Get Permission Dharam, Gupta, Nilanshu, Sood, Kumar, and Panda: An intergenerational analysis of cognitive impairment in healthy elders


Introduction

The Montreal Cognitive Assessment (MoCA) is a test that was designed as a rapid screening instrument for mild cognitive dysfunction. MoCA is a tool which takes about 10 minutes to administer making it a practical tool to use in a clinical setting. It assesses different cognitive domains including attention and concentration, executive functioning, memory, language, visuoconstructional skills, conceptual thinking, calculations and orientation.1  MoCA is freely available for noncommercial, clinical, and academic purposes. MoCA due to its increased sensitivity for detecting patients with cognitive impairment is widely used in clinics.2, 3 Many of the elements are familiar or similar to other tests of cognitive function. Visuospatial abilities are assessed using a clock-drawing task and a trail-making task which is said to be useful in assessing fitness to drive. Attention, concentration and working memory are evaluated using a sustained attention task (target detection using tapping), a serial subtraction task and digits forward and backward. The MoCA also measures a wider range of abilities including executive functions.4 The high-level cognitive abilities are required for the implementation of goal directed behavior. These activities demand high executive functioning which depend largely on the integrity of frontal lobe and its associated structures. It is generally agreed that intact executive functioning is necessary for efficient execution of a plan. To complete the testing a subject needs to first perceive the stimulus, than do its processing and than respond to the stimulus. Both sensory perception and processing speed decline with age, thus impacting test performance in many cognitive domains. The total possible score in MoCA is 30 points; a score of 26 or above is considered normal. According to the validation study (Nasreddine et al., 2005), the sensitivity and specificity of the MoCA for detecting Mild Cognitive Impairment (MCI) (n=94 subjects) were 90% and 87% respectively.5

Cognitive abilities peak in 30s, plateau through 50s, 60s and slow decline typical for late 70s.6, 4, 2, 3 Chief complaint of cognitive decline such as memory and computing problems in Middle-aged and elderly people increase with age. Activities of daily living are impacted in varying degrees, with dementia in most severe cases, which is hard to deal with and may brought heavy burden to society and people's living conditions. Therefore, more research should be concentrated on early warning signals of cognitive decline. The main aim of this study was to assess the cognitive ability among the normal adults and among healthy elders and to compare the MoCA scores between normal adults and healthy elders.

Materials and Methods

It was a retrospective study. The data collection done at unit of audiology and speech language pathology at a tertiary care center in North India during 2011 and 2012 was analyzed. Participants were recruited from a geriatric neurology outpatient clinic and from general community.

Participants

Two groups of participants were included in the study. Group I included 18 elderly people (aged 62 to 82 years, with average age 78 years) with 10 males and 8 females. The participants had varied level of education .33.3 % of individuals had 12 years of education, while 66.7% had more than graduation level of education. Group II included normal 18 healthy adults (10 males and 8 females) with aged 22to 28 years, with average age 25 years). They all are graduates or post graduates.

Inclusion criteria

A community sample of older and younger adults without any history of neurological impairment or mood disorder or any psychiatric issues. The group of healthy elders and adults should be from high socioeconomic status.

Exclusion criteria

The adults with any neurological disorder or head trauma or any debilitating disease illness or with any significant history which can cause cognitive impairment are excluded from the study.

Procedure

This study was conducted at tertiary care center in North India, where each elderly individual underwent approximately 30 min of cognitive screening. At the single study session, informed consent was obtained by one of the assessors. The participants provided information about their age, gender, and highest level of education. A geriatric psychologist determined the diagnosis of a mood or neurocognitive disorder if applicable based on DSM-5 criteria. For all of the study participants MoCA was administered first. This paper-and-pencil assessment requires approximately 10 min to administer, and is scored out of 30 points. The cognitive domains assessed include: visuospatial skills, executive functions, memory, attention, concentration, calculation, language, abstraction, memory, and orientation. The three versions of the MoCA and their instructions are available on the official MoCA website (http://www.mocatest.org/). For this study, both assessors used the standard English version 1 (original) MoCA test with its associated instructions, to ensure accurate administration.

Data analysis

Raw scores for MoCA for each participant were recorded for the MoCA. No additional point was given on the MoCA for participants with 12 years of education. Cognitive status was defined by the number of errors on the 30 points Montreal Cognitive Assessment (MoCA) test; a score of 26 or above is considered normal. The error count was chosen to parallel the deficit count score in the adults and elders.

Results

In this study the mean MOCA score was 15.6± 4.9 for group1 which is lower than the average MoCA score of healthy adults i.e. group 2 where it was 28.2±1.5. On average, the chance of making errors increased from minimum 33.3% to maximum 100% in several cognitive domains of elderly as compared to the number of errors in adults. Changes in cognitive status were observed with higher percentage of errors among the elderly age group in short term memory recall task especially. Delayed recall 88.8% in males (N=10) and 100% in females (N= 8), Attention, Forward order 33.33% in both (M=10) and (F=8), Backward order 44.4% (M=10) and 33.3% (F=8), list of letters 44.4% (M=10) and 55.5% (F=8) and subtraction 77.7% (M=10) and 66.6% (F=8), Abstraction 88.8% (M =10) and 77.7% (F=8), Visuo-constructional (line drawing 44.4% (M=10) and 66.6% (F=8), Copy 77.7 % (M=10) and 44.4% (F=8) and Clock (Contour 44.4% (M=10) and 33.3% (F=8), numbers 55.5% (M =10) and 33.3% (F=8) and hands 55.5% (M=10) and 33.3% (F=8). and language (repeat 77.7% (M=10) and 66.6% (F=8), Fluency, 55.5% (M=10) and 66.6% (F=8). The naming and orientation were least impaired and there was no impairment found in the adults of north India. On the average of all normal adults were found more than 26 MoCA scores. These results show significant changes between healthy elderly and normal adults. The proportional test and two sample wilcoxon rank-sum test is applied for statistical analysis to compare the various cognitive domains between the healthy elderly and normal adults. The analysis of proportional test and wilcoxon rank-sum test is shown in table 1, 2,3 & 4. As expected the scores of healthy elderly group is significantly lower than normal adult group (p<0.05). It is most significant in the areas, copy (P=-3.98,P>Z=0.00), clock [numbers (P=-3.21, P>Z=0.001, contour (P=-3.21P>Z=0.001, hands (P=-3.21, P>Z=0.001)] attention [forward order (P=-2.68, P>Z=0.007), Backward order (P=-2.95, P>Z=0.003)], language [repeat (P=0.139, P>Z=0.00) fluency (P=0.194,P>Z=0.0001)], abstraction (P=0.165,P>Z=0.002, memory P=0.065, P>Z=0.0000) and less significant in list of letters (P=-1.37, P>Z=0.171) and naming (P=0.444, P>Z=0.1515) and more significant in orientation (P=0.5000, P>Z=0.000).

Table 1

Comparison of visuospatial and attention variables among normal adults and healthy elderly.

Variable

Mean

SD

P

P>Z

Visuospatial

Line drawing

1178511

LD1

.5

LD2

.66666667

1111111

Diff

-.1666667

1619709

Under Ho:

1643355

-1.01

0.310

Copy

Copy1

.3888889

1149044

Copy2

1

0

Diff

-.6111111

1149044

Under Ho:

1535474

-3.98

0.000

Clock

Clock

Contour1

5555556

.1171214

Contour2

1

0

Diff

4444444

.1171214

Under Ho:

.1385799

-3.21

0.001

Number1

5555556

.1171214

Number2

1

0

Diff

4444444

.1171214

Under Ho:

.1385799

-3.21

0.001

Hands1

5555556

.1171214

Hands2

1

0

Diff

4444444

.1171214

Under Ho:

.1385799

-3.21

0.001

Attention

Forward order

FO1

6666667

.1111111

FO2

1

0

Diff

3333333

.1111111

Under Ho:

.124226

-2.68

0.007

Backward order

BO1

61111111

.1149044

BO2

1

0

Diff

3888889

.1149044

Under Ho:

.1319241

-2.95

0.003

List of letters

ll1

5

.1178511

ll2

7222222

.1055718

Diff

2222222

.1582223

Under Ho:

.1624993

-1.37

0.171

Table 2

Comparison of naming, memory and subtraction variables among normal adults and healthy elders (Two sample wilcoxon rank-sum test)

Variable

N

Rank sum

Expected

Z

Prob>Z

P{naming group(1>2)}

Unadjusted Variance

Adjustment For ties

Adjusted variance

Naming

1 Group

18

315

333

2 Group

18

351

333

Combined

36

666

666

-1.434

0.1515

0.444

999.00

-841.50

157.50

1 Group

18

192

333

Memory

2 Group

18

474

333

Combined

36

666

666

-4.569

0.0000

0.065

999.00

-46.76

952.33

1 Group

18

226.5

333

Subtraction

2 Group

18

439.5

333

Combined

36

666

666

-3.733

0.0002

0.171

999.00

-184.89

814.11

Table 3

Comparison of language variables among normal adults and healthy elders

Variable

N

Rank sum

expected

Z

Prob>Z

P {lang Group (1>2)}

Unadjusted Variance

Adjustment For ties

Adjusted variance

Language

Repeat

1 Group

18

216

333

2 Group

18

450

333

Combined

36

666

666

-4.354

0.0000

0.139

999.00

-276.94

722.06

Fluency

1 Group

18

234

333

2 Group

18

432

333

Combined

36

666

666

-3.924

0.0001

0.194

999.00

-362.57

636.43

Table 4

Comparison of abstraction & orientation variables among normal adults and healthy elders

Variables

N

Rank sum

expected

Z

Prob>Z

P{abstract group(1>2)}

Unadjusted Variance

Adjustment For ties

Adjusted variance

1 Group

18

224.5

333

2 Group

18

441.5

333

Combined

36

666

666

-3.711

0.0002

0.165

999.00

-144.00

855.00

Orientation

1 Group

18

333

333

2 Group

18

333

333

Combined

36

666

666

0

0.0000

0.5000

999.00

-999.00

0.00

Discussion

We found that the use of the MoCA – was a valid cognitive screening method for complex mental capacity assessment. These cognitive screening tests provide useful information about an individual’s cognitive state. In this study we have administered the MoCA on the normal adults and healthy elderly. First, we tried to find out the cognitive deficits with age. Our data must be interpreted with caution. This is not a comprehensive measure of all aspects of brain function. Cognitive aging is obviously more complex than errors on the MoCA. Even though, the data suggests that in some fundamental ways, brain aging corresponds to a more general pattern of aging seen in our earlier studies.6, 4

We observed the differences in the MoCA scores of healthy elders and normal adults.7 We have seen that the MoCA scores of healthy elders were decreased in all the cognitive domains like attention and concentration, executive functioning, memory and orientation. In this way, the data potentially contributes to our understanding of the cognitive impairment with aging. Donald L Round suggested similar findings in his own study.8, 7, 9 The high fit suggests that, at some level of deficit accumulation, the number of deficits is more important than exactly which ones are present. If so, this has implications for the way that we think about the impact of specific diseases in aging, in the face of many other decrements. As many studies have cited poor MoCA score for Dementia and Alzheimer’s diseases which corresponds to definite cognitive impairment.8, 7 of note, the introduction of separable background and incremental parameters also allows us to explore whether all risk factors that are associated with late life decrements, such as cognitive impairment, are equally associated with variability in both background and increments. These investigations have the potential to inform the modeling of ageing, perhaps by distinguished more fixed factors from more mutable ones.

Secondly, as the MoCA scores shown in results were more than 26 which suggest there was no significant cognitive impairment among normal adults. The results of the present study support the results of earlier investigations.

Thirdly, there was significant cognitive impairment between healthy elders. The results of MoCA scores of healthy elderly group is significantly lower than normal adult group (p<0.05). This could be because of structural and functional changes in brain at the level of neurons, synapses and hippocampus size. With increase in age atrophy of hippocampus and other neuronal degeneration occurs which is often associated with other factors like diabetes mellitus, hypertension, obesity, hypoxic brain injury further declining cognitive abilities.10, 11, 12, 13

Conclusion

In total 36 subjects’ healthy elders (n=18) and normal adults (n=18) the number of errors in a cognitive test corresponded to age-related changes in deficits. First, we tried to find out the cognitive deficits with age. Secondly, there was no significant cognitive impairment among normal adults.10, 11

Thirdly, there was significant cognitive impairment between healthy elders and normal adults (p<0.05). Present study suggests that there is a definite cognitive impairment among healthy elders of high socioeconomic status. Age has a significant influence on MoCA score in older adults. Hence there is a need for age specific stratification in cut-off scores. In our study more than 90% of the subjects scored less than the current accepted cut off score. These findings highlight the need for large scale population studies for defining the cut-off score for MOCA in our population. The poor MoCA scores are not always associated with Dementia and Alzheimer’s diseases or any other geriatric syndromes which corresponds to definite cognitive impairment. This may be the reason of maladjustment of geriatric population in today’s family system. We should always look for the cognitive aspects among healthy elders for adequate adjustment.12, 13

Future Implications: The future implications of this study are to study the limitations of the Western instrument and non-familiarity of the items of the test in North Indian elderly even though they understand and speak the English language. There is a tremendous need to develop cultural and language specific tool to measure the real cognitive decline in the elderly population.

Source of Funding

None.

Conflict of Interest

None.

References

1 

T Dai A Davey J Woodard L S Miller Y Gondo S H Kim Sources of variation on the mini-mental state examination in a population-based sample of centenariansJ Am Geriatr Soc2013619136976

2 

F Newcombe Missile Wounds of the Brain: A Study of Psychological DeficitsOxford University PressLondon1969334

3 

A L Benton Differential behavioral effects in frontal lobe diseaseNeuropsychologia1968615360

4 

B C Stephan T Minett P Siervo L G Mckeith Diagnosing mild cognitive impairment (MCI) in clinical trials: A systematic reviewBMJ Open2013615360

5 

Z S Nasreddine N A Phillips V Bédirian S Charbonneau V Whitehead I Collin MoCA: a brief screening tool for mild cognitive impairmentMontreal Cogn Asses2005534695704

6 

H C Rossetti L H Lacritz M Cullum C Weiner Normative data for the Montreal Cognitive Assessment (MoCA) in a population-based sampleNeurology2011171312725

7 

M F Folstein S E Folstein P R Mchugh Mini-mental state”: a practical method for grading the cognitive state of patients for the clinicianJ Psychiatr Res19751239002632

8 

D R Roalf P J Moberg S X Xie D A Wolk S T Moelter S E Arnold Comparative accuracies of two common screening instruments for classification of Alzheimer's disease, mild cognitive impairment, and healthy agingAlzheimers Dement20139552966

9 

D M Round B Cullen M Allerhand D J Smith D Mackay J Evans Cognitive Test Scores in UK Biobank: Data Reduction in 480,416 Participants and Longitudinal Stability in 20,346 Participants. PLoS OnePLoS One20161144844168PMCID

10 

J C Morris J L Price Pathologic correlates of nondemented aging, mild cognitive impairment, and early-stage Alzheimer's diseaseJ Mol Neurosci200117210118

11 

S Gauthier B Reisberg M Zaudig Mild cognitive impairmentLancet20063679518126270

12 

M Fotuhi D Do C Jack Modifiable factors that alter the size of the hippocampus with ageingNat Rev Neurol201284189202

13 

D L Murman The Impact of Age on CognitionSemin Hear201536311121



jats-html.xsl


This is an Open Access (OA) journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.

  • Article highlights
  • Article tables
  • Article images

Article History

Received : 09-03-2022

Accepted : 10-05-2022


View Article

PDF File   Full Text Article


Copyright permission

Get article permission for commercial use

Downlaod

PDF File   XML File   ePub File


Digital Object Identifier (DOI)

Article DOI

https://doi.org/10.18231/j.agems.2022.005


Article Metrics






Article Access statistics

Viewed: 426

PDF Downloaded: 181



Medical Abbreviation List