Pattern of Cognitive Impairment Among Community Dwelling Elderly in Egypt and Its Relation to Socioeconomic Status

doi:10.21203/rs.3.rs-3097804/v1

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Research Article

Pattern of Cognitive Impairment Among Community Dwelling Elderly in Egypt and Its Relation to Socioeconomic Status

https://doi.org/10.21203/rs.3.rs-3097804/v1

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Background

Cognitive decline is one of the aging health problems that strongly affects daily functioning and quality of life of older adults and threatening their independence with different levels of cognitive health among people from different socioeconomic groups.

Objective

To assess the prevalence and pattern of cognitive impairment among community dwelling elderly in Egypt and the contribution of socioeconomic status to inequality in cognitive impairment.

Material and Methods

This study involved 470 elderly participants ≥ 60 years, males and females. The Montreal Cognitive Assessment (MoCA) was used to assess the prevalence of cognitive impairment, Hachinski ischemic score (HIS) to investigate type of cognitive impairment, Ain Shams Cognitive Assessment (ASCA) to assess pattern of specific cognitive domain affection, and an Egyptian Socioeconomic status (SES) scale was used to describe the SES of participants.

Results

The prevalence of cognitive impairment was 50.2% that was distributed as 37.7% for MCI and 12.5% for Dementia. The most common type of cognitive impairment was degenerative type (47.8%). Pattern of specific domain affection among cognitively impaired subjects, ranged from 94% for visuospatial function to 12.7% for abstraction. Cognitive impairment was significantly associated with increasing age, female sex, marital status single or widow, low education and with increasing total number of comorbidities and positive family history of cognitive impairment. Cognitive impairment was mainly concentrated in the economically disadvantaged population (low educational level, non-occupied, limited computer use, low income and bad sanitation).

Conclusion

In Egypt, cognitive impairment is significantly prevalent and concentrated among those who are in low socioeconomic status. Increasing educational level of low SES population and improving their access to healthcare services will help to improve the inequity of cognitive impairment.

ASCA

MoCA

Pattern of Cognitive Impairment

Socioeconomic Status

Among the world's population, the elderly compromises a rapidly expanding demographic group, representing the fastest-growing segment. This age group exhibits a high vulnerability to a wide range of diseases compared to younger adults, with increase in the health burden associated with age-related disorders and diseases ^[1].

Cognitive impairment, as an age-related health problem, imposes a significant burden on families and caregivers. It emerges as a major challenge not only for healthcare systems but also for society as a whole, necessitating comprehensive strategies to address its impact ^[2].

Dementia predominantly affects older people, with global prevalence rates over the age of 60 years ranging between 5% and 7%, increasing with age with an estimate 20% of people over 85 years showing evidence of the disease ^[3].

With the rapid aging of populations in recent years, there is an anticipation of a substantial rise in the prevalence of cognitive impairment, making it a significant global public health concern ^[3]. Therefore, the World Health Organization (WHO) has designated dementia as a public health priority and has devised the global action plan on the public health response to dementia (2017–2025) with the aim of reducing the impact of dementia on individuals and communities ^[4].

The significance of cognition in maintaining functional independence as individuals’ progress through the aging process. Cognitive abilities serve as a fundamental cornerstone, enabling one to live independently, proficiently handle financial responsibilities, adhere to medication regimens, and drive safely. Moreover, the preservation of cognitive functions is vital for effective interpersonal communication, sensory information processing, integration, and appropriate responsiveness to others ^[5].

Under the broad umbrella of cognitive abilities, several distinct cognitive domains are present, each contributing to overall mental performance. These domains include attention, memory, executive function, language, and visuospatial abilities. With aging, each of these domains exhibits measurable decline ^[6].

Although cognitive abilities often decline with age, older people display a continuum of cognitive abilities that range from no impairment to the severe deficits that are seen in dementia. Mild cognitive impairment (MCI) is a stage of transition between ‘normal’ functional ability and a fullblown clinical picture of dementia ^[7].

As cognitive decline has a spectrum of presentations clinicians must distinguish dementia from normal aging, ageassociated cognitive impairment, MCI or other focal cognitive syndromes ^[8].

Indeed, numerous risk factors have been elucidated in relation to the onset of cognitive impairment. These encompass a range of factors, including biological, lifestyle, environmental, and pathological influences that are linked to specific medical conditions and diseases ^[9].

These factors can influence cognition through life in both positive and negative ways. Factors that contribute positively include engaging in higher education, social interactions, seeking intellectual stimulation, and maintaining regular physical activity. Conversely, factors such as limited educational attainment, insufficient physical activity, health problems, and substance abuse (including alcohol and drug misuse) can yield detrimental effects on cognitive function ^[10].

The impact of social determinants on cognitive health is a universal and enduring phenomenon that operates persistently and cumulatively. Imperceptibly, these determinants can shape the development of cognitive impairment by placing individuals within upper and lower limits of access to variety of resources ^[11].

Socioeconomic status (SES) serves as a comprehensive construct that encompasses an individual's social factors (e.g., formal education, occupational prestige) and economic factors (e.g., material possessions, income). It stands as a prominent factor from which life outcomes are derived, exerting significant influence ^[12].

The dynamic nature of SES extends through the entirety of an individual's lifespan, wherein a variety of socioeconomic indicators exert distinct influences on cognitive well-being. These multifaceted indicators interact synergistically, contributing to the onset and progression of cognitive impairment. This highlights the critical role played by multiple individual socioeconomic risk factors in shaping cognitive health ^{[13, 14]}.

In developing countries like Egypt, the distributional disparities in SES have been observed to influence the diversity in cognitive performance and rates of cognitive decline ^[11]. It is wisely to understand the contributing factors that give rise to varying levels of cognitive health within lower and higher socioeconomic groups.

So, the aim of this study is to examine the pattern of cognitive impairment and distribution of specific cognitive domain affection among community dwelling elderly living in Egypt and its relation to socioeconomic status.

A cross sectional study of 470 participants aged 60 years and older from community dwelling elderly. the sample size was calculated based on the average estimate of prevalence of cognitive impairment among community dwelling elderly in Egypt about 7.5%. A sample size of at least 470 participants produces a two-sided 95% confidence interval with a width equal to 0.050 when the sample proportion is 0.075. This sample was satisfactory to compare the SES mean score of the two groups by the two independent samples t-test with a moderate effect size of 0.5 at level of significance = 0.05 and power = 80%. The study populations were recruited from home visits, geriatric clubs and from patients and relatives attending outpatient clinics using a simple random method during the period from 1 May 2020 to 1 October 2022. Subjects with delirium, severe depression, acute illness or communication disability that interfere with applying the assessment tools e.g. severe hearing or visual impairment were excluded. Inclusion criteria included males and females’ community dwelling elderly (> 60 years old) who were willing to participate in the study. The study was accepted by Ain Shams University's Ethics Board, and each subject signed an informed written consent.

The following assessments were done for each participant:

Cognitive function assessment

we used Montreal Cognitive Assessment tool (MoCA) with a maximum score of 30. A score of 26 or more is considered normal, score of 19–25 is considered MCI and score of 18 or less in Alzheimer dementia ^[15].

We used (MoCA) test for educated subjects and (MoCA)-Basic for illiterate and low educated subjects using the Arabic versions of both ^[16].

For assessment of specific cognitive domain affection among cognitively impaired subjects, we used a new valid and reliable neurocognitive diagnostic evaluation battery that can evaluate specific domain affection in both educated and illiterate subjects under the name of Ain Shams Cognitive Assessment (ASCA) scale ^[17].

This scale includes the following cognitive subtests; paired associated test (verbal learning (VL), distractor interval (DI), delayed recall (DR)), Word recognition test (WRNP), Bender Gestalt (BG) copy and recall, Digit span forward (FW) and backward, set shifting line and time of trail making test, verbal fluency lexical and semantic, confrontation object naming (CN), cuing (stimulus or phonemic), abstraction and judgment.

These subtests can assess several cognitive domains including {memory (episodic, working, semantic and spatial), attention, executive function, language, visuospatial function, processing speed abstraction and judgment}. Each domain was assessed separately to see if it is normal or impaired. So, we used ASCA test to evaluate which domain is affected among cognitively impaired subjects.

In this study, we defined test and domain impairment as z-scores falling below − 1.5, equivalent to at least 1.5 standard deviations (SDs) below the mean of the normative population. This criterion aligns with the midpoint of the range (1–2 SD) suggested in the DSM-5 as a reference for mild cognitive disorders ^[18].

Type of cognitive impairment: Hachinski ischemic score (HIS) was used for differentiating major types of cognitive impairment, such as primary degenerative, vascular or multi infarct, and mixed type. The total score is determined: if < 4 suggests a degenerative type, if score 4–7 it is mixed type and if > 7 it suggests a vascular type ^[19].

Depression assessment: Patient Health Questionnaire-9 (PHQ-9) is a clinical tool for assessment of depression. Total Score for Depression Severity: 0–4 none or Minimal depression, 5–9 Mild depression, 10–14 Mild to Moderate depression, 15–19 Moderate depression, 20–27 severe depression. Participants with moderate or severe depression were excluded. The Arabic version was used ^[20].

Socioeconomic Status (SES): Egyptian Socioeconomic Scale was used for assessment of participants’ socioeconomic status (high, medium and low). The scale includes several subdomains and each domain has a specific score then the total score was calculated (maximum score = 48) and the cut-off points to be used for SES classification were: High level was indicated as at least 70% (≥ 33), Medium level as 40 to less than 70% (19–33), Low level as less than 40% (< 19) ^[21].

Statistical analysis

"The collected data underwent coding, tabulation, and statistical analysis using SPSS software version 22. Quantitative variables were described in terms of their mean, standard deviation (SD), and range. Qualitative variables were described by presenting the count and percentage. To compare qualitative variables between groups, the chi-square test was employed, and in cases where there was an expected cell count of less than five, Fisher's exact test was used. For comparisons of means among groups, Student's t-test or ANOVA was utilized as appropriate. Pearson's correlation coefficient (r) was employed to assess the correlation between numerical variables. All statistical tests were two-tailed, and the significance level was determined based on the probability (P) value, where P > 0.05 was considered insignificant, P < 0.05 was deemed significant, and P < 0.01 was regarded as highly significant. The analysis of ASCA subtests impairment using Z scores analysis, considering positive and negative deviations around the standardized Z score using the mean and SD of the normative Egyptian populations."

A total of 470 subjects were investigated in this study, the mean age of the study population was 66.32 years old with standard deviation ± 5.61. Most of them were males 72.13%, married 67.87%, have low education58.51% with no special habits of medical importance 52.77%.

The prevalence of cognitive impairment (CI) according to MoCA test examination of the studied population, was 50.2%. that was distributed as 37.66% were MCI and 12.55% were demented. By investigation of the type of cognitive impairment using HIS, it was found that degenerative type was the most common (47.88%) followed by mixed type (37.7%) then vascular type (14.4%).

By examination the pattern of distribution of specific cognitive domain affection among cognitively impaired subjects by ASCA scale, it was found that the most affected domain was visuospatial function (94%) followed by memory and language (88%) functions and the least was for abstraction function (12%) (Table 1).

With comparison of the cognitive performance across cognitive domains and the educational level it was found that working memory function was the most affected domain among the highly educated group followed by visuospatial and executive functions, while among illiterate and low educated group the visuospatial function was the most affected domain followed by language and semantic memory functions with significant difference between the two groups as regard all domains functions except for attention, abstraction and judgment (Fig. 1).

The prevalence of CI had a certain degree of inequality, the results showed that older age, female gender, marital status other than married (single, widow, divorced) and low educational level were significantly associated with CI.

Also, CI was significantly associated with increasing total number of comorbidity (≥ 3) and most of chronic medical conditions had a higher distribution among demented subjects than both MCI and normal ones with significant difference between them such as DM (54%, 45%, 37%), hypertension (64%,41%,37%), neurological disorders (42%, 16%, 7%) and sensory impairment (58%, 29%, 16%) respectively.

Also, CI was significantly associated with depressive status that most of cognitively impaired subjects (dementia or MCI) were having depression compared to normal subjects (44%, 39%, 12%) respectively for mild depression and (34%,14%, 4%) for mild to moderate depression with significant difference between the three groups.

Besides CI was significantly associated with positive family history of cognitive impairment that family history was positive in (20%) of demented subjects and (12.5%) in MCI subjects compared to only (6%) in normal ones.

The prevalence of CI was mainly concentrated in subjects with low and medium SES (Table 2). That demented subjects had a higher distribution of low SES level than both MCI and normal subjects while normal subjects a higher distribution of high SES level than both MCI and demented subjects with most of significance between normal and both MCI and demented subjects but no statistical significant difference between the MCI and demented subjects.

There was a statistical significance between cognitive function (normal, MCI, demented) and all SE domains except for family size and crowding index that cognitive impairment was significantly associated with low education, no occupation, low income, infrequent computer use and bad sanitation (Table 3).

With comparison between cognitive subdomain impairment by ASCA scale and SES level (high, low, medium) it was found that there was significant association between SES level and impairment in the following cognitive sub domains (episodic verbal recall, language and semantic memory, visuospatial and processing speed). Most of significance was between high and low SES group or medium and low one (Table 4).

There was a significant correlation between SES score most of ASCA tests with highest correlation with BG copy and recall followed by CN and set shifting lines.

Table 1

Discriptive analysis of cognitive domains function among CI subjects by ASCA scale with comparison of performance between high and low educated subjects.
		Education						Chi-Square
		low-Educated		High-Educated		Total		Chi-Square
		N	%	N	%	N	%	X²	P-value
Learning & verbal memory	Normal	121	79.61	43	51.19	164	69.49	20.604	< 0.001*
Learning & verbal memory	Abnormal	31	20.39	41	48.81	72	30.51	20.604	< 0.001*
Working memory	Normal	28	18.42	0	0.00	28	11.86	17.557	< 0.001*
Working memory	Abnormal	124	81.58	84	100.00	208	88.14	17.557	< 0.001*
Visuospatial	Normal	1	0.66	13	15.48	14	5.93	21.289	< 0.001*
Visuospatial	Abnormal	151	99.34	71	84.52	222	94.07	21.289	< 0.001*
Executive	Normal	58	38.16	14	16.67	72	30.51	11.786	0.001*
Executive	Abnormal	94	61.84	70	83.33	164	69.49	11.786	0.001*
Attention	Normal	42	27.63	17	20.24	59	25.00	1.577	0.209
Attention	Abnormal	110	72.37	67	79.76	177	75.00	1.577	0.209
Language &semantic memory	Normal	10	6.58	18	21.43	28	11.86	11.409	0.001*
Language &semantic memory	Abnormal	142	93.42	66	78.57	208	88.14	11.409	0.001*
Abstraction	Normal	135	88.82	71	84.52	206	87.29	0.898	0.343
Abstraction	Abnormal	17	11.18	13	15.48	30	12.71	0.898	0.343
Judgment	Normal	112	73.68	64	76.19	176	74.58	0.179	0.672
Judgment	Abnormal	40	26.32	20	23.81	60	25.42	0.179	0.672

Table 2

Comparison of cognitive function assessed by MoCA test with socioeconomic status (SES) level.
		MoCA test						Chi-Square		Chi-Square
		Normal(234)		MCI(177)		Demented(59)
		N	%	N	%	N	%	X²	P-value	N&M	N&D	M&D
SES level	High	63	26.92	19	10.73	4	6.78	61.338	< 0.001*	< 0.001*	< 0.001*	0.442
	Medium	160	68.38	111	62.71	35	59.32
	Low	11	4.70	47	26.55	20	33.90
ANOVA								F P-value		TUKEY'S Test
										N&M	N&D	M&D
SES score	Range	11–46		8–41		9–35		50.421	< 0.001*	< 0.001*	< 0.001*	0.129
	Mean ± SD	28.380 ± 6.278		22.983 ± 6.797		21.102 ± 6.082

Table 3

Comparison of cognitive function assessed by MoCA test with different Socio Economic (SE) domains
		MoCA test						Chi-Square
		Normal		MCI		Demented		Chi-Square
		N	%	N	%	N	%	X²	P-value
Mother education	Illiterate	103	44.02	123	69.49	39	66.10	42.326	< 0.001*
	Primary	62	26.50	28	15.82	17	28.81
	Preparatory	33	14.10	18	10.17	3	5.08
	Secondary	32	13.68	8	4.52	0	0.00
	University	4	1.71	0	0.00	0	0.00
Father education	Illiterate	29	12.39	53	29.94	21	35.59	59.194	< 0.001*
	Literate certificate	26	11.11	20	11.30	9	15.25
	Primary	49	20.94	26	14.69	4	6.78
	Preparatory	38	16.24	45	25.42	17	28.81
	Secondary	70	29.91	31	17.51	8	13.56
	University	21	8.97	2	1.13	0	0.00
	Postgraduate	1	0.43	0	0.00	0	0.00
Mother work	No	180	76.92	161	90.96	59	100.00	27.473	< 0.001*
Mother work	Yes	54	23.08	16	9.04	0	0.00	27.473	< 0.001*
Father work	No	11	4.70	26	14.69	17	28.81	29.799	< 0.001*
Father work	Yes	223	95.30	151	85.31	42	71.19	29.799	< 0.001*
Computer use	Never	77	32.91	138	77.97	53	89.83	115.985	< 0.001*
	Sometimes	144	61.54	39	22.03	6	10.17
	Lot of time	13	5.56	0	0.00	0	0.00
Per capital income	Lean not repaid	0	0.00	1	0.56	0	0.00	55.363	< 0.001*
	Big loan	5	2.14	6	3.39	3	5.08
	Small loan	28	11.97	59	33.33	14	23.73
	Enough only	94	40.17	81	45.76	30	50.85
	Enough and saving	107	45.73	30	16.95	12	20.34
Family size	6	50	21.37	45	25.42	20	33.90	7.880	0.096
	5	105	44.87	81	45.76	29	49.15
	< 5	79	33.76	51	28.81	10	16.95
Crowding index	2–4	134	57.26	111	62.71	41	69.49	3.369	0.185
Crowding index	< 2	100	42.74	66	37.29	18	30.51	3.369	0.185
Sewage disposal	No	3	1.28	13	7.34	6	10.17	12.857	0.002*
Sewage disposal	Yes	231	98.72	164	92.66	53	89.83	12.857	0.002*
Refuse disposal	No	45	19.23	86	48.59	26	44.07	42.489	< 0.001*
Refuse disposal	Yes	189	80.77	91	51.41	33	55.93	42.489	< 0.001*

Table 4

Comparison between cognitive sub domain impairment by ASCA scale and SES level.
		SES level						Chi-Square		Chi-square
		High(N:23)		Medium(N:146)		Low(N:67)		Chi-Square		Chi-square
		N	%	N	%	N	%	X²	P-value	H&M	H&L	M&L
Learning& verbal memory	Verbal learning	4	17.39	26	17.81	19	28.36	3.283	0.194	0.961	0.298	0.080
Learning& verbal memory	Verbal recall	3	13.04	35	23.97	25	37.31	6.604	0.037*	0.243	0.030*	0.044*
Working Memory	Working encoding	18	78.26	113	77.40	58	86.57	2.474	0.290	0.927	0.343	0.118
	Working spatial	20	86.95	136	93.15	66	98.51	4.671	0.097	0.300	0.083	0.101
	Working cuing	8	43.78	41	28.08	23	34.33	1.065	0.587	0.510	0.968	0.356
Executive Functions	Executive function	19	82.61	92	63.01	50	74.63	5.290	0.071	0.066	0.435	0.095
Executive Functions	Processing speed	1	4.34	18	12.33	18	26.87	9.816	0.007*	0.260	0.022*	0.009*
Attention		16	69.56	111	76.03	50	74.63	0.449	0.799	0.505	0.636	0.825
Language & Semantic Memory		16	69.56	128	87.67	64	95.52	11.112	0.004*	0.023*	0.001*	0.074
Visuospatial		14	60.86	94	64.38	61	91.04	17.503	< 0.001*	0.744	0.001*	< 0.001*
Abstraction		4	17.39	16	10.96	10	14.93	1.154	0.562	0.375	0.778	0.412
Judgment		3	13.04	36	24.66	21	31.34	3.143	0.208	0.219	0.087	0.306

Cognitive impairment (CI) includes a wide spectrum of cognitive decline arising from diverse etiologies, spanning the continuum from mild cognitive impairment (MCI) to the more severe form of dementia ^[22]. With the increasing proportion of elderly individuals within the population, CI emerges as a significant public health concern, posing threats to the independence of older adults and exerting profound challenges on the social security and healthcare systems ^[1].

The social determinants and its influence on cognitive health is universal, persistent and cumulative, which can imperceptibly affect the development of CI, and gradually shape the inequality in cognitive health ^[3].

The population under the study were 470 subject males and females aged 60 years and older. The mean age of the studied population was 66.32 years old with SD ± 5.6. Most of them were males, married with low educational level (illiterate or < 10-year education).

According to MoCA test examination of the studied population the estimated prevalence of CI in this study was 50.2% (236 participant) distributed as 37.6% had MCI and 12.5% were demented. That is consistent with an Egyptian study estimated the prevalence of CI in community dwelling elderly was 51.4% ^[23].

The prevalence of CI worldwide varies widely. In a systematic review study (80 studies) estimated the prevalence of CI that ranged between 5.1% and 41% with a median of 19.0% ^[24].

The literature presents a broad spectrum of reported prevalence rates for CI, which can be attributed to various factors such as the study settings, demographic characteristics of the population, cultural differences, and variations in the assessment tools utilized for screening. These factors contribute to variations in the definition and categorization of mental and neurocognitive disorders, thereby influencing the wide range of CI prevalence reported ^[25].

The prevalence of MCI in Egypt was estimated as (32%) by Amer et al, ^[26] another study also found the prevalence to be 34.2 and 44.3% of the elderly men and women, respectively. ^[27] That was consistent with the result of current study that the prevalence of MCI was 37.6%.

The higher prevalence of CI, both MCI and dementia, within the Egyptian population can potentially be attributed to the significant proportion of illiteracy among Egyptian elderly individuals, accounting for approximately 56.5% ^[28]. In the current study, the illiterate individuals or those with lower educational levels, comprised 58.5%of the studied population that further emphasizing the association between educational attainment and cognitive health.

By investigation the type of CI using the Hachinski ischemic score. In the current study the degenerative type was the most common accounted for 48% among cognitively impaired subjects followed by mixed type (37.6%) then the vascular type 14.4%.

This is a consistent with classification of dementia in most literatures where it is divided into subtypes that found that the most common type of neurodegenerative dementia was Alzheimer (55.6%), then vascular dementia (18.9%) ^[29].

Moreover, the extent and patterns of impairment across the range of cognitive domains are not yet well established so we used a newly developed validated tool named Ain Shams Cognitive Assessment tool(ASCA) that assess specific cognitive domain functions among cognitively impaired subjects ^[17].

Several cognitive sub domains were assessed including (learning and episodic verbal memory, working memory {encoding, spatial, cuing}, attention, executive function, language and semantic memory, visuospatial function, processing speed, abstraction and judgment).

For easier comparison with other literature we classified the cognitive domains in to the most common domains classified by DSM-5 (learning and memory, complex attention, executive function, language, perceptual motor function) ^[18].

In the current study we found that the greatest proportion of test impairment was for the figure copy and recall of Bender Gestalt test (94%), naming (83%) and word recognition test (80%) which primarily assess visuospatial and memory functions respectively.

This results suggest that patients were particularly impaired on cognitive functions of visuospatial and memory domains. This is consistent with the type of cognitive impairment tested above where the most common type of impairment was the degenerative type. Given the common predominance of memory impairments in neurodegenerative-related cognitive impairment, compared with predominance of attention/executive in vascular-related impairment ^[30].

By examination the distribution of patterns of impairment across participants it was very diverse and most of them were impaired on at least one cognitive domain with a very few participants had cognitive performance at or above average expectations that is consistent with previous studies ^[31].

Patterns of impairment across cognitive domains were as follows: 94% for visuospatial function,88% for language and semantic memory, 75%for attention and working memory, 69% for executive functions, 30% for learning, 25% for judgment and 12%for abstraction.

Moreover, With comparison of the cognitive performance across domains and the educational level it was found that working memory function was the most affected domain among the highly educated group followed by visuospatial and executive functions, while among illiterate and low educated group the visuospatial function was the most affected domain followed by language and semantic memory functions with significant difference between the two groups as regard all domain functions except for attention, abstraction and judgment.

In another study the prevalence of specific domain affection was as follows: 31.5% for perceptual-motor function, 41.2% for language, 41.7% for executive function, 42.2% for learning and memory and 48.8% for complex attention ^[31].

That had lower prevalence rate than current study this was attributed to the different data presentation method as the they assessed the pattern of domain affection in the total study population but in the current study, we assessed it only among the cognitively impaired subjects, so the proportion of impairment was higher in the current study.

Furthermore, the distribution of pattern was different, which could be attributed to different risk factors. As their study was conducted among hemodialysis patients who have vascular risk factors for vascular dementia which was reflected on higher affection of attention and executive functions

The diversity in cognitive performance and varying rates of cognitive decline have been documented to undergo alterations in relation to a range of factors, including demographic characteristics, educational background, lifestyle choices, physical well-being, social engagement, and economic resources ^[32].

In this study, education level, income, occupation, computer use, family size and sanitary supply were used to describe SES. Using the Egyptian socio economic scale that is widely used in research to assess the subject’s SES ^[21].

By comparison between cognitive function and socioeconomic domains in the current study it was found that CI (MCI or dementia) was significantly associated with low educational level, non-occupied, low income, limited computer^, use and bad sanitary condition but there was no significance as regard family size and crowding index.

A recent study revealed that older adults who reported lower perceived income, lower educational attainment, compromised physical and mental health, and limited access to physical and social resources were found to have a higher likelihood of cognitive impairment ^[33]. Moreover, it is important to note that the influence of these sociodemographic characteristics on cognitive function is not uniform, as they can interact with one another, giving rise to unique patterns of cognitive performance ^[34].

By examination the effect of SES level on performance across different cognitive domains in the current study it was found that there was significant association between SES level and impairment in the following cognitive sub domains (episodic verbal memory, language and semantic memory, processing speed and visuospatial functions).

Impairment of those sub domains were distributed higher in low SES subjects in comparison with high and medium SES subjects with significant difference. Although impairment in the working spatial function was the most distributed sub domain impairment among the three groups there was no statistical difference between them.

The observed distribution of cognitive domain impairment can be explained by exposure to persistent chronic stressors such as financial needs that have been linked to reductions in hippocampal and amygdala volume, as well as atypical activity in the prefrontal cortex. These brain regions play a vital role in various cognitive functions, including memory, emotion processing, executive functions, and social behavior ^[35].

A substantial body of literature demonstrates a consistent and independent association between socioeconomic status and cognitive function in later stages of life ^{[32, 33, 34]}.

In the current study there was a highly significant association between cognitive function and SES level that the prevalence of CI (MCI or dementia) was mainly concentrated in subjects with low and medium SES. Also, we found that demented subjects had a higher distribution of low SES level than both MCI and normal subjects while normal subjects a higher distribution of high SES level than both MCI and demented subjects

It is widely accepted that low SES is one of the risk factors for CI in older adults ^[36]. Individuals with lower SES often have limited health literacy due to their lower levels of education. Additionally, they are less likely to receive health advice and have reduced motivation to undergo CI screening, which is compounded by limited access to health resources. This economic disparity also results in reduced social participation, as low SES individuals may lack the time and energy to engage in socially enriching activities that can expand their cognitive reserve and buffer the risk of CI ^[37]. Thus, low SES populations are more susceptible to CI.

In contrast, individuals from higher socioeconomic groups are typically more advantaged with regards to health. Their good working and living conditions and greater access to health care knowledge and medical technology, resulting from their educational background, occupational status, and income, make them less susceptible to health injuries and better able to prevent cognitive decline. Furthermore, they are more inclined towards a healthy lifestyle and social network, which can help delay cognitive decline ^[38]. Even when cognitive decline occurs, those with higher SES have a better chance of detecting the condition early and correcting adverse factors to avoid further deterioration of cognitive function ^[39].

The mechanism by which SES impacts cognitive impairment is thought to be through the building and preservation of brain reserve capacity ^[34].

The concept of cognitive reserve highlights the brain's remarkable capacity for flexibility and adaptability, enabling it to actively counteract the impact of age- or disease-related alterations within its networks ^[40]. This further illustrates that CI inequity is a problem with worldwide prevalence specially, in developing countries like Egypt and its inequity that continues to worsen will be detrimental to overall social welfare.

So, there is an urgent need to prioritize efforts aimed at enhancing cognitive function and preventing the progression from MCI to dementia, particularly among older adults who are at higher risk, including those from low SES backgrounds. Ensuring improved access to healthcare services becomes a critical focus in addressing the needs of this vulnerable population.

In conclusion, this study found that the prevalence of cognitive impairment among community dwelling elderly in Egypt was estimated as 50.2% that 37.6% had MCI and 12.55% were demented. The most common type of CI was degenerative type (47.8%).

The distribution of specific cognitive domain impairment ranged from 94% for visuospatial function to 12.7% for abstraction, with the other domains being 88% for language and semantic memory, 75% for attention, 69% for executive functions, 30% for learning and verbal memory and 25% for judgment.

Co-occurrence of impairment across domains was very common. Working memory function was the most affected domain among the highly educated group, while among illiterate and low educated group the visuospatial function was the most affected domain.

CI was significantly associated with increasing age, female gender, multiple comorbid conditions, depression and positive family history. It also had a highly significant association with SES level that it was mainly concentrated in the socioeconomically disadvantaged population (low educational level, non-occupied, limited computer use, low income, and bad sanitation).

There was a significant association between SES level and impairment in the following cognitive sub domains (episodic verbal memory, language and semantic memory, processing speed and visuospatial functions).

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or this article

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Acknowledgements

Not applicable.

Authors’ contributions

All authors designed the study, contributed to and have approved the final manuscript.

Availability of data and materials

Not applicable.

Ethics approval and consent to participate.

The study was approved by Faculty of Medicine Ain-Shams University (FMASU) Research Ethics Committee (REC) on 18/9/2019 with reference number 285/2019. The FMASU REC operated according to guidelines of the International Council on Harmonization and the Islamic Organization for Medical Sciences, the United States Office for Human Research Protections and the United States Code of Federal Regulations and operates under Federal Wide Assurance No., FWA 000017585. A written consent was obtained from all participants.

Consent for publication

Not applicable (no personal data in the study).

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Pattern of Cognitive Impairment Among Community Dwelling Elderly in Egypt and Its Relation to Socioeconomic Status

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