-00589-2

Cardiovascular disease and the risk of dementia: a survival analysis using administrative data from Manitoba

Luc Clair 1,2,✉, Hope Anderson 2,3, Christopher Anderson 4,5, Okechukwu Ekuma 6, Heather J Prior 6
PMCID: PMC9043061  PMID: 35025100

Abstract

Objectives

Recent research has shown that cardiovascular disease (CVD) raises the risk of dementia and other forms of cognitive decline. Generally, these studies are unable to model the time of diagnosis of CVD in their analyses and treat CVD as a time-fixed variable. Our objective was to assess the risk of being diagnosed with dementia for individuals diagnosed with CVD when CVD is time-dependent.

Methods

We performed a retrospective cohort study using administrative health datasets from the Manitoba Population Research Data Repository in Canada. We constructed a longitudinal dataset to track individuals enrolled in the Manitoba Health Insurance Registry between April 1, 1997 and March 31, 2015. The study population consisted of 496,192 individuals 30 years of age or older who were not diagnosed with CVD or dementia prior to April 1, 1997. Diagnoses of CVD and dementia were based on diagnosis codes from medical claims and hospitalizations and the use of prescription medications. Hazard ratios were then computed using adjusted Cox-proportional hazards analyses.

Results

Among the CVD subgroups considered, atrial fibrillation, ischemic heart disease, and stroke increased the risk of developing dementia, with stroke doubling one’s risk of being diagnosed with the disease (hazard ratio: 1.95; 95% confidence interval: 1.9, 2.01). Age, lower socioeconomic status, and worsening comorbidities also increased the risk of being diagnosed with dementia.

Conclusion

A diagnosis of CVD is associated with an increased risk of a future diagnosis of dementia. Promoting good cardiovascular health may serve as an effective measure for preventing dementia.

Supplementary Information

The online version contains supplementary material available at 10.17269/s41997-021-00589-2.

Keywords: Cardiovascular disease, Dementia, Survival analysis, Time-varying coefficients, Retrospective study

Introduction

Cardiovascular disease (CVD) and dementia impose significant burdens on society. At the individual level, these illnesses reduce one’s quality of life by restricting activities, inducing physical and psychological distress, increasing the number of visits to the doctor, and raising the probability of hospitalization and/or death (Britton et al., 2012; MacNeil-Vroomen et al., 2020; Nowbar et al., 2019; Szpakowski et al., 2017). At the community level, CVD and dementia are associated with increased health care costs and reduced productivity (Jeon et al., 2020; Garland et al. 2019; Szpakowski et al., 2017; Wong et al., 2016; Zhu et al., 2015). In addition, recent research suggests there is a link between dementia and a myriad of CVDs, including acute myocardial infarction (AMI), atrial fibrillation (AF), and stroke (Graves et al., 2017; Hachinski et al., 2019; Haring et al., 2013; Harrison et al., 2014; Kalaria et al., 2016; Kuzma et al., 2018; Pendlebury & Rothwell, 2019; Song et al., 2020; Stephan et al., 2017). The association between CVD and dementia is likely to compound the burden on society already imposed by these illnesses (MacNeil-Vroomen et al., 2020).

Diabetes, hypertension, obesity, and atherosclerosis are typical comorbid conditions for both CVD and dementia, which could account for the observed correlations (Cannon et al., 2017). These conditions may promote aortic stiffening, which negatively affects cognitive functioning and may result in accelerated vascular aging (de Roos et al., 2017). This in turn results in accelerated development of cerebral small vessel disease, which leads to early cognitive decline, vascular dementia, and Alzheimer’s disease (de Roos et al., 2017; Paciaroni & Bogousslavsky, 2013).

Studies examining the association of cardiovascular health with dementia or other forms of cognitive decline generally take a prospective approach, where cardiovascular health is assessed at baseline and may be defined by an individual’s history of CVD or by a CVD risk prediction model (Graves et al., 2017; Hachinski et al., 2019; Haring et al., 2013; Harrison et al., 2014; Kalaria et al., 2016; Kuzma et al., 2018; Pendlebury & Rothwell, 2019; Song et al., 2020; Stephan et al., 2017). Survival analyses are then conducted to assess the associated risk of cognitive decline for those with CVD (or a high risk of CVD). When CVD is assessed only at baseline, it is a time-fixed variable and the onset of CVD cannot be factored into the analysis.

The purpose of this study was to assess the risk of being diagnosed with dementia for individuals with CVD when the diagnosis of CVD is time-dependent. We performed a retrospective cohort study using de-identified administrative health datasets from the Province of Manitoba. Our study differs from previous reports on this topic for two reasons. First, we excluded anyone with a diagnosis of CVD or dementia prior to baseline. Second, we treated CVD as a time-varying covariate in our survival analyses to avoid biases related to immortal time.

Methods

Data and study population

We used data from the Manitoba Population Research Data Repository (henceforth referred to as the “Repository”) held at the Manitoba Centre for Health Policy (MCHP) in Canada. The Repository is a unique data initiative that allows users to link administrative, registry, and survey datasets in the Province of Manitoba covering a variety of topics, including health care, education, social assistance, and the justice system. The data are de-identified but can be linked, at the individual level, across databases, and over time, using a scrambled personal identifier from the Manitoba Health Insurance Registry (MHIR). The MHIR is a registry of all individuals qualified to receive health care coverage under the Manitoba Health Services Insurance Plan (MHSIP). Non-participation in the plan is minimal as all medically necessary hospital and physician services are publicly financed in Canada. The databases we accessed for this study were the Medical Claims database, the Hospital Abstracts database (DAD), the Drug Program Information Network (DPIN) database, the Cardiac Surgical database (CSD), the MHIR, and the Canada Census.

We used the Medical Claims database and the DAD to identify diagnoses from outpatient and inpatient physician claims, respectively. Diagnoses in the Medical Claims database are based on three-digit International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes. Diagnoses in the DAD are coded in ICD-9-CM prior to April 1, 2004, and ICD-10-CA (Canada) afterwards. The DPIN provided information on prescribed medications identified using their anatomical therapeutic classification (ATC). We accessed the CSD to identify if anyone underwent cardiovascular surgery during the study period. Population demographic information was obtained from the MHIR and the Canada Census data. In addition, the MHIR provided reasons for cessation of coverage in the MHSIP (e.g., death or moved out of province).

These datasets have been validated for linkage accuracy and have been used extensively in previous research (Roos et al., 2005; Roos & Nicol, 1999). This study was approved by the University of Manitoba Health Research Ethics Board (HREB), the University of Winnipeg HREB, the Government of Manitoba Health Information Privacy Committee, and the Winnipeg Regional Health Authority Research Review Committee.

Study population

The study population consisted of individuals 30 years of age or older as of April 1, 1997, registered in the MHIR in the 2 years prior to the study start date. We imposed a 2-year washout period from April 1, 1995 to March 31, 1997 to exclude anyone who met the criteria for dementia and/or any of the cardiovascular indicators prior to the study period. The final sample was made up of 496,192 individuals tracked over an 18-year period until diagnosis of CVD, death, loss to follow-up, or March 31, 2015, whichever came first.

Variables

Diagnosis of dementia

Using information from the Medical Claims database, the DAD, and the DPIN database, we defined a diagnosis of dementia as a hospitalization or physician visit with a diagnosis for an organic psychotic condition, a cerebral degeneration, or senility (diagnosis codes listed in Table 1) or one or more prescriptions for donepezil, rivastigmine, galantamine, and/or memantine (ATC codes listed in Table 1). This definition is based on the MCHP concept for dementia, which has been applied in previous studies to identify diagnoses of dementia using Repository data (Manitoba Centre for Health Policy, 2019a, 2019b; Chartier et al., 2015, 2018).

Table 1.

Diagnosis codes, CCI codes, and ATC codes for indicators

Indicator ICD-9-CM ICD-10-CA CCI ATC
AMI 410 I21 – –
Atrial fibrillation 427 I48 – –
Cardiac surgery 36.01, 36.02, 36.05, 36.06, 36.1x, 37.21, 37.22, 37.23 – 1.IJ.50, 1.IJ.57, 1.IJ.76 –
Dementia 290, 291.1, 292.2, 292.82294, 331, 797 F00, F01, F02, F03, F04, F05.1, F06.5, F06.6, F06.8, F06.9, F09, F1x.7, G30, G31.0, G31.1, G31.9, G32.8, G91, G93.7, G94, R54 –

Donepezil, N06DA02

Rivastigmine, N06DA03

Galantamine, N06DA04

Memantine, N06DX01
IHD 410–414 I20-I22, I24, I25 – –
Stroke 430–438 I60-I69 – –
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AMI indicates acute myocardial infarction; CCI, Canadian Classification of Interventions Codes; CHF, congestive heart failure disease; ICD-9-CM, International Classification of Diseases, Ninth Revision, Clinical Modifications; ICD-10-CA, International Classification of Diseases, Tenth Revision, with Canadian Enhancements; IHD, ischemic heart disease; PVD, peripheral vascular disease

Cardiovascular indicators

The CVDs we considered were AMI, ischemic heart disease (IHD), AF, and stroke. Individuals were identified as having a CVD if they were hospitalized or visited a physician with the corresponding diagnosis code(s). Table 1 lists the diagnosis codes used to classify CVD patients for each illness. The definition for IHD includes diagnoses for AMI, as well as subsequent AMI, angina pectoris, other acute and subacute forms of IHD, and other forms of chronic IHD (Manitoba Centre for Health Policy 2020).

In addition to CVD, we considered a “cardiac surgery” variable, which identifies if an individual underwent a coronary artery bypass graft (CABG), aortic valve replacement, or percutaneous coronary intervention as identified as having an intervention in the CSD or in the hospital discharge abstracts data using Canadian Classification of Health Interventions (CCI) codes. Table 1 lists the CCI codes used in our analysis. Finally, we included a composite CVD variable, which indicates if an individual met the criteria for any CVD or underwent cardiac surgery.

Covariates

CVD and dementia share a number of risk factors, including demographic, socioeconomic, and health characteristics. The demographic variables we considered were age and sex. The risk of dementia increases with age and it has been shown that women are at a higher risk of dementia (Rasmussen et al., 2018; Mielke, 2018). In our study, age was measured in years and represents the individual’s age as of April 1, 1997, and sex is a binary variable taking a value of 1 if male and 0 if female.

We elected to use the Elixhauser comorbidity index (ECI) at baseline as a measure of health status. The ECI used diagnosis codes in the Medical Claims and the DAD one year prior to study start date to categorize patient comorbidities, allowing one to rank health status by index number. The ECI contains 31 categories covering a wide range of illnesses, including cardiovascular disease, diabetes, hypertension, neurological disorders, pulmonary disorders, kidney disease, liver disease, digestive illnesses, cancer, arthritis, substance abuse, and mental illness. For a full list of illnesses, please see Table B.1 in the supplementary material. We used the established algorithm by Walraven et al., (2009) to weight each category based on risk of mortality and condense these values into a single numeric score. The higher the score, the more severe are the individual’s comorbidities. For the purpose of our analyses, we modified the index to remove categories related to dementia and the CVDs considered above.

Socioeconomic status (SES) has also been identified as a possible risk factor for dementia (Fischer et al., 2009). To measure SES, we calculated individual scores on the socioeconomic factor index (SEFI) based on results from the 1996 Canada Census, linked to postal codes of residence at baseline. The SEFI is a measure of non-medical social determinants of health and includes factors such as single parent status, labour force participation, unemployment rate, and high school graduation. SEFI scores less than zero indicate more favourable socioeconomic conditions, while SEFI scores greater than zero indicate worsening socioeconomic conditions.

Finally, we included a variable measuring urban residence, which was defined as residence in one of the two major cities in Manitoba: Winnipeg (capital city) or Brandon, as of April 1, 1997. Individuals who live in rural areas tend to have limited access to health care services and are more likely to suffer from ambulatory care sensitive conditions, including hypertension and diabetes, which may contribute to both CVD and dementia (Ou et al., 2020; Canadian Institute of Health Information, 2012; Cheng et al., 2012).

Statistical analysis

Descriptive statistics

The characteristics of individuals were compared based on whether an individual developed CVD over the course of the study period or not. Differences between individuals who develop CVD and those who do not were compared using standard t-test for continuous variables and χ2-statistics for categorical variables.

Survival analysis

The time to an initial diagnosis of dementia was calculated by the number of days from the time origin (Apri1 1, 1997) to first of date of dementia diagnosis, death, loss to follow-up, or end of study. Individuals who met the criteria for at least one CVD variable before either of these events were considered part of the CVD group. Hazard ratios (HRs) for the risk of dementia associated with the composite variable of CVD and its subgroups (AMI, IHD, AF, stroke, and cardiac surgery) were calculated using adjusted Cox-proportional hazards analyses. These models were adjusted for age, sex, ECI, SEFI, and urban residence at baseline. Furthermore, we treated CVD and its subgroups as time-varying covariates to control for immortal time. In our study, immortal time refers to the span of time between baseline and diagnosis of CVD for which dementia could not be diagnosed. This added time slows the effect of CVD, reducing an individual’s risk of developing dementia. This differs from prospective studies on this topic that consider CVD prior to baseline (Graves et al., 2017; Harrison et al., 2014; Saglietto et al., 2019; Song et al., 2020; Stephan et al., 2017). Given that we are interested in whether CVD expedites the development of dementia or not, the ability to model the time of diagnosis of CVD is an asset. The time to diagnosis of CVD was calculated as the number of days between the time origin and the date of diagnosis.

Sensitivity analyses treating death as a competing risk were also completed. We defined death as a competing event if a dementia-free individual was listed as leaving the MHIR because of death. Finally, we estimated adjusted models treating both IHD and cardiac surgery as time-varying covariates with and without death as a competing risk. All analyses were performed using SAS/STAT® software, version 9.4 of the SAS system (© 2016 SAS Institute Inc.).

Results

Of the 496,192 individuals in our sample, 272,265 (54.87%) met the criteria for at least one of the selected CVD indicators over the course of the study period and 3.05% underwent cardiovascular surgery (Table 2). Compared to the non-CVD group, the CVD group was older, had more comorbid conditions, had a higher percentage develop dementia, and had a higher percentage of individuals die during the study period (Table 3).

Table 2.

Number and percentage of sample with selected cardiovascular indicators

CVD Number (%)
Composite CVD 272,265 (54.87)
AMI 21,329 (4.30)
Atrial fibrillation 57,404 (11.57)
Cardiac surgery* 8137  (3.05)
IHD 245,048 (49.39)
Stroke 50,713 (10.22)
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AMI indicates acute myocardial infarction; CVD, cardiovascular disease; IHD, ischemic heart disease

*One of coronary artery bypass graft, aortic valve replacement, percutaneous coronary intervention, or cardiac catheterization

Table 3.

Means and percentages of dementia and covariate for the CVD group, non-CVD group, and overall

Characteristic CVD group1
N = 272,265		 Non-CVD group
N = 223,927		 p-value from testing difference in proportions/means Overall
N = 496,192
Mean age (SD) 51.1 (13.8) 43.6 (12.6)  < 0.0001 47.7 (13.8)
Mean SEFI (SD)  − 0.1658 (1.0299)  − 0.2578 (1.0375)  < 0.0001  − 0.2073 (1.0343)
Mean Elixhauser comorbidity index, weighted (SD) (CVD and dementia free) 0.5330 (0.7782) 0.3394 (0.6465)  < 0.0001 0.4456 (0.7281)
N (%) N (%) N (%)
Male 134,182 (49.3) 108,209 (48.3)  < 0.0001 242,391 (48.9)
Urban 164,069 (60.26) 146,558 (65.45)  < 0.0001 310,627 (62.60)
Dementia 27,248 (10.01) 12,468 (5.57)  < 0.0001 39,716 (8.00)
Death 68,577 (25.19) 29,062 (12.98)  < 0.0001 97,639 (19.68)
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CVD indicates cardiovascular disease; SEFI, socioeconomic factor index

1Individuals who were diagnosed with cardiovascular disease or underwent cardiovascular surgery between April 1, 1997 and March 31, 2015

The HRs for dementia diagnosis related to CVD are presented in Table 4. The HR for individuals with any CVD over the study period compared to those free of CVD was 1.17 (see column (1) in Table 4). After controlling for death as a competing risk, the HR increased to 1.46 (see column (2) in Table 4). Among the subgroups of CVD, AF (HR: 1.23; 95% CI: 1.2, 1.27), AMI (HR: 1.05; 95% CI: 1.03, 1.1), IHD (HR: 1.25; 95% CI: 1.22, 1.29), and stroke (HR: 1.95; 95% CI: 1.9, 2.01) were found to be associated with a diagnosis of dementia. Initially, cardiac surgery was found to have a protective effect (HR: 0.92; 95% CI: 0.87, 0.97); however, the hazard ratio increased to 1.21 (95% CI: 1.15, 1.28) after controlling for death as a competing risk.

Table 4.

Estimated hazard ratios from adjusted Cox-proportional hazard analysis with CVD as a time-varying covariate and death as a competing risk

CVD (1) (2)
Adjusted1 model with time-varying CVD
(95% CI)		 Adjusted1 model with time-varying CVD and death as a competing risk (95% CI)
Composite CVD

1.17

(1.15, 1.2)

1.46

(1.43, 1.5)
AF

1.15

(1.12, 1.18)

1.23

(1.2, 1.27)
AMI

1.08

(1.03, 1.12)

1.05

(1.03, 1.1)
IHD

1.11

(1.09, 1.14)

1.25

(1.22, 1.29)
Stroke

1.84

(1.8, 1.88)

1.95

(1.9, 1.01)
Cardiac surgery2

0.92

(0.87, 0.97)

1.21

(1.15, 1.28)
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AMI indicates acute myocardial infarction; CI, confidence interval; CVD, cardiovascular disease; AF, atrial fibrillation; IHD, ischemic heart disease

1Adjusted for age, sex, Elixhauser comorbidity index, socioeconomic factor index, and urban residence

2One of coronary artery bypass graft, aortic valve replacement, or percutaneous coronary intervention

Interactions on the effects of age, sex, urban residence, SEFI, and comorbidities at baseline were examined in each model. Figure 1 displays the results from the adjusted Cox-proportional hazard model treating any CVD indicator as time-varying. Age (HR: 1.12; 95% CI: 1.12, 1.12), urban residence (HR: 1.18; 95% CI: 1.16, 1.21), SEFI (HR: 1.15; 95% CI: 1.14, 1.16), and increasing comorbidity scores (HR: 1.11, 95% CI: 1.1, 1.2) were associated with a diagnosis of dementia, while males had a slightly lower risk of being diagnosed with dementia (HR: 0.98; 95% CI: 0.96, 0.99). The effects of age, sex, population density, SEFI, and comorbidities were similar in all models and are not reported here (see Figure A. 1 in the Online Resource for tree plots of the interaction effects of the covariates with each CVD subgroup).

Fig. 1.

Fig. 1

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Hazard ratio (95% confidence interval) of a diagnosis of dementia when CVD is treated as a time-varying covariate

Figure 2 displays the results from estimating the adjusted Cox-proportional hazard model including both IHD and cardiovascular surgery as time-varying covariates. In this case, cardiac surgery appears to have a protective effect for dementia (HR: 0.85; 95% CI: 0.8, 0.9). However, when death is treated as a competing risk, the hazard ratio for cardiac surgery increased to 1.03 (95% CI: 1, 1.1; see Fig. 2). In this final model, IHD, age, urban residence, and comorbidity score remain positively associated with a diagnosis of dementia, while being male is negatively associated with a diagnosis of dementia.

Fig. 2.

Fig. 2

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Hazard ratios (95% CI) of a diagnosis of dementia treating ischemic heart disease (IHD) and cardiac surgery as time-varying covariates when a there is no competing risk and b death is treated as a competing risk

Discussion

CVD and dementia

The results from this study support the hypothesis that CVD is associated with an increased risk of dementia. Among the CVD subgroups considered, atrial fibrillation, acute myocardial infarction, ischemic heart disease, and stroke increased the risk of developing dementia, with stroke doubling one’s risk of being diagnosed with the disease. These findings complement a growing body of literature on the relationship between cardiovascular health and dementia.

In the literature, there are two approaches to studying this relationship. First, as is the approach in this study, is to investigate the effect of CVD on the development of dementia or other forms of cognitive decline. The most commonly studied relationship is the impact of stroke on cognitive functioning (Gorelick et al., 2011; Hachinski et al., 2019; Ivan et al., 2004; Kalaria et al., 2016; Kuzma et al., 2018; Pendlebury & Rothwell, 2019). Investigations into the impact of stroke on dementia consistently report an increased risk of dementia for stroke patients compared to the general population. This result has led to a call for action to treat stroke prevention as an effective method for preventing dementia (Hachinski et al., 2019).

Other forms of CVD have also been shown to have adverse effects on cognition (Graves et al., 2017; Haring et al., 2013; Harrison et al., 2014; Song et al., 2020; Stephan et al., 2017). Haring et al. (2013) compared the incidence rates of mild cognitive impairment and probable dementia for women with a history of CVD to those free of CVD, excluding anyone with a history of stroke at baseline. The authors found that CVD was strongly associated with cognitive decline (HR: 1.29), with myocardial infarction posing the greatest risk (HR: 2.10). These results remained even after excluding women with an incidence of stroke after baseline. Studies using CVD risk prediction models, including the Framingham General Cardiovascular Risk Score; the Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) model; the congestive heart failure, hypertension, age greater than 75 years, diabetes, and stroke (CHADS2) score; and other cardiovascular risk models, have also shown that CVD and vascular risk factors are associated with cognitive decline (including reductions in episodic memory, working memory, and perceptual speed) and neurodegeneration (Graves et al., 2017; Harrison et al., 2014; Song et al., 2020; Stephan et al., 2017).

The second approach is to study the impact of cardiovascular health-promoting activities on the risk of developing dementia. A common measure for cardiovascular health is the American Heart Association’s (AHA) “Simple 7’s” metric, which assigns a score between 0 and 7 based on four health behaviours (nonsmoking, a body mass index less than 25, regular physical activity, and a healthy diet) and three biological measures (untreated blood cholesterol less than 200 mg/dL, untreated fasting glucose less than 100 mg/dL, and untreated blood pressure less than 120/80 mm Hg). This cardiovascular health (CVH) measure assigns 1 point for each characteristic an individual possesses so that higher scores represent better cardiovascular health. Studies using the AHA’s Simple 7’s metric have shown that higher CVH scores were significantly associated with lower risk of dementia and better cognitive functioning (Gardener et al., 2016; Samieri et al., 2018).

Cardiac surgery

In addition to the CVDs considered, we examined the impact of cardiovascular surgery on the risk of developing dementia. Similar to Haring et al. (2013), we observed that those who underwent a cardiovascular procedure had an increased risk of being diagnosed with dementia. On-pump cardiac surgery is a man-made ischemic event, which may lead to cerebral hypoxia, increasing the risk of cognitive decline (Lopez et al., 2017). Also, individuals who undergo a CABG, an aortic valve replacement, or a percutaneous coronary intervention typically suffer from some form of CVD, which may account for the positive association. In our analysis, cardiac surgery did not appear to have a protective effect against dementia for those with IHD. Therefore, surgery to correct underlying IHD does not appear to mitigate the risk of developing dementia in our study.

Strengths and limitations

The greatest strength of this analysis was the ability to combine a number of administrative, registry, and survey databases to produce a longitudinal dataset including dates of diagnoses for dementia and CVDs, dates of cardiac surgery, and important confounders (i.e., comorbidities, SES, age, and sex) with a substantial sample size. Given the dates of diagnoses for the selected CVDs, we were able to treat CVD as time-varying, which allowed us to control for the immortal time bias. Nevertheless, this study faced a number of limitations. First, we are restricted to only three-digit ICD-9-CM codes in the medical claims data, so we could not distinguish between sub-types of dementia (e.g., Alzheimer’s disease or vascular dementia) when patients were diagnosed in an outpatient setting. Second, the onset of both CVD and dementia occurs prior to the date of diagnosis. Therefore, the date of diagnosis is used as an approximation of the date of onset. Furthermore, many forms of CVD may be asymptomatic (e.g., silent heart attacks and silent strokes), and therefore, go undiagnosed by physicians. In our analysis, these individuals would be incorrectly considered in the non-CVD group. Third, we were unable to control for all individual behaviours that may contribute to both CVD and dementia. While the Elixhauser comorbidity index incorporates alcohol abuse and drug use (including smoking), we were unable to observe other health-changing behaviours, e.g., exercise regimen. Also, this variable is static, taking only baseline measures into account. Finally, we were unable to control for all comorbidities that may contribute to dementia, e.g., schizophrenia.

Conclusion

In this study, we assessed the risk of being diagnosed with dementia for those diagnosed with CVD when the time of CVD diagnosis is allowed to vary. Our analysis showed that CVD is associated with an increased risk of dementia. Furthermore, cardiac surgery does not appear to mitigate the effects of IHD on the risk of being diagnosed with dementia. Therefore, activities to promote cardiovascular health and prevent CVD may be more effective at preventing dementia, a disease with no known cure.

Contributions to knowledge

What does this study add to existing knowledge?

  • This study assessed the risk of being diagnosed with dementia for individuals with cardiovascular disease (CVD) when the diagnosis of CVD is time-dependent.

  • This study adds further evidence that CVD increases the risk of developing dementia, with stroke doubling one’s risk of developing the disease.

  • Our results also showed that cardiac surgery does not appear to reduce the risk of dementia among patients with ischemic heart disease.

What are the key implications for public health interventions, practice or policy?

  • Activities to promote cardiovascular health and prevent CVD may be an effective method to reduce one’s risk of developing dementia.

  • When assessing the health care costs associated with CVD, one should consider the increased risk of dementia and health care costs associated with this disease.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 147 KB) (147.1KB, docx)

Acknowledgements

Funding for this project came from the Manitoba Medical Services Foundation Operating Grant (#8–2018-04) and the Government of Manitoba Canadian Agriculture Partnership Program (#1,000,218,608). The authors acknowledge the Manitoba Centre for Health Policy for use of data contained in the Manitoba Population Research Data Repository under project #2017/2018–60. The results and conclusions are those of the authors and no official endorsement by the Manitoba Centre for Health Policy, Manitoba Health, or other data providers is intended or should be inferred. Data used in this study are from the Manitoba Population Research Data Repository housed at the Manitoba Centre for Health Policy, University of Manitoba and were derived from data provided by Manitoba Health and Winnipeg Regional Health Authority.

Author contributions

All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by LC, OE, and HP. The first draft of the manuscript was written by LC and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Funding

Manitoba Medical Services Foundation Operating Grant (#8–2018-04) and Government of Manitoba Canadian Agriculture Partnership Program Grant (#1000218608).

Code availability

Code available upon request from the author.

Declarations

Ethics approval

This retrospective study was approved by the University of Manitoba Health Research Ethics Board (HREB), the University of Winnipeg HREB, the Government of Manitoba Health Information Privacy Committee, and the Winnipeg Regional Health Authority Research Review Committee.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Conflict of interest

The authors declare that they have no conflict of interest.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary file1 (DOCX 147 KB) (147.1KB, docx)

Data Availability Statement

Code available upon request from the author.

Articles from Canadian Journal of Public Health = Revue Canadienne de Santé Publique are provided here courtesy of Springer

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