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T. Alaama1,2, M. Basheikh1,2, A. Khiyami1, M. Mutwalli1, S. Batawi1, G. Watfa3


1. King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia (KSA); 2. King Fahad Medical Research Center, Jeddah, Kingdom of Saudi Arabia (KSA); 3. King Saud Medical City, Community Health, Riyadh, Kingdom of Saudi Arabia (KSA)

Corresponding Author: Dr. Ghassan WATFA, MD; PhD, King Saud Medical City – Community Health Centre, 12746 Riyadh, Kingdom of Saudi Arabia (KSA), Tel: +966599192881; E-mail: ghassanwatfa@hotmail.com


J Aging Res Clin Practice 2016;inpress
Published online October 27, 2016, http://dx.doi.org/10.14283/jarcp.2016.120



Objective: Previous studies have shown that Diabetes mellitus (DM) is associated with an increased risk of cognitive impairment, but little data is available on Arabic populations, inspite of their remarkably high prevalence of DM. In this study we attempt to study the effect of DM on cognitive performance in middle-aged and elderly patients. Design: Observational cross sectional study. Setting: Outpatient clinics in King Abdulaziz University Hospital (KAUH) in Jeddah, Saudi Arabia. Participants: The study included 241 volunteers aged 59.6 ± 9.2 years; 171 outpatients with DM, matched with 70 controls without. Measurements: Volunteers underwent cognitive assessment using the Montreal Cognitive Assessment Test (MoCA) and the Rowland Universal Dementia Assessment Scale (RUDAS). Results: RUDAS score was poorer in diabetics (25,25 ± 2,78 vs. 26,71 ± 2,57 in controls; p<0.0001) who are more  likely to  have  cognitive  impairment 16% , than  those  who  are not  diabetics 3%; p=0.004.  This association was confirmed in multivariate analyses and shown to be independent of female gender and low education level, all of which were associated with worse RUDAS cognitive score.The results were not significant when the MoCA was used, as 85 % of the cases and 78 % of the controls had abnormal results;p=0.194.Among diabetics, there was no statistically significant effect found for glycemic control or DM duration on either one of the tests.The prevalence of obesity was similar in the two groups with 63% in diabetics and 62% in controls. Conclusion: In our population with an alarming prevalence of obesity, diabetes was associated with poorer cognitive performance independent of female gender or low education level, drawing attention to this under-recognized problem of cognitive impairment that could result in significant health and social problems, particularly in areas with high diabetes prevalence. RUDAS was found to be a very reasonable and convenient test to assess cognition in our sample characterized by a low educational level.

Key words: Diabetes mellitus (DM), cognitive impairment, RUDAS, MoCA, Kingdom of Saudi Arabia (KSA).



Diabetes Mellitus (DM) is a prevalent condition worldwide. However, the prevalence of DM in Saudi Arabia is alarmingly high, ranging from 18 to 30% (1, 2).
Moreover, the International Diabetes Federation (IDF) identified 6 countries of the Middle East and North Africa, including Saudi Arabia, among the world’s ten highest countries in the prevalence of DM (3).
Previous studies have shown that diabetes is associated with an increased risk of cognitive impairment and the development of dementia (4, 5).
As life expectancy improves in Saudi Arabia (6), the Saudi elderly population is expected to grow resulting in unmasking of more of these age-related complications in the future.
However, most of the existing studies addressing relationship between diabetes and cognitive impairment have been conducted in industrial countries, while few or no data is available in emerging populations and Arabic populations. Moreover, the majority of studies were conducted in the elderly population, however it has been suggested that cognitive decline could begin in midlife in diabetic patients (7).
This study attempts to assess in a tertiary hospital-King Abdulaziz University Hospital (KAUH) in Jeddah, Saudi Arabia, the cognitive performance in middle-aged and elderly diabetic patients with comparison to matched controls.


Patients and methods

A cross sectional study was carried out from June to July 2012 in the outpatient department of King Abdulaziz University Hospital (KAUH), Jeddah, Kingdom of Saudi Arabia. This study included a total of 171 outpatients with diabetes, matched with 68 controls without.
The studied patients were consecutively recruited among patients who were approached while they waited for appointments at various hospital clinics. Data collection took place in the Internal medicine clinics.
Participants were included if they were aged ≥ 45 years and had signed an informed consent form. Subjects were excluded if they had documented dementia or in the case of absence of a hospital medical record number.
Volunteers underwent cognitive assessment using two validated tests: the Montreal Cognitive Assessment Test (MoCA), and the Rowland Universal Dementia Assessment Scale (RUDAS).
The Montreal Cognitive Assessment is a brief cognitive screening tool. A score of 30 is obtained when all answers are correct. The MoCA has been found to have a specificity of 87% and a sensitivity of 90-100%for detecting mild cognitive impairment (MCI) with a cutoff score of 26 (25 or below indicating impairment) (8).
The RUDAS is a six item screening test scored out of a total of 30 points. It assesses language, praxis, memory, judgment, construction and fluency. Performance on RUDAS has been shown to be affected by age, but not by education, gender or preferred language. The RUDAS dementia screening cut-off is a score of<23 which yields a specificity of 95.8% and a sensitivity of 81%(9).
Cognitive assessments were carried out by researchers who were trained by experienced geriatricians prior to the study period. Training of researchers took place over several weeks; through sessions in which the tests were explained and performed several times to ensure inter-rater and intra-rater reliability.
As well as undergoing the MoCA and the RUDAS, the Geriatric Depression Scale (GDS) (10) was administered to all subjects and several other variables were collected. These included: age, gender, and marital status, smoking habits, level of education, body mass index (BMI), waist circumference (WC), number of comorbidities and history of hypertension, depression, coronary heart disease (CHD), and stroke or transient ischemic attack (TIA). For diabetic patients, HbA1C results and the duration of diabetes were also collected.
Regarding marital status, subjects were categorized into two groups, married and others (single, window or divorced). Patients were classified into two categories according to smoking habits as never smokers and past smokers or current smokers. Education level was classified into four categories according the years of education: illiterate (<1 year), Fundamental (1-6 years), intermediate (>6-12 years) and Higher Education (>12 years).
Anthropometric measurements were recorded for each subject. Patients’ weight in kilograms and height in meters were both measured using a Seca Medical Physician Electronic Scale. BMI was then calculated according to the equation: BMI = Weight (kg)/Height² (M²). The WC was measured for each subject at the umbilicus directly after expiration. Results were recorded in centimeters.

Statistical Analysis

Sample size considerations were based on RUDAS score values established in diabetic patients (11) and in general population previously studies (12), a minimum of 63 diabetic patients and 63 controls was considered as necessary for an alpha risk of 5 % and a beta risk of 20 %.Since our population could be different from the above mentioned studies, it was therefore decided to include more subjects than the minimum indicated above.
The data was analyzed using NCSS 9 statistical software package (Kaysville, UT). Descriptive values are expressed as means ± SD or percentages. The two-tailed significance level was set to p = 0.05.
The variables were compared using Student T-test, Chi-Square tests or ANOVA, as appropriate. Pearson’s correlation test was performed to examine various correlations.
Analyses of factors associated with RUDAS were performed using multiple regression analyses with an interactive backward selection method. Validity of the model assumption was verified using analysis of model residuals and testing for heteroscedasticity.



Study population characteristics

The present study encompassed 241 participants (171 with diabetes and 70 without) aged 59.6 ± 9.2 years. The age  of  diabetic patients  ranged  between  45  and  86  years  and  45  and  80  years for controls.
Table 1 shows the characteristics of the studied population. Data are presented according the presence of diabetes. Diabetic patients were older than controls 61.1 ± 9.1 versus 55.7 ± 8.5; p <0.0001. In term of morbidity, hypertension history was increased in diabetic patients in comparison with controls, 65% versus 30%; < 0.0001, and they were more frequently sick with higher number of comorbidities than controls 4.1 ± 2.1 versus 2.8 ± 1.8; p < 0.0001.
The prevalence of obesity was similar in the two groups with 63% in diabetics and 62% in controls.
To be noted, no significant difference was found between the two groups in terms of education levels (table I), nor in term of years of education which was found in diabetics and controls to be 6.34 ± 5.885 years and 7.57 ± 6.051 years; p = 0.220, respectively. The percentage of illiterate, fundamental, intermediate and high education levels were 31, 28.5, 14.5 and 26 %in diabetics and 26, 29, 14 and 31 % in controls, respectively.
The two groups did not differ significantly in terms of other studied parameters.
Among diabetic patients, the mean HbA1c level was found to be 8.9 ± 2.2 % and the duration of diabetes was 13.8 ± 9.7 years.

Table 1 Clinical and biological characteristics of the population

Table 1
Clinical and biological characteristics of the population

Data are expressed as: Mean ± SD and Percentage (%), *: Probability of the Student’s t-test (continuous variables) or Chi-Square test (categorical variables), CHD: coronary heart disease; TIA: transient ischemic attack; GDS: geriatric depression scale; WC: waist circumference; BMI: body mass index.

Cognitive performance

Both  cognitive  tests  (RUDAS and MoCA) demonstrated  a  direct  and  significant  correlation  with   the  subjects’  level  of  education  (r=0.437, p<0.0001 and r=0.661, p<0.0001) and BMI score (r= 0.172, p=0.009 and r= 0.139, p=0.041), and an inverse  relation  with  advancing  age (r=-0.241; p = 0.0004 and r=-0.162; p=0.023).
MoCA score was better in men (18.8 ± 5.5) than in women (21.1 ± 4.8); p= 0,001, and also in married patients (20.3 ± 5.1) than in others (20.3 ± 5.1); p= 0,016, whereas no difference of RUDAS score was found in the distribution of gender or marital status.
Nevertheless,  a  highly  significant  correlation  was  observed  between  RUDAS  and  MoCA (r= 0,523; p < 0.000).

Association between diabetes andcognitive function

Diabetic patients are more likely to have less performance than controls in term of RUDAS score (Table 1), and this association persists after adjustment for age, gender, education level, GDS, BMI, hypertension history and number of comorbidities (26.7 ± 0.31 in diabetics versus 25.3 ± 0.19 in controls; p= 0,0007).
As we divided the RUDAS score into normal for these who scored ≥23 and abnormal for those scoring less, we found that among diabetics 16% had abnormal scores compared to 3% for controls (p = 0.004).


Table 2 Analysis of factors associated with RUDAS score using multiple regression models

Table 2
Analysis of factors associated with RUDAS score using multiple regression models


Regarding MoCA Scores, there was no significant difference between diabetics and controls (Table 1), as when MoCA was used as categorical score (abnormal if < 26), 85 %  of  the  diabetics  and  78%  of  the  controls  had  abnormal  results; p=0.194.
In order to further investigate our primary finding that RUDAS score was worse in diabetics, additional multiple regression analyses were performed, adjusting for age, gender, education level, marital status, smoking, hypertension history, number of comorbidities, GDS, and BMI. The analyses show that the RUDAS scores decreased in females and with a history of diabetes, and increased when education level was high (Table 2). The model accounted for 28 % of the total variance in RUDAS score.
Among diabetics, no statistically significant effect was foundfor neither the duration of diabetes on RUDAS (r= -0,039; p=0.607) or MoCA (r= -0,096; p= 0.235), nor for glycemic control (HbA1C) on RUDAS (r= 0,116; p=0.194) or MoCA (r= -0.027; p= 0.776).


The present case-control study conducted in a population sample from Saudi Arabia provides some elements of an effect of diabetes on cognition. Notably, the cognitive performance, as assessed by RUDAS, is poorer in diabetes, who  are  more  likely  to  have  cognitive  impairment , than  those  who  are  not  diabetics.  This association was confirmed in multivariate analyses and shown to be independent of female gender and low education level all of which were associated with worse RUDAS cognitive score.
These results corroborate and extend results obtained in different populations reporting that diabetic patients are at an increased risk for development of cognitive performance or dementia (4, 13, 14).
Although the design of the present study cannot provide an ascertain causality, it is of note that there are many direct mechanism linking diabetes and cognitive impairment such as insulin dysregulation (15-17) and chronic exposure to glucose (18-20). In the present study, we did not find a role for the duration of diabetes or glycemic control on cognitive performance.  This was contrary to our expectation, but the observational study design with one assessment of HbA1C does not allow ascertaining causality. Nevertheless, the landmark ACCORD MIND trial  did  not  show  a  benefit   for   strict  glycemic  control  on  cognition  as  well (21).
In addition, the impact of the cardiovascular risk factors, which are increased in diabetic patients, could contribute to explain this association between diabetes and cognitive impairment (14). Indeed, several studies have indicated that individuals with cardiovascular risk factors and vascular alterations are at increased risk of developing cognitive disorders (22-24). In the present study, the prevalence of hypertension and the number of comorbidities were significantly higher in diabetic patient, but without significant direct association with cognitive performance as assessed by the both cognitive tests.
Our findings indicated a positive effect of increasing BMI on cognition (evident in both tests).  This is in accordance with the results of some previous studies (25), but  in  contrast  to  others (26). However, the effect of BMI did not remain significant in the regression analyses (Table 2). Moreover, we have to mention that the prevalence of obesity is quite alarming in our sample.  This however does reflect the unfortunate fact of the widespread of this problem in our society (1). Indeed, this high prevalence of obesity could make minimize the significance of the BMI when entered as covariable in the regression model.
As expected and shown in many previous studies (27, 28), cognitive tests scores herein were superior in those individuals that were more educated. Although education levels were similar in diabetics and controls in our study, it could be considered as a shared risk factor for cognitive impairment and diabetes since there is evidence that low educational levels increase the risk of diabetes (29) given the overall low education level among our study population. This last observation could contribute to explain our results demonstrating the cognitive impairment in diabetics using the RUDAS, but not the MOCA. Although MOCA is validated, quick, and easy  to  administer, it  requires a certain  level  of education  and therefore can lose  its sensitivity  in  a  low-education  population.  The MoCA was reported to be more sensitive in individuals with a high level of education (30), whereas the RUDAS has been found to be particularly helpful in populations with limited education (31, 32). Moreover, We have found RUDAS easy to administer, both for the testerand the tested, which is very important  in  an  ethnically and educationally diverse population  like  ours. This also carries important implications infuture  research in our region  given  the  dearth  of  cognitive  research in our region,  perhaps  due  to  the  difficulty  of  administering  the  more  popular  cognitive  tests.
Beyond diabetes and low education level, female gender was also independently associated with lower score son RUDAS. Indeed, it was reported that there is gender-difference in term of cognitive function in the developing countries (33). Since it was observed that the combining between socio-cultural factors with gender has more effect on cognition rather than sex alone (34), this negative effect of female gender on cognitive performance could also be explained by lesser levels of education in females who could for example lose their sex-advantage in terms of cardiovascular profile relating to socio-cultural factors (35).
To our knowledge, this is the first study that addresses cognitive impairment in diabetics in an Arabic country. In addition, it is important to mention that our population included not only elderly but middle-aged as well as there is evidence of the role of mid-life rather than late-life diabetes in the development of cognitive impairment (36).
Our results could draw attention  to  this  under-recognized problem of cognitive impairment that  can lead to significant health  and  social  outcomes,  especially that  diabetes in KSA is now  a national  health problem. Indeed, diabetics with cognitive impairment are more likely to experience poor compliance to  medications, are more susceptible to medication errors,  and less likely to measure blood sugars and adjust  their  medications properly. Moreover, the functional disability that could result from cognitive impairment adds up to the burden of diabetes on the  person, caregivers, and the community as a whole.
Certain limitations in this study should be noted. The controlswere  determined  based  on  their  self-reported  health,  raising  the  possibility  of  underreporting  in  the  control  group. Indeed, many reports highlight educational levels and ethnicity as biases in disease under-reporting in self-assessed health (37). Moreover, the observational study design does not allow ascertaining causality, and the cross sectional design does not allow testing for temporal changes in cognitive performance.
We believe that largerlongitudinal studiesare needed to furtheridentify possible modifiable risk factors for cognitive impairment in diabetes taking into account life style, education, contextual, social and metabolic proprieties of our population. Moreover, new cognitivemarkers such as advanced neuroimaging could be utilized to shed  light on the possible underlying pathology and the potential relationship between diabetes and cognitive impairment.
However, in keeping with the present study results, diabetes and female gender increased the likelihood of classifying patients as cognitively impaired while high education level may protect them from cognitive impairment.



In our population with an alarming prevalence of obesity, diabetes was associated with poorer cognitive performance independent of female gender and low education levels, drawing attention  to  this  under-recognized  problem  of cognitive impairment that  can  lead  to  significant  health  and  social  outcomes, particularly in areas with high prevalence of DM. RUDAS was found to be a very reasonable and convenient test to assess cognition in our sample characterized by a low educational level.


Ethical standards: The research was conducted in accordance withthe current laws of KSA and obtained the approval from KAUH. The investigators undertook to respect the protocol in all respects.

Acknowledgment: The authors would like to extend their thanks to King Abdulaziz City for Science and technology (KACST) for the support of this research.

Conflict of interest: No



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D.A. Davey


Corresponding Author: Faculty of Health Sciences, University of Cape Town, Anzio Road, Observatory, Western Cape, South Africa 7925, e-mail profdad@eject.co.za, Tel +27 21 712 1314



Abstract: Alzheimer’s disease (AD) and cerebrovascular disease (CVD) frequently co-exist and CVD acts additionally and synergistically with AD in ageing–related impairment of cognitive function and dementia. A significant number of men and women with normal cognition at the time of death have the neurodegenerative and cerebrovascular changes of AD and CVD and are regarded as having high cognitive reserve or cognitive resilience. Many measures used to prevent and treat cardiovascular disease, decrease the incidence, or delay the onset of ageing-related cognitive impairment and dementia. Ageing-related cognitive impairment and dementia are increased by adverse psycho-social factors and can be prevented or mitigated by appropriate psycho-social measures. There is now more than sufficient evidence to implement, as a matter of urgency, personal health and life-style measures and public health initiatives in the endeavor to prevent, postpone or ameliorate ageing-related cognitive impairment and dementia and to decrease its burden world-wide.

Key words: Alzheimer’s disease, cognitive impairment, cerebrovascular disease, dementia, prevention.



Alois Alzheimer in 1906 described a “peculiar severe disease process of the cerebral cortex” with “miliary foci” (β-amyloid plaques) and “fibrils” (neurofibrillary tangles) in a patient with dementia praecox and the condition was named “Alzheimer’s Disease” (1). The term “Alzheimer’s Disease” is currently used in several different senses:
(a) specifically, by neurologists, psychiatrists and others to mean the form of neurodegeneration characterized by β-amyloid plaques and neurofibrillary tangles in the brain as described by Alzheimer. The term “vascular dementia” (VaD) is used for dementia attributed to cerebrovascular disease
(b) loosely, to include all forms of ageing-related cognitive impairment and dementia with varying cerebral pathologies
(c) generally, in non-medical circles instead of the word “dementia”.
The different uses of the term “Alzheimer’s Disease” have led to misunderstanding and the meaning may only be clear from the context. Alzheimer’s disease (AD) as first described by Alzheimer is but one of several causes of Ageing-Related Cognitive Impairment and Dementia (ARCID) (Table 1). The commonest are AD, cerebrovascular disease (CVD) and Lewy Body Disease (LBD) which frequently co-exist .It has been proposed that ARCID and dementia should be regarded as a syndrome i.e. a complex of symptoms with multiple causes, similar to other chronic diseases (2).
The purpose of this review is to substantiate the evidence that:
(A) AD and CVD are commonly associated and act additively and synergistically in ARCID
(B) Many risk factors for ARCID and measures that may prevent or postpone its development are very similar to the risk factors and measures to prevent and treat cardiovascular and cerebrovascular disease.
(C) Adverse psycho-social factors are significant risk factors for ARCID and psycho-social measures that increase cognitive reserve and resilience may prevent, delay the onset or ameliorate ARCID
(D) In the current absence of effective disease-modifying treatments, primary prevention combining all possible protective measures is the best hope to prevent, delay the onset and ameliorate ARCID


Association of Alzheimer’s disease and cerebrovascular disease

The cerebral pathology in men and women with dementia and of those with normal cognition at the time of death has been investigated in at least four major post-mortem studies: the Religious Orders Study and Rush Memory and Aging Project, the Medical Research Council Cognitive and Ageing Study, the Vienna Trans-Danube Aging Study, and The National Alzheimer’s Coordinating Centre USA Study (3-6). The main conclusions were very similar in all four studies, namely that the changes of AD and CVD (a) frequently co-exist in late-onset dementia (b) overlap to varying degrees and have additive and synergistic effects on cognitive decline (c) are sometimes found in persons with normal cognition at the time of death (7). The neurodegenerative and cerebrovascular changes associated with dementia form a spectrum from “pure” AD to “pure” CVD and most commonly are combined and result in “mixed dementia” (8) Fig1. The separation of AD as described by Alzheimer, and “vascular dementia” has been claimed to be a false dichotomy (8).

Table 1 Brain pathologies associated with cognitive impairment and dementia

Table 1
Brain pathologies associated with cognitive impairment and dementia

Figure 1 Conceptual Diagram of Mixed Dementia

Figure 1
Conceptual Diagram of Mixed Dementia


Cognitive reserve and cognitive resilience

A significant proportion of men and women with normal cognition at the time of death have the neurodegenerative and cerebrovascular changes of the brain associated with AD, CVD and dementia. The discordance between neuropathology and lack of cognitive impairment constitutes prima facie evidence for the role of some type of brain, neural or cognitive reserve (9). The absence of impaired cognition and dementia in such cases has been ascribed to high cognitive reserve and cognitive resilience. Cognitive reserve” implies high cognitive ability from early in life and its maintenance in mid and later life with the consequent prevention or postponement of ARCID (10). “Cognitive resilience” refers to the prevention or delay of ARCID in spite of the development of the pathological changes of AD, CVD and LBD.


Risk factors for ageing-related cognitive impairment and dementia

Ageing-related cognitive impairment and dementia has been associated with a large number of risk factors. A recent extensive meta-analysis of 323 papers including 93 factors considered suitable for epidemiological analysis, identified nine potentially modifiable risk factor; type-2 diabetes, obesity, hypertension, homocystinaemia, frailty, depression, current smoking, carotid artery narrowing, low educational achievement (11). The calculated population attributable risk combining all nine factors was 0.66 and it was claimed that two third of AD cases could be explained by these factors. In another study, potentially modifiable risk factors have been estimated to be present in approximately 50% of individuals with AD in the USA and worldwide (12). The seven modifiable risk factors included in these estimates were midlife hypertension, midlife obesity, diabetes mellitus, physical inactivity, smoking, depression and low education. The estimates do not take into account the non-independence of risk factors and the combined population-attributable risk factors have been estimated to be about 30% in the USA and Europe (13). Risk Factors can be divided into (a) Personal and Psycho-Social and (b) Cerebrovascular and Lifestyle (Table 2).

Table 2 Risk Factors for Ageing-related cognitive impairment and dementia

Table 2
Risk Factors for Ageing-related cognitive impairment and dementia


Personal factors

Personal factors including age, family history and the presence of the lipoprotein APOEε4 allele, are not modifiable but their effects can be mitigated or postponed by favourable environmental factors. Age is the most important factor determining the incidence and prevalence of cognitive impairment and dementia; the incidence of all-cause dementia increases exponentially from about 5/1,000 person-years in the 65-69 years age group to about 85/1,000 person-years in the age 90+ years (14). The most common genetic risk factor is the ε4 allele of the lipoprotein APOE4 and the APOEε4 allele has been estimated to increase the risk of AD about 3 times in heterozygotes and 15 times in homozygotes (15).

Psycho-social factors

Psycho-social factors often play an important part in ARCID and measures that increase cognitive reserve and cognitive resilience may be of considerable benefit in preventing, delaying or ameliorating ARCID. In an analysis of more than 20 studies involving 29,000 individuals followed for a median of 7.1 years, higher brain reserve was associated with a lower risk for incident dementia OR 0.54 (0.49–0.59) (10). The psycho-social factors that have been studied include, level of education, continuing cognitive activity and cognitive interventions, social and personality factors, depression and traumatic injury.

Level of education

The relative risks for low versus high education in a meta-analysis of 13 cohort and 6 case-control studies were, for AD 1.80 (1.43–2.27), for non-AD 1.32(0.92–1.88) and for all dementias 1.59(1.26–2.01) (16). In a meta-analysis of 31 studies with incident AD the pooled relative risk for lower education was RR 1.99(1.30–3.04)(17). In an analysis of 22 longitudinal studies including 21,456 individuals and 1,733 cases of dementia, the risk of dementia was lower for those with higher education OR 0.53 (0.45–0.62) (17). Low level of education is one of the biggest contributors to the high prevalence of AD world-wide (12).

Continued Cognitive Activity and Cognitive Interventions

A systematic review of 22 cohort studies including 29,000 individuals concluded that complex patterns of mental activity in early and mid-life was associated with a significant reduction in the incidence of dementia in later life RR 0.54(0.49–0.59) (10). In the Rush Memory Project frequent participation in cognitive stimulating activities was associated with less rapid decline in cognitive function and a lower incidence of AD, HR 0.58 (0.44–0.77) after controlling for a low baseline cognitive function, past cognitive activity, socioeconomic status and current social and physical activity (18). A Cochrane review in 2011 concluded that cognitive training interventions significantly improved immediate and delayed recall in healthy older adults and that more studies in other cognitive domains were necessary (19).

Social and Personality Factors

Social isolation and loneliness increase cognitive decline and the risk of late-life dementia (20, 21). Conscientiousness and purpose in life have been associated with a reduced risk of ARCID (22, 23). In the MRC-CFAS Study a combined Cognitive Lifestyle Score (CLS) based on educational attainment, occupational complexity and social engagement found that those who maintained a high CLS throughout life had a 40% reduced risk of developing dementia (24).


Depression may be a cause or consequence of cognitive impairment and dementia. A systematic review and meta-analysis of 20 studies including1,020,172 individuals found that history of depression increased risk of developing AD with a pooled OR of 2.03(1.73–2.38) for case control studies and of 1.90 (1.55–2.33) for cohort studies (25).

Traumatic brain Injury

Moderate and severe traumatic brain injury increases the risk of cognitive decline and is estimated to increase the risk of dementia in later life two to three fold (26). There is an increased risk of cognitive impairment and later onset of dementia in military veterans who have suffered brain injuries and in those involved in sports such as boxing and football of all forms, particularly in players who have experienced multiple concussions (27).

Cerebrovascular and life-style factors

Many cerebrovascular and lifestyle factors that predispose to ageing-related MCI and dementia are potentially preventable or modifiable (7). Measures that may prevent CVD are similar to those that prevent cardiovascular disease and include active treatment of hypertension, hyperlipidaemia and diabetes. The extensive study of 5,715 cases with a single neurodegenerative disease in the National Alzheimer’s Coordinating Centre USA database concluded that “in the absence of any specific disease-modifying treatments for Alzheimer’s disease in the near future, we urge, based on the high prevalence on cerebrovascular disease described in our data here, that aggressive management of vascular risk factors and encouragement of healthy life styles in mid-life may have benefit for Alzheimer’s disease or α-synucleinopathies individuals at increased risk to become clinically symptomatic, and probably to those with other causes of cognitive impairment. Indeed, even those who already manifest the clinical features of Alzheimer’s disease or α-synucleinopathy may benefit from effective therapies that mitigate vascular risk factors and cerebrovascular disease” (6).


Mid-life, but not late-life, hypertension is associated with an increased risk of AD and dementia with a calculated OR of 1.61(1.16–2.24) (28). A cohort of a random, population-based sample of 1449 individuals in Sweden was followed for an average of 21 years. Those with a raised systolic pressure in midlife (BP>160mm Hg) had a significantly higher risk of AD in later life OD 2.3 (1.0–5.5), after adjusting for age, body mass index, education, vascular effects, smoking and alcohol consumption (29). A quantitative meta-analysis of 14 studies of subjects without cognitive impairment or dementia, 32,658 with and 36,905 without hypertensive medication found no significant difference in the incidence of AD between the two groups but that those who had received anti-hypertensive medication has a significantly lower incidence of vascular dementia RR 0.67 (0.52–0.87) and of all-cause dementia RR 0.87 (0.7–-0.96) (30)


A systematic review of 18 prospective studies found a significant association between high mid-life total cholesterol (TC) and an increased risk of AD and all-cause dementia but there was only weak evidence of an association between TC and cognitive decline (31).


A number of systematic reviews and meta-analyses have reported an increased risk of impaired cognition or dementia in association with Type-II diabetes (11). A meta-analysis of prospective 28 observational studies found that the pooled relative risk of developing AD was 1.56 (1.41–1.73) of VaD was 2.27 (1.96–2.66) and all-cause dementia was 1.73 (1.65-1.82) (32). Diabetes increased the risk of conversion of mild cognitive impairment to dementia and Mediterranean diet decreased the risk (33).


In prospective studies and meta-analyses mid-life obesity has been found to be associated with a significant increase of all-cause dementia with a pooled estimate of RR of 1.60 (1.34–1.92) (17).
In addition to the specific effect of obesity on ARCID, obesity is associated with an increased incidence of hypertension, diabetes and cardiovascular disease.


A Mediterranean diet – high intake of vegetables, fruits, nuts and olive oil, relatively low intake of dairy products and red meat, and a moderate intake of wine – has been claimed in several observational studies to slow cognitive decline and to lower the risk of AD (34). In a prospective study of a similar “MIND” diet, high adherence was reported to be associated with a reduced risk of AD (35).


A review of 37 studies found that compared with never smokers, current smokers had an increased risk of AD (RR1.40 (1.13–1.73), VaD (RR 1.38 (1.15-1.66) and all cause dementia (RR1.30 (1.13-1.73) (36). The risk of all-cause dementia increased by 34% for every 20 cigarettes smoked per day but was not increased in former smokers. In a study of a cohort of 21,123 people, heavy smoking in mid-life was associated during two decades of follow-up with a more than 100% increase in AD, VaD and all–cause dementia (37).

Physical Inactivity

A review and meta-analysis of 16 prospective studies on the association between physical activity and dementia found that comparing highest v lowest activity groups the combined RR for AD was 0.55 (0.36–0.84) and for all-cause dementia was 0.72 (0.60–0.80) (38). These values have been reversed to reflect the risks with inactivity as 1.82 (1.19–2.78) for AD and 1.39 (1.6–1.67) for all cause dementia (12). A review and meta-analysis of physical activity in 21 prospective cohorts comparing higher with lower levels of activity the RR on cognitive decline was 0.65 (0.55–0.76) and on dementia was 0.86 (0.76–0.97) (39). A Cochrane analysis in 2015 found that healthy, sedentary elders who begin exercise have a significant improvement in cognitive function, particularly mental processing speed (40).


Prevention of ageing-related cognitive impaiment and dementia: Combined measures

In the absence of disease-modifying treatments, measures to prevent or postpone the onset of ARCID should include measures to prevent cerebrovascular disease and improve physical health and to ensure an optimum psycho-social environment. In view of the long preclinical phase of both CVD and AD these measures need to be actively instituted as early in life as possible and not later than mid-life. Many studies of individual risk factors have been published but there have to date been virtually no long-term, randomized, controlled studies of combined measures to prevent or postpone ARCID. A recent Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) reported the results of a double-blind, randomized, controlled trial of 2,654 individuals aged 60-77 years assigned in a 1:1 ratio to multidomain intervention (cognitive training, diet, exercise and vascular risk monitoring) or a control group (general health advice) (41). The primary outcome was a change in cognition in a neuro-psychological test battery score (NTB). The difference in NTB between the two groups after 2 years was statistically significant (p=0.03). There was also a significant difference in the secondary outcomes of executive functioning (p=0.04) and processing speed (0.04) but not in memory (p=0.36). It was concluded that a multidomain intervention can improve cognitive function in at-risk elderly people.



Nine population-based studies of dementia incidence and prevalence have reported a declining prevalence and age-specific incidence of dementia in England, Sweden, The Netherlands and the USA (42). The decreases have been attributed to rising levels of education, better prevention and treatment of cardiovascular disease and healthier life-style including exercise. It is uncertain whether these favourable trends will continue in the face of rising levels of obesity and diabetes in these populations, and whether they will manifest in low income countries. Although the age-specific incidence of dementia may be decreasing in some countries, the population of the world, the number living to advanced old age and the number with dementia world-wide is increasing. The incidence of dementia rises rapidly over the age of 75 and it has been estimated that the total number of people with dementia will triple from 2015 to 2050. The best hope for reducing the incidence and prevalence of ageing-related dementia currently lies in primary prevention, and in particular better education, continued mental and physical exercise and strict control of vascular risk factors. The evidence is now more than sufficient evidence to urge the immediate implementation of both personal health and life-style measures and public health initiatives to prevent or delay the onset of ARCID and to decrease the burden world-wide.


Acknowledgements: I wish to acknowledge the authors M. Valenzuela, M Esler, K Ritchie and H Brodaty (8) and the publishers Translational Psychiatry ©Macmillan Publishers Limited for permission to publish Fig 1.

Conflict of interest: There are no conflicting interests. I have received no funds or writing assistance in preparation of the paper.



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