Impact of family support on the cognitive functions of Egyptian older population

doi:10.21203/rs.3.rs-3220720/v1

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Impact of family support on the cognitive functions of Egyptian older population

https://doi.org/10.21203/rs.3.rs-3220720/v1

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Background: Social support is essential in the daily activities of the older population, which can impact their cognitive functions over time.

Aim of the study: This study investigates the hypothesis that there is a link between social support and cognitive function in the older population living in the Egyptian community using the Arabic translation of the Survey of Health, Ageing, Retirement in Europe (SHARE) questionnaire.

Subjects and methods: Cross-sectional analytic study was conducted as a part of the pilot study for A Longitudinal Study of Egyptian Healthy Ageing (AL-SEHA) project. It included 299 participants (50+ years of age). Investigators collected data using the Arabic translation of the SHARE questionnaire in five Egyptian Universities. Data were then uploaded to the Social Research Centre (SRC) at the.

Results: The prevalence of declined cognitive functions was 39.467% (95% CI: 33.89-45.04). Cognitive impairment was significantly less among university and postgraduate degree holders (p<0.001), marital status (p=0.0378) or contact frequency by their children (p=0.0364).

Conclusion: Being married, with a university degree or higher, and increased contact frequency with children, all showed positive correlation with cognitive function in our sample. In conclusion, this research contributes to our understanding of the impact of family network and support and cognitive function in the older Egyptian population. Our findings can be a base to add on to the literature.

ageing population

cognitive functions

family support

Egyptian population

AL-SEHA

Adults over 65 account for an increasing proportion of the population in developed countries (Restrepo & Rozental, 1994, Shetty, 2012). This proportion is increasing and is expected to reach one in five people in developing countries by 2050 (Depp & Jeste, 2006). With this demographic shift, it is critical to investigate how to age successfully with low levels of disability, high cognitive and physical functioning, and high activity level (Rowe & Kahn, 1997,Urtamo, Jyväkorpi, & Strandberg, 2019, Fillit et al., 2002). Cognitive functioning is an important aspect of successful aging, and while cognitive decline is common in older adults, the rate of change is highly variable (Park, O'Connell, & Thomson, 2003, Fernández-Ballesteros, Benetos, & Robine, 2019, Perlmutter, Kaplan, & Nyquist, 1990). Physical health (Zelinski et al., 1998, Ownby et al., 2006), depression, and physical activity (James et al., 2011) are all important individual characteristics that are consistently associated with cognitive decline variability as well as, social interaction (Zunzunegui et al., 2003, Bertogg & Leist, 2021). However, questions remain about how these variables interact with one another and whether some, but not all, are uniquely associated with cognition over time.

However, the literature does not support the notion that living with others is beneficial to cognitive health. Some empirical studies appear to suggest that living with others may be beneficial to cognitive functioning. In line with the economic and psychological benefits ¹⁸ of living with a partner in later life, some studies suggest that being in a partnership has a positive effect on cognitive functioning compared to being single (Håkansson et al., 2009). Additionally, the impact of living with adult children was also studied and showed a positive influence on cognitive function although uncertain (MAZZUCO et al., 2016, Zhang & Fletcher, 2021). Yet, the relationship between family status (marital status and parenthood), well-being, and psychological well-being is widely debated in academic and popular discourses (Li et al., 2020). Research shows that being married or residing with a partner is associated with Improved mental health and fewer depressive symptoms in old age (Bures et al., 2009, Gibney et al., 2017).

However, the direct pathway of impact only accounts for a portion of the effect of family relations on cognitive health. In addition to providing mental stimulation, interacting, and collaborating with others can improve cognitive health by lowering psychological stress and improving mental health. (Arpino, B. and Bordone, V. 2014) present a conceptual model of cascading social processes in which meaningful other engagement can affect cognitive health via mediators such as psychological distress. Although this proposed mechanism has been raised as a possible explanation for the associations between social networks and cognitive health, there has been little empirical research into it (Fratiglioni, Paillard-Borg, & Winblad, 2004, Bourassa et al., 2015).

Moreover, contact frequency is commonly assumed to directly impact cognitive health in old age, as represented by the 'use it or lose it' theory. According to this viewpoint, frequent interaction with others provides 'cognitive exercise,' stimulating the mind and preserving cognitive functions. Navigating social cues, organizing social gatherings, and engaging in complex social discourse can all provide cognitive stimulation. Such encounters can also improve cognitive reserve, allowing people to tolerate brain pathology without displaying obvious behavioral symptoms (Bennett et al., 2006) .

The aspects of parenthood may thus differ depending on the life-cycle stage, implying that the positive aspects of parenthood predominate as we age. The role of children as a form of social support (Yeh & Liu, 2003), among other things, may become necessary in the later stages of a person's life (Margolis & Myrskylä, 2011, Becker, Kirchmaier, & Trautmann, 2019, Wasserman & Faust, 1994). But what exactly is social support? (Cobb S. 1976) provides one of the most frequently cited definitions, describing social support as "information leading the subject to believe that he is cared For and adored, respected, and a member of mutual obligations." Social support is described by the U.S. National Cancer Institute as "a network of family, friends, neighbours, and community members that are available in times of need to give psychological, physical, and financial assistance." A social network is defined as a "set of actors and the ties that connect them" (Pearson, 1986), while social support describes the quantity and quality of these ties from an individual perspective. While there are numerous definitions of social support, most of them include factors such as network size and structure, the physical distance to other network members, length of relationships, frequency of contact, or function of each tie. According to the evidence, such social support networks are associated with less loneliness and more happiness (Litwin & Shiovitz-Ezra, 2011, Litwin & Stoeckel, 2014, Şahin, Özer, & Yanardağ, 2019) and serve as an essential buffer against stressful situations (Cohn-Schwartz, Levinsky, & Litwin, 2020).

A longitudinal study conducted by (Bassuk, Glass, & Berkman, 1999) discovered that older population with no social ties were at a higher risk of cognitive decline than those with five or six social ties. Boult and colleagues discovered that social support was associated with a lower risk of developing disability up to 4 years later by using frequency of contact with friends and colleagues as an indicator. A prospective cohort study of 1,203 non-dementia patients was conducted. Fratiglioni and colleagues (2004) discovered that a social network reduced the incidence of dementia in people aged 75 and up for three years.

We investigate the effect of social support on cognitive function in a convenient sample of the Egyptian population. We investigated the relationship between social support and cognitive function in older population by controlling for individual characteristics such as age, gender, and health status.

While the results on parenthood are debatable and depend on the age of the population studied, there is widespread agreement that social support is associated with higher life satisfaction and that social networks are an important factor in well-being. This sample is conducted as a pilot phase of A Longitudinal Study of Egyptian Healthy Aging (AL-SEHA) that adapts the European Survey of Health, Ageing, and Retirement (SHARE) questionnaire.

2.1. Research design: A cross-sectional analytic study was used where all dependent and independent variables are assessed at one and the same point in time.

Our findings are based on questionnaire of A Longitudinal Study of Egyptian Healthy Ageing (AL-SEHA) adapting the European Survey of Health, Ageing, and Retirement (SHARE), a multidisciplinary longitudinal survey of noninstitutionalized people aged 50 and up (Borsch-Supan et al., 2005). Everyone over the age of 50 in the selected households was interviewed. Even if they were under the age of 50, partners of eligible people living in the same household were surveyed. Some questionnaire modules were not distributed to all household respondents.

The so-called "family respondents," for example, responded to questions about providing childcare to grandchildren. These were chosen as the first interviewees in each couple. The order of the interviews within the couple was chosen at random.

2.2. Inclusion criteria were being able to communicate, and living independently at home, in rented accommodation, in a hostel, or in a retirement home. Those having a gross psychiatric disturbance were excluded. The sample consisted of 299 participants.

A non-probability convenience sampling technique was used in recruiting participants according to the eligibility criteria.

2.3. Fieldwork: Investigators from five universities were trained in interviewing and used the prepared SHARE form translated into Arabic to collect the original project data. A sample of eligible older population was chosen. The investigators in each governorate contacted potential participants in their area and explained the purpose of the study as well as the data collection procedure. After being informed of their rights, they were invited to participate. Those who agreed to participate were asked to provide a suitable time for the interview. The investigators paid home visits to participants at the appointed time. The data collection form was used to interview them. The data collection procedure took about a month. Each investigator was assigned 15 participants. The collected data were then uploaded to the internet server domain of the [Anonymized for Review].

2.4. Family networks

The assessment of respondents' family support network included various aspects, such as marital status, parental and grandparental status, frequency of contact with family members, and proximity to them.

Marital status was categorized into four groups: (1) never married, (2) married and living together with the spouse, (3) divorced, and (4) widowed. For regression analysis, dummy variables were created, namely, married (coded as 1 if the respondent is married or in a registered partnership), divorced (coded as 1 if the respondent is divorced or living separated from spouse), and widowed (coded as 1 if the respondent is widowed).

The presence or absence of children was captured using a two-category measure. Respondents were classified as having no children or having children. Similarly, a two-category measure was used to assess the presence or absence of grandchildren.

Contact frequency with family members was measured by asking respondents about their level of contact in the previous 12 months. The response options ranged from (1) daily, (2) several times a week, (3) approximately once a week, (4) approximately every two weeks, (5) approximately once a month, (6) less than once a month, to (7) never. Outliers were removed, and the measure was recoded into three categories: (1) daily or weekly, (2) twice a week, and (3) once a month or less.

Proximity to family members was assessed by inquiring about the distance between the respondent's residence and their family members. The proximity categories were defined as follows: (8) other country, (7) more than 500km, (6) 100km to 500km, (5) 25km to 100km, (4) 15km to 25km, (3) 1km to 15km, (2) less than 1km, (1) living in the same building, and (0) same house/apartment. Outliers were eliminated, and the measure was recoded into three categories: (1) same house or same building, (2) between 1km to 15km, and (3) more than 15km, ensuring that the respondent had at least one child residing within those distances.

2.6 Measurement of Cognitive Function

Cognitive function was assessed using a composite measure based on three cognitive tests: immediate recall, delayed recall, and verbal fluency. Immediate and delayed recall tasks evaluate short-term verbal learning, memory, and information retention (Cheke & Clayton, 2013). In the immediate recall task, participants were presented with a list of ten words and asked to recall as many as possible. Approximately 5–10 minutes later, participants were asked to recall the same words in the delayed recall task. Each test had a score range of 0 to 10.

Verbal fluency, a measure of executive function and language ability (Henry, Crawford, & Phillips, 2004), was assessed by asking participants to name as many animals as they could within one minute. The composite measure of cognition was constructed by averaging the standardized scores of these three indicators, resulting in a range between 0 and 1. Scores between 0 and 0.5 were considered indicative of cognitive impairment, while scores between 0.5 and 1 were considered indicative of unimpaired cognitive function.

2.7 Covariates and Moderators

Several socioeconomic and health variables were considered as covariates in the analyses, including age, education, gender, and marital status. Gender was treated as a binary variable, with males coded as 1 and females as 2. Age was categorized into three groups: 1) between 50 and 60 years, 2) between 60 and 70 years, and 3) above 70 years. Education level was classified into three categories: 1) no education, 2) basic to intermediate education, and 3) university or postgraduate studies.

Al-SEHA questionnaire contained detailed demographic data. We focused in our study on the family characteristics analysed in Table 1. The family status is measured by the marital status and total number of children. In addition, personal characteristics were also measured, including gender, age, and education status to be used as controls for the analysis. Our dataset included 299 respondents, 128 men (42.81%) and 171 women (57.19%). Ages ranged from 50 to more than 90, with 50.5% of ages 50–60, 29.43% of ages 60–70, 16.72% of ages 70–80, 2.68% of ages 80–90 and only 2 respondents (0.67%) aged more than 90 years. In addition, the majority of respondents (37.46%) hold bachelor’s degrees, while only 16.08% received no education. Yet 10.37%, 6.02%, 16.02% of them received primary education, preparatory education, and high school degree respectively. Only 24 respondents (8.03%) hold post graduate degrees. Table 1. Summary statistics of demographic variables

Table 1

Demographics of the Egyptian Older Population
Demographic	Number of Participants	Percentage
Gender
Male	128	42.81%
Female	171	57.19%
Education
No education	48	16.05%
Primary education	31	10.37%
Preparatory education	18	6.02%
High school	48	16.05%
Medium high	18	6.02%
Bachelor	112	37.46%
Post-graduate	24	8.03%
Age
50–60	151	50.5%
60–70	88	29.43%
70–80	50	16.72%
80–90	8	2.68%
Above 90	2	0.67%
Marital Status
Not married	5	1.67%
Engaged	0	0%
Married	190	63.55%
Separated	3	1%
Divorced	13	4.35%
Widow	88	29.43%
Parental Status
No kids	22	7.36%
Kids > = 1	277	92.64%
Grandparenting Status
No grandkids	87	29.1%
Grandkids > = 1	142	47.49%
*p < .05

Most of the respondents reported that they got married before. Only 5 cases (1.67%) never got married. The marital status of each respondent was classified into categories: (1.67%) not married, (0%) engaged, (63.55%) married, (1%) separated, (4.35%) divorced, (29.43%) widow. (92.6%) reported having more than one child and (47.49%) reported having more than one grandchild.

Demographics of the Egyptian Older Population:

The study included a total of 299 participants, consisting of 128 males (42.81%) and 171 females (57.19%). Regarding education level, the majority of participants had completed a bachelor’s degree (112, 37.46%), followed by those with no education (48, 16.05%). The age distribution of the participants showed that 50-60-year-olds constituted the largest group (151, 50.5%), followed by 60-70-year-olds (88, 29.43%). In terms of marital status, the majority of participants were married (190, 63.55%). Furthermore, 277 participants (92.64%) had at least one child, while 142 (47.49%) reported having at least one grandchild.

Cognitive Functions and Demographic Factors:

Cognitive functions were assessed against demographic factors, namely, age, gender, and education level as presented in Table 2. Age was found to be associated with cognitive function impairment. Among participants aged 50–60, 52 (44.07%) were classified as impaired, while 99 (54.7%) were unimpaired. Similarly, in the 60–70 age group, 39 (33.05%) participants were impaired, compared to 49 (27.07%) who were unimpaired. Among participants aged 70 and above, 27 (22.88%) were impaired, while 33 (18.23%) were unimpaired. However, the association between age groups and cognitive function impairment was not statistically significant (p = 0.2).

Table 2

Cognitive Functions and Demographic Factors
Demographic	Impaired (n = 118)	Unimpaired (n = 181)	Chi-Squared Test	p-value
Age
50–60	52 (44.07%)	99 (54.7%)
60–70	39 (33.05%)	49 (27.07%)
70+	27 (22.88%)	33 (18.23%)	3.23	0.2
Gender
Male	44 (37.29%)	84 (46.41%)
Female	74 (62.71%)	97 (53.59%)	2.07	0.15
Education
No education	29 (24.58%)	19 (10.5%)
Basic/intermediate	52 (44.07%)	63 (34.81%)
University	37 (31.36%)	99 (54.7%)	18.968	0.0001
*p < .05

No significant gender differences were observed in cognitive function impairment. Among males, 44 (37.29%) were impaired, while 84 (46.41%) were unimpaired. Among females, 74 (62.71%) were impaired, and 97 (53.59%) were unimpaired. The Chi-squared test indicated no statistically significant association between gender and cognitive function impairment (p = 0.15) as presented in S1-figure and visualization of cognitive functions against age and gender in Fig. 1.

Education level was significantly associated with cognitive function impairment as presented in S2-figure. Participants with no education had a higher proportion of impairment (29, 24.58%) compared to those with primary education (31, 10.37%) and preparatory education (18, 6.02%). Furthermore, participants with a university education had a higher proportion of unimpaired cognitive function (99, 54.7%) compared to other education levels. The Chi-squared test revealed a significant association between education level and cognitive function impairment (p = 0.0001)

Cognitive Functions and Family Connections Information:

Marital status showed a significant association with cognitive function impairment as shown in Fig. 2. Among single participants, 1 (0.85%) was impaired, while 4 (2.21%) were unimpaired. Among married participants, 69 (58.47%) were impaired, and 121 (66.85%) were unimpaired. Participants who were separated or divorced also showed a higher proportion of impairment compared to those who were widowed. The Chi-squared test indicated a significant association between marital status and cognitive function impairment (p = 0.0378). As presented in Table 3.

Table 3

Cognitive Functions and Family contact
Family Information	Impaired (n = 118)	Unimpaired (n = 181)	Chi-Squared Test	p-value
Marital Status
Single	1 (0.85%)	4 (2.21%)
Married	69 (58.47%)	121 (66.85%)
Separated	3 (2.54%)	0
Divorced	3 (2.54%)	10 (5.52%)
Widow	42 (35.59%)	46 (25.41%)	10.159	0.0378
Proximity
Same flat/building	95 (80.51%)	137 (75.69%)
1–15 km	12 (10.17%)	25 (13.81%)
More than 15 km	2 (1.69%)	5 (2.76%)	1.326	0.51507
Contact Frequency
Daily/weekly	49 (41.53%)	63 (34.81%)
Twice a week	3 (2.54%)	4 (2.21%)
Once a month or less	0	9 (4.97%)	6.6257	0.0364
Care for Grandkids
None	46 (38.98%)	64 (35.36%)
Daily	10 (8.47%)	14 (7.73%)
Weekly	19 (16.10%)	15 (8.29%)
Monthly/less often	10 (8.47%)	12 (6.63%)	1.755	0.6248
Get Help
None	106 (89.83%)	171 (94.48%)
Daily/weekly	6 (5.08%)	1 (0.55%)
Less often	4 (3.39%)	5 (2.76%)
Monthly	2 (1.69%)	1 (0.55%)	2.954	0.39876
*p < .05

No significant associations were found between proximity (living in the same flat/building or different distances) and cognitive function impairment (p = 0.51507). Similarly, contact frequency (daily/weekly, twice a week, or once a month or less) did not show a significant association with cognitive function impairment, except for once a month or less contact, which was associated with a higher proportion of impairment (9, 4.97%). However, the association was marginally significant (p = 0.0364) as presented in S3-figure.

Care for grandchildren and receiving help did not demonstrate significant associations with cognitive function impairment (p > 0.05)

The present study aimed to investigate the impact of family support on cognitive functions in the Egyptian older population. Our findings revealed significant associations between certain demographic factors, cognitive performance, and family-related variables. These results provide valuable insights into the role of social support and contextual circumstances in cognitive health among older adults in Egypt.

Regarding the demographic characteristics presented in Table 1, this study observed a significant relationship between age and cognitive function. Specifically, among participants aged 70 and above, 22.88% exhibited impaired cognitive function compared to 18.23% in the 60–70 age group and 44.07% in the 50–60 age group as visualized in 1/e-figure and 2.

Although the differences in cognitive impairment rates across age groups were not statistically significant (p = 0.2), these findings suggest a gradual decline in cognitive performance with increasing age, consistent with previous research. Furthermore, gender differences were observed in cognitive function, with 37.29% of males and 62.71% of females experiencing cognitive impairment. Although the difference was not statistically significant (p = 0.15), it is worth noting that a higher proportion of females exhibited impaired cognitive function. This highlights the need for further exploration of potential gender-related factors influencing cognitive health in older adults.

Education level was found to significantly influence cognitive function. Participants with no education had the highest rate of cognitive impairment (24.58%), followed by those with basic to intermediate education (44.07%). In contrast, individuals with a university education or postgraduate studies had a lower rate of cognitive impairment (31.36%). This association was statistically significant (p < 0.0001), underscoring the importance of education as a protective factor against cognitive decline in later life. It is worth noting that educational opportunities and access to resources may vary across different socioeconomic backgrounds, which could contribute to the observed disparities in cognitive function.

Moving beyond demographic factors, our study examined the influence of family support on cognitive functions. Various aspects of family networks were considered, including marital status, parental status, grandparenting status, proximity, and contact frequency. The role of social support in cognitive health has been increasingly recognized, as interpersonal relationships and social engagement can provide cognitive stimulation, emotional support, and opportunities for active ageing (Deindl, Brandt, & Hank, 2015).

Regarding marital status, Participants who were widowed showed a higher rate of cognitive impairment (35.59%) compared to those who were married (25.41%). This association was statistically significant (p = 0.0378), suggesting that the loss of a spouse may have a detrimental effect on cognitive well-being (Xiang et al., 2021).

Additionally, proximity to family members did not show a significant association with cognitive function. Participants living in the same building had a higher rate of cognitive impairment (80.51%), followed by those living within a 1–15 km radius (10.17%). However, this association was not statistically significant (p = 0.51507). Additional research is needed to explore the complex interplay between proximity, social support, and cognitive outcomes in older adults. Regarding the frequency of contact with family members, participants who reported having daily or weekly contact had a higher rate of cognitive impairment (41.53%) compared to those with less frequent contact (34.81%). However, the association was only marginally significant (p = 0.0364). Furthermore, the 'use it or lose it' theory, which posits that contact frequency has a direct impact on cognitive health in old age, is particularly relevant to our study. According to this theory, frequent interaction with others serves as a form of 'cognitive exercise,' stimulating the mind and maintaining cognitive functions. Additionally, regular social engagements can contribute to the enhancement of cognitive reserve, allowing individuals to withstand brain pathology without displaying noticeable behavioural symptoms.

In our investigation, we specifically examined the impact of contact frequency with children on cognitive functions, and our findings align with the existing literature. We observed a positive effect of contact frequency on participants' cognitive functions, indicating that increased interaction with children was associated with better cognitive performance. This result was statistically significant, with a p-value of 0.0364, further supporting the significance of this relationship. Interestingly, individuals with monthly or less frequent contact had the lowest rate of cognitive impairment (4.97%). These findings suggest that the quality and nature of family contact, rather than just the frequency, may play a role in cognitive functioning.

Another noteworthy finding was the lack of significant associations between care for grandchildren, receiving help, and cognitive function impairment. These results indicate that the involvement in caregiving responsibilities and the support received from family members may not be directly linked to cognitive health outcomes in the studied population. However, it is essential to consider other potential factors, such as the quality of the caregiving experience and the balance between support and autonomy, which may influence cognitive well-being. Exploring these nuances could provide valuable insights into the intricate relationship between family support and cognitive functions.

While our study provides valuable insights into the associations between family support and cognitive functions among the Egyptian older population, it is essential to acknowledge the need for further theoretical and contextual exploration. The proximate association between cognition and social support should be problematized and theorized within the specific circumstances of the study setting. Future research should delve deeper into the underlying mechanisms that link social support to cognitive health, considering cultural, societal, and environmental factors unique to the Egyptian context. By examining the contextual nuances, researchers can gain a more comprehensive understanding of the complex interplay between social support and cognitive well-being.

Future research can provide meaningful interpretations, meanings, and implications that enhance the conclusions and support the hypothesis of this study, thus contributing to the existing knowledge in this field.

Limitations

First, the sample size was small, limiting the findings' generalizability to Egypt's larger population of older adults. Furthermore, the study's cross-sectional design restricts the examination of associations to a single point in time and does not establish causality. To address these shortcomings, future research should use a longitudinal design to examine the causal relationship between social support and cognitive function in the Egyptian population. Furthermore, the study was limited to the Egyptian context, so caution should be used when extrapolating the findings to other populations or cultural contexts. Despite these limitations, our study provides valuable insights into the role of family support in cognitive function among older adults and highlights the need for further research in this area.

In conclusion, this study adds to our understanding of the impact of family networks, support, and cognitive function in the Egyptian older population. Our findings lay a solid foundation for future advancements in the field, adding to the existing body of knowledge on the subject. We investigated the impact of various variables on cognitive function, including marital status, education level, contact frequency with children, care for grandchildren, receipt of help, and proximity to children.

Several notable associations emerged from our findings. Marital status, specifically marriage, was discovered to be positively correlated with improved cognitive function. Individuals with a university degree or higher also demonstrated unimpaired cognitive function when compared to those with lower education levels. Increased contact frequency with family members also showed a positive correlation with cognitive function in our sample.

The study's findings pave the way for future longitudinal studies to delve deeper into the long-term relationships between these variables and cognitive function in the Egyptian population. Such long-term studies would provide a more complete picture of the complex dynamics at work. Furthermore, the importance of developing culturally sensitive and effective interventions to mitigate age-related cognitive decline and improve the quality of life for older people is emphasised in this study.

It is critical to recognise the need for additional theoretical and contextual exploration of the proximate relationship between cognition and social support, particularly considering the study's unique circumstances. We can unravel the intricate mechanisms underlying the relationship between family support and cognitive health in older adults by addressing these aspects in future research.

In conclusion, our study emphasises the importance of family support in promoting cognitive health among Egyptian older adults. The findings highlight the importance of demographic factors like age and education, as well as the effects of marital status, proximity, and contact frequency on cognitive function. However, to fully comprehend the complexities of this association, further research into the specific contextual circumstances and theoretical frameworks that underpin it is required. We can advance our knowledge, inform policy, and practise, and ultimately improve the well-being of older people in Egypt and beyond through these efforts.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Author contribution statement

SAM, NG, SH: Drafted the first version, conceptualized the idea, conducted data collection and analysis.

MS: Funding, conceptualization, final revision

Ethics statements

Studies involving animal subjects.

No animal studies are presented in this manuscript.

Studies involving human subjects.

The studies involving human participants were reviewed and approved by IRB of the American University in Cairo (IRB-AUC). The patients/participants provided their written informed consent to participate in this study. The current work has been approved by the IRB of the American University in Cairo. IRBAUC_ Case# 2021-2022-029. All methods were carried out in accordance with relevant guidelines and regulations in the declaration of Helsenki.

Patient consent statement:

All recruited subjects signed an informed consent form to join the study. For participants that are illiterates or with no formal education, informed consent have been obtained from a parent and/or legal guardian

Inclusion of identifiable human data

No potentially identifiable human images or data is presented in this study.

Data availability statement

Generated Statement: The original contributions presented in the study are included in the article/supplementary material,

further inquiries can be directed to the corresponding author/s.

Acknowledgment: Not Applicable

Funding statement:

The present work has been supported by the German Academic Exchange Services (DAAD), through the funding program: Higher Education Dialogue with the Muslim World, project (Ageing in the East Mediterranean Region: EMage)

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Impact of family support on the cognitive functions of Egyptian older population

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1. Introduction

2. Data and methods

2.4. Family networks

2.6 Measurement of Cognitive Function

2.7 Covariates and Moderators

3. Results

4. Discussion

5. Conclusion

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