Nutritional status in older adults with mild cognitive impairment living in elderly homes in Cairo, Egypt

Abstract

Objectives

To delineate the difference in nutritional risk between older adults with normal cognitive function and mild cognitive impairment living in elderly homes.

Design

Cross-sectional study.

Setting

Three elderly homes in Cairo, Egypt.

Participants

One hundred twenty older adults; men and women aged 60 years and older.

Measurements

Comprehensive geriatric assessment was done for every participant to evaluate medical, functional, cognitive and affective aspects. Nutritional status was assessed by using the mini-nutritional assessment (MNA). Nutritional deficit was considered to be present if the individuals were classified as malnourished or at nutritional risk by means of the MNA. The cognitive function was assessed by using the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA).

Results

MCI was identified in 46 (38.3%) of the participants. According to the MNA classification, 58 (48.3%) of the sample study was assessed as well nourished, 49 (40.8%) at risk of malnutrition and 13 (10.8%) as malnourished. Older adults with MCI had significantly higher frequency of being at risk of malnutrition or malnourished than those with normal cognition. Multiple logistic regression analysis revealed that the associations between MCI and nutritional deficit remained significant after adjustment for age, illiteracy, female gender and depression.

Conclusion

These results suggest that MCI may be associated with nutritional risk, which emphasizes the importance of early identification of nutritional status among individuals with MCI. It remains to be demonstrated whether improvement in nutritional status may improve the cognitive function or delay progression to dementia in these patients.

Introduction

Mild cognitive impairment (MCI) is a transitional stage between normal cognitive aging and dementia (1). Subjects with MCI are non-demented individuals, yet they have demonstrable impairment in cognitive functions according to their performance on tests adjusted for age and educational level (2). These deficits have no impact on global intellectual functioning and on the ability to perform activities of daily living (ADL) (2). Longitudinal studies have shown that older people with MCI develop Alzheimer dementia at a rate of 10% to 30% annually (3), whereas elderly people without MCI develop dementia at a rate of 1% to 2% annually (4).

Malnutrition has great importance in promoting health and quality of life among the elderly, since it is associated with increased morbidity-mortality (5), and impaired functional capacity at this stage of life (6). It is prevalent among the older adult population, particularly among those who are institutionalized (7).

Although recent studies confirmed a higher prevalence of malnutrition in older patients with dementia (8), the relationship between the nutritional status and the preclinical phase of dementia (particularly MCI among older adults) still remains unclear.

The aim of this study was to delineate the difference in nutritional risk between older adults with normal cognitive function and those with mild cognitive impairment living in elderly homes. In this study, it was hypothesized that individuals with malnutrition and those who were at risk for malnutrition might suffer from MCI. Hence the risk of malnutrition is higher in participants with MCI than those without MCI.

Methods

Study Sample

This was a cross-sectional study among older adults who were living in elderly homes in Cairo. Elderly homes are residential homes where the elderly live with their peers and are helped in their activities of daily living and instrumental activities of daily living by trained workers.

A total of 120 participants had a mean age ± standard deviation of 71.4 ± 6.9 years, were included from three elderly homes in Cairo; El Safa, El Kholafaa el Rashedeen, and The Egyptian ladies society home. An Informed consent was obtained from the participants. The study was also approved by the Institutional Review Board.

Sample Size

The sample size was calculated with Type I error (or alpha) =0.05 and power of 0.80, and with a proposed incidence of mild cognitive impairment of 15% among elderly population (9) and to detect at least a difference of 30% (about 45%) in elderly with malnutrition (10), a sample size of at least 35 cases in each group was required (35 cases of malnutrition and 35 controls without malnutrition).

Each participant was subjected to comprehensive geriatric assessment including medical history and physical examination.

Functional assessment was done by the Activities of Daily Living (ADL) scale (11), and the Instrumental Activities of Daily Living (IADL) scale (12). The Arabic version (13) of The Mini-Mental State Examination (MMSE) (14) was performed to assess global cognitive function. The Arabic version (15) of the Montreal Cognitive Assessment (MoCA) (16), a brief screening tool for MCI with high sensitivity and specificity, was used to categorize participants as with, or without MCI. It is a 30-point test covering 8 cognitive domains: 1) attention and concentration, 2) executive functions, 3) memory, 4) language, 5) visuo-constructional skills, 6) conceptual thinking, 7) calculations. and 8) orientation. Scores below 26 are considered to be indicative of MCI. A bonus point is given to individuals with less than 12 years of education.

MMSE test may not be sensitive to mild cognitive changes because it is designed to identify the presence of dementia and have ceiling effects when applied to non-demented patients (10). Most of the individuals with MCI have normal MMSE score (17). However the MoCA test has been shown to be more sensitive to MCI than the MMSE (16).

In this study the MMSE was used to rule out individuals with dementia, while the MoCA test was used to identify individuals with normal cognitive function and those with MCI. Hence the participants were classified as those with normal cognitive function and those with MCI. The subtypes of MCI weren't analyzed, and participants with dementia were excluded.

The mini-nutritional assessment (MNA), a comprehensive tool developed for nutritional assessment in geriatric setting, was used to classify subjects as well nourished (score of 24––30), at risk for malnutrition (score of 17–23.5), or malnourished (score of <17) (18).

Assessment for depression by using the Arabic version (19) of the Geriatric Depression scale (GDS) (20). It is the 15-item GDS which is a well –validated tool often used to screen for depressive symptoms in older individuals. This measure is scored based on a 15-points scale and impairment is indicated by a score of 5 or higher.

Exclusion Criteria

Elderly persons who had score below 24 in the MMSE, those who had any significant major medical disease, or on regular medications known to affect the cognitive function and persons who refused to participate.

Statistical Methods

Quantitative data are presented as mean ± standard deviation (SD). Independent student t test (t) was used to compare such data between two groups and one-way ANOVA is used when more than two group are to be compared. Qualitative data are presented as count and percentage. Chi-squared test (x²) is used to compare such data between two or more groups. We used Pearson correlations to test the association between the cognitive tests (MMSE and MoCA), the GDS and age. Multiple logistic regression analysis was performed to assess the risk of

MCI based on the presence or absence of nutritional deficit (MNA score <24) after adjustment for age, sex, educational level and depression. The Statistical Package for the Social Sciences (SPSS) program, version 12.0 was used as the statistical software program, p < 0.05 was considered to be statistically significant.

Results

Among the 120 participants 56 (46.7%) were males and 64 (53.3%) were females. The mean age of the participants was 71.4 years (SD= 6.9 years). It was found that 16.7% of the participants were illiterate, 25% were able to read and write, 37.5% had high school education and 20.8% were university graduates. Regarding history of common chronic diseases found among our participants; 34% of the participants were diabetics, 50% were hypertensive, 20% had ischemic heart disease, 48% were depressed, and 16% had symptoms of osteoarthritis.

According to the MMSE and MoCA tests 74 (61.7%) of the participants had normal cognitive function and MCI was identified in 46 (38.3%). Nutritional deficit was identified in 62 (51.6%) individuals, of whom 10.8% were malnourished and 40.8% were at nutritional risk.

Table (1) shows the differences between the MCI group and those with normal cognitive function based on the Demographic and clinical features of the studied population. MCI was significantly associated with advanced age (p=0.000), female gender (p=0.015), illiteracy (p=0.027), functional impairment in IADL (p=0.05), and depression (p=0.006).

Table 1.

Demographic and clinical features of the studied population

Characteristics	NCF	MCI	p-value
	(n=74)	(n=46)
Age (years) ∗	69.4 ± 6.4	74.5 ± 6.7	0.000
Gender †
Male	41 (55.4%)	15 (32.6%)	0.015
Female	33 (44.6%)	31 (67.4%)
Education †
Illiterate	7 (9.5%)	13 (28.3%)	0.027
Can read & write	17 (23%)	13 (28.3%)
School education	32 (43.2%)	13 (28.3%)
University education	18 (24.3%)	7 (8.7%)
Smoking status †
Non-smoker	43 (58.1%)	32 (69.6%)	0.408
Ex-smoker	20 (27%)	8 (17.4%)
Smoker	11 (14.9%)	6 (13%)
Need assistance in ADL†	3 (4.1%)	2 (4.3%)	0.94
Need assistance in IADL†	18 (24.3%)	19 (41.3%)	0.05
Depression †	30 (40.5%)	28 (60.9%)	0.03
Diabetes Mellitus †	27 (36.5%)	14 (30.4%)	0.497
Hypertension†	39 (52.7%)	21 (45.7%)	0.453
IHD †	11 (14.9%)	13 (28.3%)	0.074
OA †	8 (10.8%)	11 (23.9%)	0.056

^∗Mean ± Standard deviation;

^†Number of cases (%); NCF = normal cognitive function; MCI = mild cognitive impairment; ADL = activities of daily living; IADL = instrumental activities of daily living; IHD = ischemic heart disease; OA = osteoarthritis.

Male participants and those with higher educational level had significantly higher scores in MMSE and MoCA tests (table 2). Age was negatively correlated to the MMSE and MoCA (r = -0.322, p = 0.000), (r = -0.382, p = 0.000) respectively. There was no association between GDS score, gender (student t test = -1.205, p = 0.230), educational level (f= 1.273, p = 0.287), and age (r = -0.382, p = 0.000). There was no association between the nutritional state, gender (x²=1.9, p= 0.37) and educational level (x²=2.4, p= 0.878). However age was associated with poorer nutritional state (f= 3.277, p = 0.041).

Table 2.

The Relationship Between Cognitive Tests with Gender and Educational Level

	MMSE		MoCA
	Mean (±SD)	p-value	Mean (±SD)	p-value
Gender
Male	28.9 ± 1.4	0.010	27.1 ± 2.5	0.003
Female	28.1 ± 1.8		25.7 ± 2.6
Education
Illiterate	27.4 ± 1.5		24.4 ± 2.6
Can read & write School education	27.9 ± 2.1 29.0 ± 1.3	0.000	28.8 ± 3.1 27.0 ± 2.1	0.000
University education	29.3 ± 1.1		27.3 ± 2.3

MMSE = Mini-Mental State Examination; MoCA = Montreal Cognitive Assessment; SD = Standard deviation

Table (3) shows the relationship between the cognitive tests and nutritional state as measured by MNA. Participants who were at risk of malnutrition and those who were malnourished had significantly poorer performance in MMSE (p=0.000) and MoCA tests (p=0.000) in comparison to those who were well nourished.

Table 3.

Cognitive tests and nutritional state

Cognitive test	Well nourished (n=58)	At risk for malnutrition(n=49)	Malnourished (n=13)	p-value
MMSE	29.1 ± 1.24	28.3 ± 1.74	26.7 ± 1.89	0.000
MoCA	27.4 ± 2.16	25.9 ± 2.47	23.4 ± 3.04	0.000

MMSE = Mini-Mental State Examination; MoCA = Montreal Cognitive Assessment.

Regarding the association between MCI and nutritional status (figure 1); A chi-square test was performed to compare the frequency of MCI according to different nutritional status (well nourished, at risk of malnutrition and malnourished). MCI was significantly higher among those with risk of malnutrition and malnourished when compared to those with well nutritional status (p=0.002).

Figure 1.

Relationship between nutritional status and mild cognitive impairment (MCI)

The vertical axis shows the number of the participants, while the horizontal axis shows the cognitive status of the participants (normal cognitive function (NCF) and MCI). The shaded bars represent those who were well nourished, the hatched bars represent those who were at risk of malnutrition, while the black bars represent those who were malnourished.

Multiple logistic regression analysis was performed in order to investigate the association between MCI with nutritional deficit (malnourished or risk of malnutrition) after adjustment of age, female gender, illiteracy, and depression. Table (4) shows that nutritional deficit and MCI maintained a strong association (Odds Ratio=6.62, 95% Confidence Interval: 1.87-23.45), after adjustment of age, gender, illiteracy and depression.

Table 4.

Multiple logistic regression analysis evaluating the association between MCI and nutritional deficit after adjustment of age, female gender, illiteracy, and depression

Variables	μ(S.E.)	p value	Odds Ratio	95%Confidence Interval
Age	0.131 (0.036)	0.000	1.14	1.063-1.22
Gender: female	1.065 (0.475)	0.025	2.90	1.14-7.36
Illiteracy	1.195 (0.488)	0.014	3.30	1.27-8.60
Nutritional
deficit	1.89 (0.645)	0.003	6.62	1.87-23.45
Depression	1.221 (0.483)	0.000	3.39	1.32-8.74
Constant	-17.48 (3.476)	0.000	0.000	-

MMSE = Mini-Mental State Examination; MoCA = Montreal Cognitive Assessment.

Discussion

The present study evaluated the relationship between nutritional status, assessed by the MNA, and MCI in a sample of institutionalized older adults who were living in elderly homes in Cairo. In the current study we found that age was associated with poor nutritional status, but educational level and gender weren't associated with the nutritional state. A recent study done among institutionalized older adults in Cairo, Egypt found that age was considered to be a risk factor for malnutrition, however they also found female gender to be a risk factor (21).

The findings of this study show that those with risk of malnutrition and malnourished had significant poorer performance in cognitive tests. We also found that the frequency of those who had malnutrition and risk of malnutrition was significantly higher in elderly diagnosed with MCI when compared to those with normal cognitive function (p=0.002).

These findings are consistent with prior studies suggesting that malnutrition state is associated with an impairment of cognitive function. Pearson et al., 2001 found that elderly people with diminished cognitive function were more than two times at a higher risk of developing malnutrition (22). Another study done by Orsitto et al., 2009 found that the frequency of malnourished elderly in MCI group was significantly higher than that in the normal cognitive function group (10).

Analysis of data in the current study showed that the socio-demographic factors associated with MCI were advanced age, female gender and illiteracy. These findings were supported by many studies; it was found that the prevalence of MCI increases with age (23, 24). Education level is related to cognitive ability and most studies showed this opinion, with the level of education increases, the prevalence of MCI decreases (25, 26). The reason that in the current study females were found to have higher prevalence of MCI; is that in the past women had less chance of receiving an education than men in Egypt. In general the association between socio-demographic factors and MCI varies in different countries and cultures. Some studies found that MCI was associated with aging and low educational level (26, 27, 28). Other studies found that MCI was not associated with aging, gender or educational level (29, 30). It is difficult to make a direct comparison between the socio-demographic factors associated with MCI in the current study and other studies as they deal with different cohorts and elderly living in different settings.

Regarding the functional status of MCI participants; our results showed that MCI participants performed like those with normal cognitive function in ADL. The fact that patients with MCI have preserved ADL goes in line with the diagnostic criteria of MCI (2). However we found that MCI participants performed significantly poorer in IADL. Most of the studies which assessed the functional status of MCI patients support our results (31, 32, 33).

In the current study MCI wasn't significantly related to diabetes mellitus, hypertension and ischemic heart disease, but other studies showed that there was a significant relationship (34, 35, 36). These differences may be attributed to the small sample size in the current study.

The present study revealed that depressed mood was significantly associated with MCI. The co-occurrence of depression and MCI was supported by other studies (37, 38). There is also evidence that depressive symptoms may be a risk factor for or an early symptom of cognitive impairment in some older persons (37).

In the current study the possible influence of aging, female gender, illiteracy depression and nutrition deficit on MCI were taken into consideration by means of the multiple logistic regression analysis. This showed that a strong relationship between nutritional deficit and MCI persisted even after adjusting for other variables (Odds Ratio=6.62). In line with this concept a recent study was done by Lee et al., 2009 to delineate the difference in nutritional risk between elderly with MCI and those with normal cognitive function (28). They found that MCI was associated with moderate or high nutritional risk even after adjustment for age, sex, educational level, and depression.

However, the interrelationships between MCI and nutritional risk are complex and reciprocal; MCI precedes malnutrition or vice versa. On the one hand, nutritional risk influences risk factors or outcomes of MCI. A research demonstrated that altered nutritional status appears to predict the severity and progression of cognitive impairment among elderly (39). On the other hand, mild changes in ability to perform the daily living activities among MCI patients increase nutritional risk. By analyzing the functional characteristics of subjects with MCI collected in the study done by Perneczky et al., 2006 it was found that elderly subjects who had MCI, compared to healthy controls, performed significantly worse in the activities of daily living that require the involvement of memory or complex reasoning (40). Similarly, a study by Feliziani et al., 2006 showed that subjects with MCI had more severe disability in their daily activities than cognitively healthy elderly controls (41). These disabilities were significantly associated with the degree of cognitive impairment. These difficulties in performing the activities in daily living and IADL among elderly with MCI may be due to the poor physical function and muscle strength which coexists with cognitive impairment among elderly (31).

In conclusion the results of the present study showed a high prevalence of malnutrition in institutionalized elderly patients with MCI. This finding suggests that nutritional status is a very important variable to be considered in the multidimensional evaluation of patients with MCI. The poor nutritional status associated with MCI may suggest that malnutrition plays a role in the pathology of cognitive decline among elderly.

Whether improvement in nutritional status may improve the cognitive function or delay progression to dementia in these patients is a question which needs to be researched. Further studies will undoubtedly be informative in this regard. The relationship between risk factors for malnutrition (e.g. type or amount of food, tooth or mouth problems, polypharmacy, and economic hardship) and cognitive function is a question which also warrants investigation.

Acknowledgments: The author would like to thank the staff members and residents of the elderly homes in which the study was conducted for their gracious help.

Conflict of Interest: The authors have no financial or any other kind of personal conflicts with this paper.

Author Contributions: Mohamed S. Khater conceived and designed the study, analyzed the data, drafted the original manuscript, and revised it. Nahla F. Abouelezz was responsible for analysis and interpretation of data, participated in the study design, and contributed to manuscript revision.

Sponsor's Role: None.