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APP| Published By AEIRC| https://doi.org/10.29052/2412-3188.v7.i1.2020.31-38 
 

Ann. psychophysiol. 
ISSN 2412-3188 (Online) | 2410-1354 (Print) 

Original Article                                                                                  

Evaluating Age-related Cognitive 
performance; An Observational Pilot Study 
Aiman Khan, Aimon Ashraf, Huda Siddiqui, Khadija Ahmed, Fatima Ali, 
Laveeza Azam, Fariha Akbar & Huma Bugti 
Psychophysiology Research Lab, MAHQ Biological Research Centre,  
University of Karachi.  

 

Abstract 
Background: To the best of our knowledge, the general population of Pakistan has 
never been evaluated for age-related cognitive performance. We aimed to 
determine the decline in cognitive abilities using the Mini-Mental State 
Examination (MMSE) and Mini-Cognition (Mini-Cog) in the three age brackets, i.e. 
younger, middle-aged and older adults. 
Methodology: This cross-sectional study was conducted over a sample of 200 
subjects (both male and female) divided into three different groups with respect to 
their age, i.e. younger, middle-aged and older adults. For cognitive assessment, 
MMSE and Mini-Cog were used with predetermined cut-off values. A point was 
scored for each correct answer based on the participant’s familiarization of 
environment, memory, speech, and ability to follow instructions to read or write. 
The collected data were analyzed using SPSS version 22.0. 
Results: Based on the study findings, MMSE suggested that 2.5% of participants 
had severe cognitive impairment, and 23% had mild cognitive impairment. Of 
these, 23 participants were in between 56 to 75 years of age, indicating increased 
cognitive decline among older adults. The mean MMSE score was 26.58 among 
young adults, which further decreased to 24.06 among older adults. The results of 
the regression analysis displayed that age, occupational load and educational 
levels were independent predictors of cognitive performances (higher MMSE 
score) (p<0.05). Besides for Mini-Cog scores, only education and occupation were 
the significant predictors.   
Conclusion: This pilot study determining the cognitive performance in different 
age groups yielded positive outcomes. Both MMSE and Mini-Cog findings were 
comparable and indicated that there was a significant age-related cognitive decline 
which was comparatively more pronounced among males than females. However, 
further descriptive studies might help in defining the appropriate and timely 
screening of cognitive abilities using MMSE and Mini-Cog. 
 

Keywords 
Cognitive Performance Decline, Ageing, Mini-Mental Status Examination 

(MMSE), Mini-Cognition (Mini-Cog). 

 

Citation: Khan A, Ashraf A, Siddiqui H, 
Ahmed K, Ali F, Azam L, Akbar F, Bugti 
H. Evaluating Age-related Cognitive 
performance; An Observational Pilot 
Study. APP. 2020; 7(1):31-38 
 
Corresponding Author Email: 
humayousaf786@outlook.com 
 
DOI: 10.29052/2412-3188.v7.i1.2020.31-38 
 
Received 12/03/2020 
 
Accepted 13/08/2020 
 
Published 01/10/2020 
 
Copyright © The Author(s). 2020 This  
 is an open access article distributed 
under the terms of the Creative 
Commons Attribution 4.0 International 
License, which permits unrestricted use, 
distribution, and reproduction in any 
medium, provided the original author 
and source are credited.  
 

 

Funding: The author(s) received no 
specific funding for this work. 

Conflicts of Interests: The authors have 
declared that no competing interests 
exist. 
 

http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)


 

   

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Introduction  
Cognitive performance refers to the 
acquisition, deposition, assimilation, and 
utilization of information relevant to the 
surrounding circumstances and performing 
accordingly, and it is critical for information 
processing, integration, and responsiveness1. 
Although there are certain brain areas 
involved in reasoning that develop with age, 
generally, it is evident that memory, 
processing, and functioning decreases with 
increasing age either as a predetermined 
physiological mechanism or due to any 
underlying disease2. This age-related 
cognitive decline is associated with 
decreasing brain function as a result of 
vascular damage or neurodegenerative 
conditions. If it went undiagnosed, it might 
further lead to unfavourable conditions. 
Therefore, various screening tests are 
performed for preliminary assessment of 
cognitive impairment in order to diagnose 
and treat the condition before the 
development of serious outcomes3. The 
appropriate diagnosis within the 
recommended time duration plays an 
important role in devising a suitable 
therapeutic plan for cognitive impairment, 
and it prevents already the feeble body of 
aged individuals from being adversely 
affected by the severe cognitive disorders4. 
 
Among various cognitive performance 
screening tools, the MMSE is globally used to 
determine any alterations in the normal 
physiology of the brain. MMSE is of immense 
importance in evaluating the impacts of 
socio-demographic characteristics on 
cognitive abilities, i.e., lower education and 
increasing age, which yield lower cognitive 
outcomes5. It has a certain set of questions 
that analyses the individual’s orientation, 
memory, speech, and ability to follow 
instructions to read or write6. Such a tool with 
a specific scoring method is essential to 
screen and predict future development of 
degenerative diseases such as Alzheimer’s 
disease based on their contemporary 
cognitive abilities7,8.  

Considering the necessity of MMSE usage in 
older patients of dementia due to its 
rationality and authenticity, it is used in 
primary care centers to gauge the extent of 
their cognitive decrement, lesser ability to 
carry out fundamental activities, and 
worsening psychomotor actions9. Also, its 
electronic version has been designed to be 
used at a comfortable and convenient setup 
of personal accommodations10. In one such 
mental health program, a pronounced 
cognitive decline is observed in elderly 
patients, i.e., 55-74 age range, with MMSE 
score < 17, and also such trend is observed in 
people with an education level less than 
grade 8 in comparison to the patients of age 
range 35-54 years. Although, a cut-off point 
of < 23 is used in the studies of MMSE to 
determine mild incongruences in cognitive 
functions11. Whereas, such optimal value to 
determine decreasing cognitive functions is 
affected by increasing age12 and by the 
population under observation13. 
 
While the Mini-Cog scale is comparatively a 
simpler tool developed by Borson et al., in 
2000, for the detection of cognitive 
impairment among the elderly14, it was 
primarily developed with the aim to improve 
the diagnostic evaluation among dementia 
patients15. The reported sensitivity and 
specificity of the tool are 76 to 99% and 89 to 
93%, respectively14,16,17. The Mini-Cog tests 
the short term memory with three-word 
recall, and it also includes the Clock Drawing 
Test (CDT). In comparison to other 
comprehensive assessment tools, Mini-Cog is 
easier and provides the overall assessment of 
cognitive functions, including memory 
testing, structural concepts, and executive 
functioning. 
 
Our aim was to examine the cognitive 
performance among different age groups, for 
which the age-wise declination in the 
cognitive abilities was assessed. The 
secondary objective was to assess the change 
in the cognitive performance with respect to 
gender, education level, and the occupational 
load. 



 

   

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Methodology 
An observational pilot study was conducted 

over a sample of 200 participants of three 

different age groups, i.e. 15 to 35 years 

(Young Adults), 36 to 55 years (Middle-

Aged), and 56 to 75 years (Older Adults). The 

study continued for a duration of 3 months, 

and data was collected from various sites as 

per the sample accessibility including 

University of Karachi, Markaz-e-Umeed, and 

Koohi Goth. The study complies with the 

Helsinki Declaration of 1975 and other 

modified proclamations. All participants 

between 15 to 75 years of age of both genders 

and with no severe physiological and 

psychological dysfunctions were included in 

the study. In contrast, those with severe brain 

trauma, injury, and those with any 

physiological disabilities were excluded from 

the study sample.  

 

The literacy rate and educational status were 

also assessed, and < 3 years of education was 

categorized as low education, 4 to 7 years as 

medium education, and ≥ 8 years as high 

education. Cognitive domains were 

measured using MMSE18 and Mini-Cog14. All 

the data concerning the subject’s socio-

demographic characteristics and cognitive 

performance was noted in a pre-designed 

questionnaire. For MMSE scoring, the 

maximum total score was 30, and the score 

between 0 to 9 was indicative of severe 

cognitive impairment, 10 to 24 as mild to 

moderate cognitive impairment, and 25 to 30 

as no cognitive impairment. While in the 

Mini-Cog, the maximum score of Mini-Cog 

was 9. 1 point assigned for each correctly 

recalled word after CDT where participants 

scoring 0 to 4 were defined having cognitive 

impairment, score 9 suggested no cognitive 

impairment while participants having 

intermediate scores like 5 to 8 were classified 

based on CDT. Participants with normal CDT 

was indicative of no cognitive impairment, 

while abnormal CDT suggested possible 

cognitive impairment. 

 

The data was statistically analyzed using 

SPSS version 22.0, where all qualitative 

variables were presented using frequency 

and percentages, and quantitative variables 

were given as mean and standard deviation. 

A Chi-square test was used for significance 

testing, and multiple linear regression 

analysis was performed to determine the 

possible predictors of cognitive impairment. 

P-value < 0.05 was considered statistically 

significant. 

Result 
Based on the study findings, 3.5% of 
participants had a low educational level, 
16.5% were labelled as a medium, while 
79.5% had a high education level, as shown in 
table 1. The mean MMSE score of the sample 
was 25.22 ± 3.49, and the Mini-Cog score was 
4.34 ± 0.766. 

 
Table 1: Demographic characteristics of study participants 

Variables   n=200 

Age (Years)  42.45 ± 16.73 

Age Categories   Younger Adults  69(34.5) 

Middle Age 64(32.0) 

Older Adults 67(33.0) 

Gender  Male 90(45) 

Female 110(55) 

Marital Status Married 142(71) 

Unmarried 58(29) 

Employment Status Working 90(45) 

Non-working 110(55) 



 

   

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Occupational Load   Moderate 137(68.5) 

High 20(10) 

Low 43(21.5) 

Education Level Low  7(3.5) 

Medium  33(16.5) 

High  159(79.5) 
*Values are given as Mean ± SD or n(%) 

 
The majority of participants displayed no cognitive impairment, i.e. 74.5% had no cognitive 

impairment followed by mild cognitive impairment among 23% participants, and 2.5% had severe 

cognitive impairment. Around 98.5% of participants had no cognitive impairment as per the scores 

obtained from the Mini-Cog tool, while only 1.5% displayed cognitive impairment. 

Table 2: Shows the distribution of study participants based on  
MMSE & Mini-Cog scores 

Scoring   n % 

MMSE  Severe cognitive Impairment (Score 0 to 9) 5 2.5 

Mild cognitive Impairment (Score 10 to 24) 46 23.0 

No cognitive Impairment (Score 25 to 30) 149 74.5 

Mini-Cog Cognitive Impairment (Score 0 to 4) 3 1.5 

No Cognitive Impairment (Score 9) 197 98.5 

 

 
 
Figure 1 & 2 shows the mean decline in cognitive abilities with increasing age. The mean MMSE score 
was 26.58 among young adults, which further decreased to 24.98 among middle-aged participants 
and, finally, 24.06 among older adults. Similar age-related declination was observed through Mini-
Cog scores, i.e. the score decreased from 4.76 among younger adults to 4.16 among older adults. 
 
Multiple linear regression analysis was performed taking MMSE score as the dependent variable 
against age, gender, education and occupational load (independent variables). A significant effect of 
age (β=-.005, p=0.032), occupational load (β=-.084, p=0.042), and educational level (β=.173, p=0.012) 
on cognitive performance (measured using MMSE) were observed. 
 

Table 3: Multiple linear regression analysis for independent predictors of  
individual’s MMSE score 

Variables  N=200 (Adj R2=.091) 

Beta 95% CI p-value 

Age -.005 -.010,.000 .032* 

Gender .105 -.045,.254 .169 

Figure 2: Age-associated decline in the mean 
Mini-Cog Score 

 

Figure 1: Age-associated decline in the mean 
MMSE Score 

 



 

   

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Marital Status .006 -.138,151 .932 

Employment .099 -.060,.257 .220 

Occupation -.084 -.165,-.003 .042* 

Education .173 .038,.308 .012* 
*Adj R2-Adjusted R2; CI – Confidence Interval  
*p-value < 0.05 is considered significant  

 
Using Mini-Cog, it was found that only occupational load (β=.138, p=0.030) and educational level  
(β=.348, p=0.001) had a significant effect on cognitive performance.   

 
Table 4: Multiple linear regression analysis for independent predictors of  

individual’s Mini-Cog Score 

Variables  N=200 (Adj R2=.073) 
Beta 95% CI p-value 

Age -.004 -.011,.003 .227 

Gender .033 -.197,.263 .779 

Marital Status .061 -.161,.283 .586 

Employment .117 -.126,.361 .342 

Occupation .138 .013,.262 .030* 

Education .348 .140,.556 .001* 
*Adj R2-Adjusted R2; CI – Confidence Interval  
*p-value < 0.05 is considered significant  

 

Discussion 
Our findings truly support the hypothesis, 

suggesting a significant age-associated 

decline in the cognitive functions. The results 

supported the widely accepted notion that 

MMSE and Mini-Cog (CDT) can be used by 

professionals for observation of the cognitive 

decline in relevance to increasing age19. 

Considering the alarmingly growing 

population with many aged 65 and above, 

and most of them being affected with 

dementia-specific to age and gender, there is 

a need to diagnose any imminent 

neuropathology20. Therefore, the urge to 

develop a reliable and sensitive tool for 

distinguishing age-related cognitive changes 

and deterioration has become inevitable21,22. 

As per the reliability is concerned, a study 

indicated that the majority of the older 

individual had a low MMSE score, which was 

further supported by their death, indicating 

that MMSE is among the most reliable 

screening methods for cognitive decline with 

age23. Similarly, a correlation was found 

between alkaline phosphatase level and low 

MMSE score among Alzheimer’s patients of 

older age group suggesting neurocognitive 

mislaying24. Presently, both MMSE and Mini-

Cog are the most widely used, comparatively 

easier and consistent tools parallel to other 

comprehensive assessment tools used for 

screening of cognitive disabilities16,25. 

Although MMSE is quite popular in the 

majority countries but the preference is 

thought to be linked with shorter time 

duration for testing, i.e. 10 minutes, while on 

the other hand, Mini-Cog takes more time, 

but it is detailed and covers diverse cognitive 

aspects26.  

We have examined the cognitive decline 

among enrolled participants using both 

MMSE and Mini-Cog Scores, and it was 

tracked with respect to age, the mean MMSE 

score decreased from 26.58 among young 

adults to 24.06 among older adults, and the 

same was with the mean Mini-Cog Scores 

(Figure 1 & 2). This is also supported by the 

results of a similar study, participants < 75 

years of age had the mean MMSE score of 



 

   

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28.14 while those > 75 years had a mean score 

of 27.81 and CDT declined from 4.47 to 4.19 

among the two age groups4. In addition to 

age, the effects of gender, educational levels, 

and occupational load on cognitive 

functioning were also investigated. No 

significant gender-based variation was 

observed in the MMSE and Mini-Cog scores 

(Table 3 & 4). Shuba and Prakash, in their 

study, also displayed no association between 

the two variables. Moreover, a higher level of 

cognitive impairment was observed among 

males, i.e., mean MMSE score of 24.94 among 

males vs. 25.47 among females, and the same 

was for the Mini-Cog score (4.30 vs. 4.37). 

Other studies with similar findings 

suggested that this gender-based difference 

might be due to various environmental and 

occupational stressors4,27. 

Occupational load plays an important role in 

the overall cognitive performance, 

occupations requiring higher cognitive 

involvement are found to be associated with 

lower cognitive impairments due to the 

indulgence of a person in high cognitive 

activities28. Another study suggested that 

physical frailty has a significant impact on 

cognitive activities and mental health28. As 

per our results, the occupational load was 

significantly associated with cognitive 

performance, and participants with low to 

moderate occupational load had mild to 

severe cognitive impairment as compared to 

those with high occupational load (Table 3 & 

4). The educational level also had a 

significant impact on the cognitive abilities of 

the participants (p < 0.05). Mild cognitive 

decline was observed more among the 

participants with low to medium educational 

levels as compared to those with high 

educational years. A similar trend was 

observed by Ghavidel et al., in their study4.    

This pilot study provided an opportunity to 

investigate the age-associated cognitive 

decline and the impact of related factors, 

including occupational load and educational 

levels, among the people of Karachi, 

Pakistan. Although the findings are not the 

true presentation of the local data but to the 

best of our knowledge, no such study 

involving the local population of all three age 

groups, i.e. younger adults, middle-aged 

people, and older adults, has been conducted 

till now. Future research is recommended to 

present descriptive outcomes involving the 

impact of other influencers like comorbid 

conditions, smoking, and health associated 

habits that might be a significant cofactor for 

this cognitive decline other than ageing.           

Conclusion 
This pilot study revealed a noticeable decline 

in cognitive performance among older adults 

as compared to those of the middle-aged or 

young ones. Findings from both of our 

screening tools MMSE and Mini-Cog, were 

comparable and suggested that this age-

related cognitive impairment was more 

pronounced among males as compared to 

females. Other than that, there was also a 

significant effect of occupational load and 

educational levels on the cognitive abilities of 

the study participants. However, a large-

scale descriptive study is required to confirm 

this hypothesis and to endorse the use of 

initial screening of cognitive performance 

using the mentioned screening tools.    

Acknowledgment  
The authors would like to acknowledge Dr. 

Sadaf Ahmed for her assistance and support 

in designing this study. 

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