Cardiovascular Disease and Cognitive Impairment: A Detailed Analysis

This report investigates the relationship between cardiovascular disease (CVD) and cognitive impairment in elderly adults, focusing on a study conducted with Greek participants. The research employs various cognitive tests, including the Mini-Mental State Examination, and assesses variables like age, education, and performance on tests such as the Digit Symbol Test, Rey-Osterrieth complex figure test, and the California Verbal Learning Test. The study utilizes t-tests to compare healthy and unhealthy individuals, revealing statistically significant differences in several cognitive domains. A linear regression model is developed to identify the key variables influencing health status, with results indicating that performance on tests related to memory, recall, and verbal learning are significant predictors. The report includes detailed tables presenting mean scores, t-test results, and regression analyses, along with a discussion of the findings and their implications for understanding the impact of CVD on cognitive function. The study concludes that there is a significant correlation between cardiovascular disease and cognitive impairment.

Running head: CARDIOVASCULAR DISEASE AND COGNITIVE IMPAIRMENT
Cardiovascular Disease and Cognitive Impairment
Name of the Student:
Name of the University:
Author Note:

1CARDIOVASCULAR DISEASE AND COGNITIVE IMPAIRMENT
Table of Contents
Results........................................................................................................................................2
Discussion..................................................................................................................................8
Conclusion................................................................................................................................10
Reference and Bibliography.....................................................................................................12
Appendices...............................................................................................................................15
Appendix A.1.......................................................................................................................15
Appendix A.2.......................................................................................................................15
Appendix B..........................................................................................................................16
Appendix C.1.......................................................................................................................16
Appendix C.2.......................................................................................................................16

2CARDIOVASCULAR DISEASE AND COGNITIVE IMPAIRMENT
Results
The t-test result comparison is presented in the table 1. There are few statistically
significant differences which were observed through the t-test. These variables are age [t (28)
= -3.621, p = 0.001], digit back [t (28) = -2.527, p = 0.017], digit total [t (28) = -2.253, p =
0.032, digit symbol [t (28) = 4.077, p = 0.00], in Rey–Osterrieth complex figure Test recall [t
(28) = 5.506, p = 0.00], 2nd recall [t (28) = 4.987, p = 0.00] and true answers [t (28) = 4.004,
p = 0.00], in California Verbal Learning Test 1-5, correct [t (28) = -21.397, p = 0.00],
intrusions [t (28) = 3.483, p = 0.00] and semclusters [t (28) = 10.877, p = 0.00], in California
Verbal Learning Test 7 correct [t (28) = 4.743, p = 0.00], intrusions [t (28) = -13.914, p =
0.00] and semclusters [t (28) = 7.933, p = 0.00], in California Verbal Learning Test 8 correct
[t (28) = 21.415, p = 0.00], intrusions [t (28) = -26.28, p = 0.00] and persev [t (28) = -3.5, p =
0.002], in California Verbal Learning Test 9 correct [t (28) = 22.769, p = 0.00] and intrusions
[t (28) = -37.34, p = 0.00], in California Verbal Learning Test 10 correct [t (28) = 23.625, p =
0.00], intrusions [t (28) = -19.579, p = 0.00] and persev [t (28) = -2.779, p = 0.01], in
semantic test corrects [t (28) = 14.293, p = 0.00] and clusters [t (28) = -6.808, p = 0.00] and
in phonemic test correct [t (28) = 12.942, p = 0.00] and clusters [t (28) = -12.109, p = 0.00].
The insignificant variables are education [t (28) = 0.138, p = 0.891], Moca [t (28) =
1.269, p = 0.215], total digit [t (28) = -1.635 p = 0.113], TMT A Time [t (28) = -0.114, p =
0.91] and TMT B Time [t (28) = 0.684, p = 0.5]. Except theses all there are more
insignificant meandifference of variables like LNSequencetot and CVLT7SDFRpersev.
Table 1:
Mean scores (+SD’s) and results of parametric comparisons using multiple t-tests for
independent samples between the two participant groups for age and education.
Variable Healthy Patient df t and p

3CARDIOVASCULAR DISEASE AND COGNITIVE IMPAIRMENT
2-tailed
Age 67.00 (6.9488) 77.067 (8.2242) 28 -3.621
0.001
Education 11.733 (3.0814) 11.533 (4.7036) 28 0.138
0.891
Table 2:
Mean scores (+SD’s) and results of parametric comparisons using multiple t-tests for
independent samples between the four participant groups for MoCA, Digit Forward, Digit
Back and Digit Total.
Variable Healthy Patient df t and p
2-tailed
MoCA 26.47 (1.457) 24.53 (5.718) 28 1.269
0.215
DigitFtotal 9.13 (2.356) 11.00 (3.742) 28 -1.635
0.113
DigitBtotal 6.00 (.138) 9.00 (4.071) 28 -2.527
0.017
Digittotal 15.13 (3.777) 20.00 (7.464) 28 -2.253
0.032
Table 3:
Mean scores (+SD’s) and results of parametric comparisons using multiple t-tests for
independent samples between the two participant groups for Trail Making Test A and Trail
Making Test B.
Variable Healthy Patient df t and p
2-tailed
TMTAtime 66.4667 (31.9573) 68.20 (49.2881) 28 -0.114
0.91
TMTBtime 136.00 (2.0886) 115.80 (96.1303) 28 0.684
0.5
Table 4:
Mean scores (+SD’s) and results of parametric comparisons using multiple t-tests for
independent samples between the two participant groups for Digit Symbol, LN Sequence test.
Variable Healthy Patient df t and p
2-tailed
DigitSymboltot 39.93 (10.793) 23.67 (11.056) 28 4.077

4CARDIOVASCULAR DISEASE AND COGNITIVE IMPAIRMENT
0.00
LNSequencetot 8.53 (3.204) 9.53 (4.969) 28 -0.655
0.518
Table 5:
Mean scores (+SD’s) and results of parametric comparisons using multiple t-tests for
independent samples between the four participant groups for Rey–Osterrieth complex figure
Test (recall, 2nd recall, true answers, copy of the schema).
Variable Healthy Patient df t and p
2-tailed
ROCFTlmRecall 20.667 (3.1034) 13.500 (3.9731) 28 5.506
0.00
ROCFTDelRecall 17.867 (2.9548) 12.400 (3.0484) 28 4.987
0.00
ROCFTRecTrueeP 10.27 (1.163) 7.27 (2.658) 28 4.004
0.00
ROCFTCopy 44.833 (49.9137) 21.700 (4.4232) 28 1.788
0.085
Table 6:
Mean scores (+SD’s) and results of parametric comparisons using multiple t-tests for
independent samples between the three participant groups for California Verbal Learning
Test_5 (correct, intrusions, semclusters).
Variable Healthy Patient df t and p
2-tailed
CVLT1_5instrusions 1.33 (1.676) 37.53 (6.334) 28 -21.397
0.00
CVLT1_5persev 2.87 (2.615) 0.40 (0.828) 28 3.483
0.002
CVLT1_5semclusters 12.93 (3.305) 1.53 (2.356) 28 10.877
0.00
Table 7:
Mean scores (+SD’s) and results of parametric comparisons using multiple t-tests for
independent samples between the four participant groups for California Verbal Learning
Test_7 (correct, intrusions, semclusters).
Variable Healthy Patient df t and p

5CARDIOVASCULAR DISEASE AND COGNITIVE IMPAIRMENT
2-tailed
CVLT7SDFRcorrect 10.93 (1.870) 7.40 (2.197) 28 4.743
0.00
CVLT7SDFRintrusions 0.33 (0.617) 8.27 (2.120) 28 -13.914
0.00
CVLT7SDFRpersev .47 (0.915) 0.53 (0.640) 28 -0.213
0.819
CVLT7SDFRsemclusters 3.00 (1.254) 0.2667 (0.4577) 28 7.933
0.00
Table 8:
Mean scores (+SD’s) and results of parametric comparisons using multiple t-tests for
independent samples between the three participant groups for California Verbal Learning
Test_8 (correct, intrusions, semclusters).
Variable Healthy Patient df t and p
2-tailed
CVLT8SDCRcorrect 11.93 (1.624) 1.67 (0.900) 28 21.415
0.00
CVLT8SDCRintrusions 0.33 (0.617) 9.27 (1.163) 28 -26.28
0.00
CVLT8SDCRpersev 0.00 (0.00) 0.47 (0.516) 28 -3.5
0.002
Table 9:
Mean scores (+SD’s) and results of parametric comparisons using multiple t-tests for
independent samples between the three participant groups for California Verbal Learning
Test_9 (correct, intrusions, semclusters).
Variable Healthy Patient df t and p
2-tailed
CVLT9LDFRcorrect 11.80 (2.007) 0.00 (0.00) 28 22.769
0.00
CVLT9LDFRintrusions 0.33 (0.617) 9.60 (0.737) 28 -37.34
0.00
CVLT9LDFRpersev 0.47 (0.834) 0.27 (0.458) 28 0.814
0.422
Table 10:

6CARDIOVASCULAR DISEASE AND COGNITIVE IMPAIRMENT
Mean scores (+SD’s) and results of parametric comparisons using multiple t-tests for
independent samples between the three participant groups for California Verbal Learning
Test_10 (correct, intrusions, semclusters).
Variable Healthy Patient df t and p
2-tailed
CVLT10LDCRcorrect 12.40 (1.957) 0.20 (0.414) 28 23.625
0.00
CVLT10LDCRintrusions 0.60 (0.910) 10.47 (1.727) 28 -19.579
0.00
CVLT10LDCRpersev 0.00 (0.00) 0.53 (0.743) 28 -2.779
0.01
Table 11:
Mean scores (+SD’s) and results of parametric comparisons using multiple t-tests for
independent samples between the two participant groups for Semantic Test (corrects,
clusters).
Variable Healthy Patient df t and p
2-tailed
SemanticFtotcorrect 18.80 (4.945) 0.40 (0.632) 28 14.293
0.00
SemanticFtotclusters 3.67 (1.175) 13.20 (5.294) 28 -6.808
0.00
Table 12:
Mean scores (+SD’s) and results of parametric comparisons using multiple t-tests for
independent samples between the two participant groups for Phonemic Test (corrects,
clusters).
Variable Healthy Patient df t and p
2-tailed
PhonemicFtotcorrect 13.73 (3.595) 1.47 (0.743) 28 12.942
0.00
PhonemicFtotclusters 1.0667 (0.5396) 9.5333 (2.6421) 28 -12.109
0.00
Table 13:
Results of the linear regression analysis using the variables that have significant differences.

7CARDIOVASCULAR DISEASE AND COGNITIVE IMPAIRMENT
Unstandardi
zed
Coefficients
Standardiz
ed
Coefficien
ts
t Sig.
B Std.
Error Beta
(Constant) 0.509 0.203 2.513 0.022
age 0.002 0.002 0.043 1.57 0.135
ROCFTImRecall 0.01 0.004 0.095 2.432 0.026
ROCFTDelRecall 0.011 0.004 0.086 2.717 0.015
CVLT1_5persev -0.013 0.006 -0.059 -
2.283 0.036
CVLT7SDFRcorre
ct 0.019 0.006 0.102 3.317 0.004
CVLT7SDFRintrus
ions 0.01 0.007 0.088 1.419 0.174
CVLT8SDCRcorre
ct -0.009 0.007 -0.099 -
1.303 0.21
CVLT8SDCRintrus
ions 0.041 0.011 0.371 3.774 0.002
CVLT9LDFRintrus
ions 0.053 0.014 0.496 3.897 0.001
CVLT10LDCRpers
ev 0.034 0.023 0.039 1.508 0.15
PhonemicFtotcorre
ct -0.011 0.004 -0.14 -
2.471 0.024
PhonemicFtotcluste
rs -0.006 0.006 -0.053 -
0.906 0.378
A linear regression model is developed with the health status as dependent variable
and the variables that have significant mean differences as independent variable. However the
result was not considered as all the independent variables were insignificant and the adjusted
R2 was high enough which means the model was good fit however the explanatory variables
did not have the explanatory power (Appendix A.1 & A.2). In the next step, the insignificant
variables that have p-values greater than 0.5 were removed. This gives a new model with
significant explanatory variables and higher adjusted R2. Table 13 presents the improved
linear regression result where few independent variables are significant as the p-value of
corresponding coefficient of the incorporated variables that have significant differences, are

8CARDIOVASCULAR DISEASE AND COGNITIVE IMPAIRMENT
less than 0.05. So, it can be said that the health status depends on these variables and the
significant variables are recall and 2nd recall of Rey-Osterrieth complex figure test, persev of
California verbal learning test 1_5, correct responses of California verbal learning test 7,
intrusions of California verbal learning test 8 and 9 and total correct response of phonemic
(Waldstein & Elias, 2015). This variables influence the health status and the adjusted R2 is
better than other models (Appendix B). However, the model contains insignificant variable.
In the next step the insignificant variables were omitted and the new model comes with a
lower adjusted R2 the model is not considered in the analysis (Appendix C.1). The adjusted R2
of the presented model in table 3 is 0.995 which means that the model can predict the health
status with 99.5% accuracy while the next model’s adjusted R2 consists more errors in the
model as the value is less which is equal to 0.991 which indicates 99.1% accuracy (Appendix
C.1). This adjusted R2 makes the difference on the basis of which the model is selected and
interpreted as well.
Discussion
This study conducts a test first that are helpful in determining the cognitive
impairment of individuals that will be grouped as healthy and unhealthy individual. The
individuals participated in the test were administrated several cognitive tests depending on
the verbal, information processing, executive function and visual capabilities. The age is a
significant factor that is examined through the t-test whether the mean is different across
healthy and unhealthy individuals. The t-stat for age is t (28) = -3.62 with p=0.001 implies
that there exist an influence of age on the status of health of the participants. This result is
supported by many papers that studies the effects of age on cardio diseases (Araújo et al.
2015). The variables’ means that are significantly not equal to zero across healthy and
unhealthy individual, are the row total, digit back and digit symbol of Digit Symbol Test have
significant mean difference for healthy and unhealthy individuals along with the recall, 2nd

9CARDIOVASCULAR DISEASE AND COGNITIVE IMPAIRMENT
recall and true answers of Rey-Osterrieth complex figure test (Alagiakrishnan et al. 2016).
The California verbal learning test conduct in trail 5, trail 6, trail 7, trail 8, trail 9 and trail 10.
Except these variables there are few more variables such as correct response, intrusions and
semcluster of California Verbal Learning Test 1-5 and 7, correct response, intrusions and
persev in California Verbal Learning Test 8 and 10 and correct responses of California
Verbal Learning Test 9. The insignificant mean different of variables across health status are
true for the variables like 30-points screening test MoCa (Montreal Cognitive Assessment)
test has no significant mean difference that is the mean difference equals to zero. Thus the
test cannot identify the healthy and unhealthy participants.
Concentrating on the above discussion it can be said that the t-test concludes that the
variables with mean difference can influence and identify the health status of the participants.
The correct response in the California Verbal Learning test in trail 5, 7, 8, 9 and 10 has
significant mean difference. This means that unhealthy individuals performed more errors
than the healthy individuals’ performance. The unhealthy individuals presented higher
inability to concentrate which is related to an attention skilled task than a healthy individual
as the mean difference in the total score of Digit Symbol is significant (Steinmetz &
Rasmussen, 2016).
The model presented in the table 13 is improved linear model which explains the
association of independent variables that has significant mean difference. The variables with
less than 0.05 p-value that means significant at 5% significance level are recall and 2nd recall
of Rey-Osterrieth complex figure test, persev of California verbal learning test 1_5, correct
responses of California verbal learning test 7, intrusions of California verbal learning test 8
and 9 and total correct response of phonemic. It can be said that the recall of Rey-Osterrieth
complex figure test can significantly influence the health status (Lagraauw, Kuiper & Bot,
2015). This implies that the recall score is better for the healthy individual compared to the

10CARDIOVASCULAR DISEASE AND COGNITIVE IMPAIRMENT
score of unhealthy individuals. Similarly, total correct response in phonemic is higher for the
healthy individuals compared to the total correct response of unhealthy individuals. The
linear model is best fit so it can predict the health status of an individual by using the values
of significant variables. The scores of Rey-Osterrieth complex figure test, California verbal
learning test 1_5 and the other significant trails are enough to predict the health of an
individual which is also studied in few related research (Chen et al. 2015).
The limitation of the study is using a very small number of observations which
contains only 30 observations. The future work should collect a large number of data to draw
a stronger relation and better results. The study should include more scientific tests to reach a
conclusion that helps to find the origin of reasons behind being unhealthy.
The further study should focus on adding more analytical tests like MRI. The study
should focus to find how the visual memory, verbal skills are significantly affective and in
the contrary the age is not significant for the health status (Alkan et al. 2017). This can help
to improve the individuals’ healthy life by providing the information about the health status
and the treatments or measures to deal with the unhealthy situations.
Conclusion
The study shows an important statistical difference between the healthy controls and
unhealthy aspects of cognitive area for example, verbal fluency, memory and visual attention,
language range capabilities, mental state appearance like attitude, behaviour, speech,
perception and insight. This is nothing but the significant role of adults with CVD on
cognitive function. The individuals with CVD performs worse in the cognitive test and ROC
test (Harrison et al. 2017). Hence, the survey can help individuals and the studies to inform
further about their health condition as well as this can spread awareness about the suffering
from CVD health conditions, cause and effects of CVD. However, the study is limited in

11CARDIOVASCULAR DISEASE AND COGNITIVE IMPAIRMENT
terms of robust analysis as it uses only 30 observations for the research. Otherwise, this can
help the future studies and in the scientific researches by generating information and insights
to the relevant surveys and thus can contribute in the scientific field to prevent the Chronic
cardiovascular disease. Moreover, an awareness program on adopting healthy habits to
prevent CVD and improving daily nutrition accordingly could be beneficial for the
individuals and an achievement by the scientist.